def test_mpl_cmap():
cm = pytest.importorskip("matplotlib.cm")
# 2D uint8
image = Image()
data = np.random.randint(0, 255, (60, 60)).astype("uint8")
image.set_data(data)
rendered = image.image_rgba
assert isinstance(rendered, np.ndarray)
# without a colormap, the output data should be nearly identical
assert data.size - np.count_nonzero(rendered[...,
0] == data) < data.size * 0.01
assert isinstance(rendered, np.ndarray)
assert rendered.shape == (60, 60, 4)
image.set_cmap("magma")
rendered2 = image.image_rgba
assert isinstance(rendered2, np.ndarray)
# the colormap has been applied
assert data.size - np.count_nonzero(rendered2[..., 0] == data) > 3000
# can also use an mpl colormap instance
image.set_cmap(cm.get_cmap("viridis"))
rendered3 = image.image_rgba
assert isinstance(rendered3, np.ndarray)
# the colormap has been applied
assert not np.allclose(rendered2, rendered3)
def test_empty_image():
image = Image()
assert image.image_data is None
assert image.image_rgba is None
assert image.get_clim() == (None, None)
with pytest.raises(RuntimeError):
image.set_clim(0, 100)
with pytest.raises(RuntimeError):
image.set_clim(0, 100)
with pytest.raises(RuntimeError):
image.set_cmap("turbo")
with pytest.raises(RuntimeError):
image.set_norm(1)
def test_internal_cmap():
cmap = _mpl_image.Colormap([[0, 0, 0, 1], [1, 0, 0, 1]])
image = Image()
data = np.random.randint(0, 255, (60, 60)).astype("uint8")
image.set_data(data, cmap=cmap)
rendered = image.image_rgba
assert isinstance(rendered, np.ndarray)
assert rendered.shape == (60, 60, 4)
image.set_cmap(
_mpl_image.Colormap([[0, 0, 0, 1], [1, 0, 0, 1]],
interpolation="nearest"))
rendered2 = image.image_rgba
assert isinstance(rendered2, np.ndarray)
assert not np.allclose(rendered, rendered2)