Add documentation for multiband

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

.docker-travis.sh

@@ -1,47 +0,0 @@
-#!/bin/bash
-
-set -e
-
-IMAGE_NAME=telecominfraproject/oopt-gnpy
-IMAGE_TAG=$(git describe --tags)
-
-ALREADY_FOUND=0
-docker pull ${IMAGE_NAME}:${IMAGE_TAG} && ALREADY_FOUND=1
-
-if [[ $ALREADY_FOUND == 0 ]]; then
-  docker build . -t ${IMAGE_NAME}
-  docker tag ${IMAGE_NAME} ${IMAGE_NAME}:${IMAGE_TAG}
-
-  # shared directory setup: do not clobber the real data
-  mkdir trash
-  cd trash
-  docker run -it --rm --volume $(pwd):/shared ${IMAGE_NAME} gnpy-transmission-example
-else
-  echo "Image ${IMAGE_NAME}:${IMAGE_TAG} already available, will just update the other tags"
-fi
-
-docker images
-
-do_docker_login() {
-  echo "${DOCKER_PASSWORD}" | docker login -u "${DOCKER_USERNAME}" --password-stdin
-}
-
-if [[ "${TRAVIS_PULL_REQUEST}" == "false" ]]; then
-  if [[ "${TRAVIS_BRANCH}" == "develop" || "${TRAVIS_BRANCH}" == "docker" ]]; then
-    echo "Publishing latest"
-    docker tag ${IMAGE_NAME}:${IMAGE_TAG} ${IMAGE_NAME}:latest
-    do_docker_login
-    if [[ $ALREADY_FOUND == 0 ]]; then
-      docker push ${IMAGE_NAME}:${IMAGE_TAG}
-    fi
-    docker push ${IMAGE_NAME}:latest
-  elif [[ "${TRAVIS_BRANCH}" == "master" ]]; then
-    echo "Publishing stable"
-    docker tag ${IMAGE_NAME}:${IMAGE_TAG} ${IMAGE_NAME}:stable
-    do_docker_login
-    if [[ $ALREADY_FOUND == 0 ]]; then
-      docker push ${IMAGE_NAME}:${IMAGE_TAG}
-    fi
-    docker push ${IMAGE_NAME}:stable
-  fi
-fi

.github/workflows/main.yml

@@ -11,22 +11,26 @@ jobs:
     name: Tox test
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
-      - uses: fedora-python/tox-github-action@v0.4
+      - uses: fedora-python/tox-github-action@v37.0
         with:
           tox_env: ${{ matrix.tox_env }}
           dnf_install: ${{ matrix.dnf_install }}
-      - uses: codecov/codecov-action@29386c70ef20e286228c72b668a06fd0e8399192
+      - uses: codecov/codecov-action@v3.1.1
         if: ${{ endswith(matrix.tox_env, '-cover') }}
         with:
           files: ${{ github.workspace }}/cover/coverage.xml
     strategy:
+      fail-fast: false
       matrix:
         tox_env:
           - py38
-          - py39-cover
+          - py39
+          - py310
+          - py311
+          - py312-cover
         include:
           - tox_env: docs
             dnf_install: graphviz
@@ -37,13 +41,13 @@ jobs:
     name: PyPI packaging
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v4
         name: Install Python
         with:
-          python-version: '3.9'
+          python-version: '3.12'
       - uses: casperdcl/deploy-pypi@bb869aafd89f657ceaafe9561d3b5584766c0f95
         with:
           password: ${{ secrets.PYPI_API_TOKEN }}
@@ -61,7 +65,7 @@ jobs:
         with:
           username: jktjkt
           password: ${{ secrets.DOCKERHUB_TOKEN }}
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
       - name: Extract tag name
@@ -91,21 +95,51 @@ jobs:
             telecominfraproject/oopt-gnpy:${{ steps.extract_tag_name.outputs.GIT_DESC }}
             telecominfraproject/oopt-gnpy:latest
 
-  windows:
-    name: Tests on Windows
-    runs-on: windows-2019
+  other-platforms:
+    name: Tests on other platforms
+    runs-on: ${{ matrix.os }}
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python_version }}
       - run: |
-          pip install --editable .
-          pip install 'pytest>=5.0.0,<6'
+          pip install --editable .[tests]
           pytest -vv
     strategy:
+      fail-fast: false
       matrix:
-        python_version:
-          - "3.9"
+        include:
+          - os: windows-2019
+            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 --editable .[tests]
+          pytest -vv
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - os: macos-13-xlarge # Apple M1 CPU
+            python_version: "3.12"

.lgtm.yml

@@ -0,0 +1,3 @@
+queries:
+- exclude: py/clear-text-logging-sensitive-data
+- exclude: py/clear-text-storage-sensitive-data

.readthedocs.yml

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

.travis.yml

@@ -1,27 +0,0 @@
-dist: focal
-os: linux
-language: python
-services: docker
-python:
-  - "3.8"
-  - "3.9"
-before_install:
-  - sudo apt-get -y install graphviz
-install: skip
-script:
-  - pip install --editable .
-  - pip install pytest-cov rstcheck
-  - pytest --cov-report=xml --cov=gnpy -v
-  - pip install -r docs/requirements.txt
-  - rstcheck --ignore-roles cite *.rst
-  - sphinx-build -W --keep-going docs/ x-throwaway-location
-after_success:
-  - bash <(curl -s https://codecov.io/bash)
-jobs:
-  include:
-    - stage: test
-      name: Docker image
-      script:
-        - git fetch --unshallow
-        - ./.docker-travis.sh
-        - docker images

.zuul.yaml

@@ -2,25 +2,33 @@
 - project:
     check:
       jobs:
-        - tox-py38-f34
-        - tox-py39-cover
-        - tox-docs-f34
+        - tox-py38:
+            vars:
+              ensure_tox_version: '<4'
+        - tox-py39:
+            vars:
+              ensure_tox_version: '<4'
+        - tox-py310-cover:
+            vars:
+              ensure_tox_version: '<4'
+        - tox-docs-f36:
+            vars:
+              ensure_tox_version: '<4'
         - coverage-diff:
             voting: false
             dependencies:
-              - tox-py39-cover-previous
-              - tox-py39-cover
+              - tox-py310-cover-previous
+              - tox-py310-cover
             vars:
-              coverage_job_name_previous: tox-py39-cover-previous
-              coverage_job_name_current: tox-py39-cover
+              coverage_job_name_previous: tox-py310-cover-previous
+              coverage_job_name_current: tox-py310-cover
         - tox-linters-diff-n-report:
             voting: false
-        - tox-py39-cover-previous
-    gate:
-      jobs:
-        - tox-py38-f34
-        - tox-py39-f34
-        - tox-docs-f34
+            vars:
+              ensure_tox_version: '<4'
+        - tox-py310-cover-previous:
+            vars:
+              ensure_tox_version: '<4'
     tag:
       jobs:
         - oopt-release-python:

AUTHORS.rst

@@ -11,18 +11,21 @@ To learn how to contribute, please see CONTRIBUTING.md
 - Brian Taylor (Facebook) <briantaylor@fb.com>
 - David Boertjes (Ciena) <dboertje@ciena.com>
 - Diego Landa (Facebook) <dlanda@fb.com>
+- Emmanuelle Delfour (Orange) <WEDE7391@orange.com>
 - Esther Le Rouzic (Orange) <esther.lerouzic@orange.com>
 - Gabriele Galimberti (Cisco) <ggalimbe@cisco.com>
 - Gert Grammel (Juniper Networks) <ggrammel@juniper.net>
+- Giacomo Borraccini (Politecnico di Torino) <giacomo.borraccini@polito.it>
 - Gilad Goldfarb (Facebook) <giladg@fb.com>
 - James Powell (Telecom Infra Project) <james.powell@telecominfraproject.com>
-- Jan Kundrát (Telecom Infra Project) <jan.kundrat@telecominfraproject.com>
+- Jan Kundrát (Telecom Infra Project) <jkt@jankundrat.com>
 - Jeanluc Augé (Orange) <jeanluc.auge@orange.com>
 - Jonas Mårtensson (RISE) <jonas.martensson@ri.se>
 - Mattia Cantono (Politecnico di Torino) <mattia.cantono@polito.it>
 - Miguel Garrich (University Catalunya) <miquel.garrich@upct.es>
 - Raj Nagarajan (Lumentum) <raj.nagarajan@lumentum.com>
 - Roberts Miculens (Lattelecom) <roberts.miculens@lattelecom.lv>
+- Sami Alavi (NUST) <sami.mansooralavi1999@gmail.com>
 - Shengxiang Zhu (University of Arizona) <szhu@email.arizona.edu>
 - Stefan Melin (Telia Company) <Stefan.Melin@teliacompany.com>
 - Vittorio Curri (Politecnico di Torino) <vittorio.curri@polito.it>

README.md

@@ -3,12 +3,12 @@
 [![Install via pip](https://img.shields.io/pypi/v/gnpy)](https://pypi.org/project/gnpy/)
 [![Python versions](https://img.shields.io/pypi/pyversions/gnpy)](https://pypi.org/project/gnpy/)
 [![Documentation status](https://readthedocs.org/projects/gnpy/badge/?version=master)](http://gnpy.readthedocs.io/en/master/?badge=master)
-[![GitHub Workflow Status](https://img.shields.io/github/workflow/status/Telecominfraproject/oopt-gnpy/build)](https://github.com/Telecominfraproject/oopt-gnpy/actions/workflows/main.yml)
+[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/Telecominfraproject/oopt-gnpy/main.yml)](https://github.com/Telecominfraproject/oopt-gnpy/actions/workflows/main.yml)
 [![Gerrit](https://img.shields.io/badge/patches-via%20Gerrit-blue)](https://review.gerrithub.io/q/project:Telecominfraproject/oopt-gnpy+is:open)
 [![Contributors](https://img.shields.io/github/contributors-anon/Telecominfraproject/oopt-gnpy)](https://github.com/Telecominfraproject/oopt-gnpy/graphs/contributors)
-[![Code Quality via LGTM.com](https://img.shields.io/lgtm/grade/python/github/Telecominfraproject/oopt-gnpy)](https://lgtm.com/projects/g/Telecominfraproject/oopt-gnpy/)
 [![Code Coverage via codecov](https://img.shields.io/codecov/c/github/Telecominfraproject/oopt-gnpy)](https://codecov.io/gh/Telecominfraproject/oopt-gnpy)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3458319.svg)](https://doi.org/10.5281/zenodo.3458319)
+[![Matrix chat](https://img.shields.io/matrix/oopt-gnpy:matrix.org)](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.
@@ -23,7 +23,9 @@ Read our [documentation](https://gnpy.readthedocs.io/), learn from the demos, an
 
 This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power:
 
-![Running a simple simulation example](https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg)
+![Running a simple simulation example](docs/images/gnpy-transmission-example.svg)
 
 GNPy can do much more, including acting as a Path Computation Engine, tracking bandwidth requests, or advising the SDN controller about a best possible path through a large DWDM network.
-Learn more about this [in the documentation](https://gnpy.readthedocs.io/).
+Learn more about this [in the documentation](https://gnpy.readthedocs.io/), or give it a [try online at `gnpy.app`](https://gnpy.app/):
+
+[![Path propagation at gnpy.app](docs/images/2022-04-12-gnpy-app.png)](https://gnpy.app/)

docs/about-project.md

@@ -7,11 +7,12 @@ There are weekly calls about our progress.
 Newcomers, users and telecom operators are especially welcome there.
 We encourage all interested people outside the TIP to [join the project](https://telecominfraproject.com/apply-for-membership/) and especially to [get in touch with us](https://github.com/Telecominfraproject/oopt-gnpy/discussions).
 
+(contributing)=
 ## Contributing
 
 `gnpy` is looking for additional contributors, especially those with experience planning and maintaining large-scale, real-world mesh optical networks.
 
-To get involved, please contact [Jan Kundrát](mailto:jan.kundrat@telecominfraproject.com) or [Gert Grammel](mailto:ggrammel@juniper.net).
+To get involved, please contact [Jan Kundrát](mailto:jkt@jankundrat.com) or [Gert Grammel](mailto:ggrammel@juniper.net).
 
 `gnpy` contributions are currently limited to members of [TIP](http://telecominfraproject.com).
 Membership is free and open to all.

docs/biblio.bib

@@ -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}
+}

docs/concepts.rst

@@ -29,7 +29,7 @@ This path is directional, and all "GNPy elements" along the path match the unidi
 
 The network topology contains not just the physical topology of the network, but also references to the :ref:`equipment library<concepts-equipment>` and a set of *operating parameters* for each entity.
 These parameters include the **fiber length** of each fiber, the connector **attenutation losses**, or an amplifier's specific **gain setting**.
-The topology is specified via :ref:`XLS files<excel>` or via :ref:`JSON<json>`.
+The topology is specified via :ref:`XLS files<excel>` or via :ref:`JSON<legacy-json>`.
 
 .. _complete-vs-incomplete:
 

docs/conf.py

@@ -65,7 +65,7 @@ author = 'Telecom Infra Project - OOPT PSE Group'
 #
 # This is also used if you do content translation via gettext catalogs.
 # Usually you set "language" from the command line for these cases.
-language = None
+language = 'en'
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
@@ -84,18 +84,11 @@ todo_include_todos = False
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
-on_rtd = os.environ.get('READTHEDOCS') == 'True'
-if on_rtd:
-    html_theme = 'default'
-    html_theme_options = {
-        'logo_only': True,
-    }
-else:
-    html_theme = 'alabaster'
-    html_theme_options = {
-        'logo': 'images/GNPy-logo.png',
-        'logo_name': False,
-    }
+html_theme = 'alabaster'
+html_theme_options = {
+    'logo': 'images/GNPy-logo.png',
+    'logo_name': False,
+}
 
 html_logo = 'images/GNPy-logo.png'
 
@@ -190,3 +183,5 @@ autodoc_default_options = {
 }
 
 graphviz_output_format = 'svg'
+
+bibtex_bibfiles = ['biblio.bib']

docs/extending.rst

@@ -4,7 +4,7 @@ Extending GNPy with vendor-specific data
 ========================================
 
 GNPy ships with an :ref:`equipment library<concepts-equipment>` containing machine-readable datasheets of networking equipment.
-Vendors who are willing to contribute descriptions of their supported products are encouraged to `submit a patch <https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html>`__.
+Vendors who are willing to contribute descriptions of their supported products are encouraged to `submit a patch <https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html>`__ -- or just :ref:`get in touch with us directly<contributing>`.
 
 This chapter discusses option for modeling performance of :ref:`EDFA amplifiers<extending-edfa>`, :ref:`Raman amplifiers<extending-raman>`, :ref:`transponders<extending-transponder>` and :ref:`ROADMs<extending-roadm>`.
 
@@ -29,7 +29,7 @@ The NF is expressed as a third-degree polynomial:
 
        f(x) &= \text{a}x^3 + \text{b}x^2 + \text{c}x + \text{d}
 
-  \text{NF} &= f(G_\text{max} - G)
+  \text{NF} &= f(G - G_\text{max})
 
 This model can be also used for fixed-gain fixed-NF amplifiers.
 In that case, use:
@@ -91,7 +91,8 @@ Advanced Specification
 **********************
 
 The amplifier performance can be further described in terms of gain ripple, NF ripple, and the dynamic gain tilt.
-When provided, the amplifier characteristic is fine-tuned as a function of carrier frequency.
+When provided, the amplifier characteristic is fine-tuned as a function of carrier frequency. Note that in this advanced
+specification tilt is defined vs frequency while tilt_target specified in EDFA instances is defined vs wavelength.
 
 .. _extending-raman:
 
@@ -100,10 +101,10 @@ Raman Amplifiers
 
 An accurate simulation of Raman amplification requires knowledge of:
 
-- the *power* and *wavelength* of all Raman pumping lasers,
-- the *direction*, whether it is co-propagating or counter-propagating,
-- the Raman efficiency of the fiber,
-- the fiber temperature.
+* the *power* and *wavelength* of all Raman pumping lasers,
+* the *direction*, whether it is co-propagating or counter-propagating,
+* the Raman efficiency of the fiber,
+* the fiber temperature.
 
 Under certain scenarios it is useful to be able to run a simulation without an accurate Raman description.
 For these purposes, it is possible to approximate a Raman amplifier via a fixed-gain EDFA with the :ref:`polynomial NF<ext-nf-model-polynomial-NF>` model using :math:`\text{a} = \text{b} = \text{c} = 0`, and a desired effective :math:`\text{d} = NF`.
@@ -119,38 +120,32 @@ A *mode* usually refers to a particular performance point that is defined by a c
 
 The following data are required for each mode:
 
-``bit-rate``
-  Data bit rate, in :math:`\text{Gbits}\times s^{-1}`.
-``baud-rate``
-  Symbol modulation rate, in :math:`\text{Gbaud}`.
-``required-osnr``
-  Minimal allowed OSNR for the receiver.
+``bit_rate``
+  Data bit rate, in :math:`\text{bits}\times s^{-1}`.
+``baud_rate``
+  Symbol modulation rate, in :math:`\text{baud}`.
+``OSNR``
+  Minimal required OSNR for the receiver. In :math:`\text{dB}`
 ``tx-osnr``
-  Initial OSNR at the transmitter's output.
-``grid-spacing``
+  Initial OSNR at the transmitter's output. In :math:`\text{dB}`
+``min-spacing``
   Minimal grid spacing, i.e., an effective channel spectral bandwidth.
   In :math:`\text{Hz}`.
-``tx-roll-off``
+``roll-off``
   Roll-off parameter (:math:`\beta`) of the TX pulse shaping filter.
   This assumes a raised-cosine filter.
 ``rx-power-min`` and ``rx-power-max``
-  The allowed range of power at the receiver.
+  (work in progress) The allowed range of power at the receiver.
   In :math:`\text{dBm}`.
-``cd-max``
-  Maximal allowed Chromatic Dispersion (CD).
-  In :math:`\text{ps}/\text{nm}`.
-``pmd-max``
-  Maximal allowed Polarization Mode Dispersion (PMD).
-  In :math:`\text{ps}`.
-``cd-penalty``
-  *Work-in-progress.*
-  Describes the increase of the requires GSNR as the :abbr:`CD (Chromatic Dispersion)` deteriorates.
-``dgd-penalty``
-  *Work-in-progress.*
-  Describes the increase of the requires GSNR as the :abbr:`DGD (Differential Group Delay)` deteriorates.
-``pmd-penalty``
-  *Work-in-progress.*
-  Describes the increase of the requires GSNR as the :abbr:`PMD (Polarization Mode Dispersion)` deteriorates.
+``penalties``
+  Impairments such as Chromatic Dispersion (CD), Polarization Mode Dispersion (PMD), and Polarization Dispersion Loss (PDL)
+  result in penalties at the receiver. The receiver's ability to handle these impairments can be defined for each mode as
+  a list of {impairment: in defined units, 'penalty_value' in dB} (see `transceiver section here <json.rst#_transceiver>`).
+  Maximum allowed CD, maximum allowed PMD, and maximum allowed PDL should be listed there with corresponding penalties.
+  Impairments experienced during propagation are linearly interpolated between given points to obtain the corresponding penalty.
+  The accumulated penalties are subtracted from the path GSNR before comparing with the minimum required OSNR.
+  Impairments: PMD in :math:`\text{ps}`, CD in :math:`\text{ps/nm}`, PDL in :math:`\text{dB}`, penalty_value in :math:`\text{dB}`
+
 
 GNPy does not directly track the FEC performance, so the type of chosen FEC is likely indicated in the *name* of the selected transponder mode alone.
 
@@ -168,6 +163,7 @@ The set of parameters for each ROADM model therefore includes:
   Per-channel target TX power towards the egress amplifier.
   Within GNPy, a ROADM is expected to attenuate any signal that enters the ROADM node to this level.
   This can be overridden on a per-link in the network topology.
+  Targets can be set using power or power spectral density (see `roadm section here <json.rst#__roadm>`)
 ``pmd``
   Polarization mode dispersion (PMD) penalty of the express path.
   In :math:`\text{ps}`.

docs/index.rst

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

docs/intro.rst

@@ -10,32 +10,33 @@ fully-functional programs.
 
     **Note**: *If you are a network operator or involved in route planning and
     optimization for your organization, please contact project maintainer Jan
-    Kundrát <jan.kundrat@telecominfraproject.com>. gnpy is looking for users with
+    Kundrát <jkt@jankundrat.com>. gnpy is looking for users with
     specific, delineated use cases to drive requirements for future
     development.*
 
-This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power:
+This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power,
+or to run a planning script to check SNR of several services:
 
-.. image:: https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg
+.. image:: images/gnpy-transmission-example.svg
    :width: 100%
    :align: left
    :alt: Running a simple simulation example
 
-By default, this script operates on a single span network defined in
-`gnpy/example-data/edfa_example_network.json <gnpy/example-data/edfa_example_network.json>`_
+By default, the gnpy-transmission-example script operates on a single span network defined in
+`gnpy/example-data/edfa_example_network.json <../gnpy/example-data/edfa_example_network.json>`_
 
 You can specify a different network at the command line as follows. For
 example, to use the CORONET Global network defined in
-`gnpy/example-data/CORONET_Global_Topology.json <gnpy/example-data/CORONET_Global_Topology.json>`_:
+`gnpy/example-data/CORONET_Global_Topology.json <../gnpy/example-data/CORONET_Global_Topology.json>`_:
 
 .. code-block:: shell-session
 
     $ gnpy-transmission-example $(gnpy-example-data)/CORONET_Global_Topology.json
 
 It is also possible to use an Excel file input (for example
-`gnpy/example-data/CORONET_Global_Topology.xls <gnpy/example-data/CORONET_Global_Topology.xls>`_).
+`gnpy/example-data/CORONET_Global_Topology.xls <../gnpy/example-data/CORONET_Global_Topology.xls>`_).
 The Excel file will be processed into a JSON file with the same prefix.
-Further details about the Excel data structure are available `in the documentation <docs/excel.rst>`__.
+Further details about the Excel data structure are available `in the documentation <excel.rst>`__.
 
 The main transmission example will calculate the average signal OSNR and SNR
 across network elements (transceiver, ROADMs, fibers, and amplifiers)
@@ -56,10 +57,10 @@ interference noise.
 Further Instructions for Use
 ----------------------------
 
-Simulations are driven by a set of `JSON <docs/json.rst>`__ or `XLS <docs/excel.rst>`__ files.
+Simulations are driven by a set of `JSON <json.rst>`__ or `XLS <excel.rst>`__ files.
 
 The ``gnpy-transmission-example`` script propagates a spectrum of channels at 32 Gbaud, 50 GHz spacing and 0 dBm/channel. 
-Launch power can be overridden by using the ``--power`` argument.
+Launch power in fiber spans can be overridden by using the ``--power`` argument.
 Spectrum information is not yet parametrized but can be modified directly in the ``eqpt_config.json`` (via the ``SpectralInformation`` -SI- structure) to accommodate any baud rate or spacing.
 The number of channel is computed based on ``spacing`` and ``f_min``, ``f_max`` values.
 
@@ -71,8 +72,8 @@ An experimental support for Raman amplification is available:
        $(gnpy-example-data)/raman_edfa_example_network.json \
        --sim $(gnpy-example-data)/sim_params.json --show-channels
 
-Configuration of Raman pumps (their frequencies, power and pumping direction) is done via the `RamanFiber element in the network topology <gnpy/example-data/raman_edfa_example_network.json>`_.
-General numeric parameters for simulation control are provided in the `gnpy/example-data/sim_params.json <gnpy/example-data/sim_params.json>`_.
+Configuration of Raman pumps (their frequencies, power and pumping direction) is done via the `RamanFiber element in the network topology <../gnpy/example-data/raman_edfa_example_network.json>`_.
+General numeric parameters for simulation control are provided in the `gnpy/example-data/sim_params.json <../gnpy/example-data/sim_params.json>`_.
 
 Use ``gnpy-path-request`` to request several paths at once:
 
@@ -82,7 +83,7 @@ Use ``gnpy-path-request`` to request several paths at once:
      $ gnpy-path-request -o output_file.json \
        meshTopologyExampleV2.xls meshTopologyExampleV2_services.json
 
-This program operates on a network topology (`JSON <docs/json.rst>`__ or `Excel <docs/excel.rst>`__ format), processing the list of service requests (JSON or XLS again).
+This program operates on a network topology (`JSON <json.rst>`__ or `Excel <excel.rst>`__ format), processing the list of service requests (JSON or XLS again).
 The service requests and reply formats are based on the `draft-ietf-teas-yang-path-computation-01 <https://tools.ietf.org/html/draft-ietf-teas-yang-path-computation-01>`__ with custom extensions (e.g., for transponder modes).
 An example of the JSON input is provided in file `service-template.json`, while results are shown in `path_result_template.json`.
 

docs/model.rst

@@ -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.
@@ -145,4 +145,4 @@ Raman Scattering in order to give a proper estimation for all channels
 :cite:`cantono2018modeling`.  This will be the main upgrade required within the
 PSE framework.
 
-.. bibliography:: biblio.bib  
+.. bibliography::

docs/release-notes.rst

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

docs/requirements.txt

@@ -1,7 +0,0 @@
-alabaster>=0.7.12,<1
-docutils>=0.15.2,<1
-myst-parser>=0.14.0,<1
-Pygments>=2.7.4,<3
-rstcheck
-Sphinx>=3.5.0,<4
-sphinxcontrib-bibtex>=0.4.2,<1

gnpy/__init__.py

@@ -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`.
-'''
+"""

gnpy/core/__init__.py

@@ -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`.
-'''
+"""

gnpy/core/ansi_escapes.py

@@ -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'

gnpy/core/equipment.py

@@ -1,73 +1,132 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+"""
 gnpy.core.equipment
 ===================
 
 This module contains functionality for specifying equipment.
-'''
+"""
+from collections import defaultdict
+from functools import reduce
+from typing import List
 
-from gnpy.core.utils import automatic_nch, db2lin
-from gnpy.core.exceptions import EquipmentConfigError
+from gnpy.core.exceptions import EquipmentConfigError, ConfigurationError
 
 
 def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=False):
-    """return the trx and SI parameters from eqpt_config for a given type_variety and mode (ie format)"""
+    """return the trx and SI parameters from eqpt_config for a given type_variety and mode (ie format)
+
+    if the type or mode do no match an existing transceiver in the library, then the function
+    raises an error if error_message is True else returns a default mode based on equipment['SI']['default']
+    If trx_mode is None (but type is valid), it returns an undetermined mode whatever the error message:
+    this is a special case for automatic mode selection.
+    """
     trx_params = {}
     default_si_data = equipment['SI']['default']
+    # default transponder characteristics
+    # mainly used with transmission_main_example.py
+    default_trx_params = {
+        'f_min': default_si_data.f_min,
+        'f_max': default_si_data.f_max,
+        'baud_rate': default_si_data.baud_rate,
+        'spacing': default_si_data.spacing,
+        'OSNR': None,
+        'penalties': {},
+        'bit_rate': None,
+        'cost': None,
+        'roll_off': default_si_data.roll_off,
+        'tx_osnr': default_si_data.tx_osnr,
+        'min_spacing': None,
+        'equalization_offset_db': 0
+    }
+    # Undetermined transponder characteristics
+    # mainly used with path_request_run.py for the automatic mode computation case
+    undetermined_trx_params = {
+        "format": "undetermined",
+        "baud_rate": None,
+        "OSNR": None,
+        "penalties": None,
+        "bit_rate": None,
+        "roll_off": None,
+        "tx_osnr": None,
+        "min_spacing": None,
+        "cost": None,
+        "equalization_offset_db": 0
+    }
 
-    try:
-        trxs = equipment['Transceiver']
-        # if called from path_requests_run.py, trx_mode is filled with None when not specified by user
-        # if called from transmission_main.py, trx_mode is ''
-        if trx_mode is not None:
-            mode_params = next(mode for trx in trxs
-                               if trx == trx_type_variety
-                               for mode in trxs[trx].mode
-                               if mode['format'] == trx_mode)
-            trx_params = {**mode_params}
-            # sanity check: spacing baudrate must be smaller than min spacing
+    trxs = equipment['Transceiver']
+    if trx_type_variety in trxs:
+        modes = {mode['format']: mode for mode in trxs[trx_type_variety].mode}
+        trx_frequencies = {'f_min': trxs[trx_type_variety].frequency['min'],
+                           'f_max': trxs[trx_type_variety].frequency['max']}
+        if trx_mode in modes:
+            # if called from transmission_main.py, trx_mode is ''
+            trx_params = {**modes[trx_mode], **trx_frequencies}
             if trx_params['baud_rate'] > trx_params['min_spacing']:
-                raise EquipmentConfigError(f'Inconsistency in equipment library:\n 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}.')
-        else:
-            mode_params = {"format": "undetermined",
-                           "baud_rate": None,
-                           "OSNR": None,
-                           "bit_rate": None,
-                           "roll_off": None,
-                           "tx_osnr": None,
-                           "min_spacing": None,
-                           "cost": None}
-            trx_params = {**mode_params}
-        trx_params['f_min'] = equipment['Transceiver'][trx_type_variety].frequency['min']
-        trx_params['f_max'] = equipment['Transceiver'][trx_type_variety].frequency['max']
-
-        # TODO: novel automatic feature maybe unwanted if spacing is specified
-        # trx_params['spacing'] = _automatic_spacing(trx_params['baud_rate'])
-        # temp = trx_params['spacing']
-        # print(f'spacing {temp}')
-    except StopIteration:
-        if error_message:
-            raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" with mode "{trx_mode}" in equipment library')
-        else:
-            # default transponder charcteristics
-            # mainly used with transmission_main_example.py
-            trx_params['f_min'] = default_si_data.f_min
-            trx_params['f_max'] = default_si_data.f_max
-            trx_params['baud_rate'] = default_si_data.baud_rate
-            trx_params['spacing'] = default_si_data.spacing
-            trx_params['OSNR'] = None
-            trx_params['bit_rate'] = None
-            trx_params['cost'] = None
-            trx_params['roll_off'] = default_si_data.roll_off
-            trx_params['tx_osnr'] = default_si_data.tx_osnr
-            trx_params['min_spacing'] = None
-            nch = automatic_nch(trx_params['f_min'], trx_params['f_max'], trx_params['spacing'])
-            trx_params['nb_channel'] = nch
-            print(f'There are {nch} channels propagating')
-
-    trx_params['power'] = db2lin(default_si_data.power_dbm) * 1e-3
+                # sanity check: baudrate must be smaller than min spacing
+                raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transponder "{trx_type_variety}" '
+                                           + f'mode "{trx_params["format"]}" has baud rate '
+                                           + f'{trx_params["baud_rate"] * 1e-9:.2f} GHz greater than min_spacing '
+                                           + f'{trx_params["min_spacing"] * 1e-9:.2f}.')
+            trx_params['equalization_offset_db'] = trx_params.get('equalization_offset_db', 0)
+            return trx_params
+        if trx_mode is None:
+            # if called from path_requests_run.py, trx_mode is filled with None when not specified by user
+            trx_params = {**undetermined_trx_params, **trx_frequencies}
+            return trx_params
+    if trx_type_variety in trxs and error_message:
+        raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" with mode "{trx_mode}" '
+                                   + 'in equipment library')
+    if error_message:
+        raise EquipmentConfigError(f'Could not find transponder "{trx_type_variety}" in equipment library')
 
