def test_contour_from_roi():
# Render volume
scene = window.Scene()
data = np.zeros((50, 50, 50))
data[20:30, 25, 25] = 1.
data[25, 20:30, 25] = 1.
affine = np.eye(4)
surface = actor.contour_from_roi(data,
affine,
color=np.array([1, 0, 1]),
opacity=.5)
scene.add(surface)
scene.reset_camera()
scene.reset_clipping_range()
# window.show(scene)
# Test Errors
npt.assert_raises(ValueError, actor.contour_from_roi, np.ones(50))
# Test binarization
scene2 = window.Scene()
data2 = np.zeros((50, 50, 50))
data2[20:30, 25, 25] = 1.
data2[35:40, 25, 25] = 1.
affine = np.eye(4)
surface2 = actor.contour_from_roi(data2,
affine,
color=np.array([0, 1, 1]),
opacity=.5)
scene2.add(surface2)
scene2.reset_camera()
scene2.reset_clipping_range()
# window.show(scene2)
arr = window.snapshot(scene, 'test_surface.png', offscreen=True)
arr2 = window.snapshot(scene2, 'test_surface2.png', offscreen=True)
report = window.analyze_snapshot(arr, find_objects=True)
report2 = window.analyze_snapshot(arr2, find_objects=True)
npt.assert_equal(report.objects, 1)
npt.assert_equal(report2.objects, 2)
# test on real streamlines using tracking example
if have_dipy:
from dipy.data import read_stanford_labels
from dipy.reconst.shm import CsaOdfModel
from dipy.data import default_sphere
from dipy.direction import peaks_from_model
from fury.colormap import line_colors
from dipy.tracking import utils
try:
from dipy.tracking.local import ThresholdTissueClassifier \
as ThresholdStoppingCriterion
from dipy.tracking.local import LocalTracking
except ImportError:
from dipy.tracking.stopping_criterion import \
ThresholdStoppingCriterion
from dipy.tracking.local_tracking import LocalTracking
hardi_img, gtab, labels_img = read_stanford_labels()
data = np.asanyarray(hardi_img.dataobj)
labels = np.asanyarray(labels_img.dataobj)
affine = hardi_img.affine
white_matter = (labels == 1) | (labels == 2)
csa_model = CsaOdfModel(gtab, sh_order=6)
csa_peaks = peaks_from_model(csa_model,
data,
default_sphere,
relative_peak_threshold=.8,
min_separation_angle=45,
mask=white_matter)
classifier = ThresholdStoppingCriterion(csa_peaks.gfa, .25)
seed_mask = labels == 2
seeds = utils.seeds_from_mask(seed_mask,
density=[1, 1, 1],
affine=affine)
# Initialization of LocalTracking.
# The computation happens in the next step.
streamlines = LocalTracking(csa_peaks,
classifier,
seeds,
affine,
step_size=2)
# Compute streamlines and store as a list.
streamlines = list(streamlines)
# Prepare the display objects.
streamlines_actor = actor.line(streamlines, line_colors(streamlines))
seedroi_actor = actor.contour_from_roi(seed_mask, affine, [0, 1, 1],
0.5)
# Create the 3d display.
r = window.Scene()
r2 = window.Scene()
r.add(streamlines_actor)
arr3 = window.snapshot(r, 'test_surface3.png', offscreen=True)
report3 = window.analyze_snapshot(arr3, find_objects=True)
r2.add(streamlines_actor)
r2.add(seedroi_actor)
arr4 = window.snapshot(r2, 'test_surface4.png', offscreen=True)
report4 = window.analyze_snapshot(arr4, find_objects=True)
# assert that the seed ROI rendering is not far
# away from the streamlines (affine error)
npt.assert_equal(report3.objects, report4.objects)
def test_manifest_standard(interactive=False):
scene = window.Scene() # Setup scene
# Setup surface
surface_actor = _generate_surface()
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(surface_actor)
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 1)
scene.clear() # Reset scene
# Contour from roi setup
data = np.zeros((50, 50, 50))
data[20:30, 25, 25] = 1.
data[25, 20:30, 25] = 1.
affine = np.eye(4)
surface = actor.contour_from_roi(data, affine, color=np.array([1, 0, 1]))
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(surface)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 1)
scene.clear() # Reset scene
# Contour from label setup
data = np.zeros((50, 50, 50))
data[5:15, 1:10, 25] = 1.
data[25:35, 1:10, 25] = 2.
data[40:49, 1:10, 25] = 3.
color = np.array([[255, 0, 0],
[0, 255, 0],
[0, 0, 255]])
surface = actor.contour_from_label(data, color=color)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(surface)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 3)
scene.clear() # Reset scene
# Streamtube setup
data1 = np.array([[0, 0, 0], [1, 1, 1], [2, 2, 2.]])
data2 = data1 + np.array([0.5, 0., 0.])
data = [data1, data2]
colors = np.array([[1, 0, 0], [0, 0, 1.]])
