def test_save_and_load_polydata():
l_ext = ["vtk", "fib", "ply", "xml"]
fname = "temp-io"
for ext in l_ext:
with InTemporaryDirectory() as odir:
data = np.random.randint(0, 255, size=(50, 3))
pd = vtk.vtkPolyData()
pd.SetPoints(numpy_to_vtk_points(data))
fname_path = pjoin(odir, "{0}.{1}".format(fname, ext))
save_polydata(pd, fname_path)
npt.assert_equal(os.path.isfile(fname_path), True)
assert_greater(os.stat(fname_path).st_size, 0)
out_pd = load_polydata(fname_path)
out_data = numpy_support.vtk_to_numpy(out_pd.GetPoints().GetData())
npt.assert_array_equal(data, out_data)
npt.assert_raises(IOError, save_polydata, vtk.vtkPolyData(), "test.vti")
npt.assert_raises(IOError, save_polydata, vtk.vtkPolyData(), "test.obj")
npt.assert_raises(IOError, load_polydata, "test.vti")
def test_save_and_load_options():
l_ext = ["ply", "vtk"]
l_options = [{
'color_array_name': 'horizon',
}, {
'binary': True,
}]
fname = "temp-io"
for ext, option in zip(l_ext, l_options):
with InTemporaryDirectory() as odir:
data = np.random.randint(0, 255, size=(50, 3))
pd = vtk.vtkPolyData()
pd.SetPoints(numpy_to_vtk_points(data))
fname_path = pjoin(odir, "{0}.{1}".format(fname, ext))
save_polydata(pd, fname_path, **option)
npt.assert_equal(os.path.isfile(fname_path), True)
assert_greater(os.stat(fname_path).st_size, 0)
out_pd = load_polydata(fname_path)
out_data = numpy_support.vtk_to_numpy(out_pd.GetPoints().GetData())
npt.assert_array_equal(data, out_data)
l_ext = ["stl", "obj"]
l_options = [{}, {
'is_mni_obj': True,
}]
for ext, option in zip(l_ext, l_options):
with InTemporaryDirectory() as odir:
data = np.random.randint(0, 255, size=(50, 3))
pd = vtk.vtkPolyData()
pd.SetPoints(numpy_to_vtk_points(data))
fname_path = pjoin(odir, "{0}.{1}".format(fname, ext))
save_polydata(pd, fname_path, **option)
npt.assert_equal(os.path.isfile(fname_path), True)
assert_greater(os.stat(fname_path).st_size, 0)
def test_save_load_image():
l_ext = ["png", "jpeg", "jpg", "bmp", "tiff", "tif"]
fname = "temp-io"
for ext in l_ext:
with InTemporaryDirectory() as odir:
data = np.random.randint(0, 255, size=(50, 3), dtype=np.uint8)
fname_path = pjoin(odir, "{0}.{1}".format(fname, ext))
save_image(data, fname_path)
npt.assert_equal(os.path.isfile(fname_path), True)
assert_greater(os.stat(fname_path).st_size, 0)
out_image = load_image(fname_path)
# import ipdb;ipdb.set_trace()
if ext not in ["jpeg", "jpg", "tiff", "tif"]:
npt.assert_array_equal(data, out_image[..., 0])
else:
npt.assert_array_almost_equal(data,
out_image[..., 0],
decimal=0)
npt.assert_raises(IOError, load_image, "test.vtk")
npt.assert_raises(IOError, save_image,
np.random.randint(0, 255, size=(50, 3)), "test.vtk")
npt.assert_raises(IOError, save_image,
np.random.randint(0, 255, size=(50, 3, 1, 1)),
"test.png")
compression_type = [None, "lzw"]
for ct in compression_type:
with InTemporaryDirectory() as odir:
data = np.random.randint(0, 255, size=(50, 3), dtype=np.uint8)
fname_path = pjoin(odir, "{0}.tif".format(fname))
save_image(data, fname_path, compression_type=ct)
npt.assert_equal(os.path.isfile(fname_path), True)
assert_greater(os.stat(fname_path).st_size, 0)
def record_events(self):
"""Record events during the interaction.