+    trx_params = {**default_trx_params}
     return trx_params
+
+
+def find_type_variety(amps: List[str], equipment: dict) -> str:
+    """Returns the multiband type_variety associated with a list of single band type_varieties
+    Args:
+    amps (List[str]): A list of single band type_varieties.
+    equipment (dict): A dictionary containing equipment information.
+
+    Returns:
+    str: an amplifier type variety
+    """
+    listes = find_type_varieties(amps, equipment)
+
+    _found_type = list(reduce(lambda x, y: set(x) & set(y), listes))
+    # Given a list of single band amplifiers, find the multiband amplifier whose multi_band group
+    # matches. For example, if amps list contains ["a1_LBAND", "a2_CBAND"], with a1.multi_band = [a1_LBAND, a1_CBAND]
+    # and a2.multi_band = [a1_LBAND, a2_CBAND], then:
+    # possible_type_varieties = {"a1_LBAND": ["a1", "a2"], "a2_CBAND": ["a2"]}
+    # listes = [["a1", "a2"],  ["a2"]]
+    # and _found_type = [a2]
+    if not _found_type:
+        msg = f'{amps} amps do not belong to the same amp type {listes}'
+        raise ConfigurationError(msg)
+    return _found_type[0]
+
+
+def find_type_varieties(amps: List[str], equipment: dict) -> List[List[str]]:
+    """Returns the multiband list of type_varieties associated with a list of single band type_varieties
+    Args:
+    amps (List[str]): A list of single band type_varieties.
+    equipment (dict): A dictionary containing equipment information.
+
+    Returns:
+    List[List[str]]: A list of lists containing the multiband type_varieties
+    associated with each single band type_variety.
+    """
+    possible_type_varieties = defaultdict(list)
+    for amp_name, amp in equipment['Edfa'].items():
+        if amp.multi_band is not None:
+            for elem in amp.multi_band:
+                # possible_type_varieties stores the list of multiband amp names that list this elem as
+                # a possible amplifier of the multiband group. For example, if "std_medium_gain_multiband"
+                # and "std_medium_gain_multiband_new" contain "std_medium_gain_C" in their "multi_band" list, then:
+                # possible_type_varieties["std_medium_gain_C"] =
+                # ["std_medium_gain_multiband", "std_medium_gain_multiband_new"]
+                possible_type_varieties[elem].append(amp_name)
+    return [possible_type_varieties[a] for a in amps]

gnpy/core/info.py

@@ -8,49 +8,421 @@ gnpy.core.info
 This module contains classes for modelling :class:`SpectralInformation`.
 """
 
+from __future__ import annotations
 from collections import namedtuple
-from gnpy.core.utils import automatic_nch, lin2db
+from collections.abc import Iterable
+from typing import Union, List
+from dataclasses import dataclass
+from numpy import argsort, mean, array, append, ones, ceil, any, zeros, outer, full, ndarray, asarray
+
+from gnpy.core.utils import automatic_nch, db2lin, watt2dbm
+from gnpy.core.exceptions import SpectrumError
+
+DEFAULT_SLOT_WIDTH_STEP = 12.5e9  # Hz
+"""Channels with unspecified slot width will have their slot width evaluated as the baud rate rounded up to the minimum
+multiple of the DEFAULT_SLOT_WIDTH_STEP (the baud rate is extended including the roll off in this evaluation)"""
 
 
 class Power(namedtuple('Power', 'signal nli ase')):
     """carriers power in W"""
 
 
-class Channel(namedtuple('Channel', 'channel_number frequency baud_rate roll_off power chromatic_dispersion pmd')):
-    """ 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)
-        :param roll_off: the roll off of the signal. It is a pure number between 0 and 1
-        :param power (gnpy.core.info.Power): power of signal, ASE noise and NLI (W)
-        :param chromatic_dispersion: chromatic dispersion (s/m)
-        :param pmd: polarization mode dispersion (s)
+    :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)
+    :param slot_width: the slot width (Hz)
+    :param roll_off: the roll off of the signal. It is a pure number between 0 and 1
+    :param power (gnpy.core.info.Power): power of signal, ASE noise and NLI (W)
+    :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, neq_ch ')):
-    """noiseless reference power in dBm:
-    p_span0: inital target carrier power
-    p_spani: carrier power after element i
-    neq_ch: equivalent channel count in dB"""
+class SpectralInformation(object):
+    """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, latency: array,
+                 delta_pdb_per_channel: array, tx_osnr: array, tx_power: array, label: array):
+        indices = argsort(frequency)
+        self._frequency = frequency[indices]
+        self._df = outer(ones(frequency.shape), frequency) - outer(frequency, ones(frequency.shape))
+        self._number_of_channels = len(self._frequency)
+        self._channel_number = [*range(1, self._number_of_channels + 1)]
+        self._slot_width = slot_width[indices]
+        self._baud_rate = baud_rate[indices]
+        overlap = self._frequency[:-1] + self._slot_width[:-1] / 2 > self._frequency[1:] - self._slot_width[1:] / 2
+        if any(overlap):
+            overlap = [pair for pair in zip(overlap * self._channel_number[:-1], overlap * self._channel_number[1:])
+                       if pair != (0, 0)]
+            raise SpectrumError(f'Spectrum required slot widths larger than the frequency spectral distances '
+                                f'between channels: {overlap}.')
+        exceed = self._baud_rate > self._slot_width
+        if any(exceed):
+            raise SpectrumError(f'Spectrum baud rate, including the roll off, larger than the slot width for channels: '
+                                f'{[ch for ch in exceed * self._channel_number if ch]}.')
+        self._signal = signal[indices]
+        self._nli = nli[indices]
+        self._ase = ase[indices]
+        self._roll_off = roll_off[indices]
+        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._tx_power = tx_power[indices]
+        self._label = label[indices]
+
+    @property
+    def frequency(self):
+        return self._frequency
+
+    @property
+    def df(self):
+        """Matrix of relative frequency distances between all channels. Positive elements in the upper right side."""
+        return self._df
+
+    @property
+    def slot_width(self):
+        return self._slot_width
+
+    @property
+    def baud_rate(self):
+        return self._baud_rate
+
+    @property
+    def number_of_channels(self):
+        return self._number_of_channels
+
+    @property
+    def powers(self):
+        powers = zip(self.signal, self.nli, self.ase)
+        return [Power(*p) for p in powers]
+
+    @property
+    def signal(self):
+        return self._signal
+
+    @signal.setter
+    def signal(self, signal):
+        self._signal = signal
+
+    @property
+    def nli(self):
+        return self._nli
+
+    @nli.setter
+    def nli(self, nli):
+        self._nli = nli
+
+    @property
+    def ase(self):
+        return self._ase
+
+    @ase.setter
+    def ase(self, ase):
+        self._ase = ase
+
+    @property
+    def roll_off(self):
+        return self._roll_off
+
+    @property
+    def chromatic_dispersion(self):
+        return self._chromatic_dispersion
+
+    @chromatic_dispersion.setter
+    def chromatic_dispersion(self, chromatic_dispersion):
+        self._chromatic_dispersion = chromatic_dispersion
+
+    @property
+    def pmd(self):
+        return self._pmd
+
+    @property
+    def label(self):
+        return self._label
+
+    @pmd.setter
+    def pmd(self, pmd):
+        self._pmd = pmd
+
+    @property
+    def pdl(self):
+        return self._pdl
+
+    @pdl.setter
+    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
+
+    @delta_pdb_per_channel.setter
+    def delta_pdb_per_channel(self, delta_pdb_per_channel):
+        self._delta_pdb_per_channel = delta_pdb_per_channel
+
+    @property
+    def tx_osnr(self):
+        return self._tx_osnr
+
+    @tx_osnr.setter
+    def tx_osnr(self, tx_osnr):
+        self._tx_osnr = tx_osnr
+
+    @property
+    def tx_power(self):
+        return self._tx_power
+
+    @tx_power.setter
+    def tx_power(self, tx_power):
+        self._tx_power = tx_power
+
+    @property
+    def channel_number(self):
+        return self._channel_number
+
+    @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.latency)
+        return [Channel(*entry) for entry in entries]
+
+    def apply_attenuation_lin(self, attenuation_lin):
+        self.signal *= attenuation_lin
+        self.nli *= attenuation_lin
+        self.ase *= attenuation_lin
+
+    def apply_attenuation_db(self, attenuation_db):
+        attenuation_lin = 1 / db2lin(attenuation_db)
+        self.apply_attenuation_lin(attenuation_lin)
+
+    def apply_gain_lin(self, gain_lin):
+        self.signal *= gain_lin
+        self.nli *= gain_lin
+        self.ase *= gain_lin
+
+    def apply_gain_db(self, gain_db):
+        gain_lin = db2lin(gain_db)
+        self.apply_gain_lin(gain_lin)
+
+    def __add__(self, other: SpectralInformation):
+        try:
+            return SpectralInformation(frequency=append(self.frequency, other.frequency),
+                                       slot_width=append(self.slot_width, other.slot_width),
+                                       signal=append(self.signal, other.signal), nli=append(self.nli, other.nli),
+                                       ase=append(self.ase, other.ase),
+                                       baud_rate=append(self.baud_rate, other.baud_rate),
+                                       roll_off=append(self.roll_off, other.roll_off),
+                                       chromatic_dispersion=append(self.chromatic_dispersion,
+                                                                   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),
+                                       tx_power=append(self.tx_power, other.tx_power),
+                                       label=append(self.label, other.label))
+        except SpectrumError:
+            raise SpectrumError('Spectra cannot be summed: channels overlapping.')
+
+    def _replace(self, carriers):
+        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])
+        return self
 
 
-class SpectralInformation(namedtuple('SpectralInformation', 'pref carriers')):
-
-    def __new__(cls, pref, carriers):
-        return super().__new__(cls, pref, carriers)
+def create_arbitrary_spectral_information(frequency: Union[ndarray, Iterable, float],
+                                          signal: Union[float, ndarray, Iterable],
+                                          baud_rate: Union[float, ndarray, Iterable],
+                                          tx_osnr: Union[float, ndarray, Iterable],
+                                          tx_power: Union[float, ndarray, Iterable] = None,
+                                          delta_pdb_per_channel: Union[float, ndarray, Iterable] = 0.,
+                                          slot_width: Union[float, ndarray, Iterable] = None,
+                                          roll_off: Union[float, ndarray, Iterable] = 0.,
+                                          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.,
+                                          label: Union[str, ndarray, Iterable] = None):
+    """This is just a wrapper around the SpectralInformation.__init__() that simplifies the creation of
+    a non-uniform spectral information with NLI and ASE powers set to zero."""
+    frequency = asarray(frequency)
+    number_of_channels = frequency.size
+    try:
+        signal = full(number_of_channels, signal)
+        baud_rate = full(number_of_channels, baud_rate)
+        roll_off = full(number_of_channels, roll_off)
+        slot_width = full(number_of_channels, slot_width) if slot_width is not None else \
+            ceil((1 + roll_off) * baud_rate / DEFAULT_SLOT_WIDTH_STEP) * DEFAULT_SLOT_WIDTH_STEP
+        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)
+        tx_osnr = full(number_of_channels, tx_osnr)
+        tx_power = full(number_of_channels, tx_power)
+        label = full(number_of_channels, label)
+        return SpectralInformation(frequency=frequency, slot_width=slot_width,
+                                   signal=signal, nli=nli, ase=ase,
+                                   baud_rate=baud_rate, roll_off=roll_off,
+                                   chromatic_dispersion=chromatic_dispersion,
+                                   pmd=pmd, pdl=pdl, latency=latency,
+                                   delta_pdb_per_channel=delta_pdb_per_channel,
+                                   tx_osnr=tx_osnr, tx_power=tx_power, label=label)
+    except ValueError as e:
+        if 'could not broadcast' in str(e):
+            raise SpectrumError('Dimension mismatch in input fields.')
+        else:
+            raise
 
 
-def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, power, spacing):
-    # pref in dB : convert power lin into power in dB
-    pref = lin2db(power * 1e3)
-    nb_channel = automatic_nch(f_min, f_max, spacing)
-    si = SpectralInformation(
-        pref=Pref(pref, pref, lin2db(nb_channel)),
-        carriers=[
-            Channel(f, (f_min + spacing * f),
-                    baud_rate, roll_off, Power(power, 0, 0), 0, 0) for f in range(1, nb_channel + 1)
-        ]
-    )
-    return si
+def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, spacing, tx_osnr, tx_power,
+                                      delta_pdb=0):
+    """Creates a fixed slot width spectral information with flat power.
+    all arguments are scalar values"""
+    number_of_channels = automatic_nch(f_min, f_max, spacing)
+    frequency = [(f_min + spacing * i) for i in range(1, number_of_channels + 1)]
+    delta_pdb_per_channel = delta_pdb * ones(number_of_channels)
+    label = [f'{baud_rate * 1e-9 :.2f}G' for i in range(number_of_channels)]
+    return create_arbitrary_spectral_information(frequency, slot_width=spacing, signal=tx_power, baud_rate=baud_rate,
+                                                 roll_off=roll_off, delta_pdb_per_channel=delta_pdb_per_channel,
+                                                 tx_osnr=tx_osnr, tx_power=tx_power, label=label)
+
+
+def is_in_band(frequency: float, band: dict) -> bool:
+    """band has {"f_min": value, "f_max": value} format
+    """
+    if frequency >= band['f_min'] and frequency <= band['f_max']:
+        return True
+    return False
+
+
+def demuxed_spectral_information(input_si: SpectralInformation, band: dict) -> SpectralInformation:
+    """extract a si based on band
+    """
+    filtered_indices = [i for i, f in enumerate(input_si.frequency)
+                        if is_in_band(f - input_si.slot_width[i] / 2, band)
+                        and is_in_band(f + input_si.slot_width[i] / 2, band)]
+    if filtered_indices:
+        frequency = input_si.frequency[filtered_indices]
+        baud_rate = input_si.baud_rate[filtered_indices]
+        slot_width = input_si.slot_width[filtered_indices]
+        signal = input_si.signal[filtered_indices]
+        nli = input_si.nli[filtered_indices]
+        ase = input_si.ase[filtered_indices]
+        roll_off = input_si.roll_off[filtered_indices]
+        chromatic_dispersion = input_si.chromatic_dispersion[filtered_indices]
+        pmd = input_si.pmd[filtered_indices]
+        pdl = input_si.pdl[filtered_indices]
+        latency = input_si.latency[filtered_indices]
+        delta_pdb_per_channel = input_si.delta_pdb_per_channel[filtered_indices]
+        tx_osnr = input_si.tx_osnr[filtered_indices]
+        tx_power = input_si.tx_power[filtered_indices]
+        label = input_si.label[filtered_indices]
+
+        return SpectralInformation(frequency=frequency, baud_rate=baud_rate, slot_width=slot_width, signal=signal,
+                                   nli=nli, ase=ase, roll_off=roll_off, chromatic_dispersion=chromatic_dispersion,
+                                   pmd=pmd, pdl=pdl, latency=latency, delta_pdb_per_channel=delta_pdb_per_channel,
+                                   tx_osnr=tx_osnr, tx_power=tx_power, label=label)
+    return None
+
+
+def muxed_spectral_information(input_si_list: List[SpectralInformation]) -> SpectralInformation:
+    """return the assembled spectrum
+    """
+    if input_si_list and len(input_si_list) > 1:
+        si = input_si_list[0] + muxed_spectral_information(input_si_list[1:])
+        return si
+    elif input_si_list and len(input_si_list) == 1:
+        return input_si_list[0]
+    else:
+        raise ValueError('liste vide')
+
+
+def carriers_to_spectral_information(initial_spectrum: dict[float, Carrier],
+                                     power: float) -> SpectralInformation:
+    """Initial spectrum is a dict with key = carrier frequency, and value a Carrier object.
+    :param initial_spectrum: indexed by frequency in Hz, with power offset (delta_pdb), baudrate, slot width,
+    tx_osnr, tx_power and roll off.
+    :param power: power of the request
+    """
+    frequency = list(initial_spectrum.keys())
+    signal = [c.tx_power for c in initial_spectrum.values()]
+    roll_off = [c.roll_off for c in initial_spectrum.values()]
+    baud_rate = [c.baud_rate for c in initial_spectrum.values()]
+    delta_pdb_per_channel = [c.delta_pdb for c in initial_spectrum.values()]
+    slot_width = [c.slot_width for c in initial_spectrum.values()]
+    tx_osnr = [c.tx_osnr for c in initial_spectrum.values()]
+    tx_power = [c.tx_power for c in initial_spectrum.values()]
+    label = [c.label for c in initial_spectrum.values()]
+    return create_arbitrary_spectral_information(frequency=frequency, signal=signal, baud_rate=baud_rate,
+                                                 slot_width=slot_width, roll_off=roll_off,
+                                                 delta_pdb_per_channel=delta_pdb_per_channel, tx_osnr=tx_osnr,
+                                                 tx_power=tx_power, label=label)
+
+
+@dataclass
+class Carrier:
+    """One channel in the initial mixed-type spectrum definition, each type being defined by
+    its delta_pdb (power offset with respect to reference power), baud rate, slot_width, roll_off
+    tx_power, and tx_osnr. delta_pdb offset is applied to target power out of Roadm.
+    Label is used to group carriers which belong to the same partition when printing results.
+    """
+    delta_pdb: float
+    baud_rate: float
+    slot_width: float
+    roll_off: float
+    tx_osnr: float
+    tx_power: float
+    label: str
+
+
+@dataclass
+class ReferenceCarrier:
+    """Reference channel type is used to determine target power out of ROADM for the reference channel when
+    constant power spectral density (PSD) equalization is set. Reference channel is the type that has been defined
+    in SI block and used for the initial design of the network.
+    Computing the power out of ROADM for the reference channel is required to correctly compute the loss
+    experienced by reference channel in Roadm element.
+
+    Baud rate is required to find the target power in constant PSD: power = PSD_target * baud_rate.
+    For example, if target PSD is 3.125e4mW/GHz and reference carrier type a 32 GBaud channel then
+    output power should be -20 dBm and for a 64 GBaud channel power target would need 3 dB more: -17 dBm.
+
+    Slot width is required to find the target power in constant PSW (constant power per slot width equalization):
+    power = PSW_target * slot_width.
+    For example, if target PSW is 2e4mW/GHz and reference carrier type a 32 GBaud channel in a 50GHz slot width then
+    output power should be -20 dBm and for a 64 GBaud channel  in a 75 GHz slot width, power target would be -18.24 dBm.
+
+    Other attributes (like roll-off) may be added there for future equalization purpose.
+    """
+    baud_rate: float
+    slot_width: float

gnpy/core/parameters.py

@@ -7,11 +7,13 @@ gnpy.core.parameters
 
 This module contains all parameters to configure standard network elements.
 """
-
+from collections import namedtuple
+from copy import deepcopy
+from dataclasses import dataclass
 from scipy.constants import c, pi
-from numpy import squeeze, log10, exp
+from numpy import asarray, array, exp, sqrt, log, outer, ones, squeeze, append, flip, linspace, full
 
-from gnpy.core.utils import db2lin, convert_length
+from gnpy.core.utils import convert_length
 from gnpy.core.exceptions import ParametersError
 
 
@@ -28,110 +30,235 @@ class Parameters:
 
 class PumpParams(Parameters):
     def __init__(self, power, frequency, propagation_direction):
-        self._power = power
-        self._frequency = frequency
-        self._propagation_direction = propagation_direction
-
-    @property
-    def power(self):
-        return self._power
-
-    @property
-    def frequency(self):
-        return self._frequency
-
-    @property
-    def propagation_direction(self):
-        return self._propagation_direction
+        self.power = power
+        self.frequency = frequency
+        self.propagation_direction = propagation_direction.lower()
 
 
 class RamanParams(Parameters):
-    def __init__(self, **kwargs):
-        self._flag_raman = kwargs['flag_raman']
-        self._space_resolution = kwargs['space_resolution'] if 'space_resolution' in kwargs else None
-        self._tolerance = kwargs['tolerance'] if 'tolerance' in kwargs else None
+    def __init__(self, flag=False, method='perturbative', order=2, result_spatial_resolution=10e3,
+                 solver_spatial_resolution=10e3):
+        """Simulation parameters used within the Raman Solver
 
-    @property
-    def flag_raman(self):
-        return self._flag_raman
+        :params flag: boolean for enabling/disable the evaluation of the Raman power profile in frequency and position
+        :params method: Raman solver method
+        :params order: solution order for perturbative method
+        :params result_spatial_resolution: spatial resolution of the evaluated Raman power profile
+        :params solver_spatial_resolution: spatial step for the iterative solution of the first order ode
+        """
+        self.flag = flag
+        self.method = method
+        self.order = order
+        self.result_spatial_resolution = result_spatial_resolution  # [m]
+        self.solver_spatial_resolution = solver_spatial_resolution  # [m]
 
-    @property
-    def space_resolution(self):
-        return self._space_resolution
-
-    @property
-    def tolerance(self):
-        return self._tolerance
+    def to_json(self):
+        return {"flag": self.flag,
+                "method": self.method,
+                "order": self.order,
+                "result_spatial_resolution": self.result_spatial_resolution,
+                "solver_spatial_resolution": self.solver_spatial_resolution}
 
 
 class NLIParams(Parameters):
-    def __init__(self, **kwargs):
-        self._nli_method_name = kwargs['nli_method_name']
-        self._wdm_grid_size = kwargs['wdm_grid_size']
-        self._dispersion_tolerance = kwargs['dispersion_tolerance']
-        self._phase_shift_tolerance = kwargs['phase_shift_tolerance']
-        self._f_cut_resolution = None
-        self._f_pump_resolution = None
-        self._computed_channels = kwargs['computed_channels'] if 'computed_channels' in kwargs else None
+    def __init__(self, method='gn_model_analytic', dispersion_tolerance=4, phase_shift_tolerance=0.1,
+                 computed_channels=None, computed_number_of_channels=None):
+        """Simulation parameters used within the Nli Solver
 
-    @property
-    def nli_method_name(self):
-        return self._nli_method_name
+        :params method: formula for NLI calculation
+        :params dispersion_tolerance: tuning parameter for ggn model solution
+        :params phase_shift_tolerance: tuning parameter for ggn model solution
+        :params computed_channels: the NLI is evaluated for these channels and extrapolated for the others
+        :params computed_number_of_channels: the NLI is evaluated for this number of channels equally distributed
+        in the spectrum and extrapolated for the others
+        """
+        self.method = method.lower()
+        self.dispersion_tolerance = dispersion_tolerance
+        self.phase_shift_tolerance = phase_shift_tolerance
+        self.computed_channels = computed_channels
+        self.computed_number_of_channels = computed_number_of_channels
 
-    @property
-    def wdm_grid_size(self):
-        return self._wdm_grid_size
-
-    @property
-    def dispersion_tolerance(self):
-        return self._dispersion_tolerance
-
-    @property
-    def phase_shift_tolerance(self):
-        return self._phase_shift_tolerance
-
-    @property
-    def f_cut_resolution(self):
-        return self._f_cut_resolution
-
-    @f_cut_resolution.setter
-    def f_cut_resolution(self, f_cut_resolution):
-        self._f_cut_resolution = f_cut_resolution
-
-    @property
-    def f_pump_resolution(self):
-        return self._f_pump_resolution
-
-    @f_pump_resolution.setter
-    def f_pump_resolution(self, f_pump_resolution):
-        self._f_pump_resolution = f_pump_resolution
-
-    @property
-    def computed_channels(self):
-        return self._computed_channels
+    def to_json(self):
+        return {"method": self.method,
+                "dispersion_tolerance": self.dispersion_tolerance,
+                "phase_shift_tolerance": self.phase_shift_tolerance,
+                "computed_channels": self.computed_channels,
+                "computed_number_of_channels": self.computed_number_of_channels}
 
 
 class SimParams(Parameters):
-    def __init__(self, **kwargs):
-        try:
-            if 'nli_parameters' in kwargs:
-                self._nli_params = NLIParams(**kwargs['nli_parameters'])
-            else:
-                self._nli_params = None
-            if 'raman_parameters' in kwargs:
-                self._raman_params = RamanParams(**kwargs['raman_parameters'])
-            else:
-                self._raman_params = None
-        except KeyError as e:
-            raise ParametersError(f'Simulation parameters must include {e}. Configuration: {kwargs}')
+    _shared_dict = {'nli_params': NLIParams(), 'raman_params': RamanParams()}
+
+    @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', {}))
 
     @property
     def nli_params(self):
-        return self._nli_params
+        return self._shared_dict['nli_params']
 
