94 Commits

Author SHA1 Message Date
EstherLerouzic
c744a97d83 Prepare release notes for v2.13
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Iff07dcd6e98b4e4abd79ec8f97d09df2cf2c0e24
2025-09-26 11:56:02 +02:00
EstherLerouzic
09221504d7 Add yang trees
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I98a16ebea347ff4913840cf6f563c34ebcf8f8d9
2025-09-26 11:52:56 +02:00
EstherLerouzic
f2039fbe1c fix: use loaded json instead of Path for extra configs
In order to be used by API.

Co-authored-by: Renato Ambrosone <renato.ambrosone@polito.it>

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I12111427c8a90b85b3158cdd95f4ee771cb39316
2025-09-26 11:17:45 +02:00
EstherLerouzic
78227e65da fix documentation and release notes
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I18457b1bdebd92bdd547877760a039706ad995a3
2025-09-26 11:17:45 +02:00
EstherLerouzic
e27e6d5c7b chore: add release notes
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ia561105ac5b3fa246bbd26a37e495e0d2ae92041
2025-09-26 11:17:45 +02:00
EstherLerouzic
e3445e1066 Update maintainer names
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I9122bfcf91a6cb55a6c50f98c6944086a21b1b73
2025-09-26 11:17:45 +02:00
EstherLerouzic
a0758d0da5 Move and refactor create_eqpt_sheet.py and add tests on it
Co-authored-by: Rodrigo Sasse David <rodrigo.sassedavid@orange.com>

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ib961c5c0e203f2225a0f1e2e7a091485567189c3
2025-09-26 11:17:45 +02:00
EstherLerouzic
0bc1fb3bf8 fix: Use openpyxl for xlsx reading and move to latest xlrd version
Create a set of excel utils to be used for .xls and .xlsx files, for
reading workbook, reading sheets, ... optimize openpyxl access to
sheet to save computation time.

Use this opportunity to refactor service sheet without namedtuple
and simplify code

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ibaf3aac40b3f6ca4829d8ea8cd506523d318103a
2025-09-26 11:17:45 +02:00
Arturo Mayoral
cd9d4c55b2 Publish calendar at docs/calendar.html and update README link to GitHub Pages
Change-Id: I0381b8d8ebcf3b40d15d1e80fa22bbc3613348e3
2025-09-17 13:13:51 +02:00
EstherLerouzic
62889bf6af feat: add a console script for yang conversion
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: If5ec36beec9d90b2f3d8c08c7fb5b629ad722245
2025-09-03 12:58:21 +02:00
EstherLerouzic
61787d5052 feat: parametrize the function that computes power targets
enable changing the reference span loss and the ratio of the
loss deviation to this reference that should be reported on
the span input.

Initial target used a hardcoded 20dB loss span with
0.3 power slope.

update documentation accordingly.

requires yang updates
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ib763db6be2bd7e947057176f3246f19ac7e6ac0d
2025-09-03 10:34:16 +02:00
Florian FRANK
6612a46a9e Fix to_json()-function of Multiband_amplifier when gain is missing
Signed-off-by: Florian FRANK <florian1.frank@orange.com>
Change-Id: I2a0c249c7e3278e282c2c45ea8be52073f014de3
2025-09-03 10:34:16 +02:00
EstherLerouzic
f30515ba9d fix: do not replace 0 with None
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I02ee8f4f1148873fd19f1c312578bc1f15355667
2025-09-03 10:34:16 +02:00
EstherLerouzic
6f9897fe40 fix: do not crash if type_variety is not defined when saving network
before autodesign type_variety may not be created yet, while ther is one default in params:
use type_variety from params

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I556bc8fa1a8241054c81cee386cf52b94a76a0bc
2025-09-03 10:34:16 +02:00
EstherLerouzic
56e615c713 Feat: Use a reference channel per OMS instead of total power for design
Correctly uses the oms band and spacing for computing the nb of channel
and total power for design per band.
In order to keep the SI values as reference, introduce a new parameter
in SI to indicate wether to use this feature or not.

If "use_si_channel_count_for_design": true, then the f_min, f_max and spacing
from SI are used for all OMSes
else, the f_min, f_max, spacing defined per OMS (design_bands) is used.

This impacts tests where the artificial C-band boudaries were hardcoded, and
it also has an impact on performances when SI's defined nb of channels is larger
than the one defined per OMS. In this case the design was considering a larger
total power than the one finally propagated which resulted in reduced performance.
This feature now corrects this case (if "use_si_channel_count_for_design": false
which is the default setting). Overall autodesign are thus improved.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I471a2c45200894ca354c90b46b662f42414b48ad

tous les test marche et les jeu de tests aussi.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: If25b47aa10f97301fde7f17daa2a9478aed46db2
2025-09-03 10:34:15 +02:00
EstherLerouzic
f447c908bc Feat: Add spacing info in the design_band info
This will be used to compute the max total power for design per OMS.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I392f06c792af9f32d4a14324c683bd3fae655de8
2025-09-03 10:34:15 +02:00
EstherLerouzic
4df6cc6b23 fix bug: use preselected restrictions also for raman flag true
otherwise restrictions that include raman are not correctly selected
eg for preamp with raman restriction in ROADM

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ie0215ca430cf463a5422d9236745710ab92ade59
2025-09-03 10:34:15 +02:00
EstherLerouzic
6c5d11d86c Implement in_voa of amplifiers
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I24feed756586a104e829275244f0868a272e5f6b
2025-09-03 10:34:15 +02:00
EstherLerouzic
1a795639c7 feat: Add conversion utilities for YANG and legacy formats in GNPy
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
2025-09-03 10:34:14 +02:00
EstherLerouzic
ee5e6f9b9e fix(CI): remove windows 2019, add windows 2025 support
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I133f5603f00d03e33add8842d34d692ab8fb1804
2025-09-03 10:34:14 +02:00
EstherLerouzic
ea4ab1d61b fix: place index first in the request-list because of libyang bug
libyang does not find key in data if not placed first in the data

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I63b9aa619e15d770e2dcb59010223318d2518eb7
2025-06-30 09:21:42 +02:00
EstherLerouzic
d43fee5945 fix: save network_name
network_name was not correctly exported in json output.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ia4ae6bf82e5d147d3c99e195151942abc21be3f3
2025-06-30 09:21:42 +02:00
EstherLerouzic
6603a50e78 chore: gnpy yang models
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I68502e76e27b43d2a6f6a5741045df3095fc7ccd
2025-06-30 09:21:39 +02:00
EstherLerouzic
b76c529c0c chore: import external ietf modules
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I02ed156105736ab538e4d5708d38b497f9479658
2025-06-11 15:05:51 +02:00
EstherLerouzic
7a1b15a916 chore: make sure all python files have the correct header
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ifdd6a566fda74c5b7d417f9d61c51d4d3da07bfd
2025-06-11 15:05:51 +02:00
EstherLerouzic
7bc9461547 chore: make sure commits authors are in th AUTHORS list
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I721957b59746738426f2356056c553d9876bcf22
2025-06-04 12:22:33 -04:00
EstherLerouzic
b0ac41e2d5 fix: PMD was not correctly read from excel or exported from json
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I1069b07dfb62bf94d4f591908c034df4e49ce22a
2025-03-21 15:42:45 +01:00
EstherLerouzic
bce42331c4 fix: improve core.networks module docstrings
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I883987bd8c1b966b9fcab6a87a62d14607d8548d
2025-03-21 10:46:43 +01:00
EstherLerouzic
d5491c9ace fix documentation: harmonize titles
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I827b4dcd1418017d925b63e50f95514dc1a0eed8
2025-03-21 10:00:25 +01:00
EstherLerouzic
689c2fb038 fix minor linter issues
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I22154752198d9c9186d185885ca83d82e8870107
2025-03-21 10:00:25 +01:00
EstherLerouzic
15c912bd72 fix improve docstring for tools.cli_examples
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Id368cb52791090d985e67be09edcc7580939524b
2025-03-21 10:00:25 +01:00
EstherLerouzic
d0c10e8537 fix: improve dosctring and typing in tools.convert
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I6640737f2255867120f829bb9709abce77693147
2025-03-21 10:00:25 +01:00
EstherLerouzic
93186b26fb fix link to example-data files in the documentation
and of the class referenced in the documentation
example-data folder is not accessible from the
generated pages on readthedocs. So use hyperlinks
to the files  github repo.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I135e2cb0b0d28fecffcbcbfec9a9d6c8cb5c7347
2025-03-21 10:00:25 +01:00
EstherLerouzic
49aee5a4e8 feat: improve elements docstring and typing
use sphinx notation for params , attributes and type

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ife5cde24f3f8dfad9f14dccc6e9b41a13ba370f3
2025-03-21 10:00:21 +01:00
EstherLerouzic
1c4da4794d fix: update excel documentation
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I34ae7e7a60d46482df1af538e6977ba9afd09f3a
2025-03-21 09:57:34 +01:00
EstherLerouzic
de42dd4a93 fix: restore rtd theme
and fix the table with the custom css

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ib16c08451aa3faaa06ea85c2b9359fc4e7a015da
2025-03-21 09:57:34 +01:00
JennyLescop
57a5e9732b fix integrate tilt data into conversion
add some tests

Signed-off-by: JennyLescop <jenny.lescop@orange.com>
Change-Id: I4bb9a16b5db7890247568cce9d4b4f81ad2f7d34
2025-03-21 08:22:37 +00:00
Renato Ambrosone
101eb8f969 Define functions for results conversion and load eqpt/topology from dict
Change-Id: I4111f20f59aeef1e25fc8b44028922bbb94dea91
2025-03-10 16:13:10 +01:00
EstherLerouzic
7ce6650109 feat: move and update documentation on equipment types
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I0f85a059e2393d2d573938bd0804fe49596bbc2d
2025-01-30 17:23:18 +01:00
EstherLerouzic
252e67a71e fix: move amp documentation to the docs folder and update it
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ie6c207e3335cbf30b1f5858c21672dff420b9c51
2025-01-30 17:23:18 +01:00
EstherLerouzic
f83869392b feat: improve documentation of the scripts options
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ic68ded41b188cd07cf87f83e31e6d4eea5af5ed9
2025-01-30 17:23:18 +01:00
EstherLerouzic
94a3714aba fix: documentation missing the worker_utils section
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I832b0f0bfdd255396e6c9809273b1171d08c9f60
2025-01-30 17:23:18 +01:00
EstherLerouzic
ccab4835fc fix: Refactor the methods to avoid returning the same value
equipment being a dict, no need to use 'return' to have the changes
applied.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ic5a4247bbaa0b4af3fca5b6cb0a74a2f434b1b6a
2025-01-30 17:23:18 +01:00
EstherLerouzic
e55f7a5d4c Define default in common parts to be used both by cli and API
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I1e9c6aa99fd2896789c73340ccf5c8adf51a5f13
2025-01-30 17:23:18 +01:00
EstherLerouzic
4fda8c6002 use explicit file arguments for additional configs
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I133bb6a2d21d573cf819e1d92b1912dfa87dbfa4
2025-01-30 17:23:18 +01:00
EstherLerouzic
8717156712 feat: Read a list of optional extra equipement files
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ic521bbacd38b3bb60da3a364a069abfd1895d337
2025-01-30 17:23:18 +01:00
EstherLerouzic
d2c0836164 Remove default_edfa_config.json dictionary and use parameters.py
But enable the user to still input its own default file with a new
'default_config_from_json' attribute useable in fixed and variable gain
amplifiers.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I773682ae6daa1025007fc051582e779986982838
2025-01-29 18:27:51 +00:00
AndreaDAmico
eac4ba80ea List of collaborative PSE publications added in the docs
Change-Id: I1db6d9fe86004cd5bc8135577421117679cb9965
2025-01-24 08:49:48 +00:00
EstherLerouzic
4ef01d54a5 fix plot bug: do not overwrite the path used for plot
The plot function failed to recognize 'path' as part
of the network due to the reuse of the 'path' variable.
This led to errors when attempting to plot.

Solution is to use a different name for the deepcopy of
path elements used to record the propagation results
'propagated_path'.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I0351c37de0d74391ebeb68e974b777b1f51572aa
2025-01-10 11:08:04 +01:00
EstherLerouzic
4b50ee0c2d fix: do not assume 0 dB default value for tilt-target
Instead keep the None value, it user has not stated anything

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I45fcff92caabbfbe514fbe30deac60426b7eb16b
2024-12-06 16:35:46 +01:00
EstherLerouzic
33a289e22b fix: restore uid info in warning logs
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I2fdd29a4461b250661b1ccaa9737836fc3fe8695
2024-12-06 16:35:46 +01:00
EstherLerouzic
e593b8c9ec fix case where there are multiple multiband amps matching the sub amp type
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ibe86499866f2f9e3dfd70b51a33b919d584b812b
2024-12-06 16:35:46 +01:00
EstherLerouzic
94a6f922cd fix typing
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I0f1621b669b4db833d0760368cd834f3186ee2db
2024-12-06 16:35:46 +01:00
EstherLerouzic
fbe387915b fix: offset was not correctly taken into account on reversed path
TODO: write a test!

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I7ac909bb9b8c9700c3841f133245f17f49ba3467
2024-12-06 16:35:46 +01:00
EstherLerouzic
fce9d1d293 chore: refactor json_io
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: If764ba7b520a060deb855c0b55e17c78fa22f841
2024-12-06 16:35:46 +01:00
EstherLerouzic
a59db8fd12 fix: cli_examples linter issues
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Id7e2f8b7282913b885062a01f1bd018bbc85e39c
2024-12-06 16:35:46 +01:00
EstherLerouzic
de509139b3 fix: linter issues on json_io
add docstrings, typing, small fixes

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I01d0fabe5e34103077ec2de829e96829e6202e1e
2024-12-06 16:35:46 +01:00
EstherLerouzic
bb77b3f4a8 fix: remove unused _automatic_spacing
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ie3c2fc226f8a549622933cbd1ba8a6b8be213f92
2024-12-06 16:35:46 +01:00
EstherLerouzic
34c7fd1b60 fix: save autodesign file after autodesign!
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: If1c82c8cb7ff9dbb8bf5c2d5c4b96beaa59dc402
2024-12-06 16:35:46 +01:00
EstherLerouzic
89a962ffaf fix remove unnecessary else after return
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I61dc58f15c8f03a686437e19a36ac0afe35904e9
2024-12-06 16:35:46 +01:00
EstherLerouzic
1722fbec13 feat: add more warnings on amplifiers
when user settings do not match library

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Id387b7781d9637f1d18c453dae75330962229902
2024-12-06 16:35:46 +01:00
EstherLerouzic
e48aa57c35 Improve error reporting by including uid of elements
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ief4125322e4db02765974c43159a014749cdab2e
2024-12-06 16:35:46 +01:00
EstherLerouzic
e3e37b1986 feat: skip path computation when path is explicit
and add tests for explicit path

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I95aaf5b56a7ea04f24153d5cb6612cd09401401c
2024-12-06 16:35:46 +01:00
EstherLerouzic
abf42afaf8 fix ci: The macOS-12 environment is deprecated
remove this check and add one for The macOS-14 instead

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ief1c990cbc67ec4d7912404c24d67f9f2fa6d96e
2024-12-06 16:35:46 +01:00
EstherLerouzic
310995045e fix: linter issues in convert and service_sheet
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I5f7490ed61b53cea8d2923a8a54d38b3fbb5fa0a
2024-12-06 16:35:43 +01:00
EstherLerouzic
c840bb1a44 Improve test coverage on ila constraint cases
explicitely check the corrections for all cases
ila defined in eqpt or not,
ila defined on the link with same direction as request or not
constraint loose or strict
several or one ila in the OMS

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I4d4b5167e7327c9aea4b13879f4e00d30e60d643
2024-11-25 17:07:36 +01:00
EstherLerouzic
4b6f4af3a5 Refactor to reduce cognitive complexity
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ia9992ebbe06498ed53b3987edd4eb139d960ff75
2024-11-25 17:07:33 +01:00
EstherLerouzic
dc68d38293 fix ila names
auto design were changed long ago and these functions did not
apply the changes. Besides there was a confusion between request_element
class where loose is a string, and PathRequest from topology.requests
where loose_list is a list of strings.
This patch corrects the naming and also the tests,
because it used the wrong class to gererate xls services

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I564b77576459d6cb47767398a2db8138ba6ad1e4
2024-11-25 16:55:25 +01:00
EstherLerouzic
defe3bee5c feat: documentation for ROADM excel sheet input
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ie662015c9cd0a90aff46c63fce47d678ffe1d4db
2024-11-25 12:09:14 +01:00
EstherLerouzic
32adc0fc53 feat: enables reading per degree impairment from xls input
- read per degre roadm-path impairment from roadm sheet
add additional optional columns: type_variety and 'from degrees'
and 'from degree to degree impairment id'
'from degrees' can contain a list of degrees separated with ' | ', then the
'from degree to degree impairment id' must contain a list of ids of the same
length.
Impairment ids are expected to be in the ROADM equipment spec and
from degree must be the previous node (no verification of user input).

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I7d326bb3d4f366835249089e9537747c7d3ec2fd
2024-11-25 12:09:09 +01:00
EstherLerouzic
4796266657 fix bug in roadm to_json: move per_degree_impairments in params
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I75ed610f201608a3cb651e8c0604de444113bc25
2024-11-25 08:55:00 +01:00
EstherLerouzic
c35104c184 Add documentation for multiband
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Iadf6d9edd8c67c1389c4a0d482466a8c52198621
2024-11-21 09:26:51 +01:00
AndreaDAmico
7b1354ee24 fix: avoid using cumtrapz from scipy
cumtrapz has been replaced with cumulative_trapezoid in the scipy version currently required by GNPy.

Change-Id: I6790f7aa8d8e8d171faa48db4b20e6a93141c471
2024-11-15 22:25:27 +00:00
AndreaDAmico
39d3f0f483 Perturbative Raman Solver
Raman effect evaluation based on a perturbative solution for faster computation

Change-Id: Ie6d4ea4d9f95d8755dc8dfd004c954d4c2c5f759
2024-11-08 19:55:20 +00:00
AndreaDAmico
bbe9ef7356 Increasing precision in Raman tests
Change-Id: I7a4de449a673d2e2ac23376d7fe64399c65e1246
2024-11-08 18:12:49 +00:00
AndreaDAmico
42a8f018cd GGN approximation formula defined
An approximated version of the GGN is implemented to reduce the computational time enabling fast multi-band transmission simulations

Change-Id: I2951a878aa04b5eb4a33ba86d626a788c4cbb100
2024-11-08 18:09:44 +00:00
EstherLerouzic
29f5dd1dc4 Add frequency dependency on ROADM impairments
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Icb88bf9c42c09deb0064e3299b78b080462fef79
2024-10-16 17:49:00 +00:00
EstherLerouzic
03da959724 insert multiband_amplifier if needed
the automatic add_missing_elements function is updated to insert
multiband booster, preamp or inline amplifiers based on the OMS
nature. If nothing is stated, then uses Edfas.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I968a2fc0a3da97aecb7b513ff211491b20cdd4f2
2024-10-16 17:47:29 +00:00
EstherLerouzic
f621ca6fe7 Add tilt computation for design targets
Compute the tilts only if raman-flag in sim_params is turned on.
Use actual input power in fiber (according to expected propagation
during design).
Creates a function that computes the expected tilt after propagation
in a span, and returns the normalized power difference at the center
frequency of each band, and the tilt experenced between lower and
upper frequency in each band.
Include the expected tilt when computing target gains of amplifiers.
Current function requires that the bands remain in the same order.
(ordering is ensured when creating the objects).

Change-Id: I28bdf13f2010153175e8b6d199fd8eea15d7b292
2024-10-16 17:46:59 +00:00
EstherLerouzic
24f4503020 Preselect multiband amplifiers based on band gain and power targets
To ensure that the multiband amplifier meets the required gain and
power targets for each band, this commit introduces a preselection
process for the amplifiers type variety. The preselection ensures
that only compatible amplifiers are considered, avoiding that
an amplifier is selected for one band that is not part of the same
multiband amplifier type variety of the amplifier selected for the
other band(s).

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I8de7e0b7c165e6edfe47d7f4cda80db23924a9c9
2024-10-16 17:46:34 +00:00
EstherLerouzic
520c3615e4 Refactor select_edfa
Objective is to reuse the functions that lists suitable type variety candidates
for each amplifier of the multiband amplifier

restrictions are processed before entering select_edfa.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I8c784cef6bfed9a2e95bc39434a32191678db81f
2024-10-16 17:40:29 +00:00
EstherLerouzic
548626a9f2 preselect amplifiers based on restrictions and bands
make sure that selected amplifiers (single or multiband) have a band
that encompasses design_band.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I8b66755efbe8413f32328b9e02099ffdedd4b7ed
2024-10-16 17:40:01 +00:00
EstherLerouzic
7a26833a5a Add some test on select_edfa
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ia54c62fe76175f16048992ca1f67439dd32c6e5e
2024-10-16 17:39:39 +00:00
EstherLerouzic
c2f6f9c6a0 Add an invocation test with multiband case
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I0a98175f0c6b4333fae6bea40dac826032a25233
2024-10-16 17:39:13 +00:00
EstherLerouzic
64a91256fc Propagate power per band during autodesign
Target setting computation is done going through each element of the OMS
and computing resulting delta power after each amplifier element. In order
to account for different delta power per band (multi band autodesign), the
computation must be made per band. The previous introduction of a standard
name for bands ("CBAND", "LBAND") ensures a stable key to index these
delta power computation.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ida4b2486ebde4f2a1fb21a44458d1fe34a788d1f
2024-10-16 17:37:35 +00:00
EstherLerouzic
bdcffc2a5e Refactor: define a separate function to compute targets
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I5698feb059f13b90c1ab3d0843fb000c4e0b6b59
2024-10-16 17:36:52 +00:00
EstherLerouzic
c384af8062 Refactor: create a function to set one single band amplifier
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I00018c38b0cc0ceefcd21d50dd0cdc639019cc70
2024-10-16 17:36:25 +00:00
EstherLerouzic
0813332adc Enable differentiated design band per OMS
Introduce a design_band parameter in ROADM and Transceiver.
- if nothing is defined, use SI band(s)
- if design band is defined in ROADM, use this one for all degrees
- if per degree design band is defined, use this one instead

unsupported case: single band OMS with default multiband design band.
Check that these definitions are consistent with actual amplifiers

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ibea4ce6e72d2b1e96ef8cf4efaf499530d24179c
2024-10-16 17:31:33 +00:00
EstherLerouzic
22fe9ead55 Introduce multi band amps
Introduce a new multi-band element that contains a list of Edfa element:
- reads multiple amps out of the element config.
- deduces frequency band from the amp in the list.

no autodesign yet: multi-band amps must have type_variety.

- checks that type variety of individual EDFAs is consistent with multiband
type variety
- demux and mux spectrum when propagate in multiband
- don't add a preamp or booster if a multiband amp is already defined.

The print of channel number is removed from equipment, since the channel number
may now depend on the path's amplifiers. This changes invocation results layout.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I44e77ff82e622cdee4021a7984d660317cb90cf9
2024-10-16 17:26:11 +00:00
EstherLerouzic
920ac30aa5 Refactor and simplify network functions
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ifa0949a8b7739036639e1a4b006ceb08804558ce
2024-10-16 17:24:52 +00:00
EstherLerouzic
ac8fd770ab Only propagates carriers that belong to Amp bandwidth
The commit introduces mux/demux functions in amps and ensures that the
propagation is only done on carriers that are in the Amp bandwitdh, ie
with all their spectrum including slot width is in bandwidth.

For consistency, default amp f_min is changed:
Objective is to use amplifiers' band to bound the possible frequencies
to be propagated. Since the current default f_min of Amp in json_io.py is
higher than the SI one, this would result in a different nb of channels
than currently used in tests, and a change in all tests. In order to
avoid this, I preferred to change this value and have consistency
between SI f_min and Amp f_min.

The commits adds a set of functions to make amps band the useable
spectrum on each OMS. Thee OMS generation is changed to use the amp band.

The commit adds filtering functions (demux and mux) to filter out spectrum
which is not in the amplifier band.

Spectrum assignment is also corrected to correctly match the amp bandwidth
constraint with guardband: center frequency index must be within the
usable part of the amp band. This changes a bit the notion of freq_index
and guardband in the functions, but this is transparent to user:
f_min, f_max represent the amp band, while self.freq_index_min/max
represent the center frequency boundary for a reference 50GHz channel.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I225b2b2dc0e1f1992c0460f6e08fa9c9bc641edf
2024-10-16 17:16:21 +00:00
EstherLerouzic
5277ae2005 Add a redesign option
redesign True means that network is redesigned using each request
as reference channel. When False it means that the design is made
once and successive propagation use the settings computed with this
design.

Default propogation is without redesign, so that path-request-script
must use the ----redesign-per-request option to behave as before this
commit.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I0084185106d14659a846136620cd17791d551a7d
2024-10-16 17:15:20 +00:00
EstherLerouzic
30ead40e76 Creates a set of functions to be called by CLI and API
Instead of copying the CLI script in API code, use functions shared
by CLI and API

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I3f9b30b8700b68237d0e80768db015d8dec3deb5
2024-10-16 17:13:25 +00:00
EstherLerouzic
ae858b911a fix: capture warning to show the ROADM uid
Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Ie13bf4c3436a5a0b8ec730698920eee2c7fb81e8
2024-10-16 17:10:34 +00:00
184 changed files with 74450 additions and 7689 deletions

View File

@@ -112,16 +112,18 @@ jobs:
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
- os: windows-2025
python_version: "3.11"
- os: windows-2025
python_version: "3.12"
- os: macos-13
python_version: "3.12"
- os: macos-14
python_version: "3.12"
paywalled-platforms:
name: Tests on paywalled platforms

View File

@@ -7,24 +7,29 @@ To learn how to contribute, please see CONTRIBUTING.md
- Alessio Ferrari (Politecnico di Torino) <alessio.ferrari@polito.it>
- Anders Lindgren (Telia Company) <Anders.X.Lindgren@teliacompany.com>
- Andrea D'Amico (Politecnico di Torino) <andrea.damico@polito.it>
- Andrea D'Amico (NEC) <adamico@nec-labs.com>
- Arturo Mayoral (Telecom Infra Project) <amayoral@telecominfraproject.com>
- Brian Taylor (Facebook) <briantaylor@fb.com>
- David Boertjes (Ciena) <dboertje@ciena.com>
- Diego Landa (Facebook) <dlanda@fb.com>
- Emmanuelle Delfour (Orange) <WEDE7391@orange.com>
- Esther Le Rouzic (Orange) <esther.lerouzic@orange.com>
- Florian Frank (Orange) <florian1.frank@orange.com>
- Gabriele Galimberti (Cisco) <ggalimbe@cisco.com>
- Gert Grammel (Juniper Networks) <ggrammel@juniper.net>
- Giacomo Borraccini (Politecnico di Torino) <giacomo.borraccini@polito.it>
- Giacomo Borraccini (NEC Laboratories America) <gborraccini@nec-labs.com>
- Gilad Goldfarb (Facebook) <giladg@fb.com>
- James Powell (Telecom Infra Project) <james.powell@telecominfraproject.com>
- Jan Kundrát (Telecom Infra Project) <jkt@jankundrat.com>
- Jeanluc Augé (Orange) <jeanluc.auge@orange.com>
- Jenny L'Escop (Orange) <jenny.lescop@orange.com>
- Jonas Mårtensson (RISE) <jonas.martensson@ri.se>
- Mattia Cantono (Politecnico di Torino) <mattia.cantono@polito.it>
- Miguel Garrich (University Catalunya) <miquel.garrich@upct.es>
- Raj Nagarajan (Lumentum) <raj.nagarajan@lumentum.com>
- Renato Ambrosone (Politecnico di Torino) <renato.ambrosone@polito.it>
- Roberts Miculens (Lattelecom) <roberts.miculens@lattelecom.lv>
- Rodrigo Sasse David (Orange) <rodrigo.sassedavid@orange.com>
- Sami Alavi (NUST) <sami.mansooralavi1999@gmail.com>
- Shengxiang Zhu (University of Arizona) <szhu@email.arizona.edu>
- Stefan Melin (Telia Company) <Stefan.Melin@teliacompany.com>

View File

@@ -29,3 +29,7 @@ GNPy can do much more, including acting as a Path Computation Engine, tracking b
Learn more about this [in the documentation](https://gnpy.readthedocs.io/), or give it a [try online at `gnpy.app`](https://gnpy.app/):
[![Path propagation at gnpy.app](docs/images/2022-04-12-gnpy-app.png)](https://gnpy.app/)
## Project Calendar
See upcoming meetings on the [Project Calendar](https://telecominfraproject.github.io/oopt-gnpy/calendar.html). The calendar is embedded from Google Calendar and updates automatically.

4
docs/_static/custom.css vendored Normal file
View File

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

View File

@@ -12,7 +12,8 @@ We encourage all interested people outside the TIP to [join the project](https:/
`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).
To get involved, please contact [Esther Le Rouzic](mailto:esther.lerouzic@orange.com) or
[Andrea d'Amico](mailto:adamico@nec-labs.com) or [Gert Grammel](mailto:ggrammel@juniper.net).
`gnpy` contributions are currently limited to members of [TIP](http://telecominfraproject.com).
Membership is free and open to all.

View File

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

View File

@@ -1860,3 +1860,165 @@ month={Sept},}
pages={3499-3511},
doi={10.1109/JLT.2022.3162134}
}
@inproceedings{grammel2018physical,
title={Physical simulation environment of the telecommunications infrastructure project (TIP)},
author={Grammel, Gert and Curri, Vittorio and Auge, Jean-Luc},
booktitle={Optical Fiber Communication Conference},
pages={M1D--3},
year={2018},
organization={Optica Publishing Group}
}
@inproceedings{taylor2018towards,
title={Towards a route planning tool for open optical networks in the telecom infrastructure project},
author={Taylor, Brian D and Goldfarb, Gilad and Bandyopadhyay, Saumil and Curri, Vittorio and Schmidtke, Hans-Juergen},
booktitle={Optical Fiber Communication Conference},
pages={Tu3E--4},
year={2018},
organization={Optica Publishing Group}
}
@article{filer2018multi,
title={Multi-vendor experimental validation of an open source QoT estimator for optical networks},
author={Filer, Mark and Cantono, Mattia and Ferrari, Alessio and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
journal={Journal of Lightwave Technology},
volume={36},
number={15},
pages={3073--3082},
year={2018},
publisher={IEEE}
}
@inproceedings{auge2019open,
title={Open optical network planning demonstration},
author={Auge, Jean-Luc and Grammel, Gert and Le Rouzic, Esther and Curri, Vittorio and Galimberti, Gabriele and Powell, James},
booktitle={Optical Fiber Communication Conference},
pages={M3Z--9},
year={2019},
organization={Optica Publishing Group}
}
@inproceedings{kundrat2020physical,
title={Physical-layer awareness: GNPy and ONOS for end-to-end circuits in disaggregated networks},
author={Kundr{\'a}t, Jan and Campanella, Andrea and Le Rouzic, Esther and Ferrari, Alessio and Havli{\v{s}}, Ond{\v{r}}ej and Ha{\v{z}}linsk{\`y}, Michal and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
booktitle={2020 Optical Fiber Communications Conference and Exhibition (OFC)},
pages={1--3},
year={2020},
organization={IEEE}
}
@inproceedings{ferrari2020experimental,
title={Experimental validation of an open source quality of transmission estimator for open optical networks},
author={Ferrari, Alessio and Filer, Mark and Balasubramanian, Karthikeyan and Yin, Yawei and Le Rouzic, Esther and Kundr{\'a}t, Jan and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
booktitle={2020 Optical Fiber Communications Conference and Exhibition (OFC)},
pages={1--3},
year={2020},
organization={IEEE}
}
@article{ferrari2020gnpy,
title={GNPy: an open source application for physical layer aware open optical networks},
author={Ferrari, Alessio and Filer, Mark and Balasubramanian, Karthikeyan and Yin, Yawei and Le Rouzic, Esther and Kundr{\'a}t, Jan and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
journal={Journal of Optical Communications and Networking},
volume={12},
number={6},
pages={C31--C40},
year={2020},
publisher={Optica Publishing Group}
}
@inproceedings{ferrari2020softwarized,
title={Softwarized optical transport QoT in production optical network: a Brownfield validation},
author={Ferrari, Alessio and Balasubramanian, Karthikeyan and Filer, Mark and Yin, Yawei and Le Rouzic, Esther and Kundr{\'a}t, Jan and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
booktitle={2020 European Conference on Optical Communications (ECOC)},
pages={1--4},
year={2020},
organization={IEEE}
}
@article{ferrari2021assessment,
title={Assessment on the in-field lightpath QoT computation including connector loss uncertainties},
author={Ferrari, Alessio and Balasubramanian, Karthikeyan and Filer, Mark and Yin, Yawei and Le Rouzic, Esther and Kundr{\'a}t, Jan and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
journal={Journal of Optical Communications and Networking},
volume={13},
number={2},
pages={A156--A164},
year={2021},
publisher={Optica Publishing Group}
}
@inproceedings{kundrat2021gnpy,
title={GNPy \& YANG: open APIs for end-to-end service provisioning in optical networks},
author={Kundr{\'a}t, Jan and Le Rouzic, Esther and M{\aa}rtensson, Jonas and Campanella, Andrea and Havli{\v{s}}, Ond{\v{r}}ej and DAmico, Andrea and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio and Vojt{\v{e}}ch, Josef},
booktitle={Optical Fiber Communication Conference},
pages={M1B--6},
year={2021},
organization={Optica Publishing Group}
}
@inproceedings{d2021gnpy,
title={GNPy experimental validation on flex-grid, flex-rate WDM optical transport scenarios},
author={DAmico, Andrea and London, Elliot and Le Guyader, Bertrand and Frank, Florian and Le Rouzic, Esther and Pincemin, Erwan and Brochier, Nicolas and Curri, Vittorio},
booktitle={Optical fiber communication conference},
pages={W1G--2},
year={2021},
organization={Optica Publishing Group}
}
@inproceedings{virgillito2021testing,
title={Testing TIP open source solutions in deployed optical networks},
author={Virgillito, Emanuele and Braun, Ralf-Peter and Breuer, Dirk and Gladisch, Andreas and Curri, Vittorio and Grammel, Gert},
booktitle={Optical Fiber Communication Conference},
pages={F1C--3},
year={2021},
organization={Optica Publishing Group}
}
@article{d2022experimental,
title={Experimental validation of GNPy in a multi-vendor flex-grid flex-rate WDM optical transport scenario},
author={DAmico, Andrea and London, Elliot and Le Guyader, Bertrand and Frank, Florian and Le Rouzic, Esther and Pincemin, Erwan and Brochier, Nicolas and Curri, Vittorio},
journal={Journal of Optical Communications and Networking},
volume={14},
number={3},
pages={79--88},
year={2022},
publisher={Optica Publishing Group}
}
@inproceedings{mano2022accuracy,
title={Accuracy of nonlinear interference estimation on launch power optimization in short-reach systems with field trial},
author={Mano, Toru and DAmico, Andrea and Virgillito, Emanuele and Borraccini, Giacomo and Huang, Yue-Kai and Kitamura, Kei and Anazawa, Kazuya and Masuda, Akira and Nishizawa, Hideki and Wang, Ting and others},
booktitle={European Conference and Exhibition on Optical Communication},
pages={We3B--1},
year={2022},
organization={Optica Publishing Group}
}
@inproceedings{kundrat2022gnpy,
title={GNPy: Lessons learned and future plans},
author={Kundr{\'a}t, Jan and Le Rouzic, Esther and M{\aa}rtensson, Jonas and Melin, Stefan and DAmico, Andrea and Grammel, Gert and Galimberti, Gabriele and Curri, Vittorio},
booktitle={European Conference and Exhibition on Optical Communication},
pages={We3B--6},
year={2022},
organization={Optica Publishing Group}
}
@inproceedings{grammel2023open,
title={Open Optical Networks: the good, the bad and the ugly},
author={Grammel, Gert and Kundrat, Jan and Le Rouzic, Esther and Melin, Stefan and Curri, Vittorio and d'Amico, Andrea and Manzotti, Roberto},
booktitle={49th European Conference on Optical Communications (ECOC 2023)},
volume={2023},
pages={1585--1588},
year={2023},
organization={IET}
}
@inproceedings{d2024gnpy,
title={GNPy Experimental Validation in a C+ L Multiband Optical Multiplex Section},
author={DAmico, Andrea and Gatto, Vittorio and Nespola, Antonino and Borraccini, Giacomo and Jiang, Yanchao and Poggiolini, Pierluigi and Le Rouzic, Esther and de Lerma, Arturo Mayoral L{\'o}pez and Grammel, Gert and Manzotti, Roberto and others},
booktitle={2024 24th International Conference on Transparent Optical Networks (ICTON)},
pages={1--4},
year={2024},
organization={IEEE}
}

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

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

View File

@@ -1,7 +1,8 @@
.. _concepts:
*****************************
Simulating networks with GNPy
=============================
*****************************
Running simulations with GNPy requires three pieces of information:
@@ -12,7 +13,7 @@ Running simulations with GNPy requires three pieces of information:
.. _concepts-topology:
Network Topology
----------------
================
The *topology* acts as a "digital self" of the simulated network.
When given a network topology, GNPy can either run a specific simulation as-is, or it can *optimize* the topology before performing the simulation.
@@ -34,7 +35,7 @@ The topology is specified via :ref:`XLS files<excel>` or via :ref:`JSON<legacy-j
.. _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:
@@ -208,7 +209,7 @@ In other cases where the location of amplifier huts is already known, but the sp
.. _concepts-equipment:
The Equipment Library
---------------------
=====================
In order to produce an accurate simulation, GNPy needs to know the physical properties of each entity which affects the optical signal.
Entries in the equipment library correspond to actual real-world, tangible entities.
@@ -231,7 +232,7 @@ GNPy currently does not take into consideration the spectrum filtering penalties
.. _concepts-nf-model:
Amplifier Noise Figure Models
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-----------------------------
One of the key parameters of an amplifier is the method to use for computing the Noise Figure (NF).
GNPy supports several different noise models with varying level of accuracy.
@@ -244,7 +245,7 @@ For scenarios where the vendor has not yet contributed an accurate EDFA NF descr
.. _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.
@@ -254,7 +255,7 @@ The worst (maximal) NF applies when the EDFA operates at its minimal gain.
This model is suitable for use when the vendor has not provided a more accurate performance description of the EDFA.
Raman Approximation
*******************
^^^^^^^^^^^^^^^^^^^
While GNPy is fully Raman-aware, under certain scenarios it is useful to be able to run a simulation without an accurate Raman description.
For these purposes the :ref:`polynomial NF<ext-nf-model-polynomial-NF>` model with :math:`\text{a} = \text{b} = \text{c} = 0`, and :math:`\text{d} = NF` can be used.
@@ -262,7 +263,7 @@ For these purposes the :ref:`polynomial NF<ext-nf-model-polynomial-NF>` model wi
.. _concepts-simulation:
Simulation
----------
==========
When the network model has been instantiated and the physical properties and operational settings of the actual physical devices are known, GNPy can start simulating how the signal propagate through the optical fiber.

View File

@@ -19,6 +19,8 @@
#
import os
import sys
sys.path.insert(0, os.path.abspath('../'))
# -- General configuration ------------------------------------------------
@@ -36,6 +38,7 @@ extensions = ['sphinx.ext.autodoc',
'sphinxcontrib.bibtex',
'sphinx.ext.graphviz',
'myst_parser',
'sphinx_rtd_theme',
]
myst_enable_extensions = [
@@ -84,11 +87,22 @@ todo_include_todos = False
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
html_theme = 'alabaster'
html_theme = "sphinx_rtd_theme"
html_theme_options = {
'logo': 'images/GNPy-logo.png',
'logo_name': False,
'prev_next_buttons_location': 'bottom',
# Toc options
'collapse_navigation': True,
'sticky_navigation': True,
'navigation_depth': 4,
'includehidden': True,
'titles_only': False
}
html_theme_options = {
'navigation_depth': 4,
}
html_favicon = 'images/GNPy-logo.png'
html_logo = 'images/GNPy-logo.png'
@@ -101,7 +115,10 @@ html_logo = 'images/GNPy-logo.png'
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = []
html_static_path = ['_static']
html_css_files = [
'custom.css', # Inclure votre fichier CSS personnalisé
]
# Custom sidebar templates, must be a dictionary that maps document names
# to template names.
@@ -118,6 +135,7 @@ html_sidebars = {
]
}
html_secnum_depth = 4
# -- Options for HTMLHelp output ------------------------------------------

View File

@@ -1,7 +1,8 @@
.. _excel:
*****************************
Excel (XLS, XLSX) input files
=============================
*****************************
``gnpy-transmission-example`` gives the possibility to use an excel input file instead of a json file. The program then will generate the corresponding json file for you.
@@ -9,21 +10,22 @@ The file named 'meshTopologyExampleV2.xls' is an example.
In order to work the excel file MUST contain at least 2 sheets:
- Nodes
- Links
- `Nodes`
- `Links`
(In progress) The File MAY contain an additional sheet:
(In progress) The File MAY contain additional sheets:
- Eqt
- Service
- `Eqpt`
- `Service`
- `Roadms`
.. _excel-nodes-sheet:
Nodes sheet
-----------
`Nodes` sheet
=============
Nodes sheet contains nine columns.
Each line represents a 'node' (ROADM site or an in line amplifier site ILA or a Fused)::
`Nodes` sheet contains nine columns.
Each line represents a 'node' (`ROADM` site or an in line amplifier site `ILA` or a `Fused`)::
City (Mandatory) ; State ; Country ; Region ; Latitude ; Longitude ; Type
@@ -50,15 +52,15 @@ Each line represents a 'node' (ROADM site or an in line amplifier site ILA or a
.. _excel-links-sheet:
Links sheet
-----------
===========
Links sheet must contain sixteen columns::
<-- east cable from a to z --> <-- west from z to -->
<-- east cable from a to z --> <-- west from z to a -->
NodeA ; NodeZ ; Distance km ; Fiber type ; Lineic att ; Con_in ; Con_out ; PMD ; Cable Id ; Distance km ; Fiber type ; Lineic att ; Con_in ; Con_out ; PMD ; Cable Id
Links sheets MUST contain all links between nodes defined in Nodes sheet.
`Links` sheet MUST contain all links between nodes defined in Nodes sheet.
Each line represents a 'bidir link' between two nodes. The two directions are represented on a single line with "east cable from a to z" fields and "west from z to a" fields. Values for 'a to z' may be different from values from 'z to a'.
Since both direction of a bidir 'a-z' link are described on the same line (east and west), 'z to a' direction MUST NOT be repeated in a different line. If repeated, it will generate another parrallel bidir link between the same end nodes.
@@ -85,43 +87,42 @@ and a fiber span from node3 to node6::
- If filled it MUST contain numbers. If empty it is replaced by a default "80" km value.
- If value is below 150 km, it is considered as a single (bidirectional) fiber span.
- If value is over 150 km the `gnpy-transmission-example`` program will automatically suppose that intermediate span description are required and will generate fiber spans elements with "_1","_2", ... trailing strings which are not visible in the json output. The reason for the splitting is that current edfa usually do not support large span loss. The current assumption is that links larger than 150km will require intermediate amplification. This value will be revisited when Raman amplification is added”
- If value is over 150 km or if the loss is greater than 28 dB, the autodesign program
will automatically split the span with "_1","_2", ... trailing strings in names.
Splitting threshold can be tuned in ["Span"]["max_length"] and ["Span"]["max_loss"] in
equipment library.
- **Fiber type** is not mandatory.
If filled it must contain types listed in `eqpt_config.json <gnpy/example-data/eqpt_config.json>`_ in "Fiber" list "type_variety".
If not filled it takes "SSMF" as default value.
- **Lineic att** is not mandatory.
- **Lineic att** is not mandatory.
It is the lineic attenuation expressed in dB/km.
If filled it must contain positive numbers.
If not filled it takes "0.2" dB/km value
- *Con_in*, *Con_out* are not mandatory.
- **Con_in**, **Con_out** are not mandatory.
They are the connector loss in dB at ingress and egress of the fiber spans.
If filled they must contain positive numbers.
If not filled they take "0.5" dB default value.
- *PMD* is not mandatory and and is not used yet.
- **PMD** is not mandatory.
It is the PMD value of the link in ps.
If filled they must contain positive numbers.
If not filled, it takes "0.1" ps value.
- *Cable Id* is not mandatory.
- **Cable Id** is not mandatory.
If filled they must contain strings with the same constraint as "City" names. Its value is used to differenate links having the same end points. In this case different Id should be used. Cable Ids are not meant to be unique in general.
(in progress)
.. _excel-equipment-sheet:
Eqpt sheet
----------
==========
The equipment sheet (named "Eqpt") is optional.
If provided, it specifies types of boosters and preamplifiers for all ROADM degrees of all ROADM nodes, and for all ILA nodes.
@@ -176,7 +177,7 @@ This generates a text file meshTopologyExampleV2_eqt_sheet.txt whose content ca
- **Node Z** is mandatory. It is the egress direction from the *Node A* site. Multiple Links between the same Node A and NodeZ is not supported.
- **amp type** is not mandatory.
If filled it must contain types listed in `eqpt_config.json <gnpy/example-data/eqpt_config.json>`_ in "Edfa" list "type_variety".
If filled it must contain types listed in the equipment librairie like in the example `eqpt_config.json <gnpy/example-data/eqpt_config.json>`_ in "Edfa" list "type_variety".
If not filled it takes "std_medium_gain" as default value.
If filled with fused, a fused element with 0.0 dB loss will be placed instead of an amplifier. This might be used to avoid booster amplifier on a ROADM direction.
@@ -184,22 +185,57 @@ This generates a text file meshTopologyExampleV2_eqt_sheet.txt whose content ca
If not filled, it will be determined with design rules in the convert.py file.
If filled, it must contain positive numbers.
- *att_in* and *att_out* are not mandatory and are not used yet. They are the value of the attenuator at input and output of amplifier (in dB).
- **att_in** and **att_out** are not mandatory. They are the value of the attenuator at input and output of amplifier (in dB).
If filled they must contain positive numbers.
- **tilt**, in dB, is not mandatory. It is the target gain tilt over the full amplfifier bandwidth and is defined with regard to wavelength, i.e. negative tilt means lower gain
for higher wavelengths (lower frequencies). If not filled, the default value is 0.
- **delta_p**, in dBm, is not mandatory. If filled it is used to set the output target power per channel at the output of the amplifier, if power_mode is True. The output power is then set to power_dbm + delta_power.
- **delta_p**, in dB, is not mandatory. If filled it is used to set the output target power per channel at the output of the amplifier, if power_mode is True. The output power is then set to power_dbm + delta_power.
# to be completed #
.. _excel-roadms-sheet:
Roadms sheet
============
The ROADM sheet (named "Roadms") is optional.
If provided, it can be used to specify:
- per channel power target on a specific ROADM degree (*per_degree_pch_out_db*),
- ROADM type variety,
- impairment ID (identifier) on a particular ROADM path (from degree - to degree).
This sheet contains six columns:
Node A ; Node Z ; per degree target power (dBm) ; type_variety ; from degrees ; from degree to degree impairment id
- **Node A** is mandatory. Name of the ROADM node (as listed in Nodes sheet).
Must be a 'ROADM' (Type attribute in Node sheet), its number of occurence may be equal to its degree.
- **Node Z** is mandatory. Egress direction from the *Node A* ROADM site. Multiple Links between the same Node A
and NodeZ is not supported.
- **per degree target power (dBm)** (optional).
If filled it must contain a value in dBm corresponding to :ref:`per_degree_pch_out_db<roadm_json_instance>` on the **Node Z** degree.
Defaults to equipment library value if not filled.
- **type_variety** (optional). Must be the same for all ROADM entries if filled,
and defined in the :ref:`equipment library<roadm>`. Defaults to 'default' if not filled.
- **from degrees** (optional): List of Node names separated by ' | '. Names must be present in Node sheet.
Together with Node Z, they define a list of internal path in ROADM for which the impairment ID applies
- **from degree to degree impairment id** (optional):List of impairment IDs separated by ' | '. Must be filled
if **from degrees** is defined.
The impairment ID must be defined in the equipment library and be of "express" type.
(in progress)
.. _excel-service-sheet:
Service sheet
-------------
=============
Service sheet is optional. It lists the services for which path and feasibility must be computed with ``gnpy-path-request``.
@@ -213,7 +249,7 @@ Service sheet must contain 11 columns::
- **Destination** is mandatory. It is the name of the destination node (as listed in Nodes sheet). Source MUST be a ROADM node. (TODO: relax this and accept trx entries)
- **TRX type** is mandatory. They are the variety type and selected mode of the transceiver to be used for the propagation simulation. These modes MUST be defined in the equipment library. The format of the mode is used as the name of the mode. (TODO: maybe add another mode id on Transceiver library ?). In particular the mode selection defines the channel baudrate to be used for the propagation simulation.
- **TRX type** is mandatory. It is the variety type of the transceiver to be used for the propagation simulation. These modes MUST be defined in the equipment library. The format of the mode is used as the name of the mode. (TODO: maybe add another mode id on Transceiver library ?). In particular the mode selection defines the channel baudrate to be used for the propagation simulation.
- **mode** is optional. If not specified, the program will search for the mode of the defined transponder with the highest baudrate fitting within the spacing value.

