15 Commits

Author SHA1 Message Date
EstherLerouzic
f6dab0477b Add the possibilty to input id instead of explicit topo or eqpt
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I81c9fd56773e6f998bc2bdf87fc2aef817e252a4
2021-03-02 15:25:26 +01:00
manuedelf
ce4a226615 add autodesign routes
Signed-off-by: manuedelf <59697943+edelfour@users.noreply.github.com>
2021-01-25 23:11:05 +01:00
manuedelf
78fc0c0680 fix error in if
Signed-off-by: manuedelf <59697943+edelfour@users.noreply.github.com>
2021-01-05 16:24:25 +01:00
manuedelf
2c4f2fbb12 Add equipments and topolgies endpoints
- add POST, PUT, DELETE on equipments
- add POST, PUT, GET, DELETE on topogies
- path-computation request body can now have equipment id and/or
topology id instead of full data
- activate embedded https of Flask while waiting for real trusted
certificate
- update readme
- add request payload samples in yang directory
- equipment data are encrypted with Fernet

Signed-off-by: manuedelf <59697943+edelfour@users.noreply.github.com>
2020-12-23 15:06:02 +01:00
manuedelf
63545c86ed Put api in a dedicated python package
Signed-off-by: manuedelf <59697943+edelfour@users.noreply.github.com>
2020-12-22 13:49:46 +01:00
manuedelf
aa78d00158 remove obsolete example 2020-11-18 14:16:58 +01:00
EstherLerouzic
6a0e73e332 add an example request (with answers)
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Id75fff88cd3b03fcf965c22763075ac3dbea41c6
2020-11-06 18:20:13 +01:00
EstherLerouzic
fa6b8c87e4 add 'gnpy-api:' context when reading the content of the request
in order to be compliant with yang

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ifa6ab93025b18a5a678b625e42e3d351499c69d7
2020-11-06 17:39:03 +01:00
EstherLerouzic
801c66aae2 adding yang corresponding to the json inputs
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I75b0cc3c3ce84dc724e588f918bddf0a5a97225d
2020-11-06 17:39:03 +01:00
EstherLerouzic
f60c347a48 support missing trx_mode in request instead of null value
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I5c05b17b0b134c7782a08e86015dc30c7c9b3713
2020-11-06 17:39:03 +01:00
EstherLerouzic
649bb3bd0f Change N values from 0 to None in case of NO_SPECTRUM
in case spectrum can not be assigned default values for N is set to 0,
which is not correct (N is a meaningfull value for
center frequency index). This changes replaces this default
value with None

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ibe642682e48d09f340d53e2092f172de6aa7cc90
2020-11-06 17:38:28 +01:00
EstherLerouzic
6051ad54bc Enabling the reading of N and M value from the json request
For this commit only the first element from the {N, M} list is read
and assigned.

This is better than not reading this value at all.

the commit also updates test_files and test data files with correct
values for the effective_freq_slot attribute

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I1e60fe833ca1092b40de27c8cbfb13083810414e
2020-11-06 14:44:13 +01:00
EstherLerouzic
95d24d8e20 Avoid overwriting blocking reason
When a path is blocked for 'NO_FEASIBLE_MODE' reason, and bidir is true,
the request attributes are filled with the last explored mode values
(baudrate notably), and the reversed path is propagated with this last
explored mode specs. if this reversed path is also not feasible the blocking
reason was overwritten with a 'MODE_NOT_FESIBLE' reasonn, because
baudrate is filled in the request attribute.

This change ensure that the blocking reason (if it exists) is not overwritten.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: If80a37d77e2b967a327562c733a44e7f78f1c544
2020-11-06 14:43:54 +01:00
manuedelf
6c449edece docker image update + readme 2020-10-16 23:34:22 +02:00
manuedelf
d051f93d55 Rest api for GNPy 2020-10-15 16:27:18 +02:00
182 changed files with 82745 additions and 106582 deletions

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

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

47
.docker-travis.sh Executable file
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@@ -0,0 +1,47 @@
#!/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

1
.dockerignore Normal file
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@@ -0,0 +1 @@
venv/

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@@ -1,7 +0,0 @@
# Thanks for contributing to GNPy
If it isn't much trouble, please send your contribution as patches to our Gerrit.
Here's [how to submit patches](https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html), and here's a [list of stuff we are currently working on](https://review.gerrithub.io/q/project:Telecominfraproject/oopt-gnpy+status:open).
Just sign in via your existing GitHub account.
However, if you feel more comfortable with filing GitHub PRs, we can work with that too.

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@@ -1,145 +0,0 @@
on:
push:
pull_request:
branches:
- master
name: CI
jobs:
build:
name: Tox test
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
with:
fetch-depth: 0
- uses: fedora-python/tox-github-action@v37.0
with:
tox_env: ${{ matrix.tox_env }}
dnf_install: ${{ matrix.dnf_install }}
- uses: codecov/codecov-action@v3.1.1
if: ${{ endswith(matrix.tox_env, '-cover') }}
with:
files: ${{ github.workspace }}/cover/coverage.xml
strategy:
fail-fast: false
matrix:
tox_env:
- py38
- py39
- py310
- py311
- py312-cover
include:
- tox_env: docs
dnf_install: graphviz
pypi:
needs: build
if: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && github.repository_owner == 'Telecominfraproject' }}
name: PyPI packaging
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
with:
fetch-depth: 0
- uses: actions/setup-python@v4
name: Install Python
with:
python-version: '3.12'
- uses: casperdcl/deploy-pypi@bb869aafd89f657ceaafe9561d3b5584766c0f95
with:
password: ${{ secrets.PYPI_API_TOKEN }}
pip: wheel -w dist/ --no-deps .
upload: true
docker:
needs: build
if: ${{ github.event_name == 'push' && (github.ref == 'refs/heads/master' || startsWith(github.ref, 'refs/tags/v')) && github.repository_owner == 'Telecominfraproject' }}
name: Docker image
runs-on: ubuntu-latest
steps:
- name: Log in to Docker Hub
uses: docker/login-action@v1
with:
username: jktjkt
password: ${{ secrets.DOCKERHUB_TOKEN }}
- uses: actions/checkout@v3
with:
fetch-depth: 0
- name: Extract tag name
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
id: extract_pretty_git
run: echo ::set-output name=GIT_DESC::$(git describe --tags)
- name: Build and push a container
uses: docker/build-push-action@v2
if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
with:
context: .
push: true
tags: |
telecominfraproject/oopt-gnpy:${{ steps.extract_pretty_git.outputs.GIT_DESC }}
telecominfraproject/oopt-gnpy:master
- name: Extract tag name
if: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') }}
id: extract_tag_name
run: echo ::set-output name=GIT_DESC::${GITHUB_REF/refs\/tags\//}
- name: Build and push a container
uses: docker/build-push-action@v2
if: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') }}
with:
context: .
push: true
tags: |
telecominfraproject/oopt-gnpy:${{ steps.extract_tag_name.outputs.GIT_DESC }}
telecominfraproject/oopt-gnpy:latest
other-platforms:
name: Tests on other platforms
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v3
with:
fetch-depth: 0
- uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python_version }}
- run: |
pip install --editable .[tests]
pytest -vv
strategy:
fail-fast: false
matrix:
include:
- os: windows-2019
python_version: "3.10"
- os: windows-2022
python_version: "3.11"
- os: windows-2022
python_version: "3.12"
- os: macos-12
python_version: "3.11"
- os: macos-13
python_version: "3.12"
paywalled-platforms:
name: Tests on paywalled platforms
if: github.repository_owner == 'Telecominfraproject'
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v3
with:
fetch-depth: 0
- uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python_version }}
- run: |
pip install --editable .[tests]
pytest -vv
strategy:
fail-fast: false
matrix:
include:
- os: macos-13-xlarge # Apple M1 CPU
python_version: "3.12"

2
.gitignore vendored
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@@ -65,3 +65,5 @@ target/
# MacOS DS_store
.DS_Store
venv/

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@@ -2,3 +2,4 @@
host=review.gerrithub.io
project=Telecominfraproject/oopt-gnpy
defaultrebase=0
defaultbranch=develop

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

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@@ -1,15 +1,4 @@
version: 2
build:
os: ubuntu-22.04
tools:
python: "3.12"
image: latest
python:
install:
- method: pip
path: .
extra_requirements:
- docs
sphinx:
configuration: docs/conf.py
version: 3.6

24
.travis.yml Normal file
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@@ -0,0 +1,24 @@
dist: xenial
sudo: false
language: python
services: docker
python:
- "3.6"
- "3.7"
install: skip
script:
- python setup.py develop
- pip install pytest-cov rstcheck
- pytest --cov-report=xml --cov=gnpy -v
- rstcheck --ignore-roles cite *.rst
- sphinx-build -W --keep-going docs/ x-throwaway-location
after_success:
- bash <(curl -s https://codecov.io/bash)
jobs:
include:
- stage: test
name: Docker image
script:
- git fetch --unshallow
- ./.docker-travis.sh
- docker images

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@@ -2,33 +2,23 @@
- project:
check:
jobs:
- 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'
- tox-py36-cover
- coverage-diff:
voting: false
dependencies:
- tox-py310-cover-previous
- tox-py310-cover
- tox-py36-cover-previous
- tox-py36-cover
vars:
coverage_job_name_previous: tox-py310-cover-previous
coverage_job_name_current: tox-py310-cover
- tox-linters-diff-n-report:
coverage_job_name_previous: tox-py36-cover-previous
coverage_job_name_current: tox-py36-cover
- tox-linters-diff:
voting: false
vars:
ensure_tox_version: '<4'
- tox-py310-cover-previous:
vars:
ensure_tox_version: '<4'
- tox-docs-el8
- tox-py36-cover-previous
gate:
jobs:
- tox-py36-el8
- tox-docs-el8
tag:
jobs:
- oopt-release-python:

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@@ -11,21 +11,18 @@ 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) <jkt@jankundrat.com>
- Jan Kundrát (Telecom Infra Project) <jan.kundrat@telecominfraproject.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>

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

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@@ -1,31 +0,0 @@
# GNPy: Optical Route Planning and DWDM Network Optimization
[![Install via pip](https://img.shields.io/pypi/v/gnpy)](https://pypi.org/project/gnpy/)
[![Python versions](https://img.shields.io/pypi/pyversions/gnpy)](https://pypi.org/project/gnpy/)
[![Documentation status](https://readthedocs.org/projects/gnpy/badge/?version=master)](http://gnpy.readthedocs.io/en/master/?badge=master)
[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/Telecominfraproject/oopt-gnpy/main.yml)](https://github.com/Telecominfraproject/oopt-gnpy/actions/workflows/main.yml)
[![Gerrit](https://img.shields.io/badge/patches-via%20Gerrit-blue)](https://review.gerrithub.io/q/project:Telecominfraproject/oopt-gnpy+is:open)
[![Contributors](https://img.shields.io/github/contributors-anon/Telecominfraproject/oopt-gnpy)](https://github.com/Telecominfraproject/oopt-gnpy/graphs/contributors)
[![Code Coverage via codecov](https://img.shields.io/codecov/c/github/Telecominfraproject/oopt-gnpy)](https://codecov.io/gh/Telecominfraproject/oopt-gnpy)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3458319.svg)](https://doi.org/10.5281/zenodo.3458319)
[![Matrix chat](https://img.shields.io/matrix/oopt-gnpy:matrix.org)](https://matrix.to/#/%23oopt-gnpy%3Amatrix.org?via=matrix.org)
GNPy is an open-source, community-developed library for building route planning and optimization tools in real-world mesh optical networks.
We are a consortium of operators, vendors, and academic researchers sponsored via the [Telecom Infra Project](http://telecominfraproject.com)'s [OOPT/PSE](https://telecominfraproject.com/open-optical-packet-transport) working group.
Together, we are building this tool for rapid development of production-grade route planning tools which is easily extensible to include custom network elements and performant to the scale of real-world mesh optical networks.
![GNPy with an OLS system](docs/images/GNPy-banner.png)
## Quick Start
Install either via [Docker](https://gnpy.readthedocs.io/en/master/install.html#using-prebuilt-docker-images), or as a [Python package](https://gnpy.readthedocs.io/en/master/install.html#using-python-on-your-computer).
Read our [documentation](https://gnpy.readthedocs.io/), learn from the demos, and [get in touch with us](https://github.com/Telecominfraproject/oopt-gnpy/discussions).
This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power:
![Running a simple simulation example](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/), 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/)

