From 5e3ca125bfc56d31b9c9ef819eab9171b73b7333 Mon Sep 17 00:00:00 2001 From: andreas128 Date: Fri, 29 Sep 2017 18:50:41 +0200 Subject: Cleanup --- dpd/apply_adapt_dumps.py | 4 +- dpd/main.py | 6 +- dpd/src/Const.py | 2 +- dpd/src/Heuristics.py | 13 ++++- dpd/src/MER.py | 7 +-- dpd/src/Measure.py | 21 +++---- dpd/src/Measure_Shoulders.py | 37 +++++++----- dpd/src/Model_AM.py | 2 + dpd/src/Model_PM.py | 21 +++---- dpd/src/Symbol_align.py | 67 +++++++++++---------- dpd/src/TX_Agc.py | 2 +- dpd/src/Test_data.py | 136 ------------------------------------------- dpd/src/subsample_align.py | 19 +++--- dpd/src/test_dab_Util.py | 92 ----------------------------- dpd/src/test_measure.py | 62 -------------------- 15 files changed, 112 insertions(+), 379 deletions(-) delete mode 100644 dpd/src/Test_data.py delete mode 100644 dpd/src/test_dab_Util.py delete mode 100644 dpd/src/test_measure.py diff --git a/dpd/apply_adapt_dumps.py b/dpd/apply_adapt_dumps.py index 4ecdc08..ee75e25 100755 --- a/dpd/apply_adapt_dumps.py +++ b/dpd/apply_adapt_dumps.py @@ -128,7 +128,7 @@ tx_gain = adapt.get_txgain() rx_gain = adapt.get_rxgain() digital_gain = adapt.get_digital_gain() -dpddata = adapt.get_predistorter +dpddata = adapt.get_predistorter() if dpddata[0] == "poly": coefs_am = dpddata[1] coefs_pm = dpddata[2] @@ -162,7 +162,7 @@ print(paths) for i, path in enumerate(paths): print(i, path) adapt.load(path) - dpddata_after = adapt.get_predistorter + dpddata_after = adapt.get_predistorter() coefs_am, coefs_pm = model.reset_coefs() adapt.set_predistorter(("poly", coefs_am, coefs_pm)) diff --git a/dpd/main.py b/dpd/main.py index 4e9647a..b2f930a 100755 --- a/dpd/main.py +++ b/dpd/main.py @@ -176,8 +176,10 @@ tx_agc = TX_Agc(adapt, c) agc = Agc(meas, adapt, c) agc.run() -state = "measure" +state = 'report' i = 0 +lr = None +n_meas = None while i < num_iter: try: # Measure @@ -218,6 +220,8 @@ while i < num_iter: # Report elif state == 'report': try: + txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples() + # Store all settings for pre-distortion, tx and rx adapt.dump() diff --git a/dpd/src/Const.py b/dpd/src/Const.py index 390dfbb..ac48b59 100644 --- a/dpd/src/Const.py +++ b/dpd/src/Const.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- # -# DPD Calculation Engine, constants +# DPD Calculation Engine, constants. # # Source for DAB standard: etsi_EN_300_401_v010401p p145 # diff --git a/dpd/src/Heuristics.py b/dpd/src/Heuristics.py index a32ccff..f98490d 100644 --- a/dpd/src/Heuristics.py +++ b/dpd/src/Heuristics.py @@ -1,26 +1,33 @@ # -*- coding: utf-8 -*- # -# DPD Calculation Engine, heuristics we use to tune the parameters +# DPD Calculation Engine, heuristics we use to tune the parameters. # # http://www.opendigitalradio.org # Licence: The MIT License, see notice at the end of this file import numpy as np + def get_learning_rate(idx_run): + """Gradually reduce learning rate from lr_max to lr_min within + idx_max steps, then keep the learning rate at lr_min""" idx_max = 10.0 lr_min = 0.05 lr_max = 0.4 lr_delta = lr_max - lr_min idx_run = min(idx_run, idx_max) - learning_rate = lr_max - lr_delta * idx_run/idx_max + learning_rate = lr_max - lr_delta * idx_run / idx_max return learning_rate + def get_n_meas(idx_run): + """Gradually increase number of measurements used to extract + a statistic from n_meas_min to n_meas_max within idx_max steps, + then keep number of measurements at n_meas_max""" idx_max = 10.0 n_meas_min = 10 n_meas_max = 20 n_meas_delta = n_meas_max - n_meas_min idx_run = min(idx_run, idx_max) - learning_rate = n_meas_delta * idx_run/idx_max + n_meas_min + learning_rate = n_meas_delta * idx_run / idx_max + n_meas_min return int(np.round(learning_rate)) diff --git a/dpd/src/MER.py b/dpd/src/MER.py index 69c94f9..0f169a7 100644 --- a/dpd/src/MER.py +++ b/dpd/src/MER.