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RF: Drop NUMPY_MMAP from surrounding code
1 parent de8785b commit c613c7d

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9 files changed

+28
-28
lines changed

9 files changed

+28
-28
lines changed

nipype/algorithms/confounds.py

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -920,7 +920,7 @@ def _run_interface(self, runtime):
920920
img = nb.load(self.inputs.in_file[0], mmap=NUMPY_MMAP)
921921
header = img.header.copy()
922922
vollist = [
923-
nb.load(filename, mmap=NUMPY_MMAP) for filename in self.inputs.in_file
923+
nb.load(filename) for filename in self.inputs.in_file
924924
]
925925
data = np.concatenate(
926926
[
@@ -1035,8 +1035,8 @@ def compute_dvars(
10351035
from nitime.algorithms import AR_est_YW
10361036
import warnings
10371037

1038-
func = nb.load(in_file, mmap=NUMPY_MMAP).get_fdata(dtype=np.float32)
1039-
mask = np.asanyarray(nb.load(in_mask, mmap=NUMPY_MMAP).dataobj).astype(np.uint8)
1038+
func = nb.load(in_file).get_fdata(dtype=np.float32)
1039+
mask = np.asanyarray(nb.load(in_mask).dataobj).astype(np.uint8)
10401040

10411041
if len(func.shape) != 4:
10421042
raise RuntimeError("Input fMRI dataset should be 4-dimensional")
@@ -1281,7 +1281,7 @@ def combine_mask_files(mask_files, mask_method=None, mask_index=None):
12811281
if mask_method == "union":
12821282
mask = None
12831283
for filename in mask_files:
1284-
img = nb.load(filename, mmap=NUMPY_MMAP)
1284+
img = nb.load(filename)
12851285
if mask is None:
12861286
mask = img.get_fdata() > 0
12871287
np.logical_or(mask, img.get_fdata() > 0, mask)
@@ -1291,7 +1291,7 @@ def combine_mask_files(mask_files, mask_method=None, mask_index=None):
12911291
if mask_method == "intersect":
12921292
mask = None
12931293
for filename in mask_files:
1294-
img = nb.load(filename, mmap=NUMPY_MMAP)
1294+
img = nb.load(filename)
12951295
if mask is None:
12961296
mask = img.get_fdata() > 0
12971297
np.logical_and(mask, img.get_fdata() > 0, mask)

nipype/algorithms/misc.py

Lines changed: 8 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -152,7 +152,7 @@ class SimpleThreshold(BaseInterface):
152152

153153
def _run_interface(self, runtime):
154154
for fname in self.inputs.volumes:
155-
img = nb.load(fname, mmap=NUMPY_MMAP)
155+
img = nb.load(fname)
156156
data = img.get_fdata()
157157

158158
active_map = data > self.inputs.threshold
@@ -1269,7 +1269,7 @@ def normalize_tpms(in_files, in_mask=None, out_files=None):
12691269
out_file = op.abspath("%s_norm_%02d%s" % (fname, i, fext))
12701270
out_files += [out_file]
12711271

1272-
imgs = [nb.load(fim, mmap=NUMPY_MMAP) for fim in in_files]
1272+
imgs = [nb.load(fim) for fim in in_files]
12731273

12741274
if len(in_files) == 1:
12751275
img_data = imgs[0].get_fdata(dtype=np.float32)
@@ -1290,7 +1290,7 @@ def normalize_tpms(in_files, in_mask=None, out_files=None):
12901290
msk[weights <= 0] = 0
12911291

12921292
if in_mask is not None:
1293-
msk = np.asanyarray(nb.load(in_mask, mmap=NUMPY_MMAP).dataobj)
1293+
msk = np.asanyarray(nb.load(in_mask).dataobj)
12941294
msk[msk <= 0] = 0
12951295
msk[msk > 0] = 1
12961296

@@ -1328,7 +1328,7 @@ def split_rois(in_file, mask=None, roishape=None):
13281328
droishape = (roishape[0], roishape[1], roishape[2], nvols)
13291329

13301330
if mask is not None:
1331-
mask = np.asanyarray(nb.load(mask, mmap=NUMPY_MMAP).dataobj)
1331+
mask = np.asanyarray(nb.load(mask).dataobj)
13321332
mask[mask > 0] = 1
13331333
mask[mask < 1] = 0
13341334
else:
@@ -1432,7 +1432,7 @@ def merge_rois(in_files, in_idxs, in_ref, dtype=None, out_file=None):
14321432
for cname, iname in zip(in_files, in_idxs):
14331433
f = np.load(iname)
14341434
idxs = np.squeeze(f["arr_0"])
1435-
cdata = np.asanyarray(nb.load(cname, mmap=NUMPY_MMAP).dataobj).reshape(
1435+
cdata = np.asanyarray(nb.load(cname).dataobj).reshape(
14361436
-1, ndirs
14371437
)
14381438
nels = len(idxs)
@@ -1464,10 +1464,10 @@ def merge_rois(in_files, in_idxs, in_ref, dtype=None, out_file=None):
14641464
idxs = np.squeeze(f["arr_0"])
14651465

