fsl/scripts/fsl_ents.py

@@ -9,8 +9,6 @@ time series from a MELODIC ``.ica`` directory.
 """
 
 
-from __future__ import print_function
-
 import os.path as op
 import            sys
 import            argparse
@@ -18,12 +16,8 @@ import            warnings
 
 import numpy   as np
 
-# See atlasq.py for explanation
-with warnings.catch_warnings():
-    warnings.filterwarnings("ignore", category=FutureWarning)
-
-    import fsl.data.fixlabels       as fixlabels
-    import fsl.data.melodicanalysis as melanalysis
+import fsl.data.fixlabels       as fixlabels
+import fsl.data.melodicanalysis as melanalysis
 
 
 DTYPE = np.float64

fsl/scripts/imcp.py

@@ -12,19 +12,13 @@ The :func:`main` function is essentially a wrapper around the
 """
 
 
-from __future__ import print_function
-
 import os.path        as op
 import                   sys
-import                   warnings
+import                   logging
 
 import fsl.utils.path as fslpath
-
-# See atlasq.py for explanation
-with warnings.catch_warnings():
-    warnings.filterwarnings("ignore", category=FutureWarning)
-    import fsl.utils.imcp as imcp
-    import fsl.data.image as fslimage
+import fsl.utils.imcp as imcp
+import fsl.data.image as fslimage
 
 
 usage = """Usage:
@@ -59,6 +53,11 @@ def main(argv=None):
         print(usage)
         return 1
 
+    # When converting to NIFTI2, nibabel
+    # emits an annoying message via log.warning:
+    #   sizeof_hdr should be 540; set sizeof_hdr to 540
+    logging.getLogger('nibabel').setLevel(logging.ERROR)
+
     try:
         srcs = [fslimage.fixExt(s) for s in srcs]
         srcs = fslpath.removeDuplicates(

fsl/scripts/imglob.py

@@ -9,17 +9,11 @@ NIFTI/ANALYZE image files.
 """
 
 
-from __future__ import print_function
-
+import itertools      as it
+import                   glob
 import                   sys
-import                   warnings
 import fsl.utils.path as fslpath
 
-# See atlasq.py for explanation
-with warnings.catch_warnings():
-    warnings.filterwarnings("ignore", category=FutureWarning)
-    import fsl.data.image as fslimage
-
 
 usage = """
 Usage: imglob [-extension/extensions] <list of names>
@@ -27,8 +21,17 @@ Usage: imglob [-extension/extensions] <list of names>
        -extensions for image list with full extensions
 """.strip()
 
-exts   = fslimage.ALLOWED_EXTENSIONS
-groups = fslimage.FILE_GROUPS
+
+# The lists below are defined in the
+# fsl.data.image class, but are duplicated
+# here for performance (to avoid import of
+# nibabel/numpy/etc).
+exts   = ['.nii.gz', '.nii', '.img', '.hdr', '.img.gz', '.hdr.gz']
+"""List of supported image file extensions. """
+
+
+groups = [('.hdr', '.img'), ('.hdr.gz', '.img.gz')]
+"""List of known image file groups (image/header file pairs). """
 
 
 def imglob(paths, output=None):
@@ -61,12 +64,38 @@ def imglob(paths, output=None):
 
     imgfiles = []
 
+    # Expand any wildcard paths if provided.
+    # Depending on the way that imglob is
+    # invoked, this may not get done by the
+    # calling shell.
+    #
+    # We also have to handle incomplete
+    # wildcards, e.g. if the user provides
+    # "img_??", we need to add possible
+    # file suffixes before it can be
+    # expanded.
+    expanded = []
+    for path in paths:
+        if any(c in path for c in '*?[]'):
+            if fslpath.hasExt(path, exts):
+                globs = [path]
+            else:
+                globs = [f'{path}{ext}' for ext in exts]
+            globs = [glob.glob(g) for g in globs]
+            expanded.extend(it.chain(*globs))
+        else:
+            expanded.append(path)
+
+    paths = expanded
+
     # Build a list of all image files (both
     # hdr and img and otherwise) that match
     for path in paths:
         try:
-            path = fslimage.removeExt(path)
-            imgfiles.extend(fslimage.addExt(path, unambiguous=False))
+            path = fslpath.removeExt(path, allowedExts=exts)
+            imgfiles.extend(fslpath.addExt(path,
+                                           allowedExts=exts,
+                                           unambiguous=False))
         except fslpath.PathError:
             continue
 

fsl/scripts/imln.py

+#!/usr/bin/env python
+#
+# imln.py - Create symbolic links to image files.
+#
+# Author: Paul McCarthy <pauldmccarthy@gmail.com>
+#
+"""This module defines the ``imln`` application, for creating sym-links
+to NIFTI image files.
+
+.. note:: When creating links to relative paths, ln requires that the path is
+          relative to the link location, rather than the invocation
+          location. This is *not* currently supported by imln, and possibly
+          never will be.
+"""
+
+
+import os.path        as op
+import                   os
+import                   sys
+import fsl.utils.path as fslpath
+
+
+# The lists below are defined in the
+# fsl.data.image class, but are duplicated
+# here for performance (to avoid import of
+# nibabel/numpy/etc).
+exts = ['.nii.gz', '.nii',
+        '.img',    '.hdr',
+        '.img.gz', '.hdr.gz',
+        '.mnc',    '.mnc.gz']
+"""List of file extensions that are supported by ``imtest``.
+"""
+
+groups = [('.hdr', '.img'), ('.hdr.gz', '.img.gz')]
+"""List of known image file groups (image/header file pairs). """
+
+
+usage = """
+Usage: imln <file1> <file2>
+  Makes a link (called file2) to file1
+  NB: filenames can be basenames or include an extension
+""".strip()
+
+
+def main(argv=None):
+    """``imln`` - create sym-links to images. """
+
+    if argv is None:
+        argv = sys.argv[1:]
+
+    if len(argv) != 2:
+        print(usage)
+        return 1
+
+    target, linkbase = argv
+    target           = fslpath.removeExt(target,   exts)
+    linkbase         = fslpath.removeExt(linkbase, exts)
+
+    # Target must exist, so we can
+    # infer the correct extension(s).
+    # Error on incomplete file groups
+    # (e.g. a.img without a.hdr).
+    try:
+        targets = fslpath.getFileGroup(target,
+                                       allowedExts=exts,
+                                       fileGroups=groups,
+                                       unambiguous=True)
+    except Exception as e:
+        print(f'Error: {e}')
+        return 1
+
+    for target in targets:
+        if not op.exists(target):
+            continue
+
+        ext  = fslpath.getExt(target, exts)
+        link = f'{linkbase}{ext}'
+
+        try:
+
+            # emulate old imln behaviour - if
+            # link already exists, it is removed
+            if op.exists(link):
+                os.remove(link)
+
+            os.symlink(target, link)
+
+        except Exception as e:
+            print(f'Error: {e}')
+            return 1
+
+    return 0
+
+
+if __name__ == '__main__':
+    sys.exit(main())

fsl/scripts/immv.py

@@ -13,19 +13,13 @@ The :func:`main` function is essentially a wrapper around the
 """
 
 
-from __future__ import print_function
-
 import os.path        as op
 import                   sys
-import                   warnings
+import                   logging
 
 import fsl.utils.path as fslpath
-
-# See atlasq.py for explanation
-with warnings.catch_warnings():
-    warnings.filterwarnings("ignore", category=FutureWarning)
-    import fsl.utils.imcp as imcp
-    import fsl.data.image as fslimage
+import fsl.utils.imcp as imcp
+import fsl.data.image as fslimage
 
 
 usage = """Usage:
@@ -60,6 +54,11 @@ def main(argv=None):
         print(usage)
         return 1
 
