def test_load_imagedata_fails(): expectedLength = 65535 expectedDepth = 1 expectedSize = 256 inputData = np.zeros((expectedLength, expectedDepth), dtype=np.uint8) with pytest.raises(ValueError): imdata, imsize, depth = untiler.load_image_data(inputData, expectedSize) print("# OK - %s " % (inspect.stack()[0][3]))
def test_load_imagedata_fails(): expectedLength = 65535 expectedDepth = 1 expectedSize = 256 inputData = np.zeros((expectedLength, expectedDepth), dtype=np.uint8) with pytest.raises(ValueError): imdata, imsize, depth = untiler.load_image_data( inputData, expectedSize) print("# OK - %s " % (inspect.stack()[0][3]))
def test_load_imagedata_grey(): expectedLength = 65536 expectedDepth = 1 expectedSize = 256 inputData = np.zeros((expectedLength, expectedDepth), dtype=np.uint8) imdata, imsize, depth = untiler.load_image_data(inputData, expectedSize) assert imdata.shape == (expectedSize, expectedSize, expectedDepth,) assert imsize == expectedLength assert depth == expectedDepth print("# OK - %s " % (inspect.stack()[0][3]))
def test_load_imagedata_random(): expectedSize = int(np.random.rand() * 256) expectedLength = expectedSize ** 2 expectedDepth = int(np.random.rand() * 5) inputData = np.zeros((expectedLength, expectedDepth), dtype=np.uint8) imdata, imsize, depth = untiler.load_image_data(inputData, expectedSize) assert imdata.shape == (expectedSize, expectedSize, expectedDepth,) assert imsize == expectedLength assert depth == expectedDepth print("# OK - %s " % (inspect.stack()[0][3]))
def test_load_imagedata_grey(): expectedLength = 65536 expectedDepth = 1 expectedSize = 256 inputData = np.zeros((expectedLength, expectedDepth), dtype=np.uint8) imdata, imsize, depth = untiler.load_image_data(inputData, expectedSize) assert imdata.shape == ( expectedSize, expectedSize, expectedDepth, ) assert imsize == expectedLength assert depth == expectedDepth print("# OK - %s " % (inspect.stack()[0][3]))
def test_load_imagedata_random(): expectedSize = int(np.random.rand() * 256) expectedLength = expectedSize**2 expectedDepth = int(np.random.rand() * 5) inputData = np.zeros((expectedLength, expectedDepth), dtype=np.uint8) imdata, imsize, depth = untiler.load_image_data(inputData, expectedSize) assert imdata.shape == ( expectedSize, expectedSize, expectedDepth, ) assert imsize == expectedLength assert depth == expectedDepth print("# OK - %s " % (inspect.stack()[0][3]))