Add documentation for multiband

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Iadf6d9edd8c67c1389c4a0d482466a8c52198621

.github/workflows/main.yml

@@ -14,7 +14,7 @@ jobs:
       - uses: actions/checkout@v3
         with:
           fetch-depth: 0
-      - uses: fedora-python/tox-github-action@v0.4
+      - uses: fedora-python/tox-github-action@v37.0
         with:
           tox_env: ${{ matrix.tox_env }}
           dnf_install: ${{ matrix.dnf_install }}
@@ -106,8 +106,7 @@ jobs:
         with:
           python-version: ${{ matrix.python_version }}
       - run: |
-          pip install -r tests/requirements.txt
-          pip install --editable .
+          pip install --editable .[tests]
           pytest -vv
     strategy:
       fail-fast: false
@@ -136,8 +135,7 @@ jobs:
         with:
           python-version: ${{ matrix.python_version }}
       - run: |
-          pip install -r tests/requirements.txt
-          pip install --editable .
+          pip install --editable .[tests]
           pytest -vv
     strategy:
       fail-fast: false

.readthedocs.yml

@@ -1,5 +1,17 @@
+version: 2
 build:
-    image: latest
+  os: ubuntu-22.04
+  tools:
+    python: "3.12"
+  apt_packages:
+    - graphviz
+
 python:
-    version: 3.8
-requirements_file: docs/requirements.txt
+  install:
+    - method: pip
+      path: .
+      extra_requirements:
+        - docs
+
+sphinx:
+  configuration: docs/conf.py

README.md

@@ -23,7 +23,7 @@ Read our [documentation](https://gnpy.readthedocs.io/), learn from the demos, an
 
 This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power:
 
-![Running a simple simulation example](https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg)
+![Running a simple simulation example](docs/images/gnpy-transmission-example.svg)
 
 GNPy can do much more, including acting as a Path Computation Engine, tracking bandwidth requests, or advising the SDN controller about a best possible path through a large DWDM network.
 Learn more about this [in the documentation](https://gnpy.readthedocs.io/), or give it a [try online at `gnpy.app`](https://gnpy.app/):

docs/conf.py

@@ -65,7 +65,7 @@ author = 'Telecom Infra Project - OOPT PSE Group'
 #
 # This is also used if you do content translation via gettext catalogs.
 # Usually you set "language" from the command line for these cases.
-language = None
+language = 'en'
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
@@ -84,18 +84,11 @@ todo_include_todos = False
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
-on_rtd = os.environ.get('READTHEDOCS') == 'True'
-if on_rtd:
-    html_theme = 'default'
-    html_theme_options = {
-        'logo_only': True,
-    }
-else:
-    html_theme = 'alabaster'
-    html_theme_options = {
+html_theme = 'alabaster'
+html_theme_options = {
     'logo': 'images/GNPy-logo.png',
     'logo_name': False,
-    }
+}
 
 html_logo = 'images/GNPy-logo.png'
 

docs/extending.rst

@@ -91,7 +91,8 @@ Advanced Specification
 **********************
 
 The amplifier performance can be further described in terms of gain ripple, NF ripple, and the dynamic gain tilt.
-When provided, the amplifier characteristic is fine-tuned as a function of carrier frequency.
+When provided, the amplifier characteristic is fine-tuned as a function of carrier frequency. Note that in this advanced
+specification tilt is defined vs frequency while tilt_target specified in EDFA instances is defined vs wavelength.
 
 .. _extending-raman:
 
@@ -119,38 +120,32 @@ A *mode* usually refers to a particular performance point that is defined by a c
 
 The following data are required for each mode:
 
-``bit-rate``
-  Data bit rate, in :math:`\text{Gbits}\times s^{-1}`.
-``baud-rate``
-  Symbol modulation rate, in :math:`\text{Gbaud}`.
-``required-osnr``
-  Minimal allowed OSNR for the receiver.
+``bit_rate``
+  Data bit rate, in :math:`\text{bits}\times s^{-1}`.
+``baud_rate``
+  Symbol modulation rate, in :math:`\text{baud}`.
+``OSNR``
+  Minimal required OSNR for the receiver. In :math:`\text{dB}`
 ``tx-osnr``
-  Initial OSNR at the transmitter's output.
-``grid-spacing``
+  Initial OSNR at the transmitter's output. In :math:`\text{dB}`
+``min-spacing``
   Minimal grid spacing, i.e., an effective channel spectral bandwidth.
   In :math:`\text{Hz}`.
-``tx-roll-off``
+``roll-off``
   Roll-off parameter (:math:`\beta`) of the TX pulse shaping filter.
   This assumes a raised-cosine filter.
 ``rx-power-min`` and ``rx-power-max``
-  The allowed range of power at the receiver.
+  (work in progress) The allowed range of power at the receiver.
   In :math:`\text{dBm}`.
-``cd-max``
-  Maximal allowed Chromatic Dispersion (CD).
-  In :math:`\text{ps}/\text{nm}`.
-``pmd-max``
-  Maximal allowed Polarization Mode Dispersion (PMD).
-  In :math:`\text{ps}`.
-``cd-penalty``
-  *Work-in-progress.*
-  Describes the increase of the requires GSNR as the :abbr:`CD (Chromatic Dispersion)` deteriorates.
-``dgd-penalty``
-  *Work-in-progress.*
-  Describes the increase of the requires GSNR as the :abbr:`DGD (Differential Group Delay)` deteriorates.
-``pmd-penalty``
-  *Work-in-progress.*
-  Describes the increase of the requires GSNR as the :abbr:`PMD (Polarization Mode Dispersion)` deteriorates.
+``penalties``
+  Impairments such as Chromatic Dispersion (CD), Polarization Mode Dispersion (PMD), and Polarization Dispersion Loss (PDL)
+  result in penalties at the receiver. The receiver's ability to handle these impairments can be defined for each mode as
+  a list of {impairment: in defined units, 'penalty_value' in dB} (see `transceiver section here <json.rst#_transceiver>`).
+  Maximum allowed CD, maximum allowed PMD, and maximum allowed PDL should be listed there with corresponding penalties.
+  Impairments experienced during propagation are linearly interpolated between given points to obtain the corresponding penalty.
+  The accumulated penalties are subtracted from the path GSNR before comparing with the minimum required OSNR.
+  Impairments: PMD in :math:`\text{ps}`, CD in :math:`\text{ps/nm}`, PDL in :math:`\text{dB}`, penalty_value in :math:`\text{dB}`
+
 
 GNPy does not directly track the FEC performance, so the type of chosen FEC is likely indicated in the *name* of the selected transponder mode alone.
 
@@ -168,6 +163,7 @@ The set of parameters for each ROADM model therefore includes:
   Per-channel target TX power towards the egress amplifier.
   Within GNPy, a ROADM is expected to attenuate any signal that enters the ROADM node to this level.
   This can be overridden on a per-link in the network topology.
+  Targets can be set using power or power spectral density (see `roadm section here <json.rst#__roadm>`)
 ``pmd``
   Polarization mode dispersion (PMD) penalty of the express path.
   In :math:`\text{ps}`.

docs/index.rst

@@ -17,6 +17,7 @@ in real-world mesh optical networks. It is based on the Gaussian Noise Model.
    about-project
    model
    gnpy-api
+   release-notes
 
 Indices and tables
 ==================

docs/intro.rst

@@ -14,28 +14,29 @@ fully-functional programs.
     specific, delineated use cases to drive requirements for future
     development.*
 
-This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power:
+This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power,
+or to run a planning script to check SNR of several services:
 
-.. image:: https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg
+.. image:: images/gnpy-transmission-example.svg
    :width: 100%
    :align: left
    :alt: Running a simple simulation example
 
-By default, this script operates on a single span network defined in
-`gnpy/example-data/edfa_example_network.json <gnpy/example-data/edfa_example_network.json>`_
+By default, the gnpy-transmission-example script operates on a single span network defined in
+`gnpy/example-data/edfa_example_network.json <../gnpy/example-data/edfa_example_network.json>`_
 
 You can specify a different network at the command line as follows. For
 example, to use the CORONET Global network defined in
-`gnpy/example-data/CORONET_Global_Topology.json <gnpy/example-data/CORONET_Global_Topology.json>`_:
+`gnpy/example-data/CORONET_Global_Topology.json <../gnpy/example-data/CORONET_Global_Topology.json>`_:
 
 .. code-block:: shell-session
 
     $ gnpy-transmission-example $(gnpy-example-data)/CORONET_Global_Topology.json
 
 It is also possible to use an Excel file input (for example
-`gnpy/example-data/CORONET_Global_Topology.xls <gnpy/example-data/CORONET_Global_Topology.xls>`_).
+`gnpy/example-data/CORONET_Global_Topology.xls <../gnpy/example-data/CORONET_Global_Topology.xls>`_).
 The Excel file will be processed into a JSON file with the same prefix.
-Further details about the Excel data structure are available `in the documentation <docs/excel.rst>`__.
+Further details about the Excel data structure are available `in the documentation <excel.rst>`__.
 
 The main transmission example will calculate the average signal OSNR and SNR
 across network elements (transceiver, ROADMs, fibers, and amplifiers)
@@ -56,10 +57,10 @@ interference noise.
 Further Instructions for Use
 ----------------------------
 
-Simulations are driven by a set of `JSON <docs/json.rst>`__ or `XLS <docs/excel.rst>`__ files.
+Simulations are driven by a set of `JSON <json.rst>`__ or `XLS <excel.rst>`__ files.
 
 The ``gnpy-transmission-example`` script propagates a spectrum of channels at 32 Gbaud, 50 GHz spacing and 0 dBm/channel. 
-Launch power can be overridden by using the ``--power`` argument.
+Launch power in fiber spans can be overridden by using the ``--power`` argument.
 Spectrum information is not yet parametrized but can be modified directly in the ``eqpt_config.json`` (via the ``SpectralInformation`` -SI- structure) to accommodate any baud rate or spacing.
 The number of channel is computed based on ``spacing`` and ``f_min``, ``f_max`` values.
 
@@ -71,8 +72,8 @@ An experimental support for Raman amplification is available:
        $(gnpy-example-data)/raman_edfa_example_network.json \
        --sim $(gnpy-example-data)/sim_params.json --show-channels
 
-Configuration of Raman pumps (their frequencies, power and pumping direction) is done via the `RamanFiber element in the network topology <gnpy/example-data/raman_edfa_example_network.json>`_.
-General numeric parameters for simulation control are provided in the `gnpy/example-data/sim_params.json <gnpy/example-data/sim_params.json>`_.
+Configuration of Raman pumps (their frequencies, power and pumping direction) is done via the `RamanFiber element in the network topology <../gnpy/example-data/raman_edfa_example_network.json>`_.
+General numeric parameters for simulation control are provided in the `gnpy/example-data/sim_params.json <../gnpy/example-data/sim_params.json>`_.
 
 Use ``gnpy-path-request`` to request several paths at once:
 
@@ -82,7 +83,7 @@ Use ``gnpy-path-request`` to request several paths at once:
      $ gnpy-path-request -o output_file.json \
        meshTopologyExampleV2.xls meshTopologyExampleV2_services.json
 
-This program operates on a network topology (`JSON <docs/json.rst>`__ or `Excel <docs/excel.rst>`__ format), processing the list of service requests (JSON or XLS again).
+This program operates on a network topology (`JSON <json.rst>`__ or `Excel <excel.rst>`__ format), processing the list of service requests (JSON or XLS again).
 The service requests and reply formats are based on the `draft-ietf-teas-yang-path-computation-01 <https://tools.ietf.org/html/draft-ietf-teas-yang-path-computation-01>`__ with custom extensions (e.g., for transponder modes).
 An example of the JSON input is provided in file `service-template.json`, while results are shown in `path_result_template.json`.
 

docs/release-notes.rst

@@ -0,0 +1,463 @@
+.. _release-notes:
+
+Release change log
+==================
+
+Each release introduces some changes and new features.
+
+(prepare text for next release)
+
+v2.11
+-----
+
+**New feature**
+
+A new type_def for amplifiers has been introduced: multi_band. This allows the definition of a
+multiband amplifier site composed of several amplifiers per band (a typical application is C+L transmission). The
+release also includes autodesign for links (Optical Multiplex Section, OMS) composed of multi_band amplifiers.
+Multi_band autodesign includes basic tilt and tilt_target calculation when the Raman flag is enabled with the
+--sim-params option. The spectrum is demultiplexed before propagation in the amplifier and multiplexed in the output
+fiber at the amplifier output.
+
+
+In the library:
+
+    .. code-block:: json
+
+        {
+            "type_variety": "std_medium_gain_C",
+            "f_min": 191.225e12,
+            "f_max": 196.125e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_medium_gain_L",
+            "f_min": 186.5e12,
+            "f_max": 190.1e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_medium_gain_multiband",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_medium_gain_C",
+                "std_medium_gain_L"
+            ],
+            "allowed_for_design": false
+        },
+
+In the network topology:
+
+    .. code-block:: json
+
+      {
+          "uid": "east edfa in Site_A to Site_B",
+          "type": "Multiband_amplifier",
+          "type_variety": "std_medium_gain_multiband",
+          "amplifiers": [{
+                  "type_variety": "std_medium_gain_C",
+                  "operational": {
+                      "gain_target": 22.55,
+                      "delta_p": 0.9,
+                      "out_voa": 3.0,
+                      "tilt_target": 0.0
+                  }
+              }, {
+                  "type_variety": "std_medium_gain_L",
+                  "operational": {
+                      "gain_target": 21,
+                      "delta_p": 3.0,
+                      "out_voa": 3.0,
+                      "tilt_target": 0.0
+                  }
+              }
+          ]
+      }
+
+**Network design**
+
+Optionally, users can define a design target per OMS (single or multi-band), with specific frequency ranges.
+Default design bands are defined in the SI.
+
+    .. code-block:: json
+
+      {
+          "uid": "roadm Site_A",
+          "type": "Roadm",
+          "params": {
+              "target_pch_out_db": -20,
+              "design_bands": [{"f_min": 191.3e12, "f_max": 195.1e12}]
+          }
+      }
+
+It is possible to define a set of bands in the SI block instead of a single Spectrum Information.
+In this case type_variety must be used.
+Each set defines a reference channel used for design functions and autodesign.
+
+The default design settings for the path-request-run script have been modified.
+Now, design is performed once for the reference channel defined in the SI block of the eqpt_config,
+and requests are propagated based on this design.
+The --redesign-per-request option can be used to restore previous behaviour
+(design using request channel types).
+
+The autodesign function has been updated to insert multiband booster, preamp or inline amplifiers based on the OMS
+nature. If nothing is stated (no amplifier defined in the OMS, no design_bands attribute in the ROADM), then
+it uses single band Edfas.
+
+**Propagation**
+
+Only carriers within the amplifier bandwidth are propagated, improving system coherence. This more rigorous checking
+of the spectrum to be propagated and the amplifier bandwidth may lead to changes in the total number of channels
+compared to previous releases. The range can be adjusted by changing the values ​​of ``f_min`` and ``f_max``
+in the amplifier library.
+
+
+``f_min`` and ``f_max`` represent the boundary frequencies of the amplification bandwidth (the entire channel must fit
+within this range).
+In the example below, a signal center frequency of 190.05THz with a 50GHz width cannot fit within the amplifier band.
+Note that this has a different meaning in the SI or Transceiver blocks, where ``f_min`` and ``f_max`` refers to the
+minimum / maximum values of the carrier center frequency.
+
+    .. code-block:: json
+
+      {
+          "type_variety": "std_booster_L",
+          "f_min": 186.55e12,
+          "f_max": 190.05e12,
+          "type_def": "fixed_gain",
+          "gain_flatmax": 21,
+          "gain_min": 20,
+          "p_max": 21,
+          "nf0": 5,
+          "allowed_for_design": false
+      }
+
+
+**Display**
+
+The CLI output for the transmission_main_example now displays the channels used for design and simulation,
+as well as the tilt target of amplifiers.
+
+  .. code-block:: text
+
+    Reference used for design: (Input optical power reference in span = 0.00dBm,
+                                spacing = 50.00GHz
+                                nb_channels = 76)
+
+    Channels propagating: (Input optical power deviation in span = 0.00dB,
+                          spacing = 50.00GHz,
+                          transceiver output power = 0.00dBm,
+                          nb_channels = 76)
+
+The CLI output displays the settings of each amplifier:
+
+  .. code-block:: text
+
+    Multiband_amplifier east edfa in Site_A to Site_B
+      type_variety:           std_medium_gain_multiband
+      type_variety:           std_medium_gain_C    type_variety:           std_medium_gain_L
+      effective gain(dB):     20.90                effective gain(dB):     22.19
+      (before att_in and before output VOA)        (before att_in and before output VOA)
+      tilt-target(dB)         0.00                 tilt-target(dB)         0.00
+      noise figure (dB):      6.38                 noise figure (dB):      6.19
+      (including att_in)                           (including att_in)
+      pad att_in (dB):        0.00                 pad att_in (dB):        0.00
+      Power In (dBm):         -1.08                Power In (dBm):         -1.49
+      Power Out (dBm):        19.83                Power Out (dBm):        20.71
+      Delta_P (dB):           0.90                 Delta_P (dB):           2.19
+      target pch (dBm):       0.90                 target pch (dBm):       3.00
+      actual pch out (dBm):   -2.09                actual pch out (dBm):   -0.80
+      output VOA (dB):        3.00                 output VOA (dB):        3.00
+
+
+**New feature**
+
+The preturbative Raman and the approximated GGN models are introduced for a faster evaluation of the Raman and
+Kerr effects, respectively.
+These implementation are intended to reduce the computational effort required by multiband transmission scenarios.
+
+Both the novel models have been validated with exstensive simulations
+(see `arXiv:2304.11756 <https://arxiv.org/abs/2304.11756>`_ for the new Raman model and
+`jlt:9741324 <https://eeexplore.ieee.org/document/9741324>`_ for the new NLI model).
+Additionally, they have been experimentally validated in a laboratory setup composed of commertial equipment
+(see `icton:10648172 <https://eeexplore.ieee.org/document/10648172>`_).
+
+
+v2.10
+-----
+
+ROADM impairments can be defined per degree and roadm-path type (add, drop or express).
+Minimum loss when crossing a ROADM is no more 0 dB. It can be set per ROADM degree with roadm-path-impairments.
+
+The transceiver output power, which was previously set using the same parameter as the input span power (power_dbm),
+can now be set using a different parameter. It can be set as:
+
+  - for all channels, with tx_power_dbm using SI similarly to tx_osnr (gnpy-transmission-example script)
+
+    .. code-block:: json
+
+      "SI": [{
+              "f_min": 191.35e12,
+              "baud_rate": 32e9,
+              "f_max": 196.1e12,
+              "spacing": 50e9,
+              "power_dbm": 3,
+              "power_range_db": [0, 0, 1],
+              "roll_off": 0.15,
+              "tx_osnr": 40,
+              "tx_power_dbm": -10,
+              "sys_margins": 2
+          }
+      ]
+
+  - for certain channels, using -spectrum option and tx_channel_power_dbm option (gnpy-transmission-example script).
+
+    .. code-block:: json
+
+      {
+        "spectrum": [
+          {
+            "f_min": 191.35e12,
+            "f_max":193.1e12,
+            "baud_rate": 32e9,
+            "slot_width": 50e9,
+            "power_dbm": 0,
+            "roll_off": 0.15,
+            "tx_osnr": 40
+          },
+          {
+            "f_min": 193.15e12,
+            "f_max":193.15e12,
+            "baud_rate": 32e9,
+            "slot_width": 50e9,
+            "power_dbm": 0,
+            "roll_off": 0.15,
+            "tx_osnr": 40,
+            "tx_power_dbm": -10
+          },
+          {
+            "f_min": 193.2e12,
+            "f_max":195.1e12,
+            "baud_rate": 32e9,
+            "slot_width": 50e9,
+            "power_dbm": 0,
+            "roll_off": 0.15,
+            "tx_osnr": 40
+          }
+        ]
+      }
+
+  - per service using the additional parameter ``tx_power`` which similarly to ``power`` should be defined in Watt (gnpy-path-request script)
+
+    .. code-block:: json
+
+      {
+        "path-request": [
+          {
+            "request-id": "0",
+            "source": "trx SITE1",
+            "destination": "trx SITE2",
+            "src-tp-id": "trx SITE1",
+            "dst-tp-id": "trx SITE2",
+            "bidirectional": false,
+            "path-constraints": {
+              "te-bandwidth": {
+                "technology": "flexi-grid",
+                "trx_type": "Voyager",
+                "trx_mode": "mode 1",
+                "spacing": 50000000000.0,
+                "path_bandwidth": 100000000000.0
+              }
+            }
+          },
+          {
+            "request-id": "0 with tx_power",
+            "source": "trx SITE1",
+            "destination": "trx SITE2",
+            "src-tp-id": "trx SITE1",
+            "dst-tp-id": "trx SITE2",
+            "bidirectional": false,
+            "path-constraints": {
+              "te-bandwidth": {
+                "technology": "flexi-grid",
+                "trx_type": "Voyager",
+                "trx_mode": "mode 1",
+                "tx_power": 0.0001,
+                "spacing": 50000000000.0,
+                "path_bandwidth": 100000000000.0
+              }
+            }
+          }
+        ]
+      }
+
+v2.9
+----
+
+The revision introduces a major refactor that separates design and propagation. Most of these changes have no impact
+on the user experience, except the following ones:
+
+**Network design - amplifiers**: amplifier saturation is checked during design in all cases, even if type_variety is
+set; amplifier gain is no more computed on the fly but only at design phase.
+
+Before, the design did not consider amplifier power saturation during design if amplifier type_variety was stated.
+With this revision, the saturation is always applied:
+If design is made for a per channel power that leads to saturation, the target are properly reduced and the design
+is freezed. So that when a new simulation is performed on the same network for lower levels of power per channel
+the same gain target is applied. Before these were recomputed, changing the gain targets, so the simulation was
+not considering the exact same working points for amplifiers in case of saturation.
+
+Note that this case (working with saturation settings) is not recommended.
+
+The gain of amplifiers was estimated on the fly also in case of RamanFiber preceding elements. The refactor now
+requires that an estimation of Raman gain of the RamanFiber is done during design to properly compute a gain target.
+The Raman gain is estimated at design for every RamanFiber span and also during propagation instead of being only
+estimated at propagation stage for those Raman Fiber spans concerned with the transmission. The auto-design is more
+accurate for unpropagated spans, but this results in an increase overall computation time.
+This will be improved in the future.
+
+**Network design - ROADMs**: ROADM target power settings are verified during design.
+
+Design checks that expected power coming from every directions ingress from a ROADM are consistent with output power
+targets. The checks only considers the adjacent previous hop. If the expected power at the input of this ROADM is
+lower than the target power on the out-degree of the ROADM, a warning is displayed, and user is asked to review the
+input network to avoid this situation. This does not change the design or propagation behaviour.
+
+**Propagation**: amplifier gain target is no more recomputed during propagation. It is now possible to freeze
+the design and propagate without automatic changes.
+
+In previous release, gain was recomputed during propagation based on an hypothetical reference noiseless channel
+propagation. It was not possible to «freeze» the autodesign, and propagate without recomputing the gain target
+of amplifiers.
+With this new release, the design is freezed, so that it is possible to compare performances on same basis.
+
+**Display**: "effective pch (dbm)" is removed. Display contains the target pch which is the target power per channel
+in dBm, computed based on reference channel used for design and the amplifier delta_p in dB (and before out VOA
+contribution). Note that "actual pch out (dBm)" is the actual propagated total power per channel averaged per spectrum
+band definition at the output of the amplifier element, including noises and out VOA contribution.
+
+v2.8
+----
+
+**Spectrum assignment**: requests can now support multiple slots.
+The definition in service file supports multiple assignments (unchanged syntax):
+
+  .. code-block:: json
+
+          "effective-freq-slot": [
+            {
+              "N": 0,
+              "M": 4
+            }, {
+              "N": 50,
+              "M": 4
+            }
+          ],
+
+But in results, label-hop is now a list of slots and center frequency index:
+
+  .. code-block:: json
+
+          {
+            "path-route-object": {
+              "index": 4,
+              "label-hop": [
+                {
+                  "N": 0,
+                  "M": 4
+                }, {
+                  "N": 50,
+                  "M": 4
+                }
+              ]
+            }
+          },
+
+instead of 
+
+  .. code-block:: json
+
+          {
+            "path-route-object": {
+              "index": 4,
+              "label-hop": {
+                "N": 0,
+                "M": 4
+              }
+            }
+          },
+
+
+
+**change in display**: only warnings are displayed ; information are disabled and needs the -v (verbose)
+option to be displayed on standard output.
+
+**frequency scaling**: A more accurate description of fiber parameters is implemented, including frequency scaling of
+chromatic dispersion, effective area, Raman gain coefficient, and nonlinear coefficient.
+
+In particular:
+
+1. Chromatic dispersion can be defined with ``'dispersion'`` and ``'dispersion_slope'``, as in previous versions, or
+with ``'dispersion_per_frequency'``; the latter must be defined as a dictionary with two keys, ``'value'`` and
+``'frequency'`` and it has higher priority than the entries ``'dispersion'`` and ``'dispersion_slope'``.
+Essential change: In previous versions, when it was not provided the ``'dispersion_slope'`` was calculated in an
+involute manner to get a vanishing beta3 , and this was a mere artifact for NLI evaluation purposes (namely to evaluate
+beta2 and beta3, not for total dispersion accumulation). Now, the evaluation of beta2 and beta3 is performed explicitly
+in the element.py module.
+
+2. The effective area is provided as a scalar value evaluated at the Fiber reference frequency and properly scaled
+considering the Fiber refractive indices n1 and n2, and the core radius. These quantities are assumed to be fixed and
+are hard coded in the parameters.py module. Essential change: The effective area is always scaled along the frequency.
+
+3. The Raman gain coefficient is properly scaled considering the overlapping of fiber effective area values scaled at
+the interacting frequencies. Essential change: In previous version the Raman gain coefficient depends only on
+the frequency offset.
+
+4. The nonlinear coefficient ``'gamma'`` is properly scaled considering the refractive index n2 and the scaling
+effective area.  Essential change: As the effective area, the nonlinear coefficient is always scaled along the
+frequency.
+
+**power offset**: Power equalization now enables defining a power offset in transceiver library to represent
+the deviation from the general equalisation strategy defined in ROADMs.
+
+  .. code-block:: json
+
+            "mode": [{
+                    "format": "100G",
+                    "baud_rate": 32.0e9,
+                    "tx_osnr": 35.0,
+                    "min_spacing": 50.0e9,
+                    "cost": 1,
+                    "OSNR": 10.0,
+                    "bit_rate": 100.0e9,
+                    "roll_off": 0.2,
+                    "equalization_offset_db": 0.0
+                }, {
+                    "format": "200G",
+                    "baud_rate": 64.0e9,
+                    "tx_osnr": 35.0,
+                    "min_spacing": 75.0e9,
+                    "cost": 1,
+                    "OSNR": 13.0,
+                    "bit_rate": 200.0e9,
+                    "roll_off": 0.2,
+                    "equalization_offset_db": 1.76
+                }
+            ]
+
+v2.7
+----

docs/requirements.txt

@@ -1,7 +0,0 @@
-alabaster>=0.7.12,<1
-docutils>=0.17.1,<1
-myst-parser>=0.16.1,<1
-Pygments>=2.11.2,<3
-rstcheck
-Sphinx>=4.4.0,<5
-sphinxcontrib-bibtex>=2.4.1,<3

gnpy/core/elements.py

@@ -5,12 +5,12 @@
 gnpy.core.elements
 ==================
 
-Standard network elements which propagate optical spectrum
+Standard network elements which propagate optical spectrum.
 
 A network element is a Python callable. It takes a :class:`.info.SpectralInformation`
 object and returns a copy with appropriate fields affected. This structure
-represents spectral information that is "propogated" by this network element.
-Network elements must have only a local "view" of the network and propogate
+represents spectral information that is "propagated" by this network element.
+Network elements must have only a local "view" of the network and propagate
 :class:`.info.SpectralInformation` using only this information. They should be independent and
 self-contained.
 
@@ -20,19 +20,22 @@ unique identifier and a printable name, and provide the :py:meth:`__call__` meth
 instance as a result.
 """
 
+from copy import deepcopy
 from numpy import abs, array, errstate, ones, interp, mean, pi, polyfit, polyval, sum, sqrt, log10, exp, asarray, full,\
-    squeeze, zeros, append, flip, outer, ndarray
+    squeeze, zeros, outer, ndarray
 from scipy.constants import h, c
 from scipy.interpolate import interp1d
 from collections import namedtuple
-from typing import Union
+from typing import Union, List
 from logging import getLogger
+import warnings
 
 from gnpy.core.utils import lin2db, db2lin, arrange_frequencies, snr_sum, per_label_average, pretty_summary_print, \
-    watt2dbm, psd2powerdbm
-from gnpy.core.parameters import RoadmParams, FusedParams, FiberParams, PumpParams, EdfaParams, EdfaOperational
+    watt2dbm, psd2powerdbm, calculate_absolute_min_or_zero, nice_column_str
+from gnpy.core.parameters import RoadmParams, FusedParams, FiberParams, PumpParams, EdfaParams, EdfaOperational, \
+    MultiBandParams, RoadmPath, RoadmImpairment, TransceiverParams, find_band_name, FrequencyBand
 from gnpy.core.science_utils import NliSolver, RamanSolver
-from gnpy.core.info import SpectralInformation, ReferenceCarrier
+from gnpy.core.info import SpectralInformation, muxed_spectral_information, demuxed_spectral_information
 from gnpy.core.exceptions import NetworkTopologyError, SpectrumError, ParametersError
 
 
@@ -79,8 +82,20 @@ class _Node:
 
 
 class Transceiver(_Node):
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
+    def __init__(self, *args, params=None, **kwargs):
+        if not params:
+            params = {}
+        try:
+            with warnings.catch_warnings(record=True) as caught_warnings:
+                super().__init__(*args, params=TransceiverParams(**params), **kwargs)
+                if caught_warnings:
+                    msg = f'In Transceiver {kwargs["uid"]}: {caught_warnings[0].message}'
+                    _logger.warning(msg)
+        except ParametersError as e:
+            msg = f'Config error in {kwargs["uid"]}: {e}'
+            _logger.critical(msg)
+            raise ParametersError(msg) from e
+
         self.osnr_ase_01nm = None
         self.osnr_ase = None
         self.osnr_nli = None
@@ -94,6 +109,9 @@ class Transceiver(_Node):
         self.penalties = {}
         self.total_penalty = 0
         self.propagated_labels = [""]
+        self.tx_power = None
+        self.design_bands = self.params.design_bands
+        self.per_degree_design_bands = self.params.per_degree_design_bands
 
     def _calc_cd(self, spectral_info):
         """Updates the Transceiver property with the CD of the received channels. CD in ps/nm.
@@ -155,6 +173,7 @@ class Transceiver(_Node):
         # use raw_values so that the added SNR penalties are not cumulated
         snr_added = 0
         for s in args:
+            if s is not None:
                 snr_added += db2lin(-s)
         snr_added = -lin2db(snr_added)
         self.osnr_ase = snr_sum(self.raw_osnr_ase, self.baud_rate, snr_added)
@@ -192,6 +211,7 @@ class Transceiver(_Node):
         osnr_ase = per_label_average(self.osnr_ase, self.propagated_labels)
         osnr_ase_01nm = per_label_average(self.osnr_ase_01nm, self.propagated_labels)
         snr_01nm = per_label_average(self.snr_01nm, self.propagated_labels)
+        tx_power_dbm = per_label_average(watt2dbm(self.tx_power), self.propagated_labels)
         cd = mean(self.chromatic_dispersion)
         pmd = mean(self.pmd)
         pdl = mean(self.pdl)
@@ -205,7 +225,8 @@ class Transceiver(_Node):
                             f'  CD (ps/nm):                {cd:.2f}',
                             f'  PMD (ps):                  {pmd:.2f}',
                             f'  PDL (dB):                  {pdl:.2f}',
-                            f'  Latency (ms):              {latency:.2f}'])
+                            f'  Latency (ms):              {latency:.2f}',
+                            f'  Actual pch out (dBm):      {pretty_summary_print(tx_power_dbm)}'])
 
         cd_penalty = self.penalties.get('chromatic_dispersion')
         if cd_penalty is not None:
@@ -220,6 +241,7 @@ class Transceiver(_Node):
         return result
 
     def __call__(self, spectral_info):
+        self.tx_power = spectral_info.tx_power
         self._calc_snr(spectral_info)
         self._calc_cd(spectral_info)
         self._calc_pmd(spectral_info)
@@ -233,7 +255,11 @@ class Roadm(_Node):
         if not params:
             params = {}
         try:
+            with warnings.catch_warnings(record=True) as caught_warnings:
                 super().__init__(*args, params=RoadmParams(**params), **kwargs)
+                if caught_warnings:
+                    msg = f'In ROADM {kwargs["uid"]}: {caught_warnings[0].message}'
+                    _logger.warning(msg)
         except ParametersError as e:
             msg = f'Config error in {kwargs["uid"]}: {e}'
             raise ParametersError(msg) from e
@@ -242,6 +268,7 @@ class Roadm(_Node):
         # on the path, since it depends on the equalization definition on the degree.
         self.ref_pch_out_dbm = None
         self.loss = 0  # auto-design interest
+        self.loss_pch_db = None
 
         # Optical power of carriers are equalized by the ROADM, so that the experienced loss is not the same for
         # different carriers. The ref_effective_loss records the loss for a reference carrier.
@@ -258,6 +285,21 @@ class Roadm(_Node):
         self.per_degree_pch_out_dbm = self.params.per_degree_pch_out_db
         self.per_degree_pch_psd = self.params.per_degree_pch_psd
         self.per_degree_pch_psw = self.params.per_degree_pch_psw
+        self.ref_pch_in_dbm = {}
+        self.ref_carrier = None
+        # Define the nature of from-to internal connection: express-path, drop-path, add-path
+        # roadm_paths contains a list of RoadmPath object for each path crossing the ROADM
+        self.roadm_paths = []
+        # roadm_path_impairments contains a dictionnary of impairments profiles corresponding to type_variety
+        # first listed add, drop an express constitute the default
+        self.roadm_path_impairments = self.params.roadm_path_impairments
+        # per degree definitions, in case some degrees have particular deviations with respect to default.
+        self.per_degree_impairments = {f'{i["from_degree"]}-{i["to_degree"]}': {"from_degree": i["from_degree"],
+                                                                                "to_degree": i["to_degree"],
+                                                                                "impairment_id": i["impairment_id"]}
+                                       for i in self.params.per_degree_impairments}
+        self.design_bands = deepcopy(self.params.design_bands)
+        self.per_degree_design_bands = deepcopy(self.params.per_degree_design_bands)
 
     @property
     def to_json(self):
@@ -272,9 +314,10 @@ class Roadm(_Node):
         to_json = {
             'uid': self.uid,
             'type': type(self).__name__,
+            'type_variety': self.type_variety,
             'params': {
                 equalisation: value,
-                'restrictions': self.restrictions,
+                'restrictions': self.restrictions
             },
             'metadata': {
                 'location': self.metadata['location']._asdict()
@@ -287,6 +330,14 @@ class Roadm(_Node):
             to_json['params']['per_degree_psd_out_mWperGHz'] = self.per_degree_pch_psd
         if self.per_degree_pch_psw:
             to_json['params']['per_degree_psd_out_mWperSlotWidth'] = self.per_degree_pch_psw
+        if self.per_degree_impairments:
+            to_json['per_degree_impairments'] = list(self.per_degree_impairments.values())
+
+        if self.params.design_bands is not None:
+            if len(self.params.design_bands) > 1:
+                to_json['params']['design_bands'] = self.params.design_bands
+        if self.params.per_degree_design_bands:
+            to_json['params']['per_degree_design_bands'] = self.params.per_degree_design_bands
         return to_json
 
     def __repr__(self):
@@ -297,13 +348,15 @@ class Roadm(_Node):
             return f'{type(self).__name__} {self.uid}'
 
         total_pch = pretty_summary_print(per_label_average(self.pch_out_dbm, self.propagated_labels))
+        total_loss = pretty_summary_print(per_label_average(self.loss_pch_db, self.propagated_labels))
         return '\n'.join([f'{type(self).__name__} {self.uid}',
-                          f'  effective loss (dB):     {self.ref_effective_loss:.2f}',
-                          f'  reference pch out (dBm): {self.ref_pch_out_dbm:.2f}',
-                          f'  actual pch out (dBm):    {total_pch}'])
+                          f'  Type_variety:            {self.type_variety}',
+                          f'  Reference loss (dB):     {self.ref_effective_loss:.2f}',
+                          f'  Actual loss (dB):        {total_loss}',
+                          f'  Reference pch out (dBm): {self.ref_pch_out_dbm:.2f}',
+                          f'  Actual pch out (dBm):    {total_pch}'])
 
-    def get_roadm_target_power(self, ref_carrier: ReferenceCarrier = None,
-                               spectral_info: SpectralInformation = None) -> Union[float, ndarray]:
+    def get_roadm_target_power(self, spectral_info: SpectralInformation = None) -> Union[float, ndarray]:
         """Computes the power in dBm for a reference carrier or for a spectral information.
         power is computed based on equalization target.
         if spectral_info baud_rate is baud_rate = [32e9, 42e9, 64e9, 42e9, 32e9], and
@@ -325,22 +378,22 @@ class Roadm(_Node):
             if self.target_pch_out_dbm is not None:
                 return self.target_pch_out_dbm
             if self.target_psd_out_mWperGHz is not None:
-                return psd2powerdbm(self.target_psd_out_mWperGHz, ref_carrier.baud_rate)
+                return psd2powerdbm(self.target_psd_out_mWperGHz, self.ref_carrier.baud_rate)
             if self.target_out_mWperSlotWidth is not None:
-                return psd2powerdbm(self.target_out_mWperSlotWidth, ref_carrier.slot_width)
+                return psd2powerdbm(self.target_out_mWperSlotWidth, self.ref_carrier.slot_width)
         return None
 
-    def get_per_degree_ref_power(self, degree, ref_carrier):
+    def get_per_degree_ref_power(self, degree):
         """Get the target power in dBm out of ROADM degree for the reference bandwidth
         If no equalization is defined on this degree use the ROADM level one.
         """
         if degree in self.per_degree_pch_out_dbm:
             return self.per_degree_pch_out_dbm[degree]
         elif degree in self.per_degree_pch_psd:
-            return psd2powerdbm(self.per_degree_pch_psd[degree], ref_carrier.baud_rate)
+            return psd2powerdbm(self.per_degree_pch_psd[degree], self.ref_carrier.baud_rate)
         elif degree in self.per_degree_pch_psw:
-            return psd2powerdbm(self.per_degree_pch_psw[degree], ref_carrier.slot_width)
-        return self.get_roadm_target_power(ref_carrier)
+            return psd2powerdbm(self.per_degree_pch_psw[degree], self.ref_carrier.slot_width)
+        return self.get_roadm_target_power()
 
     def get_per_degree_power(self, degree, spectral_info):
         """Get the target power in dBm out of ROADM degree for the spectral information
@@ -354,34 +407,43 @@ class Roadm(_Node):
             return psd2powerdbm(self.per_degree_pch_psw[degree], spectral_info.slot_width)
         return self.get_roadm_target_power(spectral_info=spectral_info)
 
-    def propagate(self, spectral_info, degree):
+    def propagate(self, spectral_info, degree, from_degree):
         """Equalization targets are read from topology file if defined and completed with default
         definition of the library.
-        If the input power is lower than the target one, use the input power instead because
-        a ROADM doesn't amplify, it can only attenuate.
-        There is no difference for add or express : the same target is applied. For the moment
-        propagates operates with spectral info carriers all having the same source or destination.
+        If the input power is lower than the target one, use the input power minus the ROADM loss
+        if is exists, because a ROADM doesn't amplify, it can only attenuate.
+        There is no difference for add or express : the same target is applied.
+        For the moment propagate operates with spectral info carriers all having the same source or destination.
         """
-        # TODO maybe add a minimum loss for the ROADM
-
+        # record input powers to compute the actual loss at the end of the process
+        input_power_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
+        # apply min ROADM loss if it exists
+        roadm_maxloss_db = self.get_impairment('roadm-maxloss', spectral_info.frequency, from_degree, degree)
+        spectral_info.apply_attenuation_db(roadm_maxloss_db)
+        # records the total power after applying minimum loss
+        net_input_power_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
         # find the target power for the reference carrier
-        ref_per_degree_pch = self.get_per_degree_ref_power(degree, spectral_info.pref.ref_carrier)
+        ref_per_degree_pch = self.get_per_degree_ref_power(degree)
         # find the target powers for each signal carrier
         per_degree_pch = self.get_per_degree_power(degree, spectral_info=spectral_info)
 
         # Definition of ref_pch_out_dbm for the reference channel:
-        # Depending on propagation upstream from this ROADM, the input power (p_spani) might be smaller than
+        # Depending on propagation upstream from this ROADM, the input power might be smaller than
         # the target power out configured for this ROADM degree's egress. Since ROADM does not amplify,
         # the power out of the ROADM for the ref channel is the min value between target power and input power.
-        # (TODO add a minimum loss for the ROADM crossing)
-        self.ref_pch_out_dbm = min(spectral_info.pref.p_spani, ref_per_degree_pch)
+        ref_pch_in_dbm = self.ref_pch_in_dbm[from_degree]
+        # Calculate the output power for the reference channel (only for visualization)
+        self.ref_pch_out_dbm = min(ref_pch_in_dbm - max(roadm_maxloss_db), ref_per_degree_pch)
+
         # Definition of effective_loss:
         # Optical power of carriers are equalized by the ROADM, so that the experienced loss is not the same for
         # different carriers. effective_loss records the loss for the reference carrier.
-        self.ref_effective_loss = spectral_info.pref.p_spani - self.ref_pch_out_dbm
-        input_power = spectral_info.signal + spectral_info.nli + spectral_info.ase
+        # Calculate the effective loss for the reference channel
+        self.ref_effective_loss = ref_pch_in_dbm - self.ref_pch_out_dbm
+
+        # Calculate the target power per channel according to the equalization policy
         target_power_per_channel = per_degree_pch + spectral_info.delta_pdb_per_channel
-        # Computation of the per channel target power according to equalization policy
+        # Computation of the correction according to equalization policy
         # If target_power_per_channel has some channels power above input power, then the whole target is reduced.
         # For example, if user specifies delta_pdb_per_channel:
         # freq1: 1dB, freq2: 3dB, freq3: -3dB, and target is -20dBm out of the ROADM,
@@ -396,28 +458,118 @@ class Roadm(_Node):
         # that had the min power.
         # This change corresponds to a discussion held during coders call. Please look at this document for
         # a reference: https://telecominfraproject.atlassian.net/wiki/spaces/OOPT/pages/669679645/PSE+Meeting+Minutes
-        correction = (abs(watt2dbm(input_power) - target_power_per_channel)
-                      - (watt2dbm(input_power) - target_power_per_channel)) / 2
+        correction = calculate_absolute_min_or_zero(net_input_power_dbm - target_power_per_channel)
         new_target = target_power_per_channel - correction
-        delta_power = watt2dbm(input_power) - new_target
+        delta_power = net_input_power_dbm - new_target
 
         spectral_info.apply_attenuation_db(delta_power)
-        spectral_info.pmd = sqrt(spectral_info.pmd ** 2 + self.params.pmd ** 2)
-        spectral_info.pdl = sqrt(spectral_info.pdl ** 2 + self.params.pdl ** 2)
+
+        # Update the PMD information
+        pmd_impairment = self.get_impairment('roadm-pmd', spectral_info.frequency, from_degree, degree)
+        spectral_info.pmd = sqrt(spectral_info.pmd ** 2 + pmd_impairment ** 2)
+
+        # Update the PMD information
+        pdl_impairment = self.get_impairment('roadm-pdl', spectral_info.frequency, from_degree, degree)
+        spectral_info.pdl = sqrt(spectral_info.pdl ** 2 + pdl_impairment ** 2)
+
+        # Update the per channel power with the result of propagation
         self.pch_out_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
+
+        # Update the loss per channel and the labels
+        self.loss_pch_db = input_power_dbm - self.pch_out_dbm
         self.propagated_labels = spectral_info.label
 
-    def update_pref(self, spectral_info):
-        """Update Reference power
+    def set_roadm_paths(self, from_degree, to_degree, path_type, impairment_id=None):
+        """set internal path type: express, drop or add with corresponding impairment
 
-        This modifies the spectral info in-place. Only the `pref` is updated with new p_spani,
-        while p_span0 is not changed.
+        If no impairment id is defined, then use the first profile that matches the path_type in the
+        profile dictionnary.
         """
-        spectral_info.pref = spectral_info.pref._replace(p_spani=self.ref_pch_out_dbm)
+        # initialize impairment with params.pmd, params.cd
+        # if more detailed parameters are available for the Roadm, the use them instead
+        roadm_global_impairment = {
+            'impairment': [{
+                'roadm-pmd': self.params.pmd,
+                'roadm-pdl': self.params.pdl,
+                'frequency-range': {
+                    'lower-frequency': None,
+                    'upper-frequency': None
+                }}]}
+        if path_type in ['add', 'drop']:
+            # without detailed imparments, we assume that add OSNR contribution is the same as drop contribution
+            # add_drop_osnr_db = - 10log10(1/add_osnr + 1/drop_osnr) with add_osnr = drop_osnr
+            # = add_osnr_db + 10log10(2)
+            roadm_global_impairment['impairment'][0]['roadm-osnr'] = self.params.add_drop_osnr + lin2db(2)
+        impairment = RoadmImpairment(roadm_global_impairment)
 
-    def __call__(self, spectral_info, degree):
-        self.propagate(spectral_info, degree=degree)
-        self.update_pref(spectral_info)
+        if impairment_id is None:
+            # get the first item in the type variety that matches the path_type
+            for path_impairment_id, path_impairment in self.roadm_path_impairments.items():
+                if path_impairment.path_type == path_type:
+                    impairment = path_impairment
+                    impairment_id = path_impairment_id
+                    break
+            # at this point, path_type is not part of roadm_path_impairment, impairment and impairment_id are None
+        else:
+            if impairment_id in self.roadm_path_impairments:
+                impairment = self.roadm_path_impairments[impairment_id]
+            else:
+                msg = f'ROADM {self.uid}: impairment profile id {impairment_id} is not defined in library'
+                raise NetworkTopologyError(msg)
+        # print(from_degree, to_degree, path_type)
+        self.roadm_paths.append(RoadmPath(from_degree=from_degree, to_degree=to_degree, path_type=path_type,
+                                          impairment_id=impairment_id, impairment=impairment))
+
+    def get_roadm_path(self, from_degree, to_degree):
+        """Get internal path type impairment"""
+        for roadm_path in self.roadm_paths:
+            if roadm_path.from_degree == from_degree and roadm_path.to_degree == to_degree:
+                return roadm_path
+        msg = f'Could not find from_degree-to_degree {from_degree}-{to_degree} path in ROADM {self.uid}'
+        raise NetworkTopologyError(msg)
+
+    def get_per_degree_impairment_id(self, from_degree, to_degree):
+        """returns the id of the impairment if the degrees are in the per_degree tab"""
+        if f'{from_degree}-{to_degree}' in self.per_degree_impairments.keys():
+            return self.per_degree_impairments[f'{from_degree}-{to_degree}']["impairment_id"]
+        return None
+
+    def get_path_type_per_id(self, impairment_id):
+        """returns the path_type of the impairment if the is is defined"""
+        if impairment_id in self.roadm_path_impairments.keys():
+            return self.roadm_path_impairments[impairment_id].path_type
+        return None
+
+    def get_impairment(self, impairment: str, frequency_array: array, from_degree: str, degree: str) \
+            -> array:
+        """
+        Retrieves the specified impairment values for the given frequency array.
+
+        Parameters:
+            impairment (str): The type of impairment to retrieve (roadm-pmd, roamd-maxloss...).
+            frequency_array (array): The frequencies at which to check for impairments.
+            from_degree (str): The ingress degree for the roadm internal path.
+            degree (str): The egress degree for the roadm internal path.
+
+        Returns:
+            array: An array of impairment values for the specified frequencies.
+        """
+        result = []
+        impairment_per_band = self.get_roadm_path(from_degree, degree).impairment.impairments
+        for frequency in frequency_array:
+            for item in impairment_per_band:
+                f_min = item['frequency-range']['lower-frequency']
+                f_max = item['frequency-range']['upper-frequency']
+                if (f_min is None or f_min <= frequency <= f_max):
+                    item[impairment] = item.get(impairment, RoadmImpairment.default_values[impairment])
+                    if item[impairment] is not None:
+                        result.append(item[impairment])
+                        break  # Stop searching after the first match for this frequency
+        if result:
+            return array(result)
+
+    def __call__(self, spectral_info, degree, from_degree):
+        self.propagate(spectral_info, degree=degree, from_degree=from_degree)
         return spectral_info
 
 
@@ -451,13 +603,8 @@ class Fused(_Node):
     def propagate(self, spectral_info):
         spectral_info.apply_attenuation_db(self.loss)
 
-    def update_pref(self, spectral_info):
-        spectral_info.pref = spectral_info.pref._replace(p_span0=spectral_info.pref.p_span0,
-                                                         p_spani=spectral_info.pref.p_spani - self.loss)
-
     def __call__(self, spectral_info):
         self.propagate(spectral_info)
-        self.update_pref(spectral_info)
         return spectral_info
 
 
@@ -482,6 +629,7 @@ class Fiber(_Node):
                                        f"({1e-3 * self.params.length} km), boundaries excluded.")
         self.lumped_losses = db2lin(- lumped_losses_power)  # [linear units]
         self.z_lumped_losses = array(z_lumped_losses) * 1e3  # [m]
+        self.ref_pch_in_dbm = None
 
     @property
     def to_json(self):
@@ -527,10 +675,17 @@ class Fiber(_Node):
             interpolation = interp1d(ref_frequency, parameter)(spectrum_frequency)
             return interpolation
         except ValueError:
+            try:
+                start = spectrum_frequency[0]
+                stop = spectrum_frequency[-1]
+            except IndexError:
+                # when frequency is a 0-dimensionnal array
+                start = spectrum_frequency
+                stop = spectrum_frequency
             raise SpectrumError('The spectrum bandwidth exceeds the frequency interval used to define the fiber '
                                 f'{name} in "{type(self).__name__} {self.uid}".'
-                                f'\nSpectrum f_min-f_max: {round(spectrum_frequency[0] * 1e-12, 2)}-'
-                                f'{round(spectrum_frequency[-1] * 1e-12, 2)}'
+                                f'\nSpectrum f_min-f_max: {round(start * 1e-12, 2)}-'
+                                f'{round(stop * 1e-12, 2)}'
                                 f'\n{name} f_min-f_max: {round(ref_frequency[0] * 1e-12, 2)}-'
                                 f'{round(ref_frequency[-1] * 1e-12, 2)}')
 
@@ -675,21 +830,16 @@ class Fiber(_Node):
         self.pch_out_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
         self.propagated_labels = spectral_info.label
 
-    def update_pref(self, spectral_info):
-        # in case of Raman, the resulting loss of the fiber is not equivalent to self.loss
-        # because of Raman gain. In order to correctly update pref, we need the resulting loss:
-        # power_out - power_in. We use the total signal power (sum on all channels) to compute
-        # this loss, because pref is a noiseless reference.
-        loss = round(lin2db(self._psig_in / sum(spectral_info.signal)), 2)
-        self.pch_out_db = spectral_info.pref.p_spani - loss
-        spectral_info.pref = spectral_info.pref._replace(p_span0=spectral_info.pref.p_span0,
-                                                         p_spani=self.pch_out_db)
-
     def __call__(self, spectral_info):
         # _psig_in records the total signal power of the spectral information before propagation.
         self._psig_in = sum(spectral_info.signal)
         self.propagate(spectral_info)
-        self.update_pref(spectral_info)
+        # In case of Raman, the resulting loss of the fiber is not equivalent to self.loss
+        # because of Raman gain. The resulting loss is:
+        # power_out - power_in. We use the total signal power (sum on all channels) to compute
+        # this loss.
+        loss = round(lin2db(self._psig_in / sum(spectral_info.signal)), 2)
+        self.pch_out_db = self.ref_pch_in_dbm - loss
         return spectral_info
 
 
@@ -717,11 +867,16 @@ class RamanFiber(Fiber):
     def to_json(self):
         return dict(super().to_json, operational=self.operational)
 
+    def __str__(self):
+        return super().__str__() + f'\n  reference gain (dB):         {round(self.estimated_gain, 2)}' \
+            + f'\n  actual gain (dB):            {round(self.actual_raman_gain, 2)}'
+
     def propagate(self, spectral_info: SpectralInformation):
         """Modifies the spectral information computing the attenuation, the non-linear interference generation,
         the CD and PMD accumulation.
         """
         # apply the attenuation due to the input connector loss
+        pin = watt2dbm(sum(spectral_info.signal))
         attenuation_in_db = self.params.con_in + self.params.att_in
         spectral_info.apply_attenuation_db(attenuation_in_db)
 
@@ -751,6 +906,8 @@ class RamanFiber(Fiber):
         spectral_info.apply_attenuation_db(attenuation_out_db)
         self.pch_out_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
         self.propagated_labels = spectral_info.label
+        pout = watt2dbm(sum(spectral_info.signal))
+        self.actual_raman_gain = self.loss + pout - pin
 
 
 class Edfa(_Node):
@@ -761,7 +918,7 @@ class Edfa(_Node):
             operational = {}
         self.variety_list = kwargs.pop('variety_list', None)
         super().__init__(*args, params=EdfaParams(**params), operational=EdfaOperational(**operational), **kwargs)
-        self.interpol_dgt = None  # interpolated dynamic gain tilt
+        self.interpol_dgt = None  # interpolated dynamic gain tilt defined per frequency on amp band
         self.interpol_gain_ripple = None  # gain ripple
         self.interpol_nf_ripple = None  # nf_ripple
         self.channel_freq = None  # SI channel frequencies
@@ -771,31 +928,41 @@ class Edfa(_Node):
         self.pin_db = None
         self.nch = None
         self.pout_db = None
-        self.target_pch_out_db = None
+        self.target_pch_out_dbm = None
         self.effective_pch_out_db = None
         self.passive = False
         self.att_in = None
         self.effective_gain = self.operational.gain_target
-        self.delta_p = self.operational.delta_p  # delta P with Pref (power swwep) in power mode
-        self.tilt_target = self.operational.tilt_target
+        # self.operational.delta_p is defined by user for reference channel
+        # self.delta_p is set with self.operational.delta_p, but it may be changed during design:
+        # - if operational.delta_p is None, self.delta_p is computed at design phase
+        # - if operational.delta_p can not be applied because of saturation, self.delta_p is recomputed
+        # - if power_mode is False, then it is set to None
+        self.delta_p = self.operational.delta_p
+        # self._delta_p contains computed delta_p during design even if power_mode is False
+        self._delta_p = None
+        self.tilt_target = self.operational.tilt_target  # defined per lambda on the amp band
         self.out_voa = self.operational.out_voa
         self.propagated_labels = [""]
 
     @property
     def to_json(self):
-        return {'uid': self.uid,
+        _to_json = {
+            'uid': self.uid,
             'type': type(self).__name__,
             'type_variety': self.params.type_variety,
             'operational': {
                 'gain_target': round(self.effective_gain, 6) if self.effective_gain else None,
                 'delta_p': self.delta_p,
-                    'tilt_target': self.tilt_target,
+                'tilt_target': round(self.tilt_target, 5) if self.tilt_target is not None else None,
+                # defined per lambda on the amp band
                 'out_voa': self.out_voa
             },
             'metadata': {
                 'location': self.metadata['location']._asdict()
             }
         }
+        return _to_json
 
     def __repr__(self):
         return (f'{type(self).__name__}(uid={self.uid!r}, '
@@ -817,15 +984,17 @@ class Edfa(_Node):
         return '\n'.join([f'{type(self).__name__} {self.uid}',
                           f'  type_variety:           {self.params.type_variety}',
                           f'  effective gain(dB):     {self.effective_gain:.2f}',
-                          f'  (before att_in and before output VOA)',
+                          '  (before att_in and before output VOA)',
+                          f'  tilt-target(dB)         {self.tilt_target:.2f}',
                           f'  noise figure (dB):      {nf:.2f}',
                           f'  (including att_in)',
                           f'  pad att_in (dB):        {self.att_in:.2f}',
                           f'  Power In (dBm):         {self.pin_db:.2f}',
                           f'  Power Out (dBm):        {self.pout_db:.2f}',
-                          f'  Delta_P (dB):           ' + (f'{self.delta_p:.2f}' if self.delta_p is not None else 'None'),
-                          f'  target pch (dBm):       ' + (f'{self.target_pch_out_db:.2f}' if self.target_pch_out_db is not None else 'None'),
-                          f'  effective pch (dBm):    {self.effective_pch_out_db:.2f}',
+                          '  Delta_P (dB):           ' + (f'{self.delta_p:.2f}'
+                                                          if self.delta_p is not None else 'None'),
+                          '  target pch (dBm):       ' + (f'{self.target_pch_out_dbm:.2f}'
+                                                          if self.target_pch_out_dbm is not None else 'None'),
                           f'  actual pch out (dBm):   {total_pch}',
                           f'  output VOA (dB):        {self.out_voa:.2f}'])
 
@@ -853,20 +1022,12 @@ class Edfa(_Node):
         # For now, with homogeneous spectrum, we can calculate it as the difference between neighbouring channels.
         self.slot_width = self.channel_freq[1] - self.channel_freq[0]
 
-        """in power mode: delta_p is defined and can be used to calculate the power target
-        This power target is used calculate the amplifier gain"""
-        pref = spectral_info.pref
-        if self.delta_p is not None:
-            self.target_pch_out_db = round(self.delta_p + pref.p_span0, 2)
-            self.effective_gain = self.target_pch_out_db - pref.p_spani
-
         """check power saturation and correct effective gain & power accordingly:"""
         # Compute the saturation accounting for actual power at the input of the amp
         self.effective_gain = min(
             self.effective_gain,
             self.params.p_max - self.pin_db
         )
-        self.effective_pch_out_db = round(pref.p_spani + self.effective_gain, 2)
 
         """check power saturation and correct target_gain accordingly:"""
         self.nf = self._calc_nf()
@@ -1026,7 +1187,7 @@ class Edfa(_Node):
         p = polyfit(self.channel_freq, self.interpol_dgt, 1)
         dgt_slope = p[0]
 
-        # Calculate the target slope
+        # Calculate the target slope defined per frequency on the amp band
         targ_slope = -self.tilt_target / (self.params.f_max - self.params.f_min)
 
         # first estimate of DGT scaling
@@ -1102,12 +1263,127 @@ class Edfa(_Node):
         self.pch_out_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
         self.propagated_labels = spectral_info.label
 
-    def update_pref(self, spectral_info):
-        spectral_info.pref = \
-            spectral_info.pref._replace(p_span0=spectral_info.pref.p_span0,
-                                        p_spani=spectral_info.pref.p_spani + self.effective_gain - self.out_voa)
-
     def __call__(self, spectral_info):
+        # filter out carriers outside the amplifier band
+        band = next(b for b in self.params.bands)
+        spectral_info = demuxed_spectral_information(spectral_info, band)
+        if spectral_info.carriers:
             self.propagate(spectral_info)
-        self.update_pref(spectral_info)
             return spectral_info
+        raise ValueError(f'Amp {self.uid} Defined propagation band does not match amplifiers band.')
+
+
+class Multiband_amplifier(_Node):
+    """Represents a multiband amplifier that manages multiple amplifiers across different frequency bands.
+
+    This class allows for the initialization and management of amplifiers, each associated with a specific
+    frequency band. It provides methods for signal propagation through the amplifiers and for exporting
+    to JSON format.
+
+    param: amplifiers: list of dict. A list of dictionaries, each containing parameters for setting an
+    individual amplifier.
+    param: params : dict. A dictionary of parameters for the multiband amplifier, which must include
+    necessary configuration settings.
+    param: args, kwargs: Additional positional and keyword arguments passed to the parent class `_Node`.
+
+    Attributes:
+    -----------
+    variety_list : A list of varieties associated with the amplifier.
+    amplifiers : A dictionary mapping band names to their corresponding amplifier instances.
+
+    Methods:
+    --------
+    __call__(spectral_info):
+    Propagates the input spectral information through each amplifier and returns the multiplexed spectrum.
+
+    to_json:
+    Converts the amplifier's state to a JSON-compatible dictionary.
+
+    __repr__():
+    Returns a string representation of the multiband amplifier instance.
+
+    __str__():
+    Returns a formatted string representation of the multiband amplifier and its amplifiers.
+
+    Raises:
+    -------
+    ParametersError: If there are conflicting amplifier definitions for the same frequency band during initialization.
+
+    ValueError: If the input spectral information does not match any defined amplifier bands during propagation.
+    """
+    # separate the top level type_variety from kwargs to avoid having multiple type_varieties on each element processing
+    def __init__(self, *args, amplifiers: List[dict], params: dict, **kwargs):
+        self.variety_list = kwargs.pop('variety_list', None)
+        try:
+            super().__init__(params=MultiBandParams(**params), **kwargs)
+        except ParametersError as e:
+            raise ParametersError(f'{kwargs["uid"]}: {e}')
+        self.amplifiers = {}
+        if 'type_variety' in kwargs:
+            kwargs.pop('type_variety')
+        self.passive = False
+        for amp_dict in amplifiers:
+            # amplifiers dict uses default names as key to represent the band
+            amp = Edfa(**amp_dict, **kwargs)
+            band = next(b for b in amp.params.bands)
+            band_name = find_band_name(FrequencyBand(f_min=band["f_min"], f_max=band["f_max"]))
+            if band_name not in self.amplifiers.keys() and band not in self.params.bands:
+                self.params.bands.append(band)
+                self.amplifiers[band_name] = amp
+            elif band_name not in self.amplifiers.keys() and band in self.params.bands:
+                self.amplifiers[band_name] = amp
+            else:
+                raise ParametersError(f'{kwargs["uid"]}: has more than one amp defined for the same band')
+
+    def __call__(self, spectral_info: SpectralInformation):
+        """propagates in each amp and returns the muxed spectrum
+        """
+        out_si = []
+        for _, amp in self.amplifiers.items():
+            si = demuxed_spectral_information(spectral_info, amp.params.bands[0])
+            # if spectral_info frequencies are outside amp band, si is None
+            if si:
+                si = amp(si)
+                out_si.append(si)
+        if not out_si:
+            raise ValueError('Defined propagation band does not match amplifiers band.')
+        return muxed_spectral_information(out_si)
+
+    @property
+    def to_json(self):
+        return {'uid': self.uid,
+                'type': type(self).__name__,
+                'type_variety': self.type_variety,
+                'amplifiers': [{
+                    'type_variety': amp.type_variety,
+                    'operational': {
+                        'gain_target': round(amp.effective_gain, 6),
+                        'delta_p': amp.delta_p,
+                        'tilt_target': amp.tilt_target,
+                        'out_voa': amp.out_voa
+                    }} for amp in self.amplifiers.values()
+                ],
+                'metadata': {
+                    'location': self.metadata['location']._asdict()
+                }
+                }
+
+    def __repr__(self):
+        return (f'{type(self).__name__}(uid={self.uid!r}, '
+                f'type_variety={self.type_variety!r}, ')
+
+    def __str__(self):
+        amp_str = [f'{type(self).__name__} {self.uid}',
+                   f'  type_variety:           {self.type_variety}']
+        multi_str_data = []
+        max_width = 0
+        for amp in self.amplifiers.values():
+            lines = amp.__str__().split('\n')
+            # start at index 1 to remove uid from each amp list of strings
+            # records only if amp is used ie si has frequencies in amp) otherwise there is no other string than the uid
+            if len(lines) > 1:
+                max_width = max(max_width, max([len(line) for line in lines[1:]]))
+                multi_str_data.append(lines[1:])
+        # multi_str_data contains lines with each amp str, instead we want to print per column: transpose the string
+        transposed_data = list(map(list, zip(*multi_str_data)))
+        return '\n'.join(amp_str) + '\n' + nice_column_str(data=transposed_data, max_length=max_width + 2, padding=3)

gnpy/core/equipment.py

@@ -7,35 +7,43 @@ gnpy.core.equipment
 
 This module contains functionality for specifying equipment.
 """
+from collections import defaultdict
+from functools import reduce
+from typing import List
 
-from gnpy.core.utils import automatic_nch, db2lin
-from gnpy.core.exceptions import EquipmentConfigError
+from gnpy.core.exceptions import EquipmentConfigError, ConfigurationError
 
 
 def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=False):
-    """return the trx and SI parameters from eqpt_config for a given type_variety and mode (ie format)"""
+    """return the trx and SI parameters from eqpt_config for a given type_variety and mode (ie format)
+
+    if the type or mode do no match an existing transceiver in the library, then the function
+    raises an error if error_message is True else returns a default mode based on equipment['SI']['default']
+    If trx_mode is None (but type is valid), it returns an undetermined mode whatever the error message:
+    this is a special case for automatic mode selection.
+    """
     trx_params = {}
     default_si_data = equipment['SI']['default']
-
-    try:
-        trxs = equipment['Transceiver']
-        # if called from path_requests_run.py, trx_mode is filled with None when not specified by user
-        # if called from transmission_main.py, trx_mode is ''
-        if trx_mode is not None:
-            mode_params = next(mode for trx in trxs
-                               if trx == trx_type_variety
-                               for mode in trxs[trx].mode
-                               if mode['format'] == trx_mode)
-            trx_params = {**mode_params}
-            # sanity check: spacing baudrate must be smaller than min spacing
-            if trx_params['baud_rate'] > trx_params['min_spacing']:
-                raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transponder "{trx_type_variety}"'
-                                           + f' mode "{trx_params["format"]}" has baud rate'
-                                           + f' {trx_params["baud_rate"] * 1e-9:.3f} GHz greater than min_spacing'
-                                           + f' {trx_params["min_spacing"] * 1e-9:.3f}.')
-            trx_params['equalization_offset_db'] = trx_params.get('equalization_offset_db', 0)
-        else:
-            mode_params = {"format": "undetermined",
+    # default transponder characteristics
+    # mainly used with transmission_main_example.py
+    default_trx_params = {
+        'f_min': default_si_data.f_min,
+        'f_max': default_si_data.f_max,
+        'baud_rate': default_si_data.baud_rate,
+        'spacing': default_si_data.spacing,
+        'OSNR': None,
+        'penalties': {},
+        'bit_rate': None,
+        'cost': None,
+        'roll_off': default_si_data.roll_off,
+        'tx_osnr': default_si_data.tx_osnr,
+        'min_spacing': None,
+        'equalization_offset_db': 0
+    }
+    # Undetermined transponder characteristics
+    # mainly used with path_request_run.py for the automatic mode computation case
+    undetermined_trx_params = {
+        "format": "undetermined",
         "baud_rate": None,
         "OSNR": None,
         "penalties": None,
@@ -44,34 +52,81 @@ def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=F
         "tx_osnr": None,
         "min_spacing": None,
         "cost": None,
-                           "equalization_offset_db": 0}
-            trx_params = {**mode_params}
-        trx_params['f_min'] = equipment['Transceiver'][trx_type_variety].frequency['min']
-        trx_params['f_max'] = equipment['Transceiver'][trx_type_variety].frequency['max']
-
-        # TODO: novel automatic feature maybe unwanted if spacing is specified
-        # trx_params['spacing'] = _automatic_spacing(trx_params['baud_rate'])
-        # temp = trx_params['spacing']
-        # print(f'spacing {temp}')
-    except StopIteration:
-        if error_message:
-            raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" with mode "{trx_mode}" in equipment library')
-        else:
-            # default transponder charcteristics
-            # mainly used with transmission_main_example.py
-            trx_params['f_min'] = default_si_data.f_min
-            trx_params['f_max'] = default_si_data.f_max
-            trx_params['baud_rate'] = default_si_data.baud_rate
-            trx_params['spacing'] = default_si_data.spacing
-            trx_params['OSNR'] = None
-            trx_params['penalties'] = {}
-            trx_params['bit_rate'] = None
-            trx_params['cost'] = None
-            trx_params['roll_off'] = default_si_data.roll_off
-            trx_params['tx_osnr'] = default_si_data.tx_osnr
-            trx_params['min_spacing'] = None
-            trx_params['equalization_offset_db'] = 0
-
-    trx_params['power'] = db2lin(default_si_data.power_dbm) * 1e-3
+        "equalization_offset_db": 0
+    }
 
+    trxs = equipment['Transceiver']
+    if trx_type_variety in trxs:
+        modes = {mode['format']: mode for mode in trxs[trx_type_variety].mode}
+        trx_frequencies = {'f_min': trxs[trx_type_variety].frequency['min'],
+                           'f_max': trxs[trx_type_variety].frequency['max']}
+        if trx_mode in modes:
+            # if called from transmission_main.py, trx_mode is ''
+            trx_params = {**modes[trx_mode], **trx_frequencies}
+            if trx_params['baud_rate'] > trx_params['min_spacing']:
+                # sanity check: baudrate must be smaller than min spacing
+                raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transponder "{trx_type_variety}" '
+                                           + f'mode "{trx_params["format"]}" has baud rate '
+                                           + f'{trx_params["baud_rate"] * 1e-9:.2f} GHz greater than min_spacing '
+                                           + f'{trx_params["min_spacing"] * 1e-9:.2f}.')
+            trx_params['equalization_offset_db'] = trx_params.get('equalization_offset_db', 0)
             return trx_params
+        if trx_mode is None:
+            # if called from path_requests_run.py, trx_mode is filled with None when not specified by user
+            trx_params = {**undetermined_trx_params, **trx_frequencies}
+            return trx_params
+    if trx_type_variety in trxs and error_message:
+        raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" with mode "{trx_mode}" '
+                                   + 'in equipment library')
+    if error_message:
+        raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" in equipment library')
+
+    trx_params = {**default_trx_params}
+    return trx_params
+
+
+def find_type_variety(amps: List[str], equipment: dict) -> str:
+    """Returns the multiband type_variety associated with a list of single band type_varieties
+    Args:
+    amps (List[str]): A list of single band type_varieties.
+    equipment (dict): A dictionary containing equipment information.
+
+    Returns:
+    str: an amplifier type variety
+    """
+    listes = find_type_varieties(amps, equipment)
+
+    _found_type = list(reduce(lambda x, y: set(x) & set(y), listes))
+    # Given a list of single band amplifiers, find the multiband amplifier whose multi_band group
+    # matches. For example, if amps list contains ["a1_LBAND", "a2_CBAND"], with a1.multi_band = [a1_LBAND, a1_CBAND]
+    # and a2.multi_band = [a1_LBAND, a2_CBAND], then:
+    # possible_type_varieties = {"a1_LBAND": ["a1", "a2"], "a2_CBAND": ["a2"]}
+    # listes = [["a1", "a2"],  ["a2"]]
+    # and _found_type = [a2]
+    if not _found_type:
+        msg = f'{amps} amps do not belong to the same amp type {listes}'
+        raise ConfigurationError(msg)
+    return _found_type[0]
+
+
+def find_type_varieties(amps: List[str], equipment: dict) -> List[List[str]]:
+    """Returns the multiband list of type_varieties associated with a list of single band type_varieties
+    Args:
+    amps (List[str]): A list of single band type_varieties.
+    equipment (dict): A dictionary containing equipment information.
+
+    Returns:
+    List[List[str]]: A list of lists containing the multiband type_varieties
+    associated with each single band type_variety.
+    """
+    possible_type_varieties = defaultdict(list)
+    for amp_name, amp in equipment['Edfa'].items():
+        if amp.multi_band is not None:
+            for elem in amp.multi_band:
+                # possible_type_varieties stores the list of multiband amp names that list this elem as
+                # a possible amplifier of the multiband group. For example, if "std_medium_gain_multiband"
+                # and "std_medium_gain_multiband_new" contain "std_medium_gain_C" in their "multi_band" list, then:
+                # possible_type_varieties["std_medium_gain_C"] =
+                # ["std_medium_gain_multiband", "std_medium_gain_multiband_new"]
+                possible_type_varieties[elem].append(amp_name)
+    return [possible_type_varieties[a] for a in amps]

gnpy/core/info.py

@@ -11,7 +11,7 @@ This module contains classes for modelling :class:`SpectralInformation`.
 from __future__ import annotations
 from collections import namedtuple
 from collections.abc import Iterable
-from typing import Union
+from typing import Union, List
 from dataclasses import dataclass
 from numpy import argsort, mean, array, append, ones, ceil, any, zeros, outer, full, ndarray, asarray
 
@@ -45,15 +45,6 @@ class Channel(
     """
 
 
-class Pref(namedtuple('Pref', 'p_span0, p_spani, ref_carrier')):
-    """noiseless reference power in dBm:
-
-    p_span0: inital target carrier power for a reference channel defined by user
-    p_spani: carrier power after element i for a reference channel defined by user
-    ref_carrier records the baud rate of the reference channel
-    """
-
-
 class SpectralInformation(object):
     """Class containing the parameters of the entire WDM comb.
 
@@ -61,7 +52,7 @@ class SpectralInformation(object):
 
     def __init__(self, frequency: array, baud_rate: array, slot_width: array, signal: array, nli: array, ase: array,
                  roll_off: array, chromatic_dispersion: array, pmd: array, pdl: array, latency: array,
-                 delta_pdb_per_channel: array, tx_osnr: array, ref_power: Pref, label: array):
+                 delta_pdb_per_channel: array, tx_osnr: array, tx_power: array, label: array):
         indices = argsort(frequency)
         self._frequency = frequency[indices]
         self._df = outer(ones(frequency.shape), frequency) - outer(frequency, ones(frequency.shape))
@@ -89,18 +80,9 @@ class SpectralInformation(object):
         self._latency = latency[indices]
         self._delta_pdb_per_channel = delta_pdb_per_channel[indices]
         self._tx_osnr = tx_osnr[indices]
-        self._pref = ref_power
+        self._tx_power = tx_power[indices]
         self._label = label[indices]
 
-    @property
-    def pref(self):
-        """Instance of gnpy.info.Pref"""
-        return self._pref
-
-    @pref.setter
-    def pref(self, pref: Pref):
-        self._pref = pref
-
     @property
     def frequency(self):
         return self._frequency
@@ -207,6 +189,14 @@ class SpectralInformation(object):
     def tx_osnr(self, tx_osnr):
         self._tx_osnr = tx_osnr
 
+    @property
+    def tx_power(self):
+        return self._tx_power
+
+    @tx_power.setter
+    def tx_power(self, tx_power):
+        self._tx_power = tx_power
+
     @property
     def channel_number(self):
         return self._channel_number
@@ -237,12 +227,6 @@ class SpectralInformation(object):
 
     def __add__(self, other: SpectralInformation):
         try:
-            # Note that pref.p_spanx from "self" and "other" must be identical for a given simulation (correspond to the
-            # the simulation setup):
-            # - for a given simulation there is only one design (one p_span0),
-            # - and p_spani is the propagation result of p_span0 so there should not be different p_spani either.
-            if (self.pref.p_span0 != other.pref.p_span0) or (self.pref.p_spani != other.pref.p_spani):
-                raise SpectrumError('reference powers of the spectrum are not identical')
             return SpectralInformation(frequency=append(self.frequency, other.frequency),
                                        slot_width=append(self.slot_width, other.slot_width),
                                        signal=append(self.signal, other.signal), nli=append(self.nli, other.nli),
@@ -257,13 +241,12 @@ class SpectralInformation(object):
                                        delta_pdb_per_channel=append(self.delta_pdb_per_channel,
                                                                     other.delta_pdb_per_channel),
                                        tx_osnr=append(self.tx_osnr, other.tx_osnr),
-                                       ref_power=Pref(self.pref.p_span0, self.pref.p_spani, self.pref.ref_carrier),
+                                       tx_power=append(self.tx_power, other.tx_power),
                                        label=append(self.label, other.label))
         except SpectrumError:
             raise SpectrumError('Spectra cannot be summed: channels overlapping.')
 