View File

@@ -1,7 +1,8 @@
.. _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>`.
@@ -11,7 +12,7 @@ This chapter discusses option for modeling performance of :ref:`EDFA amplifiers<
.. _extending-edfa:
EDFAs
-----
=====
An accurate description of the :abbr:`EDFA (Erbium-Doped Fiber Amplifier)` and especially its noise characteristics is required.
GNPy describes this property in terms of the **Noise Figure (NF)** of an amplifier model as a function of its operating point.
@@ -20,7 +21,7 @@ GNPy supports several different :ref:`noise models<concepts-nf-model>`, and vend
.. _ext-nf-model-polynomial-NF:
Polynomial NF
*************
-------------
This model computes the NF as a function of the difference between the optimal gain and the current gain.
The NF is expressed as a third-degree polynomial:
@@ -43,7 +44,7 @@ In that case, use:
.. _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.
@@ -55,7 +56,7 @@ The amplifier performance is evaluated via its incremental OSNR, which is a func
.. _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.
@@ -70,7 +71,7 @@ GNPy emulates this specification via two special NF models:
.. _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.
@@ -80,7 +81,7 @@ The worst (maximal) NF applies when the EDFA operates at the minimal gain.
.. _ext-nf-model-dual-stage-amplifier:
Dual-stage
**********
----------
Dual-stage amplifier combines two distinct amplifiers.
Vendors which provide an accurate description of their preamp and booster stages separately can use the dual-stage model for an aggregate description of the whole amplifier.
@@ -88,7 +89,7 @@ Vendors which provide an accurate description of their preamp and booster stages
.. _ext-nf-model-advanced:
Advanced Specification
**********************
----------------------
The amplifier performance can be further described in terms of gain ripple, NF ripple, and the dynamic gain tilt.
When provided, the amplifier characteristic is fine-tuned as a function of carrier frequency. Note that in this advanced
@@ -97,7 +98,7 @@ specification tilt is defined vs frequency while tilt_target specified in EDFA i
.. _extending-raman:
Raman Amplifiers
----------------
================
An accurate simulation of Raman amplification requires knowledge of:
@@ -113,7 +114,7 @@ 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)`.
@@ -152,7 +153,7 @@ GNPy does not directly track the FEC performance, so the type of chosen FEC is l
.. _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:

View File

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

View File

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

View File

@@ -1,5 +1,6 @@
************************************
GNPy: Optical Route Planning Library
=====================================================================
************************************
`GNPy <http://github.com/telecominfraproject/gnpy>`_ is an open-source,
community-developed library for building route planning and optimization tools
@@ -7,20 +8,27 @@ in real-world mesh optical networks. It is based on the Gaussian Noise Model.
.. toctree::
:maxdepth: 4
:caption: Contents
intro
intro
concepts
install
cli_options
amplifier_models_description
json
json_instance_examples
excel
extending
about-project
model
gnpy-api
release-notes
publications
genindex
modindex
Indices and tables
==================
------------------
* :ref:`genindex`
* :ref:`modindex`

View File

@@ -1,5 +1,6 @@
***************
Installing GNPy
---------------
***************
There are several methods on how to obtain GNPy.
The easiest option for a non-developer is probably going via our :ref:`Docker images<install-docker>`.
@@ -9,7 +10,7 @@ Note that this needs a :ref:`working installation of Python<install-python>`, fo
.. _install-docker:
Using prebuilt Docker images
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
============================
Our `Docker images <https://hub.docker.com/r/telecominfraproject/oopt-gnpy>`_ contain everything needed to run all examples from this guide.
Docker transparently fetches the image over the network upon first use.
@@ -35,7 +36,7 @@ Remove that directory if you want to start from scratch.
.. _install-python:
Using Python on your computer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
=============================
**Note**: `gnpy` supports Python 3 only. Python 2 is not supported.
`gnpy` requires Python ≥3.8
@@ -89,7 +90,7 @@ exact version of Python you are using.
.. _install-pip:
Installing the Python package
*****************************
-----------------------------
From within your Anaconda Python 3 environment, you can clone the master branch
of the `gnpy` repo and install it with:

View File

@@ -1,7 +1,8 @@
.. _intro:
************
Introduction
============
************
``gnpy`` is a library for building route planning and optimization tools.
@@ -9,8 +10,9 @@ 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
optimization for your organization, please contact project maintainers
esther Le Rouzic <esther.lerouzic@orange.com>, Andrea D'Amico <adamico@nec-labs.com>.
gnpy is looking for users with
specific, delineated use cases to drive requirements for future
development.*
@@ -23,18 +25,18 @@ or to run a planning script to check SNR of several services:
:alt: Running a simple simulation example
By default, the gnpy-transmission-example script operates on a single span network defined in
`gnpy/example-data/edfa_example_network.json <../gnpy/example-data/edfa_example_network.json>`_
`gnpy/example-data/edfa_example_network.json <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/edfa_example_network.json>`_
You can specify a different network at the command line as follows. For
example, to use the CORONET Global network defined in
`gnpy/example-data/CORONET_Global_Topology.json <../gnpy/example-data/CORONET_Global_Topology.json>`_:
`gnpy/example-data/CORONET_Global_Topology.json <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/CORONET_Global_Topology.json>`_:
.. code-block:: shell-session
$ gnpy-transmission-example $(gnpy-example-data)/CORONET_Global_Topology.json
It is also possible to use an Excel file input (for example
`gnpy/example-data/CORONET_Global_Topology.xls <../gnpy/example-data/CORONET_Global_Topology.xls>`_).
`gnpy/example-data/CORONET_Global_Topology.xls <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/CORONET_Global_Topology.xls>`_).
The Excel file will be processed into a JSON file with the same prefix.
Further details about the Excel data structure are available `in the documentation <excel.rst>`__.
@@ -55,7 +57,7 @@ interference noise.
.. |Pnli| replace:: P\ :sub:`nli`
Further Instructions for Use
----------------------------
============================
Simulations are driven by a set of `JSON <json.rst>`__ or `XLS <excel.rst>`__ files.
@@ -72,8 +74,8 @@ An experimental support for Raman amplification is available:
$(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>`_.
Configuration of Raman pumps (their frequencies, power and pumping direction) is done via the `RamanFiber element in the network topology <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/raman_edfa_example_network.json>`_.
General numeric parameters for simulation control are provided in the `gnpy/example-data/sim_params.json <https://github.com/Telecominfraproject/oopt-gnpy/blob/master/gnpy/example-data/sim_params.json>`_.
Use ``gnpy-path-request`` to request several paths at once:

