30 Commits
v2.9 ... v2.10

Author SHA1 Message Date
EstherLerouzic
0d236fd31e fix: remove unused invocation test file
Wrongly added by commit #4a071c5

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I337b8d4560cd7f2634fca7d242783da327127de5
2024-10-16 16:42:09 +00:00
EstherLerouzic
9a84e29433 fix: remove freq2wavelength that is already defined
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I8ef480460e689bfcb33116cd393ad92ed0e03338
2024-10-08 11:07:13 +00:00
‘Renato
143f63170e FIX: json indentation in example-data
Change-Id: If3585fc554638cb1e5f7e4564d10af29420b6159
2024-09-20 13:49:26 +00:00
EstherLerouzic
b2d7f883a1 Add documentation for topology, service and sim-params files
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I0d917b742acd91aa52403f1ac96a378bb3cd8497
2024-06-02 19:26:33 +02:00
EstherLerouzic
73dbdf3042 Add documentation for the roadm impairment feature
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ief7e79ef10edf098c49ab1a0164284e5ae604961
2024-06-02 19:26:33 +02:00
EstherLerouzic
4a071c53d7 feat: transform roadm-paths into list indexed with frequency band
to be conformed with ietf + to prepare for next multiband case

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: If71857ef7dff9eaaa4c16e3837d3500bcef2fa72
2024-06-02 19:26:33 +02:00
EstherLerouzic
dcde64a8db clean some leftover from previous refactor
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ibd6e32090155433d7b1aa5b6572f1fe07a4cbe4a
2024-06-02 19:26:33 +02:00
EstherLerouzic
38cc0e3cc5 feat: separate span power from tx power
gnpy currently uses the same parameter for tx output power and span
input power: this prevents from modelling low tx power effect.
This patch introduces a new tx-cannel-power and uses it to
propagate in ROADM.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Id3ac75e2cb617b513bdb38b51a52e05d15af46f5
2024-06-02 19:26:33 +02:00
EstherLerouzic
fb70413784 Refactor equipment and add some tests
This fixes error message for wrong trx type,  catches the case of
KeyError when trx_type is not part of the library.

removes power setting from this function: power out of transceiver or
at the input of span is nor defined in equipment Transceiver

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I15fa7cc772ab5c1a8c7637738eb83c2ddffa1219
2024-06-02 19:26:33 +02:00
EstherLerouzic
87e10c240e Add test on blocking due to PDL penalty
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I2d6a7f9ed0ff8ad6977bcfe1b78ed620bb0e848d
2024-06-02 19:26:33 +02:00
EstherLerouzic
43c1085be6 feat: apply per path_type ROADM OSNR
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I2b0838c9a217a7f918b2cf08c233aacdbf686a72
2024-06-02 19:26:33 +02:00
EstherLerouzic
4ace60bea2 Feat: apply roadm-path loss
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I87e27d5b653bdce814f43e4c9c1183fb51fbcc1e
2024-06-02 19:26:33 +02:00
EstherLerouzic
f950a6aee8 Feat: add detailed ROADM impairments per roadm-path
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I09c55dcff53ffb264609654cde0f1d8b9dc7fe9b
2024-06-02 19:26:33 +02:00
EstherLerouzic
fb4195c775 Feat: Enable multiple type_varieties for ROADM
This commit introduces the 'type_variety' attribute for ROADM elements,
allowing the use of different types of ROADM specifications instead of
being limited to the default one.

If no type variety name is provided in the eqpt_config, the 'default'
name is used for backward compatibility with libraries. Additionally,
if no type variety is defined in the ROADM element in the topology,
the default one is used for backward compatibility with topologies.

The 'type_variety' attribute is included in the 'to_json' and
'display' methods for ROADM elements.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I61a2491f994e47ad0b08cf8eaef30d6d855aa706
2024-06-02 19:26:33 +02:00
EstherLerouzic
29f42666e5 remove whites spaces and align parentheses
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I0f5f389a3cf20155ceb0e9d9f071d1334a5ad688
2024-06-02 19:26:33 +02:00
EstherLerouzic
9bf7f336e3 Update release notes of v2.9
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ib949ff81fa818886a69339117bc66290dc2685b0
2024-06-02 19:26:27 +02:00
EstherLerouzic
eed6564f11 Add power sweep functionality description in documentation
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ic8db566bc168f120ddb0016c91bcc1d24263548c
2024-06-02 19:17:07 +02:00
EstherLerouzic
fbb2f2c587 fix missing to_json export of computed_number_of_channels
The parameter was introduced in commit 9736f7c032
but the export to_json was not added.

In the next commits, it is necessary to compute Raman gain during the design
phase. The sim-params used for this computation are updated during the
design phase for speed reasons. To ensure the proper restoration of user
settings for propagation, the export must include all parameters. Therefore,
this commit adds 'computed_number_of_channels' to the JSON export. This allows
for the accurate recording of all user settings locally and enables their
restoration.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I221a6f614010edea9cf46c3a7d43c5be064ff09c
2024-06-01 19:17:50 +02:00
EstherLerouzic
44040c4d06 fix missing description of computed_number_of_channels
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I5c8d057dcdab535617eee8de3eccdd806cec403e
2024-06-01 09:11:56 +02:00
EstherLerouzic
ee9af69558 Improve doc to state when tilt is vs wavelength
add some text in the docs to explain that tilt can be expressed
vs freq or lambda depending on context:
advanced_model expresses dgt as a function of frequency,
while tilt target is still defined vs wavelength (common usage).

Change the variable to have explicit name when it is per wavelength,
or add a comment to help identifyper wavelength or per frequency
variables.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I7727f00b38244152b95954e981cc9da096bb3d1d
2024-05-24 07:11:02 +00:00
Esther Le Rouzic
ce21609fec Merge "fix: image of the script and documentation" 2024-05-22 14:24:26 +00:00
Esther Le Rouzic
a1289e6a9b Merge "feat: enable different sim_param vectors for multiple requests" 2024-05-22 14:19:35 +00:00
AndreaDAmico
138115e1d7 Frequency scaling description in release notes v2.8
Change-Id: I74f3d52a3cbc087b914ff18075869d2162b693ac
2024-05-16 01:23:27 -04:00
EstherLerouzic
ed41305f55 fix: image of the script and documentation
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ib022320efd36a2d912f7b443686d7fee137e48b1
2024-04-26 18:19:53 +02:00
EstherLerouzic
9736f7c032 feat: enable different sim_param vectors for multiple requests
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ia800a7b98b33b795cc3553500116be61c612e45c
2024-04-26 17:12:43 +02:00
EstherLerouzic
be7ae35db3 Refactor amp default in parameters
default parameters are shared between json and network function,
so it is better to have them on the parameters to avoid circular
dependency when importing modules

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ib9d41852e394586d36f74992c91f67f3330cc552
2024-04-25 17:51:56 +02:00
EstherLerouzic
2b4a4ab72c fix Raman gain estimation during design
- Replaced multiple calls to the span_loss function
  with recording the span loss result in the fiber elements,
  reducing computation time.
- Updated Raman gain estimation based on design target powers to ensure
  accurate Edfa gain calculation or gain reduction during design.
- display the computed and design Raman gain in RamanFiber string output
- do not add padding on Raman fibers
- Added to_json function to preserve user input SimParams values,
  which were previously overwritten by initializing SimParams
  with fake values during design.

Next step is to allow users to balance computation time and
target accuracy of the design by inputing their own SimParams
and ref channels design values.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I1ca4954d0621858cefb3d776a538131992cae3e3
2024-04-12 08:58:16 +02:00
EstherLerouzic
426c88432d fix: update README script animation
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I31381ddf3e372f34836416162c080a5205ef969d
2024-04-12 08:41:27 +02:00
AndreaDAmico
2a800b781f Bug fix: Raman coefficient properly scaled in non SSMF case
Before the Raman coefficient was normalized with respect the given effective area, instead of the reference.

Change-Id: I4c0547db4fbd0f823a9058022b93c1ca37d67b51
2024-04-11 01:21:02 -04:00
Jan Kundrát
8d1d3677ed docs: fix graphs on RTD
At OFC I was talking with the OpenROADM people, and it turned out that
our docs stopped rendering properly at RTD. It turned out that the build
started skipping the bindep.txt file at some (unknown) point in time.

Reported-by: Aparaajitha G L <aparaajitha.gomathinayakamlatha@utdallas.edu>
Change-Id: Ie9a4b61f36fb979fb5c109d02de06e0b2cbf270e
2024-03-29 19:23:08 +01:00
65 changed files with 4788 additions and 2474 deletions

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@@ -3,6 +3,8 @@ build:
os: ubuntu-22.04
tools:
python: "3.12"
apt_packages:
- graphviz
python:
install:

View File

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

View File

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

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

View File

@@ -154,6 +154,8 @@ it is suggested to include an estimation of the loss coefficient for the Raman p
a dictionary-like definition of the ``RamanFiber.params.loss_coef``
(e.g. ``loss_coef = {"value": [0.18, 0.18, 0.20, 0.20], "frequency": [191e12, 196e12, 200e12, 210e12]}``).
.. _transceiver:
Transceiver
~~~~~~~~~~~
@@ -235,6 +237,8 @@ for example:
}
]
.. _roadm:
ROADM
~~~~~
@@ -243,6 +247,10 @@ The user can only modify the value of existing parameters:
+-------------------------------+-----------+----------------------------------------------------+
| field | type | description |
+===============================+===========+====================================================+
| ``type_variety`` | (string) | Optional. Default: ``default`` |
| | | A unique name to ID the ROADM variety in the JSON |
| | | template topology input file. |
+-------------------------------+-----------+----------------------------------------------------+
| ``target_pch_out_db`` | (number) | Default :ref:`equalization strategy<equalization>` |
| or | | for this ROADM type. |
| ``target_psd_out_mWperGHz`` | | |
@@ -270,6 +278,189 @@ The user can only modify the value of existing parameters:
| | | insert a ``Fused`` node on the degree |
| | | output. |
+-------------------------------+-----------+----------------------------------------------------+
| ``roadm-path-impairments`` | (list of | Optional. List of ROADM path category impairments. |
| | dict) | |
+-------------------------------+-----------+----------------------------------------------------+
In addition to these general impairment, the user may define detailed set of impairments for add,
drop and express path within the the ROADM. The impairment description is inspired from the `IETF
CCAMP optical impairment topology <https://github.com/ietf-ccamp-wg/draft-ietf-ccamp-optical-impairment-topology-yang>`_
(details here: `ROADM attributes IETF <https://github.com/ietf-ccamp-wg/draft-ietf-ccamp-optical-impairment-topology-yang/files/4262135/ROADM.attributes_IETF_v8draft.pptx>`_).
The ``roadm-path-impairments`` list allows the definition of the list of impairments by internal path category (add, drop or express). Several additional paths can be defined -- add-path, drop-path or express-path. They are indexed and the related impairments are defined per band.
Each item should contain:
+--------------------------------+-----------+----------------------------------------------------+
| field | type | description |
+================================+===========+====================================================+
| ``roadm-path-impairments-id`` | (number) | A unique number to ID the impairments. |
+--------------------------------+-----------+----------------------------------------------------+
| ``roadm-express-path`` | (list) | List of the impairments defined per frequency |
| or | | range. The impairments are detailed in the |
| ``roadm-add-path`` | | following table. |
| or | | |
| ``roadm-drop-path`` | | |
| (mutually exclusive) | | |
+--------------------------------+-----------+----------------------------------------------------+
Here are the parameters for each path category and the implementation status:
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| field | Type | Description | Drop path | Add path | Express (thru) path |
+============================+===========+===========================================================+=============+=============+=====================+
| ``frequency-range`` | (list) | List containing ``lower-frequency`` and | | | |
| | | ``upper-frequency`` in Hz. | | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-maxloss`` | (number) | In dB. Default: 0 dB. Maximum expected path loss on this | Implemented | Implemented | Implemented |
| | | roadm-path assuming no additional path loss is added = | | | |
| | | minimum loss applied to channels when crossing the ROADM | | | |
| | | (worst case expected loss due to the ROADM). | | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-minloss`` | | The net loss from the ROADM input, to the output of the | Not yet | N.A. | N.A. |
| | | drop block (best case expected loss). | implemented | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-typloss`` | | The net loss from the ROADM input, to the output of the | Not yet | N.A. | N.A. |
| | | drop block (typical). | implemented | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-pmin`` | | Minimum power levels per carrier expected at the output | Not yet | N.A. | N.A. |
| | | of the drop block. | implemented | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-pmax`` | | (Add) Maximum (per carrier) power level permitted at the | Not yet | Not yet | N.A. |
| | | add block input ports. | implemented | implemented | |
| | | | | | |
| | | (Drop) Best case per carrier power levels expected at | | | |
| | | the output of the drop block. | | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-ptyp`` | | Typical case per carrier power levels expected at the | Not yet | N.A. | N.A. |
| | | output of the drop block. | implemented | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-noise-figure`` | | If the add (drop) path contains an amplifier, this is | Not yet | Not yet | N.A. |
| | | the noise figure of that amplifier inferred to the | Implemented | Implemented | |
| | | add (drop) port. | | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-osnr`` | (number) | (Add) Optical Signal-to-Noise Ratio (OSNR). | implemented | Implemented | N.A. |
| | | If the add path contains the ability to adjust the | | | |
| | | carrier power levels into an add path amplifier | | | |
| | | (if present) to a target value, | | | |
| | | this reflects the OSNR contribution of the | | | |
| | | add amplifier assuming this target value is obtained. | | | |
| | | | | | |
| | | (Drop) Expected OSNR contribution of the drop path | | | |
| | | amplifier(if present) | | | |
| | | for the case of additional drop path loss | | | |
| | | (before this amplifier) | | | |
| | | in order to hit a target power level (per carrier). | | | |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-pmd`` | (number) | PMD contribution of the specific roadm path. | Implemented | Implemented | Implemented |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-cd`` | | | Not yet | Not yet | Not yet |
| | | | Implemented | Implemented | Implemented |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-pdl`` | (number) | PDL contribution of the specific roadm path. | Implemented | Implemented | Implemented |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
| ``roadm-inband-crosstalk`` | | | Not yet | Not yet | Not yet |
| | | | Implemented | Implemented | Implemented |
+----------------------------+-----------+-----------------------------------------------------------+-------------+-------------+---------------------+
Here is a ROADM example with two add-path possible impairments:
.. code-block:: json
"roadm-path-impairments": [
{
"roadm-path-impairments-id": 0,
"roadm-express-path": [{
"frequency-range": {
"lower-frequency": 191.3e12,
"upper-frequency": 196.1e12
},
"roadm-maxloss": 16.5
}]
}, {
"roadm-path-impairments-id": 1,
"roadm-add-path": [{
"frequency-range": {
"lower-frequency": 191.3e12,
"upper-frequency": 196.1e12
},
"roadm-maxloss": 11.5,
"roadm-osnr": 41
}]
}, {
"roadm-path-impairments-id": 2,
"roadm-drop-path": [{
"frequency-range": {
"lower-frequency": 191.3e12,
"upper-frequency": 196.1e12
},
"roadm-pmd": 0,
"roadm-cd": 0,
"roadm-pdl": 0,
"roadm-maxloss": 11.5,
"roadm-osnr": 41
}]
}, {
"roadm-path-impairments-id": 3,
"roadm-add-path": [{
"frequency-range": {
"lower-frequency": 191.3e12,
"upper-frequency": 196.1e12
},
"roadm-pmd": 0,
"roadm-cd": 0,
"roadm-pdl": 0,
"roadm-maxloss": 11.5,
"roadm-osnr": 20
}]
}]
On this example, the express channel has at least 16.5 dB loss when crossing the ROADM express path with the corresponding impairment id.
roadm-path-impairments is optional. If present, its values are considered instead of the ROADM general parameters.
For example, if add-path specifies 0.5 dB PDL and the general PDL parameter states 1.0 dB, then 0.5 dB is applied for this roadm-path only.
If present in add and/or drop path, roadm-osnr replaces the portion of add-drop-osnr defined for the whole ROADM,
assuming that add and drop contribution aggregated in add-drop-osnr are identical:
.. math::
add\_drop\_osnr = - 10log10(1/add_{osnr} + 1/drop_{osnr})
when:
.. math::
add_{osnr} = drop_{osnr}
.. math::
add_{osnr} = drop_{osnr} = add\_drop\_osnr + 10log10(2)
The user can specify the roadm type_variety in the json topology ROADM instance. If no variety is defined, ``default`` ID is used.
The user can define the impairment type for each roadm-path using the degrees ingress/egress immediate neighbor elements and the roadm-path-impairment-id defined in the library for the corresponding type-variety.
Here is an example:
.. 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
}]
}
}
It is not permitted to use a roadm-path-impairment-id for the wrong roadm path type (add impairment only for add path).
If nothing is stated for impairments on roadm-paths, the program identifies the paths implicitly and assigns the first impairment_id that matches the type: if a transceiver is present on one degree, then it is an add/drop degree.
On the previous example, all «implicit» express roadm-path are assigned roadm-path-impairment-id = 0
Global parameters
-----------------
@@ -333,13 +524,37 @@ See ``delta_power_range_db`` for more explaination.
| | | from `arXiv:1710.02225 |
| | | <https://arxiv.org/abs/1710.02225>`_). |
+---------------------------------------------+-----------+---------------------------------------------+
| ``nli_params.computed_channels`` | (number) | The channels on which the NLI is |
| | | explicitly evaluated. |
| ``dispersion_tolerance`` | (number) | Optional. Pure number. Tuning parameter for |
| | | ggn model solution. Default value is 1. |
+---------------------------------------------+-----------+---------------------------------------------+
| ``phase_shift_tolerance`` | (number) | Optional. Pure number. Tuning parameter for |
| | | ggn model solution. Defaut value is 0.1. |
+---------------------------------------------+-----------+---------------------------------------------+
| ``nli_params.computed_channels`` | (list | Optional. The exact channel indices |
| | of | (starting from 1) on which the NLI is |
| | numbers) | explicitly evaluated. |
| | | The NLI of the other channels is |
| | | interpolated using ``numpy.interp``. |
| | | In a C-band simulation with 96 channels in |
| | | a 50 GHz spacing fix-grid we recommend at |
| | | one computed channel every 20 channels. |
| | | least one computed channel every 20 |
| | | channels. If this option is present, the |
| | | next option "computed_number_of_channels" |
| | | is ignored. If none of the options are |
| | | present, the NLI is computed for all |
| | | channels (no interpolation) |
+---------------------------------------------+-----------+---------------------------------------------+
| ``nli_params.computed_number_of_channels`` | (number) | Optional. The number of channels on which |
| | | the NLI is explicitly evaluated. |
| | | The channels are |
| | | evenly selected between the first and the |
| | | last carrier of the current propagated |
| | | spectrum. |
| | | The NLI of the other channels is |
| | | interpolated using ``numpy.interp``. |
| | | In a C-band simulation with 96 channels in |
| | | a 50 GHz spacing fix-grid we recommend at |
| | | least 6 channels. |
+---------------------------------------------+-----------+---------------------------------------------+
Span
@@ -472,6 +687,31 @@ Span configuration is not a list (which may change in later releases) and the us
}
}
Power sweep functionality is triggered when setting "power_range_db" in SI in the library. This defines a
list of reference powers on which a new design is performed and propagation is triggered
(only gnpy-transmission-example script).
for example, with the following settings:
- ``power_dbm`` = 0 dBm
- max power of the amplifier = 20 dBm,
- user defined ``delta_p`` set by user = 3 dB
- 80 channels, so :math:`pch_{max}` = 20 - 10log10(80) = 0.96 dBm
- ``delta_power_range_db`` = [-3, 0, 3]
- power_sweep -> power range [-3, 0] dBm
then the computation of delta_p during design for each power of this power sweep is:
- with :math:`p_{ref}` = 0 dBm, computed_delta_p = min(:math:`pch_{max}`, :math:`p_{ref}` + ``delta_p``) - :math:`p_{ref}` = 0.96 ;
- user defined ``delta_p`` = 3 dB **can not** be applied because of saturation,
- with :math:`p_{ref}` = -3 dBm (power sweep) computed_delta_p = min(:math:`pch_{max}`, :math:`p_{ref}` + ``delta_p``) - :math:`p_{ref}` =
min(0.96, -3.0 + 3.0) - (-3.0) = 3.0 ;
- user defined ``delta_p`` = 3 dB **can** be applied.
so the user defined delta_p is applied as much as possible.
.. _spectral_info:
SpectralInformation
~~~~~~~~~~~~~~~~~~~
@@ -529,6 +769,9 @@ In the simplest case, homogeneous channel allocation can be defined via the ``Sp
| | | If the ``--power`` CLI option is used, |
| | | its value replaces this parameter. |
+----------------------+-----------+-------------------------------------------+
| ``tx_power_dbm`` | (number) | In dBm. Optional. Power out from |
| | | transceiver. Default = power_dbm |
+----------------------+-----------+-------------------------------------------+
| ``power_range_db`` | (number) | Power sweep excursion around |
| | | ``power_dbm``. |
| | | This defines a list of reference powers |
@@ -585,6 +828,9 @@ In this approach, each partition is internally homogeneous, but different partit
| ``tx_osnr`` | (number) | In dB. Optional. OSNR out from |
| | | transponder. Default value is 40 dB. |
+----------------------+-----------+-------------------------------------------+
| ``tx_power_dbm`` | (number) | In dBm. Optional. Power out from |
| | | transceiver. Default value is 0 dBm |
+----------------------+-----------+-------------------------------------------+
| ``delta_pdb`` | (number) | In dB. Optional. Power offset compared to |
| | | the reference power used for design |
| | | (SI block in equipment library) to be |
@@ -688,3 +934,467 @@ With the PSW equalization:
the power out of the ROADM will be computed as 2.0e-4 * 50 = 0.01 mW ie -20 dBm for label 1 types of carriers
and 2.0e4 * 75 = 0.015 mW ie -18.24 dBm for label2 channels. So a ratio of ~ 1.76 dB between target powers for these carriers.
.. _topology:
Topology
--------
Topology file contains a list of elements and a list of connections between the elements to form a graph.
Elements can be:
- Fiber
- RamanFiber
- Edfa
- Fused
- Roadm
- Transceiver
Common attributes
~~~~~~~~~~~~~~~~~
All elements contain the followind attributes:
- **"uid"**: mandatory, element unique identifier.
- **"type"**: mandatory, element type among possible types (Fiber, RamanFiber, Edfa, Fused, Roadm, Transceiver).
- **"metadata"**: optional data including goelocation.
Fiber attributes/ RamanFiber attributes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+----------------------+-----------+--------------------------------------------------+
| field | type | description |
+======================+===========+==================================================+
| ``type_variety`` | (string) | optional, value must be listed in the |
| | | library to be a valid type. Default type |
| | | is SSMF. |
+----------------------+-----------+--------------------------------------------------+
| ``params`` | (dict of | see table below. |
| | numbers) | |
+----------------------+-----------+--------------------------------------------------+
+----------------------+-----------+--------------------------------------------------+
| params fields | type | description |
+======================+===========+==================================================+
| ``length`` | (number) | optional, length in ``length_units``, default |
| | | length is 80 km. |
+----------------------+-----------+--------------------------------------------------+
| ``length_units`` | (string) | Length unit of measurement. Default is "km". |
+----------------------+-----------+--------------------------------------------------+
| ``loss_coef`` | (number | In dB/km. Optional, loss coefficient. Default |
| | or dict) | is 0.2 dB/km. Slope of the loss can be defined |
| | | using a dict of frequency values such as |
| | | ``{"value": [0.18, 0.18, 0.20, 0.20], |
| | | "frequency": [191e12, 196e12, 200e12, 210e12]}`` |
+----------------------+-----------+--------------------------------------------------+
| ``att_in`` | (number) | In dB. Optional, attenuation at fiber input, for |
| | | padding purpose. Default is 0 dB. |
+----------------------+-----------+--------------------------------------------------+
| ``con_in`` | (number) | In dB. Optional, input connector loss. Default |
| | | is using value defined in library ``Span`` |
| | | section. |
+----------------------+-----------+--------------------------------------------------+
| ``con_out`` | (number) | In dB. Optional, output connector loss. Default |
| | | is using value defined in library ``Span`` |
| | | section. |
+----------------------+-----------+--------------------------------------------------+
.. code-block:: json
{
"uid": "fiber (A1->A2)",
"type": "Fiber",
"type_variety": "SSMF",
"params":
{
"length": 120.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0,
"con_in": 0,
"con_out": 0
}
}
The RamanFiber can be used to simulate Raman amplification through dedicated Raman pumps. The Raman pumps must be listed
in the key ``raman_pumps`` within the RamanFiber ``operational`` dictionary. The description of each Raman pump must
contain the following:
+---------------------------+-----------+------------------------------------------------------------+
| operational fields | type | description |
+===========================+===========+============================================================+
| ``power`` | (number) | Total pump power in :math:`W` |
| | | considering a depolarized pump |
+---------------------------+-----------+------------------------------------------------------------+
| ``frequency`` | (number) | Pump central frequency in :math:`Hz` |
+---------------------------+-----------+------------------------------------------------------------+
| ``propagation_direction`` | (string) | The pumps can propagate in the same or opposite direction |
| | | with respect the signal. Valid choices are ``coprop`` and |
| | | ``counterprop``, respectively |
+---------------------------+-----------+------------------------------------------------------------+
Beside the list of Raman pumps, the RamanFiber ``operational`` dictionary must include the ``temperature`` that affects
the amplified spontaneous emission noise generated by the Raman amplification.
As the loss coefficient significantly varies outside the C-band, where the Raman pumps are usually placed,
it is suggested to include an estimation of the loss coefficient for the Raman pump central frequencies within
a dictionary-like definition of the ``RamanFiber.params.loss_coef``
(e.g. ``loss_coef = {"value": [0.18, 0.18, 0.20, 0.20], "frequency": [191e12, 196e12, 200e12, 210e12]}``).
.. code-block:: json
{
"uid": "Span1",
"type": "RamanFiber",
"type_variety": "SSMF",
"operational": {
"temperature": 283,
"raman_pumps": [
{
"power": 224.403e-3,
"frequency": 205e12,
"propagation_direction": "counterprop"
},
{
"power": 231.135e-3,
"frequency": 201e12,
"propagation_direction": "counterprop"
}
]
},
"params": {
"type_variety": "SSMF",
"length": 80.0,
"loss_coef": {
"value": [0.18, 0.18, 0.20, 0.20],
"frequency": [191e12, 196e12, 200e12, 210e12]
},
"length_units": "km",
"att_in": 0,
"con_in": 0.5,
"con_out": 0.5
},
"metadata": {
"location": {
"latitude": 1,
"longitude": 0,
"city": null,
"region": ""
}
}
}
Edfa attributes
~~~~~~~~~~~~~~~
The user can specify the amplifier configurations, which are applied depending on general simulation setup:
- if the user has specified ``power_mode`` as True in Span section, delta_p is applied and gain_target is ignored and recomputed.
- if the user has specified ``power_mode`` as False in Span section, gain_target is applied and delta_p is ignored.
If the user has specified unfeasible targets with respect to the type_variety, targets might be changed accordingly.
For example, if gain_target leads to a power value above the maximum output power of the amplifier, the gain is saturated to
the maximum achievable total power.
The exact layout used by simulation can be retrieved thanks to --save-network option.
+----------------------+-----------+--------------------------------------------------+
| field | type | description |
+======================+===========+==================================================+
| ``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``. Autodesign selection is |
| | | based J. -L. Auge, V. Curri and E. Le Rouzic, |
| | | Open Design for Multi-Vendor Optical Networks |
| | | , OFC 2019. equation 4 |
+----------------------+-----------+--------------------------------------------------+
| ``operational`` | (dict of | Optional, configuration settings of the |
| | numbers) | amplifier. See table below |
+----------------------+-----------+--------------------------------------------------+
+----------------------+-----------+-------------------------------------------------------------+
| operational field | type | description |
+======================+===========+=============================================================+
| ``gain_target`` | (number) | In dB. Optional Gain target between in_voa and out_voa. |
| | | |
+----------------------+-----------+-------------------------------------------------------------+
| ``delta_p`` | (number) | In dB. Optional Power offset at the outpout of the |
| | | amplifier and before out_voa compared to reference channel |
| | | power defined in SI block of library. |
+----------------------+-----------+-------------------------------------------------------------+
| ``out_voa`` | (number) | In dB. Optional, output variable optical attenuator loss. |
+----------------------+-----------+-------------------------------------------------------------+
| ``in_voa`` | (number) | In dB. Optional, input variable optical attenuator loss. |
+----------------------+-----------+-------------------------------------------------------------+
| ``tilt_target`` | (number) | In dB. Optional, tilt target on the whole wavelength range |
| | | of the amplifier. |
+----------------------+-----------+-------------------------------------------------------------+
.. code-block:: json
{
"uid": "Edfa1",
"type": "Edfa",
"type_variety": "std_low_gain",
"operational": {
"gain_target": 15.0,
"delta_p": -2,
"tilt_target": -1,
"out_voa": 0
},
"metadata": {
"location": {
"latitude": 2,
"longitude": 0,
"city": null,
"region": ""
}
}
}
Roadm
~~~~~
+----------------------------------------+-----------+----------------------------------------------------+
| field | type | description |
+========================================+===========+====================================================+
| ``type_variety`` | (string) | Optional. If no variety is defined, ``default`` |
| | | ID is used. |
| | | A unique name must be used to ID the ROADM |
| | | variety in the JSON library file. |
+----------------------------------------+-----------+----------------------------------------------------+
| ``target_pch_out_db`` | (number) | :ref:`Equalization strategy<equalization>` |
| or | | for this ROADM. Optional: if not defined, the |
| ``target_psd_out_mWperGHz`` | | one defined in library for this type_variety is |
| or | | used. |
| ``target_out_mWperSlotWidth`` | | |
| (mutually exclusive) | | |
+----------------------------------------+-----------+----------------------------------------------------+
| ``restrictions`` | (dict of | Optional. If defined, it overrides restriction |
| | strings) | defined in library for this roadm type_variety. |
+----------------------------------------+-----------+----------------------------------------------------+
| ``per_degree_pch_out_db`` | (dict of | Optional. If defined, it overrides ROADM's general |
| or | string, | target power/psd for this degree. Dictionary with |
| ``per_degree_psd_out_mWperGHz`` | number) | key = degree name (uid of the immediate adjacent |
| or | | element) and value = target power/psd value. |
| ``per_degree_psd_out_mWperSlotWidth`` | | |
+----------------------------------------+-----------+----------------------------------------------------+
| ``per_degree_impairments`` | (list of | Optional. Impairments id for roadm-path. If |
| | dict) | defined, it overrides the general values defined |
| | | by type_variety. |
+----------------------------------------+-----------+----------------------------------------------------+
Definition example:
.. 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": {
"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.
Fused
~~~~~
The user can define concentrated losses thanks to Fused element. This can be useful for example to materialize connector with its loss between two fiber spans.
``params`` and ``loss`` are optional, loss of the concentrated loss is in dB. Default value is 0 dB.
A fused element connected to the egress of a ROADM will disable the automatic booster/preamp selection.
Fused ``params`` only contains a ``loss`` value in dB.
.. code-block:: json
"params": {
"loss": 2
}
Transceiver
~~~~~~~~~~~
Transceiver elements represent the logical function that generates a spectrum. This must be specified to start and stop propagation. However, the characteristics of the spectrum are defined elsewhere, so Transceiver elements do not contain any attribute.
Information on transceivers' type, modes and frequency must be listed in :ref:`service file<service>` or :ref:`spectrum file<mixed-rate>`. Without any definition, default :ref:`SI<spectral_info>` values of the library are propagated.
.. _service:
Service JSON file
-----------------
Service file lists all requests and their possible constraints. This is derived from draft-ietf-teas-yang-path-computation-01.txt:
gnpy-path-request computes performance of each request independantly from each other, considering full load (based on the request settings),
but computes spectrum occupation based on the list of request, so that the requests should not define overlapping spectrum.
Lack of spectrum leads to blocking, but performance estimation is still returned for information.
+-----------------------+-------------------+----------------------------------------------------------------+
| field | type | description |
+=======================+===================+================================================================+
| ``path-request`` | (list of | list of requests. |
| | request) | |
+-----------------------+-------------------+----------------------------------------------------------------+
| ``synchronization`` | (list of | Optional. List of synchronization vector. One synchronization |
| | synchronization) | vector contains the disjunction constraints. |
+-----------------------+-------------------+----------------------------------------------------------------+
- **"path-request"** list of requests made of:
+-----------------------+------------+----------------------------------------------------------------+
| field | type | description |
+=======================+============+================================================================+
| ``request-id`` | (number) | Mandatory. Unique id of request. The same id is referenced in |
| | | response with ``response-id``. |
+-----------------------+------------+----------------------------------------------------------------+
| ``source`` | (string) | Mandatory. Source of traffic. It must be one of the UID of |
| | | transceivers listed in the topology. |
+-----------------------+------------+----------------------------------------------------------------+
| ``src-tp-id`` | (string) | Mandatory. It must be equal to ``source``. |
+-----------------------+------------+----------------------------------------------------------------+
| ``destination`` | (string) | Mandatory. Destination of traffic. It must be one of the UID |
| | | of transceivers listed in the topology. |
+-----------------------+------------+----------------------------------------------------------------+
| ``dst-tp-id`` | (string) | Mandatory. It must be equal to ``destination``. |
+-----------------------+------------+----------------------------------------------------------------+
| ``bidirectional`` | (boolean) | Mandatory. Boolean indicating if the propagation should be |
| | | checked on source-destination only (false) or on |
| | | destination-source (true). |
+-----------------------+------------+----------------------------------------------------------------+
| ``path-constraints`` | (dict) | Mandatory. It contains the list of constraints including type |
| | | of transceiver, mode and nodes to be included in the path. |
+-----------------------+------------+----------------------------------------------------------------+
``path-constraints`` contains ``te-bandwidth`` with the following attributes:
+-----------------------------------+------------+----------------------------------------------------------------+
| field | type | description |
+===================================+============+================================================================+
| ``technology`` | (string) | Mandatory. Only one possible value ``flex-grid``. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``trx_type`` | (string) | Mandatory. Type of the transceiver selected for this request. |
| | | It must be listed in the library transceivers list. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``trx_mode`` | (string) | Optional. Mode selected for this path. It must be listed |
| | | within the library transceiver's modes. If not defined, |
| | | the gnpy-path-request script automatically selects the mode |
| | | that has performance above minimum required threshold |
| | | including margins and penalties for all channels (full load) |
| | | and 1) fit in the spacing, 2) has the largest baudrate, |
| | | 3) has the largest bitrate. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``spacing`` | (number) | Mandatory. In :math:`Hz`. Spacing is used for full spectral |
| | | load feasibility evaluation. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``path_bandwidth`` | (number) | Mandatory. In :math:`bit/s`. Required capacity on this |
| | | service. It is used to determine the needed number of channels |
| | | and spectrum occupation. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``max-nb-of-channel`` | (number) | Optional. Number of channels to take into account for the full |
| | | load computation. Default value is computed based on f_min |
| | | and f_max of transceiver frequency range and min_spacing of |
| | | mode (once selected). |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``output-power`` | (number) | Optional. In :math:`W`. Target power to be considered at the |
| | | fiber span input. Default value uses power defined in SI in |
| | | the library converted in Watt: |
| | | :math:`10^(power\_dbm/10)`. |
| | | |
| | | Current script gnpy-path-request redesign the network on each |
| | | new request, using this power together with |
| | | ``max-nb-of-channel`` to compute target gains or power in |
| | | amplifiers. This parameter can therefore be useful to test |
| | | different designs with the same script. |
| | | |
| | | In order to keep the same design for different requests, |
| | | ``max-nb-of-channel` and ``output-power`` of each request |
| | | should be kept identical. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``tx_power`` | (number) | Optional. In :math:`W`. Optical output power emitted by the |
| | | transceiver. Default value is output-power. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``effective-freq-slot`` | (list) | Optional. List of N, M values defining the requested spectral |
| | | occupation for this service. N, M use ITU-T G694.1 Flexible |
| | | DWDM grid definition. |
| | | For the flexible DWDM grid, the allowed frequency slots have a |
| | | nominal central frequency (in :math:`THz`) defined by: |
| | | 193.1 + N × 0.00625 where N is a positive or negative integer |
| | | including 0 |
| | | and 0.00625 is the nominal central frequency granularity in |
| | | :math:`THz` and a slot width defined by: |
| | | 12.5 × M where M is a positive integer and 12.5 is the slot |
| | | width granularity in :math:`GHz`. |
| | | Any combination of frequency slots is allowed as long as |
| | | there is no overlap between two frequency slots. |
| | | Requested spectrum should be consistent with mode min_spacing |
| | | and path_bandwidth: 1) each slot inside the list must be |
| | | large enough to fit one carrier with min_spacing width, |
| | | 2) total number of channels should be large enough to support |
| | | the requested path_bandwidth. |
| | | Note that gnpy-path-request script uses full spectral load and |
| | | not this spectrum constraint to compute performance. Thus, the |
| | | specific mix of channels resulting from the list of requests |
| | | is not considered to compute performances. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``route-object-include-exclude`` | (list) | Optional. Indexed List of routing include/exclude constraints |
| | | to compute the path between source and destination. |
+-----------------------------------+------------+----------------------------------------------------------------+
``route-object-include-exclude`` attributes:
+-----------------------------------+------------+----------------------------------------------------------------+
| field | type | description |
+===================================+============+================================================================+
| ``explicit-route-usage`` | (string) | Mandatory. Only one value is supported: ``route-include-ero`` |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``index`` | (number) | Mandatory. Index of the element to be included. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``nodes_id`` | (string) | Mandatory. UID of the node to include in the path. |
| | | It must be listed in the list of elements in topology file. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``hop-type`` | (string) | Mandatory. One among these two values: ``LOOSE`` or |
| | | ``STRICT``. If LOOSE, constraint may be ignored at |
| | | computation time if no solution is found that satisfies the |
| | | constraint. If STRICT, constraint MUST be satisfied, else the |
| | | computation is stopped and no solution is returned. |
+-----------------------------------+------------+----------------------------------------------------------------+
- **"synchronization"**:
+-----------------------------------+------------+----------------------------------------------------------------+
| field | type | description |
+===================================+============+================================================================+
| ``"relaxable`` | (boolean) | Mandatory. Only false is supported. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``disjointness`` | (string) | Mandatory. Only ``node link`` is supported. |
+-----------------------------------+------------+----------------------------------------------------------------+
| ``request-id-number`` | (list) | Mandatory. List of ``request-id`` whose path should be |
| | | disjointed. |
+-----------------------------------+------------+----------------------------------------------------------------+
.. code-block:: json
"synchronization-id": "3",
"svec": {
"relaxable": false,
"disjointness": "node link",
"request-id-number": [
"3",
"1"
]

View File

@@ -5,6 +5,157 @@ Release change log
Each release introduces some changes and new features.
(prepare text for next release)
ROADM impairments can be defined per degree and roadm-path type (add, drop or express).
Minimum loss when crossing a ROADM is no more 0 dB. It can be set per ROADM degree with roadm-path-impairments.
The transceiver output power, which was previously set using the same parameter as the input span power (power_dbm),
can now be set using a different parameter. It can be set as:
- for all channels, with tx_power_dbm using SI similarly to tx_osnr (gnpy-transmission-example script)
.. code-block:: json
"SI": [{
"f_min": 191.35e12,
"baud_rate": 32e9,
"f_max": 196.1e12,
"spacing": 50e9,
"power_dbm": 3,
"power_range_db": [0, 0, 1],
"roll_off": 0.15,
"tx_osnr": 40,
"tx_power_dbm": -10,
"sys_margins": 2
}
]
- for certain channels, using -spectrum option and tx_channel_power_dbm option (gnpy-transmission-example script).
.. code-block:: json
{
"spectrum": [
{
"f_min": 191.35e12,
"f_max":193.1e12,
"baud_rate": 32e9,
"slot_width": 50e9,
"power_dbm": 0,
"roll_off": 0.15,
"tx_osnr": 40
},
{
"f_min": 193.15e12,
"f_max":193.15e12,
"baud_rate": 32e9,
"slot_width": 50e9,
"power_dbm": 0,
"roll_off": 0.15,
"tx_osnr": 40,
"tx_power_dbm": -10
},
{
"f_min": 193.2e12,
"f_max":195.1e12,
"baud_rate": 32e9,
"slot_width": 50e9,
"power_dbm": 0,
"roll_off": 0.15,
"tx_osnr": 40
}
]
}
- per service using the additional parameter ``tx_power`` which similarly to ``power`` should be defined in Watt (gnpy-path-request script)
.. code-block:: json
{
"path-request": [
{
"request-id": "0",
"source": "trx SITE1",
"destination": "trx SITE2",
"src-tp-id": "trx SITE1",
"dst-tp-id": "trx SITE2",
"bidirectional": false,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"trx_mode": "mode 1",
"spacing": 50000000000.0,
"path_bandwidth": 100000000000.0
}
}
},
{
"request-id": "0 with tx_power",
"source": "trx SITE1",
"destination": "trx SITE2",
"src-tp-id": "trx SITE1",
"dst-tp-id": "trx SITE2",
"bidirectional": false,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"trx_mode": "mode 1",
"tx_power": 0.0001,
"spacing": 50000000000.0,
"path_bandwidth": 100000000000.0
}
}
}
]
}
v2.9
----
The revision introduces a major refactor that separates design and propagation. Most of these changes have no impact
on the user experience, except the following ones:
**Network design - amplifiers**: amplifier saturation is checked during design in all cases, even if type_variety is
set; amplifier gain is no more computed on the fly but only at design phase.
Before, the design did not consider amplifier power saturation during design if amplifier type_variety was stated.
With this revision, the saturation is always applied:
If design is made for a per channel power that leads to saturation, the target are properly reduced and the design
is freezed. So that when a new simulation is performed on the same network for lower levels of power per channel
the same gain target is applied. Before these were recomputed, changing the gain targets, so the simulation was
not considering the exact same working points for amplifiers in case of saturation.
Note that this case (working with saturation settings) is not recommended.
The gain of amplifiers was estimated on the fly also in case of RamanFiber preceding elements. The refactor now
requires that an estimation of Raman gain of the RamanFiber is done during design to properly compute a gain target.
The Raman gain is estimated at design for every RamanFiber span and also during propagation instead of being only
estimated at propagation stage for those Raman Fiber spans concerned with the transmission. The auto-design is more
accurate for unpropagated spans, but this results in an increase overall computation time.
This will be improved in the future.
**Network design - ROADMs**: ROADM target power settings are verified during design.
Design checks that expected power coming from every directions ingress from a ROADM are consistent with output power
targets. The checks only considers the adjacent previous hop. If the expected power at the input of this ROADM is
lower than the target power on the out-degree of the ROADM, a warning is displayed, and user is asked to review the
input network to avoid this situation. This does not change the design or propagation behaviour.
**Propagation**: amplifier gain target is no more recomputed during propagation. It is now possible to freeze
the design and propagate without automatic changes.
In previous release, gain was recomputed during propagation based on an hypothetical reference noiseless channel
propagation. It was not possible to «freeze» the autodesign, and propagate without recomputing the gain target
of amplifiers.
With this new release, the design is freezed, so that it is possible to compare performances on same basis.
**Display**: "effective pch (dbm)" is removed. Display contains the target pch which is the target power per channel
in dBm, computed based on reference channel used for design and the amplifier delta_p in dB (and before out VOA
contribution). Note that "actual pch out (dBm)" is the actual propagated total power per channel averaged per spectrum
band definition at the output of the amplifier element, including noises and out VOA contribution.
v2.8
----
@@ -61,8 +212,30 @@ instead of
**change in display**: only warnings are displayed ; information are disabled and needs the -v (verbose)
option to be displayed on standard output.
**frequency scaling**: Chromatic dispersion, effective area, Raman Gain coefficient,
and nonlinear coefficient can now be defined with a scaling along frequency.
**frequency scaling**: A more accurate description of fiber parameters is implemented, including frequency scaling of
chromatic dispersion, effective area, Raman gain coefficient, and nonlinear coefficient.
In particular:
1. Chromatic dispersion can be defined with ``'dispersion'`` and ``'dispersion_slope'``, as in previous versions, or
with ``'dispersion_per_frequency'``; the latter must be defined as a dictionary with two keys, ``'value'`` and
``'frequency'`` and it has higher priority than the entries ``'dispersion'`` and ``'dispersion_slope'``.
Essential change: In previous versions, when it was not provided the ``'dispersion_slope'`` was calculated in an
involute manner to get a vanishing beta3 , and this was a mere artifact for NLI evaluation purposes (namely to evaluate
beta2 and beta3, not for total dispersion accumulation). Now, the evaluation of beta2 and beta3 is performed explicitly
in the element.py module.
2. The effective area is provided as a scalar value evaluated at the Fiber reference frequency and properly scaled
considering the Fiber refractive indices n1 and n2, and the core radius. These quantities are assumed to be fixed and
are hard coded in the parameters.py module. Essential change: The effective area is always scaled along the frequency.
3. The Raman gain coefficient is properly scaled considering the overlapping of fiber effective area values scaled at
the interacting frequencies. Essential change: In previous version the Raman gain coefficient depends only on
the frequency offset.
4. The nonlinear coefficient ``'gamma'`` is properly scaled considering the refractive index n2 and the scaling
effective area. Essential change: As the effective area, the nonlinear coefficient is always scaled along the
frequency.
**power offset**: Power equalization now enables defining a power offset in transceiver library to represent
the deviation from the general equalisation strategy defined in ROADMs.

