def test_API_get_buffer(config):
test_name = test_API_get_buffer.__name__
expected = 5
buffer = get_buffer(config, key='validation')
actual = len(buffer.read_ids)
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
def test_loader_read_id_length(data_filepath):
test_name = test_loader_read_id_length.__name__
expected = len('002f0f2d-ffc1-4072-82d3-6ce425d9724e')
loader = DataLoader(data_filepath)
actual = len(loader.load_read_ids()[0])
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
def test_API_get_generator(config):
test_name = test_API_get_generator.__name__
expected = 10
generator = get_generator(config, key='validation')
batches = next(generator.get_batches(10))
actual = len(batches)
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
def test_loader_read_id_list_length(data_filepath):
test_name = test_loader_read_id_list_length.__name__
expected = 5
loader = DataLoader(data_filepath)
reads = loader.load_read_ids()
actual = len(reads)
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
def test_buffer_get_batched_read_x_shape(data_loader):
test_name = test_buffer_get_batched_read_x_shape.__name__
batch_size = 32
buffer_size = 5
signal_window_size = 300
signal_window_stride = 30
min_labels_per_window = 1
buffer = DataBuffer(data_loader, buffer_size, batch_size, signal_window_size, signal_window_stride)
x, _, _, _, _ = buffer.get_batched_read()
actual = np.array(x).shape
result1 = AssertThat(actual[0]).is_in_interval(5e2, 1e5)
result2 = AssertThat(actual[1], 300).are_equal()
result3 = AssertThat(actual[2], 1).are_equal()
print_test_result(result1, f'{test_name}_a', f'Value betweem {5e2} - {1e5}', actual[0])
print_test_result(result1, f'{test_name}_b', 300, actual[1])
print_test_result(result1, f'{test_name}_c', 1, actual[2])
def test_loader_read_dacs_is_normilized(data_filepath):
test_name = test_loader_read_dacs_is_normilized.__name__
loader = DataLoader(data_filepath)
read_id = loader.load_read_ids()[0]
dacs, _, _ = loader.load_read(read_id)
arr = np.array(dacs)
actual = np.std(arr)
result = AssertThat(actual).is_in_interval(0.99, 1.01)
print_test_result(result, test_name,
"std of signal to be < 1.3 and > 0.7.", actual)
def test_loader_read_dacs_list_elemnt(data_filepath):
test_name = test_loader_read_dacs_list_elemnt.__name__
expected = np.float64
loader = DataLoader(data_filepath)
read_id = loader.load_read_ids()[0]
dacs, _, _ = loader.load_read(read_id)
actual = type(dacs[0])
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
def test_generator_get_batch_y_end_token(buffer, label_window_size):
setup(buffer)
test_name = test_generator_get_batch_y_end_token.__name__
generator = DataGenerator(buffer, label_window_size)
_, y = next(generator.get_batch())
end_token_indexes = np.where(y[0] == 6)[0]
result = AssertThat(len(end_token_indexes), 1).are_equal()
print_test_result(result, test_name, 1, len(end_token_indexes))
teardown(buffer)
def test_generator_get_batched_read_x_shape(buffer, label_window_size):
setup(buffer)
test_name = test_generator_get_batched_read_x_shape.__name__
expected = (buffer.signal_window_size, 1) # (any, 300, 1)
generator = DataGenerator(buffer, label_window_size)
x, _, _, _, _ = next(generator.get_batched_read())
actual = x.shape[1:]
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
teardown(buffer)
def test_generator_get_batch_y_start_token(buffer, label_window_size):
setup(buffer)
test_name = test_generator_get_batch_y_start_token.__name__
expected = 5
generator = DataGenerator(buffer, label_window_size)
_, y = next(generator.get_batch())
actual = y[0][0]
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
teardown(buffer)
def test_generator_get_batch_y_shape(buffer, label_window_size):
setup(buffer)
test_name = test_generator_get_batch_y_shape.__name__
expected = (buffer.batch_size, label_window_size) #(32,100)
generator = DataGenerator(buffer, label_window_size)
_, y = next(generator.get_batch())
actual = y.shape
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
teardown(buffer)
def test_buffer_get_batch_y_shape(data_loader):
test_name = test_buffer_get_batch_y_shape.__name__
expected = (32,)
batch_size = 32
buffer_size = 5
signal_window_size = 300
signal_window_stride = 30
min_labels_per_window = 1
buffer = DataBuffer(data_loader, buffer_size, batch_size, signal_window_size, signal_window_stride)
_, y = buffer.get_batch()
actual = y.shape
result = AssertThat(actual, expected).are_equal()
print_test_result(result, test_name, expected, actual)
def test_generator_get_batch_y_padding(buffer, label_window_size):
setup(buffer)
test_name = test_generator_get_batch_y_padding.__name__
generator = DataGenerator(buffer, label_window_size)
_, y = next(generator.get_batch())
end_token_indexes = np.where(y[0] == 6)[0]
i = end_token_indexes[0]
padding = y[0][i + 1:]
zeros = np.where(padding == 0)[0]
result = AssertThat(len(zeros), len(padding)).are_equal()
print_test_result(result, f'{test_name}_only_zero_padding', len(padding),
len(zeros))
teardown(buffer)
def test_API_get_trained_model(config, experiment_name):
test_name = test_API_get_trained_model.__name__
actual = get_trained_model(config, experiment_name)
result = AssertThat(actual).is_instance_of(FishNChips)
print_test_result(result, f'{test_name}', 'Is isntance of FishNChips',
actual)
def test_API_get_new_model(config):
test_name = test_API_get_new_model.__name__
actual = get_new_model(config)
result = AssertThat(actual).is_instance_of(FishNChips)
print_test_result(result, test_name, 'Is isntance of FishNChips', actual)