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README.rst Normal file
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.. image:: docs/images/GNPy-banner.png
:width: 100%
:align: left
:alt: GNPy with an OLS system
====================================================================
`gnpy`: mesh optical network route planning and optimization library
====================================================================
|docs| |travis| |doi| |contributors| |codacy-quality| |codecov|
**`gnpy` is an open-source, community-developed library for building route
planning and optimization tools in real-world mesh optical networks.**
`gnpy <http://github.com/telecominfraproject/oopt-gnpy>`__ is:
--------------------------------------------------------------
- a sponsored project of the `OOPT/PSE <https://telecominfraproject.com/open-optical-packet-transport/>`_ working group of the `Telecom Infra Project <http://telecominfraproject.com>`_
- fully community-driven, fully open source library
- driven by a consortium of operators, vendors, and academic researchers
- intended for rapid development of production-grade route planning tools
- easily extensible to include custom network elements
- performant to the scale of real-world mesh optical networks
Documentation: https://gnpy.readthedocs.io
Get In Touch
~~~~~~~~~~~~
There are `weekly calls <https://telecominfraproject.workplace.com/events/702894886867547/>`__ about our progress.
Newcomers, users and telecom operators are especially welcome there.
We encourage all interested people outside the TIP to `join the project <https://telecominfraproject.com/apply-for-membership/>`__.
How to Install
--------------
Install either via `Docker <docs/install.rst#install-docker>`__, or as a `Python package <docs/install.rst#install-pip>`__.
Instructions for First Use
--------------------------
``gnpy`` is a library for building route planning and optimization tools.
It ships with a number of example programs. Release versions will ship with
fully-functional programs.
**Note**: *If you are a network operator or involved in route planning and
optimization for your organization, please contact project maintainer Jan
Kundrát <jan.kundrat@telecominfraproject.com>. gnpy is looking for users with
specific, delineated use cases to drive requirements for future
development.*
This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power:
.. image:: https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg
:width: 100%
:align: left
:alt: Running a simple simulation example
:target: https://asciinema.org/a/252295
By default, this script operates on a single span network defined in
`gnpy/example-data/edfa_example_network.json <gnpy/example-data/edfa_example_network.json>`_
You can specify a different network at the command line as follows. For
example, to use the CORONET Global network defined in
`gnpy/example-data/CORONET_Global_Topology.json <gnpy/example-data/CORONET_Global_Topology.json>`_:
.. code-block:: shell-session
$ gnpy-transmission-example $(gnpy-example-data)/CORONET_Global_Topology.json
It is also possible to use an Excel file input (for example
`gnpy/example-data/CORONET_Global_Topology.xlsx <gnpy/example-data/CORONET_Global_Topology.xlsx>`_).
The Excel file will be processed into a JSON file with the same prefix.
Further details about the Excel data structure are available `in the documentation <docs/excel.rst>`__.
The main transmission example will calculate the average signal OSNR and SNR
across network elements (transceiver, ROADMs, fibers, and amplifiers)
between two transceivers selected by the user. Additional details are provided by doing ``gnpy-transmission-example -h``. (By default, for the CORONET Global
network, it will show the transmission of spectral information between Abilene and Albany)
This script calculates the average signal OSNR = |OSNR| and SNR = |SNR|.
.. |OSNR| replace:: P\ :sub:`ch`\ /P\ :sub:`ase`
.. |SNR| replace:: P\ :sub:`ch`\ /(P\ :sub:`nli`\ +\ P\ :sub:`ase`)
|Pase| is the amplified spontaneous emission noise, and |Pnli| the non-linear
interference noise.
.. |Pase| replace:: P\ :sub:`ase`
.. |Pnli| replace:: P\ :sub:`nli`
Further Instructions for Use
----------------------------
Simulations are driven by a set of `JSON <docs/json.rst>`__ or `XLS <docs/excel.rst>`__ files.
The ``gnpy-transmission-example`` script propagates a spectrum of channels at 32 Gbaud, 50 GHz spacing and 0 dBm/channel.
Launch power can be overridden by using the ``--power`` argument.
Spectrum information is not yet parametrized but can be modified directly in the ``eqpt_config.json`` (via the ``SpectralInformation`` -SI- structure) to accommodate any baud rate or spacing.
The number of channel is computed based on ``spacing`` and ``f_min``, ``f_max`` values.
An experimental support for Raman amplification is available:
.. code-block:: shell-session
$ gnpy-transmission-example \
$(gnpy-example-data)/raman_edfa_example_network.json \
--sim $(gnpy-example-data)/sim_params.json --show-channels
Configuration of Raman pumps (their frequencies, power and pumping direction) is done via the `RamanFiber element in the network topology <gnpy/example-data/raman_edfa_example_network.json>`_.
General numeric parameters for simulaiton control are provided in the `gnpy/example-data/sim_params.json <gnpy/example-data/sim_params.json>`_.
Use ``gnpy-path-request`` to request several paths at once:
.. code-block:: shell-session
$ cd $(gnpy-example-data)
$ gnpy-path-request -o output_file.json \
meshTopologyExampleV2.xls meshTopologyExampleV2_services.json
This program operates on a network topology (`JSON <docs/json.rst>`__ or `Excel <docs/excel.rst>`__ format), processing the list of service requests (JSON or XLS again).
The service requests and reply formats are based on the `draft-ietf-teas-yang-path-computation-01 <https://tools.ietf.org/html/draft-ietf-teas-yang-path-computation-01>`__ with custom extensions (e.g., for transponder modes).
An example of the JSON input is provided in file `service-template.json`, while results are shown in `path_result_template.json`.
Important note: ``gnpy-path-request`` is not a network dimensionning tool: each service does not reserve spectrum, or occupy ressources such as transponders. It only computes path feasibility assuming the spectrum (between defined frequencies) is loaded with "nb of channels" spaced by "spacing" values as specified in the system parameters input in the service file, each cannel having the same characteristics in terms of baudrate, format,... as the service transponder. The transceiver element acts as a "logical starting/stopping point" for the spectral information propagation. At that point it is not meant to represent the capacity of add drop ports.
As a result transponder type is not part of the network info. it is related to the list of services requests.
The current version includes a spectrum assigment features that enables to compute a candidate spectrum assignment for each service based on a first fit policy. Spectrum is assigned based on service specified spacing value, path_bandwidth value and selected mode for the transceiver. This spectrum assignment includes a basic capacity planning capability so that the spectrum resource is limited by the frequency min and max values defined for the links. If the requested services reach the link spectrum capacity, additional services feasibility are computed but marked as blocked due to spectrum reason.
REST API (experimental)
-----------------------
``gnpy`` provides an experimental api for requesting several paths at once. It is based on Flask server.
You can run it through command line or Docker.
.. code-block:: shell-session
$ gnpy-rest
.. code-block:: shell-session
$ docker run -p 8080:8080 -it emmanuelledelfour/gnpy-experimental:candi-1.0 gnpy-rest
When starting the api server will aks for an encryption/decryption key. This key i used to encrypt equipment file when using /api/v1/equipments endpoint.
This key is a Fernet key and can be generated this way:
.. code-block:: python
from cryptography.fernet import Fernet
Fernet.generate_key()
After typing the key, you can detach the container by typing ^P^Q.
After starting the api server, you can launch a request
.. code-block:: shell-session
$ curl -v -X POST -H "Content-Type: application/json" -d @<PATH_TO_JSON_REQUEST_FILE> https://localhost:8080/api/v1/path-computation -k
TODO: api documentation, unit tests, real WSGI server with trusted certificates
Contributing
------------
``gnpy`` is looking for additional contributors, especially those with experience
planning and maintaining large-scale, real-world mesh optical networks.
To get involved, please contact Jan Kundrát
<jan.kundrat@telecominfraproject.com> or Gert Grammel <ggrammel@juniper.net>.
``gnpy`` contributions are currently limited to members of `TIP
<http://telecominfraproject.com>`_. Membership is free and open to all.
See the `Onboarding Guide
<https://github.com/Telecominfraproject/gnpy/wiki/Onboarding-Guide>`_ for
specific details on code contributions.
See `AUTHORS.rst <AUTHORS.rst>`_ for past and present contributors.
Project Background
------------------
Data Centers are built upon interchangeable, highly standardized node and
network architectures rather than a sum of isolated solutions. This also
translates to optical networking. It leads to a push in enabling multi-vendor
optical network by disaggregating HW and SW functions and focusing on
interoperability. In this paradigm, the burden of responsibility for ensuring
the performance of such disaggregated open optical systems falls on the
operators. Consequently, operators and vendors are collaborating in defining
control models that can be readily used by off-the-shelf controllers. However,
node and network models are only part of the answer. To take reasonable
decisions, controllers need to incorporate logic to simulate and assess optical
performance. Hence, a vendor-independent optical quality estimator is required.
Given its vendor-agnostic nature, such an estimator needs to be driven by a
consortium of operators, system and component suppliers.
Founded in February 2016, the Telecom Infra Project (TIP) is an
engineering-focused initiative which is operator driven, but features
collaboration across operators, suppliers, developers, integrators, and
startups with the goal of disaggregating the traditional network deployment
approach. The groups ultimate goal is to help provide better connectivity for
communities all over the world as more people come on-line and demand more
bandwidth- intensive experiences like video, virtual reality and augmented
reality.
Within TIP, the Open Optical Packet Transport (OOPT) project group is chartered
with unbundling monolithic packet-optical network technologies in order to
unlock innovation and support new, more flexible connectivity paradigms.
The key to unbundling is the ability to accurately plan and predict the
performance of optical line systems based on an accurate simulation of optical
parameters. Under that OOPT umbrella, the Physical Simulation Environment (PSE)
working group set out to disrupt the planning landscape by providing an open
source simulation model which can be used freely across multiple vendor
implementations.
.. |docs| image:: https://readthedocs.org/projects/gnpy/badge/?version=master
:target: http://gnpy.readthedocs.io/en/master/?badge=master
:alt: Documentation Status
:scale: 100%
.. |travis| image:: https://travis-ci.com/Telecominfraproject/oopt-gnpy.svg?branch=master
:target: https://travis-ci.com/Telecominfraproject/oopt-gnpy
:alt: Build Status via Travis CI
:scale: 100%
.. |doi| image:: https://zenodo.org/badge/96894149.svg
:target: https://zenodo.org/badge/latestdoi/96894149
:alt: DOI
:scale: 100%
.. |contributors| image:: https://img.shields.io/github/contributors-anon/Telecominfraproject/oopt-gnpy
:target: https://github.com/Telecominfraproject/oopt-gnpy/graphs/contributors
:alt: Code Contributors via GitHub
:scale: 100%
.. |codacy-quality| image:: https://img.shields.io/lgtm/grade/python/github/Telecominfraproject/oopt-gnpy
:target: https://lgtm.com/projects/g/Telecominfraproject/oopt-gnpy/
:alt: Code Quality via LGTM.com
:scale: 100%
.. |codecov| image:: https://img.shields.io/codecov/c/github/Telecominfraproject/oopt-gnpy
:target: https://codecov.io/gh/Telecominfraproject/oopt-gnpy
:alt: Code Coverage via codecov
:scale: 100%
TIP OOPT/PSE & PSE WG Charter
-----------------------------
We believe that openly sharing ideas, specifications, and other intellectual
property is the key to maximizing innovation and reducing complexity
TIP OOPT/PSE's goal is to build an end-to-end simulation environment which
defines the network models of the optical device transfer functions and their
parameters. This environment will provide validation of the optical
performance requirements for the TIP OLS building blocks.
- The model may be approximate or complete depending on the network complexity.
Each model shall be validated against the proposed network scenario.
- The environment must be able to process network models from multiple vendors,
and also allow users to pick any implementation in an open source framework.
- The PSE will influence and benefit from the innovation of the DTC, API, and
OLS working groups.
- The PSE represents a step along the journey towards multi-layer optimization.
License
-------
``gnpy`` is distributed under a standard BSD 3-Clause License.
See `LICENSE <LICENSE>`__ for more details.

View File

@@ -1 +0,0 @@
graphviz

View File

@@ -1,59 +0,0 @@
(about-gnpy)=
# About the project
GNPy is a sponsored project of the [OOPT/PSE](https://telecominfraproject.com/open-optical-packet-transport/) working group of the [Telecom Infra Project](http://telecominfraproject.com).
There are weekly calls about our progress.
Newcomers, users and telecom operators are especially welcome there.
We encourage all interested people outside the TIP to [join the project](https://telecominfraproject.com/apply-for-membership/) and especially to [get in touch with us](https://github.com/Telecominfraproject/oopt-gnpy/discussions).
(contributing)=
## Contributing
`gnpy` is looking for additional contributors, especially those with experience planning and maintaining large-scale, real-world mesh optical networks.
To get involved, please contact [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.
See the [Onboarding Guide](https://github.com/Telecominfraproject/gnpy/wiki/Onboarding-Guide) for specific details on code contributions, or just [upload patches to our Gerrit](https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html).
Here is [what we are currently working on](https://review.gerrithub.io/q/project:Telecominfraproject/oopt-gnpy+status:open).
## Project Background
Data Centers are built upon interchangeable, highly standardized node and network architectures rather than a sum of isolated solutions.
This also translates to optical networking.
It leads to a push in enabling multi-vendor optical network by disaggregating HW and SW functions and focusing on interoperability.
In this paradigm, the burden of responsibility for ensuring the performance of such disaggregated open optical systems falls on the operators.
Consequently, operators and vendors are collaborating in defining control models that can be readily used by off-the-shelf controllers.
However, node and network models are only part of the answer.
To take reasonable decisions, controllers need to incorporate logic to simulate and assess optical performance.
Hence, a vendor-independent optical quality estimator is required.
Given its vendor-agnostic nature, such an estimator needs to be driven by a consortium of operators, system and component suppliers.
Founded in February 2016, the Telecom Infra Project (TIP) is an engineering-focused initiative which is operator driven, but features collaboration across operators, suppliers, developers, integrators, and startups with the goal of disaggregating the traditional network deployment approach.
The groups ultimate goal is to help provide better connectivity for communities all over the world as more people come on-line and demand more bandwidth-intensive experiences like video, virtual reality and augmented reality.
Within TIP, the Open Optical Packet Transport (OOPT) project group is chartered with unbundling monolithic packet-optical network technologies in order to unlock innovation and support new, more flexible connectivity paradigms.
The key to unbundling is the ability to accurately plan and predict the performance of optical line systems based on an accurate simulation of optical parameters.
Under that OOPT umbrella, the Physical Simulation Environment (PSE) working group set out to disrupt the planning landscape by providing an open source simulation model which can be used freely across multiple vendor implementations.
## TIP OOPT/PSE & PSE WG Charter
We believe that openly sharing ideas, specifications, and other intellectual property is the key to maximizing innovation and reducing complexity
TIP OOPT/PSE's goal is to build an end-to-end simulation environment which defines the network models of the optical device transfer functions and their parameters.
This environment will provide validation of the optical performance requirements for the TIP OLS building blocks.
- The model may be approximate or complete depending on the network complexity.
Each model shall be validated against the proposed network scenario.
- The environment must be able to process network models from multiple vendors, and also allow users to pick any implementation in an open source framework.
- The PSE will influence and benefit from the innovation of the DTC, API, and OLS working groups.
- The PSE represents a step along the journey towards multi-layer optimization.
License
-------
GNPy is distributed under a standard BSD 3-Clause License.

View File

@@ -1848,15 +1848,3 @@ month={Sept},}
title = {Telecom Infra Project},
url = {https://www.telecominfraproject.com},
}
@ARTICLE{DAmicoJLT2022,
author={DAmico, 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}
}

View File

@@ -1,270 +0,0 @@
.. _concepts:
Simulating networks with GNPy
=============================
Running simulations with GNPy requires three pieces of information:
- the :ref:`network topology<concepts-topology>`, which describes how the network looks like, what are the fiber lengths, what amplifiers are used, etc.,
- the :ref:`equipment library<concepts-equipment>`, which holds machine-readable datasheets of the equipment used in the network,
- the :ref:`simulation options<concepts-simulation>` holding instructions about what to simulate, and under which conditions.
.. _concepts-topology:
Network Topology
----------------
The *topology* acts as a "digital self" of the simulated network.
When given a network topology, GNPy can either run a specific simulation as-is, or it can *optimize* the topology before performing the simulation.
A network topology for GNPy is often a generic, mesh network.
This enables GNPy to take into consideration the current spectrum allocation as well as availability and resiliency considerations.
When the time comes to run a particular *propagation* of a signal and its impairments are computed, though, a linear path through the network is used.
For this purpose, the *path* through the network refers to an ordered, acyclic sequence of *nodes* that are processed.
This path is directional, and all "GNPy elements" along the path match the unidirectional part of a real-world network equipment.
.. note::
In practical terms, an amplifier in GNPy refers to an entity with a single input port and a single output port.
A real-world inline EDFA enclosed in a single chassis will be therefore represented as two GNPy-level amplifiers.
The network topology contains not just the physical topology of the network, but also references to the :ref:`equipment library<concepts-equipment>` and a set of *operating parameters* for each entity.
These parameters include the **fiber length** of each fiber, the connector **attenutation losses**, or an amplifier's specific **gain setting**.
The topology is specified via :ref:`XLS files<excel>` or via :ref:`JSON<legacy-json>`.
.. _complete-vs-incomplete:
Fully Specified vs. Partially Designed Networks
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Let's consider a simple triangle topology with three :abbr:`PoPs (Points of Presence)` covering three cities:
.. graphviz::
:layout: neato
:align: center
graph "High-level topology with three PoPs" {
A -- B
B -- C
C -- A
}
In the real world, each city would probably host a ROADM and some transponders:
.. graphviz::
:layout: neato
:align: center
graph "Simplified topology with transponders" {
"ROADM A" [pos="2,2!"]
"ROADM B" [pos="4,2!"]
"ROADM C" [pos="3,1!"]
"Transponder A" [shape=box, pos="0,2!"]
"Transponder B" [shape=box, pos="6,2!"]
"Transponder C" [shape=box, pos="3,0!"]
"ROADM A" -- "ROADM B"
"ROADM B" -- "ROADM C"
"ROADM C" -- "ROADM A"
"Transponder A" -- "ROADM A"
"Transponder B" -- "ROADM B"
"Transponder C" -- "ROADM C"
}
GNPy simulation works by propagating the optical signal over a sequence of elements, which means that one has to add some preamplifiers and boosters.
The amplifiers are, by definition, unidirectional, so the graph becomes quite complex:
.. _topo-roadm-preamp-booster:
.. graphviz::
:layout: neato
:align: center
digraph "Preamps and boosters are explicitly modeled in GNPy" {
"ROADM A" [pos="2,4!"]
"ROADM B" [pos="6,4!"]
"ROADM C" [pos="4,0!"]
"Transponder A" [shape=box, pos="1,5!"]
"Transponder B" [shape=box, pos="7,5!"]
"Transponder C" [shape=box, pos="4,-1!"]
"Transponder A" -> "ROADM A"
"Transponder B" -> "ROADM B"
"Transponder C" -> "ROADM C"
"ROADM A" -> "Transponder A"
"ROADM B" -> "Transponder B"
"ROADM C" -> "Transponder C"
"Booster A C" [shape=triangle, orientation=-150, fixedsize=true, width=0.5, height=0.5, pos="2.2,3.2!", color=red, label=""]
"Preamp A C" [shape=triangle, orientation=0, fixedsize=true, width=0.5, height=0.5, pos="1.5,3.0!", color=red, label=""]
"ROADM A" -> "Booster A C"
"Preamp A C" -> "ROADM A"
"Booster A B" [shape=triangle, orientation=-90, fixedsize=true, width=0.5, height=0.5, pos="3,4.3!", color=red, fontcolor=red, labelloc=b, label="\N\n\n"]
"Preamp A B" [shape=triangle, orientation=90, fixedsize=true, width=0.5, height=0.5, pos="3,3.6!", color=red, fontcolor=red, labelloc=t, label="\n \N"]
"ROADM A" -> "Booster A B"
"Preamp A B" -> "ROADM A"
"Booster C B" [shape=triangle, orientation=-30, fixedsize=true, width=0.5, height=0.5, pos="4.7,0.9!", color=red, label=""]
"Preamp C B" [shape=triangle, orientation=120, fixedsize=true, width=0.5, height=0.5, pos="5.4,0.7!", color=red, label=""]
"ROADM C" -> "Booster C B"
"Preamp C B" -> "ROADM C"
"Booster C A" [shape=triangle, orientation=30, fixedsize=true, width=0.5, height=0.5, pos="2.6,0.7!", color=red, label=""]
"Preamp C A" [shape=triangle, orientation=-30, fixedsize=true, width=0.5, height=0.5, pos="3.3,0.9!", color=red, label=""]
"ROADM C" -> "Booster C A"
"Preamp C A" -> "ROADM C"
"Booster B A" [shape=triangle, orientation=90, fixedsize=true, width=0.5, height=0.5, pos="5,3.6!", labelloc=t, color=red, fontcolor=red, label="\n\N "]
"Preamp B A" [shape=triangle, orientation=-90, fixedsize=true, width=0.5, height=0.5, pos="5,4.3!", labelloc=b, color=red, fontcolor=red, label="\N\n\n"]
"ROADM B" -> "Booster B A"
"Preamp B A" -> "ROADM B"
"Booster B C" [shape=triangle, orientation=-180, fixedsize=true, width=0.5, height=0.5, pos="6.5,3.0!", color=red, label=""]
"Preamp B C" [shape=triangle, orientation=-20, fixedsize=true, width=0.5, height=0.5, pos="5.8,3.2!", color=red, label=""]
"ROADM B" -> "Booster B C"
"Preamp B C" -> "ROADM B"
"Booster A C" -> "Preamp C A"
"Booster A B" -> "Preamp B A"
"Booster C A" -> "Preamp A C"
"Booster C B" -> "Preamp B C"
"Booster B C" -> "Preamp C B"
"Booster B A" -> "Preamp A B"
}
In many regions, the ROADMs are not placed physically close to each other, so the long-haul fiber links (:abbr:`OMS (Optical Multiplex Section)`) are split into individual spans (:abbr:`OTS (Optical Transport Section)`) by in-line amplifiers, resulting in an even more complicated topology graphs:
.. graphviz::
:layout: neato
:align: center
digraph "A subset of a real topology with inline amplifiers" {
"ROADM A" [pos="2,4!"]
"ROADM B" [pos="6,4!"]
"ROADM C" [pos="4,-3!"]
"Transponder A" [shape=box, pos="1,5!"]
"Transponder B" [shape=box, pos="7,5!"]
"Transponder C" [shape=box, pos="4,-4!"]
"Transponder A" -> "ROADM A"
"Transponder B" -> "ROADM B"
"Transponder C" -> "ROADM C"
"ROADM A" -> "Transponder A"
"ROADM B" -> "Transponder B"
"ROADM C" -> "Transponder C"
"Booster A C" [shape=triangle, orientation=-166, fixedsize=true, width=0.5, height=0.5, pos="2.2,3.2!", label=""]
"Preamp A C" [shape=triangle, orientation=0, fixedsize=true, width=0.5, height=0.5, pos="1.5,3.0!", label=""]
"ROADM A" -> "Booster A C"
"Preamp A C" -> "ROADM A"
"Booster A B" [shape=triangle, orientation=-90, fixedsize=true, width=0.5, height=0.5, pos="3,4.3!", label=""]
"Preamp A B" [shape=triangle, orientation=90, fixedsize=true, width=0.5, height=0.5, pos="3,3.6!", label=""]
"ROADM A" -> "Booster A B"
"Preamp A B" -> "ROADM A"
"Booster C B" [shape=triangle, orientation=-30, fixedsize=true, width=0.5, height=0.5, pos="4.7,-2.1!", label=""]
"Preamp C B" [shape=triangle, orientation=10, fixedsize=true, width=0.5, height=0.5, pos="5.4,-2.3!", label=""]
"ROADM C" -> "Booster C B"
"Preamp C B" -> "ROADM C"
"Booster C A" [shape=triangle, orientation=20, fixedsize=true, width=0.5, height=0.5, pos="2.6,-2.3!", label=""]
"Preamp C A" [shape=triangle, orientation=-30, fixedsize=true, width=0.5, height=0.5, pos="3.3,-2.1!", label=""]
"ROADM C" -> "Booster C A"
"Preamp C A" -> "ROADM C"
"Booster B A" [shape=triangle, orientation=90, fixedsize=true, width=0.5, height=0.5, pos="5,3.6!", label=""]
"Preamp B A" [shape=triangle, orientation=-90, fixedsize=true, width=0.5, height=0.5, pos="5,4.3!", label=""]
"ROADM B" -> "Booster B A"
"Preamp B A" -> "ROADM B"
"Booster B C" [shape=triangle, orientation=-180, fixedsize=true, width=0.5, height=0.5, pos="6.5,3.0!", label=""]
"Preamp B C" [shape=triangle, orientation=-20, fixedsize=true, width=0.5, height=0.5, pos="5.8,3.2!", label=""]
"ROADM B" -> "Booster B C"
"Preamp B C" -> "ROADM B"
"Inline A C 1" [shape=triangle, orientation=-166, fixedsize=true, width=0.5, pos="2.4,2.2!", label=" \N", color=red, fontcolor=red]
"Inline A C 2" [shape=triangle, orientation=-166, fixedsize=true, width=0.5, pos="2.6,1.2!", label=" \N", color=red, fontcolor=red]
"Inline A C 3" [shape=triangle, orientation=-166, fixedsize=true, width=0.5, pos="2.8,0.2!", label=" \N", color=red, fontcolor=red]
"Inline A C n" [shape=triangle, orientation=-166, fixedsize=true, width=0.5, pos="3.0,-1.1!", label=" \N", color=red, fontcolor=red]
"Booster A C" -> "Inline A C 1"
"Inline A C 1" -> "Inline A C 2"
"Inline A C 2" -> "Inline A C 3"
"Inline A C 3" -> "Inline A C n" [style=dotted]
"Inline A C n" -> "Preamp C A"
"Booster A B" -> "Preamp B A" [style=dotted]
"Booster C A" -> "Preamp A C" [style=dotted]
"Booster C B" -> "Preamp B C" [style=dotted]
"Booster B C" -> "Preamp C B" [style=dotted]
"Booster B A" -> "Preamp A B" [style=dotted]
}
In such networks, GNPy's autodesign features becomes very useful.
It is possible to connect ROADMs via "tentative links" which will be replaced by a sequence of actual fibers and specific amplifiers.
In other cases where the location of amplifier huts is already known, but the specific EDFA models have not yet been decided, one can put in amplifier placeholders and let GNPy assign the best amplifier.
.. _concepts-equipment:
The Equipment Library
---------------------
In order to produce an accurate simulation, GNPy needs to know the physical properties of each entity which affects the optical signal.
Entries in the equipment library correspond to actual real-world, tangible entities.
Unlike a typical :abbr:`NMS (Network Management System)`, GNPy considers not just the active :abbr:`NEs (Network Elements)` such as amplifiers and :abbr:`ROADMs (Reconfigurable Optical Add/Drop Multiplexers)`, but also the passive ones, such as the optical fiber.
As the signal propagates through the network, the largest source of optical impairments is the noise introduced from amplifiers.
An accurate description of the :abbr:`EDFA (Erbium-Doped Fiber Amplifier)` and especially its noise characteristics is required.
GNPy describes this property in terms of the **Noise Figure (NF)** of an amplifier model as a function of its operating point.
The amplifiers compensate power losses induced on the signal in the optical fiber.
The linear losses, however, are just one phenomenon of a multitude of effects that affect the signals in a long fiber run.
While a more detailed description is available :ref:`in the literature<physical-model>`, for the purpose of the equipment library, the description of the *optical fiber* comprises its **linear attenutation coefficient**, a set of parameters for the **Raman effect**, optical **dispersion**, etc.
Signals are introduced into the network via *transponders*.
The set of parameters that are required describe the physical properties of each supported *mode* of the transponder, including its **symbol rate**, spectral **width**, etc.
In the junctions of the network, *ROADMs* are used for spectrum routing.
GNPy currently does not take into consideration the spectrum filtering penalties of the :abbr:`WSSes (Wavelength Selective Switches)`, but the equipment library nonetheless contains a list of required parameters, such as the attenuation options, so that the network can be properly simulated.
.. _concepts-nf-model:
Amplifier Noise Figure Models
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
One of the key parameters of an amplifier is the method to use for computing the Noise Figure (NF).
GNPy supports several different noise models with varying level of accuracy.
When in doubt, contact your vendor's technical support and ask them to :ref:`contribute their equipment descriptions<extending-edfa>` to GNPy.
The most accurate noise models describe the resulting NF of an EDFA as a third-degree polynomial.
GNPy understands polynomials as a NF-yielding function of the :ref:`gain difference from the optimal gain<ext-nf-model-polynomial-NF>`, or as a function of the input power resulting in an incremental OSNR as used in :ref:`OpenROADM inline amplifiers<ext-nf-model-polynomial-OSNR-OpenROADM>` and :ref:`OpenROADM booster/preamps in the ROADMs<ext-nf-model-noise-mask-OpenROADM>`.
For scenarios where the vendor has not yet contributed an accurate EDFA NF description to GNPy, it is possible to approximate the characteristics via an operator-focused, min-max NF model.
.. _nf-model-min-max-NF:
Min-max NF
**********
This is an operator-focused model where performance is defined by the *minimal* and *maximal NF*.
These are especially suited to model a dual-coil EDFA with a VOA in between.
In these amplifiers, the minimal NF is achieved when the EDFA operates at its maximal (and usually optimal, in terms of flatness) gain.
The worst (maximal) NF applies when the EDFA operates at its minimal gain.
This model is suitable for use when the vendor has not provided a more accurate performance description of the EDFA.
Raman Approximation
*******************
While GNPy is fully Raman-aware, under certain scenarios it is useful to be able to run a simulation without an accurate Raman description.
For these purposes the :ref:`polynomial NF<ext-nf-model-polynomial-NF>` model with :math:`\text{a} = \text{b} = \text{c} = 0`, and :math:`\text{d} = NF` can be used.
.. _concepts-simulation:
Simulation
----------
When the network model has been instantiated and the physical properties and operational settings of the actual physical devices are known, GNPy can start simulating how the signal propagate through the optical fiber.
This set of input parameters include options such as the *spectrum allocation*, i.e., the number of channels and their spacing.
Various strategies for network optimization can be provided as well.

View File

@@ -31,17 +31,10 @@ sys.path.insert(0, os.path.abspath('../'))
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = ['sphinx.ext.autodoc',
'sphinx.ext.mathjax',
'sphinx.ext.githubpages',
'sphinxcontrib.bibtex',
'sphinx.ext.graphviz',
'myst_parser',
]
myst_enable_extensions = [
"deflist",
"dollarmath",
]
'sphinx.ext.mathjax',
'sphinx.ext.githubpages',
'sphinxcontrib.bibtex',
'pbr.sphinxext',]
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
@@ -57,15 +50,15 @@ master_doc = 'index'
# General information about the project.
project = 'gnpy'
copyright = '2018 - 2021, Telecom Infra Project - OOPT PSE Group'
author = 'Telecom Infra Project - OOPT PSE Group'
copyright = '2018, Telecom InfraProject - OOPT PSE Group'
author = 'Telecom InfraProject - OOPT PSE Group'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = 'en'
language = None
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
@@ -84,11 +77,18 @@ todo_include_todos = False
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
html_theme = 'alabaster'
html_theme_options = {
'logo': 'images/GNPy-logo.png',
'logo_name': False,
}
on_rtd = os.environ.get('READTHEDOCS') == 'True'
if on_rtd:
html_theme = 'default'
html_theme_options = {
'logo_only': True,
}
else:
html_theme = 'alabaster'
html_theme_options = {
'logo': 'images/GNPy-logo.png',
'logo_name': False,
}
html_logo = 'images/GNPy-logo.png'
@@ -150,7 +150,7 @@ latex_elements = {
# author, documentclass [howto, manual, or own class]).
latex_documents = [
(master_doc, 'gnpy.tex', 'gnpy Documentation',
'Telecom Infra Project - OOPT PSE Group', 'manual'),
'Telecom InfraProject - OOPT PSE Group', 'manual'),
]
@@ -181,7 +181,3 @@ autodoc_default_options = {
'private-members': True,
'show-inheritance': True,
}
graphviz_output_format = 'svg'
bibtex_bibfiles = ['biblio.bib']

View File

@@ -1,5 +1,3 @@
.. _excel:
Excel (XLS, XLSX) input files
=============================
@@ -123,17 +121,15 @@ and a fiber span from node3 to node6::
Eqpt sheet
----------
The equipment sheet (named "Eqpt") is optional.
If provided, it specifies types of boosters and preamplifiers for all ROADM degrees of all ROADM nodes, and for all ILA nodes.
This sheet contains twelve columns::
Eqt sheet is optional. It lists the amplifiers types and characteristics on each degree of the *Node A* line.
Eqpt sheet must contain twelve columns::
<-- east cable from a to z --> <-- west from z to a -->
Node A ; Node Z ; amp type ; att_in ; amp gain ; tilt ; att_out ; delta_p ; amp type ; att_in ; amp gain ; tilt ; att_out ; delta_p
If the sheet is present, it MUST have as many lines as there are egress directions of ROADMs defined in Links Sheet, and all ILAs.
If the sheet is present, it MUST have as many lines as egress directions of ROADMs defined in Links Sheet.
For example, consider the following list of links (A, B and C being a ROADM and amp# ILAs):
For example, consider the following list of links (A,B and C being a ROADM and amp# ILAs)
::
@@ -145,8 +141,8 @@ For example, consider the following list of links (A, B and C being a ROADM and
then Eqpt sheet should contain:
- one line for each ILAs: amp1, amp2, amp3
- one line for each one-degree ROADM (B and C in this example)
- two lines for each two-degree ROADM (just the ROADM A)
- one line for each degree 1 ROADMs B and C
- two lines for ROADM A which is a degree 2 ROADM
::
@@ -187,8 +183,7 @@ This generates a text file meshTopologyExampleV2_eqt_sheet.txt whose content ca
- *att_in* and *att_out* are not mandatory and are not used yet. They are the value of the attenuator at input and output of amplifier (in dB).
If filled they must contain positive numbers.
- **tilt**, in dB, is not mandatory. It is the target gain tilt over the full amplfifier bandwidth and is defined with regard to wavelength, i.e. negative tilt means lower gain
for higher wavelengths (lower frequencies). If not filled, the default value is 0.
- *tilt* --TODO--
- **delta_p**, in dBm, is not mandatory. If filled it is used to set the output target power per channel at the output of the amplifier, if power_mode is True. The output power is then set to power_dbm + delta_power.
@@ -201,7 +196,7 @@ This generates a text file meshTopologyExampleV2_eqt_sheet.txt whose content ca
Service sheet
-------------
Service sheet is optional. It lists the services for which path and feasibility must be computed with ``gnpy-path-request``.
Service sheet is optional. It lists the services for which path and feasibility must be computed with ``gnpy-path_request``.
Service sheet must contain 11 columns::

View File

@@ -1,176 +0,0 @@
.. _extending:
Extending GNPy with vendor-specific data
========================================
GNPy ships with an :ref:`equipment library<concepts-equipment>` containing machine-readable datasheets of networking equipment.
Vendors who are willing to contribute descriptions of their supported products are encouraged to `submit a patch <https://review.gerrithub.io/Documentation/intro-gerrit-walkthrough-github.html>`__ -- or just :ref:`get in touch with us directly<contributing>`.
This chapter discusses option for modeling performance of :ref:`EDFA amplifiers<extending-edfa>`, :ref:`Raman amplifiers<extending-raman>`, :ref:`transponders<extending-transponder>` and :ref:`ROADMs<extending-roadm>`.
.. _extending-edfa:
EDFAs
-----
An accurate description of the :abbr:`EDFA (Erbium-Doped Fiber Amplifier)` and especially its noise characteristics is required.
GNPy describes this property in terms of the **Noise Figure (NF)** of an amplifier model as a function of its operating point.
GNPy supports several different :ref:`noise models<concepts-nf-model>`, and vendors are encouraged to pick one which describes performance of their equipment most accurately.
.. _ext-nf-model-polynomial-NF:
Polynomial NF
*************
This model computes the NF as a function of the difference between the optimal gain and the current gain.
The NF is expressed as a third-degree polynomial:
.. math::
f(x) &= \text{a}x^3 + \text{b}x^2 + \text{c}x + \text{d}
\text{NF} &= f(G - G_\text{max})
This model can be also used for fixed-gain fixed-NF amplifiers.
In that case, use:
.. math::
a = b = c &= 0
d &= \text{NF}
.. _ext-nf-model-polynomial-OSNR-OpenROADM:
Polynomial OSNR (OpenROADM-style for inline amplifier)
******************************************************
This model is useful for amplifiers compliant to the OpenROADM specification for ILA (an in-line amplifier).
The amplifier performance is evaluated via its incremental OSNR, which is a function of the input power.
.. math::
\text{OSNR}_\text{inc}(P_\text{in}) = \text{a}P_\text{in}^3 + \text{b}P_\text{in}^2 + \text{c}P_\text{in} + \text{d}
.. _ext-nf-model-noise-mask-OpenROADM:
Noise mask (OpenROADM-style for combined preamp and booster)
************************************************************
Unlike GNPy which simluates the preamplifier and the booster separately as two amplifiers for best accuracy, the OpenROADM specification mandates a certain performance level for a combination of these two amplifiers.
For the express path, the effective noise mask comprises the preamplifier and the booster.
When terminating a channel, the same effective noise mask is mandated for a combination of the preamplifier and the drop stage.
GNPy emulates this specification via two special NF models:
- The ``openroadm_preamp`` NF model for preamplifiers.
This NF model provides all of the linear impairments to the signal, including those which are incured by the booster in a real network.
- The ``openroadm_booster`` NF model is a special "zero noise" faux amplifier in place of the booster.
.. _ext-nf-model-min-max-NF:
Min-max NF
