Merge pull request #480 from jktjkt/python-3.12

CI: Python 3.12 and extended platform coverage

.docker-travis.sh

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

.github/workflows/main.yml

@@ -11,35 +11,43 @@ jobs:
     name: Tox test
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
       - uses: fedora-python/tox-github-action@v0.4
         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.event.ref, 'refs/tags/v') }}
+    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@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v4
         name: Install Python
         with:
-          python-version: '3.9'
+          python-version: '3.12'
       - uses: casperdcl/deploy-pypi@bb869aafd89f657ceaafe9561d3b5584766c0f95
         with:
           password: ${{ secrets.PYPI_API_TOKEN }}
@@ -48,7 +56,7 @@ jobs:
 
   docker:
     needs: build
-    if: github.event_name == 'push' && (github.ref == 'refs/heads/master' || startsWith(github.ref, 'refs/tags/v'))
+    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:
@@ -57,31 +65,83 @@ jobs:
         with:
           username: jktjkt
           password: ${{ secrets.DOCKERHUB_TOKEN }}
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 0
       - name: Extract tag name
-        if: github.event_name == 'push' && github.ref == 'refs/heads/master'
+        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'
+        if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
         with:
           context: .
           push: true
           tags: |
-            telecominfraproject/oopt-gnpy:dev-${{ steps.extract_pretty_git.outputs.GIT_DESC }}
+            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')
+        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')
+        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 -r tests/requirements.txt
+          pip install --editable .
+          pytest -vv
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - os: windows-2019
+            python_version: "3.10"
+          - os: windows-2022
+            python_version: "3.11"
+          - os: windows-2022
+            python_version: "3.12"
+          - os: macos-12
+            python_version: "3.11"
+          - os: macos-13
+            python_version: "3.12"
+
+  paywalled-platforms:
+    name: Tests on paywalled platforms
+    if: github.repository_owner == 'Telecominfraproject'
+    runs-on: ${{ matrix.os }}
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+      - uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python_version }}
+      - run: |
+          pip install -r tests/requirements.txt
+          pip install --editable .
+          pytest -vv
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - os: macos-13-xlarge # Apple M1 CPU
+            python_version: "3.12"

.lgtm.yml

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

.travis.yml

@@ -1,29 +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
-  - pip install -r docs/requirements.txt
-  - rstcheck --ignore-roles cite *.rst
-  - sphinx-build -W --keep-going docs/ x-throwaway-location
-after_success:
-  - bash <(curl -s https://codecov.io/bash)
-jobs:
-  include:
-    - stage: test
-      name: Docker image
-      script:
-        - git fetch --unshallow
-        - ./.docker-travis.sh
-        - docker images

.zuul.yaml

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

AUTHORS.rst

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

README.md

@@ -3,12 +3,12 @@
 [![Install via pip](https://img.shields.io/pypi/v/gnpy)](https://pypi.org/project/gnpy/)
 [![Python versions](https://img.shields.io/pypi/pyversions/gnpy)](https://pypi.org/project/gnpy/)
 [![Documentation status](https://readthedocs.org/projects/gnpy/badge/?version=master)](http://gnpy.readthedocs.io/en/master/?badge=master)
-[![GitHub Workflow Status](https://img.shields.io/github/workflow/status/Telecominfraproject/oopt-gnpy/build)](https://github.com/Telecominfraproject/oopt-gnpy/actions/workflows/main.yml)
+[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/Telecominfraproject/oopt-gnpy/main.yml)](https://github.com/Telecominfraproject/oopt-gnpy/actions/workflows/main.yml)
 [![Gerrit](https://img.shields.io/badge/patches-via%20Gerrit-blue)](https://review.gerrithub.io/q/project:Telecominfraproject/oopt-gnpy+is:open)
 [![Contributors](https://img.shields.io/github/contributors-anon/Telecominfraproject/oopt-gnpy)](https://github.com/Telecominfraproject/oopt-gnpy/graphs/contributors)
-[![Code Quality via LGTM.com](https://img.shields.io/lgtm/grade/python/github/Telecominfraproject/oopt-gnpy)](https://lgtm.com/projects/g/Telecominfraproject/oopt-gnpy/)
 [![Code Coverage via codecov](https://img.shields.io/codecov/c/github/Telecominfraproject/oopt-gnpy)](https://codecov.io/gh/Telecominfraproject/oopt-gnpy)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3458319.svg)](https://doi.org/10.5281/zenodo.3458319)
+[![Matrix chat](https://img.shields.io/matrix/oopt-gnpy:matrix.org)](https://matrix.to/#/%23oopt-gnpy%3Amatrix.org?via=matrix.org)
 
 GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks.
 We are a consortium of operators, vendors, and academic researchers sponsored via the [Telecom Infra Project](http://telecominfraproject.com)'s [OOPT/PSE](https://telecominfraproject.com/open-optical-packet-transport) working group.
@@ -18,12 +18,14 @@ Together, we are building this tool for rapid development of production-grade ro
 
 ## Quick Start
 
-Install either via [Docker](docs/install.rst#install-docker), or as a [Python package](docs/install.rst#install-pip).
+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](https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg)](https://asciinema.org/a/252295)
+![Running a simple simulation example](https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg)
 
 GNPy can do much more, including acting as a Path Computation Engine, tracking bandwidth requests, or advising the SDN controller about a best possible path through a large DWDM network.
-Learn more about this [in the documentation](https://gnpy.readthedocs.io/).
+Learn more about this [in the documentation](https://gnpy.readthedocs.io/), or give it a [try online at `gnpy.app`](https://gnpy.app/):
+
+[![Path propagation at gnpy.app](docs/images/2022-04-12-gnpy-app.png)](https://gnpy.app/)

docs/about-project.md

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

docs/biblio.bib

@@ -1848,3 +1848,15 @@ month={Sept},}
   title = {Telecom Infra Project},
   url = {https://www.telecominfraproject.com},
 }
+
+@ARTICLE{DAmicoJLT2022,
+  author={D’Amico, Andrea and Correia, Bruno and London, Elliot and Virgillito,
+  Emanuele and Borraccini, Giacomo and Napoli, Antonio and Curri, Vittorio},
+  journal={Journal of Lightwave Technology},
+  title={Scalable and Disaggregated GGN Approximation Applied to a C+L+S Optical Network},
+  year={2022},
+  volume={40},
+  number={11},
+  pages={3499-3511},
+  doi={10.1109/JLT.2022.3162134}
+}

docs/concepts.rst

@@ -29,6 +29,7 @@ This path is directional, and all "GNPy elements" along the path match the unidi
 
 The network topology contains not just the physical topology of the network, but also references to the :ref:`equipment library<concepts-equipment>` and a set of *operating parameters* for each entity.
 These parameters include the **fiber length** of each fiber, the connector **attenutation losses**, or an amplifier's specific **gain setting**.
+The topology is specified via :ref:`XLS files<excel>` or via :ref:`JSON<legacy-json>`.
 
 .. _complete-vs-incomplete:
 

docs/conf.py

@@ -190,3 +190,5 @@ autodoc_default_options = {
 }
 
 graphviz_output_format = 'svg'
+
+bibtex_bibfiles = ['biblio.bib']

docs/excel.rst

@@ -1,3 +1,5 @@
+.. _excel:
+
 Excel (XLS, XLSX) input files
 =============================
 

docs/extending.rst

@@ -4,7 +4,7 @@ Extending GNPy with vendor-specific data
 ========================================
 
 GNPy ships with an :ref:`equipment library<concepts-equipment>` containing machine-readable datasheets of networking equipment.
-Vendors who are willing to contribute descriptions of their supported products are encouraged to `submit a patch <https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html>`__.
+Vendors who are willing to contribute descriptions of their supported products are encouraged to `submit a patch <https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html>`__ -- or just :ref:`get in touch with us directly<contributing>`.
 
 This chapter discusses option for modeling performance of :ref:`EDFA amplifiers<extending-edfa>`, :ref:`Raman amplifiers<extending-raman>`, :ref:`transponders<extending-transponder>` and :ref:`ROADMs<extending-roadm>`.
 
@@ -29,7 +29,7 @@ The NF is expressed as a third-degree polynomial:
 
        f(x) &= \text{a}x^3 + \text{b}x^2 + \text{c}x + \text{d}
 
-  \text{NF} &= f(G_\text{max} - G)
+  \text{NF} &= f(G - G_\text{max})
 
 This model can be also used for fixed-gain fixed-NF amplifiers.
 In that case, use:
@@ -100,10 +100,10 @@ Raman Amplifiers
 
 An accurate simulation of Raman amplification requires knowledge of:
 
-- the *power* and *wavelength* of all Raman pumping lasers,
+* the *power* and *wavelength* of all Raman pumping lasers,
-- the *direction*, whether it is co-propagating or counter-propagating,
+* the *direction*, whether it is co-propagating or counter-propagating,
-- the Raman efficiency of the fiber,
+* the Raman efficiency of the fiber,
-- the fiber temperature.
+* 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`.

docs/install.rst

@@ -38,7 +38,7 @@ 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.
@@ -84,7 +84,7 @@ 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:
 

docs/intro.rst

@@ -10,7 +10,7 @@ fully-functional programs.
 
     **Note**: *If you are a network operator or involved in route planning and
     optimization for your organization, please contact project maintainer Jan
-    Kundrát <jan.kundrat@telecominfraproject.com>. gnpy is looking for users with
+    Kundrát <jkt@jankundrat.com>. gnpy is looking for users with
     specific, delineated use cases to drive requirements for future
     development.*
 
@@ -20,7 +20,6 @@ This example demonstrates how GNPy can be used to check the expected SNR at the
    :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>`_
@@ -92,4 +91,4 @@ As a result transponder type is not part of the network info. it is related to t
 
 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. 
+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/json.rst

@@ -1,3 +1,5 @@
+.. _legacy-json:
+
 JSON Input Files
 ================
 
@@ -42,7 +44,7 @@ For all amplifier models:
 | ``type_variety``       | (string)  | a unique name to ID the amplifier in the|
 |                        |           | JSON/Excel template topology input file |
 +------------------------+-----------+-----------------------------------------+
-| ``out_voa_auto``       | (boolean) | auto_design feature to optimize the     |
+| ``out_voa_auto``       | (boolean) | auto-design feature to optimize the     |
 |                        |           | amplifier output VOA. If true, output   |
 |                        |           | VOA is present and will be used to push |
 |                        |           | amplifier gain to its maximum, within   |
@@ -59,25 +61,98 @@ Fiber
 
 The fiber library currently describes SSMF and NZDF but additional fiber types can be entered by the user following the same model:
 
-+----------------------+-----------+------------------------------------------+
++------------------------------+-----------------+------------------------------------------------+
 | field                        | type            | description                                    |
-+======================+===========+==========================================+
++==============================+=================+================================================+
 | ``type_variety``             | (string)        | a unique name to ID the fiber in the           |
 |                              |                 | JSON or Excel template topology input          |
 |                              |                 | file                                           |
-+----------------------+-----------+------------------------------------------+
++------------------------------+-----------------+------------------------------------------------+
-| ``dispersion``       | (number)  | In :math:`s \times m^{-1} \times m^{-1}`.|
+| ``dispersion``               | (number)        | In :math:`s \times m^{-1} \times m^{-1}`.      |
-+----------------------+-----------+------------------------------------------+
++------------------------------+-----------------+------------------------------------------------+
 | ``dispersion_slope``         | (number)        | In :math:`s \times m^{-1} \times m^{-1}        |
 |                              |                 | \times m^{-1}`                                 |
-+----------------------+-----------+------------------------------------------+
++------------------------------+-----------------+------------------------------------------------+
-| ``gamma``            | (number)  | :math:`2\pi\times n^2/(\lambda*A_{eff})`,|
+| ``dispersion_per_frequency`` | (dict)          | Dictionary of dispersion values evaluated at   |
-|                      |           | in :math:`w^{-1} \times m^{-1}`.         |
+|                              |                 | various frequencies, as follows:               |
-+----------------------+-----------+------------------------------------------+
+|                              |                 | ``{"value": [], "frequency": []}``.            |
+|                              |                 | ``value`` in                                   |
+|                              |                 | :math:`s \times m^{-1} \times m^{-1}` and      |
+|                              |                 | ``frequency`` in Hz.                           |
++------------------------------+-----------------+------------------------------------------------+
+| ``effective_area``           | (number)        | Effective area of the fiber (not just          |
+|                              |                 | the MFD circle). This is the                   |
+|                              |                 | :math:`A_{eff}`, see e.g., the                 |
+|                              |                 | `Corning whitepaper on MFD/EA`_.               |
+|                              |                 | Specified in :math:`m^{2}`.                    |
++------------------------------+-----------------+------------------------------------------------+
+| ``gamma``                    | (number)        | Coefficient :math:`\gamma = 2\pi\times         |
+|                              |                 | n^2/(\lambda*A_{eff})`.                        |
+|                              |                 | If not provided, this will be derived          |
+|                              |                 | from the ``effective_area``                    |
+|                              |                 | :math:`A_{eff}`.                               |
+|                              |                 | In :math:`w^{-1} \times m^{-1}`.               |
+|                              |                 | This quantity is evaluated at the              |
+|                              |                 | reference frequency and it is scaled           |
+|                              |                 | along frequency accordingly to the             |
+|                              |                 | effective area scaling.                        |
++------------------------------+-----------------+------------------------------------------------+
 | ``pmd_coef``                 | (number)        | Polarization mode dispersion (PMD)             |
 |                              |                 | coefficient. In                                |
 |                              |                 | :math:`s\times\sqrt{m}^{-1}`.                  |
-+----------------------+-----------+------------------------------------------+
++------------------------------+-----------------+------------------------------------------------+
+| ``lumped_losses``            | (array)         | Places along the fiber length with extra       |
+|                              |                 | losses. Specified as a loss in dB at           |
+|                              |                 | each relevant position (in km):                |
+|                              |                 | ``{"position": 10, "loss": 1.5}``)             |
++------------------------------+-----------------+------------------------------------------------+
+| ``raman_coefficient``        | (dict)          | The fundamental parameter that describes       |
+|                              |                 | the regulation of the power transfer           |
+|                              |                 | between channels during fiber propagation      |
+|                              |                 | is the Raman gain coefficient (see             |
+|                              |                 | :cite:`DAmicoJLT2022` for further              |
+|                              |                 | details); :math:`f_{ref}` represents the       |
+|                              |                 | pump reference frequency used for the          |
+|                              |                 | Raman gain coefficient profile                 |
+|                              |                 | measurement ("reference_frequency"),           |
+|                              |                 | :math:`\Delta f` is the frequency shift        |
+|                              |                 | between the pump and the specific Stokes       |
+|                              |                 | wave, the Raman gain coefficient               |
+|                              |                 | in terms of optical power                      |
+|                              |                 | :math:`g_0`, expressed in                      |
+|                              |                 | :math:`1/(m\;W)`.                              |
+|                              |                 | Default values measured for a SSMF are         |
+|                              |                 | considered when not specified.                 |
++------------------------------+-----------------+------------------------------------------------+
+
+.. _Corning whitepaper on MFD/EA: https://www.corning.com/microsites/coc/oem/documents/specialty-fiber/WP7071-Mode-Field-Diam-and-Eff-Area.pdf
+
+RamanFiber
+~~~~~~~~~~
+
+The RamanFiber can be used to simulate Raman amplification through dedicated Raman pumps. The Raman pumps must be listed
+in the key ``raman_pumps`` within the RamanFiber ``operational`` dictionary. The description of each Raman pump must
+contain the following:
+
++---------------------------+-----------+------------------------------------------------------------+
+| field                     | type      | description                                                |
++===========================+===========+============================================================+
+| ``power``                 | (number)  | Total pump power in :math:`W`                              |
+|                           |           | considering a depolarized pump                             |
++---------------------------+-----------+------------------------------------------------------------+
+| ``frequency``             | (number)  | Pump central frequency in :math:`Hz`                       |
++---------------------------+-----------+------------------------------------------------------------+
+| ``propagation_direction`` | (number)  | The pumps can propagate in the same or opposite direction  |
+|                           |           | with respect the signal. Valid choices are ``coprop`` and  |
+|                           |           | ``counterprop``, respectively                              |
++---------------------------+-----------+------------------------------------------------------------+
+
+Beside the list of Raman pumps, the RamanFiber ``operational`` dictionary must include the ``temperature`` that affects
+the amplified spontaneous emission noise generated by the Raman amplification.
+As the loss coefficient significantly varies outside the C-band, where the Raman pumps are usually placed,
+it is suggested to include an estimation of the loss coefficient for the Raman pump central frequencies within
+a dictionary-like definition of the ``RamanFiber.params.loss_coef``
+(e.g. ``loss_coef = {"value": [0.18, 0.18, 0.20, 0.20], "frequency": [191e12, 196e12, 200e12, 210e12]}``).
 
 Transceiver
 ~~~~~~~~~~~
@@ -130,26 +205,26 @@ ROADM
 
 The user can only modify the value of existing parameters:
 
-+--------------------------+-----------+---------------------------------------------+
++-------------------------------+-----------+----------------------------------------------------+
 | field                         |   type    | description                                        |
-+==========================+===========+=============================================+
++===============================+===========+====================================================+
-| ``target_pch_out_db``    | (number)  | Auto-design sets the ROADM egress channel   |
+| ``target_pch_out_db``         | (number)  | Default :ref:`equalization strategy<equalization>` |
-|                          |           | power. This reflects typical control loop   |
+| or                            |           | for this ROADM type.                               |
-|                          |           | algorithms that adjust ROADM losses to      |
+| ``target_psd_out_mWperGHz``   |           |                                                    |
-|                          |           | equalize channels (eg coming from different |
+| or                            |           | Auto-design sets the ROADM egress channel          |
-|                          |           | ingress direction or add ports)             |
+| ``target_out_mWperSlotWidth`` |           | power. This reflects typical control loop          |
-|                          |           | This is the default value                   |
+| (mutually exclusive)          |           | algorithms that adjust ROADM losses to             |
-|                          |           | Roadm/params/target_pch_out_db if no value  |
+|                               |           | equalize channels (e.g., coming from               |
-|                          |           | is given in the ``Roadm`` element in the    |
+|                               |           | different ingress direction or add ports).         |
-|                          |           | topology input description.                 |
+|                               |           |                                                    |
-|                          |           | This default value is ignored if a          |
+|                               |           | These values are used as defaults when no          |
-|                          |           | params/target_pch_out_db value is input in  |
+|                               |           | overrides are set per each ``Roadm``               |
-|                          |           | the topology for a given ROADM.             |
+|                               |           | element in the network topology.                   |
-+--------------------------+-----------+---------------------------------------------+
++-------------------------------+-----------+----------------------------------------------------+
 | ``add_drop_osnr``             | (number)  | OSNR contribution from the add/drop ports          |
-+--------------------------+-----------+---------------------------------------------+
++-------------------------------+-----------+----------------------------------------------------+
 | ``pmd``                       | (number)  | Polarization mode dispersion (PMD). (s)            |
-+--------------------------+-----------+---------------------------------------------+
++-------------------------------+-----------+----------------------------------------------------+
 | ``restrictions``              | (dict of  | If non-empty, keys ``preamp_variety_list``         |
 |                               |  strings) | and ``booster_variety_list`` represent             |
 |                               |           | list of ``type_variety`` amplifiers which          |
@@ -159,7 +234,7 @@ The user can only modify the value of existing parameters:
 |                               |           | If no booster should be placed on a degree,        |
 |                               |           | insert a ``Fused`` node on the degree              |
 |                               |           | output.                                            |
-+--------------------------+-----------+---------------------------------------------+
++-------------------------------+-----------+----------------------------------------------------+
 
 Global parameters
 -----------------
@@ -174,6 +249,64 @@ Only the EDFA that are marked ``'allowed_for_design': true`` are considered.
 
 For amplifiers defined in the topology JSON input but whose ``gain = 0`` (placeholder), auto-design will set its gain automatically: see ``power_mode`` in the ``Spans`` library to find out how the gain is calculated.
 
+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.
+
+If amplifiers don't have settings, auto-design also sets amplifiers gain, output VOA and target powers according to [J. -L. Auge, V. Curri and E. Le Rouzic, Open Design for Multi-Vendor Optical Networks, OFC 2019](https://ieeexplore.ieee.org/document/8696699), equation 4.
+See ``delta_power_range_db`` for more explaination.
+
++---------------------------------------------+-----------+---------------------------------------------+
+| field                                       |   type    | description                                 |
++=============================================+===========+=============================================+
+| ``raman_params.flag``                       | (boolean) | Enable/Disable the Raman effect that        |
+|                                             |           | produces a power transfer from higher to    |
+|                                             |           | lower frequencies.                          |
+|                                             |           | In general, considering the Raman effect    |
+|                                             |           | provides more accurate results. It is       |
+|                                             |           | mandatory when Raman amplification is       |
+|                                             |           | included in the simulation                  |
++---------------------------------------------+-----------+---------------------------------------------+
+| ``raman_params.result_spatial_resolution``  | (number)  | Spatial resolution of the output            |
+|                                             |           | Raman profile along the entire fiber span.  |
+|                                             |           | This affects the accuracy and the           |
+|                                             |           | computational time of the NLI               |
+|                                             |           | calculation when the GGN method is used:    |
+|                                             |           | smaller the spatial resolution higher both  |
+|                                             |           | the accuracy and the computational time.    |
+|                                             |           | In C-band simulations, with input power per |
+|                                             |           | channel around 0 dBm, a suggested value of  |
+|                                             |           | spatial resolution is 10e3 m                |
++---------------------------------------------+-----------+---------------------------------------------+
+| ``raman_params.solver_spatial_resolution``  | (number)  | Spatial step for the iterative solution     |
+|                                             |           | of the first order differential equation    |
+|                                             |           | used to calculate the Raman profile         |
+|                                             |           | along the entire fiber span.                |
+|                                             |           | This affects the accuracy and the           |
+|                                             |           | computational time of the evaluated         |
+|                                             |           | Raman profile:                              |
+|                                             |           | smaller the spatial resolution higher both  |
+|                                             |           | the accuracy and the computational time.    |
+|                                             |           | In C-band simulations, with input power per |
+|                                             |           | channel around 0 dBm, a suggested value of  |
+|                                             |           | spatial resolution is 100 m                 |
++---------------------------------------------+-----------+---------------------------------------------+
+| ``nli_params.method``                       | (string)  | Model used for the NLI evaluation. Valid    |
+|                                             |           | choices are ``gn_model_analytic`` (see      |
+|                                             |           | eq. 120 from `arXiv:1209.0394               |
+|                                             |           | <https://arxiv.org/abs/1209.0394>`_) and    |
+|                                             |           | ``ggn_spectrally_separated`` (see eq. 21    |
+|                                             |           | from `arXiv:1710.02225                      |
+|                                             |           | <https://arxiv.org/abs/1710.02225>`_).      |
++---------------------------------------------+-----------+---------------------------------------------+
+| ``nli_params.computed_channels``            | (number)  | The channels on which the NLI is            |
+|                                             |           | explicitly evaluated.                       |
+|                                             |           | The NLI of the other channels is            |
+|                                             |           | interpolated using ``numpy.interp``.        |
+|                                             |           | In a C-band simulation with 96 channels in  |
+|                                             |           | a 50 GHz spacing fix-grid we recommend at   |
+|                                             |           | one computed channel every 20 channels.     |
++---------------------------------------------+-----------+---------------------------------------------+
+
 Span
 ~~~~
 