tubes = actor.streamtube(data, colors, linewidth=.1)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(tubes)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 2)
scene.clear() # Reset scene
# ODF slicer setup
if have_dipy:
from dipy.data import get_sphere
from tempfile import mkstemp
sphere = get_sphere('symmetric362')
shape = (11, 11, 11, sphere.vertices.shape[0])
fid, fname = mkstemp(suffix='_odf_slicer.mmap')
odfs = np.memmap(fname, dtype=np.float64, mode='w+', shape=shape)
odfs[:] = 1
affine = np.eye(4)
mask = np.ones(odfs.shape[:3])
mask[:4, :4, :4] = 0
odfs[..., 0] = 1
odf_actor = actor.odf_slicer(odfs, affine, mask=mask, sphere=sphere,
scale=.25, colormap='blues')
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
k = 5
I, J, _ = odfs.shape[:3]
odf_actor.display_extent(0, I, 0, J, k, k)
odf_actor.GetProperty().SetOpacity(1.0)
scene.add(odf_actor)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 11 * 11)
scene.clear() # Reset scene
# Tensor slicer setup
if have_dipy:
from dipy.data import get_sphere
sphere = get_sphere('symmetric724')
evals = np.array([1.4, .35, .35]) * 10 ** (-3)
evecs = np.eye(3)
mevals = np.zeros((3, 2, 4, 3))
mevecs = np.zeros((3, 2, 4, 3, 3))
mevals[..., :] = evals
mevecs[..., :, :] = evecs
affine = np.eye(4)
scene = window.Scene()
tensor_actor = actor.tensor_slicer(mevals, mevecs, affine=affine,
sphere=sphere, scale=.3)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
_, J, K = mevals.shape[:3]
tensor_actor.display_extent(0, 1, 0, J, 0, K)
scene.add(tensor_actor)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 4)
scene.clear() # Reset scene
# Point setup
points = np.array([[0, 0, 0], [0, 1, 0], [1, 0, 0]])
colors = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
opacity = 0.5
points_actor = actor.point(points, colors, opacity=opacity)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(points_actor)
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 3)
scene.clear() # Reset scene
# Sphere setup
xyzr = np.array([[0, 0, 0, 10], [100, 0, 0, 25], [200, 0, 0, 50]])
colors = np.array([[1, 0, 0, 0.3], [0, 1, 0, 0.4], [0, 0, 1., 0.99]])
opacity = 0.5
sphere_actor = actor.sphere(centers=xyzr[:, :3], colors=colors[:],
radii=xyzr[:, 3], opacity=opacity)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(sphere_actor)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 3)
scene.clear() # Reset scene
# Advanced geometry actors setup (Arrow, cone, cylinder)
xyz = np.array([[0, 0, 0], [50, 0, 0], [100, 0, 0]])
dirs = np.array([[0, 1, 0], [1, 0, 0], [0, 0.5, 0.5]])
colors = np.array([[1, 0, 0, 0.3], [0, 1, 0, 0.4], [1, 1, 0, 1]])
heights = np.array([5, 7, 10])
actor_list = [[actor.cone, {'directions': dirs, 'resolution': 8}],
[actor.arrow, {'directions': dirs, 'resolution': 9}],
[actor.cylinder, {'directions': dirs}]]
for act_func, extra_args in actor_list:
aga_actor = act_func(centers=xyz, colors=colors[:], heights=heights,
**extra_args)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(aga_actor)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 3)
scene.clear()
# Basic geometry actors (Box, cube, frustum, octagonalprism, rectangle,
# square)
centers = np.array([[4, 0, 0], [0, 4, 0], [0, 0, 0]])
colors = np.array([[1, 0, 0, 0.4], [0, 1, 0, 0.8], [0, 0, 1, 0.5]])
directions = np.array([[1, 1, 0]])
scale_list = [1, 2, (1, 1, 1), [3, 2, 1], np.array([1, 2, 3]),
np.array([[1, 2, 3], [1, 3, 2], [3, 1, 2]])]
actor_list = [[actor.box, {}], [actor.cube, {}], [actor.frustum, {}],
[actor.octagonalprism, {}], [actor.rectangle, {}],
[actor.square, {}]]
for act_func, extra_args in actor_list:
for scale in scale_list:
scene = window.Scene()
bga_actor = act_func(centers=centers, directions=directions,
colors=colors, scales=scale, **extra_args)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(bga_actor)
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
msg = 'Failed with {}, scale={}'.format(act_func.__name__, scale)
npt.assert_equal(report.objects, 3, err_msg=msg)
scene.clear()
# Cone setup using vertices
centers = np.array([[0, 0, 0], [20, 0, 0], [40, 0, 0]])
directions = np.array([[0, 1, 0], [1, 0, 0], [0, 0, 1]])
colors = np.array([[1, 0, 0, 0.3], [0, 1, 0, 0.4], [0, 0, 1., 0.99]])
vertices = np.array([[0.0, 0.0, 0.0], [0.0, 10.0, 0.0],
[10.0, 0.0, 0.0], [0.0, 0.0, 10.0]])
faces = np.array([[0, 1, 3], [0, 1, 2]])
cone_actor = actor.cone(centers=centers, directions=directions,
colors=colors[:], vertices=vertices, faces=faces)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(cone_actor)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 3)
scene.clear() # Reset scene
# Superquadric setup
centers = np.array([[8, 0, 0], [0, 8, 0], [0, 0, 0]])
colors = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
directions = np.random.rand(3, 3)
scales = [1, 2, 3]
roundness = np.array([[1, 1], [1, 2], [2, 1]])
sq_actor = actor.superquadric(centers, roundness=roundness,
directions=directions,
colors=colors.astype(np.uint8),
scales=scales)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(sq_actor)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
ft.assert_greater_equal(report.objects, 3)
scene.clear() # Reset scene
# Label setup
text_actor = actor.label("Hello")
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(text_actor)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 5)
scene.clear() # Reset scene
# Texture setup
arr = (255 * np.ones((512, 212, 4))).astype('uint8')
arr[20:40, 20:40, :] = np.array([255, 0, 0, 255], dtype='uint8')
tp2 = actor.texture(arr)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(tp2)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 1)
scene.clear() # Reset scene
# Texture on sphere setup
arr = 255 * np.ones((810, 1620, 3), dtype='uint8')
rows, cols, _ = arr.shape
rs = rows // 2
cs = cols // 2
w = 150 // 2
arr[rs - w: rs + w, cs - 10 * w: cs + 10 * w] = np.array([255, 127, 0])
tsa = actor.texture_on_sphere(arr)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(tsa)
scene.reset_camera()
scene.reset_clipping_range()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 1)
