d190e8dc4f51f73e9d6b6e2fdf08f9cbfa352c5b,plot_haxby_searchlight.py,,,#,17

Before Change

// Use the fmri mean image as a surrogate of anatomical data
from nilearn import image
mean_fmri = image.mean_img(fmri_img).get_data()

////// Searchlight results
plt.figure(1)
// searchlight.scores_ contains per voxel cross validation scores
s_scores = np.ma.array(searchlight.scores_, mask=np.logical_not(process_mask))
plt.imshow(np.rot90(mean_fmri[..., picked_slice]), interpolation="nearest",
          cmap=plt.cm.gray)
plt.imshow(np.rot90(s_scores[..., picked_slice]), interpolation="nearest",
          cmap=plt.cm.hot, vmax=1)
plt.axis("off")
plt.title("Searchlight")

////// F_score results
plt.figure(2)
p_ma = np.ma.array(p_unmasked, mask=np.logical_not(process_mask))
plt.imshow(np.rot90(mean_fmri[..., picked_slice]), interpolation="nearest",
          cmap=plt.cm.gray)
plt.imshow(np.rot90(p_ma[..., picked_slice]), interpolation="nearest",
          cmap=plt.cm.hot)

After Change

////// F_score results
p_ma = np.ma.array(p_unmasked, mask=np.logical_not(process_mask))
plot_stat_map(nibabel.Nifti1Image(p_ma, 
                                  mean_fmri.get_affine()), mean_fmri, 
              title="F-scores", slicer="z", cut_coords=[-16])

plt.show()

Instances