.. AUTO-GENERATED FILE -- DO NOT EDIT!

.. _example_viz_slice:


=====================
Simple volume slicing
=====================

Here we present an example for visualizing slices from 3D images.


::
  
  import os
  import nibabel as nib
  from dipy.data import fetch_bundles_2_subjects
  from dipy.viz import window, actor
  

Let's download and load a T1.

::
  
  fetch_bundles_2_subjects()
  
  fname_t1 = os.path.join(os.path.expanduser('~'), '.dipy',
                          'exp_bundles_and_maps', 'bundles_2_subjects',
                          'subj_1', 't1_warped.nii.gz')
  
  
  img = nib.load(fname_t1)
  data = img.get_data()
  affine = img.get_affine()
  

Create a Renderer object which holds all the actors which we want to visualize.

::
  
  renderer = window.Renderer()
  renderer.background((1, 1, 1))
  

Render slices from T1 with a specific value range
=================================================

The T1 has usually a higher range of values than what can be visualized in an
image. We can set the range that we would like to see.

::
  
  mean, std = data[data > 0].mean(), data[data > 0].std()
  value_range = (mean - 0.5 * std, mean + 1.5 * std)
  

The ``slice`` function will read data and resample the data using an affine
transformation matrix. The default behavior of this function is to show the
middle slice of the last dimension of the resampled data.

::
  
  slice_actor = actor.slicer(data, affine, value_range)
  

The ``slice_actor`` contains an axial slice.

::
  
  renderer.add(slice_actor)
  

The same actor can show any different slice from the given data using its
``display`` function. However, if we want to show multiple slices we need to
copy the actor first.

::
  
  slice_actor2 = slice_actor.copy()
  

Now we have a new ``slice_actor`` which displays the middle slice of saggital
plane.

::
  
  slice_actor2.display(slice_actor2.shape[0]/2, None, None)
  
  renderer.add(slice_actor2)
  
  renderer.reset_camera()
  renderer.zoom(1.4)
  

In order to interact with the data you will need to uncomment the line below.

::
  
  # window.show(renderer, size=(600, 600), reset_camera=False)
  

Otherwise, you can save a screenshot using the following command.

::
  
  window.record(renderer, out_path='slices.png', size=(600, 600),
                reset_camera=False)
  

.. figure:: slices.png
   :align: center

   **Simple slice viewer**.

Render slices from FA with your colormap
========================================

It is also possible to set the colormap of your preference. Here we are loading
an FA image and showing it in a non-standard way using an HSV colormap.

::
  
  fname_fa = os.path.join(os.path.expanduser('~'), '.dipy',
                          'exp_bundles_and_maps', 'bundles_2_subjects',
                          'subj_1', 'fa_1x1x1.nii.gz')
  
  img = nib.load(fname_fa)
  fa = img.get_data()
  

Notice here how the scale range is (0, 255) and not (0, 1) which is the usual
range of FA values.

::
  
  lut = actor.colormap_lookup_table(scale_range=(0, 255),
                                    hue_range=(0.4, 1.),
                                    saturation_range=(1, 1.),
                                    value_range=(0., 1.))
  

This is because the lookup table is applied in the slice after interpolating
to (0, 255).

::
  
  fa_actor = actor.slicer(fa, affine, lookup_colormap=lut)
  
  renderer.clear()
  renderer.add(fa_actor)
  
  renderer.reset_camera()
  renderer.zoom(1.4)
  
  # window.show(renderer, size=(600, 600), reset_camera=False)
  
  window.record(renderer, out_path='slices_lut.png', size=(600, 600),
                reset_camera=False)
  

.. figure:: slices_lut.png
   :align: center

   **Simple slice viewer with an HSV colormap**.


Create a mosaic
================

By using the ``copy`` and ``display`` method of the ``slice_actor`` becomes
easy and efficient to create a mosaic of all the slices.

So, let's clear the renderer and change the projection from perspective to
parallel.

::
  
  renderer.clear()
  renderer.projection('parallel')
  

Now we need to create two nested for loops which will set the positions of
the grid of the mosaic and add the new actors to the renderer. We are going
to use 15 columns and 10 rows but you can adjust those with your datasets.

::
  
  cnt = 0
  
  X, Y, Z = slice_actor.shape[:3]
  
  rows = 10
  cols = 15
  border = 10
  
  for j in range(rows):
      for i in range(cols):
          slice_mosaic = slice_actor.copy()
          slice_mosaic.display(None, None, cnt)
          slice_mosaic.SetPosition((X + border) * i,
                                   0.5 * cols * (Y + border) - (Y + border) * j,
                                   0)
          renderer.add(slice_mosaic)
          cnt += 1
          if cnt > Z:
              break
      if cnt > Z:
          break
  
  renderer.reset_camera()
  renderer.zoom(1.6)
  
  # window.show(renderer, size=(900, 600), reset_camera=False)
  

If you uncomment the ``window.show`` line above, you will be able to move the
mosaic up/down and left/right using the middle mouse button pressed. And zoom
in/out using the scroll wheel.

::
  
  window.record(renderer, out_path='mosaic.png', size=(900, 600),
                reset_camera=False)
  

.. figure:: mosaic.png
   :align: center

   **A mosaic of all the slices in the T1 volume**.

        
.. admonition:: Example source code

   You can download :download:`the full source code of this example <./viz_slice.py>`.
   This same script is also included in the dipy source distribution under the
   :file:`doc/examples/` directory.

