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author | andreas128 <Andreas> | 2017-05-29 21:55:44 +0100 |
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committer | andreas128 <Andreas> | 2017-05-29 21:55:44 +0100 |
commit | 59ff35e5b6a81150a87cc0b5a972a91bd64c3ab9 (patch) | |
tree | 84996d2f963fc90bef09802fbb74916e14da0f15 | |
parent | c8d61fa0a7b36e3c3acec5a4c22ee4b4ab14a700 (diff) | |
download | ODR-StaticPrecorrection-59ff35e5b6a81150a87cc0b5a972a91bd64c3ab9.tar.gz ODR-StaticPrecorrection-59ff35e5b6a81150a87cc0b5a972a91bd64c3ab9.tar.bz2 ODR-StaticPrecorrection-59ff35e5b6a81150a87cc0b5a972a91bd64c3ab9.zip |
Add subsample_alignment and it's test
-rw-r--r-- | calc_lag.py | 44 | ||||
-rwxr-xr-x | grc/live_analyse_dab_poly.py | 51 | ||||
-rw-r--r-- | src/dab_util.py | 40 | ||||
-rw-r--r-- | src/dab_util_test.py | 49 | ||||
-rwxr-xr-x | src/subsample_align.py | 13 |
5 files changed, 145 insertions, 52 deletions
diff --git a/calc_lag.py b/calc_lag.py new file mode 100644 index 0000000..5f5cf70 --- /dev/null +++ b/calc_lag.py @@ -0,0 +1,44 @@ +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import argparse +import re +import sys +from tqdm import tqdm + +from glob import glob +from natsort import natsorted +import numpy as np +import pandas as pd +import matplotlib.pyplot as plt + +import src.dab_util as du + + + + +tx_paths = natsorted(glob(r'/home/andreas/dab/ODR-StaticPrecorrection/data/received/*_tx_record.iq')) +rx_paths = natsorted(glob(r'/home/andreas/dab/ODR-StaticPrecorrection/data/received/*_rx_record.iq')) + +res = [] + +for tx_path, rx_path in zip(tx_paths, rx_paths): + s1 = du.fromfile(tx_path) + s2 = du.fromfile(rx_path) + + res.append({ + '1':du.lag_upsampling(s2, s1, n_up=1), + '2':du.lag_upsampling(s2, s1, n_up=2), + '3':du.lag_upsampling(s2, s1, n_up=3), + '4':du.lag_upsampling(s2, s1, n_up=4), + '8':du.lag_upsampling(s2, s1, n_up=8), + '16':du.lag_upsampling(s2, s1, n_up=16), + '32':du.lag_upsampling(s2, s1, n_up=32), + }) + +df = pd.DataFrame(res) +df = df.reindex_axis(sorted(df.columns), axis=1) +print(df) +print(df.describe()) + diff --git a/grc/live_analyse_dab_poly.py b/grc/live_analyse_dab_poly.py index cc7672b..126c43d 100755 --- a/grc/live_analyse_dab_poly.py +++ b/grc/live_analyse_dab_poly.py @@ -3,7 +3,7 @@ ################################################## # GNU Radio Python Flow Graph # Title: Live Analyse Dab Poly -# Generated: Mon Apr 10 14:20:48 2017 +# Generated: Tue May 23 20:21:44 2017 ################################################## if __name__ == '__main__': @@ -60,13 +60,12 @@ class live_analyse_dab_poly(gr.top_block, Qt.QWidget): ################################################## # Variables ################################################## - self.samp_rate = samp_rate = 8e6 self.txgain = txgain = 80 self.shift_freq = shift_freq = 1 + self.samp_rate_2 = samp_rate_2 = 2048000 + self.samp_rate_1 = samp_rate_1 = 8192000 self.rxgain = rxgain = 10 self.freq = freq = 222e6 - self.f2 = f2 = samp_rate / 3.875 - self.f1 = f1 = samp_rate / 4 self.ampl = ampl = 0.4 self.a_8 = a_8 = 0 self.a_7 = a_7 = 0 @@ -122,7 +121,7 @@ class live_analyse_dab_poly(gr.top_block, Qt.QWidget): channels=range(1), ), ) - self.uhd_usrp_source_0.set_samp_rate(samp_rate) + self.uhd_usrp_source_0.set_samp_rate(samp_rate_2) self.uhd_usrp_source_0.set_center_freq(freq, 0) self.uhd_usrp_source_0.set_gain(rxgain, 0) self.uhd_usrp_sink_0 = uhd.usrp_sink( @@ -132,7 +131,7 @@ class live_analyse_dab_poly(gr.top_block, Qt.QWidget): channels=range(1), ), ) - self.uhd_usrp_sink_0.set_samp_rate(samp_rate) + self.uhd_usrp_sink_0.set_samp_rate(samp_rate_1) self.uhd_usrp_sink_0.set_center_freq(freq, 0) self.uhd_usrp_sink_0.set_gain(txgain, 0) self.uhd_amsg_source_0 = uhd.amsg_source(device_addr="", msgq=uhd_amsg_source_0_msgq_out) @@ -143,7 +142,7 @@ class live_analyse_dab_poly(gr.top_block, Qt.QWidget): 