From a4dd9c219947417e4925e789944c38eb41b4c0f6 Mon Sep 17 00:00:00 2001
From: David <david@rowetel.com>
Date: Sun, 5 Apr 2020 08:28:26 +0930
Subject: [PATCH] added arguments to plot-pulaw

---
 src/plot_pulaw.py | 28 +++++++++++++---------------
 1 file changed, 13 insertions(+), 15 deletions(-)

diff --git a/src/plot_pulaw.py b/src/plot_pulaw.py
index d71bf31..10d5656 100755
--- a/src/plot_pulaw.py
+++ b/src/plot_pulaw.py
@@ -1,15 +1,21 @@
 #!/usr/bin/python3
-# Utility to inspect packed ulaw samples before training from sw2packedulaw.c
+# Utility to inspect packed ulaw samples from sw2packedulaw.c (or dump_data.c) before training 
 
 import numpy as np
 import matplotlib.pyplot as plt
 import sys
 import ulaw
+import argparse
 
-data = np.fromfile(sys.argv[1], dtype='uint8')
-nb_samples = 8000
+parser = argparse.ArgumentParser(description='Plot LPCNet training packed ulaw samples')
+parser.add_argument('file1', help='pulaw file of packed ulaw samples')
+parser.add_argument('--file2', help='optional second packed ulaw file to compare')
+parser.add_argument('--nb_samples', type=int, default=-1, help='Optional number of samples to plot')
+args = parser.parse_args()
 
-#data = data[:nb_samples*20]
+data = np.fromfile(args.file1, dtype='uint8')
+nb_samples = args.nb_samples
+data = data[:nb_samples]
 
 sig = np.array(data[0::4], dtype='float')
 pred = np.array(data[1::4], dtype='float')
@@ -18,15 +24,6 @@ out_exc = np.array(data[3::4], dtype='float')
    
 print("exc var: %4.3e" % (np.var(ulaw.ulaw2lin(in_exc))))
 
-"""
-s_in = 32000*np.sin(np.arange(0,8000)*np.pi*2/100)
-s_out = ulaw.ulaw2lin(ulaw.lin2ulaw(s_in))
-plt.figure(1)
-plt.plot(s_in)
-plt.plot(s_out)
-plt.show(block=False)
-"""
-
 plt.figure(1)
 plt.subplot(211)
 plt.plot(ulaw.ulaw2lin(sig), label='sig')
@@ -41,8 +38,9 @@ plt.show(block=False)
 plt.figure(2)
 plt.subplot(211)
 plt.plot(ulaw.ulaw2lin(in_exc), label='in_exc')
-if len(sys.argv) == 3:
-    data2 = np.fromfile(sys.argv[2], dtype='uint8')
+if args.file2:
+    data2 = np.fromfile(args.file2, dtype='uint8')
+    data2 = data2[:nb_samples]
     in_exc2 = np.array(data2[2::4], dtype='float')
     plt.plot(ulaw.ulaw2lin(in_exc2), label='in_exc2')
 plt.ylim((-30000,30000))