fix: remove code added by oscar

Author: satra

nipype/algorithms/misc.py

@@ -1164,171 +1164,6 @@ def normalize_tpms(in_files, in_mask=None, out_files=[]):
 
     return out_files
 
-
-def split_rois(in_file, mask=None, roishape=None):
-    """
-    Splits an image in ROIs for parallel processing
-    """
-    import nibabel as nb
-    import numpy as np
-    from math import sqrt, ceil
-    import os.path as op
-
-    if roishape is None:
-        roishape = (10, 10, 1)
-
-    im = nb.load(in_file)
-    imshape = im.get_shape()
-    dshape = imshape[:3]
-    nvols = imshape[-1]
-    roisize = roishape[0] * roishape[1] * roishape[2]
-    droishape = (roishape[0], roishape[1], roishape[2], nvols)
-
-    if mask is not None:
-        mask = nb.load(mask).get_data()
-        mask[mask > 0] = 1
-        mask[mask < 1] = 0
-    else:
-        mask = np.ones(dshape)
-
-    mask = mask.reshape(-1).astype(np.uint8)
-    nzels = np.nonzero(mask)
-    els = np.sum(mask)
-    nrois = int(ceil(els/roisize))
-
-    data = im.get_data().reshape((mask.size, -1))
-    data = np.squeeze(data.take(nzels, axis=0))
-    nvols = data.shape[-1]
-
-    roidefname = op.abspath('onesmask.nii.gz')
-    nb.Nifti1Image(np.ones(roishape, dtype=np.uint8), None,
-                   None).to_filename(roidefname)
-
-    out_files = []
-    out_mask = []
-    out_idxs = []
-
-    for i in xrange(nrois):
-        first = i * roisize
-        last = (i+1) * roisize
-        fill = 0
-
-        if last > els:
-            fill = last - els
-            last = els
-
-        droi = data[first:last, ...]
-        iname = op.abspath('roi%010d_idx' % i)
-        out_idxs.append(iname+'.npz')
-        np.savez(iname, (nzels[0][first:last],))
-
-        if fill > 0:
-            droi = np.vstack((droi, np.zeros((fill, nvols), dtype=np.float32)))
-            partialmsk = np.ones((roisize,), dtype=np.uint8)
-            partialmsk[-fill:] = 0
-            partname = op.abspath('partialmask.nii.gz')
-            nb.Nifti1Image(partialmsk.reshape(roishape), None,
-                           None).to_filename(partname)
-            out_mask.append(partname)
-        else:
-            out_mask.append(roidefname)
-
-        fname = op.abspath('roi%010d.nii.gz' % i)
-        nb.Nifti1Image(droi.reshape(droishape),
-                       None, None).to_filename(fname)
-        out_files.append(fname)
-    return out_files, out_mask, out_idxs
-
-
-def merge_rois(in_files, in_idxs, in_ref,
-               dtype=None, out_file=None):
-    """
-    Re-builds an image resulting from a parallelized processing
-    """
-    import nibabel as nb
-    import numpy as np
-    import os.path as op
-    import subprocess as sp
-
-    if out_file is None:
-        out_file = op.abspath('merged.nii.gz')
-
-    if dtype is None:
-        dtype = np.float32
-
-    # if file is compressed, uncompress using os
-    # to avoid memory errors
-    if op.splitext(in_ref)[1] == '.gz':
-        try:
-            iflogger.info('uncompress %i' % in_ref)
-            sp.check_call(['gunzip', in_ref], stdout=sp.PIPE, shell=True)
-            in_ref = op.splitext(in_ref)[0]
-        except:
-            pass
-
-    ref = nb.load(in_ref)
-    aff = ref.get_affine()
-    hdr = ref.get_header().copy()
-    rsh = ref.get_shape()
-    del ref
-    npix = rsh[0] * rsh[1] * rsh[2]
-    fcdata = nb.load(in_files[0]).get_data()
-
-    if fcdata.ndim == 4:
-        ndirs = fcdata.shape[-1]
-    else:
-        ndirs = 1
-    newshape = (rsh[0], rsh[1], rsh[2], ndirs)
-    hdr.set_data_dtype(dtype)
-    hdr.set_xyzt_units('mm', 'sec')
-
-    if ndirs < 300:
-        data = np.zeros((npix, ndirs))
-        for cname, iname in zip(in_files, in_idxs):
-            with np.load(iname) as f:
-                idxs = np.squeeze(f['arr_0'])
-            cdata = nb.load(cname).get_data().reshape(-1, ndirs)
-            nels = len(idxs)
-            idata = (idxs, )
-            try:
-                data[idata, ...] = cdata[0:nels, ...]
-            except:
-                print(data.shape, cdata.shape)
-                raise
-
-        hdr.set_data_shape(newshape)
-
-        nb.Nifti1Image(data.reshape(newshape).astype(dtype),
-                       aff, hdr).to_filename(out_file)
-
-
-    else:
-        hdr.set_data_shape(rsh[:3])
-        nii = []
-        for d in xrange(ndirs):
-            fname = op.abspath('vol%06d.nii' % d)
-            nb.Nifti1Image(np.zeros(rsh[:3]), aff, hdr).to_filename(fname)
-            nii.append(fname)
-
-        for cname, iname in zip(in_files, in_idxs):
-            with np.load(iname) as f:
-                idxs = np.squeeze(f['arr_0'])
-
-            for d, fname in enumerate(nii):
-                data = nb.load(fname).get_data().reshape(-1)
-                cdata = nb.load(cname).get_data().reshape(-1, ndirs)[:, d]
-                nels = len(idxs)
-                idata = (idxs, )
-                data[idata] = cdata[0:nels]
-                nb.Nifti1Image(data.reshape(rsh[:3]), aff, hdr).to_filename(fname)
-
-        imgs = [nb.load(im) for im in nii]
-        allim = nb.concat_images(imgs)
-        allim.to_filename(out_file)
-
-    return out_file
-
-
 # Deprecated interfaces ------------------------------------------------------
 
 class Distance(nam.Distance):