14661466
for d, fname in enumerate(nii):
1467-
data = np.asanyarray(nb.load(fname, mmap=NUMPY_MMAP).dataobj).reshape(
1467+
data = np.asanyarray(nb.load(fname).dataobj).reshape(
14681468
-1
14691469
)
1470-
cdata = nb.load(cname, mmap=NUMPY_MMAP).dataobj[..., d].reshape(-1)
1470+
cdata = nb.load(cname).dataobj[..., d].reshape(-1)
14711471
nels = len(idxs)
14721472
idata = (idxs,)
14731473
data[idata] = cdata[0:nels]
@@ -1547,7 +1547,7 @@ def _run_interface(self, runtime):
15471547
total = None
15481548
self._median_files = []
15491549
for idx, fname in enumerate(ensure_list(self.inputs.in_files)):
1550-
img = nb.load(fname, mmap=NUMPY_MMAP)
1550+
img = nb.load(fname)
15511551
data = np.median(img.get_fdata(), axis=3)
15521552
if self.inputs.median_per_file:
15531553
self._median_files.append(self._write_nifti(img, data, idx))

nipype/algorithms/rapidart.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -525,7 +525,7 @@ def _detect_outliers_core(self, imgfile, motionfile, runidx, cwd=None):
525525
mask[:, :, :, t0] = mask_tmp
526526
g[t0] = np.nansum(vol * mask_tmp) / np.nansum(mask_tmp)
527527
elif masktype == "file": # uses a mask image to determine intensity
528-
maskimg = load(self.inputs.mask_file, mmap=NUMPY_MMAP)
528+
maskimg = load(self.inputs.mask_file)
529529
mask = maskimg.get_fdata()
530530
affine = maskimg.affine
531531
mask = mask > 0.5

nipype/algorithms/tests/test_normalize_tpms.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -19,7 +19,7 @@
1919
def test_normalize_tpms(tmpdir):
2020

2121
in_mask = example_data("tpms_msk.nii.gz")
22-
mskdata = np.asanyarray(nb.load(in_mask, mmap=NUMPY_MMAP).dataobj)
22+
mskdata = np.asanyarray(nb.load(in_mask).dataobj)
2323
mskdata[mskdata > 0.0] = 1.0
2424

2525
mapdata = []
@@ -31,7 +31,7 @@ def test_normalize_tpms(tmpdir):
3131
filename = tmpdir.join("modtpm_%02d.nii.gz" % i).strpath
3232
out_files.append(tmpdir.join("normtpm_%02d.nii.gz" % i).strpath)
3333

34-
im = nb.load(mapname, mmap=NUMPY_MMAP)
34+
im = nb.load(mapname)
3535
data = im.get_fdata()
3636
mapdata.append(data)
3737

@@ -45,7 +45,7 @@ def test_normalize_tpms(tmpdir):
4545
sumdata = np.zeros_like(mskdata)
4646

4747
for i, tstfname in enumerate(out_files):
48-
normdata = nb.load(tstfname, mmap=NUMPY_MMAP).get_fdata()
48+
normdata = nb.load(tstfname).get_fdata()
4949
sumdata += normdata
5050
assert np.all(normdata[mskdata == 0] == 0)
5151
assert np.allclose(normdata, mapdata[i])

nipype/algorithms/tests/test_splitmerge.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -15,7 +15,7 @@ def test_split_and_merge(tmpdir):
1515

1616
in_mask = example_data("tpms_msk.nii.gz")
1717
dwfile = tmpdir.join("dwi.nii.gz").strpath
18-
mask_img = nb.load(in_mask, mmap=NUMPY_MMAP)
18+
mask_img = nb.load(in_mask)
1919
mskdata = np.asanyarray(mask_img.dataobj)
2020
aff = mask_img.affine
2121

@@ -26,7 +26,7 @@ def test_split_and_merge(tmpdir):
2626

2727
resdw, resmsk, resid = split_rois(dwfile, in_mask, roishape=(20, 20, 2))
2828
merged = merge_rois(resdw, resid, in_mask)
29-
dwmerged = nb.load(merged, mmap=NUMPY_MMAP).get_fdata(dtype=np.float32)
29+
dwmerged = nb.load(merged).get_fdata(dtype=np.float32)
3030