The recording is represented as a list of VTK events that happened
during the interaction. The recorded events are then returned.
Returns
-------
events : str
Recorded events (one per line).
Notes
-----
Since VTK only allows recording events to a file, we use a
temporary file from which we then read the events.
"""
with InTemporaryDirectory():
filename = "recorded_events.log"
recorder = vtk.vtkInteractorEventRecorder()
recorder.SetInteractor(self.iren)
recorder.SetFileName(filename)
def _stop_recording_and_close(obj, evt):
if recorder:
recorder.Stop()
self.iren.TerminateApp()
self.iren.AddObserver("ExitEvent", _stop_recording_and_close)
recorder.EnabledOn()
recorder.Record()
self.initialize()
self.render()
self.iren.Start()
# Deleting this object is the unique way
# to close the file.
recorder = None
# Retrieved recorded events.
with open(filename, 'r') as f:
events = f.read()
return events
def test_slicer():
renderer = window.renderer()
data = (255 * np.random.rand(50, 50, 50))
affine = np.eye(4)
slicer = actor.slicer(data, affine)
slicer.display(None, None, 25)
renderer.add(slicer)
renderer.reset_camera()
renderer.reset_clipping_range()
# window.show(renderer)
# copy pixels in numpy array directly
arr = window.snapshot(renderer, 'test_slicer.png', offscreen=True)
import scipy
print(scipy.__version__)
print(scipy.__file__)
print(arr.sum())
print(np.sum(arr == 0))
print(np.sum(arr > 0))
print(arr.shape)
print(arr.dtype)
report = window.analyze_snapshot(arr, find_objects=True)
npt.assert_equal(report.objects, 1)
# print(arr[..., 0])
# The slicer can cut directly a smaller part of the image
slicer.display_extent(10, 30, 10, 30, 35, 35)
renderer.ResetCamera()
renderer.add(slicer)
# save pixels in png file not a numpy array
with InTemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'slice.png')
# window.show(renderer)
window.snapshot(renderer, fname, offscreen=True)
report = window.analyze_snapshot(fname, find_objects=True)
npt.assert_equal(report.objects, 1)
npt.assert_raises(ValueError, actor.slicer, np.ones(10))
renderer.clear()
rgb = np.zeros((30, 30, 30, 3))
rgb[..., 0] = 1.
rgb_actor = actor.slicer(rgb)
renderer.add(rgb_actor)
renderer.reset_camera()
renderer.reset_clipping_range()
arr = window.snapshot(renderer, offscreen=True)
report = window.analyze_snapshot(arr, colors=[(255, 0, 0)])
npt.assert_equal(report.objects, 1)
npt.assert_equal(report.colors_found, [True])
lut = actor.colormap_lookup_table(scale_range=(0, 255),
hue_range=(0.4, 1.),
saturation_range=(1, 1.),
value_range=(0., 1.))
