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Diffstat (limited to 'dpd/src/test_dab_Util.py')
| -rw-r--r-- | dpd/src/test_dab_Util.py | 92 |
1 files changed, 92 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..ec15586 --- /dev/null +++ b/dpd/src/test_dab_Util.py @@ -0,0 +1,92 @@ +# -*- coding: utf-8 -*- +# +# Test code for DAB util +# +# http://www.opendigitalradio.org +# Licence: The MIT License, see notice at the end of this file + +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() + + +# The MIT License (MIT) +# +# Copyright (c) 2017 Andreas Steger +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in all +# copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +# SOFTWARE. |