Prepare release notes for v2.13

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Iff07dcd6e98b4e4abd79ec8f97d09df2cf2c0e24

.codecov.yml

@@ -1 +1,9 @@
 comment: off
+coverage:
+  status:
+    project:
+      default:
+        threshold: 5%
+    patch:
+      default:
+        only_pulls: true

.docker-entry.sh

@@ -1,3 +1,3 @@
 #!/bin/bash
-cp -nr /opt/application/oopt-gnpy/gnpy/example-data /shared
+cp -nr /oopt-gnpy/gnpy/example-data /shared
 exec "$@"

.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

.dockerignore

@@ -1 +0,0 @@
-venv/

.github/pull_request_template.md

@@ -1,7 +1,7 @@
 # Thanks for contributing to GNPy
 
 If it isn't much trouble, please send your contribution as patches to our Gerrit.
-Here's [how to submit patches](https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html), and here's a [list of stuff we are currently working on](https://review.gerrithub.io/p/Telecominfraproject/oopt-gnpy/+/dashboard/main:main).
+Here's [how to submit patches](https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html), and here's a [list of stuff we are currently working on](https://review.gerrithub.io/q/project:Telecominfraproject/oopt-gnpy+status:open).
 Just sign in via your existing GitHub account.
 
 However, if you feel more comfortable with filing GitHub PRs, we can work with that too.

.github/workflows/main.yml

@@ -0,0 +1,147 @@
+on:
+  push:
+  pull_request:
+    branches:
+      - master
+
+name: CI
+
+jobs:
+  build:
+    name: Tox test
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+      - uses: fedora-python/tox-github-action@v37.0
+        with:
+          tox_env: ${{ matrix.tox_env }}
+          dnf_install: ${{ matrix.dnf_install }}
+      - 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
+          - py310
+          - py311
+          - py312-cover
+        include:
+          - tox_env: docs
+            dnf_install: graphviz
+
+  pypi:
+    needs: build
+    if: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && github.repository_owner == 'Telecominfraproject' }}
+    name: PyPI packaging
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+      - uses: actions/setup-python@v4
+        name: Install Python
+        with:
+          python-version: '3.12'
+      - uses: casperdcl/deploy-pypi@bb869aafd89f657ceaafe9561d3b5584766c0f95
+        with:
+          password: ${{ secrets.PYPI_API_TOKEN }}
+          pip: wheel -w dist/ --no-deps .
+          upload: true
+
+  docker:
+    needs: build
+    if: ${{ github.event_name == 'push' && (github.ref == 'refs/heads/master' || startsWith(github.ref, 'refs/tags/v')) && github.repository_owner == 'Telecominfraproject' }}
+    name: Docker image
+    runs-on: ubuntu-latest
+    steps:
+      - name: Log in to Docker Hub
+        uses: docker/login-action@v1
+        with:
+          username: jktjkt
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+      - name: Extract tag name
+        if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+        id: extract_pretty_git
+        run: echo ::set-output name=GIT_DESC::$(git describe --tags)
+      - name: Build and push a container
+        uses: docker/build-push-action@v2
+        if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
+        with:
+          context: .
+          push: true
+          tags: |
+            telecominfraproject/oopt-gnpy:${{ steps.extract_pretty_git.outputs.GIT_DESC }}
+            telecominfraproject/oopt-gnpy:master
+      - name: Extract tag name
+        if: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') }}
+        id: extract_tag_name
+        run: echo ::set-output name=GIT_DESC::${GITHUB_REF/refs\/tags\//}
+      - name: Build and push a container
+        uses: docker/build-push-action@v2
+        if: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') }}
+        with:
+          context: .
+          push: true
+          tags: |
+            telecominfraproject/oopt-gnpy:${{ steps.extract_tag_name.outputs.GIT_DESC }}
+            telecominfraproject/oopt-gnpy:latest
+
+  other-platforms:
+    name: Tests on other platforms
+    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: windows-2022
+            python_version: "3.11"
+          - os: windows-2022
+            python_version: "3.12"
+          - os: windows-2025
+            python_version: "3.11"
+          - os: windows-2025
+            python_version: "3.12"
+          - os: macos-13
+            python_version: "3.12"
+          - os: macos-14
+            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"

.gitignore

@@ -65,5 +65,3 @@ target/
 
 # MacOS DS_store
 .DS_Store
-
-venv/

.lgtm.yml

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

.readthedocs.yml

@@ -1,4 +1,17 @@
+version: 2
 build:
-    image: latest
+  os: ubuntu-22.04
+  tools:
+    python: "3.12"
+  apt_packages:
+    - graphviz
+
 python:
-    version: 3.6
+  install:
+    - method: pip
+      path: .
+      extra_requirements:
+        - docs
+
+sphinx:
+  configuration: docs/conf.py

.travis.yml

@@ -1,28 +0,0 @@
-dist: focal
-os: linux
-language: python
-services: docker
-python:
-  - "3.6"
-  - "3.7"
-  - "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
-  - 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

@@ -2,24 +2,33 @@
 - project:
     check:
       jobs:
-        - tox-py38-cover
+        - 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-py38-cover-previous
-              - tox-py38-cover
+              - tox-py310-cover-previous
+              - tox-py310-cover
             vars:
-              coverage_job_name_previous: tox-py38-cover-previous
-              coverage_job_name_current: tox-py38-cover
-        - tox-linters-diff:
+              coverage_job_name_previous: tox-py310-cover-previous
+              coverage_job_name_current: tox-py310-cover
+        - tox-linters-diff-n-report:
             voting: false
-        - tox-py36-el8
-        - tox-docs-f32
-        - tox-py38-cover-previous
-    gate:
-      jobs:
-        - tox-py38-f32
-        - tox-docs-f32
+            vars:
+              ensure_tox_version: '<4'
+        - tox-py310-cover-previous:
+            vars:
+              ensure_tox_version: '<4'
     tag:
       jobs:
         - oopt-release-python:

AUTHORS.rst

@@ -7,22 +7,30 @@ To learn how to contribute, please see CONTRIBUTING.md
 
 - Alessio Ferrari (Politecnico di Torino) <alessio.ferrari@polito.it>
 - Anders Lindgren (Telia Company) <Anders.X.Lindgren@teliacompany.com>
-- Andrea D'Amico (Politecnico di Torino) <andrea.damico@polito.it>
+- Andrea D'Amico (NEC) <adamico@nec-labs.com>
+- Arturo Mayoral (Telecom Infra Project) <amayoral@telecominfraproject.com>
 - 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>
+- Florian Frank (Orange) <florian1.frank@orange.com>
 - Gabriele Galimberti (Cisco) <ggalimbe@cisco.com>
 - Gert Grammel (Juniper Networks) <ggrammel@juniper.net>
+- Giacomo Borraccini (NEC Laboratories America) <gborraccini@nec-labs.com>
 - 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>
+- Jenny L'Escop (Orange) <jenny.lescop@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>
+- Renato Ambrosone (Politecnico di Torino) <renato.ambrosone@polito.it>
 - Roberts Miculens (Lattelecom) <roberts.miculens@lattelecom.lv>
+- Rodrigo Sasse David (Orange) <rodrigo.sassedavid@orange.com>
+- 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>

Dockerfile

@@ -1,18 +1,8 @@
-FROM python:3.7-slim
-WORKDIR /opt/application/oopt-gnpy
-RUN mkdir -p /shared/example-data \
-    && groupadd gnpy \
-    && useradd -u 1000 -g gnpy -m gnpy \
-    && apt-get update \
-    && apt-get install git -y \
-    && rm -rf /var/lib/apt/lists/*
-COPY . /opt/application/oopt-gnpy
-WORKDIR /opt/application/oopt-gnpy
-RUN mkdir topology \
-    && mkdir equipment \
-    && mkdir autodesign \
-    && pip install . \
-    && chown -Rc gnpy:gnpy /opt/application/oopt-gnpy /shared/example-data
-USER gnpy
-ENTRYPOINT ["/opt/application/oopt-gnpy/.docker-entry.sh"]
+FROM python:3.9-slim
+COPY . /oopt-gnpy
+WORKDIR /oopt-gnpy
+RUN apt update; apt install -y git
+RUN pip install .
+WORKDIR /shared/example-data
+ENTRYPOINT ["/oopt-gnpy/.docker-entry.sh"]
 CMD ["/bin/bash"]

README.md

@@ -0,0 +1,35 @@
+# GNPy: Optical Route Planning and DWDM Network Optimization
+
+[![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/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 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.
+Together, we are building this tool for rapid development of production-grade route planning tools which is easily extensible to include custom network elements and performant to the scale of real-world mesh optical networks.
+
+![GNPy with an OLS system](docs/images/GNPy-banner.png)
+
+## Quick Start
+
+Install either via [Docker](https://gnpy.readthedocs.io/en/master/install.html#using-prebuilt-docker-images), or as a [Python package](https://gnpy.readthedocs.io/en/master/install.html#using-python-on-your-computer).
+Read our [documentation](https://gnpy.readthedocs.io/), learn from the demos, and [get in touch with us](https://github.com/Telecominfraproject/oopt-gnpy/discussions).
+
+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](docs/images/gnpy-transmission-example.svg)
+
+GNPy can do much more, including acting as a Path Computation Engine, tracking bandwidth requests, or advising the SDN controller about a best possible path through a large DWDM network.
+Learn more about this [in the documentation](https://gnpy.readthedocs.io/), or give it a [try online at `gnpy.app`](https://gnpy.app/):
+
+[![Path propagation at gnpy.app](docs/images/2022-04-12-gnpy-app.png)](https://gnpy.app/)
+
+## Project Calendar
+
+See upcoming meetings on the [Project Calendar](https://telecominfraproject.github.io/oopt-gnpy/calendar.html). The calendar is embedded from Google Calendar and updates automatically.

README.rst

@@ -1,278 +0,0 @@
-.. image:: docs/images/GNPy-banner.png
-   :width: 100%
-   :align: left
-   :alt: GNPy with an OLS system
-
-====================================================================
-`gnpy`: mesh optical network route planning and optimization library
-====================================================================
-
-|pypi| |docs| |travis| |doi| |contributors| |codacy-quality| |codecov|
-
-**`gnpy` is an open-source, community-developed library for building route
-planning and optimization tools in real-world mesh optical networks.**
-
-`gnpy <http://github.com/telecominfraproject/oopt-gnpy>`__ is:
---------------------------------------------------------------
-
-- a sponsored project of the `OOPT/PSE <https://telecominfraproject.com/open-optical-packet-transport/>`_ working group of the `Telecom Infra Project <http://telecominfraproject.com>`_
-- fully community-driven, fully open source library
-- driven by a consortium of operators, vendors, and academic researchers
-- intended for rapid development of production-grade route planning tools
-- easily extensible to include custom network elements
-- performant to the scale of real-world mesh optical networks
-
-Documentation: https://gnpy.readthedocs.io
-
-Get In Touch
-~~~~~~~~~~~~
-
-There are `weekly calls <https://telecominfraproject.workplace.com/events/702894886867547/>`__ 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/>`__.
-
-How to Install
---------------
-
-Install either via `Docker <docs/install.rst#install-docker>`__, or as a `Python package <docs/install.rst#install-pip>`__.
-
-Instructions for First Use
---------------------------
-
-``gnpy`` is a library for building route planning and optimization tools.
-
-It ships with a number of example programs. Release versions will ship with
-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
-    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:
-
-.. image:: https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg
-   :width: 100%
-   :align: left
-   :alt: Running a simple simulation example
-   :target: https://asciinema.org/a/252295
-
-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>`_
-
-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>`_:
-
-.. 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>`_).
-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>`__.
-
-The main transmission example will calculate the average signal OSNR and SNR
-across network elements (transceiver, ROADMs, fibers, and amplifiers)
-between two transceivers selected by the user. Additional details are provided by doing ``gnpy-transmission-example -h``. (By default, for the CORONET Global
-network, it will show the transmission of spectral information between Abilene and Albany)
-
-This script calculates the average signal OSNR = |OSNR| and SNR = |SNR|.
-
-.. |OSNR| replace:: P\ :sub:`ch`\ /P\ :sub:`ase`
-.. |SNR| replace:: P\ :sub:`ch`\ /(P\ :sub:`nli`\ +\ P\ :sub:`ase`)
-
-|Pase| is the amplified spontaneous emission noise, and |Pnli| the non-linear
-interference noise.
-
-.. |Pase| replace:: P\ :sub:`ase`
-.. |Pnli| replace:: P\ :sub:`nli`
-
-Further Instructions for Use
-----------------------------
-
-Simulations are driven by a set of `JSON <docs/json.rst>`__ or `XLS <docs/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.
-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.
-
-An experimental support for Raman amplification is available:
-
-.. code-block:: shell-session
-
-     $ gnpy-transmission-example \
-       $(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 simulaiton 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:
-
-.. code-block:: shell-session
-
-     $ cd $(gnpy-example-data)
-     $ 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).
-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`.
-
-Important note: ``gnpy-path-request`` is not a network dimensionning tool: each service does not reserve spectrum, or occupy ressources such as transponders. It only computes path feasibility assuming the spectrum (between defined frequencies) is loaded with "nb of channels" spaced by "spacing" values as specified in the system parameters input in the service file, each cannel having the same characteristics in terms of baudrate, format,... as the service transponder. The transceiver element acts as a "logical starting/stopping point" for the spectral information propagation. At that point it is not meant to represent the capacity of add drop ports.
-As a result transponder type is not part of the network info. it is related to the list of services requests.
-
-The current version includes a spectrum assigment features that enables to compute a candidate spectrum assignment for each service based on a first fit policy. Spectrum is assigned based on service specified spacing value, path_bandwidth value and selected mode for the transceiver. This spectrum assignment includes a basic capacity planning capability so that the spectrum resource is limited by the frequency min and max values defined for the links. If the requested services reach the link spectrum capacity, additional services feasibility are computed but marked as blocked due to spectrum reason.
-
-REST API (experimental)
------------------------
-``gnpy`` provides an experimental api for requesting several paths at once. It is based on Flask server.
-You can run it through command line or Docker.
-
-.. code-block:: shell-session
-
-     $ gnpy-rest
-
-.. code-block:: shell-session
-
-    $ docker run -p 8080:8080 -it emmanuelledelfour/gnpy-experimental:candi-1.1 gnpy-rest
-
-When starting the api server will aks for an encryption/decryption key. This key i used to encrypt equipment file when using /api/v1/equipments endpoint.
-This key is a Fernet key and can be generated this way:
-
-.. code-block:: python
-
-from cryptography.fernet import Fernet
-Fernet.generate_key()
-
-
-After typing the key, you can detach the container by typing ^P^Q.
-After starting the api server, you can launch a request
-
-.. code-block:: shell-session
-
-    $ curl -v -X POST -H "Content-Type: application/json" -d @<PATH_TO_JSON_REQUEST_FILE> https://localhost:8080/api/v1/path-computation -k
-
-TODO: api documentation, unit tests, real WSGI server with trusted certificates
-
-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
-<jan.kundrat@telecominfraproject.com> or Gert Grammel <ggrammel@juniper.net>.
-
-``gnpy`` contributions are currently limited to members of `TIP
-<http://telecominfraproject.com>`_. Membership is free and open to all.
-
-See the `Onboarding Guide
-<https://github.com/Telecominfraproject/gnpy/wiki/Onboarding-Guide>`_ for
-specific details on code contributions, or just `upload patches to our Gerrit
-<https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html>`_.
-
-See `AUTHORS.rst <AUTHORS.rst>`_ for past and present contributors.
-
-Project Background
-------------------
-
-Data Centers are built upon interchangeable, highly standardized node and
-network architectures rather than a sum of isolated solutions. This also
-translates to optical networking. It leads to a push in enabling multi-vendor
-optical network by disaggregating HW and SW functions and focusing on
-interoperability. In this paradigm, the burden of responsibility for ensuring
-the performance of such disaggregated open optical systems falls on the
-operators. Consequently, operators and vendors are collaborating in defining
-control models that can be readily used by off-the-shelf controllers. However,
-node and network models are only part of the answer. To take reasonable
-decisions, controllers need to incorporate logic to simulate and assess optical
-performance. Hence, a vendor-independent optical quality estimator is required.
-Given its vendor-agnostic nature, such an estimator needs to be driven by a
-consortium of operators, system and component suppliers.
-
-Founded in February 2016, the Telecom Infra Project (TIP) is an
-engineering-focused initiative which is operator driven, but features
-collaboration across operators, suppliers, developers, integrators, and
-startups with the goal of disaggregating the traditional network deployment
-approach. The group’s ultimate goal is to help provide better connectivity for
-communities all over the world as more people come on-line and demand more
-bandwidth- intensive experiences like video, virtual reality and augmented
-reality.
-
-Within TIP, the Open Optical Packet Transport (OOPT) project group is chartered
-with unbundling monolithic packet-optical network technologies in order to
-unlock innovation and support new, more flexible connectivity paradigms.
-
-The key to unbundling is the ability to accurately plan and predict the
-performance of optical line systems based on an accurate simulation of optical
-parameters. Under that OOPT umbrella, the Physical Simulation Environment (PSE)
-working group set out to disrupt the planning landscape by providing an open
-source simulation model which can be used freely across multiple vendor
-implementations.
-
-.. |docs| image:: https://readthedocs.org/projects/gnpy/badge/?version=master
-  :target: http://gnpy.readthedocs.io/en/master/?badge=master
-  :alt: Documentation Status
-  :scale: 100%
-
-.. |travis| image:: https://travis-ci.com/Telecominfraproject/oopt-gnpy.svg?branch=master
-  :target: https://travis-ci.com/Telecominfraproject/oopt-gnpy
-  :alt: Build Status via Travis CI
-  :scale: 100%
-
-.. |doi| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3458319.svg
-  :target: https://doi.org/10.5281/zenodo.3458319
-  :alt: DOI
-  :scale: 100%
-
-.. |contributors| image:: https://img.shields.io/github/contributors-anon/Telecominfraproject/oopt-gnpy
-  :target: https://github.com/Telecominfraproject/oopt-gnpy/graphs/contributors
-  :alt: Code Contributors via GitHub
-  :scale: 100%
-
-.. |codacy-quality| image:: https://img.shields.io/lgtm/grade/python/github/Telecominfraproject/oopt-gnpy
-  :target: https://lgtm.com/projects/g/Telecominfraproject/oopt-gnpy/
-  :alt: Code Quality via LGTM.com
-  :scale: 100%
-
-.. |codecov| image:: https://img.shields.io/codecov/c/github/Telecominfraproject/oopt-gnpy
-  :target: https://codecov.io/gh/Telecominfraproject/oopt-gnpy
-  :alt: Code Coverage via codecov
-  :scale: 100%
-
-.. |pypi| image:: https://img.shields.io/pypi/v/gnpy
-  :target: https://pypi.org/project/gnpy/
-  :alt: Install via PyPI
-  :scale: 100%
-
-
-TIP OOPT/PSE & PSE WG Charter
------------------------------
-
-We believe that openly sharing ideas, specifications, and other intellectual
-property is the key to maximizing innovation and reducing complexity
-
-TIP OOPT/PSE's goal is to build an end-to-end simulation environment which
-defines the network models of the optical device transfer functions and their
-parameters.  This environment will provide validation of the optical
-performance requirements for the TIP OLS building blocks.
-
-- The model may be approximate or complete depending on the network complexity.
-  Each model shall be validated against the proposed network scenario.
-- The environment must be able to process network models from multiple vendors,
-  and also allow users to pick any implementation in an open source framework.
-- The PSE will influence and benefit from the innovation of the DTC, API, and
-  OLS working groups.
-- The PSE represents a step along the journey towards multi-layer optimization.
-
-License
--------
-
-``gnpy`` is distributed under a standard BSD 3-Clause License.
-
-See `LICENSE <LICENSE>`__ for more details.

docs/_static/custom.css

@@ -0,0 +1,4 @@
+
+.wy-table-responsive table td, .wy-table-responsive table th {
+  white-space: normal;
+}

docs/about-project.md

@@ -0,0 +1,60 @@
+(about-gnpy)=
+# About the project
+
+GNPy is a sponsored project of the [OOPT/PSE](https://telecominfraproject.com/open-optical-packet-transport/) working group of the [Telecom Infra Project](http://telecominfraproject.com).
+
+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 [Esther Le Rouzic](mailto:esther.lerouzic@orange.com) or
+[Andrea d'Amico](mailto:adamico@nec-labs.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.
+
+See the [Onboarding Guide](https://github.com/Telecominfraproject/gnpy/wiki/Onboarding-Guide) for specific details on code contributions, or just [upload patches to our Gerrit](https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html).
+Here is [what we are currently working on](https://review.gerrithub.io/q/project:Telecominfraproject/oopt-gnpy+status:open).
+
+## Project Background
+
+Data Centers are built upon interchangeable, highly standardized node and network architectures rather than a sum of isolated solutions.
+This also translates to optical networking.
+It leads to a push in enabling multi-vendor optical network by disaggregating HW and SW functions and focusing on interoperability.
+In this paradigm, the burden of responsibility for ensuring the performance of such disaggregated open optical systems falls on the operators.
+Consequently, operators and vendors are collaborating in defining control models that can be readily used by off-the-shelf controllers.
+However, node and network models are only part of the answer.
+To take reasonable decisions, controllers need to incorporate logic to simulate and assess optical performance.
+Hence, a vendor-independent optical quality estimator is required.
+Given its vendor-agnostic nature, such an estimator needs to be driven by a consortium of operators, system and component suppliers.
+
+Founded in February 2016, the Telecom Infra Project (TIP) is an engineering-focused initiative which is operator driven, but features collaboration across operators, suppliers, developers, integrators, and startups with the goal of disaggregating the traditional network deployment approach.
+The group’s ultimate goal is to help provide better connectivity for communities all over the world as more people come on-line and demand more bandwidth-intensive experiences like video, virtual reality and augmented reality.
+
+Within TIP, the Open Optical Packet Transport (OOPT) project group is chartered with unbundling monolithic packet-optical network technologies in order to unlock innovation and support new, more flexible connectivity paradigms.
+
+The key to unbundling is the ability to accurately plan and predict the performance of optical line systems based on an accurate simulation of optical parameters.
+Under that OOPT umbrella, the Physical Simulation Environment (PSE) working group set out to disrupt the planning landscape by providing an open source simulation model which can be used freely across multiple vendor implementations.
+
+## TIP OOPT/PSE & PSE WG Charter
+
+We believe that openly sharing ideas, specifications, and other intellectual property is the key to maximizing innovation and reducing complexity
+
+TIP OOPT/PSE's goal is to build an end-to-end simulation environment which defines the network models of the optical device transfer functions and their parameters.
+This environment will provide validation of the optical performance requirements for the TIP OLS building blocks.
+
+- The model may be approximate or complete depending on the network complexity.
+Each model shall be validated against the proposed network scenario.
+- The environment must be able to process network models from multiple vendors, and also allow users to pick any implementation in an open source framework.
+- The PSE will influence and benefit from the innovation of the DTC, API, and OLS working groups.
+- The PSE represents a step along the journey towards multi-layer optimization.
+
+License
+-------
+
+GNPy is distributed under a standard BSD 3-Clause License.

docs/amplifier_models_description.rst

@@ -1,18 +1,20 @@
-*********************************************
-Amplifier models and configuration
-*********************************************
+.. _amp_models:
+
+**********************************
+Amplifier models and Configuration
+**********************************
 
 
 1. Equipment configuration description
-#######################################
+======================================
 
 Equipment description defines equipment types and parameters.
-It takes place in the default **eqpt_config.json** file. 
+It takes place in the equipment library such as **eqpt_config.json** file defined in example-data folder.
 By default **gnpy-transmission-example** uses **eqpt_config.json** file and that
 can be changed with **-e** or **--equipment** command line parameter.
 
