Add documentation for multiband

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

docs/json.rst

@@ -19,7 +19,7 @@ EDFA
 ~~~~
 
 The EDFA equipment library is a list of supported amplifiers. New amplifiers
-can be added and existing ones removed. Three different noise models are available:
+can be added and existing ones removed. Various noise models are available.
 
 1. ``'type_def': 'variable_gain'`` is a simplified model simulating a 2-coil EDFA with internal, input and output VOAs.
    The NF vs gain response is calculated accordingly based on the input parameters: ``nf_min``, ``nf_max``, and ``gain_flatmax``.
@@ -35,8 +35,12 @@ can be added and existing ones removed. Three different noise models are availab
    A detailed JSON configuration file is required (by default `gnpy/example-data/std_medium_gain_advanced_config.json <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/std_medium_gain_advanced_config.json>`_).
    It uses a 3rd order polynomial where NF = f(gain), NF_ripple = f(frequency), gain_ripple = f(frequency), N-array dgt = f(frequency).
    Compared to the previous models, NF ripple and gain ripple are modelled.
+6. ``'type_def': 'multi_band'`` defines an amplifier type corresponding to an amplification site composed of multiple amplifier elements, where each amplifies a different band of the spectrum.
+   The ``amplifiers`` list contains the list of single-band amplifier type varieties that can compose such multiband
+   amplifiers. Several options can be listed for the same spectrum band. Only one can be selected
+   for the actual :ref:`Multiband_amplifier<multiband_amps>` element.
 
-For all amplifier models:
+For all single band amplifier models:
 
 +------------------------+-----------+-----------------------------------------+
 | field                  |   type    | description                             |
@@ -55,6 +59,30 @@ For all amplifier models:
 |                        |           | be used as a manual input (from JSON or |
 |                        |           | Excel template topology files.)         |
 +------------------------+-----------+-----------------------------------------+
+| ``f_min``              | (number)  | Optional. In :math:`Hz`. Minimum and    |
+| and ``f_max``          |           | maximum frequency range for the         |
+|                        |           | amplifier. Signal must fit entirely     |
+|                        |           | within this range (center frequency and |
+|                        |           | spectrum width).                        |
+|                        |           | Default is 191.275e-12 Hz and           |
+|                        |           | 196.125e-12 (tunable in                 |
+|                        |           | default_edfa_config.json)               |
++------------------------+-----------+-----------------------------------------+
+
+
+For multi_band amplifier models:
+
++------------------------+-----------+-----------------------------------------+
+| field                  |   type    | description                             |
++========================+===========+=========================================+
+| ``type_variety``       | (string)  | A unique name to ID the amplifier in the|
+|                        |           | JSON template topology input file.      |
++------------------------+-----------+-----------------------------------------+
+| ``allowed_for_design`` | (boolean) | If false, the amplifier will not be     |
+|                        |           | picked by auto-design but it can still  |
+|                        |           | be used as a manual input (from JSON or |
+|                        |           | Excel template topology files.)         |
++------------------------+-----------+-----------------------------------------+
 
 Fiber
 ~~~~~
@@ -447,14 +475,14 @@ Here is an example:
       "uid": "roadm SITE1",
       "type": "Roadm",
       "type_variety": "detailed_impairments",
-	    "params": {
-		    "per_degree_impairments": [
-		    {
-			    "from_degree": "trx SITE1",
-		      "to_degree": "east edfa in SITE1 to ILA1",
-			    "impairment_id": 1
-		    }]
-	    }
+      "params": {
+        "per_degree_impairments": [
+        {
+          "from_degree": "trx SITE1",
+          "to_degree": "east edfa in SITE1 to ILA1",
+          "impairment_id": 1
+        }]
+      }
     }
 
