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Merge branch 'master' of git://github.com/nipy/nipype
2 parents c09c47f + c13f967 commit 507c514

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‎.zenodo.json

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@@ -170,7 +170,7 @@
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},
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{
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"affiliation": "California Institute of Technology",
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"name": "PAULI, WOLFGANG M.",
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"name": "Pauli, Wolfgang M.",
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"orcid": "0000-0002-0966-0254"
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},
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{

‎README.rst

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@@ -33,6 +33,9 @@ NIPYPE: Neuroimaging in Python: Pipelines and Interfaces
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.. image:: https://img.shields.io/badge/gitter-join%20chat%20%E2%86%92-brightgreen.svg?style=flat
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:target: http://gitter.im/nipy/nipype
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:alt: Chat
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.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.581704.svg
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:target: https://doi.org/10.5281/zenodo.581704
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Current neuroimaging software offer users an incredible opportunity to
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analyze data using a variety of different algorithms. However, this has

‎circle.yml

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@@ -1,4 +1,6 @@
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machine:
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pre:
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- curl -sSL https://s3.amazonaws.com/circle-downloads/install-circleci-docker.sh | bash -s -- 1.10.0
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environment:
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OSF_NIPYPE_URL: "https://files.osf.io/v1/resources/nefdp/providers/osfstorage"
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DATA_NIPYPE_TUTORIAL_URL: "${OSF_NIPYPE_URL}/57f4739cb83f6901ed94bf21"

‎nipype/algorithms/confounds.py

Lines changed: 9 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -398,7 +398,7 @@ def _run_interface(self, runtime):
398398
if len(mask_images) == 0:
399399
img = nb.Nifti1Image(np.ones(imgseries.shape[:3], dtype=np.bool),
400400
affine=imgseries.affine,
401-
header=imgseries.get_header())
401+
header=imgseries.header)
402402
mask_images = [img]
403403

404404
mask_images = self._process_masks(mask_images, imgseries.get_data())
@@ -501,7 +501,7 @@ def _process_masks(self, mask_images, timeseries=None):
501501
mask_data = np.zeros_like(mask)
502502
mask_data[mask != 0] = tSTD >= threshold_std
503503
out_image = nb.Nifti1Image(mask_data, affine=img.affine,
504-
header=img.get_header())
504+
header=img.header)
505505

506506
# save mask
507507
mask_file = os.path.abspath('mask_{:03d}.nii.gz'.format(i))
@@ -561,7 +561,7 @@ def _run_interface(self, runtime):
561561
header = img.header.copy()
562562
vollist = [nb.load(filename, mmap=NUMPY_MMAP) for filename in self.inputs.in_file]
563563
data = np.concatenate([vol.get_data().reshape(
564-
vol.get_shape()[:3] + (-1,)) for vol in vollist], axis=3)
564+
vol.shape[:3] + (-1,)) for vol in vollist], axis=3)
565565
data = np.nan_to_num(data)
566566

567567
if data.dtype.kind == 'i':
@@ -570,18 +570,18 @@ def _run_interface(self, runtime):
570570

571571
if isdefined(self.inputs.regress_poly):
572572
data = regress_poly(self.inputs.regress_poly, data, remove_mean=False)
573-
img = nb.Nifti1Image(data, img.get_affine(), header)
573+
img = nb.Nifti1Image(data, img.affine, header)
574574
nb.save(img, op.abspath(self.inputs.detrended_file))
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576576
meanimg = np.mean(data, axis=3)
577577
stddevimg = np.std(data, axis=3)
578578
tsnr = np.zeros_like(meanimg)
579579
tsnr[stddevimg > 1.e-3] = meanimg[stddevimg > 1.e-3] / stddevimg[stddevimg > 1.e-3]
580-
img = nb.Nifti1Image(tsnr, img.get_affine(), header)
580+
img = nb.Nifti1Image(tsnr, img.affine, header)
581581
nb.save(img, op.abspath(self.inputs.tsnr_file))
582-
img = nb.Nifti1Image(meanimg, img.get_affine(), header)
582+
img = nb.Nifti1Image(meanimg, img.affine, header)
583583
nb.save(img, op.abspath(self.inputs.mean_file))
584-
img = nb.Nifti1Image(stddevimg, img.get_affine(), header)
584+
img = nb.Nifti1Image(stddevimg, img.affine, header)
585585
nb.save(img, op.abspath(self.inputs.stddev_file))
586586
return runtime
587587

