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satrasatra
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Merge pull request #1276 from effigies/deprecations
RF: Remove deprecated nibabel get_* methods
2 parents 5e1161f + 10ed182 commit 175a6de

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+168
-181
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‎doc/devel/python_interface_devel.rst‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -41,7 +41,7 @@ do is to define inputs, outputs, _run_interface() (not run()), and _list_outputs
4141
thresholded_map = np.zeros(data.shape)
4242
thresholded_map[active_map] = data[active_map]
4343

44-
new_img = nb.Nifti1Image(thresholded_map, img.get_affine(), img.get_header())
44+
new_img = nb.Nifti1Image(thresholded_map, img.affine, img.header)
4545
_, base, _ = split_filename(fname)
4646
nb.save(new_img, base + '_thresholded.nii')
4747

‎examples/dmri_camino_dti.py‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -39,7 +39,7 @@ def get_vox_dims(volume):
3939
if isinstance(volume, list):
4040
volume = volume[0]
4141
nii = nb.load(volume)
42-
hdr = nii.get_header()
42+
hdr = nii.header
4343
voxdims = hdr.get_zooms()
4444
return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])]
4545

@@ -49,15 +49,15 @@ def get_data_dims(volume):
4949
if isinstance(volume, list):
5050
volume = volume[0]
5151
nii = nb.load(volume)
52-
hdr = nii.get_header()
52+
hdr = nii.header
5353
datadims = hdr.get_data_shape()
5454
return [int(datadims[0]), int(datadims[1]), int(datadims[2])]
5555

5656

5757
def get_affine(volume):
5858
import nibabel as nb
5959
nii = nb.load(volume)
60-
return nii.get_affine()
60+
return nii.affine
6161

6262
subject_list = ['subj1']
6363
fsl.FSLCommand.set_default_output_type('NIFTI')

‎examples/dmri_connectivity.py‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -77,7 +77,7 @@ def get_vox_dims(volume):
7777
if isinstance(volume, list):
7878
volume = volume[0]
7979
nii = nb.load(volume)
80-
hdr = nii.get_header()
80+
hdr = nii.header
8181
voxdims = hdr.get_zooms()
8282
return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])]
8383

@@ -87,15 +87,15 @@ def get_data_dims(volume):
8787
if isinstance(volume, list):
8888
volume = volume[0]
8989
nii = nb.load(volume)
90-
hdr = nii.get_header()
90+
hdr = nii.header
9191
datadims = hdr.get_data_shape()
9292
return [int(datadims[0]), int(datadims[1]), int(datadims[2])]
9393

9494

9595
def get_affine(volume):
9696
import nibabel as nb
9797
nii = nb.load(volume)
98-
return nii.get_affine()
98+
return nii.affine
9999

100100

101101
def select_aparc(list_of_files):

‎examples/fmri_ants_openfmri.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -80,8 +80,8 @@ def median(in_files):
8080
average = data
8181
else:
8282
average = average + data
83-
median_img = nb.Nifti1Image(average / float(idx + 1),
84-
img.get_affine(), img.get_header())
83+
median_img = nb.Nifti1Image(average / float(idx + 1), img.affine,
84+
img.header)
8585
filename = os.path.join(os.getcwd(), 'median.nii.gz')
8686
median_img.to_filename(filename)
8787
return filename

‎examples/fmri_fsl.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -108,7 +108,7 @@ def getmiddlevolume(func):
108108
funcfile = func
109109
if isinstance(func, list):
110110
funcfile = func[0]
111-
_, _, _, timepoints = load(funcfile).get_shape()
111+
_, _, _, timepoints = load(funcfile).shape
112112
return int(timepoints / 2) - 1
113113

114114
preproc.connect(inputnode, ('func', getmiddlevolume), extract_ref, 't_min')

‎examples/fmri_spm_auditory.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -123,7 +123,7 @@ def get_vox_dims(volume):
123123
if isinstance(volume, list):
124124
volume = volume[0]
125125
nii = nb.load(volume)
126-
hdr = nii.get_header()
126+
hdr = nii.header
127127
voxdims = hdr.get_zooms()
128128
return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])]
129129