-
-    def _replace(self, carriers, pref):
+    def _replace(self, carriers):
         self.chromatic_dispersion = array([c.chromatic_dispersion for c in carriers])
         self.pmd = array([c.pmd for c in carriers])
         self.pdl = array([c.pdl for c in carriers])
@@ -271,7 +254,6 @@ class SpectralInformation(object):
         self.signal = array([c.power.signal for c in carriers])
         self.nli = array([c.power.nli for c in carriers])
         self.ase = array([c.power.ase for c in carriers])
-        self.pref = pref
         return self
 
 
@@ -279,6 +261,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
                                           signal: Union[float, ndarray, Iterable],
                                           baud_rate: Union[float, ndarray, Iterable],
                                           tx_osnr: Union[float, ndarray, Iterable],
+                                          tx_power: Union[float, ndarray, Iterable] = None,
                                           delta_pdb_per_channel: Union[float, ndarray, Iterable] = 0.,
                                           slot_width: Union[float, ndarray, Iterable] = None,
                                           roll_off: Union[float, ndarray, Iterable] = 0.,
@@ -286,7 +269,6 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
                                           pmd: Union[float, ndarray, Iterable] = 0.,
                                           pdl: Union[float, ndarray, Iterable] = 0.,
                                           latency: Union[float, ndarray, Iterable] = 0.,
-                                          ref_power: Pref = None,
                                           label: Union[str, ndarray, Iterable] = None):
     """This is just a wrapper around the SpectralInformation.__init__() that simplifies the creation of
     a non-uniform spectral information with NLI and ASE powers set to zero."""
@@ -306,6 +288,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
         ase = zeros(number_of_channels)
         delta_pdb_per_channel = full(number_of_channels, delta_pdb_per_channel)
         tx_osnr = full(number_of_channels, tx_osnr)
+        tx_power = full(number_of_channels, tx_power)
         label = full(number_of_channels, label)
         return SpectralInformation(frequency=frequency, slot_width=slot_width,
                                    signal=signal, nli=nli, ase=ase,
@@ -313,8 +296,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
                                    chromatic_dispersion=chromatic_dispersion,
                                    pmd=pmd, pdl=pdl, latency=latency,
                                    delta_pdb_per_channel=delta_pdb_per_channel,
-                                   tx_osnr=tx_osnr,
-                                   ref_power=ref_power, label=label)
+                                   tx_osnr=tx_osnr, tx_power=tx_power, label=label)
     except ValueError as e:
         if 'could not broadcast' in str(e):
             raise SpectrumError('Dimension mismatch in input fields.')
@@ -322,55 +304,96 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
             raise
 
 
-def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, power, spacing, tx_osnr, delta_pdb=0,
-                                      ref_carrier=None):
+def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, spacing, tx_osnr, tx_power,
+                                      delta_pdb=0):
     """Creates a fixed slot width spectral information with flat power.
     all arguments are scalar values"""
     number_of_channels = automatic_nch(f_min, f_max, spacing)
     frequency = [(f_min + spacing * i) for i in range(1, number_of_channels + 1)]
-    p_span0 = watt2dbm(power)
-    p_spani = watt2dbm(power)
     delta_pdb_per_channel = delta_pdb * ones(number_of_channels)
     label = [f'{baud_rate * 1e-9 :.2f}G' for i in range(number_of_channels)]
-    return create_arbitrary_spectral_information(frequency, slot_width=spacing, signal=power, baud_rate=baud_rate,
+    return create_arbitrary_spectral_information(frequency, slot_width=spacing, signal=tx_power, baud_rate=baud_rate,
                                                  roll_off=roll_off, delta_pdb_per_channel=delta_pdb_per_channel,
-                                                 tx_osnr=tx_osnr,
-                                                 ref_power=Pref(p_span0=p_span0, p_spani=p_spani,
-                                                                ref_carrier=ref_carrier),
-                                                 label=label)
+                                                 tx_osnr=tx_osnr, tx_power=tx_power, label=label)
 
 
-def carriers_to_spectral_information(initial_spectrum: dict[float, Carrier], power: float,
-                                     ref_carrier: ReferenceCarrier) -> SpectralInformation:
+def is_in_band(frequency: float, band: dict) -> bool:
+    """band has {"f_min": value, "f_max": value} format
+    """
+    if frequency >= band['f_min'] and frequency <= band['f_max']:
+        return True
+    return False
+
+
+def demuxed_spectral_information(input_si: SpectralInformation, band: dict) -> SpectralInformation:
+    """extract a si based on band
+    """
+    filtered_indices = [i for i, f in enumerate(input_si.frequency)
+                        if is_in_band(f - input_si.slot_width[i] / 2, band)
+                        and is_in_band(f + input_si.slot_width[i] / 2, band)]
+    if filtered_indices:
+        frequency = input_si.frequency[filtered_indices]
+        baud_rate = input_si.baud_rate[filtered_indices]
+        slot_width = input_si.slot_width[filtered_indices]
+        signal = input_si.signal[filtered_indices]
+        nli = input_si.nli[filtered_indices]
+        ase = input_si.ase[filtered_indices]
+        roll_off = input_si.roll_off[filtered_indices]
+        chromatic_dispersion = input_si.chromatic_dispersion[filtered_indices]
+        pmd = input_si.pmd[filtered_indices]
+        pdl = input_si.pdl[filtered_indices]
+        latency = input_si.latency[filtered_indices]
+        delta_pdb_per_channel = input_si.delta_pdb_per_channel[filtered_indices]
+        tx_osnr = input_si.tx_osnr[filtered_indices]
+        tx_power = input_si.tx_power[filtered_indices]
+        label = input_si.label[filtered_indices]
+
+        return SpectralInformation(frequency=frequency, baud_rate=baud_rate, slot_width=slot_width, signal=signal,
+                                   nli=nli, ase=ase, roll_off=roll_off, chromatic_dispersion=chromatic_dispersion,
+                                   pmd=pmd, pdl=pdl, latency=latency, delta_pdb_per_channel=delta_pdb_per_channel,
+                                   tx_osnr=tx_osnr, tx_power=tx_power, label=label)
+    return None
+
+
+def muxed_spectral_information(input_si_list: List[SpectralInformation]) -> SpectralInformation:
+    """return the assembled spectrum
+    """
+    if input_si_list and len(input_si_list) > 1:
+        si = input_si_list[0] + muxed_spectral_information(input_si_list[1:])
+        return si
+    elif input_si_list and len(input_si_list) == 1:
+        return input_si_list[0]
+    else:
+        raise ValueError('liste vide')
+
+
+def carriers_to_spectral_information(initial_spectrum: dict[float, Carrier],
+                                     power: float) -> SpectralInformation:
     """Initial spectrum is a dict with key = carrier frequency, and value a Carrier object.
     :param initial_spectrum: indexed by frequency in Hz, with power offset (delta_pdb), baudrate, slot width,
-    tx_osnr and roll off.
+    tx_osnr, tx_power and roll off.
     :param power: power of the request
-    :param ref_carrier: reference carrier (baudrate) used for the reference channel
     """
     frequency = list(initial_spectrum.keys())
-    signal = [power * db2lin(c.delta_pdb) for c in initial_spectrum.values()]
+    signal = [c.tx_power for c in initial_spectrum.values()]
     roll_off = [c.roll_off for c in initial_spectrum.values()]
     baud_rate = [c.baud_rate for c in initial_spectrum.values()]
     delta_pdb_per_channel = [c.delta_pdb for c in initial_spectrum.values()]
     slot_width = [c.slot_width for c in initial_spectrum.values()]
     tx_osnr = [c.tx_osnr for c in initial_spectrum.values()]
+    tx_power = [c.tx_power for c in initial_spectrum.values()]
     label = [c.label for c in initial_spectrum.values()]
-    p_span0 = watt2dbm(power)
-    p_spani = watt2dbm(power)
     return create_arbitrary_spectral_information(frequency=frequency, signal=signal, baud_rate=baud_rate,
                                                  slot_width=slot_width, roll_off=roll_off,
                                                  delta_pdb_per_channel=delta_pdb_per_channel, tx_osnr=tx_osnr,
-                                                 ref_power=Pref(p_span0=p_span0, p_spani=p_spani,
-                                                                ref_carrier=ref_carrier),
-                                                 label=label)
+                                                 tx_power=tx_power, label=label)
 
 
 @dataclass
 class Carrier:
     """One channel in the initial mixed-type spectrum definition, each type being defined by
     its delta_pdb (power offset with respect to reference power), baud rate, slot_width, roll_off
-    and tx_osnr. delta_pdb offset is applied to target power out of Roadm.
+    tx_power, and tx_osnr. delta_pdb offset is applied to target power out of Roadm.
     Label is used to group carriers which belong to the same partition when printing results.
     """
     delta_pdb: float
@@ -378,6 +401,7 @@ class Carrier:
     slot_width: float
     roll_off: float
     tx_osnr: float
+    tx_power: float
     label: str
 
 
@@ -387,7 +411,7 @@ class ReferenceCarrier:
     constant power spectral density (PSD) equalization is set. Reference channel is the type that has been defined
     in SI block and used for the initial design of the network.
     Computing the power out of ROADM for the reference channel is required to correctly compute the loss
-    experienced by p_span_i in Roadm element.
+    experienced by reference channel in Roadm element.
 
     Baud rate is required to find the target power in constant PSD: power = PSD_target * baud_rate.
     For example, if target PSD is 3.125e4mW/GHz and reference carrier type a 32 GBaud channel then
@@ -398,7 +422,7 @@ class ReferenceCarrier:
     For example, if target PSW is 2e4mW/GHz and reference carrier type a 32 GBaud channel in a 50GHz slot width then
     output power should be -20 dBm and for a 64 GBaud channel  in a 75 GHz slot width, power target would be -18.24 dBm.
 
-    Other attributes (like slot_width or roll-off) may be added there for future equalization purpose.
+    Other attributes (like roll-off) may be added there for future equalization purpose.
     """
     baud_rate: float
     slot_width: float

gnpy/core/parameters.py

@@ -8,7 +8,8 @@ gnpy.core.parameters
 This module contains all parameters to configure standard network elements.
 """
 from collections import namedtuple
-
+from copy import deepcopy
+from dataclasses import dataclass
 from scipy.constants import c, pi
 from numpy import asarray, array, exp, sqrt, log, outer, ones, squeeze, append, flip, linspace, full
 
@@ -35,32 +36,54 @@ class PumpParams(Parameters):
 
 
 class RamanParams(Parameters):
-    def __init__(self, flag=False, result_spatial_resolution=10e3, solver_spatial_resolution=50):
+    def __init__(self, flag=False, method='perturbative', order=2, result_spatial_resolution=10e3,
+                 solver_spatial_resolution=10e3):
         """Simulation parameters used within the Raman Solver
 
         :params flag: boolean for enabling/disable the evaluation of the Raman power profile in frequency and position
+        :params method: Raman solver method
+        :params order: solution order for perturbative method
         :params result_spatial_resolution: spatial resolution of the evaluated Raman power profile
         :params solver_spatial_resolution: spatial step for the iterative solution of the first order ode
         """
         self.flag = flag
+        self.method = method
+        self.order = order
         self.result_spatial_resolution = result_spatial_resolution  # [m]
         self.solver_spatial_resolution = solver_spatial_resolution  # [m]
 
+    def to_json(self):
+        return {"flag": self.flag,
+                "method": self.method,
+                "order": self.order,
+                "result_spatial_resolution": self.result_spatial_resolution,
+                "solver_spatial_resolution": self.solver_spatial_resolution}
+
 
 class NLIParams(Parameters):
-    def __init__(self, method='gn_model_analytic', dispersion_tolerance=1, phase_shift_tolerance=0.1,
-                 computed_channels=None):
+    def __init__(self, method='gn_model_analytic', dispersion_tolerance=4, phase_shift_tolerance=0.1,
+                 computed_channels=None, computed_number_of_channels=None):
         """Simulation parameters used within the Nli Solver
 
         :params method: formula for NLI calculation
         :params dispersion_tolerance: tuning parameter for ggn model solution
         :params phase_shift_tolerance: tuning parameter for ggn model solution
         :params computed_channels: the NLI is evaluated for these channels and extrapolated for the others
+        :params computed_number_of_channels: the NLI is evaluated for this number of channels equally distributed
+        in the spectrum and extrapolated for the others
         """
         self.method = method.lower()
         self.dispersion_tolerance = dispersion_tolerance
         self.phase_shift_tolerance = phase_shift_tolerance
         self.computed_channels = computed_channels
+        self.computed_number_of_channels = computed_number_of_channels
+
+    def to_json(self):
+        return {"method": self.method,
+                "dispersion_tolerance": self.dispersion_tolerance,
+                "phase_shift_tolerance": self.phase_shift_tolerance,
+                "computed_channels": self.computed_channels,
+                "computed_number_of_channels": self.computed_number_of_channels}
 
 
 class SimParams(Parameters):
@@ -98,8 +121,68 @@ class RoadmParams(Parameters):
             self.pmd = kwargs['pmd']
             self.pdl = kwargs['pdl']
             self.restrictions = kwargs['restrictions']
+            self.roadm_path_impairments = self.get_roadm_path_impairments(kwargs['roadm-path-impairments'])
         except KeyError as e:
             raise ParametersError(f'ROADM configurations must include {e}. Configuration: {kwargs}')
+        self.per_degree_impairments = kwargs.get('per_degree_impairments', [])
+        self.design_bands = kwargs.get('design_bands', [])
+        self.per_degree_design_bands = kwargs.get('per_degree_design_bands', {})
+
+    def get_roadm_path_impairments(self, path_impairments_list):
+        """Get the ROADM list of profiles for impairments definition
+
+        transform the ietf model into gnpy internal model: add a path-type in the attributes
+        """
+        if not path_impairments_list:
+            return {}
+        authorized_path_types = {
+            'roadm-express-path': 'express',
+            'roadm-add-path': 'add',
+            'roadm-drop-path': 'drop',
+        }
+        roadm_path_impairments = {}
+        for path_impairment in path_impairments_list:
+            index = path_impairment['roadm-path-impairments-id']
+            path_type = next(key for key in path_impairment if key in authorized_path_types.keys())
+            impairment_dict = {'path-type': authorized_path_types[path_type], 'impairment': path_impairment[path_type]}
+            roadm_path_impairments[index] = RoadmImpairment(impairment_dict)
+        return roadm_path_impairments
+
+
+class RoadmPath:
+    def __init__(self, from_degree, to_degree, path_type, impairment_id=None, impairment=None):
+        """Records roadm internal paths, types and impairment
+
+        path_type must be in "express", "add", "drop"
+        impairment_id must be one of the id detailed in equipement
+        """
+        self.from_degree = from_degree
+        self.to_degree = to_degree
+        self.path_type = path_type
+        self.impairment_id = impairment_id
+        self.impairment = impairment
+
+
+class RoadmImpairment:
+    """Generic definition of impairments for express, add and drop"""
+    default_values = {
+        'roadm-pmd': None,
+        'roadm-cd': None,
+        'roadm-pdl': None,
+        'roadm-inband-crosstalk': None,
+        'roadm-maxloss': 0,
+        'roadm-osnr': None,
+        'roadm-pmax': None,
+        'roadm-noise-figure': None,
+        'minloss': None,
+        'typloss': None,
+        'pmin': None,
+        'ptyp': None
+    }
+
+    def __init__(self, params):
+        self.path_type = params.get('path-type')
+        self.impairments = params['impairment']
 
 
 class FusedParams(Parameters):
@@ -108,7 +191,33 @@ class FusedParams(Parameters):
 
 
 DEFAULT_RAMAN_COEFFICIENT = {
-    # SSMF Raman coefficient profile normalized with respect to the effective area overlap (g0 * A_eff(f_probe, f_pump))
+    # SSMF Raman coefficient profile in terms of mode intensity (g0 * A_ff_overlap)
+    'gamma_raman': array(
+        [0.0, 8.524419934705497e-16, 2.643567866245371e-15, 4.410548410941305e-15, 6.153422961291078e-15,
+         7.484924703044943e-15, 8.452060808349209e-15, 9.101549322698156e-15, 9.57837595158966e-15,
+         1.0008642675474562e-14, 1.0865773569905647e-14, 1.1300776305865833e-14, 1.2143238647099625e-14,
+         1.3231065750676068e-14, 1.4624900971525384e-14, 1.6013330554840492e-14, 1.7458119359310242e-14,
+         1.9320241330434762e-14, 2.1720395392873534e-14, 2.4137337406734775e-14, 2.628163218460466e-14,
+         2.8041019963285974e-14, 2.9723155447089933e-14, 3.129353531005888e-14, 3.251796163324624e-14,
+         3.3198839487612773e-14, 3.329527690685666e-14, 3.313155691238456e-14, 3.289013852154548e-14,
+         3.2458917188506916e-14, 3.060684277937575e-14, 3.2660349473783173e-14, 2.957419109657689e-14,
+         2.518894321396672e-14, 1.734560485857344e-14, 9.902860761605233e-15, 7.219176385099358e-15,
+         6.079565990401311e-15, 5.828373065963427e-15, 7.20580801091692e-15, 7.561924351387493e-15,
+         7.621152352332206e-15, 6.8859886780643254e-15, 5.629181047471162e-15, 3.679727598966185e-15,
+         2.7555869742500355e-15, 2.4810133942597675e-15, 2.2160080532403624e-15, 2.1440626024765557e-15,
+         2.33873070799544e-15, 2.557317929858713e-15, 3.039839048226572e-15, 4.8337165515610065e-15,
+         5.4647431818257436e-15, 5.229187813711269e-15, 4.510768525811313e-15, 3.3213473130607794e-15,
+         2.2602577027996455e-15, 1.969576495866441e-15, 1.5179853954188527e-15, 1.2953988551200156e-15,
+         1.1304672156251838e-15, 9.10004390675213e-16, 8.432919922183503e-16, 7.849224069008326e-16,
+         7.827568196032024e-16, 9.000514440646232e-16, 1.3025926460013665e-15, 1.5444108938497558e-15,
+         1.8795594063060786e-15, 1.7796130169921014e-15, 1.5938159865046653e-15, 1.1585522355108287e-15,
+         8.507044444633358e-16, 7.625404663756823e-16, 8.14510750925789e-16, 9.047944693473188e-16,
+         9.636431901702084e-16, 9.298633899602105e-16, 8.349739503637023e-16, 7.482901278066085e-16,
+         6.240794767134268e-16, 5.00652535687506e-16, 3.553373263685851e-16, 2.0344217706119682e-16,
+         1.4267522642294203e-16, 8.980016576743517e-17, 2.9829068181832594e-17, 1.4861959129014824e-17,
+         7.404482113326137e-18]
+    ),  # m/W
+    # SSMF Raman coefficient profile
     'g0': array(
         [0.00000000e+00, 1.12351610e-05, 3.47838074e-05, 5.79356636e-05, 8.06921680e-05, 9.79845709e-05, 1.10454361e-04,
          1.18735302e-04, 1.24736889e-04, 1.30110053e-04, 1.41001273e-04, 1.46383247e-04, 1.57011792e-04, 1.70765865e-04,
@@ -123,22 +232,21 @@ DEFAULT_RAMAN_COEFFICIENT = {
          2.03744008e-05, 1.81939341e-05, 1.31862121e-05, 9.65352116e-06, 8.62698322e-06, 9.18688016e-06, 1.01737784e-05,
          1.08017817e-05, 1.03903588e-05, 9.30040333e-06, 8.30809173e-06, 6.90650401e-06, 5.52238029e-06, 3.90648708e-06,
          2.22908227e-06, 1.55796177e-06, 9.77218716e-07, 3.23477236e-07, 1.60602454e-07, 7.97306386e-08]
-    ),  # [m/W]
+    ),  # [1 / (W m)]
 
     # Note the non-uniform spacing of this range; this is required for properly capturing the Raman peak shape.
     'frequency_offset': array([
         0., 0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5, 8., 8.5, 9., 9.5, 10., 10.5, 11., 11.5,
-        12.,
-        12.5, 12.75, 13., 13.25, 13.5, 14., 14.5, 14.75, 15., 15.5, 16., 16.5, 17., 17.5, 18., 18.25, 18.5, 18.75, 19.,
-        19.5, 20., 20.5, 21., 21.5, 22., 22.5, 23., 23.5, 24., 24.5, 25., 25.5, 26., 26.5, 27., 27.5, 28., 28.5, 29.,
-        29.5,
-        30., 30.5, 31., 31.5, 32., 32.5, 33., 33.5, 34., 34.5, 35., 35.5, 36., 36.5, 37., 37.5, 38., 38.5, 39., 39.5,
-        40.,
-        40.5, 41., 41.5, 42.]
-    ) * 1e12,  # [Hz]
+        12., 12.5, 12.75, 13., 13.25, 13.5, 14., 14.5, 14.75, 15., 15.5, 16., 16.5, 17., 17.5, 18., 18.25, 18.5, 18.75,
+        19., 19.5, 20., 20.5, 21., 21.5, 22., 22.5, 23., 23.5, 24., 24.5, 25., 25.5, 26., 26.5, 27., 27.5, 28., 28.5,
+        29., 29.5, 30., 30.5, 31., 31.5, 32., 32.5, 33., 33.5, 34., 34.5, 35., 35.5, 36., 36.5, 37., 37.5, 38., 38.5,
+        39., 39.5, 40., 40.5, 41., 41.5, 42.]) * 1e12,  # [Hz]
 
     # Raman profile reference frequency
-    'reference_frequency': 206184634112792  # [Hz] (1454 nm)}
+    'reference_frequency': 206.184634112792e12,  # [Hz] (1454 nm)
+
+    # Raman profile reference effective area
+    'reference_effective_area': 75.74659443542413e-12  # [m^2] (@1454 nm)
 }
 
 
@@ -179,8 +287,8 @@ class FiberParams(Parameters):
             # Chromatic Dispersion
             if 'dispersion_per_frequency' in kwargs:
                 # Frequency-dependent dispersion
-                self._dispersion = asarray(kwargs['dispersion']['value'])  # s/m/m
-                self._f_dispersion_ref = asarray(kwargs['dispersion']['frequency'])  # Hz
+                self._dispersion = asarray(kwargs['dispersion_per_frequency']['value'])  # s/m/m
+                self._f_dispersion_ref = asarray(kwargs['dispersion_per_frequency']['frequency'])  # Hz
                 self._dispersion_slope = None
             elif 'dispersion' in kwargs:
                 # Single value dispersion
@@ -211,14 +319,21 @@ class FiberParams(Parameters):
                 pi * self._core_radius ** 2 / self._effective_area)) ** 2
 
             # Raman Gain Coefficient
-            raman_coefficient = kwargs.get('raman_coefficient', DEFAULT_RAMAN_COEFFICIENT)
-            self._g0 = asarray(raman_coefficient['g0'])
-            raman_reference_frequency = raman_coefficient['reference_frequency']
+            raman_coefficient = kwargs.get('raman_coefficient')
+            if raman_coefficient is None:
+                self._raman_reference_frequency = DEFAULT_RAMAN_COEFFICIENT['reference_frequency']
+                frequency_offset = asarray(DEFAULT_RAMAN_COEFFICIENT['frequency_offset'])
+                gamma_raman = asarray(DEFAULT_RAMAN_COEFFICIENT['gamma_raman'])
+                stokes_wave = self._raman_reference_frequency - frequency_offset
+                normalized_gamma_raman = gamma_raman / self._raman_reference_frequency  # 1 / m / W / Hz
+                self._g0 = gamma_raman / self.effective_area_overlap(stokes_wave, self._raman_reference_frequency)
+            else:
+                self._raman_reference_frequency = raman_coefficient['reference_frequency']
                 frequency_offset = asarray(raman_coefficient['frequency_offset'])
-            stokes_wave = raman_reference_frequency - frequency_offset
-            gamma_raman = self._g0 * self.effective_area_overlap(stokes_wave, raman_reference_frequency)
-            normalized_gamma_raman = gamma_raman / raman_reference_frequency  # 1 / m / W / Hz
-            self._raman_reference_frequency = raman_reference_frequency
+                stokes_wave = self._raman_reference_frequency - frequency_offset
+                self._g0 = asarray(raman_coefficient['g0'])
+                gamma_raman = self._g0 * self.effective_area_overlap(stokes_wave, self._raman_reference_frequency)
+                normalized_gamma_raman = gamma_raman / self._raman_reference_frequency  # 1 / m / W / Hz
 
             # Raman gain coefficient array of the frequency offset constructed such that positive frequency values
             # represent a positive power transfer from higher frequency and vice versa
@@ -355,6 +470,38 @@ class FiberParams(Parameters):
 
 
 class EdfaParams:
+    default_values = {
+        'f_min': None,
+        'f_max': None,
+        'multi_band': None,
+        'bands': None,
+        'type_variety': '',
+        'type_def': '',
+        'gain_flatmax': None,
+        'gain_min': None,
+        'p_max': None,
+        'nf_model': None,
+        'dual_stage_model': None,
+        'preamp_variety': None,
+        'booster_variety': None,
+        'nf_min': None,
+        'nf_max': None,
+        'nf_coef': None,
+        'nf0': None,
+        'nf_fit_coeff': None,
+        'nf_ripple': 0,
+        'dgt': None,
+        'gain_ripple': 0,
+        'tilt_ripple': 0,
+        'f_ripple_ref': None,
+        'out_voa_auto': False,
+        'allowed_for_design': False,
+        'raman': False,
+        'pmd': 0,
+        'pdl': 0,
+        'advance_configurations_from_json': None
+    }
+
     def __init__(self, **params):
         try:
             self.type_variety = params['type_variety']
@@ -363,9 +510,11 @@ class EdfaParams:
             # Bandwidth
             self.f_min = params['f_min']
             self.f_max = params['f_max']
-            self.bandwidth = self.f_max - self.f_min
-            self.f_cent = (self.f_max + self.f_min) / 2
+            self.bandwidth = self.f_max - self.f_min if self.f_max and self.f_min else None
+            self.f_cent = (self.f_max + self.f_min) / 2 if self.f_max and self.f_min else None
             self.f_ripple_ref = params['f_ripple_ref']
+            self.bands = [{'f_min': params['f_min'],
+                           'f_max': params['f_max']}]
 
             # Gain
             self.gain_flatmax = params['gain_flatmax']
@@ -452,7 +601,7 @@ class EdfaParams:
 
     def update_params(self, kwargs):
         for k, v in kwargs.items():
-            setattr(self, k, self.update_params(**v) if isinstance(v, dict) else v)
+            setattr(self, k, v)
 
 
 class EdfaOperational:
@@ -460,7 +609,7 @@ class EdfaOperational:
         'gain_target': None,
         'delta_p': None,
         'out_voa': None,
-        'tilt_target': 0
+        'tilt_target': None
     }
 
     def __init__(self, **operational):
@@ -475,3 +624,62 @@ class EdfaOperational:
         return (f'{type(self).__name__}('
                 f'gain_target={self.gain_target!r}, '
                 f'tilt_target={self.tilt_target!r})')
+
+
+class MultiBandParams:
+    default_values = {
+        'bands': [],
+        'type_variety': '',
+        'type_def': None,
+        'allowed_for_design': False
+    }
+
+    def __init__(self, **params):
+        try:
+            self.update_attr(params)
+        except KeyError as e:
+            raise ParametersError(f'Multiband configurations json must include {e}. Configuration: {params}')
+
+    def update_attr(self, kwargs):
+        clean_kwargs = {k: v for k, v in kwargs.items() if v != ''}
+        for k, v in self.default_values.items():
+            # use deepcopy to avoid sharing same object amongst all instance when v is a list or a dict!
+            if isinstance(v, (list, dict)):
+                setattr(self, k, clean_kwargs.get(k, deepcopy(v)))
+            else:
+                setattr(self, k, clean_kwargs.get(k, v))
+
+
+class TransceiverParams:
+    def __init__(self, **params):
+        self.design_bands = params.get('design_bands', [])
+        self.per_degree_design_bands = params.get('per_degree_design_bands', {})
+
+
+@dataclass
+class FrequencyBand:
+    """Frequency band
+    """
+    f_min: float
+    f_max: float
+
+
+DEFAULT_BANDS_DEFINITION = {
+    "LBAND": FrequencyBand(f_min=187e12, f_max=189e12),
+    "CBAND": FrequencyBand(f_min=191.3e12, f_max=196.0e12)
+}
+# use this definition to index amplifiers'element of a multiband amplifier.
+# this is not the design band
+
+
+def find_band_name(band: FrequencyBand) -> str:
+    """return the default band name (CBAND, LBAND, ...) that corresponds to the band frequency range
+    Use the band center frequency: if center frequency is inside the band then returns CBAND.
+    This is to flexibly encompass all kind of bands definitions.
+    returns the first matching band name.
+    """
+    for band_name, frequency_range in DEFAULT_BANDS_DEFINITION.items():
+        center_frequency = (band.f_min + band.f_max) / 2
+        if center_frequency >= frequency_range.f_min and center_frequency <= frequency_range.f_max:
+            return band_name
+    return 'unknown_band'

gnpy/core/science_utils.py

@@ -12,14 +12,14 @@ The solvers take as input instances of the spectral information, the fiber and t
 
 from numpy import interp, pi, zeros, cos, array, append, ones, exp, arange, sqrt, trapz, arcsinh, clip, abs, sum, \
     concatenate, flip, outer, inner, transpose, max, format_float_scientific, diag, sort, unique, argsort, cumprod, \
-    polyfit
+    polyfit, log, reshape, swapaxes, full, nan, cumsum
 from logging import getLogger
 from scipy.constants import k, h
 from scipy.interpolate import interp1d
-from math import isclose
+from math import isclose, factorial
 
 from gnpy.core.utils import db2lin, lin2db
-from gnpy.core.exceptions import EquipmentConfigError
+from gnpy.core.exceptions import EquipmentConfigError, ParametersError
 from gnpy.core.parameters import SimParams
 from gnpy.core.info import SpectralInformation
 
@@ -136,15 +136,17 @@ class RamanSolver:
                     co_cr = fiber.cr(co_frequency)
                     co_alpha = fiber.alpha(co_frequency)
                     co_power_profile = \
-                        RamanSolver.first_order_derivative_solution(co_power, co_alpha, co_cr, z, lumped_losses)
+                        RamanSolver.calculate_unidirectional_stimulated_raman_scattering(co_power, co_alpha, co_cr, z,
+                                                                                         lumped_losses)
                 # Counter-propagating profile initialization
                 cnt_power_profile = zeros([cnt_frequency.size, z.size])
                 if cnt_frequency.size:
                     cnt_cr = fiber.cr(cnt_frequency)
                     cnt_alpha = fiber.alpha(cnt_frequency)
-                    cnt_power_profile = \
-                        flip(RamanSolver.first_order_derivative_solution(cnt_power, cnt_alpha, cnt_cr,
-                                                                         z[-1] - flip(z), flip(lumped_losses)), axis=1)
+                    cnt_power_profile = flip(
+                        RamanSolver.calculate_unidirectional_stimulated_raman_scattering(cnt_power, cnt_alpha, cnt_cr,
+                                                                                         z[-1] - flip(z),
+                                                                                         flip(lumped_losses)), axis=1)
                 # Co-propagating and Counter-propagating Profile Computation
                 if co_frequency.size and cnt_frequency.size:
                     co_power_profile, cnt_power_profile = \
@@ -163,8 +165,9 @@ class RamanSolver:
                 alpha = fiber.alpha(spectral_info.frequency)
                 cr = fiber.cr(spectral_info.frequency)
                 # Power profile
-                power_profile = \
-                    RamanSolver.first_order_derivative_solution(spectral_info.signal, alpha, cr, z, lumped_losses)
+                power_profile = (
+                    RamanSolver.calculate_unidirectional_stimulated_raman_scattering(spectral_info.signal, alpha, cr, z,
+                                                                                     lumped_losses))
                 # Loss profile
                 loss_profile = power_profile / outer(spectral_info.signal, ones(z.size))
                 frequency = spectral_info.frequency
@@ -200,8 +203,8 @@ class RamanSolver:
         return ase
 
     @staticmethod
-    def first_order_derivative_solution(power_in, alpha, cr, z, lumped_losses):
-        """Solves the Raman first order derivative equation
+    def calculate_unidirectional_stimulated_raman_scattering(power_in, alpha, cr, z, lumped_losses):
+        """Solves the Raman equation
 
         :param power_in: launch power array
         :param alpha: loss coefficient array
@@ -210,18 +213,66 @@ class RamanSolver:
         :param lumped_losses: concentrated losses array along the fiber span
         :return: power profile matrix
         """
+        if sim_params.raman_params.method == 'perturbative':
+            if sim_params.raman_params.order > 4:
+                raise ValueError(f'Order {sim_params.raman_params.order} not implemented in Raman Solver.')
+            z_lumped_losses = append(z[lumped_losses != 1], z[-1])
+            llumped_losses = append(1, lumped_losses[lumped_losses != 1])
+            power = outer(power_in, ones(z.size))
+            last_position = 0
+            z_indices = arange(0, z.size)
+
+            for z_lumped_loss, lumped_loss in zip(z_lumped_losses, llumped_losses):
+                if last_position < z[-1]:
+                    interval = z_indices[(z >= last_position) * (z <= z_lumped_loss) == 1]
+                    z_interval = z[interval] - last_position
+                    dz = z_interval[1:] - z_interval[:-1]
+                    last_position = z[interval][-1]
+                    p0 = power_in * lumped_loss
+                    power_interval = outer(p0, ones(z_interval.size))
+                    alphaz = outer(alpha, z_interval)
+                    expz = exp(- alphaz)
+                    eff_length = 1 / outer(alpha, ones(z_interval.size)) * (1 - expz)
+                    crpz = transpose(ones([z_interval.size, cr.shape[0], cr.shape[1]]) * cr * p0, (1, 2, 0))
+                    exponent = - alphaz
+                    if sim_params.raman_params.order >= 1:
+                        gamma1 = sum(crpz * eff_length, 1)
+                        exponent += gamma1
+                    if sim_params.raman_params.order >= 2:
+                        z_integrand = expz * gamma1
+                        z_integral = cumsum((z_integrand[:, :-1] + z_integrand[:, 1:]) / 2 * dz, 1)
+                        gamma2 = zeros(gamma1.shape)
+                        gamma2[:, 1:] = sum(crpz[:, :, 1:] * z_integral, 1)
+                        exponent += gamma2
+                    if sim_params.raman_params.order >= 3:
+                        z_integrand = expz * (gamma2 + 1/2 * gamma1**2)
+                        z_integral = cumsum((z_integrand[:, :-1] + z_integrand[:, 1:]) / 2 * dz, 1)
+                        gamma3 = zeros(gamma1.shape)
+                        gamma3[:, 1:] = sum(crpz[:, :, 1:] * z_integral, 1)
+                        exponent += gamma3
+                    if sim_params.raman_params.order >= 4:
+                        z_integrand = expz * (gamma3 + gamma1 * gamma2 + 1/factorial(3) * gamma1**3)
+                        z_integral = cumsum((z_integrand[:, :-1] + z_integrand[:, 1:]) / 2 * dz, 1)
+                        gamma4 = zeros(gamma1.shape)
+                        gamma4[:, 1:] = sum(crpz[:, :, 1:] * z_integral, 1)
+                        exponent += gamma4
+                    power_interval *= exp(exponent)
+                    power[:, interval[1:]] = power_interval[:, 1:]
+                    power_in = power_interval[:, -1]
+        elif sim_params.raman_params.method == 'numerical':
             dz = z[1:] - z[:-1]
             power = outer(power_in, ones(z.size))
             for i in range(1, z.size):
-            power[:, i] = \
-                power[:, i - 1] * (1 + (- alpha + sum(cr * power[:, i - 1], 1)) * dz[i - 1]) * lumped_losses[i - 1]
+                power[:, i] = (power[:, i - 1] * (1 + (- alpha + sum(cr * power[:, i - 1], 1)) * dz[i - 1]) *
+                               lumped_losses[i - 1])
+        else:
+            raise ValueError(f'Method {sim_params.raman_params.method} not implemented in Raman Solver.')
         return power
 
     @staticmethod
     def iterative_algorithm(co_initial_guess_power, cnt_initial_guess_power, co_frequency, cnt_frequency, z, fiber,
                             lumped_losses):
-        """Solves the Raman first order derivative equation in case of both co- and counter-propagating
-        frequencies
+        """Solves the Raman equation in case of both co- and counter-propagating frequencies
 
         :param co_initial_guess_power: co-propagationg Raman first order derivative equation solution
         :param cnt_initial_guess_power: counter-propagationg Raman first order derivative equation solution
@@ -276,6 +327,7 @@ class NliSolver:
     List of implemented methods:
     'gn_model_analytic': eq. 120 from arXiv:1209.0394
     'ggn_spectrally_separated': eq. 21 from arXiv: 1710.02225
+    'ggn_approx': eq. 24-25 jlt:9741324
     """
 
     SPM_WEIGHT = (16.0 / 27.0)
@@ -305,6 +357,10 @@ class NliSolver:
         elif 'ggn_spectrally_separated' in sim_params.nli_params.method:
             if sim_params.nli_params.computed_channels is not None:
                 cut_indices = array(sim_params.nli_params.computed_channels) - 1
+            elif sim_params.nli_params.computed_number_of_channels is not None:
+                nb_ch_computed = sim_params.nli_params.computed_number_of_channels
+                nb_ch = len(spectral_info.channel_number)
+                cut_indices = array([round(i * (nb_ch - 1) / (nb_ch_computed - 1)) for i in range(0, nb_ch_computed)])
             else:
                 cut_indices = array(spectral_info.channel_number) - 1
 
@@ -320,6 +376,28 @@ class NliSolver:
             g_nli = sum(g_nli, 1)
             g_nli = interp(spectral_info.frequency, cut_frequency, g_nli)
             nli = spectral_info.baud_rate * g_nli  # Local white noise
+        elif 'ggn_approx' in sim_params.nli_params.method:
+            if sim_params.nli_params.computed_channels is not None:
+                cut_indices = array(sim_params.nli_params.computed_channels) - 1
+            elif sim_params.nli_params.computed_number_of_channels is not None:
+                nb_ch_computed = sim_params.nli_params.computed_number_of_channels
+                nb_ch = len(spectral_info.channel_number)
+                cut_indices = array([round(i * (nb_ch - 1) / (nb_ch_computed - 1)) for i in range(0, nb_ch_computed)])
+            else:
+                cut_indices = array(spectral_info.channel_number) - 1
+
+            eta = NliSolver._ggn_approx(cut_indices, spectral_info, fiber, srs)
+
+            # Interpolation over the channels not indicated as computed channels in simulation parameters
+            cut_power = outer(spectral_info.signal[cut_indices], ones(spectral_info.number_of_channels))
+            cut_frequency = spectral_info.frequency[cut_indices]
+            pump_power = outer(ones(cut_indices.size), spectral_info.signal)
+            cut_baud_rate = outer(spectral_info.baud_rate[cut_indices], ones(spectral_info.number_of_channels))
+
+            g_nli = eta * cut_power * pump_power ** 2 / cut_baud_rate
+            g_nli = sum(g_nli, 1)
+            g_nli = interp(spectral_info.frequency, cut_frequency, g_nli)
+            nli = spectral_info.baud_rate * g_nli  # Local white noise
         else:
             raise ValueError(f'Method {sim_params.nli_params.method} not implemented.')
 
@@ -522,6 +600,89 @@ class NliSolver:
         freq_offset_th = ((k_ref * delta_f_ref) * rs_ref * beta2_ref) / (beta2 * symbol_rate)
         return freq_offset_th
 
+    @staticmethod
+    def _ggn_approx(cut_indices, spectral_info: SpectralInformation, fiber, srs, spm_weight=SPM_WEIGHT,
+                    xpm_weight=XPM_WEIGHT):
+        """Computes the nonlinear interference power evaluated at the fiber input.
+        The method uses eq. 24-25 of https://ieeexplore.ieee.org/document/9741324
+        """
+        # Spectral Features
+        nch = spectral_info.number_of_channels
+        frequency = spectral_info.frequency
+        baud_rate = spectral_info.baud_rate
+        slot_width = spectral_info.slot_width
+        roll_off = spectral_info.roll_off
+        df = spectral_info.df + diag(full(nch, nan))
+
+        # Physical fiber parameters
+        alpha = fiber.alpha(frequency)
+        beta2 = fiber.beta2(frequency)
+        gamma = outer(fiber.gamma(frequency[cut_indices]), ones(nch))
+
+        identity = diag(ones(nch))
+        weight = spm_weight * identity + xpm_weight * (ones([nch, nch]) - identity)
+        weight = weight[cut_indices, :]
+
+        dispersion_tolerance = sim_params.nli_params.dispersion_tolerance
+        phase_shift_tolerance = sim_params.nli_params.phase_shift_tolerance
+        max_slot_width = max(slot_width)
+        max_beta2 = max(abs(beta2))
+        delta_z = sim_params.raman_params.result_spatial_resolution
+
+        # Approximation psi
+        loss_profile = srs.loss_profile[:nch]
+        z = srs.z
+        psi = NliSolver._approx_psi(df=df, frequency=frequency, beta2=beta2, baud_rate=baud_rate,
+                                    loss_profile=loss_profile, z=z)
+
+        # GGN for SPM
+        for cut_index in cut_indices:
+            dn = 0
+            cut_frequency = frequency[cut_index]
+            cut_baud_rate = baud_rate[cut_index]
+            cut_roll_off = roll_off[cut_index]
+            cut_beta2 = beta2[cut_index]
+            cut_alpha = alpha[cut_index]
+            k_tol = dispersion_tolerance * abs(cut_alpha)
+            phi_tol = phase_shift_tolerance / delta_z
+            f_cut_resolution = min(k_tol, phi_tol) / abs(max_beta2) / (4 * pi ** 2 * (1 + dn) * max_slot_width)
+            f_pump_resolution = min(k_tol, phi_tol) / abs(max_beta2) / (4 * pi ** 2 * max_slot_width)
+            psi[cut_index, cut_index] = NliSolver._generalized_psi(cut_frequency, cut_frequency, cut_baud_rate,
+                                                                   cut_roll_off, cut_frequency, cut_baud_rate,
+                                                                   cut_roll_off, f_cut_resolution, f_pump_resolution,
+                                                                   srs, cut_alpha, cut_beta2, 0, cut_frequency)
+        psi = psi[cut_indices, :]
+        cut_baud_rate = outer(baud_rate[cut_indices], ones(nch))
+        pump_baud_rate = outer(ones(cut_indices.size), baud_rate)
+
+        eta_cut_central_frequency = \
+            gamma ** 2 * weight * psi / (cut_baud_rate * pump_baud_rate ** 2)
+        eta = cut_baud_rate * eta_cut_central_frequency  # Local white noise
+
+        return eta
+
+    @staticmethod
+    def _approx_psi(df, frequency, baud_rate, beta2, loss_profile, z):
+        """Computes the approximated psi function similarly to the one used in the GN model.
+        The method uses eq. 25 of https://ieeexplore.ieee.org/document/9741324"""
+        pump_baud_rate = outer(ones(frequency.size), baud_rate)
+        cut_beta = outer(beta2, ones(frequency.size))
+        pump_beta = outer(ones(frequency.size), beta2)
+        delta_z = abs(z[:-1] - z[1:])
+
+        loss_lin = log(loss_profile)
+        pump_alpha = (loss_lin[:, 1:] - loss_lin[:, :-1]) / delta_z
+        leff = abs((loss_profile[:, 1:] - loss_profile[:, :-1]) / sqrt(abs(pump_alpha))) * pump_alpha / abs(pump_alpha)
+        leff = reshape(outer(leff, ones(z.size - 1)), newshape=[leff.shape[0], leff.shape[1], leff.shape[1]])
+        leff2 = leff * swapaxes(leff, 2, 1)
+        leff2 = sum(leff2, axis=(1, 2))
+        z_int = outer(ones(frequency.size), leff2)
+
+        delta_beta = (cut_beta + pump_beta) / 2
+        psi = z_int * pump_baud_rate / (4 * pi * abs(delta_beta * df))
+        return psi
+
+
 
 def estimate_nf_model(type_variety, gain_min, gain_max, nf_min, nf_max):
     if nf_min < -10:

gnpy/core/utils.py

@@ -9,9 +9,10 @@ This module contains utility functions that are used with gnpy.
 """
 
 from csv import writer
-from numpy import pi, cos, sqrt, log10, linspace, zeros, shape, where, logical_and, mean
+from numpy import pi, cos, sqrt, log10, linspace, zeros, shape, where, logical_and, mean, array
 from scipy import constants
 from copy import deepcopy
+from typing import List
 
 from gnpy.core.exceptions import ConfigurationError
 
@@ -213,17 +214,6 @@ wavelength2freq = constants.lambda2nu
 freq2wavelength = constants.nu2lambda
 
 
-def freq2wavelength(value):
-    """Converts frequency units to wavelength units.
-
-    >>> round(freq2wavelength(191.35e12) * 1e9, 3)
-    1566.723
-    >>> round(freq2wavelength(196.1e12) * 1e9, 3)
-    1528.773
-    """
-    return constants.c / value
-
-
 def snr_sum(snr, bw, snr_added, bw_added=12.5e9):
     snr_added = snr_added - lin2db(bw / bw_added)
     snr = -lin2db(db2lin(-snr) + db2lin(-snr_added))
@@ -452,3 +442,86 @@ def restore_order(elements, order):
     [3, 2, 7]
     """
     return [elements[i[0]] for i in sorted(enumerate(order), key=lambda x:x[1]) if elements[i[0]] is not None]
+
+
+def calculate_absolute_min_or_zero(x: array) -> array:
+    """Calculates the element-wise absolute minimum between the x and zero.
+
+    Parameters:
+    x (array): The first input array.
+
+    Returns:
+    array: The element-wise absolute minimum between x and zero.
+
+    Example:
+    >>> x = array([-1, 2, -3])
+    >>> calculate_absolute_min_or_zero(x)
+    array([1., 0., 3.])
+    """
+    return (abs(x) - x) / 2
+
+
+def nice_column_str(data: List[List[str]], max_length: int = 30, padding: int = 1) -> str:
+    """data is a list of rows, creates strings with nice alignment per colum and padding with spaces
+    letf justified
+
+    >>> table_data = [['aaa', 'b', 'c'], ['aaaaaaaa', 'bbb', 'c'], ['a', 'bbbbbbbbbb', 'c']]
+    >>> print(nice_column_str(table_data))
+    aaa      b          c 
+    aaaaaaaa bbb        c 
+    a        bbbbbbbbbb c 
+    """
+    # transpose data to determine size of columns
+    transposed_data = list(map(list, zip(*data)))
+    column_width = [max(len(word) for word in column) + padding for column in transposed_data]
+    nice_str = []
+    for row in data:
+        column = ''.join(word[0:max_length].ljust(min(width, max_length)) for width, word in zip(column_width, row))
+        nice_str.append(f'{column}')
+    return '\n'.join(nice_str)
+
+
+def find_common_range(amp_bands: List[List[dict]], default_band_f_min: float, default_band_f_max: float) \
+        -> List[dict]:
+    """Find the common frequency range of bands
+    If there are no amplifiers in the path, then use default band
+
+    >>> amp_bands = [[{'f_min': 191e12, 'f_max' : 195e12}, {'f_min': 186e12, 'f_max' : 190e12} ], \
+        [{'f_min': 185e12, 'f_max' : 189e12}, {'f_min': 192e12, 'f_max' : 196e12}], \
+        [{'f_min': 186e12, 'f_max': 193e12}]]
+    >>> find_common_range(amp_bands, 190e12, 195e12)
+    [{'f_min': 186000000000000.0, 'f_max': 189000000000000.0}, {'f_min': 192000000000000.0, 'f_max': 193000000000000.0}]
+    >>> amp_bands = [[{'f_min': 191e12, 'f_max' : 195e12}, {'f_min': 186e12, 'f_max' : 190e12} ], \
+        [{'f_min': 185e12, 'f_max' : 189e12}, {'f_min': 192e12, 'f_max' : 196e12}], \
+        [{'f_min': 186e12, 'f_max': 192e12}]]
+    >>> find_common_range(amp_bands, 190e12, 195e12)
+    [{'f_min': 186000000000000.0, 'f_max': 189000000000000.0}]
+
+    """
+    _amp_bands = [sorted(amp, key=lambda x: x['f_min']) for amp in amp_bands]
+    _temp = []
+    # remove None bands
+    for amp in _amp_bands:
+        is_band = True
+        for band in amp:
+            if not (is_band and band['f_min'] and band['f_max']):
+                is_band = False
+        if is_band:
+            _temp.append(amp)
+
+    # remove duplicate
+    unique_amp_bands = []
+    for amp in _temp:
+        if amp not in unique_amp_bands:
+            unique_amp_bands.append(amp)
+    if unique_amp_bands:
+        common_range = unique_amp_bands[0]
+    else:
+        if default_band_f_min is None or default_band_f_max is None:
+            return []
+        common_range = [{'f_min': default_band_f_min, 'f_max': default_band_f_max}]
+    for bands in unique_amp_bands:
+        common_range = [{'f_min': max(first['f_min'], second['f_min']), 'f_max': min(first['f_max'], second['f_max'])}
+                        for first in common_range for second in bands
+                        if max(first['f_min'], second['f_min']) < min(first['f_max'], second['f_max'])]
+    return sorted(common_range, key=lambda x: x['f_min'])

gnpy/example-data/default_edfa_config.json

@@ -5,6 +5,8 @@
   "gain_ripple": [
     0.0
   ],
+  "f_min": 191.275e12,
+  "f_max": 196.125e12,
   "dgt": [
     1.0,
     1.017807767853702,

gnpy/example-data/edfa_example_network.json

@@ -1,6 +1,7 @@
 {
   "network_name": "EDFA Example Network - P2P",
-    "elements": [{
+  "elements": [
+    {
       "uid": "Site_A",
       "type": "Transceiver",
       "metadata": {
@@ -61,9 +62,9 @@
         }
       }
     }
-
   ],
-    "connections": [{
+  "connections": [
+    {
       "from_node": "Site_A",
       "to_node": "Span1"
     },
@@ -75,6 +76,5 @@
       "from_node": "Edfa1",
       "to_node": "Site_B"
     }
-
   ]
 }

gnpy/example-data/eqpt_config.json

@@ -1,4 +1,6 @@
-{     "Edfa":[{
+{
+  "Edfa": [
+    {
       "type_variety": "high_detail_model_example",
       "type_def": "advanced_model",
       "gain_flatmax": 25,
@@ -7,7 +9,8 @@
       "advanced_config_from_json": "std_medium_gain_advanced_config.json",
       "out_voa_auto": false,
       "allowed_for_design": false
-            },                  {
+    },
+    {
       "type_variety": "Juniper_BoosterHG",
       "type_def": "advanced_model",
       "gain_flatmax": 25,
@@ -34,7 +37,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-8.104e-4,-6.221e-2,-5.889e-1,37.62],
+      "nf_coef": [
+        -8.104e-4,
+        -6.221e-2,
+        -5.889e-1,
+        37.62
+      ],
       "allowed_for_design": false
     },
     {
@@ -43,7 +51,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
+      ],
       "allowed_for_design": false
     },
     {
@@ -60,7 +73,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
+      ],
       "allowed_for_design": false
     },
     {
@@ -69,7 +87,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,27.99],
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        27.99
+      ],
       "allowed_for_design": false
     },
     {
@@ -177,7 +200,8 @@
       "allowed_for_design": false
     }
   ],
-      "Fiber":[{
+  "Fiber": [
+    {
       "type_variety": "SSMF",
       "dispersion": 1.67e-05,
       "effective_area": 83e-12,
@@ -196,16 +220,22 @@
       "pmd_coef": 1.265e-15
     }
   ],
-      "RamanFiber":[{
+  "RamanFiber": [
+    {
       "type_variety": "SSMF",
       "dispersion": 1.67e-05,
       "effective_area": 83e-12,
       "pmd_coef": 1.265e-15
     }
   ],
-      "Span":[{
-            "power_mode":true,
-            "delta_power_range_db": [-2,3,0.5],
+  "Span": [
+    {
+      "power_mode": true,
+      "delta_power_range_db": [
+        -2,
+        3,
+        0.5
+      ],
       "max_fiber_lineic_loss_for_raman": 0.25,
       "target_extended_gain": 2.5,
       "max_length": 150,
@@ -217,37 +247,128 @@
       "con_out": 0
     }
   ],
-      "Roadm":[{
+  "Roadm": [
+    {
       "target_pch_out_db": -20,
       "add_drop_osnr": 38,
       "pmd": 0,
       "pdl": 0,
       "restrictions": {
-                            "preamp_variety_list":[],
-                            "booster_variety_list":[]
+        "preamp_variety_list": [],
+        "booster_variety_list": []
       }
-            }],
-      "SI":[{
+    },
+    {
+      "type_variety": "roadm_type_1",
+      "target_pch_out_db": -18,
+      "add_drop_osnr": 35,
+      "pmd": 0,
+      "pdl": 0,
+      "restrictions": {
+        "preamp_variety_list": [],
+        "booster_variety_list": []
+      },
+      "roadm-path-impairments": []
+    },
+    {
+      "type_variety": "detailed_impairments",
+      "target_pch_out_db": -20,
+      "add_drop_osnr": 38,
+      "pmd": 0,
+      "pdl": 0,
+      "restrictions": {
+        "preamp_variety_list": [],
+        "booster_variety_list": []
+      },
+      "roadm-path-impairments": [
+        {
+          "roadm-path-impairments-id": 0,
+          "roadm-express-path": [
+            {
+              "frequency-range": {
+                "lower-frequency": 191.3e12,
+                "upper-frequency": 196.1e12
+              },
+              "roadm-pmd": 0,
+              "roadm-cd": 0,
+              "roadm-pdl": 0,
+              "roadm-inband-crosstalk": 0,
+              "roadm-maxloss": 16.5
+            }
+          ]
+        },
+        {
+          "roadm-path-impairments-id": 1,
+          "roadm-add-path": [
+            {
+              "frequency-range": {
+                "lower-frequency": 191.3e12,
+                "upper-frequency": 196.1e12
+              },
+              "roadm-pmd": 0,
+              "roadm-cd": 0,
+              "roadm-pdl": 0,
+              "roadm-inband-crosstalk": 0,
+              "roadm-maxloss": 11.5,
+              "roadm-pmax": 2.5,
+              "roadm-osnr": 41,
+              "roadm-noise-figure": 23
+            }
+          ]
+        },
+        {
+          "roadm-path-impairments-id": 2,
+          "roadm-drop-path": [
+            {
+              "frequency-range": {
+                "lower-frequency": 191.3e12,
+                "upper-frequency": 196.1e12
+              },
+              "roadm-pmd": 0,
+              "roadm-cd": 0,
+              "roadm-pdl": 0,
+              "roadm-inband-crosstalk": 0,
+              "roadm-maxloss": 11.5,
+              "roadm-minloss": 7.5,
+              "roadm-typloss": 10,
+              "roadm-pmin": -13.5,
+              "roadm-pmax": -9.5,
+              "roadm-ptyp": -12,
+              "roadm-osnr": 41,
+              "roadm-noise-figure": 15
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "SI": [
+    {
       "f_min": 191.3e12,
       "baud_rate": 32e9,
-            "f_max":195.1e12,
+      "f_max": 195.1e12,
       "spacing": 50e9,
       "power_dbm": 0,
-            "power_range_db": [0,0,1],
+      "power_range_db": [
+        0,
+        0,
+        1
+      ],
+      "tx_power_dbm": 0,
       "roll_off": 0.15,
       "tx_osnr": 40,
       "sys_margins": 2
-            }],
-      "Transceiver":[
+    }
+  ],
+  "Transceiver": [
     {
       "type_variety": "vendorA_trx-type1",
-            "frequency":{
+      "frequency": {
         "min": 191.35e12,
         "max": 196.1e12
       },
-            "mode":[
+      "mode": [
         {
-
           "format": "mode 1",
           "baud_rate": 32e9,
           "OSNR": 11,
@@ -255,7 +376,7 @@
           "roll_off": 0.15,
           "tx_osnr": 40,
           "min_spacing": 37.5e9,
-                       "cost":1
+          "cost": 1
         },
         {
           "format": "mode 2",
@@ -265,17 +386,17 @@
           "roll_off": 0.15,
           "tx_osnr": 40,
           "min_spacing": 75e9,
-                       "cost":1
+          "cost": 1
         }
       ]
     },
     {
       "type_variety": "Voyager",
-            "frequency":{
+      "frequency": {
         "min": 191.35e12,
         "max": 196.1e12
       },
-            "mode":[
+      "mode": [
         {
           "format": "mode 1",
           "baud_rate": 32e9,
@@ -284,7 +405,7 @@
           "roll_off": 0.15,
           "tx_osnr": 40,
           "min_spacing": 37.5e9,
-                       "cost":1
+          "cost": 1
         },
         {
           "format": "mode 3",
@@ -294,7 +415,7 @@
           "roll_off": 0.15,
           "tx_osnr": 40,
           "min_spacing": 62.5e9,
-                       "cost":1
+          "cost": 1
         },
         {
           "format": "mode 2",
@@ -304,7 +425,7 @@
           "roll_off": 0.15,
           "tx_osnr": 40,
           "min_spacing": 75e9,
-                       "cost":1
+          "cost": 1
         },
         {
           "format": "mode 4",
@@ -314,10 +435,9 @@
           "roll_off": 0.15,
           "tx_osnr": 40,
           "min_spacing": 75e9,
-                       "cost":1
+          "cost": 1
         }
       ]
     }
   ]
-
 }

gnpy/example-data/eqpt_config_multiband.json

@@ -0,0 +1,479 @@
+{
+    "Edfa": [
+        {
+            "type_variety": "std_high_gain",
+            "type_def": "variable_gain",
+            "gain_flatmax": 35,
+            "gain_min": 25,
+            "p_max": 21,
+            "nf_min": 5.5,
+            "nf_max": 7,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_medium_gain",
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 23,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain",
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 23,
+            "nf_min": 6.5,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "high_power",
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 25,
+            "nf_min": 9,
+            "nf_max": 15,
+            "out_voa_auto": false,
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_fixed_gain",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5.5,
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "4pumps_raman",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 12,
+            "gain_min": 12,
+            "p_max": 21,
+            "nf0": -1,
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "hybrid_4pumps_lowgain",
+            "type_def": "dual_stage",
+            "raman": true,
+            "gain_min": 25,
+            "preamp_variety": "4pumps_raman",
+            "booster_variety": "std_low_gain",
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "hybrid_4pumps_mediumgain",
+            "type_def": "dual_stage",
+            "raman": true,
+            "gain_min": 25,
+            "preamp_variety": "4pumps_raman",
+            "booster_variety": "std_medium_gain",
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "medium+low_gain",
+            "type_def": "dual_stage",
+            "gain_min": 25,
+            "preamp_variety": "std_medium_gain",
+            "booster_variety": "std_low_gain",
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "medium+high_power",
+            "type_def": "dual_stage",
+            "gain_min": 25,
+            "preamp_variety": "std_medium_gain",
+            "booster_variety": "high_power",
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_medium_gain_C",
+            "f_min": 191.225e12,
+            "f_max": 196.125e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_medium_gain_L",
+            "f_min": 186.5e12,
+            "f_max": 190.1e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain",
+            "f_min": 191.25e12,
+            "f_max": 196.15e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain_reduced_band",
+            "f_min": 192.25e12,
+            "f_max": 196.15e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain_bis",
+            "f_min": 191.25e12,
+            "f_max": 196.15e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain_L_ter",
+            "f_min": 186.55e12,
+            "f_max": 190.05e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 16,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain_L",
+            "f_min": 186.55e12,
+            "f_max": 190.05e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain_L_reduced_band",
+            "f_min": 187.3e12,
+            "f_max": 190.05e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "test",
+            "type_def": "variable_gain",
+            "gain_flatmax": 25,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 5.8,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "test_fixed_gain",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_booster",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_booster_L",
+            "f_min": 186.55e12,
+            "f_max": 190.05e12,
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_booster_multiband",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_booster",
+                "std_booster_L"
+            ],
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_medium_gain_multiband",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_medium_gain_C",
+                "std_medium_gain_L"
+            ],
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_low_gain_multiband",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain",
+                "std_low_gain_L"
+            ],
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_low_gain_multiband_ter",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain",
+                "std_low_gain_L_ter"
+            ],
+            "allowed_for_design": false
+        },
+        {
+            "type_variety": "std_low_gain_multiband_bis",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain_bis",
+                "std_low_gain_L"
+            ],
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain_multiband_reduced",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain_reduced",
+                "std_low_gain_L"
+            ],
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain_multiband_reduced",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain_bis",
+                "std_low_gain_L_reduced_band"
+            ],
+            "allowed_for_design": true
+        }
+    ],
+    "Fiber": [
+        {
+            "type_variety": "SSMF",
+            "dispersion": 1.67e-05,
+            "effective_area": 83e-12,
+            "pmd_coef": 1.265e-15
+        },
+        {
+            "type_variety": "NZDF",
+            "dispersion": 0.5e-05,
+            "effective_area": 72e-12,
+            "pmd_coef": 1.265e-15
+        },
+        {
+            "type_variety": "LOF",
+            "dispersion": 2.2e-05,
+            "effective_area": 125e-12,
+            "pmd_coef": 1.265e-15
+        }
+    ],
+    "RamanFiber": [
+        {
+            "type_variety": "SSMF",
+            "dispersion": 1.67e-05,
+            "effective_area": 83e-12,
+            "pmd_coef": 1.265e-15
+        }
+    ],
+    "Span": [
+        {
+            "power_mode": true,
+            "delta_power_range_db": [
+                -2,
+                3,
+                0.5
+            ],
+            "max_fiber_lineic_loss_for_raman": 0.25,
+            "target_extended_gain": 2.5,
+            "max_length": 150,
+            "length_units": "km",
+            "max_loss": 28,
+            "padding": 10,
+            "EOL": 0,
+            "con_in": 0,
+            "con_out": 0
+        }
+    ],
+    "Roadm": [
+        {
+            "target_pch_out_db": -20,
+            "add_drop_osnr": 38,
+            "pmd": 0,
+            "pdl": 0,
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            }
+        }
+    ],
+    "SI": [
+        {
+            "f_min": 191.3e12,
+            "baud_rate": 32e9,
+            "f_max": 195.1e12,
+            "spacing": 50e9,
+            "power_dbm": 0,
+            "power_range_db": [
+                0,
+                0,
+                1
+            ],
+            "roll_off": 0.15,
+            "tx_osnr": 40,
+            "sys_margins": 2
+        },
+        {
+            "type_variety": "lband",
+            "f_min": 186.3e12,
+            "baud_rate": 32e9,
+            "f_max": 190.1e12,
+            "spacing": 50e9,
+            "power_dbm": 0,
+            "power_range_db": [
+                0,
+                0,
+                1
+            ],
+            "roll_off": 0.15,
+            "tx_osnr": 40,
+            "sys_margins": 2
+        }
+    ],
+    "Transceiver": [
+        {
+            "type_variety": "vendorA_trx-type1",
+            "frequency": {
+                "min": 191.35e12,
+                "max": 196.1e12
+            },
+            "mode": [
+                {
+                    "format": "mode 1",
+                    "baud_rate": 32e9,
+                    "OSNR": 11,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 40,
+                    "min_spacing": 37.5e9,
+                    "cost": 1
+                },
+                {
+                    "format": "mode 2",
+                    "baud_rate": 66e9,
+                    "OSNR": 15,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 40,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }
+            ]
+        },
+        {
+            "type_variety": "Voyager",
+            "frequency": {
+                "min": 191.35e12,
+                "max": 196.1e12
+            },
+            "mode": [
+                {
+                    "format": "mode 1",
+                    "baud_rate": 32e9,
+                    "OSNR": 12,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 40,
+                    "min_spacing": 37.5e9,
+                    "cost": 1
+                },
+                {
+                    "format": "mode 3",
+                    "baud_rate": 44e9,
+                    "OSNR": 18,
+                    "bit_rate": 300e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 40,
+                    "min_spacing": 62.5e9,
+                    "cost": 1
+                },
+                {
+                    "format": "mode 2",
+                    "baud_rate": 66e9,
+                    "OSNR": 21,
+                    "bit_rate": 400e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 40,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                },
+                {
+                    "format": "mode 4",
+                    "baud_rate": 66e9,
+                    "OSNR": 16,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 40,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }
+            ]
+        }
+    ]
+}

gnpy/example-data/eqpt_config_openroadm_ver4.json

@@ -6,7 +6,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-8.104e-4, -6.221e-2, -5.889e-1, 37.62],
+      "nf_coef": [
+        -8.104e-4,
+        -6.221e-2,
+        -5.889e-1,
+        37.62
+      ],
       "pmd": 3e-12,
       "pdl": 0.7,
       "allowed_for_design": true
@@ -17,7 +22,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-5.952e-4, -6.250e-2, -1.071, 28.99],
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
+      ],
       "pmd": 3e-12,
       "pdl": 0.7,
       "allowed_for_design": true
@@ -74,7 +84,11 @@
   "Span": [
     {
       "power_mode": true,
-            "delta_power_range_db": [0, 0, 0],
+      "delta_power_range_db": [
+        0,
+        0,
+        0
+      ],
       "max_fiber_lineic_loss_for_raman": 0.25,
       "target_extended_gain": 0,
       "max_length": 135,
@@ -93,8 +107,12 @@
       "pmd": 3e-12,
       "pdl": 1.5,
       "restrictions": {
-                "preamp_variety_list": ["openroadm_mw_mw_preamp"],
-                "booster_variety_list": ["openroadm_mw_mw_booster"]
+        "preamp_variety_list": [
+          "openroadm_mw_mw_preamp"
+        ],
+        "booster_variety_list": [
+          "openroadm_mw_mw_booster"
+        ]
       }
     }
   ],
@@ -105,7 +123,11 @@
       "f_max": 196.1e12,
       "spacing": 50e9,
       "power_dbm": 2,
-            "power_range_db": [0, 0, 1],
+      "power_range_db": [
+        0,
+        0,
+        1
+      ],
       "roll_off": 0.15,
       "tx_osnr": 35,
       "sys_margins": 2

gnpy/example-data/eqpt_config_openroadm_ver5.json

@@ -6,7 +6,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-8.104e-4, -6.221e-2, -5.889e-1, 37.62],
+      "nf_coef": [
+        -8.104e-4,
+        -6.221e-2,
+        -5.889e-1,
+        37.62
+      ],
       "pmd": 3e-12,
       "pdl": 0.7,
       "allowed_for_design": true
@@ -17,7 +22,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-5.952e-4, -6.250e-2, -1.071, 28.99],
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
+      ],
       "pmd": 3e-12,
       "pdl": 0.7,
       "allowed_for_design": true
@@ -28,7 +38,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-5.952e-4, -6.250e-2, -1.071, 28.99],
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
+      ],
       "pmd": 0,
       "pdl": 0,
       "allowed_for_design": false
@@ -39,7 +54,12 @@
       "gain_flatmax": 27,
       "gain_min": 0,
       "p_max": 22,
-            "nf_coef": [-5.952e-4, -6.250e-2, -1.071, 27.99],
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        27.99
+      ],
       "pmd": 0,
       "pdl": 0,
       "allowed_for_design": false
@@ -86,7 +106,11 @@
   "Span": [
     {
       "power_mode": true,
-            "delta_power_range_db": [0, 0, 0],
+      "delta_power_range_db": [
+        0,
+        0,
+        0
+      ],
       "max_fiber_lineic_loss_for_raman": 0.25,
       "target_extended_gain": 0,
       "max_length": 135,
@@ -105,8 +129,12 @@
       "pmd": 3e-12,
       "pdl": 1.5,
       "restrictions": {
-                "preamp_variety_list": ["openroadm_mw_mw_preamp_worstcase_ver5"],
-                "booster_variety_list": ["openroadm_mw_mw_booster"]
+        "preamp_variety_list": [
+          "openroadm_mw_mw_preamp_worstcase_ver5"
+        ],
+        "booster_variety_list": [
+          "openroadm_mw_mw_booster"
+        ]
       }
     }
   ],
@@ -117,7 +145,11 @@
       "f_max": 196.1e12,
       "spacing": 50e9,
       "power_dbm": 2,
-            "power_range_db": [0, 0, 1],
+      "power_range_db": [
+        0,
+        0,
+        1
+      ],
       "roll_off": 0.15,
       "tx_osnr": 35,
       "sys_margins": 2

gnpy/example-data/initial_spectrum1.json

@@ -1,5 +1,5 @@
 {
-      "spectrum":[
+  "spectrum": [
     {
       "f_min": 191.35e12,
       "f_max": 195.1e12,

gnpy/example-data/initial_spectrum2.json

@@ -1,8 +1,8 @@
 {
-      "spectrum":[
+  "spectrum": [
     {
       "f_min": 191.4e12,
-            "f_max":193.1e12,
+      "f_max": 193.1e12,
       "baud_rate": 32e9,
       "slot_width": 50e9,
       "delta_pdb": 0,
@@ -12,7 +12,7 @@
     },
     {
       "f_min": 193.1625e12,
-            "f_max":195e12,
+      "f_max": 195e12,
       "baud_rate": 64e9,
       "slot_width": 75e9,
       "roll_off": 0.15,

gnpy/example-data/multiband_spectrum.json

@@ -0,0 +1,24 @@
+{
+    "spectrum": [
+        {
+            "f_min": 191.25e12,
+            "baud_rate": 32e9,
+            "f_max": 195.1e12,
+            "slot_width": 50e9,
+            "delta_pdb": 0,
+            "roll_off": 0.15,
+            "tx_osnr": 40,
+            "label": "cband"
+        },
+        {
+            "f_min": 186.3e12,
+            "baud_rate": 32e9,
+            "f_max": 190.1e12,
+            "slot_width": 50e9,
+            "delta_pdb": 0,
+            "roll_off": 0.15,
+            "tx_osnr": 40,
+            "label": "lband"
+        }
+    ]
+}

gnpy/example-data/sim_params.json

@@ -8,6 +8,12 @@
     "method": "ggn_spectrally_separated",
     "dispersion_tolerance": 1,
     "phase_shift_tolerance": 0.1,
-    "computed_channels": [1, 18, 37, 56, 75]
+    "computed_channels": [
+      1,
+      18,
+      37,
+      56,
+      75
+    ]
   }
 }

gnpy/example-data/std_medium_gain_advanced_config.json

@@ -5,8 +5,8 @@
     0.0359549,
     5.82851
   ],
-    "f_min": 191.35e12,
-    "f_max": 196.1e12,
+  "f_min": 191.275e12,
+  "f_max": 196.125e12,
   "nf_ripple": [
     0.4372876328262819,
     0.4372876328262819,

gnpy/tools/cli_examples.py

@@ -12,24 +12,21 @@ import argparse
 import logging
 import sys
 from math import ceil
-from numpy import linspace, mean
+from numpy import mean
 from pathlib import Path
+from copy import deepcopy
 
 import gnpy.core.ansi_escapes as ansi_escapes
-from gnpy.core.elements import Transceiver, Fiber, RamanFiber
-from gnpy.core.equipment import trx_mode_params
+from gnpy.core.elements import Transceiver, Fiber, RamanFiber, Roadm
 import gnpy.core.exceptions as exceptions
-from gnpy.core.network import build_network
 from gnpy.core.parameters import SimParams
-from gnpy.core.utils import db2lin, lin2db, automatic_nch
-from gnpy.topology.request import (ResultElement, jsontocsv, compute_path_dsjctn, requests_aggregation,
-                                   BLOCKING_NOPATH, correct_json_route_list,
-                                   deduplicate_disjunctions, compute_path_with_disjunction,
-                                   PathRequest, compute_constrained_path, propagate)
-from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum
+from gnpy.core.utils import lin2db, pretty_summary_print, per_label_average, watt2dbm
+from gnpy.topology.request import (ResultElement, jsontocsv, BLOCKING_NOPATH)
 from gnpy.tools.json_io import (load_equipment, load_network, load_json, load_requests, save_network,
-                                requests_from_json, disjunctions_from_json, save_json, load_initial_spectrum)
+                                requests_from_json, save_json, load_initial_spectrum)
 from gnpy.tools.plots import plot_baseline, plot_results
+from gnpy.tools.worker_utils import designed_network, transmission_simulation, planning
+
 
 _logger = logging.getLogger(__name__)
 _examples_dir = Path(__file__).parent.parent / 'example-data'
@@ -144,19 +141,17 @@ def transmission_main_example(args=None):
         sys.exit()
 
     # First try to find exact match if source/destination provided
+    source = None
     if args.source:
         source = transceivers.pop(args.source, None)
         valid_source = True if source else False
-    else:
-        source = None
-        _logger.info('No source node specified: picking random transceiver')
 
+    destination = None
+    nodes_list = []
+    loose_list = []
     if args.destination:
         destination = transceivers.pop(args.destination, None)
         valid_destination = True if destination else False
-    else:
-        destination = None
-        _logger.info('No destination node specified: picking random transceiver')
 
     # If no exact match try to find partial match
     if args.source and not source:
@@ -173,87 +168,72 @@ def transmission_main_example(args=None):
     if not source:
         source = list(transceivers.values())[0]
         del transceivers[source.uid]
+        _logger.info('No source node specified: picking random transceiver')
 
     if not destination:
         destination = list(transceivers.values())[0]
+        nodes_list = [destination.uid]
+        loose_list = ['STRICT']
+        _logger.info('No destination node specified: picking random transceiver')
 
-    _logger.info(f'source = {args.source!r}')
-    _logger.info(f'destination = {args.destination!r}')
+    _logger.info(f'source = {source.uid!r}')
+    _logger.info(f'destination = {destination.uid!r}')
 
-    params = {}
-    params['request_id'] = 0
-    params['trx_type'] = ''
-    params['trx_mode'] = ''
-    params['source'] = source.uid
-    params['destination'] = destination.uid
-    params['bidir'] = False
-    params['nodes_list'] = [destination.uid]
-    params['loose_list'] = ['strict']
-    params['format'] = ''
-    params['path_bandwidth'] = 0
-    params['effective_freq_slot'] = None
-    trx_params = trx_mode_params(equipment)
-    if args.power:
-        trx_params['power'] = db2lin(float(args.power)) * 1e-3
-    params.update(trx_params)
     initial_spectrum = None
-    nb_channels = automatic_nch(trx_params['f_min'], trx_params['f_max'], trx_params['spacing'])
     if args.spectrum:
+        # use the spectrum defined by user for the propagation.
+        # the nb of channel for design remains the one of the reference channel
         initial_spectrum = load_initial_spectrum(args.spectrum)
-        nb_channels = len(initial_spectrum)
         print('User input for spectrum used for propagation instead of SI')
-    params['nb_channel'] = nb_channels
-    req = PathRequest(**params)
-    req.initial_spectrum = initial_spectrum
-    print(f'There are {nb_channels} channels propagating')
     power_mode = equipment['Span']['default'].power_mode
     print('\n'.join([f'Power mode is set to {power_mode}',
-                     f'=> it can be modified in eqpt_config.json - Span']))
+                     '=> it can be modified in eqpt_config.json - Span']))
 
