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35 Commits

Author SHA1 Message Date
Alessio Ferrari
c8fa7635e0 Bug fix in converting the dispersion D in beta2 
The actual conversion formula includes the minus (-), not the absolute
value. We never noticed it as GNPy simulates only modern networks
based on uncompensated transmission which have not DCUs. In this case,
the sign of beta2 along a path is the same for all the spans and,
in this case, the actual amount of NLI does not change.

Change-Id: I60a61d00c578a1a0436231a2bda8e3b6256fc8b3
 2020-06-12 07:35:40 +02:00
Jan Kundrát
a094568d6e equipment: move NF estimation into science_utils 
I envision equipment.py as something which deals exclusively with the
traditional GNPy's JSON-formatted data, so make sure we do not include
any computation in that file.

Change-Id: I8473cccd84243147181a7195ba39fc6c9db3c42f
 2020-05-23 16:37:56 +02:00
Jan Kundrát
db28011c61 coding style: manual tweaks 
This mainly reverts some auto-fix-ups done in
I2f0fca5aa1314f9bb546a3e6dc712a42580cd562 which do not make that much
sense. By reverting them by hand, it's (hopefully) easy to see what is
just a tool work and what is an opinionated preference.

Change-Id: I6cb479e34b552fadc85c41b4b06b24e60c87b4a3
 2020-05-19 13:59:56 +02:00
Jan Kundrát
0b1557fdf1 flake8: fix F841 (local variable is assigned to but never used) 
Change-Id: Ic79d0189bf4e97b953604edd0a6932f28c71a071
 2020-05-19 13:30:04 +02:00
Jan Kundrát
46f89aa770 coding style: autopep8 in an aggressive mode (-aaaaaaaaaa) 
I decided to skip the following chunk of the diff because I think that
it would actually made the code a bit harder to read:

diff --git gnpy/core/service_sheet.py gnpy/core/service_sheet.py
index 9965840..9834111 100644
--- gnpy/core/service_sheet.py
+++ gnpy/core/service_sheet.py
@@ -41,8 +41,22 @@ 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)
+    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)

 # Type for output data:  // from dutc

diff --git tests/test_automaticmodefeature.py tests/test_automaticmodefeature.py
index 0e5f633..5ba5881 100644
--- tests/test_automaticmodefeature.py
+++ tests/test_automaticmodefeature.py
@@ -32,7 +32,26 @@ eqpt_library_name = Path(__file__).parent.parent / 'tests/data/eqpt_config.json'
 @pytest.mark.parametrize("net", [network_file_name])
 @pytest.mark.parametrize("eqpt", [eqpt_library_name])
 @pytest.mark.parametrize("serv", [service_file_name])
-@pytest.mark.parametrize("expected_mode", [['16QAM', 'PS_SP64_1', 'PS_SP64_1', 'PS_SP64_1', 'mode 2 - fake', 'mode 2', 'PS_SP64_1', 'mode 3', 'PS_SP64_1', 'PS_SP64_1', '16QAM', 'mode 1', 'PS_SP64_1', 'PS_SP64_1', 'mode 1', 'mode 2', 'mode 1', 'mode 2', 'nok']])
+@pytest.mark.parametrize("expected_mode",
+                         [['16QAM',
+                           'PS_SP64_1',
+                           'PS_SP64_1',
+                           'PS_SP64_1',
+                           'mode 2 - fake',
+                           'mode 2',
+                           'PS_SP64_1',
+                           'mode 3',
+                           'PS_SP64_1',
+                           'PS_SP64_1',
+                           '16QAM',
+                           'mode 1',
+                           'PS_SP64_1',
+                           'PS_SP64_1',
+                           'mode 1',
+                           'mode 2',
+                           'mode 1',
+                           'mode 2',
+                           'nok']])
 def test_automaticmodefeature(net, eqpt, serv, expected_mode):
     equipment = load_equipment(eqpt)
     network = load_network(net, equipment)

Change-Id: I522c45c079b3a9540568657e2ae0a4bfc5fb1272
 2020-05-19 12:53:11 +02:00
Jan Kundrát
3548ed74e2 coding style: autopep --in-place --recursive --jobs 4 --max-line-length 120 gnpy/ tests/ 
Change-Id: I2f0fca5aa1314f9bb546a3e6dc712a42580cd562
 2020-05-19 12:40:00 +02:00
Jan Kundrát
5af195bd2b Remove unused imports 
Change-Id: I66174048a9eaab0f79ba4c3b1d31ef4dc9c2009b
 2020-04-30 17:30:55 +02:00
AndreaDAmico
80eced85ec Refactoring with some incompatible changes 
Please be advised that there were incompatible changes in the Raman
options, including a `s/phase_shift_tollerance/phase_shift_tolerance/`.

Signed-off-by: AndreaDAmico <andrea.damico@polito.it>
Co-authored-by: EstherLerouzic <esther.lerouzic@orange.com>
Co-authored-by: Jan Kundrát <jan.kundrat@telecominfraproject.com>
 2019-12-17 11:51:09 +01:00
Jan Kundrát
54bf426472 Raman: linear interpolation of channel NLI 
The Raman engine computes NLI just for a subset of channels; this is an
important speed optimization because the computation is rather CPU
heavy. However, the code just left NaNs in place for NLI of those
channels which were not explicitly simulated.

This is wrong because these NaNs propagate all the way to the total
input/output powers per the whole spectrum, etc, leading to NaNs being
shown to the user.

This patch uses a very simple linear approximation just in order to
prevent these NaNs.

fixes #288
 2019-09-02 21:10:20 +02:00
Jan Kundrát
81585c5a86 Unify implementations of psi computation 
Both of these places referred to "eq. 123 from arXiv:1209.0394", the
only difference (apart from the source of the input parameters, beta2
and asymptotic_length) was calling the two branches "SCI" and "XCI" vs.
"SPM" and "XPM".

In this commit I've only moved the code to a single implementation. The
input data are still being read from the same parameters, of course.
 2019-08-08 13:38:23 +02:00
Jan Kundrát
2f52c11589 More intuitive name for list of channels where Raman gain is computed 2019-08-08 11:34:33 +02:00
Jan Kundrát
0f4d8573cf Move Raman parameter propagation to gnpy.core.network 
Conceptually, this is just about propagating the input parameters (which
drive the simulation) into all RamanFiber instances. The network module
already contains similar functions, let's move it there.
 2019-08-08 11:19:25 +02:00
Jan Kundrát
36ca22db9b Raman: use logging instead of debugging print()s 2019-08-07 23:31:20 +02:00
Jan Kundrát
4e786a32b5 Merge branch 'no-convenience-access' into raman 
This required some adaptations in the new Raman code now that the
property aliases are gone.
 2019-08-06 11:43:16 +02:00
Alessio Ferrari
8a1001cd40 dynamic evaluation of threshold frequency between near XPM and far XPM 2019-08-01 14:42:47 +02:00
Alessio Ferrari
beb2b576aa changed output of propagate_raman_fiber to return a list 2019-08-01 14:41:40 +02:00
Alessio Ferrari
8f3923046b alpha0 computation moved from NLI solver to Fiber Params 2019-08-01 11:36:32 +02:00
Alessio Ferrari
88c68d2065 introduced classes for the parameters 2019-08-01 11:32:07 +02:00
Alessio Ferrari
8bcde72a10 changes on variable names to be more clear 2019-08-01 10:49:25 +02:00
Alessio Ferrari
4653dbcf4b introduced a faster computation for XPM 2019-08-01 10:48:02 +02:00
Alessio Ferrari
2eed891f8d new variable names for SPM and XPM 2019-07-31 11:29:25 +02:00
Alessio Ferrari
c0b84e84c8 double underscore replaced with single one for some attributes 2019-07-31 11:24:16 +02:00
Alessio Ferrari
2c20fd3f9f strings 'XPM' and 'SPM' removed while computing NLI, now it is implicit 2019-07-31 11:20:34 +02:00
Alessio Ferrari
f4db56ca29 minor fix to comments 2019-07-31 11:18:46 +02:00
Alessio Ferrari
e29f8485ea integration of the GGN-model with spectral separation 2019-06-18 13:31:01 +02:00
Alessio Ferrari
ff82c5171b propagate_raman_fiber function introduced 2019-06-11 13:39:41 +02:00
Alessio Ferrari
f9bd6310f1 introcude NLI solver 2019-06-11 13:38:39 +02:00
Alessio Ferrari
471eab126e fix raman solver parameters 2019-06-11 13:38:05 +02:00
Alessio Ferrari
fd406c106b gn model introduced in the science utils module 2019-06-03 16:33:26 +02:00
Alessio Ferrari
3f7180c706 configure_network function created to configure the RamanFiber.sim_params in a network 2019-05-28 11:35:42 +02:00
Alessio Ferrari
c0fda8c3a2 fix to Raman solver 2019-05-27 17:09:34 +02:00
Alessio Ferrari
0b2ee6fdaf add Raman solver 2019-05-22 12:05:51 +02:00
Alessio Ferrari
d86bea80d3 fix load_sim_params 2019-05-22 11:00:02 +02:00
Alessio Ferrari
efae43f122 utility to load sim params from json 2019-05-22 10:26:24 +02:00
Alessio Ferrari
45e8c8692b add science utils module 2019-05-22 10:09:27 +02:00