From c428f937281546c309eca6dba982885f34b13cbc Mon Sep 17 00:00:00 2001
From: Paul McCarthy <pauld.mccarthy@gmail.com>
Date: Thu, 22 Sep 2016 14:38:23 +0100
Subject: [PATCH] That last ImageWrapper fix didn't fix anything. This should.
---
fsl/data/image.py | 25 ++++++-----------
fsl/data/imagewrapper.py | 60 ++++++++++++++++++++++++++++++++--------
2 files changed, 56 insertions(+), 29 deletions(-)
diff --git a/fsl/data/image.py b/fsl/data/image.py
index 90a1c8e63..84f4ea32a 100644
--- a/fsl/data/image.py
+++ b/fsl/data/image.py
@@ -161,26 +161,17 @@ class Nifti(object):
- A sequence/tuple containing the zooms/pixdims.
"""
+ # The canonicalShape method figures out
+ # the data shape that we should use.
origShape = list(header.get_data_shape())
- shape = list(origShape)
+ shape = imagewrapper.canonicalShape(origShape)
pixdims = list(header.get_zooms())
- # Squeeze out empty dimensions, as
- # 3D image can sometimes be listed
- # as having 4 or more dimensions
- for i in reversed(range(len(shape))):
- if shape[i] == 1: shape = shape[:i]
- else: break
-
- # But make sure the shape
- # has at 3 least dimensions
- if len(shape) < 3:
- shape = shape + [1] * (3 - len(shape))
-
- # The same goes for the pixdim - if get_zooms()
- # doesn't return at least 3 values, we'll fall
- # back to the pixdim field in the header.
- if len(pixdims) < 3:
+ # if get_zooms() doesn't return at
+ # least len(shape) values, we'll
+ # fall back to the pixdim field in
+ # the header.
+ if len(pixdims) < len(shape):
pixdims = header['pixdim'][1:]
pixdims = pixdims[:len(shape)]
diff --git a/fsl/data/imagewrapper.py b/fsl/data/imagewrapper.py
index 79a5b0c37..b05510d8a 100644
--- a/fsl/data/imagewrapper.py
+++ b/fsl/data/imagewrapper.py
@@ -168,6 +168,15 @@ class ImageWrapper(notifier.Notifier):
# 'padding' dimensions too.
self.__numPadDims = len(image.shape) - self.__numRealDims
+ # Too many shapes! Figure out
+ # what shape we should present
+ # the data as (e.g. at least 3
+ # dimensions). This is used in
+ # __getitem__ to force the
+ # result to have the correct
+ # dimensionality.
+ self.__canonicalShape = canonicalShape(image.shape)
+
# The internal state is stored
# in these attributes - they're
# initialised in the reset method.
@@ -335,14 +344,6 @@ class ImageWrapper(notifier.Notifier):
if isTuple:
sliceobj = sliceTupleToSliceObj(sliceobj)
- # Truncate some dimensions from the
- # slice object if it has too many
- # (e.g. trailing dims of length 1).
- ndims = len(self.__image.shape)
-
- if len(sliceobj) > ndims:
- sliceobj = sliceobj[:ndims]
-
# If the image has not been loaded
# into memory, we can use the nibabel
# ArrayProxy. Otheriwse if it is in
@@ -541,6 +542,12 @@ class ImageWrapper(notifier.Notifier):
if not isinstance(sliceobj, tuple):
sliceobj = (sliceobj,)
+ # Figure out the number of dimensions
+ # that the result should have, given
+ # this slice object.
+ expNdims = len(self.__canonicalShape) - \
+ len([s for s in sliceobj if isinstance(s, int)])
+
# Truncate some dimensions from the
# slice object if it has too many
# (e.g. trailing dims of length 1).
@@ -550,20 +557,26 @@ class ImageWrapper(notifier.Notifier):
if len(sliceobj) > ndims:
sliceobj = sliceobj[:ndims]
- sliceobj = nib.fileslice.canonical_slicers(sliceobj, shape)
-
# TODO Cache 3D images for large 4D volumes,
# so you don't have to hit the disk?
- data = self.__getData(sliceobj)
+ sliceobj = nib.fileslice.canonical_slicers(sliceobj, shape)
+ data = self.__getData(sliceobj)
if not self.__covered:
- slices = sliceObjToSliceTuple(sliceobj, self.__image.shape)
+ slices = sliceObjToSliceTuple(sliceobj, shape)
if not sliceCovered(slices, self.__coverage):
self.__updateDataRangeOnRead(slices, data)
+ # Make sure that the result has
+ # the shape that the caller is
+ # expecting.
+ ndims = len(data.shape)
+ if ndims < expNdims:
+ data = data.reshape(list(data.shape) + [1] * (expNdims - ndims))
+
return data
@@ -594,6 +607,29 @@ class ImageWrapper(notifier.Notifier):
self.__updateDataRangeOnWrite(slices, values)
+def canonicalShape(shape):
+ """Calculates a *canonical* shape, how the given ``shape`` should
+ be presented. The shape is forced to be at least three dimensions,
+ with any other trailing dimensions of length 1 ignored.
+ """
+
+ shape = list(shape)
+
+ # Squeeze out empty dimensions, as
+ # 3D image can sometimes be listed
+ # as having 4 or more dimensions
+ for i in reversed(range(len(shape))):
+ if shape[i] == 1: shape = shape[:i]
+ else: break
+
+ # But make sure the shape
+ # has at 3 least dimensions
+ if len(shape) < 3:
+ shape = shape + [1] * (3 - len(shape))
+
+ return shape
+
+
def sliceObjToSliceTuple(sliceobj, shape):
"""Turns an array slice object into a tuple of (low, high) index
pairs, one pair for each dimension in the given shape
--
GitLab