     @property
     def raman_params(self):
-        return self._raman_params
+        return self._shared_dict['raman_params']
+
+
+class RoadmParams(Parameters):
+    def __init__(self, **kwargs):
+        self.target_pch_out_db = kwargs.get('target_pch_out_db')
+        self.target_psd_out_mWperGHz = kwargs.get('target_psd_out_mWperGHz')
+        self.target_out_mWperSlotWidth = kwargs.get('target_out_mWperSlotWidth')
+        equalisation_type = ['target_pch_out_db', 'target_psd_out_mWperGHz', 'target_out_mWperSlotWidth']
+        temp = [kwargs.get(k) is not None for k in equalisation_type]
+        if sum(temp) > 1:
+            raise ParametersError('ROADM config contains more than one equalisation type.'
+                                  + 'Please choose only one', kwargs)
+        self.per_degree_pch_out_db = kwargs.get('per_degree_pch_out_db', {})
+        self.per_degree_pch_psd = kwargs.get('per_degree_psd_out_mWperGHz', {})
+        self.per_degree_pch_psw = kwargs.get('per_degree_psd_out_mWperSlotWidth', {})
+        try:
+            self.add_drop_osnr = kwargs['add_drop_osnr']
+            self.pmd = kwargs['pmd']
+            self.pdl = kwargs['pdl']
+            self.restrictions = kwargs['restrictions']
+            self.roadm_path_impairments = self.get_roadm_path_impairments(kwargs['roadm-path-impairments'])
+        except KeyError as e:
+            raise ParametersError(f'ROADM configurations must include {e}. Configuration: {kwargs}')
+        self.per_degree_impairments = kwargs.get('per_degree_impairments', [])
+        self.design_bands = kwargs.get('design_bands', [])
+        self.per_degree_design_bands = kwargs.get('per_degree_design_bands', {})
+
+    def get_roadm_path_impairments(self, path_impairments_list):
+        """Get the ROADM list of profiles for impairments definition
+
+        transform the ietf model into gnpy internal model: add a path-type in the attributes
+        """
+        if not path_impairments_list:
+            return {}
+        authorized_path_types = {
+            'roadm-express-path': 'express',
+            'roadm-add-path': 'add',
+            'roadm-drop-path': 'drop',
+        }
+        roadm_path_impairments = {}
+        for path_impairment in path_impairments_list:
+            index = path_impairment['roadm-path-impairments-id']
+            path_type = next(key for key in path_impairment if key in authorized_path_types.keys())
+            impairment_dict = {'path-type': authorized_path_types[path_type], 'impairment': path_impairment[path_type]}
+            roadm_path_impairments[index] = RoadmImpairment(impairment_dict)
+        return roadm_path_impairments
+
+
+class RoadmPath:
+    def __init__(self, from_degree, to_degree, path_type, impairment_id=None, impairment=None):
+        """Records roadm internal paths, types and impairment
+
+        path_type must be in "express", "add", "drop"
+        impairment_id must be one of the id detailed in equipement
+        """
+        self.from_degree = from_degree
+        self.to_degree = to_degree
+        self.path_type = path_type
+        self.impairment_id = impairment_id
+        self.impairment = impairment
+
+
+class RoadmImpairment:
+    """Generic definition of impairments for express, add and drop"""
+    default_values = {
+        'roadm-pmd': None,
+        'roadm-cd': None,
+        'roadm-pdl': None,
+        'roadm-inband-crosstalk': None,
+        'roadm-maxloss': 0,
+        'roadm-osnr': None,
+        'roadm-pmax': None,
+        'roadm-noise-figure': None,
+        'minloss': None,
+        'typloss': None,
+        'pmin': None,
+        'ptyp': None
+    }
+
+    def __init__(self, params):
+        self.path_type = params.get('path-type')
+        self.impairments = params['impairment']
+
+
+class FusedParams(Parameters):
+    def __init__(self, **kwargs):
+        self.loss = kwargs['loss'] if 'loss' in kwargs else 1
+
+
+DEFAULT_RAMAN_COEFFICIENT = {
+    # SSMF Raman coefficient profile in terms of mode intensity (g0 * A_ff_overlap)
+    'gamma_raman': array(
+        [0.0, 8.524419934705497e-16, 2.643567866245371e-15, 4.410548410941305e-15, 6.153422961291078e-15,
+         7.484924703044943e-15, 8.452060808349209e-15, 9.101549322698156e-15, 9.57837595158966e-15,
+         1.0008642675474562e-14, 1.0865773569905647e-14, 1.1300776305865833e-14, 1.2143238647099625e-14,
+         1.3231065750676068e-14, 1.4624900971525384e-14, 1.6013330554840492e-14, 1.7458119359310242e-14,
+         1.9320241330434762e-14, 2.1720395392873534e-14, 2.4137337406734775e-14, 2.628163218460466e-14,
+         2.8041019963285974e-14, 2.9723155447089933e-14, 3.129353531005888e-14, 3.251796163324624e-14,
+         3.3198839487612773e-14, 3.329527690685666e-14, 3.313155691238456e-14, 3.289013852154548e-14,
+         3.2458917188506916e-14, 3.060684277937575e-14, 3.2660349473783173e-14, 2.957419109657689e-14,
+         2.518894321396672e-14, 1.734560485857344e-14, 9.902860761605233e-15, 7.219176385099358e-15,
+         6.079565990401311e-15, 5.828373065963427e-15, 7.20580801091692e-15, 7.561924351387493e-15,
+         7.621152352332206e-15, 6.8859886780643254e-15, 5.629181047471162e-15, 3.679727598966185e-15,
+         2.7555869742500355e-15, 2.4810133942597675e-15, 2.2160080532403624e-15, 2.1440626024765557e-15,
+         2.33873070799544e-15, 2.557317929858713e-15, 3.039839048226572e-15, 4.8337165515610065e-15,
+         5.4647431818257436e-15, 5.229187813711269e-15, 4.510768525811313e-15, 3.3213473130607794e-15,
+         2.2602577027996455e-15, 1.969576495866441e-15, 1.5179853954188527e-15, 1.2953988551200156e-15,
+         1.1304672156251838e-15, 9.10004390675213e-16, 8.432919922183503e-16, 7.849224069008326e-16,
+         7.827568196032024e-16, 9.000514440646232e-16, 1.3025926460013665e-15, 1.5444108938497558e-15,
+         1.8795594063060786e-15, 1.7796130169921014e-15, 1.5938159865046653e-15, 1.1585522355108287e-15,
+         8.507044444633358e-16, 7.625404663756823e-16, 8.14510750925789e-16, 9.047944693473188e-16,
+         9.636431901702084e-16, 9.298633899602105e-16, 8.349739503637023e-16, 7.482901278066085e-16,
+         6.240794767134268e-16, 5.00652535687506e-16, 3.553373263685851e-16, 2.0344217706119682e-16,
+         1.4267522642294203e-16, 8.980016576743517e-17, 2.9829068181832594e-17, 1.4861959129014824e-17,
+         7.404482113326137e-18]
+    ),  # m/W
+    # SSMF Raman coefficient profile
+    'g0': array(
+        [0.00000000e+00, 1.12351610e-05, 3.47838074e-05, 5.79356636e-05, 8.06921680e-05, 9.79845709e-05, 1.10454361e-04,
+         1.18735302e-04, 1.24736889e-04, 1.30110053e-04, 1.41001273e-04, 1.46383247e-04, 1.57011792e-04, 1.70765865e-04,
+         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]
+    ),  # [1 / (W m)]
+
+    # Note the non-uniform spacing of this range; this is required for properly capturing the Raman peak shape.
+    'frequency_offset': array([
+        0., 0.5, 1., 1.5, 2., 2.5, 3., 3.5, 4., 4.5, 5., 5.5, 6., 6.5, 7., 7.5, 8., 8.5, 9., 9.5, 10., 10.5, 11., 11.5,
+        12., 12.5, 12.75, 13., 13.25, 13.5, 14., 14.5, 14.75, 15., 15.5, 16., 16.5, 17., 17.5, 18., 18.25, 18.5, 18.75,
+        19., 19.5, 20., 20.5, 21., 21.5, 22., 22.5, 23., 23.5, 24., 24.5, 25., 25.5, 26., 26.5, 27., 27.5, 28., 28.5,
+        29., 29.5, 30., 30.5, 31., 31.5, 32., 32.5, 33., 33.5, 34., 34.5, 35., 35.5, 36., 36.5, 37., 37.5, 38., 38.5,
+        39., 39.5, 40., 40.5, 41., 41.5, 42.]) * 1e12,  # [Hz]
+
+    # Raman profile reference frequency
+    'reference_frequency': 206.184634112792e12,  # [Hz] (1454 nm)
+
+    # Raman profile reference effective area
+    'reference_effective_area': 75.74659443542413e-12  # [m^2] (@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):
@@ -139,45 +266,94 @@ class FiberParams(Parameters):
         try:
             self._length = convert_length(kwargs['length'], kwargs['length_units'])
             # fixed attenuator for padding
-            self._att_in = kwargs['att_in'] if 'att_in' in kwargs else 0
+            self._att_in = kwargs.get('att_in', 0)
             # if not defined in the network json connector loss in/out
             # the None value will be updated in network.py[build_network]
             # with default values from eqpt_config.json[Spans]
-            self._con_in = kwargs['con_in'] if 'con_in' in kwargs else None
-            self._con_out = kwargs['con_out'] if 'con_out' in kwargs else None
+            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
+                self._ref_frequency = c / self._ref_wavelength
             elif 'ref_frequency' in kwargs:
                 self._ref_frequency = kwargs['ref_frequency']
-                self._ref_wavelength = c / self.ref_frequency
+                self._ref_wavelength = c / self._ref_frequency
             else:
-                self._ref_wavelength = 1550e-9
-                self._ref_frequency = c / self.ref_wavelength
-            self._dispersion = kwargs['dispersion']  # s/m/m
-            self._dispersion_slope = kwargs['dispersion_slope'] if 'dispersion_slope' in kwargs else \
-                -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)
-            self._gamma = kwargs['gamma']  # 1/W/m
+                self._ref_wavelength = 1550e-9  # conventional central C band wavelength [m]
+                self._ref_frequency = c / self._ref_wavelength
+
+            # Chromatic Dispersion
+            if 'dispersion_per_frequency' in kwargs:
+                # Frequency-dependent dispersion
+                self._dispersion = asarray(kwargs['dispersion_per_frequency']['value'])  # s/m/m
+                self._f_dispersion_ref = asarray(kwargs['dispersion_per_frequency']['frequency'])  # Hz
+                self._dispersion_slope = None
+            elif 'dispersion' in kwargs:
+                # Single value dispersion
+                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
+            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 * self._n2 / (self._ref_wavelength * self._gamma)  # m^2
+            else:
+                self._effective_area = 83e-12  # m^2
+                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')
+            if raman_coefficient is None:
+                self._raman_reference_frequency = DEFAULT_RAMAN_COEFFICIENT['reference_frequency']
+                frequency_offset = asarray(DEFAULT_RAMAN_COEFFICIENT['frequency_offset'])
+                gamma_raman = asarray(DEFAULT_RAMAN_COEFFICIENT['gamma_raman'])
+                stokes_wave = self._raman_reference_frequency - frequency_offset
+                normalized_gamma_raman = gamma_raman / self._raman_reference_frequency  # 1 / m / W / Hz
+                self._g0 = gamma_raman / self.effective_area_overlap(stokes_wave, self._raman_reference_frequency)
+            else:
+                self._raman_reference_frequency = raman_coefficient['reference_frequency']
+                frequency_offset = asarray(raman_coefficient['frequency_offset'])
+                stokes_wave = self._raman_reference_frequency - frequency_offset
+                self._g0 = asarray(raman_coefficient['g0'])
+                gamma_raman = self._g0 * self.effective_area_overlap(stokes_wave, self._raman_reference_frequency)
+                normalized_gamma_raman = gamma_raman / self._raman_reference_frequency  # 1 / m / W / Hz
+
+            # Raman gain coefficient array of the frequency offset constructed such that positive frequency values
+            # represent a positive power transfer from higher frequency and vice versa
+            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:
-                self._loss_coef = squeeze(kwargs['loss_coef']['loss_coef_power']) * 1e-3  # lineic loss dB/m
-                self._f_loss_ref = squeeze(kwargs['loss_coef']['frequency'])  # Hz
+
+            # 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 = kwargs['loss_coef'] * 1e-3  # lineic loss dB/m
-                self._f_loss_ref = 193.5e12  # Hz
-            self._lin_attenuation = db2lin(self.length * self.loss_coef)
-            self._lin_loss_exp = self.loss_coef / (10 * log10(exp(1)))  # linear power exponent loss Neper/m
-            self._effective_length = (1 - exp(- self.lin_loss_exp * self.length)) / self.lin_loss_exp
-            self._asymptotic_length = 1 / self.lin_loss_exp
-            # raman parameters (not compulsory)
-            self._raman_efficiency = kwargs['raman_efficiency'] if 'raman_efficiency' in kwargs else None
-            self._pumps_loss_coef = kwargs['pumps_loss_coef'] if 'pumps_loss_coef' in kwargs else None
+                self._loss_coef = asarray(kwargs['loss_coef']) * 1e-3  # lineic loss dB/m
+                self._f_loss_ref = asarray(self._ref_frequency)  # Hz
+            # 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}')
 
@@ -210,6 +386,10 @@ class FiberParams(Parameters):
     def con_out(self):
         return self._con_out
 
+    @property
+    def lumped_losses(self):
+        return self._lumped_losses
+
     @con_out.setter
     def con_out(self, con_out):
         self._con_out = con_out
@@ -218,6 +398,10 @@ 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
@@ -226,6 +410,20 @@ 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
@@ -238,14 +436,6 @@ 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
@@ -255,31 +445,241 @@ class FiberParams(Parameters):
         return self._f_loss_ref
 
     @property
-    def lin_loss_exp(self):
-        return self._lin_loss_exp
+    def raman_coefficient(self):
+        return self._raman_coefficient
 
     @property
-    def lin_attenuation(self):
-        return self._lin_attenuation
-
-    @property
-    def effective_length(self):
-        return self._effective_length
-
-    @property
-    def asymptotic_length(self):
-        return self._asymptotic_length
-
-    @property
-    def raman_efficiency(self):
-        return self._raman_efficiency
-
-    @property
-    def pumps_loss_coef(self):
-        return self._pumps_loss_coef
+    def latency(self):
+        return self._latency
 
     def asdict(self):
         dictionary = super().asdict()
         dictionary['loss_coef'] = self.loss_coef * 1e3
         dictionary['length_units'] = 'm'
+        if len(self.lumped_losses) == 0:
+            dictionary.pop('lumped_losses')
+        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:
+    default_values = {
+        'f_min': None,
+        'f_max': None,
+        'multi_band': None,
+        'bands': None,
+        'type_variety': '',
+        'type_def': '',
+        'gain_flatmax': None,
+        'gain_min': None,
+        'p_max': None,
+        'nf_model': None,
+        'dual_stage_model': None,
+        'preamp_variety': None,
+        'booster_variety': None,
+        'nf_min': None,
+        'nf_max': None,
+        'nf_coef': None,
+        'nf0': None,
+        'nf_fit_coeff': None,
+        'nf_ripple': 0,
+        'dgt': None,
+        'gain_ripple': 0,
+        'tilt_ripple': 0,
+        'f_ripple_ref': None,
+        'out_voa_auto': False,
+        'allowed_for_design': False,
+        'raman': False,
+        'pmd': 0,
+        'pdl': 0,
+        'advance_configurations_from_json': None
+    }
+
+    def __init__(self, **params):
+        try:
+            self.type_variety = params['type_variety']
+            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 if self.f_max and self.f_min else None
+            self.f_cent = (self.f_max + self.f_min) / 2 if self.f_max and self.f_min else None
+            self.f_ripple_ref = params['f_ripple_ref']
+            self.bands = [{'f_min': params['f_min'],
+                           'f_max': params['f_max']}]
+
+            # Gain
+            self.gain_flatmax = params['gain_flatmax']
+            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():
+            setattr(self, k, v)
+
+
+class EdfaOperational:
+    default_values = {
+        'gain_target': None,
+        'delta_p': None,
+        'out_voa': None,
+        'tilt_target': None
+    }
+
+    def __init__(self, **operational):
+        self.update_attr(operational)
+
+    def update_attr(self, kwargs):
+        clean_kwargs = {k: v for k, v in kwargs.items() if v != ''}
+        for k, v in self.default_values.items():
+            setattr(self, k, clean_kwargs.get(k, v))
+
+    def __repr__(self):
+        return (f'{type(self).__name__}('
+                f'gain_target={self.gain_target!r}, '
+                f'tilt_target={self.tilt_target!r})')
+
+
+class MultiBandParams:
+    default_values = {
+        'bands': [],
+        'type_variety': '',
+        'type_def': None,
+        'allowed_for_design': False
+    }
+
+    def __init__(self, **params):
+        try:
+            self.update_attr(params)
+        except KeyError as e:
+            raise ParametersError(f'Multiband configurations json must include {e}. Configuration: {params}')
+
+    def update_attr(self, kwargs):
+        clean_kwargs = {k: v for k, v in kwargs.items() if v != ''}
+        for k, v in self.default_values.items():
+            # use deepcopy to avoid sharing same object amongst all instance when v is a list or a dict!
+            if isinstance(v, (list, dict)):
+                setattr(self, k, clean_kwargs.get(k, deepcopy(v)))
+            else:
+                setattr(self, k, clean_kwargs.get(k, v))
+
+
+class TransceiverParams:
+    def __init__(self, **params):
+        self.design_bands = params.get('design_bands', [])
+        self.per_degree_design_bands = params.get('per_degree_design_bands', {})
+
+
+@dataclass
+class FrequencyBand:
+    """Frequency band
+    """
+    f_min: float
+    f_max: float
+
+
+DEFAULT_BANDS_DEFINITION = {
+    "LBAND": FrequencyBand(f_min=187e12, f_max=189e12),
+    "CBAND": FrequencyBand(f_min=191.3e12, f_max=196.0e12)
+}
+# use this definition to index amplifiers'element of a multiband amplifier.
+# this is not the design band
+
+
+def find_band_name(band: FrequencyBand) -> str:
+    """return the default band name (CBAND, LBAND, ...) that corresponds to the band frequency range
+    Use the band center frequency: if center frequency is inside the band then returns CBAND.
+    This is to flexibly encompass all kind of bands definitions.
+    returns the first matching band name.
+    """
+    for band_name, frequency_range in DEFAULT_BANDS_DEFINITION.items():
+        center_frequency = (band.f_min + band.f_max) / 2
+        if center_frequency >= frequency_range.f_min and center_frequency <= frequency_range.f_max:
+            return band_name
+    return 'unknown_band'

gnpy/core/utils.py

@@ -9,8 +9,10 @@ This module contains utility functions that are used with gnpy.
 """
 
 from csv import writer
-from numpy import pi, cos, sqrt, log10, linspace, zeros, shape, where, logical_and
+from numpy import pi, cos, sqrt, log10, linspace, zeros, shape, where, logical_and, mean, array
 from scipy import constants
+from copy import deepcopy
+from typing import List
 
 from gnpy.core.exceptions import ConfigurationError
 
@@ -106,6 +108,69 @@ def db2lin(value):
     return 10**(value / 10)
 
 
+def watt2dbm(value):
+    """Convert Watt units to dBm
+
+    >>> round(watt2dbm(0.001), 1)
+    0.0
+    >>> round(watt2dbm(0.02), 1)
+    13.0
+    """
+    return lin2db(value * 1e3)
+
+
+def dbm2watt(value):
+    """Convert dBm units to Watt
+
+    >>> round(dbm2watt(0), 4)
+    0.001
+    >>> round(dbm2watt(-3), 4)
+    0.0005
+    >>> round(dbm2watt(13), 4)
+    0.02
+    """
+    return db2lin(value) * 1e-3
+
+
+def psd2powerdbm(psd_mwperghz, baudrate_baud):
+    """computes power in dBm based on baudrate in bauds and psd in mW/GHz
+
+    >>> round(psd2powerdbm(0.031176, 64e9),3)
+    3.0
+    >>> round(psd2powerdbm(0.062352, 32e9),3)
+    3.0
+    >>> round(psd2powerdbm(0.015625, 64e9),3)
+    0.0
+    """
+    return lin2db(baudrate_baud * psd_mwperghz * 1e-9)
+
+
+def power_dbm_to_psd_mw_ghz(power_dbm, baudrate_baud):
+    """computes power spectral density in  mW/GHz based on baudrate in bauds and power in dBm
+
+    >>> power_dbm_to_psd_mw_ghz(0, 64e9)
+    0.015625
+    >>> round(power_dbm_to_psd_mw_ghz(3, 64e9), 6)
+    0.031176
+    >>> round(power_dbm_to_psd_mw_ghz(3, 32e9), 6)
+    0.062352
+    """
+    return db2lin(power_dbm) / (baudrate_baud * 1e-9)
+
+
+def psd_mw_per_ghz(power_watt, baudrate_baud):
+    """computes power spectral density in  mW/GHz based on baudrate in bauds and power in W
+
+    >>> psd_mw_per_ghz(2e-3, 32e9)
+    0.0625
+    >>> psd_mw_per_ghz(1e-3, 64e9)
+    0.015625
+    >>> psd_mw_per_ghz(0.5e-3, 32e9)
+    0.015625
+    """
+    return power_watt * 1e3 / (baudrate_baud * 1e-9)
+
+
 def round2float(number, step):
     """Round a floating point number so that its "resolution" is not bigger than 'step'
 
@@ -149,25 +214,39 @@ wavelength2freq = constants.lambda2nu
 freq2wavelength = constants.nu2lambda
 
 
-def freq2wavelength(value):
-    """ Converts frequency units to wavelength units.
-
-    >>> round(freq2wavelength(191.35e12) * 1e9, 3)
-    1566.723
-    >>> round(freq2wavelength(196.1e12) * 1e9, 3)
-    1528.773
-    """
-    return constants.c / value
-
-
 def snr_sum(snr, bw, snr_added, bw_added=12.5e9):
     snr_added = snr_added - lin2db(bw / bw_added)
     snr = -lin2db(db2lin(-snr) + db2lin(-snr_added))
     return snr
 
 
+def per_label_average(values, labels):
+    """computes the average per defined spectrum band, using labels
+
+    >>> labels = ['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'C', 'D', 'D', 'D', 'D']
+    >>> values = [28.51, 28.23, 28.15, 28.17, 28.36, 28.53, 28.64, 28.68, 28.7, 28.71, 28.72, 28.73, 28.74, 28.91, 27.96, 27.85, 27.87, 28.02]
+    >>> per_label_average(values, labels)
+    {'A': 28.28, 'B': 28.68, 'C': 28.91, 'D': 27.92}
+    """
+
+    label_set = sorted(set(labels))
+    summary = {}
+    for label in label_set:
+        vals = [val for val, lab in zip(values, labels) if lab == label]
+        summary[label] = round(mean(vals), 2)
+    return summary
+
+
+def pretty_summary_print(summary):
+    """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()])
+    return text
+
+
 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
@@ -185,9 +264,9 @@ 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
@@ -202,8 +281,7 @@ 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
@@ -229,7 +307,7 @@ 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}}
@@ -324,3 +402,126 @@ 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]
+
+
+def calculate_absolute_min_or_zero(x: array) -> array:
+    """Calculates the element-wise absolute minimum between the x and zero.
+
+    Parameters:
+    x (array): The first input array.
+
+    Returns:
+    array: The element-wise absolute minimum between x and zero.
+
+    Example:
+    >>> x = array([-1, 2, -3])
+    >>> calculate_absolute_min_or_zero(x)
+    array([1., 0., 3.])
+    """
+    return (abs(x) - x) / 2
+
+
+def nice_column_str(data: List[List[str]], max_length: int = 30, padding: int = 1) -> str:
+    """data is a list of rows, creates strings with nice alignment per colum and padding with spaces
+    letf justified
+
+    >>> table_data = [['aaa', 'b', 'c'], ['aaaaaaaa', 'bbb', 'c'], ['a', 'bbbbbbbbbb', 'c']]
+    >>> print(nice_column_str(table_data))
+    aaa      b          c 
+    aaaaaaaa bbb        c 
+    a        bbbbbbbbbb c 
+    """
+    # transpose data to determine size of columns
+    transposed_data = list(map(list, zip(*data)))
+    column_width = [max(len(word) for word in column) + padding for column in transposed_data]
+    nice_str = []
+    for row in data:
+        column = ''.join(word[0:max_length].ljust(min(width, max_length)) for width, word in zip(column_width, row))
+        nice_str.append(f'{column}')
+    return '\n'.join(nice_str)
+
+
+def find_common_range(amp_bands: List[List[dict]], default_band_f_min: float, default_band_f_max: float) \
+        -> List[dict]:
+    """Find the common frequency range of bands
+    If there are no amplifiers in the path, then use default band
+
+    >>> amp_bands = [[{'f_min': 191e12, 'f_max' : 195e12}, {'f_min': 186e12, 'f_max' : 190e12} ], \
+        [{'f_min': 185e12, 'f_max' : 189e12}, {'f_min': 192e12, 'f_max' : 196e12}], \
+        [{'f_min': 186e12, 'f_max': 193e12}]]
+    >>> find_common_range(amp_bands, 190e12, 195e12)
+    [{'f_min': 186000000000000.0, 'f_max': 189000000000000.0}, {'f_min': 192000000000000.0, 'f_max': 193000000000000.0}]
+    >>> amp_bands = [[{'f_min': 191e12, 'f_max' : 195e12}, {'f_min': 186e12, 'f_max' : 190e12} ], \
+        [{'f_min': 185e12, 'f_max' : 189e12}, {'f_min': 192e12, 'f_max' : 196e12}], \
+        [{'f_min': 186e12, 'f_max': 192e12}]]
+    >>> find_common_range(amp_bands, 190e12, 195e12)
+    [{'f_min': 186000000000000.0, 'f_max': 189000000000000.0}]
+
+    """
+    _amp_bands = [sorted(amp, key=lambda x: x['f_min']) for amp in amp_bands]
+    _temp = []
+    # remove None bands
+    for amp in _amp_bands:
+        is_band = True
+        for band in amp:
+            if not (is_band and band['f_min'] and band['f_max']):
+                is_band = False
+        if is_band:
+            _temp.append(amp)
+
+    # remove duplicate
+    unique_amp_bands = []
+    for amp in _temp:
+        if amp not in unique_amp_bands:
+            unique_amp_bands.append(amp)
+    if unique_amp_bands:
+        common_range = unique_amp_bands[0]
+    else:
+        if default_band_f_min is None or default_band_f_max is None:
+            return []
+        common_range = [{'f_min': default_band_f_min, 'f_max': default_band_f_max}]
+    for bands in unique_amp_bands:
+        common_range = [{'f_min': max(first['f_min'], second['f_min']), 'f_max': min(first['f_max'], second['f_max'])}
+                        for first in common_range for second in bands
+                        if max(first['f_min'], second['f_min']) < min(first['f_max'], second['f_max'])]
+    return sorted(common_range, key=lambda x: x['f_min'])

gnpy/example-data/Juniper-BoosterHG.json

@@ -1,160 +1,160 @@
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 }

gnpy/example-data/default_edfa_config.json

@@ -1,106 +1,108 @@
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+    2.3699990328716107,
+    2.414398437185221,
+    2.4587748041127506,
+    2.499446286796604,
+    2.5364027376452056,
+    2.5696460593920065,
+    2.602860350286428,
+    2.630396440815385,
+    2.6521732021128046,
+    2.6681935771243177,
+    2.6841217449620203,
+    2.6947834587664494,
+    2.705443819238505,
+    2.714526681131686
+  ]
 }

gnpy/example-data/edfa_example_network.json

@@ -1,80 +1,80 @@
 {
-    "network_name": "EDFA Example Network - P2P",
-    "elements": [{
-            "uid": "Site_A",
-            "type": "Transceiver",
-            "metadata": {
-                "location": {
-                    "city": "Site A",
-                    "region": "",
-                    "latitude": 0,
-                    "longitude": 0
-                }
-            }
-        },
-        {
-            "uid": "Span1",
-            "type": "Fiber",
-            "type_variety": "SSMF",
-            "params": {
-                "length": 80,
-                "loss_coef": 0.2,
-                "length_units": "km",
-                "att_in": 0,
-                "con_in": 0.5,
-                "con_out": 0.5                
-                },
-            "metadata": {
-                "location": {
-                    "region": "",
-                    "latitude": 1,
-                    "longitude": 0
-                }
-            }
-        },
-        {
-            "uid": "Edfa1",
-            "type": "Edfa",
-            "type_variety": "std_low_gain",            
-            "operational": {
-                "gain_target": 17,
-                "tilt_target": 0,
-                "out_voa": 0
-            },
-            "metadata": {
-                "location": {
-                    "region": "",
-                    "latitude": 2,
-                    "longitude": 0
-                }
-            }
-        },
-        {
-            "uid": "Site_B",
-            "type": "Transceiver",
-            "metadata": {
-                "location": {
-                    "city": "Site B",
-                    "region": "",
-                    "latitude": 2,
-                    "longitude": 0
-                }
-            }
+  "network_name": "EDFA Example Network - P2P",
+  "elements": [
+    {
+      "uid": "Site_A",
+      "type": "Transceiver",
+      "metadata": {
+        "location": {
+          "city": "Site A",
+          "region": "",
+          "latitude": 0,
+          "longitude": 0
         }
-
-    ],
-    "connections": [{
-            "from_node": "Site_A",
-            "to_node": "Span1"
-        },
-        {
-            "from_node": "Span1",
-            "to_node": "Edfa1"
-        },
-        {
-            "from_node": "Edfa1",
-            "to_node": "Site_B"
+      }
+    },
+    {
+      "uid": "Span1",
+      "type": "Fiber",
+      "type_variety": "SSMF",
+      "params": {
+        "length": 80,
+        "loss_coef": 0.2,
+        "length_units": "km",
+        "att_in": 0,
+        "con_in": 0.5,
+        "con_out": 0.5
+      },
+      "metadata": {
+        "location": {
+          "region": "",
+          "latitude": 1,
+          "longitude": 0
         }
-
-    ]
+      }
+    },
+    {
+      "uid": "Edfa1",
+      "type": "Edfa",
+      "type_variety": "std_low_gain",
+      "operational": {
+        "gain_target": 17,
+        "tilt_target": 0,
+        "out_voa": 0
+      },
+      "metadata": {
+        "location": {
+          "region": "",
+          "latitude": 2,
+          "longitude": 0
+        }
+      }
+    },
+    {
+      "uid": "Site_B",
+      "type": "Transceiver",
+      "metadata": {
+        "location": {
+          "city": "Site B",
+          "region": "",
+          "latitude": 2,
+          "longitude": 0
+        }
+      }
+    }
+  ],
+  "connections": [
+    {
+      "from_node": "Site_A",
+      "to_node": "Span1"
+    },
+    {
+      "from_node": "Span1",
+      "to_node": "Edfa1"
+    },
+    {
+      "from_node": "Edfa1",
+      "to_node": "Site_B"
+    }
+  ]
 }