@@ -182,23 +315,27 @@ Span configuration is not a list (which may change in later releases) and the us
 +-------------------------------------+-----------+---------------------------------------------+
 | field                               | type      | description                                 |
 +=====================================+===========+=============================================+
-| ``power_mode``                      | (boolean) | If false, gain mode. Auto-design sets       |
+| ``power_mode``                      | (boolean) | If false, **gain mode**. In the gain mode,  |
-|                                     |           | amplifier gain = preceding span loss,       |
+|                                     |           | only gain settings are used for             |
-|                                     |           | unless the amplifier exists and its         |
+|                                     |           | propagation, and ``delta_p`` is ignored.    |
-|                                     |           | gain > 0 in the topology input JSON.        |
+|                                     |           | If no ``gain_target`` is set in an          |
-|                                     |           | If true, power mode (recommended for        |
+|                                     |           | amplifier, auto-design computes one         |
-|                                     |           | auto-design and power sweep.)               |
+|                                     |           | according to the ``delta_power_range``      |
-|                                     |           | Auto-design sets amplifier power            |
+|                                     |           | optimisation range.                         |
-|                                     |           | according to delta_power_range. If the      |
+|                                     |           | The gain mode                               |
-|                                     |           | amplifier exists with gain > 0 in the       |
+|                                     |           | is recommended if all the amplifiers        |
-|                                     |           | topology JSON input, then its gain is       |
+|                                     |           | have already consistent gain settings in    |
-|                                     |           | translated into a power target/channel.     |
+|                                     |           | the topology input file.                    |
-|                                     |           | Moreover, when performing a power sweep     |
+|                                     |           |                                             |
-|                                     |           | (see ``power_range_db`` in the SI           |
+|                                     |           | If true, **power mode**. In the power mode, |
-|                                     |           | configuration library) the power sweep      |
+|                                     |           | only the ``delta_p`` is used for            |
-|                                     |           | is performed w/r/t this power target,       |
+|                                     |           | propagation, and ``gain_target`` is         |
-|                                     |           | regardless of preceding amplifiers          |
+|                                     |           | ignored.                                    |
-|                                     |           | power saturation/limitations.               |
+|                                     |           | The power mode is recommended for           |
+|                                     |           | auto-design and power sweep.                |
+|                                     |           | If no ``delta_p``  is set,                  |
+|                                     |           | auto-design sets an amplifier power target  |
+|                                     |           | according to delta_power_range_db.          |
 +-------------------------------------+-----------+---------------------------------------------+
 | ``delta_power_range_db``            | (number)  | Auto-design only, power-mode                |
 |                                     |           | only. Specifies the [min, max, step]        |
@@ -303,9 +440,9 @@ Span configuration is not a list (which may change in later releases) and the us
 SpectralInformation
 ~~~~~~~~~~~~~~~~~~~
 
-The user can only modify the value of existing parameters.
+GNPy requires a description of all channels that are propagated through the network.
-It defines a spectrum of N identical carriers.
+Flexgrid channel partitioning is available since the 2.7 release via the extra ``--spectrum`` option.
-While the code libraries allow for different carriers and power levels, the current user parametrization only allows one carrier type and one power/channel definition.
+In the simplest case, homogeneous channel allocation can be defined via the ``SpectralInformation`` construct which defines a spectrum of N identical carriers:
 
 +----------------------+-----------+-------------------------------------------+
 | field                |   type    | description                               |
@@ -326,11 +463,20 @@ While the code libraries allow for different carriers and power levels, the curr
 +----------------------+-----------+-------------------------------------------+
 | ``tx_osnr``          | (number)  | In dB. OSNR out from transponder.         |
 +----------------------+-----------+-------------------------------------------+
-| ``power_dbm``        | (number)  | Reference channel power. In gain mode     |
+| ``power_dbm``        | (number)  | Reference channel power, in dBm.          |
-|                      |           | (see spans/power_mode = false), all gain  |
+|                      |           | In gain mode                              |
-|                      |           | settings are offset w/r/t this reference  |
+|                      |           | (see spans/power_mode = false), if no     |
-|                      |           | power. In power mode, it is the           |
+|                      |           | gain is set in an amplifier, auto-design  |
-|                      |           | reference power for                       |
+|                      |           | sets gain to meet this reference          |
+|                      |           | power. If amplifiers gain is set,         |
+|                      |           | ``power_dbm`` is                          |
+|                      |           | ignored.                                  |
+|                      |           |                                           |
+|                      |           | In power mode, the ``power_dbm``          |
+|                      |           | is the reference power for                |
+|                      |           | the ``delta_p`` settings in amplifiers.   |
+|                      |           | It is also the reference power for        |
+|                      |           | auto-design power optimisation range      |
 |                      |           | Spans/delta_power_range_db. For example,  |
 |                      |           | if delta_power_range_db = `[0,0,0]`, the  |
 |                      |           | same power=power_dbm is launched in every |
@@ -338,12 +484,166 @@ While the code libraries allow for different carriers and power levels, the curr
 |                      |           | with the power_dbm value: even if a       |
 |                      |           | power sweep is defined (see after) the    |
 |                      |           | design is not repeated.                   |
+|                      |           |                                           |
+|                      |           | If the ``--power`` CLI option is used,    |
+|                      |           | its value replaces this parameter.        |
 +----------------------+-----------+-------------------------------------------+
-| ``power_range_db``   | (number)  | Power sweep excursion around power_dbm.   |
+| ``power_range_db``   | (number)  | Power sweep excursion around              |
-|                      |           | It is not the min and max channel power   |
+|                      |           | ``power_dbm``.                            |
-|                      |           | values! The reference power becomes:      |
+|                      |           | This defines a list of reference powers   |
+|                      |           | to run the propagation, in the range      |
 |                      |           | power_range_db + power_dbm.               |
+|                      |           | Power sweep uses the ``delta_p`` targets  |
+|                      |           | or, if they have not been set, the ones   |
+|                      |           | computed by auto-design, regardless of    |
+|                      |           | of preceding amplifiers' power            |
+|                      |           | saturation.                               |
+|                      |           |                                           |
+|                      |           | Power sweep is an easy way to find the    |
+|                      |           | optimal reference power.                  |
+|                      |           |                                           |
+|                      |           | Power sweep excursion is ignored in case  |
+|                      |           | of gain mode.                             |
 +----------------------+-----------+-------------------------------------------+
 | ``sys_margins``      | (number)  | In dB. Added margin on min required       |
 |                      |           | transceiver OSNR.                         |
 +----------------------+-----------+-------------------------------------------+
+
+.. _mixed-rate:
+
+Arbitrary channel definition
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Non-uniform channels are defined via a list of spectrum "partitions" which are defined in an extra JSON file via the ``--spectrum`` option.
+In this approach, each partition is internally homogeneous, but different partitions might use different channel widths, power targets, modulation rates, etc.
+
++----------------------+-----------+-------------------------------------------+
+| field                |   type    | description                               |
++======================+===========+===========================================+
+| ``f_min``,           | (number)  | In Hz. Mandatory.                         |
+| ``f_max``            |           | Define partition :math:`f_{min}` is       |
+|                      |           | the first carrier central frequency       |
+|                      |           | :math:`f_{max}` is the last one.          |
+|                      |           | :math:`f_{min}` -:math:`f_{max}`          |
+|                      |           | partitions must not overlap.              |
+|                      |           |                                           |
+|                      |           | Note that the meaning of ``f_min`` and    |
+|                      |           | ``f_max`` is different than the one in    |
+|                      |           | ``SpectralInformation``.                  |
++----------------------+-----------+-------------------------------------------+
+| ``baud_rate``        | (number)  | In Hz. Mandatory. Simulated baud rate.    |
++----------------------+-----------+-------------------------------------------+
+| ``slot_width``       | (number)  | In Hz. Carrier spectrum occupation.       |
+|                      |           | Carriers of this partition are spaced at  |
+|                      |           | ``slot_width`` offsets.                   |
++----------------------+-----------+-------------------------------------------+
+| ``roll_off``         | (number)  | Pure number between 0 and 1. Mandatory    |
+|                      |           | TX signal roll-off shape. Used by         |
+|                      |           | Raman-aware simulation code.              |
++----------------------+-----------+-------------------------------------------+
+| ``tx_osnr``          | (number)  | In dB. Optional. OSNR out from            |
+|                      |           | transponder. Default value is 40 dB.      |
++----------------------+-----------+-------------------------------------------+
+| ``delta_pdb``        | (number)  | In dB. Optional. Power offset compared to |
+|                      |           | the reference power used for design       |
+|                      |           | (SI block in equipment library) to be     |
+|                      |           | applied by ROADM to equalize the carriers |
+|                      |           | in this partition. Default value is 0 dB. |
++----------------------+-----------+-------------------------------------------+
+
+For example this example:
+
+.. code-block:: json
+
+ {
+   "SI":[
+     {
+       "f_min": 191.4e12,
+       "f_max":193.1e12,
+       "baud_rate": 32e9,
+       "slot_width": 50e9,
+       "roll_off": 0.15,
+       "tx_osnr": 40
+     },
+     {
+       "f_min": 193.1625e12,
+       "f_max":195e12,
+       "baud_rate": 64e9,
+       "delta_pdb": 3,
+       "slot_width": 75e9,
+       "roll_off": 0.15,
+       "tx_osnr": 40
+     }
+   ]
+ }
+
+...defines a spectrum split into two parts.
+Carriers with central frequencies ranging from 191.4 THz to 193.1 THz will have 32 GBaud rate and will be spaced by 50 Ghz.
+Carriers with central frequencies ranging from 193.1625 THz to 195 THz will have 64 GBaud rate and will be spaced by 75 GHz with 3 dB power offset.
+
+If the SI reference carrier is set to ``power_dbm`` = 0dBm, and the ROADM has ``target_pch_out_db`` set to -20 dBm, then all channels ranging from 191.4 THz to 193.1 THz will have their power equalized to -20 + 0 dBm (due to the 0 dB power offset).
+All channels ranging from 193.1625 THz to 195 THz will have their power equalized to -20 + 3 = -17 dBm (total power signal + noise).
+
+Note that first carrier of the second partition has center frequency 193.1625 THz (its spectrum occupation ranges from 193.125 THz to 193.2 THz).
+The last carrier of the second partition has center frequency 193.1 THz and spectrum occupation ranges from 193.075 THz to 193.125 THz.
+There is no overlap of the occupation and both share the same boundary.
+
+.. _equalization:
+
+Equalization choices
+~~~~~~~~~~~~~~~~~~~~
+
+ROADMs typically equalize the optical power across multiple channels using one of the available equalization strategies — either targeting a specific output power, or a specific power spectral density (PSD), or a spectfic power spectral density using slot_width as spectrum width reference (PSW).
+All of these strategies can be adjusted by a per-channel power offset.
+The equalization strategy can be defined globally per a ROADM model, or per each ROADM instance in the topology, and within a ROADM also on a per-degree basis.
+
+Let's consider some example for the equalization. Suppose that the types of signal to be propagated are the following:
+
+.. code-block:: json
+
+   {
+        "baud_rate": 32e9,
+        "f_min":191.3e12,
+        "f_max":192.3e12,
+        "spacing": 50e9,
+        "label": 1
+    },
+    {
+        "baud_rate": 64e9,
+        "f_min":193.3e12,
+        "f_max":194.3e12,
+        "spacing": 75e9,
+        "label": 2
+    }
+
+
+with the PSD equalization in a ROADM:
+
+.. code-block:: json
+
+    {
+      "uid": "roadm A",
+      "type": "Roadm",
+      "params": {
+        "target_psd_out_mWperGHz": 3.125e-4,
+      }
+    },
+
+
+This means that power out of the ROADM will be computed as 3.125e-4 * 32 = 0.01 mW ie -20 dBm for label 1 types of carriers
+and 3.125e4 * 64 = 0.02 mW ie -16.99 dBm for label2 channels. So a ratio of ~ 3 dB between target powers for these carriers.
+
+With the PSW equalization:
+
+.. code-block:: json
+
+    {
+      "uid": "roadm A",
+      "type": "Roadm",
+      "params": {
+        "target_out_mWperSlotWidth": 2.0e-4,
+      }
+    },
+
+the power out of the ROADM will be computed as 2.0e-4 * 50 = 0.01 mW ie -20 dBm for label 1 types of carriers
+and 2.0e4 * 75 = 0.015 mW ie -18.24 dBm for label2 channels. So a ratio of ~ 1.76 dB between target powers for these carriers.

docs/model.rst

@@ -126,9 +126,9 @@ that can be easily evaluated extending the FWM theory from a set of discrete
 tones - the standard FWM theory introduced back in the 90s by Inoue
 :cite:`Innoue-FWM`- to a continuity of tones, possibly spectrally shaped.
 Signals propagating in the fiber are not equivalent to Gaussian noise, but
-thanks to the absence of in-line compensation for choromatic dispersion, the
+thanks to the absence of in-line compensation for chromatic dispersion, the
 become so, over short distances.  So, the Gaussian noise model with incoherent
-accumulation of NLI has estensively proved to be a quick yet accurate and
+accumulation of NLI has extensively proved to be a quick yet accurate and
 conservative tool to estimate propagation impairments of fiber propagation.
 Note that the GN-model has not been derived with the aim of an *exact*
 performance estimation, but to pursue a conservative performance prediction.
@@ -145,4 +145,4 @@ Raman Scattering in order to give a proper estimation for all channels
 :cite:`cantono2018modeling`.  This will be the main upgrade required within the
 PSE framework.
 
-.. bibliography:: biblio.bib  
+.. bibliography::

docs/requirements.txt

@@ -1,7 +1,7 @@
 alabaster>=0.7.12,<1
-docutils>=0.15.2,<1
+docutils>=0.17.1,<1
-myst-parser>=0.14.0,<1
+myst-parser>=0.16.1,<1
-Pygments>=2.7.4,<3
+Pygments>=2.11.2,<3
 rstcheck
-Sphinx>=3.5.0,<4
+Sphinx>=4.4.0,<5
-sphinxcontrib-bibtex>=0.4.2,<1
+sphinxcontrib-bibtex>=2.4.1,<3

gnpy/__init__.py

@@ -1,8 +1,8 @@
-'''
+"""
 GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks. It is based on the Gaussian Noise Model.
 
 Signal propagation is implemented in :py:mod:`.core`.
 Path finding and spectrum assignment is in :py:mod:`.topology`.
 Various tools and auxiliary code, including the JSON I/O handling, is in
 :py:mod:`.tools`.
-'''
+"""

gnpy/core/__init__.py

@@ -1,4 +1,4 @@
-'''
+"""
 Simulation of signal propagation in the DWDM network
 
 Optical signals, as defined via :class:`.info.SpectralInformation`, enter
@@ -6,4 +6,4 @@ Optical signals, as defined via :class:`.info.SpectralInformation`, enter
 through the :py:mod:`.network`.
 The simulation is controlled via :py:mod:`.parameters` and implemented mainly
 via :py:mod:`.science_utils`.
-'''
+"""

gnpy/core/ansi_escapes.py

@@ -1,12 +1,12 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+"""
 gnpy.core.ansi_escapes
 ======================
 
 A random subset of ANSI terminal escape codes for colored messages
-'''
+"""
 
 red = '\x1b[1;31;40m'
 blue = '\x1b[1;34;40m'

gnpy/core/equipment.py

@@ -1,12 +1,12 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+"""
 gnpy.core.equipment
 ===================
 
 This module contains functionality for specifying equipment.
-'''
+"""
 
 from gnpy.core.utils import automatic_nch, db2lin
 from gnpy.core.exceptions import EquipmentConfigError
@@ -29,17 +29,22 @@ def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=F
             trx_params = {**mode_params}
             # sanity check: spacing baudrate must be smaller than min spacing
             if trx_params['baud_rate'] > trx_params['min_spacing']:
-                raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transpoder "{trx_type_variety}" mode "{trx_params["format"]}" ' +
+                raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transponder "{trx_type_variety}"'
-                                           f'has baud rate {trx_params["baud_rate"]*1e-9} GHz greater than min_spacing {trx_params["min_spacing"]*1e-9}.')
+                                           + f' mode "{trx_params["format"]}" has baud rate'
+                                           + f' {trx_params["baud_rate"] * 1e-9:.3f} GHz greater than min_spacing'
+                                           + f' {trx_params["min_spacing"] * 1e-9:.3f}.')
+            trx_params['equalization_offset_db'] = trx_params.get('equalization_offset_db', 0)
         else:
             mode_params = {"format": "undetermined",
                            "baud_rate": None,
                            "OSNR": None,
+                           "penalties": None,
                            "bit_rate": None,
                            "roll_off": None,
                            "tx_osnr": None,
                            "min_spacing": None,
-                           "cost": None}
+                           "cost": None,
+                           "equalization_offset_db": 0}
             trx_params = {**mode_params}
         trx_params['f_min'] = equipment['Transceiver'][trx_type_variety].frequency['min']
         trx_params['f_max'] = equipment['Transceiver'][trx_type_variety].frequency['max']
@@ -59,14 +64,13 @@ def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=F
             trx_params['baud_rate'] = default_si_data.baud_rate
             trx_params['spacing'] = default_si_data.spacing
             trx_params['OSNR'] = None
+            trx_params['penalties'] = {}
             trx_params['bit_rate'] = None
             trx_params['cost'] = None
             trx_params['roll_off'] = default_si_data.roll_off
             trx_params['tx_osnr'] = default_si_data.tx_osnr
             trx_params['min_spacing'] = None
-            nch = automatic_nch(trx_params['f_min'], trx_params['f_max'], trx_params['spacing'])
+            trx_params['equalization_offset_db'] = 0
-            trx_params['nb_channel'] = nch
-            print(f'There are {nch} channels propagating')
 
     trx_params['power'] = db2lin(default_si_data.power_dbm) * 1e-3
 

gnpy/core/info.py

@@ -8,49 +8,397 @@ 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
+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 Channel(
-    """ Class containing the parameters of a WDM signal.
+    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 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 ')):
+class Pref(namedtuple('Pref', 'p_span0, p_spani, ref_carrier')):
     """noiseless reference power in dBm:
-    p_span0: inital target carrier power
+
-    p_spani: carrier power after element i
+    p_span0: inital target carrier power for a reference channel defined by user
-    neq_ch: equivalent channel count in dB"""
+    p_spani: carrier power after element i for a reference channel defined by user
+    ref_carrier records the baud rate of the reference channel
+    """
 
 
-class SpectralInformation(namedtuple('SpectralInformation', 'pref carriers')):
+class SpectralInformation(object):
+    """Class containing the parameters of the entire WDM comb.
 
-    def __new__(cls, pref, carriers):
+    delta_pdb_per_channel: (per frequency) per channel delta power in dbm for the actual mix of channels"""
-        return super().__new__(cls, pref, carriers)
+
+    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, ref_power: Pref, 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._pref = ref_power
+        self._label = label[indices]
+
+    @property
+    def pref(self):
+        """Instance of gnpy.info.Pref"""
+        return self._pref
+
+    @pref.setter
+    def pref(self, pref: Pref):
+        self._pref = pref
+
+    @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 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:
+            # Note that pref.p_spanx from "self" and "other" must be identical for a given simulation (correspond to the
+            # the simulation setup):
+            # - for a given simulation there is only one design (one p_span0),
+            # - and p_spani is the propagation result of p_span0 so there should not be different p_spani either.
+            if (self.pref.p_span0 != other.pref.p_span0) or (self.pref.p_spani != other.pref.p_spani):
+                raise SpectrumError('reference powers of the spectrum are not identical')
+            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),
+                                       ref_power=Pref(self.pref.p_span0, self.pref.p_spani, self.pref.ref_carrier),
+                                       label=append(self.label, other.label))
+        except SpectrumError:
+            raise SpectrumError('Spectra cannot be summed: channels overlapping.')
 
 
-def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, power, spacing):
+    def _replace(self, carriers, pref):
-    # pref in dB : convert power lin into power in dB
+        self.chromatic_dispersion = array([c.chromatic_dispersion for c in carriers])
-    pref = lin2db(power * 1e3)
+        self.pmd = array([c.pmd for c in carriers])
-    nb_channel = automatic_nch(f_min, f_max, spacing)
+        self.pdl = array([c.pdl for c in carriers])
-    si = SpectralInformation(
+        self.latency = array([c.latency for c in carriers])
-        pref=Pref(pref, pref, lin2db(nb_channel)),
+        self.signal = array([c.power.signal for c in carriers])
-        carriers=[
+        self.nli = array([c.power.nli for c in carriers])
-            Channel(f, (f_min + spacing * f),
+        self.ase = array([c.power.ase for c in carriers])
-                    baud_rate, roll_off, Power(power, 0, 0), 0, 0) for f in range(1, nb_channel + 1)
+        self.pref = pref
-        ]
+        return self
-    )
+
-    return si
+
+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],
+                                          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.,
+                                          ref_power: Pref = None,
+                                          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)
+        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,
+                                   ref_power=ref_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, tx_osnr, delta_pdb=0,
+                                      ref_carrier=None):
+    """Creates a fixed slot width spectral information with flat power.
+    all arguments are scalar values"""
+    number_of_channels = automatic_nch(f_min, f_max, spacing)
+    frequency = [(f_min + spacing * i) for i in range(1, number_of_channels + 1)]
+    p_span0 = watt2dbm(power)
+    p_spani = watt2dbm(power)
+    delta_pdb_per_channel = delta_pdb * ones(number_of_channels)
+    label = [f'{baud_rate * 1e-9 :.2f}G' for i in range(number_of_channels)]
+    return create_arbitrary_spectral_information(frequency, slot_width=spacing, signal=power, baud_rate=baud_rate,
+                                                 roll_off=roll_off, delta_pdb_per_channel=delta_pdb_per_channel,
+                                                 tx_osnr=tx_osnr,
+                                                 ref_power=Pref(p_span0=p_span0, p_spani=p_spani,
+                                                                ref_carrier=ref_carrier),
+                                                 label=label)
+
+
+def carriers_to_spectral_information(initial_spectrum: dict[float, Carrier], power: float,
+                                     ref_carrier: ReferenceCarrier) -> SpectralInformation:
+    """Initial spectrum is a dict with key = carrier frequency, and value a Carrier object.
+    :param initial_spectrum: indexed by frequency in Hz, with power offset (delta_pdb), baudrate, slot width,
+    tx_osnr and roll off.
+    :param power: power of the request
+    :param ref_carrier: reference carrier (baudrate) used for the reference channel
+    """
+    frequency = list(initial_spectrum.keys())
+    signal = [power * db2lin(c.delta_pdb) 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()]
+    label = [c.label for c in initial_spectrum.values()]
+    p_span0 = watt2dbm(power)
+    p_spani = watt2dbm(power)
+    return create_arbitrary_spectral_information(frequency=frequency, signal=signal, baud_rate=baud_rate,
+                                                 slot_width=slot_width, roll_off=roll_off,
+                                                 delta_pdb_per_channel=delta_pdb_per_channel, tx_osnr=tx_osnr,
+                                                 ref_power=Pref(p_span0=p_span0, p_spani=p_spani,
+                                                                ref_carrier=ref_carrier),
+                                                 label=label)
+
+
+@dataclass
+class Carrier:
+    """One channel in the initial mixed-type spectrum definition, each type being defined by
+    its delta_pdb (power offset with respect to reference power), baud rate, slot_width, roll_off
+    and tx_osnr. delta_pdb offset is applied to target power out of Roadm.
+    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
+    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 p_span_i 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 slot_width or roll-off) may be added there for future equalization purpose.
+    """
+    baud_rate: float
+    slot_width: float

gnpy/core/network.py

@@ -1,18 +1,25 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+"""
 gnpy.core.network
 =================
 
 Working with networks which consist of network elements
-'''
+"""
 
 from operator import attrgetter
-from gnpy.core import ansi_escapes, elements
+from collections import namedtuple
+from logging import getLogger
+
+from gnpy.core import elements
 from gnpy.core.exceptions import ConfigurationError, NetworkTopologyError
 from gnpy.core.utils import round2float, convert_length
-from collections import namedtuple
+from gnpy.core.info import ReferenceCarrier
+from gnpy.tools.json_io import Amp
+
+
+logger = getLogger(__name__)
 
 
 def edfa_nf(gain_target, variety_type, equipment):
@@ -27,6 +34,7 @@ def edfa_nf(gain_target, variety_type, equipment):
     )
     amp.pin_db = 0
     amp.nch = 88
+    amp.slot_width = 50e9
     return amp._calc_nf(True)
 
 
@@ -102,10 +110,9 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restri
                     please increase span fiber padding')
         else:
             # TODO: convert to logging
-            print(
+            logger.warning(f'\n\tWARNING: target gain in node {uid} is below all available amplifiers min gain: '
-                f'{ansi_escapes.red}WARNING:{ansi_escapes.reset} target gain in node {uid} is below all available amplifiers min gain: \
+                           + '\n\tamplifier input padding will be assumed, consider increase span fiber padding '
-                  amplifier input padding will be assumed, consider increase span fiber padding instead'
+                           + 'instead.\n')
-            )
             acceptable_gain_min_list = edfa_list
 
     # filter on gain+power limitation:
@@ -127,12 +134,9 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restri
     # check what are the gain and power limitations of this amp
     power_reduction = round(min(selected_edfa.power, 0), 2)
     if power_reduction < -0.5:
-        print(
+        logger.warning(f'\n\tWARNING: target gain and power in node {uid}\n'
-            f'{ansi_escapes.red}WARNING:{ansi_escapes.reset} target gain and power in node {uid}\n \
+                       + '\tis beyond all available amplifiers capabilities and/or extended_gain_range:\n'
-    is beyond all available amplifiers capabilities and/or extended_gain_range:\n\
+                       + f'\ta power reduction of {power_reduction} is applied\n')
-    a power reduction of {power_reduction} is applied\n'
-        )
-
     return selected_edfa.variety, power_reduction
 
 
@@ -233,25 +237,22 @@ def set_amplifier_voa(amp, power_target, power_mode):
 
 
 def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_db):
-    """ this node can be a transceiver or a ROADM (same function called in both cases)
+    """this node can be a transceiver or a ROADM (same function called in both cases)"""
-    """
     power_mode = equipment['Span']['default'].power_mode
+    ref_carrier = ReferenceCarrier(baud_rate=equipment['SI']['default'].baud_rate,
+                                   slot_width=equipment['SI']['default'].spacing)
     next_oms = (n for n in network.successors(this_node) if not isinstance(n, elements.Transceiver))
-    this_node_degree = {k: v for k, v in this_node.per_degree_pch_out_db.items()} if hasattr(this_node, 'per_degree_pch_out_db') else {}
     for oms in next_oms:
         # go through all the OMS departing from the ROADM
         prev_node = this_node
         node = oms
-        # if isinstance(next_node, elements.Fused): #support ROADM wo egress amp for metro applications
+        if isinstance(this_node, elements.Transceiver):
-        #     node = find_last_node(next_node)
+            this_node_out_power = 0.0     # default value if this_node is a transceiver
-        #     next_node = next(n for n in network.successors(node))
+        if isinstance(this_node, elements.Roadm):
-        #     next_node = find_last_node(next_node)
+            # get target power out from ROADM for the reference carrier based on equalization settings
-        if node.uid not in this_node_degree:
+            this_node_out_power = this_node.get_per_degree_ref_power(degree=node.uid, ref_carrier=ref_carrier)
-            # if no target power is defined on this degree or no per degree target power is given use the global one
-            # if target_pch_out_db  is not an attribute, then the element must be a transceiver
-            this_node_degree[node.uid] = getattr(this_node.params, 'target_pch_out_db', 0)
         # use the target power on this degree
-        prev_dp = this_node_degree[node.uid] - pref_ch_db
+        prev_dp = this_node_out_power - pref_ch_db
         dp = prev_dp
         prev_voa = 0
         voa = 0
@@ -269,7 +270,7 @@ def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_d
                 node_loss = span_loss(network, prev_node)
                 voa = node.out_voa if node.out_voa else 0
                 if node.delta_p is None:
-                    dp = target_power(network, next_node, equipment)
+                    dp = target_power(network, next_node, equipment) + voa
                 else:
                     dp = node.delta_p
                 if node.effective_gain is None or power_mode:
@@ -282,8 +283,8 @@ def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_d
 
                 if isinstance(prev_node, elements.Fiber):
                     max_fiber_lineic_loss_for_raman = \
-                        equipment['Span']['default'].max_fiber_lineic_loss_for_raman
+                        equipment['Span']['default'].max_fiber_lineic_loss_for_raman * 1e-3  # dB/m
-                    raman_allowed = prev_node.params.loss_coef < max_fiber_lineic_loss_for_raman
+                    raman_allowed = (prev_node.params.loss_coef < max_fiber_lineic_loss_for_raman).all()
                 else:
                     raman_allowed = False
 
@@ -303,19 +304,24 @@ def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_d
                     node.params.update_params(extra_params.__dict__)
                     dp += power_reduction
                     gain_target += power_reduction
-                elif node.params.raman and not raman_allowed:
-                    print(f'{ansi_escapes.red}WARNING{ansi_escapes.reset}: raman is used in node {node.uid}\n but fiber lineic loss is above threshold\n')
                 else:
+                    if node.params.raman and not raman_allowed:
+                        if isinstance(prev_node, elements.Fiber):
+                            logger.warning(f'\n\tWARNING: raman is used in node {node.uid}\n '
+                                           + '\tbut fiber lineic loss is above threshold\n')
+                        else:
+                            logger.critical(f'\n\tWARNING: raman is used in node {node.uid}\n '
+                                            + '\tbut previous node is not a fiber\n')
                     # if variety is imposed by user, and if the gain_target (computed or imposed) is also above
                     # variety max gain + extended range, then warn that gain > max_gain + extended range
                     if gain_target - equipment['Edfa'][node.params.type_variety].gain_flatmax - \
                             equipment['Span']['default'].target_extended_gain > 1e-2:
                         # 1e-2 to allow a small margin according to round2float min step
-                        print(f'{ansi_escapes.red}WARNING{ansi_escapes.reset}: '
+                        logger.warning(f'\n\tWARNING: effective gain in Node {node.uid}\n'
-                              f'WARNING: effective gain in Node {node.uid} is above user '
+                                       + f'\tis above user specified amplifier {node.params.type_variety}\n'
-                              f'specified amplifier {node.params.type_variety}\n'
+                                       + '\tmax flat gain: '
-                              f'max flat gain: {equipment["Edfa"][node.params.type_variety].gain_flatmax}dB ; '
+                                       + f'{equipment["Edfa"][node.params.type_variety].gain_flatmax}dB ; '
-                              f'required gain: {gain_target}dB. Please check amplifier type.')
+                                       + f'required gain: {gain_target}dB. Please check amplifier type.\n')
 
                 node.delta_p = dp if power_mode else None
                 node.effective_gain = gain_target
@@ -325,10 +331,28 @@ def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_d
             prev_voa = voa
             prev_node = node
             node = next_node
-            # print(f'{node.uid}')
 
-    if isinstance(this_node, elements.Roadm):
+
-        this_node.per_degree_pch_out_db = {k: v for k, v in this_node_degree.items()}
+def set_roadm_per_degree_targets(roadm, network):
+    """Set target powers/PSD on all degrees
+    This is needed to populate per_degree_pch_out_dbm or per_degree_pch_psd or per_degree_pch_psw dicts when
+    they are not initialized by users.
+    """
+    next_oms = (n for n in network.successors(roadm) if not isinstance(n, elements.Transceiver))
+
+    for node in next_oms:
+        # go through all the OMS departing from the ROADM
+        if node.uid not in roadm.per_degree_pch_out_dbm and node.uid not in roadm.per_degree_pch_psd and \
+                node.uid not in roadm.per_degree_pch_psw:
+            # if no target power is defined on this degree or no per degree target power is given use the global one
+            if roadm.params.target_pch_out_db:
+                roadm.per_degree_pch_out_dbm[node.uid] = roadm.params.target_pch_out_db
+            elif roadm.params.target_psd_out_mWperGHz:
+                roadm.per_degree_pch_psd[node.uid] = roadm.params.target_psd_out_mWperGHz
+            elif roadm.params.target_out_mWperSlotWidth:
+                roadm.per_degree_pch_psw[node.uid] = roadm.params.target_out_mWperSlotWidth
+            else:
+                raise ConfigurationError(roadm.uid, 'needs an equalization target')
 
 
 def add_roadm_booster(network, roadm):
@@ -339,7 +363,7 @@ def add_roadm_booster(network, roadm):
         network.remove_edge(roadm, next_node)
         amp = elements.Edfa(
             uid=f'Edfa_booster_{roadm.uid}_to_{next_node.uid}',
-            params={},
+            params=Amp.default_values,
             metadata={
                 'location': {
                     'latitude': roadm.lat,
@@ -365,7 +389,7 @@ def add_roadm_preamp(network, roadm):
         network.remove_edge(prev_node, roadm)
         amp = elements.Edfa(
             uid=f'Edfa_preamp_{roadm.uid}_from_{prev_node.uid}',
-            params={},
+            params=Amp.default_values,
             metadata={
                 'location': {
                     'latitude': roadm.lat,
@@ -394,7 +418,7 @@ def add_inline_amplifier(network, fiber):
         network.remove_edge(fiber, next_node)
         amp = elements.Edfa(
             uid=f'Edfa_{fiber.uid}',
-            params={},
+            params=Amp.default_values,
             metadata={
                 'location': {
                     'latitude': (fiber.lat + next_node.lat) / 2,
@@ -426,10 +450,10 @@ def calculate_new_length(fiber_length, bounds, target_length):
         return (length1, n_spans1)
     elif (bounds.start <= length2 <= bounds.stop) and not(bounds.start <= length1 <= bounds.stop):
         return (length2, n_spans2)
-    elif target_length - length1 < length2 - target_length:
+    elif length2 - target_length <= target_length - length1 and length2 <= bounds.stop:
-        return (length1, n_spans1)
-    else:
         return (length2, n_spans2)
+    else:
+        return (length1, n_spans1)
 
 
 def split_fiber(network, fiber, bounds, target_length, equipment):
@@ -511,23 +535,25 @@ def add_fiber_padding(network, fibers, padding):
                 first_fiber.params.att_in = first_fiber.params.att_in + padding - this_span_loss
 
 
-def build_network(network, equipment, pref_ch_db, pref_total_db):
+def build_network(network, equipment, pref_ch_db, pref_total_db, no_insert_edfas=False):
     default_span_data = equipment['Span']['default']
     max_length = int(convert_length(default_span_data.max_length, default_span_data.length_units))
     min_length = max(int(default_span_data.padding / 0.2 * 1e3), 50_000)
     bounds = range(min_length, max_length)
-    target_length = max(min_length, 90_000)
+    target_length = max(min_length, min(max_length, 90_000))
 
     # set roadm loss for gain_mode before to build network
     fibers = [f for f in network.nodes() if isinstance(f, elements.Fiber)]
     add_connector_loss(network, fibers, default_span_data.con_in, default_span_data.con_out, default_span_data.EOL)
-    add_fiber_padding(network, fibers, default_span_data.padding)
     # don't group split fiber and add amp in the same loop
     # =>for code clarity (at the expense of speed):
+
+    roadms = [r for r in network.nodes() if isinstance(r, elements.Roadm)]