@@ -872,7 +872,7 @@ def combine_mask_files(mask_files, mask_method=None, mask_index=None):
872872
if mask is None:
873873
mask = img.get_data() > 0
874874
np.logical_or(mask, img.get_data() > 0, mask)
875-
img = nb.Nifti1Image(mask, img.affine, header=img.get_header())
875+
img = nb.Nifti1Image(mask, img.affine, header=img.header)
876876
return [img]
877877

878878
if mask_method == 'intersect':
@@ -882,7 +882,7 @@ def combine_mask_files(mask_files, mask_method=None, mask_index=None):
882882
if mask is None:
883883
mask = img.get_data() > 0
884884
np.logical_and(mask, img.get_data() > 0, mask)
885-
img = nb.Nifti1Image(mask, img.affine, header=img.get_header())
885+
img = nb.Nifti1Image(mask, img.affine, header=img.header)
886886
return [img]
887887

888888

‎nipype/algorithms/tests/test_tsnr.py

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@@ -113,7 +113,7 @@ def assert_default_outputs(self, outputs):
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114114
def assert_unchanged(self, expected_ranges):
115115
for key, (min_, max_) in expected_ranges.items():
116-
data = np.asarray(nb.load(self.out_filenames[key])._data)
116+
data = np.asarray(nb.load(self.out_filenames[key]).dataobj)
117117
npt.assert_almost_equal(np.amin(data), min_, decimal=1)
118118
npt.assert_almost_equal(np.amax(data), max_, decimal=1)
119119

‎nipype/caching/memory.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -70,7 +70,7 @@ def __call__(self, **kwargs):
7070
kwargs = modify_paths(kwargs, relative=False)
7171
interface = self.interface()
7272
# Set the inputs early to get some argument checking
73-
interface.inputs.set(**kwargs)
73+
interface.inputs.trait_set(**kwargs)
7474
# Make a name for our node
7575
inputs = interface.inputs.get_hashval()
7676
hasher = hashlib.new('md5')

‎nipype/info.py

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@@ -45,7 +45,7 @@ def get_nipype_gitversion():
4545
if __version__.endswith('-dev'):
4646
gitversion = get_nipype_gitversion()
4747
if gitversion:
48-
__version__ = __version__.replace('-dev', '-' + gitversion + '.dev')
48+
__version__ = '{}+{}'.format(__version__, gitversion)
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5050
CLASSIFIERS = ['Development Status :: 5 - Production/Stable',
5151
'Environment :: Console',
@@ -141,7 +141,8 @@ def get_nipype_gitversion():
141141
'funcsigs',
142142
'pytest>=%s' % PYTEST_MIN_VERSION,
143143
'mock',
144-
'pydotplus'
144+
'pydotplus',
145+
'packaging',
145146
]
146147

147148
if sys.version_info <= (3, 4):

‎nipype/interfaces/afni/utils.py

Lines changed: 1 addition & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -171,13 +171,10 @@ def aggregate_outputs(self, runtime=None, needed_outputs=None):
171171
m = re.search(pattern, line)
172172
if m:
173173
d = m.groupdict()
174-
for k in list(d.keys()):
175-
d[k] = int(d[k])
176-
outputs.set(**d)
174+
outputs.trait_set(**{k: int(d[k]) for k in d.keys()})
177175
return outputs
178176

179177

180-
181178
class BrickStatInputSpec(CommandLineInputSpec):
182179
in_file = File(
183180
desc='input file to 3dmaskave',

‎nipype/interfaces/base.py

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Original file line numberDiff line numberDiff line change
@@ -31,6 +31,7 @@
3131
from warnings import warn
3232
import simplejson as json
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from dateutil.parser import parse as parseutc
34+
from packaging.version import Version
3435

3536
from .. import config, logging, LooseVersion, __version__
3637
from ..utils.provenance import write_provenance
@@ -43,7 +44,7 @@
4344
from ..external.due import due
4445

4546
runtime_profile = str2bool(config.get('execution', 'profile_runtime'))
46-
nipype_version = LooseVersion(__version__)
47+
nipype_version = Version(__version__)
4748
iflogger = logging.getLogger('interface')
4849

