2132ba8ab2
to_json export includes a round that makes the export crash when
loss_coef is an array. This patch includes a test on the data to
correctly export per frequency loss coeff.
legacy format supports
"loss_coef": {"value": [0.29, 0.28, 0.29], "frequency": [186.3e12, 194e12, 197e12]},
yang format should be:
"loss_coef_per_frequency": [
{"frequency": "186300000000000.0", "loss_coef_value": "0.29"},
{"frequency": "194000000000000.0", "loss_coef_value": "0.28"},
{"frequency": "197000000000000.0", "loss_coef_value": "0.29"}]
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Id4e49d2b3cce22b85228fe790c15c5a93dea7e06
GNPy: Optical Route Planning and DWDM Network Optimization
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's OOPT/PSE 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.
Quick Start
Install either via Docker, or as a Python package. Read our documentation, learn from the demos, and get in touch with us.
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:
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, or give it a try online at gnpy.app:
Project Calendar
See upcoming meetings on the Project Calendar. The calendar is embedded from Google Calendar and updates automatically.