View File

@@ -11,15 +11,17 @@ 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).
This file defines the equipment libraries that can be customized (Amplifiers, ROADMs, fibers, and transceivers).
It also defines the simulation parameters (spans, ROADMs, and the spectral information to transmit.)
It also defines the simulation parameters (spans and the spectral information to transmit.)
Examples of instances are commented here :ref:`json instances examples<json-instance-examples>`.
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:
can be added and existing ones removed. Various 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``.
@@ -35,8 +37,12 @@ can be added and existing ones removed. Three different noise models are availab
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.
6. ``'type_def': 'multi_band'`` defines an amplifier type corresponding to an amplification site composed of multiple amplifier elements, where each amplifies a different band of the spectrum.
The ``amplifiers`` list contains the list of single-band amplifier type varieties that can compose such multiband
amplifiers. Several options can be listed for the same spectrum band. Only one can be selected
for the actual :ref:`Multiband_amplifier<multiband_amps>` element.
For all amplifier models:
For all single band amplifier models:
+------------------------+-----------+-----------------------------------------+
| field | type | description |
@@ -55,6 +61,36 @@ For all amplifier models:
| | | be used as a manual input (from JSON or |
| | | Excel template topology files.) |
+------------------------+-----------+-----------------------------------------+
| ``f_min`` | (number) | Optional. In :math:`Hz`. Minimum and |
| and ``f_max`` | | maximum frequency range for the |
| | | amplifier. Signal must fit entirely |
| | | within this range (center frequency and |
| | | spectrum width). |
| | | Default is 191.275e-12 Hz and |
| | | 196.125e-12. |
+------------------------+-----------+-----------------------------------------+
Default values are defined for the frequency range for:
- noise figure ripple
- gain ripple
- dynamic gain tilt
Users can introduce custom values using ``default_config_from_json`` which should be populated with a file name containing the desired parameters.
For multi_band amplifier models:
+------------------------+-----------+-----------------------------------------+
| field | type | description |
+========================+===========+=========================================+
| ``type_variety`` | (string) | A unique name to ID the amplifier in the|
| | | JSON template topology input file. |
+------------------------+-----------+-----------------------------------------+
| ``allowed_for_design`` | (boolean) | 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.) |
+------------------------+-----------+-----------------------------------------+
Fiber
~~~~~
@@ -193,6 +229,9 @@ The modes are defined as follows:
+----------------------------+-----------+-----------------------------------------+
| ``bit_rate`` | (number) | in bit/s |
+----------------------------+-----------+-----------------------------------------+
| ``min_spacing`` | (number) | in Hz. Min required slot size for this |
| | | mode. |
+----------------------------+-----------+-----------------------------------------+
| ``roll_off`` | (number) | Pure number between 0 and 1. TX signal |
| | | roll-off shape. Used by Raman-aware |
| | | simulation code. |
@@ -447,14 +486,14 @@ Here is an example:
"uid": "roadm SITE1",
"type": "Roadm",
"type_variety": "detailed_impairments",
"params": {
"per_degree_impairments": [
{
"from_degree": "trx SITE1",
"to_degree": "east edfa in SITE1 to ILA1",
"impairment_id": 1
}]
}
"params": {
"per_degree_impairments": [
{
"from_degree": "trx SITE1",
"to_degree": "east edfa in SITE1 to ILA1",
"impairment_id": 1
}]
}
}
It is not permitted to use a roadm-path-impairment-id for the wrong roadm path type (add impairment only for add path).
@@ -462,6 +501,8 @@ If nothing is stated for impairments on roadm-paths, the program identifies the
On the previous example, all «implicit» express roadm-path are assigned roadm-path-impairment-id = 0
.. _sim-params:
Global parameters
-----------------
@@ -492,6 +533,19 @@ See ``delta_power_range_db`` for more explaination.
| | | mandatory when Raman amplification is |
| | | included in the simulation |
+---------------------------------------------+-----------+---------------------------------------------+
| ``raman_params.method`` | (string) | Model used for Raman evaluation. Valid |
| | | choices are ``perturbative`` (see |
| | | `arXiv:2304.11756 |
| | | <https://arxiv.org/abs/2304.11756>`_) and |
| | | ``numerical``, the GNPy legacy first order |
| | | derivative numerical solution. |
+---------------------------------------------+-----------+---------------------------------------------+
|``raman_params.order`` | | Order of the perturbative expansion. |
| | | For C- and C+L-band transmission scenarios |
| | | the second order provides high accuracy |
| | | considering common values of fiber input |
| | | power. (Default is 2) |
+---------------------------------------------+-----------+---------------------------------------------+
| ``raman_params.result_spatial_resolution`` | (number) | Spatial resolution of the output |
| | | Raman profile along the entire fiber span. |
| | | This affects the accuracy and the |
@@ -503,11 +557,18 @@ See ``delta_power_range_db`` for more explaination.
| | | 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 |
| ``raman_params.solver_spatial_resolution`` | (number) | When using the ``perturbative`` method, |
| | | the step for the spatial integration does |
| | | not affect the first order. Therefore, a |
| | | large step can be used when no |
| | | counter-propagating Raman amplification is |
| | | present; a suggested value is 10e3 m. |
| | | In presence of counter-propagating Raman |
| | | amplification or when using the |
| | | ``numerical`` method the following remains |
| | | valid. |
| | | The spatial step for the iterative solution |
| | | affects the accuracy and the |
| | | computational time of the evaluated |
| | | Raman profile: |
| | | smaller the spatial resolution higher both |
@@ -523,6 +584,10 @@ See ``delta_power_range_db`` for more explaination.
| | | ``ggn_spectrally_separated`` (see eq. 21 |
| | | from `arXiv:1710.02225 |
| | | <https://arxiv.org/abs/1710.02225>`_). |
| | | ``ggn_approx`` (see eq. 24-25 |
| | | from `jlt:9741324 |
| | | <https://eeexplore.ieee.org/document/ |
| | | 9741324>`_). |
+---------------------------------------------+-----------+---------------------------------------------+
| ``dispersion_tolerance`` | (number) | Optional. Pure number. Tuning parameter for |
| | | ggn model solution. Default value is 1. |
@@ -669,6 +734,30 @@ Span configuration is not a list (which may change in later releases) and the us
| | | value is input in the topology for a |
| | | given Fiber. |
+-------------------------------------+-----------+---------------------------------------------+
| ``span_loss_ref`` | (number) | (optional) in dB. For autodesign. |
| | | Reference span loss value in dB, used to |
| | | calculate all delta_p deviations during |
| | | network autodesign. The default value is |
| | | 20dB. |
+-------------------------------------+-----------+---------------------------------------------+
| ``power_slope`` | (number) | (optional) Pure number. For autodesign. |
| | | Ratio used to compute all delta_p |
| | | deviations during network autodesign. |
| | | The default value is 0.3. |
+-------------------------------------+-----------+---------------------------------------------+
| ``voa_margin`` | (float) | (optional) in dB. For autodesign. |
| | | Margin to subtract from the calculated VOA |
| | | during gain optimisation process, to |
| | | prevent maximum attenuation. |
| | | This creates a safety buffer. |
| | | Default value is 1dB. |
+-------------------------------------+-----------+---------------------------------------------+
| ``voa_step`` | (float) | (optional) in dB. For autodesign. |
| | | Step size used for rounding the VOA value. |
| | | Ensures VOA adjustments align with hardware |
| | | resolution. |
| | | Default value is 0.5dB. |
+-------------------------------------+-----------+---------------------------------------------+
.. code-block:: json
@@ -724,74 +813,91 @@ It also defines the channels to be propagated for the gnpy-transmission-example
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:
+----------------------+-----------+-------------------------------------------+
| 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}`. |
+----------------------+-----------+-------------------------------------------+
| ``baud_rate`` | (number) | In Hz. Simulated baud rate. |
+----------------------+-----------+-------------------------------------------+
| ``spacing`` | (number) | In Hz. Carrier spacing. |
+----------------------+-----------+-------------------------------------------+
| ``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. |
+----------------------+-----------+-------------------------------------------+
| ``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 |
| | | Spans/delta_power_range_db. For example, |
| | | if delta_power_range_db = `[0,0,0]`, the |
| | | same power=power_dbm is launched in every |
| | | spans. The network design is performed |
| | | 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. |
+----------------------+-----------+-------------------------------------------+
| ``tx_power_dbm`` | (number) | In dBm. Optional. Power out from |
| | | transceiver. Default = power_dbm |
+----------------------+-----------+-------------------------------------------+
| ``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 + 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. |
+----------------------+-----------+-------------------------------------------+
+-------------------------------------+-----------+-------------------------------------------+
| field | type | description |
+=====================================+===========+===========================================+
| ``type_variety`` | (string) | Optional. Default: ``default`` |
| | | A unique name to ID the band for |
| | | propagation or design. |
+-------------------------------------+-----------+-------------------------------------------+
| ``f_min``, ``f_max`` | (number) | In Hz. Define spectrum boundaries. Note |
| | | 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}`. |
+-------------------------------------+-----------+-------------------------------------------+
| ``baud_rate`` | (number) | In Hz. Simulated baud rate. |
+-------------------------------------+-----------+-------------------------------------------+
| ``spacing`` | (number) | In Hz. Carrier spacing. |
+-------------------------------------+-----------+-------------------------------------------+
| ``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. |
+-------------------------------------+-----------+-------------------------------------------+
| ``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 |
| | | Spans/delta_power_range_db. For example, |
| | | if delta_power_range_db = `[0,0,0]`, the |
| | | same power=power_dbm is launched in every |
| | | spans. The network design is performed |
| | | 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. |
+-------------------------------------+-----------+-------------------------------------------+
| ``tx_power_dbm`` | (number) | In dBm. Optional. Power out from |
| | | transceiver. Default = power_dbm |
+-------------------------------------+-----------+-------------------------------------------+
| ``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 + 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. |
+-------------------------------------+-----------+-------------------------------------------+
| ``use_si_channel_count_for_design`` | (boolean) | Optional. If True, the design uses the SI |
| | | definition for channel count computation |
| | | instead of the amplifier bandwidth. |
| | | This option enable to reproduce legacy |
| | | behaviour. |
+-------------------------------------+-----------+-------------------------------------------+
It is possible to define a set of bands in the SI block. In this case, type_variety must be used.
Each set defines a reference channel used for design functions and autodesign processes.
If no spectrum is defined (--spectrum or --services), then the same type of reference channel is
also used for simulation.
.. _mixed-rate:
@@ -843,7 +949,7 @@ For example this example:
.. code-block:: json
{
"SI":[
"spectrum":[
{
"f_min": 191.4e12,
"f_max":193.1e12,
@@ -854,7 +960,7 @@ For example this example:
},
{
"f_min": 193.1625e12,
"f_max":195e12,
"f_max": 195e12,
"baud_rate": 64e9,
"delta_pdb": 3,
"slot_width": 75e9,
@@ -1100,6 +1206,8 @@ the maximum achievable total power.
The exact layout used by simulation can be retrieved thanks to --save-network option.
.. _operational_field:
+----------------------+-----------+--------------------------------------------------+
| field | type | description |
+======================+===========+==================================================+
@@ -1155,9 +1263,68 @@ The exact layout used by simulation can be retrieved thanks to --save-network op
}
}
.. _multiband_amps:
Multiband_amplifier attributes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+----------------------+-----------+--------------------------------------------------+
| field | type | description |
+======================+===========+==================================================+
| ``type`` | (string) | Mandatory: ``Multiband_amplifier`` |
+----------------------+-----------+--------------------------------------------------+
| ``type_variety`` | (string) | Optional, value must be listed in the library |
| | | to be a valid type. If not defined, autodesign |
| | | will pick one in the library among the |
| | | ``allowed_for_design``. |
+----------------------+-----------+--------------------------------------------------+
| ``amplifiers`` | (list of | Optional, configuration settings of the |
| | dict) | amplifiers composing the multiband amplifier. |
| | | Single band amplifier can be set with the |
| | | parameters of tables: |
| | | :ref:`operational_field<operational_field>`: |
+----------------------+-----------+--------------------------------------------------+
Example of Multiband_amplifier element setting:
.. code-block:: json
{
"uid": "east edfa in Site_A to Site_B",
"type": "Multiband_amplifier",
"type_variety": "std_medium_gain_multiband",
"amplifiers": [{
"type_variety": "std_medium_gain_C",
"operational": {
"gain_target": 22.55,
"delta_p": 0.9,
"out_voa": 3.0,
"tilt_target": 0.0
}
}, {
"type_variety": "std_medium_gain_L",
"operational": {
"gain_target": 21,
"delta_p": 3.0,
"out_voa": 3.0,
"tilt_target": 0.0
}
}
]
}
The frequency band of the element is the concatenation of the bands of each individual amplifier contained in
the Multiband_amplifier element. Only carriers within these bands are propagated through the Multiband_amplifier
element. If the user defines a spectrum larger than these bands, carriers that do not match the bands will be
filtered out. The user can define the bandwidth of the amplifiers in the library. f_min and f_max represent the
bandwidth of the amplifier (the entire channel must fit). The individual amplifier type_variety must be part of the
allowed ``amplifiers`` list defined in the library.
Roadm
~~~~~
.. _roadm_json_instance:
+----------------------------------------+-----------+----------------------------------------------------+
| field | type | description |
+========================================+===========+====================================================+
@@ -1186,32 +1353,69 @@ Roadm
| | dict) | defined, it overrides the general values defined |
| | | by type_variety. |
+----------------------------------------+-----------+----------------------------------------------------+
| ``design_bands`` | (list of | Optional. List of bands expressed as dictionnary, |
| | dict) | e.g. {"f_min": 191.3e12, "f_max": 195.1e12} |
| | | To be considered for autodesign on all degrees of |
| | | the ROADM, if nothing is defined on the degrees. |
+----------------------------------------+-----------+----------------------------------------------------+
| ``per_degree_design_bands`` | (dict of | Optional. If defined, it overrides ROADM's general |
| | string, | design_bands, on the degree identified with the |
| | list of | key string. Value is a list of bands defined by |
| | dict) | their frequency bounds ``f_min`` and ``f_max`` |
| | | expressed in THz. |
+----------------------------------------+-----------+----------------------------------------------------+
Definition example:
.. code-block:: json
.. code-block:: json
{
"uid": "roadm SITE1",
"type": "Roadm",
"type_variety": "detailed_impairments",
"params": {
"per_degree_impairments": [
{
"from_degree": "trx SITE1",
"to_degree": "east edfa in SITE1 to ILA1",
"impairment_id": 1
}],
"per_degree_pch_out_db": {
"params": {
"per_degree_impairments": [
{
"from_degree": "trx SITE1",
"to_degree": "east edfa in SITE1 to ILA1",
"impairment_id": 1
}],
"per_degree_pch_out_db": {
"east edfa in SITE1 to ILA1": -13.5
}
}
}
}
}
In this example, all «implicit» express roadm-path are assigned as roadm-path-impairment-id = 0, and the target power is
set according to the value defined in the library except for the direction heading to "east edfa in SITE1 to ILA1", where
constant power equalization is used to reach -13.5 dBm target power.
.. code-block:: json
{
"uid": "roadm SITE1",
"type": "Roadm",
"params": {
"per_degree_design_bands": {
"east edfa in SITE1 to ILA1": [
{"f_min": 191.3e12, "f_max": 196.0e12},
{"f_min": 187.0e12, "f_max": 190.0e12}
]
}
}
}
In this example the OMS starting from east edfa in SITE1 to ILA1 is defined as a multiband OMS. This means that
if there is no setting in all or some of the amplifiers in the OMS, the autodesign function will select amplifiers
from those that have ``multi_band`` ``type_def`` amplifiers.
The default ``design_bands`` is inferred from the :ref:`SI<spectral_info>` block.
Note that ``design_bands`` and ``type_variety`` amplifiers must be consistent:
- you cannot mix single band and multiband amplifiers on the same OMS;
- the frequency range of the amplifiers must include ``design_bands``.
Fused
~~~~~
@@ -1221,7 +1425,7 @@ A fused element connected to the egress of a ROADM will disable the automatic bo
Fused ``params`` only contains a ``loss`` value in dB.
.. code-block:: json
.. code-block:: json
"params": {
"loss": 2

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

25
docs/publications.rst Normal file
View File

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

View File

@@ -1,11 +1,269 @@
.. _release-notes:
******************
Release change log
==================
******************
Each release introduces some changes and new features.
(prepare text for next release)
v2.13
=====
**Environment**
The windows-2019 environment is no more supported.
**Yang Conversion Utilities**
This release introduces new conversion utilities to facilitate conversion between YANG and legacy formats,
ensuring full compatibility with GNPy. The "legacy" format also benefit from the YANG validation for
a stricter verification of input files.
Console Script for Yang Conversion: Added a new command-line script to perform Yang format conversions easily.
**Design Enhancements**
This release adds the ability to parametrize power target calculations, allowing customization of reference
span loss and deviation ratios. It implements the use of a reference channel per OMS (Optical Multiplex Section)
instead of total power for design calculations, improving accuracy and performance.
It also includes spacing information in design band data to assist in maximum power computation for EDFA
targets compution during autodesign.
**Excel handling**
XLSX files are now read with openpyxl library (while XLS files are still read with xlrd library). Latest release of
xlrd is supported, which solves compatibility issues with anaconda install.
v2.12
=====
**Important Changes:**
The default values for EDFA configuration, including frequency range, gain ripple, noise figure ripple, or dynamic gain tilt
are now hardcoded in parameters.py and are no longer read from the default_edfa_config.json file (the file has been removed).
However, users can define their own custom parameters using the default_config_from_json variable, which should be populated with a file name containing the desired parameter description. This applies to both variable_gain and fixed_gain amplifier types.
This change streamlines the configuration process but requires users to explicitly set parameters through the new
model if the default values do not suit their needs via the --extra-config option.
v2.11.1
-------
**Environment**
The macOS-12 environment is no more supported.
**per degree impairment enabled in xls input**
This release now read per degre roadm-path impairment from roadm sheet
Several optional columns are added: 'type_variety' and 'from degrees'
and 'from degree to degree impairment id'.
- 'from degrees' can contain a list of degrees separated with ' | ', then the
'from degree to degree impairment id' must contain a list of ids of the same
length.
Impairment ids are expected to be defined in the ROADM equipment library and
from degree must be among the previous node from this ROADM.
**optimizing computation speed**
The computation of path is skipped if the provided include nodes provides
a complete explicit path (speeds simulation time).
v2.11
=====
**New feature**
A new type_def for amplifiers has been introduced: multi_band. This allows the definition of a
multiband amplifier site composed of several amplifiers per band (a typical application is C+L transmission). The
release also includes autodesign for links (Optical Multiplex Section, OMS) composed of multi_band amplifiers.
Multi_band autodesign includes basic tilt and tilt_target calculation when the Raman flag is enabled with the
--sim-params option. The spectrum is demultiplexed before propagation in the amplifier and multiplexed in the output
fiber at the amplifier output.
In the library:
.. code-block:: json
{
"type_variety": "std_medium_gain_C",
"f_min": 191.225e12,
"f_max": 196.125e12,
"type_def": "variable_gain",
"gain_flatmax": 26,
"gain_min": 15,
"p_max": 21,
"nf_min": 6,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": false
},
{
"type_variety": "std_medium_gain_L",
"f_min": 186.5e12,
"f_max": 190.1e12,
"type_def": "variable_gain",
"gain_flatmax": 26,
"gain_min": 15,
"p_max": 21,
"nf_min": 6,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_medium_gain_multiband",
"type_def": "multi_band",
"amplifiers": [
"std_medium_gain_C",
"std_medium_gain_L"
],
"allowed_for_design": false
},
In the network topology:
.. code-block:: json
{
"uid": "east edfa in Site_A to Site_B",
"type": "Multiband_amplifier",
"type_variety": "std_medium_gain_multiband",
"amplifiers": [{
"type_variety": "std_medium_gain_C",
"operational": {
"gain_target": 22.55,
"delta_p": 0.9,
"out_voa": 3.0,
"tilt_target": 0.0
}
}, {
"type_variety": "std_medium_gain_L",
"operational": {
"gain_target": 21,
"delta_p": 3.0,
"out_voa": 3.0,
"tilt_target": 0.0
}
}
]
}
**Network design**
Optionally, users can define a design target per OMS (single or multi-band), with specific frequency ranges.
Default design bands are defined in the SI.
.. code-block:: json
{
"uid": "roadm Site_A",
"type": "Roadm",
"params": {
"target_pch_out_db": -20,
"design_bands": [{"f_min": 191.3e12, "f_max": 195.1e12}]
}
}
It is possible to define a set of bands in the SI block instead of a single Spectrum Information.
In this case type_variety must be used.
Each set defines a reference channel used for design functions and autodesign.
The default design settings for the path-request-run script have been modified.
Now, design is performed once for the reference channel defined in the SI block of the eqpt_config,
and requests are propagated based on this design.
The --redesign-per-request option can be used to restore previous behaviour
(design using request channel types).
The autodesign function has been updated to insert multiband booster, preamp or inline amplifiers based on the OMS
nature. If nothing is stated (no amplifier defined in the OMS, no design_bands attribute in the ROADM), then
it uses single band Edfas.
**Propagation**
Only carriers within the amplifier bandwidth are propagated, improving system coherence. This more rigorous checking
of the spectrum to be propagated and the amplifier bandwidth may lead to changes in the total number of channels
compared to previous releases. The range can be adjusted by changing the values of ``f_min`` and ``f_max``
in the amplifier library.
``f_min`` and ``f_max`` represent the boundary frequencies of the amplification bandwidth (the entire channel must fit
within this range).
In the example below, a signal center frequency of 190.05THz with a 50GHz width cannot fit within the amplifier band.
Note that this has a different meaning in the SI or Transceiver blocks, where ``f_min`` and ``f_max`` refers to the
minimum / maximum values of the carrier center frequency.
.. code-block:: json
{
"type_variety": "std_booster_L",
"f_min": 186.55e12,
"f_max": 190.05e12,
"type_def": "fixed_gain",
"gain_flatmax": 21,
"gain_min": 20,
"p_max": 21,
"nf0": 5,
"allowed_for_design": false
}
**Display**
The CLI output for the transmission_main_example now displays the channels used for design and simulation,
as well as the tilt target of amplifiers.
.. code-block:: text
Reference used for design: (Input optical power reference in span = 0.00dBm,
spacing = 50.00GHz
nb_channels = 76)
Channels propagating: (Input optical power deviation in span = 0.00dB,
spacing = 50.00GHz,
transceiver output power = 0.00dBm,
nb_channels = 76)
The CLI output displays the settings of each amplifier:
.. code-block:: text
Multiband_amplifier east edfa in Site_A to Site_B
type_variety: std_medium_gain_multiband
type_variety: std_medium_gain_C type_variety: std_medium_gain_L
effective gain(dB): 20.90 effective gain(dB): 22.19
(before att_in and before output VOA) (before att_in and before output VOA)
tilt-target(dB) 0.00 tilt-target(dB) 0.00
noise figure (dB): 6.38 noise figure (dB): 6.19
(including att_in) (including att_in)
pad att_in (dB): 0.00 pad att_in (dB): 0.00
Power In (dBm): -1.08 Power In (dBm): -1.49
Power Out (dBm): 19.83 Power Out (dBm): 20.71
Delta_P (dB): 0.90 Delta_P (dB): 2.19
target pch (dBm): 0.90 target pch (dBm): 3.00
actual pch out (dBm): -2.09 actual pch out (dBm): -0.80
output VOA (dB): 3.00 output VOA (dB): 3.00
**New feature**
The preturbative Raman and the approximated GGN models are introduced for a faster evaluation of the Raman and
Kerr effects, respectively.
These implementation are intended to reduce the computational effort required by multiband transmission scenarios.
Both the novel models have been validated with exstensive simulations
(see `arXiv:2304.11756 <https://arxiv.org/abs/2304.11756>`_ for the new Raman model and
`jlt:9741324 <https://eeexplore.ieee.org/document/9741324>`_ for the new NLI model).
Additionally, they have been experimentally validated in a laboratory setup composed of commertial equipment
(see `icton:10648172 <https://eeexplore.ieee.org/document/10648172>`_).
v2.10
=====
ROADM impairments can be defined per degree and roadm-path type (add, drop or express).
Minimum loss when crossing a ROADM is no more 0 dB. It can be set per ROADM degree with roadm-path-impairments.
@@ -112,7 +370,7 @@ can now be set using a different parameter. It can be set as:
}
v2.9
----
====
The revision introduces a major refactor that separates design and propagation. Most of these changes have no impact
on the user experience, except the following ones:
@@ -157,7 +415,7 @@ contribution). Note that "actual pch out (dBm)" is the actual propagated total p
band definition at the output of the amplifier element, including noises and out VOA contribution.
v2.8
----
====
**Spectrum assignment**: requests can now support multiple slots.
The definition in service file supports multiple assignments (unchanged syntax):
@@ -225,15 +483,15 @@ involute manner to get a vanishing beta3 , and this was a mere artifact for NLI
beta2 and beta3, not for total dispersion accumulation). Now, the evaluation of beta2 and beta3 is performed explicitly
in the element.py module.
2. The effective area is provided as a scalar value evaluated at the Fiber reference frequency and properly scaled
1. The effective area is provided as a scalar value evaluated at the Fiber reference frequency and properly scaled
considering the Fiber refractive indices n1 and n2, and the core radius. These quantities are assumed to be fixed and
are hard coded in the parameters.py module. Essential change: The effective area is always scaled along the frequency.
3. The Raman gain coefficient is properly scaled considering the overlapping of fiber effective area values scaled at
1. The Raman gain coefficient is properly scaled considering the overlapping of fiber effective area values scaled at
the interacting frequencies. Essential change: In previous version the Raman gain coefficient depends only on
the frequency offset.
4. The nonlinear coefficient ``'gamma'`` is properly scaled considering the refractive index n2 and the scaling
1. The nonlinear coefficient ``'gamma'`` is properly scaled considering the refractive index n2 and the scaling
effective area. Essential change: As the effective area, the nonlinear coefficient is always scaled along the
frequency.
@@ -266,4 +524,4 @@ the deviation from the general equalisation strategy defined in ROADMs.
]
v2.7
----
====

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@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.core.ansi_escapes: A random subset of ANSI terminal escape codes for colored messages
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.core.ansi_escapes
======================

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@@ -1,14 +1,22 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.core.equipment: functionality for specifying equipment
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.core.equipment
===================
This module contains functionality for specifying equipment.
"""
from collections import defaultdict
from functools import reduce
from typing import List
from gnpy.core.exceptions import EquipmentConfigError
from gnpy.core.exceptions import EquipmentConfigError, ConfigurationError
def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=False):
@@ -80,3 +88,50 @@ def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=F
trx_params = {**default_trx_params}
return trx_params
def find_type_variety(amps: List[str], equipment: dict) -> List[str]:
"""Returns the multiband type_variety associated with a list of single band type_varieties
Args:
amps (List[str]): A list of single band type_varieties.
equipment (dict): A dictionary containing equipment information.
Returns:
str: an amplifier type variety
"""
listes = find_type_varieties(amps, equipment)
_found_type = list(reduce(lambda x, y: set(x) & set(y), listes))
# Given a list of single band amplifiers, find the multiband amplifier whose multi_band group
# matches. For example, if amps list contains ["a1_LBAND", "a2_CBAND"], with a1.multi_band = [a1_LBAND, a1_CBAND]
# and a2.multi_band = [a1_LBAND, a2_CBAND], then:
# possible_type_varieties = {"a1_LBAND": ["a1", "a2"], "a2_CBAND": ["a2"]}
# listes = [["a1", "a2"], ["a2"]]
# and _found_type = [a2]
if not _found_type:
msg = f'{amps} amps do not belong to the same amp type {listes}'
raise ConfigurationError(msg)
return _found_type
def find_type_varieties(amps: List[str], equipment: dict) -> List[List[str]]:
"""Returns the multiband list of type_varieties associated with a list of single band type_varieties
Args:
amps (List[str]): A list of single band type_varieties.
equipment (dict): A dictionary containing equipment information.
Returns:
List[List[str]]: A list of lists containing the multiband type_varieties
associated with each single band type_variety.
"""
possible_type_varieties = defaultdict(list)
for amp_name, amp in equipment['Edfa'].items():
if amp.multi_band is not None:
for elem in amp.multi_band:
# possible_type_varieties stores the list of multiband amp names that list this elem as
# a possible amplifier of the multiband group. For example, if "std_medium_gain_multiband"
# and "std_medium_gain_multiband_new" contain "std_medium_gain_C" in their "multi_band" list, then:
# possible_type_varieties["std_medium_gain_C"] =
# ["std_medium_gain_multiband", "std_medium_gain_multiband_new"]
possible_type_varieties[elem].append(amp_name)
return [possible_type_varieties[a] for a in amps]

View File

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

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.core.info: classes for modelling Spectral Information
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.core.info
==============
@@ -11,7 +16,7 @@ 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 typing import Union, List, Optional
from dataclasses import dataclass
from numpy import argsort, mean, array, append, ones, ceil, any, zeros, outer, full, ndarray, asarray
@@ -317,6 +322,56 @@ def create_input_spectral_information(f_min, f_max, roll_off, baud_rate, spacing
tx_osnr=tx_osnr, tx_power=tx_power, label=label)
def is_in_band(frequency: float, band: dict) -> bool:
"""band has {"f_min": value, "f_max": value} format
"""
if frequency >= band['f_min'] and frequency <= band['f_max']:
return True
return False
def demuxed_spectral_information(input_si: SpectralInformation, band: dict) -> Optional[SpectralInformation]:
"""extract a si based on band
"""
filtered_indices = [i for i, f in enumerate(input_si.frequency)
if is_in_band(f - input_si.slot_width[i] / 2, band)
and is_in_band(f + input_si.slot_width[i] / 2, band)]
if filtered_indices:
frequency = input_si.frequency[filtered_indices]
baud_rate = input_si.baud_rate[filtered_indices]
slot_width = input_si.slot_width[filtered_indices]
signal = input_si.signal[filtered_indices]
nli = input_si.nli[filtered_indices]
ase = input_si.ase[filtered_indices]
roll_off = input_si.roll_off[filtered_indices]
chromatic_dispersion = input_si.chromatic_dispersion[filtered_indices]
pmd = input_si.pmd[filtered_indices]
pdl = input_si.pdl[filtered_indices]
latency = input_si.latency[filtered_indices]
delta_pdb_per_channel = input_si.delta_pdb_per_channel[filtered_indices]
tx_osnr = input_si.tx_osnr[filtered_indices]
tx_power = input_si.tx_power[filtered_indices]
label = input_si.label[filtered_indices]
return SpectralInformation(frequency=frequency, baud_rate=baud_rate, slot_width=slot_width, signal=signal,
nli=nli, ase=ase, roll_off=roll_off, chromatic_dispersion=chromatic_dispersion,
pmd=pmd, pdl=pdl, latency=latency, delta_pdb_per_channel=delta_pdb_per_channel,
tx_osnr=tx_osnr, tx_power=tx_power, label=label)
return None
def muxed_spectral_information(input_si_list: List[SpectralInformation]) -> SpectralInformation:
"""return the assembled spectrum
"""
if input_si_list and len(input_si_list) > 1:
si = input_si_list[0] + muxed_spectral_information(input_si_list[1:])
return si
elif input_si_list and len(input_si_list) == 1:
return input_si_list[0]
else:
raise ValueError('liste vide')
def carriers_to_spectral_information(initial_spectrum: dict[float, Carrier],
power: float) -> SpectralInformation:
"""Initial spectrum is a dict with key = carrier frequency, and value a Carrier object.

File diff suppressed because it is too large Load Diff

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.core.parameters: parameters to configure standard network elements
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.core.parameters
====================
@@ -8,7 +13,8 @@ gnpy.core.parameters
This module contains all parameters to configure standard network elements.
"""
from collections import namedtuple
from copy import deepcopy
from dataclasses import dataclass
from scipy.constants import c, pi
from numpy import asarray, array, exp, sqrt, log, outer, ones, squeeze, append, flip, linspace, full
@@ -35,25 +41,32 @@ class PumpParams(Parameters):
class RamanParams(Parameters):
def __init__(self, flag=False, result_spatial_resolution=10e3, solver_spatial_resolution=50):
def __init__(self, flag=False, method='perturbative', order=2, result_spatial_resolution=10e3,
solver_spatial_resolution=10e3):
"""Simulation parameters used within the Raman Solver
:params flag: boolean for enabling/disable the evaluation of the Raman power profile in frequency and position
:params method: Raman solver method
:params order: solution order for perturbative method
:params result_spatial_resolution: spatial resolution of the evaluated Raman power profile
:params solver_spatial_resolution: spatial step for the iterative solution of the first order ode
"""
self.flag = flag
self.method = method
self.order = order
self.result_spatial_resolution = result_spatial_resolution # [m]
self.solver_spatial_resolution = solver_spatial_resolution # [m]
def to_json(self):
return {"flag": self.flag,
"method": self.method,
"order": self.order,
"result_spatial_resolution": self.result_spatial_resolution,
"solver_spatial_resolution": self.solver_spatial_resolution}
class NLIParams(Parameters):
def __init__(self, method='gn_model_analytic', dispersion_tolerance=1, phase_shift_tolerance=0.1,
def __init__(self, method='gn_model_analytic', dispersion_tolerance=4, phase_shift_tolerance=0.1,
computed_channels=None, computed_number_of_channels=None):
"""Simulation parameters used within the Nli Solver
@@ -117,6 +130,8 @@ class RoadmParams(Parameters):
except KeyError as e:
raise ParametersError(f'ROADM configurations must include {e}. Configuration: {kwargs}')
self.per_degree_impairments = kwargs.get('per_degree_impairments', [])
self.design_bands = kwargs.get('design_bands', [])
self.per_degree_design_bands = kwargs.get('per_degree_design_bands', {})
def get_roadm_path_impairments(self, path_impairments_list):
"""Get the ROADM list of profiles for impairments definition
@@ -134,7 +149,7 @@ class RoadmParams(Parameters):
for path_impairment in path_impairments_list:
index = path_impairment['roadm-path-impairments-id']
path_type = next(key for key in path_impairment if key in authorized_path_types.keys())
impairment_dict = dict({'path-type': authorized_path_types[path_type]}, **path_impairment[path_type][0])
impairment_dict = {'path-type': authorized_path_types[path_type], 'impairment': path_impairment[path_type]}
roadm_path_impairments[index] = RoadmImpairment(impairment_dict)
return roadm_path_impairments
@@ -155,26 +170,24 @@ class RoadmPath:
class RoadmImpairment:
"""Generic definition of impairments for express, add and drop"""
default_values = {
'roadm-pmd': None,
'roadm-cd': None,
'roadm-pdl': None,
'roadm-inband-crosstalk': None,
'roadm-maxloss': 0,
'roadm-osnr': None,
'roadm-pmax': None,
'roadm-noise-figure': None,
'minloss': None,
'typloss': None,
'pmin': None,
'ptyp': None
}
def __init__(self, params):
"""Records roadm internal paths and types"""
self.path_type = params.get('path-type')
self.pmd = params.get('roadm-pmd')
self.cd = params.get('roadm-cd')
self.pdl = params.get('roadm-pdl')
self.inband_crosstalk = params.get('roadm-inband-crosstalk')
self.maxloss = params.get('roadm-maxloss', 0)
if params.get('frequency-range') is not None:
self.fmin = params.get('frequency-range')['lower-frequency']
self.fmax = params.get('frequency-range')['upper-frequency']
else:
self.fmin, self.fmax = None, None
self.osnr = params.get('roadm-osnr', None)
self.pmax = params.get('roadm-pmax', None)
self.nf = params.get('roadm-noise-figure', None)
self.minloss = params.get('minloss', None)
self.typloss = params.get('typloss', None)
self.pmin = params.get('pmin', None)
self.ptyp = params.get('ptyp', None)
self.impairments = params['impairment']
class FusedParams(Parameters):
@@ -335,6 +348,7 @@ class FiberParams(Parameters):
# Polarization Mode Dispersion
self._pmd_coef = kwargs['pmd_coef'] # s/sqrt(m)
self._pmd_coef_defined = kwargs.get('pmd_coef_defined', kwargs['pmd_coef'] is True)
# Loss Coefficient
if isinstance(kwargs['loss_coef'], dict):
@@ -420,6 +434,10 @@ class FiberParams(Parameters):
def pmd_coef(self):
return self._pmd_coef
@property
def pmd_coef_defined(self):
return self._pmd_coef_defined
@property
def ref_wavelength(self):
return self._ref_wavelength
@@ -463,10 +481,10 @@ class FiberParams(Parameters):
class EdfaParams:
default_values = {
'f_min': 191.3e12,
'f_max': 196.1e12,
'f_min': None,
'f_max': None,
'multi_band': None,
'bands': [],
'bands': None,
'type_variety': '',
'type_def': '',
'gain_flatmax': None,
@@ -502,9 +520,11 @@ class EdfaParams:
# 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.bandwidth = self.f_max - self.f_min if self.f_max and self.f_min else None
self.f_cent = (self.f_max + self.f_min) / 2 if self.f_max and self.f_min else None
self.f_ripple_ref = params['f_ripple_ref']
self.bands = [{'f_min': params['f_min'],
'f_max': params['f_max']}]
# Gain
self.gain_flatmax = params['gain_flatmax']
@@ -552,7 +572,9 @@ class EdfaParams:
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.")
raise ParametersError(
"The noise figure ripple and the gain ripple must have the same size. %s, %s",
self.nf_ripple.size, self.gain_ripple.size)
# VOA
self.out_voa_auto = params['out_voa_auto']
@@ -591,7 +613,7 @@ class EdfaParams:
def update_params(self, kwargs):
for k, v in kwargs.items():
setattr(self, k, self.update_params(**v) if isinstance(v, dict) else v)
setattr(self, k, v)
class EdfaOperational:
@@ -599,7 +621,8 @@ class EdfaOperational:
'gain_target': None,
'delta_p': None,
'out_voa': None,
'tilt_target': 0
'in_voa': 0,
'tilt_target': None
}
def __init__(self, **operational):
@@ -614,3 +637,95 @@ class EdfaOperational:
return (f'{type(self).__name__}('
f'gain_target={self.gain_target!r}, '
f'tilt_target={self.tilt_target!r})')
DEFAULT_EDFA_CONFIG = {
"nf_ripple": [
0.0
],
"gain_ripple": [
0.0
],
"f_min": 191.275e12,
"f_max": 196.125e12,
"dgt": [
1.0, 1.017807767853702, 1.0356155337864215, 1.0534217504465226, 1.0712204022764056, 1.0895983485572227,
1.108555289615659, 1.1280891949729075, 1.1476135933863398, 1.1672278304018044, 1.1869318618366975,
1.2067249615595257, 1.2264996957264114, 1.2428104897182262, 1.2556591482982988, 1.2650555289898042,
1.2744470198196236, 1.2838336236692311, 1.2932153453410835, 1.3040618749785347, 1.316383926863083,
1.3301807335621048, 1.3439818461440451, 1.3598972673004606, 1.3779439775587023, 1.3981208704326855,
1.418273806730323, 1.4340878115214444, 1.445565137158368, 1.45273959485914, 1.4599103316162523,
1.4670307626366115, 1.474100442252211, 1.48111939735681, 1.488134243479226, 1.495145456062699,
1.502153039909686, 1.5097346239790443, 1.5178910621476225, 1.5266220576235803, 1.5353620432989845,
1.545374152761467, 1.5566577309558969, 1.569199764184379, 1.5817353179379183, 1.5986915141218316,
1.6201194134191075, 1.6460167077689267, 1.6719047669939942, 1.6918150918099673, 1.7057507692361864,
1.7137640932265894, 1.7217732861435076, 1.7297783508684146, 1.737780757913635, 1.7459181197626403,
1.7541903672600494, 1.7625959636196327, 1.7709972329654864, 1.7793941781790852, 1.7877868031023945,
1.7961751115773796, 1.8045606557581335, 1.8139629377087627, 1.824381436842932, 1.835814081380705,
1.847275503201129, 1.862235672444246, 1.8806927939516411, 1.9026104247588487, 1.9245345552113182,
1.9482128147680253, 1.9736443063300082, 2.0008103857988204, 2.0279625371819305, 2.055100772005235,
2.082225099873648, 2.1183028432496016, 2.16337565384239, 2.2174389328192197, 2.271520771371253,
2.322373696229342, 2.3699990328716107, 2.414398437185221, 2.4587748041127506, 2.499446286796604,
2.5364027376452056, 2.5696460593920065, 2.602860350286428, 2.630396440815385, 2.6521732021128046,
2.6681935771243177, 2.6841217449620203, 2.6947834587664494, 2.705443819238505, 2.714526681131686
]
}
class MultiBandParams:
default_values = {
'bands': [],
'type_variety': '',
'type_def': None,
'allowed_for_design': False
}
def __init__(self, **params):
try:
self.update_attr(params)
except KeyError as e:
raise ParametersError(f'Multiband configurations json must include {e}. Configuration: {params}')
def update_attr(self, kwargs):
clean_kwargs = {k: v for k, v in kwargs.items() if v != ''}
for k, v in self.default_values.items():
# use deepcopy to avoid sharing same object amongst all instance when v is a list or a dict!
if isinstance(v, (list, dict)):
setattr(self, k, clean_kwargs.get(k, deepcopy(v)))
else:
setattr(self, k, clean_kwargs.get(k, v))
class TransceiverParams:
def __init__(self, **params):
self.design_bands = params.get('design_bands', [])
self.per_degree_design_bands = params.get('per_degree_design_bands', {})
@dataclass
class FrequencyBand:
"""Frequency band
"""
f_min: float
f_max: float
DEFAULT_BANDS_DEFINITION = {
"LBAND": FrequencyBand(f_min=187e12, f_max=189e12),
"CBAND": FrequencyBand(f_min=191.3e12, f_max=196.0e12)
}
# use this definition to index amplifiers'element of a multiband amplifier.
# this is not the design band
def find_band_name(band: FrequencyBand) -> str:
"""return the default band name (CBAND, LBAND, ...) that corresponds to the band frequency range
Use the band center frequency: if center frequency is inside the band then returns CBAND.
This is to flexibly encompass all kind of bands definitions.
returns the first matching band name.
"""
for band_name, frequency_range in DEFAULT_BANDS_DEFINITION.items():
center_frequency = (band.f_min + band.f_max) / 2
if center_frequency >= frequency_range.f_min and center_frequency <= frequency_range.f_max:
return band_name
return 'unknown_band'

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.core.science_utils: Solver definitions to calculate the Raman effect and the nonlinear interference noise
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.core.science_utils
=======================
@@ -12,14 +17,14 @@ The solvers take as input instances of the spectral information, the fiber and t
from numpy import interp, pi, zeros, cos, array, append, ones, exp, arange, sqrt, trapz, arcsinh, clip, abs, sum, \
concatenate, flip, outer, inner, transpose, max, format_float_scientific, diag, sort, unique, argsort, cumprod, \
polyfit
polyfit, log, reshape, swapaxes, full, nan, cumsum
from logging import getLogger
from scipy.constants import k, h
from scipy.interpolate import interp1d
from math import isclose
from math import isclose, factorial
from gnpy.core.utils import db2lin, lin2db
from gnpy.core.exceptions import EquipmentConfigError
from gnpy.core.exceptions import EquipmentConfigError, ParametersError
from gnpy.core.parameters import SimParams
from gnpy.core.info import SpectralInformation
@@ -136,15 +141,17 @@ class RamanSolver:
co_cr = fiber.cr(co_frequency)
co_alpha = fiber.alpha(co_frequency)
co_power_profile = \
RamanSolver.first_order_derivative_solution(co_power, co_alpha, co_cr, z, lumped_losses)
RamanSolver.calculate_unidirectional_stimulated_raman_scattering(co_power, co_alpha, co_cr, z,
lumped_losses)
# Counter-propagating profile initialization
cnt_power_profile = zeros([cnt_frequency.size, z.size])
if cnt_frequency.size:
cnt_cr = fiber.cr(cnt_frequency)
cnt_alpha = fiber.alpha(cnt_frequency)
cnt_power_profile = \
flip(RamanSolver.first_order_derivative_solution(cnt_power, cnt_alpha, cnt_cr,
z[-1] - flip(z), flip(lumped_losses)), axis=1)
cnt_power_profile = flip(
RamanSolver.calculate_unidirectional_stimulated_raman_scattering(cnt_power, cnt_alpha, cnt_cr,
z[-1] - flip(z),
flip(lumped_losses)), axis=1)
# Co-propagating and Counter-propagating Profile Computation
if co_frequency.size and cnt_frequency.size:
co_power_profile, cnt_power_profile = \
@@ -163,8 +170,9 @@ class RamanSolver:
alpha = fiber.alpha(spectral_info.frequency)
cr = fiber.cr(spectral_info.frequency)
# Power profile
power_profile = \
RamanSolver.first_order_derivative_solution(spectral_info.signal, alpha, cr, z, lumped_losses)
power_profile = (
RamanSolver.calculate_unidirectional_stimulated_raman_scattering(spectral_info.signal, alpha, cr, z,
lumped_losses))
# Loss profile
loss_profile = power_profile / outer(spectral_info.signal, ones(z.size))
frequency = spectral_info.frequency
@@ -200,8 +208,8 @@ class RamanSolver:
return ase
@staticmethod
def first_order_derivative_solution(power_in, alpha, cr, z, lumped_losses):
"""Solves the Raman first order derivative equation
def calculate_unidirectional_stimulated_raman_scattering(power_in, alpha, cr, z, lumped_losses):
"""Solves the Raman equation
:param power_in: launch power array
:param alpha: loss coefficient array
@@ -210,18 +218,66 @@ class RamanSolver:
:param lumped_losses: concentrated losses array along the fiber span
:return: power profile matrix
"""
dz = z[1:] - z[:-1]
power = outer(power_in, ones(z.size))
for i in range(1, z.size):
power[:, i] = \
power[:, i - 1] * (1 + (- alpha + sum(cr * power[:, i - 1], 1)) * dz[i - 1]) * lumped_losses[i - 1]
if sim_params.raman_params.method == 'perturbative':
if sim_params.raman_params.order > 4:
raise ValueError(f'Order {sim_params.raman_params.order} not implemented in Raman Solver.')
z_lumped_losses = append(z[lumped_losses != 1], z[-1])
llumped_losses = append(1, lumped_losses[lumped_losses != 1])
power = outer(power_in, ones(z.size))
last_position = 0
z_indices = arange(0, z.size)
for z_lumped_loss, lumped_loss in zip(z_lumped_losses, llumped_losses):
if last_position < z[-1]:
interval = z_indices[(z >= last_position) * (z <= z_lumped_loss) == 1]
z_interval = z[interval] - last_position
dz = z_interval[1:] - z_interval[:-1]
last_position = z[interval][-1]
p0 = power_in * lumped_loss
power_interval = outer(p0, ones(z_interval.size))
alphaz = outer(alpha, z_interval)
expz = exp(- alphaz)
eff_length = 1 / outer(alpha, ones(z_interval.size)) * (1 - expz)
crpz = transpose(ones([z_interval.size, cr.shape[0], cr.shape[1]]) * cr * p0, (1, 2, 0))
exponent = - alphaz
if sim_params.raman_params.order >= 1:
gamma1 = sum(crpz * eff_length, 1)
exponent += gamma1
if sim_params.raman_params.order >= 2:
z_integrand = expz * gamma1
z_integral = cumsum((z_integrand[:, :-1] + z_integrand[:, 1:]) / 2 * dz, 1)
gamma2 = zeros(gamma1.shape)
gamma2[:, 1:] = sum(crpz[:, :, 1:] * z_integral, 1)
exponent += gamma2
if sim_params.raman_params.order >= 3:
z_integrand = expz * (gamma2 + 1/2 * gamma1**2)
z_integral = cumsum((z_integrand[:, :-1] + z_integrand[:, 1:]) / 2 * dz, 1)
gamma3 = zeros(gamma1.shape)
gamma3[:, 1:] = sum(crpz[:, :, 1:] * z_integral, 1)
exponent += gamma3
if sim_params.raman_params.order >= 4:
z_integrand = expz * (gamma3 + gamma1 * gamma2 + 1/factorial(3) * gamma1**3)
z_integral = cumsum((z_integrand[:, :-1] + z_integrand[:, 1:]) / 2 * dz, 1)
gamma4 = zeros(gamma1.shape)
gamma4[:, 1:] = sum(crpz[:, :, 1:] * z_integral, 1)
exponent += gamma4
power_interval *= exp(exponent)
power[:, interval[1:]] = power_interval[:, 1:]
power_in = power_interval[:, -1]
elif sim_params.raman_params.method == 'numerical':
dz = z[1:] - z[:-1]
power = outer(power_in, ones(z.size))
for i in range(1, z.size):
power[:, i] = (power[:, i - 1] * (1 + (- alpha + sum(cr * power[:, i - 1], 1)) * dz[i - 1]) *
lumped_losses[i - 1])
else:
raise ValueError(f'Method {sim_params.raman_params.method} not implemented in Raman Solver.')
return power
@staticmethod
def iterative_algorithm(co_initial_guess_power, cnt_initial_guess_power, co_frequency, cnt_frequency, z, fiber,
lumped_losses):
"""Solves the Raman first order derivative equation in case of both co- and counter-propagating
frequencies
"""Solves the Raman equation in case of both co- and counter-propagating frequencies
:param co_initial_guess_power: co-propagationg Raman first order derivative equation solution
:param cnt_initial_guess_power: counter-propagationg Raman first order derivative equation solution
@@ -276,6 +332,7 @@ class NliSolver:
List of implemented methods:
'gn_model_analytic': eq. 120 from arXiv:1209.0394
'ggn_spectrally_separated': eq. 21 from arXiv: 1710.02225
'ggn_approx': eq. 24-25 jlt:9741324
"""
SPM_WEIGHT = (16.0 / 27.0)
@@ -324,6 +381,28 @@ class NliSolver:
g_nli = sum(g_nli, 1)
g_nli = interp(spectral_info.frequency, cut_frequency, g_nli)
nli = spectral_info.baud_rate * g_nli # Local white noise
elif 'ggn_approx' in sim_params.nli_params.method:
if sim_params.nli_params.computed_channels is not None:
cut_indices = array(sim_params.nli_params.computed_channels) - 1
elif sim_params.nli_params.computed_number_of_channels is not None:
nb_ch_computed = sim_params.nli_params.computed_number_of_channels
nb_ch = len(spectral_info.channel_number)
cut_indices = array([round(i * (nb_ch - 1) / (nb_ch_computed - 1)) for i in range(0, nb_ch_computed)])
else:
cut_indices = array(spectral_info.channel_number) - 1
eta = NliSolver._ggn_approx(cut_indices, spectral_info, fiber, srs)
# Interpolation over the channels not indicated as computed channels in simulation parameters
cut_power = outer(spectral_info.signal[cut_indices], ones(spectral_info.number_of_channels))
cut_frequency = spectral_info.frequency[cut_indices]
pump_power = outer(ones(cut_indices.size), spectral_info.signal)
cut_baud_rate = outer(spectral_info.baud_rate[cut_indices], ones(spectral_info.number_of_channels))
g_nli = eta * cut_power * pump_power ** 2 / cut_baud_rate
g_nli = sum(g_nli, 1)
g_nli = interp(spectral_info.frequency, cut_frequency, g_nli)
nli = spectral_info.baud_rate * g_nli # Local white noise
else:
raise ValueError(f'Method {sim_params.nli_params.method} not implemented.')
@@ -526,6 +605,89 @@ class NliSolver:
freq_offset_th = ((k_ref * delta_f_ref) * rs_ref * beta2_ref) / (beta2 * symbol_rate)
return freq_offset_th
@staticmethod
def _ggn_approx(cut_indices, spectral_info: SpectralInformation, fiber, srs, spm_weight=SPM_WEIGHT,
xpm_weight=XPM_WEIGHT):
"""Computes the nonlinear interference power evaluated at the fiber input.
The method uses eq. 24-25 of https://ieeexplore.ieee.org/document/9741324
"""
# Spectral Features
nch = spectral_info.number_of_channels
frequency = spectral_info.frequency
baud_rate = spectral_info.baud_rate
slot_width = spectral_info.slot_width
roll_off = spectral_info.roll_off
df = spectral_info.df + diag(full(nch, nan))
# Physical fiber parameters
alpha = fiber.alpha(frequency)
beta2 = fiber.beta2(frequency)
gamma = outer(fiber.gamma(frequency[cut_indices]), ones(nch))
identity = diag(ones(nch))
weight = spm_weight * identity + xpm_weight * (ones([nch, nch]) - identity)
weight = weight[cut_indices, :]
dispersion_tolerance = sim_params.nli_params.dispersion_tolerance
phase_shift_tolerance = sim_params.nli_params.phase_shift_tolerance
max_slot_width = max(slot_width)
max_beta2 = max(abs(beta2))
delta_z = sim_params.raman_params.result_spatial_resolution
# Approximation psi
loss_profile = srs.loss_profile[:nch]
z = srs.z
psi = NliSolver._approx_psi(df=df, frequency=frequency, beta2=beta2, baud_rate=baud_rate,
loss_profile=loss_profile, z=z)
# GGN for SPM
for cut_index in cut_indices:
dn = 0
cut_frequency = frequency[cut_index]
cut_baud_rate = baud_rate[cut_index]
cut_roll_off = roll_off[cut_index]
cut_beta2 = beta2[cut_index]
cut_alpha = alpha[cut_index]
k_tol = dispersion_tolerance * abs(cut_alpha)
phi_tol = phase_shift_tolerance / delta_z
f_cut_resolution = min(k_tol, phi_tol) / abs(max_beta2) / (4 * pi ** 2 * (1 + dn) * max_slot_width)
f_pump_resolution = min(k_tol, phi_tol) / abs(max_beta2) / (4 * pi ** 2 * max_slot_width)
psi[cut_index, cut_index] = NliSolver._generalized_psi(cut_frequency, cut_frequency, cut_baud_rate,
cut_roll_off, cut_frequency, cut_baud_rate,
cut_roll_off, f_cut_resolution, f_pump_resolution,
srs, cut_alpha, cut_beta2, 0, cut_frequency)
psi = psi[cut_indices, :]
cut_baud_rate = outer(baud_rate[cut_indices], ones(nch))
pump_baud_rate = outer(ones(cut_indices.size), baud_rate)
eta_cut_central_frequency = \
gamma ** 2 * weight * psi / (cut_baud_rate * pump_baud_rate ** 2)
eta = cut_baud_rate * eta_cut_central_frequency # Local white noise
return eta
@staticmethod
def _approx_psi(df, frequency, baud_rate, beta2, loss_profile, z):
"""Computes the approximated psi function similarly to the one used in the GN model.
The method uses eq. 25 of https://ieeexplore.ieee.org/document/9741324"""
pump_baud_rate = outer(ones(frequency.size), baud_rate)
cut_beta = outer(beta2, ones(frequency.size))
pump_beta = outer(ones(frequency.size), beta2)
delta_z = abs(z[:-1] - z[1:])
loss_lin = log(loss_profile)
pump_alpha = (loss_lin[:, 1:] - loss_lin[:, :-1]) / delta_z
leff = abs((loss_profile[:, 1:] - loss_profile[:, :-1]) / sqrt(abs(pump_alpha))) * pump_alpha / abs(pump_alpha)
leff = reshape(outer(leff, ones(z.size - 1)), newshape=[leff.shape[0], leff.shape[1], leff.shape[1]])
leff2 = leff * swapaxes(leff, 2, 1)
leff2 = sum(leff2, axis=(1, 2))
z_int = outer(ones(frequency.size), leff2)
delta_beta = (cut_beta + pump_beta) / 2
psi = z_int * pump_baud_rate / (4 * pi * abs(delta_beta * df))
return psi
def estimate_nf_model(type_variety, gain_min, gain_max, nf_min, nf_max):
if nf_min < -10:

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.core.utils: utility functions that are used with gnpy
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.core.utils
===============
@@ -12,6 +17,7 @@ from csv import writer
from numpy import pi, cos, sqrt, log10, linspace, zeros, shape, where, logical_and, mean, array
from scipy import constants
from copy import deepcopy
from typing import List, Union, Dict
from gnpy.core.exceptions import ConfigurationError
@@ -328,6 +334,35 @@ def merge_amplifier_restrictions(dict1, dict2):
return copy_dict1
def use_pmd_coef(dict1: dict, dict2: dict):
"""If Fiber dict1 is missing the pmd_coef value then use the one of dict2.
In addition records in "pmd_coef_defined" key the pmd_coef if is was defined in dict1.
:param dict1: A dictionnary that contains "pmd_coef" key.
:type dict1: dict
:param dict2: Another dictionnary that contains "pmd_coef" key.
:type dict2: dict
>>> dict1 = {'a': 1, 'pmd_coef': 1.5e-15}
>>> dict2 = {'a': 2, 'pmd_coef': 2e-15}
>>> use_pmd_coef(dict1, dict2)
>>> dict1
{'a': 1, 'pmd_coef': 1.5e-15, 'pmd_coef_defined': True}
>>> dict1 = {'a': 1}
>>> use_pmd_coef(dict1, dict2)
>>> dict1
{'a': 1, 'pmd_coef_defined': False, 'pmd_coef': 2e-15}
"""
if 'pmd_coef' in dict1 and not dict1['pmd_coef'] \
or ('pmd_coef' not in dict1 and 'pmd_coef' in dict2):
dict1['pmd_coef_defined'] = False
dict1['pmd_coef'] = dict2['pmd_coef']
elif 'pmd_coef' in dict1 and dict1['pmd_coef']:
dict1['pmd_coef_defined'] = True
# all other case do not need any change
def silent_remove(this_list, elem):
"""Remove matching elements from a list without raising ValueError
@@ -443,6 +478,119 @@ def restore_order(elements, order):
return [elements[i[0]] for i in sorted(enumerate(order), key=lambda x:x[1]) if elements[i[0]] is not None]
def unique_ordered(elements):
"""
"""
unique_elements = []
for element in elements:
if element not in unique_elements:
unique_elements.append(element)
return unique_elements
def convert_empty_to_none(json_data: Union[list, dict]) -> dict:
"""Convert all instances of "a": [None] into "a": None
:param json_data: the input data.
:type json_data: dict
:return: the converted data.
:rtype: dict
>>> json_data = {
... "uid": "[east edfa in Lannion",
... "type_variety": "multiband_booster",
... "metadata": {
... "location": {
... "latitude": 0.000000,
... "longitude": 0.000000,
... "city": "Zion",
... "region": ""
... }
... },
... "type": "Multiband_amplifier",
... "amplifiers": [{
... "type_variety": "multiband_booster_LOW_C",
... "operational": {
... "gain_target": 12.22,
... "delta_p": 4.19,
... "out_voa": [None],
... "tilt_target": 0.00,
... "f_min": 191.3,
... "f_max": 196.1
... }
... }, {
... "type_variety": "multiband_booster_LOW_L",
... "operational": {
... "gain_target": 12.05,
... "delta_p": 4.19,
... "out_voa": [None],
... "tilt_target": 0.00,
... "f_min": 186.1,
... "f_max": 190.9
... }
... }
... ]
... }
>>> convert_empty_to_none(json_data)
{'uid': '[east edfa in Lannion', 'type_variety': 'multiband_booster', \
'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}}, \
'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'multiband_booster_LOW_C', \
'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0, \
'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'multiband_booster_LOW_L', \
'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0, \
'f_min': 186.1, 'f_max': 190.9}}]}
"""
if isinstance(json_data, dict):
for key, value in json_data.items():
json_data[key] = convert_empty_to_none(value)
elif isinstance(json_data, list):