gnpy/example-data/eqpt_config.json

@@ -1,346 +1,443 @@
-{     "Edfa":[{
-            "type_variety": "high_detail_model_example",
-            "type_def": "advanced_model",
-            "gain_flatmax": 25,
-            "gain_min": 15,
-            "p_max": 21,
-            "advanced_config_from_json": "std_medium_gain_advanced_config.json",
-            "out_voa_auto": false,
-            "allowed_for_design": false
-            },                  {
-            "type_variety": "Juniper_BoosterHG",
-            "type_def": "advanced_model",
-            "gain_flatmax": 25,
-            "gain_min": 10,
-            "p_max": 21,
-            "advanced_config_from_json": "Juniper-BoosterHG.json",
-            "out_voa_auto": false,
-            "allowed_for_design": false
-            }, 
-            {
-            "type_variety": "operator_model_example",
-            "type_def": "variable_gain",
-            "gain_flatmax": 26,
-            "gain_min": 15,
-            "p_max": 23,
-            "nf_min": 6,
-            "nf_max": 10,
-            "out_voa_auto": false,
-            "allowed_for_design": false           
-            },
-            {
-            "type_variety": "openroadm_ila_low_noise",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-8.104e-4,-6.221e-2,-5.889e-1,37.62],
-            "allowed_for_design": false
-            },          
-            {
-            "type_variety": "openroadm_ila_standard",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
-            "allowed_for_design": false
-            },
-            {
-            "type_variety": "openroadm_mw_mw_preamp",
-            "type_def": "openroadm_preamp",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "allowed_for_design": false
-            },
-            {
-            "type_variety": "openroadm_mw_mw_preamp_typical_ver5",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
-            "allowed_for_design": false
-            },
-            {
-            "type_variety": "openroadm_mw_mw_preamp_worstcase_ver5",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,27.99],
-            "allowed_for_design": false
-            },
-            {
-            "type_variety": "openroadm_mw_mw_booster",
-            "type_def": "openroadm_booster",
-            "gain_flatmax": 32,
-            "gain_min": 0,
-            "p_max": 22,
-            "allowed_for_design": false
-            },
-            {
-            "type_variety": "std_high_gain",
-            "type_def": "variable_gain",
-            "gain_flatmax": 35,
-            "gain_min": 25,
-            "p_max": 21,
-            "nf_min": 5.5,
-            "nf_max": 7,
-            "out_voa_auto": false,
-            "allowed_for_design": true
-            },            
-            {
-            "type_variety": "std_medium_gain",
-            "type_def": "variable_gain",
-            "gain_flatmax": 26,
-            "gain_min": 15,
-            "p_max": 23,
-            "nf_min": 6,
-            "nf_max": 10,
-            "out_voa_auto": false,
-            "allowed_for_design": true
-            },
-            {
-            "type_variety": "std_low_gain",
-            "type_def": "variable_gain",
-            "gain_flatmax": 16,
-            "gain_min": 8,
-            "p_max": 23,
-            "nf_min": 6.5,
-            "nf_max": 11,
-            "out_voa_auto": false,
-            "allowed_for_design": true
-            },
-            {
-            "type_variety": "high_power",
-            "type_def": "variable_gain",
-            "gain_flatmax": 16,
-            "gain_min": 8,
-            "p_max": 25,
-            "nf_min": 9,
-            "nf_max": 15,
-            "out_voa_auto": false,
-            "allowed_for_design": false
-            },            
-            {
-            "type_variety": "std_fixed_gain",
-            "type_def": "fixed_gain",
-            "gain_flatmax": 21,
-            "gain_min": 20,
-            "p_max": 21,
-            "nf0": 5.5,
-            "allowed_for_design": false
-            },
-            {
-            "type_variety": "4pumps_raman",
-            "type_def": "fixed_gain",
-            "gain_flatmax": 12,
-            "gain_min": 12,
-            "p_max": 21,
-            "nf0": -1,
-            "allowed_for_design": false
-            },   
-            {
-            "type_variety": "hybrid_4pumps_lowgain",
-            "type_def": "dual_stage",
-            "raman": true,
-            "gain_min": 25,
-            "preamp_variety": "4pumps_raman",
-            "booster_variety": "std_low_gain",
-            "allowed_for_design": true
-            },
-            {
-            "type_variety": "hybrid_4pumps_mediumgain",
-            "type_def": "dual_stage",
-            "raman": true,
-            "gain_min": 25,
-            "preamp_variety": "4pumps_raman",
-            "booster_variety": "std_medium_gain",
-            "allowed_for_design": true
-            },            
-            {
-            "type_variety": "medium+low_gain",
-            "type_def": "dual_stage",
-            "gain_min": 25,
-            "preamp_variety": "std_medium_gain",
-            "booster_variety": "std_low_gain",
-            "allowed_for_design": true
-            },
-            {
-            "type_variety": "medium+high_power",
-            "type_def": "dual_stage",
-            "gain_min": 25,
-            "preamp_variety": "std_medium_gain",
-            "booster_variety": "high_power",
-            "allowed_for_design": false
-            }                                  
+{
+  "Edfa": [
+    {
+      "type_variety": "high_detail_model_example",
+      "type_def": "advanced_model",
+      "gain_flatmax": 25,
+      "gain_min": 15,
+      "p_max": 21,
+      "advanced_config_from_json": "std_medium_gain_advanced_config.json",
+      "out_voa_auto": false,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "Juniper_BoosterHG",
+      "type_def": "advanced_model",
+      "gain_flatmax": 25,
+      "gain_min": 10,
+      "p_max": 21,
+      "advanced_config_from_json": "Juniper-BoosterHG.json",
+      "out_voa_auto": false,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "operator_model_example",
+      "type_def": "variable_gain",
+      "gain_flatmax": 26,
+      "gain_min": 15,
+      "p_max": 23,
+      "nf_min": 6,
+      "nf_max": 10,
+      "out_voa_auto": false,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_ila_low_noise",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -8.104e-4,
+        -6.221e-2,
+        -5.889e-1,
+        37.62
       ],
-      "Fiber":[{
-            "type_variety": "SSMF",
-            "dispersion": 1.67e-05,
-            "gamma": 0.00127,
-            "pmd_coef": 1.265e-15
-            },
-            {
-            "type_variety": "NZDF",
-            "dispersion": 0.5e-05,
-            "gamma": 0.00146,
-            "pmd_coef": 1.265e-15
-            },
-            {
-            "type_variety": "LOF",
-            "dispersion": 2.2e-05,
-            "gamma": 0.000843,
-            "pmd_coef": 1.265e-15
-            }
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_ila_standard",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
       ],
-      "RamanFiber":[{
-            "type_variety": "SSMF",
-            "dispersion": 1.67e-05,
-            "gamma": 0.00127,
-            "pmd_coef": 1.265e-15,
-            "raman_efficiency": {
-              "cr":[
-                  0, 9.4E-06, 2.92E-05, 4.88E-05, 6.82E-05, 8.31E-05, 9.4E-05, 0.0001014, 0.0001069, 0.0001119,
-                  0.0001217, 0.0001268, 0.0001365, 0.000149, 0.000165, 0.000181, 0.0001977, 0.0002192, 0.0002469,
-                  0.0002749, 0.0002999, 0.0003206, 0.0003405, 0.0003592, 0.000374, 0.0003826, 0.0003841, 0.0003826,
-                  0.0003802, 0.0003756, 0.0003549, 0.0003795, 0.000344, 0.0002933, 0.0002024, 0.0001158, 8.46E-05,
-                  7.14E-05, 6.86E-05, 8.5E-05, 8.93E-05, 9.01E-05, 8.15E-05, 6.67E-05, 4.37E-05, 3.28E-05, 2.96E-05,
-                  2.65E-05, 2.57E-05, 2.81E-05, 3.08E-05, 3.67E-05, 5.85E-05, 6.63E-05, 6.36E-05, 5.5E-05, 4.06E-05,
-                  2.77E-05, 2.42E-05, 1.87E-05, 1.6E-05, 1.4E-05, 1.13E-05, 1.05E-05, 9.8E-06, 9.8E-06, 1.13E-05,
-                  1.64E-05, 1.95E-05, 2.38E-05, 2.26E-05, 2.03E-05, 1.48E-05, 1.09E-05, 9.8E-06, 1.05E-05, 1.17E-05,
-                  1.25E-05, 1.21E-05, 1.09E-05, 9.8E-06, 8.2E-06, 6.6E-06, 4.7E-06, 2.7E-06, 1.9E-06, 1.2E-06, 4E-07,
-                  2E-07, 1E-07
-              ],
-              "frequency_offset":[
-                0, 0.5e12, 1e12, 1.5e12, 2e12, 2.5e12, 3e12, 3.5e12, 4e12, 4.5e12, 5e12, 5.5e12, 6e12, 6.5e12, 7e12,
-                7.5e12, 8e12, 8.5e12, 9e12, 9.5e12, 10e12, 10.5e12, 11e12, 11.5e12, 12e12, 12.5e12, 12.75e12,
-                13e12, 13.25e12, 13.5e12, 14e12, 14.5e12, 14.75e12, 15e12, 15.5e12, 16e12, 16.5e12, 17e12,
-                17.5e12, 18e12, 18.25e12, 18.5e12, 18.75e12, 19e12, 19.5e12, 20e12, 20.5e12, 21e12, 21.5e12,
-                22e12, 22.5e12, 23e12, 23.5e12, 24e12, 24.5e12, 25e12, 25.5e12, 26e12, 26.5e12, 27e12, 27.5e12, 28e12,
-                28.5e12, 29e12, 29.5e12, 30e12, 30.5e12, 31e12, 31.5e12, 32e12, 32.5e12, 33e12, 33.5e12, 34e12, 34.5e12,
-                35e12, 35.5e12, 36e12, 36.5e12, 37e12, 37.5e12, 38e12, 38.5e12, 39e12, 39.5e12, 40e12, 40.5e12, 41e12,
-                41.5e12, 42e12
-              ]
-              }
-            }
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_mw_mw_preamp",
+      "type_def": "openroadm_preamp",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_mw_mw_preamp_typical_ver5",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
       ],
-      "Span":[{
-            "power_mode":true,
-            "delta_power_range_db": [-2,3,0.5],
-            "max_fiber_lineic_loss_for_raman": 0.25,
-            "target_extended_gain": 2.5,
-            "max_length": 150,
-            "length_units": "km",
-            "max_loss": 28,
-            "padding": 10,
-            "EOL": 0,
-            "con_in": 0,
-            "con_out": 0
-            }
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_mw_mw_preamp_worstcase_ver5",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        27.99
       ],
-      "Roadm":[{
-            "target_pch_out_db": -20,
-            "add_drop_osnr": 38,
-            "pmd": 0,
-            "restrictions": {
-                            "preamp_variety_list":[],
-                            "booster_variety_list":[]
-                            }            
-            }],
-      "SI":[{
-            "f_min": 191.3e12,
-            "baud_rate": 32e9,
-            "f_max":195.1e12,
-            "spacing": 50e9,
-            "power_dbm": 0,
-            "power_range_db": [0,0,1],
-            "roll_off": 0.15,
-            "tx_osnr": 40,
-            "sys_margins": 2
-            }],
-      "Transceiver":[
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_mw_mw_booster",
+      "type_def": "openroadm_booster",
+      "gain_flatmax": 32,
+      "gain_min": 0,
+      "p_max": 22,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "std_high_gain",
+      "type_def": "variable_gain",
+      "gain_flatmax": 35,
+      "gain_min": 25,
+      "p_max": 21,
+      "nf_min": 5.5,
+      "nf_max": 7,
+      "out_voa_auto": false,
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "std_medium_gain",
+      "type_def": "variable_gain",
+      "gain_flatmax": 26,
+      "gain_min": 15,
+      "p_max": 23,
+      "nf_min": 6,
+      "nf_max": 10,
+      "out_voa_auto": false,
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "std_low_gain",
+      "type_def": "variable_gain",
+      "gain_flatmax": 16,
+      "gain_min": 8,
+      "p_max": 23,
+      "nf_min": 6.5,
+      "nf_max": 11,
+      "out_voa_auto": false,
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "high_power",
+      "type_def": "variable_gain",
+      "gain_flatmax": 16,
+      "gain_min": 8,
+      "p_max": 25,
+      "nf_min": 9,
+      "nf_max": 15,
+      "out_voa_auto": false,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "std_fixed_gain",
+      "type_def": "fixed_gain",
+      "gain_flatmax": 21,
+      "gain_min": 20,
+      "p_max": 21,
+      "nf0": 5.5,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "4pumps_raman",
+      "type_def": "fixed_gain",
+      "gain_flatmax": 12,
+      "gain_min": 12,
+      "p_max": 21,
+      "nf0": -1,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "hybrid_4pumps_lowgain",
+      "type_def": "dual_stage",
+      "raman": true,
+      "gain_min": 25,
+      "preamp_variety": "4pumps_raman",
+      "booster_variety": "std_low_gain",
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "hybrid_4pumps_mediumgain",
+      "type_def": "dual_stage",
+      "raman": true,
+      "gain_min": 25,
+      "preamp_variety": "4pumps_raman",
+      "booster_variety": "std_medium_gain",
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "medium+low_gain",
+      "type_def": "dual_stage",
+      "gain_min": 25,
+      "preamp_variety": "std_medium_gain",
+      "booster_variety": "std_low_gain",
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "medium+high_power",
+      "type_def": "dual_stage",
+      "gain_min": 25,
+      "preamp_variety": "std_medium_gain",
+      "booster_variety": "high_power",
+      "allowed_for_design": false
+    }
+  ],
+  "Fiber": [
+    {
+      "type_variety": "SSMF",
+      "dispersion": 1.67e-05,
+      "effective_area": 83e-12,
+      "pmd_coef": 1.265e-15
+    },
+    {
+      "type_variety": "NZDF",
+      "dispersion": 0.5e-05,
+      "effective_area": 72e-12,
+      "pmd_coef": 1.265e-15
+    },
+    {
+      "type_variety": "LOF",
+      "dispersion": 2.2e-05,
+      "effective_area": 125e-12,
+      "pmd_coef": 1.265e-15
+    }
+  ],
+  "RamanFiber": [
+    {
+      "type_variety": "SSMF",
+      "dispersion": 1.67e-05,
+      "effective_area": 83e-12,
+      "pmd_coef": 1.265e-15
+    }
+  ],
+  "Span": [
+    {
+      "power_mode": true,
+      "delta_power_range_db": [
+        -2,
+        3,
+        0.5
+      ],
+      "max_fiber_lineic_loss_for_raman": 0.25,
+      "target_extended_gain": 2.5,
+      "max_length": 150,
+      "length_units": "km",
+      "max_loss": 28,
+      "padding": 10,
+      "EOL": 0,
+      "con_in": 0,
+      "con_out": 0
+    }
+  ],
+  "Roadm": [
+    {
+      "target_pch_out_db": -20,
+      "add_drop_osnr": 38,
+      "pmd": 0,
+      "pdl": 0,
+      "restrictions": {
+        "preamp_variety_list": [],
+        "booster_variety_list": []
+      }
+    },
+    {
+      "type_variety": "roadm_type_1",
+      "target_pch_out_db": -18,
+      "add_drop_osnr": 35,
+      "pmd": 0,
+      "pdl": 0,
+      "restrictions": {
+        "preamp_variety_list": [],
+        "booster_variety_list": []
+      },
+      "roadm-path-impairments": []
+    },
+    {
+      "type_variety": "detailed_impairments",
+      "target_pch_out_db": -20,
+      "add_drop_osnr": 38,
+      "pmd": 0,
+      "pdl": 0,
+      "restrictions": {
+        "preamp_variety_list": [],
+        "booster_variety_list": []
+      },
+      "roadm-path-impairments": [
+        {
+          "roadm-path-impairments-id": 0,
+          "roadm-express-path": [
             {
-            "type_variety": "vendorA_trx-type1",
-            "frequency":{
-                        "min": 191.35e12,
-                        "max": 196.1e12
-                        },
-            "mode":[
-                       {
-
-                       "format": "mode 1",
-                       "baud_rate": 32e9,
-                       "OSNR": 11,
-                       "bit_rate": 100e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 40,
-                       "min_spacing": 37.5e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "mode 2",
-                       "baud_rate": 66e9,
-                       "OSNR": 15,
-                       "bit_rate": 200e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 40,
-                       "min_spacing": 75e9,
-                       "cost":1
-                       }
-                   ]
-            },
-            {
-            "type_variety": "Voyager",
-            "frequency":{
-                        "min": 191.35e12,
-                        "max": 196.1e12
-                        },
-            "mode":[
-                       {
-                       "format": "mode 1",
-                       "baud_rate": 32e9,
-                       "OSNR": 12,
-                       "bit_rate": 100e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 40,
-                       "min_spacing": 37.5e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "mode 3",
-                       "baud_rate": 44e9,
-                       "OSNR": 18,
-                       "bit_rate": 300e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 40,
-                       "min_spacing": 62.5e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "mode 2",
-                       "baud_rate": 66e9,
-                       "OSNR": 21,
-                       "bit_rate": 400e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 40,
-                       "min_spacing": 75e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "mode 4",
-                       "baud_rate": 66e9,
-                       "OSNR": 16,
-                       "bit_rate": 200e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 40,
-                       "min_spacing": 75e9,
-                       "cost":1
-                       }
-                   ]
+              "frequency-range": {
+                "lower-frequency": 191.3e12,
+                "upper-frequency": 196.1e12
+              },
+              "roadm-pmd": 0,
+              "roadm-cd": 0,
+              "roadm-pdl": 0,
+              "roadm-inband-crosstalk": 0,
+              "roadm-maxloss": 16.5
             }
+          ]
+        },
+        {
+          "roadm-path-impairments-id": 1,
+          "roadm-add-path": [
+            {
+              "frequency-range": {
+                "lower-frequency": 191.3e12,
+                "upper-frequency": 196.1e12
+              },
+              "roadm-pmd": 0,
+              "roadm-cd": 0,
+              "roadm-pdl": 0,
+              "roadm-inband-crosstalk": 0,
+              "roadm-maxloss": 11.5,
+              "roadm-pmax": 2.5,
+              "roadm-osnr": 41,
+              "roadm-noise-figure": 23
+            }
+          ]
+        },
+        {
+          "roadm-path-impairments-id": 2,
+          "roadm-drop-path": [
+            {
+              "frequency-range": {
+                "lower-frequency": 191.3e12,
+                "upper-frequency": 196.1e12
+              },
+              "roadm-pmd": 0,
+              "roadm-cd": 0,
+              "roadm-pdl": 0,
+              "roadm-inband-crosstalk": 0,
+              "roadm-maxloss": 11.5,
+              "roadm-minloss": 7.5,
+              "roadm-typloss": 10,
+              "roadm-pmin": -13.5,
+              "roadm-pmax": -9.5,
+              "roadm-ptyp": -12,
+              "roadm-osnr": 41,
+              "roadm-noise-figure": 15
+            }
+          ]
+        }
       ]
-
+    }
+  ],
+  "SI": [
+    {
+      "f_min": 191.3e12,
+      "baud_rate": 32e9,
+      "f_max": 195.1e12,
+      "spacing": 50e9,
+      "power_dbm": 0,
+      "power_range_db": [
+        0,
+        0,
+        1
+      ],
+      "tx_power_dbm": 0,
+      "roll_off": 0.15,
+      "tx_osnr": 40,
+      "sys_margins": 2
+    }
+  ],
+  "Transceiver": [
+    {
+      "type_variety": "vendorA_trx-type1",
+      "frequency": {
+        "min": 191.35e12,
+        "max": 196.1e12
+      },
+      "mode": [
+        {
+          "format": "mode 1",
+          "baud_rate": 32e9,
+          "OSNR": 11,
+          "bit_rate": 100e9,
+          "roll_off": 0.15,
+          "tx_osnr": 40,
+          "min_spacing": 37.5e9,
+          "cost": 1
+        },
+        {
+          "format": "mode 2",
+          "baud_rate": 66e9,
+          "OSNR": 15,
+          "bit_rate": 200e9,
+          "roll_off": 0.15,
+          "tx_osnr": 40,
+          "min_spacing": 75e9,
+          "cost": 1
+        }
+      ]
+    },
+    {
+      "type_variety": "Voyager",
+      "frequency": {
+        "min": 191.35e12,
+        "max": 196.1e12
+      },
+      "mode": [
+        {
+          "format": "mode 1",
+          "baud_rate": 32e9,
+          "OSNR": 12,
+          "bit_rate": 100e9,
+          "roll_off": 0.15,
+          "tx_osnr": 40,
+          "min_spacing": 37.5e9,
+          "cost": 1
+        },
+        {
+          "format": "mode 3",
+          "baud_rate": 44e9,
+          "OSNR": 18,
+          "bit_rate": 300e9,
+          "roll_off": 0.15,
+          "tx_osnr": 40,
+          "min_spacing": 62.5e9,
+          "cost": 1
+        },
+        {
+          "format": "mode 2",
+          "baud_rate": 66e9,
+          "OSNR": 21,
+          "bit_rate": 400e9,
+          "roll_off": 0.15,
+          "tx_osnr": 40,
+          "min_spacing": 75e9,
+          "cost": 1
+        },
+        {
+          "format": "mode 4",
+          "baud_rate": 66e9,
+          "OSNR": 16,
+          "bit_rate": 200e9,
+          "roll_off": 0.15,
+          "tx_osnr": 40,
+          "min_spacing": 75e9,
+          "cost": 1
+        }
+      ]
+    }
+  ]
 }

gnpy/example-data/eqpt_config_multiband.json

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

gnpy/example-data/eqpt_config_openroadm_ver4.json

@@ -1,190 +1,371 @@
-{     "Edfa":[
+{
+  "Edfa": [
+    {
+      "type_variety": "openroadm_ila_low_noise",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -8.104e-4,
+        -6.221e-2,
+        -5.889e-1,
+        37.62
+      ],
+      "pmd": 3e-12,
+      "pdl": 0.7,
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "openroadm_ila_standard",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
+      ],
+      "pmd": 3e-12,
+      "pdl": 0.7,
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "openroadm_mw_mw_preamp",
+      "type_def": "openroadm_preamp",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "pmd": 0,
+      "pdl": 0,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_mw_mw_booster",
+      "type_def": "openroadm_booster",
+      "gain_flatmax": 32,
+      "gain_min": 0,
+      "p_max": 22,
+      "pmd": 0,
+      "pdl": 0,
+      "allowed_for_design": false
+    }
+  ],
+  "Fiber": [
+    {
+      "type_variety": "SSMF",
+      "dispersion": 1.67e-05,
+      "effective_area": 83e-12,
+      "pmd_coef": 1.265e-15
+    },
+    {
+      "type_variety": "NZDF",
+      "dispersion": 0.5e-05,
+      "effective_area": 72e-12,
+      "pmd_coef": 1.265e-15
+    },
+    {
+      "type_variety": "LOF",
+      "dispersion": 2.2e-05,
+      "effective_area": 125e-12,
+      "pmd_coef": 1.265e-15
+    }
+  ],
+  "RamanFiber": [
+    {
+      "type_variety": "SSMF",
+      "dispersion": 1.67e-05,
+      "effective_area": 83e-12,
+      "pmd_coef": 1.265e-15
+    }
+  ],
+  "Span": [
+    {
+      "power_mode": true,
+      "delta_power_range_db": [
+        0,
+        0,
+        0
+      ],
+      "max_fiber_lineic_loss_for_raman": 0.25,
+      "target_extended_gain": 0,
+      "max_length": 135,
+      "length_units": "km",
+      "max_loss": 28,
+      "padding": 11,
+      "EOL": 0,
+      "con_in": 0,
+      "con_out": 0
+    }
+  ],
+  "Roadm": [
+    {
+      "target_pch_out_db": -20,
+      "add_drop_osnr": 30,
+      "pmd": 3e-12,
+      "pdl": 1.5,
+      "restrictions": {
+        "preamp_variety_list": [
+          "openroadm_mw_mw_preamp"
+        ],
+        "booster_variety_list": [
+          "openroadm_mw_mw_booster"
+        ]
+      }
+    }
+  ],
+  "SI": [
+    {
+      "f_min": 191.3e12,
+      "baud_rate": 31.57e9,
+      "f_max": 196.1e12,
+      "spacing": 50e9,
+      "power_dbm": 2,
+      "power_range_db": [
+        0,
+        0,
+        1
+      ],
+      "roll_off": 0.15,
+      "tx_osnr": 35,
+      "sys_margins": 2
+    }
+  ],
+  "Transceiver": [
+    {
+      "type_variety": "OpenROADM MSA ver. 4.0",
+      "frequency": {
+        "min": 191.35e12,
+        "max": 196.1e12
+      },
+      "mode": [
+        {
+          "format": "100 Gbit/s, 27.95 Gbaud, DP-QPSK",
+          "baud_rate": 27.95e9,
+          "OSNR": 17,
+          "bit_rate": 100e9,
+          "roll_off": null,
+          "tx_osnr": 33,
+          "penalties": [
             {
-            "type_variety": "openroadm_ila_low_noise",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-8.104e-4,-6.221e-2,-5.889e-1,37.62],
-            "allowed_for_design": true
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
             },
             {
-            "type_variety": "openroadm_ila_standard",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
-            "allowed_for_design": true
-            },
-		{
-            "type_variety": "openroadm_mw_mw_preamp",
-            "type_def": "openroadm_preamp",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "allowed_for_design": false
-            },
-		{
-            "type_variety": "openroadm_mw_mw_booster",
-            "type_def": "openroadm_booster",
-            "gain_flatmax": 32,
-            "gain_min": 0,
-            "p_max": 22,
-            "allowed_for_design": false
-            }
-      ],
-      "Fiber":[
-            {
-            "type_variety": "SSMF",
-            "dispersion": 1.67e-05,
-            "gamma": 0.00127,
-            "pmd_coef": 1.265e-15
+              "chromatic_dispersion": 18e3,
+              "penalty_value": 0.5
             },
             {
-            "type_variety": "NZDF",
-            "dispersion": 0.5e-05,
-            "gamma": 0.00146,
-            "pmd_coef": 1.265e-15
+              "pmd": 10,
+              "penalty_value": 0
             },
             {
-            "type_variety": "LOF",
-            "dispersion": 2.2e-05,
-            "gamma": 0.000843,
-            "pmd_coef": 1.265e-15
-            }
-      ],
-      "RamanFiber":[
+              "pmd": 30,
+              "penalty_value": 0.5
+            },
             {
-            "type_variety": "SSMF",
-            "dispersion": 1.67e-05,
-            "gamma": 0.00127,
-            "pmd_coef": 1.265e-15,
-            "raman_efficiency": {
-              "cr":[
-                  0, 9.4E-06, 2.92E-05, 4.88E-05, 6.82E-05, 8.31E-05, 9.4E-05, 0.0001014, 0.0001069, 0.0001119,
-                  0.0001217, 0.0001268, 0.0001365, 0.000149, 0.000165, 0.000181, 0.0001977, 0.0002192, 0.0002469,
-                  0.0002749, 0.0002999, 0.0003206, 0.0003405, 0.0003592, 0.000374, 0.0003826, 0.0003841, 0.0003826,
-                  0.0003802, 0.0003756, 0.0003549, 0.0003795, 0.000344, 0.0002933, 0.0002024, 0.0001158, 8.46E-05,
-                  7.14E-05, 6.86E-05, 8.5E-05, 8.93E-05, 9.01E-05, 8.15E-05, 6.67E-05, 4.37E-05, 3.28E-05, 2.96E-05,
-                  2.65E-05, 2.57E-05, 2.81E-05, 3.08E-05, 3.67E-05, 5.85E-05, 6.63E-05, 6.36E-05, 5.5E-05, 4.06E-05,
-                  2.77E-05, 2.42E-05, 1.87E-05, 1.6E-05, 1.4E-05, 1.13E-05, 1.05E-05, 9.8E-06, 9.8E-06, 1.13E-05,
-                  1.64E-05, 1.95E-05, 2.38E-05, 2.26E-05, 2.03E-05, 1.48E-05, 1.09E-05, 9.8E-06, 1.05E-05, 1.17E-05,
-                  1.25E-05, 1.21E-05, 1.09E-05, 9.8E-06, 8.2E-06, 6.6E-06, 4.7E-06, 2.7E-06, 1.9E-06, 1.2E-06, 4E-07,
-                  2E-07, 1E-07
-              ],
-              "frequency_offset":[
-                0, 0.5e12, 1e12, 1.5e12, 2e12, 2.5e12, 3e12, 3.5e12, 4e12, 4.5e12, 5e12, 5.5e12, 6e12, 6.5e12, 7e12,
-                7.5e12, 8e12, 8.5e12, 9e12, 9.5e12, 10e12, 10.5e12, 11e12, 11.5e12, 12e12, 12.5e12, 12.75e12,
-                13e12, 13.25e12, 13.5e12, 14e12, 14.5e12, 14.75e12, 15e12, 15.5e12, 16e12, 16.5e12, 17e12,
-                17.5e12, 18e12, 18.25e12, 18.5e12, 18.75e12, 19e12, 19.5e12, 20e12, 20.5e12, 21e12, 21.5e12,
-                22e12, 22.5e12, 23e12, 23.5e12, 24e12, 24.5e12, 25e12, 25.5e12, 26e12, 26.5e12, 27e12, 27.5e12, 28e12,
-                28.5e12, 29e12, 29.5e12, 30e12, 30.5e12, 31e12, 31.5e12, 32e12, 32.5e12, 33e12, 33.5e12, 34e12, 34.5e12,
-                35e12, 35.5e12, 36e12, 36.5e12, 37e12, 37.5e12, 38e12, 38.5e12, 39e12, 39.5e12, 40e12, 40.5e12, 41e12,
-                41.5e12, 42e12
-              ]
-              }
-            }
-      ],
-      "Span":[
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
             {
-            "power_mode":true,
-            "delta_power_range_db": [0,0,0],
-            "max_fiber_lineic_loss_for_raman": 0.25,
-            "target_extended_gain": 0,
-            "max_length": 135,
-            "length_units": "km",
-            "max_loss": 28,
-            "padding": 11,
-            "EOL": 0,
-            "con_in": 0,
-            "con_out": 0
-            }
-      ],
-      "Roadm":[
+              "pdl": 2,
+              "penalty_value": 1
+            },
             {
-            "target_pch_out_db": -20,
-            "add_drop_osnr": 30,
-            "pmd": 0,
-            "restrictions": {
-                            "preamp_variety_list":["openroadm_mw_mw_preamp"],
-                            "booster_variety_list":["openroadm_mw_mw_booster"]
-                            }            
-            }
-      ],
-      "SI":[
+              "pdl": 4,
+              "penalty_value": 2.5
+            },
             {
-            "f_min": 191.3e12,
-            "baud_rate": 31.57e9,
-            "f_max":196.1e12,
-            "spacing": 50e9,
-            "power_dbm": 2,
-            "power_range_db": [0,0,1],
-            "roll_off": 0.15,
-            "tx_osnr": 35,
-            "sys_margins": 2
+              "pdl": 6,
+              "penalty_value": 4
             }
-      ],
-      "Transceiver":[
-		{
-            "type_variety": "OpenROADM MSA ver. 4.0",
-            "frequency":{
-                        "min": 191.35e12,
-                        "max": 196.1e12
-                        },
-            "mode":[
-                       {
-                       "format": "100 Gbit/s, 27.95 Gbaud, DP-QPSK",
-                       "baud_rate": 27.95e9,
-                       "OSNR": 17,
-                       "bit_rate": 100e9,
-                       "roll_off": null,
-                       "tx_osnr": 33,
-                       "min_spacing": 50e9,
-                       "cost":1
-                       },
-					   {
-                       "format": "100 Gbit/s, 31.57 Gbaud, DP-QPSK",
-                       "baud_rate": 31.57e9,
-                       "OSNR": 12,
-                       "bit_rate": 100e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 35,
-                       "min_spacing": 50e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "200 Gbit/s, DP-QPSK",
-                       "baud_rate": 63.1e9,
-                       "OSNR": 17,
-                       "bit_rate": 200e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 36,
-                       "min_spacing": 87.5e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "300 Gbit/s, DP-8QAM",
-                       "baud_rate": 63.1e9,
-                       "OSNR": 21,
-                       "bit_rate": 300e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 36,
-                       "min_spacing": 87.5e9,
-                       "cost":1
-                       },
-					   {
-                       "format": "400 Gbit/s, DP-16QAM",
-                       "baud_rate": 63.1e9,
-                       "OSNR": 24,
-                       "bit_rate": 400e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 36,
-                       "min_spacing": 87.5e9,
-                       "cost":1
-                       }
-                   ]
+          ],
+          "min_spacing": 50e9,
+          "cost": 1
+        },
+        {
+          "format": "100 Gbit/s, 31.57 Gbaud, DP-QPSK",
+          "baud_rate": 31.57e9,
+          "OSNR": 12,
+          "bit_rate": 100e9,
+          "roll_off": 0.15,
+          "tx_osnr": 35,
+          "penalties": [
+            {
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 40e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 30,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            },
+            {
+              "pdl": 6,
+              "penalty_value": 4
             }
+          ],
+          "min_spacing": 50e9,
+          "cost": 1
+        },
+        {
+          "format": "200 Gbit/s, DP-QPSK",
+          "baud_rate": 63.1e9,
+          "OSNR": 17,
+          "bit_rate": 200e9,
+          "roll_off": 0.15,
+          "tx_osnr": 36,
+          "penalties": [
+            {
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 24e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 25,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            }
+          ],
+          "min_spacing": 87.5e9,
+          "cost": 1
+        },
+        {
+          "format": "300 Gbit/s, DP-8QAM",
+          "baud_rate": 63.1e9,
+          "OSNR": 21,
+          "bit_rate": 300e9,
+          "roll_off": 0.15,
+          "tx_osnr": 36,
+          "penalties": [
+            {
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 18e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 25,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            }
+          ],
+          "min_spacing": 87.5e9,
+          "cost": 1
+        },
+        {
+          "format": "400 Gbit/s, DP-16QAM",
+          "baud_rate": 63.1e9,
+          "OSNR": 24,
+          "bit_rate": 400e9,
+          "roll_off": 0.15,
+          "tx_osnr": 36,
+          "penalties": [
+            {
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 12e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 20,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            }
+          ],
+          "min_spacing": 87.5e9,
+          "cost": 1
+        }
       ]
-
+    }
+  ]
 }