+    # When converting to NIFTI2, nibabel
+    # emits an annoying message via log.warning:
+    #   sizeof_hdr should be 540; set sizeof_hdr to 540
+    logging.getLogger('nibabel').setLevel(logging.ERROR)
+
     try:
         srcs = [fslimage.fixExt(s) for s in srcs]
         srcs = fslpath.removeDuplicates(

fsl/scripts/imrm.py

+#!/usr/bin/env python
+#
+# imrm.py - Remove image files.
+#
+# Author: Paul McCarthy <paulmc@fmrib.ox.ac.uk>
+#
+"""This module defines the ``imrm`` application, for removing NIFTI image
+files.
+"""
+
+
+import os.path            as op
+import                       os
+import                       sys
+import fsl.scripts.imglob as imglob
+
+
+usage = """Usage: imrm <list of image names to remove>
+NB: filenames can be basenames or not
+""".strip()
+
+
+def main(argv=None):
+    """Removes all images which are specified on the command line. """
+
+    if argv is None:
+        argv = sys.argv[1:]
+
+    if len(argv) < 1:
+        print(usage)
+        return 1
+
+    paths = imglob.imglob(argv, 'all')
+
+    for path in paths:
+        if op.exists(path):
+            os.remove(path)
+
+    return 0
+
+
+if __name__ == '__main__':
+    sys.exit(main())

fsl/scripts/imtest.py

+#!/usr/bin/env python
+#
+# imtest.py - Test whether an image file exists or not.
+#
+# Author: Paul McCarthy <pauldmccarthy@gmail.com>
+#
+"""The ``imtest`` script can be used to test whether an image file exists or
+not, without having to know the file suffix (.nii, .nii.gz, etc).
+"""
+
+
+import os.path        as op
+import                   sys
+import fsl.utils.path as fslpath
+
+
+# The lists below are defined in the
+# fsl.data.image class, but are duplicated
+# here for performance (to avoid import of
+# nibabel/numpy/etc).
+exts = ['.nii.gz', '.nii',
+        '.img',    '.hdr',
+        '.img.gz', '.hdr.gz',
+        '.mnc',    '.mnc.gz']
+"""List of file extensions that are supported by ``imtest``.
+"""
+
+groups = [('.hdr', '.img'), ('.hdr.gz', '.img.gz')]
+"""List of known image file groups (image/header file pairs). """
+
+
+def imtest(path):
+    """Returns ``True`` if the given image path exists, False otherwise. """
+
+    path = fslpath.removeExt(path, exts)
+    path = op.realpath(path)
+
+    # getFileGroup will raise an error
+    # if the image (including all
+    # components - i.e. header and
+    # image) does not exist
+    try:
+        fslpath.getFileGroup(path,
+                             allowedExts=exts,
+                             fileGroups=groups,
+                             unambiguous=True)
+        return True
+
+    except fslpath.PathError:
+        return False
+
+
+def main(argv=None):
+    """Test if an image path exists, and prints ``'1'`` if it does or ``'0'``
+    if it doesn't.
+    """
+
+    if argv is None:
+        argv = sys.argv[1:]
+
+    # emulate old fslio/imtest - always return 0
+    if len(argv) != 1:
+        print('0')
+        return 0
+
+    if imtest(argv[0]):
+        print('1')
+    else:
+        print('0')
+
+    return 0
+
+
+if __name__ == '__main__':
+    sys.exit(main())

fsl/scripts/remove_ext.py

+#!/usr/bin/env python
+#
+# remove_ext.py - Remove file extensions from NIFTI image paths
+#
+# Author: Paul McCarthy <pauldmccarthy@gmail.com>
+#
+
+
+import                   sys
+import fsl.utils.path as fslpath
+
+
+usage = """Usage: remove_ext <list of image paths to remove extension from>
+""".strip()
+
+
+# This list is defined in the
+# fsl.data.image class, but are duplicated
+# here for performance (to avoid import of
+# nibabel/numpy/etc).
+exts = ['.nii.gz', '.nii',
+        '.img',    '.hdr',
+        '.img.gz', '.hdr.gz',
+        '.mnc',    '.mnc.gz']
+"""List of file extensions that are removed by ``remove_ext``. """
+
+
+def main(argv=None):
+    """Removes file extensions from all paths which are specified on the
+    command line.
+    """
+
+    if argv is None:
+        argv = sys.argv[1:]
+
+    if len(argv) < 1:
+        print(usage)
+        return 1
+
+    removed = []
+
+    for path in argv:
+        removed.append(fslpath.removeExt(path, exts))
+
+    print(' '.join(removed))
+
+    return 0
+
+
+if __name__ == '__main__':
+    sys.exit(main())

tests/__init__.py → fsl/tests/__init__.py

@@ -10,6 +10,7 @@
 import              os
 import              sys
 import              glob
+import              hashlib
 import              shutil
 import              fnmatch
 import              logging
@@ -20,14 +21,12 @@ import os.path   as op
 import numpy     as np
 import nibabel   as nib
 
-from six import StringIO
+from io import StringIO
 
-
-try: from unittest import mock
-except ImportError: import mock
+from unittest import mock
 
 import fsl.data.image                     as fslimage
-from   fsl.utils.tempdir import              tempdir
+from   fsl.utils.tempdir  import             tempdir
 from   fsl.utils.platform import platform as fslplatform
 
 
@@ -50,7 +49,10 @@ def mockFSLDIR(**kwargs):
                 if not op.isdir(subdir):
                     os.makedirs(subdir)
                 for fname in files:
-                    touch(op.join(subdir, fname))
+                    fname = op.join(subdir, fname)
+                    touch(fname)
+                    if subdir == bindir:
+                        os.chmod(fname, 0o755)
             fslplatform.fsldir = fsldir
             fslplatform.fsldevdir = None
 
@@ -68,7 +70,7 @@ def touch(fname):
         pass
 
 
-class CaptureStdout(object):
+class CaptureStdout:
     """Context manager which captures stdout and stderr. """
 
     def __init__(self):
@@ -87,6 +89,7 @@ class CaptureStdout(object):
 
         sys.stdout = self.__mock_stdout
         sys.stderr = self.__mock_stderr
+        return self
 
 
     def __exit__(self, *args, **kwargs):
@@ -145,6 +148,8 @@ def testdir(contents=None, suffix=""):
             shutil.rmtree(self.testdir)
 
     return ctx(contents)
+testdir.__test__ = False
+
 
 def make_dummy_files(paths):
     """Creates dummy files for all of the given paths. """
@@ -284,7 +289,8 @@ def make_mock_feat_analysis(featdir,
                             copes=True,
                             zstats=True,
                             residuals=True,
-                            clustMasks=True):
+                            clustMasks=True,
+                            zfstats=True):
 
     if xform is None:
         xform = np.eye(4)
@@ -317,6 +323,7 @@ def make_mock_feat_analysis(featdir,
             data = np.ravel_multi_index(data, shape)
             data = data.reshape(list(shape) + [1]).repeat(timepoints, axis=3)
             data[..., :] += range(i, i + timepoints)
+            data = data.astype(np.int32)
 
             img = nib.nifti1.Nifti1Image(data, xform)
 