 2. Amplifier parameters and subtypes
-#######################################
+====================================
 
 Several amplifiers can be used by GNpy, so they are defined as an array of equipment parameters in **eqpt_config.json** file.
 
@@ -28,9 +30,16 @@ Several amplifiers can be used by GNpy, so they are defined as an array of equip
     - *"variable_gain"*
     - *"fixed_gain"*
     - *"dual_stage"*
+    - *"multi_band"*
     - *"openroadm"*
         *see next section for a full description of these models*
 
+
+- *"default_config_from_json"*:
+    Use a custom per frequency dynamic gain tilt, gain and noise ripple arrays defined in the file specified with
+    this option, instead of the default values from GNPy.
+
+
 - *"advanced_config_from_json"*:
     **This parameter is only applicable to the _"advanced_model"_ model**
     
@@ -135,7 +144,7 @@ Several amplifiers can be used by GNpy, so they are defined as an array of equip
 
 
 3. Amplifier models
-#######################################
+===================
 
 In an opensource and multi-vendor environnement, it is needed to support different use cases and context. Therefore several models are supported for amplifiers.
 
@@ -179,7 +188,7 @@ In an opensource and multi-vendor environnement, it is needed to support differe
 - *"variable_gain"* 
     This model is refered as an operator model because a lower level of knowledge is required. A full polynomial description of the NF cross the gain range is not required. Instead, NF_min and NF_max values are required and used by the code to model a dual stage amplifier with an internal mid stage VOA. NF_min and NF_max values are typically available from equipment suppliers data-sheet.
 
-    There is a default JSON file ”default_edfa_config.json”* to enforce 0 tilt and ripple values because GNpy core algorithm is a multi-carrier propogation.
+    There is a default configuration to enforce 0 tilt and ripple values because GNPy core algorithm is a multi-carrier propagation.
     - gain_ripple =[0,...,0]
     - nf_ripple = [0,...,0]
     - dgt = [...] generic dgt comb
@@ -227,7 +236,7 @@ In an opensource and multi-vendor environnement, it is needed to support differe
     .. code-block:: json-object
 
         "Edfa":[{
-                "type_variety": "low_noise",
+                "type_variety": "openroadm_ila_low_noise",
                 "type_def": "openroadm",
                 "gain_flatmax": 27,
                 "gain_min": 12,
@@ -250,7 +259,7 @@ In an opensource and multi-vendor environnement, it is needed to support differe
     
     - gain_min indicates to auto_design when this dual_stage should be used
     
-    But unlike other models the 1st stage input will not be padded: it is always operated to its maximu gain and min NF. Therefore if gain adaptation and padding is needed it will be performed by the 2nd stage.
+    But unlike other models the 1st stage input will not be padded: it is always operated to its maximum gain and min NF. Therefore if gain adaptation and padding is needed it will be performed by the 2nd stage.
 
     .. code-block:: json
 
@@ -263,8 +272,18 @@ In an opensource and multi-vendor environnement, it is needed to support differe
                 "allowed_for_design": true
                 }
 
+
+- *"multiband"*
+    This model enables the definition of multiband amplifiers that consist of multiple single-band
+    amplifier elements, with each amplifier responsible for amplifying a different portion of the spectrum.
+    The types of single-band amplifiers that can be included in these multiband amplifiers are specified,
+    allowing for multiple options to be available for the same spectrum band (for instance, providing
+    several permitted type varieties for both the C-band and the L-band). The actual element utilizing the
+    type_variety must implement only one option for each band.
+
+
 4. advanced_config_from_json 
-#######################################
+============================
 
 The build_oa_json.py library in ``gnpy/example-data/edfa_model/`` can be used to build the json file required for the amplifier advanced_model type_def:
 
@@ -297,4 +316,3 @@ the json input file should have the following fields:
             "gain_ripple": "DFG_filename.txt",
             "dgt": "DGT_filename.txt"
         }
-

docs/biblio.bib

@@ -1848,3 +1848,177 @@ 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}
+}
+
+@inproceedings{grammel2018physical,
+  title={Physical simulation environment of the telecommunications infrastructure project (TIP)},
+  author={Grammel, Gert and Curri, Vittorio and Auge, Jean-Luc},
+  booktitle={Optical Fiber Communication Conference},
+  pages={M1D--3},
+  year={2018},
+  organization={Optica Publishing Group}
+}
+
+@inproceedings{taylor2018towards,
+  title={Towards a route planning tool for open optical networks in the telecom infrastructure project},
+  author={Taylor, Brian D and Goldfarb, Gilad and Bandyopadhyay, Saumil and Curri, Vittorio and Schmidtke, Hans-Juergen},
+  booktitle={Optical Fiber Communication Conference},
+  pages={Tu3E--4},
+  year={2018},
+  organization={Optica Publishing Group}
+}
+
+@article{filer2018multi,
+  title={Multi-vendor experimental validation of an open source QoT estimator for optical networks},
+  author={Filer, Mark and Cantono, Mattia and Ferrari, Alessio and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
+  journal={Journal of Lightwave Technology},
+  volume={36},
+  number={15},
+  pages={3073--3082},
+  year={2018},
+  publisher={IEEE}
+}
+
+@inproceedings{auge2019open,
+  title={Open optical network planning demonstration},
+  author={Auge, Jean-Luc and Grammel, Gert and Le Rouzic, Esther and Curri, Vittorio and Galimberti, Gabriele and Powell, James},
+  booktitle={Optical Fiber Communication Conference},
+  pages={M3Z--9},
+  year={2019},
+  organization={Optica Publishing Group}
+}
+
+@inproceedings{kundrat2020physical,
+  title={Physical-layer awareness: GNPy and ONOS for end-to-end circuits in disaggregated networks},
+  author={Kundr{\'a}t, Jan and Campanella, Andrea and Le Rouzic, Esther and Ferrari, Alessio and Havli{\v{s}}, Ond{\v{r}}ej and Ha{\v{z}}linsk{\`y}, Michal and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
+  booktitle={2020 Optical Fiber Communications Conference and Exhibition (OFC)},
+  pages={1--3},
+  year={2020},
+  organization={IEEE}
+}
+
+@inproceedings{ferrari2020experimental,
+  title={Experimental validation of an open source quality of transmission estimator for open optical networks},
+  author={Ferrari, Alessio and Filer, Mark and Balasubramanian, Karthikeyan and Yin, Yawei and Le Rouzic, Esther and Kundr{\'a}t, Jan and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
+  booktitle={2020 Optical Fiber Communications Conference and Exhibition (OFC)},
+  pages={1--3},
+  year={2020},
+  organization={IEEE}
+}
+
+@article{ferrari2020gnpy,
+  title={GNPy: an open source application for physical layer aware open optical networks},
+  author={Ferrari, Alessio and Filer, Mark and Balasubramanian, Karthikeyan and Yin, Yawei and Le Rouzic, Esther and Kundr{\'a}t, Jan and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
+  journal={Journal of Optical Communications and Networking},
+  volume={12},
+  number={6},
+  pages={C31--C40},
+  year={2020},
+  publisher={Optica Publishing Group}
+}
+
+@inproceedings{ferrari2020softwarized,
+  title={Softwarized optical transport QoT in production optical network: a Brownfield validation},
+  author={Ferrari, Alessio and Balasubramanian, Karthikeyan and Filer, Mark and Yin, Yawei and Le Rouzic, Esther and Kundr{\'a}t, Jan and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
+  booktitle={2020 European Conference on Optical Communications (ECOC)},
+  pages={1--4},
+  year={2020},
+  organization={IEEE}
+}
+
+@article{ferrari2021assessment,
+  title={Assessment on the in-field lightpath QoT computation including connector loss uncertainties},
+  author={Ferrari, Alessio and Balasubramanian, Karthikeyan and Filer, Mark and Yin, Yawei and Le Rouzic, Esther and Kundr{\'a}t, Jan and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
+  journal={Journal of Optical Communications and Networking},
+  volume={13},
+  number={2},
+  pages={A156--A164},
+  year={2021},
+  publisher={Optica Publishing Group}
+}
+
+@inproceedings{kundrat2021gnpy,
+  title={GNPy \& YANG: open APIs for end-to-end service provisioning in optical networks},
+  author={Kundr{\'a}t, Jan and Le Rouzic, Esther and M{\aa}rtensson, Jonas and Campanella, Andrea and Havli{\v{s}}, Ond{\v{r}}ej and D’Amico, Andrea and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio and Vojt{\v{e}}ch, Josef},
+  booktitle={Optical Fiber Communication Conference},
+  pages={M1B--6},
+  year={2021},
+  organization={Optica Publishing Group}
+}
+
+@inproceedings{d2021gnpy,
+  title={GNPy experimental validation on flex-grid, flex-rate WDM optical transport scenarios},
+  author={D’Amico, Andrea and London, Elliot and Le Guyader, Bertrand and Frank, Florian and Le Rouzic, Esther and Pincemin, Erwan and Brochier, Nicolas and Curri, Vittorio},
+  booktitle={Optical fiber communication conference},
+  pages={W1G--2},
+  year={2021},
+  organization={Optica Publishing Group}
+}
+
+@inproceedings{virgillito2021testing,
+  title={Testing TIP open source solutions in deployed optical networks},
+  author={Virgillito, Emanuele and Braun, Ralf-Peter and Breuer, Dirk and Gladisch, Andreas and Curri, Vittorio and Grammel, Gert},
+  booktitle={Optical Fiber Communication Conference},
+  pages={F1C--3},
+  year={2021},
+  organization={Optica Publishing Group}
+}
+
+@article{d2022experimental,
+  title={Experimental validation of GNPy in a multi-vendor flex-grid flex-rate WDM optical transport scenario},
+  author={D’Amico, Andrea and London, Elliot and Le Guyader, Bertrand and Frank, Florian and Le Rouzic, Esther and Pincemin, Erwan and Brochier, Nicolas and Curri, Vittorio},
+  journal={Journal of Optical Communications and Networking},
+  volume={14},
+  number={3},
+  pages={79--88},
+  year={2022},
+  publisher={Optica Publishing Group}
+}
+
+@inproceedings{mano2022accuracy,
+  title={Accuracy of nonlinear interference estimation on launch power optimization in short-reach systems with field trial},
+  author={Mano, Toru and D’Amico, Andrea and Virgillito, Emanuele and Borraccini, Giacomo and Huang, Yue-Kai and Kitamura, Kei and Anazawa, Kazuya and Masuda, Akira and Nishizawa, Hideki and Wang, Ting and others},
+  booktitle={European Conference and Exhibition on Optical Communication},
+  pages={We3B--1},
+  year={2022},
+  organization={Optica Publishing Group}
+}
+
+@inproceedings{kundrat2022gnpy,
+  title={GNPy: Lessons learned and future plans},
+  author={Kundr{\'a}t, Jan and Le Rouzic, Esther and M{\aa}rtensson, Jonas and Melin, Stefan and D’Amico, Andrea and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
+  booktitle={European Conference and Exhibition on Optical Communication},
+  pages={We3B--6},
+  year={2022},
+  organization={Optica Publishing Group}
+}
+
+@inproceedings{grammel2023open,
+  title={Open Optical Networks: the good, the bad and the ugly},
+  author={Grammel, Gert and Kundrat, Jan and Le Rouzic, Esther and Melin, Stefan and Curri, Vittorio and d'Amico, Andrea and Manzotti, Roberto},
+  booktitle={49th European Conference on Optical Communications (ECOC 2023)},
+  volume={2023},
+  pages={1585--1588},
+  year={2023},
+  organization={IET}
+}
+
+@inproceedings{d2024gnpy,
+  title={GNPy Experimental Validation in a C+ L Multiband Optical Multiplex Section},
+  author={D’Amico, Andrea and Gatto, Vittorio and Nespola, Antonino and Borraccini, Giacomo and Jiang, Yanchao and Poggiolini, Pierluigi and Le Rouzic, Esther and de Lerma, Arturo Mayoral L{\'o}pez and Grammel, Gert and Manzotti, Roberto and others},
+  booktitle={2024 24th International Conference on Transparent Optical Networks (ICTON)},
+  pages={1--4},
+  year={2024},
+  organization={IEEE}
+}

docs/calendar.html

@@ -0,0 +1,29 @@
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="utf-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1" />
+    <title>Project Calendar</title>
+    <style>
+      body { font-family: system-ui, -apple-system, Segoe UI, Roboto, Helvetica, Arial, sans-serif; margin: 20px; }
+      .container { max-width: 1000px; margin: 0 auto; }
+      h1 { font-size: 1.8rem; margin-bottom: 1rem; }
+      iframe { border: 0; width: 100%; height: 800px; }
+      .note { color: #555; margin-top: 1rem; font-size: 0.9rem; }
+    </style>
+  </head>
+  <body>
+    <div class="container">
+      <h1>Project Calendar</h1>
+      <p>This page embeds the public project calendar. It updates automatically when events change in Google Calendar.</p>
+      <iframe
+        src="https://calendar.google.com/calendar/embed?src=c_0895d13d880537c3e54db61ba95e9df167db19a49b96d41e42e2c6d842f30a6a%40group.calendar.google.com&ctz=Europe%2FMadrid"
+        frameborder="0"
+        scrolling="no"
+      ></iframe>
+      <p class="note">Timezone: Europe/Madrid. If you prefer your local timezone, add <code>&amp;ctz=Your%2FTimezone</code> to the URL.</p>
+    </div>
+  </body>
+  </html>
+
+

docs/cli_options.rst

@@ -0,0 +1,297 @@
+.. _cli-options:
+
+***********************************************************
+`gnpy-path-request` and `gnpy-transmission-example` scripts
+***********************************************************
+
+Common options
+==============
+
+**Option**: `--no-insert-edfas`
+-------------------------------
+
+**Purpose**: Disables the automatic insertion of EDFAs after ROADMs and fibers, as well as the splitting
+of fibers during the auto-design process.
+
+The `--no-insert-edfas` option is a command-line argument available in GNPy that allows users to control the
+automatic insertion of amplifiers during the network design process. This option provides flexibility for
+users who may want to manually manage amplifier placements or who have specific design requirements that
+do not necessitate automatic amplification.
+
+To use the `--no-insert-edfas` option, simply include it in the command line when running your GNPy program. For example:
+
+.. code-block:: shell-session
+
+  gnpy-transmission-example my_network.json --no-insert-edfas
+
+When the `--no-insert-edfas` option is specified:
+
+1. **No Automatic Amplifiers**: The program will not automatically add EDFAs to the network topology after
+   ROADMs or fiber elements. This means that if the network design requires amplification, users must ensure
+   that amplifiers are manually defined in the network topology file. Users should be aware that disabling
+   automatic amplifier insertion may lead to insufficient amplification in the network if not managed properly.
+   It is essential to ensure that the network topology includes the necessary amplifiers to meet performance requirements.
+
+2. **No Fiber Splitting**: The option also prevents the automatic splitting of fibers during the design process.
+   This is particularly useful for users who want to maintain specific fiber lengths or configurations without
+   the program altering them.
+
+
+**Option**: `--equipment`, `-e`
+-------------------------------
+
+**Description**: Specifies the equipment library file.
+
+**Usage**: 
+
+.. code-block:: shell-session
+
+  gnpy-transmission-example my_network.json --equipment <FILE.json>
+
+**Default**: Uses the default equipment configuration in the example-data folder if not specified.
+
+**Functionality**: This option allows users to load a specific equipment configuration that defines the characteristics of the network elements.
+
+**Option**: `--extra-equipment` and `--extra-config`
+----------------------------------------------------
+
+The `--extra-equipment` and `--extra-config` options allow users to extend the default equipment library and configuration
+settings used by the GNPy program. This feature is particularly useful for users who need to incorporate additional
+equipment types or specific configurations that are not included in the standard equipment library (such as third party pluggables).
+
+**Usage**:
+  
+.. code-block:: shell-session
+
+  --extra-equipment <file1.json> [<file2.json> ...]
+
+**Parameters**:
+
+  - `<file1.json>`: Path to the first additional equipment file.
+  - `<file2.json>`: Path to any subsequent additional equipment files (optional).
+
+**Functionality**:
+
+  - The program will merge the equipment definitions from the specified files into the main equipment library.
+  - If an equipment type defined in the additional files has the same name as one in the main library, the program
+    will issue a warning about the duplicate entry and will include ony the last definition.
+  - This allows for flexibility in defining equipment that may be specific to certain use cases or vendor-specific models.
+
+**`--extra-config`**:
+
+**Description**: This option allows users to specify additional configuration files that can override
+  or extend the default configuration settings used by the program. This is useful for customizing simulation
+  parameters or equipment settings. To set an amplifier with a specific such config, it must be defined in the
+  library with the keyword "default_config_from_json" filled with the file name containing the config in the case of
+  "variable_gain" amplifier or with the "advanced_config_from_json" for the "advanced_model" amplifier.
+
+**Usage**:
+  
+.. code-block:: shell-session
+
+  --extra-config <file1.json> [<file2.json> ...]
+
+**Parameters**:
+  - `<file1.json>`: Path to the first additional configuration file.
+  - `<file2.json>`: Path to any subsequent additional configuration files (optional).
+
+**Functionality**:
+  The program will load the configurations from the specified files and consider them instead of the
+  default configurations for the amplifiers that use the "default_config_from_json" or "advanced_config_from_json" keywords.
+
+To run the program with additional equipment and configuration files, you can use the following command:
+
+.. code-block:: shell-session
+
+gnpy-transmission-example --equipment main_equipment.json \
+                          --extra-equipment additional_equipment1.json additional_equipment2.json \
+                          --extra-config additional_config1.json
+
+
+In this example:
+- `main_equipment.json` is the primary equipment file.
+- `additional_equipment1.json` and `additional_equipment2.json` are additional equipment files that will be merged into the main library.
+- `additional_config1.json` is an additional configuration file that will override the default settings for the amplifiers pointing to it.
+
+
+**Option**: `--save-network`
+----------------------------
+
+**Description**: Saves the final network configuration to a specified JSON file.
+
+**Usage**:
+
+.. code-block:: shell-session
+
+  --save-network <FILE.json>
+
+**Functionality**: This option allows users to save the network state after the simulation, which can be useful for future reference or analysis.
+
+
+**Option**: `--save-network-before-autodesign`
+----------------------------------------------
+
+**Description**: Dumps the network into a JSON file prior to autodesign.
+
+**Usage**:
+
+.. code-block:: shell-session
+
+  gnpy-path-request my_network.json my_services.json --save-network-before-autodesign <FILE.json>
+
+**Functionality**: This option is useful for users who want to inspect the network configuration before any automatic design adjustments are made.
+
+
+**Option**: `--sim-params`
+--------------------------
+
+**Description**: Path to the JSON file containing simulation parameters.
+
+**Usage**:
+
+.. code-block:: shell-session
+
+  gnpy-transmission-example my_network.json --sim-params <FILE.json>
+
+**Functionality**: The `--sim-params` option is a command-line argument available in GNPy that allows users to specify a
+JSON file containing simulation parameters. This option is crucial for customizing the behavior of the simulation:
+the file ``sim_params.json`` contains the tuning parameters used within both the ``gnpy.science_utils.RamanSolver`` and
+the ``gnpy.science_utils.NliSolver`` for the evaluation of the Raman profile and the NLI generation, respectively.
+
+The tuning of the parameters is detailed here: :ref:`json input sim-params<sim-params>`.
+
+
+`gnpy-transmission-example` options
+===================================
+
+**Option**: `--show-channels`
+-----------------------------
+
+**Description**: Displays the final per-channel OSNR and GSNR summary.
+
+**Usage**: 
+
+.. code-block:: shell-session
+
+  gnpy-transmission-example my_network.json --show-channels
+
+**Functionality**: This option provides a summary of the optical signal-to-noise ratio (OSNR)
+and generalized signal-to-noise ratio (GSNR) for each channel after the simulation.
+
+
+**Option**: `-pl`, `--plot`
+---------------------------
+
+**Description**: Generates plots of the results.
+
+**Usage**: 
+
+.. code-block:: shell-session
+
+  gnpy-transmission-example my_network.json -pl
+  
+**Functionality**: This option allows users to visualize the results of the simulation through graphical plots.
+
+
+**Option**: `-l`, `--list-nodes`
+--------------------------------
+
+**Description**: Lists all transceiver nodes in the network.
+
+**Usage**: 
+
+.. code-block:: shell-session
+
+  gnpy-transmission-example my_network.json -l
+
+**Functionality**: This option provides a quick way to view all transceiver nodes present in the network topology.
+
+**Option**: `-po`, `--power`
+----------------------------
+
+**Description**: Specifies the reference channel power in span in dBm.
+
+**Usage**:
+
+.. code-block:: shell-session
+
+  gnpy-transmission-example my_network.json -po <value>
+
+**Functionality**: This option allows users to set the input power level for the reference channel used in the simulation.
+It replaces the value specified in the `SI` section of the equipment library (:ref:`power_dbm<spectral_info>`).
+
+
+**Option**: `--spectrum`
+------------------------
+
+**Description**: Specifies a user-defined mixed rate spectrum JSON file for propagation.
+
+**Usage**:
+
+.. code-block:: shell-session
+
+  gnpy-transmission-example my_network.json --spectrum <FILE.json>
+
+**Functionality**: This option allows users to define a custom spectrum for the simulation, which can
+include varying channel rates and configurations. More details here: :ref:`mixed-rate<mixed-rate>`.
+
+
+Options for `path_requests_run`
+===============================
+
+The `gnpy-path-request` script provides a simple path computation function that supports routing, transceiver mode selection, and spectrum assignment.
+
+It supports include and disjoint constraints for the path computation, but does not provide any optimisation.
+It requires two mandatory arguments: network file and service file (see :ref:`XLS files<excel-service-sheet>` or :ref:`JSON files<legacy-json>`).
+
+The `gnpy-path-request` computes:
+
+  - design network once and propagate the service requests on this design
+  - computes performance of each request defined in the service file independently from each other, considering full load (based on the request settings),
+  - assigns spectrum for each request according to the remaining spectrum, on a first arrived first served basis.
+    Lack of spectrum leads to blocking, but performance estimation is still returned for information.
+
+
+**Option**: `-bi`, `--bidir`
+----------------------------
+
+**Description**: Indicates that all demands are bidirectional.
+
+**Usage**:
+
+.. code-block:: shell-session
+
+  gnpy-path-request my_network.json my_service.json -e my_equipment.json -bi
+
+**Functionality**: This option allows users to specify that the performance of the service requests should be
+computed in both directions (source to destination and destination to source). This forces the 'bidirectional'
+attribute to true in the service file, possibly affecting feasibility if one direction is not feasible.
+
+
+**Option**: `-o`, `--output`
+----------------------------
+
+**Description**: Stores computation results requests into a JSON or CSV file.
+
+**Usage**: 
+
+.. code-block:: shell-session
+
+  gnpy-path-request my_network.json my_service.json -o <FILE.json|FILE.csv>
+
+**Functionality**: This option allows users to save the results of the path requests into a specified output file
+for further analysis.
+
+
+**Option**: `--redesign-per-request`
+------------------------------------
+
+**Description**: Redesigns the network for each request using the request as the reference channel
+(replaces the `SI` section of the equipment library with the request specifications).
+
+**Usage**:
+.. code-block:: shell-session
+
+  gnpy-path-request my_network.json my_services.json --redesign-per-request
+
+**Functionality**: This option enables checking different scenarios for design.

docs/concepts.rst

@@ -1,7 +1,8 @@
 .. _concepts:
 
+*****************************
 Simulating networks with GNPy
-=============================
+*****************************
 
 Running simulations with GNPy requires three pieces of information:
 
@@ -12,7 +13,7 @@ Running simulations with GNPy requires three pieces of information:
 .. _concepts-topology:
 
 Network Topology
-----------------
+================
 
 The *topology* acts as a "digital self" of the simulated network.
 When given a network topology, GNPy can either run a specific simulation as-is, or it can *optimize* the topology before performing the simulation.
@@ -29,11 +30,12 @@ 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<legacy-json>`.
 