+
+    if not no_insert_edfas:
         for fiber in fibers:
             split_fiber(network, fiber, bounds, target_length, equipment)
 
-    roadms = [r for r in network.nodes() if isinstance(r, elements.Roadm)]
         for roadm in roadms:
             add_roadm_preamp(network, roadm)
             add_roadm_booster(network, roadm)
@@ -536,7 +562,10 @@ def build_network(network, equipment, pref_ch_db, pref_total_db):
         for fiber in fibers:
             add_inline_amplifier(network, fiber)
 
+    add_fiber_padding(network, fibers, default_span_data.padding)
+
     for roadm in roadms:
+        set_roadm_per_degree_targets(roadm, network)
         set_egress_amplifier(network, roadm, equipment, pref_ch_db, pref_total_db)
 
     trx = [t for t in network.nodes() if isinstance(t, elements.Transceiver)]

gnpy/core/parameters.py

@@ -7,11 +7,12 @@ gnpy.core.parameters
 
 This module contains all parameters to configure standard network elements.
 """
+from collections import namedtuple
 
 from scipy.constants import c, pi
-from numpy import 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 +29,128 @@ class Parameters:
 
 class PumpParams(Parameters):
     def __init__(self, power, frequency, propagation_direction):
-        self._power = power
+        self.power = power
-        self._frequency = frequency
+        self.frequency = frequency
-        self._propagation_direction = propagation_direction
+        self.propagation_direction = propagation_direction.lower()
-
-    @property
-    def power(self):
-        return self._power
-
-    @property
-    def frequency(self):
-        return self._frequency
-
-    @property
-    def propagation_direction(self):
-        return self._propagation_direction
 
 
 class RamanParams(Parameters):
-    def __init__(self, **kwargs):
+    def __init__(self, flag=False, result_spatial_resolution=10e3, solver_spatial_resolution=50):
-        self._flag_raman = kwargs['flag_raman']
+        """Simulation parameters used within the Raman Solver
-        self._space_resolution = kwargs['space_resolution'] if 'space_resolution' in kwargs else None
-        self._tolerance = kwargs['tolerance'] if 'tolerance' in kwargs else None
 
-    @property
+        :params flag: boolean for enabling/disable the evaluation of the Raman power profile in frequency and position
-    def flag_raman(self):
+        :params result_spatial_resolution: spatial resolution of the evaluated Raman power profile
-        return self._flag_raman
+        :params solver_spatial_resolution: spatial step for the iterative solution of the first order ode
-
+        """
-    @property
+        self.flag = flag
-    def space_resolution(self):
+        self.result_spatial_resolution = result_spatial_resolution  # [m]
-        return self._space_resolution
+        self.solver_spatial_resolution = solver_spatial_resolution  # [m]
-
-    @property
-    def tolerance(self):
-        return self._tolerance
 
 
 class NLIParams(Parameters):
-    def __init__(self, **kwargs):
+    def __init__(self, method='gn_model_analytic', dispersion_tolerance=1, phase_shift_tolerance=0.1,
-        self._nli_method_name = kwargs['nli_method_name']
+                 computed_channels=None):
-        self._wdm_grid_size = kwargs['wdm_grid_size']
+        """Simulation parameters used within the Nli Solver
-        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
 
-    @property
+        :params method: formula for NLI calculation
-    def nli_method_name(self):
+        :params dispersion_tolerance: tuning parameter for ggn model solution
-        return self._nli_method_name
+        :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
-    @property
+        """
-    def wdm_grid_size(self):
+        self.method = method.lower()
-        return self._wdm_grid_size
+        self.dispersion_tolerance = dispersion_tolerance
-
+        self.phase_shift_tolerance = phase_shift_tolerance
-    @property
+        self.computed_channels = computed_channels
-    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
 
 
 class SimParams(Parameters):
-    def __init__(self, **kwargs):
+    _shared_dict = {'nli_params': NLIParams(), 'raman_params': RamanParams()}
-        try:
+
-            if 'nli_parameters' in kwargs:
+    @classmethod
-                self._nli_params = NLIParams(**kwargs['nli_parameters'])
+    def set_params(cls, sim_params):
-            else:
+        cls._shared_dict['nli_params'] = NLIParams(**sim_params.get('nli_params', {}))
-                self._nli_params = None
+        cls._shared_dict['raman_params'] = RamanParams(**sim_params.get('raman_params', {}))
-            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}')
 
     @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']
+        except KeyError as e:
+            raise ParametersError(f'ROADM configurations must include {e}. Configuration: {kwargs}')
+
+
+class FusedParams(Parameters):
+    def __init__(self, **kwargs):
+        self.loss = kwargs['loss'] if 'loss' in kwargs else 1
+
+
+DEFAULT_RAMAN_COEFFICIENT = {
+    # SSMF Raman coefficient profile normalized with respect to the effective area overlap (g0 * A_eff(f_probe, f_pump))
+    'g0': array(
+        [0.00000000e+00, 1.12351610e-05, 3.47838074e-05, 5.79356636e-05, 8.06921680e-05, 9.79845709e-05, 1.10454361e-04,
+         1.18735302e-04, 1.24736889e-04, 1.30110053e-04, 1.41001273e-04, 1.46383247e-04, 1.57011792e-04, 1.70765865e-04,
+         1.88408911e-04, 2.05914127e-04, 2.24074028e-04, 2.47508283e-04, 2.77729174e-04, 3.08044243e-04, 3.34764439e-04,
+         3.56481704e-04, 3.77127256e-04, 3.96269124e-04, 4.10955175e-04, 4.18718761e-04, 4.19511263e-04, 4.17025384e-04,
+         4.13565369e-04, 4.07726048e-04, 3.83671291e-04, 4.08564283e-04, 3.69571936e-04, 3.14442090e-04, 2.16074535e-04,
+         1.23097823e-04, 8.95457457e-05, 7.52470400e-05, 7.19806145e-05, 8.87961158e-05, 9.30812065e-05, 9.37058268e-05,
+         8.45719619e-05, 6.90585286e-05, 4.50407159e-05, 3.36521245e-05, 3.02292475e-05, 2.69376939e-05, 2.60020897e-05,
+         2.82958958e-05, 3.08667558e-05, 3.66024657e-05, 5.80610307e-05, 6.54797937e-05, 6.25022715e-05, 5.37806442e-05,
+         3.94996621e-05, 2.68120644e-05, 2.33038554e-05, 1.79140757e-05, 1.52472424e-05, 1.32707565e-05, 1.06541760e-05,
+         9.84649374e-06, 9.13999627e-06, 9.08971012e-06, 1.04227525e-05, 1.50419271e-05, 1.77838232e-05, 2.15810815e-05,
+         2.03744008e-05, 1.81939341e-05, 1.31862121e-05, 9.65352116e-06, 8.62698322e-06, 9.18688016e-06, 1.01737784e-05,
+         1.08017817e-05, 1.03903588e-05, 9.30040333e-06, 8.30809173e-06, 6.90650401e-06, 5.52238029e-06, 3.90648708e-06,
+         2.22908227e-06, 1.55796177e-06, 9.77218716e-07, 3.23477236e-07, 1.60602454e-07, 7.97306386e-08]
+    ),  # [m/W]
+
+    # Note the non-uniform spacing of this range; this is required for properly capturing the Raman peak shape.
+    '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': 206184634112792  # [Hz] (1454 nm)}
+}
+
+
+class RamanGainCoefficient(namedtuple('RamanGainCoefficient', 'normalized_gamma_raman frequency_offset')):
+    """ Raman Gain Coefficient Parameters
+
+        Based on:
+            Andrea D’Amico, Bruno Correia, Elliot London, Emanuele Virgillito, Giacomo Borraccini, Antonio Napoli,
+            and Vittorio Curri, "Scalable and Disaggregated GGN Approximation Applied to a C+L+S Optical Network,"
+            J. Lightwave Technol. 40, 3499-3511 (2022)
+            Section III.D
+    """
 
 
 class FiberParams(Parameters):
@@ -139,45 +158,87 @@ 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_in = kwargs.get('con_in')
-            self._con_out = kwargs['con_out'] if 'con_out' in kwargs else None
+            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_wavelength = 1550e-9  # conventional central C band wavelength [m]
-                self._ref_frequency = c / self.ref_wavelength
+                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 \
+            # Chromatic Dispersion
-                -2 * self._dispersion/self.ref_wavelength  # s/m/m/m
+            if 'dispersion_per_frequency' in kwargs:
-            self._beta2 = -(self.ref_wavelength ** 2) * self.dispersion / (2 * pi * c)  # 1/(m * Hz^2)
+                # Frequency-dependent dispersion
-            # Eq. (3.23) in  Abramczyk, Halina. "Dispersion phenomena in optical fibers." Virtual European University
+                self._dispersion = asarray(kwargs['dispersion']['value'])  # s/m/m
-            # on Lasers. Available online: http://mitr.p.lodz.pl/evu/lectures/Abramczyk3.pdf
+                self._f_dispersion_ref = asarray(kwargs['dispersion']['frequency'])  # Hz
-            # (accessed on 25 March 2018) (2005).
+                self._dispersion_slope = None
-            self._beta3 = ((self.dispersion_slope - (4*pi*c/self.ref_wavelength**3) * self.beta2) /
+            elif 'dispersion' in kwargs:
-                           (2*pi*c/self.ref_wavelength**2)**2)
+                # 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._pmd_coef = kwargs['pmd_coef']  # s/sqrt(m)
+                self._effective_area = 2 * pi * self._n2 / (self._ref_wavelength * self._gamma)  # m^2
-            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
             else:
-                self._loss_coef = kwargs['loss_coef'] * 1e-3  # lineic loss dB/m
+                self._effective_area = 83e-12  # m^2
-                self._f_loss_ref = 193.5e12  # Hz
+                self._gamma = 2 * pi * self._n2 / (self._ref_wavelength * self._effective_area)  # 1/W/m
-            self._lin_attenuation = db2lin(self.length * self.loss_coef)
+            self._contrast = 0.5 * (c / (2 * pi * self._ref_frequency * self._core_radius * self._n1) * exp(
-            self._lin_loss_exp = self.loss_coef / (10 * log10(exp(1)))  # linear power exponent loss Neper/m
+                pi * self._core_radius ** 2 / self._effective_area)) ** 2
-            self._effective_length = (1 - exp(- self.lin_loss_exp * self.length)) / self.lin_loss_exp
+
-            self._asymptotic_length = 1 / self.lin_loss_exp
+            # Raman Gain Coefficient
-            # raman parameters (not compulsory)
+            raman_coefficient = kwargs.get('raman_coefficient', DEFAULT_RAMAN_COEFFICIENT)
-            self._raman_efficiency = kwargs['raman_efficiency'] if 'raman_efficiency' in kwargs else None
+            self._g0 = asarray(raman_coefficient['g0'])
-            self._pumps_loss_coef = kwargs['pumps_loss_coef'] if 'pumps_loss_coef' in kwargs else None
+            raman_reference_frequency = raman_coefficient['reference_frequency']
+            frequency_offset = asarray(raman_coefficient['frequency_offset'])
+            stokes_wave = raman_reference_frequency - frequency_offset
+            gamma_raman = self._g0 * self.effective_area_overlap(stokes_wave, raman_reference_frequency)
+            normalized_gamma_raman = gamma_raman / raman_reference_frequency  # 1 / m / W / Hz
+            self._raman_reference_frequency = raman_reference_frequency
+
+            # Raman gain coefficient array of the frequency offset constructed such that positive frequency values
+            # represent a positive power transfer from higher frequency and vice versa
+            frequency_offset = append(-flip(frequency_offset[1:]), frequency_offset)
+            normalized_gamma_raman = append(- flip(normalized_gamma_raman[1:]), normalized_gamma_raman)
+            self._raman_coefficient = RamanGainCoefficient(normalized_gamma_raman, frequency_offset)
+
+            # Polarization Mode Dispersion
+            self._pmd_coef = kwargs['pmd_coef']  # s/sqrt(m)
+
+            # Loss Coefficient
+            if isinstance(kwargs['loss_coef'], dict):
+                self._loss_coef = asarray(kwargs['loss_coef']['value']) * 1e-3  # lineic loss dB/m
+                self._f_loss_ref = asarray(kwargs['loss_coef']['frequency'])  # Hz
+            else:
+                self._loss_coef = asarray(kwargs['loss_coef']) * 1e-3  # lineic loss dB/m
+                self._f_loss_ref = asarray(self._ref_frequency)  # Hz
+            # 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 +271,10 @@ 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 +283,10 @@ class FiberParams(Parameters):
     def dispersion(self):
         return self._dispersion
 
+    @property
+    def f_dispersion_ref(self):
+        return self._f_dispersion_ref
+
     @property
     def dispersion_slope(self):
         return self._dispersion_slope
@@ -226,6 +295,20 @@ class FiberParams(Parameters):
     def gamma(self):
         return self._gamma
 
+    def effective_area_scaling(self, frequency):
+        V = 2 * pi * frequency / c * self._core_radius * self._n1 * sqrt(2 * self._contrast)
+        w = self._core_radius / sqrt(log(V))
+        return asarray(pi * w ** 2)
+
+    def effective_area_overlap(self, frequency_stokes_wave, frequency_pump):
+        effective_area_stokes_wave = self.effective_area_scaling(frequency_stokes_wave)
+        effective_area_pump = self.effective_area_scaling(frequency_pump)
+        return squeeze(outer(effective_area_stokes_wave, ones(effective_area_pump.size)) + outer(
+            ones(effective_area_stokes_wave.size), effective_area_pump)) / 2
+
+    def gamma_scaling(self, frequency):
+        return asarray(2 * pi * self._n2 * frequency / (c * self.effective_area_scaling(frequency)))
+
     @property
     def pmd_coef(self):
         return self._pmd_coef
@@ -238,14 +321,6 @@ class FiberParams(Parameters):
     def ref_frequency(self):
         return self._ref_frequency
 
-    @property
-    def beta2(self):
-        return self._beta2
-
-    @property
-    def beta3(self):
-        return self._beta3
-
     @property
     def loss_coef(self):
         return self._loss_coef
@@ -255,31 +330,148 @@ class FiberParams(Parameters):
         return self._f_loss_ref
 
     @property
-    def lin_loss_exp(self):
+    def raman_coefficient(self):
-        return self._lin_loss_exp
+        return self._raman_coefficient
 
     @property
-    def lin_attenuation(self):
+    def latency(self):
-        return self._lin_attenuation
+        return self._latency
-
-    @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 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:
+    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
+            self.f_cent = (self.f_max + self.f_min) / 2
+            self.f_ripple_ref = params['f_ripple_ref']
+
+            # Gain
+            self.gain_flatmax = params['gain_flatmax']
+            self.gain_min = params['gain_min']
+
+            gain_ripple = params['gain_ripple']
+            if gain_ripple == 0:
+                self.gain_ripple = asarray([0, 0])
+                self.f_ripple_ref = asarray([self.f_min, self.f_max])
+            else:
+                self.gain_ripple = asarray(gain_ripple)
+                if self.f_ripple_ref is not None:
+                    if (self.f_ripple_ref[0] != self.f_min) or (self.f_ripple_ref[-1] != self.f_max):
+                        raise ParametersError("The reference ripple frequency maximum and minimum have to coincide "
+                                              "with the EDFA frequency maximum and minimum.")
+                    elif self.gain_ripple.size != self.f_ripple_ref.size:
+                        raise ParametersError("The reference ripple frequency and the gain ripple must have the same "
+                                              "size.")
+                else:
+                    self.f_ripple_ref = linspace(self.f_min, self.f_max, self.gain_ripple.size)
+
+            tilt_ripple = params['tilt_ripple']
+
+            if tilt_ripple == 0:
+                self.tilt_ripple = full(self.gain_ripple.size, 0)
+            else:
+                self.tilt_ripple = asarray(tilt_ripple)
+                if self.tilt_ripple.size != self.gain_ripple.size:
+                    raise ParametersError("The tilt ripple and the gain ripple must have the same size.")
+
+            # Power
+            self.p_max = params['p_max']
+
+            # Noise Figure
+            self.nf_model = params['nf_model']
+            self.nf_min = params['nf_min']
+            self.nf_max = params['nf_max']
+            self.nf_coef = params['nf_coef']
+            self.nf0 = params['nf0']
+            self.nf_fit_coeff = params['nf_fit_coeff']
+
+            nf_ripple = params['nf_ripple']
+            if nf_ripple == 0:
+                self.nf_ripple = full(self.gain_ripple.size, 0)
+            else:
+                self.nf_ripple = asarray(nf_ripple)
+                if self.nf_ripple.size != self.gain_ripple.size:
+                    raise ParametersError("The noise figure ripple and the gain ripple must have the same size.")
+
+            # VOA
+            self.out_voa_auto = params['out_voa_auto']
+
+            # Dual Stage
+            self.dual_stage_model = params['dual_stage_model']
+            if self.dual_stage_model is not None:
+                # Preamp
+                self.preamp_variety = params['preamp_variety']
+                self.preamp_type_def = params['preamp_type_def']
+                self.preamp_nf_model = params['preamp_nf_model']
+                self.preamp_nf_fit_coeff = params['preamp_nf_fit_coeff']
+                self.preamp_gain_min = params['preamp_gain_min']
+                self.preamp_gain_flatmax = params['preamp_gain_flatmax']
+
+                # Booster
+                self.booster_variety = params['booster_variety']
+                self.booster_type_def = params['booster_type_def']
+                self.booster_nf_model = params['booster_nf_model']
+                self.booster_nf_fit_coeff = params['booster_nf_fit_coeff']
+                self.booster_gain_min = params['booster_gain_min']
+                self.booster_gain_flatmax = params['booster_gain_flatmax']
+
+            # Others
+            self.pmd = params['pmd']
+            self.pdl = params['pdl']
+            self.raman = params['raman']
+            self.dgt = params['dgt']
+            self.advance_configurations_from_json = params['advance_configurations_from_json']
+
+            # Design
+            self.allowed_for_design = params['allowed_for_design']
+
+        except KeyError as e:
+            raise ParametersError(f'Edfa configurations json must include {e}. Configuration: {params}')
+
+    def update_params(self, kwargs):
+        for k, v in kwargs.items():
+            setattr(self, k, self.update_params(**v) if isinstance(v, dict) else v)
+
+
+class EdfaOperational:
+    default_values = {
+        'gain_target': None,
+        'delta_p': None,
+        'out_voa': None,
+        'tilt_target': 0
+    }
+
+    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})')

gnpy/core/utils.py

@@ -9,8 +9,9 @@ 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
 from scipy import constants
+from copy import deepcopy
 
 from gnpy.core.exceptions import ConfigurationError
 
@@ -106,7 +107,99 @@ 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)
@@ -121,7 +214,7 @@ freq2wavelength = constants.nu2lambda
 
 
 def freq2wavelength(value):
-    """ Converts frequency units to wavelength units.
+    """Converts frequency units to wavelength units.
 
     >>> round(freq2wavelength(191.35e12) * 1e9, 3)
     1566.723
@@ -137,8 +230,33 @@ def snr_sum(snr, bw, snr_added, bw_added=12.5e9):
     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 +274,9 @@ def deltawl2deltaf(delta_wl, wavelength):
 
 
 def deltaf2deltawl(delta_f, frequency):
-    """ deltawl2deltaf(delta_f, frequency):
+    """convert delta frequency to delta wavelength
-        converts delta frequency to delta wavelength
+
-        units for delta_wl and wavelength must be same
+    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 +291,7 @@ def deltaf2deltawl(delta_f, frequency):
 
 
 def rrc(ffs, baud_rate, alpha):
-    """ rrc(ffs, baud_rate, alpha): computes the root-raised cosine filter
+    """compute the root-raised cosine filter function
-    function.
 
     :param ffs: A numpy array of frequencies
     :param baud_rate: The Baud Rate of the System
@@ -200,7 +317,7 @@ def rrc(ffs, baud_rate, alpha):
 
 
 def merge_amplifier_restrictions(dict1, dict2):
-    """Updates contents of dicts recursively
+    """Update contents of dicts recursively
 
     >>> d1 = {'params': {'restrictions': {'preamp_variety_list': [], 'booster_variety_list': []}}}
     >>> d2 = {'params': {'target_pch_out_db': -20}}
@@ -295,3 +412,43 @@ def convert_length(value, units):
         return value * 1e3
     else:
         raise ConfigurationError(f'Cannot convert length in "{units}" into meters')
+
+
+def replace_none(dictionary):
+    """ Replaces None with inf values in a frequency slots dict
+
+    >>> replace_none({'N': 3, 'M': None})
+    {'N': 3, 'M': inf}
+
+    """
+    for key, val in dictionary.items():
+        if val is None:
+            dictionary[key] = float('inf')
+        if val == float('inf'):
+            dictionary[key] = None
+    return dictionary
+
+
+def order_slots(slots):
+    """ Order frequency slots from larger slots to smaller ones up to None
+
+    >>> l = [{'N': 3, 'M': None}, {'N': 2, 'M': 1}, {'N': None, 'M': None},{'N': 7, 'M': 2},{'N': None, 'M': 1} , {'N': None, 'M': 0}]
+    >>> order_slots(l)
+    ([7, 2, None, None, 3, None], [2, 1, 1, 0, None, None], [3, 1, 4, 5, 0, 2])
+    """
+    slots_list = deepcopy(slots)
+    slots_list = [replace_none(e) for e in slots_list]
+    for i, e in enumerate(slots_list):
+        e['i'] = i
+    slots_list = sorted(slots_list, key=lambda x: (-x['M'], x['N']) if x['M'] != float('inf') else (x['M'], x['N']))
+    slots_list = [replace_none(e) for e in slots_list]
+    return [e['N'] for e in slots_list], [e['M'] for e in slots_list], [e['i'] for e in slots_list]
+
+
+def restore_order(elements, order):
+    """ Use order to re-order the element of the list, and ignore None values
+
+    >>> restore_order([7, 2, None, None, 3, None], [3, 1, 4, 5, 0, 2])
+    [3, 2, 7]
+    """
+    return [elements[i[0]] for i in sorted(enumerate(order), key=lambda x:x[1]) if elements[i[0]] is not None]

gnpy/example-data/eqpt_config.json

@@ -55,6 +55,24 @@
             "allowed_for_design": false
             },
             {
+            "type_variety": "openroadm_mw_mw_preamp_typical_ver5",
+            "type_def": "openroadm",
+            "gain_flatmax": 27,
+            "gain_min": 0,
+            "p_max": 22,
+            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
+            "allowed_for_design": false
+            },
+            {
+            "type_variety": "openroadm_mw_mw_preamp_worstcase_ver5",
+            "type_def": "openroadm",
+            "gain_flatmax": 27,
+            "gain_min": 0,
+            "p_max": 22,
+            "nf_coef": [-5.952e-4,-6.250e-2,-1.071,27.99],
+            "allowed_for_design": false
+            },
+            {
             "type_variety": "openroadm_mw_mw_booster",
             "type_def": "openroadm_booster",
             "gain_flatmax": 32,
@@ -162,51 +180,27 @@
       "Fiber":[{
             "type_variety": "SSMF",
             "dispersion": 1.67e-05,
-            "gamma": 0.00127,
+            "effective_area": 83e-12,
             "pmd_coef": 1.265e-15
             },
             {
             "type_variety": "NZDF",
             "dispersion": 0.5e-05,
-            "gamma": 0.00146,
+            "effective_area": 72e-12,
             "pmd_coef": 1.265e-15
             },
             {
             "type_variety": "LOF",
             "dispersion": 2.2e-05,
-            "gamma": 0.000843,
+            "effective_area": 125e-12,
             "pmd_coef": 1.265e-15
             }
       ],
       "RamanFiber":[{
             "type_variety": "SSMF",
             "dispersion": 1.67e-05,
-            "gamma": 0.00127,
+            "effective_area": 83e-12,
-            "pmd_coef": 1.265e-15,
+            "pmd_coef": 1.265e-15
-            "raman_efficiency": {
-              "cr":[
-                  0, 9.4E-06, 2.92E-05, 4.88E-05, 6.82E-05, 8.31E-05, 9.4E-05, 0.0001014, 0.0001069, 0.0001119,
-                  0.0001217, 0.0001268, 0.0001365, 0.000149, 0.000165, 0.000181, 0.0001977, 0.0002192, 0.0002469,
-                  0.0002749, 0.0002999, 0.0003206, 0.0003405, 0.0003592, 0.000374, 0.0003826, 0.0003841, 0.0003826,
-                  0.0003802, 0.0003756, 0.0003549, 0.0003795, 0.000344, 0.0002933, 0.0002024, 0.0001158, 8.46E-05,
-                  7.14E-05, 6.86E-05, 8.5E-05, 8.93E-05, 9.01E-05, 8.15E-05, 6.67E-05, 4.37E-05, 3.28E-05, 2.96E-05,
-                  2.65E-05, 2.57E-05, 2.81E-05, 3.08E-05, 3.67E-05, 5.85E-05, 6.63E-05, 6.36E-05, 5.5E-05, 4.06E-05,
-                  2.77E-05, 2.42E-05, 1.87E-05, 1.6E-05, 1.4E-05, 1.13E-05, 1.05E-05, 9.8E-06, 9.8E-06, 1.13E-05,
-                  1.64E-05, 1.95E-05, 2.38E-05, 2.26E-05, 2.03E-05, 1.48E-05, 1.09E-05, 9.8E-06, 1.05E-05, 1.17E-05,
-                  1.25E-05, 1.21E-05, 1.09E-05, 9.8E-06, 8.2E-06, 6.6E-06, 4.7E-06, 2.7E-06, 1.9E-06, 1.2E-06, 4E-07,
-                  2E-07, 1E-07
-              ],
-              "frequency_offset":[
-                0, 0.5e12, 1e12, 1.5e12, 2e12, 2.5e12, 3e12, 3.5e12, 4e12, 4.5e12, 5e12, 5.5e12, 6e12, 6.5e12, 7e12,
-                7.5e12, 8e12, 8.5e12, 9e12, 9.5e12, 10e12, 10.5e12, 11e12, 11.5e12, 12e12, 12.5e12, 12.75e12,
-                13e12, 13.25e12, 13.5e12, 14e12, 14.5e12, 14.75e12, 15e12, 15.5e12, 16e12, 16.5e12, 17e12,
-                17.5e12, 18e12, 18.25e12, 18.5e12, 18.75e12, 19e12, 19.5e12, 20e12, 20.5e12, 21e12, 21.5e12,
-                22e12, 22.5e12, 23e12, 23.5e12, 24e12, 24.5e12, 25e12, 25.5e12, 26e12, 26.5e12, 27e12, 27.5e12, 28e12,
-                28.5e12, 29e12, 29.5e12, 30e12, 30.5e12, 31e12, 31.5e12, 32e12, 32.5e12, 33e12, 33.5e12, 34e12, 34.5e12,
-                35e12, 35.5e12, 36e12, 36.5e12, 37e12, 37.5e12, 38e12, 38.5e12, 39e12, 39.5e12, 40e12, 40.5e12, 41e12,
-                41.5e12, 42e12
-              ]
-              }
             }
       ],
       "Span":[{
@@ -227,6 +221,7 @@
             "target_pch_out_db": -20,
             "add_drop_osnr": 38,
             "pmd": 0,
+            "pdl": 0,
             "restrictions": {
                             "preamp_variety_list":[],
                             "booster_variety_list":[]

gnpy/example-data/eqpt_config_openroadm.json

@@ -1,190 +0,0 @@
-{     "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],
-            "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],
-            "allowed_for_design": true
-            },
-		{
-            "type_variety": "openroadm_mw_mw_preamp",
-            "type_def": "openroadm_preamp",
-            "gain_flatmax": 27,
-            "gain_min": 0,
-            "p_max": 22,
-            "allowed_for_design": false
-            },
-		{
-            "type_variety": "openroadm_mw_mw_booster",
-            "type_def": "openroadm_booster",
-            "gain_flatmax": 32,
-            "gain_min": 0,
-            "p_max": 22,
-            "allowed_for_design": false
-            }
-      ],
-      "Fiber":[
-            {
-            "type_variety": "SSMF",
-            "dispersion": 1.67e-05,
-            "gamma": 0.00127,
-            "pmd_coef": 1.265e-15
-            },
-            {
-            "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
-            }
-      ],
-      "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
-              ]
-              }
-            }
-      ],
-      "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": 0,
-            "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,
-                       "min_spacing": 50e9,
-                       "cost":1
-                       },
-					   {
-                       "format": "100 Gbit/s, 31.57 Gbaud, DP-QPSK",
-                       "baud_rate": 31.57e9,
-                       "OSNR": 12,
-                       "bit_rate": 100e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 35,
-                       "min_spacing": 50e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "200 Gbit/s, DP-QPSK",
-                       "baud_rate": 63.1e9,
-                       "OSNR": 17,
-                       "bit_rate": 200e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 36,
-                       "min_spacing": 87.5e9,
-                       "cost":1
-                       },
-                       {
-                       "format": "300 Gbit/s, DP-8QAM",
-                       "baud_rate": 63.1e9,
-                       "OSNR": 21,
-                       "bit_rate": 300e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 36,
-                       "min_spacing": 87.5e9,
-                       "cost":1
-                       },
-					   {
-                       "format": "400 Gbit/s, DP-16QAM",
-                       "baud_rate": 63.1e9,
-                       "OSNR": 24,
-                       "bit_rate": 400e9,
-                       "roll_off": 0.15,
-                       "tx_osnr": 36,
-                       "min_spacing": 87.5e9,
-                       "cost":1
-                       }
-                   ]
-            }
-      ]
-
-}

gnpy/example-data/eqpt_config_openroadm_ver4.json

@@ -0,0 +1,349 @@
+{
+    "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 +1,409 @@
+{
+    "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/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_services.json

@@ -14,8 +14,8 @@
           "trx_mode": null,
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -39,8 +39,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -104,8 +104,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -129,8 +129,8 @@
           "trx_mode": null,
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 75000000000.0,
@@ -154,8 +154,8 @@
           "trx_mode": "mode 2",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 75000000000.0,
@@ -179,8 +179,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -204,8 +204,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -229,8 +229,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 75000000000.0,

gnpy/example-data/raman_edfa_example_network.json

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

gnpy/example-data/sim_params.json

@@ -1,12 +1,11 @@
 {
-  "raman_parameters": {
+  "raman_params": {
-    "flag_raman": true,
+    "flag": true,
-    "space_resolution": 10e3,
+    "result_spatial_resolution": 10e3,
-    "tolerance": 1e-8
+    "solver_spatial_resolution": 50
   },
-  "nli_parameters": {
+  "nli_params": {
-  	"nli_method_name": "ggn_spectrally_separated",
+    "method": "ggn_spectrally_separated",
-  	"wdm_grid_size": 50e9,
     "dispersion_tolerance": 1,
     "phase_shift_tolerance": 0.1,
     "computed_channels": [1, 18, 37, 56, 75]

gnpy/example-data/write_path_jsontocsv.py

@@ -18,9 +18,9 @@ from gnpy.tools.json_io import load_equipment
 from gnpy.topology.request import jsontocsv
 
 
-parser = ArgumentParser(description='A function that writes json path results in an excel sheet.')
+parser = ArgumentParser(description='Converting JSON path results into a CSV')
-parser.add_argument('filename', nargs='?', type=Path)
+parser.add_argument('filename', type=Path)
-parser.add_argument('output_filename', nargs='?', type=Path)
+parser.add_argument('output_filename', type=Path)
 parser.add_argument('eqpt_filename', nargs='?', type=Path, default=Path(__file__).parent / 'eqpt_config.json')
 
 if __name__ == '__main__':

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

@@ -1,35 +1,34 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+"""
 gnpy.tools.cli_examples
 =======================
 
 Common code for CLI examples
-'''
+"""
 
 import argparse
 import logging
-import os.path
 import sys
 from math import ceil
 from numpy import linspace, mean
 from pathlib import Path
+
 import gnpy.core.ansi_escapes as 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.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, \
+from gnpy.tools.json_io import (load_equipment, load_network, load_json, load_requests, save_network,
-                               requests_from_json, disjunctions_from_json, save_json
+                                requests_from_json, disjunctions_from_json, save_json, load_initial_spectrum)
 from gnpy.tools.plots import plot_baseline, plot_results
 
 _logger = logging.getLogger(__name__)
@@ -49,7 +48,7 @@ def show_example_data_dir():
 
 
 def load_common_data(equipment_filename, topology_filename, simulation_filename, save_raw_network_filename):
-    '''Load common configuration from JSON files'''
+    """Load common configuration from JSON files"""
 
     try:
         equipment = load_equipment(equipment_filename)
@@ -57,14 +56,15 @@ def load_common_data(equipment_filename, topology_filename, simulation_filename,
         if save_raw_network_filename is not None:
             save_network(network, save_raw_network_filename)
             print(f'{ansi_escapes.blue}Raw network (no optimizations) saved to {save_raw_network_filename}{ansi_escapes.reset}')
-        sim_params = SimParams(**load_json(simulation_filename)) if simulation_filename is not None else None
+        if not simulation_filename:
-        if not sim_params:
+            sim_params = {}
             if next((node for node in network if isinstance(node, RamanFiber)), None) is not None:
                 print(f'{ansi_escapes.red}Invocation error:{ansi_escapes.reset} '
                       f'RamanFiber requires passing simulation params via --sim-params')
                 sys.exit(1)
         else:
-            Simulation.set_params(sim_params)
+            sim_params = load_json(simulation_filename)
+        SimParams.set_params(sim_params)
     except exceptions.EquipmentConfigError as e:
         print(f'{ansi_escapes.red}Configuration error in the equipment library:{ansi_escapes.reset} {e}')
         sys.exit(1)
@@ -85,7 +85,7 @@ def load_common_data(equipment_filename, topology_filename, simulation_filename,
 
 
 def _setup_logging(args):
-    logging.basicConfig(level={2: logging.DEBUG, 1: logging.INFO, 0: logging.CRITICAL}.get(args.verbose, logging.DEBUG))
+    logging.basicConfig(level={2: logging.DEBUG, 1: logging.INFO, 0: logging.WARNING}.get(args.verbose, logging.DEBUG))
 
 
 def _add_common_options(parser: argparse.ArgumentParser, network_default: Path):
@@ -103,6 +103,9 @@ 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.')
 
 
 def transmission_main_example(args=None):
@@ -116,6 +119,7 @@ def transmission_main_example(args=None):
     parser.add_argument('-pl', '--plot', action='store_true')
     parser.add_argument('-l', '--list-nodes', action='store_true', help='list all transceiver nodes')
     parser.add_argument('-po', '--power', default=0, help='channel ref power in dBm')
+    parser.add_argument('--spectrum', type=Path, help='user defined mixed rate spectrum JSON file')
     parser.add_argument('source', nargs='?', help='source node')
     parser.add_argument('destination', nargs='?', help='destination node')
 
@@ -187,20 +191,30 @@ def transmission_main_example(args=None):
     params['loose_list'] = ['strict']
     params['format'] = ''
     params['path_bandwidth'] = 0
+    params['effective_freq_slot'] = None
     trx_params = trx_mode_params(equipment)
     if args.power:
         trx_params['power'] = db2lin(float(args.power)) * 1e-3
     params.update(trx_params)
+    initial_spectrum = None
+    nb_channels = automatic_nch(trx_params['f_min'], trx_params['f_max'], trx_params['spacing'])
+    if args.spectrum:
+        initial_spectrum = load_initial_spectrum(args.spectrum)
+        nb_channels = len(initial_spectrum)
+        print('User input for spectrum used for propagation instead of SI')
+    params['nb_channel'] = nb_channels
     req = PathRequest(**params)
-
+    req.initial_spectrum = initial_spectrum
+    print(f'There are {nb_channels} channels propagating')
     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']))
 
+    # Keep the reference channel for design: the one from SI, with full load same channels
     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)
     try:
-        build_network(network, equipment, pref_ch_db, pref_total_db)
+        build_network(network, equipment, pref_ch_db, pref_total_db, args.no_insert_edfas)
     except exceptions.NetworkTopologyError as e:
         print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
         sys.exit(1)
@@ -214,19 +228,22 @@ def transmission_main_example(args=None):
           f'and {destination.uid}')
     print(f'\nNow propagating between {source.uid} and {destination.uid}:')
 
+    power_range = [0]
+    if power_mode:
+        # power cannot be changed in gain mode
         try:
             p_start, p_stop, p_step = equipment['SI']['default'].power_range_db
             p_num = abs(int(round((p_stop - p_start) / p_step))) + 1 if p_step != 0 else 1
             power_range = list(linspace(p_start, p_stop, p_num))
         except TypeError:
             print('invalid power range definition in eqpt_config, should be power_range_db: [lower, upper, step]')
-        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
+        # if initial spectrum did not contain any power, now we need to use this one.
+        # note the initial power defines a differential wrt req.power so that if req.power is set to 2mW (3dBm)
+        # and initial spectrum was set to 0, this sets a initial per channel delta power to -3dB, so that
+        # whatever the equalization, -3 dB is applied on all channels (ie initial power in initial spectrum pre-empts
+        # "--power" option)
         if power_mode:
             print(f'\nPropagating with input power = {ansi_escapes.cyan}{lin2db(req.power*1e3):.2f} dBm{ansi_escapes.reset}:')
         else:
@@ -262,9 +279,9 @@ def transmission_main_example(args=None):
             ch_freq = final_carrier.frequency * 1e-12
             ch_power = lin2db(final_carrier.power.signal * 1e3)
             print(
-                '{:5}{:26.2f}{:26.2f}{:28.2f}{:28.2f}{:28.2f}' .format(
+                '{:5}{:26.5f}{:26.2f}{:28.2f}{:28.2f}{:28.2f}' .format(
                     final_carrier.channel_number, round(
-                        ch_freq, 2), round(
+                        ch_freq, 5), round(
                         ch_power, 2), round(
                         ch_osnr, 2), round(
                         ch_snr_nl, 2), round(
@@ -306,8 +323,7 @@ def path_requests_run(args=None):
     args = parser.parse_args(args if args is not None else sys.argv[1:])
     _setup_logging(args)
 
-    _logger.info(f'Computing path requests {args.service_filename} into JSON format')
+    _logger.info(f'Computing path requests {args.service_filename.name} into JSON format')
-    print(f'{ansi_escapes.blue}Computing path requests {os.path.relpath(args.service_filename)} into JSON format{ansi_escapes.reset}')
 
     (equipment, network) = load_common_data(args.equipment, args.topology, args.sim_params, args.save_network_before_autodesign)
 
@@ -315,11 +331,10 @@ def path_requests_run(args=None):
     # TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
     # spacing, f_min and f_max
     p_db = equipment['SI']['default'].power_dbm
-
     p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
                                              equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
     try:
-        build_network(network, equipment, p_db, p_total_db)
+        build_network(network, equipment, p_db, p_total_db, args.no_insert_edfas)
     except exceptions.NetworkTopologyError as e:
         print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
         sys.exit(1)

gnpy/tools/convert.py

@@ -21,18 +21,22 @@ the "east" information so that it is possible to input undirected data.
 """
 
 from xlrd import open_workbook
+from logging import getLogger
 from argparse import ArgumentParser
 from collections import namedtuple, Counter, defaultdict
 from itertools import chain
 from json import dumps
 from pathlib import Path
 from copy import copy
-from gnpy.core import ansi_escapes
+
 from gnpy.core.utils import silent_remove
 from gnpy.core.exceptions import NetworkTopologyError
 from gnpy.core.elements import Edfa, Fused, Fiber
 
 
+_logger = getLogger(__name__)
+
+
 def all_rows(sh, start=0):
     return (sh.row(x) for x in range(start, sh.nrows))
 
@@ -183,18 +187,18 @@ def parse_headers(my_sheet, input_headers_dict, headers, start_line, slice_in):
             slice_out = read_slice(my_sheet, start_line + iteration, slice_in, h0)
             iteration += 1
         if slice_out == (-1, -1):
+            msg = f'missing header {h0}'
             if h0 in ('east', 'Node A', 'Node Z', 'City'):
-                print(f'{ansi_escapes.red}CRITICAL{ansi_escapes.reset}: missing _{h0}_ header: EXECUTION ENDS')
+                raise NetworkTopologyError(msg)
-                raise NetworkTopologyError(f'Missing _{h0}_ header')
             else:
-                print(f'missing header {h0}')
+                _logger.warning(msg)
         elif not isinstance(input_headers_dict[h0], dict):
             headers[slice_out[0]] = input_headers_dict[h0]
         else:
             headers = parse_headers(my_sheet, input_headers_dict[h0], headers, start_line + 1, slice_out)
     if headers == {}:
-        print(f'{ansi_escapes.red}CRITICAL ERROR{ansi_escapes.reset}: could not find any header to read _ ABORT')
+        msg = 'CRITICAL ERROR: could not find any header to read _ ABORT'
-        raise NetworkTopologyError('Could not find any header to read')
+        raise NetworkTopologyError(msg)
     return headers
 
 
@@ -219,40 +223,76 @@ def sanity_check(nodes, links, nodes_by_city, links_by_city, eqpts_by_city):
     for l1 in links:
         for l2 in links:
             if l1 is not l2 and l1 == l2 and l2 not in duplicate_links:
-                print(f'\nWARNING\n \
+                _logger.warning(f'\nWARNING\n \
                     link {l1.from_city}-{l1.to_city} is duplicate \
                     \nthe 1st duplicate link will be removed but you should check Links sheet input')
                 duplicate_links.append(l1)
-    for l in duplicate_links:
+    if duplicate_links:
-        links.remove(l)
