Plot Haxby masks#

Small script to plot the masks of the Haxby dataset.

plot haxby masks
First subject anatomical nifti image (3D) is at: /home/yasmin/nilearn/nilearn_data/haxby2001/subj2/anat.nii.gz
First subject functional nifti image (4D) is at: /home/yasmin/nilearn/nilearn_data/haxby2001/subj2/bold.nii.gz
/home/yasmin/nilearn/nilearn/nilearn/plotting/displays/ UserWarning: No contour levels were found within the data range.
  im = getattr(ax, type)(data_2d.copy(),
/home/yasmin/nilearn/nilearn/nilearn/plotting/displays/ UserWarning: The following kwargs were not used by contour: 'contours'
  im = getattr(ax, type)(data_2d.copy(),

import matplotlib.pyplot as plt

from nilearn import datasets
haxby_dataset = datasets.fetch_haxby()

# print basic information on the dataset
print('First subject anatomical nifti image (3D) is at: %s' %
print('First subject functional nifti image (4D) is at: %s' %
      haxby_dataset.func[0])  # 4D data

# Build the mean image because we have no anatomic data
from nilearn import image
func_filename = haxby_dataset.func[0]
mean_img = image.mean_img(func_filename)

z_slice = -14

fig = plt.figure(figsize=(4, 5.4), facecolor='k')

from nilearn.plotting import plot_anat, show
display = plot_anat(mean_img, display_mode='z', cut_coords=[z_slice],
mask_vt_filename = haxby_dataset.mask_vt[0]
mask_house_filename = haxby_dataset.mask_house[0]
mask_face_filename = haxby_dataset.mask_face[0]
display.add_contours(mask_vt_filename, contours=1, antialiased=False,
                     linewidths=4., levels=[0], colors=['red'])
display.add_contours(mask_house_filename, contours=1, antialiased=False,
                     linewidths=4., levels=[0], colors=['blue'])
display.add_contours(mask_face_filename, contours=1, antialiased=False,
                     linewidths=4., levels=[0], colors=['limegreen'])

# We generate a legend using the trick described on
from matplotlib.patches import Rectangle
p_v = Rectangle((0, 0), 1, 1, fc="red")
p_h = Rectangle((0, 0), 1, 1, fc="blue")
p_f = Rectangle((0, 0), 1, 1, fc="limegreen")
plt.legend([p_v, p_h, p_f], ["vt", "house", "face"])


Total running time of the script: ( 0 minutes 5.743 seconds)

Estimated memory usage: 914 MB

Gallery generated by Sphinx-Gallery