3131
dwmasked = dwdata * mskdata[:, :, :, np.newaxis]
3232

nipype/interfaces/cmtk/cmtk.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -200,7 +200,7 @@ def cmat(
200200
fib, hdr = nb.trackvis.read(track_file, False)
201201
stats["orig_n_fib"] = len(fib)
202202

203-
roi = nb.load(roi_file, mmap=NUMPY_MMAP)
203+
roi = nb.load(roi_file)
204204
# Preserve on-disk type unless scaled
205205
roiData = np.asanyarray(roi.dataobj)
206206
roiVoxelSize = roi.header.get_zooms()
@@ -838,7 +838,7 @@ def _run_interface(self, runtime):
838838
aparc_aseg_file = self.inputs.aparc_aseg_file
839839
aparcpath, aparcname, aparcext = split_filename(aparc_aseg_file)
840840
iflogger.info("Using Aparc+Aseg file: %s", aparcname + aparcext)
841-
niiAPARCimg = nb.load(aparc_aseg_file, mmap=NUMPY_MMAP)
841+
niiAPARCimg = nb.load(aparc_aseg_file)
842842
# Preserve on-disk type
843843
niiAPARCdata = np.asanyarray(niiAPARCimg.dataobj)
844844
niiDataLabels = np.unique(niiAPARCdata)
@@ -1056,7 +1056,7 @@ def _gen_outfilename(self, ext):
10561056
def create_nodes(roi_file, resolution_network_file, out_filename):
10571057
G = nx.Graph()
10581058
gp = nx.read_graphml(resolution_network_file)
1059-
roi_image = nb.load(roi_file, mmap=NUMPY_MMAP)
1059+
roi_image = nb.load(roi_file)
10601060
# Preserve on-disk type unless scaled
10611061
roiData = np.asanyarray(roi_image.dataobj)
10621062
for u, d in gp.nodes(data=True):

nipype/interfaces/dipy/simulate.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -142,7 +142,7 @@ def _run_interface(self, runtime):
142142
nballs = len(self.inputs.in_vfms)
143143
vfs = np.squeeze(
144144
nb.concat_images(
145-
[nb.load(f, mmap=NUMPY_MMAP) for f in self.inputs.in_vfms]
145+
self.inputs.in_vfms
146146
).dataobj
147147
)
148148
if nballs == 1:
@@ -163,7 +163,7 @@ def _run_interface(self, runtime):
163163

164164
# Fiber fractions
165165
ffsim = nb.concat_images(
166-
[nb.load(f, mmap=NUMPY_MMAP) for f in self.inputs.in_frac]
166+
self.inputs.in_frac
167167
)
168168
ffs = np.nan_to_num(np.squeeze(ffsim.dataobj)) # fiber fractions
169169
ffs = np.clip(ffs, 0.0, 1.0)
@@ -207,7 +207,7 @@ def _run_interface(self, runtime):
207207
dirs = None
208208
for i in range(nsticks):
209209
f = self.inputs.in_dirs[i]
210-
fd = np.nan_to_num(nb.load(f, mmap=NUMPY_MMAP).dataobj)
210+
fd = np.nan_to_num(nb.load(f).dataobj)
211211
w = np.linalg.norm(fd, axis=3)[..., np.newaxis]
212212
w[w < np.finfo(float).eps] = 1.0
213213
fd /= w

nipype/interfaces/freesurfer/tests/test_model.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -37,7 +37,7 @@ def test_concatenate(tmpdir):
3737
# Test specified concatenated_file
3838
res = model.Concatenate(in_files=[in1, in2], concatenated_file=out).run()
3939
assert res.outputs.concatenated_file == tmpdir.join(out).strpath
40-
assert np.allclose(nb.load(out, mmap=NUMPY_MMAP).get_fdata(), out_data)
40+
assert np.allclose(nb.load(out).get_fdata(), out_data)
4141

4242
# Test in workflow
4343
wf = pe.Workflow("test_concatenate", base_dir=tmpdir.strpath)
@@ -55,4 +55,4 @@ def test_concatenate(tmpdir):
5555
res = model.Concatenate(
5656
in_files=[in1, in2], concatenated_file=out, stats="mean"
5757
).run()
58-
assert np.allclose(nb.load(out, mmap=NUMPY_MMAP).get_fdata(), mean_data)
58+
assert np.allclose(nb.load(out).get_fdata(), mean_data)

nipype/interfaces/nipy/preprocess.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -57,7 +57,7 @@ def _run_interface(self, runtime):
5757
value = getattr(self.inputs, key)
5858
if isdefined(value):
5959
if key in ["mean_volume", "reference_volume"]:
60-
value = np.asanyarray(nb.load(value, mmap=NUMPY_MMAP).dataobj)
60+
value = np.asanyarray(nb.load(value).dataobj)
6161
args[key] = value
6262

6363
brain_mask = compute_mask(**args)

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