@@ -341,6 +348,11 @@ def make_mock_feat_analysis(featdir,
         otherFiles .extend(files)
         otherShapes.extend([shape] * len(files))
 
+    if zfstats:
+        files = glob.glob(op.join(featdir, 'stats', 'zfstat*nii.gz'))
+        otherFiles .extend(files)
+        otherShapes.extend([shape] * len(files))
+
     if residuals:
         files = glob.glob(op.join(featdir, 'stats', 'res4d.nii.gz'))
         otherFiles .extend(files)
@@ -428,3 +440,10 @@ def make_random_mask(filename, shape, xform, premask=None, minones=1):
     img.save(filename)
 
     return img
+
+
+def sha256(filename):
+    hashobj = hashlib.sha256()
+    with open(filename, 'rb') as f:
+        hashobj.update(f.read())
+    return hashobj.hexdigest()

tests/test_assertions.py → fsl/tests/test_assertions.py

@@ -14,8 +14,8 @@ import pytest
 import fsl.utils.assertions as assertions
 import fsl.utils.tempdir    as tempdir
 
-from . import make_random_image
-from . import testdir
+from fsl.tests import make_random_image
+from fsl.tests import testdir
 
 
 def test_assertFileExists():
@@ -160,14 +160,14 @@ def test_assertIsMelodicDir():
         ('analysis.ica', [                      'melodic_mix', 'melodic_FTmix'], False),
         ('analysis.ica', ['melodic_IC.nii.gz',                 'melodic_FTmix'], False),
         ('analysis.ica', ['melodic_IC.nii.gz',  'melodic_mix'],                  False),
-        ('analysis',     ['melodic_IC.nii.gz',  'melodic_mix', 'melodic_FTmix'], False),
-        ('analysis',     ['melodic_oIC.nii.gz', 'melodic_mix', 'melodic_FTmix'], False),
+        ('analysis',     ['melodic_IC.nii.gz',  'melodic_mix', 'melodic_FTmix'], True),
+        ('analysis',     [                      'melodic_mix', 'melodic_FTmix'], False),
     ]
 
     for dirname, paths, expected in tests:
         with testdir(paths, dirname):
             if expected:
-                assertions.assertIsMelodicDir(dirname)
+                assertions.assertIsMelodicDir('.')
             else:
                 with pytest.raises(AssertionError):
                     assertions.assertIsMelodicDir(dirname)

tests/test_atlases.py → fsl/tests/test_atlases.py

@@ -13,10 +13,11 @@ import              os
 import os.path   as op
 import numpy     as np
 
-import mock
+
+from unittest import mock
 import pytest
 
-import tests
+import fsl.tests                as tests
 import fsl.utils.image.resample as resample
 import fsl.data.atlases         as atlases
 import fsl.data.image           as fslimage
@@ -40,7 +41,8 @@ dummy_atlas_desc = """<?xml version="1.0" encoding="ISO-8859-1"?>
   <header>
     <name>{name}</name>
     <shortname>{shortname}</shortname>
-    <type>Label</type>
+    <type>{atlastype}</type>
+    {extraheader}
     <images>
       <imagefile>/{shortname}/{filename}</imagefile>
        <summaryimagefile>/{shortname}/My{filename}</summaryimagefile>
@@ -52,7 +54,8 @@ dummy_atlas_desc = """<?xml version="1.0" encoding="ISO-8859-1"?>
   </data>
 </atlas>
 """
-def _make_dummy_atlas(savedir, name, shortName, filename):
+def _make_dummy_atlas(
+        savedir, name, shortName, filename, atlastype='Label', extraheader=''):
     mladir     = op.join(savedir, shortName)
     mlaxmlfile = op.join(savedir, '{}.xml'.format(shortName))
     mlaimgfile = op.join(savedir, shortName, '{}.nii.gz'.format(filename))
@@ -70,7 +73,9 @@ def _make_dummy_atlas(savedir, name, shortName, filename):
         desc = dummy_atlas_desc.format(
             name=name,
             shortname=shortName,
-            filename=filename)
+            filename=filename,
+            atlastype=atlastype,
+            extraheader=extraheader)
         f.write(desc)
 
     return mlaxmlfile
@@ -142,6 +147,28 @@ def test_AtlasDescription():
         registry.getAtlasDescription('non-existent-atlas')
 
 
+def test_StatisticHeader():
+    with tests.testdir() as testdir:
+        hdr = '<statistic>T</statistic>' \
+              '<units></units>' \
+              '<precision>3</precision>' \
+              '<upper>75</upper>'
+        xmlfile = _make_dummy_atlas(testdir,
+                                    'statlas',
+                                    'STA',
+                                    'StAtlas',
+                                    atlastype='Statistic',
+                                    extraheader=hdr)
+
+        desc = atlases.AtlasDescription(xmlfile, 'StAtlas')
+        assert desc.atlasType == 'statistic'
+        assert desc.statistic == 'T'
+        assert desc.units     == ''
+        assert desc.precision == 3
+        assert desc.lower     == 0
+        assert desc.upper     == 75
+
+
 def test_add_remove_atlas():
 
     with tests.testdir() as testdir:
@@ -225,8 +252,7 @@ def test_load_atlas():
     reg = atlases.registry
     reg.rescanAtlases()
 
-    probatlas    = reg.loadAtlas('harvardoxford-cortical',
-                                 calcRange=False, loadData=False)
+    probatlas    = reg.loadAtlas('harvardoxford-cortical')
     probsumatlas = reg.loadAtlas('harvardoxford-cortical', loadSummary=True)
     lblatlas     = reg.loadAtlas('talairach')
 
@@ -250,6 +276,9 @@ def test_get():
             assert (target == atlas.get(index=label.index).data).all()
             assert (target == atlas.get(value=label.value).data).all()
             assert (target == atlas.get(name=label.name).data).all()
+            if atlas is lblatlas:
+                target = target * label.value
+                assert (target == atlas.get(value=label.value, binary=False).data).all()
 
 
 def test_find():
@@ -257,8 +286,7 @@ def test_find():
     reg = atlases.registry
     reg.rescanAtlases()
 
-    probatlas    = reg.loadAtlas('harvardoxford-cortical',
-                                 calcRange=False, loadData=False)
+    probatlas    = reg.loadAtlas('harvardoxford-cortical')
     probsumatlas = reg.loadAtlas('harvardoxford-cortical', loadSummary=True)
     lblatlas     = reg.loadAtlas('talairach')
 
@@ -305,8 +333,7 @@ def test_prepareMask():
     reg = atlases.registry
     reg.rescanAtlases()
 
-    probatlas    = reg.loadAtlas('harvardoxford-cortical',
-                                 loadData=False, calcRange=False)
+    probatlas    = reg.loadAtlas('harvardoxford-cortical')
     probsumatlas = reg.loadAtlas('harvardoxford-cortical', loadSummary=True)
     lblatlas     = reg.loadAtlas('talairach')
 

tests/test_atlases_query.py → fsl/tests/test_atlases_query.py

@@ -17,7 +17,7 @@ import fsl.transform.affine     as affine
 import fsl.utils.image.resample as resample
 import fsl.utils.cache          as cache
 