**********
When the vendor prefers not to share the amplifier description in full detail, GNPy also supports describing the NF characteristics via the *minimal* and *maximal NF*.
This approximates a more accurate polynomial description reasonably well for some models of a dual-coil EDFA with a VOA in between.
In these amplifiers, the minimal NF is achieved when the EDFA operates at its maximal (and usually optimal, in terms of flatness) gain.
The worst (maximal) NF applies when the EDFA operates at the minimal gain.
.. _ext-nf-model-dual-stage-amplifier:
Dual-stage
**********
Dual-stage amplifier combines two distinct amplifiers.
Vendors which provide an accurate description of their preamp and booster stages separately can use the dual-stage model for an aggregate description of the whole amplifier.
.. _ext-nf-model-advanced:
Advanced Specification
**********************
The amplifier performance can be further described in terms of gain ripple, NF ripple, and the dynamic gain tilt.
When provided, the amplifier characteristic is fine-tuned as a function of carrier frequency.
.. _extending-raman:
Raman Amplifiers
----------------
An accurate simulation of Raman amplification requires knowledge of:
* the *power* and *wavelength* of all Raman pumping lasers,
* the *direction*, whether it is co-propagating or counter-propagating,
* the Raman efficiency of the fiber,
* the fiber temperature.
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`.
This is also useful to quickly approximate a hybrid EDFA+Raman amplifier.
.. _extending-transponder:
Transponders
------------
Since transponders are usually capable of operating in a variety of modes, these are described separately.
A *mode* usually refers to a particular performance point that is defined by a combination of the symbol rate, modulation format, and :abbr:`FEC (Forward Error Correction)`.
The following data are required for each mode:
``bit-rate``
Data bit rate, in :math:`\text{Gbits}\times s^{-1}`.
``baud-rate``
Symbol modulation rate, in :math:`\text{Gbaud}`.
``required-osnr``
Minimal allowed OSNR for the receiver.
``tx-osnr``
Initial OSNR at the transmitter's output.
``grid-spacing``
Minimal grid spacing, i.e., an effective channel spectral bandwidth.
In :math:`\text{Hz}`.
``tx-roll-off``
Roll-off parameter (:math:`\beta`) of the TX pulse shaping filter.
This assumes a raised-cosine filter.
``rx-power-min`` and ``rx-power-max``
The allowed range of power at the receiver.
In :math:`\text{dBm}`.
``cd-max``
Maximal allowed Chromatic Dispersion (CD).
In :math:`\text{ps}/\text{nm}`.
``pmd-max``
Maximal allowed Polarization Mode Dispersion (PMD).
In :math:`\text{ps}`.
``cd-penalty``
*Work-in-progress.*
Describes the increase of the requires GSNR as the :abbr:`CD (Chromatic Dispersion)` deteriorates.
``dgd-penalty``
*Work-in-progress.*
Describes the increase of the requires GSNR as the :abbr:`DGD (Differential Group Delay)` deteriorates.
``pmd-penalty``
*Work-in-progress.*
Describes the increase of the requires GSNR as the :abbr:`PMD (Polarization Mode Dispersion)` deteriorates.
GNPy does not directly track the FEC performance, so the type of chosen FEC is likely indicated in the *name* of the selected transponder mode alone.
.. _extending-roadm:
ROADMs
------
In a :abbr:`ROADM (Reconfigurable Add/Drop Multiplexer)`, GNPy simulates the impairments of the preamplifiers and boosters of line degrees :ref:`separately<topo-roadm-preamp-booster>`.
The set of parameters for each ROADM model therefore includes:
``add-drop-osnr``
OSNR penalty introduced by the Add and Drop stages of this ROADM type.
``target-channel-out-power``
Per-channel target TX power towards the egress amplifier.
Within GNPy, a ROADM is expected to attenuate any signal that enters the ROADM node to this level.
This can be overridden on a per-link in the network topology.
``pmd``
Polarization mode dispersion (PMD) penalty of the express path.
In :math:`\text{ps}`.
Provisions are in place to define the list of all allowed booster and preamplifier types.
This is useful for specifying constraints on what amplifier modules fit into ROADM chassis, and when using fully disaggregated ROADM topologies as well.

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@@ -8,16 +8,11 @@ in real-world mesh optical networks. It is based on the Gaussian Noise Model.
.. toctree::
:maxdepth: 4
intro
concepts
install
json
excel
extending
about-project
model
gnpy-api
release-notes
Indices and tables
==================

View File

@@ -38,7 +38,7 @@ Using Python on your computer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
**Note**: `gnpy` supports Python 3 only. Python 2 is not supported.
`gnpy` requires Python ≥3.8
`gnpy` requires Python ≥3.6
**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 3.8.0 :: Anaconda, Inc.
Python 3.6.5 :: Anaconda, Inc.
.. _install-pip:
@@ -98,7 +98,7 @@ of the `gnpy` repo and install it with:
$ git clone https://github.com/Telecominfraproject/oopt-gnpy # clone the repo
$ cd oopt-gnpy
$ pip install --editable . # note the trailing dot
$ python setup.py develop
To test that `gnpy` was successfully installed, you can run this command. If it
executes without a ``ModuleNotFoundError``, you have successfully installed

View File

@@ -1,94 +0,0 @@
.. _intro:
Introduction
============
``gnpy`` is a library for building route planning and optimization tools.
It ships with a number of example programs. Release versions will ship with
fully-functional programs.
**Note**: *If you are a network operator or involved in route planning and
optimization for your organization, please contact project maintainer Jan
Kundrát <jkt@jankundrat.com>. gnpy is looking for users with
specific, delineated use cases to drive requirements for future
development.*
This example demonstrates how GNPy can be used to check the expected SNR at the end of the line by varying the channel input power:
.. image:: https://telecominfraproject.github.io/oopt-gnpy/docs/images/transmission_main_example.svg
:width: 100%
:align: left
:alt: Running a simple simulation example
By default, this script operates on a single span network defined in
`gnpy/example-data/edfa_example_network.json <gnpy/example-data/edfa_example_network.json>`_
You can specify a different network at the command line as follows. For
example, to use the CORONET Global network defined in
`gnpy/example-data/CORONET_Global_Topology.json <gnpy/example-data/CORONET_Global_Topology.json>`_:
.. code-block:: shell-session
$ gnpy-transmission-example $(gnpy-example-data)/CORONET_Global_Topology.json
It is also possible to use an Excel file input (for example
`gnpy/example-data/CORONET_Global_Topology.xls <gnpy/example-data/CORONET_Global_Topology.xls>`_).
The Excel file will be processed into a JSON file with the same prefix.
Further details about the Excel data structure are available `in the documentation <docs/excel.rst>`__.
The main transmission example will calculate the average signal OSNR and SNR
across network elements (transceiver, ROADMs, fibers, and amplifiers)
between two transceivers selected by the user. Additional details are provided by doing ``gnpy-transmission-example -h``. (By default, for the CORONET Global
network, it will show the transmission of spectral information between Abilene and Albany)
This script calculates the average signal OSNR = |OSNR| and SNR = |SNR|.
.. |OSNR| replace:: P\ :sub:`ch`\ /P\ :sub:`ase`
.. |SNR| replace:: P\ :sub:`ch`\ /(P\ :sub:`nli`\ +\ P\ :sub:`ase`)
|Pase| is the amplified spontaneous emission noise, and |Pnli| the non-linear
interference noise.
.. |Pase| replace:: P\ :sub:`ase`
.. |Pnli| replace:: P\ :sub:`nli`
Further Instructions for Use
----------------------------
Simulations are driven by a set of `JSON <docs/json.rst>`__ or `XLS <docs/excel.rst>`__ files.
The ``gnpy-transmission-example`` script propagates a spectrum of channels at 32 Gbaud, 50 GHz spacing and 0 dBm/channel.
Launch power can be overridden by using the ``--power`` argument.
Spectrum information is not yet parametrized but can be modified directly in the ``eqpt_config.json`` (via the ``SpectralInformation`` -SI- structure) to accommodate any baud rate or spacing.
The number of channel is computed based on ``spacing`` and ``f_min``, ``f_max`` values.
An experimental support for Raman amplification is available:
.. code-block:: shell-session
$ gnpy-transmission-example \
$(gnpy-example-data)/raman_edfa_example_network.json \
--sim $(gnpy-example-data)/sim_params.json --show-channels
Configuration of Raman pumps (their frequencies, power and pumping direction) is done via the `RamanFiber element in the network topology <gnpy/example-data/raman_edfa_example_network.json>`_.
General numeric parameters for simulation control are provided in the `gnpy/example-data/sim_params.json <gnpy/example-data/sim_params.json>`_.
Use ``gnpy-path-request`` to request several paths at once:
.. code-block:: shell-session
$ cd $(gnpy-example-data)
$ gnpy-path-request -o output_file.json \
meshTopologyExampleV2.xls meshTopologyExampleV2_services.json
This program operates on a network topology (`JSON <docs/json.rst>`__ or `Excel <docs/excel.rst>`__ format), processing the list of service requests (JSON or XLS again).
The service requests and reply formats are based on the `draft-ietf-teas-yang-path-computation-01 <https://tools.ietf.org/html/draft-ietf-teas-yang-path-computation-01>`__ with custom extensions (e.g., for transponder modes).
An example of the JSON input is provided in file `service-template.json`, while results are shown in `path_result_template.json`.
Important note: ``gnpy-path-request`` is not a network dimensionning tool: each service does not reserve spectrum, or occupy ressources such as transponders. It only computes path feasibility assuming the spectrum (between defined frequencies) is loaded with "nb of channels" spaced by "spacing" values as specified in the system parameters input in the service file, each cannel having the same characteristics in terms of baudrate, format,... as the service transponder. The transceiver element acts as a "logical starting/stopping point" for the spectral information propagation. At that point it is not meant to represent the capacity of add drop ports.
As a result transponder type is not part of the network info. it is related to the list of services requests.
The current version includes a spectrum assigment features that enables to compute a candidate spectrum assignment for each service based on a first fit policy. Spectrum is assigned based on service specified spacing value, path_bandwidth value and selected mode for the transceiver. This spectrum assignment includes a basic capacity planning capability so that the spectrum resource is limited by the frequency min and max values defined for the links. If the requested services reach the link spectrum capacity, additional services feasibility are computed but marked as blocked due to spectrum reason.
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.

View File

@@ -1,5 +1,3 @@
.. _legacy-json:
JSON Input Files
================
@@ -9,11 +7,13 @@ Some data (such as network topology or the service requests) can be also passed
Equipment Library
-----------------
Design and transmission parameters are defined in a dedicated json file.
By default, this information is read from `gnpy/example-data/eqpt_config.json <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/eqpt_config.json>`_.
This file defines the equipment libraries that can be customized (EDFAs, fibers, and transceivers).
Design and transmission parameters are defined in a dedicated json file. By
default, this information is read from `gnpy/example-data/eqpt_config.json
<gnpy/example-data/eqpt_config.json>`_. This file defines the equipment libraries that
can be customized (EDFAs, fibers, and transceivers).
It also defines the simulation parameters (spans, ROADMs, and the spectral information to transmit.)
It also defines the simulation parameters (spans, ROADMs, and the spectral
information to transmit.)
EDFA
~~~~
@@ -21,20 +21,9 @@ EDFA
The EDFA equipment library is a list of supported amplifiers. New amplifiers
can be added and existing ones removed. Three different noise models are available:
1. ``'type_def': 'variable_gain'`` is a simplified model simulating a 2-coil EDFA with internal, input and output VOAs.
The NF vs gain response is calculated accordingly based on the input parameters: ``nf_min``, ``nf_max``, and ``gain_flatmax``.
It is not a simple interpolation but a 2-stage NF calculation.
2. ``'type_def': 'fixed_gain'`` is a fixed gain model.
`NF == Cte == nf0` if `gain_min < gain < gain_flatmax`
3. ``'type_def': 'openroadm'`` models the incremental OSNR contribution as a function of input power.
It is suitable for inline amplifiers that conform to the OpenROADM specification.
The input parameters are coefficients of the :ref:`third-degree polynomial<ext-nf-model-polynomial-OSNR-OpenROADM>`.
4. ``'type_def': 'openroadm_preamp'`` and ``openroadm_booster`` approximate the :ref:`preamp and booster within an OpenROADM network<ext-nf-model-noise-mask-OpenROADM>`.
No extra parameters specific to the NF model are accepted.
5. ``'type_def': 'advanced_model'`` is an advanced model.
A detailed JSON configuration file is required (by default `gnpy/example-data/std_medium_gain_advanced_config.json <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/std_medium_gain_advanced_config.json>`_).
It uses a 3rd order polynomial where NF = f(gain), NF_ripple = f(frequency), gain_ripple = f(frequency), N-array dgt = f(frequency).
Compared to the previous models, NF ripple and gain ripple are modelled.
1. ``'type_def': 'variable_gain'`` is a simplified model simulating a 2-coil EDFA with internal, input and output VOAs. The NF vs gain response is calculated accordingly based on the input parameters: ``nf_min``, ``nf_max``, and ``gain_flatmax``. It is not a simple interpolation but a 2-stage NF calculation.
2. ``'type_def': 'fixed_gain'`` is a fixed gain model. `NF == Cte == nf0` if `gain_min < gain < gain_flatmax`
3. ``'type_def': None`` is an advanced model. A detailed JSON configuration file is required (by default `gnpy/example-data/std_medium_gain_advanced_config.json <gnpy/example-data/std_medium_gain_advanced_config.json>`_). It uses a 3rd order polynomial where NF = f(gain), NF_ripple = f(frequency), gain_ripple = f(frequency), N-array dgt = f(frequency). Compared to the previous models, NF ripple and gain ripple are modelled.
For all amplifier models:
@@ -44,7 +33,7 @@ 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 |
@@ -61,98 +50,22 @@ 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_slope`` | (number) | In :math:`s \times m^{-1} \times m^{-1} |
| | | \times m^{-1}` |
+------------------------------+-----------------+------------------------------------------------+
| ``dispersion_per_frequency`` | (dict) | Dictionary of dispersion values evaluated at |
| | | various frequencies, as follows: |
| | | ``{"value": [], "frequency": []}``. |
| | | ``value`` in |
| | | :math:`s \times m^{-1} \times m^{-1}` and |
| | | ``frequency`` in Hz. |
+------------------------------+-----------------+------------------------------------------------+
| ``effective_area`` | (number) | Effective area of the fiber (not just |
| | | the MFD circle). This is the |
| | | :math:`A_{eff}`, see e.g., the |
| | | `Corning whitepaper on MFD/EA`_. |
| | | Specified in :math:`m^{2}`. |
+------------------------------+-----------------+------------------------------------------------+
| ``gamma`` | (number) | Coefficient :math:`\gamma = 2\pi\times |
| | | n^2/(\lambda*A_{eff})`. |
| | | If not provided, this will be derived |
| | | from the ``effective_area`` |
| | | :math:`A_{eff}`. |
| | | In :math:`w^{-1} \times m^{-1}`. |
| | | This quantity is evaluated at the |
| | | reference frequency and it is scaled |
| | | along frequency accordingly to the |
| | | effective area scaling. |
+------------------------------+-----------------+------------------------------------------------+
| ``pmd_coef`` | (number) | Polarization mode dispersion (PMD) |
| | | coefficient. In |
| | | :math:`s\times\sqrt{m}^{-1}`. |
+------------------------------+-----------------+------------------------------------------------+
| ``lumped_losses`` | (array) | Places along the fiber length with extra |
| | | losses. Specified as a loss in dB at |
| | | each relevant position (in km): |
| | | ``{"position": 10, "loss": 1.5}``) |
+------------------------------+-----------------+------------------------------------------------+
| ``raman_coefficient`` | (dict) | The fundamental parameter that describes |
| | | the regulation of the power transfer |
| | | between channels during fiber propagation |
| | | is the Raman gain coefficient (see |
| | | :cite:`DAmicoJLT2022` for further |
| | | details); :math:`f_{ref}` represents the |
| | | pump reference frequency used for the |
| | | Raman gain coefficient profile |
| | | measurement ("reference_frequency"), |
| | | :math:`\Delta f` is the frequency shift |
| | | between the pump and the specific Stokes |
| | | wave, the Raman gain coefficient |
| | | in terms of optical power |
| | | :math:`g_0`, expressed in |
| | | :math:`1/(m\;W)`. |
| | | Default values measured for a SSMF are |
| | | considered when not specified. |
+------------------------------+-----------------+------------------------------------------------+
.. _Corning whitepaper on MFD/EA: https://www.corning.com/microsites/coc/oem/documents/specialty-fiber/WP7071-Mode-Field-Diam-and-Eff-Area.pdf
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]}``).
+----------------------+-----------+-----------------------------------------+
| field | type | description |
+======================+===========+=========================================+
| ``type_variety`` | (string) | a unique name to ID the fiber in the |
| | | JSON or Excel template topology input |
| | | file |
+----------------------+-----------+-----------------------------------------+
| ``dispersion`` | (number) | (s.m-1.m-1) |
+----------------------+-----------+-----------------------------------------+
| ``dispersion_slope`` | (number) | (s.m-1.m-1.m-1) |
+----------------------+-----------+-----------------------------------------+
| ``gamma`` | (number) | 2pi.n2/(lambda*Aeff) (w-1.m-1) |
+----------------------+-----------+-----------------------------------------+
| ``pmd_coef`` | (number) | Polarization mode dispersion (PMD) |
| | | coefficient. (s.sqrt(m)-1) |
+----------------------+-----------+-----------------------------------------+
Transceiver
~~~~~~~~~~~
@@ -160,7 +73,7 @@ Transceiver
The transceiver equipment library is a list of supported transceivers. New
transceivers can be added and existing ones removed at will by the user. It is
used to determine the service list path feasibility when running the
``gnpy-path-request`` script.
`path_request_run.py routine <gnpy/example-data/path_request_run.py>`_.
+----------------------+-----------+-----------------------------------------+
| field | type | description |
@@ -169,7 +82,7 @@ used to determine the service list path feasibility when running the
| | | the JSON or Excel template topology |
| | | input file |
+----------------------+-----------+-----------------------------------------+
| ``frequency`` | (number) | Min/max central channel frequency. |
| ``frequency`` | (number) | Min/max as below. |
+----------------------+-----------+-----------------------------------------+
| ``mode`` | (number) | A list of modes supported by the |
| | | transponder. New modes can be added at |
@@ -180,197 +93,68 @@ used to determine the service list path feasibility when running the
The modes are defined as follows:
+----------------------------+-----------+-----------------------------------------+
| field | type | description |
+============================+===========+=========================================+
| ``format`` | (string) | a unique name to ID the mode |
+----------------------------+-----------+-----------------------------------------+
| ``baud_rate`` | (number) | in Hz |
+----------------------------+-----------+-----------------------------------------+
| ``OSNR`` | (number) | min required OSNR in 0.1nm (dB) |
+----------------------------+-----------+-----------------------------------------+
| ``bit_rate`` | (number) | in bit/s |
+----------------------------+-----------+-----------------------------------------+
| ``roll_off`` | (number) | Pure number between 0 and 1. TX signal |
| | | roll-off shape. Used by Raman-aware |
| | | simulation code. |
+----------------------------+-----------+-----------------------------------------+
| ``tx_osnr`` | (number) | In dB. OSNR out from transponder. |
+----------------------------+-----------+-----------------------------------------+
| ``equalization_offset_db`` | (number) | In dB. Deviation from the per channel |
| | | equalization target in ROADM for this |
| | | type of transceiver. |
+----------------------------+-----------+-----------------------------------------+
| ``penalties`` | (list) | list of impairments as described in |
| | | impairment table. |
+----------------------------+-----------+-----------------------------------------+
| ``cost`` | (number) | Arbitrary unit |
+----------------------------+-----------+-----------------------------------------+
+----------------------+-----------+-----------------------------------------+
| field | type | description |
+======================+===========+=========================================+
| ``format`` | (string) | a unique name to ID the mode |
+----------------------+-----------+-----------------------------------------+
| ``baud_rate`` | (number) | in Hz |
+----------------------+-----------+-----------------------------------------+
| ``OSNR`` | (number) | min required OSNR in 0.1nm (dB) |
+----------------------+-----------+-----------------------------------------+
| ``bit_rate`` | (number) | in bit/s |
+----------------------+-----------+-----------------------------------------+
| ``roll_off`` | (number) | Pure number between 0 and 1. TX signal |
| | | roll-off shape. Used by Raman-aware |
| | | simulation code. |
+----------------------+-----------+-----------------------------------------+
| ``tx_osnr`` | (number) | In dB. OSNR out from transponder. |
+----------------------+-----------+-----------------------------------------+
| ``cost`` | (number) | Arbitrary unit |
+----------------------+-----------+-----------------------------------------+
Penalties are linearly interpolated between given points and set to 'inf' outside interval.
The accumulated penalties are substracted to the path GSNR before comparing with the min required OSNR.
The penalties per impairment type are defined as a list of dict (impairment type - penalty values) as follows:
Simulation parameters
~~~~~~~~~~~~~~~~~~~~~
+-----------------------------+-----------+-----------------------------------------------+
| field | type | description |
+=============================+===========+===============================================+
| ``chromatic_dispersion`` or | (number) | In ps/nm/. Value of chromatic dispersion. |
| ``pdl`` or | | In dB. Value of polarization dependant loss. |
| ``pmd`` | (string) | In ps. Value of polarization mode dispersion. |
+-----------------------------+-----------+-----------------------------------------------+
| ``penalty_value`` | (number) | in dB. Penalty on the transceiver min OSNR |
| | | corresponding to the impairment level |
+-----------------------------+-----------+-----------------------------------------------+
Auto-design automatically creates EDFA amplifier network elements when they are
missing, after a fiber, or between a ROADM and a fiber. This auto-design
functionality can be manually and locally deactivated by introducing a ``Fused``
network element after a ``Fiber`` or a ``Roadm`` that doesn't need amplification.
The amplifier is chosen in the EDFA list of the equipment library based on
gain, power, and NF criteria. Only the EDFA that are marked
``'allowed_for_design': true`` are considered.
for example:
.. code-block:: json
"penalties": [{
"chromatic_dispersion": 360000,
"penalty_value": 0.5
}, {
"pmd": 110,
"penalty_value": 0.5
}
]
ROADM
~~~~~
The user can only modify the value of existing parameters:
+-------------------------------+-----------+----------------------------------------------------+
| field | type | description |
+===============================+===========+====================================================+
| ``target_pch_out_db`` | (number) | Default :ref:`equalization strategy<equalization>` |
| or | | for this ROADM type. |
| ``target_psd_out_mWperGHz`` | | |
| or | | Auto-design sets the ROADM egress channel |
| ``target_out_mWperSlotWidth`` | | power. This reflects typical control loop |
| (mutually exclusive) | | algorithms that adjust ROADM losses to |
| | | equalize channels (e.g., coming from |
| | | different ingress direction or add ports). |
| | | |
| | | These values are used as defaults when no |
| | | overrides are set per each ``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 |
| | | are allowed for auto-design within ROADM's |
| | | line degrees. |
| | | |
| | | If no booster should be placed on a degree, |
| | | insert a ``Fused`` node on the degree |
| | | output. |
+-------------------------------+-----------+----------------------------------------------------+
Global parameters
-----------------
The following options are still defined in ``eqpt_config.json`` for legacy reasons, but
they do not correspond to tangible network devices.
Auto-design automatically creates EDFA amplifier network elements when they are missing, after a fiber, or between a ROADM and a fiber.
This auto-design functionality can be manually and locally deactivated by introducing a ``Fused`` network element after a ``Fiber`` or a ``Roadm`` that doesn't need amplification.
The amplifier is chosen in the EDFA list of the equipment library based on gain, power, and NF criteria.
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. |
+---------------------------------------------+-----------+---------------------------------------------+
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.
Span
~~~~
Span configuration is not a list (which may change in later releases) and the user can only modify the value of existing parameters:
Span configuration is not a list (which may change
in later releases) and the user can only modify the value of existing
parameters:
+-------------------------------------+-----------+---------------------------------------------+
| field | type | description |
+=====================================+===========+=============================================+
| ``power_mode`` | (boolean) | If false, **gain mode**. In the gain mode, |
| | | only gain settings are used for |
| | | propagation, and ``delta_p`` is ignored. |
| | | If no ``gain_target`` is set in an |
| | | amplifier, auto-design computes one |
| | | according to the ``delta_power_range`` |
| | | optimisation range. |
| | | The gain mode |
| | | is recommended if all the amplifiers |
| | | have already consistent gain settings in |
| | | the topology input file. |
| | | |
| | | If true, **power mode**. In the power mode, |
| | | only the ``delta_p`` is used for |
| | | propagation, and ``gain_target`` is |
| | | ignored. |
| | | 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. |
| ``power_mode`` | (boolean) | If false, gain mode. Auto-design sets |
| | | amplifier gain = preceding span loss, |
| | | unless the amplifier exists and its |
| | | gain > 0 in the topology input JSON. |
| | | If true, power mode (recommended for |
| | | auto-design and power sweep.) |
| | | Auto-design sets amplifier power |
| | | according to delta_power_range. If the |
| | | amplifier exists with gain > 0 in the |
| | | topology JSON input, then its gain is |
| | | translated into a power target/channel. |
| | | Moreover, when performing a power sweep |
| | | (see ``power_range_db`` in the SI |
| | | configuration library) the power sweep |
| | | is performed w/r/t this power target, |
| | | regardless of preceding amplifiers |
| | | power saturation/limitations. |
+-------------------------------------+-----------+---------------------------------------------+
| ``delta_power_range_db`` | (number) | Auto-design only, power-mode |
| | | only. Specifies the [min, max, step] |
@@ -472,26 +256,55 @@ Span configuration is not a list (which may change in later releases) and the us
}
}
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 |
| | | power. This reflects typical control loop |
| | | algorithms that adjust ROADM losses to |
| | | equalize channels (eg coming from different |
| | | ingress direction or add ports) |
| | | This is the default value |
| | | Roadm/params/target_pch_out_db if no value |
| | | is given in the ``Roadm`` element in the |
| | | topology input description. |
| | | This default value is ignored if a |
| | | params/target_pch_out_db value is input in |
| | | the topology for a given ROADM. |
+--------------------------+-----------+---------------------------------------------+
| ``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 |
| | | are allowed for auto-design within ROADM's |
| | | line degrees. |
| | | |
| | | If no booster should be placed on a degree, |
| | | insert a ``Fused`` node on the degree |
| | | output. |
+--------------------------+-----------+---------------------------------------------+
SpectralInformation
~~~~~~~~~~~~~~~~~~~
GNPy requires a description of all channels that are propagated through the network.
This block defines a reference channel (target input power in spans, nb of channels) which is used to design the network or correct the settings.
It may be updated with different options --power.
It also defines the channels to be propagated for the gnpy-transmission-example script unless a different definition is provided with ``--spectrum`` option.
Flexgrid channel partitioning is available since the 2.7 release via the extra ``--spectrum`` option.
In the simplest case, homogeneous channel allocation can be defined via the ``SpectralInformation`` construct which defines a spectrum of N identical carriers:
The user can only modify the value of existing parameters. It defines a spectrum of N
identical carriers. 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.
+----------------------+-----------+-------------------------------------------+
| field | type | description |
+======================+===========+===========================================+
| ``f_min``, | (number) | In Hz. Define spectrum boundaries. Note |
| ``f_max`` | | that due to backward compatibility, the |
| | | first channel central frequency is placed |
| | | at :math:`f_{min} + spacing` and the last |
| | | one at :math:`f_{max}`. |
| ``f_min``, | (number) | In Hz. Carrier min max excursion. |
| ``f_max`` | | |
+----------------------+-----------+-------------------------------------------+
| ``baud_rate`` | (number) | In Hz. Simulated baud rate. |
+----------------------+-----------+-------------------------------------------+
@@ -503,21 +316,11 @@ In the simplest case, homogeneous channel allocation can be defined via the ``Sp
+----------------------+-----------+-------------------------------------------+
| ``tx_osnr`` | (number) | In dB. OSNR out from transponder. |
+----------------------+-----------+-------------------------------------------+
| ``power_dbm`` | (number) | In dBm. Target input power in spans to |
| | | be considered for the design |
| | | In gain mode |
| | | (see spans/power_mode = false), if no |
| | | gain is set in an amplifier, auto-design |
| | | 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 |
| ``power_dbm`` | (number) | Reference channel power. In gain mode |
| | | (see spans/power_mode = false), all gain |
| | | settings are offset w/r/t this reference |
| | | power. In power mode, it is the |
| | | reference power for |
| | | Spans/delta_power_range_db. For example, |
| | | if delta_power_range_db = `[0,0,0]`, the |
| | | same power=power_dbm is launched in every |
@@ -525,166 +328,12 @@ In the simplest case, homogeneous channel allocation can be defined via the ``Sp
| | | 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``. |
| | | This defines a list of reference powers |
| | | to run the propagation, in the range |
| ``power_range_db`` | (number) | Power sweep excursion around power_dbm. |
| | | It is not the min and max channel power |
| | | values! The reference power becomes: |
| | | 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.

View File

@@ -1,5 +1,3 @@
.. _physical-model:
Physical Model used in GNPy
===========================
@@ -126,9 +124,9 @@ 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 chromatic dispersion, the
thanks to the absence of in-line compensation for choromatic dispersion, the
become so, over short distances. So, the Gaussian noise model with incoherent
accumulation of NLI has extensively proved to be a quick yet accurate and
accumulation of NLI has estensively 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 +143,4 @@ 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::
.. bibliography:: biblio.bib

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.. _release-notes:
Release change log
==================
Each release introduces some changes and new features.
v2.8
----
**Spectrum assignment**: requests can now support multiple slots.
The definition in service file supports multiple assignments (unchanged syntax):
.. code-block:: json
"effective-freq-slot": [
{
"N": 0,
"M": 4
}, {
"N": 50,
"M": 4
}
],
But in results, label-hop is now a list of slots and center frequency index:
.. code-block:: json
{
"path-route-object": {
"index": 4,
"label-hop": [
{
"N": 0,
"M": 4
}, {
"N": 50,
"M": 4
}
]
}
},
instead of
.. code-block:: json
{
"path-route-object": {
"index": 4,
"label-hop": {
"N": 0,
"M": 4
}
}
},
**change in display**: only warnings are displayed ; information are disabled and needs the -v (verbose)
option to be displayed on standard output.
**frequency scaling**: Chromatic dispersion, effective area, Raman Gain coefficient,
and nonlinear coefficient can now be defined with a scaling along frequency.
**power offset**: Power equalization now enables defining a power offset in transceiver library to represent
the deviation from the general equalisation strategy defined in ROADMs.
.. code-block:: json
"mode": [{
"format": "100G",
"baud_rate": 32.0e9,
"tx_osnr": 35.0,
"min_spacing": 50.0e9,
"cost": 1,
"OSNR": 10.0,
"bit_rate": 100.0e9,
"roll_off": 0.2,
"equalization_offset_db": 0.0
}, {
"format": "200G",
"baud_rate": 64.0e9,
"tx_osnr": 35.0,
"min_spacing": 75.0e9,
"cost": 1,
"OSNR": 13.0,
"bit_rate": 200.0e9,
"roll_off": 0.2,
"equalization_offset_db": 1.76
}
]
v2.7
----

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"""
'''
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`.
"""
'''

9
gnpy/api/__init__.py Normal file
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# coding: utf-8
from flask import Flask
app = Flask(__name__)
import gnpy.api.route.path_request_route
import gnpy.api.route.status_route
import gnpy.api.route.topology_route
import gnpy.api.route.equipments_route

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# coding: utf-8

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

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

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

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

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

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# coding: utf-8

17
gnpy/api/model/error.py Normal file
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# coding: utf-8
class Error:
def __init__(self, code: int = None, message: str = None, description: str = None):
"""Error
:param code: The code of this Error.
:type code: int
:param message: The message of this Error.
:type message: str
:param description: The description of this Error.
:type description: str
"""
self.code = code
self.message = message
self.description = description

8
gnpy/api/model/result.py Normal file
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# coding: utf-8
class Result:
def __init__(self, message: str = None, description: str = None):
self.message = message
self.description = description

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

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# coding: utf-8

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

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

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

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

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# coding: utf-8

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

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

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

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# -*- coding: utf-8 -*-
import json
import logging
import os
import uuid
import gnpy.core.ansi_escapes as ansi_escapes
from gnpy.api.exception.path_computation_error import PathComputationError
from gnpy.api.service import config_service
from gnpy.api.service.encryption_service import EncryptionService
from gnpy.core.network import build_network
from gnpy.core.utils import lin2db, automatic_nch
from gnpy.tools.json_io import requests_from_json, disjunctions_from_json, network_to_json
from gnpy.topology.request import (compute_path_dsjctn, requests_aggregation,
correct_json_route_list,
deduplicate_disjunctions, compute_path_with_disjunction)
from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum
_logger = logging.getLogger(__name__)
class PathRequestService:
def __init__(self, encryption_service: EncryptionService):
self.encryption = encryption_service
def path_requests_run(self, service, network, equipment):
# Build the network once using the default power defined in SI in eqpt config
# TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
# spacing, f_min and f_max
p_db = equipment['SI']['default'].power_dbm
p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
build_network(network, equipment, p_db, p_total_db)
path_computation_identifier = str(uuid.uuid4())
autodesign_dir = config_service.get_autodesign_dir()
with(open(os.path.join(autodesign_dir, '.'.join([path_computation_identifier, 'json'])), 'wb')) as file:
file.write(self.encryption.encrypt(json.dumps(network_to_json(network)).encode()))
oms_list = build_oms_list(network, equipment)
rqs = requests_from_json(service, equipment)
# check that request ids are unique. Non unique ids, may
# mess the computation: better to stop the computation
all_ids = [r.request_id for r in rqs]
if len(all_ids) != len(set(all_ids)):
for item in list(set(all_ids)):
all_ids.remove(item)
msg = f'Requests id {all_ids} are not unique'
_logger.critical(msg)
raise ValueError('Requests id ' + all_ids + ' are not unique')
rqs = correct_json_route_list(network, rqs)
# pths = compute_path(network, equipment, rqs)
dsjn = disjunctions_from_json(service)
# need to warn or correct in case of wrong disjunction form
# disjunction must not be repeated with same or different ids
dsjn = deduplicate_disjunctions(dsjn)
rqs, dsjn = requests_aggregation(rqs, dsjn)
# TODO export novel set of aggregated demands in a json file
_logger.info(f'{ansi_escapes.blue}The following services have been requested:{ansi_escapes.reset}' + str(rqs))
_logger.info(f'{ansi_escapes.blue}Computing all paths with constraints{ansi_escapes.reset}')
pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
_logger.info(f'{ansi_escapes.blue}Propagating on selected path{ansi_escapes.reset}')
propagatedpths, reversed_pths, reversed_propagatedpths = compute_path_with_disjunction(network, equipment, rqs,
pths)
