diff --git a/fsl/data/image.py b/fsl/data/image.py
index 898e5efe6a4b0d2c01e2a34b7399412ccb9081af..0cd061e86098f5485317440fc26042bc8b4e4e79 100644
--- a/fsl/data/image.py
+++ b/fsl/data/image.py
@@ -343,7 +343,8 @@ class Image(Nifti1, notifier.Notifier):
name=None,
header=None,
xform=None,
- loadData=True):
+ loadData=True,
+ calcRange=False):
"""Create an ``Image`` object with the given image data or file name.
:arg image: A string containing the name of an image file to load,
@@ -363,13 +364,17 @@ class Image(Nifti1, notifier.Notifier):
array, and ``header`` is ``None``.
:arg loadData: If ``True`` (the default) the image data is loaded
- immediately (although see the note above about large
- compressed files). Otherwise, only the image header
- information is read - the data may be loaded later on
- via the :meth:`loadData` method. In this case, the
- reported ``dataRange`` will be ``(None, None)``, and
- ``data`` will be ``None``, until the image data is
- loaded via a call to :meth:``loadData``.
+ in to memory. Otherwise, only the image header
+ information is read, and the image data is kept
+ from disk. In either case, the image data is
+ accessed through an :class:`.ImageWrapper` instance.
+ The data may be loaded into memory later on via the
+ :meth:`loadData` method.
+
+ :arg calcRange: If ``True``, the image range is calculated immediately.
+ Otherwise (the default), the image range is
+ incrementally updated as more data is read from memory
+ or disk.
"""
import nibabel as nib
@@ -420,12 +425,18 @@ class Image(Nifti1, notifier.Notifier):
self.__dataSource = dataSource
self.__nibImage = nibImage
self.__saveState = dataSource is not None
- self.__imageWrapper = None
+ self.__imageWrapper = imagewrapper.ImageWrapper(self.nibImage,
+ self.name,
+ loadData=loadData)
- if loadData:
- self.loadData()
-
+ if calcRange:
+ self.calcRange()
+
+ self.__imageWrapper.register(
+ '{}_{}'.format(id(self), self.name),
+ self.__dataRangeChanged)
+
def __hash__(self):
"""Returns a number which uniquely idenfities this ``Image`` instance
(the result of ``id(self)``).
@@ -478,49 +489,63 @@ class Image(Nifti1, notifier.Notifier):
def dataRange(self):
"""
"""
- if self.__imageWrapper is None: return (None, None)
- else: return self.__imageWrapper.dataRange
+ if self.__imageWrapper is None: drange = (None, None)
+ else: drange = self.__imageWrapper.dataRange
+
+
+ # Fall back to the cal_min/max
+ # fields in the NIFTI1 header
+ # if we don't yet know anything
+ # about the image data range.
+ if drange[0] is None or drange[1] is None:
+ drange = (self.header.get('cal_min', None),
+ self.header.get('cal_max', None))
+
+ return drange
+
+
+ @property
+ def dtype(self):
+ """Returns the ``numpy`` data type of the image data. """
+
+ # Get the data type from the
+ # first voxel in the image
+ coords = [0] * len(self.__nibImage.shape)
+ return self.__nibImage.dataobj[tuple(coords)].dtype
def __dataRangeChanged(self, *args, **kwargs):
+ """Called when the :class:`.ImageWrapper` data range changes.
+ Notifies any listeners of this ``Image`` (registered through the
+ :class:`.Notifier` interface) on the ``'dataRange'`` topic.
+ """
self.notify('dataRange')
-
- def loadData(self):
- """Calculates initial values for :attr:`dataRange`.
- """
- if self.__imageWrapper is not None:
- raise RuntimeError('loadData can only be called once')
+ def calcRange(self, sizethres=None):
- self.__imageWrapper = imagewrapper.ImageWrapper(
- self.nibImage, self.name)
-
- self.__imageWrapper.register('{}_{}'.format(id(self), self.name),
- self.__dataRangeChanged)
-
- # How big is this image? If it's not too big,
- # then we'll calculate the actual data range
- # right now.
- #
- # This hard-coded threshold is equal to twice
- # the number of voxels in the MNI152 T1 0.5mm
- # standard image. Any bigger than this, and
- # we'll calculate the range from a sample:
- #
# The ImageWrapper automatically calculates
# the range of the specified slice, whenever
# it gets indexed. All we have to do is
# access a portion of the data to trigger the
- # range calculation.
- #
- # Note: Only 3D/4D images supported here
-# if np.prod(self.shape) < 115536512: self.__imageWrapper[:]
-# elif len(self.shape) >= 4: self.__imageWrapper[:, :, :, 0]
-# else: self.__imageWrapper[:, :, 0]
+ # range calculation.
+
+ # If an image size threshold has not been specified,
+ # then we'll calculate the full data range right now.
+ if sizethres is None:
+ self.__imageWrapper[:]
+
+ # Otherwise if the number of values in the
+ # image is bigger than the size threshold,
+ # we'll calculate the range from a sample:
+ elif np.prod(self.shape) < sizethres:
+ if len(self.shape) == 3: self.__imageWrapper[:, :, 0]
+ else: self.__imageWrapper[:, :, :, 0]
def __getitem__(self, sliceobj):
+ """
+ """
return self.__imageWrapper.__getitem__(sliceobj)