gnpy/example-data/eqpt_config_openroadm_ver5.json

@@ -1,210 +1,441 @@
-{     "Edfa":[
+{
+  "Edfa": [
+    {
+      "type_variety": "openroadm_ila_low_noise",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -8.104e-4,
+        -6.221e-2,
+        -5.889e-1,
+        37.62
+      ],
+      "pmd": 3e-12,
+      "pdl": 0.7,
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "openroadm_ila_standard",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
+      ],
+      "pmd": 3e-12,
+      "pdl": 0.7,
+      "allowed_for_design": true
+    },
+    {
+      "type_variety": "openroadm_mw_mw_preamp_typical_ver5",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        28.99
+      ],
+      "pmd": 0,
+      "pdl": 0,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_mw_mw_preamp_worstcase_ver5",
+      "type_def": "openroadm",
+      "gain_flatmax": 27,
+      "gain_min": 0,
+      "p_max": 22,
+      "nf_coef": [
+        -5.952e-4,
+        -6.250e-2,
+        -1.071,
+        27.99
+      ],
+      "pmd": 0,
+      "pdl": 0,
+      "allowed_for_design": false
+    },
+    {
+      "type_variety": "openroadm_mw_mw_booster",
+      "type_def": "openroadm_booster",
+      "gain_flatmax": 32,
+      "gain_min": 0,
+      "p_max": 22,
+      "pmd": 0,
+      "pdl": 0,
+      "allowed_for_design": false
+    }
+  ],
+  "Fiber": [
+    {
+      "type_variety": "SSMF",
+      "dispersion": 1.67e-05,
+      "effective_area": 83e-12,
+      "pmd_coef": 1.265e-15
+    },
+    {
+      "type_variety": "NZDF",
+      "dispersion": 0.5e-05,
+      "effective_area": 72e-12,
+      "pmd_coef": 1.265e-15
+    },
+    {
+      "type_variety": "LOF",
+      "dispersion": 2.2e-05,
+      "effective_area": 125e-12,
+      "pmd_coef": 1.265e-15
+    }
+  ],
+  "RamanFiber": [
+    {
+      "type_variety": "SSMF",
+      "dispersion": 1.67e-05,
+      "effective_area": 83e-12,
+      "pmd_coef": 1.265e-15
+    }
+  ],
+  "Span": [
+    {
+      "power_mode": true,
+      "delta_power_range_db": [
+        0,
+        0,
+        0
+      ],
+      "max_fiber_lineic_loss_for_raman": 0.25,
+      "target_extended_gain": 0,
+      "max_length": 135,
+      "length_units": "km",
+      "max_loss": 28,
+      "padding": 11,
+      "EOL": 0,
+      "con_in": 0,
+      "con_out": 0
+    }
+  ],
+  "Roadm": [
+    {
+      "target_pch_out_db": -20,
+      "add_drop_osnr": 33,
+      "pmd": 3e-12,
+      "pdl": 1.5,
+      "restrictions": {
+        "preamp_variety_list": [
+          "openroadm_mw_mw_preamp_worstcase_ver5"
+        ],
+        "booster_variety_list": [
+          "openroadm_mw_mw_booster"
+        ]
+      }
+    }
+  ],
+  "SI": [
+    {
+      "f_min": 191.3e12,
+      "baud_rate": 31.57e9,
+      "f_max": 196.1e12,
+      "spacing": 50e9,
+      "power_dbm": 2,
+      "power_range_db": [
+        0,
+        0,
+        1
+      ],
+      "roll_off": 0.15,
+      "tx_osnr": 35,
+      "sys_margins": 2
+    }
+  ],
+  "Transceiver": [
+    {
+      "type_variety": "OpenROADM MSA ver. 5.0",
+      "frequency": {
+        "min": 191.35e12,
+        "max": 196.1e12
+      },
+      "mode": [
+        {
+          "format": "100 Gbit/s, 27.95 Gbaud, DP-QPSK",
+          "baud_rate": 27.95e9,
+          "OSNR": 17,
+          "bit_rate": 100e9,
+          "roll_off": null,
+          "tx_osnr": 33,
+          "penalties": [
             {
-            "type_variety": "openroadm_ila_low_noise",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-8.104e-4,-6.221e-2,-5.889e-1,37.62],
-            "allowed_for_design": true
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
             },
             {
-            "type_variety": "openroadm_ila_standard",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
-            "allowed_for_design": true
-            },
-		{
-            "type_variety": "openroadm_mw_mw_preamp_typical_ver5",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
-            "allowed_for_design": false
+              "chromatic_dispersion": 18e3,
+              "penalty_value": 0.5
             },
             {
-            "type_variety": "openroadm_mw_mw_preamp_worstcase_ver5",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,27.99],
-            "allowed_for_design": false
-            },
-		{
-            "type_variety": "openroadm_mw_mw_booster",
-            "type_def": "openroadm_booster",
-            "gain_flatmax": 32,
-            "gain_min": 0,
-            "p_max": 22,
-            "allowed_for_design": false
-            }
-      ],
-      "Fiber":[
-            {
-            "type_variety": "SSMF",
-            "dispersion": 1.67e-05,
-            "gamma": 0.00127,
-            "pmd_coef": 1.265e-15
+              "pmd": 10,
+              "penalty_value": 0
             },
             {
-            "type_variety": "NZDF",
-            "dispersion": 0.5e-05,
-            "gamma": 0.00146,
-            "pmd_coef": 1.265e-15
+              "pmd": 30,
+              "penalty_value": 0.5
             },
             {
-            "type_variety": "LOF",
-            "dispersion": 2.2e-05,
-            "gamma": 0.000843,
-            "pmd_coef": 1.265e-15
-            }
-      ],
-      "RamanFiber":[
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
             {
-            "type_variety": "SSMF",
-            "dispersion": 1.67e-05,
-            "gamma": 0.00127,
-            "pmd_coef": 1.265e-15,
-            "raman_efficiency": {
-              "cr":[
-                  0, 9.4E-06, 2.92E-05, 4.88E-05, 6.82E-05, 8.31E-05, 9.4E-05, 0.0001014, 0.0001069, 0.0001119,
-                  0.0001217, 0.0001268, 0.0001365, 0.000149, 0.000165, 0.000181, 0.0001977, 0.0002192, 0.0002469,
-                  0.0002749, 0.0002999, 0.0003206, 0.0003405, 0.0003592, 0.000374, 0.0003826, 0.0003841, 0.0003826,
-                  0.0003802, 0.0003756, 0.0003549, 0.0003795, 0.000344, 0.0002933, 0.0002024, 0.0001158, 8.46E-05,
-                  7.14E-05, 6.86E-05, 8.5E-05, 8.93E-05, 9.01E-05, 8.15E-05, 6.67E-05, 4.37E-05, 3.28E-05, 2.96E-05,
-                  2.65E-05, 2.57E-05, 2.81E-05, 3.08E-05, 3.67E-05, 5.85E-05, 6.63E-05, 6.36E-05, 5.5E-05, 4.06E-05,
-                  2.77E-05, 2.42E-05, 1.87E-05, 1.6E-05, 1.4E-05, 1.13E-05, 1.05E-05, 9.8E-06, 9.8E-06, 1.13E-05,
-                  1.64E-05, 1.95E-05, 2.38E-05, 2.26E-05, 2.03E-05, 1.48E-05, 1.09E-05, 9.8E-06, 1.05E-05, 1.17E-05,
-                  1.25E-05, 1.21E-05, 1.09E-05, 9.8E-06, 8.2E-06, 6.6E-06, 4.7E-06, 2.7E-06, 1.9E-06, 1.2E-06, 4E-07,
-                  2E-07, 1E-07
-              ],
-              "frequency_offset":[
-                0, 0.5e12, 1e12, 1.5e12, 2e12, 2.5e12, 3e12, 3.5e12, 4e12, 4.5e12, 5e12, 5.5e12, 6e12, 6.5e12, 7e12,
-                7.5e12, 8e12, 8.5e12, 9e12, 9.5e12, 10e12, 10.5e12, 11e12, 11.5e12, 12e12, 12.5e12, 12.75e12,
-                13e12, 13.25e12, 13.5e12, 14e12, 14.5e12, 14.75e12, 15e12, 15.5e12, 16e12, 16.5e12, 17e12,
-                17.5e12, 18e12, 18.25e12, 18.5e12, 18.75e12, 19e12, 19.5e12, 20e12, 20.5e12, 21e12, 21.5e12,
-                22e12, 22.5e12, 23e12, 23.5e12, 24e12, 24.5e12, 25e12, 25.5e12, 26e12, 26.5e12, 27e12, 27.5e12, 28e12,
-                28.5e12, 29e12, 29.5e12, 30e12, 30.5e12, 31e12, 31.5e12, 32e12, 32.5e12, 33e12, 33.5e12, 34e12, 34.5e12,
-                35e12, 35.5e12, 36e12, 36.5e12, 37e12, 37.5e12, 38e12, 38.5e12, 39e12, 39.5e12, 40e12, 40.5e12, 41e12,
-                41.5e12, 42e12
-              ]
-              }
-            }
-      ],
-      "Span":[
+              "pdl": 2,
+              "penalty_value": 1
+            },
             {
-            "power_mode":true,
-            "delta_power_range_db": [0,0,0],
-            "max_fiber_lineic_loss_for_raman": 0.25,
-            "target_extended_gain": 0,
-            "max_length": 135,
-            "length_units": "km",
-            "max_loss": 28,
-            "padding": 11,
-            "EOL": 0,
-            "con_in": 0,
-            "con_out": 0
-            }
-      ],
-      "Roadm":[
+              "pdl": 4,
+              "penalty_value": 2.5
+            },
             {
-            "target_pch_out_db": -20,
-            "add_drop_osnr": 33,
-            "pmd": 0,
-            "restrictions": {
-                            "preamp_variety_list":["openroadm_mw_mw_preamp_worstcase_ver5"],
-                            "booster_variety_list":["openroadm_mw_mw_booster"]
-                            }            
+              "pdl": 6,
+              "penalty_value": 4
             }
-      ],
-      "SI":[
+          ],
+          "min_spacing": 50e9,
+          "cost": 1
+        },
+        {
+          "format": "100 Gbit/s, 31.57 Gbaud, DP-QPSK",
+          "baud_rate": 31.57e9,
+          "OSNR": 12,
+          "bit_rate": 100e9,
+          "roll_off": 0.15,
+          "tx_osnr": 36,
+          "penalties": [
             {
-            "f_min": 191.3e12,
-            "baud_rate": 31.57e9,
-            "f_max":196.1e12,
-            "spacing": 50e9,
-            "power_dbm": 2,
-            "power_range_db": [0,0,1],
-            "roll_off": 0.15,
-            "tx_osnr": 35,
-            "sys_margins": 2
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 48e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 30,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            },
+            {
+              "pdl": 6,
+              "penalty_value": 4
             }
-      ],
-      "Transceiver":[
-		{
-            "type_variety": "OpenROADM MSA ver. 5.0",
-            "frequency":{
-                        "min": 191.35e12,
-                        "max": 196.1e12
-                        },
-            "mode":[
-                        {
-                        "format": "100 Gbit/s, 27.95 Gbaud, DP-QPSK",
-                        "baud_rate": 27.95e9,
-                        "OSNR": 17,
-                        "bit_rate": 100e9,
-                        "roll_off": null,
-                        "tx_osnr": 33,
-                        "min_spacing": 50e9,
-                        "cost":1
-                        },
-                        {
-                        "format": "100 Gbit/s, 31.57 Gbaud, DP-QPSK",
-                        "baud_rate": 31.57e9,
-                        "OSNR": 12,
-                        "bit_rate": 100e9,
-                        "roll_off": 0.15,
-                        "tx_osnr": 36,
-                        "min_spacing": 50e9,
-                        "cost":1
-                        },
-                        {
-                        "format": "200 Gbit/s, 31.57 Gbaud, DP-16QAM",
-                        "baud_rate": 31.57e9,
-                        "OSNR": 20.5,
-                        "bit_rate": 100e9,
-                        "roll_off": 0.15,
-                        "tx_osnr": 36,
-                        "min_spacing": 50e9,
-                        "cost":1
-                        },
-                        {
-                        "format": "200 Gbit/s, DP-QPSK",
-                        "baud_rate": 63.1e9,
-                        "OSNR": 17,
-                        "bit_rate": 200e9,
-                        "roll_off": 0.15,
-                        "tx_osnr": 36,
-                        "min_spacing": 87.5e9,
-                        "cost":1
-                        },
-                        {
-                        "format": "300 Gbit/s, DP-8QAM",
-                        "baud_rate": 63.1e9,
-                        "OSNR": 21,
-                        "bit_rate": 300e9,
-                        "roll_off": 0.15,
-                        "tx_osnr": 36,
-                        "min_spacing": 87.5e9,
-                        "cost":1
-                        },
-                        {
-                        "format": "400 Gbit/s, DP-16QAM",
-                        "baud_rate": 63.1e9,
-                        "OSNR": 24,
-                        "bit_rate": 400e9,
-                        "roll_off": 0.15,
-                        "tx_osnr": 36,
-                        "min_spacing": 87.5e9,
-                        "cost":1
-                        }
-                        ]
+          ],
+          "min_spacing": 50e9,
+          "cost": 1
+        },
+        {
+          "format": "200 Gbit/s, 31.57 Gbaud, DP-16QAM",
+          "baud_rate": 31.57e9,
+          "OSNR": 20.5,
+          "bit_rate": 100e9,
+          "roll_off": 0.15,
+          "tx_osnr": 36,
+          "penalties": [
+            {
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 24e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 30,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            },
+            {
+              "pdl": 6,
+              "penalty_value": 4
             }
+          ],
+          "min_spacing": 50e9,
+          "cost": 1
+        },
+        {
+          "format": "200 Gbit/s, DP-QPSK",
+          "baud_rate": 63.1e9,
+          "OSNR": 17,
+          "bit_rate": 200e9,
+          "roll_off": 0.15,
+          "tx_osnr": 36,
+          "penalties": [
+            {
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 24e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 25,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            }
+          ],
+          "min_spacing": 87.5e9,
+          "cost": 1
+        },
+        {
+          "format": "300 Gbit/s, DP-8QAM",
+          "baud_rate": 63.1e9,
+          "OSNR": 21,
+          "bit_rate": 300e9,
+          "roll_off": 0.15,
+          "tx_osnr": 36,
+          "penalties": [
+            {
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 18e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 25,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            }
+          ],
+          "min_spacing": 87.5e9,
+          "cost": 1
+        },
+        {
+          "format": "400 Gbit/s, DP-16QAM",
+          "baud_rate": 63.1e9,
+          "OSNR": 24,
+          "bit_rate": 400e9,
+          "roll_off": 0.15,
+          "tx_osnr": 36,
+          "penalties": [
+            {
+              "chromatic_dispersion": -1e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 12e3,
+              "penalty_value": 0.5
+            },
+            {
+              "pmd": 10,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 20,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 2,
+              "penalty_value": 1
+            },
+            {
+              "pdl": 4,
+              "penalty_value": 2.5
+            }
+          ],
+          "min_spacing": 87.5e9,
+          "cost": 1
+        }
       ]
-
+    }
+  ]
 }

gnpy/example-data/initial_spectrum1.json

@@ -0,0 +1,12 @@
+{
+  "spectrum": [
+    {
+      "f_min": 191.35e12,
+      "f_max": 195.1e12,
+      "baud_rate": 32e9,
+      "slot_width": 50e9,
+      "roll_off": 0.15,
+      "tx_osnr": 40
+    }
+  ]
+}

gnpy/example-data/initial_spectrum2.json

@@ -0,0 +1,23 @@
+{
+  "spectrum": [
+    {
+      "f_min": 191.4e12,
+      "f_max": 193.1e12,
+      "baud_rate": 32e9,
+      "slot_width": 50e9,
+      "delta_pdb": 0,
+      "roll_off": 0.15,
+      "tx_osnr": 40,
+      "label": "mode_1"
+    },
+    {
+      "f_min": 193.1625e12,
+      "f_max": 195e12,
+      "baud_rate": 64e9,
+      "slot_width": 75e9,
+      "roll_off": 0.15,
+      "tx_osnr": 40,
+      "label": "mode_2"
+    }
+  ]
+}

gnpy/example-data/multiband_spectrum.json

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

gnpy/example-data/raman_edfa_example_network.json

@@ -20,12 +20,12 @@
         "temperature": 283,
         "raman_pumps": [
           {
-            "power": 200e-3,
+            "power": 224.403e-3,
             "frequency": 205e12,
             "propagation_direction": "counterprop"
           },
           {
-            "power": 206e-3,
+            "power": 231.135e-3,
             "frequency": 201e12,
             "propagation_direction": "counterprop"
           }
@@ -49,6 +49,21 @@
         }
       }
     },
+    {
+      "uid": "Fused1",
+      "type": "Fused",
+      "params": {
+        "loss": 0
+      },
+      "metadata": {
+        "location": {
+          "latitude": 1.5,
+          "longitude": 0,
+          "city": null,
+          "region": ""
+        }
+      }
+    },
     {
       "uid": "Edfa1",
       "type": "Edfa",
@@ -88,6 +103,10 @@
     },
     {
       "from_node": "Span1",
+      "to_node": "Fused1"
+    },
+    {
+      "from_node": "Fused1",
       "to_node": "Edfa1"
     },
     {

gnpy/example-data/sim_params.json

@@ -1,14 +1,19 @@
 {
-  "raman_parameters": {
-    "flag_raman": true,
-    "space_resolution": 10e3,
-    "tolerance": 1e-8
+  "raman_params": {
+    "flag": true,
+    "result_spatial_resolution": 10e3,
+    "solver_spatial_resolution": 50
   },
-  "nli_parameters": {
-  	"nli_method_name": "ggn_spectrally_separated",
-  	"wdm_grid_size": 50e9,
-  	"dispersion_tolerance": 1,
-  	"phase_shift_tolerance": 0.1,
-	"computed_channels": [1, 18, 37, 56, 75] 
+  "nli_params": {
+    "method": "ggn_spectrally_separated",
+    "dispersion_tolerance": 1,
+    "phase_shift_tolerance": 0.1,
+    "computed_channels": [
+      1,
+      18,
+      37,
+      56,
+      75
+    ]
   }
-}
+}

gnpy/example-data/std_medium_gain_advanced_config.json

@@ -1,304 +1,304 @@
 {
-    "nf_fit_coeff": [
-        0.000168241,
-        0.0469961,
-        0.0359549,
-        5.82851
-    ],
-    "f_min": 191.35e12,
-    "f_max": 196.1e12,
-    "nf_ripple": [
-        0.4372876328262819,
-        0.4372876328262819,
-        0.41270842850729195,
-        0.38814205928193013,
-        0.36358851509924695,
-        0.3390191214858807,
-        0.30474360397422756,
-        0.27048596623174515,
-        0.23624619427167134,
-        0.202035284929368,
-        0.1694483010211072,
-        0.13687829834471027,
-        0.1043252636301016,
-        0.07184040799914815,
-        0.061288823415841555,
-        0.050742731588695494,
-        0.04020212822983975,
-        0.029667009055877668,
-        0.01913736978785662,
-        0.00861320615127981,
-        -0.010157321677553965,
-        -0.028982516728038848,
-        -0.04779792991567815,
-        -0.06660356886269536,
-        -0.06256260169582961,
-        -0.05832916277634124,
-        -0.05409792133358102,
-        -0.04990610405914272,
-        -0.05078533294804249,
-        -0.05166410580536087,
-        -0.05254242298580185,
-        -0.05342028484370278,
-        -0.051742390657545205,
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 }

gnpy/tools/__init__.py

@@ -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`.
-'''
+"""

gnpy/tools/cli_examples.py

@@ -1,36 +1,32 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+"""
 gnpy.tools.cli_examples
 =======================
 
 Common code for CLI examples
-'''
+"""
 
 import argparse
 import logging
-import os.path
 import sys
 from math import ceil
-from numpy import linspace, mean
+from numpy import mean
 from pathlib import Path
+from copy import deepcopy
+
 import gnpy.core.ansi_escapes as ansi_escapes
-from gnpy.core.elements import Transceiver, Fiber, RamanFiber
-from gnpy.core.equipment import trx_mode_params
+from gnpy.core.elements import Transceiver, Fiber, RamanFiber, Roadm
 import gnpy.core.exceptions as exceptions
-from gnpy.core.network import build_network
 from gnpy.core.parameters import SimParams
-from gnpy.core.science_utils import Simulation
-from gnpy.core.utils import db2lin, lin2db, automatic_nch
-from gnpy.topology.request import (ResultElement, jsontocsv, compute_path_dsjctn, requests_aggregation,
-                                   BLOCKING_NOPATH, correct_json_route_list,
-                                   deduplicate_disjunctions, compute_path_with_disjunction,
-                                   PathRequest, compute_constrained_path, propagate)
-from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum
-from gnpy.tools.json_io import load_equipment, load_network, load_json, load_requests, save_network, \
-                               requests_from_json, disjunctions_from_json, save_json
+from gnpy.core.utils import lin2db, pretty_summary_print, per_label_average, watt2dbm
+from gnpy.topology.request import (ResultElement, jsontocsv, BLOCKING_NOPATH)
+from gnpy.tools.json_io import (load_equipment, load_network, load_json, load_requests, save_network,
+                                requests_from_json, save_json, load_initial_spectrum)
 from gnpy.tools.plots import plot_baseline, plot_results
+from gnpy.tools.worker_utils import designed_network, transmission_simulation, planning
+
 
 _logger = logging.getLogger(__name__)
 _examples_dir = Path(__file__).parent.parent / 'example-data'
@@ -49,7 +45,7 @@ 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)
@@ -57,14 +53,15 @@ def load_common_data(equipment_filename, topology_filename, simulation_filename,
         if save_raw_network_filename is not None:
             save_network(network, save_raw_network_filename)
             print(f'{ansi_escapes.blue}Raw network (no optimizations) saved to {save_raw_network_filename}{ansi_escapes.reset}')
-        sim_params = SimParams(**load_json(simulation_filename)) if simulation_filename is not None else None
-        if not sim_params:
+        if not simulation_filename:
+            sim_params = {}
             if next((node for node in network if isinstance(node, RamanFiber)), None) is not None:
                 print(f'{ansi_escapes.red}Invocation error:{ansi_escapes.reset} '
                       f'RamanFiber requires passing simulation params via --sim-params')
                 sys.exit(1)
         else:
-            Simulation.set_params(sim_params)
+            sim_params = load_json(simulation_filename)
+        SimParams.set_params(sim_params)
     except exceptions.EquipmentConfigError as e:
         print(f'{ansi_escapes.red}Configuration error in the equipment library:{ansi_escapes.reset} {e}')
         sys.exit(1)
@@ -85,7 +82,7 @@ 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):
@@ -119,6 +116,7 @@ def transmission_main_example(args=None):
     parser.add_argument('-pl', '--plot', action='store_true')
     parser.add_argument('-l', '--list-nodes', action='store_true', help='list all transceiver nodes')
     parser.add_argument('-po', '--power', default=0, help='channel ref power in dBm')
+    parser.add_argument('--spectrum', type=Path, help='user defined mixed rate spectrum JSON file')
     parser.add_argument('source', nargs='?', help='source node')
     parser.add_argument('destination', nargs='?', help='destination node')
 
@@ -143,19 +141,17 @@ def transmission_main_example(args=None):
         sys.exit()
 
     # First try to find exact match if source/destination provided
+    source = None
     if args.source:
         source = transceivers.pop(args.source, None)
         valid_source = True if source else False
-    else:
-        source = None
-        _logger.info('No source node specified: picking random transceiver')
 
+    destination = None
+    nodes_list = []
+    loose_list = []
     if args.destination:
         destination = transceivers.pop(args.destination, None)
         valid_destination = True if destination else False
-    else:
-        destination = None
-        _logger.info('No destination node specified: picking random transceiver')
 
     # If no exact match try to find partial match
     if args.source and not source:
@@ -172,74 +168,72 @@ def transmission_main_example(args=None):
     if not source:
         source = list(transceivers.values())[0]
         del transceivers[source.uid]
+        _logger.info('No source node specified: picking random transceiver')
 
     if not destination:
         destination = list(transceivers.values())[0]
+        nodes_list = [destination.uid]
+        loose_list = ['STRICT']
+        _logger.info('No destination node specified: picking random transceiver')
 
-    _logger.info(f'source = {args.source!r}')
-    _logger.info(f'destination = {args.destination!r}')
-
-    params = {}
-    params['request_id'] = 0
-    params['trx_type'] = ''
-    params['trx_mode'] = ''
-    params['source'] = source.uid
-    params['destination'] = destination.uid
-    params['bidir'] = False
-    params['nodes_list'] = [destination.uid]
-    params['loose_list'] = ['strict']
-    params['format'] = ''
-    params['path_bandwidth'] = 0
-    params['effective_freq_slot'] = None
-    trx_params = trx_mode_params(equipment)
-    if args.power:
-        trx_params['power'] = db2lin(float(args.power)) * 1e-3
-    params.update(trx_params)
-    req = PathRequest(**params)
+    _logger.info(f'source = {source.uid!r}')
+    _logger.info(f'destination = {destination.uid!r}')
 
+    initial_spectrum = None
+    if args.spectrum:
+        # use the spectrum defined by user for the propagation.
+        # the nb of channel for design remains the one of the reference channel
+        initial_spectrum = load_initial_spectrum(args.spectrum)
+        print('User input for spectrum used for propagation instead of SI')
     power_mode = equipment['Span']['default'].power_mode
     print('\n'.join([f'Power mode is set to {power_mode}',
-                     f'=> it can be modified in eqpt_config.json - Span']))
+                     '=> it can be modified in eqpt_config.json - Span']))
 
-    pref_ch_db = lin2db(req.power * 1e3)  # reference channel power / span (SL=20dB)
-    pref_total_db = pref_ch_db + lin2db(req.nb_channel)  # reference total power / span (SL=20dB)
+    # Simulate !
     try:
-        build_network(network, equipment, pref_ch_db, pref_total_db, args.no_insert_edfas)
+        network, req, ref_req = designed_network(equipment, network, source.uid, destination.uid,
+                                                 nodes_list=nodes_list, loose_list=loose_list,
+                                                 args_power=args.power,
+                                                 initial_spectrum=initial_spectrum,
+                                                 no_insert_edfas=args.no_insert_edfas)
+        path, propagations_for_path, powers_dbm, infos = transmission_simulation(equipment, network, req, ref_req)
     except exceptions.NetworkTopologyError as e:
         print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
         sys.exit(1)
     except exceptions.ConfigurationError as e:
         print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
         sys.exit(1)
-    path = compute_constrained_path(network, req)
-
+    except exceptions.ServiceError as e:
+        print(f'Service error: {e}')
+        sys.exit(1)
+    except ValueError:
+        sys.exit(1)
+    # print or export results
     spans = [s.params.length for s in path if isinstance(s, RamanFiber) or isinstance(s, Fiber)]
     print(f'\nThere are {len(spans)} fiber spans over {sum(spans)/1000:.0f} km between {source.uid} '
           f'and {destination.uid}')
     print(f'\nNow propagating between {source.uid} and {destination.uid}:')
-
-    power_range = [0]
-    if power_mode:
-        # power cannot be changed in gain mode
-        try:
-            p_start, p_stop, p_step = equipment['SI']['default'].power_range_db
-            p_num = abs(int(round((p_stop - p_start) / p_step))) + 1 if p_step != 0 else 1
-            power_range = list(linspace(p_start, p_stop, p_num))
-        except TypeError:
-            print('invalid power range definition in eqpt_config, should be power_range_db: [lower, upper, step]')
-
-    for dp_db in power_range:
-        req.power = db2lin(pref_ch_db + dp_db) * 1e-3
+    print(f'Reference used for design: (Input optical power reference in span = {watt2dbm(ref_req.power):.2f}dBm,\n'
+          + f'                            spacing = {ref_req.spacing * 1e-9:.2f}GHz\n'
+          + f'                            nb_channels = {ref_req.nb_channel})')
+    print('\nChannels propagating: (Input optical power deviation in span = '
+          + f'{pretty_summary_print(per_label_average(infos.delta_pdb_per_channel, infos.label))}dB,\n'
+          + '                       spacing = '
+          + f'{pretty_summary_print(per_label_average(infos.slot_width * 1e-9, infos.label))}GHz,\n'
+          + '                       transceiver output power = '
+          + f'{pretty_summary_print(per_label_average(watt2dbm(infos.tx_power), infos.label))}dBm,\n'
+          + f'                       nb_channels = {infos.number_of_channels})')
+    for path, power_dbm in zip(propagations_for_path, powers_dbm):
         if power_mode:
-            print(f'\nPropagating with input power = {ansi_escapes.cyan}{lin2db(req.power*1e3):.2f} dBm{ansi_escapes.reset}:')
+            print(f'Input optical power reference in span = {ansi_escapes.cyan}{power_dbm:.2f} '
+                  + f'dBm{ansi_escapes.reset}:')
         else:
-            print(f'\nPropagating in {ansi_escapes.cyan}gain mode{ansi_escapes.reset}: power cannot be set manually')
-        infos = propagate(path, req, equipment)
-        if len(power_range) == 1:
+            print('\nPropagating in {ansi_escapes.cyan}gain mode{ansi_escapes.reset}: power cannot be set manually')
+        if len(powers_dbm) == 1:
             for elem in path:
                 print(elem)
             if power_mode:
-                print(f'\nTransmission result for input power = {lin2db(req.power*1e3):.2f} dBm:')
+                print(f'\nTransmission result for input optical power reference in span = {power_dbm:.2f} dBm:')
             else:
                 print(f'\nTransmission results:')
             print(f'  Final GSNR (0.1 nm): {ansi_escapes.cyan}{mean(destination.snr_01nm):.02f} dB{ansi_escapes.reset}')
@@ -265,9 +259,9 @@ def transmission_main_example(args=None):
             ch_freq = final_carrier.frequency * 1e-12
             ch_power = lin2db(final_carrier.power.signal * 1e3)
             print(
-                '{:5}{:26.2f}{:26.2f}{:28.2f}{:28.2f}{:28.2f}' .format(
+                '{:5}{:26.5f}{:26.2f}{:28.2f}{:28.2f}{:28.2f}' .format(
                     final_carrier.channel_number, round(
-                        ch_freq, 2), round(
+                        ch_freq, 5), round(
                         ch_power, 2), round(
                         ch_osnr, 2), round(
                         ch_snr_nl, 2), round(
@@ -305,84 +299,50 @@ def path_requests_run(args=None):
                         help='considers that all demands are bidir')
     parser.add_argument('-o', '--output', type=Path, metavar=_help_fname_json_csv,
                         help='Store satisifed requests into a JSON or CSV file')
+    parser.add_argument('--redesign-per-request', action='store_true', help='Redesign the network at each request'
+                        + ' computation using the request as the reference channel')
+
 
     args = parser.parse_args(args if args is not None else sys.argv[1:])
     _setup_logging(args)
 
-    _logger.info(f'Computing path requests {args.service_filename} 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)
+    (equipment, network) = \
+        load_common_data(args.equipment, args.topology, args.sim_params, args.save_network_before_autodesign)
 
     # Build the network once using the default power defined in SI in eqpt config
     # TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
     # spacing, f_min and f_max
-    p_db = equipment['SI']['default'].power_dbm
+    if args.save_network is not None:
+        save_network(network, args.save_network)
+        print(f'Network (after autodesign) saved to {args.save_network}')
 
-    p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
-                                             equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
     try:
-        build_network(network, equipment, p_db, p_total_db, args.no_insert_edfas)
+        network, _, _ = designed_network(equipment, network, no_insert_edfas=args.no_insert_edfas)
+        data = load_requests(args.service_filename, equipment, bidir=args.bidir,
+                             network=network, network_filename=args.topology)
+        _data = requests_from_json(data, equipment)
+        oms_list, propagatedpths, reversed_propagatedpths, rqs, dsjn, result = \
+            planning(network, equipment, data, redesign=args.redesign_per_request)
     except exceptions.NetworkTopologyError as e:
         print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
         sys.exit(1)
     except exceptions.ConfigurationError as e:
         print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
         sys.exit(1)
-    if args.save_network is not None:
-        save_network(network, args.save_network)
-        print(f'{ansi_escapes.blue}Network (after autodesign) saved to {args.save_network}{ansi_escapes.reset}')
-    oms_list = build_oms_list(network, equipment)
-
-    try:
-        data = load_requests(args.service_filename, equipment, bidir=args.bidir,
-                             network=network, network_filename=args.topology)
-        rqs = requests_from_json(data, equipment)
-    except exceptions.ServiceError as e:
-        print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {e}')
-        sys.exit(1)
-    # check that request ids are unique. Non unique ids, may
-    # mess the computation: better to stop the computation
-    all_ids = [r.request_id for r in rqs]
-    if len(all_ids) != len(set(all_ids)):
-        for item in list(set(all_ids)):
-            all_ids.remove(item)
-        msg = f'Requests id {all_ids} are not unique'
-        _logger.critical(msg)
-        sys.exit()
-    rqs = correct_json_route_list(network, rqs)
-
-    # pths = compute_path(network, equipment, rqs)
-    dsjn = disjunctions_from_json(data)
-
-    print(f'{ansi_escapes.blue}List of disjunctions{ansi_escapes.reset}')
-    print(dsjn)
-    # need to warn or correct in case of wrong disjunction form
-    # disjunction must not be repeated with same or different ids
-    dsjn = deduplicate_disjunctions(dsjn)
-
-    # Aggregate demands with same exact constraints
-    print(f'{ansi_escapes.blue}Aggregating similar requests{ansi_escapes.reset}')
-
-    rqs, dsjn = requests_aggregation(rqs, dsjn)
-    # TODO export novel set of aggregated demands in a json file
-
-    print(f'{ansi_escapes.blue}The following services have been requested:{ansi_escapes.reset}')
-    print(rqs)
-
-    print(f'{ansi_escapes.blue}Computing all paths with constraints{ansi_escapes.reset}')
-    try:
-        pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
     except exceptions.DisjunctionError as this_e:
         print(f'{ansi_escapes.red}Disjunction error:{ansi_escapes.reset} {this_e}')
         sys.exit(1)
-
-    print(f'{ansi_escapes.blue}Propagating on selected path{ansi_escapes.reset}')
-    propagatedpths, reversed_pths, reversed_propagatedpths = compute_path_with_disjunction(network, equipment, rqs, pths)
-    # Note that deepcopy used in compute_path_with_disjunction returns
-    # a list of nodes which are not belonging to network (they are copies of the node objects).
-    # so there can not be propagation on these nodes.
-
-    pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
+    except exceptions.ServiceError as e:
+        print(f'Service error: {e}')
+        sys.exit(1)
+    except ValueError:
+        sys.exit(1)
+    print(f'{ansi_escapes.blue}List of disjunctions{ansi_escapes.reset}')
+    print(dsjn)
+    print(f'{ansi_escapes.blue}The following services have been requested:{ansi_escapes.reset}')
+    print(_data)
 
     print(f'{ansi_escapes.blue}Result summary{ansi_escapes.reset}')
     header = ['req id', '  demand', ' GSNR@bandwidth A-Z (Z-A)', ' GSNR@0.1nm A-Z (Z-A)',

gnpy/tools/convert.py

@@ -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))
 