+        msg = 'XLS error: ' \
-        links_by_city[l.from_city].remove(l)
+              + f'links {_format_items([(d.from_city, d.to_city) for d in duplicate_links])} are duplicate'
-        links_by_city[l.to_city].remove(l)
+        raise NetworkTopologyError(msg)
-
     unreferenced_nodes = [n for n in nodes_by_city if n not in links_by_city]
     if unreferenced_nodes:
-        raise NetworkTopologyError(f'{ansi_escapes.red}XLS error:{ansi_escapes.reset} The following nodes are not '
+        msg = 'XLS error: The following nodes are not ' \
-                                   f'referenced from the {ansi_escapes.cyan}Links{ansi_escapes.reset} sheet. '
+              + 'referenced from the Links sheet. ' \
-                                   f'If unused, remove them from the {ansi_escapes.cyan}Nodes{ansi_escapes.reset} '
+              + 'If unused, remove them from the Nodes sheet:\n' \
-                                   f'sheet:\n'
+              + _format_items(unreferenced_nodes)
-                                   + _format_items(unreferenced_nodes))
+        raise NetworkTopologyError(msg)
     # no need to check "Links" for invalid nodes because that's already in parse_excel()
     wrong_eqpt_from = [n for n in eqpts_by_city if n not in nodes_by_city]
     wrong_eqpt_to = [n.to_city for destinations in eqpts_by_city.values()
                      for n in destinations if n.to_city not in nodes_by_city]
     wrong_eqpt = wrong_eqpt_from + wrong_eqpt_to
     if wrong_eqpt:
-        raise NetworkTopologyError(f'{ansi_escapes.red}XLS error:{ansi_escapes.reset} '
+        msg = 'XLS error: ' \
-                                   f'The {ansi_escapes.cyan}Eqpt{ansi_escapes.reset} sheet refers to nodes that '
+              + 'The Eqpt sheet refers to nodes that ' \
-                                   f'are not defined in the {ansi_escapes.cyan}Nodes{ansi_escapes.reset} sheet:\n'
+              + 'are not defined in the Nodes sheet:\n'\
-                                   + _format_items(wrong_eqpt))
+              + _format_items(wrong_eqpt)
+        raise NetworkTopologyError(msg)
+    # Now check links that are not listed in Links sheet, and duplicates
+    bad_eqpt = []
+    possible_links = [f'{e.from_city}|{e.to_city}' for e in links] + [f'{e.to_city}|{e.from_city}' for e in links]
+    possible_eqpt = []
+    duplicate_eqpt = []
+    duplicate_ila = []
+    for city, eqpts in eqpts_by_city.items():
+        for eqpt in eqpts:
+            # Check that each node_A-node_Z exists in links
+            nodea_nodez = f'{eqpt.from_city}|{eqpt.to_city}'
+            nodez_nodea = f'{eqpt.to_city}|{eqpt.from_city}'
+            if nodea_nodez not in possible_links \
+                    or nodez_nodea not in possible_links:
+                bad_eqpt.append([eqpt.from_city, eqpt.to_city])
+            else:
+                # Check that there are no duplicate lines in the Eqpt sheet
+                if nodea_nodez in possible_eqpt:
+                    duplicate_eqpt.append([eqpt.from_city, eqpt.to_city])
+                else:
+                    possible_eqpt.append(nodea_nodez)
+            # check that there are no two lines defining an ILA with different directions
+        if nodes_by_city[city].node_type == 'ILA' and len(eqpts) > 1:
+            duplicate_ila.append(city)
+    if bad_eqpt:
+        msg = 'XLS error: ' \
+              + 'The Eqpt sheet references links that ' \
+              + 'are not defined in the Links sheet:\n' \
+              + _format_items(f'{item[0]} -> {item[1]}' for item in bad_eqpt)
+        raise NetworkTopologyError(msg)
+    if duplicate_eqpt:
+        msg = 'XLS error: Duplicate lines in Eqpt sheet:' \
+              + _format_items(f'{item[0]} -> {item[1]}' for item in duplicate_eqpt)
+        raise NetworkTopologyError(msg)
+    if duplicate_ila:
+        msg = 'XLS error: Duplicate ILA eqpt definition in Eqpt sheet:' \
+              + _format_items(duplicate_ila)
+        raise NetworkTopologyError(msg)
 
     for city, link in links_by_city.items():
         if nodes_by_city[city].node_type.lower() == 'ila' and len(link) != 2:
             # wrong input: ILA sites can only be Degree 2
             # => correct to make it a ROADM and remove entry in links_by_city
-            # TODO: put in log rather than print
+            _logger.warning(f'invalid node type ({nodes_by_city[city].node_type}) '
-            print(f'invalid node type ({nodes_by_city[city].node_type})\
+                            + f'specified in {city}, replaced by ROADM')
-                  specified in {city}, replaced by ROADM')
             nodes_by_city[city].node_type = 'ROADM'
             for n in nodes:
                 if n.city == city:
@@ -642,17 +682,19 @@ def parse_excel(input_filename):
     # sanity check
     all_cities = Counter(n.city for n in nodes)
     if len(all_cities) != len(nodes):
-        raise ValueError(f'Duplicate city: {all_cities}')
+        msg = f'Duplicate city: {all_cities}'
+        raise NetworkTopologyError(msg)
     bad_links = []
     for lnk in links:
         if lnk.from_city not in all_cities or lnk.to_city not in all_cities:
             bad_links.append([lnk.from_city, lnk.to_city])
 
     if bad_links:
-        raise NetworkTopologyError(f'{ansi_escapes.red}XLS error:{ansi_escapes.reset} '
+        msg = 'XLS error: ' \
-                                   f'The {ansi_escapes.cyan}Links{ansi_escapes.reset} sheet references nodes that '
+              + 'The Links sheet references nodes that ' \
-                                   f'are not defined in the {ansi_escapes.cyan}Nodes{ansi_escapes.reset} sheet:\n'
+              + 'are not defined in the Nodes sheet:\n' \
-                                   + _format_items(f'{item[0]} -> {item[1]}' for item in bad_links))
+              + _format_items(f'{item[0]} -> {item[1]}' for item in bad_links)
+        raise NetworkTopologyError(msg)
 
     return nodes, links, eqpts, roadms
 

gnpy/tools/json_io.py

@@ -1,24 +1,29 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+"""
 gnpy.tools.json_io
 ==================
 
 Loading and saving data from JSON files in GNPy's internal data format
-'''
+"""
 
 from networkx import DiGraph
 from logging import getLogger
 from pathlib import Path
 import json
 from collections import namedtuple
-from gnpy.core import ansi_escapes, elements
+from numpy import arange
+
+from gnpy.core import elements
 from gnpy.core.equipment import trx_mode_params
 from gnpy.core.exceptions import ConfigurationError, EquipmentConfigError, NetworkTopologyError, ServiceError
 from gnpy.core.science_utils import estimate_nf_model
+from gnpy.core.info import Carrier
 from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions
-from gnpy.topology.request import PathRequest, Disjunction
+from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT
+from gnpy.topology.request import PathRequest, Disjunction, compute_spectrum_slot_vs_bandwidth
+from gnpy.topology.spectrum_assignment import mvalue_to_slots
 from gnpy.tools.convert import xls_to_json_data
 from gnpy.tools.service_sheet import read_service_sheet
 
@@ -33,16 +38,23 @@ Model_hybrid = namedtuple('Model_hybrid', 'nf_ram gain_ram edfa_variety')
 Model_dual_stage = namedtuple('Model_dual_stage', 'preamp_variety booster_variety')
 
 
+class Model_openroadm_preamp:
+    pass
+
+
+class Model_openroadm_booster:
+    pass
+
+
 class _JsonThing:
     def update_attr(self, default_values, kwargs, name):
         clean_kwargs = {k: v for k, v in kwargs.items() if v != ''}
         for k, v in default_values.items():
             setattr(self, k, clean_kwargs.get(k, v))
             if k not in clean_kwargs and name != 'Amp':
-                print(ansi_escapes.red +
+                msg = f'\n WARNING missing {k} attribute in eqpt_config.json[{name}]' \
-                      f'\n WARNING missing {k} attribute in eqpt_config.json[{name}]' +
+                    + f'\n default value is {k} = {v}'
-                      f'\n default value is {k} = {v}' +
+                _logger.warning(msg)
-                      ansi_escapes.reset)
 
 
 class SI(_JsonThing):
@@ -83,9 +95,9 @@ class Span(_JsonThing):
 
 class Roadm(_JsonThing):
     default_values = {
-        'target_pch_out_db': -17,
         'add_drop_osnr': 100,
         'pmd': 0,
+        'pdl': 0,
         'restrictions': {
             'preamp_variety_list': [],
             'booster_variety_list': []
@@ -93,6 +105,21 @@ class Roadm(_JsonThing):
     }
 
     def __init__(self, **kwargs):
+        # If equalization is not defined in equipment, then raise an error.
+        # Only one type of equalization must be defined.
+        allowed_equalisations = ['target_pch_out_db', 'target_psd_out_mWperGHz', 'target_out_mWperSlotWidth']
+        requested_eq_mask = [eq in kwargs for eq in allowed_equalisations]
+        if sum(requested_eq_mask) > 1:
+            msg = 'Only one equalization type should be set in ROADM, found: ' \
+                  + ', '.join(eq for eq in allowed_equalisations if eq in kwargs)
+            raise EquipmentConfigError(msg)
+        if not any(requested_eq_mask):
+            msg = 'No equalization type set in ROADM'
+            raise EquipmentConfigError(msg)
+        for key in allowed_equalisations:
+            if key in kwargs:
+                setattr(self, key, kwargs[key])
+                break
         self.update_attr(self.default_values, kwargs, 'Roadm')
 
 
@@ -105,36 +132,51 @@ class Transceiver(_JsonThing):
 
     def __init__(self, **kwargs):
         self.update_attr(self.default_values, kwargs, 'Transceiver')
+        for mode_params in self.mode:
+            penalties = mode_params.get('penalties')
+            mode_params['penalties'] = {}
+            mode_params['equalization_offset_db'] = mode_params.get('equalization_offset_db', 0)
+            if not penalties:
+                continue
+            for impairment in ('chromatic_dispersion', 'pmd', 'pdl'):
+                imp_penalties = [p for p in penalties if impairment in p]
+                if not imp_penalties:
+                    continue
+                if all(p[impairment] > 0 for p in imp_penalties):
+                    # make sure the list of penalty values include a proper lower boundary
+                    # (we assume 0 penalty for 0 impairment)
+                    imp_penalties.insert(0, {impairment: 0, 'penalty_value': 0})
+                # make sure the list of penalty values are sorted by impairment value
+                imp_penalties.sort(key=lambda i: i[impairment])
+                # rearrange as dict of lists instead of list of dicts
+                mode_params['penalties'][impairment] = {
+                    'up_to_boundary': [p[impairment] for p in imp_penalties],
+                    'penalty_value': [p['penalty_value'] for p in imp_penalties]
+                }
 
 
 class Fiber(_JsonThing):
     default_values = {
         'type_variety': '',
         'dispersion': None,
-        'gamma': 0,
+        'effective_area': None,
         'pmd_coef': 0
     }
 
     def __init__(self, **kwargs):
-        self.update_attr(self.default_values, kwargs, 'Fiber')
+        self.update_attr(self.default_values, kwargs, self.__class__.__name__)
+        if 'gamma' in kwargs:
+            setattr(self, 'gamma', kwargs['gamma'])
+        if 'raman_efficiency' in kwargs:
+            raman_coefficient = kwargs['raman_efficiency']
+            cr = raman_coefficient.pop('cr')
+            raman_coefficient['g0'] = cr
+            raman_coefficient['reference_frequency'] = DEFAULT_RAMAN_COEFFICIENT['reference_frequency']
+            setattr(self, 'raman_coefficient', raman_coefficient)
 
 
-class RamanFiber(_JsonThing):
+class RamanFiber(Fiber):
-    default_values = {
+    pass
-        'type_variety': '',
-        'dispersion': None,
-        'gamma': 0,
-        'pmd_coef': 0,
-        'raman_efficiency': None
-    }
-
-    def __init__(self, **kwargs):
-        self.update_attr(self.default_values, kwargs, 'RamanFiber')
-        for param in ('cr', 'frequency_offset'):
-            if param not in self.raman_efficiency:
-                raise EquipmentConfigError(f'RamanFiber.raman_efficiency: missing "{param}" parameter')
-        if self.raman_efficiency['frequency_offset'] != sorted(self.raman_efficiency['frequency_offset']):
-            raise EquipmentConfigError(f'RamanFiber.raman_efficiency.frequency_offset is not sorted')
 
 
 class Amp(_JsonThing):
@@ -148,13 +190,24 @@ class Amp(_JsonThing):
         'p_max': None,
         'nf_model': None,
         'dual_stage_model': None,
+        'preamp_variety': None,
+        'booster_variety': None,
+        'nf_min': None,
+        'nf_max': None,
+        'nf_coef': None,
+        'nf0': None,
         'nf_fit_coeff': None,
-        'nf_ripple': None,
+        'nf_ripple': 0,
         'dgt': None,
-        'gain_ripple': None,
+        'gain_ripple': 0,
+        'tilt_ripple': 0,
+        'f_ripple_ref': None,
         'out_voa_auto': False,
         'allowed_for_design': False,
-        'raman': False
+        'raman': False,
+        'pmd': 0,
+        'pdl': 0,
+        'advance_configurations_from_json': None
     }
 
     def __init__(self, **kwargs):
@@ -173,7 +226,8 @@ class Amp(_JsonThing):
             try:
                 nf0 = kwargs.pop('nf0')
             except KeyError:  # nf0 is expected for a fixed gain amp
-                raise EquipmentConfigError(f'missing nf0 value input for amplifier: {type_variety} in equipment config')
+                msg = f'missing nf0 value input for amplifier: {type_variety} in equipment config'
+                raise EquipmentConfigError(msg)
             for k in ('nf_min', 'nf_max'):
                 try:
                     del kwargs[k]
@@ -188,7 +242,8 @@ class Amp(_JsonThing):
                 nf_min = kwargs.pop('nf_min')
                 nf_max = kwargs.pop('nf_max')
             except KeyError:
-                raise EquipmentConfigError(f'missing nf_min or nf_max value input for amplifier: {type_variety} in equipment config')
+                msg = f'missing nf_min or nf_max value input for amplifier: {type_variety} in equipment config'
+                raise EquipmentConfigError(msg)
             try:  # remove all remaining nf inputs
                 del kwargs['nf0']
             except KeyError:
@@ -201,14 +256,17 @@ class Amp(_JsonThing):
             except KeyError:  # nf_coef is expected for openroadm amp
                 raise EquipmentConfigError(f'missing nf_coef input for amplifier: {type_variety} in equipment config')
             nf_def = Model_openroadm_ila(nf_coef)
-        elif type_def in ('openroadm_preamp', 'openroadm_booster'):
+        elif type_def == 'openroadm_preamp':
-            pass  # no extra parameters needed
+            nf_def = Model_openroadm_preamp()
+        elif type_def == 'openroadm_booster':
+            nf_def = Model_openroadm_booster()
         elif type_def == 'dual_stage':
             try:  # nf_ram and gain_ram are expected for a hybrid amp
                 preamp_variety = kwargs.pop('preamp_variety')
                 booster_variety = kwargs.pop('booster_variety')
             except KeyError:
-                raise EquipmentConfigError(f'missing preamp/booster variety input for amplifier: {type_variety} in equipment config')
+                msg = f'missing preamp/booster variety input for amplifier: {type_variety} in equipment config'
+                raise EquipmentConfigError(msg)
             dual_stage_def = Model_dual_stage(preamp_variety, booster_variety)
         else:
             raise EquipmentConfigError(f'Edfa type_def {type_def} does not exist')
@@ -227,11 +285,89 @@ def _automatic_spacing(baud_rate):
     return min((s[1] for s in spacing_list if s[0] > baud_rate), default=baud_rate * 1.2)
 
 
+def _spectrum_from_json(json_data):
+    """JSON_data is a list of spectrum partitions each with
+    {f_min, f_max, baud_rate, roll_off, delta_pdb, slot_width, tx_osnr, label}
+    Creates the per freq Carrier's dict.
+    f_min, f_max, baud_rate, slot_width and roll_off are mandatory
+    label, tx_osnr and delta_pdb are created if not present
+    label should be different for each partition
+    >>> json_data = {'spectrum': \
+        [{'f_min': 193.2e12, 'f_max': 193.4e12, 'slot_width': 50e9, 'baud_rate': 32e9, 'roll_off': 0.15, \
+            'delta_pdb': 1, 'tx_osnr': 45},\
+        {'f_min': 193.4625e12, 'f_max': 193.9875e12, 'slot_width': 75e9, 'baud_rate': 64e9, 'roll_off': 0.15},\
+        {'f_min': 194.075e12, 'f_max': 194.075e12, 'slot_width': 100e9, 'baud_rate': 90e9, 'roll_off': 0.15},\
+        {'f_min': 194.2e12, 'f_max': 194.35e12, 'slot_width': 50e9, 'baud_rate': 32e9, 'roll_off': 0.15}]}
+    >>> spectrum = _spectrum_from_json(json_data['spectrum'])
+    >>> for k, v in spectrum.items():
+    ...     print(f'{k}: {v}')
+    ...
+    193200000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
+    193250000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
+    193300000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
+    193350000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
+    193400000000000.0: Carrier(delta_pdb=1, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=45, label='0-32.00G')
+    193462500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
+    193537500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
+    193612500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
+    193687500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
+    193762500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
+    193837500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
+    193912500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
+    193987500000000.0: Carrier(delta_pdb=0, baud_rate=64000000000.0, slot_width=75000000000.0, roll_off=0.15, tx_osnr=40, label='1-64.00G')
+    194075000000000.0: Carrier(delta_pdb=0, baud_rate=90000000000.0, slot_width=100000000000.0, roll_off=0.15, tx_osnr=40, label='2-90.00G')
+    194200000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
+    194250000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
+    194300000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
+    194350000000000.0: Carrier(delta_pdb=0, baud_rate=32000000000.0, slot_width=50000000000.0, roll_off=0.15, tx_osnr=40, label='3-32.00G')
+    """
+    spectrum = {}
+    json_data = sorted(json_data, key=lambda x: x['f_min'])
+    # min freq of occupation is f_min - slot_width/2 (numbering starts at 0)
+    previous_part_max_freq = 0.0
+    for index, part in enumerate(json_data):
+        # default delta_pdb is 0 dB
+        if 'delta_pdb' not in part:
+            part['delta_pdb'] = 0
+        # add a label to the partition for the printings
+        if 'label' not in part:
+            part['label'] = f'{index}-{part["baud_rate"] * 1e-9 :.2f}G'
+        # default tx_osnr is set to 40 dB
+        if 'tx_osnr' not in part:
+            part['tx_osnr'] = 40
+        # starting freq is exactly f_min to be consistent with utils.automatic_nch
+        # first partition min occupation is f_min - slot_width / 2 (central_frequency is f_min)
+        # supposes that carriers are centered on frequency
+        if previous_part_max_freq > (part['f_min'] - part['slot_width'] / 2):
+            # check that previous part last channel does not overlap on next part first channel
+            # max center of the part should be below part['f_max'] and aligned on the slot_width
+            msg = 'Not a valid initial spectrum definition:\nprevious spectrum last carrier max occupation ' +\
+                f'{previous_part_max_freq * 1e-12 :.5f}GHz ' +\
+                'overlaps on next spectrum first carrier occupation ' +\
+                f'{(part["f_min"] - part["slot_width"] / 2) * 1e-12 :.5f}GHz'
+            raise ValueError(msg)
+
+        max_range = ((part['f_max'] - part['f_min']) // part['slot_width'] + 1) * part['slot_width']
+        for current_freq in arange(part['f_min'],
+                                   part['f_min'] + max_range,
+                                   part['slot_width']):
+            spectrum[current_freq] = Carrier(delta_pdb=part['delta_pdb'], baud_rate=part['baud_rate'],
+                                             slot_width=part['slot_width'], roll_off=part['roll_off'],
+                                             tx_osnr=part['tx_osnr'], label=part['label'])
+        previous_part_max_freq = current_freq + part['slot_width'] / 2
+    return spectrum
+
+
 def load_equipment(filename):
     json_data = load_json(filename)
     return _equipment_from_json(json_data, filename)
 
 
+def load_initial_spectrum(filename):
+    json_data = load_json(filename)
+    return _spectrum_from_json(json_data['spectrum'])
+
+
 def _update_dual_stage(equipment):
     edfa_dict = equipment['Edfa']
     for edfa in edfa_dict.values():
@@ -252,9 +388,7 @@ def _update_dual_stage(equipment):
 
 
 def _roadm_restrictions_sanity_check(equipment):
-    """ verifies that booster and preamp restrictions specified in roadm equipment are listed
+    """verifies that booster and preamp restrictions specified in roadm equipment are listed in the edfa."""
-    in the edfa.
-    """
     restrictions = equipment['Roadm']['default'].restrictions['booster_variety_list'] + \
         equipment['Roadm']['default'].restrictions['preamp_variety_list']
     for amp_name in restrictions:
@@ -267,7 +401,7 @@ def _check_fiber_vs_raman_fiber(equipment):
     if 'RamanFiber' not in equipment:
         return
     for fiber_type in set(equipment['Fiber'].keys()) & set(equipment['RamanFiber'].keys()):
-        for attr in ('dispersion', 'dispersion-slope', 'gamma', 'pmd-coefficient'):
+        for attr in ('dispersion', 'dispersion-slope', 'effective_area', 'gamma', 'pmd-coefficient'):
             fiber = equipment['Fiber'][fiber_type]
             raman = equipment['RamanFiber'][fiber_type]
             a = getattr(fiber, attr, None)
@@ -324,11 +458,11 @@ def load_network(filename, equipment):
 
 
 def save_network(network: DiGraph, filename: str):
-    '''Dump the network into a JSON file
+    """Dump the network into a JSON file
 
     :param network: network to work on
     :param filename: file to write to
-    '''
+    """
     save_json(network_to_json(network), filename)
 
 
@@ -362,14 +496,28 @@ def network_from_json(json_data, equipment):
             # well, there's no variety for the 'Fused' node type
             pass
         elif variety in equipment[typ]:
-            extra_params = equipment[typ][variety]
+            extra_params = equipment[typ][variety].__dict__
             temp = el_config.setdefault('params', {})
-            temp = merge_amplifier_restrictions(temp, extra_params.__dict__)
+            if typ == 'Roadm':
+                # if equalization is defined, remove default equalization from the extra_params
+                # If equalisation is not defined in the element config, then use the default one from equipment
+                # if more than one equalization was defined in element config, then raise an error
+                extra_params = merge_equalization(temp, extra_params)
+                if not extra_params:
+                    msg = f'ROADM {el_config["uid"]}: invalid equalization settings'
+                    raise ConfigurationError(msg)
+            temp = merge_amplifier_restrictions(temp, extra_params)
             el_config['params'] = temp
             el_config['type_variety'] = variety
-        elif (typ in ['Fiber', 'RamanFiber']) or (typ == 'Edfa' and variety not in ['default', '']):
+        elif (typ in ['Fiber', 'RamanFiber']):
             raise ConfigurationError(f'The {typ} of variety type {variety} was not recognized:'
                                      '\nplease check it is properly defined in the eqpt_config json file')
+        elif typ == 'Edfa':
+            if variety in ['default', '']:
+                el_config['params'] = Amp.default_values
+            else:
+                raise ConfigurationError(f'The Edfa of variety type {variety} was not recognized:'
+                                         '\nplease check it is properly defined in the eqpt_config json file')
         el = cls(**el_config)
         g.add_node(el)
 
@@ -384,7 +532,8 @@ def network_from_json(json_data, equipment):
                 edge_length = 0.01
             g.add_edge(nodes[from_node], nodes[to_node], weight=edge_length)
         except KeyError:
-            raise NetworkTopologyError(f'can not find {from_node} or {to_node} defined in {cx}')
+            msg = f'can not find {from_node} or {to_node} defined in {cx}'
+            raise NetworkTopologyError(msg)
 
     return g
 
@@ -415,15 +564,13 @@ def save_json(obj, filename):
 
 
 def load_requests(filename, eqpt, bidir, network, network_filename):
-    """ loads the requests from a json or an excel file into a data string
+    """loads the requests from a json or an excel file into a data string"""
-    """
     if filename.suffix.lower() in ('.xls', '.xlsx'):
         _logger.info('Automatically converting requests from XLS to JSON')
         try:
             return convert_service_sheet(filename, eqpt, network, network_filename=network_filename, bidir=bidir)
         except ServiceError as this_e:
-            print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {this_e}')
+            raise ServiceError(f'Service error: {this_e}')
-            exit(1)
     else:
         return load_json(filename)
 
@@ -435,16 +582,19 @@ def requests_from_json(json_data, equipment):
     for req in json_data['path-request']:
         # init all params from request
         params = {}
-        params['request_id'] = req['request-id']
+        params['request_id'] = f'{req["request-id"]}'
         params['source'] = req['source']
         params['bidir'] = req['bidirectional']
         params['destination'] = req['destination']
         params['trx_type'] = req['path-constraints']['te-bandwidth']['trx_type']
-        params['trx_mode'] = req['path-constraints']['te-bandwidth']['trx_mode']
+        if params['trx_type'] is None:
+            msg = f'Request {req["request-id"]} has no transceiver type defined.'
+            raise ServiceError(msg)
+        params['trx_mode'] = req['path-constraints']['te-bandwidth'].get('trx_mode', None)
         params['format'] = params['trx_mode']
         params['spacing'] = req['path-constraints']['te-bandwidth']['spacing']
         try:
-            nd_list = req['explicit-route-objects']['route-object-include-exclude']
+            nd_list = sorted(req['explicit-route-objects']['route-object-include-exclude'], key=lambda x: x['index'])
         except KeyError:
             nd_list = []
         params['nodes_list'] = [n['num-unnum-hop']['node-id'] for n in nd_list]
@@ -452,9 +602,12 @@ def requests_from_json(json_data, equipment):
         # recover trx physical param (baudrate, ...) from type and mode
         # in trx_mode_params optical power is read from equipment['SI']['default'] and
         # nb_channel is computed based on min max frequency and spacing
+        try:
             trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
+        except EquipmentConfigError as e:
+            msg = f'Equipment Config error in {req["request-id"]}: {e}'
+            raise EquipmentConfigError(msg) from e
         params.update(trx_params)
-        # print(trx_params['min_spacing'])
         # optical power might be set differently in the request. if it is indicated then the
         # params['power'] is updated
         try:
@@ -475,12 +628,13 @@ def requests_from_json(json_data, equipment):
                 params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing'])
         except KeyError:
             params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing'])
-        _check_one_request(params, f_max_from_si)
+        params['effective_freq_slot'] = \
-
+            req['path-constraints']['te-bandwidth'].get('effective-freq-slot', [{'N': None, 'M': None}])
         try:
             params['path_bandwidth'] = req['path-constraints']['te-bandwidth']['path_bandwidth']
         except KeyError:
             pass
+        _check_one_request(params, f_max_from_si)
         requests_list.append(PathRequest(**params))
     return requests_list
 
@@ -489,27 +643,65 @@ def _check_one_request(params, f_max_from_si):
     """Checks that the requested parameters are consistant (spacing vs nb channel vs transponder mode...)"""
     f_min = params['f_min']
     f_max = params['f_max']
-    max_recommanded_nb_channels = automatic_nch(f_min, f_max, params['spacing'])
+    max_recommanded_nb_channels = automatic_nch(f_min, f_max_from_si, params['spacing'])
     if params['baud_rate'] is not None:
         # implicitly means that a mode is defined with min_spacing
         if params['min_spacing'] > params['spacing']:
             msg = f'Request {params["request_id"]} has spacing below transponder ' +\
                   f'{params["trx_type"]} {params["trx_mode"]} min spacing value ' +\
                   f'{params["min_spacing"]*1e-9}GHz.\nComputation stopped'
-            print(msg)
-            _logger.critical(msg)
             raise ServiceError(msg)
         if f_max > f_max_from_si:
-            msg = f'''Requested channel number {params["nb_channel"]}, baud rate {params["baud_rate"]} GHz
+            msg = f'Requested channel number {params["nb_channel"]}, baud rate {params["baud_rate"] * 1e-9} GHz' \
-            and requested spacing {params["spacing"]*1e-9}GHz is not consistent with frequency range
+                  + f' and requested spacing {params["spacing"]*1e-9}GHz is not consistent with frequency range' \
-            {f_min*1e-12} THz, {f_max*1e-12} THz, min recommanded spacing {params["min_spacing"]*1e-9}GHz.
+                  + f' {f_min*1e-12} THz, {f_max_from_si*1e-12} THz.' \
-            max recommanded nb of channels is {max_recommanded_nb_channels}.'''
+                  + f' Max recommanded nb of channels is {max_recommanded_nb_channels}.'
-            _logger.critical(msg)
             raise ServiceError(msg)
+    # Transponder mode already selected; will it fit to the requested bandwidth?
+    if params['trx_mode'] is not None and params['effective_freq_slot'] is not None:
+        required_nb_of_channels, requested_m = compute_spectrum_slot_vs_bandwidth(params['path_bandwidth'],
+                                                                                  params['spacing'],
+                                                                                  params['bit_rate'])
+        _, per_channel_m = compute_spectrum_slot_vs_bandwidth(params['bit_rate'],
+                                                              params['spacing'],
+                                                              params['bit_rate'])
+        # each M should fit one or more channels if it is not None
+        # spectrum slots should not overlap
+        # resulting nb of channels should be bigger than the nb computed with path_bandwidth
+        # without being splitted
+        # TODO: elaborate a more accurate estimate with nb_wl * tx_osnr + possibly guardbands in case of
+        # superchannel closed packing.
+        nb_of_channels = 0
+        # order slots
+        slots = sorted(params['effective_freq_slot'], key=lambda x: float('inf') if x['N'] is None else x['N'])
+        for slot in slots:
+            nb_of_channels = nb_of_channels + slot['M'] // per_channel_m if slot['M'] is not None \
+                and nb_of_channels is not None else None
+            if slot['M'] is not None and slot['M'] < per_channel_m:
+                msg = f'Requested M {slot} number of slots for request' +\
+                      f' {params["request_id"]} should be greater than {per_channel_m} to support request' +\
+                      f'with {params["trx_type"]} {params["trx_mode"]}'
+                _logger.critical(msg)
+        if nb_of_channels is not None and nb_of_channels < required_nb_of_channels:
+            msg = f'Requested M {slots} number of slots for request {params["request_id"]} support {nb_of_channels}' +\
+                  f' nb of channels while {required_nb_of_channels} are required to support request' +\
+                  f' {params["path_bandwidth"] * 1e-9} Gbit/s with {params["trx_type"]} {params["trx_mode"]}'
+            raise ServiceError(msg)
+        if nb_of_channels is not None:
+            _, stop0n = mvalue_to_slots(slots[0]['N'], slots[0]['M'])
+            i = 1
+            while i < len(slots):
+                slot = slots[i]
+                startn, stopn = mvalue_to_slots(slot['N'], slot['M'])
+                if startn <= stop0n:
+                    msg = f'Requested M {slots} for request {params["request_id"]} overlap'
+                    raise ServiceError(msg)
+                _, stop0n = startn, stopn
+                i += 1
 
 
 def disjunctions_from_json(json_data):
-    """ reads the disjunction requests from the json dict and create the list
+    """reads the disjunction requests from the json dict and create the list
     of requested disjunctions for this set of requests
     """
     disjunctions_list = []
@@ -538,3 +730,42 @@ def convert_service_sheet(
     data = read_service_sheet(input_filename, eqpt, network, network_filename, bidir)
     save_json(data, output_filename)
     return data
+
+
+def find_equalisation(params, equalization_types):
+    """Find the equalization(s) defined in params. params can be a dict or a Roadm object.
+
+    >>> roadm = {'add_drop_osnr': 100, 'pmd': 1, 'pdl': 0.5,
+    ...     'restrictions': {'preamp_variety_list': ['a'], 'booster_variety_list': ['b']},
+    ...     'target_psd_out_mWperGHz': 4e-4}
+    >>> equalization_types = ['target_pch_out_db', 'target_psd_out_mWperGHz']
+    >>> find_equalisation(roadm, equalization_types)
+    {'target_pch_out_db': False, 'target_psd_out_mWperGHz': True}
+    """
+    equalization = {e: False for e in equalization_types}
+    for equ in equalization_types:
+        if equ in params:
+            equalization[equ] = True
+    return equalization
+
+
+def merge_equalization(params, extra_params):
+    """params contains ROADM element config and extra_params default values from equipment library.
+    If equalization is not defined in ROADM element use the one defined in equipment library.
+    Only one type of equalization must be defined: power (target_pch_out_db) or PSD (target_psd_out_mWperGHz)
+    or PSW (target_out_mWperSlotWidth)
+    params and extra_params are dict
+    """
+    equalization_types = ['target_pch_out_db', 'target_psd_out_mWperGHz', 'target_out_mWperSlotWidth']
+    roadm_equalizations = find_equalisation(params, equalization_types)
+    if sum(roadm_equalizations.values()) > 1:
+        # if ROADM config contains more than one equalization type then this is an error
+        return None
+    if sum(roadm_equalizations.values()) == 1:
+        # if ROADM config contains one equalization
+        # don't use the default equalization
+        return {k: v for k, v in extra_params.items() if k not in equalization_types}
+    if sum(roadm_equalizations.values()) == 0:
+        # If ROADM config doesn't contain any equalization type, keep the default one
+        return extra_params
+    return None

gnpy/tools/plots.py

@@ -1,12 +1,12 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 
-'''
+"""
 gnpy.tools.plots
 ================
 
 Graphs and plots usable from a CLI application
-'''
+"""
 
 from matplotlib.pyplot import show, axis, figure, title, text
 from networkx import draw_networkx

gnpy/tools/service_sheet.py

@@ -18,7 +18,6 @@ from copy import deepcopy
 from gnpy.core.utils import db2lin
 from gnpy.core.exceptions import ServiceError
 from gnpy.core.elements import Transceiver, Roadm, Edfa, Fiber
-import gnpy.core.ansi_escapes as ansi_escapes
 from gnpy.tools.convert import corresp_names, corresp_next_node
 
 SERVICES_COLUMN = 12
@@ -68,24 +67,21 @@ class Request_element(Element):
                 if [mode for mode in equipment['Transceiver'][Request.trx_type].mode if mode['format'] == Requestmode]:
                     self.mode = Requestmode
                 else:
-                    msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' with mode: \'{Requestmode}\' in eqpt library \nComputation stopped.'
+                    msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' ' \
-                    # print(msg)
+                        + f'with mode: \'{Requestmode}\' in eqpt library \nComputation stopped.'
-                    logger.critical(msg)
                     raise ServiceError(msg)
             else:
                 Requestmode = None
                 self.mode = Request.mode
         except KeyError:
-            msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' with mode: \'{Request.mode}\' in eqpt library \nComputation stopped.'
+            msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' ' \
-            # print(msg)
+                + f'with mode: \'{Request.mode}\' in eqpt library \nComputation stopped.'
-            logger.critical(msg)
             raise ServiceError(msg)
         # excel input are in GHz and dBm
         if Request.spacing is not None:
             self.spacing = Request.spacing * 1e9
         else:
             msg = f'Request {self.request_id} missing spacing: spacing is mandatory.\ncomputation stopped'
-            logger.critical(msg)
             raise ServiceError(msg)
         if Request.power is not None:
             self.power = db2lin(Request.power) * 1e-3
@@ -127,7 +123,7 @@ class Request_element(Element):
                     'technology': 'flexi-grid',
                     'trx_type': self.trx_type,
                     'trx_mode': self.mode,
-                    'effective-freq-slot': [{'N': 'null', 'M': 'null'}],
+                    'effective-freq-slot': [{'N': None, 'M': None}],
                     'spacing': self.spacing,
                     'max-nb-of-channel': self.nb_channel,
                     'output-power': self.power
@@ -225,7 +221,7 @@ def parse_excel(input_filename):
 def parse_service_sheet(service_sheet):
     """ reads each column according to authorized fieldnames. order is not important.
     """
-    logger.info(f'Validating headers on {service_sheet.name!r}')
+    logger.debug(f'Validating headers on {service_sheet.name!r}')
     # add a test on field to enable the '' field case that arises when columns on the
     # right hand side are used as comments or drawing in the excel sheet
     header = [x.value.strip() for x in service_sheet.row(4)[0:SERVICES_COLUMN]
@@ -245,7 +241,6 @@ def parse_service_sheet(service_sheet):
         service_fieldnames = [authorized_fieldnames[e] for e in header]
     except KeyError:
         msg = f'Malformed header on Service sheet: {header} field not in {authorized_fieldnames}'
-        logger.critical(msg)
         raise ValueError(msg)
     for row in all_rows(service_sheet, start=5):
         yield Request(**parse_row(row[0:SERVICES_COLUMN], service_fieldnames))
@@ -273,15 +268,13 @@ def correct_xls_route_list(network_filename, network, pathreqlist):
     for pathreq in pathreqlist:
         # first check that source and dest are transceivers
         if pathreq.source not in transponders:
-            msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find' +\
+            msg = f'Request: {pathreq.request_id}: could not find' +\
-                f' transponder source : {pathreq.source}.{ansi_escapes.reset}'
+                f' transponder source : {pathreq.source}.'
-            logger.critical(msg)
             raise ServiceError(msg)
 
         if pathreq.destination not in transponders:
-            msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find' +\
+            msg = f'Request: {pathreq.request_id}: could not find' +\
-                f' transponder destination: {pathreq.destination}.{ansi_escapes.reset}'
+                f' transponder destination: {pathreq.destination}.'
-            logger.critical(msg)
             raise ServiceError(msg)
         # silently pop source and dest nodes from the list if they were added by the user as first
         # and last elem in the constraints respectively. Other positions must lead to an error
@@ -333,17 +326,16 @@ def correct_xls_route_list(network_filename, network, pathreqlist):
                             # too much ambiguity, 'b' is an ila, its name can be:
                             # Edfa0_fiber (a → b)-xx if next node is c or
                             # Edfa0_fiber (c → b)-xx if next node is a
-                            msg = f'{ansi_escapes.yellow}Invalid route node specified:' +\
+                            msg = f'Request {pathreq.request_id}: Invalid route node specified:' \
-                                f'\n\t\'{n_id}\', replaced with \'{new_n}\'{ansi_escapes.reset}'
+                                + f'\n\t\'{n_id}\', replaced with \'{new_n}\''
-                            logger.info(msg)
+                            logger.warning(msg)
                             pathreq.nodes_list[pathreq.nodes_list.index(n_id)] = new_n
                     except StopIteration:
                         # shall not come in this case, unless requested direction does not exist
-                        msg = f'{ansi_escapes.yellow}Invalid route specified {n_id}: could' +\
+                        msg = f'Request {pathreq.request_id}: Invalid route specified {n_id}: could' \
-                            f' not decide on direction, skipped!.\nPlease add a valid' +\
+                            + ' not decide on direction, skipped!.\nPlease add a valid' \
-                            f' direction in constraints (next neighbour node){ansi_escapes.reset}'
+                            + ' direction in constraints (next neighbour node)'
-                        print(msg)
+                        logger.warning(msg)
-                        logger.info(msg)
                         pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
                         pathreq.nodes_list.remove(n_id)
                 else:
@@ -351,28 +343,24 @@ def correct_xls_route_list(network_filename, network, pathreqlist):