-from . import (testdir, make_random_mask)
+from fsl.tests import (testdir, make_random_mask)
 
 
 pytestmark = pytest.mark.fsltest
@@ -41,17 +41,16 @@ _atlases = cache.Cache()
 def _get_atlas(atlasID, res, summary=False):
     atlas = _atlases.get((atlasID, res, summary), default=None)
     if atlas is None:
+        atlas = fslatlases.loadAtlas(atlasID,
+                                     loadSummary=summary,
+                                     resolution=res)
+
+        # We need some atlases to be loaded into memory,
+        # so we can use boolean-mask-based indexing
         if summary or atlasID in ('talairach', 'striatum-structural',
                                   'jhu-labels', 'smatt'):
-            kwargs = {}
-        else:
-            kwargs = {'loadData'  : False,
-                      'calcRange' : False}
+            atlas.data
 
-        atlas = fslatlases.loadAtlas(atlasID,
-                                     loadSummary=summary,
-                                     resolution=res,
-                                     **kwargs)
         _atlases.put((atlasID, res, summary), atlas)
 
     return atlas
@@ -85,7 +84,7 @@ def _get_zero_mask(aimg):
         elif isinstance(aimg, fslatlases.ProbabilisticAtlas):
 
             # Keep memory usage down
-            zmask = np.ones(aimg.shape[:3], dtype=np.bool)
+            zmask = np.ones(aimg.shape[:3], dtype=bool)
             for vol in range(aimg.shape[-1]):
                 zmask = np.logical_and(zmask, aimg[..., vol] == 0)
 
@@ -218,8 +217,8 @@ def _eval_coord_voxel_query(atlas, query, qtype, qin):
         elif qin == 'out':
             expval = []
 
-        assert atlas.proportions(     query, voxel=voxel) == expval
-        assert atlas.coordProportions(query, voxel=voxel) == expval
+        assert atlas.values(     query, voxel=voxel) == expval
+        assert atlas.coordValues(query, voxel=voxel) == expval
 
     if   isinstance(atlas, fslatlases.LabelAtlas):         evalLabel()
     elif isinstance(atlas, fslatlases.ProbabilisticAtlas): evalProb()
@@ -284,7 +283,7 @@ def _eval_mask_query(atlas, query, qtype, qin):
         rmask = resample.resample(
             mask, atlas.shape[:3], dtype=np.float32, order=0)[0]
 
-    rmask = np.array(rmask, dtype=np.bool)
+    rmask = np.array(rmask, dtype=bool)
 
     def evalLabel():
 
@@ -343,13 +342,13 @@ def _eval_mask_query(atlas, query, qtype, qin):
 
         if qin == 'out':
             with pytest.raises(fslatlases.MaskError):
-                atlas.maskProportions(mask)
+                atlas.maskValues(mask)
             with pytest.raises(fslatlases.MaskError):
-                atlas.proportions(    mask)
+                atlas.values(    mask)
             return
 
-        props  = atlas.    proportions(mask)
-        props2 = atlas.maskProportions(mask)
+        props  = atlas.    values(mask)
+        props2 = atlas.maskValues(mask)
 
         assert np.all(np.isclose(props, props2))
 

fsl/tests/test_bids.py

+#!/usr/bin/env python
+#
+# test_bids.py -
+#
+# Author: Paul McCarthy <pauldmccarthy@gmail.com>
+#
+
+
+import                  json
+import os.path   as     op
+import itertools as     it
+from   pathlib   import Path
+
+import pytest
+
+from fsl.utils.tempdir import tempdir
+import fsl.utils.bids  as     fslbids
+
+
+def test_parseFilename():
+    badtests = ['bad_file.txt']
+
+    for test in badtests:
+        with pytest.raises(ValueError):
+            fslbids.parseFilename(test)
+
+    tests = [
+        ('sub-01_ses-01_t1w.nii.gz',
+         ({'sub' : '01', 'ses' : '01'}, 't1w')),
+        ('a-1_b-2_c-3_d-4_e.json',
+         ({'a' : '1', 'b' : '2', 'c' : '3', 'd' : '4'}, 'e')),
+    ]
+
+    for filename, expect in tests:
+        assert fslbids.parseFilename(filename) == expect
+
+
+def test_isBIDSDir():
+    with tempdir():
+        assert not fslbids.isBIDSDir('.')
+    with tempdir():
+        Path('dataset_description.json').touch()
+        assert fslbids.isBIDSDir('.')
+
+
+def test_inBIDSDir():
+    with tempdir():
+        Path('a/b/c').mkdir(parents=True)
+        Path('dataset_description.json').touch()
+        assert fslbids.inBIDSDir(Path('.'))
+        assert fslbids.inBIDSDir(Path('a'))
+        assert fslbids.inBIDSDir(Path('a/b'))
+        assert fslbids.inBIDSDir(Path('a/b/c'))
+    with tempdir():
+        Path('a/b/c').mkdir(parents=True)
+        assert not fslbids.inBIDSDir(Path('.'))
+        assert not fslbids.inBIDSDir(Path('a'))
+        assert not fslbids.inBIDSDir(Path('a/b'))
+        assert not fslbids.inBIDSDir(Path('a/b/c'))
+
+
+def test_isBIDSFile():
+    goodfiles = [
+        Path('sub-01_ses-01_t1w.nii.gz'),
+        Path('sub-01_ses-01_t1w.nii'),
+        Path('sub-01_ses-01_t1w.json'),
+        Path('a-1_b-2_c-3_d-4_e.nii.gz'),
+        Path('sub-01_ses-01_t1w.txt'),
+    ]
+    badfiles = [
+        Path('sub-01_ses-01.nii.gz'),
+        Path('sub-01_ses-01_t1w'),
+        Path('sub-01_ses-01_t1w.'),
+        Path('sub_ses-01_t1w.nii.gz'),
+        Path('sub-01_ses_t1w.nii.gz'),
+    ]
+    with tempdir():
+        Path('dataset_description.json').touch()
+        for f in goodfiles: assert     fslbids.isBIDSFile(f)
+        for f in badfiles:  assert not fslbids.isBIDSFile(f)
+    with tempdir():
+        for f in it.chain(goodfiles, badfiles):
+            assert not fslbids.isBIDSFile(f)
+
+
+def test_loadMetadata():
+    dd    = Path('dataset_description.json')
+    t1    = Path('sub-01/func/sub-01_task-stim_bold.nii.gz')
+    json1 = Path('sub-01/func/sub-01_task-stim_bold.json')
+    json2 = Path('sub-01/sub-01_bold.json')
+    json3 = Path('sub-01_t1w.json')
+    json4 = Path('sub-01/task-stim_bold.json')
+    meta1 = {'a' : '1',   'b' : '2'}
+    meta2 = {'a' : '10',  'c' : '3'}
+    meta3 = {'a' : '109', 'b' : '99'}
+    meta4 = {'c' : '9',   'd' : '5'}
+
+    with tempdir():
+        dd.touch()
+        Path(op.dirname(t1)).mkdir(parents=True)
+        t1.touch()
+        assert fslbids.loadMetadata(t1) == {}
+        json1.write_text(json.dumps(meta1))
+        assert fslbids.loadMetadata(t1) == meta1
+        json2.write_text(json.dumps(meta2))
+        assert fslbids.loadMetadata(t1) == {**meta2, **meta1}
+        json3.write_text(json.dumps(meta3))
+        assert fslbids.loadMetadata(t1) == {**meta2, **meta1}
+        json4.write_text(json.dumps(meta4))
+        assert fslbids.loadMetadata(t1) == {**meta4, **meta2, **meta1}
+
+
+def test_loadMetadata_control_characters():
+    dd     = Path('dataset_description.json')
+    t1     = Path('sub-01/func/sub-01_task-stim_bold.nii.gz')
+    json1  = Path('sub-01/func/sub-01_task-stim_bold.json')
+    meta1  =  {"a" : "1",  "b" : "2\x19\x20"}
+    smeta1 = '{"a" : "1",  "b" : "2\x19\x20"}'
+
+    with tempdir():
+        dd.touch()
+        Path(op.dirname(t1)).mkdir(parents=True)
+        t1.touch()
+        assert fslbids.loadMetadata(t1) == {}
+        json1.write_text(smeta1)
+        assert fslbids.loadMetadata(t1) == meta1
+
+
+def test_loadMetadata_symlinked():
+    ddreal = Path('a')
+    t1real = Path('b')
+    j1real = Path('c')
+    j2real = Path('d')
+    j3real = Path('e')
+    j4real = Path('f')
+    dd     = Path('data/dataset_description.json')
+    t1     = Path('data/sub-01/func/sub-01_task-stim_bold.nii.gz')
+    json1  = Path('data/sub-01/func/sub-01_task-stim_bold.json')
+    json2  = Path('data/sub-01/sub-01_bold.json')
+    json3  = Path('data/sub-01_t1w.json')
+    json4  = Path('data/sub-01/task-stim_bold.json')
+    meta1  = {'a' : '1',   'b' : '2'}
+    meta2  = {'a' : '10',  'c' : '3'}
+    meta3  = {'a' : '109', 'b' : '99'}
+    meta4  = {'c' : '9',   'd' : '5'}
+
+    with tempdir():
+        ddreal.touch()
+        t1real.touch()
+        j1real.write_text(json.dumps(meta1))
+        j2real.write_text(json.dumps(meta2))
+        j3real.write_text(json.dumps(meta3))
+        j4real.write_text(json.dumps(meta4))
+
+        Path(op.dirname(t1)).mkdir(parents=True)
+        dd   .symlink_to(op.join('..',             ddreal))
+        t1   .symlink_to(op.join('..', '..', '..', t1real))
+        json1.symlink_to(op.join('..', '..', '..', j1real))
+        json2.symlink_to(op.join('..', '..',       j2real))
+        json3.symlink_to(op.join('..',             j3real))
+        json4.symlink_to(op.join('..', '..',       j4real))
+
+        assert fslbids.loadMetadata(t1) == {**meta4, **meta2, **meta1}

