Merge branch 'next' into outputRefactoring

17 files changed, 92 insertions, 110 deletions

diff --git a/dpd/src/Adapt.py b/dpd/src/Adapt.py
index 7e19a2c..329ee20 100644
--- a/dpd/src/Adapt.py
+++ b/dpd/src/Adapt.py
@@ -16,8 +16,6 @@ import os
 import datetime
 import pickle
 
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 LUT_LEN = 32
 FORMAT_POLY = 1
 FORMAT_LUT = 2
@@ -44,6 +42,19 @@ def _write_lut_file(scalefactor, lut, path):
         f.write("{}\n{}\n".format(coef.real, coef.imag))
     f.close()
 
+def dpddata_to_str(dpddata):
+    if dpddata[0] == "poly":
+        coefs_am = dpddata[1]
+        coefs_pm = dpddata[2]
+        return "dpd_coefs_am {}, dpd_coefs_pm {}".format(
+                coefs_am, coefs_pm)
+    elif dpddata[0] == "lut":
+        scalefactor = dpddata[1]
+        lut = dpddata[2]
+        return "LUT scalefactor {}, LUT {}".format(
+                scalefactor, lut)
+    else:
+        raise ValueError("Unknown dpddata type {}".format(dpddata[0]))
 
 class Adapt:
     """Uses the ZMQ remote control to change parameters of the DabMod
@@ -55,8 +66,9 @@ class Adapt:
         ZMQ remote control.
     """
 
-    def __init__(self, port, coef_path):
+    def __init__(self, config, port, coef_path):
         logging.debug("Instantiate Adapt object")
+        self.c = config
         self.port = port
         self.coef_path = coef_path
         self.host = "localhost"
@@ -226,27 +238,30 @@ class Adapt:
         """Backup current settings to a file"""
         dt = datetime.datetime.now().isoformat()
         if path is None:
-            path = logging_path + "/" + dt + "_adapt.pkl"
+            if self.c.plot_location is not None:
+                path = self.c.plot_location + "/" + dt + "_adapt.pkl"
+            else:
+                raise Exception("Cannot dump Adapt without either plot_location or path set")
         d = {
             "txgain": self.get_txgain(),
             "rxgain": self.get_rxgain(),
             "digital_gain": self.get_digital_gain(),
             "predistorter": self.get_predistorter()
         }
-        with open(path, "w") as f:
+        with open(path, "wb") as f:
             pickle.dump(d, f)
 
         return path
 
     def load(self, path):
         """Restore settings from a file"""
-        with open(path, "r") as f:
+        with open(path, "rb") as f:
             d = pickle.load(f)
 
-        self.set_txgain(d["txgain"])
-        self.set_digital_gain(d["digital_gain"])
-        self.set_rxgain(d["rxgain"])
-        self.set_predistorter(d["predistorter"])
+            self.set_txgain(d["txgain"])
+            self.set_digital_gain(d["digital_gain"])
+            self.set_rxgain(d["rxgain"])
+            self.set_predistorter(d["predistorter"])
 
 # The MIT License (MIT)
 #
diff --git a/dpd/src/Dab_Util.py b/dpd/src/Dab_Util.py
index 2021f38..bc89a39 100644
--- a/dpd/src/Dab_Util.py
+++ b/dpd/src/Dab_Util.py
@@ -8,9 +8,6 @@
 import datetime
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib
 
@@ -33,10 +30,11 @@ class Dab_Util:
      complex IQ samples of a DAB signal
      """
 
-    def __init__(self, sample_rate, plot=False):
+    def __init__(self, config, sample_rate, plot=False):
         """
         :param sample_rate: sample rate [sample/sec] to use for calculations
         """
+        self.c = config
         self.sample_rate = sample_rate
         self.dab_bandwidth = 1536000  # Bandwidth of a dab signal
         self.frame_ms = 96  # Duration of a Dab frame
@@ -53,9 +51,9 @@ class Dab_Util:
         off = sig_rec.shape[0]
         c = np.abs(signal.correlate(sig_orig, sig_rec))
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            corr_path = (logging_path + "/" + dt + "_tx_rx_corr.svg")
+            corr_path = self.c.plot_location + "/" + dt + "_tx_rx_corr.png"
             plt.plot(c, label="corr")
             plt.legend()
             plt.savefig(corr_path)
@@ -107,9 +105,9 @@ class Dab_Util:
         Returns an aligned version of sig_tx and sig_rx by cropping and subsample alignment
         """
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_sync_raw.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_sync_raw.png"
 