@@ -118,7 +122,7 @@ class Eqpt(object):
         'east_att_in': 0,
         'east_amp_gain': None,
         'east_amp_dp': None,
-        'east_tilt': 0,
+        'east_tilt_vs_wavelength': 0,
         'east_att_out': None
     }
 
@@ -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:
@@ -305,13 +345,13 @@ def create_east_eqpt_element(node):
         eqpt['type_variety'] = f'{node.east_amp_type}'
         eqpt['operational'] = {'gain_target': node.east_amp_gain,
                                'delta_p':     node.east_amp_dp,
-                               'tilt_target': node.east_tilt,
+                               'tilt_target': node.east_tilt_vs_wavelength,
                                'out_voa':     node.east_att_out}
     elif node.east_amp_type.lower() == '':
         eqpt['type'] = 'Edfa'
         eqpt['operational'] = {'gain_target': node.east_amp_gain,
                                'delta_p':     node.east_amp_dp,
-                               'tilt_target': node.east_tilt,
+                               'tilt_target': node.east_tilt_vs_wavelength,
                                'out_voa':     node.east_att_out}
     elif node.east_amp_type.lower() == 'fused':
         # fused edfa variety is a hack to indicate that there should not be
@@ -338,12 +378,12 @@ def create_west_eqpt_element(node):
         eqpt['type_variety'] = f'{node.west_amp_type}'
         eqpt['operational'] = {'gain_target': node.west_amp_gain,
                                'delta_p':     node.west_amp_dp,
-                               'tilt_target': node.west_tilt,
+                               'tilt_target': node.west_tilt_vs_wavelength,
                                'out_voa':     node.west_att_out}
     elif node.west_amp_type.lower() == '':
         eqpt['operational'] = {'gain_target': node.west_amp_gain,
                                'delta_p':     node.west_amp_dp,
-                               'tilt_target': node.west_tilt,
+                               'tilt_target': node.west_tilt_vs_wavelength,
                                'out_voa':     node.west_att_out}
     elif node.west_amp_type.lower() == 'fused':
         eqpt['type'] = 'Fused'
@@ -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
 

gnpy/tools/json_io.py

@@ -1,24 +1,30 @@
 #!/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
 from pathlib import Path
 import json
 from collections import namedtuple
-from gnpy.core import ansi_escapes, elements
-from gnpy.core.equipment import trx_mode_params
+from numpy import arange
+from copy import deepcopy
+
+from gnpy.core import elements
+from gnpy.core.equipment import trx_mode_params, find_type_variety
 from gnpy.core.exceptions import ConfigurationError, EquipmentConfigError, NetworkTopologyError, ServiceError
 from gnpy.core.science_utils import estimate_nf_model
-from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions
+from gnpy.core.info import Carrier
+from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions, dbm2watt
+from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT, EdfaParams, MultiBandParams
 from gnpy.topology.request import PathRequest, Disjunction, compute_spectrum_slot_vs_bandwidth
+from gnpy.topology.spectrum_assignment import mvalue_to_slots
 from gnpy.tools.convert import xls_to_json_data
 from gnpy.tools.service_sheet import read_service_sheet
 
@@ -46,11 +52,11 @@ class _JsonThing:
         clean_kwargs = {k: v for k, v in kwargs.items() if v != ''}
         for k, v in default_values.items():
             setattr(self, k, clean_kwargs.get(k, v))
-            if k not in clean_kwargs and name != 'Amp':
-                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)
+            if k not in clean_kwargs and name != 'Amp' and v is not None and v != []:
+                # do not show this warning if the default value is None
+                msg = f'\n\tWARNING missing {k} attribute in eqpt_config.json[{name}]' \
+                    + f'\n\tdefault value is {k} = {v}\n'
+                _logger.warning(msg)
 
 
 class SI(_JsonThing):
@@ -63,7 +69,8 @@ class SI(_JsonThing):
         "power_range_db": [0, 0, 0.5],
         "roll_off": 0.15,
         "tx_osnr": 45,
-        "sys_margins": 0
+        "sys_margins": 0,
+        "tx_power_dbm": None  # optional value in SI
     }
 
     def __init__(self, **kwargs):
@@ -91,16 +98,33 @@ class Span(_JsonThing):
 
 class Roadm(_JsonThing):
     default_values = {
-        'target_pch_out_db': -17,
+        'type_variety': 'default',
         'add_drop_osnr': 100,
         'pmd': 0,
+        'pdl': 0,
         'restrictions': {
             'preamp_variety_list': [],
             'booster_variety_list': []
-        }
+        },
+        'roadm-path-impairments': []
     }
 
     def __init__(self, **kwargs):
+        # If equalization is not defined in equipment, then raise an error.
+        # Only one type of equalization must be defined.
+        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:
+            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):
+            msg = 'No equalization type set in ROADM'
+            raise EquipmentConfigError(msg)
+        for key in allowed_equalisations:
+            if key in kwargs:
+                setattr(self, key, kwargs[key])
+                break
         self.update_attr(self.default_values, kwargs, 'Roadm')
 
 
@@ -113,57 +137,55 @@ class Transceiver(_JsonThing):
 
     def __init__(self, **kwargs):
         self.update_attr(self.default_values, kwargs, 'Transceiver')
+        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'):
+                imp_penalties = [p for p in penalties if impairment in p]
+                if not imp_penalties:
+                    continue
+                if all(p[impairment] > 0 for p in imp_penalties):
+                    # make sure the list of penalty values include a proper lower boundary
+                    # (we assume 0 penalty for 0 impairment)
+                    imp_penalties.insert(0, {impairment: 0, 'penalty_value': 0})
+                # make sure the list of penalty values are sorted by impairment value
+                imp_penalties.sort(key=lambda i: i[impairment])
+                # rearrange as dict of lists instead of list of dicts
+                mode_params['penalties'][impairment] = {
+                    'up_to_boundary': [p[impairment] for p in imp_penalties],
+                    'penalty_value': [p['penalty_value'] for p in imp_penalties]
+                }
 
 
 class Fiber(_JsonThing):
     default_values = {
         'type_variety': '',
         'dispersion': None,
-        'gamma': 0,
+        'effective_area': None,
         'pmd_coef': 0
     }
 
     def __init__(self, **kwargs):
-        self.update_attr(self.default_values, kwargs, 'Fiber')
+        self.update_attr(self.default_values, kwargs, self.__class__.__name__)
+        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(_JsonThing):
-    default_values = {
-        'type_variety': '',
-        'dispersion': None,
-        'gamma': 0,
-        'pmd_coef': 0,
-        'raman_efficiency': None
-    }
-
-    def __init__(self, **kwargs):
-        self.update_attr(self.default_values, kwargs, 'RamanFiber')
-        for param in ('cr', 'frequency_offset'):
-            if param not in self.raman_efficiency:
-                raise EquipmentConfigError(f'RamanFiber.raman_efficiency: missing "{param}" parameter')
-        if self.raman_efficiency['frequency_offset'] != sorted(self.raman_efficiency['frequency_offset']):
-            raise EquipmentConfigError(f'RamanFiber.raman_efficiency.frequency_offset is not sorted')
+class RamanFiber(Fiber):
+    pass
 
 
 class Amp(_JsonThing):
-    default_values = {
-        'f_min': 191.35e12,
-        'f_max': 196.1e12,
-        'type_variety': '',
-        'type_def': '',
-        'gain_flatmax': None,
-        'gain_min': None,
-        'p_max': None,
-        'nf_model': None,
-        'dual_stage_model': None,
-        'nf_fit_coeff': None,
-        'nf_ripple': None,
-        'dgt': None,
-        'gain_ripple': None,
-        'out_voa_auto': False,
-        'allowed_for_design': False,
-        'raman': False
-    }
+    default_values = EdfaParams.default_values
 
     def __init__(self, **kwargs):
         self.update_attr(self.default_values, kwargs, 'Amp')
@@ -171,17 +193,19 @@ class Amp(_JsonThing):
     @classmethod
     def from_json(cls, filename, **kwargs):
         config = Path(filename).parent / 'default_edfa_config.json'
-
+        # default_edfa_config.json assumes a DGT profile independantly from fmin/fmax, that's a generic profile
         type_variety = kwargs['type_variety']
         type_def = kwargs.get('type_def', 'variable_gain')  # default compatibility with older json eqpt files
         nf_def = None
         dual_stage_def = None
+        amplifiers = None
 
         if type_def == 'fixed_gain':
             try:
                 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]
@@ -196,7 +220,8 @@ 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:
@@ -218,15 +243,25 @@ 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')
+                raise EquipmentConfigError(f'missing preamp/booster variety input for amplifier: {type_variety}'
+                                           + ' in equipment config')
             dual_stage_def = Model_dual_stage(preamp_variety, booster_variety)
+        elif type_def == 'multi_band':
+            amplifiers = kwargs['amplifiers']
         else:
             raise EquipmentConfigError(f'Edfa type_def {type_def} does not exist')
 
         json_data = load_json(config)
-
+        # raise an error if config does not contain f_min, f_max
+        if 'f_min' not in json_data or 'f_max' not in json_data:
+            raise EquipmentConfigError('default Edfa config does not contain f_min and f_max values.'
+                                       + ' Please correct file.')
+        # use f_min, f_max from kwargs
+        if 'f_min' in kwargs:
+            json_data.pop('f_min', None)
+            json_data.pop('f_max', None)
         return cls(**{**kwargs, **json_data,
-                      'nf_model': nf_def, 'dual_stage_model': dual_stage_def})
+                      'nf_model': nf_def, 'dual_stage_model': dual_stage_def, 'multi_band': amplifiers})
 
 
 def _automatic_spacing(baud_rate):
@@ -237,11 +272,93 @@ def _automatic_spacing(baud_rate):
     return min((s[1] for s in spacing_list if s[0] > baud_rate), default=baud_rate * 1.2)
 
 
+def _spectrum_from_json(json_data):
+    """JSON_data is a list of spectrum partitions each with
+    {f_min, f_max, baud_rate, roll_off, delta_pdb, slot_width, tx_osnr, label}
+    Creates the per freq Carrier's dict.
+    f_min, f_max, baud_rate, slot_width and roll_off are mandatory
+    label, tx_osnr and delta_pdb are created if not present
+    label should be different for each partition
+    >>> json_data = {'spectrum': \
+        [{'f_min': 193.2e12, 'f_max': 193.4e12, 'slot_width': 50e9, 'baud_rate': 32e9, 'roll_off': 0.15, \
+            'delta_pdb': 1, 'tx_osnr': 45, 'tx_power_dbm': -7},\
+        {'f_min': 193.4625e12, 'f_max': 193.9875e12, 'slot_width': 75e9, 'baud_rate': 64e9, 'roll_off': 0.15},\
+        {'f_min': 194.075e12, 'f_max': 194.075e12, 'slot_width': 100e9, 'baud_rate': 90e9, 'roll_off': 0.15},\
+        {'f_min': 194.2e12, 'f_max': 194.35e12, 'slot_width': 50e9, 'baud_rate': 32e9, 'roll_off': 0.15}]}
+    >>> spectrum = _spectrum_from_json(json_data['spectrum'])
+    >>> for k, v in spectrum.items():
+    ...     print(f'{k}: {v}')
+    ...
+    193200000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193250000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193300000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193350000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193400000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, tx_power=0.00019952623149688798, label='0-32.00G')
+    193462500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193537500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193612500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193687500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193762500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193837500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193912500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    193987500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='1-64.00G')
+    194075000000000.0: Carrier(delta_pdb=0, baud_rate=90000000000.0, slot_width=100000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='2-90.00G')
+    194200000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
+    194250000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
+    194300000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
+    194350000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, tx_power=0.001, label='3-32.00G')
+    """
+    spectrum = {}
+    json_data = sorted(json_data, key=lambda x: x['f_min'])
+    # min freq of occupation is f_min - slot_width/2 (numbering starts at 0)
+    previous_part_max_freq = 0.0
+    for index, part in enumerate(json_data):
+        # default delta_pdb is 0 dB
+        if 'delta_pdb' not in part:
+            part['delta_pdb'] = 0
+        # add a label to the partition for the printings
+        if 'label' not in part:
+            part['label'] = f'{index}-{part["baud_rate"] * 1e-9 :.2f}G'
+        # default tx_osnr is set to 40 dB
+        if 'tx_osnr' not in part:
+            part['tx_osnr'] = 40
+        # default tx_power_dbm is set to 0 dBn
+        if 'tx_power_dbm' not in part:
+            part['tx_power_dbm'] = 0
+        # starting freq is exactly f_min to be consistent with utils.automatic_nch
+        # first partition min occupation is f_min - slot_width / 2 (central_frequency is f_min)
+        # supposes that carriers are centered on frequency
+        if previous_part_max_freq > (part['f_min'] - part['slot_width'] / 2):
+            # check that previous part last channel does not overlap on next part first channel
+            # max center of the part should be below part['f_max'] and aligned on the slot_width
+            msg = 'Not a valid initial spectrum definition:\nprevious spectrum last carrier max occupation ' +\
+                f'{previous_part_max_freq * 1e-12 :.5f}GHz ' +\
+                'overlaps on next spectrum first carrier occupation ' +\
+                f'{(part["f_min"] - part["slot_width"] / 2) * 1e-12 :.5f}GHz'
+            raise ValueError(msg)
+
+        max_range = ((part['f_max'] - part['f_min']) // part['slot_width'] + 1) * part['slot_width']
+        for current_freq in arange(part['f_min'],
+                                   part['f_min'] + max_range,
+                                   part['slot_width']):
+            spectrum[current_freq] = Carrier(delta_pdb=part['delta_pdb'], baud_rate=part['baud_rate'],
+                                             slot_width=part['slot_width'], roll_off=part['roll_off'],
+                                             tx_osnr=part['tx_osnr'], tx_power=dbm2watt(part['tx_power_dbm']),
+                                             label=part['label'])
+        previous_part_max_freq = current_freq + part['slot_width'] / 2
+    return spectrum
+
+
 def load_equipment(filename):
     json_data = load_json(filename)
     return _equipment_from_json(json_data, filename)
 
 
+def load_initial_spectrum(filename):
+    json_data = load_json(filename)
+    return _spectrum_from_json(json_data['spectrum'])
+
+
 def _update_dual_stage(equipment):
     edfa_dict = equipment['Edfa']
     for edfa in edfa_dict.values():
@@ -261,15 +378,40 @@ def _update_dual_stage(equipment):
     return equipment
 
 
-def _roadm_restrictions_sanity_check(equipment):
-    """ verifies that booster and preamp restrictions specified in roadm equipment are listed
-    in the edfa.
+def _update_band(equipment: dict) -> dict:
+    """Creates a list of bands for this amplifier, and remove other parameters which are not applicable
     """
-    restrictions = equipment['Roadm']['default'].restrictions['booster_variety_list'] + \
-        equipment['Roadm']['default'].restrictions['preamp_variety_list']
-    for amp_name in restrictions:
-        if amp_name not in equipment['Edfa']:
-            raise EquipmentConfigError(f'ROADM restriction {amp_name} does not refer to a defined EDFA name')
+    amp_dict = equipment['Edfa']
+    for amplifier in amp_dict.values():
+        if amplifier.type_def != 'multi_band':
+            amplifier.bands = [{'f_min': amplifier.f_min,
+                                'f_max': amplifier.f_max}]
+            # updates band parameter
+        else:
+            _bands = [{'f_min': amp_dict[a].f_min,
+                       'f_max': amp_dict[a].f_max} for a in amp_dict[amplifier.type_variety].multi_band]
+            # remove duplicates
+            amplifier.bands = []
+            for b in _bands:
+                if b not in amplifier.bands:
+                    amplifier.bands.append(b)
+            # remove non applicable parameters
+            for key in ['f_min', 'f_max', 'gain_flatmax', 'gain_min', 'p_max', 'nf_model', 'dual_stage_model',
+                        'nf_fit_coeff', 'nf_ripple', 'dgt', 'gain_ripple']:
+                delattr(amplifier, key)
+
+    return equipment
+
+
+def _roadm_restrictions_sanity_check(equipment):
+    """verifies that booster and preamp restrictions specified in roadm equipment are listed in the edfa."""
+    for roadm_type, roadm_eqpt in equipment['Roadm'].items():
+        restrictions = roadm_eqpt.restrictions['booster_variety_list'] + \
+            roadm_eqpt.restrictions['preamp_variety_list']
+        for amp_name in restrictions:
+            if amp_name not in equipment['Edfa']:
+                raise EquipmentConfigError(f'ROADM {roadm_type} restriction {amp_name} does not refer to a '
+                                           + 'defined EDFA name')
 
 
 def _check_fiber_vs_raman_fiber(equipment):
@@ -277,7 +419,7 @@ def _check_fiber_vs_raman_fiber(equipment):
     if 'RamanFiber' not in equipment:
         return
     for fiber_type in set(equipment['Fiber'].keys()) & set(equipment['RamanFiber'].keys()):
-        for attr in ('dispersion', 'dispersion-slope', 'gamma', 'pmd-coefficient'):
+        for attr in ('dispersion', 'dispersion-slope', 'effective_area', 'gamma', 'pmd-coefficient'):
             fiber = equipment['Fiber'][fiber_type]
             raman = equipment['RamanFiber'][fiber_type]
             a = getattr(fiber, attr, None)
@@ -310,6 +452,9 @@ def _equipment_from_json(json_data, filename):
             elif key == 'Roadm':
                 equipment[key][subkey] = Roadm(**entry)
             elif key == 'SI':
+                # use power_dbm value for tx_power_dbm if the key is not in 'SI'
+                # if 'tx_power_dbm' not in entry.keys():
+                #     entry['tx_power_dbm'] = entry['power_dbm']
                 equipment[key][subkey] = SI(**entry)
             elif key == 'Transceiver':
                 equipment[key][subkey] = Transceiver(**entry)
@@ -319,7 +464,13 @@ def _equipment_from_json(json_data, filename):
                 raise EquipmentConfigError(f'Unrecognized network element type "{key}"')
     _check_fiber_vs_raman_fiber(equipment)
     equipment = _update_dual_stage(equipment)
+    equipment = _update_band(equipment)
     _roadm_restrictions_sanity_check(equipment)
+    possible_SI = list(equipment['SI'].keys())
+    if 'default' not in possible_SI:
+        # Use "default" key in the equipment, using the first listed keys
+        equipment['SI']['default'] = equipment['SI'][possible_SI[0]]
+        del equipment['SI'][possible_SI[0]]
     return equipment
 
 
@@ -334,11 +485,11 @@ 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)
 
 
@@ -355,6 +506,8 @@ def _cls_for(equipment_type):
         return elements.Fiber
     elif equipment_type == 'RamanFiber':
         return elements.RamanFiber
+    elif equipment_type == 'Multiband_amplifier':
+        return elements.Multiband_amplifier
     else:
         raise ConfigurationError(f'Unknown network equipment "{equipment_type}"')
 
@@ -368,18 +521,80 @@ def network_from_json(json_data, equipment):
         typ = el_config.pop('type')
         variety = el_config.pop('type_variety', 'default')
         cls = _cls_for(typ)
-        if typ == 'Fused':
+        if typ == 'Transceiver':
+            temp = el_config.setdefault('params', {})
+        if typ == 'Multiband_amplifier':
+            if variety in ['default', '']:
+                extra_params = None
+                temp = el_config.setdefault('params', {})
+                temp = merge_amplifier_restrictions(temp, deepcopy(MultiBandParams.default_values))
+                el_config['params'] = temp
+            else:
+                extra_params = equipment['Edfa'][variety]
+                temp = el_config.setdefault('params', {})
+                # use config params preferably to library params, only use library params to fill in
+                # the missing attribute
+                temp = merge_amplifier_restrictions(temp, deepcopy(extra_params.__dict__))
+                el_config['params'] = temp
+                el_config['type_variety'] = variety
+            # if config does not contain any amp list create one
+            amps = el_config.setdefault('amplifiers', [])
+            for amp in amps:
+                amp_variety = amp['type_variety']    # juste pour essayer
+                amp_extra_params = equipment['Edfa'][amp_variety]
+                temp = amp.setdefault('params', {})
+                temp = merge_amplifier_restrictions(temp, amp_extra_params.__dict__)
+                amp['params'] = temp
+                amp['type_variety'] = amp_variety
+            # check type_variety consistant with amps type_variety
+            if amps:
+                try:
+                    multiband_type_variety = find_type_variety([a['type_variety'] for a in amps], equipment)
+                except ConfigurationError as e:
+                    msg = f'Node {el_config["uid"]}: {e}'
+                    raise ConfigurationError(msg)
+                if variety is not None and variety != multiband_type_variety:
+                    raise ConfigurationError(f'In node {el_config["uid"]}: multiband amplifier type_variety is not '
+                                             + 'consistent with its amps type varieties.')
+            if not amps and extra_params is not None:
+                # the amp config does not contain the amplifiers operational settings, but has a type_variety
+                # defined so that it is possible to create the template of amps for design for each band. This
+                # defines the default design bands.
+                # This lopp populates each amp with default values, for each band
+                for band in extra_params.bands:
+                    params = {k: v for k, v in Amp.default_values.items()}
+                    # update frequencies with band values
+                    params['f_min'] = band['f_min']
+                    params['f_max'] = band['f_max']
+                    amps.append({'params': params})
+            # without type_variety, it is not possible to set the amplifier dict at this point: need to wait
+            # for design, and use user defined design-bands
+        elif typ == 'Fused':
             # well, there's no variety for the 'Fused' node type
             pass
         elif variety in equipment[typ]:
-            extra_params = equipment[typ][variety]
+            extra_params = equipment[typ][variety].__dict__
             temp = el_config.setdefault('params', {})
-            temp = merge_amplifier_restrictions(temp, extra_params.__dict__)
+            if typ == 'Roadm':
+                # if equalization is defined, remove default equalization from the extra_params
+                # If equalisation is not defined in the element config, then use the default one from 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:
+                    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', 'Roadm']):
             raise ConfigurationError(f'The {typ} of variety type {variety} was not recognized:'
                                      '\nplease check it is properly defined in the eqpt_config json file')
+        elif typ == 'Edfa':
+            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)
 
@@ -394,7 +609,8 @@ 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
 
@@ -425,15 +641,13 @@ 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)
 
@@ -445,33 +659,36 @@ def requests_from_json(json_data, equipment):
     for req in json_data['path-request']:
         # init all params from request
         params = {}
-        params['request_id'] = req['request-id']
+        params['request_id'] = f'{req["request-id"]}'
         params['source'] = req['source']
         params['bidir'] = req['bidirectional']
         params['destination'] = req['destination']
         params['trx_type'] = req['path-constraints']['te-bandwidth']['trx_type']
-        params['trx_mode'] = req['path-constraints']['te-bandwidth']['trx_mode']
+        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']
         try:
-            nd_list = req['explicit-route-objects']['route-object-include-exclude']
+            nd_list = sorted(req['explicit-route-objects']['route-object-include-exclude'], key=lambda x: x['index'])
         except KeyError:
             nd_list = []
         params['nodes_list'] = [n['num-unnum-hop']['node-id'] for n in nd_list]
         params['loose_list'] = [n['num-unnum-hop']['hop-type'] for n in nd_list]
         # recover trx physical param (baudrate, ...) from type and mode
-        # in trx_mode_params optical power is read from equipment['SI']['default'] and
         # nb_channel is computed based on min max frequency and spacing
-        trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
-        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:
-            if req['path-constraints']['te-bandwidth']['output-power']:
-                params['power'] = req['path-constraints']['te-bandwidth']['output-power']
-        except KeyError:
-            pass
+            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)
+        params['power'] = req['path-constraints']['te-bandwidth'].get('output-power')
+        # params must not be None, but user can set to None: catch this case
+        if params['power'] is None:
+            params['power'] = dbm2watt(equipment['SI']['default'].power_dbm)
+
         # same process for nb-channel
         f_min = params['f_min']
         f_max_from_si = params['f_max']
@@ -485,11 +702,20 @@ 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:
             pass
+        params['tx_power'] = req['path-constraints']['te-bandwidth'].get('tx_power')
+        default_tx_power_dbm = equipment['SI']['default'].tx_power_dbm
+        if params['tx_power'] is None:
+            # use request's input power in span instead
+            params['tx_power'] = params['power']
+            if default_tx_power_dbm is not None:
+                # use default tx power
+                params['tx_power'] = dbm2watt(default_tx_power_dbm)
         _check_one_request(params, f_max_from_si)
         requests_list.append(PathRequest(**params))
     return requests_list
@@ -499,44 +725,66 @@ 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'],
-                                                            params['spacing'],
-                                                            params['bit_rate'])
-        # params['effective_freq_slot']['M'] value should be bigger than the computed requested_m (simple estimate)
+    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'])
+        _, 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"]}'
-            _logger.critical(msg)
+        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
-        of requested disjunctions for this set of requests
+    """reads the disjunction requests from the json dict and create the list
+    of requested disjunctions for this set of requests
     """
     disjunctions_list = []
     if 'synchronization' in json_data:
@@ -564,3 +812,42 @@ def convert_service_sheet(
     data = read_service_sheet(input_filename, eqpt, network, network_filename, bidir)
     save_json(data, output_filename)
     return data
+
+
+def find_equalisation(params, equalization_types):
+    """Find the equalization(s) defined in params. params can be a dict or a Roadm object.
+
+    >>> roadm = {'add_drop_osnr': 100, 'pmd': 1, 'pdl': 0.5,
+    ...     'restrictions': {'preamp_variety_list': ['a'], 'booster_variety_list': ['b']},
+    ...     'target_psd_out_mWperGHz': 4e-4}
+    >>> equalization_types = ['target_pch_out_db', 'target_psd_out_mWperGHz']
+    >>> find_equalisation(roadm, equalization_types)
+    {'target_pch_out_db': False, 'target_psd_out_mWperGHz': True}
+    """
+    equalization = {e: False for e in equalization_types}
+    for equ in equalization_types:
+        if equ in params:
+            equalization[equ] = True
+    return equalization
+
+
+def merge_equalization(params, extra_params):
+    """params contains ROADM element config and extra_params default values from equipment library.
+    If equalization is not defined in ROADM element use the one defined in equipment library.
+    Only one type of equalization must be defined: power (target_pch_out_db) or PSD (target_psd_out_mWperGHz)
+    or PSW (target_out_mWperSlotWidth)
+    params and extra_params are dict
+    """
+    equalization_types = ['target_pch_out_db', 'target_psd_out_mWperGHz', 'target_out_mWperSlotWidth']
+    roadm_equalizations = find_equalisation(params, equalization_types)
+    if sum(roadm_equalizations.values()) > 1:
+        # if ROADM config contains more than one equalization type then this is an error
+        return None
+    if sum(roadm_equalizations.values()) == 1:
+        # if ROADM config contains one equalization
+        # don't use the default equalization
+        return {k: v for k, v in extra_params.items() if k not in equalization_types}
+    if sum(roadm_equalizations.values()) == 0:
+        # If ROADM config doesn't contain any equalization type, keep the default one
+        return extra_params
+    return None

gnpy/tools/plots.py

@@ -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

gnpy/tools/service_sheet.py

@@ -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

gnpy/tools/worker_utils.py

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

gnpy/topology/__init__.py

@@ -1,3 +1,3 @@
-'''
+"""
 Tracking :py:mod:`.request` for spectrum and their :py:mod:`.spectrum_assignment`.
-'''
+"""

gnpy/topology/request.py

@@ -16,34 +16,36 @@ See: draft-ietf-teas-yang-path-computation-01.txt
 """
 
 from collections import namedtuple, OrderedDict
+from typing import List
 from logging import getLogger
 from networkx import (dijkstra_path, NetworkXNoPath,
                       all_simple_paths, shortest_simple_paths)
 from networkx.utils import pairwise
-from numpy import mean
-from gnpy.core.elements import Transceiver, Roadm
-from gnpy.core.utils import lin2db
-from gnpy.core.info import create_input_spectral_information
+from numpy import mean, argmin
+
+from gnpy.core.elements import Transceiver, Roadm, Edfa, Multiband_amplifier
+from gnpy.core.utils import lin2db, find_common_range
+from gnpy.core.info import create_input_spectral_information, carriers_to_spectral_information, \
+    demuxed_spectral_information, muxed_spectral_information, SpectralInformation
+from gnpy.core import network as network_module
 from gnpy.core.exceptions import ServiceError, DisjunctionError
-import gnpy.core.ansi_escapes as ansi_escapes
 from copy import deepcopy
 from csv import writer
 from math import ceil
 
