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-rw-r--r--src/dab_util_test.py49
1 files changed, 49 insertions, 0 deletions
diff --git a/src/dab_util_test.py b/src/dab_util_test.py
index be36d53..3f9e941 100644
--- a/src/dab_util_test.py
+++ b/src/dab_util_test.py
@@ -1,5 +1,7 @@
from scipy import signal
import numpy as np
+import pandas as pd
+from tqdm import tqdm
import src.gen_source as gs
import src.dab_util as du
@@ -28,7 +30,54 @@ def test_phase_offset(lag_function, tol):
res.append(np.abs(off-off_meas)<tol)
return np.mean(res)
+
+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())
+
+def test_subsample_alignment(sample_orig=r'../data/orig_rough_aligned.dat',
+ sample_rec =r'../data/recored_rough_aligned.dat', length = 10240, max_size = 1000000):
+ res1 = []
+ res2 = []
+ for i in tqdm(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))
+
+ print("Before subsample alignment: lag_std = %.2f, lag_abs_mean = %.2f" % (np.std(res1), np.mean(np.abs(res1))))
+ print("After subsample alignment: lag_std = %.2f, lag_abs_mean = %.2f" % (np.std(res2), np.mean(np.abs(res2))))
+
+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()