# NOTE: From this point on, these actors don't have full support for PBR
# interpolation. This is, the test passes but there is no evidence of the
# desired effect.
"""
# Setup slicer
data = (255 * np.random.rand(50, 50, 50))
affine = np.eye(4)
slicer = actor.slicer(data, affine, value_range=[data.min(), data.max()])
slicer.display(None, None, 25)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(slicer)
"""
"""
# Line setup
data1 = np.array([[0, 0, 0], [1, 1, 1], [2, 2, 2.]])
data2 = data1 + np.array([0.5, 0., 0.])
data = [data1, data2]
colors = np.array([[1, 0, 0], [0, 0, 1.]])
lines = actor.line(data, colors, linewidth=5)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(lines)
"""
"""
# Scalar bar setup
lut = actor.colormap_lookup_table(
scale_range=(0., 100.), hue_range=(0., 0.1), saturation_range=(1, 1),
value_range=(1., 1))
sb_actor = actor.scalar_bar(lut, ' ')
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(sb_actor)
"""
"""
# Axes setup
axes = actor.axes()
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(axes)
"""
"""
# Peak slicer setup
_peak_dirs = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]], dtype='f4')
# peak_dirs.shape = (1, 1, 1) + peak_dirs.shape
peak_dirs = np.zeros((11, 11, 11, 3, 3))
peak_dirs[:, :, :] = _peak_dirs
peak_actor = actor.peak_slicer(peak_dirs)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(peak_actor)
"""
"""
# Dots setup
points = np.array([[0, 0, 0], [0, 1, 0], [1, 0, 0]])
dots_actor = actor.dots(points, color=(0, 255, 0))
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(dots_actor)
"""
"""
# Text3D setup
msg = 'I \nlove\n FURY'
txt_actor = actor.text_3d(msg)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(txt_actor)
"""
"""
# Figure setup
arr = (255 * np.ones((512, 212, 4))).astype('uint8')
arr[20:40, 20:40, 3] = 0
tp = actor.figure(arr)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(tp)
"""
"""
# SDF setup
centers = np.array([[2, 0, 0], [0, 2, 0], [0, 0, 0]]) * 11
colors = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
directions = np.array([[0, 1, 0], [1, 0, 0], [0, 0, 1]])
scales = [1, 2, 3]
primitive = ['sphere', 'ellipsoid', 'torus']
sdf_actor = actor.sdf(centers, directions=directions, colors=colors,
primitives=primitive, scales=scales)
material.manifest_standard(surface_actor, ambient_level=.3,
diffuse_level=.25)
scene.add(sdf_actor)
"""
# NOTE: For these last set of actors, there is not support for PBR
# interpolation at all.
"""
# Billboard setup
centers = np.array([[0, 0, 0], [5, -5, 5], [-7, 7, -7], [10, 10, 10],
[10.5, 11.5, 11.5], [12, -12, -12], [-17, 17, 17],
[-22, -22, 22]])
colors = np.array([[1, 1, 0], [0, 0, 0], [1, 0, 1], [0, 0, 1], [1, 1, 1],
[1, 0, 0], [0, 1, 0], [0, 1, 1]])
scales = [6, .4, 1.2, 1, .2, .7, 3, 2]
"""
fake_sphere = \
"""
float len = length(point);
float radius = 1.;
if (len > radius)
discard;
vec3 normalizedPoint = normalize(vec3(point.xy, sqrt(1. - len)));
vec3 direction = normalize(vec3(1., 1., 1.));
float df_1 = max(0, dot(direction, normalizedPoint));
float sf_1 = pow(df_1, 24);
fragOutput0 = vec4(max(df_1 * color, sf_1 * vec3(1)), 1);
"""
"""
billboard_actor = actor.billboard(centers, colors=colors, scales=scales,
fs_impl=fake_sphere)
material.manifest_pbr(billboard_actor)
scene.add(billboard_actor)
"""
if interactive:
window.show(scene)
def main():
parser = _build_arg_parser()
args = parser.parse_args()
assert_inputs_exist(parser, args.in_volume)
assert_outputs_exist(parser, args, args.out_image)
output_names = [
'axial_superior', 'axial_inferior', 'coronal_posterior',
'coronal_anterior', 'sagittal_left', 'sagittal_right'
]
for filename in args.in_bundles:
if not is_header_compatible(args.in_volume, filename):
parser.error('{} does not have a compatible header with {}'.format(
filename, args.in_volume))
output_dir = os.path.dirname(args.out_image)
if output_dir:
assert_output_dirs_exist_and_empty(parser,
args,
output_dir,
create_dir=True)
# ----------------------------------------------------------------------- #
# Mosaic, column 0: orientation names and data description
# ----------------------------------------------------------------------- #
width = args.resolution_of_thumbnails
height = args.resolution_of_thumbnails
rows = 6
cols = len(args.in_bundles)
text_pos_x = 50
text_pos_y = 50
# Creates a new empty image, RGB mode
mosaic = Image.new('RGB', ((cols + 1) * width, (rows + 1) * height))
# Prepare draw and font objects to render text
draw = ImageDraw.Draw(mosaic)
font = get_font(args)
# Data of the volume used as background
ref_img = nib.load(args.in_volume)
data = ref_img.get_fdata(dtype=np.float32)
affine = ref_img.affine
mean, std = data[data > 0].mean(), data[data > 0].std()
value_range = (mean - 0.5 * std, mean + 1.5 * std)
# First column with rows description
draw_column_with_names(draw, output_names, text_pos_x, text_pos_y, height,
font)
# ----------------------------------------------------------------------- #
# Columns with bundles
# ----------------------------------------------------------------------- #
random.seed(args.random_coloring)
for idx_bundle, bundle_file in enumerate(args.in_bundles):
bundle_file_name = os.path.basename(bundle_file)
bundle_name, bundle_ext = split_name_with_nii(bundle_file_name)