# Note that deepcopy used in compute_path_with_disjunction returns
# a list of nodes which are not belonging to network (they are copies of the node objects).
# so there can not be propagation on these nodes.
pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
return propagatedpths, reversed_propagatedpths, rqs, path_computation_identifier
def get_autodesign(self, path_computation_id):
"""
Get the autodesign with id topology_id
@param path_computation_id:
@return: the autodesign in json format
"""
autodesign_dir = config_service.get_autodesign_dir()
autodesign_file = os.path.join(autodesign_dir, '.'.join([path_computation_id, 'json']))
if not os.path.exists(autodesign_file):
raise PathComputationError('Autodesign with id {} does not exist '.format(path_computation_id))
with(open(autodesign_file, 'rb')) as file:
return json.loads(self.encryption.decrypt(file.read()))
def delete_autodesign(self, path_computation_id: str):
"""
Delete autodesign with id equipment_id
@param path_computation_id:
"""
autodesign_dir = config_service.get_autodesign_dir()
autodesign_file = os.path.join(autodesign_dir, '.'.join([path_computation_id, 'json']))
if os.path.exists(autodesign_file):
os.remove(autodesign_file)

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[DIRECTORY]
topology: /opt/application/oopt-gnpy/topology
equipment: /opt/application/oopt-gnpy/equipment
autodesign: /opt/application/oopt-gnpy/autodesign

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

View File

@@ -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`.
"""
'''

View File

@@ -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'

File diff suppressed because it is too large Load Diff

View File

@@ -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
@@ -29,22 +29,17 @@ 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 Transponder "{trx_type_variety}"'
+ f' mode "{trx_params["format"]}" has baud rate'
+ f' {trx_params["baud_rate"] * 1e-9:.3f} GHz greater than min_spacing'
+ f' {trx_params["min_spacing"] * 1e-9:.3f}.')
trx_params['equalization_offset_db'] = trx_params.get('equalization_offset_db', 0)
raise EquipmentConfigError(f'Inconsistency in equipment library:\n Transpoder "{trx_type_variety}" mode "{trx_params["format"]}" ' +
f'has baud rate {trx_params["baud_rate"]*1e-9} GHz greater than min_spacing {trx_params["min_spacing"]*1e-9}.')
else:
mode_params = {"format": "undetermined",
"baud_rate": None,
"OSNR": None,
"penalties": None,
"bit_rate": None,
"roll_off": None,
"tx_osnr": None,
"min_spacing": None,
"cost": None,
"equalization_offset_db": 0}
"cost": None}
trx_params = {**mode_params}
trx_params['f_min'] = equipment['Transceiver'][trx_type_variety].frequency['min']
trx_params['f_max'] = equipment['Transceiver'][trx_type_variety].frequency['max']
@@ -64,13 +59,14 @@ 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
trx_params['equalization_offset_db'] = 0
nch = automatic_nch(trx_params['f_min'], trx_params['f_max'], trx_params['spacing'])
trx_params['nb_channel'] = nch
print(f'There are {nch} channels propagating')
trx_params['power'] = db2lin(default_si_data.power_dbm) * 1e-3

View File

@@ -1,37 +1,37 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
'''
gnpy.core.exceptions
====================
Exceptions thrown by other gnpy modules
"""
'''
class ConfigurationError(Exception):
"""User-provided configuration contains an error"""
'''User-provided configuration contains an error'''
class EquipmentConfigError(ConfigurationError):
"""Incomplete or wrong configuration within the equipment library"""
'''Incomplete or wrong configuration within the equipment library'''
class NetworkTopologyError(ConfigurationError):
"""Topology of user-provided network is wrong"""
'''Topology of user-provided network is wrong'''
class ServiceError(Exception):
"""Service of user-provided request is wrong"""
'''Service of user-provided request is wrong'''
class DisjunctionError(ServiceError):
"""Disjunction of user-provided request can not be satisfied"""
'''Disjunction of user-provided request can not be satisfied'''
class SpectrumError(Exception):
"""Spectrum errors of the program"""
'''Spectrum errors of the program'''
class ParametersError(ConfigurationError):
"""Incomplete or wrong configurations within parameters json"""
'''Incomplete or wrong configurations within parameters json'''

View File

@@ -1,364 +1,57 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
'''
gnpy.core.info
==============
This module contains classes for modelling :class:`SpectralInformation`.
"""
'''
from __future__ import annotations
from collections import namedtuple
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)"""
from gnpy.core.utils import automatic_nch, lin2db
class Power(namedtuple('Power', 'signal nli ase')):
"""carriers power in W"""
class Channel(
namedtuple('Channel',
'channel_number frequency baud_rate slot_width roll_off power chromatic_dispersion pmd pdl latency')):
"""Class containing the parameters of a WDM signal.
class Channel(namedtuple('Channel', 'channel_number frequency baud_rate roll_off power chromatic_dispersion pmd')):
""" 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)
:param channel_number: channel number in the WDM grid
:param frequency: central frequency of the signal (Hz)
:param baud_rate: the symbol rate of the signal (Baud)
:param roll_off: the roll off of the signal. It is a pure number between 0 and 1
:param power (gnpy.core.info.Power): power of signal, ASE noise and NLI (W)
:param chromatic_dispersion: chromatic dispersion (s/m)
:param pmd: polarization mode dispersion (s)
"""
class SpectralInformation(object):
"""Class containing the parameters of the entire WDM comb.
delta_pdb_per_channel: (per frequency) per channel delta power in dbm for the actual mix of channels"""
def __init__(self, frequency: array, baud_rate: array, slot_width: array, signal: array, nli: array, ase: array,
roll_off: array, chromatic_dispersion: array, pmd: array, pdl: array, latency: array,
delta_pdb_per_channel: array, tx_osnr: array, 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._label = label[indices]
@property
def frequency(self):
return self._frequency
@property
def df(self):
"""Matrix of relative frequency distances between all channels. Positive elements in the upper right side."""
return self._df
@property
def slot_width(self):
return self._slot_width
@property
def baud_rate(self):
return self._baud_rate
@property
def number_of_channels(self):
return self._number_of_channels
@property
def powers(self):
powers = zip(self.signal, self.nli, self.ase)
return [Power(*p) for p in powers]
@property
def signal(self):
return self._signal
@signal.setter
def signal(self, signal):
self._signal = signal
@property
def nli(self):
return self._nli
@nli.setter
def nli(self, nli):
self._nli = nli
@property
def ase(self):
return self._ase
@ase.setter
def ase(self, ase):
self._ase = ase
@property
def roll_off(self):
return self._roll_off
@property
def chromatic_dispersion(self):
return self._chromatic_dispersion
@chromatic_dispersion.setter
def chromatic_dispersion(self, chromatic_dispersion):
self._chromatic_dispersion = chromatic_dispersion
@property
def pmd(self):
return self._pmd
@property
def label(self):
return self._label
@pmd.setter
def pmd(self, pmd):
self._pmd = pmd
@property
def pdl(self):
return self._pdl
@pdl.setter
def pdl(self, pdl):
self._pdl = pdl
@property
def latency(self):
return self._latency
@latency.setter
def latency(self, latency):
self._latency = latency
@property
def delta_pdb_per_channel(self):
return self._delta_pdb_per_channel
@delta_pdb_per_channel.setter
def delta_pdb_per_channel(self, delta_pdb_per_channel):
self._delta_pdb_per_channel = delta_pdb_per_channel
@property
def tx_osnr(self):
return self._tx_osnr
@tx_osnr.setter
def tx_osnr(self, tx_osnr):
self._tx_osnr = tx_osnr
@property
def channel_number(self):
return self._channel_number
@property
def carriers(self):
entries = zip(self.channel_number, self.frequency, self.baud_rate, self.slot_width,
self.roll_off, self.powers, self.chromatic_dispersion, self.pmd, self.pdl, self.latency)
return [Channel(*entry) for entry in entries]
def apply_attenuation_lin(self, attenuation_lin):
self.signal *= attenuation_lin
self.nli *= attenuation_lin
self.ase *= attenuation_lin
def apply_attenuation_db(self, attenuation_db):
attenuation_lin = 1 / db2lin(attenuation_db)
self.apply_attenuation_lin(attenuation_lin)
def apply_gain_lin(self, gain_lin):
self.signal *= gain_lin
self.nli *= gain_lin
self.ase *= gain_lin
def apply_gain_db(self, gain_db):
gain_lin = db2lin(gain_db)
self.apply_gain_lin(gain_lin)
def __add__(self, other: SpectralInformation):
try:
return SpectralInformation(frequency=append(self.frequency, other.frequency),
slot_width=append(self.slot_width, other.slot_width),
signal=append(self.signal, other.signal), nli=append(self.nli, other.nli),
ase=append(self.ase, other.ase),
baud_rate=append(self.baud_rate, other.baud_rate),
roll_off=append(self.roll_off, other.roll_off),
chromatic_dispersion=append(self.chromatic_dispersion,
other.chromatic_dispersion),
pmd=append(self.pmd, other.pmd),
pdl=append(self.pdl, other.pdl),
latency=append(self.latency, other.latency),
delta_pdb_per_channel=append(self.delta_pdb_per_channel,
other.delta_pdb_per_channel),
tx_osnr=append(self.tx_osnr, other.tx_osnr),
label=append(self.label, other.label))
except SpectrumError:
raise SpectrumError('Spectra cannot be summed: channels overlapping.')
def _replace(self, carriers):
self.chromatic_dispersion = array([c.chromatic_dispersion for c in carriers])
self.pmd = array([c.pmd for c in carriers])
self.pdl = array([c.pdl for c in carriers])
self.latency = array([c.latency for c in carriers])
self.signal = array([c.power.signal for c in carriers])
self.nli = array([c.power.nli for c in carriers])
self.ase = array([c.power.ase for c in carriers])
return self
class Pref(namedtuple('Pref', 'p_span0, p_spani, neq_ch ')):
"""noiseless reference power in dBm:
p_span0: inital target carrier power
p_spani: carrier power after element i
neq_ch: equivalent channel count in dB"""
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.,
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, label=label)
except ValueError as e:
if 'could not broadcast' in str(e):
raise SpectrumError('Dimension mismatch in input fields.')
else:
raise
class SpectralInformation(namedtuple('SpectralInformation', 'pref carriers')):
def __new__(cls, pref, carriers):
return super().__new__(cls, pref, carriers)
def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, power, spacing, tx_osnr, delta_pdb=0):
"""Creates a fixed slot width spectral information with flat power.
all arguments are scalar values"""
number_of_channels = automatic_nch(f_min, f_max, spacing)
frequency = [(f_min + spacing * i) for i in range(1, number_of_channels + 1)]
delta_pdb_per_channel = delta_pdb * ones(number_of_channels)
label = [f'{baud_rate * 1e-9 :.2f}G' for i in range(number_of_channels)]
return create_arbitrary_spectral_information(frequency, slot_width=spacing, signal=power, baud_rate=baud_rate,
roll_off=roll_off, delta_pdb_per_channel=delta_pdb_per_channel,
tx_osnr=tx_osnr, label=label)
def carriers_to_spectral_information(initial_spectrum: dict[float, Carrier],
power: float) -> SpectralInformation:
"""Initial spectrum is a dict with key = carrier frequency, and value a Carrier object.
:param initial_spectrum: indexed by frequency in Hz, with power offset (delta_pdb), baudrate, slot width,
tx_osnr and roll off.
:param power: power of the request
"""
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)
return create_arbitrary_spectral_information(frequency=frequency, signal=signal, baud_rate=baud_rate,
slot_width=slot_width, roll_off=roll_off,
delta_pdb_per_channel=delta_pdb_per_channel, tx_osnr=tx_osnr,
label=label)
@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
def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, power, spacing):
# pref in dB : convert power lin into power in dB
pref = lin2db(power * 1e3)
nb_channel = automatic_nch(f_min, f_max, spacing)
si = SpectralInformation(
pref=Pref(pref, pref, lin2db(nb_channel)),
carriers=[
Channel(f, (f_min + spacing * f),
baud_rate, roll_off, Power(power, 0, 0), 0, 0) for f in range(1, nb_channel + 1)
]
)
return si

View File

@@ -1,27 +1,19 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
'''
gnpy.core.network
=================
Working with networks which consist of network elements
"""
'''
from copy import deepcopy
from scipy.interpolate import interp1d
from operator import attrgetter
from collections import namedtuple
from logging import getLogger
from gnpy.core import elements
from gnpy.core import ansi_escapes, elements
from gnpy.core.exceptions import ConfigurationError, NetworkTopologyError
from gnpy.core.utils import round2float, convert_length, psd2powerdbm, lin2db, watt2dbm, dbm2watt
from gnpy.core.info import ReferenceCarrier, create_input_spectral_information
from gnpy.tools import json_io
from gnpy.core.parameters import SimParams
logger = getLogger(__name__)
from gnpy.core.utils import round2float, convert_length
from collections import namedtuple
def edfa_nf(gain_target, variety_type, equipment):
@@ -36,11 +28,10 @@ def edfa_nf(gain_target, variety_type, equipment):
)
amp.pin_db = 0
amp.nch = 88
amp.slot_width = 50e9
return amp._calc_nf(True)
def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restrictions=None, verbose=True):
def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restrictions=None):
"""amplifer selection algorithm
@Orange Jean-Luc Augé
"""
@@ -63,8 +54,15 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restri
# power attribut include power AND gain limitations
edfa_list = [Edfa_list(
variety=edfa_variety,
power=min(pin + edfa.gain_flatmax + TARGET_EXTENDED_GAIN, edfa.p_max) - power_target,
gain_min=gain_target + 3 - edfa.gain_min,
power=min(
pin
+ edfa.gain_flatmax
+ TARGET_EXTENDED_GAIN,
edfa.p_max
)
- power_target,
gain_min=gain_target + 3
- edfa.gain_min,
nf=edfa_nf(gain_target, edfa_variety, equipment))
for edfa_variety, edfa in edfa_dict.items()
if ((edfa.allowed_for_design or restrictions is not None) and not edfa.raman)]
@@ -73,8 +71,15 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restri
# do not allow extended gain min for Raman
raman_list = [Edfa_list(
variety=edfa_variety,
power=min(pin + edfa.gain_flatmax + TARGET_EXTENDED_GAIN, edfa.p_max) - power_target,
gain_min=gain_target - edfa.gain_min,
power=min(
pin
+ edfa.gain_flatmax
+ TARGET_EXTENDED_GAIN,
edfa.p_max
)
- power_target,
gain_min=gain_target
- edfa.gain_min,
nf=edfa_nf(gain_target, edfa_variety, equipment))
for edfa_variety, edfa in edfa_dict.items()
if (edfa.allowed_for_design and edfa.raman)] \
@@ -98,10 +103,10 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restri
please increase span fiber padding')
else:
# TODO: convert to logging
if verbose:
logger.warning(f'\n\tWARNING: target gain in node {uid} is below all available amplifiers min gain: '
+ '\n\tamplifier input padding will be assumed, consider increase span fiber padding '
+ 'instead.\n')
print(
f'{ansi_escapes.red}WARNING:{ansi_escapes.reset} target gain in node {uid} is below all available amplifiers min gain: \
amplifier input padding will be assumed, consider increase span fiber padding instead'
)
acceptable_gain_min_list = edfa_list
# filter on gain+power limitation:
@@ -121,130 +126,84 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restri
# =>chose the amp with the best NF among the acceptable ones:
selected_edfa = min(acceptable_power_list, key=attrgetter('nf')) # filter on NF
# check what are the gain and power limitations of this amp
power_reduction = min(selected_edfa.power, 0)
if power_reduction < -0.5 and verbose:
logger.warning(f'\n\tWARNING: target gain and power in node {uid}\n'
+ '\tis beyond all available amplifiers capabilities and/or extended_gain_range:\n'
+ f'\ta power reduction of {round(power_reduction, 2)} is applied\n')
power_reduction = round(min(selected_edfa.power, 0), 2)
if power_reduction < -0.5:
print(
f'{ansi_escapes.red}WARNING:{ansi_escapes.reset} target gain and power in node {uid}\n \
is beyond all available amplifiers capabilities and/or extended_gain_range:\n\
a power reduction of {power_reduction} is applied\n'
)
return selected_edfa.variety, power_reduction
def target_power(network, node, equipment): # get_fiber_dp
"""Computes target power using J. -L. Auge, V. Curri and E. Le Rouzic,
Open Design for Multi-Vendor Optical Networks, OFC 2019.
equation 4
"""
if isinstance(node, elements.Roadm):
return 0
SPAN_LOSS_REF = 20
POWER_SLOPE = 0.3
dp_range = list(equipment['Span']['default'].delta_power_range_db)
node_loss = span_loss(network, node, equipment)
node_loss = span_loss(network, node)
try:
dp = round2float((node_loss - SPAN_LOSS_REF) * POWER_SLOPE, dp_range[2])
dp = max(dp_range[0], dp)
dp = min(dp_range[1], dp)
except IndexError:
raise ConfigurationError('invalid delta_power_range_db definition in eqpt_config[Span]'
'delta_power_range_db: [lower_bound, upper_bound, step]')
except KeyError:
raise ConfigurationError(f'invalid delta_power_range_db definition in eqpt_config[Span]'
f'delta_power_range_db: [lower_bound, upper_bound, step]')
if isinstance(node, elements.Roadm):
dp = 0
return dp
_fiber_fused_types = (elements.Fused, elements.Fiber)
def prev_node_generator(network, node):
"""fused spans interest:
iterate over all predecessors while they are either Fused or Fibers succeeded by Fused"""
iterate over all predecessors while they are Fused or Fiber type"""
try:
prev_node = next(network.predecessors(node))
prev_node = next(n for n in network.predecessors(node))
except StopIteration:
if isinstance(node, elements.Transceiver):
return
raise NetworkTopologyError(f'Node {node.uid} is not properly connected, please check network topology')
if ((isinstance(prev_node, elements.Fused) and isinstance(node, _fiber_fused_types)) or
(isinstance(prev_node, _fiber_fused_types) and isinstance(node, elements.Fused))):
# yield and re-iterate
if isinstance(prev_node, elements.Fused) or isinstance(node, elements.Fused):
yield prev_node
yield from prev_node_generator(network, prev_node)
else:
StopIteration
def next_node_generator(network, node):
"""fused spans interest:
iterate over all predecessors while they are either Fused or Fibers preceded by Fused"""
iterate over all successors while they are Fused or Fiber type"""
try:
next_node = next(network.successors(node))
next_node = next(n for n in network.successors(node))
except StopIteration:
if isinstance(node, elements.Transceiver):
return
raise NetworkTopologyError(f'Node {node.uid} is not properly connected, please check network topology')
if ((isinstance(next_node, elements.Fused) and isinstance(node, _fiber_fused_types)) or
(isinstance(next_node, _fiber_fused_types) and isinstance(node, elements.Fused))):
raise NetworkTopologyError('Node {node.uid} is not properly connected, please check network topology')
# yield and re-iterate
if isinstance(next_node, elements.Fused) or isinstance(node, elements.Fused):
yield next_node
yield from next_node_generator(network, next_node)
def estimate_raman_gain(node, equipment):
"""If node is RamanFiber, then estimate the possible Raman gain if any
for this purpose propagate a fake signal in a copy.
to be accurate the nb of channel should be the same as in SI, but this increases computation time
"""
f_min = equipment['SI']['default'].f_min
f_max = equipment['SI']['default'].f_max
roll_off = equipment['SI']['default'].roll_off
baud_rate = equipment['SI']['default'].baud_rate
power_dbm = equipment['SI']['default'].power_dbm
power = dbm2watt(equipment['SI']['default'].power_dbm)
spacing = equipment['SI']['default'].spacing
tx_osnr = equipment['SI']['default'].tx_osnr
sim_params = {
"raman_params": {
"flag": True,
"result_spatial_resolution": 10e3,
"solver_spatial_resolution": 50
},
"nli_params": {
"method": "ggn_spectrally_separated",
"dispersion_tolerance": 1,
"phase_shift_tolerance": 0.1,
"computed_channels": [1, 18, 37, 56, 75]
}
}
if isinstance(node, elements.RamanFiber):
# in order to take into account gain generated in RamanFiber, propagate in the RamanFiber with
# SI reference channel.
spectral_info_input = create_input_spectral_information(f_min=f_min, f_max=f_max, roll_off=roll_off,
baud_rate=baud_rate, power=power, spacing=spacing,
tx_osnr=tx_osnr)
n_copy = deepcopy(node)
# need to set ref_pch_in_dbm in order to correctly run propagate of the element, because this
# setting has not yet been done by autodesign
n_copy.ref_pch_in_dbm = power_dbm
SimParams.set_params(sim_params)
pin = watt2dbm(sum(spectral_info_input.signal))
spectral_info_out = n_copy(spectral_info_input)
pout = watt2dbm(sum(spectral_info_out.signal))
estimated_gain = pout - pin + node.loss
return round(estimated_gain, 2)
else:
return 0.0
StopIteration
def span_loss(network, node, equipment):
"""Total loss of a span (Fiber and Fused nodes) which contains the given node"""
def span_loss(network, node):
"""Fused span interest:
return the total span loss of all the fibers spliced by a Fused node"""
loss = node.loss if node.passive else 0
loss += sum(n.loss for n in prev_node_generator(network, node))
loss += sum(n.loss for n in next_node_generator(network, node))
# add the possible Raman gain
gain = estimate_raman_gain(node, equipment)
gain += sum(estimate_raman_gain(n, equipment) for n in prev_node_generator(network, node))
gain += sum(estimate_raman_gain(n, equipment) for n in next_node_generator(network, node))
return loss - gain
try:
prev_node = next(n for n in network.predecessors(node))
if isinstance(prev_node, elements.Fused):
loss += sum(n.loss for n in prev_node_generator(network, node))
except StopIteration:
pass
try:
next_node = next(n for n in network.successors(node))
if isinstance(next_node, elements.Fused):
loss += sum(n.loss for n in next_node_generator(network, node))
except StopIteration:
pass
return loss
def find_first_node(network, node):
@@ -270,10 +229,10 @@ def find_last_node(network, node):
def set_amplifier_voa(amp, power_target, power_mode):
VOA_MARGIN = 1 # do not maximize the VOA optimization
if amp.out_voa is None:
if power_mode and amp.params.out_voa_auto:
if power_mode:
voa = min(amp.params.p_max - power_target,
amp.params.gain_flatmax - amp.effective_gain)
voa = max(round2float(voa, 0.5) - VOA_MARGIN, 0)
voa = max(round2float(max(voa, 0), 0.5) - VOA_MARGIN, 0) if amp.params.out_voa_auto else 0
amp.delta_p = amp.delta_p + voa
amp.effective_gain = amp.effective_gain + voa
else:
@@ -281,287 +240,98 @@ def set_amplifier_voa(amp, power_target, power_mode):
amp.out_voa = voa
def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_db, verbose):
"""This node can be a transceiver or a ROADM (same function called in both cases).
go through each link staring from this_node until next Roadm or Transceiver and
set gain and delta_p according to configurations set by user.
power_mode = True, set amplifiers delta_p and effective_gain
power_mode = False, set amplifiers effective_gain and ignore delta_p config: set it to None
"""
def set_egress_amplifier(network, roadm, equipment, pref_total_db):
power_mode = equipment['Span']['default'].power_mode
next_oms = (n for n in network.successors(this_node) if not isinstance(n, elements.Transceiver))
next_oms = (n for n in network.successors(roadm) if not isinstance(n, elements.Transceiver))
for oms in next_oms:
# go through all the OMS departing from the ROADM
prev_node = this_node
node = oms
if isinstance(this_node, elements.Transceiver):
# for the time being use the same power for the target of roadms and for transceivers
# TODO: This should be changed when introducing a power parameter dedicated to transceivers
this_node_out_power = pref_ch_db
if isinstance(this_node, elements.Roadm):
# get target power out from ROADM for the reference carrier based on equalization settings
this_node_out_power = this_node.get_per_degree_ref_power(degree=node.uid)
# use the target power on this degree
prev_dp = this_node_out_power - pref_ch_db
# go through all the OMS departing from the Roadm
node = roadm
prev_node = roadm
next_node = oms
# if isinstance(next_node, elements.Fused): #support ROADM wo egress amp for metro applications
# node = find_last_node(next_node)
# next_node = next(n for n in network.successors(node))
# next_node = find_last_node(next_node)
prev_dp = getattr(node.params, 'target_pch_out_db', 0)
dp = prev_dp
prev_voa = 0
voa = 0
visited_nodes = []
while not (isinstance(node, elements.Roadm) or isinstance(node, elements.Transceiver)):
while True:
# go through all nodes in the OMS (loop until next Roadm instance)
next_node = get_next_node(node, network)
visited_nodes.append(node)
if next_node in visited_nodes:
raise NetworkTopologyError(f'Loop detected for {type(node).__name__} {node.uid}, '
+ 'please check network topology')
if isinstance(node, elements.Edfa):
node_loss = span_loss(network, prev_node, equipment)
node_loss = span_loss(network, prev_node)
voa = node.out_voa if node.out_voa else 0
if node.operational.delta_p is None:
dp = target_power(network, next_node, equipment) + voa
if node.delta_p is None:
dp = target_power(network, next_node, equipment)
else:
dp = node.operational.delta_p
dp = node.delta_p
gain_from_dp = node_loss + dp - prev_dp + prev_voa
if node.effective_gain is None or power_mode:
gain_target = node_loss + dp - prev_dp + prev_voa
gain_target = gain_from_dp
else: # gain mode with effective_gain
gain_target = node.effective_gain
dp = prev_dp - node_loss - prev_voa + gain_target
dp = prev_dp - node_loss + gain_target
power_target = pref_total_db + dp
raman_allowed = False
if isinstance(prev_node, elements.Fiber):
max_fiber_lineic_loss_for_raman = \
equipment['Span']['default'].max_fiber_lineic_loss_for_raman * 1e-3 # dB/m
raman_allowed = (prev_node.params.loss_coef < max_fiber_lineic_loss_for_raman).all()
else:
raman_allowed = False
equipment['Span']['default'].max_fiber_lineic_loss_for_raman
raman_allowed = prev_node.params.loss_coef < max_fiber_lineic_loss_for_raman
if node.params.type_variety == '':
if node.variety_list and isinstance(node.variety_list, list):
restrictions = node.variety_list
elif isinstance(prev_node, elements.Roadm) and prev_node.restrictions['booster_variety_list']:
# implementation of restrictions on roadm boosters
# implementation of restrictions on roadm boosters
if isinstance(prev_node, elements.Roadm):
if prev_node.restrictions['booster_variety_list']:
restrictions = prev_node.restrictions['booster_variety_list']
elif isinstance(next_node, elements.Roadm) and next_node.restrictions['preamp_variety_list']:
# implementation of restrictions on roadm preamp
else:
restrictions = None
elif isinstance(next_node, elements.Roadm):
# implementation of restrictions on roadm preamp
if next_node.restrictions['preamp_variety_list']:
restrictions = next_node.restrictions['preamp_variety_list']
else:
restrictions = None
edfa_variety, power_reduction = select_edfa(raman_allowed, gain_target, power_target, equipment,
node.uid, restrictions, verbose)
else:
restrictions = None
if node.params.type_variety == '':
edfa_variety, power_reduction = select_edfa(raman_allowed, gain_target, power_target, equipment, node.uid, restrictions)
extra_params = equipment['Edfa'][edfa_variety]
node.params.update_params(extra_params.__dict__)
dp += power_reduction
gain_target += power_reduction
else:
# Check power saturation also in this case
p_max = equipment['Edfa'][node.params.type_variety].p_max
if power_mode:
power_reduction = min(0, p_max - (pref_total_db + dp))
else:
pout = pref_total_db + prev_dp - node_loss - prev_voa + gain_target
power_reduction = min(0, p_max - pout)
dp += power_reduction
gain_target += power_reduction
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 and verbose:
# 1e-2 to allow a small margin according to round2float min step
logger.warning(f'\n\tWARNING: effective gain in Node {node.uid}\n'
+ f'\tis above user specified amplifier {node.params.type_variety}\n'
+ '\tmax flat gain: '
+ f'{equipment["Edfa"][node.params.type_variety].gain_flatmax}dB ; '
+ f'required gain: {round(gain_target, 2)}dB. Please check amplifier type.\n')
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')
node.delta_p = dp if power_mode else None
node.effective_gain = gain_target
# if voa is not set, then set it and possibly optimize it with gain and update delta_p and
# effective_gain values
set_amplifier_voa(node, power_target, power_mode)
# set_amplifier_voa may change delta_p in power_mode
node._delta_p = node.delta_p if power_mode else dp
# target_pch_out_dbm records target power for design: If user defines one, then this is displayed,
# else display the one computed during design
if node.delta_p is not None and node.operational.delta_p is not None:
# use the user defined target
node.target_pch_out_dbm = round(node.operational.delta_p + pref_ch_db, 2)
elif node.delta_p is not None:
# use the design target if no target were set
node.target_pch_out_dbm = round(node.delta_p + pref_ch_db, 2)
elif node.delta_p is None:
node.target_pch_out_dbm = None
if isinstance(next_node, elements.Roadm) or isinstance(next_node, elements.Transceiver):
break
prev_dp = dp
prev_voa = voa
prev_node = node
node = next_node
# print(f'{node.uid}')
next_node = next(n for n in network.successors(node))
def set_roadm_ref_carrier(roadm, equipment):
"""ref_carrier records carrier information used for design and usefull for equalization
"""
roadm.ref_carrier = ReferenceCarrier(baud_rate=equipment['SI']['default'].baud_rate,
slot_width=equipment['SI']['default'].spacing)
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 set_roadm_input_powers(network, roadm, equipment, pref_ch_db):
"""Set reference powers at ROADM input for a reference channel and based on the adjacent OMS.
This supposes that there is no dependency on path. For example, the succession:
node power out of element
roadm A (target power -10dBm) -10dBm
fiber A (16 dB loss) -26dBm
roadm B (target power -12dBm) -26dBm
fiber B (10 dB loss) -36dBm
roadm C (target power -14dBm) -36dBm
is not consistent because target powers in roadm B and roadm C can not be met.
input power for the reference channel will be set -26 dBm in roadm B and -22dBm in roadm C,
because at design time we can not know about path.
The function raises a warning if target powers can not be met with the design.
User should be aware that design was not successfull and that power reduction was applied.
Note that this value is only used for visualisation purpose (to compute ROADM loss in elements).
"""
previous_elements = [n for n in network.predecessors(roadm)]
roadm.ref_pch_in_dbm = {}
for element in previous_elements:
node = element
loss = 0.0
while isinstance(node, (elements.Fiber, elements.Fused, elements.RamanFiber)):
# go through all predecessors until a power target is found either in an amplifier, a ROADM or a transceiver
# then deduce power at ROADM input from this degree based on this target and crossed losses
loss += node.loss
previous_node = node
node = next(network.predecessors(node))
if isinstance(node, elements.Edfa):
roadm.ref_pch_in_dbm[element.uid] = pref_ch_db + node._delta_p - node.out_voa - loss
elif isinstance(node, elements.Roadm):
roadm.ref_pch_in_dbm[element.uid] = \
node.get_per_degree_ref_power(degree=previous_node.uid) - loss
elif isinstance(node, elements.Transceiver):
roadm.ref_pch_in_dbm[element.uid] = pref_ch_db - loss
# check if target power can be met
temp = []
if roadm.per_degree_pch_out_dbm:
temp.append(max([p for p in roadm.per_degree_pch_out_dbm.values()]))
if roadm.per_degree_pch_psd:
temp.append(max([psd2powerdbm(p, roadm.ref_carrier.baud_rate) for p in roadm.per_degree_pch_psd.values()]))
if roadm.per_degree_pch_psw:
temp.append(max([psd2powerdbm(p, roadm.ref_carrier.slot_width) for p in roadm.per_degree_pch_psw.values()]))
if roadm.params.target_pch_out_db:
temp.append(roadm.params.target_pch_out_db)
if roadm.params.target_psd_out_mWperGHz:
temp.append(psd2powerdbm(roadm.params.target_psd_out_mWperGHz, roadm.ref_carrier.baud_rate))
if roadm.params.target_out_mWperSlotWidth:
temp.append(psd2powerdbm(roadm.params.target_out_mWperSlotWidth, roadm.ref_carrier.slot_width))
if not temp:
raise ConfigurationError(f'Could not find target power/PSD/PSW in ROADM "{roadm.uid}"')
target_to_be_supported = max(temp)
for from_degree, in_power in roadm.ref_pch_in_dbm.items():
if in_power < target_to_be_supported:
logger.warning(
f'WARNING: maximum target power {target_to_be_supported}dBm '
+ f'in ROADM "{roadm.uid}" can not be met for at least one crossing path. Min input power '
+ f'from "{from_degree}" direction is {round(in_power, 2)}dBm. Please correct input topology.'
)
def set_fiber_input_power(network, fiber, equipment, pref_ch_db):
"""Set reference powers at fiber input for a reference channel.
Supposes that target power out of ROADMs and amplifiers are consistent.
This is only for visualisation purpose
"""
loss = 0.0
node = next(network.predecessors(fiber))
while isinstance(node, elements.Fused):
loss += node.loss
previous_node = node
node = next(network.predecessors(node))
if isinstance(node, (elements.Fiber, elements.RamanFiber)) and node.ref_pch_in_dbm is not None:
fiber.ref_pch_in_dbm = node.ref_pch_in_dbm - loss - node.loss
if isinstance(node, (elements.Fiber, elements.RamanFiber)) and node.ref_pch_in_dbm is None:
set_fiber_input_power(network, node, equipment, pref_ch_db)
fiber.ref_pch_in_dbm = node.ref_pch_in_dbm - loss - node.loss
elif isinstance(node, elements.Roadm):
fiber.ref_pch_in_dbm = \
node.get_per_degree_ref_power(degree=previous_node.uid) - loss
elif isinstance(node, elements.Edfa):
fiber.ref_pch_in_dbm = pref_ch_db + node._delta_p - node.out_voa - loss
elif isinstance(node, elements.Transceiver):
fiber.ref_pch_in_dbm = pref_ch_db - loss
def add_roadm_booster(network, roadm):
next_nodes = [n for n in network.successors(roadm)
if not (isinstance(n, elements.Transceiver) or isinstance(n, elements.Fused)
or isinstance(n, elements.Edfa))]
# no amplification for fused spans or TRX
for next_node in next_nodes:
network.remove_edge(roadm, next_node)
amp = elements.Edfa(
uid=f'Edfa_booster_{roadm.uid}_to_{next_node.uid}',
params=json_io.Amp.default_values,
metadata={
'location': {
'latitude': roadm.lat,
'longitude': roadm.lng,
'city': roadm.loc.city,
'region': roadm.loc.region,
}
},
operational={
'gain_target': None,
'tilt_target': 0,
})
network.add_node(amp)
network.add_edge(roadm, amp, weight=0.01)
network.add_edge(amp, next_node, weight=0.01)
def add_roadm_preamp(network, roadm):
prev_nodes = [n for n in network.predecessors(roadm)
def add_egress_amplifier(network, node):
next_nodes = [n for n in network.successors(node)
if not (isinstance(n, elements.Transceiver) or isinstance(n, elements.Fused) or isinstance(n, elements.Edfa))]
# no amplification for fused spans or TRX
for prev_node in prev_nodes:
network.remove_edge(prev_node, roadm)
for i, next_node in enumerate(next_nodes):
network.remove_edge(node, next_node)
amp = elements.Edfa(
uid=f'Edfa_preamp_{roadm.uid}_from_{prev_node.uid}',
params=json_io.Amp.default_values,
uid=f'Edfa{i}_{node.uid}',
params={},
metadata={
'location': {
'latitude': roadm.lat,
'longitude': roadm.lng,
'city': roadm.loc.city,
'region': roadm.loc.region,
'latitude': (node.lat * 2 + next_node.lat * 2) / 4,
'longitude': (node.lng * 2 + next_node.lng * 2) / 4,
'city': node.loc.city,
'region': node.loc.region,
}
},
operational={
@@ -569,77 +339,39 @@ def add_roadm_preamp(network, roadm):
'tilt_target': 0,
})
network.add_node(amp)
if isinstance(prev_node, elements.Fiber):
edgeweight = prev_node.params.length
if isinstance(node, elements.Fiber):
edgeweight = node.params.length
else:
edgeweight = 0.01
network.add_edge(prev_node, amp, weight=edgeweight)
network.add_edge(amp, roadm, weight=0.01)
def add_inline_amplifier(network, fiber):
next_node = get_next_node(fiber, network)
if isinstance(next_node, elements.Fiber) or isinstance(next_node, elements.RamanFiber):
# no amplification for fused spans or TRX
network.remove_edge(fiber, next_node)
amp = elements.Edfa(
uid=f'Edfa_{fiber.uid}',
params=json_io.Amp.default_values,
metadata={
'location': {
'latitude': (fiber.lat + next_node.lat) / 2,
'longitude': (fiber.lng + next_node.lng) / 2,
'city': fiber.loc.city,
'region': fiber.loc.region,
}
},
operational={
'gain_target': None,
'tilt_target': 0,
})
network.add_node(amp)
network.add_edge(fiber, amp, weight=fiber.params.length)
network.add_edge(node, amp, weight=edgeweight)
network.add_edge(amp, next_node, weight=0.01)
def calculate_new_length(fiber_length, bounds, target_length):
"""If fiber is over boundary, then assume this is a link "intent" and computes the set of
identical fiber spans this link should be composed of.
"""
if fiber_length < bounds.stop:
return fiber_length, 1
n_spans2 = int(fiber_length // target_length)
n_spans1 = n_spans2 + 1
n_spans = int(fiber_length // target_length)
length1 = fiber_length / n_spans1
length2 = fiber_length / n_spans2
length1 = fiber_length / (n_spans + 1)
delta1 = target_length - length1
result1 = (length1, n_spans + 1)
length2 = fiber_length / n_spans
delta2 = length2 - target_length
result2 = (length2, n_spans)
if (bounds.start <= length1 <= bounds.stop) and not(bounds.start <= length2 <= bounds.stop):
return (length1, n_spans1)
result = result1
elif (bounds.start <= length2 <= bounds.stop) and not(bounds.start <= length1 <= bounds.stop):
return (length2, n_spans2)
elif length2 - target_length <= target_length - length1 and length2 <= bounds.stop:
return (length2, n_spans2)
result = result2
else:
return (length1, n_spans1)
result = result1 if delta1 < delta2 else result2
return result
def get_next_node(node, network):
"""get_next node else raise tha appropriate error
"""
try:
next_node = next(network.successors(node))
return next_node
except StopIteration:
raise NetworkTopologyError(
f'{type(node).__name__} {node.uid} is not properly connected, please check network topology')
def split_fiber(network, fiber, bounds, target_length):
"""If fiber length exceeds boundary then assume this is a link "intent", and replace this one-span link
with an n_spans link, with identical fiber types.
"""
def split_fiber(network, fiber, bounds, target_length, equipment):
new_length, n_spans = calculate_new_length(fiber.params.length, bounds, target_length)
if n_spans == 1:
return
@@ -654,8 +386,9 @@ def split_fiber(network, fiber, bounds, target_length):
fiber.params.length = new_length
xpos = [prev_node.lng + (next_node.lng - prev_node.lng) * (n + 0.5) / n_spans for n in range(n_spans)]
ypos = [prev_node.lat + (next_node.lat - prev_node.lat) * (n + 0.5) / n_spans for n in range(n_spans)]
f = interp1d([prev_node.lng, next_node.lng], [prev_node.lat, next_node.lat])
xpos = [prev_node.lng + (next_node.lng - prev_node.lng) * (n + 1) / (n_spans + 1) for n in range(n_spans)]
ypos = f(xpos)
for span, lng, lat in zip(range(n_spans), xpos, ypos):
new_span = elements.Fiber(uid=f'{fiber.uid}_({span+1}/{n_spans})',
type_variety=fiber.type_variety,
@@ -682,95 +415,70 @@ def split_fiber(network, fiber, bounds, target_length):
def add_connector_loss(network, fibers, default_con_in, default_con_out, EOL):
"""Add default connector loss if no loss are defined. EOL repair margin is added as a connector loss
"""
for fiber in fibers:
next_node = get_next_node(fiber, network)
if fiber.params.con_in is None:
fiber.params.con_in = default_con_in
if fiber.params.con_out is None:
fiber.params.con_out = default_con_out
next_node = next(n for n in network.successors(fiber))
if not isinstance(next_node, elements.Fused):
fiber.params.con_out += EOL
def add_fiber_padding(network, fibers, padding, equipment):
"""Add a padding att_in at the input of the 1st fiber of a succession of fibers and fused
"""
def add_fiber_padding(network, fibers, padding):
"""last_fibers = (fiber for n in network.nodes()
if not (isinstance(n, elements.Fiber) or isinstance(n, elements.Fused))