 It is not permitted to use a roadm-path-impairment-id for the wrong roadm path type (add impairment only for add path).
@@ -492,6 +520,19 @@ See ``delta_power_range_db`` for more explaination.
 |                                             |           | mandatory when Raman amplification is       |
 |                                             |           | included in the simulation                  |
 +---------------------------------------------+-----------+---------------------------------------------+
+| ``raman_params.method``                     | (string)  | Model used for Raman evaluation. Valid      |
+|                                             |           | choices are ``perturbative`` (see           |
+|                                             |           | `arXiv:2304.11756                           |
+|                                             |           | <https://arxiv.org/abs/2304.11756>`_) and   |
+|                                             |           | ``numerical``, the GNPy legacy first order  |
+|                                             |           | derivative numerical solution.              |
++---------------------------------------------+-----------+---------------------------------------------+
+|``raman_params.order``                       |           | Order of the perturbative expansion.        |
+|                                             |           | For C- and C+L-band transmission scenarios  |
+|                                             |           | the second order provides high accuracy     |
+|                                             |           | considering common values of fiber input    |
+|                                             |           | power. (Default is 2)                       |
++---------------------------------------------+-----------+---------------------------------------------+
 | ``raman_params.result_spatial_resolution``  | (number)  | Spatial resolution of the output            |
 |                                             |           | Raman profile along the entire fiber span.  |
 |                                             |           | This affects the accuracy and the           |
@@ -503,11 +544,18 @@ See ``delta_power_range_db`` for more explaination.
 |                                             |           | channel around 0 dBm, a suggested value of  |
 |                                             |           | spatial resolution is 10e3 m                |
 +---------------------------------------------+-----------+---------------------------------------------+
-| ``raman_params.solver_spatial_resolution``  | (number)  | Spatial step for the iterative solution     |
-|                                             |           | of the first order differential equation    |
-|                                             |           | used to calculate the Raman profile         |
-|                                             |           | along the entire fiber span.                |
-|                                             |           | This affects the accuracy and the           |
+| ``raman_params.solver_spatial_resolution``  | (number)  | When using the ``perturbative`` method,     |
+|                                             |           | the step for the spatial integration does   |
+|                                             |           | not affect the first order. Therefore, a    |
+|                                             |           | large step can be used when no              |
+|                                             |           | counter-propagating Raman amplification is  |
+|                                             |           | present; a suggested value is 10e3 m.       |
+|                                             |           | In presence of counter-propagating Raman    |
+|                                             |           | amplification or when using the             |
+|                                             |           | ``numerical`` method the following remains  |
+|                                             |           | valid.                                      |
+|                                             |           | The spatial step for the iterative solution |
+|                                             |           | affects the accuracy and the                |
 |                                             |           | computational time of the evaluated         |
 |                                             |           | Raman profile:                              |
 |                                             |           | smaller the spatial resolution higher both  |
@@ -523,6 +571,10 @@ See ``delta_power_range_db`` for more explaination.
 |                                             |           | ``ggn_spectrally_separated`` (see eq. 21    |
 |                                             |           | from `arXiv:1710.02225                      |
 |                                             |           | <https://arxiv.org/abs/1710.02225>`_).      |
+|                                             |           | ``ggn_approx`` (see eq. 24-25               |
+|                                             |           | from `jlt:9741324                           |
+|                                             |           | <https://eeexplore.ieee.org/document/       |
+|                                             |           | 9741324>`_).                                |
 +---------------------------------------------+-----------+---------------------------------------------+
 | ``dispersion_tolerance``                    | (number)  | Optional. Pure number. Tuning parameter for |
 |                                             |           | ggn model solution. Default value is 1.     |
@@ -727,6 +779,10 @@ In the simplest case, homogeneous channel allocation can be defined via the ``Sp
 +----------------------+-----------+-------------------------------------------+
 | field                |   type    | description                               |
 +======================+===========+===========================================+
+| ``type_variety``     | (string)  | Optional. Default: ``default``            |
+|                      |           | A unique name to ID the band for          |
+|                      |           | propagation or design.                    |
++----------------------+-----------+-------------------------------------------+
 | ``f_min``,           | (number)  | In Hz. Define spectrum boundaries. Note   |
 | ``f_max``            |           | that due to backward compatibility, the   |
 |                      |           | first channel central frequency is placed |
@@ -793,6 +849,13 @@ In the simplest case, homogeneous channel allocation can be defined via the ``Sp
 |                      |           | transceiver OSNR.                         |
 +----------------------+-----------+-------------------------------------------+
 
+It is possible to define a set of bands in the SI block. In this case, type_variety must be used.
+Each set defines a reference channel used for design functions and autodesign processes.
+
+If no spectrum is defined (--spectrum or --services), then the same type of reference channel is
+also used for simulation.
+
+
 .. _mixed-rate:
 
 Arbitrary channel definition
@@ -843,7 +906,7 @@ For example this example:
 .. code-block:: json
 
  {
-   "SI":[
+   "spectrum":[
      {
        "f_min": 191.4e12,
        "f_max":193.1e12,
@@ -854,7 +917,7 @@ For example this example:
      },
      {
        "f_min": 193.1625e12,
-       "f_max":195e12,
+       "f_max": 195e12,
        "baud_rate": 64e9,
        "delta_pdb": 3,
        "slot_width": 75e9,
@@ -1100,6 +1163,8 @@ the maximum achievable total power.
 
 The exact layout used by simulation can be retrieved thanks to --save-network option.
 
+.. _operational_field:
+
 +----------------------+-----------+--------------------------------------------------+
 | field                |   type    | description                                      |
 +======================+===========+==================================================+
@@ -1155,6 +1220,63 @@ The exact layout used by simulation can be retrieved thanks to --save-network op
       }
     }
 
