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e633a788ad
* rename signalFunctions -> signal_functions * basic methods for auto interpretation * cythonize k means * reorder tests * remove check and update gitignore * estimate tolerance and implement score for choosing modulation type * use absdiff * remove comment * cythonize messsage segmentation * improve message segementation and add test for xavax * integrate OOK special case * add check if psk is possible * integrate xavax and improve score * improve noise detection * add test for noise detection multiple messages * improve noise detection * homematic fix: use percetange of signal length instead of num flanks * homematic has some trash at start of messages, which counts as flanks * additonally set score to 0 if found only one bit length lower 5 * calculate minimum bit length from tolerance * improve noise noise detection * refactor limit and propose new limit calculation * improve minimum bit length penalty * only increase score for mod_type if bit length surpasses a minimum * this way scoring loop later becomes easier and * score is more accurate as there is no division needed which does not scale well with the length of message vectors * remove demodulated complex files and demod live in tests * remove enocean.coco * add a new check to prevent PSK misclassification * add tolerance unit test * use z=2 for finding outlier free max in tolerance estimation * prevent numpy warnings * adapt threshold of unit test * normalize the score by dividing by plateau vector length * improve OOK segmentation: Use minimum pulse length instead pause length for reference * use 50 percentile for detecting n_digits in plateau rounding * add elektromaten integration test * improve center detection to deal with varying signal power levels * use 10% clustering for rect signal * calculate min and max of each cluster * return max(minima) + min(maxima) / 2 * improve the center aggregation, separate between modulation types * add validity checks if message can be ASK or FSK modulated * use a weighted mean for center estimation: 60/40 for high/low * improve bit length estimation: use decimal deviation for filtering * add scislo test * improve tolerance estimation: use 50 percentile + revert to normal mean for bitlength estimation * add haar wavelet transform * add median filter * rename to Wavelet * add signal generation with configurable snr for lab test * add method for testdata generation * prepare fsk test: generate messages and estimate parameters * improve performance of plateau length filtering * remove unused import * improve robustness * improve robustness * add fsk error plot * only append bit length if it surpasses minimum * fix plot title * improve noise level detection, prevent it from being too low * integrate all modulations to test * increase pause threshold for ook * improve tolerance estimation * improve noise detection: take maximum of all maxima of noise clusters * improve scoring algorithm to prevent PSK misclassify as FSK * use histogram based approach for center detection * modulation detection with wavelets * fix median filter when at end of data * integrate modulation detection with wavelets * improve robustness * improve psk parameters * improve psk threshold * improve robustness * swap psk angles for easier demod * better xticks * add message segmentation test and fix noise generation snr * add error print * update audi test * fix runtime warning * improve accuracy of center detection * avoid warning * remove unused functions * fine tune fsk fft threshold * update esaver test * improve fsk fft threshold * change test order * update enocean test signal * update enocean test signal * enhance bit length estimation: use a threshold divisor histogram * improve noise estimation: round to fourth digit * update enocean signal * consider special case if message pause is 0 * remove unused * improve noise detection * improve center detection * improve center detection * prevent warning * refactor * cythonize get_plateau_lengths * improve syntax * use c++ sort * optimize PSK threshold * optimize coverage * fix buffer types * integrate new auto detection routine * update test * remove unused stuff * fix tests * backward compat * backward compat * update test * add threshold for large signals for performance * update changelog * make algorithm more robust against short bit length outliers * make multi button for selecting auto detect options * update unittest
79 lines
5.3 KiB
Python
79 lines
5.3 KiB
Python
import unittest
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import numpy as np
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from tests.test_util import get_path_for_data_file
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from urh.ainterpretation.AutoInterpretation import segment_messages_from_magnitudes, merge_message_segments_for_ook
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from urh.signalprocessing.Modulator import Modulator
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from urh.signalprocessing.Signal import Signal
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class TestMessageSegmentation(unittest.TestCase):
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def test_segmentation_for_fsk(self):
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signal = np.fromfile(get_path_for_data_file("fsk.complex"), dtype=np.complex64)
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segments = segment_messages_from_magnitudes(np.abs(signal), 0.0009)
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self.assertEqual(len(segments), 1)
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self.assertEqual(segments[0], (0, 17742))
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def test_segmentation_for_ask(self):
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signal = np.fromfile(get_path_for_data_file("ask.complex"), dtype=np.complex64)
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segments = segment_messages_from_magnitudes(np.abs(signal), 0.02)
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segments = merge_message_segments_for_ook(segments)
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self.assertEqual(len(segments), 1)
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self.assertEqual(segments[0], (462, 12011))