for fiber in network.predecessors(n)
if isinstance(fiber, elements.Fiber))"""
for fiber in fibers:
next_node = get_next_node(fiber, network)
if isinstance(next_node, elements.Fused):
continue
this_span_loss = span_loss(network, fiber, equipment)
if this_span_loss < padding:
this_span_loss = span_loss(network, fiber)
try:
next_node = next(network.successors(fiber))
except StopIteration:
raise NetworkTopologyError(f'Fiber {fiber.uid} is not properly connected, please check network topology')
if this_span_loss < padding and not (isinstance(next_node, elements.Fused)):
# add a padding att_in at the input of the 1st fiber:
# address the case when several fibers are spliced together
first_fiber = find_first_node(network, fiber)
# in order to support no booster , fused might be placed
# just after a roadm: need to check that first_fiber is really a fiber
if isinstance(first_fiber, elements.Fiber):
first_fiber.params.att_in = first_fiber.params.att_in + padding - this_span_loss
if first_fiber.params.att_in is None:
first_fiber.params.att_in = padding - this_span_loss
else:
first_fiber.params.att_in = first_fiber.params.att_in + padding - this_span_loss
def add_missing_elements_in_network(network, equipment):
"""Autodesign network: add missing elements. split fibers if their length is too big
add ROADM preamp or booster and inline amplifiers between fibers
"""
def build_network(network, equipment, pref_ch_db, pref_total_db):
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, min(max_length, 90_000))
fibers = [f for f in network.nodes() if isinstance(f, elements.Fiber)]
for fiber in fibers:
split_fiber(network, fiber, bounds, target_length)
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)
fibers = [f for f in network.nodes() if isinstance(f, elements.Fiber)]
for fiber in fibers:
add_inline_amplifier(network, fiber)
target_length = max(min_length, 90_000)
default_con_in = default_span_data.con_in
default_con_out = default_span_data.con_out
padding = default_span_data.padding
def add_missing_fiber_attributes(network, equipment):
"""Fill in connector loss with default values. Add the padding loss is required.
EOL is added as a connector loss
"""
default_span_data = equipment['Span']['default']
# 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_connector_loss(network, fibers, default_con_in, default_con_out, default_span_data.EOL)
add_fiber_padding(network, fibers, padding)
# don't group split fiber and add amp in the same loop
# =>for code clarity (at the expense of speed):
add_fiber_padding(network, fibers, default_span_data.padding, equipment)
for fiber in fibers:
split_fiber(network, fiber, bounds, target_length, equipment)
amplified_nodes = [n for n in network.nodes() if isinstance(n, elements.Fiber) or isinstance(n, elements.Roadm)]
for node in amplified_nodes:
add_egress_amplifier(network, node)
def build_network(network, equipment, pref_ch_db, pref_total_db, set_connector_losses=True, verbose=True):
"""Set roadm equalization target and amplifier gain and power
"""
roadms = [r for r in network.nodes() if isinstance(r, elements.Roadm)]
transceivers = [t for t in network.nodes() if isinstance(t, elements.Transceiver)]
if set_connector_losses:
add_missing_fiber_attributes(network, equipment)
# set roadm equalization targets first
for roadm in roadms:
set_roadm_ref_carrier(roadm, equipment)
set_roadm_per_degree_targets(roadm, network)
# then set amplifiers gain, delta_p and out_voa on each OMS
for roadm in roadms + transceivers:
set_egress_amplifier(network, roadm, equipment, pref_ch_db, pref_total_db, verbose)
for roadm in roadms:
set_roadm_input_powers(network, roadm, equipment, pref_ch_db)
for fiber in [f for f in network.nodes() if isinstance(f, (elements.Fiber, elements.RamanFiber))]:
set_fiber_input_power(network, fiber, equipment, pref_ch_db)
set_egress_amplifier(network, roadm, equipment, pref_total_db)
def design_network(reference_channel, network, equipment, set_connector_losses=True, verbose=True):
"""Network is designed according to reference channel. Verbose indicate if the function should
print all warnings or not
"""
pref_ch_db = watt2dbm(reference_channel.power) # reference channel power
pref_total_db = pref_ch_db + lin2db(reference_channel.nb_channel) # reference total power
build_network(network, equipment, pref_ch_db, pref_total_db, set_connector_losses=set_connector_losses,
verbose=verbose)
# support older json input topology wo Roadms:
if len(roadms) == 0:
trx = [t for t in network.nodes() if isinstance(t, elements.Transceiver)]
for t in trx:
set_egress_amplifier(network, t, equipment, pref_total_db)

View File

@@ -6,13 +6,14 @@ gnpy.core.parameters
====================
This module contains all parameters to configure standard network elements.
"""
from collections import namedtuple
from scipy.constants import c, pi
from numpy import asarray, array, exp, sqrt, log, outer, ones, squeeze, append, flip, linspace, full
from numpy import squeeze, log10, exp
from gnpy.core.utils import convert_length
from gnpy.core.utils import db2lin, convert_length
from gnpy.core.exceptions import ParametersError
@@ -29,128 +30,110 @@ class Parameters:
class PumpParams(Parameters):
def __init__(self, power, frequency, propagation_direction):
self.power = power
self.frequency = frequency
self.propagation_direction = propagation_direction.lower()
self._power = power
self._frequency = frequency
self._propagation_direction = propagation_direction
@property
def power(self):
return self._power
@property
def frequency(self):
return self._frequency
@property
def propagation_direction(self):
return self._propagation_direction
class RamanParams(Parameters):
def __init__(self, flag=False, result_spatial_resolution=10e3, solver_spatial_resolution=50):
"""Simulation parameters used within the Raman Solver
def __init__(self, **kwargs):
self._flag_raman = kwargs['flag_raman']
self._space_resolution = kwargs['space_resolution'] if 'space_resolution' in kwargs else None
self._tolerance = kwargs['tolerance'] if 'tolerance' in kwargs else None
:params flag: boolean for enabling/disable the evaluation of the Raman power profile in frequency and position
:params result_spatial_resolution: spatial resolution of the evaluated Raman power profile
:params solver_spatial_resolution: spatial step for the iterative solution of the first order ode
"""
self.flag = flag
self.result_spatial_resolution = result_spatial_resolution # [m]
self.solver_spatial_resolution = solver_spatial_resolution # [m]
@property
def flag_raman(self):
return self._flag_raman
@property
def space_resolution(self):
return self._space_resolution
@property
def tolerance(self):
return self._tolerance
class NLIParams(Parameters):
def __init__(self, method='gn_model_analytic', dispersion_tolerance=1, phase_shift_tolerance=0.1,
computed_channels=None):
"""Simulation parameters used within the Nli Solver
def __init__(self, **kwargs):
self._nli_method_name = kwargs['nli_method_name']
self._wdm_grid_size = kwargs['wdm_grid_size']
self._dispersion_tolerance = kwargs['dispersion_tolerance']
self._phase_shift_tolerance = kwargs['phase_shift_tolerance']
self._f_cut_resolution = None
self._f_pump_resolution = None
self._computed_channels = kwargs['computed_channels'] if 'computed_channels' in kwargs else None
:params method: formula for NLI calculation
:params dispersion_tolerance: tuning parameter for ggn model solution
:params phase_shift_tolerance: tuning parameter for ggn model solution
:params computed_channels: the NLI is evaluated for these channels and extrapolated for the others
"""
self.method = method.lower()
self.dispersion_tolerance = dispersion_tolerance
self.phase_shift_tolerance = phase_shift_tolerance
self.computed_channels = computed_channels
@property
def nli_method_name(self):
return self._nli_method_name
@property
def wdm_grid_size(self):
return self._wdm_grid_size
@property
def dispersion_tolerance(self):
return self._dispersion_tolerance
@property
def phase_shift_tolerance(self):
return self._phase_shift_tolerance
@property
def f_cut_resolution(self):
return self._f_cut_resolution
@f_cut_resolution.setter
def f_cut_resolution(self, f_cut_resolution):
self._f_cut_resolution = f_cut_resolution
@property
def f_pump_resolution(self):
return self._f_pump_resolution
@f_pump_resolution.setter
def f_pump_resolution(self, f_pump_resolution):
self._f_pump_resolution = f_pump_resolution
@property
def computed_channels(self):
return self._computed_channels
class SimParams(Parameters):
_shared_dict = {'nli_params': NLIParams(), 'raman_params': RamanParams()}
@classmethod
def set_params(cls, sim_params):
cls._shared_dict['nli_params'] = NLIParams(**sim_params.get('nli_params', {}))
cls._shared_dict['raman_params'] = RamanParams(**sim_params.get('raman_params', {}))
def __init__(self, **kwargs):
try:
if 'nli_parameters' in kwargs:
self._nli_params = NLIParams(**kwargs['nli_parameters'])
else:
self._nli_params = None
if 'raman_parameters' in kwargs:
self._raman_params = RamanParams(**kwargs['raman_parameters'])
else:
self._raman_params = None
except KeyError as e:
raise ParametersError(f'Simulation parameters must include {e}. Configuration: {kwargs}')
@property
def nli_params(self):
return self._shared_dict['nli_params']
return self._nli_params
@property
def raman_params(self):
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 DAmico, 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
"""
return self._raman_params
class FiberParams(Parameters):
@@ -158,87 +141,45 @@ class FiberParams(Parameters):
try:
self._length = convert_length(kwargs['length'], kwargs['length_units'])
# fixed attenuator for padding
self._att_in = kwargs.get('att_in', 0)
self._att_in = kwargs['att_in'] if 'att_in' in kwargs else 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.get('con_in')
self._con_out = kwargs.get('con_out')
# Reference frequency (unique for all parameters: beta2, beta3, gamma, effective_area)
self._con_in = kwargs['con_in'] if 'con_in' in kwargs else None
self._con_out = kwargs['con_out'] if 'con_out' in kwargs else None
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 # conventional central C band wavelength [m]
self._ref_frequency = c / self._ref_wavelength
# Chromatic Dispersion
if 'dispersion_per_frequency' in kwargs:
# Frequency-dependent dispersion
self._dispersion = asarray(kwargs['dispersion_per_frequency']['value']) # s/m/m
self._f_dispersion_ref = asarray(kwargs['dispersion_per_frequency']['frequency']) # Hz
self._dispersion_slope = None
elif 'dispersion' in kwargs:
# Single value dispersion
self._dispersion = asarray(kwargs['dispersion']) # s/m/m
self._dispersion_slope = kwargs.get('dispersion_slope') # s/m/m/m
self._f_dispersion_ref = asarray(self._ref_frequency) # Hz
else:
# Default single value dispersion
self._dispersion = asarray(1.67e-05) # s/m/m
self._dispersion_slope = None
self._f_dispersion_ref = asarray(self.ref_frequency) # Hz
# Effective Area and Nonlinear Coefficient
self._effective_area = kwargs.get('effective_area') # m^2
self._n1 = 1.468
self._core_radius = 4.2e-6 # m
self._n2 = 2.6e-20 # m^2/W
if self._effective_area is not None:
default_gamma = 2 * pi * self._n2 / (self._ref_wavelength * self._effective_area)
self._gamma = kwargs.get('gamma', default_gamma) # 1/W/m
elif 'gamma' in kwargs:
self._gamma = kwargs['gamma'] # 1/W/m
self._effective_area = 2 * pi * self._n2 / (self._ref_wavelength * self._gamma) # m^2
else:
self._effective_area = 83e-12 # m^2
self._gamma = 2 * pi * self._n2 / (self._ref_wavelength * self._effective_area) # 1/W/m
self._contrast = 0.5 * (c / (2 * pi * self._ref_frequency * self._core_radius * self._n1) * exp(
pi * self._core_radius ** 2 / self._effective_area)) ** 2
# Raman Gain Coefficient
raman_coefficient = kwargs.get('raman_coefficient', DEFAULT_RAMAN_COEFFICIENT)
self._g0 = asarray(raman_coefficient['g0'])
raman_reference_frequency = raman_coefficient['reference_frequency']
frequency_offset = asarray(raman_coefficient['frequency_offset'])
stokes_wave = raman_reference_frequency - frequency_offset
gamma_raman = self._g0 * self.effective_area_overlap(stokes_wave, raman_reference_frequency)
normalized_gamma_raman = gamma_raman / raman_reference_frequency # 1 / m / W / Hz
self._raman_reference_frequency = raman_reference_frequency
# Raman gain coefficient array of the frequency offset constructed such that positive frequency values
# represent a positive power transfer from higher frequency and vice versa
frequency_offset = append(-flip(frequency_offset[1:]), frequency_offset)
normalized_gamma_raman = append(- flip(normalized_gamma_raman[1:]), normalized_gamma_raman)
self._raman_coefficient = RamanGainCoefficient(normalized_gamma_raman, frequency_offset)
# Polarization Mode Dispersion
self._ref_wavelength = 1550e-9
self._ref_frequency = c / self.ref_wavelength
self._dispersion = kwargs['dispersion'] # s/m/m
self._dispersion_slope = kwargs['dispersion_slope'] if 'dispersion_slope' in kwargs else \
-2 * self._dispersion/self.ref_wavelength # s/m/m/m
self._beta2 = -(self.ref_wavelength ** 2) * self.dispersion / (2 * pi * c) # 1/(m * Hz^2)
# Eq. (3.23) in Abramczyk, Halina. "Dispersion phenomena in optical fibers." Virtual European University
# on Lasers. Available online: http://mitr.p.lodz.pl/evu/lectures/Abramczyk3.pdf
# (accessed on 25 March 2018) (2005).
self._beta3 = ((self.dispersion_slope - (4*pi*c/self.ref_wavelength**3) * self.beta2) /
(2*pi*c/self.ref_wavelength**2)**2)
self._gamma = kwargs['gamma'] # 1/W/m
self._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
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 = 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
self._loss_coef = kwargs['loss_coef'] * 1e-3 # lineic loss dB/m
self._f_loss_ref = 193.5e12 # Hz
self._lin_attenuation = db2lin(self.length * self.loss_coef)
self._lin_loss_exp = self.loss_coef / (10 * log10(exp(1))) # linear power exponent loss Neper/m
self._effective_length = (1 - exp(- self.lin_loss_exp * self.length)) / self.lin_loss_exp
self._asymptotic_length = 1 / self.lin_loss_exp
# raman parameters (not compulsory)
self._raman_efficiency = kwargs['raman_efficiency'] if 'raman_efficiency' in kwargs else None
self._pumps_loss_coef = kwargs['pumps_loss_coef'] if 'pumps_loss_coef' in kwargs else None
except KeyError as e:
raise ParametersError(f'Fiber configurations json must include {e}. Configuration: {kwargs}')
@@ -271,10 +212,6 @@ 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
@@ -283,10 +220,6 @@ 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
@@ -295,20 +228,6 @@ 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
@@ -321,6 +240,14 @@ 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
@@ -330,148 +257,31 @@ class FiberParams(Parameters):
return self._f_loss_ref
@property
def raman_coefficient(self):
return self._raman_coefficient
def lin_loss_exp(self):
return self._lin_loss_exp
@property
def latency(self):
return self._latency
def lin_attenuation(self):
return self._lin_attenuation
@property
def effective_length(self):
return self._effective_length
@property
def asymptotic_length(self):
return self._asymptotic_length
@property
def raman_efficiency(self):
return self._raman_efficiency
@property
def pumps_loss_coef(self):
return self._pumps_loss_coef
def 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})')

File diff suppressed because it is too large Load Diff

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@@ -1,18 +1,18 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
'''
gnpy.core.utils
===============
This module contains utility functions that are used with gnpy.
"""
'''
from csv import writer
from numpy import pi, cos, sqrt, log10, linspace, zeros, shape, where, logical_and, mean
import numpy as np
from numpy import pi, cos, sqrt, log10
from scipy import constants
from copy import deepcopy
from gnpy.core.exceptions import ConfigurationError
@@ -70,7 +70,7 @@ def arrange_frequencies(length, start, stop):
:return: an array of frequencies determined by the spacing parameter
:rtype: numpy.ndarray
"""
return linspace(start, stop, length)
return np.linspace(start, stop, length)
def lin2db(value):
@@ -107,99 +107,7 @@ 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)
@@ -214,7 +122,7 @@ 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
@@ -230,33 +138,8 @@ 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
@@ -274,9 +157,9 @@ def deltawl2deltaf(delta_wl, wavelength):
def deltaf2deltawl(delta_f, frequency):
"""convert delta frequency to delta wavelength
Units for delta_wl and wavelength must be same.
""" deltawl2deltaf(delta_f, frequency):
converts delta frequency to delta wavelength
units for delta_wl and wavelength must be same
:param delta_f: delta frequency in same units as frequency
:param frequency: frequency BW is relevant for
@@ -291,7 +174,8 @@ def deltaf2deltawl(delta_f, frequency):
def rrc(ffs, baud_rate, alpha):
"""compute the root-raised cosine filter function
""" rrc(ffs, baud_rate, alpha): computes the root-raised cosine filter
function.
:param ffs: A numpy array of frequencies
:param baud_rate: The Baud Rate of the System
@@ -306,18 +190,18 @@ def rrc(ffs, baud_rate, alpha):
Ts = 1 / baud_rate
l_lim = (1 - alpha) / (2 * Ts)
r_lim = (1 + alpha) / (2 * Ts)
hf = zeros(shape(ffs))
slope_inds = where(
logical_and(abs(ffs) > l_lim, abs(ffs) < r_lim))
hf = np.zeros(np.shape(ffs))
slope_inds = np.where(
np.logical_and(np.abs(ffs) > l_lim, np.abs(ffs) < r_lim))
hf[slope_inds] = 0.5 * (1 + cos((pi * Ts / alpha) *
(abs(ffs[slope_inds]) - l_lim)))
p_inds = where(logical_and(abs(ffs) > 0, abs(ffs) < l_lim))
(np.abs(ffs[slope_inds]) - l_lim)))
p_inds = np.where(np.logical_and(np.abs(ffs) > 0, np.abs(ffs) < l_lim))
hf[p_inds] = 1
return sqrt(hf)
def merge_amplifier_restrictions(dict1, dict2):
"""Update contents of dicts recursively
"""Updates contents of dicts recursively
>>> d1 = {'params': {'restrictions': {'preamp_variety_list': [], 'booster_variety_list': []}}}
>>> d2 = {'params': {'target_pch_out_db': -20}}
@@ -412,43 +296,3 @@ 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]

View File

@@ -1,13 +1,13 @@
{
"nf_fit_coeff": [
"nf_fit_coeff": [
0.0008,
0.0272,
-0.2249,
6.4902
],
"f_min": 191.4e12,
"f_max": 196.1e12,
"nf_ripple": [
],
"f_min": 191.35e12,
"f_max": 196.1e12,
"nf_ripple": [
0.0,
0.0,
0.0,
@@ -58,103 +58,103 @@
0.0
],
"gain_ripple": [
-0.15656302345061,
-0.22244242043552,
-0.25188965661642,
-0.23575900335007,
-0.20897508375209,
-0.19440221943049,
-0.18324644053602,
-0.18053287269681,
-0.17113588777219,
-0.15460322445561,
-0.13550774706866,
-0.10606051088777,
-0.0765630234506,
-0.04962835008375,
-0.01319618927973,
0.01027114740367,
0.03378873534338,
0.04961788107202,
0.04494451423784,
0.0399193886097,
0.01584903685091,
-0.00420121440538,
-0.01847257118928,
-0.02475397822447,
-0.01053287269681,
0.01509526800668,
0.05921587102177,
0.1191656197655,
0.18147717755444,
0.23579878559464,
0.26941687604691,
0.27836159966498,
0.26956762981574,
0.23826109715241,
0.18936662479061,
0.1204721524288,
0.0453465242881,
-0.00877407872698,
-0.02199015912898,
0.00107516750419,
0.02795958961474,
0.02740682579566,
-0.01028161641541,
-0.05982935510889,
-0.06701528475711,
0.00223094639866,
0.15017064489112,
0.14157768006701,
0.15017064489112
0.00223094639866,
-0.06701528475711,
-0.05982935510889,
-0.01028161641541,
0.02740682579566,
0.02795958961474,
0.00107516750419,
-0.02199015912898,
-0.00877407872698,
0.0453465242881,
0.1204721524288,
0.18936662479061,
0.23826109715241,
0.26956762981574,
0.27836159966498,
0.26941687604691,
0.23579878559464,
0.18147717755444,
0.1191656197655,
0.05921587102177,
0.01509526800668,
-0.01053287269681,
-0.02475397822447,
-0.01847257118928,
-0.00420121440538,
0.01584903685091,
0.0399193886097,
0.04494451423784,
0.04961788107202,
0.03378873534338,
0.01027114740367,
-0.01319618927973,
-0.04962835008375,
-0.0765630234506,
-0.10606051088777,
-0.13550774706866,
-0.15460322445561,
-0.17113588777219,
-0.18053287269681,
-0.18324644053602,
-0.19440221943049,
-0.20897508375209,
-0.23575900335007,
-0.25188965661642,
-0.22244242043552,
-0.15656302345061
],
"dgt": [
1.0,
1.03941448941778,
1.07773189112355,
1.11575888725852,
1.15209185089701,
1.18632744096844,
1.21911100318577,
1.24931318255134,
1.27657903892303,
1.30069883494415,
1.32210817897091,
1.3405812000038,
1.35690844654118,
1.3710092503689,
1.38430337205545,
1.3966294751726,
1.40864903907609,
1.42089447397912,
1.43476940680732,
1.44977369463316,
1.46637521309853,
1.48420288841848,
1.50335352244996,
1.5242627235492,
1.54578500307573,
1.56750088631614,
1.58973304612691,
1.61073904908309,
1.63068023161292,
1.64799163036252,
1.66286684904577,
1.6761448370895,
1.68845480656382,
1.70379790088896,
1.72461030013125,
1.75428006928365,
1.79748596476494,
1.85543800978691,
1.92915262384742,
2.01414465424155,
2.10336369905543,
2.19013043016015,
2.26678136721453,
2.33147727493671,
2.38192717604575,
2.41879254989742,
2.4553191172498,
2.44342862248888,
2.4553191172498
2.41879254989742,
2.38192717604575,
2.33147727493671,
2.26678136721453,
2.19013043016015,
2.10336369905543,
2.01414465424155,
1.92915262384742,
1.85543800978691,
1.79748596476494,
1.75428006928365,
1.72461030013125,
1.70379790088896,
1.68845480656382,
1.6761448370895,
1.66286684904577,
1.64799163036252,
1.63068023161292,
1.61073904908309,
1.58973304612691,
1.56750088631614,
1.54578500307573,
1.5242627235492,
1.50335352244996,
1.48420288841848,
1.46637521309853,
1.44977369463316,
1.43476940680732,
1.42089447397912,
1.40864903907609,
1.3966294751726,
1.38430337205545,
1.3710092503689,
1.35690844654118,
1.3405812000038,
1.32210817897091,
1.30069883494415,
1.27657903892303,
1.24931318255134,
1.21911100318577,
1.18632744096844,
1.15209185089701,
1.11575888725852,
1.07773189112355,
1.03941448941778,
1.0
]
}

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File diff suppressed because it is too large Load Diff

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@@ -5,104 +5,102 @@
"gain_ripple": [
0.0
],
"f_min": 191.35e12,
"f_max": 196.1e12,
"dgt": [
1.0,
1.017807767853702,
1.0356155337864215,
1.0534217504465226,
1.0712204022764056,
1.0895983485572227,
1.108555289615659,
1.1280891949729075,
1.1476135933863398,
1.1672278304018044,
1.1869318618366975,
1.2067249615595257,
1.2264996957264114,
1.2428104897182262,
1.2556591482982988,
1.2650555289898042,
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]
}

View File

@@ -227,7 +227,7 @@ In an opensource and multi-vendor environnement, it is needed to support differe
.. code-block:: json-object
"Edfa":[{
"type_variety": "openroadm_ila_low_noise",
"type_variety": "low_noise",
"type_def": "openroadm",
"gain_flatmax": 27,
"gain_min": 12,

View File

@@ -29,58 +29,24 @@
"allowed_for_design": false
},
{
"type_variety": "openroadm_ila_low_noise",
"type_variety": "low_noise",
"type_def": "openroadm",
"gain_flatmax": 27,
"gain_min": 0,
"gain_min": 12,
"p_max": 22,
"nf_coef": [-8.104e-4,-6.221e-2,-5.889e-1,37.62],
"allowed_for_design": false
},
{
"type_variety": "openroadm_ila_standard",
"type_variety": "standard",
"type_def": "openroadm",
"gain_flatmax": 27,
"gain_min": 0,
"gain_min": 12,
"p_max": 22,
"nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
"allowed_for_design": false
},
{
"type_variety": "openroadm_mw_mw_preamp",
"type_def": "openroadm_preamp",
"gain_flatmax": 27,
"gain_min": 0,
"p_max": 22,
"allowed_for_design": false
},
{
"type_variety": "openroadm_mw_mw_preamp_typical_ver5",
"type_def": "openroadm",
"gain_flatmax": 27,
"gain_min": 0,
"p_max": 22,
"nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
"allowed_for_design": false
},
{
"type_variety": "openroadm_mw_mw_preamp_worstcase_ver5",
"type_def": "openroadm",
"gain_flatmax": 27,
"gain_min": 0,
"p_max": 22,
"nf_coef": [-5.952e-4,-6.250e-2,-1.071,27.99],
"allowed_for_design": false
},
{
"type_variety": "openroadm_mw_mw_booster",
"type_def": "openroadm_booster",
"gain_flatmax": 32,
"gain_min": 0,
"p_max": 22,
"allowed_for_design": false
},
{
"type_variety": "std_high_gain",
"type_def": "variable_gain",
"gain_flatmax": 35,
@@ -180,27 +146,51 @@
"Fiber":[{
"type_variety": "SSMF",
"dispersion": 1.67e-05,
"effective_area": 83e-12,
"gamma": 0.00127,
"pmd_coef": 1.265e-15
},
{
"type_variety": "NZDF",
"dispersion": 0.5e-05,
"effective_area": 72e-12,
"gamma": 0.00146,
"pmd_coef": 1.265e-15
},
{
"type_variety": "LOF",
"dispersion": 2.2e-05,
"effective_area": 125e-12,
"gamma": 0.000843,
"pmd_coef": 1.265e-15
}
],
"RamanFiber":[{
"type_variety": "SSMF",
"dispersion": 1.67e-05,
"effective_area": 83e-12,
"pmd_coef": 1.265e-15
"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":[{
@@ -221,7 +211,6 @@
"target_pch_out_db": -20,
"add_drop_osnr": 38,
"pmd": 0,
"pdl": 0,
"restrictions": {
"preamp_variety_list":[],
"booster_variety_list":[]

View File

@@ -1,349 +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],
"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,
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},
{
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},
{
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},
{
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},
{
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}
],
"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
},
{
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},
{
"pmd": 25,
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},
{
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},
{
"pdl": 2,
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},
{
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}
],
"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
},
{
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},
{
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},
{
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},
{
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{
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}
],
"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
},
{
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{
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{
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{
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{
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],
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"cost": 1
}
]
}
]
}

View File

@@ -1,409 +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],
"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,
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View File

@@ -1,12 +0,0 @@
{
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View File

@@ -1,23 +0,0 @@
{
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View File

@@ -624,70 +624,6 @@
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{
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{
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{
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{
"uid": "east edfa in Lannion_CAS to Corlay",
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{
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{
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}
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}
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}
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@@ -1254,34 +1190,18 @@
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View File

@@ -20,12 +20,12 @@
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{

View File

@@ -1,13 +1,14 @@
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View File

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}
{ "nf_fit_coeff": [
0.000168241,
0.0469961,
0.0359549,
5.82851
],
"f_min": 191.35e12,
"f_max": 196.1e12,
"nf_ripple": [
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],
"dgt": [
2.714526681131686,
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"gain_ripple": [
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]
}

View File

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

View File

@@ -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`.
"""
'''

View File

@@ -1,34 +1,36 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
'''
gnpy.tools.cli_examples
=======================
Common code for CLI examples
"""
'''
import argparse
from json import dumps
import logging
import os.path
import sys
from math import ceil
from numpy import linspace, mean
from pathlib import Path
import gnpy.core.ansi_escapes as ansi_escapes
from 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 add_missing_elements_in_network, design_network
from gnpy.core.network import build_network
from gnpy.core.parameters import SimParams
from gnpy.core.utils import db2lin, lin2db, automatic_nch, watt2dbm, dbm2watt
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)
PathRequest, compute_constrained_path, propagate2)
from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum
from gnpy.tools.json_io import (load_equipment, load_network, load_json, load_requests, save_network,
requests_from_json, disjunctions_from_json, save_json, load_initial_spectrum)
from gnpy.tools.json_io import load_equipment, load_network, load_json, load_requests, save_network, \
requests_from_json, disjunctions_from_json, save_json
from gnpy.tools.plots import plot_baseline, plot_results
_logger = logging.getLogger(__name__)
@@ -48,7 +50,7 @@ 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)
@@ -56,27 +58,26 @@ 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}')
if not simulation_filename:
sim_params = {}
sim_params = SimParams(**load_json(simulation_filename)) if simulation_filename is not None else None
if not 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:
sim_params = load_json(simulation_filename)
SimParams.set_params(sim_params)
Simulation.set_params(sim_params)
except exceptions.EquipmentConfigError as e:
print(f'{ansi_escapes.red}Configuration error in the equipment library:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.NetworkTopologyError as e:
print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ParametersError as e:
print(f'{ansi_escapes.red}Simulation parameters error:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ConfigurationError as e:
print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ParametersError as e:
print(f'{ansi_escapes.red}Simulation parameters error:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ServiceError as e:
print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {e}')
sys.exit(1)
@@ -85,7 +86,7 @@ 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.WARNING}.get(args.verbose, logging.DEBUG))
logging.basicConfig(level={2: logging.DEBUG, 1: logging.INFO, 0: logging.CRITICAL}.get(args.verbose, logging.DEBUG))
def _add_common_options(parser: argparse.ArgumentParser, network_default: Path):
@@ -103,9 +104,6 @@ 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):
@@ -115,11 +113,10 @@ def transmission_main_example(args=None):
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
_add_common_options(parser, network_default=_examples_dir / 'edfa_example_network.json')
parser.add_argument('--show-channels', action='store_true', help='Show final per-channel OSNR and GSNR summary')
parser.add_argument('--show-channels', action='store_true', help='Show final per-channel OSNR summary')
parser.add_argument('-pl', '--plot', action='store_true')
parser.add_argument('-l', '--list-nodes', action='store_true', help='list all transceiver nodes')
parser.add_argument('-po', '--power', default=0, help='channel ref power in dBm')
parser.add_argument('--spectrum', type=Path, help='user defined mixed rate spectrum JSON file')
parser.add_argument('source', nargs='?', help='source node')
parser.add_argument('destination', nargs='?', help='destination node')
@@ -196,76 +193,40 @@ def transmission_main_example(args=None):
if args.power:
trx_params['power'] = db2lin(float(args.power)) * 1e-3
params.update(trx_params)
initial_spectrum = None
params['nb_channel'] = automatic_nch(trx_params['f_min'], trx_params['f_max'], trx_params['spacing'])
# use ref_req to hold reference channel used for design and req for the propagation
# and req to hold channels to be propagated
# apply power sweep on the design and on the channels
ref_req = PathRequest(**params)
pref_ch_db = watt2dbm(ref_req.power)
if args.spectrum:
# use the spectrum defined by user for the propagation.
# the nb of channel for design remains the one of the reference channel
initial_spectrum = load_initial_spectrum(args.spectrum)
params['nb_channel'] = len(initial_spectrum)
print('User input for spectrum used for propagation instead of SI')
req = PathRequest(**params)
p_ch_db = watt2dbm(req.power)
req.initial_spectrum = initial_spectrum
print(f'There are {req.nb_channel} channels propagating')
power_mode = equipment['Span']['default'].power_mode
print('\n'.join([f'Power mode is set to {power_mode}',
'=> it can be modified in eqpt_config.json - Span']))
if not args.no_insert_edfas:
try:
add_missing_elements_in_network(network, equipment)
except exceptions.NetworkTopologyError as e:
print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ConfigurationError as e:
print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
sys.exit(1)
f'=> it can be modified in eqpt_config.json - Span']))
pref_ch_db = lin2db(req.power * 1e3) # reference channel power / span (SL=20dB)
pref_total_db = pref_ch_db + lin2db(req.nb_channel) # reference total power / span (SL=20dB)
build_network(network, equipment, pref_ch_db, pref_total_db)
path = compute_constrained_path(network, req)
spans = [s.params.length for s in path if isinstance(s, RamanFiber) or isinstance(s, Fiber)]
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]')
# initial network is designed using req.power. that is that any missing information (amp gain or delta_p) is filled
# using this req.power, previous to any sweep requested later on.
try:
design_network(ref_req, network, equipment, set_connector_losses=True, verbose=True)
except exceptions.NetworkTopologyError as e:
print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ConfigurationError as e:
print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
sys.exit(1)
spans = [s.params.length for s in path if isinstance(s, RamanFiber) or isinstance(s, Fiber)]
print(f'\nThere are {len(spans)} fiber spans over {sum(spans)/1000:.0f} km between {source.uid} '
f'and {destination.uid}')
print(f'\nNow propagating between {source.uid} and {destination.uid}:')
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:
ref_req.power = dbm2watt(pref_ch_db + dp_db)
req.power = dbm2watt(p_ch_db + dp_db)
design_network(ref_req, network, equipment, set_connector_losses=False, verbose=False)
# 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)
req.power = db2lin(pref_ch_db + dp_db) * 1e-3
if power_mode:
print(f'\nPropagating with input power = {ansi_escapes.cyan}{watt2dbm(req.power):.2f} '
+ f'dBm{ansi_escapes.reset}:')
print(f'\nPropagating with input power = {ansi_escapes.cyan}{lin2db(req.power*1e3):.2f} dBm{ansi_escapes.reset}:')
else:
print(f'\nPropagating in {ansi_escapes.cyan}gain mode{ansi_escapes.reset}: power cannot be set manually')
infos = propagate(path, req, equipment)
infos = propagate2(path, req, equipment)
if len(power_range) == 1:
for elem in path:
print(elem)
@@ -273,16 +234,21 @@ def transmission_main_example(args=None):
print(f'\nTransmission result for input power = {lin2db(req.power*1e3):.2f} dBm:')
else:
print(f'\nTransmission results:')
print(f' Final GSNR (0.1 nm): {ansi_escapes.cyan}{mean(destination.snr_01nm):.02f} dB{ansi_escapes.reset}')
print(f' Final SNR total (0.1 nm): {ansi_escapes.cyan}{mean(destination.snr_01nm):.02f} dB{ansi_escapes.reset}')
else:
print(path[-1])
# print(f'\n !!!!!!!!!!!!!!!!! TEST POINT !!!!!!!!!!!!!!!!!!!!!')
# print(f'carriers ase output of {path[1]} =\n {list(path[1].carriers("out", "nli"))}')
# => use "in" or "out" parameter
# => use "nli" or "ase" or "signal" or "total" parameter
if args.save_network is not None:
save_network(network, args.save_network)
print(f'{ansi_escapes.blue}Network (after autodesign) saved to {args.save_network}{ansi_escapes.reset}')
if args.show_channels:
print('\nThe GSNR per channel at the end of the line is:')
print('\nThe total SNR per channel at the end of the line is:')
print(
'{:>5}{:>26}{:>26}{:>28}{:>28}{:>28}' .format(
'Ch. #',
@@ -290,15 +256,15 @@ def transmission_main_example(args=None):
'Channel power (dBm)',
'OSNR ASE (signal bw, dB)',
'SNR NLI (signal bw, dB)',
'GSNR (signal bw, dB)'))
'SNR total (signal bw, dB)'))
for final_carrier, ch_osnr, ch_snr_nl, ch_snr in zip(
infos.carriers, path[-1].osnr_ase, path[-1].osnr_nli, path[-1].snr):
infos[path[-1]][1].carriers, path[-1].osnr_ase, path[-1].osnr_nli, path[-1].snr):
ch_freq = final_carrier.frequency * 1e-12
ch_power = lin2db(final_carrier.power.signal * 1e3)
print(
'{:5}{:26.5f}{:26.2f}{:28.2f}{:28.2f}{:28.2f}' .format(
'{:5}{:26.2f}{:26.2f}{:28.2f}{:28.2f}{:28.2f}' .format(
final_carrier.channel_number, round(
ch_freq, 5), round(
ch_freq, 2), round(
ch_power, 2), round(
ch_osnr, 2), round(
ch_snr_nl, 2), round(
@@ -315,7 +281,7 @@ def transmission_main_example(args=None):
print(f'\n(Invalid destination node {args.destination!r} replaced with {destination.uid})')
if args.plot:
plot_results(network, path, source, destination)
plot_results(network, path, source, destination, infos)
def _path_result_json(pathresult):
@@ -340,50 +306,19 @@ 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.name} into JSON format')
_logger.info(f'Computing path requests {args.service_filename} into JSON format')
print(f'{ansi_escapes.blue}Computing path requests {os.path.relpath(args.service_filename)} into JSON format{ansi_escapes.reset}')
(equipment, network) = load_common_data(args.equipment, args.topology, args.sim_params, args.save_network_before_autodesign)
# Build the network once using the default power defined in SI in eqpt config
# TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
# spacing, f_min and f_max
if not args.no_insert_edfas:
try:
add_missing_elements_in_network(network, equipment)
except exceptions.NetworkTopologyError as e:
print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ConfigurationError as e:
print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
sys.exit(1)
params = {
'request_id': 'reference',
'trx_type': '',
'trx_mode': '',
'source': None,
'destination': None,
'bidir': False,
'nodes_list': [],
'loose_list': [],
'format': '',
'path_bandwidth': 0,
'effective_freq_slot': None,
'nb_channel': automatic_nch(equipment['SI']['default'].f_min, equipment['SI']['default'].f_max,
equipment['SI']['default'].spacing)
}
trx_params = trx_mode_params(equipment)
params.update(trx_params)
reference_channel = PathRequest(**params)
try:
design_network(reference_channel, network, equipment, verbose=True)
except exceptions.NetworkTopologyError as e:
print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ConfigurationError as e:
print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
sys.exit(1)
p_db = equipment['SI']['default'].power_dbm
p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
build_network(network, equipment, p_db, p_total_db)
if args.save_network is not None:
save_network(network, args.save_network)
print(f'{ansi_escapes.blue}Network (after autodesign) saved to {args.save_network}{ansi_escapes.reset}')
@@ -441,7 +376,7 @@ def path_requests_run(args=None):
pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
print(f'{ansi_escapes.blue}Result summary{ansi_escapes.reset}')
header = ['req id', ' demand', ' GSNR@bandwidth A-Z (Z-A)', ' GSNR@0.1nm A-Z (Z-A)',
header = ['req id', ' demand', ' snr@bandwidth A-Z (Z-A)', ' snr@0.1nm A-Z (Z-A)',
' Receiver minOSNR', ' mode', ' Gbit/s', ' nb of tsp pairs',
'N,M or blocking reason']
data = []
@@ -467,8 +402,7 @@ def path_requests_run(args=None):
f'-', f'{rqs[i].blocking_reason}']
except AttributeError:
line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} : ', psnrb,