+.. _multiband_amps:
+
+Multiband_amplifier attributes
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
++----------------------+-----------+--------------------------------------------------+
+| field                |   type    | description                                      |
++======================+===========+==================================================+
+| ``type``             | (string)  | Mandatory: ``Multiband_amplifier``               |
++----------------------+-----------+--------------------------------------------------+
+| ``type_variety``     | (string)  | Optional, value must be listed in the library    |
+|                      |           | to be a valid type. If not defined, autodesign   |
+|                      |           | will pick one in the library among the           |
+|                      |           | ``allowed_for_design``.                          |
++----------------------+-----------+--------------------------------------------------+
+| ``amplifiers``       | (list of  | Optional, configuration settings of the          |
+|                      |  dict)    | amplifiers composing the multiband amplifier.    |
+|                      |           | Single band amplifier can be set with the        |
+|                      |           | parameters of tables:                            |
+|                      |           | :ref:`operational_field<operational_field>`:     |
++----------------------+-----------+--------------------------------------------------+
+
+Example of Multiband_amplifier element setting:
+
+    .. 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
+                  }
+              }
+          ]
+      }
+
+The frequency band of the element is the concatenation of the bands of each individual amplifier contained in
+the Multiband_amplifier element. Only carriers within these bands are propagated through the Multiband_amplifier
+element. If the user defines a spectrum larger than these bands, carriers that do not match the bands will be
+filtered out. The user can define the bandwidth of the amplifiers in the library. f_min and f_max represent the
+bandwidth of the amplifier (the entire channel must fit). The individual amplifier type_variety must be part of the
+allowed ``amplifiers`` list defined in the library.
+
 Roadm
 ~~~~~
 
@@ -1186,32 +1308,69 @@ Roadm
 |                                        |  dict)    | defined, it overrides the general values defined   |
 |                                        |           | by type_variety.                                   |
 +----------------------------------------+-----------+----------------------------------------------------+
+| ``design_bands``                       | (list of  | Optional. List of bands expressed as dictionnary,  |
+|                                        |  dict)    | e.g. {"f_min": 191.3e12, "f_max": 195.1e12}        |
+|                                        |           | To be considered for autodesign on all degrees of  |
+|                                        |           | the ROADM, if nothing is defined on the degrees.   |
++----------------------------------------+-----------+----------------------------------------------------+
+| ``per_degree_design_bands``            | (dict of  | Optional. If defined, it overrides ROADM's general |
+|                                        |  string,  | design_bands, on the degree identified with the    |
+|                                        |  list of  | key string. Value is a list of bands defined by    |
+|                                        |  dict)    | their frequency bounds ``f_min`` and ``f_max``     |
+|                                        |           | expressed in THz.                                  |
++----------------------------------------+-----------+----------------------------------------------------+
+
 
 Definition example:
 
-.. code-block:: json
+  .. code-block:: json
 
     {
       "uid": "roadm SITE1",
       "type": "Roadm",
       "type_variety": "detailed_impairments",
-	    "params": {
-		  "per_degree_impairments": [
-		    {
-			    "from_degree": "trx SITE1",
-		      "to_degree": "east edfa in SITE1 to ILA1",
-			    "impairment_id": 1
-		    }],
-          "per_degree_pch_out_db": {
+      "params": {
+        "per_degree_impairments": [
+          {
+            "from_degree": "trx SITE1",
+            "to_degree": "east edfa in SITE1 to ILA1",
+            "impairment_id": 1
+          }],
+        "per_degree_pch_out_db": {
             "east edfa in SITE1 to ILA1": -13.5
-          }
-	    }
+        }
+      }
     }
 
 In this example, all «implicit» express roadm-path are assigned as roadm-path-impairment-id = 0, and the target power is
 set according to the value defined in the library except for the direction heading to "east edfa in SITE1 to ILA1", where
 constant power equalization is used to reach -13.5 dBm target power.
 
+  .. code-block:: json
+
+    {
+      "uid": "roadm SITE1",
+      "type": "Roadm",
+      "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}
+          ]
+        }
+      }
+    }
+
+In this example the OMS starting from east edfa in SITE1 to ILA1 is defined as a multiband OMS. This means that
+if there is no setting in all or some of the amplifiers in the OMS, the autodesign function will select amplifiers
+from those that have ``multi_band`` ``type_def`` amplifiers.
+
+The default ``design_bands`` is inferred from the :ref:`SI<spectral_info>` block.
+
+Note that ``design_bands`` and ``type_variety`` amplifiers must be consistent:
+- you cannot mix single band and multiband amplifiers on the same OMS;
+- the frequency range of the amplifiers must include ``design_bands``.
+
 Fused
 ~~~~~
 
@@ -1221,7 +1380,7 @@ A fused element connected to the egress of a ROADM will disable the automatic bo
 
 Fused ``params`` only contains a ``loss`` value in dB.
 
-.. code-block:: json
+  .. code-block:: json
 
       "params": {
         "loss": 2

docs/release-notes.rst

@@ -6,6 +6,200 @@ 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.
 

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.
 
@@ -20,20 +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, calculate_absolute_min_or_zero
+    watt2dbm, psd2powerdbm, calculate_absolute_min_or_zero, nice_column_str
 from gnpy.core.parameters import RoadmParams, FusedParams, FiberParams, PumpParams, EdfaParams, EdfaOperational, \
-    RoadmPath, RoadmImpairment
+    MultiBandParams, RoadmPath, RoadmImpairment, TransceiverParams, find_band_name, FrequencyBand
 from gnpy.core.science_utils import NliSolver, RamanSolver
-from gnpy.core.info import SpectralInformation
+from gnpy.core.info import SpectralInformation, muxed_spectral_information, demuxed_spectral_information
 from gnpy.core.exceptions import NetworkTopologyError, SpectrumError, ParametersError
 
 
@@ -80,8 +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
@@ -96,6 +110,8 @@ class Transceiver(_Node):
         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.
@@ -239,7 +255,11 @@ class Roadm(_Node):
         if not params:
             params = {}
         try:
-            super().__init__(*args, params=RoadmParams(**params), **kwargs)
+            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
@@ -278,6 +298,8 @@ class Roadm(_Node):
                                                                                 "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):
@@ -311,6 +333,11 @@ class Roadm(_Node):
         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):
@@ -391,7 +418,7 @@ class Roadm(_Node):
         # 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_roadm_path(from_degree, degree).impairment.maxloss
+        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)
@@ -406,7 +433,7 @@ class Roadm(_Node):
         # the power out of the ROADM for the ref channel is the min value between target power and input power.
         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 - roadm_maxloss_db, ref_per_degree_pch)
+        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
@@ -438,11 +465,11 @@ class Roadm(_Node):
         spectral_info.apply_attenuation_db(delta_power)
 