 .. _complete-vs-incomplete:
 
 Fully Specified vs. Partially Designed Networks
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+-----------------------------------------------
 
 Let's consider a simple triangle topology with three :abbr:`PoPs (Points of Presence)` covering three cities:
 
@@ -207,7 +209,7 @@ In other cases where the location of amplifier huts is already known, but the sp
 .. _concepts-equipment:
 
 The Equipment Library
----------------------
+=====================
 
 In order to produce an accurate simulation, GNPy needs to know the physical properties of each entity which affects the optical signal.
 Entries in the equipment library correspond to actual real-world, tangible entities.
@@ -230,20 +232,20 @@ GNPy currently does not take into consideration the spectrum filtering penalties
 .. _concepts-nf-model:
 
 Amplifier Noise Figure Models
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+-----------------------------
 
 One of the key parameters of an amplifier is the method to use for computing the Noise Figure (NF).
 GNPy supports several different noise models with varying level of accuracy.
 When in doubt, contact your vendor's technical support and ask them to :ref:`contribute their equipment descriptions<extending-edfa>` to GNPy.
 
 The most accurate noise models describe the resulting NF of an EDFA as a third-degree polynomial.
-GNPy understands polynomials as a NF-yielding function of the :ref:`gain difference from the optimal gain<ext-nf-model-polynomial-NF>`, or as a function of the input power resulting in an :ref:`incremental OSNR as used in OpenROADM<ext-nf-model-polynomial-OSNR-OpenROADM>`.
+GNPy understands polynomials as a NF-yielding function of the :ref:`gain difference from the optimal gain<ext-nf-model-polynomial-NF>`, or as a function of the input power resulting in an incremental OSNR as used in :ref:`OpenROADM inline amplifiers<ext-nf-model-polynomial-OSNR-OpenROADM>` and :ref:`OpenROADM booster/preamps in the ROADMs<ext-nf-model-noise-mask-OpenROADM>`.
 For scenarios where the vendor has not yet contributed an accurate EDFA NF description to GNPy, it is possible to approximate the characteristics via an operator-focused, min-max NF model.
 
 .. _nf-model-min-max-NF:
 
 Min-max NF
-**********
+^^^^^^^^^^
 
 This is an operator-focused model where performance is defined by the *minimal* and *maximal NF*.
 These are especially suited to model a dual-coil EDFA with a VOA in between.
@@ -253,7 +255,7 @@ The worst (maximal) NF applies  when the EDFA operates at its minimal gain.
 This model is suitable for use when the vendor has not provided a more accurate performance description of the EDFA.
 
 Raman Approximation
-*******************
+^^^^^^^^^^^^^^^^^^^
 
 While GNPy is fully Raman-aware, under certain scenarios it is useful to be able to run a simulation without an accurate Raman description.
 For these purposes the :ref:`polynomial NF<ext-nf-model-polynomial-NF>` model with :math:`\text{a} = \text{b} = \text{c} = 0`, and :math:`\text{d} = NF` can be used.
@@ -261,7 +263,7 @@ For these purposes the :ref:`polynomial NF<ext-nf-model-polynomial-NF>` model wi
 .. _concepts-simulation:
 
 Simulation
-----------
+==========
 
 When the network model has been instantiated and the physical properties and operational settings of the actual physical devices are known, GNPy can start simulating how the signal propagate through the optical fiber.
 

docs/conf.py

@@ -19,6 +19,8 @@
 #
 import os
 import sys
+
+
 sys.path.insert(0, os.path.abspath('../'))
 
 # -- General configuration ------------------------------------------------
@@ -34,10 +36,16 @@ extensions = ['sphinx.ext.autodoc',
               'sphinx.ext.mathjax',
               'sphinx.ext.githubpages',
               'sphinxcontrib.bibtex',
-              'pbr.sphinxext',
               'sphinx.ext.graphviz',
+              'myst_parser',
+              'sphinx_rtd_theme',
               ]
 
+myst_enable_extensions = [
+    "deflist",
+    "dollarmath",
+]
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
 
@@ -60,7 +68,7 @@ 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.
@@ -79,18 +87,22 @@ 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 = "sphinx_rtd_theme"
+html_theme_options = {
+    'logo': 'images/GNPy-logo.png',
+    'logo_name': False,
+    'prev_next_buttons_location': 'bottom',
+    # Toc options
+    'collapse_navigation': True,
+    'sticky_navigation': True,
+    'navigation_depth': 4,
+    'includehidden': True,
+    'titles_only': False
+}
+html_theme_options = {
+    'navigation_depth': 4,
+}
+html_favicon = 'images/GNPy-logo.png'
 
 html_logo = 'images/GNPy-logo.png'
 
@@ -103,7 +115,10 @@ html_logo = 'images/GNPy-logo.png'
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = []
+html_static_path = ['_static']
+html_css_files = [
+    'custom.css',  # Inclure votre fichier CSS personnalisé
+]
 
 # Custom sidebar templates, must be a dictionary that maps document names
 # to template names.
@@ -120,6 +135,7 @@ html_sidebars = {
     ]
 }
 
+html_secnum_depth = 4
 
 # -- Options for HTMLHelp output ------------------------------------------
 
@@ -185,3 +201,5 @@ autodoc_default_options = {
 }
 
 graphviz_output_format = 'svg'
+
+bibtex_bibfiles = ['biblio.bib']

docs/excel.rst

@@ -1,5 +1,8 @@
+.. _excel:
+
+*****************************
 Excel (XLS, XLSX) input files
-=============================
+*****************************
 
 ``gnpy-transmission-example`` gives the possibility to use an excel input file instead of a json file. The program then will generate the corresponding json file for you.
 
@@ -7,21 +10,22 @@ The file named 'meshTopologyExampleV2.xls' is an example.
 
 In order to work the excel file MUST contain at least 2 sheets:
 
-- Nodes
-- Links
+- `Nodes`
+- `Links`
 
-(In progress) The File MAY contain an additional sheet:
+(In progress) The File MAY contain additional sheets:
 
-- Eqt
-- Service
+- `Eqpt`
+- `Service`
+- `Roadms`
 
 .. _excel-nodes-sheet:
 
-Nodes sheet
------------
+`Nodes` sheet
+=============
 
-Nodes sheet contains nine columns.
-Each line represents a 'node' (ROADM site or an in line amplifier site ILA or a Fused)::
+`Nodes` sheet contains nine columns.
+Each line represents a 'node' (`ROADM` site or an in line amplifier site `ILA` or a `Fused`)::
 
   City (Mandatory) ; State ; Country ; Region ; Latitude ; Longitude ; Type
 
@@ -48,15 +52,15 @@ Each line represents a 'node' (ROADM site or an in line amplifier site ILA or a
 .. _excel-links-sheet:
 
 Links sheet
------------
+===========
 
 Links sheet must contain sixteen columns::
 
-                   <--           east cable from a to z                                   --> <--                  west from z to                                   -->
+                   <--           east cable from a to z                                   --> <--                  west from z to a                                 -->
    NodeA ; NodeZ ; Distance km ; Fiber type ; Lineic att ; Con_in ; Con_out ; PMD ; Cable Id ; Distance km ; Fiber type ; Lineic att ; Con_in ; Con_out ; PMD ; Cable Id
 
 
-Links sheets MUST contain all links between nodes defined in Nodes sheet.
+`Links` sheet MUST contain all links between nodes defined in Nodes sheet.
 Each line represents a 'bidir link' between two nodes. The two directions are represented on a single line with "east cable from a to z" fields and "west from z to a" fields. Values for 'a to z' may be different from values from 'z to a'. 
 Since both direction of a bidir 'a-z' link are described on the same line (east and west), 'z to a' direction MUST NOT be repeated in a different line. If repeated, it will generate another parrallel bidir link between the same end nodes.
 
@@ -83,43 +87,42 @@ and a fiber span from node3 to node6::
 
   - If filled it MUST contain numbers. If empty it is replaced by a default "80" km value. 
   - If value is below 150 km, it is considered as a single (bidirectional) fiber span.
-  - If value is over 150 km the `gnpy-transmission-example`` program will automatically suppose that intermediate span description are required and will generate fiber spans elements with "_1","_2", ... trailing strings which are not visible in the json output. The reason for the splitting is that current edfa usually do not support large span loss. The current assumption is that links larger than 150km will require intermediate amplification. This value will be revisited when Raman amplification is added”
+  - If value is over 150 km or if the loss is greater than 28 dB, the autodesign program
+    will automatically split the span with "_1","_2", ... trailing strings in names.
+    Splitting threshold can be tuned in ["Span"]["max_length"] and ["Span"]["max_loss"] in
+    equipment library.
 
 - **Fiber type** is not mandatory. 
 
   If filled it must contain types listed in `eqpt_config.json <gnpy/example-data/eqpt_config.json>`_ in "Fiber" list "type_variety".
   If not filled it takes "SSMF" as default value.
 
-- **Lineic att** is not mandatory. 
+- **Lineic att** is not mandatory.
 
   It is the lineic attenuation expressed in dB/km.
   If filled it must contain positive numbers.
   If not filled it takes "0.2" dB/km value
 
-- *Con_in*, *Con_out* are not mandatory. 
+- **Con_in**, **Con_out** are not mandatory.
 
   They are the connector loss in dB at ingress and egress of the fiber spans.
   If filled they must contain positive numbers.
   If not filled they take "0.5" dB default value.
 
-- *PMD* is not mandatory and and is not used yet. 
+- **PMD** is not mandatory.
 
   It is the PMD value of the link in ps.
   If filled they must contain positive numbers.
   If not filled, it takes "0.1" ps value.
 
-- *Cable Id* is not mandatory. 
+- **Cable Id** is not mandatory.
   If filled they must contain strings with the same constraint as "City" names. Its value is used to differenate links having the same end points. In this case different Id should be used. Cable Ids are not meant to be unique in general.
 
 
-
-
-(in progress)
-
 .. _excel-equipment-sheet:
 
 Eqpt sheet 
-----------
+==========
 
 The equipment sheet (named "Eqpt") is optional.
 If provided, it specifies types of boosters and preamplifiers for all ROADM degrees of all ROADM nodes, and for all ILA nodes.
@@ -174,7 +177,7 @@ This generates a text file meshTopologyExampleV2_eqt_sheet.txt  whose content ca
 - **Node Z** is mandatory. It is the egress direction from the *Node A* site. Multiple Links between the same Node A and NodeZ is not supported.
 
 - **amp type** is not mandatory. 
-  If filled it must contain types listed in `eqpt_config.json <gnpy/example-data/eqpt_config.json>`_ in "Edfa" list "type_variety".
+  If filled it must contain types listed in the equipment librairie like in the example `eqpt_config.json <gnpy/example-data/eqpt_config.json>`_ in "Edfa" list "type_variety".
   If not filled it takes "std_medium_gain" as default value.
   If filled with fused, a fused element with 0.0 dB loss will be placed instead of an amplifier. This might be used to avoid booster amplifier on a ROADM direction.
 
@@ -182,21 +185,57 @@ This generates a text file meshTopologyExampleV2_eqt_sheet.txt  whose content ca
   If not filled, it will be determined with design rules in the convert.py file.
   If filled, it must contain positive numbers.
 
-- *att_in* and *att_out* are not mandatory and are not used yet. They are the value of the attenuator at input and output of amplifier (in dB).
+- **att_in** and **att_out** are not mandatory. They are the value of the attenuator at input and output of amplifier (in dB).
   If filled they must contain positive numbers.
 
-- *tilt* --TODO--
+- **tilt**, in dB, is not mandatory. It is the target gain tilt over the full amplfifier bandwidth and is defined with regard to wavelength, i.e. negative tilt means lower gain
+  for higher wavelengths (lower frequencies). If not filled, the default value is 0.
 
-- **delta_p**, in dBm,  is not mandatory. If filled it is used to set the output target power per channel at the output of the amplifier, if power_mode is True. The output power is then set to power_dbm + delta_power.
+- **delta_p**, in dB,  is not mandatory. If filled it is used to set the output target power per channel at the output of the amplifier, if power_mode is True. The output power is then set to power_dbm + delta_power.
 
-# to be completed #
+
+.. _excel-roadms-sheet:
+
+Roadms sheet 
+============
+
+The ROADM sheet (named "Roadms") is optional.
+If provided, it can be used to specify:
+
+  - per channel power target on a specific ROADM degree (*per_degree_pch_out_db*),
+  - ROADM type variety,
+  - impairment ID (identifier) on a particular ROADM path (from degree - to degree).
+
+This sheet contains six columns:
+
+  Node A ; Node Z ; per degree target power (dBm) ; type_variety ; from degrees ; from degree to degree impairment id
+
+- **Node A** is mandatory. Name of the ROADM node (as listed in Nodes sheet).
+  Must be a 'ROADM' (Type attribute in Node sheet), its number of occurence may be equal to its degree.
+
+- **Node Z** is mandatory. Egress direction from the *Node A* ROADM site. Multiple Links between the same Node A
+  and NodeZ is not supported. 
+
+- **per degree target power (dBm)** (optional). 
+  If filled it must contain a value in dBm corresponding to :ref:`per_degree_pch_out_db<roadm_json_instance>` on the **Node Z** degree.
+  Defaults to equipment library value if not filled.
+
+- **type_variety** (optional). Must be the same for all ROADM entries if filled,
+  and defined in the :ref:`equipment library<roadm>`. Defaults to 'default' if not filled.
+
+- **from degrees** (optional): List of Node names separated by ' | '. Names must be present in Node sheet.
+  Together with Node Z, they define a list of internal path in ROADM for which the impairment ID applies
+
+- **from degree to degree impairment id** (optional):List of impairment IDs separated by ' | '. Must be filled
+  if **from degrees** is defined.
+  The impairment ID must be defined in the equipment library and be of "express" type.
 
 (in progress)
 
 .. _excel-service-sheet:
 
 Service sheet 
--------------
+=============
 
 Service sheet is optional. It lists the services for which path and feasibility must be computed with ``gnpy-path-request``.
 
@@ -210,7 +249,7 @@ Service sheet must contain 11 columns::
 
 - **Destination** is mandatory. It is the name of the destination node (as listed in Nodes sheet). Source MUST be a ROADM node. (TODO: relax this and accept trx entries)
 
-- **TRX type** is mandatory. They are the variety type and selected mode of the transceiver to be used for the propagation simulation. These modes MUST be defined in the equipment library. The format of the mode is used as the name of the mode. (TODO: maybe add another  mode id on Transceiver library ?). In particular the mode selection defines the channel baudrate to be used for the propagation simulation.
+- **TRX type** is mandatory. It is the variety type of the transceiver to be used for the propagation simulation. These modes MUST be defined in the equipment library. The format of the mode is used as the name of the mode. (TODO: maybe add another  mode id on Transceiver library ?). In particular the mode selection defines the channel baudrate to be used for the propagation simulation.
 
 - **mode** is optional. If not specified, the program will search for the mode of the defined transponder with the highest baudrate fitting within the spacing value. 
 

docs/extending.rst

@@ -1,17 +1,18 @@
 .. _extending:
 
+****************************************
 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>`.
 
 .. _extending-edfa:
 
 EDFAs
------
+=====
 
 An accurate description of the :abbr:`EDFA (Erbium-Doped Fiber Amplifier)` and especially its noise characteristics is required.
 GNPy describes this property in terms of the **Noise Figure (NF)** of an amplifier model as a function of its operating point.
@@ -20,7 +21,7 @@ GNPy supports several different :ref:`noise models<concepts-nf-model>`, and vend
 .. _ext-nf-model-polynomial-NF:
 
 Polynomial NF
-*************
+-------------
 
 This model computes the NF as a function of the difference between the optimal gain and the current gain.
 The NF is expressed as a third-degree polynomial:
@@ -29,7 +30,7 @@ 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:
@@ -42,20 +43,35 @@ In that case, use:
 
 .. _ext-nf-model-polynomial-OSNR-OpenROADM:
 
-Polynomial OSNR (OpenROADM-style)
-*********************************
+Polynomial OSNR (OpenROADM-style for inline amplifier)
+------------------------------------------------------
 
-This model is useful for amplifiers compliant to the OpenROADM specification for ILA.
-In OpenROADM, amplifier performance is evaluated via its incremental OSNR, which is a function of the input power.
+This model is useful for amplifiers compliant to the OpenROADM specification for ILA (an in-line amplifier).
+The amplifier performance is evaluated via its incremental OSNR, which is a function of the input power.
 
 .. math::
 
     \text{OSNR}_\text{inc}(P_\text{in}) = \text{a}P_\text{in}^3 + \text{b}P_\text{in}^2 + \text{c}P_\text{in} + \text{d}
 
+.. _ext-nf-model-noise-mask-OpenROADM:
+
+Noise mask (OpenROADM-style for combined preamp and booster)
+------------------------------------------------------------
+
+Unlike GNPy which simluates the preamplifier and the booster separately as two amplifiers for best accuracy, the OpenROADM specification mandates a certain performance level for a combination of these two amplifiers.
+For the express path, the effective noise mask comprises the preamplifier and the booster.
+When terminating a channel, the same effective noise mask is mandated for a combination of the preamplifier and the drop stage.
+
+GNPy emulates this specification via two special NF models:
+
+- The ``openroadm_preamp`` NF model for preamplifiers.
+  This NF model provides all of the linear impairments to the signal, including those which are incured by the booster in a real network.
+- The ``openroadm_booster`` NF model is a special "zero noise" faux amplifier in place of the booster.
+
 .. _ext-nf-model-min-max-NF:
 
 Min-max NF
-**********
+----------
 
 When the vendor prefers not to share the amplifier description in full detail, GNPy also supports describing the NF characteristics via the *minimal* and *maximal NF*.
 This approximates a more accurate polynomial description reasonably well for some models of a dual-coil EDFA with a VOA in between.
@@ -65,7 +81,7 @@ The worst (maximal) NF applies  when the EDFA operates at the minimal gain.
 .. _ext-nf-model-dual-stage-amplifier:
 
 Dual-stage
-**********
+----------
 
 Dual-stage amplifier combines two distinct amplifiers.
 Vendors which provide an accurate description of their preamp and booster stages separately can use the dual-stage model for an aggregate description of the whole amplifier.
@@ -73,22 +89,23 @@ Vendors which provide an accurate description of their preamp and booster stages
 .. _ext-nf-model-advanced:
 
 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:
 
 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`.
@@ -97,52 +114,46 @@ This is also useful to quickly approximate a hybrid EDFA+Raman amplifier.
 .. _extending-transponder:
 
 Transponders
-------------
+============
 
 Since transponders are usually capable of operating in a variety of modes, these are described separately.
 A *mode* usually refers to a particular performance point that is defined by a combination of the symbol rate, modulation format, and :abbr:`FEC (Forward Error Correction)`.
 
 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.
 
 .. _extending-roadm:
 
 ROADMs
-------
+======
 
 In a :abbr:`ROADM (Reconfigurable Add/Drop Multiplexer)`, GNPy simulates the impairments of the preamplifiers and boosters of line degrees :ref:`separately<topo-roadm-preamp-booster>`.
 The set of parameters for each ROADM model therefore includes:
@@ -153,6 +164,7 @@ 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/gnpy-api-tools.rst

@@ -7,3 +7,4 @@
 .. automodule:: gnpy.tools.json_io
 .. automodule:: gnpy.tools.plots
 .. automodule:: gnpy.tools.service_sheet
+.. automodule:: gnpy.tools.worker_utils

docs/gnpy-api.rst

@@ -2,8 +2,8 @@
 API Reference Documentation
 ***************************
 
-``gnpy`` package
-================
+GNPy package
+============
 
 .. automodule:: gnpy
 

docs/index.rst

@@ -1,5 +1,6 @@
+************************************
 GNPy: Optical Route Planning Library
-=====================================================================
+************************************
 
 `GNPy <http://github.com/telecominfraproject/gnpy>`_ is an open-source,
 community-developed library for building route planning and optimization tools
@@ -7,17 +8,27 @@ in real-world mesh optical networks. It is based on the Gaussian Noise Model.
 
 .. toctree::
    :maxdepth: 4
+   :caption: Contents
 
+   intro 
    concepts
    install
+   cli_options
+   amplifier_models_description
    json
+   json_instance_examples
    excel
    extending
+   about-project
    model
    gnpy-api
+   release-notes
+   publications
+   genindex
+   modindex
 
 Indices and tables
-==================
+------------------
 
 * :ref:`genindex`
 * :ref:`modindex`

docs/install.rst

@@ -1,5 +1,6 @@
+***************
 Installing GNPy
----------------
+***************
 
 There are several methods on how to obtain GNPy.
 The easiest option for a non-developer is probably going via our :ref:`Docker images<install-docker>`.
@@ -9,7 +10,7 @@ Note that this needs a :ref:`working installation of Python<install-python>`, fo
 .. _install-docker:
 
 Using prebuilt Docker images
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+============================
 
 Our `Docker images <https://hub.docker.com/r/telecominfraproject/oopt-gnpy>`_ contain everything needed to run all examples from this guide.
 Docker transparently fetches the image over the network upon first use.
@@ -35,10 +36,10 @@ Remove that directory if you want to start from scratch.
 .. _install-python:
 
 Using Python on your computer
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+=============================
 
    **Note**: `gnpy` supports Python 3 only. Python 2 is not supported.
-   `gnpy` requires Python ≥3.6
+   `gnpy` requires Python ≥3.8
 
    **Note**: the `gnpy` maintainers strongly recommend the use of Anaconda for
    managing dependencies.
@@ -84,12 +85,12 @@ exact version of Python you are using.
     $ which python                   # check which Python executable is used
     /path/to/anaconda/bin/python
     $ python -V                      # check your Python version
-    Python 3.6.5 :: Anaconda, Inc.
+    Python 3.8.0 :: Anaconda, Inc.
 