# !! It creates a temporary folder to create
# the images to concatenate in the mosaic !!
output_bundle_dir = os.path.join(output_dir, bundle_name)
if not os.path.isdir(output_bundle_dir):
os.makedirs(output_bundle_dir)
output_paths = [
os.path.join(output_bundle_dir, '{}_' +
os.path.basename(output_bundle_dir)).format(name)
for name in output_names
]
i = (idx_bundle + 1) * width
if not os.path.isfile(bundle_file):
print('\nInput file {} doesn\'t exist.'.format(bundle_file))
number_streamlines = 0
view_number = 6
j = height * view_number
draw_bundle_information(draw, bundle_file_name, number_streamlines,
i + text_pos_x, j + text_pos_y, font)
else:
if args.uniform_coloring:
colors = args.uniform_coloring
elif args.random_coloring is not None:
colors = random_rgb()
# Select the streamlines to plot
if bundle_ext in ['.tck', '.trk']:
if args.random_coloring is None and args.uniform_coloring is None:
colors = None
bundle_tractogram_file = nib.streamlines.load(bundle_file)
streamlines = bundle_tractogram_file.streamlines
bundle_actor = actor.line(streamlines, colors)
nbr_of_elem = len(streamlines)
# Select the volume to plot
elif bundle_ext in ['.nii.gz', '.nii']:
if not args.random_coloring and not args.uniform_coloring:
colors = [1.0, 1.0, 1.0]
bundle_img_file = nib.load(bundle_file)
roi = get_data_as_mask(bundle_img_file)
bundle_actor = actor.contour_from_roi(roi,
bundle_img_file.affine,
colors)
nbr_of_elem = np.count_nonzero(roi)
# Render
ren = window.Scene()
zoom = args.zoom
opacity = args.opacity_background
# Structural data
slice_actor = actor.slicer(data, affine, value_range)
slice_actor.opacity(opacity)
ren.add(slice_actor)
# Streamlines
ren.add(bundle_actor)
ren.reset_camera()
ren.zoom(zoom)
view_number = 0
set_img_in_cell(mosaic, ren, view_number,
output_paths[view_number], width, height, i)
ren.pitch(180)
ren.reset_camera()
ren.zoom(zoom)
view_number = 1
set_img_in_cell(mosaic, ren, view_number,
output_paths[view_number], width, height, i)
ren.rm(slice_actor)
slice_actor2 = slice_actor.copy()
slice_actor2.display(None, slice_actor2.shape[1] // 2, None)
slice_actor2.opacity(opacity)
ren.add(slice_actor2)
ren.pitch(90)
ren.set_camera(view_up=(0, 0, 1))
ren.reset_camera()
ren.zoom(zoom)
view_number = 2
set_img_in_cell(mosaic, ren, view_number,
output_paths[view_number], width, height, i)
ren.pitch(180)
ren.set_camera(view_up=(0, 0, 1))
ren.reset_camera()
ren.zoom(zoom)
view_number = 3
set_img_in_cell(mosaic, ren, view_number,
output_paths[view_number], width, height, i)
ren.rm(slice_actor2)
slice_actor3 = slice_actor.copy()
slice_actor3.display(slice_actor3.shape[0] // 2, None, None)
slice_actor3.opacity(opacity)
ren.add(slice_actor3)
ren.yaw(90)
ren.reset_camera()
ren.zoom(zoom)
view_number = 4
set_img_in_cell(mosaic, ren, view_number,
output_paths[view_number], width, height, i)
ren.yaw(180)
ren.reset_camera()
ren.zoom(zoom)
view_number = 5
set_img_in_cell(mosaic, ren, view_number,
output_paths[view_number], width, height, i)
view_number = 6
j = height * view_number
draw_bundle_information(draw, bundle_file_name, nbr_of_elem,
i + text_pos_x, j + text_pos_y, font)
shutil.rmtree(output_bundle_dir)
# Save image to file
mosaic.save(args.out_image)
def test_grid(_interactive=False):
vol1 = np.zeros((100, 100, 100))
vol1[25:75, 25:75, 25:75] = 100
contour_actor1 = actor.contour_from_roi(vol1, np.eye(4), (1., 0, 0), 1.)
