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tests: prefer pandas.read_csv over numpy.genfromtext

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Change-Id: Icc9618afc4cad0c7a07f3a785c99b6b438e0c6cc
This commit is contained in:
AndreaDAmico
2023-06-26 13:47:29 +02:00
committed by Jan Kundrát
parent eb2363a3d4
commit 4ea0180caf
1 changed files with 6 additions and 5 deletions
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11
tests/test_science_utils.py
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@@ -9,10 +9,11 @@ are tested.
from pathlib import Path
from pandas import read_csv
from numpy.testing import assert_allclose
from numpy import array, genfromtxt
from numpy import array
import pytest
from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information, Pref, ReferenceCarrier
from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information, Pref, \
ReferenceCarrier
from gnpy.core.elements import Fiber, RamanFiber
from gnpy.core.parameters import SimParams
from gnpy.tools.json_io import load_json
@@ -118,18 +119,18 @@ def test_fiber_lumped_losses_srs(set_sim_params):
stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering(
spectral_info_input, fiber)
power_profile = stimulated_raman_scattering.power_profile
expected_power_profile = genfromtxt(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_pumps.csv', delimiter=',')
expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_pumps.csv', header=None)
assert_allclose(power_profile, expected_power_profile, rtol=1e-3)
# with Raman pumps
expected_power_profile = genfromtxt(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber.csv', delimiter=',')
expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_raman_fiber.csv', header=None)
stimulated_raman_scattering = RamanSolver.calculate_stimulated_raman_scattering(
spectral_info_input, raman_fiber)
power_profile = stimulated_raman_scattering.power_profile
assert_allclose(power_profile, expected_power_profile, rtol=1e-3)
# without Stimulated Raman Scattering
expected_power_profile = genfromtxt(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_raman.csv', delimiter=',')
expected_power_profile = read_csv(TEST_DIR / 'data' / 'test_lumped_losses_fiber_no_raman.csv', header=None)
stimulated_raman_scattering = RamanSolver.calculate_attenuation_profile(spectral_info_input, fiber)
power_profile = stimulated_raman_scattering.power_profile
assert_allclose(power_profile, expected_power_profile, rtol=1e-3)