tests/test_cache.py → fsl/tests/test_cache.py

@@ -113,7 +113,55 @@ def test_expiry():
     with pytest.raises(cache.Expired):
         c.get(0)
 
+    with pytest.raises(cache.Expired):
+        c.get(1)
+
     assert c.get(1, default='default') == 'default'
 
     # And that the cache is empty
     assert len(c) == 0
+
+
+def test_lru():
+    c = cache.Cache(maxsize=3, lru=True)
+
+    c[0] = '0'
+    c[1] = '1'
+    c[2] = '2'
+    c[3] = '3'
+
+    # normal behaviour - first inserted
+    # is dropped
+    with pytest.raises(KeyError):
+        assert c.get(0)
+
+    # lru behaviour - oldest accessed is
+    # dropped
+    c[1]
+    c[4] = '4'
+    with pytest.raises(KeyError):
+        c[2]
+
+    c[1]
+    c[3]
+    c[4]
+    assert len(c) == 3
+
+
+
+def test_accessors():
+    c = cache.Cache(maxsize=3)
+
+    c[0] = '0'
+    c[1] = '1'
+    c[2] = '2'
+    c[3] = '3'
+
+    assert list(c.keys())   == [ 1,        2,        3]
+    assert list(c.values()) == ['1',      '2',      '3']
+    assert list(c.items())  == [(1, '1'), (2, '2'), (3, '3')]
+
+    assert 0 not in c
+    assert 1     in c
+    assert 2     in c
+    assert 3     in c

