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							| @@ -29,7 +29,8 @@ jobs: | ||||
|           - py38 | ||||
|           - py39 | ||||
|           - py310 | ||||
|           - py311-cover | ||||
|           - py311 | ||||
|           - py312-cover | ||||
|         include: | ||||
|           - tox_env: docs | ||||
|             dnf_install: graphviz | ||||
| @@ -46,7 +47,7 @@ jobs: | ||||
|       - uses: actions/setup-python@v4 | ||||
|         name: Install Python | ||||
|         with: | ||||
|           python-version: '3.11' | ||||
|           python-version: '3.12' | ||||
|       - uses: casperdcl/deploy-pypi@bb869aafd89f657ceaafe9561d3b5584766c0f95 | ||||
|         with: | ||||
|           password: ${{ secrets.PYPI_API_TOKEN }} | ||||
| @@ -116,5 +117,31 @@ jobs: | ||||
|             python_version: "3.10" | ||||
|           - os: windows-2022 | ||||
|             python_version: "3.11" | ||||
|           - os: windows-2022 | ||||
|             python_version: "3.12" | ||||
|           - os: macos-12 | ||||
|             python_version: "3.11" | ||||
|           - os: macos-13 | ||||
|             python_version: "3.12" | ||||
|  | ||||
|   paywalled-platforms: | ||||
|     name: Tests on paywalled platforms | ||||
|     if: github.repository_owner == 'Telecominfraproject' | ||||
|     runs-on: ${{ matrix.os }} | ||||
|     steps: | ||||
|       - uses: actions/checkout@v3 | ||||
|         with: | ||||
|           fetch-depth: 0 | ||||
|       - uses: actions/setup-python@v4 | ||||
|         with: | ||||
|           python-version: ${{ matrix.python_version }} | ||||
|       - run: | | ||||
|           pip install -r tests/requirements.txt | ||||
|           pip install --editable . | ||||
|           pytest -vv | ||||
|     strategy: | ||||
|       fail-fast: false | ||||
|       matrix: | ||||
|         include: | ||||
|           - os: macos-13-xlarge # Apple M1 CPU | ||||
|             python_version: "3.12" | ||||
|   | ||||
| @@ -8,7 +8,7 @@ | ||||
| [](https://github.com/Telecominfraproject/oopt-gnpy/graphs/contributors) | ||||
| [](https://codecov.io/gh/Telecominfraproject/oopt-gnpy) | ||||
| [](https://doi.org/10.5281/zenodo.3458319) | ||||
| [](https://matrix.to/#/%23oopt-gnpy%3Afoss.wtf?via=matrix.org&via=foss.wtf) | ||||
| [](https://matrix.to/#/%23oopt-gnpy%3Amatrix.org?via=matrix.org) | ||||
|  | ||||
| GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks. | ||||
| We are a consortium of operators, vendors, and academic researchers sponsored via the [Telecom Infra Project](http://telecominfraproject.com)'s [OOPT/PSE](https://telecominfraproject.com/open-optical-packet-transport) working group. | ||||
|   | ||||
| @@ -1848,3 +1848,15 @@ month={Sept},} | ||||
|   title = {Telecom Infra Project}, | ||||
|   url = {https://www.telecominfraproject.com}, | ||||
| } | ||||
|  | ||||
| @ARTICLE{DAmicoJLT2022, | ||||
|   author={D’Amico, Andrea and Correia, Bruno and London, Elliot and Virgillito, | ||||
|   Emanuele and Borraccini, Giacomo and Napoli, Antonio and Curri, Vittorio}, | ||||
|   journal={Journal of Lightwave Technology}, | ||||
|   title={Scalable and Disaggregated GGN Approximation Applied to a C+L+S Optical Network}, | ||||
|   year={2022}, | ||||
|   volume={40}, | ||||
|   number={11}, | ||||
|   pages={3499-3511}, | ||||
|   doi={10.1109/JLT.2022.3162134} | ||||
| } | ||||
|   | ||||
| @@ -61,40 +61,69 @@ Fiber | ||||
|  | ||||
| The fiber library currently describes SSMF and NZDF but additional fiber types can be entered by the user following the same model: | ||||
|  | ||||
| +----------------------+-----------+------------------------------------------+ | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | field                        | type            | description                                    | | ||||
| +======================+===========+==========================================+ | ||||
| +==============================+=================+================================================+ | ||||
| | ``type_variety``             | (string)        | a unique name to ID the fiber in the           | | ||||
| |                              |                 | JSON or Excel template topology input          | | ||||
| |                              |                 | file                                           | | ||||
| +----------------------+-----------+------------------------------------------+ | ||||
| | ``dispersion``       | (number)  | In :math:`s \times m^{-1} \times m^{-1}`.| | ||||
| +----------------------+-----------+------------------------------------------+ | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | ``dispersion``               | (number)        | In :math:`s \times m^{-1} \times m^{-1}`.      | | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | ``dispersion_slope``         | (number)        | In :math:`s \times m^{-1} \times m^{-1}        | | ||||
| |                              |                 | \times m^{-1}`                                 | | ||||
| +----------------------+-----------+------------------------------------------+ | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | ``dispersion_per_frequency`` | (dict)          | Dictionary of dispersion values evaluated at   | | ||||
| |                              |                 | various frequencies, as follows:               | | ||||
| |                              |                 | ``{"value": [], "frequency": []}``.            | | ||||
| |                              |                 | ``value`` in                                   | | ||||
| |                              |                 | :math:`s \times m^{-1} \times m^{-1}` and      | | ||||
| |                              |                 | ``frequency`` in Hz.                           | | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | ``effective_area``           | (number)        | Effective area of the fiber (not just          | | ||||
| |                              |                 | the MFD circle). This is the                   | | ||||
| |                              |                 | :math:`A_{eff}`, see e.g., the                 | | ||||
| |                              |                 | `Corning whitepaper on MFD/EA`_.               | | ||||
| |                              |                 | Specified in :math:`m^{2}`.                    | | ||||
| +----------------------+-----------+------------------------------------------+ | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | ``gamma``                    | (number)        | Coefficient :math:`\gamma = 2\pi\times         | | ||||
| |                              |                 | n^2/(\lambda*A_{eff})`.                        | | ||||
| |                              |                 | If not provided, this will be derived          | | ||||
| |                              |                 | from the ``effective_area``                    | | ||||
| |                              |                 | :math:`A_{eff}`.                               | | ||||
| |                              |                 | In :math:`w^{-1} \times m^{-1}`.               | | ||||
| +----------------------+-----------+------------------------------------------+ | ||||
| |                              |                 | This quantity is evaluated at the              | | ||||
| |                              |                 | reference frequency and it is scaled           | | ||||
| |                              |                 | along frequency accordingly to the             | | ||||
| |                              |                 | effective area scaling.                        | | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | ``pmd_coef``                 | (number)        | Polarization mode dispersion (PMD)             | | ||||
| |                              |                 | coefficient. In                                | | ||||
| |                              |                 | :math:`s\times\sqrt{m}^{-1}`.                  | | ||||
| +----------------------+-----------+------------------------------------------+ | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | ``lumped_losses``            | (array)         | Places along the fiber length with extra       | | ||||
| |                              |                 | losses. Specified as a loss in dB at           | | ||||
| |                              |                 | each relevant position (in km):                | | ||||
| |                              |                 | ``{"position": 10, "loss": 1.5}``)             | | ||||
| +----------------------+-----------+------------------------------------------+ | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
| | ``raman_coefficient``        | (dict)          | The fundamental parameter that describes       | | ||||
| |                              |                 | the regulation of the power transfer           | | ||||
| |                              |                 | between channels during fiber propagation      | | ||||
| |                              |                 | is the Raman gain coefficient (see             | | ||||
| |                              |                 | :cite:`DAmicoJLT2022` for further              | | ||||
| |                              |                 | details); :math:`f_{ref}` represents the       | | ||||
| |                              |                 | pump reference frequency used for the          | | ||||
| |                              |                 | Raman gain coefficient profile                 | | ||||
| |                              |                 | measurement ("reference_frequency"),           | | ||||
| |                              |                 | :math:`\Delta f` is the frequency shift        | | ||||
| |                              |                 | between the pump and the specific Stokes       | | ||||
| |                              |                 | wave, the Raman gain coefficient               | | ||||
| |                              |                 | in terms of optical power                      | | ||||
| |                              |                 | :math:`g_0`, expressed in                      | | ||||
| |                              |                 | :math:`1/(m\;W)`.                              | | ||||
| |                              |                 | Default values measured for a SSMF are         | | ||||
| |                              |                 | considered when not specified.                 | | ||||
| +------------------------------+-----------------+------------------------------------------------+ | ||||
|  | ||||
| .. _Corning whitepaper on MFD/EA: https://www.corning.com/microsites/coc/oem/documents/specialty-fiber/WP7071-Mode-Field-Diam-and-Eff-Area.pdf | ||||
|  | ||||
|   | ||||
| @@ -126,9 +126,9 @@ that can be easily evaluated extending the FWM theory from a set of discrete | ||||
| tones - the standard FWM theory introduced back in the 90s by Inoue | ||||
| :cite:`Innoue-FWM`- to a continuity of tones, possibly spectrally shaped. | ||||
| Signals propagating in the fiber are not equivalent to Gaussian noise, but | ||||
| thanks to the absence of in-line compensation for choromatic dispersion, the | ||||
| thanks to the absence of in-line compensation for chromatic dispersion, the | ||||
| become so, over short distances.  So, the Gaussian noise model with incoherent | ||||
| accumulation of NLI has estensively proved to be a quick yet accurate and | ||||
| accumulation of NLI has extensively proved to be a quick yet accurate and | ||||
| conservative tool to estimate propagation impairments of fiber propagation. | ||||
| Note that the GN-model has not been derived with the aim of an *exact* | ||||
| performance estimation, but to pursue a conservative performance prediction. | ||||
|   | ||||
| @@ -1,8 +1,8 @@ | ||||
| ''' | ||||
| """ | ||||
| GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks. It is based on the Gaussian Noise Model. | ||||
|  | ||||
| Signal propagation is implemented in :py:mod:`.core`. | ||||
| Path finding and spectrum assignment is in :py:mod:`.topology`. | ||||
| Various tools and auxiliary code, including the JSON I/O handling, is in | ||||
| :py:mod:`.tools`. | ||||
| ''' | ||||
| """ | ||||
|   | ||||
| @@ -1,4 +1,4 @@ | ||||
| ''' | ||||
| """ | ||||
| Simulation of signal propagation in the DWDM network | ||||
|  | ||||
| Optical signals, as defined via :class:`.info.SpectralInformation`, enter | ||||
| @@ -6,4 +6,4 @@ Optical signals, as defined via :class:`.info.SpectralInformation`, enter | ||||
| through the :py:mod:`.network`. | ||||
| The simulation is controlled via :py:mod:`.parameters` and implemented mainly | ||||
| via :py:mod:`.science_utils`. | ||||
| ''' | ||||
| """ | ||||
|   | ||||
| @@ -1,12 +1,12 @@ | ||||
| #!/usr/bin/env python3 | ||||
| # -*- coding: utf-8 -*- | ||||
|  | ||||
| ''' | ||||
| """ | ||||
| gnpy.core.ansi_escapes | ||||
| ====================== | ||||
|  | ||||
| A random subset of ANSI terminal escape codes for colored messages | ||||
| ''' | ||||
| """ | ||||
|  | ||||
| red = '\x1b[1;31;40m' | ||||
| blue = '\x1b[1;34;40m' | ||||
|   | ||||
| @@ -26,7 +26,7 @@ from scipy.constants import h, c | ||||
| from scipy.interpolate import interp1d | ||||
| from collections import namedtuple | ||||
| 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 | ||||
| @@ -36,17 +36,20 @@ from gnpy.core.info import SpectralInformation, ReferenceCarrier | ||||
| from gnpy.core.exceptions import NetworkTopologyError, SpectrumError, ParametersError | ||||
|  | ||||
|  | ||||
| _logger = getLogger(__name__) | ||||
|  | ||||
|  | ||||
| class Location(namedtuple('Location', 'latitude longitude city region')): | ||||
|     def __new__(cls, latitude=0, longitude=0, city=None, region=None): | ||||
|         return super().__new__(cls, latitude, longitude, city, region) | ||||
|  | ||||
|  | ||||
| class _Node: | ||||
|     '''Convenience class for providing common functionality of all network elements | ||||
|     """Convenience class for providing common functionality of all network elements | ||||
|  | ||||
|     This class is just an internal implementation detail; do **not** assume that all network elements | ||||
|     inherit from :class:`_Node`. | ||||
|     ''' | ||||
|     """ | ||||
|     def __init__(self, uid, name=None, params=None, metadata=None, operational=None, type_variety=None): | ||||
|         if name is None: | ||||
|             name = uid | ||||
| @@ -87,12 +90,13 @@ class Transceiver(_Node): | ||||
|         self.chromatic_dispersion = None | ||||
|         self.pmd = None | ||||
|         self.pdl = None | ||||
|         self.latency = None | ||||
|         self.penalties = {} | ||||
|         self.total_penalty = 0 | ||||
|         self.propagated_labels = [""] | ||||
|  | ||||
|     def _calc_cd(self, spectral_info): | ||||
|         """ Updates the Transceiver property with the CD of the received channels. CD in ps/nm. | ||||
|         """Updates the Transceiver property with the CD of the received channels. CD in ps/nm. | ||||
|         """ | ||||
|         self.chromatic_dispersion = spectral_info.chromatic_dispersion * 1e3 | ||||
|  | ||||
| @@ -106,6 +110,11 @@ class Transceiver(_Node): | ||||
|         """ | ||||
|         self.pdl = spectral_info.pdl | ||||
|  | ||||
|     def _calc_latency(self, spectral_info): | ||||
|         """Updates the Transceiver property with the latency of the received channels. Latency in ms. | ||||
|         """ | ||||
|         self.latency = spectral_info.latency * 1e3 | ||||
|  | ||||
|     def _calc_penalty(self, impairment_value, boundary_list): | ||||
|         return interp(impairment_value, boundary_list['up_to_boundary'], boundary_list['penalty_value'], | ||||
|                       left=float('inf'), right=float('inf')) | ||||
| @@ -172,6 +181,7 @@ class Transceiver(_Node): | ||||
|                 f'chromatic_dispersion={self.chromatic_dispersion!r}, ' | ||||
|                 f'pmd={self.pmd!r}, ' | ||||
|                 f'pdl={self.pdl!r}, ' | ||||
|                 f'latency={self.latency!r}, ' | ||||
|                 f'penalties={self.penalties!r})') | ||||
|  | ||||
|     def __str__(self): | ||||
| @@ -185,6 +195,7 @@ class Transceiver(_Node): | ||||
|         cd = mean(self.chromatic_dispersion) | ||||
|         pmd = mean(self.pmd) | ||||
|         pdl = mean(self.pdl) | ||||
|         latency = mean(self.latency) | ||||
|  | ||||
|         result = '\n'.join([f'{type(self).__name__} {self.uid}', | ||||
|                             f'  GSNR (0.1nm, dB):          {pretty_summary_print(snr_01nm)}', | ||||
| @@ -193,7 +204,8 @@ class Transceiver(_Node): | ||||
|                             f'  OSNR ASE (signal bw, dB):  {pretty_summary_print(osnr_ase)}', | ||||
|                             f'  CD (ps/nm):                {cd:.2f}', | ||||
|                             f'  PMD (ps):                  {pmd:.2f}', | ||||
|                             f'  PDL (dB):                  {pdl:.2f}']) | ||||
|                             f'  PDL (dB):                  {pdl:.2f}', | ||||
|                             f'  Latency (ms):              {latency:.2f}']) | ||||
|  | ||||
|         cd_penalty = self.penalties.get('chromatic_dispersion') | ||||
|         if cd_penalty is not None: | ||||
| @@ -212,6 +224,7 @@ class Transceiver(_Node): | ||||
|         self._calc_cd(spectral_info) | ||||
|         self._calc_pmd(spectral_info) | ||||
|         self._calc_pdl(spectral_info) | ||||
|         self._calc_latency(spectral_info) | ||||
|         return spectral_info | ||||
|  | ||||
|  | ||||
| @@ -222,7 +235,8 @@ class Roadm(_Node): | ||||
|         try: | ||||
|             super().__init__(*args, params=RoadmParams(**params), **kwargs) | ||||
|         except ParametersError as e: | ||||
|             raise ParametersError(f'Config error in {kwargs["uid"]}: {e}') from e | ||||
|             msg = f'Config error in {kwargs["uid"]}: {e}' | ||||
|             raise ParametersError(msg) from e | ||||
|  | ||||
|         # Target output power for the reference carrier, can only be computed on the fly, because it depends | ||||
|         # on the path, since it depends on the equalization definition on the degree. | ||||
| @@ -336,6 +350,8 @@ class Roadm(_Node): | ||||
|             return self.per_degree_pch_out_dbm[degree] | ||||
|         elif degree in self.per_degree_pch_psd: | ||||
|             return psd2powerdbm(self.per_degree_pch_psd[degree], spectral_info.baud_rate) | ||||
|         elif degree in self.per_degree_pch_psw: | ||||
|             return psd2powerdbm(self.per_degree_pch_psw[degree], spectral_info.slot_width) | ||||
|         return self.get_roadm_target_power(spectral_info=spectral_info) | ||||
|  | ||||
|     def propagate(self, spectral_info, degree): | ||||
| @@ -449,21 +465,14 @@ class Fiber(_Node): | ||||
|     def __init__(self, *args, params=None, **kwargs): | ||||
|         if not params: | ||||
|             params = {} | ||||
|         try: | ||||
|             super().__init__(*args, params=FiberParams(**params), **kwargs) | ||||
|         except ParametersError as e: | ||||
|             msg = f'Config error in {kwargs["uid"]}: {e}' | ||||
|             raise ParametersError(msg) from e | ||||
|         self.pch_out_db = None | ||||
|         self.passive = True | ||||
|         self.propagated_labels = [""] | ||||
|         # Raman efficiency matrix function of the delta frequency constructed such that each row is related to a | ||||
|         # fixed frequency: positive elements represent a gain (from higher frequency) and negative elements represent | ||||
|         # a loss (to lower frequency) | ||||
|         if self.params.raman_efficiency: | ||||
|             frequency_offset = self.params.raman_efficiency['frequency_offset'] | ||||
|             frequency_offset = append(-flip(frequency_offset[1:]), frequency_offset) | ||||
|             cr = self.params.raman_efficiency['cr'] | ||||
|             cr = append(- flip(cr[1:]), cr) | ||||
|             self._cr_function = lambda frequency: interp(frequency, frequency_offset, cr) | ||||
|         else: | ||||
|             self._cr_function = lambda frequency: zeros(squeeze(frequency).shape) | ||||
|  | ||||
|         # Lumped losses | ||||
|         z_lumped_losses = array([lumped['position'] for lumped in self.params.lumped_losses])  # km | ||||
| @@ -513,28 +522,32 @@ class Fiber(_Node): | ||||
|                           f'  reference pch out (dBm):     {self.pch_out_db:.2f}', | ||||
|                           f'  actual pch out (dBm):        {total_pch}']) | ||||
|  | ||||
|     def interpolate_parameter_over_spectrum(self, parameter, ref_frequency, spectrum_frequency, name): | ||||
|         try: | ||||
|             interpolation = interp1d(ref_frequency, parameter)(spectrum_frequency) | ||||
|             return interpolation | ||||
|         except ValueError: | ||||
|             raise SpectrumError('The spectrum bandwidth exceeds the frequency interval used to define the fiber ' | ||||
|                                 f'{name} in "{type(self).__name__} {self.uid}".' | ||||
|                                 f'\nSpectrum f_min-f_max: {round(spectrum_frequency[0] * 1e-12, 2)}-' | ||||
|                                 f'{round(spectrum_frequency[-1] * 1e-12, 2)}' | ||||
|                                 f'\n{name} f_min-f_max: {round(ref_frequency[0] * 1e-12, 2)}-' | ||||
|                                 f'{round(ref_frequency[-1] * 1e-12, 2)}') | ||||
|  | ||||
|     def loss_coef_func(self, frequency): | ||||
|         frequency = asarray(frequency) | ||||
|         if self.params.loss_coef.size > 1: | ||||
|             try: | ||||
|                 loss_coef = interp1d(self.params.f_loss_ref, self.params.loss_coef)(frequency) | ||||
|             except ValueError: | ||||
|                 raise SpectrumError('The spectrum bandwidth exceeds the frequency interval used to define the fiber ' | ||||
|                                     f'loss coefficient in "{type(self).__name__} {self.uid}".' | ||||
|                                     f'\nSpectrum f_min-f_max: {round(frequency[0]*1e-12,2)}-' | ||||
|                                     f'{round(frequency[-1]*1e-12,2)}' | ||||
|                                     f'\nLoss coefficient f_min-f_max: {round(self.params.f_loss_ref[0]*1e-12,2)}-' | ||||
|                                     f'{round(self.params.f_loss_ref[-1]*1e-12,2)}') | ||||
|             loss_coef = self.interpolate_parameter_over_spectrum(self.params.loss_coef, self.params.f_loss_ref, | ||||
|                                                                  frequency, 'Loss Coefficient') | ||||
|         else: | ||||
|             loss_coef = full(frequency.size, self.params.loss_coef) | ||||
|         return squeeze(loss_coef) | ||||
|  | ||||
|  | ||||
|     @property | ||||
|     def loss(self): | ||||
|         """total loss including padding att_in: useful for polymorphism with roadm loss""" | ||||
|         return self.loss_coef_func(self.params.ref_frequency) * self.params.length + \ | ||||
|             self.params.con_in + self.params.con_out + self.params.att_in | ||||
|             self.params.con_in + self.params.con_out + self.params.att_in + sum(lin2db(1 / self.lumped_losses)) | ||||
|  | ||||
|     def alpha(self, frequency): | ||||
|         """Returns the linear exponent attenuation coefficient such that | ||||
| @@ -545,16 +558,71 @@ class Fiber(_Node): | ||||
|         """ | ||||
|         return self.loss_coef_func(frequency) / (10 * log10(exp(1))) | ||||
|  | ||||
|     def beta2(self, frequency=None): | ||||
|         """Returns the beta2 chromatic dispersion coefficient as the second order term of the beta function | ||||
|         expanded as a Taylor series evaluated at the given frequency | ||||
|  | ||||
|         :param frequency: the frequency at which alpha is computed [Hz] | ||||
|         :return: beta2: beta2 chromatic dispersion coefficient for f in frequency # 1/(m * Hz^2) | ||||
|         """ | ||||
|         frequency = asarray(self.params.ref_frequency if frequency is None else frequency) | ||||
|         if self.params.dispersion.size > 1: | ||||
|             dispersion = self.interpolate_parameter_over_spectrum(self.params.dispersion, self.params.f_dispersion_ref, | ||||
|                                                                   frequency, 'Chromatic Dispersion') | ||||
|         else: | ||||
|             if self.params.dispersion_slope is None: | ||||
|                 dispersion = (frequency / self.params.f_dispersion_ref) ** 2 * self.params.dispersion | ||||
|             else: | ||||
|                 wavelength = c / frequency | ||||
|                 dispersion = self.params.dispersion + self.params.dispersion_slope * \ | ||||
|                              (wavelength - c / self.params.f_dispersion_ref) | ||||
|         beta2 = -((c / frequency) ** 2 * dispersion) / (2 * pi * c) | ||||
|         return beta2 | ||||
|  | ||||
|     def beta3(self, frequency=None): | ||||
|         """Returns the beta3 chromatic dispersion coefficient as the third order term of the beta function | ||||
|         expanded as a Taylor series evaluated at the given frequency | ||||
|  | ||||
|         :param frequency: the frequency at which alpha is computed [Hz] | ||||
|         :return: beta3: beta3 chromatic dispersion coefficient for f in frequency # 1/(m * Hz^3) | ||||
|         """ | ||||
|         frequency = asarray(self.params.ref_frequency if frequency is None else frequency) | ||||
|         if self.params.dispersion.size > 1: | ||||
|             beta3 = polyfit(self.params.f_dispersion_ref - self.params.ref_frequency, | ||||
|                             self.beta2(self.params.f_dispersion_ref), 2)[1] / (2*pi) | ||||
|             beta3 = full(frequency.size, beta3) | ||||
|         else: | ||||
|             if self.params.dispersion_slope is None: | ||||
|                 beta3 = zeros(frequency.size) | ||||
|             else: | ||||
|                 dispersion_slope = self.params.dispersion_slope | ||||
|                 beta2 = self.beta2(frequency) | ||||
|                 beta3 = (dispersion_slope - (4 * pi * frequency ** 3 / c ** 2) * beta2) / ( | ||||
|                             2 * pi * frequency ** 2 / c) ** 2 | ||||
|         return beta3 | ||||
|  | ||||
|     def gamma(self, frequency=None): | ||||
|         """Returns the nonlinear interference coefficient such that | ||||
|         :math: `gamma(f) = 2 pi f n_2 c^{-1} A_{eff}^{-1}` | ||||
|  | ||||
|         :param frequency: the frequency at which gamma is computed [Hz] | ||||
|         :return: gamma: nonlinear interference coefficient for f in frequency [1/(W m)] | ||||
|         """ | ||||
|         frequency = self.params.ref_frequency if frequency is None else frequency | ||||
|         return self.params.gamma_scaling(frequency) | ||||
|  | ||||
|     def cr(self, frequency): | ||||
|         """Returns the raman efficiency matrix including the vibrational loss | ||||
|         """Returns the raman gain coefficient matrix including the vibrational loss | ||||
|  | ||||
|         :param frequency: the frequency at which cr is computed [Hz] | ||||
|         :return: cr: raman efficiency matrix [1 / (W m)] | ||||
|         :return: cr: raman gain coefficient matrix [1 / (W m)] | ||||
|         """ | ||||
|         df = outer(ones(frequency.shape), frequency) - outer(frequency, ones(frequency.shape)) | ||||
|         cr = self._cr_function(df) | ||||
|         effective_area_overlap = self.params.effective_area_overlap(frequency, frequency) | ||||
|         cr = interp(df, self.params.raman_coefficient.frequency_offset, | ||||
|                     self.params.raman_coefficient.normalized_gamma_raman) * frequency / effective_area_overlap | ||||
|         vibrational_loss = outer(frequency, ones(frequency.shape)) / outer(ones(frequency.shape), frequency) | ||||
|         return cr * (cr >= 0) + cr * (cr < 0) * vibrational_loss  # Raman efficiency [1/(W m)] | ||||
|         return cr * (cr >= 0) + cr * (cr < 0) * vibrational_loss  # [1/(W m)] | ||||
|  | ||||
|     def chromatic_dispersion(self, freq=None): | ||||
|         """Returns accumulated chromatic dispersion (CD). | ||||
| @@ -563,8 +631,8 @@ class Fiber(_Node): | ||||
|         :return: chromatic dispersion: the accumulated dispersion [s/m] | ||||
|         """ | ||||
|         freq = self.params.ref_frequency if freq is None else freq | ||||
|         beta2 = self.params.beta2 | ||||
|         beta3 = self.params.beta3 | ||||
|         beta2 = self.beta2(freq) | ||||
|         beta3 = self.beta3(freq) | ||||
|         ref_f = self.params.ref_frequency | ||||
|         length = self.params.length | ||||
|         beta = beta2 + 2 * pi * beta3 * (freq - ref_f) | ||||
| @@ -594,6 +662,9 @@ class Fiber(_Node): | ||||
|         spectral_info.chromatic_dispersion += self.chromatic_dispersion(spectral_info.frequency) | ||||
|         spectral_info.pmd = sqrt(spectral_info.pmd ** 2 + self.pmd ** 2) | ||||
|  | ||||
|         # latency | ||||
|         spectral_info.latency += self.params.latency | ||||
|  | ||||
|         # apply the attenuation due to the fiber losses | ||||
|         attenuation_fiber = stimulated_raman_scattering.loss_profile[:, -1] | ||||
|         spectral_info.apply_attenuation_lin(attenuation_fiber) | ||||
| @@ -667,6 +738,9 @@ class RamanFiber(Fiber): | ||||
|         spectral_info.chromatic_dispersion += self.chromatic_dispersion(spectral_info.frequency) | ||||
|         spectral_info.pmd = sqrt(spectral_info.pmd ** 2 + self.pmd ** 2) | ||||
|  | ||||
|         # latency | ||||
|         spectral_info.latency += self.params.latency | ||||
|  | ||||
|         # apply the attenuation due to the fiber losses | ||||
|         attenuation_fiber = stimulated_raman_scattering.loss_profile[:spectral_info.number_of_channels, -1] | ||||
|  | ||||
|   | ||||
| @@ -1,12 +1,12 @@ | ||||
| #!/usr/bin/env python3 | ||||
| # -*- coding: utf-8 -*- | ||||
|  | ||||
| ''' | ||||
| """ | ||||
| gnpy.core.equipment | ||||
| =================== | ||||
|  | ||||
| This module contains functionality for specifying equipment. | ||||
| ''' | ||||
| """ | ||||
|  | ||||
| from gnpy.core.utils import automatic_nch, db2lin | ||||
| from gnpy.core.exceptions import EquipmentConfigError | ||||
| @@ -29,8 +29,11 @@ def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=F | ||||
|             trx_params = {**mode_params} | ||||
|             # sanity check: spacing baudrate must be smaller than min spacing | ||||
|             if trx_params['baud_rate'] > trx_params['min_spacing']: | ||||
|                 raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transpoder "{trx_type_variety}" mode "{trx_params["format"]}" ' + | ||||
|                                            f'has baud rate {trx_params["baud_rate"]*1e-9} GHz greater than min_spacing {trx_params["min_spacing"]*1e-9}.') | ||||
|                 raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transponder "{trx_type_variety}"' | ||||
|                                            + f' mode "{trx_params["format"]}" has baud rate' | ||||
|                                            + f' {trx_params["baud_rate"] * 1e-9:.3f} GHz greater than min_spacing' | ||||
|                                            + f' {trx_params["min_spacing"] * 1e-9:.3f}.') | ||||
|             trx_params['equalization_offset_db'] = trx_params.get('equalization_offset_db', 0) | ||||
|         else: | ||||
|             mode_params = {"format": "undetermined", | ||||
|                            "baud_rate": None, | ||||
| @@ -40,7 +43,8 @@ def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=F | ||||
|                            "roll_off": None, | ||||
|                            "tx_osnr": None, | ||||
|                            "min_spacing": None, | ||||
|                            "cost": 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'] | ||||
| @@ -66,6 +70,7 @@ def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=F | ||||
|             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 | ||||
|  | ||||
|   | ||||
| @@ -27,9 +27,11 @@ class Power(namedtuple('Power', 'signal nli ase')): | ||||
|     """carriers power in W""" | ||||
|  | ||||
|  | ||||
| class Channel(namedtuple('Channel', | ||||
|                          'channel_number frequency baud_rate slot_width roll_off power chromatic_dispersion pmd pdl')): | ||||
|     """ Class containing the parameters of a WDM signal. | ||||
| class Channel( | ||||
|     namedtuple('Channel', | ||||
|                'channel_number frequency baud_rate slot_width roll_off power chromatic_dispersion pmd pdl latency')): | ||||
|     """Class containing the parameters of a WDM signal. | ||||
|  | ||||
|     :param channel_number: channel number in the WDM grid | ||||
|     :param frequency: central frequency of the signal (Hz) | ||||
|     :param baud_rate: the symbol rate of the signal (Baud) | ||||
| @@ -39,11 +41,13 @@ class Channel(namedtuple('Channel', | ||||
|     :param chromatic_dispersion: chromatic dispersion (s/m) | ||||
|     :param pmd: polarization mode dispersion (s) | ||||
|     :param pdl: polarization dependent loss (dB) | ||||
|     :param latency: propagation latency (s) | ||||
|     """ | ||||
|  | ||||
|  | ||||
| class Pref(namedtuple('Pref', 'p_span0, p_spani, ref_carrier')): | ||||
|     """noiseless reference power in dBm: | ||||
|  | ||||
|     p_span0: inital target carrier power for a reference channel defined by user | ||||
|     p_spani: carrier power after element i for a reference channel defined by user | ||||
|     ref_carrier records the baud rate of the reference channel | ||||
| @@ -51,12 +55,13 @@ class Pref(namedtuple('Pref', 'p_span0, p_spani, ref_carrier')): | ||||
|  | ||||
|  | ||||
| class SpectralInformation(object): | ||||
|     """ Class containing the parameters of the entire WDM comb. | ||||
|     """Class containing the parameters of the entire WDM comb. | ||||
|  | ||||
|     delta_pdb_per_channel: (per frequency) per channel delta power in dbm for the actual mix of channels""" | ||||
|  | ||||
|     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, delta_pdb_per_channel: array, | ||||
|                  tx_osnr: array, ref_power: Pref, label: array): | ||||
|                  roll_off: array, chromatic_dispersion: array, pmd: array, pdl: array, latency: array, | ||||
|                  delta_pdb_per_channel: array, tx_osnr: array, ref_power: Pref, label: array): | ||||
|         indices = argsort(frequency) | ||||
|         self._frequency = frequency[indices] | ||||
|         self._df = outer(ones(frequency.shape), frequency) - outer(frequency, ones(frequency.shape)) | ||||
| @@ -81,6 +86,7 @@ class SpectralInformation(object): | ||||
|         self._chromatic_dispersion = chromatic_dispersion[indices] | ||||
|         self._pmd = pmd[indices] | ||||
|         self._pdl = pdl[indices] | ||||
|         self._latency = latency[indices] | ||||
|         self._delta_pdb_per_channel = delta_pdb_per_channel[indices] | ||||
|         self._tx_osnr = tx_osnr[indices] | ||||
|         self._pref = ref_power | ||||
| @@ -177,6 +183,14 @@ class SpectralInformation(object): | ||||
|     def pdl(self, pdl): | ||||
|         self._pdl = pdl | ||||
|  | ||||
|     @property | ||||
|     def latency(self): | ||||
|         return self._latency | ||||
|  | ||||
|     @latency.setter | ||||
|     def latency(self, latency): | ||||
|         self._latency = latency | ||||
|  | ||||
|     @property | ||||
|     def delta_pdb_per_channel(self): | ||||
|         return self._delta_pdb_per_channel | ||||
| @@ -200,7 +214,7 @@ class SpectralInformation(object): | ||||
|     @property | ||||
|     def carriers(self): | ||||
|         entries = zip(self.channel_number, self.frequency, self.baud_rate, self.slot_width, | ||||
|                       self.roll_off, self.powers, self.chromatic_dispersion, self.pmd, self.pdl) | ||||
|                       self.roll_off, self.powers, self.chromatic_dispersion, self.pmd, self.pdl, self.latency) | ||||
|         return [Channel(*entry) for entry in entries] | ||||
|  | ||||
|     def apply_attenuation_lin(self, attenuation_lin): | ||||
| @@ -239,6 +253,7 @@ class SpectralInformation(object): | ||||
|                                                                    other.chromatic_dispersion), | ||||
|                                        pmd=append(self.pmd, other.pmd), | ||||
|                                        pdl=append(self.pdl, other.pdl), | ||||
|                                        latency=append(self.latency, other.latency), | ||||
|                                        delta_pdb_per_channel=append(self.delta_pdb_per_channel, | ||||
|                                                                     other.delta_pdb_per_channel), | ||||
|                                        tx_osnr=append(self.tx_osnr, other.tx_osnr), | ||||
| @@ -252,6 +267,7 @@ class SpectralInformation(object): | ||||
|         self.chromatic_dispersion = array([c.chromatic_dispersion for c in carriers]) | ||||
|         self.pmd = array([c.pmd for c in carriers]) | ||||
|         self.pdl = array([c.pdl for c in carriers]) | ||||
|         self.latency = array([c.latency for c in carriers]) | ||||
|         self.signal = array([c.power.signal for c in carriers]) | ||||
|         self.nli = array([c.power.nli for c in carriers]) | ||||
|         self.ase = array([c.power.ase for c in carriers]) | ||||
| @@ -269,6 +285,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl | ||||
|                                           chromatic_dispersion: Union[float, ndarray, Iterable] = 0., | ||||
|                                           pmd: Union[float, ndarray, Iterable] = 0., | ||||
|                                           pdl: Union[float, ndarray, Iterable] = 0., | ||||
|                                           latency: Union[float, ndarray, Iterable] = 0., | ||||
|                                           ref_power: Pref = None, | ||||
|                                           label: Union[str, ndarray, Iterable] = None): | ||||
|     """This is just a wrapper around the SpectralInformation.__init__() that simplifies the creation of | ||||
| @@ -284,6 +301,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl | ||||
|         chromatic_dispersion = full(number_of_channels, chromatic_dispersion) | ||||
|         pmd = full(number_of_channels, pmd) | ||||
|         pdl = full(number_of_channels, pdl) | ||||
|         latency = full(number_of_channels, latency) | ||||
|         nli = zeros(number_of_channels) | ||||
|         ase = zeros(number_of_channels) | ||||
|         delta_pdb_per_channel = full(number_of_channels, delta_pdb_per_channel) | ||||
| @@ -293,7 +311,7 @@ def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, fl | ||||
|                                    signal=signal, nli=nli, ase=ase, | ||||
|                                    baud_rate=baud_rate, roll_off=roll_off, | ||||
|                                    chromatic_dispersion=chromatic_dispersion, | ||||
|                                    pmd=pmd, pdl=pdl, | ||||
|                                    pmd=pmd, pdl=pdl, latency=latency, | ||||
|                                    delta_pdb_per_channel=delta_pdb_per_channel, | ||||
|                                    tx_osnr=tx_osnr, | ||||
|                                    ref_power=ref_power, label=label) | ||||
| @@ -304,14 +322,15 @@ 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, ref_carrier=None): | ||||
|     """ Creates a fixed slot width spectral information with flat power. | ||||
| def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, power, spacing, tx_osnr, delta_pdb=0, | ||||
|                                       ref_carrier=None): | ||||
|     """Creates a fixed slot width spectral information with flat power. | ||||
|     all arguments are scalar values""" | ||||
|     number_of_channels = automatic_nch(f_min, f_max, spacing) | ||||
|     frequency = [(f_min + spacing * i) for i in range(1, number_of_channels + 1)] | ||||
|     p_span0 = watt2dbm(power) | ||||
|     p_spani = watt2dbm(power) | ||||
|     delta_pdb_per_channel = zeros(number_of_channels) | ||||
|     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, | ||||
|                                                  roll_off=roll_off, delta_pdb_per_channel=delta_pdb_per_channel, | ||||
|   | ||||
| @@ -1,19 +1,25 @@ | ||||
| #!/usr/bin/env python3 | ||||
| # -*- coding: utf-8 -*- | ||||
|  | ||||
| ''' | ||||
| """ | ||||
| gnpy.core.network | ||||
| ================= | ||||
|  | ||||
| Working with networks which consist of network elements | ||||
| ''' | ||||
| """ | ||||
|  | ||||
| from operator import attrgetter | ||||
| from gnpy.core import ansi_escapes, elements | ||||
| from collections import namedtuple | ||||
| from logging import getLogger | ||||
|  | ||||
| from gnpy.core import elements | ||||
| from gnpy.core.exceptions import ConfigurationError, NetworkTopologyError | ||||
| from gnpy.core.utils import round2float, convert_length | ||||
| from gnpy.core.info import ReferenceCarrier | ||||
| from collections import namedtuple | ||||
| from gnpy.tools.json_io import Amp | ||||
|  | ||||
|  | ||||
| logger = getLogger(__name__) | ||||
|  | ||||
|  | ||||
| def edfa_nf(gain_target, variety_type, equipment): | ||||
| @@ -104,10 +110,9 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restri | ||||
|                     please increase span fiber padding') | ||||
|         else: | ||||
|             # TODO: convert to logging | ||||
|             print( | ||||
|                 f'{ansi_escapes.red}WARNING:{ansi_escapes.reset} target gain in node {uid} is below all available amplifiers min gain: \ | ||||
|                   amplifier input padding will be assumed, consider increase span fiber padding instead' | ||||
|             ) | ||||
|             logger.warning(f'\n\tWARNING: target gain in node {uid} is below all available amplifiers min gain: ' | ||||
|                            + '\n\tamplifier input padding will be assumed, consider increase span fiber padding ' | ||||
|                            + 'instead.\n') | ||||
|             acceptable_gain_min_list = edfa_list | ||||
|  | ||||
|     # filter on gain+power limitation: | ||||
| @@ -129,12 +134,9 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restri | ||||
|     # check what are the gain and power limitations of this amp | ||||
|     power_reduction = round(min(selected_edfa.power, 0), 2) | ||||
|     if power_reduction < -0.5: | ||||
|         print( | ||||
|             f'{ansi_escapes.red}WARNING:{ansi_escapes.reset} target gain and power in node {uid}\n \ | ||||
|     is beyond all available amplifiers capabilities and/or extended_gain_range:\n\ | ||||
|     a power reduction of {power_reduction} is applied\n' | ||||
|         ) | ||||
|  | ||||
|         logger.warning(f'\n\tWARNING: target gain and power in node {uid}\n' | ||||
|                        + '\tis beyond all available amplifiers capabilities and/or extended_gain_range:\n' | ||||
|                        + f'\ta power reduction of {power_reduction} is applied\n') | ||||
|     return selected_edfa.variety, power_reduction | ||||
|  | ||||
|  | ||||
| @@ -235,8 +237,7 @@ def set_amplifier_voa(amp, power_target, power_mode): | ||||
|  | ||||
|  | ||||
| def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_db): | ||||
|     """ this node can be a transceiver or a ROADM (same function called in both cases) | ||||
|     """ | ||||
|     """this node can be a transceiver or a ROADM (same function called in both cases)""" | ||||
|     power_mode = equipment['Span']['default'].power_mode | ||||
|     ref_carrier = ReferenceCarrier(baud_rate=equipment['SI']['default'].baud_rate, | ||||
|                                    slot_width=equipment['SI']['default'].spacing) | ||||
| @@ -283,7 +284,7 @@ def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_d | ||||
|                 if isinstance(prev_node, elements.Fiber): | ||||
|                     max_fiber_lineic_loss_for_raman = \ | ||||
|                         equipment['Span']['default'].max_fiber_lineic_loss_for_raman * 1e-3  # dB/m | ||||
|                     raman_allowed = prev_node.params.loss_coef < max_fiber_lineic_loss_for_raman | ||||
|                     raman_allowed = (prev_node.params.loss_coef < max_fiber_lineic_loss_for_raman).all() | ||||
|                 else: | ||||
|                     raman_allowed = False | ||||
|  | ||||
| @@ -306,21 +307,21 @@ def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_d | ||||
|                 else: | ||||
|                     if node.params.raman and not raman_allowed: | ||||
|                         if isinstance(prev_node, elements.Fiber): | ||||
|                             print(f'{ansi_escapes.red}WARNING{ansi_escapes.reset}: raman is used in node {node.uid}\n ' | ||||
|                                   'but fiber lineic loss is above threshold\n') | ||||
|                             logger.warning(f'\n\tWARNING: raman is used in node {node.uid}\n ' | ||||
|                                            + '\tbut fiber lineic loss is above threshold\n') | ||||
|                         else: | ||||
|                             print(f'{ansi_escapes.red}WARNING{ansi_escapes.reset}: raman is used in node {node.uid}\n ' | ||||
|                                   'but previous node is not a fiber\n') | ||||
|                             logger.critical(f'\n\tWARNING: raman is used in node {node.uid}\n ' | ||||
|                                             + '\tbut previous node is not a fiber\n') | ||||
|                     # if variety is imposed by user, and if the gain_target (computed or imposed) is also above | ||||
|                     # variety max gain + extended range, then warn that gain > max_gain + extended range | ||||
|                     if gain_target - equipment['Edfa'][node.params.type_variety].gain_flatmax - \ | ||||
|                             equipment['Span']['default'].target_extended_gain > 1e-2: | ||||
|                         # 1e-2 to allow a small margin according to round2float min step | ||||
|                         print(f'{ansi_escapes.red}WARNING{ansi_escapes.reset}: ' | ||||
|                               f'WARNING: effective gain in Node {node.uid} is above user ' | ||||
|                               f'specified amplifier {node.params.type_variety}\n' | ||||
|                               f'max flat gain: {equipment["Edfa"][node.params.type_variety].gain_flatmax}dB ; ' | ||||
|                               f'required gain: {gain_target}dB. Please check amplifier type.') | ||||
|                         logger.warning(f'\n\tWARNING: effective gain in Node {node.uid}\n' | ||||
|                                        + f'\tis above user specified amplifier {node.params.type_variety}\n' | ||||
|                                        + '\tmax flat gain: ' | ||||
|                                        + f'{equipment["Edfa"][node.params.type_variety].gain_flatmax}dB ; ' | ||||
|                                        + f'required gain: {gain_target}dB. Please check amplifier type.\n') | ||||
|  | ||||
|                 node.delta_p = dp if power_mode else None | ||||
|                 node.effective_gain = gain_target | ||||
| @@ -362,7 +363,7 @@ 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={}, | ||||
|             params=Amp.default_values, | ||||
|             metadata={ | ||||
|                 'location': { | ||||
|                     'latitude': roadm.lat, | ||||
| @@ -388,7 +389,7 @@ 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={}, | ||||
|             params=Amp.default_values, | ||||
|             metadata={ | ||||
|                 'location': { | ||||
|                     'latitude': roadm.lat, | ||||
| @@ -417,7 +418,7 @@ def add_inline_amplifier(network, fiber): | ||||
|         network.remove_edge(fiber, next_node) | ||||
|         amp = elements.Edfa( | ||||
|             uid=f'Edfa_{fiber.uid}', | ||||
|             params={}, | ||||
|             params=Amp.default_values, | ||||
|             metadata={ | ||||
|                 'location': { | ||||
|                     'latitude': (fiber.lat + next_node.lat) / 2, | ||||
|   | ||||
| @@ -7,9 +7,10 @@ gnpy.core.parameters | ||||
|  | ||||
| This module contains all parameters to configure standard network elements. | ||||
| """ | ||||
| from collections import namedtuple | ||||
|  | ||||
| from scipy.constants import c, pi | ||||
| from numpy import asarray, array | ||||
| from numpy import asarray, array, exp, sqrt, log, outer, ones, squeeze, append, flip, linspace, full | ||||
|  | ||||
| from gnpy.core.utils import convert_length | ||||
| from gnpy.core.exceptions import ParametersError | ||||
| @@ -35,7 +36,8 @@ class PumpParams(Parameters): | ||||
|  | ||||
| class RamanParams(Parameters): | ||||
|     def __init__(self, flag=False, result_spatial_resolution=10e3, solver_spatial_resolution=50): | ||||
|         """ Simulation parameters used within the Raman Solver | ||||
|         """Simulation parameters used within the Raman Solver | ||||
|  | ||||
|         :params flag: boolean for enabling/disable the evaluation of the Raman power profile in frequency and position | ||||
|         :params result_spatial_resolution: spatial resolution of the evaluated Raman power profile | ||||
|         :params solver_spatial_resolution: spatial step for the iterative solution of the first order ode | ||||
| @@ -48,7 +50,8 @@ class RamanParams(Parameters): | ||||
| class NLIParams(Parameters): | ||||
|     def __init__(self, method='gn_model_analytic', dispersion_tolerance=1, phase_shift_tolerance=0.1, | ||||
|                  computed_channels=None): | ||||
|         """ Simulation parameters used within the Nli Solver | ||||
|         """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 | ||||
| @@ -63,20 +66,11 @@ class NLIParams(Parameters): | ||||
| class SimParams(Parameters): | ||||
|     _shared_dict = {'nli_params': NLIParams(), 'raman_params': RamanParams()} | ||||
|  | ||||
|     def __init__(self): | ||||
|         if type(self) == SimParams: | ||||
|             raise NotImplementedError('Instances of SimParams cannot be generated') | ||||
|  | ||||
|     @classmethod | ||||
|     def set_params(cls, sim_params): | ||||
|         cls._shared_dict['nli_params'] = NLIParams(**sim_params.get('nli_params', {})) | ||||
|         cls._shared_dict['raman_params'] = RamanParams(**sim_params.get('raman_params', {})) | ||||
|  | ||||
|     @classmethod | ||||
|     def get(cls): | ||||
|         self = cls.__new__(cls) | ||||
|         return self | ||||
|  | ||||
|     @property | ||||
|     def nli_params(self): | ||||
|         return self._shared_dict['nli_params'] | ||||
| @@ -113,26 +107,50 @@ class FusedParams(Parameters): | ||||
|         self.loss = kwargs['loss'] if 'loss' in kwargs else 1 | ||||
|  | ||||
|  | ||||