                         # if no matching can be found in the network just ignore this constraint
                         # if it is a loose constraint
                         # warns the user that this node is not part of the topology
-                        msg = f'{ansi_escapes.yellow}Invalid node specified:\n\t\'{n_id}\'' +\
+                        msg = f'Request {pathreq.request_id}: Invalid node specified:\n\t\'{n_id}\'' \
-                            f', could not use it as constraint, skipped!{ansi_escapes.reset}'
+                            + ', could not use it as constraint, skipped!'
-                        print(msg)
+                        logger.warning(msg)
-                        logger.info(msg)
                         pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
                         pathreq.nodes_list.remove(n_id)
                     else:
-                        msg = f'{ansi_escapes.red}Could not find node:\n\t\'{n_id}\' in network' +\
+                        msg = f'Request {pathreq.request_id}: Could not find node:\n\t\'{n_id}\' in network' \
-                            f' topology. Strict constraint can not be applied.{ansi_escapes.reset}'
+                            + ' topology. Strict constraint can not be applied.'
-                        logger.critical(msg)
                         raise ServiceError(msg)
             else:
                 if temp.loose_list[i] == 'LOOSE':
-                    print(f'{ansi_escapes.yellow}Invalid route node specified:\n\t\'{n_id}\'' +
+                    logger.warning(f'Request {pathreq.request_id}: Invalid route node specified:\n\t\'{n_id}\''
-                          f' type is not supported as constraint with xls network input,' +
+                                   + ' type is not supported as constraint with xls network input, skipped!')
-                          f' skipped!{ansi_escapes.reset}')
                     pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
                     pathreq.nodes_list.remove(n_id)
                 else:
-                    msg = f'{ansi_escapes.red}Invalid route node specified \n\t\'{n_id}\'' +\
+                    msg = f'Invalid route node specified \n\t\'{n_id}\'' \
-                        f' type is not supported as constraint with xls network input,' +\
+                        + ' type is not supported as constraint with xls network input,' \
-                        f', Strict constraint can not be applied.{ansi_escapes.reset}'
+                        + ', Strict constraint can not be applied.'
-                    logger.critical(msg)
                     raise ServiceError(msg)
     return pathreqlist

gnpy/topology/__init__.py

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

gnpy/topology/request.py

@@ -20,30 +20,28 @@ from logging import getLogger
 from networkx import (dijkstra_path, NetworkXNoPath,
                       all_simple_paths, shortest_simple_paths)
 from networkx.utils import pairwise
-from numpy import mean
+from numpy import mean, argmin
 from gnpy.core.elements import Transceiver, Roadm
 from gnpy.core.utils import lin2db
-from gnpy.core.info import create_input_spectral_information
+from gnpy.core.info import create_input_spectral_information, carriers_to_spectral_information, ReferenceCarrier
 from gnpy.core.exceptions import ServiceError, DisjunctionError
-import gnpy.core.ansi_escapes as ansi_escapes
 from copy import deepcopy
 from csv import writer
 from math import ceil
 
 LOGGER = getLogger(__name__)
 
-RequestParams = namedtuple('RequestParams', 'request_id source destination bidir trx_type' +
+RequestParams = namedtuple('RequestParams', 'request_id source destination bidir trx_type'
-                           ' trx_mode nodes_list loose_list spacing power nb_channel f_min' +
+                           ' trx_mode nodes_list loose_list spacing power nb_channel f_min'
-                           ' f_max format baud_rate OSNR bit_rate roll_off tx_osnr' +
+                           ' f_max format baud_rate OSNR penalties bit_rate'
-                           ' min_spacing cost path_bandwidth')
+                           ' roll_off tx_osnr min_spacing cost path_bandwidth effective_freq_slot'
-DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link' +
+                           ' equalization_offset_db')
-                               '_diverse node_diverse disjunctions_req')
+DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link_diverse'
+                               ' node_diverse disjunctions_req')
 
 
 class PathRequest:
-    """ the class that contains all attributes related to a request
+    """the class that contains all attributes related to a request"""
-    """
-
     def __init__(self, *args, **params):
         params = RequestParams(**params)
         self.request_id = params.request_id
@@ -62,12 +60,18 @@ class PathRequest:
         self.f_max = params.f_max
         self.format = params.format
         self.OSNR = params.OSNR
+        self.penalties = params.penalties
         self.bit_rate = params.bit_rate
         self.roll_off = params.roll_off
         self.tx_osnr = params.tx_osnr
         self.min_spacing = params.min_spacing
         self.cost = params.cost
         self.path_bandwidth = params.path_bandwidth
+        if params.effective_freq_slot is not None:
+            self.N = [s['N'] for s in params.effective_freq_slot]
+            self.M = [s['M'] for s in params.effective_freq_slot]
+        self.initial_spectrum = None
+        self.offset_db = params.equalization_offset_db
 
     def __str__(self):
         return '\n\t'.join([f'{type(self).__name__} {self.request_id}',
@@ -75,7 +79,7 @@ class PathRequest:
                             f'destination:  {self.destination}'])
 
     def __repr__(self):
-        if self.baud_rate is not None:
+        if self.baud_rate is not None and self.bit_rate is not None:
             temp = self.baud_rate * 1e-9
             temp2 = self.bit_rate * 1e-9
         else:
@@ -99,8 +103,7 @@ class PathRequest:
 
 
 class Disjunction:
-    """ the class that contains all attributes related to disjunction constraints
+    """the class that contains all attributes related to disjunction constraints"""
-    """
 
     def __init__(self, *args, **params):
         params = DisjunctionParams(**params)
@@ -129,7 +132,7 @@ BLOCKING_NOPATH = ['NO_PATH', 'NO_PATH_WITH_CONSTRAINT',
                    'NO_FEASIBLE_BAUDRATE_WITH_SPACING',
                    'NO_COMPUTED_SNR']
 BLOCKING_NOMODE = ['NO_FEASIBLE_MODE', 'MODE_NOT_FEASIBLE']
-BLOCKING_NOSPECTRUM = 'NO_SPECTRUM'
+BLOCKING_NOSPECTRUM = ['NO_SPECTRUM', 'NOT_ENOUGH_RESERVED_SPECTRUM']
 
 
 class ResultElement:
@@ -145,8 +148,7 @@ class ResultElement:
 
     @property
     def detailed_path_json(self):
-        """ a function that builds path object for normal and blocking cases
+        """a function that builds path object for normal and blocking cases"""
-        """
         index = 0
         pro_list = []
         for element in self.computed_path:
@@ -162,24 +164,30 @@ class ResultElement:
             }
             pro_list.append(temp)
             index += 1
-            if self.path_request.M > 0:
+            if not hasattr(self.path_request, 'blocking_reason'):
+                # M and N values should not be None at this point
+                if self.path_request.M is None or self.path_request.N is None:
+                    raise ServiceError('request {self.path_id} should have positive non null n and m values.')
+
                 temp = {
                     'path-route-object': {
                         'index': index,
-                        "label-hop": {
+                        "label-hop": [{
-                            "N": self.path_request.N,
+                            "N": n,
-                            "M": self.path_request.M
+                            "M": m
-                        },
+                        } for n, m in zip(self.path_request.N, self.path_request.M)],
                     }
                 }
                 pro_list.append(temp)
                 index += 1
-            elif self.path_request.M == 0 and hasattr(self.path_request, 'blocking_reason'):
-                # if the path is blocked due to spectrum, no label object is created, but
-                # the json response includes a detailed path for user infromation.
-                pass
             else:
-                raise ServiceError('request {self.path_id} should have positive path bandwidth value.')
+                # if the path is blocked, no label object is created, but
+                # the json response includes a detailed path for user information.
+                # M and N values should be None at this point
+                if self.path_request.M is not None or self.path_request.N is not None:
+                    raise ServiceError('request {self.path_id} should not have label M and N values at this point.')
+
+
             if isinstance(element, Transceiver):
                 temp = {
                     'path-route-object': {
@@ -196,11 +204,9 @@ class ResultElement:
 
     @property
     def path_properties(self):
-        """ a function that returns the path properties (metrics, crossed elements) into a dict
+        """a function that returns the path properties (metrics, crossed elements) into a dict"""
-        """
         def path_metric(pth, req):
-            """ creates the metrics dictionary
+            """creates the metrics dictionary"""
-            """
             return [
                 {
                     'metric-type': 'SNR-bandwidth',
@@ -242,8 +248,7 @@ class ResultElement:
 
     @property
     def pathresult(self):
-        """ create the result dictionnary (response for a request)
+        """create the result dictionnary (response for a request)"""
-        """
         try:
             if self.path_request.blocking_reason in BLOCKING_NOPATH:
                 response = {
@@ -281,7 +286,6 @@ def compute_constrained_path(network, req):
         # been corrected and harmonized before
         msg = (f'Request {req.request_id} malformed list of nodes: last node should '
                'be destination trx')
-        LOGGER.critical(msg)
         raise ValueError()
 
     trx = [n for n in network if isinstance(n, Transceiver)]
@@ -296,10 +300,9 @@ def compute_constrained_path(network, req):
         path_generator = shortest_simple_paths(network, source, destination, weight='weight')
         total_path = next(path for path in path_generator if ispart(nodes_list, path))
     except NetworkXNoPath:
-        msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path from'
+        msg = (f'Request {req.request_id} could not find a path from'
-               f' {source.uid} to node: {destination.uid} in network topology{ansi_escapes.reset}')
+               f' {source.uid} to node: {destination.uid} in network topology')
         LOGGER.critical(msg)
-        print(msg)
         req.blocking_reason = 'NO_PATH'
         total_path = []
     except StopIteration:
@@ -308,67 +311,88 @@ def compute_constrained_path(network, req):
         # last node which is the transceiver)
         # if all nodes i n node_list are LOOSE constraint, skip the constraints and find
         # a path w/o constraints, else there is no possible path
-        print(f'{ansi_escapes.yellow}Request {req.request_id} could not find a path crossing '
+        LOGGER.warning(f'Request {req.request_id} could not find a path crossing '
-              f'{[el.uid for el in nodes_list[:-1]]} in network topology{ansi_escapes.reset}')
+                       f'{[el.uid for el in nodes_list[:-1]]} in network topology')
 
         if 'STRICT' not in req.loose_list[:-1]:
-            msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path with user_'
+            msg = (f'Request {req.request_id} could not find a path with user_'
-                   f'include node constraints{ansi_escapes.reset}')
+                   f'include node constraints. Constraint ignored')
-            LOGGER.info(msg)
+            LOGGER.warning(msg)
-            print(f'constraint ignored')
             total_path = dijkstra_path(network, source, destination, weight='weight')
         else:
             # one STRICT makes the whole list STRICT
-            msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path with user '
+            msg = (f'Request {req.request_id} could not find a path with user '
-                   f'include node constraints.\nNo path computed{ansi_escapes.reset}')
+                   f'include node constraints.\nNo path computed')
             LOGGER.critical(msg)
-            print(msg)
             req.blocking_reason = 'NO_PATH_WITH_CONSTRAINT'
             total_path = []
-
     return total_path
 
 
+def ref_carrier(equipment):
+    """Create a reference carier based SI information with the specified request's power:
+    req_power records the power in W that the user has defined for a given request
+    (which might be different from the one used for the design).
+    """
+    return ReferenceCarrier(baud_rate=equipment['SI']['default'].baud_rate,
+                            slot_width=equipment['SI']['default'].spacing)
+
+
 def propagate(path, req, equipment):
+    """propagates signals in each element according to initial spectrum set by user"""
+    if req.initial_spectrum is not None:
+        si = carriers_to_spectral_information(initial_spectrum=req.initial_spectrum,
+                                              power=req.power, ref_carrier=ref_carrier(equipment))
+    else:
         si = create_input_spectral_information(
-        req.f_min, req.f_max, req.roll_off, req.baud_rate,
+            f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
-        req.power, req.spacing)
+            power=req.power, spacing=req.spacing, tx_osnr=req.tx_osnr, delta_pdb=req.offset_db,
+            ref_carrier=ref_carrier(equipment))
     for i, el in enumerate(path):
         if isinstance(el, Roadm):
             si = el(si, degree=path[i+1].uid)
         else:
             si = el(si)
-    path[0].update_snr(req.tx_osnr)
+    path[0].update_snr(si.tx_osnr)
+    path[0].calc_penalties(req.penalties)
     if any(isinstance(el, Roadm) for el in path):
-        path[-1].update_snr(req.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
+        path[-1].update_snr(si.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
     else:
-        path[-1].update_snr(req.tx_osnr)
+        path[-1].update_snr(si.tx_osnr)
+    path[-1].calc_penalties(req.penalties)
     return si
 
 
 def propagate_and_optimize_mode(path, req, equipment):
     # if mode is unknown : loops on the modes starting from the highest baudrate fiting in the
-    # step 1: create an ordered list of modes based on baudrate
+    # step 1: create an ordered list of modes based on baudrate and power offset
-    baudrate_to_explore = list(set([this_mode['baud_rate']
+    # order higher baudrate with higher power offset first
+    baudrate_offset_to_explore = list(set([(this_mode['baud_rate'], this_mode['equalization_offset_db'])
                                            for this_mode in equipment['Transceiver'][req.tsp].mode
                                            if float(this_mode['min_spacing']) <= req.spacing]))
     # TODO be carefull on limits cases if spacing very close to req spacing eg 50.001 50.000
-    baudrate_to_explore = sorted(baudrate_to_explore, reverse=True)
+    baudrate_offset_to_explore = sorted(baudrate_offset_to_explore, reverse=True)
-    if baudrate_to_explore:
+    if baudrate_offset_to_explore:
         # at least 1 baudrate can be tested wrt spacing
-        for this_br in baudrate_to_explore:
+        for (this_br, this_offset) in baudrate_offset_to_explore:
             modes_to_explore = [this_mode for this_mode in equipment['Transceiver'][req.tsp].mode
-                                if this_mode['baud_rate'] == this_br and
+                                if this_mode['baud_rate'] == this_br
-                                float(this_mode['min_spacing']) <= req.spacing]
+                                and float(this_mode['min_spacing']) <= req.spacing]
             modes_to_explore = sorted(modes_to_explore,
-                                      key=lambda x: x['bit_rate'], reverse=True)
+                                      key=lambda x: (x['bit_rate'], x['equalization_offset_db']), reverse=True)
-            # print(modes_to_explore)
             # step2: computes propagation for each baudrate: stop and select the first that passes
-            # TODO: the case of roll of is not included: for now use SI one
+            # TODO: the case of roll off is not included: for now use SI one
             # TODO: if the loop in mode optimization does not have a feasible path, then bugs
-            spc_info = create_input_spectral_information(req.f_min, req.f_max,
+            if req.initial_spectrum is not None:
-                                                         equipment['SI']['default'].roll_off,
+                # this case is not yet handled: spectrum can not be defined for the path-request-run function
-                                                         this_br, req.power, req.spacing)
+                # and this function is only called in this case. so coming here should not be considered yet.
+                msg = f'Request: {req.request_id} contains a unexpected initial_spectrum.'
+                raise ServiceError(msg)
+            spc_info = create_input_spectral_information(f_min=req.f_min, f_max=req.f_max,
+                                                         roll_off=equipment['SI']['default'].roll_off,
+                                                         baud_rate=this_br, power=req.power, spacing=req.spacing,
+                                                         delta_pdb=this_offset,
+                                                         tx_osnr=req.tx_osnr, ref_carrier=ref_carrier(equipment))
             for i, el in enumerate(path):
                 if isinstance(el, Roadm):
                     spc_info = el(spc_info, degree=path[i+1].uid)
@@ -377,11 +401,13 @@ def propagate_and_optimize_mode(path, req, equipment):
             for this_mode in modes_to_explore:
                 if path[-1].snr is not None:
                     path[0].update_snr(this_mode['tx_osnr'])
+                    path[0].calc_penalties(this_mode['penalties'])
                     if any(isinstance(el, Roadm) for el in path):
                         path[-1].update_snr(this_mode['tx_osnr'], equipment['Roadm']['default'].add_drop_osnr)
                     else:
                         path[-1].update_snr(this_mode['tx_osnr'])
-                    if round(min(path[-1].snr + lin2db(this_br / (12.5e9))), 2) \
+                    path[-1].calc_penalties(this_mode['penalties'])
+                    if round(min(path[-1].snr_01nm - path[-1].total_penalty), 2) \
                             > this_mode['OSNR'] + equipment['SI']['default'].sys_margins:
                         return path, this_mode
                     else:
@@ -389,27 +415,23 @@ def propagate_and_optimize_mode(path, req, equipment):
                 else:
                     req.blocking_reason = 'NO_COMPUTED_SNR'
                     return path, None
-
         # only get to this point if no baudrate/mode satisfies OSNR requirement
 
         # returns the last propagated path and mode
         msg = f'\tWarning! Request {req.request_id}: no mode satisfies path SNR requirement.\n'
-        print(msg)
+        LOGGER.warning(msg)
-        LOGGER.info(msg)
         req.blocking_reason = 'NO_FEASIBLE_MODE'
         return path, last_explored_mode
     else:
         # no baudrate satisfying spacing
         msg = f'\tWarning! Request {req.request_id}: no baudrate satisfies spacing requirement.\n'
-        print(msg)
+        LOGGER.warning(msg)
-        LOGGER.info(msg)
         req.blocking_reason = 'NO_FEASIBLE_BAUDRATE_WITH_SPACING'
         return [], None
 
 
 def jsontopath_metric(path_metric):
-    """ a functions that reads resulting metric  from json string
+    """a functions that reads resulting metric  from json string"""
-    """
     output_snr = next(e['accumulative-value']
                       for e in path_metric if e['metric-type'] == 'SNR-0.1nm')
     output_snrbandwidth = next(e['accumulative-value']
@@ -427,9 +449,7 @@ def jsontopath_metric(path_metric):
 
 
 def jsontoparams(my_p, tsp, mode, equipment):
-    """ a function that derives optical params from transponder type and mode
+    """a function that derives optical params from transponder type and mode supports the no mode case"""
-        supports the no mode case
-    """
     temp = []
     for elem in my_p['path-properties']['path-route-objects']:
         if 'num-unnum-hop' in elem['path-route-object']:
@@ -439,8 +459,8 @@ def jsontoparams(my_p, tsp, mode, equipment):
     temp2 = []
     for elem in my_p['path-properties']['path-route-objects']:
         if 'label-hop' in elem['path-route-object'].keys():
-            temp2.append(f'{elem["path-route-object"]["label-hop"]["N"]}, ' +
+            temp2.append(f'{[e["N"] for e in elem["path-route-object"]["label-hop"]]}, '
-                         f'{elem["path-route-object"]["label-hop"]["M"]}')
+                         + f'{[e["M"] for e in elem["path-route-object"]["label-hop"]]}')
     # OrderedDict.fromkeys returns the unique set of strings.
     # TODO: if spectrum changes along the path, we should be able to give the segments
     #       eg for regeneration case
@@ -464,7 +484,7 @@ def jsontoparams(my_p, tsp, mode, equipment):
 
 
 def jsontocsv(json_data, equipment, fileout):
-    """ reads json path result file in accordance with:
+    """reads json path result file in accordance with:
     Yang model for requesting Path Computation
     draft-ietf-teas-yang-path-computation-01.txt.
     and write results in an CSV file
@@ -696,8 +716,8 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list):
         # in each loop, dpath is updated with a path for rq that satisfies
         # disjunction with each path in dpath
         # for example, assume set of requests in the vector (disjunction_list) is  {rq1,rq2, rq3}
-        # rq1  p1: abfhg
+        # rq1  p1: aefhg
-        #      p2: aefhg
+        #      p2: abfhg
         #      p3: abcg
         # rq2  p8: bf
         # rq3  p4: abcgh
@@ -714,6 +734,7 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list):
         #  after second loop:
         #  dpath = [ p3 p8 p6 ]
         #  since p1 and p4 are not disjoint
+        #        p1 and p6 are not disjoint
         #        p1 and p7 are not disjoint
         #        p3 and p4 are not disjoint
         #        p3 and p7 are not disjoint
@@ -737,7 +758,6 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list):
                         temp.append(temp2)
                         # print(f' coucou {elem1}: \t{temp}')
             dpath = temp
-        # print(dpath)
         candidates[dis.disjunction_id] = dpath
 
     # for i in disjunctions_list:
@@ -778,9 +798,9 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list):
                         if pth in cndt:
                             candidates[this_id].remove(cndt)
 
-#    for i in disjunctions_list:
+    # for i in disjunctions_list:
-#        print(i.disjunction_id)
+    #     print(i.disjunction_id)
-#        print(f'\n{candidates[i.disjunction_id]}')
+    #     print(f'\n{candidates[i.disjunction_id]}')
 
     # step 4 apply route constraints: remove candidate path that do not satisfy
     # the constraint only in  the case of disjounction: the simple path is processed in
@@ -788,33 +808,34 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list):
     # TODO: keep a version without the loose constraint
     for this_d in disjunctions_list:
         temp = []
+        alternatetemp = []
         for j, sol in enumerate(candidates[this_d.disjunction_id]):
             testispartok = True
+            testispartnokloose = True
             for pth in sol:
                 # print(f'test {allpaths[id(pth)].req.request_id}')
                 # print(f'length of route {len(allpaths[id(pth)].req.nodes_list)}')
                 if allpaths[id(pth)].req.nodes_list:
-                    # if pth does not containt the ordered list node, remove sol from the candidate
+                    # if any pth from sol does not contain the ordered list node,
-                    # except if this was the last solution: then check if the constraint is loose
+                    # remove sol from the candidate, except if constraint was loose:
-                    # or not
+                    # then keep sol as an alternate solution
                     if not ispart(allpaths[id(pth)].req.nodes_list, pth):
-                        # print(f'nb of solutions {len(temp)}')
-                        if j < len(candidates[this_d.disjunction_id]) - 1:
-                            msg = f'removing {sol}'
-                            LOGGER.info(msg)
-                            testispartok = False
-                            # break
-                        else:
-                            if 'LOOSE' in allpaths[id(pth)].req.loose_list:
-                                LOGGER.info(f'Could not apply route constraint' +
-                                            f'{allpaths[id(pth)].req.nodes_list} on request' +
-                                            f' {allpaths[id(pth)].req.request_id}')
-                            else:
-                                LOGGER.info(f'removing last solution from candidate paths\n{sol}')
                         testispartok = False
+                        if 'STRICT' in allpaths[id(pth)].req.loose_list:
+                            LOGGER.debug(f'removing solution from candidate paths\n{pth}')
+                            testispartnokloose = False
+                            break
             if testispartok:
                 temp.append(sol)
+            elif testispartnokloose:
+                LOGGER.debug(f'Adding solution as alternate solution not satisfying constraint\n{pth}')
+                alternatetemp.append(sol)
+        if temp:
             candidates[this_d.disjunction_id] = temp
+        elif alternatetemp:
+            candidates[this_d.disjunction_id] = alternatetemp
+        else:
+            candidates[this_d.disjunction_id] = []
 
     # step 5 select the first combination that works
     pathreslist_disjoint = {}
@@ -829,9 +850,7 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list):
                     # remove duplicated candidates
                     candidates = remove_candidate(candidates, allpaths, allpaths[id(pth)].req, pth)
         else:
-            msg = f'No disjoint path found with added constraint'
+            msg = 'No disjoint path found with added constraint\nComputation stopped.'
-            LOGGER.critical(msg)
-            print(f'{msg}\nComputation stopped.')
             # TODO in this case: replay step 5  with the candidate without constraints
             raise DisjunctionError(msg)
 
@@ -852,8 +871,7 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list):
 
 
 def isdisjoint(pth1, pth2):
-    """ returns 0 if disjoint
+    """returns 0 if disjoint"""
-    """
     edge1 = list(pairwise(pth1))
     edge2 = list(pairwise(pth2))
     for edge in edge1:
@@ -863,7 +881,7 @@ def isdisjoint(pth1, pth2):
 
 
 def find_reversed_path(pth):
-    """ select of intermediate roadms and find the path between them
+    """select of intermediate roadms and find the path between them
     note that this function may not give an exact result in case of multiple
     links between two adjacent nodes.
     """
@@ -888,9 +906,8 @@ def find_reversed_path(pth):
             # concatenation should be [roadma el1 el2 roadmb el3 el4 roadmc]
             reversed_path = list(OrderedDict.fromkeys(reversed_path))
         else:
-            msg = f'Error while handling reversed path {pth[-1].uid} to {pth[0].uid}:' +\
+            msg = f'Error while handling reversed path {pth[-1].uid} to {pth[0].uid}:' \
-                ' can not handle unidir topology. TO DO.'
+                + ' can not handle unidir topology. TO DO.'
-            LOGGER.critical(msg)
             raise ValueError(msg)
     reversed_path.append(pth[0])
 
@@ -898,9 +915,7 @@ def find_reversed_path(pth):
 
 
 def ispart(ptha, pthb):
-    """ the functions takes two paths a and b and retrns True
+    """the functions takes two paths a and b and retrns True if all a elements are part of b and in the same order"""
-        if all a elements are part of b and in the same order
-    """
     j = 0
     for elem in ptha:
         if elem in pthb:
@@ -914,8 +929,7 @@ def ispart(ptha, pthb):
 
 
 def remove_candidate(candidates, allpaths, rqst, pth):
-    """ filter duplicate candidates
+    """filter duplicate candidates"""
-    """
     # print(f'coucou {rqst.request_id}')
     for key, candidate in candidates.items():
         temp = candidate.copy()
@@ -930,8 +944,7 @@ def remove_candidate(candidates, allpaths, rqst, pth):
 
 
 def compare_reqs(req1, req2, disjlist):
-    """ compare two requests: returns True or False
+    """compare two requests: returns True or False"""
-    """
     dis1 = [d for d in disjlist if req1.request_id in d.disjunctions_req]
     dis2 = [d for d in disjlist if req2.request_id in d.disjunctions_req]
     same_disj = False
@@ -971,19 +984,24 @@ def compare_reqs(req1, req2, disjlist):
 
 
 def requests_aggregation(pathreqlist, disjlist):
-    """ this function aggregates requests so that if several requests
+    """this function aggregates requests so that if several requests
     exist between same source and destination and with same transponder type
+    If transponder mode is defined and identical, then also agregates demands.
     """
     # todo maybe add conditions on mode ??, spacing ...
     # currently if undefined takes the default values
     local_list = pathreqlist.copy()
     for req in pathreqlist:
         for this_r in local_list:
-            if req.request_id != this_r.request_id and compare_reqs(req, this_r, disjlist):
+            if req.request_id != this_r.request_id and compare_reqs(req, this_r, disjlist) and\
+                    this_r.tsp_mode is not None:
                 # aggregate
                 this_r.path_bandwidth += req.path_bandwidth
+                this_r.N = this_r.N + req.N
+                this_r.M = this_r.M + req.M
                 temp_r_id = this_r.request_id
                 this_r.request_id = ' | '.join((this_r.request_id, req.request_id))
+
                 # remove request from list
                 local_list.remove(req)
                 # todo change also disjunction req with new demand
@@ -1000,7 +1018,8 @@ def requests_aggregation(pathreqlist, disjlist):
 
 
 def correct_json_route_list(network, pathreqlist):
-    """ all names in list should be exact name in the network, and there is no ambiguity
+    """all names in list should be exact name in the network, and there is no ambiguity
+
     This function only checks that list is correct, warns user if the name is incorrect and
     suppresses the constraint it it is loose or raises an error if it is strict
     """
@@ -1008,15 +1027,13 @@ def correct_json_route_list(network, pathreqlist):
     transponders = [n.uid for n in network.nodes() if isinstance(n, Transceiver)]
     for pathreq in pathreqlist:
         if pathreq.source not in transponders:
-            msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find transponder' +\
+            msg = f'Request: {pathreq.request_id}: could not find transponder' \
-                f' source : {pathreq.source}.{ansi_escapes.reset}'
+                + f' source : {pathreq.source}.'
-            LOGGER.critical(msg)
             raise ServiceError(msg)
 
         if pathreq.destination not in transponders:
-            msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find transponder' +\
+            msg = f'Request: {pathreq.request_id}: could not find transponder' \
-                f' destination : {pathreq.destination}.{ansi_escapes.reset}'
+                + f' destination : {pathreq.destination}.'
-            LOGGER.critical(msg)
             raise ServiceError(msg)
 
         # silently remove source and dest nodes from the list
@@ -1035,24 +1052,21 @@ def correct_json_route_list(network, pathreqlist):
                     # if no matching can be found in the network just ignore this constraint
                     # if it is a loose constraint
                     # warns the user that this node is not part of the topology
-                    msg = f'{ansi_escapes.yellow}invalid route node specified:\n\t\'{n_id}\',' +\
+                    msg = f'invalid route node specified:\n\t\'{n_id}\',' \
-                        f' could not use it as constraint, skipped!{ansi_escapes.reset}'
+                        + ' could not use it as constraint, skipped!'
-                    print(msg)
+                    LOGGER.warning(msg)
-                    LOGGER.info(msg)
                     pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
                     pathreq.nodes_list.remove(n_id)
                 else:
-                    msg = f'{ansi_escapes.red}could not find node:\n\t \'{n_id}\' in network' +\
+                    msg = f'could not find node:\n\t \'{n_id}\' in network' \
-                        f' topology. Strict constraint can not be applied.{ansi_escapes.reset}'
+                        + ' topology. Strict constraint can not be applied.'
-                    LOGGER.critical(msg)
                     raise ServiceError(msg)
 
     return pathreqlist
 
 
 def deduplicate_disjunctions(disjn):
-    """ clean disjunctions to remove possible repetition
+    """clean disjunctions to remove possible repetition"""
-    """
     local_disjn = disjn.copy()
     for elem in local_disjn:
         for dis_elem in local_disjn:
@@ -1063,7 +1077,8 @@ def deduplicate_disjunctions(disjn):
 
 
 def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
-    """ use a list but a dictionnary might be helpful to find path based on request_id
+    """use a list but a dictionnary might be helpful to find path based on request_id
+
     TODO change all these req, dsjct, res lists into dict !
     """
     path_res_list = []
@@ -1075,10 +1090,10 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
         # use the power specified in requests but might be different from the one
         # specified for design the power is an optional parameter for requests
         # definition if optional, use the one defines in eqt_config.json
-        print(f'request {pathreq.request_id}')
+        msg = f'\n\trequest {pathreq.request_id}\n' \
-        print(f'Computing path from {pathreq.source} to {pathreq.destination}')
+              + f'\tComputing path from {pathreq.source} to {pathreq.destination}\n' \
-        # adding first node to be clearer on the output
+              + f'\twith path constraint: {[pathreq.source] + pathreq.nodes_list}'
-        print(f'with path constraint: {[pathreq.source] + pathreq.nodes_list}')
+        # # adding first node to be clearer on the output
 
         # pathlist[i] contains the whole path information for request i
         # last element is a transciver and where the result of the propagation is
@@ -1088,7 +1103,8 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
         # may use the same transponder for the performance simulation. This is why
         # we use deepcopy: to ensure that each propagation is recorded and not overwritten
         total_path = deepcopy(pathlist[i])
-        print(f'Computed path (roadms):{[e.uid for e in total_path  if isinstance(e, Roadm)]}')
+        msg = msg + f'\n\tComputed path (roadms):{[e.uid for e in total_path  if isinstance(e, Roadm)]}'
+        LOGGER.info(msg)
         # for debug
         # print(f'{pathreq.baud_rate}   {pathreq.power}   {pathreq.spacing}   {pathreq.nb_channel}')
         if total_path:
@@ -1096,13 +1112,15 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
                 # means that at this point the mode was entered/forced by user and thus a
                 # baud_rate was defined
                 propagate(total_path, pathreq, equipment)
-                temp_snr01nm = round(mean(total_path[-1].snr+lin2db(pathreq.baud_rate/(12.5e9))), 2)
+                snr01nm_with_penalty = total_path[-1].snr_01nm - total_path[-1].total_penalty
-                if temp_snr01nm < pathreq.OSNR + equipment['SI']['default'].sys_margins:
+                min_ind = argmin(snr01nm_with_penalty)
-                    msg = f'\tWarning! Request {pathreq.request_id} computed path from' +\
+                if round(snr01nm_with_penalty[min_ind], 2) < pathreq.OSNR + equipment['SI']['default'].sys_margins:
-                          f' {pathreq.source} to {pathreq.destination} does not pass with' +\
+                    msg = f'\tWarning! Request {pathreq.request_id} computed path from' \
-                          f' {pathreq.tsp_mode}\n\tcomputedSNR in 0.1nm = {temp_snr01nm} ' +\
+                          + f' {pathreq.source} to {pathreq.destination} does not pass with {pathreq.tsp_mode}' \
-                          f'- required osnr {pathreq.OSNR} + {equipment["SI"]["default"].sys_margins} margin'
+                          + f'\n\tcomputed SNR in 0.1nm = {round(total_path[-1].snr_01nm[min_ind], 2)}'
-                    print(msg)
+                    msg = _penalty_msg(total_path, msg, min_ind) \
+                        + f'\n\trequired osnr = {pathreq.OSNR}' \
+                        + f'\n\tsystem margin = {equipment["SI"]["default"].sys_margins}'
                     LOGGER.warning(msg)
                     pathreq.blocking_reason = 'MODE_NOT_FEASIBLE'
             else:
@@ -1122,6 +1140,7 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
                         pathreq.OSNR = mode['OSNR']
                         pathreq.tx_osnr = mode['tx_osnr']
                         pathreq.bit_rate = mode['bit_rate']
+                        pathreq.penalties = mode['penalties']
                     # other blocking reason should not appear at this point
                 except AttributeError:
                     pathreq.baud_rate = mode['baud_rate']
@@ -1130,35 +1149,36 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
                     pathreq.OSNR = mode['OSNR']
                     pathreq.tx_osnr = mode['tx_osnr']
                     pathreq.bit_rate = mode['bit_rate']
+                    pathreq.penalties = mode['penalties']
 
             # reversed path is needed for correct spectrum assignment
             reversed_path = find_reversed_path(pathlist[i])
             if pathreq.bidir and pathreq.baud_rate is not None:
                 # Both directions requested, and a feasible mode was found
                 rev_p = deepcopy(reversed_path)
-
+                msg = f'\n\tPropagating Z to A direction {pathreq.destination} to {pathreq.source}\n' \
-                print(f'\n\tPropagating Z to A direction {pathreq.destination} to {pathreq.source}')
+                      + f'\tPath (roadms) {[r.uid for r in rev_p if isinstance(r,Roadm)]}\n'
-                print(f'\tPath (roadsm) {[r.uid for r in rev_p if isinstance(r,Roadm)]}\n')
+                LOGGER.info(msg)
                 propagate(rev_p, pathreq, equipment)
                 propagated_reversed_path = rev_p
-                temp_snr01nm = round(mean(propagated_reversed_path[-1].snr +\
+                snr01nm_with_penalty = rev_p[-1].snr_01nm - rev_p[-1].total_penalty
-                                          lin2db(pathreq.baud_rate/(12.5e9))), 2)
+                min_ind = argmin(snr01nm_with_penalty)
-                if temp_snr01nm < pathreq.OSNR + equipment['SI']['default'].sys_margins:
+                if round(snr01nm_with_penalty[min_ind], 2) < pathreq.OSNR + equipment['SI']['default'].sys_margins:
-                    msg = f'\tWarning! Request {pathreq.request_id} computed path from' +\
+                    msg = f'\tWarning! Request {pathreq.request_id} computed path from' \
-                          f' {pathreq.source} to {pathreq.destination} does not pass with' +\
+                          + f' {pathreq.destination} to {pathreq.source} does not pass with {pathreq.tsp_mode}' \
-                          f' {pathreq.tsp_mode}\n' +\
+                          + f'\n\tcomputed SNR in 0.1nm = {round(rev_p[-1].snr_01nm[min_ind], 2)}'
-                          f'\tcomputedSNR in 0.1nm = {temp_snr01nm} -' \
+                    msg = _penalty_msg(rev_p, msg, min_ind) \
-                          f' required osnr {pathreq.OSNR} + {equipment["SI"]["default"].sys_margins} margin'
+                        + f'\n\trequired osnr = {pathreq.OSNR}' \
-                    print(msg)
+                        + f'\n\tsystem margin = {equipment["SI"]["default"].sys_margins}'
                     LOGGER.warning(msg)
                     # TODO selection of mode should also be on reversed direction !!
+                    if not hasattr(pathreq, 'blocking_reason'):
                         pathreq.blocking_reason = 'MODE_NOT_FEASIBLE'
             else:
                 propagated_reversed_path = []
         else:
-            msg = 'Total path is empty. No propagation'
+            msg = f'Request {pathreq.request_id}: Total path is empty. No propagation'
-            print(msg)
+            LOGGER.warning(msg)
-            LOGGER.info(msg)
             reversed_path = []
             propagated_reversed_path = []
 
@@ -1166,5 +1186,33 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
         reversed_path_res_list.append(reversed_path)
         propagated_reversed_path_res_list.append(propagated_reversed_path)
         # print to have a nice output
-        print('')
     return path_res_list, reversed_path_res_list, propagated_reversed_path_res_list
+
+
+def compute_spectrum_slot_vs_bandwidth(bandwidth, spacing, bit_rate, slot_width=0.0125e12):
+    """Compute the number of required wavelengths and the M value (number of consumed slots)
+