vol2 = np.zeros((100, 100, 100))
vol2[25:75, 25:75, 25:75] = 100
contour_actor2 = actor.contour_from_roi(vol2, np.eye(4), (1., 0.5, 0), 1.)
vol3 = np.zeros((100, 100, 100))
vol3[25:75, 25:75, 25:75] = 100
contour_actor3 = actor.contour_from_roi(vol3, np.eye(4), (1., 0.5, 0.5),
1.)
scene = window.Scene()
actors = []
texts = []
actors.append(contour_actor1)
text_actor1 = actor.text_3d('cube 1', justification='center')
texts.append(text_actor1)
actors.append(contour_actor2)
text_actor2 = actor.text_3d('cube 2', justification='center')
texts.append(text_actor2)
actors.append(contour_actor3)
text_actor3 = actor.text_3d('cube 3', justification='center')
texts.append(text_actor3)
actors.append(shallow_copy(contour_actor1))
text_actor1 = 'cube 4'
texts.append(text_actor1)
actors.append(shallow_copy(contour_actor2))
text_actor2 = 'cube 5'
texts.append(text_actor2)
actors.append(shallow_copy(contour_actor3))
text_actor3 = 'cube 6'
texts.append(text_actor3)
# show the grid without the captions
container = grid(actors=actors,
captions=None,
caption_offset=(0, -40, 0),
cell_padding=(10, 10),
dim=(2, 3))
scene.add(container)
scene.projection('orthogonal')
counter = itertools.count()
show_m = window.ShowManager(scene)
show_m.initialize()
def timer_callback(_obj, _event):
cnt = next(counter)
# show_m.scene.zoom(1)
show_m.render()
if cnt == 4:
show_m.exit()
show_m.destroy_timers()
show_m.add_timer_callback(True, 200, timer_callback)
show_m.start()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects, 6)
scene.rm_all()
counter = itertools.count()
show_m = window.ShowManager(scene)
show_m.initialize()
# show the grid with the captions
container = grid(actors=actors,
captions=texts,
caption_offset=(0, -50, 0),
cell_padding=(10, 10),
dim=(3, 3))
scene.add(container)
show_m.add_timer_callback(True, 200, timer_callback)
show_m.start()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects > 6, True)
showManager = window.ShowManager()
# Renderer
renderer = showManager.scene
## inital view
# streamlines
stream_actor = actor.line(streamlines)
renderer.add(stream_actor)
# ROI
roiActor = actor.contour_from_roi(handknob_left.get_data(),
affine=handknob_left.affine,
color=np.array([1, 0, 0]),
opacity=0.5)
renderer.AddActor(roiActor)
roiActor = actor.contour_from_roi(handknob_right.get_data(),
affine=handknob_right.affine,
color=np.array([0, 0, 1]),
opacity=0.5)
renderer.AddActor(roiActor)
# Render Window
renderWindow = showManager.window
renderWindow.AddRenderer(renderer)
# Interactor
renderWindowInteractor = vtk.vtkRenderWindowInteractor()
renderWindowInteractor.SetRenderWindow(renderWindow)
def test_grid_ui(interactive=False):
vol1 = np.zeros((100, 100, 100))
vol1[25:75, 25:75, 25:75] = 100
colors = distinguishable_colormap(nb_colors=3)
contour_actor1 = actor.contour_from_roi(vol1, np.eye(4), colors[0], 1.)
vol2 = np.zeros((100, 100, 100))
vol2[25:75, 25:75, 25:75] = 100
contour_actor2 = actor.contour_from_roi(vol2, np.eye(4), colors[1], 1.)
vol3 = np.zeros((100, 100, 100))
vol3[25:75, 25:75, 25:75] = 100
contour_actor3 = actor.contour_from_roi(vol3, np.eye(4), colors[2], 1.)
scene = window.Scene()
actors = []
texts = []
actors.append(contour_actor1)
text_actor1 = actor.text_3d('cube 1', justification='center')
texts.append(text_actor1)
actors.append(contour_actor2)
text_actor2 = actor.text_3d('cube 2', justification='center')
texts.append(text_actor2)
actors.append(contour_actor3)
text_actor3 = actor.text_3d('cube 3', justification='center')
texts.append(text_actor3)
actors.append(shallow_copy(contour_actor1))
text_actor1 = actor.text_3d('cube 4', justification='center')
texts.append(text_actor1)
actors.append(shallow_copy(contour_actor2))
text_actor2 = actor.text_3d('cube 5', justification='center')
texts.append(text_actor2)
actors.append(shallow_copy(contour_actor3))
text_actor3 = actor.text_3d('cube 6', justification='center')
texts.append(text_actor3)
actors.append(shallow_copy(contour_actor1))
text_actor1 = actor.text_3d('cube 7', justification='center')
texts.append(text_actor1)
actors.append(shallow_copy(contour_actor2))
text_actor2 = actor.text_3d('cube 8', justification='center')
texts.append(text_actor2)
actors.append(shallow_copy(contour_actor3))
text_actor3 = actor.text_3d('cube 9', justification='center')
texts.append(text_actor3)
counter = itertools.count()
show_m = window.ShowManager(scene)
show_m.initialize()
def timer_callback(_obj, _event):
cnt = next(counter)
show_m.scene.zoom(1)
show_m.render()
if cnt == 10:
show_m.exit()
# show the grid with the captions
grid_ui = ui.GridUI(actors=actors,
captions=texts,
caption_offset=(0, -50, 0),
cell_padding=(60, 60),
dim=(3, 3),
rotation_axis=(1, 0, 0))
scene.add(grid_ui)
show_m.add_timer_callback(True, 200, timer_callback)
show_m.start()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr)
npt.assert_equal(report.objects > 9, True)