| # SSMF Raman coefficient profile normalized with respect to the effective area (Cr * A_eff) | ||||
| CR_NORM = array([ | ||||
|     0., 7.802e-16, 2.4236e-15, 4.0504e-15, 5.6606e-15, 6.8973e-15, 7.802e-15, 8.4162e-15, 8.8727e-15, 9.2877e-15, | ||||
|     1.01011e-14, 1.05244e-14, 1.13295e-14, 1.2367e-14, 1.3695e-14, 1.5023e-14, 1.64091e-14, 1.81936e-14, 2.04927e-14, | ||||
|     2.28167e-14, 2.48917e-14, 2.66098e-14, 2.82615e-14, 2.98136e-14, 3.1042e-14, 3.17558e-14, 3.18803e-14, 3.17558e-14, | ||||
|     3.15566e-14, 3.11748e-14, 2.94567e-14, 3.14985e-14, 2.8552e-14, 2.43439e-14, 1.67992e-14, 9.6114e-15, 7.02180e-15, | ||||
|     5.9262e-15, 5.6938e-15, 7.055e-15, 7.4119e-15, 7.4783e-15, 6.7645e-15, 5.5361e-15, 3.6271e-15, 2.7224e-15, | ||||
|     2.4568e-15, 2.1995e-15, 2.1331e-15, 2.3323e-15, 2.5564e-15, 3.0461e-15, 4.8555e-15, 5.5029e-15, 5.2788e-15, | ||||
|     4.565e-15, 3.3698e-15, 2.2991e-15, 2.0086e-15, 1.5521e-15, 1.328e-15, 1.162e-15, 9.379e-16, 8.715e-16, 8.134e-16, | ||||
|     8.134e-16, 9.379e-16, 1.3612e-15, 1.6185e-15, 1.9754e-15, 1.8758e-15, 1.6849e-15, 1.2284e-15, 9.047e-16, 8.134e-16, | ||||
|     8.715e-16, 9.711e-16, 1.0375e-15, 1.0043e-15, 9.047e-16, 8.134e-16, 6.806e-16, 5.478e-16, 3.901e-16, 2.241e-16, | ||||
|     1.577e-16, 9.96e-17, 3.32e-17, 1.66e-17, 8.3e-18]) | ||||
| DEFAULT_RAMAN_COEFFICIENT = { | ||||
|     # SSMF Raman coefficient profile normalized with respect to the effective area overlap (g0 * A_eff(f_probe, f_pump)) | ||||
|     '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, | ||||
|          1.88408911e-04, 2.05914127e-04, 2.24074028e-04, 2.47508283e-04, 2.77729174e-04, 3.08044243e-04, 3.34764439e-04, | ||||
|          3.56481704e-04, 3.77127256e-04, 3.96269124e-04, 4.10955175e-04, 4.18718761e-04, 4.19511263e-04, 4.17025384e-04, | ||||
|          4.13565369e-04, 4.07726048e-04, 3.83671291e-04, 4.08564283e-04, 3.69571936e-04, 3.14442090e-04, 2.16074535e-04, | ||||
|          1.23097823e-04, 8.95457457e-05, 7.52470400e-05, 7.19806145e-05, 8.87961158e-05, 9.30812065e-05, 9.37058268e-05, | ||||
|          8.45719619e-05, 6.90585286e-05, 4.50407159e-05, 3.36521245e-05, 3.02292475e-05, 2.69376939e-05, 2.60020897e-05, | ||||
|          2.82958958e-05, 3.08667558e-05, 3.66024657e-05, 5.80610307e-05, 6.54797937e-05, 6.25022715e-05, 5.37806442e-05, | ||||
|          3.94996621e-05, 2.68120644e-05, 2.33038554e-05, 1.79140757e-05, 1.52472424e-05, 1.32707565e-05, 1.06541760e-05, | ||||
|          9.84649374e-06, 9.13999627e-06, 9.08971012e-06, 1.04227525e-05, 1.50419271e-05, 1.77838232e-05, 2.15810815e-05, | ||||
|          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] | ||||
|  | ||||
| # Note the non-uniform spacing of this range; this is required for properly capturing the Raman peak shape. | ||||
| FREQ_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., | ||||
|     # 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 | ||||
|         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)} | ||||
| } | ||||
|  | ||||
|  | ||||
| class RamanGainCoefficient(namedtuple('RamanGainCoefficient', 'normalized_gamma_raman frequency_offset')): | ||||
|     """ Raman Gain Coefficient Parameters | ||||
|  | ||||
|         Based on: | ||||
|             Andrea D’Amico, Bruno Correia, Elliot London, Emanuele Virgillito, Giacomo Borraccini, Antonio Napoli, | ||||
|             and Vittorio Curri, "Scalable and Disaggregated GGN Approximation Applied to a C+L+S Optical Network," | ||||
|             J. Lightwave Technol. 40, 3499-3511 (2022) | ||||
|             Section III.D | ||||
|     """ | ||||
|  | ||||
|  | ||||
| class FiberParams(Parameters): | ||||
| @@ -146,6 +164,8 @@ class FiberParams(Parameters): | ||||
|             # with default values from eqpt_config.json[Spans] | ||||
|             self._con_in = kwargs.get('con_in') | ||||
|             self._con_out = kwargs.get('con_out') | ||||
|  | ||||
|             # Reference frequency (unique for all parameters: beta2, beta3, gamma, effective_area) | ||||
|             if 'ref_wavelength' in kwargs: | ||||
|                 self._ref_wavelength = kwargs['ref_wavelength'] | ||||
|                 self._ref_frequency = c / self._ref_wavelength | ||||
| @@ -155,35 +175,70 @@ class FiberParams(Parameters): | ||||
|             else: | ||||
|                 self._ref_wavelength = 1550e-9  # conventional central C band wavelength [m] | ||||
|                 self._ref_frequency = c / self._ref_wavelength | ||||
|             self._dispersion = kwargs['dispersion']  # s/m/m | ||||
|             self._dispersion_slope = \ | ||||
|                 kwargs.get('dispersion_slope', -2 * self._dispersion / self.ref_wavelength)  # s/m/m/m | ||||
|             self._beta2 = -(self.ref_wavelength ** 2) * self.dispersion / (2 * pi * c)  # 1/(m * Hz^2) | ||||
|             # Eq. (3.23) in  Abramczyk, Halina. "Dispersion phenomena in optical fibers." Virtual European University | ||||
|             # on Lasers. Available online: http://mitr.p.lodz.pl/evu/lectures/Abramczyk3.pdf | ||||
|             # (accessed on 25 March 2018) (2005). | ||||
|             self._beta3 = ((self.dispersion_slope - (4*pi*c/self.ref_wavelength**3) * self.beta2) / | ||||
|                            (2*pi*c/self.ref_wavelength**2)**2) | ||||
|  | ||||
|             # Chromatic Dispersion | ||||
|             if 'dispersion_per_frequency' in kwargs: | ||||
|                 # Frequency-dependent dispersion | ||||
|                 self._dispersion = asarray(kwargs['dispersion']['value'])  # s/m/m | ||||
|                 self._f_dispersion_ref = asarray(kwargs['dispersion']['frequency'])  # Hz | ||||
|                 self._dispersion_slope = None | ||||
|             elif 'dispersion' in kwargs: | ||||
|                 # Single value dispersion | ||||
|                 self._dispersion = asarray(kwargs['dispersion'])  # s/m/m | ||||
|                 self._dispersion_slope = kwargs.get('dispersion_slope')  # s/m/m/m | ||||
|                 self._f_dispersion_ref = asarray(self._ref_frequency)  # Hz | ||||
|             else: | ||||
|                 # Default single value dispersion | ||||
|                 self._dispersion = asarray(1.67e-05)  # s/m/m | ||||
|                 self._dispersion_slope = None | ||||
|                 self._f_dispersion_ref = asarray(self.ref_frequency)  # Hz | ||||
|  | ||||
|             # Effective Area and Nonlinear Coefficient | ||||
|             self._effective_area = kwargs.get('effective_area')  # m^2 | ||||
|             n2 = 2.6e-20  # m^2/W | ||||
|             if self._effective_area: | ||||
|                 self._gamma = kwargs.get('gamma', 2 * pi * n2 / (self.ref_wavelength * self._effective_area))  # 1/W/m | ||||
|             self._n1 = 1.468 | ||||
|             self._core_radius = 4.2e-6  # m | ||||
|             self._n2 = 2.6e-20  # m^2/W | ||||
|             if self._effective_area is not None: | ||||
|                 default_gamma = 2 * pi * self._n2 / (self._ref_wavelength * self._effective_area) | ||||
|                 self._gamma = kwargs.get('gamma', default_gamma)  # 1/W/m | ||||
|             elif 'gamma' in kwargs: | ||||
|                 self._gamma = kwargs['gamma']  # 1/W/m | ||||
|                 self._effective_area = 2 * pi * n2 / (self.ref_wavelength * self._gamma)  # m^2 | ||||
|                 self._effective_area = 2 * pi * self._n2 / (self._ref_wavelength * self._gamma)  # m^2 | ||||
|             else: | ||||
|                 self._gamma = 0  # 1/W/m | ||||
|                 self._effective_area = 83e-12  # m^2 | ||||
|             default_raman_efficiency = {'cr': CR_NORM / self._effective_area, 'frequency_offset': FREQ_OFFSET} | ||||
|             self._raman_efficiency = kwargs.get('raman_efficiency', default_raman_efficiency) | ||||
|                 self._gamma = 2 * pi * self._n2 / (self._ref_wavelength * self._effective_area)  # 1/W/m | ||||
|             self._contrast = 0.5 * (c / (2 * pi * self._ref_frequency * self._core_radius * self._n1) * exp( | ||||
|                 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 gain coefficient array of the frequency offset constructed such that positive frequency values | ||||
|             # represent a positive power transfer from higher frequency and vice versa | ||||
|             frequency_offset = append(-flip(frequency_offset[1:]), frequency_offset) | ||||
|             normalized_gamma_raman = append(- flip(normalized_gamma_raman[1:]), normalized_gamma_raman) | ||||
|             self._raman_coefficient = RamanGainCoefficient(normalized_gamma_raman, frequency_offset) | ||||
|  | ||||
|             # Polarization Mode Dispersion | ||||
|             self._pmd_coef = kwargs['pmd_coef']  # s/sqrt(m) | ||||
|             if type(kwargs['loss_coef']) == dict: | ||||
|  | ||||
|             # Loss Coefficient | ||||
|             if isinstance(kwargs['loss_coef'], dict): | ||||
|                 self._loss_coef = asarray(kwargs['loss_coef']['value']) * 1e-3  # lineic loss dB/m | ||||
|                 self._f_loss_ref = asarray(kwargs['loss_coef']['frequency'])  # Hz | ||||
|             else: | ||||
|                 self._loss_coef = asarray(kwargs['loss_coef']) * 1e-3  # lineic loss dB/m | ||||
|                 self._f_loss_ref = asarray(self._ref_frequency)  # Hz | ||||
|             self._lumped_losses = kwargs['lumped_losses'] if 'lumped_losses' in kwargs else [] | ||||
|             # Lumped Losses | ||||
|             self._lumped_losses = kwargs['lumped_losses'] if 'lumped_losses' in kwargs else array([]) | ||||
|             self._latency = self._length / (c / self._n1)  # s | ||||
|         except KeyError as e: | ||||
|             raise ParametersError(f'Fiber configurations json must include {e}. Configuration: {kwargs}') | ||||
|  | ||||
| @@ -228,6 +283,10 @@ class FiberParams(Parameters): | ||||
|     def dispersion(self): | ||||
|         return self._dispersion | ||||
|  | ||||
|     @property | ||||
|     def f_dispersion_ref(self): | ||||
|         return self._f_dispersion_ref | ||||
|  | ||||
|     @property | ||||
|     def dispersion_slope(self): | ||||
|         return self._dispersion_slope | ||||
| @@ -236,6 +295,20 @@ class FiberParams(Parameters): | ||||
|     def gamma(self): | ||||
|         return self._gamma | ||||
|  | ||||
|     def effective_area_scaling(self, frequency): | ||||
|         V = 2 * pi * frequency / c * self._core_radius * self._n1 * sqrt(2 * self._contrast) | ||||
|         w = self._core_radius / sqrt(log(V)) | ||||
|         return asarray(pi * w ** 2) | ||||
|  | ||||
|     def effective_area_overlap(self, frequency_stokes_wave, frequency_pump): | ||||
|         effective_area_stokes_wave = self.effective_area_scaling(frequency_stokes_wave) | ||||
|         effective_area_pump = self.effective_area_scaling(frequency_pump) | ||||
|         return squeeze(outer(effective_area_stokes_wave, ones(effective_area_pump.size)) + outer( | ||||
|             ones(effective_area_stokes_wave.size), effective_area_pump)) / 2 | ||||
|  | ||||
|     def gamma_scaling(self, frequency): | ||||
|         return asarray(2 * pi * self._n2 * frequency / (c * self.effective_area_scaling(frequency))) | ||||
|  | ||||
|     @property | ||||
|     def pmd_coef(self): | ||||
|         return self._pmd_coef | ||||
| @@ -248,14 +321,6 @@ class FiberParams(Parameters): | ||||
|     def ref_frequency(self): | ||||
|         return self._ref_frequency | ||||
|  | ||||
|     @property | ||||
|     def beta2(self): | ||||
|         return self._beta2 | ||||
|  | ||||
|     @property | ||||
|     def beta3(self): | ||||
|         return self._beta3 | ||||
|  | ||||
|     @property | ||||
|     def loss_coef(self): | ||||
|         return self._loss_coef | ||||
| @@ -265,36 +330,125 @@ class FiberParams(Parameters): | ||||
|         return self._f_loss_ref | ||||
|  | ||||
|     @property | ||||
|     def raman_efficiency(self): | ||||
|         return self._raman_efficiency | ||||
|     def raman_coefficient(self): | ||||
|         return self._raman_coefficient | ||||
|  | ||||
|     @property | ||||
|     def latency(self): | ||||
|         return self._latency | ||||
|  | ||||
|     def asdict(self): | ||||
|         dictionary = super().asdict() | ||||
|         dictionary['loss_coef'] = self.loss_coef * 1e3 | ||||
|         dictionary['length_units'] = 'm' | ||||
|         if not self.lumped_losses: | ||||
|         if len(self.lumped_losses) == 0: | ||||
|             dictionary.pop('lumped_losses') | ||||
|         if not self.raman_efficiency: | ||||
|             dictionary.pop('raman_efficiency') | ||||
|         if not self.raman_coefficient: | ||||
|             dictionary.pop('raman_coefficient') | ||||
|         else: | ||||
|             raman_frequency_offset = \ | ||||
|                 self.raman_coefficient.frequency_offset[self.raman_coefficient.frequency_offset >= 0] | ||||
|             dictionary['raman_coefficient'] = {'g0': self._g0.tolist(), | ||||
|                                                'frequency_offset': raman_frequency_offset.tolist(), | ||||
|                                                'reference_frequency': self._raman_reference_frequency} | ||||
|         return dictionary | ||||
|  | ||||
|  | ||||
| class EdfaParams: | ||||
|     def __init__(self, **params): | ||||
|         self.update_params(params) | ||||
|         if params == {}: | ||||
|             self.type_variety = '' | ||||
|             self.type_def = '' | ||||
|             # self.gain_flatmax = 0 | ||||
|             # self.gain_min = 0 | ||||
|             # self.p_max = 0 | ||||
|             # self.nf_model = None | ||||
|             # self.nf_fit_coeff = None | ||||
|             # self.nf_ripple = None | ||||
|             # self.dgt = None | ||||
|             # self.gain_ripple = None | ||||
|             # self.out_voa_auto = False | ||||
|             # self.allowed_for_design = None | ||||
|         try: | ||||
|             self.type_variety = params['type_variety'] | ||||
|             self.type_def = params['type_def'] | ||||
|  | ||||
|             # Bandwidth | ||||
|             self.f_min = params['f_min'] | ||||
|             self.f_max = params['f_max'] | ||||
|             self.bandwidth = self.f_max - self.f_min | ||||
|             self.f_cent = (self.f_max + self.f_min) / 2 | ||||
|             self.f_ripple_ref = params['f_ripple_ref'] | ||||
|  | ||||
|             # Gain | ||||
|             self.gain_flatmax = params['gain_flatmax'] | ||||
|             self.gain_min = params['gain_min'] | ||||
|  | ||||
|             gain_ripple = params['gain_ripple'] | ||||
|             if gain_ripple == 0: | ||||
|                 self.gain_ripple = asarray([0, 0]) | ||||
|                 self.f_ripple_ref = asarray([self.f_min, self.f_max]) | ||||
|             else: | ||||
|                 self.gain_ripple = asarray(gain_ripple) | ||||
|                 if self.f_ripple_ref is not None: | ||||
|                     if (self.f_ripple_ref[0] != self.f_min) or (self.f_ripple_ref[-1] != self.f_max): | ||||
|                         raise ParametersError("The reference ripple frequency maximum and minimum have to coincide " | ||||
|                                               "with the EDFA frequency maximum and minimum.") | ||||
|                     elif self.gain_ripple.size != self.f_ripple_ref.size: | ||||
|                         raise ParametersError("The reference ripple frequency and the gain ripple must have the same " | ||||
|                                               "size.") | ||||
|                 else: | ||||
|                     self.f_ripple_ref = linspace(self.f_min, self.f_max, self.gain_ripple.size) | ||||
|  | ||||
|             tilt_ripple = params['tilt_ripple'] | ||||
|  | ||||
|             if tilt_ripple == 0: | ||||
|                 self.tilt_ripple = full(self.gain_ripple.size, 0) | ||||
|             else: | ||||
|                 self.tilt_ripple = asarray(tilt_ripple) | ||||
|                 if self.tilt_ripple.size != self.gain_ripple.size: | ||||
|                     raise ParametersError("The tilt ripple and the gain ripple must have the same size.") | ||||
|  | ||||
|             # Power | ||||
|             self.p_max = params['p_max'] | ||||
|  | ||||
|             # Noise Figure | ||||
|             self.nf_model = params['nf_model'] | ||||
|             self.nf_min = params['nf_min'] | ||||
|             self.nf_max = params['nf_max'] | ||||
|             self.nf_coef = params['nf_coef'] | ||||
|             self.nf0 = params['nf0'] | ||||
|             self.nf_fit_coeff = params['nf_fit_coeff'] | ||||
|  | ||||
|             nf_ripple = params['nf_ripple'] | ||||
|             if nf_ripple == 0: | ||||
|                 self.nf_ripple = full(self.gain_ripple.size, 0) | ||||
|             else: | ||||
|                 self.nf_ripple = asarray(nf_ripple) | ||||
|                 if self.nf_ripple.size != self.gain_ripple.size: | ||||
|                     raise ParametersError("The noise figure ripple and the gain ripple must have the same size.") | ||||
|  | ||||
|             # VOA | ||||
|             self.out_voa_auto = params['out_voa_auto'] | ||||
|  | ||||
|             # Dual Stage | ||||
|             self.dual_stage_model = params['dual_stage_model'] | ||||
|             if self.dual_stage_model is not None: | ||||
|                 # Preamp | ||||
|                 self.preamp_variety = params['preamp_variety'] | ||||
|                 self.preamp_type_def = params['preamp_type_def'] | ||||
|                 self.preamp_nf_model = params['preamp_nf_model'] | ||||
|                 self.preamp_nf_fit_coeff = params['preamp_nf_fit_coeff'] | ||||
|                 self.preamp_gain_min = params['preamp_gain_min'] | ||||
|                 self.preamp_gain_flatmax = params['preamp_gain_flatmax'] | ||||
|  | ||||
|                 # Booster | ||||
|                 self.booster_variety = params['booster_variety'] | ||||
|                 self.booster_type_def = params['booster_type_def'] | ||||
|                 self.booster_nf_model = params['booster_nf_model'] | ||||
|                 self.booster_nf_fit_coeff = params['booster_nf_fit_coeff'] | ||||
|                 self.booster_gain_min = params['booster_gain_min'] | ||||
|                 self.booster_gain_flatmax = params['booster_gain_flatmax'] | ||||
|  | ||||
|             # Others | ||||
|             self.pmd = params['pmd'] | ||||
|             self.pdl = params['pdl'] | ||||
|             self.raman = params['raman'] | ||||
|             self.dgt = params['dgt'] | ||||
|             self.advance_configurations_from_json = params['advance_configurations_from_json'] | ||||
|  | ||||
|             # Design | ||||
|             self.allowed_for_design = params['allowed_for_design'] | ||||
|  | ||||
|         except KeyError as e: | ||||
|             raise ParametersError(f'Edfa configurations json must include {e}. Configuration: {params}') | ||||
|  | ||||
|     def update_params(self, kwargs): | ||||
|         for k, v in kwargs.items(): | ||||
|   | ||||
| @@ -10,9 +10,9 @@ Solver definitions to calculate the Raman effect and the nonlinear interference | ||||
| The solvers take as input instances of the spectral information, the fiber and the simulation parameters | ||||
| """ | ||||
|  | ||||
| from numpy import interp, pi, zeros, shape, where, cos, array, append, ones, exp, arange, sqrt, trapz, arcsinh, \ | ||||
|     clip, abs, sum, concatenate, flip, outer, inner, transpose, max, format_float_scientific, diag, prod, argwhere, \ | ||||
|     unique, argsort, cumprod | ||||
| from numpy import interp, pi, zeros, cos, array, append, ones, exp, arange, sqrt, trapz, arcsinh, clip, abs, sum, \ | ||||
|     concatenate, flip, outer, inner, transpose, max, format_float_scientific, diag, sort, unique, argsort, cumprod, \ | ||||
|     polyfit | ||||
| from logging import getLogger | ||||
| from scipy.constants import k, h | ||||
| from scipy.interpolate import interp1d | ||||
| @@ -24,31 +24,30 @@ from gnpy.core.parameters import SimParams | ||||
| from gnpy.core.info import SpectralInformation | ||||
|  | ||||
| logger = getLogger(__name__) | ||||
| sim_params = SimParams.get() | ||||
| sim_params = SimParams() | ||||
|  | ||||
| def raised_cosine_comb(f, *carriers): | ||||
|     """ Returns an array storing the PSD of a WDM comb of raised cosine shaped | ||||
|     channels at the input frequencies defined in array f | ||||
|  | ||||
|     :param f: numpy array of frequencies in Hz | ||||
|     :param carriers: namedtuple describing the WDM comb | ||||
|     :return: PSD of the WDM comb evaluated over f | ||||
| def raised_cosine(frequency, channel_frequency, channel_baud_rate, channel_roll_off): | ||||
|     """Returns a unitary raised cosine profile for the given parame | ||||
|  | ||||
|     :param frequency: numpy array of frequencies in Hz for the resulting raised cosine | ||||
|     :param channel_frequency: channel frequencies in Hz | ||||
|     :param channel_baud_rate: channel baud rate in Hz | ||||
|     :param channel_roll_off: channel roll off | ||||
|     """ | ||||
|     psd = zeros(shape(f)) | ||||
|     for carrier in carriers: | ||||
|         f_nch = carrier.frequency | ||||
|         g_ch = carrier.power.signal / carrier.baud_rate | ||||
|         ts = 1 / carrier.baud_rate | ||||
|         pass_band = (1 - carrier.roll_off) / (2 / carrier.baud_rate) | ||||
|         stop_band = (1 + carrier.roll_off) / (2 / carrier.baud_rate) | ||||
|         ff = abs(f - f_nch) | ||||
|         tf = ff - pass_band | ||||
|         if carrier.roll_off == 0: | ||||
|             psd = where(tf <= 0, g_ch, 0.) + psd | ||||
|         else: | ||||
|             psd = g_ch * (where(tf <= 0, 1., 0.) + 1 / 2 * (1 + cos(pi * ts / carrier.roll_off * tf)) * | ||||
|                           where(tf > 0, 1., 0.) * where(abs(ff) <= stop_band, 1., 0.)) + psd | ||||
|     return psd | ||||
|     raised_cosine_mask = zeros(frequency.size) | ||||
|     base_frequency = frequency - channel_frequency | ||||
|     ts = 1 / channel_baud_rate | ||||
|     pass_band = (1 - channel_roll_off) * channel_baud_rate / 2 | ||||
|     stop_band = (1 + channel_roll_off) * channel_baud_rate / 2 | ||||
|  | ||||
|     flat_condition = (abs(base_frequency) <= pass_band) == 1 | ||||
|     cosine_condition = (pass_band < abs(base_frequency)) * (abs(base_frequency) < stop_band) == 1 | ||||
|  | ||||
|     raised_cosine_mask[flat_condition] = 1 | ||||
|     raised_cosine_mask[cosine_condition] = \ | ||||
|         0.5 * (1 + cos(pi * ts / channel_roll_off * (abs(base_frequency[cosine_condition]) - pass_band))) | ||||
|     return raised_cosine_mask | ||||
|  | ||||
|  | ||||
| class StimulatedRamanScattering: | ||||
| @@ -110,6 +109,7 @@ class RamanSolver: | ||||
|             z_step = sim_params.raman_params.solver_spatial_resolution | ||||
|             z = append(arange(0, fiber.params.length, z_step), fiber.params.length) | ||||
|             z_final = append(arange(0, fiber.params.length, z_resolution), fiber.params.length) | ||||
|             z_final = sort(unique(concatenate((fiber.z_lumped_losses, z_final)))) | ||||
|  | ||||
|             # Lumped losses array definition | ||||
|             z, lumped_losses = RamanSolver._create_lumped_losses(z, fiber.lumped_losses, fiber.z_lumped_losses) | ||||
| @@ -190,13 +190,13 @@ class RamanSolver: | ||||
|  | ||||
|         # calculate ase power | ||||
|         ase = zeros(spectral_info.number_of_channels) | ||||
|         cr = fiber.cr(srs.frequency)[:spectral_info.number_of_channels, spectral_info.number_of_channels:] | ||||
|         for i, pump in enumerate(fiber.raman_pumps): | ||||
|             pump_power = srs.power_profile[spectral_info.number_of_channels + i, :] | ||||
|             df = pump.frequency - frequency | ||||
|             eta = - 1 / (1 - exp(h * df / (k * fiber.temperature))) | ||||
|             cr = fiber._cr_function(df) | ||||
|             integral = trapz(pump_power / channels_loss, z, axis=1) | ||||
|             ase += 2 * h * baud_rate * frequency * (1 + eta) * cr * (df > 0) * integral  # 2 factor for double pol | ||||
|             ase += 2 * h * baud_rate * frequency * (1 + eta) * cr[:, i] * (df > 0) * integral  # 2 factor for double pol | ||||
|         return ase | ||||
|  | ||||
|     @staticmethod | ||||
| @@ -271,13 +271,16 @@ class RamanSolver: | ||||
|  | ||||
|  | ||||
| class NliSolver: | ||||
|     """ This class implements the NLI models. | ||||
|     """This class implements the NLI models. | ||||
|     Model and method can be specified in `sim_params.nli_params.method`. | ||||
|     List of implemented methods: | ||||
|     'gn_model_analytic': eq. 120 from arXiv:1209.0394 | ||||
|         'ggn_spectrally_separated': eq. 21 from arXiv: 1710.02225 spectrally separated | ||||
|     'ggn_spectrally_separated': eq. 21 from arXiv: 1710.02225 | ||||
|     """ | ||||
|  | ||||
|     SPM_WEIGHT = (16.0 / 27.0) | ||||
|     XPM_WEIGHT = 2 * (16.0 / 27.0) | ||||
|  | ||||
|     @staticmethod | ||||
|     def effective_length(alpha, length): | ||||
|         """The effective length identify the region in which the NLI has a significant contribution to | ||||
| @@ -287,58 +290,81 @@ class NliSolver: | ||||
|  | ||||
|     @staticmethod | ||||
|     def compute_nli(spectral_info: SpectralInformation, srs: StimulatedRamanScattering, fiber): | ||||
|         """ Compute NLI power generated by the WDM comb `*carriers` on the channel under test `carrier` | ||||
|         """Compute NLI power generated by the WDM comb `*carriers` on the channel under test `carrier` | ||||
|         at the end of the fiber span. | ||||
|         """ | ||||
|         logger.debug('Start computing fiber NLI noise') | ||||
|         # Physical fiber parameters | ||||
|         alpha = fiber.alpha(spectral_info.frequency) | ||||
|         beta2 = fiber.params.beta2 | ||||
|         beta3 = fiber.params.beta3 | ||||
|         f_ref_beta = fiber.params.ref_frequency | ||||
|         gamma = fiber.params.gamma | ||||
|         length = fiber.params.length | ||||
|  | ||||
|         if 'gn_model_analytic' == sim_params.nli_params.method: | ||||
|             nli = NliSolver._gn_analytic(spectral_info, alpha, beta2, gamma, length) | ||||
|             eta = NliSolver._gn_analytic(spectral_info, fiber) | ||||
|  | ||||
|             cut_power = outer(spectral_info.signal, ones(spectral_info.number_of_channels)) | ||||
|             pump_power = outer(ones(spectral_info.number_of_channels), spectral_info.signal) | ||||
|             nli_matrix = cut_power * pump_power ** 2 * eta | ||||
|             nli = sum(nli_matrix, 1) | ||||
|         elif 'ggn_spectrally_separated' in sim_params.nli_params.method: | ||||
|             nli = NliSolver._ggn_spectrally_separated(spectral_info, srs, alpha, beta2, beta3, f_ref_beta, gamma) | ||||
|             if sim_params.nli_params.computed_channels is not None: | ||||
|                 cut_indices = array(sim_params.nli_params.computed_channels) - 1 | ||||
|             else: | ||||
|                 cut_indices = array(spectral_info.channel_number) - 1 | ||||
|  | ||||
|             eta = NliSolver._ggn_spectrally_separated(cut_indices, spectral_info, fiber, srs) | ||||
|  | ||||
|             # Interpolation over the channels not indicated as compted channels in simulation parameters | ||||
|             cut_power = outer(spectral_info.signal[cut_indices], ones(spectral_info.number_of_channels)) | ||||
|             cut_frequency = spectral_info.frequency[cut_indices] | ||||
|             pump_power = outer(ones(cut_indices.size), spectral_info.signal) | ||||
|             cut_baud_rate = outer(spectral_info.baud_rate[cut_indices], ones(spectral_info.number_of_channels)) | ||||
|  | ||||
|             g_nli = eta * cut_power * pump_power**2 / cut_baud_rate | ||||
|             g_nli = sum(g_nli, 1) | ||||
|             g_nli = interp(spectral_info.frequency, cut_frequency, g_nli) | ||||
|             nli = spectral_info.baud_rate * g_nli  # Local white noise | ||||
|         else: | ||||
|             raise ValueError(f'Method {sim_params.nli_params.method} not implemented.') | ||||
|  | ||||
|         return nli | ||||
|  | ||||
|     # Methods for computing GN-model | ||||
|     # Methods for computing GN-model eta matrix | ||||
|     @staticmethod | ||||
|     def _gn_analytic(spectral_info: SpectralInformation, alpha, beta2, gamma, length): | ||||
|         """ Computes the nonlinear interference power evaluated at the fiber input. | ||||
|     def _gn_analytic(spectral_info, fiber, spm_weight=SPM_WEIGHT, xpm_weight=XPM_WEIGHT): | ||||
|         """Computes the nonlinear interference power evaluated at the fiber input. | ||||
|         The method uses eq. 120 from arXiv:1209.0394 | ||||
|         """ | ||||
|         spm_weight = (16.0 / 27.0) * gamma ** 2 | ||||
|         xpm_weight = 2 * (16.0 / 27.0) * gamma ** 2 | ||||
|  | ||||
|         # Spectral Features | ||||
|         nch = spectral_info.number_of_channels | ||||
|         frequency = spectral_info.frequency | ||||
|         baud_rate = spectral_info.baud_rate | ||||
|         delta_frequency = spectral_info.df | ||||
|  | ||||
|         # Physical fiber parameters | ||||
|         alpha = fiber.alpha(frequency) | ||||
|         beta2 = fiber.beta2(frequency) | ||||
|         gamma = outer(fiber.gamma(frequency), ones(nch)) | ||||
|         length = fiber.params.length | ||||
|  | ||||
|         identity = diag(ones(nch)) | ||||
|         weight = spm_weight * identity + xpm_weight * (ones([nch, nch]) - identity) | ||||
|  | ||||
|         effective_length = NliSolver.effective_length(alpha, length) | ||||
|         asymptotic_length = 1 / alpha | ||||
|  | ||||
|         df = spectral_info.df | ||||
|         baud_rate = spectral_info.baud_rate | ||||
|         cut_baud_rate = outer(baud_rate, ones(nch)) | ||||
|         pump_baud_rate = outer(ones(nch), baud_rate) | ||||
|  | ||||
|         psd = spectral_info.signal / baud_rate | ||||
|         ggg = outer(psd, psd**2) | ||||
|  | ||||
|         psi = NliSolver._psi(df, baud_rate, beta2, effective_length, asymptotic_length) | ||||
|         g_nli = sum(weight * ggg * psi, 1) | ||||
|         nli = spectral_info.baud_rate * g_nli  # Local white noise | ||||
|         return nli | ||||
|         psi = NliSolver._psi(delta_frequency, baud_rate, beta2, effective_length, asymptotic_length) | ||||
|         eta_cut_central_frequency = gamma ** 2 * weight * psi / (cut_baud_rate * pump_baud_rate ** 2) | ||||
|         eta = cut_baud_rate * eta_cut_central_frequency  # Local white noise | ||||
|         return eta | ||||
|  | ||||
|     @staticmethod | ||||
|     def _psi(df, baud_rate, beta2, effective_length, asymptotic_length): | ||||
|         """Calculates eq. 123 from `arXiv:1209.0394 <https://arxiv.org/abs/1209.0394>`__""" | ||||
|         cut_baud_rate = outer(baud_rate, ones(baud_rate.size)) | ||||
|         cut_beta = outer(beta2, ones(baud_rate.size)) | ||||
|         pump_baud_rate = baud_rate | ||||
|         pump_beta = outer(ones(baud_rate.size), beta2) | ||||
|         beta2 = (cut_beta + pump_beta) / 2 | ||||
|         right_extreme = df + pump_baud_rate / 2 | ||||
|         left_extreme = df - pump_baud_rate / 2 | ||||
|         psi = (arcsinh(pi ** 2 * asymptotic_length * abs(beta2) * cut_baud_rate * right_extreme) - | ||||
| @@ -346,112 +372,133 @@ class NliSolver: | ||||
|         psi *= effective_length ** 2 / (2 * pi * abs(beta2) * asymptotic_length) | ||||
|         return psi | ||||
|  | ||||
|     # Methods for computing the GGN-model | ||||
|     # Methods for computing the GGN-model eta matrix | ||||
|     @staticmethod | ||||
|     def _ggn_spectrally_separated(spectral_info: SpectralInformation, srs: StimulatedRamanScattering, | ||||
|                                   alpha, beta2, beta3, f_ref_beta, gamma): | ||||
|         """ Computes the nonlinear interference power evaluated at the fiber input. | ||||
|     def _ggn_spectrally_separated(cut_indices, spectral_info, fiber, srs, spm_weight=SPM_WEIGHT, xpm_weight=XPM_WEIGHT): | ||||
|         """Computes the nonlinear interference power evaluated at the fiber input. | ||||
|         The method uses eq. 21 from arXiv: 1710.02225 | ||||
|         """ | ||||
|         # Spectral Features | ||||
|         nch = spectral_info.number_of_channels | ||||
|         frequency = spectral_info.frequency | ||||
|         baud_rate = spectral_info.baud_rate | ||||
|         slot_width = spectral_info.slot_width | ||||
|         roll_off = spectral_info.roll_off | ||||
|  | ||||
|         # Physical fiber parameters | ||||
|         alpha = fiber.alpha(frequency) | ||||
|         beta2 = fiber.beta2(frequency) | ||||
|         gamma = outer(fiber.gamma(frequency[cut_indices]), ones(nch)) | ||||
|  | ||||
|         identity = diag(ones(nch)) | ||||
|         weight = spm_weight * identity + xpm_weight * (ones([nch, nch]) - identity) | ||||
|         weight = weight[cut_indices, :] | ||||
|  | ||||
|         dispersion_tolerance = sim_params.nli_params.dispersion_tolerance | ||||
|         phase_shift_tolerance = sim_params.nli_params.phase_shift_tolerance | ||||
|         slot_width = max(spectral_info.slot_width) | ||||
|         max_slot_width = max(slot_width) | ||||
|         delta_z = sim_params.raman_params.result_spatial_resolution | ||||
|         spm_weight = (16.0 / 27.0) * gamma ** 2 | ||||
|         xpm_weight = 2 * (16.0 / 27.0) * gamma ** 2 | ||||
|         cuts = [carrier for carrier in spectral_info.carriers if carrier.channel_number | ||||
|                 in sim_params.nli_params.computed_channels] if sim_params.nli_params.computed_channels \ | ||||
|             else spectral_info.carriers | ||||
|  | ||||
|         g_nli = array([]) | ||||
|         f_nli = array([]) | ||||
|         for cut_carrier in cuts: | ||||
|             logger.debug(f'Start computing fiber NLI noise of cut: {cut_carrier}') | ||||
|             f_eval = cut_carrier.frequency | ||||
|             g_nli_computed = 0 | ||||
|             g_cut = (cut_carrier.power.signal / cut_carrier.baud_rate) | ||||
|             for j, pump_carrier in enumerate(spectral_info.carriers): | ||||
|                 dn = abs(pump_carrier.channel_number - cut_carrier.channel_number) | ||||
|                 delta_f = abs(cut_carrier.frequency - pump_carrier.frequency) | ||||
|                 k_tol = dispersion_tolerance * abs(alpha[j]) | ||||
|         psi_cut_central_frequency = zeros([cut_indices.size, nch]) | ||||
|         for i, cut_index in enumerate(cut_indices): | ||||
|             logger.debug(f'Start computing fiber NLI noise of cut: {cut_index + 1}') | ||||
|             cut_frequency = frequency[cut_index] | ||||
|             cut_baud_rate = baud_rate[cut_index] | ||||
|             cut_roll_off = roll_off[cut_index] | ||||
|             cut_number = cut_index + 1 | ||||
|             cut_beta2 = beta2[cut_index] | ||||
|             cut_base_frequency = frequency - cut_frequency | ||||
|             cut_beta_coefficients = polyfit(cut_base_frequency, beta2, 2) | ||||
|             cut_beta3 = cut_beta_coefficients[1] / (2 * pi) | ||||
|  | ||||
|             for pump_index in range(nch): | ||||
|                 pump_frequency = frequency[pump_index] | ||||
|                 pump_baud_rate = baud_rate[pump_index] | ||||
|                 pump_roll_off = roll_off[pump_index] | ||||
|                 pump_number = pump_index + 1 | ||||
|                 pump_alpha = alpha[pump_index] | ||||
|                 dn = abs(pump_number - cut_number) | ||||
|                 delta_f = abs(cut_frequency - pump_frequency) | ||||
|                 k_tol = dispersion_tolerance * abs(alpha[pump_index]) | ||||
|                 phi_tol = phase_shift_tolerance / delta_z | ||||
|                 f_cut_resolution = min(k_tol, phi_tol) / abs(beta2) / (4 * pi ** 2 * (1 + dn) * slot_width) | ||||
|                 f_pump_resolution = min(k_tol, phi_tol) / abs(beta2) / (4 * pi ** 2 * slot_width) | ||||
|                 if dn == 0:  # SPM | ||||
|                     ggg = g_cut ** 3 | ||||
|                     g_nli_computed += \ | ||||
|                         spm_weight * ggg * NliSolver._generalized_psi(f_eval, cut_carrier, pump_carrier, | ||||
|                                                                       f_cut_resolution, f_pump_resolution, | ||||
|                                                                       srs, alpha[j], beta2, beta3, f_ref_beta) | ||||
|                 f_cut_resolution = min(k_tol, phi_tol) / abs(cut_beta2) / (4 * pi ** 2 * (1 + dn) * max_slot_width) | ||||
|                 f_pump_resolution = min(k_tol, phi_tol) / abs(cut_beta2) / (4 * pi ** 2 * max_slot_width) | ||||
|                 if cut_index == pump_index:  # SPM | ||||
|                     psi_cut_central_frequency[i, pump_index] = \ | ||||
|                         NliSolver._generalized_psi(cut_frequency, cut_frequency, cut_baud_rate, cut_roll_off, | ||||
|                                                    pump_frequency, pump_baud_rate, pump_roll_off, f_cut_resolution, | ||||
|                                                    f_pump_resolution, srs, pump_alpha, cut_beta2, cut_beta3, | ||||
|                                                    cut_frequency) | ||||
|                 else:  # XPM | ||||
|                     g_pump = (pump_carrier.power.signal / pump_carrier.baud_rate) | ||||
|                     ggg = g_cut * g_pump ** 2 | ||||
|                     frequency_offset_threshold = NliSolver._frequency_offset_threshold(beta2, pump_carrier.baud_rate) | ||||
|                     frequency_offset_threshold = NliSolver._frequency_offset_threshold(cut_beta2, pump_baud_rate) | ||||
|                     if abs(delta_f) <= frequency_offset_threshold: | ||||
|                         g_nli_computed += \ | ||||
|                             xpm_weight * ggg * NliSolver._generalized_psi(f_eval, cut_carrier, pump_carrier, | ||||
|                                                                           f_cut_resolution, f_pump_resolution, | ||||
|                                                                           srs, alpha[j], beta2, beta3, f_ref_beta) | ||||
|                         psi_cut_central_frequency[i, pump_index] = \ | ||||
|                             NliSolver._generalized_psi(cut_frequency, cut_frequency, cut_baud_rate, cut_roll_off, | ||||
|                                                        pump_frequency, pump_baud_rate, pump_roll_off, f_cut_resolution, | ||||
|                                                        f_pump_resolution, srs, pump_alpha, cut_beta2, cut_beta3, | ||||
|                                                        cut_frequency) | ||||
|                     else: | ||||
|                         g_nli_computed += \ | ||||
|                             xpm_weight * ggg * NliSolver._fast_generalized_psi(f_eval, cut_carrier, pump_carrier, | ||||
|                                                                                f_cut_resolution, srs, alpha[j], beta2, | ||||
|                                                                                beta3, f_ref_beta) | ||||
|             f_nli = append(f_nli, cut_carrier.frequency) | ||||
|             g_nli = append(g_nli, g_nli_computed) | ||||
|         g_nli = interp(spectral_info.frequency, f_nli, g_nli) | ||||
|         nli = spectral_info.baud_rate * g_nli  # Local white noise | ||||
|         return nli | ||||
|                         psi_cut_central_frequency[i, pump_index] = \ | ||||
|                             NliSolver._fast_generalized_psi(cut_frequency, cut_frequency, cut_baud_rate, cut_roll_off, | ||||
|                                                             pump_frequency, pump_baud_rate, pump_roll_off, | ||||
|                                                             f_cut_resolution, srs, pump_alpha, cut_beta2, cut_beta3, | ||||
|                                                             cut_frequency) | ||||
|  | ||||
|         cut_baud_rate = outer(baud_rate[cut_indices], ones(nch)) | ||||
|         pump_baud_rate = outer(ones(cut_indices.size), baud_rate) | ||||
|  | ||||
|         eta_cut_central_frequency = \ | ||||
|             gamma ** 2 * weight * psi_cut_central_frequency / (cut_baud_rate * pump_baud_rate ** 2) | ||||
|         eta = cut_baud_rate * eta_cut_central_frequency  # Local white noise | ||||
|         return eta | ||||
|  | ||||
|     @staticmethod | ||||
|     def _fast_generalized_psi(f_eval, cut_carrier, pump_carrier, f_cut_resolution, srs, alpha, beta2, beta3, | ||||
|                               f_ref_beta): | ||||
|         """Computes the generalized psi function similarly to the one used in the GN model.""" | ||||
|         z = srs.z | ||||
|         rho_norm = srs.rho * exp(outer(alpha/2, z)) | ||||
|         rho_pump = interp1d(srs.frequency, rho_norm, axis=0)(pump_carrier.frequency) | ||||
|  | ||||
|         f1_array = array([pump_carrier.frequency - (pump_carrier.baud_rate * (1 + pump_carrier.roll_off) / 2), | ||||
|                           pump_carrier.frequency + (pump_carrier.baud_rate * (1 + pump_carrier.roll_off) / 2)]) | ||||
|         f2_array = arange(cut_carrier.frequency, | ||||
|                           cut_carrier.frequency + (cut_carrier.baud_rate * (1 + cut_carrier.roll_off) / 2), | ||||
|                           f_cut_resolution)  # Only positive f2 is used since integrand_f2 is symmetric | ||||
|  | ||||
|         integrand_f1 = zeros(len(f1_array)) | ||||
|         for f1_index, f1 in enumerate(f1_array): | ||||
|             delta_beta = 4 * pi ** 2 * (f1 - f_eval) * (f2_array - f_eval) * \ | ||||
|                 (beta2 + pi * beta3 * (f1 + f2_array - 2 * f_ref_beta)) | ||||
|             integrand_f2 = NliSolver._generalized_rho_nli(delta_beta, rho_pump, z, alpha) | ||||
|             integrand_f1[f1_index] = 2 * trapz(integrand_f2, f2_array)  # 2x since integrand_f2 is symmetric in f2 | ||||
|         generalized_psi = 0.5 * sum(integrand_f1) * pump_carrier.baud_rate | ||||
|         return generalized_psi | ||||
|  | ||||
|     @staticmethod | ||||
|     def _generalized_psi(f_eval, cut_carrier, pump_carrier, f_cut_resolution, f_pump_resolution, srs, alpha, beta2, | ||||
|                          beta3, f_ref_beta): | ||||
|     def _fast_generalized_psi(f_eval, cut_frequency, cut_baud_rate, cut_roll_off, pump_frequency, pump_baud_rate, | ||||
|                               pump_roll_off, f_cut_resolution, srs, alpha, beta2, beta3, f_ref_beta): | ||||
|         """Computes the generalized psi function similarly to the one used in the GN model.""" | ||||
|         z = srs.z | ||||
|         rho_norm = srs.rho * exp(outer(alpha / 2, z)) | ||||
|         rho_pump = interp1d(srs.frequency, rho_norm, axis=0)(pump_carrier.frequency) | ||||
|         rho_pump = interp1d(srs.frequency, rho_norm, axis=0)(pump_frequency) | ||||
|  | ||||
|         f1_array = arange(pump_carrier.frequency - (pump_carrier.baud_rate * (1 + pump_carrier.roll_off) / 2), | ||||
|                           pump_carrier.frequency + (pump_carrier.baud_rate * (1 + pump_carrier.roll_off) / 2), | ||||
|         f1_array = array([pump_frequency - (pump_baud_rate * (1 + pump_roll_off) / 2), | ||||
|                           pump_frequency + (pump_baud_rate * (1 + pump_roll_off) / 2)]) | ||||
|         f2_array = arange(cut_frequency, cut_frequency + (cut_baud_rate * (1 + cut_roll_off) / 2), | ||||
|                           f_cut_resolution)  # Only positive f2 is used since integrand_f2 is symmetric | ||||
|  | ||||
|         integrand_f1 = zeros(f1_array.size) | ||||
|         for f1_index, f1 in enumerate(f1_array): | ||||
|             delta_beta = 4 * pi ** 2 * (f1 - f_eval) * (f2_array - f_eval) * ( | ||||
|                         beta2 + pi * beta3 * (f1 + f2_array - 2 * f_ref_beta)) | ||||
|             integrand_f2 = NliSolver._generalized_rho_nli(delta_beta, rho_pump, z, alpha) | ||||
|             integrand_f1[f1_index] = 2 * trapz(integrand_f2, f2_array)  # 2x since integrand_f2 is symmetric in f2 | ||||
|         generalized_psi = 0.5 * sum(integrand_f1) * pump_baud_rate | ||||
|         return generalized_psi | ||||
|  | ||||
|     @staticmethod | ||||
|     def _generalized_psi(f_eval, cut_frequency, cut_baud_rate, cut_roll_off, pump_frequency, pump_baud_rate, | ||||
|                          pump_roll_off, f_cut_resolution, f_pump_resolution, srs, alpha, beta2, beta3, f_ref_beta): | ||||
|         """Computes the generalized psi function similarly to the one used in the GN model.""" | ||||
|         z = srs.z | ||||
|         rho_norm = srs.rho * exp(outer(alpha / 2, z)) | ||||
|         rho_pump = interp1d(srs.frequency, rho_norm, axis=0)(pump_frequency) | ||||
|  | ||||
|         f1_array = arange(pump_frequency - (pump_baud_rate * (1 + pump_roll_off) / 2), | ||||
|                           pump_frequency + (pump_baud_rate * (1 + pump_roll_off) / 2), | ||||
|                           f_pump_resolution) | ||||
|         f2_array = arange(cut_carrier.frequency - (cut_carrier.baud_rate * (1 + cut_carrier.roll_off) / 2), | ||||
|                           cut_carrier.frequency + (cut_carrier.baud_rate * (1 + cut_carrier.roll_off) / 2), | ||||
|         f2_array = arange(cut_frequency - (cut_baud_rate * (1 + cut_roll_off) / 2), | ||||
|                           cut_frequency + (cut_baud_rate * (1 + cut_roll_off) / 2), | ||||
|                           f_cut_resolution) | ||||
|         psd1 = raised_cosine_comb(f1_array, pump_carrier) * (pump_carrier.baud_rate / pump_carrier.power.signal) | ||||
|         rc1 = raised_cosine(f1_array, pump_frequency, pump_baud_rate, pump_roll_off) | ||||
|  | ||||
|         integrand_f1 = zeros(len(f1_array)) | ||||
|         for f1_index, (f1, psd1_sample) in enumerate(zip(f1_array, psd1)): | ||||
|             f3_array = f1 + f2_array - f_eval | ||||
|             psd2 = raised_cosine_comb(f2_array, cut_carrier) * (cut_carrier.baud_rate / cut_carrier.power.signal) | ||||
|             psd3 = raised_cosine_comb(f3_array, pump_carrier) * (pump_carrier.baud_rate / pump_carrier.power.signal) | ||||
|             ggg = psd1_sample * psd2 * psd3 | ||||
|             delta_beta = 4 * pi**2 * (f1 - f_eval) * (f2_array - f_eval) * \ | ||||
|                 (beta2 + pi * beta3 * (f1 + f2_array - 2 * f_ref_beta)) | ||||
|             integrand_f2 = ggg * NliSolver._generalized_rho_nli(delta_beta, rho_pump, z, alpha) | ||||
|             integrand_f1[f1_index] = trapz(integrand_f2, f2_array) | ||||
|         integrand_f1 = zeros(f1_array.size) | ||||
|         for i in range(f1_array.size): | ||||
|             f3_array = f1_array[i] + f2_array - f_eval | ||||
|             rc2 = raised_cosine(f2_array, cut_frequency, cut_baud_rate, cut_roll_off) | ||||
|             rc3 = raised_cosine(f3_array, pump_frequency, pump_baud_rate, pump_roll_off) | ||||
|             delta_beta = 4 * pi ** 2 * (f1_array[i] - f_eval) * (f2_array - f_eval) * ( | ||||
|                         beta2 + pi * beta3 * (f1_array[i] + f2_array - 2 * f_ref_beta)) | ||||
|             integrand_f2 = rc1[i] * rc2 * rc3 * NliSolver._generalized_rho_nli(delta_beta, rho_pump, z, alpha) | ||||
|             integrand_f1[i] = trapz(integrand_f2, f2_array) | ||||
|         generalized_psi = trapz(integrand_f1, f1_array) | ||||
|         return generalized_psi | ||||
|  | ||||
|   | ||||
| @@ -11,6 +11,7 @@ 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 scipy import constants | ||||
| from copy import deepcopy | ||||
|  | ||||
| from gnpy.core.exceptions import ConfigurationError | ||||
|  | ||||
| @@ -213,7 +214,7 @@ freq2wavelength = constants.nu2lambda | ||||
|  | ||||
|  | ||||
| def freq2wavelength(value): | ||||
|     """ Converts frequency units to wavelength units. | ||||
|     """Converts frequency units to wavelength units. | ||||
|  | ||||
|     >>> round(freq2wavelength(191.35e12) * 1e9, 3) | ||||
|     1566.723 | ||||
| @@ -247,8 +248,7 @@ def per_label_average(values, labels): | ||||
|  | ||||
|  | ||||
| def pretty_summary_print(summary): | ||||
|     """Build a prettty string that shows the summary dict values per label with 2 digits | ||||
|     """ | ||||
|     """Build a prettty string that shows the summary dict values per label with 2 digits""" | ||||
|     if len(summary) == 1: | ||||
|         return f'{list(summary.values())[0]:.2f}' | ||||
|     text = ', '.join([f'{label}: {value:.2f}' for label, value in summary.items()]) | ||||
| @@ -256,7 +256,7 @@ def pretty_summary_print(summary): | ||||
|  | ||||
|  | ||||
| def deltawl2deltaf(delta_wl, wavelength): | ||||
|     """ deltawl2deltaf(delta_wl, wavelength): | ||||
|     """deltawl2deltaf(delta_wl, wavelength): | ||||
|     delta_wl is BW in wavelength units | ||||
|     wavelength is the center wl | ||||
|     units for delta_wl and wavelength must be same | ||||
| @@ -274,9 +274,9 @@ def deltawl2deltaf(delta_wl, wavelength): | ||||
|  | ||||
|  | ||||
| def deltaf2deltawl(delta_f, frequency): | ||||
|     """ deltawl2deltaf(delta_f, frequency): | ||||
|         converts delta frequency to delta wavelength | ||||
|         units for delta_wl and wavelength must be same | ||||
|     """convert delta frequency to delta wavelength | ||||
|  | ||||
|     Units for delta_wl and wavelength must be same. | ||||
|  | ||||
|     :param delta_f: delta frequency in same units as frequency | ||||
|     :param frequency: frequency BW is relevant for | ||||
| @@ -291,8 +291,7 @@ def deltaf2deltawl(delta_f, frequency): | ||||
|  | ||||
|  | ||||
| def rrc(ffs, baud_rate, alpha): | ||||
|     """ rrc(ffs, baud_rate, alpha): computes the root-raised cosine filter | ||||
|     function. | ||||
|     """compute the root-raised cosine filter function | ||||
|  | ||||
|     :param ffs: A numpy array of frequencies | ||||
|     :param baud_rate: The Baud Rate of the System | ||||
| @@ -318,7 +317,7 @@ def rrc(ffs, baud_rate, alpha): | ||||
|  | ||||
|  | ||||
| def merge_amplifier_restrictions(dict1, dict2): | ||||
|     """Updates contents of dicts recursively | ||||
|     """Update contents of dicts recursively | ||||
|  | ||||
|     >>> d1 = {'params': {'restrictions': {'preamp_variety_list': [], 'booster_variety_list': []}}} | ||||
|     >>> d2 = {'params': {'target_pch_out_db': -20}} | ||||
| @@ -413,3 +412,43 @@ def convert_length(value, units): | ||||
|         return value * 1e3 | ||||
|     else: | ||||
|         raise ConfigurationError(f'Cannot convert length in "{units}" into meters') | ||||
|  | ||||
|  | ||||
| def replace_none(dictionary): | ||||
|     """ Replaces None with inf values in a frequency slots dict | ||||
|  | ||||
|     >>> replace_none({'N': 3, 'M': None}) | ||||
|     {'N': 3, 'M': inf} | ||||
|  | ||||
|     """ | ||||
|     for key, val in dictionary.items(): | ||||
|         if val is None: | ||||
|             dictionary[key] = float('inf') | ||||
|         if val == float('inf'): | ||||
|             dictionary[key] = None | ||||
|     return dictionary | ||||
|  | ||||
|  | ||||
| def order_slots(slots): | ||||
|     """ Order frequency slots from larger slots to smaller ones up to None | ||||
|  | ||||