         # Update the PMD information
-        pmd_impairment = self.get_roadm_path(from_degree=from_degree, to_degree=degree).impairment.pmd
+        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_roadm_path(from_degree=from_degree, to_degree=degree).impairment.pdl
+        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
@@ -460,13 +487,19 @@ class Roadm(_Node):
         """
         # initialize impairment with params.pmd, params.cd
         # if more detailed parameters are available for the Roadm, the use them instead
-        roadm_global_impairment = {'roadm-pmd': self.params.pmd,
-                                   'roadm-pdl': self.params.pdl}
+        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['roadm-osnr'] = self.params.add_drop_osnr + lin2db(2)
+            roadm_global_impairment['impairment'][0]['roadm-osnr'] = self.params.add_drop_osnr + lin2db(2)
         impairment = RoadmImpairment(roadm_global_impairment)
 
         if impairment_id is None:
@@ -507,6 +540,34 @@ class Roadm(_Node):
             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
@@ -886,19 +947,22 @@ class Edfa(_Node):
 
     @property
     def to_json(self):
-        return {'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,  # defined per lambda on the amp band
-                    'out_voa': self.out_voa
-                },
-                'metadata': {
-                    'location': self.metadata['location']._asdict()
-                }
-                }
+        _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': 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}, '
@@ -920,7 +984,8 @@ 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}',
@@ -1199,5 +1264,126 @@ class Edfa(_Node):
         self.propagated_labels = spectral_info.label
 
     def __call__(self, spectral_info):
-        self.propagate(spectral_info)
-        return 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)
+            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

@@ -7,8 +7,11 @@ 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.exceptions import EquipmentConfigError
+from gnpy.core.exceptions import EquipmentConfigError, ConfigurationError
 
 
 def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=False):
@@ -80,3 +83,50 @@ def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=F
 
     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
 
@@ -317,6 +317,56 @@ def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, spacing
                                                  tx_osnr=tx_osnr, tx_power=tx_power, label=label)
 
 
+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.

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
 
@@ -35,25 +36,32 @@ 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,
+    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
 
@@ -117,6 +125,8 @@ class RoadmParams(Parameters):
         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
@@ -134,7 +144,7 @@ class RoadmParams(Parameters):
         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 = dict({'path-type': authorized_path_types[path_type]}, **path_impairment[path_type][0])
+            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
 
@@ -155,26 +165,24 @@ class RoadmPath:
 
 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):
-        """Records roadm internal paths and types"""
         self.path_type = params.get('path-type')
-        self.pmd = params.get('roadm-pmd')
-        self.cd = params.get('roadm-cd')
-        self.pdl = params.get('roadm-pdl')
-        self.inband_crosstalk = params.get('roadm-inband-crosstalk')
-        self.maxloss = params.get('roadm-maxloss', 0)
-        if params.get('frequency-range') is not None:
-            self.fmin = params.get('frequency-range')['lower-frequency']
-            self.fmax = params.get('frequency-range')['upper-frequency']
-        else:
-            self.fmin, self.fmax = None, None
-        self.osnr = params.get('roadm-osnr', None)
-        self.pmax = params.get('roadm-pmax', None)
-        self.nf = params.get('roadm-noise-figure', None)
-        self.minloss = params.get('minloss', None)
-        self.typloss = params.get('typloss', None)
-        self.pmin = params.get('pmin', None)
-        self.ptyp = params.get('ptyp', None)
+        self.impairments = params['impairment']
 
 
 class FusedParams(Parameters):
@@ -463,10 +471,10 @@ class FiberParams(Parameters):
 
 class EdfaParams:
     default_values = {
-        'f_min': 191.3e12,
-        'f_max': 196.1e12,
+        'f_min': None,
+        'f_max': None,
         'multi_band': None,
-        'bands': [],
+        'bands': None,
         'type_variety': '',
         'type_def': '',
         'gain_flatmax': None,
@@ -502,9 +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']
@@ -591,7 +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:
@@ -599,7 +609,7 @@ class EdfaOperational:
         'gain_target': None,
         'delta_p': None,
         'out_voa': None,
-        'tilt_target': 0
+        'tilt_target': None
     }
 
     def __init__(self, **operational):
@@ -614,3 +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
         """
-        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]
+        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])
+        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)
@@ -324,6 +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.')
 
@@ -526,6 +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

@@ -12,6 +12,7 @@ from csv import writer
 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
 
@@ -458,3 +459,69 @@ def calculate_absolute_min_or_zero(x: array) -> array:
     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

@@ -5,8 +5,8 @@
   "gain_ripple": [
     0.0
   ],
-  "f_min": 191.35e12,
-  "f_max": 196.1e12,
+  "f_min": 191.275e12,
+  "f_max": 196.125e12,
   "dgt": [
     1.0,
     1.017807767853702,