# this needs to happen automatically when start() ends.
for act in actors:
act.RemoveAllObservers()
filename = "test_grid_ui"
recording_filename = pjoin(DATA_DIR, filename + ".log.gz")
expected_events_counts_filename = pjoin(DATA_DIR, filename + ".pkl")
current_size = (900, 600)
scene = window.Scene()
show_manager = window.ShowManager(scene,
size=current_size,
title="FURY GridUI")
show_manager.initialize()
grid_ui2 = ui.GridUI(actors=actors,
captions=texts,
caption_offset=(0, -50, 0),
cell_padding=(60, 60),
dim=(3, 3),
rotation_axis=None)
scene.add(grid_ui2)
event_counter = EventCounter()
event_counter.monitor(grid_ui2)
if interactive:
show_manager.start()
recording = False
if recording:
# Record the following events
# 1. Left click on top left box (will rotate the box)
show_manager.record_events_to_file(recording_filename)
print(list(event_counter.events_counts.items()))
event_counter.save(expected_events_counts_filename)
else:
show_manager.play_events_from_file(recording_filename)
expected = EventCounter.load(expected_events_counts_filename)
event_counter.check_counts(expected)
def test_manifest_standard():
# Test non-supported property
test_actor = actor.text_3d('Test')
npt.assert_warns(UserWarning, material.manifest_standard, test_actor)
center = np.array([[0, 0, 0]])
# Test non-supported interpolation method
test_actor = actor.square(center, directions=(1, 1, 1), colors=(0, 0, 1))
npt.assert_warns(UserWarning, material.manifest_standard, test_actor,
interpolation='test')
scene = window.Scene() # Setup scene
test_actor = actor.box(center, directions=(1, 1, 1), colors=(0, 0, 1),
scales=1)
scene.add(test_actor)
# scene.reset_camera()
# window.show(scene)
ss = window.snapshot(scene, size=(200, 200))
actual = ss[75, 100, :] / 1000
desired = np.array([0, 0, 170]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([0, 0, 85]) / 1000
# TODO: check if camera affects this assert
# npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test ambient level
material.manifest_standard(test_actor, ambient_level=1)
ss = window.snapshot(scene, size=(200, 200))
actual = ss[75, 100, :] / 1000
desired = np.array([0, 0, 255]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test ambient color
material.manifest_standard(test_actor, ambient_level=.5,
ambient_color=(1, 0, 0))
ss = window.snapshot(scene, size=(200, 200))
actual = ss[75, 100, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([0, 0, 212]) / 1000
# TODO: check what affects this
# npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test diffuse level
material.manifest_standard(test_actor, diffuse_level=.75)
ss = window.snapshot(scene, size=(200, 200))
actual = ss[75, 100, :] / 1000
desired = np.array([0, 0, 127]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
desired = np.array([0, 0, 128]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([0, 0, 64]) / 1000
# TODO: check what affects this
# npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test diffuse color
material.manifest_standard(test_actor, diffuse_level=.5,
diffuse_color=(1, 0, 0))
ss = window.snapshot(scene, size=(200, 200))
actual = ss[75, 100, :] / 1000
desired = np.array([0, 0, 85]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([0, 0, 42]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test specular level
material.manifest_standard(test_actor, specular_level=1)
ss = window.snapshot(scene, size=(200, 200))
actual = ss[75, 100, :] / 1000
desired = np.array([170, 170, 255]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([85, 85, 170]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test specular power
material.manifest_standard(test_actor, specular_level=1,
specular_power=5)
ss = window.snapshot(scene, size=(200, 200))
actual = ss[75, 100, :] / 1000
desired = np.array([34, 34, 204]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([1, 1, 86]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test specular color
material.manifest_standard(test_actor, specular_level=1,
specular_color=(1, 0, 0), specular_power=5)
ss = window.snapshot(scene, size=(200, 200))
actual = ss[75, 100, :] / 1000
desired = np.array([34, 0, 170]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([1, 0, 85]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
scene.clear() # Reset scene
# Special case: Contour from roi
data = np.zeros((50, 50, 50))
data[20:30, 25, 25] = 1.
data[25, 20:30, 25] = 1.