             fig, axs = plt.subplots(2)
             axs[0].plot(np.abs(sig_tx[:128]), label="TX Frame")
@@ -151,9 +149,9 @@ class Dab_Util:
             sig_tx = sig_tx[:-1]
             sig_rx = sig_rx[:-1]
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_sync_sample_aligned.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_sync_sample_aligned.png"
 
             fig, axs = plt.subplots(2)
             axs[0].plot(np.abs(sig_tx[:128]), label="TX Frame")
@@ -175,9 +173,9 @@ class Dab_Util:
 
         sig_rx = sa.subsample_align(sig_rx, sig_tx)
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_sync_subsample_aligned.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_sync_subsample_aligned.png"
 
             fig, axs = plt.subplots(2)
             axs[0].plot(np.abs(sig_tx[:128]), label="TX Frame")
@@ -199,9 +197,9 @@ class Dab_Util:
 
         sig_rx = pa.phase_align(sig_rx, sig_tx)
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_sync_phase_aligned.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_sync_phase_aligned.png"
 
             fig, axs = plt.subplots(2)
             axs[0].plot(np.abs(sig_tx[:128]), label="TX Frame")
diff --git a/dpd/src/ExtractStatistic.py b/dpd/src/ExtractStatistic.py
index d27cd77..639513a 100644
--- a/dpd/src/ExtractStatistic.py
+++ b/dpd/src/ExtractStatistic.py
@@ -8,13 +8,10 @@
 
 import numpy as np
 import matplotlib.pyplot as plt
-
 import datetime
 import os
 import logging
 
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 
 def _check_input_extract(tx_dpd, rx_received):
     # Check data type
@@ -64,10 +61,9 @@ class ExtractStatistic:
         self.plot = c.ES_plot
 
     def _plot_and_log(self, tx_values, rx_values, phase_diffs_values, phase_diffs_values_lists):
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
-
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_ExtractStatistic.png"
+            fig_path = self.c.plot_location + "/" + dt + "_ExtractStatistic.png"
             sub_rows = 3
             sub_cols = 1
             fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6))
diff --git a/dpd/src/Const.py b/dpd/src/GlobalConfig.py
index 6c9bafa..b84b9d7 100644
--- a/dpd/src/Const.py
+++ b/dpd/src/GlobalConfig.py
@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 #
-# DPD Computation Engine, constants.
+# DPD Computation Engine, constants and global configuration
 #
 # Source for DAB standard: etsi_EN_300_401_v010401p p145
 #
@@ -9,19 +9,20 @@
 
 import numpy as np
 
+class GlobalConfig:
+    def __init__(self, cli_args, plot_location):
+        self.sample_rate = cli_args.samplerate
+        assert self.sample_rate == 8192000  # By now only constants for 8192000
 
-class Const:
-    def __init__(self, sample_rate, target_median, plot):
-        assert sample_rate == 8192000  # By now only constants for 8192000
-        self.sample_rate = sample_rate
+        self.plot_location = plot_location
 
         # DAB frame
         # Time domain
-        self.T_F = sample_rate / 2048000 * 196608  # Transmission frame duration
-        self.T_NULL = sample_rate / 2048000 * 2656  # Null symbol duration
-        self.T_S = sample_rate / 2048000 * 2552  # Duration of OFDM symbols of indices l = 1, 2, 3,... L;
-        self.T_U = sample_rate / 2048000 * 2048  # Inverse of carrier spacing
-        self.T_C = sample_rate / 2048000 * 504  # Duration of cyclic prefix
+        self.T_F = self.sample_rate / 2048000 * 196608  # Transmission frame duration
+        self.T_NULL = self.sample_rate / 2048000 * 2656  # Null symbol duration
+        self.T_S = self.sample_rate / 2048000 * 2552  # Duration of OFDM symbols of indices l = 1, 2, 3,... L;
+        self.T_U = self.sample_rate / 2048000 * 2048  # Inverse of carrier spacing
+        self.T_C = self.sample_rate / 2048000 * 504  # Duration of cyclic prefix
 