4950
FLOAT_FORMAT = '{:.10f}'.format
@@ -352,6 +353,7 @@ class BaseTraitedSpec(traits.HasTraits):
352353
XXX Reconsider this in the long run, but it seems like the best
353354
solution to move forward on the refactoring.
354355
"""
356+
package_version = nipype_version
355357

356358
def __init__(self, **kwargs):
357359
""" Initialize handlers and inputs"""
@@ -367,7 +369,7 @@ def __init__(self, **kwargs):
367369
undefined_traits[trait] = Undefined
368370
self.trait_set(trait_change_notify=False, **undefined_traits)
369371
self._generate_handlers()
370-
self.set(**kwargs)
372+
self.trait_set(**kwargs)
371373

372374
def items(self):
373375
""" Name, trait generator for user modifiable traits
@@ -444,7 +446,7 @@ def _deprecated_warn(self, obj, name, old, new):
444446
else:
445447
msg3 = ''
446448
msg = ' '.join((msg1, msg2, msg3))
447-
if LooseVersion(str(trait_spec.deprecated)) < nipype_version:
449+
if Version(str(trait_spec.deprecated)) < self.package_version:
448450
raise TraitError(msg)
449451
else:
450452
if trait_spec.new_name:
@@ -650,7 +652,7 @@ def __deepcopy__(self, memo):
650652
pass
651653
# clone twice
652654
dup = self.clone_traits(memo=memo)
653-
dup.set(**dup_dict)
655+
dup.trait_set(**dup_dict)
654656
return dup
655657

656658

@@ -1060,7 +1062,7 @@ def run(self, **inputs):
10601062
results : an InterfaceResult object containing a copy of the instance
10611063
that was executed, provenance information and, if successful, results
10621064
"""
1063-
self.inputs.set(**inputs)
1065+
self.inputs.trait_set(**inputs)
10641066
self._check_mandatory_inputs()
10651067
self._check_version_requirements(self.inputs)
10661068
interface = self.__class__

‎nipype/interfaces/dipy/reconstruction.py

Lines changed: 8 additions & 8 deletions
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@@ -74,8 +74,8 @@ def _run_interface(self, runtime):
7474
import gc
7575

7676
img = nb.load(self.inputs.in_file)
77-
hdr = img.get_header().copy()
78-
affine = img.get_affine()
77+
hdr = img.header.copy()
78+
affine = img.affine
7979
data = img.get_data()
8080
gtab = self._get_gradient_table()
8181

@@ -210,14 +210,14 @@ def _run_interface(self, runtime):
210210

211211
img = nb.load(self.inputs.in_file)
212212
imref = nb.four_to_three(img)[0]
213-
affine = img.get_affine()
213+
affine = img.affine
214214

215215
if isdefined(self.inputs.in_mask):
216216
msk = nb.load(self.inputs.in_mask).get_data()
217217
msk[msk > 0] = 1
218218
msk[msk < 0] = 0
219219
else:
220-
msk = np.ones(imref.get_shape())
220+
msk = np.ones(imref.shape)
221221

222222
data = img.get_data().astype(np.float32)
223223
gtab = self._get_gradient_table()
@@ -326,15 +326,15 @@ def _run_interface(self, runtime):
326326

327327
img = nb.load(self.inputs.in_file)
328328
imref = nb.four_to_three(img)[0]
329-
affine = img.get_affine()
329+
affine = img.affine
330330

331331
if isdefined(self.inputs.in_mask):
332332
msk = nb.load(self.inputs.in_mask).get_data()
333333
else:
334-
msk = np.ones(imref.get_shape())
334+
msk = np.ones(imref.shape)
335335

336336
data = img.get_data().astype(np.float32)
337-
hdr = imref.get_header().copy()
337+
hdr = imref.header.copy()
338338

339339
gtab = self._get_gradient_table()
340340
resp_file = np.loadtxt(self.inputs.response)
@@ -359,7 +359,7 @@ def _run_interface(self, runtime):
359359
if self.inputs.save_fods:
360360
sphere = get_sphere('symmetric724')
361361
fods = csd_fit.odf(sphere)
362-
nb.Nifti1Image(fods.astype(np.float32), img.get_affine(),
362+
nb.Nifti1Image(fods.astype(np.float32), img.affine,
363363
None).to_filename(self._gen_filename('fods'))
364364

365365
return runtime

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