 .. _install-pip:
 
 Installing the Python package
-*****************************
+-----------------------------
 
 From within your Anaconda Python 3 environment, you can clone the master branch
 of the `gnpy` repo and install it with:

docs/intro.rst

@@ -0,0 +1,97 @@
+.. _intro:
+
+************
+Introduction
+************
+
+``gnpy`` is a library for building route planning and optimization tools.
+
+It ships with a number of example programs. Release versions will ship with
+fully-functional programs.
+
+    **Note**: *If you are a network operator or involved in route planning and
+    optimization for your organization, please contact project maintainers
+    esther Le Rouzic <esther.lerouzic@orange.com>, Andrea D'Amico <adamico@nec-labs.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,
+or to run a planning script to check SNR of several services:
+
+.. image:: images/gnpy-transmission-example.svg
+   :width: 100%
+   :align: left
+   :alt: Running a simple simulation example
+
+By default, the gnpy-transmission-example script operates on a single span network defined in
+`gnpy/example-data/edfa_example_network.json <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/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 <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/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 <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/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 <excel.rst>`__.
+
+The main transmission example will calculate the average signal OSNR and SNR
+across network elements (transceiver, ROADMs, fibers, and amplifiers)
+between two transceivers selected by the user. Additional details are provided by doing ``gnpy-transmission-example -h``. (By default, for the CORONET Global
+network, it will show the transmission of spectral information between Abilene and Albany)
+
+This script calculates the average signal OSNR = |OSNR| and SNR = |SNR|.
+
+.. |OSNR| replace:: P\ :sub:`ch`\ /P\ :sub:`ase`
+.. |SNR| replace:: P\ :sub:`ch`\ /(P\ :sub:`nli`\ +\ P\ :sub:`ase`)
+
+|Pase| is the amplified spontaneous emission noise, and |Pnli| the non-linear
+interference noise.
+
+.. |Pase| replace:: P\ :sub:`ase`
+.. |Pnli| replace:: P\ :sub:`nli`
+
+Further Instructions for Use
+============================
+
+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 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.
+
+An experimental support for Raman amplification is available:
+
+.. code-block:: shell-session
+
+     $ gnpy-transmission-example \
+       $(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 <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/raman_edfa_example_network.json>`_.
+General numeric parameters for simulation control are provided in the `gnpy/example-data/sim_params.json <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/sim_params.json>`_.
+
+Use ``gnpy-path-request`` to request several paths at once:
+
+.. code-block:: shell-session
+
+     $ cd $(gnpy-example-data)
+     $ gnpy-path-request -o output_file.json \
+       meshTopologyExampleV2.xls meshTopologyExampleV2_services.json
+
+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`.
+
+Important note: ``gnpy-path-request`` is not a network dimensionning tool: each service does not reserve spectrum, or occupy ressources such as transponders. It only computes path feasibility assuming the spectrum (between defined frequencies) is loaded with "nb of channels" spaced by "spacing" values as specified in the system parameters input in the service file, each cannel having the same characteristics in terms of baudrate, format,... as the service transponder. The transceiver element acts as a "logical starting/stopping point" for the spectral information propagation. At that point it is not meant to represent the capacity of add drop ports.
+As a result transponder type is not part of the network info. it is related to the list of services requests.
+
+The current version includes a spectrum assigment features that enables to compute a candidate spectrum assignment for each service based on a first fit policy. Spectrum is assigned based on service specified spacing value, path_bandwidth value and selected mode for the transceiver. This spectrum assignment includes a basic capacity planning capability so that the spectrum resource is limited by the frequency min and max values defined for the links. If the requested services reach the link spectrum capacity, additional services feasibility are computed but marked as blocked due to spectrum reason.
+
+OpenROADM networks can be simulated via ``gnpy/example-data/eqpt_config_openroadm_*.json`` -- see ``gnpy/example-data/Sweden_OpenROADM*_example_network.json`` as an example. 

docs/model.rst

@@ -1,10 +1,11 @@
 .. _physical-model:
 
+***************************
 Physical Model used in GNPy
-===========================
+***************************
 
 QoT-E including ASE noise and NLI accumulation 
-----------------------------------------------
+==============================================
 
 The operations of PSE simulative framework are based on the capability to
 estimate the QoT of one or more channels operating lightpaths over a given
@@ -83,7 +84,7 @@ ps/nm/km, the analytical approximation ensures an excellent accuracy
 with a computational time compatible with real-time operations.
 
 The Gaussian Noise Model to evaluate the NLI
---------------------------------------------
+============================================
 
 As previously stated, fiber propagation of multilevel modulation formats
 relying on the polarization-division-multiplexing  generates impairments that
@@ -126,9 +127,9 @@ 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 +146,4 @@ 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/publications.rst

@@ -0,0 +1,25 @@
+.. _publications:
+
+************
+Publications
+************
+
+Below is a chronological list of notable publications that emerged from the PSE group's collaborative work.
+These articles detail the evolution of GNPy and confirm its performance through experimental trials:
+
+- `G. Grammel, V. Curri, and J. Auge, "Physical Simulation Environment of The Telecommunications Infrastructure Project (TIP)," in Optical Fiber Communication Conference, OSA Technical Digest (online) (Optica Publishing Group, 2018), paper M1D.3. <https://opg.optica.org/abstract.cfm?uri=OFC-2018-M1D.3>`_
+- `B. D. Taylor, G. Goldfarb, S. Bandyopadhyay, V. Curri, and H. Schmidtke, "Towards a Route Planning Tool for Open Optical Networks in the Telecom Infrastructure Project," in Optical Fiber Communication Conference, OSA Technical Digest (online) (Optica Publishing Group, 2018), paper Tu3E.4. <https://opg.optica.org/abstract.cfm?uri=OFC-2018-Tu3E.4>`_
+- `M. Filer, M. Cantono, A. Ferrari, G. Grammel, G. Galimberti, and V. Curri, "Multi-Vendor Experimental Validation of an Open Source QoT Estimator for Optical Networks," J. Lightwave Technol. 36, 3073-3082 (2018). <https://opg.optica.org/jlt/abstract.cfm?uri=jlt-36-15-3073>`_
+- `J. Auge, G. Grammel, E. le Rouzic, V. Curri, G. Galimberti, and J. Powell, "Open optical network planning demonstration," in Optical Fiber Communication Conference (OFC) 2019, OSA Technical Digest (Optica Publishing Group, 2019), paper M3Z.9. <https://opg.optica.org/abstract.cfm?uri=OFC-2019-M3Z.9>`_
+- `J. Kundrát, A. Campanella, E. Le Rouzic, A. Ferrari, O. Havliš, M. Hažlinský, G. Grammel, G. Galimberti, and V. Curri, "Physical-Layer Awareness: GNPy and ONOS for End-to-End Circuits in Disaggregated Networks," in Optical Fiber Communication Conference (OFC) 2020, OSA Technical Digest (Optica Publishing Group, 2020), paper M3Z.17. <https://opg.optica.org/abstract.cfm?uri=ofc-2020-m3z.17>`_
+- `A. Ferrari, M. Filer, K. Balasubramanian, Y. Yin, E. Le Rouzic, J. Kundrát, G. Grammel, G. Galimberti, and V. Curri, "Experimental Validation of an Open Source Quality of Transmission Estimator for Open Optical Networks," in Optical Fiber Communication Conference (OFC) 2020, OSA Technical Digest (Optica Publishing Group, 2020), paper W3C.2. <https://opg.optica.org/abstract.cfm?uri=ofc-2020-W3C.2>`_
+- `A. Ferrari, M. Filer, K. Balasubramanian, Y. Yin, E. Le Rouzic, J. Kundrát, G. Grammel, G. Galimberti, and V. Curri, "GNPy: an open source application for physical layer aware open optical networks," J. Opt. Commun. Netw. 12, C31-C40 (2020). <https://opg.optica.org/jocn/fulltext.cfm?uri=jocn-12-6-C31&id=429003>`_
+- `A. Ferrari, K. Balasubramanian, M. Filer, Y. Yin, E. Le Rouzic, J. Kundrát, G. Grammel, G. Galimberti, and V. Curri, "Softwarized Optical Transport QoT in Production Optical Network: a Brownfield Validation," 2020 European Conference on Optical Communications (ECOC), Brussels, Belgium, 2020. <https://ieeexplore.ieee.org/document/9333280>`_
+- `A. Ferrari, K. Balasubramanian, M. Filer, Y. Yin, E. Le Rouzic, J. Kundrát, G. Grammel, G. Galimberti, and V. Curri, "Assessment on the in-field lightpath QoT computation including connector loss uncertainties," in Journal of Optical Communications and Networking, vol. 13, no. 2, pp. A156-A164, February 2021. <https://ieeexplore.ieee.org/document/9308057>`_
+- `J. Kundrát, E. Le Rouzic, J. Mårtensson, A. Campanella, O. Havliš, A. D’Amico, G. Grammel, G. Galimberti, V. Curri, and J. Vojtěch, "GNPy & YANG: Open APIs for End-to-End Service Provisioning in Optical Networks," in Optical Fiber Communication Conference (OFC) 2021, P. Dong, J. Kani, C. Xie, R. Casellas, C. Cole, and M. Li, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper M1B.6. <https://opg.optica.org/abstract.cfm?uri=ofc-2021-M1B.6>`_
+- `A. D’Amico, E. London, B. Le Guyader, F. Frank, E. Le Rouzic, E. Pincemin, N. Brochier, and V. Curri, "GNPy experimental validation on flex-grid, flex-rate WDM optical transport scenarios," in Optical Fiber Communication Conference (OFC) 2021, P. Dong, J. Kani, C. Xie, R. Casellas, C. Cole, and M. Li, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper W1G.2. <https://opg.optica.org/abstract.cfm?uri=ofc-2021-W1G.2>`_
+- `E. Virgillito, R. Braun, D. Breuer, A. Gladisch, V. Curri, and G. Grammel, "Testing TIP Open Source Solutions in Deployed Optical Networks," in Optical Fiber Communication Conference (OFC) 2021, P. Dong, J. Kani, C. Xie, R. Casellas, C. Cole, and M. Li, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper F1C.3. <https://opg.optica.org/abstract.cfm?uri=ofc-2021-F1C.3>`_
+- `A. D’Amico, E. London, B. Le Guyader, F. Frank, E. Le Rouzic, E. Pincemin, N. Brochier, and V. Curri, "Experimental validation of GNPy in a multi-vendor flex-grid flex-rate WDM optical transport scenario," J. Opt. Commun. Netw. 14, 79-88 (2022). <https://opg.optica.org/jocn/fulltext.cfm?uri=jocn-14-3-79&id=466355>`_
+- `J. Kundrát, E. Le Rouzic, J. Mårtensson, S. Melin, A. D’Amico, G. Grammel, G. Galimberti, and V. Curri, "GNPy: Lessons Learned and Future Plans [Invited]," in European Conference on Optical Communication (ECOC) 2022, J. Leuthold, C. Harder, B. Offrein, and H. Limberger, eds., Technical Digest Series (Optica Publishing Group, 2022), paper We3B.6. <https://opg.optica.org/abstract.cfm?uri=ECEOC-2022-We3B.6>`_
+- `G. Grammel, J. Kundrat, E. Le Rouzic, S. Melin, V. Curri, A. D'Amico, R. Manzotti, "Open Optical Networks: the good, the bad and the ugly," 49th European Conference on Optical Communications (ECOC 2023), Hybrid Conference, Glasgow, UK, 2023. <https://ieeexplore.ieee.org/document/10484723>`_
+- `A. D’Amico, V. Gatto, A. Nespola, G. Borraccini, Y. Jiang, P. Poggiolini, E. Le Rouzic,  A. M. L. de Lerma, G. Grammel, R. Manzotti, V. Curri, "GNPy Experimental Validation in a C+L Multiband Optical Multiplex Section," 2024 24th International Conference on Transparent Optical Networks (ICTON), Bari, Italy, 2024. <https://ieeexplore.ieee.org/document/10648172>`_

docs/release-notes.rst

@@ -0,0 +1,527 @@
+.. _release-notes:
+
+******************
+Release change log
+******************
+
+Each release introduces some changes and new features.
+
+(prepare text for next release)
+
+v2.13
+=====
+
+**Environment**
+
+The windows-2019 environment is no more supported.
+
+**Yang Conversion Utilities**
+
+This release introduces new conversion utilities to facilitate conversion between YANG and legacy formats,
+ensuring full compatibility with GNPy. The "legacy" format also benefit from the YANG validation for
+a stricter verification of input files.
+Console Script for Yang Conversion: Added a new command-line script to perform Yang format conversions easily.
+
+**Design Enhancements**
+
+This release adds the ability to parametrize power target calculations, allowing customization of reference
+span loss and deviation ratios. It implements the use of a reference channel per OMS (Optical Multiplex Section)
+instead of total power for design calculations, improving accuracy and performance.
+It also includes spacing information in design band data to assist in maximum power computation for EDFA
+targets compution during autodesign.
+
+**Excel handling**
+
+XLSX files are now read with openpyxl library (while XLS files are still read with xlrd library). Latest release of
+xlrd is supported, which solves compatibility issues with anaconda install.
+
+v2.12
+=====
+
+**Important Changes:**
+
+The default values for EDFA configuration, including frequency range, gain ripple, noise figure ripple, or dynamic gain tilt
+are now hardcoded in parameters.py and are no longer read from the default_edfa_config.json file (the file has been removed).
+However, users can define their own custom parameters using the default_config_from_json variable, which should be populated with a file name containing the desired parameter description. This applies to both variable_gain and fixed_gain amplifier types.
+
+This change streamlines the configuration process but requires users to explicitly set parameters through the new
+model if the default values do not suit their needs via the --extra-config option.
+
+v2.11.1
+-------
+
+**Environment**
+
+The macOS-12 environment is no more supported.
+
+**per degree impairment enabled in xls input**
+
+This release now read per degre roadm-path impairment from roadm sheet
+Several optional columns are added: 'type_variety' and 'from degrees'
+and 'from degree to degree impairment id'.
+
+- 'from degrees' can contain a list of degrees separated with ' | ', then the
+  'from degree to degree impairment id' must contain a list of ids of the same
+  length.
+
+Impairment ids are expected to be defined in the ROADM equipment library and
+from degree must be among the previous node from this ROADM.
+
+**optimizing computation speed**
+The computation of path is skipped if the provided include nodes provides
+a complete explicit path (speeds simulation time).
+
+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.
+
+1. 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.
+
+1. 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.
+
+1. 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
+====

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/api/__init__.py

@@ -1,9 +0,0 @@
-# coding: utf-8
-from flask import Flask
-
-app = Flask(__name__)
-
-import gnpy.api.route.path_request_route
-import gnpy.api.route.status_route
-import gnpy.api.route.topology_route
-import gnpy.api.route.equipments_route

gnpy/api/exception/__init__.py

@@ -1 +0,0 @@
-# coding: utf-8

gnpy/api/exception/config_error.py

@@ -1,14 +0,0 @@
-# coding: utf-8
-
-
-class ConfigError(Exception):
-    """ Exception raise for configuration file error
-    Attributes:
-        message -- explanation of the error
-    """
-
-    def __init__(self, message):
-        self.message = message
-
-    def __str__(self):
-        return self.message

gnpy/api/exception/equipment_error.py

@@ -1,14 +0,0 @@
-# coding: utf-8
-
-
-class EquipmentError(Exception):
-    """ Exception raise for equipment error
-    Attributes:
-        message -- explanation of the error
-    """
-
-    def __init__(self, message):
-        self.message = message
-
-    def __str__(self):
-        return self.message

gnpy/api/exception/exception_handler.py

@@ -1,33 +0,0 @@
-# coding: utf-8
-import json
-import re
-
-import werkzeug
-
-from gnpy.api.model.error import Error
-
-_reaesc = re.compile(r'\x1b[^m]*m')
-
-
-def common_error_handler(exception):
-    """
-
-    :type exception: Exception
-
-    """
-    status_code = 500
-    if not isinstance(exception, werkzeug.exceptions.HTTPException):
-        exception = werkzeug.exceptions.InternalServerError()
-        exception.description = "Something went wrong on our side."
-    else:
-        status_code = exception.code
-    response = Error(message=exception.name, description=exception.description,
-                     code=status_code)
-
-    return werkzeug.Response(response=json.dumps(response.__dict__), status=status_code, mimetype='application/json')
-
-
-def bad_request_handler(exception):
-    response = Error(message='bad request', description=_reaesc.sub('', str(exception)),
-                     code=400)
-    return werkzeug.Response(response=json.dumps(response.__dict__), status=400, mimetype='application/json')

gnpy/api/exception/path_computation_error.py

@@ -1,14 +0,0 @@
-# coding: utf-8
-
-
-class PathComputationError(Exception):
-    """ Exception raise for path computation error error
-    Attributes:
-        message -- explanation of the error
-    """
-
-    def __init__(self, message):
-        self.message = message
-
-    def __str__(self):
-        return self.message

gnpy/api/exception/topology_error.py

@@ -1,14 +0,0 @@
-# coding: utf-8
-
-
-class TopologyError(Exception):
-    """ Exception raise for topology error
-    Attributes:
-        message -- explanation of the error
-    """
-
-    def __init__(self, message):
-        self.message = message
-
-    def __str__(self):
-        return self.message

gnpy/api/model/__init__.py

@@ -1 +0,0 @@
-# coding: utf-8

gnpy/api/model/error.py

@@ -1,17 +0,0 @@
-# coding: utf-8
-
-
-class Error:
-
-    def __init__(self, code: int = None, message: str = None, description: str = None):
-        """Error
-        :param code: The code of this Error.
-        :type code: int
-        :param message: The message of this Error.
-        :type message: str
-        :param description: The description of this Error.
-        :type description: str
-        """
-        self.code = code
-        self.message = message
-        self.description = description

gnpy/api/model/result.py

@@ -1,8 +0,0 @@
-# coding: utf-8
-
-
-class Result:
-
-    def __init__(self, message: str = None, description: str = None):
-        self.message = message
-        self.description = description

gnpy/api/rest_example.py

@@ -1,83 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-'''
-gnpy.tools.rest_example
-=======================
-
-GNPy as a rest API example
-'''
-
-import logging
-from logging.handlers import RotatingFileHandler
-
-import werkzeug
-from flask_injector import FlaskInjector
-from injector import singleton
-from werkzeug.exceptions import InternalServerError
-
-import gnpy.core.exceptions as exceptions
-from gnpy.api import app
-from gnpy.api.exception.exception_handler import bad_request_handler, common_error_handler
-from gnpy.api.exception.path_computation_error import PathComputationError
-from gnpy.api.exception.topology_error import TopologyError
-from gnpy.api.service import config_service
-from gnpy.api.service.encryption_service import EncryptionService
-from gnpy.api.service.equipment_service import EquipmentService
-from gnpy.api.service.path_request_service import PathRequestService
-
-_logger = logging.getLogger(__name__)
-
-
-def _init_logger():
-    handler = RotatingFileHandler('api.log', maxBytes=1024 * 1024, backupCount=5, encoding='utf-8')
-    ch = logging.StreamHandler()
-    logging.basicConfig(level=logging.INFO, handlers=[handler, ch],
-                        format="%(asctime)s %(levelname)s %(name)s(%(lineno)s) [%(threadName)s - %(thread)d] - %("
-                               "message)s")
-
-
-def _init_app(key):
-    app.register_error_handler(KeyError, bad_request_handler)
-    app.register_error_handler(TypeError, bad_request_handler)
-    app.register_error_handler(ValueError, bad_request_handler)
-    app.register_error_handler(exceptions.ConfigurationError, bad_request_handler)
-    app.register_error_handler(exceptions.DisjunctionError, bad_request_handler)
-    app.register_error_handler(exceptions.EquipmentConfigError, bad_request_handler)
-    app.register_error_handler(exceptions.NetworkTopologyError, bad_request_handler)
-    app.register_error_handler(exceptions.ServiceError, bad_request_handler)
-    app.register_error_handler(exceptions.SpectrumError, bad_request_handler)
-    app.register_error_handler(exceptions.ParametersError, bad_request_handler)
-    app.register_error_handler(AssertionError, bad_request_handler)
-    app.register_error_handler(InternalServerError, common_error_handler)
-    app.register_error_handler(TopologyError, bad_request_handler)
-    app.register_error_handler(PathComputationError, bad_request_handler)
-    for error_code in werkzeug.exceptions.default_exceptions:
-        app.register_error_handler(error_code, common_error_handler)
-    config = config_service.init_config()
-    config.add_section('SECRET')
-    config.set('SECRET', 'equipment', key)
-    app.config['properties'] = config
-
-
-def _configure(binder):
-    binder.bind(EquipmentService,
-                to=EquipmentService(EncryptionService(app.config['properties'].get('SECRET', 'equipment'))),
-                scope=singleton)
-    binder.bind(PathRequestService,
-                to=PathRequestService(EncryptionService(app.config['properties'].get('SECRET', 'equipment'))),
-                scope=singleton)
-    app.config['properties'].pop('SECRET', None)
-
-
-def main():
-    key = input('Enter encryption/decryption key: ')
-    _init_logger()
-    _init_app(key)
-    FlaskInjector(app=app, modules=[_configure])
-
-    app.run(host='0.0.0.0', port=8080, ssl_context='adhoc')
-
-
-if __name__ == '__main__':
-    main()

gnpy/api/route/__init__.py

@@ -1,2 +0,0 @@
-# coding: utf-8
-

gnpy/api/route/equipments_route.py

@@ -1,38 +0,0 @@
-# coding: utf-8
-import http
-import json
-
-from flask import request
-
-from gnpy.api import app
-from gnpy.api.exception.equipment_error import EquipmentError
-from gnpy.api.model.result import Result
-from gnpy.api.service.equipment_service import EquipmentService
-
-EQUIPMENT_BASE_PATH = '/api/v1/equipments'
-EQUIPMENT_ID_PATH = EQUIPMENT_BASE_PATH + '/<equipment_id>'
-
-
-@app.route(EQUIPMENT_BASE_PATH, methods=['POST'])
-def create_equipment(equipment_service: EquipmentService):
-    if not request.is_json:
-        raise EquipmentError('Request body is not json')
-    equipment_identifier = equipment_service.save_equipment(request.json)
-    response = Result(message='Equipment creation ok', description=equipment_identifier)
-    return json.dumps(response.__dict__), 201, {'location': EQUIPMENT_BASE_PATH + '/' + equipment_identifier}
-
-
-@app.route(EQUIPMENT_ID_PATH, methods=['PUT'])
-def update_equipment(equipment_id, equipment_service: EquipmentService):
-    if not request.is_json:
-        raise EquipmentError('Request body is not json')
-    equipment_identifier = equipment_service.update_equipment(request.json, equipment_id)
-    response = Result(message='Equipment update ok', description=equipment_identifier)
-    return json.dumps(response.__dict__), http.HTTPStatus.OK, {
-        'location': EQUIPMENT_BASE_PATH + '/' + equipment_identifier}
-
-
-@app.route(EQUIPMENT_ID_PATH, methods=['DELETE'])
-def delete_equipment(equipment_id, equipment_service: EquipmentService):
-    equipment_service.delete_equipment(equipment_id)
-    return '', http.HTTPStatus.NO_CONTENT

