and create a save_gnpy_json for specific gnpy exports.
because save_json is used as dependency in other projects
Fix example and test file.
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I9af07a13510658dece0685a3bce7589efd57e259
Make sure that a library which includes metada (library-information)
is correctly loaded, and these metada ignored.
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I9c3dc46d502f061b2b31aa430865aa265f1631ad
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
This commit introduces new functions for converting between YANG formatted files and
legacy formats. The conversion processes adhere to RFC7951 for encoding YANG data.
Key changes include:
- Conversion of float and empty type representations.
- Transformation of Span and SI lists xx_power_range into dictionaries.
- Addition of necessary namespaces.
- use of oopt-gnpy-libyang to enforce compliancy to yang models
These utilities enable full compatibility with GNPy.
Co-authored-by: Renato Ambrosone <renato.ambrosone@polito.it>
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ia004113bca2b0631d1648564e5ccb60504fe80f8