-    # Keep the reference channel for design: the one from SI, with full load same channels
-    pref_ch_db = lin2db(req.power * 1e3)  # reference channel power / span (SL=20dB)
-    pref_total_db = pref_ch_db + lin2db(req.nb_channel)  # reference total power / span (SL=20dB)
+    # Simulate !
     try:
-        build_network(network, equipment, pref_ch_db, pref_total_db, args.no_insert_edfas)
+        network, req, ref_req = designed_network(equipment, network, source.uid, destination.uid,
+                                                 nodes_list=nodes_list, loose_list=loose_list,
+                                                 args_power=args.power,
+                                                 initial_spectrum=initial_spectrum,
+                                                 no_insert_edfas=args.no_insert_edfas)
+        path, propagations_for_path, powers_dbm, infos = transmission_simulation(equipment, network, req, ref_req)
     except exceptions.NetworkTopologyError as e:
         print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
         sys.exit(1)
     except exceptions.ConfigurationError as e:
         print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
         sys.exit(1)
-    path = compute_constrained_path(network, req)
-
+    except exceptions.ServiceError as e:
+        print(f'Service error: {e}')
+        sys.exit(1)
+    except ValueError:
+        sys.exit(1)
+    # print or export results
     spans = [s.params.length for s in path if isinstance(s, RamanFiber) or isinstance(s, Fiber)]
     print(f'\nThere are {len(spans)} fiber spans over {sum(spans)/1000:.0f} km between {source.uid} '
           f'and {destination.uid}')
     print(f'\nNow propagating between {source.uid} and {destination.uid}:')
-
-    power_range = [0]
+    print(f'Reference used for design: (Input optical power reference in span = {watt2dbm(ref_req.power):.2f}dBm,\n'
+          + f'                            spacing = {ref_req.spacing * 1e-9:.2f}GHz\n'
+          + f'                            nb_channels = {ref_req.nb_channel})')
+    print('\nChannels propagating: (Input optical power deviation in span = '
+          + f'{pretty_summary_print(per_label_average(infos.delta_pdb_per_channel, infos.label))}dB,\n'
+          + '                       spacing = '
+          + f'{pretty_summary_print(per_label_average(infos.slot_width * 1e-9, infos.label))}GHz,\n'
+          + '                       transceiver output power = '
+          + f'{pretty_summary_print(per_label_average(watt2dbm(infos.tx_power), infos.label))}dBm,\n'
+          + f'                       nb_channels = {infos.number_of_channels})')
+    for path, power_dbm in zip(propagations_for_path, powers_dbm):
         if power_mode:
-        # power cannot be changed in gain mode
-        try:
-            p_start, p_stop, p_step = equipment['SI']['default'].power_range_db
-            p_num = abs(int(round((p_stop - p_start) / p_step))) + 1 if p_step != 0 else 1
-            power_range = list(linspace(p_start, p_stop, p_num))
-        except TypeError:
-            print('invalid power range definition in eqpt_config, should be power_range_db: [lower, upper, step]')
-    for dp_db in power_range:
-        req.power = db2lin(pref_ch_db + dp_db) * 1e-3
-        # if initial spectrum did not contain any power, now we need to use this one.
-        # note the initial power defines a differential wrt req.power so that if req.power is set to 2mW (3dBm)
-        # and initial spectrum was set to 0, this sets a initial per channel delta power to -3dB, so that
-        # whatever the equalization, -3 dB is applied on all channels (ie initial power in initial spectrum pre-empts
-        # "--power" option)
-        if power_mode:
-            print(f'\nPropagating with input power = {ansi_escapes.cyan}{lin2db(req.power*1e3):.2f} dBm{ansi_escapes.reset}:')
+            print(f'Input optical power reference in span = {ansi_escapes.cyan}{power_dbm:.2f} '
+                  + f'dBm{ansi_escapes.reset}:')
         else:
-            print(f'\nPropagating in {ansi_escapes.cyan}gain mode{ansi_escapes.reset}: power cannot be set manually')
-        infos = propagate(path, req, equipment)
-        if len(power_range) == 1:
+            print('\nPropagating in {ansi_escapes.cyan}gain mode{ansi_escapes.reset}: power cannot be set manually')
+        if len(powers_dbm) == 1:
             for elem in path:
                 print(elem)
             if power_mode:
-                print(f'\nTransmission result for input power = {lin2db(req.power*1e3):.2f} dBm:')
+                print(f'\nTransmission result for input optical power reference in span = {power_dbm:.2f} dBm:')
             else:
                 print(f'\nTransmission results:')
             print(f'  Final GSNR (0.1 nm): {ansi_escapes.cyan}{mean(destination.snr_01nm):.02f} dB{ansi_escapes.reset}')
@@ -319,83 +299,50 @@ def path_requests_run(args=None):
                         help='considers that all demands are bidir')
     parser.add_argument('-o', '--output', type=Path, metavar=_help_fname_json_csv,
                         help='Store satisifed requests into a JSON or CSV file')
+    parser.add_argument('--redesign-per-request', action='store_true', help='Redesign the network at each request'
+                        + ' computation using the request as the reference channel')
+
 
     args = parser.parse_args(args if args is not None else sys.argv[1:])
     _setup_logging(args)
 
     _logger.info(f'Computing path requests {args.service_filename.name} into JSON format')
 
-    (equipment, network) = load_common_data(args.equipment, args.topology, args.sim_params, args.save_network_before_autodesign)
+    (equipment, network) = \
+        load_common_data(args.equipment, args.topology, args.sim_params, args.save_network_before_autodesign)
 
     # Build the network once using the default power defined in SI in eqpt config
     # TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
     # spacing, f_min and f_max
-    p_db = equipment['SI']['default'].power_dbm
-    p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
-                                             equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
+    if args.save_network is not None:
+        save_network(network, args.save_network)
+        print(f'Network (after autodesign) saved to {args.save_network}')
+
     try:
-        build_network(network, equipment, p_db, p_total_db, args.no_insert_edfas)
+        network, _, _ = designed_network(equipment, network, no_insert_edfas=args.no_insert_edfas)
+        data = load_requests(args.service_filename, equipment, bidir=args.bidir,
+                             network=network, network_filename=args.topology)
+        _data = requests_from_json(data, equipment)
+        oms_list, propagatedpths, reversed_propagatedpths, rqs, dsjn, result = \
+            planning(network, equipment, data, redesign=args.redesign_per_request)
     except exceptions.NetworkTopologyError as e:
         print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
         sys.exit(1)
     except exceptions.ConfigurationError as e:
         print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
         sys.exit(1)
-    if args.save_network is not None:
-        save_network(network, args.save_network)
-        print(f'{ansi_escapes.blue}Network (after autodesign) saved to {args.save_network}{ansi_escapes.reset}')
-    oms_list = build_oms_list(network, equipment)
-
-    try:
-        data = load_requests(args.service_filename, equipment, bidir=args.bidir,
-                             network=network, network_filename=args.topology)
-        rqs = requests_from_json(data, equipment)
-    except exceptions.ServiceError as e:
-        print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {e}')
-        sys.exit(1)
-    # check that request ids are unique. Non unique ids, may
-    # mess the computation: better to stop the computation
-    all_ids = [r.request_id for r in rqs]
-    if len(all_ids) != len(set(all_ids)):
-        for item in list(set(all_ids)):
-            all_ids.remove(item)
-        msg = f'Requests id {all_ids} are not unique'
-        _logger.critical(msg)
-        sys.exit()
-    rqs = correct_json_route_list(network, rqs)
-
-    # pths = compute_path(network, equipment, rqs)
-    dsjn = disjunctions_from_json(data)
-
-    print(f'{ansi_escapes.blue}List of disjunctions{ansi_escapes.reset}')
-    print(dsjn)
-    # need to warn or correct in case of wrong disjunction form
-    # disjunction must not be repeated with same or different ids
-    dsjn = deduplicate_disjunctions(dsjn)
-
-    # Aggregate demands with same exact constraints
-    print(f'{ansi_escapes.blue}Aggregating similar requests{ansi_escapes.reset}')
-
-    rqs, dsjn = requests_aggregation(rqs, dsjn)
-    # TODO export novel set of aggregated demands in a json file
-
-    print(f'{ansi_escapes.blue}The following services have been requested:{ansi_escapes.reset}')
-    print(rqs)
-
-    print(f'{ansi_escapes.blue}Computing all paths with constraints{ansi_escapes.reset}')
-    try:
-        pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
     except exceptions.DisjunctionError as this_e:
         print(f'{ansi_escapes.red}Disjunction error:{ansi_escapes.reset} {this_e}')
         sys.exit(1)
-
-    print(f'{ansi_escapes.blue}Propagating on selected path{ansi_escapes.reset}')
-    propagatedpths, reversed_pths, reversed_propagatedpths = compute_path_with_disjunction(network, equipment, rqs, pths)
-    # Note that deepcopy used in compute_path_with_disjunction returns
-    # a list of nodes which are not belonging to network (they are copies of the node objects).
-    # so there can not be propagation on these nodes.
-
-    pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
+    except exceptions.ServiceError as e:
+        print(f'Service error: {e}')
+        sys.exit(1)
+    except ValueError:
+        sys.exit(1)
+    print(f'{ansi_escapes.blue}List of disjunctions{ansi_escapes.reset}')
+    print(dsjn)
+    print(f'{ansi_escapes.blue}The following services have been requested:{ansi_escapes.reset}')
+    print(_data)
 
     print(f'{ansi_escapes.blue}Result summary{ansi_escapes.reset}')
     header = ['req id', '  demand', ' GSNR@bandwidth A-Z (Z-A)', ' GSNR@0.1nm A-Z (Z-A)',

gnpy/tools/convert.py

@@ -122,7 +122,7 @@ class Eqpt(object):
         'east_att_in': 0,
         'east_amp_gain': None,
         'east_amp_dp': None,
-        'east_tilt': 0,
+        'east_tilt_vs_wavelength': 0,
         'east_att_out': None
     }
 
@@ -345,13 +345,13 @@ def create_east_eqpt_element(node):
         eqpt['type_variety'] = f'{node.east_amp_type}'
         eqpt['operational'] = {'gain_target': node.east_amp_gain,
                                'delta_p':     node.east_amp_dp,
-                               'tilt_target': node.east_tilt,
+                               'tilt_target': node.east_tilt_vs_wavelength,
                                'out_voa':     node.east_att_out}
     elif node.east_amp_type.lower() == '':
         eqpt['type'] = 'Edfa'
         eqpt['operational'] = {'gain_target': node.east_amp_gain,
                                'delta_p':     node.east_amp_dp,
-                               'tilt_target': node.east_tilt,
+                               'tilt_target': node.east_tilt_vs_wavelength,
                                'out_voa':     node.east_att_out}
     elif node.east_amp_type.lower() == 'fused':
         # fused edfa variety is a hack to indicate that there should not be
@@ -378,12 +378,12 @@ def create_west_eqpt_element(node):
         eqpt['type_variety'] = f'{node.west_amp_type}'
         eqpt['operational'] = {'gain_target': node.west_amp_gain,
                                'delta_p':     node.west_amp_dp,
-                               'tilt_target': node.west_tilt,
+                               'tilt_target': node.west_tilt_vs_wavelength,
                                'out_voa':     node.west_att_out}
     elif node.west_amp_type.lower() == '':
         eqpt['operational'] = {'gain_target': node.west_amp_gain,
                                'delta_p':     node.west_amp_dp,
-                               'tilt_target': node.west_tilt,
+                               'tilt_target': node.west_tilt_vs_wavelength,
                                'out_voa':     node.west_att_out}
     elif node.west_amp_type.lower() == 'fused':
         eqpt['type'] = 'Fused'

gnpy/tools/json_io.py

@@ -14,14 +14,15 @@ from pathlib import Path
 import json
 from collections import namedtuple
 from numpy import arange
+from copy import deepcopy
 
 from gnpy.core import elements
-from gnpy.core.equipment import trx_mode_params
+from gnpy.core.equipment import trx_mode_params, find_type_variety
 from gnpy.core.exceptions import ConfigurationError, EquipmentConfigError, NetworkTopologyError, ServiceError
 from gnpy.core.science_utils import estimate_nf_model
 from gnpy.core.info import Carrier
-from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions
-from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT
+from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions, dbm2watt
+from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT, EdfaParams, MultiBandParams
 from gnpy.topology.request import PathRequest, Disjunction, compute_spectrum_slot_vs_bandwidth
 from gnpy.topology.spectrum_assignment import mvalue_to_slots
 from gnpy.tools.convert import xls_to_json_data
@@ -51,9 +52,10 @@ class _JsonThing:
         clean_kwargs = {k: v for k, v in kwargs.items() if v != ''}
         for k, v in default_values.items():
             setattr(self, k, clean_kwargs.get(k, v))
-            if k not in clean_kwargs and name != 'Amp':
-                msg = f'\n WARNING missing {k} attribute in eqpt_config.json[{name}]' \
-                    + f'\n default value is {k} = {v}'
+            if k not in clean_kwargs and name != 'Amp' and v is not None and v != []:
+                # do not show this warning if the default value is None
+                msg = f'\n\tWARNING missing {k} attribute in eqpt_config.json[{name}]' \
+                    + f'\n\tdefault value is {k} = {v}\n'
                 _logger.warning(msg)
 
 
@@ -67,7 +69,8 @@ class SI(_JsonThing):
         "power_range_db": [0, 0, 0.5],
         "roll_off": 0.15,
         "tx_osnr": 45,
-        "sys_margins": 0
+        "sys_margins": 0,
+        "tx_power_dbm": None  # optional value in SI
     }
 
     def __init__(self, **kwargs):
@@ -95,13 +98,15 @@ class Span(_JsonThing):
 
 class Roadm(_JsonThing):
     default_values = {
+        'type_variety': 'default',
         'add_drop_osnr': 100,
         'pmd': 0,
         'pdl': 0,
         'restrictions': {
             'preamp_variety_list': [],
             'booster_variety_list': []
-        }
+        },
+        'roadm-path-impairments': []
     }
 
     def __init__(self, **kwargs):
@@ -180,35 +185,7 @@ class RamanFiber(Fiber):
 
 
 class Amp(_JsonThing):
-    default_values = {
-        'f_min': 191.35e12,
-        'f_max': 196.1e12,
-        'type_variety': '',
-        'type_def': '',
-        'gain_flatmax': None,
-        'gain_min': None,
-        'p_max': None,
-        'nf_model': None,
-        'dual_stage_model': None,
-        'preamp_variety': None,
-        'booster_variety': None,
-        'nf_min': None,
-        'nf_max': None,
-        'nf_coef': None,
-        'nf0': None,
-        'nf_fit_coeff': None,
-        'nf_ripple': 0,
-        'dgt': None,
-        'gain_ripple': 0,
-        'tilt_ripple': 0,
-        'f_ripple_ref': None,
-        'out_voa_auto': False,
-        'allowed_for_design': False,
-        'raman': False,
-        'pmd': 0,
-        'pdl': 0,
-        'advance_configurations_from_json': None
-    }
+    default_values = EdfaParams.default_values
 
     def __init__(self, **kwargs):
         self.update_attr(self.default_values, kwargs, 'Amp')
@@ -216,11 +193,12 @@ class Amp(_JsonThing):
     @classmethod
     def from_json(cls, filename, **kwargs):
         config = Path(filename).parent / 'default_edfa_config.json'
-
+        # default_edfa_config.json assumes a DGT profile independantly from fmin/fmax, that's a generic profile
         type_variety = kwargs['type_variety']
         type_def = kwargs.get('type_def', 'variable_gain')  # default compatibility with older json eqpt files
         nf_def = None
         dual_stage_def = None
+        amplifiers = None
 
         if type_def == 'fixed_gain':
             try:
@@ -265,16 +243,25 @@ class Amp(_JsonThing):
                 preamp_variety = kwargs.pop('preamp_variety')
                 booster_variety = kwargs.pop('booster_variety')
             except KeyError:
-                msg = f'missing preamp/booster variety input for amplifier: {type_variety} in equipment config'
-                raise EquipmentConfigError(msg)
+                raise EquipmentConfigError(f'missing preamp/booster variety input for amplifier: {type_variety}'
+                                           + ' in equipment config')
             dual_stage_def = Model_dual_stage(preamp_variety, booster_variety)
+        elif type_def == 'multi_band':
+            amplifiers = kwargs['amplifiers']
         else:
             raise EquipmentConfigError(f'Edfa type_def {type_def} does not exist')
 
         json_data = load_json(config)
-
+        # raise an error if config does not contain f_min, f_max
+        if 'f_min' not in json_data or 'f_max' not in json_data:
+            raise EquipmentConfigError('default Edfa config does not contain f_min and f_max values.'
+                                       + ' Please correct file.')
+        # use f_min, f_max from kwargs
+        if 'f_min' in kwargs:
+            json_data.pop('f_min', None)
+            json_data.pop('f_max', None)
         return cls(**{**kwargs, **json_data,
-                      'nf_model': nf_def, 'dual_stage_model': dual_stage_def})
+                      'nf_model': nf_def, 'dual_stage_model': dual_stage_def, 'multi_band': amplifiers})
 
 
 def _automatic_spacing(baud_rate):
@@ -294,7 +281,7 @@ def _spectrum_from_json(json_data):
     label should be different for each partition
     >>> json_data = {'spectrum': \
         [{'f_min': 193.2e12, 'f_max': 193.4e12, 'slot_width': 50e9, 'baud_rate': 32e9, 'roll_off': 0.15, \
-            'delta_pdb': 1, 'tx_osnr': 45},\
+            'delta_pdb': 1, 'tx_osnr': 45, 'tx_power_dbm': -7},\
         {'f_min': 193.4625e12, 'f_max': 193.9875e12, 'slot_width': 75e9, 'baud_rate': 64e9, 'roll_off': 0.15},\
         {'f_min': 194.075e12, 'f_max': 194.075e12, 'slot_width': 100e9, 'baud_rate': 90e9, 'roll_off': 0.15},\
         {'f_min': 194.2e12, 'f_max': 194.35e12, 'slot_width': 50e9, 'baud_rate': 32e9, 'roll_off': 0.15}]}
@@ -302,24 +289,24 @@ def _spectrum_from_json(json_data):
     >>> for k, v in spectrum.items():
     ...     print(f'{k}: {v}')
     ...
-    193200000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
-    193250000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
-    193300000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
-    193350000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
-    193400000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
-    193462500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
-    193537500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
-    193612500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
-    193687500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
-    193762500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
-    193837500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
-    193912500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
-    193987500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
-    194075000000000.0: Carrier(delta_pdb=0, baud_rate=90000000000.0, slot_width=100000000000.0, roll_off=0.15, tx_osnr=40, label='2-90.00G')
-    194200000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
-    194250000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
-    194300000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
-    194350000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
+    193200000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193250000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193300000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193350000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193400000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193462500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193537500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193612500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193687500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193762500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193837500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193912500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193987500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    194075000000000.0: Carrier(delta_pdb=0, baud_rate=90000000000.0, slot_width=100000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='2-90.00G')
+    194200000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
+    194250000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
+    194300000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
+    194350000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
     """
     spectrum = {}
     json_data = sorted(json_data, key=lambda x: x['f_min'])
@@ -335,6 +322,9 @@ def _spectrum_from_json(json_data):
         # default tx_osnr is set to 40 dB
         if 'tx_osnr' not in part:
             part['tx_osnr'] = 40
+        # default tx_power_dbm is set to 0 dBn
+        if 'tx_power_dbm' not in part:
+            part['tx_power_dbm'] = 0
         # starting freq is exactly f_min to be consistent with utils.automatic_nch
         # first partition min occupation is f_min - slot_width / 2 (central_frequency is f_min)
         # supposes that carriers are centered on frequency
@@ -353,7 +343,8 @@ def _spectrum_from_json(json_data):
                                    part['slot_width']):
             spectrum[current_freq] = Carrier(delta_pdb=part['delta_pdb'], baud_rate=part['baud_rate'],
                                              slot_width=part['slot_width'], roll_off=part['roll_off'],
-                                             tx_osnr=part['tx_osnr'], label=part['label'])
+                                             tx_osnr=part['tx_osnr'], tx_power=dbm2watt(part['tx_power_dbm']),
+                                             label=part['label'])
         previous_part_max_freq = current_freq + part['slot_width'] / 2
     return spectrum
 
@@ -387,13 +378,40 @@ def _update_dual_stage(equipment):
     return equipment
 
 
+def _update_band(equipment: dict) -> dict:
+    """Creates a list of bands for this amplifier, and remove other parameters which are not applicable
+    """
+    amp_dict = equipment['Edfa']
+    for amplifier in amp_dict.values():
+        if amplifier.type_def != 'multi_band':
+            amplifier.bands = [{'f_min': amplifier.f_min,
+                                'f_max': amplifier.f_max}]
+            # updates band parameter
+        else:
+            _bands = [{'f_min': amp_dict[a].f_min,
+                       'f_max': amp_dict[a].f_max} for a in amp_dict[amplifier.type_variety].multi_band]
+            # remove duplicates
+            amplifier.bands = []
+            for b in _bands:
+                if b not in amplifier.bands:
+                    amplifier.bands.append(b)
+            # remove non applicable parameters
+            for key in ['f_min', 'f_max', 'gain_flatmax', 'gain_min', 'p_max', 'nf_model', 'dual_stage_model',
+                        'nf_fit_coeff', 'nf_ripple', 'dgt', 'gain_ripple']:
+                delattr(amplifier, key)
+
+    return equipment
+
+
 def _roadm_restrictions_sanity_check(equipment):
     """verifies that booster and preamp restrictions specified in roadm equipment are listed in the edfa."""
-    restrictions = equipment['Roadm']['default'].restrictions['booster_variety_list'] + \
-        equipment['Roadm']['default'].restrictions['preamp_variety_list']
+    for roadm_type, roadm_eqpt in equipment['Roadm'].items():
+        restrictions = roadm_eqpt.restrictions['booster_variety_list'] + \
+            roadm_eqpt.restrictions['preamp_variety_list']
         for amp_name in restrictions:
             if amp_name not in equipment['Edfa']:
-            raise EquipmentConfigError(f'ROADM restriction {amp_name} does not refer to a defined EDFA name')
+                raise EquipmentConfigError(f'ROADM {roadm_type} restriction {amp_name} does not refer to a '
+                                           + 'defined EDFA name')
 
 
 def _check_fiber_vs_raman_fiber(equipment):
@@ -434,6 +452,9 @@ def _equipment_from_json(json_data, filename):
             elif key == 'Roadm':
                 equipment[key][subkey] = Roadm(**entry)
             elif key == 'SI':
+                # use power_dbm value for tx_power_dbm if the key is not in 'SI'
+                # if 'tx_power_dbm' not in entry.keys():
+                #     entry['tx_power_dbm'] = entry['power_dbm']
                 equipment[key][subkey] = SI(**entry)
             elif key == 'Transceiver':
                 equipment[key][subkey] = Transceiver(**entry)
@@ -443,7 +464,13 @@ def _equipment_from_json(json_data, filename):
                 raise EquipmentConfigError(f'Unrecognized network element type "{key}"')
     _check_fiber_vs_raman_fiber(equipment)
     equipment = _update_dual_stage(equipment)
+    equipment = _update_band(equipment)
     _roadm_restrictions_sanity_check(equipment)
+    possible_SI = list(equipment['SI'].keys())
+    if 'default' not in possible_SI:
+        # Use "default" key in the equipment, using the first listed keys
+        equipment['SI']['default'] = equipment['SI'][possible_SI[0]]
+        del equipment['SI'][possible_SI[0]]
     return equipment
 
 
@@ -479,6 +506,8 @@ def _cls_for(equipment_type):
         return elements.Fiber
     elif equipment_type == 'RamanFiber':
         return elements.RamanFiber
+    elif equipment_type == 'Multiband_amplifier':
+        return elements.Multiband_amplifier
     else:
         raise ConfigurationError(f'Unknown network equipment "{equipment_type}"')
 
@@ -492,7 +521,55 @@ def network_from_json(json_data, equipment):
         typ = el_config.pop('type')
         variety = el_config.pop('type_variety', 'default')
         cls = _cls_for(typ)
-        if typ == 'Fused':
+        if typ == 'Transceiver':
+            temp = el_config.setdefault('params', {})
+        if typ == 'Multiband_amplifier':
+            if variety in ['default', '']:
+                extra_params = None
+                temp = el_config.setdefault('params', {})
+                temp = merge_amplifier_restrictions(temp, deepcopy(MultiBandParams.default_values))
+                el_config['params'] = temp
+            else:
+                extra_params = equipment['Edfa'][variety]
+                temp = el_config.setdefault('params', {})
+                # use config params preferably to library params, only use library params to fill in
+                # the missing attribute
+                temp = merge_amplifier_restrictions(temp, deepcopy(extra_params.__dict__))
+                el_config['params'] = temp
+                el_config['type_variety'] = variety
+            # if config does not contain any amp list create one
+            amps = el_config.setdefault('amplifiers', [])
+            for amp in amps:
+                amp_variety = amp['type_variety']    # juste pour essayer
+                amp_extra_params = equipment['Edfa'][amp_variety]
+                temp = amp.setdefault('params', {})
+                temp = merge_amplifier_restrictions(temp, amp_extra_params.__dict__)
+                amp['params'] = temp
+                amp['type_variety'] = amp_variety
+            # check type_variety consistant with amps type_variety
+            if amps:
+                try:
+                    multiband_type_variety = find_type_variety([a['type_variety'] for a in amps], equipment)
+                except ConfigurationError as e:
+                    msg = f'Node {el_config["uid"]}: {e}'
+                    raise ConfigurationError(msg)
+                if variety is not None and variety != multiband_type_variety:
+                    raise ConfigurationError(f'In node {el_config["uid"]}: multiband amplifier type_variety is not '
+                                             + 'consistent with its amps type varieties.')
+            if not amps and extra_params is not None:
+                # the amp config does not contain the amplifiers operational settings, but has a type_variety
+                # defined so that it is possible to create the template of amps for design for each band. This
+                # defines the default design bands.
+                # This lopp populates each amp with default values, for each band
+                for band in extra_params.bands:
+                    params = {k: v for k, v in Amp.default_values.items()}
+                    # update frequencies with band values
+                    params['f_min'] = band['f_min']
+                    params['f_max'] = band['f_max']
+                    amps.append({'params': params})
+            # without type_variety, it is not possible to set the amplifier dict at this point: need to wait
+            # for design, and use user defined design-bands
+        elif typ == 'Fused':
             # well, there's no variety for the 'Fused' node type
             pass
         elif variety in equipment[typ]:
@@ -509,7 +586,7 @@ def network_from_json(json_data, equipment):
             temp = merge_amplifier_restrictions(temp, extra_params)
             el_config['params'] = temp
             el_config['type_variety'] = variety
-        elif (typ in ['Fiber', 'RamanFiber']):
+        elif (typ in ['Fiber', 'RamanFiber', 'Roadm']):
             raise ConfigurationError(f'The {typ} of variety type {variety} was not recognized:'
                                      '\nplease check it is properly defined in the eqpt_config json file')
         elif typ == 'Edfa':
@@ -600,7 +677,6 @@ def requests_from_json(json_data, equipment):
         params['nodes_list'] = [n['num-unnum-hop']['node-id'] for n in nd_list]
         params['loose_list'] = [n['num-unnum-hop']['hop-type'] for n in nd_list]
         # recover trx physical param (baudrate, ...) from type and mode
-        # in trx_mode_params optical power is read from equipment['SI']['default'] and
         # nb_channel is computed based on min max frequency and spacing
         try:
             trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
@@ -608,13 +684,11 @@ def requests_from_json(json_data, equipment):
             msg = f'Equipment Config error in {req["request-id"]}: {e}'
             raise EquipmentConfigError(msg) from e
         params.update(trx_params)
-        # optical power might be set differently in the request. if it is indicated then the
-        # params['power'] is updated
-        try:
-            if req['path-constraints']['te-bandwidth']['output-power']:
-                params['power'] = req['path-constraints']['te-bandwidth']['output-power']
-        except KeyError:
-            pass
+        params['power'] = req['path-constraints']['te-bandwidth'].get('output-power')
+        # params must not be None, but user can set to None: catch this case
+        if params['power'] is None:
+            params['power'] = dbm2watt(equipment['SI']['default'].power_dbm)
+
         # same process for nb-channel
         f_min = params['f_min']
         f_max_from_si = params['f_max']
@@ -634,6 +708,14 @@ def requests_from_json(json_data, equipment):
             params['path_bandwidth'] = req['path-constraints']['te-bandwidth']['path_bandwidth']
         except KeyError:
             pass
+        params['tx_power'] = req['path-constraints']['te-bandwidth'].get('tx_power')
+        default_tx_power_dbm = equipment['SI']['default'].tx_power_dbm
+        if params['tx_power'] is None:
+            # use request's input power in span instead
+            params['tx_power'] = params['power']
+            if default_tx_power_dbm is not None:
+                # use default tx power
+                params['tx_power'] = dbm2watt(default_tx_power_dbm)
         _check_one_request(params, f_max_from_si)
         requests_list.append(PathRequest(**params))
     return requests_list

gnpy/tools/worker_utils.py

@@ -0,0 +1,248 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+'''
+gnpy.tools.worker_utils
+=======================
+
+Common code for CLI examples and API
+'''
+import logging
+from copy import deepcopy
+from typing import Union, List, Tuple
+from numpy import linspace
+from networkx import DiGraph
+
+from gnpy.core.utils import automatic_nch, watt2dbm, dbm2watt, pretty_summary_print, per_label_average
+from gnpy.core.equipment import trx_mode_params
+from gnpy.core.network import add_missing_elements_in_network, design_network
+from gnpy.core import exceptions
+from gnpy.core.info import SpectralInformation
+from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum, OMS
+from gnpy.topology.request import correct_json_route_list, deduplicate_disjunctions, requests_aggregation, \
+    compute_path_dsjctn, compute_path_with_disjunction, ResultElement, PathRequest, Disjunction, \
+    compute_constrained_path, propagate
+from gnpy.tools.json_io import requests_from_json, disjunctions_from_json
+
+
+logger = logging.getLogger(__name__)
+
+
+def designed_network(equipment: dict, network: DiGraph, source: str = None, destination: str = None,
+                     nodes_list: List[str] = None, loose_list: List[str] = None,
+                     initial_spectrum: dict = None, no_insert_edfas: bool = False,
+                     args_power: Union[str, float, int] = None,
+                     service_req: PathRequest = None) -> Tuple[DiGraph, PathRequest, PathRequest]:
+    """Build the reference channels based on inputs and design the network for this reference channel, and build the
+    channel to be propagated for the single transmission script.
+
+    Reference channel (target input power in spans, nb of channels, transceiver output power) is built using
+    equipment['SI'] information. If indicated,  with target input power in spans is updated with args_power.
+    Channel to be propagated is using the same channel reference, except if different settings are provided
+    with service_req and initial_spectrum. The service to be propagated uses specified source, destination
+    and list nodes_list of include nodes constraint except if the service_req is specified.
+
+    Args:
+    - equipment: a dictionary containing equipment information.
+    - network: a directed graph representing the initial network.
+    - no_insert_edfas: a boolean indicating whether to insert EDFAs in the network.
+    - args_power: the power to be used for the network design.
+    - service_req: the service request the user wants to propagate.
+    - source: the source node for the channel to be propagated if no service_req is specified.
+    - destination: the destination node for the channel to be propagated if no service_req is specified.
+    - nodes_list: a list of nodes to be included ifor the channel to be propagated if no service_req is specified.
+    - loose_list: a list of loose nodes to be included in the network design.
+    - initial_spectrum: a dictionary representing the initial spectrum to propagate.
+
+    Returns:
+    - The designed network.
+    - The channel to propagate.
+    - The reference channel used for the design.
+    """
+    if loose_list is None:
+        loose_list = []
+    if nodes_list is None:
+        nodes_list = []
+    if not no_insert_edfas:
+        add_missing_elements_in_network(network, equipment)
+
+    if not nodes_list:
+        if destination:
+            nodes_list = [destination]
+            loose_list = ['STRICT']
+        else:
+            nodes_list = []
+            loose_list = []
+    params = {
+        'request_id': 'reference',
+        'trx_type': '',
+        'trx_mode': '',
+        'source': source,
+        'destination': destination,
+        'bidir': False,
+        'nodes_list': nodes_list,
+        'loose_list': loose_list,
+        'format': '',
+        'path_bandwidth': 0,
+        'effective_freq_slot': None,
+        'nb_channel': automatic_nch(equipment['SI']['default'].f_min, equipment['SI']['default'].f_max,
+                                    equipment['SI']['default'].spacing),
+        'power': dbm2watt(equipment['SI']['default'].power_dbm),
+        'tx_power': None
+    }
+    params['tx_power'] = dbm2watt(equipment['SI']['default'].power_dbm)
+    if equipment['SI']['default'].tx_power_dbm is not None:
+        # use SI tx_power if present
+        params['tx_power'] = dbm2watt(equipment['SI']['default'].tx_power_dbm)
+    trx_params = trx_mode_params(equipment)
+    params.update(trx_params)
+
+    # use args_power instead of si
+    if args_power:
+        params['power'] = dbm2watt(float(args_power))
+        if equipment['SI']['default'].tx_power_dbm is None:
+            params['tx_power'] = params['power']
+
+    # use si as reference channel
+    reference_channel = PathRequest(**params)
+    # temporary till multiband design feat is available: do not design for L band
+    reference_channel.nb_channel = min(params['nb_channel'], automatic_nch(191.2e12, 196.0e12, params['spacing']))
+
+    if service_req:
+        # use service_req as reference channel with si tx_power if service_req tx_power is None
+        if service_req.tx_power is None:
+            service_req.tx_power = params['tx_power']
+        reference_channel = service_req
+
+    design_network(reference_channel, network, equipment, set_connector_losses=True, verbose=True)
+
+    if initial_spectrum:
+        params['nb_channel'] = len(initial_spectrum)
+
+    req = PathRequest(**params)
+    if service_req:
+        req = service_req
+
+    req.initial_spectrum = initial_spectrum
+    return network, req, reference_channel
+
+
+def check_request_path_ids(rqs: List[PathRequest]):
+    """check that request ids are unique. Non unique ids, may
+    mess the computation: better to stop the computation
+    """
+    all_ids = [r.request_id for r in rqs]
+    if len(all_ids) != len(set(all_ids)):
+        for item in list(set(all_ids)):
+            all_ids.remove(item)
+        msg = f'Requests id {all_ids} are not unique'
+        logger.error(msg)
+        raise ValueError(msg)
+
+
+def planning(network: DiGraph, equipment: dict, data: dict, redesign: bool = False) \
+        -> Tuple[List[OMS], list, list, List[PathRequest], List[Disjunction], List[ResultElement]]:
+    """Run planning
+    data contain the service dict from json
+    redesign True means that network is redesign using each request as reference channel
+    when False it means that the design is made once and successive propagation use the settings
+    computed with this design.
+    """
+    oms_list = build_oms_list(network, equipment)
+    rqs = requests_from_json(data, equipment)
+    # check that request ids are unique.
+    check_request_path_ids(rqs)
+    rqs = correct_json_route_list(network, rqs)
+    dsjn = disjunctions_from_json(data)
+    logger.info('List of disjunctions:\n%s', dsjn)
+    # need to warn or correct in case of wrong disjunction form
+    # disjunction must not be repeated with same or different ids
+    dsjn = deduplicate_disjunctions(dsjn)
+    logger.info('Aggregating similar requests')
+    rqs, dsjn = requests_aggregation(rqs, dsjn)
+    logger.info('The following services have been requested:\n%s', rqs)
+    # logger.info('Computing all paths with constraints for request %s', optical_path_result_id)
+
+    pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
+    logger.info('Propagating on selected path')
+    propagatedpths, reversed_pths, reversed_propagatedpths = \
+        compute_path_with_disjunction(network, equipment, rqs, pths, redesign=redesign)
+    # Note that deepcopy used in compute_path_with_disjunction returns
+    # a list of nodes which are not belonging to network (they are copies of the node objects).
+    # so there can not be propagation on these nodes.
+
+    # Allowed user_policy are first_fit and 2partition
+    pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
+    for i, rq in enumerate(rqs):
+        if hasattr(rq, 'OSNR') and rq.OSNR:
+            rq.osnr_with_sys_margin = rq.OSNR + equipment["SI"]["default"].sys_margins
+
+    # assumes that list of rqs and list of propgatedpths have same order
+    result = [ResultElement(rq, pth, rpth) for rq, pth, rpth in zip(rqs, propagatedpths, reversed_propagatedpths)]
+    return oms_list, propagatedpths, reversed_propagatedpths, rqs, dsjn, result
+
+
+def transmission_simulation(equipment: dict, network: DiGraph, req: PathRequest, ref_req: PathRequest) \
+        -> Tuple[list, List[list], List[Union[float, int]], SpectralInformation]:
+    """Run simulation and returms the propagation result for each power sweep iteration.
+    Args:
+    - equipment: a dictionary containing equipment information.
+    - network: network after being designed using ref_req. Any missing information (amp gain or delta_p) must have
+    been filled using ref_req as reference channel previuos to this function.
+    - req: channel to be propagated.
+    - ref_req: the reference channel used for filling missing information in the network.
+    In case of power sweep, network is redesigned using ref_req whose target input power in span is
+    updated with the power step.
+
+    Returns a tuple containing:
+    - path: last propagated path. Power sweep is not possible with gain mode (as gain targets are used)
+    - propagations: list of propagated path for each power iteration
+    - powers_dbm: list of power used for the power sweep
+    - infos: last propagated spectral information
+    """
+    power_mode = equipment['Span']['default'].power_mode
+    logger.info('Power mode is set to %s=> it can be modified in eqpt_config.json - Span', power_mode)
+    # initial network is designed using ref_req. that is that any missing information (amp gain or delta_p) is filled
+    # using this ref_req.power, previous to any sweep requested later on.
+
+    pref_ch_db = watt2dbm(ref_req.power)
+    p_ch_db = watt2dbm(req.power)
+    path = compute_constrained_path(network, req)
+    power_range = [0]
+    if power_mode:
+        # power cannot be changed in gain mode
+        try:
+            p_start, p_stop, p_step = equipment['SI']['default'].power_range_db
+            p_num = abs(int(round((p_stop - p_start) / p_step))) + 1 if p_step != 0 else 1
+            power_range = list(linspace(p_start, p_stop, p_num))
+        except TypeError as e:
+            msg = 'invalid power range definition in eqpt_config, should be power_range_db: [lower, upper, step]'
+            logger.error(msg)
+            raise exceptions.EquipmentConfigError(msg) from e
+
+    logger.info('Now propagating between %s and %s', req.source, req.destination)
+
+    propagations = []
+    powers_dbm = []
+    for dp_db in power_range:
+        ref_req.power = dbm2watt(pref_ch_db + dp_db)
+        req.power = dbm2watt(p_ch_db + dp_db)
+
+        # Power sweep is made to evaluate different span input powers, so redesign is mandatory for each power,
+        #  but no need to redesign if there are no power sweep
+        if len(power_range) > 1:
+            design_network(ref_req, network.subgraph(path), equipment, set_connector_losses=False, verbose=False)
+
+        infos = propagate(path, req, equipment)
+        propagations.append(deepcopy(path))
+        powers_dbm.append(pref_ch_db + dp_db)
+        logger.info('\nChannels propagating: (Input optical power deviation in span = '
+                    + f'{pretty_summary_print(per_label_average(infos.delta_pdb_per_channel, infos.label))}dB,\n'
+                    + '                       spacing = '
+                    + f'{pretty_summary_print(per_label_average(infos.slot_width * 1e-9, infos.label))}GHz,\n'
+                    + '                       transceiver output power = '
+                    + f'{pretty_summary_print(per_label_average(watt2dbm(infos.tx_power), infos.label))}dBm,\n'
+                    + f'                       nb_channels = {infos.number_of_channels})')
+        if not power_mode:
+            logger.info('\n\tPropagating using gain targets: Input optical power deviation in span ignored')
+    return path, propagations, powers_dbm, infos

gnpy/topology/request.py

@@ -16,14 +16,18 @@ See: draft-ietf-teas-yang-path-computation-01.txt
 """
 
 from collections import namedtuple, OrderedDict
+from typing import List
 from logging import getLogger
 from networkx import (dijkstra_path, NetworkXNoPath,
                       all_simple_paths, shortest_simple_paths)
 from networkx.utils import pairwise
 from numpy import mean, argmin
-from gnpy.core.elements import Transceiver, Roadm
-from gnpy.core.utils import lin2db
-from gnpy.core.info import create_input_spectral_information, carriers_to_spectral_information, ReferenceCarrier
+
+from gnpy.core.elements import Transceiver, Roadm, Edfa, Multiband_amplifier
+from gnpy.core.utils import lin2db, find_common_range
+from gnpy.core.info import create_input_spectral_information, carriers_to_spectral_information, \
+    demuxed_spectral_information, muxed_spectral_information, SpectralInformation
+from gnpy.core import network as network_module
 from gnpy.core.exceptions import ServiceError, DisjunctionError
 from copy import deepcopy
 from csv import writer
@@ -35,7 +39,7 @@ RequestParams = namedtuple('RequestParams', 'request_id source destination bidir
                            ' trx_mode nodes_list loose_list spacing power nb_channel f_min'
                            ' f_max format baud_rate OSNR penalties bit_rate'
                            ' roll_off tx_osnr min_spacing cost path_bandwidth effective_freq_slot'
-                           ' equalization_offset_db')
+                           ' equalization_offset_db, tx_power')
 DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link_diverse'
                                ' node_diverse disjunctions_req')
 
@@ -64,6 +68,7 @@ class PathRequest:
         self.bit_rate = params.bit_rate
         self.roll_off = params.roll_off
         self.tx_osnr = params.tx_osnr
+        self.tx_power = params.tx_power
         self.min_spacing = params.min_spacing
         self.cost = params.cost
         self.path_bandwidth = params.path_bandwidth
@@ -94,7 +99,8 @@ class PathRequest:
                             f'baud_rate:\t{temp} Gbaud',
                             f'bit_rate:\t{temp2} Gb/s',
                             f'spacing:\t{self.spacing * 1e-9} GHz',
-                            f'power:  \t{round(lin2db(self.power)+30, 2)} dBm',
+                            f'power:  \t{round(lin2db(self.power) + 30, 2)} dBm',
+                            f'tx_power_dbm:  \t{round(lin2db(self.tx_power) + 30, 2)} dBm',
                             f'nb channels: \t{self.nb_channel}',
                             f'path_bandwidth: \t{round(self.path_bandwidth * 1e-9, 2)} Gbit/s',
                             f'nodes-list:\t{self.nodes_list}',
@@ -329,36 +335,46 @@ def compute_constrained_path(network, req):
     return total_path
 
 
-def ref_carrier(equipment):
-    """Create a reference carier based SI information with the specified request's power:
-    req_power records the power in W that the user has defined for a given request
-    (which might be different from the one used for the design).
-    """
-    return ReferenceCarrier(baud_rate=equipment['SI']['default'].baud_rate,
-                            slot_width=equipment['SI']['default'].spacing)
+def filter_si(path: list, equipment: dict, si: SpectralInformation) -> SpectralInformation:
+    """Filter spectral information based on the amplifiers common range"""
+    # First retrieve f_min, f_max spectrum according to amplifiers' spectrum on the path
+    common_range = find_elements_common_range(path, equipment)
+    # filter out frequencies that should not be created
+    filtered_si = []
+    for band in common_range:
+        temp = demuxed_spectral_information(si, band)
+        if temp:
+            filtered_si.append(temp)
+    if not filtered_si:
+        raise ValueError('Defined propagation band does not match amplifiers band.')
+    return muxed_spectral_information(filtered_si)
 
 
 def propagate(path, req, equipment):
-    """propagates signals in each element according to initial spectrum set by user"""
+    """propagates signals in each element according to initial spectrum set by user
+    Spectrum is specified in request through f_min, f_max and spacing, or initial_spectrum
+    and amps frequency band on the path is used to filter out frequencies"""
+    # generates spectrum based on request
     if req.initial_spectrum is not None:
-        si = carriers_to_spectral_information(initial_spectrum=req.initial_spectrum,
-                                              power=req.power, ref_carrier=ref_carrier(equipment))
+        si = carriers_to_spectral_information(initial_spectrum=req.initial_spectrum, power=req.power)
     else:
         si = create_input_spectral_information(
             f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
-            power=req.power, spacing=req.spacing, tx_osnr=req.tx_osnr, delta_pdb=req.offset_db,
-            ref_carrier=ref_carrier(equipment))
+            spacing=req.spacing, tx_osnr=req.tx_osnr, tx_power=req.tx_power, delta_pdb=req.offset_db)
+    # filter out frequencies that should not be created
+    si = filter_si(path, equipment, si)
+    roadm_osnr = []
     for i, el in enumerate(path):
         if isinstance(el, Roadm):
-            si = el(si, degree=path[i+1].uid)
+            si = el(si, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
+            roadm_osnr.append(el.get_impairment('roadm-osnr', si.frequency,
+                                                from_degree=path[i - 1].uid, degree=path[i + 1].uid))
         else:
             si = el(si)
     path[0].update_snr(si.tx_osnr)
     path[0].calc_penalties(req.penalties)
-    if any(isinstance(el, Roadm) for el in path):
-        path[-1].update_snr(si.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
-    else:
-        path[-1].update_snr(si.tx_osnr)
+    roadm_osnr.append(si.tx_osnr)
+    path[-1].update_snr(*roadm_osnr)
     path[-1].calc_penalties(req.penalties)
     return si
 
@@ -390,22 +406,26 @@ def propagate_and_optimize_mode(path, req, equipment):
                 raise ServiceError(msg)
             spc_info = create_input_spectral_information(f_min=req.f_min, f_max=req.f_max,
                                                          roll_off=equipment['SI']['default'].roll_off,
-                                                         baud_rate=this_br, power=req.power, spacing=req.spacing,
-                                                         delta_pdb=this_offset,
-                                                         tx_osnr=req.tx_osnr, ref_carrier=ref_carrier(equipment))
+                                                         baud_rate=this_br, spacing=req.spacing,
+                                                         delta_pdb=this_offset, tx_osnr=req.tx_osnr,
+                                                         tx_power=req.tx_power)
+            spc_info = filter_si(path, equipment, spc_info)
+            roadm_osnr = []
             for i, el in enumerate(path):
                 if isinstance(el, Roadm):
-                    spc_info = el(spc_info, degree=path[i+1].uid)
+                    spc_info = el(spc_info, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
+                    roadm_osnr.append(el.get_impairment('roadm-osnr', spc_info.frequency,
+                                                        from_degree=path[i - 1].uid, degree=path[i + 1].uid))
                 else:
                     spc_info = el(spc_info)
             for this_mode in modes_to_explore:
                 if path[-1].snr is not None:
                     path[0].update_snr(this_mode['tx_osnr'])
                     path[0].calc_penalties(this_mode['penalties'])
-                    if any(isinstance(el, Roadm) for el in path):
-                        path[-1].update_snr(this_mode['tx_osnr'], equipment['Roadm']['default'].add_drop_osnr)
-                    else:
-                        path[-1].update_snr(this_mode['tx_osnr'])
+                    roadm_osnr.append(this_mode['tx_osnr'])
+                    path[-1].update_snr(*roadm_osnr)
+                    # remove the tx_osnr from roadm_osnr list for the next iteration
+                    del roadm_osnr[-1]
                     path[-1].calc_penalties(this_mode['penalties'])
                     if round(min(path[-1].snr_01nm - path[-1].total_penalty), 2) \
                             > this_mode['OSNR'] + equipment['SI']['default'].sys_margins:
@@ -977,6 +997,7 @@ def compare_reqs(req1, req2, disjlist):
             req1.format == req2.format and \
             req1.OSNR == req2.OSNR and \
             req1.roll_off == req2.roll_off and \
+            req1.tx_power == req2.tx_power and \
             same_disj:
         return True
     else:
@@ -1076,7 +1097,7 @@ def deduplicate_disjunctions(disjn):
     return local_disjn
 
 
-def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
+def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist, redesign=False):
     """use a list but a dictionnary might be helpful to find path based on request_id
 
     TODO change all these req, dsjct, res lists into dict !
@@ -1085,6 +1106,10 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
     reversed_path_res_list = []
     propagated_reversed_path_res_list = []
 
+    total_nb_requests = len(pathreqlist)
+    if redesign:
+        LOGGER.warning('Redesign the network for each request channel, '
+                       + 'using the request channel as the reference channel for the design.')
     for i, pathreq in enumerate(pathreqlist):
 
         # use the power specified in requests but might be different from the one
@@ -1102,6 +1127,16 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
         # elements to simulate performance, several demands having the same destination
         # may use the same transponder for the performance simulation. This is why
         # we use deepcopy: to ensure that each propagation is recorded and not overwritten
+        # reversed path is needed for correct spectrum assignment
+        if redesign:
+            # this is the legacy case where network was automatically redesigned using the
+            # request channel as reference (nb and power used for amplifiers total power out)
+            reversed_path = []
+            if pathlist[i]:
+                reversed_path = find_reversed_path(pathlist[i])
+            network_nodes_for_redesign = pathlist[i] + reversed_path
+            network_module.design_network(pathreq, network.subgraph(network_nodes_for_redesign), equipment,
+                                          set_connector_losses=False, verbose=False)
         total_path = deepcopy(pathlist[i])
         msg = msg + f'\n\tComputed path (roadms):{[e.uid for e in total_path  if isinstance(e, Roadm)]}'
         LOGGER.info(msg)
@@ -1216,3 +1251,11 @@ def _penalty_msg(total_path, msg, min_ind):
         else:
             msg += f'\n\t{pretty} penalty not evaluated'
     return msg
+
+
+def find_elements_common_range(el_list: list, equipment: dict) -> List[dict]:
+    """Find the common frequency range of amps of a given list of elements (for example an OMS or a path)
+    If there are no amplifiers in the path, then use the SI
+    """
+    amp_bands = [n.params.bands for n in el_list if isinstance(n, (Edfa, Multiband_amplifier))]
+    return find_common_range(amp_bands, equipment['SI']['default'].f_min, equipment['SI']['default'].f_max)

gnpy/topology/spectrum_assignment.py

@@ -15,28 +15,31 @@ element/oms correspondace
 
 from collections import namedtuple
 from logging import getLogger
-from gnpy.core.elements import Roadm, Transceiver
+
+from gnpy.core.elements import Roadm, Transceiver, Edfa, Multiband_amplifier
 from gnpy.core.exceptions import ServiceError, SpectrumError
 from gnpy.core.utils import order_slots, restore_order
-from gnpy.topology.request import compute_spectrum_slot_vs_bandwidth
+from gnpy.topology.request import compute_spectrum_slot_vs_bandwidth, find_elements_common_range
 
 LOGGER = getLogger(__name__)
+GUARDBAND = 25e9
 
 
 class Bitmap:
     """records the spectrum occupation"""
 
-    def __init__(self, f_min, f_max, grid, guardband=0.15e12, bitmap=None):
-        # n is the min index including guardband. Guardband is require to be sure
+    def __init__(self, f_min, f_max, grid, guardband=GUARDBAND, bitmap=None):
+        # n is the min index including guardband. Guardband is required to be sure
         # that a channel can be assigned  with center frequency fmin (means that its
         # slot occupation goes below freq_index_min
-        n_min = frequency_to_n(f_min - guardband, grid)
-        n_max = frequency_to_n(f_max + guardband, grid) - 1
+        n_min = frequency_to_n(f_min, grid)
+        n_max = frequency_to_n(f_max, grid)
         self.n_min = n_min
         self.n_max = n_max
-        self.freq_index_min = frequency_to_n(f_min)
-        self.freq_index_max = frequency_to_n(f_max)
+        self.freq_index_min = frequency_to_n(f_min + guardband)
+        self.freq_index_max = frequency_to_n(f_max - guardband)
         self.freq_index = list(range(n_min, n_max + 1))
+        self.guardband = guardband
         if bitmap is None:
             self.bitmap = [1] * (n_max - n_min + 1)
         elif len(bitmap) == len(self.freq_index):
@@ -83,7 +86,6 @@ class OMS:
         self.spectrum_bitmap = []
         self.nb_channels = 0
         self.service_list = []
-    # TODO
 
     def __str__(self):
         return '\n\t'.join([f'{type(self).__name__} {self.oms_id}',
@@ -98,7 +100,7 @@ class OMS:
         self.el_id_list.append(elem.uid)
         self.el_list.append(elem)
 
-    def update_spectrum(self, f_min, f_max, guardband=0.15e12, existing_spectrum=None, grid=0.00625e12):
+    def update_spectrum(self, f_min, f_max, guardband=GUARDBAND, existing_spectrum=None, grid=0.00625e12):
         """Frequencies expressed in Hz.
         Add 150 GHz margin to enable a center channel on f_min
         Use ITU-T G694.1 Flexible DWDM grid definition
@@ -226,6 +228,40 @@ def align_grids(oms_list):
     return oms_list
 
 
+def find_network_freq_range(network, equipment):
+    """Find the lowest freq from amps and highest freq among all amps to determine the resulting bitmap
+    """
+    amp_bands = [band for n in network.nodes() if isinstance(n, (Edfa, Multiband_amplifier)) for band in n.params.bands]
+    min_frequencies = [a['f_min'] for a in amp_bands]
+    max_frequencies = [a['f_max'] for a in amp_bands]
+    return min(min_frequencies), max(max_frequencies)
+
+
+def create_oms_bitmap(oms, equipment, f_min, f_max, guardband, grid):
+    """Find the highest low freq from oms amps and lowest high freq among oms amps to determine
+    the possible bitmap window.
+    f_min and f_max represent the useable spectrum (not the useable center frequencies)
+    ie n smaller than frequency_to_n(min_freq, grid) are not useable
+    """
+    n_min = frequency_to_n(f_min, grid)
+    n_max = frequency_to_n(f_max, grid) - 1
+    common_range = find_elements_common_range(oms.el_list, equipment)
+    band0 = common_range[0]
+    band0_n_min = frequency_to_n(band0['f_min'], grid)
+    band0_n_max = frequency_to_n(band0['f_max'], grid)
+    bitmap = [0] * (band0_n_min - n_min) + [1] * (band0_n_max - band0_n_min + 1)
+    i = 1
+    while i < len(common_range):
+        band = common_range[i]
+        band_n_min = frequency_to_n(band['f_min'], grid)
+        band_n_max = frequency_to_n(band['f_max'], grid)
+        bitmap = bitmap + [0] * (band_n_min - band0_n_max - 1) + [1] * (band_n_max - band_n_min + 1)
+        band0_n_max = band_n_max
+        i += 1
+    bitmap = bitmap + [0] * (n_max - band0_n_max)
+    return bitmap
+
+
 def build_oms_list(network, equipment):
     """initialization of OMS list in the network
 
@@ -237,7 +273,15 @@ def build_oms_list(network, equipment):
     """
     oms_id = 0
     oms_list = []
-    for node in [n for n in network.nodes() if isinstance(n, Roadm)]:
+    # identify all vertices of OMS: of course ROADM, but aso links to external chassis transponders
+    oms_vertices = [n for n in network.nodes() if isinstance(n, Roadm)] +\
+                   [n for n in network.nodes() if isinstance(n, Transceiver)
+                    and not isinstance(next(network.successors(n)), Roadm)]
+    # determine the size of the bitmap common to all the omses: find min and max frequencies of all amps
+    # in the network. These gives the band not the center frequency. Thhen we use a reference channel
+    # slot width (50GHz) to set the f_min, f_max
+    f_min, f_max = find_network_freq_range(network, equipment)
+    for node in oms_vertices:
         for edge in network.edges([node]):
             if not isinstance(edge[1], Transceiver):
                 nd_in = edge[0]  # nd_in is a Roadm
@@ -271,8 +315,9 @@ def build_oms_list(network, equipment):
                     nd_out.oms_list = []
                     nd_out.oms_list.append(oms_id)
 
-                oms.update_spectrum(equipment['SI']['default'].f_min,
-                                    equipment['SI']['default'].f_max, grid=0.00625e12)
+                bitmap = create_oms_bitmap(oms, equipment, f_min=f_min, f_max=f_max, guardband=GUARDBAND,
+                                           grid=0.00625e12)
+                oms.update_spectrum(f_min, f_max, guardband=GUARDBAND, grid=0.00625e12, existing_spectrum=bitmap)
                 # oms.assign_spectrum(13,7) gives back (193137500000000.0, 193225000000000.0)
                 # as in the example in the standard
                 # oms.assign_spectrum(13,7)
@@ -333,10 +378,11 @@ def aggregate_oms_bitmap(path_oms, oms_list):
         'el_id_list': 0,
         'el_list': []
     }
-    freq_min = nvalue_to_frequency(spectrum.freq_index_min)
-    freq_max = nvalue_to_frequency(spectrum.freq_index_max)
+    freq_min = nvalue_to_frequency(spectrum.n_min)
+    freq_max = nvalue_to_frequency(spectrum.n_max)
     aggregate_oms = OMS(**params)
-    aggregate_oms.update_spectrum(freq_min, freq_max, grid=0.00625e12, existing_spectrum=bitmap)
+    aggregate_oms.update_spectrum(freq_min, freq_max, grid=0.00625e12, guardband=spectrum.guardband,
+                                  existing_spectrum=bitmap)
     return aggregate_oms
 
 

requirements.txt

@@ -1,11 +0,0 @@
-# matplotlib 3.8 removed support for Python 3.8
-matplotlib>=3.7.3,<4
-# networkx 3.2 removed support for Python 3.8
-networkx>=3.1,<4
-# numpy 1.25 removed support for Python 3.8
-numpy>=1.24.4,<2
-pbr>=6.0.0,<7
-# scipy 1.11 removed support for Python 3.8
-scipy>=1.10.1,<2
-# xlrd 2.x removed support for .xlsx, it's only .xls now
-xlrd>=1.2.0,<2

setup.cfg

@@ -49,3 +49,35 @@ console_scripts =
     gnpy-transmission-example = gnpy.tools.cli_examples:transmission_main_example
     gnpy-path-request = gnpy.tools.cli_examples:path_requests_run
     gnpy-convert-xls = gnpy.tools.convert:_do_convert
+
+[options]
+install_requires =
+	# matplotlib 3.8 removed support for Python 3.8
+	matplotlib>=3.7.3,<4
+	# networkx 3.2 removed support for Python 3.8
+	networkx>=3.1,<4
+	# numpy 1.25 removed support for Python 3.8
+	numpy>=1.24.4,<2
+	pbr>=6.0.0,<7
+	# scipy 1.11 removed support for Python 3.8
+	scipy>=1.10.1,<2
+	# xlrd 2.x removed support for .xlsx, it's only .xls now
+	xlrd>=1.2.0,<2
+
+[options.extras_require]
+tests =
+	build>=1.0.3,<2
+	pytest>=7.4.3,<8
+	# pandas 2.1 removed support for Python 3.8
+	pandas>=2.0.3,<3
+	# flake v6 killed the --diff option
+	flake8>=5.0.4,<6
+
+docs =
+	alabaster>=0.7.12,<1
+	docutils>=0.17.1,<1
+	myst-parser>=0.16.1,<1
+	Pygments>=2.11.2,<3
+	rstcheck
+	Sphinx>=5.3.0,<6
+	sphinxcontrib-bibtex>=2.4.1,<3

tests/data/CORONET_Global_Topology_auto_design_expected.json

@@ -1203,6 +1203,7 @@
     {
       "uid": "roadm Abilene",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1226,6 +1227,7 @@
     {
       "uid": "roadm Albany",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1249,6 +1251,7 @@
     {
       "uid": "roadm Albuquerque",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1274,6 +1277,7 @@
     {
       "uid": "roadm Atlanta",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1298,6 +1302,7 @@
     {
       "uid": "roadm Austin",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1321,6 +1326,7 @@
     {
       "uid": "roadm Baltimore",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1345,6 +1351,7 @@
     {
       "uid": "roadm Baton_Rouge",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1368,6 +1375,7 @@
     {
       "uid": "roadm Billings",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1392,6 +1400,7 @@
     {
       "uid": "roadm Birmingham",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1416,6 +1425,7 @@
     {
       "uid": "roadm Bismarck",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1439,6 +1449,7 @@
     {
       "uid": "roadm Boston",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1462,6 +1473,7 @@
     {
       "uid": "roadm Buffalo",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1485,6 +1497,7 @@
     {
       "uid": "roadm Charleston",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1508,6 +1521,7 @@
     {
       "uid": "roadm Charlotte",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1531,6 +1545,7 @@
     {
       "uid": "roadm Chicago",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1555,6 +1570,7 @@
     {
       "uid": "roadm Cincinnati",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1579,6 +1595,7 @@
     {
       "uid": "roadm Cleveland",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1603,6 +1620,7 @@
     {
       "uid": "roadm Columbus",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1627,6 +1645,7 @@
     {
       "uid": "roadm Dallas",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1653,6 +1672,7 @@
     {
       "uid": "roadm Denver",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1678,6 +1698,7 @@
     {
       "uid": "roadm Detroit",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1701,6 +1722,7 @@
     {
       "uid": "roadm El_Paso",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1726,6 +1748,7 @@
     {
       "uid": "roadm Fresno",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1750,6 +1773,7 @@
     {
       "uid": "roadm Greensboro",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1775,6 +1799,7 @@
     {
       "uid": "roadm Hartford",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1798,6 +1823,7 @@
     {
       "uid": "roadm Houston",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1822,6 +1848,7 @@
     {
       "uid": "roadm Jacksonville",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1846,6 +1873,7 @@
     {
       "uid": "roadm Kansas_City",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1870,6 +1898,7 @@
     {
       "uid": "roadm Las_Vegas",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1895,6 +1924,7 @@
     {
       "uid": "roadm Little_Rock",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1918,6 +1948,7 @@
     {
       "uid": "roadm Long_Island",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1941,6 +1972,7 @@
     {
       "uid": "roadm Los_Angeles",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1966,6 +1998,7 @@
     {
       "uid": "roadm Louisville",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1991,6 +2024,7 @@
     {
       "uid": "roadm Memphis",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2014,6 +2048,7 @@
     {
       "uid": "roadm Miami",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2038,6 +2073,7 @@
     {
       "uid": "roadm Milwaukee",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2061,6 +2097,7 @@
     {
       "uid": "roadm Minneapolis",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2085,6 +2122,7 @@
     {
       "uid": "roadm Nashville",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2109,6 +2147,7 @@
     {
       "uid": "roadm New_Orleans",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2133,6 +2172,7 @@
     {
       "uid": "roadm New_York",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2159,6 +2199,7 @@
     {
       "uid": "roadm Newark",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2182,6 +2223,7 @@
     {
       "uid": "roadm Norfolk",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2205,6 +2247,7 @@
     {
       "uid": "roadm Oakland",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2231,6 +2274,7 @@
     {
       "uid": "roadm Oklahoma_City",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2254,6 +2298,7 @@
     {
       "uid": "roadm Omaha",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2278,6 +2323,7 @@
     {
       "uid": "roadm Orlando",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2301,6 +2347,7 @@
     {
       "uid": "roadm Philadelphia",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2325,6 +2372,7 @@
     {
       "uid": "roadm Phoenix",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2349,6 +2397,7 @@
     {
       "uid": "roadm Pittsburgh",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2373,6 +2422,7 @@
     {
       "uid": "roadm Portland",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2398,6 +2448,7 @@
     {
       "uid": "roadm Providence",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2421,6 +2472,7 @@
     {
       "uid": "roadm Raleigh",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2445,6 +2497,7 @@
     {
       "uid": "roadm Richmond",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2468,6 +2521,7 @@
     {
       "uid": "roadm Rochester",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2491,6 +2545,7 @@
     {
       "uid": "roadm Sacramento",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2514,6 +2569,7 @@
     {
       "uid": "roadm Salt_Lake_City",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2539,6 +2595,7 @@
     {
       "uid": "roadm San_Antonio",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2562,6 +2619,7 @@
     {
       "uid": "roadm San_Diego",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2585,6 +2643,7 @@
     {
       "uid": "roadm San_Francisco",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2608,6 +2667,7 @@
     {
       "uid": "roadm San_Jose",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2631,6 +2691,7 @@
     {
       "uid": "roadm Santa_Barbara",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2654,6 +2715,7 @@
     {
       "uid": "roadm Scranton",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2679,6 +2741,7 @@
     {
       "uid": "roadm Seattle",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2702,6 +2765,7 @@
     {
       "uid": "roadm Spokane",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2725,6 +2789,7 @@
     {
       "uid": "roadm Springfield",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2748,6 +2813,7 @@
     {
       "uid": "roadm St_Louis",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2772,6 +2838,7 @@
     {
       "uid": "roadm Syracuse",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2796,6 +2863,7 @@
     {
       "uid": "roadm Tallahassee",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2819,6 +2887,7 @@
     {
       "uid": "roadm Tampa",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2842,6 +2911,7 @@
     {
       "uid": "roadm Toledo",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2865,6 +2935,7 @@
     {
       "uid": "roadm Tucson",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2888,6 +2959,7 @@
     {
       "uid": "roadm Tulsa",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2911,6 +2983,7 @@
     {
       "uid": "roadm Washington_DC",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2936,6 +3009,7 @@
     {
       "uid": "roadm West_Palm_Beach",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2959,6 +3033,7 @@
     {
       "uid": "roadm Wilmington",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -2982,6 +3057,7 @@
     {
       "uid": "roadm Amsterdam",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3007,6 +3083,7 @@
     {
       "uid": "roadm Berlin",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3030,6 +3107,7 @@
     {
       "uid": "roadm Brussels",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3053,6 +3131,7 @@
     {
       "uid": "roadm Bucharest",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3076,6 +3155,7 @@
     {
       "uid": "roadm Frankfurt",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3099,6 +3179,7 @@
     {
       "uid": "roadm Istanbul",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3123,6 +3204,7 @@
     {
       "uid": "roadm London",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3147,6 +3229,7 @@
     {
       "uid": "roadm Madrid",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3170,6 +3253,7 @@
     {
       "uid": "roadm Paris",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3194,6 +3278,7 @@
     {
       "uid": "roadm Rome",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3219,6 +3304,7 @@
     {
       "uid": "roadm Vienna",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3243,6 +3329,7 @@
     {
       "uid": "roadm Warsaw",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3267,6 +3354,7 @@
     {
       "uid": "roadm Zurich",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3290,6 +3378,7 @@
     {
       "uid": "roadm Bangkok",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3313,6 +3402,7 @@
     {
       "uid": "roadm Beijing",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3336,6 +3426,7 @@
     {
       "uid": "roadm Delhi",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3360,6 +3451,7 @@
     {
       "uid": "roadm Hong_Kong",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3385,6 +3477,7 @@
     {
       "uid": "roadm Honolulu",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3409,6 +3502,7 @@
     {
       "uid": "roadm Mumbai",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3433,6 +3527,7 @@
     {
       "uid": "roadm Seoul",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3456,6 +3551,7 @@
     {
       "uid": "roadm Shanghai",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3479,6 +3575,7 @@
     {
       "uid": "roadm Singapore",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3502,6 +3599,7 @@
     {
       "uid": "roadm Sydney",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3526,6 +3624,7 @@
     {
       "uid": "roadm Taipei",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -3551,6 +3650,7 @@
     {
       "uid": "roadm Tokyo",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -83375,7 +83475,7 @@
       "type": "Edfa",
       "type_variety": "std_medium_gain",
       "operational": {
-        "gain_target": 28.5006,
+        "gain_target": 28.5,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -88752,7 +88852,7 @@
       "type": "Edfa",
       "type_variety": "std_medium_gain",
       "operational": {
-        "gain_target": 28.5032,
+        "gain_target": 28.5,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -89037,7 +89137,7 @@
       "type": "Edfa",
       "type_variety": "std_medium_gain",
       "operational": {
-        "gain_target": 28.5006,
+        "gain_target": 28.5,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -89721,7 +89821,7 @@
       "type": "Edfa",
       "type_variety": "std_medium_gain",
       "operational": {
-        "gain_target": 28.502,
+        "gain_target": 28.5,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -89797,7 +89897,7 @@
       "type": "Edfa",
       "type_variety": "std_medium_gain",
       "operational": {
-        "gain_target": 28.502,
+        "gain_target": 28.5,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -89911,7 +90011,7 @@
       "type": "Edfa",
       "type_variety": "std_medium_gain",
       "operational": {
-        "gain_target": 28.5032,
+        "gain_target": 28.5,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0

tests/data/default_edfa_config.json

@@ -1,4 +1,6 @@
 {
+    "f_min": 191.275e12,
+    "f_max": 196.125e12,
     "nf_ripple": [
         0.0,
         0.0,

tests/data/eqpt_config.json

@@ -1,4 +1,5 @@
-{     "Edfa":[{
+{
+    "Edfa": [{
             "type_variety": "CienaDB_medium_gain",
             "type_def": "advanced_model",
             "gain_flatmax": 25,
@@ -7,8 +8,7 @@
             "advanced_config_from_json": "std_medium_gain_advanced_config.json",
             "out_voa_auto": false,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "std_medium_gain",
             "type_def": "variable_gain",
             "gain_flatmax": 26,
@@ -18,8 +18,7 @@
             "nf_max": 10,
             "out_voa_auto": false,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "std_low_gain",
             "type_def": "variable_gain",
             "gain_flatmax": 16,
@@ -29,8 +28,7 @@
             "nf_max": 11,
             "out_voa_auto": false,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "test",
             "type_def": "variable_gain",
             "gain_flatmax": 25,
@@ -40,8 +38,7 @@
             "nf_max": 10,
             "out_voa_auto": false,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "test_fixed_gain",
             "type_def": "fixed_gain",
             "gain_flatmax": 21,
@@ -49,8 +46,7 @@
             "p_max": 21,
             "nf0": 5,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "std_booster",
             "type_def": "fixed_gain",
             "gain_flatmax": 21,
@@ -60,16 +56,16 @@
             "allowed_for_design": false
         }
     ],
-      "Fiber":[{
+    "Fiber": [{
             "type_variety": "SSMF",
             "dispersion": 1.67e-05,
             "effective_area": 83e-12,
             "pmd_coef": 1.265e-15
         }
     ],
-      "Span":[{
-            "power_mode":true,
-            "delta_power_range_db": [0,0,0.5],
+    "Span": [{
+            "power_mode": true,
+            "delta_power_range_db": [0, 0, 0.5],
             "max_fiber_lineic_loss_for_raman": 0.25,
             "target_extended_gain": 2.5,
             "max_length": 150,
@@ -81,23 +77,111 @@
             "con_out": 0
         }
     ],
-      "Roadm":[{
+    "Roadm": [{
+            "type_variety": "example_test",
+            "target_pch_out_db": -18,
+            "add_drop_osnr": 35,
+            "pmd": 1e-12,
+            "pdl": 0.5,
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            },
+            "roadm-path-impairments": []
+        }, {
+            "type_variety": "example_detailed_impairments",
             "target_pch_out_db": -20,
-            "add_drop_osnr": 38,
+            "add_drop_osnr": 35,
             "pmd": 0,
             "pdl": 0,
             "restrictions": {
                 "preamp_variety_list":[],
                 "booster_variety_list":[]
+                            },
+            "roadm-path-impairments": [
+                  {
+                    "roadm-path-impairments-id": 0,
+                    "roadm-express-path": [{
+                        "frequency-range": {
+                            "lower-frequency": 191.3e12,
+                            "upper-frequency": 196.1e12
+                            },
+                        "roadm-pmd": 0,
+                        "roadm-cd": 0,
+                        "roadm-pdl": 0,
+                        "roadm-inband-crosstalk": 0,
+                        "roadm-maxloss": 16.5
                         }
-            }],
-      "SI":[{
+                    ]
+                }, {
+                    "roadm-path-impairments-id": 1,
+                    "roadm-add-path": [{
+                        "frequency-range": {
+                            "lower-frequency": 191.3e12,
+                            "upper-frequency": 196.1e12
+                        },
+                        "roadm-pmd": 0,
+                        "roadm-cd": 0,
+                        "roadm-pdl": 0,
+                        "roadm-inband-crosstalk": 0,
+                        "roadm-maxloss": 11.5,
+                        "roadm-pmax": 2.5,
+                        "roadm-osnr": 41,
+                        "roadm-noise-figure": 23
+                    }, {
+                        "frequency-range": {
+                            "lower-frequency": 186.3e12,
+                            "upper-frequency": 190.1e12
+                        },
+                        "roadm-pmd": 0,
+                        "roadm-cd": 0,
+                        "roadm-pdl": 0.5,
+                        "roadm-inband-crosstalk": 0,
+                        "roadm-maxloss": 5,
+                        "roadm-pmax": 0,
+                        "roadm-osnr": 35,
+                        "roadm-noise-figure": 6
+                    }]
+                }, {
+                    "roadm-path-impairments-id": 2,
+                    "roadm-drop-path": [{
+                        "frequency-range": {
+                            "lower-frequency": 191.3e12,
+                            "upper-frequency": 196.1e12
+                            },
+                        "roadm-pmd": 0,
+                        "roadm-cd": 0,
+                        "roadm-pdl": 0,
+                        "roadm-inband-crosstalk": 0,
+                        "roadm-maxloss": 11.5,
+                        "roadm-minloss": 7.5,
+                        "roadm-typloss": 10,
+                        "roadm-pmin": -13.5,
+                        "roadm-pmax": -9.5,
+                        "roadm-ptyp": -12,
+                        "roadm-osnr": 41,
+                        "roadm-noise-figure": 15
+                    }]
+                }]
+        }, {
+            "target_pch_out_db": -20,
+            "add_drop_osnr": 38,
+            "pmd": 0,
+            "pdl": 0,
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            }
+        }
+    ],
+    "SI": [{
+            "type_variety": "default",
             "f_min": 191.3e12,
-            "f_max":196.1e12,
+            "f_max": 196.1e12,
             "baud_rate": 32e9,
             "spacing": 50e9,
             "power_dbm": 0,
-            "power_range_db": [0,0,0.5],
+            "power_range_db": [0, 0, 0.5],
             "roll_off": 0.15,
             "tx_osnr": 100,
             "sys_margins": 0
@@ -105,12 +189,11 @@
       "Transceiver":[
             {
             "type_variety": "vendorA_trx-type1",
-            "frequency":{
+            "frequency": {
                 "min": 191.35e12,
                 "max": 196.1e12
             },
-            "mode":[
-                       {
+            "mode": [{
                     "format": "PS_SP64_1",
                     "baud_rate": 32e9,
                     "OSNR": 11,
@@ -118,9 +201,8 @@
                     "roll_off": 0.15,
                     "tx_osnr": 100,
                     "min_spacing": 50e9,
-                       "cost":1
-                       },
-                       {
+                    "cost": 1
+                }, {
                     "format": "PS_SP64_2",
                     "baud_rate": 64e9,
                     "OSNR": 15,
@@ -128,9 +210,8 @@
                     "roll_off": 0.15,
                     "tx_osnr": 100,
                     "min_spacing": 75e9,
-                       "cost":1                       
-                       },
-                       {
+                    "cost": 1
+                }, {
                     "format": "mode 1",
                     "baud_rate": 32e9,
                     "OSNR": 11,
@@ -138,9 +219,8 @@
                     "roll_off": 0.15,
                     "tx_osnr": 100,
                     "min_spacing": 50e9,
-                       "cost":1
-                       },
-                       {
+                    "cost": 1
+                }, {
                     "format": "mode 2",
                     "baud_rate": 64e9,
                     "OSNR": 15,
@@ -148,18 +228,16 @@
                     "roll_off": 0.15,
                     "tx_osnr": 100,
                     "min_spacing": 75e9,
-                       "cost":1                       
+                    "cost": 1
                 }
             ]
-            },
-            {
+        }, {
             "type_variety": "Voyager_16QAM",
-            "frequency":{
+            "frequency": {
                 "min": 191.35e12,
                 "max": 196.1e12
             },
-            "mode":[
-                       {
+            "mode": [{
                     "format": "16QAM",
                     "baud_rate": 32e9,
                     "OSNR": 19,
@@ -167,18 +245,16 @@
                     "roll_off": 0.15,
                     "tx_osnr": 100,
                     "min_spacing": 50e9,
-                       "cost":1
+                    "cost": 1
                 }
             ]
-            },
-            {
+        }, {
             "type_variety": "Voyager",
-            "frequency":{
+            "frequency": {
                 "min": 191.35e12,
                 "max": 196.1e12
             },
-            "mode":[
-                       {
+            "mode": [{
                     "format": "mode 1",
                     "baud_rate": 32e9,
                     "OSNR": 12,
@@ -186,9 +262,8 @@
                     "roll_off": 0.15,
                     "tx_osnr": 45,
                     "min_spacing": 50e9,
-                       "cost":1
-                       },
-                       {
+                    "cost": 1
+                }, {
                     "format": "mode 3",
                     "baud_rate": 44e9,
                     "OSNR": 18,
@@ -196,9 +271,8 @@
                     "roll_off": 0.15,
                     "tx_osnr": 45,
                     "min_spacing": 62.5e9,
-                       "cost":1
-                       },
-                       {
+                    "cost": 1
+                }, {
                     "format": "mode 2",
                     "baud_rate": 66e9,
                     "OSNR": 21,
@@ -206,9 +280,8 @@
                     "roll_off": 0.15,
                     "tx_osnr": 45,
                     "min_spacing": 75e9,
-                       "cost":1
-                       },
-                       {
+                    "cost": 1
+                }, {
                     "format": "mode 2 - fake",
                     "baud_rate": 66e9,
                     "OSNR": 21,
@@ -216,9 +289,8 @@
                     "roll_off": 0.15,
                     "tx_osnr": 45,
                     "min_spacing": 75e9,
-                       "cost":1
-                       },
-                       {
+                    "cost": 1
+                }, {
                     "format": "mode 4",
                     "baud_rate": 66e9,
                     "OSNR": 16,
@@ -226,10 +298,9 @@
                     "roll_off": 0.15,
                     "tx_osnr": 45,
                     "min_spacing": 75e9,
-                       "cost":1
+                    "cost": 1
                 }
             ]
         }
     ]
-
 }

