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Diffstat (limited to 'dpd/src/subsample_align.py')
| -rwxr-xr-x | dpd/src/subsample_align.py | 111 |
1 files changed, 0 insertions, 111 deletions
diff --git a/dpd/src/subsample_align.py b/dpd/src/subsample_align.py deleted file mode 100755 index 20ae56b..0000000 --- a/dpd/src/subsample_align.py +++ /dev/null @@ -1,111 +0,0 @@ -# -*- coding: utf-8 -*- -# -# DPD Computation Engine, utility to do subsample alignment. -# -# http://www.opendigitalradio.org -# Licence: The MIT License, see notice at the end of this file -import datetime -import logging -import os -import numpy as np -from scipy import optimize -import matplotlib.pyplot as plt - -def gen_omega(length): - if (length % 2) == 1: - raise ValueError("Needs an even length array.") - - halflength = int(length / 2) - factor = 2.0 * np.pi / length - - omega = np.zeros(length, dtype=np.float) - for i in range(halflength): - omega[i] = factor * i - - for i in range(halflength, length): - omega[i] = factor * (i - length) - - return omega - - -def subsample_align(sig, ref_sig, plot_location=None): - """Do subsample alignment for sig relative to the reference signal - ref_sig. The delay between the two must be less than sample - - Returns the aligned signal""" - - n = len(sig) - if (n % 2) == 1: - raise ValueError("Needs an even length signal.") - halflen = int(n / 2) - - fft_sig = np.fft.fft(sig) - - omega = gen_omega(n) - - def correlate_for_delay(tau): - # A subsample offset between two signals corresponds, in the frequency - # domain, to a linearly increasing phase shift, whose slope - # corresponds to the delay. - # - # Here, we build this phase shift in rotate_vec, and multiply it with - # our signal. - - rotate_vec = np.exp(1j * tau * omega) - # zero-frequency is rotate_vec[0], so rotate_vec[N/2] is the - # bin corresponding to the [-1, 1, -1, 1, ...] time signal, which - # is both the maximum positive and negative frequency. - # I don't remember why we handle it differently. - rotate_vec[halflen] = np.cos(np.pi * tau) - - corr_sig = np.fft.ifft(rotate_vec * fft_sig) - - return -np.abs(np.sum(np.conj(corr_sig) * ref_sig)) - - optim_result = optimize.minimize_scalar(correlate_for_delay, bounds=(-1, 1), method='bounded', - options={'disp': True}) - - if optim_result.success: - best_tau = optim_result.x - - if plot_location is not None: - corr = np.vectorize(correlate_for_delay) - ixs = np.linspace(-1, 1, 100) - taus = corr(ixs) - - dt = datetime.datetime.now().isoformat() - tau_path = (plot_location + "/" + dt + "_tau.png") - plt.plot(ixs, taus) - plt.title("Subsample correlation, minimum is best: {}".format(best_tau)) - plt.savefig(tau_path) - plt.close() - - # Prepare rotate_vec = fft_sig with rotated phase - rotate_vec = np.exp(1j * best_tau * omega) - rotate_vec[halflen] = np.cos(np.pi * best_tau) - return np.fft.ifft(rotate_vec * fft_sig).astype(np.complex64) - else: - # print("Could not optimize: " + optim_result.message) - return np.zeros(0, dtype=np.complex64) - -# The MIT License (MIT) -# -# Copyright (c) 2017 Andreas Steger -# -# Permission is hereby granted, free of charge, to any person obtaining a copy -# of this software and associated documentation files (the "Software"), to deal -# in the Software without restriction, including without limitation the rights -# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -# copies of the Software, and to permit persons to whom the Software is -# furnished to do so, subject to the following conditions: -# -# The above copyright notice and this permission notice shall be included in all -# copies or substantial portions of the Software. -# -# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -# SOFTWARE. |