def test_figure_io(self):
vpl.close()
self.assertIs(vpl.gcf(False), None)
vpl.auto_figure(False)
self.assertIs(vpl.gcf(), None)
with self.assertRaises(vpl.figures.figure_manager.NoFigureError):
vpl.screenshot_fig()
fig = vpl.figure()
self.assertIs(vpl.gcf(), None)
del fig
vpl.auto_figure(True)
fig = vpl.gcf()
self.assertTrue(fig is not None)
self.assertIs(fig, vpl.gcf())
vpl.close()
self.assertIs(vpl.gcf(False), None)
vpl.scf(fig)
self.assertIs(fig, vpl.gcf())
vpl.close()
fig = vpl.figure()
self.assertIs(fig, vpl.gcf())
vpl.close()
def test_figure_io():
vpl.close()
assert vpl.gcf(False) is None
vpl.auto_figure(False)
assert vpl.gcf() is None
with pytest.raises(vpl.figures.figure_manager.NoFigureError):
vpl.screenshot_fig()
fig = vpl.figure()
assert vpl.gcf() is None
del fig
vpl.auto_figure(True)
fig = vpl.gcf()
assert fig is not None
assert fig is vpl.gcf()
vpl.close()
assert vpl.gcf(False) is None
vpl.scf(fig)
assert fig is vpl.gcf()
vpl.close()
fig = vpl.figure()
assert fig is vpl.gcf()
vpl.close()
def test_conversions():
vpl.quick_test_plot()
arr = vpl.screenshot_fig()
vpl.close()
image_data = vpl.image_io.vtkimagedata_from_array(arr)
arr2 = vpl.image_io.vtkimagedata_to_array(image_data)
assert np.array_equal(arr, arr2)
def test_trim_image():
fig = vpl.figure()
# Shouldn't do anything if the figure is empty.
assert vpl.screenshot_fig(trim_pad_width=.05).shape[:2] == fig.render_size
vpl.quick_test_plot()
arr = vpl.screenshot_fig()
vpl.close()
trimmed = vpl.image_io.trim_image(arr, fig.background_color, 10)
background_color = np.asarray(fig.background_color) * 255
# Check that no non-background coloured pixels have been lost.
assert (arr != background_color).any(-1).sum() \
== (trimmed != background_color).any(-1).sum()
return trimmed
def test_save(self):
plots = vpl.scatter(np.random.uniform(-10, 10, (30, 3)))
# I can't get python2 to cooperate with unicode here.
# The os functions just don't like them.
if sys.version[0] == "3":
path = Path.cwd() / u"ҢघԝઌƔࢳܢˀા\\Հએࡓ\u061cཪЈतயଯ\u0886.png"
try:
os.mkdir(str(path.parent))
vpl.save_fig(path)
self.assertTrue(path.exists())
os.remove(str(path))
finally:
if path.parent.exists():
os.rmdir(str(path.parent))
else:
path = Path.cwd() / "image.png"
vpl.save_fig(path)
os.remove(str(path))
array = vpl.screenshot_fig(2)
self.assertEqual(array.shape,
tuple(i * 2 for i in vpl.gcf().render_size) + (3, ))
plt.imshow(array)
plt.show()
shape = tuple(i * j for (i, j) in zip(vpl.gcf().render_size, (2, 3)))
vpl.screenshot_fig(pixels=shape).shape
# The following will fail depending on VTK version
# self.assertEqual(vpl.screenshot_fig(pixels=shape).shape,
# shape[::-1] + (3,))
vpl.close()
fig = vpl.figure()
for plot in plots:
fig += plot
vpl.show()
def test_save():
plots = vpl.scatter(np.random.uniform(-10, 10, (30, 3)))
path = TEST_DIR / "name.png"
if path.exists():
os.remove(str(path))
vpl.save_fig(path)
assert path.exists()
array = vpl.screenshot_fig(magnification=2)
assert array.shape == tuple(i * 2 for i in vpl.gcf().render_size) + (3, )
shape = tuple(i * j for (i, j) in zip(vpl.gcf().render_size, (2, 3)))
vpl.screenshot_fig(pixels=shape).shape
# The following will fail depending on VTK version
# .assertEqual(vpl.screenshot_fig(pixels=shape).shape,
# shape[::-1] + (3,))
vpl.close()
return array
def test_qfigure():
vpl.QtFigure._abc_assert_no_abstract_methods()
self = vpl.QtFigure("a Qt widget figure")
assert self is vpl.gcf()
direction = np.array([1, 0, 0])
vpl.quiver(np.array([0, 0, 0]), direction)
vpl.view(camera_direction=direction)
vpl.reset_camera()
self.show(block=False)
self.close()
self.showMaximized(block=not VTKPLOTLIB_WINDOWLESS_TEST)
out = vpl.screenshot_fig(fig=self)
vpl.close(fig=self)
globals().update(locals())
return out
def test_qfigure2():
fig = vpl.QtFigure2("a QWidget figure")
fig.setWindowTitle(fig.window_name)
assert fig is vpl.gcf()
plot = vpl.scatter(np.arange(9).reshape((3, 3)).T)[0]
vpl.quick_test_plot()
fig.add_all()
fig.show(block=False)
fig.qapp.processEvents()
for i in fig.view_buttons.buttons:
i.released.emit()
fig.qapp.processEvents()
time.sleep(.1)
if not VTKPLOTLIB_WINDOWLESS_TEST:
fig.screenshot_button.released.emit()
fig.show_plot_table_button.released.emit()
fig.show(block=False)
for plot in fig.plot_table.rows:
fig.plot_table.rows[plot].text.released.emit()
fig.qapp.processEvents()
assert not plot.visible
assert np.allclose(vpl.screenshot_fig(fig=fig),
np.array(255) * fig.background_color,
atol=1.)
for plot in fig.plot_table.rows:
fig.plot_table.rows[plot].text.released.emit()
fig.qapp.processEvents()
assert plot.visible
fig.plot_table.close()
def get_projections(file, camera_directions=CAMERA_DIRS):
""" Get projection views in given camera directions from an STL file.
Returns: Numpy array of shape (PROJ_SHAPE, len(camera_directions)).
"""
views = []
for dir in camera_directions[::-1]:
mesh = Mesh.from_file(file)
vpl.mesh_plot(mesh, color="black")
r = vpl.view(camera_position=(0, 0, 0), camera_direction=dir)
vpl.reset_camera()
vpl.zoom_to_contents(padding=1)
# Upscale first so downscale is more accurate
arr = vpl.screenshot_fig(magnification=10, off_screen=True)
# Change 3-channel RGB image to single channel binary matrix
arr = cv2.cvtColor(arr, cv2.COLOR_BGR2GRAY)
arr[arr == 0] = 1
arr[arr == 218] = 0
arr = cv2.resize(arr, dsize=PROJ_SHAPE, interpolation=cv2.INTER_LINEAR)
vpl.close()
views.append(arr)
views = np.array(views).reshape(
(PROJ_SHAPE[0], PROJ_SHAPE[1], len(camera_directions)))
return views