+    Each wavelength consumes one `spacing`, and the result is rounded up to consume a natural number of slots.
+
+    >>> compute_spectrum_slot_vs_bandwidth(400e9, 50e9, 200e9)
+    (2, 8)
+    """
+    number_of_wavelengths = ceil(bandwidth / bit_rate)
+    total_number_of_slots = ceil(spacing / slot_width) * number_of_wavelengths
+    return number_of_wavelengths, total_number_of_slots
+
+
+def _penalty_msg(total_path, msg, min_ind):
+    """formatting helper for reporting unfeasible paths
+
+    The penalty info are optional, so this checks that penalty exists before creating a message."""
+    penalty_dict = {
+        'pdl': 'PDL',
+        'chromatic_dispersion': 'CD',
+        'pmd': 'PMD'}
+    for key, pretty in penalty_dict.items():
+        if key in total_path[-1].penalties:
+            msg += f'\n\t{pretty} penalty = {round(total_path[-1].penalties[key][min_ind], 2)}'
+        else:
+            msg += f'\n\t{pretty} penalty not evaluated'
+    return msg

gnpy/topology/spectrum_assignment.py

@@ -15,16 +15,16 @@ element/oms correspondace
 
 from collections import namedtuple
 from logging import getLogger
-from math import ceil
 from gnpy.core.elements import Roadm, Transceiver
 from gnpy.core.exceptions import ServiceError, SpectrumError
+from gnpy.core.utils import order_slots, restore_order
+from gnpy.topology.request import compute_spectrum_slot_vs_bandwidth
 
 LOGGER = getLogger(__name__)
 
 
 class Bitmap:
-    """ records the spectrum occupation
+    """records the spectrum occupation"""
-    """
 
     def __init__(self, f_min, f_max, grid, guardband=0.15e12, bitmap=None):
         # n is the min index including guardband. Guardband is require to be sure
@@ -45,26 +45,22 @@ class Bitmap:
             raise SpectrumError(f'bitmap is not consistant with f_min{f_min} - n: {n_min} and f_max{f_max}- n :{n_max}')
 
     def getn(self, i):
-        """ converts the n (itu grid) into a local index
+        """converts the n (itu grid) into a local index"""
-        """
         return self.freq_index[i]
 
     def geti(self, nvalue):
-        """ converts the local index into n (itu grid)
+        """converts the local index into n (itu grid)"""
-        """
         return self.freq_index.index(nvalue)
 
     def insert_left(self, newbitmap):
-        """ insert bitmap on the left to align oms bitmaps if their start frequencies are different
+        """insert bitmap on the left to align oms bitmaps if their start frequencies are different"""
-        """
         self.bitmap = newbitmap + self.bitmap
         temp = list(range(self.n_min - len(newbitmap), self.n_min))
         self.freq_index = temp + self.freq_index
         self.n_min = self.freq_index[0]
 
     def insert_right(self, newbitmap):
-        """ insert bitmap on the right to align oms bitmaps if their stop frequencies are different
+        """insert bitmap on the right to align oms bitmaps if their stop frequencies are different"""
-        """
         self.bitmap = self.bitmap + newbitmap
         self.freq_index = self.freq_index + list(range(self.n_max, self.n_max + len(newbitmap)))
         self.n_max = self.freq_index[-1]
@@ -75,7 +71,7 @@ OMSParams = namedtuple('OMSParams', 'oms_id el_id_list el_list')
 
 
 class OMS:
-    """ OMS class is the logical container that represent a link between two adjacent ROADMs and
+    """OMS class is the logical container that represent a link between two adjacent ROADMs and
     records the crossed elements and the occupied spectrum
     """
 
@@ -98,36 +94,28 @@ class OMS:
                             f'{self.el_id_list[0]} - {self.el_id_list[-1]}', '\n'])
 
     def add_element(self, elem):
-        """ records oms elements
+        """records oms elements"""
-        """
         self.el_id_list.append(elem.uid)
         self.el_list.append(elem)
 
-    def update_spectrum(self, f_min, f_max, guardband=0.15e12, existing_spectrum=None,
+    def update_spectrum(self, f_min, f_max, guardband=0.15e12, existing_spectrum=None, grid=0.00625e12):
-                        grid=0.00625e12):
+        """Frequencies expressed in Hz.
-        """ frequencies expressed in Hz
+        Add 150 GHz margin to enable a center channel on f_min
+        Use ITU-T G694.1 Flexible DWDM grid definition
+        For the flexible DWDM grid, the allowed frequency slots have a nominal central frequency (in THz) defined by:
+        193.1 + n × 0.00625 where n is a positive or negative integer including 0
+        and 0.00625 is the nominal central frequency granularity in THz
+        and a slot width defined by:
+        12.5 × m where m is a positive integer and 12.5 is the slot width granularity in GHz.
+        Any combination of frequency slots is allowed as long as no two frequency slots overlap.
+        If bitmap is not None, then use it: Bitmap checks its consistency with f_min f_max
+        else a brand new bitmap is created
         """
-        if existing_spectrum is None:
+        self.spectrum_bitmap = Bitmap(f_min=f_min, f_max=f_max, grid=grid, guardband=guardband,
-            # add some 150 GHz margin to enable a center channel on f_min
+                                      bitmap=existing_spectrum)
-            # use ITU-T G694.1
-            # Flexible DWDM grid definition
-            # For the flexible DWDM grid, the allowed frequency slots have a nominal
-            # central frequency (in THz) defined by:
-            # 193.1 + n × 0.00625 where n is a positive or negative integer including 0
-            # and 0.00625 is the nominal central frequency granularity in THz
-            # and a slot width defined by:
-            # 12.5 × m where m is a positive integer and 12.5 is the slot width granularity in
-            # GHz.
-            # Any combination of frequency slots is allowed as long as no two frequency
-            # slots overlap.
-
-            # TODO : add explaination on that / parametrize ....
-            self.spectrum_bitmap = Bitmap(f_min, f_max, grid, guardband)
-            # print(len(self.spectrum_bitmap.bitmap))
 
     def assign_spectrum(self, nvalue, mvalue):
-        """ change oms spectrum to mark spectrum assigned
+        """change oms spectrum to mark spectrum assigned"""
-        """
         if not isinstance(nvalue, int):
             raise SpectrumError(f'N must be a signed integer, got {nvalue}')
         if not isinstance(mvalue, int):
@@ -146,14 +134,14 @@ class OMS:
         self.spectrum_bitmap.bitmap[self.spectrum_bitmap.geti(startn):self.spectrum_bitmap.geti(stopn) + 1] = [0] * (stopn - startn + 1)
 
     def add_service(self, service_id, nb_wl):
-        """ record service and mark spectrum as occupied
+        """record service and mark spectrum as occupied"""
-        """
         self.service_list.append(service_id)
         self.nb_channels += nb_wl
 
 
 def frequency_to_n(freq, grid=0.00625e12):
-    """ converts frequency into the n value (ITU grid)
+    """converts frequency into the n value (ITU grid)
+
     reference to Recommendation G.694.1 (02/12), Figure I.3
     https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
 
@@ -167,7 +155,8 @@ def frequency_to_n(freq, grid=0.00625e12):
 
 
 def nvalue_to_frequency(nvalue, grid=0.00625e12):
-    """ converts n value into a frequency
+    """converts n value into a frequency
+
     reference to Recommendation G.694.1 (02/12), Table 1
     https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
 
@@ -181,15 +170,15 @@ def nvalue_to_frequency(nvalue, grid=0.00625e12):
 
 
 def mvalue_to_slots(nvalue, mvalue):
-    """ convert center n an m into start and stop n
+    """convert center n an m into start and stop n"""
-    """
     startn = nvalue - mvalue
     stopn = nvalue + mvalue - 1
     return startn, stopn
 
 
 def slots_to_m(startn, stopn):
-    """ converts the start and stop n values to the center n and m value
+    """converts the start and stop n values to the center n and m value
+
     reference to Recommendation G.694.1 (02/12), Figure I.3
     https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
 
@@ -206,7 +195,8 @@ def slots_to_m(startn, stopn):
 
 
 def m_to_freq(nvalue, mvalue, grid=0.00625e12):
-    """ converts m into frequency range
+    """converts m into frequency range
+
     spectrum(13,7) is (193137500000000.0, 193225000000000.0)
     reference to Recommendation G.694.1 (02/12), Figure I.3
     https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
@@ -225,9 +215,7 @@ def m_to_freq(nvalue, mvalue, grid=0.00625e12):
 
 
 def align_grids(oms_list):
-    """ used to apply same grid to all oms : same starting n, stop n and slot size
+    """Used to apply same grid to all oms : same starting n, stop n and slot size. Out of grid slots are set to 0."""
-        out of grid slots are set to 0
-    """
     n_min = min([o.spectrum_bitmap.n_min for o in oms_list])
     n_max = max([o.spectrum_bitmap.n_max for o in oms_list])
     for this_o in oms_list:
@@ -239,7 +227,8 @@ def align_grids(oms_list):
 
 
 def build_oms_list(network, equipment):
-    """ initialization of OMS list in the network
+    """initialization of OMS list in the network
+
     an oms is build reading all intermediate nodes between two adjacent ROADMs
     each element within the list is being added an oms and oms_id to record the
     oms it belongs to.
@@ -296,7 +285,8 @@ def build_oms_list(network, equipment):
 
 
 def reversed_oms(oms_list):
-    """ identifies reversed OMS
+    """identifies reversed OMS
+
     only applicable for non parallel OMS
     """
     for oms in oms_list:
@@ -322,28 +312,41 @@ def bitmap_sum(band1, band2):
     return res
 
 
-def spectrum_selection(pth, oms_list, requested_m, requested_n=None):
+def build_path_oms_id_list(pth):
-    """Collects spectrum availability and call the select_candidate function"""
-
-    # use indexes instead of ITU-T n values
     path_oms = []
     for elem in pth:
         if not isinstance(elem, Roadm) and not isinstance(elem, Transceiver):
             # only edfa, fused and fibers have oms_id attribute
             path_oms.append(elem.oms_id)
     # remove duplicate oms_id, order is not important
-    path_oms = list(set(path_oms))
+    return list(set(path_oms))
-    # assuming all oms have same freq index
-    if not path_oms:
-        candidate = (None, None, None)
-        return candidate, path_oms
-    freq_index = oms_list[path_oms[0]].spectrum_bitmap.freq_index
-    freq_index_min = oms_list[path_oms[0]].spectrum_bitmap.freq_index_min
-    freq_index_max = oms_list[path_oms[0]].spectrum_bitmap.freq_index_max
 
-    freq_availability = oms_list[path_oms[0]].spectrum_bitmap.bitmap
+
+def aggregate_oms_bitmap(path_oms, oms_list):
+    spectrum = oms_list[path_oms[0]].spectrum_bitmap
+    bitmap = spectrum.bitmap
+    # assuming all oms have same freq indices
     for oms in path_oms[1:]:
-        freq_availability = bitmap_sum(oms_list[oms].spectrum_bitmap.bitmap, freq_availability)
+        bitmap = bitmap_sum(oms_list[oms].spectrum_bitmap.bitmap, bitmap)
+    params = {
+        'oms_id': 0,
+        'el_id_list': 0,
+        'el_list': []
+    }
+    freq_min = nvalue_to_frequency(spectrum.freq_index_min)
+    freq_max = nvalue_to_frequency(spectrum.freq_index_max)
+    aggregate_oms = OMS(**params)
+    aggregate_oms.update_spectrum(freq_min, freq_max, grid=0.00625e12, existing_spectrum=bitmap)
+    return aggregate_oms
+
+
+def spectrum_selection(test_oms, requested_m, requested_n=None):
+    """Collects spectrum availability and call the select_candidate function"""
+    freq_index = test_oms.spectrum_bitmap.freq_index
+    freq_index_min = test_oms.spectrum_bitmap.freq_index_min
+    freq_index_max = test_oms.spectrum_bitmap.freq_index_max
+    freq_availability = test_oms.spectrum_bitmap.bitmap
+
     if requested_n is None:
         # avoid slots reserved on the edge 0.15e-12 on both sides -> 24
         candidates = [(freq_index[i] + requested_m, freq_index[i], freq_index[i] + 2 * requested_m - 1)
@@ -354,29 +357,36 @@ def spectrum_selection(pth, oms_list, requested_m, requested_n=None):
 
         candidate = select_candidate(candidates, policy='first_fit')
     else:
-        i = oms_list[path_oms[0]].spectrum_bitmap.geti(requested_n)
+        i = test_oms.spectrum_bitmap.geti(requested_n)
-        # print(f'N {requested_n} i {i}')
+        if (freq_availability[i - requested_m:i + requested_m] == [1] * (2 * requested_m)
-        # print(freq_availability[i-m:i+m] )
+                and freq_index[i - requested_m] >= freq_index_min
-        # print(freq_index[i-m:i+m])
-        if (freq_availability[i - requested_m:i + requested_m] == [1] * (2 * requested_m) and
-                freq_index[i - requested_m] >= freq_index_min
                 and freq_index[i + requested_m - 1] <= freq_index_max):
             # candidate is the triplet center_n, startn and stopn
             candidate = (requested_n, requested_n - requested_m, requested_n + requested_m - 1)
         else:
             candidate = (None, None, None)
-        # print("coucou11")
+    return candidate
-        # print(candidate)
+
-    # print(freq_availability[321:321+2*m])
+
-    # a = [i+321 for i in range(2*m)]
+def determine_slot_numbers(test_oms, requested_n, required_m, per_channel_m):
-    # print(a)
+    """determines max availability around requested_n. requested_n should not be None"""
-    # print(candidate)
+    bitmap = test_oms.spectrum_bitmap
-    return candidate, path_oms
+    freq_index = bitmap.freq_index
+    freq_index_min = bitmap.freq_index_min
+    freq_index_max = bitmap.freq_index_max
+    freq_availability = bitmap.bitmap
+    center_i = bitmap.geti(requested_n)
+    i = per_channel_m
+    while (freq_availability[center_i - i:center_i + i] == [1] * (2 * i)
+           and freq_index[center_i - i] >= freq_index_min
+           and freq_index[center_i + i - 1] <= freq_index_max
+           and i <= required_m):
+        i += per_channel_m
+    return i - per_channel_m
 
 
 def select_candidate(candidates, policy):
-    """ selects a candidate among all available spectrum
+    """selects a candidate among all available spectrum"""
-    """
     if policy == 'first_fit':
         if candidates:
             return candidates[0]
@@ -386,46 +396,112 @@ def select_candidate(candidates, policy):
         raise ServiceError('Only first_fit spectrum assignment policy is implemented.')
 
 
+def compute_n_m(required_m, rq, path_oms, oms_list, per_channel_m, policy='first_fit'):
+    """ based on requested path_bandwidth fill in M=None values with uint values, using per_channel_m
+    and center frequency, with first fit strategy. The function checks the available spectrum but check
+    consistencies among M values of the request, but not with other requests.
+    For example, if request is for 32 slots corresponding to 8 x 4 slots of 32Gbauds channels,
+    the following frequency slots will result in the following assignment
+
+    N = 0, 8,    16, 32           -> 0,   8,   16,   32
+    M = 8, None, 8,  None         -> 8,   8,    8,    8
+
+    N = 0,    8,    16, 32        -> 0,   , 16
+    M = None, None, 8,  None      -> 24,  , 8
+    """
+    selected_m = []
+    selected_n = []
+    remaining_slots_to_serve = required_m
+    # order slots for the computation: assign biggest m first
+    rq_N, rq_M, order = order_slots([{'N': n, 'M': m} for n, m in zip(rq.N, rq.M)])
+    # Create an oms that represents current assignments of all oms listed in path_oms, and test N and M on it.
+    # If M is defined, checks that proposed N, M is free
+    test_oms = aggregate_oms_bitmap(path_oms, oms_list)
+    for n, m in zip(rq_N, rq_M):
+        if m is not None and n is not None:
+            # check availabilityfor this n, m
+            available_slots = determine_slot_numbers(test_oms, n, m, m)
+            if available_slots == 0:
+                # if n, m are not feasible, break at this point no have non zero remaining_slots_to_serve
+                # in order to blocks the request (even is other N,M where feasible)
+                break
+        elif m is not None and n is None:
+            # find a candidate n
+            n, _, _ = spectrum_selection(test_oms, m, None)
+            if n is None:
+                # if no n is feasible for the m, block the request
+                break
+        elif m is None and n is not None:
+            # find a feasible m for this n. If None is found, then block the request
+            m = determine_slot_numbers(test_oms, n, remaining_slots_to_serve, per_channel_m)
+            if m == 0 or remaining_slots_to_serve == 0:
+                break
+        else:
+            # if n and m are not defined, try to find a single  assignment to fits the remaining slots to serve
+            # (first fit strategy)
+            n, _, _ = spectrum_selection(test_oms, remaining_slots_to_serve, None)
+            if n is None or remaining_slots_to_serve == 0:
+                break
+            else:
+                m = remaining_slots_to_serve
+        selected_m.append(m)
+        selected_n.append(n)
+        test_oms.assign_spectrum(n, m)
+        remaining_slots_to_serve = remaining_slots_to_serve - m
+
+    # re-order selected_m and selected_n according to initial request N, M order, ignoring None values
+    not_selected = [None for i in range(len(rq_N) - len(selected_n))]
+    selected_m = restore_order(selected_m + not_selected, order)
+    selected_n = restore_order(selected_n + not_selected, order)
+    return selected_n, selected_m, remaining_slots_to_serve
+
+
 def pth_assign_spectrum(pths, rqs, oms_list, rpths):
-    """ basic first fit assignment
+    """basic first fit assignment
+
     if reversed path are provided, means that occupation is bidir
     """
-    for i, pth in enumerate(pths):
+    for pth, rq, rpth in zip(pths, rqs, rpths):
-        # computes the number of channels required
+        if hasattr(rq, 'blocking_reason'):
-        try:
+            rq.N = None
-            if rqs[i].blocking_reason:
+            rq.M = None
-                rqs[i].blocked = True
-                rqs[i].N = 0
-                rqs[i].M = 0
-        except AttributeError:
-            nb_wl = ceil(rqs[i].path_bandwidth / rqs[i].bit_rate)
-            # computes the total nb of slots according to requested spacing
-            # TODO : express superchannels
-            # assumes that all channels must be grouped
-            # TODO : enables non contiguous reservation in case of blocking
-            requested_m = ceil(rqs[i].spacing / 0.0125e12) * nb_wl
-            # concatenate all path and reversed path elements to derive slots availability
-            (center_n, startn, stopn), path_oms = spectrum_selection(pth + rpths[i], oms_list, requested_m,
-                                                                     requested_n=None)
-            # checks that requested_m is fitting startm and stopm
-            # if not None, center_n and start, stop frequencies are applicable to all oms of pth
-            # checks that spectrum is not None else indicate blocking reason
-            if center_n is not None:
-                # checks that requested_m is fitting startm and stopm
-                if 2 * requested_m > (stopn - startn + 1):
-                    msg = f'candidate: {(center_n, startn, stopn)} is not consistant ' +\
-                        f'with {requested_m}'
-                    LOGGER.critical(msg)
-                    raise ValueError(msg)
-
-                for oms_elem in path_oms:
-                    oms_list[oms_elem].assign_spectrum(center_n, requested_m)
-                    oms_list[oms_elem].add_service(rqs[i].request_id, nb_wl)
-                rqs[i].blocked = False
-                rqs[i].N = center_n
-                rqs[i].M = requested_m
         else:
-                rqs[i].blocked = True
+            # computes the number of channels required for path_bandwidth and the min required nb of slots
-                rqs[i].N = 0
+            # for one channel (corresponds to the spacing)
-                rqs[i].M = 0
+            nb_wl, required_m = compute_spectrum_slot_vs_bandwidth(rq.path_bandwidth,
-                rqs[i].blocking_reason = 'NO_SPECTRUM'
+                                                                   rq.spacing, rq.bit_rate)
+            _, per_channel_m = compute_spectrum_slot_vs_bandwidth(rq.bit_rate,
+                                                                  rq.spacing, rq.bit_rate)
+            # find oms ids that are concerned both by pth and rpth
+            path_oms = build_path_oms_id_list(pth + rpth)
+            if getattr(rq, 'M', None) is not None and all(rq.M):
+                # if all M are well defined: Consistency check that the requested M are enough to carry the nb_wl:
+                # check that the integer number of per_channel_m carried in each M value is enough to carry nb_wl.
+                # if not, blocks the demand
+                nb_channels_of_request = sum([m // per_channel_m for m in rq.M])
+                # TODO: elaborate a more accurate estimate with nb_wl * min_spacing + possibly guardbands in case of
+                # superchannel closed packing.
+                if nb_wl > nb_channels_of_request:
+                    rq.N = None
+                    rq.M = None
+                    rq.blocking_reason = 'NOT_ENOUGH_RESERVED_SPECTRUM'
+                    # need to stop here for this request and not go though spectrum selection process
+                    continue
+            # Use the req.M even if nb_wl and required_m are smaller.
+            # first fit strategy: assign as many lambda as possible in the None remaining N, M values
+            selected_n, selected_m, remaining_slots_to_serve = \
+                compute_n_m(required_m, rq, path_oms, oms_list, per_channel_m)
+            # if there are some remaining_slots_to_serve, this means that provided rq.M and rq.N values were
+            # not possible. Then do not go though spectrum assignment process and blocks the demand
+            if remaining_slots_to_serve > 0:
+                rq.N = None
+                rq.M = None
+                rq.blocking_reason = 'NO_SPECTRUM'
+                continue
+            for oms_elem in path_oms:
+                for this_n, this_m in zip(selected_n, selected_m):
+                    if this_m is not None:
+                        oms_list[oms_elem].assign_spectrum(this_n, this_m)
+                oms_list[oms_elem].add_service(rq.request_id, nb_wl)
+            rq.N = selected_n
+            rq.M = selected_m

requirements.txt

@@ -1,7 +1,11 @@
-matplotlib>=3.3.3,<4
+# matplotlib 3.8 removed support for Python 3.8
-networkx>=2.5,<3
+matplotlib>=3.7.3,<4
-numpy>=1.19.4,<2
+# networkx 3.2 removed support for Python 3.8
-pandas>=1.1.5,<2
+networkx>=3.1,<4
-pbr>=5.5.1,<6
+# numpy 1.25 removed support for Python 3.8
-scipy>=1.5.4,<2
+numpy>=1.24.4,<2
+pbr>=6.0.0,<7
+# scipy 1.11 removed support for Python 3.8
+scipy>=1.10.1,<2
+# xlrd 2.x removed support for .xlsx, it's only .xls now
 xlrd>=1.2.0,<2

setup.cfg

@@ -3,13 +3,13 @@ name = gnpy
 description-file = README.md
 description-content-type = text/markdown; variant=GFM
 author = Telecom Infra Project
-author-email = jan.kundrat@telecominfraproject.com
+author-email = jkt@jankundrat.com
 license = BSD-3-Clause
 home-page = https://github.com/Telecominfraproject/oopt-gnpy
 project_urls =
     Bug Tracker = https://github.com/Telecominfraproject/oopt-gnpy/issues
     Documentation = https://gnpy.readthedocs.io/
-python-requires = >=3.6
+python-requires = >=3.8
 classifier =
     Development Status :: 5 - Production/Stable
     Intended Audience :: Developers
@@ -19,10 +19,11 @@ classifier =
     Natural Language :: English
     Programming Language :: Python
     Programming Language :: Python :: 3 :: Only
-    Programming Language :: Python :: 3.6
-    Programming Language :: Python :: 3.7
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
+    Programming Language :: Python :: 3.10
+    Programming Language :: Python :: 3.11
+    Programming Language :: Python :: 3.12
     Programming Language :: Python :: Implementation :: CPython
     Topic :: Scientific/Engineering
     Topic :: Scientific/Engineering :: Physics
@@ -41,9 +42,6 @@ warnerrors = True
 
 [files]
 packages = gnpy
-data_files =
-	examples = examples/*
-# FIXME: solve example data files
 
 [options.entry_points]
 console_scripts =

tests/compare.py

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

tests/conftest.py

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

tests/data/CORONET_services.json

@@ -0,0 +1,21 @@
+{
+  "path-request": [
+    {
+      "request-id": "0",
+      "source": "trx Abilene",
+      "destination": "trx Albany",
+      "src-tp-id": "trx Abilene",
+      "dst-tp-id": "trx Albany",
+      "bidirectional": false,
+      "path-constraints": {
+        "te-bandwidth": {
+          "technology": "flexi-grid",
+          "trx_type": "Voyager",
+          "trx_mode": "mode 3",
+          "spacing": 62500000000.0,
+          "path_bandwidth": 100000000000.0
+        }
+      }
+    }
+  ]
+}

tests/data/default_edfa_config.json

@@ -196,101 +196,101 @@
         0.0
     ],
     "dgt": [
-        2.714526681131686,
+        1.0,
-        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,
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 }

tests/data/eqpt_config.json

@@ -63,7 +63,7 @@
       "Fiber":[{
             "type_variety": "SSMF",
             "dispersion": 1.67e-05,
-            "gamma": 0.00127,
+            "effective_area": 83e-12,
             "pmd_coef": 1.265e-15
             }
       ],
@@ -85,6 +85,7 @@
             "target_pch_out_db": -20,
             "add_drop_osnr": 38,
             "pmd": 0,
+            "pdl": 0,
             "restrictions": {
                             "preamp_variety_list":[],
                             "booster_variety_list":[]

tests/data/raman_fiber_config.json

@@ -1,224 +0,0 @@
-{
-  "uid": "Span1",
-  "params": {
-    "length": 80,
-    "loss_coef": 0.2,
-    "length_units": "km",
-    "att_in": 0,
-    "con_in": 0.5,
-    "con_out": 0.5,
-    "type_variety": "SSMF",
-    "dispersion": 0.0000167,
-    "gamma": 0.00127,
-    "pmd_coef": 1.265e-15,
-    "raman_efficiency": {
-      "cr": [
-        0,
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-        0.0000292,
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-      "frequency_offset": [
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-        2500000000000,
-        3000000000000,
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-    }
-  },
-  "operational": {
-    "temperature": 283,
-    "raman_pumps": [
-      {
-        "power": 0.2,
-        "frequency": 205000000000000,
-        "propagation_direction": "counterprop"
-      },
-      {
-        "power": 0.206,
-        "frequency": 201000000000000,
-        "propagation_direction": "counterprop"
-      }
-    ]
-  },
-  "metadata": {
-    "location": {
-      "latitude": 1,
-      "longitude": 0,
-      "city": null,
-      "region": ""
-    }
-  }
-}

tests/data/sim_params.json

@@ -1,12 +1,11 @@
 {
-  "raman_parameters": {
+  "raman_params": {
-    "flag_raman": true,
+    "flag": true,
-    "space_resolution": 10e3,
+    "result_spatial_resolution": 10e3,
-    "tolerance": 1e-8
+    "solver_spatial_resolution": 50
   },
-  "nli_parameters": {
+  "nli_params": {
-    "nli_method_name": "ggn_spectrally_separated",
+    "method": "ggn_spectrally_separated",
-    "wdm_grid_size": 50e9,
     "dispersion_tolerance": 1,
     "phase_shift_tolerance": 0.1,
     "computed_channels": [1, 18, 37, 56, 75]

tests/data/testService_services_expected.json

@@ -14,8 +14,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -39,8 +39,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -64,8 +64,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,

tests/data/testTopology_response.json

@@ -42,10 +42,12 @@
           {
             "path-route-object": {
               "index": 1,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -69,10 +71,12 @@
           {
             "path-route-object": {
               "index": 4,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -87,10 +91,12 @@
           {
             "path-route-object": {
               "index": 6,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -105,10 +111,12 @@
           {
             "path-route-object": {
               "index": 8,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -123,10 +131,12 @@
           {
             "path-route-object": {
               "index": 10,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -141,10 +151,12 @@
           {
             "path-route-object": {
               "index": 12,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -159,10 +171,12 @@
           {
             "path-route-object": {
               "index": 14,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -219,10 +233,12 @@
           {
             "path-route-object": {
               "index": 1,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -246,10 +262,12 @@
           {
             "path-route-object": {
               "index": 4,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -264,10 +282,12 @@
           {
             "path-route-object": {
               "index": 6,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -282,10 +302,12 @@
           {
             "path-route-object": {
               "index": 8,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -300,10 +322,12 @@
           {
             "path-route-object": {
               "index": 10,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -318,10 +342,12 @@
           {
             "path-route-object": {
               "index": 12,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -336,10 +362,12 @@
           {
             "path-route-object": {
               "index": 14,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -354,10 +382,12 @@
           {
             "path-route-object": {
               "index": 16,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -372,10 +402,12 @@
           {
             "path-route-object": {
               "index": 18,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -390,10 +422,12 @@
           {
             "path-route-object": {
               "index": 20,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -408,10 +442,12 @@
           {
             "path-route-object": {
               "index": 22,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -426,10 +462,12 @@
           {
             "path-route-object": {
               "index": 24,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -444,10 +482,12 @@
           {
             "path-route-object": {
               "index": 26,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -462,10 +502,12 @@
           {
             "path-route-object": {
               "index": 28,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -480,10 +522,12 @@
           {
             "path-route-object": {
               "index": 30,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -498,10 +542,12 @@
           {
             "path-route-object": {
               "index": 32,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -516,10 +562,12 @@
           {
             "path-route-object": {
               "index": 34,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -534,10 +582,12 @@
           {
             "path-route-object": {
               "index": 36,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -552,10 +602,12 @@
           {
             "path-route-object": {
               "index": 38,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -570,10 +622,12 @@
           {
             "path-route-object": {
               "index": 40,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -588,10 +642,12 @@
           {
             "path-route-object": {
               "index": 42,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -276,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -648,10 +704,12 @@
           {
             "path-route-object": {
               "index": 1,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -675,10 +733,12 @@
           {
             "path-route-object": {
               "index": 4,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -693,10 +753,12 @@
           {
             "path-route-object": {
               "index": 6,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -711,10 +773,12 @@
           {
             "path-route-object": {
               "index": 8,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -729,10 +793,12 @@
           {
             "path-route-object": {
               "index": 10,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -747,10 +813,12 @@
           {
             "path-route-object": {
               "index": 12,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -765,10 +833,12 @@
           {
             "path-route-object": {
               "index": 14,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -783,10 +853,12 @@
           {
             "path-route-object": {
               "index": 16,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -801,10 +873,12 @@
           {
             "path-route-object": {
               "index": 18,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -284,
                   "M": 4
                 }
+              ]
             }
           },
           {
@@ -829,7 +903,7 @@
           },
           {
             "metric-type": "SNR-0.1nm",
-            "accumulative-value": 22.15
+            "accumulative-value": 22.14
           },
           {
             "metric-type": "OSNR-bandwidth",
@@ -861,10 +935,12 @@
           {
             "path-route-object": {
               "index": 1,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -888,10 +964,12 @@
           {
             "path-route-object": {
               "index": 4,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -906,10 +984,12 @@
           {
             "path-route-object": {
               "index": 6,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -924,10 +1004,12 @@
           {
             "path-route-object": {
               "index": 8,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -942,10 +1024,12 @@
           {
             "path-route-object": {
               "index": 10,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -960,10 +1044,12 @@
           {
             "path-route-object": {
               "index": 12,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -978,10 +1064,12 @@
           {
             "path-route-object": {
               "index": 14,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -996,10 +1084,12 @@
           {
             "path-route-object": {
               "index": 16,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1014,10 +1104,12 @@
           {
             "path-route-object": {
               "index": 18,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1032,10 +1124,12 @@
           {
             "path-route-object": {
               "index": 20,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1050,10 +1144,12 @@
           {
             "path-route-object": {
               "index": 22,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1068,10 +1164,12 @@
           {
             "path-route-object": {
               "index": 24,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1086,10 +1184,12 @@
           {
             "path-route-object": {
               "index": 26,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1104,10 +1204,12 @@
           {
             "path-route-object": {
               "index": 28,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1122,10 +1224,12 @@
           {
             "path-route-object": {
               "index": 30,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1140,10 +1244,12 @@
           {
             "path-route-object": {
               "index": 32,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1158,10 +1264,12 @@
           {
             "path-route-object": {
               "index": 34,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1176,10 +1284,12 @@
           {
             "path-route-object": {
               "index": 36,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1194,10 +1304,12 @@
           {
             "path-route-object": {
               "index": 38,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1212,10 +1324,12 @@
           {
             "path-route-object": {
               "index": 40,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1230,10 +1344,12 @@
           {
             "path-route-object": {
               "index": 42,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -266,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1254,11 +1370,11 @@
         "path-metric": [
           {
             "metric-type": "SNR-bandwidth",
-            "accumulative-value": 21.68
+            "accumulative-value": 21.67
           },
           {
             "metric-type": "SNR-0.1nm",
-            "accumulative-value": 28.77
+            "accumulative-value": 28.76
           },
           {
             "metric-type": "OSNR-bandwidth",
@@ -1290,10 +1406,12 @@
           {
             "path-route-object": {
               "index": 1,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1317,10 +1435,12 @@
           {
             "path-route-object": {
               "index": 4,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1335,10 +1455,12 @@
           {
             "path-route-object": {
               "index": 6,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1353,10 +1475,12 @@
           {
             "path-route-object": {
               "index": 8,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1371,10 +1495,12 @@
           {
             "path-route-object": {
               "index": 10,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1389,10 +1515,12 @@
           {
             "path-route-object": {
               "index": 12,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1407,10 +1535,12 @@
           {
             "path-route-object": {
               "index": 14,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1425,10 +1555,12 @@
           {
             "path-route-object": {
               "index": 16,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {
@@ -1443,10 +1575,12 @@
           {
             "path-route-object": {
               "index": 18,
-              "label-hop": {
+              "label-hop": [
+                {
                   "N": -274,
                   "M": 6
                 }
+              ]
             }
           },
           {

tests/data/testTopology_response_expected.csv

@@ -1,7 +1,7 @@
 response-id,source,destination,path_bandwidth,Pass?,nb of tsp pairs,total cost,transponder-type,transponder-mode,OSNR-0.1nm,SNR-0.1nm,SNR-bandwidth,baud rate (Gbaud),input power (dBm),path,"spectrum (N,M)",reversed path OSNR-0.1nm,reversed path SNR-0.1nm,reversed path SNR-bandwidth
-0,trx Lorient_KMA,trx Vannes_KBE,100.0,True,1,1,Voyager,mode 1,30.84,30.84,26.75,32.0,0.0,trx Lorient_KMA | roadm Lorient_KMA | east edfa in Lorient_KMA to Vannes_KBE | fiber (Lorient_KMA → Vannes_KBE)-F055 | west edfa in Vannes_KBE to Lorient_KMA | roadm Vannes_KBE | trx Vannes_KBE,"-284, 4",,,
+0,trx Lorient_KMA,trx Vannes_KBE,100.0,True,1,1,Voyager,mode 1,30.84,30.84,26.75,32.0,0.0,trx Lorient_KMA | roadm Lorient_KMA | east edfa in Lorient_KMA to Vannes_KBE | fiber (Lorient_KMA → Vannes_KBE)-F055 | west edfa in Vannes_KBE to Lorient_KMA | roadm Vannes_KBE | trx Vannes_KBE,"[-284], [4]",,,
-1,trx Brest_KLA,trx Vannes_KBE,10.0,True,1,1,Voyager,mode 1,22.65,22.11,18.03,32.0,1.0,trx Brest_KLA | roadm Brest_KLA | east edfa in Brest_KLA to Morlaix | fiber (Brest_KLA → Morlaix)-F060 | east fused spans in Morlaix | fiber (Morlaix → Lannion_CAS)-F059 | west edfa in Lannion_CAS to Morlaix | roadm Lannion_CAS | east edfa in Lannion_CAS to Corlay | fiber (Lannion_CAS → Corlay)-F061 | west fused spans in Corlay | fiber (Corlay → Loudeac)-F010 | west fused spans in Loudeac | fiber (Loudeac → Lorient_KMA)-F054 | west edfa in Lorient_KMA to Loudeac | roadm Lorient_KMA | east edfa in Lorient_KMA to Vannes_KBE | fiber (Lorient_KMA → Vannes_KBE)-F055 | west edfa in Vannes_KBE to Lorient_KMA | roadm Vannes_KBE | trx Vannes_KBE,"-276, 4",,,
+1,trx Brest_KLA,trx Vannes_KBE,10.0,True,1,1,Voyager,mode 1,22.65,22.11,18.03,32.0,1.0,trx Brest_KLA | roadm Brest_KLA | east edfa in Brest_KLA to Morlaix | fiber (Brest_KLA → Morlaix)-F060 | east fused spans in Morlaix | fiber (Morlaix → Lannion_CAS)-F059 | west edfa in Lannion_CAS to Morlaix | roadm Lannion_CAS | east edfa in Lannion_CAS to Corlay | fiber (Lannion_CAS → Corlay)-F061 | west fused spans in Corlay | fiber (Corlay → Loudeac)-F010 | west fused spans in Loudeac | fiber (Loudeac → Lorient_KMA)-F054 | west edfa in Lorient_KMA to Loudeac | roadm Lorient_KMA | east edfa in Lorient_KMA to Vannes_KBE | fiber (Lorient_KMA → Vannes_KBE)-F055 | west edfa in Vannes_KBE to Lorient_KMA | roadm Vannes_KBE | trx Vannes_KBE,"[-276], [4]",,,
-3,trx Lannion_CAS,trx Rennes_STA,60.0,True,1,1,vendorA_trx-type1,mode 1,28.29,25.85,21.77,32.0,1.0,trx Lannion_CAS | roadm Lannion_CAS | east edfa in Lannion_CAS to Stbrieuc | fiber (Lannion_CAS → Stbrieuc)-F056 | east edfa in Stbrieuc to Rennes_STA | fiber (Stbrieuc → Rennes_STA)-F057 | west edfa in Rennes_STA to Stbrieuc | roadm Rennes_STA | trx Rennes_STA,"-284, 4",,,
+3,trx Lannion_CAS,trx Rennes_STA,60.0,True,1,1,vendorA_trx-type1,mode 1,28.29,25.85,21.77,32.0,1.0,trx Lannion_CAS | roadm Lannion_CAS | east edfa in Lannion_CAS to Stbrieuc | fiber (Lannion_CAS → Stbrieuc)-F056 | east edfa in Stbrieuc to Rennes_STA | fiber (Stbrieuc → Rennes_STA)-F057 | west edfa in Rennes_STA to Stbrieuc | roadm Rennes_STA | trx Rennes_STA,"[-284], [4]",,,
