def apply_colormap(r1, r2):
if mem.slicer_rgb:
return
if mem.slicer_colormap == 'disting':
# use distinguishable colors
rgb = colormap.distinguishable_colormap(nb_colors=256)
rgb = np.asarray(rgb)
else:
# use matplotlib colormaps
rgb = colormap.create_colormap(np.linspace(r1, r2, 256),
name=mem.slicer_colormap,
auto=True)
N = rgb.shape[0]
lut = colormap.LookupTable()
lut.SetNumberOfTableValues(N)
lut.SetRange(r1, r2)
for i in range(N):
r, g, b = rgb[i]
lut.SetTableValue(i, r, g, b)
lut.SetRampToLinear()
lut.Build()
mem.slicer_curr_actor_z.output.SetLookupTable(lut)
mem.slicer_curr_actor_z.output.Update()
def color_tree2(tree, bg=(1, 1, 1), min_level=0):
import colorsys
from dipy.viz.colormap import distinguishable_colormap
global colormap
colormap = iter(distinguishable_colormap(bg=bg, exclude=[(1., 1., 0.93103448)]))
def _color_subtree(node, color=None, level=0, max_lum=0.9, min_lum=0.1):
global colormap
node.color = color
#max_lum = 1
if color is not None:
hls = np.asarray(colorsys.rgb_to_hls(*color))
max_lum = min(max_lum, hls[1] + 0.2)
min_lum = max(min_lum, hls[1] - 0.2)
children_sizes = map(len, node.children)
indices = np.argsort(children_sizes)[::-1]
luminosities = np.linspace(max_lum, min_lum, len(node.children)+1)
#for child, luminosity, offset in zip(node.children, luminosities, offsets):
for i, idx in enumerate(indices):
child = node.children[idx]
if level <= min_level:
color = next(colormap)
_color_subtree(child, color, level+1)
else:
hls = np.asarray(colorsys.rgb_to_hls(*color))
#rbg = colorsys.hls_to_rgb(hls[0], (luminosities[i]+luminosities[i+1])/2, hls[2])
rbg = colorsys.hls_to_rgb(hls[0], luminosities[i+1], hls[2])
_color_subtree(child, np.asarray(rbg), level+1, luminosities[i], luminosities[i+1])
_color_subtree(tree.root)
def _cluster(self, threshold):
qb = QuickBundles(metric=metric, threshold=threshold)
self.last_threshold = threshold
self.clusters = qb.cluster(self.streamlines)
self.clusters_colors = [
color for c, color in zip(
self.clusters,
distinguishable_colormap(bg=(0, 0, 0), exclude=darkcolors))
]
if threshold < np.inf:
print("{} clusters with QB threshold of {}mm".format(
len(self.clusters), threshold))
# Keep a flag telling there have been changes.
self.has_changed = True
if len(self.clusters) == 1:
# Keep initial color
self.clusters_colors = [self.color
] if self.color is not None else [(0, 0,
1)]
vtk_colors = utils.numpy_to_vtk_colors(255 * self.original_colors)
vtk_colors.SetName("Colors")
self.actor.GetMapper().GetInput().GetPointData().SetScalars(
vtk_colors)
return
for cluster, color in zip(self.clusters, self.clusters_colors):
self.streamlines_colors[cluster.indices] = color
self.colors = []
for color, streamline in zip(self.streamlines_colors,
self.streamlines):
self.colors += [color] * len(streamline)
vtk_colors = utils.numpy_to_vtk_colors(255 * np.array(self.colors))
vtk_colors.SetName("Colors")
self.actor.GetMapper().GetInput().GetPointData().SetScalars(vtk_colors)
def color_tree(tree, bg=(1, 1, 1), min_level=0):
import colorsys
from dipy.viz.colormap import distinguishable_colormap
global colormap
colormap = iter(distinguishable_colormap(bg=bg, exclude=[(1., 1., 0.93103448)]))
def _color_subtree(node, color=None, level=0):
global colormap
node.color = color
max_luminosity = 0
if color is not None:
hls = np.asarray(colorsys.rgb_to_hls(*color))
max_luminosity = hls[1]
#luminosities = np.linspace(0.3, 0.8, len(node.children))
children_sizes = map(len, node.children)
indices = np.argsort(children_sizes)[::-1]
luminosities = np.linspace(max_luminosity, 0.2, len(node.children))
#for child, luminosity, offset in zip(node.children, luminosities, offsets):
for idx, luminosity in zip(indices, luminosities):
child = node.children[idx]
if level <= min_level:
color = next(colormap)
_color_subtree(child, color, level+1)
else:
hls = np.asarray(colorsys.rgb_to_hls(*color))
#if hls[1] > 0.8:
# hls[1] -= 0.3
#elif hls[1] < 0.3:
# hls[1] += 0.3
rbg = colorsys.hls_to_rgb(hls[0], luminosity, hls[2])
_color_subtree(child, np.asarray(rbg), level+1)
_color_subtree(tree.root)