16000, #size firdes.WIN_BLACKMAN_hARRIS, #wintype 0, #fc - samp_rate, #bw + samp_rate_2, #bw "", #name 1 #number of inputs ) @@ -206,17 +205,6 @@ class live_analyse_dab_poly(gr.top_block, Qt.QWidget): event.accept() - def get_samp_rate(self): - return self.samp_rate - - def set_samp_rate(self, samp_rate): - self.samp_rate = samp_rate - self.set_f1(self.samp_rate / 4) - self.set_f2(self.samp_rate / 3.875) - self.qtgui_freq_sink_x_0_0.set_frequency_range(0, self.samp_rate) - self.uhd_usrp_sink_0.set_samp_rate(self.samp_rate) - self.uhd_usrp_source_0.set_samp_rate(self.samp_rate) - def get_txgain(self): return self.txgain @@ -231,6 +219,21 @@ class live_analyse_dab_poly(gr.top_block, Qt.QWidget): def set_shift_freq(self, shift_freq): self.shift_freq = shift_freq + def get_samp_rate_2(self): + return self.samp_rate_2 + + def set_samp_rate_2(self, samp_rate_2): + self.samp_rate_2 = samp_rate_2 + self.qtgui_freq_sink_x_0_0.set_frequency_range(0, self.samp_rate_2) + self.uhd_usrp_source_0.set_samp_rate(self.samp_rate_2) + + def get_samp_rate_1(self): + return self.samp_rate_1 + + def set_samp_rate_1(self, samp_rate_1): + self.samp_rate_1 = samp_rate_1 + self.uhd_usrp_sink_0.set_samp_rate(self.samp_rate_1) + def get_rxgain(self): return self.rxgain @@ -247,18 +250,6 @@ class live_analyse_dab_poly(gr.top_block, Qt.QWidget): self.uhd_usrp_sink_0.set_center_freq(self.freq, 0) self.uhd_usrp_source_0.set_center_freq(self.freq, 0) - def get_f2(self): - return self.f2 - - def set_f2(self, f2): - self.f2 = f2 - - def get_f1(self): - return self.f1 - - def set_f1(self, f1): - self.f1 = f1 - def get_ampl(self): return self.ampl diff --git a/src/dab_util.py b/src/dab_util.py index 617bd9a..3187036 100644 --- a/src/dab_util.py +++ b/src/dab_util.py @@ -2,6 +2,7 @@ import numpy as np import scipy import matplotlib.pyplot as plt import src.dabconst as dabconst +import src.subsample_align as sa from scipy import signal c = {} @@ -76,22 +77,26 @@ def lag_upsampling(sig_orig, sig_rec, n_up): l_orig = float(l) / n_up return l_orig -def fftlag(sig_orig, sig_rec, n_upsampling = 1): +def subsample_align(sig1, sig2): """ - Efficient way to find lag between two signals - Args: - sig_orig: The signal that has been sent - sig_rec: The signal that has been recored + Returns an aligned version of sig1 and sig2 by cropping and subsample alignment """ - #off = sig_rec.shape[0] - #fft1 = np.fft.fft(sig_orig, n=sig_orig.shape[0]) - #fft2 = np.fft.fft(np.flipud(sig_rec), n=sig_rec.shape[0]) - #fftc = fft1 * fft2 - #c = np.fft.ifft(fftc) - c = signal.convolve(sig_orig, np.flipud(sig_rec)) - #c = signal.correlate(sig_orig, sig_rec) - return c - return np.argmax(c) - off + 1 + off_meas = lag_upsampling(sig2, sig1, n_up=1) + off = int(abs(off_meas)) + + if off_meas > 0: + sig1 = sig1[:-off] + sig2 = sig2[off:] + elif off_meas < 0: + sig1 = sig1[off:] + sig2 = sig2[:-off] + + if off % 2 == 1: + sig1 = sig1[:-1] + sig2 = sig2[:-1] + + sig2 = sa.subsample_align(sig2, sig1) + return sig1, sig2 def get_amp_ratio(ampl_1, ampl_2, a_out_abs, a_in_abs): idxs = (a_in_abs > ampl_1) & (a_in_abs < ampl_2) @@ -108,5 +113,8 @@ def get_transmission_frame_indices(n_frames, offset, rate = 2048000): indices = [tm1.S_F * i + offset for i in range(n_frames)] return indices -def fromfile(filename, offset, length): - return np.memmap(filename, dtype=np.complex64, mode='r', offset=64/8*offset, shape=length) +def fromfile(filename, offset=0, length=None): + if length is None: + return np.memmap(filename, dtype=np.complex64, mode='r', offset=64/8*offset) + else: + return np.memmap(filename, dtype=np.complex64, mode='r', offset=64/8*offset, shape=length) diff --git a/src/dab_util_test.py b/src/dab_util_test.py index be36d53..3f9e941 100644 --- a/src/dab_util_test.py +++ b/src/dab_util_test.py @@ -1,5 +1,7 @@ from scipy import signal import numpy as np +import pandas as pd +from tqdm import tqdm import src.gen_source as gs import src.dab_util as du @@ -28,7 +30,54 @@ def test_phase_offset(lag_function, tol): res.append(np.abs(off-off_meas)<tol) return np.mean(res) + +def test_using_aligned_pair(sample_orig=r'../data/orig_rough_aligned.dat', sample_rec =r'../data/recored_rough_aligned.dat', length = 10240, max_size = 1000000): + res = [] + for i in tqdm(range(100)): + start = np.random.randint(50, max_size) + r = np.random.randint(-50, 50) + + s1 = du.fromfile(sample_orig, offset=start+r, length=length) + s2 = du.fromfile(sample_rec, offset=start, length=length) + + res.append({'offset':r, + '1':r - du.lag_upsampling(s2, s1, n_up=1), + '2':r - du.lag_upsampling(s2, s1, n_up=2), + '3':r - du.lag_upsampling(s2, s1, n_up=3), + '4':r - du.lag_upsampling(s2, s1, n_up=4), + '8':r - du.lag_upsampling(s2, s1, n_up=8), + '16':r - du.lag_upsampling(s2, s1, n_up=16), + '32':r - du.lag_upsampling(s2, s1, n_up=32), + }) + df = pd.DataFrame(res) + df = df.reindex_axis(sorted(df.columns), axis=1) + print(df.describe()) + +def test_subsample_alignment(sample_orig=r'../data/orig_rough_aligned.dat', + sample_rec =r'../data/recored_rough_aligned.dat', length = 10240, max_size = 1000000): + res1 = [] + res2 = [] + for i in tqdm(range(10)): + start = np.random.randint(50, max_size) + r = np.random.randint(-50, 50) + + s1 = du.fromfile(sample_orig, offset=start+r, length=length) + s2 = du.fromfile(sample_rec, offset=start, length=length) + + res1.append(du.lag_upsampling(s2, s1, 32)) + + s1_aligned, s2_aligned = du.subsample_align(s1,s2) + + res2.append(du.lag_upsampling(s2_aligned, s1_aligned, 32)) + + print("Before subsample alignment: lag_std = %.2f, lag_abs_mean = %.2f" % (np.std(res1), np.mean(np.abs(res1)))) + print("After subsample alignment: lag_std = %.2f, lag_abs_mean = %.2f" % (np.std(res2), np.mean(np.abs(res2)))) + +print("Align using upsampling") for n_up in [1, 2, 3, 4, 7, 8, 16]: correct_ratio = test_phase_offset(lambda x,y: du.lag_upsampling(x,y,n_up), tol=1./n_up) print("%.1f%% of the tested offsets were measured within tolerance %.4f for n_up = %d" % (correct_ratio * 100, 1./n_up, n_up)) +test_using_aligned_pair() +print("Phase alignment") +test_subsample_alignment() diff --git a/src/subsample_align.py b/src/subsample_align.py index 376058c..1657131 100755 --- a/src/subsample_align.py +++ b/src/subsample_align.py @@ -3,6 +3,7 @@ import numpy as np from scipy import signal, optimize import sys import matplotlib.pyplot as plt +import dab_util as du def gen_omega(length): if (length % 2) == 1: @@ -59,29 +60,29 @@ def subsample_align(sig, ref_sig): optim_result = optimize.minimize_scalar(correlate_for_delay, bounds=(-1,1), method='bounded', options={'disp': True}) if optim_result.success: - print("x:") - print(optim_result.x) + #print("x:") + #print(optim_result.x) best_tau = optim_result.x - print("Found subsample delay = {}".format(best_tau)) + #print("Found subsample delay = {}".format(best_tau)) # 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) else: - print("Could not optimize: " + optim_result.message) + #print("Could not optimize: " + optim_result.message) return np.zeros(0, dtype=np.complex64) if __name__ == "__main__": - phaseref_filename = "/home/bram/dab/aux/odr-dab-cir/phasereference.2048000.fc64.iq" + phaseref_filename = "/home/andreas/dab/ODR-StaticPrecorrection/data/samples/sample_orig_0.iq" phase_ref = np.fromfile(phaseref_filename, np.complex64) delay = 15 n_up = 32 - print("Generate signal with delay {}/{} = {}".format(delay, n_up, delay/n_up)) + print("Generate signal with delay {}/{} = {}".format(delay, n_up, float(delay)/n_up)) phase_ref_up = signal.resample(phase_ref, phase_ref.shape[0] * n_up) phase_ref_up_late = np.append(np.zeros(delay, dtype=np.complex64), phase_ref_up[:-delay]) phase_ref_late = signal.resample(phase_ref_up_late, phase_ref.shape[0]) |