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- # -# Modulation Error Rate +# DPD Calculation Engine, Modulation Error Rate. # # http://www.opendigitalradio.org # Licence: The MIT License, see notice at the end of this file @@ -13,7 +13,6 @@ try: except: logging_path = "/tmp/" -import src.Const import numpy as np import matplotlib matplotlib.use('agg') @@ -72,8 +71,8 @@ class MER: return x_mean, y_mean, U_RMS, U_ERR, MER def calc_mer(self, tx, debug_name=""): - assert tx.shape[0] == self.c.T_U,\ - "Wrong input length" + """Calculate MER for input signal from a symbol aligned signal.""" + assert tx.shape[0] == self.c.T_U, "Wrong input length" spectrum = self._calc_spectrum(tx) diff --git a/dpd/src/Measure.py b/dpd/src/Measure.py index 7a9246c..d485a86 100644 --- a/dpd/src/Measure.py +++ b/dpd/src/Measure.py @@ -6,14 +6,11 @@ # http://www.opendigitalradio.org # Licence: The MIT License, see notice at the end of this file -import sys import socket import struct import numpy as np -import logging import src.Dab_Util as DU import os -import datetime import logging logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename) @@ -78,15 +75,15 @@ class Measure: rxframe = np.array([], dtype=np.complex64) if logging.getLogger().getEffectiveLevel() == logging.DEBUG: - logging.debug("txframe: min %f, max %f, median %f" % - (np.min(np.abs(txframe)), - np.max(np.abs(txframe)), - np.median(np.abs(txframe)))) - - logging.debug("rxframe: min %f, max %f, median %f" % - (np.min(np.abs(rxframe)), - np.max(np.abs(rxframe)), - np.median(np.abs(rxframe)))) + logging.debug('txframe: min {}, max {}, median {}'.format( + np.min(np.abs(txframe)), + np.max(np.abs(txframe)), + np.median(np.abs(txframe)))) + + logging.debug('rxframe: min {}, max {}, median {}'.format( + np.min(np.abs(rxframe)), + np.max(np.abs(rxframe)), + np.median(np.abs(rxframe)))) logging.debug("Disconnecting") s.close() diff --git a/dpd/src/Measure_Shoulders.py b/dpd/src/Measure_Shoulders.py index 7d48a2b..4cf7d0d 100644 --- a/dpd/src/Measure_Shoulders.py +++ b/dpd/src/Measure_Shoulders.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- # -# DPD Calculation Engine, calculate peak to shoulder difference +# DPD Calculation Engine, calculate peak to shoulder difference. # # http://www.opendigitalradio.org # Licence: The MIT License, see notice at the end of this file @@ -15,28 +15,35 @@ logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFil import numpy as np import matplotlib.pyplot as plt + def plt_next_axis(sub_rows, sub_cols, i_sub): i_sub += 1 ax = plt.subplot(sub_rows, sub_cols, i_sub) return i_sub, ax -def plt_annotate(ax, x,y,title=None,legend_loc=None): + +def plt_annotate(ax, x, y, title=None, legend_loc=None): ax.set_xlabel(x) ax.set_ylabel(y) - if title is not None: ax.set_title(title) - if legend_loc is not None: ax.legend(loc=legend_loc) + if title is not None: + ax.set_title(title) + if legend_loc is not None: + ax.legend(loc=legend_loc) + def calc_fft_db(signal, offset, c): fft = np.fft.fftshift(np.fft.fft(signal[offset:offset + c.MS_FFT_size])) fft_db = 20 * np.log10(np.abs(fft)) return fft_db + def _calc_peak(fft, c): assert fft.shape == (c.MS_FFT_size,), fft.shape idxs = (c.MS_peak_start, c.MS_peak_end) peak = np.mean(fft[idxs[0]:idxs[1]]) return peak, idxs + def _calc_shoulder_hight(fft_db, c): assert fft_db.shape == (c.MS_FFT_size,), fft_db.shape idxs_left = (c.MS_shoulder_left_start, c.MS_shoulder_left_end) @@ -48,26 +55,26 @@ def _calc_shoulder_hight(fft_db, c): shoulder = np.mean((shoulder_left, shoulder_right)) return