|     >>> l = [{'N': 3, 'M': None}, {'N': 2, 'M': 1}, {'N': None, 'M': None},{'N': 7, 'M': 2},{'N': None, 'M': 1} , {'N': None, 'M': 0}] | ||||
|     >>> order_slots(l) | ||||
|     ([7, 2, None, None, 3, None], [2, 1, 1, 0, None, None], [3, 1, 4, 5, 0, 2]) | ||||
|     """ | ||||
|     slots_list = deepcopy(slots) | ||||
|     slots_list = [replace_none(e) for e in slots_list] | ||||
|     for i, e in enumerate(slots_list): | ||||
|         e['i'] = i | ||||
|     slots_list = sorted(slots_list, key=lambda x: (-x['M'], x['N']) if x['M'] != float('inf') else (x['M'], x['N'])) | ||||
|     slots_list = [replace_none(e) for e in slots_list] | ||||
|     return [e['N'] for e in slots_list], [e['M'] for e in slots_list], [e['i'] for e in slots_list] | ||||
|  | ||||
|  | ||||
| def restore_order(elements, order): | ||||
|     """ Use order to re-order the element of the list, and ignore None values | ||||
|  | ||||
|     >>> restore_order([7, 2, None, None, 3, None], [3, 1, 4, 5, 0, 2]) | ||||
|     [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] | ||||
|   | ||||
| @@ -1,5 +1,5 @@ | ||||
| ''' | ||||
| """ | ||||
| Processing of data via :py:mod:`.json_io`. | ||||
| Utilities for Excel conversion in :py:mod:`.convert` and :py:mod:`.service_sheet`. | ||||
| Example code in :py:mod:`.cli_examples` and :py:mod:`.plots`. | ||||
| ''' | ||||
| """ | ||||
|   | ||||
| @@ -1,12 +1,12 @@ | ||||
| #!/usr/bin/env python3 | ||||
| # -*- coding: utf-8 -*- | ||||
|  | ||||
| ''' | ||||
| """ | ||||
| gnpy.tools.cli_examples | ||||
| ======================= | ||||
|  | ||||
| Common code for CLI examples | ||||
| ''' | ||||
| """ | ||||
|  | ||||
| import argparse | ||||
| import logging | ||||
| @@ -48,7 +48,7 @@ def show_example_data_dir(): | ||||
|  | ||||
|  | ||||
| def load_common_data(equipment_filename, topology_filename, simulation_filename, save_raw_network_filename): | ||||
|     '''Load common configuration from JSON files''' | ||||
|     """Load common configuration from JSON files""" | ||||
|  | ||||
|     try: | ||||
|         equipment = load_equipment(equipment_filename) | ||||
| @@ -85,7 +85,7 @@ def load_common_data(equipment_filename, topology_filename, simulation_filename, | ||||
|  | ||||
|  | ||||
| def _setup_logging(args): | ||||
|     logging.basicConfig(level={2: logging.DEBUG, 1: logging.INFO, 0: logging.CRITICAL}.get(args.verbose, logging.DEBUG)) | ||||
|     logging.basicConfig(level={2: logging.DEBUG, 1: logging.INFO, 0: logging.WARNING}.get(args.verbose, logging.DEBUG)) | ||||
|  | ||||
|  | ||||
| def _add_common_options(parser: argparse.ArgumentParser, network_default: Path): | ||||
| @@ -323,7 +323,7 @@ def path_requests_run(args=None): | ||||
|     args = parser.parse_args(args if args is not None else sys.argv[1:]) | ||||
|     _setup_logging(args) | ||||
|  | ||||
|     _logger.info(f'Computing path requests {args.service_filename} into JSON format') | ||||
|     _logger.info(f'Computing path requests {args.service_filename.name} into JSON format') | ||||
|  | ||||
|     (equipment, network) = load_common_data(args.equipment, args.topology, args.sim_params, args.save_network_before_autodesign) | ||||
|  | ||||
| @@ -331,7 +331,6 @@ def path_requests_run(args=None): | ||||
|     # TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by | ||||
|     # spacing, f_min and f_max | ||||
|     p_db = equipment['SI']['default'].power_dbm | ||||
|  | ||||
|     p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min, | ||||
|                                              equipment['SI']['default'].f_max, equipment['SI']['default'].spacing)) | ||||
|     try: | ||||
|   | ||||
| @@ -21,18 +21,22 @@ the "east" information so that it is possible to input undirected data. | ||||
| """ | ||||
|  | ||||
| from xlrd import open_workbook | ||||
| from logging import getLogger | ||||
| from argparse import ArgumentParser | ||||
| from collections import namedtuple, Counter, defaultdict | ||||
| from itertools import chain | ||||
| from json import dumps | ||||
| from pathlib import Path | ||||
| from copy import copy | ||||
| from gnpy.core import ansi_escapes | ||||
|  | ||||
| from gnpy.core.utils import silent_remove | ||||
| from gnpy.core.exceptions import NetworkTopologyError | ||||
| from gnpy.core.elements import Edfa, Fused, Fiber | ||||
|  | ||||
|  | ||||
| _logger = getLogger(__name__) | ||||
|  | ||||
|  | ||||
| def all_rows(sh, start=0): | ||||
|     return (sh.row(x) for x in range(start, sh.nrows)) | ||||
|  | ||||
| @@ -183,18 +187,18 @@ def parse_headers(my_sheet, input_headers_dict, headers, start_line, slice_in): | ||||
|             slice_out = read_slice(my_sheet, start_line + iteration, slice_in, h0) | ||||
|             iteration += 1 | ||||
|         if slice_out == (-1, -1): | ||||
|             msg = f'missing header {h0}' | ||||
|             if h0 in ('east', 'Node A', 'Node Z', 'City'): | ||||
|                 print(f'{ansi_escapes.red}CRITICAL{ansi_escapes.reset}: missing _{h0}_ header: EXECUTION ENDS') | ||||
|                 raise NetworkTopologyError(f'Missing _{h0}_ header') | ||||
|                 raise NetworkTopologyError(msg) | ||||
|             else: | ||||
|                 print(f'missing header {h0}') | ||||
|                 _logger.warning(msg) | ||||
|         elif not isinstance(input_headers_dict[h0], dict): | ||||
|             headers[slice_out[0]] = input_headers_dict[h0] | ||||
|         else: | ||||
|             headers = parse_headers(my_sheet, input_headers_dict[h0], headers, start_line + 1, slice_out) | ||||
|     if headers == {}: | ||||
|         print(f'{ansi_escapes.red}CRITICAL ERROR{ansi_escapes.reset}: could not find any header to read _ ABORT') | ||||
|         raise NetworkTopologyError('Could not find any header to read') | ||||
|         msg = 'CRITICAL ERROR: could not find any header to read _ ABORT' | ||||
|         raise NetworkTopologyError(msg) | ||||
|     return headers | ||||
|  | ||||
|  | ||||
| @@ -219,40 +223,76 @@ def sanity_check(nodes, links, nodes_by_city, links_by_city, eqpts_by_city): | ||||
|     for l1 in links: | ||||
|         for l2 in links: | ||||
|             if l1 is not l2 and l1 == l2 and l2 not in duplicate_links: | ||||
|                 print(f'\nWARNING\n \ | ||||
|                 _logger.warning(f'\nWARNING\n \ | ||||
|                     link {l1.from_city}-{l1.to_city} is duplicate \ | ||||
|                     \nthe 1st duplicate link will be removed but you should check Links sheet input') | ||||
|                 duplicate_links.append(l1) | ||||
|     for l in duplicate_links: | ||||
|         links.remove(l) | ||||
|         links_by_city[l.from_city].remove(l) | ||||
|         links_by_city[l.to_city].remove(l) | ||||
|  | ||||
|     if duplicate_links: | ||||
|         msg = 'XLS error: ' \ | ||||
|               + f'links {_format_items([(d.from_city, d.to_city) for d in duplicate_links])} are duplicate' | ||||
|         raise NetworkTopologyError(msg) | ||||
|     unreferenced_nodes = [n for n in nodes_by_city if n not in links_by_city] | ||||
|     if unreferenced_nodes: | ||||
|         raise NetworkTopologyError(f'{ansi_escapes.red}XLS error:{ansi_escapes.reset} The following nodes are not ' | ||||
|                                    f'referenced from the {ansi_escapes.cyan}Links{ansi_escapes.reset} sheet. ' | ||||
|                                    f'If unused, remove them from the {ansi_escapes.cyan}Nodes{ansi_escapes.reset} ' | ||||
|                                    f'sheet:\n' | ||||
|                                    + _format_items(unreferenced_nodes)) | ||||
|         msg = 'XLS error: The following nodes are not ' \ | ||||
|               + 'referenced from the Links sheet. ' \ | ||||
|               + 'If unused, remove them from the Nodes sheet:\n' \ | ||||
|               + _format_items(unreferenced_nodes) | ||||
|         raise NetworkTopologyError(msg) | ||||
|     # no need to check "Links" for invalid nodes because that's already in parse_excel() | ||||
|     wrong_eqpt_from = [n for n in eqpts_by_city if n not in nodes_by_city] | ||||
|     wrong_eqpt_to = [n.to_city for destinations in eqpts_by_city.values() | ||||
|                      for n in destinations if n.to_city not in nodes_by_city] | ||||
|     wrong_eqpt = wrong_eqpt_from + wrong_eqpt_to | ||||
|     if wrong_eqpt: | ||||
|         raise NetworkTopologyError(f'{ansi_escapes.red}XLS error:{ansi_escapes.reset} ' | ||||
|                                    f'The {ansi_escapes.cyan}Eqpt{ansi_escapes.reset} sheet refers to nodes that ' | ||||
|                                    f'are not defined in the {ansi_escapes.cyan}Nodes{ansi_escapes.reset} sheet:\n' | ||||
|                                    + _format_items(wrong_eqpt)) | ||||
|         msg = 'XLS error: ' \ | ||||
|               + 'The Eqpt sheet refers to nodes that ' \ | ||||
|               + 'are not defined in the Nodes sheet:\n'\ | ||||
|               + _format_items(wrong_eqpt) | ||||
|         raise NetworkTopologyError(msg) | ||||
|     # Now check links that are not listed in Links sheet, and duplicates | ||||
|     bad_eqpt = [] | ||||
|     possible_links = [f'{e.from_city}|{e.to_city}' for e in links] + [f'{e.to_city}|{e.from_city}' for e in links] | ||||
|     possible_eqpt = [] | ||||
|     duplicate_eqpt = [] | ||||
|     duplicate_ila = [] | ||||
|     for city, eqpts in eqpts_by_city.items(): | ||||
|         for eqpt in eqpts: | ||||
|             # Check that each node_A-node_Z exists in links | ||||
|             nodea_nodez = f'{eqpt.from_city}|{eqpt.to_city}' | ||||
|             nodez_nodea = f'{eqpt.to_city}|{eqpt.from_city}' | ||||
|             if nodea_nodez not in possible_links \ | ||||
|                     or nodez_nodea not in possible_links: | ||||
|                 bad_eqpt.append([eqpt.from_city, eqpt.to_city]) | ||||
|             else: | ||||
|                 # Check that there are no duplicate lines in the Eqpt sheet | ||||
|                 if nodea_nodez in possible_eqpt: | ||||
|                     duplicate_eqpt.append([eqpt.from_city, eqpt.to_city]) | ||||
|                 else: | ||||
|                     possible_eqpt.append(nodea_nodez) | ||||
|             # check that there are no two lines defining an ILA with different directions | ||||
|         if nodes_by_city[city].node_type == 'ILA' and len(eqpts) > 1: | ||||
|             duplicate_ila.append(city) | ||||
|     if bad_eqpt: | ||||
|         msg = 'XLS error: ' \ | ||||
|               + 'The Eqpt sheet references links that ' \ | ||||
|               + 'are not defined in the Links sheet:\n' \ | ||||
|               + _format_items(f'{item[0]} -> {item[1]}' for item in bad_eqpt) | ||||
|         raise NetworkTopologyError(msg) | ||||
|     if duplicate_eqpt: | ||||
|         msg = 'XLS error: Duplicate lines in Eqpt sheet:' \ | ||||
|               + _format_items(f'{item[0]} -> {item[1]}' for item in duplicate_eqpt) | ||||
|         raise NetworkTopologyError(msg) | ||||
|     if duplicate_ila: | ||||
|         msg = 'XLS error: Duplicate ILA eqpt definition in Eqpt sheet:' \ | ||||
|               + _format_items(duplicate_ila) | ||||
|         raise NetworkTopologyError(msg) | ||||
|  | ||||
|     for city, link in links_by_city.items(): | ||||
|         if nodes_by_city[city].node_type.lower() == 'ila' and len(link) != 2: | ||||
|             # wrong input: ILA sites can only be Degree 2 | ||||
|             # => correct to make it a ROADM and remove entry in links_by_city | ||||
|             # TODO: put in log rather than print | ||||
|             print(f'invalid node type ({nodes_by_city[city].node_type})\ | ||||
|                   specified in {city}, replaced by ROADM') | ||||
|             _logger.warning(f'invalid node type ({nodes_by_city[city].node_type}) ' | ||||
|                             + f'specified in {city}, replaced by ROADM') | ||||
|             nodes_by_city[city].node_type = 'ROADM' | ||||
|             for n in nodes: | ||||
|                 if n.city == city: | ||||
| @@ -642,17 +682,19 @@ def parse_excel(input_filename): | ||||
|     # sanity check | ||||
|     all_cities = Counter(n.city for n in nodes) | ||||
|     if len(all_cities) != len(nodes): | ||||
|         raise ValueError(f'Duplicate city: {all_cities}') | ||||
|         msg = f'Duplicate city: {all_cities}' | ||||
|         raise NetworkTopologyError(msg) | ||||
|     bad_links = [] | ||||
|     for lnk in links: | ||||
|         if lnk.from_city not in all_cities or lnk.to_city not in all_cities: | ||||
|             bad_links.append([lnk.from_city, lnk.to_city]) | ||||
|  | ||||
|     if bad_links: | ||||
|         raise NetworkTopologyError(f'{ansi_escapes.red}XLS error:{ansi_escapes.reset} ' | ||||
|                                    f'The {ansi_escapes.cyan}Links{ansi_escapes.reset} sheet references nodes that ' | ||||
|                                    f'are not defined in the {ansi_escapes.cyan}Nodes{ansi_escapes.reset} sheet:\n' | ||||
|                                    + _format_items(f'{item[0]} -> {item[1]}' for item in bad_links)) | ||||
|         msg = 'XLS error: ' \ | ||||
|               + 'The Links sheet references nodes that ' \ | ||||
|               + 'are not defined in the Nodes sheet:\n' \ | ||||
|               + _format_items(f'{item[0]} -> {item[1]}' for item in bad_links) | ||||
|         raise NetworkTopologyError(msg) | ||||
|  | ||||
|     return nodes, links, eqpts, roadms | ||||
|  | ||||
|   | ||||
| @@ -1,12 +1,12 @@ | ||||
| #!/usr/bin/env python3 | ||||
| # -*- coding: utf-8 -*- | ||||
|  | ||||
| ''' | ||||
| """ | ||||
| gnpy.tools.json_io | ||||
| ================== | ||||
|  | ||||
| Loading and saving data from JSON files in GNPy's internal data format | ||||
| ''' | ||||
| """ | ||||
|  | ||||
| from networkx import DiGraph | ||||
| from logging import getLogger | ||||
| @@ -15,13 +15,15 @@ import json | ||||
| from collections import namedtuple | ||||
| from numpy import arange | ||||
|  | ||||
| from gnpy.core import ansi_escapes, elements | ||||
| from gnpy.core import elements | ||||
| 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.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 | ||||
| from gnpy.tools.service_sheet import read_service_sheet | ||||
|  | ||||
| @@ -50,10 +52,9 @@ class _JsonThing: | ||||
|         for k, v in default_values.items(): | ||||
|             setattr(self, k, clean_kwargs.get(k, v)) | ||||
|             if k not in clean_kwargs and name != 'Amp': | ||||
|                 print(ansi_escapes.red + | ||||
|                       f'\n WARNING missing {k} attribute in eqpt_config.json[{name}]' + | ||||
|                       f'\n default value is {k} = {v}' + | ||||
|                       ansi_escapes.reset) | ||||
|                 msg = f'\n WARNING missing {k} attribute in eqpt_config.json[{name}]' \ | ||||
|                     + f'\n default value is {k} = {v}' | ||||
|                 _logger.warning(msg) | ||||
|  | ||||
|  | ||||
| class SI(_JsonThing): | ||||
| @@ -109,11 +110,12 @@ class Roadm(_JsonThing): | ||||
|         allowed_equalisations = ['target_pch_out_db', 'target_psd_out_mWperGHz', 'target_out_mWperSlotWidth'] | ||||
|         requested_eq_mask = [eq in kwargs for eq in allowed_equalisations] | ||||
|         if sum(requested_eq_mask) > 1: | ||||
|             raise EquipmentConfigError('Only one equalization type should be set in ROADM, found: ' | ||||
|                                        + ', '.join(eq for eq in allowed_equalisations if eq in kwargs)) | ||||
|             msg = 'Only one equalization type should be set in ROADM, found: ' \ | ||||
|                   + ', '.join(eq for eq in allowed_equalisations if eq in kwargs) | ||||
|             raise EquipmentConfigError(msg) | ||||
|         if not any(requested_eq_mask): | ||||
|             raise EquipmentConfigError('No equalization type set in ROADM') | ||||
|  | ||||
|             msg = 'No equalization type set in ROADM' | ||||
|             raise EquipmentConfigError(msg) | ||||
|         for key in allowed_equalisations: | ||||
|             if key in kwargs: | ||||
|                 setattr(self, key, kwargs[key]) | ||||
| @@ -133,6 +135,7 @@ class Transceiver(_JsonThing): | ||||
|         for mode_params in self.mode: | ||||
|             penalties = mode_params.get('penalties') | ||||
|             mode_params['penalties'] = {} | ||||
|             mode_params['equalization_offset_db'] = mode_params.get('equalization_offset_db', 0) | ||||
|             if not penalties: | ||||
|                 continue | ||||
|             for impairment in ('chromatic_dispersion', 'pmd', 'pdl'): | ||||
| @@ -162,9 +165,14 @@ class Fiber(_JsonThing): | ||||
|  | ||||
|     def __init__(self, **kwargs): | ||||
|         self.update_attr(self.default_values, kwargs, self.__class__.__name__) | ||||
|         for optional in ['gamma', 'raman_efficiency']: | ||||
|             if optional in kwargs: | ||||
|                 setattr(self, optional, kwargs[optional]) | ||||
|         if 'gamma' in kwargs: | ||||
|             setattr(self, 'gamma', kwargs['gamma']) | ||||
|         if 'raman_efficiency' in kwargs: | ||||
|             raman_coefficient = kwargs['raman_efficiency'] | ||||
|             cr = raman_coefficient.pop('cr') | ||||
|             raman_coefficient['g0'] = cr | ||||
|             raman_coefficient['reference_frequency'] = DEFAULT_RAMAN_COEFFICIENT['reference_frequency'] | ||||
|             setattr(self, 'raman_coefficient', raman_coefficient) | ||||
|  | ||||
|  | ||||
| class RamanFiber(Fiber): | ||||
| @@ -182,15 +190,24 @@ class Amp(_JsonThing): | ||||
|         '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': None, | ||||
|         'nf_ripple': 0, | ||||
|         'dgt': None, | ||||
|         'gain_ripple': 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 | ||||
|         'pdl': 0, | ||||
|         'advance_configurations_from_json': None | ||||
|     } | ||||
|  | ||||
|     def __init__(self, **kwargs): | ||||
| @@ -209,7 +226,8 @@ class Amp(_JsonThing): | ||||
|             try: | ||||
|                 nf0 = kwargs.pop('nf0') | ||||
|             except KeyError:  # nf0 is expected for a fixed gain amp | ||||
|                 raise EquipmentConfigError(f'missing nf0 value input for amplifier: {type_variety} in equipment config') | ||||
|                 msg = f'missing nf0 value input for amplifier: {type_variety} in equipment config' | ||||
|                 raise EquipmentConfigError(msg) | ||||
|             for k in ('nf_min', 'nf_max'): | ||||
|                 try: | ||||
|                     del kwargs[k] | ||||
| @@ -224,7 +242,8 @@ class Amp(_JsonThing): | ||||
|                 nf_min = kwargs.pop('nf_min') | ||||
|                 nf_max = kwargs.pop('nf_max') | ||||
|             except KeyError: | ||||
|                 raise EquipmentConfigError(f'missing nf_min or nf_max value input for amplifier: {type_variety} in equipment config') | ||||
|                 msg = f'missing nf_min or nf_max value input for amplifier: {type_variety} in equipment config' | ||||
|                 raise EquipmentConfigError(msg) | ||||
|             try:  # remove all remaining nf inputs | ||||
|                 del kwargs['nf0'] | ||||
|             except KeyError: | ||||
| @@ -246,7 +265,8 @@ class Amp(_JsonThing): | ||||
|                 preamp_variety = kwargs.pop('preamp_variety') | ||||
|                 booster_variety = kwargs.pop('booster_variety') | ||||
|             except KeyError: | ||||
|                 raise EquipmentConfigError(f'missing preamp/booster variety input for amplifier: {type_variety} in equipment config') | ||||
|                 msg = f'missing preamp/booster variety input for amplifier: {type_variety} in equipment config' | ||||
|                 raise EquipmentConfigError(msg) | ||||
|             dual_stage_def = Model_dual_stage(preamp_variety, booster_variety) | ||||
|         else: | ||||
|             raise EquipmentConfigError(f'Edfa type_def {type_def} does not exist') | ||||
| @@ -368,9 +388,7 @@ 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. | ||||
|     """ | ||||
|     """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: | ||||
| @@ -440,11 +458,11 @@ def load_network(filename, equipment): | ||||
|  | ||||
|  | ||||
| def save_network(network: DiGraph, filename: str): | ||||
|     '''Dump the network into a JSON file | ||||
|     """Dump the network into a JSON file | ||||
|  | ||||
|     :param network: network to work on | ||||
|     :param filename: file to write to | ||||
|     ''' | ||||
|     """ | ||||
|     save_json(network_to_json(network), filename) | ||||
|  | ||||
|  | ||||
| @@ -486,13 +504,20 @@ def network_from_json(json_data, equipment): | ||||
|                 # if more than one equalization was defined in element config, then raise an error | ||||
|                 extra_params = merge_equalization(temp, extra_params) | ||||
|                 if not extra_params: | ||||
|                     raise ConfigurationError(f'ROADM {el_config["uid"]}: invalid equalization settings') | ||||
|                     msg = f'ROADM {el_config["uid"]}: invalid equalization settings' | ||||
|                     raise ConfigurationError(msg) | ||||
|             temp = merge_amplifier_restrictions(temp, extra_params) | ||||
|             el_config['params'] = temp | ||||
|             el_config['type_variety'] = variety | ||||
|         elif (typ in ['Fiber', 'RamanFiber']) or (typ == 'Edfa' and variety not in ['default', '']): | ||||
|         elif (typ in ['Fiber', 'RamanFiber']): | ||||
|             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': | ||||
|             if variety in ['default', '']: | ||||
|                 el_config['params'] = Amp.default_values | ||||
|             else: | ||||
|                 raise ConfigurationError(f'The Edfa of variety type {variety} was not recognized:' | ||||
|                                          '\nplease check it is properly defined in the eqpt_config json file') | ||||
|         el = cls(**el_config) | ||||
|         g.add_node(el) | ||||
|  | ||||
| @@ -507,7 +532,8 @@ def network_from_json(json_data, equipment): | ||||
|                 edge_length = 0.01 | ||||
|             g.add_edge(nodes[from_node], nodes[to_node], weight=edge_length) | ||||
|         except KeyError: | ||||
|             raise NetworkTopologyError(f'can not find {from_node} or {to_node} defined in {cx}') | ||||
|             msg = f'can not find {from_node} or {to_node} defined in {cx}' | ||||
|             raise NetworkTopologyError(msg) | ||||
|  | ||||
|     return g | ||||
|  | ||||
| @@ -538,15 +564,13 @@ def save_json(obj, filename): | ||||
|  | ||||
|  | ||||
| def load_requests(filename, eqpt, bidir, network, network_filename): | ||||
|     """ loads the requests from a json or an excel file into a data string | ||||
|     """ | ||||
|     """loads the requests from a json or an excel file into a data string""" | ||||
|     if filename.suffix.lower() in ('.xls', '.xlsx'): | ||||
|         _logger.info('Automatically converting requests from XLS to JSON') | ||||
|         try: | ||||
|             return convert_service_sheet(filename, eqpt, network, network_filename=network_filename, bidir=bidir) | ||||
|         except ServiceError as this_e: | ||||
|             print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {this_e}') | ||||
|             exit(1) | ||||
|             raise ServiceError(f'Service error: {this_e}') | ||||
|     else: | ||||
|         return load_json(filename) | ||||
|  | ||||
| @@ -563,6 +587,9 @@ def requests_from_json(json_data, equipment): | ||||
|         params['bidir'] = req['bidirectional'] | ||||
|         params['destination'] = req['destination'] | ||||
|         params['trx_type'] = req['path-constraints']['te-bandwidth']['trx_type'] | ||||
|         if params['trx_type'] is None: | ||||
|             msg = f'Request {req["request-id"]} has no transceiver type defined.' | ||||
|             raise ServiceError(msg) | ||||
|         params['trx_mode'] = req['path-constraints']['te-bandwidth'].get('trx_mode', None) | ||||
|         params['format'] = params['trx_mode'] | ||||
|         params['spacing'] = req['path-constraints']['te-bandwidth']['spacing'] | ||||
| @@ -575,9 +602,12 @@ def requests_from_json(json_data, equipment): | ||||
|         # 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) | ||||
|         except EquipmentConfigError as e: | ||||
|             msg = f'Equipment Config error in {req["request-id"]}: {e}' | ||||
|             raise EquipmentConfigError(msg) from e | ||||
|         params.update(trx_params) | ||||
|         # print(trx_params['min_spacing']) | ||||
|         # optical power might be set differently in the request. if it is indicated then the | ||||
|         # params['power'] is updated | ||||
|         try: | ||||
| @@ -598,7 +628,8 @@ def requests_from_json(json_data, equipment): | ||||
|                 params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing']) | ||||
|         except KeyError: | ||||
|             params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing']) | ||||
|         params['effective_freq_slot'] = req['path-constraints']['te-bandwidth'].get('effective-freq-slot', [None])[0] | ||||
|         params['effective_freq_slot'] = \ | ||||
|             req['path-constraints']['te-bandwidth'].get('effective-freq-slot', [{'N': None, 'M': None}]) | ||||
|         try: | ||||
|             params['path_bandwidth'] = req['path-constraints']['te-bandwidth']['path_bandwidth'] | ||||
|         except KeyError: | ||||
| @@ -612,43 +643,65 @@ def _check_one_request(params, f_max_from_si): | ||||
|     """Checks that the requested parameters are consistant (spacing vs nb channel vs transponder mode...)""" | ||||
|     f_min = params['f_min'] | ||||
|     f_max = params['f_max'] | ||||
|     max_recommanded_nb_channels = automatic_nch(f_min, f_max, params['spacing']) | ||||
|     max_recommanded_nb_channels = automatic_nch(f_min, f_max_from_si, params['spacing']) | ||||
|     if params['baud_rate'] is not None: | ||||
|         # implicitly means that a mode is defined with min_spacing | ||||
|         if params['min_spacing'] > params['spacing']: | ||||
|             msg = f'Request {params["request_id"]} has spacing below transponder ' +\ | ||||
|                   f'{params["trx_type"]} {params["trx_mode"]} min spacing value ' +\ | ||||
|                   f'{params["min_spacing"]*1e-9}GHz.\nComputation stopped' | ||||
|             print(msg) | ||||
|             _logger.critical(msg) | ||||
|             raise ServiceError(msg) | ||||
|         if f_max > f_max_from_si: | ||||
|             msg = f'''Requested channel number {params["nb_channel"]}, baud rate {params["baud_rate"]} GHz | ||||
|             and requested spacing {params["spacing"]*1e-9}GHz is not consistent with frequency range | ||||
|             {f_min*1e-12} THz, {f_max*1e-12} THz, min recommanded spacing {params["min_spacing"]*1e-9}GHz. | ||||
|             max recommanded nb of channels is {max_recommanded_nb_channels}.''' | ||||
|             _logger.critical(msg) | ||||
|             msg = f'Requested channel number {params["nb_channel"]}, baud rate {params["baud_rate"] * 1e-9} GHz' \ | ||||
|                   + f' and requested spacing {params["spacing"]*1e-9}GHz is not consistent with frequency range' \ | ||||
|                   + f' {f_min*1e-12} THz, {f_max_from_si*1e-12} THz.' \ | ||||
|                   + f' Max recommanded nb of channels is {max_recommanded_nb_channels}.' | ||||
|             raise ServiceError(msg) | ||||
|     # Transponder mode already selected; will it fit to the requested bandwidth? | ||||
|     if params['trx_mode'] is not None and params['effective_freq_slot'] is not None \ | ||||
|             and params['effective_freq_slot']['M'] is not None: | ||||
|         _, requested_m = compute_spectrum_slot_vs_bandwidth(params['path_bandwidth'], | ||||
|     if params['trx_mode'] is not None and params['effective_freq_slot'] is not None: | ||||
|         required_nb_of_channels, requested_m = compute_spectrum_slot_vs_bandwidth(params['path_bandwidth'], | ||||
|                                                                                   params['spacing'], | ||||
|                                                                                   params['bit_rate']) | ||||
|         # params['effective_freq_slot']['M'] value should be bigger than the computed requested_m (simple estimate) | ||||
|         _, per_channel_m = compute_spectrum_slot_vs_bandwidth(params['bit_rate'], | ||||
|                                                               params['spacing'], | ||||
|                                                               params['bit_rate']) | ||||
|         # each M should fit one or more channels if it is not None | ||||
|         # spectrum slots should not overlap | ||||
|         # resulting nb of channels should be bigger than the nb computed with path_bandwidth | ||||
|         # without being splitted | ||||
|         # TODO: elaborate a more accurate estimate with nb_wl * tx_osnr + possibly guardbands in case of | ||||
|         # superchannel closed packing. | ||||
|  | ||||
|         if requested_m > params['effective_freq_slot']['M']: | ||||
|             msg = f'requested M {params["effective_freq_slot"]["M"]} number of slots for request' +\ | ||||
|                   f'{params["request_id"]} should be greater than {requested_m} to support request' +\ | ||||
|                   f'{params["path_bandwidth"] * 1e-9} Gbit/s with {params["trx_type"]} {params["trx_mode"]}' | ||||
|         nb_of_channels = 0 | ||||
|         # order slots | ||||
|         slots = sorted(params['effective_freq_slot'], key=lambda x: float('inf') if x['N'] is None else x['N']) | ||||
|         for slot in slots: | ||||
|             nb_of_channels = nb_of_channels + slot['M'] // per_channel_m if slot['M'] is not None \ | ||||
|                 and nb_of_channels is not None else None | ||||
|             if slot['M'] is not None and slot['M'] < per_channel_m: | ||||
|                 msg = f'Requested M {slot} number of slots for request' +\ | ||||
|                       f' {params["request_id"]} should be greater than {per_channel_m} to support request' +\ | ||||
|                       f'with {params["trx_type"]} {params["trx_mode"]}' | ||||
|                 _logger.critical(msg) | ||||
|         if nb_of_channels is not None and nb_of_channels < required_nb_of_channels: | ||||
|             msg = f'Requested M {slots} number of slots for request {params["request_id"]} support {nb_of_channels}' +\ | ||||
|                   f' nb of channels while {required_nb_of_channels} are required to support request' +\ | ||||
|                   f' {params["path_bandwidth"] * 1e-9} Gbit/s with {params["trx_type"]} {params["trx_mode"]}' | ||||
|             raise ServiceError(msg) | ||||
|         if nb_of_channels is not None: | ||||
|             _, stop0n = mvalue_to_slots(slots[0]['N'], slots[0]['M']) | ||||
|             i = 1 | ||||
|             while i < len(slots): | ||||
|                 slot = slots[i] | ||||
|                 startn, stopn = mvalue_to_slots(slot['N'], slot['M']) | ||||
|                 if startn <= stop0n: | ||||
|                     msg = f'Requested M {slots} for request {params["request_id"]} overlap' | ||||
|                     raise ServiceError(msg) | ||||
|                 _, stop0n = startn, stopn | ||||
|                 i += 1 | ||||
|  | ||||
|  | ||||
| def disjunctions_from_json(json_data): | ||||
|     """ reads the disjunction requests from the json dict and create the list | ||||
|     """reads the disjunction requests from the json dict and create the list | ||||
|     of requested disjunctions for this set of requests | ||||
|     """ | ||||
|     disjunctions_list = [] | ||||
|   | ||||
| @@ -1,12 +1,12 @@ | ||||
| #!/usr/bin/env python3 | ||||
| # -*- coding: utf-8 -*- | ||||
|  | ||||
| ''' | ||||
| """ | ||||
| gnpy.tools.plots | ||||
| ================ | ||||
|  | ||||
| Graphs and plots usable from a CLI application | ||||
| ''' | ||||
| """ | ||||
|  | ||||
| from matplotlib.pyplot import show, axis, figure, title, text | ||||
| from networkx import draw_networkx | ||||
|   | ||||
| @@ -18,7 +18,6 @@ from copy import deepcopy | ||||
| from gnpy.core.utils import db2lin | ||||
| from gnpy.core.exceptions import ServiceError | ||||
| from gnpy.core.elements import Transceiver, Roadm, Edfa, Fiber | ||||
| import gnpy.core.ansi_escapes as ansi_escapes | ||||
| from gnpy.tools.convert import corresp_names, corresp_next_node | ||||
|  | ||||
| SERVICES_COLUMN = 12 | ||||
| @@ -68,24 +67,21 @@ class Request_element(Element): | ||||
|                 if [mode for mode in equipment['Transceiver'][Request.trx_type].mode if mode['format'] == Requestmode]: | ||||
|                     self.mode = Requestmode | ||||
|                 else: | ||||
|                     msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' with mode: \'{Requestmode}\' in eqpt library \nComputation stopped.' | ||||
|                     # print(msg) | ||||
|                     logger.critical(msg) | ||||
|                     msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' ' \ | ||||
|                         + f'with mode: \'{Requestmode}\' in eqpt library \nComputation stopped.' | ||||
|                     raise ServiceError(msg) | ||||
|             else: | ||||
|                 Requestmode = None | ||||
|                 self.mode = Request.mode | ||||
|         except KeyError: | ||||
|             msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' with mode: \'{Request.mode}\' in eqpt library \nComputation stopped.' | ||||
|             # print(msg) | ||||
|             logger.critical(msg) | ||||
|             msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' ' \ | ||||
|                 + f'with mode: \'{Request.mode}\' in eqpt library \nComputation stopped.' | ||||
|             raise ServiceError(msg) | ||||
|         # excel input are in GHz and dBm | ||||
|         if Request.spacing is not None: | ||||
|             self.spacing = Request.spacing * 1e9 | ||||
|         else: | ||||
|             msg = f'Request {self.request_id} missing spacing: spacing is mandatory.\ncomputation stopped' | ||||
|             logger.critical(msg) | ||||
|             raise ServiceError(msg) | ||||
|         if Request.power is not None: | ||||
|             self.power = db2lin(Request.power) * 1e-3 | ||||
| @@ -225,7 +221,7 @@ def parse_excel(input_filename): | ||||
| def parse_service_sheet(service_sheet): | ||||
|     """ reads each column according to authorized fieldnames. order is not important. | ||||
|     """ | ||||
|     logger.info(f'Validating headers on {service_sheet.name!r}') | ||||
|     logger.debug(f'Validating headers on {service_sheet.name!r}') | ||||
|     # add a test on field to enable the '' field case that arises when columns on the | ||||
|     # right hand side are used as comments or drawing in the excel sheet | ||||
|     header = [x.value.strip() for x in service_sheet.row(4)[0:SERVICES_COLUMN] | ||||
| @@ -245,7 +241,6 @@ def parse_service_sheet(service_sheet): | ||||
|         service_fieldnames = [authorized_fieldnames[e] for e in header] | ||||
|     except KeyError: | ||||
|         msg = f'Malformed header on Service sheet: {header} field not in {authorized_fieldnames}' | ||||
|         logger.critical(msg) | ||||
|         raise ValueError(msg) | ||||
|     for row in all_rows(service_sheet, start=5): | ||||
|         yield Request(**parse_row(row[0:SERVICES_COLUMN], service_fieldnames)) | ||||
| @@ -273,15 +268,13 @@ def correct_xls_route_list(network_filename, network, pathreqlist): | ||||
|     for pathreq in pathreqlist: | ||||
|         # first check that source and dest are transceivers | ||||
|         if pathreq.source not in transponders: | ||||
|             msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find' +\ | ||||
|                 f' transponder source : {pathreq.source}.{ansi_escapes.reset}' | ||||
|             logger.critical(msg) | ||||
|             msg = f'Request: {pathreq.request_id}: could not find' +\ | ||||
|                 f' transponder source : {pathreq.source}.' | ||||
|             raise ServiceError(msg) | ||||
|  | ||||
|         if pathreq.destination not in transponders: | ||||
|             msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find' +\ | ||||
|                 f' transponder destination: {pathreq.destination}.{ansi_escapes.reset}' | ||||
|             logger.critical(msg) | ||||
|             msg = f'Request: {pathreq.request_id}: could not find' +\ | ||||
|                 f' transponder destination: {pathreq.destination}.' | ||||
|             raise ServiceError(msg) | ||||
|         # silently pop source and dest nodes from the list if they were added by the user as first | ||||
|         # and last elem in the constraints respectively. Other positions must lead to an error | ||||
| @@ -333,17 +326,16 @@ def correct_xls_route_list(network_filename, network, pathreqlist): | ||||
|                             # too much ambiguity, 'b' is an ila, its name can be: | ||||
|                             # Edfa0_fiber (a → b)-xx if next node is c or | ||||
|                             # Edfa0_fiber (c → b)-xx if next node is a | ||||
|                             msg = f'{ansi_escapes.yellow}Invalid route node specified:' +\ | ||||
|                                 f'\n\t\'{n_id}\', replaced with \'{new_n}\'{ansi_escapes.reset}' | ||||
|                             logger.info(msg) | ||||
|                             msg = f'Request {pathreq.request_id}: Invalid route node specified:' \ | ||||
|                                 + f'\n\t\'{n_id}\', replaced with \'{new_n}\'' | ||||
|                             logger.warning(msg) | ||||
|                             pathreq.nodes_list[pathreq.nodes_list.index(n_id)] = new_n | ||||
|                     except StopIteration: | ||||
|                         # shall not come in this case, unless requested direction does not exist | ||||
|                         msg = f'{ansi_escapes.yellow}Invalid route specified {n_id}: could' +\ | ||||
|                             f' not decide on direction, skipped!.\nPlease add a valid' +\ | ||||
|                             f' direction in constraints (next neighbour node){ansi_escapes.reset}' | ||||
|                         print(msg) | ||||
|                         logger.info(msg) | ||||
|                         msg = f'Request {pathreq.request_id}: Invalid route specified {n_id}: could' \ | ||||
|                             + ' not decide on direction, skipped!.\nPlease add a valid' \ | ||||
|                             + ' direction in constraints (next neighbour node)' | ||||
|                         logger.warning(msg) | ||||
|                         pathreq.loose_list.pop(pathreq.nodes_list.index(n_id)) | ||||
|                         pathreq.nodes_list.remove(n_id) | ||||
|                 else: | ||||
| @@ -351,28 +343,24 @@ def correct_xls_route_list(network_filename, network, pathreqlist): | ||||
|                         # if no matching can be found in the network just ignore this constraint | ||||
|                         # if it is a loose constraint | ||||
|                         # warns the user that this node is not part of the topology | ||||
|                         msg = f'{ansi_escapes.yellow}Invalid node specified:\n\t\'{n_id}\'' +\ | ||||
|                             f', could not use it as constraint, skipped!{ansi_escapes.reset}' | ||||
|                         print(msg) | ||||
|                         logger.info(msg) | ||||
|                         msg = f'Request {pathreq.request_id}: Invalid node specified:\n\t\'{n_id}\'' \ | ||||
|                             + ', could not use it as constraint, skipped!' | ||||
|                         logger.warning(msg) | ||||
|                         pathreq.loose_list.pop(pathreq.nodes_list.index(n_id)) | ||||
|                         pathreq.nodes_list.remove(n_id) | ||||
|                     else: | ||||
|                         msg = f'{ansi_escapes.red}Could not find node:\n\t\'{n_id}\' in network' +\ | ||||
|                             f' topology. Strict constraint can not be applied.{ansi_escapes.reset}' | ||||
|                         logger.critical(msg) | ||||
|                         msg = f'Request {pathreq.request_id}: Could not find node:\n\t\'{n_id}\' in network' \ | ||||
|                             + ' topology. Strict constraint can not be applied.' | ||||
|                         raise ServiceError(msg) | ||||
|             else: | ||||
|                 if temp.loose_list[i] == 'LOOSE': | ||||
|                     print(f'{ansi_escapes.yellow}Invalid route node specified:\n\t\'{n_id}\'' + | ||||
|                           f' type is not supported as constraint with xls network input,' + | ||||
|                           f' skipped!{ansi_escapes.reset}') | ||||
|                     logger.warning(f'Request {pathreq.request_id}: Invalid route node specified:\n\t\'{n_id}\'' | ||||
|                                    + ' type is not supported as constraint with xls network input, skipped!') | ||||
|                     pathreq.loose_list.pop(pathreq.nodes_list.index(n_id)) | ||||
|                     pathreq.nodes_list.remove(n_id) | ||||
|                 else: | ||||
|                     msg = f'{ansi_escapes.red}Invalid route node specified \n\t\'{n_id}\'' +\ | ||||
|                         f' type is not supported as constraint with xls network input,' +\ | ||||
|                         f', Strict constraint can not be applied.{ansi_escapes.reset}' | ||||
|                     logger.critical(msg) | ||||
|                     msg = f'Invalid route node specified \n\t\'{n_id}\'' \ | ||||
|                         + ' type is not supported as constraint with xls network input,' \ | ||||
|                         + ', Strict constraint can not be applied.' | ||||
|                     raise ServiceError(msg) | ||||
|     return pathreqlist | ||||
|   | ||||
| @@ -1,3 +1,3 @@ | ||||
| ''' | ||||
| """ | ||||
| Tracking :py:mod:`.request` for spectrum and their :py:mod:`.spectrum_assignment`. | ||||
| ''' | ||||
| """ | ||||
|   | ||||
| @@ -25,7 +25,6 @@ from gnpy.core.elements import Transceiver, Roadm | ||||
| from gnpy.core.utils import lin2db | ||||
| from gnpy.core.info import create_input_spectral_information, carriers_to_spectral_information, ReferenceCarrier | ||||
| from gnpy.core.exceptions import ServiceError, DisjunctionError | ||||
| import gnpy.core.ansi_escapes as ansi_escapes | ||||
| from copy import deepcopy | ||||
| from csv import writer | ||||
| from math import ceil | ||||
| @@ -35,15 +34,14 @@ LOGGER = getLogger(__name__) | ||||
| RequestParams = namedtuple('RequestParams', 'request_id source destination bidir trx_type' | ||||
|                            ' 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') | ||||
|                            ' roll_off tx_osnr min_spacing cost path_bandwidth effective_freq_slot' | ||||
|                            ' equalization_offset_db') | ||||
| DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link_diverse' | ||||
|                                ' node_diverse disjunctions_req') | ||||
|  | ||||
|  | ||||
| class PathRequest: | ||||
|     """ the class that contains all attributes related to a request | ||||
|     """ | ||||
|  | ||||
|     """the class that contains all attributes related to a request""" | ||||
|     def __init__(self, *args, **params): | ||||
|         params = RequestParams(**params) | ||||
|         self.request_id = params.request_id | ||||
| @@ -70,9 +68,10 @@ class PathRequest: | ||||
|         self.cost = params.cost | ||||
|         self.path_bandwidth = params.path_bandwidth | ||||
|         if params.effective_freq_slot is not None: | ||||
|             self.N = params.effective_freq_slot['N'] | ||||
|             self.M = params.effective_freq_slot['M'] | ||||
|             self.N = [s['N'] for s in params.effective_freq_slot] | ||||
|             self.M = [s['M'] for s in params.effective_freq_slot] | ||||
|         self.initial_spectrum = None | ||||
|         self.offset_db = params.equalization_offset_db | ||||
|  | ||||
|     def __str__(self): | ||||
|         return '\n\t'.join([f'{type(self).__name__} {self.request_id}', | ||||
| @@ -104,8 +103,7 @@ class PathRequest: | ||||
|  | ||||
|  | ||||
| class Disjunction: | ||||
|     """ the class that contains all attributes related to disjunction constraints | ||||
|     """ | ||||
|     """the class that contains all attributes related to disjunction constraints""" | ||||
|  | ||||
|     def __init__(self, *args, **params): | ||||
|         params = DisjunctionParams(**params) | ||||
| @@ -150,8 +148,7 @@ class ResultElement: | ||||
|  | ||||
|     @property | ||||
|     def detailed_path_json(self): | ||||
|         """ a function that builds path object for normal and blocking cases | ||||
|         """ | ||||
|         """a function that builds path object for normal and blocking cases""" | ||||
|         index = 0 | ||||
|         pro_list = [] | ||||
|         for element in self.computed_path: | ||||
| @@ -175,10 +172,10 @@ class ResultElement: | ||||
|                 temp = { | ||||
|                     'path-route-object': { | ||||
|                         'index': index, | ||||
|                         "label-hop": { | ||||
|                             "N": self.path_request.N, | ||||
|                             "M": self.path_request.M | ||||
|                         }, | ||||
|                         "label-hop": [{ | ||||
|                             "N": n, | ||||
|                             "M": m | ||||
|                         } for n, m in zip(self.path_request.N, self.path_request.M)], | ||||
|                     } | ||||
|                 } | ||||
|                 pro_list.append(temp) | ||||
| @@ -207,11 +204,9 @@ class ResultElement: | ||||
|  | ||||
|     @property | ||||
|     def path_properties(self): | ||||
|         """ a function that returns the path properties (metrics, crossed elements) into a dict | ||||
|         """ | ||||
|         """a function that returns the path properties (metrics, crossed elements) into a dict""" | ||||
|         def path_metric(pth, req): | ||||
|             """ creates the metrics dictionary | ||||
|             """ | ||||
|             """creates the metrics dictionary""" | ||||
|             return [ | ||||
|                 { | ||||
|                     'metric-type': 'SNR-bandwidth', | ||||
| @@ -253,8 +248,7 @@ class ResultElement: | ||||
|  | ||||
|     @property | ||||
|     def pathresult(self): | ||||
|         """ create the result dictionnary (response for a request) | ||||
|         """ | ||||
|         """create the result dictionnary (response for a request)""" | ||||
|         try: | ||||
|             if self.path_request.blocking_reason in BLOCKING_NOPATH: | ||||
|                 response = { | ||||
| @@ -292,7 +286,6 @@ def compute_constrained_path(network, req): | ||||
|         # been corrected and harmonized before | ||||
|         msg = (f'Request {req.request_id} malformed list of nodes: last node should ' | ||||
|                'be destination trx') | ||||
|         LOGGER.critical(msg) | ||||
|         raise ValueError() | ||||
|  | ||||
|     trx = [n for n in network if isinstance(n, Transceiver)] | ||||
| @@ -307,10 +300,9 @@ def compute_constrained_path(network, req): | ||||
|         path_generator = shortest_simple_paths(network, source, destination, weight='weight') | ||||
|         total_path = next(path for path in path_generator if ispart(nodes_list, path)) | ||||
|     except NetworkXNoPath: | ||||
|         msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path from' | ||||
|                f' {source.uid} to node: {destination.uid} in network topology{ansi_escapes.reset}') | ||||
|         msg = (f'Request {req.request_id} could not find a path from' | ||||
|                f' {source.uid} to node: {destination.uid} in network topology') | ||||
|         LOGGER.critical(msg) | ||||
|         print(msg) | ||||
|         req.blocking_reason = 'NO_PATH' | ||||
|         total_path = [] | ||||
|     except StopIteration: | ||||
| @@ -319,24 +311,21 @@ def compute_constrained_path(network, req): | ||||
|         # last node which is the transceiver) | ||||
|         # if all nodes i n node_list are LOOSE constraint, skip the constraints and find | ||||
|         # a path w/o constraints, else there is no possible path | ||||
|         print(f'{ansi_escapes.yellow}Request {req.request_id} could not find a path crossing ' | ||||
|               f'{[el.uid for el in nodes_list[:-1]]} in network topology{ansi_escapes.reset}') | ||||
|         LOGGER.warning(f'Request {req.request_id} could not find a path crossing ' | ||||
|                        f'{[el.uid for el in nodes_list[:-1]]} in network topology') | ||||
|  | ||||
|         if 'STRICT' not in req.loose_list[:-1]: | ||||
|             msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path with user_' | ||||
|                    f'include node constraints{ansi_escapes.reset}') | ||||
|             LOGGER.info(msg) | ||||
|             print(f'constraint ignored') | ||||
|             msg = (f'Request {req.request_id} could not find a path with user_' | ||||
|                    f'include node constraints. Constraint ignored') | ||||
|             LOGGER.warning(msg) | ||||
|             total_path = dijkstra_path(network, source, destination, weight='weight') | ||||
|         else: | ||||
|             # one STRICT makes the whole list STRICT | ||||
|             msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path with user ' | ||||
|                    f'include node constraints.\nNo path computed{ansi_escapes.reset}') | ||||
|             msg = (f'Request {req.request_id} could not find a path with user ' | ||||
|                    f'include node constraints.\nNo path computed') | ||||
|             LOGGER.critical(msg) | ||||
|             print(msg) | ||||
|             req.blocking_reason = 'NO_PATH_WITH_CONSTRAINT' | ||||
|             total_path = [] | ||||
|  | ||||
|     return total_path | ||||
|  | ||||
|  | ||||
| @@ -350,15 +339,15 @@ def ref_carrier(equipment): | ||||
|  | ||||
|  | ||||
| def propagate(path, req, equipment): | ||||
|     """ propagates signals in each element according to initial spectrum set by user | ||||
|     """ | ||||
|     """propagates signals in each element according to initial spectrum set by user""" | ||||
|     if req.initial_spectrum is not None: | ||||
|         si = carriers_to_spectral_information(initial_spectrum=req.initial_spectrum, | ||||
|                                               power=req.power, ref_carrier=ref_carrier(equipment)) | ||||
|     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, ref_carrier=ref_carrier(equipment)) | ||||
|             power=req.power, spacing=req.spacing, tx_osnr=req.tx_osnr, delta_pdb=req.offset_db, | ||||
