diff --git a/fsl/data/imagewrapper.py b/fsl/data/imagewrapper.py
index c55912d4508f707bffe2bf187fc74d6730602275..b50f32e220da8cd49c6271b992247a0b3df66a8d 100644
--- a/fsl/data/imagewrapper.py
+++ b/fsl/data/imagewrapper.py
@@ -49,7 +49,7 @@ class ImageWrapper(notifier.Notifier):
sliceObjToSliceTuple
sliceTupleToSliceObj
sliceCovered
- calcSliceExpansion
+ calcExpansion
adjustCoverage
"""
@@ -111,8 +111,7 @@ class ImageWrapper(notifier.Notifier):
# row/column for a slice, or row/column/depth
# for a volume).
#
- # All of these indices are stored in a big numpy
- # array:
+ # All of these indices are stored in a numpy array:
# - first dimension: low/high index
# - second dimension: image dimension
# - third dimension: slice/volume index
@@ -148,7 +147,14 @@ class ImageWrapper(notifier.Notifier):
def __getData(self, sliceobj, isTuple=False):
- """
+ """Retrieves and the image data at the location specified by
+ ``sliceobj``.
+
+ :arg sliceobj: Something which can be used to slice an array, or
+ a sequence of (low, high) index pairs.
+
+ :arg isTuple: Set to ``True`` if ``sliceobj`` is a sequence of
+ (low, high) index pairs.
"""
if isTuple:
@@ -176,10 +182,11 @@ class ImageWrapper(notifier.Notifier):
the image specified by ``slices``), and updates the known data range
of the image.
- :arg slices: A sequence of ``(low, high)`` index pairs, one for each
- dimension in the image. Tuples are used instead of
- ``slice`` objects, because this method is memoized (and
- ``slice`` objects are unhashable).
+ :arg slices: A tuple of of tuples, each tuple being a ``(low, high)``
+ index pair, one for each dimension in the image. Tuples
+ must be used instead of lists or ``slice`` objects,
+ because this method is memoized (and ``slice``/``list``
+ objects are unhashable).
:arg data: The image data at the given ``slices`` (as a ``numpy``
array).
@@ -194,10 +201,7 @@ class ImageWrapper(notifier.Notifier):
self.__range[1],
self.__coverage))
- volumes, expansions = calcSliceExpansion(slices,
- self.__coverage,
- self.__numRealDims,
- self.__numPadDims)
+ volumes, expansions = calcExpansion(slices, self.__coverage)
newmin = oldmin
newmax = oldmax
@@ -255,11 +259,7 @@ class ImageWrapper(notifier.Notifier):
slices = sliceObjToSliceTuple(sliceobj, self.__image.shape)
- if not sliceCovered(slices,
- self.__coverage,
- self.__image.shape,
- self.__numRealDims):
-
+ if not sliceCovered(slices, self.__coverage, self.__image.shape):
self.__updateDataRangeOnRead(slices, data)
return data
@@ -277,9 +277,12 @@ def sliceObjToSliceTuple(sliceobj, shape):
indices = []
+ # The sliceobj could be a single sliceobj
+ # or integer, instead of a tuple
if not isinstance(sliceobj, collections.Sequence):
sliceobj = [sliceobj]
+ # Turn e.g. array[6] into array[6, :, :]
if len(sliceobj) != len(shape):
missing = len(shape) - len(sliceobj)
sliceobj = list(sliceobj) + [slice(None) for i in range(missing)]
@@ -301,7 +304,7 @@ def sliceObjToSliceTuple(sliceobj, shape):
def sliceTupleToSliceObj(slices):
"""Turns a sequence of (low, high) index pairs into a tuple of array
- slice objects.
+ ``slice`` objects.
:arg slices: A sequence of (low, high) index pairs.
"""
@@ -319,8 +322,8 @@ def adjustCoverage(oldCoverage, slices):
given set of ``slices``.
:arg oldCoverage: A ``numpy`` array of shape ``(2, n)`` containing
- the (low, high) index pairs for a single slice/volume
- in the image.
+ the (low, high) index pairs for ``n`` dimensions of
+ a single slice/volume in the image.
:arg slices: A sequence of (low, high) index pairs. If ``slices``
contains more dimensions than are specified in
@@ -336,26 +339,27 @@ def adjustCoverage(oldCoverage, slices):
low, high = slices[ dim]
lowCover, highCover = oldCoverage[:, dim]
- if lowCover is None or low < lowCover: lowCover = low
- if highCover is None or high > highCover: highCover = high
+ if np.isnan(lowCover) or low < lowCover: lowCover = low
+ if np.isnan(highCover) or high > highCover: highCover = high
newCoverage[:, dim] = lowCover, highCover
return newCoverage
-def sliceCovered(slices, coverage, shape, realDims):
+def sliceCovered(slices, coverage, shape):
"""Returns ``True`` if the portion of the image data calculated by
the given ``slices` has already been calculated, ``False`` otherwise.
- :arg slices:
+ :arg slices:
:arg coverage:
:arg shape:
:arg volDim:
"""
- lowVol, highVol = slices[realDims - 1]
- shape = shape[:realDims - 1]
+ numDims = coverage.shape[1]
+ lowVol, highVol = slices[numDims]
+ shape = shape[:numDims]
for vol in range(lowVol, highVol):
@@ -364,7 +368,7 @@ def sliceCovered(slices, coverage, shape, realDims):
lowCover, highCover = coverage[:, dim, vol]
lowSlice, highSlice = slices[ dim]
- if lowCover is None or highCover is None:
+ if np.isnan(lowCover) or np.isnan(highCover):
return False
if lowSlice is None: lowSlice = 0
@@ -376,30 +380,36 @@ def sliceCovered(slices, coverage, shape, realDims):
return True
-def calcSliceExpansion(slices, coverage, realDims, padDims):
+def calcExpansion(slices, coverage):
"""
"""
# One per volume
- lowVol, highVol = slices[realDims - 1]
+ numDims = coverage.shape[1]
+ padDims = len(slices) - numDims - 1
+ lowVol, highVol = slices[numDims]
expansions = []
volumes = list(range(lowVol, highVol))
- # TODO Reduced slice duplication.
- # You know what this means.
+ # TODO Currently, the returned expansion(s) includes
+ # the current coverage. Remove this duplication;
+ # you can return multiple expansions per volume,
+ # so figure out how to expand the coverage with
+ # one or more expansion slices without
+ # overlapping the existing coverage.
for vol in volumes:
expansion = []
- for dim in range(realDims - 1):
+ for dim in range(numDims):
lowCover, highCover = coverage[:, dim, vol]
lowSlice, highSlice = slices[ dim]
- if lowCover is None: lowCover = lowSlice
- if highCover is None: highCover = highSlice
+ if np.isnan(lowCover): lowCover = lowSlice
+ if np.isnan(highCover): highCover = highSlice
expansion.append((min(lowCover, lowSlice),
max(highCover, highSlice)))