fsl/tests/test_cifti.py

+from fsl.data import cifti
+import os.path as op
+import numpy as np
+import nibabel as nib
+from numpy import testing
+import fsl.tests as tests
+from nibabel.cifti2 import cifti2_axes
+
+
+def volumetric_brain_model():
+    mask = np.random.randint(2, size=(10, 10, 10)) > 0
+    return cifti2_axes.BrainModelAxis.from_mask(mask, affine=np.eye(4))
+
+
+def surface_brain_model():
+    mask = np.random.randint(2, size=100) > 0
+    return cifti2_axes.BrainModelAxis.from_mask(mask, name='cortex')
+
+
+def volumetric_parcels(return_mask=False):
+    mask = np.random.randint(5, size=(10, 10, 10))
+    axis = cifti2_axes.ParcelsAxis(
+        [f'vol_{idx}' for idx in range(1, 5)],
+        voxels=[np.stack(np.where(mask == idx), axis=-1) for idx in range(1, 5)],
+        vertices=[{} for _ in range(1, 5)],
+        volume_shape=mask.shape,
+        affine=np.eye(4),
+    )
+    if return_mask:
+        return axis, mask
+    else:
+        return axis
+
+
+def surface_parcels(return_mask=False):
+    mask = np.random.randint(5, size=100)
+    axis = cifti2_axes.ParcelsAxis(
+        [f'surf_{idx}' for idx in range(1, 5)],
+        voxels=[np.zeros((0, 3), dtype=int) for _ in range(1, 5)],
+        vertices=[{'CIFTI_STRUCTURE_CORTEX': np.where(mask == idx)[0]} for idx in range(1, 5)],
+        nvertices={'CIFTI_STRUCTURE_CORTEX': 100},
+    )
+    if return_mask:
+        return axis, mask
+    else:
+        return axis
+
+
+def gen_data(axes):
+    return np.random.randn(*(5 if ax is None else len(ax) for ax in axes))
+
+
+def test_read_gifti():
+    testdir = op.join(op.dirname(__file__), 'testdata')
+
+    shapefile = op.join(testdir, 'example.shape.gii')
+    ref_data = nib.load(shapefile).darrays[0].data
+
+    data = cifti.load(shapefile)
+    assert isinstance(data, cifti.DenseCifti)
+    assert data.arr.shape == (642, )
+    testing.assert_equal(data.arr, ref_data)
+    testing.assert_equal(data.brain_model_axis.vertex, np.arange(642))
+    assert len(data.brain_model_axis.nvertices) == 1
+    assert data.brain_model_axis.nvertices['CIFTI_STRUCTURE_OTHER'] == 642
+
+    data = cifti.load(shapefile, mask_values=(ref_data[0], ))
+    assert isinstance(data, cifti.DenseCifti)
+    assert data.arr.shape == (np.sum(ref_data != ref_data[0]), )
+    testing.assert_equal(data.arr, ref_data[ref_data != ref_data[0]])
+    testing.assert_equal(data.brain_model_axis.vertex, np.where(ref_data != ref_data[0])[0])
+    assert len(data.brain_model_axis.nvertices) == 1
+    assert data.brain_model_axis.nvertices['CIFTI_STRUCTURE_OTHER'] == 642
+
+    cifti.load(op.join(testdir, 'example'))
+
+
+def test_read_nifti():
+    mask = np.random.randint(2, size=(10, 10, 10)) > 0
+    values = np.random.randn(10, 10, 10)
+    for mask_val in (0, np.nan):
+        values[~mask] = mask_val
+        affine = np.concatenate((np.random.randn(3, 4), np.array([0, 0, 0, 1])[None, :]), axis=0)
+        with tests.testdir():
+            nib.Nifti1Image(values, affine).to_filename("masked_image.nii.gz")
+            data = cifti.load("masked_image")
+            assert isinstance(data, cifti.DenseCifti)
+            testing.assert_equal(data.arr, values[mask])
+            testing.assert_allclose(data.brain_model_axis.affine, affine)
+            assert len(data.brain_model_axis.nvertices) == 0
+
+
+def check_io(data: cifti.Cifti, extension):
+    with tests.testdir():
+        data.save("test")
+        assert op.isfile(f'test.{extension}.nii')
+        loaded = cifti.load("test")
+        if data.arr.ndim == 1:
+            testing.assert_equal(data.arr, loaded.arr[0])
+            assert data.axes == loaded.axes[1:]
+        else:
+            testing.assert_equal(data.arr, loaded.arr)
+            assert data.axes == loaded.axes
+
+
+def test_io_cifti():
+    for cifti_class, cifti_type, main_axis_options in (
+        (cifti.DenseCifti, 'd', (volumetric_brain_model(), surface_brain_model(),
+                                 volumetric_brain_model() + surface_brain_model())),
+        (cifti.ParcelCifti, 'p', (volumetric_parcels(), surface_parcels(),
+                                  volumetric_parcels() + surface_parcels())),
+    ):
+        for main_axis in main_axis_options:
+            with tests.testdir():
+                data_1d = cifti_class(gen_data([main_axis]), [main_axis])
+                check_io(data_1d, f'{cifti_type}scalar')
+
+                connectome = cifti_class(gen_data([main_axis, main_axis]), (main_axis, main_axis))
+                check_io(connectome, f'{cifti_type}conn')
+
+                scalar_axis = cifti2_axes.ScalarAxis(['A', 'B', 'C'])
+                scalar = cifti_class(gen_data([scalar_axis, main_axis]), (scalar_axis, main_axis))
+                check_io(scalar, f'{cifti_type}scalar')
+
+                label_axis = cifti2_axes.LabelAxis(['A', 'B', 'C'], {1: ('some parcel', (1, 0, 0, 1))})
+                label = cifti_class(gen_data([label_axis, main_axis]), (label_axis, main_axis))
+                check_io(label, f'{cifti_type}label')
+
+                series_axis = cifti2_axes.SeriesAxis(10, 3, 50, unit='HERTZ')
+                series = cifti_class(gen_data([series_axis, main_axis]), (series_axis, main_axis))
+                check_io(series, f'{cifti_type}tseries')
+
+                if cifti_type == 'd':
+                    parcel_axis = surface_parcels()
+                    dpconn = cifti_class(gen_data([parcel_axis, main_axis]), (parcel_axis, main_axis))
+                    check_io(dpconn, 'dpconn')
+                else:
+                    dense_axis = surface_brain_model()
+                    pdconn = cifti_class(gen_data([dense_axis, main_axis]), (dense_axis, main_axis))
+                    check_io(pdconn, 'pdconn')
+
+
+def test_extract_dense():
+    vol_bm = volumetric_brain_model()
+    surf_bm = surface_brain_model()
+    for bm in (vol_bm + surf_bm, surf_bm + vol_bm):
+        for ndim, no_other_axis in ((1, True), (2, False), (2, True)):
+            if ndim == 1:
+                data = cifti.DenseCifti(gen_data([bm]), [bm])
+            else:
+                scl = cifti2_axes.ScalarAxis(['A', 'B', 'C'])
+                data = cifti.DenseCifti(gen_data([scl, bm]),
+                                        [None if no_other_axis else scl, bm])
+
+            # extract volume
+            ref_arr = data.arr[..., data.brain_model_axis.volume_mask]
+            vol_image = data.to_image(fill=np.nan)
+            if ndim == 1:
+                assert vol_image.shape == data.brain_model_axis.volume_shape
+            else:
+                assert vol_image.shape == data.brain_model_axis.volume_shape + (3, )
+            assert np.isfinite(vol_image.data).sum() == len(vol_bm) * (3 if ndim == 2 else 1)
+            testing.assert_equal(vol_image.data[tuple(vol_bm.voxel.T)], ref_arr.T)
+
+            from_image = cifti.DenseCifti.from_image(vol_image)
+            assert from_image.brain_model_axis == vol_bm
+            testing.assert_equal(from_image.arr, ref_arr)
+
+            # extract surface
+            ref_arr = data.arr[..., data.brain_model_axis.surface_mask]
+            mask, surf_data = data.surface('cortex', partial=True)
+            assert surf_data.shape[-1] < 100
+            testing.assert_equal(ref_arr, surf_data)
+            testing.assert_equal(surf_bm.vertex, mask)
+
+            surf_data_full = data.surface('cortex', fill=np.nan)
+            assert surf_data_full.shape[-1] == 100
+            mask_full = np.isfinite(surf_data_full)
+            if ndim == 2:
+                assert (mask_full.any(0) == mask_full.all(0)).all()
+                mask_full = mask_full[0]
+            assert mask_full.sum() == len(surf_bm)
+            assert mask_full[..., mask].sum() == len(surf_bm)
+            testing.assert_equal(surf_data_full[..., mask_full], ref_arr)
+
+
+def test_extract_parcel():
+    vol_parcel, vol_mask = volumetric_parcels(return_mask=True)
+    surf_parcel, surf_mask = surface_parcels(return_mask=True)
+    parcel = vol_parcel + surf_parcel
+    for ndim, no_other_axis in ((1, True), (2, False), (2, True)):
+        if ndim == 1:
+            data = cifti.ParcelCifti(gen_data([parcel]), [parcel])
+        else:
+            scl = cifti2_axes.ScalarAxis(['A', 'B', 'C'])
+            data = cifti.ParcelCifti(gen_data([scl, parcel]),
+                                     [None if no_other_axis else scl, parcel])
+
+        # extract volume
+        vol_image = data.to_image(fill=np.nan)
+        if ndim == 1:
+            assert vol_image.shape == data.parcel_axis.volume_shape
+        else:
+            assert vol_image.shape == data.parcel_axis.volume_shape + (3, )
+        assert np.isfinite(vol_image.data).sum() == np.sum(vol_mask != 0) * (3 if ndim == 2 else 1)
+        if ndim == 1:
+            testing.assert_equal(vol_mask != 0, np.isfinite(vol_image.data))
+            for idx in range(1, 5):
+                testing.assert_allclose(vol_image.data[vol_mask == idx], data.arr[..., idx - 1])
+        else:
+            for idx in range(3):
+                testing.assert_equal(vol_mask != 0, np.isfinite(vol_image.data[..., idx]))
+                for idx2 in range(1, 5):
+                    testing.assert_allclose(vol_image.data[vol_mask == idx2, idx], data.arr[idx, idx2 - 1])
+
+        # extract surface
+        mask, surf_data = data.surface('cortex', partial=True)
+        assert surf_data.shape[-1] == (surf_mask != 0).sum()
+        assert (surf_mask[mask] != 0).all()
+        print(data.arr)
+        for idx in range(1, 5):
+            if ndim == 1:
+                testing.assert_equal(surf_data.T[surf_mask[mask] == idx], data.arr[idx + 3])
+            else:
+                for idx2 in range(3):
+                    testing.assert_equal(surf_data.T[surf_mask[mask] == idx, idx2], data.arr[idx2, idx + 3])
+
+        surf_data_full = data.surface('cortex', partial=False)
+        assert surf_data_full.shape[-1] == 100
+        if ndim == 1:
+            testing.assert_equal(np.isfinite(surf_data_full), surf_mask != 0)
+            for idx in range(1, 5):
+                testing.assert_equal(surf_data_full.T[surf_mask == idx], data.arr[idx + 3])
+        else:
+            for idx2 in range(3):
+                testing.assert_equal(np.isfinite(surf_data_full)[idx2], (surf_mask != 0))
+                for idx in range(1, 5):
+                    testing.assert_equal(surf_data_full.T[surf_mask == idx, idx2], data.arr[idx2, idx + 3])
+
+
+def test_brainstructure():
+    for primary in ['cortex', 'cerebellum']:
+        for secondary in [None, 'white', 'pial']:
+            for gtype in [None, 'volume', 'surface']:
+                for orientation in ['left', 'right', 'both']:
+                    bst = cifti.BrainStructure(primary, secondary, orientation, gtype)
+                    print(bst.cifti)
+                    assert bst.cifti == 'CIFTI_STRUCTURE_%s%s' % (primary.upper(), '' if orientation == 'both' else '_' + orientation.upper())
+                    assert bst.gifti['AnatomicalStructurePrimary'][:len(primary)] == primary.capitalize()
+                    assert len(bst.gifti) == (1 if secondary is None else 2)
+                    if secondary is not None:
+                        assert bst.gifti['AnatomicalStructureSecondary'] == secondary.capitalize()
+                    assert bst == cifti.BrainStructure(primary, secondary, orientation, gtype)
+                    assert bst == bst
+                    assert bst != cifti.BrainStructure('Thalamus', secondary, orientation, gtype)
+                    if secondary is None:
+                        assert bst == cifti.BrainStructure(primary, 'midplane', orientation, gtype)
+                    else:
+                        assert bst != cifti.BrainStructure(primary, 'midplane', orientation, gtype)
+                    if (gtype == 'volume' and primary == 'cortex') or (gtype == 'surface' and primary != 'cortex'):
+                        assert cifti.BrainStructure.from_string(bst.cifti) != bst
+                    else:
+                        assert cifti.BrainStructure.from_string(bst.cifti) == bst
+                    assert cifti.BrainStructure.from_string(bst.cifti).secondary is None