|             ref_carrier=ref_carrier(equipment)) | ||||
|     for i, el in enumerate(path): | ||||
|         if isinstance(el, Roadm): | ||||
|             si = el(si, degree=path[i+1].uid) | ||||
| @@ -376,20 +365,21 @@ def propagate(path, req, equipment): | ||||
|  | ||||
| def propagate_and_optimize_mode(path, req, equipment): | ||||
|     # if mode is unknown : loops on the modes starting from the highest baudrate fiting in the | ||||
|     # step 1: create an ordered list of modes based on baudrate | ||||
|     baudrate_to_explore = list(set([this_mode['baud_rate'] | ||||
|     # step 1: create an ordered list of modes based on baudrate and power offset | ||||
|     # order higher baudrate with higher power offset first | ||||
|     baudrate_offset_to_explore = list(set([(this_mode['baud_rate'], this_mode['equalization_offset_db']) | ||||
|                                            for this_mode in equipment['Transceiver'][req.tsp].mode | ||||
|                                            if float(this_mode['min_spacing']) <= req.spacing])) | ||||
|     # TODO be carefull on limits cases if spacing very close to req spacing eg 50.001 50.000 | ||||
|     baudrate_to_explore = sorted(baudrate_to_explore, reverse=True) | ||||
|     if baudrate_to_explore: | ||||
|     baudrate_offset_to_explore = sorted(baudrate_offset_to_explore, reverse=True) | ||||
|     if baudrate_offset_to_explore: | ||||
|         # at least 1 baudrate can be tested wrt spacing | ||||
|         for this_br in baudrate_to_explore: | ||||
|         for (this_br, this_offset) in baudrate_offset_to_explore: | ||||
|             modes_to_explore = [this_mode for this_mode in equipment['Transceiver'][req.tsp].mode | ||||
|                                 if this_mode['baud_rate'] == this_br and | ||||
|                                 float(this_mode['min_spacing']) <= req.spacing] | ||||
|                                 if this_mode['baud_rate'] == this_br | ||||
|                                 and float(this_mode['min_spacing']) <= req.spacing] | ||||
|             modes_to_explore = sorted(modes_to_explore, | ||||
|                                       key=lambda x: x['bit_rate'], reverse=True) | ||||
|                                       key=lambda x: (x['bit_rate'], x['equalization_offset_db']), reverse=True) | ||||
|             # step2: computes propagation for each baudrate: stop and select the first that passes | ||||
|             # TODO: the case of roll off is not included: for now use SI one | ||||
|             # TODO: if the loop in mode optimization does not have a feasible path, then bugs | ||||
| @@ -401,6 +391,7 @@ def propagate_and_optimize_mode(path, req, equipment): | ||||
|             spc_info = create_input_spectral_information(f_min=req.f_min, f_max=req.f_max, | ||||
|                                                          roll_off=equipment['SI']['default'].roll_off, | ||||
|                                                          baud_rate=this_br, power=req.power, spacing=req.spacing, | ||||
|                                                          delta_pdb=this_offset, | ||||
|                                                          tx_osnr=req.tx_osnr, ref_carrier=ref_carrier(equipment)) | ||||
|             for i, el in enumerate(path): | ||||
|                 if isinstance(el, Roadm): | ||||
| @@ -428,22 +419,19 @@ def propagate_and_optimize_mode(path, req, equipment): | ||||
|  | ||||
|         # returns the last propagated path and mode | ||||
|         msg = f'\tWarning! Request {req.request_id}: no mode satisfies path SNR requirement.\n' | ||||
|         print(msg) | ||||
|         LOGGER.info(msg) | ||||
|         LOGGER.warning(msg) | ||||
|         req.blocking_reason = 'NO_FEASIBLE_MODE' | ||||
|         return path, last_explored_mode | ||||
|     else: | ||||
|         # no baudrate satisfying spacing | ||||
|         msg = f'\tWarning! Request {req.request_id}: no baudrate satisfies spacing requirement.\n' | ||||
|         print(msg) | ||||
|         LOGGER.info(msg) | ||||
|         LOGGER.warning(msg) | ||||
|         req.blocking_reason = 'NO_FEASIBLE_BAUDRATE_WITH_SPACING' | ||||
|         return [], None | ||||
|  | ||||
|  | ||||
| def jsontopath_metric(path_metric): | ||||
|     """ a functions that reads resulting metric  from json string | ||||
|     """ | ||||
|     """a functions that reads resulting metric  from json string""" | ||||
|     output_snr = next(e['accumulative-value'] | ||||
|                       for e in path_metric if e['metric-type'] == 'SNR-0.1nm') | ||||
|     output_snrbandwidth = next(e['accumulative-value'] | ||||
| @@ -461,9 +449,7 @@ def jsontopath_metric(path_metric): | ||||
|  | ||||
|  | ||||
| def jsontoparams(my_p, tsp, mode, equipment): | ||||
|     """ a function that derives optical params from transponder type and mode | ||||
|         supports the no mode case | ||||
|     """ | ||||
|     """a function that derives optical params from transponder type and mode supports the no mode case""" | ||||
|     temp = [] | ||||
|     for elem in my_p['path-properties']['path-route-objects']: | ||||
|         if 'num-unnum-hop' in elem['path-route-object']: | ||||
| @@ -473,8 +459,8 @@ def jsontoparams(my_p, tsp, mode, equipment): | ||||
|     temp2 = [] | ||||
|     for elem in my_p['path-properties']['path-route-objects']: | ||||
|         if 'label-hop' in elem['path-route-object'].keys(): | ||||
|             temp2.append(f'{elem["path-route-object"]["label-hop"]["N"]}, ' + | ||||
|                          f'{elem["path-route-object"]["label-hop"]["M"]}') | ||||
|             temp2.append(f'{[e["N"] for e in elem["path-route-object"]["label-hop"]]}, ' | ||||
|                          + f'{[e["M"] for e in elem["path-route-object"]["label-hop"]]}') | ||||
|     # OrderedDict.fromkeys returns the unique set of strings. | ||||
|     # TODO: if spectrum changes along the path, we should be able to give the segments | ||||
|     #       eg for regeneration case | ||||
| @@ -498,7 +484,7 @@ def jsontoparams(my_p, tsp, mode, equipment): | ||||
|  | ||||
|  | ||||
| def jsontocsv(json_data, equipment, fileout): | ||||
|     """ reads json path result file in accordance with: | ||||
|     """reads json path result file in accordance with: | ||||
|     Yang model for requesting Path Computation | ||||
|     draft-ietf-teas-yang-path-computation-01.txt. | ||||
|     and write results in an CSV file | ||||
| @@ -836,13 +822,13 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list): | ||||
|                     if not ispart(allpaths[id(pth)].req.nodes_list, pth): | ||||
|                         testispartok = False | ||||
|                         if 'STRICT' in allpaths[id(pth)].req.loose_list: | ||||
|                             LOGGER.info(f'removing solution from candidate paths\n{pth}') | ||||
|                             LOGGER.debug(f'removing solution from candidate paths\n{pth}') | ||||
|                             testispartnokloose = False | ||||
|                             break | ||||
|             if testispartok: | ||||
|                 temp.append(sol) | ||||
|             elif testispartnokloose: | ||||
|                 LOGGER.info(f'Adding solution as alternate solution not satisfying constraint\n{pth}') | ||||
|                 LOGGER.debug(f'Adding solution as alternate solution not satisfying constraint\n{pth}') | ||||
|                 alternatetemp.append(sol) | ||||
|         if temp: | ||||
|             candidates[this_d.disjunction_id] = temp | ||||
| @@ -864,9 +850,7 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list): | ||||
|                     # remove duplicated candidates | ||||
|                     candidates = remove_candidate(candidates, allpaths, allpaths[id(pth)].req, pth) | ||||
|         else: | ||||
|             msg = f'No disjoint path found with added constraint' | ||||
|             LOGGER.critical(msg) | ||||
|             print(f'{msg}\nComputation stopped.') | ||||
|             msg = 'No disjoint path found with added constraint\nComputation stopped.' | ||||
|             # TODO in this case: replay step 5  with the candidate without constraints | ||||
|             raise DisjunctionError(msg) | ||||
|  | ||||
| @@ -887,8 +871,7 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list): | ||||
|  | ||||
|  | ||||
| def isdisjoint(pth1, pth2): | ||||
|     """ returns 0 if disjoint | ||||
|     """ | ||||
|     """returns 0 if disjoint""" | ||||
|     edge1 = list(pairwise(pth1)) | ||||
|     edge2 = list(pairwise(pth2)) | ||||
|     for edge in edge1: | ||||
| @@ -898,7 +881,7 @@ def isdisjoint(pth1, pth2): | ||||
|  | ||||
|  | ||||
| def find_reversed_path(pth): | ||||
|     """ select of intermediate roadms and find the path between them | ||||
|     """select of intermediate roadms and find the path between them | ||||
|     note that this function may not give an exact result in case of multiple | ||||
|     links between two adjacent nodes. | ||||
|     """ | ||||
| @@ -923,9 +906,8 @@ def find_reversed_path(pth): | ||||
|             # concatenation should be [roadma el1 el2 roadmb el3 el4 roadmc] | ||||
|             reversed_path = list(OrderedDict.fromkeys(reversed_path)) | ||||
|         else: | ||||
|             msg = f'Error while handling reversed path {pth[-1].uid} to {pth[0].uid}:' +\ | ||||
|                 ' can not handle unidir topology. TO DO.' | ||||
|             LOGGER.critical(msg) | ||||
|             msg = f'Error while handling reversed path {pth[-1].uid} to {pth[0].uid}:' \ | ||||
|                 + ' can not handle unidir topology. TO DO.' | ||||
|             raise ValueError(msg) | ||||
|     reversed_path.append(pth[0]) | ||||
|  | ||||
| @@ -933,9 +915,7 @@ def find_reversed_path(pth): | ||||
|  | ||||
|  | ||||
| def ispart(ptha, pthb): | ||||
|     """ the functions takes two paths a and b and retrns True | ||||
|         if all a elements are part of b and in the same order | ||||
|     """ | ||||
|     """the functions takes two paths a and b and retrns True if all a elements are part of b and in the same order""" | ||||
|     j = 0 | ||||
|     for elem in ptha: | ||||
|         if elem in pthb: | ||||
| @@ -949,8 +929,7 @@ def ispart(ptha, pthb): | ||||
|  | ||||
|  | ||||
| def remove_candidate(candidates, allpaths, rqst, pth): | ||||
|     """ filter duplicate candidates | ||||
|     """ | ||||
|     """filter duplicate candidates""" | ||||
|     # print(f'coucou {rqst.request_id}') | ||||
|     for key, candidate in candidates.items(): | ||||
|         temp = candidate.copy() | ||||
| @@ -965,8 +944,7 @@ def remove_candidate(candidates, allpaths, rqst, pth): | ||||
|  | ||||
|  | ||||
| def compare_reqs(req1, req2, disjlist): | ||||
|     """ compare two requests: returns True or False | ||||
|     """ | ||||
|     """compare two requests: returns True or False""" | ||||
|     dis1 = [d for d in disjlist if req1.request_id in d.disjunctions_req] | ||||
|     dis2 = [d for d in disjlist if req2.request_id in d.disjunctions_req] | ||||
|     same_disj = False | ||||
| @@ -999,28 +977,31 @@ def compare_reqs(req1, req2, disjlist): | ||||
|             req1.format == req2.format and \ | ||||
|             req1.OSNR == req2.OSNR and \ | ||||
|             req1.roll_off == req2.roll_off and \ | ||||
|             same_disj and \ | ||||
|             getattr(req1, 'N', None) is None and getattr(req2, 'N', None) is None and \ | ||||
|             getattr(req1, 'M', None) is None and getattr(req2, 'M', None) is None: | ||||
|             same_disj: | ||||
|         return True | ||||
|     else: | ||||
|         return False | ||||
|  | ||||
|  | ||||
| def requests_aggregation(pathreqlist, disjlist): | ||||
|     """ this function aggregates requests so that if several requests | ||||
|     """this function aggregates requests so that if several requests | ||||
|     exist between same source and destination and with same transponder type | ||||
|     If transponder mode is defined and identical, then also agregates demands. | ||||
|     """ | ||||
|     # todo maybe add conditions on mode ??, spacing ... | ||||
|     # currently if undefined takes the default values | ||||
|     local_list = pathreqlist.copy() | ||||
|     for req in pathreqlist: | ||||
|         for this_r in local_list: | ||||
|             if req.request_id != this_r.request_id and compare_reqs(req, this_r, disjlist): | ||||
|             if req.request_id != this_r.request_id and compare_reqs(req, this_r, disjlist) and\ | ||||
|                     this_r.tsp_mode is not None: | ||||
|                 # aggregate | ||||
|                 this_r.path_bandwidth += req.path_bandwidth | ||||
|                 this_r.N = this_r.N + req.N | ||||
|                 this_r.M = this_r.M + req.M | ||||
|                 temp_r_id = this_r.request_id | ||||
|                 this_r.request_id = ' | '.join((this_r.request_id, req.request_id)) | ||||
|  | ||||
|                 # remove request from list | ||||
|                 local_list.remove(req) | ||||
|                 # todo change also disjunction req with new demand | ||||
| @@ -1037,7 +1018,8 @@ def requests_aggregation(pathreqlist, disjlist): | ||||
|  | ||||
|  | ||||
| def correct_json_route_list(network, pathreqlist): | ||||
|     """ all names in list should be exact name in the network, and there is no ambiguity | ||||
|     """all names in list should be exact name in the network, and there is no ambiguity | ||||
|  | ||||
|     This function only checks that list is correct, warns user if the name is incorrect and | ||||
|     suppresses the constraint it it is loose or raises an error if it is strict | ||||
|     """ | ||||
| @@ -1045,15 +1027,13 @@ def correct_json_route_list(network, pathreqlist): | ||||
|     transponders = [n.uid for n in network.nodes() if isinstance(n, Transceiver)] | ||||
|     for pathreq in pathreqlist: | ||||
|         if pathreq.source not in transponders: | ||||
|             msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find transponder' +\ | ||||
|                 f' source : {pathreq.source}.{ansi_escapes.reset}' | ||||
|             LOGGER.critical(msg) | ||||
|             msg = f'Request: {pathreq.request_id}: could not find transponder' \ | ||||
|                 + f' source : {pathreq.source}.' | ||||
|             raise ServiceError(msg) | ||||
|  | ||||
|         if pathreq.destination not in transponders: | ||||
|             msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find transponder' +\ | ||||
|                 f' destination : {pathreq.destination}.{ansi_escapes.reset}' | ||||
|             LOGGER.critical(msg) | ||||
|             msg = f'Request: {pathreq.request_id}: could not find transponder' \ | ||||
|                 + f' destination : {pathreq.destination}.' | ||||
|             raise ServiceError(msg) | ||||
|  | ||||
|         # silently remove source and dest nodes from the list | ||||
| @@ -1072,24 +1052,21 @@ def correct_json_route_list(network, pathreqlist): | ||||
|                     # if no matching can be found in the network just ignore this constraint | ||||
|                     # if it is a loose constraint | ||||
|                     # warns the user that this node is not part of the topology | ||||
|                     msg = f'{ansi_escapes.yellow}invalid route node specified:\n\t\'{n_id}\',' +\ | ||||
|                         f' could not use it as constraint, skipped!{ansi_escapes.reset}' | ||||
|                     print(msg) | ||||
|                     LOGGER.info(msg) | ||||
|                     msg = f'invalid route node specified:\n\t\'{n_id}\',' \ | ||||
|                         + ' could not use it as constraint, skipped!' | ||||
|                     LOGGER.warning(msg) | ||||
|                     pathreq.loose_list.pop(pathreq.nodes_list.index(n_id)) | ||||
|                     pathreq.nodes_list.remove(n_id) | ||||
|                 else: | ||||
|                     msg = f'{ansi_escapes.red}could not find node:\n\t \'{n_id}\' in network' +\ | ||||
|                         f' topology. Strict constraint can not be applied.{ansi_escapes.reset}' | ||||
|                     LOGGER.critical(msg) | ||||
|                     msg = f'could not find node:\n\t \'{n_id}\' in network' \ | ||||
|                         + ' topology. Strict constraint can not be applied.' | ||||
|                     raise ServiceError(msg) | ||||
|  | ||||
|     return pathreqlist | ||||
|  | ||||
|  | ||||
| def deduplicate_disjunctions(disjn): | ||||
|     """ clean disjunctions to remove possible repetition | ||||
|     """ | ||||
|     """clean disjunctions to remove possible repetition""" | ||||
|     local_disjn = disjn.copy() | ||||
|     for elem in local_disjn: | ||||
|         for dis_elem in local_disjn: | ||||
| @@ -1100,7 +1077,8 @@ def deduplicate_disjunctions(disjn): | ||||
|  | ||||
|  | ||||
| def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist): | ||||
|     """ use a list but a dictionnary might be helpful to find path based on request_id | ||||
|     """use a list but a dictionnary might be helpful to find path based on request_id | ||||
|  | ||||
|     TODO change all these req, dsjct, res lists into dict ! | ||||
|     """ | ||||
|     path_res_list = [] | ||||
| @@ -1112,10 +1090,10 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist): | ||||
|         # use the power specified in requests but might be different from the one | ||||
|         # specified for design the power is an optional parameter for requests | ||||
|         # definition if optional, use the one defines in eqt_config.json | ||||
|         print(f'request {pathreq.request_id}') | ||||
|         print(f'Computing path from {pathreq.source} to {pathreq.destination}') | ||||
|         # adding first node to be clearer on the output | ||||
|         print(f'with path constraint: {[pathreq.source] + pathreq.nodes_list}') | ||||
|         msg = f'\n\trequest {pathreq.request_id}\n' \ | ||||
|               + f'\tComputing path from {pathreq.source} to {pathreq.destination}\n' \ | ||||
|               + f'\twith path constraint: {[pathreq.source] + pathreq.nodes_list}' | ||||
|         # # adding first node to be clearer on the output | ||||
|  | ||||
|         # pathlist[i] contains the whole path information for request i | ||||
|         # last element is a transciver and where the result of the propagation is | ||||
| @@ -1125,7 +1103,8 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist): | ||||
|         # may use the same transponder for the performance simulation. This is why | ||||
|         # we use deepcopy: to ensure that each propagation is recorded and not overwritten | ||||
|         total_path = deepcopy(pathlist[i]) | ||||
|         print(f'Computed path (roadms):{[e.uid for e in total_path  if isinstance(e, Roadm)]}') | ||||
|         msg = msg + f'\n\tComputed path (roadms):{[e.uid for e in total_path  if isinstance(e, Roadm)]}' | ||||
|         LOGGER.info(msg) | ||||
|         # for debug | ||||
|         # print(f'{pathreq.baud_rate}   {pathreq.power}   {pathreq.spacing}   {pathreq.nb_channel}') | ||||
|         if total_path: | ||||
| @@ -1136,14 +1115,12 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist): | ||||
|                 snr01nm_with_penalty = total_path[-1].snr_01nm - total_path[-1].total_penalty | ||||
|                 min_ind = argmin(snr01nm_with_penalty) | ||||
|                 if round(snr01nm_with_penalty[min_ind], 2) < pathreq.OSNR + equipment['SI']['default'].sys_margins: | ||||
|                     msg = f'\tWarning! Request {pathreq.request_id} computed path from' +\ | ||||
|                           f' {pathreq.source} to {pathreq.destination} does not pass with {pathreq.tsp_mode}' +\ | ||||
|                           f'\n\tcomputed SNR in 0.1nm = {round(total_path[-1].snr_01nm[min_ind], 2)}' +\ | ||||
|                           f'\n\tCD penalty = {round(total_path[-1].penalties["chromatic_dispersion"][min_ind], 2)}' +\ | ||||
|                           f'\n\tPMD penalty = {round(total_path[-1].penalties["pmd"][min_ind], 2)}' +\ | ||||
|                           f'\n\trequired osnr = {pathreq.OSNR}' +\ | ||||
|                           f'\n\tsystem margin = {equipment["SI"]["default"].sys_margins}' | ||||
|                     print(msg) | ||||
|                     msg = f'\tWarning! Request {pathreq.request_id} computed path from' \ | ||||
|                           + f' {pathreq.source} to {pathreq.destination} does not pass with {pathreq.tsp_mode}' \ | ||||
|                           + f'\n\tcomputed SNR in 0.1nm = {round(total_path[-1].snr_01nm[min_ind], 2)}' | ||||
|                     msg = _penalty_msg(total_path, msg, min_ind) \ | ||||
|                         + f'\n\trequired osnr = {pathreq.OSNR}' \ | ||||
|                         + f'\n\tsystem margin = {equipment["SI"]["default"].sys_margins}' | ||||
|                     LOGGER.warning(msg) | ||||
|                     pathreq.blocking_reason = 'MODE_NOT_FEASIBLE' | ||||
|             else: | ||||
| @@ -1179,22 +1156,20 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist): | ||||
|             if pathreq.bidir and pathreq.baud_rate is not None: | ||||
|                 # Both directions requested, and a feasible mode was found | ||||
|                 rev_p = deepcopy(reversed_path) | ||||
|  | ||||
|                 print(f'\n\tPropagating Z to A direction {pathreq.destination} to {pathreq.source}') | ||||
|                 print(f'\tPath (roadsm) {[r.uid for r in rev_p if isinstance(r,Roadm)]}\n') | ||||
|                 msg = f'\n\tPropagating Z to A direction {pathreq.destination} to {pathreq.source}\n' \ | ||||
|                       + f'\tPath (roadms) {[r.uid for r in rev_p if isinstance(r,Roadm)]}\n' | ||||
|                 LOGGER.info(msg) | ||||
|                 propagate(rev_p, pathreq, equipment) | ||||
|                 propagated_reversed_path = rev_p | ||||
|                 snr01nm_with_penalty = rev_p[-1].snr_01nm - rev_p[-1].total_penalty | ||||
|                 min_ind = argmin(snr01nm_with_penalty) | ||||
|                 if round(snr01nm_with_penalty[min_ind], 2) < pathreq.OSNR + equipment['SI']['default'].sys_margins: | ||||
|                     msg = f'\tWarning! Request {pathreq.request_id} computed path from' +\ | ||||
|                           f' {pathreq.source} to {pathreq.destination} does not pass with {pathreq.tsp_mode}' +\ | ||||
|                           f'\n\tcomputed SNR in 0.1nm = {round(rev_p[-1].snr_01nm[min_ind], 2)}' +\ | ||||
|                           f'\n\tCD penalty = {round(rev_p[-1].penalties["chromatic_dispersion"][min_ind], 2)}' +\ | ||||
|                           f'\n\tPMD penalty = {round(rev_p[-1].penalties["pmd"][min_ind], 2)}' +\ | ||||
|                           f'\n\trequired osnr = {pathreq.OSNR}' +\ | ||||
|                           f'\n\tsystem margin = {equipment["SI"]["default"].sys_margins}' | ||||
|                     print(msg) | ||||
|                     msg = f'\tWarning! Request {pathreq.request_id} computed path from' \ | ||||
|                           + f' {pathreq.destination} to {pathreq.source} does not pass with {pathreq.tsp_mode}' \ | ||||
|                           + f'\n\tcomputed SNR in 0.1nm = {round(rev_p[-1].snr_01nm[min_ind], 2)}' | ||||
|                     msg = _penalty_msg(rev_p, msg, min_ind) \ | ||||
|                         + f'\n\trequired osnr = {pathreq.OSNR}' \ | ||||
|                         + f'\n\tsystem margin = {equipment["SI"]["default"].sys_margins}' | ||||
|                     LOGGER.warning(msg) | ||||
|                     # TODO selection of mode should also be on reversed direction !! | ||||
|                     if not hasattr(pathreq, 'blocking_reason'): | ||||
| @@ -1202,9 +1177,8 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist): | ||||
|             else: | ||||
|                 propagated_reversed_path = [] | ||||
|         else: | ||||
|             msg = 'Total path is empty. No propagation' | ||||
|             print(msg) | ||||
|             LOGGER.info(msg) | ||||
|             msg = f'Request {pathreq.request_id}: Total path is empty. No propagation' | ||||
|             LOGGER.warning(msg) | ||||
|             reversed_path = [] | ||||
|             propagated_reversed_path = [] | ||||
|  | ||||
| @@ -1212,12 +1186,12 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist): | ||||
|         reversed_path_res_list.append(reversed_path) | ||||
|         propagated_reversed_path_res_list.append(propagated_reversed_path) | ||||
|         # print to have a nice output | ||||
|         print('') | ||||
|     return path_res_list, reversed_path_res_list, propagated_reversed_path_res_list | ||||
|  | ||||
|  | ||||
| def compute_spectrum_slot_vs_bandwidth(bandwidth, spacing, bit_rate, slot_width=0.0125e12): | ||||
|     """ Compute the number of required wavelengths and the M value (number of consumed slots) | ||||
|     """Compute the number of required wavelengths and the M value (number of consumed slots) | ||||
|  | ||||
|     Each wavelength consumes one `spacing`, and the result is rounded up to consume a natural number of slots. | ||||
|  | ||||
|     >>> compute_spectrum_slot_vs_bandwidth(400e9, 50e9, 200e9) | ||||
| @@ -1226,3 +1200,19 @@ def compute_spectrum_slot_vs_bandwidth(bandwidth, spacing, bit_rate, slot_width= | ||||
|     number_of_wavelengths = ceil(bandwidth / bit_rate) | ||||
|     total_number_of_slots = ceil(spacing / slot_width) * number_of_wavelengths | ||||
|     return number_of_wavelengths, total_number_of_slots | ||||
|  | ||||
|  | ||||
| def _penalty_msg(total_path, msg, min_ind): | ||||
|     """formatting helper for reporting unfeasible paths | ||||
|  | ||||
|     The penalty info are optional, so this checks that penalty exists before creating a message.""" | ||||
|     penalty_dict = { | ||||
|         'pdl': 'PDL', | ||||
|         'chromatic_dispersion': 'CD', | ||||
|         'pmd': 'PMD'} | ||||
|     for key, pretty in penalty_dict.items(): | ||||
|         if key in total_path[-1].penalties: | ||||
|             msg += f'\n\t{pretty} penalty = {round(total_path[-1].penalties[key][min_ind], 2)}' | ||||
|         else: | ||||
|             msg += f'\n\t{pretty} penalty not evaluated' | ||||
|     return msg | ||||
|   | ||||
| @@ -17,14 +17,14 @@ from collections import namedtuple | ||||
| from logging import getLogger | ||||
| from gnpy.core.elements import Roadm, Transceiver | ||||
| from gnpy.core.exceptions import ServiceError, SpectrumError | ||||
| from gnpy.core.utils import order_slots, restore_order | ||||
| from gnpy.topology.request import compute_spectrum_slot_vs_bandwidth | ||||
|  | ||||
| LOGGER = getLogger(__name__) | ||||
|  | ||||
|  | ||||
| class Bitmap: | ||||
|     """ records the spectrum occupation | ||||
|     """ | ||||
|     """records the spectrum occupation""" | ||||
|  | ||||
|     def __init__(self, f_min, f_max, grid, guardband=0.15e12, bitmap=None): | ||||
|         # n is the min index including guardband. Guardband is require to be sure | ||||
| @@ -45,26 +45,22 @@ class Bitmap: | ||||
|             raise SpectrumError(f'bitmap is not consistant with f_min{f_min} - n: {n_min} and f_max{f_max}- n :{n_max}') | ||||
|  | ||||
|     def getn(self, i): | ||||
|         """ converts the n (itu grid) into a local index | ||||
|         """ | ||||
|         """converts the n (itu grid) into a local index""" | ||||
|         return self.freq_index[i] | ||||
|  | ||||
|     def geti(self, nvalue): | ||||
|         """ converts the local index into n (itu grid) | ||||
|         """ | ||||
|         """converts the local index into n (itu grid)""" | ||||
|         return self.freq_index.index(nvalue) | ||||
|  | ||||
|     def insert_left(self, newbitmap): | ||||
|         """ insert bitmap on the left to align oms bitmaps if their start frequencies are different | ||||
|         """ | ||||
|         """insert bitmap on the left to align oms bitmaps if their start frequencies are different""" | ||||
|         self.bitmap = newbitmap + self.bitmap | ||||
|         temp = list(range(self.n_min - len(newbitmap), self.n_min)) | ||||
|         self.freq_index = temp + self.freq_index | ||||
|         self.n_min = self.freq_index[0] | ||||
|  | ||||
|     def insert_right(self, newbitmap): | ||||
|         """ insert bitmap on the right to align oms bitmaps if their stop frequencies are different | ||||
|         """ | ||||
|         """insert bitmap on the right to align oms bitmaps if their stop frequencies are different""" | ||||
|         self.bitmap = self.bitmap + newbitmap | ||||
|         self.freq_index = self.freq_index + list(range(self.n_max, self.n_max + len(newbitmap))) | ||||
|         self.n_max = self.freq_index[-1] | ||||
| @@ -75,7 +71,7 @@ OMSParams = namedtuple('OMSParams', 'oms_id el_id_list el_list') | ||||
|  | ||||
|  | ||||
| class OMS: | ||||
|     """ OMS class is the logical container that represent a link between two adjacent ROADMs and | ||||
|     """OMS class is the logical container that represent a link between two adjacent ROADMs and | ||||
|     records the crossed elements and the occupied spectrum | ||||
|     """ | ||||
|  | ||||
| @@ -98,36 +94,28 @@ class OMS: | ||||
|                             f'{self.el_id_list[0]} - {self.el_id_list[-1]}', '\n']) | ||||
|  | ||||
|     def add_element(self, elem): | ||||
|         """ records oms elements | ||||
|         """ | ||||
|         """records oms elements""" | ||||
|         self.el_id_list.append(elem.uid) | ||||
|         self.el_list.append(elem) | ||||
|  | ||||
|     def update_spectrum(self, f_min, f_max, guardband=0.15e12, existing_spectrum=None, | ||||
|                         grid=0.00625e12): | ||||
|         """ frequencies expressed in Hz | ||||
|     def update_spectrum(self, f_min, f_max, guardband=0.15e12, existing_spectrum=None, grid=0.00625e12): | ||||
|         """Frequencies expressed in Hz. | ||||
|         Add 150 GHz margin to enable a center channel on f_min | ||||
|         Use ITU-T G694.1 Flexible DWDM grid definition | ||||
|         For the flexible DWDM grid, the allowed frequency slots have a nominal central frequency (in 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 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 GHz. | ||||
|         Any combination of frequency slots is allowed as long as no two frequency slots overlap. | ||||
|         If bitmap is not None, then use it: Bitmap checks its consistency with f_min f_max | ||||
|         else a brand new bitmap is created | ||||
|         """ | ||||
|         if existing_spectrum is None: | ||||
|             # add some 150 GHz margin to enable a center channel on f_min | ||||
|             # use ITU-T G694.1 | ||||
|             # Flexible DWDM grid definition | ||||
|             # For the flexible DWDM grid, the allowed frequency slots have a nominal | ||||
|             # central frequency (in 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 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 | ||||
|             # GHz. | ||||
|             # Any combination of frequency slots is allowed as long as no two frequency | ||||
|             # slots overlap. | ||||
|  | ||||
|             # TODO : add explaination on that / parametrize .... | ||||
|             self.spectrum_bitmap = Bitmap(f_min, f_max, grid, guardband) | ||||
|             # print(len(self.spectrum_bitmap.bitmap)) | ||||
|         self.spectrum_bitmap = Bitmap(f_min=f_min, f_max=f_max, grid=grid, guardband=guardband, | ||||
|                                       bitmap=existing_spectrum) | ||||
|  | ||||
|     def assign_spectrum(self, nvalue, mvalue): | ||||
|         """ change oms spectrum to mark spectrum assigned | ||||
|         """ | ||||
|         """change oms spectrum to mark spectrum assigned""" | ||||
|         if not isinstance(nvalue, int): | ||||
|             raise SpectrumError(f'N must be a signed integer, got {nvalue}') | ||||
|         if not isinstance(mvalue, int): | ||||
| @@ -146,14 +134,14 @@ class OMS: | ||||
|         self.spectrum_bitmap.bitmap[self.spectrum_bitmap.geti(startn):self.spectrum_bitmap.geti(stopn) + 1] = [0] * (stopn - startn + 1) | ||||
|  | ||||
|     def add_service(self, service_id, nb_wl): | ||||
|         """ record service and mark spectrum as occupied | ||||
|         """ | ||||
|         """record service and mark spectrum as occupied""" | ||||
|         self.service_list.append(service_id) | ||||
|         self.nb_channels += nb_wl | ||||
|  | ||||
|  | ||||
| def frequency_to_n(freq, grid=0.00625e12): | ||||
|     """ converts frequency into the n value (ITU grid) | ||||
|     """converts frequency into the n value (ITU grid) | ||||
|  | ||||
|     reference to Recommendation G.694.1 (02/12), Figure I.3 | ||||
|     https://www.itu.int/rec/T-REC-G.694.1-201202-I/en | ||||
|  | ||||
| @@ -167,7 +155,8 @@ def frequency_to_n(freq, grid=0.00625e12): | ||||
|  | ||||
|  | ||||
| def nvalue_to_frequency(nvalue, grid=0.00625e12): | ||||
|     """ converts n value into a frequency | ||||
|     """converts n value into a frequency | ||||
|  | ||||
|     reference to Recommendation G.694.1 (02/12), Table 1 | ||||
|     https://www.itu.int/rec/T-REC-G.694.1-201202-I/en | ||||
|  | ||||
| @@ -181,15 +170,15 @@ def nvalue_to_frequency(nvalue, grid=0.00625e12): | ||||
|  | ||||
|  | ||||
| def mvalue_to_slots(nvalue, mvalue): | ||||
|     """ convert center n an m into start and stop n | ||||
|     """ | ||||
|     """convert center n an m into start and stop n""" | ||||
|     startn = nvalue - mvalue | ||||
|     stopn = nvalue + mvalue - 1 | ||||
|     return startn, stopn | ||||
|  | ||||
|  | ||||
| def slots_to_m(startn, stopn): | ||||
|     """ converts the start and stop n values to the center n and m value | ||||
|     """converts the start and stop n values to the center n and m value | ||||
|  | ||||
|     reference to Recommendation G.694.1 (02/12), Figure I.3 | ||||
|     https://www.itu.int/rec/T-REC-G.694.1-201202-I/en | ||||
|  | ||||
| @@ -206,7 +195,8 @@ def slots_to_m(startn, stopn): | ||||
|  | ||||
|  | ||||
| def m_to_freq(nvalue, mvalue, grid=0.00625e12): | ||||
|     """ converts m into frequency range | ||||
|     """converts m into frequency range | ||||
|  | ||||
|     spectrum(13,7) is (193137500000000.0, 193225000000000.0) | ||||
|     reference to Recommendation G.694.1 (02/12), Figure I.3 | ||||
|     https://www.itu.int/rec/T-REC-G.694.1-201202-I/en | ||||
| @@ -225,9 +215,7 @@ def m_to_freq(nvalue, mvalue, grid=0.00625e12): | ||||
|  | ||||
|  | ||||
| def align_grids(oms_list): | ||||
|     """ used to apply same grid to all oms : same starting n, stop n and slot size | ||||
|         out of grid slots are set to 0 | ||||
|     """ | ||||
|     """Used to apply same grid to all oms : same starting n, stop n and slot size. Out of grid slots are set to 0.""" | ||||
|     n_min = min([o.spectrum_bitmap.n_min for o in oms_list]) | ||||
|     n_max = max([o.spectrum_bitmap.n_max for o in oms_list]) | ||||
|     for this_o in oms_list: | ||||
| @@ -239,7 +227,8 @@ def align_grids(oms_list): | ||||
|  | ||||
|  | ||||
| def build_oms_list(network, equipment): | ||||
|     """ initialization of OMS list in the network | ||||
|     """initialization of OMS list in the network | ||||
|  | ||||
|     an oms is build reading all intermediate nodes between two adjacent ROADMs | ||||
|     each element within the list is being added an oms and oms_id to record the | ||||
|     oms it belongs to. | ||||
| @@ -296,7 +285,8 @@ def build_oms_list(network, equipment): | ||||
|  | ||||
|  | ||||
| def reversed_oms(oms_list): | ||||
|     """ identifies reversed OMS | ||||
|     """identifies reversed OMS | ||||
|  | ||||
|     only applicable for non parallel OMS | ||||
|     """ | ||||
|     for oms in oms_list: | ||||
| @@ -322,28 +312,41 @@ def bitmap_sum(band1, band2): | ||||
|     return res | ||||
|  | ||||
|  | ||||
| def spectrum_selection(pth, oms_list, requested_m, requested_n=None): | ||||
|     """Collects spectrum availability and call the select_candidate function""" | ||||
|  | ||||
|     # use indexes instead of ITU-T n values | ||||
| def build_path_oms_id_list(pth): | ||||
|     path_oms = [] | ||||
|     for elem in pth: | ||||
|         if not isinstance(elem, Roadm) and not isinstance(elem, Transceiver): | ||||
|             # only edfa, fused and fibers have oms_id attribute | ||||
|             path_oms.append(elem.oms_id) | ||||
|     # remove duplicate oms_id, order is not important | ||||
|     path_oms = list(set(path_oms)) | ||||
|     # assuming all oms have same freq index | ||||
|     if not path_oms: | ||||
|         candidate = (None, None, None) | ||||
|         return candidate, path_oms | ||||
|     freq_index = oms_list[path_oms[0]].spectrum_bitmap.freq_index | ||||
|     freq_index_min = oms_list[path_oms[0]].spectrum_bitmap.freq_index_min | ||||
|     freq_index_max = oms_list[path_oms[0]].spectrum_bitmap.freq_index_max | ||||
|     return list(set(path_oms)) | ||||
|  | ||||
|     freq_availability = oms_list[path_oms[0]].spectrum_bitmap.bitmap | ||||
|  | ||||
| def aggregate_oms_bitmap(path_oms, oms_list): | ||||
|     spectrum = oms_list[path_oms[0]].spectrum_bitmap | ||||
|     bitmap = spectrum.bitmap | ||||
|     # assuming all oms have same freq indices | ||||
|     for oms in path_oms[1:]: | ||||
|         freq_availability = bitmap_sum(oms_list[oms].spectrum_bitmap.bitmap, freq_availability) | ||||
|         bitmap = bitmap_sum(oms_list[oms].spectrum_bitmap.bitmap, bitmap) | ||||
|     params = { | ||||
|         'oms_id': 0, | ||||
|         'el_id_list': 0, | ||||
|         'el_list': [] | ||||
|     } | ||||
|     freq_min = nvalue_to_frequency(spectrum.freq_index_min) | ||||
|     freq_max = nvalue_to_frequency(spectrum.freq_index_max) | ||||
|     aggregate_oms = OMS(**params) | ||||
|     aggregate_oms.update_spectrum(freq_min, freq_max, grid=0.00625e12, existing_spectrum=bitmap) | ||||
|     return aggregate_oms | ||||
|  | ||||
|  | ||||
| def spectrum_selection(test_oms, requested_m, requested_n=None): | ||||
|     """Collects spectrum availability and call the select_candidate function""" | ||||
|     freq_index = test_oms.spectrum_bitmap.freq_index | ||||
|     freq_index_min = test_oms.spectrum_bitmap.freq_index_min | ||||
|     freq_index_max = test_oms.spectrum_bitmap.freq_index_max | ||||
|     freq_availability = test_oms.spectrum_bitmap.bitmap | ||||
|  | ||||
|     if requested_n is None: | ||||
|         # avoid slots reserved on the edge 0.15e-12 on both sides -> 24 | ||||
|         candidates = [(freq_index[i] + requested_m, freq_index[i], freq_index[i] + 2 * requested_m - 1) | ||||
| @@ -354,23 +357,36 @@ def spectrum_selection(pth, oms_list, requested_m, requested_n=None): | ||||
|  | ||||
|         candidate = select_candidate(candidates, policy='first_fit') | ||||
|     else: | ||||
|         i = oms_list[path_oms[0]].spectrum_bitmap.geti(requested_n) | ||||
|         # print(f'N {requested_n} i {i}') | ||||
|         # print(freq_availability[i-m:i+m] ) | ||||
|         # print(freq_index[i-m:i+m]) | ||||
|         if (freq_availability[i - requested_m:i + requested_m] == [1] * (2 * requested_m) and | ||||
|                 freq_index[i - requested_m] >= freq_index_min | ||||
|         i = test_oms.spectrum_bitmap.geti(requested_n) | ||||
|         if (freq_availability[i - requested_m:i + requested_m] == [1] * (2 * requested_m) | ||||
|                 and freq_index[i - requested_m] >= freq_index_min | ||||
|                 and freq_index[i + requested_m - 1] <= freq_index_max): | ||||
|             # candidate is the triplet center_n, startn and stopn | ||||
|             candidate = (requested_n, requested_n - requested_m, requested_n + requested_m - 1) | ||||
|         else: | ||||
|             candidate = (None, None, None) | ||||
|     return candidate, path_oms | ||||
|     return candidate | ||||
|  | ||||
|  | ||||
| def determine_slot_numbers(test_oms, requested_n, required_m, per_channel_m): | ||||
|     """determines max availability around requested_n. requested_n should not be None""" | ||||
|     bitmap = test_oms.spectrum_bitmap | ||||
|     freq_index = bitmap.freq_index | ||||
|     freq_index_min = bitmap.freq_index_min | ||||
|     freq_index_max = bitmap.freq_index_max | ||||
|     freq_availability = bitmap.bitmap | ||||
|     center_i = bitmap.geti(requested_n) | ||||
|     i = per_channel_m | ||||
|     while (freq_availability[center_i - i:center_i + i] == [1] * (2 * i) | ||||
|            and freq_index[center_i - i] >= freq_index_min | ||||
|            and freq_index[center_i + i - 1] <= freq_index_max | ||||
|            and i <= required_m): | ||||
|         i += per_channel_m | ||||
|     return i - per_channel_m | ||||
|  | ||||
|  | ||||
| def select_candidate(candidates, policy): | ||||
|     """ selects a candidate among all available spectrum | ||||
|     """ | ||||
|     """selects a candidate among all available spectrum""" | ||||
|     if policy == 'first_fit': | ||||
|         if candidates: | ||||
|             return candidates[0] | ||||
| @@ -380,44 +396,112 @@ def select_candidate(candidates, policy): | ||||
|         raise ServiceError('Only first_fit spectrum assignment policy is implemented.') | ||||
|  | ||||
|  | ||||
| def compute_n_m(required_m, rq, path_oms, oms_list, per_channel_m, policy='first_fit'): | ||||
|     """ based on requested path_bandwidth fill in M=None values with uint values, using per_channel_m | ||||
|     and center frequency, with first fit strategy. The function checks the available spectrum but check | ||||
|     consistencies among M values of the request, but not with other requests. | ||||
|     For example, if request is for 32 slots corresponding to 8 x 4 slots of 32Gbauds channels, | ||||
|     the following frequency slots will result in the following assignment | ||||
|  | ||||
|     N = 0, 8,    16, 32           -> 0,   8,   16,   32 | ||||
|     M = 8, None, 8,  None         -> 8,   8,    8,    8 | ||||
|  | ||||
|     N = 0,    8,    16, 32        -> 0,   , 16 | ||||
|     M = None, None, 8,  None      -> 24,  , 8 | ||||
|     """ | ||||
|     selected_m = [] | ||||
|     selected_n = [] | ||||
|     remaining_slots_to_serve = required_m | ||||
|     # order slots for the computation: assign biggest m first | ||||
|     rq_N, rq_M, order = order_slots([{'N': n, 'M': m} for n, m in zip(rq.N, rq.M)]) | ||||
|     # Create an oms that represents current assignments of all oms listed in path_oms, and test N and M on it. | ||||
|     # If M is defined, checks that proposed N, M is free | ||||
|     test_oms = aggregate_oms_bitmap(path_oms, oms_list) | ||||
|     for n, m in zip(rq_N, rq_M): | ||||
|         if m is not None and n is not None: | ||||
|             # check availabilityfor this n, m | ||||
|             available_slots = determine_slot_numbers(test_oms, n, m, m) | ||||
|             if available_slots == 0: | ||||
|                 # if n, m are not feasible, break at this point no have non zero remaining_slots_to_serve | ||||
|                 # in order to blocks the request (even is other N,M where feasible) | ||||
|                 break | ||||
|         elif m is not None and n is None: | ||||
|             # find a candidate n | ||||
|             n, _, _ = spectrum_selection(test_oms, m, None) | ||||
|             if n is None: | ||||
|                 # if no n is feasible for the m, block the request | ||||
|                 break | ||||
|         elif m is None and n is not None: | ||||
|             # find a feasible m for this n. If None is found, then block the request | ||||
|             m = determine_slot_numbers(test_oms, n, remaining_slots_to_serve, per_channel_m) | ||||
|             if m == 0 or remaining_slots_to_serve == 0: | ||||
|                 break | ||||
|         else: | ||||
|             # if n and m are not defined, try to find a single  assignment to fits the remaining slots to serve | ||||
|             # (first fit strategy) | ||||
|             n, _, _ = spectrum_selection(test_oms, remaining_slots_to_serve, None) | ||||
|             if n is None or remaining_slots_to_serve == 0: | ||||
|                 break | ||||
|             else: | ||||
|                 m = remaining_slots_to_serve | ||||
|         selected_m.append(m) | ||||
|         selected_n.append(n) | ||||
|         test_oms.assign_spectrum(n, m) | ||||
|         remaining_slots_to_serve = remaining_slots_to_serve - m | ||||
|  | ||||
|     # re-order selected_m and selected_n according to initial request N, M order, ignoring None values | ||||
|     not_selected = [None for i in range(len(rq_N) - len(selected_n))] | ||||
|     selected_m = restore_order(selected_m + not_selected, order) | ||||
|     selected_n = restore_order(selected_n + not_selected, order) | ||||
|     return selected_n, selected_m, remaining_slots_to_serve | ||||
|  | ||||
|  | ||||
| def pth_assign_spectrum(pths, rqs, oms_list, rpths): | ||||
|     """ basic first fit assignment | ||||
|     """basic first fit assignment | ||||
|  | ||||
|     if reversed path are provided, means that occupation is bidir | ||||
|     """ | ||||
|     for pth, rq, rpth in zip(pths, rqs, rpths): | ||||
|         # computes the number of channels required | ||||
|         if hasattr(rq, 'blocking_reason'): | ||||
|             rq.N = None | ||||
|             rq.M = None | ||||
|         else: | ||||
|             nb_wl, requested_m = compute_spectrum_slot_vs_bandwidth(rq.path_bandwidth, | ||||
|             # computes the number of channels required for path_bandwidth and the min required nb of slots | ||||
|             # for one channel (corresponds to the spacing) | ||||
|             nb_wl, required_m = compute_spectrum_slot_vs_bandwidth(rq.path_bandwidth, | ||||
|                                                                    rq.spacing, rq.bit_rate) | ||||
|             if getattr(rq, 'M', None) is not None: | ||||
|                 # Consistency check between the requested M and path_bandwidth | ||||
|                 # M value should be bigger than the computed requested_m (simple estimate) | ||||
|                 # TODO: elaborate a more accurate estimate with nb_wl * tx_osnr + possibly guardbands in case of | ||||
|             _, per_channel_m = compute_spectrum_slot_vs_bandwidth(rq.bit_rate, | ||||
|                                                                   rq.spacing, rq.bit_rate) | ||||
|             # find oms ids that are concerned both by pth and rpth | ||||
|             path_oms = build_path_oms_id_list(pth + rpth) | ||||
|             if getattr(rq, 'M', None) is not None and all(rq.M): | ||||
|                 # if all M are well defined: Consistency check that the requested M are enough to carry the nb_wl: | ||||
|                 # check that the integer number of per_channel_m carried in each M value is enough to carry nb_wl. | ||||
|                 # if not, blocks the demand | ||||
|                 nb_channels_of_request = sum([m // per_channel_m for m in rq.M]) | ||||
|                 # TODO: elaborate a more accurate estimate with nb_wl * min_spacing + possibly guardbands in case of | ||||
|                 # superchannel closed packing. | ||||
|                 if requested_m > rq.M: | ||||
|                 if nb_wl > nb_channels_of_request: | ||||
|                     rq.N = None | ||||
|                     rq.M = None | ||||
|                     rq.blocking_reason = 'NOT_ENOUGH_RESERVED_SPECTRUM' | ||||
|                     # need to stop here for this request and not go though spectrum selection process with requested_m | ||||
|                     # need to stop here for this request and not go though spectrum selection process | ||||
|                     continue | ||||
|                 # use the req.M even if requested_m is smaller | ||||
|                 requested_m = rq.M | ||||
|             requested_n = getattr(rq, 'N', None) | ||||
|             (center_n, startn, stopn), path_oms = spectrum_selection(pth + rpth, oms_list, requested_m, | ||||
|                                                                      requested_n) | ||||
|             # if requested n and m concern already occupied spectrum the previous function returns a None candidate | ||||
|             # if not None, center_n and start, stop frequencies are applicable to all oms of pth | ||||
|             # checks that spectrum is not None else indicate blocking reason | ||||
|             if center_n is not None: | ||||
|                 for oms_elem in path_oms: | ||||
|                     oms_list[oms_elem].assign_spectrum(center_n, requested_m) | ||||
|                     oms_list[oms_elem].add_service(rq.request_id, nb_wl) | ||||
|                 rq.N = center_n | ||||
|                 rq.M = requested_m | ||||
|             else: | ||||
|             # Use the req.M even if nb_wl and required_m are smaller. | ||||
|             # first fit strategy: assign as many lambda as possible in the None remaining N, M values | ||||
|             selected_n, selected_m, remaining_slots_to_serve = \ | ||||
|                 compute_n_m(required_m, rq, path_oms, oms_list, per_channel_m) | ||||
|             # if there are some remaining_slots_to_serve, this means that provided rq.M and rq.N values were | ||||
|             # not possible. Then do not go though spectrum assignment process and blocks the demand | ||||
|             if remaining_slots_to_serve > 0: | ||||
|                 rq.N = None | ||||
|                 rq.M = None | ||||
|                 rq.blocking_reason = 'NO_SPECTRUM' | ||||
|                 continue | ||||
|             for oms_elem in path_oms: | ||||
|                 for this_n, this_m in zip(selected_n, selected_m): | ||||
|                     if this_m is not None: | ||||
|                         oms_list[oms_elem].assign_spectrum(this_n, this_m) | ||||
|                 oms_list[oms_elem].add_service(rq.request_id, nb_wl) | ||||
|             rq.N = selected_n | ||||
|             rq.M = selected_m | ||||
|   | ||||
| @@ -1,6 +1,11 @@ | ||||
| matplotlib>=3.5.1,<4 | ||||
| networkx>=2.6,<3 | ||||
| numpy>=1.22.0,<2 | ||||
| pbr>=5.7.0,<6 | ||||
| scipy>=1.7.3,<2 | ||||
| # matplotlib 3.8 removed support for Python 3.8 | ||||
| matplotlib>=3.7.3,<4 | ||||
| # networkx 3.2 removed support for Python 3.8 | ||||
| networkx>=3.1,<4 | ||||
| # numpy 1.25 removed support for Python 3.8 | ||||
| numpy>=1.24.4,<2 | ||||
| pbr>=6.0.0,<7 | ||||
| # scipy 1.11 removed support for Python 3.8 | ||||
| scipy>=1.10.1,<2 | ||||
| # xlrd 2.x removed support for .xlsx, it's only .xls now | ||||
| xlrd>=1.2.0,<2 | ||||
|   | ||||
| @@ -23,6 +23,7 @@ classifier = | ||||
|     Programming Language :: Python :: 3.9 | ||||
|     Programming Language :: Python :: 3.10 | ||||
|     Programming Language :: Python :: 3.11 | ||||
|     Programming Language :: Python :: 3.12 | ||||
|     Programming Language :: Python :: Implementation :: CPython | ||||
|     Topic :: Scientific/Engineering | ||||
|     Topic :: Scientific/Engineering :: Physics | ||||
|   | ||||
							