psnr, f'{rqs[i].OSNR + equipment["SI"]["default"].sys_margins}',
f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9,2)}',
psnr, f'{rqs[i].OSNR}', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9,2)}',
f'{ceil(rqs[i].path_bandwidth / rqs[i].bit_rate) }', f'({rqs[i].N},{rqs[i].M})']
data.append(line)
@@ -480,7 +414,7 @@ def path_requests_run(args=None):
secondcol = ''.join(row[1].ljust(secondcol_width))
remainingcols = ''.join(word.center(col_width, ' ') for word in row[2:])
print(f'{firstcol} {secondcol} {remainingcols}')
print(f'{ansi_escapes.yellow}Result summary shows mean GSNR and OSNR (average over all channels){ansi_escapes.reset}')
print(f'{ansi_escapes.yellow}Result summary shows mean SNR and OSNR (average over all channels){ansi_escapes.reset}')
if args.output:
result = []

View File

@@ -20,23 +20,20 @@ In the "Links" sheet, only the first three columns ("Node A", "Node Z" and
the "east" information so that it is possible to input undirected data.
"""
from sys import exit
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))
@@ -127,23 +124,6 @@ class Eqpt(object):
}
class Roadm(object):
def __init__(self, **kwargs):
super(Roadm, self).__init__()
self.update_attr(kwargs)
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():
v = clean_kwargs.get(k, v)
setattr(self, k, v)
default_values = {'from_node': '',
'to_node': '',
'target_pch_out_db': None
}
def read_header(my_sheet, line, slice_):
""" return the list of headers !:= ''
header_i = [(header, header_column_index), ...]
@@ -187,18 +167,18 @@ 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'):
raise NetworkTopologyError(msg)
print(f'{ansi_escapes.red}CRITICAL{ansi_escapes.reset}: missing _{h0}_ header: EXECUTION ENDS')
exit()
else:
_logger.warning(msg)
print(f'missing header {h0}')
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 == {}:
msg = 'CRITICAL ERROR: could not find any header to read _ ABORT'
raise NetworkTopologyError(msg)
print(f'{ansi_escapes.red}CRITICAL ERROR{ansi_escapes.reset}: could not find any header to read _ ABORT')
exit()
return headers
@@ -213,86 +193,40 @@ def parse_sheet(my_sheet, input_headers_dict, header_line, start_line, column):
yield parse_row(row[0: column], headers)
def _format_items(items):
return '\n'.join(f' - {item}' for item in items)
def sanity_check(nodes, links, nodes_by_city, links_by_city, eqpts_by_city):
duplicate_links = []
for l1 in links:
for l2 in links:
if l1 is not l2 and l1 == l2 and l2 not in duplicate_links:
_logger.warning(f'\nWARNING\n \
print(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)
if duplicate_links:
msg = 'XLS error: ' \
+ f'links {_format_items([(d.from_city, d.to_city) for d in duplicate_links])} are duplicate'
raise NetworkTopologyError(msg)
unreferenced_nodes = [n for n in nodes_by_city if n not in links_by_city]
if unreferenced_nodes:
msg = 'XLS error: The following nodes are not ' \
+ 'referenced from the Links sheet. ' \
+ 'If unused, remove them from the Nodes sheet:\n' \
+ _format_items(unreferenced_nodes)
raise NetworkTopologyError(msg)
# no need to check "Links" for invalid nodes because that's already in parse_excel()
wrong_eqpt_from = [n for n in eqpts_by_city if n not in nodes_by_city]
wrong_eqpt_to = [n.to_city for destinations in eqpts_by_city.values()
for n in destinations if n.to_city not in nodes_by_city]
wrong_eqpt = wrong_eqpt_from + wrong_eqpt_to
if wrong_eqpt:
msg = 'XLS error: ' \
+ 'The Eqpt sheet refers to nodes that ' \
+ 'are not defined in the Nodes sheet:\n'\
+ _format_items(wrong_eqpt)
raise NetworkTopologyError(msg)
# Now check links that are not listed in Links sheet, and duplicates
bad_eqpt = []
possible_links = [f'{e.from_city}|{e.to_city}' for e in links] + [f'{e.to_city}|{e.from_city}' for e in links]
possible_eqpt = []
duplicate_eqpt = []
duplicate_ila = []
for city, eqpts in eqpts_by_city.items():
for eqpt in eqpts:
# Check that each node_A-node_Z exists in links
nodea_nodez = f'{eqpt.from_city}|{eqpt.to_city}'
nodez_nodea = f'{eqpt.to_city}|{eqpt.from_city}'
if nodea_nodez not in possible_links \
or nodez_nodea not in possible_links:
bad_eqpt.append([eqpt.from_city, eqpt.to_city])
else:
# Check that there are no duplicate lines in the Eqpt sheet
if nodea_nodez in possible_eqpt:
duplicate_eqpt.append([eqpt.from_city, eqpt.to_city])
else:
possible_eqpt.append(nodea_nodez)
# check that there are no two lines defining an ILA with different directions
if nodes_by_city[city].node_type == 'ILA' and len(eqpts) > 1:
duplicate_ila.append(city)
if bad_eqpt:
msg = 'XLS error: ' \
+ 'The Eqpt sheet references links that ' \
+ 'are not defined in the Links sheet:\n' \
+ _format_items(f'{item[0]} -> {item[1]}' for item in bad_eqpt)
raise NetworkTopologyError(msg)
if duplicate_eqpt:
msg = 'XLS error: Duplicate lines in Eqpt sheet:' \
+ _format_items(f'{item[0]} -> {item[1]}' for item in duplicate_eqpt)
raise NetworkTopologyError(msg)
if duplicate_ila:
msg = 'XLS error: Duplicate ILA eqpt definition in Eqpt sheet:' \
+ _format_items(duplicate_ila)
for l in duplicate_links:
links.remove(l)
try:
test_nodes = [n for n in nodes_by_city if n not in links_by_city]
test_links = [n for n in links_by_city if n not in nodes_by_city]
test_eqpts = [n for n in eqpts_by_city if n not in nodes_by_city]
assert (test_nodes == [] or test_nodes == [''])\
and (test_links == [] or test_links == [''])\
and (test_eqpts == [] or test_eqpts == [''])
except AssertionError:
msg = f'CRITICAL error in excel input: Names in Nodes and Links sheets do no match, check:\
\n{test_nodes} in Nodes sheet\
\n{test_links} in Links sheet\
\n{test_eqpts} in Eqpt sheet'
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
_logger.warning(f'invalid node type ({nodes_by_city[city].node_type}) '
+ f'specified in {city}, replaced by ROADM')
# TODO: put in log rather than print
print(f'invalid node type ({nodes_by_city[city].node_type})\
specified in {city}, replaced by ROADM')
nodes_by_city[city].node_type = 'ROADM'
for n in nodes:
if n.city == city:
@@ -300,98 +234,8 @@ def sanity_check(nodes, links, nodes_by_city, links_by_city, eqpts_by_city):
return nodes, links
def create_roadm_element(node, roadms_by_city):
""" create the json element for a roadm node, including the different cases:
- if there are restrictions
- if there are per degree target power defined on a direction
direction is defined by the booster name, so that booster must also be created in eqpt sheet
if the direction is defined in roadm
"""
roadm = {'uid': f'roadm {node.city}'}
if node.preamp_restriction != '' or node.booster_restriction != '':
roadm['params'] = {
'restrictions': {
'preamp_variety_list': silent_remove(node.preamp_restriction.split(' | '), ''),
'booster_variety_list': silent_remove(node.booster_restriction.split(' | '), '')}
}
if node.city in roadms_by_city.keys():
if 'params' not in roadm.keys():
roadm['params'] = {}
roadm['params']['per_degree_pch_out_db'] = {}
for elem in roadms_by_city[node.city]:
to_node = f'east edfa in {node.city} to {elem.to_node}'
if elem.target_pch_out_db is not None:
roadm['params']['per_degree_pch_out_db'][to_node] = elem.target_pch_out_db
roadm['metadata'] = {'location': {'city': node.city,
'region': node.region,
'latitude': node.latitude,
'longitude': node.longitude}}
roadm['type'] = 'Roadm'
return roadm
def create_east_eqpt_element(node):
""" create amplifiers json elements for the east direction.
this includes the case where the case of a fused element defined instead of an
ILA in eqpt sheet
"""
eqpt = {'uid': f'east edfa in {node.from_city} to {node.to_city}',
'metadata': {'location': {'city': nodes_by_city[node.from_city].city,
'region': nodes_by_city[node.from_city].region,
'latitude': nodes_by_city[node.from_city].latitude,
'longitude': nodes_by_city[node.from_city].longitude}}}
if node.east_amp_type.lower() != '' and node.east_amp_type.lower() != 'fused':
eqpt['type'] = 'Edfa'
eqpt['type_variety'] = f'{node.east_amp_type}'
eqpt['operational'] = {'gain_target': node.east_amp_gain,
'delta_p': node.east_amp_dp,
'tilt_target': node.east_tilt,
'out_voa': node.east_att_out}
elif node.east_amp_type.lower() == '':
eqpt['type'] = 'Edfa'
eqpt['operational'] = {'gain_target': node.east_amp_gain,
'delta_p': node.east_amp_dp,
'tilt_target': node.east_tilt,
'out_voa': node.east_att_out}
elif node.east_amp_type.lower() == 'fused':
# fused edfa variety is a hack to indicate that there should not be
# booster amplifier out the roadm.
# If user specifies ILA in Nodes sheet and fused in Eqpt sheet, then assumes that
# this is a fused nodes.
eqpt['type'] = 'Fused'
eqpt['params'] = {'loss': 0}
return eqpt
def create_west_eqpt_element(node):
""" create amplifiers json elements for the west direction.
this includes the case where the case of a fused element defined instead of an
ILA in eqpt sheet
"""
eqpt = {'uid': f'west edfa in {node.from_city} to {node.to_city}',
'metadata': {'location': {'city': nodes_by_city[node.from_city].city,
'region': nodes_by_city[node.from_city].region,
'latitude': nodes_by_city[node.from_city].latitude,
'longitude': nodes_by_city[node.from_city].longitude}},
'type': 'Edfa'}
if node.west_amp_type.lower() != '' and node.west_amp_type.lower() != 'fused':
eqpt['type_variety'] = f'{node.west_amp_type}'
eqpt['operational'] = {'gain_target': node.west_amp_gain,
'delta_p': node.west_amp_dp,
'tilt_target': node.west_tilt,
'out_voa': node.west_att_out}
elif node.west_amp_type.lower() == '':
eqpt['operational'] = {'gain_target': node.west_amp_gain,
'delta_p': node.west_amp_dp,
'tilt_target': node.west_tilt,
'out_voa': node.west_att_out}
elif node.west_amp_type.lower() == 'fused':
eqpt['type'] = 'Fused'
eqpt['params'] = {'loss': 0}
return eqpt
def xls_to_json_data(input_filename, filter_region=[]):
nodes, links, eqpts, roadms = parse_excel(input_filename)
nodes, links, eqpts = parse_excel(input_filename)
if filter_region:
nodes = [n for n in nodes if n.region.lower() in filter_region]
cities = {n.city for n in nodes}
@@ -414,10 +258,6 @@ def xls_to_json_data(input_filename, filter_region=[]):
for eqpt in eqpts:
eqpts_by_city[eqpt.from_city].append(eqpt)
roadms_by_city = defaultdict(list)
for roadm in roadms:
roadms_by_city[roadm.from_node].append(roadm)
nodes, links = sanity_check(nodes, links, nodes_by_city, links_by_city, eqpts_by_city)
return {
@@ -429,8 +269,28 @@ def xls_to_json_data(input_filename, filter_region=[]):
'longitude': x.longitude}},
'type': 'Transceiver'}
for x in nodes_by_city.values() if x.node_type.lower() == 'roadm'] +
[create_roadm_element(x, roadms_by_city)
for x in nodes_by_city.values() if x.node_type.lower() == 'roadm'] +
[{'uid': f'roadm {x.city}',
'metadata': {'location': {'city': x.city,
'region': x.region,
'latitude': x.latitude,
'longitude': x.longitude}},
'type': 'Roadm'}
for x in nodes_by_city.values() if x.node_type.lower() == 'roadm'
and x.booster_restriction == '' and x.preamp_restriction == ''] +
[{'uid': f'roadm {x.city}',
'params': {
'restrictions': {
'preamp_variety_list': silent_remove(x.preamp_restriction.split(' | '), ''),
'booster_variety_list': silent_remove(x.booster_restriction.split(' | '), '')
}
},
'metadata': {'location': {'city': x.city,
'region': x.region,
'latitude': x.latitude,
'longitude': x.longitude}},
'type': 'Roadm'}
for x in nodes_by_city.values() if x.node_type.lower() == 'roadm' and
(x.booster_restriction != '' or x.preamp_restriction != '')] +
[{'uid': f'west fused spans in {x.city}',
'metadata': {'location': {'city': x.city,
'region': x.region,
@@ -467,27 +327,58 @@ def xls_to_json_data(input_filename, filter_region=[]):
'loss_coef': x.west_lineic,
'con_in': x.west_con_in,
'con_out': x.west_con_out}
} for x in links] +
[{'uid': f'west edfa in {x.city}',
'metadata': {'location': {'city': x.city,
'region': x.region,
'latitude': x.latitude,
'longitude': x.longitude}},
} # missing ILA construction
for x in links] +
[{'uid': f'east edfa in {e.from_city} to {e.to_city}',
'metadata': {'location': {'city': nodes_by_city[e.from_city].city,
'region': nodes_by_city[e.from_city].region,
'latitude': nodes_by_city[e.from_city].latitude,
'longitude': nodes_by_city[e.from_city].longitude}},
'type': 'Edfa',
'operational': {'gain_target': None,
'tilt_target': 0}
} for x in nodes_by_city.values() if x.node_type.lower() == 'ila' and x.city not in eqpts_by_city] +
[{'uid': f'east edfa in {x.city}',
'metadata': {'location': {'city': x.city,
'region': x.region,
'latitude': x.latitude,
'longitude': x.longitude}},
'type_variety': e.east_amp_type,
'operational': {'gain_target': e.east_amp_gain,
'delta_p': e.east_amp_dp,
'tilt_target': e.east_tilt,
'out_voa': e.east_att_out}
}
for e in eqpts if (e.east_amp_type.lower() != '' and \
e.east_amp_type.lower() != 'fused')] +
[{'uid': f'west edfa in {e.from_city} to {e.to_city}',
'metadata': {'location': {'city': nodes_by_city[e.from_city].city,
'region': nodes_by_city[e.from_city].region,
'latitude': nodes_by_city[e.from_city].latitude,
'longitude': nodes_by_city[e.from_city].longitude}},
'type': 'Edfa',
'operational': {'gain_target': None,
'tilt_target': 0}
} for x in nodes_by_city.values() if x.node_type.lower() == 'ila' and x.city not in eqpts_by_city] +
[create_east_eqpt_element(e) for e in eqpts] +
[create_west_eqpt_element(e) for e in eqpts],
'type_variety': e.west_amp_type,
'operational': {'gain_target': e.west_amp_gain,
'delta_p': e.west_amp_dp,
'tilt_target': e.west_tilt,
'out_voa': e.west_att_out}
}
for e in eqpts if (e.west_amp_type.lower() != '' and \
e.west_amp_type.lower() != 'fused')] +
# fused edfa variety is a hack to indicate that there should not be
# booster amplifier out the roadm.
# If user specifies ILA in Nodes sheet and fused in Eqpt sheet, then assumes that
# this is a fused nodes.
[{'uid': f'east edfa in {e.from_city} to {e.to_city}',
'metadata': {'location': {'city': nodes_by_city[e.from_city].city,
'region': nodes_by_city[e.from_city].region,
'latitude': nodes_by_city[e.from_city].latitude,
'longitude': nodes_by_city[e.from_city].longitude}},
'type': 'Fused',
'params': {'loss': 0}
}
for e in eqpts if e.east_amp_type.lower() == 'fused'] +
[{'uid': f'west edfa in {e.from_city} to {e.to_city}',
'metadata': {'location': {'city': nodes_by_city[e.from_city].city,
'region': nodes_by_city[e.from_city].region,
'latitude': nodes_by_city[e.from_city].latitude,
'longitude': nodes_by_city[e.from_city].longitude}},
'type': 'Fused',
'params': {'loss': 0}
}
for e in eqpts if e.west_amp_type.lower() == 'fused'],
'connections':
list(chain.from_iterable([eqpt_connection_by_city(n.city)
for n in nodes]))
@@ -508,7 +399,6 @@ def convert_file(input_filename, filter_region=[], output_json_file_name=None):
output_json_file_name = input_filename.with_suffix('.json')
with open(output_json_file_name, 'w', encoding='utf-8') as edfa_json_file:
edfa_json_file.write(dumps(data, indent=2, ensure_ascii=False))
edfa_json_file.write('\n') # add end of file newline because json dumps does not.
return output_json_file_name
@@ -517,7 +407,7 @@ def corresp_names(input_filename, network):
and names used in the json, and created by the autodesign.
All names are listed
"""
nodes, links, eqpts, roadms = parse_excel(input_filename)
nodes, links, eqpts = parse_excel(input_filename)
fused = [n.uid for n in network.nodes() if isinstance(n, Fused)]
ila = [n.uid for n in network.nodes() if isinstance(n, Edfa)]
@@ -545,15 +435,17 @@ def corresp_names(input_filename, network):
# build corresp ila based on eqpt sheet
# start with east direction
corresp_ila = {e.from_city: [f'east edfa in {e.from_city} to {e.to_city}']
for e in eqpts if f'east edfa in {e.from_city} to {e.to_city}' in ila}
for e in eqpts if e.east_amp_type.lower() != '' and
f'east edfa in {e.from_city} to {e.to_city}' in ila}
# west direction, append name or create a new item in dict
for my_e in eqpts:
name = f'west edfa in {my_e.from_city} to {my_e.to_city}'
if name in ila:
if my_e.from_city in corresp_ila.keys():
corresp_ila[my_e.from_city].append(name)
else:
corresp_ila[my_e.from_city] = [name]
if my_e.west_amp_type.lower() != '':
name = f'west edfa in {my_e.from_city} to {my_e.to_city}'
if name in ila:
if my_e.from_city in corresp_ila.keys():
corresp_ila[my_e.from_city].append(name)
else:
corresp_ila[my_e.from_city] = [name]
# complete with potential autodesign names: amplifiers
for my_l in links:
name = f'Edfa0_fiber ({my_l.to_city} \u2192 {my_l.from_city})-{my_l.west_cable}'
@@ -574,6 +466,7 @@ def corresp_names(input_filename, network):
corresp_ila[my_l.to_city].append(name)
else:
corresp_ila[my_l.to_city] = [name]
# merge fused with ila:
for key, val in corresp_fused.items():
if key in corresp_ila.keys():
@@ -638,10 +531,6 @@ def parse_excel(input_filename):
'att_out': 'west_att_out'
}
}
roadm_headers = {'Node A': 'from_node',
'Node Z': 'to_node',
'per degree target power (dBm)': 'target_pch_out_db'
}
with open_workbook(input_filename) as wb:
nodes_sheet = wb.sheet_by_name('Nodes')
@@ -651,11 +540,6 @@ def parse_excel(input_filename):
except Exception:
# eqpt_sheet is optional
eqpt_sheet = None
try:
roadm_sheet = wb.sheet_by_name('Roadms')
except Exception:
# roadm_sheet is optional
roadm_sheet = None
nodes = []
for node in parse_sheet(nodes_sheet, node_headers, NODES_LINE, NODES_LINE + 1, NODES_COLUMN):
@@ -674,29 +558,18 @@ def parse_excel(input_filename):
for eqpt in parse_sheet(eqpt_sheet, eqpt_headers, EQPTS_LINE, EQPTS_LINE + 2, EQPTS_COLUMN):
eqpts.append(Eqpt(**eqpt))
roadms = []
if roadm_sheet is not None:
for roadm in parse_sheet(roadm_sheet, roadm_headers, ROADMS_LINE, ROADMS_LINE+2, ROADMS_COLUMN):
roadms.append(Roadm(**roadm))
# sanity check
all_cities = Counter(n.city for n in nodes)
if len(all_cities) != len(nodes):
msg = f'Duplicate city: {all_cities}'
raise NetworkTopologyError(msg)
raise ValueError(f'Duplicate city: {all_cities}')
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:
msg = 'XLS error: ' \
+ 'The Links sheet references nodes that ' \
+ 'are not defined in the Nodes sheet:\n' \
+ _format_items(f'{item[0]} -> {item[1]}' for item in bad_links)
raise NetworkTopologyError(msg)
raise NetworkTopologyError(f'Bad link(s): {bad_links}.')
return nodes, links, eqpts, roadms
return nodes, links, eqpts
def eqpt_connection_by_city(city_name):
@@ -736,18 +609,20 @@ def connect_eqpt(from_, in_, to_):
def eqpt_in_city_to_city(in_city, to_city, direction='east'):
rev_direction = 'west' if direction == 'east' else 'east'
amp_direction = f'{direction}_amp_type'
amp_rev_direction = f'{rev_direction}_amp_type'
return_eqpt = ''
if in_city in eqpts_by_city:
for e in eqpts_by_city[in_city]:
if nodes_by_city[in_city].node_type.lower() == 'roadm':
if e.to_city == to_city:
if e.to_city == to_city and getattr(e, amp_direction) != '':
return_eqpt = f'{direction} edfa in {e.from_city} to {e.to_city}'
elif nodes_by_city[in_city].node_type.lower() == 'ila':
if e.to_city != to_city:
direction = rev_direction
return_eqpt = f'{direction} edfa in {e.from_city} to {e.to_city}'
elif nodes_by_city[in_city].node_type.lower() == 'ila':
return_eqpt = f'{direction} edfa in {in_city}'
amp_direction = amp_rev_direction
if getattr(e, amp_direction) != '':
return_eqpt = f'{direction} edfa in {e.from_city} to {e.to_city}'
if nodes_by_city[in_city].node_type.lower() == 'fused':
return_eqpt = f'{direction} fused spans in {in_city}'
return return_eqpt
@@ -854,8 +729,6 @@ LINKS_COLUMN = 16
LINKS_LINE = 3
EQPTS_LINE = 3
EQPTS_COLUMN = 14
ROADMS_LINE = 3
ROADMS_COLUMN = 3
def _do_convert():

View File

@@ -1,60 +1,50 @@
#!/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 numpy import arange
from gnpy.core import elements
from gnpy.core import ansi_escapes, elements
from gnpy.core.equipment import trx_mode_params
from gnpy.core.exceptions import ConfigurationError, EquipmentConfigError, NetworkTopologyError, ServiceError
from gnpy.core.science_utils import estimate_nf_model
from gnpy.core.info import Carrier
from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions
from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT
from gnpy.topology.request import PathRequest, Disjunction, compute_spectrum_slot_vs_bandwidth
from gnpy.topology.spectrum_assignment import mvalue_to_slots
from gnpy.topology.request import PathRequest, Disjunction
from gnpy.tools.convert import xls_to_json_data
from gnpy.tools.service_sheet import read_service_sheet
import time
_logger = getLogger(__name__)
Model_vg = namedtuple('Model_vg', 'nf1 nf2 delta_p orig_nf_min orig_nf_max')
Model_vg = namedtuple('Model_vg', 'nf1 nf2 delta_p')
Model_fg = namedtuple('Model_fg', 'nf0')
Model_openroadm_ila = namedtuple('Model_openroadm_ila', 'nf_coef')
Model_openroadm = namedtuple('Model_openroadm', 'nf_coef')
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':
msg = f'\n WARNING missing {k} attribute in eqpt_config.json[{name}]' \
+ f'\n default value is {k} = {v}'
_logger.warning(msg)
print(ansi_escapes.red +
f'\n WARNING missing {k} attribute in eqpt_config.json[{name}]' +
f'\n default value is {k} = {v}' +
ansi_escapes.reset)
time.sleep(1)
class SI(_JsonThing):
@@ -95,9 +85,9 @@ 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': []
@@ -105,21 +95,6 @@ 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')
@@ -132,51 +107,36 @@ 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,
'effective_area': None,
'gamma': 0,
'pmd_coef': 0
}
def __init__(self, **kwargs):
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)
self.update_attr(self.default_values, kwargs, 'Fiber')
class RamanFiber(Fiber):
pass
class RamanFiber(_JsonThing):
default_values = {
'type_variety': '',
'dispersion': None,
'gamma': 0,
'pmd_coef': 0,
'raman_efficiency': None
}
def __init__(self, **kwargs):
self.update_attr(self.default_values, kwargs, 'RamanFiber')
for param in ('cr', 'frequency_offset'):
if param not in self.raman_efficiency:
raise EquipmentConfigError(f'RamanFiber.raman_efficiency: missing "{param}" parameter')
if self.raman_efficiency['frequency_offset'] != sorted(self.raman_efficiency['frequency_offset']):
raise EquipmentConfigError(f'RamanFiber.raman_efficiency.frequency_offset is not sorted')
class Amp(_JsonThing):
@@ -190,24 +150,13 @@ 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': 0,
'nf_ripple': None,
'dgt': None,
'gain_ripple': 0,
'tilt_ripple': 0,
'f_ripple_ref': None,
'gain_ripple': None,
'out_voa_auto': False,
'allowed_for_design': False,
'raman': False,
'pmd': 0,
'pdl': 0,
'advance_configurations_from_json': None
'raman': False
}
def __init__(self, **kwargs):
@@ -226,8 +175,7 @@ class Amp(_JsonThing):
try:
nf0 = kwargs.pop('nf0')
except KeyError: # nf0 is expected for a fixed gain amp
msg = f'missing nf0 value input for amplifier: {type_variety} in equipment config'
raise EquipmentConfigError(msg)
raise EquipmentConfigError(f'missing nf0 value input for amplifier: {type_variety} in equipment config')
for k in ('nf_min', 'nf_max'):
try:
del kwargs[k]
@@ -242,34 +190,26 @@ class Amp(_JsonThing):
nf_min = kwargs.pop('nf_min')
nf_max = kwargs.pop('nf_max')
except KeyError:
msg = f'missing nf_min or nf_max value input for amplifier: {type_variety} in equipment config'
raise EquipmentConfigError(msg)
raise EquipmentConfigError(f'missing nf_min or nf_max value input for amplifier: {type_variety} in equipment config')
try: # remove all remaining nf inputs
del kwargs['nf0']
except KeyError:
pass # nf0 is not needed for variable gain amp
nf1, nf2, delta_p = estimate_nf_model(type_variety, gain_min, gain_max, nf_min, nf_max)
nf_def = Model_vg(nf1, nf2, delta_p, nf_min, nf_max)
nf_def = Model_vg(nf1, nf2, delta_p)
elif type_def == 'openroadm':
try:
nf_coef = kwargs.pop('nf_coef')
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 == 'openroadm_preamp':
nf_def = Model_openroadm_preamp()
elif type_def == 'openroadm_booster':
nf_def = Model_openroadm_booster()
nf_def = Model_openroadm(nf_coef)
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:
msg = f'missing preamp/booster variety input for amplifier: {type_variety} in equipment config'
raise EquipmentConfigError(msg)
raise EquipmentConfigError(f'missing preamp/booster variety input for amplifier: {type_variety} in equipment config')
dual_stage_def = Model_dual_stage(preamp_variety, booster_variety)
else:
raise EquipmentConfigError(f'Edfa type_def {type_def} does not exist')
json_data = load_json(config)
@@ -285,87 +225,17 @@ 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_trx_osnr(equipment):
"""add sys_margins to all Transceivers OSNR values"""
for trx in equipment['Transceiver'].values():
for m in trx.mode:
m['OSNR'] = m['OSNR'] + equipment['SI']['default'].sys_margins
return equipment
def _update_dual_stage(equipment):
@@ -388,7 +258,9 @@ def _update_dual_stage(equipment):
def _roadm_restrictions_sanity_check(equipment):
"""verifies that booster and preamp restrictions specified in roadm equipment are listed in the edfa."""
""" verifies that booster and preamp restrictions specified in roadm equipment are listed
in the edfa.
"""
restrictions = equipment['Roadm']['default'].restrictions['booster_variety_list'] + \
equipment['Roadm']['default'].restrictions['preamp_variety_list']
for amp_name in restrictions:
@@ -396,21 +268,6 @@ def _roadm_restrictions_sanity_check(equipment):
raise EquipmentConfigError(f'ROADM restriction {amp_name} does not refer to a defined EDFA name')
def _check_fiber_vs_raman_fiber(equipment):
"""Ensure that Fiber and RamanFiber with the same name define common properties equally"""
if 'RamanFiber' not in equipment:
return
for fiber_type in set(equipment['Fiber'].keys()) & set(equipment['RamanFiber'].keys()):
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)
b = getattr(raman, attr, None)
if a != b:
raise EquipmentConfigError(f'WARNING: Fiber and RamanFiber definition of "{fiber_type}" '
f'disagrees for "{attr}": {a} != {b}')
def _equipment_from_json(json_data, filename):
"""build global dictionnary eqpt_library that stores all eqpt characteristics:
edfa type type_variety, fiber type_variety
@@ -441,7 +298,7 @@ def _equipment_from_json(json_data, filename):
equipment[key][subkey] = RamanFiber(**entry)
else:
raise EquipmentConfigError(f'Unrecognized network element type "{key}"')
_check_fiber_vs_raman_fiber(equipment)
equipment = _update_trx_osnr(equipment)
equipment = _update_dual_stage(equipment)
_roadm_restrictions_sanity_check(equipment)
return equipment
@@ -458,11 +315,11 @@ 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)
@@ -496,28 +353,14 @@ 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].__dict__
extra_params = equipment[typ][variety]
temp = el_config.setdefault('params', {})
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)
temp = merge_amplifier_restrictions(temp, extra_params.__dict__)
el_config['params'] = temp
el_config['type_variety'] = variety
elif (typ in ['Fiber', 'RamanFiber']):
elif typ in ['Edfa', 'Fiber', 'RamanFiber']: # catch it now because the code will crash later!
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)
@@ -532,8 +375,7 @@ 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:
msg = f'can not find {from_node} or {to_node} defined in {cx}'
raise NetworkTopologyError(msg)
raise NetworkTopologyError(f'can not find {from_node} or {to_node} defined in {cx}')
return g
@@ -564,13 +406,15 @@ 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:
raise ServiceError(f'Service error: {this_e}')
print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {this_e}')
exit(1)
else:
return load_json(filename)
@@ -582,19 +426,19 @@ def requests_from_json(json_data, equipment):
for req in json_data['path-request']:
# init all params from request
params = {}
params['request_id'] = f'{req["request-id"]}'
params['request_id'] = 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']
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)
if 'trx_mode' in req['path-constraints']['te-bandwidth'].keys():
params['trx_mode'] = req['path-constraints']['te-bandwidth']['trx_mode']
else:
params['trx_mode'] = None
params['format'] = params['trx_mode']
params['spacing'] = req['path-constraints']['te-bandwidth']['spacing']
try:
nd_list = sorted(req['explicit-route-objects']['route-object-include-exclude'], key=lambda x: x['index'])
nd_list = req['explicit-route-objects']['route-object-include-exclude']
except KeyError:
nd_list = []
params['nodes_list'] = [n['num-unnum-hop']['node-id'] for n in nd_list]
@@ -602,12 +446,9 @@ 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
trx_params = trx_mode_params(equipment, params['trx_type'], params['trx_mode'], True)
params.update(trx_params)
# print(trx_params['min_spacing'])
# optical power might be set differently in the request. if it is indicated then the
# params['power'] is updated
try:
@@ -628,13 +469,17 @@ def requests_from_json(json_data, equipment):
params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing'])
except KeyError:
params['nb_channel'] = automatic_nch(f_min, f_max_from_si, params['spacing'])
params['effective_freq_slot'] = \
req['path-constraints']['te-bandwidth'].get('effective-freq-slot', [{'N': None, 'M': None}])
if 'effective-freq-slot' in req['path-constraints']['te-bandwidth']:
# temporarily reads only the first slot
params['effective_freq_slot'] = req['path-constraints']['te-bandwidth']['effective-freq-slot'][0]
else:
params['effective_freq_slot'] = None
_check_one_request(params, f_max_from_si)
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
@@ -643,69 +488,35 @@ 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_from_si, params['spacing'])
max_recommanded_nb_channels = automatic_nch(f_min, f_max, 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"] * 1e-9} GHz' \
+ f' and requested spacing {params["spacing"]*1e-9}GHz is not consistent with frequency range' \
+ f' {f_min*1e-12} THz, {f_max_from_si*1e-12} THz.' \
+ f' Max recommanded nb of channels is {max_recommanded_nb_channels}.'
msg = f'''Requested channel number {params["nb_channel"]}, baud rate {params["baud_rate"]} GHz
and requested spacing {params["spacing"]*1e-9}GHz is not consistent with frequency range
{f_min*1e-12} THz, {f_max*1e-12} THz, min recommanded spacing {params["min_spacing"]*1e-9}GHz.
max recommanded nb of channels is {max_recommanded_nb_channels}.'''
_logger.critical(msg)
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
of requested disjunctions for this set of requests
""" reads the disjunction requests from the json dict and create the list
of requested disjunctions for this set of requests
"""
disjunctions_list = []
if 'synchronization' in json_data:
try:
temp_test = json_data['synchronization']
except KeyError:
temp_test = []
if temp_test:
for snc in json_data['synchronization']:
params = {}
params['disjunction_id'] = snc['synchronization-id']
@@ -724,48 +535,10 @@ def convert_service_sheet(
network,
network_filename=None,
output_filename='',
bidir=False):
bidir=False,
filter_region=None):
if output_filename == '':
output_filename = f'{str(input_filename)[0:len(str(input_filename))-len(str(input_filename.suffixes[0]))]}_services.json'
data = read_service_sheet(input_filename, eqpt, network, network_filename, bidir)
data = read_service_sheet(input_filename, eqpt, network, network_filename, bidir, filter_region)
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

View File

@@ -1,50 +1,62 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
'''
gnpy.tools.plots
================
Graphs and plots usable from a CLI application
"""
Graphs and plots usable form a CLI application
'''
from matplotlib.pyplot import show, axis, figure, title, text
from networkx import draw_networkx
from networkx import draw_networkx_nodes, draw_networkx_edges, draw_networkx_labels
from gnpy.core.elements import Transceiver
def _try_city(node):
return node.location.city if node.location.city else node.uid
def plot_baseline(network):
edges = set(network.edges())
pos = {n: (n.lng, n.lat) for n in network.nodes()}
labels = {n: _try_city(n) for n in network.nodes() if isinstance(n, Transceiver)}
draw_networkx(network, pos=pos, node_size=50, node_color='#ababab', edge_color='#ababab',
labels=labels, font_size=14)
labels = {n: n.location.city for n in network.nodes() if isinstance(n, Transceiver)}
city_labels = set(labels.values())
for n in network.nodes():
if n.location.city and n.location.city not in city_labels:
labels[n] = n.location.city
city_labels.add(n.location.city)
label_pos = pos
fig = figure()
kwargs = {'figure': fig, 'pos': pos}
plot = draw_networkx_nodes(network, nodelist=network.nodes(), node_color='#ababab', **kwargs)
draw_networkx_edges(network, edgelist=edges, edge_color='#ababab', **kwargs)
draw_networkx_labels(network, labels=labels, font_size=14, **{**kwargs, 'pos': label_pos})
axis('off')
show()
def plot_results(network, path, source, destination):
def plot_results(network, path, source, destination, infos):
path_edges = set(zip(path[:-1], path[1:]))
edges = set(network.edges()) - path_edges
nodes = [n for n in network.nodes() if n not in path]
pos = {n: (n.lng, n.lat) for n in network.nodes()}
nodes_by_pos = {}
nodes = {}
for k, (x, y) in pos.items():
nodes_by_pos.setdefault((round(x, 1), round(y, 1)), []).append(k)
labels = {n: _try_city(n) for n in network.nodes() if isinstance(n, Transceiver)}
nodes.setdefault((round(x, 1), round(y, 1)), []).append(k)
labels = {n: n.location.city for n in network.nodes() if isinstance(n, Transceiver)}
city_labels = set(labels.values())
for n in network.nodes():
if n.location.city and n.location.city not in city_labels:
labels[n] = n.location.city
city_labels.add(n.location.city)
label_pos = pos
fig = figure()
draw_networkx(network, pos=pos, labels=labels, font_size=14,
nodelist=nodes, node_color='#ababab', node_size=50,
edgelist=edges, edge_color='#ababab')
draw_networkx(network, pos=pos, with_labels=False,
nodelist=path, node_color='#ff0000', node_size=55,
edgelist=path_edges, edge_color='#ff0000')
title(f'Propagating from {_try_city(source)} to {_try_city(destination)}')
kwargs = {'figure': fig, 'pos': pos}
all_nodes = [n for n in network.nodes() if n not in path]
plot = draw_networkx_nodes(network, nodelist=all_nodes, node_color='#ababab', node_size=50, **kwargs)
draw_networkx_nodes(network, nodelist=path, node_color='#ff0000', node_size=55, **kwargs)
draw_networkx_edges(network, edgelist=edges, edge_color='#ababab', **kwargs)
draw_networkx_edges(network, edgelist=path_edges, edge_color='#ff0000', **kwargs)
draw_networkx_labels(network, labels=labels, font_size=14, **{**kwargs, 'pos': label_pos})
title(f'Propagating from {source.loc.city} to {destination.loc.city}')
axis('off')
heading = 'Spectral Information\n\n'
@@ -53,7 +65,7 @@ def plot_results(network, path, source, destination):
bbox={'boxstyle': 'round', 'facecolor': 'wheat', 'alpha': 0.5})
msgs = {(x, y): heading + '\n\n'.join(str(n) for n in ns if n in path)
for (x, y), ns in nodes_by_pos.items()}
for (x, y), ns in nodes.items()}
def hover(event):
if event.xdata is None or event.ydata is None:

View File

@@ -18,6 +18,7 @@ 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
@@ -67,21 +68,24 @@ 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}\' ' \
+ f'with mode: \'{Requestmode}\' in eqpt library \nComputation stopped.'
msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' with mode: \'{Requestmode}\' in eqpt library \nComputation stopped.'
# print(msg)
logger.critical(msg)
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}\' ' \
+ f'with mode: \'{Request.mode}\' in eqpt library \nComputation stopped.'
msg = f'Request Id: {self.request_id} - could not find tsp : \'{Request.trx_type}\' with mode: \'{Request.mode}\' in eqpt library \nComputation stopped.'
# print(msg)
logger.critical(msg)
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
@@ -174,9 +178,12 @@ def read_service_sheet(
eqpt,
network,
network_filename=None,
bidir=False):
bidir=False,
filter_region=None):
""" converts a service sheet into a json structure
"""
if filter_region is None:
filter_region = []
if network_filename is None:
network_filename = input_filename
service = parse_excel(input_filename)
@@ -221,7 +228,7 @@ def parse_excel(input_filename):
def parse_service_sheet(service_sheet):
""" reads each column according to authorized fieldnames. order is not important.
"""
logger.debug(f'Validating headers on {service_sheet.name!r}')
logger.info(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]
@@ -241,6 +248,7 @@ 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))
@@ -268,13 +276,15 @@ 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'Request: {pathreq.request_id}: could not find' +\
f' transponder source : {pathreq.source}.'
msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find' +\
f' transponder source : {pathreq.source}.{ansi_escapes.reset}'
logger.critical(msg)
raise ServiceError(msg)
if pathreq.destination not in transponders:
msg = f'Request: {pathreq.request_id}: could not find' +\
f' transponder destination: {pathreq.destination}.'
msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find' +\
f' transponder destination: {pathreq.destination}.{ansi_escapes.reset}'
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
@@ -326,16 +336,17 @@ 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'Request {pathreq.request_id}: Invalid route node specified:' \
+ f'\n\t\'{n_id}\', replaced with \'{new_n}\''
logger.warning(msg)
msg = f'{ansi_escapes.yellow}Invalid route node specified:' +\
f'\n\t\'{n_id}\', replaced with \'{new_n}\'{ansi_escapes.reset}'
logger.info(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'Request {pathreq.request_id}: Invalid route specified {n_id}: could' \
+ ' not decide on direction, skipped!.\nPlease add a valid' \
+ ' direction in constraints (next neighbour node)'
logger.warning(msg)
msg = f'{ansi_escapes.yellow}Invalid route specified {n_id}: could' +\
f' not decide on direction, skipped!.\nPlease add a valid' +\
f' direction in constraints (next neighbour node){ansi_escapes.reset}'
print(msg)
logger.info(msg)
pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
pathreq.nodes_list.remove(n_id)
else:
@@ -343,24 +354,28 @@ 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'Request {pathreq.request_id}: Invalid node specified:\n\t\'{n_id}\'' \
+ ', could not use it as constraint, skipped!'
logger.warning(msg)
msg = f'{ansi_escapes.yellow}Invalid node specified:\n\t\'{n_id}\'' +\
f', could not use it as constraint, skipped!{ansi_escapes.reset}'
print(msg)
logger.info(msg)
pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
pathreq.nodes_list.remove(n_id)
else:
msg = f'Request {pathreq.request_id}: Could not find node:\n\t\'{n_id}\' in network' \
+ ' topology. Strict constraint can not be applied.'
msg = f'{ansi_escapes.red}Could not find node:\n\t\'{n_id}\' in network' +\
f' topology. Strict constraint can not be applied.{ansi_escapes.reset}'
logger.critical(msg)
raise ServiceError(msg)
else:
if temp.loose_list[i] == 'LOOSE':
logger.warning(f'Request {pathreq.request_id}: Invalid route node specified:\n\t\'{n_id}\''
+ ' type is not supported as constraint with xls network input, skipped!')
print(f'{ansi_escapes.yellow}Invalid route node specified:\n\t\'{n_id}\'' +
f' type is not supported as constraint with xls network input,' +
f' skipped!{ansi_escapes.reset}')
pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
pathreq.nodes_list.remove(n_id)
else:
msg = f'Invalid route node specified \n\t\'{n_id}\'' \
+ ' type is not supported as constraint with xls network input,' \
+ ', Strict constraint can not be applied.'
msg = f'{ansi_escapes.red}Invalid route node specified \n\t\'{n_id}\'' +\
f' type is not supported as constraint with xls network input,' +\
f', Strict constraint can not be applied.{ansi_escapes.reset}'
logger.critical(msg)
raise ServiceError(msg)
return pathreqlist

View File

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

View File

@@ -20,29 +20,30 @@ 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, argmin
from numpy import mean
from gnpy.core.elements import Transceiver, Roadm
from gnpy.core.utils import lin2db
from gnpy.core.info import create_input_spectral_information, carriers_to_spectral_information