shoulder, (idxs_left, idxs_right) + def calc_shoulder(fft, c): peak = _calc_peak(fft, c)[0] shoulder = _calc_shoulder_hight(fft, c)[0] assert (peak >= shoulder), (peak, shoulder) return peak, shoulder + def shoulder_from_sig_offset(arg): signal, offset, c = arg fft_db = calc_fft_db(signal, offset, c) peak, shoulder = calc_shoulder(fft_db, c) - return peak-shoulder, peak, shoulder + return peak - shoulder, peak, shoulder class Measure_Shoulders: """Calculate difference between the DAB signal and the shoulder hight in the power spectrum""" - def __init__(self, - c, - plot=False): + def __init__(self, c): self.c = c self.plot = c.MS_plot @@ -75,9 +82,9 @@ class Measure_Shoulders: dt = datetime.datetime.now().isoformat() fig_path = logging_path + "/" + dt + "_sync_subsample_aligned.svg" - fft = calc_fft_db(signal, 100, 10) - peak, idxs_peak = self._calc_peak(fft) - shoulder, idxs_sh = self._calc_shoulder_hight(fft, self.c) + fft = calc_fft_db(signal, 100, self.c) + peak, idxs_peak = _calc_peak(fft, self.c) + shoulder, idxs_sh = _calc_shoulder_hight(fft, self.c) sub_rows = 1 sub_cols = 1 @@ -93,7 +100,7 @@ class Measure_Shoulders: ax.plot(idxs_sh[1], (shoulder, shoulder), color='blue') plt_annotate(ax, "Frequency", "Magnitude [dB]", None, 4) - ax.text(100, -17, str(self.calc_shoulder(fft, self.c))) + ax.text(100, -17, str(calc_shoulder(fft, self.c))) ax.set_ylim(-20, 30) fig.tight_layout() @@ -106,14 +113,13 @@ class Measure_Shoulders: return None assert signal.shape[0] > 4 * self.c.MS_FFT_size - if n_avg is None: n_avg = self.c.MS_averaging_size + if n_avg is None: + n_avg = self.c.MS_averaging_size off_min = 0 off_max = signal.shape[0] - self.c.MS_FFT_size offsets = np.linspace(off_min, off_max, num=n_avg, dtype=int) - shoulders = [] - args = zip( [signal, ] * offsets.shape[0], offsets, @@ -129,7 +135,6 @@ class Measure_Shoulders: return np.mean(shoulders_diff), np.mean(shoulders), np.mean(peaks) - # The MIT License (MIT) # # Copyright (c) 2017 Andreas Steger diff --git a/dpd/src/Model_AM.py b/dpd/src/Model_AM.py index cdc3de1..a40f421 100644 --- a/dpd/src/Model_AM.py +++ b/dpd/src/Model_AM.py @@ -90,6 +90,8 @@ class Model_AM: plt.close(fig) def get_next_coefs(self, tx_dpd, rx_received, coefs_am): + """Calculate the next AM/AM coefficients using the extracted + statistic of TX and RX amplitude""" check_input_get_next_coefs(tx_dpd, rx_received) coefs_am_new = fit_poly(tx_dpd, rx_received) diff --git a/dpd/src/Model_PM.py b/dpd/src/Model_PM.py index e0fcb55..b0c7ae2 100644 --- a/dpd/src/Model_PM.py +++ b/dpd/src/Model_PM.py @@ -15,17 +15,16 @@ import numpy as np import matplotlib.pyplot as plt +def is_npfloat32(array): + assert isinstance(array, np.ndarray), type(array) + assert array.dtype == np.float32, array.dtype + assert array.flags.contiguous + assert not any(np.isnan(array)) + + def check_input_get_next_coefs(tx_dpd, phase_diff): - is_float32 = lambda x: (isinstance(x, np.ndarray) and - x.dtype == np.float32 and - x.flags.contiguous) - assert is_float32(tx_dpd), \ - "tx_dpd is not float32 but {}".format(tx_dpd[0].dtype) - assert is_float32(phase_diff), \ - "phase_diff is not float32 but {}".format(tx_dpd[0].dtype) - assert tx_dpd.shape == phase_diff.shape, \ - "tx_dpd.shape {}, phase_diff.shape {}".format( - tx_dpd.shape, phase_diff.shape) + is_npfloat32(tx_dpd) + is_npfloat32(phase_diff) class Model_PM: @@ -93,6 +92,8 @@ class Model_PM: return tx_range, phase_diff def get_next_coefs(self, tx_dpd, phase_diff, coefs_pm): + """Calculate the next AM/PM coefficients using the extracted + statistic of TX amplitude and phase difference""" tx_dpd, phase_diff = self._discard_small_values(tx_dpd, phase_diff) check_input_get_next_coefs(tx_dpd, phase_diff) diff --git a/dpd/src/Symbol_align.py b/dpd/src/Symbol_align.py index e21e793..4ea79c5 100644 --- a/dpd/src/Symbol_align.py +++ b/dpd/src/Symbol_align.