								
								
									
										21
									
								
								tests/data/CORONET_services.json
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										21
									
								
								tests/data/CORONET_services.json
									
									
									
									
									
										Normal file
									
								
							| @@ -0,0 +1,21 @@ | ||||
| { | ||||
|   "path-request": [ | ||||
|     { | ||||
|       "request-id": "0", | ||||
|       "source": "trx Abilene", | ||||
|       "destination": "trx Albany", | ||||
|       "src-tp-id": "trx Abilene", | ||||
|       "dst-tp-id": "trx Albany", | ||||
|       "bidirectional": false, | ||||
|       "path-constraints": { | ||||
|         "te-bandwidth": { | ||||
|           "technology": "flexi-grid", | ||||
|           "trx_type": "Voyager", | ||||
|           "trx_mode": "mode 3", | ||||
|           "spacing": 62500000000.0, | ||||
|           "path_bandwidth": 100000000000.0 | ||||
|         } | ||||
|       } | ||||
|     } | ||||
|   ] | ||||
| } | ||||
| @@ -42,10 +42,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 1, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -69,10 +71,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 4, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -87,10 +91,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 6, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -105,10 +111,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 8, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -123,10 +131,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 10, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -141,10 +151,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 12, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -159,10 +171,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 14, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -219,10 +233,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 1, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -246,10 +262,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 4, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -264,10 +282,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 6, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -282,10 +302,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 8, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -300,10 +322,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 10, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -318,10 +342,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 12, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -336,10 +362,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 14, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -354,10 +382,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 16, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -372,10 +402,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 18, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -390,10 +422,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 20, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -408,10 +442,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 22, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -426,10 +462,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 24, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -444,10 +482,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 26, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -462,10 +502,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 28, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -480,10 +522,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 30, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -498,10 +542,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 32, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -516,10 +562,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 34, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -534,10 +582,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 36, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -552,10 +602,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 38, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -570,10 +622,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 40, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -588,10 +642,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 42, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -276, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -648,10 +704,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 1, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -675,10 +733,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 4, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -693,10 +753,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 6, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -711,10 +773,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 8, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -729,10 +793,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 10, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -747,10 +813,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 12, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -765,10 +833,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 14, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -783,10 +853,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 16, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -801,10 +873,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 18, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -284, | ||||
|                   "M": 4 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -829,7 +903,7 @@ | ||||
|           }, | ||||
|           { | ||||
|             "metric-type": "SNR-0.1nm", | ||||
|             "accumulative-value": 22.15 | ||||
|             "accumulative-value": 22.14 | ||||
|           }, | ||||
|           { | ||||
|             "metric-type": "OSNR-bandwidth", | ||||
| @@ -861,10 +935,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 1, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -888,10 +964,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 4, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -906,10 +984,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 6, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -924,10 +1004,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 8, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -942,10 +1024,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 10, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -960,10 +1044,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 12, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -978,10 +1064,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 14, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -996,10 +1084,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 16, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1014,10 +1104,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 18, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1032,10 +1124,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 20, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1050,10 +1144,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 22, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1068,10 +1164,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 24, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1086,10 +1184,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 26, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1104,10 +1204,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 28, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1122,10 +1224,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 30, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1140,10 +1244,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 32, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1158,10 +1264,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 34, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1176,10 +1284,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 36, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1194,10 +1304,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 38, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1212,10 +1324,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 40, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1230,10 +1344,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 42, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -266, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1254,11 +1370,11 @@ | ||||
|         "path-metric": [ | ||||
|           { | ||||
|             "metric-type": "SNR-bandwidth", | ||||
|             "accumulative-value": 21.68 | ||||
|             "accumulative-value": 21.67 | ||||
|           }, | ||||
|           { | ||||
|             "metric-type": "SNR-0.1nm", | ||||
|             "accumulative-value": 28.78 | ||||
|             "accumulative-value": 28.76 | ||||
|           }, | ||||
|           { | ||||
|             "metric-type": "OSNR-bandwidth", | ||||
| @@ -1290,10 +1406,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 1, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1317,10 +1435,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 4, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1335,10 +1455,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 6, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1353,10 +1475,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 8, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1371,10 +1495,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 10, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1389,10 +1515,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 12, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1407,10 +1535,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 14, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1425,10 +1555,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 16, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
| @@ -1443,10 +1575,12 @@ | ||||
|           { | ||||
|             "path-route-object": { | ||||
|               "index": 18, | ||||
|               "label-hop": { | ||||
|               "label-hop": [ | ||||
|                 { | ||||
|                   "N": -274, | ||||
|                   "M": 6 | ||||
|                 } | ||||
|               ] | ||||
|             } | ||||
|           }, | ||||
|           { | ||||
|   | ||||
| @@ -1,7 +1,7 @@ | ||||
| response-id,source,destination,path_bandwidth,Pass?,nb of tsp pairs,total cost,transponder-type,transponder-mode,OSNR-0.1nm,SNR-0.1nm,SNR-bandwidth,baud rate (Gbaud),input power (dBm),path,"spectrum (N,M)",reversed path OSNR-0.1nm,reversed path SNR-0.1nm,reversed path SNR-bandwidth | ||||
| 0,trx Lorient_KMA,trx Vannes_KBE,100.0,True,1,1,Voyager,mode 1,30.84,30.84,26.75,32.0,0.0,trx Lorient_KMA | roadm Lorient_KMA | east edfa in Lorient_KMA to Vannes_KBE | fiber (Lorient_KMA → Vannes_KBE)-F055 | west edfa in Vannes_KBE to Lorient_KMA | roadm Vannes_KBE | trx Vannes_KBE,"-284, 4",,, | ||||
| 1,trx Brest_KLA,trx Vannes_KBE,10.0,True,1,1,Voyager,mode 1,22.65,22.11,18.03,32.0,1.0,trx Brest_KLA | roadm Brest_KLA | east edfa in Brest_KLA to Morlaix | fiber (Brest_KLA → Morlaix)-F060 | east fused spans in Morlaix | fiber (Morlaix → Lannion_CAS)-F059 | west edfa in Lannion_CAS to Morlaix | roadm Lannion_CAS | east edfa in Lannion_CAS to Corlay | fiber (Lannion_CAS → Corlay)-F061 | west fused spans in Corlay | fiber (Corlay → Loudeac)-F010 | west fused spans in Loudeac | fiber (Loudeac → Lorient_KMA)-F054 | west edfa in Lorient_KMA to Loudeac | roadm Lorient_KMA | east edfa in Lorient_KMA to Vannes_KBE | fiber (Lorient_KMA → Vannes_KBE)-F055 | west edfa in Vannes_KBE to Lorient_KMA | roadm Vannes_KBE | trx Vannes_KBE,"-276, 4",,, | ||||
| 3,trx Lannion_CAS,trx Rennes_STA,60.0,True,1,1,vendorA_trx-type1,mode 1,28.29,25.85,21.77,32.0,1.0,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,"-284, 4",,, | ||||
| 4,trx Rennes_STA,trx Lannion_CAS,150.0,True,1,1,vendorA_trx-type1,mode 2,22.27,22.15,15.05,64.0,0.0,trx Rennes_STA | roadm Rennes_STA | east edfa in Rennes_STA to Ploermel | fiber (Rennes_STA → Ploermel)- | east edfa in Ploermel to Vannes_KBE | fiber (Ploermel → Vannes_KBE)- | west edfa in Vannes_KBE to Ploermel | roadm Vannes_KBE | east edfa in Vannes_KBE to Lorient_KMA | fiber (Vannes_KBE → Lorient_KMA)-F055 | west edfa in Lorient_KMA to Vannes_KBE | roadm Lorient_KMA | east edfa in Lorient_KMA to Loudeac | fiber (Lorient_KMA → Loudeac)-F054 | east fused spans in Loudeac | fiber (Loudeac → Corlay)-F010 | east fused spans in Corlay | fiber (Corlay → Lannion_CAS)-F061 | west edfa in Lannion_CAS to Corlay | roadm Lannion_CAS | trx Lannion_CAS,"-266, 6",,, | ||||
| 5,trx Rennes_STA,trx Lannion_CAS,20.0,True,1,1,vendorA_trx-type1,mode 2,30.79,28.78,21.68,64.0,3.0,trx Rennes_STA | roadm Rennes_STA | east edfa in Rennes_STA to Stbrieuc | fiber (Rennes_STA → Stbrieuc)-F057 | west edfa in Stbrieuc to Rennes_STA | fiber (Stbrieuc → Lannion_CAS)-F056 | west edfa in Lannion_CAS to Stbrieuc | roadm Lannion_CAS | trx Lannion_CAS,"-274, 6",,, | ||||
| 0,trx Lorient_KMA,trx Vannes_KBE,100.0,True,1,1,Voyager,mode 1,30.84,30.84,26.75,32.0,0.0,trx Lorient_KMA | roadm Lorient_KMA | east edfa in Lorient_KMA to Vannes_KBE | fiber (Lorient_KMA → Vannes_KBE)-F055 | west edfa in Vannes_KBE to Lorient_KMA | roadm Vannes_KBE | trx Vannes_KBE,"[-284], [4]",,, | ||||
| 1,trx Brest_KLA,trx Vannes_KBE,10.0,True,1,1,Voyager,mode 1,22.65,22.11,18.03,32.0,1.0,trx Brest_KLA | roadm Brest_KLA | east edfa in Brest_KLA to Morlaix | fiber (Brest_KLA → Morlaix)-F060 | east fused spans in Morlaix | fiber (Morlaix → Lannion_CAS)-F059 | west edfa in Lannion_CAS to Morlaix | roadm Lannion_CAS | east edfa in Lannion_CAS to Corlay | fiber (Lannion_CAS → Corlay)-F061 | west fused spans in Corlay | fiber (Corlay → Loudeac)-F010 | west fused spans in Loudeac | fiber (Loudeac → Lorient_KMA)-F054 | west edfa in Lorient_KMA to Loudeac | roadm Lorient_KMA | east edfa in Lorient_KMA to Vannes_KBE | fiber (Lorient_KMA → Vannes_KBE)-F055 | west edfa in Vannes_KBE to Lorient_KMA | roadm Vannes_KBE | trx Vannes_KBE,"[-276], [4]",,, | ||||
| 3,trx Lannion_CAS,trx Rennes_STA,60.0,True,1,1,vendorA_trx-type1,mode 1,28.29,25.85,21.77,32.0,1.0,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,"[-284], [4]",,, | ||||
| 4,trx Rennes_STA,trx Lannion_CAS,150.0,True,1,1,vendorA_trx-type1,mode 2,22.27,22.14,15.05,64.0,0.0,trx Rennes_STA | roadm Rennes_STA | east edfa in Rennes_STA to Ploermel | fiber (Rennes_STA → Ploermel)- | east edfa in Ploermel to Vannes_KBE | fiber (Ploermel → Vannes_KBE)- | west edfa in Vannes_KBE to Ploermel | roadm Vannes_KBE | east edfa in Vannes_KBE to Lorient_KMA | fiber (Vannes_KBE → Lorient_KMA)-F055 | west edfa in Lorient_KMA to Vannes_KBE | roadm Lorient_KMA | east edfa in Lorient_KMA to Loudeac | fiber (Lorient_KMA → Loudeac)-F054 | east fused spans in Loudeac | fiber (Loudeac → Corlay)-F010 | east fused spans in Corlay | fiber (Corlay → Lannion_CAS)-F061 | west edfa in Lannion_CAS to Corlay | roadm Lannion_CAS | trx Lannion_CAS,"[-266], [6]",,, | ||||
| 5,trx Rennes_STA,trx Lannion_CAS,20.0,True,1,1,vendorA_trx-type1,mode 2,30.79,28.76,21.67,64.0,3.0,trx Rennes_STA | roadm Rennes_STA | east edfa in Rennes_STA to Stbrieuc | fiber (Rennes_STA → Stbrieuc)-F057 | west edfa in Stbrieuc to Rennes_STA | fiber (Stbrieuc → Lannion_CAS)-F056 | west edfa in Lannion_CAS to Stbrieuc | roadm Lannion_CAS | trx Lannion_CAS,"[-274], [6]",,, | ||||
| 6,,,,NO_PATH,,,,,,,,,,,,,, | ||||
|   | ||||
| 
 | 
| @@ -1,97 +1,97 @@ | ||||
| signal,nli | ||||
| 1.9952623149688793e-05,1.1158426495504604e-08 | ||||
| 1.9952623149688793e-05,1.263949624403159e-08 | ||||
| 1.9952623149688793e-05,1.3358478621325285e-08 | ||||
| 1.9952623149688793e-05,1.3830775406251184e-08 | ||||
| 1.9952623149688793e-05,1.4180462471172083e-08 | ||||
| 1.9952623149688793e-05,1.4456701012984246e-08 | ||||
| 1.9952623149688793e-05,1.4683973899785875e-08 | ||||
| 1.9952623149688793e-05,1.487624147046227e-08 | ||||
| 1.9952623149688793e-05,1.5042217041806274e-08 | ||||
| 1.9952623149688793e-05,1.5187703614492153e-08 | ||||
| 1.9952623149688793e-05,1.5316759790785317e-08 | ||||
| 1.9952623149688793e-05,1.543233485150211e-08 | ||||
| 1.9952623149688793e-05,1.553663885878994e-08 | ||||
| 1.9952623149688793e-05,1.5631370249579246e-08 | ||||
| 1.9952623149688793e-05,1.5717862065800704e-08 | ||||
| 1.9952623149688793e-05,1.57971793985894e-08 | ||||
| 1.9952623149688793e-05,1.5870186356579704e-08 | ||||
| 1.9952623149688793e-05,1.593759332223716e-08 | ||||
| 1.9952623149688793e-05,1.5999991070923486e-08 | ||||
| 1.9952623149688793e-05,1.6057875903450682e-08 | ||||
| 1.9952623149688793e-05,1.6111668489205982e-08 | ||||
| 1.9952623149688793e-05,1.6161728217386366e-08 | ||||
| 1.9952623149688793e-05,1.6208364281630228e-08 | ||||
| 1.9952623149688793e-05,1.6251844350226973e-08 | ||||
| 1.9952623149688793e-05,1.629240142540359e-08 | ||||
| 1.9952623149688793e-05,1.6330239326114482e-08 | ||||
| 1.9952623149688793e-05,1.6365537111728e-08 | ||||
| 1.9952623149688793e-05,1.6398452681655655e-08 | ||||
| 1.9952623149688793e-05,1.642912572715412e-08 | ||||
| 1.9952623149688793e-05,1.6457680168940455e-08 | ||||
| 1.9952623149688793e-05,1.6484226183026747e-08 | ||||
| 1.9952623149688793e-05,1.6508861894003893e-08 | ||||
| 1.9952623149688793e-05,1.6531674797617433e-08 | ||||
| 1.9952623149688793e-05,1.655274296130114e-08 | ||||
| 1.9952623149688793e-05,1.657213604125123e-08 | ||||
| 1.9952623149688793e-05,1.6589916146838222e-08 | ||||
| 1.9952623149688793e-05,1.660613857708963e-08 | ||||
| 1.9952623149688793e-05,1.6620852449214096e-08 | ||||
| 1.9952623149688793e-05,1.6634101235366932e-08 | ||||
| 1.9952623149688793e-05,1.664592322084737e-08 | ||||
| 1.9952623149688793e-05,1.6656351894496074e-08 | ||||
| 1.9952623149688793e-05,1.666541628009631e-08 | ||||
| 1.9952623149688793e-05,1.6673141215973025e-08 | ||||
| 1.9952623149688793e-05,1.6679547588653583e-08 | ||||
| 1.9952623149688793e-05,1.6684652525341145e-08 | ||||
| 1.9952623149688793e-05,1.668846954900963e-08 | ||||
| 1.9952623149688793e-05,1.66910086991187e-08 | ||||
| 1.9952623149688793e-05,1.6692276620238304e-08 | ||||
| 1.9952623149688793e-05,1.6692276620238304e-08 | ||||
| 1.9952623149688793e-05,1.6691008699118703e-08 | ||||
| 1.9952623149688793e-05,1.6688469549009633e-08 | ||||
| 1.9952623149688793e-05,1.6684652525341148e-08 | ||||
| 1.9952623149688793e-05,1.6679547588653586e-08 | ||||
| 1.9952623149688793e-05,1.6673141215973028e-08 | ||||
| 1.9952623149688793e-05,1.666541628009631e-08 | ||||
| 1.9952623149688793e-05,1.6656351894496084e-08 | ||||
| 1.9952623149688793e-05,1.6645923220847374e-08 | ||||
| 1.9952623149688793e-05,1.6634101235366935e-08 | ||||
| 1.9952623149688793e-05,1.66208524492141e-08 | ||||
| 1.9952623149688793e-05,1.6606138577089633e-08 | ||||
| 1.9952623149688793e-05,1.6589916146838225e-08 | ||||
| 1.9952623149688793e-05,1.6572136041251237e-08 | ||||
| 1.9952623149688793e-05,1.6552742961301146e-08 | ||||
| 1.9952623149688793e-05,1.653167479761744e-08 | ||||
| 1.9952623149688793e-05,1.6508861894003893e-08 | ||||
| 1.9952623149688793e-05,1.648422618302675e-08 | ||||
| 1.9952623149688793e-05,1.645768016894046e-08 | ||||
| 1.9952623149688793e-05,1.6429125727154126e-08 | ||||
| 1.9952623149688793e-05,1.6398452681655658e-08 | ||||
| 1.9952623149688793e-05,1.6365537111728004e-08 | ||||
| 1.9952623149688793e-05,1.6330239326114482e-08 | ||||
| 1.9952623149688793e-05,1.6292401425403594e-08 | ||||
| 1.9952623149688793e-05,1.6251844350226973e-08 | ||||
| 1.9952623149688793e-05,1.6208364281630228e-08 | ||||
| 1.9952623149688793e-05,1.616172821738637e-08 | ||||
| 1.9952623149688793e-05,1.6111668489205982e-08 | ||||
| 1.9952623149688793e-05,1.605787590345069e-08 | ||||
| 1.9952623149688793e-05,1.5999991070923493e-08 | ||||
| 1.9952623149688793e-05,1.5937593322237167e-08 | ||||
| 1.9952623149688793e-05,1.5870186356579704e-08 | ||||
| 1.9952623149688793e-05,1.5797179398589402e-08 | ||||
| 1.9952623149688793e-05,1.571786206580071e-08 | ||||
| 1.9952623149688793e-05,1.5631370249579252e-08 | ||||
| 1.9952623149688793e-05,1.5536638858789946e-08 | ||||
| 1.9952623149688793e-05,1.5432334851502114e-08 | ||||
| 1.9952623149688793e-05,1.531675979078532e-08 | ||||
| 1.9952623149688793e-05,1.5187703614492156e-08 | ||||
| 1.9952623149688793e-05,1.5042217041806274e-08 | ||||
| 1.9952623149688793e-05,1.4876241470462273e-08 | ||||
| 1.9952623149688793e-05,1.4683973899785879e-08 | ||||
| 1.9952623149688793e-05,1.4456701012984246e-08 | ||||
| 1.9952623149688793e-05,1.4180462471172086e-08 | ||||
| 1.9952623149688793e-05,1.3830775406251184e-08 | ||||
| 1.9952623149688793e-05,1.3358478621325285e-08 | ||||
| 1.9952623149688793e-05,1.2639496244031593e-08 | ||||
| 1.9952623149688793e-05,1.1158426495504613e-08 | ||||
| 1.9952623149688796e-05,1.0570305869494063e-08 | ||||
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|   | ||||
| 
 | 
| @@ -1,6 +1,6 @@ | ||||
| signal,nli | ||||
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|   | ||||
| 
 | 
| @@ -1,96 +1,96 @@ | ||||
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| 0.001,0.0007038020712072354,0.0005429365478183962,0.00034136940918446675,0.0002209236320980648,0.00014848117283038098,0.00010555633431743894,8.210263744821714e-05,7.434860458126827e-05,8.847824135377829e-05 | ||||
| 0.001,0.0007032398600991381,0.0005423613371043419,0.00034075574151016483,0.0002203786864681782,0.00014800154862415601,0.00010510371328265478,8.161429921011451e-05,7.369623501807121e-05,8.724287943554497e-05 | ||||
| 0.001,0.0007026797730466592,0.0005417884525961108,0.00034014496942632764,0.0002198365624959981,0.00014752460674093983,0.00010465389615779026,8.112955064604149e-05,7.305018913687007e-05,8.602540201539488e-05 | ||||
| 0.001,0.0007021196874055633,0.0005412157406692665,0.0003395348927353949,0.00021929545761274023,0.00014704895219343257,0.00010420578859113516,8.064746506639534e-05,7.240953347459202e-05,8.482441661675139e-05 | ||||
| 0.001,0.0007015596012323657,0.0005406431992153213,0.0003389255082691921,0.00021875536780717296,0.00014657457987728414,0.00010375938295149973,8.016802726693694e-05,7.17742234562459e-05,8.363970356449741e-05 | ||||
| 0.001,0.0007009995125587165,0.0005400708260946051,0.0003383168128172846,0.00021821628903476192,0.00014610148467187763,0.0001033146716169485,7.969122211456026e-05,7.114421486558773e-05,8.247104609297546e-05 | ||||
| 0.001,0.000700426120570031,0.0005394817717340144,0.00033767827777106695,0.00021763678242090514,0.00014557802543177205,0.00010280805245363877,7.913535785684264e-05,7.040274681183516e-05,8.111172191387726e-05 | ||||
| 0.001,0.0006998527383823768,0.0005388929110101418,0.0003370405259007354,0.00021705847496470142,0.00014505616500334602,0.00010230367256069614,7.858312049704058e-05,6.966868896041247e-05,7.977423771714316e-05 | ||||
| 0.0010496228983614124,0.002020602352332682,0.0024834354692445607,0.004712247621156641,0.00854174709233096,0.015197203876184536,0.027142477151470907,0.049749449744480465,0.09589624880110185,0.2 | ||||
| 0.004235602571438949,0.007336805952289255,0.008714058005603317,0.015024716476258112,0.025061770718850837,0.04079161627542227,0.0649508755581543,0.10074574737193842,0.14993445055894863,0.206 | ||||
|   | ||||
| 
 | 
							
								
								
									
										224
									
								
								tests/data/test_old_parameters_fiber_config.json
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										224
									
								
								tests/data/test_old_parameters_fiber_config.json
									
									
									
									
									
										Normal file
									
								
							| @@ -0,0 +1,224 @@ | ||||
| { | ||||
|   "uid": "Span1", | ||||
|   "params": { | ||||
|     "length": 80, | ||||
|     "loss_coef": 0.2, | ||||
|     "length_units": "km", | ||||
|     "att_in": 0, | ||||
|     "con_in": 0.5, | ||||
|     "con_out": 0.5, | ||||
|     "type_variety": "SSMF", | ||||
|     "dispersion": 0.0000167, | ||||
|     "effective_area": 83e-12, | ||||
|     "pmd_coef": 1.265e-15, | ||||
|     "raman_efficiency": { | ||||
|       "cr": [ | ||||
|         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, | ||||
|         1.88408911e-04, | ||||
|         2.05914127e-04, | ||||
|         2.24074028e-04, | ||||
|         2.47508283e-04, | ||||
|         2.77729174e-04, | ||||
|         3.08044243e-04, | ||||
|         3.34764439e-04, | ||||
|         3.56481704e-04, | ||||
|         3.77127256e-04, | ||||
|         3.96269124e-04, | ||||
|         4.10955175e-04, | ||||
|         4.18718761e-04, | ||||
|         4.19511263e-04, | ||||
|         4.17025384e-04, | ||||
|         4.13565369e-04, | ||||
|         4.07726048e-04, | ||||
|         3.83671291e-04, | ||||
|         4.08564283e-04, | ||||
|         3.69571936e-04, | ||||
|         3.14442090e-04, | ||||
|         2.16074535e-04, | ||||
|         1.23097823e-04, | ||||
|         8.95457457e-05, | ||||
|         7.52470400e-05, | ||||
|         7.19806145e-05, | ||||
|         8.87961158e-05, | ||||
|         9.30812065e-05, | ||||
|         9.37058268e-05, | ||||
|         8.45719619e-05, | ||||
|         6.90585286e-05, | ||||
|         4.50407159e-05, | ||||
|         3.36521245e-05, | ||||
|         3.02292475e-05, | ||||
|         2.69376939e-05, | ||||
|         2.60020897e-05, | ||||
|         2.82958958e-05, | ||||
|         3.08667558e-05, | ||||
|         3.66024657e-05, | ||||
|         5.80610307e-05, | ||||
|         6.54797937e-05, | ||||
|         6.25022715e-05, | ||||
|         5.37806442e-05, | ||||
|         3.94996621e-05, | ||||
|         2.68120644e-05, | ||||
|         2.33038554e-05, | ||||
|         1.79140757e-05, | ||||
|         1.52472424e-05, | ||||
|         1.32707565e-05, | ||||
|         1.06541760e-05, | ||||
|         9.84649374e-06, | ||||
|         9.13999627e-06, | ||||
|         9.08971012e-06, | ||||
|         1.04227525e-05, | ||||
|         1.50419271e-05, | ||||
|         1.77838232e-05, | ||||
|         2.15810815e-05, | ||||
|         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 | ||||
|       ], | ||||
|       "frequency_offset": [ | ||||
|         0.0e12, | ||||
|         0.5e12, | ||||
|         1.0e12, | ||||
|         1.5e12, | ||||
|         2.0e12, | ||||
|         2.5e12, | ||||
|         3.0e12, | ||||
|         3.5e12, | ||||
|         4.0e12, | ||||
|         4.5e12, | ||||
|         5.0e12, | ||||
|         5.5e12, | ||||
|         6.0e12, | ||||
|         6.5e12, | ||||
|         7.0e12, | ||||
|         7.5e12, | ||||
|         8.0e12, | ||||
|         8.5e12, | ||||
|         9.0e12, | ||||
|         9.5e12, | ||||
|         10.0e12, | ||||
|         10.5e12, | ||||
|         11.0e12, | ||||
|         11.5e12, | ||||
|         12.0e12, | ||||
|         12.5e12, | ||||
|         12.75e12, | ||||
|         13.0e12, | ||||
|         13.25e12, | ||||
|         13.5e12, | ||||
|         14.0e12, | ||||
|         14.5e12, | ||||
|         14.75e12, | ||||
|         15.0e12, | ||||
|         15.5e12, | ||||
|         16.0e12, | ||||
|         16.5e12, | ||||
|         17.0e12, | ||||
|         17.5e12, | ||||
|         18.0e12, | ||||
|         18.25e12, | ||||
|         18.5e12, | ||||
|         18.75e12, | ||||
|         19.0e12, | ||||
|         19.5e12, | ||||
|         20.0e12, | ||||
|         20.5e12, | ||||
|         21.0e12, | ||||
|         21.5e12, | ||||
|         22.0e12, | ||||
|         22.5e12, | ||||
|         23.0e12, | ||||
|         23.5e12, | ||||
|         24.0e12, | ||||
|         24.5e12, | ||||
|         25.0e12, | ||||
|         25.5e12, | ||||
|         26.0e12, | ||||
|         26.5e12, | ||||
|         27.0e12, | ||||
|         27.5e12, | ||||
|         28.0e12, | ||||
|         28.5e12, | ||||
|         29.0e12, | ||||
|         29.5e12, | ||||
|         30.0e12, | ||||
|         30.5e12, | ||||
|         31.0e12, | ||||
|         31.5e12, | ||||
|         32.0e12, | ||||
|         32.5e12, | ||||
|         33.0e12, | ||||
|         33.5e12, | ||||
|         34.0e12, | ||||
|         34.5e12, | ||||
|         35.0e12, | ||||
|         35.5e12, | ||||
|         36.0e12, | ||||
|         36.5e12, | ||||
|         37.0e12, | ||||
|         37.5e12, | ||||
|         38.0e12, | ||||
|         38.5e12, | ||||
|         39.0e12, | ||||
|         39.5e12, | ||||
|         40.0e12, | ||||
|         40.5e12, | ||||
|         41.0e12, | ||||
|         41.5e12, | ||||
|         42.0e12 | ||||
|       ] | ||||
|     } | ||||
|   }, | ||||
|   "operational": { | ||||
|         "temperature": 283, | ||||
|         "raman_pumps": [ | ||||
|           { | ||||
|             "power": 224.403e-3, | ||||
|             "frequency": 205e12, | ||||
|             "propagation_direction": "counterprop" | ||||
|           }, | ||||
|           { | ||||
|             "power": 231.135e-3, | ||||
|             "frequency": 201e12, | ||||
|             "propagation_direction": "counterprop" | ||||
|           } | ||||
|         ] | ||||
|       }, | ||||
|   "metadata": { | ||||
|     "location": { | ||||
|       "latitude": 1, | ||||
|       "longitude": 0, | ||||
|       "city": null, | ||||
|       "region": "" | ||||
|     } | ||||
|   } | ||||
| } | ||||
							
								
								
									
										225
									
								
								tests/data/test_parameters_fiber_config.json
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										225
									
								
								tests/data/test_parameters_fiber_config.json
									
									
									
									
									
										Normal file
									
								
							| @@ -0,0 +1,225 @@ | ||||
| { | ||||
|   "uid": "Span1", | ||||
|   "params": { | ||||
|     "length": 80, | ||||
|     "loss_coef": 0.2, | ||||
|     "length_units": "km", | ||||
|     "att_in": 0, | ||||
|     "con_in": 0.5, | ||||
|     "con_out": 0.5, | ||||
|     "type_variety": "SSMF", | ||||
|     "dispersion": 0.0000167, | ||||
|     "effective_area": 83e-12, | ||||
|     "pmd_coef": 1.265e-15, | ||||
|     "raman_coefficient": { | ||||
|       "g0": [ | ||||
|         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, | ||||
|         1.88408911e-04, | ||||
|         2.05914127e-04, | ||||
|         2.24074028e-04, | ||||
|         2.47508283e-04, | ||||
|         2.77729174e-04, | ||||
|         3.08044243e-04, | ||||
|         3.34764439e-04, | ||||
|         3.56481704e-04, | ||||
|         3.77127256e-04, | ||||
|         3.96269124e-04, | ||||
|         4.10955175e-04, | ||||
|         4.18718761e-04, | ||||
|         4.19511263e-04, | ||||
|         4.17025384e-04, | ||||
|         4.13565369e-04, | ||||
|         4.07726048e-04, | ||||
|         3.83671291e-04, | ||||
|         4.08564283e-04, | ||||
|         3.69571936e-04, | ||||
|         3.14442090e-04, | ||||
|         2.16074535e-04, | ||||
|         1.23097823e-04, | ||||
|         8.95457457e-05, | ||||
|         7.52470400e-05, | ||||
|         7.19806145e-05, | ||||
|         8.87961158e-05, | ||||
|         9.30812065e-05, | ||||
|         9.37058268e-05, | ||||
|         8.45719619e-05, | ||||
|         6.90585286e-05, | ||||
|         4.50407159e-05, | ||||
|         3.36521245e-05, | ||||
|         3.02292475e-05, | ||||
|         2.69376939e-05, | ||||
|         2.60020897e-05, | ||||
|         2.82958958e-05, | ||||
|         3.08667558e-05, | ||||
|         3.66024657e-05, | ||||
|         5.80610307e-05, | ||||
|         6.54797937e-05, | ||||
|         6.25022715e-05, | ||||
|         5.37806442e-05, | ||||
|         3.94996621e-05, | ||||
|         2.68120644e-05, | ||||
|         2.33038554e-05, | ||||
|         1.79140757e-05, | ||||
|         1.52472424e-05, | ||||
|         1.32707565e-05, | ||||
|         1.06541760e-05, | ||||
|         9.84649374e-06, | ||||
|         9.13999627e-06, | ||||
|         9.08971012e-06, | ||||
|         1.04227525e-05, | ||||
|         1.50419271e-05, | ||||
|         1.77838232e-05, | ||||
|         2.15810815e-05, | ||||
|         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 | ||||
|       ], | ||||
|       "frequency_offset": [ | ||||
|         0.0e12, | ||||
|         0.5e12, | ||||
|         1.0e12, | ||||
|         1.5e12, | ||||
|         2.0e12, | ||||
|         2.5e12, | ||||
|         3.0e12, | ||||
|         3.5e12, | ||||
|         4.0e12, | ||||
|         4.5e12, | ||||
|         5.0e12, | ||||
|         5.5e12, | ||||
|         6.0e12, | ||||
|         6.5e12, | ||||
|         7.0e12, | ||||
|         7.5e12, | ||||
|         8.0e12, | ||||
|         8.5e12, | ||||
|         9.0e12, | ||||
|         9.5e12, | ||||
|         10.0e12, | ||||
|         10.5e12, | ||||
|         11.0e12, | ||||
|         11.5e12, | ||||
|         12.0e12, | ||||
|         12.5e12, | ||||
|         12.75e12, | ||||
|         13.0e12, | ||||
|         13.25e12, | ||||
|         13.5e12, | ||||
|         14.0e12, | ||||
|         14.5e12, | ||||
|         14.75e12, | ||||
|         15.0e12, | ||||
|         15.5e12, | ||||
|         16.0e12, | ||||
|         16.5e12, | ||||
|         17.0e12, | ||||
|         17.5e12, | ||||
|         18.0e12, | ||||
|         18.25e12, | ||||
|         18.5e12, | ||||
|         18.75e12, | ||||
|         19.0e12, | ||||
|         19.5e12, | ||||
|         20.0e12, | ||||
|         20.5e12, | ||||
|         21.0e12, | ||||
|         21.5e12, | ||||
|         22.0e12, | ||||
|         22.5e12, | ||||
|         23.0e12, | ||||
|         23.5e12, | ||||
|         24.0e12, | ||||
|         24.5e12, | ||||
|         25.0e12, | ||||
|         25.5e12, | ||||
|         26.0e12, | ||||
|         26.5e12, | ||||
|         27.0e12, | ||||
|         27.5e12, | ||||
|         28.0e12, | ||||
|         28.5e12, | ||||
|         29.0e12, | ||||
|         29.5e12, | ||||
|         30.0e12, | ||||
|         30.5e12, | ||||
|         31.0e12, | ||||
|         31.5e12, | ||||
|         32.0e12, | ||||
|         32.5e12, | ||||
|         33.0e12, | ||||
|         33.5e12, | ||||
|         34.0e12, | ||||
|         34.5e12, | ||||
|         35.0e12, | ||||
|         35.5e12, | ||||
|         36.0e12, | ||||
|         36.5e12, | ||||
|         37.0e12, | ||||
|         37.5e12, | ||||
|         38.0e12, | ||||
|         38.5e12, | ||||
|         39.0e12, | ||||
|         39.5e12, | ||||
|         40.0e12, | ||||
|         40.5e12, | ||||
|         41.0e12, | ||||
|         41.5e12, | ||||
|         42.0e12 | ||||
|       ], | ||||
|       "reference_frequency": 206184634112792 | ||||
|     } | ||||
|   }, | ||||
|   "operational": { | ||||
|         "temperature": 283, | ||||
|         "raman_pumps": [ | ||||
|           { | ||||
|             "power": 224.403e-3, | ||||
|             "frequency": 205e12, | ||||
|             "propagation_direction": "counterprop" | ||||
|           }, | ||||
|           { | ||||
|             "power": 231.135e-3, | ||||
|             "frequency": 201e12, | ||||
|             "propagation_direction": "counterprop" | ||||
|           } | ||||
|         ] | ||||
|       }, | ||||
|   "metadata": { | ||||
|     "location": { | ||||
|       "latitude": 1, | ||||
|       "longitude": 0, | ||||
|       "city": null, | ||||
|       "region": "" | ||||
|     } | ||||
|   } | ||||
| } | ||||
| @@ -1,97 +1,97 @@ | ||||
| ,Unnamed: 0,signal,ase,nli | ||||
| 0,0,0.00028461768874888705,3.436639817118301e-08,2.1584395398371026e-07 | ||||
| 1,1,0.00028211666293476406,3.423996759499589e-08,2.1809245861954257e-07 | ||||
| 2,2,0.0002796385058453953,3.411427963331182e-08,2.2028548201656645e-07 | ||||
| 3,3,0.0002771829951915728,3.398932824433299e-08,2.224238538437057e-07 | ||||
| 4,4,0.00027338904730863836,3.371109366484941e-08,2.2339638015421542e-07 | ||||
| 5,5,0.0002696478418176822,3.3435235312069656e-08,2.2430128879557504e-07 | ||||
| 6,6,0.00026595862771951147,3.316172589770091e-08,2.2514026889123164e-07 | ||||
| 7,7,0.0002623182345801782,3.289051654795761e-08,2.2591288176837496e-07 | ||||
| 8,8,0.00025872603823298804,3.262158136113203e-08,2.2662073272007013e-07 | ||||
| 9,9,0.0002548422077504841,3.231480491053109e-08,2.269632917207947e-07 | ||||
| 10,10,0.0002510150800727548,3.201089350512762e-08,2.2724305184561305e-07 | ||||
| 11,11,0.0002472372108596339,3.1709697987730424e-08,2.274556638142854e-07 | ||||
| 12,12,0.0002435081184388883,3.1411188710954923e-08,2.2760284870806473e-07 | ||||
| 13,13,0.0002398273228957255,3.1115336193393125e-08,2.2768630096746835e-07 | ||||
| 14,14,0.00023610099948769217,3.081056270085416e-08,2.27617695956038e-07 | ||||
| 15,15,0.00023242489102440902,3.050859262250336e-08,2.274887362838919e-07 | ||||
| 16,16,0.00022879847092097078,3.020939430576677e-08,2.273011122655665e-07 | ||||
| 17,17,0.00022522143236587835,2.991293825364657e-08,2.27056704831033e-07 | ||||
| 18,18,0.00022169324298613107,2.9619193056612953e-08,2.2315585168570266e-07 | ||||
| 19,19,0.0002178178461312317,2.9278097616561043e-08,2.189169855906453e-07 | ||||
| 20,20,0.0002140033759047069,2.8940600865395135e-08,2.1475128288390263e-07 | ||||
| 21,21,0.00021024912752446947,2.8606658136588645e-08,2.1065775386659407e-07 | ||||
| 22,22,0.000206554289175574,2.827622313698371e-08,2.0663530613832196e-07 | ||||
| 23,23,0.00020291805701626135,2.7949249962519028e-08,2.0268286030011824e-07 | ||||
| 24,24,0.00019961589106178864,2.765975998385304e-08,1.9907485701921993e-07 | ||||
| 25,25,0.00019636137150032674,2.7373095433009936e-08,1.9552454239910457e-07 | ||||
| 26,26,0.0001931539326017224,2.7089223372231097e-08,1.9203113225618846e-07 | ||||
| 27,27,0.00018999370973089413,2.68081175642488e-08,1.885945418493717e-07 | ||||
| 28,28,0.00018688010986276862,2.6529745205109403e-08,1.8521396370161997e-07 | ||||
| 29,29,0.00018381254538966195,2.6254073731438793e-08,1.818885993764317e-07 | ||||
| 30,30,0.00018079043504395085,2.5981070886269e-08,1.78617660347401e-07 | ||||
| 31,31,0.00017781329518445636,2.5710706310905614e-08,1.7540045799671345e-07 | ||||
| 32,32,0.00017488055045064023,2.544294811944895e-08,1.7223621637516225e-07 | ||||
| 33,33,0.00017199163096488036,2.5177764647772334e-08,1.691241684952796e-07 | ||||
| 34,34,0.00016923198600435235,2.4926164244345613e-08,1.6614800249846462e-07 | ||||
| 35,35,0.00016651223518287261,2.4676978561810828e-08,1.632195038378843e-07 | ||||
| 36,36,0.00016383188581753214,2.443018036493577e-08,1.6033800467387247e-07 | ||||
| 37,37,0.0001611915388800597,2.418575294396746e-08,1.5725354810318075e-07 | ||||
| 38,38,0.0001585906555197023,2.394366896238391e-08,1.5422386234766858e-07 | ||||
| 39,39,0.00015602870309712287,2.3703901303924173e-08,1.5124806354481474e-07 | ||||
| 40,40,0.0001535051551031788,2.3466423066629146e-08,1.4832528036973196e-07 | ||||
| 41,41,0.0001510212597387019,2.3231240549132765e-08,1.4545635735033158e-07 | ||||
| 42,42,0.00014857641307701306,2.2998325757462813e-08,1.4264034538487909e-07 | ||||
| 43,43,0.00014617002011358969,2.276765094680208e-08,1.3987631140917146e-07 | ||||
| 44,44,0.00014368188097051016,2.252080862505795e-08,1.3704924606778587e-07 | ||||
| 45,45,0.00014123500136325632,2.227648394665253e-08,1.342768563640109e-07 | ||||
| 46,46,0.00013882871459443323,2.2034644371118186e-08,1.31558126246417e-07 | ||||
| 47,47,0.00013646341840215168,2.1795267893415555e-08,1.2889305332810146e-07 | ||||
| 48,48,0.00013413841082142,2.155832207437193e-08,1.2628059500046815e-07 | ||||
| 49,49,0.00013185300210097483,2.132377480769977e-08,1.2371972883222934e-07 | ||||
| 50,50,0.00012960651423053282,2.1091594291962705e-08,1.2120945193769904e-07 | ||||
| 51,51,0.00012739961074346843,2.0861774576065466e-08,1.1875002031242091e-07 | ||||
| 52,52,0.00012523156633255863,2.0634283235397628e-08,1.1634039147633555e-07 | ||||
| 53,53,0.00012310166960708747,2.0409088189365173e-08,1.1397954484148417e-07 | ||||
| 54,54,0.00012096529298347188,2.0178855168888422e-08,1.1162594309222065e-07 | ||||
| 55,55,0.00011886718830718708,1.9950983760858723e-08,1.093208043434055e-07 | ||||
| 56,56,0.00011680664424128133,1.9725440474060072e-08,1.0695583879566178e-07 | ||||
| 57,57,0.00011478396058700633,1.950220202088885e-08,1.0464196732373097e-07 | ||||
| 58,58,0.00011279839933843229,1.9281235055452333e-08,1.0237806316789167e-07 | ||||
| 59,59,0.00011084923776207272,1.906250658388995e-08,1.0016302524437989e-07 | ||||
| 60,60,0.00010893576763351642,1.884598391874928e-08,9.79957771514819e-08 | ||||
| 61,61,0.00010705827573621923,1.8631654017664683e-08,9.587614496435341e-08 | ||||
| 62,62,0.00010521603014069265,1.8419483867548078e-08,9.380304193213288e-08 | ||||
| 63,63,0.00010340831493293095,1.8209440802910146e-08,9.1775407295826e-08 | ||||
| 64,64,0.00010178667717264663,1.8029552937387797e-08,8.992671343771878e-08 | ||||
| 65,65,0.00010019319833745167,1.7851381317094802e-08,8.811583172055121e-08 | ||||
| 66,66,9.86273426809622e-05,1.767490377589294e-08,8.634195328719705e-08 | ||||
| 67,67,9.70886230248071e-05,1.7500098774413897e-08,8.460432022445385e-08 | ||||
| 68,68,9.557652367577673e-05,1.7326944621204857e-08,8.290215772518696e-08 | ||||
| 69,69,9.409053958216297e-05,1.7155419863785074e-08,8.123470846820667e-08 | ||||
| 70,70,9.263017577528553e-05,1.698550325493719e-08,7.960123192429599e-08 | ||||
| 71,71,9.119540203213482e-05,1.681718296074974e-08,7.800139303615196e-08 | ||||
| 72,72,8.978572151582878e-05,1.6650437769918198e-08,7.643446000507212e-08 | ||||
| 73,73,8.840064792008674e-05,1.648524670194174e-08,7.489971794966337e-08 | ||||
| 74,74,8.704752218385389e-05,1.6323921332107853e-08,7.340306015991841e-08 | ||||
| 75,75,8.571782151670807e-05,1.616417166590195e-08,7.228178645083984e-08 | ||||
| 76,76,8.441109599127084e-05,1.6005979385519616e-08,7.117988659258102e-08 | ||||
| 77,77,8.312693723019766e-05,1.584932678267078e-08,7.009701621983393e-08 | ||||
| 78,78,8.186491243372442e-05,1.569419608150936e-08,6.90328103730187e-08 | ||||
| 79,79,8.062459786565112e-05,1.554056978222129e-08,6.798691173543069e-08 | ||||
| 80,80,7.94055784447779e-05,1.538843064058219e-08,6.695897028871753e-08 | ||||
| 81,81,7.820755061857071e-05,1.523776381588298e-08,6.594873006137818e-08 | ||||
| 82,82,7.703011159024537e-05,1.5088552513719166e-08,6.495585139392737e-08 | ||||
| 83,83,7.587286701386211e-05,1.494078021244127e-08,6.398000175307732e-08 | ||||
| 84,84,7.483848702669918e-05,1.481852757489104e-08,6.310775801171533e-08 | ||||
| 85,85,7.382059659354297e-05,1.4697575551136038e-08,6.224941913167962e-08 | ||||
| 86,86,7.281889798107282e-05,1.4577917663325962e-08,6.140473404853674e-08 | ||||
| 87,87,7.183165666349203e-05,1.4459532716368791e-08,6.057224011868445e-08 | ||||
| 88,88,7.08586484091438e-05,1.4342415672865158e-08,5.975174825816752e-08 | ||||
| 89,89,6.989965271824705e-05,1.422656189652791e-08,5.8943072529944956e-08 | ||||
| 90,90,6.895445267562359e-05,1.411196715686287e-08,5.814603001970201e-08 | ||||
| 91,91,6.802197391413278e-05,1.3998609279853771e-08,5.735971476442124e-08 | ||||
| 92,92,6.710204336793658e-05,1.3886485591019257e-08,5.6583980825863337e-08 | ||||
| 93,93,6.619449037899918e-05,1.3775593851234834e-08,5.581868429617485e-08 | ||||
| 94,94,6.515268324911003e-05,1.3628882565600955e-08,5.494017759648076e-08 | ||||
| 95,95,6.412720169535454e-05,1.3483606920728348e-08,5.407543748332493e-08 | ||||
| signal,ase,nli | ||||
| 0.000325019416624,3.8827360617812335e-08,2.397604591245591e-07 | ||||
| 0.0003222815415358,3.8702821151814216e-08,2.4267833614138976e-07 | ||||
| 0.0003195661748689,3.8578942925493807e-08,2.455296149641726e-07 | ||||
| 0.000316873132879,3.8455721305309324e-08,2.483151861322029e-07 | ||||
| 0.0003125687708988,3.815158818797417e-08,2.497308542349044e-07 | ||||
| 0.0003083216327341,3.784989647314237e-08,2.5106122773764815e-07 | ||||
| 0.0003041309702107,3.755062053762566e-08,2.523083160653813e-07 | ||||
| 0.0002999931829076,3.725370771318225e-08,2.534716728592015e-07 | ||||
| 0.0002959076621852,3.695913382975532e-08,2.545532047834699e-07 | ||||
| 0.0002914749637887,3.6620413511505286e-08,2.5520557429118934e-07 | ||||
| 0.0002871045786391,3.62847038107824e-08,2.557776344401253e-07 | ||||
| 0.0002827879891071,3.5951828869209396e-08,2.5626453052593257e-07 | ||||
| 0.0002785247470154,3.562176113110911e-08,2.5666832208790035e-07 | ||||
| 0.0002743144039041,3.5294473123494e-08,2.569910409348857e-07 | ||||
| 0.000270032675166,3.4954880805048256e-08,2.571167784361306e-07 | ||||
| 0.0002658067200554,3.4618272391047544e-08,2.571652788509227e-07 | ||||
| 0.000261636025157,3.428461757057609e-08,2.5713860104931033e-07 | ||||
| 0.00025752034599,3.395388872366444e-08,2.570390408700655e-07 | ||||
| 0.000253459157096,3.362605558722993e-08,2.5284986247287787e-07 | ||||
| 0.000248983782073,3.3242702224575744e-08,2.48252059976888e-07 | ||||
| 0.0002445773493265,3.286328176612301e-08,2.437277481862015e-07 | ||||
| 0.0002402391773459,3.2487750441670215e-08,2.392761376865807e-07 | ||||
| 0.0002359684123723,3.2116061418127753e-08,2.3489626905665574e-07 | ||||
| 0.0002317642070805,3.174816817069829e-08,2.3058719110264335e-07 | ||||
| 0.0002279695550926,3.1424928539548144e-08,2.2668986526609113e-07 | ||||
| 0.0002242281358436,3.1104729317697146e-08,2.228495045304229e-07 | ||||
| 0.0002205393783222,3.078753835343166e-08,2.190654562751529e-07 | ||||
| 0.0002169035545525,3.047333197100547e-08,2.1533790605165431e-07 | ||||
| 0.0002133200561122,3.01620779209974e-08,2.1166616520930645e-07 | ||||
| 0.0002097882786443,2.9853744125792176e-08,2.080495504306458e-07 | ||||
| 0.0002063076230434,2.9548298767727423e-08,2.0448738489666716e-07 | ||||
| 0.0002028776374913,2.9245712991289203e-08,2.009791389793126e-07 | ||||
| 0.0001994977236946,2.8945955168147914e-08,1.975241389908885e-07 | ||||
| 0.0001961672877059,2.8648993828553545e-08,1.9412171682473827e-07 | ||||
| 0.0001929967738963,2.8368195292008612e-08,1.9088102669437356e-07 | ||||
| 0.0001898709450753,2.8090002575266257e-08,1.8768789971552863e-07 | ||||
| 0.0001867892958482,2.7814389032455363e-08,1.8454176486632323e-07 | ||||
| 0.000183752636707,2.754134148447891e-08,1.8115002092564538e-07 | ||||
| 0.0001807604032471,2.7270832946920812e-08,1.7781492252546064e-07 | ||||
| 0.0001778120365192,2.7002836607760232e-08,1.745356369687972e-07 | ||||
| 0.0001749069829579,2.673732582084065e-08,1.7131134159682263e-07 | ||||
| 0.0001720467771106,2.6474316260529432e-08,1.6814325920632144e-07 | ||||
| 0.0001692307716138,2.6213779758633963e-08,1.6503047175593728e-07 | ||||
| 0.0001664583277393,2.5955688359138642e-08,1.619720751255672e-07 | ||||
| 0.0001635796256227,2.5677295228672648e-08,1.588223280583729e-07 | ||||
| 0.0001607481963598,2.540169810843596e-08,1.557306487644946e-07 | ||||
| 0.0001579633073114,2.512886316325068e-08,1.526960267832303e-07 | ||||
| 0.0001552255108883,2.4858770138402143e-08,1.4971869736122287e-07 | ||||
| 0.000152534027681,2.4591385101783997e-08,1.467976093017761e-07 | ||||
| 0.0001498880910245,2.432667443532368e-08,1.439317302908228e-07 | ||||
| 0.0001472869464661,2.4064604800471338e-08,1.411200462508912e-07 | ||||
| 0.0001447314108795,2.3805175801260087e-08,1.3836305172259211e-07 | ||||
| 0.0001422206714078,2.3548353146553164e-08,1.3565967973526553e-07 | ||||
| 0.0001397539300508,2.3294102880186107e-08,1.3300888438790536e-07 | ||||
| 0.0001372700286953,2.3032485432340423e-08,1.3035230831596558e-07 | ||||
| 0.0001348306664569,2.2773547798807564e-08,1.277485195296911e-07 | ||||
| 0.0001324350333325,2.2517253805739807e-08,1.2505815113074245e-07 | ||||
| 0.0001300835425363,2.2263580536243144e-08,1.2242454150816991e-07 | ||||
| 0.0001277753479236,2.2012491805819457e-08,1.1984647647989558e-07 | ||||
| 0.0001255096202792,2.1763951788812352e-08,1.1732276843747534e-07 | ||||
| 0.0001232855464269,2.1517924960982367e-08,1.148522552473446e-07 | ||||
| 0.0001211034718808,2.1274400813402842e-08,1.1243486085670634e-07 | ||||
| 0.0001189625537742,2.1033343271785093e-08,1.100694052812587e-07 | ||||
| 0.0001168619671686,2.0794716623616593e-08,1.0775473577456182e-07 | ||||
| 0.0001149842862687,2.0591381044652174e-08,1.056582342233035e-07 | ||||
| 0.0001131392424142,2.038998454906055e-08,1.0360354473279054e-07 | ||||
| 0.0001113262252932,2.0190503422606346e-08,1.0158979943539652e-07 | ||||
| 0.0001095446965516,1.9992914861970927e-08,9.961620365200192e-08 | ||||
| 0.0001077940670993,1.9797195630879305e-08,9.768192356581421e-08 | ||||
| 0.0001060737596438,1.9603322741072024e-08,9.578614349620901e-08 | ||||
| 0.0001043832080373,1.9411273409584944e-08,9.392806512410292e-08 | ||||
| 0.0001027223865858,1.922103688152168e-08,9.210738192714242e-08 | ||||
| 0.0001010907257366,1.9032590330084783e-08,9.032330177845482e-08 | ||||
| 9.948766769187398e-05,1.8845911172333032e-08,8.857505025129074e-08 | ||||
| 9.792267601599324e-05,1.8663442661346744e-08,8.687075031773093e-08 | ||||
| 9.638489299064336e-05,1.848276820506329e-08,8.550652733411691e-08 | ||||
| 9.48738026587305e-05,1.830386814585904e-08,8.416598440502352e-08 | ||||
| 9.338895072626004e-05,1.8126723701740663e-08,8.284871850980459e-08 | ||||
| 9.192983962632808e-05,1.7951315790883015e-08,8.155428823884958e-08 | ||||
| 9.049598195913348e-05,1.7777625631449783e-08,8.028226120215297e-08 | ||||
| 8.908690001727453e-05,1.7605634715742614e-08,7.903221360818749e-08 | ||||
| 8.77022482135352e-05,1.743532764682425e-08,7.780383887402493e-08 | ||||
| 8.634156228069215e-05,1.7266686393258476e-08,7.659672513140668e-08 | ||||
| 8.50043874741986e-05,1.7099693224424935e-08,7.541046895998541e-08 | ||||
| 8.381694660770028e-05,1.6962933489525264e-08,7.43570471865261e-08 | ||||
| 8.26484651987276e-05,1.682764479561346e-08,7.33204450340972e-08 | ||||
| 8.149860566615124e-05,1.6693821025332528e-08,7.230036302225977e-08 | ||||
| 8.036532369463753e-05,1.6561436760581683e-08,7.129498756488483e-08 | ||||
| 7.924836834130927e-05,1.6430487594212236e-08,7.030409604146297e-08 | ||||
| 7.814749266035204e-05,1.6300969571299207e-08,6.932746937742372e-08 | ||||
| 7.706245353522453e-05,1.6172879193985398e-08,6.836489189528336e-08 | ||||
| 7.599203524832233e-05,1.6046190191322708e-08,6.741528508795074e-08 | ||||
| 7.493604414299442e-05,1.5920900877281144e-08,6.647847715560108e-08 | ||||
| 7.389428911314724e-05,1.57970100612018e-08,6.555429856110159e-08 | ||||
| 7.268136514077581e-05,1.5628904744452727e-08,6.447826980203191e-08 | ||||
| 7.148784598320314e-05,1.5462487634551132e-08,6.341945575654982e-08 | ||||
|   | ||||
| 
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								tests/data/wrong_node_type.xlsx
									