from gnpy.core import network as network_module
from gnpy.core.info import create_input_spectral_information
from gnpy.core.exceptions import ServiceError, DisjunctionError
import gnpy.core.ansi_escapes as ansi_escapes
from copy import deepcopy
from csv import writer
from math import ceil
LOGGER = getLogger(__name__)
RequestParams = namedtuple('RequestParams', 'request_id source destination bidir trx_type'
' trx_mode nodes_list loose_list spacing power nb_channel f_min'
' f_max format baud_rate OSNR penalties bit_rate'
' roll_off tx_osnr min_spacing cost path_bandwidth effective_freq_slot'
' equalization_offset_db')
DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link_diverse'
' node_diverse disjunctions_req')
RequestParams = namedtuple('RequestParams', 'request_id source destination bidir trx_type' +
' trx_mode nodes_list loose_list spacing power nb_channel f_min' +
' f_max format baud_rate OSNR bit_rate roll_off tx_osnr' +
' min_spacing cost path_bandwidth effective_freq_slot')
DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link' +
'_diverse node_diverse disjunctions_req')
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
@@ -61,7 +62,6 @@ 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
@@ -69,10 +69,8 @@ class PathRequest:
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
self.N = params.effective_freq_slot['N']
self.M = params.effective_freq_slot['M']
def __str__(self):
return '\n\t'.join([f'{type(self).__name__} {self.request_id}',
@@ -80,7 +78,7 @@ class PathRequest:
f'destination: {self.destination}'])
def __repr__(self):
if self.baud_rate is not None and self.bit_rate is not None:
if self.baud_rate is not None:
temp = self.baud_rate * 1e-9
temp2 = self.bit_rate * 1e-9
else:
@@ -104,7 +102,8 @@ 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)
@@ -133,7 +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', 'NOT_ENOUGH_RESERVED_SPECTRUM']
BLOCKING_NOSPECTRUM = 'NO_SPECTRUM'
class ResultElement:
@@ -149,7 +148,8 @@ 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:
@@ -165,30 +165,24 @@ class ResultElement:
}
pro_list.append(temp)
index += 1
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.')
if self.path_request.M > 0:
temp = {
'path-route-object': {
'index': index,
"label-hop": [{
"N": n,
"M": m
} for n, m in zip(self.path_request.N, self.path_request.M)],
"label-hop": {
"N": self.path_request.N,
"M": 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:
# 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.')
raise ServiceError('request {self.path_id} should have positive path bandwidth value.')
if isinstance(element, Transceiver):
temp = {
'path-route-object': {
@@ -205,9 +199,11 @@ 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',
@@ -249,7 +245,8 @@ 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 = {
@@ -287,6 +284,7 @@ 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)]
@@ -301,9 +299,10 @@ 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'Request {req.request_id} could not find a path from'
f' {source.uid} to node: {destination.uid} in network topology')
msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path from'
f' {source.uid} to node: {destination.uid} in network topology{ansi_escapes.reset}')
LOGGER.critical(msg)
print(msg)
req.blocking_reason = 'NO_PATH'
total_path = []
except StopIteration:
@@ -312,92 +311,79 @@ 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
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')
print(f'{ansi_escapes.yellow}Request {req.request_id} could not find a path crossing '
f'{[el.uid for el in nodes_list[:-1]]} in network topology{ansi_escapes.reset}')
if 'STRICT' not in req.loose_list[:-1]:
msg = (f'Request {req.request_id} could not find a path with user_'
f'include node constraints. Constraint ignored')
LOGGER.warning(msg)
msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path with user_'
f'include node constraints{ansi_escapes.reset}')
LOGGER.info(msg)
print(f'constraint ignored')
total_path = dijkstra_path(network, source, destination, weight='weight')
else:
# one STRICT makes the whole list STRICT
msg = (f'Request {req.request_id} could not find a path with user '
f'include node constraints.\nNo path computed')
msg = (f'{ansi_escapes.yellow}Request {req.request_id} could not find a path with user '
f'include node constraints.\nNo path computed{ansi_escapes.reset}')
LOGGER.critical(msg)
print(msg)
req.blocking_reason = 'NO_PATH_WITH_CONSTRAINT'
total_path = []
return total_path
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)
else:
si = create_input_spectral_information(
f_min=req.f_min, f_max=req.f_max, roll_off=req.roll_off, baud_rate=req.baud_rate,
power=req.power, spacing=req.spacing, tx_osnr=req.tx_osnr, delta_pdb=req.offset_db)
for i, el in enumerate(path):
if isinstance(el, Roadm):
si = el(si, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
else:
si = el(si)
path[0].update_snr(si.tx_osnr)
path[0].calc_penalties(req.penalties)
if any(isinstance(el, Roadm) for el in path):
path[-1].update_snr(si.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
else:
path[-1].update_snr(si.tx_osnr)
path[-1].calc_penalties(req.penalties)
return si
si = create_input_spectral_information(
req.f_min, req.f_max, req.roll_off, req.baud_rate,
req.power, req.spacing)
for el in path:
si = el(si)
path[-1].update_snr(req.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
return path
def propagate2(path, req, equipment):
si = create_input_spectral_information(
req.f_min, req.f_max, req.roll_off, req.baud_rate,
req.power, req.spacing)
infos = {}
for el in path:
before_si = si
after_si = si = el(si)
infos[el] = before_si, after_si
path[-1].update_snr(req.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
return infos
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 and power offset
# order higher baudrate with higher power offset first
baudrate_offset_to_explore = list(set([(this_mode['baud_rate'], this_mode['equalization_offset_db'])
for this_mode in equipment['Transceiver'][req.tsp].mode
if float(this_mode['min_spacing']) <= req.spacing]))
# step 1: create an ordered list of modes based on baudrate
baudrate_to_explore = list(set([this_mode['baud_rate']
for this_mode in equipment['Transceiver'][req.tsp].mode
if float(this_mode['min_spacing']) <= req.spacing]))
# TODO be carefull on limits cases if spacing very close to req spacing eg 50.001 50.000
baudrate_offset_to_explore = sorted(baudrate_offset_to_explore, reverse=True)
if baudrate_offset_to_explore:
baudrate_to_explore = sorted(baudrate_to_explore, reverse=True)
if baudrate_to_explore:
# at least 1 baudrate can be tested wrt spacing
for (this_br, this_offset) in baudrate_offset_to_explore:
for this_br in baudrate_to_explore:
modes_to_explore = [this_mode for this_mode in equipment['Transceiver'][req.tsp].mode
if this_mode['baud_rate'] == this_br
and float(this_mode['min_spacing']) <= req.spacing]
if this_mode['baud_rate'] == this_br and
float(this_mode['min_spacing']) <= req.spacing]
modes_to_explore = sorted(modes_to_explore,
key=lambda x: (x['bit_rate'], x['equalization_offset_db']), reverse=True)
key=lambda x: x['bit_rate'], reverse=True)
# print(modes_to_explore)
# step2: computes propagation for each baudrate: stop and select the first that passes
# TODO: the case of roll off is not included: for now use SI one
# TODO: the case of roll of is not included: for now use SI one
# TODO: if the loop in mode optimization does not have a feasible path, then bugs
if req.initial_spectrum is not None:
# this case is not yet handled: spectrum can not be defined for the path-request-run function
# and this function is only called in this case. so coming here should not be considered yet.
msg = f'Request: {req.request_id} contains a unexpected initial_spectrum.'
raise ServiceError(msg)
spc_info = create_input_spectral_information(f_min=req.f_min, f_max=req.f_max,
roll_off=equipment['SI']['default'].roll_off,
baud_rate=this_br, power=req.power, spacing=req.spacing,
delta_pdb=this_offset, tx_osnr=req.tx_osnr)
for i, el in enumerate(path):
if isinstance(el, Roadm):
spc_info = el(spc_info, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
else:
spc_info = el(spc_info)
spc_info = create_input_spectral_information(req.f_min, req.f_max,
equipment['SI']['default'].roll_off,
this_br, req.power, req.spacing)
for el in path:
spc_info = el(spc_info)
for this_mode in modes_to_explore:
if path[-1].snr is not None:
path[0].update_snr(this_mode['tx_osnr'])
path[0].calc_penalties(this_mode['penalties'])
if any(isinstance(el, Roadm) for el in path):
path[-1].update_snr(this_mode['tx_osnr'], equipment['Roadm']['default'].add_drop_osnr)
else:
path[-1].update_snr(this_mode['tx_osnr'])
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:
path[-1].update_snr(this_mode['tx_osnr'], equipment['Roadm']['default'].add_drop_osnr)
if round(min(path[-1].snr + lin2db(this_br / (12.5e9))), 2) > this_mode['OSNR']:
return path, this_mode
else:
last_explored_mode = this_mode
@@ -408,19 +394,22 @@ def propagate_and_optimize_mode(path, req, equipment):
# returns the last propagated path and mode
msg = f'\tWarning! Request {req.request_id}: no mode satisfies path SNR requirement.\n'
LOGGER.warning(msg)
print(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'
LOGGER.warning(msg)
print(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']
@@ -438,7 +427,9 @@ def jsontopath_metric(path_metric):
def jsontoparams(my_p, tsp, mode, equipment):
"""a function that derives optical params from transponder type and mode supports the no mode case"""
""" a function that derives optical params from transponder type and mode
supports the no mode case
"""
temp = []
for elem in my_p['path-properties']['path-route-objects']:
if 'num-unnum-hop' in elem['path-route-object']:
@@ -448,8 +439,8 @@ 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'{[e["N"] for e in elem["path-route-object"]["label-hop"]]}, '
+ f'{[e["M"] for e in elem["path-route-object"]["label-hop"]]}')
temp2.append(f'{elem["path-route-object"]["label-hop"]["N"]}, ' +
f'{elem["path-route-object"]["label-hop"]["M"]}')
# 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
@@ -473,10 +464,10 @@ def jsontoparams(my_p, tsp, mode, equipment):
def jsontocsv(json_data, equipment, fileout):
"""reads json path result file in accordance with:
Yang model for requesting Path Computation
draft-ietf-teas-yang-path-computation-01.txt.
and write results in an CSV file
""" reads json path result file in accordance with:
Yang model for requesting Path Computation
draft-ietf-teas-yang-path-computation-01.txt.
and write results in an CSV file
"""
mywriter = writer(fileout)
mywriter.writerow(('response-id', 'source', 'destination', 'path_bandwidth', 'Pass?',
@@ -705,8 +696,8 @@ 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: aefhg
# p2: abfhg
# rq1 p1: abfhg
# p2: aefhg
# p3: abcg
# rq2 p8: bf
# rq3 p4: abcgh
@@ -723,7 +714,6 @@ 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
@@ -747,6 +737,7 @@ 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:
@@ -787,9 +778,9 @@ def compute_path_dsjctn(network, equipment, pathreqlist, disjunctions_list):
if pth in cndt:
candidates[this_id].remove(cndt)
# for i in disjunctions_list:
# print(i.disjunction_id)
# print(f'\n{candidates[i.disjunction_id]}')
# for i in disjunctions_list:
# print(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
@@ -797,51 +788,54 @@ 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 any pth from sol does not contain the ordered list node,
# remove sol from the candidate, except if constraint was loose:
# then keep sol as an alternate solution
# if pth does not containt the ordered list node, remove sol from the candidate
# except if this was the last solution: then check if the constraint is loose
# or not
if not ispart(allpaths[id(pth)].req.nodes_list, pth):
testispartok = False
if 'STRICT' in allpaths[id(pth)].req.loose_list:
LOGGER.debug(f'removing solution from candidate paths\n{pth}')
testispartnokloose = False
break
# 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 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] = []
candidates[this_d.disjunction_id] = temp
# step 5 select the first combination that works
pathreslist_disjoint = {}
for dis in disjunctions_list:
if candidates[dis.disjunction_id]:
for pth in candidates[dis.disjunction_id][0]:
if allpaths[id(pth)].req in pathreqlist_disjt:
# print(f'selected path:{pth} for req {allpaths[id(pth)].req.request_id}')
pathreslist_disjoint[allpaths[id(pth)].req] = allpaths[id(pth)].pth
# remove request from list of requests (in case of duplicate)
pathreqlist_disjt.remove(allpaths[id(pth)].req)
# remove duplicated candidates
candidates = remove_candidate(candidates, allpaths, allpaths[id(pth)].req, pth)
else:
msg = 'No disjoint path found with added constraint\nComputation stopped.'
# TODO in this case: replay step 5 with the candidate without constraints
raise DisjunctionError(msg)
test_sol = True
while test_sol:
# print('coucou')
if candidates[dis.disjunction_id]:
for pth in candidates[dis.disjunction_id][0]:
if allpaths[id(pth)].req in pathreqlist_disjt:
# print(f'selected path:{pth} for req {allpaths[id(pth)].req.request_id}')
pathreslist_disjoint[allpaths[id(pth)].req] = allpaths[id(pth)].pth
pathreqlist_disjt.remove(allpaths[id(pth)].req)
candidates = remove_candidate(candidates, allpaths, allpaths[id(pth)].req, pth)
test_sol = False
else:
msg = f'No disjoint path found with added constraint'
LOGGER.critical(msg)
print(f'{msg}\nComputation stopped.')
# TODO in this case: replay step 5 with the candidate without constraints
raise DisjunctionError(msg)
# for i in disjunctions_list:
# print(i.disjunction_id)
@@ -860,7 +854,8 @@ 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:
@@ -870,9 +865,9 @@ def isdisjoint(pth1, pth2):
def find_reversed_path(pth):
"""select of intermediate roadms and find the path between them
note that this function may not give an exact result in case of multiple
links between two adjacent nodes.
""" select of intermediate roadms and find the path between them
note that this function may not give an exact result in case of multiple
links between two adjacent nodes.
"""
# TODO add some indication on elements to indicate from which other they
# are the reversed direction. This is partly done with oms indication
@@ -895,8 +890,9 @@ def find_reversed_path(pth):
# concatenation should be [roadma el1 el2 roadmb el3 el4 roadmc]
reversed_path = list(OrderedDict.fromkeys(reversed_path))
else:
msg = f'Error while handling reversed path {pth[-1].uid} to {pth[0].uid}:' \
+ ' can not handle unidir topology. TO DO.'
msg = f'Error while handling reversed path {pth[-1].uid} to {pth[0].uid}:' +\
' can not handle unidir topology. TO DO.'
LOGGER.critical(msg)
raise ValueError(msg)
reversed_path.append(pth[0])
@@ -904,7 +900,9 @@ def find_reversed_path(pth):
def ispart(ptha, pthb):
"""the functions takes two paths a and b and retrns True if all a elements are part of b and in the same order"""
""" the functions takes two paths a and b and retrns True
if all a elements are part of b and in the same order
"""
j = 0
for elem in ptha:
if elem in pthb:
@@ -918,7 +916,8 @@ 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()
@@ -933,7 +932,8 @@ def remove_candidate(candidates, allpaths, rqst, pth):
def compare_reqs(req1, req2, disjlist):
"""compare two requests: returns True or False"""
""" compare two requests: returns True or False
"""
dis1 = [d for d in disjlist if req1.request_id in d.disjunctions_req]
dis2 = [d for d in disjlist if req2.request_id in d.disjunctions_req]
same_disj = False
@@ -973,24 +973,19 @@ def compare_reqs(req1, req2, disjlist):
def requests_aggregation(pathreqlist, disjlist):
"""this function aggregates requests so that if several requests
exist between same source and destination and with same transponder type
If transponder mode is defined and identical, then also agregates demands.
""" this function aggregates requests so that if several requests
exist between same source and destination and with same transponder type
"""
# 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) and\
this_r.tsp_mode is not None:
if req.request_id != this_r.request_id and compare_reqs(req, this_r, disjlist):
# 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
@@ -1007,22 +1002,23 @@ def requests_aggregation(pathreqlist, disjlist):
def correct_json_route_list(network, pathreqlist):
"""all names in list should be exact name in the network, and there is no ambiguity
This function only checks that list is correct, warns user if the name is incorrect and
suppresses the constraint it it is loose or raises an error if it is strict
""" all names in list should be exact name in the network, and there is no ambiguity
This function only checks that list is correct, warns user if the name is incorrect and
suppresses the constraint it it is loose or raises an error if it is strict
"""
all_uid = [n.uid for n in network.nodes()]
transponders = [n.uid for n in network.nodes() if isinstance(n, Transceiver)]
for pathreq in pathreqlist:
if pathreq.source not in transponders:
msg = f'Request: {pathreq.request_id}: could not find transponder' \
+ f' source : {pathreq.source}.'
msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find transponder' +\
f' source : {pathreq.source}.{ansi_escapes.reset}'
LOGGER.critical(msg)
raise ServiceError(msg)
if pathreq.destination not in transponders:
msg = f'Request: {pathreq.request_id}: could not find transponder' \
+ f' destination : {pathreq.destination}.'
msg = f'{ansi_escapes.red}Request: {pathreq.request_id}: could not find transponder' +\
f' destination : {pathreq.destination}.{ansi_escapes.reset}'
LOGGER.critical(msg)
raise ServiceError(msg)
# silently remove source and dest nodes from the list
@@ -1041,21 +1037,24 @@ 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'invalid route node specified:\n\t\'{n_id}\',' \
+ ' could not use it as constraint, skipped!'
LOGGER.warning(msg)
msg = f'{ansi_escapes.yellow}invalid route node specified:\n\t\'{n_id}\',' +\
f' could not use it as constraint, skipped!{ansi_escapes.reset}'
print(msg)
LOGGER.info(msg)
pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
pathreq.nodes_list.remove(n_id)
else:
msg = f'could not find node:\n\t \'{n_id}\' in network' \
+ ' topology. Strict constraint can not be applied.'
msg = f'{ansi_escapes.red}could not find node:\n\t \'{n_id}\' in network' +\
f' topology. Strict constraint can not be applied.{ansi_escapes.reset}'
LOGGER.critical(msg)
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:
@@ -1066,9 +1065,8 @@ 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
TODO change all these req, dsjct, res lists into dict !
""" use a list but a dictionnary might be helpful to find path based on request_id
TODO change all these req, dsjct, res lists into dict !
"""
path_res_list = []
reversed_path_res_list = []
@@ -1079,10 +1077,10 @@ 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
msg = f'\n\trequest {pathreq.request_id}\n' \
+ f'\tComputing path from {pathreq.source} to {pathreq.destination}\n' \
+ f'\twith path constraint: {[pathreq.source] + pathreq.nodes_list}'
# # adding first node to be clearer on the output
print(f'request {pathreq.request_id}')
print(f'Computing path from {pathreq.source} to {pathreq.destination}')
# adding first node to be clearer on the output
print(f'with path constraint: {[pathreq.source] + pathreq.nodes_list}')
# pathlist[i] contains the whole path information for request i
# last element is a transciver and where the result of the propagation is
@@ -1091,26 +1089,22 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
# elements to simulate performance, several demands having the same destination
# may use the same transponder for the performance simulation. This is why
# we use deepcopy: to ensure that each propagation is recorded and not overwritten
network_module.design_network(pathreq, network, equipment, set_connector_losses=False, verbose=False)
total_path = deepcopy(pathlist[i])
msg = msg + f'\n\tComputed path (roadms):{[e.uid for e in total_path if isinstance(e, Roadm)]}'
LOGGER.info(msg)
print(f'Computed path (roadms):{[e.uid for e in total_path if isinstance(e, Roadm)]}')
# for debug
# print(f'{pathreq.baud_rate} {pathreq.power} {pathreq.spacing} {pathreq.nb_channel}')
if total_path:
if pathreq.baud_rate is not None:
# means that at this point the mode was entered/forced by user and thus a
# baud_rate was defined
propagate(total_path, pathreq, equipment)
snr01nm_with_penalty = total_path[-1].snr_01nm - total_path[-1].total_penalty
min_ind = argmin(snr01nm_with_penalty)
if round(snr01nm_with_penalty[min_ind], 2) < pathreq.OSNR + equipment['SI']['default'].sys_margins:
msg = f'\tWarning! Request {pathreq.request_id} computed path from' \
+ f' {pathreq.source} to {pathreq.destination} does not pass with {pathreq.tsp_mode}' \
+ f'\n\tcomputed SNR in 0.1nm = {round(total_path[-1].snr_01nm[min_ind], 2)}'
msg = _penalty_msg(total_path, msg, min_ind) \
+ f'\n\trequired osnr = {pathreq.OSNR}' \
+ f'\n\tsystem margin = {equipment["SI"]["default"].sys_margins}'
total_path = propagate(total_path, pathreq, equipment)
temp_snr01nm = round(mean(total_path[-1].snr+lin2db(pathreq.baud_rate/(12.5e9))), 2)
if temp_snr01nm < pathreq.OSNR:
msg = f'\tWarning! Request {pathreq.request_id} computed path from' +\
f' {pathreq.source} to {pathreq.destination} does not pass with' +\
f' {pathreq.tsp_mode}\n\tcomputedSNR in 0.1nm = {temp_snr01nm} ' +\
f'- required osnr {pathreq.OSNR}'
print(msg)
LOGGER.warning(msg)
pathreq.blocking_reason = 'MODE_NOT_FEASIBLE'
else:
@@ -1130,7 +1124,6 @@ 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']
@@ -1139,27 +1132,25 @@ 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
if pathreq.bidir:
# only propagate if bidir is true, but needs the reversed path anyway for
# correct spectrum assignment
rev_p = deepcopy(reversed_path)
msg = f'\n\tPropagating Z to A direction {pathreq.destination} to {pathreq.source}\n' \
+ f'\tPath (roadms) {[r.uid for r in rev_p if isinstance(r,Roadm)]}\n'
LOGGER.info(msg)
propagate(rev_p, pathreq, equipment)
propagated_reversed_path = rev_p
snr01nm_with_penalty = rev_p[-1].snr_01nm - rev_p[-1].total_penalty
min_ind = argmin(snr01nm_with_penalty)
if round(snr01nm_with_penalty[min_ind], 2) < pathreq.OSNR + equipment['SI']['default'].sys_margins:
msg = f'\tWarning! Request {pathreq.request_id} computed path from' \
+ f' {pathreq.destination} to {pathreq.source} does not pass with {pathreq.tsp_mode}' \
+ f'\n\tcomputed SNR in 0.1nm = {round(rev_p[-1].snr_01nm[min_ind], 2)}'
msg = _penalty_msg(rev_p, msg, min_ind) \
+ f'\n\trequired osnr = {pathreq.OSNR}' \
+ f'\n\tsystem margin = {equipment["SI"]["default"].sys_margins}'
print(f'\n\tPropagating Z to A direction {pathreq.destination} to {pathreq.source}')
print(f'\tPath (roadsm) {[r.uid for r in rev_p if isinstance(r,Roadm)]}\n')
propagated_reversed_path = propagate(rev_p, pathreq, equipment)
temp_snr01nm = round(mean(propagated_reversed_path[-1].snr +\
lin2db(pathreq.baud_rate/(12.5e9))), 2)
if temp_snr01nm < pathreq.OSNR:
msg = f'\tWarning! Request {pathreq.request_id} computed path from' +\
f' {pathreq.source} to {pathreq.destination} does not pass with' +\
f' {pathreq.tsp_mode}\n' +\
f'\tcomputedSNR in 0.1nm = {temp_snr01nm} - required osnr {pathreq.OSNR}'
print(msg)
LOGGER.warning(msg)
# TODO selection of mode should also be on reversed direction !!
if not hasattr(pathreq, 'blocking_reason'):
@@ -1167,8 +1158,9 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
else:
propagated_reversed_path = []
else:
msg = f'Request {pathreq.request_id}: Total path is empty. No propagation'
LOGGER.warning(msg)
msg = 'Total path is empty. No propagation'
print(msg)
LOGGER.info(msg)
reversed_path = []
propagated_reversed_path = []
@@ -1176,33 +1168,5 @@ 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

View File

@@ -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
@@ -45,22 +45,26 @@ 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]
@@ -71,8 +75,8 @@ OMSParams = namedtuple('OMSParams', 'oms_id el_id_list el_list')
class OMS:
"""OMS class is the logical container that represent a link between two adjacent ROADMs and
records the crossed elements and the occupied spectrum
""" OMS class is the logical container that represent a link between two adjacent ROADMs and
records the crossed elements and the occupied spectrum
"""
def __init__(self, *args, **params):
@@ -94,28 +98,36 @@ class OMS:
f'{self.el_id_list[0]} - {self.el_id_list[-1]}', '\n'])
def add_element(self, elem):
"""records oms elements"""
""" records oms elements
"""
self.el_id_list.append(elem.uid)
self.el_list.append(elem)
def update_spectrum(self, f_min, f_max, guardband=0.15e12, existing_spectrum=None, grid=0.00625e12):
"""Frequencies expressed in Hz.
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
def update_spectrum(self, f_min, f_max, guardband=0.15e12, existing_spectrum=None,
grid=0.00625e12):
""" frequencies expressed in Hz
"""
self.spectrum_bitmap = Bitmap(f_min=f_min, f_max=f_max, grid=grid, guardband=guardband,
bitmap=existing_spectrum)
if existing_spectrum is None:
# add some 150 GHz margin to enable a center channel on f_min
# use ITU-T G694.1
# Flexible DWDM grid definition
# For the flexible DWDM grid, the allowed frequency slots have a nominal
# central frequency (in THz) defined by:
# 193.1 + n × 0.00625 where n is a positive or negative integer including 0
# and 0.00625 is the nominal central frequency granularity in THz
# and a slot width defined by:
# 12.5 × m where m is a positive integer and 12.5 is the slot width granularity in
# GHz.
# Any combination of frequency slots is allowed as long as no two frequency
# slots overlap.
# TODO : add explaination on that / parametrize ....
self.spectrum_bitmap = Bitmap(f_min, f_max, grid, guardband)
# print(len(self.spectrum_bitmap.bitmap))
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):
@@ -134,16 +146,16 @@ class OMS:
self.spectrum_bitmap.bitmap[self.spectrum_bitmap.geti(startn):self.spectrum_bitmap.geti(stopn) + 1] = [0] * (stopn - startn + 1)
def add_service(self, service_id, nb_wl):
"""record service and mark spectrum as occupied"""
""" record service and mark spectrum as occupied
"""
self.service_list.append(service_id)
self.nb_channels += nb_wl
def frequency_to_n(freq, grid=0.00625e12):
"""converts frequency into the n value (ITU grid)
reference to Recommendation G.694.1 (02/12), Figure I.3
https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
""" converts frequency into the n value (ITU grid)
reference to Recommendation G.694.1 (02/12), Figure I.3
https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
>>> frequency_to_n(193.1375e12)
6
@@ -155,10 +167,9 @@ def frequency_to_n(freq, grid=0.00625e12):
def nvalue_to_frequency(nvalue, grid=0.00625e12):
"""converts n value into a frequency
reference to Recommendation G.694.1 (02/12), Table 1
https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
""" converts n value into a frequency
reference to Recommendation G.694.1 (02/12), Table 1
https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
>>> nvalue_to_frequency(6)
193137500000000.0
@@ -170,17 +181,17 @@ def nvalue_to_frequency(nvalue, grid=0.00625e12):
def mvalue_to_slots(nvalue, mvalue):
"""convert center n an m into start and stop n"""
""" convert center n an m into start and stop n
"""
startn = nvalue - mvalue
stopn = nvalue + mvalue - 1
return startn, stopn
def slots_to_m(startn, stopn):
"""converts the start and stop n values to the center n and m value
reference to Recommendation G.694.1 (02/12), Figure I.3
https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
""" converts the start and stop n values to the center n and m value
reference to Recommendation G.694.1 (02/12), Figure I.3
https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
>>> nval, mval = slots_to_m(6, 20)
>>> nval
@@ -195,11 +206,10 @@ def slots_to_m(startn, stopn):
def m_to_freq(nvalue, mvalue, grid=0.00625e12):
"""converts m into frequency range
spectrum(13,7) is (193137500000000.0, 193225000000000.0)
reference to Recommendation G.694.1 (02/12), Figure I.3
https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
""" converts m into frequency range
spectrum(13,7) is (193137500000000.0, 193225000000000.0)
reference to Recommendation G.694.1 (02/12), Figure I.3
https://www.itu.int/rec/T-REC-G.694.1-201202-I/en
>>> fstart, fstop = m_to_freq(13, 7)
>>> fstart
@@ -215,7 +225,9 @@ def m_to_freq(nvalue, mvalue, grid=0.00625e12):
def align_grids(oms_list):
"""Used to apply same grid to all oms : same starting n, stop n and slot size. Out of grid slots are set to 0."""
""" used to apply same grid to all oms : same starting n, stop n and slot size
out of grid slots are set to 0
"""
n_min = min([o.spectrum_bitmap.n_min for o in oms_list])
n_max = max([o.spectrum_bitmap.n_max for o in oms_list])
for this_o in oms_list:
@@ -227,13 +239,12 @@ def align_grids(oms_list):
def build_oms_list(network, equipment):
"""initialization of OMS list in the network
an oms is build reading all intermediate nodes between two adjacent ROADMs
each element within the list is being added an oms and oms_id to record the
oms it belongs to.
the function supports different spectrum width and supposes that the whole network
works with the min range among OMSs
""" initialization of OMS list in the network
an oms is build reading all intermediate nodes between two adjacent ROADMs
each element within the list is being added an oms and oms_id to record the
oms it belongs to.
the function supports different spectrum width and supposes that the whole network
works with the min range among OMSs
"""
oms_id = 0
oms_list = []
@@ -285,9 +296,8 @@ def build_oms_list(network, equipment):
def reversed_oms(oms_list):
"""identifies reversed OMS
only applicable for non parallel OMS
""" identifies reversed OMS
only applicable for non parallel OMS
"""
for oms in oms_list:
has_reversed = False
@@ -312,41 +322,28 @@ def bitmap_sum(band1, band2):
return res
def build_path_oms_id_list(pth):
def spectrum_selection(pth, oms_list, requested_m, requested_n=None):
"""Collects spectrum availability and call the select_candidate function"""
# use indexes instead of ITU-T n values
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
return list(set(path_oms))
path_oms = list(set(path_oms))
# assuming all oms have same freq index
if not path_oms:
candidate = (None, None, None)
return candidate, path_oms
freq_index = oms_list[path_oms[0]].spectrum_bitmap.freq_index
freq_index_min = oms_list[path_oms[0]].spectrum_bitmap.freq_index_min
freq_index_max = oms_list[path_oms[0]].spectrum_bitmap.freq_index_max
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
freq_availability = oms_list[path_oms[0]].spectrum_bitmap.bitmap
for oms in path_oms[1:]:
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
freq_availability = bitmap_sum(oms_list[oms].spectrum_bitmap.bitmap, freq_availability)
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)
@@ -357,36 +354,29 @@ def spectrum_selection(test_oms, requested_m, requested_n=None):
candidate = select_candidate(candidates, policy='first_fit')
else:
i = test_oms.spectrum_bitmap.geti(requested_n)
if (freq_availability[i - requested_m:i + requested_m] == [1] * (2 * requested_m)
and freq_index[i - requested_m] >= freq_index_min
i = oms_list[path_oms[0]].spectrum_bitmap.geti(requested_n)
# print(f'N {requested_n} i {i}')
# print(freq_availability[i-m:i+m] )
# print(freq_index[i-m:i+m])
if (freq_availability[i - requested_m:i + requested_m] == [1] * (2 * requested_m) and
freq_index[i - requested_m] >= freq_index_min
and freq_index[i + requested_m - 1] <= freq_index_max):
# candidate is the triplet center_n, startn and stopn
candidate = (requested_n, requested_n - requested_m, requested_n + requested_m - 1)
else:
candidate = (None, None, None)
return candidate
def determine_slot_numbers(test_oms, requested_n, required_m, per_channel_m):
"""determines max availability around requested_n. requested_n should not be None"""
bitmap = test_oms.spectrum_bitmap
freq_index = bitmap.freq_index
freq_index_min = bitmap.freq_index_min
freq_index_max = bitmap.freq_index_max
freq_availability = bitmap.bitmap
center_i = bitmap.geti(requested_n)
i = per_channel_m
while (freq_availability[center_i - i:center_i + i] == [1] * (2 * i)
and freq_index[center_i - i] >= freq_index_min
and freq_index[center_i + i - 1] <= freq_index_max
and i <= required_m):
i += per_channel_m
return i - per_channel_m
# print("coucou11")
# print(candidate)
# print(freq_availability[321:321+2*m])
# a = [i+321 for i in range(2*m)]
# print(a)
# print(candidate)
return candidate, path_oms
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]
@@ -396,112 +386,62 @@ def select_candidate(candidates, policy):
raise ServiceError('Only first_fit spectrum assignment policy is implemented.')
def compute_n_m(required_m, rq, path_oms, oms_list, per_channel_m, policy='first_fit'):
""" based on requested path_bandwidth fill in M=None values with uint values, using per_channel_m
and center frequency, with first fit strategy. The function checks the available spectrum but check
consistencies among M values of the request, but not with other requests.
For example, if request is for 32 slots corresponding to 8 x 4 slots of 32Gbauds channels,
the following frequency slots will result in the following assignment
N = 0, 8, 16, 32 -> 0, 8, 16, 32
M = 8, None, 8, None -> 8, 8, 8, 8
N = 0, 8, 16, 32 -> 0, , 16
M = None, None, 8, None -> 24, , 8
"""
selected_m = []
selected_n = []
remaining_slots_to_serve = required_m
# order slots for the computation: assign biggest m first
rq_N, rq_M, order = order_slots([{'N': n, 'M': m} for n, m in zip(rq.N, rq.M)])
# Create an oms that represents current assignments of all oms listed in path_oms, and test N and M on it.
# If M is defined, checks that proposed N, M is free
test_oms = aggregate_oms_bitmap(path_oms, oms_list)
for n, m in zip(rq_N, rq_M):
if m is not None and n is not None:
# check availabilityfor this n, m
available_slots = determine_slot_numbers(test_oms, n, m, m)
if available_slots == 0:
# if n, m are not feasible, break at this point no have non zero remaining_slots_to_serve
# in order to blocks the request (even is other N,M where feasible)
break
elif m is not None and n is None:
# find a candidate n
n, _, _ = spectrum_selection(test_oms, m, None)
if n is None:
# if no n is feasible for the m, block the request
break
elif m is None and n is not None:
# find a feasible m for this n. If None is found, then block the request
m = determine_slot_numbers(test_oms, n, remaining_slots_to_serve, per_channel_m)
if m == 0 or remaining_slots_to_serve == 0:
break
else:
# if n and m are not defined, try to find a single assignment to fits the remaining slots to serve
# (first fit strategy)
n, _, _ = spectrum_selection(test_oms, remaining_slots_to_serve, None)
if n is None or remaining_slots_to_serve == 0:
break
else:
m = remaining_slots_to_serve
selected_m.append(m)
selected_n.append(n)
test_oms.assign_spectrum(n, m)
remaining_slots_to_serve = remaining_slots_to_serve - m
# re-order selected_m and selected_n according to initial request N, M order, ignoring None values
not_selected = [None for i in range(len(rq_N) - len(selected_n))]
selected_m = restore_order(selected_m + not_selected, order)
selected_n = restore_order(selected_n + not_selected, order)
return selected_n, selected_m, remaining_slots_to_serve
def pth_assign_spectrum(pths, rqs, oms_list, rpths):
"""basic first fit assignment
if reversed path are provided, means that occupation is bidir
""" basic first fit assignment
if reversed path are provided, means that occupation is bidir
"""
for pth, rq, rpth in zip(pths, rqs, rpths):
if hasattr(rq, 'blocking_reason'):
rq.N = None
rq.M = None
else:
# computes the number of channels required for path_bandwidth and the min required nb of slots
# for one channel (corresponds to the spacing)
nb_wl, required_m = compute_spectrum_slot_vs_bandwidth(rq.path_bandwidth,
rq.spacing, rq.bit_rate)
_, per_channel_m = compute_spectrum_slot_vs_bandwidth(rq.bit_rate,
rq.spacing, rq.bit_rate)
# find oms ids that are concerned both by pth and rpth
path_oms = build_path_oms_id_list(pth + rpth)
if getattr(rq, 'M', None) is not None and all(rq.M):
# if all M are well defined: Consistency check that the requested M are enough to carry the nb_wl:
# check that the integer number of per_channel_m carried in each M value is enough to carry nb_wl.
# if not, blocks the demand
nb_channels_of_request = sum([m // per_channel_m for m in rq.M])
# TODO: elaborate a more accurate estimate with nb_wl * min_spacing + possibly guardbands in case of
for i, pth in enumerate(pths):
# computes the number of channels required
try:
if rqs[i].blocking_reason:
rqs[i].blocked = True
rqs[i].N = None
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
if hasattr(rqs[i], 'M') and rqs[i].M is not None:
# Consistency check between the requested M and path_bandwidth
# M value should be bigger than the computed requested_m (simple estimate)
# TODO: elaborate a more accurate estimate with nb_wl * tx_osnr + possibly guardbands in case of
# 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
if requested_m <= rqs[i].M:
requested_m = rqs[i].M
else:
# TODO : create a specific blocking reason and following process for this case instead of an exception
raise SpectrumError(f'requested M {rqs[i].M} number of slots for request {rqs[i].request_id} ' +
f'should be greater than {requested_m} to support request ' +
f'{rqs[i].path_bandwidth * 1e-9} Gbit/s with {rqs[i].tsp} {rqs[i].tsp_mode}')
# else: there is no M value so the programs uses the requested_m one
if hasattr(rqs[i], 'N'):
requested_n = rqs[i].N
else:
requested_n = None
(center_n, startn, stopn), path_oms = spectrum_selection(pth + rpths[i], oms_list, requested_m,
requested_n)
# 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
rqs[i].N = None
rqs[i].M = 0
rqs[i].blocking_reason = 'NO_SPECTRUM'

View File

@@ -0,0 +1,310 @@
{
"Edfa":[{
"type_variety": "high_detail_model_example",
"type_def": "advanced_model",
"gain_flatmax": 25.0,
"gain_min": 15.0,
"p_max": 21.0,
"advanced_config_from_json": "std_medium_gain_advanced_config.json",
"out_voa_auto": false,
"allowed_for_design": false
}, {
"type_variety": "Juniper_BoosterHG",
"type_def": "advanced_model",
"gain_flatmax": 25.0,
"gain_min": 10.0,
"p_max": 21.0,
"advanced_config_from_json": "Juniper-BoosterHG.json",
"out_voa_auto": false,
"allowed_for_design": false
},
{
"type_variety": "operator_model_example",
"type_def": "variable_gain",
"gain_flatmax": 26.0,
"gain_min": 15.0,
"p_max": 23.0,
"nf_min": 6.0,
"nf_max": 10.0,
"out_voa_auto": false,
"allowed_for_design": false
},
{
"type_variety": "low_noise",
"type_def": "openroadm",
"gain_flatmax": 27.0,
"gain_min": 12.0,
"p_max": 22.0,
"nf_coef": [-8.104e-4,-6.221e-2,-5.889e-1,37.62],
"allowed_for_design": false
},
{
"type_variety": "standard",
"type_def": "openroadm",
"gain_flatmax": 27.0,
"gain_min": 12.0,
"p_max": 22.0,
"nf_coef": [-5.952e-4,-6.250e-2,-1.071,28.99],
"allowed_for_design": false
},
{
"type_variety": "std_high_gain",
"type_def": "variable_gain",
"gain_flatmax": 35.0,
"gain_min": 25.0,
"p_max": 21.0,
"nf_min": 5.5,
"nf_max": 7.0,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_medium_gain",
"type_def": "variable_gain",
"gain_flatmax": 26.0,
"gain_min": 15.0,
"p_max": 23.0,
"nf_min": 6.0,
"nf_max": 10.0,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain",
"type_def": "variable_gain",
"gain_flatmax": 16.0,
"gain_min": 8.0,
"p_max": 23.0,
"nf_min": 6.5,
"nf_max": 11.0,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "high_power",
"type_def": "variable_gain",
"gain_flatmax": 16.0,
"gain_min": 8.0,
"p_max": 25.0,
"nf_min": 9.0,
"nf_max": 15.0,
"out_voa_auto": false,
"allowed_for_design": false
},
{
"type_variety": "std_fixed_gain",