 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 bit_rate roll_off tx_osnr' +
-                           ' min_spacing cost path_bandwidth effective_freq_slot')
-DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link' +
-                               '_diverse node_diverse disjunctions_req')
+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'
+                           ' equalization_offset_db, tx_power')
+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
@@ -62,15 +64,19 @@ class PathRequest:
         self.f_max = params.f_max
         self.format = params.format
         self.OSNR = params.OSNR
+        self.penalties = params.penalties
         self.bit_rate = params.bit_rate
         self.roll_off = params.roll_off
         self.tx_osnr = params.tx_osnr
+        self.tx_power = params.tx_power
         self.min_spacing = params.min_spacing
         self.cost = params.cost
         self.path_bandwidth = params.path_bandwidth
         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}',
@@ -93,7 +99,8 @@ class PathRequest:
                             f'baud_rate:\t{temp} Gbaud',
                             f'bit_rate:\t{temp2} Gb/s',
                             f'spacing:\t{self.spacing * 1e-9} GHz',
-                            f'power:  \t{round(lin2db(self.power)+30, 2)} dBm',
+                            f'power:  \t{round(lin2db(self.power) + 30, 2)} dBm',
+                            f'tx_power_dbm:  \t{round(lin2db(self.tx_power) + 30, 2)} dBm',
                             f'nb channels: \t{self.nb_channel}',
                             f'path_bandwidth: \t{round(self.path_bandwidth * 1e-9, 2)} Gbit/s',
                             f'nodes-list:\t{self.nodes_list}',
@@ -102,8 +109,7 @@ 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)
@@ -148,8 +154,7 @@ 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:
@@ -173,10 +178,10 @@ 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)
@@ -205,11 +210,9 @@ 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',
@@ -251,8 +254,7 @@ 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 = {
@@ -290,7 +292,6 @@ 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)]
@@ -305,10 +306,9 @@ 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:
@@ -317,80 +317,117 @@ 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
 
 
+def filter_si(path: list, equipment: dict, si: SpectralInformation) -> SpectralInformation:
+    """Filter spectral information based on the amplifiers common range"""
+    # First retrieve f_min, f_max spectrum according to amplifiers' spectrum on the path
+    common_range = find_elements_common_range(path, equipment)
+    # filter out frequencies that should not be created
+    filtered_si = []
+    for band in common_range:
+        temp = demuxed_spectral_information(si, band)
+        if temp:
+            filtered_si.append(temp)
+    if not filtered_si:
+        raise ValueError('Defined propagation band does not match amplifiers band.')
+    return muxed_spectral_information(filtered_si)
+
+
 def propagate(path, req, equipment):
-    si = create_input_spectral_information(
-        req.f_min, req.f_max, req.roll_off, req.baud_rate,
-        req.power, req.spacing)
+    """propagates signals in each element according to initial spectrum set by user
+    Spectrum is specified in request through f_min, f_max and spacing, or initial_spectrum
+    and amps frequency band on the path is used to filter out frequencies"""
+    # generates spectrum based on request
+    if req.initial_spectrum is not None:
+        si = carriers_to_spectral_information(initial_spectrum=req.initial_spectrum, power=req.power)
+    else:
+        si = create_input_spectral_information(
+            f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
+            spacing=req.spacing, tx_osnr=req.tx_osnr, tx_power=req.tx_power, delta_pdb=req.offset_db)
+    # filter out frequencies that should not be created
+    si = filter_si(path, equipment, si)
+    roadm_osnr = []
     for i, el in enumerate(path):
         if isinstance(el, Roadm):
-            si = el(si, degree=path[i+1].uid)
+            si = el(si, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
+            roadm_osnr.append(el.get_impairment('roadm-osnr', si.frequency,
+                                                from_degree=path[i - 1].uid, degree=path[i + 1].uid))
         else:
             si = el(si)
-    path[0].update_snr(req.tx_osnr)
-    if any(isinstance(el, Roadm) for el in path):
-        path[-1].update_snr(req.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
-    else:
-        path[-1].update_snr(req.tx_osnr)
+    path[0].update_snr(si.tx_osnr)
+    path[0].calc_penalties(req.penalties)
+    roadm_osnr.append(si.tx_osnr)
+    path[-1].update_snr(*roadm_osnr)
+    path[-1].calc_penalties(req.penalties)
     return si
 
 
 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']
-                                    for this_mode in equipment['Transceiver'][req.tsp].mode
-                                    if float(this_mode['min_spacing']) <= req.spacing]))
+    # 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)
-            # print(modes_to_explore)
+                                      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 of is not included: for now use SI one
+            # 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
-            spc_info = create_input_spectral_information(req.f_min, req.f_max,
-                                                         equipment['SI']['default'].roll_off,
-                                                         this_br, req.power, req.spacing)
+            if req.initial_spectrum is not None:
+                # this case is not yet handled: spectrum can not be defined for the path-request-run function
+                # and this function is only called in this case. so coming here should not be considered yet.
+                msg = f'Request: {req.request_id} contains a unexpected initial_spectrum.'
+                raise ServiceError(msg)
+            spc_info = create_input_spectral_information(f_min=req.f_min, f_max=req.f_max,
+                                                         roll_off=equipment['SI']['default'].roll_off,
+                                                         baud_rate=this_br, spacing=req.spacing,
+                                                         delta_pdb=this_offset, tx_osnr=req.tx_osnr,
+                                                         tx_power=req.tx_power)
+            spc_info = filter_si(path, equipment, spc_info)
+            roadm_osnr = []
             for i, el in enumerate(path):
                 if isinstance(el, Roadm):
-                    spc_info = el(spc_info, degree=path[i+1].uid)
+                    spc_info = el(spc_info, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
+                    roadm_osnr.append(el.get_impairment('roadm-osnr', spc_info.frequency,
+                                                        from_degree=path[i - 1].uid, degree=path[i + 1].uid))
                 else:
                     spc_info = el(spc_info)
             for this_mode in modes_to_explore:
                 if path[-1].snr is not None:
                     path[0].update_snr(this_mode['tx_osnr'])
-                    if any(isinstance(el, Roadm) for el in path):
-                        path[-1].update_snr(this_mode['tx_osnr'], equipment['Roadm']['default'].add_drop_osnr)
-                    else:
-                        path[-1].update_snr(this_mode['tx_osnr'])
-                    if round(min(path[-1].snr + lin2db(this_br / (12.5e9))), 2) \
+                    path[0].calc_penalties(this_mode['penalties'])
+                    roadm_osnr.append(this_mode['tx_osnr'])
+                    path[-1].update_snr(*roadm_osnr)
+                    # remove the tx_osnr from roadm_osnr list for the next iteration
+                    del roadm_osnr[-1]
+                    path[-1].calc_penalties(this_mode['penalties'])
+                    if round(min(path[-1].snr_01nm - path[-1].total_penalty), 2) \
                             > this_mode['OSNR'] + equipment['SI']['default'].sys_margins:
                         return path, this_mode
                     else:
@@ -402,22 +439,19 @@ 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']
@@ -435,9 +469,7 @@ 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']:
@@ -447,8 +479,8 @@ 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
@@ -472,10 +504,10 @@ def jsontoparams(my_p, tsp, mode, equipment):
 
 
 def jsontocsv(json_data, equipment, fileout):
-    """ 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
+    """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
     """
     mywriter = writer(fileout)
     mywriter.writerow(('response-id', 'source', 'destination', 'path_bandwidth', 'Pass?',
@@ -810,13 +842,13 @@ 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
@@ -838,9 +870,7 @@ 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)
 
@@ -861,8 +891,7 @@ 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:
@@ -872,9 +901,9 @@ def isdisjoint(pth1, pth2):
 
 
 def find_reversed_path(pth):
-    """ 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.
+    """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.
     """
     # TODO add some indication on elements to indicate from which other they
     # are the reversed direction. This is partly done with oms indication
@@ -897,9 +926,8 @@ 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])
 
@@ -907,9 +935,7 @@ 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:
@@ -923,8 +949,7 @@ 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()
@@ -939,8 +964,7 @@ 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
@@ -973,28 +997,32 @@ 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:
+            req1.tx_power == req2.tx_power and \
+            same_disj:
         return True
     else:
         return False
 
 
 def requests_aggregation(pathreqlist, disjlist):
-    """ this function aggregates requests so that if several requests
-        exist between same source and destination and with same transponder type
+    """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
@@ -1011,23 +1039,22 @@ 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
-        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
+    """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
     """
     all_uid = [n.uid for n in network.nodes()]
     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
@@ -1046,24 +1073,21 @@ 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:
@@ -1073,23 +1097,28 @@ def deduplicate_disjunctions(disjn):
     return local_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
-        TODO change all these req, dsjct, res lists into dict !
+def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist, redesign=False):
+    """use a list but a dictionnary might be helpful to find path based on request_id
+
+    TODO change all these req, dsjct, res lists into dict !
     """
     path_res_list = []
     reversed_path_res_list = []
     propagated_reversed_path_res_list = []
 
+    total_nb_requests = len(pathreqlist)
+    if redesign:
+        LOGGER.warning('Redesign the network for each request channel, '
+                       + 'using the request channel as the reference channel for the design.')
     for i, pathreq in enumerate(pathreqlist):
 
         # use the power specified in requests but might be different from the one
         # 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
@@ -1098,8 +1127,19 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
         # elements to simulate performance, several demands having the same destination
         # may use the same transponder for the performance simulation. This is why
         # we use deepcopy: to ensure that each propagation is recorded and not overwritten
+        # reversed path is needed for correct spectrum assignment
+        if redesign:
+            # this is the legacy case where network was automatically redesigned using the
+            # request channel as reference (nb and power used for amplifiers total power out)
+            reversed_path = []
+            if pathlist[i]:
+                reversed_path = find_reversed_path(pathlist[i])
+            network_nodes_for_redesign = pathlist[i] + reversed_path
+            network_module.design_network(pathreq, network.subgraph(network_nodes_for_redesign), equipment,
+                                          set_connector_losses=False, verbose=False)
         total_path = deepcopy(pathlist[i])
-        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:
@@ -1107,13 +1147,15 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
                 # means that at this point the mode was entered/forced by user and thus a
                 # baud_rate was defined
                 propagate(total_path, pathreq, equipment)
-                temp_snr01nm = round(mean(total_path[-1].snr+lin2db(pathreq.baud_rate/(12.5e9))), 2)
-                if temp_snr01nm < 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' +\
-                          f' {pathreq.tsp_mode}\n\tcomputedSNR in 0.1nm = {temp_snr01nm} ' +\
-                          f'- required osnr {pathreq.OSNR} + {equipment["SI"]["default"].sys_margins} margin'
-                    print(msg)
+                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)}'
+                    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:
@@ -1133,6 +1175,7 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
                         pathreq.OSNR = mode['OSNR']
                         pathreq.tx_osnr = mode['tx_osnr']
                         pathreq.bit_rate = mode['bit_rate']
+                        pathreq.penalties = mode['penalties']
                     # other blocking reason should not appear at this point
                 except AttributeError:
                     pathreq.baud_rate = mode['baud_rate']
@@ -1141,26 +1184,27 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
                     pathreq.OSNR = mode['OSNR']
                     pathreq.tx_osnr = mode['tx_osnr']
                     pathreq.bit_rate = mode['bit_rate']
+                    pathreq.penalties = mode['penalties']
 
             # reversed path is needed for correct spectrum assignment
             reversed_path = find_reversed_path(pathlist[i])
             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
-                temp_snr01nm = round(mean(propagated_reversed_path[-1].snr +\
-                                          lin2db(pathreq.baud_rate/(12.5e9))), 2)
-                if temp_snr01nm < 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' +\
-                          f' {pathreq.tsp_mode}\n' +\
-                          f'\tcomputedSNR in 0.1nm = {temp_snr01nm} -' \
-                          f' required osnr {pathreq.OSNR} + {equipment["SI"]["default"].sys_margins} margin'
-                    print(msg)
+                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.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'):
@@ -1168,9 +1212,8 @@ 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 = []
 
@@ -1178,12 +1221,12 @@ 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)
@@ -1192,3 +1235,27 @@ 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
+
+
+def find_elements_common_range(el_list: list, equipment: dict) -> List[dict]:
+    """Find the common frequency range of amps of a given list of elements (for example an OMS or a path)
+    If there are no amplifiers in the path, then use the SI
+    """
+    amp_bands = [n.params.bands for n in el_list if isinstance(n, (Edfa, Multiband_amplifier))]
+    return find_common_range(amp_bands, equipment['SI']['default'].f_min, equipment['SI']['default'].f_max)

gnpy/topology/spectrum_assignment.py

@@ -15,29 +15,31 @@ element/oms correspondace
 
 from collections import namedtuple
 from logging import getLogger
-from math import ceil
-from gnpy.core.elements import Roadm, Transceiver
+
+from gnpy.core.elements import Roadm, Transceiver, Edfa, Multiband_amplifier
 from gnpy.core.exceptions import ServiceError, SpectrumError
-from gnpy.topology.request import compute_spectrum_slot_vs_bandwidth
+from gnpy.core.utils import order_slots, restore_order
+from gnpy.topology.request import compute_spectrum_slot_vs_bandwidth, find_elements_common_range
 
 LOGGER = getLogger(__name__)
+GUARDBAND = 25e9
 
 
 class Bitmap:
-    """ records the spectrum occupation
-    """
+    """records the spectrum occupation"""
 
-    def __init__(self, f_min, f_max, grid, guardband=0.15e12, bitmap=None):
-        # n is the min index including guardband. Guardband is require to be sure
+    def __init__(self, f_min, f_max, grid, guardband=GUARDBAND, bitmap=None):
+        # n is the min index including guardband. Guardband is required to be sure
         # that a channel can be assigned  with center frequency fmin (means that its
         # slot occupation goes below freq_index_min
-        n_min = frequency_to_n(f_min - guardband, grid)
-        n_max = frequency_to_n(f_max + guardband, grid) - 1
+        n_min = frequency_to_n(f_min, grid)
+        n_max = frequency_to_n(f_max, grid)
         self.n_min = n_min
         self.n_max = n_max
-        self.freq_index_min = frequency_to_n(f_min)
-        self.freq_index_max = frequency_to_n(f_max)
+        self.freq_index_min = frequency_to_n(f_min + guardband)
+        self.freq_index_max = frequency_to_n(f_max - guardband)
         self.freq_index = list(range(n_min, n_max + 1))
+        self.guardband = guardband
         if bitmap is None:
             self.bitmap = [1] * (n_max - n_min + 1)
         elif len(bitmap) == len(self.freq_index):
@@ -46,26 +48,22 @@ 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]
@@ -76,8 +74,8 @@ 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
-        records the crossed elements and the occupied spectrum
+    """OMS class is the logical container that represent a link between two adjacent ROADMs and
+    records the crossed elements and the occupied spectrum
     """
 
     def __init__(self, *args, **params):
@@ -88,7 +86,6 @@ class OMS:
         self.spectrum_bitmap = []
         self.nb_channels = 0
         self.service_list = []
-    # TODO
 
     def __str__(self):
         return '\n\t'.join([f'{type(self).__name__} {self.oms_id}',
@@ -99,36 +96,28 @@ 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=GUARDBAND, existing_spectrum=None, grid=0.00625e12):
+        """Frequencies expressed in Hz.
+        Add 150 GHz margin to enable a center channel on f_min
+        Use ITU-T G694.1 Flexible DWDM grid definition
+        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):
@@ -147,16 +136,16 @@ 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)
-        reference to Recommendation G.694.1 (02/12), Figure I.3
-        https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
+    """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
 
     >>> frequency_to_n(193.1375e12)
     6
@@ -168,9 +157,10 @@ def frequency_to_n(freq, grid=0.00625e12):
 
 
 def nvalue_to_frequency(nvalue, grid=0.00625e12):
-    """ 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
+    """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
 
     >>> nvalue_to_frequency(6)
     193137500000000.0
@@ -182,17 +172,17 @@ 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
-        reference to Recommendation G.694.1 (02/12), Figure I.3
-        https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
+    """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
 
     >>> nval, mval = slots_to_m(6, 20)
     >>> nval
@@ -207,10 +197,11 @@ def slots_to_m(startn, stopn):
 
 
 def m_to_freq(nvalue, mvalue, grid=0.00625e12):
-    """ 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
+    """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
 
     >>> fstart, fstop = m_to_freq(13, 7)
     >>> fstart
@@ -226,9 +217,7 @@ 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:
@@ -239,17 +228,60 @@ def align_grids(oms_list):
     return oms_list
 
 
+def find_network_freq_range(network, equipment):
+    """Find the lowest freq from amps and highest freq among all amps to determine the resulting bitmap
+    """
+    amp_bands = [band for n in network.nodes() if isinstance(n, (Edfa, Multiband_amplifier)) for band in n.params.bands]
+    min_frequencies = [a['f_min'] for a in amp_bands]
+    max_frequencies = [a['f_max'] for a in amp_bands]
+    return min(min_frequencies), max(max_frequencies)
+
+
+def create_oms_bitmap(oms, equipment, f_min, f_max, guardband, grid):
+    """Find the highest low freq from oms amps and lowest high freq among oms amps to determine
+    the possible bitmap window.
+    f_min and f_max represent the useable spectrum (not the useable center frequencies)
+    ie n smaller than frequency_to_n(min_freq, grid) are not useable
+    """
+    n_min = frequency_to_n(f_min, grid)
+    n_max = frequency_to_n(f_max, grid) - 1
+    common_range = find_elements_common_range(oms.el_list, equipment)
+    band0 = common_range[0]
+    band0_n_min = frequency_to_n(band0['f_min'], grid)
+    band0_n_max = frequency_to_n(band0['f_max'], grid)
+    bitmap = [0] * (band0_n_min - n_min) + [1] * (band0_n_max - band0_n_min + 1)
+    i = 1
+    while i < len(common_range):
+        band = common_range[i]
+        band_n_min = frequency_to_n(band['f_min'], grid)
+        band_n_max = frequency_to_n(band['f_max'], grid)
+        bitmap = bitmap + [0] * (band_n_min - band0_n_max - 1) + [1] * (band_n_max - band_n_min + 1)
+        band0_n_max = band_n_max
+        i += 1
+    bitmap = bitmap + [0] * (n_max - band0_n_max)
+    return bitmap
+
+
 def build_oms_list(network, equipment):
-    """ initialization of OMS list in the network
-        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.
-        the function supports different spectrum width and supposes that the whole network
-        works with the min range among OMSs
+    """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.
+    the function supports different spectrum width and supposes that the whole network
+    works with the min range among OMSs
     """
     oms_id = 0
     oms_list = []
-    for node in [n for n in network.nodes() if isinstance(n, Roadm)]:
+    # identify all vertices of OMS: of course ROADM, but aso links to external chassis transponders
+    oms_vertices = [n for n in network.nodes() if isinstance(n, Roadm)] +\
+                   [n for n in network.nodes() if isinstance(n, Transceiver)
+                    and not isinstance(next(network.successors(n)), Roadm)]
+    # determine the size of the bitmap common to all the omses: find min and max frequencies of all amps
+    # in the network. These gives the band not the center frequency. Thhen we use a reference channel
+    # slot width (50GHz) to set the f_min, f_max
+    f_min, f_max = find_network_freq_range(network, equipment)
+    for node in oms_vertices:
         for edge in network.edges([node]):
             if not isinstance(edge[1], Transceiver):
                 nd_in = edge[0]  # nd_in is a Roadm
@@ -283,8 +315,9 @@ def build_oms_list(network, equipment):
                     nd_out.oms_list = []
                     nd_out.oms_list.append(oms_id)
 
-                oms.update_spectrum(equipment['SI']['default'].f_min,
-                                    equipment['SI']['default'].f_max, grid=0.00625e12)
+                bitmap = create_oms_bitmap(oms, equipment, f_min=f_min, f_max=f_max, guardband=GUARDBAND,
+                                           grid=0.00625e12)
+                oms.update_spectrum(f_min, f_max, guardband=GUARDBAND, grid=0.00625e12, existing_spectrum=bitmap)
                 # oms.assign_spectrum(13,7) gives back (193137500000000.0, 193225000000000.0)
                 # as in the example in the standard
                 # oms.assign_spectrum(13,7)
@@ -297,8 +330,9 @@ def build_oms_list(network, equipment):
 
 
 def reversed_oms(oms_list):
-    """ identifies reversed OMS
-        only applicable for non parallel OMS
+    """identifies reversed OMS
+
+    only applicable for non parallel OMS
     """
     for oms in oms_list:
         has_reversed = False
@@ -323,28 +357,42 @@ 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.n_min)
+    freq_max = nvalue_to_frequency(spectrum.n_max)
+    aggregate_oms = OMS(**params)
+    aggregate_oms.update_spectrum(freq_min, freq_max, grid=0.00625e12, guardband=spectrum.guardband,
+                                  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)
@@ -355,29 +403,36 @@ 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)
-        # print("coucou11")
-        # print(candidate)
-    # print(freq_availability[321:321+2*m])
-    # a = [i+321 for i in range(2*m)]
-    # print(a)
-    # print(candidate)
-    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]
@@ -387,44 +442,112 @@ 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
-        if reversed path are provided, means that occupation is bidir
+    """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,
-                                                                    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
+            # 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)
+            _, 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

requirements.txt

@@ -1,7 +0,0 @@
-matplotlib>=3.3.3,<4
-networkx>=2.5,<3
-numpy>=1.19.4,<2
-pandas>=1.1.5,<2
-pbr>=5.5.1,<6
-scipy>=1.5.4,<2
-xlrd>=1.2.0,<2

setup.cfg

@@ -3,7 +3,7 @@ name = gnpy
 description-file = README.md
 description-content-type = text/markdown; variant=GFM
 author = Telecom Infra Project
-author-email = jan.kundrat@telecominfraproject.com
+author-email = jkt@jankundrat.com
 license = BSD-3-Clause
 home-page = https://github.com/Telecominfraproject/oopt-gnpy
 project_urls =
@@ -21,6 +21,9 @@ classifier =
     Programming Language :: Python :: 3 :: Only
     Programming Language :: Python :: 3.8
     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
@@ -39,9 +42,6 @@ warnerrors = True
 
 [files]
 packages = gnpy
-data_files =
-	examples = examples/*
-# FIXME: solve example data files
 
 [options.entry_points]
 console_scripts =
@@ -49,3 +49,35 @@ console_scripts =
     gnpy-transmission-example = gnpy.tools.cli_examples:transmission_main_example
     gnpy-path-request = gnpy.tools.cli_examples:path_requests_run
     gnpy-convert-xls = gnpy.tools.convert:_do_convert
+
+[options]
+install_requires =
+	# matplotlib 3.8 removed support for Python 3.8
+	matplotlib>=3.7.3,<4
+	# networkx 3.2 removed support for Python 3.8
+	networkx>=3.1,<4
+	# numpy 1.25 removed support for Python 3.8
+	numpy>=1.24.4,<2
+	pbr>=6.0.0,<7
+	# scipy 1.11 removed support for Python 3.8
+	scipy>=1.10.1,<2
+	# xlrd 2.x removed support for .xlsx, it's only .xls now
+	xlrd>=1.2.0,<2
+
+[options.extras_require]
+tests =
+	build>=1.0.3,<2
+	pytest>=7.4.3,<8
+	# pandas 2.1 removed support for Python 3.8
+	pandas>=2.0.3,<3
+	# flake v6 killed the --diff option
+	flake8>=5.0.4,<6
+
+docs =
+	alabaster>=0.7.12,<1
+	docutils>=0.17.1,<1
+	myst-parser>=0.16.1,<1
+	Pygments>=2.11.2,<3
+	rstcheck
+	Sphinx>=5.3.0,<6
+	sphinxcontrib-bibtex>=2.4.1,<3

tests/compare.py

@@ -1,135 +0,0 @@
-#!/usr/bin/env python3
-from json import dump
-from pathlib import Path
-from argparse import ArgumentParser
-from collections import namedtuple
-from gnpy.tools.json_io import load_json
-
-
-class Results(namedtuple('Results', 'missing extra different expected actual')):
-    def _asdict(self):
-        return {'missing': self.missing,
-                'extra': self.extra,
-                'different': self.different}
-
-    def __str__(self):
-        rv = []
-        if self.missing:
-            rv.append('Missing: {len(self.missing)}/{len(self.expected)}')
-            rv.extend(f'\t{x}' for x in sorted(self.missing))
-        if self.extra:
-            rv.append('Extra: {len(self.extra)}/{len(self.expected)}')
-            rv.extend(f'\t{x}' for x in sorted(self.extra))
-        if self.different:
-            rv.append('Different: {len(self.different)}/{len(self.expected)}')
-            rv.extend(f'\tExpected: {x}\n\tActual:   {y}' for x, y in self.different)
-        if not self.missing and not self.extra and not self.different:
-            rv.append('All match!')
-        return '\n'.join(rv)
-
-
-class NetworksResults(namedtuple('NetworksResult', 'elements connections')):
-    def _asdict(self):
-        return {'elements': self.elements._asdict(),
-                'connections': self.connections._asdict()}
-
-    def __str__(self):
-        return '\n'.join([
-            'Elements'.center(40, '='),
-            str(self.elements),
-            'Connections'.center(40, '='),
-            str(self.connections),
-        ])
-
-
-class ServicesResults(namedtuple('ServicesResult', 'requests synchronizations')):
-    def _asdict(self):
-        return {'requests': self.requests.asdict(),
-                'synchronizations': self.synchronizations.asdict()}
-
-    def __str__(self):
-        return '\n'.join([
-            'Requests'.center(40, '='),
-            str(self.requests),
-            'Synchronizations'.center(40, '='),
-            str(self.synchronizations),
-        ])
-
-
-class PathsResults(namedtuple('PathsResults', 'paths')):
-    def _asdict(self):
-        return {'paths': self.paths.asdict()}
-
-    def __str__(self):
-        return '\n'.join([
-            'Paths'.center(40, '='),
-            str(self.paths),
-        ])
-
-
-def compare(expected, actual, key=lambda x: x):
-    expected = {key(el): el for el in expected}
-    actual = {key(el): el for el in actual}
-    missing = set(expected) - set(actual)
-    extra = set(actual) - set(expected)
-    different = [(expected[x], actual[x]) for
-                 x in set(expected) & set(actual)
-                 if expected[x] != actual[x]]
-    return Results(missing, extra, different, expected, actual)
-
-
-def compare_networks(expected, actual):
-    elements = compare(expected['elements'], actual['elements'],
-                       key=lambda el: el['uid'])
-    connections = compare(expected['connections'], actual['connections'],
-                          key=lambda el: (el['from_node'], el['to_node']))
-    return NetworksResults(elements, connections)
-
-
-def compare_services(expected, actual):
-    requests = compare(expected['path-request'], actual['path-request'],
-                       key=lambda el: el['request-id'])
-    synchronizations = compare(expected['path-request'], expected['path-request'],
-                               key=lambda el: el['request-id'])
-    if 'synchronization' in expected.keys():
-        synchronizations = compare(expected['synchronization'], actual['synchronization'],
-                                   key=lambda el: el['synchronization-id'])
-    return ServicesResults(requests, synchronizations)
-
-
-def compare_paths(expected_output, actual_output):
-    paths = compare(expected['path'], actual['path'], key=lambda el: el['path-id'])
-    return PathsResults(paths)
-
-
-COMPARISONS = {
-    'networks': compare_networks,
-    'services': compare_services,
-    'paths': compare_paths,
-}
-
-parser = ArgumentParser()
-parser.add_argument('expected_output', type=Path, metavar='FILE')
-parser.add_argument('actual_output', type=Path, metavar='FILE')
-parser.add_argument('-o', '--output', default=None)
-parser.add_argument('-c', '--comparison', choices=COMPARISONS, default='networks')
-
-
-def encode_sets(obj):
-    if isinstance(obj, set):
-        return list(obj)
-    raise TypeError(f'{obj!r} is not JSON serializable!')
-
-
-if __name__ == '__main__':
-    args = parser.parse_args()
-    expected = load_json(args.expected_output)
-    actual = load_json(args.actual_output)
-
-    result = COMPARISONS[args.comparison](expected, actual)
-
-    if args.output:
-        with open(args.output, 'w', encoding='utf-8') as f:
-            dump(result, f, default=encode_sets, indent=2, ensure_ascii=False)
-    else:
-        print(str(result))

tests/conftest.py

@@ -0,0 +1,13 @@
+# SPDX-License-Identifier: BSD-3-Clause
+#
+# Copyright (C) 2020 Telecom Infra Project and GNPy contributors
+# see LICENSE.md for a list of contributors
+#
+
+import pytest
+from gnpy.core.parameters import SimParams, NLIParams, RamanParams
+
+
+@pytest.fixture
+def set_sim_params(monkeypatch):
+    monkeypatch.setattr(SimParams, '_shared_dict', {'nli_params': NLIParams(), 'raman_params': RamanParams()})

tests/data/CORONET_services.json

@@ -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
+        }
+      }
+    }
+  ]
+}

