mirror of
https://github.com/Telecominfraproject/oopt-gnpy.git
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131 lines
3.2 KiB
Python
131 lines
3.2 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import json
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import numpy as np
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from numpy import pi, cos, sqrt, log10
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def load_json(filename):
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with open(filename, 'r') as f:
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data = json.load(f)
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return data
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def save_json(obj, filename):
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with open(filename, 'w') as f:
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json.dump(obj, f)
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def c():
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"""
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Returns the speed of light in meters per second
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"""
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return 299792458.0
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def itufs(spacing, startf=191.35, stopf=196.10):
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"""Creates an array of frequencies whose default range is
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191.35-196.10 THz
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:param spacing: Frequency spacing in THz
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:param starf: Start frequency in THz
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:param stopf: Stop frequency in THz
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:type spacing: float
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:type startf: float
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:type stopf: float
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:return an array of frequnecies determined by the spacing parameter
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:rtype: numpy.ndarray
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"""
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return np.arange(startf, stopf + spacing / 2, spacing)
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def h():
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"""
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Returns plank's constant in J*s
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"""
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return 6.62607004e-34
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def lin2db(value):
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return 10 * log10(value)
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def db2lin(value):
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return 10**(value / 10)
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def wavelength2freq(value):
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""" Converts wavelength units to frequeuncy units.
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"""
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return c() / value
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def freq2wavelength(value):
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""" Converts frequency units to wavelength units.
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"""
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return c() / value
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def deltawl2deltaf(delta_wl, wavelength):
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""" deltawl2deltaf(delta_wl, wavelength):
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delta_wl is BW in wavelength units
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wavelength is the center wl
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units for delta_wl and wavelength must be same
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:param delta_wl: delta wavelength BW in same units as wavelength
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:param wavelength: wavelength BW is relevant for
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:type delta_wl: float or numpy.ndarray
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:type wavelength: float
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:return: The BW in frequency units
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:rtype: float or ndarray
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"""
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f = wavelength2freq(wavelength)
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return delta_wl * f / wavelength
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def deltaf2deltawl(delta_f, frequency):
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""" deltawl2deltaf(delta_f, frequency):
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converts delta frequency to delta wavelength
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units for delta_wl and wavelength must be same
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:param delta_f: delta frequency in same units as frequency
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:param frequency: frequency BW is relevant for
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:type delta_f: float or numpy.ndarray
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:type frequency: float
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:return: The BW in wavelength units
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:rtype: float or ndarray
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"""
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wl = freq2wavelength(frequency)
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return delta_f * wl / frequency
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def rrc(ffs, baud_rate, alpha):
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""" rrc(ffs, baud_rate, alpha): computes the root-raised cosine filter
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function.
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:param ffs: A numpy array of frequencies
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:param baud_rate: The Baud Rate of the System
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:param alpha: The roll-off factor of the filter
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:type ffs: numpy.ndarray
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:type baud_rate: float
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:type alpha: float
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:return: hf a numpy array of the filter shape
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:rtype: numpy.ndarray
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"""
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Ts = 1 / baud_rate
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l_lim = (1 - alpha) / (2 * Ts)
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r_lim = (1 + alpha) / (2 * Ts)
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hf = np.zeros(np.shape(ffs))
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slope_inds = np.where(
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np.logical_and(np.abs(ffs) > l_lim, np.abs(ffs) < r_lim))
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hf[slope_inds] = 0.5 * (1 + cos((pi * Ts / alpha) *
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(np.abs(ffs[slope_inds]) - l_lim)))
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p_inds = np.where(np.logical_and(np.abs(ffs) > 0, np.abs(ffs) < l_lim))
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hf[p_inds] = 1
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return sqrt(hf)
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