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/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/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 add_missing_elements_in_network, design_network
 from gnpy.core.parameters import SimParams
-from gnpy.core.utils import db2lin, lin2db, automatic_nch, watt2dbm, dbm2watt
-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:
@@ -173,107 +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)
-    trx_params['power'] = dbm2watt(equipment['SI']['default'].power_dbm)
-    trx_params['tx_power'] = dbm2watt(equipment['SI']['default'].power_dbm)
-    if args.power:
-        trx_params['power'] = dbm2watt(float(args.power))
-        trx_params['tx_power'] = dbm2watt(float(args.power))
-    params.update(trx_params)
     initial_spectrum = None
-    params['nb_channel'] = automatic_nch(trx_params['f_min'], trx_params['f_max'], trx_params['spacing'])
-    # use ref_req to hold reference channel used for design and req for the propagation
-    # and req to hold channels to be propagated
-    # apply power sweep on the design and on the channels
-    ref_req = PathRequest(**params)
-    pref_ch_db = watt2dbm(ref_req.power)
     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)
-        params['nb_channel'] = len(initial_spectrum)
         print('User input for spectrum used for propagation instead of SI')
-    req = PathRequest(**params)
-    p_ch_db = watt2dbm(req.power)
-    req.initial_spectrum = initial_spectrum
-    print(f'There are {req.nb_channel} channels propagating')
     power_mode = equipment['Span']['default'].power_mode
     print('\n'.join([f'Power mode is set to {power_mode}',
                      '=> it can be modified in eqpt_config.json - Span']))
-    if not args.no_insert_edfas:
-        try:
-            add_missing_elements_in_network(network, equipment)
-        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)
-    spans = [s.params.length for s in path if isinstance(s, RamanFiber) or isinstance(s, Fiber)]
-    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:
-            print('invalid power range definition in eqpt_config, should be power_range_db: [lower, upper, step]')
-    # initial network is designed using req.power. that is that any missing information (amp gain or delta_p) is filled
-    # using this req.power, previous to any sweep requested later on.
+    # Simulate !
     try:
-        design_network(ref_req, network, equipment, set_connector_losses=True, verbose=True)
+        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)
-
+    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}:')
-    for dp_db in power_range:
-        ref_req.power = dbm2watt(pref_ch_db + dp_db)
-        req.power = dbm2watt(p_ch_db + dp_db)
-        design_network(ref_req, network, equipment, set_connector_losses=False, verbose=False)
-        # 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)
+    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:
-            print(f'\nPropagating with input power = {ansi_escapes.cyan}{watt2dbm(req.power):.2f} '
+            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}')
@@ -339,111 +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
-    if not args.no_insert_edfas:
-        try:
-            add_missing_elements_in_network(network, equipment)
-        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'Network (after autodesign) saved to {args.save_network}')
 
-    params = {
-        'request_id': 'reference',
-        'trx_type': '',
-        'trx_mode': '',
-        'source': None,
-        'destination': None,
-        'bidir': False,
-        'nodes_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': dbm2watt(equipment['SI']['default'].power_dbm)
-    }
-    trx_params = trx_mode_params(equipment)
-    params.update(trx_params)
-    reference_channel = PathRequest(**params)
     try:
-        design_network(reference_channel, network, equipment, verbose=True)
+        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/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, dbm2watt
-from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT, EdfaParams
+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
@@ -192,11 +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:
@@ -241,16 +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):
@@ -367,6 +378,31 @@ 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."""
     for roadm_type, roadm_eqpt in equipment['Roadm'].items():
@@ -428,7 +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
 
 
@@ -464,6 +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}"')
 
@@ -477,7 +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]:

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 +16,17 @@ 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
+
+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
@@ -332,19 +335,40 @@ def compute_constrained_path(network, req):
     return total_path
 
 
+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)
     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,
             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, from_degree=path[i - 1].uid)
-            roadm_osnr.append(el.get_roadm_path(from_degree=path[i - 1].uid, to_degree=path[i + 1].uid).impairment.osnr)
+            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)
@@ -385,11 +409,13 @@ def propagate_and_optimize_mode(path, req, 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, from_degree=path[i - 1].uid)
-                    roadm_osnr.append(el.get_roadm_path(from_degree=path[i - 1].uid, to_degree=path[i + 1].uid).impairment.osnr)
+                    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:
@@ -1071,7 +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 !
@@ -1080,6 +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
@@ -1097,7 +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
-        network_module.design_network(pathreq, network, equipment, set_connector_losses=False, verbose=False)
+        # 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)
@@ -1212,3 +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
 
 

tests/data/default_edfa_config.json

@@ -1,6 +1,6 @@
 {
-    "f_min": 191.35e12,
-    "f_max": 196.1e12,
+    "f_min": 191.275e12,
+    "f_max": 196.125e12,
     "nf_ripple": [
         0.0,
         0.0,

tests/data/eqpt_config.json

@@ -128,6 +128,19 @@
                         "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,
@@ -162,6 +175,7 @@
         }
     ],
     "SI": [{
+            "type_variety": "default",
             "f_min": 191.3e12,
             "f_max": 196.1e12,
             "baud_rate": 32e9,
@@ -171,7 +185,7 @@
             "roll_off": 0.15,
             "tx_osnr": 100,
             "sys_margins": 0
-            }],
+        }],
       "Transceiver":[
             {
             "type_variety": "vendorA_trx-type1",

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/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/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 @@
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tests/invocation/logs_path_request

@@ -4,6 +4,121 @@ WARNING  gnpy.tools.json_io:json_io.py
 	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

