From 38f171903a897d4b77b8d54d9cac772ccb8791c2 Mon Sep 17 00:00:00 2001
From: andreas128 <Andreas>
Date: Fri, 4 Aug 2017 21:58:31 +0100
Subject: Add main.py and basic functions to get measurement

---
 dpd/src/test_dab_Util.py | 62 ++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 62 insertions(+)
 create mode 100644 dpd/src/test_dab_Util.py

(limited to 'dpd/src/test_dab_Util.py')

diff --git a/dpd/src/test_dab_Util.py b/dpd/src/test_dab_Util.py
new file mode 100644
index 0000000..0b2fa4f
--- /dev/null
+++ b/dpd/src/test_dab_Util.py
@@ -0,0 +1,62 @@
+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.Dab_Util(8196000)
+        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()
-- 
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