.. AUTO-GENERATED FILE -- DO NOT EDIT!
.. _example_viz_bundles:
========================================
Visualize bundles and metrics on bundles
========================================
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))
Show every streamline with an orientation color
===============================================
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))
.. figure:: bundle1.png
:align: center
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()
Show every point with a value from a volume with default colormap
=================================================================
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))
.. figure:: bundle2.png
:align: center
Every point with a color from FA.
Show every point with a value from a volume with your colormap
==============================================================
Here we will need to input the ``fa`` map in ``streamtube``
::
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))
.. figure:: bundle3.png
:align: center
Every point with a color from FA using a non default colormap.
Show every bundle with a specific color
========================================
You can have a bundle with a specific color. In this example, we are chosing
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))
.. figure:: bundle4.png
:align: center
Entire bundle with a specific color.
Show every streamline of a bundle with a different 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) # blue 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))
.. figure:: bundle5.png
:align: center
Color every streamline by the length of the streamline
Show every point of every streamline with a different color
============================================================
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))
.. figure:: bundle6.png
:align: center
Random colors per points per streamline.
In summary, we showed that there are many useful ways for visualizing maps
on bundles.
.. admonition:: Example source code
You can download :download:`the full source code of this example <./viz_bundles.py>`. This same script is also included in the dipy source distribution under the :file:`doc/examples/` directory.