if len(json_data) == 1 and json_data[0] is None:
return None
for i, elem in enumerate(json_data):
json_data[i] = convert_empty_to_none(elem)
return json_data
def convert_none_to_empty(json_data: Union[list, dict]) -> dict:
"""Convert all instances of "a": None into "a": [None], to be compliant with RFC7951.
:param json_data: the input data.
:type json_data: dict
:return: the converted data.
:rtype: dict
>>> a = {'uid': '[east edfa in Lannion', 'type_variety': 'multiband_booster',
... 'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}},
... 'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'multiband_booster_LOW_C',
... 'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0,
... 'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'multiband_booster_LOW_L',
... 'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0,
... 'f_min': 186.1, 'f_max': 190.9}}]}
>>> convert_none_to_empty(a)
{'uid': '[east edfa in Lannion', 'type_variety': 'multiband_booster', \
'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}}, \
'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'multiband_booster_LOW_C', \
'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': [None], 'tilt_target': 0.0, \
'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'multiband_booster_LOW_L', \
'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': [None], 'tilt_target': 0.0, \
'f_min': 186.1, 'f_max': 190.9}}]}
"""
if json_data == [None]:
# already conformed
return json_data
if isinstance(json_data, dict):
for key, value in json_data.items():
json_data[key] = convert_none_to_empty(value)
elif isinstance(json_data, list):
for i, elem in enumerate(json_data):
json_data[i] = convert_none_to_empty(elem)
elif json_data is None:
return [None]
return json_data
def calculate_absolute_min_or_zero(x: array) -> array:
"""Calculates the element-wise absolute minimum between the x and zero.
@@ -458,3 +606,220 @@ def calculate_absolute_min_or_zero(x: array) -> array:
array([1., 0., 3.])
"""
return (abs(x) - x) / 2
def nice_column_str(data: List[List[str]], max_length: int = 30, padding: int = 1) -> str:
"""data is a list of rows, creates strings with nice alignment per colum and padding with spaces
letf justified
>>> table_data = [['aaa', 'b', 'c'], ['aaaaaaaa', 'bbb', 'c'], ['a', 'bbbbbbbbbb', 'c']]
>>> print(nice_column_str(table_data))
aaa b c
aaaaaaaa bbb c
a bbbbbbbbbb c
"""
# transpose data to determine size of columns
transposed_data = list(map(list, zip(*data)))
column_width = [max(len(word) for word in column) + padding for column in transposed_data]
nice_str = []
for row in data:
column = ''.join(word[0:max_length].ljust(min(width, max_length)) for width, word in zip(column_width, row))
nice_str.append(f'{column}')
return '\n'.join(nice_str)
def filter_valid_amp_bands(amp_bands: List[List[dict]]) -> List[List[dict]]:
"""Filter out invalid amplifier bands that lack f_min or f_max.
:param amp_bands: A list of lists containing amplifier band dictionaries.
:type amp_bands: List[List[dict]]
:return: A filtered list of amplifier bands that contain valid f_min and f_max.
:rtype: List[List[dict]]
"""
return [amp for amp in amp_bands if all(band.get('f_min') is not None and band.get('f_max') is not None
for band in amp)]
def remove_duplicates(amp_bands: List[List[dict]]) -> List[List[dict]]:
"""Remove duplicate amplifier bands.
:param amp_bands: A list of lists containing amplifier band dictionaries.
:type amp_bands: List[List[dict]]
:return: A list of unique amplifier bands.
:rtype: List[List[dict]]
"""
unique_amp_bands = []
for amp in amp_bands:
if amp not in unique_amp_bands:
unique_amp_bands.append(amp)
return unique_amp_bands
def calculate_spacing(first: dict, second: dict, default_spacing: float, default_design_bands: Union[List[Dict], None],
f_min: float, f_max: float) -> float:
"""Calculate the spacing for the given frequency range.
:param first: The first amplifier band dictionary.
:type first: dict
:param second: The second amplifier band dictionary.
:type second: dict
:param default_spacing: The default spacing to use if no specific spacing can be determined.
:type default_spacing: float
:param default_design_bands: Optional list of design bands to determine spacing from.
:type default_design_bands: Union[List[Dict], None]
:param f_min: The minimum frequency of the range.
:type f_min: float
:param f_max: The maximum frequency of the range.
:type f_max: float
:return: The calculated spacing for the given frequency range.
:rtype: float
"""
if first.get('spacing') is not None and second.get('spacing') is not None:
return max(first['spacing'], second['spacing'])
elif first.get('spacing') is not None:
return first['spacing']
elif second.get('spacing') is not None:
return second['spacing']
elif default_design_bands:
temp = get_spacing_from_band(default_design_bands, f_min, f_max)
return temp if temp is not None else default_spacing
return default_spacing
def find_common_range(amp_bands: List[List[dict]], default_band_f_min: Union[float, None],
default_band_f_max: Union[float, None], default_spacing: float,
default_design_bands: Union[List[Dict], None] = None) -> List[dict]:
"""
Find the common frequency range of amplifier bands.
If there are no amplifiers in the path, then use the default band parameters.
:param amp_bands: A list of lists containing amplifier band dictionaries, each with 'f_min', 'f_max',
and optionally 'spacing'.
:type amp_bands: List[List[dict]]
:param default_band_f_min: The minimum frequency of the default band.
:type default_band_f_min: Union[float, None]
:param default_band_f_max: The maximum frequency of the default band.
:type default_band_f_max: Union[float, None]
:param default_spacing: The default spacing to use if no specific spacing can be determined.
:type default_spacing: float
:param default_design_bands: Optional list of design bands to determine spacing from.
:type default_design_bands: Union[List[Dict], None]
:return: A list of dictionaries representing the common frequency ranges with their respective spacings.
:rtype: List[dict]
>>> amp_bands = [[{'f_min': 191e12, 'f_max' : 195e12, 'spacing': 70e9}, {'f_min': 186e12, 'f_max' : 190e12}], \
[{'f_min': 185e12, 'f_max' : 189e12}, {'f_min': 192e12, 'f_max' : 196e12}], \
[{'f_min': 186e12, 'f_max': 193e12}]]
>>> find_common_range(amp_bands, 190e12, 195e12, 50e9)
[{'f_min': 186000000000000.0, 'f_max': 189000000000000.0, 'spacing': 50000000000.0}, \
{'f_min': 192000000000000.0, 'f_max': 193000000000000.0, 'spacing': 70000000000.0}]
>>> amp_bands = [[{'f_min': 191e12, 'f_max' : 195e12}, {'f_min': 186e12, 'f_max' : 190e12}], \
[{'f_min': 185e12, 'f_max' : 189e12}, {'f_min': 192e12, 'f_max' : 196e12}], \
[{'f_min': 186e12, 'f_max': 192e12}]]
>>> find_common_range(amp_bands, 190e12, 195e12, 50e9)
[{'f_min': 186000000000000.0, 'f_max': 189000000000000.0, 'spacing': 50000000000.0}]
"""
# Step 1: Filter and sort amplifier bands
_amp_bands = [sorted(amp, key=lambda x: x['f_min']) for amp in filter_valid_amp_bands(amp_bands)]
unique_amp_bands = remove_duplicates(_amp_bands)
# Step 2: Handle cases with no valid bands
if unique_amp_bands:
common_range = unique_amp_bands[0]
else:
if default_band_f_min is None or default_band_f_max is None:
return []
return [{'f_min': default_band_f_min, 'f_max': default_band_f_max, 'spacing': None}]
# Step 3: Calculate common frequency range
for bands in unique_amp_bands:
new_common_range = []
for first in common_range:
for second in bands:
f_min = max(first['f_min'], second['f_min'])
f_max = min(first['f_max'], second['f_max'])
if f_min < f_max:
spacing = calculate_spacing(first, second, default_spacing, default_design_bands, f_min, f_max)
new_common_range.append({'f_min': f_min, 'f_max': f_max, 'spacing': spacing})
common_range = new_common_range
return sorted(common_range, key=lambda x: x['f_min'])
def transform_data(data: str) -> Union[List[int], None]:
"""Transforms a float into an list of one integer or a string separated by "|" into a list of integers.
Args:
data (float or str): The data to transform.
Returns:
list of int: The transformed data as a list of integers.
Examples:
>>> transform_data(5.0)
[5]
>>> transform_data('1 | 2 | 3')
[1, 2, 3]
"""
if isinstance(data, float):
return [int(data)]
if isinstance(data, str):
return [int(x) for x in data.split(' | ')]
return None
def convert_pmd_lineic(pmd: Union[float, None], length: float, length_unit: str) -> Union[float, None]:
"""Convert PMD value of the span in ps into pmd_lineic in s/sqrt(km)
:param pmd: value in ps
:type pmd: Union[float, None]
:param length: value in length_unit
:type length: float
:param length_unit: 'km' or 'm'
:type length_unit: str
:return: lineic PMD s/sqrt(m)
:rtype: Union[float, None]
>>> convert_pmd_lineic(10, 0.001, 'km')
1e-11
"""
if pmd:
return pmd * 1e-12 / sqrt(convert_length(length, length_unit))
return None
def get_spacing_from_band(design_bands: List[Dict], f_min, f_max):
"""Retrieve the spacing for a frequency range based on design bands.
This function checks if the midpoint of the provided frequency range (f_min, f_max)
falls within any of the design bands. If it does, the corresponding spacing is returned.
:param design_bands: A list of design band dictionaries, each containing 'f_min', 'f_max', and 'spacing'.
:type design_bands: List[Dict]
:param f_min: The minimum frequency of the range.
:type f_min: float
:param f_max: The maximum frequency of the range.
:type f_max: float
:return: The spacing corresponding to the design band that contains the midpoint of the range,
or None if no such band exists.
:rtype: Union[float, None]
"""
midpoint = (f_min + f_max) / 2
for band in design_bands:
if midpoint >= band['f_min'] and midpoint <= band['f_max']:
return band['spacing']
return None
def reorder_per_degree_design_bands(per_degree_design_bands: dict):
"""Sort the design bands for each degree by their minimum frequency (f_min).
This function modifies the input dictionary in place, sorting the design bands for each unique identifier.
:param per_degree_design_bands: A dictionary where keys are unique identifiers and values are lists of design band dictionaries.
:type per_degree_design_bands: Dict[str, List[Dict]]
"""
for uid, design_bands in per_degree_design_bands.items():
per_degree_design_bands[uid] = sorted(design_bands, key=lambda x: x['f_min'])

View File

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

View File

@@ -1,108 +0,0 @@
{
"nf_ripple": [
0.0
],
"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,
1.2744470198196236,
1.2838336236692311,
1.2932153453410835,
1.3040618749785347,
1.316383926863083,
1.3301807335621048,
1.3439818461440451,
1.3598972673004606,
1.3779439775587023,
1.3981208704326855,
1.418273806730323,
1.4340878115214444,
1.445565137158368,
1.45273959485914,
1.4599103316162523,
1.4670307626366115,
1.474100442252211,
1.48111939735681,
1.488134243479226,
1.495145456062699,
1.502153039909686,
1.5097346239790443,
1.5178910621476225,
1.5266220576235803,
1.5353620432989845,
1.545374152761467,
1.5566577309558969,
1.569199764184379,
1.5817353179379183,
1.5986915141218316,
1.6201194134191075,
1.6460167077689267,
1.6719047669939942,
1.6918150918099673,
1.7057507692361864,
1.7137640932265894,
1.7217732861435076,
1.7297783508684146,
1.737780757913635,
1.7459181197626403,
1.7541903672600494,
1.7625959636196327,
1.7709972329654864,
1.7793941781790852,
1.7877868031023945,
1.7961751115773796,
1.8045606557581335,
1.8139629377087627,
1.824381436842932,
1.835814081380705,
1.847275503201129,
1.862235672444246,
1.8806927939516411,
1.9026104247588487,
1.9245345552113182,
1.9482128147680253,
1.9736443063300082,
2.0008103857988204,
2.0279625371819305,
2.055100772005235,
2.082225099873648,
2.1183028432496016,
2.16337565384239,
2.2174389328192197,
2.271520771371253,
2.322373696229342,
2.3699990328716107,
2.414398437185221,
2.4587748041127506,
2.499446286796604,
2.5364027376452056,
2.5696460593920065,
2.602860350286428,
2.630396440815385,
2.6521732021128046,
2.6681935771243177,
2.6841217449620203,
2.6947834587664494,
2.705443819238505,
2.714526681131686
]
}

View File

@@ -23,7 +23,8 @@
"length_units": "km",
"att_in": 0,
"con_in": 0.5,
"con_out": 0.5
"con_out": 0.5,
"pmd_coef": 3.0e-15
},
"metadata": {
"location": {

View File

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

View File

@@ -357,7 +357,8 @@
"tx_power_dbm": 0,
"roll_off": 0.15,
"tx_osnr": 40,
"sys_margins": 2
"sys_margins": 2,
"use_si_channel_count_for_design": true
}
],
"Transceiver": [

View File

@@ -0,0 +1,479 @@
{
"Edfa": [
{
"type_variety": "std_high_gain",
"type_def": "variable_gain",
"gain_flatmax": 35,
"gain_min": 25,
"p_max": 21,
"nf_min": 5.5,
"nf_max": 7,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_medium_gain",
"type_def": "variable_gain",
"gain_flatmax": 26,
"gain_min": 15,
"p_max": 23,
"nf_min": 6,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain_reduced",
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 23,
"nf_min": 6.5,
"nf_max": 11,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "high_power",
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 25,
"nf_min": 9,
"nf_max": 15,
"out_voa_auto": false,
"allowed_for_design": false
},
{
"type_variety": "std_fixed_gain",
"type_def": "fixed_gain",
"gain_flatmax": 21,
"gain_min": 20,
"p_max": 21,
"nf0": 5.5,
"allowed_for_design": false
},
{
"type_variety": "4pumps_raman",
"type_def": "fixed_gain",
"gain_flatmax": 12,
"gain_min": 12,
"p_max": 21,
"nf0": -1,
"allowed_for_design": false
},
{
"type_variety": "hybrid_4pumps_lowgain",
"type_def": "dual_stage",
"raman": true,
"gain_min": 25,
"preamp_variety": "4pumps_raman",
"booster_variety": "std_low_gain",
"allowed_for_design": true
},
{
"type_variety": "hybrid_4pumps_mediumgain",
"type_def": "dual_stage",
"raman": true,
"gain_min": 25,
"preamp_variety": "4pumps_raman",
"booster_variety": "std_medium_gain",
"allowed_for_design": true
},
{
"type_variety": "medium+low_gain",
"type_def": "dual_stage",
"gain_min": 25,
"preamp_variety": "std_medium_gain",
"booster_variety": "std_low_gain",
"allowed_for_design": true
},
{
"type_variety": "medium+high_power",
"type_def": "dual_stage",
"gain_min": 25,
"preamp_variety": "std_medium_gain",
"booster_variety": "high_power",
"allowed_for_design": false
},
{
"type_variety": "std_medium_gain_C",
"f_min": 191.225e12,
"f_max": 196.125e12,
"type_def": "variable_gain",
"gain_flatmax": 26,
"gain_min": 15,
"p_max": 21,
"nf_min": 6,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": false
},
{
"type_variety": "std_medium_gain_L",
"f_min": 186.5e12,
"f_max": 190.1e12,
"type_def": "variable_gain",
"gain_flatmax": 26,
"gain_min": 15,
"p_max": 21,
"nf_min": 6,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain",
"f_min": 191.25e12,
"f_max": 196.15e12,
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 21,
"nf_min": 7,
"nf_max": 11,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain_reduced_band",
"f_min": 192.25e12,
"f_max": 196.15e12,
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 21,
"nf_min": 7,
"nf_max": 11,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain_bis",
"f_min": 191.25e12,
"f_max": 196.15e12,
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 21,
"nf_min": 6,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain_L_ter",
"f_min": 186.55e12,
"f_max": 190.05e12,
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 16,
"nf_min": 7,
"nf_max": 11,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain_L",
"f_min": 186.55e12,
"f_max": 190.05e12,
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 21,
"nf_min": 7,
"nf_max": 11,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain_L_reduced_band",
"f_min": 187.3e12,
"f_max": 190.05e12,
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 21,
"nf_min": 7,
"nf_max": 11,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "test",
"type_def": "variable_gain",
"gain_flatmax": 25,
"gain_min": 15,
"p_max": 21,
"nf_min": 5.8,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "test_fixed_gain",
"type_def": "fixed_gain",
"gain_flatmax": 21,
"gain_min": 20,
"p_max": 21,
"nf0": 5,
"allowed_for_design": true
},
{
"type_variety": "std_booster",
"type_def": "fixed_gain",
"gain_flatmax": 21,
"gain_min": 20,
"p_max": 21,
"nf0": 5,
"allowed_for_design": false
},
{
"type_variety": "std_booster_L",
"f_min": 186.55e12,
"f_max": 190.05e12,
"type_def": "fixed_gain",
"gain_flatmax": 21,
"gain_min": 20,
"p_max": 21,
"nf0": 5,
"allowed_for_design": false
},
{
"type_variety": "std_booster_multiband",
"type_def": "multi_band",
"amplifiers": [
"std_booster",
"std_booster_L"
],
"allowed_for_design": false
},
{
"type_variety": "std_medium_gain_multiband",
"type_def": "multi_band",
"amplifiers": [
"std_medium_gain_C",
"std_medium_gain_L"
],
"allowed_for_design": false
},
{
"type_variety": "std_low_gain_multiband",
"type_def": "multi_band",
"amplifiers": [
"std_low_gain",
"std_low_gain_L"
],
"allowed_for_design": false
},
{
"type_variety": "std_low_gain_multiband_ter",
"type_def": "multi_band",
"amplifiers": [
"std_low_gain",
"std_low_gain_L_ter"
],
"allowed_for_design": false
},
{
"type_variety": "std_low_gain_multiband_bis",
"type_def": "multi_band",
"amplifiers": [
"std_low_gain_bis",
"std_low_gain_L"
],
"allowed_for_design": true
},
{
"type_variety": "std_low_gain_multiband_reduced",
"type_def": "multi_band",
"amplifiers": [
"std_low_gain_reduced",
"std_low_gain_L"
],
"allowed_for_design": true
},
{
"type_variety": "std_low_gain_multiband_reduced_bis",
"type_def": "multi_band",
"amplifiers": [
"std_low_gain_bis",
"std_low_gain_L_reduced_band"
],
"allowed_for_design": true
}
],
"Fiber": [
{
"type_variety": "SSMF",
"dispersion": 1.67e-05,
"effective_area": 83e-12,
"pmd_coef": 1.265e-15
},
{
"type_variety": "NZDF",
"dispersion": 0.5e-05,
"effective_area": 72e-12,
"pmd_coef": 1.265e-15
},
{
"type_variety": "LOF",
"dispersion": 2.2e-05,
"effective_area": 125e-12,
"pmd_coef": 1.265e-15
}
],
"RamanFiber": [
{
"type_variety": "SSMF",
"dispersion": 1.67e-05,
"effective_area": 83e-12,
"pmd_coef": 1.265e-15
}
],
"Span": [
{
"power_mode": true,
"delta_power_range_db": [
-2,
3,
0.5
],
"max_fiber_lineic_loss_for_raman": 0.25,
"target_extended_gain": 2.5,
"max_length": 150,
"length_units": "km",
"max_loss": 28,
"padding": 10,
"EOL": 0,
"con_in": 0,
"con_out": 0
}
],
"Roadm": [
{
"target_pch_out_db": -20,
"add_drop_osnr": 38,
"pmd": 0,
"pdl": 0,
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
}
],
"SI": [
{
"f_min": 191.3e12,
"baud_rate": 32e9,
"f_max": 195.1e12,
"spacing": 50e9,
"power_dbm": 0,
"power_range_db": [
0,
0,
1
],
"roll_off": 0.15,
"tx_osnr": 40,
"sys_margins": 2
},
{
"type_variety": "lband",
"f_min": 186.3e12,
"baud_rate": 32e9,
"f_max": 190.1e12,
"spacing": 50e9,
"power_dbm": 0,
"power_range_db": [
0,
0,
1
],
"roll_off": 0.15,
"tx_osnr": 40,
"sys_margins": 2
}
],
"Transceiver": [
{
"type_variety": "vendorA_trx-type1",
"frequency": {
"min": 191.35e12,
"max": 196.1e12
},
"mode": [
{
"format": "mode 1",
"baud_rate": 32e9,
"OSNR": 11,
"bit_rate": 100e9,
"roll_off": 0.15,
"tx_osnr": 40,
"min_spacing": 37.5e9,
"cost": 1
},
{
"format": "mode 2",
"baud_rate": 66e9,
"OSNR": 15,
"bit_rate": 200e9,
"roll_off": 0.15,
"tx_osnr": 40,
"min_spacing": 75e9,
"cost": 1
}
]
},
{
"type_variety": "Voyager",
"frequency": {
"min": 191.35e12,
"max": 196.1e12
},
"mode": [
{
"format": "mode 1",
"baud_rate": 32e9,
"OSNR": 12,
"bit_rate": 100e9,
"roll_off": 0.15,
"tx_osnr": 40,
"min_spacing": 37.5e9,
"cost": 1
},
{
"format": "mode 3",
"baud_rate": 44e9,
"OSNR": 18,
"bit_rate": 300e9,
"roll_off": 0.15,
"tx_osnr": 40,
"min_spacing": 62.5e9,
"cost": 1
},
{
"format": "mode 2",
"baud_rate": 66e9,
"OSNR": 21,
"bit_rate": 400e9,
"roll_off": 0.15,
"tx_osnr": 40,
"min_spacing": 75e9,
"cost": 1
},
{
"format": "mode 4",
"baud_rate": 66e9,
"OSNR": 16,
"bit_rate": 200e9,
"roll_off": 0.15,
"tx_osnr": 40,
"min_spacing": 75e9,
"cost": 1
}
]
}
]
}

View File

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

View File

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

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,24 @@
{
"spectrum": [
{
"f_min": 191.25e12,
"baud_rate": 32e9,
"f_max": 195.1e12,
"slot_width": 50e9,
"delta_pdb": 0,
"roll_off": 0.15,
"tx_osnr": 40,
"label": "cband"
},
{
"f_min": 186.3e12,
"baud_rate": 32e9,
"f_max": 190.1e12,
"slot_width": 50e9,
"delta_pdb": 0,
"roll_off": 0.15,
"tx_osnr": 40,
"label": "lband"
}
]
}

View File

@@ -32,7 +32,6 @@
]
},
"params": {
"type_variety": "SSMF",
"length": 80.0,
"loss_coef": 0.2,
"length_units": "km",

View File

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

View File

@@ -5,8 +5,8 @@
0.0359549,
5.82851
],
"f_min": 191.35e12,
"f_max": 196.1e12,
"f_min": 191.275e12,
"f_max": 196.125e12,
"nf_ripple": [
0.4372876328262819,
0.4372876328262819,

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.tools.cli_examples: Common code for CLI examples
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.tools.cli_examples
=======================
@@ -11,28 +16,28 @@ Common code for CLI examples
import argparse
import logging
import sys
from math import ceil
from numpy import linspace, mean
from pathlib import Path
from typing import Union, List
from math import ceil
from numpy import mean
import gnpy.core.ansi_escapes as ansi_escapes
from gnpy.core import ansi_escapes
from gnpy.core.elements import Transceiver, Fiber, RamanFiber
from gnpy.core.equipment import trx_mode_params
import gnpy.core.exceptions as exceptions
from gnpy.core.network import add_missing_elements_in_network, design_network
from gnpy.core import exceptions
from gnpy.core.parameters import SimParams
from gnpy.core.utils import db2lin, lin2db, automatic_nch, watt2dbm, dbm2watt
from gnpy.topology.request import (ResultElement, jsontocsv, compute_path_dsjctn, requests_aggregation,
BLOCKING_NOPATH, correct_json_route_list,
deduplicate_disjunctions, compute_path_with_disjunction,
PathRequest, compute_constrained_path, propagate)
from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum
from gnpy.tools.json_io import (load_equipment, load_network, load_json, load_requests, save_network,
requests_from_json, disjunctions_from_json, save_json, load_initial_spectrum)
from gnpy.core.utils import lin2db, pretty_summary_print, per_label_average, watt2dbm
from gnpy.topology.request import (ResultElement, jsontocsv, BLOCKING_NOPATH)
from gnpy.tools.json_io import (load_equipments_and_configs, load_network, load_json, load_requests, save_network,
requests_from_json, save_json, load_initial_spectrum, DEFAULT_EQPT_CONFIG)
from gnpy.tools.plots import plot_baseline, plot_results
from gnpy.tools.worker_utils import designed_network, transmission_simulation, planning
_logger = logging.getLogger(__name__)
_examples_dir = Path(__file__).parent.parent / 'example-data'
_default_config_files = ['example-data/std_medium_gain_advanced_config.json',
'example-data/Juniper-BoosterHG.json',
'parameters.DEFAULT_EDFA_CONFIG']
_help_footer = '''
This program is part of GNPy, https://github.com/TelecomInfraProject/oopt-gnpy
@@ -44,14 +49,35 @@ _help_fname_json_csv = 'FILE.(json|csv)'
def show_example_data_dir():
"""Print the example data directory path."""
print(f'{_examples_dir}/')
def load_common_data(equipment_filename, topology_filename, simulation_filename, save_raw_network_filename):
"""Load common configuration from JSON files"""
def load_common_data(equipment_filename: Path,
extra_equipment_filenames: List[Path], extra_config_filenames: List[Path],
topology_filename: Path, simulation_filename: Path, save_raw_network_filename: Path):
"""Load common configuration from JSON files, merging additional equipment if provided.
:param equipment_filename: Path to the main equipment configuration file.
:type equipment_filename: Path
:param extra_equipment_filenames: List of additional equipment configuration files.
:type extra_equipment_filenames: List[Path]
:param extra_config_filenames: List of additional configuration files.
:type extra_config_filenames: List[Path]
:param topology_filename: Path to the network topology file.
:type topology_filename: Path
:param simulation_filename: Path to the simulation parameters file.
:type simulation_filename: Path
:param save_raw_network_filename: Path to save the raw network configuration.
:type save_raw_network_filename: Path
:raises exceptions.EquipmentConfigError: If there is a configuration error in the equipment library.
:raises exceptions.NetworkTopologyError: If the network definition is invalid.
:raises exceptions.ParametersError: If there is an error with simulation parameters.
:raises exceptions.ConfigurationError: If there is a general configuration error.
:raises exceptions.ServiceError: If there is a service-related error.
"""
try:
equipment = load_equipment(equipment_filename)
equipment = load_equipments_and_configs(equipment_filename, extra_equipment_filenames, extra_config_filenames)
network = load_network(topology_filename, equipment)
if save_raw_network_filename is not None:
save_network(network, save_raw_network_filename)
@@ -84,18 +110,30 @@ def load_common_data(equipment_filename, topology_filename, simulation_filename,
return (equipment, network)
def _setup_logging(args):
def _setup_logging(args: argparse.Namespace):
"""Set up logging based on verbosity level.
:param args: The parsed command-line arguments.
:type args: argparse.Namespace
"""
logging.basicConfig(level={2: logging.DEBUG, 1: logging.INFO, 0: logging.WARNING}.get(args.verbose, logging.DEBUG))
def _add_common_options(parser: argparse.ArgumentParser, network_default: Path):
"""Add common command-line options to the argument parser.
:param parser: The argument parser to which options will be added.
:type parser: argparse.ArgumentParser
:param network_default: The default path for the network topology file.
:type network_default: Path
"""
parser.add_argument('topology', nargs='?', type=Path, metavar='NETWORK-TOPOLOGY.(json|xls|xlsx)',
default=network_default,
help='Input network topology')
parser.add_argument('-v', '--verbose', action='count', default=0,
help='Increase verbosity (can be specified several times)')
parser.add_argument('-e', '--equipment', type=Path, metavar=_help_fname_json,
default=_examples_dir / 'eqpt_config.json', help='Equipment library')
default=DEFAULT_EQPT_CONFIG, help='Equipment library')
parser.add_argument('--sim-params', type=Path, metavar=_help_fname_json,
default=None, help='Path to the JSON containing simulation parameters (required for Raman). '
f'Example: {_examples_dir / "sim_params.json"}')
@@ -106,14 +144,30 @@ def _add_common_options(parser: argparse.ArgumentParser, network_default: Path):
parser.add_argument('--no-insert-edfas', action='store_true',
help='Disable insertion of EDFAs after ROADMs and fibers '
'as well as splitting of fibers by auto-design.')
# Option for additional equipment files
parser.add_argument('--extra-equipment', nargs='+', type=Path,
metavar=_help_fname_json, default=None,
help='List of additional equipment files to complement the main equipment file.')
# Option for additional config files
parser.add_argument('--extra-config', nargs='+', type=Path,
metavar=_help_fname_json,
help='List of additional config files as referenced in equipment files with '
'"advanced_config_from_json" or "default_config_from_json".'
f'Existing configs:\n{_default_config_files}')
def transmission_main_example(args=None):
def transmission_main_example(args: Union[List[str], None] = None):
"""Main script running a single simulation. It returns the detailed power across crossed elements and
average performance accross all channels.
:param args: Command-line arguments (default is None).
:type args: Union[List[str], None]
"""
parser = argparse.ArgumentParser(
description='Send a full spectrum load through the network from point A to point B',
epilog=_help_footer,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
)
_add_common_options(parser, network_default=_examples_dir / 'edfa_example_network.json')
parser.add_argument('--show-channels', action='store_true', help='Show final per-channel OSNR and GSNR summary')
parser.add_argument('-pl', '--plot', action='store_true')
@@ -126,7 +180,8 @@ def transmission_main_example(args=None):
args = parser.parse_args(args if args is not None else sys.argv[1:])
_setup_logging(args)
(equipment, network) = load_common_data(args.equipment, args.topology, args.sim_params, args.save_network_before_autodesign)
(equipment, network) = load_common_data(args.equipment, args.extra_equipment, args.extra_config, args.topology,
args.sim_params, args.save_network_before_autodesign)
if args.plot:
plot_baseline(network)
@@ -144,19 +199,17 @@ def transmission_main_example(args=None):
sys.exit()
# First try to find exact match if source/destination provided
source = None
if args.source:
source = transceivers.pop(args.source, None)
valid_source = True if source else False
else:
source = None
_logger.info('No source node specified: picking random transceiver')
valid_source = bool(source)
destination = None
nodes_list = []
loose_list = []
if args.destination:
destination = transceivers.pop(args.destination, None)
valid_destination = True if destination else False
else:
destination = None
_logger.info('No destination node specified: picking random transceiver')
valid_destination = bool(destination)
# If no exact match try to find partial match
if args.source and not source:
@@ -173,112 +226,77 @@ def transmission_main_example(args=None):
if not source:
source = list(transceivers.values())[0]
del transceivers[source.uid]
_logger.info('No source node specified: picking random transceiver')
if not destination:
destination = list(transceivers.values())[0]
nodes_list = [destination.uid]
loose_list = ['STRICT']
_logger.info('No destination node specified: picking random transceiver')
_logger.info(f'source = {args.source!r}')
_logger.info(f'destination = {args.destination!r}')
_logger.info(f'source = {source.uid!r}')
_logger.info(f'destination = {destination.uid!r}')
params = {}
params['request_id'] = 0
params['trx_type'] = ''
params['trx_mode'] = ''
params['source'] = source.uid
params['destination'] = destination.uid
params['bidir'] = False
params['nodes_list'] = [destination.uid]
params['loose_list'] = ['strict']
params['format'] = ''
params['path_bandwidth'] = 0
params['effective_freq_slot'] = None
trx_params = trx_mode_params(equipment)
trx_params['power'] = dbm2watt(equipment['SI']['default'].power_dbm)
trx_params['tx_power'] = dbm2watt(equipment['SI']['default'].power_dbm)
if args.power:
trx_params['power'] = dbm2watt(float(args.power))
trx_params['tx_power'] = dbm2watt(float(args.power))
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)
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.
# Simulate !
try:
design_network(ref_req, network, equipment, set_connector_losses=True, verbose=True)
network, req, ref_req = designed_network(equipment, network, source.uid, destination.uid,
nodes_list=nodes_list, loose_list=loose_list,
args_power=args.power,
initial_spectrum=initial_spectrum,
no_insert_edfas=args.no_insert_edfas)
path, propagations_for_path, powers_dbm, infos = transmission_simulation(equipment, network, req, ref_req)
except exceptions.NetworkTopologyError as e:
print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ConfigurationError as e:
print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
sys.exit(1)
print(f'\nThere are {len(spans)} fiber spans over {sum(spans)/1000:.0f} km between {source.uid} '
except exceptions.ServiceError as e:
print(f'Service error: {e}')
sys.exit(1)
except ValueError:
sys.exit(1)
# print or export results
spans = [s.params.length for s in path if isinstance(s, (Fiber, RamanFiber))]
print(f'\nThere are {len(spans)} fiber spans over {sum(spans) / 1000:.0f} km between {source.uid} '
f'and {destination.uid}')
print(f'\nNow propagating between {source.uid} and {destination.uid}:')
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)
print(f'Reference used for design: (Input optical power reference in span = {watt2dbm(ref_req.power):.2f}dBm,\n'
+ f' spacing = {ref_req.spacing * 1e-9:.2f}GHz\n'
+ f' nb_channels = {ref_req.nb_channel})')
print('\nChannels propagating: (Input optical power deviation in span = '
+ f'{pretty_summary_print(per_label_average(infos.delta_pdb_per_channel, infos.label))}dB,\n'
+ ' spacing = '
+ f'{pretty_summary_print(per_label_average(infos.slot_width * 1e-9, infos.label))}GHz,\n'
+ ' transceiver output power = '
+ f'{pretty_summary_print(per_label_average(watt2dbm(infos.tx_power), infos.label))}dBm,\n'
+ f' nb_channels = {infos.number_of_channels})')
for mypath, power_dbm in zip(propagations_for_path, powers_dbm):
if power_mode:
print(f'\nPropagating with input power = {ansi_escapes.cyan}{watt2dbm(req.power):.2f} '
print(f'Input optical power reference in span = {ansi_escapes.cyan}{power_dbm:.2f} '
+ f'dBm{ansi_escapes.reset}:')
else:
print(f'\nPropagating in {ansi_escapes.cyan}gain mode{ansi_escapes.reset}: power cannot be set manually')
infos = propagate(path, req, equipment)
if len(power_range) == 1:
for elem in path:
print('\nPropagating in {ansi_escapes.cyan}gain mode{ansi_escapes.reset}: power cannot be set manually')
if len(powers_dbm) == 1:
for elem in mypath:
print(elem)
if power_mode:
print(f'\nTransmission result for input power = {lin2db(req.power*1e3):.2f} dBm:')
print(f'\nTransmission result for input optical power reference in span = {power_dbm:.2f} dBm:')
else:
print(f'\nTransmission results:')
print('\nTransmission results:')
print(f' Final GSNR (0.1 nm): {ansi_escapes.cyan}{mean(destination.snr_01nm):.02f} dB{ansi_escapes.reset}')
else:
print(path[-1])
print(mypath[-1])
if args.save_network is not None:
save_network(network, args.save_network)
@@ -326,11 +344,17 @@ def _path_result_json(pathresult):
def path_requests_run(args=None):
"""Main script running several services simulations. It returns a summary of the average performance
for each service.
:param args: Command-line arguments (default is None).
:type args: Union[List[str], None]
"""
parser = argparse.ArgumentParser(
description='Compute performance for a list of services provided in a json file or an excel sheet',
epilog=_help_footer,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
)
_add_common_options(parser, network_default=_examples_dir / 'meshTopologyExampleV2.xls')
parser.add_argument('service_filename', nargs='?', type=Path, metavar='SERVICES-REQUESTS.(json|xls|xlsx)',
default=_examples_dir / 'meshTopologyExampleV2.xls',
@@ -339,111 +363,49 @@ def path_requests_run(args=None):
help='considers that all demands are bidir')
parser.add_argument('-o', '--output', type=Path, metavar=_help_fname_json_csv,
help='Store satisifed requests into a JSON or CSV file')
parser.add_argument('--redesign-per-request', action='store_true', help='Redesign the network at each request'
+ ' computation using the request as the reference channel')
args = parser.parse_args(args if args is not None else sys.argv[1:])
_setup_logging(args)
_logger.info(f'Computing path requests {args.service_filename.name} into JSON format')
(equipment, network) = load_common_data(args.equipment, args.topology, args.sim_params, args.save_network_before_autodesign)
(equipment, network) = \
load_common_data(args.equipment, args.extra_equipment, args.extra_config, args.topology, args.sim_params,
args.save_network_before_autodesign)
# Build the network once using the default power defined in SI in eqpt config
# TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
# spacing, f_min and f_max
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),
'power': dbm2watt(equipment['SI']['default'].power_dbm),
'tx_power': dbm2watt(equipment['SI']['default'].power_dbm)
}
trx_params = trx_mode_params(equipment)
params.update(trx_params)
reference_channel = PathRequest(**params)
try:
design_network(reference_channel, network, equipment, verbose=True)
network, _, _ = designed_network(equipment, network, no_insert_edfas=args.no_insert_edfas)
data = load_requests(args.service_filename, equipment, bidir=args.bidir,
network=network, network_filename=args.topology)
_data = requests_from_json(data, equipment)
_, propagatedpths, reversed_propagatedpths, rqs, dsjn, result = \
planning(network, equipment, data, redesign=args.redesign_per_request)
except exceptions.NetworkTopologyError as e:
print(f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {e}')
sys.exit(1)
except exceptions.ConfigurationError as e:
print(f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {e}')
sys.exit(1)
if args.save_network is not None:
save_network(network, args.save_network)
print(f'{ansi_escapes.blue}Network (after autodesign) saved to {args.save_network}{ansi_escapes.reset}')
oms_list = build_oms_list(network, equipment)
try:
data = load_requests(args.service_filename, equipment, bidir=args.bidir,
network=network, network_filename=args.topology)
rqs = requests_from_json(data, equipment)
except exceptions.ServiceError as e:
print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {e}')
sys.exit(1)
# check that request ids are unique. Non unique ids, may
# mess the computation: better to stop the computation
all_ids = [r.request_id for r in rqs]
if len(all_ids) != len(set(all_ids)):
for item in list(set(all_ids)):
all_ids.remove(item)
msg = f'Requests id {all_ids} are not unique'
_logger.critical(msg)
sys.exit()
rqs = correct_json_route_list(network, rqs)
# pths = compute_path(network, equipment, rqs)
dsjn = disjunctions_from_json(data)
print(f'{ansi_escapes.blue}List of disjunctions{ansi_escapes.reset}')
print(dsjn)
# need to warn or correct in case of wrong disjunction form
# disjunction must not be repeated with same or different ids
dsjn = deduplicate_disjunctions(dsjn)
# Aggregate demands with same exact constraints
print(f'{ansi_escapes.blue}Aggregating similar requests{ansi_escapes.reset}')
rqs, dsjn = requests_aggregation(rqs, dsjn)
# TODO export novel set of aggregated demands in a json file
print(f'{ansi_escapes.blue}The following services have been requested:{ansi_escapes.reset}')
print(rqs)
print(f'{ansi_escapes.blue}Computing all paths with constraints{ansi_escapes.reset}')
try:
pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
except exceptions.DisjunctionError as this_e:
print(f'{ansi_escapes.red}Disjunction error:{ansi_escapes.reset} {this_e}')
sys.exit(1)
except exceptions.ServiceError as e:
print(f'Service error: {e}')
sys.exit(1)
except ValueError:
sys.exit(1)
print(f'{ansi_escapes.blue}List of disjunctions{ansi_escapes.reset}')
print(dsjn)
print(f'{ansi_escapes.blue}The following services have been requested:{ansi_escapes.reset}')
print(_data)
print(f'{ansi_escapes.blue}Propagating on selected path{ansi_escapes.reset}')
propagatedpths, reversed_pths, reversed_propagatedpths = compute_path_with_disjunction(network, equipment, rqs, pths)
# Note that deepcopy used in compute_path_with_disjunction returns
# a list of nodes which are not belonging to network (they are copies of the node objects).
# so there can not be propagation on these nodes.
pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
if args.save_network is not None:
save_network(network, args.save_network)
print(f'Network (after autodesign) saved to {args.save_network}')
print(f'{ansi_escapes.blue}Result summary{ansi_escapes.reset}')
header = ['req id', ' demand', ' GSNR@bandwidth A-Z (Z-A)', ' GSNR@0.1nm A-Z (Z-A)',
@@ -454,27 +416,27 @@ def path_requests_run(args=None):
for i, this_p in enumerate(propagatedpths):
rev_pth = reversed_propagatedpths[i]
if rev_pth and this_p:
psnrb = f'{round(mean(this_p[-1].snr),2)} ({round(mean(rev_pth[-1].snr),2)})'
psnrb = f'{round(mean(this_p[-1].snr), 2)} ({round(mean(rev_pth[-1].snr), 2)})'
psnr = f'{round(mean(this_p[-1].snr_01nm), 2)}' +\
f' ({round(mean(rev_pth[-1].snr_01nm),2)})'
f' ({round(mean(rev_pth[-1].snr_01nm), 2)})'
elif this_p:
psnrb = f'{round(mean(this_p[-1].snr),2)}'
psnr = f'{round(mean(this_p[-1].snr_01nm),2)}'
psnrb = f'{round(mean(this_p[-1].snr), 2)}'
psnr = f'{round(mean(this_p[-1].snr_01nm), 2)}'
try:
if rqs[i].blocking_reason in BLOCKING_NOPATH:
line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} :',
f'-', f'-', f'-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9,2)}',
f'-', f'{rqs[i].blocking_reason}']
'-', '-', '-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',
'-', '{rqs[i].blocking_reason}']
else:
line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} : ', psnrb,
psnr, f'-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',
f'-', f'{rqs[i].blocking_reason}']
psnr, '-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',
'-', f'{rqs[i].blocking_reason}']
except AttributeError:
line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} : ', psnrb,
psnr, f'{rqs[i].OSNR + equipment["SI"]["default"].sys_margins}',
f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9,2)}',
f'{ceil(rqs[i].path_bandwidth / rqs[i].bit_rate) }', f'({rqs[i].N},{rqs[i].M})']
f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',
f'{ceil(rqs[i].path_bandwidth / rqs[i].bit_rate)}', f'({rqs[i].N},{rqs[i].M})']
data.append(line)
col_width = max(len(word) for row in data for word in row[2:]) # padding

File diff suppressed because it is too large Load Diff

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

View File

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

View File

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

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.tools.json_io: Loading and saving data from JSON files in GNPy's internal data format
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.tools.json_io
==================
@@ -8,24 +13,29 @@ 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 copy import deepcopy
from typing import Union, Dict, List, Tuple, Optional
from networkx import DiGraph
from numpy import arange
from gnpy.core import elements
from gnpy.core.equipment import trx_mode_params
from gnpy.core.equipment import trx_mode_params, find_type_variety
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, dbm2watt
from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT, EdfaParams
from gnpy.topology.request import PathRequest, Disjunction, compute_spectrum_slot_vs_bandwidth
from gnpy.core.utils import automatic_nch, automatic_fmax, merge_amplifier_restrictions, dbm2watt, use_pmd_coef
from gnpy.core.parameters import DEFAULT_RAMAN_COEFFICIENT, EdfaParams, MultiBandParams, DEFAULT_EDFA_CONFIG
from gnpy.topology.request import PathRequest, Disjunction, compute_spectrum_slot_vs_bandwidth, ResultElement
from gnpy.topology.spectrum_assignment import mvalue_to_slots
from gnpy.tools.convert import xls_to_json_data
from gnpy.tools.service_sheet import read_service_sheet
from gnpy.tools.convert_legacy_yang import yang_to_legacy, legacy_to_yang
from gnpy.tools.default_edfa_config import DEFAULT_EXTRA_CONFIG, DEFAULT_EQPT_CONFIG
_logger = getLogger(__name__)
@@ -39,19 +49,27 @@ Model_dual_stage = namedtuple('Model_dual_stage', 'preamp_variety booster_variet
class Model_openroadm_preamp:
pass
"""class to hold nf model specific to OpenROADM preamp
"""
class Model_openroadm_booster:
pass
"""class to hold nf model specific to OpenROADM booster
"""
class _JsonThing:
"""Base class for json equipment
"""
def update_attr(self, default_values, kwargs, name):
"""Build the attributes based on kwargs dict
"""
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' and v is not None and v != []:
disable_warning_keys = ['use_si_channel_count_for_design', 'voa_step', 'voa_margin', 'span_loss_ref',
'power_slope']
if k not in clean_kwargs and name != 'Amp' and v is not None and v != [] and k not in disable_warning_keys:
# do not show this warning if the default value is None
msg = f'\n\tWARNING missing {k} attribute in eqpt_config.json[{name}]' \
+ f'\n\tdefault value is {k} = {v}\n'
@@ -59,6 +77,8 @@ class _JsonThing:
class SI(_JsonThing):
"""Spectrum Information
"""
default_values = {
"f_min": 191.35e12,
"f_max": 196.1e12,
@@ -69,7 +89,8 @@ class SI(_JsonThing):
"roll_off": 0.15,
"tx_osnr": 45,
"sys_margins": 0,
"tx_power_dbm": None # optional value in SI
"tx_power_dbm": None, # optional value in SI
"use_si_channel_count_for_design": False # optional value in SI
}
def __init__(self, **kwargs):
@@ -77,6 +98,8 @@ class SI(_JsonThing):
class Span(_JsonThing):
"""Span simulations definition
"""
default_values = {
'power_mode': True,
'delta_power_range_db': None,
@@ -88,7 +111,11 @@ class Span(_JsonThing):
'padding': 10,
'EOL': 0,
'con_in': 0,
'con_out': 0
'con_out': 0,
"span_loss_ref": 20.0,
"power_slope": 0.3,
"voa_margin": 1,
"voa_step": 0.5
}
def __init__(self, **kwargs):
@@ -96,6 +123,8 @@ class Span(_JsonThing):
class Roadm(_JsonThing):
"""List of ROADM and their specs
"""
default_values = {
'type_variety': 'default',
'add_drop_osnr': 100,
@@ -128,6 +157,8 @@ class Roadm(_JsonThing):
class Transceiver(_JsonThing):
"""List of transceivers and their modes
"""
default_values = {
'type_variety': None,
'frequency': None,
@@ -160,6 +191,8 @@ class Transceiver(_JsonThing):
class Fiber(_JsonThing):
"""Fiber default settings
"""
default_values = {
'type_variety': '',
'dispersion': None,
@@ -180,30 +213,42 @@ class Fiber(_JsonThing):
class RamanFiber(Fiber):
pass
"""Raman Fiber default settings
"""
class Amp(_JsonThing):
"""List of amplifiers with their specs
"""
default_values = EdfaParams.default_values
def __init__(self, **kwargs):
self.update_attr(self.default_values, kwargs, 'Amp')
@classmethod
def from_json(cls, filename, **kwargs):
config = Path(filename).parent / 'default_edfa_config.json'
def from_json(cls, extra_configs, **kwargs):
"""
"""
# default EDFA DGT and ripples are defined in parameters DEFAULT_EDFA_CONFIG. copy these values when
# creating a new amplifier
config = {k: v for k, v in DEFAULT_EDFA_CONFIG.items()}
config_filename = 'default' # default value to display in case of error
type_variety = kwargs['type_variety']
type_def = kwargs.get('type_def', 'variable_gain') # default compatibility with older json eqpt files
nf_def = None
dual_stage_def = None
amplifiers = None
if type_def == 'fixed_gain':
if 'default_config_from_json' in kwargs:
# use user defined default instead of DEFAULT_EDFA_CONFIG
config_filename = kwargs.pop('default_config_from_json')
config = deepcopy(extra_configs[config_filename])
try:
nf0 = kwargs.pop('nf0')
except KeyError: # nf0 is expected for a fixed gain amp
except KeyError as exc: # 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(msg) from exc
for k in ('nf_min', 'nf_max'):
try:
del kwargs[k]
@@ -211,15 +256,21 @@ class Amp(_JsonThing):
pass
nf_def = Model_fg(nf0)
elif type_def == 'advanced_model':
config = Path(filename).parent / kwargs.pop('advanced_config_from_json')
# use the user file name define in library instead of default config
config_filename = kwargs.pop('advanced_config_from_json')
config = deepcopy(extra_configs[config_filename])
elif type_def == 'variable_gain':
if 'default_config_from_json' in kwargs:
# use user defined default instead of DEFAULT_EDFA_CONFIG
config_filename = kwargs.pop('default_config_from_json')
config = deepcopy(extra_configs[config_filename])
gain_min, gain_max = kwargs['gain_min'], kwargs['gain_flatmax']
try: # nf_min and nf_max are expected for a variable gain amp
nf_min = kwargs.pop('nf_min')
nf_max = kwargs.pop('nf_max')
except KeyError:
except KeyError as exc:
msg = f'missing nf_min or nf_max value input for amplifier: {type_variety} in equipment config'
raise EquipmentConfigError(msg)
raise EquipmentConfigError(msg) from exc
try: # remove all remaining nf inputs
del kwargs['nf0']
except KeyError:
@@ -229,8 +280,8 @@ class Amp(_JsonThing):
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')
except KeyError as exc: # nf_coef is expected for openroadm amp
raise EquipmentConfigError(f'missing nf_coef input for amplifier: {type_variety} in equipment config') from exc
nf_def = Model_openroadm_ila(nf_coef)
elif type_def == 'openroadm_preamp':
nf_def = Model_openroadm_preamp()
@@ -240,28 +291,28 @@ class Amp(_JsonThing):
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)
except KeyError as exc:
raise EquipmentConfigError(f'missing preamp/booster variety input for amplifier: {type_variety}'
+ ' in equipment config') from exc
dual_stage_def = Model_dual_stage(preamp_variety, booster_variety)
elif type_def == 'multi_band':
amplifiers = kwargs['amplifiers']
else:
raise EquipmentConfigError(f'Edfa type_def {type_def} does not exist')
json_data = load_json(config)
return cls(**{**kwargs, **json_data,
'nf_model': nf_def, 'dual_stage_model': dual_stage_def})
# raise an error if config does not contain f_min, f_max
if 'f_min' not in config or 'f_max' not in config:
raise EquipmentConfigError(f'Config file {config_filename} does not contain f_min and f_max values.'
+ ' Please correct file.')
# use f_min, f_max from kwargs
if 'f_min' in kwargs:
config.pop('f_min', None)
config.pop('f_max', None)
return cls(**{**kwargs, **config,
'nf_model': nf_def, 'dual_stage_model': dual_stage_def, 'multi_band': amplifiers})
def _automatic_spacing(baud_rate):
"""return the min possible channel spacing for a given baud rate"""
# TODO : this should parametrized in a cfg file
# list of possible tuples [(max_baud_rate, spacing_for_this_baud_rate)]
spacing_list = [(33e9, 37.5e9), (38e9, 50e9), (50e9, 62.5e9), (67e9, 75e9), (92e9, 100e9)]
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):
def _spectrum_from_json(json_data: dict):
"""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.
@@ -303,17 +354,13 @@ def _spectrum_from_json(json_data):
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
part.setdefault('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'
part.setdefault('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
part.setdefault('tx_osnr', 40)
# default tx_power_dbm is set to 0 dBn
if 'tx_power_dbm' not in part:
part['tx_power_dbm'] = 0
part.setdefault('tx_power_dbm', 0)
# 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
@@ -321,12 +368,13 @@ def _spectrum_from_json(json_data):
# 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 ' +\
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'
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']
previous_part_max_freq = None
for current_freq in arange(part['f_min'],
part['f_min'] + max_range,
part['slot_width']):
@@ -338,17 +386,86 @@ def _spectrum_from_json(json_data):
return spectrum
def load_equipment(filename):
json_data = load_json(filename)
return _equipment_from_json(json_data, filename)
def merge_equipment(equipment: Dict, extra_equipments: Dict[str, Dict], extra_configs: Dict[str, Dict]):
"""Merge additional equipment libraries into the base equipment dictionary.
Typical case is the use of third party transceivers which are not part of a the supplier library.
raise warnings if the same reference is used on two different libraries
"""
for filename, json_data in extra_equipments.items():
extra_eqpt = _equipment_from_json(json_data, extra_configs)
# populate with default eqpt to streamline loading
for eqpt_type, extra_items in extra_eqpt.items():
for type_variety, item in extra_items.items():
if type_variety not in equipment[eqpt_type]:
equipment[eqpt_type][type_variety] = item
else:
msg = f'\n\tEquipment file {filename}: duplicate equipment entry found: {eqpt_type}-{type_variety}\n'
_logger.warning(msg)
def load_initial_spectrum(filename):
json_data = load_json(filename)
def load_equipments_and_configs(equipment_filename: Path,
extra_equipment_filenames: List[Path],
extra_config_filenames: List[Path]) -> Dict:
"""Loads equipment configurations and merge with additional equipment and configuration files.
:param equipment_filename: The path to the primary equipment configuration file.
:type equipment_filename: Path
:param extra_equipment_filenames: A list of paths to additional equipment configuration files to merge.
:type extra_equipment_filenames: List[Path]
:param extra_config_filenames: A list of paths to additional configuration files to include.
:type extra_config_filenames: List[Path]
:return: A dictionary containing the loaded equipment configurations.
:rtype: Dict
Notes:
If no equipment filename is provided, a default equipment configuration will be used.
Additional configurations from `extra_config_filenames` will override the default configurations.
If `extra_equipment_filenames` are provided, their contents will be merged into the loaded equipment.
"""
extra_configs = DEFAULT_EXTRA_CONFIG
if not equipment_filename:
equipment_filename = DEFAULT_EQPT_CONFIG
if extra_config_filenames:
# All files must have different filenames (as filename is used as the key in the library)
filename_list = [f.name for f in extra_config_filenames]
if len(set(filename_list)) != len(extra_config_filenames):
msg = f'Identical filenames for extra-config {filename_list}'
_logger.error(msg)
raise ConfigurationError(msg)
extra_configs = {f.name: load_json(f) for f in extra_config_filenames}
for k, v in DEFAULT_EXTRA_CONFIG.items():
extra_configs[k] = v
equipment = load_equipment(equipment_filename, extra_configs)
if extra_equipment_filenames:
# use the string representation of the path to support identical filenames but placed in different folders.
extra_equipments = {f.as_posix(): load_json(f) for f in extra_equipment_filenames}
merge_equipment(equipment, extra_equipments, extra_configs)
return equipment
def load_equipment(filename: Path, extra_configs: Dict[str, Dict] = DEFAULT_EXTRA_CONFIG) -> Dict:
"""Load equipment, returns equipment dict
"""
json_data = load_gnpy_json(filename)
return _equipment_from_json(json_data, extra_configs)
def load_initial_spectrum(filename: Path) -> dict:
"""Load spectrum to propagate, returns spectrum dict
"""
json_data = load_gnpy_json(filename)
return _spectrum_from_json(json_data['spectrum'])
def _update_dual_stage(equipment):
def _update_dual_stage(equipment: dict):
"""Update attributes of all dual stage amps with the preamp and booster attributes
(defined in the equipment dictionary)
Returns the updated equiment dictionary
"""
if 'Edfa' not in equipment:
return
edfa_dict = equipment['Edfa']
for edfa in edfa_dict.values():
if edfa.type_def == 'dual_stage':
@@ -367,8 +484,35 @@ def _update_dual_stage(equipment):
return equipment
def _roadm_restrictions_sanity_check(equipment):
def _update_band(equipment: dict):
"""Creates a list of bands for this amplifier, and remove other parameters which are not applicable
"""
if 'Edfa' not in equipment:
return
amp_dict = equipment['Edfa']
for amplifier in amp_dict.values():
if amplifier.type_def != 'multi_band':
amplifier.bands = [{'f_min': amplifier.f_min,
'f_max': amplifier.f_max}]
# updates band parameter
else:
_bands = [{'f_min': amp_dict[a].f_min,
'f_max': amp_dict[a].f_max} for a in amp_dict[amplifier.type_variety].multi_band]
# remove duplicates
amplifier.bands = []
for b in _bands:
if b not in amplifier.bands:
amplifier.bands.append(b)
# remove non applicable parameters
for key in ['f_min', 'f_max', 'gain_flatmax', 'gain_min', 'p_max', 'nf_model', 'dual_stage_model',
'nf_fit_coeff', 'nf_ripple', 'dgt', 'gain_ripple']:
delattr(amplifier, key)
def _roadm_restrictions_sanity_check(equipment: dict):
"""verifies that booster and preamp restrictions specified in roadm equipment are listed in the edfa."""
if 'Roadm' not in equipment:
return equipment
for roadm_type, roadm_eqpt in equipment['Roadm'].items():
restrictions = roadm_eqpt.restrictions['booster_variety_list'] + \
roadm_eqpt.restrictions['preamp_variety_list']
@@ -378,7 +522,7 @@ def _roadm_restrictions_sanity_check(equipment):
+ 'defined EDFA name')
def _check_fiber_vs_raman_fiber(equipment):
def _check_fiber_vs_raman_fiber(equipment: dict):
"""Ensure that Fiber and RamanFiber with the same name define common properties equally"""
if 'RamanFiber' not in equipment:
return
@@ -393,7 +537,20 @@ def _check_fiber_vs_raman_fiber(equipment):
f'disagrees for "{attr}": {a} != {b}')
def _equipment_from_json(json_data, filename):
def _si_sanity_check(equipment):
"""Check that 'default' key correctly exists in SI list. (There must be at list one element and it must be default)
If not create one entry in the list with this key.
"""
if 'SI' not in equipment:
return
possible_SI = list(equipment['SI'].keys())
if 'default' not in possible_SI:
# Use "default" key in the equipment, using the first listed keys
equipment['SI']['default'] = equipment['SI'][possible_SI[0]]
del equipment['SI'][possible_SI[0]]
def _equipment_from_json(json_data: dict, extra_configs: Dict[str, Dict]) -> Dict:
"""build global dictionnary eqpt_library that stores all eqpt characteristics:
edfa type type_variety, fiber type_variety
from the eqpt_config.json (filename parameter)
@@ -408,7 +565,7 @@ def _equipment_from_json(json_data, filename):
for entry in entries:
subkey = entry.get('type_variety', 'default')
if key == 'Edfa':
equipment[key][subkey] = Amp.from_json(filename, **entry)
equipment[key][subkey] = Amp.from_json(extra_configs, **entry)
elif key == 'Fiber':
equipment[key][subkey] = Fiber(**entry)
elif key == 'Span':
@@ -427,16 +584,23 @@ def _equipment_from_json(json_data, filename):
else:
raise EquipmentConfigError(f'Unrecognized network element type "{key}"')
_check_fiber_vs_raman_fiber(equipment)
equipment = _update_dual_stage(equipment)
_update_dual_stage(equipment)
_update_band(equipment)
_roadm_restrictions_sanity_check(equipment)
_si_sanity_check(equipment)
return equipment
def load_network(filename, equipment):
def load_network(filename: Path, equipment: dict) -> DiGraph:
"""load network json or excel
:param filename: input file to read from
:param equipment: equipment library
"""
if filename.suffix.lower() in ('.xls', '.xlsx'):
json_data = xls_to_json_data(filename)
elif filename.suffix.lower() == '.json':
json_data = load_json(filename)
json_data = load_gnpy_json(filename)
else:
raise ValueError(f'unsupported topology filename extension {filename.suffix.lower()}')
return network_from_json(json_data, equipment)
@@ -456,28 +620,80 @@ def _cls_for(equipment_type):
return elements.Edfa
if equipment_type == 'Fused':
return elements.Fused
elif equipment_type == 'Roadm':
if equipment_type == 'Roadm':
return elements.Roadm
elif equipment_type == 'Transceiver':
if equipment_type == 'Transceiver':
return elements.Transceiver
elif equipment_type == 'Fiber':
if equipment_type == 'Fiber':
return elements.Fiber
elif equipment_type == 'RamanFiber':
if equipment_type == 'RamanFiber':
return elements.RamanFiber
else:
raise ConfigurationError(f'Unknown network equipment "{equipment_type}"')
if equipment_type == 'Multiband_amplifier':
return elements.Multiband_amplifier
raise ConfigurationError(f'Unknown network equipment "{equipment_type}"')
def network_from_json(json_data, equipment):
def network_from_json(json_data: dict, equipment: dict) -> DiGraph:
"""create digraph based on json input dict and using equipment library to fill in the gaps
"""
# NOTE|dutc: we could use the following, but it would tie our data format
# too closely to the graph library
# from networkx import node_link_graph
g = DiGraph()
g.graph['network_name'] = json_data.get('network_name', None)
for el_config in json_data['elements']:
typ = el_config.pop('type')
variety = el_config.pop('type_variety', 'default')
cls = _cls_for(typ)
if typ == 'Fused':
if typ == 'Transceiver':
temp = el_config.setdefault('params', {})
if typ == 'Multiband_amplifier':
if variety in ['default', '']:
extra_params = None
temp = el_config.setdefault('params', {})
temp = merge_amplifier_restrictions(temp, deepcopy(MultiBandParams.default_values))
el_config['params'] = temp
else:
extra_params = equipment['Edfa'][variety]
temp = el_config.setdefault('params', {})
# use config params preferably to library params, only use library params to fill in
# the missing attribute
temp = merge_amplifier_restrictions(temp, deepcopy(extra_params.__dict__))
el_config['params'] = temp
el_config['type_variety'] = variety
# if config does not contain any amp list create one
amps = el_config.setdefault('amplifiers', [])
for amp in amps:
amp_variety = amp['type_variety'] # juste pour essayer
amp_extra_params = equipment['Edfa'][amp_variety]
temp = amp.setdefault('params', {})
temp = merge_amplifier_restrictions(temp, amp_extra_params.__dict__)
amp['params'] = temp
amp['type_variety'] = amp_variety
# check type_variety consistant with amps type_variety
if amps:
try:
multiband_type_variety = find_type_variety([a['type_variety'] for a in amps], equipment)
except ConfigurationError as e:
msg = f'Node {el_config["uid"]}: {e}'
raise ConfigurationError(msg)
if variety is not None and variety not in multiband_type_variety:
raise ConfigurationError(f'In node {el_config["uid"]}: multiband amplifier type_variety is not '
+ 'consistent with its amps type varieties.')
if not amps and extra_params is not None:
# the amp config does not contain the amplifiers operational settings, but has a type_variety
# defined so that it is possible to create the template of amps for design for each band. This
# defines the default design bands.
# This lopp populates each amp with default values, for each band
for band in extra_params.bands:
params = {k: v for k, v in Amp.default_values.items()}
# update frequencies with band values
params['f_min'] = band['f_min']
params['f_max'] = band['f_max']
amps.append({'params': params})
# without type_variety, it is not possible to set the amplifier dict at this point: need to wait
# for design, and use user defined design-bands
elif typ == 'Fused':
# well, there's no variety for the 'Fused' node type
pass
elif variety in equipment[typ]:
@@ -491,6 +707,9 @@ def network_from_json(json_data, equipment):
if not extra_params:
msg = f'ROADM {el_config["uid"]}: invalid equalization settings'
raise ConfigurationError(msg)
# use temp pmd_coef if it exists else use the default one from library and keep this knowledge in
# pmd_coef_defined
use_pmd_coef(temp, extra_params)
temp = merge_amplifier_restrictions(temp, extra_params)
el_config['params'] = temp
el_config['type_variety'] = variety
@@ -516,14 +735,16 @@ def network_from_json(json_data, equipment):
else:
edge_length = 0.01
g.add_edge(nodes[from_node], nodes[to_node], weight=edge_length)
except KeyError:
except KeyError as exc:
msg = f'can not find {from_node} or {to_node} defined in {cx}'
raise NetworkTopologyError(msg)
raise NetworkTopologyError(msg) from exc
return g
def network_to_json(network):
def network_to_json(network: DiGraph) -> dict:
"""Export network graph as a json dict
"""
data = {
'elements': [n.to_json for n in network]
}
@@ -534,56 +755,82 @@ def network_to_json(network):
for next_n in network.successors(n) if next_n is not None]
}
data.update(connections)
if network.graph['network_name']:
data['network_name'] = network.graph['network_name']
return data
def load_json(filename):
def load_json(filename: Path) -> dict:
"""load json data
:param filename: Path to the file to convert
:type filemname: Path
:return: json data in a dictionnary
:rtype: Dict
"""
with open(filename, 'r', encoding='utf-8') as f:
data = json.load(f)
return data
def save_json(obj, filename):
def load_gnpy_json(filename: Path) -> dict:
"""load json data. It supports both legacy ang yang formatted inputs based on yang models.
:param filename: Path to the file to convert
:type filemname: Path
:return: json data in a dictionnary
:rtype: Dict
"""
return yang_to_legacy(load_json(filename))
def save_json(obj: dict, filename: Path):
"""Save in json format. Export yang formatted data (RFC7951)
"""
data = legacy_to_yang(obj)
with open(filename, 'w', encoding='utf-8') as f:
json.dump(obj, f, indent=2, ensure_ascii=False)
def load_requests(filename, eqpt, bidir, network, network_filename):
def load_requests(filename: Path, eqpt: dict, bidir: bool, network: DiGraph, network_filename: str) -> dict:
"""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}')
raise ServiceError(f'Service error: {this_e}') from this_e
else:
return load_json(filename)
def requests_from_json(json_data, equipment):
def requests_from_json(json_data: dict, equipment: dict) -> List[PathRequest]:
"""Extract list of requests from data parsed from JSON"""
requests_list = []
for req in json_data['path-request']:
# init all params from request
params = {}
params['request_id'] = f'{req["request-id"]}'
params['source'] = req['source']
params['bidir'] = req['bidirectional']
params['destination'] = req['destination']
params['trx_type'] = req['path-constraints']['te-bandwidth']['trx_type']
if params['trx_type'] is None:
trx_type = req['path-constraints']['te-bandwidth']['trx_type']
trx_mode = req['path-constraints']['te-bandwidth'].get('trx_mode', None)
if trx_type is None:
msg = f'Request {req["request-id"]} has no transceiver type defined.'
raise ServiceError(msg)
params['trx_mode'] = req['path-constraints']['te-bandwidth'].get('trx_mode', None)
params['format'] = params['trx_mode']
params['spacing'] = req['path-constraints']['te-bandwidth']['spacing']
try:
nd_list = sorted(req['explicit-route-objects']['route-object-include-exclude'], key=lambda x: x['index'])
except KeyError:
nd_list = []
params['nodes_list'] = [n['num-unnum-hop']['node-id'] for n in nd_list]
params['loose_list'] = [n['num-unnum-hop']['hop-type'] for n in nd_list]
params = {
'request_id': f'{req["request-id"]}',
'source': req['source'],
'destination': req['destination'],
'bidir': req['bidirectional'],
'trx_type': trx_type,
'trx_mode': trx_mode,
'format': trx_mode,
'spacing': req['path-constraints']['te-bandwidth']['spacing'],
'nodes_list': [n['num-unnum-hop']['node-id'] for n in nd_list],
'loose_list': [n['num-unnum-hop']['hop-type'] for n in nd_list]
}
# recover trx physical param (baudrate, ...) from type and mode
# nb_channel is computed based on min max frequency and spacing
try:
@@ -629,7 +876,7 @@ def requests_from_json(json_data, equipment):
return requests_list
def _check_one_request(params, f_max_from_si):
def _check_one_request(params: dict, f_max_from_si: float):
"""Checks that the requested parameters are consistant (spacing vs nb channel vs transponder mode...)"""
f_min = params['f_min']
f_max = params['f_max']
@@ -639,19 +886,19 @@ def _check_one_request(params, f_max_from_si):
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'
f'{params["min_spacing"] * 1e-9}GHz.\nComputation stopped'
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' 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}.'
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'])
required_nb_of_channels, _ = 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'])
@@ -690,7 +937,7 @@ def _check_one_request(params, f_max_from_si):
i += 1
def disjunctions_from_json(json_data):
def disjunctions_from_json(json_data: dict) -> List[Disjunction]:
"""reads the disjunction requests from the json dict and create the list
of requested disjunctions for this set of requests
"""
@@ -709,20 +956,30 @@ def disjunctions_from_json(json_data):
def convert_service_sheet(
input_filename,
eqpt,
network,
network_filename=None,
output_filename='',
bidir=False):
input_filename: Path,
eqpt: dict,
network: DiGraph,
network_filename: Union[Path, None] = None,
output_filename: str = '',
bidir: bool = False):
"""Converts xls into json format services
:param input_filename: xls(x) file containing the service sheet
:param eqpt: equipment library
:param network: network for which these services apply (required for xls inputs to correct names)
:param network_filename: optional network file name that was used for network creation
(required for xls inputs to correct names)
:param output_filename: name of the file where converted data are savec
:param bidir: set all services bidir attribute with this bool
"""
if output_filename == '':
output_filename = f'{str(input_filename)[0:len(str(input_filename))-len(str(input_filename.suffixes[0]))]}_services.json'
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)
save_json(data, output_filename)
return data
def find_equalisation(params, equalization_types):
def find_equalisation(params: Dict, equalization_types: List[str]):
"""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,
@@ -739,7 +996,7 @@ def find_equalisation(params, equalization_types):
return equalization
def merge_equalization(params, extra_params):
def merge_equalization(params: dict, extra_params: dict) -> Union[dict, None]:
"""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)
@@ -759,3 +1016,42 @@ def merge_equalization(params, extra_params):
# If ROADM config doesn't contain any equalization type, keep the default one
return extra_params
return None
def results_to_json(pathresults: List[ResultElement]):
"""Converts a list of `ResultElement` objects into a JSON-compatible dictionary.
:param pathresults: List of `ResultElement` objects to be converted.
:return: A dictionary with a single key `"response"`, containing a list of
the `json` attributes of the provided `ResultElement` objects.
"""
return {'response': [n.json for n in pathresults]}
def load_eqpt_topo_from_json(eqpt: dict, topology: dict, extra_equipments: Optional[Dict[str, Dict]] = None,
extra_configs: Dict[str, Dict] = DEFAULT_EXTRA_CONFIG) -> Tuple[dict, DiGraph]:
"""Loads equipment configuration and network topology from JSON data.
:param eqpt: Dictionary containing the equipment configuration in JSON format.
It includes details about the devices to be processed and structured.
:type eqpt: dict
:param topology: Dictionary representing the network topology in JSON format,
defining the structure of the network and its connections.
:type topology: dict
:param extra_equipments: dictionary containing additional libraries (eg for pluggables). Key can be
the file Path or any other string.
:type extra_equipments: Optional[Dict[str, Dict]]
:param extra_configs: Additional configurations for amplifiers in the library
:type extra_configs: Dict[str, Dict]
:return: A tuple containing:
- A dictionary with the processed equipment configuration.
- A directed graph (DiGraph) representing the network topology, where nodes
correspond to equipment and edges define their connections.
"""
equipment = _equipment_from_json(eqpt, extra_configs)
if extra_equipments:
merge_equipment(equipment, extra_equipments, extra_configs)
network = network_from_json(topology, equipment)
return equipment, network

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.tools.plots: Graphs and plots usable from a CLI application
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.tools.plots
================

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.tools.service_sheet: XLS parser that can be called to create a JSON request file
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.tools.service_sheet
========================
@@ -11,105 +16,181 @@ Yang model for requesting path computation.
See: draft-ietf-teas-yang-path-computation-01.txt
"""
from xlrd import open_workbook, XL_CELL_EMPTY
from collections import namedtuple
from logging import getLogger
from copy import deepcopy
from pathlib import Path
from typing import Dict, List, Generator
from networkx import DiGraph
from gnpy.core.utils import db2lin
from gnpy.core.exceptions import ServiceError
from gnpy.core.elements import Transceiver, Roadm, Edfa, Fiber
from gnpy.tools.convert import corresp_names, corresp_next_node
from gnpy.tools.convert import corresp_names, corresp_next_node, all_rows, generic_open_workbook, get_sheet, \
parse_row, parse_headers
from gnpy.tools.xls_utils import correct_cell_int_to_str, get_sheet_name, is_type_cell_empty
SERVICES_COLUMN = 12
def all_rows(sheet, start=0):
return (sheet.row(x) for x in range(start, sheet.nrows))
SERVICE_LINE = 4
logger = getLogger(__name__)
class Request(namedtuple('Request', 'request_id source destination trx_type mode \
spacing power nb_channel disjoint_from nodes_list is_loose path_bandwidth')):
def __new__(cls, request_id, source, destination, trx_type, mode=None, spacing=None, power=None, nb_channel=None, disjoint_from='', nodes_list=None, is_loose='', path_bandwidth=None):
return super().__new__(cls, request_id, source, destination, trx_type, mode, spacing, power, nb_channel, disjoint_from, nodes_list, is_loose, path_bandwidth)
class Request:
"""DATA class for a request.
:params request_id (int): The unique identifier for the request.
:params source (str): The source node for the communication.
:params destination (str): The destination node for the communication.
:params trx_type (str): The type of transmission for the communication.
:params mode (str, optional): The mode of transmission. Defaults to None.
:params spacing (float, optional): The spacing between channels. Defaults to None.
:params power (float, optional): The power level for the communication. Defaults to None.
:params nb_channel (int, optional): The number of channels required for the communication. Defaults to None.
:params disjoint_from (str, optional): The node to be disjoint from. Defaults to ''.
:params nodes_list (list, optional): The list of nodes involved in the communication. Defaults to None.
:params is_loose (str, optional): Indicates if the communication is loose. Defaults to ''.
:params path_bandwidth (float, optional): The bandwidth required for the communication. Defaults to None.
"""
def __init__(self, **kwargs):
"""Constructor method
"""
super().__init__()
self.update_attr(kwargs)
def update_attr(self, kwargs):
"""Updates the attributes of the node based on provided keyword arguments.
:param kwargs: A dictionary of attributes to update.
"""
clean_kwargs = {k: v for k, v in kwargs.items() if v != '' and v is not None}
for k, v in self.default_values.items():
v = clean_kwargs.get(k, v)
if k != 'is_loose':
if k in ['request_id', 'trx_type', 'mode', 'disjoint_from']:
v = correct_cell_int_to_str(v)
setattr(self, k, v)
else:
self.is_loose = v in ['', None, 'yes', 'Yes', 'YES']
default_values = {
'request_id': None,
'source': None,
'destination': None,
'trx_type': None,
'mode': None,
'spacing': None,
'power': None,
'nb_channel': None,
'disjoint_from': '',
'nodes_list': '',
'is_loose': None,
'path_bandwidth': None
}
class Element:
"""
"""
def __init__(self, uid):
self.uid = uid
def __eq__(self, other):
return type(self) == type(other) and self.uid == other.uid
return isinstance(other, type(self)) and self.uid == other.ui
def __hash__(self):
return hash((type(self), self.uid))
class Request_element(Element):
def __init__(self, Request, equipment, bidir):
"""Class that generate the request in the json format
:params request_param (Request): The request object containing the information for the element.
:params equipment (dict): The equipment configuration for the communication.
:params bidir (bool): Indicates if the communication is bidirectional.
Attributes:
request_id (str): The unique identifier for the request.
source (str): The source node for the communication.
destination (str): The destination node for the communication.
srctpid (str): The source TP ID for the communication.
dsttpid (str): The destination TP ID for the communication.
bidir (bool): Indicates if the communication is bidirectional.
trx_type (str): The type of transmission for the communication.
mode (str): The mode of transmission for the communication.
spacing (float): The spacing between channels for the communication.
power (float): The power level for the communication.
nb_channel (int): The number of channels required for the communication.
disjoint_from (list): The list of nodes to be disjoint from.
nodes_list (list): The list of nodes involved in the communication.
loose (str): Indicates if the communication is loose or strict.
path_bandwidth (float): The bandwidth required for the communication.
"""
def __init__(self, request_param: Request, equipment: Dict, bidir: bool):
"""
"""
super().__init__(uid=request_param.request_id)
# request_id is str
# excel has automatic number formatting that adds .0 on integer values
# the next lines recover the pure int value, assuming this .0 is unwanted
self.request_id = correct_xlrd_int_to_str_reading(Request.request_id)
self.source = f'trx {Request.source}'
self.destination = f'trx {Request.destination}'
# TODO: the automatic naming generated by excel parser requires that source and dest name
self.request_id = request_param.request_id
self.source = f'trx {request_param.source}'
self.destination = f'trx {request_param.destination}'
# The automatic naming generated by excel parser requires that source and dest name
# be a string starting with 'trx' : this is manually added here.
self.srctpid = f'trx {Request.source}'
self.dsttpid = f'trx {Request.destination}'
self.srctpid = f'trx {request_param.source}'
self.dsttpid = f'trx {request_param.destination}'
self.bidir = bidir
# test that trx_type belongs to eqpt_config.json
# if not replace it with a default
self.mode = None
try:
if equipment['Transceiver'][Request.trx_type]:
self.trx_type = correct_xlrd_int_to_str_reading(Request.trx_type)
if Request.mode is not None:
Requestmode = correct_xlrd_int_to_str_reading(Request.mode)
if [mode for mode in equipment['Transceiver'][Request.trx_type].mode if mode['format'] == Requestmode]:
self.mode = Requestmode
available_modes = [mode['format'] for mode in equipment['Transceiver'][request_param.trx_type].mode]
self.trx_type = request_param.trx_type
if request_param.mode not in [None, '']:
if request_param.mode in available_modes:
self.mode = request_param.mode
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_param.trx_type}\' ' \
+ f'with mode: \'{request_param.mode}\' in eqpt library \nComputation stopped.'
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.'
raise ServiceError(msg)
except KeyError as e:
msg = f'Request Id: {self.request_id} - could not find tsp : \'{request_param.trx_type}\' with mode: ' \
+ f'\'{request_param.mode}\' in eqpt library \nComputation stopped.'
raise ServiceError(msg) from e
# excel input are in GHz and dBm
if Request.spacing is not None:
self.spacing = Request.spacing * 1e9
if request_param.spacing:
self.spacing = request_param.spacing * 1e9
else:
msg = f'Request {self.request_id} missing spacing: spacing is mandatory.\ncomputation stopped'
raise ServiceError(msg)
if Request.power is not None:
self.power = db2lin(Request.power) * 1e-3
else:
self.power = None
if Request.nb_channel is not None:
self.nb_channel = int(Request.nb_channel)
else:
self.nb_channel = None
value = correct_xlrd_int_to_str_reading(Request.disjoint_from)
self.disjoint_from = [n for n in value.split(' | ') if value]
self.power = None
if request_param.power is not None:
self.power = db2lin(request_param.power) * 1e-3
self.nb_channel = None
if request_param.nb_channel is not None:
self.nb_channel = int(request_param.nb_channel)
self.disjoint_from = [n for n in request_param.disjoint_from.split(' | ') if request_param.disjoint_from]
self.nodes_list = []
if Request.nodes_list:
self.nodes_list = Request.nodes_list.split(' | ')
self.loose = 'LOOSE'
if Request.is_loose.lower() == 'no':
self.loose = 'STRICT'
self.path_bandwidth = None
if Request.path_bandwidth is not None:
self.path_bandwidth = Request.path_bandwidth * 1e9
else:
self.path_bandwidth = 0
if request_param.nodes_list:
self.nodes_list = request_param.nodes_list.split(' | ')
uid = property(lambda self: repr(self))
self.loose = 'LOOSE'
if not request_param.is_loose:
self.loose = 'STRICT'
self.path_bandwidth = 0
if request_param.path_bandwidth is not None:
self.path_bandwidth = request_param.path_bandwidth * 1e9
@property
def pathrequest(self):
"""Creates json dictionnary for the request
"""
# Default assumption for bidir is False
req_dictionnary = {
'request-id': self.request_id,
@@ -134,14 +215,15 @@ class Request_element(Element):
if self.nodes_list:
req_dictionnary['explicit-route-objects'] = {}
temp = {'route-object-include-exclude': [
{'explicit-route-usage': 'route-include-ero',
'index': self.nodes_list.index(node),
'num-unnum-hop': {
'node-id': f'{node}',
'link-tp-id': 'link-tp-id is not used',
'hop-type': f'{self.loose}',
}
}
{
'index': self.nodes_list.index(node),
'explicit-route-usage': 'route-include-ero',
'num-unnum-hop': {
'node-id': f'{node}',
'link-tp-id': 'link-tp-id is not used',
'hop-type': f'{self.loose}',
}
}
for node in self.nodes_list]
}
req_dictionnary['explicit-route-objects'] = temp
@@ -152,29 +234,32 @@ class Request_element(Element):
@property
def pathsync(self):
"""Creates json dictionnary for disjunction list (synchronization vector)
"""
if self.disjoint_from:
return {'synchronization-id': self.request_id,
'svec': {
'relaxable': 'false',
'disjointness': 'node link',
'request-id-number': [self.request_id] + [n for n in self.disjoint_from]
'request-id-number': [self.request_id] + list(self.disjoint_from)
}
}
else:
return None
return None
# TO-DO: avoid multiple entries with same synchronisation vectors
@property
def json(self):
"""Returns the json dictionnary for requests and for synchronisation vector
"""
return self.pathrequest, self.pathsync
def read_service_sheet(
input_filename,
eqpt,
network,
network_filename=None,
bidir=False):
input_filename: Path,
eqpt: Dict,
network: DiGraph,
network_filename: Path = None,
bidir: bool = False) -> Dict:
""" converts a service sheet into a json structure
"""
if network_filename is None:
@@ -184,69 +269,86 @@ def read_service_sheet(
req = correct_xls_route_list(network_filename, network, req)
# if there is no sync vector , do not write any synchronization
synchro = [n.json[1] for n in req if n.json[1] is not None]
data = {'path-request': [n.json[0] for n in req]}
if synchro:
data = {
'path-request': [n.json[0] for n in req],
'synchronization': synchro
}
else:
data = {
'path-request': [n.json[0] for n in req]
}
data['synchronization'] = synchro
return data
def correct_xlrd_int_to_str_reading(v):
if not isinstance(v, str):
value = str(int(v))
if value.endswith('.0'):
value = value[:-2]
else:
value = v
return value
def parse_row(row, fieldnames):
return {f: r.value for f, r in zip(fieldnames, row[0:SERVICES_COLUMN])
if r.ctype != XL_CELL_EMPTY}
def parse_excel(input_filename):
with open_workbook(input_filename) as wb:
service_sheet = wb.sheet_by_name('Service')
services = list(parse_service_sheet(service_sheet))
def parse_excel(input_filename: Path) -> List[Request]:
"""Open xls_file and reads 'Service' sheet
Returns the list of services data in Request class
"""
wb, is_xlsx = generic_open_workbook(input_filename)
service_sheet = get_sheet(wb, 'Service', is_xlsx)
services = list(parse_service_sheet(service_sheet, is_xlsx))
return services
def parse_service_sheet(service_sheet):
def parse_service_sheet(service_sheet, is_xlsx) -> Generator[Request, None, None]:
""" reads each column according to authorized fieldnames. order is not important.
"""
logger.debug(f'Validating headers on {service_sheet.name!r}')
logger.debug('Validating headers on %r', get_sheet_name(service_sheet, is_xlsx))
# 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]
if len(x.value.strip()) > 0]
# create a service_fieldname independant from the excel column order
# to be compatible with any version of the sheet
# the following dictionnary records the excel field names and the corresponding parameter's name
authorized_fieldnames = {
'route id': 'request_id', 'Source': 'source', 'Destination': 'destination',
'TRX type': 'trx_type', 'Mode': 'mode', 'System: spacing': 'spacing',
'System: input power (dBm)': 'power', 'System: nb of channels': 'nb_channel',
'routing: disjoint from': 'disjoint_from', 'routing: path': 'nodes_list',
'routing: is loose?': 'is_loose', 'path bandwidth': 'path_bandwidth'}
try:
service_fieldnames = [authorized_fieldnames[e] for e in header]
except KeyError:
msg = f'Malformed header on Service sheet: {header} field not in {authorized_fieldnames}'
raise ValueError(msg)
for row in all_rows(service_sheet, start=5):
yield Request(**parse_row(row[0:SERVICES_COLUMN], service_fieldnames))
header = parse_headers(service_sheet, is_xlsx, authorized_fieldnames, {}, SERVICE_LINE, (0, SERVICES_COLUMN))
# create a service_fieldname independant from the excel column order
# to be compatible with any version of the sheet
# the following dictionnary records the excel field names and the corresponding parameter's name
for row in all_rows(service_sheet, is_xlsx, start=5):
if not is_type_cell_empty(row[0], is_xlsx):
# Check required because openpyxl in read_only mode can return "ghost" rows at the end of the document
# (ReadOnlyCell cells with no actual value but formatting information even for empty rows).
yield Request(**parse_row(row[0:SERVICES_COLUMN], header))
def correct_xls_route_list(network_filename, network, pathreqlist):
def check_end_points(pathreq: Request_element, network: DiGraph):
"""Raise error if end point is not correct
"""
transponders = [n.uid for n in network.nodes() if isinstance(n, Transceiver)]
if pathreq.source not in transponders:
msg = f'Request: {pathreq.request_id}: could not find' +\
f' transponder source : {pathreq.source}.'
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}.'
logger.critical(msg)
raise ServiceError(msg)
def find_node_sugestion(n_id, corresp_roadm, corresp_fused, corresp_ila, network):
"""
"""
roadmtype = [n.uid for n in network.nodes() if isinstance(n, Roadm)]
edfatype = [n.uid for n in network.nodes() if isinstance(n, Edfa)]
# check that n_id is in the node list, if not find a correspondance name
if n_id in roadmtype + edfatype:
return [n_id]
# checks first roadm, fused, and ila in this order, because ila automatic name
# contains roadm names. If it is a fused node, next ila names might be correct
# suggestions, especially if following fibers were splitted and ila names
# created with the name of the fused node
if n_id in corresp_roadm.keys():
return corresp_roadm[n_id]
if n_id in corresp_fused.keys():
return corresp_fused[n_id] + corresp_ila[n_id]
if n_id in corresp_ila.keys():
return corresp_ila[n_id]
return []
def correct_xls_route_list(network_filename: Path, network: DiGraph,
pathreqlist: List[Request_element]) -> List[Request_element]:
""" prepares the format of route list of nodes to be consistant with nodes names:
remove wrong names, find correct names for ila, roadm and fused if the entry was
xls.
@@ -260,30 +362,17 @@ def correct_xls_route_list(network_filename, network, pathreqlist):
corresp_ila, next_node = corresp_next_node(network, corresp_ila, corresp_roadm)
# finally correct constraints based on these dict
trxfibertype = [n.uid for n in network.nodes() if isinstance(n, (Transceiver, Fiber))]
roadmtype = [n.uid for n in network.nodes() if isinstance(n, Roadm)]
edfatype = [n.uid for n in network.nodes() if isinstance(n, Edfa)]
# TODO there is a problem of identification of fibers in case of parallel
# fibers between two adjacent roadms so fiber constraint is not supported
transponders = [n.uid for n in network.nodes() if isinstance(n, Transceiver)]
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}.'
raise ServiceError(msg)
if pathreq.destination not in transponders:
msg = f'Request: {pathreq.request_id}: could not find' +\
f' transponder destination: {pathreq.destination}.'
raise ServiceError(msg)
check_end_points(pathreq, network)
# 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
# caught later on
if pathreq.nodes_list and pathreq.source == pathreq.nodes_list[0]:
pathreq.loose_list.pop(0)
pathreq.nodes_list.pop(0)
if pathreq.nodes_list and pathreq.destination == pathreq.nodes_list[-1]:
pathreq.loose_list.pop(-1)
pathreq.nodes_list.pop(-1)
# Then process user defined constraints with respect to automatic namings
temp = deepcopy(pathreq)
@@ -293,73 +382,56 @@ def correct_xls_route_list(network_filename, network, pathreqlist):
# n_id must not be a transceiver and must not be a fiber (non supported, user
# can not enter fiber names in excel)
if n_id not in trxfibertype:
# check that n_id is in the node list, if not find a correspondance name
if n_id in roadmtype + edfatype:
nodes_suggestion = [n_id]
else:
# checks first roadm, fused, and ila in this order, because ila automatic name
# contain roadm names. If it is a fused node, next ila names might be correct
# suggestions, especially if following fibers were splitted and ila names
# created with the name of the fused node
if n_id in corresp_roadm.keys():
nodes_suggestion = corresp_roadm[n_id]
elif n_id in corresp_fused.keys():
nodes_suggestion = corresp_fused[n_id] + corresp_ila[n_id]
elif n_id in corresp_ila.keys():
nodes_suggestion = corresp_ila[n_id]
nodes_suggestion = find_node_sugestion(n_id, corresp_roadm, corresp_fused, corresp_ila, network)
try:
if len(nodes_suggestion) > 1:
# if there is more than one suggestion, we need to choose the direction
# we rely on the next node provided by the user for this purpose
new_n = next(n for n in nodes_suggestion
if n in next_node
and next_node[n] in temp.nodes_list[i:] + [pathreq.destination]
and next_node[n] not in temp.nodes_list[:i])
elif len(nodes_suggestion) == 1:
new_n = nodes_suggestion[0]
else:
nodes_suggestion = []
if nodes_suggestion:
try:
if len(nodes_suggestion) > 1:
# if there is more than one suggestion, we need to choose the direction
# we rely on the next node provided by the user for this purpose
new_n = next(n for n in nodes_suggestion
if n in next_node.keys() and next_node[n]
in temp.nodes_list[i:] + [pathreq.destination] and
next_node[n] not in temp.nodes_list[:i])
else:
new_n = nodes_suggestion[0]
if new_n != n_id:
# warns the user when the correct name is used only in verbose mode,
# eg 'a' is a roadm and correct name is 'roadm a' or when there was
# 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)
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)
pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
pathreq.nodes_list.remove(n_id)
else:
if temp.loose_list[i] == 'LOOSE':
# 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)
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' \
if temp.loose == 'LOOSE':
# 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'{pathreq.request_id}: Invalid node specified:\n\t\'{n_id}\'' \
+ ', could not use it as constraint, skipped!'
print(msg)
logger.info(msg)
pathreq.nodes_list.remove(n_id)
continue
msg = f'{pathreq.request_id}: Could not find node:\n\t\'{n_id}\' in network' \
+ ' topology. Strict constraint can not be applied.'
raise ServiceError(msg)
if new_n != n_id:
# warns the user when the correct name is used only in verbose mode,
# eg 'a' is a roadm and correct name is 'roadm a' or when there was
# too much ambiguity, 'b' is an ila, its name can be:
# "east edfa in b to c", or "west edfa in b to a" if next node is c or
# "west edfa in b to c", or "east edfa in b to a" if next node is a
msg = f'{pathreq.request_id}: Invalid route node specified:' \
+ f'\n\t\'{n_id}\', replaced with \'{new_n}\''
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'{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.info(msg)
pathreq.nodes_list.remove(n_id)
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!')
pathreq.loose_list.pop(pathreq.nodes_list.index(n_id))
if temp.loose == 'LOOSE':
msg = f'{pathreq.request_id}: Invalid route node specified:\n\t\'{n_id}\'' \
+ ' type is not supported as constraint with xls network input, skipped!'
logger.warning(msg)
pathreq.nodes_list.remove(n_id)
else:
msg = f'Invalid route node specified \n\t\'{n_id}\'' \
msg = f'{pathreq.request_id}: Invalid route node specified \n\t\'{n_id}\'' \
+ ' type is not supported as constraint with xls network input,' \
+ ', Strict constraint can not be applied.'
raise ServiceError(msg)

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.tools.worker_utils: Common code for CLI examples and API
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.tools.worker_utils
=======================
Common code for CLI examples and API
"""
import logging
from copy import deepcopy
from typing import Union, List, Tuple
from numpy import linspace
from networkx import DiGraph
from gnpy.core.utils import automatic_nch, watt2dbm, dbm2watt, pretty_summary_print, per_label_average
from gnpy.core.equipment import trx_mode_params
from gnpy.core.network import add_missing_elements_in_network, design_network
from gnpy.core import exceptions
from gnpy.core.info import SpectralInformation
from gnpy.topology.spectrum_assignment import build_oms_list, pth_assign_spectrum, OMS
from gnpy.topology.request import correct_json_route_list, deduplicate_disjunctions, requests_aggregation, \
compute_path_dsjctn, compute_path_with_disjunction, ResultElement, PathRequest, Disjunction, \
compute_constrained_path, propagate
from gnpy.tools.json_io import requests_from_json, disjunctions_from_json
logger = logging.getLogger(__name__)
def designed_network(equipment: dict, network: DiGraph, source: str = None, destination: str = None,
nodes_list: List[str] = None, loose_list: List[str] = None,
initial_spectrum: dict = None, no_insert_edfas: bool = False,
args_power: Union[str, float, int] = None,
service_req: PathRequest = None) -> Tuple[DiGraph, PathRequest, PathRequest]:
"""Build the reference channels based on inputs and design the network for this reference channel, and build the
channel to be propagated for the single transmission script.
Reference channel (target input power in spans, nb of channels, transceiver output power) is built using
equipment['SI'] information. If indicated, with target input power in spans is updated with args_power.
Channel to be propagated is using the same channel reference, except if different settings are provided
with service_req and initial_spectrum. The service to be propagated uses specified source, destination
and list nodes_list of include nodes constraint except if the service_req is specified.
Args:
- equipment: a dictionary containing equipment information.
- network: a directed graph representing the initial network.
- no_insert_edfas: a boolean indicating whether to insert EDFAs in the network.
- args_power: the power to be used for the network design.
- service_req: the service request the user wants to propagate.
- source: the source node for the channel to be propagated if no service_req is specified.
- destination: the destination node for the channel to be propagated if no service_req is specified.
- nodes_list: a list of nodes to be included ifor the channel to be propagated if no service_req is specified.
- loose_list: a list of loose nodes to be included in the network design.
- initial_spectrum: a dictionary representing the initial spectrum to propagate.
Returns:
- The designed network.
- The channel to propagate.
- The reference channel used for the design.
"""
if loose_list is None:
loose_list = []
if nodes_list is None:
nodes_list = []
if not no_insert_edfas:
add_missing_elements_in_network(network, equipment)
if not nodes_list:
if destination:
nodes_list = [destination]
loose_list = ['STRICT']
else:
nodes_list = []
loose_list = []
params = {
'request_id': 'reference',
'trx_type': '',
'trx_mode': '',
'source': source,
'destination': destination,
'bidir': False,
'nodes_list': nodes_list,
'loose_list': loose_list,
'format': '',
'path_bandwidth': 0,
'effective_freq_slot': None,
'nb_channel': None if equipment['SI']['default'].use_si_channel_count_for_design is False
else automatic_nch(equipment['SI']['default'].f_min, equipment['SI']['default'].f_max,
equipment['SI']['default'].spacing),
'power': dbm2watt(equipment['SI']['default'].power_dbm),
'tx_power': dbm2watt(equipment['SI']['default'].power_dbm)
}
if equipment['SI']['default'].tx_power_dbm is not None:
# use SI tx_power if present
params['tx_power'] = dbm2watt(equipment['SI']['default'].tx_power_dbm)
trx_params = trx_mode_params(equipment)
params.update(trx_params)
# use args_power instead of si
if args_power:
params['power'] = dbm2watt(float(args_power))
if equipment['SI']['default'].tx_power_dbm is None:
params['tx_power'] = params['power']
# use si as reference channel
reference_channel = PathRequest(**params)
if service_req:
# use service_req as reference channel with si tx_power if service_req tx_power is None
if service_req.tx_power is None:
service_req.tx_power = params['tx_power']
reference_channel = deepcopy(service_req)
if equipment['SI']['default'].use_si_channel_count_for_design is False:
reference_channel.nb_channel = None
design_network(reference_channel, network, equipment, set_connector_losses=True, verbose=True)
if initial_spectrum:
params['nb_channel'] = len(initial_spectrum)
req = PathRequest(**params)
if service_req:
req = service_req
req.initial_spectrum = initial_spectrum
return network, req, reference_channel
def check_request_path_ids(rqs: List[PathRequest]):
"""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.error(msg)
raise ValueError(msg)
def planning(network: DiGraph, equipment: dict, data: dict, redesign: bool = False) \
-> Tuple[List[OMS], list, list, List[PathRequest], List[Disjunction], List[ResultElement]]:
"""Run planning
data contain the service dict from json
redesign True means that network is redesign using each request as reference channel
when False it means that the design is made once and successive propagation use the settings
computed with this design.
"""
oms_list = build_oms_list(network, equipment)
rqs = requests_from_json(data, equipment)
# check that request ids are unique.
check_request_path_ids(rqs)
rqs = correct_json_route_list(network, rqs)
dsjn = disjunctions_from_json(data)
logger.info('List of disjunctions:\n%s', dsjn)
# need to warn or correct in case of wrong disjunction form
# disjunction must not be repeated with same or different ids
dsjn = deduplicate_disjunctions(dsjn)
logger.info('Aggregating similar requests')
rqs, dsjn = requests_aggregation(rqs, dsjn)
logger.info('The following services have been requested:\n%s', rqs)
# logger.info('Computing all paths with constraints for request %s', optical_path_result_id)
pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
logger.info('Propagating on selected path')
propagatedpths, reversed_pths, reversed_propagatedpths = \
compute_path_with_disjunction(network, equipment, rqs, pths, redesign=redesign)
# 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.
# Allowed user_policy are first_fit and 2partition
pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
for i, rq in enumerate(rqs):
if hasattr(rq, 'OSNR') and rq.OSNR:
rq.osnr_with_sys_margin = rq.OSNR + equipment["SI"]["default"].sys_margins
# assumes that list of rqs and list of propgatedpths have same order
result = [ResultElement(rq, pth, rpth) for rq, pth, rpth in zip(rqs, propagatedpths, reversed_propagatedpths)]
return oms_list, propagatedpths, reversed_propagatedpths, rqs, dsjn, result
def transmission_simulation(equipment: dict, network: DiGraph, req: PathRequest, ref_req: PathRequest) \
-> Tuple[list, List[list], List[Union[float, int]], SpectralInformation]:
"""Run simulation and returms the propagation result for each power sweep iteration.
Args:
- equipment: a dictionary containing equipment information.
- network: network after being designed using ref_req. Any missing information (amp gain or delta_p) must have
been filled using ref_req as reference channel previuos to this function.
- req: channel to be propagated.
- ref_req: the reference channel used for filling missing information in the network.
In case of power sweep, network is redesigned using ref_req whose target input power in span is
updated with the power step.
Returns a tuple containing:
- path: last propagated path. Power sweep is not possible with gain mode (as gain targets are used)
- propagations: list of propagated path for each power iteration
- powers_dbm: list of power used for the power sweep
- infos: last propagated spectral information
"""
power_mode = equipment['Span']['default'].power_mode
logger.info('Power mode is set to %s=> it can be modified in eqpt_config.json - Span', power_mode)
# initial network is designed using ref_req. that is that any missing information (amp gain or delta_p) is filled
# using this ref_req.power, previous to any sweep requested later on.
pref_ch_db = watt2dbm(ref_req.power)
p_ch_db = watt2dbm(req.power)
path = compute_constrained_path(network, req)
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 as e:
msg = 'invalid power range definition in eqpt_config, should be power_range_db: [lower, upper, step]'
logger.error(msg)
raise exceptions.EquipmentConfigError(msg) from e
logger.info('Now propagating between %s and %s', req.source, req.destination)
propagations = []
powers_dbm = []
for dp_db in power_range:
ref_req.power = dbm2watt(pref_ch_db + dp_db)
req.power = dbm2watt(p_ch_db + dp_db)
# Power sweep is made to evaluate different span input powers, so redesign is mandatory for each power,
# but no need to redesign if there are no power sweep
if len(power_range) > 1:
design_network(ref_req, network.subgraph(path), equipment, set_connector_losses=False, verbose=False)
infos = propagate(path, req, equipment)
propagations.append(deepcopy(path))
powers_dbm.append(pref_ch_db + dp_db)
logger.info('\nChannels propagating: (Input optical power deviation in span = '
+ f'{pretty_summary_print(per_label_average(infos.delta_pdb_per_channel, infos.label))}dB,\n'
+ ' spacing = '
+ f'{pretty_summary_print(per_label_average(infos.slot_width * 1e-9, infos.label))}GHz,\n'
+ ' transceiver output power = '
+ f'{pretty_summary_print(per_label_average(watt2dbm(infos.tx_power), infos.label))}dBm,\n'
+ f' nb_channels = {infos.number_of_channels})')
if not power_mode:
logger.info('\n\tPropagating using gain targets: Input optical power deviation in span ignored')
return path, propagations, powers_dbm, infos

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@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# Reads JSON path result file and writes results to a CSV file
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
write_path_jsontocsv.py
========================

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.tools.worker_utils: Utilities for reading and writing XLS, XLSX
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.tools.xls_utils
====================
This module contains utilities for reading and writing XLS, XLSX
"""
from pathlib import Path
from typing import Generator, Tuple, List, Union, Optional, Iterator, Callable
from openpyxl import load_workbook, Workbook
from openpyxl.worksheet.worksheet import Worksheet
from openpyxl.cell.cell import Cell as OpenpyxlCell
from openpyxl.cell.read_only import ReadOnlyCell as OpenpyxlReadOnlyCell
from openpyxl.utils.exceptions import InvalidFileException
from xlrd import Book, open_workbook, XL_CELL_EMPTY
from xlrd.sheet import Sheet as XlrdSheet, Cell as XlrdCell
from xlrd.biffh import XLRDError
SheetType = Union[Worksheet, XlrdSheet]
WorkbookType = Union[Workbook, Book]
CellType = Union[OpenpyxlCell, OpenpyxlReadOnlyCell, XlrdCell]
XLS_EXCEPTIONS = (InvalidFileException, KeyError, XLRDError)
def generic_open_workbook(file_path: Union[str, Path]) -> Tuple[WorkbookType, bool]:
"""Open an Excel file supporting both XLS or XLSX.
:param file_path: Path of excel file
:type file_path: Union[str, Path]
:return: Tuple (workbook, is_xlsx) where is_xlsx inidcate if the file is XLSX or not
:rtype: Tuple[WorkbookType, bool]
"""
file_path = Path(file_path) if isinstance(file_path, str) else file_path
if file_path.suffix.lower() in ['.xlsx', '.xlsm']:
return load_workbook(file_path, read_only=True, data_only=True), True
return open_workbook(file_path), False
def get_sheet(workbook: WorkbookType,
sheet_name: str,
is_xlsx: bool) -> SheetType:
"""Get the Excel Sheet by name
:param workbook: Opened Excel workbook
:type workbook: WorkbookType
:param sheet_name: Sheet name
:type sheet_name: SheetType
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:return: Excel sheet
:rtype: SheetType
"""
if is_xlsx:
return workbook[sheet_name]
return workbook.sheet_by_name(sheet_name)
def get_cell_value(sheet: SheetType, row: int, col: int, is_xlsx: bool) -> Optional[Union[str, int, float]]:
"""Get the cell value
:param sheet: Excel sheet
:type sheet: SheetType
:param row: Line index (0-based)
:type row: int
:param col: Column index (0-based)
:type: int
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:return: cell value
:rtype: Optional[Union[str, int, float]]
"""
if is_xlsx:
# openpyxl uses a 1-based index
cell = sheet.cell(row=row + 1, column=col + 1)
return cell.value
# xlrd uses a 0-base index
return sheet.cell(row, col).value
def get_row(sheet: SheetType, row_index: int, is_xlsx: bool, get_rows=None) -> List[CellType]:
"""Get row in a workbook sheet.
:param sheet: Excel sheet
:type sheet: SheetType
:param row_index: Line index (0-based)
:type row_index: int
:param is_xlsx: True si c'est un fichier XLSX, False si XLS
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:param get_rows: Optional function that returns preloaded rows (from fast_get_sheet_rows)
:type get_rows: Optional[Callable]
:return: List row cells
:rtype: List[CellType]
"""
if is_xlsx:
if get_rows is not None:
# use fast access with aclosure function
rows = get_rows()
else:
rows = list(sheet.rows)
return rows[row_index] if row_index < len(rows) else []
return sheet.row(row_index)
def fast_get_sheet_rows(sheet: Worksheet) -> Callable:
"""Preloads all rows from an Excel sheet for fast access.
This function loads the sheet data only once and returns a function
that provides access to this preloaded data without having to query
the Excel sheet on each access, which significantly improves performance,
particularly with openpyxl.
:param sheet: Excel worksheet (openpyxl.worksheet.worksheet.Worksheet object)
:type sheet: Worksheet
:return: Function that returns the preloaded rows
:rtype: Callable[[], List[Tuple[Cell, ...]]]
Usage example:
> get_rows = fast_get_sheet_rows(sheet)
> rows = get_rows() # Access to preloaded data
> first_row = rows[0] # First row
"""
# Load all sheet rows into memory only once
# This operation can be expensive, but it's performed only once
# load the rows only once.
preloaded_data = list(sheet.rows)
def get_rows():
"""Inner function (clodure function) that returns the preloaded data.
This function doesn't reload the data on each call,
it simply returns the reference to the already loaded data.
:return: List of preloaded rows
:rtype: List[Tuple[Cell, ...]]
"""
return preloaded_data
return get_rows
def get_row_slice(sheet: SheetType, row_index: int, start_col: int, end_col: int, is_xlsx: bool,
get_rows: Callable = None) -> Union[Tuple[CellType], List[CellType]]:
"""Get a row slice.
:param sheet: Excel sheet
:type sheet: SheetType
:param row_index: Line index (0-based)
:type row_index: int
:param start_col: Index of start column (0-based)
:type start_col: int
:param end_col: Index of end column (0-based)
:type end_col: int
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:param get_rows: Optional function that returns preloaded rows (from fast_get_sheet_rows)
:type get_rows: Optional[Callable]
:return: List of cells in the selected slice
:rtype: List[CellType]
"""
if is_xlsx:
if get_rows is not None:
rows = get_rows()
else:
rows = list(sheet.rows)
return rows[row_index][start_col:end_col] if row_index < len(rows) else []
return sheet.row_slice(row_index, start_col, end_col)
def convert_empty(cell_value: Optional[Union[str, int, float]]) -> Optional[Union[str, int, float]]:
"""Convert empty string into None
:param cell_value: Cell value
:type cell_value: Optional[Union[str, int, float]]
>>> convert_empty('')
>>> convert_empty('data')
'data'
>>> convert_empty(123)
123
"""
if cell_value == '':
return None
return cell_value
def get_num_rows(sheet: SheetType, is_xlsx: bool, get_rows: Callable = None) -> int:
"""Get the number of lines of an Excel sheet. Note that openpyxl in read_only mode can return "ghost" rows
at the end (ReadOnlyCell cells with no actual value but formatting information even for empty rows).
:param sheet: Excel sheet
:type sheet: SheetType
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:param get_rows: Optional function that returns preloaded rows (from fast_get_sheet_rows)
:type get_rows: Optional[Callable]
:return: Number of lines
:rtype: int
"""
if is_xlsx:
if get_rows is not None:
return len(list(get_rows()))
else:
return len(list(sheet.rows))
return sheet.nrows
def is_type_cell_empty(cell, is_xlsx: bool) -> bool:
"""Check is a cell is empty.
:param sheet: Excel sheet
:type sheet: SheetType
:param row: Line index (0-based)
:type row: int
:param col: Column index (0-based)
:type: int
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:return: True if cell is empty, else returns False
:rtype: bool
"""
if is_xlsx:
return cell.value in [None, '']
return cell.ctype == XL_CELL_EMPTY
def get_sheet_name(sheet: SheetType, is_xlsx: bool) -> str:
"""Get the name of the current sheet
:param sheet: Excel sheet
:type sheet: SheetType
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:return: Name of the sheet
:rtype: str
"""
if is_xlsx:
return sheet.title
return sheet.name
def all_rows(sh: Worksheet, is_xlsx: bool, start: int = 0, get_rows: Callable = None) -> Generator[list, None, None]:
"""Returns all rows of the xls(x) sheet starting from start row.
:param sh: sheet: Excel sheet
:type sheet: SheetType
:param start: The starting row index (0-based).
:type start: int
:param get_rows: Optional function that returns preloaded rows (from fast_get_sheet_rows)
:type get_rows: Optional[Callable]
:return: A generator yielding all rows from the specified starting index.
:rtype: Generator[list, None, None]
"""
return (get_row(sh, x, is_xlsx, get_rows) for x in range(start, get_num_rows(sh, is_xlsx, get_rows)))
def correct_cell_int_to_str(v: Optional[Union[str, int, float]]) -> Optional[Union[str, int, float]]:
"""Ensure that int values in "id" cells are read as strings containing the int and
do not use the automatic float conversion from xlrd or openpyxl
:param v: cell value to convert
:type v: Optional[Union[str, int, float]]
:return: corrected cell value
:rtype: Optional[Union[str, int, float]]
>>> correct_cell_int_to_str(123)
'123'
>>> correct_cell_int_to_str(123.0)
'123'
>>> correct_cell_int_to_str('abc')
'abc'
>>> correct_cell_int_to_str(None)
"""
if not isinstance(v, str) and v is not None:
value = str(int(v))
if value.endswith('.0'):
value = value[:-2]
else:
value = v
return value
def get_all_sheets(workbook: WorkbookType, is_xlsx: bool) -> Iterator[SheetType]:
"""Get all sheets from an Excel workbook.
:param workbook: Opened Excel workbook
:type workbook: WorkbookType
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:return: Iterator of all sheets in the workbook
:rtype: Iterator[SheetType]
"""
if is_xlsx:
for sheet in workbook.worksheets:
yield sheet
else:
for i in range(workbook.nsheets):
yield workbook.sheet_by_index(i)
def get_sheet_names(workbook: WorkbookType, is_xlsx: bool) -> List[str]:
"""Get all sheet names from an Excel workbook.
:param workbook: Opened Excel workbook
:type workbook: WorkbookType
:param is_xlsx: True if this is an XLSX workbook, False if XLS
:type is_xlsx: bool
:return: List of sheet names
:rtype: List[str]
"""
if is_xlsx:
return workbook.sheetnames
return workbook.sheet_names()

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# Utils for yang <-> legacy format conversion
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
Utils for yang <-> legacy format conversion
===========================================
Format conversion utils.
"""
from pathlib import Path
from copy import deepcopy
from typing import Dict, Union, List, Any, NamedTuple
import json
import os
import oopt_gnpy_libyang as ly
from gnpy.yang.precision_dict import PRECISION_DICT
ELEMENTS_KEY = 'elements'
ROADM_KEY = 'Roadm'
PARAMS_KEY = 'params'
METADATA_KEY = 'metadata'
LOCATION_KEY = 'location'
DEGREE_KEY = 'degree_uid'
PATH_REQUEST_KEY = 'path-request'
RESPONSE_KEY = 'response'
SPECTRUM_KEY = 'spectrum'
LOSS_COEF_KEY = 'loss_coef'
LOSS_COEF_KEY_PER_FREQ = 'loss_coef_per_frequency'
RAMAN_COEF_KEY = 'raman_coefficient'
RAMAN_EFFICIENCY_KEY = 'raman_efficiency'
EQPT_TYPES = ['Edfa', 'Transceiver', 'Fiber', 'Roadm']
EDFA_CONFIG_KEYS = ['nf_fit_coeff', 'nf_ripple', 'gain_ripple', 'dgt']
SIM_PARAMS_KEYS = ['raman_params', 'nli_params']
TOPO_NMSP = 'gnpy-network-topology:topology'
EQPT_NMSP = 'gnpy-eqpt-config:equipment'
SERV_NMSP = 'gnpy-path-computation:services'
RESP_NMSP = 'gnpy-path-computation:responses'
EDFA_CONFIG_NMSP = 'gnpy-edfa-config:edfa-config'
SIM_PARAMS_NMSP = 'gnpy-sim-params:sim-params'
SPECTRUM_NMSP = 'gnpy-spectrum:spectrum'
class PrettyFloat(float):
""""A float subclass for formatting according to specific fraction digit requirements.
>>> PrettyFloat(3.1245)
3.12
>>> PrettyFloat(100.65, 5)
100.65
>>> PrettyFloat(2.1e-5, 8)
0.000021
>>> PrettyFloat(10, 3)
10.0
>>> PrettyFloat(-0.3110761646066259, 18)
-0.3110761646066259
"""
def __new__(cls, value: float, fraction_digit: int = 2):
"""Create a new instance of PrettyFloat"""
instance = super().__new__(cls, value)
instance.fraction_digit = fraction_digit
instance.value = value
return instance
def __repr__(self) -> str:
"""Return the string representation of the float formatted to the specified fraction digits. It removes
scientific notation ("e-x").
"""
# When fraction digit is over 16, the usual formatting does not works properly because of floating point issues.
# For example -0.3110761646066259 is represented as "-0.311076164606625905". The following function makes
# sure that the unwanted floating point issue does not change the value. Maximum fraction digit in YANG is 18.
if self.fraction_digit in range(0, 19):
temp = str(self.value)
if 'e' in temp or '.' not in temp or self.fraction_digit < 17:
formatted_value = f'{self:.{self.fraction_digit}f}' # noqa E231
if '.' in formatted_value:
formatted_value = formatted_value.rstrip('0')
if formatted_value.endswith('.'):
formatted_value += '0'
return formatted_value
if '.' in temp:
parts = temp.split('.')
formatted_value = parts[0] + '.' + parts[1][0:min(self.fraction_digit, len(parts[1]))]
formatted_value = formatted_value.rstrip('0')
if formatted_value.endswith('.'):
formatted_value += '0'
return formatted_value
return temp
raise ValueError(f'Fraction digit {self.fraction_digit} not handled')
def gnpy_precision_dict() -> Dict[str, int]:
"""Return a dictionary of fraction-digit definitions for GNPy.
Precision correspond to fraction digit number if it is a decimal64 yang type, or 0 if it is an
(u)int < 64 or -1 if it is a string or an (u)int64 type.
:return: Dictionnary mapping key names with digit numbers for values.
:rtype: Dict[str, int]
"""
return PRECISION_DICT
def convert_dict(data: Dict, fraction_digit: int = 2, precision: Union[Dict[str, int], None] = None) \
-> Union[Dict, List, float, int, str, None]:
"""Recursive conversion from float to str, conformed to RFC7951
does not work for int64 (will not returm str as stated in standard)
If nothing is stated precision is using gnpy_precision_dict.
:param data: the input dictionary to convert.
:type data: data: Dict
:param fraction_digit: the number of decimal places to format.
:type fraction_digit: int
:param precision: A dictionary defining precision for specific keys.
:type precision: Union[Dict[str, int], None]
:return: A new dictionary with converted values.
:rtype: Dict
>>> convert_dict({"y": "amp", "t": "vn", "g": 25, "gamma": 0.0016, "p": 21.5, "o": True, \
"output-power": 14.12457896})
{'y': 'amp', 't': 'vn', 'g': '25.0', 'gamma': '0.0016', 'p': '21.5', 'o': True, 'output-power': '14.12457896'}
"""
if not precision:
precision = gnpy_precision_dict()
if isinstance(data, dict):
for k, v in data.items():
fraction_digit = precision.get(k, 2)
data[k] = convert_dict(v, fraction_digit, precision=precision)
elif isinstance(data, list):
temp = deepcopy(data)
for i, el in enumerate(temp):
if isinstance(el, float):
data[i] = PrettyFloat(el, fraction_digit)
data[i] = str(data[i])
else:
data[i] = convert_dict(el, fraction_digit=fraction_digit, precision=precision)
elif isinstance(data, bool):
return data
elif isinstance(data, int):
data = PrettyFloat(data)
data.fraction_digit = fraction_digit
if fraction_digit > 0:
return str(data)
if fraction_digit < 0:
return data
return int(data)
elif isinstance(data, float):
data = PrettyFloat(data)
data.fraction_digit = fraction_digit
return str(data)
return data
def convert_back(data: Dict, fraction_digit: Union[int, None] = None, precision: Union[Dict[str, int], None] = None) \
-> Union[Dict, List, float, int, str, None]:
"""Recursively convert strings back to their original types int, float according to RFC7951.
:param data: the input dictionary to convert.
:type data: Dict
:param fraction_digit: the number of decimal places to format.
:type fraction_digit: Union[int, None]
:param precision: A dictionary defining precision for specific keys.
:type precision: Union[Dict[str, int], None]
:return: A new dictionary with converted values.
:rtype: Dict
>>> a = {'y': 'amp', 't': 'vn', 'N': '25', 'gamma': '0.0000000000000016', 'p': '21.50', 'o': True, \
'output-power': '14.12458'}
>>> convert_back({'a': a, 'delta_power_range_db': ['12.3', '10.6', True]})
{'a': {'y': 'amp', 't': 'vn', 'N': 25, 'gamma': 1.6e-15, 'p': '21.50', 'o': True, 'output-power': 14.12458}, \
'delta_power_range_db': ['12.3', '10.6', True]}
"""
if not precision:
precision = gnpy_precision_dict()
if isinstance(data, dict):
for k, v in data.items():
fraction_digit = None
if k in precision:
fraction_digit = precision[k]
data[k] = convert_back(v, fraction_digit, precision=precision)
elif isinstance(data, list):
for i, el in enumerate(data):
if isinstance(el, str) and fraction_digit not in [None, -1]:
data[i] = float(data[i])
else:
data[i] = convert_back(el, fraction_digit=fraction_digit, precision=precision)
elif isinstance(data, (bool, int, float)):
return data
elif isinstance(data, str) and fraction_digit is not None:
if fraction_digit > 0:
return float(data)
if fraction_digit < 0:
return data
return int(data)
return data
def model_path() -> Path:
"""Filesystem path to YANG models.
return: path to the GNPy YANG modules.
rtype: Path
"""
return Path(__file__).parent.parent / 'yang'
def external_yang() -> Path:
"""Filesystem to the IETF external yang modules.
return: path to the IETF modules.
rtype: Path
"""
return Path(__file__).parent.parent / 'yang' / 'ext'
def yang_lib() -> Path:
"""Path to the json library of needed yang modules.
return: path to the library describing all modules and revisions for this gnpy release.
rtype: Path
"""
return Path(__file__).parent.parent / 'yang' / 'yang-library-gnpy.json'
def _create_context(yang_library) -> ly.Context:
"""Prepare a libyang context for validating data against GNPy YANG models.
:param yang_library: path to the library describing all modules and revisions to be considered for the formatted
string generation.
:type yang_library: Path
:return: Context used to hold all information about schemas.
:rtype: ly.Context
"""
ly.set_log_options(ly.LogOptions.Log | ly.LogOptions.Store)
ctx = ly.Context(str(model_path()) + os.pathsep + str(external_yang()),
ly.ContextOptions.AllImplemented | ly.ContextOptions.DisableSearchCwd)
with open(yang_library, 'r', encoding='utf-8') as file:
data = json.load(file)
yang_modules = [{'name': e['name'], 'revision': e['revision']}
for e in data['ietf-yang-library:modules-state']['module']]
for module in yang_modules:
ctx.load_module(module['name'], revision=module['revision'])
return ctx
class ErrorMessage(NamedTuple):
# pylint: disable=C0115
what: str
where: str
def load_data(s: str, yang_library: Path = yang_lib()) -> ly.DataNode:
"""Load data from YANG-based JSON input and validate them.
:param data: a string contating the json data to be loaded.
:type data: str
:param yang_library: path to the library describing all modules and revisions to be considered for the formatted
string generation.
:type yang_library: Path
:return: DataNode containing the loaded data
:rtype: ly.DataNode
"""
ctx = _create_context(yang_library)
try:
data = ctx.parse_data(s, ly.DataFormat.JSON,
ly.ParseOptions.Strict | ly.ParseOptions.Ordered,
ly.ValidationOptions.Present
| ly.ValidationOptions.MultiError)
except ly.Error as exc:
raise ly.Error(exc, [ErrorMessage(err.message, err.path) for err in ctx.errors()]) from None
return data
def dump_data(data: Dict, yang_library: Path = yang_lib()) -> str:
"""Creates a formatted string using oopt-gnpy-libyang.
:param data: a json dict with data already formatted
:type data: Dict
:param yang_library: path to the library describing all modules and revisions to be considered for the formatted
string generation.
:type yang_library: Path
:return: formatted string data
:rtype: str
"""
return load_data(json.dumps(data), yang_library).print(ly.DataFormat.JSON, ly.PrintFlags.WithSiblings)
def convert_degree(json_data: Dict) -> Dict:
"""Convert legacy json topology format to gnpy yang format revision 2025-01-20:
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: Dict
"""
for elem in json_data[ELEMENTS_KEY]:
if elem['type'] == ROADM_KEY and PARAMS_KEY in elem:
new_targets = []
for equalization_type in ['per_degree_pch_out_db', 'per_degree_psd_out_mWperGHz',
'per_degree_psd_out_mWperSlotWidth']:
targets = elem[PARAMS_KEY].pop(equalization_type, None)
if targets:
new_targets.extend([{DEGREE_KEY: degree, equalization_type: target}
for degree, target in targets.items()])
if new_targets:
elem[PARAMS_KEY]['per_degree_power_targets'] = new_targets
return json_data
def convert_back_degree(json_data: Dict) -> Dict:
"""Convert gnpy yang format back to legacy json topology format.
:param json_data: The input JSON topology data to convert back.
:type json_data: Dict
:return: the converted JSON data
:rtype: Dict
"""
for elem in json_data[ELEMENTS_KEY]:
if elem['type'] != ROADM_KEY or PARAMS_KEY not in elem:
continue
power_targets = elem[PARAMS_KEY].pop('per_degree_power_targets', None)
if not power_targets:
continue
# Process each power target
process_power_targets(elem, power_targets)
return json_data
def process_power_targets(elem: Dict, power_targets: List[Dict]) -> None:
"""Process power targets and update element parameters.
:param elem: The element to update
:type elem: Dict
:param power_targets: List of power target configurations
:type power_targets: List[Dict]
"""
equalization_types = [
'per_degree_pch_out_db',
'per_degree_psd_out_mWperGHz',
'per_degree_psd_out_mWperSlotWidth'
]
for target in power_targets:
degree_uid = target[DEGREE_KEY]
for eq_type in equalization_types:
if eq_type not in target:
continue
# Initialize the equalization type dict if needed
if eq_type not in elem[PARAMS_KEY]:
elem[PARAMS_KEY][eq_type] = {}
# Set the value for this degree
elem[PARAMS_KEY][eq_type][degree_uid] = target[eq_type]
def convert_loss_coeff_list(json_data: Dict) -> Dict:
"""Convert legacy json topology format to gnpy yang format revision 2025-01-20:
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: Dict
"""
for elem in json_data[ELEMENTS_KEY]:
if PARAMS_KEY in elem and LOSS_COEF_KEY in elem[PARAMS_KEY] \
and isinstance(elem[PARAMS_KEY][LOSS_COEF_KEY], dict):
loss_coef_per_frequency = elem[PARAMS_KEY].pop(LOSS_COEF_KEY)
loss_coef_list = loss_coef_per_frequency.pop('loss_coef_value', None)
frequency_list = loss_coef_per_frequency.pop('frequency', None)
if loss_coef_list:
new_loss_coef_per_frequency = [{'frequency': f, 'loss_coef_value': v}
for f, v in zip(frequency_list, loss_coef_list)]
elem[PARAMS_KEY][LOSS_COEF_KEY_PER_FREQ] = new_loss_coef_per_frequency
return json_data
def convert_back_loss_coeff_list(json_data: Dict) -> Dict:
"""Convert gnpy yang format revision 2025-01-20 back to legacy json topology format
:param json_data: The input JSON topology data to convert back
:type json_data: Dict
:return: the converted JSON data
:rtype: Dict
"""
for elem in json_data[ELEMENTS_KEY]:
if PARAMS_KEY in elem and LOSS_COEF_KEY_PER_FREQ in elem[PARAMS_KEY]:
loss_coef_per_frequency = elem[PARAMS_KEY].pop(LOSS_COEF_KEY_PER_FREQ)
if loss_coef_per_frequency:
new_loss_coef_per_frequency = {
'frequency': [item['frequency'] for item in loss_coef_per_frequency],
'loss_coef_value': [item['loss_coef_value'] for item in loss_coef_per_frequency]}
elem[PARAMS_KEY]['loss_coef'] = new_loss_coef_per_frequency
return json_data
def convert_design_band(json_data: Dict) -> Dict:
"""Convert legacy json topology format to gnpy yang format revision 2025-01-20:
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: Dict
"""
for elem in json_data[ELEMENTS_KEY]:
if elem['type'] == ROADM_KEY and PARAMS_KEY in elem:
new_targets = []
targets = elem[PARAMS_KEY].pop('per_degree_design_bands', None)
if targets:
new_targets.extend([{DEGREE_KEY: degree, 'design_bands': target}
for degree, target in targets.items()])
if new_targets:
elem[PARAMS_KEY]['per_degree_design_bands_targets'] = new_targets
return json_data
def convert_back_design_band(json_data: Dict) -> Dict:
"""Convert gnpy yang format revision 2025-01-20 back to legacy json topology format
:param json_data: The input JSON topology data to convert back
:type json_data: Dict
:return: the converted JSON data
:rtype: Dict
"""
for elem in json_data[ELEMENTS_KEY]:
if elem['type'] == ROADM_KEY and PARAMS_KEY in elem:
targets = elem[PARAMS_KEY].pop('per_degree_design_bands_targets', None)
if targets:
design_bands = {}
for target in targets:
design_bands[target[DEGREE_KEY]] = target['design_bands']
if design_bands:
elem[PARAMS_KEY]['per_degree_design_bands'] = design_bands
return json_data
def convert_range_to_dict(range_values: List[float]) -> Dict[str, float]:
"""Convert a range list to a dictionary format:
:param range_values: range of loat values defined with the format [min, max, step].
:type range_value: List[float]
:return: range formatted as a dict {"min_value": min, "max_value": max, "step": step}
:rtype: Dict[str, float]
"""
return {
'min_value': range_values[0],
'max_value': range_values[1],
'step': range_values[2]
}
def process_span_data(span: Dict) -> None:
"""Convert Span data with range in dict format
:param span: The span data to process.
:type span: Dict
"""
if 'delta_power_range_dict_db' in span:
return
if 'delta_power_range_db' not in span:
raise KeyError('delta_power_range or delta_power_range_dict_db missing in Span dict.')
delta_power_range_db = span.get('delta_power_range_db', [0, 0, 0])
span['delta_power_range_dict_db'] = convert_range_to_dict(delta_power_range_db)
del span['delta_power_range_db']
def process_si_data(si: Dict) -> None:
"""Convert Span data with range in dict format
:param si: The span data to process.
:type si: Dict
"""
if 'power_range_dict_db' in si:
return
if 'power_range_db' not in si:
raise KeyError('power_range_db or power_range_dict_db missing in SI dict.')
power_range_db = si.get('power_range_db', [0, 0, 0])
si['power_range_dict_db'] = convert_range_to_dict(power_range_db)
del si['power_range_db']
def convert_delta_power_range(json_data: Dict) -> Dict:
"""Convert legacy json equipment format to GNPy yang format revision 2025-01-20
:param json_data: the input JSON data to convert.
:type json_data: Dict
:return: The converted JSON data.
:rtype: Dict
"""
if 'Span' in json_data:
for span in json_data['Span']:
process_span_data(span)
if 'SI' in json_data:
for si in json_data['SI']:
process_si_data(si)
return json_data
def convert_back_delta_power_range(json_data: Dict) -> Dict:
"""Convert Yang JSON revision 2025-01-20 equipment format to legacy GNPy format.
:param json_data: the input JSON data to convert.
:type json_data: Dict
:return: The converted JSON data.
:rtype: Dict
"""
if 'Span' in json_data and 'delta_power_range_dict_db' in json_data['Span'][0]:
delta_power_range_db = json_data['Span'][0]['delta_power_range_dict_db']
json_data['Span'][0]['delta_power_range_db'] = [
delta_power_range_db['min_value'],
delta_power_range_db['max_value'],
delta_power_range_db['step']]
del json_data['Span'][0]['delta_power_range_dict_db']
if 'SI' in json_data and 'power_range_dict_db' in json_data['SI'][0]:
power_range_db = json_data['SI'][0]['power_range_dict_db']
json_data['SI'][0]['power_range_db'] = [
power_range_db['min_value'],
power_range_db['max_value'],
power_range_db['step']]
del json_data['SI'][0]['power_range_dict_db']
return json_data
def add_missing_default_type_variety(json_data: Dict) -> Dict:
"""Case of ROADM: legacy does not enforce type_variety to be present.
This utils ensures that 'default' type_variety is inserted if the key is missing.
:param json_data: the input JSON data to convert.
:type json_data: Dict
:return: The converted JSON data.
:rtype: Dict
"""
if 'Roadm' not in json_data:
return json_data
for i, elem in enumerate(json_data['Roadm']):
if 'type_variety' not in elem:
# make sure type_variety is the first key in the elem
temp = {'type_variety': 'default'}
temp.update(elem)
json_data['Roadm'][i] = temp
break
return json_data
def remove_null_region_city(json_data: Dict) -> Dict:
"""if present, name should not be None.
:param json_data: the input JSON data to convert.
:type json_data: Dict
:return: The converted JSON data.
:rtype: Dict
"""
for elem in json_data[ELEMENTS_KEY]:
if "metadata" in elem and "location" in elem[METADATA_KEY]:
for name in ['city', 'region']:
if name in elem[METADATA_KEY][LOCATION_KEY] \
and elem[METADATA_KEY][LOCATION_KEY][name] is None:
elem[METADATA_KEY][LOCATION_KEY][name] = ""
return json_data
def remove_union_that_fail(json_data: Dict) -> Dict:
"""Convert GNPy legacy JSON request format to GNPy yang format revision 2025-01-20
If present "N": or "M": should not contain empy data.
If present max-nb-of-channel should not contain empty data.
:param json_data: the input JSON data to convert.
:type json_data: Dict
:return: The converted JSON data.
:rtype: Dict
"""
for elem in json_data[PATH_REQUEST_KEY]:
te = elem['path-constraints']['te-bandwidth']
freq_slot = te.get('effective-freq-slot', None)
if freq_slot:
for slot in freq_slot:
if slot.get('N', None) is None:
slot.pop('N', None)
if slot.get('M', None) is None:
slot.pop('M', None)
if not slot:
te['effective-freq-slot'].remove(slot)
if not te['effective-freq-slot']:
te.pop('effective-freq-slot', None)
for attribute in ['max-nb-of-channel', 'trx_mode', 'output-power']:
if te.get(attribute) is None:
te.pop(attribute, None)
return json_data
def convert_none_to_empty(json_data: Any):
"""Convert all instances of None in the input to [None].
This function recursively traverses the input and replaces any None
values with a list containing None. If the input is already a list
containing None, it returns the input unchanged.
:param json_data: The input data to process, which can be of any type.
:type json_data: Any
:return: A new representation of the input with None values replaced by [None].
:rtype: Any
:example:
>>> a = {'uid': '[930/WRT-2-2-SIG=>923/WRT-1-9-SIG]-923/AMP-1-13', 'type_variety': 'AMP',
... 'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}},
... 'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'AMP_LOW_C',
... 'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0,
... 'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'AMP_LOW_L',
... 'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0,
... 'f_min': 186.1, 'f_max': 190.9}}]}
>>> convert_none_to_empty(a)
{'uid': '[930/WRT-2-2-SIG=>923/WRT-1-9-SIG]-923/AMP-1-13', 'type_variety': 'AMP', \
'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}}, \
'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'AMP_LOW_C', \
'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': [None], 'tilt_target': 0.0, \
'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'AMP_LOW_L', \
'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': [None], 'tilt_target': 0.0, \
'f_min': 186.1, 'f_max': 190.9}}]}
"""
if json_data == [None]:
# already conformed
return json_data
if isinstance(json_data, dict):
for key, value in json_data.items():
json_data[key] = convert_none_to_empty(value)
elif isinstance(json_data, list):
for i, elem in enumerate(json_data):
json_data[i] = convert_none_to_empty(elem)
elif json_data is None:
return [None]
return json_data
def convert_empty_to_none(json_data: Any):
"""Convert all instances of [None] in the input to None.
This function recursively traverses the input data and replaces any
lists containing a single None element with None. If the input is
already None, it returns None unchanged.
:param json_data: The input data to process, which can be of any type.
:type json_data: Any
:return: A new representation of the input with [None] replaced by None.
:rtype: Any
>>> json_data = {
... "uid": "[930/WRT-2-2-SIG=>923/WRT-1-9-SIG]-923/AMP-1-13",
... "type_variety": "AMP",
... "metadata": {
... "location": {
... "latitude": 0.000000,
... "longitude": 0.000000,
... "city": "Zion",
... "region": ""
... }
... },
... "type": "Multiband_amplifier",
... "amplifiers": [{
... "type_variety": "AMP_LOW_C",
... "operational": {
... "gain_target": 12.22,
... "delta_p": 4.19,
... "out_voa": [None],
... "tilt_target": 0.00,
... "f_min": 191.3,
... "f_max": 196.1
... }
... }, {
... "type_variety": "AMP_LOW_L",
... "operational": {
... "gain_target": 12.05,
... "delta_p": 4.19,
... "out_voa": [None],
... "tilt_target": 0.00,
... "f_min": 186.1,
... "f_max": 190.9
... }
... }
... ]
... }
>>> convert_empty_to_none(json_data)
{'uid': '[930/WRT-2-2-SIG=>923/WRT-1-9-SIG]-923/AMP-1-13', 'type_variety': 'AMP', \
'metadata': {'location': {'latitude': 0.0, 'longitude': 0.0, 'city': 'Zion', 'region': ''}}, \
'type': 'Multiband_amplifier', 'amplifiers': [{'type_variety': 'AMP_LOW_C', \
'operational': {'gain_target': 12.22, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0, \
'f_min': 191.3, 'f_max': 196.1}}, {'type_variety': 'AMP_LOW_L', \
'operational': {'gain_target': 12.05, 'delta_p': 4.19, 'out_voa': None, 'tilt_target': 0.0, \
'f_min': 186.1, 'f_max': 190.9}}]}
"""
if isinstance(json_data, dict):
for key, value in json_data.items():
json_data[key] = convert_empty_to_none(value)
elif isinstance(json_data, list):
if len(json_data) == 1 and json_data[0] is None:
return None
for i, elem in enumerate(json_data):
json_data[i] = convert_empty_to_none(elem)
return json_data
def remove_namespace_context(json_data: Union[Dict, List, float, int, str, bool, None], namespace: str) \
-> Union[Dict, List, float, int, str, bool, None]:
"""Serialisation with yang introduces a namespace in values that
are defined as identity. this function filter them out.
:param json_data: The input JSON topology data to process.
:type json_data: Union[Dict, List, float, int, str, bool, None]
:param namespace: a namespace string
:type namespace: str
:return: the converted JSON data
:rtype: Union[Dict, List, float, int, str, bool, None]
>>> a = [{"a": 123, "b": "123:alkdje"}, {"a": 456, "c": "123", "d": "123:123"}]
>>> remove_namespace_context(a, "123:")
[{'a': 123, 'b': 'alkdje'}, {'a': 456, 'c': '123', 'd': '123'}]
"""
if isinstance(json_data, dict):
for key, value in json_data.items():
json_data[key] = remove_namespace_context(value, namespace)
elif isinstance(json_data, list):
for i, elem in enumerate(json_data):
json_data[i] = remove_namespace_context(elem, namespace)
elif isinstance(json_data, str) and namespace in json_data:
return json_data.split(namespace)[1]
return json_data
def convert_nf_coef(json_data: Dict) -> Dict:
"""Convert gnpy legacy format yang topology format.
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: dict
"""
if 'Edfa' not in json_data:
return json_data
for edfa in json_data['Edfa']:
if 'nf_coef' in edfa and not isinstance(edfa['nf_coef'][0], dict):
nf_coef = edfa.pop('nf_coef')
new_nf_coef = [{'coef_order': i, 'nf_coef': c} for i, c in enumerate(nf_coef)]
edfa['nf_coef'] = new_nf_coef
return json_data
def convert_back_nf_coef(json_data: Dict) -> Dict:
"""Convert gnpy yang format back to legacy json topology format.
:param json_data: The input JSON topology data to convert back.
:type json_data: Dict
:return: the converted back JSON data
:rtype: dict
"""
if 'Edfa' not in json_data:
return json_data
for edfa in json_data['Edfa']:
if 'nf_coef' in edfa and isinstance(edfa['nf_coef'][0], dict):
nf_coef = edfa.pop('nf_coef')
sorted_nf_coef = sorted(nf_coef, key=lambda x: x['coef_order'])
new_nf_coef = [c['nf_coef'] for c in sorted_nf_coef]
edfa['nf_coef'] = new_nf_coef
return json_data
def convert_nf_fit_coef(json_data: Dict) -> Dict:
"""Convert gnpy legacy format yang topology format.
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: dict
"""
if 'nf_fit_coeff' in json_data and not isinstance(json_data['nf_fit_coeff'][0], dict):
nf_coef = json_data.pop('nf_fit_coeff')
new_nf_coef = [{'coef_order': i, 'nf_coef': c} for i, c in enumerate(nf_coef)]
json_data['nf_fit_coeff'] = new_nf_coef
return json_data
def convert_back_nf_fit_coef(json_data: Dict) -> Dict:
"""Convert gnpy yang format back to legacy json topology format.
:param json_data: The input JSON topology data to convert back.
:type json_data: Dict
:return: the converted back JSON data
:rtype: dict
"""
if 'nf_fit_coeff' in json_data and isinstance(json_data['nf_fit_coeff'][0], dict):
nf_coef = json_data.pop('nf_fit_coeff')
sorted_nf_coef = sorted(nf_coef, key=lambda x: x['coef_order'])
new_nf_coef = [c['nf_coef'] for c in sorted_nf_coef]
json_data['nf_fit_coeff'] = new_nf_coef
return json_data
def convert_raman_coef(json_data: Dict) -> Dict:
"""Convert gnpy legacy format yang topology format.
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: dict
"""
for elem in json_data[ELEMENTS_KEY]:
if PARAMS_KEY in elem and RAMAN_COEF_KEY in elem[PARAMS_KEY] \
and 'g0' in elem[PARAMS_KEY][RAMAN_COEF_KEY]:
raman_coef = elem[PARAMS_KEY].pop(RAMAN_COEF_KEY)
g0_list = raman_coef.pop('g0', [])
frequency_offset_list = raman_coef.pop('frequency_offset', [])
if frequency_offset_list:
new_raman_coef = {'reference_frequency': raman_coef['reference_frequency'],
'g0_per_frequency': [{'frequency_offset': f, 'g0': v}
for f, v in zip(frequency_offset_list, g0_list)]}
elem[PARAMS_KEY][RAMAN_COEF_KEY] = new_raman_coef
return json_data
def convert_back_raman_coef(json_data: Dict) -> Dict:
"""Convert gnpy yang format back to legacy json topology format.
:param json_data: The input JSON topology data to convert back.
:type json_data: Dict
:return: the converted back JSON data
:rtype: dict
"""
for elem in json_data[ELEMENTS_KEY]:
if PARAMS_KEY in elem and RAMAN_COEF_KEY in elem[PARAMS_KEY] \
and 'g0_per_frequency' in elem[PARAMS_KEY][RAMAN_COEF_KEY]:
raman_coef = elem[PARAMS_KEY].pop(RAMAN_COEF_KEY)
g0_list = [g['g0'] for g in raman_coef.pop('g0_per_frequency', [])]
frequency_offset_list = [f['frequency_offset'] for f in raman_coef.pop('g0_per_frequency', [])]
if frequency_offset_list:
new_raman_coef = {'reference_frequency': raman_coef['reference_frequency'],
'g0': g0_list,
'frequency_offset': frequency_offset_list}
elem[PARAMS_KEY][RAMAN_COEF_KEY] = new_raman_coef
return json_data
def convert_raman_efficiency(json_data: Dict) -> Dict:
"""Convert gnpy legacy format yang topology format.
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: dict
"""
if 'RamanFiber' not in json_data:
return json_data
for fiber_eqpt in json_data['RamanFiber']:
if RAMAN_EFFICIENCY_KEY in fiber_eqpt \
and 'cr' in fiber_eqpt[RAMAN_EFFICIENCY_KEY]:
raman_efficiency = fiber_eqpt.pop(RAMAN_EFFICIENCY_KEY)
cr_list = raman_efficiency.pop('cr', [])
frequency_offset_list = raman_efficiency.pop('frequency_offset', [])
if frequency_offset_list:
new_raman_efficiency = [{'frequency_offset': f, 'cr': v}
for f, v in zip(frequency_offset_list, cr_list)]
fiber_eqpt[RAMAN_EFFICIENCY_KEY] = new_raman_efficiency
return json_data
def convert_back_raman_efficiency(json_data: Dict) -> Dict:
"""Convert gnpy yang format back to legacy json topology format.
:param json_data: The input JSON topology data to convert back.
:type json_data: Dict
:return: the converted back JSON data
:rtype: dict
"""
if 'RamanFiber' not in json_data:
return json_data
for fiber_eqpt in json_data['RamanFiber']:
if RAMAN_EFFICIENCY_KEY in fiber_eqpt and isinstance(fiber_eqpt[RAMAN_EFFICIENCY_KEY], list):
raman_efficiency = fiber_eqpt.pop(RAMAN_EFFICIENCY_KEY)
cr_list = [c['cr'] for c in raman_efficiency]
frequency_offset_list = [f['frequency_offset'] for f in raman_efficiency]
if frequency_offset_list:
old_raman_efficiency = {'cr': cr_list,
'frequency_offset': frequency_offset_list}
fiber_eqpt[RAMAN_COEF_KEY] = old_raman_efficiency
return json_data
def reorder_keys(data_list: List, key: str) -> List:
"""Roarder item in a dict placing the key (the key of a list with YANG meaning) first.
This is required because oopt-gnpy-libyang does not recognize the key when it is not placed first in the data node.
:param json_data: the list of dictionary items.
:type data_list: List
:return: the converted back JSON data
:rtype: List
"""
for item in data_list:
index_value = item.pop(key, None)
if index_value is not None:
# Place key first
new_item = {key: index_value}
# add other items
new_item.update(item)
# replace old element with new element
for k in list(item.keys()):
item.pop(k)
item.update(new_item)
return data_list
# next functions because ly requires that the key of a list be in the first position in the item
def reorder_route_objects(json_data: Dict) -> Dict:
"""Make sure that the index of a route object is placed first in the object.
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: dict
"""
for request in json_data['path-request']:
if "explicit-route-objects" in request:
request["explicit-route-objects"]["route-object-include-exclude"] = \
reorder_keys(request["explicit-route-objects"]["route-object-include-exclude"], "index")
return json_data
def reorder_lumped_losses_objects(json_data: Dict) -> Dict:
"""Make sure that the position of a lumped loss object is placed first in the object.
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: dict
"""
for element in json_data['elements']:
if "params" in element and "lumped_losses" in element["params"]:
element["params"]["lumped_losses"] = reorder_keys(element["params"]["lumped_losses"], "position")
return json_data
def reorder_raman_pumps(json_data: Dict) -> Dict:
"""Make sure that the frequency of a Raman pum object is placed first in the object.
:param json_data: The input JSON topology data to convert.
:type json_data: Dict
:return: the converted JSON data
:rtype: dict
"""
for element in json_data['elements']:
if "operational" in element and "raman_pumps" in element["operational"]:
element["operational"]["raman_pumps"] = reorder_keys(element["operational"]["raman_pumps"], "frequency")
return json_data

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.topology.request: path computation functionality
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.topology.request
=====================
@@ -16,27 +21,34 @@ See: draft-ietf-teas-yang-path-computation-01.txt
"""
from collections import namedtuple, OrderedDict
from typing import List
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 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.elements import Transceiver, Roadm, Edfa, Multiband_amplifier
from gnpy.core.utils import lin2db, unique_ordered, find_common_range
from gnpy.core.info import create_input_spectral_information, carriers_to_spectral_information, \
demuxed_spectral_information, muxed_spectral_information, SpectralInformation
from gnpy.core import network as network_module
from gnpy.core.exceptions import ServiceError, DisjunctionError
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, tx_power')
DisjunctionParams = namedtuple('DisjunctionParams', 'disjunction_id relaxable link_diverse'
' node_diverse disjunctions_req')
@@ -298,7 +310,9 @@ def compute_constrained_path(network, req):
nodes_list = []
for node in req.nodes_list[:-1]:
nodes_list.append(next(el for el in network if el.uid == node))
total_path = explicit_path(nodes_list, source, destination, network)
if total_path is not None:
return total_path
try:
path_generator = shortest_simple_paths(network, source, destination, weight='weight')
total_path = next(path for path in path_generator if ispart(nodes_list, path))
@@ -332,19 +346,40 @@ def compute_constrained_path(network, req):
return total_path
def filter_si(path: list, equipment: dict, si: SpectralInformation) -> SpectralInformation:
"""Filter spectral information based on the amplifiers common range"""
# First retrieve f_min, f_max spectrum according to amplifiers' spectrum on the path
common_range = find_elements_common_range(path, equipment)
# filter out frequencies that should not be created
filtered_si = []
for band in common_range:
temp = demuxed_spectral_information(si, band)
if temp:
filtered_si.append(temp)
if not filtered_si:
raise ValueError('Defined propagation band does not match amplifiers band.')
return muxed_spectral_information(filtered_si)
def propagate(path, req, equipment):
"""propagates signals in each element according to initial spectrum set by user"""
"""propagates signals in each element according to initial spectrum set by user
Spectrum is specified in request through f_min, f_max and spacing, or initial_spectrum
and amps frequency band on the path is used to filter out frequencies"""
# generates spectrum based on request
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,
spacing=req.spacing, tx_osnr=req.tx_osnr, tx_power=req.tx_power, delta_pdb=req.offset_db)
# filter out frequencies that should not be created
si = filter_si(path, equipment, si)
roadm_osnr = []
for i, el in enumerate(path):
if isinstance(el, Roadm):
si = el(si, degree=path[i + 1].uid, from_degree=path[i - 1].uid)
roadm_osnr.append(el.get_roadm_path(from_degree=path[i - 1].uid, to_degree=path[i + 1].uid).impairment.osnr)
roadm_osnr.append(el.get_impairment('roadm-osnr', si.frequency,
from_degree=path[i - 1].uid, degree=path[i + 1].uid))
else:
si = el(si)
path[0].update_snr(si.tx_osnr)
@@ -354,7 +389,6 @@ def propagate(path, req, equipment):
path[-1].calc_penalties(req.penalties)
return si
def propagate_and_optimize_mode(path, req, equipment):
# if mode is unknown : loops on the modes starting from the highest baudrate fiting in the
# step 1: create an ordered list of modes based on baudrate and power offset
@@ -385,11 +419,13 @@ def propagate_and_optimize_mode(path, req, equipment):
baud_rate=this_br, spacing=req.spacing,
delta_pdb=this_offset, tx_osnr=req.tx_osnr,
tx_power=req.tx_power)
spc_info = filter_si(path, equipment, spc_info)
roadm_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)
roadm_osnr.append(el.get_roadm_path(from_degree=path[i - 1].uid, to_degree=path[i + 1].uid).impairment.osnr)
roadm_osnr.append(el.get_impairment('roadm-osnr', spc_info.frequency,
from_degree=path[i - 1].uid, degree=path[i + 1].uid))
else:
spc_info = el(spc_info)
for this_mode in modes_to_explore:
@@ -1071,7 +1107,7 @@ def deduplicate_disjunctions(disjn):
return local_disjn
def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist, redesign=False):
"""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 !
@@ -1080,6 +1116,10 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
reversed_path_res_list = []
propagated_reversed_path_res_list = []
total_nb_requests = len(pathreqlist)
if redesign:
LOGGER.warning('Redesign the network for each request channel, '
+ 'using the request channel as the reference channel for the design.')
for i, pathreq in enumerate(pathreqlist):
# use the power specified in requests but might be different from the one
@@ -1097,7 +1137,16 @@ 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)
# reversed path is needed for correct spectrum assignment
if redesign:
# this is the legacy case where network was automatically redesigned using the
# request channel as reference (nb and power used for amplifiers total power out)
reversed_path = []
if pathlist[i]:
reversed_path = find_reversed_path(pathlist[i])
network_nodes_for_redesign = pathlist[i] + reversed_path
network_module.design_network(pathreq, network.subgraph(network_nodes_for_redesign), 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)
@@ -1137,6 +1186,7 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
pathreq.tx_osnr = mode['tx_osnr']
pathreq.bit_rate = mode['bit_rate']
pathreq.penalties = mode['penalties']
pathreq.offset_db = mode['equalization_offset_db']
# other blocking reason should not appear at this point
except AttributeError:
pathreq.baud_rate = mode['baud_rate']
@@ -1146,6 +1196,7 @@ def compute_path_with_disjunction(network, equipment, pathreqlist, pathlist):
pathreq.tx_osnr = mode['tx_osnr']
pathreq.bit_rate = mode['bit_rate']
pathreq.penalties = mode['penalties']
pathreq.offset_db = mode['equalization_offset_db']
# reversed path is needed for correct spectrum assignment
reversed_path = find_reversed_path(pathlist[i])
@@ -1212,3 +1263,50 @@ def _penalty_msg(total_path, msg, min_ind):
else:
msg += f'\n\t{pretty} penalty not evaluated'
return msg
def is_adjacent(oms1, oms2):
""" oms1's egress ROADM is oms2's ingress ROADM
"""
return oms1.el_list[-1] == oms2.el_list[0]
def explicit_path(node_list, source, destination, network):
""" if list of nodes leads to adjacent oms, then means that the path is explicit, and no need to compute
the function returns the explicit path (including source and destination ROADMs)
"""
path_oms = []
for elem in node_list:
if hasattr(elem, 'oms'):
path_oms.append(elem.oms)
if not path_oms:
return None
path_oms = unique_ordered(path_oms)
try:
next_node = next(network.successors(source))
source_roadm = next_node if isinstance(next_node, Roadm) else source
previous_node = next(network.predecessors(destination))
destination_roadm = previous_node if isinstance(previous_node, Roadm) else destination
if not (path_oms[0].el_list[0] == source_roadm and path_oms[-1].el_list[-1] == destination_roadm):
return None
except StopIteration:
return None
oms0 = path_oms[0]
path = [source] + oms0.el_list
for oms in path_oms[1:]:
if not is_adjacent(oms0, oms):
return None
oms0 = oms
path.extend(oms.el_list)
path.append(destination)
return unique_ordered(path)
def find_elements_common_range(el_list: list, equipment: dict) -> List[dict]:
"""Find the common frequency range of amps of a given list of elements (for example an OMS or a path)
If there are no amplifiers in the path, then use the SI
"""
amp_bands = [n.params.bands for n in el_list if isinstance(n, (Edfa, Multiband_amplifier))]
return find_common_range(amp_bands, equipment['SI']['default'].f_min, equipment['SI']['default'].f_max,
equipment['SI']['default'].spacing)

View File

@@ -1,6 +1,11 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# gnpy.topology.spectrum_assignment: spectrum assignment functionality
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
"""
gnpy.topology.spectrum_assignment
=================================
@@ -15,28 +20,31 @@ element/oms correspondace
from collections import namedtuple
from logging import getLogger
from gnpy.core.elements import Roadm, Transceiver
from gnpy.core.elements import Roadm, Transceiver, Edfa, Multiband_amplifier
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
from gnpy.topology.request import compute_spectrum_slot_vs_bandwidth, find_elements_common_range
LOGGER = getLogger(__name__)
GUARDBAND = 25e9
class Bitmap:
"""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
def __init__(self, f_min, f_max, grid, guardband=GUARDBAND, bitmap=None):
# n is the min index including guardband. Guardband is required to be sure
# that a channel can be assigned with center frequency fmin (means that its
# slot occupation goes below freq_index_min
n_min = frequency_to_n(f_min - guardband, grid)
n_max = frequency_to_n(f_max + guardband, grid) - 1
n_min = frequency_to_n(f_min, grid)
n_max = frequency_to_n(f_max, grid)
self.n_min = n_min
self.n_max = n_max
self.freq_index_min = frequency_to_n(f_min)
self.freq_index_max = frequency_to_n(f_max)
self.freq_index_min = frequency_to_n(f_min + guardband)
self.freq_index_max = frequency_to_n(f_max - guardband)
self.freq_index = list(range(n_min, n_max + 1))
self.guardband = guardband
if bitmap is None:
self.bitmap = [1] * (n_max - n_min + 1)
elif len(bitmap) == len(self.freq_index):
@@ -83,7 +91,6 @@ class OMS:
self.spectrum_bitmap = []
self.nb_channels = 0
self.service_list = []
# TODO
def __str__(self):
return '\n\t'.join([f'{type(self).__name__} {self.oms_id}',
@@ -98,7 +105,7 @@ class OMS:
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):
def update_spectrum(self, f_min, f_max, guardband=GUARDBAND, 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
@@ -226,6 +233,40 @@ def align_grids(oms_list):
return oms_list
def find_network_freq_range(network, equipment):
"""Find the lowest freq from amps and highest freq among all amps to determine the resulting bitmap
"""
amp_bands = [band for n in network.nodes() if isinstance(n, (Edfa, Multiband_amplifier)) for band in n.params.bands]
min_frequencies = [a['f_min'] for a in amp_bands]
max_frequencies = [a['f_max'] for a in amp_bands]
return min(min_frequencies), max(max_frequencies)
def create_oms_bitmap(oms, equipment, f_min, f_max, guardband, grid):
"""Find the highest low freq from oms amps and lowest high freq among oms amps to determine
the possible bitmap window.
f_min and f_max represent the useable spectrum (not the useable center frequencies)
ie n smaller than frequency_to_n(min_freq, grid) are not useable
"""
n_min = frequency_to_n(f_min, grid)
n_max = frequency_to_n(f_max, grid) - 1
common_range = find_elements_common_range(oms.el_list, equipment)
band0 = common_range[0]
band0_n_min = frequency_to_n(band0['f_min'], grid)
band0_n_max = frequency_to_n(band0['f_max'], grid)
bitmap = [0] * (band0_n_min - n_min) + [1] * (band0_n_max - band0_n_min + 1)
i = 1
while i < len(common_range):
band = common_range[i]
band_n_min = frequency_to_n(band['f_min'], grid)
band_n_max = frequency_to_n(band['f_max'], grid)
bitmap = bitmap + [0] * (band_n_min - band0_n_max - 1) + [1] * (band_n_max - band_n_min + 1)
band0_n_max = band_n_max
i += 1
bitmap = bitmap + [0] * (n_max - band0_n_max)
return bitmap
def build_oms_list(network, equipment):
"""initialization of OMS list in the network
@@ -237,7 +278,15 @@ def build_oms_list(network, equipment):
"""
oms_id = 0
oms_list = []
for node in [n for n in network.nodes() if isinstance(n, Roadm)]:
# identify all vertices of OMS: of course ROADM, but aso links to external chassis transponders
oms_vertices = [n for n in network.nodes() if isinstance(n, Roadm)] +\
[n for n in network.nodes() if isinstance(n, Transceiver)
and not isinstance(next(network.successors(n)), Roadm)]
# determine the size of the bitmap common to all the omses: find min and max frequencies of all amps
# in the network. These gives the band not the center frequency. Thhen we use a reference channel
# slot width (50GHz) to set the f_min, f_max
f_min, f_max = find_network_freq_range(network, equipment)
for node in oms_vertices:
for edge in network.edges([node]):
if not isinstance(edge[1], Transceiver):
nd_in = edge[0] # nd_in is a Roadm
@@ -271,8 +320,9 @@ def build_oms_list(network, equipment):
nd_out.oms_list = []
nd_out.oms_list.append(oms_id)
oms.update_spectrum(equipment['SI']['default'].f_min,
equipment['SI']['default'].f_max, grid=0.00625e12)
bitmap = create_oms_bitmap(oms, equipment, f_min=f_min, f_max=f_max, guardband=GUARDBAND,
grid=0.00625e12)
oms.update_spectrum(f_min, f_max, guardband=GUARDBAND, grid=0.00625e12, existing_spectrum=bitmap)
# oms.assign_spectrum(13,7) gives back (193137500000000.0, 193225000000000.0)
# as in the example in the standard
# oms.assign_spectrum(13,7)
@@ -333,10 +383,11 @@ def aggregate_oms_bitmap(path_oms, oms_list):
'el_id_list': 0,
'el_list': []
}
freq_min = nvalue_to_frequency(spectrum.freq_index_min)
freq_max = nvalue_to_frequency(spectrum.freq_index_max)
freq_min = nvalue_to_frequency(spectrum.n_min)
freq_max = nvalue_to_frequency(spectrum.n_max)
aggregate_oms = OMS(**params)
aggregate_oms.update_spectrum(freq_min, freq_max, grid=0.00625e12, existing_spectrum=bitmap)
aggregate_oms.update_spectrum(freq_min, freq_max, grid=0.00625e12, guardband=spectrum.guardband,
existing_spectrum=bitmap)
return aggregate_oms

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module ietf-network-topology {
yang-version 1.1;
namespace "urn:ietf:params:xml:ns:yang:ietf-network-topology";
prefix nt;
import ietf-inet-types {
prefix inet;
reference
"RFC 6991: Common YANG Data Types";
}
import ietf-network {
prefix nw;
reference
"RFC 8345: A YANG Data Model for Network Topologies";
}
organization
"IETF I2RS (Interface to the Routing System) Working Group";
contact
"WG Web: <https://datatracker.ietf.org/wg/i2rs/>
WG List: <mailto:i2rs@ietf.org>
Editor: Alexander Clemm
<mailto:ludwig@clemm.org>
Editor: Jan Medved
<mailto:jmedved@cisco.com>
Editor: Robert Varga
<mailto:robert.varga@pantheon.tech>
Editor: Nitin Bahadur
<mailto:nitin_bahadur@yahoo.com>
Editor: Hariharan Ananthakrishnan
<mailto:hari@packetdesign.com>
Editor: Xufeng Liu
<mailto:xufeng.liu.ietf@gmail.com>";
description
"This module defines a common base model for a network topology,
augmenting the base network data model with links to connect
nodes, as well as termination points to terminate links
on nodes.
Copyright (c) 2018 IETF Trust and the persons identified as
authors of the code. All rights reserved.
Redistribution and use in source and binary forms, with or
without modification, is permitted pursuant to, and subject
to the license terms contained in, the Simplified BSD License
set forth in Section 4.c of the IETF Trust's Legal Provisions
Relating to IETF Documents
(https://trustee.ietf.org/license-info).
This version of this YANG module is part of RFC 8345;
see the RFC itself for full legal notices.";
revision 2018-02-26 {
description
"Initial revision.";
reference
"RFC 8345: A YANG Data Model for Network Topologies";
}
typedef link-id {
type inet:uri;
description
"An identifier for a link in a topology. The precise
structure of the link-id will be up to the implementation.
The identifier SHOULD be chosen such that the same link in a
real network topology will always be identified through the
same identifier, even if the data model is instantiated in
separate datastores. An implementation MAY choose to capture
semantics in the identifier -- for example, to indicate the
type of link and/or the type of topology of which the link is
a part.";
}
typedef tp-id {
type inet:uri;
description
"An identifier for termination points on a node. The precise
structure of the tp-id will be up to the implementation.
The identifier SHOULD be chosen such that the same termination
point in a real network topology will always be identified
through the same identifier, even if the data model is
instantiated in separate datastores. An implementation MAY
choose to capture semantics in the identifier -- for example,
to indicate the type of termination point and/or the type of
node that contains the termination point.";
}
grouping link-ref {
description
"This grouping can be used to reference a link in a specific
network. Although it is not used in this module, it is
defined here for the convenience of augmenting modules.";
leaf link-ref {
type leafref {
path "/nw:networks/nw:network[nw:network-id=current()/../"+
"network-ref]/nt:link/nt:link-id";
require-instance false;
}
description
"A type for an absolute reference to a link instance.
(This type should not be used for relative references.
In such a case, a relative path should be used instead.)";
}
uses nw:network-ref;
}
grouping tp-ref {
description
"This grouping can be used to reference a termination point
in a specific node. Although it is not used in this module,
it is defined here for the convenience of augmenting
modules.";
leaf tp-ref {
type leafref {
path "/nw:networks/nw:network[nw:network-id=current()/../"+
"network-ref]/nw:node[nw:node-id=current()/../"+
"node-ref]/nt:termination-point/nt:tp-id";
require-instance false;
}
description
"A type for an absolute reference to a termination point.
(This type should not be used for relative references.
In such a case, a relative path should be used instead.)";
}
uses nw:node-ref;
}
augment "/nw:networks/nw:network" {
description
"Add links to the network data model.";
list link {
key "link-id";
description
"A network link connects a local (source) node and
a remote (destination) node via a set of the respective
node's termination points. It is possible to have several
links between the same source and destination nodes.
Likewise, a link could potentially be re-homed between
termination points. Therefore, in order to ensure that we
would always know to distinguish between links, every link
is identified by a dedicated link identifier. Note that a
link models a point-to-point link, not a multipoint link.";
leaf link-id {
type link-id;
description
"The identifier of a link in the topology.
A link is specific to a topology to which it belongs.";
}
container source {
description
"This container holds the logical source of a particular
link.";
leaf source-node {
type leafref {
path "../../../nw:node/nw:node-id";
require-instance false;
}
description
"Source node identifier. Must be in the same topology.";
}
leaf source-tp {
type leafref {
path "../../../nw:node[nw:node-id=current()/../"+
"source-node]/termination-point/tp-id";
require-instance false;
}
description
"This termination point is located within the source node
and terminates the link.";
}
}
container destination {
description
"This container holds the logical destination of a
particular link.";
leaf dest-node {
type leafref {
path "../../../nw:node/nw:node-id";
require-instance false;
}
description
"Destination node identifier. Must be in the same
network.";
}
leaf dest-tp {
type leafref {
path "../../../nw:node[nw:node-id=current()/../"+
"dest-node]/termination-point/tp-id";
require-instance false;
}
description
"This termination point is located within the
destination node and terminates the link.";
}
}
list supporting-link {
key "network-ref link-ref";
description
"Identifies the link or links on which this link depends.";
leaf network-ref {
type leafref {
path "../../../nw:supporting-network/nw:network-ref";
require-instance false;
}
description
"This leaf identifies in which underlay topology
the supporting link is present.";
}
leaf link-ref {
type leafref {
path "/nw:networks/nw:network[nw:network-id=current()/"+
"../network-ref]/link/link-id";
require-instance false;
}
description
"This leaf identifies a link that is a part
of this link's underlay. Reference loops in which
a link identifies itself as its underlay, either
directly or transitively, are not allowed.";
}
}
}
}
augment "/nw:networks/nw:network/nw:node" {
description
"Augments termination points that terminate links.
Termination points can ultimately be mapped to interfaces.";
list termination-point {
key "tp-id";
description
"A termination point can terminate a link.
Depending on the type of topology, a termination point
could, for example, refer to a port or an interface.";
leaf tp-id {
type tp-id;
description
"Termination point identifier.";
}
list supporting-termination-point {
key "network-ref node-ref tp-ref";
description
"This list identifies any termination points on which a
given termination point depends or onto which it maps.
Those termination points will themselves be contained
in a supporting node. This dependency information can be
inferred from the dependencies between links. Therefore,
this item is not separately configurable. Hence, no
corresponding constraint needs to be articulated.
The corresponding information is simply provided by the
implementing system.";
leaf network-ref {
type leafref {
path "../../../nw:supporting-node/nw:network-ref";
require-instance false;
}
description
"This leaf identifies in which topology the
supporting termination point is present.";
}
leaf node-ref {
type leafref {
path "../../../nw:supporting-node/nw:node-ref";
require-instance false;
}
description
"This leaf identifies in which node the supporting
termination point is present.";
}
leaf tp-ref {
type leafref {
path "/nw:networks/nw:network[nw:network-id=current()/"+
"../network-ref]/nw:node[nw:node-id=current()/../"+
"node-ref]/termination-point/tp-id";
require-instance false;
}
description
"Reference to the underlay node (the underlay node must
be in a different topology).";
}
}
}
}
}

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@@ -0,0 +1,192 @@
module ietf-network {
yang-version 1.1;
namespace "urn:ietf:params:xml:ns:yang:ietf-network";
prefix nw;
import ietf-inet-types {
prefix inet;
reference
"RFC 6991: Common YANG Data Types";
}
organization
"IETF I2RS (Interface to the Routing System) Working Group";
contact
"WG Web: <https://datatracker.ietf.org/wg/i2rs/>
WG List: <mailto:i2rs@ietf.org>
Editor: Alexander Clemm
<mailto:ludwig@clemm.org>
Editor: Jan Medved
<mailto:jmedved@cisco.com>
Editor: Robert Varga
<mailto:robert.varga@pantheon.tech>
Editor: Nitin Bahadur
<mailto:nitin_bahadur@yahoo.com>
Editor: Hariharan Ananthakrishnan
<mailto:hari@packetdesign.com>
Editor: Xufeng Liu
<mailto:xufeng.liu.ietf@gmail.com>";
description
"This module defines a common base data model for a collection
of nodes in a network. Node definitions are further used
in network topologies and inventories.
Copyright (c) 2018 IETF Trust and the persons identified as
authors of the code. All rights reserved.
Redistribution and use in source and binary forms, with or
without modification, is permitted pursuant to, and subject
to the license terms contained in, the Simplified BSD License
set forth in Section 4.c of the IETF Trust's Legal Provisions
Relating to IETF Documents
(https://trustee.ietf.org/license-info).
This version of this YANG module is part of RFC 8345;
see the RFC itself for full legal notices.";
revision 2018-02-26 {
description
"Initial revision.";
reference
"RFC 8345: A YANG Data Model for Network Topologies";
}
typedef node-id {
type inet:uri;
description
"Identifier for a node. The precise structure of the node-id
will be up to the implementation. For example, some
implementations MAY pick a URI that includes the network-id
as part of the path. The identifier SHOULD be chosen
such that the same node in a real network topology will
always be identified through the same identifier, even if
the data model is instantiated in separate datastores. An
implementation MAY choose to capture semantics in the
identifier -- for example, to indicate the type of node.";
}
typedef network-id {
type inet:uri;
description
"Identifier for a network. The precise structure of the
network-id will be up to the implementation. The identifier
SHOULD be chosen such that the same network will always be
identified through the same identifier, even if the data model
is instantiated in separate datastores. An implementation MAY
choose to capture semantics in the identifier -- for example,
to indicate the type of network.";
}
grouping network-ref {
description
"Contains the information necessary to reference a network --
for example, an underlay network.";
leaf network-ref {
type leafref {
path "/nw:networks/nw:network/nw:network-id";
require-instance false;
}
description
"Used to reference a network -- for example, an underlay
network.";
}
}
grouping node-ref {
description
"Contains the information necessary to reference a node.";
leaf node-ref {
type leafref {
path "/nw:networks/nw:network[nw:network-id=current()/../"+
"network-ref]/nw:node/nw:node-id";
require-instance false;
}
description
"Used to reference a node.
Nodes are identified relative to the network that
contains them.";
}
uses network-ref;
}
container networks {
description
"Serves as a top-level container for a list of networks.";
list network {
key "network-id";
description
"Describes a network.
A network typically contains an inventory of nodes,
topological information (augmented through the
network-topology data model), and layering information.";
leaf network-id {
type network-id;
description
"Identifies a network.";
}
container network-types {
description
"Serves as an augmentation target.
The network type is indicated through corresponding
presence containers augmented into this container.";
}
list supporting-network {
key "network-ref";
description
"An underlay network, used to represent layered network
topologies.";
leaf network-ref {
type leafref {
path "/nw:networks/nw:network/nw:network-id";
require-instance false;
}
description
"References the underlay network.";
}
}
list node {
key "node-id";
description
"The inventory of nodes of this network.";
leaf node-id {
type node-id;
description
"Uniquely identifies a node within the containing
network.";
}
list supporting-node {
key "network-ref node-ref";
description
"Represents another node that is in an underlay network
and that supports this node. Used to represent layering
structure.";
leaf network-ref {
type leafref {
path "../../../nw:supporting-network/nw:network-ref";
require-instance false;
}
description
"References the underlay network of which the
underlay node is a part.";
}
leaf node-ref {
type leafref {
path "/nw:networks/nw:network/nw:node/nw:node-id";
require-instance false;
}
description
"References the underlay node itself.";
}
}
}
}
}
}

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module ietf-routing-types {
namespace "urn:ietf:params:xml:ns:yang:ietf-routing-types";
prefix rt-types;
import ietf-yang-types {
prefix yang;
}
import ietf-inet-types {
prefix inet;
}
organization
"IETF RTGWG - Routing Area Working Group";
contact
"WG Web: <https://datatracker.ietf.org/wg/rtgwg/>
WG List: <mailto:rtgwg@ietf.org>
Editors: Xufeng Liu
<mailto:Xufeng_Liu@jabail.com>
Yingzhen Qu
<mailto:yingzhen.qu@huawei.com>
Acee Lindem
<mailto:acee@cisco.com>
Christian Hopps
<mailto:chopps@chopps.org>
Lou Berger
<mailto:lberger@labn.com>";
description
"This module contains a collection of YANG data types
considered generally useful for routing protocols.
Copyright (c) 2017 IETF Trust and the persons
identified as authors of the code. All rights reserved.
Redistribution and use in source and binary forms, with or
without modification, is permitted pursuant to, and subject
to the license terms contained in, the Simplified BSD License
set forth in Section 4.c of the IETF Trust's Legal Provisions
Relating to IETF Documents
(https://trustee.ietf.org/license-info).
This version of this YANG module is part of RFC 8294; see
the RFC itself for full legal notices.";
revision 2017-12-04 {
description "Initial revision.";
reference
"RFC 8294: Common YANG Data Types for the Routing Area.
Section 3.";
}
/*** Identities related to MPLS/GMPLS ***/
identity mpls-label-special-purpose-value {
description
"Base identity for deriving identities describing
special-purpose Multiprotocol Label Switching (MPLS) label
values.";
reference
"RFC 7274: Allocating and Retiring Special-Purpose MPLS
Labels.";
}
identity ipv4-explicit-null-label {
base mpls-label-special-purpose-value;
description
"This identity represents the IPv4 Explicit NULL Label.";
reference
"RFC 3032: MPLS Label Stack Encoding. Section 2.1.";
}
identity router-alert-label {
base mpls-label-special-purpose-value;
description
"This identity represents the Router Alert Label.";
reference
"RFC 3032: MPLS Label Stack Encoding. Section 2.1.";
}
identity ipv6-explicit-null-label {
base mpls-label-special-purpose-value;
description
"This identity represents the IPv6 Explicit NULL Label.";
reference
"RFC 3032: MPLS Label Stack Encoding. Section 2.1.";
}
identity implicit-null-label {
base mpls-label-special-purpose-value;
description
"This identity represents the Implicit NULL Label.";
reference
"RFC 3032: MPLS Label Stack Encoding. Section 2.1.";
}
identity entropy-label-indicator {
base mpls-label-special-purpose-value;
description
"This identity represents the Entropy Label Indicator.";
reference
"RFC 6790: The Use of Entropy Labels in MPLS Forwarding.
Sections 3 and 10.1.";
}
identity gal-label {
base mpls-label-special-purpose-value;
description
"This identity represents the Generic Associated Channel
(G-ACh) Label (GAL).";
reference
"RFC 5586: MPLS Generic Associated Channel.
Sections 4 and 10.";
}
identity oam-alert-label {
base mpls-label-special-purpose-value;
description
"This identity represents the OAM Alert Label.";
reference
"RFC 3429: Assignment of the 'OAM Alert Label' for
Multiprotocol Label Switching Architecture (MPLS)
Operation and Maintenance (OAM) Functions.
Sections 3 and 6.";
}
identity extension-label {
base mpls-label-special-purpose-value;
description
"This identity represents the Extension Label.";
reference
"RFC 7274: Allocating and Retiring Special-Purpose MPLS
Labels. Sections 3.1 and 5.";
}
/*** Collection of types related to routing ***/
typedef router-id {
type yang:dotted-quad;
description
"A 32-bit number in the dotted-quad format assigned to each
router. This number uniquely identifies the router within
an Autonomous System.";
}
/*** Collection of types related to VPNs ***/
typedef route-target {
type string {
pattern
'(0:(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0):(429496729[0-5]|'
+ '42949672[0-8][0-9]|'
+ '4294967[01][0-9]{2}|429496[0-6][0-9]{3}|'
+ '42949[0-5][0-9]{4}|'
+ '4294[0-8][0-9]{5}|429[0-3][0-9]{6}|'
+ '42[0-8][0-9]{7}|4[01][0-9]{8}|'
+ '[1-3][0-9]{9}|[1-9][0-9]{0,8}|0))|'
+ '(1:((([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|'
+ '25[0-5])\.){3}([0-9]|[1-9][0-9]|'
+ '1[0-9]{2}|2[0-4][0-9]|25[0-5])):(6553[0-5]|'
+ '655[0-2][0-9]|'
+ '65[0-4][0-9]{2}|6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0))|'
+ '(2:(429496729[0-5]|42949672[0-8][0-9]|'
+ '4294967[01][0-9]{2}|'
+ '429496[0-6][0-9]{3}|42949[0-5][0-9]{4}|'
+ '4294[0-8][0-9]{5}|'
+ '429[0-3][0-9]{6}|42[0-8][0-9]{7}|4[01][0-9]{8}|'
+ '[1-3][0-9]{9}|[1-9][0-9]{0,8}|0):'
+ '(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0))|'
+ '(6(:[a-fA-F0-9]{2}){6})|'
+ '(([3-57-9a-fA-F]|[1-9a-fA-F][0-9a-fA-F]{1,3}):'
+ '[0-9a-fA-F]{1,12})';
}
description
"A Route Target is an 8-octet BGP extended community
initially identifying a set of sites in a BGP VPN
(RFC 4364). However, it has since taken on a more general
role in BGP route filtering. A Route Target consists of two
or three fields: a 2-octet Type field, an administrator
field, and, optionally, an assigned number field.
According to the data formats for types 0, 1, 2, and 6 as
defined in RFC 4360, RFC 5668, and RFC 7432, the encoding
pattern is defined as:
0:2-octet-asn:4-octet-number
1:4-octet-ipv4addr:2-octet-number
2:4-octet-asn:2-octet-number
6:6-octet-mac-address
Additionally, a generic pattern is defined for future
Route Target types:
2-octet-other-hex-number:6-octet-hex-number
Some valid examples are 0:100:100, 1:1.1.1.1:100,
2:1234567890:203, and 6:26:00:08:92:78:00.";
reference
"RFC 4360: BGP Extended Communities Attribute.
RFC 4364: BGP/MPLS IP Virtual Private Networks (VPNs).
RFC 5668: 4-Octet AS Specific BGP Extended Community.
RFC 7432: BGP MPLS-Based Ethernet VPN.";
}
typedef ipv6-route-target {
type string {
pattern
'((:|[0-9a-fA-F]{0,4}):)([0-9a-fA-F]{0,4}:){0,5}'
+ '((([0-9a-fA-F]{0,4}:)?(:|[0-9a-fA-F]{0,4}))|'
+ '(((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])\.){3}'
+ '(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])))'
+ ':'
+ '(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0)';
pattern '((([^:]+:){6}(([^:]+:[^:]+)|(.*\..*)))|'
+ '((([^:]+:)*[^:]+)?::(([^:]+:)*[^:]+)?))'
+ ':'
+ '(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0)';
}
description
"An IPv6 Route Target is a 20-octet BGP IPv6 Address
Specific Extended Community serving the same function
as a standard 8-octet Route Target, except that it only
allows an IPv6 address as the global administrator.
The format is <ipv6-address:2-octet-number>.
Two valid examples are 2001:db8::1:6544 and
2001:db8::5eb1:791:6b37:17958.";
reference
"RFC 5701: IPv6 Address Specific BGP Extended Community
Attribute.";
}
typedef route-target-type {
type enumeration {
enum import {
value 0;
description
"The Route Target applies to route import.";
}
enum export {
value 1;
description
"The Route Target applies to route export.";
}
enum both {
value 2;
description
"The Route Target applies to both route import and
route export.";
}
}
description
"Indicates the role a Route Target takes in route filtering.";
reference
"RFC 4364: BGP/MPLS IP Virtual Private Networks (VPNs).";
}
typedef route-distinguisher {
type string {
pattern
'(0:(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0):(429496729[0-5]|'
+ '42949672[0-8][0-9]|'
+ '4294967[01][0-9]{2}|429496[0-6][0-9]{3}|'
+ '42949[0-5][0-9]{4}|'
+ '4294[0-8][0-9]{5}|429[0-3][0-9]{6}|'
+ '42[0-8][0-9]{7}|4[01][0-9]{8}|'
+ '[1-3][0-9]{9}|[1-9][0-9]{0,8}|0))|'
+ '(1:((([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|'
+ '25[0-5])\.){3}([0-9]|[1-9][0-9]|'
+ '1[0-9]{2}|2[0-4][0-9]|25[0-5])):(6553[0-5]|'
+ '655[0-2][0-9]|'
+ '65[0-4][0-9]{2}|6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0))|'
+ '(2:(429496729[0-5]|42949672[0-8][0-9]|'
+ '4294967[01][0-9]{2}|'
+ '429496[0-6][0-9]{3}|42949[0-5][0-9]{4}|'
+ '4294[0-8][0-9]{5}|'
+ '429[0-3][0-9]{6}|42[0-8][0-9]{7}|4[01][0-9]{8}|'
+ '[1-3][0-9]{9}|[1-9][0-9]{0,8}|0):'
+ '(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0))|'
+ '(6(:[a-fA-F0-9]{2}){6})|'
+ '(([3-57-9a-fA-F]|[1-9a-fA-F][0-9a-fA-F]{1,3}):'
+ '[0-9a-fA-F]{1,12})';
}
description
"A Route Distinguisher is an 8-octet value used to
distinguish routes from different BGP VPNs (RFC 4364).
A Route Distinguisher will have the same format as a
Route Target as per RFC 4360 and will consist of
two or three fields: a 2-octet Type field, an administrator
field, and, optionally, an assigned number field.
According to the data formats for types 0, 1, 2, and 6 as
defined in RFC 4360, RFC 5668, and RFC 7432, the encoding
pattern is defined as:
0:2-octet-asn:4-octet-number
1:4-octet-ipv4addr:2-octet-number
2:4-octet-asn:2-octet-number
6:6-octet-mac-address
Additionally, a generic pattern is defined for future
route discriminator types:
2-octet-other-hex-number:6-octet-hex-number
Some valid examples are 0:100:100, 1:1.1.1.1:100,
2:1234567890:203, and 6:26:00:08:92:78:00.";
reference
"RFC 4360: BGP Extended Communities Attribute.
RFC 4364: BGP/MPLS IP Virtual Private Networks (VPNs).
RFC 5668: 4-Octet AS Specific BGP Extended Community.
RFC 7432: BGP MPLS-Based Ethernet VPN.";
}
typedef route-origin {
type string {
pattern
'(0:(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0):(429496729[0-5]|'
+ '42949672[0-8][0-9]|'
+ '4294967[01][0-9]{2}|429496[0-6][0-9]{3}|'
+ '42949[0-5][0-9]{4}|'
+ '4294[0-8][0-9]{5}|429[0-3][0-9]{6}|'
+ '42[0-8][0-9]{7}|4[01][0-9]{8}|'
+ '[1-3][0-9]{9}|[1-9][0-9]{0,8}|0))|'
+ '(1:((([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|'
+ '25[0-5])\.){3}([0-9]|[1-9][0-9]|'
+ '1[0-9]{2}|2[0-4][0-9]|25[0-5])):(6553[0-5]|'
+ '655[0-2][0-9]|'
+ '65[0-4][0-9]{2}|6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0))|'
+ '(2:(429496729[0-5]|42949672[0-8][0-9]|'
+ '4294967[01][0-9]{2}|'
+ '429496[0-6][0-9]{3}|42949[0-5][0-9]{4}|'
+ '4294[0-8][0-9]{5}|'
+ '429[0-3][0-9]{6}|42[0-8][0-9]{7}|4[01][0-9]{8}|'
+ '[1-3][0-9]{9}|[1-9][0-9]{0,8}|0):'
+ '(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0))|'
+ '(6(:[a-fA-F0-9]{2}){6})|'
+ '(([3-57-9a-fA-F]|[1-9a-fA-F][0-9a-fA-F]{1,3}):'
+ '[0-9a-fA-F]{1,12})';
}
description
"A Route Origin is an 8-octet BGP extended community
identifying the set of sites where the BGP route
originated (RFC 4364). A Route Origin will have the same
format as a Route Target as per RFC 4360 and will consist
of two or three fields: a 2-octet Type field, an
administrator field, and, optionally, an assigned number
field.
According to the data formats for types 0, 1, 2, and 6 as
defined in RFC 4360, RFC 5668, and RFC 7432, the encoding
pattern is defined as:
0:2-octet-asn:4-octet-number
1:4-octet-ipv4addr:2-octet-number
2:4-octet-asn:2-octet-number
6:6-octet-mac-address
Additionally, a generic pattern is defined for future
Route Origin types:
2-octet-other-hex-number:6-octet-hex-number
Some valid examples are 0:100:100, 1:1.1.1.1:100,
2:1234567890:203, and 6:26:00:08:92:78:00.";
reference
"RFC 4360: BGP Extended Communities Attribute.
RFC 4364: BGP/MPLS IP Virtual Private Networks (VPNs).
RFC 5668: 4-Octet AS Specific BGP Extended Community.
RFC 7432: BGP MPLS-Based Ethernet VPN.";
}
typedef ipv6-route-origin {
type string {
pattern
'((:|[0-9a-fA-F]{0,4}):)([0-9a-fA-F]{0,4}:){0,5}'
+ '((([0-9a-fA-F]{0,4}:)?(:|[0-9a-fA-F]{0,4}))|'
+ '(((25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])\.){3}'
+ '(25[0-5]|2[0-4][0-9]|1[0-9]{2}|[1-9]?[0-9])))'
+ ':'
+ '(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0)';
pattern '((([^:]+:){6}(([^:]+:[^:]+)|(.*\..*)))|'
+ '((([^:]+:)*[^:]+)?::(([^:]+:)*[^:]+)?))'
+ ':'
+ '(6553[0-5]|655[0-2][0-9]|65[0-4][0-9]{2}|'
+ '6[0-4][0-9]{3}|'
+ '[1-5][0-9]{4}|[1-9][0-9]{0,3}|0)';
}
description
"An IPv6 Route Origin is a 20-octet BGP IPv6 Address
Specific Extended Community serving the same function
as a standard 8-octet route, except that it only allows
an IPv6 address as the global administrator. The format
is <ipv6-address:2-octet-number>.
Two valid examples are 2001:db8::1:6544 and
2001:db8::5eb1:791:6b37:17958.";
reference
"RFC 5701: IPv6 Address Specific BGP Extended Community
Attribute.";
}
/*** Collection of types common to multicast ***/
typedef ipv4-multicast-group-address {
type inet:ipv4-address {
pattern '(2((2[4-9])|(3[0-9]))\.).*';
}
description
"This type represents an IPv4 multicast group address,
which is in the range of 224.0.0.0 to 239.255.255.255.";
reference
"RFC 1112: Host Extensions for IP Multicasting.";
}
typedef ipv6-multicast-group-address {
type inet:ipv6-address {
pattern '(([fF]{2}[0-9a-fA-F]{2}):).*';
}
description
"This type represents an IPv6 multicast group address,
which is in the range of ff00::/8.";
reference
"RFC 4291: IP Version 6 Addressing Architecture. Section 2.7.
RFC 7346: IPv6 Multicast Address Scopes.";
}
typedef ip-multicast-group-address {
type union {
type ipv4-multicast-group-address;
type ipv6-multicast-group-address;
}
description
"This type represents a version-neutral IP multicast group
address. The format of the textual representation implies
the IP version.";
}
typedef ipv4-multicast-source-address {
type union {
type enumeration {
enum * {
description
"Any source address.";
}
}
type inet:ipv4-address;
}
description
"Multicast source IPv4 address type.";
}
typedef ipv6-multicast-source-address {
type union {
type enumeration {
enum * {
description
"Any source address.";
}
}
type inet:ipv6-address;
}
description
"Multicast source IPv6 address type.";
}
/*** Collection of types common to protocols ***/
typedef bandwidth-ieee-float32 {
type string {
pattern
'0[xX](0((\.0?)?[pP](\+)?0?|(\.0?))|'
+ '1(\.([0-9a-fA-F]{0,5}[02468aAcCeE]?)?)?[pP](\+)?(12[0-7]|'
+ '1[01][0-9]|0?[0-9]?[0-9])?)';
}
description
"Bandwidth in IEEE 754 floating-point 32-bit binary format:
(-1)**(S) * 2**(Exponent-127) * (1 + Fraction),
where Exponent uses 8 bits and Fraction uses 23 bits.
The units are octets per second.
The encoding format is the external hexadecimal-significant