tests/test_deprecated.py → fsl/tests/test_deprecated.py

@@ -7,12 +7,22 @@ import pytest
 import fsl.utils.deprecated as deprecated
 
 
-# the line number of the warning is hard coded in
-# the unit tests below. Don't change the line number!
+# these  get updated in the relevant functions
+WARNING_LINE_NUMBER = None
+DEPRECATED_LINE_NUMBER = None
+
+def _linenum(pattern):
+    with open(__file__, 'rt') as f:
+        for i, line in enumerate(f.readlines(), 1):
+            if pattern in line:
+                return i
+    return -1
+
+
 def emit_warning():
     deprecated.warn('blag', vin='1.0.0', rin='2.0.0', msg='yo')
-
-WARNING_LINE_NUMBER = 13
+    global WARNING_LINE_NUMBER
+    WARNING_LINE_NUMBER = _linenum('deprecated.warn(\'blag\'')
 
 
 @deprecated.deprecated(vin='1.0.0', rin='2.0.0', msg='yo')
@@ -20,9 +30,9 @@ def depfunc():
     pass
 
 def call_dep_func():
-    depfunc()
-
-DEPRECATED_LINE_NUMBER = 23
+    depfunc()  # mark
+    global DEPRECATED_LINE_NUMBER
+    DEPRECATED_LINE_NUMBER = _linenum('depfunc()  # mark')
 
 
 def _check_warning(w, name, lineno):