@@ -3,6 +3,26 @@ 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

@@ -2,8 +2,8 @@ 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 = 'brest'
-INFO     gnpy.tools.cli_examples:cli_examples.py destination = 'rennes'
+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:
@@ -309,3 +309,70 @@ WARNING  gnpy.core.network:network.py
 	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

@@ -2,8 +2,8 @@ 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 = 'lannion'
-INFO     gnpy.tools.cli_examples:cli_examples.py destination = 'lorient'
+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:
@@ -309,3 +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
@@ -27,6 +33,7 @@ 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
@@ -49,6 +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
@@ -71,6 +79,7 @@ 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
@@ -90,6 +99,7 @@ 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
@@ -112,6 +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
@@ -131,6 +142,7 @@ 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
@@ -153,6 +165,7 @@ 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
@@ -172,6 +185,7 @@ 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
@@ -194,6 +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
@@ -213,6 +228,7 @@ 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
@@ -235,6 +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
@@ -261,7 +278,7 @@ Transceiver trx_Gothenburg
   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
@@ -27,6 +33,7 @@ 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
@@ -49,6 +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
@@ -71,6 +79,7 @@ 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)
+  tilt-target(dB)         0.00
   noise figure (dB):      11.43
   (including att_in)
   pad att_in (dB):        0.00
@@ -90,6 +99,7 @@ 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
@@ -112,6 +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
@@ -131,6 +142,7 @@ 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
@@ -153,6 +165,7 @@ 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
@@ -172,6 +185,7 @@ 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
@@ -194,6 +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
@@ -213,6 +228,7 @@ 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
@@ -235,6 +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
@@ -261,7 +278,7 @@ Transceiver trx_Gothenburg
   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
@@ -82,7 +81,7 @@
 	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
@@ -93,7 +92,21 @@
 	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
@@ -111,8 +124,6 @@
 	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
@@ -17,8 +16,6 @@
 	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

@@ -1,12 +1,18 @@
-There are 95 channels propagating
 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)
 
-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 = 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
@@ -17,8 +23,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = -2.50 dBm:
+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
@@ -29,8 +34,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = -2.00 dBm:
+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
@@ -41,8 +45,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = -1.50 dBm:
+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
@@ -53,8 +56,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = -1.00 dBm:
+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
@@ -65,8 +67,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = -0.50 dBm:
+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
@@ -77,8 +78,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = -0.00 dBm:
+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
@@ -89,8 +89,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = 0.50 dBm:
+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
@@ -101,8 +100,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = 1.00 dBm:
+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
@@ -113,8 +111,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = 1.50 dBm:
+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
@@ -125,8 +122,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = 2.00 dBm:
+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
@@ -137,8 +133,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = 2.50 dBm:
+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
@@ -149,8 +144,7 @@ Transceiver trx Rennes_STA
   PDL (dB):                  0.00
   Latency (ms):              0.98
   Actual pch out (dBm):      3.00
-
-Propagating with input power = 3.00 dBm:
+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

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
@@ -28,6 +34,7 @@ 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
@@ -72,6 +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
@@ -98,7 +106,7 @@ Transceiver trx Lorient_KMA
   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
@@ -28,6 +34,7 @@ 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
@@ -72,6 +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
@@ -98,7 +106,7 @@ Transceiver trx Lorient_KMA
   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

@@ -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 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 = 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
@@ -28,6 +34,7 @@ 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
@@ -50,6 +57,7 @@ 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
@@ -72,6 +80,7 @@ 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
@@ -94,6 +103,7 @@ 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
@@ -116,6 +126,7 @@ 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
@@ -138,6 +149,7 @@ 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
@@ -157,6 +169,7 @@ 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
@@ -179,6 +192,7 @@ 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
@@ -201,6 +215,7 @@ 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
@@ -223,6 +238,7 @@ 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
@@ -245,6 +261,7 @@ 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
@@ -267,6 +284,7 @@ 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
@@ -286,6 +304,7 @@ 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
@@ -308,6 +327,7 @@ 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
@@ -330,6 +350,7 @@ 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
@@ -349,6 +370,7 @@ 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
@@ -371,6 +393,7 @@ 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
@@ -393,6 +416,7 @@ 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
@@ -415,6 +439,7 @@ 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
@@ -441,7 +466,7 @@ Transceiver Site_B
   Latency (ms):              5.88
   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): 18.56 dB
 
 (No source node specified: picked Site_A)

tests/invocation/transmission_long_psd

@@ -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 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)
 
-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 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
@@ -28,6 +34,7 @@ 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
@@ -50,6 +57,7 @@ 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
@@ -72,6 +80,7 @@ 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
@@ -94,6 +103,7 @@ 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
@@ -116,6 +126,7 @@ 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
@@ -138,6 +149,7 @@ 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
@@ -157,6 +169,7 @@ 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
@@ -179,6 +192,7 @@ 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
@@ -201,6 +215,7 @@ 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
@@ -223,6 +238,7 @@ 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
@@ -245,6 +261,7 @@ 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
@@ -267,6 +284,7 @@ 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
@@ -286,6 +304,7 @@ 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
@@ -308,6 +327,7 @@ 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
@@ -330,6 +350,7 @@ 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
@@ -349,6 +370,7 @@ 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
@@ -371,6 +393,7 @@ 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
@@ -393,6 +416,7 @@ 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
@@ -415,6 +439,7 @@ 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
@@ -441,7 +466,7 @@ Transceiver Site_B
   Latency (ms):              5.88
   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): 18.94 dB
 