test_actor = actor.contour_from_roi(data, color=np.array([1, 0, 1]))
scene.add(test_actor)
ss = window.snapshot(scene, size=(200, 200))
actual = ss[90, 110, :] / 1000
desired = np.array([253, 0, 253]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[90, 60, :] / 1000
desired = np.array([180, 0, 180]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
material.manifest_standard(test_actor)
ss = window.snapshot(scene, size=(200, 200))
actual = ss[90, 110, :] / 1000
desired = np.array([253, 253, 253]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[90, 60, :] / 1000
desired = np.array([180, 180, 180]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
material.manifest_standard(test_actor, diffuse_color=(1, 0, 1))
ss = window.snapshot(scene, size=(200, 200))
actual = ss[90, 110, :] / 1000
desired = np.array([253, 0, 253]) / 1000
# TODO: check what affects the line below
# npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[90, 60, :] / 1000
desired = np.array([180, 0, 180]) / 1000
def structural_plotting(conn_matrix,
uatlas,
streamlines_mni,
template_mask,
interactive=False):
"""
:param conn_matrix:
:param uatlas:
:param streamlines_mni:
:param template_mask:
:param interactive:
:return:
"""
import nibabel as nib
import numpy as np
import networkx as nx
import os
import pkg_resources
from nibabel.affines import apply_affine
from fury import actor, window, colormap, ui
from dipy.tracking.utils import streamline_near_roi
from nilearn.plotting import find_parcellation_cut_coords
from nilearn.image import resample_to_img
from pynets.thresholding import normalize
from pynets.nodemaker import mmToVox
ch2better_loc = pkg_resources.resource_filename(
"pynets", "templates/ch2better.nii.gz")
# Instantiate scene
r = window.Renderer()
# Set camera
r.set_camera(position=(-176.42, 118.52, 128.20),
focal_point=(113.30, 128.31, 76.56),
view_up=(0.18, 0.00, 0.98))
# Load atlas rois
atlas_img = nib.load(uatlas)
atlas_img_data = atlas_img.get_data()
# Collapse list of connected streamlines for visualization
streamlines = nib.streamlines.load(streamlines_mni).streamlines
parcels = []
i = 0
for roi in np.unique(atlas_img_data)[1:]:
parcels.append(atlas_img_data == roi)
i = i + 1
# Add streamlines as cloud of 'white-matter'
streamlines_actor = actor.line(streamlines,
colormap.create_colormap(np.ones(
[len(streamlines)]),
name='Greys_r',
auto=True),
lod_points=10000,
depth_cue=True,
linewidth=0.2,
fake_tube=True,
opacity=1.0)
r.add(streamlines_actor)
# Creat palette of roi colors and add them to the scene as faint contours
roi_colors = np.random.rand(int(np.max(atlas_img_data)), 3)
parcel_contours = []
i = 0
for roi in np.unique(atlas_img_data)[1:]:
include_roi_coords = np.array(np.where(atlas_img_data == roi)).T
x_include_roi_coords = apply_affine(np.eye(4), include_roi_coords)
bool_list = []
for sl in streamlines:
bool_list.append(
streamline_near_roi(sl,
x_include_roi_coords,
tol=1.0,
mode='either_end'))
if sum(bool_list) > 0:
print('ROI: ' + str(i))
parcel_contours.append(
actor.contour_from_roi(atlas_img_data == roi,
color=roi_colors[i],
opacity=0.2))
else:
pass
i = i + 1
for vol_actor in parcel_contours:
r.add(vol_actor)
# Get voxel coordinates of parcels and add them as 3d spherical centroid nodes
[coords, labels] = find_parcellation_cut_coords(atlas_img,
background_label=0,
return_labels=True)
coords_vox = []
for i in coords:
coords_vox.append(mmToVox(atlas_img.affine, i))
coords_vox = list(set(list(tuple(x) for x in coords_vox)))
# Build an edge list of 3d lines
G = nx.from_numpy_array(normalize(conn_matrix))
for i in G.nodes():
nx.set_node_attributes(G, {i: coords_vox[i]}, labels[i])
G.remove_nodes_from(list(nx.isolates(G)))
G_filt = nx.Graph()
fedges = filter(lambda x: G.degree()[x[0]] > 0 and G.degree()[x[1]] > 0,
G.edges())
G_filt.add_edges_from(fedges)
coord_nodes = []
for i in range(len(G.edges())):
edge = list(G.edges())[i]
[x, y] = edge
x_coord = list(G.nodes[x].values())[0]
x_label = list(G.nodes[x].keys())[0]
l_x = actor.label(text=str(x_label),
pos=x_coord,
scale=(1, 1, 1),
color=(50, 50, 50))
r.add(l_x)
y_coord = list(G.nodes[y].values())[0]
y_label = list(G.nodes[y].keys())[0]
l_y = actor.label(text=str(y_label),
pos=y_coord,
scale=(1, 1, 1),
color=(50, 50, 50))
r.add(l_y)
coord_nodes.append(x_coord)
coord_nodes.append(y_coord)
c = actor.line([(x_coord, y_coord)],
window.colors.coral,
linewidth=100 * (float(G.get_edge_data(x, y)['weight']))
^ 2)
r.add(c)
point_actor = actor.point(list(set(coord_nodes)),
window.colors.grey,
point_radius=0.75)
r.add(point_actor)
# Load glass brain template and resample to MNI152_2mm brain
template_img = nib.load(ch2better_loc)
template_target_img = nib.load(template_mask)
res_brain_img = resample_to_img(template_img, template_target_img)
template_img_data = res_brain_img.get_data().astype('bool')
template_actor = actor.contour_from_roi(template_img_data,
color=(50, 50, 50),
opacity=0.05)
r.add(template_actor)
# Show scene
if interactive is True:
window.show(r, size=(600, 600), reset_camera=False)
else:
fig_path = os.path.dirname(streamlines_mni) + '/3d_connectome_fig.png'
window.record(r, out_path=fig_path, size=(600, 600))
return
# pass
# i = i + 1
visible_callback.parcel_contours = parcel_contours
# for vol_actor in parcel_contours:
# # vol_actor.AddObserver('LeftButtonPressEvent',
# # point_left_click_callback,
# # 1.0)
# scene.add(vol_actor)
# Load glass brain template and resample to MNI152_2mm brain
template_img = nib.load(ch2bet)
template_target_img = nib.load(ch2bet_target)
res_brain_img = resample_to_img(template_img, template_target_img)
template_img_data = res_brain_img.get_data().astype('bool')
template_actor = actor.contour_from_roi(template_img_data, color=(50, 50, 50), opacity=0.05)
scene.add(template_actor)
visible_callback.brain_actor = template_actor
# Get voxel coordinates of parcels and add them as 3d spherical centroid nodes
[coords, label_names] = find_parcellation_cut_coords(atlas_img, background_label=0, return_label_names=True)