									
									
									
									
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								tests/data/wrong_service.xlsx
									
									
									
									
									
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								tests/data/wrong_service_type.xlsx
									
									
									
									
									
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								tests/data/wrong_topo_bad_eqpt.xlsx
									
									
									
									
									
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								tests/data/wrong_topo_duplicate_eqpt.xlsx
									
									
									
									
									
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								tests/data/wrong_topo_duplicate_node.xlsx
									
									
									
									
									
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								tests/data/wrong_topo_link.xlsx
									
									
									
									
									
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								tests/data/wrong_topo_link_header.xlsx
									
									
									
									
									
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								tests/data/wrong_topo_node.xlsx
									
									
									
									
									
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										37
									
								
								tests/invocation/logs_path_request
									
									
									
									
									
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										37
									
								
								tests/invocation/logs_path_request
									
									
									
									
									
										Normal file
									
								
							| @@ -0,0 +1,37 @@ | ||||
| INFO     gnpy.tools.cli_examples:cli_examples.py Computing path requests meshTopologyExampleV2.xls into JSON format | ||||
| INFO     gnpy.tools.json_io:json_io.py Automatically converting requests from XLS to JSON | ||||
| INFO     gnpy.topology.request:request.py  | ||||
| 	request 0 | ||||
| 	Computing path from trx Lorient_KMA to trx Vannes_KBE | ||||
| 	with path constraint: ['trx Lorient_KMA', 'trx Vannes_KBE'] | ||||
| 	Computed path (roadms):['roadm Lorient_KMA', 'roadm Vannes_KBE'] | ||||
| INFO     gnpy.topology.request:request.py  | ||||
| 	request 1 | ||||
| 	Computing path from trx Brest_KLA to trx Vannes_KBE | ||||
| 	with path constraint: ['trx Brest_KLA', 'roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE', 'trx Vannes_KBE'] | ||||
| 	Computed path (roadms):['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE'] | ||||
| INFO     gnpy.topology.request:request.py  | ||||
| 	request 3 | ||||
| 	Computing path from trx Lannion_CAS to trx Rennes_STA | ||||
| 	with path constraint: ['trx Lannion_CAS', 'trx Rennes_STA'] | ||||
| 	Computed path (roadms):['roadm Lannion_CAS', 'roadm Rennes_STA'] | ||||
| INFO     gnpy.topology.request:request.py  | ||||
| 	request 4 | ||||
| 	Computing path from trx Rennes_STA to trx Lannion_CAS | ||||
| 	with path constraint: ['trx Rennes_STA', 'trx Lannion_CAS'] | ||||
| 	Computed path (roadms):['roadm Rennes_STA', 'roadm Vannes_KBE', 'roadm Lorient_KMA', 'roadm Lannion_CAS'] | ||||
| INFO     gnpy.topology.request:request.py  | ||||
| 	request 5 | ||||
| 	Computing path from trx Rennes_STA to trx Lannion_CAS | ||||
| 	with path constraint: ['trx Rennes_STA', 'trx Lannion_CAS'] | ||||
| 	Computed path (roadms):['roadm Rennes_STA', 'roadm Lannion_CAS'] | ||||
| INFO     gnpy.topology.request:request.py  | ||||
| 	request 7 | 6 | ||||
| 	Computing path from trx Lannion_CAS to trx Lorient_KMA | ||||
| 	with path constraint: ['trx Lannion_CAS', 'trx Lorient_KMA'] | ||||
| 	Computed path (roadms):['roadm Lannion_CAS', 'roadm Lorient_KMA'] | ||||
| INFO     gnpy.topology.request:request.py  | ||||
| 	request 7b | ||||
| 	Computing path from trx Lannion_CAS to trx Lorient_KMA | ||||
| 	with path constraint: ['trx Lannion_CAS', 'trx Lorient_KMA'] | ||||
| 	Computed path (roadms):['roadm Lannion_CAS', 'roadm Lorient_KMA'] | ||||
							
								
								
									
										13
									
								
								tests/invocation/logs_path_requests_run_CD_PMD_PDL_missing
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										13
									
								
								tests/invocation/logs_path_requests_run_CD_PMD_PDL_missing
									
									
									
									
									
										Normal file
									
								
							| @@ -0,0 +1,13 @@ | ||||
| INFO     gnpy.tools.cli_examples:cli_examples.py Computing path requests CORONET_services.json into JSON format | ||||
| INFO     gnpy.topology.request:request.py  | ||||
| 	request 0 | ||||
| 	Computing path from trx Abilene to trx Albany | ||||
| 	with path constraint: ['trx Abilene', 'trx Albany'] | ||||
| 	Computed path (roadms):['roadm Abilene', 'roadm Dallas', 'roadm Little_Rock', 'roadm Memphis', 'roadm Nashville', 'roadm Louisville', 'roadm Cincinnati', 'roadm Columbus', 'roadm Cleveland', 'roadm Buffalo', 'roadm Rochester', 'roadm Syracuse', 'roadm Albany'] | ||||
| WARNING  gnpy.topology.request:request.py 	Warning! Request 0 computed path from trx Abilene to trx Albany does not pass with mode 3 | ||||
| 	computed SNR in 0.1nm = 14.44 | ||||
| 	PDL penalty not evaluated | ||||
| 	CD penalty not evaluated | ||||
| 	PMD penalty not evaluated | ||||
| 	required osnr = 18 | ||||
| 	system margin = 2 | ||||
							
								
								
									
										307
									
								
								tests/invocation/logs_transmission_saturated
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										307
									
								
								tests/invocation/logs_transmission_saturated
									
									
									
									
									
										Normal file
									
								
							| @@ -0,0 +1,307 @@ | ||||
| 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  | ||||
| 	WARNING: target gain and power in node west edfa in Lorient_KMA to Loudeac | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: effective gain in Node east edfa in Lannion_CAS to Stbrieuc | ||||
| 	is above user specified amplifier std_low_gain | ||||
| 	max flat gain: 16dB ; required gain: 23.0dB. Please check amplifier type. | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Rennes_STA to Stbrieuc | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: effective gain in Node east edfa in Lannion_CAS to Morlaix | ||||
| 	is above user specified amplifier std_low_gain | ||||
| 	max flat gain: 16dB ; required gain: 23.5dB. Please check amplifier type. | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Brest_KLA to Morlaix | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Lorient_KMA to Loudeac | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: effective gain in Node west edfa in Lannion_CAS to Corlay | ||||
| 	is above user specified amplifier test | ||||
| 	max flat gain: 25dB ; required gain: 29.82dB. Please check amplifier type. | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Lorient_KMA to Vannes_KBE | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Vannes_KBE to Lorient_KMA | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Lorient_KMA to Quimper | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Quimper to Lorient_KMA | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Brest_KLA to Quimper | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Vannes_KBE to Lorient_KMA | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Lorient_KMA to Vannes_KBE | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Vannes_KBE to Ploermel | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Ploermel to Vannes_KBE | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Rennes_STA to Ploermel | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Rennes_STA to Stbrieuc | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Stbrieuc to Rennes_STA | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Lannion_CAS to Stbrieuc | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Rennes_STA to Ploermel | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Vannes_KBE to Ploermel | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Brest_KLA to Morlaix | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: effective gain in Node east edfa in Brest_KLA to Quimper | ||||
| 	is above user specified amplifier std_low_gain | ||||
| 	max flat gain: 16dB ; required gain: 23.0dB. Please check amplifier type. | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in Quimper to Lorient_KMA | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in Lorient_KMA to Quimper | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in a to b | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in b to a | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in a to c | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in c to a | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in b to a | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in a to b | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in b to f | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in f to b | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in c to a | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in a to c | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in d to c | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in c to f | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in f to c | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in d to c | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in c to d | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in d to e | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in e to d | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in e to d | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in d to e | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in e to g | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in g to e | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in f to c | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in c to f | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in f to b | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in b to f | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in f to h | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in h to f | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in g to e | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in e to g | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in g to h | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in h to g | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in h to f | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in f to h | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node east edfa in h to g | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| WARNING  gnpy.core.network:network.py  | ||||
| 	WARNING: target gain and power in node west edfa in g to h | ||||
| 	is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
| 	a power reduction of -1.82 is applied | ||||
|  | ||||
| @@ -15,6 +15,7 @@ Transceiver trx_Stockholm | ||||
|   CD (ps/nm):                0.00 | ||||
|   PMD (ps):                  0.00 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.00 | ||||
| Roadm roadm_Stockholm | ||||
|   effective loss (dB):     22.00 | ||||
|   reference pch out (dBm): -20.00 | ||||
| @@ -64,7 +65,7 @@ Fiber          fiber (Stockholm → Norrköping)_(2/2) | ||||
|   (includes conn loss (dB) in: 0.00 out: 0.00) | ||||
|   (conn loss out includes EOL margin defined in eqpt_config.json) | ||||
|   reference pch out (dBm):     -14.33 | ||||
|   actual pch out (dBm):        -14.30 | ||||
|   actual pch out (dBm):        -14.29 | ||||
| Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2) | ||||
|   type_variety:           openroadm_mw_mw_preamp | ||||
|   effective gain(dB):     16.33 | ||||
| @@ -248,16 +249,17 @@ Roadm roadm_Gothenburg | ||||
|   reference pch out (dBm): -20.00 | ||||
|   actual pch out (dBm):    -20.00 | ||||
| Transceiver trx_Gothenburg | ||||
|   GSNR (0.1nm, dB):          18.90 | ||||
|   GSNR (signal bw, dB):      14.88 | ||||
|   GSNR (0.1nm, dB):          18.89 | ||||
|   GSNR (signal bw, dB):      14.86 | ||||
|   OSNR ASE (0.1nm, dB):      21.20 | ||||
|   OSNR ASE (signal bw, dB):  17.18 | ||||
|   CD (ps/nm):                8350.42 | ||||
|   PMD (ps):                  7.99 | ||||
|   PDL (dB):                  3.74 | ||||
|   Latency (ms):              2.45 | ||||
|  | ||||
| Transmission result for input power = 2.00 dBm: | ||||
|   Final GSNR (0.1 nm): [1;36;40m18.90 dB[0m | ||||
|   Final GSNR (0.1 nm): [1;36;40m18.89 dB[0m | ||||
|  | ||||
| (No source node specified: picked trx_Stockholm) | ||||
|  | ||||
|   | ||||
| @@ -15,6 +15,7 @@ Transceiver trx_Stockholm | ||||
|   CD (ps/nm):                0.00 | ||||
|   PMD (ps):                  0.00 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.00 | ||||
| Roadm roadm_Stockholm | ||||
|   effective loss (dB):     22.00 | ||||
|   reference pch out (dBm): -20.00 | ||||
| @@ -64,7 +65,7 @@ Fiber          fiber (Stockholm → Norrköping)_(2/2) | ||||
|   (includes conn loss (dB) in: 0.00 out: 0.00) | ||||
|   (conn loss out includes EOL margin defined in eqpt_config.json) | ||||
|   reference pch out (dBm):     -14.33 | ||||
|   actual pch out (dBm):        -14.30 | ||||
|   actual pch out (dBm):        -14.29 | ||||
| Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2) | ||||
|   type_variety:           openroadm_mw_mw_preamp_worstcase_ver5 | ||||
|   effective gain(dB):     16.33 | ||||
| @@ -248,16 +249,17 @@ Roadm roadm_Gothenburg | ||||
|   reference pch out (dBm): -20.00 | ||||
|   actual pch out (dBm):    -20.00 | ||||
| Transceiver trx_Gothenburg | ||||
|   GSNR (0.1nm, dB):          19.27 | ||||
|   GSNR (signal bw, dB):      15.24 | ||||
|   GSNR (0.1nm, dB):          19.25 | ||||
|   GSNR (signal bw, dB):      15.23 | ||||
|   OSNR ASE (0.1nm, dB):      21.84 | ||||
|   OSNR ASE (signal bw, dB):  17.82 | ||||
|   CD (ps/nm):                8350.42 | ||||
|   PMD (ps):                  7.99 | ||||
|   PDL (dB):                  3.74 | ||||
|   Latency (ms):              2.45 | ||||
|  | ||||
| Transmission result for input power = 2.00 dBm: | ||||
|   Final GSNR (0.1 nm): [1;36;40m19.27 dB[0m | ||||
|   Final GSNR (0.1 nm): [1;36;40m19.25 dB[0m | ||||
|  | ||||
| (No source node specified: picked trx_Stockholm) | ||||
|  | ||||
|   | ||||
| @@ -106,48 +106,13 @@ | ||||
| ] | ||||
| [1;34;40mComputing all paths with constraints[0m | ||||
| [1;34;40mPropagating on selected path[0m | ||||
| request 0 | ||||
| Computing path from trx Lorient_KMA to trx Vannes_KBE | ||||
| with path constraint: ['trx Lorient_KMA', 'trx Vannes_KBE'] | ||||
| Computed path (roadms):['roadm Lorient_KMA', 'roadm Vannes_KBE'] | ||||
|  | ||||
| request 1 | ||||
| Computing path from trx Brest_KLA to trx Vannes_KBE | ||||
| with path constraint: ['trx Brest_KLA', 'roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE', 'trx Vannes_KBE'] | ||||
| Computed path (roadms):['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE'] | ||||
|  | ||||
| request 3 | ||||
| Computing path from trx Lannion_CAS to trx Rennes_STA | ||||
| with path constraint: ['trx Lannion_CAS', 'trx Rennes_STA'] | ||||
| Computed path (roadms):['roadm Lannion_CAS', 'roadm Rennes_STA'] | ||||
|  | ||||
| request 4 | ||||
| Computing path from trx Rennes_STA to trx Lannion_CAS | ||||
| with path constraint: ['trx Rennes_STA', 'trx Lannion_CAS'] | ||||
| Computed path (roadms):['roadm Rennes_STA', 'roadm Vannes_KBE', 'roadm Lorient_KMA', 'roadm Lannion_CAS'] | ||||
|  | ||||
| request 5 | ||||
| Computing path from trx Rennes_STA to trx Lannion_CAS | ||||
| with path constraint: ['trx Rennes_STA', 'trx Lannion_CAS'] | ||||
| Computed path (roadms):['roadm Rennes_STA', 'roadm Lannion_CAS'] | ||||
|  | ||||
| request 7 | 6 | ||||
| Computing path from trx Lannion_CAS to trx Lorient_KMA | ||||
| with path constraint: ['trx Lannion_CAS', 'trx Lorient_KMA'] | ||||
| Computed path (roadms):['roadm Lannion_CAS', 'roadm Lorient_KMA'] | ||||
|  | ||||
| request 7b | ||||
| Computing path from trx Lannion_CAS to trx Lorient_KMA | ||||
| with path constraint: ['trx Lannion_CAS', 'trx Lorient_KMA'] | ||||
| Computed path (roadms):['roadm Lannion_CAS', 'roadm Lorient_KMA'] | ||||
|  | ||||
| [1;34;40mResult summary[0m | ||||
| req id   demand                                GSNR@bandwidth A-Z (Z-A)   GSNR@0.1nm A-Z (Z-A)        Receiver minOSNR               mode                    Gbit/s              nb of tsp pairs      N,M or blocking reason  | ||||
| 0       trx Lorient_KMA to trx Vannes_KBE :             24.83                    28.92                      14                     mode 1                   100.0                      1                     (-284,4)         | ||||
| 1       trx Brest_KLA to trx Vannes_KBE :               17.75                    21.83                      14                     mode 1                   200.0                      2                     (-272,8)         | ||||
| 3       trx Lannion_CAS to trx Rennes_STA :             22.21                    26.29                      13                     mode 1                    60.0                      1                     (-284,4)         | ||||
| 4       trx Rennes_STA to trx Lannion_CAS :             16.06                    23.29                      17                     mode 2                   150.0                      1                     (-258,6)         | ||||
| 5       trx Rennes_STA to trx Lannion_CAS :             20.31                    27.54                      17                     mode 2                    20.0                      1                     (-274,6)         | ||||
| 7 | 6   trx Lannion_CAS to trx Lorient_KMA :            19.52                    23.61                      14                     mode 1                   700.0                      7                    (-224,28)         | ||||
| 7b      trx Lannion_CAS to trx Lorient_KMA :            19.61                    23.69                      14                     mode 1                   400.0                      4                    (-172,24)         | ||||
| 0       trx Lorient_KMA to trx Vannes_KBE :             24.83                    28.92                      14                     mode 1                   100.0                      1                   ([-284],[4])       | ||||
| 1       trx Brest_KLA to trx Vannes_KBE :               17.74                    21.82                      14                     mode 1                   200.0                      2                   ([-272],[8])       | ||||
| 3       trx Lannion_CAS to trx Rennes_STA :             22.19                    26.28                      13                     mode 1                    60.0                      1                   ([-284],[4])       | ||||
| 4       trx Rennes_STA to trx Lannion_CAS :             16.06                    23.29                      17                     mode 2                   150.0                      1                   ([-258],[6])       | ||||
| 5       trx Rennes_STA to trx Lannion_CAS :              20.3                    27.53                      17                     mode 2                    20.0                      1                   ([-274],[6])       | ||||
| 7 | 6   trx Lannion_CAS to trx Lorient_KMA :            19.52                    23.61                      14                     mode 1                   700.0                      7                  ([-224],[28])       | ||||
| 7b      trx Lannion_CAS to trx Lorient_KMA :            19.61                    23.69                      14                     mode 1                   400.0                      4                  ([-172],[24])       | ||||
| [1;33;40mResult summary shows mean GSNR and OSNR (average over all channels)[0m | ||||
|   | ||||
							
								
								
									
										24
									
								
								tests/invocation/path_requests_run_CD_PMD_PDL_missing
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										24
									
								
								tests/invocation/path_requests_run_CD_PMD_PDL_missing
									
									
									
									
									
