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https://github.com/Telecominfraproject/oopt-gnpy.git
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09920c0af2
Modification of the Fiber and the NliSolver in order to properly propagate the new definition of the spectral information taking advantage of the numpy array structures. In the previous version, the propagation of the spectral information was implemented by means of for cycles over each channel, in turn. In this change the propagation is applied directly on the newly defined spectral information attributes as numpy arrays. Additional changes: - Simplification of the FiberParameters and the NliParameters; - Previous issues regarding the loss_coef definition along the frequency are solved; - New test in test_science_utils.py verifing that the fiber propagation provides the correct values in case of a few cases of flex grid spectra. Change-Id: Id71f36effba35fc3ed4bbf2481a3cf6566ccb51c
79 lines
3.2 KiB
Python
79 lines
3.2 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Checks that RamanFiber propagates properly the spectral information. In this way, also the RamanSolver and the NliSolver
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are tested.
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"""
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from pathlib import Path
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from pandas import read_csv
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from numpy.testing import assert_allclose
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from numpy import array
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import pytest
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from gnpy.core.info import create_input_spectral_information, create_arbitrary_spectral_information
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from gnpy.core.elements import Fiber, RamanFiber
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from gnpy.core.parameters import SimParams
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from gnpy.tools.json_io import load_json
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TEST_DIR = Path(__file__).parent
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def test_fiber():
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""" Test the accuracy of propagating the Fiber."""
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fiber = Fiber(**load_json(TEST_DIR / 'data' / 'test_science_utils_fiber_config.json'))
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# fix grid spectral information generation
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spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
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baud_rate=32e9, power=1e-3, spacing=50e9)
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# propagation
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spectral_info_out = fiber(spectral_info_input)
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p_signal = spectral_info_out.signal
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p_nli = spectral_info_out.nli
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expected_results = read_csv(TEST_DIR / 'data' / 'test_fiber_fix_expected_results.csv')
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assert_allclose(p_signal, expected_results['signal'], rtol=1e-3)
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assert_allclose(p_nli, expected_results['nli'], rtol=1e-3)
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# flex grid spectral information generation
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frequency = 191e12 + array([0, 50e9, 150e9, 225e9, 275e9])
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slot_width = array([37.5e9, 50e9, 75e9, 50e9, 37.5e9])
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baud_rate = array([32e9, 42e9, 64e9, 42e9, 32e9])
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signal = 1e-3 + array([0, -1e-4, 3e-4, -2e-4, +2e-4])
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spectral_info_input = create_arbitrary_spectral_information(frequency=frequency, slot_width=slot_width,
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signal=signal, baud_rate=baud_rate, roll_off=0.15)
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# propagation
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spectral_info_out = fiber(spectral_info_input)
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p_signal = spectral_info_out.signal
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p_nli = spectral_info_out.nli
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expected_results = read_csv(TEST_DIR / 'data' / 'test_fiber_flex_expected_results.csv')
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assert_allclose(p_signal, expected_results['signal'], rtol=1e-3)
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assert_allclose(p_nli, expected_results['nli'], rtol=1e-3)
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@pytest.mark.usefixtures('set_sim_params')
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def test_raman_fiber():
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""" Test the accuracy of propagating the RamanFiber."""
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# spectral information generation
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spectral_info_input = create_input_spectral_information(f_min=191.3e12, f_max=196.1e12, roll_off=0.15,
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baud_rate=32e9, power=1e-3, spacing=50e9)
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SimParams.set_params(load_json(TEST_DIR / 'data' / 'sim_params.json'))
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fiber = RamanFiber(**load_json(TEST_DIR / 'data' / 'test_science_utils_fiber_config.json'))
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# propagation
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spectral_info_out = fiber(spectral_info_input)
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p_signal = spectral_info_out.signal
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p_ase = spectral_info_out.ase
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p_nli = spectral_info_out.nli
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expected_results = read_csv(TEST_DIR / 'data' / 'test_raman_fiber_expected_results.csv')
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assert_allclose(p_signal, expected_results['signal'], rtol=1e-3)
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assert_allclose(p_ase, expected_results['ase'], rtol=1e-3)
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assert_allclose(p_nli, expected_results['nli'], rtol=1e-3)
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