 (No source node specified: picked Site_A)

tests/invocation/transmission_long_psw

@@ -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 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)
 
-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 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
@@ -28,6 +34,7 @@ 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
@@ -50,6 +57,7 @@ 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
@@ -72,6 +80,7 @@ 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
@@ -94,6 +103,7 @@ 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
@@ -116,6 +126,7 @@ 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
@@ -138,6 +149,7 @@ 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
@@ -157,6 +169,7 @@ 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
@@ -179,6 +192,7 @@ 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
@@ -201,6 +215,7 @@ 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
@@ -223,6 +238,7 @@ 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
@@ -245,6 +261,7 @@ 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
@@ -267,6 +284,7 @@ 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
@@ -286,6 +304,7 @@ 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
@@ -308,6 +327,7 @@ 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
@@ -330,6 +350,7 @@ 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
@@ -349,6 +370,7 @@ 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
@@ -371,6 +393,7 @@ 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
@@ -393,6 +416,7 @@ 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
@@ -415,6 +439,7 @@ 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
@@ -441,7 +466,7 @@ Transceiver Site_B
   Latency (ms):              5.88
   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): 18.94 dB
 
 (No source node specified: picked Site_A)

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
@@ -30,6 +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
@@ -50,7 +57,7 @@ Transceiver Site_B
   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
@@ -34,6 +40,7 @@ Edfa Edfa1
   type_variety:           std_low_gain
   effective gain(dB):     5.26
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      13.74
   (including att_in)
   pad att_in (dB):        2.74
@@ -54,7 +61,7 @@ Transceiver Site_B
   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): 31.44 dB
 
 The GSNR per channel at the end of the line is:

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
@@ -27,6 +33,7 @@ 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
@@ -49,6 +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
@@ -71,6 +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
@@ -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
@@ -115,6 +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
@@ -137,6 +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
@@ -156,6 +168,7 @@ 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
@@ -178,6 +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
@@ -200,6 +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
@@ -222,6 +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
@@ -244,6 +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
@@ -266,6 +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
@@ -285,6 +303,7 @@ 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
@@ -307,6 +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
@@ -329,6 +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
@@ -348,6 +369,7 @@ 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
@@ -370,6 +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
@@ -392,6 +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
@@ -414,6 +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
@@ -440,7 +465,7 @@ Transceiver Site_B
   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
@@ -27,6 +33,7 @@ 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
@@ -71,6 +78,7 @@ Edfa west edfa in Lorient_KMA to Loudeac
   type_variety:           std_medium_gain
   effective gain(dB):     27.99
   (before att_in and before output VOA)
+  tilt-target(dB)         0.00
   noise figure (dB):      5.98
   (including att_in)
   pad att_in (dB):        0.00
@@ -97,7 +105,7 @@ Transceiver trx Lorient_KMA
   Latency (ms):              0.64
   Actual pch out (dBm):      3.00
 
-Transmission result for input power = 3.00 dBm:
+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/test_amplifier.py

@@ -9,7 +9,7 @@ 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, network_from_json
+from gnpy.tools.json_io import load_network, load_equipment, load_json, _equipment_from_json, network_from_json
 from pathlib import Path
 import pytest
 
@@ -251,35 +251,35 @@ def test_amp_behaviour(tilt_target, delta_p):
     else:
         if delta_p != 2:
             expected_sig_out = [
-                -32.00529182, -31.93540907, -31.86554231, -31.79417979, -31.71903263,
-                -31.6424009, -31.56531159, -31.48775435, -31.41468382, -31.35973323,
-                -31.32286555, -31.28602346, -31.2472908, -31.20086569, -31.14671746,
-                -31.08702653, -31.01341963, -30.93430243, -30.87791656, -30.84413339,
-                -30.81605918, -30.78824936, -30.76071036, -30.73319161, -30.70494101,
-                -30.67368479, -30.63941012, -30.60178381, -30.55585766, -30.5066561,
-                -30.43426575, -30.33848379, -30.24471112, -30.18220815, -30.15076699,
-                -30.11934744, -30.08776718, -30.05548097, -30.02250068, -29.98954302,
-                -29.95661362, -29.92370274, -29.8854762, -29.84193785, -29.79238328,
-                -29.72452662, -29.6385071, -29.54788144, -29.44581202, -29.33924103,
-                -29.23276107, -29.10289365, -28.91425473, -28.70204648, -28.50670713,
-                -28.3282514, -28.15895225, -28.009065, -27.87864672, -27.76315964,
-                -27.68523133, -27.62260405, -27.58076622]
+                -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 = [
-                -30.00529182, -29.93540907, -29.86554231, -29.79417979, -29.71903263,
-                -29.6424009, -29.56531159, -29.48775435, -29.41468382, -29.35973323,
-                -29.32286555, -29.28602346, -29.2472908, -29.20086569, -29.14671746,
-                -29.08702653, -29.01341963, -28.93430243, -28.87791656, -28.84413339,
-                -28.81605918, -28.78824936, -28.76071036, -28.73319161, -28.70494101,
-                -28.67368479, -28.63941012, -28.60178381, -28.55585766, -28.5066561,
-                -28.43426575, -28.33848379, -28.24471112, -28.18220815, -28.15076699,
-                -28.11934744, -28.08776718, -28.05548097, -28.02250068, -27.98954302,
-                -27.95661362, -27.92370274, -27.8854762, -27.84193785, -27.79238328,
-                -27.72452662, -27.6385071, -27.54788144, -27.44581202, -27.33924103,
-                -27.23276107, -27.10289365, -26.91425473, -26.70204648, -26.50670713,
-                -26.3282514, -26.15895225, -26.009065, -25.87864672, -25.76315964,
-                -25.68523133, -25.62260405, -25.58076622]
+                -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)
@@ -365,3 +365,143 @@ def test_set_out_voa():
     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_equalization.py