tests/data/eqpt_config_multiband.json

@@ -0,0 +1,396 @@
+{     "Edfa":[{
+            "type_variety": "CienaDB_medium_gain",
+            "type_def": "advanced_model",
+            "gain_flatmax": 25,
+            "gain_min": 15,
+            "p_max": 21,
+            "advanced_config_from_json": "std_medium_gain_advanced_config.json",
+            "out_voa_auto": false,
+            "allowed_for_design": true
+            },
+            {
+            "type_variety": "std_medium_gain",
+            "f_min": 191.25e12,
+            "f_max": 196.15e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+            },
+            {
+            "type_variety": "std_medium_gain_L",
+            "f_min": 186.55e12,
+            "f_max": 190.05e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+            },
+            {
+            "type_variety": "std_low_gain",
+            "f_min": 191.25e12,
+            "f_max": 196.15e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+            "type_variety": "std_low_gain_reduced_band",
+            "f_min": 192.25e12,
+            "f_max": 196.15e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+        {
+        "type_variety": "std_low_gain_reduced",
+        "f_min": 192.25e12,
+        "f_max": 196.15e12,
+        "type_def": "variable_gain",
+        "gain_flatmax": 16,
+        "gain_min": 8,
+        "p_max": 21,
+        "nf_min": 7,
+        "nf_max": 11,
+        "out_voa_auto": false,
+        "allowed_for_design": true
+    },
+		{
+            "type_variety": "std_low_gain_bis",
+            "f_min": 191.25e12,
+            "f_max": 196.15e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_low_gain_L_ter",
+            "f_min": 186.55e12,
+            "f_max": 190.05e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 16,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        },
+		{
+            "type_variety": "std_low_gain_L",
+            "f_min": 186.55e12,
+            "f_max": 190.05e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+            },
+            {
+                "type_variety": "std_low_gain_L_reduced_band",
+                "f_min": 187.3e12,
+                "f_max": 190.05e12,
+                "type_def": "variable_gain",
+                "gain_flatmax": 16,
+                "gain_min": 8,
+                "p_max": 21,
+                "nf_min": 7,
+                "nf_max": 11,
+                "out_voa_auto": false,
+                "allowed_for_design": true
+                },
+            {
+            "type_variety": "test",
+            "type_def": "variable_gain",
+            "gain_flatmax": 25,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 5.8,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+            },
+            {
+            "type_variety": "test_fixed_gain",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": true
+            },
+            {
+            "type_variety": "std_booster",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": false
+                    }, {
+            "type_variety": "std_booster_L",
+            "f_min": 186.55e12,
+            "f_max": 190.05e12,
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": false
+        }, {
+            "type_variety": "std_booster_multiband",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_booster",
+                "std_booster_L"
+            ],
+            "allowed_for_design": false
+        }, {
+            "type_variety": "std_medium_gain_multiband",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_medium_gain",
+                "std_medium_gain_L"
+            ],
+            "allowed_for_design": true
+            },
+            {
+            "type_variety": "std_low_gain_multiband",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain",
+                "std_low_gain_L"
+            ],
+            "allowed_for_design": false
+        }, {
+            "type_variety": "std_low_gain_multiband_ter",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain",
+                "std_low_gain_L_ter"
+            ],
+            "allowed_for_design": false
+        }, {
+            "type_variety": "std_low_gain_multiband_bis",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain_bis",
+                "std_low_gain_L"
+            ],
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_low_gain_multiband_reduced_bis",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain_reduced",
+                "std_low_gain_L"
+            ],
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_low_gain_multiband_reduced",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_low_gain_bis",
+                "std_low_gain_L_reduced_band"
+            ],
+            "allowed_for_design": true
+        }
+      ],
+      "Fiber":[{
+            "type_variety": "SSMF",
+            "dispersion": 1.67e-05,
+            "effective_area": 83e-12,
+            "pmd_coef": 1.265e-15
+            }
+      ],
+      "Span":[{
+            "power_mode":true,
+            "delta_power_range_db": [0,0,0.5],
+            "max_fiber_lineic_loss_for_raman": 0.25,
+            "target_extended_gain": 2.5,
+            "max_length": 150,
+            "length_units": "km",
+            "max_loss": 28,
+            "padding": 10,
+            "EOL": 0,
+            "con_in": 0,
+            "con_out": 0
+            }
+      ],
+      "Roadm":[{
+            "target_pch_out_db": -20,
+            "add_drop_osnr": 38,
+            "pmd": 0,
+            "pdl": 0,
+            "restrictions": {
+                            "preamp_variety_list":[],
+                            "booster_variety_list":[]
+                            }
+            }],
+      "SI":[{
+            "f_min": 191.3e12,
+            "f_max":196.1e12,
+            "baud_rate": 32e9,
+            "spacing": 50e9,
+            "power_dbm": 0,
+            "power_range_db": [0,0,0.5],
+            "roll_off": 0.15,
+            "tx_osnr": 100,
+            "sys_margins": 0
+            }],
+      "Transceiver":[
+            {
+            "type_variety": "vendorA_trx-type1",
+            "frequency":{
+                        "min": 191.35e12,
+                        "max": 196.1e12
+                        },
+            "mode":[
+                       {
+                       "format": "PS_SP64_1",
+                       "baud_rate": 32e9,
+                       "OSNR": 11,
+                       "bit_rate": 100e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 100,
+                       "min_spacing": 50e9,
+                       "cost":1
+                       },
+                       {
+                       "format": "PS_SP64_2",
+                       "baud_rate": 64e9,
+                       "OSNR": 15,
+                       "bit_rate": 200e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 100,
+                       "min_spacing": 75e9,
+                       "cost":1
+                       },
+                       {
+                       "format": "mode 1",
+                       "baud_rate": 32e9,
+                       "OSNR": 11,
+                       "bit_rate": 100e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 100,
+                       "min_spacing": 50e9,
+                       "cost":1
+                       },
+                       {
+                       "format": "mode 2",
+                       "baud_rate": 64e9,
+                       "OSNR": 15,
+                       "bit_rate": 200e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 100,
+                       "min_spacing": 75e9,
+                       "cost":1
+                       }
+                   ]
+            },
+            {
+            "type_variety": "Voyager_16QAM",
+            "frequency":{
+                        "min": 191.35e12,
+                        "max": 196.1e12
+                        },
+            "mode":[
+                       {
+                       "format": "16QAM",
+                       "baud_rate": 32e9,
+                       "OSNR": 19,
+                       "bit_rate": 200e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 100,
+                       "min_spacing": 50e9,
+                       "cost":1
+                       }
+                   ]
+            },
+            {
+            "type_variety": "Voyager",
+            "frequency":{
+                        "min": 191.35e12,
+                        "max": 196.1e12
+                        },
+            "mode":[
+                       {
+                       "format": "mode 1",
+                       "baud_rate": 32e9,
+                       "OSNR": 12,
+                       "bit_rate": 100e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 45,
+                       "min_spacing": 50e9,
+                       "cost":1
+                       },
+                       {
+                       "format": "mode 3",
+                       "baud_rate": 44e9,
+                       "OSNR": 18,
+                       "bit_rate": 300e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 45,
+                       "min_spacing": 62.5e9,
+                       "cost":1
+                       },
+                       {
+                       "format": "mode 2",
+                       "baud_rate": 66e9,
+                       "OSNR": 21,
+                       "bit_rate": 400e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 45,
+                       "min_spacing": 75e9,
+                       "cost":1
+                       },
+                       {
+                       "format": "mode 2 - fake",
+                       "baud_rate": 66e9,
+                       "OSNR": 21,
+                       "bit_rate": 400e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 45,
+                       "min_spacing": 75e9,
+                       "cost":1
+                       },
+                       {
+                       "format": "mode 4",
+                       "baud_rate": 66e9,
+                       "OSNR": 16,
+                       "bit_rate": 200e9,
+                       "roll_off": 0.15,
+                       "tx_osnr": 45,
+                       "min_spacing": 75e9,
+                       "cost":1
+                       }
+                   ]
+            }
+      ]
+
+}

tests/data/eqpt_config_psd.json

@@ -0,0 +1,220 @@
+{
+    "Edfa": [{
+            "type_variety": "CienaDB_medium_gain",
+            "type_def": "advanced_model",
+            "gain_flatmax": 25,
+            "gain_min": 15,
+            "p_max": 21,
+            "advanced_config_from_json": "std_medium_gain_advanced_config.json",
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_medium_gain",
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_low_gain",
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "test",
+            "type_def": "variable_gain",
+            "gain_flatmax": 25,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 5.8,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "test_fixed_gain",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_booster",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": false
+        }
+    ],
+    "Fiber": [{
+            "type_variety": "SSMF",
+            "dispersion": 1.67e-05,
+            "effective_area": 83e-12,
+            "pmd_coef": 1.265e-15
+        }
+    ],
+    "Span": [{
+            "power_mode": true,
+            "delta_power_range_db": [0, 0, 0.5],
+            "max_fiber_lineic_loss_for_raman": 0.25,
+            "target_extended_gain": 2.5,
+            "max_length": 150,
+            "length_units": "km",
+            "max_loss": 28,
+            "padding": 10,
+            "EOL": 0,
+            "con_in": 0,
+            "con_out": 0
+        }
+    ],
+    "Roadm": [{
+            "target_psd_out_mWperGHz": 3.125e-4,
+            "add_drop_osnr": 38,
+            "pmd": 0,
+            "pdl": 0,
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            }
+        }
+    ],
+    "SI": [{
+            "f_min": 191.35e12,
+            "f_max": 196.1e12,
+            "baud_rate": 32e9,
+            "spacing": 50e9,
+            "power_dbm": 0,
+            "power_range_db": [0, 0, 0.5],
+            "roll_off": 0.15,
+            "tx_osnr": 100,
+            "sys_margins": 0
+        }
+    ],
+    "Transceiver": [{
+            "type_variety": "vendorA_trx-type1",
+            "frequency": {
+                "min": 191.4e12,
+                "max": 196.1e12
+            },
+            "mode": [{
+                    "format": "PS_SP64_1",
+                    "baud_rate": 32e9,
+                    "OSNR": 11,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "PS_SP64_2",
+                    "baud_rate": 64e9,
+                    "OSNR": 15,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 1",
+                    "baud_rate": 32e9,
+                    "OSNR": 11,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2",
+                    "baud_rate": 64e9,
+                    "OSNR": 15,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }
+            ]
+        }, {
+            "type_variety": "Voyager_16QAM",
+            "frequency": {
+                "min": 191.4e12,
+                "max": 196.1e12
+            },
+            "mode": [{
+                    "format": "16QAM",
+                    "baud_rate": 32e9,
+                    "OSNR": 19,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }
+            ]
+        }, {
+            "type_variety": "Voyager",
+            "frequency": {
+                "min": 191.4e12,
+                "max": 196.1e12
+            },
+            "mode": [{
+                    "format": "mode 1",
+                    "baud_rate": 32e9,
+                    "OSNR": 12,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 3",
+                    "baud_rate": 44e9,
+                    "OSNR": 18,
+                    "bit_rate": 300e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 62.5e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2",
+                    "baud_rate": 66e9,
+                    "OSNR": 21,
+                    "bit_rate": 400e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2 - fake",
+                    "baud_rate": 66e9,
+                    "OSNR": 21,
+                    "bit_rate": 400e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 4",
+                    "baud_rate": 66e9,
+                    "OSNR": 16,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }
+            ]
+        }
+    ]
+
+}

tests/data/eqpt_config_psw.json

@@ -0,0 +1,220 @@
+{
+    "Edfa": [{
+            "type_variety": "CienaDB_medium_gain",
+            "type_def": "advanced_model",
+            "gain_flatmax": 25,
+            "gain_min": 15,
+            "p_max": 21,
+            "advanced_config_from_json": "std_medium_gain_advanced_config.json",
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_medium_gain",
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_low_gain",
+            "type_def": "variable_gain",
+            "gain_flatmax": 16,
+            "gain_min": 8,
+            "p_max": 21,
+            "nf_min": 7,
+            "nf_max": 11,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "test",
+            "type_def": "variable_gain",
+            "gain_flatmax": 25,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 5.8,
+            "nf_max": 10,
+            "out_voa_auto": false,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "test_fixed_gain",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": true
+        }, {
+            "type_variety": "std_booster",
+            "type_def": "fixed_gain",
+            "gain_flatmax": 21,
+            "gain_min": 20,
+            "p_max": 21,
+            "nf0": 5,
+            "allowed_for_design": false
+        }
+    ],
+    "Fiber": [{
+            "type_variety": "SSMF",
+            "dispersion": 1.67e-05,
+            "effective_area": 83e-12,
+            "pmd_coef": 1.265e-15
+        }
+    ],
+    "Span": [{
+            "power_mode": true,
+            "delta_power_range_db": [0, 0, 0.5],
+            "max_fiber_lineic_loss_for_raman": 0.25,
+            "target_extended_gain": 2.5,
+            "max_length": 150,
+            "length_units": "km",
+            "max_loss": 28,
+            "padding": 10,
+            "EOL": 0,
+            "con_in": 0,
+            "con_out": 0
+        }
+    ],
+    "Roadm": [{
+            "target_out_mWperSlotWidth": 2.0e-4,
+            "add_drop_osnr": 38,
+            "pmd": 0,
+            "pdl": 0,
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            }
+        }
+    ],
+    "SI": [{
+            "f_min": 191.35e12,
+            "f_max": 196.1e12,
+            "baud_rate": 32e9,
+            "spacing": 50e9,
+            "power_dbm": 0,
+            "power_range_db": [0, 0, 0.5],
+            "roll_off": 0.15,
+            "tx_osnr": 100,
+            "sys_margins": 0
+        }
+    ],
+    "Transceiver": [{
+            "type_variety": "vendorA_trx-type1",
+            "frequency": {
+                "min": 191.4e12,
+                "max": 196.1e12
+            },
+            "mode": [{
+                    "format": "PS_SP64_1",
+                    "baud_rate": 32e9,
+                    "OSNR": 11,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "PS_SP64_2",
+                    "baud_rate": 64e9,
+                    "OSNR": 15,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 1",
+                    "baud_rate": 32e9,
+                    "OSNR": 11,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2",
+                    "baud_rate": 64e9,
+                    "OSNR": 15,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }
+            ]
+        }, {
+            "type_variety": "Voyager_16QAM",
+            "frequency": {
+                "min": 191.4e12,
+                "max": 196.1e12
+            },
+            "mode": [{
+                    "format": "16QAM",
+                    "baud_rate": 32e9,
+                    "OSNR": 19,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }
+            ]
+        }, {
+            "type_variety": "Voyager",
+            "frequency": {
+                "min": 191.4e12,
+                "max": 196.1e12
+            },
+            "mode": [{
+                    "format": "mode 1",
+                    "baud_rate": 32e9,
+                    "OSNR": 12,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 3",
+                    "baud_rate": 44e9,
+                    "OSNR": 18,
+                    "bit_rate": 300e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 62.5e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2",
+                    "baud_rate": 66e9,
+                    "OSNR": 21,
+                    "bit_rate": 400e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2 - fake",
+                    "baud_rate": 66e9,
+                    "OSNR": 21,
+                    "bit_rate": 400e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 4",
+                    "baud_rate": 66e9,
+                    "OSNR": 16,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }
+            ]
+        }
+    ]
+
+}

tests/data/eqpt_config_sweep.json

@@ -0,0 +1,238 @@
+{
+      "Edfa": [{
+                  "type_variety": "CienaDB_medium_gain",
+                  "type_def": "advanced_model",
+                  "gain_flatmax": 25,
+                  "gain_min": 15,
+                  "p_max": 21,
+                  "advanced_config_from_json": "std_medium_gain_advanced_config.json",
+                  "out_voa_auto": false,
+                  "allowed_for_design": true
+            },
+            {
+                  "type_variety": "std_medium_gain",
+                  "type_def": "variable_gain",
+                  "gain_flatmax": 26,
+                  "gain_min": 15,
+                  "p_max": 21,
+                  "nf_min": 6,
+                  "nf_max": 10,
+                  "out_voa_auto": false,
+                  "allowed_for_design": true
+            },
+            {
+                  "type_variety": "std_low_gain",
+                  "type_def": "variable_gain",
+                  "gain_flatmax": 16,
+                  "gain_min": 8,
+                  "p_max": 21,
+                  "nf_min": 7,
+                  "nf_max": 11,
+                  "out_voa_auto": false,
+                  "allowed_for_design": true
+            },
+            {
+                  "type_variety": "test",
+                  "type_def": "variable_gain",
+                  "gain_flatmax": 25,
+                  "gain_min": 15,
+                  "p_max": 21,
+                  "nf_min": 5.8,
+                  "nf_max": 10,
+                  "out_voa_auto": false,
+                  "allowed_for_design": true
+            },
+            {
+                  "type_variety": "test_fixed_gain",
+                  "type_def": "fixed_gain",
+                  "gain_flatmax": 21,
+                  "gain_min": 20,
+                  "p_max": 21,
+                  "nf0": 5,
+                  "allowed_for_design": true
+            },
+            {
+                  "type_variety": "std_booster",
+                  "type_def": "fixed_gain",
+                  "gain_flatmax": 21,
+                  "gain_min": 20,
+                  "p_max": 21,
+                  "nf0": 5,
+                  "allowed_for_design": false
+            }
+      ],
+      "Fiber": [{
+                  "type_variety": "SSMF",
+                  "dispersion": 1.67e-05,
+                  "effective_area": 83e-12,
+                  "pmd_coef": 1.265e-15
+            }
+      ],
+      "Span": [{
+                  "power_mode":true,
+                  "delta_power_range_db": [0,0,0.5],
+                  "max_fiber_lineic_loss_for_raman": 0.25,
+                  "target_extended_gain": 2.5,
+                  "max_length": 150,
+                  "length_units": "km",
+                  "max_loss": 28,
+                  "padding": 10,
+                  "EOL": 0,
+                  "con_in": 0,
+                  "con_out": 0
+            }
+      ],
+      "Roadm": [{
+                  "target_pch_out_db": -20,
+                  "add_drop_osnr": 38,
+                  "pmd": 0,
+                  "pdl": 0,
+                  "restrictions": {
+                                  "preamp_variety_list":[],
+                                  "booster_variety_list":[]
+                  }
+            }
+      ],
+      "SI": [{
+                  "f_min": 191.35e12,
+                  "f_max": 196.1e12,
+                  "baud_rate": 32e9,
+                  "spacing": 50e9,
+                  "power_dbm": 0,
+                  "power_range_db": [-6,0,0.5],
+                  "roll_off": 0.15,
+                  "tx_osnr": 100,
+                  "sys_margins": 0
+            }
+      ],
+      "Transceiver":[
+            {
+            "type_variety": "vendorA_trx-type1",
+            "frequency":{
+                  "min": 191.4e12,
+                  "max": 196.1e12
+            },
+            "mode":[
+                       {
+                             "format": "PS_SP64_1",
+                             "baud_rate": 32e9,
+                             "OSNR": 11,
+                             "bit_rate": 100e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 100,
+                             "min_spacing": 50e9,
+                             "cost": 1
+                       },
+                       {
+                             "format": "PS_SP64_2",
+                             "baud_rate": 64e9,
+                             "OSNR": 15,
+                             "bit_rate": 200e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 100,
+                             "min_spacing": 75e9,
+                             "cost": 1
+                       },
+                       {
+                             "format": "mode 1",
+                             "baud_rate": 32e9,
+                             "OSNR": 11,
+                             "bit_rate": 100e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 100,
+                             "min_spacing": 50e9,
+                             "cost": 1
+                       },
+                       {
+                             "format": "mode 2",
+                             "baud_rate": 64e9,
+                             "OSNR": 15,
+                             "bit_rate": 200e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 100,
+                             "min_spacing": 75e9,
+                             "cost": 1
+                       }
+                  ]
+            },
+            {
+            "type_variety": "Voyager_16QAM",
+            "frequency": {
+                  "min": 191.4e12,
+                  "max": 196.1e12
+            },
+            "mode": [
+                       {
+                             "format": "16QAM",
+                             "baud_rate": 32e9,
+                             "OSNR": 19,
+                             "bit_rate": 200e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 100,
+                             "min_spacing": 50e9,
+                             "cost": 1
+                       }
+                  ]
+            },
+            {
+            "type_variety": "Voyager",
+            "frequency": {
+                  "min": 191.4e12,
+                  "max": 196.1e12
+            },
+            "mode": [
+                       {
+                             "format": "mode 1",
+                             "baud_rate": 32e9,
+                             "OSNR": 12,
+                             "bit_rate": 100e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 45,
+                             "min_spacing": 50e9,
+                             "cost": 1
+                       },
+                       {
+                             "format": "mode 3",
+                             "baud_rate": 44e9,
+                             "OSNR": 18,
+                             "bit_rate": 300e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 45,
+                             "min_spacing": 62.5e9,
+                             "cost": 1
+                       },
+                       {
+                             "format": "mode 2",
+                             "baud_rate": 66e9,
+                             "OSNR": 21,
+                             "bit_rate": 400e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 45,
+                             "min_spacing": 75e9,
+                             "cost": 1
+                       },
+                       {
+                             "format": "mode 2 - fake",
+                             "baud_rate": 66e9,
+                             "OSNR": 21,
+                             "bit_rate": 400e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 45,
+                             "min_spacing": 75e9,
+                             "cost": 1
+                       },
+                       {
+                             "format": "mode 4",
+                             "baud_rate": 66e9,
+                             "OSNR": 16,
+                             "bit_rate": 200e9,
+                             "roll_off": 0.15,
+                             "tx_osnr": 45,
+                             "min_spacing": 75e9,
+                             "cost": 1
+                       }
+                  ]
+            }
+      ]
+
+}

tests/data/perdegreemeshTopologyExampleV2_auto_design_expected.json

@@ -63,6 +63,7 @@
     {
       "uid": "roadm Lannion_CAS",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -18.6,
         "restrictions": {
@@ -87,6 +88,7 @@
     {
       "uid": "roadm Lorient_KMA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -111,6 +113,7 @@
     {
       "uid": "roadm Vannes_KBE",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -134,6 +137,7 @@
     {
       "uid": "roadm Rennes_STA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -157,6 +161,7 @@
     {
       "uid": "roadm Brest_KLA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {

tests/data/sim_params.json

@@ -2,7 +2,7 @@
   "raman_params": {
     "flag": true,
     "result_spatial_resolution": 10e3,
-    "solver_spatial_resolution": 50
+    "solver_spatial_resolution": 10e3
   },
   "nli_params": {
     "method": "ggn_spectrally_separated",

tests/data/std_medium_gain_advanced_config.json

@@ -1,4 +1,7 @@
-{     "nf_fit_coeff": [
+{
+      "f_min": 191.275e12,
+      "f_max": 196.125e12,
+      "nf_fit_coeff": [
       0.000168241,
       0.0469961,
       0.0359549,

tests/data/testTopology_auto_design_expected.json

@@ -159,6 +159,7 @@
     {
       "uid": "roadm Lannion_CAS",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -183,6 +184,7 @@
     {
       "uid": "roadm Lorient_KMA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -207,6 +209,7 @@
     {
       "uid": "roadm Vannes_KBE",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -230,6 +233,7 @@
     {
       "uid": "roadm Rennes_STA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -240,7 +244,6 @@
           "east edfa in Rennes_STA to Stbrieuc": -20,
           "east edfa in Rennes_STA to Ploermel": -20
         }
-
       },
       "metadata": {
         "location": {
@@ -254,6 +257,7 @@
     {
       "uid": "roadm Brest_KLA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -277,6 +281,7 @@
     {
       "uid": "roadm a",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -302,6 +307,7 @@
     {
       "uid": "roadm b",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -310,7 +316,7 @@
           ],
           "booster_variety_list": []
         },
-        "per_degree_pch_out_db":{
+        "per_degree_pch_out_db": {
           "east edfa in b to a": -20,
           "east edfa in b to f": -20
         }
@@ -327,13 +333,14 @@
     {
       "uid": "roadm c",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
           "preamp_variety_list": [],
           "booster_variety_list": []
         },
-        "per_degree_pch_out_db":{
+        "per_degree_pch_out_db": {
           "east edfa in c to a": -20,
           "east edfa in c to d": -20,
           "east edfa in c to f": -20
@@ -351,6 +358,7 @@
     {
       "uid": "roadm d",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -374,6 +382,7 @@
     {
       "uid": "roadm e",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -397,6 +406,7 @@
     {
       "uid": "roadm f",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -421,6 +431,7 @@
     {
       "uid": "roadm g",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -444,6 +455,7 @@
     {
       "uid": "roadm h",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1593,7 +1605,7 @@
       "type": "Edfa",
       "type_variety": "std_medium_gain",
       "operational": {
-        "gain_target": 18.5,
+        "gain_target": 13.177288,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -2235,7 +2247,7 @@
       "type": "Edfa",
       "type_variety": "std_low_gain",
       "operational": {
-        "gain_target": 6.5,
+        "gain_target": 11.822712,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -2292,7 +2304,7 @@
       "type": "Edfa",
       "type_variety": "std_low_gain",
       "operational": {
-        "gain_target": 13.82,
+        "gain_target": 13.822712,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -2311,7 +2323,7 @@
       "type": "Edfa",
       "type_variety": "test_fixed_gain",
       "operational": {
-        "gain_target": 15.18,
+        "gain_target": 15.177288,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0

tests/data/test_fiber_flex_expected_with_raman_results.csv

@@ -0,0 +1,6 @@
+,signal,nli
+0,3.9807550201531427e-07,1.0345007661598643e-10
+1,3.582672964406964e-07,8.554802579711129e-11
+2,5.174953110822109e-07,1.2476289414924814e-10
+3,3.1845777742391393e-07,8.147850636202276e-11
+4,4.776857897651456e-07,1.5683132697931042e-10

tests/data/test_lumped_losses_fiber_no_pumps.csv

@@ -1,96 +1,97 @@
-0.001,0.0007537739940510926,0.0005921033539224395,0.000384643453726324,0.00024710943492700773,0.00015765779381207088,0.00010015276356884663,6.345008665672524e-05,4.012925332336102e-05,2.535268958174273e-05
-0.001,0.0007532443480762404,0.0005915606741358828,0.00038408573214392957,0.00024666764094038643,0.00015734224135307426,9.993879038586218e-05,6.330912140259024e-05,4.003794165686942e-05,2.529414108865862e-05
-0.001,0.0007527148738848327,0.0005910183036445593,0.0003835286706438232,0.0002462265418760313,0.00015702726304657165,9.972523988324127e-05,6.316844848796591e-05,3.994682503096186e-05,2.5235719950422228e-05
-0.001,0.0007521855703345118,0.0005904762413907948,0.00038297226807207136,0.0002457861365766504,0.00015671285789580896,9.9512111295817e-05,6.302806736731544e-05,3.985590307420444e-05,2.5177425921282973e-05
-0.001,0.0007516564362539944,0.0005899344862777934,0.00038241652320864807,0.0002453464238190796,0.00015639902485083639,9.929940381972637e-05,6.288797746852316e-05,3.976517539750482e-05,2.511925874398998e-05
-0.001,0.0007511274704431355,0.0005893930371697809,0.0003818614347679428,0.0002449074023149522,0.00015608576280913723,9.908711661290977e-05,6.27481781932559e-05,3.967464159435973e-05,2.5061218149955632e-05
-0.001,0.0007505986716729718,0.0005888518928921378,0.00038130700139925517,0.0002444690707113658,0.00015577307061625246,9.887524879560432e-05,6.260866891731864e-05,3.958430124109855e-05,2.5003303859417958e-05
-0.001,0.0007500678710880661,0.0005883088511431218,0.000380751009486411,0.0002440296996901373,0.00015545972380501664,9.866297459432463e-05,6.246890748950651e-05,3.949380391318895e-05,2.4945291488462056e-05
-0.001,0.0007495350705096461,0.0005877639154939723,0.000380193466563788,0.00024358929686534952,0.00015514572847430736,9.8450298405315e-05,6.232889690863924e-05,3.9403151593579556e-05,2.4887182324516918e-05
-0.001,0.0007490002717484986,0.0005872170894971442,0.00037963438011605534,0.00024314786979147204,0.00015483109067004745,9.823722458416644e-05,6.218864014470764e-05,3.931234624568946e-05,2.4828977642138712e-05
-0.001,0.0007484634766050366,0.000586668376686434,0.0003790737575785661,0.00024270542596389042,0.0001545158163857142,9.802375744622405e-05,6.204814013916893e-05,3.9221389813611975e-05,2.4770678703146694e-05
-0.001,0.0007479199274773811,0.0005861128912299699,0.0003785065486556895,0.00024225795000622747,0.0001541970308568484,9.780794472023814e-05,6.190610951865765e-05,3.9129447888412384e-05,2.471175028700643e-05
-0.001,0.0007473696306726699,0.0005855506450602122,0.0003779327791658341,0.00024180546890527417,0.0001538747562360148,9.758980264023896e-05,6.176255947727244e-05,3.903652792388679e-05,2.4652197254708885e-05
-0.001,0.0007468125926679213,0.0005849816503235855,0.0003773524752207052,0.00024134800990073543,0.00015354901486124996,9.736934756691086e-05,6.161750129261558e-05,3.8942637427869684e-05,2.459202450185328e-05
-0.001,0.0007462488201102061,0.0005844059193804029,0.00037676566322402907,0.00024088560048334876,0.0001532198292542639,9.714659598616437e-05,6.147094632476142e-05,3.884778396152801e-05,2.4531236958179027e-05
-0.001,0.0007456783198168171,0.0005838234648047683,0.00037617236987025305,0.00024041826839299018,0.00015288722211863548,9.692156450770277e-05,6.132290601522212e-05,3.875197513865345e-05,2.4469839587096592e-05
-0.001,0.0007451010987754332,0.0005832342993844907,0.0003755726221432343,0.0002399460416167659,0.00015255121633799497,9.66942698635831e-05,6.11733918859104e-05,3.8655218624953314e-05,2.4407837385217267e-05
-0.001,0.0007445173992825126,0.0005826386743528757,0.00037496668540476865,0.00023946913369259697,0.00015221196586566552,9.646481704279825e-05,6.102247334575324e-05,3.85575594785277e-05,2.4345259282747418e-05
-0.001,0.0007439272282773631,0.0005820366023339485,0.0003743545861363169,0.00023898757201912962,0.00015186949307274757,9.623322238874437e-05,6.0870161643097905e-05,3.845900518061352e-05,2.4282110155051444e-05
-0.001,0.0007433305928659832,0.0005814280961601982,0.00037373635109929905,0.0002385013842326201,0.0001515238205025659,9.599950236146117e-05,6.071646810276464e-05,3.835956326175255e-05,2.4218394908993806e-05
-0.001,0.0007427275003211868,0.0005808131688724332,0.0003731120073337174,0.00023801059820498021,0.0001511749708688244,9.576367353617374e-05,6.05614041249978e-05,3.825924130107498e-05,2.4154118482464792e-05
-0.001,0.0007421180800523362,0.0005801919587229117,0.00037248171070273063,0.0002375153439047009,0.00015082303982525373,9.55258019540184e-05,6.0405013700224733e-05,3.815806798909622e-05,2.4089299350133826e-05
-0.001,0.0007415023395254894,0.0005795644789202474,0.00037184548827748576,0.0002370156491221818,0.00015046804996987382,9.528590408468248e-05,6.0247308147258e-05,3.8056050847170796e-05,2.4023942410771268e-05
-0.001,0.0007408802863797739,0.000578930742889133,0.00037120336741830446,0.00023651154189285886,0.00015011002407818366,9.504399651802114e-05,6.008829886368558e-05,3.7953197447440844e-05,2.395805259559495e-05
-0.001,0.0007402519284274773,0.00057829076427012,0.0003705553757730914,0.00023600305049498863,0.0001497489851010917,9.480009596242987e-05,5.992799732470356e-05,3.784951541204015e-05,2.389163486774317e-05
-0.001,0.0007396172736541335,0.0005776445569193926,0.0003699015412757306,0.000235490203447419,0.00014938495616282697,9.455421924320194e-05,5.976641508193571e-05,3.774501241228877e-05,2.38246942217421e-05
-0.001,0.0007389763302186035,0.0005769921349085269,0.00036924189214444916,0.00023497302950733012,0.00014901796055883247,9.4306383300876e-05,5.960356376224896e-05,3.763969616788547e-05,2.37572356829714e-05
-0.001,0.000738329973009011,0.0005763343882557762,0.00036857732657886674,0.00023445223185895243,0.00014864849677321228,9.40569245366171e-05,5.943966431343476e-05,3.753370952478887e-05,2.3689350732036766e-05
-0.001,0.0007376782088319843,0.0005756713289449496,0.0003679078688863157,0.00023392783529630037,0.00014827658488585004,9.38058575472753e-05,5.927472675087035e-05,3.7427059131368685e-05,2.362104369630353e-05
-0.001,0.0007370210446325295,0.0005750029691304239,0.000367233543593211,0.00023339986479263558,0.00014790224510292775,9.355319701349314e-05,5.910876114408311e-05,3.7319751670569666e-05,2.3552318925085614e-05
-0.001,0.0007363584874940915,0.0005743293211369546,0.0003665543754437431,0.00023286834549865966,0.00014752549775524457,9.329895769838934e-05,5.8941777615809794e-05,3.721179385927125e-05,2.348318078922229e-05
-0.001,0.0007356906659117175,0.0005736505214206793,0.00036587051603697917,0.00023233340267585003,0.00014714643450378646,9.30432026577021e-05,5.8773818072131705e-05,3.710321298927822e-05,2.3413646846771747e-05
-0.001,0.0007350175870680764,0.0005729665823498456,0.00036518198995355594,0.00023179506120909636,0.00014676507541963834,9.278594644638945e-05,5.8604892484780656e-05,3.699401567385024e-05,2.3343721399750524e-05
-0.001,0.000734339258284937,0.0005722775164633901,0.0003644888219905243,0.00023125334615855053,0.0001463814406964208,9.252720370024704e-05,5.8435010877524154e-05,3.688420855938328e-05,2.327340877117354e-05
-0.001,0.0007336556870231954,0.0005715833364706749,0.00036379103715988533,0.00023070828275766533,0.00014599555064848363,9.226698913450141e-05,5.82641833251609e-05,3.677379832472749e-05,2.320271330460301e-05
-0.001,0.0007329668808828947,0.0005708840552512191,0.00036308866068712113,0.00023015989641122435,0.00014560742570909416,9.200531754239911e-05,5.8092419952513674e-05,3.666279168050168e-05,2.313163936369656e-05
-0.001,0.000732272847603227,0.0005701796858544125,0.000362381718009681,0.0002296082126933358,0.00014521708642859763,9.174220379377606e-05,5.791973093340874e-05,3.6551195368400524e-05,2.3060191331749373e-05
-0.001,0.0007315751779154508,0.0005694718366517781,0.00036167180797618383,0.00022905447155647377,0.00014482540661409508,9.147823538482221e-05,5.774650123146614e-05,3.643925790598459e-05,2.2988528215049473e-05
-0.001,0.0007308738763564251,0.0005687605159526348,0.00036095894758939165,0.00022849869020493823,0.00014443240010265552,9.121342232553745e-05,5.7572737692798364e-05,3.6326983828340116e-05,2.2916652961499898e-05
-0.001,0.0007301689475478705,0.0005680457321686527,0.00036024315397386176,0.00022794088593578913,0.00014403808079282816,9.094777466478586e-05,5.739844718775089e-05,3.6214377685641065e-05,2.2844568528419092e-05
-0.001,0.0007294603961963875,0.0005673274938137002,0.0003595244443750873,0.00022738107613769066,0.00014364246264358423,9.068130248947494e-05,5.72236366103174e-05,3.610144404275241e-05,2.2772277882278848e-05
-0.001,0.0007287502876018436,0.0005666079096289159,0.00035880496633647314,0.00022682095171468864,0.00014324674865159545,9.041481948469436e-05,5.7048841153261715e-05,3.598852922211342e-05,2.270000293927642e-05
-0.001,0.0007280386231103084,0.0005658869826353605,0.0003580847262718071,0.00022626051891339797,0.00014285094367250402,9.014832907727154e-05,5.687406312117876e-05,3.587563473352017e-05,2.2627744673782604e-05
-0.001,0.0007273254041056322,0.0005651647158992671,0.00035736373064750184,0.00022569978402038908,0.00014245505258865028,8.988183471111395e-05,5.669930482943582e-05,3.5762762093538084e-05,2.2555504064421286e-05
-0.001,0.0007266106320094578,0.0005644411125319691,0.00035664198598218,0.00022513875336164715,0.0001420590803085807,8.961533984682783e-05,5.652456860390248e-05,3.564991282531874e-05,2.2483282093948716e-05
-0.001,0.000725894308281204,0.0005637161756897977,0.0003559194988462394,0.00022457743330201225,0.00014166303176654256,8.934884796133105e-05,5.634985678067539e-05,3.5537088458413665e-05,2.2411079749130865e-05
-0.001,0.0007251764344180624,0.0005629899085739927,0.00035519627586142176,0.0002240158302446243,0.00014126691192198565,8.90823625474685e-05,5.6175171705805915e-05,3.542429052859005e-05,2.233889802062196e-05
-0.001,0.0007244588135748975,0.0005622641246704724,0.00035447409591105305,0.0002234553120905153,0.00014087167955905718,8.881652603390643e-05,5.600093342830372e-05,3.531178983274928e-05,2.2266910019981595e-05
-0.001,0.000723741443178776,0.000561538821268995,0.0003537529553873339,0.00022289587522719752,0.00014047733166655684,8.855133617099835e-05,5.5827140373801375e-05,3.519958531186087e-05,2.219511505192651e-05
-0.001,0.0007230243206833482,0.0005608139956950427,0.00035303285074046774,0.00022233751609917817,0.00014008386527925162,8.82867907426191e-05,5.565379099102327e-05,3.508767592227262e-05,2.212351243120618e-05
-0.001,0.0007223074435688039,0.0005600896453097011,0.0003523137784782074,0.00022178023120736695,0.00013969127747733319,8.802288756574066e-05,5.5480883751481105e-05,3.4976060635503277e-05,2.2052101482465692e-05
-0.001,0.0007215926247557181,0.0005593676122940626,0.00035159759247597197,0.00022122546934306127,0.00013930059415776796,8.776031848020719e-05,5.5308872854303e-05,3.486503301641155e-05,2.198107017600086e-05
-0.001,0.0007208798585848073,0.0005586478889723664,0.0003508842795507963,0.0002206732171528304,0.00013891180440309996,8.749907547557891e-05,5.513775276548628e-05,3.475458937431628e-05,2.1910416102241813e-05
-0.001,0.0007201691394257483,0.000557930467712979,0.00035017382661216696,0.00022012346138632064,0.00013852489738482468,8.723915060881119e-05,5.49675179985075e-05,3.464472605058592e-05,2.184013687270143e-05
-0.001,0.0007194604616770773,0.00055721534092818,0.00034946622066134466,0.00021957618889536463,0.00013813986236255893,8.698053600359808e-05,5.4798163113848986e-05,3.453543941831367e-05,2.177023011975932e-05
-0.001,0.0007187538197660722,0.0005565025010739346,0.00034876144879066544,0.00021903138663308575,0.0001377566886832086,8.672322384971475e-05,5.462968271852315e-05,3.442672588199151e-05,2.1700693496445714e-05
-0.001,0.0007180492081486484,0.0005557919406496801,0.00034805949818288173,0.0002184890416530366,0.00013737536578016266,8.646720640237894e-05,5.446207146561145e-05,3.431858187719449e-05,2.1631524676231647e-05
-0.001,0.000717348639431565,0.0005550856739198547,0.00034736232071304855,0.00021795064331956514,0.00013699693247692832,8.621317757037385e-05,5.429578217858938e-05,3.421129897003673e-05,2.1562909902755936e-05
-0.001,0.0007166521035756881,0.0005543836868927082,0.0003466698924934393,0.00021741616794755068,0.00013662136971116798,8.596112351100096e-05,5.413080535731451e-05,3.410487085131832e-05,2.1494845067789903e-05
-0.001,0.0007159595906065037,0.0005536859656730149,0.00034598218983055497,0.0002168855920630381,0.0001362486585998701,8.571103051605296e-05,5.396713159578493e-05,3.399929127512844e-05,2.142732610463052e-05
-0.001,0.0007152710906138687,0.0005529924964615861,0.00034529918922366796,0.00021635889240138666,0.0001358787804376394,8.546288501047042e-05,5.380475158117202e-05,3.389455405818364e-05,2.1360348987661796e-05
-0.001,0.0007145881681833736,0.0005523048607339887,0.0003446224616264519,0.00021583728670966556,0.00013551259312919557,8.521726369129195e-05,5.364404315662281e-05,3.379090310339315e-05,2.129406976339983e-05
-0.001,0.0007139108109389651,0.0005516230407004492,0.0003439519758859039,0.00021532074399295122,0.00013515007172518374,8.497414844816332e-05,5.3484993898260945e-05,3.368833016244125e-05,2.122848306212633e-05
-0.001,0.0007132390066148024,0.0005509470187317473,0.00034328770115903844,0.00021480923358720733,0.0001347911915544671,8.473352137819455e-05,5.3327591526929936e-05,3.358682708410006e-05,2.1163583577742056e-05
-0.001,0.0007125727430549207,0.0005502767773585094,0.000342629606910633,0.00021430272515636744,0.0001344359282214269,8.449536478383494e-05,5.317182390666476e-05,3.348638581318404e-05,2.109936606707349e-05
-0.001,0.0007119120082129148,0.0005496122992705212,0.0003419776629110174,0.0002138011886894788,0.00013408425760331254,8.425966117078749e-05,5.3017679043188334e-05,3.3386998389521964e-05,2.1035825349191292e-05
-0.001,0.000711256790151613,0.0005489535673160376,0.0003413318392338714,0.00021330459449785352,0.00013373615584760944,8.40263932459383e-05,5.286514508242194e-05,3.3288656946938245e-05,2.0972956304734848e-05
-0.001,0.0007106071943639499,0.0005483006816957998,0.00034069221933208274,0.0002128129992904075,0.00013339165932644894,8.379558393280961e-05,5.271423641048183e-05,3.31913705135711e-05,2.091076460544407e-05
-0.001,0.000709963208882901,0.0005476536252143895,0.0003400587732671483,0.0002123263734210078,0.00013305074425072359,8.356721599784782e-05,5.256494122003263e-05,3.3095131256746724e-05,2.0849245154782437e-05
-0.001,0.0007093248218486061,0.0005470123808316875,0.00033943147139689077,0.0002118446875576196,0.00013271338709432742,8.334127240311385e-05,5.241724783997488e-05,3.299993143509595e-05,2.0788392916005465e-05
-0.001,0.0007086920215080653,0.0005463769316622218,0.0003388102843733889,0.00021136791267964032,0.0001323795645916927,8.311773630434548e-05,5.2271144734051514e-05,3.290576339760186e-05,2.07282029115292e-05
-0.001,0.0007080656480431051,0.0005457481216341828,0.0003381960373995552,0.00021089668206097172,0.0001320497200486003,8.289690449717853e-05,5.2126825862102536e-05,3.2812752146082854e-05,2.0668755034757233e-05
-0.001,0.0007074456886869565,0.0005451259321489777,0.0003375886977799707,0.0002104309633113142,0.00013172382748945162,8.26787581753205e-05,5.198427834496719e-05,3.2720889139431744e-05,2.061004372929991e-05
-0.001,0.0007068321308093747,0.0005445103448031184,0.0003369882331820464,0.00020997072442018424,0.00013140186125447996,8.246327876643199e-05,5.18434894660219e-05,3.2630165945308436e-05,2.055206350992823e-05
-0.001,0.0007062249619162967,0.0005439013413874698,0.00033639461163356655,0.00020951593375373114,0.00013108379599680725,8.225044792981545e-05,5.170444666951808e-05,3.254057423900392e-05,2.0494808961820763e-05
-0.001,0.00070562416964951,0.0005432989038865089,0.00033580780152024723,0.000209066560051587,0.00013076960667953474,8.204024755412909e-05,5.156713755893784e-05,3.2452105802317056e-05,2.0438274739819433e-05
-0.001,0.0007050297417863318,0.0005427030144775926,0.0003352277715833316,0.00020862257242375786,0.00013045926857287288,8.183265975513502e-05,5.143154989537623e-05,3.236475252244954e-05,2.038245556769746e-05
-0.001,0.0007044417829621171,0.000542113771820027,0.0003346546023905152,0.00020818402485557293,0.00013015281596227648,8.162770599537212e-05,5.129769708700084e-05,3.227852278867728e-05,2.032735670561579e-05
-0.001,0.0007038602809995153,0.0005415311581470623,0.00033408826282687573,0.00020775088664703998,0.00012985022429639665,8.142536853201701e-05,5.116556699709043e-05,3.219340855821242e-05,2.0272972923816322e-05
-0.001,0.0007032852238493367,0.0005409551558747416,0.0003335287221154158,0.00020732312745044945,0.00012955146931603386,8.122562983828357e-05,5.103514763884953e-05,3.2109401888525124e-05,2.0219299058105656e-05
-0.001,0.0007027165995902542,0.0005403857476012292,0.00033297594981485264,0.00020690071726752732,0.0001292565270515082,8.102847260135871e-05,5.090642717392409e-05,3.202649493632917e-05,2.0166330009182866e-05
-0.001,0.0007021546252265139,0.0005398231466905069,0.00033243014325207994,0.00020648380199548492,0.0001289654971719027,8.083396250547584e-05,5.077944809587575e-05,3.194471491165552e-05,2.0114083097018264e-05
-0.001,0.0007015992888126556,0.0005392673356287205,0.0003318912717105927,0.00020607235137144977,0.0001286783555062261,8.06420820982489e-05,5.065419847368218e-05,3.186405391103787e-05,2.006255318369691e-05
-0.001,0.0007010505785332368,0.0005387182970867077,0.00033135930481238495,0.00020566633548374424,0.0001283950781739038,8.04528141416734e-05,5.053066652493675e-05,3.1784504130324826e-05,2.001173519622426e-05
-0.001,0.000700508482702546,0.0005381760139193414,0.00033083421251577956,0.00020526572476908743,0.000128115641582197,8.026614161010359e-05,5.040884061439589e-05,3.170605786368809e-05,1.9961624125869314e-05
-0.001,0.0006999729897643184,0.0005376404691648787,0.00033031596511327947,0.00020487049000982136,0.00012784002242364822,8.008204768824872e-05,5.028870925253973e-05,3.1628707502639986e-05,1.9912215027513866e-05
-0.001,0.0006994440882914515,0.0005371116460443127,0.0003298045332294241,0.0002044806023311588,0.0001275681976735486,7.990051576919067e-05,5.0170261094149856e-05,3.155244553506268e-05,1.9863503019009735e-05
-0.001,0.0006989172535560769,0.0005365850419669894,0.000329295612913881,0.00020409280438264766,0.00012729790663346764,7.972004038787022e-05,5.0052515589855926e-05,3.147664135129994e-05,1.9815085586326718e-05
-0.001,0.0006983924815322933,0.0005360606511477293,0.0003287891938968759,0.00020370708584067882,0.00012702914094133737,7.954061545150935e-05,4.993546855036179e-05,3.140129216611291e-05,1.9766960914662127e-05
-0.001,0.0006978697681747856,0.000535538467781285,0.000328285265898271,0.00020332343638453147,0.00012676189224377013,7.936223487646896e-05,4.981911579385119e-05,3.1326395199731696e-05,1.971912719297887e-05
-0.001,0.0006973491094188342,0.0005350184860423863,0.0003277838186277228,0.0002029418456965422,0.0001264961521961901,7.918489258833681e-05,4.970345314604528e-05,3.125194767789152e-05,1.967158261402843e-05
-0.001,0.0006968284099289676,0.000534498597351666,0.00032728277956097635,0.00020256071739357045,0.0001262308004979493,7.900783730702533e-05,4.958798911408524e-05,3.1177632631488905e-05,1.9624124503146986e-05
-0.001,0.0006963076677967887,0.0005339787996978908,0.00032678214616920946,0.00020218004908417888,0.0001259658352285323,7.883106763041168e-05,4.947272273059253e-05,3.110344941552445e-05,1.957675243920473e-05
-0.001,0.0006957868810888677,0.0005334590910383602,0.00032628191587964447,0.00020179983833834103,0.00012570125443876325,7.865458213663353e-05,4.935765301510161e-05,3.102939737649859e-05,1.9529465995615212e-05
-0.001,0.0006952660478468047,0.0005329394692990367,0.0003257820860759608,0.00020142008268794192,0.0001254370561512512,7.847837938443003e-05,4.924277897429975e-05,3.0955475852573814e-05,1.94822647404421e-05
-0.001,0.00069474516608728,0.0005324199323746772,0.00032528265409871067,0.0002010407796272818,0.0001251732383608348,7.830245791348127e-05,4.91280996022673e-05,3.088168417373684e-05,1.943514823650581e-05
+0 km,7 km,10 km,20 km,30 km,40 km,50 km,60 km,70 km,80 km
+0.001,0.0007539177767305848,0.0005922648034750569,0.00038490617279658137,0.000247392320543982,0.00015791555306607623,0.0001003671566373715,6.361853747449743e-05,4.0256607010916584e-05,2.5446360651215025e-05
+0.001,0.0007533902419958185,0.0005917244917926066,0.0003843504806873478,0.0002469518485683003,0.0001576007478372822,0.00010015356028336005,6.347773727057954e-05,4.016534974386181e-05,2.5387814123899557e-05
+0.001,0.0007528628792251897,0.0005911844879166931,0.0003837954443648265,0.0002465120671477305,0.00015728651344926157,9.994038442151031e-05,6.333722806950528e-05,4.007428674216739e-05,2.5329394519652018e-05
+0.001,0.0007523356872805944,0.0005906447907925071,0.0003832410626787123,0.0002460729751307637,0.00015697284891103737,9.972762829117227e-05,6.319700932883725e-05,3.9983417636365086e-05,2.5271101593906498e-05
+0.001,0.0007518086649950493,0.0005901053993262767,0.0003826873344129807,0.000245634571300401,0.00015665975317873245,9.95152910932062e-05,6.305708047968383e-05,3.9892742039402306e-05,2.5212935090640287e-05
+0.001,0.0007512818111727442,0.0005895663123854124,0.00038213425828639575,0.0002451968543747938,0.0001563472251561599,9.930337199043154e-05,6.291744092702573e-05,3.980225954686196e-05,2.5154894742516358e-05
+0.001,0.0007507551245890757,0.0005890275287986403,0.0003815818329529933,0.00024475982300791935,0.00015603526369546326,9.909187010814736e-05,6.277809005009466e-05,3.9711969737226656e-05,2.5096980271060998e-05
+0.001,0.0007502264452226824,0.0005884868559085152,0.00038102785262825065,0.00024432175277214066,0.00015572264698517112,9.88799609470651e-05,6.26384862087587e-05,3.9621522312922004e-05,2.5038967246912867e-05
+0.001,0.000749695774901522,0.0005879442972710813,0.00038047232480109013,0.00024388265123925605,0.00015540938109456906,9.866764888521257e-05,6.249863239143498e-05,3.953091925128679e-05,2.498085695464162e-05
+0.001,0.0007491631154430714,0.0005873998564236413,0.00037991525691100856,0.00024344252592185564,0.00015509547204033507,9.845493826021018e-05,6.235853155787194e-05,3.944016251022327e-05,2.4922650665997884e-05
+0.001,0.0007486284686543365,0.0005868535368848297,0.00037935665634847824,0.00024300138427382333,0.00015478092578703268,9.824183336966692e-05,6.2218186639435e-05,3.9349254028404254e-05,2.4864349640052216e-05
+0.001,0.0007480870957031576,0.000586300474032492,0.00037879149123861057,0.0002425552230413961,0.00015446287448415177,9.80263854642033e-05,6.207631182945079e-05,3.925735993392708e-05,2.4805418700342044e-05
+0.001,0.0007475390029192987,0.0005857406797529387,0.0003782197872436036,0.00024210406905347345,0.00015414134016629157,9.780861070114894e-05,6.193291827596257e-05,3.9164487654400794e-05,2.4745862693628148e-05
+0.001,0.0007469841968019674,0.0005851741661454001,0.0003776415703174324,0.00024164794939077438,0.0001538163450528885,9.758852536415706e-05,6.178801721036571e-05,3.907064467141267e-05,2.4685686501265697e-05
+0.001,0.0007464226840200367,0.0005846009455219824,0.00037705686670463337,0.0002411868913840224,0.0001534879115464833,9.736614586183658e-05,6.164161994641891e-05,3.897583851984993e-05,2.462489503874857e-05
+0.001,0.0007458544714121565,0.0005840210304075477,0.00037646570293897594,0.00024072092261200308,0.00015315606223087128,9.714148872627883e-05,6.149373787917076e-05,3.888007678716513e-05,2.45634932552282e-05
+0.001,0.0007452795659868886,0.0005834344335395587,0.00037586810584214404,0.0002402500708997022,0.000152820819869329,9.691457061165131e-05,6.134438248396139e-05,3.878336711269497e-05,2.450148613305654e-05
+0.001,0.0007446982091229053,0.0005828414050804809,0.00037526433980072227,0.0002397745491251193,0.0001524823380310375,9.668549630724793e-05,6.119362307821724e-05,3.868575452092861e-05,2.4438902597094615e-05
+0.001,0.0007441104077793266,0.0005822419576041865,0.000374654431136991,0.00023929438452844706,0.0001521406389697796,9.645428208068799e-05,6.10414708650461e-05,3.858724646752558e-05,2.4375747508899864e-05
+0.001,0.0007435161690815189,0.0005816361038919765,0.0003740384064517259,0.00023880960458647735,0.00015179574511101,9.622094431596755e-05,6.0887937123913e-05,3.848785045741014e-05,2.4312025761525238e-05
+0.001,0.0007429155003212045,0.0005810238569324259,0.0003734162926228523,0.00023832023701067176,0.00015144767905002232,9.598549951201614e-05,6.073303320960556e-05,3.83875740440667e-05,2.42477422790523e-05
+0.001,0.0007423085305088799,0.0005804053544492479,0.00037278824495395505,0.0002378264113599139,0.00015109653618969462,9.574801357389848e-05,6.057680304696976e-05,3.828644589147927e-05,2.4182915529390252e-05
+0.001,0.0007416952671281527,0.0005797806095975203,0.0003721542903540935,0.000237328155265129,0.00015074233901078615,9.550850289594038e-05,6.041925791001213e-05,3.8184473495775654e-05,2.411755039775751e-05
+0.001,0.0007410757178351933,0.0005791496357472955,0.0003715144560199718,0.00023682549660121693,0.00015038511017095082,9.526698399235154e-05,6.026040915139781e-05,3.8081664403831414e-05,2.4051651801815565e-05
+0.001,0.0007404498904588522,0.0005785124464833875,0.0003708687694343879,0.00023631846348487102,0.00015002487250269267,9.502347349561174e-05,6.0100268201280124e-05,3.797802621247342e-05,2.3985224691142176e-05
+0.001,0.000739817793000736,0.0005778690556051271,0.0003702172583646133,0.00023580708427235972,0.00014966164901128063,9.477798815483971e-05,5.9938846566140114e-05,3.787356656768574e-05,2.3918274046705576e-05
+0.001,0.0007391794336352683,0.0005772194771261406,0.00036955995086080306,0.00023529138755728292,0.00014929546287266413,9.453054483414699e-05,5.977615582759686e-05,3.776829316380097e-05,2.385080488032797e-05
+0.001,0.0007385356837401969,0.0005765645972068202,0.00036889774196575574,0.0002347720745464529,0.00014892681149659162,9.42814794200372e-05,5.9612416728092556e-05,3.7662348796962334e-05,2.378290869241134e-05
+0.001,0.0007378865501365786,0.0005759044277808471,0.0003682306558404449,0.0002342491698918279,0.00014855571485941296,9.403080644324396e-05,5.944763924389705e-05,3.755574009362634e-05,2.371458979861065e-05
+0.001,0.0007372320397833855,0.0005752389809515306,0.00036755871686373843,0.00023372269842386576,0.0001481821930634036,9.377854051813779e-05,5.92818334053861e-05,3.74484737148236e-05,2.364585253654512e-05
+0.001,0.0007365721597776102,0.0005745682689916729,0.0003668819496311701,0.00023319268514975972,0.00014780626633511263,9.352469634142839e-05,5.911500929610015e-05,3.734055635551828e-05,2.35767012653732e-05
+0.001,0.0007359070382096695,0.0005738924278329212,0.00036620050520582223,0.0002326592549483615,0.00014742802610623578,9.326933684741753e-05,5.8947208765596136e-05,3.723201528626343e-05,2.3507153539330125e-05
+0.001,0.0007352366822744919,0.0005732114697907263,0.0003655144080205807,0.0002321224325628545,0.00014704749234532768,9.30124765259338e-05,5.877844174725213e-05,3.712285709891949e-05,2.3437213649054356e-05
+0.001,0.0007345610993055855,0.0005725254073502257,0.0003648236827235576,0.00023158224291094424,0.00014666468514311576,9.275412994749425e-05,5.860871822644595e-05,3.701308841848994e-05,2.336688590620212e-05
+0.001,0.0007338802967751745,0.0005718342531661053,0.0003641283541767086,0.00023103871108296522,0.00014627962471074844,9.249431176193324e-05,5.843804823954878e-05,3.690271590243443e-05,2.32961746429929e-05
+0.001,0.0007331942822941306,0.0005711380200622195,0.000363428447454292,0.00023049186233985435,0.00014589233137793237,9.223303669696582e-05,5.826644187292669e-05,3.679174623998899e-05,2.3225084211761806e-05
+0.001,0.0007325030636119942,0.000570436721031382,0.0003627239878414387,0.00022994172211121704,0.00014550282559116622,9.197031955679165e-05,5.809390926192732e-05,3.66801861514784e-05,2.3153618984504423e-05
+0.001,0.0007318082249846354,0.000569731957456593,0.0003620165686744435,0.0002293895269980944,0.0001451119793900387,9.170674702405544e-05,5.792083507086079e-05,3.656828410642266e-05,2.3081938026911105e-05
+0.001,0.0007311097709589727,0.0005690237376093709,0.0003613062068501535,0.00022883529410468975,0.00014471980653999792,9.14423290636205e-05,5.774722611940683e-05,3.6456044625219865e-05,2.3010044279099164e-05
+0.001,0.0007304077061664716,0.0005683120698629669,0.00036059291938656614,0.00022827904062761942,0.00014432632086784533,9.117707567918865e-05,5.757308925149413e-05,3.6343472243382366e-05,2.293794069062729e-05
+0.001,0.0007297020353231152,0.0005675969626922158,0.0003598767234219355,0.00022772078385475435,0.00014393153626068395,9.091099691249356e-05,5.739843133472259e-05,3.6230571511141116e-05,2.2865630220232028e-05
+0.001,0.0007289948155254126,0.0005668805157203741,0.00035915975887038315,0.00022716220982550104,0.00014353665302637602,9.064490513205597e-05,5.722378701487135e-05,3.611768859725593e-05,2.279333481077374e-05
+0.001,0.0007282860481242219,0.0005661627319510184,0.0003584420321019746,0.00022660332474955334,0.0001431416759965279,9.037880375071969e-05,5.7049158588914064e-05,3.6004825007582225e-05,2.2721055434706506e-05
+0.001,0.0007275757345080665,0.0005654436144326382,0.00035772354953912867,0.0002260441348764214,0.00014274661002939483,9.011269619839399e-05,5.687454836459578e-05,3.5891982254752056e-05,2.2648793068745655e-05
+0.001,0.0007268638761030398,0.0005647231662585116,0.0003570043176561602,0.0002254846464948739,0.0001423514600093734,8.984658592167178e-05,5.6699958660169715e-05,3.5779161857992474e-05,2.2576548693746487e-05
+0.001,0.0007261504743729061,0.0005640013905666712,0.00035628434297892044,0.0002249248659324104,0.00014195623084652692,8.958047638345721e-05,5.652539180412445e-05,3.5666365342942064e-05,2.250432329458613e-05
+0.001,0.0007254355308190145,0.0005632782905397587,0.00035556363208430486,0.00022436479955468554,0.0001415609274760624,8.931437106256734e-05,5.635085013490999e-05,3.5553594241465086e-05,2.2432117860037706e-05
+0.001,0.0007247208411865314,0.0005625556717890254,0.0003548439578507697,0.00022380581171795803,0.00014116650687104502,8.904891159204534e-05,5.61767534392646e-05,3.544111934056619e-05,2.2360105593797506e-05
+0.001,0.00072400640290786,0.000561833531609933,0.00035412531668185007,0.00022324789882467925,0.00014077296603347102,8.878409573173543e-05,5.600310014889176e-05,3.5328939584811035e-05,2.228828580259237e-05
+0.001,0.0007232922134419361,0.000561111867333509,0.00035340770503880037,0.00022269105733400152,0.00014038030201108317,8.8519921274859e-05,5.5829888718494674e-05,3.521705393409239e-05,2.221665780315407e-05
+0.001,0.0007225782702742098,0.0005603906763262448,0.0003526911194401051,0.00022213528376118449,0.00013998851189683077,8.825638604758897e-05,5.5657117625479614e-05,3.510546136342301e-05,2.214522092208301e-05
+0.001,0.0007218663790349207,0.0005596717927826706,0.0003519774072686018,0.00022158202285215626,0.0001395986194011808,8.79941808494171e-05,5.5485240659247415e-05,3.499445534348073e-05,2.207416317565271e-05
+0.001,0.0007211565340671307,0.000558955209053062,0.0003512665554090523,0.0002210312613239567,0.0001392106136609281,8.773329770591506e-05,5.531425230770577e-05,3.4884032196140665e-05,2.200348216114185e-05
+0.001,0.0007204487297429265,0.0005582409175317231,0.00035055855083818805,0.00022048298599609717,0.00013882448390129787,8.747372870968443e-05,5.514414710600884e-05,3.477418827518741e-05,2.1933175496831414e-05
+0.001,0.0007197429604633029,0.0005575289106567639,0.00034985338062403464,0.00021993718378969884,0.00013844021943515845,8.721546601972457e-05,5.497491963609735e-05,3.466491996599965e-05,2.1863240821795316e-05
+0.001,0.0007190392206580874,0.0005568191809099186,0.0003491510319252488,0.00021939384172660586,0.00013805780966217872,8.695850186076947e-05,5.480656452622117e-05,3.455622368522282e-05,2.1793675795681418e-05
+0.001,0.0007183375047857581,0.0005561117208162645,0.0003484514919904163,0.00021885294692850114,0.00013767724406801954,8.670282852265318e-05,5.463907645048003e-05,3.444809588045186e-05,2.172447809850241e-05
+0.001,0.0007176398171146462,0.0005554085359032386,0.00034775670623974134,0.0002183159850558065,0.00013729955964329822,8.644913914890404e-05,5.447290801376681e-05,3.4340828149382966e-05,2.165583410030806e-05
+0.001,0.0007169461476104001,0.0005547096122322624,0.0003470666509123452,0.00021778293254731739,0.00013692473741724035,8.61974199558567e-05,5.430804975101775e-05,3.423441420247442e-05,2.15877397033261e-05
+0.001,0.0007162564863033777,0.0005540149359610161,0.00034638130244054916,0.00021725376605180745,0.00013655275859741984,8.594765729366703e-05,5.4144492290891566e-05,3.412884781322755e-05,2.152019085117201e-05
+0.001,0.0007155708232884887,0.0005533244933430584,0.0003457006374485156,0.00021672846242622396,0.00013618360456808432,8.569983764497563e-05,5.3982226354801364e-05,3.40241228175218e-05,2.1453183528407172e-05
+0.001,0.0007148907167777357,0.0005526398589811358,0.0003450262214786548,0.00021620823613271921,0.00013581813150424676,8.545453691240582e-05,5.3821629494988794e-05,3.392048307301558e-05,2.1386873841072776e-05
+0.001,0.0007142161543980302,0.0005519610151552632,0.0003443580235484482,0.00021569305634208547,0.00013545631457844443,8.521173706397784e-05,5.366268933409295e-05,3.381792035746172e-05,2.1321256433336487e-05
+0.001,0.0007135471238866448,0.0005512879443055973,0.0003436960129838173,0.0002151828925541902,0.0001350981292399717,8.497142027417112e-05,5.350539363884576e-05,3.371642654533412e-05,2.1256326012778444e-05
+0.001,0.0007128836130908273,0.0005506206290316834,0.00034304015941680915,0.00021467771459500972,0.00013474355121214092,8.473356892178238e-05,5.3349730318534455e-05,3.361599360677474e-05,2.1192077349695405e-05
+0.001,0.0007122256099675188,0.0005499590520918091,0.0003423904327834519,0.00021417749261385993,0.00013439255648970008,8.449816558787534e-05,5.319568742351694e-05,3.35166136065783e-05,2.1128505276425763e-05
+0.001,0.0007115731025829938,0.0005493031964022937,0.0003417468033215544,0.0002136821970805245,0.000134045121336186,8.426519305371512e-05,5.304325314373989e-05,3.341827870317759e-05,2.106560468667675e-05
+0.001,0.0007109261960066054,0.0005486531617838624,0.0003411093543337103,0.00021319188469384628,0.00013370128216574169,8.403467429429362e-05,5.289244191063335e-05,3.3320997960119286e-05,2.1003381278303992e-05
+0.001,0.0007102848782749661,0.0005480089311096272,0.00034047805604549785,0.00021270652596543237,0.00013336101530442401,8.380659214968773e-05,5.274324196034732e-05,3.3224763568979684e-05,2.0941829967612013e-05
+0.001,0.0007096491375319776,0.0005473704874075498,0.00033985287897724074,0.00021222609171923644,0.00013302429733989257,8.358092965463258e-05,5.25956416646764e-05,3.312956781229619e-05,2.088094573050621e-05
+0.001,0.0007090189620285115,0.0005467378138598193,0.00033923379394201156,0.00021175055308892372,0.0001326911051189623,8.335767003660405e-05,5.244962952967474e-05,3.3035403062615115e-05,2.0820723601860106e-05
+0.001,0.0007083951884833238,0.0005461117507284293,0.0003386216233705354,0.00021128054172409337,0.00013236188112429926,8.31371097341464e-05,5.230539940125761e-05,3.294239432192892e-05,2.076124352066865e-05
+0.001,0.0007077778041323896,0.000545492279490185,0.00033801633474888146,0.00021081602540817874,0.00013203659950671687,8.291923002160208e-05,5.216293844781483e-05,3.285053307562121e-05,2.0702499944560498e-05
+0.001,0.0007071667963482699,0.0005448793818164008,0.0003374178959240363,0.00021035697230232543,0.00013171523473119512,8.270401240613943e-05,5.202223399957759e-05,3.2759810917439646e-05,2.064448740210184e-05
+0.001,0.0007065621526397901,0.000544273039572169,0.0003368262751014692,0.00020990335094223987,0.0001313977615739679,8.249143862546502e-05,5.188327354697137e-05,3.267021954836586e-05,2.0587200492045967e-05
+0.001,0.0007059638606517004,0.0005436732348155853,0.0003362414408426963,0.00020945513023505862,0.00013108415511962746,8.228149064554578e-05,5.174604473897535e-05,3.258175077549588e-05,2.053063388259103e-05
+0.001,0.0007053719081643225,0.0005430799497970297,0.00033566336206289793,0.00020901227945626015,0.00013077439075827684,8.20741506583782e-05,5.161053538152209e-05,3.249439651094783e-05,2.047478231065629e-05
+0.001,0.0007047863993885064,0.0005424932828039034,0.0003350921191971394,0.0002085748525953015,0.00013046850282623395,8.186944018288875e-05,5.147675893062123e-05,3.240816518060804e-05,2.0419651063027786e-05
+0.001,0.0007042073221500205,0.000541913216142546,0.0003345276813035574,0.00020814281911618103,0.00013016646689064054,8.166734155142674e-05,5.134470329367606e-05,3.232304876615549e-05,2.0365234922821375e-05
+0.001,0.0007036346644028755,0.0005413397323015136,0.0003339700177764314,0.00020771614883326046,0.00012986825880927205,8.146783731136239e-05,5.121435652738549e-05,3.2239039349161415e-05,2.0311528738515718e-05
+0.001,0.0007030684142289592,0.0005407728139509093,0.00033341909834398085,0.00020729481190839792,0.00012957385472790145,8.12709102230124e-05,5.1085706836262186e-05,3.215612911007561e-05,2.0258527423278803e-05
+0.001,0.0007025087877125606,0.0005402126735385767,0.0003328751197405316,0.00020687895394469412,0.00012928335419699167,8.107662593993734e-05,5.095879672189383e-05,3.2074345280702784e-05,2.0206248321016987e-05
+0.001,0.0007019557729111361,0.0005396592936234858,0.0003323380514212155,0.00020646854484108668,0.0001289967331620245,8.088496708343894e-05,5.083361429641059e-05,3.1993679981452625e-05,2.0154686306347033e-05
+0.001,0.0007014093580122255,0.0005391126569487217,0.00033180786317787807,0.00020606355484577673,0.00012871396785738722,8.069591648818549e-05,5.071014781993386e-05,3.191412543168724e-05,2.010383631860697e-05
+0.001,0.0007008695313331482,0.0005385727464408199,0.0003312845251369297,0.00020566395455347188,0.0001284350348038258,8.050945720021523e-05,5.058838569914163e-05,3.1835673948741706e-05,2.0053693361205354e-05
+0.001,0.0007003362813206957,0.0005380395452091099,0.00033076800775717,0.00020526971490259695,0.00012815991080588224,8.032557247492852e-05,5.046831648582724e-05,3.175831794694013e-05,2.0004252500969603e-05
+0.001,0.0006998095965508554,0.0005375130365450592,0.00033025828182767485,0.00020488080717254625,0.00012788857294937395,8.014424577511121e-05,5.0349928875481843e-05,3.168204993662801e-05,1.9955508867504938e-05
+0.001,0.0006992849713647436,0.000536988737498668,0.0003297510574308719,0.00020449398184933928,0.0001276187643023316,7.996397313508213e-05,5.023224268320585e-05,3.160623916862529e-05,1.9907059627792014e-05
+0.001,0.0006987624017369506,0.0005364666423066755,0.0003292463243531191,0.00020410922866516542,0.000127350476544274,7.978474848904117e-05,5.011525373583123e-05,3.153088286679667e-05,1.985890297191875e-05
+0.001,0.0006982418836227756,0.0005359467451858974,0.000328744072370431,0.00020372653735498857,0.00012708370136324496,7.960656578019794e-05,4.9998957867578574e-05,3.1455978260416835e-05,1.9811037093701456e-05
+0.001,0.0006977234129582083,0.0005354290403332512,0.00032824429124863073,0.00020334589765671668,0.0001268184304559618,7.942941896086744e-05,4.988335092011608e-05,3.138152258420484e-05,1.976346019070644e-05
+0.001,0.0006972049031024503,0.0005349114284143175,0.00032774491556384407,0.00020296571741865816,0.00012655354571184963,7.925255773427056e-05,4.976794174339877e-05,3.130719890433304e-05,1.971596949574029e-05
+0.001,0.0006966863521517465,0.000534393907423076,0.000327245942795149,0.00020258599425811892,0.00012628904521745982,7.907598070306232e-05,4.965272937294146e-05,3.123300657741713e-05,1.966856458850977e-05
+0.001,0.000696167758177353,0.0005338764753221901,0.0003267473703778833,0.00020220672575398438,0.00012602492703077633,7.889968645020544e-05,4.95377128311886e-05,3.1158944951577065e-05,1.9621245043263798e-05
+0.001,0.0006956491192256274,0.0005333591300431401,0.0003262491957040711,0.00020182790944721542,0.00012576118918167348,7.872367353931904e-05,4.942289112776892e-05,3.108501336660957e-05,1.957401042890837e-05
+0.001,0.0006951304333180151,0.0005328418694862771,0.0003257514161227785,0.00020144954284132072,0.00012549782967232552,7.854794051499734e-05,4.9308263259716635e-05,3.1011211154138606e-05,1.9526860309103978e-05

