def test_grey(self): with expected_warnings(['precision loss']): tmp = np.arange(12, dtype=float).reshape((4, 3)) / 11 x = prepare_for_display(tmp) assert_array_equal(x[..., 0], x[..., 2]) assert x[0, 0, 0] == 0 assert x[3, 2, 0] == 255
def test_grey(self): x = prepare_for_display(np.arange(12, dtype=float).reshape((4, 3)) / 11) assert_array_equal(x[..., 0], x[..., 2]) assert x[0, 0, 0] == 0 assert x[3, 2, 0] == 255
def test_dtype(self): x = prepare_for_display(np.random.random((10, 15))) assert x.dtype == np.dtype(np.uint8)
def test_wrong_depth(self): with testing.raises(ValueError): with expected_warnings(['precision loss']): prepare_for_display(np.random.rand(10, 10, 5))
def test_wrong_dimensionality(self): with expected_warnings(['precision loss']): prepare_for_display(np.random.rand(10, 10, 1, 1))
def test_basic(self): prepare_for_display(np.random.random((10, 10)))
def test_alpha(self): prepare_for_display(np.random.random((10, 10, 4)))
def test_wrong_dimensionality(self): prepare_for_display(np.random.random((10, 10, 1, 1)))
def test_colour(self): prepare_for_display(np.random.random((10, 10, 3)))
def test_wrong_depth(self): with testing.raises(ValueError): prepare_for_display(np.random.rand(10, 10, 5))
def test_wrong_dimensionality(self): with testing.raises(ValueError): prepare_for_display(np.random.rand(10, 10, 1, 1))
def test_wrong_depth(self): prepare_for_display(np.random.random((10, 10, 5)))
def test_dtype(self): with expected_warnings(['precision loss']): x = prepare_for_display(np.random.rand(10, 15)) assert x.dtype == np.dtype(np.uint8)
def test_basic(self): with expected_warnings(['precision loss']): prepare_for_display(np.random.rand(10, 10))
def test_alpha(self): with expected_warnings(['precision loss']): prepare_for_display(np.random.rand(10, 10, 4))
def test_wrong_depth(self): with expected_warnings(['precision loss']): prepare_for_display(np.random.rand(10, 10, 5))