Cleanup

15 files changed, 112 insertions, 379 deletions

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.