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- # -# Modulation Error Rate +# DPD Calculation Engine, Modulation Error Rate. # # http://www.opendigitalradio.org # Licence: The MIT License, see notice at the end of this file @@ -8,24 +8,50 @@ import datetime import os import logging -import time + try: logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename) except: logging_path = "/tmp/" import numpy as np -import src.Const import scipy import matplotlib + matplotlib.use('agg') import matplotlib.pyplot as plt + +def _remove_outliers(x, stds=5): + deviation_from_mean = np.abs(x - np.mean(x)) + inlier_idxs = deviation_from_mean < stds * np.std(x) + x = x[inlier_idxs] + return x + + +def _calc_delta_angle(fft): + # Introduce invariance against carrier + angles = np.angle(fft) % (np.pi / 2.) + + # Calculate Angle difference and compensate jumps + deltas_angle = np.diff(angles) + deltas_angle[deltas_angle > np.pi / 4.] = \ + deltas_angle[deltas_angle > np.pi / 4.] - np.pi / 2. + deltas_angle[-deltas_angle > np.pi / 4.] = \ + deltas_angle[-deltas_angle > np.pi / 4.] + np.pi / 2. + deltas_angle = _remove_outliers(deltas_angle) + + delta_angle = np.mean(deltas_angle) + + return delta_angle + + class Symbol_align: """ Find the phase offset to the start of the DAB symbols in an unaligned dab signal. """ + def __init__(self, c, plot=False): self.c = c self.plot = plot @@ -95,8 +121,8 @@ class Symbol_align: ax.set_title("Min Filter") ax = fig.add_subplot(4, 1, 4) - tx_product_crop = tx_product[peaks[0]-50:peaks[0]+50] - x = range(tx_product.shape[0])[peaks[0]-50:peaks[0]+50] + tx_product_crop = tx_product[peaks[0] - 50:peaks[0] + 50] + x = range(tx_product.shape[0])[peaks[0] - 50:peaks[0] + 50] ax.plot(x, tx_product_crop) ylim = ax.get_ylim() ax.plot((peaks[0], peaks[0]), (ylim[0], ylim[1])) @@ -113,38 +139,16 @@ class Symbol_align: # of the shift to find the offset of the symbol start. return (offset + self.c.T_C) % self.c.T_S - def _remove_outliers(self, x, stds=5): - deviation_from_mean = np.abs(x - np.mean(x)) - inlier_idxs = deviation_from_mean < stds * np.std(x) - x = x[inlier_idxs] - return x - - def _calc_delta_angle(self, fft): - # Introduce invariance against carrier - angles = np.angle(fft) % (np.pi / 2.) - - # Calculate Angle difference and compensate jumps - deltas_angle = np.diff(angles) - deltas_angle[deltas_angle > np.pi/4.] =\ - deltas_angle[deltas_angle > np.pi/4.] - np.pi/2. - deltas_angle[-deltas_angle > np.pi/4.] = \ - deltas_angle[-deltas_angle > np.pi/4.] + np.pi/2. - deltas_angle = self._remove_outliers(deltas_angle) - - delta_angle = np.mean(deltas_angle) - - return delta_angle - def _delta_angle_to_samples(self, angle): return - angle / self.c.phase_offset_per_sample - def _calc_sample_offset(self, sig, debug=False): - assert sig.shape[0] == self.c.T_U,\ + def _calc_sample_offset(self, sig): + assert sig.shape[0] == self.c.T_U, \ "Input length is not a Symbol without cyclic prefix" fft = np.fft.fftshift(np.fft.fft(sig)) fft_crop = np.delete(fft[self.c.FFT_start:self.c.FFT_end], self.c.FFT_delete) - delta_angle = self._calc_delta_angle(fft_crop) + delta_angle = _calc_delta_angle(fft_crop) delta_sample = self._delta_angle_to_samples(delta_angle) delta_sample_int = np.round(delta_sample).astype(int) error = np.abs(delta_sample_int - delta_sample) @@ -154,6 +158,7 @@ class Symbol_align: return delta_sample_int def calc_offset(self, tx): + """Calculate the offset the first symbol""" off_sym = self._calc_offset_to_first_symbol_without_prefix( tx) off_sam = self._calc_sample_offset( @@ -168,7 +173,7 @@ class Symbol_align: off = self.calc_offset(tx) return tx[ off: - off+self.c.T_U + off + self.c.T_U ] # The MIT License (MIT) diff --git a/dpd/src/TX_Agc.py b/dpd/src/TX_Agc.py index 2602ea6..857ae06 100644 --- a/dpd/src/TX_Agc.py +++ b/dpd/src/TX_Agc.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- # -# Automatic Gain Control +# DPD Calculation Engine, Automatic Gain Control. # # http://www.opendigitalradio.org # Licence: The MIT License, see notice at the end of this file diff --git a/dpd/src/Test_data.py b/dpd/src/Test_data.py deleted file mode 100644 index bbef282..0000000 --- a/dpd/src/Test_data.py +++ /dev/null @@ -1,136 +0,0 @@ -# -*- coding: utf-8 -*- -# -# Modulation Error Rate -# -# http://www.opendigitalradio.org -# Licence: The MIT License, see notice at the end of this file - -import datetime -import os -import logging -import time -try: - logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename) -except: - logging_path = "/tmp/" - -import src.Const -import src.Dab_Util -import numpy as np -import matplotlib -matplotlib.use('agg') -import matplotlib.pyplot as plt - - -class Test_data: - def __init__(self, sample_rate, type): - """ - Standardized access to complex64 test data files. - - :param sample_rate: - :param type: - - Testing: - TD = src.Test_data.Test_data(8192000, 'file') - tx_orig = TD.get_symbol(0,0) - fig = plt.figure(figsize=(9,6)) - ax = fig.add_subplot(2,1,1) - ax.plot(tx_orig) - ax = fig.add_subplot(2,1,2) - plt.plot(np.angle(np.fft.fftshift(np.fft.fft(tx_orig))), 'p') - """ - - self.c = src.Const.Const(sample_rate,, False - self.du = src.Dab_Util.Dab_Util(sample_rate) - - self.file_paths = { - (2048000, 'file'): - ("./test_data/odr-dabmod_to_file_2048_NoFir_noDPD.iq", - ( - self.c.T_F + # Pipelineing - self.c.T_NULL + # NULL Symbol - self.c.T_S + # Synchronization Symbol - self.c.T_C # Cyclic Prefix - )), - (8192000, 'file'): - ("./test_data/odr-dabmod_to_file_8192_NoFir_noDPD.iq", - ( - self.c.T_F + # Pipelining - self.c.T_U + # Pipelining Resampler TODO(?) - self.c.T_NULL + # NULL Symbol - self.c.T_S + # Synchronization Symbol - self.c.T_C # Cyclic Prefix - )), - (8192000, 'rec_noFir'): - ("./test_data/odr-dabmod_reconding_8192_NoFir_DPD_2104.iq", - ( 64 )), - (8192000, 'rec_fir'): - ("./test_data/odr-dabmod_reconding_8192_Fir_DPD_2104.iq", - ( 232 )), - } - - config = (sample_rate, type) - if not config in self.file_paths.keys(): - raise RuntimeError("Configuration not found, possible are:\n {}". - format(self.file_paths)) - - self.path, self.file_offset = self.file_paths[(sample_rate, type)] - - def _load_from_file(self, offset, length): - print(offset, length, self.file_offset) - return self.du.fromfile( - self.path, - length=length, - offset=offset + self.file_offset) - - def get_symbol_without_prefix(self, - frame_idx=0, - symbol_idx=0, - off=0): - return self._load_from_file( - frame_idx*self.c.T_F + - symbol_idx*self.c.T_S + - off, - self.c.T_U) - - def get_symbol_with_prefix(self, - frame_idx=0, - symbol_idx=0, - n_symbols=1, - off=0): - offset = ( - frame_idx*self.c.T_F + - symbol_idx*self.c.T_S - - self.c.T_C + - off) - return self._load_from_file( offset, self.c.T_S * n_symbols) - - def get_file_length_in_symbols(self): - symbol_size = float( - 64/8 * # complex 64 - self.c.T_S # Symbol Size - ) - return os.path.getsize(self.path) / symbol_size - - -# 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. diff --git a/dpd/src/subsample_align.py b/dpd/src/subsample_align.py index b0cbe88..0c98e50 100755 --- a/dpd/src/subsample_align.py +++ b/dpd/src/subsample_align.py @@ -1,23 +1,25 @@ # -*- coding: utf-8 -*- # -# DPD Calculation Engine, utility to do subsample