Merge branch 'master' into 'master'

Support > 4D

See merge request !34

.gitlab-ci.yml

@@ -66,6 +66,9 @@ stages:
 #   - TWINE_PASSWORD:                - Password to use when uploading to pypi
 #
 #   - TWINE_REPOSITORY_URL:          - Pypi repository to upload to
+#
+#   - WXPYTHON_DEBIAN8_URL:          - Url to a location containg binary wheels
+#                                      for wxPython/debian 8
 ###############################################################################
 
 
@@ -230,12 +233,12 @@ variables:
     # We need to install xvfb, and all of
     # the wxpython dependencies.
     - apt-get update  -y
-    - apt-get install -y xvfb libgtk-3-0
+    - apt-get install -y xvfb libgtk-2-0
     - apt-get install -y libnotify4 freeglut3 libsdl1.2debian
 
     # Linux builds for wxPython are currently not
     # on pypi, but are available at this url.
-    - pip install --only-binary wxpython -f https://wxpython.org/Phoenix/snapshot-builds/linux/gtk3/debian-8/ wxpython
+    - pip install --only-binary wxpython -f $WXPYTHON_DEBIAN8_URL wxpython
 
     # All other deps can be installed as
     # normal. scipy is required by nibabel,

fsl/__init__.py

@@ -13,16 +13,12 @@ following sub-packages:
    fsl.data
    fsl.utils
    fsl.scripts
+   fsl.version
 
-.. note:: The ``fslpy`` version number (currently |version|) is set in a
-          single place - the :mod:`fsl.version` module.
+.. note:: The ``fsl`` namespace is a ``pkgutil``-style *namespace package* -
+          it can be used across different projects - see
+          https://packaging.python.org/guides/packaging-namespace-packages/
+          for details.
 """
 
-
-import fsl.version
-
-
-__version__ = fsl.version.__version__
-"""The current ``fslpy`` version number. This information is stored in the
-:mod:`fsl.version` module.
-"""
+__path__ = __import__('pkgutil').extend_path(__path__, __name__)

fsl/data/atlases.py

@@ -599,7 +599,7 @@ class Atlas(fslimage.Image):
         # Even though all the FSL atlases
         # are in MNI152 space, not all of
         # their sform_codes are correctly set
-        self.nibImage.get_header().set_sform(
+        self.nibImage.header.set_sform(
             None, code=constants.NIFTI_XFORM_MNI_152)
 
         self.desc = atlasDesc

fsl/data/image.py

@@ -6,7 +6,7 @@
 # Author: Paul McCarthy <pauldmccarthy@gmail.com>
 #
 """This module provides the :class:`Nifti` and :class:`Image` classes, for
-representing 3D/4D NIFTI1 and NIFTI2 images. The ``nibabel`` package is used
+representing NIFTI1 and NIFTI2 images. The ``nibabel`` package is used
 for file I/O.
 
 
@@ -38,6 +38,7 @@ import                      string
 import                      logging
 
 import                      six
+import                      deprecation
 import numpy             as np
 
 import nibabel           as nib
@@ -187,9 +188,6 @@ class Nifti(notifier.Notifier):
         header                   = header
         origShape, shape, pixdim = self.__determineShape(header)
 
-        if len(shape) < 3 or len(shape) > 4:
-            raise RuntimeError('Only 3D or 4D images are supported')
-
         voxToWorldMat = self.__determineTransform(header)
         worldToVoxMat = transform.invert(voxToWorldMat)
 
@@ -451,7 +449,19 @@ class Nifti(notifier.Notifier):
         return fileslice.canonical_slicers(sliceobj, self.__origShape)
 