tests/data/test_lumped_losses_raman_fiber.csv

@@ -1,98 +1,99 @@
-0.001,0.0007651928200015371,0.0006070713937965498,0.00041423535558437785,0.0002897888610631573,0.00021340907299884933,0.00017198131811953097,0.00016127923791982795,0.00019503601408127412,0.00036549739730595273
-0.001,0.0007645995806173374,0.0006064422887178694,0.00041349144049413134,0.00028906380160320487,0.00021270693331134475,0.0001712438796411692,0.0001603765556252246,0.00019363496213474675,0.00036239423700181427
-0.001,0.0007640065772643761,0.0006058136176614386,0.00041274866023030733,0.0002883403899406645,0.0002120069527025505,0.00017050944162049183,0.000159478716966613,0.00019224364342300643,0.0003593168093314386
-0.001,0.0007634138087852742,0.000605185379478,0.0004120070127662441,0.0002876186224176594,0.00021130912485491145,0.00016977799240843955,0.0001585856969223786,0.00019086199210672448,0.0003562649023666937
-0.001,0.0007628028346998721,0.0006045332187986192,0.0004112166712442958,0.0002868226029691562,0.00021050564591298308,0.0001688917074786142,0.00015743651373617922,0.00018893812235512526,0.0003514029291704815
-0.001,0.0007621921143131398,0.0006038815297458003,0.00041042762231867933,0.00028602858816935265,0.00020970502628600424,0.00016800982241073787,0.00015629534163924753,0.00018703308452519017,0.00034660591682276115
-0.001,0.0007615816463554626,0.0006032303109890501,0.0004096398633263614,0.0002852365728026657,0.00020890725596775628,0.00016713231600712825,0.00015516212643578583,0.00018514669874176095,0.00034187301148734186
-0.001,0.0007609692265548555,0.000602577299493926,0.0004088509941253184,0.00028444450359523985,0.00020811064471691694,0.00016625772561605027,0.00015403541161623416,0.00018327705284413884,0.00033720006213702974
-0.001,0.0007603548574442921,0.0006019224999904981,0.0004080610253035772,0.00028365239238410656,0.0002073152021201705,0.00016538605339556675,0.00015291517504370476,0.00018142402424673905,0.0003325863766610152
-0.001,0.0007597350402439383,0.0006012612395706585,0.0004072600935672035,0.0002828447987841907,0.00020649842223713097,0.00016448344741808307,0.00015174362495246272,0.00017946021794659197,0.00032758319657592714
-0.001,0.0007591132829776185,0.0006005982088110791,0.0004064581175876688,0.00028203726728774387,0.00020568299547110922,0.00016358411213968798,0.00015057934813125987,0.00017751539893581778,0.00032265060787650516
-0.001,0.000758484736453085,0.0005999283660908604,0.0004056495676510805,0.00028122495212139567,0.00020486486304104927,0.00016268449575399985,0.00014941879820841596,0.00017558496339953558,0.0003177787884410679
-0.001,0.0007578494094215417,0.0005992517275730322,0.0004048344831924046,0.000280407904430663,0.00020404408117776887,0.0001617846565020927,0.00014826202727426984,0.00017366890284920263,0.0003129672376410902
-0.001,0.0007572073108060312,0.0005985683096346821,0.0004040129039083478,0.0002795861755026316,0.00020322070604404603,0.00016088465224596546,0.00014710908652278506,0.00017176720707727308,0.00030821545426856767
-0.001,0.0007565575890478602,0.00059787696153193,0.0004031823074325593,0.00027875567967892653,0.00020238859856737548,0.00015997497741322437,0.00014594324831107206,0.00016984173084389243,0.0003033838449669414
-0.001,0.0007559011152632264,0.0005971788697390111,0.00040234530612592536,0.0002779206290242912,0.00020155405878687617,0.00015906535701622418,0.0001447815990558725,0.00016793142878541938,0.0002986152551090434
-0.001,0.000755237898986442,0.000596474051424026,0.00040150194087318277,0.00027708107588917086,0.00020071714346489746,0.00015815584855490808,0.00014362418708307366,0.00016603627832169687,0.00029390910930431773
-0.001,0.0007545681886825906,0.0005957627683701927,0.00040065250958751827,0.00027623729012494873,0.00019987808563904174,0.00015724665811831285,0.0001424712015659587,0.00016415642490307197,0.0002892651425802985
-0.001,0.0007538919937536639,0.0005950450374279253,0.0003997970520738093,0.0002753893223189692,0.00019903693960802692,0.00015633783972296886,0.0001413226854400146,0.00016229183664828758,0.0002846827650697017
-0.001,0.0007532045557665671,0.0005943145247994342,0.0003989223236188871,0.00027451662339635243,0.0001981640806362608,0.00015538551594067732,0.00014010540813129958,0.00016028630721570607,0.00027963581042999
-0.001,0.0007525106592079478,0.0005935776116184588,0.00039804170193550713,0.0002736399653899091,0.00019728948692008958,0.00015443417816766013,0.00013889388158999866,0.0001582996284854468,0.0002746667454821644
-0.001,0.0007518104383956622,0.000592834444449282,0.0003971553683797481,0.0002727595219957832,0.00019641331428482412,0.00015348396557824612,0.00013768822268133468,0.000156331819705631,0.00026977480754699626
-0.001,0.0007511039033537896,0.0005920850408658466,0.0003962633635582371,0.00027187534416274955,0.00019553561634171146,0.00015253492870981108,0.00013648846139846028,0.00015438279270990136,0.0002649590347362105
-0.001,0.0007503910642803073,0.0005913294186556257,0.0003953657283217157,0.0002709874829437419,0.00019465644657888978,0.0001515871176567501,0.0001352946268320504,0.0001524524582210848,0.0002602184722292356
-0.001,0.0007496855573046408,0.0005905851062898704,0.00039449552403657745,0.00027014241927282736,0.0001938361803657908,0.0001507194393001951,0.00013421767536698768,0.000150722476765932,0.0002559376038022294
-0.001,0.0007489737467556278,0.0005898345737440663,0.000393619635985906,0.00026929349394052985,0.00019301404332913125,0.00014985216957655317,0.00013314488789598826,0.00014900672746282064,0.00025171693602497907
-0.001,0.0007482556429977025,0.0005890778388714725,0.00039273810426086416,0.0002684407562332248,0.0001921900867993824,0.00014898535811302548,0.00013207630234912348,0.00014730517414690737,0.000247555825445753
-0.001,0.000747532135526673,0.0005883158165865031,0.0003918519024244402,0.00026758503804540166,0.0001913649895279964,0.00014811957577380352,0.00013101244041258906,0.0001456183389249714,0.00024345460151209766
-0.001,0.0007468032330641541,0.0005875485221384682,0.0003909610648762846,0.00026672638132361175,0.0001905387943939666,0.00014725486211264363,0.00012995332641946747,0.00014394616337354944,0.00023941257691738652
-0.001,0.0007460689444707028,0.0005867759709451519,0.0003900656262003575,0.00026586482808789615,0.00018971154418348472,0.00014639125636754904,0.00012889898406950181,0.00014228858823944247,0.00023542906884335907
-0.001,0.0007453292787585437,0.0005859981786120694,0.0003891656212152682,0.00026500042051039684,0.000188883281693472,0.0001455287975953345,0.000127849436626481,0.0001406455538271199,0.00023150340029334736
-0.001,0.0007445843685250069,0.0005852152884984452,0.0003882612223549495,0.00026413331906842847,0.00018805414639063353,0.00014466760638632992,0.00012680478406473458,0.00013901709088191773,0.00022763506393382832
-0.001,0.0007438342228409441,0.0005844273161744179,0.0003873524639441998,0.00026326356496406687,0.00018722417962072503,0.0001438077197030893,0.00012576504647438162,0.00013740313489262333,0.00022382338328436597
-0.001,0.0007430788509165626,0.0005836342773781009,0.0003864393804873395,0.0002623911994661588,0.00018639342263244998,0.00014294917419819004,0.000124730243348245,0.00013580362065026603,0.00022006768669446508
-0.001,0.000742327254060605,0.0005828476385639736,0.00038554300530339766,0.00026154496076193957,0.00018559797011481673,0.0001421370333657246,0.00012375932796391997,0.00013430279846409174,0.00021649152387618443
-0.001,0.0007415704350109161,0.0005820559385468977,0.00038464228372291103,0.0002606960153281244,0.00018480150743526303,0.00014132579578003348,0.000122792459010487,0.0001328143978658426,0.0002129659469511457
-0.001,0.0007408084031449065,0.0005812591931755618,0.00038373724983374976,0.00025984440338310303,0.0001840040745362742,0.0001405154975809745,0.00012182965960439977,0.00013133837476817992,0.00020949038404752677
-0.001,0.0007400427720784002,0.0005804590496942265,0.00038282961864956994,0.0002589915613698488,0.00018320681873232144,0.00013970708155515462,0.00012087177639736769,0.00012987560432955444,0.00020606578076074432
-0.001,0.0007392735475065714,0.0005796555183614057,0.00038191941292656456,0.0002581375157328154,0.0001824097650442608,0.00013890056717630873,0.00011991881140841177,0.0001284260094133047,0.00020269149646849757
-0.001,0.0007385007352097838,0.0005788486095364762,0.00038100665551987393,0.00025728229294257515,0.00018161293842329387,0.00013809597373520515,0.00011897076635433426,0.0001269895128043655,0.00019936689671873207
-0.001,0.0007377243410529983,0.0005780383336785572,0.0003800913693799712,0.0002564259194903244,0.00018081636374445108,0.00013729332033271256,0.00011802764264291933,0.00012556603720150224,0.00019609135315036536
-0.001,0.0007369464655998592,0.0005772268587748353,0.0003791758785432219,0.0002555703831979673,0.00018002165393456068,0.00013649394990366146,0.00011709066577140669,0.00012415690240967774,0.0001928666431485617
-0.001,0.0007361671107233329,0.000576414188654825,0.000378260191109379,0.00025471569177879693,0.0001792288130669198,0.00013569785799734456,0.00011615980704210183,0.00012276198311838844,0.00018969202938803596
-0.001,0.0007353862783344302,0.000575600327192691,0.00037734431522203,0.00025386185296321013,0.00017843784520433673,0.00013490504014296103,0.00011523503783001357,0.00012138115492992521,0.0001865667844236815
-0.001,0.0007346027258369329,0.0005747835721418604,0.00037642443290667116,0.0002530026346493095,0.000177639416207763,0.0001341012793025371,0.0001142922256260196,0.00011996295037667013,0.00018332302768968173
-0.001,0.0007338177018431625,0.0005739656376861859,0.00037550439543261463,0.0002521443237629474,0.00017684294734265143,0.00013330094534015117,0.00011335582519792064,0.00011855974750452474,0.00018013280630154984
-0.001,0.0007330312083387708,0.0005731465277735759,0.000374584210907019,0.00025128692777751636,0.0001760484420635206,0.00013250403238709868,0.00011242580398299235,0.00011717140625198769,0.000176995286763841
-0.001,0.0007322450716827681,0.0005723280950701311,0.00037366577307640326,0.00025043200586833656,0.00017525712146802507,0.00013171151729665014,0.00011150300328069361,0.00011579873047427355,0.00017391111613739919
-0.001,0.0007314592892342591,0.0005715103366354928,0.0003727490765712826,0.00024957954955556494,0.0001744689721973381,0.00013092337604814113,0.00011058736861417956,0.00011444154833756723,0.0001708794064250159
-0.001,0.0007306738583803173,0.0005706932495677312,0.00037183411609277345,0.00024872955044744495,0.00017368398100343736,0.0001301395848004509,0.00010967884595770732,0.00011309968990727626,0.00016789928423747183
-0.001,0.0007298887765314699,0.0005698768309963597,0.00037092088639398746,0.0002478820002115871,0.00017290213471209804,0.00012936011984533696,0.0001087773816703527,0.00011177298701463364,0.00016496989019036454
-0.001,0.0007291058850619836,0.0005690629705872476,0.0003700113801847071,0.0002470385774678141,0.00017212477134492983,0.0001285860674779147,0.00010788392632853856,0.00011046237940908493,0.00016209217355659912
-0.001,0.0007283251776795193,0.0005682516594285885,0.0003691055790623401,0.0002461992575642169,0.00017135185999287266,0.00012781738439880834,0.00010699840217906239,0.00010916766306641233,0.00015926520709064215
-0.001,0.000727546648123048,0.000567442888658507,0.0003682034647519281,0.00024536401604150686,0.00017058337001160307,0.00012705402771768452,0.00010612073231230378,0.0001078886367084761,0.00015648808062028533
-0.001,0.0007267691175258129,0.0005666351120658079,0.00036730194585451363,0.00024452825978826814,0.00016981299319253088,0.00012628722374912656,0.00010523753204397677,0.00010660034638564814,0.00015369233245141463
-0.001,0.0007259937543683618,0.0005658298620581495,0.00036640409142867466,0.00024369656281803695,0.0001690470312136919,0.00012552576286196436,0.00010436224908854787,0.00010532792661952348,0.00015094700928094292
-0.001,0.0007252205525006216,0.0005650271299429238,0.0003655098835814395,0.0002428689011484816,0.0001682854538881413,0.00012476960247399048,0.00010349480634605481,0.00010407117393308648,0.00014825118806841486
-0.001,0.0007244515476870691,0.0005642289688561167,0.00036462138604045246,0.00024204694758546622,0.00016752954803985582,0.00012401974721449815,0.00010263603739686231,0.00010283083470852359,0.0001456053538142381
-0.001,0.0007236867286572494,0.0005634353625294562,0.0003637385663464586,0.00024123066115747858,0.00016677926586679636,0.00012327613591461942,0.00010178584352378332,0.00010160667618634935,0.0001430085413998934
-0.001,0.0007229260842094953,0.0005626462948017631,0.0003628613922977866,0.00024042000126051454,0.00016603456004153966,0.00012253870808207087,0.0001009441272602465,0.00010039846917127745,0.000140459805170444
-0.001,0.0007221696032014468,0.000561861749604344,0.00036198983191176377,0.0002396149275989645,0.00016529538363567852,0.00012180740380654271,0.00010011079225737115,9.920598777483068e-05,0.00013795821792425024
-0.001,0.0007214188723728384,0.00056108334509554,0.0003611255610840681,0.0002388168283348348,0.00016456282140960994,0.00012108307905286178,9.928655238677393e-05,9.802986918413655e-05,0.0001355041849544529
-0.001,0.0007206738776295639,0.0005603110603628828,0.0003602685373417506,0.00023802565027806571,0.00016383681258690845,0.00012036565891864721,9.847129356381268e-05,9.686986333449523e-05,0.0001330967445342526
-0.001,0.0007199346049934109,0.0005595448746691314,0.00035941871861020354,0.00023724134078502595,0.00016311729706930416,0.00011965506942237431,9.7664903298557e-05,9.57257243308077e-05,0.00013073495556510661
-0.001,0.0007192103057281418,0.0005587965882928195,0.000358597914203722,0.00023649404923234267,0.0001624426539507404,0.00011900000933912548,9.693290327537121e-05,9.469853254875163e-05,0.0001286228242214262
-0.001,0.0007184916860834766,0.000558054333130965,0.0003577841401235257,0.0002357533416394368,0.00016177407584741055,0.00011835110239617177,9.620855295571759e-05,9.368449216343134e-05,0.0001265476735456528
-0.001,0.000717778732645577,0.0005573180893469085,0.0003569773567342285,0.0002350191694371068,0.0001611115088719043,0.00011770828481211398,9.549176022876216e-05,9.268341301362701e-05,0.00012450880618841231
-0.001,0.0007170715507844816,0.0005565879566941514,0.0003561776441627035,0.00023429158098135867,0.00016045497378223205,0.00011707155159443024,9.47824835635146e-05,9.169515755193108e-05,0.00012250560759307665
-0.001,0.0007163701270344053,0.0005558639152622166,0.0003553849627325309,0.00023357052778616886,0.00015980441694230793,0.00011644083951173604,9.408063218207804e-05,9.071953997714039e-05,0.00012053740486430812
-0.001,0.0007156744480415676,0.0005551459453084167,0.00035459927313802623,0.00023285596185845654,0.00015915978530381373,0.00011581608608941654,9.338611653058621e-05,8.975637744384618e-05,0.00011860353870291344
-0.001,0.0007149845005557793,0.0005544340272448129,0.0003538205364097734,0.0002321478356456351,0.0001585210263398076,0.00011519722952770958,9.269884816673769e-05,8.880548985453175e-05,0.00011670336266552508
-0.001,0.0007143011352806332,0.0005537290222260827,0.0003530496254918224,0.00023144685778402562,0.00015788868071804074,0.00011458468167101622,9.20191492389152e-05,8.786712068874325e-05,0.00011483685132763588
-0.001,0.0007136243377311475,0.0005530309085687206,0.00035228649684153725,0.0002307529751854999,0.00015726269010384348,0.00011397837465469773,9.134692457668887e-05,8.694108196461404e-05,0.00011300335424584403
-0.001,0.0007129540935643617,0.0005523396647985742,0.000351531107363628,0.0002300661353432777,0.0001566429968410848,0.00011337824146720777,9.06820803490277e-05,8.602718880727694e-05,0.00011120223452206596
-0.001,0.0007122949300063586,0.0005516609446370161,0.0003507932546232374,0.0002293990178082647,0.00015604454205901748,0.00011280134646728481,9.004396195380538e-05,8.514641523915274e-05,0.00010944396621311202
-0.001,0.0007116422850379047,0.0005509890404263221,0.00035006301886912226,0.00022873877079420107,0.00015545216193435095,0.00011223032450910806,8.941277122627028e-05,8.427699754143763e-05,0.00010771649233683978
-0.001,0.0007109961448775265,0.0005503239315436604,0.00034934035900275196,0.00022808534468017605,0.00015486580256638324,0.00011166511373672321,8.878842266662507e-05,8.341876815036907e-05,0.00010601922394974779
-0.001,0.0007103566138672342,0.0005496657159311855,0.0003486253516297722,0.00022743878433373037,0.00015428548213839886,0.00011110570832676001,8.81708780194749e-05,8.25716070442755e-05,0.00010435164299643007
-0.001,0.0007097236782517396,0.0005490143729973408,0.0003479179557857281,0.0002267990403962617,0.0001537111471536449,0.00011055204708289399,8.756005313455197e-05,8.173535064610718e-05,0.0001027131817052566
-0.001,0.0007090973244087274,0.0005483698823458906,0.00034721813091834777,0.000226166064037726,0.00015314274472297157,0.00011000406955950422,8.695586501935841e-05,8.090983803329783e-05,0.00010110328401062253
-0.001,0.0007084775388425413,0.0005477322237660661,0.0003465258368613831,0.00022553980691704316,0.00015258022251510344,0.00010946171600087524,8.635823175652435e-05,8.00949107862898e-05,9.952140501322636e-05
-0.001,0.0007078645400735427,0.0005471016129101978,0.0003458412757255009,0.00022492042013778988,0.00015202368335334558,0.00010892504915290583,8.57671759148139e-05,7.929051589048381e-05,9.796715152670613e-05
-0.001,0.0007072583145347741,0.0005464780293804963,0.00034516440688163317,0.00022430785483116316,0.0001514730744232032,0.00010839400891826328,8.518261565996433e-05,7.84964968569563e-05,9.643999410136803e-05
-0.001,0.0007066588487940405,0.000545861452976259,0.0003444951901125997,0.00022370206265319418,0.00015092834351042303,0.00010786853593723236,8.460447028623623e-05,7.771269974698105e-05,9.493941424410264e-05
-0.001,0.0007060768113835355,0.0005452653567881146,0.00034385780916102886,0.0002231355522451839,0.0001504295746545273,0.00010739737531972382,8.409424224945842e-05,7.702434963545377e-05,9.360618912201228e-05
-0.001,0.0007055014939207988,0.0005446762036784223,0.00034322791998477503,0.0002225755642266546,0.00014993632274793293,0.00010693123855410087,8.358951092264173e-05,7.634435339541097e-05,9.22944227993744e-05
-0.001,0.0007049328836329239,0.0005440939744776738,0.0003426054850001757,0.00022202205441602206,0.000149448541485554,0.00010647007505716636,8.309021096715739e-05,7.567259318109089e-05,9.100372969350909e-05
-0.001,0.0007043664108869901,0.0005435140913972429,0.00034198598587466614,0.00022147141590047654,0.00014896349766232102,0.00010601178096740148,8.259459730216135e-05,7.500736724232048e-05,8.973176442333615e-05
-0.001,0.0007038020712072354,0.0005429365478183962,0.00034136940918446675,0.0002209236320980648,0.00014848117283038098,0.00010555633431743894,8.210263744821714e-05,7.434860458126827e-05,8.847824135377829e-05
-0.001,0.0007032398600991381,0.0005423613371043419,0.00034075574151016483,0.0002203786864681782,0.00014800154862415601,0.00010510371328265478,8.161429921011451e-05,7.369623501807121e-05,8.724287943554497e-05
-0.001,0.0007026797730466592,0.0005417884525961108,0.00034014496942632764,0.0002198365624959981,0.00014752460674093983,0.00010465389615779026,8.112955064604149e-05,7.305018913687007e-05,8.602540201539488e-05
-0.001,0.0007021196874055633,0.0005412157406692665,0.0003395348927353949,0.00021929545761274023,0.00014704895219343257,0.00010420578859113516,8.064746506639534e-05,7.240953347459202e-05,8.482441661675139e-05
-0.001,0.0007015596012323657,0.0005406431992153213,0.0003389255082691921,0.00021875536780717296,0.00014657457987728414,0.00010375938295149973,8.016802726693694e-05,7.17742234562459e-05,8.363970356449741e-05
-0.001,0.0007009995125587165,0.0005400708260946051,0.0003383168128172846,0.00021821628903476192,0.00014610148467187763,0.0001033146716169485,7.969122211456026e-05,7.114421486558773e-05,8.247104609297546e-05
-0.001,0.000700426120570031,0.0005394817717340144,0.00033767827777106695,0.00021763678242090514,0.00014557802543177205,0.00010280805245363877,7.913535785684264e-05,7.040274681183516e-05,8.111172191387726e-05
-0.001,0.0006998527383823768,0.0005388929110101418,0.0003370405259007354,0.00021705847496470142,0.00014505616500334602,0.00010230367256069614,7.858312049704058e-05,6.966868896041247e-05,7.977423771714316e-05
-0.0010496228983614124,0.002020602352332682,0.0024834354692445607,0.004712247621156641,0.00854174709233096,0.015197203876184536,0.027142477151470907,0.049749449744480465,0.09589624880110185,0.2
-0.004235602571438949,0.007336805952289255,0.008714058005603317,0.015024716476258112,0.025061770718850837,0.04079161627542227,0.0649508755581543,0.10074574737193842,0.14993445055894863,0.206
+0 km,7 km,10 km,20 km,30 km,40 km,50 km,60 km,70 km,80 km
+0.001,0.0007654185419972524,0.0006073276056093792,0.0004146475603472041,0.0002902671662170687,0.00021391771777705748,0.0001725335650783217,0.0001619576961300996,0.00019613348481478226,0.00036856555154569
+0.001,0.0007648265274364283,0.0006066999211698721,0.00041390447843586643,0.00028954214777674505,0.00021321488386807227,0.000171794621873672,0.00016105212098646378,0.00019472570335261124,0.00036543839103292923
+0.001,0.00076423475082742,0.0006060726714187721,0.00041316253063080743,0.0002888187769396436,0.00021251421079625184,0.0001710586847350929,0.00016015140443848455,0.0001933277019274264,0.0003623371672096105
+0.001,0.0007636432110143774,0.0006054458552058583,0.0004124217148997164,0.0002880970500399001,0.00021181569222935437,0.00017032574197864756,0.00015925552136261768,0.00019193941431515274,0.0003592616661738057
+0.001,0.00076303338083269,0.0006047950045143256,0.0004116319711720434,0.0002873006965446473,0.00021101094555209704,0.00016943701776024394,0.00015810165194844262,0.00019000410483730154,0.00035435344277520014
+0.001,0.0007624238065102939,0.0006041446264165162,0.00041084352013847123,0.0002865063493191246,0.0002102090638489634,0.00016855270795343295,0.00015695583271993784,0.000188087762219128,0.00034951092824224374
+0.001,0.0007618144867783217,0.0006034947195801519,0.00041005635912737644,0.00028571400313117073,0.000209410037075066,0.00016767279125308264,0.000155818009114819,0.0001861902048930817,0.00034473325633896016
+0.001,0.0007612032230964268,0.0006028430274261829,0.0004092680923152776,0.00028492160640338084,0.00020861217469969167,0.00016679580316719344,0.00015468672086849377,0.00018430951195784153,0.0003400162401556392
+0.001,0.0007605900180176352,0.0006021895546863309,0.000408478730269415,0.00028412917095061395,0.00020781548628341263,0.00016592174578786424,0.0001535619455802766,0.00018244555944842464,0.000335359176825339
+0.001,0.0007599713504055552,0.0006015295991965402,0.0004076783487865176,0.0002833211587561824,0.00020699731581240013,0.00016501652229006483,0.00015238542164450143,0.000180469716663273,0.00033030742335106797
+0.001,0.0007593507507343548,0.0006008678808679657,0.00040687692763931326,0.0002825132124386522,0.00020618050489600874,0.00016411458466993175,0.0001512162128542595,0.00017851301079839705,0.00032532712476693115
+0.001,0.0007587233815624382,0.0006001993719156019,0.00040606894689472706,0.0002817004901671922,0.0002053609939218913,0.0001632123763493078,0.00015005076311129325,0.00017657081573262424,0.0003204083683965919
+0.001,0.0007580892517126006,0.0005995240885208491,0.0004052544459439752,0.0002808830430533993,0.00020453883912382008,0.0001623099555953223,0.0001488891244397257,0.00017464312199372379,0.0003155506430768726
+0.001,0.000757448370179369,0.0005988420470784952,0.00040443346443882024,0.0002800609223493252,0.00020371409666633197,0.00016140738029416416,0.00014773134796391561,0.00017272991838834854,0.0003107534371554913
+0.001,0.0007567998780637095,0.00059815208713495,0.0004036034596839685,0.0002792300099339312,0.0002028805779162198,0.0001604950646725177,0.00014656055358564036,0.0001707926621492761,0.00030587527063737443
+0.001,0.0007561446539823046,0.0005974554049330684,0.00040276706435836743,0.0002783945504517164,0.00020204463288750894,0.00015958281494627715,0.00014539398266818048,0.00016887071348766508,0.00030106092293455183
+0.001,0.0007554827075416216,0.0005967520176577599,0.00040192431930056663,0.00027755459621831854,0.00020120631834502002,0.0001586706886366497,0.00014423168344504801,0.00016696404870095068,0.0002963098069760517
+0.001,0.0007548142866478835,0.0005960421864035,0.00040107552190864405,0.000276710416864016,0.00020036586735025836,0.00015775889202640647,0.00014307384532883863,0.00016507281278915244,0.00029162164835553234
+0.001,0.0007541394007727726,0.0005953259280357876,0.00040022071194032425,0.0002758620629396957,0.00019952333420039184,0.0001568474791446172,0.00014192051114461952,0.000163196972716382,0.0002869958456117749
+0.001,0.000753453261276124,0.0005945968692177485,0.0003993465628625302,0.0002749888554209862,0.00019864889698783253,0.00015589225679197793,0.00014069786108208423,0.00016117883466097707,0.0002818995386546663
+0.001,0.0007527606830746849,0.0005938614307668164,0.00039846653446453577,0.00027411169702333635,0.00019777273283424246,0.00015493803621995225,0.00013948100714945055,0.00015917971666279146,0.00027688213338452353
+0.001,0.000752061800251107,0.000593119758904669,0.0003975808078042764,0.0002732307613051971,0.00019689499757748,0.00015398495670235495,0.00013827006619590224,0.00015719963654088831,0.0002719428500764955
+0.001,0.0007513566228984858,0.0005923718712186205,0.00039668942343994645,0.00027234609917798486,0.0001960157448213401,0.0001530330687596212,0.0001370650679700252,0.0001552385042294358,0.000267080708365827
+0.001,0.0007506451612836396,0.000591617785508762,0.0003957924221725467,0.000271457761656054,0.00019513502804513515,0.00015208242246717618,0.00013586604131538964,0.00015329622856198138,0.00026229473523033993
+0.001,0.0007499410764512782,0.0005908750616328752,0.0003949229270536377,0.00027061232560569935,0.0001943133661054677,0.00015121214860141992,0.00013478433495717895,0.0001515553239579192,0.0002579720674546429
+0.001,0.0007492307077939692,0.0005901261380362599,0.0003940477612542949,0.0002697630351391033,0.0001934898396676657,0.00015034229582385722,0.00013370682839182124,0.00014982878466439454,0.0002537103994437239
+0.001,0.0007485140657428474,0.0005893710325813375,0.00039316696481225496,0.0002689099395032721,0.00019266450005914697,0.0001494729137699088,0.00013263355942168804,0.00014811657325897344,0.00024950907434075407
+0.001,0.0007477920374988207,0.0005886106575770754,0.00039228150952041026,0.0002680538698732277,0.00019183802609277662,0.00014860457389983926,0.00013156505071301006,0.00014641921273032577,0.00024536841469387607
+0.001,0.0007470646318417684,0.000587845028280153,0.00039139142972943226,0.00026719486815718823,0.00019101046063687028,0.0001477373157547231,0.00013050132642612272,0.00014473664329931894,0.00024128771968956965
+0.001,0.000746331857690334,0.0005870741601150847,0.0003904967599732611,0.0002663329763359202,0.00019018184646592208,0.0001468711785583918,0.00012944241008601634,0.0001430688043627681,0.00023726629318772418
+0.001,0.000745593724114763,0.0005862980686936137,0.0003895975350198339,0.0002654682365419898,0.00018935222636504533,0.00014600620135329296,0.00012838832478192589,0.0001414156348862137,0.00023330344508078714
+0.001,0.0007448503634609417,0.0005855168970231048,0.00038869392700388675,0.0002646008091121948,0.00018852173980288115,0.00014514250481571783,0.00012733917050730646,0.00013977716467553823,0.00022939865638927297
+0.001,0.0007441017848559784,0.0005847306606783223,0.0003877859701983709,0.00026373073520765555,0.0001876904281105713,0.0001442801258881357,0.00012629496716723198,0.0001381533278738466,0.00022555123779529113
+0.001,0.000743347997566111,0.0005839393754013221,0.00038687369905472224,0.00026285805605533836,0.00018685833252122952,0.0001434191012016364,0.000125255734067765,0.0001365440579330561,0.0002217605049922782
+0.001,0.0007425980122165197,0.0005831545190886928,0.0003859781684512971,0.00026201154253776947,0.00018606159531590292,0.00014260456502787665,0.00012428053620243385,0.0001350337902936029,0.00021815009586241928
+0.001,0.0007418428222422646,0.0005823646190291856,0.00038507830193089523,0.00026116232813230903,0.0001852638537460305,0.00014179094397584395,0.00012330941740530514,0.00013353605951814913,0.000214590937375532
+0.001,0.0007410824370750857,0.0005815696910727474,0.00038417413352571667,0.0002603104530145326,0.00018446514774054143,0.00014097827417406666,0.00012234240064855456,0.00013205082038162874,0.00021108244611026217
+0.001,0.0007403184660014679,0.0005807713776603622,0.0003832673750805624,0.0002594573523562161,0.0001836666246937272,0.00014016749938812904,0.00012138033426810311,0.00013057895028626532,0.00020762556561303502
+0.001,0.0007395509147560407,0.0005799696890514251,0.0003823580493090658,0.0002586030525652665,0.00018286830960336872,0.00013935863904919696,0.00012042322007081454,0.00012912037080446074,0.00020421964337946413
+0.001,0.0007387797891584386,0.0005791646356057247,0.0003814461790231548,0.0002577475800751799,0.00018207022739706005,0.00013855171240478834,0.00011947105956106815,0.0001276750034397535,0.00020086403326178727
+0.001,0.0007380050951127038,0.000578356227782297,0.00038053178712941366,0.00025689096133950617,0.0001812724029256328,0.00013774673851177748,0.00011852385393388548,0.0001262427696188339,0.00019755809538624924
+0.001,0.0007372289278765602,0.0005775466274590334,0.00037961719344922816,0.00025603518246549605,0.00018047644930614432,0.00013694506185961904,0.00011758283148187963,0.00012482499369662246,0.0001943036135491255
+0.001,0.0007364512893389424,0.0005767358384619004,0.0003787024060562486,0.0002551802511391958,0.00017968237057615404,0.0001361466779099092,0.00011664796319397039,0.00012342154884218158,0.00019109983808810176
+0.001,0.0007356721814267267,0.0005759238646613067,0.0003777874330677233,0.0002543261750635963,0.00017889017076266666,0.00013535158210437542,0.00011571922013388507,0.00012203230915507028,0.00018794602945024216
+0.001,0.0007348903474707337,0.0005751089853685418,0.00037686841880625214,0.0002534666634479025,0.00017809042928748983,0.00013454542482553396,0.00011477223754870921,0.00012060527355137842,0.0001846722184263047
+0.001,0.0007341070502230424,0.0005742929332546843,0.0003759492523595486,0.00025260806222015907,0.0001772926545344648,0.0001337427099649026,0.00011383170595735486,0.00011919336498115804,0.00018145260378874068
+0.001,0.0007333222916846016,0.0005734757122629472,0.0003750299418068227,0.0002517503788238516,0.00017649684991694604,0.00013294343155185963,0.00011289759243683735,0.00011779644164652425,0.00017828633792123003
+0.001,0.0007325378931581444,0.0005726591695542582,0.00037411237735305734,0.00025089517102575937,0.00017570423657326553,0.00013214856737581396,0.00011197073980433406,0.0001164153090011861,0.00017517406255147756
+0.001,0.0007317538520017976,0.0005718433021851622,0.00037319655361857124,0.00025004243032543557,0.00017491480109484205,0.00013135809328305347,0.0001110510931582075,0.00011504979334922632,0.00017211487548789828
+0.001,0.0007309701656016873,0.0005710281072505973,0.0003722824652942578,0.0002491921483105776,0.0001741285301842189,0.000130571985300518,0.00011013859805243972,0.00011369972292133188,0.00016910788945367707
+0.001,0.0007301868313673829,0.0005702135818768351,0.00037137010712276296,0.0002483443166280691,0.00017334541061775574,0.0001297902195887095,0.00010923320042963165,0.00011236492773944517,0.00016615223146969552
+0.001,0.0007294056858799279,0.0005694016103111181,0.00037046146816096116,0.0002475006124214696,0.00017256678052747222,0.0001290138836109195,0.0001083358528422491,0.00011104635018836138,0.0001632488500459303
+0.001,0.0007286267228265342,0.0005685921836368309,0.00036955653001307385,0.0002466610110284357,0.00017179260894632618,0.00012824293390221287,0.00010744647704539295,0.00010974378427192081,0.00016039680402653037
+0.001,0.0007278499359259242,0.0005677852929874075,0.0003686552744110329,0.000245825487979439,0.00017102286517266867,0.00012747732740860064,0.00010656499564424898,0.00010845702677323144,0.00015759516965436614
+0.001,0.0007270741396329974,0.0005669793834682747,0.00036775459243596013,0.0002449894231786493,0.00017025120181982169,0.00012670823171859124,0.00010567792500018758,0.00010716091111285436,0.00015477474449137119
+0.001,0.000726300509089127,0.0005661759961906673,0.0003668575707603942,0.00024415741777526555,0.00016948395998088835,0.00012594449635600327,0.000104798812682607,0.00010588078664841973,0.00015200532201362785
+0.001,0.0007255290381246482,0.0005653751224576382,0.0003659641914980988,0.00024332944777626794,0.00016872110941070693,0.00012518607857232714,0.00010392758109688598,0.00010461644792633948,0.00014928596543342006
+0.001,0.0007247617567123682,0.0005645788092050789,0.0003650765144822908,0.0002425071844547339,0.00016796393694001768,0.00012443398389681975,0.0001030650652169494,0.00010336864256044427,0.00014661715384500229
+0.001,0.0007239986535454607,0.0005637870401634551,0.0003641945072810511,0.0002416905868396016,0.00016721239470100498,0.00012368815096486452,0.00010221116577265065,0.00010213713571582715,0.00014399790845116419
+0.001,0.0007232397173862652,0.0005629997991705343,0.0003633181377200508,0.00024087961432750444,0.00016646643530137355,0.0001229485190910589,0.00010136578475280116,0.00010092169616032506,0.00014142727026178776
+0.001,0.00072248493705675,0.0005622170701566371,0.0003624473738436701,0.00024007422662323307,0.0001657260117481481,0.0001222150281737581,0.00010052882527084345,9.972209600365954e-05,0.000138904299062937
+0.001,0.0007217358950348228,0.000561440466555814,0.00036158388844431124,0.00023927581064585389,0.0001649922088518066,0.00012148853502428482,9.97010025298723e-05,9.853897375975792e-05,0.00013642939611266722
+0.001,0.0007209925771752469,0.0005606699674539418,0.0003607276390906435,0.00023848431321443392,0.00016426496576549843,0.00012076896452456461,9.888220185750974e-05,9.737207727303015e-05,0.00013400158668478175
+0.001,0.0007202549694492843,0.0005599055521123883,0.0003598785837495114,0.00023769968169456287,0.0001635442223215586,0.00012005624248053424,9.807231018575002e-05,9.622115859912247e-05,0.0001316199170239902
+0.001,0.0007195323462520794,0.0005591590509921624,0.0003590585920958888,0.00023695215697134095,0.00016286848728581805,0.00011939925459233543,9.733714368639992e-05,9.518785816120323e-05,0.00012948993319015237
+0.001,0.0007188153904868624,0.0005584185656809617,0.00035824561959240325,0.0002362112130369942,0.00016219882234612553,0.00011874843483873407,9.660966052802588e-05,9.416779973181015e-05,0.00012739732395025585
+0.001,0.0007181040886926203,0.0005576840763431772,0.00035743962664792336,0.00023547680133784063,0.00016153517356182933,0.00011810371926813217,9.588976814961258e-05,9.316079161517574e-05,0.00012534138272701054
+0.001,0.0007173985458519898,0.0005569556823713467,0.0003566406932084415,0.00023474897015812488,0.0001608775616408074,0.00011746510277705029,9.517742467544867e-05,9.216669491688869e-05,0.00012332148630987257
+0.001,0.0007166987484521553,0.0005562333638566226,0.00035584877964252954,0.00023402767102794237,0.00016022593289484238,0.00011683252196707568,9.447253888812898e-05,9.118532235085734e-05,0.00012133695300052025
+0.001,0.0007160046830928351,0.0005555171010581067,0.00035506384668924896,0.00023331285597027454,0.00015958023422419515,0.00011620591419889337,9.377502080118898e-05,9.021648961473911e-05,0.0001193871149139895
+0.001,0.0007153163364777631,0.0005548068743897313,0.0003542858554234702,0.00023260447744820426,0.00015894041305074621,0.00011558521750971036,9.308478154551746e-05,8.926001517936315e-05,0.00011747131722415646
+0.001,0.0007146345569433116,0.0005541035424399441,0.0003535156771553805,0.00023190324345165713,0.00015830701004295562,0.00011497084410199294,9.240214376206843e-05,8.831614266750221e-05,0.00011558953011398195
+0.001,0.0007139593299513231,0.0005534070835269872,0.0003527532683936443,0.00023120910091256188,0.0001576799668132194,0.0001143627259393922,9.172701183766888e-05,8.738468264977303e-05,0.00011374109491336212
+0.001,0.0007132906411062882,0.000552717476178626,0.00035199858609393853,0.00023052199734406963,0.00015705922565321226,0.00011376079584113645,9.105929150577112e-05,8.646544883197101e-05,0.0001119253667056674
+0.001,0.0007126330184449588,0.0005520403753247726,0.0003512614302897459,0.0002298546155988536,0.00015645973111213718,0.0001131821199461313,9.041832213305081e-05,8.557937250804453e-05,0.00011015252685143603
+0.001,0.000711981898998139,0.0005513700720769836,0.0003505318788510462,0.00022919410061472063,0.0001558663157908185,0.00011260933085632868,8.978431049296584e-05,8.47047300887107e-05,0.00010841080451458245
+0.001,0.0007113372689341813,0.0005507065458152156,0.0003498098907291114,0.00022854040278969112,0.00015527892573799634,0.00011204236655473188,8.91571706762786e-05,8.384135267939557e-05,0.00010669960309782175
+0.001,0.0007106992322019796,0.0005500498941226498,0.0003490955423571875,0.00022789356692450827,0.00015469757908825738,0.00011148122111140715,8.85368641132709e-05,8.298911908997276e-05,0.00010501839736063321
+0.001,0.0007100677749962943,0.0005494000964108962,0.0003483887928208825,0.00022725354367970012,0.00015412222229517684,0.0001109258331719869,8.792330625417495e-05,8.214786445649906e-05,0.00010336661223747767
+0.001,0.0007094428836454011,0.0005487571322870243,0.0003476896016176379,0.00022662028424420426,0.00015355280242059424,0.00011037614213504096,8.731641371338838e-05,8.131742659415625e-05,0.00010174368455214035
+0.001,0.000708824544604701,0.0005481209815436059,0.0003469979286303459,0.00022599374029548395,0.00015298926708448145,0.00010983208809074389,8.671610418600222e-05,8.049764584384383e-05,0.0001001490624678555
+0.001,0.0007082129757140411,0.0005474918591435615,0.0003463139755716002,0.00022537406278014643,0.00015243171907300512,0.00010929373376222763,8.612240008214866e-05,7.968846833775761e-05,9.858234685897841e-05
+0.001,0.000707608163356494,0.0005468697446924577,0.00034563770186245746,0.00022476120284855867,0.000151880105523236,0.00010876101889898551,8.55352191851817e-05,7.888973637819775e-05,9.704300162684373e-05
+0.001,0.0007070100940503908,0.0005462546179930401,0.0003449690673354809,0.0002241551121757662,0.0001513343741731098,0.00010823388399029377,8.495448041312896e-05,7.810129484091103e-05,9.553050179700698e-05
+0.001,0.0007064294568015821,0.0005456599791780414,0.0003443323098548347,0.00022358838010950836,0.00015083471987353974,0.00010776122599922914,8.444190686735427e-05,7.7408734986085e-05,9.418640444056476e-05
+0.001,0.0007058555225588962,0.0005450722639773927,0.0003437030311737585,0.0002230281662249932,0.00015034058581471813,0.00010729360256509277,8.39348527119689e-05,7.67245852554126e-05,9.28639870067709e-05
+0.001,0.0007052882785030611,0.0005444914532267761,0.0003430811937591523,0.00022247442636251605,0.00014985192565331347,0.00010683096298015644,8.343325230960875e-05,7.604872690242875e-05,9.156285904414627e-05
+0.001,0.0007047231683832071,0.0005439129831785586,0.00034246228783126086,0.00022192355689618922,0.00014936600614401393,0.00010637120139586071,8.293535717958106e-05,7.537945268589432e-05,9.028066182205625e-05
+0.001,0.0007041601877072604,0.0005433368472132987,0.00034184629997988753,0.0002213755412469509,0.00014888280881520869,0.00010591429577334988,8.244113465160048e-05,7.471669094184598e-05,8.901710564172274e-05
+0.001,0.0007035993319644686,0.0005427630386936696,0.0003412332167993905,0.00022083036287728357,0.0001484023152778868,0.00010546022421726945,8.195055234184008e-05,7.406037083397318e-05,8.777190547391773e-05
+0.001,0.0007030405966226531,0.0005421915509602746,0.00034062302487816926,0.00022028800527546067,0.00014792450720603156,0.00010500896495215848,8.146357812174912e-05,7.341042229889045e-05,8.65447807653603e-05
+0.001,0.000702481864866424,0.0005416202367428493,0.000340013528083159,0.00021974666745789773,0.00014744798951136416,0.00010455942245749231,8.097928325582809e-05,7.276590831707151e-05,8.53343290345859e-05
+0.001,0.0007019231347536531,0.000541049093933996,0.00033940472324505365,0.0002192063454080809,0.00014697275707368812,0.00010411158905958576,8.049765241221972e-05,7.212678380437272e-05,8.414032725111873e-05
+0.001,0.0007013644043173649,0.0005404781203952333,0.00033879660715245314,0.0002186670350763442,0.0001464988047567028,0.00010366545709431046,8.001867033124847e-05,7.149300404124133e-05,8.296255535497e-05
+0.001,0.0007007923380838431,0.0005398904209305891,0.0003381585602637609,0.00021808716235465733,0.0001459743062317574,0.00010315717126101123,7.946027734643345e-05,7.0747191644443e-05,8.159291401029592e-05
+0.001,0.0007002202839606736,0.0005393029161815334,0.0003375212965814363,0.0002175084901000057,0.0001454514108138073,0.00010265113449578299,7.890553328521924e-05,7.000884795811205e-05,8.02453392500888e-05
+0.0010564983206625808,0.0020323156209598047,0.0024972245821602065,0.004735193374982383,0.008578320915529132,0.015253393937469889,0.027225142859919765,0.049861478431656114,0.09601482521493776,0.2
+0.004249939542299966,0.007357791565894658,0.008737301696751656,0.01505607870396766,0.02510093603015811,0.040835074437955504,0.0649892582783015,0.10076225398432796,0.14991538310282454,0.206

tests/data/test_raman_fiber_expected_results.csv

@@ -1,97 +1,97 @@
 signal,ase,nli
-0.000325019416624,3.8827360617812335e-08,2.397604591245591e-07
-0.0003222815415358,3.8702821151814216e-08,2.4267833614138976e-07
-0.0003195661748689,3.8578942925493807e-08,2.455296149641726e-07
-0.000316873132879,3.8455721305309324e-08,2.483151861322029e-07
-0.0003125687708988,3.815158818797417e-08,2.497308542349044e-07
-0.0003083216327341,3.784989647314237e-08,2.5106122773764815e-07
-0.0003041309702107,3.755062053762566e-08,2.523083160653813e-07
-0.0002999931829076,3.725370771318225e-08,2.534716728592015e-07
-0.0002959076621852,3.695913382975532e-08,2.545532047834699e-07
-0.0002914749637887,3.6620413511505286e-08,2.5520557429118934e-07
-0.0002871045786391,3.62847038107824e-08,2.557776344401253e-07
-0.0002827879891071,3.5951828869209396e-08,2.5626453052593257e-07
-0.0002785247470154,3.562176113110911e-08,2.5666832208790035e-07
-0.0002743144039041,3.5294473123494e-08,2.569910409348857e-07
-0.000270032675166,3.4954880805048256e-08,2.571167784361306e-07
-0.0002658067200554,3.4618272391047544e-08,2.571652788509227e-07
-0.000261636025157,3.428461757057609e-08,2.5713860104931033e-07
-0.00025752034599,3.395388872366444e-08,2.570390408700655e-07
-0.000253459157096,3.362605558722993e-08,2.5284986247287787e-07
-0.000248983782073,3.3242702224575744e-08,2.48252059976888e-07
-0.0002445773493265,3.286328176612301e-08,2.437277481862015e-07
-0.0002402391773459,3.2487750441670215e-08,2.392761376865807e-07
-0.0002359684123723,3.2116061418127753e-08,2.3489626905665574e-07
-0.0002317642070805,3.174816817069829e-08,2.3058719110264335e-07
-0.0002279695550926,3.1424928539548144e-08,2.2668986526609113e-07
-0.0002242281358436,3.1104729317697146e-08,2.228495045304229e-07
-0.0002205393783222,3.078753835343166e-08,2.190654562751529e-07
-0.0002169035545525,3.047333197100547e-08,2.1533790605165431e-07
-0.0002133200561122,3.01620779209974e-08,2.1166616520930645e-07
-0.0002097882786443,2.9853744125792176e-08,2.080495504306458e-07
-0.0002063076230434,2.9548298767727423e-08,2.0448738489666716e-07
-0.0002028776374913,2.9245712991289203e-08,2.009791389793126e-07
-0.0001994977236946,2.8945955168147914e-08,1.975241389908885e-07
-0.0001961672877059,2.8648993828553545e-08,1.9412171682473827e-07
-0.0001929967738963,2.8368195292008612e-08,1.9088102669437356e-07
-0.0001898709450753,2.8090002575266257e-08,1.8768789971552863e-07
-0.0001867892958482,2.7814389032455363e-08,1.8454176486632323e-07
-0.000183752636707,2.754134148447891e-08,1.8115002092564538e-07
-0.0001807604032471,2.7270832946920812e-08,1.7781492252546064e-07
-0.0001778120365192,2.7002836607760232e-08,1.745356369687972e-07
-0.0001749069829579,2.673732582084065e-08,1.7131134159682263e-07
-0.0001720467771106,2.6474316260529432e-08,1.6814325920632144e-07
-0.0001692307716138,2.6213779758633963e-08,1.6503047175593728e-07
-0.0001664583277393,2.5955688359138642e-08,1.619720751255672e-07
-0.0001635796256227,2.5677295228672648e-08,1.588223280583729e-07
-0.0001607481963598,2.540169810843596e-08,1.557306487644946e-07
-0.0001579633073114,2.512886316325068e-08,1.526960267832303e-07
-0.0001552255108883,2.4858770138402143e-08,1.4971869736122287e-07
-0.000152534027681,2.4591385101783997e-08,1.467976093017761e-07
-0.0001498880910245,2.432667443532368e-08,1.439317302908228e-07
-0.0001472869464661,2.4064604800471338e-08,1.411200462508912e-07
-0.0001447314108795,2.3805175801260087e-08,1.3836305172259211e-07
-0.0001422206714078,2.3548353146553164e-08,1.3565967973526553e-07
-0.0001397539300508,2.3294102880186107e-08,1.3300888438790536e-07
-0.0001372700286953,2.3032485432340423e-08,1.3035230831596558e-07
-0.0001348306664569,2.2773547798807564e-08,1.277485195296911e-07
-0.0001324350333325,2.2517253805739807e-08,1.2505815113074245e-07
-0.0001300835425363,2.2263580536243144e-08,1.2242454150816991e-07
-0.0001277753479236,2.2012491805819457e-08,1.1984647647989558e-07
-0.0001255096202792,2.1763951788812352e-08,1.1732276843747534e-07
-0.0001232855464269,2.1517924960982367e-08,1.148522552473446e-07
-0.0001211034718808,2.1274400813402842e-08,1.1243486085670634e-07
-0.0001189625537742,2.1033343271785093e-08,1.100694052812587e-07
-0.0001168619671686,2.0794716623616593e-08,1.0775473577456182e-07
-0.0001149842862687,2.0591381044652174e-08,1.056582342233035e-07
-0.0001131392424142,2.038998454906055e-08,1.0360354473279054e-07
-0.0001113262252932,2.0190503422606346e-08,1.0158979943539652e-07
-0.0001095446965516,1.9992914861970927e-08,9.961620365200192e-08
-0.0001077940670993,1.9797195630879305e-08,9.768192356581421e-08
-0.0001060737596438,1.9603322741072024e-08,9.578614349620901e-08
-0.0001043832080373,1.9411273409584944e-08,9.392806512410292e-08
-0.0001027223865858,1.922103688152168e-08,9.210738192714242e-08
-0.0001010907257366,1.9032590330084783e-08,9.032330177845482e-08
-9.948766769187398e-05,1.8845911172333032e-08,8.857505025129074e-08
-9.792267601599324e-05,1.8663442661346744e-08,8.687075031773093e-08
-9.638489299064336e-05,1.848276820506329e-08,8.550652733411691e-08
-9.48738026587305e-05,1.830386814585904e-08,8.416598440502352e-08
-9.338895072626004e-05,1.8126723701740663e-08,8.284871850980459e-08
-9.192983962632808e-05,1.7951315790883015e-08,8.155428823884958e-08
-9.049598195913348e-05,1.7777625631449783e-08,8.028226120215297e-08
-8.908690001727453e-05,1.7605634715742614e-08,7.903221360818749e-08
-8.77022482135352e-05,1.743532764682425e-08,7.780383887402493e-08
-8.634156228069215e-05,1.7266686393258476e-08,7.659672513140668e-08
-8.50043874741986e-05,1.7099693224424935e-08,7.541046895998541e-08
-8.381694660770028e-05,1.6962933489525264e-08,7.43570471865261e-08
-8.26484651987276e-05,1.682764479561346e-08,7.33204450340972e-08
-8.149860566615124e-05,1.6693821025332528e-08,7.230036302225977e-08
-8.036532369463753e-05,1.6561436760581683e-08,7.129498756488483e-08
-7.924836834130927e-05,1.6430487594212236e-08,7.030409604146297e-08
-7.814749266035204e-05,1.6300969571299207e-08,6.932746937742372e-08
-7.706245353522453e-05,1.6172879193985398e-08,6.836489189528336e-08
-7.599203524832233e-05,1.6046190191322708e-08,6.741528508795074e-08
-7.493604414299442e-05,1.5920900877281144e-08,6.647847715560108e-08
-7.389428911314724e-05,1.57970100612018e-08,6.555429856110159e-08
-7.268136514077581e-05,1.5628904744452727e-08,6.447826980203191e-08
-7.148784598320314e-05,1.5462487634551132e-08,6.341945575654982e-08
+0.0003277611420723,3.899470345438449e-08,2.4249796960234704e-07
+0.0003250017686895,3.88695612548288e-08,2.454439759471401e-07
+0.0003222650868463,3.8745084795940443e-08,2.483227752372772e-07
+0.0003195509110308,3.8621269402790665e-08,2.5113526636955305e-07
+0.0003152051917212,3.831511482545576e-08,2.525571834385986e-07
+0.0003109173643927,3.801142847546096e-08,2.538929936309988e-07
+0.0003066866698276,3.7710184357421544e-08,2.551447305997623e-07
+0.0003025094755105,3.74113291159896e-08,2.5631194688927884e-07
+0.0002983851632227,3.711483823464807e-08,2.57396572290435e-07
+0.0002939090370085,3.677384148134545e-08,2.580457272005108e-07
+0.0002894959951166,3.6435889805735655e-08,2.586138532899247e-07
+0.0002851374388563,3.6100804786136576e-08,2.590960415051975e-07
+0.0002808329106728,3.5768558450009235e-08,2.594943775098954e-07
+0.0002765819528091,3.543912291177373e-08,2.5981091869063053e-07
+0.0002722585970856,3.509728654683229e-08,2.599278683420713e-07
+0.0002679917286135,3.475846792019279e-08,2.5996691909916645e-07
+0.0002637808235807,3.44226362592242e-08,2.599301554005377e-07
+0.000259625629125,3.4089763516669025e-08,2.598199006832183e-07
+0.0002555256094681,3.375981897519707e-08,2.555756892447018e-07
+0.0002510061132968,3.3373930606403456e-08,2.509166795385623e-07
+0.0002465564627785,3.299202134196193e-08,2.463324441551975e-07
+0.0002421759612383,3.2614046686258965e-08,2.418221717126139e-07
+0.0002378637384678,3.2239959043845714e-08,2.373848791838885e-07
+0.0002336189309368,3.18697111382095e-08,2.3301959212527745e-07
+0.000229786907623,3.154429519674801e-08,2.290704910449234e-07
+0.0002260088301865,3.1221956560459585e-08,2.251793706228873e-07
+0.0002222841156937,3.090266251951521e-08,2.213455610060874e-07
+0.0002186130300924,3.058638893853768e-08,2.175692384572231e-07
+0.000214994952946,3.027310301755256e-08,2.138496969887665e-07
+0.0002114292680468,2.9962772135295886e-08,2.1018623618806562e-07
+0.0002079153646262,2.9655363939172943e-08,2.0657816240778285e-07
+0.0002044527805171,2.9350849083358333e-08,2.0302493091347645e-07
+0.0002010409060047,2.904919541568693e-08,1.995258515561229e-07
+0.0001976791358816,2.8750370949174832e-08,1.9608024000424985e-07
+0.0001944779969388,2.8467714690234763e-08,1.9279758501200657e-07
+0.0001913221363037,2.8187696076865265e-08,1.895633279917293e-07
+0.0001882110383135,2.7910287978744905e-08,1.8637688328585562e-07
+0.0001851455117447,2.763547687941092e-08,1.8294394600063082e-07
+0.000182124981625,2.7363235313116972e-08,1.795685295609545e-07
+0.0001791488786026,2.7093535992876882e-08,1.762497841686646e-07
+0.0001762166388716,2.6826351803791374e-08,1.729868703567211e-07
+0.0001733298028653,2.6561698509687352e-08,1.6978101465406346e-07
+0.0001704877122406,2.6299547455845844e-08,1.666312813274778e-07
+0.0001676897174922,2.603987020688793e-08,1.635367489137303e-07
+0.0001647841340631,2.575975887106765e-08,1.603495310656704e-07
+0.0001619264140112,2.5482476734612484e-08,1.57221255401216e-07
+0.0001591158121254,2.520798936957748e-08,1.541508918468439e-07
+0.0001563528761692,2.493627607244877e-08,1.5113866658054666e-07
+0.0001536368140911,2.4667302328210823e-08,1.4818350881997277e-07
+0.0001509668468559,2.4401033945674264e-08,1.452843671077152e-07
+0.0001483422079002,2.4137437022238145e-08,1.4244020864846993e-07
+0.0001457637135497,2.3876511018332856e-08,1.3965152374161321e-07
+0.0001432305385497,2.3618221073161605e-08,1.369172264569389e-07
+0.0001407418727912,2.3362532671027093e-08,1.342362523931659e-07
+0.0001382358967136,2.3099449050292612e-08,1.3154948565189317e-07
+0.0001357749763134,2.283907541163823e-08,1.2891625322154978e-07
+0.0001333582893299,2.2581374993581207e-08,1.2619656354429104e-07
+0.0001309862438042,2.232632442642508e-08,1.2353438214155152e-07
+0.0001286579813897,2.2073886950323847e-08,1.2092847534724114e-07
+0.000126372660974,2.182402617504561e-08,1.1837763658356932e-07
+0.0001241294577704,2.1576706021416435e-08,1.1588068523754277e-07
+0.0001219287137845,2.1331915734067192e-08,1.1343753674855828e-07
+0.0001197695745451,2.108961868593061e-08,1.110469928559736e-07
+0.0001176512038143,2.08497786224886e-08,1.0870788304064741e-07
+0.0001157575507964,2.064536482973696e-08,1.0658919731348233e-07
+0.0001138968874049,2.0442910777630443e-08,1.0451285530046546e-07
+0.0001120685950893,2.0242392369145183e-08,1.0247797592009348e-07
+0.0001102721277733,2.0043786431072003e-08,1.004837520181078e-07
+0.0001085068885057,1.9847069357675e-08,9.852933720632749e-08
+0.0001067722923259,1.96522177979178e-08,9.661390355735894e-08
+0.0001050677655983,1.9459208611917452e-08,9.473664081358061e-08
+0.0001033932787473,1.9268030831168163e-08,9.289723486055733e-08
+0.000101748254869,1.9078661277163014e-08,9.109488193990664e-08
+0.0001001321289996,1.8891077021770737e-08,8.932879630040843e-08
+9.855410305682533e-05,1.8707685556144628e-08,8.760688138727519e-08
+9.70035750524988e-05,1.8526106268805162e-08,8.622858338902384e-08
+9.54800221910602e-05,1.834631916025987e-08,8.487426418079828e-08
+9.398298376195116e-05,1.816830511796191e-08,8.35435142269833e-08
+9.251195567959074e-05,1.7992044730451886e-08,8.223588543496443e-08
+9.106644418852578e-05,1.7817518892375448e-08,8.095093889480209e-08
+8.964596537975902e-05,1.7644708778076547e-08,7.968824444928503e-08
+8.825016836609303e-05,1.7473598709850392e-08,7.844749018716727e-08
+8.687858293497841e-05,1.7304170348281186e-08,7.722825812630736e-08
+8.553074854577241e-05,1.7136405660531677e-08,7.603013888213162e-08
+8.433358305815234e-05,1.6998940860777966e-08,7.496595249494088e-08
+8.315557511358139e-05,1.6862959916000355e-08,7.39187956635932e-08
+8.199638277812437e-05,1.6728456488525712e-08,7.28883644355918e-08
+8.085394966108952e-05,1.6595404781975636e-08,7.187283084061544e-08
+7.972802118918304e-05,1.6463800186495995e-08,7.087196858293762e-08
+7.861834686065792e-05,1.6333638547854104e-08,6.988555498611813e-08
+7.752468007410017e-05,1.6204916172056103e-08,6.891337084080734e-08
+7.644579608395804e-05,1.607760634807453e-08,6.795432744410053e-08
+7.538149823706338e-05,1.5951707212505497e-08,6.700824998672802e-08
+7.433159248509273e-05,1.5827217400105257e-08,6.607496597492307e-08
+7.310944660054646e-05,1.5658417045863033e-08,6.498857397068902e-08
+7.190690836035234e-05,1.5491319571073834e-08,6.391961162711614e-08

tests/invocation/logs_path_request

@@ -1,5 +1,124 @@
 INFO     gnpy.tools.cli_examples:cli_examples.py Computing path requests meshTopologyExampleV2.xls into JSON format
+WARNING  gnpy.tools.json_io:json_io.py 
+	WARNING missing type_variety attribute in eqpt_config.json[Roadm]
+	default value is type_variety = default
+
 INFO     gnpy.tools.json_io:json_io.py Automatically converting requests from XLS to JSON
+INFO     gnpy.tools.worker_utils:worker_utils.py List of disjunctions:
+[Disjunction 3
+	relaxable:    false
+	link-diverse: True
+	node-diverse: True
+	request-id-numbers: ['3', '1']
+, Disjunction 4
+	relaxable:    false
+	link-diverse: True
+	node-diverse: True
+	request-id-numbers: ['4', '5']
+]
+INFO     gnpy.tools.worker_utils:worker_utils.py Aggregating similar requests
+INFO     gnpy.tools.worker_utils:worker_utils.py The following services have been requested:
+[PathRequest 0
+	source: 	trx Lorient_KMA
+	destination:	trx Vannes_KBE
+	trx type:	Voyager
+	trx mode:	None
+	baud_rate:	None Gbaud
+	bit_rate:	None Gb/s
+	spacing:	50.0 GHz
+	power:  	1.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	80
+	path_bandwidth: 	100.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 1
+	source: 	trx Brest_KLA
+	destination:	trx Vannes_KBE
+	trx type:	Voyager
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	50.0 GHz
+	power:  	1.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	95
+	path_bandwidth: 	200.0 Gbit/s
+	nodes-list:	['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE']
+	loose-list:	['LOOSE', 'LOOSE', 'LOOSE', 'LOOSE']
+, PathRequest 3
+	source: 	trx Lannion_CAS
+	destination:	trx Rennes_STA
+	trx type:	vendorA_trx-type1
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	50.0 GHz
+	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	95
+	path_bandwidth: 	60.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 4
+	source: 	trx Rennes_STA
+	destination:	trx Lannion_CAS
+	trx type:	vendorA_trx-type1
+	trx mode:	None
+	baud_rate:	None Gbaud
+	bit_rate:	None Gb/s
+	spacing:	75.0 GHz
+	power:  	3.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	63
+	path_bandwidth: 	150.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 5
+	source: 	trx Rennes_STA
+	destination:	trx Lannion_CAS
+	trx type:	vendorA_trx-type1
+	trx mode:	mode 2
+	baud_rate:	66.0 Gbaud
+	bit_rate:	200.0 Gb/s
+	spacing:	75.0 GHz
+	power:  	3.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	63
+	path_bandwidth: 	20.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 7 | 6
+	source: 	trx Lannion_CAS
+	destination:	trx Lorient_KMA
+	trx type:	Voyager
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	50.0 GHz
+	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	76
+	path_bandwidth: 	700.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 7b
+	source: 	trx Lannion_CAS
+	destination:	trx Lorient_KMA
+	trx type:	Voyager
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	75.0 GHz
+	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	50
+	path_bandwidth: 	400.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+]
+INFO     gnpy.tools.worker_utils:worker_utils.py Propagating on selected path
+WARNING  gnpy.topology.request:request.py Redesign the network for each request channel, using the request channel as the reference channel for the design.
 INFO     gnpy.topology.request:request.py 
 	request 0
 	Computing path from trx Lorient_KMA to trx Vannes_KBE

tests/invocation/logs_path_requests_run_CD_PMD_PDL_missing

@@ -1,4 +1,28 @@
 INFO     gnpy.tools.cli_examples:cli_examples.py Computing path requests CORONET_services.json into JSON format
+WARNING  gnpy.tools.json_io:json_io.py 
+	WARNING missing type_variety attribute in eqpt_config.json[Roadm]
+	default value is type_variety = default
+
+INFO     gnpy.tools.worker_utils:worker_utils.py List of disjunctions:
+[]
+INFO     gnpy.tools.worker_utils:worker_utils.py Aggregating similar requests
+INFO     gnpy.tools.worker_utils:worker_utils.py The following services have been requested:
+[PathRequest 0
+	source: 	trx Abilene
+	destination:	trx Albany
+	trx type:	Voyager
+	trx mode:	mode 3
+	baud_rate:	44.0 Gbaud
+	bit_rate:	300.0 Gb/s
+	spacing:	62.50000000000001 GHz
+	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	76
+	path_bandwidth: 	100.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+]
+INFO     gnpy.tools.worker_utils:worker_utils.py Propagating on selected path
 INFO     gnpy.topology.request:request.py 
 	request 0
 	Computing path from trx Abilene to trx Albany

tests/invocation/logs_power_sweep_example

@@ -0,0 +1,378 @@
+WARNING  gnpy.tools.json_io:json_io.py 
+	WARNING missing type_variety attribute in eqpt_config.json[Roadm]
+	default value is type_variety = default
+
+INFO     gnpy.tools.cli_examples:cli_examples.py source = 'trx Brest_KLA'
+INFO     gnpy.tools.cli_examples:cli_examples.py destination = 'trx Rennes_STA'
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Lorient_KMA to Loudeac
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: effective gain in Node east edfa in Lannion_CAS to Stbrieuc
+	is above user specified amplifier std_low_gain
+	max flat gain: 16dB ; required gain: 21.22dB. Please check amplifier type.
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Rennes_STA to Stbrieuc
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: effective gain in Node east edfa in Lannion_CAS to Morlaix
+	is above user specified amplifier std_low_gain
+	max flat gain: 16dB ; required gain: 21.22dB. Please check amplifier type.
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Brest_KLA to Morlaix
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Lorient_KMA to Loudeac
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: effective gain in Node west edfa in Lannion_CAS to Corlay
+	is above user specified amplifier test
+	max flat gain: 25dB ; required gain: 28.0dB. Please check amplifier type.
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Lorient_KMA to Vannes_KBE
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Vannes_KBE to Lorient_KMA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Lorient_KMA to Quimper
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Quimper to Lorient_KMA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Brest_KLA to Quimper
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Vannes_KBE to Lorient_KMA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Lorient_KMA to Vannes_KBE
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Vannes_KBE to Ploermel
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Ploermel to Vannes_KBE
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Rennes_STA to Ploermel
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Rennes_STA to Stbrieuc
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Stbrieuc to Rennes_STA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Lannion_CAS to Stbrieuc
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Rennes_STA to Ploermel
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Vannes_KBE to Ploermel
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Brest_KLA to Morlaix
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: effective gain in Node east edfa in Brest_KLA to Quimper
+	is above user specified amplifier std_low_gain
+	max flat gain: 16dB ; required gain: 21.22dB. Please check amplifier type.
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Quimper to Lorient_KMA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Lorient_KMA to Quimper
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in a to b
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in b to a
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in a to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in c to a
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in b to a
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in a to b
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in b to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in f to b
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in c to a
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in a to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in d to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in c to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in f to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in d to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in c to d
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in d to e
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in e to d
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in e to d
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in d to e
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in e to g
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in g to e
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in f to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in c to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in f to b
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in b to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in f to h
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in h to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in g to e
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in e to g
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in g to h
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in h to g
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in h to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in f to h
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in h to g
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in g to h
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.78 is applied
+
+INFO     gnpy.tools.worker_utils:worker_utils.py Power mode is set to True=> it can be modified in eqpt_config.json - Span
+INFO     gnpy.tools.worker_utils:worker_utils.py Now propagating between trx Brest_KLA and trx Rennes_STA
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)

tests/invocation/logs_transmission_saturated

@@ -1,5 +1,9 @@
-INFO     gnpy.tools.cli_examples:cli_examples.py source = 'lannion'
-INFO     gnpy.tools.cli_examples:cli_examples.py destination = 'lorient'
+WARNING  gnpy.tools.json_io:json_io.py 
+	WARNING missing type_variety attribute in eqpt_config.json[Roadm]
+	default value is type_variety = default
+
+INFO     gnpy.tools.cli_examples:cli_examples.py source = 'trx Lannion_CAS'
+INFO     gnpy.tools.cli_examples:cli_examples.py destination = 'trx Lorient_KMA'
 WARNING  gnpy.core.network:network.py 
 	WARNING: target gain and power in node west edfa in Lorient_KMA to Loudeac
 	is beyond all available amplifiers capabilities and/or extended_gain_range:
@@ -8,7 +12,7 @@ WARNING  gnpy.core.network:network.py
 WARNING  gnpy.core.network:network.py 
 	WARNING: effective gain in Node east edfa in Lannion_CAS to Stbrieuc
 	is above user specified amplifier std_low_gain
-	max flat gain: 16dB ; required gain: 23.0dB. Please check amplifier type.
+	max flat gain: 16dB ; required gain: 21.18dB. Please check amplifier type.
 
 WARNING  gnpy.core.network:network.py 
 	WARNING: target gain and power in node west edfa in Rennes_STA to Stbrieuc
@@ -18,7 +22,7 @@ WARNING  gnpy.core.network:network.py
 WARNING  gnpy.core.network:network.py 
 	WARNING: effective gain in Node east edfa in Lannion_CAS to Morlaix
 	is above user specified amplifier std_low_gain
-	max flat gain: 16dB ; required gain: 23.5dB. Please check amplifier type.
+	max flat gain: 16dB ; required gain: 21.18dB. Please check amplifier type.
 
 WARNING  gnpy.core.network:network.py 
 	WARNING: target gain and power in node west edfa in Brest_KLA to Morlaix
@@ -33,7 +37,7 @@ WARNING  gnpy.core.network:network.py
 WARNING  gnpy.core.network:network.py 
 	WARNING: effective gain in Node west edfa in Lannion_CAS to Corlay
 	is above user specified amplifier test
-	max flat gain: 25dB ; required gain: 29.82dB. Please check amplifier type.
+	max flat gain: 25dB ; required gain: 28.0dB. Please check amplifier type.
 
 WARNING  gnpy.core.network:network.py 
 	WARNING: target gain and power in node east edfa in Lorient_KMA to Vannes_KBE
@@ -118,7 +122,7 @@ WARNING  gnpy.core.network:network.py
 WARNING  gnpy.core.network:network.py 
 	WARNING: effective gain in Node east edfa in Brest_KLA to Quimper
 	is above user specified amplifier std_low_gain
-	max flat gain: 16dB ; required gain: 23.0dB. Please check amplifier type.
+	max flat gain: 16dB ; required gain: 21.18dB. Please check amplifier type.
 