character sequences specified in IEEE 754 and ISO/IEC C99.
The format is restricted to be normalized, non-negative, and
non-fraction: 0x1.hhhhhhp{+}d, 0X1.HHHHHHP{+}D, or 0x0p0,
where 'h' and 'H' are hexadecimal digits and 'd' and 'D' are
integers in the range of [0..127].
When six hexadecimal digits are used for 'hhhhhh' or
'HHHHHH', the least significant digit must be an even
number. 'x' and 'X' indicate hexadecimal; 'p' and 'P'
indicate a power of two. Some examples are 0x0p0, 0x1p10,
and 0x1.abcde2p+20.";
reference
"IEEE Std 754-2008: IEEE Standard for Floating-Point
Arithmetic.
ISO/IEC C99: Information technology - Programming
Languages - C.";
}
typedef link-access-type {
type enumeration {
enum broadcast {
description
"Specify broadcast multi-access network.";
}
enum non-broadcast-multiaccess {
description
"Specify Non-Broadcast Multi-Access (NBMA) network.";
}
enum point-to-multipoint {
description
"Specify point-to-multipoint network.";
}
enum point-to-point {
description
"Specify point-to-point network.";
}
}
description
"Link access type.";
}
typedef timer-multiplier {
type uint8;
description
"The number of timer value intervals that should be
interpreted as a failure.";
}
typedef timer-value-seconds16 {
type union {
type uint16 {
range "1..65535";
}
type enumeration {
enum infinity {
description
"The timer is set to infinity.";
}
enum not-set {
description
"The timer is not set.";
}
}
}
units "seconds";
description
"Timer value type, in seconds (16-bit range).";
}
typedef timer-value-seconds32 {
type union {
type uint32 {
range "1..4294967295";
}
type enumeration {
enum infinity {
description
"The timer is set to infinity.";
}
enum not-set {
description
"The timer is not set.";
}
}
}
units "seconds";
description
"Timer value type, in seconds (32-bit range).";
}
typedef timer-value-milliseconds {
type union {
type uint32 {
range "1..4294967295";
}
type enumeration {
enum infinity {
description
"The timer is set to infinity.";
}
enum not-set {
description
"The timer is not set.";
}
}
}
units "milliseconds";
description
"Timer value type, in milliseconds.";
}
typedef percentage {
type uint8 {
range "0..100";
}
description
"Integer indicating a percentage value.";
}
typedef timeticks64 {
type uint64;
description
"This type is based on the timeticks type defined in
RFC 6991, but with 64-bit width. It represents the time,
modulo 2^64, in hundredths of a second between two epochs.";
reference
"RFC 6991: Common YANG Data Types.";
}
typedef uint24 {
type uint32 {
range "0..16777215";
}
description
"24-bit unsigned integer.";
}
/*** Collection of types related to MPLS/GMPLS ***/
typedef generalized-label {
type binary;
description
"Generalized Label. Nodes sending and receiving the
Generalized Label are aware of the link-specific
label context and type.";
reference
"RFC 3471: Generalized Multi-Protocol Label Switching (GMPLS)
Signaling Functional Description. Section 3.2.";
}
typedef mpls-label-special-purpose {
type identityref {
base mpls-label-special-purpose-value;
}
description
"This type represents the special-purpose MPLS label values.";
reference
"RFC 3032: MPLS Label Stack Encoding.
RFC 7274: Allocating and Retiring Special-Purpose MPLS
Labels.";
}
typedef mpls-label-general-use {
type uint32 {
range "16..1048575";
}
description
"The 20-bit label value in an MPLS label stack as specified
in RFC 3032. This label value does not include the
encodings of Traffic Class and TTL (Time to Live).
The label range specified by this type is for general use,
with special-purpose MPLS label values excluded.";
reference
"RFC 3032: MPLS Label Stack Encoding.";
}
typedef mpls-label {
type union {
type mpls-label-special-purpose;
type mpls-label-general-use;
}
description
"The 20-bit label value in an MPLS label stack as specified
in RFC 3032. This label value does not include the
encodings of Traffic Class and TTL.";
reference
"RFC 3032: MPLS Label Stack Encoding.";
}
/*** Groupings **/
grouping mpls-label-stack {
description
"This grouping specifies an MPLS label stack. The label
stack is encoded as a list of label stack entries. The
list key is an identifier that indicates the relative
ordering of each entry, with the lowest-value identifier
corresponding to the top of the label stack.";
container mpls-label-stack {
description
"Container for a list of MPLS label stack entries.";
list entry {
key "id";
description
"List of MPLS label stack entries.";
leaf id {
type uint8;
description
"Identifies the entry in a sequence of MPLS label
stack entries. An entry with a smaller identifier
value precedes an entry with a larger identifier
value in the label stack. The value of this ID has
no semantic meaning other than relative ordering
and referencing the entry.";
}
leaf label {
type rt-types:mpls-label;
description
"Label value.";
}
leaf ttl {
type uint8;
description
"Time to Live (TTL).";
reference
"RFC 3032: MPLS Label Stack Encoding.";
}
leaf traffic-class {
type uint8 {
range "0..7";
}
description
"Traffic Class (TC).";
reference
"RFC 5462: Multiprotocol Label Switching (MPLS) Label
Stack Entry: 'EXP' Field Renamed to 'Traffic Class'
Field.";
}
}
}
}
grouping vpn-route-targets {
description
"A grouping that specifies Route Target import-export rules
used in BGP-enabled VPNs.";
reference
"RFC 4364: BGP/MPLS IP Virtual Private Networks (VPNs).
RFC 4664: Framework for Layer 2 Virtual Private Networks
(L2VPNs).";
list vpn-target {
key "route-target";
description
"List of Route Targets.";
leaf route-target {
type rt-types:route-target;
description
"Route Target value.";
}
leaf route-target-type {
type rt-types:route-target-type;
mandatory true;
description
"Import/export type of the Route Target.";
}
}
}
}

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module ietf-yang-types {
namespace "urn:ietf:params:xml:ns:yang:ietf-yang-types";
prefix "yang";
organization
"IETF NETMOD (NETCONF Data Modeling Language) Working Group";
contact
"WG Web: <http://tools.ietf.org/wg/netmod/>
WG List: <mailto:netmod@ietf.org>
WG Chair: David Kessens
<mailto:david.kessens@nsn.com>
WG Chair: Juergen Schoenwaelder
<mailto:j.schoenwaelder@jacobs-university.de>
Editor: Juergen Schoenwaelder
<mailto:j.schoenwaelder@jacobs-university.de>";
description
"This module contains a collection of generally useful derived
YANG data types.
Copyright (c) 2013 IETF Trust and the persons identified as
authors of the code. All rights reserved.
Redistribution and use in source and binary forms, with or
without modification, is permitted pursuant to, and subject
to the license terms contained in, the Simplified BSD License
set forth in Section 4.c of the IETF Trust's Legal Provisions
Relating to IETF Documents
(http://trustee.ietf.org/license-info).
This version of this YANG module is part of RFC 6991; see
the RFC itself for full legal notices.";
revision 2013-07-15 {
description
"This revision adds the following new data types:
- yang-identifier
- hex-string
- uuid
- dotted-quad";
reference
"RFC 6991: Common YANG Data Types";
}
revision 2010-09-24 {
description
"Initial revision.";
reference
"RFC 6021: Common YANG Data Types";
}
/*** collection of counter and gauge types ***/
typedef counter32 {
type uint32;
description
"The counter32 type represents a non-negative integer
that monotonically increases until it reaches a
maximum value of 2^32-1 (4294967295 decimal), when it
wraps around and starts increasing again from zero.
Counters have no defined 'initial' value, and thus, a
single value of a counter has (in general) no information
content. Discontinuities in the monotonically increasing
value normally occur at re-initialization of the
management system, and at other times as specified in the
description of a schema node using this type. If such
other times can occur, for example, the creation of
a schema node of type counter32 at times other than
re-initialization, then a corresponding schema node
should be defined, with an appropriate type, to indicate
the last discontinuity.
The counter32 type should not be used for configuration
schema nodes. A default statement SHOULD NOT be used in
combination with the type counter32.
In the value set and its semantics, this type is equivalent
to the Counter32 type of the SMIv2.";
reference
"RFC 2578: Structure of Management Information Version 2
(SMIv2)";
}
typedef zero-based-counter32 {
type yang:counter32;
default "0";
description
"The zero-based-counter32 type represents a counter32
that has the defined 'initial' value zero.
A schema node of this type will be set to zero (0) on creation
and will thereafter increase monotonically until it reaches
a maximum value of 2^32-1 (4294967295 decimal), when it
wraps around and starts increasing again from zero.
Provided that an application discovers a new schema node
of this type within the minimum time to wrap, it can use the
'initial' value as a delta. It is important for a management
station to be aware of this minimum time and the actual time
between polls, and to discard data if the actual time is too
long or there is no defined minimum time.
In the value set and its semantics, this type is equivalent
to the ZeroBasedCounter32 textual convention of the SMIv2.";
reference
"RFC 4502: Remote Network Monitoring Management Information
Base Version 2";
}
typedef counter64 {
type uint64;
description
"The counter64 type represents a non-negative integer
that monotonically increases until it reaches a
maximum value of 2^64-1 (18446744073709551615 decimal),
when it wraps around and starts increasing again from zero.
Counters have no defined 'initial' value, and thus, a
single value of a counter has (in general) no information
content. Discontinuities in the monotonically increasing
value normally occur at re-initialization of the
management system, and at other times as specified in the
description of a schema node using this type. If such
other times can occur, for example, the creation of
a schema node of type counter64 at times other than
re-initialization, then a corresponding schema node
should be defined, with an appropriate type, to indicate
the last discontinuity.
The counter64 type should not be used for configuration
schema nodes. A default statement SHOULD NOT be used in
combination with the type counter64.
In the value set and its semantics, this type is equivalent
to the Counter64 type of the SMIv2.";
reference
"RFC 2578: Structure of Management Information Version 2
(SMIv2)";
}
typedef zero-based-counter64 {
type yang:counter64;
default "0";
description
"The zero-based-counter64 type represents a counter64 that
has the defined 'initial' value zero.
A schema node of this type will be set to zero (0) on creation
and will thereafter increase monotonically until it reaches
a maximum value of 2^64-1 (18446744073709551615 decimal),
when it wraps around and starts increasing again from zero.
Provided that an application discovers a new schema node
of this type within the minimum time to wrap, it can use the
'initial' value as a delta. It is important for a management
station to be aware of this minimum time and the actual time
between polls, and to discard data if the actual time is too
long or there is no defined minimum time.
In the value set and its semantics, this type is equivalent
to the ZeroBasedCounter64 textual convention of the SMIv2.";
reference
"RFC 2856: Textual Conventions for Additional High Capacity
Data Types";
}
typedef gauge32 {
type uint32;
description
"The gauge32 type represents a non-negative integer, which
may increase or decrease, but shall never exceed a maximum
value, nor fall below a minimum value. The maximum value
cannot be greater than 2^32-1 (4294967295 decimal), and
the minimum value cannot be smaller than 0. The value of
a gauge32 has its maximum value whenever the information
being modeled is greater than or equal to its maximum
value, and has its minimum value whenever the information
being modeled is smaller than or equal to its minimum value.
If the information being modeled subsequently decreases
below (increases above) the maximum (minimum) value, the
gauge32 also decreases (increases).
In the value set and its semantics, this type is equivalent
to the Gauge32 type of the SMIv2.";
reference
"RFC 2578: Structure of Management Information Version 2
(SMIv2)";
}
typedef gauge64 {
type uint64;
description
"The gauge64 type represents a non-negative integer, which
may increase or decrease, but shall never exceed a maximum
value, nor fall below a minimum value. The maximum value
cannot be greater than 2^64-1 (18446744073709551615), and
the minimum value cannot be smaller than 0. The value of
a gauge64 has its maximum value whenever the information
being modeled is greater than or equal to its maximum
value, and has its minimum value whenever the information
being modeled is smaller than or equal to its minimum value.
If the information being modeled subsequently decreases
below (increases above) the maximum (minimum) value, the
gauge64 also decreases (increases).
In the value set and its semantics, this type is equivalent
to the CounterBasedGauge64 SMIv2 textual convention defined
in RFC 2856";
reference
"RFC 2856: Textual Conventions for Additional High Capacity
Data Types";
}
/*** collection of identifier-related types ***/
typedef object-identifier {
type string {
pattern '(([0-1](\.[1-3]?[0-9]))|(2\.(0|([1-9]\d*))))'
+ '(\.(0|([1-9]\d*)))*';
}
description
"The object-identifier type represents administratively
assigned names in a registration-hierarchical-name tree.
Values of this type are denoted as a sequence of numerical
non-negative sub-identifier values. Each sub-identifier
value MUST NOT exceed 2^32-1 (4294967295). Sub-identifiers
are separated by single dots and without any intermediate
whitespace.
The ASN.1 standard restricts the value space of the first
sub-identifier to 0, 1, or 2. Furthermore, the value space
of the second sub-identifier is restricted to the range
0 to 39 if the first sub-identifier is 0 or 1. Finally,
the ASN.1 standard requires that an object identifier
has always at least two sub-identifiers. The pattern
captures these restrictions.
Although the number of sub-identifiers is not limited,
module designers should realize that there may be
implementations that stick with the SMIv2 limit of 128
sub-identifiers.
This type is a superset of the SMIv2 OBJECT IDENTIFIER type
since it is not restricted to 128 sub-identifiers. Hence,
this type SHOULD NOT be used to represent the SMIv2 OBJECT
IDENTIFIER type; the object-identifier-128 type SHOULD be
used instead.";
reference
"ISO9834-1: Information technology -- Open Systems
Interconnection -- Procedures for the operation of OSI
Registration Authorities: General procedures and top
arcs of the ASN.1 Object Identifier tree";
}
typedef object-identifier-128 {
type object-identifier {
pattern '\d*(\.\d*){1,127}';
}
description
"This type represents object-identifiers restricted to 128
sub-identifiers.
In the value set and its semantics, this type is equivalent
to the OBJECT IDENTIFIER type of the SMIv2.";
reference
"RFC 2578: Structure of Management Information Version 2
(SMIv2)";
}
typedef yang-identifier {
type string {
length "1..max";
pattern '[a-zA-Z_][a-zA-Z0-9\-_.]*';
pattern '.|..|[^xX].*|.[^mM].*|..[^lL].*';
}
description
"A YANG identifier string as defined by the 'identifier'
rule in Section 12 of RFC 6020. An identifier must
start with an alphabetic character or an underscore
followed by an arbitrary sequence of alphabetic or
numeric characters, underscores, hyphens, or dots.
A YANG identifier MUST NOT start with any possible
combination of the lowercase or uppercase character
sequence 'xml'.";
reference
"RFC 6020: YANG - A Data Modeling Language for the Network
Configuration Protocol (NETCONF)";
}
/*** collection of types related to date and time***/
typedef date-and-time {
type string {
pattern '\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}(\.\d+)?'
+ '(Z|[\+\-]\d{2}:\d{2})';
}
description
"The date-and-time type is a profile of the ISO 8601
standard for representation of dates and times using the
Gregorian calendar. The profile is defined by the
date-time production in Section 5.6 of RFC 3339.
The date-and-time type is compatible with the dateTime XML
schema type with the following notable exceptions:
(a) The date-and-time type does not allow negative years.
(b) The date-and-time time-offset -00:00 indicates an unknown
time zone (see RFC 3339) while -00:00 and +00:00 and Z
all represent the same time zone in dateTime.
(c) The canonical format (see below) of data-and-time values
differs from the canonical format used by the dateTime XML
schema type, which requires all times to be in UTC using
the time-offset 'Z'.
This type is not equivalent to the DateAndTime textual
convention of the SMIv2 since RFC 3339 uses a different
separator between full-date and full-time and provides
higher resolution of time-secfrac.
The canonical format for date-and-time values with a known time
zone uses a numeric time zone offset that is calculated using
the device's configured known offset to UTC time. A change of
the device's offset to UTC time will cause date-and-time values
to change accordingly. Such changes might happen periodically
in case a server follows automatically daylight saving time
(DST) time zone offset changes. The canonical format for
date-and-time values with an unknown time zone (usually
referring to the notion of local time) uses the time-offset
-00:00.";
reference
"RFC 3339: Date and Time on the Internet: Timestamps
RFC 2579: Textual Conventions for SMIv2
XSD-TYPES: XML Schema Part 2: Datatypes Second Edition";
}
typedef timeticks {
type uint32;
description
"The timeticks type represents a non-negative integer that
represents the time, modulo 2^32 (4294967296 decimal), in
hundredths of a second between two epochs. When a schema
node is defined that uses this type, the description of
the schema node identifies both of the reference epochs.
In the value set and its semantics, this type is equivalent
to the TimeTicks type of the SMIv2.";
reference
"RFC 2578: Structure of Management Information Version 2
(SMIv2)";
}
typedef timestamp {
type yang:timeticks;
description
"The timestamp type represents the value of an associated
timeticks schema node at which a specific occurrence
happened. The specific occurrence must be defined in the
description of any schema node defined using this type. When
the specific occurrence occurred prior to the last time the
associated timeticks attribute was zero, then the timestamp
value is zero. Note that this requires all timestamp values
to be reset to zero when the value of the associated timeticks
attribute reaches 497+ days and wraps around to zero.
The associated timeticks schema node must be specified
in the description of any schema node using this type.
In the value set and its semantics, this type is equivalent
to the TimeStamp textual convention of the SMIv2.";
reference
"RFC 2579: Textual Conventions for SMIv2";
}
/*** collection of generic address types ***/
typedef phys-address {
type string {
pattern '([0-9a-fA-F]{2}(:[0-9a-fA-F]{2})*)?';
}
description
"Represents media- or physical-level addresses represented
as a sequence octets, each octet represented by two hexadecimal
numbers. Octets are separated by colons. The canonical
representation uses lowercase characters.
In the value set and its semantics, this type is equivalent
to the PhysAddress textual convention of the SMIv2.";
reference
"RFC 2579: Textual Conventions for SMIv2";
}
typedef mac-address {
type string {
pattern '[0-9a-fA-F]{2}(:[0-9a-fA-F]{2}){5}';
}
description
"The mac-address type represents an IEEE 802 MAC address.
The canonical representation uses lowercase characters.
In the value set and its semantics, this type is equivalent
to the MacAddress textual convention of the SMIv2.";
reference
"IEEE 802: IEEE Standard for Local and Metropolitan Area
Networks: Overview and Architecture
RFC 2579: Textual Conventions for SMIv2";
}
/*** collection of XML-specific types ***/
typedef xpath1.0 {
type string;
description
"This type represents an XPATH 1.0 expression.
When a schema node is defined that uses this type, the
description of the schema node MUST specify the XPath
context in which the XPath expression is evaluated.";
reference
"XPATH: XML Path Language (XPath) Version 1.0";
}
/*** collection of string types ***/
typedef hex-string {
type string {
pattern '([0-9a-fA-F]{2}(:[0-9a-fA-F]{2})*)?';
}
description
"A hexadecimal string with octets represented as hex digits
separated by colons. The canonical representation uses
lowercase characters.";
}
typedef uuid {
type string {
pattern '[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-'
+ '[0-9a-fA-F]{4}-[0-9a-fA-F]{12}';
}
description
"A Universally Unique IDentifier in the string representation
defined in RFC 4122. The canonical representation uses
lowercase characters.
The following is an example of a UUID in string representation:
f81d4fae-7dec-11d0-a765-00a0c91e6bf6
";
reference
"RFC 4122: A Universally Unique IDentifier (UUID) URN
Namespace";
}
typedef dotted-quad {
type string {
pattern
'(([0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5])\.){3}'
+ '([0-9]|[1-9][0-9]|1[0-9][0-9]|2[0-4][0-9]|25[0-5])';
}
description
"An unsigned 32-bit number expressed in the dotted-quad
notation, i.e., four octets written as decimal numbers
and separated with the '.' (full stop) character.";
}
}

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module gnpy-api {
yang-version 1.1;
namespace "urn:gnpy-api";
prefix gapi;
organization
"Telecom Infra Project OOPT PSE Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:esther.lerouzic@orange.com>
";
description
"YANG model for gnpy network input for path computation simulation params- 2025";
revision 2025-06-13 {
description
"First yang model for api";
reference
"YANG model for network input for API path computation with gnpy";
}
container api {
description
"Top container for the API data.";
list extra-configs {
key name;
description
"List of extra configurations for the amplifiers defined in the
equipment libraries.";
leaf name {
type string;
description "Unique name used in the equipment library to reference this config.";
}
}
list extra-eqpts {
key name;
description
"List of additional libraries, eg for third party pluggables definitions.";
leaf name {
type string;
description "Unique name of the extra library.";
}
}
}
}

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@@ -0,0 +1,21 @@
module: gnpy-edfa-config
+--rw edfa-config
+--rw f_min decimal64
+--rw f_max decimal64
+--ro nf_ripple* decimal64
+--ro dgt* decimal64
+--ro gain_ripple* decimal64
+--ro nf_fit_coeff* [coef_order]
+--ro coef_order uint8
+--ro nf_coef? decimal64
augment /gapi:api/gapi:extra-configs:
+--rw edfa-config
+--rw f_min decimal64
+--rw f_max decimal64
+--ro nf_ripple* decimal64
+--ro dgt* decimal64
+--ro gain_ripple* decimal64
+--ro nf_fit_coeff* [coef_order]
+--ro coef_order uint8
+--ro nf_coef? decimal64

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module gnpy-edfa-config {
yang-version 1.1;
namespace "urn:gnpy-edaf-config";
prefix edfa-config;
import gnpy-api {
prefix "gapi";
revision-date 2025-06-13;
}
import gnpy-eqpt-config {
prefix "geqpt";
revision-date 2025-05-26;
}
organization
"Telecom Infra Project OOPT PSE Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:esther.lerouzic@orange.com>
";
description
"YANG model for gnpy network input for path computation extra edfa config- 2025";
revision 2025-04-10 {
description
"First yang model for extra edfa config option";
reference
"YANG model for network input for path computation with gnpy";
}
grouping edfa-config-grouping {
description
"Attributes for detailed configuration of EDFA.";
leaf f_min {
type decimal64 {
fraction-digits 1;
}
mandatory true;
description " Minimum and maximum frequency range for the amplifier.
Signal must fit entirely within this range (center frequency and spectrum width
";
}
leaf f_max {
type decimal64 {
fraction-digits 1;
}
mandatory true;
}
leaf-list nf_ripple {
config false;
type decimal64 {
fraction-digits 18;
}
}
leaf-list dgt {
config false;
type decimal64 {
fraction-digits 18;
}
}
leaf-list gain_ripple {
config false;
type decimal64 {
fraction-digits 18;
}
}
list nf_fit_coeff {
key coef_order;
config false;
uses geqpt:polynomial-coef;
must "./coef_order <= 3";
description "3rd order polynomial NF = f(-dg) coeficients list";
}
}
grouping edfa-config {
container edfa-config {
uses edfa-config-grouping;
}
}
container edfa-config {
uses edfa-config-grouping;
}
augment "/gapi:api/gapi:extra-configs" {
description "Add the list of additional configuration of EDFA in the API request.";
when "/gapi:api/gapi:extra-configs" ;
uses edfa-config;
}
}

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module: gnpy-eqpt-config
+--rw equipment
+--rw library-information
| +--rw name? string
| +--rw content-schema
| | +--rw module* module-with-revision-date
| +--rw description* string
| +--rw contact* string
| +--rw organization? string
| +--rw revision* [date]
| +--rw date string
| +--rw description? string
+--rw Edfa* [type_variety]
| +--rw type_variety string
| +--rw other_name* string
| +--rw f_min? decimal64
| +--rw f_max? decimal64
| +--rw allowed_for_design? boolean
| +--rw gain_flatmax? decimal64
| +--rw gain_min? decimal64
| +--rw extended_gain_range? decimal64
| +--rw p_max? decimal64
| +--rw type_def? identityref
| +--rw raman? boolean
| +--rw out_voa_auto? boolean
| +--rw in_voa_auto? boolean
| +--rw voa_step? decimal64
| +--rw pmd? decimal64
| +--rw pdl? decimal64
| +--rw (type_of_model)?
| +--:(variable_gain)
| | +--rw nf_min? decimal64
| | +--rw nf_max? decimal64
| | +--rw default_config_from_json? string
| +--:(fixed_gain)
| | +--rw nf0? decimal64
| +--:(openroadm)
| | +--rw nf_coef* [coef_order]
| | +--rw coef_order uint8
| | +--rw nf_coef? decimal64
| +--:(dual_stage)
| | +--rw preamp_variety? union
| | +--rw booster_variety? union
| +--:(multi_band)
| | +--rw amplifiers* string
| +--:(advanced_model)
| +--rw advanced_config_from_json? string
+--rw Fiber* [type_variety]
| +--rw type_variety string
| +--rw dispersion? decimal64
| +--rw gamma? decimal64
| +--rw pmd_coef? decimal64
| +--rw effective_area? decimal64
| +--rw loss_coef_lut* [freq]
| | +--rw freq decimal64
| | +--rw loss_coef_value? decimal64
| +--rw (ref_freq_or_wl)?
| +--:(frequency)
| | +--rw ref_frequency? decimal64
| +--:(wavelength)
| +--rw ref_wavelength? decimal64
+--rw RamanFiber* [type_variety]
| +--rw type_variety string
| +--rw dispersion? decimal64
| +--rw gamma? decimal64
| +--rw pmd_coef? decimal64
| +--rw effective_area? decimal64
| +--rw loss_coef_lut* [freq]
| | +--rw freq decimal64
| | +--rw loss_coef_value? decimal64
| +--rw (ref_freq_or_wl)?
| | +--:(frequency)
| | | +--rw ref_frequency? decimal64
| | +--:(wavelength)
| | +--rw ref_wavelength? decimal64
| +--rw raman_efficiency* [frequency_offset]
| +--rw cr? decimal64
| +--rw frequency_offset decimal64
+--ro Span* []
| +--ro power_mode? boolean
| +--ro delta_power_range_dict_db
| | +--ro min_value? decimal64
| | +--ro max_value? decimal64
| | +--ro step? decimal64
| +--ro max_length? decimal64
| +--ro max_loss? decimal64
| +--ro max_fiber_lineic_loss_for_raman? decimal64
| +--ro target_extended_gain? decimal64
| +--ro length_units? string
| +--ro padding? decimal64
| +--ro EOL? decimal64
| +--ro con_in? decimal64
| +--ro con_out? decimal64
| +--ro span_loss_ref? decimal64
| +--ro power_slope? decimal64
| +--ro voa_margin? decimal64
| +--ro voa_step? decimal64
+--rw Roadm* [type_variety]
| +--rw type_variety string
| +--rw (target_type)?
| | +--:(constant_power)
| | | +--rw target_pch_out_db? decimal64
| | +--:(constant_psd)
| | | +--rw target_psd_out_mWperGHz? decimal64
| | +--:(constant_psw)
| | +--rw target_out_mWperSlotWidth? decimal64
| +--rw add_drop_osnr? decimal64
| +--rw pmd? decimal64
| +--rw pdl? decimal64
| +--rw restrictions
| | +--rw preamp_variety_list* string
| | +--rw booster_variety_list* string
| +--rw roadm-path-impairments* [roadm-path-impairments-id]
| +--rw roadm-path-impairments-id uint32
| +--rw (impairment-type)?
| +--:(roadm-express-path)
| | +--ro roadm-express-path* []
| | +--ro frequency-range
| | | +--ro lower-frequency union
| | | +--ro upper-frequency union
| | +--ro roadm-pmd? union
| | +--ro roadm-cd? l0-types:decimal-5-or-null
| | +--ro roadm-pdl? l0-types:power-loss-or-null
| | +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| | +--ro roadm-maxloss? l0-types:power-loss-or-null
| | +--ro roadm-osnr? l0-types:snr-or-null
| +--:(roadm-add-path)
| | +--ro roadm-add-path* []
| | +--ro frequency-range
| | | +--ro lower-frequency union
| | | +--ro upper-frequency union
| | +--ro roadm-pmd? union
| | +--ro roadm-cd? l0-types:decimal-5-or-null
| | +--ro roadm-pdl? l0-types:power-loss-or-null
| | +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| | +--ro roadm-maxloss? l0-types:power-loss-or-null
| | +--ro roadm-pmax? l0-types:power-dbm-or-null
| | +--ro roadm-osnr? l0-types:snr-or-null
| | +--ro roadm-noise-figure? l0-types:decimal-5-or-null
| +--:(roadm-drop-path)
| +--ro roadm-drop-path* []
| +--ro frequency-range
| | +--ro lower-frequency union
| | +--ro upper-frequency union
| +--ro roadm-pmd? union
| +--ro roadm-cd? l0-types:decimal-5-or-null
| +--ro roadm-pdl? l0-types:power-loss-or-null
| +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| +--ro roadm-maxloss? l0-types:power-loss-or-null
| +--ro roadm-minloss? l0-types:power-loss-or-null
| +--ro roadm-typloss? l0-types:power-loss-or-null
| +--ro roadm-pmin? l0-types:power-dbm-or-null
| +--ro roadm-pmax? l0-types:power-dbm-or-null
| +--ro roadm-ptyp? l0-types:power-dbm-or-null
| +--ro roadm-osnr? l0-types:snr-or-null
| +--ro roadm-noise-figure? l0-types:decimal-5-or-null
+--ro SI* []
| +--ro f_min? decimal64
| +--ro f_max? decimal64
| +--ro spacing? decimal64
| +--ro power_dbm? decimal64
| +--ro power_range_dict_db
| | +--ro min_value? decimal64
| | +--ro max_value? decimal64
| | +--ro step? decimal64
| +--ro type_variety? string
| +--ro sys_margins? decimal64
| +--ro use_si_channel_count_for_design? boolean
| +--ro baud_rate? decimal64
| +--ro tx_osnr? decimal64
| +--ro roll_off? union
| +--ro tx_power_dbm? decimal64
+--rw Transceiver* [type_variety]
+--rw type_variety string
+--rw other_name* string
+--rw comment? string
+--rw frequency
| +--rw min? decimal64
| +--rw max? decimal64
+--rw mode* [format]
+--rw format string
+--rw other_name* string
+--rw OSNR? decimal64
+--rw min_spacing? decimal64
+--rw bit_rate? decimal64
+--rw cost? decimal64
+--rw baud_rate? decimal64
+--rw tx_osnr? decimal64
+--rw roll_off? union
+--rw tx_power_dbm? decimal64
+--ro penalties* []
| +--ro chromatic_dispersion? decimal64
| +--ro pmd? decimal64
| +--ro pdl? decimal64
| +--ro rx-channel-power-value? decimal64
| +--ro penalty_value? decimal64
+--rw equalization_offset_db? decimal64
+--rw tx-channel-power-min? decimal64
+--rw tx-channel-power-max? decimal64
+--rw rx-channel-power-min? decimal64
+--rw rx-channel-power-max? decimal64
augment /gapi:api:
+--rw equipment
+--rw library-information
| +--rw name? string
| +--rw content-schema
| | +--rw module* module-with-revision-date
| +--rw description* string
| +--rw contact* string
| +--rw organization? string
| +--rw revision* [date]
| +--rw date string
| +--rw description? string
+--rw Edfa* [type_variety]
| +--rw type_variety string
| +--rw other_name* string
| +--rw f_min? decimal64
| +--rw f_max? decimal64
| +--rw allowed_for_design? boolean
| +--rw gain_flatmax? decimal64
| +--rw gain_min? decimal64
| +--rw extended_gain_range? decimal64
| +--rw p_max? decimal64
| +--rw type_def? identityref
| +--rw raman? boolean
| +--rw out_voa_auto? boolean
| +--rw in_voa_auto? boolean
| +--rw voa_step? decimal64
| +--rw pmd? decimal64
| +--rw pdl? decimal64
| +--rw (type_of_model)?
| +--:(variable_gain)
| | +--rw nf_min? decimal64
| | +--rw nf_max? decimal64
| | +--rw default_config_from_json? string
| +--:(fixed_gain)
| | +--rw nf0? decimal64
| +--:(openroadm)
| | +--rw nf_coef* [coef_order]
| | +--rw coef_order uint8
| | +--rw nf_coef? decimal64
| +--:(dual_stage)
| | +--rw preamp_variety? union
| | +--rw booster_variety? union
| +--:(multi_band)
| | +--rw amplifiers* string
| +--:(advanced_model)
| +--rw advanced_config_from_json? string
+--rw Fiber* [type_variety]
| +--rw type_variety string
| +--rw dispersion? decimal64
| +--rw gamma? decimal64
| +--rw pmd_coef? decimal64
| +--rw effective_area? decimal64
| +--rw loss_coef_lut* [freq]
| | +--rw freq decimal64
| | +--rw loss_coef_value? decimal64
| +--rw (ref_freq_or_wl)?
| +--:(frequency)
| | +--rw ref_frequency? decimal64
| +--:(wavelength)
| +--rw ref_wavelength? decimal64
+--rw RamanFiber* [type_variety]
| +--rw type_variety string
| +--rw dispersion? decimal64
| +--rw gamma? decimal64
| +--rw pmd_coef? decimal64
| +--rw effective_area? decimal64
| +--rw loss_coef_lut* [freq]
| | +--rw freq decimal64
| | +--rw loss_coef_value? decimal64
| +--rw (ref_freq_or_wl)?
| | +--:(frequency)
| | | +--rw ref_frequency? decimal64
| | +--:(wavelength)
| | +--rw ref_wavelength? decimal64
| +--rw raman_efficiency* [frequency_offset]
| +--rw cr? decimal64
| +--rw frequency_offset decimal64
+--ro Span* []
| +--ro power_mode? boolean
| +--ro delta_power_range_dict_db
| | +--ro min_value? decimal64
| | +--ro max_value? decimal64
| | +--ro step? decimal64
| +--ro max_length? decimal64
| +--ro max_loss? decimal64
| +--ro max_fiber_lineic_loss_for_raman? decimal64
| +--ro target_extended_gain? decimal64
| +--ro length_units? string
| +--ro padding? decimal64
| +--ro EOL? decimal64
| +--ro con_in? decimal64
| +--ro con_out? decimal64
| +--ro span_loss_ref? decimal64
| +--ro power_slope? decimal64
| +--ro voa_margin? decimal64
| +--ro voa_step? decimal64
+--rw Roadm* [type_variety]
| +--rw type_variety string
| +--rw (target_type)?
| | +--:(constant_power)
| | | +--rw target_pch_out_db? decimal64
| | +--:(constant_psd)
| | | +--rw target_psd_out_mWperGHz? decimal64
| | +--:(constant_psw)
| | +--rw target_out_mWperSlotWidth? decimal64
| +--rw add_drop_osnr? decimal64
| +--rw pmd? decimal64
| +--rw pdl? decimal64
| +--rw restrictions
| | +--rw preamp_variety_list* string
| | +--rw booster_variety_list* string
| +--rw roadm-path-impairments* [roadm-path-impairments-id]
| +--rw roadm-path-impairments-id uint32
| +--rw (impairment-type)?
| +--:(roadm-express-path)
| | +--ro roadm-express-path* []
| | +--ro frequency-range
| | | +--ro lower-frequency union
| | | +--ro upper-frequency union
| | +--ro roadm-pmd? union
| | +--ro roadm-cd? l0-types:decimal-5-or-null
| | +--ro roadm-pdl? l0-types:power-loss-or-null
| | +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| | +--ro roadm-maxloss? l0-types:power-loss-or-null
| +--:(roadm-add-path)
| | +--ro roadm-add-path* []
| | +--ro frequency-range
| | | +--ro lower-frequency union
| | | +--ro upper-frequency union
| | +--ro roadm-pmd? union
| | +--ro roadm-cd? l0-types:decimal-5-or-null
| | +--ro roadm-pdl? l0-types:power-loss-or-null
| | +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| | +--ro roadm-maxloss? l0-types:power-loss-or-null
| | +--ro roadm-pmax? l0-types:power-dbm-or-null
| | +--ro roadm-osnr? l0-types:snr-or-null
| | +--ro roadm-noise-figure? l0-types:decimal-5-or-null
| +--:(roadm-drop-path)
| +--ro roadm-drop-path* []
| +--ro frequency-range
| | +--ro lower-frequency union
| | +--ro upper-frequency union
| +--ro roadm-pmd? union
| +--ro roadm-cd? l0-types:decimal-5-or-null
| +--ro roadm-pdl? l0-types:power-loss-or-null
| +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| +--ro roadm-maxloss? l0-types:power-loss-or-null
| +--ro roadm-minloss? l0-types:power-loss-or-null
| +--ro roadm-typloss? l0-types:power-loss-or-null
| +--ro roadm-pmin? l0-types:power-dbm-or-null
| +--ro roadm-pmax? l0-types:power-dbm-or-null
| +--ro roadm-ptyp? l0-types:power-dbm-or-null
| +--ro roadm-osnr? l0-types:snr-or-null
| +--ro roadm-noise-figure? l0-types:decimal-5-or-null
+--ro SI* []
| +--ro f_min? decimal64
| +--ro f_max? decimal64
| +--ro spacing? decimal64
| +--ro power_dbm? decimal64
| +--ro power_range_dict_db
| | +--ro min_value? decimal64
| | +--ro max_value? decimal64
| | +--ro step? decimal64
| +--ro type_variety? string
| +--ro sys_margins? decimal64
| +--ro use_si_channel_count_for_design? boolean
| +--ro baud_rate? decimal64
| +--ro tx_osnr? decimal64
| +--ro roll_off? union
| +--ro tx_power_dbm? decimal64
+--rw Transceiver* [type_variety]
+--rw type_variety string
+--rw other_name* string
+--rw comment? string
+--rw frequency
| +--rw min? decimal64
| +--rw max? decimal64
+--rw mode* [format]
+--rw format string
+--rw other_name* string
+--rw OSNR? decimal64
+--rw min_spacing? decimal64
+--rw bit_rate? decimal64
+--rw cost? decimal64
+--rw baud_rate? decimal64
+--rw tx_osnr? decimal64
+--rw roll_off? union
+--rw tx_power_dbm? decimal64
+--ro penalties* []
| +--ro chromatic_dispersion? decimal64
| +--ro pmd? decimal64
| +--ro pdl? decimal64
| +--ro rx-channel-power-value? decimal64
| +--ro penalty_value? decimal64
+--rw equalization_offset_db? decimal64
+--rw tx-channel-power-min? decimal64
+--rw tx-channel-power-max? decimal64
+--rw rx-channel-power-min? decimal64
+--rw rx-channel-power-max? decimal64
augment /gapi:api/gapi:extra-eqpts:
+--rw equipment
+--rw library-information
| +--rw name? string
| +--rw content-schema
| | +--rw module* module-with-revision-date
| +--rw description* string
| +--rw contact* string
| +--rw organization? string
| +--rw revision* [date]
| +--rw date string
| +--rw description? string
+--rw Edfa* [type_variety]
| +--rw type_variety string
| +--rw other_name* string
| +--rw f_min? decimal64
| +--rw f_max? decimal64
| +--rw allowed_for_design? boolean
| +--rw gain_flatmax? decimal64
| +--rw gain_min? decimal64
| +--rw extended_gain_range? decimal64
| +--rw p_max? decimal64
| +--rw type_def? identityref
| +--rw raman? boolean
| +--rw out_voa_auto? boolean
| +--rw in_voa_auto? boolean
| +--rw voa_step? decimal64
| +--rw pmd? decimal64
| +--rw pdl? decimal64
| +--rw (type_of_model)?
| +--:(variable_gain)
| | +--rw nf_min? decimal64
| | +--rw nf_max? decimal64
| | +--rw default_config_from_json? string
| +--:(fixed_gain)
| | +--rw nf0? decimal64
| +--:(openroadm)
| | +--rw nf_coef* [coef_order]
| | +--rw coef_order uint8
| | +--rw nf_coef? decimal64
| +--:(dual_stage)
| | +--rw preamp_variety? union
| | +--rw booster_variety? union
| +--:(multi_band)
| | +--rw amplifiers* string
| +--:(advanced_model)
| +--rw advanced_config_from_json? string
+--rw Fiber* [type_variety]
| +--rw type_variety string
| +--rw dispersion? decimal64
| +--rw gamma? decimal64
| +--rw pmd_coef? decimal64
| +--rw effective_area? decimal64
| +--rw loss_coef_lut* [freq]
| | +--rw freq decimal64
| | +--rw loss_coef_value? decimal64
| +--rw (ref_freq_or_wl)?
| +--:(frequency)
| | +--rw ref_frequency? decimal64
| +--:(wavelength)
| +--rw ref_wavelength? decimal64
+--rw RamanFiber* [type_variety]
| +--rw type_variety string
| +--rw dispersion? decimal64
| +--rw gamma? decimal64
| +--rw pmd_coef? decimal64
| +--rw effective_area? decimal64
| +--rw loss_coef_lut* [freq]
| | +--rw freq decimal64
| | +--rw loss_coef_value? decimal64
| +--rw (ref_freq_or_wl)?
| | +--:(frequency)
| | | +--rw ref_frequency? decimal64
| | +--:(wavelength)
| | +--rw ref_wavelength? decimal64
| +--rw raman_efficiency* [frequency_offset]
| +--rw cr? decimal64
| +--rw frequency_offset decimal64
+--ro Span* []
| +--ro power_mode? boolean
| +--ro delta_power_range_dict_db
| | +--ro min_value? decimal64
| | +--ro max_value? decimal64
| | +--ro step? decimal64
| +--ro max_length? decimal64
| +--ro max_loss? decimal64
| +--ro max_fiber_lineic_loss_for_raman? decimal64
| +--ro target_extended_gain? decimal64
| +--ro length_units? string
| +--ro padding? decimal64
| +--ro EOL? decimal64
| +--ro con_in? decimal64
| +--ro con_out? decimal64
| +--ro span_loss_ref? decimal64
| +--ro power_slope? decimal64
| +--ro voa_margin? decimal64
| +--ro voa_step? decimal64
+--rw Roadm* [type_variety]
| +--rw type_variety string
| +--rw (target_type)?
| | +--:(constant_power)
| | | +--rw target_pch_out_db? decimal64
| | +--:(constant_psd)
| | | +--rw target_psd_out_mWperGHz? decimal64
| | +--:(constant_psw)
| | +--rw target_out_mWperSlotWidth? decimal64
| +--rw add_drop_osnr? decimal64
| +--rw pmd? decimal64
| +--rw pdl? decimal64
| +--rw restrictions
| | +--rw preamp_variety_list* string
| | +--rw booster_variety_list* string
| +--rw roadm-path-impairments* [roadm-path-impairments-id]
| +--rw roadm-path-impairments-id uint32
| +--rw (impairment-type)?
| +--:(roadm-express-path)
| | +--ro roadm-express-path* []
| | +--ro frequency-range
| | | +--ro lower-frequency union
| | | +--ro upper-frequency union
| | +--ro roadm-pmd? union
| | +--ro roadm-cd? l0-types:decimal-5-or-null
| | +--ro roadm-pdl? l0-types:power-loss-or-null
| | +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| | +--ro roadm-maxloss? l0-types:power-loss-or-null
| +--:(roadm-add-path)
| | +--ro roadm-add-path* []
| | +--ro frequency-range
| | | +--ro lower-frequency union
| | | +--ro upper-frequency union
| | +--ro roadm-pmd? union
| | +--ro roadm-cd? l0-types:decimal-5-or-null
| | +--ro roadm-pdl? l0-types:power-loss-or-null
| | +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| | +--ro roadm-maxloss? l0-types:power-loss-or-null
| | +--ro roadm-pmax? l0-types:power-dbm-or-null
| | +--ro roadm-osnr? l0-types:snr-or-null
| | +--ro roadm-noise-figure? l0-types:decimal-5-or-null
| +--:(roadm-drop-path)
| +--ro roadm-drop-path* []
| +--ro frequency-range
| | +--ro lower-frequency union
| | +--ro upper-frequency union
| +--ro roadm-pmd? union
| +--ro roadm-cd? l0-types:decimal-5-or-null
| +--ro roadm-pdl? l0-types:power-loss-or-null
| +--ro roadm-inband-crosstalk? l0-types:decimal-2-or-null
| +--ro roadm-maxloss? l0-types:power-loss-or-null
| +--ro roadm-minloss? l0-types:power-loss-or-null
| +--ro roadm-typloss? l0-types:power-loss-or-null
| +--ro roadm-pmin? l0-types:power-dbm-or-null
| +--ro roadm-pmax? l0-types:power-dbm-or-null
| +--ro roadm-ptyp? l0-types:power-dbm-or-null
| +--ro roadm-osnr? l0-types:snr-or-null
| +--ro roadm-noise-figure? l0-types:decimal-5-or-null
+--ro SI* []
| +--ro f_min? decimal64
| +--ro f_max? decimal64
| +--ro spacing? decimal64
| +--ro power_dbm? decimal64
| +--ro power_range_dict_db
| | +--ro min_value? decimal64
| | +--ro max_value? decimal64
| | +--ro step? decimal64
| +--ro type_variety? string
| +--ro sys_margins? decimal64
| +--ro use_si_channel_count_for_design? boolean
| +--ro baud_rate? decimal64
| +--ro tx_osnr? decimal64
| +--ro roll_off? union
| +--ro tx_power_dbm? decimal64
+--rw Transceiver* [type_variety]
+--rw type_variety string
+--rw other_name* string
+--rw comment? string
+--rw frequency
| +--rw min? decimal64
| +--rw max? decimal64
+--rw mode* [format]
+--rw format string
+--rw other_name* string
+--rw OSNR? decimal64
+--rw min_spacing? decimal64
+--rw bit_rate? decimal64
+--rw cost? decimal64
+--rw baud_rate? decimal64
+--rw tx_osnr? decimal64
+--rw roll_off? union
+--rw tx_power_dbm? decimal64
+--ro penalties* []
| +--ro chromatic_dispersion? decimal64
| +--ro pmd? decimal64
| +--ro pdl? decimal64
| +--ro rx-channel-power-value? decimal64
| +--ro penalty_value? decimal64
+--rw equalization_offset_db? decimal64
+--rw tx-channel-power-min? decimal64
+--rw tx-channel-power-max? decimal64
+--rw rx-channel-power-min? decimal64
+--rw rx-channel-power-max? decimal64

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module: gnpy-network-topology
+--rw topology
+--rw elements* [uid]
| +--rw uid string
| +--rw type identityref
| +--rw type_variety? string
| +--rw metadata
| | +--rw location
| | +--rw city? union
| | +--rw region? union
| | +--rw latitude? Coordinate
| | +--rw longitude? Coordinate
| +--rw operational
| | +--rw (ramanfiber)?
| | +--:(RamanFiber)
| | | +--rw temperature? decimal64
| | | +--rw raman_pumps* [frequency]
| | | +--rw power? decimal64
| | | +--rw frequency decimal64
| | | +--rw propagation_direction? identityref
| | +--:(Edfa)
| | +--rw gain_target? union
| | +--rw tilt_target? union
| | +--rw out_voa? union
| | +--rw in_voa? union
| | +--rw delta_p? union
| | +--rw f_min? decimal64
| | +--rw f_max? decimal64
| +--rw (element-type)?
| +--:(FiberRoadm)
| | +--rw params
| | +--rw (fiberroadmfused)?
| | +--:(Fiber)
| | | +--rw length decimal64
| | | +--rw pmd_coef? decimal64
| | | +--rw (ref_freq_or_wl)?
| | | | +--:(frequency)
| | | | | +--rw ref_frequency? decimal64
| | | | +--:(wavelength)
| | | | +--rw ref_wavelength? decimal64
| | | +--rw (dispersion-vector-or-scalar)?
| | | | +--:(scalar)
| | | | | +--rw dispersion? decimal64
| | | | | +--rw dispersion_slope? decimal64
| | | | +--:(vector)
| | | | +--rw dispersion_per_frequency* [frequency]
| | | | +--rw frequency decimal64
| | | | +--rw dispersion? decimal64
| | | +--rw effective_area? decimal64
| | | +--rw gamma? decimal64
| | | +--rw raman_coefficient
| | | | +--rw reference_frequency? decimal64
| | | | +--rw g0_per_frequency* [frequency_offset]
| | | | +--rw frequency_offset decimal64
| | | | +--rw g0? decimal64
| | | +--rw lumped_losses* [position]
| | | | +--rw position decimal64
| | | | +--rw loss decimal64
| | | +--rw (loss_coef-vector-or-scalar)?
| | | | +--:(scalar)
| | | | | +--rw loss_coef decimal64
| | | | +--:(vector)
| | | | +--rw loss_coef_per_frequency* [frequency]
| | | | +--rw frequency decimal64
| | | | +--rw loss_coef_value? decimal64
| | | +--rw length_units identityref
| | | +--rw att_in? decimal64
| | | +--rw con_in? union
| | | +--rw con_out? union
| | +--:(RoadmTransceiver)
| | | +--rw design_bands* [f_min]
| | | | +--rw f_min decimal64
| | | | +--rw f_max? decimal64
| | | | +--rw (parameter-used-for-design)?
| | | | +--:(spacing)
| | | | | +--rw spacing? decimal64
| | | | +--:(number-of-channels)
| | | | +--rw number-of-channels? uint16
| | | +--rw per_degree_design_bands_targets* [degree_uid]
| | | | +--rw degree_uid -> ../../../../elements/uid
| | | | +--rw design_bands* [f_min]
| | | | +--rw f_min decimal64
| | | | +--rw f_max? decimal64
| | | | +--rw (parameter-used-for-design)?
| | | | +--:(spacing)
| | | | | +--rw spacing? decimal64
| | | | +--:(number-of-channels)
| | | | +--rw number-of-channels? uint16
| | | +--rw (roadm)?
| | | +--:(roadm)
| | | +--rw (target_type)?
| | | | +--:(constant_power)
| | | | | +--rw target_pch_out_db? decimal64
| | | | +--:(constant_psd)
| | | | | +--rw target_psd_out_mWperGHz? decimal64
| | | | +--:(constant_psw)
| | | | +--rw target_out_mWperSlotWidth? decimal64
| | | +--rw restrictions
| | | | +--rw preamp_variety_list* string
| | | | +--rw booster_variety_list* string
| | | +--rw per_degree_power_targets* [degree_uid]
| | | | +--rw degree_uid -> ../../../../elements/uid
| | | | +--rw (per_degree_target_type)?
| | | | +--:(constant_power)
| | | | | +--rw per_degree_pch_out_db? decimal64
| | | | +--:(constant_psd)
| | | | | +--rw per_degree_psd_out_mWperGHz? decimal64
| | | | +--:(constant_psw)
| | | | +--rw per_degree_psd_out_mWperSlotWidth? decimal64
| | | +--rw per_degree_impairments* [from_degree to_degree]
| | | +--rw from_degree -> ../../../../elements/uid
| | | +--rw to_degree -> ../../../../elements/uid
| | | +--rw impairment_id? uint32
| | +--:(Fused)
| | | +--rw loss? union
| | +--:(Multiband_amplifier)
| | +--rw variety_list* string
| +--:(Multiband_amplifier)
| +--rw amplifiers* [type_variety]
| +--rw type_variety string
| +--rw operational
| +--rw gain_target? union
| +--rw tilt_target? union
| +--rw out_voa? union
| +--rw in_voa? union
| +--rw delta_p? union
| +--rw f_min? decimal64
| +--rw f_max? decimal64
+--rw connections* [from_node to_node]
| +--rw from_node -> ../../elements/uid
| +--rw to_node -> ../../elements/uid
+--rw network_name? string
augment /gapi:api:
+--rw topology
+--rw elements* [uid]
| +--rw uid string
| +--rw type identityref
| +--rw type_variety? string
| +--rw metadata
| | +--rw location
| | +--rw city? union
| | +--rw region? union
| | +--rw latitude? Coordinate
| | +--rw longitude? Coordinate
| +--rw operational
| | +--rw (ramanfiber)?
| | +--:(RamanFiber)
| | | +--rw temperature? decimal64
| | | +--rw raman_pumps* [frequency]
| | | +--rw power? decimal64
| | | +--rw frequency decimal64
| | | +--rw propagation_direction? identityref
| | +--:(Edfa)
| | +--rw gain_target? union
| | +--rw tilt_target? union
| | +--rw out_voa? union
| | +--rw in_voa? union
| | +--rw delta_p? union
| | +--rw f_min? decimal64
| | +--rw f_max? decimal64
| +--rw (element-type)?
| +--:(FiberRoadm)
| | +--rw params
| | +--rw (fiberroadmfused)?
| | +--:(Fiber)
| | | +--rw length decimal64
| | | +--rw pmd_coef? decimal64
| | | +--rw (ref_freq_or_wl)?
| | | | +--:(frequency)
| | | | | +--rw ref_frequency? decimal64
| | | | +--:(wavelength)
| | | | +--rw ref_wavelength? decimal64
| | | +--rw (dispersion-vector-or-scalar)?
| | | | +--:(scalar)
| | | | | +--rw dispersion? decimal64
| | | | | +--rw dispersion_slope? decimal64
| | | | +--:(vector)
| | | | +--rw dispersion_per_frequency* [frequency]
| | | | +--rw frequency decimal64
| | | | +--rw dispersion? decimal64
| | | +--rw effective_area? decimal64
| | | +--rw gamma? decimal64
| | | +--rw raman_coefficient
| | | | +--rw reference_frequency? decimal64
| | | | +--rw g0_per_frequency* [frequency_offset]
| | | | +--rw frequency_offset decimal64
| | | | +--rw g0? decimal64
| | | +--rw lumped_losses* [position]
| | | | +--rw position decimal64
| | | | +--rw loss decimal64
| | | +--rw (loss_coef-vector-or-scalar)?
| | | | +--:(scalar)
| | | | | +--rw loss_coef decimal64
| | | | +--:(vector)
| | | | +--rw loss_coef_per_frequency* [frequency]
| | | | +--rw frequency decimal64
| | | | +--rw loss_coef_value? decimal64
| | | +--rw length_units identityref
| | | +--rw att_in? decimal64
| | | +--rw con_in? union
| | | +--rw con_out? union
| | +--:(RoadmTransceiver)
| | | +--rw design_bands* [f_min]
| | | | +--rw f_min decimal64
| | | | +--rw f_max? decimal64
| | | | +--rw (parameter-used-for-design)?
| | | | +--:(spacing)
| | | | | +--rw spacing? decimal64
| | | | +--:(number-of-channels)
| | | | +--rw number-of-channels? uint16
| | | +--rw per_degree_design_bands_targets* [degree_uid]
| | | | +--rw degree_uid -> ../../../../elements/uid
| | | | +--rw design_bands* [f_min]
| | | | +--rw f_min decimal64
| | | | +--rw f_max? decimal64
| | | | +--rw (parameter-used-for-design)?
| | | | +--:(spacing)
| | | | | +--rw spacing? decimal64
| | | | +--:(number-of-channels)
| | | | +--rw number-of-channels? uint16
| | | +--rw (roadm)?
| | | +--:(roadm)
| | | +--rw (target_type)?
| | | | +--:(constant_power)
| | | | | +--rw target_pch_out_db? decimal64
| | | | +--:(constant_psd)
| | | | | +--rw target_psd_out_mWperGHz? decimal64
| | | | +--:(constant_psw)
| | | | +--rw target_out_mWperSlotWidth? decimal64
| | | +--rw restrictions
| | | | +--rw preamp_variety_list* string
| | | | +--rw booster_variety_list* string
| | | +--rw per_degree_power_targets* [degree_uid]
| | | | +--rw degree_uid -> ../../../../elements/uid
| | | | +--rw (per_degree_target_type)?
| | | | +--:(constant_power)
| | | | | +--rw per_degree_pch_out_db? decimal64
| | | | +--:(constant_psd)
| | | | | +--rw per_degree_psd_out_mWperGHz? decimal64
| | | | +--:(constant_psw)
| | | | +--rw per_degree_psd_out_mWperSlotWidth? decimal64
| | | +--rw per_degree_impairments* [from_degree to_degree]
| | | +--rw from_degree -> ../../../../elements/uid
| | | +--rw to_degree -> ../../../../elements/uid
| | | +--rw impairment_id? uint32
| | +--:(Fused)
| | | +--rw loss? union
| | +--:(Multiband_amplifier)
| | +--rw variety_list* string
| +--:(Multiband_amplifier)
| +--rw amplifiers* [type_variety]
| +--rw type_variety string
| +--rw operational
| +--rw gain_target? union
| +--rw tilt_target? union
| +--rw out_voa? union
| +--rw in_voa? union
| +--rw delta_p? union
| +--rw f_min? decimal64
| +--rw f_max? decimal64
+--rw connections* [from_node to_node]
| +--rw from_node -> ../../elements/uid
| +--rw to_node -> ../../elements/uid
+--rw network_name? string

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module gnpy-network-topology {
yang-version 1.1;
namespace "gnpy:gnpy-network-topology";
prefix gnpynt;
import gnpy-api {
prefix "gapi";
revision-date 2025-06-13;
}
import gnpy-eqpt-config {
prefix "geqpt";
revision-date 2025-05-26;
}
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 2025-03-01 {
description
"spacing for design band and pmd_coef";
reference
"YANG model for network input for path computation with gnpy";
}
revision 2025-01-20 {
description
"Add RamanFiber, design bands, impairments";
reference
"YANG model for network input for path computation with gnpy";
}
revision 2024-02-21 {
description
"fix namespaces for identity-ref,
add roadm impairment";
reference
"YANG model for network input for path computation with gnpy";
}
revision 2023-02-01 {
description
"change per-degree roadm targets
set 6 digits for fiber length
set 6 digits for loss_coef
add type empty for con_in and con_out";
reference
"YANG model for network input for path computation with gnpy";
}
revision 2022-11-21 {
description
"draft for detecon - GNPy API";
reference
"YANG model for network input for path computation with gnpy";
}
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 RamanFiber {
base type-element;
description
"RamanFiber 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 Multiband_amplifier {
base type-element;
description
"Multiband_amplifier element";
}
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;
}
description
"Latitude or longitude type";
}
identity pumping-direction {
description
"Raman pumping direction";
}
identity coprop {
base pumping-direction;
description
"forward pumping";
}
identity counterprop {
base pumping-direction;
description
"backward pumping";
}
grouping location-attributes {
description
"grouping for location imformation: city, region names
and coordinates.";
container location {
description
"Information for a node location: city, region names
and coordinates.";
leaf city {
type union {
type string;
type empty;
}
description
"City name.";
}
leaf region {
type union {
type string;
type empty;
}
description
"Region name. Used for filtering purpose.";
}
leaf latitude {
type Coordinate;
description
"Latitude coordinate.";
}
leaf longitude {
type Coordinate;
description
"Longitude coordinate.";
}
}
}
grouping fiber-common-params {
description
"Common attributes to fiber and raman fiber.";
leaf length {
type decimal64 {
fraction-digits 6;
}
mandatory true;
description
"Length of the fiber span.";
}
leaf pmd_coef {
type decimal64 {
fraction-digits 18;
}
units "s/km^0.5";
description "PMD coefficient of the fiber span (s/km^0.5)";
}
choice ref_freq_or_wl {
description
"Definition of the reference: frequency or wavelength.";
case frequency {
leaf ref_frequency {
type decimal64 {
fraction-digits 1;
}
units "Hz";
description
"Reference frequency for all parameters evaluation
(unique for all parameters: beta2, beta3, gamma, effective_area)";
}
}
case wavelength {
leaf ref_wavelength {
type decimal64 {
fraction-digits 12;
}
units "m";
description
"Reference wavelength for all parameters evaluation
(unique for all parameters: beta2, beta3, gamma, effective_area)";
}
}
}
choice dispersion-vector-or-scalar {
description
"Dispersion definition: scalar with its slope or array of
values and the slope is computed based on the values.";
case scalar {
leaf dispersion {
type decimal64 {
fraction-digits 8;
}
units "s.m-1.m-1";
description "Dispersion of the span fiber.";
}
leaf dispersion_slope {
type decimal64 {
fraction-digits 11;
}
units "s.m-1.m-1.m-1";
description "Dispersion slope of the span fiber.";
}
}
case vector {
list dispersion_per_frequency {
key "frequency";
description
"Dispersion per frequency value.";
leaf frequency {
type decimal64 {
fraction-digits 1;
}
units "Hz";
description "Frequency of the loss coef.";
}
leaf dispersion {
type decimal64 {
fraction-digits 8;
}
units "s.m-1.m-1";
description "Dispersion of the span fiber.";
}
}
}
}
leaf effective_area {
type decimal64 {
fraction-digits 14;
}
units "m^2";
description "Effective Area of the span fibery.";
}
leaf gamma{
type decimal64 {
fraction-digits 8;
}
units "w-1.m-1" ;
description "2pi.n2/(lambda*Aeff) (w-2.m-1)";
}
container raman_coefficient {
description
"Raman coeeficient definition (for Stimulated Raman Scattering
and Raman amplification)";
leaf reference_frequency {
type decimal64 {
fraction-digits 1;
}
units "Hz";
description
"Reference frequency used with frequency offset values
for Raman coefficient evaluation.";
}
list g0_per_frequency {
key frequency_offset;
description
"Raman gain coefficient in terms of optical power defined per frequency.";
leaf frequency_offset {
type decimal64 {
fraction-digits 1;
}
units "Hz";
description
"Frequency offset.";
}
leaf g0 {
type decimal64 {
fraction-digits 14;
}
units "1/(m.W)";
description "Raman gain coefficient in terms of optical power.";
}
}
}
list lumped_losses {
key "position";
description "Places along the fiber length with extra
losses. Specified as a loss in dB at each relevant position (in km).";
leaf position {
type decimal64 {
fraction-digits 6;
}
units "km";
mandatory true;
description "Position of the lumped loss on the fiber.";
}
leaf loss {
type decimal64 {
fraction-digits 2;
}
units "dB";
mandatory true;
description "Loss of the lumped loss on the fiber.";
}
}
choice loss_coef-vector-or-scalar {
description
"Loss coef definition: scalar or per frequency vector";
case scalar {
leaf loss_coef {
type decimal64 {
fraction-digits 6;
}
units "dB/km";
mandatory true;
description "Loss coefficient of the fiber span (dB/km)";
}
}
case vector {
list loss_coef_per_frequency {
key frequency;
description
"Per frequency loss_coef definition.";
leaf frequency {
type decimal64 {
fraction-digits 1;
}
units "Hz";
description
"Frequency of the loss coef value.";
}
leaf loss_coef_value {
type decimal64 {
fraction-digits 16;
}
units "dB/km";
description
"Loss coef oat the frequency value.";
}
}
}
}
leaf length_units {
type identityref {
base length-unit;
}
mandatory true;
description
"Length unit used for the length definition (m or km)";
}
leaf att_in {
type decimal64 {
fraction-digits 2;
}
units "dB";
description
"Padding attenuation placed at span input to reach min loss
target defined in the library.";
}
leaf con_in {
type union {
type decimal64 {
fraction-digits 2;
}
type empty;
}
units "dB";
description
"Input connector loss.";
}
leaf con_out {
type union {
type decimal64 {
fraction-digits 2;
}
type empty;
}
units "dB";
description
"Output connector loss.";
}
}
grouping raman-fiber-operational {
description
"Raman pumps definition of the Raman Fiber.";
leaf temperature {
type decimal64 {
fraction-digits 2;
}
description
"Temperature of the fiber.";
}
list raman_pumps {
description
"Definition of Raman pumps.";
key "frequency";
leaf power {
type decimal64 {
fraction-digits 9;
}
units "W";
description
"Total pump power considering a depolarized pump.";
}
leaf frequency {
type decimal64 {
fraction-digits 1;
}
units "Hz";
description
"Pump central frequency.";
}
leaf propagation_direction {
type identityref {
base pumping-direction;
}
description
"Pump injection direction: the pumps can propagate in
the same or opposite direction with respect the signal.
Valid choices are coprop and counterprop";
}
}
}
grouping edfa-params {
description
"Common parameters for amplifiers definition.";
leaf gain_target {
type union {
type decimal64 {
fraction-digits 6;
}
type empty;
}
units "dB";
description
"gain target of the amplifier (before VOA and after att_in)";
}
leaf tilt_target {
type union {
type decimal64 {
fraction-digits 6;
}
type empty;
}
units "dB";
description
"Tilt target on the whole wavelength range of the amplifier.";
}
leaf out_voa {
type union {
type decimal64 {
fraction-digits 2;
}
type empty;
}
units "dB";
description
"Output variable optical attenuator loss";
}
leaf in_voa {
type union {
type decimal64 {
fraction-digits 2;
}
type empty;
}
units "dB";
description
"Input variable optical attenuator loss";
}
leaf delta_p {
type union {
type decimal64 {
fraction-digits 6;
}
type empty;
}
units "dB";
description
"Per channel target output power deviation with respect to power settings in SI.";
}
}
grouping multiband-params {
description
"Attributes for multiband amplifiers";
list amplifiers {
key "type_variety";
description
"Definition of attributes of each amplifier of the multiband amplifier.";
leaf type_variety {
type string;
description
"Type_variety definition.";
}
container operational {
description
"Operational values for the Edfa ";
uses edfa-params;
uses geqpt:frequency-band;
}
}
}
grouping design-bands {
description "Values used to compute the maximum power in
amplifier during autodesign phase";
choice parameter-used-for-design {
description