gnpy/api/route/path_request_route.py

@@ -1,63 +0,0 @@
-# coding: utf-8
-import http
-import os
-from pathlib import Path
-
-from flask import request
-
-from gnpy.api import app
-from gnpy.api.exception.equipment_error import EquipmentError
-from gnpy.api.exception.topology_error import TopologyError
-from gnpy.api.service import topology_service
-from gnpy.api.service.equipment_service import EquipmentService
-from gnpy.api.service.path_request_service import PathRequestService
-from gnpy.tools.json_io import _equipment_from_json, network_from_json
-from gnpy.topology.request import ResultElement
-
-PATH_COMPUTATION_BASE_PATH = '/api/v1/path-computation'
-AUTODESIGN_PATH = PATH_COMPUTATION_BASE_PATH + '/<path_computation_id>/autodesign'
-
-_examples_dir = Path(__file__).parent.parent.parent / 'example-data'
-
-
-@app.route(PATH_COMPUTATION_BASE_PATH, methods=['POST'])
-def compute_path(equipment_service: EquipmentService, path_request_service: PathRequestService):
-    data = request.json
-    service = data['gnpy-api:service']
-    if 'gnpy-api:topology' in data:
-        topology = data['gnpy-api:topology']
-    elif 'gnpy-api:topology_id' in data:
-        topology = topology_service.get_topology(data['gnpy-api:topology_id'])
-    else:
-        raise TopologyError('No topology found in request')
-    if 'gnpy-api:equipment' in data:
-        equipment = data['gnpy-api:equipment']
-    elif 'gnpy-api:equipment_id' in data:
-        equipment = equipment_service.get_equipment(data['gnpy-api:equipment_id'])
-    else:
-        raise EquipmentError('No equipment found in request')
-    equipment = _equipment_from_json(equipment,
-                                     os.path.join(_examples_dir, 'std_medium_gain_advanced_config.json'))
-    network = network_from_json(topology, equipment)
-
-    propagatedpths, reversed_propagatedpths, rqs, path_computation_id = path_request_service.path_requests_run(service,
-                                                                                                               network,
-                                                                                                               equipment)
-    # Generate the output
-    result = []
-    # assumes that list of rqs and list of propgatedpths have same order
-    for i, pth in enumerate(propagatedpths):
-        result.append(ResultElement(rqs[i], pth, reversed_propagatedpths[i]))
-    return {"result": {"response": [n.json for n in result]}}, 201, {
-        'location': AUTODESIGN_PATH.replace('<path_computation_id>', path_computation_id)}
-
-
-@app.route(AUTODESIGN_PATH, methods=['GET'])
-def get_autodesign(path_computation_id, path_request_service: PathRequestService):
-    return path_request_service.get_autodesign(path_computation_id), http.HTTPStatus.OK
-
-
-@app.route(AUTODESIGN_PATH, methods=['DELETE'])
-def delete_autodesign(path_computation_id, path_request_service: PathRequestService):
-    path_request_service.delete_autodesign(path_computation_id)
-    return '', http.HTTPStatus.NO_CONTENT

gnpy/api/route/status_route.py

@@ -1,7 +0,0 @@
-# coding: utf-8
-from gnpy.api import app
-
-
-@app.route('/api/v1/status', methods=['GET'])
-def api_status():
-    return {"version": "v1", "status": "ok"}, 200

gnpy/api/route/topology_route.py

@@ -1,43 +0,0 @@
-# coding: utf-8
-import http
-import json
-
-from flask import request
-
-from gnpy.api import app
-from gnpy.api.exception.topology_error import TopologyError
-from gnpy.api.model.result import Result
-from gnpy.api.service import topology_service
-
-TOPOLOGY_BASE_PATH = '/api/v1/topologies'
-TOPOLOGY_ID_PATH = TOPOLOGY_BASE_PATH + '/<topology_id>'
-
-
-@app.route(TOPOLOGY_BASE_PATH, methods=['POST'])
-def create_topology():
-    if not request.is_json:
-        raise TopologyError('Request body is not json')
-    topology_identifier = topology_service.save_topology(request.json)
-    response = Result(message='Topology creation ok', description=topology_identifier)
-    return json.dumps(response.__dict__), 201, {'location': TOPOLOGY_BASE_PATH + '/' + topology_identifier}
-
-
-@app.route(TOPOLOGY_ID_PATH, methods=['PUT'])
-def update_topology(topology_id):
-    if not request.is_json:
-        raise TopologyError('Request body is not json')
-    topology_identifier = topology_service.update_topology(request.json, topology_id)
-    response = Result(message='Topology update ok', description=topology_identifier)
-    return json.dumps(response.__dict__), http.HTTPStatus.OK, {
-        'location': TOPOLOGY_BASE_PATH + '/' + topology_identifier}
-
-
-@app.route(TOPOLOGY_ID_PATH, methods=['GET'])
-def get_topology(topology_id):
-    return topology_service.get_topology(topology_id), http.HTTPStatus.OK
-
-
-@app.route(TOPOLOGY_ID_PATH, methods=['DELETE'])
-def delete_topology(topology_id):
-    topology_service.delete_topology(topology_id)
-    return '', http.HTTPStatus.NO_CONTENT

gnpy/api/service/__init__.py

@@ -1 +0,0 @@
-# coding: utf-8

gnpy/api/service/config_service.py

@@ -1,45 +0,0 @@
-# coding: utf-8
-import configparser
-import os
-
-from flask import current_app
-
-from gnpy.api.exception.config_error import ConfigError
-
-
-def init_config(properties_file_path: str = os.path.join(os.path.dirname(__file__),
-                                                         'properties.ini')) -> configparser.ConfigParser:
-    """
-    Read config from properties_file_path
-    @param properties_file_path: the properties file to read
-    @return: config parser
-    """
-    if not os.path.exists(properties_file_path):
-        raise ConfigError('Properties file does not exist ' + properties_file_path)
-    config = configparser.ConfigParser()
-    config.read(properties_file_path)
-    return config
-
-
-def get_topology_dir() -> str:
-    """
-    Get the base dir where topologies are saved
-    @return: the directory of topologies
-    """
-    return current_app.config['properties'].get('DIRECTORY', 'topology')
-
-
-def get_equipment_dir() -> str:
-    """
-    Get the base dir where equipments are saved
-    @return: the directory of equipments
-    """
-    return current_app.config['properties'].get('DIRECTORY', 'equipment')
-
-
-def get_autodesign_dir() -> str:
-    """
-    Get the base dir where autodesign are saved
-    @return: the directory of equipments
-    """
-    return current_app.config['properties'].get('DIRECTORY', 'autodesign')

gnpy/api/service/encryption_service.py

@@ -1,13 +0,0 @@
-# coding: utf-8
-from cryptography.fernet import Fernet
-
-
-class EncryptionService:
-    def __init__(self, key):
-        self._fernet = Fernet(key)
-
-    def encrypt(self, data):
-        return self._fernet.encrypt(data)
-
-    def decrypt(self, data):
-        return self._fernet.decrypt(data)

gnpy/api/service/equipment_service.py

@@ -1,66 +0,0 @@
-# coding: utf-
-import json
-import os
-import uuid
-
-from injector import Inject
-
-from gnpy.api.exception.equipment_error import EquipmentError
-from gnpy.api.service import config_service
-from gnpy.api.service.encryption_service import EncryptionService
-
-
-class EquipmentService:
-
-    def __init__(self, encryption_service: EncryptionService):
-        self.encryption = encryption_service
-
-    def save_equipment(self, equipment):
-        """
-        Save equipment to file.
-        @param equipment: json content
-        @return: a UUID identifier to identify the equipment
-        """
-        equipment_identifier = str(uuid.uuid4())
-        # TODO: validate json content
-        self._write_equipment(equipment, equipment_identifier)
-        return equipment_identifier
-
-    def update_equipment(self, equipment, equipment_identifier):
-        """
-        Update equipment with identifier equipment_identifier.
-        @param equipment_identifier: the identifier of the equipment to be updated
-        @param equipment: json content
-        @return: a UUID identifier to identify the equipment
-        """
-        # TODO: validate json content
-        self._write_equipment(equipment, equipment_identifier)
-        return equipment_identifier
-
-    def _write_equipment(self, equipment, equipment_identifier):
-        equipment_dir = config_service.get_equipment_dir()
-        with(open(os.path.join(equipment_dir, '.'.join([equipment_identifier, 'json'])), 'wb')) as file:
-            file.write(self.encryption.encrypt(json.dumps(equipment).encode()))
-
-    def get_equipment(self, equipment_id: str) -> dict:
-        """
-        Get the equipment with id equipment_id
-        @param equipment_id:
-        @return: the equipment in json format
-        """
-        equipment_dir = config_service.get_equipment_dir()
-        equipment_file = os.path.join(equipment_dir, '.'.join([equipment_id, 'json']))
-        if not os.path.exists(equipment_file):
-            raise EquipmentError('Equipment with id {} does not exist '.format(equipment_id))
-        with(open(equipment_file, 'rb')) as file:
-            return json.loads(self.encryption.decrypt(file.read()))
-
-    def delete_equipment(self, equipment_id: str):
-        """
-        Delete equipment with id equipment_id
-        @param equipment_id:
-        """
-        equipment_dir = config_service.get_equipment_dir()
-        equipment_file = os.path.join(equipment_dir, '.'.join([equipment_id, 'json']))
-        if os.path.exists(equipment_file):
-            os.remove(equipment_file)

gnpy/api/service/path_request_service.py

@@ -1,100 +0,0 @@
-# -*- coding: utf-8 -*-
-import json
-import logging
-import os
-import uuid
-
-import gnpy.core.ansi_escapes as ansi_escapes
-from gnpy.api.exception.path_computation_error import PathComputationError
-from gnpy.api.service import config_service
-from gnpy.api.service.encryption_service import EncryptionService
-from gnpy.core.network import build_network
-from gnpy.core.utils import lin2db, automatic_nch
-from gnpy.tools.json_io import requests_from_json, disjunctions_from_json, network_to_json
-from gnpy.topology.request import (compute_path_dsjctn, requests_aggregation,
-                                   correct_json_route_list,
-                                   deduplicate_disjunctions, compute_path_with_disjunction)
-from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum
-
-_logger = logging.getLogger(__name__)
-
-
-class PathRequestService:
-
-    def __init__(self, encryption_service: EncryptionService):
-        self.encryption = encryption_service
-
-    def path_requests_run(self, service, network, equipment):
-        # Build the network once using the default power defined in SI in eqpt config
-        # TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
-        # spacing, f_min and f_max
-        p_db = equipment['SI']['default'].power_dbm
-
-        p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
-                                                 equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
-        build_network(network, equipment, p_db, p_total_db)
-        path_computation_identifier = str(uuid.uuid4())
-        autodesign_dir = config_service.get_autodesign_dir()
-        with(open(os.path.join(autodesign_dir, '.'.join([path_computation_identifier, 'json'])), 'wb')) as file:
-            file.write(self.encryption.encrypt(json.dumps(network_to_json(network)).encode()))
-        oms_list = build_oms_list(network, equipment)
-        rqs = requests_from_json(service, equipment)
-
-        # 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)
-            raise ValueError('Requests id ' + all_ids + ' are not unique')
-        rqs = correct_json_route_list(network, rqs)
-
-        # pths = compute_path(network, equipment, rqs)
-        dsjn = disjunctions_from_json(service)
-
-        # 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)
-
-        rqs, dsjn = requests_aggregation(rqs, dsjn)
-        # TODO export novel set of aggregated demands in a json file
-
-        _logger.info(f'{ansi_escapes.blue}The following services have been requested:{ansi_escapes.reset}' + str(rqs))
-
-        _logger.info(f'{ansi_escapes.blue}Computing all paths with constraints{ansi_escapes.reset}')
-        pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
-
-        _logger.info(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)
-        return propagatedpths, reversed_propagatedpths, rqs, path_computation_identifier
-
-    def get_autodesign(self, path_computation_id):
-        """
-        Get the autodesign with id topology_id
-        @param path_computation_id:
-        @return: the autodesign in json format
-        """
-        autodesign_dir = config_service.get_autodesign_dir()
-        autodesign_file = os.path.join(autodesign_dir, '.'.join([path_computation_id, 'json']))
-        if not os.path.exists(autodesign_file):
-            raise PathComputationError('Autodesign with id {} does not exist '.format(path_computation_id))
-        with(open(autodesign_file, 'rb')) as file:
-            return json.loads(self.encryption.decrypt(file.read()))
-
-    def delete_autodesign(self, path_computation_id: str):
-        """
-        Delete autodesign with id equipment_id
-        @param path_computation_id:
-        """
-        autodesign_dir = config_service.get_autodesign_dir()
-        autodesign_file = os.path.join(autodesign_dir, '.'.join([path_computation_id, 'json']))
-        if os.path.exists(autodesign_file):
-            os.remove(autodesign_file)

gnpy/api/service/properties.ini

@@ -1,4 +0,0 @@
-[DIRECTORY]
-topology: /opt/application/oopt-gnpy/topology
-equipment: /opt/application/oopt-gnpy/equipment
-autodesign: /opt/application/oopt-gnpy/autodesign

gnpy/api/service/topology_service.py

@@ -1,62 +0,0 @@
-# coding: utf-
-import json
-import os
-import uuid
-
-from gnpy.api.exception.topology_error import TopologyError
-from gnpy.api.service import config_service
-
-
-def save_topology(topology):
-    """
-    Save topology to file.
-    @param topology: json content
-    @return: a UUID identifier to identify the topology
-    """
-    topology_identifier = str(uuid.uuid4())
-    # TODO: validate json content
-    _write_topology(topology, topology_identifier)
-    return topology_identifier
-
-
-def update_topology(topology, topology_identifier):
-    """
-    Update topology with identifier topology_identifier.
-    @param topology_identifier: the identifier of the topology to be updated
-    @param topology: json content
-    @return: a UUID identifier to identify the topology
-    """
-    # TODO: validate json content
-    _write_topology(topology, topology_identifier)
-    return topology_identifier
-
-
-def _write_topology(topology, topology_identifier):
-    topology_dir = config_service.get_topology_dir()
-    with(open(os.path.join(topology_dir, '.'.join([topology_identifier, 'json'])), 'w')) as file:
-        json.dump(topology, file)
-
-
-def get_topology(topology_id: str) -> dict:
-    """
-    Get the topology with id topology_id
-    @param topology_id:
-    @return: the topology in json format
-    """
-    topology_dir = config_service.get_topology_dir()
-    topology_file = os.path.join(topology_dir, '.'.join([topology_id, 'json']))
-    if not os.path.exists(topology_file):
-        raise TopologyError('Topology with id {} does not exist '.format(topology_id))
-    with(open(topology_file, 'r')) as file:
-        return json.load(file)
-
-
-def delete_topology(topology_id: str):
-    """
-    Delete topology with id topology_id
-    @param topology_id:
-    """
-    topology_dir = config_service.get_topology_dir()
-    topology_file = os.path.join(topology_dir, '.'.join([topology_id, 'json']))
-    if os.path.exists(topology_file):
-        os.remove(topology_file)

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 +1,17 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+# SPDX-License-Identifier: BSD-3-Clause
+# gnpy.core.ansi_escapes: A random subset of ANSI terminal escape codes for colored messages
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
+"""
 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 +1,137 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+# SPDX-License-Identifier: BSD-3-Clause
+# gnpy.core.equipment: functionality for specifying equipment
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
+"""
 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) -> List[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
+
+
+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/exceptions.py

@@ -1,6 +1,11 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+# SPDX-License-Identifier: BSD-3-Clause
+# gnpy.core.exceptions: Exceptions thrown by other gnpy modules
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
 """
 gnpy.core.exceptions
 ====================

gnpy/core/info.py

@@ -1,6 +1,11 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+# SPDX-License-Identifier: BSD-3-Clause
+# gnpy.core.info: classes for modelling Spectral Information
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
 """
 gnpy.core.info
 ==============
@@ -8,49 +13,421 @@ 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, Optional
+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) -> Optional[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

@@ -1,17 +1,24 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+# SPDX-License-Identifier: BSD-3-Clause
+# gnpy.core.parameters: parameters to configure standard network elements
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
 """
 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 +35,235 @@ 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 +271,95 @@ 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
+            self._pmd_coef_defined = kwargs.get('pmd_coef_defined', kwargs['pmd_coef'] is True)
+
+            # 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 +392,10 @@ 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 +404,10 @@ 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
@@ -226,10 +416,28 @@ 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
 
+    @property
+    def pmd_coef_defined(self):
+        return self._pmd_coef_defined
+
     @property
     def ref_wavelength(self):
         return self._ref_wavelength
@@ -238,14 +446,6 @@ 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 +455,277 @@ 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. %s, %s",
+                        self.nf_ripple.size, self.gain_ripple.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,
+        'in_voa': 0,
+        '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})')
+
+
+DEFAULT_EDFA_CONFIG = {
+    "nf_ripple": [
+        0.0
+    ],
+    "gain_ripple": [
+        0.0
+    ],
+    "f_min": 191.275e12,
+    "f_max": 196.125e12,
+    "dgt": [
+        1.0, 1.017807767853702, 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
+    ]
+}
+
+
+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

@@ -1,6 +1,11 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+# SPDX-License-Identifier: BSD-3-Clause
+# gnpy.core.utils: utility functions that are used with gnpy
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
 """
 gnpy.core.utils
 ===============
@@ -9,8 +14,10 @@ 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, Union, Dict
 
 from gnpy.core.exceptions import ConfigurationError
 
@@ -106,7 +113,99 @@ 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'
+
+    The finest step is fixed at 0.01; smaller values are silently changed to 0.01.
+
+    >>> round2float(123.456, 1000)
+    0.0
+    >>> round2float(123.456, 100)
+    100.0
+    >>> round2float(123.456, 10)
+    120.0
+    >>> round2float(123.456, 1)
+    123.0
+    >>> round2float(123.456, 0.1)
+    123.5
+    >>> round2float(123.456, 0.01)
+    123.46
+    >>> round2float(123.456, 0.001)
+    123.46
+    >>> round2float(123.249, 0.5)
+    123.0
+    >>> round2float(123.250, 0.5)
+    123.0
+    >>> round2float(123.251, 0.5)
+    123.5
+    >>> round2float(123.300, 0.2)
+    123.2
+    >>> round2float(123.301, 0.2)
+    123.4
+    """
     step = round(step, 1)
     if step >= 0.01:
         number = round(number / step, 0)
@@ -120,25 +219,39 @@ 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
@@ -156,9 +269,9 @@ 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
@@ -173,8 +286,7 @@ 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
@@ -200,7 +312,7 @@ 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}}
@@ -222,6 +334,35 @@ def merge_amplifier_restrictions(dict1, dict2):
     return copy_dict1
 
 
+def use_pmd_coef(dict1: dict, dict2: dict):
+    """If Fiber dict1 is missing the pmd_coef value then use the one of dict2.
+    In addition records in "pmd_coef_defined" key the pmd_coef if is was defined in dict1.
+
+    :param dict1: A dictionnary that contains "pmd_coef" key.
+    :type dict1: dict
+    :param dict2: Another dictionnary that contains "pmd_coef" key.
+    :type dict2: dict
+
+    >>> dict1 = {'a': 1, 'pmd_coef': 1.5e-15}
+    >>> dict2 = {'a': 2, 'pmd_coef': 2e-15}
+    >>> use_pmd_coef(dict1, dict2)
+    >>> dict1
+    {'a': 1, 'pmd_coef': 1.5e-15, 'pmd_coef_defined': True}
+
+    >>> dict1 = {'a': 1}
+    >>> use_pmd_coef(dict1, dict2)
+    >>> dict1
+    {'a': 1, 'pmd_coef_defined': False, 'pmd_coef': 2e-15}
+    """
+    if 'pmd_coef' in dict1 and not dict1['pmd_coef'] \
+            or ('pmd_coef' not in dict1 and 'pmd_coef' in dict2):
+        dict1['pmd_coef_defined'] = False
+        dict1['pmd_coef'] = dict2['pmd_coef']
+    elif 'pmd_coef' in dict1 and dict1['pmd_coef']:
+        dict1['pmd_coef_defined'] = True
+    # all other case do not need any change
+
+
 def silent_remove(this_list, elem):
     """Remove matching elements from a list without raising ValueError
 