										Normal file
									
								
							| @@ -0,0 +1,24 @@ | ||||
| [1;34;40mList of disjunctions[0m | ||||
| [] | ||||
| [1;34;40mAggregating similar requests[0m | ||||
| [1;34;40mThe following services have been requested:[0m | ||||
| [PathRequest 0 | ||||
| 	source: 	trx Abilene | ||||
| 	destination:	trx Albany | ||||
| 	trx type:	Voyager | ||||
| 	trx mode:	mode 3 | ||||
| 	baud_rate:	44.0 Gbaud | ||||
| 	bit_rate:	300.0 Gb/s | ||||
| 	spacing:	62.50000000000001 GHz | ||||
| 	power:  	0.0 dBm | ||||
| 	nb channels: 	76 | ||||
| 	path_bandwidth: 	100.0 Gbit/s | ||||
| 	nodes-list:	[] | ||||
| 	loose-list:	[] | ||||
| ] | ||||
| [1;34;40mComputing all paths with constraints[0m | ||||
| [1;34;40mPropagating on selected path[0m | ||||
| [1;34;40mResult summary[0m | ||||
| req id   demand                       GSNR@bandwidth A-Z (Z-A)   GSNR@0.1nm A-Z (Z-A)        Receiver minOSNR               mode                    Gbit/s              nb of tsp pairs      N,M or blocking reason  | ||||
| 0       trx Abilene to trx Albany :             9.04                     14.5                      -                      mode 3                   100.0                      -                MODE_NOT_FEASIBLE     | ||||
| [1;33;40mResult summary shows mean GSNR and OSNR (average over all channels)[0m | ||||
| @@ -16,6 +16,7 @@ Transceiver trx Lannion_CAS | ||||
|   CD (ps/nm):                0.00 | ||||
|   PMD (ps):                  0.00 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.00 | ||||
| Roadm roadm Lannion_CAS | ||||
|   effective loss (dB):     20.00 | ||||
|   reference pch out (dBm): -20.00 | ||||
| @@ -85,12 +86,13 @@ Roadm roadm Lorient_KMA | ||||
|   actual pch out (dBm):    -20.00 | ||||
| Transceiver trx Lorient_KMA | ||||
|   GSNR (0.1nm, dB):          23.61 | ||||
|   GSNR (signal bw, dB):      19.52 | ||||
|   GSNR (signal bw, dB):      19.53 | ||||
|   OSNR ASE (0.1nm, dB):      23.89 | ||||
|   OSNR ASE (signal bw, dB):  19.81 | ||||
|   CD (ps/nm):                2171.00 | ||||
|   PMD (ps):                  0.46 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.64 | ||||
|  | ||||
| Transmission result for input power = 0.00 dBm: | ||||
|   Final GSNR (0.1 nm): [1;36;40m23.61 dB[0m | ||||
|   | ||||
| @@ -16,6 +16,7 @@ Transceiver trx Lannion_CAS | ||||
|   CD (ps/nm):                0.00 | ||||
|   PMD (ps):                  0.00 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.00 | ||||
| Roadm roadm Lannion_CAS | ||||
|   effective loss (dB):     20.00 | ||||
|   reference pch out (dBm): -20.00 | ||||
| @@ -84,79 +85,80 @@ Roadm roadm Lorient_KMA | ||||
|   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: 23.65, mode_2: 23.81 | ||||
|   GSNR (signal bw, dB):      mode_1: 19.57, mode_2: 16.72 | ||||
|   GSNR (0.1nm, dB):          mode_1: 23.66, mode_2: 23.81 | ||||
|   GSNR (signal bw, dB):      mode_1: 19.58, mode_2: 16.72 | ||||
|   OSNR ASE (0.1nm, dB):      mode_1: 23.91, mode_2: 23.87 | ||||
|   OSNR ASE (signal bw, dB):  mode_1: 19.83, mode_2: 16.78 | ||||
|   CD (ps/nm):                2171.00 | ||||
|   PMD (ps):                  0.46 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.64 | ||||
|  | ||||
| Transmission result for input power = 0.00 dBm: | ||||
|   Final GSNR (0.1 nm): [1;36;40m23.72 dB[0m | ||||
|  | ||||
| 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                 191.40000                    -20.04                       19.85                       33.30                       19.65 | ||||
|     2                 191.45000                    -20.04                       19.85                       32.70                       19.63 | ||||
|     3                 191.50000                    -20.04                       19.84                       32.45                       19.61 | ||||
|     4                 191.55000                    -20.04                       19.84                       32.29                       19.60 | ||||
|     5                 191.60000                    -20.04                       19.84                       32.18                       19.60 | ||||
|     6                 191.65000                    -20.04                       19.84                       32.10                       19.59 | ||||
|     7                 191.70000                    -20.04                       19.84                       32.03                       19.59 | ||||
|     8                 191.75000                    -20.04                       19.84                       31.98                       19.58 | ||||
|     9                 191.80000                    -20.04                       19.84                       31.93                       19.58 | ||||
|    10                 191.85000                    -20.04                       19.84                       31.90                       19.57 | ||||
|    11                 191.90000                    -20.04                       19.84                       31.86                       19.57 | ||||
|    12                 191.95000                    -20.04                       19.84                       31.84                       19.57 | ||||
|    13                 192.00000                    -20.04                       19.83                       31.82                       19.57 | ||||
|    14                 192.05000                    -20.04                       19.83                       31.80                       19.57 | ||||
|    15                 192.10000                    -20.04                       19.83                       31.78                       19.56 | ||||
|    16                 192.15000                    -20.04                       19.83                       31.77                       19.56 | ||||
|    17                 192.20000                    -20.04                       19.83                       31.76                       19.56 | ||||
|    18                 192.25000                    -20.04                       19.83                       31.75                       19.56 | ||||
|    19                 192.30000                    -20.04                       19.83                       31.75                       19.56 | ||||
|    20                 192.35000                    -20.04                       19.83                       31.75                       19.56 | ||||
|    21                 192.40000                    -20.05                       19.83                       31.75                       19.56 | ||||
|    22                 192.45000                    -20.05                       19.82                       31.75                       19.55 | ||||
|    23                 192.50000                    -20.05                       19.82                       31.76                       19.55 | ||||
|    24                 192.55000                    -20.05                       19.82                       31.76                       19.55 | ||||
|    25                 192.60000                    -20.05                       19.82                       31.78                       19.55 | ||||
|    26                 192.65000                    -20.05                       19.82                       31.79                       19.55 | ||||
|    27                 192.70000                    -20.05                       19.82                       31.81                       19.55 | ||||
|    28                 192.75000                    -20.05                       19.82                       31.83                       19.55 | ||||
|    29                 192.80000                    -20.05                       19.82                       31.86                       19.55 | ||||
|    30                 192.85000                    -20.05                       19.82                       31.90                       19.56 | ||||
|    31                 192.90000                    -20.04                       19.82                       31.95                       19.56 | ||||
|    32                 192.95000                    -20.04                       19.81                       32.02                       19.56 | ||||
|    33                 193.00000                    -20.04                       19.81                       32.11                       19.56 | ||||
|    34                 193.05000                    -20.04                       19.81                       32.27                       19.57 | ||||
|    35                 193.10000                    -20.04                       19.81                       32.61                       19.59 | ||||
|    36                 193.16250                    -20.09                       16.80                       33.70                       16.71 | ||||
|    37                 193.23750                    -20.09                       16.80                       34.20                       16.72 | ||||
|    38                 193.31250                    -20.09                       16.80                       34.45                       16.72 | ||||
|    39                 193.38750                    -20.09                       16.79                       34.62                       16.72 | ||||
|     1                 191.40000                    -20.04                       19.85                       33.52                       19.66 | ||||
|     2                 191.45000                    -20.04                       19.85                       32.93                       19.64 | ||||
|     3                 191.50000                    -20.04                       19.84                       32.67                       19.62 | ||||
|     4                 191.55000                    -20.04                       19.84                       32.50                       19.61 | ||||
|     5                 191.60000                    -20.04                       19.84                       32.39                       19.61 | ||||
|     6                 191.65000                    -20.04                       19.84                       32.30                       19.60 | ||||
|     7                 191.70000                    -20.04                       19.84                       32.22                       19.60 | ||||
|     8                 191.75000                    -20.04                       19.84                       32.16                       19.59 | ||||
|     9                 191.80000                    -20.04                       19.84                       32.11                       19.59 | ||||
|    10                 191.85000                    -20.04                       19.84                       32.07                       19.59 | ||||
|    11                 191.90000                    -20.04                       19.84                       32.04                       19.58 | ||||
|    12                 191.95000                    -20.04                       19.84                       32.00                       19.58 | ||||
|    13                 192.00000                    -20.04                       19.83                       31.98                       19.58 | ||||
|    14                 192.05000                    -20.04                       19.83                       31.95                       19.57 | ||||
|    15                 192.10000                    -20.04                       19.83                       31.93                       19.57 | ||||
|    16                 192.15000                    -20.04                       19.83                       31.91                       19.57 | ||||
|    17                 192.20000                    -20.04                       19.83                       31.90                       19.57 | ||||
|    18                 192.25000                    -20.04                       19.83                       31.88                       19.57 | ||||
|    19                 192.30000                    -20.04                       19.83                       31.87                       19.56 | ||||
|    20                 192.35000                    -20.04                       19.83                       31.87                       19.56 | ||||
|    21                 192.40000                    -20.04                       19.83                       31.86                       19.56 | ||||
|    22                 192.45000                    -20.04                       19.82                       31.86                       19.56 | ||||
|    23                 192.50000                    -20.04                       19.82                       31.86                       19.56 | ||||
|    24                 192.55000                    -20.04                       19.82                       31.86                       19.56 | ||||
|    25                 192.60000                    -20.04                       19.82                       31.87                       19.56 | ||||
|    26                 192.65000                    -20.04                       19.82                       31.88                       19.56 | ||||
|    27                 192.70000                    -20.04                       19.82                       31.89                       19.56 | ||||
|    28                 192.75000                    -20.04                       19.82                       31.91                       19.56 | ||||
|    29                 192.80000                    -20.04                       19.82                       31.93                       19.56 | ||||
|    30                 192.85000                    -20.04                       19.82                       31.97                       19.56 | ||||
|    31                 192.90000                    -20.04                       19.82                       32.01                       19.56 | ||||
|    32                 192.95000                    -20.04                       19.81                       32.07                       19.56 | ||||
|    33                 193.00000                    -20.04                       19.81                       32.16                       19.57 | ||||
|    34                 193.05000                    -20.04                       19.81                       32.31                       19.57 | ||||
|    35                 193.10000                    -20.04                       19.81                       32.65                       19.59 | ||||
|    36                 193.16250                    -20.09                       16.80                       33.73                       16.71 | ||||
|    37                 193.23750                    -20.09                       16.80                       34.22                       16.72 | ||||
|    38                 193.31250                    -20.09                       16.80                       34.47                       16.72 | ||||
|    39                 193.38750                    -20.09                       16.79                       34.63                       16.72 | ||||
|    40                 193.46250                    -20.09                       16.79                       34.75                       16.72 | ||||
|    41                 193.53750                    -20.09                       16.79                       34.85                       16.72 | ||||
|    42                 193.61250                    -20.09                       16.79                       34.94                       16.72 | ||||
|    43                 193.68750                    -20.09                       16.79                       35.02                       16.72 | ||||
|    44                 193.76250                    -20.09                       16.79                       35.08                       16.72 | ||||
|    45                 193.83750                    -20.09                       16.78                       35.15                       16.72 | ||||
|    46                 193.91250                    -20.09                       16.78                       35.20                       16.72 | ||||
|    47                 193.98750                    -20.09                       16.78                       35.26                       16.72 | ||||
|    48                 194.06250                    -20.09                       16.78                       35.31                       16.72 | ||||
|    49                 194.13750                    -20.09                       16.78                       35.36                       16.72 | ||||
|    50                 194.21250                    -20.09                       16.78                       35.41                       16.72 | ||||
|    51                 194.28750                    -20.09                       16.78                       35.47                       16.72 | ||||
|    52                 194.36250                    -20.09                       16.77                       35.52                       16.72 | ||||
|    53                 194.43750                    -20.09                       16.77                       35.58                       16.72 | ||||
|    54                 194.51250                    -20.09                       16.77                       35.65                       16.71 | ||||
|    55                 194.58750                    -20.09                       16.77                       35.72                       16.71 | ||||
|    56                 194.66250                    -20.09                       16.77                       35.81                       16.71 | ||||
|    57                 194.73750                    -20.09                       16.77                       35.92                       16.71 | ||||
|    58                 194.81250                    -20.09                       16.76                       36.06                       16.71 | ||||
|    59                 194.88750                    -20.09                       16.76                       36.27                       16.71 | ||||
|    60                 194.96250                    -20.09                       16.76                       36.75                       16.72 | ||||
|    41                 193.53750                    -20.09                       16.79                       34.84                       16.72 | ||||
|    42                 193.61250                    -20.09                       16.79                       34.92                       16.72 | ||||
|    43                 193.68750                    -20.09                       16.79                       34.99                       16.72 | ||||
|    44                 193.76250                    -20.09                       16.79                       35.04                       16.72 | ||||
|    45                 193.83750                    -20.09                       16.78                       35.10                       16.72 | ||||
|    46                 193.91250                    -20.09                       16.78                       35.15                       16.72 | ||||
|    47                 193.98750                    -20.09                       16.78                       35.19                       16.72 | ||||
|    48                 194.06250                    -20.09                       16.78                       35.24                       16.72 | ||||
|    49                 194.13750                    -20.09                       16.78                       35.28                       16.72 | ||||
|    50                 194.21250                    -20.09                       16.78                       35.33                       16.72 | ||||
|    51                 194.28750                    -20.09                       16.78                       35.37                       16.72 | ||||
|    52                 194.36250                    -20.09                       16.77                       35.42                       16.72 | ||||
|    53                 194.43750                    -20.09                       16.77                       35.47                       16.71 | ||||
|    54                 194.51250                    -20.09                       16.77                       35.53                       16.71 | ||||
|    55                 194.58750                    -20.09                       16.77                       35.59                       16.71 | ||||
|    56                 194.66250                    -20.09                       16.77                       35.67                       16.71 | ||||
|    57                 194.73750                    -20.09                       16.77                       35.77                       16.71 | ||||
|    58                 194.81250                    -20.09                       16.76                       35.90                       16.71 | ||||
|    59                 194.88750                    -20.09                       16.76                       36.11                       16.71 | ||||
|    60                 194.96250                    -20.09                       16.76                       36.58                       16.72 | ||||
|  | ||||
| (No source node specified: picked trx Lannion_CAS) | ||||
|  | ||||
|   | ||||
| @@ -15,6 +15,7 @@ Transceiver Site_A | ||||
|   CD (ps/nm):                0.00 | ||||
|   PMD (ps):                  0.00 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.00 | ||||
| Fiber          Span1 | ||||
|   type_variety:                SSMF | ||||
|   length (km):                 80.00 | ||||
| @@ -39,16 +40,17 @@ Edfa Edfa1 | ||||
|   actual pch out (dBm):   -1.99 | ||||
|   output VOA (dB):        0.00 | ||||
| Transceiver Site_B | ||||
|   GSNR (0.1nm, dB):          31.17 | ||||
|   GSNR (signal bw, dB):      27.09 | ||||
|   GSNR (0.1nm, dB):          31.18 | ||||
|   GSNR (signal bw, dB):      27.10 | ||||
|   OSNR ASE (0.1nm, dB):      33.30 | ||||
|   OSNR ASE (signal bw, dB):  29.21 | ||||
|   CD (ps/nm):                1336.00 | ||||
|   PMD (ps):                  0.36 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.39 | ||||
|  | ||||
| Transmission result for input power = 0.00 dBm: | ||||
|   Final GSNR (0.1 nm): [1;36;40m31.17 dB[0m | ||||
|   Final GSNR (0.1 nm): [1;36;40m31.18 dB[0m | ||||
|  | ||||
| (No source node specified: picked Site_A) | ||||
|  | ||||
|   | ||||
| @@ -15,6 +15,7 @@ Transceiver Site_A | ||||
|   CD (ps/nm):                0.00 | ||||
|   PMD (ps):                  0.00 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.00 | ||||
| RamanFiber          Span1 | ||||
|   type_variety:                SSMF | ||||
|   length (km):                 80.00 | ||||
| @@ -22,18 +23,18 @@ RamanFiber          Span1 | ||||
|   total loss (dB):             17.00 | ||||
|   (includes conn loss (dB) in: 0.50 out: 0.50) | ||||
|   (conn loss out includes EOL margin defined in eqpt_config.json) | ||||
|   reference pch out (dBm):     -7.77 | ||||
|   actual pch out (dBm):        -8.03 | ||||
|   reference pch out (dBm):     -7.20 | ||||
|   actual pch out (dBm):        -7.47 | ||||
| Fused Fused1 | ||||
|   loss (dB): 0.00 | ||||
| Edfa Edfa1 | ||||
|   type_variety:           std_low_gain | ||||
|   effective gain(dB):     5.77 | ||||
|   effective gain(dB):     5.20 | ||||
|   (before att_in and before output VOA) | ||||
|   noise figure (dB):      13.23 | ||||
|   noise figure (dB):      13.80 | ||||
|   (including att_in) | ||||
|   pad att_in (dB):        2.23 | ||||
|   Power In (dBm):         11.04 | ||||
|   pad att_in (dB):        2.80 | ||||
|   Power In (dBm):         11.61 | ||||
|   Power Out (dBm):        16.81 | ||||
|   Delta_P (dB):           -2.00 | ||||
|   target pch (dBm):       -2.00 | ||||
| @@ -41,95 +42,96 @@ Edfa Edfa1 | ||||
|   actual pch out (dBm):   -2.26 | ||||
|   output VOA (dB):        0.00 | ||||
| Transceiver Site_B | ||||
|   GSNR (0.1nm, dB):          31.44 | ||||
|   GSNR (signal bw, dB):      27.36 | ||||
|   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 | ||||
|   CD (ps/nm):                1336.00 | ||||
|   PMD (ps):                  0.36 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.39 | ||||
|  | ||||
| Transmission result for input power = 0.00 dBm: | ||||
|   Final GSNR (0.1 nm): [1;36;40m31.44 dB[0m | ||||
|   Final GSNR (0.1 nm): [1;36;40m31.42 dB[0m | ||||
|  | ||||
| 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                      0.21                       31.62                       31.43                       28.52 | ||||
|     2                 191.40000                      0.17                       31.60                       31.35                       28.46 | ||||
|     3                 191.45000                      0.13                       31.58                       31.26                       28.41 | ||||
|     4                 191.50000                      0.09                       31.56                       31.18                       28.36 | ||||
|     5                 191.55000                      0.03                       31.53                       31.10                       28.30 | ||||
|     6                 191.60000                     -0.02                       31.50                       31.02                       28.24 | ||||
|     7                 191.65000                     -0.08                       31.46                       30.94                       28.19 | ||||
|     8                 191.70000                     -0.14                       31.43                       30.87                       28.13 | ||||
|     9                 191.75000                     -0.20                       31.40                       30.79                       28.08 | ||||
|    10                 191.80000                     -0.27                       31.37                       30.72                       28.02 | ||||
|    11                 191.85000                     -0.33                       31.33                       30.65                       27.97 | ||||
|    12                 191.90000                     -0.40                       31.29                       30.58                       27.91 | ||||
|    13                 191.95000                     -0.46                       31.26                       30.51                       27.86 | ||||
|    14                 192.00000                     -0.53                       31.22                       30.44                       27.80 | ||||
|    15                 192.05000                     -0.59                       31.18                       30.37                       27.75 | ||||
|    16                 192.10000                     -0.66                       31.15                       30.30                       27.69 | ||||
|    17                 192.15000                     -0.73                       31.11                       30.24                       27.64 | ||||
|    18                 192.20000                     -0.80                       31.07                       30.17                       27.59 | ||||
|    19                 192.25000                     -0.86                       31.03                       30.18                       27.57 | ||||
|    20                 192.30000                     -0.94                       30.99                       30.19                       27.56 | ||||
|    21                 192.35000                     -1.02                       30.94                       30.20                       27.54 | ||||
|    22                 192.40000                     -1.09                       30.90                       30.20                       27.53 | ||||
|    23                 192.45000                     -1.17                       30.86                       30.21                       27.51 | ||||
|    24                 192.50000                     -1.24                       30.81                       30.22                       27.50 | ||||
|    25                 192.55000                     -1.31                       30.77                       30.23                       27.48 | ||||
|    26                 192.60000                     -1.38                       30.73                       30.23                       27.46 | ||||
|    27                 192.65000                     -1.45                       30.69                       30.24                       27.45 | ||||
|    28                 192.70000                     -1.52                       30.65                       30.25                       27.43 | ||||
|    29                 192.75000                     -1.59                       30.60                       30.26                       27.42 | ||||
|    30                 192.80000                     -1.67                       30.56                       30.27                       27.40 | ||||
|    31                 192.85000                     -1.74                       30.52                       30.27                       27.38 | ||||
|    32                 192.90000                     -1.81                       30.47                       30.28                       27.37 | ||||
|    33                 192.95000                     -1.88                       30.43                       30.29                       27.35 | ||||
|    34                 193.00000                     -1.95                       30.39                       30.30                       27.33 | ||||
|    35                 193.05000                     -2.02                       30.34                       30.30                       27.31 | ||||
|    36                 193.10000                     -2.08                       30.30                       30.31                       27.30 | ||||
|    37                 193.15000                     -2.15                       30.26                       30.32                       27.28 | ||||
|    38                 193.20000                     -2.22                       30.21                       30.34                       27.26 | ||||
|    39                 193.25000                     -2.29                       30.17                       30.36                       27.25 | ||||
|    40                 193.30000                     -2.36                       30.13                       30.37                       27.24 | ||||
|    41                 193.35000                     -2.43                       30.08                       30.39                       27.22 | ||||
|    42                 193.40000                     -2.50                       30.04                       30.41                       27.21 | ||||
|    43                 193.45000                     -2.56                       29.99                       30.43                       27.19 | ||||
|    44                 193.50000                     -2.63                       29.95                       30.44                       27.18 | ||||
|    45                 193.55000                     -2.70                       29.90                       30.46                       27.16 | ||||
|    46                 193.60000                     -2.78                       29.85                       30.48                       27.15 | ||||
|    47                 193.65000                     -2.85                       29.80                       30.50                       27.13 | ||||
|    48                 193.70000                     -2.92                       29.76                       30.52                       27.11 | ||||
|    49                 193.75000                     -2.99                       29.71                       30.54                       27.09 | ||||
|    50                 193.80000                     -3.06                       29.66                       30.55                       27.07 | ||||
|    51                 193.85000                     -3.14                       29.61                       30.57                       27.06 | ||||
|    52                 193.90000                     -3.21                       29.56                       30.59                       27.04 | ||||
|    53                 193.95000                     -3.28                       29.52                       30.61                       27.02 | ||||
|    54                 194.00000                     -3.35                       29.47                       30.63                       27.00 | ||||
|    55                 194.05000                     -3.42                       29.42                       30.65                       26.98 | ||||
|    56                 194.10000                     -3.50                       29.37                       30.67                       26.96 | ||||
|    57                 194.15000                     -3.57                       29.32                       30.72                       26.95 | ||||
|    58                 194.20000                     -3.64                       29.26                       30.78                       26.95 | ||||
|    59                 194.25000                     -3.72                       29.21                       30.84                       26.94 | ||||
|    60                 194.30000                     -3.79                       29.16                       30.90                       26.94 | ||||
|    61                 194.35000                     -3.86                       29.11                       30.96                       26.93 | ||||
|    62                 194.40000                     -3.93                       29.06                       31.02                       26.92 | ||||
|    63                 194.45000                     -4.01                       29.01                       31.09                       26.91 | ||||
|    64                 194.50000                     -4.08                       28.96                       31.15                       26.91 | ||||
|    65                 194.55000                     -4.14                       28.91                       31.21                       26.90 | ||||
|    66                 194.60000                     -4.21                       28.86                       31.28                       26.90 | ||||
|    67                 194.65000                     -4.27                       28.82                       31.34                       26.89 | ||||
|    68                 194.70000                     -4.34                       28.77                       31.41                       26.88 | ||||
|    69                 194.75000                     -4.41                       28.72                       31.48                       26.88 | ||||
|    70                 194.80000                     -4.47                       28.67                       31.55                       26.87 | ||||
|    71                 194.85000                     -4.54                       28.63                       31.62                       26.86 | ||||
|    72                 194.90000                     -4.60                       28.58                       31.69                       26.85 | ||||
|    73                 194.95000                     -4.67                       28.53                       31.76                       26.84 | ||||
|    74                 195.00000                     -4.73                       28.48                       31.84                       26.83 | ||||
|    75                 195.05000                     -4.80                       28.43                       31.91                       26.82 | ||||
|    76                 195.10000                     -4.86                       28.38                       31.91                       26.79 | ||||
|     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 | ||||
|  | ||||
| (No source node specified: picked Site_A) | ||||
|  | ||||
|   | ||||
| @@ -15,6 +15,7 @@ Transceiver Site_A | ||||
|   CD (ps/nm):                0.00 | ||||
|   PMD (ps):                  0.00 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.00 | ||||
| Roadm roadm Site A | ||||
|   effective loss (dB):     20.00 | ||||
|   reference pch out (dBm): -20.00 | ||||
| @@ -182,7 +183,7 @@ Edfa Edfa6 | ||||
|   noise figure (dB):      9.00 | ||||
|   (including att_in) | ||||
|   pad att_in (dB):        4.00 | ||||
|   Power In (dBm):         3.83 | ||||
|   Power In (dBm):         3.84 | ||||
|   Power Out (dBm):        19.84 | ||||
|   Delta_P (dB):           0.00 | ||||
|   target pch (dBm):       0.00 | ||||
| @@ -437,16 +438,17 @@ Roadm roadm Site B | ||||
|   reference pch out (dBm): -20.00 | ||||
|   actual pch out (dBm):    -20.00 | ||||
| Transceiver Site_B | ||||
|   GSNR (0.1nm, dB):          17.85 | ||||
|   GSNR (signal bw, dB):      13.77 | ||||
|   GSNR (0.1nm, dB):          17.84 | ||||
|   GSNR (signal bw, dB):      13.76 | ||||
|   OSNR ASE (0.1nm, dB):      19.70 | ||||
|   OSNR ASE (signal bw, dB):  15.62 | ||||
|   CD (ps/nm):                20040.00 | ||||
|   PMD (ps):                  1.39 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              5.88 | ||||
|  | ||||
| Transmission result for input power = 0.00 dBm: | ||||
|   Final GSNR (0.1 nm): [1;36;40m17.85 dB[0m | ||||
|   Final GSNR (0.1 nm): [1;36;40m17.84 dB[0m | ||||
|  | ||||
| (No source node specified: picked Site_A) | ||||
|  | ||||
|   | ||||
| @@ -1,242 +1,6 @@ | ||||
| There are 96 channels propagating | ||||
| Power mode is set to True | ||||
| => it can be modified in eqpt_config.json - Span | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Lorient_KMA to Loudeac | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING[0m: WARNING: effective gain in Node east edfa in Lannion_CAS to Stbrieuc is above user specified amplifier std_low_gain | ||||
| max flat gain: 16dB ; required gain: 23.0dB. Please check amplifier type. | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Rennes_STA to Stbrieuc | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING[0m: WARNING: effective gain in Node east edfa in Lannion_CAS to Morlaix is above user specified amplifier std_low_gain | ||||
| max flat gain: 16dB ; required gain: 23.5dB. Please check amplifier type. | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Brest_KLA to Morlaix | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Lorient_KMA to Loudeac | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING[0m: WARNING: effective gain in Node west edfa in Lannion_CAS to Corlay is above user specified amplifier test | ||||
| max flat gain: 25dB ; required gain: 29.82dB. Please check amplifier type. | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Lorient_KMA to Vannes_KBE | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Vannes_KBE to Lorient_KMA | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Lorient_KMA to Quimper | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Quimper to Lorient_KMA | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Brest_KLA to Quimper | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Vannes_KBE to Lorient_KMA | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Lorient_KMA to Vannes_KBE | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Vannes_KBE to Ploermel | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Ploermel to Vannes_KBE | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Rennes_STA to Ploermel | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Rennes_STA to Stbrieuc | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Stbrieuc to Rennes_STA | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Lannion_CAS to Stbrieuc | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Rennes_STA to Ploermel | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Vannes_KBE to Ploermel | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Brest_KLA to Morlaix | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING[0m: WARNING: effective gain in Node east edfa in Brest_KLA to Quimper is above user specified amplifier std_low_gain | ||||
| max flat gain: 16dB ; required gain: 23.0dB. Please check amplifier type. | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in Quimper to Lorient_KMA | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in Lorient_KMA to Quimper | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in a to b | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in b to a | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in a to c | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in c to a | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in b to a | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in a to b | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in b to f | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in f to b | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in c to a | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in a to c | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in d to c | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in c to f | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in f to c | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in d to c | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in c to d | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in d to e | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in e to d | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in e to d | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in d to e | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in e to g | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in g to e | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in f to c | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in c to f | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in f to b | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in b to f | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in f to h | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in h to f | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in g to e | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in e to g | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in g to h | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in h to g | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in h to f | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in f to h | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node east edfa in h to g | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
| [1;31;40mWARNING:[0m target gain and power in node west edfa in g to h | ||||
|      is beyond all available amplifiers capabilities and/or extended_gain_range: | ||||
|     a power reduction of -1.82 is applied | ||||
|  | ||||
|  | ||||
| There are 3 fiber spans over 130 km between trx Lannion_CAS and trx Lorient_KMA | ||||
|  | ||||
| @@ -251,6 +15,7 @@ Transceiver trx Lannion_CAS | ||||
|   CD (ps/nm):                0.00 | ||||
|   PMD (ps):                  0.00 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.00 | ||||
| Roadm roadm Lannion_CAS | ||||
|   effective loss (dB):     23.00 | ||||
|   reference pch out (dBm): -20.00 | ||||
| @@ -319,16 +84,17 @@ Roadm roadm Lorient_KMA | ||||
|   reference pch out (dBm): -20.00 | ||||
|   actual pch out (dBm):    -20.00 | ||||
| Transceiver trx Lorient_KMA | ||||
|   GSNR (0.1nm, dB):          23.94 | ||||
|   GSNR (0.1nm, dB):          23.93 | ||||
|   GSNR (signal bw, dB):      19.85 | ||||
|   OSNR ASE (0.1nm, dB):      24.29 | ||||
|   OSNR ASE (signal bw, dB):  20.20 | ||||
|   CD (ps/nm):                2171.00 | ||||
|   PMD (ps):                  0.46 | ||||
|   PDL (dB):                  0.00 | ||||
|   Latency (ms):              0.64 | ||||
|  | ||||
| Transmission result for input power = 3.00 dBm: | ||||
|   Final GSNR (0.1 nm): [1;36;40m23.94 dB[0m | ||||
|   Final GSNR (0.1 nm): [1;36;40m23.93 dB[0m | ||||
|  | ||||
| (Invalid source node 'lannion' replaced with trx Lannion_CAS) | ||||
|  | ||||
|   | ||||
| @@ -1,6 +1,7 @@ | ||||
| build>=0.10.0,<1 | ||||
| pytest>=6.2.5,<7 | ||||
| pandas>=1.3.5,<2 | ||||
| build>=1.0.3,<2 | ||||
| pytest>=7.4.3,<8 | ||||
| # pandas 2.1 removed support for Python 3.8 | ||||
| pandas>=2.0.3,<3 | ||||
|  | ||||
| # flake v6 killed the --diff option | ||||
| flake8>=5.0.4,<6 | ||||
|   | ||||
| @@ -115,7 +115,7 @@ def test_si(si, nch_and_spacing): | ||||
|  | ||||
| @pytest.mark.parametrize("gain", [17, 19, 21, 23]) | ||||
| def test_compare_nf_models(gain, setup_edfa_variable_gain, si): | ||||
|     """ compare the 2 amplifier models (polynomial and estimated from nf_min and max) | ||||
|     """compare the 2 amplifier models (polynomial and estimated from nf_min and max) | ||||
|      => nf_model vs nf_poly_fit for intermediate gain values: | ||||
|      between gain_min and gain_flatmax some discrepancy is expected but target < 0.5dB | ||||
|      => unitary test for Edfa._calc_nf (and Edfa.interpol_params)""" | ||||
|   | ||||
| @@ -4,12 +4,12 @@ | ||||
| # License: BSD 3-Clause Licence | ||||
| # Copyright (c) 2018, Telecom Infra Project | ||||
|  | ||||
| ''' | ||||
| """ | ||||
| @author: esther.lerouzic | ||||
| checks that computed paths are disjoint as specified in the json service file | ||||
| that computed paths do not loop | ||||
| that include node constraints are correctly taken into account | ||||
| ''' | ||||
| """ | ||||
|  | ||||
| from pathlib import Path | ||||
| import pytest | ||||
| @@ -19,7 +19,7 @@ from gnpy.core.exceptions import ServiceError, DisjunctionError | ||||
| from gnpy.core.utils import automatic_nch, lin2db | ||||
| from gnpy.core.elements import Roadm | ||||
| from gnpy.topology.request import (compute_path_dsjctn, isdisjoint, find_reversed_path, PathRequest, | ||||
|                                    correct_json_route_list) | ||||
|                                    correct_json_route_list, requests_aggregation, Disjunction) | ||||
| from gnpy.topology.spectrum_assignment import build_oms_list | ||||
| from gnpy.tools.json_io import requests_from_json, load_requests, load_network, load_equipment, disjunctions_from_json | ||||
|  | ||||
| @@ -31,8 +31,7 @@ EQPT_LIBRARY_NAME = Path(__file__).parent.parent / 'tests/data/eqpt_config.json' | ||||
|  | ||||
| @pytest.fixture() | ||||
| def serv(test_setup): | ||||
|     ''' common setup for service list | ||||
|     ''' | ||||
|     """common setup for service list""" | ||||
|     network, equipment = test_setup | ||||
|     data = load_requests(SERVICE_FILE_NAME, equipment, bidir=False, network=network, network_filename=NETWORK_FILE_NAME) | ||||
|     rqs = requests_from_json(data, equipment) | ||||
| @@ -43,8 +42,7 @@ def serv(test_setup): | ||||
|  | ||||
| @pytest.fixture() | ||||
| def test_setup(): | ||||
|     ''' common setup for tests: builds network, equipment and oms only once | ||||
|     ''' | ||||
|     """common setup for tests: builds network, equipment and oms only once""" | ||||
|     equipment = load_equipment(EQPT_LIBRARY_NAME) | ||||
|     network = load_network(NETWORK_FILE_NAME, equipment) | ||||
|     # Build the network once using the default power defined in SI in eqpt config | ||||
| @@ -61,9 +59,10 @@ def test_setup(): | ||||
|  | ||||
|  | ||||
| def test_disjunction(serv): | ||||
|     ''' service_file contains sevaral combination of disjunction constraint. The test checks | ||||
|         that computed paths with disjunction constraint are effectively disjoint | ||||
|     ''' | ||||
|     """service_file contains sevaral combination of disjunction constraint | ||||
|  | ||||
|     The test checks that computed paths with disjunction constraint are effectively disjoint. | ||||
|     """ | ||||
|     network, equipment, rqs, dsjn = serv | ||||
|     pths = compute_path_dsjctn(network, equipment, rqs, dsjn) | ||||
|     print(dsjn) | ||||
| @@ -86,8 +85,7 @@ def test_disjunction(serv): | ||||
|  | ||||
|  | ||||
| def test_does_not_loop_back(serv): | ||||
|     ''' check that computed paths do not loop back ie each element appears only once | ||||
|     ''' | ||||
|     """check that computed paths do not loop back ie each element appears only once""" | ||||
|     network, equipment, rqs, dsjn = serv | ||||
|     pths = compute_path_dsjctn(network, equipment, rqs, dsjn) | ||||
|     test = True | ||||
| @@ -108,8 +106,7 @@ def test_does_not_loop_back(serv): | ||||
|  | ||||
|  | ||||
| def create_rq(equipment, srce, dest, bdir, node_list, loose_list, rqid='test_request'): | ||||
|     ''' create the usual request list according to parameters | ||||
|     ''' | ||||
|     """create the usual request list according to parameters""" | ||||
|     requests_list = [] | ||||
|     params = { | ||||
|         'request_id': rqid, | ||||
| @@ -151,7 +148,8 @@ def create_rq(equipment, srce, dest, bdir, node_list, loose_list, rqid='test_req | ||||
|     ['trx a', 'trx h', 'pass', 'found_path', ['trx h'], ['STRICT']], | ||||
|     ['trx a', 'trx h', 'pass', 'found_path', ['roadm a'], ['STRICT']]]) | ||||
| def test_include_constraints(test_setup, srce, dest, result, pth, node_list, loose_list): | ||||
|     ''' check that all combinations of constraints are correctly handled: | ||||
|     """check that all combinations of constraints are correctly handled: | ||||
|  | ||||
|     - STRICT/LOOSE | ||||
|     - correct names/incorrect names -> pass/fail | ||||
|     - possible include/impossible include | ||||
| @@ -163,7 +161,7 @@ def test_include_constraints(test_setup, srce, dest, result, pth, node_list, loo | ||||
|                             | cannot be applied | no_path           | found_path | ||||
|         ---------------------------------------------------------------------------------- | ||||
|         0                   |                   |          computation stops | ||||
|     ''' | ||||
|     """ | ||||
|     network, equipment = test_setup | ||||
|     dsjn = [] | ||||
|     bdir = False | ||||
| @@ -201,7 +199,7 @@ def test_include_constraints(test_setup, srce, dest, result, pth, node_list, loo | ||||
|       ['roadm c', 'roadm f'], | ||||
|       ['roadm a', 'roadm b', 'roadm f', 'roadm h']]]]) | ||||
| def test_create_disjunction(test_setup, dis1, dis2, node_list1, loose_list1, result, expected_paths): | ||||
|     """ verifies that the expected result is obtained for a set of particular constraints: | ||||
|     """verifies that the expected result is obtained for a set of particular constraints: | ||||
|     in particular, verifies that: | ||||
|     - multiple disjunction constraints are correcly handled | ||||
|     - in case a loose constraint can not be met, the first alternate candidate is selected | ||||
| @@ -242,3 +240,91 @@ def test_create_disjunction(test_setup, dis1, dis2, node_list1, loose_list1, res | ||||
|             path_names.append(roadm_names) | ||||
|         assert path_names == expected_paths | ||||
|         # if loose, one path can be returned | ||||
|  | ||||
|  | ||||
| @pytest.fixture() | ||||
| def request_set(): | ||||
|     """ creates default request dict | ||||
|     """ | ||||
|     return { | ||||
|         # 'request_id': '0', | ||||
|         'source': 'trx a', | ||||
|         'bidir': False, | ||||
|         'destination': 'trx g', | ||||
|         'trx_type': 'Voyager', | ||||
|         'spacing': 50e9, | ||||
|         'nodes_list': [], | ||||
|         'loose_list': [], | ||||
|         'f_min': 191.1e12, | ||||
|         'f_max': 196.3e12, | ||||
|         'nb_channel': None, | ||||
|         'power': 0, | ||||
|         'path_bandwidth': 200e9} | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize( | ||||
|     'ids, modes, req_n, req_m, disjunction, final_ids, final_ns, final_ms, final_path_bandwidths', | ||||
|     # requests that should be correctly aggregated: | ||||
|     [(['a', 'b', 'c', 'd'], ['mode 1', 'mode 1', 'mode 1', 'mode 1'], | ||||
|       [[0], [16], [32], [48]], [[8], [8], [8], [8]], [[]], | ||||
|       ['d | c | b | a'], [[48, 32, 16, 0]], [[8, 8, 8, 8]], [800e9]), | ||||
|      (['a', 'b', 'c', 'd'], ['mode 1', 'mode 1', 'mode 1', 'mode 1'], | ||||
|       [[0, 8], [16, 24], [32, 40], [48]], [[4, 4], [4, 4], [4, 4], [8]], [[]], | ||||
|       ['d | c | b | a'], [[48, 32, 40, 16, 24, 0, 8]], [[8, 4, 4, 4, 4, 4, 4]], [800e9]), | ||||
|      (['a', 'b', 'c', 'd'], ['mode 1', 'mode 1', 'mode 1', 'mode 1'], | ||||
|       [[0, 8], [None, 24], [32, 40], [None]], [[4, 4], [4, 4], [4, 4], [None]], [[]], | ||||
|       ['d | c | b | a'], [[None, 32, 40, None, 24, 0, 8]], [[None, 4, 4, 4, 4, 4, 4]], [800e9]), | ||||
|      # 'a' and 'b' have same constraint and can be aggregated | ||||
|      (['a', 'b', 'c', 'd'], ['mode 1', 'mode 1', 'mode 1', 'mode 1'], | ||||
|       [[0], [16], [32], [48]], [[8], [8], [8], [8]], [['c', 'd']], | ||||
|       ['b | a', 'c', 'd'], [[16, 0], [32], [48]], [[8, 8], [8], [8]], [400e9, 200e9, 200e9]), | ||||
|      (['a', 'b', 'c', 'd'], ['mode 1', 'mode 1', 'mode 1', 'mode 1'], | ||||
|       [[0], [16], [32], [48]], [[8], [8], [8], [8]], [['a', 'd'], ['b', 'd']], | ||||
|       ['b | a', 'c', 'd'], [[16, 0], [32], [48]], [[8, 8], [8], [8]], [400e9, 200e9, 200e9]), | ||||
|      # requests that should not be aggregated: | ||||
|      (['a', 'b', 'c', 'd'], [None, None, None, 'mode 1'], | ||||
|       [[0, 8], [None, 24], [32, 40], [None]], [[4, 4], [4, 4], [4, 4], [None]], [[]], | ||||
|       ['a', 'b', 'c', 'd'], [[0, 8], [None, 24], [32, 40], [None]], [[4, 4], [4, 4], [4, 4], [None]], | ||||
|       [200e9, 200e9, 200e9, 200e9]), | ||||
|      (['a', 'b', 'c', 'd'], ['mode 1', 'mode 1', 'mode 1', 'mode 1'], | ||||
|       [[0], [16], [32], [48]], [[8], [8], [8], [8]], [['c', 'd', 'a']], | ||||
|       ['a', 'b', 'c', 'd'], [[0], [16], [32], [48]], [[8], [8], [8], [8]], [200e9, 200e9, 200e9, 200e9]), ]) | ||||
| def test_aggregation(ids, modes, req_n, req_m, disjunction, final_ids, final_ns, final_ms, final_path_bandwidths, | ||||
|                      request_set): | ||||
|     """ tests that identical requests are correctly aggregated (included frequency slots merging) | ||||
|     if mode is not defined, requests must not be merged, | ||||
|     if requests are in a synchronization vector, they should not be merged | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_LIBRARY_NAME) | ||||
|     requests = [] | ||||
|     for request_id, mode, req_n, req_m in zip(ids, modes, req_n, req_m): | ||||
|         params = request_set | ||||
|         params['request_id'] = request_id | ||||
|         params['trx_mode'] = mode | ||||
|         params['effective_freq_slot'] = [{'N': n, 'M': m} for n, m in zip(req_n, req_m)] | ||||
|         trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True) | ||||
|         params.update(trx_params) | ||||
|         requests.append(PathRequest(**params)) | ||||
|     params = { | ||||
|         'relaxable': False, | ||||
|         'link_diverse': True, | ||||
|         'node_diverse': True | ||||
|     } | ||||
|  | ||||
|     disjunctions = [] | ||||
|     i = 0 | ||||
|     for vector in disjunction: | ||||
|         params['disjunctions_req'] = vector | ||||
|         params['disjunction_id'] = i | ||||
|         disjunctions.append(Disjunction(**params)) | ||||
|         i += 1 | ||||
|     requests, disjunctions = requests_aggregation(requests, disjunctions) | ||||
|     print(disjunctions) | ||||
|     print(requests) | ||||
|     i = 0 | ||||
|     for final_id, final_n, final_m, final_path_bandwidth in zip(final_ids, final_ns, final_ms, final_path_bandwidths): | ||||
|         assert requests[i].request_id == final_id | ||||
|         assert requests[i].N == final_n | ||||
|         assert requests[i].M == final_m | ||||
|         assert requests[i].path_bandwidth == final_path_bandwidth | ||||
|         i += 1 | ||||
|   | ||||
| @@ -12,6 +12,7 @@ from pathlib import Path | ||||
| import pytest | ||||
| from numpy.testing import assert_allclose, assert_array_equal, assert_raises | ||||
| from numpy import array | ||||
| 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 | ||||
| @@ -20,8 +21,9 @@ from gnpy.core.info import create_input_spectral_information, Pref, create_arbit | ||||
|     ReferenceCarrier | ||||
| 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 | ||||
| from gnpy.topology.request import PathRequest, compute_constrained_path, propagate | ||||
| 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 | ||||
|  | ||||
|  | ||||
| TEST_DIR = Path(__file__).parent | ||||
| @@ -299,8 +301,7 @@ def test_2low_input_power(target_out, delta_pdb_per_channel, correction): | ||||
|  | ||||
|  | ||||
| def net_setup(equipment): | ||||
|     """ common setup for tests: builds network, equipment and oms only once | ||||
|     """ | ||||
|     """common setup for tests: builds network, equipment and oms only once""" | ||||
|     network = load_network(NETWORK_FILENAME, equipment) | ||||
|     spectrum = equipment['SI']['default'] | ||||
|     p_db = spectrum.power_dbm | ||||
| @@ -310,8 +311,7 @@ def net_setup(equipment): | ||||
|  | ||||
|  | ||||
| def create_voyager_req(equipment, source, dest, bidir, nodes_list, loose_list, mode, spacing, power_dbm): | ||||
|     """ create the usual request list according to parameters | ||||
|     """ | ||||
|     """create the usual request list according to parameters""" | ||||
|     params = {'request_id': 'test_request', | ||||
|               'source': source, | ||||
|               'bidir': bidir, | ||||
| @@ -336,8 +336,7 @@ def create_voyager_req(equipment, source, dest, bidir, nodes_list, loose_list, m | ||||
| @pytest.mark.parametrize('power_dbm', [0, 1, -2, None]) | ||||
| @pytest.mark.parametrize('mode, slot_width', (['mode 1', 50e9], ['mode 2', 75e9])) | ||||
| def test_initial_spectrum(mode, slot_width, power_dbm): | ||||
|     """ checks that propagation using the user defined spectrum identical to SI, gives same result as SI | ||||
|     """ | ||||
|     """checks that propagation using the user defined spectrum identical to SI, gives same result as SI""" | ||||
|     # first propagate without any req.initial_spectrum attribute | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
|     req = create_voyager_req(equipment, 'trx Brest_KLA', 'trx Vannes_KBE', False, ['trx Vannes_KBE'], ['STRICT'], | ||||
| @@ -373,7 +372,7 @@ def test_initial_spectrum(mode, slot_width, power_dbm): | ||||
|  | ||||
|  | ||||
| def test_initial_spectrum_not_identical(): | ||||
|     """ checks that user defined spectrum overrides spectrum defined in SI | ||||
|     """checks that user defined spectrum overrides spectrum defined in SI | ||||
|     """ | ||||
|     # first propagate without any req.initial_spectrum attribute | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
| @@ -408,7 +407,7 @@ def test_initial_spectrum_not_identical(): | ||||
|     ('target_psd_out_mWperGHz', power_dbm_to_psd_mw_ghz(-20, 32e9))]) | ||||
| @pytest.mark.parametrize('power_dbm', [0, 2, -0.5]) | ||||
| def test_target_psd_or_psw(power_dbm, equalization, target_value): | ||||
|     """ checks that if target_out_mWperSlotWidth or target_psd_out_mWperGHz is defined, it is used as equalization | ||||
|     """checks that if target_out_mWperSlotWidth or target_psd_out_mWperGHz is defined, it is used as equalization | ||||
|     and it gives same result if computed target is the same | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
| @@ -438,8 +437,7 @@ def test_target_psd_or_psw(power_dbm, equalization, target_value): | ||||
|  | ||||
|  | ||||
| def ref_network(): | ||||
|     """ Create a network instance with a instance of propagated path | ||||
|     """ | ||||
|     """Create a network instance with a instance of propagated path""" | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
|     network = net_setup(equipment) | ||||
|     req0 = create_voyager_req(equipment, 'trx Brest_KLA', 'trx Vannes_KBE', False, ['trx Vannes_KBE'], ['STRICT'], | ||||
| @@ -451,7 +449,8 @@ def ref_network(): | ||||
|  | ||||
| @pytest.mark.parametrize('deltap', [0, +1.2, -0.5]) | ||||
| def test_target_psd_out_mwperghz_deltap(deltap): | ||||
|     """ checks that if target_psd_out_mWperGHz is defined, delta_p of amps is correctly updated | ||||
|     """checks that if target_psd_out_mWperGHz is defined, delta_p of amps is correctly updated | ||||
|  | ||||
|     Power over 1.2dBm saturate amp with this test: TODO add a test on this saturation | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
| @@ -586,3 +585,253 @@ def test_power_option(req_power): | ||||
|     assert_array_equal(infos_expected.pmd, infos_actual.pmd) | ||||
|     assert_array_equal(infos_expected.channel_number, infos_actual.channel_number) | ||||
|     assert_array_equal(infos_expected.number_of_channels, infos_actual.number_of_channels) | ||||
|  | ||||
|  | ||||
| def transceiver(slot_width, value): | ||||
|     return { | ||||
|         "type_variety": "test_offset", | ||||
|         "frequency": { | ||||
|             "min": 191.3e12, | ||||
|             "max": 196.1e12 | ||||
|         }, | ||||
|         "mode": [ | ||||
|             { | ||||
|                 "format": "mode 1", | ||||
|                 "baud_rate": 64e9, | ||||
|                 "OSNR": 18, | ||||
|                 "bit_rate": 100e9, | ||||
|                 "roll_off": 0.15, | ||||
|                 "tx_osnr": 40, | ||||
|                 "min_spacing": 75e9, | ||||
|                 "cost": 1 | ||||
|             }, | ||||
|             { | ||||
|                 "format": "mode 3", | ||||
|                 "baud_rate": 64e9, | ||||
|                 "OSNR": 18, | ||||
|                 "bit_rate": 100e9, | ||||
|                 "roll_off": 0.15, | ||||
|                 "tx_osnr": 40, | ||||
|                 "min_spacing": slot_width, | ||||
|                 "equalization_offset_db": value, | ||||
|                 "cost": 1 | ||||
|             } | ||||
|         ] | ||||
|     } | ||||
|  | ||||
|  | ||||
| def some_requests(): | ||||
|     route = { | ||||
|         "route-object-include-exclude": [ | ||||
|             { | ||||
|                 "explicit-route-usage": "route-include-ero", | ||||
|                 "index": 0, | ||||
|                 "num-unnum-hop": { | ||||
|                     "node-id": "trx Brest_KLA", | ||||
|                     "link-tp-id": "link-tp-id is not used", | ||||
|                     "hop-type": "STRICT" | ||||
|                 } | ||||
|             }, | ||||
|             { | ||||
|                 "explicit-route-usage": "route-include-ero", | ||||
|                 "index": 1, | ||||
|                 "num-unnum-hop": { | ||||
|                     "node-id": "trx Vannes_KBE", | ||||
|                     "link-tp-id": "link-tp-id is not used", | ||||
|                     "hop-type": "STRICT" | ||||
|                 } | ||||
|             } | ||||
|         ] | ||||
|     } | ||||
|     return { | ||||
|         "path-request": [{ | ||||
|             "request-id": "2", | ||||
|             "source": "trx Brest_KLA", | ||||
|             "destination": "trx Vannes_KBE", | ||||
|             "src-tp-id": "trx Brest_KLA", | ||||
|             "dst-tp-id": "trx Vannes_KBE", | ||||
|             "bidirectional": False, | ||||
|             "path-constraints": { | ||||
|                 "te-bandwidth": { | ||||
|                     "technology": "flexi-grid", | ||||
|                     "trx_type": "test_offset", | ||||
|                     "trx_mode": "mode 1", | ||||
|                     "spacing": 75000000000.0, | ||||
|                     "path_bandwidth": 100000000000.0 | ||||
|                 } | ||||
|             }, | ||||
|             "explicit-route-objects": route | ||||
|         }, { | ||||
|             "request-id": "3", | ||||
|             "source": "trx Brest_KLA", | ||||
|             "destination": "trx Vannes_KBE", | ||||
|             "src-tp-id": "trx Brest_KLA", | ||||
|             "dst-tp-id": "trx Vannes_KBE", | ||||
|             "bidirectional": False, | ||||
|             "path-constraints": { | ||||
|                 "te-bandwidth": { | ||||
|                     "technology": "flexi-grid", | ||||
|                     "trx_type": "test_offset", | ||||
|                     "trx_mode": "mode 3", | ||||
|                     "spacing": 87500000000.0, | ||||
|                     "path_bandwidth": 100000000000.0 | ||||
|                 } | ||||
|             }, | ||||
|             "explicit-route-objects": route | ||||
|         }, { | ||||
|             "request-id": "4", | ||||
|             "source": "trx Brest_KLA", | ||||
|             "destination": "trx Vannes_KBE", | ||||
|             "src-tp-id": "trx Brest_KLA", | ||||
|             "dst-tp-id": "trx Vannes_KBE", | ||||
|             "bidirectional": False, | ||||
|             "path-constraints": { | ||||
|                 "te-bandwidth": { | ||||
|                     "technology": "flexi-grid", | ||||
|                     "trx_type": "test_offset", | ||||
|                     "trx_mode": "mode 1", | ||||
|                     "spacing": 87500000000.0, | ||||
|                     "path_bandwidth": 100000000000.0 | ||||
|                 } | ||||
|             }, | ||||
|             "explicit-route-objects": route | ||||
|         }] | ||||
|     } | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('slot_width, value', [(75e9, lin2db(75 / 87.5)), | ||||
|                                                (87.5e9, lin2db(75 / 87.5))]) | ||||
| def test_power_offset_trx_equalization_psw(slot_width, value): | ||||
|     """Check that the equalization with the offset is giving the same result as with reference slot_width | ||||
|     Check that larger slot width but no offset takes larger slot width for equalization | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
|     trx = transceiver(slot_width, value) | ||||
|     equipment['Transceiver'][trx['type_variety']] = Transceiver(**trx) | ||||
|     setattr(equipment['Roadm']['default'], 'target_pch_out_db', None) | ||||
|     setattr(equipment['Roadm']['default'], 'target_out_mWperSlotWidth', power_dbm_to_psd_mw_ghz(-20, 50e9)) | ||||
|     network = net_setup(equipment) | ||||
|     json_data = some_requests() | ||||
|     ref_request, request, other = requests_from_json(json_data, equipment) | ||||
|     # ref_request (_expected) has no offset, equalization on 75GH basis | ||||
|     path_expected = compute_constrained_path(network, ref_request) | ||||
|     _ = propagate(path_expected, ref_request, equipment) | ||||
|     roadm1_expected = deepcopy(path_expected[1]) | ||||
|     # request has an offset either defined in power and a larger slot width. | ||||
|     # The defined offset is "equalize as if it was a 75 GHz channel" although slot_width is 87.5GHz | ||||
|     path = compute_constrained_path(network, request) | ||||
|     _ = propagate(path, request, equipment) | ||||
|     roadm1 = deepcopy(path[1]) | ||||
|     # the other request has a larger slot width (spacing) but no offset. so equalization uses this slot width | ||||
|     path_other = compute_constrained_path(network, other) | ||||
|     _ = propagate(path, other, equipment) | ||||
|     roadm1_other = path_other[1] | ||||
|     # check the first frequency since all cariers have the same equalization | ||||
|     # Check that the power is equalized as if it was for a 75GHz channel (mode 1) instead of a 87.5GHz | ||||
|     assert roadm1.pch_out_dbm[0] == roadm1_expected.pch_out_dbm[0] | ||||
|     # Check that equalization instead uses 87.5GHz basis | ||||
|     assert roadm1_other.pch_out_dbm[0] == roadm1_expected.pch_out_dbm[0] + lin2db(87.5 / 75) | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('slot_width, value', [(75e9, lin2db(75 / 50)), | ||||
|                                                (87.5e9, lin2db(75 / 50))]) | ||||
| def test_power_offset_trx_equalization_p(slot_width, value): | ||||
|     """Check that the constant power equalization with the offset is applied | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
|     trx = transceiver(slot_width, value) | ||||
|     equipment['Transceiver'][trx['type_variety']] = Transceiver(**trx) | ||||
|     setattr(equipment['Roadm']['default'], 'target_pch_out_db', -20) | ||||
|     network = net_setup(equipment) | ||||
|     json_data = some_requests() | ||||
|     ref_request, request, _ = requests_from_json(json_data, equipment) | ||||
|     path_expected = compute_constrained_path(network, ref_request) | ||||
|     _ = propagate(path_expected, ref_request, equipment) | ||||
|     roadm1_expected = deepcopy(path_expected[1]) | ||||
|     path = compute_constrained_path(network, request) | ||||
|     _ = propagate(path, request, equipment) | ||||
|     roadm1 = deepcopy(path[1]) | ||||
|     assert roadm1.pch_out_dbm[0] == roadm1_expected.pch_out_dbm[0] + lin2db(75 / 50) | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('equalization, target_value', | ||||
|     [('target_pch_out_db', -20), | ||||
|      ('target_psd_out_mWperGHz', power_dbm_to_psd_mw_ghz(-20, 64e9)), | ||||
|      ('target_out_mWperSlotWidth', power_dbm_to_psd_mw_ghz(-20, 50e9))]) | ||||
| @pytest.mark.parametrize('slot_width, value, expected_mode', [(75e9, 3.0, 'mode 3')]) | ||||
| def test_power_offset_automatic_mode_selection(slot_width, value, equalization, | ||||
|                                                target_value, expected_mode): | ||||
|     """Check that the same result is obtained if the mode is user defined or if it is | ||||
|     automatically selected | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
|     trx = transceiver(slot_width, value) | ||||
|     equipment['Transceiver'][trx['type_variety']] = Transceiver(**trx) | ||||
|     setattr(equipment['Roadm']['default'], 'target_pch_out_db', None) | ||||
|     setattr(equipment['Roadm']['default'], equalization, target_value) | ||||
|     network = net_setup(equipment) | ||||
|     route = { | ||||
|         "route-object-include-exclude": [ | ||||
|             { | ||||
|                 "explicit-route-usage": "route-include-ero", | ||||
|                 "index": 0, | ||||
|                 "num-unnum-hop": { | ||||
|                     "node-id": "trx Brest_KLA", | ||||
|                     "link-tp-id": "link-tp-id is not used", | ||||
|                     "hop-type": "STRICT" | ||||
|                 } | ||||
|             }, | ||||
|             { | ||||
|                 "explicit-route-usage": "route-include-ero", | ||||
|                 "index": 1, | ||||
|                 "num-unnum-hop": { | ||||
|                     "node-id": "trx Vannes_KBE", | ||||
|                     "link-tp-id": "link-tp-id is not used", | ||||
|                     "hop-type": "STRICT" | ||||
|                 } | ||||
|             } | ||||
|         ] | ||||
|     } | ||||
|     json_data = { | ||||
|         "path-request": [{ | ||||
|             "request-id": "imposed_mode", | ||||
|             "source": "trx Brest_KLA", | ||||
|             "destination": "trx Vannes_KBE", | ||||
|             "src-tp-id": "trx Brest_KLA", | ||||
|             "dst-tp-id": "trx Vannes_KBE", | ||||
|             "bidirectional": False, | ||||
|             "path-constraints": { | ||||
|                 "te-bandwidth": { | ||||
|                     "technology": "flexi-grid", | ||||
|                     "trx_type": "test_offset", | ||||
|                     "trx_mode": "mode 3", | ||||
|                     "spacing": 75000000000.0, | ||||
|                     "path_bandwidth": 100000000000.0 | ||||
|                 } | ||||
|             }, | ||||
|             "explicit-route-objects": route | ||||
|         }, { | ||||
|             "request-id": "free_mode", | ||||
|             "source": "trx Brest_KLA", | ||||
|             "destination": "trx Vannes_KBE", | ||||
|             "src-tp-id": "trx Brest_KLA", | ||||
|             "dst-tp-id": "trx Vannes_KBE", | ||||
|             "bidirectional": False, | ||||
|             "path-constraints": { | ||||
|                 "te-bandwidth": { | ||||
|                     "technology": "flexi-grid", | ||||
|                     "trx_type": "test_offset", | ||||
|                     "spacing": 75000000000.0, | ||||
|                     "path_bandwidth": 100000000000.0 | ||||
|                 } | ||||
|             }, | ||||
|             "explicit-route-objects": route | ||||
|         }]} | ||||
|     imposed_req, free_req, = requests_from_json(json_data, equipment) | ||||
|     assert free_req.tsp_mode is None | ||||
|     path_expected = compute_constrained_path(network, imposed_req) | ||||
|     _ = propagate(path_expected, imposed_req, equipment) | ||||
|     path = compute_constrained_path(network, free_req) | ||||
|     _, 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) | ||||
|   | ||||
| @@ -2,6 +2,7 @@ | ||||
|  | ||||
| from pathlib import Path | ||||
| import os | ||||
| from logging import INFO, Formatter | ||||
| import pytest | ||||
| import subprocess | ||||
| from gnpy.tools.cli_examples import transmission_main_example, path_requests_run | ||||
| @@ -9,39 +10,46 @@ from gnpy.tools.cli_examples import transmission_main_example, path_requests_run | ||||
| SRC_ROOT = Path(__file__).parent.parent | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize("output, handler, args", ( | ||||
|     ('transmission_main_example', transmission_main_example, []), | ||||
|     ('transmission_saturated', transmission_main_example, | ||||
| @pytest.mark.parametrize("output, log, handler, args", ( | ||||
|     ('transmission_main_example', None, transmission_main_example, []), | ||||
|     ('transmission_saturated', 'logs_transmission_saturated', transmission_main_example, | ||||
|      ['tests/data/testTopology_expected.json', 'lannion', 'lorient', '-e', 'tests/data/eqpt_config.json', '--pow', '3']), | ||||
|     ('path_requests_run', path_requests_run, []), | ||||
|     ('transmission_main_example__raman', transmission_main_example, | ||||
|     ('path_requests_run', 'logs_path_request', path_requests_run, ['-v']), | ||||
|     ('transmission_main_example__raman', None, transmission_main_example, | ||||
|      ['gnpy/example-data/raman_edfa_example_network.json', '--sim', 'gnpy/example-data/sim_params.json', '--show-channels', ]), | ||||
|     ('openroadm-v4-Stockholm-Gothenburg', transmission_main_example, | ||||
|     ('openroadm-v4-Stockholm-Gothenburg', None, transmission_main_example, | ||||
|      ['-e', 'gnpy/example-data/eqpt_config_openroadm_ver4.json', 'gnpy/example-data/Sweden_OpenROADMv4_example_network.json', ]), | ||||
|     ('openroadm-v5-Stockholm-Gothenburg', transmission_main_example, | ||||
|     ('openroadm-v5-Stockholm-Gothenburg', None, transmission_main_example, | ||||
|      ['-e', 'gnpy/example-data/eqpt_config_openroadm_ver5.json', 'gnpy/example-data/Sweden_OpenROADMv5_example_network.json', ]), | ||||
|     ('transmission_main_example_long', transmission_main_example, | ||||
|     ('transmission_main_example_long', None, transmission_main_example, | ||||
|      ['-e', 'tests/data/eqpt_config.json', 'tests/data/test_long_network.json']), | ||||
|     ('spectrum1_transmission_main_example', transmission_main_example, | ||||
|     ('spectrum1_transmission_main_example', None, transmission_main_example, | ||||
|      ['--spectrum', 'gnpy/example-data/initial_spectrum1.json', 'gnpy/example-data/meshTopologyExampleV2.xls', ]), | ||||
|     ('spectrum2_transmission_main_example', transmission_main_example, | ||||
|     ('spectrum2_transmission_main_example', None, transmission_main_example, | ||||
|      ['--spectrum', 'gnpy/example-data/initial_spectrum2.json', 'gnpy/example-data/meshTopologyExampleV2.xls', '--show-channels', ]), | ||||
|     )) | ||||
|  | ||||
|  | ||||
| def test_example_invocation(capfd, output, handler, args): | ||||
|     '''Make sure that our examples produce useful output''' | ||||
|     ('path_requests_run_CD_PMD_PDL_missing', 'logs_path_requests_run_CD_PMD_PDL_missing', path_requests_run, | ||||
|      ['tests/data/CORONET_Global_Topology_expected.json', 'tests/data/CORONET_services.json', '-v']), | ||||
| )) | ||||
| def test_example_invocation(capfd, caplog, output, log, handler, args): | ||||
|     """Make sure that our examples produce useful output""" | ||||
|     os.chdir(SRC_ROOT) | ||||
|     expected = open(SRC_ROOT / 'tests' / 'invocation' / output, mode='r', encoding='utf-8').read() | ||||
|     formatter = Formatter('%(levelname)-9s%(name)s:%(filename)s %(message)s') | ||||
|     caplog.handler.setFormatter(formatter) | ||||
|     # keep INFO level to at least test those logs once | ||||
|     caplog.set_level(INFO) | ||||
|     handler(args) | ||||
|     captured = capfd.readouterr() | ||||
|     assert captured.out == expected | ||||
|     assert captured.err == '' | ||||
|     if log: | ||||
|         expected_log = open(SRC_ROOT / 'tests' / 'invocation' / log, mode='r', encoding='utf-8').read() | ||||
|         assert expected_log == caplog.text | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('program', ('gnpy-transmission-example', 'gnpy-path-request')) | ||||
| def test_run_wrapper(program): | ||||
|     '''Ensure that our wrappers really, really work''' | ||||
|     """Ensure that our wrappers really, really work""" | ||||
|     proc = subprocess.run((program, '--help'), stdout=subprocess.PIPE, stderr=subprocess.PIPE, | ||||
|                           check=True, universal_newlines=True) | ||||
|     assert proc.stderr == '' | ||||
| @@ -53,5 +61,5 @@ def test_conversion_xls(): | ||||
|     proc = subprocess.run( | ||||
|         ('gnpy-convert-xls', SRC_ROOT / 'tests' / 'data' / 'testTopology.xls', '--output', os.path.devnull), | ||||
|         stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True, universal_newlines=True) | ||||
|     assert proc.stderr == '' | ||||
|     assert proc.stderr == 'missing header delta p\nmissing header delta p\n' | ||||
|     assert os.path.devnull in proc.stdout | ||||
|   | ||||
							
								
								
									
										422
									
								
								tests/test_logger.py
									
									
									
									
									
										Normal file
									
								
							
							
						
						
									
										422
									
								
								tests/test_logger.py
									
									
									
									
									