"Values used to compute the maximum power in
amplifier during autodesign phase";
case spacing {
leaf spacing {
type decimal64 {
fraction-digits 2;
}
units "Hz";
description
"Spacing used to compute max power in the spans
during autodesign.";
}
}
case number-of-channels {
leaf number-of-channels {
type uint16 {
range "1 .. max";
}
description
"Number of channels used to compute max power in the spans
during autodesign.";
}
}
}
}
grouping roadm-trx-params {
description
"Design band attributes common to ROADM and Transceivers,
Used for autodesign";
list design_bands {
key "f_min";
uses geqpt:frequency-band;
uses design-bands;
description
"Value used to compute the maximum power in
amplifier during autodesign phase, same for all degrees.";
}
list per_degree_design_bands_targets {
key "degree_uid";
description
"Per degree definition of design bands used to compute the maximum power in
amplifier during autodesign phase.";
leaf degree_uid {
type leafref {
path "../../../../elements/uid";
}
description
"Degree identifier (= uid of the next element on this direction).";
}
list design_bands {
key "f_min";
uses geqpt:frequency-band;
uses design-bands;
description
"Value used to compute the maximum power in
amplifier during autodesign phase, same for all degrees.";
}
}
}
grouping roadm-params {
description
"Definition of ROADM configuration parameters.";
uses geqpt:roadm-equalization-params;
uses geqpt:restrictions;
list per_degree_power_targets {
key "degree_uid";
description
"Equalization strategy for this degree. If not defined, use the
one defined in ROADM.";
leaf degree_uid {
type leafref {
path "../../../../elements/uid";
}
description
"Degree identifier (= uid of the next element on this direction).";
}
choice per_degree_target_type {
description
"Equalization strategy for this ROADM. If not defined, the
one defined in library for this type_variety is used.";
case constant_power {
leaf per_degree_pch_out_db {
type decimal64 {
fraction-digits 2;
}
units "dBm";
description
"Equalization applied on all channels on this degree.
This target replaces the one defined for all degrees";
}
}
case constant_psd {
leaf per_degree_psd_out_mWperGHz {
type decimal64 {
fraction-digits 10;
}
units "mW/GHz";
description
"Equalization applied on all channels on this degree.
This target replaces the one defined for all degrees";
}
}
case constant_psw {
leaf per_degree_psd_out_mWperSlotWidth {
type decimal64 {
fraction-digits 10;
}
units "mW/GHz";
description
"Equalization applied on all channels on this degree.
This target replaces the one defined for all degrees";
}
}
}
}
list per_degree_impairments {
key "from_degree to_degree";
description
"Definition of impairments for this ROADM.";
leaf from_degree {
type leafref {
path "../../../../elements/uid";
}
description
"Degree identifier (= uid of the next element on this direction).";
}
leaf to_degree {
type leafref {
path "../../../../elements/uid";
}
description
"Degree identifier (= uid of the next element on this direction).";
}
leaf impairment_id {
type uint32;
description
"Reference to the impairment ID defined in the library.";
}
}
}
grouping fused-params{
description
"Parameters for Fused elements.";
leaf loss {
type union {
type decimal64 {
fraction-digits 2;
}
type empty;
}
units "dB";
description
"Concentrated loss of the fused element";
}
}
grouping element-type-choice {
description
"Definition of operational container for RamanFiber or Edfa, and of
params container for all elements.";
container operational {
when "../type = 'gnpynt:Edfa' or ../type = 'gnpynt:RamanFiber'";
description
"Operational values for the Edfa and the RamanFiber";
choice ramanfiber {
description
"Definition of operational parameters for RamanFibers";
case RamanFiber {
when "../type = 'gnpynt:RamanFiber'";
uses raman-fiber-operational;
}
case Edfa {
when "../type = 'gnpynt:Edfa'";
uses edfa-params;
uses geqpt:frequency-band;
}
}
}
choice element-type {
description
"Params content depending on element type.";
case FiberRoadm {
container params {
description
"parameters definition in case of Fiber, RamanFiber, Roadm, Fused, Transceivers";
choice fiberroadmfused {
description
"parameters definition in case of Fiber, RamanFiber, Roadm, Fused, Transceivers";
case Fiber {
when "../type = 'gnpynt:Fiber' or ../type = 'gnpynt:RamanFiber'";
uses fiber-common-params;
}
case RoadmTransceiver {
when "../type = 'gnpynt:Roadm' or ../type = 'gnpynt:Transceiver'";
uses roadm-trx-params;
choice roadm {
description
"parameters definition only in case of Roadm.";
case roadm {
when "../type = 'gnpynt:Roadm'";
uses roadm-params;
}
}
}
case Fused {
when "../type = 'gnpynt:Fused'";
uses fused-params;
}
case Multiband_amplifier {
when "../type = 'gnpynt:Multiband_amplifier'";
leaf-list variety_list {
type string;
description
"List of authorized type-variety";
}
}
}
}
}
case Multiband_amplifier {
when "type = 'gnpynt:Multiband_amplifier'";
uses multiband-params;
}
}
}
grouping topo {
description
"Definition of the topology: list of elements and connections.";
list elements {
description
"element definition.";
key "uid";
leaf uid {
type string;
description
"element unique identifier";
}
leaf type {
type identityref {
base type-element;
}
mandatory true;
description
"element type among possible types (Fiber, RamanFiber, Edfa,
Multiband_amplifier, Fused, Roadm, Transceiver).";
}
leaf type_variety {
type string;
description
"Valid reference to a library reference type variety for (Fiber,
RamanFiber, Edfa, Multiband_amplifier, Roadm).";
}
container metadata {
description
"Metadata definitions.";
uses location-attributes;
}
uses element-type-choice;
}
list connections {
key "from_node to_node";
description
"List on connections between elements.";
leaf from_node {
type leafref {
path "../../elements/uid";
}
description
"Ingress node of the connection, reference to a defined element in the topology";
}
leaf to_node {
type leafref {
path "../../elements/uid";
}
description
"Egress node of the connection, reference to a defined element in the topology";
}
}
}
grouping gnpytopo {
description
"Reusable grouping for topology definition.";
container topology {
description
"Describe the topology gnpy-formated for release 2.6 toaster (including mixed rate and multiband)";
uses topo;
leaf network_name {
type string;
}
}
}
container topology {
description
"Describe the topology gnpy-formated for release 2.6 toaster (including mixed rate and multiband)";
uses topo;
leaf network_name {
type string;
}
}
augment "/gapi:api" {
description "Add the gnpy-network-topology input in the API request.";
uses gnpytopo;
}
}

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@@ -0,0 +1,235 @@
module: gnpy-path-computation
+--rw services
| +--rw path-request* [request-id]
| | +--rw request-id string
| | +--rw bidirectional boolean
| | +--rw source? string
| | +--rw destination? string
| | +--rw src-tp-id? string
| | +--rw dst-tp-id? string
| | +--rw explicit-route-objects
| | | +--ro route-object-include-exclude* [index]
| | | +--ro explicit-route-usage? identityref
| | | +--ro index uint32
| | | +--ro (subobject-type)?
| | | +--:(num-unnum-hop)
| | | | +--ro num-unnum-hop
| | | | +--ro node-id? string
| | | | +--ro link-tp-id? string
| | | | +--ro hop-type? te-hop-type
| | | +--:(label)
| | | | +--ro label-hop* [N]
| | | | +--ro N union
| | | | +--ro M? union
| | | +--:(hop-attribute)
| | | +--ro (hop-type)?
| | | +--:(tsp)
| | | | +--ro transponder
| | | | +--ro transponder-type? string
| | | | +--ro transponder-mode? string
| | | +--:(regen)
| | | +--ro regenerator
| | | +--ro transponder-type? string
| | | +--ro transponder-mode? string
| | +--rw path-constraints
| | +--rw te-bandwidth
| | +--rw technology? string
| | +--rw trx_type string
| | +--rw trx_mode? union
| | +--rw effective-freq-slot* [N]
| | | +--rw N union
| | | +--rw M? union
| | +--rw spacing decimal64
| | +--rw max-nb-of-channel? union
| | +--rw output-power? union
| | +--rw tx_power? union
| | +--rw path_bandwidth decimal64
| +--rw synchronization* [synchronization-id]
| +--rw synchronization-id string
| +--rw svec
| +--rw relaxable? boolean
| +--rw disjointness? te-path-disjointness
| +--rw request-id-number* string
+--rw responses
+--rw response* [response-id]
+--rw response-id string
+--rw path-properties
| +--rw path-metric* [metric-type]
| | +--rw metric-type identityref
| | +--rw accumulative-value? union
| +--rw z-a-path-metric* [metric-type]
| | +--rw metric-type identityref
| | +--rw accumulative-value? union
| +--ro path-route-objects* []
| +--ro path-route-object
| +--ro index? uint32
| +--ro (subobject-type)?
| +--:(num-unnum-hop)
| | +--ro num-unnum-hop
| | +--ro node-id? string
| | +--ro link-tp-id? string
| | +--ro hop-type? te-hop-type
| +--:(label)
| | +--ro label-hop* [N]
| | +--ro N union
| | +--ro M? union
| +--:(hop-attribute)
| +--ro (hop-type)?
| +--:(tsp)
| | +--ro transponder
| | +--ro transponder-type? string
| | +--ro transponder-mode? string
| +--:(regen)
| +--ro regenerator
| +--ro transponder-type? string
| +--ro transponder-mode? string
+--rw no-path
+--rw no-path? identityref
+--rw path-properties
+--rw path-metric* [metric-type]
| +--rw metric-type identityref
| +--rw accumulative-value? union
+--rw z-a-path-metric* [metric-type]
| +--rw metric-type identityref
| +--rw accumulative-value? union
+--ro path-route-objects* []
+--ro path-route-object
+--ro index? uint32
+--ro (subobject-type)?
+--:(num-unnum-hop)
| +--ro num-unnum-hop
| +--ro node-id? string
| +--ro link-tp-id? string
| +--ro hop-type? te-hop-type
+--:(label)
| +--ro label-hop* [N]
| +--ro N union
| +--ro M? union
+--:(hop-attribute)
+--ro (hop-type)?
+--:(tsp)
| +--ro transponder
| +--ro transponder-type? string
| +--ro transponder-mode? string
+--:(regen)
+--ro regenerator
+--ro transponder-type? string
+--ro transponder-mode? string
augment /gapi:api:
+--rw services
| +--rw path-request* [request-id]
| | +--rw request-id string
| | +--rw bidirectional boolean
| | +--rw source? string
| | +--rw destination? string
| | +--rw src-tp-id? string
| | +--rw dst-tp-id? string
| | +--rw explicit-route-objects
| | | +--ro route-object-include-exclude* [index]
| | | +--ro explicit-route-usage? identityref
| | | +--ro index uint32
| | | +--ro (subobject-type)?
| | | +--:(num-unnum-hop)
| | | | +--ro num-unnum-hop
| | | | +--ro node-id? string
| | | | +--ro link-tp-id? string
| | | | +--ro hop-type? te-hop-type
| | | +--:(label)
| | | | +--ro label-hop* [N]
| | | | +--ro N union
| | | | +--ro M? union
| | | +--:(hop-attribute)
| | | +--ro (hop-type)?
| | | +--:(tsp)
| | | | +--ro transponder
| | | | +--ro transponder-type? string
| | | | +--ro transponder-mode? string
| | | +--:(regen)
| | | +--ro regenerator
| | | +--ro transponder-type? string
| | | +--ro transponder-mode? string
| | +--rw path-constraints
| | +--rw te-bandwidth
| | +--rw technology? string
| | +--rw trx_type string
| | +--rw trx_mode? union
| | +--rw effective-freq-slot* [N]
| | | +--rw N union
| | | +--rw M? union
| | +--rw spacing decimal64
| | +--rw max-nb-of-channel? union
| | +--rw output-power? union
| | +--rw tx_power? union
| | +--rw path_bandwidth decimal64
| +--rw synchronization* [synchronization-id]
| +--rw synchronization-id string
| +--rw svec
| +--rw relaxable? boolean
| +--rw disjointness? te-path-disjointness
| +--rw request-id-number* string
+--rw responses
+--rw response* [response-id]
+--rw response-id string
+--rw path-properties
| +--rw path-metric* [metric-type]
| | +--rw metric-type identityref
| | +--rw accumulative-value? union
| +--rw z-a-path-metric* [metric-type]
| | +--rw metric-type identityref
| | +--rw accumulative-value? union
| +--ro path-route-objects* []
| +--ro path-route-object
| +--ro index? uint32
| +--ro (subobject-type)?
| +--:(num-unnum-hop)
| | +--ro num-unnum-hop
| | +--ro node-id? string
| | +--ro link-tp-id? string
| | +--ro hop-type? te-hop-type
| +--:(label)
| | +--ro label-hop* [N]
| | +--ro N union
| | +--ro M? union
| +--:(hop-attribute)
| +--ro (hop-type)?
| +--:(tsp)
| | +--ro transponder
| | +--ro transponder-type? string
| | +--ro transponder-mode? string
| +--:(regen)
| +--ro regenerator
| +--ro transponder-type? string
| +--ro transponder-mode? string
+--rw no-path
+--rw no-path? identityref
+--rw path-properties
+--rw path-metric* [metric-type]
| +--rw metric-type identityref
| +--rw accumulative-value? union
+--rw z-a-path-metric* [metric-type]
| +--rw metric-type identityref
| +--rw accumulative-value? union
+--ro path-route-objects* []
+--ro path-route-object
+--ro index? uint32
+--ro (subobject-type)?
+--:(num-unnum-hop)
| +--ro num-unnum-hop
| +--ro node-id? string
| +--ro link-tp-id? string
| +--ro hop-type? te-hop-type
+--:(label)
| +--ro label-hop* [N]
| +--ro N union
| +--ro M? union
+--:(hop-attribute)
+--ro (hop-type)?
+--:(tsp)
| +--ro transponder
| +--ro transponder-type? string
| +--ro transponder-mode? string
+--:(regen)
+--ro regenerator
+--ro transponder-type? string
+--ro transponder-mode? string

View File

@@ -0,0 +1,728 @@
module gnpy-path-computation {
yang-version 1.1;
namespace "gnpy:gnpy-path-computation";
prefix "gnpypc";
import gnpy-api {
prefix "gapi";
revision-date 2025-06-13;
}
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 "2025-01-20" {
description
"Add tx_power";
reference
"YANG model for path computation with gnpy inputs";
}
revision "2022-12-01" {
description
"draft for detecon - GNPy API";
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 union {
type int32;
type empty;
}
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 union {
type uint32;
type empty;
}
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 transceiver type (to be read from equipment library";
}
leaf trx_mode {
type union {
type string;
type empty;
}
description "name of the transceiver mode (to be read from equipment library";
}
list effective-freq-slot {
key "N";
description
"Definition of a list of frequency slots using n and m values (ITU T G694.1)";
uses effective-freq-slot ;
}
leaf spacing {
type decimal64 {
fraction-digits 2;
}
units Hz;
mandatory true;
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 union {
type int32;
type empty;
}
description "Nb of channel to take into account for the full load case.
";
}
leaf output-power{
type union {
type decimal64 {
fraction-digits 8;
}
type empty;
}
units W;
description "optical power setting to be used for the propagation";
}
leaf tx_power{
type union {
type decimal64 {
fraction-digits 5;
}
type empty;
}
units W;
description "optical power out of transceiver";
}
leaf path_bandwidth{
type decimal64 {
fraction-digits 1;
}
units bit/s;
mandatory true;
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 lowest_SNR-0.1nm {
base path-metric-type;
description
"A metric that records the lowest SNR in 0.1nm in spectrum";
}
identity biggest_SNR-0.1nm {
base path-metric-type;
description
"A metric that records the lowest SNR in 0.1nm in spectrum";
}
identity PDL_penalty {
base path-metric-type;
description
"A metric that records the PDL penalty.";
}
identity PMD_penalty {
base path-metric-type;
description
"A metric that records the PMD penalty.";
}
identity CD_penalty {
base path-metric-type;
description
"A metric that records the CD penalty.";
}
identity reference_power {
base path-metric-type;
description
"to be revised";
}
identity path_bandwidth {
base path-metric-type;
description
"to be revised";
}
grouping transponder{
description
"Transponder type and mode used in the hop.";
leaf transponder-type {
type string ;
description
"transceiver type.";
}
leaf transponder-mode {
type string ;
description
"transceiver mode.";
}
}
grouping hop-attribute{
description
"This grouping defines the hop attribute parameters for request or response";
choice hop-type{
description
"Hop may be a regenerator or a terminal.";
case tsp {
container transponder {
description
"Transponder hop in the path. (at source and at destination)";
uses transponder ;
}
}
case regen {
container regenerator{
description
"Regenerator hop in the path.";
uses transponder ;
}
}
}
}
identity no-path-type {
description
"base for blocking reasons";
}
identity NO_PATH {
base no-path-type;
description
"Cause of feasibility failure: no path could be computed.";
}
identity NO_PATH_WITH_CONSTRAINT {
base no-path-type;
description
"Cause of feasibility failure: no path can meet the includec
node constraint.";
}
identity NO_FEASIBLE_BAUDRATE_WITH_SPACING {
base no-path-type;
description
"Cause of feasibility failure: no mode can fit in the
requested spectrum.";
}
identity NO_COMPUTED_SNR {
base no-path-type;
description
"Cause of feasibility failure: requests SNR performance
could not be computed";
}
identity MODE_NOT_FEASIBLE {
base no-path-type;
description
"Cause of feasibility failure: requested mode does not provide
enough performance for this path.";
}
identity NO_FEASIBLE_MODE {
base no-path-type;
description
"Cause of feasibility failure: no mode of this transceiver
can achieve enough performance for the path.";
}
identity NO_SPECTRUM {
base no-path-type;
description
"Cause of feasibility failure: requests requires more spectrum
than the actual available spectrum on the path.";
}
identity NOT_ENOUGH_RESERVED_SPECTRUM {
base no-path-type;
description
"Cause of feasibility failure: signal requires more spectrum
than the one defined in the request.";
}
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 {
key "index";
config false;
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.";
}
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 subobject-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 {
list label-hop {
key "N";
config false;
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 service {
description
"reusable grouping for path computation requests.";
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 accumulated-metric-object {
description
"Reusable grouping for performance metrics.";
leaf metric-type {
type identityref {
base path-metric-type;
}
description
"Metric type.";
}
leaf accumulative-value {
type union {
type decimal64 {
fraction-digits 8;
}
type decimal64 {
fraction-digits 2;
}
type decimal64 {
fraction-digits 1;
}
type string;
type empty;
}
description
"Accumulative value.";
}
}
grouping response-path-property {
description
"Reusable grouping for responses of a path computation request.";
list path-metric {
key metric-type;
description
"List of accumulated metrics at the end of the path.";
uses accumulated-metric-object;
}
list z-a-path-metric {
key metric-type;
description
"List of accumulated metrics at the end of the path.";
uses accumulated-metric-object;
}
}
grouping response-path-route-object {
description
"Definition of the explicit path of one response";
list path-route-objects {
config false;
description
"List of the explicit path hops.";
container path-route-object {
description
"Definition of the hop.";
uses explicit-route-hop ;
}
}
}
grouping response {
description
"Reusable grouping for path computation response.";
list response {
key response-id;
description
"List of responses for the path-computation request.";
leaf response-id {
type string;
mandatory true;
description "Each path computation response is uniquely identified by the response-id number.";
}
container path-properties {
description
"Definition of the content of the successful response";
uses response-path-property;
uses response-path-route-object;
}
container no-path {
description
"Definition of the content of the response when feasibility is not achieved.";
leaf no-path {
type identityref {
base no-path-type;
}
description
"Detailed reason for feasibility failure.";
}
container path-properties {
description
"Definition of the content of the failed response";
uses response-path-property;
uses response-path-route-object;
}
}
}
}
grouping path-computation {
description
"Reusable grouping that defined data for requests or for
responses of a path-computation";
container services {
description
"Definition of path-computation requests.";
uses service;
}
container responses {
description
"Definition of path-computation responses.";
uses response;
}
}
container services {
description
"Definition of path-computation requests.";
uses service;
}
container responses {
description
"Definition of path-computation responses.";
uses response;
}
augment "/gapi:api" {
description "Add the gnpy-path-computation imput in the API request.";
uses path-computation;
}
}

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@@ -0,0 +1,35 @@
module: gnpy-sim-params
+--rw sim-params
+--rw raman_params
| +--rw flag? boolean
| +--rw order? uint16
| +--rw method? identityref
| +--rw result_spatial_resolution? decimal64
| +--rw solver_spatial_resolution? decimal64
+--rw nli_params
+--rw method? identityref
+--rw dispersion_tolerance? decimal64
+--rw phase_shift_tolerance? decimal64
+--rw (computation)?
+--:(explicit-channels)
| +--rw computed_channels* uint16
+--:(nb_of_channels)
+--rw computed_number_of_channels? uint16
augment /gapi:api:
+--rw sim-params
+--rw raman_params
| +--rw flag? boolean
| +--rw order? uint16
| +--rw method? identityref
| +--rw result_spatial_resolution? decimal64
| +--rw solver_spatial_resolution? decimal64
+--rw nli_params
+--rw method? identityref
+--rw dispersion_tolerance? decimal64
+--rw phase_shift_tolerance? decimal64
+--rw (computation)?
+--:(explicit-channels)
| +--rw computed_channels* uint16
+--:(nb_of_channels)
+--rw computed_number_of_channels? uint16

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module gnpy-sim-params {
yang-version 1.1;
namespace "urn:gnpy-sim-params";
prefix sim-params;
import gnpy-api {
prefix "gapi";
revision-date 2025-06-13;
}
organization
"Telecom Infra Project OOPT PSE Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:esther.lerouzic@orange.com>
";
description
"YANG model for gnpy network input for path computation simulation params- 2025";
revision 2025-04-10 {
description
"First yang model for sim-params option";
reference
"YANG model for network input for path computation with gnpy";
}
identity nli-method {
description "Base identity for NLI calculation methods";
}
identity ggn_spectrally_separated {
base nli-method;
description "GGN spectrally separated method";
}
identity ggn_approx {
base nli-method;
description "GGN approximation method";
}
identity gn_model_analytic {
base nli-method;
description "GN model analytic method";
}
identity raman-method {
description "Base identity for Raman calculation methods";
}
identity perturbative {
base raman-method;
description "Raman perturbative method";
}
identity numerical {
base raman-method;
description "Raman numerical first order method";
}
grouping raman-sim-params {
description
"Raman simulation attributes";
container raman_params {
description
"Simulation parameters definition for Raman effect evaluation.";
leaf flag {
type boolean;
description
"boolean for enabling/disable the evaluation of the Raman power
profile in frequency and position
";
}
leaf order {
type uint16;
default 2;
description
"Solution order for perturbative method";
}
leaf method {
type identityref {
base raman-method;
}
description
"Method used for Raman effect evaluation.";
}
leaf result_spatial_resolution {
type decimal64 {
fraction-digits 3;
}
description
"Spatial resolution of the evaluated Raman power profile in m. Suggested value is 10e3m";
}
leaf solver_spatial_resolution {
type decimal64 {
fraction-digits 3;
}
description
"Spatial step for the iterative solution of the first order ode. a suggested value is 10e3 m";
}
}
}
grouping nli-sim-params {
description
"NLI simulation attributes";
container nli_params {
description
"Simulation parameters definition for Non Linear
Interference (NLI) effect evaluation.";
leaf method {
type identityref {
base nli-method;
}
description "Model used for the NLI evaluation.";
}
leaf dispersion_tolerance {
type decimal64 {
fraction-digits 1;
}
default "1.0";
description "Tuning parameter for ggn model solution";
}
leaf phase_shift_tolerance {
type decimal64 {
fraction-digits 1;
}
default "0.1";
description "Tuning parameter for ggn model solution";
}
choice computation {
description
"Definition of the channels on which the NLI is evaluated: explicir position or amount.";
case explicit-channels {
leaf-list computed_channels {
type uint16 {
range "1..max";
}
ordered-by user;
description "The exact channel indices (starting from 1) on which the NLI is evaluated";
}
}
case nb_of_channels {
leaf computed_number_of_channels {
type uint16;
description "The number of channels on which the NLI is evaluated";
}
}
}
}
}
grouping sim-params {
description
"Simulation parameters definition.";
container sim-params {
description
"Simulation parameters definition.";
uses raman-sim-params;
uses nli-sim-params;
}
}
container sim-params {
description
"Simulation parameters definition.";
uses raman-sim-params;
uses nli-sim-params;
}
augment "/gapi:api" {
description "Add the gnpy-sim-params input in the API request.";
uses sim-params;
}
}

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@@ -0,0 +1,23 @@
module: gnpy-spectrum
+--rw spectrum* [f_min]
+--rw f_min decimal64
+--rw f_max decimal64
+--rw slot_width decimal64
+--rw delta_pdb? decimal64
+--rw baud_rate? decimal64
+--rw tx_osnr? decimal64
+--rw roll_off? union
+--rw tx_power_dbm? decimal64
+--rw label? string
augment /gapi:api:
+--rw spectrum* [f_min]
+--rw f_min decimal64
+--rw f_max decimal64
+--rw slot_width decimal64
+--rw delta_pdb? decimal64
+--rw baud_rate? decimal64
+--rw tx_osnr? decimal64
+--rw roll_off? union
+--rw tx_power_dbm? decimal64
+--rw label? string

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@@ -0,0 +1,105 @@
module gnpy-spectrum {
yang-version 1.1;
namespace "urn:gnpy-spectrum";
prefix spectrum;
import gnpy-api {
prefix "gapi";
revision-date 2025-06-13;
}
import gnpy-eqpt-config {
prefix "geqpt";
revision-date 2025-05-26;
}
organization
"Telecom Infra Project OOPT PSE Working Group";
contact
"WG Web: <https://github.com/Telecominfraproject/oopt-gnpy>
contact: <mailto:esther.lerouzic@orange.com>
";
description
"YANG model for gnpy network input for path computation simulation params- 2025";
revision 2025-04-10 {
description
"First yang model for spectrum option";
reference
"YANG model for network input for path computation with gnpy";
}
grouping spectrum-grouping {
description
"Attributes of a spectrum partition.";
leaf f_min {
type decimal64 {
fraction-digits 1;
}
mandatory true;
description
"Partition definition: f_min is the first carrier central frequency
f_max is the last one. partitions must not overlap.
Note that the meaning of f_min and f_max is different than the one
in equipment_config SpectralInformation";
}
leaf f_max {
type decimal64 {
fraction-digits 1;
}
must ". >= ./../f_min";
mandatory true;
description
"Partition definition: f_min is the first carrier central frequency
f_max is the last one. partitions must not overlap.
Note that the meaning of f_min and f_max is different than the one
in equipment_config SpectralInformation";
}
leaf slot_width {
type decimal64 {
fraction-digits 2;
}
mandatory true;
description "Carrier spectrum occupation. Carriers of this partition
are spaced at slot_width offsets.";
}
leaf delta_pdb {
type decimal64 {
fraction-digits 2;
}
description "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.";
}
uses geqpt:SI-Transceiver;
leaf label {
type string;
description
"Unique label that identifies the spectrum partition.";
}
}
grouping spectrum {
description
"Definition of the spectrum to propagate.";
list spectrum {
description
"List of spectrum partitions.";
key f_min;
uses spectrum-grouping;
}
}
list spectrum {
description
"List of spectrum partitions.";
key f_min;
uses spectrum-grouping;
}
augment "/gapi:api" {
description "Add the gnpy-spectrum input in the API request.";
uses spectrum;
}
}

293
gnpy/yang/precision_dict.py Normal file
View File

@@ -0,0 +1,293 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
# precision of fraction digits collected in yang models
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
PRECISION_DICT = {
"contact": -1, "date": -1, "description": -1, "module": -1, "organization": -1,
"f_min": 1,
"f_max": 1,
"length": 6,
"loss_coef": 6,
"pmd_coef": 18,
"frequency": 1,
"freq": 2, "ref_frequency": 1, "ref_wavelength": 12,
"g0": 14, "loss_coef_value": 16, "position": 6, "reference_frequency": 1,
"att_in": 2,
"con_in": 2,
"con_out": 2,
"temperature": 2,
"power": 9,
"gain_target": 6,
"tilt_target": 6,
"out_voa": 2,
"in_voa": 2,
"delta_p": 6,
"spacing": 2,
"target_pch_out_db": 2,
"target_psd_out_mWperGHz": 10,
"target_out_mWperSlotWidth": 10,
"per_degree_pch_out_db": 2,
"per_degree_psd_out_mWperGHz": 10,
"per_degree_psd_out_mWperSlotWidth": 10,
"number-of-channels": 0,
"loss": 2,
"city": -1,
"region": -1,
"latitude": 6,
"longitude": 6,
"length_units": -1,
"propagation_direction": -1,
"type_variety": -1,
"degree_uid": -1,
"preamp_variety_list": -1,
"booster_variety_list": -1,
"from_degree": -1,
"to_degree": -1,
"impairment_id": 0,
"variety_list": -1,
"uid": -1,
"type": -1,
"from_node": -1,
"to_node": -1,
"network_name": -1,
"output-power": 8,
"tx_power": 5,
"path_bandwidth": 1,
"accumulative-value": 8,
"N": 0,
"M": 0,
"trx_mode": -1,
"max-nb-of-channel": 0,
"technology": -1,
"trx_type": -1,
"transponder-type": -1,
"transponder-mode": -1,
"explicit-route-usage": -1,
"disjointness": -1,
"index": 0,
"node-id": -1,
"link-tp-id": -1,
"hop-type": -1,
"source": -1,
"destination": -1,
"src-tp-id": -1,
"dst-tp-id": -1,
"synchronization-id": -1,
"relaxable": -1,
"request-id-number": -1,
"request-id": -1,
"bidirectional": -1,
"metric-type": -1,
"response-id": -1,
"no-path": -1,
"result_spatial_resolution": 3,
"solver_spatial_resolution": 3,
"dispersion_tolerance": 1,
"phase_shift_tolerance": 1,
"flag": -1,
"order": 0,
"method": -1,
"computed_channels": 0,
"computed_number_of_channels": 0,
"nf_min": 2,
"nf_max": 2,
"nf0": 2,
"nf_coef": 10,
"coef_order": 0,
"gain_flatmax": 2,
"gain_min": 2,
"extended_gain_range": 2,
"p_max": 2,
"dispersion": 8,
'dispersion_slope': 11,
"gamma": 8,
"effective_area": 14,
"min_value": 2,
"max_value": 2,
"step": 2,
"lower-frequency": 2,
"upper-frequency": 2,
"cr": 9,
"frequency_offset": 2,
"max_length": 2,
"max_loss": 2,
"max_fiber_lineic_loss_for_raman": 2,
"target_extended_gain": 2,
"padding": 2,
"EOL": 2,
"span_loss_ref": 2,
"power_slope": 2,
"voa_margin": 2,
"voa_step": 2,
"add_drop_osnr": 2,
"pmd": 15,
"pdl": 2,
"baud_rate": 2,
"power_dbm": 2,
"roll_off": 2,
"tx_osnr": 2,
"tx_power_dbm": 2,
"sys_margins": 2,
"min": 2,
"max": 2,
"OSNR": 2,
"min_spacing": 2,
"bit_rate": 2,
"cost": 2,
"chromatic_dispersion": 2,
"penalty_value": 2,
"equalization_offset_db": 4,
"preamp_variety": -1,
"booster_variety": -1,
"amplifiers": -1,
"advanced_config_from_json": -1,
"default_config_from_json": -1,
"allowed_for_design": -1,
"type_def": -1,
"raman": -1,
"out_voa_auto": -1,
"in_voa_auto": -1,
"other_name": -1,
"power_mode": -1,
"roadm-path-impairments-id": 0,
"use_si_channel_count_for_design": -1,
"comment": -1,
"format": -1,
"roadm-osnr": 2,
"nf_ripple": 18,
"dgt": 18,
"gain_ripple": 18,
"slot_width": 2,
"delta_pdb": 2,
"label": -1,
"roadm-pmd": 8,
"otsi-carrier-frequency": 9,
"oms-element-uid": -1,
"configured-mode": -1,
"type-variety": -1,
"frequency-range-id": 0,
"stage-order": 0,
"name": -1,
"nominal-carrier-power": 2,
"nominal-psd": 16,
"actual-gain": 2,
"in-voa": 2,
"out-voa": 2,
"tilt-target": 2,
"total-output-power": 2,
"raman-direction": -1,
"pump-id": 0,
"delta-power": 2,
"loss-coef": 2,
"total-loss": 2,
"conn-in": 2,
"conn-out": 2,
"roadm-cd": 5,
"roadm-pdl": 2,
"roadm-inband-crosstalk": 2,
"roadm-maxloss": 2,
"roadm-pmax": 2,
"roadm-noise-figure": 5,
"roadm-minloss": 2,
"roadm-typloss": 2,
"roadm-pmin": 2,
"roadm-ptyp": 2,
"generalized-snr": 2,
"equalization-mode": -1,
"otsi-carrier-id": 0,
"e2e-mc-path-id": 0,
"otsi-group-ref": -1,
"media-channel-id": 0,
"otsi-carrier-ref": -1,
"e2e-mc-path-ref": -1,
"elt-index": 0,
"link-ref": -1,
"oms-element-ref": -1,
"otsi-ref": -1,
"otsi-group-id": -1,
"explicit-transceiver-mode-id": -1,
"transponder-id": 0,
"termination-type-capabilities": -1,
"transceiver-id": 0,
"explicit-transceiver-mode-ref": -1,
"configured-termination-type": -1,
"group-id": 0,
"regen-metric": 0,
"transponder-ref": -1,
"transceiver-ref": -1,
"protection-type": -1,
"inter-layer-sequence-number": 0,
"roadm-path-impairments": -1,
"ltp-ref": -1,
"add-path-impairments": -1,
"drop-path-impairments": -1,
"ttp-transponder-ref": -1,
"ttp-transceiver-ref": -1,
"is-allowed": -1,
"penalty-value": 2,
"max-chromatic-dispersion": 2,
"cd-value": 2,
"max-polarization-mode-dispersion": 2,
"pmd-value": 2,
"available-baud-rate": 1,
"roll-off": 4,
"fec-code-rate": 8,
"fec-threshold": 8,
"polarization-skew": 2,
"dwdm-n": -1,
"cwdm-n": -1,
"wson-dwdm-channel-spacing": -1,
"wson-cwdm-channel-spacing": -1,
"subcarrier-dwdm-n": 0,
"slot-width-granularity": -1,
"min-slot-width-factor": 0,
"max-slot-width-factor": 0,
"grid-type": -1,
"priority": 0,
"flexi-n": 0,
"flexi-m": 0,
"flexi-grid-channel-spacing": -1,
"flexi-ncfg": -1,
"flexi-n-step": 0,
"mode-id": -1,
"supported-application-codes": -1,
"supported-organizational-modes": -1,
"standard-mode": -1,
"operational-mode": -1,
"organization-identifier": -1,
"line-coding-bitrate": -1,
"bitrate": 0,
"max-diff-group-delay": 2,
"max-polarization-dependant-loss": 2,
"pdl-value": 2,
"available-modulation-type": -1,
"min-OSNR": 2,
"rx-ref-channel-power": 2,
"rx-channel-power-value": 2,
"min-Q-factor": 2,
"min-carrier-spacing": 6,
"available-fec-type": -1,
"in-band-osnr": 2,
"out-of-band-osnr": 2,
"tx-polarization-power-difference": 2,
"min-central-frequency": 9,
"max-central-frequency": 9,
"transceiver-tunability": 6,
"tx-channel-power-min": 2,
"tx-channel-power-max": 2,
"rx-channel-power-min": 2,
"rx-channel-power-max": 2,
"rx-total-power-max": 2,
"tx-channel-power": 2,
"rx-channel-power": 2,
"rx-total-power": 2,
"wavelength-assignment": -1,
"gsnr-extra-margin": 2,
"estimated-gsnr": 2,
"estimated-eol-gsnr": 2,
"estimated-lowest-gsnr": 2
}

View File

@@ -0,0 +1,61 @@
{
"ietf-yang-library:modules-state": {
"module-set-id": "gnpy-library",
"module": [
{
"name": "gnpy-network-topology",
"namespace": "gnpy:gnpy-network-topology",
"revision": "2025-03-01",
"conformance-type": "implement"
},
{
"name": "gnpy-path-computation",
"namespace": "gnpy:gnpy-path-computation",
"revision": "2025-01-20",
"conformance-type": "implement"
},
{
"name": "gnpy-sim-params",
"namespace": "gnpy:gnpy-sim-params",
"revision": "2025-04-10",
"conformance-type": "implement"
},
{
"name": "gnpy-eqpt-config",
"namespace": "gnpy:gnpy-eqpt",
"revision": "2025-05-26",
"conformance-type": "implement"
},
{
"name": "gnpy-edfa-config",
"namespace": "gnpy:gnpy-edfa-config",
"revision": "2025-04-10",
"conformance-type": "implement"
},
{
"name": "gnpy-sim-params",
"namespace": "gnpy:gnpy-sim-params",
"revision": "2025-04-10",
"conformance-type": "implement"
},
{
"name": "gnpy-spectrum",
"namespace": "gnpy:gnpy-spectrum",
"revision": "2025-04-10",
"conformance-type": "implement"
},
{
"name": "ietf-optical-impairment-topology",
"namespace": "urn:ietf:params:xml:ns:yang:ietf-optical-impairment-topology",
"revision": "2024-05-21",
"conformance-type": "implement"
},
{
"name": "ietf-layer0-types",
"namespace": "urn:ietf:params:xml:ns:yang:ietf-layer0-types",
"revision": "2024-03-04",
"conformance-type": "implement"
}
]
}
}

View File

@@ -1,559 +0,0 @@
*********************************************
Equipment and Network description definitions
*********************************************
1. Equipment description
########################
Equipment description defines equipment types and those parameters.
Description is made in JSON file with predefined structure. By default
**gnpy-transmission-example** uses **eqpt_config.json** file and that
can be changed with **-e** or **--equipment** command line parameter.
Parsing of JSON file is made with
**gnpy.core.equipment.load_equipment(equipment_description)** and return
value is a dictionary of format **dict[equipment
type][subtype]=object**
1.1. Structure definition
*************************
1.1.1. Equipment types
*************************
Every equipment type is defined in JSON root with according name and
array of parameters as value.
.. code-block:: none
{"Edfa": [...],
"Fiber": [...]
}
1.1.2. Equipment parameters and subtypes
*****************************************
Array of parameters is a list of objects with unordered parameter name
and its value definition. In case of multiple equipment subtypes each
object contains **"type_variety":”type name”** name:value combination,
if only one subtype exists **"type_variety"** name is not mandatory and
it will be marked with **”default”** value.
.. code-block:: json
{"Edfa": [{
"type_variety": "std_medium_gain",
"type_def": "variable_gain",
"gain_flatmax": 26,
"gain_min": 15,
"p_max": 23,
"nf_min": 6,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "std_low_gain",
"type_def": "variable_gain",
"gain_flatmax": 16,
"gain_min": 8,
"p_max": 23,
"nf_min": 6.5,
"nf_max": 11,
"out_voa_auto": false,
"allowed_for_design": true
}
],
"Fiber": [{
"type_variety": "SSMF",
"dispersion": 1.67e-05,
"gamma": 0.00127
}
]
}
1.2. Equipment parameters by type
*********************************
1.2.1. EDFA element
*******************
Four types of EDFA definition are possible. Description JSON file
location is in **gnpy-transmission-example** folder:
- Advanced with JSON file describing gain/noise figure tilt and
gain/noise figure ripple. **"advanced_config_from_json"** value
contains filename.
.. code-block:: json-object
"Edfa":[{
"type_variety": "high_detail_model_example",
"gain_flatmax": 25,
"gain_min": 15,
"p_max": 21,
"advanced_config_from_json": "std_medium_gain_advanced_config.json",
"out_voa_auto": false,
"allowed_for_design": false
}
]
- Variable gain with JSON file describing gain figure tilt and gain/noise
figure ripple. **”default_edfa_config.json”** as source file.
.. code-block:: json-object
"Edfa":[{
"type_variety": "std_medium_gain",
"type_def": "variable_gain",
"gain_flatmax": 26,
"gain_min": 15,
"p_max": 23,
"nf_min": 6,
"nf_max": 10,
"out_voa_auto": false,
"allowed_for_design": true
}
]
- Fixed gain with JSON file describing gain figure tilt and gain/noise
figure ripple. **”default_edfa_config.json”** as source file.
.. code-block:: json-object
"Edfa":[{
"type_variety": "std_fixed_gain",
"type_def": "fixed_gain",
"gain_flatmax": 21,
"gain_min": 20,
"p_max": 21,
"nf0": 5.5,
"allowed_for_design": false
}
]
- openroadm with JSON file describing gain figure tilt and gain/noise
figure ripple. **”default_edfa_config.json”** as source file.
.. code-block:: json-object
"Edfa":[{
"type_variety": "openroadm_ila_low_noise",
"type_def": "openroadm",
"gain_flatmax": 27,
"gain_min": 12,
"p_max": 22,
"nf_coef": [-8.104e-4,-6.221e-2,-5.889e-1,37.62],
"allowed_for_design": false
}
]
1.2.2. Fiber element
********************
Fiber element with its parameters:
.. code-block:: json-object
"Fiber":[{
"type_variety": "SSMF",
"dispersion": 1.67e-05,
"gamma": 0.00127
}
]
RamanFiber element
******************
A special variant of the regular ``Fiber`` where the simulation engine accounts for the Raman effect.
The newly added parameters are nested in the ``raman_efficiency`` dictionary.
Its shape corresponds to typical properties of silica.
More details are available from :cite:`curri_merit_2016`.
The ``cr`` property is the normailzed Raman efficiency, so it is is (almost) independent of the fiber type, while the coefficient actually giving Raman gain is g_R=C_R/Aeff.
The ``frequency_offset`` represents the spectral difference between the pumping photon and the one receiving energy.
.. code-block:: json-object
"RamanFiber":[{
"type_variety": "SSMF",
"dispersion": 1.67e-05,
"gamma": 0.00127,
"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
]
}
}
]
1.2.3 Roadm element
*******************
Roadm element with its parameters:
.. code-block:: json-object
"Roadms":[{
"gain_mode_default_loss": 20,
"power_mode_pout_target": -20,
"add_drop_osnr": 38
}
]
1.2.3. Spans element
********************
Spans element with its parameters:
.. code-block:: json-object
"Spans":[{
"power_mode":true,
"delta_power_range_db": [0,0,0.5],
"max_length": 150,
"length_units": "km",
"max_loss": 28,
"padding": 10,
"EOL": 0,
"con_in": 0,
"con_out": 0
}
]
1.2.4. Spectral Information
***************************
Spectral information with its parameters:
.. code-block:: json-object
"SI":[{
"f_min": 191.3e12,
"baud_rate": 32e9,
"f_max":195.1e12,
"spacing": 50e9,
"power_dbm": 0,
"power_range_db": [0,0,0.5],
"roll_off": 0.15,
"tx_osnr": 40,
"sys_margins": 0
}
]
1.2.5. Transceiver element
**************************
Transceiver element with its parameters. **”mode”** can contain multiple
Transceiver operation formats.
Note that ``OSNR`` parameter refers to the receiver's minimal OSNR threshold for a given mode.
.. code-block:: json-object
"Transceiver":[{
"frequency":{
"min": 191.35e12,
"max": 196.1e12
},
"mode":[
{
"format": "mode 1",
"baud_rate": 32e9,
"OSNR": 11,
"bit_rate": 100e9,
"roll_off": 0.15,
"tx_osnr": 40,
"min_spacing": 37.5e9,
"cost":1
},
{
"format": "mode 2",
"baud_rate": 66e9,
"OSNR": 15,
"bit_rate": 200e9,
"roll_off": 0.15,
"tx_osnr": 40,
"min_spacing": 75e9,
"cost":1
}
]
}
]
***********************
2. Network description
***********************
Network description defines network elements with additional to
equipment description parameters, metadata and elements interconnection.
Description is made in JSON file with predefined structure. By default
**gnpy-transmission-example** uses **edfa_example_network.json** file
and can be changed from command line. Parsing of JSON file is made with
**gnpy.core.network.load_network(network_description,
equipment_description)** and return value is **DiGraph** object which
mimics network description.
2.1. Structure definition
##########################
2.1.1. File root structure
***************************
Network description JSON file root consist of three unordered parts:
- network_name name of described network or service, is not used as
of now
- elements - contains array of network element objects with their
respective parameters
- connections contains array of unidirectional connection objects
.. code-block:: none
{"network_name": "Example Network",
"elements": [{...},
{...}
],
"connections": [{...},
{...}
]
}
2.1.2. Elements parameters and subtypes
****************************************
Array of network element objects consist of unordered parameter names
and those values. In case of **"type_variety"** absence
**"type_variety":”default”** name:value combination is used. As of the
moment, existence of used **"type_variety"** in equipment description is
obligatory.
2.2. Element parameters by type
*********************************
2.2.1. Transceiver element
***************************
Transceiver element with its parameters.
.. code-block:: json
{"uid": "trx Site_A",
"metadata": {
"location": {
"city": "Site_A",
"region": "",
"latitude": 0,
"longitude": 0
}
},
"type": "Transceiver"
}
2.2.2. ROADM element
*********************
ROADM element with its parameters. **“params”** is optional, if not used
default loss value of 20dB is used.
.. code-block:: json
{"uid": "roadm Site_A",
"metadata": {
"location": {
"city": "Site_A",
"region": "",
"latitude": 0,
"longitude": 0
}
},
"type": "Roadm",
"params": {
"loss": 17
}
}
2.2.3. Fused element
*********************
Fused element with its parameters. **“params”** is optional, if not used
default loss value of 1dB is used.
.. code-block:: json
{"uid": "ingress fused spans in Site_B",
"metadata": {
"location": {
"city": "Site_B",
"region": "",
"latitude": 0,
"longitude": 0
}
},
"type": "Fused",
"params": {
"loss": 0.5
}
}
2.2.4. Fiber element
*********************
Fiber element with its parameters.
.. code-block:: json
{"uid": "fiber (Site_A \\u2192 Site_B)",
"metadata": {
"location": {
"city": "",
"region": "",
"latitude": 0.0,
"longitude": 0.0
}
},
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 40.0,
"length_units": "km",
"loss_coef": 0.2
}
}
2.2.5. RamanFiber element
*************************
.. code-block:: json
{
"uid": "Span1",
"type": "RamanFiber",
"type_variety": "SSMF",
"operational": {
"temperature": 283,
"raman_pumps": [
{
"power": 200e-3,
"frequency": 205e12,
"propagation_direction": "counterprop"
},
{
"power": 206e-3,
"frequency": 201e12,
"propagation_direction": "counterprop"
}
]
},
"params": {
"type_variety": "SSMF",
"length": 80.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0,
"con_in": 0.5,
"con_out": 0.5
},
"metadata": {
"location": {
"latitude": 1,
"longitude": 0,
"city": null,
"region": ""
}
}
}
2.2.6. EDFA element
********************
EDFA element with its parameters.
.. code-block:: json
{"uid": "Edfa1",
"type": "Edfa",
"type_variety": "std_low_gain",
"operational": {
"gain_target": 16,
"tilt_target": 0
},
"metadata": {
"location": {
"city": "Site_A",
"region": "",
"latitude": 2,
"longitude": 0
}
}
}
2.3. Connections objects
*************************
Each unidirectional connection object in connections array consist of
two unordered **”from_node”** and **”to_node”** name pair with values
corresponding to element **”uid”**
.. code-block:: json
{"from_node": "roadm Site_C",
"to_node": "trx Site_C"
}
************************
3. Simulation Parameters
************************
Additional details of the simulation are controlled via ``sim_params.json``:
.. code-block:: json
{
"raman_parameters": {
"flag_raman": true,
"space_resolution": 10e3,
"tolerance": 1e-8
},
"nli_parameters": {
"nli_method_name": "ggn_spectrally_separated",
"wdm_grid_size": 50e9,
"dispersion_tolerance": 1,
"phase_shift_tolerance": 0.1,
"computed_channels": [1, 18, 37, 56, 75]
}
}

View File

@@ -49,6 +49,7 @@ console_scripts =
gnpy-transmission-example = gnpy.tools.cli_examples:transmission_main_example
gnpy-path-request = gnpy.tools.cli_examples:path_requests_run
gnpy-convert-xls = gnpy.tools.convert:_do_convert
gnpy-convert-yang = gnpy.tools.convert_legacy_yang:main
[options]
install_requires =
@@ -58,11 +59,13 @@ install_requires =
networkx>=3.1,<4
# numpy 1.25 removed support for Python 3.8
numpy>=1.24.4,<2
oopt_gnpy_libyang>=0.0.14
openpyxl>=3.1.5,<4
pbr>=6.0.0,<7
# scipy 1.11 removed support for Python 3.8
scipy>=1.10.1,<2
# xlrd 2.x removed support for .xlsx, it's only .xls now
xlrd>=1.2.0,<2
xlrd>=2.0.1,<3
[options.extras_require]
tests =
@@ -76,8 +79,9 @@ tests =
docs =
alabaster>=0.7.12,<1
docutils>=0.17.1,<1
myst-parser>=0.16.1,<1
myst-parser>=4.0.1,<5
Pygments>=2.11.2,<3
rstcheck
Sphinx>=5.3.0,<6
Sphinx>=8.1.3,<9
sphinxcontrib-bibtex>=2.4.1,<3
sphinx_rtd_theme>=3.0.2,<4

View File

@@ -1,8 +1,10 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# SPDX-License-Identifier: BSD-3-Clause
#
# Copyright (C) 2020 Telecom Infra Project and GNPy contributors
# see LICENSE.md for a list of contributors
#
# test_amplifier
# Copyright (C) 2025 Telecom Infra Project and GNPy contributors
# see AUTHORS.rst for a list of contributors
import pytest
from gnpy.core.parameters import SimParams, NLIParams, RamanParams

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{
"network_name": "EDFA Example Network - P2P",
"elements": [
{
"uid": "Site_A",
"type": "Transceiver",
"metadata": {
"location": {
"city": "Site A",
"region": "",
"latitude": 0.0,
"longitude": 0.0
}
}
},
{
"uid": "Span1",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 80.0,
"loss_coef": 0.2,
"length_units": "km",
"att_in": 0.0,
"con_in": 0.5,
"con_out": 0.5,
"pmd_coef": 3.0e-15
},
"metadata": {
"location": {
"region": "",
"latitude": 1.0,
"longitude": 0.0
}
}
},
{
"uid": "Edfa1",
"type": "Edfa",
"type_variety": "std_low_gain",
"operational": {
"gain_target": 17.0,
"tilt_target": 0.0,
"out_voa": 0.0
},
"metadata": {
"location": {
"region": "",
"latitude": 2.0,
"longitude": 0.0
}
}
},
{
"uid": "Site_B",
"type": "Transceiver",
"metadata": {
"location": {
"city": "Site B",
"region": "",
"latitude": 2.0,
"longitude": 0.0
}
}
}
],
"connections": [
{
"from_node": "Site_A",
"to_node": "Span1"
},
{
"from_node": "Span1",
"to_node": "Edfa1"
},
{
"from_node": "Edfa1",
"to_node": "Site_B"
}
]
}

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{
"gnpy-edfa-config:edfa-config": {
"f_min": "191275000000000.0",
"f_max": "196125000000000.0",
"nf_fit_coeff": [
{
"coef_order": 0,
"nf_coef": "0.000168241"
},
{
"coef_order": 1,
"nf_coef": "0.0469961"
},
{
"coef_order": 2,
"nf_coef": "0.0359549"
},
{
"coef_order": 3,
"nf_coef": "5.82851"
}
],
"nf_ripple": [
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"-0.3110761646066259",
"-0.31110274831665313",
"-0.31419329378173544",
"-0.3172854168606314",
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],
"dgt": [
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],
"gain_ripple": [
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]
}
}

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{
"gnpy-network-topology:topology": {
"network_name": "EDFA Example Network - P2P",
"elements": [
{
"uid": "Site_A",
"type": "Transceiver",
"metadata": {
"location": {
"city": "Site A",
"region": "",
"latitude": "0.0",
"longitude": "0.0"
}
}
},
{
"uid": "Span1",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": "80.0",
"loss_coef": "0.200000",
"length_units": "km",
"att_in": "0.0",
"con_in": "0.5",
"con_out": "0.5",
"pmd_coef": "0.000000000000003"
},
"metadata": {
"location": {
"region": "",
"latitude": "1.0",
"longitude": "0.0"
}
}
},
{
"uid": "Edfa1",
"type": "Edfa",
"type_variety": "std_low_gain",
"operational": {
"gain_target": "17.0",
"tilt_target": "0.0",
"out_voa": "0.0"
},
"metadata": {
"location": {
"region": "",
"latitude": "2.0",
"longitude": "0.0"
}
}
},
{
"uid": "Site_B",
"type": "Transceiver",
"metadata": {
"location": {
"city": "Site B",
"region": "",
"latitude": "2.0",
"longitude": "0.0"
}
}
}
],
"connections": [
{
"from_node": "Site_A",
"to_node": "Span1"
},
{
"from_node": "Span1",
"to_node": "Edfa1"
},
{
"from_node": "Edfa1",
"to_node": "Site_B"
}
]
}
}

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{
"gnpy-network-topology:topology": {
"network_name": "EDFA Example Network - P2P",
"elements": [
{
"uid": "Site_A",
"type": "Transceiver",
"metadata": {
"location": {
"city": "Site A",
"region": "",
"latitude": "0.0",
"longitude": "0.0"
}
}
},
{
"uid": "Span1",
"type": "RamanFiber",
"type_variety": "SSMF",
"params": {
"length": "80.0",
"loss_coef": "0.2",
"length_units": "km",
"att_in": "0.0",
"con_in": "0.5",
"con_out": "0.0",
"lumped_losses": [
{
"position": "7.0",
"loss": "0.5"
}
],
"dispersion": "0.0000167",
"effective_area": "0.000000000083",
"pmd_coef": "0.000000000000001265",
"raman_coefficient": {
"reference_frequency": "206184634112792.0",
"g0_per_frequency": [
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},
{
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},
{
"frequency_offset": "34000000000000.0",
"g0": "0.00000965352116"
},
{
"frequency_offset": "34500000000000.0",
"g0": "0.00000862698322"
},
{
"frequency_offset": "35000000000000.0",
"g0": "0.00000918688016"
},
{
"frequency_offset": "35500000000000.0",
"g0": "0.0000101737784"
},
{
"frequency_offset": "36000000000000.0",
"g0": "0.0000108017817"
},
{
"frequency_offset": "36500000000000.0",
"g0": "0.0000103903588"
},
{
"frequency_offset": "37000000000000.0",
"g0": "0.00000930040333"
},
{
"frequency_offset": "37500000000000.0",
"g0": "0.00000830809173"
},
{
"frequency_offset": "38000000000000.0",
"g0": "0.00000690650401"
},
{
"frequency_offset": "38500000000000.0",
"g0": "0.00000552238029"
},
{
"frequency_offset": "39000000000000.0",
"g0": "0.00000390648708"
},
{
"frequency_offset": "39500000000000.0",
"g0": "0.00000222908227"
},
{
"frequency_offset": "40000000000000.0",
"g0": "0.00000155796177"
},
{
"frequency_offset": "40500000000000.0",
"g0": "0.00000097721872"
},
{
"frequency_offset": "41000000000000.0",
"g0": "0.00000032347724"
},
{
"frequency_offset": "41500000000000.0",
"g0": "0.00000016060245"
},
{
"frequency_offset": "42000000000000.0",
"g0": "0.00000007973064"
}
]
}
},
"operational": {
"temperature": "283.0",
"raman_pumps": [
{
"frequency": "205000000000000.0",
"power": "0.2",
"propagation_direction": "counterprop"
},
{
"frequency": "201000000000000.0",
"power": "0.206",
"propagation_direction": "counterprop"
}
]
},
"metadata": {
"location": {
"region": "",
"latitude": "1.0",
"longitude": "0.0"
}
}
},
{
"uid": "Edfa1",
"type": "Edfa",
"type_variety": "std_low_gain",
"operational": {
"gain_target": "17.0",
"tilt_target": "0.0",
"out_voa": "0.0"
},
"metadata": {
"location": {
"region": "",
"latitude": "2.0",
"longitude": "0.0"
}
}
},
{
"uid": "Site_B",
"type": "Transceiver",
"metadata": {
"location": {
"city": "Site B",
"region": "",
"latitude": "2.0",
"longitude": "0.0"
}
}
}
],
"connections": [
{
"from_node": "Site_A",
"to_node": "Span1"
},
{
"from_node": "Span1",
"to_node": "Edfa1"
},
{
"from_node": "Edfa1",
"to_node": "Site_B"
}
]
}
}

View File

@@ -0,0 +1,381 @@
{
"gnpy-eqpt-config:equipment": {
"Edfa": [
{
"type_variety": "CienaDB_medium_gain",
"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": true
},
{
"type_variety": "std_medium_gain",
"type_def": "variable_gain",
"gain_flatmax": "26.0",
"gain_min": "15.0",
"p_max": "21.0",
"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": "21.0",
"nf_min": "7.0",
"nf_max": "11.0",
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "test",
"type_def": "variable_gain",
"gain_flatmax": "25.0",
"gain_min": "15.0",
"p_max": "21.0",
"nf_min": "5.8",
"nf_max": "10.0",
"out_voa_auto": false,
"allowed_for_design": true
},
{
"type_variety": "test_fixed_gain",
"type_def": "fixed_gain",
"gain_flatmax": "21.0",
"gain_min": "20.0",
"p_max": "21.0",
"nf0": "5.0",
"allowed_for_design": true
},
{
"type_variety": "std_booster",
"type_def": "fixed_gain",
"gain_flatmax": "21.0",
"gain_min": "20.0",
"p_max": "21.0",
"nf0": "5.0",
"allowed_for_design": false
}
],
"Fiber": [
{
"type_variety": "SSMF",
"dispersion": "0.0000167",
"effective_area": "0.000000000083",
"pmd_coef": "0.000000000000001265"
}
],
"Span": [
{
"power_mode": true,
"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",
"delta_power_range_dict_db": {
"min_value": "0.0",
"max_value": "0.0",
"step": "0.5"
}
}
],
"Roadm": [
{
"type_variety": "example_test",
"target_pch_out_db": "-18.0",
"add_drop_osnr": "35.0",
"pmd": "0.000000000001",
"pdl": "0.5",
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
},
"roadm-path-impairments": []
},
{
"type_variety": "example_detailed_impairments",
"target_pch_out_db": "-20.0",
"add_drop_osnr": "35.0",
"pmd": "0.0",
"pdl": "0.0",
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
},
"roadm-path-impairments": [
{
"roadm-path-impairments-id": 0,
"roadm-express-path": [
{
"frequency-range": {
"lower-frequency": "191300000000000.0",
"upper-frequency": "196100000000000.0"
},
"roadm-pmd": "0.0",
"roadm-cd": "0.0",
"roadm-pdl": "0.0",
"roadm-inband-crosstalk": "0.0",
"roadm-maxloss": "16.5"
}
]
},
{
"roadm-path-impairments-id": 1,
"roadm-add-path": [
{
"frequency-range": {
"lower-frequency": "191300000000000.0",
"upper-frequency": "196100000000000.0"
},
"roadm-pmd": "0.0",
"roadm-cd": "0.0",
"roadm-pdl": "0.0",
"roadm-inband-crosstalk": "0.0",
"roadm-maxloss": "11.5",
"roadm-pmax": "2.5",
"roadm-osnr": "41.0",
"roadm-noise-figure": "23.0"
},
{
"frequency-range": {
"lower-frequency": "186300000000000.0",
"upper-frequency": "190100000000000.0"
},
"roadm-pmd": "0.0",
"roadm-cd": "0.0",
"roadm-pdl": "0.5",
"roadm-inband-crosstalk": "0.0",
"roadm-maxloss": "5.0",
"roadm-pmax": "0.0",
"roadm-osnr": "35.0",
"roadm-noise-figure": "6.0"
}
]
},
{
"roadm-path-impairments-id": 2,
"roadm-drop-path": [
{
"frequency-range": {
"lower-frequency": "191300000000000.0",
"upper-frequency": "196100000000000.0"
},
"roadm-pmd": "0.0",
"roadm-cd": "0.0",
"roadm-pdl": "0.0",
"roadm-inband-crosstalk": "0.0",
"roadm-maxloss": "11.5",
"roadm-minloss": "7.5",
"roadm-typloss": "10.0",
"roadm-pmin": "-13.5",
"roadm-pmax": "-9.5",
"roadm-ptyp": "-12.0",
"roadm-osnr": "41.0",
"roadm-noise-figure": "15.0"
}
]
}
]
},
{
"type_variety": "default",
"target_pch_out_db": "-20.0",
"add_drop_osnr": "38.0",
"pmd": "0.0",
"pdl": "0.0",
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
}
},
{
"type_variety": "detailed_impairments",
"target_pch_out_db": "-20.0",
"add_drop_osnr": "35.0",
"pmd": "0.0",
"pdl": "0.0",
"restrictions": {
"preamp_variety_list": [],
"booster_variety_list": []
},
"roadm-path-impairments": [
{
"roadm-path-impairments-id": 0,
"roadm-express-path": [
{
"frequency-range": {
"lower-frequency": "191300000000000.0",
"upper-frequency": "196100000000000.0"
},
"roadm-pmd": "0.0",
"roadm-cd": "0.0",
"roadm-pdl": "0.0",
"roadm-inband-crosstalk": "0.0",
"roadm-maxloss": "16.5"
}
]
}
]
}
],
"SI": [
{
"type_variety": "default",
"f_min": "191300000000000.0",
"f_max": "196100000000000.0",
"baud_rate": "32000000000.0",
"spacing": "50000000000.0",
"power_dbm": "0.0",
"roll_off": "0.15",
"tx_osnr": "100.0",
"sys_margins": "0.0",
"use_si_channel_count_for_design": false,
"power_range_dict_db": {
"min_value": "0.0",
"max_value": "0.0",
"step": "0.5"
}
}
],
"Transceiver": [
{
"type_variety": "vendorA_trx-type1",
"frequency": {
"min": "191350000000000.0",
"max": "196100000000000.0"
},
"mode": [
{
"format": "PS_SP64_1",
"baud_rate": "32000000000.0",
"OSNR": "11.0",
"bit_rate": "100000000000.0",
"roll_off": "0.15",
"tx_osnr": "100.0",
"min_spacing": "50000000000.0",
"cost": "1.0"
},
{
"format": "PS_SP64_2",
"baud_rate": "64000000000.0",
"OSNR": "15.0",
"bit_rate": "200000000000.0",
"roll_off": "0.15",
"tx_osnr": "100.0",
"min_spacing": "75000000000.0",
"cost": "1.0"
},
{
"format": "mode 1",
"baud_rate": "32000000000.0",
"OSNR": "11.0",
"bit_rate": "100000000000.0",
"roll_off": "0.15",
"tx_osnr": "100.0",
"min_spacing": "50000000000.0",
"cost": "1.0"
},
{
"format": "mode 2",
"baud_rate": "64000000000.0",
"OSNR": "15.0",
"bit_rate": "200000000000.0",
"roll_off": "0.15",
"tx_osnr": "100.0",
"min_spacing": "75000000000.0",
"cost": "1.0"
}
]
},
{
"type_variety": "Voyager_16QAM",
"frequency": {
"min": "191350000000000.0",
"max": "196100000000000.0"
},
"mode": [
{
"format": "16QAM",
"baud_rate": "32000000000.0",
"OSNR": "19.0",
"bit_rate": "200000000000.0",
"roll_off": "0.15",
"tx_osnr": "100.0",
"min_spacing": "50000000000.0",
"cost": "1.0"
}
]
},
{
"type_variety": "Voyager",
"frequency": {
"min": "191350000000000.0",
"max": "196100000000000.0"
},
"mode": [
{
"format": "mode 1",
"baud_rate": "32000000000.0",
"OSNR": "12.0",
"bit_rate": "100000000000.0",
"roll_off": "0.15",
"tx_osnr": "45.0",
"min_spacing": "50000000000.0",
"cost": "1.0"
},
{
"format": "mode 3",
"baud_rate": "44000000000.0",
"OSNR": "18.0",
"bit_rate": "300000000000.0",
"roll_off": "0.15",
"tx_osnr": "45.0",
"min_spacing": "62500000000.0",
"cost": "1.0"
},
{
"format": "mode 2",
"baud_rate": "66000000000.0",
"OSNR": "21.0",
"bit_rate": "400000000000.0",
"roll_off": "0.15",
"tx_osnr": "45.0",
"min_spacing": "75000000000.0",
"cost": "1.0"
},
{
"format": "mode 2 - fake",
"baud_rate": "66000000000.0",
"OSNR": "21.0",
"bit_rate": "400000000000.0",
"roll_off": "0.15",
"tx_osnr": "45.0",
"min_spacing": "75000000000.0",
"cost": "1.0"
},
{
"format": "mode 4",
"baud_rate": "66000000000.0",
"OSNR": "16.0",
"bit_rate": "200000000000.0",
"roll_off": "0.15",
"tx_osnr": "45.0",
"min_spacing": "75000000000.0",
"cost": "1.0"
}
]
}
]
}
}

View File

@@ -0,0 +1,37 @@
{
"gnpy-eqpt-config:equipment": {
"Transceiver": [
{
"type_variety": "ZR400G",
"frequency": {
"min": "191350000000000.0",
"max": "196100000000000.0"
},
"mode": [
{
"format": "400G",
"baud_rate": "60000000000.0",
"OSNR": "24.0",
"bit_rate": "400000000000.0",
"roll_off": "0.2",
"tx_osnr": "38.0",
"min_spacing": "75000000000.0",
"cost": "1.0"
}
]
}
],
"Edfa": [
{
"type_variety": "user_defined_default_amplifier",
"type_def": "advanced_model",
"gain_flatmax": "25.0",
"gain_min": "15.0",
"p_max": "21.0",
"advanced_config_from_json": "default_edfa_config.json",
"out_voa_auto": false,
"allowed_for_design": false
}
]
}
}

View File

@@ -0,0 +1,21 @@
{
"gnpy-sim-params:sim-params": {
"raman_params": {
"flag": true,
"result_spatial_resolution": "10000.0",
"solver_spatial_resolution": "10000.0"
},
"nli_params": {
"method": "ggn_spectrally_separated",
"dispersion_tolerance": "1.0",
"phase_shift_tolerance": "0.1",
"computed_channels": [
1,
18,
37,
56,
75
]
}
}
}

View File

@@ -0,0 +1,24 @@
{
"gnpy-spectrum:spectrum": [
{
"f_min": "191400000000000.0",
"f_max": "193100000000000.0",
"baud_rate": "32000000000.0",
"slot_width": "50000000000.0",
"delta_pdb": "0.0",
"roll_off": "0.15",
"tx_osnr": "40.0",
"label": "mode_1"
},
{
"f_min": "193162500000000.0",
"f_max": "195000000000000.0",
"baud_rate": "64000000000.0",
"slot_width": "75000000000.0",
"roll_off": "0.15",
"tx_osnr": "40.0",
"tx_power_dbm": "-10.0",
"label": "mode_2"
}
]
}

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