@@ -295,3 +436,390 @@ 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 unique_ordered(elements):
+    """
+    """
+    unique_elements = []
+    for element in elements:
+        if element not in unique_elements:
+            unique_elements.append(element)
+    return unique_elements
+
+
+def convert_empty_to_none(json_data: Union[list, dict]) -> dict:
+    """Convert all instances of "a": [None] into "a": None
+
+    :param json_data: the input data.
+    :type json_data: dict
+    :return: the converted data.
+    :rtype: dict
+
+    >>> json_data = {
+    ...     "uid": "[east edfa in Lannion",
+    ...     "type_variety": "multiband_booster",
+    ...     "metadata": {
+    ...         "location": {
+    ...             "latitude": 0.000000,
+    ...             "longitude": 0.000000,
+    ...             "city": "Zion",
+    ...             "region": ""
+    ...         }
+    ...     },
+    ...     "type": "Multiband_amplifier",
+    ...     "amplifiers": [{
+    ...             "type_variety": "multiband_booster_LOW_C",
+    ...             "operational": {
+    ...                 "gain_target": 12.22,
+    ...                 "delta_p": 4.19,
+    ...                 "out_voa": [None],
+    ...                 "tilt_target": 0.00,
+    ...                 "f_min": 191.3,
+    ...                 "f_max": 196.1
+    ...             }
+    ...         }, {
+    ...             "type_variety": "multiband_booster_LOW_L",
+    ...             "operational": {
+    ...                 "gain_target": 12.05,
+    ...                 "delta_p": 4.19,
+    ...                 "out_voa": [None],
+    ...                 "tilt_target": 0.00,
+    ...                 "f_min": 186.1,
+    ...                 "f_max": 190.9
+    ...             }
+    ...         }
+    ...     ]
+    ... }
+    >>> convert_empty_to_none(json_data)
+    {'uid': '[east edfa in Lannion', 'type_variety': 'multiband_booster', \
+'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}}, \
+'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'multiband_booster_LOW_C', \
+'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0, \
+'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'multiband_booster_LOW_L', \
+'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0, \
+'f_min': 186.1, 'f_max': 190.9}}]}
+
+    """
+    if isinstance(json_data, dict):
+        for key, value in json_data.items():
+            json_data[key] = convert_empty_to_none(value)
+    elif isinstance(json_data, list):
+        if len(json_data) == 1 and json_data[0] is None:
+            return None
+        for i, elem in enumerate(json_data):
+            json_data[i] = convert_empty_to_none(elem)
+    return json_data
+
+
+def convert_none_to_empty(json_data: Union[list, dict]) -> dict:
+    """Convert all instances of "a": None into "a": [None], to be compliant with RFC7951.
+
+    :param json_data: the input data.
+    :type json_data: dict
+    :return: the converted data.
+    :rtype: dict
+
+    >>> a = {'uid': '[east edfa in Lannion', 'type_variety': 'multiband_booster',
+    ... 'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}},
+    ... 'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'multiband_booster_LOW_C',
+    ... 'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0,
+    ... 'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'multiband_booster_LOW_L',
+    ... 'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0,
+    ... 'f_min': 186.1, 'f_max': 190.9}}]}
+    >>> convert_none_to_empty(a)
+    {'uid': '[east edfa in Lannion', 'type_variety': 'multiband_booster', \
+'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}}, \
+'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'multiband_booster_LOW_C', \
+'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': [None], 'tilt_target': 0.0, \
+'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'multiband_booster_LOW_L', \
+'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': [None], 'tilt_target': 0.0, \
+'f_min': 186.1, 'f_max': 190.9}}]}
+
+    """
+    if json_data == [None]:
+        # already conformed
+        return json_data
+    if isinstance(json_data, dict):
+        for key, value in json_data.items():
+            json_data[key] = convert_none_to_empty(value)
+    elif isinstance(json_data, list):
+        for i, elem in enumerate(json_data):
+            json_data[i] = convert_none_to_empty(elem)
+    elif json_data is None:
+        return [None]
+    return json_data
+
+
+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 filter_valid_amp_bands(amp_bands: List[List[dict]]) -> List[List[dict]]:
+    """Filter out invalid amplifier bands that lack f_min or f_max.
+
+    :param amp_bands: A list of lists containing amplifier band dictionaries.
+    :type amp_bands: List[List[dict]]
+    :return: A filtered list of amplifier bands that contain valid f_min and f_max.
+    :rtype: List[List[dict]]
+    """
+    return [amp for amp in amp_bands if all(band.get('f_min') is not None and band.get('f_max') is not None
+                                            for band in amp)]
+
+
+def remove_duplicates(amp_bands: List[List[dict]]) -> List[List[dict]]:
+    """Remove duplicate amplifier bands.
+
+    :param amp_bands: A list of lists containing amplifier band dictionaries.
+    :type amp_bands: List[List[dict]]
+    :return: A list of unique amplifier bands.
+    :rtype: List[List[dict]]
+    """
+    unique_amp_bands = []
+    for amp in amp_bands:
+        if amp not in unique_amp_bands:
+            unique_amp_bands.append(amp)
+    return unique_amp_bands
+
+
+def calculate_spacing(first: dict, second: dict, default_spacing: float, default_design_bands: Union[List[Dict], None],
+                      f_min: float, f_max: float) -> float:
+    """Calculate the spacing for the given frequency range.
+
+    :param first: The first amplifier band dictionary.
+    :type first: dict
+    :param second: The second amplifier band dictionary.
+    :type second: dict
+    :param default_spacing: The default spacing to use if no specific spacing can be determined.
+    :type default_spacing: float
+    :param default_design_bands: Optional list of design bands to determine spacing from.
+    :type default_design_bands: Union[List[Dict], None]
+    :param f_min: The minimum frequency of the range.
+    :type f_min: float
+    :param f_max: The maximum frequency of the range.
+    :type f_max: float
+    :return: The calculated spacing for the given frequency range.
+    :rtype: float
+    """
+    if first.get('spacing') is not None and second.get('spacing') is not None:
+        return max(first['spacing'], second['spacing'])
+    elif first.get('spacing') is not None:
+        return first['spacing']
+    elif second.get('spacing') is not None:
+        return second['spacing']
+    elif default_design_bands:
+        temp = get_spacing_from_band(default_design_bands, f_min, f_max)
+        return temp if temp is not None else default_spacing
+    return default_spacing
+
+
+def find_common_range(amp_bands: List[List[dict]], default_band_f_min: Union[float, None],
+                      default_band_f_max: Union[float, None], default_spacing: float,
+                      default_design_bands: Union[List[Dict], None] = None) -> List[dict]:
+    """
+    Find the common frequency range of amplifier bands.
+
+    If there are no amplifiers in the path, then use the default band parameters.
+
+    :param amp_bands: A list of lists containing amplifier band dictionaries, each with 'f_min', 'f_max',
+                      and optionally 'spacing'.
+    :type amp_bands: List[List[dict]]
+    :param default_band_f_min: The minimum frequency of the default band.
+    :type default_band_f_min: Union[float, None]
+    :param default_band_f_max: The maximum frequency of the default band.
+    :type default_band_f_max: Union[float, None]
+    :param default_spacing: The default spacing to use if no specific spacing can be determined.
+    :type default_spacing: float
+    :param default_design_bands: Optional list of design bands to determine spacing from.
+    :type default_design_bands: Union[List[Dict], None]
+    :return: A list of dictionaries representing the common frequency ranges with their respective spacings.
+    :rtype: List[dict]
+
+    >>> amp_bands = [[{'f_min': 191e12, 'f_max' : 195e12, 'spacing': 70e9}, {'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, 50e9)
+    [{'f_min': 186000000000000.0, 'f_max': 189000000000000.0, 'spacing': 50000000000.0}, \
+{'f_min': 192000000000000.0, 'f_max': 193000000000000.0, 'spacing': 70000000000.0}]
+
+    >>> 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, 50e9)
+    [{'f_min': 186000000000000.0, 'f_max': 189000000000000.0, 'spacing': 50000000000.0}]
+    """
+    # Step 1: Filter and sort amplifier bands
+    _amp_bands = [sorted(amp, key=lambda x: x['f_min']) for amp in filter_valid_amp_bands(amp_bands)]
+    unique_amp_bands = remove_duplicates(_amp_bands)
+
+    # Step 2: Handle cases with no valid bands
+    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 []
+        return [{'f_min': default_band_f_min, 'f_max': default_band_f_max, 'spacing': None}]
+
+    # Step 3: Calculate common frequency range
+    for bands in unique_amp_bands:
+        new_common_range = []
+        for first in common_range:
+            for second in bands:
+                f_min = max(first['f_min'], second['f_min'])
+                f_max = min(first['f_max'], second['f_max'])
+                if f_min < f_max:
+                    spacing = calculate_spacing(first, second, default_spacing, default_design_bands, f_min, f_max)
+                    new_common_range.append({'f_min': f_min, 'f_max': f_max, 'spacing': spacing})
+
+        common_range = new_common_range
+
+    return sorted(common_range, key=lambda x: x['f_min'])
+
+
+def transform_data(data: str) -> Union[List[int], None]:
+    """Transforms a float into an list of one integer or a string separated by "|" into a list of integers.
+
+    Args:
+        data (float or str): The data to transform.
+
+    Returns:
+        list of int: The transformed data as a list of integers.
+
+    Examples:
+        >>> transform_data(5.0)
+        [5]
+
+        >>> transform_data('1 | 2 | 3')
+        [1, 2, 3]
+    """
+    if isinstance(data, float):
+        return [int(data)]
+    if isinstance(data, str):
+        return [int(x) for x in data.split(' | ')]
+    return None
+
+
+def convert_pmd_lineic(pmd: Union[float, None], length: float, length_unit: str) -> Union[float, None]:
+    """Convert PMD value of the span in ps into pmd_lineic in s/sqrt(km)
+
+    :param pmd: value in ps
+    :type pmd: Union[float, None]
+    :param length: value in length_unit
+    :type length: float
+    :param length_unit: 'km' or 'm'
+    :type length_unit: str
+    :return: lineic PMD s/sqrt(m)
+    :rtype: Union[float, None]
+
+    >>> convert_pmd_lineic(10, 0.001, 'km')
+    1e-11
+    """
+    if pmd:
+        return pmd * 1e-12 / sqrt(convert_length(length, length_unit))
+    return None
+def get_spacing_from_band(design_bands: List[Dict], f_min, f_max):
+    """Retrieve the spacing for a frequency range based on design bands.
+
+    This function checks if the midpoint of the provided frequency range (f_min, f_max)
+    falls within any of the design bands. If it does, the corresponding spacing is returned.
+
+    :param design_bands: A list of design band dictionaries, each containing 'f_min', 'f_max', and 'spacing'.
+    :type design_bands: List[Dict]
+    :param f_min: The minimum frequency of the range.
+    :type f_min: float
+    :param f_max: The maximum frequency of the range.
+    :type f_max: float
+    :return: The spacing corresponding to the design band that contains the midpoint of the range,
+             or None if no such band exists.
+    :rtype: Union[float, None]
+    """
+    midpoint = (f_min + f_max) / 2
+    for band in design_bands:
+        if midpoint >= band['f_min'] and midpoint <= band['f_max']:
+            return band['spacing']
+    return None
+
+
+def reorder_per_degree_design_bands(per_degree_design_bands: dict):
+    """Sort the design bands for each degree by their minimum frequency (f_min).
+
+    This function modifies the input dictionary in place, sorting the design bands for each unique identifier.
+
+    :param per_degree_design_bands: A dictionary where keys are unique identifiers and values are lists of design band dictionaries.
+    :type per_degree_design_bands: Dict[str, List[Dict]]
+    """
+    for uid, design_bands in per_degree_design_bands.items():
+        per_degree_design_bands[uid] = sorted(design_bands, key=lambda x: x['f_min'])

gnpy/example-data/Juniper-BoosterHG.json

@@ -1,160 +1,160 @@
 {
-      "nf_fit_coeff": [
-        0.0008,
-        0.0272,
-        -0.2249,
-        6.4902
-       ],
-      "f_min": 191.35e12,
-      "f_max": 196.1e12,
-       "nf_ripple": [
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0,
-        0.0
-    ],
-    "gain_ripple": [
-        0.15017064489112,
-        0.14157768006701,
-        0.00223094639866,
-        -0.06701528475711,
-        -0.05982935510889,
-        -0.01028161641541,
-        0.02740682579566,
-        0.02795958961474,
-        0.00107516750419,
-        -0.02199015912898,
-        -0.00877407872698,
-        0.0453465242881,
-        0.1204721524288,
-        0.18936662479061,
-        0.23826109715241,
-        0.26956762981574,
-        0.27836159966498,
-        0.26941687604691,
-        0.23579878559464,
-        0.18147717755444,
-        0.1191656197655,
-        0.05921587102177,
-        0.01509526800668,
-        -0.01053287269681,
-        -0.02475397822447,
-        -0.01847257118928,
-        -0.00420121440538,
-        0.01584903685091,
-        0.0399193886097,
-        0.04494451423784,
-        0.04961788107202,
-        0.03378873534338,
-        0.01027114740367,
-        -0.01319618927973,
-        -0.04962835008375,
-        -0.0765630234506,
-        -0.10606051088777,
-        -0.13550774706866,
-        -0.15460322445561,
-        -0.17113588777219,
-        -0.18053287269681,
-        -0.18324644053602,
-        -0.19440221943049,
-        -0.20897508375209,
-        -0.23575900335007,
-        -0.25188965661642,
-        -0.22244242043552,
-        -0.15656302345061
-    ],
-    "dgt": [
-        2.4553191172498,
-        2.44342862248888,
-        2.41879254989742,
-        2.38192717604575,
-        2.33147727493671,
-        2.26678136721453,
-        2.19013043016015,
-        2.10336369905543,
-        2.01414465424155,
-        1.92915262384742,
-        1.85543800978691,
-        1.79748596476494,
-        1.75428006928365,
-        1.72461030013125,
-        1.70379790088896,
-        1.68845480656382,
-        1.6761448370895,
-        1.66286684904577,
-        1.64799163036252,
-        1.63068023161292,
-        1.61073904908309,
-        1.58973304612691,
-        1.56750088631614,
-        1.54578500307573,
-        1.5242627235492,
-        1.50335352244996,
-        1.48420288841848,
-        1.46637521309853,
-        1.44977369463316,
-        1.43476940680732,
-        1.42089447397912,
-        1.40864903907609,
-        1.3966294751726,
-        1.38430337205545,
-        1.3710092503689,
-        1.35690844654118,
-        1.3405812000038,
-        1.32210817897091,
-        1.30069883494415,
-        1.27657903892303,
-        1.24931318255134,
-        1.21911100318577,
-        1.18632744096844,
-        1.15209185089701,
-        1.11575888725852,
-        1.07773189112355,
-        1.03941448941778,
-        1.0
-    ]
+  "nf_fit_coeff": [
+    0.0008,
+    0.0272,
+    -0.2249,
+    6.4902
+  ],
+  "f_min": 191.4e12,
+  "f_max": 196.1e12,
+  "nf_ripple": [
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0,
+    0.0
+  ],
+  "gain_ripple": [
+    -0.15656302345061,
+    -0.22244242043552,
+    -0.25188965661642,
+    -0.23575900335007,
+    -0.20897508375209,
+    -0.19440221943049,
+    -0.18324644053602,
+    -0.18053287269681,
+    -0.17113588777219,
+    -0.15460322445561,
+    -0.13550774706866,
+    -0.10606051088777,
+    -0.0765630234506,
+    -0.04962835008375,
+    -0.01319618927973,
+    0.01027114740367,
+    0.03378873534338,
+    0.04961788107202,
+    0.04494451423784,
+    0.0399193886097,
+    0.01584903685091,
+    -0.00420121440538,
+    -0.01847257118928,
+    -0.02475397822447,
+    -0.01053287269681,
+    0.01509526800668,
+    0.05921587102177,
+    0.1191656197655,
+    0.18147717755444,
+    0.23579878559464,
+    0.26941687604691,
+    0.27836159966498,
+    0.26956762981574,
+    0.23826109715241,
+    0.18936662479061,
+    0.1204721524288,
+    0.0453465242881,
+    -0.00877407872698,
+    -0.02199015912898,
+    0.00107516750419,
+    0.02795958961474,
+    0.02740682579566,
+    -0.01028161641541,
+    -0.05982935510889,
+    -0.06701528475711,
+    0.00223094639866,
+    0.14157768006701,
+    0.15017064489112
+  ],
+  "dgt": [
+    1.0,
+    1.03941448941778,
+    1.07773189112355,
+    1.11575888725852,
+    1.15209185089701,
+    1.18632744096844,
+    1.21911100318577,
+    1.24931318255134,
+    1.27657903892303,
+    1.30069883494415,
+    1.32210817897091,
+    1.3405812000038,
+    1.35690844654118,
+    1.3710092503689,
+    1.38430337205545,
+    1.3966294751726,
+    1.40864903907609,
+    1.42089447397912,
+    1.43476940680732,
+    1.44977369463316,
+    1.46637521309853,
+    1.48420288841848,
+    1.50335352244996,
+    1.5242627235492,
+    1.54578500307573,
+    1.56750088631614,
+    1.58973304612691,
+    1.61073904908309,
+    1.63068023161292,
+    1.64799163036252,
+    1.66286684904577,
+    1.6761448370895,
+    1.68845480656382,
+    1.70379790088896,
+    1.72461030013125,
+    1.75428006928365,
+    1.79748596476494,
+    1.85543800978691,
+    1.92915262384742,
+    2.01414465424155,
+    2.10336369905543,
+    2.19013043016015,
+    2.26678136721453,
+    2.33147727493671,
+    2.38192717604575,
+    2.41879254989742,
+    2.44342862248888,
+    2.4553191172498
+  ]
 }

gnpy/example-data/create_eqpt_sheet.py

@@ -1,6 +1,11 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
+# SPDX-License-Identifier: BSD-3-Clause
+# Utility functions that creates an Eqpt sheet template
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
 """
 create_eqpt_sheet.py
 ====================

gnpy/example-data/default_edfa_config.json

@@ -1,106 +0,0 @@
-{
-    "nf_ripple": [
-        0.0
-    ],
-    "gain_ripple": [
-        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,
-        1.017807767853702,
-        1.0
-    ]
-}

gnpy/example-data/edfa_example_network.json

@@ -1,80 +1,81 @@
 {
-    "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,
+        "pmd_coef": 3.0e-15
+      },
+      "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/edfa_model/build_oa_json.py

@@ -1,5 +1,11 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+
+# SPDX-License-Identifier: BSD-3-Clause
+# update an existing json file with all the 96ch txt files for a given amplifier type
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
 """
 Created on Tue Jan 30 12:32:00 2018
 

gnpy/example-data/eqpt_config.json

@@ -1,312 +1,444 @@
-{     "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": "low_noise",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 12,
-            "p_max": 22,
-            "nf_coef": [-8.104e-4,-6.221e-2,-5.889e-1,37.62],
-            "allowed_for_design": false
-            },          
-            {
-            "type_variety": "standard",
-            "type_def": "openroadm",
-            "gain_flatmax": 27,
-            "gain_min": 12,
-            "p_max": 22,
-            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
-            "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,
+      "use_si_channel_count_for_design": true
+    }
+  ],
+  "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_reduced",
+            "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_bis",
+            "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

@@ -0,0 +1,371 @@
+{
+  "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": [
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 18e3,
+              "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": "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

@@ -0,0 +1,441 @@
+{
+  "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": [
+            {
+              "chromatic_dispersion": 4e3,
+              "penalty_value": 0
+            },
+            {
+              "chromatic_dispersion": 18e3,
+              "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": "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": [
+            {
+              "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
+            }
+          ],
+          "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/extra_eqpt_config.json

@@ -0,0 +1,74 @@
+{
+  "Edfa": [
+    {
+      "type_variety": "user_defined",
+      "type_def": "variable_gain",
+      "f_min": 192.0e12,
+      "f_max": 195.9e12,
+      "gain_flatmax": 25,
+      "gain_min": 15,
+      "p_max": 21,
+      "nf_min": 6,
+      "nf_max": 10,
+      "default_config_from_json": "user_edfa_config.json",
+      "out_voa_auto": false,
+      "allowed_for_design": true
+    }, {
+      "type_variety": "user_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
+    }
+  ],
+  "Transceiver": [
+    {
+      "type_variety": "ZR400G",
+      "frequency": {
+        "min": 191.3e12,
+        "max": 196.1e12
+      },
+      "mode": [
+        {
+          "format": "SFF-ID:70",
+          "baud_rate": 60138546798,
+          "OSNR": 24,
+          "bit_rate": 400e9,
+          "roll_off": 0.2,
+          "tx_osnr": 34,
+          "min_spacing": 75e9,
+          "penalties": [
+            {
+              "chromatic_dispersion": 20e3,
+              "penalty_value": 0.5
+            },
+            {
+              "chromatic_dispersion": 0,
+              "penalty_value": 0
+            },
+            {
+              "pmd": 20,
+              "penalty_value": 0.5
+            },
+            {
+              "pdl": 1.5,
+              "penalty_value": 0
+            },
+            {
+              "pdl": 3.5,
+              "penalty_value": 1.8
+            },
+            {
+              "pdl": 3,
+              "penalty_value": 1.3
+            }
+          ],
+          "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/meshTopologyExampleV2.json

@@ -624,6 +624,70 @@
         "con_out": null
       }
     },
+    {
+      "uid": "west edfa in Quimper",
+      "metadata": {
+        "location": {
+          "city": "Quimper",
+          "region": "RLD",
+          "latitude": 1.0,
+          "longitude": 1.0
+        }
+      },
+      "type": "Edfa",
+      "operational": {
+        "gain_target": null,
+        "tilt_target": 0
+      }
+    },
+    {
+      "uid": "west edfa in Ploermel",
+      "metadata": {
+        "location": {
+          "city": "Ploermel",
+          "region": "RLD",
+          "latitude": 1.0,
+          "longitude": 2.0
+        }
+      },
+      "type": "Edfa",
+      "operational": {
+        "gain_target": null,
+        "tilt_target": 0
+      }
+    },
+    {
+      "uid": "east edfa in Quimper",
+      "metadata": {
+        "location": {
+          "city": "Quimper",
+          "region": "RLD",
+          "latitude": 1.0,
+          "longitude": 1.0
+        }
+      },
+      "type": "Edfa",
+      "operational": {
+        "gain_target": null,
+        "tilt_target": 0
+      }
+    },
+    {
+      "uid": "east edfa in Ploermel",
+      "metadata": {
+        "location": {
+          "city": "Ploermel",
+          "region": "RLD",
+          "latitude": 1.0,
+          "longitude": 2.0
+        }
+      },
+      "type": "Edfa",
+      "operational": {
+        "gain_target": null,
+        "tilt_target": 0
+      }
+    },
     {
       "uid": "east edfa in Lannion_CAS to Corlay",
       "metadata": {
@@ -1190,18 +1254,34 @@
     },
     {
       "from_node": "fiber (Brest_KLA → Quimper)-",
+      "to_node": "west edfa in Quimper"
+    },
+    {
+      "from_node": "west edfa in Quimper",
       "to_node": "fiber (Quimper → Lorient_KMA)-"
     },
     {
       "from_node": "fiber (Lorient_KMA → Quimper)-",
+      "to_node": "east edfa in Quimper"
+    },
+    {
+      "from_node": "east edfa in Quimper",
       "to_node": "fiber (Quimper → Brest_KLA)-"
     },
     {
       "from_node": "fiber (Vannes_KBE → Ploermel)-",
+      "to_node": "west edfa in Ploermel"
+    },
+    {
+      "from_node": "west edfa in Ploermel",
       "to_node": "fiber (Ploermel → Rennes_STA)-"
     },
     {
       "from_node": "fiber (Rennes_STA → Ploermel)-",
+      "to_node": "east edfa in Ploermel"
+    },
+    {
+      "from_node": "east edfa in Ploermel",
       "to_node": "fiber (Ploermel → Vannes_KBE)-"
     },
     {

gnpy/example-data/meshTopologyExampleV2_services.json

@@ -52,8 +52,8 @@
       "explicit-route-objects": {
         "route-object-include-exclude": [
           {
-            "explicit-route-usage": "route-include-ero",
             "index": 0,
+            "explicit-route-usage": "route-include-ero",
             "num-unnum-hop": {
               "node-id": "roadm Brest_KLA",
               "link-tp-id": "link-tp-id is not used",
@@ -61,8 +61,8 @@
             }
           },
           {
-            "explicit-route-usage": "route-include-ero",
             "index": 1,
+            "explicit-route-usage": "route-include-ero",
             "num-unnum-hop": {
               "node-id": "roadm Lannion_CAS",
               "link-tp-id": "link-tp-id is not used",
@@ -70,8 +70,8 @@
             }
           },
           {
-            "explicit-route-usage": "route-include-ero",
             "index": 2,
+            "explicit-route-usage": "route-include-ero",
             "num-unnum-hop": {
               "node-id": "roadm Lorient_KMA",
               "link-tp-id": "link-tp-id is not used",
@@ -79,8 +79,8 @@
             }
           },
           {
-            "explicit-route-usage": "route-include-ero",
             "index": 3,
+            "explicit-route-usage": "route-include-ero",
             "num-unnum-hop": {
               "node-id": "roadm Vannes_KBE",
               "link-tp-id": "link-tp-id is not used",

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

@@ -20,19 +20,18 @@
         "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"
           }
         ]
       },
       "params": {
-        "type_variety": "SSMF",
         "length": 80.0,
         "loss_coef": 0.2,
         "length_units": "km",
@@ -49,6 +48,21 @@
         }
       }
     },
+    {
+      "uid": "Fused1",
+      "type": "Fused",
+      "params": {
+        "loss": 0
+      },
+      "metadata": {
+        "location": {
+          "latitude": 1.5,
+          "longitude": 0,
+          "city": null,
+          "region": ""
+        }
+      }
+    },
     {
       "uid": "Edfa1",
       "type": "Edfa",
@@ -88,6 +102,10 @@
     },
     {
       "from_node": "Span1",
+      "to_node": "Fused1"
+    },
+    {
+      "from_node": "Fused1",
       "to_node": "Edfa1"
     },
     {

gnpy/example-data/service_pluggable.json

@@ -0,0 +1,22 @@
+{
+  "path-request": [
+    {
+      "request-id": "0",
+      "source": "trx Brest_KLA",
+      "destination": "trx Lannion_CAS",
+      "src-tp-id": "trx Brest_KLA",
+      "dst-tp-id": "trx Lannion_CAS",
+      "bidirectional": false,
+      "path-constraints": {
+        "te-bandwidth": {
+          "technology": "flexi-grid",
+          "trx_type": "ZR400G",
+          "trx_mode": "SFF-ID:70",
+          "spacing": 100000000000.0,
+          "tx_power": 0.0015,
+          "path_bandwidth": 400000000000.0
+        }
+      }
+    }
+  ]
+}

