def test_get_window_samples_pre_consecutive(make_data):
num_features = 7
data = make_data(25, num_features, reverse=True)
sample_size = 4
num_consecutive = 2
samples, dropped = get_window_samples(data, sample_size, num_consecutive, (-23, -3))
assert dropped == 4
expected_shape = (sample_size, num_features)
expected_sample = np.arange(sample_size * num_features).reshape(expected_shape)
assert type(samples) is list
assert len(samples) == 2 * num_consecutive
for sample in samples:
assert type(sample) is np.ndarray
assert sample.shape == expected_shape
for i in range(len(samples)):
assert np.all(
samples[-1 - i]
== np.array(
[
[48, 47, 46, 45, 44, 43, 42],
[41, 40, 39, 38, 37, 36, 35],
[34, 33, 32, 31, 30, 29, 28],
[27, 26, 25, 24, 23, 22, 21],
]
)
+ i * samples[-1].size
)
def test_get_window_samples_short(num_readings, sample_size, window, make_data):
data = make_data(num_readings, 5)
samples, dropped = get_window_samples(data, sample_size, 1, window)
assert dropped == num_readings - min(abs(ix) for ix in window)
assert type(samples) is list
assert len(samples) == 0
def test_get_window_samples_pre_not_consecutive(make_data):
num_features = 5
data = make_data(10, num_features, reverse=True)
sample_size = 3
samples, dropped = get_window_samples(data, sample_size, 1, (-8, -1))
assert dropped == 1
expected_shape = (sample_size, num_features)
expected_sample = np.arange(sample_size * num_features).reshape(expected_shape)
assert type(samples) is list
assert len(samples) == 2
for sample in samples:
assert type(sample) is np.ndarray
assert sample.shape == expected_shape
assert np.all(
samples[1] == [[19, 18, 17, 16, 15], [14, 13, 12, 11, 10], [9, 8, 7, 6, 5],]
)
assert np.all(samples[0] == samples[1] + samples[1].size)
def test_get_window_samples_post_not_consecutive(make_data):
num_features = 5
data = make_data(10, num_features)
sample_size = 3
samples, dropped = get_window_samples(data, sample_size, 1, (0, 8))
assert dropped == 2
expected_shape = (sample_size, num_features)
expected_sample = np.arange(sample_size * num_features).reshape(expected_shape)
assert type(samples) is list
assert len(samples) == 2
for sample in samples:
assert type(sample) is np.ndarray
assert sample.shape == expected_shape
assert np.all(
samples[0] == [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [10, 11, 12, 13, 14],]
)
assert np.all(samples[1] == samples[0] + samples[0].size)