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def test_segmentation_enocean_multiple_messages(self):
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signal = np.fromfile(get_path_for_data_file("enocean.complex"), dtype=np.complex64)
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segments = segment_messages_from_magnitudes(np.abs(signal), 0.0448)
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segments = merge_message_segments_for_ook(segments)
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self.assertEqual(len(segments), 3)
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self.assertEqual(segments[0], (2107, 5432))
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self.assertEqual(segments[1], (20428, 23758))
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self.assertEqual(segments[2], (44216, 47546))
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def test_message_segmentation_fsk_xavax(self):
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signal = Signal(get_path_for_data_file("xavax.coco"), "")
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segments = segment_messages_from_magnitudes(np.abs(signal.data), noise_threshold=0.002)
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# Signal starts with overdrive, so one message more
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self.assertTrue(len(segments) == 6 or len(segments) == 7)
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if len(segments) == 7:
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segments = segments[1:]
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self.assertEqual(segments,
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[(275146, 293697), (321073, 338819), (618213, 1631898), (1657890, 1678041), (1803145, 1820892),
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(1846213, 1866364)])
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def test_segmentation_ask_50(self):
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modulator = Modulator("ask50")
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modulator.modulation_type_str = "ASK"
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modulator.param_for_zero = 50
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modulator.param_for_one = 100
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modulator.samples_per_bit = 100
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msg1 = modulator.modulate("1010101111", pause=10000)
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msg2 = modulator.modulate("1010101110010101", pause=20000)
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msg3 = modulator.modulate("1010101010101111", pause=30000)
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data = np.concatenate((msg1, msg2, msg3))
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segments = segment_messages_from_magnitudes(np.abs(data), noise_threshold=0)
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print(segments)
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self.assertEqual(len(segments), 3)
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self.assertEqual(segments, [(0, 999), (10999, 12599), (32599, 34199)])
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print(merge_message_segments_for_ook(segments))
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def test_segmentation_elektromaten(self):
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signal = Signal(get_path_for_data_file("elektromaten.coco"), "")
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segments = segment_messages_from_magnitudes(np.abs(signal.data), noise_threshold=0.0167)
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segments = merge_message_segments_for_ook(segments)
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self.assertEqual(len(segments), 11)
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def test_ook_merge(self):
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input = [(26728, 27207), (28716, 29216), (30712, 32190), (32695, 34178), (34686, 35181), (36683, 38181), (38670, 39165), (40668, 42154), (42659, 44151), (44642, 46139), (46634, 47121), (47134, 47145), (48632, 50129), (50617, 51105), (52612, 54089), (54100, 54113), (54601, 56095), (56592, 58075), (58581, 59066), (59076, 59091), (60579, 61081), (62567, 64063), (64559, 66053), (66548, 67035), (68539, 69031), (70533, 71035), (72527, 73008), (73019, 73035), (74522, 75006), (90465, 90958), (92456, 92944), (94455, 95935), (96441, 97930), (98437, 98937), (100430, 101914), (102414, 102901), (104413, 105889), (106398, 107895), (108389, 109873), (110385, 110877), (112374, 113853), (114367, 114862), (116355, 117842), (118344, 119826), (120340, 121824), (122324, 122825), (124323, 124821), (126316, 127807), (128300, 129782), (130293, 130777), (132280, 132774), (134275, 134773), (136266, 136767), (138265, 138751), (154205, 154694), (156206, 156703), (158191, 159685), (160189, 161683), (162176, 162667), (164164, 165657), (166159, 166648), (168147, 169631), (170145, 171621), (172131, 173611), (174125, 174607), (176118, 177600), (178105, 178590), (180093, 181574), (181585, 181599), (182090, 183573), (184074, 185565), (186070, 186553), (188061, 188555), (190052, 191533), (192043, 193523), (194034, 194518), (196021, 196510), (198012, 198503), (200014, 200496), (202003, 202485), (202498, 202511), (217953, 218430), (218442, 218457), (219940, 220426), (221935, 223431), (223926, 225409), (225912, 226399), (227912, 229387), (229896, 230382), (231886, 233369), (233383, 233393), (233882, 235375), (235874, 237357), (237858, 238361), (239850, 241343), (241844, 242328), (243840, 245331), (245828, 247306), (247820, 249296), (249811, 250298), (251803, 252283), (252296, 252309), (253790, 255271), (255778, 257276), (257774, 258258), (259764, 260257), (261760, 262239), (263744, 264241), (265744, 266225), (281684, 282171), (283676, 284163), (285668, 287153), (287665, 289149), (289654, 290145), (291642, 293131), (293633, 294120), (295629, 297104), (297116, 297129)]
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merged = merge_message_segments_for_ook(input)
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self.assertEqual(len(merged), 5)
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