renderer.clear()
slicer_lut = actor.slicer(data, lookup_colormap=lut)
slicer_lut.display(10, None, None)
slicer_lut.display(None, 10, None)
slicer_lut.display(None, None, 10)
slicer_lut.opacity(0.5)
slicer_lut.tolerance(0.03)
slicer_lut2 = slicer_lut.copy()
npt.assert_equal(slicer_lut2.GetOpacity(), 0.5)
npt.assert_equal(slicer_lut2.picker.GetTolerance(), 0.03)
slicer_lut2.opacity(1)
slicer_lut2.tolerance(0.025)
slicer_lut2.display(None, None, 10)
renderer.add(slicer_lut2)
renderer.reset_clipping_range()
arr = window.snapshot(renderer, offscreen=True)
report = window.analyze_snapshot(arr, find_objects=True)
npt.assert_equal(report.objects, 1)
renderer.clear()
data = (255 * np.random.rand(50, 50, 50))
affine = np.diag([1, 3, 2, 1])
slicer = actor.slicer(data, affine, interpolation='nearest')
slicer.display(None, None, 25)
renderer.add(slicer)
renderer.reset_camera()
renderer.reset_clipping_range()
arr = window.snapshot(renderer, offscreen=True)
report = window.analyze_snapshot(arr, find_objects=True)
npt.assert_equal(report.objects, 1)
npt.assert_equal(data.shape, slicer.shape)
renderer.clear()
data = (255 * np.random.rand(50, 50, 50))
affine = np.diag([1, 3, 2, 1])
from dipy.align.reslice import reslice
data2, affine2 = reslice(data, affine, zooms=(1, 3, 2),
new_zooms=(1, 1, 1))
slicer = actor.slicer(data2, affine2, interpolation='linear')
slicer.display(None, None, 25)
renderer.add(slicer)
renderer.reset_camera()
renderer.reset_clipping_range()
# window.show(renderer, reset_camera=False)
arr = window.snapshot(renderer, offscreen=True)
report = window.analyze_snapshot(arr, find_objects=True)
npt.assert_equal(report.objects, 1)
npt.assert_array_equal([1, 3, 2] * np.array(data.shape),
np.array(slicer.shape))
def test_record():
xyzr = np.array([[0, 0, 0, 10], [100, 0, 0, 25], [200, 0, 0, 50]])
colors = np.array([[1, 0, 0, 1], [0, 1, 0, 1], [0, 0, 1., 1]])
sphere_actor = actor.sphere(centers=xyzr[:, :3], colors=colors[:],
radii=xyzr[:, 3])
scene = window.Scene()
scene.add(sphere_actor)
def test_content(filename='fury.png', colors_found=(True, True)):
npt.assert_equal(os.path.isfile(filename), True)
arr = io.load_image(filename)
report = window.analyze_snapshot(arr, colors=[(0, 255, 0),
(255, 0, 0)])
npt.assert_equal(report.objects, 3)
npt.assert_equal(report.colors_found, colors_found)
return arr
# Basic test
with InTemporaryDirectory():
window.record(scene)
test_content()
# test out_path and path_numbering, n_frame
with InTemporaryDirectory():
filename = "tmp_snapshot.png"
window.record(scene, out_path=filename)
test_content(filename)
window.record(scene, out_path=filename, path_numbering=True)
test_content(filename + "000000.png")
window.record(scene, out_path=filename, path_numbering=True,
n_frames=3)
test_content(filename + "000000.png")
test_content(filename + "000001.png")
test_content(filename + "000002.png")
npt.assert_equal(os.path.isfile(filename + "000003.png"), False)
# test verbose
with captured_output() as (out, _):
window.record(scene, verbose=True)
npt.assert_equal(out.getvalue().strip(),
"Camera Position (315.14, 0.00, 536.43)\n"
"Camera Focal Point (119.89, 0.00, 0.00)\n"
"Camera View Up (0.00, 1.00, 0.00)")
# test camera option
with InTemporaryDirectory():
window.record(scene, cam_pos=(310, 0, 530), cam_focal=(120, 0, 0),
cam_view=(0, 0, 1))
test_content()
# test size and clipping
with InTemporaryDirectory():
window.record(scene, out_path='fury_1.png', size=(1000, 1000),
magnification=5)
npt.assert_equal(os.path.isfile('fury_1.png'), True)
arr = io.load_image('fury_1.png')
npt.assert_equal(arr.shape, (5000, 5000, 3))
window.record(scene, out_path='fury_2.png', size=(5000, 5000),
screen_clip=True)
npt.assert_equal(os.path.isfile('fury_2.png'), True)
arr = io.load_image('fury_2.png')
assert_less_equal(arr.shape[0], 5000)
assert_less_equal(arr.shape[1], 5000)