‎examples/fmri_spm_face.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -117,7 +117,7 @@ def get_vox_dims(volume):
117117
if isinstance(volume, list):
118118
volume = volume[0]
119119
nii = nb.load(volume)
120-
hdr = nii.get_header()
120+
hdr = nii.header
121121
voxdims = hdr.get_zooms()
122122
return [float(voxdims[0]), float(voxdims[1]), float(voxdims[2])]
123123

‎examples/rsfmri_vol_surface_preprocessing.py‎

Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -125,8 +125,8 @@ def median(in_files):
125125
average = data
126126
else:
127127
average = average + data
128-
median_img = nb.Nifti1Image(average / float(idx + 1),
129-
img.get_affine(), img.get_header())
128+
median_img = nb.Nifti1Image(average / float(idx + 1), img.affine,
129+
img.header)
130130
filename = os.path.join(os.getcwd(), 'median.nii.gz')
131131
median_img.to_filename(filename)
132132
return filename
@@ -165,8 +165,7 @@ def bandpass_filter(files, lowpass_freq, highpass_freq, fs):
165165
filtered_data = data
166166
else:
167167
filtered_data = np.real(np.fft.ifftn(np.fft.fftn(data) * F))
168-
img_out = nb.Nifti1Image(filtered_data, img.get_affine(),
169-
img.get_header())
168+
img_out = nb.Nifti1Image(filtered_data, img.affine, img.header)
170169
img_out.to_filename(out_file)
171170
out_files.append(out_file)
172171
return list_to_filename(out_files)

‎examples/rsfmri_vol_surface_preprocessing_nipy.py‎

Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -119,8 +119,8 @@ def median(in_files):
119119
average = data
120120
else:
121121
average = average + data
122-
median_img = nb.Nifti1Image(average / float(idx + 1),
123-
img.get_affine(), img.get_header())
122+
median_img = nb.Nifti1Image(average / float(idx + 1), img.affine,
123+
img.header)
124124
filename = os.path.join(os.getcwd(), 'median.nii.gz')
125125
median_img.to_filename(filename)
126126
return filename
@@ -156,8 +156,7 @@ def bandpass_filter(files, lowpass_freq, highpass_freq, fs):
156156
filtered_data = data
157157
else:
158158
filtered_data = np.real(np.fft.ifftn(np.fft.fftn(data) * F))
159-
img_out = nb.Nifti1Image(filtered_data, img.get_affine(),
160-
img.get_header())
159+
img_out = nb.Nifti1Image(filtered_data, img.affine, img.header)
161160
img_out.to_filename(out_file)
162161
out_files.append(out_file)
163162
return list_to_filename(out_files)

‎nipype/algorithms/icc.py‎

Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -49,19 +49,19 @@ def _run_interface(self, runtime):
4949
icc[x], subject_var[x], session_var[x], session_F[x], _, _ = ICC_rep_anova(Y)
5050

5151
nim = nb.load(self.inputs.subjects_sessions[0][0])
52-
new_data = np.zeros(nim.get_shape())
52+
new_data = np.zeros(nim.shape)
5353
new_data[maskdata] = icc.reshape(-1,)
54-
new_img = nb.Nifti1Image(new_data, nim.get_affine(), nim.get_header())
54+
new_img = nb.Nifti1Image(new_data, nim.affine, nim.header)
5555
nb.save(new_img, 'icc_map.nii')
5656

57-
new_data = np.zeros(nim.get_shape())
57+
new_data = np.zeros(nim.shape)
5858
new_data[maskdata] = session_var.reshape(-1,)
59-
new_img = nb.Nifti1Image(new_data, nim.get_affine(), nim.get_header())
59+
new_img = nb.Nifti1Image(new_data, nim.affine, nim.header)
6060
nb.save(new_img, 'session_var_map.nii')
6161

62-
new_data = np.zeros(nim.get_shape())
62+
new_data = np.zeros(nim.shape)
6363
new_data[maskdata] = subject_var.reshape(-1,)
64-
new_img = nb.Nifti1Image(new_data, nim.get_affine(), nim.get_header())
64+
new_img = nb.Nifti1Image(new_data, nim.affine, nim.header)
6565
nb.save(new_img, 'subject_var_map.nii')
6666

6767
return runtime

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