View File

@@ -29,10 +29,11 @@ from typing import Union
from logging import getLogger
from gnpy.core.utils import lin2db, db2lin, arrange_frequencies, snr_sum, per_label_average, pretty_summary_print, \
watt2dbm, psd2powerdbm
from gnpy.core.parameters import RoadmParams, FusedParams, FiberParams, PumpParams, EdfaParams, EdfaOperational
watt2dbm, psd2powerdbm, calculate_absolute_min_or_zero
from gnpy.core.parameters import RoadmParams, FusedParams, FiberParams, PumpParams, EdfaParams, EdfaOperational, \
RoadmPath, RoadmImpairment
from gnpy.core.science_utils import NliSolver, RamanSolver
from gnpy.core.info import SpectralInformation, ReferenceCarrier
from gnpy.core.info import SpectralInformation
from gnpy.core.exceptions import NetworkTopologyError, SpectrumError, ParametersError
@@ -94,6 +95,7 @@ class Transceiver(_Node):
self.penalties = {}
self.total_penalty = 0
self.propagated_labels = [""]
self.tx_power = None
def _calc_cd(self, spectral_info):
"""Updates the Transceiver property with the CD of the received channels. CD in ps/nm.
@@ -155,7 +157,8 @@ class Transceiver(_Node):
# use raw_values so that the added SNR penalties are not cumulated
snr_added = 0
for s in args:
snr_added += db2lin(-s)
if s is not None:
snr_added += db2lin(-s)
snr_added = -lin2db(snr_added)
self.osnr_ase = snr_sum(self.raw_osnr_ase, self.baud_rate, snr_added)
self.snr = snr_sum(self.raw_snr, self.baud_rate, snr_added)
@@ -192,6 +195,7 @@ class Transceiver(_Node):
osnr_ase = per_label_average(self.osnr_ase, self.propagated_labels)
osnr_ase_01nm = per_label_average(self.osnr_ase_01nm, self.propagated_labels)
snr_01nm = per_label_average(self.snr_01nm, self.propagated_labels)
tx_power_dbm = per_label_average(watt2dbm(self.tx_power), self.propagated_labels)
cd = mean(self.chromatic_dispersion)
pmd = mean(self.pmd)
pdl = mean(self.pdl)
@@ -205,7 +209,8 @@ class Transceiver(_Node):
f' CD (ps/nm): {cd:.2f}',
f' PMD (ps): {pmd:.2f}',
f' PDL (dB): {pdl:.2f}',
f' Latency (ms): {latency:.2f}'])
f' Latency (ms): {latency:.2f}',
f' Actual pch out (dBm): {pretty_summary_print(tx_power_dbm)}'])
cd_penalty = self.penalties.get('chromatic_dispersion')
if cd_penalty is not None:
@@ -220,6 +225,7 @@ class Transceiver(_Node):
return result
def __call__(self, spectral_info):
self.tx_power = spectral_info.tx_power
self._calc_snr(spectral_info)
self._calc_cd(spectral_info)
self._calc_pmd(spectral_info)
@@ -242,6 +248,7 @@ class Roadm(_Node):
# on the path, since it depends on the equalization definition on the degree.
self.ref_pch_out_dbm = None
self.loss = 0 # auto-design interest
self.loss_pch_db = None
# Optical power of carriers are equalized by the ROADM, so that the experienced loss is not the same for
# different carriers. The ref_effective_loss records the loss for a reference carrier.
@@ -260,6 +267,17 @@ class Roadm(_Node):
self.per_degree_pch_psw = self.params.per_degree_pch_psw
self.ref_pch_in_dbm = {}
self.ref_carrier = None
# Define the nature of from-to internal connection: express-path, drop-path, add-path
# roadm_paths contains a list of RoadmPath object for each path crossing the ROADM
self.roadm_paths = []
# roadm_path_impairments contains a dictionnary of impairments profiles corresponding to type_variety
# first listed add, drop an express constitute the default
self.roadm_path_impairments = self.params.roadm_path_impairments
# per degree definitions, in case some degrees have particular deviations with respect to default.
self.per_degree_impairments = {f'{i["from_degree"]}-{i["to_degree"]}': {"from_degree": i["from_degree"],
"to_degree": i["to_degree"],
"impairment_id": i["impairment_id"]}
for i in self.params.per_degree_impairments}
@property
def to_json(self):
@@ -274,9 +292,10 @@ class Roadm(_Node):
to_json = {
'uid': self.uid,
'type': type(self).__name__,
'type_variety': self.type_variety,
'params': {
equalisation: value,
'restrictions': self.restrictions,
'restrictions': self.restrictions
},
'metadata': {
'location': self.metadata['location']._asdict()
@@ -289,6 +308,9 @@ class Roadm(_Node):
to_json['params']['per_degree_psd_out_mWperGHz'] = self.per_degree_pch_psd
if self.per_degree_pch_psw:
to_json['params']['per_degree_psd_out_mWperSlotWidth'] = self.per_degree_pch_psw
if self.per_degree_impairments:
to_json['per_degree_impairments'] = list(self.per_degree_impairments.values())
return to_json
def __repr__(self):
@@ -299,10 +321,13 @@ class Roadm(_Node):
return f'{type(self).__name__} {self.uid}'
total_pch = pretty_summary_print(per_label_average(self.pch_out_dbm, self.propagated_labels))
total_loss = pretty_summary_print(per_label_average(self.loss_pch_db, self.propagated_labels))
return '\n'.join([f'{type(self).__name__} {self.uid}',
f' effective loss (dB): {self.ref_effective_loss:.2f}',
f' reference pch out (dBm): {self.ref_pch_out_dbm:.2f}',
f' actual pch out (dBm): {total_pch}'])
f' Type_variety: {self.type_variety}',
f' Reference loss (dB): {self.ref_effective_loss:.2f}',
f' Actual loss (dB): {total_loss}',
f' Reference pch out (dBm): {self.ref_pch_out_dbm:.2f}',
f' Actual pch out (dBm): {total_pch}'])
def get_roadm_target_power(self, spectral_info: SpectralInformation = None) -> Union[float, ndarray]:
"""Computes the power in dBm for a reference carrier or for a spectral information.
@@ -358,13 +383,18 @@ class Roadm(_Node):
def propagate(self, spectral_info, degree, from_degree):
"""Equalization targets are read from topology file if defined and completed with default
definition of the library.
If the input power is lower than the target one, use the input power instead because
a ROADM doesn't amplify, it can only attenuate.
There is no difference for add or express : the same target is applied. For the moment
propagates operates with spectral info carriers all having the same source or destination.
If the input power is lower than the target one, use the input power minus the ROADM loss
if is exists, because a ROADM doesn't amplify, it can only attenuate.
There is no difference for add or express : the same target is applied.
For the moment propagate operates with spectral info carriers all having the same source or destination.
"""
# TODO maybe add a minimum loss for the ROADM
# record input powers to compute the actual loss at the end of the process
input_power_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
# apply min ROADM loss if it exists
roadm_maxloss_db = self.get_roadm_path(from_degree, degree).impairment.maxloss
spectral_info.apply_attenuation_db(roadm_maxloss_db)
# records the total power after applying minimum loss
net_input_power_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
# find the target power for the reference carrier
ref_per_degree_pch = self.get_per_degree_ref_power(degree)
# find the target powers for each signal carrier
@@ -374,15 +404,19 @@ class Roadm(_Node):
# Depending on propagation upstream from this ROADM, the input power might be smaller than
# the target power out configured for this ROADM degree's egress. Since ROADM does not amplify,
# the power out of the ROADM for the ref channel is the min value between target power and input power.
# (TODO add a minimum loss for the ROADM crossing)
self.ref_pch_out_dbm = min(self.ref_pch_in_dbm[from_degree], ref_per_degree_pch)
ref_pch_in_dbm = self.ref_pch_in_dbm[from_degree]
# Calculate the output power for the reference channel (only for visualization)
self.ref_pch_out_dbm = min(ref_pch_in_dbm - roadm_maxloss_db, ref_per_degree_pch)
# Definition of effective_loss:
# Optical power of carriers are equalized by the ROADM, so that the experienced loss is not the same for
# different carriers. effective_loss records the loss for the reference carrier.
self.ref_effective_loss = self.ref_pch_in_dbm[from_degree] - self.ref_pch_out_dbm
input_power = spectral_info.signal + spectral_info.nli + spectral_info.ase
# Calculate the effective loss for the reference channel
self.ref_effective_loss = ref_pch_in_dbm - self.ref_pch_out_dbm
# Calculate the target power per channel according to the equalization policy
target_power_per_channel = per_degree_pch + spectral_info.delta_pdb_per_channel
# Computation of the per channel target power according to equalization policy
# Computation of the correction according to equalization policy
# If target_power_per_channel has some channels power above input power, then the whole target is reduced.
# For example, if user specifies delta_pdb_per_channel:
# freq1: 1dB, freq2: 3dB, freq3: -3dB, and target is -20dBm out of the ROADM,
@@ -397,17 +431,82 @@ class Roadm(_Node):
# that had the min power.
# This change corresponds to a discussion held during coders call. Please look at this document for
# a reference: https://telecominfraproject.atlassian.net/wiki/spaces/OOPT/pages/669679645/PSE+Meeting+Minutes
correction = (abs(watt2dbm(input_power) - target_power_per_channel)
- (watt2dbm(input_power) - target_power_per_channel)) / 2
correction = calculate_absolute_min_or_zero(net_input_power_dbm - target_power_per_channel)
new_target = target_power_per_channel - correction
delta_power = watt2dbm(input_power) - new_target
delta_power = net_input_power_dbm - new_target
spectral_info.apply_attenuation_db(delta_power)
spectral_info.pmd = sqrt(spectral_info.pmd ** 2 + self.params.pmd ** 2)
spectral_info.pdl = sqrt(spectral_info.pdl ** 2 + self.params.pdl ** 2)
# Update the PMD information
pmd_impairment = self.get_roadm_path(from_degree=from_degree, to_degree=degree).impairment.pmd
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
spectral_info.pdl = sqrt(spectral_info.pdl ** 2 + pdl_impairment ** 2)
# Update the per channel power with the result of propagation
self.pch_out_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
# Update the loss per channel and the labels
self.loss_pch_db = input_power_dbm - self.pch_out_dbm
self.propagated_labels = spectral_info.label
def set_roadm_paths(self, from_degree, to_degree, path_type, impairment_id=None):
"""set internal path type: express, drop or add with corresponding impairment
If no impairment id is defined, then use the first profile that matches the path_type in the
profile dictionnary.
"""
# 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}
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)
impairment = RoadmImpairment(roadm_global_impairment)
if impairment_id is None:
# get the first item in the type variety that matches the path_type
for path_impairment_id, path_impairment in self.roadm_path_impairments.items():
if path_impairment.path_type == path_type:
impairment = path_impairment
impairment_id = path_impairment_id
break
# at this point, path_type is not part of roadm_path_impairment, impairment and impairment_id are None
else:
if impairment_id in self.roadm_path_impairments:
impairment = self.roadm_path_impairments[impairment_id]
else:
msg = f'ROADM {self.uid}: impairment profile id {impairment_id} is not defined in library'
raise NetworkTopologyError(msg)
# print(from_degree, to_degree, path_type)
self.roadm_paths.append(RoadmPath(from_degree=from_degree, to_degree=to_degree, path_type=path_type,
impairment_id=impairment_id, impairment=impairment))
def get_roadm_path(self, from_degree, to_degree):
"""Get internal path type impairment"""
for roadm_path in self.roadm_paths:
if roadm_path.from_degree == from_degree and roadm_path.to_degree == to_degree:
return roadm_path
msg = f'Could not find from_degree-to_degree {from_degree}-{to_degree} path in ROADM {self.uid}'
raise NetworkTopologyError(msg)
def get_per_degree_impairment_id(self, from_degree, to_degree):
"""returns the id of the impairment if the degrees are in the per_degree tab"""
if f'{from_degree}-{to_degree}' in self.per_degree_impairments.keys():
return self.per_degree_impairments[f'{from_degree}-{to_degree}']["impairment_id"]
return None
def get_path_type_per_id(self, impairment_id):
"""returns the path_type of the impairment if the is is defined"""
if impairment_id in self.roadm_path_impairments.keys():
return self.roadm_path_impairments[impairment_id].path_type
return None
def __call__(self, spectral_info, degree, from_degree):
self.propagate(spectral_info, degree=degree, from_degree=from_degree)
return spectral_info
@@ -707,11 +806,16 @@ class RamanFiber(Fiber):
def to_json(self):
return dict(super().to_json, operational=self.operational)
def __str__(self):
return super().__str__() + f'\n reference gain (dB): {round(self.estimated_gain, 2)}' \
+ f'\n actual gain (dB): {round(self.actual_raman_gain, 2)}'
def propagate(self, spectral_info: SpectralInformation):
"""Modifies the spectral information computing the attenuation, the non-linear interference generation,
the CD and PMD accumulation.
"""
# apply the attenuation due to the input connector loss
pin = watt2dbm(sum(spectral_info.signal))
attenuation_in_db = self.params.con_in + self.params.att_in
spectral_info.apply_attenuation_db(attenuation_in_db)
@@ -741,6 +845,8 @@ class RamanFiber(Fiber):
spectral_info.apply_attenuation_db(attenuation_out_db)
self.pch_out_dbm = watt2dbm(spectral_info.signal + spectral_info.nli + spectral_info.ase)
self.propagated_labels = spectral_info.label
pout = watt2dbm(sum(spectral_info.signal))
self.actual_raman_gain = self.loss + pout - pin
class Edfa(_Node):
@@ -751,7 +857,7 @@ class Edfa(_Node):
operational = {}
self.variety_list = kwargs.pop('variety_list', None)
super().__init__(*args, params=EdfaParams(**params), operational=EdfaOperational(**operational), **kwargs)
self.interpol_dgt = None # interpolated dynamic gain tilt
self.interpol_dgt = None # interpolated dynamic gain tilt defined per frequency on amp band
self.interpol_gain_ripple = None # gain ripple
self.interpol_nf_ripple = None # nf_ripple
self.channel_freq = None # SI channel frequencies
@@ -774,7 +880,7 @@ class Edfa(_Node):
self.delta_p = self.operational.delta_p
# self._delta_p contains computed delta_p during design even if power_mode is False
self._delta_p = None
self.tilt_target = self.operational.tilt_target
self.tilt_target = self.operational.tilt_target # defined per lambda on the amp band
self.out_voa = self.operational.out_voa
self.propagated_labels = [""]
@@ -786,7 +892,7 @@ class Edfa(_Node):
'operational': {
'gain_target': round(self.effective_gain, 6) if self.effective_gain else None,
'delta_p': self.delta_p,
'tilt_target': self.tilt_target,
'tilt_target': self.tilt_target, # defined per lambda on the amp band
'out_voa': self.out_voa
},
'metadata': {
@@ -1016,7 +1122,7 @@ class Edfa(_Node):
p = polyfit(self.channel_freq, self.interpol_dgt, 1)
dgt_slope = p[0]
# Calculate the target slope
# Calculate the target slope defined per frequency on the amp band
targ_slope = -self.tilt_target / (self.params.f_max - self.params.f_min)
# first estimate of DGT scaling

View File

@@ -8,70 +8,75 @@ gnpy.core.equipment
This module contains functionality for specifying equipment.
"""
from gnpy.core.utils import automatic_nch, db2lin
from gnpy.core.exceptions import EquipmentConfigError
def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=False):
"""return the trx and SI parameters from eqpt_config for a given type_variety and mode (ie format)"""
"""return the trx and SI parameters from eqpt_config for a given type_variety and mode (ie format)
if the type or mode do no match an existing transceiver in the library, then the function
raises an error if error_message is True else returns a default mode based on equipment['SI']['default']
If trx_mode is None (but type is valid), it returns an undetermined mode whatever the error message:
this is a special case for automatic mode selection.
"""
trx_params = {}
default_si_data = equipment['SI']['default']
# default transponder characteristics
# mainly used with transmission_main_example.py
default_trx_params = {
'f_min': default_si_data.f_min,
'f_max': default_si_data.f_max,
'baud_rate': default_si_data.baud_rate,
'spacing': default_si_data.spacing,
'OSNR': None,
'penalties': {},
'bit_rate': None,
'cost': None,
'roll_off': default_si_data.roll_off,
'tx_osnr': default_si_data.tx_osnr,
'min_spacing': None,
'equalization_offset_db': 0
}
# Undetermined transponder characteristics
# mainly used with path_request_run.py for the automatic mode computation case
undetermined_trx_params = {
"format": "undetermined",
"baud_rate": None,
"OSNR": None,
"penalties": None,
"bit_rate": None,
"roll_off": None,
"tx_osnr": None,
"min_spacing": None,
"cost": None,
"equalization_offset_db": 0
}
try:
trxs = equipment['Transceiver']
# if called from path_requests_run.py, trx_mode is filled with None when not specified by user
# if called from transmission_main.py, trx_mode is ''
if trx_mode is not None:
mode_params = next(mode for trx in trxs
if trx == trx_type_variety
for mode in trxs[trx].mode
if mode['format'] == trx_mode)
trx_params = {**mode_params}
# sanity check: spacing baudrate must be smaller than min spacing
trxs = equipment['Transceiver']
if trx_type_variety in trxs:
modes = {mode['format']: mode for mode in trxs[trx_type_variety].mode}
trx_frequencies = {'f_min': trxs[trx_type_variety].frequency['min'],
'f_max': trxs[trx_type_variety].frequency['max']}
if trx_mode in modes:
# if called from transmission_main.py, trx_mode is ''
trx_params = {**modes[trx_mode], **trx_frequencies}
if trx_params['baud_rate'] > trx_params['min_spacing']:
raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transponder "{trx_type_variety}"'
+ f' mode "{trx_params["format"]}" has baud rate'
+ f' {trx_params["baud_rate"] * 1e-9:.3f} GHz greater than min_spacing'
+ f' {trx_params["min_spacing"] * 1e-9:.3f}.')
# sanity check: baudrate must be smaller than min spacing
raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transponder "{trx_type_variety}" '
+ f'mode "{trx_params["format"]}" has baud rate '
+ f'{trx_params["baud_rate"] * 1e-9:.2f} GHz greater than min_spacing '
+ f'{trx_params["min_spacing"] * 1e-9:.2f}.')
trx_params['equalization_offset_db'] = trx_params.get('equalization_offset_db', 0)
else:
mode_params = {"format": "undetermined",
"baud_rate": None,
"OSNR": None,
"penalties": None,
"bit_rate": None,
"roll_off": None,
"tx_osnr": None,
"min_spacing": None,
"cost": None,
"equalization_offset_db": 0}
trx_params = {**mode_params}
trx_params['f_min'] = equipment['Transceiver'][trx_type_variety].frequency['min']
trx_params['f_max'] = equipment['Transceiver'][trx_type_variety].frequency['max']
# TODO: novel automatic feature maybe unwanted if spacing is specified
# trx_params['spacing'] = _automatic_spacing(trx_params['baud_rate'])
# temp = trx_params['spacing']
# print(f'spacing {temp}')
except StopIteration:
if error_message:
raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" with mode "{trx_mode}" in equipment library')
else:
# default transponder charcteristics
# mainly used with transmission_main_example.py
trx_params['f_min'] = default_si_data.f_min
trx_params['f_max'] = default_si_data.f_max
trx_params['baud_rate'] = default_si_data.baud_rate
trx_params['spacing'] = default_si_data.spacing
trx_params['OSNR'] = None
trx_params['penalties'] = {}
trx_params['bit_rate'] = None
trx_params['cost'] = None
trx_params['roll_off'] = default_si_data.roll_off
trx_params['tx_osnr'] = default_si_data.tx_osnr
trx_params['min_spacing'] = None
trx_params['equalization_offset_db'] = 0
trx_params['power'] = db2lin(default_si_data.power_dbm) * 1e-3
return trx_params
if trx_mode is None:
# if called from path_requests_run.py, trx_mode is filled with None when not specified by user
trx_params = {**undetermined_trx_params, **trx_frequencies}
return trx_params
if trx_type_variety in trxs and error_message:
raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" with mode "{trx_mode}" '
+ 'in equipment library')
if error_message:
raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" in equipment library')
trx_params = {**default_trx_params}
return trx_params

View File

@@ -52,7 +52,7 @@ class SpectralInformation(object):
def __init__(self, frequency: array, baud_rate: array, slot_width: array, signal: array, nli: array, ase: array,
roll_off: array, chromatic_dispersion: array, pmd: array, pdl: array, latency: array,
delta_pdb_per_channel: array, tx_osnr: array, label: array):
delta_pdb_per_channel: array, tx_osnr: array, tx_power: array, label: array):
indices = argsort(frequency)
self._frequency = frequency[indices]
self._df = outer(ones(frequency.shape), frequency) - outer(frequency, ones(frequency.shape))
@@ -80,6 +80,7 @@ class SpectralInformation(object):
self._latency = latency[indices]
self._delta_pdb_per_channel = delta_pdb_per_channel[indices]
self._tx_osnr = tx_osnr[indices]
self._tx_power = tx_power[indices]
self._label = label[indices]
@property
@@ -188,6 +189,14 @@ class SpectralInformation(object):
def tx_osnr(self, tx_osnr):
self._tx_osnr = tx_osnr
@property
def tx_power(self):
return self._tx_power
@tx_power.setter
def tx_power(self, tx_power):
self._tx_power = tx_power
@property
def channel_number(self):
return self._channel_number
@@ -232,6 +241,7 @@ class SpectralInformation(object):
delta_pdb_per_channel=append(self.delta_pdb_per_channel,
other.delta_pdb_per_channel),
tx_osnr=append(self.tx_osnr, other.tx_osnr),
tx_power=append(self.tx_power, other.tx_power),
label=append(self.label, other.label))
except SpectrumError:
raise SpectrumError('Spectra cannot be summed: channels overlapping.')
@@ -251,6 +261,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
signal: Union[float, ndarray, Iterable],
baud_rate: Union[float, ndarray, Iterable],
tx_osnr: Union[float, ndarray, Iterable],
tx_power: Union[float, ndarray, Iterable] = None,
delta_pdb_per_channel: Union[float, ndarray, Iterable] = 0.,
slot_width: Union[float, ndarray, Iterable] = None,
roll_off: Union[float, ndarray, Iterable] = 0.,
@@ -277,6 +288,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
ase = zeros(number_of_channels)
delta_pdb_per_channel = full(number_of_channels, delta_pdb_per_channel)
tx_osnr = full(number_of_channels, tx_osnr)
tx_power = full(number_of_channels, tx_power)
label = full(number_of_channels, label)
return SpectralInformation(frequency=frequency, slot_width=slot_width,
signal=signal, nli=nli, ase=ase,
@@ -284,7 +296,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
chromatic_dispersion=chromatic_dispersion,
pmd=pmd, pdl=pdl, latency=latency,
delta_pdb_per_channel=delta_pdb_per_channel,
tx_osnr=tx_osnr, label=label)
tx_osnr=tx_osnr, tx_power=tx_power, label=label)
except ValueError as e:
if 'could not broadcast' in str(e):
raise SpectrumError('Dimension mismatch in input fields.')
@@ -292,45 +304,46 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl
raise
def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, power, spacing, tx_osnr, delta_pdb=0):
def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, spacing, tx_osnr, tx_power,
delta_pdb=0):
"""Creates a fixed slot width spectral information with flat power.
all arguments are scalar values"""
number_of_channels = automatic_nch(f_min, f_max, spacing)
frequency = [(f_min + spacing * i) for i in range(1, number_of_channels + 1)]
delta_pdb_per_channel = delta_pdb * ones(number_of_channels)
label = [f'{baud_rate * 1e-9 :.2f}G' for i in range(number_of_channels)]
return create_arbitrary_spectral_information(frequency, slot_width=spacing, signal=power, baud_rate=baud_rate,
return create_arbitrary_spectral_information(frequency, slot_width=spacing, signal=tx_power, baud_rate=baud_rate,
roll_off=roll_off, delta_pdb_per_channel=delta_pdb_per_channel,
tx_osnr=tx_osnr, label=label)
tx_osnr=tx_osnr, tx_power=tx_power, label=label)
def carriers_to_spectral_information(initial_spectrum: dict[float, Carrier],
power: float) -> SpectralInformation:
"""Initial spectrum is a dict with key = carrier frequency, and value a Carrier object.
:param initial_spectrum: indexed by frequency in Hz, with power offset (delta_pdb), baudrate, slot width,
tx_osnr and roll off.
tx_osnr, tx_power and roll off.
:param power: power of the request
"""
frequency = list(initial_spectrum.keys())
signal = [power * db2lin(c.delta_pdb) for c in initial_spectrum.values()]
signal = [c.tx_power for c in initial_spectrum.values()]
roll_off = [c.roll_off for c in initial_spectrum.values()]
baud_rate = [c.baud_rate for c in initial_spectrum.values()]
delta_pdb_per_channel = [c.delta_pdb for c in initial_spectrum.values()]
slot_width = [c.slot_width for c in initial_spectrum.values()]
tx_osnr = [c.tx_osnr for c in initial_spectrum.values()]
tx_power = [c.tx_power for c in initial_spectrum.values()]
label = [c.label for c in initial_spectrum.values()]
p_span0 = watt2dbm(power)
return create_arbitrary_spectral_information(frequency=frequency, signal=signal, baud_rate=baud_rate,
slot_width=slot_width, roll_off=roll_off,
delta_pdb_per_channel=delta_pdb_per_channel, tx_osnr=tx_osnr,
label=label)
tx_power=tx_power, label=label)
@dataclass
class Carrier:
"""One channel in the initial mixed-type spectrum definition, each type being defined by
its delta_pdb (power offset with respect to reference power), baud rate, slot_width, roll_off
and tx_osnr. delta_pdb offset is applied to target power out of Roadm.
tx_power, and tx_osnr. delta_pdb offset is applied to target power out of Roadm.
Label is used to group carriers which belong to the same partition when printing results.
"""
delta_pdb: float
@@ -338,6 +351,7 @@ class Carrier:
slot_width: float
roll_off: float
tx_osnr: float
tx_power: float
label: str
@@ -347,7 +361,7 @@ class ReferenceCarrier:
constant power spectral density (PSD) equalization is set. Reference channel is the type that has been defined
in SI block and used for the initial design of the network.
Computing the power out of ROADM for the reference channel is required to correctly compute the loss
experienced by p_span_i in Roadm element.
experienced by reference channel in Roadm element.
Baud rate is required to find the target power in constant PSD: power = PSD_target * baud_rate.
For example, if target PSD is 3.125e4mW/GHz and reference carrier type a 32 GBaud channel then
@@ -358,7 +372,7 @@ class ReferenceCarrier:
For example, if target PSW is 2e4mW/GHz and reference carrier type a 32 GBaud channel in a 50GHz slot width then
output power should be -20 dBm and for a 64 GBaud channel in a 75 GHz slot width, power target would be -18.24 dBm.
Other attributes (like slot_width or roll-off) may be added there for future equalization purpose.
Other attributes (like roll-off) may be added there for future equalization purpose.
"""
baud_rate: float
slot_width: float

