aboutsummaryrefslogtreecommitdiffstats
path: root/dpd/src/test_dab_Util.py
diff options
context:
space:
mode:
Diffstat (limited to 'dpd/src/test_dab_Util.py')
-rw-r--r--dpd/src/test_dab_Util.py62
1 files changed, 62 insertions, 0 deletions
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()