core.image.image_list¶
ImageList¶
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class
nipy.core.image.image_list.ImageList(images=None)¶ Bases:
objectClass to contain ND image as list of (N-1)D images
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__init__(images=None)¶ An implementation of a list of images.
Parameters: images : iterable
an iterable object whose items are meant to be images; this is checked by asserting that each has a coordmap attribute and a
get_datamethod. Note that Image objects are not iterable by default; use thefrom_imageclassmethod oriter_axisfunction to convert images to image lists - see examples below for the latter.Examples
>>> from nipy.testing import funcfile >>> from nipy.core.api import Image, ImageList, iter_axis >>> from nipy.io.api import load_image >>> funcim = load_image(funcfile) >>> iterable_img = iter_axis(funcim, 't') >>> ilist = ImageList(iterable_img) >>> sublist = ilist[2:5]
Slicing an ImageList returns a new ImageList
>>> isinstance(sublist, ImageList) True
Indexing an ImageList returns a new Image
>>> newimg = ilist[2] >>> isinstance(newimg, Image) True >>> isinstance(newimg, ImageList) False >>> np.asarray(sublist).shape (3, 17, 21, 3) >>> newimg.get_data().shape (17, 21, 3)
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classmethod
from_image(image, axis=None, dropout=True)¶ Create an image list from an image by slicing over axis
Parameters: image : object
object with
coordmapattributeaxis : str or int
axis of image that should become the axis indexed by the image list.
dropout : bool, optional
When taking slices from an image, we will leave an output dimension to the coordmap that has no corresponding input dimension. If dropout is True, drop this output dimension.
Returns: ilist :
ImageListinstance
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get_list_data(axis=None)¶ Return data in ndarray with list dimension at position axis
Parameters: axis : int
axis specifies which axis of the output will take the role of the list dimension. For example, 0 will put the list dimension in the first axis of the result.
Returns: data : ndarray
data in image list as array, with data across elements of the list concetenated at dimension axis of the array.
Examples
>>> from nipy.testing import funcfile >>> from nipy.io.api import load_image >>> funcim = load_image(funcfile) >>> ilist = ImageList.from_image(funcim, axis='t') >>> ilist.get_list_data(axis=0).shape (20, 17, 21, 3)
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