Trying to fix up examples for nibabel

examples/.gitignore

@@ -0,0 +1,6 @@
+# Generated data files
+ammon_TO_anubis.npy
+labs/fmri_data.nii
+labs/localizer_paradigm.csv
+labs/need_data/results/
+labs/zmap.nii

examples/compute_fmri_contrast.py

@@ -77,9 +77,9 @@
 # Show Z-map image
 mean_map = multi_session_model.means[0]
 plot_map(z_map.get_fdata(),
-         z_map.get_affine(),
+         z_map.affine,
          anat=mean_map.get_fdata(),
-         anat_affine=mean_map.get_affine(),
+         anat_affine=mean_map.affine,
          cmap=cm.cold_hot,
          threshold=2.5,
          black_bg=True)

examples/data/README_mni_basal_ganglia.rst

@@ -21,7 +21,7 @@ The script to extract the data was::
                         'AtlasGrey.mnc')
     atlas_img = nib.load(atlas_fname)
     # Data is in fact uint8, but with trivial float scaling
-    data = atlas_img.get_data().astype(np.uint8)
+    data = np.array(atlas_img.dataobj).astype(np.uint8)
     bg_data = np.zeros_like(data)
     for code in (14, 16, 39, 53): # LR striatum, LR caudate
         in_mask = data == code

examples/labs/need_data/demo_blob_from_image.py

@@ -38,7 +38,7 @@
 # prepare the data
 nim = load(input_image)
 mask_image = Nifti1Image((nim.get_fdata() ** 2 > 0).astype('u8'),
-                         nim.get_affine())
+                         nim.affine)
 domain = grid_domain_from_image(mask_image)
 data = nim.get_fdata()
 values = data[data != 0]

examples/labs/need_data/demo_roi.py

@@ -63,7 +63,7 @@
 
 # prepare the data
 nim = load(input_image)
-affine = nim.get_affine()
+affine = nim.affine
 shape = nim.shape
 data = nim.get_fdata()
 values = data[data != 0]

examples/labs/need_data/demo_ward_clustering.py

@@ -43,5 +43,5 @@
 label_image = path.join(write_dir, 'label.nii')
 wdata = mask - 1
 wdata[mask] = u
-save(Nifti1Image(wdata, load(mask_image).get_affine()), label_image)
+save(Nifti1Image(wdata, load(mask_image).affine), label_image)
 print(f"Label image written in {label_image}")

examples/labs/need_data/example_roi_and_glm.py

@@ -48,7 +48,7 @@
     get_second_level_dataset()
 
 mask = load(mask_path)
-mask_array, affine = mask.get_fdata() > 0, mask.get_affine()
+mask_array, affine = mask.get_fdata() > 0, mask.affine
 
 # timing
 n_scans = 128

examples/labs/need_data/first_level_fiac.py

@@ -95,8 +95,8 @@ def length_p_vector(con, p):
     if contrast_id == 'Effects_of_interest':
         vmax = max(- z_map.get_fdata().min(), z_map.get_fdata().max())
         vmin = - vmax
-        plot_map(z_map.get_fdata(), z_map.get_affine(),
-                 anat=mean_map.get_fdata(), anat_affine=mean_map.get_affine(),
+        plot_map(z_map.get_fdata(), z_map.affine,
+                 anat=mean_map.get_fdata(), anat_affine=mean_map.affine,
                  cmap=cm.cold_hot,
                  vmin=vmin,
                  vmax=vmax,

examples/labs/need_data/localizer_glm_ar.py

@@ -142,7 +142,7 @@
     vmax = max(- z_map.get_fdata().min(), z_map.get_fdata().max())
     if index > 0:
         plt.clf()
-    plot_map(z_map.get_fdata(), z_map.get_affine(),
+    plot_map(z_map.get_fdata(), z_map.affine,
              cmap=cm.cold_hot,
              vmin=- vmax,
              vmax=vmax,

examples/labs/need_data/one_sample_t_test.py

@@ -54,7 +54,7 @@
 
 # Compute a population-level mask as the intersection of individual masks
 grp_mask = Nifti1Image(intersect_masks(mask_images).astype(np.int8),
-                       load(mask_images[0]).get_affine())
+                       load(mask_images[0]).affine)
 
 # concatenate the individual images
 first_level_image = concat_images(betas)
@@ -76,7 +76,7 @@
 # look at the result
 vmax = max(- z_map.get_fdata().min(), z_map.get_fdata().max())
 vmin = - vmax
-plot_map(z_map.get_fdata(), z_map.get_affine(),
+plot_map(z_map.get_fdata(), z_map.affine,
          cmap=cm.cold_hot,
          vmin=vmin,
          vmax=vmax,

examples/labs/need_data/viz.py

@@ -30,7 +30,7 @@
 # First example, with a anatomical template
 img = load(os.path.join(data_dir, 'spmT_0029.nii.gz'))
 data = img.get_fdata()
-affine = img.get_affine()
+affine = img.affine
 
 viz.plot_map(data, affine, cut_coords=(-52, 10, 22),
                         threshold=2.0, cmap=viz.cm.cold_hot)
@@ -41,7 +41,7 @@
     anat_img = load(example_data.get_filename('neurospin', 'sulcal2000',
                                               'nobias_anubis.nii.gz'))
     anat = anat_img.get_fdata()
-    anat_affine = anat_img.get_affine()
+    anat_affine = anat_img.affine
 except OSError as e:
     # File does not exist: the data package is not installed
     print(e)

examples/labs/need_data/viz3d.py

@@ -36,7 +36,7 @@
 vmin, vmax = brain_map.get_fdata().min(), brain_map.get_fdata().max()
 
 # make a simple 2D plot
-plot_map(brain_map.get_fdata(), brain_map.get_affine(),
+plot_map(brain_map.get_fdata(), brain_map.affine,
          cmap=cm.cold_hot,
          vmin=vmin,
          vmax=vmax,
@@ -46,7 +46,7 @@
 
 # More plots using 3D
 if True:  # replace with False to skip this
-    plot_map(brain_map.get_fdata(), brain_map.get_affine(),
+    plot_map(brain_map.get_fdata(), brain_map.affine,
              cmap=cm.cold_hot,
              vmin=vmin,
              vmax=vmax,
@@ -56,7 +56,7 @@
 
     from nipy.labs import viz3d
     try:
-        viz3d.plot_map_3d(brain_map.get_fdata(), brain_map.get_affine(),
+        viz3d.plot_map_3d(brain_map.get_fdata(), brain_map.affine,
                         cmap=cm.cold_hot,
                         vmin=vmin,
                         vmax=vmax,