View File

@@ -17,8 +17,8 @@ from gnpy.core import elements
from gnpy.core.exceptions import ConfigurationError, NetworkTopologyError
from gnpy.core.utils import round2float, convert_length, psd2powerdbm, lin2db, watt2dbm, dbm2watt
from gnpy.core.info import ReferenceCarrier, create_input_spectral_information
from gnpy.tools import json_io
from gnpy.core.parameters import SimParams
from gnpy.core.parameters import SimParams, EdfaParams
from gnpy.core.science_utils import RamanSolver
logger = getLogger(__name__)
@@ -141,7 +141,6 @@ def target_power(network, node, equipment): # get_fiber_dp
POWER_SLOPE = 0.3
dp_range = list(equipment['Span']['default'].delta_power_range_db)
node_loss = span_loss(network, node, equipment)
try:
dp = round2float((node_loss - SPAN_LOSS_REF) * POWER_SLOPE, dp_range[2])
dp = max(dp_range[0], dp)
@@ -187,63 +186,73 @@ def next_node_generator(network, node):
yield from next_node_generator(network, next_node)
def estimate_raman_gain(node, equipment):
def estimate_raman_gain(node, equipment, power_dbm):
"""If node is RamanFiber, then estimate the possible Raman gain if any
for this purpose propagate a fake signal in a copy.
to be accurate the nb of channel should be the same as in SI, but this increases computation time
for this purpose computes stimulated_raman_scattering loss_profile. This may be time consuming.
"""
f_min = equipment['SI']['default'].f_min
f_max = equipment['SI']['default'].f_max
roll_off = equipment['SI']['default'].roll_off
baud_rate = equipment['SI']['default'].baud_rate
power_dbm = equipment['SI']['default'].power_dbm
power = dbm2watt(equipment['SI']['default'].power_dbm)
spacing = equipment['SI']['default'].spacing
tx_osnr = equipment['SI']['default'].tx_osnr
sim_params = {
"raman_params": {
"flag": True,
"result_spatial_resolution": 10e3,
"solver_spatial_resolution": 50
},
"nli_params": {
"method": "ggn_spectrally_separated",
"dispersion_tolerance": 1,
"phase_shift_tolerance": 0.1,
"computed_channels": [1, 18, 37, 56, 75]
}
}
if isinstance(node, elements.RamanFiber):
if hasattr(node, "estimated_gain"):
return node.estimated_gain
f_min = equipment['SI']['default'].f_min
f_max = equipment['SI']['default'].f_max
roll_off = equipment['SI']['default'].roll_off
baud_rate = equipment['SI']['default'].baud_rate
power = dbm2watt(power_dbm)
spacing = equipment['SI']['default'].spacing
tx_osnr = equipment['SI']['default'].tx_osnr
# reduce the nb of channels to speed up
spacing = spacing * 3
power = power * 3
sim_params = {
"raman_params": {
"flag": True,
"result_spatial_resolution": 50e3,
"solver_spatial_resolution": 100
}
}
# in order to take into account gain generated in RamanFiber, propagate in the RamanFiber with
# SI reference channel.
spectral_info_input = create_input_spectral_information(f_min=f_min, f_max=f_max, roll_off=roll_off,
baud_rate=baud_rate, power=power, spacing=spacing,
tx_osnr=tx_osnr)
n_copy = deepcopy(node)
# need to set ref_pch_in_dbm in order to correctly run propagate of the element, because this
# setting has not yet been done by autodesign
n_copy.ref_pch_in_dbm = power_dbm
if hasattr(node, "estimated_gain"):
# do not compute twice to save on time
return node.estimated_gain
spectral_info = create_input_spectral_information(f_min=f_min, f_max=f_max, roll_off=roll_off,
baud_rate=baud_rate, tx_power=power, spacing=spacing,
tx_osnr=tx_osnr)
pin = watt2dbm(sum(spectral_info.signal))
attenuation_in_db = node.params.con_in + node.params.att_in
spectral_info.apply_attenuation_db(attenuation_in_db)
save_sim_params = {"raman_params": SimParams._shared_dict['raman_params'].to_json(),
"nli_params": SimParams._shared_dict['nli_params'].to_json()}
SimParams.set_params(sim_params)
pin = watt2dbm(sum(spectral_info_input.signal))
spectral_info_out = n_copy(spectral_info_input)
pout = watt2dbm(sum(spectral_info_out.signal))
estimated_gain = pout - pin + node.loss
stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering(spectral_info, node)
attenuation_fiber = stimulated_raman_scattering.loss_profile[:spectral_info.number_of_channels, -1]
spectral_info.apply_attenuation_lin(attenuation_fiber)
attenuation_out_db = node.params.con_out
spectral_info.apply_attenuation_db(attenuation_out_db)
pout = watt2dbm(sum(spectral_info.signal))
estimated_loss = pin - pout
estimated_gain = node.loss - estimated_loss
node.estimated_gain = estimated_gain
SimParams.set_params(save_sim_params)
return round(estimated_gain, 2)
else:
return 0.0
def span_loss(network, node, equipment):
"""Total loss of a span (Fiber and Fused nodes) which contains the given node"""
def span_loss(network, node, equipment, input_power=None):
"""Total loss of a span (Fiber and Fused nodes) which contains the given node
Do not recompute, if it was already computed: records it in design_span_loss"""
if hasattr(node, "design_span_loss"):
return node.design_span_loss
loss = node.loss if node.passive else 0
loss += sum(n.loss for n in prev_node_generator(network, node))
loss += sum(n.loss for n in next_node_generator(network, node))
# add the possible Raman gain
gain = estimate_raman_gain(node, equipment)
gain += sum(estimate_raman_gain(n, equipment) for n in prev_node_generator(network, node))
gain += sum(estimate_raman_gain(n, equipment) for n in next_node_generator(network, node))
gain = estimate_raman_gain(node, equipment, input_power)
gain += sum(estimate_raman_gain(n, equipment, input_power) for n in prev_node_generator(network, node))
gain += sum(estimate_raman_gain(n, equipment, input_power) for n in next_node_generator(network, node))
return loss - gain
@@ -295,9 +304,11 @@ def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_d
prev_node = this_node
node = oms
if isinstance(this_node, elements.Transceiver):
# for the time being use the same power for the target of roadms and for transceivers
# TODO: This should be changed when introducing a power parameter dedicated to transceivers
this_node_out_power = pref_ch_db
# todo change pref to a ref channel
if equipment['SI']['default'].tx_power_dbm is not None:
this_node_out_power = equipment['SI']['default'].tx_power_dbm
else:
this_node_out_power = pref_ch_db
if isinstance(this_node, elements.Roadm):
# get target power out from ROADM for the reference carrier based on equalization settings
this_node_out_power = this_node.get_per_degree_ref_power(degree=node.uid)
@@ -399,7 +410,8 @@ def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_d
node.target_pch_out_dbm = round(node.delta_p + pref_ch_db, 2)
elif node.delta_p is None:
node.target_pch_out_dbm = None
elif isinstance(node, elements.RamanFiber):
_ = span_loss(network, node, equipment, input_power=pref_ch_db + dp)
prev_dp = dp
prev_voa = voa
prev_node = node
@@ -520,6 +532,62 @@ def set_fiber_input_power(network, fiber, equipment, pref_ch_db):
fiber.ref_pch_in_dbm = pref_ch_db - loss
def set_roadm_internal_paths(roadm, network):
"""Set ROADM path types (express, add, drop)
Uses implicit guess if no information is set in ROADM
"""
next_oms = [n.uid for n in network.successors(roadm) if not isinstance(n, elements.Transceiver)]
previous_oms = [n.uid for n in network.predecessors(roadm) if not isinstance(n, elements.Transceiver)]
drop_port = [n.uid for n in network.successors(roadm) if isinstance(n, elements.Transceiver)]
add_port = [n.uid for n in network.predecessors(roadm) if isinstance(n, elements.Transceiver)]
default_express = 'express'
default_add = 'add'
default_drop = 'drop'
# take user defined element impairment id if it exists
correct_from_degrees = []
correct_add = []
correct_to_degrees = []
correct_drop = []
for from_degree in previous_oms:
correct_from_degrees.append(from_degree)
for to_degree in next_oms:
correct_to_degrees.append(to_degree)
impairment_id = roadm.get_per_degree_impairment_id(from_degree, to_degree)
roadm.set_roadm_paths(from_degree=from_degree, to_degree=to_degree, path_type=default_express,
impairment_id=impairment_id)
for drop in drop_port:
correct_drop.append(drop)
impairment_id = roadm.get_per_degree_impairment_id(from_degree, drop)
path_type = roadm.get_path_type_per_id(impairment_id)
# a degree connected to a transceiver MUST be add or drop
# but a degree connected to something else could be an express, add or drop
# (for example case of external shelves)
if path_type and path_type != 'drop':
msg = f'Roadm {roadm.uid} path_type is defined as {path_type} but it should be drop'
raise NetworkTopologyError(msg)
roadm.set_roadm_paths(from_degree=from_degree, to_degree=drop, path_type=default_drop,
impairment_id=impairment_id)
for to_degree in next_oms:
for add in add_port:
correct_add.append(add)
impairment_id = roadm.get_per_degree_impairment_id(add, to_degree)
path_type = roadm.get_path_type_per_id(impairment_id)
if path_type and path_type != 'add':
msg = f'Roadm {roadm.uid} path_type is defined as {path_type} but it should be add'
raise NetworkTopologyError(msg)
roadm.set_roadm_paths(from_degree=add, to_degree=to_degree, path_type=default_add,
impairment_id=impairment_id)
# sanity check: raise an error if per_degree from or to degrees are not in the correct list
# raise an error if user defined path_type is not consistent with inferred path_type:
for item in roadm.per_degree_impairments.values():
if item['from_degree'] not in correct_from_degrees + correct_add or \
item['to_degree'] not in correct_to_degrees + correct_drop:
msg = f'Roadm {roadm.uid} has wrong from-to degree uid {item["from_degree"]} - {item["to_degree"]}'
raise NetworkTopologyError(msg)
def add_roadm_booster(network, roadm):
next_nodes = [n for n in network.successors(roadm)
if not (isinstance(n, elements.Transceiver) or isinstance(n, elements.Fused)
@@ -529,7 +597,7 @@ def add_roadm_booster(network, roadm):
network.remove_edge(roadm, next_node)
amp = elements.Edfa(
uid=f'Edfa_booster_{roadm.uid}_to_{next_node.uid}',
params=json_io.Amp.default_values,
params=EdfaParams.default_values,
metadata={
'location': {
'latitude': roadm.lat,
@@ -555,7 +623,7 @@ def add_roadm_preamp(network, roadm):
network.remove_edge(prev_node, roadm)
amp = elements.Edfa(
uid=f'Edfa_preamp_{roadm.uid}_from_{prev_node.uid}',
params=json_io.Amp.default_values,
params=EdfaParams.default_values,
metadata={
'location': {
'latitude': roadm.lat,
@@ -584,7 +652,7 @@ def add_inline_amplifier(network, fiber):
network.remove_edge(fiber, next_node)
amp = elements.Edfa(
uid=f'Edfa_{fiber.uid}',
params=json_io.Amp.default_values,
params=EdfaParams.default_values,
metadata={
'location': {
'latitude': (fiber.lat + next_node.lat) / 2,
@@ -701,7 +769,11 @@ def add_fiber_padding(network, fibers, padding, equipment):
next_node = get_next_node(fiber, network)
if isinstance(next_node, elements.Fused):
continue
# do not pad if this is a Raman Fiber
if isinstance(fiber, elements.RamanFiber):
continue
this_span_loss = span_loss(network, fiber, equipment)
fiber.design_span_loss = this_span_loss
if this_span_loss < padding:
# add a padding att_in at the input of the 1st fiber:
# address the case when several fibers are spliced together
@@ -710,6 +782,7 @@ def add_fiber_padding(network, fibers, padding, equipment):
# just after a roadm: need to check that first_fiber is really a fiber
if isinstance(first_fiber, elements.Fiber):
first_fiber.params.att_in = first_fiber.params.att_in + padding - this_span_loss
fiber.design_span_loss += first_fiber.params.att_in
def add_missing_elements_in_network(network, equipment):
@@ -762,6 +835,7 @@ def build_network(network, equipment, pref_ch_db, pref_total_db, set_connector_l
set_egress_amplifier(network, roadm, equipment, pref_ch_db, pref_total_db, verbose)
for roadm in roadms:
set_roadm_input_powers(network, roadm, equipment, pref_ch_db)
set_roadm_internal_paths(roadm, network)
for fiber in [f for f in network.nodes() if isinstance(f, (elements.Fiber, elements.RamanFiber))]:
set_fiber_input_power(network, fiber, equipment, pref_ch_db)

View File

@@ -46,21 +46,36 @@ class RamanParams(Parameters):
self.result_spatial_resolution = result_spatial_resolution # [m]
self.solver_spatial_resolution = solver_spatial_resolution # [m]
def to_json(self):
return {"flag": self.flag,
"result_spatial_resolution": self.result_spatial_resolution,
"solver_spatial_resolution": self.solver_spatial_resolution}
class NLIParams(Parameters):
def __init__(self, method='gn_model_analytic', dispersion_tolerance=1, phase_shift_tolerance=0.1,
computed_channels=None):
computed_channels=None, computed_number_of_channels=None):
"""Simulation parameters used within the Nli Solver
:params method: formula for NLI calculation
:params dispersion_tolerance: tuning parameter for ggn model solution
:params phase_shift_tolerance: tuning parameter for ggn model solution
:params computed_channels: the NLI is evaluated for these channels and extrapolated for the others
:params computed_number_of_channels: the NLI is evaluated for this number of channels equally distributed
in the spectrum and extrapolated for the others
"""
self.method = method.lower()
self.dispersion_tolerance = dispersion_tolerance
self.phase_shift_tolerance = phase_shift_tolerance
self.computed_channels = computed_channels
self.computed_number_of_channels = computed_number_of_channels
def to_json(self):
return {"method": self.method,
"dispersion_tolerance": self.dispersion_tolerance,
"phase_shift_tolerance": self.phase_shift_tolerance,
"computed_channels": self.computed_channels,
"computed_number_of_channels": self.computed_number_of_channels}
class SimParams(Parameters):
@@ -98,8 +113,68 @@ class RoadmParams(Parameters):
self.pmd = kwargs['pmd']
self.pdl = kwargs['pdl']
self.restrictions = kwargs['restrictions']
self.roadm_path_impairments = self.get_roadm_path_impairments(kwargs['roadm-path-impairments'])
except KeyError as e:
raise ParametersError(f'ROADM configurations must include {e}. Configuration: {kwargs}')
self.per_degree_impairments = kwargs.get('per_degree_impairments', [])
def get_roadm_path_impairments(self, path_impairments_list):
"""Get the ROADM list of profiles for impairments definition
transform the ietf model into gnpy internal model: add a path-type in the attributes
"""
if not path_impairments_list:
return {}
authorized_path_types = {
'roadm-express-path': 'express',
'roadm-add-path': 'add',
'roadm-drop-path': 'drop',
}
roadm_path_impairments = {}
for path_impairment in path_impairments_list:
index = path_impairment['roadm-path-impairments-id']
path_type = next(key for key in path_impairment if key in authorized_path_types.keys())
impairment_dict = dict({'path-type': authorized_path_types[path_type]}, **path_impairment[path_type][0])
roadm_path_impairments[index] = RoadmImpairment(impairment_dict)
return roadm_path_impairments
class RoadmPath:
def __init__(self, from_degree, to_degree, path_type, impairment_id=None, impairment=None):
"""Records roadm internal paths, types and impairment
path_type must be in "express", "add", "drop"
impairment_id must be one of the id detailed in equipement
"""
self.from_degree = from_degree
self.to_degree = to_degree
self.path_type = path_type
self.impairment_id = impairment_id
self.impairment = impairment
class RoadmImpairment:
"""Generic definition of impairments for express, add and drop"""
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)
class FusedParams(Parameters):
@@ -108,7 +183,33 @@ class FusedParams(Parameters):
DEFAULT_RAMAN_COEFFICIENT = {
# SSMF Raman coefficient profile normalized with respect to the effective area overlap (g0 * A_eff(f_probe, f_pump))
# SSMF Raman coefficient profile in terms of mode intensity (g0 * A_ff_overlap)
'gamma_raman': array(
[0.0, 8.524419934705497e-16, 2.643567866245371e-15, 4.410548410941305e-15, 6.153422961291078e-15,
7.484924703044943e-15, 8.452060808349209e-15, 9.101549322698156e-15, 9.57837595158966e-15,
1.0008642675474562e-14, 1.0865773569905647e-14, 1.1300776305865833e-14, 1.2143238647099625e-14,
1.3231065750676068e-14, 1.4624900971525384e-14, 1.6013330554840492e-14, 1.7458119359310242e-14,
1.9320241330434762e-14, 2.1720395392873534e-14, 2.4137337406734775e-14, 2.628163218460466e-14,
2.8041019963285974e-14, 2.9723155447089933e-14, 3.129353531005888e-14, 3.251796163324624e-14,
3.3198839487612773e-14, 3.329527690685666e-14, 3.313155691238456e-14, 3.289013852154548e-14,
3.2458917188506916e-14, 3.060684277937575e-14, 3.2660349473783173e-14, 2.957419109657689e-14,
2.518894321396672e-14, 1.734560485857344e-14, 9.902860761605233e-15, 7.219176385099358e-15,
6.079565990401311e-15, 5.828373065963427e-15, 7.20580801091692e-15, 7.561924351387493e-15,
7.621152352332206e-15, 6.8859886780643254e-15, 5.629181047471162e-15, 3.679727598966185e-15,
2.7555869742500355e-15, 2.4810133942597675e-15, 2.2160080532403624e-15, 2.1440626024765557e-15,
2.33873070799544e-15, 2.557317929858713e-15, 3.039839048226572e-15, 4.8337165515610065e-15,
5.4647431818257436e-15, 5.229187813711269e-15, 4.510768525811313e-15, 3.3213473130607794e-15,
2.2602577027996455e-15, 1.969576495866441e-15, 1.5179853954188527e-15, 1.2953988551200156e-15,
1.1304672156251838e-15, 9.10004390675213e-16, 8.432919922183503e-16, 7.849224069008326e-16,
7.827568196032024e-16, 9.000514440646232e-16, 1.3025926460013665e-15, 1.5444108938497558e-15,
1.8795594063060786e-15, 1.7796130169921014e-15, 1.5938159865046653e-15, 1.1585522355108287e-15,
8.507044444633358e-16, 7.625404663756823e-16, 8.14510750925789e-16, 9.047944693473188e-16,
9.636431901702084e-16, 9.298633899602105e-16, 8.349739503637023e-16, 7.482901278066085e-16,
6.240794767134268e-16, 5.00652535687506e-16, 3.553373263685851e-16, 2.0344217706119682e-16,
1.4267522642294203e-16, 8.980016576743517e-17, 2.9829068181832594e-17, 1.4861959129014824e-17,
7.404482113326137e-18]
), # m/W
# SSMF Raman coefficient profile
'g0': array(
[0.00000000e+00, 1.12351610e-05, 3.47838074e-05, 5.79356636e-05, 8.06921680e-05, 9.79845709e-05, 1.10454361e-04,
1.18735302e-04, 1.24736889e-04, 1.30110053e-04, 1.41001273e-04, 1.46383247e-04, 1.57011792e-04, 1.70765865e-04,
@@ -123,22 +224,21 @@ DEFAULT_RAMAN_COEFFICIENT = {
2.03744008e-05, 1.81939341e-05, 1.31862121e-05, 9.65352116e-06, 8.62698322e-06, 9.18688016e-06, 1.01737784e-05,
1.08017817e-05, 1.03903588e-05, 9.30040333e-06, 8.30809173e-06, 6.90650401e-06, 5.52238029e-06, 3.90648708e-06,
2.22908227e-06, 1.55796177e-06, 9.77218716e-07, 3.23477236e-07, 1.60602454e-07, 7.97306386e-08]
), # [m/W]
), # [1 / (W m)]
# Note the non-uniform spacing of this range; this is required for properly capturing the Raman peak shape.
'frequency_offset': array([
0., 0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5, 8., 8.5, 9., 9.5, 10., 10.5, 11., 11.5,
12.,
12.5, 12.75, 13., 13.25, 13.5, 14., 14.5, 14.75, 15., 15.5, 16., 16.5, 17., 17.5, 18., 18.25, 18.5, 18.75, 19.,
19.5, 20., 20.5, 21., 21.5, 22., 22.5, 23., 23.5, 24., 24.5, 25., 25.5, 26., 26.5, 27., 27.5, 28., 28.5, 29.,
29.5,
30., 30.5, 31., 31.5, 32., 32.5, 33., 33.5, 34., 34.5, 35., 35.5, 36., 36.5, 37., 37.5, 38., 38.5, 39., 39.5,
40.,
40.5, 41., 41.5, 42.]
) * 1e12, # [Hz]
12., 12.5, 12.75, 13., 13.25, 13.5, 14., 14.5, 14.75, 15., 15.5, 16., 16.5, 17., 17.5, 18., 18.25, 18.5, 18.75,
19., 19.5, 20., 20.5, 21., 21.5, 22., 22.5, 23., 23.5, 24., 24.5, 25., 25.5, 26., 26.5, 27., 27.5, 28., 28.5,
29., 29.5, 30., 30.5, 31., 31.5, 32., 32.5, 33., 33.5, 34., 34.5, 35., 35.5, 36., 36.5, 37., 37.5, 38., 38.5,
39., 39.5, 40., 40.5, 41., 41.5, 42.]) * 1e12, # [Hz]
# Raman profile reference frequency
'reference_frequency': 206184634112792 # [Hz] (1454 nm)}
'reference_frequency': 206.184634112792e12, # [Hz] (1454 nm)
# Raman profile reference effective area
'reference_effective_area': 75.74659443542413e-12 # [m^2] (@1454 nm)
}
@@ -211,14 +311,21 @@ class FiberParams(Parameters):
pi * self._core_radius ** 2 / self._effective_area)) ** 2
# Raman Gain Coefficient
raman_coefficient = kwargs.get('raman_coefficient', DEFAULT_RAMAN_COEFFICIENT)
self._g0 = asarray(raman_coefficient['g0'])
raman_reference_frequency = raman_coefficient['reference_frequency']
frequency_offset = asarray(raman_coefficient['frequency_offset'])
stokes_wave = raman_reference_frequency - frequency_offset
gamma_raman = self._g0 * self.effective_area_overlap(stokes_wave, raman_reference_frequency)
normalized_gamma_raman = gamma_raman / raman_reference_frequency # 1 / m / W / Hz
self._raman_reference_frequency = raman_reference_frequency
raman_coefficient = kwargs.get('raman_coefficient')
if raman_coefficient is None:
self._raman_reference_frequency = DEFAULT_RAMAN_COEFFICIENT['reference_frequency']
frequency_offset = asarray(DEFAULT_RAMAN_COEFFICIENT['frequency_offset'])
gamma_raman = asarray(DEFAULT_RAMAN_COEFFICIENT['gamma_raman'])
stokes_wave = self._raman_reference_frequency - frequency_offset
normalized_gamma_raman = gamma_raman / self._raman_reference_frequency # 1 / m / W / Hz
self._g0 = gamma_raman / self.effective_area_overlap(stokes_wave, self._raman_reference_frequency)
else:
self._raman_reference_frequency = raman_coefficient['reference_frequency']
frequency_offset = asarray(raman_coefficient['frequency_offset'])
stokes_wave = self._raman_reference_frequency - frequency_offset
self._g0 = asarray(raman_coefficient['g0'])
gamma_raman = self._g0 * self.effective_area_overlap(stokes_wave, self._raman_reference_frequency)
normalized_gamma_raman = gamma_raman / self._raman_reference_frequency # 1 / m / W / Hz
# Raman gain coefficient array of the frequency offset constructed such that positive frequency values
# represent a positive power transfer from higher frequency and vice versa
@@ -355,6 +462,38 @@ class FiberParams(Parameters):
class EdfaParams:
default_values = {
'f_min': 191.3e12,
'f_max': 196.1e12,
'multi_band': None,
'bands': [],
'type_variety': '',
'type_def': '',
'gain_flatmax': None,
'gain_min': None,
'p_max': None,
'nf_model': None,
'dual_stage_model': None,
'preamp_variety': None,
'booster_variety': None,
'nf_min': None,
'nf_max': None,
'nf_coef': None,
'nf0': None,
'nf_fit_coeff': None,
'nf_ripple': 0,
'dgt': None,
'gain_ripple': 0,
'tilt_ripple': 0,
'f_ripple_ref': None,
'out_voa_auto': False,
'allowed_for_design': False,
'raman': False,
'pmd': 0,
'pdl': 0,
'advance_configurations_from_json': None
}
def __init__(self, **params):
try:
self.type_variety = params['type_variety']