 
-    # TODO: Remove this method, and use the shape attribute directly
+    @property
+    def ndims(self):
+        """Returns the number of dimensions in this image. This number may not
+        match the number of dimensions specified in the NIFTI header, as
+        trailing dimensions of length 1 are ignored. But it is guaranteed to be
+        at least 3.
+        """
+        return len(self.__shape)
+
+
+    @deprecation.deprecated(deprecated_in='1.1.0',
+                            removed_in='1.2.0',
+                            details='Use ndims instead')
     def is4DImage(self):
         """Returns ``True`` if this image is 4D, ``False`` otherwise. """
         return len(self.__shape) > 3 and self.__shape[3] > 1
@@ -626,7 +636,7 @@ class Nifti(notifier.Notifier):
 
 
 class Image(Nifti):
-    """Class which represents a 3D/4D NIFTI image. Internally, the image is
+    """Class which represents a NIFTI image. Internally, the image is
     loaded/stored using a :mod:`nibabel.nifti1.Nifti1Image` or
     :mod:`nibabel.nifti2.Nifti2Image`, and data access managed by a
     :class:`.ImageWrapper`.
@@ -818,7 +828,7 @@ class Image(Nifti):
             else:
                 name = 'Nibabel image'
 
-        Nifti.__init__(self, nibImage.get_header())
+        Nifti.__init__(self, nibImage.header)
 
         self.name                = name
         self.__lName             = '{}_{}'.format(id(self), self.name)
@@ -1001,8 +1011,7 @@ class Image(Nifti):
             # Otherwise if the number of values in the
             # image is bigger than the size threshold,
             # we'll calculate the range from a sample:
-            if len(self.shape) == 3: self.__imageWrapper[:, :, 0]
-            else:                    self.__imageWrapper[:, :, :, 0]
+            self.__imageWrapper[..., 0]
 
 
     def loadData(self):
@@ -1056,7 +1065,7 @@ class Image(Nifti):
             nib.save(self.__nibImage, filename)
             self.__fileobj.close()
             self.__nibImage, self.__fileobj = loadIndexedImageFile(filename)
-            self.header = self.__nibImage.get_header()
+            self.header = self.__nibImage.header
 
             # We have to create a new ImageWrapper
             # instance too, as we have just destroyed

fsl/data/imagewrapper.py

@@ -187,6 +187,11 @@ class ImageWrapper(notifier.Notifier):
             if d == 1: self.__numRealDims -= 1
             else:      break
 
+        # Degenerate case - if every
+        # dimension has length 1
+        if self.__numRealDims == 0:
+            self.__numRealDims = len(image.shape)
+
         # And save the number of
         # 'padding' dimensions too.
         self.__numPadDims = len(image.shape) - self.__numRealDims
@@ -314,7 +319,7 @@ class ImageWrapper(notifier.Notifier):
         # header (which may or may not contain
         # useful values).
         low, high = self.__range
-        hdr       = self.__image.get_header()
+        hdr       = self.__image.header
 
         if low  is None: low  = float(hdr['cal_min'])
         if high is None: high = float(hdr['cal_max'])

fsl/data/melodicimage.py

@@ -77,7 +77,7 @@ class MelodicImage(fslimage.Image):
             dataImage = fslimage.Image(dataFile,
                                        loadData=False,
                                        calcRange=False)
-            if dataImage.is4DImage():
+            if dataImage.ndims >= 4:
                 self.__tr = dataImage.pixdim[3]
 
 

fsl/version.py

@@ -41,7 +41,7 @@ import            re
 import            string
 
 
-__version__ = '1.0.6.dev'
+__version__ = '1.1.0.dev'
 """Current version number, as a string. """
 