@@ -72,7 +72,8 @@ def test_equalization_combination_degree(delta_pdb_per_channel, degree, equaliza
                 "preamp_variety_list": [],
                 "booster_variety_list": []
             },
-            "roadm-path-impairments": []
+            "roadm-path-impairments": [],
+            "design_bands": None
         }
     }
     roadm = Roadm(**roadm_config)
@@ -124,7 +125,8 @@ def test_wrong_element_config(equalization_type):
             "restrictions": {
                 "preamp_variety_list": [],
                 "booster_variety_list": []
-            }
+            },
+            "design_bands": None
         },
         "metadata": {
             "location": {
@@ -236,7 +238,8 @@ def test_low_input_power(target_out, delta_pdb_per_channel, correction):
                 "preamp_variety_list": [],
                 "booster_variety_list": []
             },
-            "roadm-path-impairments": []
+            "roadm-path-impairments": [],
+            "design_bands": None
         },
         "metadata": {
             "location": {
@@ -290,7 +293,8 @@ def test_2low_input_power(target_out, delta_pdb_per_channel, correction):
                 "preamp_variety_list": [],
                 "booster_variety_list": []
             },
-            "roadm-path-impairments": []
+            "roadm-path-impairments": [],
+            "design_bands": None
         },
         "metadata": {
             "location": {

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,
@@ -37,6 +37,9 @@ SRC_ROOT = Path(__file__).parent.parent
      ['-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\t' \
-                   + '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
 
 

tests/test_network_functions.py

@@ -6,15 +6,20 @@
 
 from pathlib import Path
 import pytest
-from gnpy.core.exceptions import NetworkTopologyError
-from gnpy.core.network import span_loss, build_network
-from gnpy.tools.json_io import load_equipment, load_network, network_from_json
-from gnpy.core.utils import lin2db, automatic_nch
-from gnpy.core.elements import Fiber, Edfa
+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'
 
 
@@ -241,3 +246,506 @@ def test_design_non_amplified_link(elem1, elem2, expected_gain, expected_delta_p
         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_parser.py

@@ -232,7 +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 = []

tests/test_roadm_restrictions.py

@@ -596,11 +596,19 @@ def test_roadm_per_degree_impairments(type_variety, from_degree, to_degree, impa
         {
             "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
@@ -657,14 +665,15 @@ def test_wrong_roadm_per_degree_impairments(from_degree, to_degree, impairment_i
         build_network(network, equipment, 0.0, 20.0)
 
 
-@pytest.mark.parametrize('path_type, type_variety, expected_pmd, expected_pdl, expected_osnr', [
-    ('express', 'default', 5.0e-12, 0.5, None),  # roadm instance parameters pre-empts library
-    ('express', 'example_test', 5.0e-12, 0.5, None),
-    ('express', 'example_detailed_impairments', 0, 0, None),  # detailed parameters pre-empts global instance ones
-    ('add', 'default', 5.0e-12, 0.5, None),
-    ('add', 'example_test', 5.0e-12, 0.5, None),
-    ('add', 'example_detailed_impairments', 0, 0, 41)])
-def test_impairment_initialization(path_type, type_variety, expected_pmd, expected_pdl, expected_osnr):
+@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
@@ -687,13 +696,16 @@ def test_impairment_initialization(path_type, type_variety, expected_pmd, expect
     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 roadm.get_roadm_path(from_degree='tata', to_degree='toto').impairment.pmd == expected_pmd
-    assert roadm.get_roadm_path(from_degree='tata', to_degree='toto').impairment.pdl == expected_pdl
+    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 roadm.get_roadm_path(from_degree='tata',
-                                        to_degree='toto').impairment.osnr == roadm.params.add_drop_osnr + lin2db(2)
+            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 roadm.get_roadm_path(from_degree='tata', to_degree='toto').impairment.osnr == expected_osnr
+            assert_allclose(roadm.get_impairment('roadm-osnr', freq, from_degree='tata', degree='toto'),
+                            expected_osnr, rtol=1e-12)

tests/test_science_utils.py

@@ -10,6 +10,7 @@ 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
@@ -22,6 +23,7 @@ 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'))
@@ -50,8 +52,7 @@ def test_fiber():
                                                                 signal=signal, baud_rate=baud_rate, roll_off=0.15,
                                                                 delta_pdb_per_channel=delta_pdb_per_channel,
                                                                 tx_osnr=40.0, tx_power=1e-3)
-
-    # propagation
+    # propagation without Raman
     spectral_info_out = fiber(spectral_info_input)
 
     p_signal = spectral_info_out.signal
@@ -61,6 +62,17 @@ 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():
@@ -70,6 +82,7 @@ def test_raman_fiber():
                                                             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
@@ -108,23 +121,22 @@ def test_fiber_lumped_losses_srs(set_sim_params):
                                                             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
@@ -132,3 +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()