View File

@@ -305,6 +305,10 @@ class NliSolver:
elif 'ggn_spectrally_separated' in sim_params.nli_params.method:
if sim_params.nli_params.computed_channels is not None:
cut_indices = array(sim_params.nli_params.computed_channels) - 1
elif sim_params.nli_params.computed_number_of_channels is not None:
nb_ch_computed = sim_params.nli_params.computed_number_of_channels
nb_ch = len(spectral_info.channel_number)
cut_indices = array([round(i * (nb_ch - 1) / (nb_ch_computed - 1)) for i in range(0, nb_ch_computed)])
else:
cut_indices = array(spectral_info.channel_number) - 1

View File

@@ -9,7 +9,7 @@ This module contains utility functions that are used with gnpy.
"""
from csv import writer
from numpy import pi, cos, sqrt, log10, linspace, zeros, shape, where, logical_and, mean
from numpy import pi, cos, sqrt, log10, linspace, zeros, shape, where, logical_and, mean, array
from scipy import constants
from copy import deepcopy
@@ -213,17 +213,6 @@ wavelength2freq = constants.lambda2nu
freq2wavelength = constants.nu2lambda
def freq2wavelength(value):
"""Converts frequency units to wavelength units.
>>> round(freq2wavelength(191.35e12) * 1e9, 3)
1566.723
>>> round(freq2wavelength(196.1e12) * 1e9, 3)
1528.773
"""
return constants.c / value
def snr_sum(snr, bw, snr_added, bw_added=12.5e9):
snr_added = snr_added - lin2db(bw / bw_added)
snr = -lin2db(db2lin(-snr) + db2lin(-snr_added))
@@ -452,3 +441,20 @@ def restore_order(elements, order):
[3, 2, 7]
"""
return [elements[i[0]] for i in sorted(enumerate(order), key=lambda x:x[1]) if elements[i[0]] is not None]
def calculate_absolute_min_or_zero(x: array) -> array:
"""Calculates the element-wise absolute minimum between the x and zero.
Parameters:
x (array): The first input array.
Returns:
array: The element-wise absolute minimum between x and zero.
Example:
>>> x = array([-1, 2, -3])
>>> calculate_absolute_min_or_zero(x)
array([1., 0., 3.])
"""
return (abs(x) - x) / 2

View File

@@ -1,160 +1,160 @@
{
"nf_fit_coeff": [
0.0008,
0.0272,
-0.2249,
6.4902
],
"f_min": 191.4e12,
"f_max": 196.1e12,
"nf_ripple": [
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0
],
"gain_ripple": [
-0.15656302345061,
-0.22244242043552,
-0.25188965661642,
-0.23575900335007,
-0.20897508375209,
-0.19440221943049,
-0.18324644053602,
-0.18053287269681,
-0.17113588777219,
-0.15460322445561,
-0.13550774706866,
-0.10606051088777,
-0.0765630234506,
-0.04962835008375,
-0.01319618927973,
0.01027114740367,
0.03378873534338,
0.04961788107202,
0.04494451423784,
0.0399193886097,
0.01584903685091,
-0.00420121440538,
-0.01847257118928,
-0.02475397822447,
-0.01053287269681,
0.01509526800668,
0.05921587102177,
0.1191656197655,
0.18147717755444,
0.23579878559464,
0.26941687604691,
0.27836159966498,
0.26956762981574,
0.23826109715241,
0.18936662479061,
0.1204721524288,
0.0453465242881,
-0.00877407872698,
-0.02199015912898,
0.00107516750419,
0.02795958961474,
0.02740682579566,
-0.01028161641541,
-0.05982935510889,
-0.06701528475711,
0.00223094639866,
0.14157768006701,
0.15017064489112
],
"dgt": [
1.0,
1.03941448941778,
1.07773189112355,
1.11575888725852,
1.15209185089701,
1.18632744096844,
1.21911100318577,
1.24931318255134,
1.27657903892303,
1.30069883494415,
1.32210817897091,
1.3405812000038,
1.35690844654118,
1.3710092503689,
1.38430337205545,
1.3966294751726,
1.40864903907609,
1.42089447397912,
1.43476940680732,
1.44977369463316,
1.46637521309853,
1.48420288841848,
1.50335352244996,
1.5242627235492,
1.54578500307573,
1.56750088631614,
1.58973304612691,
1.61073904908309,
1.63068023161292,
1.64799163036252,
1.66286684904577,
1.6761448370895,
1.68845480656382,
1.70379790088896,
1.72461030013125,
1.75428006928365,
1.79748596476494,
1.85543800978691,
1.92915262384742,
2.01414465424155,
2.10336369905543,
2.19013043016015,
2.26678136721453,
2.33147727493671,
2.38192717604575,
2.41879254989742,
2.44342862248888,
2.4553191172498
]
"nf_fit_coeff": [
0.0008,
0.0272,
-0.2249,
6.4902
],
"f_min": 191.4e12,
"f_max": 196.1e12,
"nf_ripple": [
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0
],
"gain_ripple": [
-0.15656302345061,
-0.22244242043552,
-0.25188965661642,
-0.23575900335007,
-0.20897508375209,
-0.19440221943049,
-0.18324644053602,
-0.18053287269681,
-0.17113588777219,
-0.15460322445561,
-0.13550774706866,
-0.10606051088777,
-0.0765630234506,
-0.04962835008375,
-0.01319618927973,
0.01027114740367,
0.03378873534338,
0.04961788107202,
0.04494451423784,
0.0399193886097,
0.01584903685091,
-0.00420121440538,
-0.01847257118928,
-0.02475397822447,
-0.01053287269681,
0.01509526800668,
0.05921587102177,
0.1191656197655,
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}

View File

@@ -1,108 +1,108 @@
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}

View File

@@ -1,80 +1,80 @@
{
"network_name": "EDFA Example Network - P2P",
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"type": "Transceiver",
"metadata": {
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}
},
{
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},
{
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},
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}
},
{
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}
"network_name": "EDFA Example Network - P2P",
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{
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],
"connections": [{
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},
{
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},
{
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},
{
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},
{
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{
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"connections": [
{
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},
{
"from_node": "Span1",
"to_node": "Edfa1"
},
{
"from_node": "Edfa1",
"to_node": "Site_B"
}
]
}

View File

@@ -1,323 +1,443 @@
{ "Edfa":[{
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{
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{
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{
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{
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{
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{
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{
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"preamp_variety": "4pumps_raman",
"booster_variety": "std_low_gain",
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},
{
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"type_def": "dual_stage",
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{
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{
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{
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{
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{
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}

View File

@@ -1,349 +1,371 @@
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View File

@@ -1,409 +1,441 @@
{
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{
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}

View File

@@ -1,12 +1,12 @@
{
"spectrum":[
{
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}
]
}

View File

@@ -1,23 +1,23 @@
{
"spectrum":[
{
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},
{
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}
]
}

View File

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

View File

@@ -1,304 +1,304 @@
{
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}

View File

@@ -193,8 +193,11 @@ def transmission_main_example(args=None):
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'] = db2lin(float(args.power)) * 1e-3
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'])
@@ -370,7 +373,9 @@ def path_requests_run(args=None):
'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)
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)

View File

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

View File

@@ -20,8 +20,8 @@ from gnpy.core.equipment import trx_mode_params
from gnpy.core.exceptions import ConfigurationError, EquipmentConfigError, NetworkTopologyError, ServiceError
from gnpy.core.science_utils import estimate_nf_model
from gnpy.core.info import Carrier
from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions
from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT
from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions, dbm2watt
from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT, EdfaParams
from gnpy.topology.request import PathRequest, Disjunction, compute_spectrum_slot_vs_bandwidth
from gnpy.topology.spectrum_assignment import mvalue_to_slots
from gnpy.tools.convert import xls_to_json_data
@@ -51,9 +51,10 @@ class _JsonThing:
clean_kwargs = {k: v for k, v in kwargs.items() if v != ''}
for k, v in default_values.items():
setattr(self, k, clean_kwargs.get(k, v))
if k not in clean_kwargs and name != 'Amp':
msg = f'\n WARNING missing {k} attribute in eqpt_config.json[{name}]' \
+ f'\n default value is {k} = {v}'
if k not in clean_kwargs and name != 'Amp' and v is not None and v != []:
# do not show this warning if the default value is None
msg = f'\n\tWARNING missing {k} attribute in eqpt_config.json[{name}]' \
+ f'\n\tdefault value is {k} = {v}\n'
_logger.warning(msg)
@@ -67,7 +68,8 @@ class SI(_JsonThing):
"power_range_db": [0, 0, 0.5],
"roll_off": 0.15,
"tx_osnr": 45,
"sys_margins": 0
"sys_margins": 0,
"tx_power_dbm": None # optional value in SI
}
def __init__(self, **kwargs):
@@ -95,13 +97,15 @@ class Span(_JsonThing):
class Roadm(_JsonThing):
default_values = {
'type_variety': 'default',
'add_drop_osnr': 100,
'pmd': 0,
'pdl': 0,
'restrictions': {
'preamp_variety_list': [],
'booster_variety_list': []
}
},
'roadm-path-impairments': []
}
def __init__(self, **kwargs):
@@ -180,35 +184,7 @@ class RamanFiber(Fiber):
class Amp(_JsonThing):
default_values = {
'f_min': 191.35e12,
'f_max': 196.1e12,
'type_variety': '',
'type_def': '',
'gain_flatmax': None,
'gain_min': None,
'p_max': None,
'nf_model': None,
'dual_stage_model': None,
'preamp_variety': None,
'booster_variety': None,
'nf_min': None,
'nf_max': None,
'nf_coef': None,
'nf0': None,
'nf_fit_coeff': None,
'nf_ripple': 0,
'dgt': None,
'gain_ripple': 0,
'tilt_ripple': 0,
'f_ripple_ref': None,
'out_voa_auto': False,
'allowed_for_design': False,
'raman': False,
'pmd': 0,
'pdl': 0,
'advance_configurations_from_json': None
}
default_values = EdfaParams.default_values
def __init__(self, **kwargs):
self.update_attr(self.default_values, kwargs, 'Amp')
@@ -294,7 +270,7 @@ def _spectrum_from_json(json_data):
label should be different for each partition
>>> json_data = {'spectrum': \
[{'f_min': 193.2e12, 'f_max': 193.4e12, 'slot_width': 50e9, 'baud_rate': 32e9, 'roll_off': 0.15, \
'delta_pdb': 1, 'tx_osnr': 45},\
'delta_pdb': 1, 'tx_osnr': 45, 'tx_power_dbm': -7},\
{'f_min': 193.4625e12, 'f_max': 193.9875e12, 'slot_width': 75e9, 'baud_rate': 64e9, 'roll_off': 0.15},\
{'f_min': 194.075e12, 'f_max': 194.075e12, 'slot_width': 100e9, 'baud_rate': 90e9, 'roll_off': 0.15},\
{'f_min': 194.2e12, 'f_max': 194.35e12, 'slot_width': 50e9, 'baud_rate': 32e9, 'roll_off': 0.15}]}
@@ -302,24 +278,24 @@ def _spectrum_from_json(json_data):
>>> for k, v in spectrum.items():
... print(f'{k}: {v}')
...
193200000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
193250000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
193300000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
193350000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
193400000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
193462500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
193537500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
193612500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
193687500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
193762500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
193837500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
193912500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
193987500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
194075000000000.0: Carrier(delta_pdb=0, baud_rate=90000000000.0, slot_width=100000000000.0, roll_off=0.15, tx_osnr=40, label='2-90.00G')
194200000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
194250000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
194300000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
194350000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
193200000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
193250000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
193300000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
193350000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
193400000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
193462500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
193537500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
193612500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
193687500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
193762500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
193837500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
193912500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
193987500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
194075000000000.0: Carrier(delta_pdb=0, baud_rate=90000000000.0, slot_width=100000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='2-90.00G')
194200000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
194250000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
194300000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
194350000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
"""
spectrum = {}
json_data = sorted(json_data, key=lambda x: x['f_min'])
@@ -335,6 +311,9 @@ def _spectrum_from_json(json_data):
# default tx_osnr is set to 40 dB
if 'tx_osnr' not in part:
part['tx_osnr'] = 40
# default tx_power_dbm is set to 0 dBn
if 'tx_power_dbm' not in part:
part['tx_power_dbm'] = 0
# starting freq is exactly f_min to be consistent with utils.automatic_nch
# first partition min occupation is f_min - slot_width / 2 (central_frequency is f_min)
# supposes that carriers are centered on frequency
@@ -353,7 +332,8 @@ def _spectrum_from_json(json_data):
part['slot_width']):
spectrum[current_freq] = Carrier(delta_pdb=part['delta_pdb'], baud_rate=part['baud_rate'],
slot_width=part['slot_width'], roll_off=part['roll_off'],
tx_osnr=part['tx_osnr'], label=part['label'])
tx_osnr=part['tx_osnr'], tx_power=dbm2watt(part['tx_power_dbm']),
label=part['label'])
previous_part_max_freq = current_freq + part['slot_width'] / 2
return spectrum
@@ -389,11 +369,13 @@ def _update_dual_stage(equipment):
def _roadm_restrictions_sanity_check(equipment):
"""verifies that booster and preamp restrictions specified in roadm equipment are listed in the edfa."""
restrictions = equipment['Roadm']['default'].restrictions['booster_variety_list'] + \
equipment['Roadm']['default'].restrictions['preamp_variety_list']
for amp_name in restrictions:
if amp_name not in equipment['Edfa']:
raise EquipmentConfigError(f'ROADM restriction {amp_name} does not refer to a defined EDFA name')
for roadm_type, roadm_eqpt in equipment['Roadm'].items():
restrictions = roadm_eqpt.restrictions['booster_variety_list'] + \
roadm_eqpt.restrictions['preamp_variety_list']
for amp_name in restrictions:
if amp_name not in equipment['Edfa']:
raise EquipmentConfigError(f'ROADM {roadm_type} restriction {amp_name} does not refer to a '
+ 'defined EDFA name')
def _check_fiber_vs_raman_fiber(equipment):
@@ -434,6 +416,9 @@ def _equipment_from_json(json_data, filename):
elif key == 'Roadm':
equipment[key][subkey] = Roadm(**entry)
elif key == 'SI':
# use power_dbm value for tx_power_dbm if the key is not in 'SI'
# if 'tx_power_dbm' not in entry.keys():
# entry['tx_power_dbm'] = entry['power_dbm']
equipment[key][subkey] = SI(**entry)
elif key == 'Transceiver':
equipment[key][subkey] = Transceiver(**entry)
@@ -509,7 +494,7 @@ def network_from_json(json_data, equipment):
temp = merge_amplifier_restrictions(temp, extra_params)
el_config['params'] = temp
el_config['type_variety'] = variety
elif (typ in ['Fiber', 'RamanFiber']):
elif (typ in ['Fiber', 'RamanFiber', 'Roadm']):
raise ConfigurationError(f'The {typ} of variety type {variety} was not recognized:'
'\nplease check it is properly defined in the eqpt_config json file')
elif typ == 'Edfa':
@@ -600,7 +585,6 @@ def requests_from_json(json_data, equipment):
params['nodes_list'] = [n['num-unnum-hop']['node-id'] for n in nd_list]
params['loose_list'] = [n['num-unnum-hop']['hop-type'] for n in nd_list]
# recover trx physical param (baudrate, ...) from type and mode
# in trx_mode_params optical power is read from equipment['SI']['default'] and
# nb_channel is computed based on min max frequency and spacing
try:
trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
@@ -608,13 +592,11 @@ def requests_from_json(json_data, equipment):
msg = f'Equipment Config error in {req["request-id"]}: {e}'
raise EquipmentConfigError(msg) from e
params.update(trx_params)
# optical power might be set differently in the request. if it is indicated then the
# params['power'] is updated
try:
if req['path-constraints']['te-bandwidth']['output-power']:
params['power'] = req['path-constraints']['te-bandwidth']['output-power']
except KeyError:
pass
params['power'] = req['path-constraints']['te-bandwidth'].get('output-power')
# params must not be None, but user can set to None: catch this case
if params['power'] is None:
params['power'] = dbm2watt(equipment['SI']['default'].power_dbm)
# same process for nb-channel
f_min = params['f_min']
f_max_from_si = params['f_max']
@@ -634,6 +616,14 @@ def requests_from_json(json_data, equipment):
params['path_bandwidth'] = req['path-constraints']['te-bandwidth']['path_bandwidth']
except KeyError:
pass
params['tx_power'] = req['path-constraints']['te-bandwidth'].get('tx_power')
default_tx_power_dbm = equipment['SI']['default'].tx_power_dbm
if params['tx_power'] is None:
# use request's input power in span instead
params['tx_power'] = params['power']
if default_tx_power_dbm is not None:
# use default tx power
params['tx_power'] = dbm2watt(default_tx_power_dbm)
_check_one_request(params, f_max_from_si)
requests_list.append(PathRequest(**params))
return requests_list

View File

@@ -36,7 +36,7 @@ RequestParams = namedtuple('RequestParams', 'request_id source destination bidir
' trx_mode nodes_list loose_list spacing power nb_channel f_min'
' f_max format baud_rate OSNR penalties bit_rate'
' roll_off tx_osnr min_spacing cost path_bandwidth effective_freq_slot'
' equalization_offset_db')
' equalization_offset_db, tx_power')
DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link_diverse'
' node_diverse disjunctions_req')
@@ -65,6 +65,7 @@ class PathRequest:
self.bit_rate = params.bit_rate
self.roll_off = params.roll_off
self.tx_osnr = params.tx_osnr
self.tx_power = params.tx_power
self.min_spacing = params.min_spacing
self.cost = params.cost
self.path_bandwidth = params.path_bandwidth
@@ -95,7 +96,8 @@ class PathRequest:
f'baud_rate:\t{temp} Gbaud',
f'bit_rate:\t{temp2} Gb/s',
f'spacing:\t{self.spacing * 1e-9} GHz',
f'power: \t{round(lin2db(self.power)+30, 2)} dBm',
f'power: \t{round(lin2db(self.power) + 30, 2)} dBm',
f'tx_power_dbm: \t{round(lin2db(self.tx_power) + 30, 2)} dBm',
f'nb channels: \t{self.nb_channel}',
f'path_bandwidth: \t{round(self.path_bandwidth * 1e-9, 2)} Gbit/s',
f'nodes-list:\t{self.nodes_list}',
@@ -337,18 +339,18 @@ def propagate(path, req, equipment):
else:
si = create_input_spectral_information(
f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
power=req.power, spacing=req.spacing, tx_osnr=req.tx_osnr, delta_pdb=req.offset_db)
spacing=req.spacing, tx_osnr=req.tx_osnr, tx_power=req.tx_power, delta_pdb=req.offset_db)
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)
else:
si = el(si)
path[0].update_snr(si.tx_osnr)
path[0].calc_penalties(req.penalties)
if any(isinstance(el, Roadm) for el in path):
path[-1].update_snr(si.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
else:
path[-1].update_snr(si.tx_osnr)
roadm_osnr.append(si.tx_osnr)
path[-1].update_snr(*roadm_osnr)
path[-1].calc_penalties(req.penalties)
return si
@@ -380,21 +382,24 @@ def propagate_and_optimize_mode(path, req, equipment):
raise ServiceError(msg)
spc_info = create_input_spectral_information(f_min=req.f_min, f_max=req.f_max,
roll_off=equipment['SI']['default'].roll_off,
baud_rate=this_br, power=req.power, spacing=req.spacing,
delta_pdb=this_offset, tx_osnr=req.tx_osnr)
baud_rate=this_br, spacing=req.spacing,
delta_pdb=this_offset, tx_osnr=req.tx_osnr,
tx_power=req.tx_power)
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)
else:
spc_info = el(spc_info)
for this_mode in modes_to_explore:
if path[-1].snr is not None:
path[0].update_snr(this_mode['tx_osnr'])
path[0].calc_penalties(this_mode['penalties'])
if any(isinstance(el, Roadm) for el in path):
path[-1].update_snr(this_mode['tx_osnr'], equipment['Roadm']['default'].add_drop_osnr)
else:
path[-1].update_snr(this_mode['tx_osnr'])
roadm_osnr.append(this_mode['tx_osnr'])
path[-1].update_snr(*roadm_osnr)
# remove the tx_osnr from roadm_osnr list for the next iteration
del roadm_osnr[-1]
path[-1].calc_penalties(this_mode['penalties'])
if round(min(path[-1].snr_01nm - path[-1].total_penalty), 2) \
> this_mode['OSNR'] + equipment['SI']['default'].sys_margins:
@@ -966,6 +971,7 @@ def compare_reqs(req1, req2, disjlist):
req1.format == req2.format and \
req1.OSNR == req2.OSNR and \
req1.roll_off == req2.roll_off and \
req1.tx_power == req2.tx_power and \
same_disj:
return True
else:

View File

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

View File

@@ -1,4 +1,5 @@
{ "Edfa":[{
{
"Edfa": [{
"type_variety": "CienaDB_medium_gain",
"type_def": "advanced_model",
"gain_flatmax": 25,
@@ -7,10 +8,9 @@
"advanced_config_from_json": "std_medium_gain_advanced_config.json",
"out_voa_auto": false,
"allowed_for_design": true
},
{
}, {
"type_variety": "std_medium_gain",
"type_def": "variable_gain",
"type_def": "variable_gain",
"gain_flatmax": 26,
"gain_min": 15,
"p_max": 21,
@@ -18,10 +18,9 @@
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
},
{
}, {
"type_variety": "std_low_gain",
"type_def": "variable_gain",
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 21,
@@ -29,8 +28,7 @@
"nf_max": 11,
"out_voa_auto": false,
"allowed_for_design": true
},
{
}, {
"type_variety": "test",
"type_def": "variable_gain",
"gain_flatmax": 25,
@@ -40,8 +38,7 @@
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
},
{
}, {
"type_variety": "test_fixed_gain",
"type_def": "fixed_gain",
"gain_flatmax": 21,
@@ -49,8 +46,7 @@
"p_max": 21,
"nf0": 5,
"allowed_for_design": true
},
{
}, {
"type_variety": "std_booster",
"type_def": "fixed_gain",
"gain_flatmax": 21,
@@ -58,18 +54,18 @@
"p_max": 21,
"nf0": 5,
"allowed_for_design": false
}
],
"Fiber":[{
}
],
"Fiber": [{
"type_variety": "SSMF",
"dispersion": 1.67e-05,
"effective_area": 83e-12,
"pmd_coef": 1.265e-15
}
],
"Span":[{
"power_mode":true,
"delta_power_range_db": [0,0,0.5],
}
],
"Span": [{
"power_mode": true,
"delta_power_range_db": [0, 0, 0.5],
"max_fiber_lineic_loss_for_raman": 0.25,
"target_extended_gain": 2.5,
"max_length": 150,
@@ -79,157 +75,218 @@
"EOL": 0,
"con_in": 0,
"con_out": 0
}
],
"Roadm":[{
}
],
"Roadm": [{
"type_variety": "example_test",
"target_pch_out_db": -18,
"add_drop_osnr": 35,
"pmd": 1e-12,
"pdl": 0.5,
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
},
"roadm-path-impairments": []
}, {
"type_variety": "example_detailed_impairments",
"target_pch_out_db": -20,
"add_drop_osnr": 35,
"pmd": 0,
"pdl": 0,
"restrictions": {
"preamp_variety_list":[],
"booster_variety_list":[]
},
"roadm-path-impairments": [
{
"roadm-path-impairments-id": 0,
"roadm-express-path": [{
"frequency-range": {
"lower-frequency": 191.3e12,
"upper-frequency": 196.1e12
},
"roadm-pmd": 0,
"roadm-cd": 0,
"roadm-pdl": 0,
"roadm-inband-crosstalk": 0,
"roadm-maxloss": 16.5
}
]
}, {
"roadm-path-impairments-id": 1,
"roadm-add-path": [{
"frequency-range": {
"lower-frequency": 191.3e12,
"upper-frequency": 196.1e12
},
"roadm-pmd": 0,
"roadm-cd": 0,
"roadm-pdl": 0,
"roadm-inband-crosstalk": 0,
"roadm-maxloss": 11.5,
"roadm-pmax": 2.5,
"roadm-osnr": 41,
"roadm-noise-figure": 23
}]
}, {
"roadm-path-impairments-id": 2,
"roadm-drop-path": [{
"frequency-range": {
"lower-frequency": 191.3e12,
"upper-frequency": 196.1e12
},
"roadm-pmd": 0,
"roadm-cd": 0,
"roadm-pdl": 0,
"roadm-inband-crosstalk": 0,
"roadm-maxloss": 11.5,
"roadm-minloss": 7.5,
"roadm-typloss": 10,
"roadm-pmin": -13.5,
"roadm-pmax": -9.5,
"roadm-ptyp": -12,
"roadm-osnr": 41,
"roadm-noise-figure": 15
}]
}]
}, {
"target_pch_out_db": -20,
"add_drop_osnr": 38,
"pmd": 0,
"pdl": 0,
"restrictions": {
"preamp_variety_list":[],
"booster_variety_list":[]
}
}],
"SI":[{
"preamp_variety_list": [],
"booster_variety_list": []
}
}
],
"SI": [{
"f_min": 191.3e12,
"f_max":196.1e12,
"f_max": 196.1e12,
"baud_rate": 32e9,
"spacing": 50e9,
"power_dbm": 0,
"power_range_db": [0,0,0.5],
"power_range_db": [0, 0, 0.5],
"roll_off": 0.15,
"tx_osnr": 100,
"sys_margins": 0
"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
}
]
"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
}
]
"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
}
]
}
]
"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
}
]
}
]
}

View File

@@ -63,6 +63,7 @@
{
"uid": "roadm Lannion_CAS",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -18.6,
"restrictions": {
@@ -87,6 +88,7 @@
{
"uid": "roadm Lorient_KMA",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -111,6 +113,7 @@
{
"uid": "roadm Vannes_KBE",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -134,6 +137,7 @@
{
"uid": "roadm Rennes_STA",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -157,6 +161,7 @@
{
"uid": "roadm Brest_KLA",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -1668,4 +1673,4 @@
"to_node": "fiber (Ploermel → Vannes_KBE)-"
}
]
}
}

View File

@@ -159,6 +159,7 @@
{
"uid": "roadm Lannion_CAS",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -183,6 +184,7 @@
{
"uid": "roadm Lorient_KMA",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -207,6 +209,7 @@
{
"uid": "roadm Vannes_KBE",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -230,6 +233,7 @@
{
"uid": "roadm Rennes_STA",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -253,6 +257,7 @@
{
"uid": "roadm Brest_KLA",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -276,6 +281,7 @@
{
"uid": "roadm a",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -301,6 +307,7 @@
{
"uid": "roadm b",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -326,6 +333,7 @@
{
"uid": "roadm c",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -350,6 +358,7 @@
{
"uid": "roadm d",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -373,6 +382,7 @@
{
"uid": "roadm e",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -396,6 +406,7 @@
{
"uid": "roadm f",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -420,6 +431,7 @@
{
"uid": "roadm g",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {
@@ -443,6 +455,7 @@
{
"uid": "roadm h",
"type": "Roadm",
"type_variety": "default",
"params": {
"target_pch_out_db": -20,
"restrictions": {

View File

@@ -1,4 +1,8 @@
INFO gnpy.tools.cli_examples:cli_examples.py Computing path requests meshTopologyExampleV2.xls into JSON format
WARNING gnpy.tools.json_io:json_io.py
WARNING missing type_variety attribute in eqpt_config.json[Roadm]
default value is type_variety = default
INFO gnpy.tools.json_io:json_io.py Automatically converting requests from XLS to JSON
INFO gnpy.topology.request:request.py
request 0

View File

@@ -1,4 +1,8 @@
INFO gnpy.tools.cli_examples:cli_examples.py Computing path requests CORONET_services.json into JSON format
WARNING gnpy.tools.json_io:json_io.py
WARNING missing type_variety attribute in eqpt_config.json[Roadm]
default value is type_variety = default
INFO gnpy.topology.request:request.py
request 0
Computing path from trx Abilene to trx Albany

View File

@@ -1,3 +1,7 @@
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'
WARNING gnpy.core.network:network.py

View File

@@ -1,3 +1,7 @@
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'
WARNING gnpy.core.network:network.py

View File

@@ -16,10 +16,13 @@ Transceiver trx_Stockholm
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): 2.00
Roadm roadm_Stockholm
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.00
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -78,9 +81,11 @@ Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2)
actual pch out (dBm): 2.03
output VOA (dB): 0.00
Roadm roadm_Norrköping
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.03
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -117,9 +122,11 @@ Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
actual pch out (dBm): 2.01
output VOA (dB): 0.00
Roadm roadm_Linköping
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.01
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -156,9 +163,11 @@ Edfa Edfa_preamp_roadm_Jönköping_from_fiber (Linköping → Jönköping)
actual pch out (dBm): 2.05
output VOA (dB): 0.00
Roadm roadm_Jönköping
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.05
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -195,9 +204,11 @@ Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
actual pch out (dBm): 2.02
output VOA (dB): 0.00
Roadm roadm_Borås
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.02
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -234,9 +245,11 @@ Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
actual pch out (dBm): 2.02
output VOA (dB): 0.00
Roadm roadm_Gothenburg
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.02
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Transceiver trx_Gothenburg
GSNR (0.1nm, dB): 18.89
GSNR (signal bw, dB): 14.86
@@ -246,6 +259,7 @@ Transceiver trx_Gothenburg
PMD (ps): 7.99
PDL (dB): 3.74
Latency (ms): 2.45
Actual pch out (dBm): 2.00
Transmission result for input power = 2.00 dBm:
Final GSNR (0.1 nm): 18.89 dB

View File

@@ -16,10 +16,13 @@ Transceiver trx_Stockholm
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): 2.00
Roadm roadm_Stockholm
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.00
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -78,9 +81,11 @@ Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2)
actual pch out (dBm): 2.03
output VOA (dB): 0.00
Roadm roadm_Norrköping
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.03
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -117,9 +122,11 @@ Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
actual pch out (dBm): 2.01
output VOA (dB): 0.00
Roadm roadm_Linköping
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.01
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -156,9 +163,11 @@ Edfa Edfa_preamp_roadm_Jönköping_from_fiber (Linköping → Jönköping)
actual pch out (dBm): 2.04
output VOA (dB): 0.00
Roadm roadm_Jönköping
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.04
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -195,9 +204,11 @@ Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
actual pch out (dBm): 2.02
output VOA (dB): 0.00
Roadm roadm_Borås
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.02
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
type_variety: openroadm_mw_mw_booster
effective gain(dB): 22.00
@@ -234,9 +245,11 @@ Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
actual pch out (dBm): 2.02
output VOA (dB): 0.00
Roadm roadm_Gothenburg
effective loss (dB): 22.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 22.00
Actual loss (dB): 22.02
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Transceiver trx_Gothenburg
GSNR (0.1nm, dB): 19.25
GSNR (signal bw, dB): 15.23
@@ -246,6 +259,7 @@ Transceiver trx_Gothenburg
PMD (ps): 7.99
PDL (dB): 3.74
Latency (ms): 2.45
Actual pch out (dBm): 2.00
Transmission result for input power = 2.00 dBm:
Final GSNR (0.1 nm): 19.25 dB

View File

@@ -21,6 +21,7 @@
bit_rate: None Gb/s
spacing: 50.0 GHz
power: 1.0 dBm
tx_power_dbm: 0.0 dBm
nb channels: 80
path_bandwidth: 100.0 Gbit/s
nodes-list: []
@@ -34,6 +35,7 @@
bit_rate: 100.0 Gb/s
spacing: 50.0 GHz
power: 1.0 dBm
tx_power_dbm: 0.0 dBm
nb channels: 95
path_bandwidth: 200.0 Gbit/s
nodes-list: ['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE']
@@ -47,6 +49,7 @@
bit_rate: 100.0 Gb/s
spacing: 50.0 GHz
power: 0.0 dBm
tx_power_dbm: 0.0 dBm
nb channels: 95
path_bandwidth: 60.0 Gbit/s
nodes-list: []
@@ -60,6 +63,7 @@
bit_rate: None Gb/s
spacing: 75.0 GHz
power: 3.0 dBm
tx_power_dbm: 0.0 dBm
nb channels: 63
path_bandwidth: 150.0 Gbit/s
nodes-list: []
@@ -73,6 +77,7 @@
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: []
@@ -86,6 +91,7 @@
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: []
@@ -99,6 +105,7 @@
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: []

View File

@@ -11,6 +11,7 @@
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: []

View File

@@ -16,6 +16,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = -2.50 dBm:
Transceiver trx Rennes_STA
@@ -27,6 +28,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = -2.00 dBm:
Transceiver trx Rennes_STA
@@ -38,6 +40,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = -1.50 dBm:
Transceiver trx Rennes_STA
@@ -49,6 +52,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = -1.00 dBm:
Transceiver trx Rennes_STA
@@ -60,6 +64,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = -0.50 dBm:
Transceiver trx Rennes_STA
@@ -71,6 +76,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = -0.00 dBm:
Transceiver trx Rennes_STA
@@ -82,6 +88,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = 0.50 dBm:
Transceiver trx Rennes_STA
@@ -93,6 +100,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = 1.00 dBm:
Transceiver trx Rennes_STA
@@ -104,6 +112,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = 1.50 dBm:
Transceiver trx Rennes_STA
@@ -115,6 +124,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = 2.00 dBm:
Transceiver trx Rennes_STA
@@ -126,6 +136,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = 2.50 dBm:
Transceiver trx Rennes_STA
@@ -137,6 +148,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
Propagating with input power = 3.00 dBm:
Transceiver trx Rennes_STA
@@ -148,6 +160,7 @@ Transceiver trx Rennes_STA
PMD (ps): 0.57
PDL (dB): 0.00
Latency (ms): 0.98
Actual pch out (dBm): 3.00
(Invalid source node 'brest' replaced with trx Brest_KLA)

View File

@@ -17,10 +17,13 @@ Transceiver trx Lannion_CAS
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): 0.00
Roadm roadm Lannion_CAS
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): 20.00
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa east edfa in Lannion_CAS to Corlay
type_variety: std_medium_gain
effective gain(dB): 21.00
@@ -79,9 +82,11 @@ Edfa west edfa in Lorient_KMA to Loudeac
actual pch out (dBm): 1.05
output VOA (dB): 0.00
Roadm roadm Lorient_KMA
effective loss (dB): 21.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 21.00
Actual loss (dB): 21.05
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Transceiver trx Lorient_KMA
GSNR (0.1nm, dB): 23.61
GSNR (signal bw, dB): 19.53
@@ -91,6 +96,7 @@ Transceiver trx Lorient_KMA
PMD (ps): 0.46
PDL (dB): 0.00
Latency (ms): 0.64
Actual pch out (dBm): 0.00
Transmission result for input power = 0.00 dBm:
Final GSNR (0.1 nm): 23.61 dB

View File

@@ -17,10 +17,13 @@ Transceiver trx Lannion_CAS
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): mode_1: 0.00, mode_2: 0.00
Roadm roadm Lannion_CAS
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.00, mode_2: 20.00
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Edfa east edfa in Lannion_CAS to Corlay
type_variety: std_medium_gain
effective gain(dB): 21.00
@@ -79,9 +82,11 @@ Edfa west edfa in Lorient_KMA to Loudeac
actual pch out (dBm): mode_1: 1.04, mode_2: 1.09
output VOA (dB): 0.00
Roadm roadm Lorient_KMA
effective loss (dB): 21.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Type_variety: default
Reference loss (dB): 21.00
Actual loss (dB): mode_1: 21.04, mode_2: 21.09
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Transceiver trx Lorient_KMA
GSNR (0.1nm, dB): mode_1: 23.66, mode_2: 23.81
GSNR (signal bw, dB): mode_1: 19.58, mode_2: 16.72
@@ -91,6 +96,7 @@ Transceiver trx Lorient_KMA
PMD (ps): 0.46
PDL (dB): 0.00
Latency (ms): 0.64
Actual pch out (dBm): mode_1: 0.00, mode_2: 0.00
Transmission result for input power = 0.00 dBm:
Final GSNR (0.1 nm): 23.72 dB

View File

@@ -17,10 +17,13 @@ Transceiver Site_A
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): mode_1: 0.00, mode_2: 0.00
Roadm roadm Site A
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.00, mode_2: 20.00
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Edfa booster A
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -145,9 +148,11 @@ Edfa Edfa5
actual pch out (dBm): mode_1: 0.05, mode_2: 0.08
output VOA (dB): 0.00
Roadm roadm Site C
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.05, mode_2: 20.08
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Edfa booster C
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -272,9 +277,11 @@ Edfa Edfa10
actual pch out (dBm): mode_1: 0.05, mode_2: 0.08
output VOA (dB): 0.00
Roadm roadm Site D
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.05, mode_2: 20.08
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Edfa booster D
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -333,9 +340,11 @@ Edfa Edfa12
actual pch out (dBm): mode_1: 0.03, mode_2: 0.04
output VOA (dB): 0.00
Roadm roadm Site E
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.03, mode_2: 20.04
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Edfa booster E
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -416,9 +425,11 @@ Edfa Edfa15
actual pch out (dBm): mode_1: 0.03, mode_2: 0.05
output VOA (dB): 0.00
Roadm roadm Site B
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.03, mode_2: 20.05
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -20.00
Transceiver Site_B
GSNR (0.1nm, dB): mode_1: 18.11, mode_2: 19.18
GSNR (signal bw, dB): mode_1: 14.02, mode_2: 12.09
@@ -428,6 +439,7 @@ Transceiver Site_B
PMD (ps): 1.39
PDL (dB): 0.00
Latency (ms): 5.88
Actual pch out (dBm): mode_1: 0.00, mode_2: 0.00
Transmission result for input power = 0.00 dBm:
Final GSNR (0.1 nm): 18.56 dB

View File

@@ -17,10 +17,13 @@ Transceiver Site_A
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): mode_1: 0.00, mode_2: 0.00
Roadm roadm Site A
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.00, mode_2: 16.99
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Edfa booster A
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -145,9 +148,11 @@ Edfa Edfa5
actual pch out (dBm): mode_1: 0.06, mode_2: 3.07
output VOA (dB): 0.00
Roadm roadm Site C
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.06, mode_2: 20.06
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Edfa booster C
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -272,9 +277,11 @@ Edfa Edfa10
actual pch out (dBm): mode_1: 0.06, mode_2: 3.07
output VOA (dB): 0.00
Roadm roadm Site D
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.06, mode_2: 20.06
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Edfa booster D
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -333,9 +340,11 @@ Edfa Edfa12
actual pch out (dBm): mode_1: 0.03, mode_2: 3.04
output VOA (dB): 0.00
Roadm roadm Site E
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.03, mode_2: 20.03
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Edfa booster E
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -416,9 +425,11 @@ Edfa Edfa15
actual pch out (dBm): mode_1: 0.04, mode_2: 3.05
output VOA (dB): 0.00
Roadm roadm Site B
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.04, mode_2: 20.04
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -16.99
Transceiver Site_B
GSNR (0.1nm, dB): mode_1: 17.91, mode_2: 20.37
GSNR (signal bw, dB): mode_1: 13.83, mode_2: 13.28
@@ -428,6 +439,7 @@ Transceiver Site_B
PMD (ps): 1.39
PDL (dB): 0.00
Latency (ms): 5.88
Actual pch out (dBm): mode_1: 0.00, mode_2: 0.00
Transmission result for input power = 0.00 dBm:
Final GSNR (0.1 nm): 18.94 dB

View File

@@ -17,10 +17,13 @@ Transceiver Site_A
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): mode_1: 0.00, mode_2: 0.00
Roadm roadm Site A
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.00, mode_2: 18.24
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Edfa booster A
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -145,9 +148,11 @@ Edfa Edfa5
actual pch out (dBm): mode_1: 0.05, mode_2: 1.82
output VOA (dB): 0.00
Roadm roadm Site C
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.05, mode_2: 20.06
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Edfa booster C
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -272,9 +277,11 @@ Edfa Edfa10
actual pch out (dBm): mode_1: 0.05, mode_2: 1.82
output VOA (dB): 0.00
Roadm roadm Site D
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.05, mode_2: 20.06
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Edfa booster D
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -333,9 +340,11 @@ Edfa Edfa12
actual pch out (dBm): mode_1: 0.03, mode_2: 1.79
output VOA (dB): 0.00
Roadm roadm Site E
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.03, mode_2: 20.03
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Edfa booster E
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -416,9 +425,11 @@ Edfa Edfa15
actual pch out (dBm): mode_1: 0.03, mode_2: 1.80
output VOA (dB): 0.00
Roadm roadm Site B
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): mode_1: 20.03, mode_2: 20.04
Reference pch out (dBm): -20.00
Actual pch out (dBm): mode_1: -20.00, mode_2: -18.24
Transceiver Site_B
GSNR (0.1nm, dB): mode_1: 18.02, mode_2: 20.22
GSNR (signal bw, dB): mode_1: 13.94, mode_2: 13.12
@@ -428,6 +439,7 @@ Transceiver Site_B
PMD (ps): 1.39
PDL (dB): 0.00
Latency (ms): 5.88
Actual pch out (dBm): mode_1: 0.00, mode_2: 0.00
Transmission result for input power = 0.00 dBm:
Final GSNR (0.1 nm): 18.94 dB

View File

@@ -16,6 +16,7 @@ Transceiver Site_A
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): 0.00
Fiber Span1
type_variety: SSMF
length (km): 80.00
@@ -47,6 +48,7 @@ Transceiver Site_B
PMD (ps): 0.36
PDL (dB): 0.00
Latency (ms): 0.39
Actual pch out (dBm): 0.00
Transmission result for input power = 0.00 dBm:
Final GSNR (0.1 nm): 31.18 dB