 WARNING  gnpy.core.network:network.py 
 	WARNING: target gain and power in node east edfa in Quimper to Lorient_KMA
@@ -305,3 +309,10 @@ WARNING  gnpy.core.network:network.py
 	is beyond all available amplifiers capabilities and/or extended_gain_range:
 	a power reduction of -1.82 is applied
 
+INFO     gnpy.tools.worker_utils:worker_utils.py Power mode is set to True=> it can be modified in eqpt_config.json - Span
+INFO     gnpy.tools.worker_utils:worker_utils.py Now propagating between trx Lannion_CAS and trx Lorient_KMA
+INFO     gnpy.tools.worker_utils:worker_utils.py 
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 96)

tests/invocation/multiband_transmission

@@ -0,0 +1,294 @@
+User input for spectrum used for propagation instead of SI
+Power mode is set to True
+=> it can be modified in eqpt_config.json - Span
+
+There are 3 fiber spans over 240 km between trx Site_A and trx Site_D
+
+Now propagating between trx Site_A and trx Site_D:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 76)
+
+Channels propagating: (Input optical power deviation in span = cband: 0.00, lband: 0.00dB,
+                       spacing = cband: 50.00, lband: 50.00GHz,
+                       transceiver output power = cband: 0.00, lband: 0.00dBm,
+                       nb_channels = 149)
+Input optical power reference in span = 0.00 dBm:
+Transceiver trx Site_A
+  GSNR (0.1nm, dB):          cband: 40.00, lband: 40.00
+  GSNR (signal bw, dB):      cband: 35.92, lband: 35.92
+  OSNR ASE (0.1nm, dB):      cband: 40.00, lband: 40.00
+  OSNR ASE (signal bw, dB):  cband: 35.92, lband: 35.92
+  CD (ps/nm):                0.00
+  PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
+  Actual pch out (dBm):      cband: 0.00, lband: 0.00
+Roadm roadm Site_A
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        cband: 20.00, lband: 20.00
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    cband: -20.00, lband: -20.00
+Multiband_amplifier east edfa in Site_A to Site_B
+  type_variety:           std_medium_gain_multiband
+  type_variety:           std_medium_gain_C    type_variety:           std_medium_gain_L  
+  effective gain(dB):     20.90                effective gain(dB):     22.19              
+  (before att_in and before output VOA)        (before att_in and before output VOA)      
+  tilt-target(dB)         0.00                 tilt-target(dB)         0.00               
+  noise figure (dB):      6.38                 noise figure (dB):      6.19               
+  (including att_in)                           (including att_in)                         
+  pad att_in (dB):        0.00                 pad att_in (dB):        0.00               
+  Power In (dBm):         -1.08                Power In (dBm):         -1.49              
+  Power Out (dBm):        19.83                Power Out (dBm):        20.71              
+  Delta_P (dB):           0.90                 Delta_P (dB):           2.19               
+  target pch (dBm):       0.90                 target pch (dBm):       3.00               
+  actual pch out (dBm):   -2.09                actual pch out (dBm):   -0.80              
+  output VOA (dB):        3.00                 output VOA (dB):        3.00               
+Fiber          fiber (Site_A → Site_B)-
+  type_variety:                SSMF
+  length (km):                 75.00
+  pad att_in (dB):             0.00
+  total loss (dB):             15.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -17.10
+  actual pch out (dBm):        cband: -17.09, lband: -15.80
+Multiband_amplifier east edfa in Site_B to Site_C
+  type_variety:           std_medium_gain_multiband
+  type_variety:           std_medium_gain_C    type_variety:           std_medium_gain_L  
+  effective gain(dB):     18.00                effective gain(dB):     18.00              
+  (before att_in and before output VOA)        (before att_in and before output VOA)      
+  tilt-target(dB)         0.00                 tilt-target(dB)         0.00               
+  noise figure (dB):      7.38                 noise figure (dB):      7.38               
+  (including att_in)                           (including att_in)                         
+  pad att_in (dB):        0.00                 pad att_in (dB):        0.00               
+  Power In (dBm):         1.83                 Power In (dBm):         2.71               
+  Power Out (dBm):        19.84                Power Out (dBm):        20.72              
+  Delta_P (dB):           0.90                 Delta_P (dB):           2.19               
+  target pch (dBm):       0.90                 target pch (dBm):       3.00               
+  actual pch out (dBm):   -2.09                actual pch out (dBm):   -0.79              
+  output VOA (dB):        3.00                 output VOA (dB):        3.00               
+Fiber          fiber (Site_B → Site_C)-
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.80
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -18.90
+  actual pch out (dBm):        cband: -18.88, lband: -17.59
+Multiband_amplifier east edfa in Site_C to Site_D
+  type_variety:           std_medium_gain_multiband
+  type_variety:           std_medium_gain_C    type_variety:           std_medium_gain_L  
+  effective gain(dB):     19.80                effective gain(dB):     19.80              
+  (before att_in and before output VOA)        (before att_in and before output VOA)      
+  tilt-target(dB)         0.00                 tilt-target(dB)         0.00               
+  noise figure (dB):      6.63                 noise figure (dB):      6.63               
+  (including att_in)                           (including att_in)                         
+  pad att_in (dB):        0.00                 pad att_in (dB):        0.00               
+  Power In (dBm):         0.04                 Power In (dBm):         0.92               
+  Power Out (dBm):        19.84                Power Out (dBm):        20.72              
+  Delta_P (dB):           0.90                 Delta_P (dB):           2.19               
+  target pch (dBm):       0.90                 target pch (dBm):       3.00               
+  actual pch out (dBm):   -2.08                actual pch out (dBm):   -0.79              
+  output VOA (dB):        3.00                 output VOA (dB):        3.00               
+Fiber          fiber (Site_C → Site_D)-
+  type_variety:                SSMF
+  length (km):                 85.00
+  pad att_in (dB):             0.00
+  total loss (dB):             18.70
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -20.80
+  actual pch out (dBm):        cband: -20.78, lband: -19.49
+Multiband_amplifier west edfa in Site_D to Site_C
+  type_variety:           std_medium_gain_multiband
+  type_variety:           std_medium_gain_C    type_variety:           std_medium_gain_L  
+  effective gain(dB):     21.70                effective gain(dB):     21.70              
+  (before att_in and before output VOA)        (before att_in and before output VOA)      
+  tilt-target(dB)         0.00                 tilt-target(dB)         0.00               
+  noise figure (dB):      6.25                 noise figure (dB):      6.25               
+  (including att_in)                           (including att_in)                         
+  pad att_in (dB):        0.00                 pad att_in (dB):        0.00               
+  Power In (dBm):         -1.85                Power In (dBm):         -0.97              
+  Power Out (dBm):        19.85                Power Out (dBm):        20.73              
+  Delta_P (dB):           0.90                 Delta_P (dB):           2.19               
+  target pch (dBm):       0.90                 target pch (dBm):       3.00               
+  actual pch out (dBm):   -2.07                actual pch out (dBm):   -0.78              
+  output VOA (dB):        3.00                 output VOA (dB):        3.00               
+Roadm roadm Site_D
+  Type_variety:            default
+  Reference loss (dB):     17.90
+  Actual loss (dB):        cband: 17.93, lband: 19.22
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    cband: -20.00, lband: -20.00
+Transceiver trx Site_D
+  GSNR (0.1nm, dB):          cband: 24.89, lband: 25.36
+  GSNR (signal bw, dB):      cband: 20.80, lband: 21.28
+  OSNR ASE (0.1nm, dB):      cband: 25.55, lband: 26.51
+  OSNR ASE (signal bw, dB):  cband: 21.47, lband: 22.43
+  CD (ps/nm):                4008.00
+  PMD (ps):                  0.62
+  PDL (dB):                  0.00
+  Latency (ms):              1.18
+  Actual pch out (dBm):      cband: 0.00, lband: 0.00
+
+Transmission result for input optical power reference in span = 0.00 dBm:
+  Final GSNR (0.1 nm): 25.11 dB
+
+The GSNR per channel at the end of the line is:
+Ch. #   Channel frequency (THz)       Channel power (dBm)    OSNR ASE (signal bw, dB)     SNR NLI (signal bw, dB)        GSNR (signal bw, dB)
+    1                 186.55000                    -20.03                       22.46                       29.10                       21.61
+    2                 186.60000                    -20.03                       22.46                       28.59                       21.51
+    3                 186.65000                    -20.03                       22.46                       28.36                       21.47
+    4                 186.70000                    -20.03                       22.46                       28.22                       21.44
+    5                 186.75000                    -20.03                       22.46                       28.12                       21.41
+    6                 186.80000                    -20.03                       22.46                       28.04                       21.40
+    7                 186.85000                    -20.03                       22.46                       27.98                       21.38
+    8                 186.90000                    -20.03                       22.45                       27.92                       21.37
+    9                 186.95000                    -20.03                       22.45                       27.88                       21.36
+   10                 187.00000                    -20.03                       22.45                       27.84                       21.35
+   11                 187.05000                    -20.03                       22.45                       27.80                       21.34
+   12                 187.10000                    -20.03                       22.45                       27.77                       21.33
+   13                 187.15000                    -20.03                       22.45                       27.74                       21.32
+   14                 187.20000                    -20.03                       22.45                       27.71                       21.32
+   15                 187.25000                    -20.03                       22.45                       27.69                       21.31
+   16                 187.30000                    -20.03                       22.45                       27.67                       21.31
+   17                 187.35000                    -20.03                       22.45                       27.65                       21.30
+   18                 187.40000                    -20.03                       22.44                       27.63                       21.29
+   19                 187.45000                    -20.03                       22.44                       27.61                       21.29
+   20                 187.50000                    -20.03                       22.44                       27.60                       21.29
+   21                 187.55000                    -20.03                       22.44                       27.58                       21.28
+   22                 187.60000                    -20.03                       22.44                       27.57                       21.28
+   23                 187.65000                    -20.03                       22.44                       27.55                       21.27
+   24                 187.70000                    -20.03                       22.44                       27.54                       21.27
+   25                 187.75000                    -20.03                       22.44                       27.53                       21.27
+   26                 187.80000                    -20.03                       22.44                       27.52                       21.26
+   27                 187.85000                    -20.03                       22.44                       27.51                       21.26
+   28                 187.90000                    -20.03                       22.43                       27.50                       21.26
+   29                 187.95000                    -20.03                       22.43                       27.49                       21.25
+   30                 188.00000                    -20.03                       22.43                       27.48                       21.25
+   31                 188.05000                    -20.03                       22.43                       27.47                       21.25
+   32                 188.10000                    -20.03                       22.43                       27.47                       21.25
+   33                 188.15000                    -20.03                       22.43                       27.46                       21.24
+   34                 188.20000                    -20.03                       22.43                       27.45                       21.24
+   35                 188.25000                    -20.03                       22.43                       27.45                       21.24
+   36                 188.30000                    -20.03                       22.43                       27.44                       21.24
+   37                 188.35000                    -20.03                       22.43                       27.44                       21.23
+   38                 188.40000                    -20.03                       22.42                       27.43                       21.23
+   39                 188.45000                    -20.03                       22.42                       27.43                       21.23
+   40                 188.50000                    -20.03                       22.42                       27.43                       21.23
+   41                 188.55000                    -20.03                       22.42                       27.42                       21.23
+   42                 188.60000                    -20.03                       22.42                       27.42                       21.23
+   43                 188.65000                    -20.03                       22.42                       27.42                       21.23
+   44                 188.70000                    -20.03                       22.42                       27.42                       21.22
+   45                 188.75000                    -20.03                       22.42                       27.42                       21.22
+   46                 188.80000                    -20.03                       22.42                       27.42                       21.22
+   47                 188.85000                    -20.03                       22.41                       27.42                       21.22
+   48                 188.90000                    -20.03                       22.41                       27.42                       21.22
+   49                 188.95000                    -20.03                       22.41                       27.42                       21.22
+   50                 189.00000                    -20.03                       22.41                       27.43                       21.22
+   51                 189.05000                    -20.03                       22.41                       27.43                       21.22
+   52                 189.10000                    -20.03                       22.41                       27.44                       21.22
+   53                 189.15000                    -20.03                       22.41                       27.44                       21.22
+   54                 189.20000                    -20.03                       22.41                       27.45                       21.22
+   55                 189.25000                    -20.03                       22.41                       27.46                       21.23
+   56                 189.30000                    -20.03                       22.41                       27.46                       21.23
+   57                 189.35000                    -20.03                       22.40                       27.47                       21.23
+   58                 189.40000                    -20.03                       22.40                       27.49                       21.23
+   59                 189.45000                    -20.03                       22.40                       27.50                       21.23
+   60                 189.50000                    -20.03                       22.40                       27.51                       21.24
+   61                 189.55000                    -20.03                       22.40                       27.53                       21.24
+   62                 189.60000                    -20.03                       22.40                       27.55                       21.24
+   63                 189.65000                    -20.03                       22.40                       27.58                       21.25
+   64                 189.70000                    -20.03                       22.40                       27.60                       21.25
+   65                 189.75000                    -20.03                       22.40                       27.63                       21.26
+   66                 189.80000                    -20.03                       22.40                       27.67                       21.27
+   67                 189.85000                    -20.03                       22.39                       27.72                       21.28
+   68                 189.90000                    -20.03                       22.39                       27.78                       21.29
+   69                 189.95000                    -20.03                       22.39                       27.86                       21.31
+   70                 190.00000                    -20.03                       22.39                       27.97                       21.33
+   71                 190.05000                    -20.03                       22.39                       28.21                       21.38
+   72                 191.25000                    -20.03                       21.51                       28.66                       20.74
+   73                 191.30000                    -20.03                       21.51                       28.96                       20.79
+   74                 191.35000                    -20.03                       21.51                       29.16                       20.82
+   75                 191.40000                    -20.03                       21.50                       29.32                       20.84
+   76                 191.45000                    -20.03                       21.50                       29.51                       20.87
+   77                 191.50000                    -20.03                       21.50                       29.75                       20.90
+   78                 191.55000                    -20.03                       21.50                       30.22                       20.95
+   79                 191.60000                    -20.03                       21.50                       30.96                       21.03
+   80                 191.65000                    -20.03                       21.50                       30.46                       20.98
+   81                 191.70000                    -20.03                       21.50                       30.23                       20.95
+   82                 191.75000                    -20.03                       21.50                       30.08                       20.93
+   83                 191.80000                    -20.03                       21.50                       29.97                       20.92
+   84                 191.85000                    -20.03                       21.50                       29.88                       20.91
+   85                 191.90000                    -20.03                       21.49                       29.81                       20.90
+   86                 191.95000                    -20.03                       21.49                       29.75                       20.89
+   87                 192.00000                    -20.03                       21.49                       29.70                       20.88
+   88                 192.05000                    -20.03                       21.49                       29.65                       20.87
+   89                 192.10000                    -20.03                       21.49                       29.61                       20.87
+   90                 192.15000                    -20.03                       21.49                       29.57                       20.86
+   91                 192.20000                    -20.03                       21.49                       29.54                       20.86
+   92                 192.25000                    -20.03                       21.49                       29.50                       20.85
+   93                 192.30000                    -20.03                       21.49                       29.47                       20.85
+   94                 192.35000                    -20.03                       21.49                       29.44                       20.84
+   95                 192.40000                    -20.03                       21.48                       29.42                       20.84
+   96                 192.45000                    -20.03                       21.48                       29.39                       20.83
+   97                 192.50000                    -20.03                       21.48                       29.37                       20.83
+   98                 192.55000                    -20.03                       21.48                       29.35                       20.82
+   99                 192.60000                    -20.03                       21.48                       29.33                       20.82
+  100                 192.65000                    -20.03                       21.48                       29.31                       20.82
+  101                 192.70000                    -20.03                       21.48                       29.29                       20.81
+  102                 192.75000                    -20.03                       21.48                       29.27                       20.81
+  103                 192.80000                    -20.03                       21.48                       29.25                       20.81
+  104                 192.85000                    -20.03                       21.47                       29.23                       20.80
+  105                 192.90000                    -20.03                       21.47                       29.22                       20.80
+  106                 192.95000                    -20.03                       21.47                       29.20                       20.80
+  107                 193.00000                    -20.03                       21.47                       29.18                       20.79
+  108                 193.05000                    -20.03                       21.47                       29.17                       20.79
+  109                 193.10000                    -20.03                       21.47                       29.16                       20.79
+  110                 193.15000                    -20.03                       21.47                       29.14                       20.78
+  111                 193.20000                    -20.03                       21.47                       29.13                       20.78
+  112                 193.25000                    -20.03                       21.47                       29.12                       20.78
+  113                 193.30000                    -20.03                       21.47                       29.10                       20.78
+  114                 193.35000                    -20.03                       21.46                       29.09                       20.77
+  115                 193.40000                    -20.03                       21.46                       29.08                       20.77
+  116                 193.45000                    -20.03                       21.46                       29.07                       20.77
+  117                 193.50000                    -20.03                       21.46                       29.06                       20.77
+  118                 193.55000                    -20.03                       21.46                       29.05                       20.76
+  119                 193.60000                    -20.03                       21.46                       29.04                       20.76
+  120                 193.65000                    -20.03                       21.46                       29.03                       20.76
+  121                 193.70000                    -20.03                       21.46                       29.02                       20.76
+  122                 193.75000                    -20.03                       21.46                       29.01                       20.75
+  123                 193.80000                    -20.03                       21.46                       29.00                       20.75
+  124                 193.85000                    -20.03                       21.45                       28.99                       20.75
+  125                 193.90000                    -20.03                       21.45                       28.99                       20.75
+  126                 193.95000                    -20.03                       21.45                       28.98                       20.75
+  127                 194.00000                    -20.03                       21.45                       28.97                       20.74
+  128                 194.05000                    -20.03                       21.45                       28.97                       20.74
+  129                 194.10000                    -20.03                       21.45                       28.96                       20.74
+  130                 194.15000                    -20.03                       21.45                       28.96                       20.74
+  131                 194.20000                    -20.03                       21.45                       28.96                       20.74
+  132                 194.25000                    -20.03                       21.45                       28.95                       20.74
+  133                 194.30000                    -20.03                       21.45                       28.95                       20.74
+  134                 194.35000                    -20.03                       21.44                       28.95                       20.73
+  135                 194.40000                    -20.03                       21.44                       28.95                       20.73
+  136                 194.45000                    -20.03                       21.44                       28.95                       20.73
+  137                 194.50000                    -20.03                       21.44                       28.96                       20.73
+  138                 194.55000                    -20.03                       21.44                       28.96                       20.73
+  139                 194.60000                    -20.03                       21.44                       28.97                       20.73
+  140                 194.65000                    -20.03                       21.44                       28.98                       20.73
+  141                 194.70000                    -20.03                       21.44                       28.99                       20.74
+  142                 194.75000                    -20.03                       21.44                       29.01                       20.74
+  143                 194.80000                    -20.03                       21.44                       29.04                       20.74
+  144                 194.85000                    -20.03                       21.43                       29.07                       20.74
+  145                 194.90000                    -20.03                       21.43                       29.12                       20.75
+  146                 194.95000                    -20.03                       21.43                       29.18                       20.76
+  147                 195.00000                    -20.03                       21.43                       29.28                       20.77
+  148                 195.05000                    -20.03                       21.43                       29.44                       20.79
+  149                 195.10000                    -20.03                       21.43                       29.84                       20.84
+
+(Invalid source node 'Site_A' replaced with trx Site_A)
+
+(Invalid destination node 'Site_D' replaced with trx Site_D)

tests/invocation/openroadm-v4-Stockholm-Gothenburg

@@ -1,12 +1,18 @@
-There are 96 channels propagating
 Power mode is set to True
 => it can be modified in eqpt_config.json - Span
 
 There are 6 fiber spans over 500 km between trx_Stockholm and trx_Gothenburg
 
 Now propagating between trx_Stockholm and trx_Gothenburg:
+Reference used for design: (Input optical power reference in span = 2.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 96)
 
-Propagating with input power = 2.00 dBm:
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 2.00dBm,
+                       nb_channels = 96)
+Input optical power reference in span = 2.00 dBm:
 Transceiver trx_Stockholm
   GSNR (0.1nm, dB):          35.00
   GSNR (signal bw, dB):      30.98
@@ -16,14 +22,18 @@ Transceiver trx_Stockholm
   PMD (ps):                  0.00
   PDL (dB):                  0.00
   Latency (ms):              0.00
+  Actual pch out (dBm):      2.00
 Roadm roadm_Stockholm
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.00
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -31,7 +41,6 @@ Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Stockholm → Norrköping)_(1/2)
@@ -47,6 +56,7 @@ Edfa Edfa_fiber (Stockholm → Norrköping)_(1/2)
   type_variety:           openroadm_ila_low_noise
   effective gain(dB):     16.33
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.01
   (including att_in)
   pad att_in (dB):        0.00
@@ -54,8 +64,7 @@ Edfa Edfa_fiber (Stockholm → Norrköping)_(1/2)
   Power Out (dBm):        21.84
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
-  actual pch out (dBm):   2.02
+  actual pch out (dBm):   2.01
   output VOA (dB):        0.00
 Fiber          fiber (Stockholm → Norrköping)_(2/2)
   type_variety:                SSMF
@@ -65,29 +74,32 @@ Fiber          fiber (Stockholm → Norrköping)_(2/2)
   (includes conn loss (dB) in: 0.00 out: 0.00)
   (conn loss out includes EOL margin defined in eqpt_config.json)
   reference pch out (dBm):     -14.33
-  actual pch out (dBm):        -14.29
+  actual pch out (dBm):        -14.30
 Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     16.33
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      12.59
   (including att_in)
   pad att_in (dB):        0.00
-  Power In (dBm):         5.53
-  Power Out (dBm):        21.87
+  Power In (dBm):         5.52
+  Power Out (dBm):        21.86
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
-  actual pch out (dBm):   2.04
+  actual pch out (dBm):   2.03
   output VOA (dB):        0.00
 Roadm roadm_Norrköping
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.03
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -95,7 +107,6 @@ Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Norrköping → Linköping)
@@ -111,6 +122,7 @@ Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     11.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      16.00
   (including att_in)
   pad att_in (dB):        0.00
@@ -118,17 +130,19 @@ Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
   Power Out (dBm):        21.83
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.01
   output VOA (dB):        0.00
 Roadm roadm_Linköping
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.01
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -136,7 +150,6 @@ Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Linköping → Jönköping)
@@ -152,24 +165,27 @@ Edfa Edfa_preamp_roadm_Jönköping_from_fiber (Linköping → Jönköping)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     26.80
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.09
   (including att_in)
   pad att_in (dB):        0.00
   Power In (dBm):         -4.97
-  Power Out (dBm):        21.86
+  Power Out (dBm):        21.87
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
-  actual pch out (dBm):   2.04
+  actual pch out (dBm):   2.05
   output VOA (dB):        0.00
 Roadm roadm_Jönköping
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.05
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -177,7 +193,6 @@ Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Jönköping → Borås)
@@ -193,6 +208,7 @@ Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     17.82
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      11.94
   (including att_in)
   pad att_in (dB):        0.00
@@ -200,17 +216,19 @@ Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
   Power Out (dBm):        21.84
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.02
   output VOA (dB):        0.00
 Roadm roadm_Borås
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.02
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -218,7 +236,6 @@ Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Borås → Gothenburg)
@@ -234,6 +251,7 @@ Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     13.53
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      13.78
   (including att_in)
   pad att_in (dB):        0.00
@@ -241,13 +259,14 @@ Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
   Power Out (dBm):        21.84
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.02
   output VOA (dB):        0.00
 Roadm roadm_Gothenburg
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.02
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Transceiver trx_Gothenburg
   GSNR (0.1nm, dB):          18.89
   GSNR (signal bw, dB):      14.86
@@ -257,8 +276,9 @@ Transceiver trx_Gothenburg
   PMD (ps):                  7.99
   PDL (dB):                  3.74
   Latency (ms):              2.45
+  Actual pch out (dBm):      2.00
 
-Transmission result for input power = 2.00 dBm:
+Transmission result for input optical power reference in span = 2.00 dBm:
   Final GSNR (0.1 nm): 18.89 dB
 
 (No source node specified: picked trx_Stockholm)

tests/invocation/openroadm-v5-Stockholm-Gothenburg

@@ -1,12 +1,18 @@
-There are 96 channels propagating
 Power mode is set to True
 => it can be modified in eqpt_config.json - Span
 
 There are 6 fiber spans over 500 km between trx_Stockholm and trx_Gothenburg
 
 Now propagating between trx_Stockholm and trx_Gothenburg:
+Reference used for design: (Input optical power reference in span = 2.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 96)
 
-Propagating with input power = 2.00 dBm:
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 2.00dBm,
+                       nb_channels = 96)
+Input optical power reference in span = 2.00 dBm:
 Transceiver trx_Stockholm
   GSNR (0.1nm, dB):          35.00
   GSNR (signal bw, dB):      30.98
@@ -16,14 +22,18 @@ Transceiver trx_Stockholm
   PMD (ps):                  0.00
   PDL (dB):                  0.00
   Latency (ms):              0.00
+  Actual pch out (dBm):      2.00
 Roadm roadm_Stockholm
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.00
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -31,7 +41,6 @@ Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Stockholm → Norrköping)_(1/2)
@@ -47,6 +56,7 @@ Edfa Edfa_fiber (Stockholm → Norrköping)_(1/2)
   type_variety:           openroadm_ila_low_noise
   effective gain(dB):     16.33
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.01
   (including att_in)
   pad att_in (dB):        0.00
@@ -54,8 +64,7 @@ Edfa Edfa_fiber (Stockholm → Norrköping)_(1/2)
   Power Out (dBm):        21.84
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
-  actual pch out (dBm):   2.02
+  actual pch out (dBm):   2.01
   output VOA (dB):        0.00
 Fiber          fiber (Stockholm → Norrköping)_(2/2)
   type_variety:                SSMF
@@ -65,29 +74,32 @@ Fiber          fiber (Stockholm → Norrköping)_(2/2)
   (includes conn loss (dB) in: 0.00 out: 0.00)
   (conn loss out includes EOL margin defined in eqpt_config.json)
   reference pch out (dBm):     -14.33
-  actual pch out (dBm):        -14.29
+  actual pch out (dBm):        -14.30
 Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2)
   type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
   effective gain(dB):     16.33
   (before att_in and before output VOA)
-  noise figure (dB):      11.44
+  tilt-target(dB)         0.00
+  noise figure (dB):      11.43
   (including att_in)
   pad att_in (dB):        0.00
-  Power In (dBm):         5.53
-  Power Out (dBm):        21.86
+  Power In (dBm):         5.52
+  Power Out (dBm):        21.85
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
-  actual pch out (dBm):   2.04
+  actual pch out (dBm):   2.03
   output VOA (dB):        0.00
 Roadm roadm_Norrköping
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.03
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -95,7 +107,6 @@ Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Norrköping → Linköping)
@@ -111,6 +122,7 @@ Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
   type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
   effective gain(dB):     11.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      16.00
   (including att_in)
   pad att_in (dB):        0.00
@@ -118,17 +130,19 @@ Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
   Power Out (dBm):        21.83
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.01
   output VOA (dB):        0.00
 Roadm roadm_Linköping
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.01
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -136,7 +150,6 @@ Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Linköping → Jönköping)
@@ -152,24 +165,27 @@ Edfa Edfa_preamp_roadm_Jönköping_from_fiber (Linköping → Jönköping)
   type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
   effective gain(dB):     26.80
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.01
   (including att_in)
   pad att_in (dB):        0.00
   Power In (dBm):         -4.97
-  Power Out (dBm):        21.86
+  Power Out (dBm):        21.87
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.04
   output VOA (dB):        0.00
 Roadm roadm_Jönköping
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.04
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -177,7 +193,6 @@ Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Jönköping → Borås)
@@ -193,6 +208,7 @@ Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
   type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
   effective gain(dB):     17.82
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      10.54
   (including att_in)
   pad att_in (dB):        0.00
@@ -200,17 +216,19 @@ Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
   Power Out (dBm):        21.84
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
-  actual pch out (dBm):   2.01
+  actual pch out (dBm):   2.02
   output VOA (dB):        0.00
 Roadm roadm_Borås
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.02
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      -inf
   (including att_in)
   pad att_in (dB):        0.00
@@ -218,7 +236,6 @@ Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
   Power Out (dBm):        21.82
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Borås → Gothenburg)
@@ -234,6 +251,7 @@ Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
   type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
   effective gain(dB):     13.53
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      13.54
   (including att_in)
   pad att_in (dB):        0.00
@@ -241,13 +259,14 @@ Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
   Power Out (dBm):        21.84
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
-  effective pch (dBm):    2.00
   actual pch out (dBm):   2.02
   output VOA (dB):        0.00
 Roadm roadm_Gothenburg
-  effective loss (dB):     22.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     22.00
+  Actual loss (dB):        22.02
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Transceiver trx_Gothenburg
   GSNR (0.1nm, dB):          19.25
   GSNR (signal bw, dB):      15.23
@@ -257,8 +276,9 @@ Transceiver trx_Gothenburg
   PMD (ps):                  7.99
   PDL (dB):                  3.74
   Latency (ms):              2.45
+  Actual pch out (dBm):      2.00
 
-Transmission result for input power = 2.00 dBm:
+Transmission result for input optical power reference in span = 2.00 dBm:
   Final GSNR (0.1 nm): 19.25 dB
 
 (No source node specified: picked trx_Stockholm)

tests/invocation/path_requests_run

@@ -10,7 +10,6 @@
 	node-diverse: True
 	request-id-numbers: ['4', '5']
 ]
-Aggregating similar requests
 The following services have been requested:
 [PathRequest 0
 	source: 	trx Lorient_KMA
@@ -21,6 +20,7 @@
 	bit_rate:	None Gb/s
 	spacing:	50.0 GHz
 	power:  	1.0 dBm
+	tx_power_dbm:  	0.0 dBm
 	nb channels: 	80
 	path_bandwidth: 	100.0 Gbit/s
 	nodes-list:	[]
@@ -34,6 +34,7 @@
 	bit_rate:	100.0 Gb/s
 	spacing:	50.0 GHz
 	power:  	1.0 dBm
+	tx_power_dbm:  	0.0 dBm
 	nb channels: 	95
 	path_bandwidth: 	200.0 Gbit/s
 	nodes-list:	['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE']
@@ -47,6 +48,7 @@
 	bit_rate:	100.0 Gb/s
 	spacing:	50.0 GHz
 	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
 	nb channels: 	95
 	path_bandwidth: 	60.0 Gbit/s
 	nodes-list:	[]
@@ -60,6 +62,7 @@
 	bit_rate:	None Gb/s
 	spacing:	75.0 GHz
 	power:  	3.0 dBm
+	tx_power_dbm:  	0.0 dBm
 	nb channels: 	63
 	path_bandwidth: 	150.0 Gbit/s
 	nodes-list:	[]
@@ -73,11 +76,12 @@
 	bit_rate:	200.0 Gb/s
 	spacing:	75.0 GHz
 	power:  	3.0 dBm
+	tx_power_dbm:  	0.0 dBm
 	nb channels: 	63
 	path_bandwidth: 	20.0 Gbit/s
 	nodes-list:	[]
 	loose-list:	[]
-, PathRequest 7 | 6
+, PathRequest 6
 	source: 	trx Lannion_CAS
 	destination:	trx Lorient_KMA
 	trx type:	Voyager
@@ -86,8 +90,23 @@
 	bit_rate:	100.0 Gb/s
 	spacing:	50.0 GHz
 	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
 	nb channels: 	76
-	path_bandwidth: 	700.0 Gbit/s
+	path_bandwidth: 	300.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 7
+	source: 	trx Lannion_CAS
+	destination:	trx Lorient_KMA
+	trx type:	Voyager
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	50.0 GHz
+	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	76
+	path_bandwidth: 	400.0 Gbit/s
 	nodes-list:	[]
 	loose-list:	[]
 , PathRequest 7b
@@ -99,13 +118,12 @@
 	bit_rate:	100.0 Gb/s
 	spacing:	75.0 GHz
 	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
 	nb channels: 	50
 	path_bandwidth: 	400.0 Gbit/s
 	nodes-list:	[]
 	loose-list:	[]
 ]
-Computing all paths with constraints
-Propagating on selected path
 Result summary
 req id   demand                                GSNR@bandwidth A-Z (Z-A)   GSNR@0.1nm A-Z (Z-A)        Receiver minOSNR               mode                    Gbit/s              nb of tsp pairs      N,M or blocking reason 
 0       trx Lorient_KMA to trx Vannes_KBE :             24.83                    28.92                      14                     mode 1                   100.0                      1                   ([-284],[4])      

tests/invocation/path_requests_run_CD_PMD_PDL_missing

@@ -1,6 +1,5 @@
 List of disjunctions
 []
-Aggregating similar requests
 The following services have been requested:
 [PathRequest 0
 	source: 	trx Abilene
@@ -11,13 +10,12 @@
 	bit_rate:	300.0 Gb/s
 	spacing:	62.50000000000001 GHz
 	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
 	nb channels: 	76
 	path_bandwidth: 	100.0 Gbit/s
 	nodes-list:	[]
 	loose-list:	[]
 ]
-Computing all paths with constraints
-Propagating on selected path
 Result summary
 req id   demand                       GSNR@bandwidth A-Z (Z-A)   GSNR@0.1nm A-Z (Z-A)        Receiver minOSNR               mode                    Gbit/s              nb of tsp pairs      N,M or blocking reason 
 0       trx Abilene to trx Albany :             9.04                     14.5                      -                      mode 3                   100.0                      -                MODE_NOT_FEASIBLE    

tests/invocation/power_sweep_example

@@ -0,0 +1,161 @@
+Power mode is set to True
+=> it can be modified in eqpt_config.json - Span
+
+There are 4 fiber spans over 200 km between trx Brest_KLA and trx Rennes_STA
+
+Now propagating between trx Brest_KLA and trx Rennes_STA:
+Reference used for design: (Input optical power reference in span = 3.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 95)
+
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 95)
+Input optical power reference in span = -3.00 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          23.73
+  GSNR (signal bw, dB):      19.65
+  OSNR ASE (0.1nm, dB):      23.99
+  OSNR ASE (signal bw, dB):  19.91
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = -2.50 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.01
+  GSNR (signal bw, dB):      19.93
+  OSNR ASE (0.1nm, dB):      24.37
+  OSNR ASE (signal bw, dB):  20.29
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = -2.00 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.25
+  GSNR (signal bw, dB):      20.17
+  OSNR ASE (0.1nm, dB):      24.74
+  OSNR ASE (signal bw, dB):  20.66
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = -1.50 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.44
+  GSNR (signal bw, dB):      20.36
+  OSNR ASE (0.1nm, dB):      25.10
+  OSNR ASE (signal bw, dB):  21.01
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = -1.00 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.57
+  GSNR (signal bw, dB):      20.49
+  OSNR ASE (0.1nm, dB):      25.44
+  OSNR ASE (signal bw, dB):  21.36
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = -0.50 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.63
+  GSNR (signal bw, dB):      20.55
+  OSNR ASE (0.1nm, dB):      25.77
+  OSNR ASE (signal bw, dB):  21.69
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = -0.00 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.60
+  GSNR (signal bw, dB):      20.52
+  OSNR ASE (0.1nm, dB):      26.09
+  OSNR ASE (signal bw, dB):  22.00
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = 0.50 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.42
+  GSNR (signal bw, dB):      20.34
+  OSNR ASE (0.1nm, dB):      26.29
+  OSNR ASE (signal bw, dB):  22.20
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = 1.00 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.16
+  GSNR (signal bw, dB):      20.08
+  OSNR ASE (0.1nm, dB):      26.47
+  OSNR ASE (signal bw, dB):  22.39
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = 1.50 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.02
+  GSNR (signal bw, dB):      19.93
+  OSNR ASE (0.1nm, dB):      26.55
+  OSNR ASE (signal bw, dB):  22.47
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = 2.00 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.02
+  GSNR (signal bw, dB):      19.93
+  OSNR ASE (0.1nm, dB):      26.55
+  OSNR ASE (signal bw, dB):  22.47
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = 2.50 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.02
+  GSNR (signal bw, dB):      19.93
+  OSNR ASE (0.1nm, dB):      26.55
+  OSNR ASE (signal bw, dB):  22.47
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+Input optical power reference in span = 3.00 dBm:
+Transceiver trx Rennes_STA
+  GSNR (0.1nm, dB):          24.02
+  GSNR (signal bw, dB):      19.93
+  OSNR ASE (0.1nm, dB):      26.55
+  OSNR ASE (signal bw, dB):  22.47
+  CD (ps/nm):                3340.00
+  PMD (ps):                  0.57
+  PDL (dB):                  0.00
+  Latency (ms):              0.98
+  Actual pch out (dBm):      3.00
+
+(Invalid source node 'brest' replaced with trx Brest_KLA)
+
+(Invalid destination node 'rennes' replaced with trx Rennes_STA)

tests/invocation/spectrum1_transmission_main_example

@@ -1,13 +1,19 @@
 User input for spectrum used for propagation instead of SI
-There are 76 channels propagating
 Power mode is set to True
 => it can be modified in eqpt_config.json - Span
 
 There are 3 fiber spans over 130 km between trx Lannion_CAS and trx Lorient_KMA
 
 Now propagating between trx Lannion_CAS and trx Lorient_KMA:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 76)
 
-Propagating with input power = 0.00 dBm:
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 0.00dBm,
+                       nb_channels = 76)
+Input optical power reference in span = 0.00 dBm:
 Transceiver trx Lannion_CAS
   GSNR (0.1nm, dB):          40.00
   GSNR (signal bw, dB):      35.92
@@ -17,14 +23,18 @@ Transceiver trx Lannion_CAS
   PMD (ps):                  0.00
   PDL (dB):                  0.00
   Latency (ms):              0.00
+  Actual pch out (dBm):      0.00
 Roadm roadm Lannion_CAS
-  effective loss (dB):     20.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        20.00
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa east edfa in Lannion_CAS to Corlay
   type_variety:           std_medium_gain
   effective gain(dB):     21.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      6.36
   (including att_in)
   pad att_in (dB):        0.00
@@ -32,7 +42,6 @@ Edfa east edfa in Lannion_CAS to Corlay
   Power Out (dBm):        19.82
   Delta_P (dB):           1.00
   target pch (dBm):       1.00
-  effective pch (dBm):    1.00
   actual pch out (dBm):   1.01
   output VOA (dB):        0.00
 Fiber          fiber (Lannion_CAS → Corlay)-F061
@@ -70,6 +79,7 @@ Edfa west edfa in Lorient_KMA to Loudeac
   type_variety:           std_high_gain
   effective gain(dB):     28.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      5.92
   (including att_in)
   pad att_in (dB):        0.00
@@ -77,13 +87,14 @@ Edfa west edfa in Lorient_KMA to Loudeac
   Power Out (dBm):        19.85
   Delta_P (dB):           1.00
   target pch (dBm):       1.00
-  effective pch (dBm):    1.00
   actual pch out (dBm):   1.05
   output VOA (dB):        0.00
 Roadm roadm Lorient_KMA
-  effective loss (dB):     21.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     21.00
+  Actual loss (dB):        21.05
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Transceiver trx Lorient_KMA
   GSNR (0.1nm, dB):          23.61
   GSNR (signal bw, dB):      19.53
@@ -93,8 +104,9 @@ Transceiver trx Lorient_KMA
   PMD (ps):                  0.46
   PDL (dB):                  0.00
   Latency (ms):              0.64
+  Actual pch out (dBm):      0.00
 
-Transmission result for input power = 0.00 dBm:
+Transmission result for input optical power reference in span = 0.00 dBm:
   Final GSNR (0.1 nm): 23.61 dB
 
 (No source node specified: picked trx Lannion_CAS)

tests/invocation/spectrum2_transmission_main_example

@@ -1,13 +1,19 @@
 User input for spectrum used for propagation instead of SI
-There are 60 channels propagating
 Power mode is set to True
 => it can be modified in eqpt_config.json - Span
 
 There are 3 fiber spans over 130 km between trx Lannion_CAS and trx Lorient_KMA
 
 Now propagating between trx Lannion_CAS and trx Lorient_KMA:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 76)
 
-Propagating with input power = 0.00 dBm:
+Channels propagating: (Input optical power deviation in span = mode_1: 0.00, mode_2: 0.00dB,
+                       spacing = mode_1: 50.00, mode_2: 75.00GHz,
+                       transceiver output power = mode_1: 0.00, mode_2: 0.00dBm,
+                       nb_channels = 60)
+Input optical power reference in span = 0.00 dBm:
 Transceiver trx Lannion_CAS
   GSNR (0.1nm, dB):          mode_1: 40.00, mode_2: 40.00
   GSNR (signal bw, dB):      mode_1: 35.92, mode_2: 32.91
@@ -17,14 +23,18 @@ Transceiver trx Lannion_CAS
   PMD (ps):                  0.00
   PDL (dB):                  0.00
   Latency (ms):              0.00
+  Actual pch out (dBm):      mode_1: 0.00, mode_2: 0.00
 Roadm roadm Lannion_CAS
-  effective loss (dB):     20.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.00, mode_2: 20.00
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
 Edfa east edfa in Lannion_CAS to Corlay
   type_variety:           std_medium_gain
   effective gain(dB):     21.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      6.36
   (including att_in)
   pad att_in (dB):        0.00
@@ -32,7 +42,6 @@ Edfa east edfa in Lannion_CAS to Corlay
   Power Out (dBm):        18.79
   Delta_P (dB):           1.00
   target pch (dBm):       1.00
-  effective pch (dBm):    1.00
   actual pch out (dBm):   mode_1: 1.01, mode_2: 1.02
   output VOA (dB):        0.00
 Fiber          fiber (Lannion_CAS → Corlay)-F061
@@ -70,6 +79,7 @@ Edfa west edfa in Lorient_KMA to Loudeac
   type_variety:           std_high_gain
   effective gain(dB):     28.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      5.92
   (including att_in)
   pad att_in (dB):        0.00
@@ -77,13 +87,14 @@ Edfa west edfa in Lorient_KMA to Loudeac
   Power Out (dBm):        18.84
   Delta_P (dB):           1.00
   target pch (dBm):       1.00
-  effective pch (dBm):    1.00
   actual pch out (dBm):   mode_1: 1.04, mode_2: 1.09
   output VOA (dB):        0.00
 Roadm roadm Lorient_KMA
-  effective loss (dB):     21.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+  Type_variety:            default
+  Reference loss (dB):     21.00
+  Actual loss (dB):        mode_1: 21.04, mode_2: 21.09
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
 Transceiver trx Lorient_KMA
   GSNR (0.1nm, dB):          mode_1: 23.66, mode_2: 23.81
   GSNR (signal bw, dB):      mode_1: 19.58, mode_2: 16.72
@@ -93,8 +104,9 @@ Transceiver trx Lorient_KMA
   PMD (ps):                  0.46
   PDL (dB):                  0.00
   Latency (ms):              0.64
+  Actual pch out (dBm):      mode_1: 0.00, mode_2: 0.00
 
-Transmission result for input power = 0.00 dBm:
+Transmission result for input optical power reference in span = 0.00 dBm:
   Final GSNR (0.1 nm): 23.72 dB
 
 The GSNR per channel at the end of the line is:

tests/invocation/transmission_long_pow

@@ -0,0 +1,474 @@
+User input for spectrum used for propagation instead of SI
+Power mode is set to True
+=> it can be modified in eqpt_config.json - Span
+
+There are 15 fiber spans over 1200 km between Site_A and Site_B
+
+Now propagating between Site_A and Site_B:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 96)
+
+Channels propagating: (Input optical power deviation in span = mode_1: 0.00, mode_2: 0.00dB,
+                       spacing = mode_1: 50.00, mode_2: 75.00GHz,
+                       transceiver output power = mode_1: 0.00, mode_2: 0.00dBm,
+                       nb_channels = 60)
+Input optical power reference in span = 0.00 dBm:
+Transceiver Site_A
+  GSNR (0.1nm, dB):          mode_1: 40.00, mode_2: 40.00
+  GSNR (signal bw, dB):      mode_1: 35.92, mode_2: 32.91
+  OSNR ASE (0.1nm, dB):      mode_1: 40.00, mode_2: 40.00
+  OSNR ASE (signal bw, dB):  mode_1: 35.92, mode_2: 32.91
+  CD (ps/nm):                0.00
+  PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
+  Actual pch out (dBm):      mode_1: 0.00, mode_2: 0.00
+Roadm roadm Site A
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.00, mode_2: 20.00
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+Edfa booster A
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -2.22
+  Power Out (dBm):        17.79
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 0.02
+  output VOA (dB):        0.00
+Fiber          Span1
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -15.98
+Edfa Edfa1
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         1.80
+  Power Out (dBm):        17.80
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 0.03
+  output VOA (dB):        0.00
+Fiber          Span2
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -15.97
+Edfa Edfa2
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         1.81
+  Power Out (dBm):        17.81
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 0.04
+  output VOA (dB):        0.00
+Fiber          Span3
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -15.96
+Edfa Edfa3
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         1.82
+  Power Out (dBm):        17.82
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 0.05
+  output VOA (dB):        0.00
+Fiber          Span4
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.96, mode_2: -15.94
+Edfa Edfa4
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         1.83
+  Power Out (dBm):        17.84
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 0.07
+  output VOA (dB):        0.00
+Fiber          Span5
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.95, mode_2: -15.93
+Edfa Edfa5
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         1.84
+  Power Out (dBm):        17.85
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.05, mode_2: 0.08
+  output VOA (dB):        0.00
+Roadm roadm Site C
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.05, mode_2: 20.08
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+Edfa booster C
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -2.22
+  Power Out (dBm):        17.79
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 0.02
+  output VOA (dB):        0.00
+Fiber          Span6
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -15.98
+Edfa Edfa6
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         1.80
+  Power Out (dBm):        17.80
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 0.03
+  output VOA (dB):        0.00
+Fiber          Span7
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -15.97
+Edfa Edfa7
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         1.81
+  Power Out (dBm):        17.81
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 0.04
+  output VOA (dB):        0.00
+Fiber          Span8
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -15.96
+Edfa Edfa8
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         1.82
+  Power Out (dBm):        17.82
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 0.05
+  output VOA (dB):        0.00
+Fiber          Span9
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.96, mode_2: -15.94
+Edfa Edfa9
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         1.83
+  Power Out (dBm):        17.83
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 0.07
+  output VOA (dB):        0.00
+Fiber          Span10
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.95, mode_2: -15.93
+Edfa Edfa10
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         1.84
+  Power Out (dBm):        17.85
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.05, mode_2: 0.08
+  output VOA (dB):        0.00
+Roadm roadm Site D
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.05, mode_2: 20.08
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+Edfa booster D
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -2.22
+  Power Out (dBm):        17.79
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 0.02
+  output VOA (dB):        0.00
+Fiber          Span11
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -15.98
+Edfa Edfa11
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         1.80
+  Power Out (dBm):        17.80
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 0.03
+  output VOA (dB):        0.00
+Fiber          Span12
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -15.97
+Edfa Edfa12
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         1.81
+  Power Out (dBm):        17.81
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 0.04
+  output VOA (dB):        0.00
+Roadm roadm Site E
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.03, mode_2: 20.04
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+Edfa booster E
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -2.22
+  Power Out (dBm):        17.79
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 0.02
+  output VOA (dB):        0.00
+Fiber          Span13
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -15.98
+Edfa Edfa13
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         1.80
+  Power Out (dBm):        17.80
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 0.03
+  output VOA (dB):        0.00
+Fiber          Span14
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -15.97
+Edfa Edfa14
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         1.81
+  Power Out (dBm):        17.81
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 0.04
+  output VOA (dB):        0.00
+Fiber          Span15
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -15.96
+Edfa Edfa15
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         1.82
+  Power Out (dBm):        17.82
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 0.05
+  output VOA (dB):        0.00
+Roadm roadm Site B
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.03, mode_2: 20.05
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+Transceiver Site_B
+  GSNR (0.1nm, dB):          mode_1: 18.11, mode_2: 19.18
+  GSNR (signal bw, dB):      mode_1: 14.02, mode_2: 12.09
+  OSNR ASE (0.1nm, dB):      mode_1: 19.69, mode_2: 19.62
+  OSNR ASE (signal bw, dB):  mode_1: 15.61, mode_2: 12.53
+  CD (ps/nm):                20040.00
+  PMD (ps):                  1.39
+  PDL (dB):                  0.00
+  Latency (ms):              5.88
+  Actual pch out (dBm):      mode_1: 0.00, mode_2: 0.00
+
+Transmission result for input optical power reference in span = 0.00 dBm:
+  Final GSNR (0.1 nm): 18.56 dB
+
+(No source node specified: picked Site_A)
+
+(No destination node specified: picked Site_B)

tests/invocation/transmission_long_psd

@@ -0,0 +1,474 @@
+User input for spectrum used for propagation instead of SI
+Power mode is set to True
+=> it can be modified in eqpt_config.json - Span
+
+There are 15 fiber spans over 1200 km between Site_A and Site_B
+
+Now propagating between Site_A and Site_B:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 95)
+
+Channels propagating: (Input optical power deviation in span = mode_1: 0.00, mode_2: 0.00dB,
+                       spacing = mode_1: 50.00, mode_2: 75.00GHz,
+                       transceiver output power = mode_1: 0.00, mode_2: 0.00dBm,
+                       nb_channels = 60)
+Input optical power reference in span = 0.00 dBm:
+Transceiver Site_A
+  GSNR (0.1nm, dB):          mode_1: 40.00, mode_2: 40.00
+  GSNR (signal bw, dB):      mode_1: 35.92, mode_2: 32.91
+  OSNR ASE (0.1nm, dB):      mode_1: 40.00, mode_2: 40.00
+  OSNR ASE (signal bw, dB):  mode_1: 35.92, mode_2: 32.91
+  CD (ps/nm):                0.00
+  PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
+  Actual pch out (dBm):      mode_1: 0.00, mode_2: 0.00
+Roadm roadm Site A
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.00, mode_2: 16.99
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -16.99
+Edfa booster A
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.71
+  Power Out (dBm):        19.30
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 3.02
+  output VOA (dB):        0.00
+Fiber          Span1
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -12.98
+Edfa Edfa1
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         3.31
+  Power Out (dBm):        19.31
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 3.03
+  output VOA (dB):        0.00
+Fiber          Span2
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -12.97
+Edfa Edfa2
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         3.32
+  Power Out (dBm):        19.32
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 3.04
+  output VOA (dB):        0.00
+Fiber          Span3
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -12.95
+Edfa Edfa3
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         3.33
+  Power Out (dBm):        19.33
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 3.05
+  output VOA (dB):        0.00
+Fiber          Span4
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.96, mode_2: -12.94
+Edfa Edfa4
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         3.34
+  Power Out (dBm):        19.34
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.05, mode_2: 3.06
+  output VOA (dB):        0.00
+Fiber          Span5
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.95, mode_2: -12.93
+Edfa Edfa5
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         3.35
+  Power Out (dBm):        19.35
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.06, mode_2: 3.07
+  output VOA (dB):        0.00
+Roadm roadm Site C
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.06, mode_2: 20.06
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -16.99
+Edfa booster C
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.71
+  Power Out (dBm):        19.30
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 3.02
+  output VOA (dB):        0.00
+Fiber          Span6
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -12.98
+Edfa Edfa6
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         3.31
+  Power Out (dBm):        19.31
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 3.03
+  output VOA (dB):        0.00
+Fiber          Span7
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -12.97
+Edfa Edfa7
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         3.32
+  Power Out (dBm):        19.32
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 3.04
+  output VOA (dB):        0.00
+Fiber          Span8
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -12.95
+Edfa Edfa8
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         3.33
+  Power Out (dBm):        19.33
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 3.05
+  output VOA (dB):        0.00
+Fiber          Span9
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.96, mode_2: -12.94
+Edfa Edfa9
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         3.34
+  Power Out (dBm):        19.34
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.05, mode_2: 3.06
+  output VOA (dB):        0.00
+Fiber          Span10
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.95, mode_2: -12.93
+Edfa Edfa10
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         3.35
+  Power Out (dBm):        19.35
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.06, mode_2: 3.07
+  output VOA (dB):        0.00
+Roadm roadm Site D
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.06, mode_2: 20.06
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -16.99
+Edfa booster D
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.71
+  Power Out (dBm):        19.30
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 3.02
+  output VOA (dB):        0.00
+Fiber          Span11
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -12.98
+Edfa Edfa11
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         3.31
+  Power Out (dBm):        19.31
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 3.03
+  output VOA (dB):        0.00
+Fiber          Span12
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -12.97
+Edfa Edfa12
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         3.32
+  Power Out (dBm):        19.32
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 3.04
+  output VOA (dB):        0.00
+Roadm roadm Site E
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.03, mode_2: 20.03
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -16.99
+Edfa booster E
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.71
+  Power Out (dBm):        19.30
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 3.02
+  output VOA (dB):        0.00
+Fiber          Span13
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -12.98
+Edfa Edfa13
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         3.31
+  Power Out (dBm):        19.31
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 3.03
+  output VOA (dB):        0.00
+Fiber          Span14
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -12.97
+Edfa Edfa14
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         3.32
+  Power Out (dBm):        19.32
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 3.04
+  output VOA (dB):        0.00
+Fiber          Span15
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -12.96
+Edfa Edfa15
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         3.33
+  Power Out (dBm):        19.33
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 3.05
+  output VOA (dB):        0.00
+Roadm roadm Site B
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.04, mode_2: 20.04
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -16.99
+Transceiver Site_B
+  GSNR (0.1nm, dB):          mode_1: 17.91, mode_2: 20.37
+  GSNR (signal bw, dB):      mode_1: 13.83, mode_2: 13.28
+  OSNR ASE (0.1nm, dB):      mode_1: 19.69, mode_2: 22.55
+  OSNR ASE (signal bw, dB):  mode_1: 15.61, mode_2: 15.46
+  CD (ps/nm):                20040.00
+  PMD (ps):                  1.39
+  PDL (dB):                  0.00
+  Latency (ms):              5.88
+  Actual pch out (dBm):      mode_1: 0.00, mode_2: 0.00
+
+Transmission result for input optical power reference in span = 0.00 dBm:
+  Final GSNR (0.1 nm): 18.94 dB
+
+(No source node specified: picked Site_A)
+
+(No destination node specified: picked Site_B)

tests/invocation/transmission_long_psw

@@ -0,0 +1,474 @@
+User input for spectrum used for propagation instead of SI
+Power mode is set to True
+=> it can be modified in eqpt_config.json - Span
+
+There are 15 fiber spans over 1200 km between Site_A and Site_B
+
+Now propagating between Site_A and Site_B:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 95)
+
+Channels propagating: (Input optical power deviation in span = mode_1: 0.00, mode_2: 0.00dB,
+                       spacing = mode_1: 50.00, mode_2: 75.00GHz,
+                       transceiver output power = mode_1: 0.00, mode_2: 0.00dBm,
+                       nb_channels = 60)
+Input optical power reference in span = 0.00 dBm:
+Transceiver Site_A
+  GSNR (0.1nm, dB):          mode_1: 40.00, mode_2: 40.00
+  GSNR (signal bw, dB):      mode_1: 35.92, mode_2: 32.91
+  OSNR ASE (0.1nm, dB):      mode_1: 40.00, mode_2: 40.00
+  OSNR ASE (signal bw, dB):  mode_1: 35.92, mode_2: 32.91
+  CD (ps/nm):                0.00
+  PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
+  Actual pch out (dBm):      mode_1: 0.00, mode_2: 0.00
+Roadm roadm Site A
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.00, mode_2: 18.24
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -18.24
+Edfa booster A
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -1.40
+  Power Out (dBm):        18.61
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 1.77
+  output VOA (dB):        0.00
+Fiber          Span1
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -14.22
+Edfa Edfa1
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         2.62
+  Power Out (dBm):        18.62
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 1.78
+  output VOA (dB):        0.00
+Fiber          Span2
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -14.21
+Edfa Edfa2
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         2.63
+  Power Out (dBm):        18.63
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 1.79
+  output VOA (dB):        0.00
+Fiber          Span3
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -14.20
+Edfa Edfa3
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         2.64
+  Power Out (dBm):        18.64
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 1.80
+  output VOA (dB):        0.00
+Fiber          Span4
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.96, mode_2: -14.19
+Edfa Edfa4
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         2.65
+  Power Out (dBm):        18.65
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.05, mode_2: 1.81
+  output VOA (dB):        0.00
+Fiber          Span5
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.95, mode_2: -14.18
+Edfa Edfa5
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         2.66
+  Power Out (dBm):        18.66
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.05, mode_2: 1.82
+  output VOA (dB):        0.00
+Roadm roadm Site C
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.05, mode_2: 20.06
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -18.24
+Edfa booster C
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -1.40
+  Power Out (dBm):        18.61
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 1.77
+  output VOA (dB):        0.00
+Fiber          Span6
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -14.23
+Edfa Edfa6
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         2.62
+  Power Out (dBm):        18.62
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 1.78
+  output VOA (dB):        0.00
+Fiber          Span7
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -14.21
+Edfa Edfa7
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         2.63
+  Power Out (dBm):        18.63
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 1.79
+  output VOA (dB):        0.00
+Fiber          Span8
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -14.20
+Edfa Edfa8
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         2.64
+  Power Out (dBm):        18.64
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 1.80
+  output VOA (dB):        0.00
+Fiber          Span9
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.96, mode_2: -14.19
+Edfa Edfa9
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         2.65
+  Power Out (dBm):        18.65
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.04, mode_2: 1.81
+  output VOA (dB):        0.00
+Fiber          Span10
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.95, mode_2: -14.18
+Edfa Edfa10
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         2.66
+  Power Out (dBm):        18.66
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.05, mode_2: 1.82
+  output VOA (dB):        0.00
+Roadm roadm Site D
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.05, mode_2: 20.06
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -18.24
+Edfa booster D
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -1.40
+  Power Out (dBm):        18.61
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 1.77
+  output VOA (dB):        0.00
+Fiber          Span11
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -14.23
+Edfa Edfa11
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         2.62
+  Power Out (dBm):        18.62
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 1.78
+  output VOA (dB):        0.00
+Fiber          Span12
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -14.21
+Edfa Edfa12
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         2.63
+  Power Out (dBm):        18.63
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 1.79
+  output VOA (dB):        0.00
+Roadm roadm Site E
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.03, mode_2: 20.03
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -18.24
+Edfa booster E
+  type_variety:           std_medium_gain
+  effective gain(dB):     20.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      6.58
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -1.40
+  Power Out (dBm):        18.61
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.01, mode_2: 1.77
+  output VOA (dB):        0.00
+Fiber          Span13
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.99, mode_2: -14.23
+Edfa Edfa13
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         2.62
+  Power Out (dBm):        18.62
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.02, mode_2: 1.78
+  output VOA (dB):        0.00
+Fiber          Span14
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.98, mode_2: -14.22
+Edfa Edfa14
+  type_variety:           test_fixed_gain
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      9.00
+  (including att_in)
+  pad att_in (dB):        4.00
+  Power In (dBm):         2.63
+  Power Out (dBm):        18.63
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 1.79
+  output VOA (dB):        0.00
+Fiber          Span15
+  type_variety:                SSMF
+  length (km):                 80.00
+  pad att_in (dB):             0.00
+  total loss (dB):             16.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -16.00
+  actual pch out (dBm):        mode_1: -15.97, mode_2: -14.20
+Edfa Edfa15
+  type_variety:           test
+  effective gain(dB):     16.00
+  (before att_in and before output VOA)
+  tilt-target(dB)         0.00
+  noise figure (dB):      8.86
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         2.64
+  Power Out (dBm):        18.64
+  Delta_P (dB):           0.00
+  target pch (dBm):       0.00
+  actual pch out (dBm):   mode_1: 0.03, mode_2: 1.80
+  output VOA (dB):        0.00
+Roadm roadm Site B
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        mode_1: 20.03, mode_2: 20.04
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    mode_1: -20.00, mode_2: -18.24
+Transceiver Site_B
+  GSNR (0.1nm, dB):          mode_1: 18.02, mode_2: 20.22
+  GSNR (signal bw, dB):      mode_1: 13.94, mode_2: 13.12
+  OSNR ASE (0.1nm, dB):      mode_1: 19.69, mode_2: 21.35
+  OSNR ASE (signal bw, dB):  mode_1: 15.61, mode_2: 14.26
+  CD (ps/nm):                20040.00
+  PMD (ps):                  1.39
+  PDL (dB):                  0.00
+  Latency (ms):              5.88
+  Actual pch out (dBm):      mode_1: 0.00, mode_2: 0.00
+
+Transmission result for input optical power reference in span = 0.00 dBm:
+  Final GSNR (0.1 nm): 18.94 dB
+
+(No source node specified: picked Site_A)
+
+(No destination node specified: picked Site_B)

tests/invocation/transmission_main_example

@@ -1,12 +1,18 @@
-There are 76 channels propagating
 Power mode is set to True
 => it can be modified in eqpt_config.json - Span
 
 There are 1 fiber spans over 80 km between Site_A and Site_B
 
 Now propagating between Site_A and Site_B:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 76)
 
-Propagating with input power = 0.00 dBm:
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 0.00dBm,
+                       nb_channels = 76)
+Input optical power reference in span = 0.00 dBm:
 Transceiver Site_A
   GSNR (0.1nm, dB):          40.00
   GSNR (signal bw, dB):      35.92
@@ -16,6 +22,7 @@ Transceiver Site_A
   PMD (ps):                  0.00
   PDL (dB):                  0.00
   Latency (ms):              0.00
+  Actual pch out (dBm):      0.00
 Fiber          Span1
   type_variety:                SSMF
   length (km):                 80.00
@@ -29,6 +36,7 @@ Edfa Edfa1
   type_variety:           std_low_gain
   effective gain(dB):     15.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      6.62
   (including att_in)
   pad att_in (dB):        0.00
@@ -36,7 +44,6 @@ Edfa Edfa1
   Power Out (dBm):        16.82
   Delta_P (dB):           -2.00
   target pch (dBm):       -2.00
-  effective pch (dBm):    -2.00
   actual pch out (dBm):   -1.99
   output VOA (dB):        0.00
 Transceiver Site_B
@@ -48,8 +55,9 @@ Transceiver Site_B
   PMD (ps):                  0.36
   PDL (dB):                  0.00
   Latency (ms):              0.39
+  Actual pch out (dBm):      0.00
 
-Transmission result for input power = 0.00 dBm:
+Transmission result for input optical power reference in span = 0.00 dBm:
   Final GSNR (0.1 nm): 31.18 dB
 
 (No source node specified: picked Site_A)

tests/invocation/transmission_main_example__raman

@@ -1,12 +1,18 @@
-There are 76 channels propagating
 Power mode is set to True
 => it can be modified in eqpt_config.json - Span
 
 There are 1 fiber spans over 80 km between Site_A and Site_B
 
 Now propagating between Site_A and Site_B:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 76)
 
-Propagating with input power = 0.00 dBm:
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 0.00dBm,
+                       nb_channels = 76)
+Input optical power reference in span = 0.00 dBm:
 Transceiver Site_A
   GSNR (0.1nm, dB):          40.00
   GSNR (signal bw, dB):      35.92
@@ -16,6 +22,7 @@ Transceiver Site_A
   PMD (ps):                  0.00
   PDL (dB):                  0.00
   Latency (ms):              0.00
+  Actual pch out (dBm):      0.00
 RamanFiber          Span1
   type_variety:                SSMF
   length (km):                 80.00
@@ -25,113 +32,116 @@ RamanFiber          Span1
   (conn loss out includes EOL margin defined in eqpt_config.json)
   reference pch out (dBm):     -7.20
   actual pch out (dBm):        -7.47
+  reference gain (dB):         9.74
+  actual gain (dB):            9.8
 Fused Fused1
   loss (dB): 0.00
 Edfa Edfa1
   type_variety:           std_low_gain
-  effective gain(dB):     5.20
+  effective gain(dB):     5.26
   (before att_in and before output VOA)
-  noise figure (dB):      13.80
+  tilt-target(dB)         0.00
+  noise figure (dB):      13.74
   (including att_in)
-  pad att_in (dB):        2.80
+  pad att_in (dB):        2.74
   Power In (dBm):         11.61
-  Power Out (dBm):        16.81
+  Power Out (dBm):        16.87
   Delta_P (dB):           -2.00
   target pch (dBm):       -2.00
-  effective pch (dBm):    -2.00
-  actual pch out (dBm):   -2.26
+  actual pch out (dBm):   -2.21
   output VOA (dB):        0.00
 Transceiver Site_B
-  GSNR (0.1nm, dB):          31.42
-  GSNR (signal bw, dB):      27.34
-  OSNR ASE (0.1nm, dB):      34.21
-  OSNR ASE (signal bw, dB):  30.13
+  GSNR (0.1nm, dB):          31.44
+  GSNR (signal bw, dB):      27.35
+  OSNR ASE (0.1nm, dB):      34.24
+  OSNR ASE (signal bw, dB):  30.16
   CD (ps/nm):                1336.00
   PMD (ps):                  0.36
   PDL (dB):                  0.00
   Latency (ms):              0.39
+  Actual pch out (dBm):      0.00
 
-Transmission result for input power = 0.00 dBm:
-  Final GSNR (0.1 nm): 31.42 dB
+Transmission result for input optical power reference in span = 0.00 dBm:
+  Final GSNR (0.1 nm): 31.44 dB
 
 The GSNR per channel at the end of the line is:
 Ch. #   Channel frequency (THz)       Channel power (dBm)    OSNR ASE (signal bw, dB)     SNR NLI (signal bw, dB)        GSNR (signal bw, dB)
-    1                 191.35000                      0.22                       31.64                       31.55                       28.58
-    2                 191.40000                      0.18                       31.62                       31.46                       28.53
-    3                 191.45000                      0.15                       31.60                       31.37                       28.47
-    4                 191.50000                      0.11                       31.58                       31.28                       28.42
-    5                 191.55000                      0.05                       31.54                       31.20                       28.36
-    6                 191.60000                     -0.01                       31.51                       31.11                       28.30
-    7                 191.65000                     -0.07                       31.48                       31.03                       28.24
-    8                 191.70000                     -0.12                       31.45                       30.95                       28.18
-    9                 191.75000                     -0.18                       31.42                       30.87                       28.13
-   10                 191.80000                     -0.25                       31.38                       30.79                       28.07
-   11                 191.85000                     -0.31                       31.35                       30.72                       28.01
-   12                 191.90000                     -0.38                       31.31                       30.64                       27.95
-   13                 191.95000                     -0.44                       31.27                       30.57                       27.90
-   14                 192.00000                     -0.51                       31.24                       30.50                       27.84
-   15                 192.05000                     -0.58                       31.20                       30.42                       27.78
-   16                 192.10000                     -0.64                       31.16                       30.35                       27.73
-   17                 192.15000                     -0.71                       31.12                       30.29                       27.67
-   18                 192.20000                     -0.78                       31.08                       30.22                       27.62
-   19                 192.25000                     -0.85                       31.04                       30.22                       27.60
-   20                 192.30000                     -0.93                       31.00                       30.22                       27.58
-   21                 192.35000                     -1.00                       30.96                       30.23                       27.57
-   22                 192.40000                     -1.08                       30.91                       30.23                       27.55
-   23                 192.45000                     -1.16                       30.87                       30.23                       27.53
-   24                 192.50000                     -1.23                       30.82                       30.24                       27.51
-   25                 192.55000                     -1.30                       30.78                       30.24                       27.49
-   26                 192.60000                     -1.37                       30.74                       30.24                       27.47
-   27                 192.65000                     -1.44                       30.70                       30.25                       27.46
-   28                 192.70000                     -1.52                       30.65                       30.25                       27.44
-   29                 192.75000                     -1.59                       30.61                       30.25                       27.42
-   30                 192.80000                     -1.66                       30.57                       30.26                       27.40
-   31                 192.85000                     -1.73                       30.52                       30.26                       27.38
-   32                 192.90000                     -1.80                       30.48                       30.26                       27.36
-   33                 192.95000                     -1.87                       30.43                       30.27                       27.34
-   34                 193.00000                     -1.94                       30.39                       30.27                       27.32
-   35                 193.05000                     -2.01                       30.35                       30.27                       27.30
-   36                 193.10000                     -2.08                       30.30                       30.28                       27.28
-   37                 193.15000                     -2.15                       30.26                       30.28                       27.26
-   38                 193.20000                     -2.22                       30.22                       30.29                       27.24
-   39                 193.25000                     -2.29                       30.17                       30.31                       27.23
-   40                 193.30000                     -2.36                       30.13                       30.32                       27.21
-   41                 193.35000                     -2.43                       30.08                       30.33                       27.19
-   42                 193.40000                     -2.50                       30.04                       30.35                       27.18
-   43                 193.45000                     -2.56                       29.99                       30.36                       27.16
-   44                 193.50000                     -2.63                       29.95                       30.37                       27.14
-   45                 193.55000                     -2.71                       29.90                       30.39                       27.12
-   46                 193.60000                     -2.78                       29.85                       30.40                       27.11
-   47                 193.65000                     -2.85                       29.80                       30.41                       27.09
-   48                 193.70000                     -2.93                       29.75                       30.43                       27.07
-   49                 193.75000                     -3.00                       29.70                       30.44                       27.05
-   50                 193.80000                     -3.07                       29.65                       30.45                       27.02
-   51                 193.85000                     -3.15                       29.60                       30.47                       27.00
-   52                 193.90000                     -3.22                       29.55                       30.48                       26.98
-   53                 193.95000                     -3.29                       29.50                       30.50                       26.96
-   54                 194.00000                     -3.37                       29.45                       30.51                       26.94
-   55                 194.05000                     -3.44                       29.40                       30.52                       26.92
-   56                 194.10000                     -3.52                       29.35                       30.54                       26.89
-   57                 194.15000                     -3.59                       29.30                       30.59                       26.89
-   58                 194.20000                     -3.66                       29.25                       30.64                       26.88
-   59                 194.25000                     -3.74                       29.19                       30.70                       26.87
-   60                 194.30000                     -3.81                       29.14                       30.75                       26.86
-   61                 194.35000                     -3.89                       29.09                       30.81                       26.86
-   62                 194.40000                     -3.96                       29.04                       30.87                       26.85
-   63                 194.45000                     -4.04                       28.98                       30.93                       26.84
-   64                 194.50000                     -4.11                       28.93                       30.98                       26.83
-   65                 194.55000                     -4.18                       28.88                       31.04                       26.82
-   66                 194.60000                     -4.25                       28.83                       31.10                       26.81
-   67                 194.65000                     -4.31                       28.78                       31.17                       26.80
-   68                 194.70000                     -4.38                       28.74                       31.23                       26.79
-   69                 194.75000                     -4.45                       28.69                       31.29                       26.79
-   70                 194.80000                     -4.51                       28.64                       31.35                       26.78
-   71                 194.85000                     -4.58                       28.59                       31.42                       26.77
-   72                 194.90000                     -4.65                       28.54                       31.48                       26.76
-   73                 194.95000                     -4.71                       28.49                       31.55                       26.74
-   74                 195.00000                     -4.78                       28.44                       31.62                       26.73
-   75                 195.05000                     -4.85                       28.39                       31.69                       26.72
-   76                 195.10000                     -4.91                       28.34                       31.69                       26.69
+    1                 191.35000                      0.27                       31.66                       31.55                       28.60
+    2                 191.40000                      0.24                       31.64                       31.46                       28.54
+    3                 191.45000                      0.20                       31.62                       31.37                       28.48
+    4                 191.50000                      0.17                       31.60                       31.28                       28.43
+    5                 191.55000                      0.11                       31.57                       31.20                       28.37
+    6                 191.60000                      0.05                       31.54                       31.11                       28.31
+    7                 191.65000                     -0.01                       31.51                       31.03                       28.25
+    8                 191.70000                     -0.07                       31.47                       30.95                       28.20
+    9                 191.75000                     -0.13                       31.44                       30.87                       28.14
+   10                 191.80000                     -0.19                       31.41                       30.79                       28.08
+   11                 191.85000                     -0.26                       31.37                       30.72                       28.02
+   12                 191.90000                     -0.32                       31.34                       30.64                       27.97
+   13                 191.95000                     -0.39                       31.30                       30.57                       27.91
+   14                 192.00000                     -0.45                       31.26                       30.50                       27.85
+   15                 192.05000                     -0.52                       31.23                       30.42                       27.80
+   16                 192.10000                     -0.59                       31.19                       30.35                       27.74
+   17                 192.15000                     -0.66                       31.15                       30.29                       27.69
+   18                 192.20000                     -0.72                       31.11                       30.22                       27.63
+   19                 192.25000                     -0.79                       31.07                       30.22                       27.62
+   20                 192.30000                     -0.87                       31.03                       30.22                       27.60
+   21                 192.35000                     -0.95                       30.99                       30.23                       27.58
+   22                 192.40000                     -1.02                       30.94                       30.23                       27.56
+   23                 192.45000                     -1.10                       30.90                       30.23                       27.54
+   24                 192.50000                     -1.18                       30.85                       30.24                       27.52
+   25                 192.55000                     -1.25                       30.81                       30.24                       27.51
+   26                 192.60000                     -1.32                       30.77                       30.24                       27.49
+   27                 192.65000                     -1.39                       30.73                       30.25                       27.47
+   28                 192.70000                     -1.46                       30.68                       30.25                       27.45
+   29                 192.75000                     -1.53                       30.64                       30.25                       27.43
+   30                 192.80000                     -1.60                       30.60                       30.26                       27.41
+   31                 192.85000                     -1.67                       30.55                       30.26                       27.39
+   32                 192.90000                     -1.74                       30.51                       30.26                       27.37
+   33                 192.95000                     -1.81                       30.47                       30.27                       27.35
+   34                 193.00000                     -1.89                       30.42                       30.27                       27.33
+   35                 193.05000                     -1.95                       30.38                       30.27                       27.32
+   36                 193.10000                     -2.02                       30.34                       30.28                       27.30
+   37                 193.15000                     -2.09                       30.29                       30.28                       27.28
+   38                 193.20000                     -2.16                       30.25                       30.29                       27.26
+   39                 193.25000                     -2.23                       30.20                       30.31                       27.24
+   40                 193.30000                     -2.30                       30.16                       30.32                       27.23
+   41                 193.35000                     -2.37                       30.11                       30.33                       27.21
+   42                 193.40000                     -2.44                       30.07                       30.35                       27.20
+   43                 193.45000                     -2.51                       30.02                       30.36                       27.18
+   44                 193.50000                     -2.58                       29.98                       30.37                       27.16
+   45                 193.55000                     -2.65                       29.93                       30.39                       27.14
+   46                 193.60000                     -2.72                       29.88                       30.40                       27.12
+   47                 193.65000                     -2.80                       29.83                       30.41                       27.10
+   48                 193.70000                     -2.87                       29.79                       30.43                       27.08
+   49                 193.75000                     -2.94                       29.74                       30.44                       27.06
+   50                 193.80000                     -3.02                       29.69                       30.45                       27.04
+   51                 193.85000                     -3.09                       29.64                       30.47                       27.02
+   52                 193.90000                     -3.16                       29.59                       30.48                       27.00
+   53                 193.95000                     -3.24                       29.54                       30.50                       26.98
+   54                 194.00000                     -3.31                       29.49                       30.51                       26.96
+   55                 194.05000                     -3.38                       29.44                       30.52                       26.94
+   56                 194.10000                     -3.46                       29.39                       30.54                       26.91
+   57                 194.15000                     -3.53                       29.33                       30.59                       26.91
+   58                 194.20000                     -3.61                       29.28                       30.64                       26.90
+   59                 194.25000                     -3.68                       29.23                       30.70                       26.89
+   60                 194.30000                     -3.76                       29.18                       30.75                       26.89
+   61                 194.35000                     -3.83                       29.13                       30.81                       26.88
+   62                 194.40000                     -3.91                       29.07                       30.87                       26.87
+   63                 194.45000                     -3.98                       29.02                       30.93                       26.86
+   64                 194.50000                     -4.05                       28.97                       30.98                       26.85
+   65                 194.55000                     -4.12                       28.92                       31.04                       26.84
+   66                 194.60000                     -4.19                       28.87                       31.10                       26.84
+   67                 194.65000                     -4.26                       28.82                       31.17                       26.83
+   68                 194.70000                     -4.32                       28.77                       31.23                       26.82
+   69                 194.75000                     -4.39                       28.72                       31.29                       26.81
+   70                 194.80000                     -4.46                       28.68                       31.35                       26.80
+   71                 194.85000                     -4.52                       28.63                       31.42                       26.79
+   72                 194.90000                     -4.59                       28.58                       31.48                       26.78
+   73                 194.95000                     -4.66                       28.53                       31.55                       26.77
+   74                 195.00000                     -4.72                       28.48                       31.62                       26.76
+   75                 195.05000                     -4.79                       28.43                       31.69                       26.75
+   76                 195.10000                     -4.86                       28.38                       31.69                       26.71
 
 (No source node specified: picked Site_A)
 

tests/invocation/transmission_main_example_long

@@ -1,12 +1,18 @@
-There are 96 channels propagating
 Power mode is set to True
 => it can be modified in eqpt_config.json - Span
 
 There are 15 fiber spans over 1200 km between Site_A and Site_B
 
 Now propagating between Site_A and Site_B:
+Reference used for design: (Input optical power reference in span = 0.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 96)
 
