Merge branch 'rf/compressed_voxelwise_evs' into 'master'

Rf/compressed voxelwise evs

See merge request fsl/fslpy!115

CHANGELOG.rst

@@ -2,6 +2,27 @@ This document contains the ``fslpy`` release history in reverse chronological
 order.
 
 
+2.1.0 (Under development)
+-------------------------
+
+
+Added
+^^^^^
+
+
+* New tensor conversion routines in the :mod:`.dtifit` module (Michiel
+  Cottaar).
+
+
+Fixed
+^^^^^
+
+
+* The :class:`.FeatDesign` class now handles "compressed" voxelwise EV files,
+  such as those generated by `PNM
+  <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PNM>`_.
+
+
 2.0.1 (Monday April 1st 2019)
 -----------------------------
 

fsl/data/dtifit.py

@@ -3,6 +3,7 @@
 # dtifit.py - The DTIFitTensor class, and some related utility functions.
 #
 # Author: Paul McCarthy <pauldmccarthy@gmail.com>
+# Author: Michiel Cottaar <michiel.cottaar@ndcn.ox.ac.uk>
 #
 """This module provides the :class:`.DTIFitTensor` class, which encapsulates
 the diffusion tensor data generated by the FSL ``dtifit`` tool.

fsl/data/featdesign.py

@@ -214,7 +214,7 @@ class FEATFSFDesign(object):
                             'for ev {}'.format(ev.index))
                 continue
 
-            design[:, ev.index] = ev.image[x, y, z, :]
+            design[:, ev.index] = ev.getData(x, y, z)
 
         return design
 
@@ -228,6 +228,17 @@ class VoxelwiseEVMixin(object):
     ``filename`` Path to the image file containing the data for this EV
     ``image``    Reference to the :class:`.Image` object
     ============ ======================================================
+
+    Some FSL tools (e.g. `PNM
+    <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PNM>`_) generate *compressed*
+    voxelwise EVs, where there is only one voxel per slice. For example,
+    if the input data has shape ``(x, y, z, t)``, and slices are acquired
+    along the Z plane, voxelwise EV files generated by PNM will have shape
+    ``(1, 1, z, t)``.
+
+    Therefore, using the :meth:`getData` method is preferable to accessing
+    the :meth:`image` directly, as ``getData`` will check for compressed
+    images, and adjust the voxel coordinates accordingly.
     """
 
     def __init__(self, filename):
@@ -272,6 +283,29 @@ class VoxelwiseEVMixin(object):
         return self.__image
 
 
+    def getData(self, x, y, z):
+        """Returns the data at the specified voxel, taking into account
+        compressed voxelwise EVs.
+        """
+        image = self.image
+
+        if image is None:
+            return None
+
+        dx, dy, dz = image.shape[:3]
+
+        # "Compressed" images have one voxel
+        # per slice, i.e. they have shape
+        # [1, 1, nslices, ntimepoints] (if
+        # Z is the slice plane).
+        if sum((dx == 1, dy == 1, dz == 1)) == 2:
+            if dx == 1: x = 0
+            if dy == 1: y = 0
+            if dz == 1: z = 0
+
+        return image[x, y, z, :]
+
+
 class EV(object):
     """Class representing an explanatory variable in a FEAT design matrix.
 

tests/test_featdesign.py

@@ -412,3 +412,19 @@ def test_VoxelwiseEVs():
             exp = img.dataobj[x, y, z, :]
             assert np.all(ev1.image[x, y, z, :] == exp)
             assert np.all(ev2.image[x, y, z, :] == exp)
+
+
+def test_compressed_voxelwise_ev():
+
+    testcases = [((1, 1, 10, 10), (0, 0, 5)),
+                 ((1, 10, 1, 10), (0, 5, 0)),
+                 ((10, 1, 1, 10), (5, 0, 0))]
+
+    with tempdir():
+
+        for shape, vox in testcases:
+            img = tests.make_random_image('vev.nii.gz',  shape)
+            vev = featdesign.VoxelwiseEV(0, 0, 'ev1', 'vev.nii.gz')
+            x, y, z = vox
+
+            assert np.all(vev.getData(5, 5, 5) == img.dataobj[x, y, z, :])