View File

@@ -16,6 +16,7 @@ Transceiver Site_A
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): 0.00
RamanFiber Span1
type_variety: SSMF
length (km): 80.00
@@ -25,112 +26,115 @@ RamanFiber Span1
(conn loss out includes EOL margin defined in eqpt_config.json)
reference pch out (dBm): -7.20
actual pch out (dBm): -7.47
reference gain (dB): 9.74
actual gain (dB): 9.8
Fused Fused1
loss (dB): 0.00
Edfa Edfa1
type_variety: std_low_gain
effective gain(dB): 5.20
effective gain(dB): 5.26
(before att_in and before output VOA)
noise figure (dB): 13.80
noise figure (dB): 13.74
(including att_in)
pad att_in (dB): 2.80
pad att_in (dB): 2.74
Power In (dBm): 11.61
Power Out (dBm): 16.81
Power Out (dBm): 16.87
Delta_P (dB): -2.00
target pch (dBm): -2.00
actual pch out (dBm): -2.26
actual pch out (dBm): -2.21
output VOA (dB): 0.00
Transceiver Site_B
GSNR (0.1nm, dB): 31.42
GSNR (signal bw, dB): 27.34
OSNR ASE (0.1nm, dB): 34.21
OSNR ASE (signal bw, dB): 30.13
GSNR (0.1nm, dB): 31.44
GSNR (signal bw, dB): 27.35
OSNR ASE (0.1nm, dB): 34.24
OSNR ASE (signal bw, dB): 30.16
CD (ps/nm): 1336.00
PMD (ps): 0.36
PDL (dB): 0.00
Latency (ms): 0.39
Actual pch out (dBm): 0.00
Transmission result for input power = 0.00 dBm:
Final GSNR (0.1 nm): 31.42 dB
Final GSNR (0.1 nm): 31.44 dB
The GSNR per channel at the end of the line is:
Ch. # Channel frequency (THz) Channel power (dBm) OSNR ASE (signal bw, dB) SNR NLI (signal bw, dB) GSNR (signal bw, dB)
1 191.35000 0.22 31.64 31.55 28.58
2 191.40000 0.18 31.62 31.46 28.53
3 191.45000 0.15 31.60 31.37 28.47
4 191.50000 0.11 31.58 31.28 28.42
5 191.55000 0.05 31.54 31.20 28.36
6 191.60000 -0.01 31.51 31.11 28.30
7 191.65000 -0.07 31.48 31.03 28.24
8 191.70000 -0.12 31.45 30.95 28.18
9 191.75000 -0.18 31.42 30.87 28.13
10 191.80000 -0.25 31.38 30.79 28.07
11 191.85000 -0.31 31.35 30.72 28.01
12 191.90000 -0.38 31.31 30.64 27.95
13 191.95000 -0.44 31.27 30.57 27.90
14 192.00000 -0.51 31.24 30.50 27.84
15 192.05000 -0.58 31.20 30.42 27.78
16 192.10000 -0.64 31.16 30.35 27.73
17 192.15000 -0.71 31.12 30.29 27.67
18 192.20000 -0.78 31.08 30.22 27.62
19 192.25000 -0.85 31.04 30.22 27.60
20 192.30000 -0.93 31.00 30.22 27.58
21 192.35000 -1.00 30.96 30.23 27.57
22 192.40000 -1.08 30.91 30.23 27.55
23 192.45000 -1.16 30.87 30.23 27.53
24 192.50000 -1.23 30.82 30.24 27.51
25 192.55000 -1.30 30.78 30.24 27.49
26 192.60000 -1.37 30.74 30.24 27.47
27 192.65000 -1.44 30.70 30.25 27.46
28 192.70000 -1.52 30.65 30.25 27.44
29 192.75000 -1.59 30.61 30.25 27.42
30 192.80000 -1.66 30.57 30.26 27.40
31 192.85000 -1.73 30.52 30.26 27.38
32 192.90000 -1.80 30.48 30.26 27.36
33 192.95000 -1.87 30.43 30.27 27.34
34 193.00000 -1.94 30.39 30.27 27.32
35 193.05000 -2.01 30.35 30.27 27.30
36 193.10000 -2.08 30.30 30.28 27.28
37 193.15000 -2.15 30.26 30.28 27.26
38 193.20000 -2.22 30.22 30.29 27.24
39 193.25000 -2.29 30.17 30.31 27.23
40 193.30000 -2.36 30.13 30.32 27.21
41 193.35000 -2.43 30.08 30.33 27.19
42 193.40000 -2.50 30.04 30.35 27.18
43 193.45000 -2.56 29.99 30.36 27.16
44 193.50000 -2.63 29.95 30.37 27.14
45 193.55000 -2.71 29.90 30.39 27.12
46 193.60000 -2.78 29.85 30.40 27.11
47 193.65000 -2.85 29.80 30.41 27.09
48 193.70000 -2.93 29.75 30.43 27.07
49 193.75000 -3.00 29.70 30.44 27.05
50 193.80000 -3.07 29.65 30.45 27.02
51 193.85000 -3.15 29.60 30.47 27.00
52 193.90000 -3.22 29.55 30.48 26.98
53 193.95000 -3.29 29.50 30.50 26.96
54 194.00000 -3.37 29.45 30.51 26.94
55 194.05000 -3.44 29.40 30.52 26.92
56 194.10000 -3.52 29.35 30.54 26.89
57 194.15000 -3.59 29.30 30.59 26.89
58 194.20000 -3.66 29.25 30.64 26.88
59 194.25000 -3.74 29.19 30.70 26.87
60 194.30000 -3.81 29.14 30.75 26.86
61 194.35000 -3.89 29.09 30.81 26.86
62 194.40000 -3.96 29.04 30.87 26.85
63 194.45000 -4.04 28.98 30.93 26.84
64 194.50000 -4.11 28.93 30.98 26.83
65 194.55000 -4.18 28.88 31.04 26.82
66 194.60000 -4.25 28.83 31.10 26.81
67 194.65000 -4.31 28.78 31.17 26.80
68 194.70000 -4.38 28.74 31.23 26.79
69 194.75000 -4.45 28.69 31.29 26.79
70 194.80000 -4.51 28.64 31.35 26.78
71 194.85000 -4.58 28.59 31.42 26.77
72 194.90000 -4.65 28.54 31.48 26.76
73 194.95000 -4.71 28.49 31.55 26.74
74 195.00000 -4.78 28.44 31.62 26.73
75 195.05000 -4.85 28.39 31.69 26.72
76 195.10000 -4.91 28.34 31.69 26.69
1 191.35000 0.27 31.66 31.55 28.60
2 191.40000 0.24 31.64 31.46 28.54
3 191.45000 0.20 31.62 31.37 28.48
4 191.50000 0.17 31.60 31.28 28.43
5 191.55000 0.11 31.57 31.20 28.37
6 191.60000 0.05 31.54 31.11 28.31
7 191.65000 -0.01 31.51 31.03 28.25
8 191.70000 -0.07 31.47 30.95 28.20
9 191.75000 -0.13 31.44 30.87 28.14
10 191.80000 -0.19 31.41 30.79 28.08
11 191.85000 -0.26 31.37 30.72 28.02
12 191.90000 -0.32 31.34 30.64 27.97
13 191.95000 -0.39 31.30 30.57 27.91
14 192.00000 -0.45 31.26 30.50 27.85
15 192.05000 -0.52 31.23 30.42 27.80
16 192.10000 -0.59 31.19 30.35 27.74
17 192.15000 -0.66 31.15 30.29 27.69
18 192.20000 -0.72 31.11 30.22 27.63
19 192.25000 -0.79 31.07 30.22 27.62
20 192.30000 -0.87 31.03 30.22 27.60
21 192.35000 -0.95 30.99 30.23 27.58
22 192.40000 -1.02 30.94 30.23 27.56
23 192.45000 -1.10 30.90 30.23 27.54
24 192.50000 -1.18 30.85 30.24 27.52
25 192.55000 -1.25 30.81 30.24 27.51
26 192.60000 -1.32 30.77 30.24 27.49
27 192.65000 -1.39 30.73 30.25 27.47
28 192.70000 -1.46 30.68 30.25 27.45
29 192.75000 -1.53 30.64 30.25 27.43
30 192.80000 -1.60 30.60 30.26 27.41
31 192.85000 -1.67 30.55 30.26 27.39
32 192.90000 -1.74 30.51 30.26 27.37
33 192.95000 -1.81 30.47 30.27 27.35
34 193.00000 -1.89 30.42 30.27 27.33
35 193.05000 -1.95 30.38 30.27 27.32
36 193.10000 -2.02 30.34 30.28 27.30
37 193.15000 -2.09 30.29 30.28 27.28
38 193.20000 -2.16 30.25 30.29 27.26
39 193.25000 -2.23 30.20 30.31 27.24
40 193.30000 -2.30 30.16 30.32 27.23
41 193.35000 -2.37 30.11 30.33 27.21
42 193.40000 -2.44 30.07 30.35 27.20
43 193.45000 -2.51 30.02 30.36 27.18
44 193.50000 -2.58 29.98 30.37 27.16
45 193.55000 -2.65 29.93 30.39 27.14
46 193.60000 -2.72 29.88 30.40 27.12
47 193.65000 -2.80 29.83 30.41 27.10
48 193.70000 -2.87 29.79 30.43 27.08
49 193.75000 -2.94 29.74 30.44 27.06
50 193.80000 -3.02 29.69 30.45 27.04
51 193.85000 -3.09 29.64 30.47 27.02
52 193.90000 -3.16 29.59 30.48 27.00
53 193.95000 -3.24 29.54 30.50 26.98
54 194.00000 -3.31 29.49 30.51 26.96
55 194.05000 -3.38 29.44 30.52 26.94
56 194.10000 -3.46 29.39 30.54 26.91
57 194.15000 -3.53 29.33 30.59 26.91
58 194.20000 -3.61 29.28 30.64 26.90
59 194.25000 -3.68 29.23 30.70 26.89
60 194.30000 -3.76 29.18 30.75 26.89
61 194.35000 -3.83 29.13 30.81 26.88
62 194.40000 -3.91 29.07 30.87 26.87
63 194.45000 -3.98 29.02 30.93 26.86
64 194.50000 -4.05 28.97 30.98 26.85
65 194.55000 -4.12 28.92 31.04 26.84
66 194.60000 -4.19 28.87 31.10 26.84
67 194.65000 -4.26 28.82 31.17 26.83
68 194.70000 -4.32 28.77 31.23 26.82
69 194.75000 -4.39 28.72 31.29 26.81
70 194.80000 -4.46 28.68 31.35 26.80
71 194.85000 -4.52 28.63 31.42 26.79
72 194.90000 -4.59 28.58 31.48 26.78
73 194.95000 -4.66 28.53 31.55 26.77
74 195.00000 -4.72 28.48 31.62 26.76
75 195.05000 -4.79 28.43 31.69 26.75
76 195.10000 -4.86 28.38 31.69 26.71
(No source node specified: picked Site_A)

View File

@@ -16,10 +16,13 @@ Transceiver Site_A
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): 0.00
Roadm roadm Site A
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): 20.00
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa booster A
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -144,9 +147,11 @@ Edfa Edfa5
actual pch out (dBm): 0.06
output VOA (dB): 0.00
Roadm roadm Site C
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): 20.06
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa booster C
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -271,9 +276,11 @@ Edfa Edfa10
actual pch out (dBm): 0.06
output VOA (dB): 0.00
Roadm roadm Site D
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): 20.06
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa booster D
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -332,9 +339,11 @@ Edfa Edfa12
actual pch out (dBm): 0.03
output VOA (dB): 0.00
Roadm roadm Site E
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): 20.03
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa booster E
type_variety: std_medium_gain
effective gain(dB): 20.00
@@ -415,9 +424,11 @@ Edfa Edfa15
actual pch out (dBm): 0.04
output VOA (dB): 0.00
Roadm roadm Site B
effective loss (dB): 20.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 20.00
Actual loss (dB): 20.04
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Transceiver Site_B
GSNR (0.1nm, dB): 17.84
GSNR (signal bw, dB): 13.76
@@ -427,6 +438,7 @@ Transceiver Site_B
PMD (ps): 1.39
PDL (dB): 0.00
Latency (ms): 5.88
Actual pch out (dBm): 0.00
Transmission result for input power = 0.00 dBm:
Final GSNR (0.1 nm): 17.84 dB

View File

@@ -16,10 +16,13 @@ Transceiver trx Lannion_CAS
PMD (ps): 0.00
PDL (dB): 0.00
Latency (ms): 0.00
Actual pch out (dBm): 3.00
Roadm roadm Lannion_CAS
effective loss (dB): 23.00
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 23.00
Actual loss (dB): 23.00
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Edfa east edfa in Lannion_CAS to Corlay
type_variety: test
effective gain(dB): 21.18
@@ -78,9 +81,11 @@ Edfa west edfa in Lorient_KMA to Loudeac
actual pch out (dBm): 1.21
output VOA (dB): 0.00
Roadm roadm Lorient_KMA
effective loss (dB): 21.18
reference pch out (dBm): -20.00
actual pch out (dBm): -20.00
Type_variety: default
Reference loss (dB): 21.18
Actual loss (dB): 21.21
Reference pch out (dBm): -20.00
Actual pch out (dBm): -20.00
Transceiver trx Lorient_KMA
GSNR (0.1nm, dB): 23.77
GSNR (signal bw, dB): 19.69
@@ -90,6 +95,7 @@ Transceiver trx Lorient_KMA
PMD (ps): 0.46
PDL (dB): 0.00
Latency (ms): 0.64
Actual pch out (dBm): 3.00
Transmission result for input power = 3.00 dBm:
Final GSNR (0.1 nm): 23.77 dB

View File

@@ -74,8 +74,8 @@ def si(nch_and_spacing, bw):
nb_channel, spacing = nch_and_spacing
f_min = 191.3e12
f_max = automatic_fmax(f_min, spacing, nb_channel)
return create_input_spectral_information(f_min=f_min, f_max=f_max, roll_off=0.15, baud_rate=bw, power=1e-3,
spacing=spacing, tx_osnr=40.0)
return create_input_spectral_information(f_min=f_min, f_max=f_max, roll_off=0.15, baud_rate=bw,
spacing=spacing, tx_osnr=40.0, tx_power=1e-3)
@pytest.mark.parametrize("gain, nf_expected", [(10, 15), (15, 10), (25, 5.8)])
@@ -232,8 +232,8 @@ def test_amp_behaviour(tilt_target, delta_p):
fiber.params.con_in = 0
fiber.params.con_out = 0
fiber.ref_pch_in_dbm = 0.0
si = create_input_spectral_information(f_min=191.3e12, f_max=196.05e12, roll_off=0.15, baud_rate=64e9, power=0.001,
spacing=75e9, tx_osnr=None)
si = create_input_spectral_information(f_min=191.3e12, f_max=196.05e12, roll_off=0.15, baud_rate=64e9,
spacing=75e9, tx_osnr=None, tx_power=1e-3)
si = fiber(si)
total_sig_powerin = sum(si.signal)
sig_in = lin2db(si.signal)
@@ -320,7 +320,7 @@ def test_amp_saturation(delta_pdb_per_channel, base_power, delta_p):
si = create_arbitrary_spectral_information(frequency=frequency, slot_width=slot_width,
signal=signal, baud_rate=baud_rate, roll_off=0.15,
delta_pdb_per_channel=delta_pdb_per_channel,
tx_osnr=None)
tx_osnr=None, tx_power=None)
total_sig_powerin = sum(si.signal)
sig_in = lin2db(si.signal)
si = edfa(si)

View File

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

View File

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

View File

@@ -17,12 +17,14 @@ from copy import deepcopy
from gnpy.core.utils import lin2db, automatic_nch, dbm2watt, power_dbm_to_psd_mw_ghz, watt2dbm, psd2powerdbm
from gnpy.core.network import build_network
from gnpy.core.elements import Roadm
from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information, ReferenceCarrier
from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information, ReferenceCarrier, \
carriers_to_spectral_information
from gnpy.core.equipment import trx_mode_params
from gnpy.core.exceptions import ConfigurationError
from gnpy.tools.json_io import network_from_json, load_equipment, load_network, _spectrum_from_json, load_json, \
Transceiver, requests_from_json
from gnpy.topology.request import PathRequest, compute_constrained_path, propagate, propagate_and_optimize_mode
from gnpy.topology.spectrum_assignment import build_oms_list
TEST_DIR = Path(__file__).parent
@@ -54,6 +56,7 @@ def test_equalization_combination_degree(delta_pdb_per_channel, degree, equaliza
roadm_config = {
"uid": "roadm Lannion_CAS",
"type_variety": "default",
"params": {
"per_degree_pch_out_db": {
"east edfa in Lannion_CAS to Corlay": -16
@@ -68,10 +71,12 @@ def test_equalization_combination_degree(delta_pdb_per_channel, degree, equaliza
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
"roadm-path-impairments": []
}
}
roadm = Roadm(**roadm_config)
roadm.set_roadm_paths(from_degree='tata', to_degree=degree, path_type='express')
roadm.ref_pch_in_dbm['tata'] = 0
roadm.ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
frequency = 191e12 + array([0, 50e9, 150e9, 225e9, 275e9])
@@ -85,6 +90,7 @@ def test_equalization_combination_degree(delta_pdb_per_channel, degree, equaliza
to_json_before_propagation = {
'uid': 'roadm Lannion_CAS',
'type': 'Roadm',
"type_variety": "default",
'params': {
equalization_type: target,
'restrictions': {'preamp_variety_list': [], 'booster_variety_list': []},
@@ -229,7 +235,8 @@ def test_low_input_power(target_out, delta_pdb_per_channel, correction):
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
"roadm-path-impairments": []
},
"metadata": {
"location": {
@@ -241,6 +248,7 @@ def test_low_input_power(target_out, delta_pdb_per_channel, correction):
}
}
roadm = Roadm(**roadm_config)
roadm.set_roadm_paths(from_degree='tata', to_degree='toto', path_type='express')
roadm.ref_pch_in_dbm['tata'] = 0
roadm.ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
si = roadm(si, degree='toto', from_degree='tata')
@@ -281,7 +289,8 @@ def test_2low_input_power(target_out, delta_pdb_per_channel, correction):
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
"roadm-path-impairments": []
},
"metadata": {
"location": {
@@ -293,6 +302,7 @@ def test_2low_input_power(target_out, delta_pdb_per_channel, correction):
}
}
roadm = Roadm(**roadm_config)
roadm.set_roadm_paths(from_degree='tata', to_degree='toto', path_type='express')
roadm.ref_pch_in_dbm['tata'] = 0
roadm.ref_carrier = ReferenceCarrier(baud_rate=32e9, slot_width=50e9)
si = roadm(si, degree='toto', from_degree='tata')
@@ -322,10 +332,11 @@ def create_voyager_req(equipment, source, dest, bidir, nodes_list, loose_list, m
'nodes_list': nodes_list,
'loose_list': loose_list,
'path_bandwidth': 100.0e9,
'effective_freq_slot': None}
'effective_freq_slot': None,
'power': 1e-3,
'tx_power': 1e-3}
trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
params.update(trx_params)
params['power'] = dbm2watt(power_dbm) if power_dbm else dbm2watt(equipment['SI']['default'].power_dbm)
f_min = params['f_min']
f_max_from_si = params['f_max']
params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing'])
@@ -360,9 +371,9 @@ def test_initial_spectrum(mode, slot_width, power_dbm):
assert_array_equal(infos_expected.frequency, infos_actual.frequency)
assert_array_equal(infos_expected.baud_rate, infos_actual.baud_rate)
assert_array_equal(infos_expected.slot_width, infos_actual.slot_width)
assert_array_equal(infos_expected.signal, infos_actual.signal)
assert_array_equal(infos_expected.nli, infos_actual.nli)
assert_array_equal(infos_expected.ase, infos_actual.ase)
assert_allclose(infos_expected.signal, infos_actual.signal, rtol=1e-10)
assert_allclose(infos_expected.nli, infos_actual.nli, rtol=1e-10)
assert_allclose(infos_expected.ase, infos_actual.ase, rtol=1e-10)
assert_array_equal(infos_expected.roll_off, infos_actual.roll_off)
assert_array_equal(infos_expected.chromatic_dispersion, infos_actual.chromatic_dispersion)
assert_array_equal(infos_expected.pmd, infos_actual.pmd)
@@ -531,8 +542,8 @@ def test_equalization(case, deltap, target, mode, slot_width, equalization):
assert getattr(roadm, equalization) == target_psd
path = compute_constrained_path(network, req)
si = create_input_spectral_information(
f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate, power=req.power,
spacing=req.spacing, tx_osnr=req.tx_osnr)
f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
spacing=req.spacing, tx_osnr=req.tx_osnr, tx_power=req.power)
for i, el in enumerate(path):
if isinstance(el, Roadm):
si = el(si, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
@@ -575,9 +586,9 @@ def test_power_option(req_power):
infos_actual = propagate(path2, req, equipment)
assert_array_equal(infos_expected.baud_rate, infos_actual.baud_rate)
assert_array_equal(infos_expected.slot_width, infos_actual.slot_width)
assert_array_equal(infos_expected.signal, infos_actual.signal)
assert_array_equal(infos_expected.nli, infos_actual.nli)
assert_array_equal(infos_expected.ase, infos_actual.ase)
assert_allclose(infos_expected.signal, infos_actual.signal, rtol=1e-10)
assert_allclose(infos_expected.nli, infos_actual.nli, rtol=1e-10)
assert_allclose(infos_expected.ase, infos_actual.ase, rtol=1e-10)
assert_array_equal(infos_expected.roll_off, infos_actual.roll_off)
assert_array_equal(infos_expected.chromatic_dispersion, infos_actual.chromatic_dispersion)
assert_array_equal(infos_expected.pmd, infos_actual.pmd)
@@ -833,3 +844,103 @@ def test_power_offset_automatic_mode_selection(slot_width, value, equalization,
_, mode = propagate_and_optimize_mode(path, free_req, equipment)
assert mode['format'] == expected_mode
assert_allclose(path_expected[-1].snr_01nm, path[-1].snr_01nm, rtol=1e-5)
@pytest.mark.parametrize('tx_power_dbm', [-10, -8, 0, 10])
def test_tx_power(tx_power_dbm):
"""If carrier add power is below equalization target + ROADM add max loss, then equalizatio
can not be applied.
"""
json_data = load_json(NETWORK_FILENAME)
for el in json_data['elements']:
if el['uid'] == 'roadm Lannion_CAS':
el['type_variety'] = 'example_detailed_impairments'
equipment = load_equipment(EQPT_FILENAME)
network = network_from_json(json_data, equipment)
default_spectrum = equipment['SI']['default']
p_db = default_spectrum.power_dbm
p_total_db = p_db + lin2db(automatic_nch(default_spectrum.f_min, default_spectrum.f_max, default_spectrum.spacing))
build_network(network, equipment, p_db, p_total_db)
build_oms_list(network, equipment)
expected_roadm_lannion = {
"uid": "roadm Lannion_CAS",
"type": "Roadm",
"type_variety": "example_detailed_impairments",
"params": {
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
},
'per_degree_pch_out_db': {'east edfa in Lannion_CAS to Corlay': -20,
'east edfa in Lannion_CAS to Morlaix': -20,
'east edfa in Lannion_CAS to Stbrieuc': -20},
"target_pch_out_db": -20
},
'metadata': {
'location': {
'city': 'Lannion_CAS',
'latitude': 2.0,
'longitude': 0.0,
'region': 'RLD'
}
}
}
roadm = next(n for n in network.nodes() if n.uid == 'roadm Lannion_CAS')
assert roadm.to_json == expected_roadm_lannion
spectrum = _spectrum_from_json([
{
"f_min": 191.35e12,
"f_max": 191.35e12,
"baud_rate": 32e9,
"slot_width": 50e9,
"power_dbm": 0,
"roll_off": 0.15,
"tx_osnr": 40
},
{
"f_min": 193.15e12,
"f_max": 193.15e12,
"baud_rate": 32e9,
"slot_width": 50e9,
"power_dbm": 0,
"roll_off": 0.15,
"tx_osnr": 40,
"tx_power_dbm": tx_power_dbm
},
{
"f_min": 193.2e12,
"f_max": 193.2e12,
"baud_rate": 32e9,
"slot_width": 50e9,
"power_dbm": 0,
"roll_off": 0.15,
"tx_osnr": 40}])
power = 1.0e-3
si = carriers_to_spectral_information(initial_spectrum=spectrum,
power=power)
si = roadm(si, "east edfa in Lannion_CAS to Corlay", "trx Lannion_CAS")
# Checks that if tx_power on add port is below min required power, its equalization target can not be met
add_max_loss = next(e for e in getattr(equipment['Roadm']['example_detailed_impairments'], 'roadm-path-impairments')
if 'roadm-add-path' in e)['roadm-add-path'][0]['roadm-maxloss']
min_required_add_power = -20 + add_max_loss
power_reduction = max(0, min_required_add_power - tx_power_dbm)
assert_allclose(si.signal, dbm2watt(array([-20, -20 - power_reduction, -20])), rtol=1e-5)
path = ['trx Lannion_CAS',
'roadm Lannion_CAS',
'east edfa in Lannion_CAS to Stbrieuc',
'fiber (Lannion_CAS → Stbrieuc)-F056',
'east edfa in Stbrieuc to Rennes_STA',
'fiber (Stbrieuc → Rennes_STA)-F057',
'west edfa in Rennes_STA to Stbrieuc',
'roadm Rennes_STA',
'trx Rennes_STA']
si = carriers_to_spectral_information(initial_spectrum=spectrum,
power=power)
for i, uid in enumerate(path):
node = next(n for n in network.nodes() if n.uid == uid)
if isinstance(node, Roadm):
si = node(si, path[i + 1], path[i - 1])
else:
si = node(si)
assert_allclose(watt2dbm(si.signal + si.ase + si.nli), array([-20, -20, -20]), rtol=1e-5)