         # Frequency Domain
         # example: np.delete(fft[3328:4865], 768)
@@ -34,10 +35,10 @@ class Const:
         # time per sample = 1 / sample_rate
         # frequency per bin = 1kHz
         # phase difference per sample offset = delta_t * 2 * pi * delta_freq
-        self.phase_offset_per_sample = 1. / sample_rate * 2 * np.pi * 1000
+        self.phase_offset_per_sample = 1. / self.sample_rate * 2 * np.pi * 1000
 
         # Constants for ExtractStatistic
-        self.ES_plot = plot
+        self.ES_plot = cli_args.plot
         self.ES_start = 0.0
         self.ES_end = 1.0
         self.ES_n_bins = 64  # Number of bins between ES_start and ES_end
@@ -45,7 +46,7 @@ class Const:
 
         # Constants for Measure_Shoulder
         self.MS_enable = False
-        self.MS_plot = plot
+        self.MS_plot = cli_args.plot
 
         meas_offset = 976  # Offset from center frequency to measure shoulder [kHz]
         meas_width = 100  # Size of frequency delta to measure shoulder [kHz]
@@ -63,24 +64,24 @@ class Const:
         self.MS_n_proc = 4
 
         # Constants for MER
-        self.MER_plot = plot
+        self.MER_plot = cli_args.plot
 
         # Constants for Model
-        self.MDL_plot = True or plot  # Override default
+        self.MDL_plot = cli_args.plot
 
         # Constants for Model_PM
         # Set all phase offsets to zero for TX amplitude < MPM_tx_min
         self.MPM_tx_min = 0.1
 
         # Constants for TX_Agc
-        self.TAGC_max_txgain = 89  # USRP specific
-        self.TAGC_tx_median_target = target_median
+        self.TAGC_max_txgain = 89  # USRP B200 specific
+        self.TAGC_tx_median_target = cli_args.target_median
         self.TAGC_tx_median_max = self.TAGC_tx_median_target * 1.4
         self.TAGC_tx_median_min = self.TAGC_tx_median_target / 1.4
 
         # Constants for RX_AGC
-        self.RAGC_min_rxgain = 25  # USRP specific
-        self.RAGC_rx_median_target = self.TAGC_tx_median_target
+        self.RAGC_min_rxgain = 25  # USRP B200 specific
+        self.RAGC_rx_median_target = cli_args.target_median
 
 # The MIT License (MIT)
 #
diff --git a/dpd/src/MER.py b/dpd/src/MER.py
index f186261..693058d 100644
--- a/dpd/src/MER.py
+++ b/dpd/src/MER.py
@@ -8,11 +8,6 @@
 import datetime
 import os
 import logging
-try:
-    logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-except:
-    logging_path = "/tmp/"
-
 import numpy as np
 import matplotlib
 matplotlib.use('agg')
@@ -76,9 +71,11 @@ class MER:
 
         spectrum = self._calc_spectrum(tx)
 
-        if self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_MER" + debug_name + ".svg"
+            fig_path = self.c.plot_location + "/" + dt + "_MER" + debug_name + ".png"
+        else:
+            fig_path = None
 
         MERs = []
         for i, (x, y) in enumerate(self._split_in_carrier(
@@ -103,7 +100,7 @@ class MER:
                 ylim = ax.get_ylim()
                 ax.set_ylim(ylim[0] - (ylim[1] - ylim[0]) * 0.1, ylim[1])
 
-        if self.plot:
+        if fig_path is not None:
             plt.tight_layout()
             plt.savefig(fig_path)
             plt.show()
diff --git a/dpd/src/Measure.py b/dpd/src/Measure.py
index d4b1d9e..b7423c6 100644
--- a/dpd/src/Measure.py
+++ b/dpd/src/Measure.py
@@ -11,14 +11,13 @@ import struct
 import numpy as np
 import src.Dab_Util as DU
 import os
-
 import logging
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
 
 class Measure:
     """Collect Measurement from DabMod"""
-    def __init__(self, samplerate, port, num_samples_to_request):
+    def __init__(self, config, samplerate, port, num_samples_to_request):
         logging.info("Instantiate Measure object")
+        self.c = config
         self.samplerate = samplerate
         self.sizeof_sample = 8 # complex floats
         self.port = port
@@ -106,7 +105,7 @@ class Measure:
         rx_median = np.median(np.abs(rxframe))
         rxframe = rxframe / rx_median * np.median(np.abs(txframe))
 
