From 2d66509237432d9bb1e7380487dd053285935fb8 Mon Sep 17 00:00:00 2001
From: Paul McCarthy <pauldmccarthy@gmail.com>
Date: Wed, 4 Oct 2017 15:30:24 +0100
Subject: [PATCH] Image.reample method allows data type to be specified
---
fsl/data/image.py | 11 +++++++----
1 file changed, 7 insertions(+), 4 deletions(-)
diff --git a/fsl/data/image.py b/fsl/data/image.py
index d6f418037..3cc6071ff 100644
--- a/fsl/data/image.py
+++ b/fsl/data/image.py
@@ -1116,12 +1116,15 @@ class Image(Nifti):
self.notify(topic='saveState')
- def resample(self, shape, sliceobj=None, **kwargs):
+ def resample(self, shape, sliceobj=None, dtype=None, **kwargs):
"""Returns a copy of the data in this ``Image``, resampled to the
specified ``shape``.
:arg shape: Desired shape
+ :arg dtype: ``numpy`` data type of the resampled data. If ``None``,
+ the :meth:`dtype` of this ``Image`` is used.
+
:arg sliceobj: Slice into this ``Image``. If ``None``, the whole
image is resampled, and it is assumed that it has the
same number of dimensions as ``shape``.
@@ -1133,14 +1136,14 @@ class Image(Nifti):
interpolated copy of the data in this ``Image``.
"""
- if sliceobj is None:
- sliceobj = slice(None)
+ if sliceobj is None: sliceobj = slice(None)
+ if dtype is None: dtype = self.dtype
ndims = len(shape)
data = self[sliceobj]
if tuple(data.shape) != tuple(shape):
- data = np.array(data, dtype=np.float, copy=False)
+ data = np.array(data, dtype=dtype, copy=False)
zooms = [float(shape[i]) / data.shape[i] for i in range(ndims)]
data = ndimage.zoom(data, zooms, **kwargs)
--
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