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1.96 kB
| from __future__ import print_function | |
| import unittest | |
| import numpy as np | |
| import os | |
| from medleydb import MultiTrack | |
| from medleydb.annotate import activation_conf as A | |
| def array_almost_equal(array1, array2, tolerance=1e-7): | |
| diff = np.abs(array1 - array2) | |
| num_not_equal = diff > tolerance | |
| print("number of unequal elements: %s" % np.sum(num_not_equal)) | |
| return np.sum(num_not_equal) == 0 | |
| class TestComputeActivationConfidence(unittest.TestCase): | |
| def test_defaults(self): | |
| mtrack = MultiTrack('LizNelson_Rainfall') | |
| C, actual_index = A.compute_activation_confidence(mtrack) | |
| actual_shape = C.shape | |
| expected_shape = (6135, 6) | |
| self.assertEqual(expected_shape, actual_shape) | |
| expected_index = [1, 2, 3, 4, 5] | |
| self.assertEqual(expected_index, actual_index) | |
| class TestTrackEnergy(unittest.TestCase): | |
| def test_compute_energy(self): | |
| wave = np.ones((20, )) | |
| win_len = 10 | |
| win = np.ones((10, )) | |
| actual = A.track_energy(wave, win_len, win) | |
| expected = np.array([0.5, 1., 1., 1., 0.5]) | |
| self.assertTrue(np.allclose(expected, actual)) | |
| class TestHwr(unittest.TestCase): | |
| def test_neg_pos(self): | |
| x = np.array([-0.5, 0, 0.5]) | |
| expected = np.array([0, 0, 0.5]) | |
| actual = A.hwr(x) | |
| def test_pos(self): | |
| x = np.array([7, 0, 0.5]) | |
| expected = np.array([7, 0, 0.5]) | |
| actual = A.hwr(x) | |
| class TestWriteActivationsToCsv(unittest.TestCase): | |
| def test_default(self): | |
| activations = np.array([ | |
| [0.0, 1.0, 1.0, 0.4], | |
| [0.5, 0.9, 0.9, 0.7], | |
| [1.0, 0.8, 0.8, 0.8] | |
| ]) | |
| mtrack = MultiTrack('Phoenix_ScotchMorris') | |
| stem_idx_list = [1, 2, 3] | |
| A.write_activations_to_csv(mtrack, activations, stem_idx_list) | |
| self.assertTrue(os.path.exists(mtrack.activation_conf_fpath)) | |
| os.remove(mtrack.activation_conf_fpath) | |