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_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_colour(self):
prepare_for_display(np.random.random((10, 10, 3)))
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):
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_colour(self):
prepare_for_display(np.random.random((10, 10, 3)))
def test_wrong_dimensionality(self):
prepare_for_display(np.random.random((10, 10, 1, 1)))
def test_alpha(self):
prepare_for_display(np.random.random((10, 10, 4)))
def test_wrong_depth(self):
prepare_for_display(np.random.random((10, 10, 5)))
def test_wrong_depth(self):
prepare_for_display(np.random.random((10, 10, 5)))
def test_basic(self):
prepare_for_display(np.random.random((10, 10)))
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_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_wrong_depth(self):
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))