-4,trx Rennes_STA,trx Lannion_CAS,150.0,True,1,1,vendorA_trx-type1,mode 2,22.27,22.15,15.05,64.0,0.0,trx Rennes_STA | roadm Rennes_STA | east edfa in Rennes_STA to Ploermel | fiber (Rennes_STA → Ploermel)- | east edfa in Ploermel to Vannes_KBE | fiber (Ploermel → Vannes_KBE)- | west edfa in Vannes_KBE to Ploermel | roadm Vannes_KBE | east edfa in Vannes_KBE to Lorient_KMA | fiber (Vannes_KBE → Lorient_KMA)-F055 | west edfa in Lorient_KMA to Vannes_KBE | roadm Lorient_KMA | east edfa in Lorient_KMA to Loudeac | fiber (Lorient_KMA → Loudeac)-F054 | east fused spans in Loudeac | fiber (Loudeac → Corlay)-F010 | east fused spans in Corlay | fiber (Corlay → Lannion_CAS)-F061 | west edfa in Lannion_CAS to Corlay | roadm Lannion_CAS | trx Lannion_CAS,"-266, 6",,,
+4,trx Rennes_STA,trx Lannion_CAS,150.0,True,1,1,vendorA_trx-type1,mode 2,22.27,22.14,15.05,64.0,0.0,trx Rennes_STA | roadm Rennes_STA | east edfa in Rennes_STA to Ploermel | fiber (Rennes_STA → Ploermel)- | east edfa in Ploermel to Vannes_KBE | fiber (Ploermel → Vannes_KBE)- | west edfa in Vannes_KBE to Ploermel | roadm Vannes_KBE | east edfa in Vannes_KBE to Lorient_KMA | fiber (Vannes_KBE → Lorient_KMA)-F055 | west edfa in Lorient_KMA to Vannes_KBE | roadm Lorient_KMA | east edfa in Lorient_KMA to Loudeac | fiber (Lorient_KMA → Loudeac)-F054 | east fused spans in Loudeac | fiber (Loudeac → Corlay)-F010 | east fused spans in Corlay | fiber (Corlay → Lannion_CAS)-F061 | west edfa in Lannion_CAS to Corlay | roadm Lannion_CAS | trx Lannion_CAS,"[-266], [6]",,,
-5,trx Rennes_STA,trx Lannion_CAS,20.0,True,1,1,vendorA_trx-type1,mode 2,30.79,28.77,21.68,64.0,3.0,trx Rennes_STA | roadm Rennes_STA | east edfa in Rennes_STA to Stbrieuc | fiber (Rennes_STA → Stbrieuc)-F057 | west edfa in Stbrieuc to Rennes_STA | fiber (Stbrieuc → Lannion_CAS)-F056 | west edfa in Lannion_CAS to Stbrieuc | roadm Lannion_CAS | trx Lannion_CAS,"-274, 6",,,
+5,trx Rennes_STA,trx Lannion_CAS,20.0,True,1,1,vendorA_trx-type1,mode 2,30.79,28.76,21.67,64.0,3.0,trx Rennes_STA | roadm Rennes_STA | east edfa in Rennes_STA to Stbrieuc | fiber (Rennes_STA → Stbrieuc)-F057 | west edfa in Stbrieuc to Rennes_STA | fiber (Stbrieuc → Lannion_CAS)-F056 | west edfa in Lannion_CAS to Stbrieuc | roadm Lannion_CAS | trx Lannion_CAS,"[-274], [6]",,,
 6,,,,NO_PATH,,,,,,,,,,,,,,

tests/data/testTopology_services_expected.json

@@ -14,8 +14,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -39,8 +39,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -104,8 +104,8 @@
           "trx_mode": "mode 1",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 50000000000.0,
@@ -129,8 +129,8 @@
           "trx_mode": "mode 2",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 75000000000.0,
@@ -154,8 +154,8 @@
           "trx_mode": "mode 2",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 75000000000.0,
@@ -179,8 +179,8 @@
           "trx_mode": "mode 2",
           "effective-freq-slot": [
             {
-              "N": "null",
+              "N": null,
-              "M": "null"
+              "M": null
             }
           ],
           "spacing": 75000000000.0,

tests/data/testTopology_testservices.json

@@ -12,12 +12,6 @@
           "technology": "flexi-grid",
           "trx_type": "Voyager_16QAM",
           "trx_mode": "16QAM",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": 80,
           "output-power": 0.001,
@@ -37,12 +31,6 @@
           "technology": "flexi-grid",
           "trx_type": "vendorA_trx-type1",
           "trx_mode": "PS_SP64_1",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": 80,
           "output-power": 0.001,
@@ -62,12 +50,6 @@
           "technology": "flexi-grid",
           "trx_type": "vendorA_trx-type1",
           "trx_mode": "PS_SP64_1",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": 80,
           "output-power": 0.001,
@@ -87,12 +69,6 @@
           "technology": "flexi-grid",
           "trx_type": "vendorA_trx-type1",
           "trx_mode": "PS_SP64_1",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": 80,
           "output-power": 0.001,
@@ -133,12 +109,6 @@
           "technology": "flexi-grid",
           "trx_type": "Voyager",
           "trx_mode": "mode 2 - fake",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 75000000000.0,
           "max-nb-of-channel": 63,
           "output-power": 0.001,
@@ -158,12 +128,6 @@
           "technology": "flexi-grid",
           "trx_type": "Voyager",
           "trx_mode": "mode 2",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 75000000000.0,
           "max-nb-of-channel": 63,
           "output-power": 0.001,
@@ -183,12 +147,6 @@
           "technology": "flexi-grid",
           "trx_type": "vendorA_trx-type1",
           "trx_mode": "PS_SP64_1",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": 80,
           "output-power": 0.001,
@@ -221,12 +179,6 @@
           "technology": "flexi-grid",
           "trx_type": "Voyager",
           "trx_mode": "mode 3",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 62500000000.0,
           "max-nb-of-channel": 76,
           "output-power": 0.001,
@@ -259,12 +211,6 @@
           "technology": "flexi-grid",
           "trx_type": "vendorA_trx-type1",
           "trx_mode": "PS_SP64_1",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": 80,
           "output-power": 0.001,
@@ -284,12 +230,6 @@
           "technology": "flexi-grid",
           "trx_type": "vendorA_trx-type1",
           "trx_mode": "PS_SP64_1",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": 80,
           "output-power": 0.001,
@@ -330,12 +270,6 @@
           "technology": "flexi-grid",
           "trx_type": "Voyager_16QAM",
           "trx_mode": "16QAM",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": 80,
           "output-power": null,
@@ -355,12 +289,6 @@
           "technology": "flexi-grid",
           "trx_type": "Voyager",
           "trx_mode": "mode 1",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": null,
           "output-power": 0.001,
@@ -380,12 +308,6 @@
           "technology": "flexi-grid",
           "trx_type": "vendorA_trx-type1",
           "trx_mode": "PS_SP64_1",
-          "effective-freq-slot": [
-            {
-              "n": "null",
-              "m": "null"
-            }
-          ],
           "spacing": 50000000000.0,
           "max-nb-of-channel": null,
           "output-power": null,
@@ -405,12 +327,6 @@
           "technology": "flexi-grid",
           "trx_type": "vendorA_trx-type1",
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@@ -526,12 +424,6 @@
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@@ -551,12 +443,6 @@
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tests/data/test_fiber_fix_expected_results.csv

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tests/data/test_fiber_flex_expected_results.csv

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tests/data/test_long_network.json

@@ -0,0 +1,809 @@
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+            "uid": "Span13",
+            "type": "Fiber",
+            "type_variety": "SSMF",
+            "params": {
+                "length": 80,
+                "loss_coef": 0.2,
+                "length_units": "km"
+                },
+            "metadata": {
+                "location": {
+                    "region": "",
+                    "latitude": 1,
+                    "longitude": 0
+                }
+            }
+        },
+        {
+            "uid": "Edfa13",
+            "type": "Edfa",
+            "type_variety": "test",
+            "operational": {
+                "gain_target": 16,
+                "tilt_target": 0
+            },
+            "metadata": {
+                "location": {
+                    "region": "",
+                    "latitude": 2,
+                    "longitude": 0
+                }
+            }
+        },
+        {
+            "uid": "Span14",
+            "type": "Fiber",
+            "type_variety": "SSMF",
+            "params": {
+                "length": 80,
+                "loss_coef": 0.2,
+                "length_units": "km"
+                },
+            "metadata": {
+                "location": {
+                    "region": "",
+                    "latitude": 1,
+                    "longitude": 0
+                }
+            }
+        },
+        {
+            "uid": "Edfa14",
+            "type": "Edfa",
+            "type_variety": "test_fixed_gain",
+            "operational": {
+                "gain_target": 16,
+                "tilt_target": 0
+            },
+            "metadata": {
+                "location": {
+                    "region": "",
+                    "latitude": 2,
+                    "longitude": 0
+                }
+            }
+        },
+        {
+            "uid": "Span15",
+            "type": "Fiber",
+            "type_variety": "SSMF",
+            "params": {
+                "length": 80,
+                "loss_coef": 0.2,
+                "length_units": "km"
+                },
+            "metadata": {
+                "location": {
+                    "region": "",
+                    "latitude": 1,
+                    "longitude": 0
+                }
+            }
+        },
+        {
+            "uid": "Edfa15",
+            "type": "Edfa",
+            "type_variety": "test",
+            "operational": {
+                "gain_target": 16,
+                "tilt_target": 0
+            },
+            "metadata": {
+                "location": {
+                    "region": "",
+                    "latitude": 2,
+                    "longitude": 0
+                }
+            }
+        },
+        {
+          "uid": "roadm Site B",
+          "metadata": {
+            "location": {
+              "city": "Site B",
+              "region": "RLD",
+              "latitude": 0.0,
+              "longitude": 0.0
+            }
+          },
+          "type": "Roadm"
+        },
+        {
+            "uid": "Site_B",
+            "type": "Transceiver",
+            "metadata": {
+                "location": {
+                    "city": "Site B",
+                    "region": "",
+                    "latitude": 3,
+                    "longitude": 0
+                }
+            }
+        }
+
+    ],
+    "connections": [{
+            "from_node": "Site_A",
+            "to_node": "roadm Site A"
+        },
+        {
+            "from_node": "roadm Site A",
+            "to_node": "booster A"
+        },
+        {
+            "from_node": "booster A",
+            "to_node": "Span1"
+        },
+        {
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+            "to_node": "Edfa1"
+        },
+        {
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+            "to_node": "Span2"
+        },
+        {
+            "from_node": "Span2",
+            "to_node": "Edfa2"
+        },       
+        {
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+            "to_node": "Span3"
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+        {
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+            "to_node": "Edfa3"
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+            "to_node": "Span4"
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+        {
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+            "to_node": "Edfa4"
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+            "to_node": "Span5"
+        },
+        {
+            "from_node": "Span5",
+            "to_node": "Edfa5"
+        },       
+        {
+            "from_node": "Edfa5",
+            "to_node": "roadm Site C"
+        },
+        {
+            "from_node": "roadm Site C",
+            "to_node": "booster C"
+        },
+        {
+            "from_node": "booster C",
+            "to_node": "Span6"
+        },
+        {
+            "from_node": "Span6",
+            "to_node": "Edfa6"
+        },
+        {
+            "from_node": "Edfa6",
+            "to_node": "Span7"
+        },
+        {
+            "from_node": "Span7",
+            "to_node": "Edfa7"
+        },       
+        {
+            "from_node": "Edfa7",
+            "to_node": "Span8"
+        },
+        {
+            "from_node": "Span8",
+            "to_node": "Edfa8"
+        },       
+        {
+            "from_node": "Edfa8",
+            "to_node": "Span9"
+        },
+        {
+            "from_node": "Span9",
+            "to_node": "Edfa9"
+        },       
+        {
+            "from_node": "Edfa9",
+            "to_node": "Span10"
+        },
+        {
+            "from_node": "Span10",
+            "to_node": "Edfa10"
+        },       
+        {
+            "from_node": "Edfa10",
+            "to_node": "roadm Site D"
+        },
+        {
+            "from_node": "roadm Site D",
+            "to_node": "booster D"
+        },
+        {
+            "from_node": "booster D",
+            "to_node": "Span11"
+        },
+        {
+            "from_node": "Span11",
+            "to_node": "Edfa11"
+        },
+        {
+            "from_node": "Edfa11",
+            "to_node": "Span12"
+        },
+        {
+            "from_node": "Span12",
+            "to_node": "Edfa12"
+        },       
+        {
+            "from_node": "Edfa12",
+            "to_node": "roadm Site E"
+        },
+        {
+            "from_node": "roadm Site E",
+            "to_node": "booster E"
+        },
+        {
+            "from_node": "booster E",
+            "to_node": "Span13"
+        },
+        {
+            "from_node": "Span13",
+            "to_node": "Edfa13"
+        },       
+        {
+            "from_node": "Edfa13",
+            "to_node": "Span14"
+        },
+        {
+            "from_node": "Span14",
+            "to_node": "Edfa14"
+        },       
+        {
+            "from_node": "Edfa14",
+            "to_node": "Span15"
+        },
+        {
+            "from_node": "Span15",
+            "to_node": "Edfa15"
+        },       
+        {
+            "from_node": "Edfa15",
+            "to_node": "roadm Site B"
+        },
+        {
+            "from_node": "roadm Site B",
+            "to_node": "Site_B"
+        }
+    ]
+}

tests/data/test_lumped_losses_fiber_no_pumps.csv

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tests/data/test_lumped_losses_raman_fiber_config.json

@@ -0,0 +1,36 @@
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+}

tests/data/test_old_parameters_fiber_config.json

@@ -0,0 +1,224 @@
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+}

tests/data/test_parameters_fiber_config.json

@@ -0,0 +1,225 @@
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tests/data/test_science_utils_fiber_config.json

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+    "type_variety": "SSMF",
+    "dispersion": 0.0000167,
+    "effective_area": 83e-12,
+    "pmd_coef": 1.265e-15
+  },
+  "operational": {
+        "temperature": 283,
+        "raman_pumps": [
+          {
+            "power": 224.403e-3,
+            "frequency": 205e12,
+            "propagation_direction": "counterprop"
+          },
+          {
+            "power": 231.135e-3,
+            "frequency": 201e12,
+            "propagation_direction": "counterprop"
+          }
+        ]
+      },
+  "metadata": {
+    "location": {
+      "latitude": 1,
+      "longitude": 0,
+      "city": null,
+      "region": ""
+    }
+  }
+}

tests/invocation/logs_path_request

@@ -0,0 +1,37 @@
+INFO     gnpy.tools.cli_examples:cli_examples.py Computing path requests meshTopologyExampleV2.xls into JSON format
+INFO     gnpy.tools.json_io:json_io.py Automatically converting requests from XLS to JSON
+INFO     gnpy.topology.request:request.py 
+	request 0
+	Computing path from trx Lorient_KMA to trx Vannes_KBE
+	with path constraint: ['trx Lorient_KMA', 'trx Vannes_KBE']
+	Computed path (roadms):['roadm Lorient_KMA', 'roadm Vannes_KBE']
+INFO     gnpy.topology.request:request.py 
+	request 1
+	Computing path from trx Brest_KLA to trx Vannes_KBE
+	with path constraint: ['trx Brest_KLA', 'roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE', 'trx Vannes_KBE']
+	Computed path (roadms):['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE']
+INFO     gnpy.topology.request:request.py 
+	request 3
+	Computing path from trx Lannion_CAS to trx Rennes_STA
+	with path constraint: ['trx Lannion_CAS', 'trx Rennes_STA']
+	Computed path (roadms):['roadm Lannion_CAS', 'roadm Rennes_STA']
+INFO     gnpy.topology.request:request.py 
+	request 4
+	Computing path from trx Rennes_STA to trx Lannion_CAS
+	with path constraint: ['trx Rennes_STA', 'trx Lannion_CAS']
+	Computed path (roadms):['roadm Rennes_STA', 'roadm Vannes_KBE', 'roadm Lorient_KMA', 'roadm Lannion_CAS']
+INFO     gnpy.topology.request:request.py 
+	request 5
+	Computing path from trx Rennes_STA to trx Lannion_CAS
+	with path constraint: ['trx Rennes_STA', 'trx Lannion_CAS']
+	Computed path (roadms):['roadm Rennes_STA', 'roadm Lannion_CAS']
+INFO     gnpy.topology.request:request.py 
+	request 7 | 6
+	Computing path from trx Lannion_CAS to trx Lorient_KMA
+	with path constraint: ['trx Lannion_CAS', 'trx Lorient_KMA']
+	Computed path (roadms):['roadm Lannion_CAS', 'roadm Lorient_KMA']
+INFO     gnpy.topology.request:request.py 
+	request 7b
+	Computing path from trx Lannion_CAS to trx Lorient_KMA
+	with path constraint: ['trx Lannion_CAS', 'trx Lorient_KMA']
+	Computed path (roadms):['roadm Lannion_CAS', 'roadm Lorient_KMA']

tests/invocation/logs_path_requests_run_CD_PMD_PDL_missing

@@ -0,0 +1,13 @@
+INFO     gnpy.tools.cli_examples:cli_examples.py Computing path requests CORONET_services.json into JSON format
+INFO     gnpy.topology.request:request.py 
+	request 0
+	Computing path from trx Abilene to trx Albany
+	with path constraint: ['trx Abilene', 'trx Albany']
+	Computed path (roadms):['roadm Abilene', 'roadm Dallas', 'roadm Little_Rock', 'roadm Memphis', 'roadm Nashville', 'roadm Louisville', 'roadm Cincinnati', 'roadm Columbus', 'roadm Cleveland', 'roadm Buffalo', 'roadm Rochester', 'roadm Syracuse', 'roadm Albany']
+WARNING  gnpy.topology.request:request.py 	Warning! Request 0 computed path from trx Abilene to trx Albany does not pass with mode 3
+	computed SNR in 0.1nm = 14.44
+	PDL penalty not evaluated
+	CD penalty not evaluated
+	PMD penalty not evaluated
+	required osnr = 18
+	system margin = 2

tests/invocation/logs_transmission_saturated

@@ -0,0 +1,307 @@
+INFO     gnpy.tools.cli_examples:cli_examples.py source = 'lannion'
+INFO     gnpy.tools.cli_examples:cli_examples.py destination = 'lorient'
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Lorient_KMA to Loudeac
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: effective gain in Node east edfa in Lannion_CAS to Stbrieuc
+	is above user specified amplifier std_low_gain
+	max flat gain: 16dB ; required gain: 23.0dB. Please check amplifier type.
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Rennes_STA to Stbrieuc
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: effective gain in Node east edfa in Lannion_CAS to Morlaix
+	is above user specified amplifier std_low_gain
+	max flat gain: 16dB ; required gain: 23.5dB. Please check amplifier type.
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Brest_KLA to Morlaix
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Lorient_KMA to Loudeac
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: effective gain in Node west edfa in Lannion_CAS to Corlay
+	is above user specified amplifier test
+	max flat gain: 25dB ; required gain: 29.82dB. Please check amplifier type.
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Lorient_KMA to Vannes_KBE
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Vannes_KBE to Lorient_KMA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Lorient_KMA to Quimper
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Quimper to Lorient_KMA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Brest_KLA to Quimper
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Vannes_KBE to Lorient_KMA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Lorient_KMA to Vannes_KBE
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Vannes_KBE to Ploermel
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Ploermel to Vannes_KBE
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Rennes_STA to Ploermel
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Rennes_STA to Stbrieuc
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Stbrieuc to Rennes_STA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Lannion_CAS to Stbrieuc
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Rennes_STA to Ploermel
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Vannes_KBE to Ploermel
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Brest_KLA to Morlaix
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: effective gain in Node east edfa in Brest_KLA to Quimper
+	is above user specified amplifier std_low_gain
+	max flat gain: 16dB ; required gain: 23.0dB. Please check amplifier type.
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in Quimper to Lorient_KMA
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in Lorient_KMA to Quimper
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in a to b
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in b to a
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in a to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in c to a
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in b to a
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in a to b
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in b to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in f to b
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in c to a
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in a to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in d to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in c to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in f to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in d to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in c to d
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in d to e
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in e to d
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in e to d
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in d to e
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in e to g
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in g to e
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in f to c
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in c to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in f to b
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in b to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in f to h
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in h to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in g to e
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in e to g
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in g to h
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in h to g
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in h to f
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in f to h
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node east edfa in h to g
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+
+WARNING  gnpy.core.network:network.py 
+	WARNING: target gain and power in node west edfa in g to h
+	is beyond all available amplifiers capabilities and/or extended_gain_range:
+	a power reduction of -1.82 is applied
+

tests/invocation/openroadm-v4-Stockholm-Gothenburg

@@ -14,9 +14,12 @@ Transceiver trx_Stockholm
   OSNR ASE (signal bw, dB):  30.98
   CD (ps/nm):                0.00
   PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
 Roadm roadm_Stockholm
   effective loss (dB):     22.00
-  pch out (dBm):        -20.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
@@ -29,6 +32,7 @@ Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Stockholm → Norrköping)_(1/2)
   type_variety:                SSMF
@@ -37,7 +41,8 @@ Fiber          fiber (Stockholm → Norrköping)_(1/2)
   total loss (dB):             16.33
   (includes conn loss (dB) in: 0.00 out: 0.00)
   (conn loss out includes EOL margin defined in eqpt_config.json)
-  pch out (dBm): -14.33
+  reference pch out (dBm):     -14.33
+  actual pch out (dBm):        -14.31
 Edfa Edfa_fiber (Stockholm → Norrköping)_(1/2)
   type_variety:           openroadm_ila_low_noise
   effective gain(dB):     16.33
@@ -50,6 +55,7 @@ Edfa Edfa_fiber (Stockholm → Norrköping)_(1/2)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.02
   output VOA (dB):        0.00
 Fiber          fiber (Stockholm → Norrköping)_(2/2)
   type_variety:                SSMF
@@ -58,7 +64,8 @@ Fiber          fiber (Stockholm → Norrköping)_(2/2)
   total loss (dB):             16.33
   (includes conn loss (dB) in: 0.00 out: 0.00)
   (conn loss out includes EOL margin defined in eqpt_config.json)
-  pch out (dBm): -14.33
+  reference pch out (dBm):     -14.33
+  actual pch out (dBm):        -14.29
 Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     16.33
@@ -71,10 +78,12 @@ Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.04
   output VOA (dB):        0.00
 Roadm roadm_Norrköping
   effective loss (dB):     22.00
-  pch out (dBm):        -20.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
@@ -87,6 +96,7 @@ Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Norrköping → Linköping)
   type_variety:                SSMF
@@ -95,7 +105,8 @@ Fiber          fiber (Norrköping → Linköping)
   total loss (dB):             11.00
   (includes conn loss (dB) in: 0.00 out: 0.00)
   (conn loss out includes EOL margin defined in eqpt_config.json)
-  pch out (dBm): -9.00
+  reference pch out (dBm):     -9.00
+  actual pch out (dBm):        -9.00
 Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     11.00
@@ -108,10 +119,12 @@ Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.01
   output VOA (dB):        0.00
 Roadm roadm_Linköping
   effective loss (dB):     22.00
-  pch out (dBm):        -20.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
@@ -124,6 +137,7 @@ Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Linköping → Jönköping)
   type_variety:                SSMF
@@ -132,7 +146,8 @@ Fiber          fiber (Linköping → Jönköping)
   total loss (dB):             26.80
   (includes conn loss (dB) in: 0.00 out: 0.00)
   (conn loss out includes EOL margin defined in eqpt_config.json)
-  pch out (dBm): -24.80
+  reference pch out (dBm):     -24.80
+  actual pch out (dBm):        -24.79
 Edfa Edfa_preamp_roadm_Jönköping_from_fiber (Linköping → Jönköping)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     26.80
@@ -145,10 +160,12 @@ Edfa Edfa_preamp_roadm_Jönköping_from_fiber (Linköping → Jönköping)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.04
   output VOA (dB):        0.00
 Roadm roadm_Jönköping
   effective loss (dB):     22.00
-  pch out (dBm):        -20.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
@@ -161,6 +178,7 @@ Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Jönköping → Borås)
   type_variety:                SSMF
@@ -169,7 +187,8 @@ Fiber          fiber (Jönköping → Borås)
   total loss (dB):             17.82
   (includes conn loss (dB) in: 0.00 out: 0.00)
   (conn loss out includes EOL margin defined in eqpt_config.json)
-  pch out (dBm): -15.82
+  reference pch out (dBm):     -15.82
+  actual pch out (dBm):        -15.81
 Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     17.82
@@ -182,10 +201,12 @@ Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.02
   output VOA (dB):        0.00
 Roadm roadm_Borås
   effective loss (dB):     22.00
-  pch out (dBm):        -20.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
 Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
   type_variety:           openroadm_mw_mw_booster
   effective gain(dB):     22.00
@@ -198,6 +219,7 @@ Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
   output VOA (dB):        0.00
 Fiber          fiber (Borås → Gothenburg)
   type_variety:                SSMF
@@ -206,7 +228,8 @@ Fiber          fiber (Borås → Gothenburg)
   total loss (dB):             13.53
   (includes conn loss (dB) in: 0.00 out: 0.00)
   (conn loss out includes EOL margin defined in eqpt_config.json)
-  pch out (dBm): -11.53
+  reference pch out (dBm):     -11.53
+  actual pch out (dBm):        -11.52
 Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
   type_variety:           openroadm_mw_mw_preamp
   effective gain(dB):     13.53
@@ -219,20 +242,24 @@ Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
   Delta_P (dB):           0.00
   target pch (dBm):       2.00
   effective pch (dBm):    2.00
+  actual pch out (dBm):   2.02
   output VOA (dB):        0.00
 Roadm roadm_Gothenburg
   effective loss (dB):     22.00
-  pch out (dBm):        -20.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
 Transceiver trx_Gothenburg
-  GSNR (0.1nm, dB):          18.90
+  GSNR (0.1nm, dB):          18.89
-  GSNR (signal bw, dB):      14.88
+  GSNR (signal bw, dB):      14.86
   OSNR ASE (0.1nm, dB):      21.20
   OSNR ASE (signal bw, dB):  17.18
   CD (ps/nm):                8350.42
-  PMD (ps):                  0.89
+  PMD (ps):                  7.99
+  PDL (dB):                  3.74
+  Latency (ms):              2.45
 
 Transmission result for input power = 2.00 dBm:
-  Final GSNR (0.1 nm): 18.90 dB
+  Final GSNR (0.1 nm): 18.89 dB
 
 (No source node specified: picked trx_Stockholm)
 

tests/invocation/openroadm-v5-Stockholm-Gothenburg

@@ -0,0 +1,266 @@
+There are 96 channels propagating
+Power mode is set to True
+=> it can be modified in eqpt_config.json - Span
+
+There are 6 fiber spans over 500 km between trx_Stockholm and trx_Gothenburg
+
+Now propagating between trx_Stockholm and trx_Gothenburg:
+
+Propagating with input power = 2.00 dBm:
+Transceiver trx_Stockholm
+  GSNR (0.1nm, dB):          35.00
+  GSNR (signal bw, dB):      30.98
+  OSNR ASE (0.1nm, dB):      35.00
+  OSNR ASE (signal bw, dB):  30.98
+  CD (ps/nm):                0.00
+  PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
+Roadm roadm_Stockholm
+  effective loss (dB):     22.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
+Edfa Edfa_booster_roadm_Stockholm_to_fiber (Stockholm → Norrköping)_(1/2)
+  type_variety:           openroadm_mw_mw_booster
+  effective gain(dB):     22.00
+  (before att_in and before output VOA)
+  noise figure (dB):      -inf
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.18
+  Power Out (dBm):        21.82
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
+  output VOA (dB):        0.00
+Fiber          fiber (Stockholm → Norrköping)_(1/2)
+  type_variety:                SSMF
+  length (km):                 81.63
+  pad att_in (dB):             0.00
+  total loss (dB):             16.33
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -14.33
+  actual pch out (dBm):        -14.31
+Edfa Edfa_fiber (Stockholm → Norrköping)_(1/2)
+  type_variety:           openroadm_ila_low_noise
+  effective gain(dB):     16.33
+  (before att_in and before output VOA)
+  noise figure (dB):      8.01
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         5.51
+  Power Out (dBm):        21.84
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.02
+  output VOA (dB):        0.00
+Fiber          fiber (Stockholm → Norrköping)_(2/2)
+  type_variety:                SSMF
+  length (km):                 81.63
+  pad att_in (dB):             0.00
+  total loss (dB):             16.33
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -14.33
+  actual pch out (dBm):        -14.29
+Edfa Edfa_preamp_roadm_Norrköping_from_fiber (Stockholm → Norrköping)_(2/2)
+  type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
+  effective gain(dB):     16.33
+  (before att_in and before output VOA)
+  noise figure (dB):      11.44
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         5.53
+  Power Out (dBm):        21.86
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.04
+  output VOA (dB):        0.00
+Roadm roadm_Norrköping
+  effective loss (dB):     22.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
+Edfa Edfa_booster_roadm_Norrköping_to_fiber (Norrköping → Linköping)
+  type_variety:           openroadm_mw_mw_booster
+  effective gain(dB):     22.00
+  (before att_in and before output VOA)
+  noise figure (dB):      -inf
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.18
+  Power Out (dBm):        21.82
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
+  output VOA (dB):        0.00
+Fiber          fiber (Norrköping → Linköping)
+  type_variety:                SSMF
+  length (km):                 45.99
+  pad att_in (dB):             1.80
+  total loss (dB):             11.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -9.00
+  actual pch out (dBm):        -9.00
+Edfa Edfa_preamp_roadm_Linköping_from_fiber (Norrköping → Linköping)
+  type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
+  effective gain(dB):     11.00
+  (before att_in and before output VOA)
+  noise figure (dB):      16.00
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         10.83
+  Power Out (dBm):        21.83
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.01
+  output VOA (dB):        0.00
+Roadm roadm_Linköping
+  effective loss (dB):     22.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
+Edfa Edfa_booster_roadm_Linköping_to_fiber (Linköping → Jönköping)
+  type_variety:           openroadm_mw_mw_booster
+  effective gain(dB):     22.00
+  (before att_in and before output VOA)
+  noise figure (dB):      -inf
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.18
+  Power Out (dBm):        21.82
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
+  output VOA (dB):        0.00
+Fiber          fiber (Linköping → Jönköping)
+  type_variety:                SSMF
+  length (km):                 134.02
+  pad att_in (dB):             0.00
+  total loss (dB):             26.80
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -24.80
+  actual pch out (dBm):        -24.79
+Edfa Edfa_preamp_roadm_Jönköping_from_fiber (Linköping → Jönköping)
+  type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
+  effective gain(dB):     26.80
+  (before att_in and before output VOA)
+  noise figure (dB):      8.01
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -4.97
+  Power Out (dBm):        21.86
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.04
+  output VOA (dB):        0.00
+Roadm roadm_Jönköping
+  effective loss (dB):     22.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
+Edfa Edfa_booster_roadm_Jönköping_to_fiber (Jönköping → Borås)
+  type_variety:           openroadm_mw_mw_booster
+  effective gain(dB):     22.00
+  (before att_in and before output VOA)
+  noise figure (dB):      -inf
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.18
+  Power Out (dBm):        21.82
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
+  output VOA (dB):        0.00
+Fiber          fiber (Jönköping → Borås)
+  type_variety:                SSMF
+  length (km):                 89.12
+  pad att_in (dB):             0.00
+  total loss (dB):             17.82
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -15.82
+  actual pch out (dBm):        -15.81
+Edfa Edfa_preamp_roadm_Borås_from_fiber (Jönköping → Borås)
+  type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
+  effective gain(dB):     17.82
+  (before att_in and before output VOA)
+  noise figure (dB):      10.54
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         4.01
+  Power Out (dBm):        21.84
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.01
+  output VOA (dB):        0.00
+Roadm roadm_Borås
+  effective loss (dB):     22.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
+Edfa Edfa_booster_roadm_Borås_to_fiber (Borås → Gothenburg)
+  type_variety:           openroadm_mw_mw_booster
+  effective gain(dB):     22.00
+  (before att_in and before output VOA)
+  noise figure (dB):      -inf
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -0.18
+  Power Out (dBm):        21.82
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.00
+  output VOA (dB):        0.00
+Fiber          fiber (Borås → Gothenburg)
+  type_variety:                SSMF
+  length (km):                 67.64
+  pad att_in (dB):             0.00
+  total loss (dB):             13.53
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -11.53
+  actual pch out (dBm):        -11.52
+Edfa Edfa_preamp_roadm_Gothenburg_from_fiber (Borås → Gothenburg)
+  type_variety:           openroadm_mw_mw_preamp_worstcase_ver5
+  effective gain(dB):     13.53
+  (before att_in and before output VOA)
+  noise figure (dB):      13.54
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         8.30
+  Power Out (dBm):        21.84
+  Delta_P (dB):           0.00
+  target pch (dBm):       2.00
+  effective pch (dBm):    2.00
+  actual pch out (dBm):   2.02
+  output VOA (dB):        0.00
+Roadm roadm_Gothenburg
+  effective loss (dB):     22.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
+Transceiver trx_Gothenburg
+  GSNR (0.1nm, dB):          19.25
+  GSNR (signal bw, dB):      15.23
+  OSNR ASE (0.1nm, dB):      21.84
+  OSNR ASE (signal bw, dB):  17.82
+  CD (ps/nm):                8350.42
+  PMD (ps):                  7.99
+  PDL (dB):                  3.74
+  Latency (ms):              2.45
+
+Transmission result for input power = 2.00 dBm:
+  Final GSNR (0.1 nm): 19.25 dB
+
+(No source node specified: picked trx_Stockholm)
+
+(No destination node specified: picked trx_Gothenburg)

tests/invocation/path_requests_run

@@ -1,4 +1,3 @@
-Computing path requests gnpy/example-data/meshTopologyExampleV2.xls into JSON format
 List of disjunctions
 [Disjunction 3
 	relaxable:    false
@@ -107,48 +106,13 @@
 ]
 Computing all paths with constraints
 Propagating on selected path
-request 0
-Computing path from trx Lorient_KMA to trx Vannes_KBE
-with path constraint: ['trx Lorient_KMA', 'trx Vannes_KBE']
-Computed path (roadms):['roadm Lorient_KMA', 'roadm Vannes_KBE']
-
-request 1
-Computing path from trx Brest_KLA to trx Vannes_KBE
-with path constraint: ['trx Brest_KLA', 'roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE', 'trx Vannes_KBE']
-Computed path (roadms):['roadm Brest_KLA', 'roadm Lannion_CAS', 'roadm Lorient_KMA', 'roadm Vannes_KBE']
-
-request 3
-Computing path from trx Lannion_CAS to trx Rennes_STA
-with path constraint: ['trx Lannion_CAS', 'trx Rennes_STA']
-Computed path (roadms):['roadm Lannion_CAS', 'roadm Rennes_STA']
-
-request 4
-Computing path from trx Rennes_STA to trx Lannion_CAS
-with path constraint: ['trx Rennes_STA', 'trx Lannion_CAS']
-Computed path (roadms):['roadm Rennes_STA', 'roadm Vannes_KBE', 'roadm Lorient_KMA', 'roadm Lannion_CAS']
-
-request 5
-Computing path from trx Rennes_STA to trx Lannion_CAS
-with path constraint: ['trx Rennes_STA', 'trx Lannion_CAS']
-Computed path (roadms):['roadm Rennes_STA', 'roadm Lannion_CAS']
-
-request 7 | 6
-Computing path from trx Lannion_CAS to trx Lorient_KMA
-with path constraint: ['trx Lannion_CAS', 'trx Lorient_KMA']
-Computed path (roadms):['roadm Lannion_CAS', 'roadm Lorient_KMA']
-
-request 7b
-Computing path from trx Lannion_CAS to trx Lorient_KMA
-with path constraint: ['trx Lannion_CAS', 'trx Lorient_KMA']
-Computed path (roadms):['roadm Lannion_CAS', 'roadm Lorient_KMA']
-
 Result summary
 req id   demand                                GSNR@bandwidth A-Z (Z-A)   GSNR@0.1nm A-Z (Z-A)        Receiver minOSNR               mode                    Gbit/s              nb of tsp pairs      N,M or blocking reason 
-0       trx Lorient_KMA to trx Vannes_KBE :             24.83                    28.92                      14                     mode 1                   100.0                      1                     (-284,4)        
+0       trx Lorient_KMA to trx Vannes_KBE :             24.83                    28.92                      14                     mode 1                   100.0                      1                   ([-284],[4])      
-1       trx Brest_KLA to trx Vannes_KBE :               17.75                    21.83                      14                     mode 1                   200.0                      2                     (-272,8)        
+1       trx Brest_KLA to trx Vannes_KBE :               17.74                    21.82                      14                     mode 1                   200.0                      2                   ([-272],[8])      
-3       trx Lannion_CAS to trx Rennes_STA :             22.21                    26.29                      13                     mode 1                    60.0                      1                     (-284,4)        
+3       trx Lannion_CAS to trx Rennes_STA :             22.19                    26.28                      13                     mode 1                    60.0                      1                   ([-284],[4])      
-4       trx Rennes_STA to trx Lannion_CAS :             16.07                    23.29                      17                     mode 2                   150.0                      1                     (-258,6)        
+4       trx Rennes_STA to trx Lannion_CAS :             16.06                    23.29                      17                     mode 2                   150.0                      1                   ([-258],[6])      
-5       trx Rennes_STA to trx Lannion_CAS :             20.31                    27.54                      17                     mode 2                    20.0                      1                     (-274,6)        
+5       trx Rennes_STA to trx Lannion_CAS :              20.3                    27.53                      17                     mode 2                    20.0                      1                   ([-274],[6])      
-7 | 6   trx Lannion_CAS to trx Lorient_KMA :            19.52                    23.61                      14                     mode 1                   700.0                      7                    (-224,28)        
+7 | 6   trx Lannion_CAS to trx Lorient_KMA :            19.52                    23.61                      14                     mode 1                   700.0                      7                  ([-224],[28])      
-7b      trx Lannion_CAS to trx Lorient_KMA :            19.61                    23.69                      14                     mode 1                   400.0                      4                    (-172,24)        
