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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, 0 insertions, 92 deletions
diff --git a/dpd/src/test_dab_Util.py b/dpd/src/test_dab_Util.py deleted file mode 100644 index 86ee2d8..0000000 --- a/dpd/src/test_dab_Util.py +++ /dev/null @@ -1,92 +0,0 @@ -# -*- 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 - 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. |