										Normal file
									
								
							| @@ -0,0 +1,422 @@ | ||||
| # SPDX-License-Identifier: BSD-3-Clause | ||||
| # | ||||
| # Copyright (C) 2020 Telecom Infra Project and GNPy contributors | ||||
| # see LICENSE.md for a list of contributors | ||||
| # | ||||
|  | ||||
| from pathlib import Path | ||||
| import re | ||||
| import pytest | ||||
|  | ||||
| from gnpy.core.exceptions import ConfigurationError, ServiceError, EquipmentConfigError, ParametersError, \ | ||||
|     NetworkTopologyError | ||||
| from gnpy.tools.json_io import SI, Roadm, Amp, load_equipment, requests_from_json, network_from_json, \ | ||||
|     load_network, load_requests | ||||
| from gnpy.tools.convert import xls_to_json_data | ||||
|  | ||||
| TEST_DIR = Path(__file__).parent | ||||
| EQPT_FILENAME = TEST_DIR / 'data/eqpt_config.json' | ||||
| DATA_DIR = TEST_DIR / 'data' | ||||
|  | ||||
|  | ||||
| def test_jsonthing(caplog): | ||||
|     """Check that a missing key correctly raises an info | ||||
|     """ | ||||
|     json_data = { | ||||
|  | ||||
|         "baud_rate": 32e9, | ||||
|         "f_max": 196.1e12, | ||||
|         "spacing": 50e9, | ||||
|         "power_dbm": 0, | ||||
|         "power_range_db": [0, 0, 1], | ||||
|         "roll_off": 0.15, | ||||
|         "tx_osnr": 40, | ||||
|         "sys_margins": 2 | ||||
|     } | ||||
|     _ = SI(**json_data) | ||||
|     expected_msg = 'WARNING missing f_min attribute in eqpt_config.json[SI]\n ' \ | ||||
|                    + 'default value is f_min = 191350000000000.0' | ||||
|     assert expected_msg in caplog.text | ||||
|  | ||||
|  | ||||
| def wrong_equipment(): | ||||
|     """Creates list of malformed equipments | ||||
|     """ | ||||
|     data = [] | ||||
|     data.append({ | ||||
|         "error": EquipmentConfigError, | ||||
|         "equipment": Roadm, | ||||
|         "json_data": { | ||||
|             "target_pch_out_db": -20, | ||||
|             "target_out_mWperSlotWidth": 3.125e-4, | ||||
|             "add_drop_osnr": 38, | ||||
|             "pmd": 0, | ||||
|             "pdl": 0, | ||||
|             "restrictions": { | ||||
|                 "preamp_variety_list": [], | ||||
|                 "booster_variety_list": [] | ||||
|             } | ||||
|         }, | ||||
|         "expected_msg": "Only one equalization type should be set in ROADM, found: target_pch_out_db," | ||||
|                         + " target_out_mWperSlotWidth" | ||||
|     }) | ||||
|     data.append({ | ||||
|         "error": EquipmentConfigError, | ||||
|         "equipment": Roadm, | ||||
|         "json_data": { | ||||
|             "add_drop_osnr": 38, | ||||
|             "pmd": 0, | ||||
|             "pdl": 0, | ||||
|             "restrictions": { | ||||
|                 "preamp_variety_list": [], | ||||
|                 "booster_variety_list": [] | ||||
|             } | ||||
|         }, | ||||
|         "expected_msg": "No equalization type set in ROADM" | ||||
|     }) | ||||
|     return data | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('error, equipment, json_data, expected_msg', | ||||
|                          [(e['error'], e['equipment'], e['json_data'], e['expected_msg']) for e in wrong_equipment()]) | ||||
| def test_wrong_equipment(caplog, error, equipment, json_data, expected_msg): | ||||
|     """ | ||||
|     """ | ||||
|     with pytest.raises(EquipmentConfigError, match=expected_msg): | ||||
|         _ = equipment(**json_data) | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('xls_service_filename, xls_topo_filename, expected_msg', | ||||
|                          [('wrong_service.xlsx', 'testTopology.xls', | ||||
|                            "Service error: Request Id: 0 - could not find tsp : 'Voyager' with mode: 'Mode 10' " | ||||
|                            + "in eqpt library \nComputation stopped."), | ||||
|                           ('wrong_service_type.xlsx', 'testTopology.xls', | ||||
|                            "Service error: Request Id: 0 - could not find tsp : 'Galileo' with mode: 'mode 1' " | ||||
|                            + "in eqpt library \nComputation stopped.")]) | ||||
| def test_wrong_xls_service(xls_service_filename, xls_topo_filename, expected_msg): | ||||
|     """ | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
|     network = load_network(DATA_DIR / xls_topo_filename, equipment) | ||||
|     with pytest.raises(ServiceError, match=expected_msg): | ||||
|         _ = load_requests(DATA_DIR / xls_service_filename, equipment, False, network, DATA_DIR / xls_topo_filename) | ||||
|  | ||||
|  | ||||
| def wrong_amp(): | ||||
|     """Creates list of malformed equipments | ||||
|     """ | ||||
|     data = [] | ||||
|     data.append({ | ||||
|         "error": EquipmentConfigError, | ||||
|         "json_data": { | ||||
|             "type_variety": "test_fixed_gain", | ||||
|             "type_def": "fixed_gain", | ||||
|             "gain_flatmax": 21, | ||||
|             "gain_min": 20, | ||||
|             "p_max": 21, | ||||
|             "allowed_for_design": True | ||||
|         }, | ||||
|         "expected_msg": "missing nf0 value input for amplifier: test_fixed_gain in equipment config" | ||||
|     }) | ||||
|     data.append({ | ||||
|         "error": EquipmentConfigError, | ||||
|         "json_data": { | ||||
|             "type_variety": "test", | ||||
|             "type_def": "variable_gain", | ||||
|             "gain_flatmax": 25, | ||||
|             "gain_min": 15, | ||||
|             "p_max": 21, | ||||
|             "nf_min": 5.8, | ||||
|             "out_voa_auto": False, | ||||
|             "allowed_for_design": True | ||||
|         }, | ||||
|         "expected_msg": "missing nf_min or nf_max value input for amplifier: test in equipment config" | ||||
|     }) | ||||
|     data.append({ | ||||
|         "error": EquipmentConfigError, | ||||
|         "json_data": { | ||||
|             "type_variety": "medium+high_power", | ||||
|             "type_def": "dual_stage", | ||||
|             "gain_min": 25, | ||||
|             "preamp_variety": "std_medium_gain", | ||||
|             "allowed_for_design": False | ||||
|         }, | ||||
|         "expected_msg": "missing preamp/booster variety input for amplifier: medium+high_power in equipment config" | ||||
|     }) | ||||
|     return data | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('error, json_data, expected_msg', | ||||
|                          [(e['error'], e['json_data'], e['expected_msg']) for e in wrong_amp()]) | ||||
| def test_wrong_amp(error, json_data, expected_msg): | ||||
|     """ | ||||
|     """ | ||||
|     with pytest.raises(error, match=re.escape(expected_msg)): | ||||
|         _ = Amp.from_json(EQPT_FILENAME, **json_data) | ||||
|  | ||||
|  | ||||
| def wrong_requests(): | ||||
|     """Creates list of malformed requests | ||||
|     """ | ||||
|     data = [] | ||||
|     data.append({ | ||||
|         'error': ConfigurationError, | ||||
|         'json_data': { | ||||
|             "path-request": [{ | ||||
|                 "request-id": "imposed_mode", | ||||
|                 "source": "trx Brest_KLA", | ||||
|                 "destination": "trx Vannes_KBE", | ||||
|                 "src-tp-id": "trx Brest_KLA", | ||||
|                 "dst-tp-id": "trx Vannes_KBE", | ||||
|                 "bidirectional": False, | ||||
|                 "path-constraints": { | ||||
|                     "te-bandwidth": { | ||||
|                         "technology": "flexi-grid", | ||||
|                         "trx_type": "test_offset", | ||||
|                         "trx_mode": "mode 3", | ||||
|                         "spacing": 75000000000.0, | ||||
|                         "path_bandwidth": 100000000000.0 | ||||
|                     } | ||||
|                 } | ||||
|             }] | ||||
|         }, | ||||
|         'expected_msg': 'Equipment Config error in imposed_mode: ' | ||||
|                         + 'Could not find transponder "test_offset" with mode "mode 3" in equipment library' | ||||
|     }) | ||||
|     data.append({ | ||||
|         'error': ServiceError, | ||||
|         'json_data': { | ||||
|             "path-request": [{ | ||||
|                 "request-id": "Missing_type", | ||||
|                 "source": "trx Brest_KLA", | ||||
|                 "destination": "trx Vannes_KBE", | ||||
|                 "src-tp-id": "trx Brest_KLA", | ||||
|                 "dst-tp-id": "trx Vannes_KBE", | ||||
|                 "bidirectional": False, | ||||
|                 "path-constraints": { | ||||
|                     "te-bandwidth": { | ||||
|                         "technology": "flexi-grid", | ||||
|                         "trx_type": None, | ||||
|                         "spacing": 75000000000.0, | ||||
|                         "path_bandwidth": 100000000000.0 | ||||
|                     } | ||||
|                 } | ||||
|             }]}, | ||||
|         'expected_msg': 'Request Missing_type has no transceiver type defined' | ||||
|     }) | ||||
|     data.append({ | ||||
|         'error': ServiceError, | ||||
|         'json_data': { | ||||
|             "path-request": [{ | ||||
|                 "request-id": "wrong_spacing", | ||||
|                 "source": "trx Brest_KLA", | ||||
|                 "destination": "trx Vannes_KBE", | ||||
|                 "src-tp-id": "trx Brest_KLA", | ||||
|                 "dst-tp-id": "trx Vannes_KBE", | ||||
|                 "bidirectional": False, | ||||
|                 "path-constraints": { | ||||
|                     "te-bandwidth": { | ||||
|                         "technology": "flexi-grid", | ||||
|                         "trx_type": "Voyager", | ||||
|                         "trx_mode": "mode 2", | ||||
|                         "spacing": 50000000000.0, | ||||
|                         "path_bandwidth": 100000000000.0 | ||||
|                     } | ||||
|                 } | ||||
|             }]}, | ||||
|         'expected_msg': 'Request wrong_spacing has spacing below transponder Voyager mode 2 min spacing' | ||||
|         + ' value 75.0GHz.\nComputation stopped' | ||||
|     }) | ||||
|     data.append({ | ||||
|         'error': ServiceError, | ||||
|         'json_data': { | ||||
|             "path-request": [{ | ||||
|                 "request-id": "Wrong_nb_channel", | ||||
|                 "source": "trx Brest_KLA", | ||||
|                 "destination": "trx Vannes_KBE", | ||||
|                 "src-tp-id": "trx Brest_KLA", | ||||
|                 "dst-tp-id": "trx Vannes_KBE", | ||||
|                 "bidirectional": False, | ||||
|                 "path-constraints": { | ||||
|                     "te-bandwidth": { | ||||
|                         "technology": "flexi-grid", | ||||
|                         "trx_type": "Voyager", | ||||
|                         "trx_mode": "mode 2", | ||||
|                         "spacing": 75000000000.0, | ||||
|                         "max-nb-of-channel": 150, | ||||
|                         "path_bandwidth": 100000000000.0 | ||||
|                     } | ||||
|                 } | ||||
|             }]}, | ||||
|         'expected_msg': 'Requested channel number 150, baud rate 66.0 GHz' | ||||
|                         + ' and requested spacing 75.0GHz is not consistent with frequency range' | ||||
|                         + ' 191.35 THz, 196.1 THz.' | ||||
|                         + ' Max recommanded nb of channels is 63.' | ||||
|     }) | ||||
|     data.append({ | ||||
|         'error': ServiceError, | ||||
|         'json_data': { | ||||
|             "path-request": [{ | ||||
|                 "request-id": "Wrong_M", | ||||
|                 "source": "trx Brest_KLA", | ||||
|                 "destination": "trx Vannes_KBE", | ||||
|                 "src-tp-id": "trx Brest_KLA", | ||||
|                 "dst-tp-id": "trx Vannes_KBE", | ||||
|                 "bidirectional": False, | ||||
|                 "path-constraints": { | ||||
|                     "te-bandwidth": { | ||||
|                         "technology": "flexi-grid", | ||||
|                         "trx_type": "Voyager", | ||||
|                         "trx_mode": "mode 2", | ||||
|                         "spacing": 75000000000.0, | ||||
|                         "effective-freq-slot": [ | ||||
|                             { | ||||
|                               "N": -208, | ||||
|                               "M": 4 | ||||
|                             } | ||||
|                         ], | ||||
|                         "path_bandwidth": 100000000000.0 | ||||
|                     } | ||||
|                 } | ||||
|             }]}, | ||||
|         'expected_msg': 'Requested M [{\'N\': -208, \'M\': 4}] number of slots for request Wrong_M ' | ||||
|                         + 'support 0 nb of channels while 1 are required to support request 100.0 Gbit/s' | ||||
|                         + ' with Voyager mode 2' | ||||
|     }) | ||||
|     return data | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('error, json_data, expected_msg', | ||||
|                          [(e['error'], e['json_data'], e['expected_msg']) for e in wrong_requests()]) | ||||
| def test_json_request(error, json_data, expected_msg): | ||||
|     """ | ||||
|     Check that a missing key is correctly raisong the logger | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
|  | ||||
|     with pytest.raises(error, match=re.escape(expected_msg)): | ||||
|         _ = requests_from_json(json_data, equipment) | ||||
|  | ||||
|  | ||||
| def wrong_element(): | ||||
|     """ | ||||
|     """ | ||||
|     data = [] | ||||
|     data.append({ | ||||
|         "error": ConfigurationError, | ||||
|         "json_data": { | ||||
|             "elements": [{ | ||||
|                 "uid": "roadm SITE2", | ||||
|                 "type": "Roadm", | ||||
|                 "params": { | ||||
|                     "target_pch_out_db": -20, | ||||
|                     "target_out_mWperSlotWidth": 3.125e-4, | ||||
|                 }, | ||||
|                 "metadata": { | ||||
|                     "location": { | ||||
|                         "latitude": 2.0, | ||||
|                         "longitude": 3.0, | ||||
|                         "city": "SITE2", | ||||
|                         "region": "RLD" | ||||
|                     } | ||||
|                 } | ||||
|             }], | ||||
|             "connections": [] | ||||
|         }, | ||||
|         "expected_msg": "ROADM roadm SITE2: invalid equalization settings" | ||||
|     }) | ||||
|     data.append({ | ||||
|         "error": ConfigurationError, | ||||
|         "json_data": { | ||||
|             "elements": [{ | ||||
|                 "uid": "east edfa in ILA2 to SITE2", | ||||
|                 "type": "Edfa", | ||||
|                 "type_variety": "not_valid_variety", | ||||
|                 "metadata": { | ||||
|                     "location": { | ||||
|                         "latitude": 2.0, | ||||
|                         "longitude": 0.0, | ||||
|                         "city": "ILA2", | ||||
|                         "region": "RLD" | ||||
|                     } | ||||
|                 } | ||||
|             }], | ||||
|             "connections": [] | ||||
|         }, | ||||
|         "expected_msg": "The Edfa of variety type not_valid_variety was not recognized:" | ||||
|                         + "\nplease check it is properly defined in the eqpt_config json file" | ||||
|     }) | ||||
|     data.append({ | ||||
|         "error": ParametersError, | ||||
|         "json_data": { | ||||
|             "elements": [{ | ||||
|                 "uid": "fiber (ILA2 → ILA1)", | ||||
|                 "type": "Fiber", | ||||
|                 "type_variety": "SSMF", | ||||
|                 "params": { | ||||
|                     "length": 100.0, | ||||
|                     "loss_coef": 0.2, | ||||
|                     "att_in": 0, | ||||
|                     "con_in": 0, | ||||
|                     "con_out": 0 | ||||
|                 }, | ||||
|                 "metadata": { | ||||
|                     "location": { | ||||
|                         "latitude": 2.0, | ||||
|                         "longitude": 1.5, | ||||
|                         "city": None, | ||||
|                         "region": None | ||||
|                     } | ||||
|                 } | ||||
|             }], | ||||
|             "connections": [] | ||||
|         }, | ||||
|         "expected_msg": "Config error in fiber (ILA2 → ILA1): " | ||||
|                         + "Fiber configurations json must include \'length_units\'. Configuration: " | ||||
|                         + "{\'length\': 100.0, \'loss_coef\': 0.2, \'att_in\': 0, \'con_in\': 0, \'con_out\': 0, " | ||||
|                         + "\'type_variety\': \'SSMF\', \'dispersion\': 1.67e-05, \'effective_area\': 8.3e-11, " | ||||
|                         + "\'pmd_coef\': 1.265e-15}" | ||||
|     }) | ||||
|     return data | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('error, json_data, expected_msg', | ||||
|                          [(e['error'], e['json_data'], e['expected_msg']) for e in wrong_element()]) | ||||
| def test_json_network(error, json_data, expected_msg): | ||||
|     """ | ||||
|     Check that a missing key is correctly raisong the logger | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_FILENAME) | ||||
|     with pytest.raises(error, match=re.escape(expected_msg)): | ||||
|         _ = network_from_json(json_data, equipment) | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('input_filename, expected_msg', | ||||
|     [(DATA_DIR / 'wrong_topo_node.xlsx', 'XLS error: The following nodes are not referenced from the Links sheet.' | ||||
|                                          + ' If unused, remove them from the Nodes sheet:\n - toto'), | ||||
|      (DATA_DIR / 'wrong_topo_link.xlsx', 'XLS error: The Links sheet references nodes that are not defined in the ' | ||||
|                                          + 'Nodes sheet:\n - ALB -> toto'), | ||||
|      (DATA_DIR / 'wrong_topo_link_header.xlsx', 'missing header Node Z'), | ||||
|      (DATA_DIR / 'wrong_topo_eqpt.xlsx', 'XLS error: The Eqpt sheet refers to nodes that are not defined in the ' | ||||
|                                          + 'Nodes sheet:\n - toto'), | ||||
|      (DATA_DIR / 'wrong_topo_duplicate_node.xlsx', 'Duplicate city: Counter({\'ALB\': 2, \'CHA_3\': 1})'), | ||||
|      (DATA_DIR / 'wrong_topo_duplicate_eqpt.xlsx', 'XLS error: Duplicate lines in Eqpt sheet: - ALB -> CHA_3'), | ||||
|      (DATA_DIR / 'wrong_topo_bad_eqpt.xlsx', 'XLS error: The Eqpt sheet references links that are not defined ' | ||||
|                                              + 'in the Links sheet:\n - toto -> CHA_3'), | ||||
|      (DATA_DIR / 'wrong_duplicate_link_reverse.xlsx', 'XLS error: links  - (\'ila\', \'siteb\') are duplicate'), | ||||
|      (DATA_DIR / 'wrong_duplicate_eqpt_ila_reverse.xlsx', 'XLS error: Duplicate ILA eqpt definition in Eqpt sheet:' | ||||
|                                                           + ' - ila')]) | ||||
| def test_wrong_xlsx(input_filename, expected_msg): | ||||
|     """Check that error and logs are correctly working | ||||
|     """ | ||||
|     with pytest.raises(NetworkTopologyError, match=re.escape(expected_msg)): | ||||
|         _ = xls_to_json_data(input_filename) | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('input_filename, expected_msg', | ||||
|     [(DATA_DIR / 'wrong_node_type.xlsx', 'invalid node type (ILA) specified in Lannion_CAS, replaced by ROADM\n')]) | ||||
| def test_log_wrong_xlsx(caplog, input_filename, expected_msg): | ||||
|     """Check that logs are correctly working | ||||
|     """ | ||||
|     _ = xls_to_json_data(input_filename) | ||||
|     assert expected_msg in caplog.text | ||||
| @@ -6,18 +6,51 @@ Checks that the class SimParams behaves as a mutable Singleton. | ||||
| """ | ||||
|  | ||||
| import pytest | ||||
| from gnpy.core.parameters import SimParams | ||||
| from pathlib import Path | ||||
| from numpy.testing import assert_allclose | ||||
|  | ||||
| from gnpy.core.parameters import SimParams, FiberParams | ||||
| from gnpy.tools.json_io import load_json, Fiber | ||||
|  | ||||
| TEST_DIR = Path(__file__).parent | ||||
|  | ||||
|  | ||||
| @pytest.mark.usefixtures('set_sim_params') | ||||
| def test_sim_parameters(): | ||||
|     sim_params = {'nli_params': {}, 'raman_params': {}} | ||||
|     SimParams.set_params(sim_params) | ||||
|     s1 = SimParams.get() | ||||
|     s1 = SimParams() | ||||
|     assert s1.nli_params.method == 'gn_model_analytic' | ||||
|     s2 = SimParams.get() | ||||
|     s2 = SimParams() | ||||
|     assert not s1.raman_params.flag | ||||
|     sim_params['raman_params']['flag'] = True | ||||
|     SimParams.set_params(sim_params) | ||||
|     assert s2.raman_params.flag | ||||
|     assert s1.raman_params.flag | ||||
|  | ||||
|  | ||||
| def test_fiber_parameters(): | ||||
|     fiber_dict_explicit_g0 = load_json(TEST_DIR/'data'/'test_parameters_fiber_config.json')['params'] | ||||
|     fiber_params_explicit_g0 = FiberParams(**fiber_dict_explicit_g0) | ||||
|  | ||||
|     fiber_dict_default_g0 = load_json(TEST_DIR/'data'/'test_science_utils_fiber_config.json')['params'] | ||||
|     fiber_params_default_g0 = FiberParams(**fiber_dict_default_g0) | ||||
|  | ||||
|     fiber_dict_cr = load_json(TEST_DIR/'data'/'test_old_parameters_fiber_config.json')['params'] | ||||
|     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 | ||||
|  | ||||
|     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 | ||||
|  | ||||
|     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(raman_coefficient_explicit_g0, raman_coefficient_default_g0, rtol=1e-10) | ||||
|     assert_allclose(raman_coefficient_explicit_g0, raman_coefficient_cr, rtol=1e-10) | ||||
|   | ||||
| @@ -3,16 +3,17 @@ | ||||
| # @Author: Esther Le Rouzic | ||||
| # @Date:   2018-06-15 | ||||
|  | ||||
| """ Adding tests to check the parser non regression | ||||
|     convention of naming of test files: | ||||
|     - ..._expected.json for the reference output | ||||
|     tests: | ||||
|     - generation of topology json | ||||
|     - reading of Eqpt sheet w and W/ power mode | ||||
|     - consistency of autodesign | ||||
|     - generation of service list based on service sheet | ||||
|     - writing of results in csv | ||||
|     - writing of results in json (same keys) | ||||
| """Adding tests to check the parser non regression | ||||
|  | ||||
| convention of naming of test files: | ||||
| - ..._expected.json for the reference output | ||||
| tests: | ||||
| - generation of topology json | ||||
| - reading of Eqpt sheet w and W/ power mode | ||||
| - consistency of autodesign | ||||
| - generation of service list based on service sheet | ||||
| - writing of results in csv | ||||
| - writing of results in json (same keys) | ||||
| """ | ||||
|  | ||||
| from pathlib import Path | ||||
| @@ -46,8 +47,7 @@ equipment = load_equipment(eqpt_filename) | ||||
|  | ||||
| }.items()) | ||||
| def test_excel_json_generation(tmpdir, xls_input, expected_json_output): | ||||
|     """ tests generation of topology json | ||||
|     """ | ||||
|     """tests generation of topology json""" | ||||
|     xls_copy = Path(tmpdir) / xls_input.name | ||||
|     shutil.copyfile(xls_input, xls_copy) | ||||
|     convert_file(xls_copy) | ||||
| @@ -68,9 +68,7 @@ def test_excel_json_generation(tmpdir, xls_input, expected_json_output): | ||||
|                           DATA_DIR / 'testTopology_auto_design_expected.json', | ||||
|                           }.items()) | ||||
| def test_auto_design_generation_fromxlsgainmode(tmpdir, xls_input, expected_json_output): | ||||
|     """ tests generation of topology json | ||||
|         test that the build network gives correct results in gain mode | ||||
|     """ | ||||
|     """tests generation of topology json and that the build network gives correct results in gain mode""" | ||||
|     equipment = load_equipment(eqpt_filename) | ||||
|     network = load_network(xls_input, equipment) | ||||
|     # in order to test the Eqpt sheet and load gain target, | ||||
| @@ -100,8 +98,7 @@ def test_auto_design_generation_fromxlsgainmode(tmpdir, xls_input, expected_json | ||||
|                           True | ||||
|                           }.items()) | ||||
| def test_auto_design_generation_fromjson(tmpdir, json_input, power_mode): | ||||
|     """test that autodesign creates same file as an input file already autodesigned | ||||
|     """ | ||||
|     """test that autodesign creates same file as an input file already autodesigned""" | ||||
|     equipment = load_equipment(eqpt_filename) | ||||
|     network = load_network(json_input, equipment) | ||||
|     # in order to test the Eqpt sheet and load gain target, | ||||
| @@ -127,8 +124,7 @@ def test_auto_design_generation_fromjson(tmpdir, json_input, power_mode): | ||||
|     DATA_DIR / 'testService.xls': DATA_DIR / 'testService_services_expected.json' | ||||
| }.items()) | ||||
| def test_excel_service_json_generation(xls_input, expected_json_output): | ||||
|     """ test services creation | ||||
|     """ | ||||
|     """test services creation""" | ||||
|     equipment = load_equipment(eqpt_filename) | ||||
|     network = load_network(DATA_DIR / 'testTopology.xls', equipment) | ||||
|     # Build the network once using the default power defined in SI in eqpt config | ||||
| @@ -148,9 +144,7 @@ def test_excel_service_json_generation(xls_input, expected_json_output): | ||||
|     (DATA_DIR / 'testTopology_response.json', ) | ||||
| ) | ||||
| def test_csv_response_generation(tmpdir, json_input): | ||||
|     """ tests if generated csv is consistant with expected generation | ||||
|         same columns (order not important) | ||||
|     """ | ||||
|     """tests if generated csv is consistant with expected generation same columns (order not important)""" | ||||
|     json_data = load_json(json_input) | ||||
|     equipment = load_equipment(eqpt_filename) | ||||
|     csv_filename = Path(tmpdir / json_input.name).with_suffix('.csv') | ||||
| @@ -215,8 +209,7 @@ def test_csv_response_generation(tmpdir, json_input): | ||||
|     DATA_DIR / 'testTopology.xls': DATA_DIR / 'testTopology_response.json', | ||||
| }.items()) | ||||
| def test_json_response_generation(xls_input, expected_response_file): | ||||
|     """ tests if json response is correctly generated for all combinations of requests | ||||
|     """ | ||||
|     """tests if json response is correctly generated for all combinations of requests""" | ||||
|  | ||||
|     equipment = load_equipment(eqpt_filename) | ||||
|     network = load_network(xls_input, equipment) | ||||
| @@ -323,8 +316,7 @@ def test_json_response_generation(xls_input, expected_response_file): | ||||
|     ('trx Brest_KLA', 'trx Rennes_STA', 'Brest_KLA | trx Lannion_CAS', 'STRICT', 'Fail') | ||||
| ]) | ||||
| def test_excel_ila_constraints(source, destination, route_list, hoptype, expected_correction): | ||||
|     """ add different kind of constraints to test all correct_route cases | ||||
|     """ | ||||
|     """add different kind of constraints to test all correct_route cases""" | ||||
|     service_xls_input = DATA_DIR / 'testTopology.xls' | ||||
|     network_json_input = DATA_DIR / 'testTopology_auto_design_expected.json' | ||||
|     equipment = load_equipment(eqpt_filename) | ||||
| @@ -363,7 +355,8 @@ def test_excel_ila_constraints(source, destination, route_list, hoptype, expecte | ||||
|         'nb_channel': 0, | ||||
|         'power': 0, | ||||
|         'path_bandwidth': 0, | ||||
|         'effective_freq_slot': None | ||||
|         'effective_freq_slot': None, | ||||
|         'equalization_offset_db': 0 | ||||
|     } | ||||
|     request = PathRequest(**params) | ||||
|  | ||||
| @@ -376,8 +369,7 @@ def test_excel_ila_constraints(source, destination, route_list, hoptype, expecte | ||||
|  | ||||
|  | ||||
| def setup_per_degree(case): | ||||
|     """ common setup for degree: returns the dict network for different cases | ||||
|     """ | ||||
|     """common setup for degree: returns the dict network for different cases""" | ||||
|     json_network = load_json(DATA_DIR / 'testTopology_expected.json') | ||||
|     json_network_auto = load_json(DATA_DIR / 'testTopology_auto_design_expected.json') | ||||
|     if case == 'no': | ||||
| @@ -401,8 +393,7 @@ def setup_per_degree(case): | ||||
|  | ||||
| @pytest.mark.parametrize('case', ['no', 'all', 'Lannion_CAS and all', 'Lannion_CAS and one']) | ||||
| def test_target_pch_out_db_global(case): | ||||
|     """ check that per degree attributes are correctly created with global values if none are given | ||||
|     """ | ||||
|     """check that per degree attributes are correctly created with global values if none are given""" | ||||
|     json_network = setup_per_degree(case) | ||||
|     per_degree = {} | ||||
|     for elem in json_network['elements']: | ||||
| @@ -442,14 +433,12 @@ def test_target_pch_out_db_global(case): | ||||
|  | ||||
|  | ||||
| def all_rows(sh, start=0): | ||||
|     """ reads excel sheet row per row | ||||
|     """ | ||||
|     """reads excel sheet row per row""" | ||||
|     return (sh.row(x) for x in range(start, sh.nrows)) | ||||
|  | ||||
|  | ||||
| class Amp: | ||||
|     """ Node element contains uid, list of connected nodes and eqpt type | ||||
|     """ | ||||
|     """Node element contains uid, list of connected nodes and eqpt type""" | ||||
|  | ||||
|     def __init__(self, uid, to_node, eqpt=None, west=None): | ||||
|         self.uid = uid | ||||
| @@ -459,7 +448,7 @@ class Amp: | ||||
|  | ||||
|  | ||||
| def test_eqpt_creation(tmpdir): | ||||
|     """ tests that convert correctly creates equipment according to equipment sheet | ||||
|     """tests that convert correctly creates equipment according to equipment sheet | ||||
|     including all cominations in testTopologyconvert.xls: if a line exists the amplifier | ||||
|     should be created even if no values are provided. | ||||
|     """ | ||||
|   | ||||
| @@ -31,10 +31,10 @@ NETWORK_FILE_NAME = TEST_DIR / 'data/testTopology_expected.json' | ||||
| # mark node_uid amps as fused for testing purpose | ||||
| @pytest.mark.parametrize("node_uid", ['east edfa in Lannion_CAS to Stbrieuc']) | ||||
| def test_no_amp_feature(node_uid): | ||||
|     ''' Check that booster is not placed on a roadm if fused is specified | ||||
|     """Check that booster is not placed on a roadm if fused is specified | ||||
|     test_parser covers partly this behaviour. This test should guaranty that the | ||||
|     feature is preserved even if convert is changed | ||||
|     ''' | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_LIBRARY_NAME) | ||||
|     json_network = load_json(NETWORK_FILE_NAME) | ||||
|  | ||||
| @@ -145,9 +145,9 @@ def equipment(): | ||||
|         'booster_variety_list':[] | ||||
|     }]) | ||||
| def test_restrictions(restrictions, equipment): | ||||
|     ''' test that restriction is correctly applied if provided in eqpt_config and if no Edfa type | ||||
|     """test that restriction is correctly applied if provided in eqpt_config and if no Edfa type | ||||
|     were provided in the network json | ||||
|     ''' | ||||
|     """ | ||||
|     # add restrictions | ||||
|     equipment['Roadm']['default'].restrictions = restrictions | ||||
|     # build network | ||||
| @@ -212,11 +212,11 @@ def test_restrictions(restrictions, equipment): | ||||
| @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): | ||||
|     ''' Check that egress power of roadm is equal to target power if input power is greater | ||||
|     """Check that egress power of roadm is equal to target power if input power is greater | ||||
|     than target power else, that it is equal to input power. Use a simple two hops A-B-C topology | ||||
|     for the test where the prev_node in ROADM B is either an amplifier or a fused, so that the target | ||||
|     power can not be met in this last case. | ||||
|     ''' | ||||
|     """ | ||||
|     equipment = load_equipment(EQPT_LIBRARY_NAME) | ||||
|     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') | ||||
|   | ||||
| @@ -9,10 +9,11 @@ are tested. | ||||
| from pathlib import Path | ||||
| from pandas import read_csv | ||||
| from numpy.testing import assert_allclose | ||||
| from numpy import array, genfromtxt | ||||
| from numpy import array | ||||
| import pytest | ||||
|  | ||||
| from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information, Pref, ReferenceCarrier | ||||
| from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information, Pref, \ | ||||
|     ReferenceCarrier | ||||
| from gnpy.core.elements import Fiber, RamanFiber | ||||
| from gnpy.core.parameters import SimParams | ||||
| from gnpy.tools.json_io import load_json | ||||
| @@ -23,13 +24,14 @@ TEST_DIR = Path(__file__).parent | ||||
|  | ||||
|  | ||||
| def test_fiber(): | ||||
|     """ Test the accuracy of propagating the Fiber.""" | ||||
|     """Test the accuracy of propagating the Fiber.""" | ||||
|     fiber = Fiber(**load_json(TEST_DIR / 'data' / 'test_science_utils_fiber_config.json')) | ||||
|  | ||||
|     # fix grid spectral information generation | ||||
|     spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15, | ||||
|                                                             baud_rate=32e9, power=1e-3, spacing=50e9, tx_osnr=40.0, | ||||
|                                                             ref_carrier=ReferenceCarrier(baud_rate=32e9, slot_width=50e9)) | ||||
|                                                             ref_carrier= | ||||
|                                                             ReferenceCarrier(baud_rate=32e9, slot_width=50e9)) | ||||
|     # propagation | ||||
|     spectral_info_out = fiber(spectral_info_input) | ||||
|  | ||||
| @@ -65,7 +67,7 @@ def test_fiber(): | ||||
|  | ||||
| @pytest.mark.usefixtures('set_sim_params') | ||||
| def test_raman_fiber(): | ||||
|     """ Test the accuracy of propagating the RamanFiber.""" | ||||
|     """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, | ||||
| @@ -92,7 +94,7 @@ def test_raman_fiber(): | ||||
|      (0.5, 81, "Lumped loss positions must be between 0 and the fiber length (80.0 km), boundaries excluded."))) | ||||
| @pytest.mark.usefixtures('set_sim_params') | ||||
| def test_fiber_lumped_losses(loss, position, errmsg, set_sim_params): | ||||
|     """ Lumped losses length sanity checking.""" | ||||
|     """Lumped losses length sanity checking.""" | ||||
|     SimParams.set_params(load_json(TEST_DIR / 'data' / 'sim_params.json')) | ||||
|     fiber_dict = load_json(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber_config.json') | ||||
|     fiber_dict['params']['lumped_losses'] = [{'position': position, 'loss': loss}] | ||||
| @@ -103,11 +105,12 @@ def test_fiber_lumped_losses(loss, position, errmsg, set_sim_params): | ||||
|  | ||||
| @pytest.mark.usefixtures('set_sim_params') | ||||
| def test_fiber_lumped_losses_srs(set_sim_params): | ||||
|     """ Test the accuracy of Fiber with lumped losses propagation.""" | ||||
|     """Test the accuracy of Fiber with lumped losses propagation.""" | ||||
|     # spectral information generation | ||||
|     spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15, | ||||
|                                                             baud_rate=32e9, power=1e-3, spacing=50e9, tx_osnr=40.0, | ||||
|                                                             ref_carrier=ReferenceCarrier(baud_rate=32e9, slot_width=50e9)) | ||||
|                                                             ref_carrier= | ||||
|                                                             ReferenceCarrier(baud_rate=32e9, slot_width=50e9)) | ||||
|  | ||||
|     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')) | ||||
| @@ -118,18 +121,18 @@ def test_fiber_lumped_losses_srs(set_sim_params): | ||||
|     stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering( | ||||
|         spectral_info_input, fiber) | ||||
|     power_profile = stimulated_raman_scattering.power_profile | ||||
|     expected_power_profile = genfromtxt(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_pumps.csv', delimiter=',') | ||||
|     expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_pumps.csv', header=None) | ||||
|     assert_allclose(power_profile, expected_power_profile, rtol=1e-3) | ||||
|  | ||||
|     # with Raman pumps | ||||
|     expected_power_profile = genfromtxt(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber.csv', delimiter=',') | ||||
|     expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber.csv', header=None) | ||||
|     stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering( | ||||
|         spectral_info_input, raman_fiber) | ||||
|     power_profile = stimulated_raman_scattering.power_profile | ||||
|     assert_allclose(power_profile, expected_power_profile, rtol=1e-3) | ||||
|  | ||||
|     # without Stimulated Raman Scattering | ||||
|     expected_power_profile = genfromtxt(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_raman.csv', delimiter=',') | ||||
|     expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_raman.csv', header=None) | ||||
|     stimulated_raman_scattering = RamanSolver.calculate_attenuation_profile(spectral_info_input, fiber) | ||||
|     power_profile = stimulated_raman_scattering.power_profile | ||||
|     assert_allclose(power_profile, expected_power_profile, rtol=1e-3) | ||||
|   | ||||
| @@ -20,7 +20,8 @@ from gnpy.core.elements import Roadm, Transceiver | ||||
| from gnpy.core.exceptions import ServiceError, SpectrumError | ||||
| from gnpy.topology.request import compute_path_dsjctn, find_reversed_path, deduplicate_disjunctions, PathRequest | ||||
| from gnpy.topology.spectrum_assignment import (build_oms_list, align_grids, nvalue_to_frequency, | ||||
|                                            bitmap_sum, Bitmap, spectrum_selection, pth_assign_spectrum) | ||||
|                                                bitmap_sum, Bitmap, spectrum_selection, pth_assign_spectrum, | ||||
|                                                build_path_oms_id_list, aggregate_oms_bitmap) | ||||
| from gnpy.tools.json_io import (load_equipment, load_network, requests_from_json, disjunctions_from_json, | ||||
|                                 _check_one_request) | ||||
|  | ||||
| @@ -45,8 +46,7 @@ def equipment(): | ||||
|  | ||||
| @pytest.fixture() | ||||
| def setup(equipment): | ||||
|     """ common setup for tests: builds network, equipment and oms only once | ||||
|     """ | ||||
|     """common setup for tests: builds network, equipment and oms only once""" | ||||
|     network = load_network(NETWORK_FILENAME, equipment) | ||||
|     spectrum = equipment['SI']['default'] | ||||
|     p_db = spectrum.power_dbm | ||||
| @@ -57,7 +57,7 @@ def setup(equipment): | ||||
|  | ||||
|  | ||||
| def test_oms(setup): | ||||
|     """ tests that the OMS is between two ROADMs, that there is no ROADM or transceivers in the OMS | ||||
|     """tests that the OMS is between two ROADMs, that there is no ROADM or transceivers in the OMS | ||||
|     except end points, checks that the id of OMS is present in the element and that the element | ||||
|     OMS id is consistant | ||||
|     """ | ||||
| @@ -150,8 +150,7 @@ def test_aligned(nmin, nmax, setup): | ||||
| @pytest.mark.parametrize('nval1', [0, 15, 24]) | ||||
| @pytest.mark.parametrize('nval2', [8, 12]) | ||||
| def test_assign_and_sum(nval1, nval2, setup): | ||||
|     """ checks that bitmap sum gives correct result | ||||
|     """ | ||||
|     """checks that bitmap sum gives correct result""" | ||||
|     network, oms_list = setup | ||||
|     guardband = grid | ||||
|     mval = 4  # slot in 12.5GHz | ||||
| @@ -198,8 +197,7 @@ def test_assign_and_sum(nval1, nval2, setup): | ||||
|  | ||||
|  | ||||
| def test_bitmap_assignment(setup): | ||||
|     """ test that a bitmap can be assigned | ||||
|     """ | ||||
|     """test that a bitmap can be assigned""" | ||||
|     network, oms_list = setup | ||||
|     random_oms = oms_list[2] | ||||
|     random_oms.assign_spectrum(13, 7) | ||||
| @@ -216,8 +214,7 @@ def test_bitmap_assignment(setup): | ||||
|  | ||||
| @pytest.fixture() | ||||
| def services(equipment): | ||||
|     """ common setup for service list: builds service only once | ||||
|     """ | ||||
|     """common setup for service list: builds service only once""" | ||||
|     with open(SERVICE_FILENAME, encoding='utf-8') as my_f: | ||||
|         services = json.loads(my_f.read()) | ||||
|     return services | ||||
| @@ -225,25 +222,24 @@ def services(equipment): | ||||
|  | ||||
| @pytest.fixture() | ||||
| def requests(equipment, services): | ||||
|     """ common setup for requests, builds requests list only once | ||||
|     """ | ||||
|     """common setup for requests, builds requests list only once""" | ||||
|     requests = requests_from_json(services, equipment) | ||||
|     return requests | ||||
|  | ||||
|  | ||||
| def test_spectrum_assignment_on_path(equipment, setup, requests): | ||||
|     """ test assignment functions on path and network | ||||
|     """ | ||||
|     """test assignment functions on path and network""" | ||||
|     network, oms_list = setup | ||||
|     req = [deepcopy(requests[1])] | ||||
|     paths = compute_path_dsjctn(network, equipment, req, []) | ||||
|  | ||||
|     first_path_oms = build_path_oms_id_list(paths[0]) | ||||
|     print(req) | ||||
|     for nval in range(100): | ||||
|         req = [deepcopy(requests[1])] | ||||
|         (center_n, startn, stopn), path_oms = spectrum_selection(paths[0], oms_list, 4) | ||||
|         test_oms = aggregate_oms_bitmap(first_path_oms, oms_list) | ||||
|         center_n, startn, stopn = spectrum_selection(test_oms, 4) | ||||
|         pth_assign_spectrum(paths, req, oms_list, [find_reversed_path(paths[0])]) | ||||
|         print(f'testing on following oms {path_oms}') | ||||
|         print(f'testing on following oms {first_path_oms}') | ||||
|         # check that only 96 channels are feasible | ||||
|         if nval >= 96: | ||||
|             print(center_n, startn, stopn) | ||||
| @@ -256,13 +252,15 @@ def test_spectrum_assignment_on_path(equipment, setup, requests): | ||||
|  | ||||
|     req = [requests[2]] | ||||
|     paths = compute_path_dsjctn(network, equipment, req, []) | ||||
|     (center_n, startn, stopn), path_oms = spectrum_selection(paths[0], oms_list, 4, 478) | ||||
|     second_path_oms = build_path_oms_id_list(paths[0]) | ||||
|     test_oms = aggregate_oms_bitmap(second_path_oms, oms_list) | ||||
|     center_n, startn, stopn = spectrum_selection(test_oms, 4, 478) | ||||
|     print(oms_list[0].spectrum_bitmap.freq_index_max) | ||||
|     print(oms_list[0]) | ||||
|     print(center_n, startn, stopn) | ||||
|     print('spectrum selection error: should be None') | ||||
|     assert center_n is None and startn is None and stopn is None | ||||
|     (center_n, startn, stopn), path_oms = spectrum_selection(paths[0], oms_list, 4, 477) | ||||
|     center_n, startn, stopn = spectrum_selection(test_oms, 4, 477) | ||||
|     print(center_n, startn, stopn) | ||||
|     print('spectrum selection error should not be None') | ||||
|     assert center_n is not None and startn is not None and stopn is not None | ||||
| @@ -270,8 +268,7 @@ def test_spectrum_assignment_on_path(equipment, setup, requests): | ||||
|  | ||||
| @pytest.fixture() | ||||
| def request_set(): | ||||
|     """ creates default request dict | ||||
|     """ | ||||
|     """creates default request dict""" | ||||
|     return { | ||||
|         'request_id': '0', | ||||
|         'source': 'trx a', | ||||
| @@ -295,29 +292,28 @@ def request_set(): | ||||
|         'min_spacing': 37.5e9, | ||||
|         'nb_channel': None, | ||||
|         'power': 0, | ||||
|         'path_bandwidth': 800e9} | ||||
|         'path_bandwidth': 800e9, | ||||
|         'equalization_offset_db': 0} | ||||
|  | ||||
|  | ||||
| def test_freq_slot_exist(setup, equipment, request_set): | ||||
|     """ test that assignment works even if effective_freq_slot is not populated | ||||
|     """ | ||||
|     """test that assignment works even if effective_freq_slot is not populated""" | ||||
|     network, oms_list = setup | ||||
|     params = request_set | ||||
|     params['effective_freq_slot'] = None | ||||
|     params['effective_freq_slot'] = [{'N': None, 'M': None}] | ||||
|     rqs = [PathRequest(**params)] | ||||
|     paths = compute_path_dsjctn(network, equipment, rqs, []) | ||||
|     pth_assign_spectrum(paths, rqs, oms_list, [find_reversed_path(paths[0])]) | ||||
|     assert rqs[0].N == -256 | ||||
|     assert rqs[0].M == 32 | ||||
|     assert rqs[0].N == [-256] | ||||
|     assert rqs[0].M == [32] | ||||
|  | ||||
|  | ||||
| def test_inconsistant_freq_slot(setup, equipment, request_set): | ||||
|     """ test that an inconsistant M correctly raises an error | ||||
|     """ | ||||
|     """test that an inconsistant M correctly raises an error""" | ||||
|     network, oms_list = setup | ||||
|     params = request_set | ||||
|     # minimum required nb of slots is 32 (800Gbit/100Gbit/s channels each occupying 50GHz ie 4 slots) | ||||
|     params['effective_freq_slot'] = {'N': 0, 'M': 4} | ||||
|     params['effective_freq_slot'] = [{'N': 0, 'M': 4}] | ||||
|     with pytest.raises(ServiceError): | ||||
|         _check_one_request(params, 196.05e12) | ||||
|     params['trx_mode'] = None | ||||
| @@ -327,27 +323,59 @@ def test_inconsistant_freq_slot(setup, equipment, request_set): | ||||
|     assert rqs[0].blocking_reason == 'NOT_ENOUGH_RESERVED_SPECTRUM' | ||||
|  | ||||
|  | ||||
| @pytest.mark.parametrize('n, m, final_n, final_m, blocking_reason', [ | ||||
| @pytest.mark.parametrize('req_n, req_m, final_n, final_m, blocking_reason, raises_error', [ | ||||
|     # regular requests that should be correctly assigned: | ||||
|     (-100, 32, -100, 32, None), | ||||
|     (150, 50, 150, 50, None), | ||||
|     ([-100], [32], [-100], [32], None, False), | ||||
|     ([150], [50], [150], [50], None, False), | ||||
|     # if n is None, there should be an assignment (enough spectrum cases) | ||||
|     # and the center frequency should be set on the lower part of the spectrum based on m value if it exists | ||||
|     # or based on 32 | ||||
|     (None, 32, -256, 32, None), | ||||
|     (None, 40, -248, 40, None), | ||||
|     (-100, None, -100, 32, None), | ||||
|     (None, None, -256, 32, None), | ||||
|     ([None], [32], [-256], [32], None, False), | ||||
|     ([None], [40], [-248], [40], None, False), | ||||
|     ([-100], [None], [-100], [32], None, False), | ||||
|     ([None], [None], [-256], [32], None, False), | ||||
|     # -280 and 60 center indexes should result in unfeasible spectrum, either out of band or | ||||
|     # overlapping with occupied spectrum. The requested spectrum is not available | ||||
|     (-280, None, None, None, 'NO_SPECTRUM'), | ||||
|     (-60, 40, None, None, 'NO_SPECTRUM'), | ||||
|     ([None], [300], None, None, 'NO_SPECTRUM', False), | ||||
|     ([-280], [None], None, None, 'NO_SPECTRUM', False), | ||||
|     ([-60], [40], None, None, 'NO_SPECTRUM', False), | ||||
|     # raises service error: M value too small | ||||
|     ([-60], [3], None, None, 'NOT_ENOUGH_RESERVED_SPECTRUM', True), | ||||
|     # 20 is smaller than min 32 required nb of slots so should also be blocked | ||||
|     (-60, 20, None, None, 'NOT_ENOUGH_RESERVED_SPECTRUM') | ||||
|     ]) | ||||
| def test_n_m_requests(setup, equipment, n, m, final_n, final_m, blocking_reason, request_set): | ||||
|     """ test that various N and M values for a request end up with the correct path assgnment | ||||
|     """ | ||||
|     ([-60], [20], None, None, 'NOT_ENOUGH_RESERVED_SPECTRUM', False), | ||||
|     # multiple assignments | ||||
|     ([-100, -164], [16, 16], [-100, -164], [16, 16], None, False), | ||||
|     ([-100, -164], [32, 32], [-100, -164], [32, 32], None, False), | ||||
|     ([-100, -164], [None, None], [-164], [32], None, False), | ||||
|     ([None, None], [16, 16], [-272, -240], [16, 16], None, False), | ||||
|     ([None, None, None], [16, 16, None], [-272, -240], [16, 16], None, False), | ||||
|     ([None, None], [None, None], [-256], [32], None, False), | ||||
|     ([-272, None], [16, 16], [-272, -240], [16, 16], None, False), | ||||
|     ([-272, 100], [None, 16], [-272, 100], [16, 16], None, False), | ||||
|     # first assign defined Ms whatever the N (but order them), and then uses imposed N. Fill in with the max | ||||
|     # available nb of slots (centered on N). | ||||
|     ([-88, -100, -116, None], [8, None, 12, None], [-88, -100, -116, -280], [8, 4, 12, 8], None, False), | ||||
|     # If no M is defined, uses th Ns to fill in with the max possible nb of slots (with respecte to request, | ||||
|     # here it is 32 slots) | ||||
|     ([-88, -106, -116, None], [None, None, None, None], [-116], [32], None, False), | ||||
|     # if one defined N, M is not applicable then blocks the spectrum (even f other slots are OK) | ||||
|     # only 2 slots remains between  -104 (-100 - 4) and -108 (-112 + 4). So (-106, None) is not feasible, because min | ||||
|     # required M is 4 for Voyager, Mode 1 | ||||
|     ([-100, -106, -112], [4, None, 4], None, None, 'NO_SPECTRUM', False), | ||||
|     # required nb of channels is 8 with 4 slots each. Next two spectrum are not providing enough spectrum | ||||
|     # raises service error: not enough nb of channels | ||||
|     ([-88, -100, -116], [4, 4, 4], None, None, 'NOT_ENOUGH_RESERVED_SPECTRUM', True), | ||||
|     ([-88, -100, -116], [4, None, 4], None, None, 'NO_SPECTRUM', False), | ||||
|     # only 4 slots remains between -96 (-88 -8) and -104 (-116 + 12), and centered on -100, so N = -101 is not | ||||
|     # feasible whatever the M. | ||||
|     ([-88, -101, -116, None], [8, 4, 12, None], None, None, 'NO_SPECTRUM', False), | ||||
|     ([-88, -101, -116, -250], [4, 4, 12, 12], None, None, 'NO_SPECTRUM', False), | ||||
|     ([-88, -101, -116, None], [8, None, 12, None], None, None, 'NO_SPECTRUM', False), | ||||
|     # raises service error: slots overlap | ||||
|     ([-88, -81, -116, -136], [8, 8, 12, 8], None, None, 'NO_SPECTRUM', True), | ||||
| ]) | ||||
| def test_n_m_requests(setup, equipment, req_n, req_m, final_n, final_m, blocking_reason, raises_error, request_set): | ||||
|     """test that various N and M values for a request end up with the correct path assignment""" | ||||
|     network, oms_list = setup | ||||
|     # add an occupation on one of the span of the expected path OMS list on both directions | ||||
|     # as defined by its offsets within the OMS list: [17, 20, 13, 22] and reversed path [19, 16, 21, 26] | ||||
| @@ -356,7 +384,10 @@ def test_n_m_requests(setup, equipment, n, m, final_n, final_m, blocking_reason, | ||||
|     some_oms = oms_list[expected_oms[3]] | ||||
|     some_oms.assign_spectrum(-30, 32)    # means that spectrum is occupied from indexes -62 to 1 on reversed path | ||||
|     params = request_set | ||||
|     params['effective_freq_slot'] = {'N': n, 'M': m} | ||||
|     params['effective_freq_slot'] = [{'N': n, 'M': m} for n, m in zip(req_n, req_m)] | ||||
|     if raises_error: | ||||
|         with pytest.raises(ServiceError): | ||||
|             _check_one_request(params, 196.3e12) | ||||
|     rqs = [PathRequest(**params)] | ||||
|  | ||||
|     paths = compute_path_dsjctn(network, equipment, rqs, []) | ||||
| @@ -372,9 +403,7 @@ def test_n_m_requests(setup, equipment, n, m, final_n, final_m, blocking_reason, | ||||
|  | ||||
|  | ||||
| def test_reversed_direction(equipment, setup, requests, services): | ||||
|     """ checks that if spectrum is selected on one direction it is also selected on reversed | ||||
|         direction | ||||
|     """ | ||||
|     """checks that if spectrum is selected on one direction it is also selected on reversed direction""" | ||||
|     network, oms_list = setup | ||||
|     dsjn = disjunctions_from_json(services) | ||||
|     dsjn = deduplicate_disjunctions(dsjn) | ||||
| @@ -392,8 +421,9 @@ def test_reversed_direction(equipment, setup, requests, services): | ||||
|         if pth: | ||||
|             number_wl = ceil(requests[i].path_bandwidth / requests[i].bit_rate) | ||||
|             requested_m = ceil(requests[i].spacing / slot) * number_wl | ||||
|             (center_n, startn, stopn), path_oms = spectrum_selection(pth, oms_list, requested_m, | ||||
|                                                                      requested_n=None) | ||||
|             path_oms = build_path_oms_id_list(pth) | ||||
|             test_oms = aggregate_oms_bitmap(path_oms, oms_list) | ||||
|             center_n, startn, stopn = spectrum_selection(test_oms, requested_m, requested_n=None) | ||||
|             spectrum_list.append([center_n, startn, stopn]) | ||||
|         else: | ||||
|             spectrum_list.append([]) | ||||
|   | ||||
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