-Propagating with input power = 0.00 dBm:
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 0.00dBm,
+                       nb_channels = 96)
+Input optical power reference in span = 0.00 dBm:
 Transceiver Site_A
   GSNR (0.1nm, dB):          100.00
   GSNR (signal bw, dB):      95.92
@@ -16,14 +22,18 @@ Transceiver Site_A
   PMD (ps):                  0.00
   PDL (dB):                  0.00
   Latency (ms):              0.00
+  Actual pch out (dBm):      0.00
 Roadm roadm Site A
-  effective loss (dB):     20.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        20.00
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa booster A
   type_variety:           std_medium_gain
   effective gain(dB):     20.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      6.58
   (including att_in)
   pad att_in (dB):        0.00
@@ -31,7 +41,6 @@ Edfa booster A
   Power Out (dBm):        19.83
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.01
   output VOA (dB):        0.00
 Fiber          Span1
@@ -47,6 +56,7 @@ Edfa Edfa1
   type_variety:           test
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.86
   (including att_in)
   pad att_in (dB):        0.00
@@ -54,7 +64,6 @@ Edfa Edfa1
   Power Out (dBm):        19.84
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.02
   output VOA (dB):        0.00
 Fiber          Span2
@@ -70,6 +79,7 @@ Edfa Edfa2
   type_variety:           test_fixed_gain
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      9.00
   (including att_in)
   pad att_in (dB):        4.00
@@ -77,7 +87,6 @@ Edfa Edfa2
   Power Out (dBm):        19.85
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.03
   output VOA (dB):        0.00
 Fiber          Span3
@@ -93,6 +102,7 @@ Edfa Edfa3
   type_variety:           test
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.86
   (including att_in)
   pad att_in (dB):        0.00
@@ -100,7 +110,6 @@ Edfa Edfa3
   Power Out (dBm):        19.86
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.04
   output VOA (dB):        0.00
 Fiber          Span4
@@ -116,6 +125,7 @@ Edfa Edfa4
   type_variety:           test_fixed_gain
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      9.00
   (including att_in)
   pad att_in (dB):        4.00
@@ -123,7 +133,6 @@ Edfa Edfa4
   Power Out (dBm):        19.87
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.05
   output VOA (dB):        0.00
 Fiber          Span5
@@ -139,6 +148,7 @@ Edfa Edfa5
   type_variety:           test
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.86
   (including att_in)
   pad att_in (dB):        0.00
@@ -146,17 +156,19 @@ Edfa Edfa5
   Power Out (dBm):        19.88
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.06
   output VOA (dB):        0.00
 Roadm roadm Site C
-  effective loss (dB):     20.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        20.06
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa booster C
   type_variety:           std_medium_gain
   effective gain(dB):     20.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      6.58
   (including att_in)
   pad att_in (dB):        0.00
@@ -164,7 +176,6 @@ Edfa booster C
   Power Out (dBm):        19.83
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.01
   output VOA (dB):        0.00
 Fiber          Span6
@@ -180,6 +191,7 @@ Edfa Edfa6
   type_variety:           test_fixed_gain
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      9.00
   (including att_in)
   pad att_in (dB):        4.00
@@ -187,7 +199,6 @@ Edfa Edfa6
   Power Out (dBm):        19.84
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.02
   output VOA (dB):        0.00
 Fiber          Span7
@@ -203,6 +214,7 @@ Edfa Edfa7
   type_variety:           test
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.86
   (including att_in)
   pad att_in (dB):        0.00
@@ -210,7 +222,6 @@ Edfa Edfa7
   Power Out (dBm):        19.85
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.03
   output VOA (dB):        0.00
 Fiber          Span8
@@ -226,6 +237,7 @@ Edfa Edfa8
   type_variety:           test_fixed_gain
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      9.00
   (including att_in)
   pad att_in (dB):        4.00
@@ -233,7 +245,6 @@ Edfa Edfa8
   Power Out (dBm):        19.86
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.04
   output VOA (dB):        0.00
 Fiber          Span9
@@ -249,6 +260,7 @@ Edfa Edfa9
   type_variety:           test
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.86
   (including att_in)
   pad att_in (dB):        0.00
@@ -256,7 +268,6 @@ Edfa Edfa9
   Power Out (dBm):        19.87
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.05
   output VOA (dB):        0.00
 Fiber          Span10
@@ -272,6 +283,7 @@ Edfa Edfa10
   type_variety:           test_fixed_gain
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      9.00
   (including att_in)
   pad att_in (dB):        4.00
@@ -279,17 +291,19 @@ Edfa Edfa10
   Power Out (dBm):        19.88
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.06
   output VOA (dB):        0.00
 Roadm roadm Site D
-  effective loss (dB):     20.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        20.06
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa booster D
   type_variety:           std_medium_gain
   effective gain(dB):     20.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      6.58
   (including att_in)
   pad att_in (dB):        0.00
@@ -297,7 +311,6 @@ Edfa booster D
   Power Out (dBm):        19.83
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.01
   output VOA (dB):        0.00
 Fiber          Span11
@@ -313,6 +326,7 @@ Edfa Edfa11
   type_variety:           test
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.86
   (including att_in)
   pad att_in (dB):        0.00
@@ -320,7 +334,6 @@ Edfa Edfa11
   Power Out (dBm):        19.84
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.02
   output VOA (dB):        0.00
 Fiber          Span12
@@ -336,6 +349,7 @@ Edfa Edfa12
   type_variety:           test_fixed_gain
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      9.00
   (including att_in)
   pad att_in (dB):        4.00
@@ -343,17 +357,19 @@ Edfa Edfa12
   Power Out (dBm):        19.85
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.03
   output VOA (dB):        0.00
 Roadm roadm Site E
-  effective loss (dB):     20.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        20.03
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa booster E
   type_variety:           std_medium_gain
   effective gain(dB):     20.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      6.58
   (including att_in)
   pad att_in (dB):        0.00
@@ -361,7 +377,6 @@ Edfa booster E
   Power Out (dBm):        19.83
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.01
   output VOA (dB):        0.00
 Fiber          Span13
@@ -377,6 +392,7 @@ Edfa Edfa13
   type_variety:           test
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.86
   (including att_in)
   pad att_in (dB):        0.00
@@ -384,7 +400,6 @@ Edfa Edfa13
   Power Out (dBm):        19.84
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.02
   output VOA (dB):        0.00
 Fiber          Span14
@@ -400,6 +415,7 @@ Edfa Edfa14
   type_variety:           test_fixed_gain
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      9.00
   (including att_in)
   pad att_in (dB):        4.00
@@ -407,7 +423,6 @@ Edfa Edfa14
   Power Out (dBm):        19.85
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.03
   output VOA (dB):        0.00
 Fiber          Span15
@@ -423,6 +438,7 @@ Edfa Edfa15
   type_variety:           test
   effective gain(dB):     16.00
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      8.86
   (including att_in)
   pad att_in (dB):        0.00
@@ -430,13 +446,14 @@ Edfa Edfa15
   Power Out (dBm):        19.86
   Delta_P (dB):           0.00
   target pch (dBm):       0.00
-  effective pch (dBm):    0.00
   actual pch out (dBm):   0.04
   output VOA (dB):        0.00
 Roadm roadm Site B
-  effective loss (dB):     20.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     20.00
+  Actual loss (dB):        20.04
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Transceiver Site_B
   GSNR (0.1nm, dB):          17.84
   GSNR (signal bw, dB):      13.76
@@ -446,8 +463,9 @@ Transceiver Site_B
   PMD (ps):                  1.39
   PDL (dB):                  0.00
   Latency (ms):              5.88
+  Actual pch out (dBm):      0.00
 
-Transmission result for input power = 0.00 dBm:
+Transmission result for input optical power reference in span = 0.00 dBm:
   Final GSNR (0.1 nm): 17.84 dB
 
 (No source node specified: picked Site_A)

tests/invocation/transmission_saturated

@@ -1,12 +1,18 @@
-There are 96 channels propagating
 Power mode is set to True
 => it can be modified in eqpt_config.json - Span
 
 There are 3 fiber spans over 130 km between trx Lannion_CAS and trx Lorient_KMA
 
 Now propagating between trx Lannion_CAS and trx Lorient_KMA:
+Reference used for design: (Input optical power reference in span = 3.00dBm,
+                            spacing = 50.00GHz
+                            nb_channels = 96)
 
-Propagating with input power = 3.00 dBm:
+Channels propagating: (Input optical power deviation in span = 0.00dB,
+                       spacing = 50.00GHz,
+                       transceiver output power = 3.00dBm,
+                       nb_channels = 96)
+Input optical power reference in span = 3.00 dBm:
 Transceiver trx Lannion_CAS
   GSNR (0.1nm, dB):          100.00
   GSNR (signal bw, dB):      95.92
@@ -16,22 +22,25 @@ Transceiver trx Lannion_CAS
   PMD (ps):                  0.00
   PDL (dB):                  0.00
   Latency (ms):              0.00
+  Actual pch out (dBm):      3.00
 Roadm roadm Lannion_CAS
-  effective loss (dB):     23.00
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     23.00
+  Actual loss (dB):        23.00
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Edfa east edfa in Lannion_CAS to Corlay
   type_variety:           test
   effective gain(dB):     21.18
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      6.13
   (including att_in)
   pad att_in (dB):        0.00
   Power In (dBm):         -0.18
   Power Out (dBm):        21.01
-  Delta_P (dB):           0.00
-  target pch (dBm):       3.00
-  effective pch (dBm):    1.18
+  Delta_P (dB):           -1.82
+  target pch (dBm):       1.18
   actual pch out (dBm):   1.18
   output VOA (dB):        0.00
 Fiber          fiber (Lannion_CAS → Corlay)-F061
@@ -66,35 +75,38 @@ Fiber          fiber (Loudeac → Lorient_KMA)-F054
   reference pch out (dBm):     -26.82
   actual pch out (dBm):        -26.81
 Edfa west edfa in Lorient_KMA to Loudeac
-  type_variety:           test
+  type_variety:           std_medium_gain
   effective gain(dB):     27.99
   (before att_in and before output VOA)
-  noise figure (dB):      5.76
+  tilt-target(dB)         0.00
+  noise figure (dB):      5.98
   (including att_in)
   pad att_in (dB):        0.00
   Power In (dBm):         -6.99
   Power Out (dBm):        21.03
   Delta_P (dB):           -1.82
   target pch (dBm):       1.18
-  effective pch (dBm):    1.17
   actual pch out (dBm):   1.21
   output VOA (dB):        0.00
 Roadm roadm Lorient_KMA
-  effective loss (dB):     21.17
-  reference pch out (dBm): -20.00
-  actual pch out (dBm):    -20.00
+  Type_variety:            default
+  Reference loss (dB):     21.18
+  Actual loss (dB):        21.21
+  Reference pch out (dBm): -20.00
+  Actual pch out (dBm):    -20.00
 Transceiver trx Lorient_KMA
-  GSNR (0.1nm, dB):          23.93
-  GSNR (signal bw, dB):      19.85
-  OSNR ASE (0.1nm, dB):      24.29
-  OSNR ASE (signal bw, dB):  20.20
+  GSNR (0.1nm, dB):          23.77
+  GSNR (signal bw, dB):      19.69
+  OSNR ASE (0.1nm, dB):      24.11
+  OSNR ASE (signal bw, dB):  20.03
   CD (ps/nm):                2171.00
   PMD (ps):                  0.46
   PDL (dB):                  0.00
   Latency (ms):              0.64
+  Actual pch out (dBm):      3.00
 
-Transmission result for input power = 3.00 dBm:
-  Final GSNR (0.1 nm): 23.93 dB
+Transmission result for input optical power reference in span = 3.00 dBm:
+  Final GSNR (0.1 nm): 23.77 dB
 
 (Invalid source node 'lannion' replaced with trx Lannion_CAS)
 

tests/requirements.txt

@@ -1,7 +0,0 @@
-build>=1.0.3,<2
-pytest>=7.4.3,<8
-# pandas 2.1 removed support for Python 3.8
-pandas>=2.0.3,<3
-
-# flake v6 killed the --diff option
-flake8>=5.0.4,<6

tests/test_amplifier.py

@@ -4,11 +4,12 @@
 # @Date:   2018-02-02 14:06:55
 
 from numpy import zeros, array
-from gnpy.core.elements import Transceiver, Edfa
-from gnpy.core.utils import automatic_fmax, lin2db, db2lin, merge_amplifier_restrictions
-from gnpy.core.info import create_input_spectral_information, ReferenceCarrier
-from gnpy.core.network import build_network
-from gnpy.tools.json_io import load_network, load_equipment
+from numpy.testing import assert_allclose
+from gnpy.core.elements import Transceiver, Edfa, Fiber
+from gnpy.core.utils import automatic_fmax, lin2db, db2lin, merge_amplifier_restrictions, dbm2watt, watt2dbm
+from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information
+from gnpy.core.network import build_network, set_amplifier_voa
+from gnpy.tools.json_io import load_network, load_equipment, load_json, _equipment_from_json, network_from_json
 from pathlib import Path
 import pytest
 
@@ -73,9 +74,8 @@ def si(nch_and_spacing, bw):
     nb_channel, spacing = nch_and_spacing
     f_min = 191.3e12
     f_max = automatic_fmax(f_min, spacing, nb_channel)
-    return create_input_spectral_information(f_min=f_min, f_max=f_max, roll_off=0.15, baud_rate=bw, power=1e-3,
-                                             spacing=spacing, tx_osnr=40.0,
-                                             ref_carrier=ReferenceCarrier(baud_rate=32e9, slot_width=50e9))
+    return create_input_spectral_information(f_min=f_min, f_max=f_max, roll_off=0.15, baud_rate=bw,
+                                             spacing=spacing, tx_osnr=40.0, tx_power=1e-3)
 
 
 @pytest.mark.parametrize("gain, nf_expected", [(10, 15), (15, 10), (25, 5.8)])
@@ -86,7 +86,7 @@ def test_variable_gain_nf(gain, nf_expected, setup_edfa_variable_gain, si):
     si.nli /= db2lin(gain)
     si.ase /= db2lin(gain)
     edfa.operational.gain_target = gain
-    si.pref = si.pref._replace(p_span0=0, p_spani=-gain)
+    edfa.effective_gain = gain
     edfa.interpol_params(si)
     result = edfa.nf
     assert pytest.approx(nf_expected, abs=0.01) == result[0]
@@ -100,7 +100,7 @@ def test_fixed_gain_nf(gain, nf_expected, setup_edfa_fixed_gain, si):
     si.nli /= db2lin(gain)
     si.ase /= db2lin(gain)
     edfa.operational.gain_target = gain
-    si.pref = si.pref._replace(p_span0=0, p_spani=-gain)
+    edfa.effective_gain = gain
     edfa.interpol_params(si)
     assert pytest.approx(nf_expected, abs=0.01) == edfa.nf[0]
 
@@ -124,8 +124,8 @@ def test_compare_nf_models(gain, setup_edfa_variable_gain, si):
     si.nli /= db2lin(gain)
     si.ase /= db2lin(gain)
     edfa.operational.gain_target = gain
+    edfa.effective_gain = gain
     # edfa is variable gain type
-    si.pref = si.pref._replace(p_span0=0, p_spani=-gain)
     edfa.interpol_params(si)
     nf_model = edfa.nf[0]
 
@@ -180,7 +180,6 @@ def test_ase_noise(gain, si, setup_trx, bw):
     si = span(si)
     print(span)
 
-    si.pref = si.pref._replace(p_span0=0, p_spani=-gain)
     edfa.interpol_params(si)
     nf = edfa.nf
     print('nf', nf)
@@ -196,3 +195,313 @@ def test_ase_noise(gain, si, setup_trx, bw):
     si = trx(si)
     osnr = trx.osnr_ase_01nm[0]
     assert pytest.approx(osnr_expected, abs=0.01) == osnr
+
+
+@pytest.mark.parametrize('delta_p', [0, None, 2])
+@pytest.mark.parametrize('tilt_target', [0, -4])
+def test_amp_behaviour(tilt_target, delta_p):
+    """Check that amp correctly applies saturation, when there is tilt
+    """
+    json_data = {
+        "elements": [{
+            "uid": "Edfa1",
+            "type": "Edfa",
+            "type_variety": "test",
+            "operational": {
+                "delta_p": delta_p,
+                "gain_target": 20 + delta_p if delta_p else 20,
+                "tilt_target": tilt_target,
+                "out_voa": 0
+            }
+        }, {
+            "uid": "Span1",
+            "type": "Fiber",
+            "type_variety": "SSMF",
+            "params": {
+                "length": 100,
+                "loss_coef": 0.2,
+                "length_units": "km"
+            }
+        }],
+        "connections": []
+    }
+    equipment = load_equipment(eqpt_library)
+    network = network_from_json(json_data, equipment)
+    edfa = [n for n in network.nodes() if isinstance(n, Edfa)][0]
+    fiber = [n for n in network.nodes() if isinstance(n, Fiber)][0]
+    fiber.params.con_in = 0
+    fiber.params.con_out = 0
+    fiber.ref_pch_in_dbm = 0.0
+    si = create_input_spectral_information(f_min=191.3e12, f_max=196.05e12, roll_off=0.15, baud_rate=64e9,
+                                           spacing=75e9, tx_osnr=None, tx_power=1e-3)
+    si = fiber(si)
+    total_sig_powerin = sum(si.signal)
+    sig_in = lin2db(si.signal)
+    si = edfa(si)
+    sig_out = lin2db(si.signal)
+    total_sig_powerout = sum(si.signal)
+    gain = lin2db(total_sig_powerout / total_sig_powerin)
+    expected_total_power_out = total_sig_powerin * 100 * db2lin(delta_p) if delta_p else total_sig_powerin * 100
+    assert pytest.approx(total_sig_powerout, abs=1e-6) == min(expected_total_power_out, dbm2watt(21))
+    assert pytest.approx(edfa.effective_gain, 1e-5) == gain
+    assert watt2dbm(sum(si.signal + si.nli + si.ase)) <= 21.01
+    # If there is no tilt on the amp: the gain is identical for all carriers
+    if tilt_target == 0:
+        assert_allclose(sig_in + gain, sig_out, rtol=1e-13)
+    else:
+        if delta_p != 2:
+            expected_sig_out = [
+                -31.95025022, -31.88168886, -31.81178634, -31.73838831, -31.66318631,
+                -31.58762141, -31.51156294, -31.43760161, -31.38124626, -31.34245197,
+                -31.30629475, -31.26970711, -31.22566555, -31.17412914, -31.11806869,
+                -31.05122228, -30.97358131, -30.90658619, -30.86616148, -30.83854197,
+                -30.81115028, -30.78403337, -30.7570206, -30.73002834, -30.70088634,
+                -30.66844432, -30.63427939, -30.59364514, -30.54659009, -30.49180643,
+                -30.41406352, -30.31434813, -30.22984104, -30.18249387, -30.1516453,
+                -30.12082034, -30.08970494, -30.05779424, -30.02543415, -29.99309889,
+                -29.96078803, -29.92798594, -29.89002127, -29.84689015, -29.79726968,
+                -29.72927112, -29.64485972, -29.55578693, -29.45569694, -29.35111795,
+                -29.24662471, -29.12148491, -28.94244964, -28.73421833, -28.53930479,
+                -28.36231261, -28.19361236, -28.04376778, -27.91280403, -27.79433658,
+                -27.7065072, -27.64495288, -27.59798975]
+
+        else:
+            expected_sig_out = [
+                -29.95025022, -29.88168886, -29.81178634, -29.73838831, -29.66318631,
+                -29.58762141, -29.51156294, -29.43760161, -29.38124626, -29.34245197,
+                -29.30629475, -29.26970711, -29.22566555, -29.17412914, -29.11806869,
+                -29.05122228, -28.97358131, -28.90658619, -28.86616148, -28.83854197,
+                -28.81115028, -28.78403337, -28.7570206, -28.73002834, -28.70088634,
+                -28.66844432, -28.63427939, -28.59364514, -28.54659009, -28.49180643,
+                -28.41406352, -28.31434813, -28.22984104, -28.18249387, -28.1516453,
+                -28.12082034, -28.08970494, -28.05779424, -28.02543415, -27.99309889,
+                -27.96078803, -27.92798594, -27.89002127, -27.84689015, -27.79726968,
+                -27.72927112, -27.64485972, -27.55578693, -27.45569694, -27.35111795,
+                -27.24662471, -27.12148491, -26.94244964, -26.73421833, -26.53930479,
+                -26.36231261, -26.19361236, -26.04376778, -25.91280403, -25.79433658,
+                -25.7065072, -25.64495288, -25.59798975]
+
+        print(sig_out)
+        assert_allclose(sig_out, expected_sig_out, rtol=1e-9)
+
+
+@pytest.mark.parametrize('delta_p', [0, None, 20])
+@pytest.mark.parametrize('base_power', [0, 20])
+@pytest.mark.parametrize('delta_pdb_per_channel',
+                         [[0, 1, 3, 0.5, -2],
+                          [0, 0, 0, 0, 0],
+                          [-2, -2, -2, -2, -2],
+                          [0, 2, -2, -5, 4],
+                          [0, 1, 3, 0.5, -2], ])
+def test_amp_saturation(delta_pdb_per_channel, base_power, delta_p):
+    """Check that amp correctly applies saturation
+    """
+    json_data = {
+        "elements": [{
+            "uid": "Edfa1",
+            "type": "Edfa",
+            "type_variety": "test",
+            "operational": {
+                "delta_p": delta_p,
+                "gain_target": 20,
+                "tilt_target": 0,
+                "out_voa": 0
+            }
+        }],
+        "connections": []
+    }
+    equipment = load_equipment(eqpt_library)
+    network = network_from_json(json_data, equipment)
+    edfa = [n for n in network.nodes()][0]
+    frequency = 193e12 + array([0, 50e9, 150e9, 225e9, 275e9])
+    slot_width = array([37.5e9, 50e9, 75e9, 50e9, 37.5e9])
+    baud_rate = array([32e9, 42e9, 64e9, 42e9, 32e9])
+    signal = dbm2watt(array([-20.0, -18.0, -22.0, -25.0, -16.0]) + array(delta_pdb_per_channel) + base_power)
+    si = create_arbitrary_spectral_information(frequency=frequency, slot_width=slot_width,
+                                               signal=signal, baud_rate=baud_rate, roll_off=0.15,
+                                               delta_pdb_per_channel=delta_pdb_per_channel,
+                                               tx_osnr=None, tx_power=None)
+    total_sig_powerin = sum(si.signal)
+    sig_in = lin2db(si.signal)
+    si = edfa(si)
+    sig_out = lin2db(si.signal)
+    total_sig_powerout = sum(si.signal)
+    gain = lin2db(total_sig_powerout / total_sig_powerin)
+    assert watt2dbm(sum(si.signal + si.nli + si.ase)) <= 21.02
+    assert pytest.approx(edfa.effective_gain, 1e-13) == gain
+    assert_allclose(sig_in + gain, sig_out, rtol=1e-13)
+
+
+def test_set_out_voa():
+    """Check that out_voa is correctly set if out_voa_auto is true
+    gain is maximized to obtain better NF:
+    if optimum input power in next span is -3 + pref_ch_db then total power at optimum is 19 -3 = 16dBm.
+    since amp has 21 dBm p_max, power out of amp can be set to 21dBm increasing out_voa by 5 to keep
+    same input power in the fiber. Since the optimisation contains a hard coded margin of 1 to account for
+    possible degradation on max power, the expected voa value is 4, and delta_p and gain are corrected
+    accordingly.
+    """
+    json_data = {
+        "elements": [{
+            "uid": "Edfa1",
+            "type": "Edfa",
+            "type_variety": "test",
+            "operational": {
+                "delta_p": -3,
+                "gain_target": 20,
+                "tilt_target": 0
+            }
+        }],
+        "connections": []
+    }
+    equipment = load_equipment(eqpt_library)
+    network = network_from_json(json_data, equipment)
+    amp = [n for n in network.nodes()][0]
+    print(amp.out_voa)
+    power_target = 19 + amp.delta_p
+    power_mode = True
+    amp.params.out_voa_auto = True
+    set_amplifier_voa(amp, power_target, power_mode)
+    assert amp.out_voa == 4.0
+    assert amp.effective_gain == 20.0 + 4.0
+    assert amp.delta_p == -3.0 + 4.0
+
+
+def test_multiband():
+
+    equipment_json = load_json(eqpt_library)
+    # add some multiband amplifiers
+    amps = [
+        {
+            "type_variety": "std_medium_gain_C",
+            "f_min": 191.25e12,
+            "f_max": 196.15e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": False,
+            "allowed_for_design": True},
+        {
+            "type_variety": "std_medium_gain_L",
+            "f_min": 186.55e12,
+            "f_max": 190.05e12,
+            "type_def": "variable_gain",
+            "gain_flatmax": 26,
+            "gain_min": 15,
+            "p_max": 21,
+            "nf_min": 6,
+            "nf_max": 10,
+            "out_voa_auto": False,
+            "allowed_for_design": True},
+        {
+            "type_variety": "std_medium_gain_multiband",
+            "type_def": "multi_band",
+            "amplifiers": [
+                "std_medium_gain_C",
+                "std_medium_gain_L"
+            ],
+            "allowed_for_design": False
+        }
+    ]
+    equipment_json['Edfa'].extend(amps)
+
+    equipment = _equipment_from_json(equipment_json, eqpt_library)
+
+    el_config = {
+        "uid": "Edfa1",
+        "type": "Multiband_amplifier",
+        "type_variety": "std_medium_gain_multiband",
+        "amplifiers": [
+            {
+                "type_variety": "std_medium_gain_C",
+                "operational": {
+                    "gain_target": 22.55,
+                    "delta_p": 0.9,
+                    "out_voa": 3.0,
+                    "tilt_target": 0.0,
+                }
+            },
+            {
+                "type_variety": "std_medium_gain_L",
+                "operational": {
+                    "gain_target": 21,
+                    "delta_p": 3.0,
+                    "out_voa": 3.0,
+                    "tilt_target": 0.0,
+                }
+            }
+        ]
+    }
+    fused_config = {
+        "uid": "[83/WR-2-4-SIG=>930/WRT-1-2-SIG]-Tl/9300",
+        "type": "Fused",
+        "params": {
+            "loss": 20
+        }
+    }
+    json_data = {
+        "elements": [
+            el_config,
+            fused_config
+        ],
+        "connections": []
+    }
+    network = network_from_json(json_data, equipment)
+    amp = next(n for n in network.nodes() if n.uid == 'Edfa1')
+    fused = next(n for n in network.nodes() if n.uid == '[83/WR-2-4-SIG=>930/WRT-1-2-SIG]-Tl/9300')
+    si = create_input_spectral_information(f_min=186e12, f_max=196e12, roll_off=0.15, baud_rate=32e9, tx_power=1e-3,
+                                           spacing=50e9, tx_osnr=40.0)
+    assert si.number_of_channels == 200
+    si = fused(si)
+    si = amp(si)
+    # assert nb of channel after mux/demux
+    assert si.number_of_channels == 164    # computed based on amp bands
+    # Check that multiband amp is correctly created with correct __str__
+    actual_c_amp = amp.amplifiers["CBAND"].__str__()
+    expected_c_amp = '\n'.join([
+        'Edfa Edfa1',
+        '  type_variety:           std_medium_gain_C',
+        '  effective gain(dB):     21.22',
+        '  (before att_in and before output VOA)',
+        '  tilt-target(dB)         0.00',
+        '  noise figure (dB):      6.32',
+        '  (including att_in)',
+        '  pad att_in (dB):        0.00',
+        '  Power In (dBm):         -0.22',
+        '  Power Out (dBm):        21.01',
+        '  Delta_P (dB):           0.90',
+        '  target pch (dBm):       None',
+        '  actual pch out (dBm):   -1.77',
+        '  output VOA (dB):        3.00'])
+    assert actual_c_amp == expected_c_amp
+    actual_l_amp = amp.amplifiers["LBAND"].__str__()
+    expected_l_amp = '\n'.join([
+        'Edfa Edfa1',
+        '  type_variety:           std_medium_gain_L',
+        '  effective gain(dB):     21.00',
+        '  (before att_in and before output VOA)',
+        '  tilt-target(dB)         0.00',
+        '  noise figure (dB):      6.36',
+        '  (including att_in)',
+        '  pad att_in (dB):        0.00',
+        '  Power In (dBm):         -1.61',
+        '  Power Out (dBm):        19.40',
+        '  Delta_P (dB):           3.00',
+        '  target pch (dBm):       None',
+        '  actual pch out (dBm):   -1.99',
+        '  output VOA (dB):        3.00'])
+    assert actual_l_amp == expected_l_amp
+
+    # check that f_min, f_max of si are within amp band
+    assert amp.amplifiers["LBAND"].params.f_min == 186.55e12
+    assert si.frequency[0] >= amp.amplifiers["LBAND"].params.f_min
+    assert amp.amplifiers["CBAND"].params.f_max == 196.15e12
+    assert si.frequency[-1] <= amp.amplifiers["CBAND"].params.f_max
+    for freq in si.frequency:
+        if freq > 190.05e12:
+            assert freq >= 191.25e12
+        if freq < 191.25e12:
+            assert freq <= 190.25e12

tests/test_automaticmodefeature.py

@@ -14,12 +14,17 @@ checks that empty info on mode, power, nbchannel in service file are supported
 """
 
 from pathlib import Path
+from logging import INFO
+from numpy.testing import assert_allclose
 import pytest
+
 from gnpy.core.network import build_network
-from gnpy.core.utils import automatic_nch, lin2db
+from gnpy.core.utils import automatic_nch, lin2db, watt2dbm
 from gnpy.core.elements import Roadm
 from gnpy.topology.request import compute_path_dsjctn, propagate, propagate_and_optimize_mode, correct_json_route_list
-from gnpy.tools.json_io import load_network, load_equipment, requests_from_json, load_requests
+from gnpy.tools.json_io import load_network, load_equipment, requests_from_json, load_requests, load_json, \
+    _equipment_from_json
+
 
 network_file_name = Path(__file__).parent.parent / 'tests/data/testTopology_expected.json'
 service_file_name = Path(__file__).parent.parent / 'tests/data/testTopology_testservices.json'
@@ -30,7 +35,9 @@ eqpt_library_name = Path(__file__).parent.parent / 'tests/data/eqpt_config.json'
 @pytest.mark.parametrize("net", [network_file_name])
 @pytest.mark.parametrize("eqpt", [eqpt_library_name])
 @pytest.mark.parametrize("serv", [service_file_name])
-@pytest.mark.parametrize("expected_mode", [['16QAM', 'PS_SP64_1', 'PS_SP64_1', 'PS_SP64_1', 'mode 2 - fake', 'mode 2', 'PS_SP64_1', 'mode 3', 'PS_SP64_1', 'PS_SP64_1', '16QAM', 'mode 1', 'PS_SP64_1', 'PS_SP64_1', 'mode 1', 'mode 2', 'mode 1', 'mode 2', 'nok']])
+@pytest.mark.parametrize("expected_mode", [['16QAM', 'PS_SP64_1', 'PS_SP64_1', 'PS_SP64_1', 'mode 2 - fake', 'mode 2',
+                                            'PS_SP64_1', 'mode 3', 'PS_SP64_1', 'PS_SP64_1', '16QAM', 'mode 1',
+                                            'PS_SP64_1', 'PS_SP64_1', 'mode 1', 'mode 2', 'mode 1', 'mode 2', 'nok']])
 def test_automaticmodefeature(net, eqpt, serv, expected_mode):
     equipment = load_equipment(eqpt)
     network = load_network(net, equipment)
@@ -83,3 +90,89 @@ def test_automaticmodefeature(net, eqpt, serv, expected_mode):
                 path_res_list.append('nok')
     print(path_res_list)
     assert path_res_list == expected_mode
+
+
+def test_propagate_and_optimize_mode(caplog):
+    """Checks that the automatic mode returns the last explored mode
+
+    Mode are explored with descending baud_rate order and descending bitrate, so the last explored mode must be mode 1
+    Mode 1 GSNR is OK but pdl penalty are not OK due to high ROADM PDL. so the last explored mode is not OK
+    Then the propagate_and_optimize_mode must return mode 1 and the blocking reason must be 'NO_FEASIBLE_MODE'
+    """
+    caplog.set_level(INFO)
+    json_data = load_json(eqpt_library_name)
+    voyager = next(e for e in json_data['Transceiver'] if e['type_variety'] == 'Voyager')
+    # expected path min GSNR is 22.11
+    # Change Voyager modes so that:
+    # - highest baud rate has min OSNR > path GSNR
+    # - lower baudrate with highest bitrate has min OSNR > path GSNR
+    # - lower baudrate with lower bitrate has has min OSNR < path GSNR but PDL penalty is infinite
+    voyager['mode'] = [
+        {
+            "format": "mode 1",
+            "baud_rate": 32e9,
+            "OSNR": 12,
+            "bit_rate": 100e9,
+            "roll_off": 0.15,
+            "tx_osnr": 45,
+            "min_spacing": 50e9,
+            "penalties": [
+                {
+                    "chromatic_dispersion": 4e3,
+                    "penalty_value": 0
+                }, {
+                    "chromatic_dispersion": 40e3,
+                    "penalty_value": 0
+                }, {
+                    "pdl": 0.5,
+                    "penalty_value": 1
+                }, {
+                    "pmd": 30,
+                    "penalty_value": 0
+                }],
+            "cost": 1
+        },
+        {
+            "format": "mode 3",
+            "baud_rate": 32e9,
+            "OSNR": 30,
+            "bit_rate": 300e9,
+            "roll_off": 0.15,
+            "tx_osnr": 45,
+            "min_spacing": 50e9,
+            "cost": 1
+        },
+        {
+            "format": "mode 2",
+            "baud_rate": 66e9,
+            "OSNR": 25,
+            "bit_rate": 400e9,
+            "roll_off": 0.15,
+            "tx_osnr": 45,
+            "min_spacing": 75e9,
+            "cost": 1
+        }]
+    # change default ROADM PDL so that crossing 2 ROADMs leasd to inifinte penalty for mode 1
+    eqpt_roadm = next(r for r in json_data['Roadm'] if 'type_variety' not in r)
+    eqpt_roadm['pdl'] = 0.5
+    equipment = _equipment_from_json(json_data, eqpt_library_name)
+    network = load_network(network_file_name, equipment)
+    data = load_requests(filename=Path(__file__).parent.parent / 'tests/data/testTopology_services_expected.json',
+                         eqpt=eqpt_library_name, bidir=False, network=network, network_filename=network_file_name)
+    # remove the mode from request, change it to larger spacing
+    data['path-request'][1]['path-constraints']['te-bandwidth']['trx_mode'] = None
+    data['path-request'][1]['path-constraints']['te-bandwidth']['spacing'] = 75e9
+    assert_allclose(watt2dbm(data['path-request'][1]['path-constraints']['te-bandwidth']['output-power']), 1, rtol=1e-9)
+    # use the request power for design, or there will be inconsistencies with the gain
+    build_network(network, equipment, 1, 21)
+
+    rqs = requests_from_json(data, equipment)
+    rqs = correct_json_route_list(network, rqs)
+    [path] = compute_path_dsjctn(network, equipment, [rqs[1]], [])
+    total_path, mode = propagate_and_optimize_mode(path, rqs[1], equipment)
+    assert round(min(path[-1].snr_01nm), 2) == 22.22
+    assert mode['format'] == 'mode 1'
+    assert rqs[1].blocking_reason == 'NO_FEASIBLE_MODE'
+    expected_mesg = '\tWarning! Request 1: no mode satisfies path SNR requirement.'
+    # Last log records mustcontain the message about the las explored mode
+    assert expected_mesg in caplog.records[-1].message

tests/test_disjunction.py

@@ -119,8 +119,9 @@ def create_rq(equipment, srce, dest, bdir, node_list, loose_list, rqid='test_req
         'nodes_list': node_list,
         'loose_list': loose_list,
         'path_bandwidth': 100.0e9,
-        'power': 1.0,
-        'effective_freq_slot': None,
+        'power': 1.0e-3,
+        'tx_power': 1.0e-3,
+        'effective_freq_slot': None
     }
     params['format'] = params['trx_mode']
     trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
@@ -258,7 +259,8 @@ def request_set():
         'f_min': 191.1e12,
         'f_max': 196.3e12,
         'nb_channel': None,
-        'power': 0,
+        'power': 1e-3,
+        'tx_power': 1e-3,
         'path_bandwidth': 200e9}
 
 

tests/test_equalization.py

@@ -17,13 +17,14 @@ from copy import deepcopy
 from gnpy.core.utils import lin2db, automatic_nch, dbm2watt, power_dbm_to_psd_mw_ghz, watt2dbm, psd2powerdbm
 from gnpy.core.network import build_network
 from gnpy.core.elements import Roadm
-from gnpy.core.info import create_input_spectral_information, Pref, create_arbitrary_spectral_information, \
-    ReferenceCarrier
+from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information, ReferenceCarrier, \
+    carriers_to_spectral_information
 from gnpy.core.equipment import trx_mode_params
 from gnpy.core.exceptions import ConfigurationError
 from gnpy.tools.json_io import network_from_json, load_equipment, load_network, _spectrum_from_json, load_json, \
     Transceiver, requests_from_json
 from gnpy.topology.request import PathRequest, compute_constrained_path, propagate, propagate_and_optimize_mode
+from gnpy.topology.spectrum_assignment import build_oms_list
 
 
 TEST_DIR = Path(__file__).parent
@@ -55,6 +56,7 @@ def test_equalization_combination_degree(delta_pdb_per_channel, degree, equaliza
 
     roadm_config = {
         "uid": "roadm Lannion_CAS",
+        "type_variety": "default",
         "params": {
             "per_degree_pch_out_db": {
                 "east edfa in Lannion_CAS to Corlay": -16
@@ -69,23 +71,27 @@ def test_equalization_combination_degree(delta_pdb_per_channel, degree, equaliza
             "restrictions": {
                 "preamp_variety_list": [],
                 "booster_variety_list": []
-            }
+            },
+            "roadm-path-impairments": [],
+            "design_bands": None
         }
     }
     roadm = Roadm(**roadm_config)
+    roadm.set_roadm_paths(from_degree='tata', to_degree=degree, path_type='express')
+    roadm.ref_pch_in_dbm['tata'] = 0
+    roadm.ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
     frequency = 191e12 + array([0, 50e9, 150e9, 225e9, 275e9])
     slot_width = array([37.5e9, 50e9, 75e9, 50e9, 37.5e9])
     baud_rate = array([32e9, 42e9, 64e9, 42e9, 32e9])
     signal = dbm2watt(array([-20.0, -18.0, -22.0, -25.0, -16.0]))
-    ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
-    pref = Pref(p_span0=0, p_spani=0, ref_carrier=ref_carrier)
     si = create_arbitrary_spectral_information(frequency=frequency, slot_width=slot_width,
                                                signal=signal, baud_rate=baud_rate, roll_off=0.15,
                                                delta_pdb_per_channel=delta_pdb_per_channel,
-                                               tx_osnr=None, ref_power=pref)
+                                               tx_osnr=None)
     to_json_before_propagation = {
         'uid': 'roadm Lannion_CAS',
         'type': 'Roadm',
+        "type_variety": "default",
         'params': {
             equalization_type: target,
             'restrictions': {'preamp_variety_list': [], 'booster_variety_list': []},
@@ -98,7 +104,7 @@ def test_equalization_combination_degree(delta_pdb_per_channel, degree, equaliza
         'metadata': {'location': {'latitude': 0, 'longitude': 0, 'city': None, 'region': None}}
     }
     assert roadm.to_json == to_json_before_propagation
-    si = roadm(si, degree)
+    si = roadm(si, degree=degree, from_degree='tata')
     assert roadm.ref_pch_out_dbm == pytest.approx(expected_pch_out_dbm, rel=1e-4)
     assert_allclose(expected_si, roadm.get_per_degree_power(degree, spectral_info=si), rtol=1e-3)
 
@@ -119,7 +125,8 @@ def test_wrong_element_config(equalization_type):
             "restrictions": {
                 "preamp_variety_list": [],
                 "booster_variety_list": []
-            }
+            },
+            "design_bands": None
         },
         "metadata": {
             "location": {
@@ -215,12 +222,10 @@ def test_low_input_power(target_out, delta_pdb_per_channel, correction):
     baud_rate = array([32e9, 42e9, 64e9, 42e9, 32e9])
     signal = dbm2watt(array([-20.0, -18.0, -22.0, -25.0, -16.0]))
     target = target_out + array(delta_pdb_per_channel)
-    ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
-    pref = Pref(p_span0=0, p_spani=-20, ref_carrier=ref_carrier)
     si = create_arbitrary_spectral_information(frequency=frequency, slot_width=slot_width,
                                                signal=signal, baud_rate=baud_rate, roll_off=0.15,
                                                delta_pdb_per_channel=delta_pdb_per_channel,
-                                               tx_osnr=None, ref_power=pref)
+                                               tx_osnr=None)
     roadm_config = {
         "uid": "roadm Brest_KLA",
         "params": {
@@ -232,7 +237,9 @@ def test_low_input_power(target_out, delta_pdb_per_channel, correction):
             "restrictions": {
                 "preamp_variety_list": [],
                 "booster_variety_list": []
-            }
+            },
+            "roadm-path-impairments": [],
+            "design_bands": None
         },
         "metadata": {
             "location": {
@@ -244,7 +251,10 @@ def test_low_input_power(target_out, delta_pdb_per_channel, correction):
         }
     }
     roadm = Roadm(**roadm_config)
-    si = roadm(si, 'toto')
+    roadm.set_roadm_paths(from_degree='tata', to_degree='toto', path_type='express')
+    roadm.ref_pch_in_dbm['tata'] = 0
+    roadm.ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
+    si = roadm(si, degree='toto', from_degree='tata')
     assert_allclose(watt2dbm(si.signal), target - correction, rtol=1e-5)
     # in other words check that if target is below input power, target is applied else power is unchanged
     assert_allclose((watt2dbm(signal) >= target) * target + (watt2dbm(signal) < target) * watt2dbm(signal),
@@ -267,12 +277,10 @@ def test_2low_input_power(target_out, delta_pdb_per_channel, correction):
     baud_rate = array([32e9, 42e9, 64e9, 42e9, 32e9])
     signal = dbm2watt(array([-20.0, -18.0, -22.0, -25.0, -16.0]))
     target = psd2powerdbm(target_out, baud_rate) + array(delta_pdb_per_channel)
-    ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
-    pref = Pref(p_span0=0, p_spani=-20, ref_carrier=ref_carrier)
     si = create_arbitrary_spectral_information(frequency=frequency, slot_width=slot_width,
                                                signal=signal, baud_rate=baud_rate, roll_off=0.15,
                                                delta_pdb_per_channel=delta_pdb_per_channel,
-                                               tx_osnr=None, ref_power=pref)
+                                               tx_osnr=None)
     roadm_config = {
         "uid": "roadm Brest_KLA",
         "params": {
@@ -284,7 +292,9 @@ def test_2low_input_power(target_out, delta_pdb_per_channel, correction):
             "restrictions": {
                 "preamp_variety_list": [],
                 "booster_variety_list": []
-            }
+            },
+            "roadm-path-impairments": [],
+            "design_bands": None
         },
         "metadata": {
             "location": {
@@ -296,15 +306,18 @@ def test_2low_input_power(target_out, delta_pdb_per_channel, correction):
         }
     }
     roadm = Roadm(**roadm_config)
-    si = roadm(si, 'toto')
+    roadm.set_roadm_paths(from_degree='tata', to_degree='toto', path_type='express')
+    roadm.ref_pch_in_dbm['tata'] = 0
+    roadm.ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
+    si = roadm(si, degree='toto', from_degree='tata')
     assert_allclose(watt2dbm(si.signal), target - correction, rtol=1e-5)
 
 
-def net_setup(equipment):
+def net_setup(equipment, deltap=0):
     """common setup for tests: builds network, equipment and oms only once"""
     network = load_network(NETWORK_FILENAME, equipment)
     spectrum = equipment['SI']['default']
-    p_db = spectrum.power_dbm
+    p_db = spectrum.power_dbm + deltap
     p_total_db = p_db + lin2db(automatic_nch(spectrum.f_min, spectrum.f_max, spectrum.spacing))
     build_network(network, equipment, p_db, p_total_db)
     return network
@@ -323,10 +336,11 @@ def create_voyager_req(equipment, source, dest, bidir, nodes_list, loose_list, m
               'nodes_list': nodes_list,
               'loose_list': loose_list,
               'path_bandwidth': 100.0e9,
-              'effective_freq_slot': None}
+              'effective_freq_slot': None,
+              'power': 1e-3,
+              'tx_power': 1e-3}
     trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
     params.update(trx_params)
-    params['power'] = dbm2watt(power_dbm) if power_dbm else dbm2watt(equipment['SI']['default'].power_dbm)
     f_min = params['f_min']
     f_max_from_si = params['f_max']
     params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing'])
@@ -361,9 +375,9 @@ def test_initial_spectrum(mode, slot_width, power_dbm):
     assert_array_equal(infos_expected.frequency, infos_actual.frequency)
     assert_array_equal(infos_expected.baud_rate, infos_actual.baud_rate)
     assert_array_equal(infos_expected.slot_width, infos_actual.slot_width)
-    assert_array_equal(infos_expected.signal, infos_actual.signal)
-    assert_array_equal(infos_expected.nli, infos_actual.nli)
-    assert_array_equal(infos_expected.ase, infos_actual.ase)
+    assert_allclose(infos_expected.signal, infos_actual.signal, rtol=1e-10)
+    assert_allclose(infos_expected.nli, infos_actual.nli, rtol=1e-10)
+    assert_allclose(infos_expected.ase, infos_actual.ase, rtol=1e-10)
     assert_array_equal(infos_expected.roll_off, infos_actual.roll_off)
     assert_array_equal(infos_expected.chromatic_dispersion, infos_actual.chromatic_dispersion)
     assert_array_equal(infos_expected.pmd, infos_actual.pmd)
@@ -447,14 +461,14 @@ def ref_network():
     return network
 
 
-@pytest.mark.parametrize('deltap', [0, +1.2, -0.5])
+@pytest.mark.parametrize('deltap', [0, +1.18, -0.5])
 def test_target_psd_out_mwperghz_deltap(deltap):
     """checks that if target_psd_out_mWperGHz is defined, delta_p of amps is correctly updated
 
-    Power over 1.2dBm saturate amp with this test: TODO add a test on this saturation
+    Power over 1.18dBm saturate amp with this test: TODO add a test on this saturation
     """
     equipment = load_equipment(EQPT_FILENAME)
-    network = net_setup(equipment)
+    network = net_setup(equipment, deltap)
     req = create_voyager_req(equipment, 'trx Brest_KLA', 'trx Vannes_KBE', False, ['trx Vannes_KBE'], ['STRICT'],
                              'mode 1', 50e9, deltap)
     temp = [{
@@ -508,7 +522,6 @@ def test_equalization(case, deltap, target, mode, slot_width, equalization):
     # boosters = ['east edfa in Brest_KLA to Quimper', 'east edfa in Lorient_KMA to Loudeac',
     #             'east edfa in Lannion_CAS to Stbrieuc']
     target_psd = power_dbm_to_psd_mw_ghz(target, 32e9)
-    ref = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
     if case == 'SI':
         delattr(equipment['Roadm']['default'], 'target_pch_out_db')
         setattr(equipment['Roadm']['default'], equalization, target_psd)
@@ -533,11 +546,11 @@ def test_equalization(case, deltap, target, mode, slot_width, equalization):
             assert getattr(roadm, equalization) == target_psd
     path = compute_constrained_path(network, req)
     si = create_input_spectral_information(
-        f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate, power=req.power,
-        spacing=req.spacing, tx_osnr=req.tx_osnr, ref_carrier=ref)
+        f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
+        spacing=req.spacing, tx_osnr=req.tx_osnr, tx_power=req.power)
     for i, el in enumerate(path):
         if isinstance(el, Roadm):
-            si = el(si, degree=path[i + 1].uid)
+            si = el(si, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
             if case in ['SI', 'nodes', 'degrees']:
                 if equalization == 'target_psd_out_mWperGHz':
                     assert_allclose(power_dbm_to_psd_mw_ghz(watt2dbm(si.signal + si.ase + si.nli), si.baud_rate),
@@ -577,9 +590,9 @@ def test_power_option(req_power):
     infos_actual = propagate(path2, req, equipment)
     assert_array_equal(infos_expected.baud_rate, infos_actual.baud_rate)
     assert_array_equal(infos_expected.slot_width, infos_actual.slot_width)
-    assert_array_equal(infos_expected.signal, infos_actual.signal)
-    assert_array_equal(infos_expected.nli, infos_actual.nli)
-    assert_array_equal(infos_expected.ase, infos_actual.ase)
+    assert_allclose(infos_expected.signal, infos_actual.signal, rtol=1e-10)
+    assert_allclose(infos_expected.nli, infos_actual.nli, rtol=1e-10)
+    assert_allclose(infos_expected.ase, infos_actual.ase, rtol=1e-10)
     assert_array_equal(infos_expected.roll_off, infos_actual.roll_off)
     assert_array_equal(infos_expected.chromatic_dispersion, infos_actual.chromatic_dispersion)
     assert_array_equal(infos_expected.pmd, infos_actual.pmd)
@@ -835,3 +848,103 @@ def test_power_offset_automatic_mode_selection(slot_width, value, equalization,
     _, mode = propagate_and_optimize_mode(path, free_req, equipment)
     assert mode['format'] == expected_mode
     assert_allclose(path_expected[-1].snr_01nm, path[-1].snr_01nm, rtol=1e-5)
+
+
+@pytest.mark.parametrize('tx_power_dbm', [-10, -8, 0, 10])
+def test_tx_power(tx_power_dbm):
+    """If carrier add power is below equalization target + ROADM add max loss, then equalizatio
+    can not be applied.
+    """
+    json_data = load_json(NETWORK_FILENAME)
+    for el in json_data['elements']:
+        if el['uid'] == 'roadm Lannion_CAS':
+            el['type_variety'] = 'example_detailed_impairments'
+    equipment = load_equipment(EQPT_FILENAME)
+    network = network_from_json(json_data, equipment)
+    default_spectrum = equipment['SI']['default']
+    p_db = default_spectrum.power_dbm
+    p_total_db = p_db + lin2db(automatic_nch(default_spectrum.f_min, default_spectrum.f_max, default_spectrum.spacing))
+    build_network(network, equipment, p_db, p_total_db)
+    build_oms_list(network, equipment)
+    expected_roadm_lannion = {
+        "uid": "roadm Lannion_CAS",
+        "type": "Roadm",
+        "type_variety": "example_detailed_impairments",
+        "params": {
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            },
+           'per_degree_pch_out_db': {'east edfa in Lannion_CAS to Corlay': -20,
+                                     'east edfa in Lannion_CAS to Morlaix': -20,
+                                     'east edfa in Lannion_CAS to Stbrieuc': -20},
+            "target_pch_out_db": -20
+        },
+        'metadata': {
+            'location': {
+                'city': 'Lannion_CAS',
+                'latitude': 2.0,
+                'longitude': 0.0,
+                'region': 'RLD'
+            }
+        }
+    }
+    roadm = next(n for n in network.nodes() if n.uid == 'roadm Lannion_CAS')
+    assert roadm.to_json == expected_roadm_lannion
+    spectrum = _spectrum_from_json([
+        {
+            "f_min": 191.35e12,
+            "f_max": 191.35e12,
+            "baud_rate": 32e9,
+            "slot_width": 50e9,
+            "power_dbm": 0,
+            "roll_off": 0.15,
+            "tx_osnr": 40
+        },
+        {
+            "f_min": 193.15e12,
+            "f_max": 193.15e12,
+            "baud_rate": 32e9,
+            "slot_width": 50e9,
+            "power_dbm": 0,
+            "roll_off": 0.15,
+            "tx_osnr": 40,
+            "tx_power_dbm": tx_power_dbm
+        },
+        {
+            "f_min": 193.2e12,
+            "f_max": 193.2e12,
+            "baud_rate": 32e9,
+            "slot_width": 50e9,
+            "power_dbm": 0,
+            "roll_off": 0.15,
+            "tx_osnr": 40}])
+    power = 1.0e-3
+    si = carriers_to_spectral_information(initial_spectrum=spectrum,
+                                          power=power)
+    si = roadm(si, "east edfa in Lannion_CAS to Corlay", "trx Lannion_CAS")
+    # Checks that if tx_power on add port is below min required power, its equalization target can not be met
+    add_max_loss = next(e for e in getattr(equipment['Roadm']['example_detailed_impairments'], 'roadm-path-impairments')
+                        if 'roadm-add-path' in e)['roadm-add-path'][0]['roadm-maxloss']
+    min_required_add_power = -20 + add_max_loss
+    power_reduction = max(0, min_required_add_power - tx_power_dbm)
+    assert_allclose(si.signal, dbm2watt(array([-20, -20 - power_reduction, -20])), rtol=1e-5)
+    path = ['trx Lannion_CAS',
+            'roadm Lannion_CAS',
+            'east edfa in Lannion_CAS to Stbrieuc',
+            'fiber (Lannion_CAS → Stbrieuc)-F056',
+            'east edfa in Stbrieuc to Rennes_STA',
+            'fiber (Stbrieuc → Rennes_STA)-F057',
+            'west edfa in Rennes_STA to Stbrieuc',
+            'roadm Rennes_STA',
+            'trx Rennes_STA']
+
+    si = carriers_to_spectral_information(initial_spectrum=spectrum,
+                                          power=power)
+    for i, uid in enumerate(path):
+        node = next(n for n in network.nodes() if n.uid == uid)
+        if isinstance(node, Roadm):
+            si = node(si, path[i + 1], path[i - 1])
+        else:
+            si = node(si)
+    assert_allclose(watt2dbm(si.signal + si.ase + si.nli), array([-20, -20, -20]), rtol=1e-5)

tests/test_gain_mode.py

@@ -0,0 +1,98 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+# @Author: Esther Le Rouzic
+# @Date:   2019-05-22
+"""
+@author: esther.lerouzic
+checks behaviour of gain mode
+- if all amps have their gains set, check that these gains are used, even if power_dbm or req_power change
+- check that saturation is correct in gain mode
+
+"""
+
+from pathlib import Path
+from numpy.testing import assert_array_equal, assert_allclose
+
+import pytest
+from gnpy.core.utils import lin2db, automatic_nch, dbm2watt
+from gnpy.core.network import build_network
+from gnpy.tools.json_io import load_equipment, load_network
+from gnpy.core.equipment import trx_mode_params
+from gnpy.topology.request import PathRequest, compute_constrained_path, propagate
+
+
+TEST_DIR = Path(__file__).parent
+EQPT_FILENAME = TEST_DIR / 'data/eqpt_config.json'
+NETWORK_FILENAME = TEST_DIR / 'data/perdegreemeshTopologyExampleV2_auto_design_expected.json'
+
+
+def net_setup(equipment):
+    """Common setup for tests: builds network, equipment
+    """
+    network = load_network(NETWORK_FILENAME, equipment)
+    spectrum = equipment['SI']['default']
+    p_db = spectrum.power_dbm
+    p_total_db = p_db + lin2db(automatic_nch(spectrum.f_min, spectrum.f_max, spectrum.spacing))
+    build_network(network, equipment, p_db, p_total_db)
+    return network
+
+
+def create_rq(equipment, srce, dest, bdir, nd_list, ls_list, mode, power_dbm):
+    """Create the usual request list according to parameters
+    """
+    params = {
+        'request_id': 'test_request',
+        'source': srce,
+        'bidir': bdir,
+        'destination': dest,
+        'trx_type': 'Voyager',
+        'trx_mode': mode,
+        'format': mode,
+        'nodes_list': nd_list,
+        'loose_list': ls_list,
+        'effective_freq_slot': None,
+        'path_bandwidth': 100000000000.0,
+        'spacing': 50e9 if mode == 'mode 1' else 75e9,
+        'power': dbm2watt(power_dbm),
+        'tx_power': dbm2watt(power_dbm)
+    }
+    trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
+    params.update(trx_params)
+    f_min = params['f_min']
+    f_max_from_si = params['f_max']
+    params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing'])
+    return PathRequest(**params)
+
+
+@pytest.mark.parametrize("power_dbm", [0, -2, 3])
+@pytest.mark.parametrize("req_power", [1e-3, 0.5e-3, 2e-3])
+def test_gain_mode(req_power, power_dbm):
+    """ Gains are all set on the selected path, so that since the design is made for 0dBm,
+    in gain mode, whatever the value of equipment power_dbm or request power, the network is unchanged
+    and the propagation remains the same as for power mode and 0dBm
+    """
+    equipment = load_equipment(EQPT_FILENAME)
+    network = net_setup(equipment)
+    req = create_rq(equipment, 'trx Brest_KLA', 'trx Rennes_STA', False,
+                    ['Edfa0_roadm Brest_KLA', 'roadm Lannion_CAS', 'trx Rennes_STA'],
+                    ['STRICT', 'STRICT', 'STRICT'], 'mode 1', 0)
+    path = compute_constrained_path(network, req)
+    # Propagation in power_mode
+    infos_expected = propagate(path, req, equipment)
+    # Now set to gain mode
+    setattr(equipment['Span']['default'], 'power_mode', False)
+    setattr(equipment['SI']['default'], 'power_dbm', power_dbm)
+    req.power = req_power
+    network2 = net_setup(equipment)
+    path2 = compute_constrained_path(network2, req)
+    infos_actual = propagate(path2, req, equipment)
+
+    assert_array_equal(infos_expected.baud_rate, infos_actual.baud_rate)
+    assert_allclose(infos_expected.signal, infos_actual.signal, rtol=1e-14)
+    assert_allclose(infos_expected.nli, infos_actual.nli, rtol=1e-14)
+    assert_allclose(infos_expected.ase, infos_actual.ase, rtol=1e-14)
+    assert_array_equal(infos_expected.roll_off, infos_actual.roll_off)
+    assert_array_equal(infos_expected.chromatic_dispersion, infos_actual.chromatic_dispersion)
+    assert_array_equal(infos_expected.pmd, infos_actual.pmd)
+    assert_array_equal(infos_expected.channel_number, infos_actual.channel_number)
+    assert_array_equal(infos_expected.number_of_channels, infos_actual.number_of_channels)

tests/test_info.py

@@ -4,7 +4,7 @@
 import pytest
 from numpy import array, zeros, ones
 from numpy.testing import assert_array_equal
-from gnpy.core.info import create_arbitrary_spectral_information, Pref
+from gnpy.core.info import create_arbitrary_spectral_information
 from gnpy.core.exceptions import SpectrumError
 
 
@@ -12,8 +12,7 @@ def test_create_arbitrary_spectral_information():
     si = create_arbitrary_spectral_information(frequency=[193.25e12, 193.3e12, 193.35e12],
                                                baud_rate=32e9, signal=[1, 1, 1],
                                                delta_pdb_per_channel=[1, 1, 1],
-                                               tx_osnr=40.0,
-                                               ref_power=Pref(1, 1, None))
+                                               tx_osnr=40.0, tx_power=[1, 1, 1])
     assert_array_equal(si.baud_rate, array([32e9, 32e9, 32e9]))
     assert_array_equal(si.slot_width, array([37.5e9, 37.5e9, 37.5e9]))
     assert_array_equal(si.signal, ones(3))
@@ -34,8 +33,7 @@ def test_create_arbitrary_spectral_information():
     si = create_arbitrary_spectral_information(frequency=array([193.35e12, 193.3e12, 193.25e12]),
                                                slot_width=array([50e9, 50e9, 50e9]),
                                                baud_rate=32e9, signal=array([1, 2, 3]),
-                                               tx_osnr=40.0,
-                                               ref_power=Pref(1, 1, None))
+                                               tx_osnr=40.0, tx_power=array([1, 2, 3]))
 
     assert_array_equal(si.signal, array([3, 2, 1]))
 
@@ -43,17 +41,16 @@ def test_create_arbitrary_spectral_information():
                                             r'larger than the slot width for channels: \[1, 3\].'):
         create_arbitrary_spectral_information(frequency=[193.25e12, 193.3e12, 193.35e12], signal=1,
                                               baud_rate=[64e9, 32e9, 64e9], slot_width=50e9,
-                                              tx_osnr=40.0,
-                                              ref_power=Pref(1, 1, None))
+                                              tx_osnr=40.0, tx_power=1)
     with pytest.raises(SpectrumError, match='Spectrum required slot widths larger than the frequency spectral '
                                             r'distances between channels: \[\(1, 2\), \(3, 4\)\].'):
         create_arbitrary_spectral_information(frequency=[193.26e12, 193.3e12, 193.35e12, 193.39e12], signal=1,
-                                              tx_osnr=40.0, baud_rate=32e9, slot_width=50e9, ref_power=Pref(1, 1, None))
+                                              tx_osnr=40.0, baud_rate=32e9, slot_width=50e9, tx_power=1)
     with pytest.raises(SpectrumError, match='Spectrum required slot widths larger than the frequency spectral '
                                             r'distances between channels: \[\(1, 2\), \(2, 3\)\].'):
         create_arbitrary_spectral_information(frequency=[193.25e12, 193.3e12, 193.35e12], signal=1, baud_rate=49e9,
-                                              tx_osnr=40.0, roll_off=0.1, ref_power=Pref(1, 1, None))
+                                              tx_osnr=40.0, roll_off=0.1, tx_power=1)
     with pytest.raises(SpectrumError,
                        match='Dimension mismatch in input fields.'):
         create_arbitrary_spectral_information(frequency=[193.25e12, 193.3e12, 193.35e12], signal=[1, 2], baud_rate=49e9,
-                                              tx_osnr=40.0, ref_power=Pref(1, 1, None))
+                                              tx_osnr=40.0, tx_power=1)

tests/test_invocation.py

@@ -14,7 +14,7 @@ SRC_ROOT = Path(__file__).parent.parent
     ('transmission_main_example', None, transmission_main_example, []),
     ('transmission_saturated', 'logs_transmission_saturated', transmission_main_example,
      ['tests/data/testTopology_expected.json', 'lannion', 'lorient', '-e', 'tests/data/eqpt_config.json', '--pow', '3']),
-    ('path_requests_run', 'logs_path_request', path_requests_run, ['-v']),
+    ('path_requests_run', 'logs_path_request', path_requests_run, ['--redesign-per-request', '-v']),
     ('transmission_main_example__raman', None, transmission_main_example,
      ['gnpy/example-data/raman_edfa_example_network.json', '--sim', 'gnpy/example-data/sim_params.json', '--show-channels', ]),
     ('openroadm-v4-Stockholm-Gothenburg', None, transmission_main_example,
@@ -29,6 +29,17 @@ SRC_ROOT = Path(__file__).parent.parent
      ['--spectrum', 'gnpy/example-data/initial_spectrum2.json', 'gnpy/example-data/meshTopologyExampleV2.xls', '--show-channels', ]),
     ('path_requests_run_CD_PMD_PDL_missing', 'logs_path_requests_run_CD_PMD_PDL_missing', path_requests_run,
      ['tests/data/CORONET_Global_Topology_expected.json', 'tests/data/CORONET_services.json', '-v']),
+    ('power_sweep_example', 'logs_power_sweep_example', transmission_main_example,
+     ['tests/data/testTopology_expected.json', 'brest', 'rennes', '-e', 'tests/data/eqpt_config_sweep.json', '--pow', '3']),
+    ('transmission_long_pow', None, transmission_main_example,
+     ['-e', 'tests/data/eqpt_config.json', 'tests/data/test_long_network.json', '--spectrum', 'gnpy/example-data/initial_spectrum2.json']),
+    ('transmission_long_psd', None, transmission_main_example,
+     ['-e', 'tests/data/eqpt_config_psd.json', 'tests/data/test_long_network.json', '--spectrum', 'gnpy/example-data/initial_spectrum2.json', ]),
+    ('transmission_long_psw', None, transmission_main_example,
+     ['-e', 'tests/data/eqpt_config_psw.json', 'tests/data/test_long_network.json', '--spectrum', 'gnpy/example-data/initial_spectrum2.json', ]),
+    ('multiband_transmission', None, transmission_main_example,
+     ['gnpy/example-data/multiband_example_network.json', 'Site_A', 'Site_D', '-e', 'gnpy/example-data/eqpt_config_multiband.json',
+      '--spectrum', 'gnpy/example-data/multiband_spectrum.json', '--show-channels'])
 ))
 def test_example_invocation(capfd, caplog, output, log, handler, args):
     """Make sure that our examples produce useful output"""

tests/test_logger.py

@@ -34,8 +34,8 @@ def test_jsonthing(caplog):
         "sys_margins": 2
     }
     _ = SI(**json_data)
-    expected_msg = 'WARNING missing f_min attribute in eqpt_config.json[SI]\n ' \
-                   + 'default value is f_min = 191350000000000.0'
+    expected_msg = '\n\tWARNING missing f_min attribute in eqpt_config.json[SI]\n' \
+                   + '\tdefault value is f_min = 191350000000000.0'
     assert expected_msg in caplog.text
 
 
@@ -181,7 +181,7 @@ def wrong_requests():
             }]
         },
         'expected_msg': 'Equipment Config error in imposed_mode: '
-                        + 'Could not find transponder "test_offset" with mode "mode 3" in equipment library'
+                        + 'Could not find transponder "test_offset" in equipment library'
     })
     data.append({
         'error': ServiceError,

tests/test_network_functions.py

@@ -6,13 +6,20 @@
 
 from pathlib import Path
 import pytest
-from gnpy.core.exceptions import NetworkTopologyError
-from gnpy.core.network import span_loss
-from gnpy.tools.json_io import load_equipment, load_network
+from numpy.testing import assert_allclose
+
+from gnpy.core.exceptions import NetworkTopologyError, ConfigurationError
+from gnpy.core.network import span_loss, build_network, select_edfa, get_node_restrictions, \
+    estimate_srs_power_deviation, add_missing_elements_in_network, get_next_node
+from gnpy.tools.json_io import load_equipment, load_network, network_from_json, load_json
+from gnpy.core.utils import lin2db, automatic_nch, merge_amplifier_restrictions
+from gnpy.core.elements import Fiber, Edfa, Roadm, Multiband_amplifier
+from gnpy.core.parameters import SimParams, EdfaParams, MultiBandParams
 
 
 TEST_DIR = Path(__file__).parent
 EQPT_FILENAME = TEST_DIR / 'data/eqpt_config.json'
+EQPT_MULTBAND_FILENAME = TEST_DIR / 'data/eqpt_config_multiband.json'
 NETWORK_FILENAME = TEST_DIR / 'data/bugfixiteratortopo.json'
 
 
@@ -49,7 +56,7 @@ def test_span_loss(node, attenuation):
     network = load_network(NETWORK_FILENAME, equipment)
     for x in network.nodes():
         if x.uid == node:
-            assert attenuation == span_loss(network, x)
+            assert attenuation == span_loss(network, x, equipment)
             return
     assert not f'node "{node}" referenced from test but not found in the topology'  # pragma: no cover
 