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

@@ -1,303 +1,304 @@
-{     "nf_fit_coeff": [
-      0.000168241,
-      0.0469961,
-      0.0359549,
-      5.82851
-      ],
-      "f_min": 191.35e12,
-      "f_max": 196.1e12,
-      "nf_ripple": [
-      -0.3110761646066259,
-      -0.3110761646066259,
-      -0.31110274831665313,
-      -0.31419329378173544,
-      -0.3172854168606314,
-      -0.32037911876162584,
-      -0.3233255190215882,
-      -0.31624321721895354,
-      -0.30915729645781326,
-      -0.30206775396360075,
-      -0.2949045115165272,
-      -0.26632156113294336,
-      -0.23772399031437283,
-      -0.20911178784023846,
-      -0.18048410390821285,
-      -0.14379944379052215,
-      -0.10709599992470213,
-      -0.07037375788020579,
-      -0.03372858157230583,
-      -0.015660302006048,
-      0.0024172385953583004,
-      0.020504047353947653,
-      0.03860013139908377,
-      0.05670549786742816,
-      0.07482015390297145,
-      0.0838762040768461,
-      0.09284481475528361,
-      0.1018180306253394,
-      0.11079585523492333,
-      0.1020395478432815,
-      0.09310160456603413,
-      0.08415906712621996,
-      0.07521193198077789,
-      0.0676340601339394,
-      0.06005437964543287,
-      0.052470799141237305,
-      0.044883315610536455,
-      0.037679759069084225,
-      0.03047647598902483,
-      0.02326948274513522,
-      0.01605877647020772,
-      0.021248462316134083,
-      0.02657315875107553,
-      0.03190060058247842,
-      0.03723078993416436,
-      0.04256372893215024,
-      0.047899419704645264,
-      0.03915515813685565,
-      0.030289222542492025,
-      0.021418708618354456,
-      0.012573926129294415,
-      0.006240488799898697,
-      -9.622162373026585e-05,
-      -0.006436207679519103,
-      -0.012779471908040341,
-      -0.02038153550619876,
-      -0.027999803010447587,
-      -0.035622012697103154,
-      -0.043236398934156144,
-      -0.04493583574805963,
-      -0.04663615264317309,
-      -0.048337350303318156,
-      -0.050039429413028365,
-      -0.051742390657545205,
-      -0.05342028484370278,
-      -0.05254242298580185,
-      -0.05166410580536087,
-      -0.05078533294804249,
-      -0.04990610405914272,
-      -0.05409792133358102,
-      -0.05832916277634124,
-      -0.06256260169582961,
-      -0.06660356886269536,
-      -0.04779792991567815,
-      -0.028982516728038848,
-      -0.010157321677553965,
-      0.00861320615127981,
-      0.01913736978785662,
-      0.029667009055877668,
-      0.04020212822983975,
-      0.050742731588695494,
-      0.061288823415841555,
-      0.07184040799914815,
-      0.1043252636301016,
-      0.13687829834471027,
-      0.1694483010211072,
-      0.202035284929368,
-      0.23624619427167134,
-      0.27048596623174515,
-      0.30474360397422756,
-      0.3390191214858807,
-      0.36358851509924695,
-      0.38814205928193013,
-      0.41270842850729195,
-      0.4372876328262819,
-      0.4372876328262819
-      ],
-      "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,
-      1.017807767853702,
-      1.0
-      ],
-      "gain_ripple": [
-      0.1359703369791596,
-      0.11822862697916037,
-      0.09542181697916163,
-      0.06245819697916133,
-      0.02602813697916062,
-      -0.0036199830208403228,
-      -0.018326963020840026,
-      -0.0246928330208398,
-      -0.016792253020838643,
-      -0.0028138630208403015,
-      0.017572956979162058,
-      0.038328296979159404,
-      0.054956336979159914,
-      0.0670723869791594,
-      0.07091459697916136,
-      0.07094413697916124,
-      0.07114372697916238,
-      0.07533675697916209,
-      0.08731066697916035,
-      0.10313984697916112,
-      0.12276252697916235,
-      0.14239527697916188,
-      0.15945681697916214,
-      0.1739275269791598,
-      0.1767381569791624,
-      0.17037189697916233,
-      0.15216302697916007,
-      0.13114358697916018,
-      0.10802383697916085,
-      0.08548825697916129,
-      0.06916723697916183,
-      0.05848224697916038,
-      0.05447361697916264,
-      0.05154489697916276,
-      0.04946107697915991,
-      0.04717897697916129,
-      0.04551704697916037,
-      0.04467697697916151,
-      0.04072968697916224,
-      0.03285456697916089,
-      0.023488786979161347,
-      0.01659282697915998,
-      0.013321846979160057,
-      0.011234826979162449,
-      0.01030063697916006,
-      0.00936596697916059,
-      0.00874012697916271,
-      0.00842583697916055,
-      0.006965146979162284,
-      0.0040435869791615175,
-      0.0007104669791608842,
-      -0.0015763130208377163,
-      -0.006936193020838033,
-      -0.016475303020840215,
-      -0.028748483020837767,
-      -0.039618433020837784,
-      -0.051112303020840244,
-      -0.06468462302083822,
-      -0.07868024302083754,
-      -0.09101254302083817,
-      -0.10103437302083762,
-      -0.11041488302083735,
-      -0.11916081302083725,
-      -0.12789859302083784,
-      -0.1353792530208402,
-      -0.14160178302083892,
-      -0.1455411330208385,
-      -0.1484450830208388,
-      -0.14823350302084037,
-      -0.14591937302083835,
-      -0.1409032730208395,
-      -0.13525493302083902,
-      -0.1279646530208396,
-      -0.11963431302083904,
-      -0.11089282302084058,
-      -0.1027863830208382,
-      -0.09717347302083823,
-      -0.09343261302083761,
-      -0.0913487130208388,
-      -0.08906007302083907,
-      -0.0865687230208394,
-      -0.08407607302083875,
-      -0.07844600302084004,
-      -0.06968090302083851,
-      -0.05947139302083926,
-      -0.05095282302083959,
-      -0.042428283020839785,
-      -0.03218106302083967,
-      -0.01819858302084043,
-      -0.0021726530208390216,
-      0.01393231697916164,
-      0.028098946979159933,
-      0.040326236979161934,
-      0.05257029697916238,
-      0.06479749697916048,
-      0.07704745697916238
-      ]
-}
+{
+  "nf_fit_coeff": [
+    0.000168241,
+    0.0469961,
+    0.0359549,
+    5.82851
+  ],
+  "f_min": 191.275e12,
+  "f_max": 196.125e12,
+  "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,
+    -0.050039429413028365,
+    -0.048337350303318156,
+    -0.04663615264317309,
+    -0.04493583574805963,
+    -0.043236398934156144,
+    -0.035622012697103154,
+    -0.027999803010447587,
+    -0.02038153550619876,
+    -0.012779471908040341,
+    -0.006436207679519103,
+    -9.622162373026585e-05,
+    0.006240488799898697,
+    0.012573926129294415,
+    0.021418708618354456,
+    0.030289222542492025,
+    0.03915515813685565,
+    0.047899419704645264,
+    0.04256372893215024,
+    0.03723078993416436,
+    0.03190060058247842,
+    0.02657315875107553,
+    0.021248462316134083,
+    0.01605877647020772,
+    0.02326948274513522,
+    0.03047647598902483,
+    0.037679759069084225,
+    0.044883315610536455,
+    0.052470799141237305,
+    0.06005437964543287,
+    0.0676340601339394,
+    0.07521193198077789,
+    0.08415906712621996,
+    0.09310160456603413,
+    0.1020395478432815,
+    0.11079585523492333,
+    0.1018180306253394,
+    0.09284481475528361,
+    0.0838762040768461,
+    0.07482015390297145,
+    0.05670549786742816,
+    0.03860013139908377,
+    0.020504047353947653,
+    0.0024172385953583004,
+    -0.015660302006048,
+    -0.03372858157230583,
+    -0.07037375788020579,
+    -0.10709599992470213,
+    -0.14379944379052215,
+    -0.18048410390821285,
+    -0.20911178784023846,
+    -0.23772399031437283,
+    -0.26632156113294336,
+    -0.2949045115165272,
+    -0.30206775396360075,
+    -0.30915729645781326,
+    -0.31624321721895354,
+    -0.3233255190215882,
+    -0.32037911876162584,
+    -0.3172854168606314,
+    -0.31419329378173544,
+    -0.31110274831665313,
+    -0.3110761646066259,
+    -0.3110761646066259
+  ],
+  "dgt": [
+    1.0,
+    1.017807767853702,
+    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
+  ],
+  "gain_ripple": [
+    0.07704745697916238,
+    0.06479749697916048,
+    0.05257029697916238,
+    0.040326236979161934,
+    0.028098946979159933,
+    0.01393231697916164,
+    -0.0021726530208390216,
+    -0.01819858302084043,
+    -0.03218106302083967,
+    -0.042428283020839785,
+    -0.05095282302083959,
+    -0.05947139302083926,
+    -0.06968090302083851,
+    -0.07844600302084004,
+    -0.08407607302083875,
+    -0.0865687230208394,
+    -0.08906007302083907,
+    -0.0913487130208388,
+    -0.09343261302083761,
+    -0.09717347302083823,
+    -0.1027863830208382,
+    -0.11089282302084058,
+    -0.11963431302083904,
+    -0.1279646530208396,
+    -0.13525493302083902,
+    -0.1409032730208395,
+    -0.14591937302083835,
+    -0.14823350302084037,
+    -0.1484450830208388,
+    -0.1455411330208385,
+    -0.14160178302083892,
+    -0.1353792530208402,
+    -0.12789859302083784,
+    -0.11916081302083725,
+    -0.11041488302083735,
+    -0.10103437302083762,
+    -0.09101254302083817,
+    -0.07868024302083754,
+    -0.06468462302083822,
+    -0.051112303020840244,
+    -0.039618433020837784,
+    -0.028748483020837767,
+    -0.016475303020840215,
+    -0.006936193020838033,
+    -0.0015763130208377163,
+    0.0007104669791608842,
+    0.0040435869791615175,
+    0.006965146979162284,
+    0.00842583697916055,
+    0.00874012697916271,
+    0.00936596697916059,
+    0.01030063697916006,
+    0.011234826979162449,
+    0.013321846979160057,
+    0.01659282697915998,
+    0.023488786979161347,
+    0.03285456697916089,
+    0.04072968697916224,
+    0.04467697697916151,
+    0.04551704697916037,
+    0.04717897697916129,
+    0.04946107697915991,
+    0.05154489697916276,
+    0.05447361697916264,
+    0.05848224697916038,
+    0.06916723697916183,
+    0.08548825697916129,
+    0.10802383697916085,
+    0.13114358697916018,
+    0.15216302697916007,
+    0.17037189697916233,
+    0.1767381569791624,
+    0.1739275269791598,
+    0.15945681697916214,
+    0.14239527697916188,
+    0.12276252697916235,
+    0.10313984697916112,
+    0.08731066697916035,
+    0.07533675697916209,
+    0.07114372697916238,
+    0.07094413697916124,
+    0.07091459697916136,
+    0.0670723869791594,
+    0.054956336979159914,
+    0.038328296979159404,
+    0.017572956979162058,
+    -0.0028138630208403015,
+    -0.016792253020838643,
+    -0.0246928330208398,
+    -0.018326963020840026,
+    -0.0036199830208403228,
+    0.02602813697916062,
+    0.06245819697916133,
+    0.09542181697916163,
+    0.11822862697916037,
+    0.1359703369791596
+  ]
+}

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

@@ -1,40 +1,43 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+# SPDX-License-Identifier: BSD-3-Clause
+# gnpy.tools.cli_examples: Common code for CLI examples
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
+"""
 gnpy.tools.cli_examples
 =======================
 
 Common code for CLI examples
-'''
+"""
 
 import argparse
-from json import dumps
 import logging
-import os.path
 import sys
-from math import ceil
-from numpy import linspace, mean
 from pathlib import Path
-import gnpy.core.ansi_escapes as ansi_escapes
+from typing import Union, List
+from math import ceil
+from numpy import mean
+
+from gnpy.core import ansi_escapes
 from gnpy.core.elements import Transceiver, Fiber, RamanFiber
-from gnpy.core.equipment import trx_mode_params
-import gnpy.core.exceptions as exceptions
-from gnpy.core.network import build_network
+from gnpy.core import exceptions
 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_equipments_and_configs, load_network, load_json, load_requests, save_network,
+                                requests_from_json, save_json, load_initial_spectrum, DEFAULT_EQPT_CONFIG)
 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'
+_default_config_files = ['example-data/std_medium_gain_advanced_config.json',
+                         'example-data/Juniper-BoosterHG.json',
+                         'parameters.DEFAULT_EDFA_CONFIG']
 _help_footer = '''
 This program is part of GNPy, https://github.com/TelecomInfraProject/oopt-gnpy
 
@@ -46,38 +49,60 @@ _help_fname_json_csv = 'FILE.(json|csv)'
 
 
 def show_example_data_dir():
+    """Print the example data directory path."""
     print(f'{_examples_dir}/')
 
 
-def load_common_data(equipment_filename, topology_filename, simulation_filename, save_raw_network_filename):
-    '''Load common configuration from JSON files'''
+def load_common_data(equipment_filename: Path,
+                     extra_equipment_filenames: List[Path], extra_config_filenames: List[Path],
+                     topology_filename: Path, simulation_filename: Path, save_raw_network_filename: Path):
+    """Load common configuration from JSON files, merging additional equipment if provided.
 
+    :param equipment_filename: Path to the main equipment configuration file.
+    :type equipment_filename: Path
+    :param extra_equipment_filenames: List of additional equipment configuration files.
+    :type extra_equipment_filenames: List[Path]
+    :param extra_config_filenames: List of additional configuration files.
+    :type extra_config_filenames: List[Path]
+    :param topology_filename: Path to the network topology file.
+    :type topology_filename: Path
+    :param simulation_filename: Path to the simulation parameters file.
+    :type simulation_filename: Path
+    :param save_raw_network_filename: Path to save the raw network configuration.
+    :type save_raw_network_filename: Path
+    :raises exceptions.EquipmentConfigError: If there is a configuration error in the equipment library.
+    :raises exceptions.NetworkTopologyError: If the network definition is invalid.
+    :raises exceptions.ParametersError: If there is an error with simulation parameters.
+    :raises exceptions.ConfigurationError: If there is a general configuration error.
+    :raises exceptions.ServiceError: If there is a service-related error.
+    """
     try:
-        equipment = load_equipment(equipment_filename)
+        equipment = load_equipments_and_configs(equipment_filename, extra_equipment_filenames, extra_config_filenames)
         network = load_network(topology_filename, equipment)
         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)
     except exceptions.NetworkTopologyError as e:
         print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
         sys.exit(1)
-    except exceptions.ConfigurationError as e:
-        print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
-        sys.exit(1)
     except exceptions.ParametersError as e:
         print(f'{ansi_escapes.red}Simulation parameters error:{ansi_escapes.reset} {e}')
         sys.exit(1)
+    except exceptions.ConfigurationError as e:
+        print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
+        sys.exit(1)
     except exceptions.ServiceError as e:
         print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {e}')
         sys.exit(1)
@@ -85,18 +110,30 @@ def load_common_data(equipment_filename, topology_filename, simulation_filename,
     return (equipment, network)
 
 
-def _setup_logging(args):
-    logging.basicConfig(level={2: logging.DEBUG, 1: logging.INFO, 0: logging.CRITICAL}.get(args.verbose, logging.DEBUG))
+def _setup_logging(args: argparse.Namespace):
+    """Set up logging based on verbosity level.
+
+    :param args: The parsed command-line arguments.
+    :type args: argparse.Namespace
+    """
+    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):
+    """Add common command-line options to the argument parser.
+
+    :param parser: The argument parser to which options will be added.
+    :type parser: argparse.ArgumentParser
+    :param network_default: The default path for the network topology file.
+    :type network_default: Path
+    """
     parser.add_argument('topology', nargs='?', type=Path, metavar='NETWORK-TOPOLOGY.(json|xls|xlsx)',
                         default=network_default,
                         help='Input network topology')
     parser.add_argument('-v', '--verbose', action='count', default=0,
                         help='Increase verbosity (can be specified several times)')
     parser.add_argument('-e', '--equipment', type=Path, metavar=_help_fname_json,
-                        default=_examples_dir / 'eqpt_config.json', help='Equipment library')
+                        default=DEFAULT_EQPT_CONFIG, help='Equipment library')
     parser.add_argument('--sim-params', type=Path, metavar=_help_fname_json,
                         default=None, help='Path to the JSON containing simulation parameters (required for Raman). '
                                            f'Example: {_examples_dir / "sim_params.json"}')
@@ -104,26 +141,47 @@ def _add_common_options(parser: argparse.ArgumentParser, network_default: Path):
                         help='Save the final network as a JSON file')
     parser.add_argument('--save-network-before-autodesign', type=Path, metavar=_help_fname_json,
                         help='Dump the network into a JSON file prior to autodesign')
+    parser.add_argument('--no-insert-edfas', action='store_true',
+                        help='Disable insertion of EDFAs after ROADMs and fibers '
+                             'as well as splitting of fibers by auto-design.')
+    # Option for additional equipment files
+    parser.add_argument('--extra-equipment', nargs='+', type=Path,
+                        metavar=_help_fname_json, default=None,
+                        help='List of additional equipment files to complement the main equipment file.')
+    # Option for additional config files
+    parser.add_argument('--extra-config', nargs='+', type=Path,
+                        metavar=_help_fname_json,
+                        help='List of additional config files as referenced in equipment files with '
+                             '"advanced_config_from_json" or "default_config_from_json".'
+                             f'Existing configs:\n{_default_config_files}')
 
 
-def transmission_main_example(args=None):
+def transmission_main_example(args: Union[List[str], None] = None):
+    """Main script running a single simulation. It returns the detailed power across crossed elements and
+    average performance accross all channels.
+
+    :param args: Command-line arguments (default is None).
+    :type args: Union[List[str], None]
+    """
     parser = argparse.ArgumentParser(
         description='Send a full spectrum load through the network from point A to point B',
         epilog=_help_footer,
         formatter_class=argparse.ArgumentDefaultsHelpFormatter,
-        )
+    )
     _add_common_options(parser, network_default=_examples_dir / 'edfa_example_network.json')
-    parser.add_argument('--show-channels', action='store_true', help='Show final per-channel OSNR summary')
+    parser.add_argument('--show-channels', action='store_true', help='Show final per-channel OSNR and GSNR summary')
     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')
 
     args = parser.parse_args(args if args is not None else sys.argv[1:])
     _setup_logging(args)
 
-    (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.extra_equipment, args.extra_config, args.topology,
+                                            args.sim_params, args.save_network_before_autodesign)
 
     if args.plot:
         plot_baseline(network)
@@ -141,19 +199,17 @@ 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')
+        valid_source = bool(source)
 
+    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')
+        valid_destination = bool(destination)
 
     # If no exact match try to find partial match
     if args.source and not source:
@@ -170,88 +226,84 @@ 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
-    params['blocking_reason'] = 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)
+        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)
-
-    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} '
+    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, (Fiber, RamanFiber))]
+    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}:')
-
-    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]')
-        power_range = [0]
-
-    if not power_mode:
-        # power cannot be changed in gain mode
-        power_range = [0]
-    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 mypath, 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:
-            for elem in path:
+            print('\nPropagating in {ansi_escapes.cyan}gain mode{ansi_escapes.reset}: power cannot be set manually')
+        if len(powers_dbm) == 1:
+            for elem in mypath:
                 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 SNR total (0.1 nm): {ansi_escapes.cyan}{mean(destination.snr_01nm):.02f} dB{ansi_escapes.reset}')
+                print('\nTransmission results:')
+            print(f'  Final GSNR (0.1 nm): {ansi_escapes.cyan}{mean(destination.snr_01nm):.02f} dB{ansi_escapes.reset}')
         else:
-            print(path[-1])
+            print(mypath[-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}')
 
     if args.show_channels:
-        print('\nThe total SNR per channel at the end of the line is:')
+        print('\nThe GSNR per channel at the end of the line is:')
         print(
             '{:>5}{:>26}{:>26}{:>28}{:>28}{:>28}' .format(
                 'Ch. #',
@@ -259,15 +311,15 @@ def transmission_main_example(args=None):
                 'Channel power (dBm)',
                 'OSNR ASE (signal bw, dB)',
                 'SNR NLI (signal bw, dB)',
-                'SNR total (signal bw, dB)'))
+                'GSNR (signal bw, dB)'))
         for final_carrier, ch_osnr, ch_snr_nl, ch_snr in zip(
                 infos.carriers, path[-1].osnr_ase, path[-1].osnr_nli, path[-1].snr):
             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(
@@ -292,11 +344,17 @@ def _path_result_json(pathresult):
 
 
 def path_requests_run(args=None):
+    """Main script running several services simulations. It returns a summary of the average performance
+    for each service.
+
+    :param args: Command-line arguments (default is None).
+    :type args: Union[List[str], None]
+    """
     parser = argparse.ArgumentParser(
         description='Compute performance for a list of services provided in a json file or an excel sheet',
         epilog=_help_footer,
         formatter_class=argparse.ArgumentDefaultsHelpFormatter,
-        )
+    )
     _add_common_options(parser, network_default=_examples_dir / 'meshTopologyExampleV2.xls')
     parser.add_argument('service_filename', nargs='?', type=Path, metavar='SERVICES-REQUESTS.(json|xls|xlsx)',
                         default=_examples_dir / 'meshTopologyExampleV2.xls',
@@ -305,88 +363,52 @@ 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')
-    print(f'{ansi_escapes.blue}Computing path requests {os.path.relpath(args.service_filename)} into JSON format{ansi_escapes.reset}')
+    _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.extra_equipment, args.extra_config, args.topology, args.sim_params,
+                         args.save_network_before_autodesign)
 
     # Build the network once using the default power defined in SI in eqpt config
-    # TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
-    # spacing, f_min and f_max
-    p_db = equipment['SI']['default'].power_dbm
 