+7b      trx Lannion_CAS to trx Lorient_KMA :            19.61                    23.69                      14                     mode 1                   400.0                      4                  ([-172],[24])      
 Result summary shows mean GSNR and OSNR (average over all channels)

tests/invocation/path_requests_run_CD_PMD_PDL_missing

@@ -0,0 +1,24 @@
+List of disjunctions
+[]
+Aggregating similar requests
+The following services have been requested:
+[PathRequest 0
+	source: 	trx Abilene
+	destination:	trx Albany
+	trx type:	Voyager
+	trx mode:	mode 3
+	baud_rate:	44.0 Gbaud
+	bit_rate:	300.0 Gb/s
+	spacing:	62.50000000000001 GHz
+	power:  	0.0 dBm
+	nb channels: 	76
+	path_bandwidth: 	100.0 Gbit/s
+	nodes-list:	[]
+	loose-list:	[]
+]
+Computing all paths with constraints
+Propagating on selected path
+Result summary
+req id   demand                       GSNR@bandwidth A-Z (Z-A)   GSNR@0.1nm A-Z (Z-A)        Receiver minOSNR               mode                    Gbit/s              nb of tsp pairs      N,M or blocking reason 
+0       trx Abilene to trx Albany :             9.04                     14.5                      -                      mode 3                   100.0                      -                MODE_NOT_FEASIBLE    
+Result summary shows mean GSNR and OSNR (average over all channels)

tests/invocation/spectrum1_transmission_main_example

@@ -0,0 +1,102 @@
+User input for spectrum used for propagation instead of SI
+There are 76 channels propagating
+Power mode is set to True
+=> it can be modified in eqpt_config.json - Span
+
+There are 3 fiber spans over 130 km between trx Lannion_CAS and trx Lorient_KMA
+
+Now propagating between trx Lannion_CAS and trx Lorient_KMA:
+
+Propagating with input power = 0.00 dBm:
+Transceiver trx Lannion_CAS
+  GSNR (0.1nm, dB):          40.00
+  GSNR (signal bw, dB):      35.92
+  OSNR ASE (0.1nm, dB):      40.00
+  OSNR ASE (signal bw, dB):  35.92
+  CD (ps/nm):                0.00
+  PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
+Roadm roadm Lannion_CAS
+  effective loss (dB):     20.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
+Edfa east edfa in Lannion_CAS to Corlay
+  type_variety:           std_medium_gain
+  effective gain(dB):     21.00
+  (before att_in and before output VOA)
+  noise figure (dB):      6.36
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -1.19
+  Power Out (dBm):        19.82
+  Delta_P (dB):           1.00
+  target pch (dBm):       1.00
+  effective pch (dBm):    1.00
+  actual pch out (dBm):   1.01
+  output VOA (dB):        0.00
+Fiber          fiber (Lannion_CAS → Corlay)-F061
+  type_variety:                SSMF
+  length (km):                 20.00
+  pad att_in (dB):             0.00
+  total loss (dB):             4.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -3.00
+  actual pch out (dBm):        -2.99
+Fused west fused spans in Corlay
+  loss (dB): 1.00
+Fiber          fiber (Corlay → Loudeac)-F010
+  type_variety:                SSMF
+  length (km):                 50.00
+  pad att_in (dB):             0.00
+  total loss (dB):             10.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -14.00
+  actual pch out (dBm):        -13.99
+Fused west fused spans in Loudeac
+  loss (dB): 1.00
+Fiber          fiber (Loudeac → Lorient_KMA)-F054
+  type_variety:                SSMF
+  length (km):                 60.00
+  pad att_in (dB):             0.00
+  total loss (dB):             12.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -27.00
+  actual pch out (dBm):        -26.99
+Edfa west edfa in Lorient_KMA to Loudeac
+  type_variety:           std_high_gain
+  effective gain(dB):     28.00
+  (before att_in and before output VOA)
+  noise figure (dB):      5.92
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -8.18
+  Power Out (dBm):        19.85
+  Delta_P (dB):           1.00
+  target pch (dBm):       1.00
+  effective pch (dBm):    1.00
+  actual pch out (dBm):   1.05
+  output VOA (dB):        0.00
+Roadm roadm Lorient_KMA
+  effective loss (dB):     21.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    -20.00
+Transceiver trx Lorient_KMA
+  GSNR (0.1nm, dB):          23.61
+  GSNR (signal bw, dB):      19.53
+  OSNR ASE (0.1nm, dB):      23.89
+  OSNR ASE (signal bw, dB):  19.81
+  CD (ps/nm):                2171.00
+  PMD (ps):                  0.46
+  PDL (dB):                  0.00
+  Latency (ms):              0.64
+
+Transmission result for input power = 0.00 dBm:
+  Final GSNR (0.1 nm): 23.61 dB
+
+(No source node specified: picked trx Lannion_CAS)
+
+(No destination node specified: picked trx Lorient_KMA)

tests/invocation/spectrum2_transmission_main_example

@@ -0,0 +1,165 @@
+User input for spectrum used for propagation instead of SI
+There are 60 channels propagating
+Power mode is set to True
+=> it can be modified in eqpt_config.json - Span
+
+There are 3 fiber spans over 130 km between trx Lannion_CAS and trx Lorient_KMA
+
+Now propagating between trx Lannion_CAS and trx Lorient_KMA:
+
+Propagating with input power = 0.00 dBm:
+Transceiver trx Lannion_CAS
+  GSNR (0.1nm, dB):          mode_1: 40.00, mode_2: 40.00
+  GSNR (signal bw, dB):      mode_1: 35.92, mode_2: 32.91
+  OSNR ASE (0.1nm, dB):      mode_1: 40.00, mode_2: 40.00
+  OSNR ASE (signal bw, dB):  mode_1: 35.92, mode_2: 32.91
+  CD (ps/nm):                0.00
+  PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
+Roadm roadm Lannion_CAS
+  effective loss (dB):     20.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+Edfa east edfa in Lannion_CAS to Corlay
+  type_variety:           std_medium_gain
+  effective gain(dB):     21.00
+  (before att_in and before output VOA)
+  noise figure (dB):      6.36
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -2.22
+  Power Out (dBm):        18.79
+  Delta_P (dB):           1.00
+  target pch (dBm):       1.00
+  effective pch (dBm):    1.00
+  actual pch out (dBm):   mode_1: 1.01, mode_2: 1.02
+  output VOA (dB):        0.00
+Fiber          fiber (Lannion_CAS → Corlay)-F061
+  type_variety:                SSMF
+  length (km):                 20.00
+  pad att_in (dB):             0.00
+  total loss (dB):             4.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -3.00
+  actual pch out (dBm):        mode_1: -2.99, mode_2: -2.98
+Fused west fused spans in Corlay
+  loss (dB): 1.00
+Fiber          fiber (Corlay → Loudeac)-F010
+  type_variety:                SSMF
+  length (km):                 50.00
+  pad att_in (dB):             0.00
+  total loss (dB):             10.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -14.00
+  actual pch out (dBm):        mode_1: -13.99, mode_2: -13.98
+Fused west fused spans in Loudeac
+  loss (dB): 1.00
+Fiber          fiber (Loudeac → Lorient_KMA)-F054
+  type_variety:                SSMF
+  length (km):                 60.00
+  pad att_in (dB):             0.00
+  total loss (dB):             12.00
+  (includes conn loss (dB) in: 0.00 out: 0.00)
+  (conn loss out includes EOL margin defined in eqpt_config.json)
+  reference pch out (dBm):     -27.00
+  actual pch out (dBm):        mode_1: -26.99, mode_2: -26.98
+Edfa west edfa in Lorient_KMA to Loudeac
+  type_variety:           std_high_gain
+  effective gain(dB):     28.00
+  (before att_in and before output VOA)
+  noise figure (dB):      5.92
+  (including att_in)
+  pad att_in (dB):        0.00
+  Power In (dBm):         -9.21
+  Power Out (dBm):        18.84
+  Delta_P (dB):           1.00
+  target pch (dBm):       1.00
+  effective pch (dBm):    1.00
+  actual pch out (dBm):   mode_1: 1.04, mode_2: 1.09
+  output VOA (dB):        0.00
+Roadm roadm Lorient_KMA
+  effective loss (dB):     21.00
+  reference pch out (dBm): -20.00
+  actual pch out (dBm):    mode_1: -20.00, mode_2: -20.00
+Transceiver trx Lorient_KMA
+  GSNR (0.1nm, dB):          mode_1: 23.66, mode_2: 23.81
+  GSNR (signal bw, dB):      mode_1: 19.58, mode_2: 16.72
+  OSNR ASE (0.1nm, dB):      mode_1: 23.91, mode_2: 23.87
+  OSNR ASE (signal bw, dB):  mode_1: 19.83, mode_2: 16.78
+  CD (ps/nm):                2171.00
+  PMD (ps):                  0.46
+  PDL (dB):                  0.00
+  Latency (ms):              0.64
+
+Transmission result for input power = 0.00 dBm:
+  Final GSNR (0.1 nm): 23.72 dB
+
+The GSNR per channel at the end of the line is:
+Ch. #   Channel frequency (THz)       Channel power (dBm)    OSNR ASE (signal bw, dB)     SNR NLI (signal bw, dB)        GSNR (signal bw, dB)
+    1                 191.40000                    -20.04                       19.85                       33.52                       19.66
+    2                 191.45000                    -20.04                       19.85                       32.93                       19.64
+    3                 191.50000                    -20.04                       19.84                       32.67                       19.62
+    4                 191.55000                    -20.04                       19.84                       32.50                       19.61
+    5                 191.60000                    -20.04                       19.84                       32.39                       19.61
+    6                 191.65000                    -20.04                       19.84                       32.30                       19.60
+    7                 191.70000                    -20.04                       19.84                       32.22                       19.60
+    8                 191.75000                    -20.04                       19.84                       32.16                       19.59
+    9                 191.80000                    -20.04                       19.84                       32.11                       19.59
+   10                 191.85000                    -20.04                       19.84                       32.07                       19.59
+   11                 191.90000                    -20.04                       19.84                       32.04                       19.58
+   12                 191.95000                    -20.04                       19.84                       32.00                       19.58
+   13                 192.00000                    -20.04                       19.83                       31.98                       19.58
+   14                 192.05000                    -20.04                       19.83                       31.95                       19.57
+   15                 192.10000                    -20.04                       19.83                       31.93                       19.57
+   16                 192.15000                    -20.04                       19.83                       31.91                       19.57
+   17                 192.20000                    -20.04                       19.83                       31.90                       19.57
+   18                 192.25000                    -20.04                       19.83                       31.88                       19.57
+   19                 192.30000                    -20.04                       19.83                       31.87                       19.56
+   20                 192.35000                    -20.04                       19.83                       31.87                       19.56
+   21                 192.40000                    -20.04                       19.83                       31.86                       19.56
+   22                 192.45000                    -20.04                       19.82                       31.86                       19.56
+   23                 192.50000                    -20.04                       19.82                       31.86                       19.56
+   24                 192.55000                    -20.04                       19.82                       31.86                       19.56
+   25                 192.60000                    -20.04                       19.82                       31.87                       19.56
+   26                 192.65000                    -20.04                       19.82                       31.88                       19.56
+   27                 192.70000                    -20.04                       19.82                       31.89                       19.56
+   28                 192.75000                    -20.04                       19.82                       31.91                       19.56
+   29                 192.80000                    -20.04                       19.82                       31.93                       19.56
+   30                 192.85000                    -20.04                       19.82                       31.97                       19.56
+   31                 192.90000                    -20.04                       19.82                       32.01                       19.56
+   32                 192.95000                    -20.04                       19.81                       32.07                       19.56
+   33                 193.00000                    -20.04                       19.81                       32.16                       19.57
+   34                 193.05000                    -20.04                       19.81                       32.31                       19.57
+   35                 193.10000                    -20.04                       19.81                       32.65                       19.59
+   36                 193.16250                    -20.09                       16.80                       33.73                       16.71
+   37                 193.23750                    -20.09                       16.80                       34.22                       16.72
+   38                 193.31250                    -20.09                       16.80                       34.47                       16.72
+   39                 193.38750                    -20.09                       16.79                       34.63                       16.72
+   40                 193.46250                    -20.09                       16.79                       34.75                       16.72
+   41                 193.53750                    -20.09                       16.79                       34.84                       16.72
+   42                 193.61250                    -20.09                       16.79                       34.92                       16.72
+   43                 193.68750                    -20.09                       16.79                       34.99                       16.72
+   44                 193.76250                    -20.09                       16.79                       35.04                       16.72
+   45                 193.83750                    -20.09                       16.78                       35.10                       16.72
+   46                 193.91250                    -20.09                       16.78                       35.15                       16.72
+   47                 193.98750                    -20.09                       16.78                       35.19                       16.72
+   48                 194.06250                    -20.09                       16.78                       35.24                       16.72
+   49                 194.13750                    -20.09                       16.78                       35.28                       16.72
+   50                 194.21250                    -20.09                       16.78                       35.33                       16.72
+   51                 194.28750                    -20.09                       16.78                       35.37                       16.72
+   52                 194.36250                    -20.09                       16.77                       35.42                       16.72
+   53                 194.43750                    -20.09                       16.77                       35.47                       16.71
+   54                 194.51250                    -20.09                       16.77                       35.53                       16.71
+   55                 194.58750                    -20.09                       16.77                       35.59                       16.71
+   56                 194.66250                    -20.09                       16.77                       35.67                       16.71
+   57                 194.73750                    -20.09                       16.77                       35.77                       16.71
+   58                 194.81250                    -20.09                       16.76                       35.90                       16.71
+   59                 194.88750                    -20.09                       16.76                       36.11                       16.71
+   60                 194.96250                    -20.09                       16.76                       36.58                       16.72
+
+(No source node specified: picked trx Lannion_CAS)
+
+(No destination node specified: picked trx Lorient_KMA)

tests/invocation/transmission_main_example

@@ -14,6 +14,8 @@ Transceiver Site_A
   OSNR ASE (signal bw, dB):  35.92
   CD (ps/nm):                0.00
   PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
 Fiber          Span1
   type_variety:                SSMF
   length (km):                 80.00
@@ -21,7 +23,8 @@ Fiber          Span1
   total loss (dB):             17.00
   (includes conn loss (dB) in: 0.50 out: 0.50)
   (conn loss out includes EOL margin defined in eqpt_config.json)
-  pch out (dBm): -17.00
+  reference pch out (dBm):     -17.00
+  actual pch out (dBm):        -17.00
 Edfa Edfa1
   type_variety:           std_low_gain
   effective gain(dB):     15.00
@@ -34,17 +37,20 @@ Edfa Edfa1
   Delta_P (dB):           -2.00
   target pch (dBm):       -2.00
   effective pch (dBm):    -2.00
+  actual pch out (dBm):   -1.99
   output VOA (dB):        0.00
 Transceiver Site_B
-  GSNR (0.1nm, dB):          31.17
+  GSNR (0.1nm, dB):          31.18
-  GSNR (signal bw, dB):      27.09
+  GSNR (signal bw, dB):      27.10
   OSNR ASE (0.1nm, dB):      33.30
   OSNR ASE (signal bw, dB):  29.21
   CD (ps/nm):                1336.00
   PMD (ps):                  0.36
+  PDL (dB):                  0.00
+  Latency (ms):              0.39
 
 Transmission result for input power = 0.00 dBm:
-  Final GSNR (0.1 nm): 31.17 dB
+  Final GSNR (0.1 nm): 31.18 dB
 
 (No source node specified: picked Site_A)
 

tests/invocation/transmission_main_example__raman

@@ -14,6 +14,8 @@ Transceiver Site_A
   OSNR ASE (signal bw, dB):  35.92
   CD (ps/nm):                0.00
   PMD (ps):                  0.00
+  PDL (dB):                  0.00
+  Latency (ms):              0.00
 RamanFiber          Span1
   type_variety:                SSMF
   length (km):                 80.00
@@ -21,109 +23,115 @@ RamanFiber          Span1
   total loss (dB):             17.00
   (includes conn loss (dB) in: 0.50 out: 0.50)
   (conn loss out includes EOL margin defined in eqpt_config.json)
-  pch out (dBm): -7.74
+  reference pch out (dBm):     -7.20
+  actual pch out (dBm):        -7.47
+Fused Fused1
+  loss (dB): 0.00
 Edfa Edfa1
   type_variety:           std_low_gain
-  effective gain(dB):     5.74
+  effective gain(dB):     5.20
   (before att_in and before output VOA)
-  noise figure (dB):      13.26
+  noise figure (dB):      13.80
   (including att_in)
-  pad att_in (dB):        2.26
+  pad att_in (dB):        2.80
-  Power In (dBm):         11.07
+  Power In (dBm):         11.61
-  Power Out (dBm):        16.82
+  Power Out (dBm):        16.81
   Delta_P (dB):           -2.00
   target pch (dBm):       -2.00
   effective pch (dBm):    -2.00
+  actual pch out (dBm):   -2.26
   output VOA (dB):        0.00
 Transceiver Site_B
-  GSNR (0.1nm, dB):          31.43
+  GSNR (0.1nm, dB):          31.42
-  GSNR (signal bw, dB):      27.35
+  GSNR (signal bw, dB):      27.34
-  OSNR ASE (0.1nm, dB):      34.18
+  OSNR ASE (0.1nm, dB):      34.21
-  OSNR ASE (signal bw, dB):  30.10
+  OSNR ASE (signal bw, dB):  30.13
   CD (ps/nm):                1336.00
   PMD (ps):                  0.36
+  PDL (dB):                  0.00
+  Latency (ms):              0.39
 
 Transmission result for input power = 0.00 dBm:
-  Final GSNR (0.1 nm): 31.43 dB
+  Final GSNR (0.1 nm): 31.42 dB
 
 The GSNR per channel at the end of the line is:
 Ch. #   Channel frequency (THz)       Channel power (dBm)    OSNR ASE (signal bw, dB)     SNR NLI (signal bw, dB)        GSNR (signal bw, dB)
-    1                    191.35                      0.21                       31.56                       31.47                       28.50
+    1                 191.35000                      0.22                       31.64                       31.55                       28.58
-    2                    191.40                      0.17                       31.54                       31.38                       28.45
+    2                 191.40000                      0.18                       31.62                       31.46                       28.53
-    3                    191.45                      0.14                       31.52                       31.30                       28.40
+    3                 191.45000                      0.15                       31.60                       31.37                       28.47
-    4                    191.50                      0.10                       31.50                       31.22                       28.34
+    4                 191.50000                      0.11                       31.58                       31.28                       28.42
-    5                    191.55                      0.04                       31.47                       31.14                       28.29
+    5                 191.55000                      0.05                       31.54                       31.20                       28.36
-    6                    191.60                     -0.02                       31.44                       31.06                       28.23
+    6                 191.60000                     -0.01                       31.51                       31.11                       28.30
-    7                    191.65                     -0.08                       31.41                       30.98                       28.18
+    7                 191.65000                     -0.07                       31.48                       31.03                       28.24
-    8                    191.70                     -0.14                       31.37                       30.90                       28.12
+    8                 191.70000                     -0.12                       31.45                       30.95                       28.18
-    9                    191.75                     -0.20                       31.34                       30.83                       28.07
+    9                 191.75000                     -0.18                       31.42                       30.87                       28.13
-   10                    191.80                     -0.26                       31.31                       30.75                       28.01
+   10                 191.80000                     -0.25                       31.38                       30.79                       28.07
-   11                    191.85                     -0.33                       31.27                       30.68                       27.96
+   11                 191.85000                     -0.31                       31.35                       30.72                       28.01
-   12                    191.90                     -0.39                       31.24                       30.61                       27.90
+   12                 191.90000                     -0.38                       31.31                       30.64                       27.95
-   13                    191.95                     -0.46                       31.20                       30.54                       27.85
+   13                 191.95000                     -0.44                       31.27                       30.57                       27.90
-   14                    192.00                     -0.52                       31.17                       30.47                       27.79
+   14                 192.00000                     -0.51                       31.24                       30.50                       27.84
-   15                    192.05                     -0.59                       31.13                       30.40                       27.74
+   15                 192.05000                     -0.58                       31.20                       30.42                       27.78
-   16                    192.10                     -0.66                       31.10                       30.33                       27.69
+   16                 192.10000                     -0.64                       31.16                       30.35                       27.73
-   17                    192.15                     -0.72                       31.06                       30.26                       27.63
+   17                 192.15000                     -0.71                       31.12                       30.29                       27.67
-   18                    192.20                     -0.79                       31.02                       30.20                       27.58
+   18                 192.20000                     -0.78                       31.08                       30.22                       27.62
-   19                    192.25                     -0.86                       30.98                       30.21                       27.57
+   19                 192.25000                     -0.85                       31.04                       30.22                       27.60
-   20                    192.30                     -0.94                       30.94                       30.21                       27.55
+   20                 192.30000                     -0.93                       31.00                       30.22                       27.58
-   21                    192.35                     -1.01                       30.90                       30.22                       27.54
+   21                 192.35000                     -1.00                       30.96                       30.23                       27.57
-   22                    192.40                     -1.09                       30.86                       30.23                       27.52
+   22                 192.40000                     -1.08                       30.91                       30.23                       27.55
-   23                    192.45                     -1.16                       30.81                       30.23                       27.50
+   23                 192.45000                     -1.16                       30.87                       30.23                       27.53
-   24                    192.50                     -1.24                       30.77                       30.24                       27.49
+   24                 192.50000                     -1.23                       30.82                       30.24                       27.51
-   25                    192.55                     -1.31                       30.73                       30.25                       27.47
+   25                 192.55000                     -1.30                       30.78                       30.24                       27.49
-   26                    192.60                     -1.38                       30.69                       30.25                       27.46
+   26                 192.60000                     -1.37                       30.74                       30.24                       27.47
-   27                    192.65                     -1.45                       30.65                       30.26                       27.44
+   27                 192.65000                     -1.44                       30.70                       30.25                       27.46
-   28                    192.70                     -1.52                       30.61                       30.27                       27.42
+   28                 192.70000                     -1.52                       30.65                       30.25                       27.44
-   29                    192.75                     -1.59                       30.56                       30.28                       27.41
+   29                 192.75000                     -1.59                       30.61                       30.25                       27.42
-   30                    192.80                     -1.66                       30.52                       30.28                       27.39
+   30                 192.80000                     -1.66                       30.57                       30.26                       27.40
-   31                    192.85                     -1.73                       30.48                       30.29                       27.37
+   31                 192.85000                     -1.73                       30.52                       30.26                       27.38
-   32                    192.90                     -1.80                       30.44                       30.30                       27.36
+   32                 192.90000                     -1.80                       30.48                       30.26                       27.36
-   33                    192.95                     -1.87                       30.39                       30.30                       27.34
+   33                 192.95000                     -1.87                       30.43                       30.27                       27.34
-   34                    193.00                     -1.94                       30.35                       30.31                       27.32
+   34                 193.00000                     -1.94                       30.39                       30.27                       27.32
-   35                    193.05                     -2.01                       30.31                       30.32                       27.30
+   35                 193.05000                     -2.01                       30.35                       30.27                       27.30
-   36                    193.10                     -2.08                       30.27                       30.33                       27.29
+   36                 193.10000                     -2.08                       30.30                       30.28                       27.28
-   37                    193.15                     -2.15                       30.22                       30.33                       27.27
+   37                 193.15000                     -2.15                       30.26                       30.28                       27.26
-   38                    193.20                     -2.22                       30.18                       30.35                       27.25
+   38                 193.20000                     -2.22                       30.22                       30.29                       27.24
-   39                    193.25                     -2.29                       30.14                       30.37                       27.24
+   39                 193.25000                     -2.29                       30.17                       30.31                       27.23
-   40                    193.30                     -2.36                       30.09                       30.39                       27.23
+   40                 193.30000                     -2.36                       30.13                       30.32                       27.21
-   41                    193.35                     -2.43                       30.05                       30.40                       27.21
+   41                 193.35000                     -2.43                       30.08                       30.33                       27.19
-   42                    193.40                     -2.49                       30.01                       30.42                       27.20
+   42                 193.40000                     -2.50                       30.04                       30.35                       27.18
-   43                    193.45                     -2.56                       29.96                       30.44                       27.18
+   43                 193.45000                     -2.56                       29.99                       30.36                       27.16
-   44                    193.50                     -2.63                       29.92                       30.46                       27.17
+   44                 193.50000                     -2.63                       29.95                       30.37                       27.14
-   45                    193.55                     -2.70                       29.87                       30.47                       27.15
+   45                 193.55000                     -2.71                       29.90                       30.39                       27.12
-   46                    193.60                     -2.78                       29.83                       30.49                       27.13
+   46                 193.60000                     -2.78                       29.85                       30.40                       27.11
-   47                    193.65                     -2.85                       29.78                       30.51                       27.12
+   47                 193.65000                     -2.85                       29.80                       30.41                       27.09
-   48                    193.70                     -2.92                       29.73                       30.53                       27.10
+   48                 193.70000                     -2.93                       29.75                       30.43                       27.07
-   49                    193.75                     -2.99                       29.68                       30.54                       27.08
+   49                 193.75000                     -3.00                       29.70                       30.44                       27.05
-   50                    193.80                     -3.06                       29.64                       30.56                       27.06
+   50                 193.80000                     -3.07                       29.65                       30.45                       27.02
-   51                    193.85                     -3.14                       29.59                       30.58                       27.05
+   51                 193.85000                     -3.15                       29.60                       30.47                       27.00
-   52                    193.90                     -3.21                       29.54                       30.60                       27.03
+   52                 193.90000                     -3.22                       29.55                       30.48                       26.98
-   53                    193.95                     -3.28                       29.49                       30.62                       27.01
+   53                 193.95000                     -3.29                       29.50                       30.50                       26.96
-   54                    194.00                     -3.35                       29.44                       30.64                       26.99
+   54                 194.00000                     -3.37                       29.45                       30.51                       26.94
-   55                    194.05                     -3.42                       29.39                       30.65                       26.97
+   55                 194.05000                     -3.44                       29.40                       30.52                       26.92
-   56                    194.10                     -3.50                       29.34                       30.67                       26.95
+   56                 194.10000                     -3.52                       29.35                       30.54                       26.89
-   57                    194.15                     -3.57                       29.29                       30.73                       26.94
+   57                 194.15000                     -3.59                       29.30                       30.59                       26.89
-   58                    194.20                     -3.64                       29.24                       30.79                       26.94
+   58                 194.20000                     -3.66                       29.25                       30.64                       26.88
-   59                    194.25                     -3.72                       29.19                       30.85                       26.93
+   59                 194.25000                     -3.74                       29.19                       30.70                       26.87
-   60                    194.30                     -3.79                       29.14                       30.91                       26.93
+   60                 194.30000                     -3.81                       29.14                       30.75                       26.86
-   61                    194.35                     -3.86                       29.09                       30.97                       26.92
+   61                 194.35000                     -3.89                       29.09                       30.81                       26.86
-   62                    194.40                     -3.93                       29.04                       31.03                       26.91
+   62                 194.40000                     -3.96                       29.04                       30.87                       26.85
-   63                    194.45                     -4.01                       28.99                       31.09                       26.90
+   63                 194.45000                     -4.04                       28.98                       30.93                       26.84
-   64                    194.50                     -4.08                       28.94                       31.15                       26.90
+   64                 194.50000                     -4.11                       28.93                       30.98                       26.83
-   65                    194.55                     -4.14                       28.89                       31.22                       26.89
+   65                 194.55000                     -4.18                       28.88                       31.04                       26.82
-   66                    194.60                     -4.21                       28.85                       31.28                       26.88
+   66                 194.60000                     -4.25                       28.83                       31.10                       26.81
-   67                    194.65                     -4.28                       28.80                       31.35                       26.88
+   67                 194.65000                     -4.31                       28.78                       31.17                       26.80
-   68                    194.70                     -4.34                       28.75                       31.41                       26.87
+   68                 194.70000                     -4.38                       28.74                       31.23                       26.79
-   69                    194.75                     -4.41                       28.70                       31.48                       26.86
+   69                 194.75000                     -4.45                       28.69                       31.29                       26.79
-   70                    194.80                     -4.47                       28.66                       31.55                       26.86
+   70                 194.80000                     -4.51                       28.64                       31.35                       26.78
-   71                    194.85                     -4.54                       28.61                       31.62                       26.85
+   71                 194.85000                     -4.58                       28.59                       31.42                       26.77
-   72                    194.90                     -4.60                       28.56                       31.69                       26.84
+   72                 194.90000                     -4.65                       28.54                       31.48                       26.76
-   73                    194.95                     -4.67                       28.51                       31.77                       26.83
+   73                 194.95000                     -4.71                       28.49                       31.55                       26.74
-   74                    195.00                     -4.73                       28.47                       31.84                       26.82
+   74                 195.00000                     -4.78                       28.44                       31.62                       26.73
-   75                    195.05                     -4.80                       28.42                       31.91                       26.81
+   75                 195.05000                     -4.85                       28.39                       31.69                       26.72
-   76                    195.10                     -4.86                       28.37                       31.91                       26.78
+   76                 195.10000                     -4.91                       28.34                       31.69                       26.69
 
 (No source node specified: picked Site_A)