alignment +# DPD Calculation 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 os import logging +import os + logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename) import numpy as np -from scipy import signal, optimize +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) + halflength = int(length / 2) factor = 2.0 * np.pi / length omega = np.zeros(length, dtype=np.float) @@ -29,6 +31,7 @@ def gen_omega(length): return omega + def subsample_align(sig, ref_sig, plot=False): """Do subsample alignment for sig relative to the reference signal ref_sig. The delay between the two must be less than sample @@ -38,7 +41,7 @@ def subsample_align(sig, ref_sig, plot=False): n = len(sig) if (n % 2) == 1: raise ValueError("Needs an even length signal.") - halflen = int(n/2) + halflen = int(n / 2) fft_sig = np.fft.fft(sig) @@ -63,7 +66,8 @@ def subsample_align(sig, ref_sig, plot=False): 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}) + 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 @@ -85,10 +89,9 @@ def subsample_align(sig, ref_sig, plot=False): 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) + # print("Could not optimize: " + optim_result.message) return np.zeros(0, dtype=np.complex64) - # The MIT License (MIT) # # Copyright (c) 2017 Andreas Steger diff --git a/dpd/src/test_dab_Util.py b/dpd/src/test_dab_Util.py deleted file mode 100644 index 86ee2d8..0000000 --- a/dpd/src/test_dab_Util.py +++ /dev/null @@ -1,92 +0,0 @@ -# -*- coding: utf-8 -*- -# -# Test code for DAB util -# -# http://www.opendigitalradio.org -# Licence: The MIT License, see notice at the end of this file - -from unittest import TestCase - -import numpy as np -import pandas as pd -import src.Dab_Util as DU - -class TestDab_Util(TestCase): - - def test_subsample_align(self, sample_orig=r'../test_data/orig_rough_aligned.dat', - sample_rec =r'../test_data/recored_rough_aligned.dat', - length = 10240, max_size = 1000000): - du = DU - res1 = [] - res2 = [] - for i in 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)) - - error_rate = np.mean(np.array(res2) != 0) - self.assertEqual(error_rate, 0.0, "The error rate for aligning was %.2f%%" - % error_rate * 100) - -#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()) -# -# -#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() - - -# 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. diff --git a/dpd/src/test_measure.py b/dpd/src/test_measure.py deleted file mode 100644 index ee3cfdb..0000000 --- a/dpd/src/test_measure.py +++ /dev/null @@ -1,62 +0,0 @@ -# -*- coding: utf-8 -*- -# -# DPD Calculation Engine, test case for measure -# -# http://www.opendigitalradio.org -# Licence: The MIT License, see notice at the end of this file -from unittest import TestCase -from Measure import Measure -import socket - - -class TestMeasure(TestCase): - - def _open_socks(self): - sock_server = socket.socket(socket.AF_INET, socket.SOCK_STREAM) - sock_server.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) - sock_server.bind(('localhost', 1234)) - sock_server.listen(1) - - sock_client = socket.socket(socket.AF_INET, socket.SOCK_STREAM) - sock_client.connect(('localhost', 1234)) - - conn_server, addr_server = sock_server.accept() - return conn_server, sock_client - - def test__recv_exact(self): - m = Measure(1234, 1) - payload = b"test payload" - - conn_server, sock_client = self._open_socks() - conn_server.send(payload) - rec = m._recv_exact(sock_client, len(payload)) - - self.assertEqual(rec, payload, - "Did not receive the same message as sended. (%s, %s)" % - (rec, payload)) - - def test_get_samples(self): - self.fail() - - -# 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. -- cgit v1.2.3