fsl/tests/test_dicom.py

+#!/usr/bin/env python
+#
+# These tests require an internet connection, and will only work on linux.
+#
+
+import os.path        as op
+import                   os
+import functools      as ft
+import subprocess     as sp
+import                   tarfile
+import                   zipfile
+import                   random
+import                   string
+import                   binascii
+import                   contextlib
+import urllib.request as request
+from   unittest import   mock
+
+import pytest
+
+import fsl.data.dicom    as fsldcm
+import fsl.utils.tempdir as tempdir
+
+
+from fsl.tests import mockFSLDIR, touch
+
+
+datadir = op.join(op.dirname(__file__), 'testdata')
+
+
+pytestmark = pytest.mark.dicomtest
+
+
+@contextlib.contextmanager
+def install_dcm2niix(version='1.0.20220720'):
+    filenames = {
+        '1.0.20201102' : 'v1.0.20201102/dcm2niix_lnx.zip',
+        '1.0.20190902' : 'v1.0.20190902/dcm2niix_lnx.zip',
+        '1.0.20181125' : 'v1.0.20181125/dcm2niix_25-Nov-2018_lnx.zip',
+        '1.0.20171017' : 'v1.0.20171017/dcm2niix_18-Oct-2017_lnx.zip',
+        '1.0.20220720' : 'v1.0.20220720/dcm2niix_lnx.zip',
+    }
+    prefix = 'https://github.com/rordenlab/dcm2niix/releases/download/'
+    url    = prefix + filenames.get(version, f'v{version}/dcm2niix_lnx.zip')
+
+    with tempdir.tempdir() as td:
+        request.urlretrieve(url, 'dcm2niix.zip')
+
+        with zipfile.ZipFile('dcm2niix.zip', 'r') as f:
+            f.extractall('.')
+
+        os.chmod(op.join(td, 'dcm2niix'), 0o755)
+
+        path = op.abspath('dcm2niix')
+
+        with mock.patch('fsl.data.dicom.dcm2niix', return_value=path):
+            try:
+                yield
+            finally:
+                fsldcm.installedVersion.invalidate()
+
+
+def test_disabled():
+    with mock.patch('fsl.data.dicom.enabled', return_value=False):
+        with pytest.raises(RuntimeError):
+            fsldcm.scanDir('.')
+        with pytest.raises(RuntimeError):
+            fsldcm.loadSeries({})
+
+
+def test_dcm2niix():
+    """
+    """
+    env = os.environ.copy()
+    env.pop('FSLDIR', None)
+    with tempdir.tempdir() as td:
+        env['PATH'] = td
+        with mock.patch('os.environ', env):
+            assert fsldcm.dcm2niix() == 'dcm2niix'
+
+        bindir   = op.join(td, 'bin')
+        dcm2niix = op.join(bindir, 'dcm2niix')
+        os.makedirs(bindir)
+        touch(dcm2niix)
+        os.chmod(dcm2niix, 0o755)
+        env['PATH'] = bindir
+        with mock.patch('os.environ', env):
+            assert fsldcm.dcm2niix() == dcm2niix
+
+        with mockFSLDIR(bin=['dcm2niix']) as fsldir:
+            env['FSLDIR'] = fsldir
+            dcm2niix      = op.join(fsldir, 'bin', 'dcm2niix')
+            with mock.patch('os.environ', env):
+                assert fsldcm.dcm2niix() == dcm2niix
+
+
+def test_installedVersion():
+    tests = [
+        ('1.0.20190902', (1, 0, 2019, 9, 2)),
+        ('1.0.20181125', (1, 0, 2018, 11, 25)),
+        ('1.0.20171017', (1, 0, 2017, 10, 17))]
+
+    for version, expect in tests:
+        fsldcm.installedVersion.invalidate()
+        with install_dcm2niix(version):
+            got = fsldcm.installedVersion()
+            assert got == expect
+
+
+
+def test_enabled():
+
+    try:
+        with install_dcm2niix('1.0.20190902'):
+            fsldcm.installedVersion.invalidate()
+            assert fsldcm.enabled()
+
+        # test dcm2niix not present
+        with mock.patch('subprocess.check_output',
+                        side_effect=Exception()):
+            fsldcm.installedVersion.invalidate()
+            assert not fsldcm.enabled()
+
+        # test presence of different versions
+        tests = [(b'version v2.1.20191212', True),
+                 (b'version v1.0.20190902', True),
+                 (b'version v1.0.20171216', True),
+                 (b'version v1.0.20171215', True),
+                 (b'version v1.0.20171214', False),
+                 (b'version v1.0.20160930', False),
+                 (b'version v1.0.20160929', False),
+                 (b'version v0.0.00000000', False),
+                 (b'version blurgh',        False)]
+
+        for verstr, expected in tests:
+            fsldcm.installedVersion.invalidate()
+            with mock.patch('subprocess.check_output', return_value=verstr):
+                assert fsldcm.enabled() == expected
+
+    finally:
+        fsldcm.installedVersion.invalidate()
+
+
+def test_scanDir():
+
+    with install_dcm2niix():
+
+        series = fsldcm.scanDir('.')
+        assert len(series) == 0
+
+        datafile = op.join(datadir, 'example_dicom.tbz2')
+
+        with tarfile.open(datafile) as f:
+            f.extractall(filter='data')
+
+        series = fsldcm.scanDir('.')
+        assert len(series) == 2
+
+        for s in series:
+            assert s['PatientName'] in ('MCCARTHY_PAUL',
+                                        'MCCARTHY^PAUL',
+                                        'MCCARTHY_PAUL_2',
+                                        'MCCARTHY^PAUL^2')
+
+
+def test_sersiesCRC():
+    RANDOM = object()
+    tests = [
+        ({'SeriesInstanceUID' : 'hello-world'},            '2983461467'),
+        ({'SeriesInstanceUID' : RANDOM, 'EchoNumber' : 0}, RANDOM),
+        ({'SeriesInstanceUID' : RANDOM, 'EchoNumber' : 1}, RANDOM),
+        ({'SeriesInstanceUID' : RANDOM, 'EchoNumber' : 2}, RANDOM),
+        ({'SeriesInstanceUID' : RANDOM, 'EchoNumber' : 3}, RANDOM),
+    ]
+
+    for series, expect in tests:
+        series = dict(series)
+        if expect is RANDOM:
+            expect = ''.join([random.choice(string.ascii_letters + string.digits)
+                              for i in range(30)])
+            series['SeriesInstanceUID'] = expect
+            expect = str(binascii.crc32(expect.encode()))
+        echo = series.get('EchoNumber', 0)
+        if echo > 1:
+            expect += '.{}'.format(echo)
+        assert fsldcm.seriesCRC(series) == expect
+
+
+def test_loadSeries():
+
+    # test a pre-CRC and a post-CRC version
+    for version in ('1.0.20181125', '1.0.20201102'):
+
+        with install_dcm2niix(version):
+
+            datafile = op.join(datadir, 'example_dicom.tbz2')
+
+            with tarfile.open(datafile) as f:
+                f.extractall()
+
+            dcmdir   = os.getcwd()
+            series   = fsldcm.scanDir(dcmdir)
+            expShape = (512, 512, 1)
+
+            for s in series:
+
+                imgs = fsldcm.loadSeries(s)
+
+                for img in imgs:
+
+                    assert img.dicomDir               == dcmdir
+                    assert img.shape                  == expShape
+                    assert img[:].shape               == expShape
+                    assert img.getMeta('PatientName') in ('MCCARTHY_PAUL',
+                                                          'MCCARTHY^PAUL',
+                                                          'MCCARTHY_PAUL_2',
+                                                          'MCCARTHY^PAUL^2')
+                    assert 'PatientName'                      in img.metaKeys()
+                    assert 'MCCARTHY_PAUL'                    in img.metaValues() or \
+                           'MCCARTHY^PAUL'                    in img.metaValues() or \
+                           'MCCARTHY_PAUL_2'                  in img.metaValues() or \
+                           'MCCARTHY^PAUL^2'                  in img.metaValues()
+                    assert ('PatientName', 'MCCARTHY_PAUL')   in img.metaItems() or \
+                           ('PatientName', 'MCCARTHY^PAUL')   in img.metaItems() or \
+                           ('PatientName', 'MCCARTHY_PAUL_2') in img.metaItems() or \
+                           ('PatientName', 'MCCARTHY^PAUL^2') in img.metaItems()

tests/test_dtifit.py → fsl/tests/test_dtifit.py

@@ -10,7 +10,7 @@ import numpy   as np
 
 import pytest
 
-import tests
+import fsl.tests       as tests
 import fsl.data.dtifit as dtifit
 import fsl.data.image  as fslimage
 
@@ -169,12 +169,12 @@ def test_DTIFitTensor():
         l2file = op.join(testdir, 'dti_L2.nii')
         l3file = op.join(testdir, 'dti_L3.nii')
 
-        v1 = tests.make_random_image(v1file, (5, 5, 5, 3)).get_data()
-        v2 = tests.make_random_image(v2file, (5, 5, 5, 3)).get_data()
-        v3 = tests.make_random_image(v3file, (5, 5, 5, 3)).get_data()
-        l1 = tests.make_random_image(l1file, (5, 5, 5))   .get_data()
-        l2 = tests.make_random_image(l2file, (5, 5, 5))   .get_data()
-        l3 = tests.make_random_image(l3file, (5, 5, 5))   .get_data()
+        v1 = np.asanyarray(tests.make_random_image(v1file, (5, 5, 5, 3)).dataobj)
+        v2 = np.asanyarray(tests.make_random_image(v2file, (5, 5, 5, 3)).dataobj)
+        v3 = np.asanyarray(tests.make_random_image(v3file, (5, 5, 5, 3)).dataobj)
+        l1 = np.asanyarray(tests.make_random_image(l1file, (5, 5, 5))   .dataobj)
+        l2 = np.asanyarray(tests.make_random_image(l2file, (5, 5, 5))   .dataobj)
+        l3 = np.asanyarray(tests.make_random_image(l3file, (5, 5, 5))   .dataobj)
 
         dtiobj = dtifit.DTIFitTensor(testdir)
 

tests/test_ensure.py → fsl/tests/test_ensure.py

@@ -5,6 +5,7 @@
 # Author: Paul McCarthy <pauldmccarthy@gmail.com>
 #
 
+import pathlib
 
 import numpy   as np
 import nibabel as nib
@@ -12,7 +13,7 @@ import nibabel as nib
 import fsl.utils.tempdir as tempdir
 import fsl.utils.ensure  as ensure
 
-from . import make_random_image
+from fsl.tests import make_random_image
 
 
 def test_ensureIsImage():
@@ -22,12 +23,14 @@ def test_ensureIsImage():
 
         assert ensure.ensureIsImage(img) is img
 
-        loaded = [ensure.ensureIsImage('image.nii'),
-                  ensure.ensureIsImage('image')]
+        loaded = [ensure.ensureIsImage(             'image.nii'),
+                  ensure.ensureIsImage(             'image'),
+                  ensure.ensureIsImage(pathlib.Path('image')),
+                  ensure.ensureIsImage(pathlib.Path('image.nii'))]
 
         for l in loaded:
             assert isinstance(l, nib.nifti1.Nifti1Image)
-            assert np.all(img.get_data() == l.get_data())
+            assert np.all(np.asanyarray(img.dataobj) == np.asanyarray(l.dataobj))
 
         l = None
         loaded = None