First, let’s download some available datasets. Here we are using a dataset which provides metrics and bundles.
import numpy as np
from dipy.viz import window, actor
from dipy.data import fetch_bundles_2_subjects, read_bundles_2_subjects
from dipy.tracking.streamline import transform_streamlines
fetch_bundles_2_subjects()
dix = read_bundles_2_subjects(subj_id='subj_1', metrics=['fa'],
bundles=['cg.left', 'cst.right'])
Store fractional anisotropy.
fa = dix['fa']
Store grid to world transformation matrix.
affine = dix['affine']
Store the cingulum bundle. A bundle is a list of streamlines.
bundle = dix['cg.left']
It happened that this bundle is in world coordinates and therefore we need to transform it into native image coordinates so that it is in the same coordinate space as the fa image.
bundle_native = transform_streamlines(bundle, np.linalg.inv(affine))
This is the default option when you are using line or streamtube.
renderer = window.Renderer()
stream_actor = actor.line(bundle_native)
renderer.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))
renderer.add(stream_actor)
# Uncomment the line below to show to display the window
# window.show(renderer, size=(600, 600), reset_camera=False)
window.record(renderer, out_path='bundle1.png', size=(600, 600))
One orientation color for every streamline.
You may wonder how we knew how to set the camera. This is very easy. You just need to run window.show once see how you want to see the object and then close the window and call the camera_info method which prints the position, focal point and view up vectors of the camera.
renderer.camera_info()
Here we will need to input the fa map in streamtube or line.
renderer.clear()
stream_actor2 = actor.line(bundle_native, fa, linewidth=0.1)
We can also show the scalar bar.
bar = actor.scalar_bar()
renderer.add(stream_actor2)
renderer.add(bar)
# window.show(renderer, size=(600, 600), reset_camera=False)
window.record(renderer, out_path='bundle2.png', size=(600, 600))
Every point with a color from FA.
Here we will need to input the fa map in streamtube or ``
renderer.clear()
hue = [0.0, 0.0] # red only
saturation = [0.0, 1.0] # white to red
lut_cmap = actor.colormap_lookup_table(hue_range=hue,
saturation_range=saturation)
stream_actor3 = actor.line(bundle_native, fa, linewidth=0.1,
lookup_colormap=lut_cmap)
bar2 = actor.scalar_bar(lut_cmap)
renderer.add(stream_actor3)
renderer.add(bar2)
# window.show(renderer, size=(600, 600), reset_camera=False)
window.record(renderer, out_path='bundle3.png', size=(600, 600))
Every point with a color from FA using a non default colomap.
You can have a bundle with a specific color. Here orange.
renderer.clear()
stream_actor4 = actor.line(bundle_native, (1., 0.5, 0), linewidth=0.1)
renderer.add(stream_actor4)
# window.show(renderer, size=(600, 600), reset_camera=False)
window.record(renderer, out_path='bundle4.png', size=(600, 600))
Entire bundle with a specific color.
Let’s make a colormap where every streamline of the bundle is colored by its length.
renderer.clear()
from dipy.tracking.streamline import length
lengths = length(bundle_native)
hue = [0.5, 0.5] # red only
saturation = [0.0, 1.0] # black to white
lut_cmap = actor.colormap_lookup_table(
scale_range=(lengths.min(), lengths.max()),
hue_range=hue,
saturation_range=saturation)
stream_actor5 = actor.line(bundle_native, lengths, linewidth=0.1,
lookup_colormap=lut_cmap)
renderer.add(stream_actor5)
bar3 = actor.scalar_bar(lut_cmap)
renderer.add(bar3)
# window.show(renderer, size=(600, 600), reset_camera=False)
window.record(renderer, out_path='bundle5.png', size=(600, 600))
In this case in which we want to have a color per point and per streamline, we can create a list of the colors to correspond to the list of streamlines (bundles). Here in colors we will insert some random RGB colors.
renderer.clear()
colors = [np.random.rand(*streamline.shape) for streamline in bundle_native]
stream_actor6 = actor.line(bundle_native, colors, linewidth=0.2)
renderer.add(stream_actor6)
# window.show(renderer, size=(600, 600), reset_camera=False)
window.record(renderer, out_path='bundle6.png', size=(600, 600))
Random colors per points per streamline.
In summary, we showed that there are many useful ways for visualizing maps on bundles.
Example source code
You can download the full source code of this example. This same script is also included in the dipy source distribution under the doc/examples/ directory.