-        du = DU.Dab_Util(self.samplerate)
+        du = DU.Dab_Util(self.c, self.samplerate)
         txframe_aligned, rxframe_aligned = du.subsample_align(txframe, rxframe)
 
         logging.info(
diff --git a/dpd/src/Measure_Shoulders.py b/dpd/src/Measure_Shoulders.py
index c733dfd..fd90050 100644
--- a/dpd/src/Measure_Shoulders.py
+++ b/dpd/src/Measure_Shoulders.py
@@ -9,9 +9,6 @@ import datetime
 import os
 import logging
 import multiprocessing
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -79,8 +76,11 @@ class Measure_Shoulders:
         self.plot = c.MS_plot
 
     def _plot(self, signal):
+        if self.c.plot_location is None:
+            return
+
         dt = datetime.datetime.now().isoformat()
-        fig_path = logging_path + "/" + dt + "_sync_subsample_aligned.svg"
+        fig_path = self.c.plot_location + "/" + dt + "_sync_subsample_aligned.png"
 
         fft = calc_fft_db(signal, 100, self.c)
         peak, idxs_peak = _calc_peak(fft, self.c)
diff --git a/dpd/src/Model.py b/dpd/src/Model.py
index 67feeb6..b2c303f 100644
--- a/dpd/src/Model.py
+++ b/dpd/src/Model.py
@@ -2,6 +2,12 @@
 from src.Model_Poly import Poly
 from src.Model_Lut import Lut
 
+def select_model_from_dpddata(dpddata):
+    if dpddata[0] == 'lut':
+        return Lut
+    elif dpddata[0] == 'poly':
+        return Poly
+
 # The MIT License (MIT)
 #
 # Copyright (c) 2017 Andreas Steger
diff --git a/dpd/src/Model_AM.py b/dpd/src/Model_AM.py
index d7e880c..9800d83 100644
--- a/dpd/src/Model_AM.py
+++ b/dpd/src/Model_AM.py
@@ -8,9 +8,6 @@
 import datetime
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -55,12 +52,12 @@ class Model_AM:
         self.plot = plot
 
     def _plot(self, tx_dpd, rx_received, coefs_am, coefs_am_new):
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             tx_range, rx_est = calc_line(coefs_am, 0, 0.6)
             tx_range_new, rx_est_new = calc_line(coefs_am_new, 0, 0.6)
 
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_Model_AM.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_Model_AM.png"
             sub_rows = 1
             sub_cols = 1
             fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6))
diff --git a/dpd/src/Model_Lut.py b/dpd/src/Model_Lut.py
index 6d4db52..e70fdb0 100644
--- a/dpd/src/Model_Lut.py
+++ b/dpd/src/Model_Lut.py
@@ -7,12 +7,8 @@
 
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 
-
 class Lut:
     """Implements a model that calculates lookup table coefficients"""
 
diff --git a/dpd/src/Model_PM.py b/dpd/src/Model_PM.py
index d4f8c00..3aafea0 100644
--- a/dpd/src/Model_PM.py
+++ b/dpd/src/Model_PM.py
@@ -8,9 +8,6 @@
 import datetime
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -41,12 +38,12 @@ class Model_PM:
         self.plot = plot
 
     def _plot(self, tx_dpd, phase_diff, coefs_pm, coefs_pm_new):
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             tx_range, phase_diff_est = self.calc_line(coefs_pm, 0, 0.6)
             tx_range_new, phase_diff_est_new = self.calc_line(coefs_pm_new, 0, 0.6)
 
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_Model_PM.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_Model_PM.png"
             sub_rows = 1
             sub_cols = 1
             fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6))
diff --git a/dpd/src/Model_Poly.py b/dpd/src/Model_Poly.py
index ff15941..cdfd319 100644
--- a/dpd/src/Model_Poly.py
+++ b/dpd/src/Model_Poly.py
@@ -7,9 +7,6 @@
 
 import os
 import logging
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 
 import src.Model_AM as Model_AM
@@ -54,13 +51,10 @@ class Poly:
         self.model_am = Model_AM.Model_AM(c, plot=self.plot)
         self.model_pm = Model_PM.Model_PM(c, plot=self.plot)
 