tests/data/default_edfa_config.json

@@ -1,4 +1,6 @@
 {
+    "f_min": 191.275e12,
+    "f_max": 196.125e12,
     "nf_ripple": [
         0.0,
         0.0,
@@ -196,101 +198,101 @@
         0.0
     ],
     "dgt": [
-        2.714526681131686,
-        2.705443819238505,
-        2.6947834587664494,
-        2.6841217449620203,
-        2.6681935771243177,
-        2.6521732021128046,
-        2.630396440815385,
-        2.602860350286428,
-        2.5696460593920065,
-        2.5364027376452056,
-        2.499446286796604,
-        2.4587748041127506,
-        2.414398437185221,
-        2.3699990328716107,
-        2.322373696229342,
-        2.271520771371253,
-        2.2174389328192197,
-        2.16337565384239,
-        2.1183028432496016,
-        2.082225099873648,
-        2.055100772005235,
-        2.0279625371819305,
-        2.0008103857988204,
-        1.9736443063300082,
-        1.9482128147680253,
-        1.9245345552113182,
-        1.9026104247588487,
-        1.8806927939516411,
-        1.862235672444246,
-        1.847275503201129,
-        1.835814081380705,
-        1.824381436842932,
-        1.8139629377087627,
-        1.8045606557581335,
-        1.7961751115773796,
-        1.7877868031023945,
-        1.7793941781790852,
-        1.7709972329654864,
-        1.7625959636196327,
-        1.7541903672600494,
-        1.7459181197626403,
-        1.737780757913635,
-        1.7297783508684146,
-        1.7217732861435076,
-        1.7137640932265894,
-        1.7057507692361864,
-        1.6918150918099673,
-        1.6719047669939942,
-        1.6460167077689267,
-        1.6201194134191075,
-        1.5986915141218316,
-        1.5817353179379183,
-        1.569199764184379,
-        1.5566577309558969,
-        1.545374152761467,
-        1.5353620432989845,
-        1.5266220576235803,
-        1.5178910621476225,
-        1.5097346239790443,
-        1.502153039909686,
-        1.495145456062699,
-        1.488134243479226,
-        1.48111939735681,
-        1.474100442252211,
-        1.4670307626366115,
-        1.4599103316162523,
-        1.45273959485914,
-        1.445565137158368,
-        1.4340878115214444,
-        1.418273806730323,
-        1.3981208704326855,
-        1.3779439775587023,
-        1.3598972673004606,
-        1.3439818461440451,
-        1.3301807335621048,
-        1.316383926863083,
-        1.3040618749785347,
-        1.2932153453410835,
-        1.2838336236692311,
-        1.2744470198196236,
-        1.2650555289898042,
-        1.2556591482982988,
-        1.2428104897182262,
-        1.2264996957264114,
-        1.2067249615595257,
-        1.1869318618366975,
-        1.1672278304018044,
-        1.1476135933863398,
-        1.1280891949729075,
-        1.108555289615659,
-        1.0895983485572227,
-        1.0712204022764056,
-        1.0534217504465226,
-        1.0356155337864215,
+        1.0,
         1.017807767853702,
-        1.0
+        1.0356155337864215,
+        1.0534217504465226,
+        1.0712204022764056,
+        1.0895983485572227,
+        1.108555289615659,
+        1.1280891949729075,
+        1.1476135933863398,
+        1.1672278304018044,
+        1.1869318618366975,
+        1.2067249615595257,
+        1.2264996957264114,
+        1.2428104897182262,
+        1.2556591482982988,
+        1.2650555289898042,
+        1.2744470198196236,
+        1.2838336236692311,
+        1.2932153453410835,
+        1.3040618749785347,
+        1.316383926863083,
+        1.3301807335621048,
+        1.3439818461440451,
+        1.3598972673004606,
+        1.3779439775587023,
+        1.3981208704326855,
+        1.418273806730323,
+        1.4340878115214444,
+        1.445565137158368,
+        1.45273959485914,
+        1.4599103316162523,
+        1.4670307626366115,
+        1.474100442252211,
+        1.48111939735681,
+        1.488134243479226,
+        1.495145456062699,
+        1.502153039909686,
+        1.5097346239790443,
+        1.5178910621476225,
+        1.5266220576235803,
+        1.5353620432989845,
+        1.545374152761467,
+        1.5566577309558969,
+        1.569199764184379,
+        1.5817353179379183,
+        1.5986915141218316,
+        1.6201194134191075,
+        1.6460167077689267,
+        1.6719047669939942,
+        1.6918150918099673,
+        1.7057507692361864,
+        1.7137640932265894,
+        1.7217732861435076,
+        1.7297783508684146,
+        1.737780757913635,
+        1.7459181197626403,
+        1.7541903672600494,
+        1.7625959636196327,
+        1.7709972329654864,
+        1.7793941781790852,
+        1.7877868031023945,
+        1.7961751115773796,
+        1.8045606557581335,
+        1.8139629377087627,
+        1.824381436842932,
+        1.835814081380705,
+        1.847275503201129,
+        1.862235672444246,
+        1.8806927939516411,
+        1.9026104247588487,
+        1.9245345552113182,
+        1.9482128147680253,
+        1.9736443063300082,
+        2.0008103857988204,
+        2.0279625371819305,
+        2.055100772005235,
+        2.082225099873648,
+        2.1183028432496016,
+        2.16337565384239,
+        2.2174389328192197,
+        2.271520771371253,
+        2.322373696229342,
+        2.3699990328716107,
+        2.414398437185221,
+        2.4587748041127506,
+        2.499446286796604,
+        2.5364027376452056,
+        2.5696460593920065,
+        2.602860350286428,
+        2.630396440815385,
+        2.6521732021128046,
+        2.6681935771243177,
+        2.6841217449620203,
+        2.6947834587664494,
+        2.705443819238505,
+        2.714526681131686
     ]
-}
+}

tests/data/eqpt_config.json

@@ -1,4 +1,5 @@
-{     "Edfa":[{
+{
+    "Edfa": [{
             "type_variety": "CienaDB_medium_gain",
             "type_def": "advanced_model",
             "gain_flatmax": 25,
@@ -7,10 +8,9 @@
             "advanced_config_from_json": "std_medium_gain_advanced_config.json",
             "out_voa_auto": false,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "std_medium_gain",
-            "type_def": "variable_gain",            
+            "type_def": "variable_gain",
             "gain_flatmax": 26,
             "gain_min": 15,
             "p_max": 21,
@@ -18,10 +18,9 @@
             "nf_max": 10,
             "out_voa_auto": false,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "std_low_gain",
-            "type_def": "variable_gain",            
+            "type_def": "variable_gain",
             "gain_flatmax": 16,
             "gain_min": 8,
             "p_max": 21,
@@ -29,8 +28,7 @@
             "nf_max": 11,
             "out_voa_auto": false,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "test",
             "type_def": "variable_gain",
             "gain_flatmax": 25,
@@ -40,8 +38,7 @@
             "nf_max": 10,
             "out_voa_auto": false,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "test_fixed_gain",
             "type_def": "fixed_gain",
             "gain_flatmax": 21,
@@ -49,8 +46,7 @@
             "p_max": 21,
             "nf0": 5,
             "allowed_for_design": true
-            },
-            {
+        }, {
             "type_variety": "std_booster",
             "type_def": "fixed_gain",
             "gain_flatmax": 21,
@@ -58,18 +54,18 @@
             "p_max": 21,
             "nf0": 5,
             "allowed_for_design": false
-            }            
-      ],
-      "Fiber":[{
+        }
+    ],
+    "Fiber": [{
             "type_variety": "SSMF",
             "dispersion": 1.67e-05,
-            "gamma": 0.00127,
+            "effective_area": 83e-12,
             "pmd_coef": 1.265e-15
-            }
-      ],
-      "Span":[{
-            "power_mode":true,
-            "delta_power_range_db": [0,0,0.5],
+        }
+    ],
+    "Span": [{
+            "power_mode": true,
+            "delta_power_range_db": [0, 0, 0.5],
             "max_fiber_lineic_loss_for_raman": 0.25,
             "target_extended_gain": 2.5,
             "max_length": 150,
@@ -79,156 +75,232 @@
             "EOL": 0,
             "con_in": 0,
             "con_out": 0
-            }
-      ],
-      "Roadm":[{
+        }
+    ],
+    "Roadm": [{
+            "type_variety": "example_test",
+            "target_pch_out_db": -18,
+            "add_drop_osnr": 35,
+            "pmd": 1e-12,
+            "pdl": 0.5,
+            "restrictions": {
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            },
+            "roadm-path-impairments": []
+        }, {
+            "type_variety": "example_detailed_impairments",
+            "target_pch_out_db": -20,
+            "add_drop_osnr": 35,
+            "pmd": 0,
+            "pdl": 0,
+            "restrictions": {
+                "preamp_variety_list":[],
+                "booster_variety_list":[]
+                            },
+            "roadm-path-impairments": [
+                  {
+                    "roadm-path-impairments-id": 0,
+                    "roadm-express-path": [{
+                        "frequency-range": {
+                            "lower-frequency": 191.3e12,
+                            "upper-frequency": 196.1e12
+                            },
+                        "roadm-pmd": 0,
+                        "roadm-cd": 0,
+                        "roadm-pdl": 0,
+                        "roadm-inband-crosstalk": 0,
+                        "roadm-maxloss": 16.5
+                        }
+                    ]
+                }, {
+                    "roadm-path-impairments-id": 1,
+                    "roadm-add-path": [{
+                        "frequency-range": {
+                            "lower-frequency": 191.3e12,
+                            "upper-frequency": 196.1e12
+                        },
+                        "roadm-pmd": 0,
+                        "roadm-cd": 0,
+                        "roadm-pdl": 0,
+                        "roadm-inband-crosstalk": 0,
+                        "roadm-maxloss": 11.5,
+                        "roadm-pmax": 2.5,
+                        "roadm-osnr": 41,
+                        "roadm-noise-figure": 23
+                    }, {
+                        "frequency-range": {
+                            "lower-frequency": 186.3e12,
+                            "upper-frequency": 190.1e12
+                        },
+                        "roadm-pmd": 0,
+                        "roadm-cd": 0,
+                        "roadm-pdl": 0.5,
+                        "roadm-inband-crosstalk": 0,
+                        "roadm-maxloss": 5,
+                        "roadm-pmax": 0,
+                        "roadm-osnr": 35,
+                        "roadm-noise-figure": 6
+                    }]
+                }, {
+                    "roadm-path-impairments-id": 2,
+                    "roadm-drop-path": [{
+                        "frequency-range": {
+                            "lower-frequency": 191.3e12,
+                            "upper-frequency": 196.1e12
+                            },
+                        "roadm-pmd": 0,
+                        "roadm-cd": 0,
+                        "roadm-pdl": 0,
+                        "roadm-inband-crosstalk": 0,
+                        "roadm-maxloss": 11.5,
+                        "roadm-minloss": 7.5,
+                        "roadm-typloss": 10,
+                        "roadm-pmin": -13.5,
+                        "roadm-pmax": -9.5,
+                        "roadm-ptyp": -12,
+                        "roadm-osnr": 41,
+                        "roadm-noise-figure": 15
+                    }]
+                }]
+        }, {
             "target_pch_out_db": -20,
             "add_drop_osnr": 38,
             "pmd": 0,
+            "pdl": 0,
             "restrictions": {
-                            "preamp_variety_list":[],
-                            "booster_variety_list":[]
-                            }    
-            }],
-      "SI":[{
+                "preamp_variety_list": [],
+                "booster_variety_list": []
+            }
+        }
+    ],
+    "SI": [{
+            "type_variety": "default",
             "f_min": 191.3e12,
-            "f_max":196.1e12,
+            "f_max": 196.1e12,
             "baud_rate": 32e9,
             "spacing": 50e9,
             "power_dbm": 0,
-            "power_range_db": [0,0,0.5],
+            "power_range_db": [0, 0, 0.5],
             "roll_off": 0.15,
             "tx_osnr": 100,
-            "sys_margins": 0            
-            }],
+            "sys_margins": 0
+        }],
       "Transceiver":[
             {
             "type_variety": "vendorA_trx-type1",
-            "frequency":{
-                        "min": 191.35e12,
-                        "max": 196.1e12
-                        },
-            "mode":[
-                       {
-                       "format": "PS_SP64_1",
-                       "baud_rate": 32e9,
-                       "OSNR": 11,
-                       "bit_rate": 100e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 100,
-                       "min_spacing": 50e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "PS_SP64_2",
-                       "baud_rate": 64e9,
-                       "OSNR": 15,
-                       "bit_rate": 200e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 100,
-                       "min_spacing": 75e9,
-                       "cost":1                       
-                       },
-                       {
-                       "format": "mode 1",
-                       "baud_rate": 32e9,
-                       "OSNR": 11,
-                       "bit_rate": 100e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 100,
-                       "min_spacing": 50e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "mode 2",
-                       "baud_rate": 64e9,
-                       "OSNR": 15,
-                       "bit_rate": 200e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 100,
-                       "min_spacing": 75e9,
-                       "cost":1                       
-                       }                       
-                   ]
+            "frequency": {
+                "min": 191.35e12,
+                "max": 196.1e12
             },
-            {
+            "mode": [{
+                    "format": "PS_SP64_1",
+                    "baud_rate": 32e9,
+                    "OSNR": 11,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "PS_SP64_2",
+                    "baud_rate": 64e9,
+                    "OSNR": 15,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 1",
+                    "baud_rate": 32e9,
+                    "OSNR": 11,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2",
+                    "baud_rate": 64e9,
+                    "OSNR": 15,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }
+            ]
+        }, {
             "type_variety": "Voyager_16QAM",
-            "frequency":{
-                        "min": 191.35e12,
-                        "max": 196.1e12
-                        },
-            "mode":[
-                       {
-                       "format": "16QAM",
-                       "baud_rate": 32e9,
-                       "OSNR": 19,
-                       "bit_rate": 200e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 100,
-                       "min_spacing": 50e9,
-                       "cost":1
-                       }
-                   ]
+            "frequency": {
+                "min": 191.35e12,
+                "max": 196.1e12
             },
-            {
+            "mode": [{
+                    "format": "16QAM",
+                    "baud_rate": 32e9,
+                    "OSNR": 19,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 100,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }
+            ]
+        }, {
             "type_variety": "Voyager",
-            "frequency":{
-                        "min": 191.35e12,
-                        "max": 196.1e12
-                        },
-            "mode":[
-                       {
-                       "format": "mode 1",
-                       "baud_rate": 32e9,
-                       "OSNR": 12,
-                       "bit_rate": 100e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 45,
-                       "min_spacing": 50e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "mode 3",
-                       "baud_rate": 44e9,
-                       "OSNR": 18,
-                       "bit_rate": 300e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 45,
-                       "min_spacing": 62.5e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "mode 2",
-                       "baud_rate": 66e9,
-                       "OSNR": 21,
-                       "bit_rate": 400e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 45,
-                       "min_spacing": 75e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "mode 2 - fake",
-                       "baud_rate": 66e9,
-                       "OSNR": 21,
-                       "bit_rate": 400e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 45,
-                       "min_spacing": 75e9,
-                       "cost":1
-                       },                       
-                       {
-                       "format": "mode 4",
-                       "baud_rate": 66e9,
-                       "OSNR": 16,
-                       "bit_rate": 200e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 45,
-                       "min_spacing": 75e9,
-                       "cost":1
-                       }
-                   ]
-            }
-      ]
-
+            "frequency": {
+                "min": 191.35e12,
+                "max": 196.1e12
+            },
+            "mode": [{
+                    "format": "mode 1",
+                    "baud_rate": 32e9,
+                    "OSNR": 12,
+                    "bit_rate": 100e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 50e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 3",
+                    "baud_rate": 44e9,
+                    "OSNR": 18,
+                    "bit_rate": 300e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 62.5e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2",
+                    "baud_rate": 66e9,
+                    "OSNR": 21,
+                    "bit_rate": 400e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 2 - fake",
+                    "baud_rate": 66e9,
+                    "OSNR": 21,
+                    "bit_rate": 400e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }, {
+                    "format": "mode 4",
+                    "baud_rate": 66e9,
+                    "OSNR": 16,
+                    "bit_rate": 200e9,
+                    "roll_off": 0.15,
+                    "tx_osnr": 45,
+                    "min_spacing": 75e9,
+                    "cost": 1
+                }
+            ]
+        }
+    ]
 }

tests/data/eqpt_config_multiband.json

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

tests/data/eqpt_config_psd.json

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

tests/data/eqpt_config_psw.json

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

tests/data/eqpt_config_sweep.json

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

tests/data/perdegreemeshTopologyExampleV2_auto_design_expected.json

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

tests/data/raman_fiber_config.json

@@ -1,224 +0,0 @@
-{
-  "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,
-    "gamma": 0.00127,
-    "pmd_coef": 1.265e-15,
-    "raman_efficiency": {
-      "cr": [
-        0,
-        0.0000094,
-        0.0000292,
-        0.0000488,
-        0.0000682,
-        0.0000831,
-        0.000094,
-        0.0001014,
-        0.0001069,
-        0.0001119,
-        0.0001217,
-        0.0001268,
-        0.0001365,
-        0.000149,
-        0.000165,
-        0.000181,
-        0.0001977,
-        0.0002192,
-        0.0002469,
-        0.0002749,
-        0.0002999,
-        0.0003206,
-        0.0003405,
-        0.0003592,
-        0.000374,
-        0.0003826,
-        0.0003841,
-        0.0003826,
-        0.0003802,
-        0.0003756,
-        0.0003549,
-        0.0003795,
-        0.000344,
-        0.0002933,
-        0.0002024,
-        0.0001158,
-        0.0000846,
-        0.0000714,
-        0.0000686,
-        0.000085,
-        0.0000893,
-        0.0000901,
-        0.0000815,
-        0.0000667,
-        0.0000437,
-        0.0000328,
-        0.0000296,
-        0.0000265,
-        0.0000257,
-        0.0000281,
-        0.0000308,
-        0.0000367,
-        0.0000585,
-        0.0000663,
-        0.0000636,
-        0.000055,
-        0.0000406,
-        0.0000277,
-        0.0000242,
-        0.0000187,
-        0.000016,
-        0.000014,
-        0.0000113,
-        0.0000105,
-        0.0000098,
-        0.0000098,
-        0.0000113,
-        0.0000164,
-        0.0000195,
-        0.0000238,
-        0.0000226,
-        0.0000203,
-        0.0000148,
-        0.0000109,
-        0.0000098,
-        0.0000105,
-        0.0000117,
-        0.0000125,
-        0.0000121,
-        0.0000109,
-        0.0000098,
-        0.0000082,
-        0.0000066,
-        0.0000047,
-        0.0000027,
-        0.0000019,
-        0.0000012,
-        4e-7,
-        2e-7,
-        1e-7
-      ],
-      "frequency_offset": [
-        0,
-        500000000000,
-        1000000000000,
-        1500000000000,
-        2000000000000,
-        2500000000000,
-        3000000000000,
-        3500000000000,
-        4000000000000,
-        4500000000000,
-        5000000000000,
-        5500000000000,
-        6000000000000,
-        6500000000000,
-        7000000000000,
-        7500000000000,
-        8000000000000,
-        8500000000000,
-        9000000000000,
-        9500000000000,
-        10000000000000,
-        10500000000000,
-        11000000000000,
-        11500000000000,
-        12000000000000,
-        12500000000000,
-        12750000000000,
-        13000000000000,
-        13250000000000,
-        13500000000000,
-        14000000000000,
-        14500000000000,
-        14750000000000,
-        15000000000000,
-        15500000000000,
-        16000000000000,
-        16500000000000,
-        17000000000000,
-        17500000000000,
-        18000000000000,
-        18250000000000,
-        18500000000000,
-        18750000000000,
-        19000000000000,
-        19500000000000,
-        20000000000000,
-        20500000000000,
-        21000000000000,
-        21500000000000,
-        22000000000000,
-        22500000000000,
-        23000000000000,
-        23500000000000,
-        24000000000000,
-        24500000000000,
-        25000000000000,
-        25500000000000,
-        26000000000000,
-        26500000000000,
-        27000000000000,
-        27500000000000,
-        28000000000000,
-        28500000000000,
-        29000000000000,
-        29500000000000,
-        30000000000000,
-        30500000000000,
-        31000000000000,
-        31500000000000,
-        32000000000000,
-        32500000000000,
-        33000000000000,
-        33500000000000,
-        34000000000000,
-        34500000000000,
-        35000000000000,
-        35500000000000,
-        36000000000000,
-        36500000000000,
-        37000000000000,
-        37500000000000,
-        38000000000000,
-        38500000000000,
-        39000000000000,
-        39500000000000,
-        40000000000000,
-        40500000000000,
-        41000000000000,
-        41500000000000,
-        42000000000000
-      ]
-    }
-  },
-  "operational": {
-    "temperature": 283,
-    "raman_pumps": [
-      {
-        "power": 0.2,
-        "frequency": 205000000000000,
-        "propagation_direction": "counterprop"
-      },
-      {
-        "power": 0.206,
-        "frequency": 201000000000000,
-        "propagation_direction": "counterprop"
-      }
-    ]
-  },
-  "metadata": {
-    "location": {
-      "latitude": 1,
-      "longitude": 0,
-      "city": null,
-      "region": ""
-    }
-  }
-}

tests/data/sim_params.json

@@ -1,14 +1,13 @@
 {
-  "raman_parameters": {
-    "flag_raman": true,
-    "space_resolution": 10e3,
-    "tolerance": 1e-8
+  "raman_params": {
+    "flag": true,
+    "result_spatial_resolution": 10e3,
+    "solver_spatial_resolution": 10e3
   },
-  "nli_parameters": {
-    "nli_method_name": "ggn_spectrally_separated",
-    "wdm_grid_size": 50e9,
+  "nli_params": {
+    "method": "ggn_spectrally_separated",
     "dispersion_tolerance": 1,
     "phase_shift_tolerance": 0.1,
     "computed_channels": [1, 18, 37, 56, 75]
   }
-}
+}

tests/data/std_medium_gain_advanced_config.json

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

tests/data/testTopology_auto_design_expected.json

@@ -159,6 +159,7 @@
     {
       "uid": "roadm Lannion_CAS",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -183,6 +184,7 @@
     {
       "uid": "roadm Lorient_KMA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -207,6 +209,7 @@
     {
       "uid": "roadm Vannes_KBE",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -230,6 +233,7 @@
     {
       "uid": "roadm Rennes_STA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -240,7 +244,6 @@
           "east edfa in Rennes_STA to Stbrieuc": -20,
           "east edfa in Rennes_STA to Ploermel": -20
         }
-
       },
       "metadata": {
         "location": {
@@ -254,6 +257,7 @@
     {
       "uid": "roadm Brest_KLA",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -277,6 +281,7 @@
     {
       "uid": "roadm a",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -302,6 +307,7 @@
     {
       "uid": "roadm b",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -310,7 +316,7 @@
           ],
           "booster_variety_list": []
         },
-        "per_degree_pch_out_db":{
+        "per_degree_pch_out_db": {
           "east edfa in b to a": -20,
           "east edfa in b to f": -20
         }
@@ -327,13 +333,14 @@
     {
       "uid": "roadm c",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
           "preamp_variety_list": [],
           "booster_variety_list": []
         },
-        "per_degree_pch_out_db":{
+        "per_degree_pch_out_db": {
           "east edfa in c to a": -20,
           "east edfa in c to d": -20,
           "east edfa in c to f": -20
@@ -351,6 +358,7 @@
     {
       "uid": "roadm d",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -374,6 +382,7 @@
     {
       "uid": "roadm e",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -397,6 +406,7 @@
     {
       "uid": "roadm f",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -421,6 +431,7 @@
     {
       "uid": "roadm g",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -430,7 +441,7 @@
         "per_degree_pch_out_db": {
           "east edfa in g to e": -20,
           "east edfa in g to h": -20
-         }
+        }
       },
       "metadata": {
         "location": {
@@ -444,6 +455,7 @@
     {
       "uid": "roadm h",
       "type": "Roadm",
+      "type_variety": "default",
       "params": {
         "target_pch_out_db": -20,
         "restrictions": {
@@ -1593,7 +1605,7 @@
       "type": "Edfa",
       "type_variety": "std_medium_gain",
       "operational": {
-        "gain_target": 18.5,
+        "gain_target": 13.177288,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -2235,7 +2247,7 @@
       "type": "Edfa",
       "type_variety": "std_low_gain",
       "operational": {
-        "gain_target": 6.5,
+        "gain_target": 11.822712,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -2292,7 +2304,7 @@
       "type": "Edfa",
       "type_variety": "std_low_gain",
       "operational": {
-        "gain_target": 13.82,
+        "gain_target": 13.822712,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0
@@ -2311,7 +2323,7 @@
       "type": "Edfa",
       "type_variety": "test_fixed_gain",
       "operational": {
-        "gain_target": 15.18,
+        "gain_target": 15.177288,
         "delta_p": null,
         "tilt_target": 0,
         "out_voa": 0

tests/data/testTopology_response_expected.csv

@@ -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 2,30.79,28.77,21.68,64.0,3.0,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,,,,,,,,,,,,,,

tests/data/test_fiber_fix_expected_results.csv

@@ -0,0 +1,97 @@
+signal,nli
+1.9952623149688796e-05,1.0570305869494063e-08
+1.9952623149688796e-05,1.1989102199581664e-08
+1.9952623149688796e-05,1.2687787891259665e-08
+1.9952623149688796e-05,1.3153676763101585e-08
+1.9952623149688796e-05,1.3504001312414315e-08
+1.9952623149688796e-05,1.378517965356758e-08
+1.9952623149688796e-05,1.4020312829929705e-08
+1.9952623149688796e-05,1.4222564206194578e-08
+1.9952623149688796e-05,1.440014394542033e-08
+1.9952623149688796e-05,1.4558516068269932e-08
+1.9952623149688796e-05,1.4701499315172012e-08
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tests/data/test_fiber_flex_expected_with_raman_results.csv

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+          "type": "Roadm"
+        },
+        {
+            "uid": "Site_B",
+            "type": "Transceiver",
+            "metadata": {
+                "location": {
+                    "city": "Site B",
+                    "region": "",
+                    "latitude": 3,
+                    "longitude": 0
+                }
+            }
+        }
+
+    ],
+    "connections": [{
+            "from_node": "Site_A",
+            "to_node": "roadm Site A"
+        },
+        {
+            "from_node": "roadm Site A",
+            "to_node": "booster A"
+        },
+        {
+            "from_node": "booster A",
+            "to_node": "Span1"
+        },
+        {
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+            "to_node": "Edfa1"
+        },
+        {
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+            "to_node": "Span2"
+        },
+        {
+            "from_node": "Span2",
+            "to_node": "Edfa2"
+        },       
+        {
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+            "to_node": "Span3"
+        },
+        {
+            "from_node": "Span3",
+            "to_node": "Edfa3"
+        },       
+        {
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+            "to_node": "Span4"
+        },
+        {
+            "from_node": "Span4",
+            "to_node": "Edfa4"
+        },       
+        {
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+            "to_node": "Span5"
+        },
+        {
+            "from_node": "Span5",
+            "to_node": "Edfa5"
+        },       
+        {
+            "from_node": "Edfa5",
+            "to_node": "roadm Site C"
+        },
+        {
+            "from_node": "roadm Site C",
+            "to_node": "booster C"
+        },
+        {
+            "from_node": "booster C",
+            "to_node": "Span6"
+        },
+        {
+            "from_node": "Span6",
+            "to_node": "Edfa6"
+        },
+        {
+            "from_node": "Edfa6",
+            "to_node": "Span7"
+        },
+        {
+            "from_node": "Span7",
+            "to_node": "Edfa7"
+        },       
+        {
+            "from_node": "Edfa7",
+            "to_node": "Span8"
+        },
+        {
+            "from_node": "Span8",
+            "to_node": "Edfa8"
+        },       
+        {
+            "from_node": "Edfa8",
+            "to_node": "Span9"
+        },
+        {
+            "from_node": "Span9",
+            "to_node": "Edfa9"
+        },       
+        {
+            "from_node": "Edfa9",
+            "to_node": "Span10"
+        },
+        {
+            "from_node": "Span10",
+            "to_node": "Edfa10"
+        },       
+        {
+            "from_node": "Edfa10",
+            "to_node": "roadm Site D"
+        },
+        {
+            "from_node": "roadm Site D",
+            "to_node": "booster D"
+        },
+        {
+            "from_node": "booster D",
+            "to_node": "Span11"
+        },
+        {
+            "from_node": "Span11",
+            "to_node": "Edfa11"
+        },
+        {
+            "from_node": "Edfa11",
+            "to_node": "Span12"
+        },
+        {
+            "from_node": "Span12",
+            "to_node": "Edfa12"
+        },       
+        {
+            "from_node": "Edfa12",
+            "to_node": "roadm Site E"
+        },
+        {
+            "from_node": "roadm Site E",
+            "to_node": "booster E"
+        },
+        {
+            "from_node": "booster E",
+            "to_node": "Span13"
+        },
+        {
+            "from_node": "Span13",
+            "to_node": "Edfa13"
+        },       
+        {
+            "from_node": "Edfa13",
+            "to_node": "Span14"
+        },
+        {
+            "from_node": "Span14",
+            "to_node": "Edfa14"
+        },       
+        {
+            "from_node": "Edfa14",
+            "to_node": "Span15"
+        },
+        {
+            "from_node": "Span15",
+            "to_node": "Edfa15"
+        },       
+        {
+            "from_node": "Edfa15",
+            "to_node": "roadm Site B"
+        },
+        {
+            "from_node": "roadm Site B",
+            "to_node": "Site_B"
+        }
+    ]
+}

tests/data/test_lumped_losses_fiber_no_pumps.csv

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tests/data/test_lumped_losses_raman_fiber_config.json

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+}

tests/data/test_old_parameters_fiber_config.json

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+}

tests/data/test_parameters_fiber_config.json

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+}

tests/data/test_raman_fiber_expected_results.csv

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tests/data/test_science_utils_fiber_config.json

@@ -0,0 +1,38 @@
+{
+  "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
+  },
+  "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": ""
+    }
+  }
+}

tests/invocation/logs_path_request

@@ -0,0 +1,156 @@
+INFO     gnpy.tools.cli_examples:cli_examples.py Computing path requests meshTopologyExampleV2.xls into JSON format
+WARNING  gnpy.tools.json_io:json_io.py 
+	WARNING missing type_variety attribute in eqpt_config.json[Roadm]
+	default value is type_variety = default
+
+INFO     gnpy.tools.json_io:json_io.py Automatically converting requests from XLS to JSON
+INFO     gnpy.tools.worker_utils:worker_utils.py List of disjunctions:
+[Disjunction 3
+	relaxable:    false
+	link-diverse: True
+	node-diverse: True
+	request-id-numbers: ['3', '1']
+, Disjunction 4
+	relaxable:    false
+	link-diverse: True
+	node-diverse: True
+	request-id-numbers: ['4', '5']
+]
+INFO     gnpy.tools.worker_utils:worker_utils.py Aggregating similar requests
+INFO     gnpy.tools.worker_utils:worker_utils.py The following services have been requested:
+[PathRequest 0
+	source: 	trx Lorient_KMA
+	destination:	trx Vannes_KBE
+	trx type:	Voyager
+	trx mode:	None
+	baud_rate:	None Gbaud
+	bit_rate:	None Gb/s
+	spacing:	50.0 GHz
+	power:  	1.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	80
+	path_bandwidth: 	100.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 1
+	source: 	trx Brest_KLA
+	destination:	trx Vannes_KBE
+	trx type:	Voyager
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	50.0 GHz
+	power:  	1.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	95
+	path_bandwidth: 	200.0 Gbit/s
+	nodes-list:	['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE']
+	loose-list:	['LOOSE', 'LOOSE', 'LOOSE', 'LOOSE']
+, PathRequest 3
+	source: 	trx Lannion_CAS
+	destination:	trx Rennes_STA
+	trx type:	vendorA_trx-type1
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	50.0 GHz
+	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	95
+	path_bandwidth: 	60.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 4
+	source: 	trx Rennes_STA
+	destination:	trx Lannion_CAS
+	trx type:	vendorA_trx-type1
+	trx mode:	None
+	baud_rate:	None Gbaud
+	bit_rate:	None Gb/s
+	spacing:	75.0 GHz
+	power:  	3.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	63
+	path_bandwidth: 	150.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 5
+	source: 	trx Rennes_STA
+	destination:	trx Lannion_CAS
+	trx type:	vendorA_trx-type1
+	trx mode:	mode 2
+	baud_rate:	66.0 Gbaud
+	bit_rate:	200.0 Gb/s
+	spacing:	75.0 GHz
+	power:  	3.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	63
+	path_bandwidth: 	20.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 7 | 6
+	source: 	trx Lannion_CAS
+	destination:	trx Lorient_KMA
+	trx type:	Voyager
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	50.0 GHz
+	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	76
+	path_bandwidth: 	700.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+, PathRequest 7b
+	source: 	trx Lannion_CAS
+	destination:	trx Lorient_KMA
+	trx type:	Voyager
+	trx mode:	mode 1
+	baud_rate:	32.0 Gbaud
+	bit_rate:	100.0 Gb/s
+	spacing:	75.0 GHz
+	power:  	0.0 dBm
+	tx_power_dbm:  	0.0 dBm
+	nb channels: 	50
+	path_bandwidth: 	400.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+]
+INFO     gnpy.tools.worker_utils:worker_utils.py Propagating on selected path
+WARNING  gnpy.topology.request:request.py Redesign the network for each request channel, using the request channel as the reference channel for the design.
+INFO     gnpy.topology.request:request.py 
+	request 0
+	Computing path from trx Lorient_KMA to trx Vannes_KBE
+	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']