more NUMPY_MMAP fixes

Author: oesteban

nipype/algorithms/modelgen.py

@@ -28,6 +28,7 @@
 import numpy as np
 from scipy.special import gammaln
 
+from ..utils import NUMPY_MMAP
 from ..interfaces.base import (BaseInterface, TraitedSpec, InputMultiPath,
                                traits, File, Bunch, BaseInterfaceInputSpec,
                                isdefined)
@@ -354,7 +355,7 @@ def _generate_standard_design(self, infolist,
             for i, out in enumerate(outliers):
                 numscans = 0
                 for f in filename_to_list(sessinfo[i]['scans']):
-                    shape = load(f).shape
+                    shape = load(f, mmap=NUMPY_MMAP).shape
                     if len(shape) == 3 or shape[3] == 1:
                         iflogger.warning(("You are using 3D instead of 4D "
                                           "files. Are you sure this was "
@@ -457,7 +458,7 @@ def _concatenate_info(self, infolist):
             if isinstance(f, list):
                 numscans = len(f)
             elif isinstance(f, (str, bytes)):
-                img = load(f)
+                img = load(f, mmap=NUMPY_MMAP)
                 numscans = img.shape[3]
             else:
                 raise Exception('Functional input not specified correctly')
@@ -781,7 +782,7 @@ def _generate_clustered_design(self, infolist):
             infoout[i].onsets = None
             infoout[i].durations = None
             if info.conditions:
-                img = load(self.inputs.functional_runs[i])
+                img = load(self.inputs.functional_runs[i], mmap=NUMPY_MMAP)
                 nscans = img.shape[3]
                 reg, regnames = self._cond_to_regress(info, nscans)
                 if hasattr(infoout[i], 'regressors') and infoout[i].regressors:

nipype/workflows/fmri/fsl/preprocess.py

@@ -28,19 +28,21 @@ def pickfirst(files):
 def pickmiddle(files):
     from nibabel import load
     import numpy as np
+    from nipype.utils import NUMPY_MMAP
     middlevol = []
     for f in files:
-        middlevol.append(int(np.ceil(load(f).shape[3] / 2)))
+        middlevol.append(int(np.ceil(load(f, mmap=NUMPY_MMAP).shape[3] / 2)))
     return middlevol
 
 
 def pickvol(filenames, fileidx, which):
     from nibabel import load
     import numpy as np
+    from nipype.utils import NUMPY_MMAP
     if which.lower() == 'first':
         idx = 0
     elif which.lower() == 'middle':
-        idx = int(np.ceil(load(filenames[fileidx]).shape[3] / 2))
+        idx = int(np.ceil(load(filenames[fileidx], mmap=NUMPY_MMAP).shape[3] / 2))
     elif which.lower() == 'last':
         idx = load(filenames[fileidx]).shape[3] - 1
     else:

nipype/workflows/rsfmri/fsl/resting.py

@@ -14,10 +14,12 @@ def select_volume(filename, which):
     """
     from nibabel import load
     import numpy as np
+    from nipype.utils import NUMPY_MMAP
+
     if which.lower() == 'first':
         idx = 0
     elif which.lower() == 'middle':
-        idx = int(np.ceil(load(filename).shape[3] / 2))
+        idx = int(np.ceil(load(filename, mmap=NUMPY_MMAP).shape[3] / 2))
     else:
         raise Exception('unknown value for volume selection : %s' % which)
     return idx