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Commit 1f3fa431 authored by Paul McCarthy's avatar Paul McCarthy :mountain_bicyclist:
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Merge branch 'bf/mesh_indices' into 'master'

Bf/mesh indices

See merge request fsl/fslpy!185
parents 90fcc75d 0ab31648
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......@@ -34,6 +34,9 @@ Fixed
* Improved the algorithm used by the :func:`.mesh.needsFixing` function.
* The :meth:`.fslmaths.run` method now accepts :attr:`.wrappers.LOAD` as an
output specification.
* Fixed a bug in the :class:`.Mesh` class to prevent indices from being loaded
as floating point type.
* Fixed a bug in the :func:`.resample` function.
Deprecated
......
......@@ -154,14 +154,6 @@ class Mesh(notifier.Notifier, meta.Meta):
"""
def __new__(cls, *args, **kwargs):
"""Create a ``Mesh``. We must override ``__new__``, otherwise the
:class:`Meta` and :class:`Notifier` ``__new__`` methods will not be
called correctly.
"""
return super(Mesh, cls).__new__(cls, *args, **kwargs)
def __init__(self,
indices,
name='mesh',
......@@ -189,7 +181,7 @@ class Mesh(notifier.Notifier, meta.Meta):
self.__name = name
self.__dataSource = dataSource
self.__nvertices = indices.max() + 1
self.__nvertices = int(indices.max()) + 1
self.__selected = None
# We potentially store two copies of
......@@ -197,7 +189,7 @@ class Mesh(notifier.Notifier, meta.Meta):
# orders. The vindices dict stores refs
# to one or the other for each vertex
# set.
self.__indices = np.asarray(indices).reshape((-1, 3))
self.__indices = np.asarray(indices, dtype=np.int32).reshape((-1, 3))
self.__fixedIndices = None
self.__vindices = collections.OrderedDict()
......
......@@ -47,9 +47,9 @@ def resampleToReference(image, reference, matrix=None, **kwargs):
along the spatial (first three) dimensions.
:arg image: :class:`.Image` to resample
:arg matrix: Optional world-to-world affine alignment matrix
:arg reference: :class:`.Nifti` defining the space to resample ``image``
into
:arg matrix: Optional world-to-world affine alignment matrix
"""
oldShape = list(image.shape)
......@@ -204,9 +204,10 @@ def resample(image,
if matrix is None:
matrix = affine.rescale(data.shape, newShape, origin)
# identity matrix? the image
# doesn't need to be resampled
if np.all(np.isclose(matrix, np.eye(len(newShape) + 1))):
# same shape and identity matrix? the
# image doesn't need to be resampled
if np.all(np.isclose(data.shape, newShape)) and \
np.all(np.isclose(matrix, np.eye(len(newShape) + 1))):
return data, image.voxToWorldMat
newShape = np.array(np.round(newShape), dtype=np.int)
......
indexed_gzip>=0.7.0
wxpython==4.*
trimesh>=2.37.29
rtree==0.8.3
rtree>=0.8.3
Pillow>=3.2.0
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