coords_vox = []
for i in coords:
coords_vox.append(mmToVox(atlas_img, i))
coords_vox = list(set(list(tuple(x) for x in coords_vox)))
# Build an edge list of 3d lines
df = pd.read_csv(graph_properties)
node_cols = [s for s in list(df.columns) if isinstance(s, int) or any(c.isdigit() for c in s)]
def test_manifest_standard():
# Test non-supported property
test_actor = actor.text_3d('Test')
npt.assert_warns(UserWarning, material.manifest_standard, test_actor)
center = np.array([[0, 0, 0]])
# Test non-supported interpolation method
test_actor = actor.square(center, directions=(1, 1, 1), colors=(0, 0, 1))
npt.assert_warns(UserWarning,
material.manifest_standard,
test_actor,
interpolation='test')
# Create tmp dir to save and query images
with TemporaryDirectory() as out_dir:
tmp_fname = os.path.join(out_dir, 'tmp_img.png') # Tmp image to test
scene = window.Scene() # Setup scene
test_actor = actor.box(center,
directions=(1, 1, 1),
colors=(0, 0, 1),
scales=1)
scene.add(test_actor)
# Test basic actor
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[75, 100, :] / 1000
desired = np.array([0, 0, 170]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([0, 0, 85]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test ambient level
material.manifest_standard(test_actor, ambient_level=1)
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[75, 100, :] / 1000
desired = np.array([0, 0, 255]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test ambient color
material.manifest_standard(test_actor,
ambient_level=.5,
ambient_color=(1, 0, 0))
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[75, 100, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([0, 0, 212]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test diffuse level
material.manifest_standard(test_actor, diffuse_level=.75)
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[75, 100, :] / 1000
desired = np.array([0, 0, 127]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
desired = np.array([0, 0, 128]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([0, 0, 64]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test diffuse color
material.manifest_standard(test_actor,
diffuse_level=.5,
diffuse_color=(1, 0, 0))
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[75, 100, :] / 1000
desired = np.array([0, 0, 85]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([0, 0, 42]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test specular level
material.manifest_standard(test_actor, specular_level=1)
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[75, 100, :] / 1000
desired = np.array([170, 170, 255]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([85, 85, 170]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test specular power
material.manifest_standard(test_actor,
specular_level=1,
specular_power=5)
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[75, 100, :] / 1000
desired = np.array([34, 34, 204]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([1, 1, 86]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
# Test specular color
material.manifest_standard(test_actor,
specular_level=1,
specular_color=(1, 0, 0),
specular_power=5)
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[75, 100, :] / 1000
desired = np.array([34, 0, 170]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 125, :] / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[125, 75, :] / 1000
desired = np.array([1, 0, 85]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
scene.clear() # Reset scene
# Special case: Contour from roi
data = np.zeros((50, 50, 50))
data[20:30, 25, 25] = 1.
data[25, 20:30, 25] = 1.
test_actor = actor.contour_from_roi(data, color=np.array([1, 0, 1]))
scene.add(test_actor)
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[90, 110, :] / 1000
desired = np.array([253, 0, 253]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[90, 60, :] / 1000
desired = np.array([180, 0, 180]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
material.manifest_standard(test_actor)
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[90, 110, :] / 1000
desired = np.array([253, 253, 253]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[90, 60, :] / 1000
desired = np.array([180, 180, 180]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
material.manifest_standard(test_actor, diffuse_color=(1, 0, 1))
window.record(scene,
out_path=tmp_fname,
size=(200, 200),
reset_camera=True)
npt.assert_equal(os.path.exists(tmp_fname), True)
ss = load_image(tmp_fname)
actual = ss[90, 110, :] / 1000
desired = np.array([253, 0, 253]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
actual = ss[90, 60, :] / 1000
desired = np.array([180, 0, 180]) / 1000
npt.assert_array_almost_equal(actual, desired, decimal=2)
###############################################################################
# We will create a streamline actor from the streamlines.
streamlines_actor = actor.line(streamlines, line_colors(streamlines))
###############################################################################
# Next, we create a surface actor from the corpus callosum seed ROI. We
# provide the ROI data, the affine, the color in [R,G,B], and the opacity as
# a decimal between zero and one. Here, we set the color as blue/green with
# 50% opacity.
surface_opacity = 0.5
surface_color = [0, 1, 1]
seedroi_actor = actor.contour_from_roi(seed_mask, affine, surface_color,
surface_opacity)
###############################################################################
# Next, we initialize a ''Renderer'' object and add both actors
# to the rendering.
ren = window.Renderer()
ren.add(streamlines_actor)
ren.add(seedroi_actor)
###############################################################################
# If you uncomment the following line, the rendering will pop up in an
# interactive window.
interactive = False
if interactive:
