Files
oopt-gnpy/tests/test_network_functions.py
EstherLerouzic 38cc0e3cc5 feat: separate span power from tx power
gnpy currently uses the same parameter for tx output power and span
input power: this prevents from modelling low tx power effect.
This patch introduces a new tx-cannel-power and uses it to
propagate in ROADM.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: Id3ac75e2cb617b513bdb38b51a52e05d15af46f5
2024-06-02 19:26:33 +02:00

244 lines
7.7 KiB
Python

# SPDX-License-Identifier: BSD-3-Clause
#
# Copyright (C) 2020 Telecom Infra Project and GNPy contributors
# see LICENSE.md for a list of contributors
#
from pathlib import Path
import pytest
from gnpy.core.exceptions import NetworkTopologyError
from gnpy.core.network import span_loss, build_network
from gnpy.tools.json_io import load_equipment, load_network, network_from_json
from gnpy.core.utils import lin2db, automatic_nch
from gnpy.core.elements import Fiber, Edfa
TEST_DIR = Path(__file__).parent
EQPT_FILENAME = TEST_DIR / 'data/eqpt_config.json'
NETWORK_FILENAME = TEST_DIR / 'data/bugfixiteratortopo.json'
@pytest.mark.parametrize("node, attenuation", [
# first fiber span
['fiber1', 10.5],
['fiber2', 10.5],
['fused1', 10.5],
# second span
['fiber3', 16.0],
# third span
['fiber4', 16.0],
# direct link between a ROADM and an amplifier
['fused5', 0],
# fourth span
['fiber6', 17],
['fused7', 17],
# fifth span
['fiber7', 0.2],
['fiber8', 12],
# all other nodes
['Site_A', 0],
['nodeA', 0],
['amp2', 0],
['nodeC', 0],
['Site_C', 0],
['amp3', 0],
['amp4', 0],
['nodeB', 0],
['Site_B', 0],
])
def test_span_loss(node, attenuation):
equipment = load_equipment(EQPT_FILENAME)
network = load_network(NETWORK_FILENAME, equipment)
for x in network.nodes():
if x.uid == node:
assert attenuation == span_loss(network, x, equipment)
return
assert not f'node "{node}" referenced from test but not found in the topology' # pragma: no cover
@pytest.mark.parametrize("node", ['fused4'])
def test_span_loss_unconnected(node):
'''Fused node that has no next and no previous nodes should be detected'''
equipment = load_equipment(EQPT_FILENAME)
network = load_network(NETWORK_FILENAME, equipment)
x = next(x for x in network.nodes() if x.uid == node)
with pytest.raises(NetworkTopologyError):
span_loss(network, x, equipment)
@pytest.mark.parametrize('typ, expected_loss',
[('Edfa', [11, 11]),
('Fused', [11, 10])])
def test_eol(typ, expected_loss):
"""Check that EOL is added only once on spans. One span can be one fiber or several fused fibers
EOL is then added on the first fiber only.
"""
json_data = {
"elements": [
{
"uid": "trx SITE1",
"type": "Transceiver"
},
{
"uid": "trx SITE2",
"type": "Transceiver"
},
{
"uid": "roadm SITE1",
"type": "Roadm"
},
{
"uid": "roadm SITE2",
"type": "Roadm"
},
{
"uid": "fiber (SITE1 → ILA1)",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 50.0,
"loss_coef": 0.2,
"length_units": "km"
}
},
{
"uid": "fiber (ILA1 → SITE2)",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 50.0,
"loss_coef": 0.2,
"length_units": "km"
}
},
{
"uid": "east edfa in SITE1 to ILA1",
"type": "Edfa"
},
{
"uid": "west edfa in SITE2 to ILA1",
"type": typ
},
{
"uid": "east edfa in ILA1 to SITE2",
"type": "Edfa"
}
],
"connections": [
{
"from_node": "trx SITE1",
"to_node": "roadm SITE1"
},
{
"from_node": "roadm SITE1",
"to_node": "east edfa in SITE1 to ILA1"
},
{
"from_node": "east edfa in SITE1 to ILA1",
"to_node": "fiber (SITE1 → ILA1)"
},
{
"from_node": "fiber (SITE1 → ILA1)",
"to_node": "east edfa in ILA1 to SITE2"
},
{
"from_node": "east edfa in ILA1 to SITE2",
"to_node": "fiber (ILA1 → SITE2)"
},
{
"from_node": "fiber (ILA1 → SITE2)",
"to_node": "west edfa in SITE2 to ILA1"
},
{
"from_node": "west edfa in SITE2 to ILA1",
"to_node": "roadm SITE2"
},
{
"from_node": "roadm SITE2",
"to_node": "trx SITE2"
}
]
}
equipment = load_equipment(EQPT_FILENAME)
equipment['Span']['default'].EOL = 1
network = network_from_json(json_data, equipment)
p_db = equipment['SI']['default'].power_dbm
p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
build_network(network, equipment, p_db, p_total_db)
fibers = [f for f in network.nodes() if isinstance(f, Fiber)]
for i in range(2):
assert fibers[i].loss == expected_loss[i]
@pytest.mark.parametrize('p_db, power_mode, elem1, elem2, expected_gain, expected_delta_p, expected_voa', [
(-17, True, 'edfa', 'fiber', 15.0, 15, 15.0),
(-17, True, 'fiber', 'edfa', 15.0, 5.0, 5.0),
(-17, False, 'edfa', 'fiber', 0.0, None, 0.0),
(-17, False, 'fiber', 'edfa', 10.0, None, 0.0),
(10, True, 'edfa', 'fiber', -9.0, -9.0, 0.0),
(10, True, 'fiber', 'edfa', 1.0, -9.0, 0.0),
(10, False, 'edfa', 'fiber', -9.0, None, 0.0),
(10, False, 'fiber', 'edfa', 1.0, None, 0.0)])
def test_design_non_amplified_link(elem1, elem2, expected_gain, expected_delta_p, expected_voa, power_mode, p_db):
"""Check that the delta_p, gain computed on an amplified link that starts from a transceiver are correct
"""
json_data = {
"elements": [
{
"uid": "trx SITE1",
"type": "Transceiver"
},
{
"uid": "trx SITE2",
"type": "Transceiver"
},
{
"uid": "edfa",
"type": "Edfa",
"type_variety": "std_low_gain"
},
{
"uid": "fiber",
"type": "Fiber",
"type_variety": "SSMF",
"params": {
"length": 50.0,
"loss_coef": 0.2,
"length_units": "km"
}
}
],
"connections": [
{
"from_node": "trx SITE1",
"to_node": elem1
},
{
"from_node": elem1,
"to_node": elem2
},
{
"from_node": elem2,
"to_node": "trx SITE2"
}
]
}
equipment = load_equipment(EQPT_FILENAME)
equipment['Span']['default'].power_mode = power_mode
equipment['SI']['default'].power_dbm = p_db
equipment['SI']['default'].tx_power_dbm = p_db
network = network_from_json(json_data, equipment)
edfa = next(a for a in network.nodes() if a.uid == 'edfa')
edfa.params.out_voa_auto = True
p_total_db = p_db + 20.0
build_network(network, equipment, p_db, p_total_db)
amps = [a for a in network.nodes() if isinstance(a, Edfa)]
for amp in amps:
assert amp.out_voa == expected_voa
assert amp.delta_p == expected_delta_p
# max power of std_low_gain is 21 dBm
assert amp.effective_gain == expected_gain