View File

@@ -53,7 +53,8 @@ def create_rq(equipment, srce, dest, bdir, nd_list, ls_list, mode, power_dbm):
'effective_freq_slot': None,
'path_bandwidth': 100000000000.0,
'spacing': 50e9 if mode == 'mode 1' else 75e9,
'power': dbm2watt(power_dbm)
'power': dbm2watt(power_dbm),
'tx_power': dbm2watt(power_dbm)
}
trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
params.update(trx_params)

View File

@@ -12,7 +12,7 @@ def test_create_arbitrary_spectral_information():
si = create_arbitrary_spectral_information(frequency=[193.25e12, 193.3e12, 193.35e12],
baud_rate=32e9, signal=[1, 1, 1],
delta_pdb_per_channel=[1, 1, 1],
tx_osnr=40.0)
tx_osnr=40.0, tx_power=[1, 1, 1])
assert_array_equal(si.baud_rate, array([32e9, 32e9, 32e9]))
assert_array_equal(si.slot_width, array([37.5e9, 37.5e9, 37.5e9]))
assert_array_equal(si.signal, ones(3))
@@ -33,7 +33,7 @@ def test_create_arbitrary_spectral_information():
si = create_arbitrary_spectral_information(frequency=array([193.35e12, 193.3e12, 193.25e12]),
slot_width=array([50e9, 50e9, 50e9]),
baud_rate=32e9, signal=array([1, 2, 3]),
tx_osnr=40.0)
tx_osnr=40.0, tx_power=array([1, 2, 3]))
assert_array_equal(si.signal, array([3, 2, 1]))
@@ -41,16 +41,16 @@ def test_create_arbitrary_spectral_information():
r'larger than the slot width for channels: \[1, 3\].'):
create_arbitrary_spectral_information(frequency=[193.25e12, 193.3e12, 193.35e12], signal=1,
baud_rate=[64e9, 32e9, 64e9], slot_width=50e9,
tx_osnr=40.0)
tx_osnr=40.0, tx_power=1)
with pytest.raises(SpectrumError, match='Spectrum required slot widths larger than the frequency spectral '
r'distances between channels: \[\(1, 2\), \(3, 4\)\].'):
create_arbitrary_spectral_information(frequency=[193.26e12, 193.3e12, 193.35e12, 193.39e12], signal=1,
tx_osnr=40.0, baud_rate=32e9, slot_width=50e9)
tx_osnr=40.0, baud_rate=32e9, slot_width=50e9, tx_power=1)
with pytest.raises(SpectrumError, match='Spectrum required slot widths larger than the frequency spectral '
r'distances between channels: \[\(1, 2\), \(2, 3\)\].'):
create_arbitrary_spectral_information(frequency=[193.25e12, 193.3e12, 193.35e12], signal=1, baud_rate=49e9,
tx_osnr=40.0, roll_off=0.1)
tx_osnr=40.0, roll_off=0.1, tx_power=1)
with pytest.raises(SpectrumError,
match='Dimension mismatch in input fields.'):
create_arbitrary_spectral_information(frequency=[193.25e12, 193.3e12, 193.35e12], signal=[1, 2], baud_rate=49e9,
tx_osnr=40.0)
tx_osnr=40.0, tx_power=1)

View File

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

View File

@@ -228,6 +228,7 @@ def test_design_non_amplified_link(elem1, elem2, expected_gain, expected_delta_p
equipment = load_equipment(EQPT_FILENAME)
equipment['Span']['default'].power_mode = power_mode
equipment['SI']['default'].power_dbm = p_db
equipment['SI']['default'].tx_power_dbm = p_db
network = network_from_json(json_data, equipment)
edfa = next(a for a in network.nodes() if a.uid == 'edfa')
edfa.params.out_voa_auto = True

View File

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

View File

@@ -25,7 +25,7 @@ import pytest
from copy import deepcopy
from gnpy.core.utils import automatic_nch, lin2db
from gnpy.core.network import build_network, add_missing_elements_in_network
from gnpy.core.exceptions import ServiceError
from gnpy.core.exceptions import ServiceError, ConfigurationError
from gnpy.topology.request import (jsontocsv, requests_aggregation, compute_path_dsjctn, deduplicate_disjunctions,
compute_path_with_disjunction, ResultElement, PathRequest)
from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum
@@ -352,6 +352,7 @@ def test_excel_ila_constraints(source, destination, route_list, hoptype, expecte
'cost': None,
'roll_off': 0,
'tx_osnr': 0,
'tx_power': 0,
'penalties': None,
'min_spacing': None,
'nb_channel': 0,
@@ -565,3 +566,52 @@ def test_service_json_constraint_order():
rqs = requests_from_json(data, equipment)
assert rqs[0].nodes_list == ['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE']
assert rqs[0].loose_list == ['STRICT', 'LOOSE', 'STRICT', 'STRICT']
@pytest.mark.parametrize('type_variety, target_pch_out_db, correct_variety', [(None, -20, True),
('example_test', -18, True),
('example', None, False)])
def test_roadm_type_variety(type_variety, target_pch_out_db, correct_variety):
"""Checks that if element has no variety, the default one is applied, and if it has one
that the type_variety is correctly applied
"""
json_data = {
"elements": [{
"uid": "roadm Oakland",
"type": "Roadm",
}],
"connections": []
}
expected_roadm = {
"uid": "roadm Oakland",
"type": "Roadm",
"params": {
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
'metadata': {
'location': {
'city': None,
'latitude': 0,
'longitude': 0,
'region': None
}
}
}
if type_variety is not None:
json_data['elements'][0]['type_variety'] = type_variety
expected_roadm['type_variety'] = type_variety
else:
# Do not add type variety in json_data to test that it creates a 'default' type_variety
expected_roadm['type_variety'] = 'default'
expected_roadm['params']['target_pch_out_db'] = target_pch_out_db
equipment = load_equipment(eqpt_filename)
if correct_variety:
network = network_from_json(json_data, equipment)
roadm = [n for n in network.nodes()][0]
assert roadm.to_json == expected_roadm
else:
with pytest.raises(ConfigurationError):
network = network_from_json(json_data, equipment)

View File

@@ -52,7 +52,8 @@ def propagation(input_power, con_in, con_out, dest):
p = db2lin(p) * 1e-3
spacing = 50e9 # THz
si = create_input_spectral_information(f_min=191.3e12, f_max=191.3e12 + 79 * spacing, roll_off=0.15,
baud_rate=32e9, power=p, spacing=spacing, tx_osnr=None)
baud_rate=32e9, spacing=spacing, tx_osnr=None,
tx_power=p)
source = next(transceivers[uid] for uid in transceivers if uid == 'trx A')
sink = next(transceivers[uid] for uid in transceivers if uid == dest)
path = dijkstra_path(network, source, sink)
@@ -181,7 +182,7 @@ def test_json_element(error, json_data, expected_msg):
network = network_from_json(json_data, equipment)
elem = next(e for e in network.nodes() if e.uid == 'Elem')
si = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
baud_rate=32e9, power=1.0e-3, spacing=50.0e9, tx_osnr=45)
baud_rate=32e9, tx_power=1.0e-3, spacing=50.0e9, tx_osnr=45)
with pytest.raises(error, match=re.escape(expected_msg)):
_ = elem(si)

View File

@@ -19,11 +19,12 @@ from gnpy.core.utils import lin2db, automatic_nch
from gnpy.core.elements import Fused, Roadm, Edfa, Transceiver, EdfaOperational, EdfaParams, Fiber
from gnpy.core.parameters import FiberParams, RoadmParams, FusedParams
from gnpy.core.network import build_network, design_network
from gnpy.tools.json_io import network_from_json, load_equipment, load_json, Amp
from gnpy.tools.json_io import network_from_json, load_equipment, load_json, Amp, _equipment_from_json
from gnpy.core.equipment import trx_mode_params
from gnpy.topology.request import PathRequest, compute_constrained_path, propagate
from gnpy.core.info import create_input_spectral_information, Carrier
from gnpy.core.utils import db2lin, dbm2watt
from gnpy.core.utils import db2lin, dbm2watt, merge_amplifier_restrictions
from gnpy.core.exceptions import ConfigurationError, NetworkTopologyError
TEST_DIR = Path(__file__).parent
@@ -212,9 +213,11 @@ def test_restrictions(restrictions, equipment):
raise AssertionError()
@pytest.mark.parametrize('roadm_type_variety, roadm_b_maxloss', [('default', 0),
('example_detailed_impairments', 16.5)])
@pytest.mark.parametrize('power_dbm', [0, +1, -2])
@pytest.mark.parametrize('prev_node_type, effective_pch_out_db', [('edfa', -20.0), ('fused', -22.0)])
def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm, roadm_type_variety, roadm_b_maxloss):
"""Check that egress power of roadm is equal to target power if input power is greater
than target power else, that it is equal to input power. Use a simple two hops A-B-C topology
for the test where the prev_node in ROADM B is either an amplifier or a fused, so that the target
@@ -225,6 +228,8 @@ def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
json_network = load_json(TEST_DIR / 'data/twohops_roadm_power_test.json')
prev_node = next(n for n in json_network['elements'] if n['uid'] == 'west edfa in node B to ila2')
json_network['elements'].remove(prev_node)
roadm_b = next(element for element in json_network['elements'] if element['uid'] == 'roadm node B')
roadm_b['type_variety'] = roadm_type_variety
if prev_node_type == 'edfa':
prev_node = {'uid': 'west edfa in node B to ila2', 'type': 'Edfa'}
elif prev_node_type == 'fused':
@@ -249,7 +254,9 @@ def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
'format': '',
'path_bandwidth': 100e9,
'effective_freq_slot': None,
'nb_channel': nb_channel
'nb_channel': nb_channel,
'power': dbm2watt(power_dbm),
'tx_power': dbm2watt(power_dbm)
}
trx_params = trx_mode_params(equipment)
params.update(trx_params)
@@ -258,7 +265,7 @@ def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
path = compute_constrained_path(network, req)
si = create_input_spectral_information(
f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
power=req.power, spacing=req.spacing, tx_osnr=req.tx_osnr)
spacing=req.spacing, tx_osnr=req.tx_osnr, tx_power=req.tx_power)
for i, el in enumerate(path):
if isinstance(el, Roadm):
power_in_roadm = si.signal + si.ase + si.nli
@@ -268,10 +275,9 @@ def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
# if previous was an EDFA, power level at ROADM input is enough for the ROADM to apply its
# target power (as specified in equipment ie -20 dBm)
# if it is a Fused, the input power to the ROADM is smaller than the target power, and the
# ROADM cannot apply this target. In this case, it is assumed that the ROADM has 0 dB loss
# so the output power will be the same as the input power, which for this particular case
# corresponds to -22dBm + power_dbm
# next step (for ROADM modelling) will be to apply a minimum loss for ROADMs !
# ROADM cannot apply this target. If the ROADM has 0 dB loss the output power will be the same
# as the input power, which for this particular case corresponds to -22dBm + power_dbm.
# If ROADM has a minimum losss, then output power will be -22dBm + power_dbm - ROADM loss. !
if prev_node_type == 'edfa':
# edfa prev_node sets input power to roadm to a high enough value:
# check that target power is correctly set in the ROADM
@@ -282,9 +288,10 @@ def test_roadm_target_power(prev_node_type, effective_pch_out_db, power_dbm):
# fused prev_node does not reamplify power after fiber propagation, so input power
# to roadm is low.
# check that target power correctly reports power_dbm from previous propagation
assert_allclose(el.ref_pch_out_dbm, effective_pch_out_db + power_dbm, rtol=1e-3)
# Check that egress power of roadm is not equalized: power out is the same as power in.
assert_allclose(power_out_roadm, power_in_roadm, rtol=1e-3)
assert_allclose(el.ref_pch_out_dbm, effective_pch_out_db + power_dbm - roadm_b_maxloss, rtol=1e-3)
# Check that egress power of roadm is not equalized:
# power out is the same as power in minus the ROADM loss.
assert_allclose(power_out_roadm, power_in_roadm / db2lin(roadm_b_maxloss), rtol=1e-3)
assert effective_pch_out_db + power_dbm ==\
pytest.approx(lin2db(min(power_in_roadm) * 1e3), rel=1e-3)
else:
@@ -304,7 +311,9 @@ def create_per_oms_request(network, eqpt, req_power):
'format': '',
'path_bandwidth': 100e9,
'effective_freq_slot': None,
'nb_channel': nb_channel
'nb_channel': nb_channel,
'power': dbm2watt(req_power),
'tx_power': dbm2watt(req_power)
}
trx_params = trx_mode_params(eqpt)
params.update(trx_params)
@@ -332,6 +341,7 @@ def create_per_oms_request(network, eqpt, req_power):
carrier['label'] = ""
carrier['slot_width'] = req.spacing
carrier['delta_pdb'] = 0
carrier['tx_power'] = 1e-3
req.initial_spectrum = {(req.f_min + req.spacing * f): Carrier(**carrier)
for f in range(1, req.nb_channel + 1)}
req_list.append(req)
@@ -346,6 +356,7 @@ def create_per_oms_request(network, eqpt, req_power):
carrier['label'] = ""
carrier['slot_width'] = req.spacing
carrier['delta_pdb'] = 0
carrier['tx_power'] = 1e-3
req.initial_spectrum = {(req.f_min + req.spacing * f): Carrier(**carrier) for f in range(1, req.nb_channel + 1)}
req_list.append(req)
return req_list
@@ -527,3 +538,162 @@ def test_compare_design_propagation_settings(power_dbm, req_power, amp_with_delt
getattr(getattr(element_copy, key), subkey), rtol=1e-12)
else:
assert getattr(getattr(element, key), subkey) == getattr(getattr(element_copy, key), subkey)
@pytest.mark.parametrize("restrictions, fail", [
({'preamp_variety_list': [], 'booster_variety_list':[]}, False),
({'preamp_variety_list': ['std_medium_gain', 'std_low_gain'], 'booster_variety_list':['std_medium_gain']}, False),
# the two next amp type_variety do not exist
({'preamp_variety_list': [], 'booster_variety_list':['booster_medium_gain']}, True),
({'preamp_variety_list': ['std_medium_gain', 'preamp_high_gain'], 'booster_variety_list':[]}, True)])
def test_wrong_restrictions(restrictions, fail):
"""Check that sanity_check correctly raises an error when restriction is incorrect and that library
correctly includes restrictions.
"""
json_data = load_json(EQPT_LIBRARY_NAME)
# define wrong restriction
json_data['Roadm'][0]['restrictions'] = restrictions
if fail:
with pytest.raises(ConfigurationError):
_ = _equipment_from_json(json_data, EQPT_LIBRARY_NAME)
else:
equipment = _equipment_from_json(json_data, EQPT_LIBRARY_NAME)
assert equipment['Roadm']['example_test'].restrictions == restrictions
@pytest.mark.parametrize('roadm, from_degree, to_degree, expected_impairment_id, expected_type', [
('roadm Lannion_CAS', 'trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 1, 'add'),
('roadm Lannion_CAS', 'west edfa in Lannion_CAS to Stbrieuc', 'east edfa in Lannion_CAS to Corlay', 0, 'express'),
('roadm Lannion_CAS', 'west edfa in Lannion_CAS to Stbrieuc', 'trx Lannion_CAS', 2, 'drop'),
('roadm h', 'west edfa in h to g', 'trx h', None, 'drop')
])
def test_roadm_impairments(roadm, from_degree, to_degree, expected_impairment_id, expected_type):
"""Check that impairment id and types are correct
"""
json_data = load_json(NETWORK_FILE_NAME)
for el in json_data['elements']:
if el['uid'] == 'roadm Lannion_CAS':
el['type_variety'] = 'example_detailed_impairments'
equipment = load_equipment(EQPT_LIBRARY_NAME)
network = network_from_json(json_data, equipment)
build_network(network, equipment, 0.0, 20.0)
roadm = next(n for n in network.nodes() if n.uid == roadm)
assert roadm.get_roadm_path(from_degree, to_degree).path_type == expected_type
assert roadm.get_roadm_path(from_degree, to_degree).impairment_id == expected_impairment_id
@pytest.mark.parametrize('type_variety, from_degree, to_degree, impairment_id, expected_type', [
(None, 'trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 1, 'add'),
('default', 'trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 3, 'add'),
(None, 'west edfa in Lannion_CAS to Stbrieuc', 'east edfa in Lannion_CAS to Corlay', None, 'express')
])
def test_roadm_per_degree_impairments(type_variety, from_degree, to_degree, impairment_id, expected_type):
"""Check that impairment type is correct also if per degree impairment is defined
"""
json_data = load_json(EQPT_LIBRARY_NAME)
assert 'type_variety' not in json_data['Roadm'][2]
json_data['Roadm'][2]['roadm-path-impairments'] = [
{
"roadm-path-impairments-id": 1,
"roadm-add-path": [{
"roadm-osnr": 41,
}]
}, {
"roadm-path-impairments-id": 3,
"roadm-add-path": [{
"roadm-inband-crosstalk": 0,
"roadm-osnr": 20,
"roadm-noise-figure": 23
}]
}]
equipment = _equipment_from_json(json_data, EQPT_LIBRARY_NAME)
assert equipment['Roadm']['default'].type_variety == 'default'
json_data = load_json(NETWORK_FILE_NAME)
for el in json_data['elements']:
if el['uid'] == 'roadm Lannion_CAS' and type_variety is not None:
el['type_variety'] = type_variety
el['params'] = {
"per_degree_impairments": [
{
"from_degree": from_degree,
"to_degree": to_degree,
"impairment_id": impairment_id
}]
}
network = network_from_json(json_data, equipment)
build_network(network, equipment, 0.0, 20.0)
roadm = next(n for n in network.nodes() if n.uid == 'roadm Lannion_CAS')
assert roadm.get_roadm_path(from_degree, to_degree).path_type == expected_type
assert roadm.get_roadm_path(from_degree, to_degree).impairment_id == impairment_id
@pytest.mark.parametrize('from_degree, to_degree, impairment_id, error, message', [
('trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 2, NetworkTopologyError,
'Roadm roadm Lannion_CAS path_type is defined as drop but it should be add'), # wrong path_type
('trx Lannion_CAS', 'east edfa toto', 1, ConfigurationError,
'Roadm roadm Lannion_CAS has wrong from-to degree uid trx Lannion_CAS - east edfa toto'), # wrong degree
('trx Lannion_CAS', 'east edfa in Lannion_CAS to Corlay', 11, NetworkTopologyError,
'ROADM roadm Lannion_CAS: impairment profile id 11 is not defined in library') # wrong impairment_id
])
def test_wrong_roadm_per_degree_impairments(from_degree, to_degree, impairment_id, error, message):
"""Check that wrong per degree definitions are correctly catched
"""
equipment = load_equipment(EQPT_LIBRARY_NAME)
json_data = load_json(NETWORK_FILE_NAME)
for el in json_data['elements']:
if el['uid'] == 'roadm Lannion_CAS':
el['type_variety'] = 'example_detailed_impairments'
el['params'] = {
"per_degree_impairments": [
{
"from_degree": from_degree,
"to_degree": to_degree,
"impairment_id": impairment_id
}]
}
network = network_from_json(json_data, equipment)
with pytest.raises(error, match=message):
build_network(network, equipment, 0.0, 20.0)
@pytest.mark.parametrize('path_type, type_variety, expected_pmd, expected_pdl, expected_osnr', [
('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):
"""Check that impairments are correctly initialized, with this order:
- use equipment roadm impairments if no impairment are set in the ROADM instance
- use roadm global impairment if roadm global impairment are set
- use roadm detailed impairment for the corresponding path_type if roadm type_variety has detailed impairments
- use roadm per degree impairment if they are defined
"""
equipment = load_equipment(EQPT_LIBRARY_NAME)
extra_params = equipment['Roadm'][type_variety].__dict__
roadm_config = {
"uid": "roadm Lannion_CAS",
"params": {
"add_drop_osnr": 38,
"pmd": 5.0e-12,
"pdl": 0.5
}
}
if type_variety != 'default':
roadm_config["type_variety"] = type_variety
roadm_config['params'] = merge_amplifier_restrictions(roadm_config['params'], extra_params)
roadm = Roadm(**roadm_config)
roadm.set_roadm_paths(from_degree='tata', to_degree='toto', path_type=path_type)
assert roadm.get_roadm_path(from_degree='tata', to_degree='toto').path_type == path_type
assert 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
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)
else:
assert roadm.get_roadm_path(from_degree='tata', to_degree='toto').impairment.osnr == expected_osnr

View File

@@ -28,7 +28,8 @@ def test_fiber():
fiber.ref_pch_in_dbm = 0.0
# fix grid spectral information generation
spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
baud_rate=32e9, power=1e-3, spacing=50e9, tx_osnr=40.0)
baud_rate=32e9, spacing=50e9, tx_osnr=40.0,
tx_power=1e-3)
# propagation
spectral_info_out = fiber(spectral_info_input)
@@ -48,7 +49,7 @@ def test_fiber():
spectral_info_input = create_arbitrary_spectral_information(frequency=frequency, slot_width=slot_width,
signal=signal, baud_rate=baud_rate, roll_off=0.15,
delta_pdb_per_channel=delta_pdb_per_channel,
tx_osnr=40.0)
tx_osnr=40.0, tx_power=1e-3)
# propagation
spectral_info_out = fiber(spectral_info_input)
@@ -66,7 +67,8 @@ def test_raman_fiber():
"""Test the accuracy of propagating the RamanFiber."""
# spectral information generation
spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
baud_rate=32e9, power=1e-3, spacing=50e9, tx_osnr=40.0)
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 = RamanFiber(**load_json(TEST_DIR / 'data' / 'test_science_utils_fiber_config.json'))
fiber.ref_pch_in_dbm = 0.0
@@ -103,7 +105,8 @@ def test_fiber_lumped_losses_srs(set_sim_params):
"""Test the accuracy of Fiber with lumped losses propagation."""
# spectral information generation
spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
baud_rate=32e9, power=1e-3, spacing=50e9, tx_osnr=40.0)
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'))

View File

@@ -288,6 +288,7 @@ def request_set():
'cost': 1,
'roll_off': 0.15,
'tx_osnr': 38,
'tx_power': 0.001,
'penalties': {},
'min_spacing': 37.5e9,
'nb_channel': None,

View File

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