"type_def": "fixed_gain",
"gain_flatmax": 21.0,
"gain_min": 20.0,
"p_max": 21.0,
"nf0": 5.5,
"allowed_for_design": false
},
{
"type_variety": "4pumps_raman",
"type_def": "fixed_gain",
"gain_flatmax": 12.0,
"gain_min": 12.0,
"p_max": 21.0,
"nf0": -1.0,
"allowed_for_design": false
},
{
"type_variety": "hybrid_4pumps_lowgain",
"type_def": "dual_stage",
"raman": true,
"gain_min": 25.0,
"preamp_variety": "4pumps_raman",
"booster_variety": "std_low_gain",
"allowed_for_design": true
},
{
"type_variety": "hybrid_4pumps_mediumgain",
"type_def": "dual_stage",
"raman": true,
"gain_min": 25.0,
"preamp_variety": "4pumps_raman",
"booster_variety": "std_medium_gain",
"allowed_for_design": true
},
{
"type_variety": "medium+low_gain",
"type_def": "dual_stage",
"gain_min": 25.0,
"preamp_variety": "std_medium_gain",
"booster_variety": "std_low_gain",
"allowed_for_design": true
},
{
"type_variety": "medium+high_power",
"type_def": "dual_stage",
"gain_min": 25.0,
"preamp_variety": "std_medium_gain",
"booster_variety": "high_power",
"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": [-2.0, 3.0, 0.5],
"max_fiber_lineic_loss_for_raman": 0.25,
"target_extended_gain": 2.5,
"max_length": 150.0,
"length_units": "km",
"max_loss": 28.0,
"padding": 10.0,
"EOL": 0.0,
"con_in": 0.0,
"con_out": 0.0
}
],
"Roadm":[{
"target_pch_out_db": -20.0,
"add_drop_osnr": 38.0,
"pmd": 0.0,
"restrictions": {
"preamp_variety_list":[],
"booster_variety_list":[]
}
}],
"SI":[{
"f_min": 191.3e12,
"baud_rate": 32e9,
"f_max":195.1e12,
"spacing": 50e9,
"power_dbm": 0.0,
"power_range_db": [0.0,0.0,1.0],
"roll_off": 0.15,
"tx_osnr": 40.0,
"sys_margins": 2.0
}],
"Transceiver":[
{
"type_variety": "vendorA_trx-type1",
"frequency":{
"min": 191.35e12,
"max": 196.1e12
},
"mode":[{
"format": "mode 1",
"baud_rate": 32e9,
"OSNR": 11.0,
"bit_rate": 100e9,
"roll_off": 0.15,
"tx_osnr": 40.0,
"min_spacing": 37.5e9,
"cost":1.0
},
{
"format": "mode 2",
"baud_rate": 66e9,
"OSNR": 15.0,
"bit_rate": 200e9,
"roll_off": 0.15,
"tx_osnr": 40.0,
"min_spacing": 75e9,
"cost":1.0
}
]
},
{
"type_variety": "Voyager",
"frequency":{
"min": 191.35e12,
"max": 196.1e12
},
"mode":[
{
"format": "mode 1",
"baud_rate": 32e9,
"OSNR": 12.0,
"bit_rate": 100e9,
"roll_off": 0.15,
"tx_osnr": 40.0,
"min_spacing": 37.5e9,
"cost":1.0
},
{
"format": "mode 3",
"baud_rate": 44e9,
"OSNR": 18.0,
"bit_rate": 300e9,
"roll_off": 0.15,
"tx_osnr": 40.0,
"min_spacing": 62.5e9,
"cost":1.0
},
{
"format": "mode 2",
"baud_rate": 66e9,
"OSNR": 21.0,
"bit_rate": 400e9,
"roll_off": 0.15,
"tx_osnr": 40.0,
"min_spacing": 75e9,
"cost":1.0
},
{
"format": "mode 4",
"baud_rate": 66e9,
"OSNR": 16.0,
"bit_rate": 200e9,
"roll_off": 0.15,
"tx_osnr": 40.0,
"min_spacing": 75e9,
"cost":1.0
}
]
}
]
}

View File

@@ -0,0 +1,180 @@
{
"gnpy-api:service":{
"path-request": [
{
"request-id": "0",
"source": "trx Alice",
"destination": "trx Bob",
"src-tp-id": "trx Alice",
"dst-tp-id": "trx Bob",
"bidirectional": false,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"trx_mode": "mode 1",
"effective-freq-slot": [
{
"N": 0,
"M": 12
}
],
"spacing": 50000000000.0,
"path_bandwidth": 100000000000.0
}
}
},
{
"request-id": "1",
"source": "trx Alice",
"destination": "trx Bob",
"src-tp-id": "trx Alice",
"dst-tp-id": "trx Bob",
"bidirectional": false,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"trx_mode": "mode 1",
"spacing": 50000000000.0,
"path_bandwidth": 100000000000.0
}
}
},
{
"request-id": "2",
"source": "trx Alice",
"destination": "trx Bob",
"src-tp-id": "trx Alice",
"dst-tp-id": "trx Bob",
"bidirectional": false,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"trx_mode": "mode 2",
"spacing": 100000000000.0,
"path_bandwidth": 100000000000.0
}
}
},
{
"request-id": "3",
"source": "trx Alice",
"destination": "trx Bob",
"src-tp-id": "trx Alice",
"dst-tp-id": "trx Bob",
"bidirectional": true,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"spacing": 50000000000.0,
"path_bandwidth": 100000000000.0
}
},
"explicit-route-objects": {
"route-object-include-exclude": [
{
"explicit-route-usage": "route-include-ero",
"index": 0,
"num-unnum-hop": {
"node-id": "roadm Carol",
"link-tp-id": "link-tp-id is not used",
"hop-type": "LOOSE"
}
}
]
}
},
{
"request-id": "4",
"source": "trx Alice",
"destination": "trx Bob",
"src-tp-id": "trx Alice",
"dst-tp-id": "trx Bob",
"bidirectional": true,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"effective-freq-slot": [
{
"N": -284,
"M": 12
}
],
"spacing": 50000000000.0,
"path_bandwidth": 100000000000.0
}
}
},
{
"request-id": "5",
"source": "trx Bob1",
"destination": "trx Carol1",
"src-tp-id": "trx Bob1",
"dst-tp-id": "trx Carol1",
"bidirectional": true,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "vendorA_trx-type1",
"spacing": 100000000000.0,
"path_bandwidth": 100000000000.0
}
}
},
{
"request-id": "6",
"source": "trx Bob1",
"destination": "trx Carol1",
"src-tp-id": "trx Bob1",
"dst-tp-id": "trx Carol1",
"bidirectional": true,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"trx_mode": "mode 1",
"spacing": 50000000000.0,
"path_bandwidth": 100000000000.0
}
}
},
{
"request-id": "7",
"source": "trx Bob1",
"destination": "trx Carol",
"src-tp-id": "trx Bob1",
"dst-tp-id": "trx Carol",
"bidirectional": true,
"path-constraints": {
"te-bandwidth": {
"technology": "flexi-grid",
"trx_type": "Voyager",
"trx_mode": "mode 1",
"spacing": 50000000000.0,
"path_bandwidth": 100000000000.0
}
}
}
],
"synchronization": [
{
"synchronization-id": "1",
"svec": {
"relaxable": false,
"disjointness": "node link",
"request-id-number": [
"1",
"0"
]
}
}
]
},
"gnpy-api:topology_id": "5cf39d4b-be10-4ee9-b38b-7f4db7403db7",
"gnpy-api:equipment_id": "9ed86e34-9d41-41b2-b8e4-984ca0901d47"
}

2777
gnpy/yang/api-request.json Normal file

File diff suppressed because it is too large Load Diff

901
gnpy/yang/api-topology.json Normal file
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@@ -0,0 +1,901 @@
{
"elements": [
{
"uid": "trx Alice",
"type": "Transceiver",
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Alice",
"region": ""
}
}
},
{
"uid": "trx Bob",
"type": "Transceiver",
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "trx Carol",
"type": "Transceiver",
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "trx Bob1",
"type": "Transceiver",
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "trx Carol1",
"type": "Transceiver",
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "roadm Alice",
"type": "Roadm",
"params": {
"target_pch_out_db": -20.0,
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Alice",
"region": ""
}
}
},
{
"uid": "roadm Bob",
"type": "Roadm",
"params": {
"target_pch_out_db": -20.0,
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "roadm Carol",
"type": "Roadm",
"params": {
"target_pch_out_db": -20.0,
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "roadm Bob1",
"type": "Roadm",
"params": {
"target_pch_out_db": -20.0,
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "roadm Carol1",
"type": "Roadm",
"params": {
"target_pch_out_db": -20.0,
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "fiber (Alice → Bob)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 75.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Bob → Carol)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 80.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Bob1 → Carol1)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 80.0,
"loss_coef": 0.5,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Carol → Dan)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 83.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Dan → Alice)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 60.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Bob → Alice)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 75.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Carol → Bob)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 80.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Carol1 → Bob1)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 80.0,
"loss_coef": 0.5,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Dan → Carol)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 83.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "fiber (Alice → Dan)-",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 60.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.0,
"con_out": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "null",
"region": "null"
}
}
},
{
"uid": "east edfa in Alice to Bob",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 18.5,
"delta_p": -1.5,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Alice",
"region": ""
}
}
},
{
"uid": "east edfa in Bob to Carol",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 19.0,
"delta_p": -1.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "east edfa in Bob1 to Carol1",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 19.0,
"delta_p": -1.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "east edfa in Carol to Dan",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 19.0,
"delta_p": -1.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "east edfa in Dan to Alice",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 15.600000000000001,
"delta_p": -2.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Dan",
"region": ""
}
}
},
{
"uid": "east edfa in Bob to Alice",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 18.5,
"delta_p": -1.5,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "east edfa in Alice to Dan",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 18.0,
"delta_p": -2.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Alice",
"region": ""
}
}
},
{
"uid": "east edfa in Carol to Bob",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 19.0,
"delta_p": -1.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "east edfa in Carol1 to Bob1",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 19.0,
"delta_p": -1.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "west edfa in Alice to Bob",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 16.5,
"delta_p": 0.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Alice",
"region": ""
}
}
},
{
"uid": "west edfa in Bob to Carol",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 17.0,
"delta_p": 0.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "west edfa in Bob1 to Carol1",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 17.0,
"delta_p": 0.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "west edfa in Carol to Dan",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 17.6,
"delta_p": 0.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "west edfa in Dan to Alice",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 13.0,
"delta_p": -1.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Dan",
"region": ""
}
}
},
{
"uid": "west edfa in Bob to Alice",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 16.5,
"delta_p": 0.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Bob",
"region": ""
}
}
},
{
"uid": "west edfa in Alice to Dan",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 14.0,
"delta_p": 0.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Alice",
"region": ""
}
}
},
{
"uid": "west edfa in Carol to Bob",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 17.0,
"delta_p": 0.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
},
{
"uid": "west edfa in Carol1 to Bob1",
"type": "Edfa",
"type_variety": "std_medium_gain",
"operational": {
"gain_target": 17.0,
"delta_p": 0.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"latitude": 0.0,
"longitude": 0.0,
"city": "Carol",
"region": ""
}
}
}
],
"connections": [
{
"from_node": "trx Alice",
"to_node": "roadm Alice"
},
{
"from_node": "trx Bob",
"to_node": "roadm Bob"
},
{
"from_node": "trx Bob1",
"to_node": "roadm Bob1"
},
{
"from_node": "trx Carol",
"to_node": "roadm Carol"
},
{
"from_node": "trx Carol1",
"to_node": "roadm Carol1"
},
{
"from_node": "roadm Alice",
"to_node": "east edfa in Alice to Bob"
},
{
"from_node": "roadm Alice",
"to_node": "east edfa in Alice to Dan"
},
{
"from_node": "roadm Alice",
"to_node": "trx Alice"
},
{
"from_node": "roadm Bob",
"to_node": "east edfa in Bob to Alice"
},
{
"from_node": "roadm Bob1",
"to_node": "east edfa in Bob1 to Carol1"
},
{
"from_node": "roadm Bob",
"to_node": "east edfa in Bob to Carol"
},
{
"from_node": "roadm Bob",
"to_node": "trx Bob"
},
{
"from_node": "roadm Bob1",
"to_node": "trx Bob1"
},
{
"from_node": "roadm Carol",
"to_node": "east edfa in Carol to Bob"
},
{
"from_node": "roadm Carol1",
"to_node": "east edfa in Carol1 to Bob1"
},
{
"from_node": "roadm Carol",
"to_node": "east edfa in Carol to Dan"
},
{
"from_node": "roadm Carol",
"to_node": "trx Carol"
},
{
"from_node": "roadm Carol1",
"to_node": "trx Carol1"
},
{
"from_node": "fiber (Alice → Bob)-",
"to_node": "west edfa in Bob to Alice"
},
{
"from_node": "fiber (Bob → Carol)-",
"to_node": "west edfa in Carol to Bob"
},
{
"from_node": "fiber (Bob1 → Carol1)-",
"to_node": "west edfa in Carol1 to Bob1"
},
{
"from_node": "fiber (Carol → Dan)-",
"to_node": "east edfa in Dan to Alice"
},
{
"from_node": "fiber (Dan → Alice)-",
"to_node": "west edfa in Alice to Dan"
},
{
"from_node": "fiber (Bob → Alice)-",
"to_node": "west edfa in Alice to Bob"
},
{
"from_node": "fiber (Carol → Bob)-",
"to_node": "west edfa in Bob to Carol"
},
{
"from_node": "fiber (Carol1 → Bob1)-",
"to_node": "west edfa in Bob1 to Carol1"
},
{
"from_node": "fiber (Dan → Carol)-",
"to_node": "west edfa in Carol to Dan"
},
{
"from_node": "fiber (Alice → Dan)-",
"to_node": "west edfa in Dan to Alice"
},
{
"from_node": "east edfa in Alice to Bob",
"to_node": "fiber (Alice → Bob)-"
},
{
"from_node": "east edfa in Bob to Carol",
"to_node": "fiber (Bob → Carol)-"
},
{
"from_node": "east edfa in Bob1 to Carol1",
"to_node": "fiber (Bob1 → Carol1)-"
},
{
"from_node": "east edfa in Carol to Dan",
"to_node": "fiber (Carol → Dan)-"
},
{
"from_node": "east edfa in Dan to Alice",
"to_node": "fiber (Dan → Alice)-"
},
{
"from_node": "east edfa in Bob to Alice",
"to_node": "fiber (Bob → Alice)-"
},
{
"from_node": "east edfa in Alice to Dan",
"to_node": "fiber (Alice → Dan)-"
},
{
"from_node": "east edfa in Carol to Bob",
"to_node": "fiber (Carol → Bob)-"
},
{
"from_node": "east edfa in Carol1 to Bob1",
"to_node": "fiber (Carol1 → Bob1)-"
},
{
"from_node": "west edfa in Alice to Bob",
"to_node": "roadm Alice"
},
{
"from_node": "west edfa in Bob to Carol",
"to_node": "roadm Bob"
},
{
"from_node": "west edfa in Bob1 to Carol1",
"to_node": "roadm Bob1"
},
{
"from_node": "west edfa in Bob1 to Carol1",
"to_node": "roadm Bob1"
},
{
"from_node": "west edfa in Carol to Dan",
"to_node": "roadm Carol"
},
{
"from_node": "west edfa in Dan to Alice",
"to_node": "fiber (Dan → Carol)-"
},
{
"from_node": "west edfa in Bob to Alice",
"to_node": "roadm Bob"
},
{
"from_node": "west edfa in Alice to Dan",
"to_node": "roadm Alice"
},
{
"from_node": "west edfa in Carol to Bob",
"to_node": "roadm Carol"
},
{
"from_node": "west edfa in Carol1 to Bob1",
"to_node": "roadm Carol1"
}
]
}

View File

@@ -0,0 +1,53 @@
module gnpy-api {
yang-version 1.1;
namespace "gnpy:gnpy-api";
prefix gnpyapi;
import gnpy-network-topology {
prefix gnpynt;
}
import gnpy-path-computation-simplified {
prefix gnpypc;
}
import gnpy-eqpt-config {
prefix gnpyeqpt;
}
organization
"Telecom Infra Project OOPT PSE Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:ahmed.triki@orange.com>
contact: <mailto:esther.lerouzic@orange.com>
";
description
"YANG model for gnpy api input for path computation - TransportPCE preversion";
revision 2020-10-22 {
description
"draft for experimental/2020-candi";
reference
"YANG model for api input for path computation with gnpy";
}
container service {
description
"Describe the service file to connect to gnpy";
uses gnpypc:service;
}
container result {
uses gnpypc:result;
description
"Describe the response object to gnpy";
}
container topology {
description
"Describe the topology file to connect to gnpy";
uses gnpynt:topo;
}
container equipment {
description
"Describe the equipment library to connect to gnpy";
uses gnpyeqpt:eqpt;
}
}

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@@ -0,0 +1,78 @@
module gnpy-api {
yang-version 1.1;
namespace "gnpy:gnpy-api";
prefix gnpyapi;
import gnpy-network-topology {
prefix gnpynt;
}
import gnpy-path-computation-simplified {
prefix gnpypc;
}
import gnpy-eqpt-config {
prefix gnpyeqpt;
}
import ietf-yang-types {
prefix ietftypes;
}
organization
"Telecom Infra Project OOPT PSE Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:ahmed.triki@orange.com>
contact: <mailto:esther.lerouzic@orange.com>
";
description
"YANG model for gnpy api input for path computation - TransportPCE preversion";
revision 2021-01-06 {
description
"draft for experimental/2020-candi.
Add the possibility to use a topology_id or an equipment_id
";
reference
"YANG model for api input for path computation with gnpy";
}
container service {
description
"Describe the service file to connect to gnpy";
uses gnpypc:service;
}
container result {
uses gnpypc:result;
description
"Describe the response object to gnpy";
}
choice topo {
case explicit {
container topology {
description
"Describe the topology file to connect to gnpy";
uses gnpynt:topo;
}
}
case id {
leaf topology_id {
type ietftypes:uuid;
mandatory true;
}
}
}
choice eqpt {
case explicit {
container equipment {
description
"Describe the equipment library to connect to gnpy";
uses gnpyeqpt:eqpt;
}
}
case id {
leaf equipment_id {
type ietftypes:uuid;
mandatory true;
}
}
}
}

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module gnpy-eqpt-config {
yang-version 1;
namespace "gnpy:gnpy-eqpt-config";
prefix "gnpyeqpt";
organization
"Telecom Infra Project OOPT PSE
Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:ahmed.triki@orange.com>
contact: <mailto:esther.lerouzic@orange.com>
";
description "Base YANG model for gnpy equipment library input for path computation - 2020 - candi preversion";
revision "2020-10-22" {
description "draft for experimental/2020-candi";
reference "Base YANG model for equipment library input for path computation with gnpy";
}
/*
* Identities
identity edfa-type-def {
description "base identity for variable gain and fixed gain";
}
identity variable-gain{
base edfa-type-def ;
description "'variable_gain' is a simplified model simulating a 2-coil
EDFA with internal, input and output VOAs. The NF vs gain response is calculated
accordingly based on the input parameters: nf_min, nf_max, and gain_flatmax. It
is not a simple interpolation but a 2-stage NF calculation.";
}
identity fixed-gain{
base edfa-type-def ;
description "'fixed_gain' is a fixed gain model. NF == Cte == nf0 if gain_min < gain < gain_flatmax";
}
identity fiber-variety {
description "base identity for fiber variety";
}
identity transceiver-variety {
description "base identity for transceiver variety";
}
*/
grouping variable-gain {
leaf nf_min {
type decimal64 {
fraction-digits 2;
}
units dB;
}
leaf nf_max {
type decimal64 {
fraction-digits 2;
}
units dB;
}
leaf out_voa_auto{
type boolean ;
description "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 EOL power margins.";
}
}
grouping fixed-gain{
leaf nf0 {
type decimal64 {
fraction-digits 2;
}
units dB;
}
}
grouping no-type-def{
leaf advanced_config_from_json {
type string ;
description " filename with json edfa";
}
}
grouping openroadm{
leaf-list nf_coef {
type decimal64 {
fraction-digits 5;
}
//default [8.1e-4,6.142e-2,1.558,19.97] ;
}
}
grouping dual-stage {
leaf raman {
type boolean;
}
leaf preamp_variety {
type leafref {
path "../../Edfa/type_variety";
}
}
leaf booster_variety {
type leafref {
path "../../Edfa/type_variety";
}
}
}
grouping edfa-common {
leaf allowed_for_design{
type boolean ;
description "If false, the amplifier will not be picked by auto-design but it can still be used as a
manual input (from JSON or Excel template topology files.)";
}
leaf gain_flatmax {
type decimal64 {
fraction-digits 2;
}
units dB;
}
leaf gain_min {
type decimal64 {
fraction-digits 2;
}
units dB;
}
leaf p_max {
type decimal64 {
fraction-digits 2;
}
units dBm;
}
leaf type_def {
type identityref{
base edfa-type-def ;
}
}
choice type_of_model {
case variable-gain {
when "type_def = 'variable-gain'";
uses variable-gain ;
}
case fixed-gain{
when "type_def = 'fixed-gain'";
uses fixed-gain;
}
case no-type-def{
when "type_def = 'no-type-def'";
uses no-type-def;
}
case openroadm{
when "type_def = 'openroadm'";
uses openroadm;
}
case dual_stage {
when "type_def = 'dual_stage'";
uses dual-stage ;
}
}
}
grouping common-fiber {
description "common parameters for fiber and raman fiber";
leaf type_variety {
type string ;
}
description "a unique name to ID the fiber in the JSON or Excel template topology input file";
leaf dispersion{
type decimal64 {
fraction-digits 8;
}
units s.m-1.m-1;
}
leaf gamma{
type decimal64 {
fraction-digits 8;
}
units w-1.m-1 ;
description "2pi.n2/(lambda*Aeff) (w-2.m-1)";
}
leaf pmd_coef{
type decimal64 {
fraction-digits 16;
}
units s.sqrt(m)-1;
}
}
grouping eqpt{
list Edfa {
key type_variety;
leaf type_variety {
type string;
description "a unique name to ID the amplifier in the JSON/Excel template topology input file";
}
uses edfa-common;
}
list Fiber {
key type_variety;
uses common-fiber;
}
list RamanFiber {
uses common-fiber;
container raman_efficiency {
leaf-list cr {
type decimal64 {
fraction-digits 8;
}
}
leaf-list frequency_offset {
type decimal64 {
fraction-digits 8;
}
}
}
}
list Span {
leaf power_mode {
type boolean ;
}
leaf-list delta_power_range_db {
type decimal64 {
fraction-digits 2;
}
}
leaf max_length {
type decimal64 {
fraction-digits 2;
}
units km;
default 150.0 ;
}
leaf max_loss {
type decimal64 {
fraction-digits 2;
}
units dB;
}
leaf max_fiber_lineic_loss_for_raman {
type decimal64 {
fraction-digits 2;
}
units dB.km-1;
}
leaf target_extended_gain {
type decimal64 {
fraction-digits 2;
}
units dB;
}
leaf length_units{
type string ;
default "km";
}
leaf padding{
type decimal64 {
fraction-digits 2;
}
default 10.0 ;
}
leaf EOL{
type decimal64 {
fraction-digits 2;
}
default 0.0 ;
}
leaf con_in{
type decimal64 {
fraction-digits 2;
}
default 0.0 ;
}
leaf con_out{
type decimal64 {
fraction-digits 2;
}
default 0.0 ;
}
}
list Roadm {
leaf target_pch_out_db {
type decimal64 {
fraction-digits 2;
}
}
leaf add_drop_osnr {
type decimal64 {
fraction-digits 2;
}
}
leaf pmd {
type decimal64 {
fraction-digits 2;
}
}
container restrictions {
leaf-list preamp_variety_list {
type string;
}
leaf-list booster_variety_list {
type string;
}
}
}
list SI {
leaf f_min {
type decimal64 {
fraction-digits 2;
}
}
leaf f_max {
type decimal64 {
fraction-digits 2;
}
}
leaf baud_rate {
type decimal64 {
fraction-digits 2;
}
}
leaf spacing {
type decimal64 {
fraction-digits 2;
}
}
leaf power_dbm {
type decimal64 {
fraction-digits 2;
}
}
leaf-list power_range_db {
type decimal64 {
fraction-digits 2;
}
}
leaf roll_off {
type decimal64 {
fraction-digits 2;
}
}
leaf tx_osnr {
type decimal64 {
fraction-digits 2;
}
}
leaf sys_margins {
type decimal64 {
fraction-digits 2;
}
}
}
list Transceiver {
leaf type_variety {
type string ;
description "a unique name to ID the transceiver in the JSON or Excel template topology input file";
}
container frequency {
leaf min {
type decimal64 {
fraction-digits 2;
}
units Hz ;
}
leaf max {
type decimal64 {
fraction-digits 2;
}
units Hz ;
}
description "Min/max frequency of transponder eg 191.35e12 and 196.1e12";
}
list mode {
leaf format {
type string ;
description "unique name of the mode";
}
leaf baud_rate {
type decimal64 {
fraction-digits 2;
}
units baud ;
description "baud_rate";
}
leaf OSNR {
type decimal64 {
fraction-digits 2;
}
units dB ;
description "min required OSNR in 0.1nm (dB)";
}
leaf tx_osnr {
type decimal64 {
fraction-digits 2;
}
units dB ;
description "min required OSNR in 0.1nm (dB)";
}
leaf min_spacing {
type decimal64 {
fraction-digits 2;
}
units GHz ;
description "...";
}
leaf bit_rate {
type decimal64 {
fraction-digits 2;
}
units bit/s ;
description "bit rate";
}
leaf roll_off {
type decimal64 {
fraction-digits 2;
}
description "...";
}
leaf cost {
type decimal64 {
fraction-digits 2;
}
description "arbitrary unit";
}
}
}
}
}

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module gnpy-network-topology {
yang-version 1.1;
namespace "gnpy:gnpy-network-topology";
prefix gnpynt;
organization
"Telecom Infra Project OOPT PSE Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:ahmed.triki@orange.com>
contact: <mailto:esther.lerouzic@orange.com>
";
description
"YANG model for gnpy network input for path computation - 2020 - candi preversion";
revision 2020-10-22 {
description
"draft for experimental/2020-candi";
reference
"YANG model for network input for path computation with gnpy";
}
identity type-element {
description
"Base identity for element type";
}
identity Transceiver {
base type-element;
description
" Transceiver element";
}
identity Fiber {
base type-element;
description
"Fiber element (unidirectional)";
}
identity Roadm {
base type-element;
description
"Roadm element";
}
identity Edfa {
base type-element;
description
"Edfa element";
}
identity Fused {
base type-element;
description
"Fused element ; non amplified connection between two fiber spans ;
can be used to model optical distribution frame, or losses due to
connectors or fused in a span";
}
identity length-unit {
description
"length unit";
}
identity km {
base length-unit;
description
"kilometers";
}
identity m {
base length-unit;
description
"meter";
}
typedef Coordinate {
type decimal64 {
fraction-digits 6;
}
}
typedef Coef {
type decimal64 {
fraction-digits 2;
}
}
grouping location-attributes {
container location {
leaf city {
type string;
mandatory true;
}
leaf region {
type string;
mandatory true;
}
leaf latitude {
type Coordinate;
mandatory true;
}
leaf longitude {
type Coordinate;
mandatory true;
}
}
}
grouping fiber-params {
description
".....";
leaf length {
type decimal64 {
fraction-digits 2;
}
mandatory true;
}
leaf loss_coef {
type decimal64 {
fraction-digits 2;
}
mandatory true;
units db/km;
description "Loss coefficient of the fiber span (dB/km)";
}
leaf length_units {
type identityref {
base length-unit;
}
mandatory true;
}
leaf att_in {
type decimal64 {
fraction-digits 2;
}
units "dB";
mandatory true;
}
leaf con_in {
type decimal64 {
fraction-digits 2;
}
units "dB";
mandatory true;
}
leaf con_out {
type decimal64 {
fraction-digits 2;
}
units "dB";
mandatory true;
}
}
grouping edfa-params {
container operational {
description
"Operational values for the Edfa ";
leaf gain_target {
type decimal64 {
fraction-digits 2;
}
units "dB";
mandatory true;
description
"gain target of the amplifier (before VOA and after att_in)";
}
leaf tilt_target {
type decimal64 {
fraction-digits 2;
}
mandatory true;
description
"..";
}
leaf out_voa {
type decimal64 {
fraction-digits 2;
}
units "dB";
mandatory true;
description
"..";
}
leaf delta_p {
type decimal64 {
fraction-digits 2;
}
units "dB";
mandatory true;
description
"per channel target output power delta with respect to power setting in SI";
}
}
}
grouping roadm-params {
leaf target_pch_out_db {
type decimal64 {
fraction-digits 2;
}
units "dB";
description
"..";
}
container restrictions {
leaf-list preamp_variety_list {
type string;
description
"List of authorized preamp type-variety";
}
leaf-list booster_variety_list {
type string;
description
"List of authorized booster type-variety";
}
}
}
grouping transceiver-params;
grouping fused-params{
leaf loss {
type decimal64 {
fraction-digits 2;
}
units "dB";
description
"Concentrated loss of the fused element";
}
}
grouping element-type-choice {
choice element-type {
case Edfa {
when "type = 'Edfa'";
uses edfa-params;
}
case FiberRoadm {
container params {
choice fiberroadmfused {
case Fiber {
when "type = 'Fiber'";
uses fiber-params;
}
case Roadm {
when "type = 'Roadm'";
uses roadm-params;
}
case Fused {
when "type = 'Fused'";
uses fused-params;
}
}
}
}
case Transceiver {
when "type = 'Transceiver'";
}
}
}
grouping topo {
list elements {
key "uid";
leaf uid {
type string;
}
leaf type {
type identityref {
base type-element;
}
mandatory true;
}
leaf type_variety {
type string;
mandatory false;
}
container metadata {
uses location-attributes;
}
uses element-type-choice;
}
list connections {
config false;
leaf from_node {
type leafref {
path "../../elements/uid";
}
}
leaf to_node {
type leafref {
path "../../elements/uid";
}
}
}
}
}

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module gnpy-path-computation-simplified {
yang-version 1.1;
namespace "gnpy:path";
prefix "gnpypc";
organization
"Telecom Infra Project OOPT PSE Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:ahmed.triki@orange.com>
contact: <mailto:esther.lerouzic@orange.com>
";
description "YANG model for gnpy path computation simplified for - 2020 - candi preversion";
revision "2020-10-22" {
description
"draft for experimental/2020-candi";
reference
"YANG model for path computation with gnpy inputs";
}
grouping effective-freq-slot{
/* content copied from ietf-flexi-grid-media-channel, because only M and N are needed
from the initial grouping.
*/
description "The effective frequency slot is an attribute
of a media channel and, being a frequency slot, it is
described by its nominal central frequency and slot
width";
reference "rfc7698";
leaf N {
type uint32;
description
"Is used to determine the Nominal Central
Frequency. The set of nominal central frequencies
can be built using the following expression:
f = 193.1 THz + n x 0.00625 THz,
where 193.1 THz is ITU-T ''anchor frequency'' for
transmission over the C band, n is a positive or
negative integer including 0.";
reference "rfc7698";
}
leaf M {
type int32;
description
"Is used to determine the slot width. A slot width
is constrained to be M x SWG (that is, M x 12.5 GHz),
where M is an integer greater than or equal to 1.";
reference "rfc7698";
}
}
grouping gnpy-specific-parameters{
description
"This grouping defines the gnpy specific parameters for requests.";
leaf technology {
type string;
default "flexi-grid";
description
"Data plane technology type.";
}
leaf trx_type {
type string ;
mandatory true;
description "name of the transponder type (to be read from equipment library";
}
leaf trx_mode {
type string;
description "name of the transponder mode (to be read from equipment library";
}
list effective-freq-slot {
key "N";
uses effective-freq-slot ;
}
leaf spacing {
mandatory true;
type decimal64 {
fraction-digits 1;
}
units Hz;
description
"It is the spacing between channels assuming full load with
same channels as the requested one. multiple of 12.5 GHz";
}
leaf max-nb-of-channel{
type int32;
description "Nb of channel to take into account for the full load case.
";
}
leaf output-power{
type decimal64 {
fraction-digits 5;
}
units W;
description "optical power setting to be used for the propagation";
}
leaf path_bandwidth{
type decimal64 {
fraction-digits 5;
}
mandatory true;
units bit/s;
description "Capacity required";
}
}
identity SNR-bandwidth {
base path-metric-type;
description
"A metric that records SNR in signal bandwidth";
}
identity OSNR-bandwidth {
base path-metric-type;
description
"A metric that records OSNR in signal bandwidth";
}
identity SNR-0.1nm {
base path-metric-type;
description
"A metric that records SNR in 0.1nm";
}
identity OSNR-0.1nm {
base path-metric-type;
description
"A metric that records OSNR in 0.1nm";
}
identity reference_power {
base path-metric-type;
description
"to be revised";
}
identity path_bandwidth {
base path-metric-type;
description
"to be revised";
}
grouping transponder{
leaf transponder-type {
type string ;
description
"transponder type.";
}
leaf transponder-mode {
type string ;
description
"transponder mode.";
}
}
grouping hop-attribute{
description
"This grouping defines the hop attribute parameters for request or response";
choice hop-type{
case tsp {
container transponder{
uses transponder ;
}
}
case regen {
container regenerator{
leaf regenerator-id{
type string ;
}
uses transponder ;
}
}
case pow {
container optical-power{
leaf optical-power{
type decimal64 {
fraction-digits 5;
}
units W;
description "not used yet. hop output (input??) power";
}
}
}
}
}
identity path-metric-type {
description
"Base identity for path metric type";
}
identity route-usage-type {
description
"Base identity for route usage";
}
identity route-include-ero {
base route-usage-type;
description
"Include ERO from route";
}
identity route-exclude-ero {
base route-usage-type;
description
"Exclude ERO from route";
}
identity route-exclude-srlg {
base route-usage-type;
description
"Exclude SRLG from route";
}
typedef te-hop-type {
type enumeration {
enum LOOSE {
description
"loose hop in an explicit path";
}
enum STRICT {
description
"strict hop in an explicit path";
}
}
description
"enumerated type for specifying loose or strict
paths";
reference "RFC3209: section-4.3.2";
}
typedef te-path-disjointness {
type bits {
bit node {
position 0;
description "Node disjoint.";
}
bit link {
position 1;
description "Link disjoint.";
}
bit srlg {
position 2;
description "SRLG (Shared Risk Link Group) disjoint.";
}
}
description
"Type of the resource disjointness for a TE tunnel path.";
reference
"RFC4872: RSVP-TE Extensions in Support of End-to-End
Generalized Multi-Protocol Label Switching (GMPLS)
Recovery";
} // te-path-disjointness
typedef accumulated-metric-type {
type union {
type uint64;
type decimal64 {
fraction-digits 2;
}
}
description
"type useable for accumulative-value";
}
grouping path-route-objects {
description
"List of EROs to be included or excluded when performing
the path computation.";
container explicit-route-objects {
description
"Container for the route object list";
list route-object-include-exclude {
description
"List of explicit route objects to include or
exclude in path computation";
leaf explicit-route-usage {
type identityref {
base route-usage-type;
}
description "Explicit-route usage.";
}
key "index";
uses explicit-route-hop ;
}
}
}
grouping generic-path-disjointness {
description "Path disjointness grouping";
leaf disjointness {
type te-path-disjointness;
description
"The type of resource disjointness.
Under primary path, disjointness level applies to
all secondary LSPs. Under secondary, disjointness
level overrides the one under primary";
}
}
grouping common-path-constraints-attributes {
description
"Common path constraints configuration grouping";
uses common-constraints_config;
}
grouping generic-path-constraints {
description
"Global named path constraints configuration
grouping";
container path-constraints {
description "TE named path constraints container";
uses common-path-constraints-attributes;
}
}
grouping explicit-route-hop {
description
"The explicit route subobject grouping";
leaf index {
type uint32;
description "ERO subobject index";
}
choice type {
description
"The explicit route subobject type";
case num-unnum-hop {
container num-unnum-hop {
leaf node-id {
//type te-node-id;
type string;
description
"The identifier of a node in the TE topology.";
}
leaf link-tp-id {
//type te-tp-id;
type string;
description
"TE link termination point identifier. The combination
of TE link ID and the TE node ID is used to identify an
unnumbered TE link.";
}
leaf hop-type {
type te-hop-type;
description "strict or loose hop";
}
description
"Numbered and Unnumbered link/node explicit route
subobject";
}
}
case label {
container label-hop {
description "Label hop type";
uses effective-freq-slot;
}
description
"The Label ERO subobject";
}
case hop-attribute{
uses gnpypc:hop-attribute ;
}
}
}
grouping common-constraints_config {
description
"Common constraints grouping that can be set on
a constraint set or directly on the tunnel";
container te-bandwidth {
uses gnpy-specific-parameters ;
description
"A requested bandwidth to use for path computation";
}
}
grouping end-points {
description
"Common grouping to define the TE tunnel end-points";
leaf source {
type string;
description "TE tunnel source address.";
}
leaf destination {
type string;
description "P2P tunnel destination address";
}
leaf src-tp-id {
type string;
description "TE tunnel source termination point identifier.";
}
leaf dst-tp-id {
type string;
description "TE tunnel destination termination point
identifier.";
}
}
grouping synchronization-info {
description "Information for sync";
list synchronization {
key "synchronization-id";
description "sync list";
leaf synchronization-id {
type string;
description "index";
}
container svec {
description
"Synchronization VECtor";
leaf relaxable {
type boolean;
default true;
description
"If this leaf is true, path computation process is free
to ignore svec content.
otherwise it must take into account this svec.";
}
uses generic-path-disjointness;
leaf-list request-id-number {
type string;
description "This list reports the set of M path computation requests that must be synchronized.";
}
}
}
}
grouping path-metric {
description "TE path metric type";
leaf metric-type {
type identityref {
base path-metric-type;
}
description "TE path metric type";
}
leaf accumulative-value {
type decimal64 {
fraction-digits 2;
}
description "TE path metric accumulative value";
}
}
grouping generic-path-properties {
description "TE generic path properties grouping";
container path-properties {
config false;
description "The TE path properties";
list path-metric {
key metric-type;
uses path-metric;
}
list z-a-path-metric {
key metric-type;
uses path-metric;
}
list path-route-objects {
description
"Container for the list of route objects either returned by
the computation engine or actually used by an LSP";
container path-route-object {
description
"List of route objects either returned by the computation
engine or actually used by an LSP";
uses explicit-route-hop;
}
}
}
}
grouping path-info {
uses generic-path-properties;
description "Path computation output information";
}
// adding some blocking reasons and info on path in case of blocking
grouping no-path-info {
description "no-path-info";
container no-path {
presence "Response without path information, due to failure
performing the path computation";
leaf no-path {
type string;
mandatory true ;
description
"returned blocking reasons:
NO_PATH
NO_COMPUTED_SNR
NO_FEASIBLE_BAUDRATE_WITH_SPACING
NO_PATH_WITH_CONSTRAINT
NO_FEASIBLE_MODE
MODE_NOT_FEASIBLE
NO_SPECTRUM
";
}
uses generic-path-properties ;
description "if path computation cannot identify a path,
rpc returns no path.";
}
}
grouping service {
list path-request {
key "request-id";
description "request-list";
leaf request-id {
type string;
mandatory true;
description "Each path computation request is uniquely identified by the request-id-number.";
}
leaf bidirectional {
type boolean;
mandatory true;
description "Specify the bidirectionality of the path";
}
uses end-points;
uses path-route-objects;
uses generic-path-constraints;
}
uses synchronization-info;
}
grouping result {
list response {
key response-id;
config false;
description "response";
leaf response-id {
type string;
description
"The list key that has to reuse request-id-number.";
}
choice response-type {
config false;
description "response-type";
case no-path-case {
uses no-path-info;
}
case path-case {
uses path-info;
description "Path computation service.";
}
}
}
}
}

View File

@@ -141,7 +141,7 @@ location is in **gnpy-transmission-example** folder:
.. code-block:: json-object
"Edfa":[{
"type_variety": "openroadm_ila_low_noise",
"type_variety": "low_noise",
"type_def": "openroadm",
"gain_flatmax": 27,
"gain_min": 12,

18
requirements.txt Normal file
View File

@@ -0,0 +1,18 @@
alabaster>=0.7.12,<1
docutils==0.15.2
matplotlib>=3.1.0,<4
networkx>=2.3,<3
numpy>=1.16.1,<2
pandas==0.24.2
pbr>=5.4.4,<6
Pygments>=2.4.2,<3
scipy>=1.3.0,<2
Sphinx>=2.4.4,<3
sphinxcontrib-bibtex>=0.4.2,<1
xlrd>=1.2.0,<2
flask>=1.1.2
gnpy~=2.2.0
cryptography~=3.3.1
Werkzeug~=1.0.1
setuptools~=50.3.1
Flask-Injector

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