-        self.plot = c.MDL_plot
-
     def reset_coefs(self):
         self.coefs_am = np.zeros(5, dtype=np.float32)
         self.coefs_am[0] = 1
         self.coefs_pm = np.zeros(5, dtype=np.float32)
-        return self.coefs_am, self.coefs_pm
 
     def train(self, tx_abs, rx_abs, phase_diff, lr=None):
         """
diff --git a/dpd/src/RX_Agc.py b/dpd/src/RX_Agc.py
index 670fbbb..f778dee 100644
--- a/dpd/src/RX_Agc.py
+++ b/dpd/src/RX_Agc.py
@@ -9,8 +9,6 @@ import datetime
 import os
 import logging
 import time
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib
 matplotlib.use('agg')
@@ -70,11 +68,14 @@ class Agc:
     def plot_estimates(self):
         """Plots the estimate of for Max, Median, Mean for different
         number of samples."""
+        if self.c.plot_location is None:
+            return
+
         self.adapt.set_rxgain(self.min_rxgain)
         time.sleep(1)
 
         dt = datetime.datetime.now().isoformat()
-        fig_path = logging_path + "/" + dt + "_agc.svg"
+        fig_path = self.c.plot_location + "/" + dt + "_agc.png"
         fig, axs = plt.subplots(2, 2, figsize=(3*6,1*6))
         axs = axs.ravel()
 
diff --git a/dpd/src/Symbol_align.py b/dpd/src/Symbol_align.py
index d921f25..2a17a65 100644
--- a/dpd/src/Symbol_align.py
+++ b/dpd/src/Symbol_align.py
@@ -8,12 +8,6 @@
 import datetime
 import os
 import logging
-
-try:
-    logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-except:
-    logging_path = "/tmp/"
-
 import numpy as np
 import scipy
 import matplotlib
@@ -75,9 +69,9 @@ class Symbol_align:
 
         offset = peaks[np.argmin([tx_product_avg[peak] for peak in peaks])]
 
-        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:
+        if self.plot and self.c.plot_location is not None:
             dt = datetime.datetime.now().isoformat()
-            fig_path = logging_path + "/" + dt + "_Symbol_align.svg"
+            fig_path = self.c.plot_location + "/" + dt + "_Symbol_align.png"
 
             fig = plt.figure(figsize=(9, 9))
 
diff --git a/dpd/src/TX_Agc.py b/dpd/src/TX_Agc.py
index 3c804fa..309193d 100644
--- a/dpd/src/TX_Agc.py
+++ b/dpd/src/TX_Agc.py
@@ -9,9 +9,6 @@ import datetime
 import os
 import logging
 import time
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib
 
diff --git a/dpd/src/phase_align.py b/dpd/src/phase_align.py
index 68c216d..8654333 100644
--- a/dpd/src/phase_align.py
+++ b/dpd/src/phase_align.py
@@ -7,8 +7,6 @@
 import datetime
 import os
 import logging
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -24,9 +22,9 @@ def phase_align(sig, ref_sig, plot=False):
     real_diffs = np.cos(angle_diff)
     imag_diffs = np.sin(angle_diff)
 
-    if logging.getLogger().getEffectiveLevel() == logging.DEBUG and plot:
+    if plot and self.c.plot_location is not None:
         dt = datetime.datetime.now().isoformat()
-        fig_path = logging_path + "/" + dt + "_phase_align.svg"
+        fig_path = self.c.plot_location + "/" + dt + "_phase_align.png"
 
         plt.subplot(511)
         plt.hist(angle_diff, bins=60, label="Angle Diff")
diff --git a/dpd/src/subsample_align.py b/dpd/src/subsample_align.py
index 68f3591..20ae56b 100755
--- a/dpd/src/subsample_align.py
+++ b/dpd/src/subsample_align.py
@@ -7,14 +7,10 @@
 import datetime
 import logging
 import os
-
-logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
-
 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.")
@@ -32,7 +28,7 @@ def gen_omega(length):
     return omega
 
 
-def subsample_align(sig, ref_sig, plot=False):
+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
 
@@ -72,13 +68,13 @@ def subsample_align(sig, ref_sig, plot=False):
     if optim_result.success:
         best_tau = optim_result.x
 
-        if plot:
+        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 = (logging_path + "/" + dt + "_tau.svg")
+            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)