Move python stuff to folder

1 files changed, 0 insertions, 166 deletions

diff --git a/gui/dpd/Align.py b/gui/dpd/Align.py
deleted file mode 100644
index 1634ec8..0000000
--- a/gui/dpd/Align.py
+++ /dev/null
@@ -1,166 +0,0 @@
-# -*- coding: utf-8 -*-
-#
-# DPD Computation Engine, utility to do subsample alignment.
-#
-#   Copyright (c) 2017 Andreas Steger
-#   Copyright (c) 2018 Matthias P. Braendli
-#
-#    http://www.opendigitalradio.org
-#
-#   This file is part of ODR-DabMod.
-#
-#   ODR-DabMod is free software: you can redistribute it and/or modify
-#   it under the terms of the GNU General Public License as
-#   published by the Free Software Foundation, either version 3 of the
-#   License, or (at your option) any later version.
-#
-#   ODR-DabMod is distributed in the hope that it will be useful,
-#   but WITHOUT ANY WARRANTY; without even the implied warranty of
-#   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-#   GNU General Public License for more details.
-#
-#   You should have received a copy of the GNU General Public License
-#   along with ODR-DabMod.  If not, see <http://www.gnu.org/licenses/>.
-import datetime
-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)
-
-def phase_align(sig, ref_sig, plot_location=None):
-    """Do phase alignment for sig relative to the reference signal
-    ref_sig.
-
-    Returns the aligned signal"""
-
-    angle_diff = (np.angle(sig) - np.angle(ref_sig)) % (2. * np.pi)
-
-    real_diffs = np.cos(angle_diff)
-    imag_diffs = np.sin(angle_diff)
-
-    if plot_location is not None:
-        dt = datetime.datetime.now().isoformat()
-        fig_path = plot_location + "/" + dt + "_phase_align.png"
-
-        plt.subplot(511)
-        plt.hist(angle_diff, bins=60, label="Angle Diff")
-        plt.xlabel("Angle")
-        plt.ylabel("Count")
-        plt.legend(loc=4)
-
-        plt.subplot(512)
-        plt.hist(real_diffs, bins=60, label="Real Diff")
-        plt.xlabel("Real Part")
-        plt.ylabel("Count")
-        plt.legend(loc=4)
-
-        plt.subplot(513)
-        plt.hist(imag_diffs, bins=60, label="Imaginary Diff")
-        plt.xlabel("Imaginary Part")
-        plt.ylabel("Count")
-        plt.legend(loc=4)
-
-        plt.subplot(514)
-        plt.plot(np.angle(ref_sig[:128]), label="ref_sig")
-        plt.plot(np.angle(sig[:128]), label="sig")
-        plt.xlabel("Angle")
-        plt.ylabel("Sample")
-        plt.legend(loc=4)
-
-    real_diff = np.median(real_diffs)
-    imag_diff = np.median(imag_diffs)
-
-    angle = np.angle(real_diff + 1j * imag_diff)
-
-    #logging.debug( "Compensating phase by {} rad, {} degree. real median {}, imag median {}".format( angle, angle*180./np.pi, real_diff, imag_diff))
-    sig = sig * np.exp(1j * -angle)
-
-    if plot_location is not None:
-        plt.subplot(515)
-        plt.plot(np.angle(ref_sig[:128]), label="ref_sig")
-        plt.plot(np.angle(sig[:128]), label="sig")
-        plt.xlabel("Angle")
-        plt.ylabel("Sample")
-        plt.legend(loc=4)
-        plt.tight_layout()
-        plt.savefig(fig_path)
-        plt.close()
-
-    return sig