@@ -61,4 +68,684 @@ def test_span_loss_unconnected(node):
     network = load_network(NETWORK_FILENAME, equipment)
     x = next(x for x in network.nodes() if x.uid == node)
     with pytest.raises(NetworkTopologyError):
-        span_loss(network, x)
+        span_loss(network, x, equipment)
+
+
+@pytest.mark.parametrize('typ, expected_loss',
+                         [('Edfa', [11, 11]),
+                          ('Fused', [11, 10])])
+def test_eol(typ, expected_loss):
+    """Check that EOL is added only once on spans. One span can be one fiber or several fused fibers
+    EOL is then added on the first fiber only.
+    """
+    json_data = {
+        "elements": [
+            {
+                "uid": "trx SITE1",
+                "type": "Transceiver"
+            },
+            {
+                "uid": "trx SITE2",
+                "type": "Transceiver"
+            },
+            {
+                "uid": "roadm SITE1",
+                "type": "Roadm"
+            },
+            {
+                "uid": "roadm SITE2",
+                "type": "Roadm"
+            },
+            {
+                "uid": "fiber (SITE1 → ILA1)",
+                "type": "Fiber",
+                "type_variety": "SSMF",
+                "params": {
+                    "length": 50.0,
+                    "loss_coef": 0.2,
+                    "length_units": "km"
+                }
+            },
+            {
+                "uid": "fiber (ILA1 → SITE2)",
+                "type": "Fiber",
+                "type_variety": "SSMF",
+                "params": {
+                    "length": 50.0,
+                    "loss_coef": 0.2,
+                    "length_units": "km"
+                }
+            },
+            {
+                "uid": "east edfa in SITE1 to ILA1",
+                "type": "Edfa"
+            },
+            {
+                "uid": "west edfa in SITE2 to ILA1",
+                "type": typ
+            },
+            {
+                "uid": "east edfa in ILA1 to SITE2",
+                "type": "Edfa"
+            }
+        ],
+        "connections": [
+            {
+                "from_node": "trx SITE1",
+                "to_node": "roadm SITE1"
+            },
+            {
+                "from_node": "roadm SITE1",
+                "to_node": "east edfa in SITE1 to ILA1"
+            },
+            {
+                "from_node": "east edfa in SITE1 to ILA1",
+                "to_node": "fiber (SITE1 → ILA1)"
+            },
+            {
+                "from_node": "fiber (SITE1 → ILA1)",
+                "to_node": "east edfa in ILA1 to SITE2"
+            },
+            {
+                "from_node": "east edfa in ILA1 to SITE2",
+                "to_node": "fiber (ILA1 → SITE2)"
+            },
+            {
+                "from_node": "fiber (ILA1 → SITE2)",
+                "to_node": "west edfa in SITE2 to ILA1"
+            },
+            {
+                "from_node": "west edfa in SITE2 to ILA1",
+                "to_node": "roadm SITE2"
+            },
+            {
+                "from_node": "roadm SITE2",
+                "to_node": "trx SITE2"
+            }
+        ]
+    }
+    equipment = load_equipment(EQPT_FILENAME)
+    equipment['Span']['default'].EOL = 1
+    network = network_from_json(json_data, equipment)
+    p_db = equipment['SI']['default'].power_dbm
+    p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
+                                             equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
+
+    build_network(network, equipment, p_db, p_total_db)
+    fibers = [f for f in network.nodes() if isinstance(f, Fiber)]
+    for i in range(2):
+        assert fibers[i].loss == expected_loss[i]
+
+
+@pytest.mark.parametrize('p_db, power_mode, elem1, elem2, expected_gain, expected_delta_p, expected_voa', [
+    (-17, True, 'edfa', 'fiber', 15.0, 15, 15.0),
+    (-17, True, 'fiber', 'edfa', 15.0, 5.0, 5.0),
+    (-17, False, 'edfa', 'fiber', 0.0, None, 0.0),
+    (-17, False, 'fiber', 'edfa', 10.0, None, 0.0),
+    (10, True, 'edfa', 'fiber', -9.0, -9.0, 0.0),
+    (10, True, 'fiber', 'edfa', 1.0, -9.0, 0.0),
+    (10, False, 'edfa', 'fiber', -9.0, None, 0.0),
+    (10, False, 'fiber', 'edfa', 1.0, None, 0.0)])
+def test_design_non_amplified_link(elem1, elem2, expected_gain, expected_delta_p, expected_voa, power_mode, p_db):
+    """Check that the delta_p, gain computed on an amplified link that starts from a transceiver are correct
+    """
+    json_data = {
+        "elements": [
+            {
+                "uid": "trx SITE1",
+                "type": "Transceiver"
+            },
+            {
+                "uid": "trx SITE2",
+                "type": "Transceiver"
+            },
+            {
+                "uid": "edfa",
+                "type": "Edfa",
+                "type_variety": "std_low_gain"
+            },
+            {
+                "uid": "fiber",
+                "type": "Fiber",
+                "type_variety": "SSMF",
+                "params": {
+                    "length": 50.0,
+                    "loss_coef": 0.2,
+                    "length_units": "km"
+                }
+            }
+        ],
+        "connections": [
+            {
+                "from_node": "trx SITE1",
+                "to_node": elem1
+            },
+            {
+                "from_node": elem1,
+                "to_node": elem2
+            },
+            {
+                "from_node": elem2,
+                "to_node": "trx SITE2"
+            }
+        ]
+    }
+    equipment = load_equipment(EQPT_FILENAME)
+    equipment['Span']['default'].power_mode = power_mode
+    equipment['SI']['default'].power_dbm = p_db
+    equipment['SI']['default'].tx_power_dbm = p_db
+    network = network_from_json(json_data, equipment)
+    edfa = next(a for a in network.nodes() if a.uid == 'edfa')
+    edfa.params.out_voa_auto = True
+    p_total_db = p_db + 20.0
+
+    build_network(network, equipment, p_db, p_total_db)
+    amps = [a for a in network.nodes() if isinstance(a, Edfa)]
+    for amp in amps:
+        assert amp.out_voa == expected_voa
+        assert amp.delta_p == expected_delta_p
+        # max power of std_low_gain is 21 dBm
+        assert amp.effective_gain == expected_gain
+
+
+def network_base(case, site_type, length=50.0, amplifier_type='Multiband_amplifier'):
+    base_network = {
+        'elements': [
+            {
+                'uid': 'trx SITE1',
+                'type': 'Transceiver'
+            },
+            {
+                'uid': 'trx SITE2',
+                'type': 'Transceiver'
+            },
+            {
+                'uid': 'roadm SITE1',
+                'type': 'Roadm'
+            },
+            {
+                'uid': 'roadm SITE2',
+                'type': 'Roadm'
+            },
+            {
+                'uid': 'fiber (SITE1 → ILA1)',
+                'type': 'Fiber',
+                'type_variety': 'SSMF',
+                'params': {
+                    'length': length,
+                    'loss_coef': 0.2,
+                    'length_units': 'km'
+                }
+            },
+            {
+                'uid': 'fiber (ILA1 → ILA2)',
+                'type': 'Fiber',
+                'type_variety': 'SSMF',
+                'params': {
+                    'length': 50.0,
+                    'loss_coef': 0.2,
+                    'length_units': 'km'
+                }
+            },
+            {
+                'uid': 'fiber (ILA2 → SITE2)',
+                'type': 'Fiber',
+                'type_variety': 'SSMF',
+                'params': {
+                    'length': 50.0,
+                    'loss_coef': 0.2,
+                    'length_units': 'km'
+                }
+            },
+            {
+                'uid': 'east edfa in SITE1 to ILA1',
+                'type': amplifier_type
+            },
+            {
+                'uid': 'east edfa or fused in ILA1',
+                'type': site_type
+            },
+            {
+                'uid': 'east edfa in ILA2',
+                'type': amplifier_type
+            }, {
+                'uid': 'west edfa in SITE2 to ILA1',
+                'type': amplifier_type
+            }
+        ],
+        'connections': [
+            {
+                'from_node': 'trx SITE1',
+                'to_node': 'roadm SITE1'
+            },
+            {
+                'from_node': 'roadm SITE1',
+                'to_node': 'east edfa in SITE1 to ILA1'
+            },
+            {
+                'from_node': 'east edfa in SITE1 to ILA1',
+                'to_node': 'fiber (SITE1 → ILA1)'
+            },
+            {
+                'from_node': 'fiber (SITE1 → ILA1)',
+                'to_node': 'east edfa or fused in ILA1'
+            },
+            {
+                'from_node': 'east edfa or fused in ILA1',
+                'to_node': 'fiber (ILA1 → ILA2)'
+            },
+            {
+                'from_node': 'fiber (ILA1 → ILA2)',
+                'to_node': 'east edfa in ILA2'
+            },
+            {
+                'from_node': 'east edfa in ILA2',
+                'to_node': 'fiber (ILA2 → SITE2)'
+            },
+            {
+                'from_node': 'fiber (ILA2 → SITE2)',
+                'to_node': 'west edfa in SITE2 to ILA1'
+            },
+            {
+                'from_node': 'west edfa in SITE2 to ILA1',
+                'to_node': 'roadm SITE2'
+            },
+            {
+                'from_node': 'roadm SITE2',
+                'to_node': 'trx SITE2'
+            }
+        ]
+    }
+    multiband_amps = [e for e in base_network['elements'] if e['type'] == 'Multiband_amplifier']
+    edfa2 = next(e for e in base_network['elements'] if e['uid'] == 'east edfa in ILA2')
+    roadm1 = next(e for e in base_network['elements'] if e['uid'] == 'roadm SITE1')
+    fused = [e for e in base_network['elements'] if e['type'] == 'Fused']
+    if case == 'monoband_no_design_band':
+        pass
+    elif case == 'monoband_roadm':
+        roadm1['params'] = {
+            'design_bands': [
+                {'f_min': 192.3e12, 'f_max': 196.0e12}
+            ]
+        }
+    elif case == 'monoband_per_degree':
+        roadm1['params'] = {
+            'per_degree_design_bands': {
+                'east edfa in SITE1 to ILA1': [
+                    {'f_min': 191.5e12, 'f_max': 195.0e12}
+                ]
+            }
+        }
+    elif case == 'monoband_design':
+        edfa2['type_variety'] = 'std_medium_gain'
+    elif case == 'design':
+        for elem in multiband_amps:
+            elem['type_variety'] = 'std_medium_gain_multiband'
+            elem['amplifiers'] = [{
+                'type_variety': 'std_medium_gain',
+                'operational': {
+                    'delta_p': 0,
+                    'tilt_target': 0
+                }
+            }, {
+                'type_variety': 'std_medium_gain_L',
+                'operational': {
+                    'delta_p': -1,
+                    'tilt_target': 0
+                }
+            }]
+        for elem in fused:
+            elem['params'] = {'loss': 0.0}
+    elif case == 'no_design':
+        # user must indicate the bands otherwise SI band (single band is assumed) and this is not
+        # consistent with multiband amps.
+        roadm1['params'] = {
+            'per_degree_design_bands': {
+                'east edfa in SITE1 to ILA1': [
+                    {'f_min': 191.3e12, 'f_max': 196.0e12},
+                    {'f_min': 187.0e12, 'f_max': 190.0e12}
+                ]
+            }
+        }
+    elif case == 'type_variety':
+        # bands are implicit based on amplifiers type_varieties
+        for elem in multiband_amps:
+            elem['type_variety'] = 'std_medium_gain_multiband'
+    return base_network
+
+
+@pytest.mark.parametrize('case, site_type, amplifier_type, expected_design_bands, expected_per_degree_design_bands', [
+    ('monoband_no_design_band', 'Edfa', 'Edfa',
+     [{'f_min': 191.3e12, 'f_max': 196.1e12}], [{'f_min': 191.3e12, 'f_max': 196.1e12}]),
+    ('monoband_roadm', 'Edfa', 'Edfa',
+     [{'f_min': 192.3e12, 'f_max': 196.0e12}], [{'f_min': 192.3e12, 'f_max': 196.0e12}]),
+    ('monoband_per_degree', 'Edfa', 'Edfa',
+     [{'f_min': 191.3e12, 'f_max': 196.1e12}], [{'f_min': 191.5e12, 'f_max': 195.0e12}]),
+    ('monoband_design', 'Edfa', 'Edfa',
+     [{'f_min': 191.3e12, 'f_max': 196.1e12}], [{'f_min': 191.3e12, 'f_max': 196.1e12}]),
+    ('design', 'Fused', 'Multiband_amplifier',
+     [{'f_min': 191.3e12, 'f_max': 196.1e12}],
+     [{'f_min': 186.55e12, 'f_max': 190.05e12}, {'f_min': 191.25e12, 'f_max': 196.15e12}]),
+    ('no_design', 'Fused', 'Multiband_amplifier',
+     [{'f_min': 191.3e12, 'f_max': 196.1e12}],
+     [{'f_min': 187.0e12, 'f_max': 190.0e12}, {'f_min': 191.3e12, 'f_max': 196.0e12}])])
+def test_design_band(case, site_type, amplifier_type, expected_design_bands, expected_per_degree_design_bands):
+    """Check design_band is the one defined:
+    - in SI if nothing is defined,
+    - in ROADM if no design_band is defined for degree
+    - in per_degree
+    - if no design is defined,
+        - if type variety is defined: use it for determining bands
+        - if no type_variety autodesign is as expected, design uses OMS defined set of bands
+    EOL is added only once on spans. One span can be one fiber or several fused fibers
+    EOL is then added on the first fiber only.
+    """
+    json_data = network_base(case, site_type, amplifier_type=amplifier_type)
+    equipment = load_equipment(EQPT_MULTBAND_FILENAME)
+    network = network_from_json(json_data, equipment)
+    p_db = equipment['SI']['default'].power_dbm
+    p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
+                                             equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
+    build_network(network, equipment, p_db, p_total_db)
+    roadm1 = next(n for n in network.nodes() if n.uid == 'roadm SITE1')
+    assert roadm1.design_bands == expected_design_bands
+    assert roadm1.per_degree_design_bands['east edfa in SITE1 to ILA1'] == expected_per_degree_design_bands
+
+
+@pytest.mark.parametrize('raman_allowed, gain_target, power_target, target_extended_gain, warning, expected_selection', [
+    (False, 20, 20, 3, False, ('test_fixed_gain', 0)),
+    (False, 20, 25, 3, False, ('test_fixed_gain', -4)),
+    (False, 10, 15, 3, False, ('std_low_gain_bis', 0)),
+    (False, 5, 15, 3, "is below all available amplifiers min gain", ('std_low_gain_bis', 0)),
+    (False, 30, 15, 3, "is beyond all available amplifiers capabilities", ('std_medium_gain', -1)),
+])
+def test_select_edfa(caplog, raman_allowed, gain_target, power_target, target_extended_gain, warning, expected_selection):
+    """
+    """
+    equipment = load_equipment(EQPT_MULTBAND_FILENAME)
+    edfa_eqpt = {n: a for n, a in equipment['Edfa'].items() if a.type_def != 'multi_band'}
+    selection = select_edfa(raman_allowed, gain_target, power_target, edfa_eqpt, "toto", target_extended_gain, verbose=True)
+    assert selection == expected_selection
+    if warning:
+        assert warning in caplog.text
+
+
+@pytest.mark.parametrize('cls, defaultparams, variety_list, booster_list, band, expected_restrictions', [
+    (Edfa, EdfaParams, [], [],
+     {'LBAND': {'f_min': 187.0e12, 'f_max': 190.0e12}},
+     ['std_medium_gain_L', 'std_low_gain_L_ter', 'std_low_gain_L']),
+    (Edfa, EdfaParams, [], [],
+     {'CBAND': {'f_min': 191.3e12, 'f_max': 196.0e12}},
+     ['CienaDB_medium_gain', 'std_medium_gain', 'std_low_gain', 'std_low_gain_bis', 'test', 'test_fixed_gain']),
+    (Edfa, EdfaParams, ['std_medium_gain', 'std_high_gain'], [],
+     {'CBAND': {'f_min': 191.3e12, 'f_max': 196.0e12}},
+     ['std_medium_gain']),   # name in variety list does not exist in library
+    (Edfa, EdfaParams, ['std_medium_gain', 'std_high_gain'], [],
+     {'LBAND': {'f_min': 187.0e12, 'f_max': 190.0e12}},
+     []),   # restrictions inconsistency with bands
+    (Edfa, EdfaParams, ['std_medium_gain', 'std_high_gain'], ['std_booster'],
+     {'CBAND': {'f_min': 191.3e12, 'f_max': 196.0e12}},
+     ['std_medium_gain']),  # variety list takes precedence over booster constraint
+    (Edfa, EdfaParams, [], ['std_booster'],
+     {'CBAND': {'f_min': 191.3e12, 'f_max': 196.0e12}},
+     ['std_booster']),
+    (Multiband_amplifier, MultiBandParams, [], [],
+     {'CBAND': {'f_min': 191.3e12, 'f_max': 196.0e12}, 'LBAND': {'f_min': 187.0e12, 'f_max': 190.0e12}},
+     ['std_medium_gain_multiband', 'std_low_gain_multiband_bis']),
+    (Multiband_amplifier, MultiBandParams, [], ['std_booster_multiband', 'std_booster'],
+     {'CBAND': {'f_min': 191.3e12, 'f_max': 196.0e12}, 'LBAND': {'f_min': 187.0e12, 'f_max': 190.0e12}},
+     ['std_booster_multiband'])
+])
+def test_get_node_restrictions(cls, defaultparams, variety_list, booster_list, band, expected_restrictions):
+    """Check that all combinations of restrictions are correctly captured
+    """
+    equipment = load_equipment(EQPT_MULTBAND_FILENAME)
+    edfa_config = {"uid": "Edfa1"}
+    if cls == Multiband_amplifier:
+        edfa_config['amplifiers'] = {}
+    edfa_config['params'] = defaultparams.default_values
+    edfa_config['variety_list'] = variety_list
+    node = cls(**edfa_config)
+    roadm_config = {
+        "uid": "roadm Brest_KLA",
+        "params": {
+            "per_degree_pch_out_db": {},
+            "target_pch_out_dbm": -18,
+            "add_drop_osnr": 38,
+            "pmd": 0,
+            "pdl": 0,
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": booster_list
+            },
+            "roadm-path-impairments": []
+        },
+        "metadata": {
+            "location": {
+                "city": "Brest_KLA",
+                "region": "RLD",
+                "latitude": 4.0,
+                "longitude": 0.0
+            }
+        }
+    }
+    prev_node = Roadm(**roadm_config)
+    fiber_config = {
+        "uid": "fiber (SITE1 → ILA1)",
+        "type_variety": "SSMF",
+        "params": {
+            "length": 100.0,
+            "loss_coef": 0.2,
+            "length_units": "km"
+        }
+    }
+    extra_params = equipment['Fiber']['SSMF'].__dict__
+
+    fiber_config['params'] = merge_amplifier_restrictions(fiber_config['params'], extra_params)
+    next_node = Fiber(**fiber_config)
+    restrictions = get_node_restrictions(node, prev_node, next_node, equipment, band)
+    assert restrictions == expected_restrictions
+
+
+@pytest.mark.usefixtures('set_sim_params')
+@pytest.mark.parametrize('case, site_type, band, expected_gain, expected_tilt, expected_variety, sim_params', [
+    ('design', 'Multiband_amplifier', 'LBAND', 10.0, 0.0, 'std_medium_gain_multiband', False),
+    ('no_design', 'Multiband_amplifier', 'LBAND', 10.0, 0.0, 'std_low_gain_multiband_bis', False),
+    ('type_variety', 'Multiband_amplifier', 'LBAND', 10.0, 0.0, 'std_medium_gain_multiband', False),
+    ('design', 'Multiband_amplifier', 'LBAND', 9.344985, 0.0, 'std_medium_gain_multiband', True),
+    ('no_design', 'Multiband_amplifier', 'LBAND', 9.344985, -0.938676, 'std_low_gain_multiband_bis', True),
+    ('no_design', 'Multiband_amplifier', 'CBAND', 10.977065, -1.600193, 'std_low_gain_multiband_bis', True),
+    ('no_design', 'Fused', 'LBAND', 21.0, 0.0, 'std_medium_gain_multiband', False),
+    ('no_design', 'Fused', 'LBAND', 20.344985, -0.819176, 'std_medium_gain_multiband', True),
+    ('no_design', 'Fused', 'CBAND', 21.770319, -1.40032, 'std_medium_gain_multiband', True),
+    ('design', 'Fused', 'CBAND', 21.21108, 0.0, 'std_medium_gain_multiband', True),
+    ('design', 'Multiband_amplifier', 'CBAND', 11.041037, 0.0, 'std_medium_gain_multiband', True)])
+def test_multiband(case, site_type, band, expected_gain, expected_tilt, expected_variety, sim_params):
+    """Check:
+    - if amplifiers are defined in multiband they are used for design,
+    - if no design is defined,
+        - if type variety is defined: use it for determining bands
+        - if no type_variety autodesign is as expected, design uses OMS defined set of bands
+    EOL is added only once on spans. One span can be one fiber or several fused fibers
+    EOL is then added on the first fiber only.
+    """
+    json_data = network_base(case, site_type)
+    equipment = load_equipment(EQPT_MULTBAND_FILENAME)
+    network = network_from_json(json_data, equipment)
+    p_db = equipment['SI']['default'].power_dbm
+    p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
+                                             equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
+
+    if sim_params:
+        SimParams.set_params(load_json(TEST_DIR / 'data' / 'sim_params.json'))
+    build_network(network, equipment, p_db, p_total_db)
+    amp2 = next(n for n in network.nodes() if n.uid == 'east edfa in ILA2')
+    # restore simParams
+    save_sim_params = {"raman_params": SimParams._shared_dict['raman_params'].to_json(),
+                       "nli_params": SimParams._shared_dict['nli_params'].to_json()}
+    SimParams.set_params(save_sim_params)
+    print(amp2.to_json)
+    assert_allclose(amp2.amplifiers[band].effective_gain, expected_gain, atol=1e-5)
+    assert_allclose(amp2.amplifiers[band].tilt_target, expected_tilt, atol=1e-5)
+    assert amp2.type_variety == expected_variety
+
+
+def test_tilt_fused():
+    """check that computed tilt is the same for one span 100km as 2 spans 30 +70 km
+    """
+    design_bands = {'CBAND': {'f_min': 191.3e12, 'f_max': 196.0e12},
+                    'LBAND': {'f_min': 187.0e12, 'f_max': 190.0e12}}
+    save_sim_params = {"raman_params": SimParams._shared_dict['raman_params'].to_json(),
+                       "nli_params": SimParams._shared_dict['nli_params'].to_json()}
+    SimParams.set_params(load_json(TEST_DIR / 'data' / 'sim_params.json'))
+    input_powers = {'CBAND': 0.001, 'LBAND': 0.001}
+    json_data = network_base("design", "Multiband_amplifier", length=100)
+    equipment = load_equipment(EQPT_MULTBAND_FILENAME)
+    network = network_from_json(json_data, equipment)
+    node = next(n for n in network.nodes() if n.uid == 'fiber (SITE1 → ILA1)')
+    tilt_db, tilt_target = estimate_srs_power_deviation(network, node, equipment, design_bands, input_powers)
+    json_data = network_base("design", "Fused", length=50)
+    equipment = load_equipment(EQPT_MULTBAND_FILENAME)
+    network = network_from_json(json_data, equipment)
+    node = next(n for n in network.nodes() if n.uid == 'fiber (ILA1 → ILA2)')
+    fused_tilt_db, fused_tilt_target = \
+        estimate_srs_power_deviation(network, node, equipment, design_bands, input_powers)
+    # restore simParams
+    SimParams.set_params(save_sim_params)
+    for key in tilt_db:
+        assert_allclose(tilt_db[key], fused_tilt_db[key], rtol=1e-3)
+    for key in tilt_target:
+        assert_allclose(tilt_target[key], fused_tilt_target[key], rtol=1e-3)
+
+
+def network_wo_booster(site_type, bands):
+    return {
+        'elements': [
+            {
+                'uid': 'trx SITE1',
+                'type': 'Transceiver'
+            },
+            {
+                'uid': 'trx SITE2',
+                'type': 'Transceiver'
+            },
+            {
+                'uid': 'roadm SITE1',
+                'params': {
+                    'design_bands': bands
+                },
+                'type': 'Roadm'
+            },
+            {
+                'uid': 'roadm SITE2',
+                'type': 'Roadm'
+            },
+            {
+                'uid': 'fiber (SITE1 → ILA1)',
+                'type': 'Fiber',
+                'type_variety': 'SSMF',
+                'params': {
+                    'length': 50.0,
+                    'loss_coef': 0.2,
+                    'length_units': 'km'
+                }
+            },
+            {
+                'uid': 'fiber (ILA1 → ILA2)',
+                'type': 'Fiber',
+                'type_variety': 'SSMF',
+                'params': {
+                    'length': 50.0,
+                    'loss_coef': 0.2,
+                    'length_units': 'km'
+                }
+            },
+            {
+                'uid': 'fiber (ILA2 → SITE2)',
+                'type': 'Fiber',
+                'type_variety': 'SSMF',
+                'params': {
+                    'length': 50.0,
+                    'loss_coef': 0.2,
+                    'length_units': 'km'
+                }
+            },
+            {
+                'uid': 'east edfa or fused in ILA1',
+                'type': site_type
+            }
+        ],
+        'connections': [
+            {
+                'from_node': 'trx SITE1',
+                'to_node': 'roadm SITE1'
+            },
+            {
+                'from_node': 'roadm SITE1',
+                'to_node': 'fiber (SITE1 → ILA1)'
+            },
+            {
+                'from_node': 'fiber (SITE1 → ILA1)',
+                'to_node': 'east edfa or fused in ILA1'
+            },
+            {
+                'from_node': 'east edfa or fused in ILA1',
+                'to_node': 'fiber (ILA1 → ILA2)'
+            },
+            {
+                'from_node': 'fiber (ILA1 → ILA2)',
+                'to_node': 'fiber (ILA2 → SITE2)'
+            },
+            {
+                'from_node': 'fiber (ILA2 → SITE2)',
+                'to_node': 'roadm SITE2'
+            },
+            {
+                'from_node': 'roadm SITE2',
+                'to_node': 'trx SITE2'
+            }
+        ]
+    }
+
+
+@pytest.mark.parametrize('site_type, expected_type, bands, expected_bands', [
+    ('Multiband_amplifier', Multiband_amplifier,
+     [{'f_min': 187.0e12, 'f_max': 190.0e12}, {'f_min': 191.3e12, 'f_max': 196.0e12}],
+     [{'f_min': 187.0e12, 'f_max': 190.0e12}, {'f_min': 191.3e12, 'f_max': 196.0e12}]),
+    ('Edfa', Edfa,
+     [{'f_min': 191.4e12, 'f_max': 196.1e12}],
+     [{'f_min': 191.4e12, 'f_max': 196.1e12}]),
+    ('Edfa', Edfa,
+     [{'f_min': 191.2e12, 'f_max': 196.0e12}],
+     []),
+    ('Fused', Multiband_amplifier,
+     [{'f_min': 187.0e12, 'f_max': 190.0e12}, {'f_min': 191.3e12, 'f_max': 196.0e12}],
+     [{'f_min': 187.0e12, 'f_max': 190.0e12}, {'f_min': 191.3e12, 'f_max': 196.0e12}]),
+    ('Fused', Edfa,
+     [{'f_min': 191.3e12, 'f_max': 196.0e12}],
+     [{'f_min': 191.3e12, 'f_max': 196.0e12}])])
+def test_insert_amp(site_type, expected_type, bands, expected_bands):
+    """Check:
+    - if amplifiers are defined in multiband they are used for design,
+    - if no design is defined,
+        - if type variety is defined: use it for determining bands
+        - if no type_variety autodesign is as expected, design uses OMS defined set of bands
+    EOL is added only once on spans. One span can be one fiber or several fused fibers
+    EOL is then added on the first fiber only.
+    """
+    json_data = network_wo_booster(site_type, bands)
+    equipment = load_equipment(EQPT_MULTBAND_FILENAME)
+    network = network_from_json(json_data, equipment)
+    p_db = equipment['SI']['default'].power_dbm
+    p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
+                                             equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
+    add_missing_elements_in_network(network, equipment)
+    if not expected_bands:
+        with pytest.raises(ConfigurationError):
+            build_network(network, equipment, p_db, p_total_db)
+    else:
+        build_network(network, equipment, p_db, p_total_db)
+        roadm1 = next(n for n in network.nodes() if n.uid == 'roadm SITE1')
+        amp1 = get_next_node(roadm1, network)
+        assert isinstance(amp1, expected_type)
+        assert roadm1.per_degree_design_bands['Edfa_booster_roadm SITE1_to_fiber (SITE1 → ILA1)'] == expected_bands

tests/test_parameters.py

@@ -40,17 +40,18 @@ def test_fiber_parameters():
     fiber_dict_cr.update(Fiber(**fiber_dict_cr).__dict__)
     fiber_params_cr = FiberParams(**fiber_dict_cr)
 
-    raman_coefficient_explicit_g0 = fiber_params_explicit_g0.raman_coefficient
-    raman_coefficient_explicit_g0 =\
-        raman_coefficient_explicit_g0.normalized_gamma_raman * fiber_params_explicit_g0._raman_reference_frequency
+    norm_gamma_raman_explicit_g0 = fiber_params_explicit_g0.raman_coefficient.normalized_gamma_raman
+    norm_gamma_raman_default_g0 = fiber_params_default_g0.raman_coefficient.normalized_gamma_raman
 
-    raman_coefficient_default_g0 = fiber_params_default_g0.raman_coefficient
-    raman_coefficient_default_g0 = \
-        raman_coefficient_default_g0.normalized_gamma_raman * fiber_params_default_g0._raman_reference_frequency
+    norm_gamma_raman_cr = fiber_params_cr.raman_coefficient.normalized_gamma_raman
 
-    raman_coefficient_cr = fiber_params_cr.raman_coefficient
-    raman_coefficient_cr = \
-        raman_coefficient_cr.normalized_gamma_raman * fiber_params_cr._raman_reference_frequency
+    assert_allclose(norm_gamma_raman_explicit_g0, norm_gamma_raman_default_g0, rtol=1e-10)
+    assert_allclose(norm_gamma_raman_explicit_g0, norm_gamma_raman_cr, rtol=1e-10)
 
-    assert_allclose(raman_coefficient_explicit_g0, raman_coefficient_default_g0, rtol=1e-10)
-    assert_allclose(raman_coefficient_explicit_g0, raman_coefficient_cr, rtol=1e-10)
+    # Change Effective Area
+    fiber_dict_default_g0['effective_area'] = 100e-12
+    no_ssmf_fiber_params = FiberParams(**fiber_dict_default_g0)
+
+    norm_gamma_raman_default_g0_no_ssmf = no_ssmf_fiber_params.raman_coefficient.normalized_gamma_raman
+
+    assert_allclose(norm_gamma_raman_explicit_g0, norm_gamma_raman_default_g0_no_ssmf, rtol=1e-10)

tests/test_parser.py

@@ -24,8 +24,8 @@ from xlrd import open_workbook
 import pytest
 from copy import deepcopy
 from gnpy.core.utils import automatic_nch, lin2db
-from gnpy.core.network import build_network
-from gnpy.core.exceptions import ServiceError
+from gnpy.core.network import build_network, add_missing_elements_in_network
+from gnpy.core.exceptions import ServiceError, ConfigurationError
 from gnpy.topology.request import (jsontocsv, requests_aggregation, compute_path_dsjctn, deduplicate_disjunctions,
                                    compute_path_with_disjunction, ResultElement, PathRequest)
 from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum
@@ -71,6 +71,7 @@ def test_auto_design_generation_fromxlsgainmode(tmpdir, xls_input, expected_json
     """tests generation of topology json and that the build network gives correct results in gain mode"""
     equipment = load_equipment(eqpt_filename)
     network = load_network(xls_input, equipment)
+    add_missing_elements_in_network(network, equipment)
     # in order to test the Eqpt sheet and load gain target,
     # change the power-mode to False (to be in gain mode)
     equipment['Span']['default'].power_mode = False
@@ -109,6 +110,7 @@ def test_auto_design_generation_fromjson(tmpdir, json_input, power_mode):
     p_db = equipment['SI']['default'].power_dbm
     p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
                                              equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
+    add_missing_elements_in_network(network, equipment)
     build_network(network, equipment, p_db, p_total_db)
     actual_json_output = tmpdir / json_input.with_name(json_input.stem + '_auto_design').with_suffix('.json').name
     save_network(network, actual_json_output)
@@ -230,7 +232,7 @@ def test_json_response_generation(xls_input, expected_response_file):
     rqs, dsjn = requests_aggregation(rqs, dsjn)
     pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
     propagatedpths, reversed_pths, reversed_propagatedpths = \
-        compute_path_with_disjunction(network, equipment, rqs, pths)
+        compute_path_with_disjunction(network, equipment, rqs, pths, redesign=True)
     pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
 
     result = []
@@ -350,6 +352,7 @@ def test_excel_ila_constraints(source, destination, route_list, hoptype, expecte
         'cost': None,
         'roll_off': 0,
         'tx_osnr': 0,
+        'tx_power': 0,
         'penalties': None,
         'min_spacing': None,
         'nb_channel': 0,
@@ -563,3 +566,52 @@ def test_service_json_constraint_order():
     rqs = requests_from_json(data, equipment)
     assert rqs[0].nodes_list == ['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE']
     assert rqs[0].loose_list == ['STRICT', 'LOOSE', 'STRICT', 'STRICT']
+
+
+@pytest.mark.parametrize('type_variety, target_pch_out_db, correct_variety', [(None, -20, True),
+                                                                              ('example_test', -18, True),
+                                                                              ('example', None, False)])
+def test_roadm_type_variety(type_variety, target_pch_out_db, correct_variety):
+    """Checks that if element has no variety, the default one is applied, and if it has one
+    that the type_variety is correctly applied
+    """
+    json_data = {
+        "elements": [{
+            "uid": "roadm Oakland",
+            "type": "Roadm",
+        }],
+        "connections": []
+    }
+    expected_roadm = {
+        "uid": "roadm Oakland",
+        "type": "Roadm",
+        "params": {
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            }
+        },
+        'metadata': {
+            'location': {
+                'city': None,
+                'latitude': 0,
+                'longitude': 0,
+                'region': None
+            }
+        }
+    }
+    if type_variety is not None:
+        json_data['elements'][0]['type_variety'] = type_variety
+        expected_roadm['type_variety'] = type_variety
+    else:
+        # Do not add type variety in json_data to test that it creates a 'default' type_variety
+        expected_roadm['type_variety'] = 'default'
+    expected_roadm['params']['target_pch_out_db'] = target_pch_out_db
+    equipment = load_equipment(eqpt_filename)
+    if correct_variety:
+        network = network_from_json(json_data, equipment)
+        roadm = [n for n in network.nodes()][0]
+        assert roadm.to_json == expected_roadm
+    else:
+        with pytest.raises(ConfigurationError):
+            network = network_from_json(json_data, equipment)

tests/test_propagation.py

@@ -4,14 +4,19 @@
 # @Date:   2018-02-02 14:06:55
 
 import pytest
-from gnpy.core.elements import Transceiver, Fiber, Edfa, Roadm
-from gnpy.core.utils import db2lin
-from gnpy.core.info import create_input_spectral_information, ReferenceCarrier
-from gnpy.core.network import build_network
-from gnpy.tools.json_io import load_network, load_equipment
+
 from pathlib import Path
 from networkx import dijkstra_path
 from numpy import mean, sqrt, ones
+import re
+
+from gnpy.core.exceptions import SpectrumError
+from gnpy.core.elements import Transceiver, Fiber, Edfa, Roadm
+from gnpy.core.utils import db2lin
+from gnpy.core.info import create_input_spectral_information
+from gnpy.core.network import build_network
+from gnpy.tools.json_io import load_network, load_equipment, network_from_json
+
 
 network_file_name = Path(__file__).parent.parent / 'tests/LinkforTest.json'
 eqpt_library_name = Path(__file__).parent.parent / 'tests/data/eqpt_config.json'
@@ -28,7 +33,6 @@ def nch_and_spacing(request):
 def propagation(input_power, con_in, con_out, dest):
     equipment = load_equipment(eqpt_library_name)
     network = load_network(network_file_name, equipment)
-    build_network(network, equipment, 0, 20)
 
     # parametrize the network elements with the con losses and adapt gain
     # (assumes all spans are identical)
@@ -40,14 +44,16 @@ def propagation(input_power, con_in, con_out, dest):
         if isinstance(e, Edfa):
             e.operational.gain_target = loss + con_in + con_out
 
+    build_network(network, equipment, 0, 20)
+
     transceivers = {n.uid: n for n in network.nodes() if isinstance(n, Transceiver)}
 
     p = input_power
     p = db2lin(p) * 1e-3
     spacing = 50e9  # THz
     si = create_input_spectral_information(f_min=191.3e12, f_max=191.3e12 + 79 * spacing, roll_off=0.15,
-                                           baud_rate=32e9, power=p, spacing=spacing, tx_osnr=None,
-                                           ref_carrier=ReferenceCarrier(baud_rate=32e9, slot_width=50e9))
+                                           baud_rate=32e9, spacing=spacing, tx_osnr=None,
+                                           tx_power=p)
     source = next(transceivers[uid] for uid in transceivers if uid == 'trx A')
     sink = next(transceivers[uid] for uid in transceivers if uid == dest)
     path = dijkstra_path(network, source, sink)
@@ -125,6 +131,62 @@ def test_dgd(dgd_test, dest):
     assert pmd == pytest.approx(expected_pmd)
 
 
+def wrong_element_propagate():
+    """
+    """
+    data = []
+    data.append({
+        "error": SpectrumError,
+        "json_data": {
+            "elements": [{
+                "uid": "Elem",
+                "type": "Fiber",
+                "type_variety": "SSMF",
+                "params": {
+                    "dispersion_per_frequency": {
+                        "frequency": [
+                            185.49234135667396e12,
+                            186.05251641137855e12,
+                            188.01312910284463e12,
+                            189.99124726477024e12],
+                        "value": [
+                            1.60e-05,
+                            1.67e-05,
+                            1.7e-05,
+                            1.8e-05]
+                    },
+                    "length": 1.02,
+                    "loss_coef": 2.85,
+                    "length_units": "km",
+                    "att_in": 0.0,
+                    "con_in": 0.0,
+                    "con_out": 0.0
+                }
+            }],
+            "connections": []
+        },
+        "expected_msg": 'The spectrum bandwidth exceeds the frequency interval used to define the fiber Chromatic '
+                        + 'Dispersion in "Fiber Elem".\nSpectrum f_min-f_max: 191.35-196.1\nChromatic Dispersion '
+                        + 'f_min-f_max: 185.49-189.99'
+    })
+    return data
+
+
+@pytest.mark.parametrize('error, json_data, expected_msg',
+                         [(e['error'], e['json_data'], e['expected_msg']) for e in wrong_element_propagate()])
+def test_json_element(error, json_data, expected_msg):
+    """
+    Check that a missing key is correctly raisong the logger
+    """
+    equipment = load_equipment(eqpt_library_name)
+    network = network_from_json(json_data, equipment)
+    elem = next(e for e in network.nodes() if e.uid == 'Elem')
+    si = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
+                                           baud_rate=32e9, tx_power=1.0e-3, spacing=50.0e9, tx_osnr=45)
+    with pytest.raises(error, match=re.escape(expected_msg)):
+        _ = elem(si)
+
+
 if __name__ == '__main__':
     from logging import getLogger, basicConfig, INFO
     logger = getLogger(__name__)

tests/test_roadm_restrictions.py

@@ -13,15 +13,19 @@ checks that restrictions in roadms are correctly applied during autodesign
 from pathlib import Path
 import pytest
 from numpy.testing import assert_allclose
-
+from numpy import ndarray, mean
+from copy import deepcopy
 from gnpy.core.utils import lin2db, automatic_nch
-from gnpy.core.elements import Fused, Roadm, Edfa
-from gnpy.core.network import build_network
-from gnpy.tools.json_io import network_from_json, load_equipment, load_json, Amp
+from gnpy.core.elements import Fused, Roadm, Edfa, Transceiver, EdfaOperational, EdfaParams, Fiber
+from gnpy.core.parameters import FiberParams, RoadmParams, FusedParams
+from gnpy.core.network import build_network, design_network
+from gnpy.tools.json_io import network_from_json, load_equipment, load_json, Amp, _equipment_from_json
 from gnpy.core.equipment import trx_mode_params
-from gnpy.topology.request import PathRequest, compute_constrained_path, ref_carrier
-from gnpy.core.info import create_input_spectral_information
-from gnpy.core.utils import db2lin
+from gnpy.topology.request import PathRequest, compute_constrained_path, propagate
+from gnpy.core.info import create_input_spectral_information, Carrier
+from gnpy.core.utils import db2lin, dbm2watt, merge_amplifier_restrictions
+from gnpy.core.exceptions import ConfigurationError, NetworkTopologyError
+
 
 TEST_DIR = Path(__file__).parent
 EQPT_LIBRARY_NAME = TEST_DIR / 'data/eqpt_config.json'
@@ -209,18 +213,23 @@ def test_restrictions(restrictions, equipment):
                     raise AssertionError()
 
 
+@pytest.mark.parametrize('roadm_type_variety, roadm_b_maxloss', [('default', 0),
+                                                                 ('example_detailed_impairments', 16.5)])
 @pytest.mark.parametrize('power_dbm', [0, +1, -2])
 @pytest.mark.parametrize('prev_node_type, effective_pch_out_db', [('edfa', -20.0), ('fused', -22.0)])
-def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
+def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm, roadm_type_variety, roadm_b_maxloss):
     """Check that egress power of roadm is equal to target power if input power is greater
     than target power else, that it is equal to input power. Use a simple two hops A-B-C topology
     for the test where the prev_node in ROADM B is either an amplifier or a fused, so that the target
     power can not be met in this last case.
     """
     equipment = load_equipment(EQPT_LIBRARY_NAME)
+    equipment['SI']['default'].power_dbm = power_dbm
     json_network = load_json(TEST_DIR / 'data/twohops_roadm_power_test.json')
     prev_node = next(n for n in json_network['elements'] if n['uid'] == 'west edfa in node B to ila2')
     json_network['elements'].remove(prev_node)
+    roadm_b = next(element for element in json_network['elements'] if element['uid'] == 'roadm node B')
+    roadm_b['type_variety'] = roadm_type_variety
     if prev_node_type == 'edfa':
         prev_node = {'uid': 'west edfa in node B to ila2', 'type': 'Edfa'}
     elif prev_node_type == 'fused':
@@ -245,7 +254,9 @@ def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
               'format': '',
               'path_bandwidth': 100e9,
               'effective_freq_slot': None,
-              'nb_channel': nb_channel
+              'nb_channel': nb_channel,
+              'power': dbm2watt(power_dbm),
+              'tx_power': dbm2watt(power_dbm)
               }
     trx_params = trx_mode_params(equipment)
     params.update(trx_params)
@@ -254,32 +265,447 @@ def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
     path = compute_constrained_path(network, req)
     si = create_input_spectral_information(
         f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
-        power=req.power, spacing=req.spacing, tx_osnr=req.tx_osnr, ref_carrier=ref_carrier(equipment))
+        spacing=req.spacing, tx_osnr=req.tx_osnr, tx_power=req.tx_power)
     for i, el in enumerate(path):
         if isinstance(el, Roadm):
             power_in_roadm = si.signal + si.ase + si.nli
-            si = el(si, degree=path[i + 1].uid)
+            si = el(si, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
             power_out_roadm = si.signal + si.ase + si.nli
             if el.uid == 'roadm node B':
                 # if previous was an EDFA, power level at ROADM input is enough for the ROADM to apply its
                 # target power (as specified in equipment ie -20 dBm)
                 # if it is a Fused, the input power to the ROADM is smaller than the target power, and the
-                # ROADM cannot apply this target. In this case, it is assumed that the ROADM has 0 dB loss
-                # so the output power will be the same as the input power, which for this particular case
-                # corresponds to -22dBm + power_dbm
-                # next step (for ROADM modelling) will be to apply a minimum loss for ROADMs !
+                # ROADM cannot apply this target. If the ROADM has 0 dB loss the output power will be the same
+                # as the input power, which for this particular case corresponds to -22dBm + power_dbm.
+                # If ROADM has a minimum losss, then output power will be -22dBm + power_dbm - ROADM loss. !
                 if prev_node_type == 'edfa':
                     # edfa prev_node sets input power to roadm to a high enough value:
                     # check that target power is correctly set in the ROADM
                     assert_allclose(el.ref_pch_out_dbm, effective_pch_out_db, rtol=1e-3)
                     # Check that egress power of roadm is equal to target power
                     assert_allclose(power_out_roadm, db2lin(effective_pch_out_db - 30), rtol=1e-3)
-                elif prev_node_type == 'fused':
-                    # fused prev_node does reamplfy power after fiber propagation, so input power
+                if prev_node_type == 'fused':
+                    # fused prev_node does not reamplify power after fiber propagation, so input power
                     # to roadm is low.
                     # check that target power correctly reports power_dbm from previous propagation
-                    assert_allclose(el.ref_pch_out_dbm, effective_pch_out_db + power_dbm, rtol=1e-3)
-                    # Check that egress power of roadm is not equalized power out is the same as power in.
-                    assert_allclose(power_out_roadm, power_in_roadm, rtol=1e-3)
+                    assert_allclose(el.ref_pch_out_dbm, effective_pch_out_db + power_dbm - roadm_b_maxloss, rtol=1e-3)
+                    # Check that egress power of roadm is not equalized:
+                    # power out is the same as power in minus the ROADM loss.
+                    assert_allclose(power_out_roadm, power_in_roadm / db2lin(roadm_b_maxloss), rtol=1e-3)
+                    assert effective_pch_out_db + power_dbm ==\
+                        pytest.approx(lin2db(min(power_in_roadm) * 1e3), rel=1e-3)
         else:
             si = el(si)
+
+
+def create_per_oms_request(network, eqpt, req_power):
+    """Create requests between every adjacent ROADMs + one additional request crossing several ROADMs
+    """
+    nb_channel = automatic_nch(eqpt['SI']['default'].f_min, eqpt['SI']['default'].f_max,
+                               eqpt['SI']['default'].spacing)
+    params = {
+        'trx_type': '',
+        'trx_mode': '',
+        'bidir': False,
+        'loose_list': ['strict', 'strict'],
+        'format': '',
+        'path_bandwidth': 100e9,
+        'effective_freq_slot': None,
+        'nb_channel': nb_channel,
+        'power': dbm2watt(req_power),
+        'tx_power': dbm2watt(req_power)
+    }
+    trx_params = trx_mode_params(eqpt)
+    params.update(trx_params)
+    trxs = [e for e in network if isinstance(e, Transceiver)]
+    req_list = []
+    req_id = 0
+    for trx in trxs:
+        source = trx.uid
+        roadm = next(n for n in network.successors(trx) if isinstance(n, Roadm))
+        for degree in roadm.per_degree_pch_out_dbm.keys():
+            node = next(n for n in network.nodes() if n.uid == degree)
+            # find next roadm
+            while not isinstance(node, Roadm):
+                node = next(n for n in network.successors(node))
+            next_roadm = node
+            destination = next(n.uid for n in network.successors(next_roadm) if isinstance(n, Transceiver))
+            params['request_id'] = req_id
+            req_id += 1
+            params['source'] = source
+            params['destination'] = destination
+            params['nodes_list'] = [degree, destination]
+            req = PathRequest(**params)
+            req.power = dbm2watt(req_power)
+            carrier = {key: getattr(req, key) for key in ['baud_rate', 'roll_off', 'tx_osnr']}
+            carrier['label'] = ""
+            carrier['slot_width'] = req.spacing
+            carrier['delta_pdb'] = 0
+            carrier['tx_power'] = 1e-3
+            req.initial_spectrum = {(req.f_min + req.spacing * f): Carrier(**carrier)
+                                    for f in range(1, req.nb_channel + 1)}
+            req_list.append(req)
+    # add one additional request crossing several roadms to have a complete view
+    params['source'] = 'trx Rennes_STA'
+    params['destination'] = 'trx Vannes_KBE'
+    params['nodes_list'] = ['roadm Lannion_CAS', 'trx Vannes_KBE']
+    params['bidir'] = True
+    req = PathRequest(**params)
+    req.power = dbm2watt(req_power)
+    carrier = {key: getattr(req, key) for key in ['baud_rate', 'roll_off', 'tx_osnr']}
+    carrier['label'] = ""
+    carrier['slot_width'] = req.spacing
+    carrier['delta_pdb'] = 0
+    carrier['tx_power'] = 1e-3
+    req.initial_spectrum = {(req.f_min + req.spacing * f): Carrier(**carrier) for f in range(1, req.nb_channel + 1)}
+    req_list.append(req)
+    return req_list
+
+
+def list_element_attr(element):
+    """Return the list of keys to be checked depending on element type. List only the keys that are not
+    created upon element effective propagation
+    """
+
+    if isinstance(element, Roadm):
+        return ['uid', 'name', 'metadata', 'operational', 'type_variety', 'target_pch_out_dbm',
+                'passive', 'restrictions', 'per_degree_pch_out_dbm',
+                'target_psd_out_mWperGHz', 'per_degree_pch_psd']
+        # Dynamically created: 'effective_loss',
+    if isinstance(element, RoadmParams):
+        return ['target_pch_out_dbm', 'target_psd_out_mWperGHz', 'per_degree_pch_out_db', 'per_degree_pch_psd',
+                'add_drop_osnr', 'pmd', 'restrictions']
+    if isinstance(element, Edfa):
+        return ['variety_list', 'uid', 'name', 'params', 'metadata', 'operational',
+                'passive', 'effective_gain', 'delta_p', 'tilt_target', 'out_voa']
+        # TODO this exhaustive test highlighted that type_variety is not correctly updated from EdfaParams to
+        # attributes in preamps
+        # Dynamically created only with channel propagation: 'att_in', 'channel_freq', 'effective_pch_out_db'
+        # 'gprofile', 'interpol_dgt', 'interpol_gain_ripple', 'interpol_nf_ripple', 'nch',  'nf', 'pin_db', 'pout_db',
+        # 'target_pch_out_db',
+    if isinstance(element, FusedParams):
+        return ['loss']
+    if isinstance(element, EdfaOperational):
+        return ['delta_p', 'gain_target', 'out_voa', 'tilt_target']
+    if isinstance(element, EdfaParams):
+        return ['f_min', 'f_max', 'type_variety', 'type_def', 'gain_flatmax', 'gain_min', 'p_max', 'nf_model',
+                'dual_stage_model', 'nf_fit_coeff', 'nf_ripple', 'dgt', 'gain_ripple', 'out_voa_auto',
+                'allowed_for_design', 'raman']
+    if isinstance(element, Fiber):
+
+        return ['uid', 'name', 'params', 'metadata', 'operational', 'type_variety', 'passive',
+                'lumped_losses', 'z_lumped_losses']
+        # Dynamically created 'output_total_power', 'pch_out_db'
+    if isinstance(element, FiberParams):
+        return ['_length', '_att_in', '_con_in', '_con_out', '_ref_frequency', '_ref_wavelength',
+                '_dispersion', '_dispersion_slope', '_dispersion', '_f_dispersion_ref',
+                '_gamma', '_pmd_coef', '_loss_coef',
+                '_f_loss_ref', '_lumped_losses']
+    if isinstance(element, Fused):
+        return ['uid', 'name', 'params', 'metadata', 'operational', 'loss', 'passive']
+    if isinstance(element, FusedParams):
+        return ['loss']
+    return ['should never come here']
+
+
+# all initial delta_p are null in topo file, so add random places to change this value
+@pytest.mark.parametrize('amp_with_deltap_one', [[],
+                                                 ['east edfa in Lorient_KMA to Vannes_KBE',
+                                                  'east edfa in Stbrieuc to Rennes_STA',
+                                                  'west edfa in Lannion_CAS to Morlaix',
+                                                  'east edfa in a to b',
+                                                  'west edfa in b to a']])
+@pytest.mark.parametrize('power_dbm, req_power', [(0, 0), (0, -3), (3, 3), (0, 3), (3, 0),
+                                                  (3, 1), (3, 5), (3, 2), (3, 4), (2, 4)])
+def test_compare_design_propagation_settings(power_dbm, req_power, amp_with_deltap_one):
+    """Check that network design does not change after propagation except for gain in
+    case of power_saturation during design and/or during propagation:
+    - in power mode only:
+        expected behaviour: target power out of roadm does not change
+        so gain of booster should be reduced/augmented by the exact power difference;
+        the following amplifiers on the OMS have unchanged gain except if augmentation
+        of channel power on booster leads to total_power above amplifier max power,
+        ie if amplifier saturates.
+
+                          roadm -----booster (pmax 21dBm, 96 channels= 19.82dB)
+        pdesign=0dBm pch= 0dBm,         ^ -20dBm  ^G=20dB, Pch=0dBm, Ptot=19.82dBm
+        pdesign=0dBm pch= -3dBm         ^ -20dBm  ^G=17dB, Pch=-3dBm, Ptot=16.82dBm
+        pdesign=3dBm pch= 3dBm          ^ -20dBm  ^G=23-1.82dB, Pch=1.18dBm, Ptot=21dBm
+            amplifier can not handle 96x3dBm channels, amplifier saturation is considered
+            for the choice of amplifier during design
+        pdesign=0dBm pch= 3dBm          ^ -20dBm  ^G=23-1.82dB, Pch=1.18dBm, Ptot=21dBm
+            amplifier can not handle 96x3dBm channels during propagation, amplifier selection
+            has been done for 0dBm. Saturation is applied for all amps only during propagation
+
+        Design applies a saturation verification on amplifiers.
+        This saturation leads to a power reduction to the max power in the amp library, which
+        is also applied on the amp delta_p and independantly from propagation.
+
+        After design, upon propagation, the amplifier gain and applied delta_p may also change
+        if total power exceeds max power (eg not the same nb of channels, not the same power per channel
+        compared to design).
+
+        This test also checks all the possible combinations and expected before/after propagation
+        gain differences. It also checks delta_p applied due to saturation during design.
+    """
+    eqpt = load_equipment(EQPT_LIBRARY_NAME)
+    eqpt['SI']['default'].power_dbm = power_dbm
+    json_network = load_json(NETWORK_FILE_NAME)
+    for element in json_network['elements']:
+        # Initialize a value for delta_p
+        if element['type'] == 'Edfa':
+            element['operational']['delta_p'] = 0 + element['operational']['out_voa'] \
+                if element['operational']['out_voa'] is not None else 0
+            # apply a 1 dB delta_p on the set of amps
+            if element['uid'] in amp_with_deltap_one:
+                element['operational']['delta_p'] = 1
+
+    network = network_from_json(json_network, eqpt)
+    # Build the network once using the default power defined in SI in eqpt config
+    p_db = power_dbm
+    p_total_db = p_db + lin2db(automatic_nch(eqpt['SI']['default'].f_min,
+                                             eqpt['SI']['default'].f_max,
+                                             eqpt['SI']['default'].spacing))
+    build_network(network, eqpt, p_db, p_total_db, verbose=False)
+    # record network settings before propagating
+    # propagate on each oms
+    req_list = create_per_oms_request(network, eqpt, req_power)
+    paths = [compute_constrained_path(network, r) for r in req_list]
+
+    # systematic comparison of elements settings before and after propagation
+    # all amps have 21 dBm max power
+    pch_max = 21 - lin2db(96)
+    for path, req in zip(paths, req_list):
+        # check all elements except source and destination trx
+        # in order to have clean initialization, use deecopy of paths
+        design_network(req, network, eqpt, verbose=False)
+        network_copy = deepcopy(network)
+        pth = deepcopy(path)
+        _ = propagate(pth, req, eqpt)
+        for i, element in enumerate(pth[1:-1]):
+            element_is_first_amp = False
+            # index of previous element in path is i
+            if (isinstance(element, Edfa) and isinstance(pth[i], Roadm)) or element.uid == 'west edfa in d to c':
+                # oms c to d has no booster but one preamp: the power difference is hold there
+                element_is_first_amp = True
+            # find the element with the same id in the network_copy
+            element_copy = next(n for n in network_copy.nodes() if n.uid == element.uid)
+            for key in list_element_attr(element):
+                if not isinstance(getattr(element, key),
+                                  (EdfaOperational, EdfaParams, FiberParams, RoadmParams, FusedParams)):
+                    if not key == 'effective_gain':
+                        # for all keys, before and after design should be the same except for gain (in power mode)
+                        if isinstance(getattr(element, key), ndarray):
+                            if len(getattr(element, key)) > 0:
+                                assert getattr(element, key) == getattr(element_copy, key)
+                            else:
+                                assert len(getattr(element_copy, key)) == 0
+                        else:
+                            assert getattr(element, key) == getattr(element_copy, key)
+                    else:
+                        dp = element.out_voa if element.uid not in amp_with_deltap_one else element.out_voa + 1
+                        # check that target power is correctly set
+                        assert element.target_pch_out_dbm == req_power + dp
+                        # check that designed gain is exactly applied except if target power exceeds max power, then
+                        # gain is slightly less than the one computed during design for the noiseless reference,
+                        # because during propagation, noise has accumulated, additing to signal.
+                        # check that delta_p is unchanged unless for saturation
+                        if element.target_pch_out_dbm > pch_max:
+                            assert element.effective_gain == pytest.approx(element_copy.effective_gain, abs=2e-2)
+                        else:
+                            assert element.effective_gain == element_copy.effective_gain
+                        # check that delta_p is unchanged unless for saturation
+                        assert element.delta_p == element_copy.delta_p
+                        if element_is_first_amp:
+                            # if element is first amp on path, then it is the one that will saturate if req_power is
+                            # too high
+                            assert mean(element.pch_out_dbm) ==\
+                                pytest.approx(min(pch_max, req_power + element.delta_p - element.out_voa), abs=2e-2)
+                        # check that delta_p is unchanged unless due to saturation
+                        assert element.delta_p == pytest.approx(min(req_power + dp, pch_max) - req_power, abs=1e-2)
+                        # check that delta_p is unchanged unless for saturation
+                else:
+                    # for all subkeys, before and after design should be the same
+                    for subkey in list_element_attr(getattr(element, key)):
+                        if isinstance(getattr(getattr(element, key), subkey), list):
+                            assert getattr(getattr(element, key), subkey) == getattr(getattr(element_copy, key), subkey)
+                        elif isinstance(getattr(getattr(element, key), subkey), dict):
+                            for value1, value2 in zip(getattr(getattr(element, key), subkey).values(),
+                                                      getattr(getattr(element_copy, key), subkey).values()):
+                                assert all(value1 == value2)
+                        elif isinstance(getattr(getattr(element, key), subkey), ndarray):
+                            assert_allclose(getattr(getattr(element, key), subkey),
+                                            getattr(getattr(element_copy, key), subkey), rtol=1e-12)
+                        else:
+                            assert getattr(getattr(element, key), subkey) == getattr(getattr(element_copy, key), subkey)
+
+
+@pytest.mark.parametrize("restrictions, fail", [
+    ({'preamp_variety_list': [], 'booster_variety_list':[]}, False),
+    ({'preamp_variety_list': ['std_medium_gain', 'std_low_gain'], 'booster_variety_list':['std_medium_gain']}, False),
+    # the two next amp type_variety do not exist
+    ({'preamp_variety_list': [], 'booster_variety_list':['booster_medium_gain']}, True),
+    ({'preamp_variety_list': ['std_medium_gain', 'preamp_high_gain'], 'booster_variety_list':[]}, True)])
+def test_wrong_restrictions(restrictions, fail):
+    """Check that sanity_check correctly raises an error when restriction is incorrect and that library
+    correctly includes restrictions.
+    """
+    json_data = load_json(EQPT_LIBRARY_NAME)
+    # define wrong restriction
+    json_data['Roadm'][0]['restrictions'] = restrictions
+    if fail:
+        with pytest.raises(ConfigurationError):
+            _ = _equipment_from_json(json_data, EQPT_LIBRARY_NAME)
+    else:
+        equipment = _equipment_from_json(json_data, EQPT_LIBRARY_NAME)
+        assert equipment['Roadm']['example_test'].restrictions == restrictions
+
+
+@pytest.mark.parametrize('roadm, from_degree, to_degree, expected_impairment_id, expected_type', [
+    ('roadm Lannion_CAS', 'trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 1, 'add'),
+    ('roadm Lannion_CAS', 'west edfa in Lannion_CAS to Stbrieuc', 'east edfa in Lannion_CAS to Corlay', 0, 'express'),
+    ('roadm Lannion_CAS', 'west edfa in Lannion_CAS to Stbrieuc', 'trx Lannion_CAS', 2, 'drop'),
+    ('roadm h', 'west edfa in h to g', 'trx h', None, 'drop')
+])
+def test_roadm_impairments(roadm, from_degree, to_degree, expected_impairment_id, expected_type):
+    """Check that impairment id and types are correct
+    """
+    json_data = load_json(NETWORK_FILE_NAME)
+    for el in json_data['elements']:
+        if el['uid'] == 'roadm Lannion_CAS':
+            el['type_variety'] = 'example_detailed_impairments'
+    equipment = load_equipment(EQPT_LIBRARY_NAME)
+    network = network_from_json(json_data, equipment)
+    build_network(network, equipment, 0.0, 20.0)
+    roadm = next(n for n in network.nodes() if n.uid == roadm)
+    assert roadm.get_roadm_path(from_degree, to_degree).path_type == expected_type
+    assert roadm.get_roadm_path(from_degree, to_degree).impairment_id == expected_impairment_id
+
+
+@pytest.mark.parametrize('type_variety, from_degree, to_degree, impairment_id, expected_type', [
+    (None, 'trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 1, 'add'),
+    ('default', 'trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 3, 'add'),
+    (None, 'west edfa in Lannion_CAS to Stbrieuc', 'east edfa in Lannion_CAS to Corlay', None, 'express')
+])
+def test_roadm_per_degree_impairments(type_variety, from_degree, to_degree, impairment_id, expected_type):
+    """Check that impairment type is correct also if per degree impairment is defined
+    """
+    json_data = load_json(EQPT_LIBRARY_NAME)
+    assert 'type_variety' not in json_data['Roadm'][2]
+    json_data['Roadm'][2]['roadm-path-impairments'] = [
+        {
+            "roadm-path-impairments-id": 1,
+            "roadm-add-path": [{
+                "frequency-range": {
+                    "lower-frequency": 191.3e12,
+                    "upper-frequency": 196.1e12
+                },
+                "roadm-osnr": 41,
+            }]
+        }, {
+            "roadm-path-impairments-id": 3,
+            "roadm-add-path": [{
+                "frequency-range": {
+                    "lower-frequency": 191.3e12,
+                    "upper-frequency": 196.1e12
+                },
+                "roadm-inband-crosstalk": 0,
+                "roadm-osnr": 20,
+                "roadm-noise-figure": 23
+            }]
+        }]
+    equipment = _equipment_from_json(json_data, EQPT_LIBRARY_NAME)
+    assert equipment['Roadm']['default'].type_variety == 'default'
+
+    json_data = load_json(NETWORK_FILE_NAME)
+    for el in json_data['elements']:
+        if el['uid'] == 'roadm Lannion_CAS' and type_variety is not None:
+            el['type_variety'] = type_variety
+            el['params'] = {
+                "per_degree_impairments": [
+                    {
+                        "from_degree": from_degree,
+                        "to_degree": to_degree,
+                        "impairment_id": impairment_id
+                    }]
+            }
+    network = network_from_json(json_data, equipment)
+    build_network(network, equipment, 0.0, 20.0)
+    roadm = next(n for n in network.nodes() if n.uid == 'roadm Lannion_CAS')
+    assert roadm.get_roadm_path(from_degree, to_degree).path_type == expected_type
+    assert roadm.get_roadm_path(from_degree, to_degree).impairment_id == impairment_id
+
+
+@pytest.mark.parametrize('from_degree, to_degree, impairment_id, error, message', [
+    ('trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 2, NetworkTopologyError,
+     'Roadm roadm Lannion_CAS path_type is defined as drop but it should be add'),  # wrong path_type
+    ('trx Lannion_CAS', 'east edfa toto', 1, ConfigurationError,
+     'Roadm roadm Lannion_CAS has wrong from-to degree uid trx Lannion_CAS - east edfa toto'),  # wrong degree
+    ('trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 11, NetworkTopologyError,
+     'ROADM roadm Lannion_CAS: impairment profile id 11 is not defined in library')  # wrong impairment_id
+])
+def test_wrong_roadm_per_degree_impairments(from_degree, to_degree, impairment_id, error, message):
+    """Check that wrong per degree definitions are correctly catched
+    """
+    equipment = load_equipment(EQPT_LIBRARY_NAME)
+    json_data = load_json(NETWORK_FILE_NAME)
+    for el in json_data['elements']:
+        if el['uid'] == 'roadm Lannion_CAS':
+            el['type_variety'] = 'example_detailed_impairments'
+            el['params'] = {
+                "per_degree_impairments": [
+                    {
+                        "from_degree": from_degree,
+                        "to_degree": to_degree,
+                        "impairment_id": impairment_id
+                    }]
+            }
+    network = network_from_json(json_data, equipment)
+    with pytest.raises(error, match=message):
+        build_network(network, equipment, 0.0, 20.0)
+
+
+@pytest.mark.parametrize('path_type, type_variety, expected_pmd, expected_pdl, expected_osnr, freq', [
+    ('express', 'default', 5.0e-12, 0.5, None, [191.3e12]),  # roadm instance parameters pre-empts library
+    ('express', 'example_test', 5.0e-12, 0.5, None, [191.3e12]),
+    ('express', 'example_detailed_impairments', 0, 0, None, [191.3e12]),  # detailed parameters pre-empts global ones
+    ('add', 'default', 5.0e-12, 0.5, None, [191.3e12]),
+    ('add', 'example_test', 5.0e-12, 0.5, None, [191.3e12]),
+    ('add', 'example_detailed_impairments', 0, 0, 41, [191.3e12]),
+    ('add', 'example_detailed_impairments', [0, 0], [0.5, 0], [35, 41], [188.5e12, 191.3e12])])
+def test_impairment_initialization(path_type, type_variety, expected_pmd, expected_pdl, expected_osnr, freq):
+    """Check that impairments are correctly initialized, with this order:
+    - use equipment roadm impairments if no impairment are set in the ROADM instance
+    - use roadm global impairment if roadm global impairment are set
+    - use roadm detailed impairment for the corresponding path_type if roadm type_variety has detailed impairments
+    - use roadm per degree impairment if they are defined
+    """
+    equipment = load_equipment(EQPT_LIBRARY_NAME)
+    extra_params = equipment['Roadm'][type_variety].__dict__
+    roadm_config = {
+        "uid": "roadm Lannion_CAS",
+        "params": {
+            "add_drop_osnr": 38,
+            "pmd": 5.0e-12,
+            "pdl": 0.5
+        }
+    }
+    if type_variety != 'default':
+        roadm_config["type_variety"] = type_variety
+    roadm_config['params'] = merge_amplifier_restrictions(roadm_config['params'], extra_params)
+    roadm = Roadm(**roadm_config)
+    roadm.set_roadm_paths(from_degree='tata', to_degree='toto', path_type=path_type)
+    assert roadm.get_roadm_path(from_degree='tata', to_degree='toto').path_type == path_type
+    assert_allclose(roadm.get_impairment('roadm-pmd', freq, from_degree='tata', degree='toto'),
+                    expected_pmd, rtol=1e-12)
+    assert_allclose(roadm.get_impairment('roadm-pdl', freq, from_degree='tata', degree='toto'),
+                    expected_pdl, rtol=1e-12)
+    if path_type == 'add':
+        # we assume for simplicity that add contribution is the same as drop contribution
+        # add_drop_osnr_db = 10log10(1/add_osnr + 1/drop_osnr)
+        if type_variety in ['default', 'example_test']:
+            assert_allclose(roadm.get_impairment('roadm-osnr', freq, from_degree='tata', degree='toto'),
+                            roadm.params.add_drop_osnr + lin2db(2), rtol=1e-12)
+        else:
+            assert_allclose(roadm.get_impairment('roadm-osnr', freq, from_degree='tata', degree='toto'),
+                            expected_osnr, rtol=1e-12)

tests/test_science_utils.py

@@ -10,10 +10,10 @@ from pathlib import Path
 from pandas import read_csv
 from numpy.testing import assert_allclose
 from numpy import array
+from copy import deepcopy
 import pytest
 
-from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information, Pref, \
-    ReferenceCarrier
+from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information
 from gnpy.core.elements import Fiber, RamanFiber
 from gnpy.core.parameters import SimParams
 from gnpy.tools.json_io import load_json
@@ -23,15 +23,15 @@ from gnpy.core.science_utils import RamanSolver
 TEST_DIR = Path(__file__).parent
 
 
+@pytest.mark.usefixtures('set_sim_params')
 def test_fiber():
     """Test the accuracy of propagating the Fiber."""
     fiber = Fiber(**load_json(TEST_DIR / 'data' / 'test_science_utils_fiber_config.json'))
-
+    fiber.ref_pch_in_dbm = 0.0
     # fix grid spectral information generation
     spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
-                                                            baud_rate=32e9, power=1e-3, spacing=50e9, tx_osnr=40.0,
-                                                            ref_carrier=
-                                                            ReferenceCarrier(baud_rate=32e9, slot_width=50e9))
+                                                            baud_rate=32e9, spacing=50e9, tx_osnr=40.0,
+                                                            tx_power=1e-3)
     # propagation
     spectral_info_out = fiber(spectral_info_input)
 
@@ -48,13 +48,11 @@ def test_fiber():
     baud_rate = array([32e9, 42e9, 64e9, 42e9, 32e9])
     signal = 1e-3 + array([0, -1e-4, 3e-4, -2e-4, +2e-4])
     delta_pdb_per_channel = [0, 0, 0, 0, 0]
-    pref = Pref(p_span0=0, p_spani=0, ref_carrier=None)
     spectral_info_input = create_arbitrary_spectral_information(frequency=frequency, slot_width=slot_width,
                                                                 signal=signal, baud_rate=baud_rate, roll_off=0.15,
                                                                 delta_pdb_per_channel=delta_pdb_per_channel,
-                                                                tx_osnr=40.0, ref_power=pref)
-
-    # propagation
+                                                                tx_osnr=40.0, tx_power=1e-3)
+    # propagation without Raman
     spectral_info_out = fiber(spectral_info_input)
 
     p_signal = spectral_info_out.signal
@@ -64,17 +62,29 @@ def test_fiber():
     assert_allclose(p_signal, expected_results['signal'], rtol=1e-3)
     assert_allclose(p_nli, expected_results['nli'], rtol=1e-3)
 
+    # propagation with Raman
+    SimParams.set_params({'raman_params': {'flag': True}})
+    spectral_info_out = fiber(spectral_info_input)
+
+    p_signal = spectral_info_out.signal
+    p_nli = spectral_info_out.nli
+
+    expected_results = read_csv(TEST_DIR / 'data' / 'test_fiber_flex_expected_with_raman_results.csv')
+    assert_allclose(p_signal, expected_results['signal'], rtol=1e-3)
+    assert_allclose(p_nli, expected_results['nli'], rtol=1e-3)
+
 
 @pytest.mark.usefixtures('set_sim_params')
 def test_raman_fiber():
     """Test the accuracy of propagating the RamanFiber."""
     # spectral information generation
     spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
-                                                            baud_rate=32e9, power=1e-3, spacing=50e9, tx_osnr=40.0,
-                                                            ref_carrier=ReferenceCarrier(baud_rate=32e9, slot_width=50e9))
+                                                            baud_rate=32e9, spacing=50e9, tx_osnr=40.0,
+                                                            tx_power=1e-3)
     SimParams.set_params(load_json(TEST_DIR / 'data' / 'sim_params.json'))
+    SimParams().raman_params.solver_spatial_resolution = 5
     fiber = RamanFiber(**load_json(TEST_DIR / 'data' / 'test_science_utils_fiber_config.json'))
-
+    fiber.ref_pch_in_dbm = 0.0
     # propagation
     spectral_info_out = fiber(spectral_info_input)
 
@@ -108,27 +118,25 @@ def test_fiber_lumped_losses_srs(set_sim_params):
     """Test the accuracy of Fiber with lumped losses propagation."""
     # spectral information generation
     spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
-                                                            baud_rate=32e9, power=1e-3, spacing=50e9, tx_osnr=40.0,
-                                                            ref_carrier=
-                                                            ReferenceCarrier(baud_rate=32e9, slot_width=50e9))
+                                                            baud_rate=32e9, spacing=50e9, tx_osnr=40.0,
+                                                            tx_power=1e-3)
 
-    SimParams.set_params(load_json(TEST_DIR / 'data' / 'sim_params.json'))
     fiber = Fiber(**load_json(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber_config.json'))
     raman_fiber = RamanFiber(**load_json(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber_config.json'))
 
     # propagation
     # without Raman pumps
-    stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering(
-        spectral_info_input, fiber)
+    SimParams.set_params({'raman_params': {'flag': True, 'order': 2}})
+    stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering(spectral_info_input, fiber)
     power_profile = stimulated_raman_scattering.power_profile
-    expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_pumps.csv', header=None)
+    expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_pumps.csv').values
     assert_allclose(power_profile, expected_power_profile, rtol=1e-3)
 
     # with Raman pumps
-    expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber.csv', header=None)
-    stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering(
-        spectral_info_input, raman_fiber)
+    SimParams.set_params({'raman_params': {'flag': True, 'order': 1, 'solver_spatial_resolution': 5}})
+    stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering(spectral_info_input, raman_fiber)
     power_profile = stimulated_raman_scattering.power_profile
+    expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber.csv').values
     assert_allclose(power_profile, expected_power_profile, rtol=1e-3)
 
     # without Stimulated Raman Scattering
@@ -136,3 +144,26 @@ def test_fiber_lumped_losses_srs(set_sim_params):
     stimulated_raman_scattering = RamanSolver.calculate_attenuation_profile(spectral_info_input, fiber)
     power_profile = stimulated_raman_scattering.power_profile
     assert_allclose(power_profile, expected_power_profile, rtol=1e-3)
+
+
+@pytest.mark.usefixtures('set_sim_params')
+def test_nli_solver():
+    """Test the accuracy of NLI solver."""
+    fiber = Fiber(**load_json(TEST_DIR / 'data' / 'test_science_utils_fiber_config.json'))
+    fiber.ref_pch_in_dbm = 0.0
+    # fix grid spectral information generation
+    spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
+                                                            baud_rate=32e9, spacing=50e9, tx_osnr=40.0,
+                                                            tx_power=1e-3)
+
+    SimParams.set_params(load_json(TEST_DIR / 'data' / 'sim_params.json'))
+    sim_params = SimParams()
+
+    spectral_info_output = fiber(deepcopy(spectral_info_input))
+
+    sim_params.nli_params.method = 'ggn_approx'
+    sim_params.raman_params.result_spatial_resolution = 10e3
+    spectral_info_output_approx = fiber(deepcopy(spectral_info_input))
+
+    assert_allclose(spectral_info_output.nli, spectral_info_output_approx.nli, rtol=1e-1)
+

tests/test_spectrum_assignment.py

@@ -33,7 +33,7 @@ SERVICE_FILENAME = DATA_DIR / 'testTopology_services_expected.json'
 
 grid = 0.00625e12
 slot = 0.0125e12
-guardband = 0.15e12
+guardband = 25.0e9
 cband_freq_min = 191.3e12
 cband_freq_max = 196.1e12
 
@@ -101,14 +101,15 @@ def test_wrong_values(nval, mval, setup):
 def test_aligned(nmin, nmax, setup):
     """Checks that the OMS grid is correctly aligned
 
-    Note that bitmap index uses guardband on both ends so that if nmin, nmax = -200, +200,
+    Note that bitmap index uses guardband on both ends so that if center frequencies nmin, nmax = -200, +200,
     min/max navalue in bitmap are -224, +223, which makes 223 -(-224) +1 frequencies.
     """
     network, oms_list = setup
     nguard = guardband / grid
     center = 193.1e12
-    freq_min = center + nmin * grid
-    freq_max = center + nmax * grid
+    # amplification band
+    freq_min = center + nmin * grid - guardband
+    freq_max = center + nmax * grid + guardband
     random_oms = oms_list[10]
 
     # We're always starting with full C-band
@@ -116,9 +117,9 @@ def test_aligned(nmin, nmax, setup):
     assert pytest.approx(nvalue_to_frequency(random_oms.spectrum_bitmap.freq_index_max) * 1e-12, abs=1e-12) == 196.1
     ind_max = len(random_oms.spectrum_bitmap.bitmap) - 1
 
-    # "inner" frequencies, without the guard baand
+    # "inner" frequencies, without the guard band
     inner_n_min = random_oms.spectrum_bitmap.getn(0) + nguard
-    inner_n_max = random_oms.spectrum_bitmap.getn(ind_max) - nguard + 1
+    inner_n_max = random_oms.spectrum_bitmap.getn(ind_max) - nguard
     assert inner_n_min == random_oms.spectrum_bitmap.freq_index_min
     assert inner_n_max == random_oms.spectrum_bitmap.freq_index_max
     assert inner_n_min == -288
@@ -136,7 +137,7 @@ def test_aligned(nmin, nmax, setup):
 
     ind_max = len(random_oms.spectrum_bitmap.bitmap) - 1
     inner_n_min = random_oms.spectrum_bitmap.getn(0) + nguard
-    inner_n_max = random_oms.spectrum_bitmap.getn(ind_max) - nguard + 1
+    inner_n_max = random_oms.spectrum_bitmap.getn(ind_max) - nguard
     assert inner_n_min == random_oms.spectrum_bitmap.freq_index_min
     assert inner_n_max == random_oms.spectrum_bitmap.freq_index_max
 
@@ -198,18 +199,20 @@ def test_assign_and_sum(nval1, nval2, setup):
 
 def test_bitmap_assignment(setup):
     """test that a bitmap can be assigned"""
-    network, oms_list = setup
+    _, oms_list = setup
     random_oms = oms_list[2]
     random_oms.assign_spectrum(13, 7)
 
     btmp = deepcopy(random_oms.spectrum_bitmap.bitmap)
     # try a first assignment that must pass
-    spectrum_btmp = Bitmap(cband_freq_min, cband_freq_max, grid=0.00625e12, guardband=0.15e12, bitmap=btmp)
+    freq_min = nvalue_to_frequency(random_oms.spectrum_bitmap.n_min)
+    freq_max = nvalue_to_frequency(random_oms.spectrum_bitmap.n_max)
+    _ = Bitmap(freq_min, freq_max, grid=0.00625e12, guardband=guardband, bitmap=btmp)
 
     # try a wrong assignment that should not pass
     btmp = btmp[1:-1]
     with pytest.raises(SpectrumError):
-        spectrum_btmp = Bitmap(cband_freq_min, cband_freq_max, grid=0.00625e12, guardband=0.15e12, bitmap=btmp)
+        _ = Bitmap(cband_freq_min, cband_freq_max, grid=0.00625e12, guardband=guardband, bitmap=btmp)
 
 
 @pytest.fixture()
@@ -288,6 +291,7 @@ def request_set():
         'cost': 1,
         'roll_off': 0.15,
         'tx_osnr': 38,
+        'tx_power': 0.001,
         'penalties': {},
         'min_spacing': 37.5e9,
         'nb_channel': None,

tests/test_trx_mode_params.py

@@ -0,0 +1,156 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+# @Author: Esther Le Rouzic
+# @Date:   2023-09-29
+"""
+@author: esther.lerouzic
+checks all possibilities of this function
+
+"""
+
+from pathlib import Path
+import pytest
+
+from gnpy.core.equipment import trx_mode_params
+from gnpy.core.exceptions import EquipmentConfigError
+from gnpy.tools.json_io import load_equipment, load_json, _equipment_from_json
+
+
+TEST_DIR = Path(__file__).parent
+EQPT_LIBRARY_NAME = TEST_DIR / 'data/eqpt_config.json'
+NETWORK_FILE_NAME = TEST_DIR / 'data/testTopology_expected.json'
+
+
+@pytest.mark.parametrize('trx_type, trx_mode, error_message, no_error, expected_result',
+    [('', '', False, True, "SI"),
+     ('', '', True, False, 'Could not find transponder "" in equipment library'),
+     ('vendorA_trx-type1', '', True, False,
+      'Could not find transponder "vendorA_trx-type1" with mode "" in equipment library'),
+     ('vendorA_trx-type1', '', False, True, "SI"),
+     ('', 'mode 1', True, False, 'Could not find transponder "" in equipment library'),
+     ('', 'mode 1', False, True, "SI"),
+     ('vendorA_trx-type1', 'mode 2', True, True, 'mode 2'),
+     ('vendorA_trx-type1', 'mode 2', False, True, 'mode 2'),
+     ('wrong type', '', True, False, 'Could not find transponder "wrong type" in equipment library'),
+     ('wrong type', '', False, True, 'SI'),
+     ('vendorA_trx-type1', 'wrong mode', True, False,
+      'Could not find transponder "vendorA_trx-type1" with mode "wrong mode" in equipment library'),
+     ('vendorA_trx-type1', 'wrong mode', False, True, 'SI'),
+     ('wrong type', 'wrong mode', True, False, 'Could not find transponder "wrong type" in equipment library'),
+     ('wrong type', 'wrong mode', False, True, 'SI'),
+     ('vendorA_trx-type1', None, True, True, 'None'),
+     ('vendorA_trx-type1', None, False, True, 'None'),
+     (None, None, True, False, 'Could not find transponder "None" in equipment library'),
+     (None, None, False, True, 'SI'),
+     (None, 'mode 2', True, False, 'Could not find transponder "None" in equipment library'),
+     (None, 'mode 2', False, True, 'SI'),
+     ])
+def test_trx_mode_params(trx_type, trx_mode, error_message, no_error, expected_result):
+    """Checks all combinations of trx_type and mode
+    """
+    possible_results = {}
+    possible_results["SI"] = {
+        'OSNR': None,
+        'baud_rate': 32000000000.0,
+        'bit_rate': None,
+        'cost': None,
+        'equalization_offset_db': 0,
+        'f_max': 196100000000000.0,
+        'f_min': 191300000000000.0,
+        'min_spacing': None,
+        'penalties': {},
+        'roll_off': 0.15,
+        'spacing': 50000000000.0,
+        'tx_osnr': 100,
+    }
+    possible_results["mode 2"] = {
+        'format': 'mode 2',
+        'baud_rate': 64e9,
+        'OSNR': 15,
+        'bit_rate': 200e9,
+        'roll_off': 0.15,
+        'tx_osnr': 100,
+        'equalization_offset_db': 0,
+        'min_spacing': 75e9,
+        'f_max': 196100000000000.0,
+        'f_min': 191350000000000.0,
+        'penalties': {},
+        'cost': 1
+    }
+    possible_results["None"] = {
+        'format': 'undetermined',
+        'baud_rate': None,
+        'OSNR': None,
+        'bit_rate': None,
+        'roll_off': None,
+        'tx_osnr': None,
+        'equalization_offset_db': 0,
+        'min_spacing': None,
+        'f_max': 196100000000000.0,
+        'f_min': 191350000000000.0,
+        'penalties': None,
+        'cost': None
+    }
+    equipment = load_equipment(EQPT_LIBRARY_NAME)
+    if no_error:
+        trx_params = trx_mode_params(equipment, trx_type, trx_mode, error_message)
+        print(trx_params)
+        assert trx_params == possible_results[expected_result]
+    else:
+        with pytest.raises(EquipmentConfigError, match=expected_result):
+            _ = trx_mode_params(equipment, trx_type, trx_mode, error_message)
+
+
+@pytest.mark.parametrize('baudrate, spacing, error_message',
+    [(60e9, 50e9, 'Inconsistency in equipment library:\n Transponder "vendorB_trx-type1" mode "wrong mode" '
+                  + 'has baud rate 60.00 GHz greater than min_spacing 50.00.'),
+     (32e9, 50, 'Inconsistency in equipment library:\n Transponder "vendorB_trx-type1" mode "wrong mode" '
+                + 'has baud rate 32.00 GHz greater than min_spacing 0.00.')])
+def test_wrong_baudrate_spacing(baudrate, spacing, error_message):
+    """Checks wrong values for baudrate and spacing correctly raise an error
+    """
+    json_data = load_json(EQPT_LIBRARY_NAME)
+    wrong_transceiver = {
+        'type_variety': 'vendorB_trx-type1',
+        'frequency': {
+            'min': 191.35e12,
+            'max': 196.1e12
+        },
+        'mode': [{
+            'format': 'PS_SP64_1',
+            'baud_rate': 32e9,
+            'OSNR': 11,
+            'bit_rate': 100e9,
+            'roll_off': 0.15,
+            'tx_osnr': 100,
+            'min_spacing': 50e9,
+            'cost': 1,
+            'penalties': [{
+                'chromatic_dispersion': 80000,
+                'penalty_value': 0.5
+            }, {
+                'pmd': 120,
+                'penalty_value': 0.5}],
+            'equalization_offset_db': 0
+        }, {
+            'format': 'wrong mode',
+            'baud_rate': baudrate,
+            'OSNR': 11,
+            'bit_rate': 100e9,
+            'roll_off': 0.15,
+            'tx_osnr': 40,
+            'min_spacing': spacing,
+            'cost': 1,
+            'penalties': [{
+                'chromatic_dispersion': 80000,
+                'penalty_value': 0.5
+            }, {
+                'pmd': 120,
+                'penalty_value': 0.5}],
+            'equalization_offset_db': 0}]
+    }
+    json_data['Transceiver'].append(wrong_transceiver)
+    equipment = _equipment_from_json(json_data, EQPT_LIBRARY_NAME)
+
+    with pytest.raises(EquipmentConfigError, match=error_message):
+        _ = trx_mode_params(equipment, 'vendorB_trx-type1', 'wrong mode', error_message=False)

tox.ini

@@ -2,9 +2,8 @@
 skipsdist = True
 
 [testenv]
+extras = tests
 deps =
-	-r{toxinidir}/requirements.txt
-	-r{toxinidir}/tests/requirements.txt
 	cover: pytest-cov
 	linters: flake8
 	linters: pep8-naming
@@ -22,9 +21,8 @@ commands =
 	python -m build
 
 [testenv:docs]
-deps =
-	-r{toxinidir}/docs/requirements.txt
-whitelist_externals =
+extras = docs
+allowlist_externals =
 	/bin/sh
 commands =
 	sphinx-build -E -W --keep-going -q -b html docs/ doc/build/html
@@ -35,7 +33,7 @@ commands =
 	flake8 {posargs}
 
 [testenv:linters-diff-ci]
-whitelist_externals = bash
+allowlist_externals = bash
 commands =
 	flake8 {posargs} --format html --htmldir linters --exit-zero
 	bash -c "git diff -U0 origin/$(git rev-parse --abbrev-ref HEAD) | flake8 --diff {posargs}"