 

requirements.txt

 six==1.*
+deprecation==1.*
 numpy==1.*
 nibabel==2.*
-indexed_gzip==0.3.*
+indexed_gzip==0.*
 wxPython>=3.0.2.0,<4.1

tests/test_image.py

@@ -22,12 +22,14 @@ import nibabel      as nib
 
 from nibabel.spatialimages import ImageFileError
 
-import fsl.data.constants as constants
-import fsl.data.image     as fslimage
-import fsl.utils.path     as fslpath
+import fsl.data.constants    as constants
+import fsl.data.image        as fslimage
+import fsl.data.imagewrapper as imagewrapper
+import fsl.utils.path        as fslpath
 
 from . import make_random_image
 from . import make_dummy_file
+from . import testdir
 
 
 def make_image(filename=None,
@@ -54,7 +56,7 @@ def make_image(filename=None,
     hdr.set_zooms([abs(p) for p in pixdims])
 
     xform = np.eye(4)
-    for i, p in enumerate(pixdims):
+    for i, p in enumerate(pixdims[:3]):
         xform[i, i] = p
 
     data  = np.array(np.random.random(dims) * 100, dtype=dtype)
@@ -239,15 +241,20 @@ def _test_Image_atts(imgtype):
 
     # (file, dims, pixdims, dtype)
     dtypes = [np.uint8, np.int16, np.int32, np.float32, np.double]
-    dims   = [(10,  1,  1),
+    dims   = [(1,   1,  1),
+              (10,  1,  1),
               (1,  10,  1),
               (1,  1,  10),
               (10,  10, 1),
               (10,  1, 10),
               (1,  10, 10),
               (10, 10, 10),
-              (1,   1,  1, 5),
-              (10,  10, 1, 5),
+              (1,   1,  1, 1),
+              (10,  1,  1, 1),
+              (1,  10,  1, 1),
+              (1,   1, 10, 1),
+              (10, 10,  1, 1),
+              (10, 10, 1, 5),
               (10,  1, 10, 5),
               (1,  10, 10, 5),
               (10, 10, 10, 5)]
@@ -276,17 +283,21 @@ def _test_Image_atts(imgtype):
 
             dims, pixdims, dtype = atts
 
-            ndims   = len(dims)
-            pixdims = pixdims[:ndims]
+            expdims    = imagewrapper.canonicalShape(dims)
+            expndims   = len(expdims)
+            ndims      = len(dims)
+            pixdims    = pixdims[:ndims]
+            exppixdims = pixdims[:expndims]
 
             path = op.abspath(op.join(testdir, path))
             i    = fslimage.Image(path)
 
-            assert tuple(i.shape)                       == tuple(dims)
-            assert tuple(i.pixdim)                      == tuple(pixdims)
+            assert tuple(i.shape)                       == tuple(expdims)
+            assert tuple(i.pixdim)                      == tuple(exppixdims)
             assert tuple(i.nibImage.shape)              == tuple(dims)
             assert tuple(i.nibImage.header.get_zooms()) == tuple(pixdims)
 
+            assert i.ndims      == expndims
             assert i.dtype      == dtype
             assert i.name       == op.basename(path)
             assert i.dataSource == fslpath.addExt(path,
@@ -817,6 +828,34 @@ def _test_Image_2D(imgtype):
         shutil.rmtree(testdir)
 
 
+def  test_Image_5D_analyze(): _test_Image_5D(0)
+def  test_Image_5D_nifti1():  _test_Image_5D(1)
+def  test_Image_5D_nifti2():  _test_Image_5D(2)
+def _test_Image_5D(imgtype):
+
+    testdims = [
+        ( 1,  1,  1, 1, 5),
+        (10, 10,  1, 1, 5),
+        (10, 10, 10, 1, 5),
+        ( 1,  1,  1, 4, 5),
+        (10, 10,  1, 4, 5),
+        (10, 10, 10, 4, 5),
+    ]
+
+    for dims in testdims:
+
+        with testdir() as td:
+
+            path = op.join(td, 'test.nii')
+
+            make_image(path, imgtype, dims, [1] * len(dims))
+
+            img = fslimage.Image(path)
+
+            assert img.shape == dims
+            assert img.ndims == 5
+
+
 def test_Image_voxelsToScaledVoxels():
 
     imgTypes = [0, 1, 2]