def test_parse_metadata(self):
with mock.patch("builtins.open", mock.mock_open()) as m:
with mock.patch("csv.reader") as mock_csv_reader:
args = _arg_parse().parse_args(
["-c", "mock_location.csv", "-u", "c"])
mock_csv_reader.return_value = [["filename", "b", "c"],
["f.wav", "v", "y"]]
d = parse_metadata(args, {"f.wav": 0})
m.assert_called_with("mock_location.csv", "r")
self.assertFalse("filename" in d,
"'filename' was not properly ignored")
self.assertTrue("b" in d)
self.assertTrue("__filterable" in d["b"],
"'__filterable' not in 'a'")
self.assertTrue(d["b"]["__filterable"],
"'__filterable' in 'b' is not True")
self.assertTrue("v" in d["b"], "'v' not in 'b'")
self.assertTrue("points" in d["b"]["v"],
"'points' not in 'b'.'v'")
self.assertEqual(d["b"]["v"]["points"], [0],
"Invalid point list for 'b'")
self.assertTrue("c" in d, "'c' not in dictionary")
self.assertTrue("__filterable" in d["c"],
"'__filterable' not in 'c'")
self.assertFalse(d["c"]["__filterable"],
"'__filterable' in 'c' is not False")
self.assertTrue("y" in d["c"], "'y' not in 'c'")
self.assertEqual(d["c"]["y"]["points"], [0],
"Invalid point list for 'c'")
self.assertTrue("points" in d["c"]["y"],
"'points' not in 'c'.'y'")
def test_pca_job(self):
args = _arg_parse().parse_args()
arr = numpy.asarray([[1, 2, 3], [3, 4, 5], [5, 6, 7]])
ret = pca(arr, 2, args)
self.assertEqual(ret[0][0].shape, (3, 2), "invalid shape")
self.assertEqual(ret[0][1], "pca")
self.assertEqual(len(ret), 1)
def test_t_sne_parallel(self):
args = _arg_parse().parse_args(["-p", "30", "50", "--parallel"])
arr = numpy.asarray([1, 2, 3])
res = t_sne(arr, 2, args)
rarr = numpy.asarray([3, 2, 1])
self.assertEqual(len(res), 2)
self.assertTrue(numpy.array_equal(res[0][0], rarr))
self.assertEqual(res[0][1], "mock")
self.assertTrue(numpy.array_equal(res[1][0], rarr))
self.assertEqual(res[1][1], "mock")
def test_t_sne_serial(self, mock_t_sne_job):
args = _arg_parse().parse_args(["-p", "30", "50"])
rarr = numpy.asarray([1, 2])
mock_t_sne_job.return_value = (rarr, "30")
arr = numpy.asarray([1, 2, 3])
res = t_sne(arr, 2, args)
self.assertEqual(len(res), 2)
self.assertEqual(mock_t_sne_job.call_count, 2)
self.assertEqual(res[0], (rarr, "30"))
self.assertEqual(res[1], (rarr, "30"))
def setUp(self):
self.ap = crunch._arg_parse()
self.def_ap = self.ap.parse_args(args=[])
self.val_ap = self.ap.parse_args(args=[
"-f", "samp/", "-p", "20", "50", "60", "-o", "pca.json", "-r",
"fing.npy", "-m", "-100", "-x", "100", "-t", "pca.png", "-c",
"samp/data.csv", "-d", "4000", "-u", "unfilterable", "-n",
"test_data_set", "-s", "sound_info.json", "-a", "1000", "-b",
"pronunciation", "-k", "pca", "-g", "fft", "-e", "input.npy",
"--td", "--colorby", "phoneme", "--parallel"
])
def test_pca_func_call(self, mock_sci_pca):
mock_func = mock.MagicMock()
args = _arg_parse().parse_args()
arr = numpy.asarray([1, 2, 3])
params = (4, 5)
res = pca(arr, 2, args, mock_func, params)
mock_sci_pca.assert_called_with(n_components=2, svd_solver='full')
self.assertEqual(mock_func.call_args[0][0][1], "pca")
self.assertEqual(mock_func.call_args[0][1], 4)
self.assertEqual(mock_func.call_args[0][2], 5)
self.assertEqual(res[0][1], "pca")
def test_load_numpy_fingerprint(self):
with mock.patch("numpy.load", mock.mock_open()) as mock_load:
args = _arg_parse().parse_args(
["-e", "mock.npy", "--format", "npy"])
mock_load.return_value = [("name_1", np.asarray([1, 2, 3])),
("name_2", np.asarray([4, 5, 6]))]
results, file_data = load_fingerprints(args)
mock_load.assert_called_with("mock.npy")
self.assertSequenceEqual(file_data, ["name_1", "name_2"])
self.assertEqual(len(results), 2)
assert_array_equal(results[0], [1, 2, 3])
assert_array_equal(results[1], [4, 5, 6])
def test_load_csv_fingerprint(self):
with mock.patch("builtins.open", mock.mock_open()) as m:
with mock.patch("csv.reader") as mock_csv_reader:
args = _arg_parse().parse_args(
["-e", "mock.csv", "--format", "csv"])
mock_csv_reader.return_value = [["name_1", "1", "2", "3"],
["name_2", "4", "5", "6"]]
results, file_data = load_fingerprints(args)
m.assert_called_with("mock.csv")
self.assertSequenceEqual(file_data, ["name_1", "name_2"])
self.assertEqual(len(results), 2)
assert_array_equal(results[0], [1, 2, 3])
assert_array_equal(results[1], [4, 5, 6])