-    p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
-                                             equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
     try:
-        build_network(network, equipment, p_db, p_total_db)
+        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)
+        _, 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)
+    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}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)
+    if args.save_network is not None:
+        save_network(network, args.save_network)
+        print(f'Network (after autodesign) saved to {args.save_network}')
 
     print(f'{ansi_escapes.blue}Result summary{ansi_escapes.reset}')
-    header = ['req id', '  demand', '  snr@bandwidth A-Z (Z-A)', '  snr@0.1nm A-Z (Z-A)',
+    header = ['req id', '  demand', ' GSNR@bandwidth A-Z (Z-A)', ' GSNR@0.1nm A-Z (Z-A)',
               '  Receiver minOSNR', '  mode', '  Gbit/s', '  nb of tsp pairs',
               'N,M or blocking reason']
     data = []
@@ -394,27 +416,27 @@ def path_requests_run(args=None):
     for i, this_p in enumerate(propagatedpths):
         rev_pth = reversed_propagatedpths[i]
         if rev_pth and this_p:
-            psnrb = f'{round(mean(this_p[-1].snr),2)} ({round(mean(rev_pth[-1].snr),2)})'
+            psnrb = f'{round(mean(this_p[-1].snr), 2)} ({round(mean(rev_pth[-1].snr), 2)})'
             psnr = f'{round(mean(this_p[-1].snr_01nm), 2)}' +\
-                f' ({round(mean(rev_pth[-1].snr_01nm),2)})'
+                f' ({round(mean(rev_pth[-1].snr_01nm), 2)})'
         elif this_p:
-            psnrb = f'{round(mean(this_p[-1].snr),2)}'
-            psnr = f'{round(mean(this_p[-1].snr_01nm),2)}'
+            psnrb = f'{round(mean(this_p[-1].snr), 2)}'
+            psnr = f'{round(mean(this_p[-1].snr_01nm), 2)}'
 
         try:
             if rqs[i].blocking_reason in BLOCKING_NOPATH:
                 line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} :',
-                        f'-', f'-', f'-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9,2)}',
-                        f'-', f'{rqs[i].blocking_reason}']
+                        '-', '-', '-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',
+                        '-', '{rqs[i].blocking_reason}']
             else:
                 line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} : ', psnrb,
-                        psnr, f'-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',
-                        f'-', f'{rqs[i].blocking_reason}']
+                        psnr, '-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',
+                        '-', f'{rqs[i].blocking_reason}']
         except AttributeError:
             line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} : ', psnrb,
                     psnr, f'{rqs[i].OSNR + equipment["SI"]["default"].sys_margins}',
-                    f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9,2)}',
-                    f'{ceil(rqs[i].path_bandwidth / rqs[i].bit_rate) }', f'({rqs[i].N},{rqs[i].M})']
+                    f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',
+                    f'{ceil(rqs[i].path_bandwidth / rqs[i].bit_rate)}', f'({rqs[i].N},{rqs[i].M})']
         data.append(line)
 
     col_width = max(len(word) for row in data for word in row[2:])   # padding
@@ -425,7 +447,7 @@ def path_requests_run(args=None):
         secondcol = ''.join(row[1].ljust(secondcol_width))
         remainingcols = ''.join(word.center(col_width, ' ') for word in row[2:])
         print(f'{firstcol} {secondcol} {remainingcols}')
-    print(f'{ansi_escapes.yellow}Result summary shows mean SNR and OSNR (average over all channels){ansi_escapes.reset}')
+    print(f'{ansi_escapes.yellow}Result summary shows mean GSNR and OSNR (average over all channels){ansi_escapes.reset}')
 
     if args.output:
         result = []

gnpy/tools/convert_legacy_yang.py

@@ -0,0 +1,243 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+# SPDX-License-Identifier: BSD-3-Clause
+# JSON files format conversion legacy <-> YANG
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
+"""
+YANG formatted to legacy format conversion
+==========================================
+
+"""
+
+from argparse import ArgumentParser
+from pathlib import Path
+from copy import deepcopy
+import json
+from typing import Dict
+
+from gnpy.tools.yang_convert_utils import convert_degree, convert_back_degree, \
+    convert_delta_power_range, convert_back_delta_power_range, \
+    convert_dict, convert_back, \
+    remove_null_region_city, remove_union_that_fail, \
+    convert_design_band, convert_back_design_band, \
+    convert_none_to_empty, convert_empty_to_none, \
+    convert_loss_coeff_list, convert_back_loss_coeff_list, \
+    ELEMENTS_KEY, PATH_REQUEST_KEY, RESPONSE_KEY, SPECTRUM_KEY, EQPT_TYPES, EDFA_CONFIG_KEYS, SIM_PARAMS_KEYS, \
+    TOPO_NMSP, SERV_NMSP, EQPT_NMSP, SPECTRUM_NMSP, SIM_PARAMS_NMSP, EDFA_CONFIG_NMSP, RESP_NMSP, \
+    dump_data, add_missing_default_type_variety, \
+    remove_namespace_context, load_data, reorder_route_objects, reorder_lumped_losses_objects, \
+    reorder_raman_pumps, convert_raman_coef, convert_back_raman_coef, convert_raman_efficiency, \
+    convert_back_raman_efficiency, convert_nf_coef, convert_back_nf_coef, \
+    convert_nf_fit_coef, convert_back_nf_fit_coef
+
+
+def legacy_to_yang(json_data: Dict) -> Dict:
+    """Convert legacy format to GNPy YANG format.
+
+    This function adds the required namespace if not present and processes the input JSON data
+    based on its structure to convert it to the appropriate YANG format. There is no validation
+    of yang formatted data.
+
+    :param json_data: The input JSON data to convert.
+    :type json_data: Dict
+    :return: The converted JSON data in GNPy YANG format.
+    :rtype: Dict
+    """
+    json_data = convert_none_to_empty(deepcopy(json_data))
+
+    # case of topology json
+    if ELEMENTS_KEY in json_data:
+        json_data = reorder_raman_pumps(json_data)
+        json_data = reorder_lumped_losses_objects(json_data)
+        json_data = remove_null_region_city(json_data)
+        json_data = convert_degree(json_data)
+        json_data = convert_design_band(json_data)
+        json_data = convert_loss_coeff_list(json_data)
+        json_data = convert_raman_coef(json_data)
+        json_data = {TOPO_NMSP: json_data}
+    elif TOPO_NMSP in json_data:
+        # then this is a new format topology json, ensure that there are no issues
+        json_data[TOPO_NMSP] = convert_degree(json_data[TOPO_NMSP])
+        json_data[TOPO_NMSP] = convert_design_band(json_data[TOPO_NMSP])
+        json_data[TOPO_NMSP] = convert_loss_coeff_list(json_data[TOPO_NMSP])
+        json_data[TOPO_NMSP] = remove_null_region_city(json_data[TOPO_NMSP])
+
+    # case of equipment json
+    elif any(k in json_data for k in EQPT_TYPES):
+        json_data = convert_raman_efficiency(json_data)
+        json_data = convert_delta_power_range(json_data)
+        json_data = convert_nf_coef(json_data)
+        json_data = add_missing_default_type_variety(json_data)
+        json_data = {EQPT_NMSP: json_data}
+    elif EQPT_NMSP in json_data:
+        # then this is already a new format topology json, ensure that there are no issues
+        json_data[EQPT_NMSP] = convert_raman_efficiency(json_data[EQPT_NMSP])
+        json_data[EQPT_NMSP] = convert_delta_power_range(json_data[EQPT_NMSP])
+        json_data[EQPT_NMSP] = convert_nf_coef(json_data[EQPT_NMSP])
+        json_data[EQPT_NMSP] = add_missing_default_type_variety(json_data[EQPT_NMSP])
+
+    # case of service json
+    elif PATH_REQUEST_KEY in json_data:
+        json_data = reorder_route_objects(json_data)
+        json_data = remove_union_that_fail(json_data)
+        json_data = {SERV_NMSP: json_data}
+
+    elif SERV_NMSP in json_data:
+        json_data[SERV_NMSP] = reorder_route_objects(json_data[SERV_NMSP])
+        json_data[SERV_NMSP] = remove_union_that_fail(json_data[SERV_NMSP])
+
+    # case of edfa_config json
+    elif any(k in json_data for k in EDFA_CONFIG_KEYS):
+        json_data = convert_nf_fit_coef(json_data)
+        json_data = {EDFA_CONFIG_NMSP: json_data}
+
+    elif EDFA_CONFIG_NMSP in json_data:
+        json_data[EDFA_CONFIG_NMSP] = convert_nf_fit_coef(json_data[EDFA_CONFIG_NMSP])
+
+    # case of spectrum json
+    elif SPECTRUM_KEY in json_data:
+        json_data = {SPECTRUM_NMSP: json_data[SPECTRUM_KEY]}
+
+    # case of sim_params json
+    elif any(k in json_data for k in SIM_PARAMS_KEYS):
+        json_data = {SIM_PARAMS_NMSP: json_data}
+
+    # case of response json
+    elif RESPONSE_KEY in json_data:
+        json_data = {RESP_NMSP: json_data}
+
+    elif any(k in json_data for k in [SPECTRUM_NMSP, SIM_PARAMS_NMSP, RESP_NMSP]):
+        # then this is a new format json, nothing to convert
+        pass
+
+    else:
+        raise ValueError('Unrecognized type of content (not topology, service or equipment)')
+
+    json_data = convert_dict(json_data)
+    return json_data
+
+
+def yang_to_legacy(json_data: Dict) -> Dict:
+    """Convert GNPy YANG format to legacy format.
+
+    This function processes the input JSON data to convert it from the new GNPy YANG format
+    back to the legacy format. It handles various types of content, including topology,
+    equipment, and service jsons, ensuring that the necessary conversions are applied.
+    The input data is validated with oopt-gnpy-libyang.
+
+    :param json_data: The input JSON data in GNPy YANG format to convert.
+    :type json_data: Dict
+    :return: The converted JSON data in legacy format.
+    :rtype: Dict
+
+    :raises ValueError: If the input JSON data does not match any recognized content type
+                        (not topology, service, or equipment).
+    """
+    # validate data compliance: make sure that this is yang formated data before validation.
+    load_data(json.dumps(legacy_to_yang(json_data)))
+    json_data = convert_empty_to_none(json_data)
+    json_data = convert_back(json_data)
+
+    # case of topology json
+    if ELEMENTS_KEY in json_data:
+        json_data = convert_back_degree(json_data)
+        json_data = convert_back_design_band(json_data)
+        json_data = convert_back_loss_coeff_list(json_data)
+        json_data = convert_back_raman_coef(json_data)
+    elif TOPO_NMSP in json_data:
+        json_data = convert_back_degree(json_data[TOPO_NMSP])
+        json_data = convert_back_design_band(json_data)
+        json_data = convert_back_loss_coeff_list(json_data)
+        json_data = convert_back_raman_coef(json_data)
+
+    # case of equipment json
+    elif any(k in json_data for k in EQPT_TYPES):
+        json_data = convert_back_delta_power_range(json_data)
+        json_data = convert_back_raman_efficiency(json_data)
+        json_data = convert_back_nf_coef(json_data)
+        json_data = remove_namespace_context(json_data, "gnpy-eqpt-config:")
+    elif EQPT_NMSP in json_data:
+        json_data[EQPT_NMSP] = convert_back_delta_power_range(json_data[EQPT_NMSP])
+        json_data[EQPT_NMSP] = convert_back_raman_efficiency(json_data[EQPT_NMSP])
+        json_data[EQPT_NMSP] = convert_back_nf_coef(json_data[EQPT_NMSP])
+        json_data = remove_namespace_context(json_data[EQPT_NMSP], "gnpy-eqpt-config:")
+
+    # case of EDFA config json
+    elif any(k in json_data for k in EDFA_CONFIG_KEYS):
+        json_data = convert_back_nf_fit_coef(json_data)
+    elif EDFA_CONFIG_NMSP in json_data:
+        json_data[EDFA_CONFIG_NMSP] = convert_back_nf_fit_coef(json_data[EDFA_CONFIG_NMSP])
+
+    # case of service json
+    elif SERV_NMSP in json_data:
+        json_data = json_data[SERV_NMSP]
+
+    # case of sim_params json
+    elif SIM_PARAMS_NMSP in json_data:
+        json_data = json_data[SIM_PARAMS_NMSP]
+
+    # case of spectrum json
+    elif SPECTRUM_NMSP in json_data:
+        json_data = {SPECTRUM_KEY: json_data[SPECTRUM_NMSP]}
+
+    # case of planning response json
+    elif RESP_NMSP in json_data:
+        json_data = json_data[RESP_NMSP]
+    elif any(k in json_data for k in SIM_PARAMS_KEYS + [SPECTRUM_KEY, RESPONSE_KEY, PATH_REQUEST_KEY]):
+        # then this is a legacy format json, nothing to convert
+        pass
+    else:
+        raise ValueError('Unrecognized type of content (not topology, service or equipment)')
+    return json_data
+
+
+def main():
+    """Conversion function
+    """
+    parser = ArgumentParser()
+    parser.add_argument('--legacy-to-yang', nargs='?', type=Path,
+                        help='convert file with this name into yangconformedname.json')
+    parser.add_argument('--yang-to-legacy', nargs='?', type=Path,
+                        help='convert file with this name into gnpy'
+                             + ' using decimal instead of strings and null instead of [null]')
+    parser.add_argument('--validate', nargs='?', type=Path,
+                        help='validate yang conformity')
+    parser.add_argument('-o', '--output', type=Path,
+                        help='Stores into file with this name; default = GNPy_legacy_formatted-<file_name>.json or'
+                        + 'GNPy_yang_formatted-<file_name>.json')
+    args = parser.parse_args()
+
+    if not (args.legacy_to_yang or args.yang_to_legacy or args.validate):
+        parser.error("You must specify at least one of --legacy-to-yang, --yang-to-legacy, or --validate ")
+
+    output = None
+    converted = None
+    if args.validate:
+        with open(args.validate, 'r', encoding='utf-8') as f:
+            json_data = json.load(f)
+            load_data(json.dumps(json_data))
+        return 0
+    elif args.legacy_to_yang:
+        prefix = 'GNPy_yang_formatted-'
+        with open(args.legacy_to_yang, 'r', encoding='utf-8') as f:
+            json_data = json.load(f)
+            # note that dump_data automatically validate date against yang models
+            converted = dump_data(legacy_to_yang(json_data))
+        output = prefix + str(args.legacy_to_yang.name)
+    elif args.yang_to_legacy:
+        prefix = 'GNPy_legacy_formatted-'
+        with open(args.yang_to_legacy, 'r', encoding='utf-8') as f:
+            json_data = json.load(f)
+            converted = json.dumps(yang_to_legacy(json_data), indent=2, ensure_ascii=False)
+        output = prefix + str(args.yang_to_legacy.name)
+    if args.output:
+        output = args.output
+    with open(output, 'w', encoding='utf-8') as f:
+        f.write(converted)
+
+
+if __name__ == '__main__':
+    main()

gnpy/tools/create_eqpt_sheet.py

@@ -0,0 +1,149 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+# SPDX-License-Identifier: BSD-3-Clause
+# Utility functions that creates an Eqpt sheet template
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
+"""
+create_eqpt_sheet.py
+====================
+
+XLS parser that can be called to create a "City" column in the "Eqpt" sheet.
+
+If not present in the "Nodes" sheet, the "Type" column will be implicitly
+determined based on the topology.
+"""
+
+from argparse import ArgumentParser
+from pathlib import Path
+import csv
+from typing import List, Dict, Optional
+from logging import getLogger
+import dataclasses
+
+from gnpy.core.exceptions import NetworkTopologyError
+from gnpy.tools.xls_utils import generic_open_workbook, get_sheet, XLS_EXCEPTIONS, all_rows, fast_get_sheet_rows, \
+    WorkbookType, SheetType
+
+
+logger = getLogger(__name__)
+EXAMPLE_DATA_DIR = Path(__file__).parent.parent / 'example-data'
+
+PARSER = ArgumentParser()
+PARSER.add_argument('workbook', type=Path, nargs='?', default=f'{EXAMPLE_DATA_DIR}/meshTopologyExampleV2.xls',
+                    help='create the mandatory columns in Eqpt sheet')
+PARSER.add_argument('-o', '--output', type=Path, help='Store CSV file')
+
+
+@dataclasses.dataclass
+class Node:
+    """Represents a network node with a unique identifier, connected nodes, and equipment type.
+
+    :param uid: Unique identifier of the node.
+    :type uid: str
+    :param to_node: List of connected node identifiers.
+    :type to_node: List[str.]
+    :param eqpt: Equipment type associated with the node (ROADM, ILA, FUSED).
+    :type eqpt: str
+    """
+    def __init__(self, uid: str, to_node: List[str], eqpt: str = None):
+        self.uid = uid
+        self.to_node = to_node
+        self.eqpt = eqpt
+
+
+def open_sheet_with_error_handling(wb: WorkbookType, sheet_name: str, is_xlsx: bool) -> SheetType:
+    """Opens a sheet from the workbook with error handling.
+
+    :param wb: The opened workbook.
+    :type wb: WorkbookType
+    :param sheet_name: Name of the sheet to open.
+    :type sheet_name: str
+    :param is_xlsx: Boolean indicating if the file is XLSX format.
+    :type is_xlsx: bool
+    :return: The worksheet object.
+    :rtype: SheetType
+    :raises NetworkTopologyError: If the sheet is not found.
+    """
+    try:
+        sheet = get_sheet(wb, sheet_name, is_xlsx)
+        return sheet
+    except XLS_EXCEPTIONS as exc:
+        msg = f'Error: no {sheet_name} sheet in the file.'
+        raise NetworkTopologyError(msg) from exc
+
+
+def read_excel(input_filename: Path) -> Dict[str, Node]:
+    """Reads the 'Nodes' and 'Links' sheets from an Excel file to build a network graph.
+
+    :param input_filename: Path to the Excel file.
+    :type input_filename: Path
+    :return: Dictionary of nodes with their connectivity and equipment type.
+    :rtype: Dict[str, Node]
+    """
+    wobo, is_xlsx = generic_open_workbook(input_filename)
+    links_sheet = open_sheet_with_error_handling(wobo, 'Links', is_xlsx)
+    get_rows_links = fast_get_sheet_rows(links_sheet) if is_xlsx else None
+
+    nodes = {}
+    for row in all_rows(links_sheet, is_xlsx, start=5, get_rows=get_rows_links):
+        node_a, node_z = row[0].value, row[1].value
+        # Add connection in both directions
+        for node1, node2 in [(node_a, node_z), (node_z, node_a)]:
+            if node1 in nodes:
+                nodes[node1].to_node.append(node2)
+            else:
+                nodes[node1] = Node(node1, [node2])
+
+    nodes_sheet = open_sheet_with_error_handling(wobo, 'Nodes', is_xlsx)
+    get_rows_nodes = fast_get_sheet_rows(nodes_sheet) if is_xlsx else None
+
+    for row in all_rows(nodes_sheet, is_xlsx, start=5, get_rows=get_rows_nodes):
+        node = row[0].value
+        eqpt = row[6].value
+        if node not in nodes:
+            raise NetworkTopologyError(f'Error: node {node} is not listed on the links sheet.')
+        if eqpt == 'ILA' and len(nodes[node].to_node) != 2:
+            degree = len(nodes[node].to_node)
+            raise NetworkTopologyError(f'Error: node {node} has an incompatible node degree ({degree}) '
+                                       + 'for its equipment type (ILA).')
+        if eqpt == '' and len(nodes[node].to_node) == 2:
+            nodes[node].eqpt = 'ILA'
+        elif eqpt == '' and len(nodes[node].to_node) != 2:
+            nodes[node].eqpt = 'ROADM'
+        else:
+            nodes[node].eqpt = eqpt
+    return nodes
+
+
+def create_eqpt_template(nodes: Dict[str, Node], input_filename: Path, output_filename: Optional[Path] = None):
+    """Creates a CSV template to help users populate equipment types for nodes.
+
+    :param nodes: Dictionary of nodes.
+    :type nodes: Dict[str, Node]
+    :param input_filename: Path to the original Excel file.
+    :type input_filename: Path
+    :param output_filename: Path to save the CSV file; generated if None.
+    :type output_filename: Optional(Path)
+    """
+    if output_filename is None:
+        output_filename = input_filename.parent / (input_filename.with_suffix('').stem + '_eqpt_sheet.csv')
+    with open(output_filename, mode='w', encoding='utf-8', newline='') as output_file:
+        output_writer = csv.writer(output_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
+        amp_header = ['amp_type', 'att_in', 'amp_gain', 'tilt', 'att_out', 'delta_p']
+        output_writer.writerow(['node_a', 'node_z'] + amp_header + amp_header)
+        for node in nodes.values():
+            if node.eqpt == 'ILA':
+                output_writer.writerow([node.uid, node.to_node[0]])
+            if node.eqpt == 'ROADM':
+                for to_node in node.to_node:
+                    output_writer.writerow([node.uid, to_node])
+    msg = f'File {output_filename} successfully created.'
+    logger.info(msg)
+
+
+if __name__ == '__main__':
+    ARGS = PARSER.parse_args()
+    create_eqpt_template(read_excel(ARGS.workbook), ARGS.workbook, ARGS.output)

gnpy/tools/default_edfa_config.py

@@ -0,0 +1,72 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+# SPDX-License-Identifier: BSD-3-Clause
+# gnpy.tools.default_edfa_configs: loads JSON configuration files at module initialization time
+# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
+# see AUTHORS.rst for a list of contributors
+
+"""
+gnpy.tools.default_edfa_config
+==============================
+
+Default configs for pre defined amplifiers:
+- Juniper-BoosterHG.json,
+- std_medium_gain_advanced_config.json
+"""
+
+from logging import getLogger
+from typing import Dict, Optional
+from json import JSONDecodeError, load
+from pathlib import Path
+
+from gnpy.core.exceptions import ConfigurationError
+from gnpy.tools.convert_legacy_yang import yang_to_legacy
+
+
+_logger = getLogger(__name__)
+_examples_dir = Path(__file__).parent.parent / 'example-data'
+
+
+def _load_json_file(file_path: Path) -> Optional[Dict]:
+    """Load and parse a JSON file.
+    :param file_path: Path to the JSON file to load
+    :type file_path: Path
+    :return: Dict containing the parsed JSON data or None if loading fails
+    :rtype: Optional[Dict]
+    """
+    try:
+        with open(file_path, 'r', encoding='utf-8') as file:
+            return yang_to_legacy(load(file))
+    except FileNotFoundError:
+        msg = f"Configuration file not found: {file_path}"
+        _logger.error(msg)
+        return None
+    except JSONDecodeError as e:
+        msg = f"Invalid JSON in configuration file {file_path}: {e}"
+        _logger.error(msg)
+        return None
+
+
+# Default files to load
+_files_to_load = {
+    "std_medium_gain_advanced_config.json": _examples_dir / "std_medium_gain_advanced_config.json",
+    "Juniper-BoosterHG.json": _examples_dir / "Juniper-BoosterHG.json"
+}
+
+# Load configurations
+_configs: Dict = {}
+
+for key, filepath in _files_to_load.items():
+    config_data = _load_json_file(filepath)
+    if config_data is not None:
+        _configs[key] = config_data
+    else:
+        _msg = f"Failed to load configuration: {key}. Using empty dict as fallback."
+        _logger.error(_msg)
+        raise ConfigurationError
+
+# Expose the constant
+DEFAULT_EXTRA_CONFIG: Dict[str, Dict] = _configs
+
+DEFAULT_EQPT_CONFIG: Path = _examples_dir / "eqpt_config.json"