labs.datasets.volumes.volume_data¶
Module: labs.datasets.volumes.volume_data
¶
Inheritance diagram for nipy.labs.datasets.volumes.volume_data
:

The volume data class
This class represents indexable data embedded in a 3D space
VolumeData
¶
-
class
nipy.labs.datasets.volumes.volume_data.
VolumeData
¶ Bases:
nipy.labs.datasets.volumes.volume_field.VolumeField
A class representing data embedded in a 3D space
This object has data stored in an array like, that knows how it is mapped to a 3D “real-world space”, and how it can change real-world coordinate system.
Notes
The data is stored in an undefined way: prescalings might need to be applied to it before using it, or the data might be loaded on demand. The best practice to access the data is not to access the _data attribute, but to use the get_data method.
Attributes
world_space: string World space the data is embedded in. For instance mni152. metadata: dictionnary Optional, user-defined, dictionnary used to carry around extra information about the data as it goes through transformations. The class consistency of this information is not maintained as the data is modified. _data: Private pointer to the data. Methods
as_volume_img
([affine, shape, …])Resample the image to be an image with the data points lying on a regular grid with an affine mapping to the word space (a nipy VolumeImg). composed_with_transform
(w2w_transform)Return a new image embedding the same data in a different word space using the given world to world transform. get_data
()Return data as a numpy array. get_transform
()Returns the transform object associated with the volumetric structure which is a general description of the mapping from the values to the world space. like_from_data
(data)Returns an volumetric data structure with the same relationship between data and world space, and same metadata, but different data. resampled_to_img
(target_image[, interpolation])Resample the data to be on the same voxel grid than the target volume structure. values_in_world
(x, y, z[, interpolation])Return the values of the data at the world-space positions given by -
__init__
()¶ x.__init__(…) initializes x; see help(type(x)) for signature
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as_volume_img
(affine=None, shape=None, interpolation=None, copy=True)¶ Resample the image to be an image with the data points lying on a regular grid with an affine mapping to the word space (a nipy VolumeImg).
Parameters: affine: 4x4 or 3x3 ndarray, optional :
Affine of the new voxel grid or transform object pointing to the new voxel coordinate grid. If a 3x3 ndarray is given, it is considered to be the rotation part of the affine, and the best possible bounding box is calculated, in this case, the shape argument is not used. If None is given, a default affine is provided by the image.
shape: (n_x, n_y, n_z), tuple of integers, optional :
The shape of the grid used for sampling, if None is given, a default affine is provided by the image.
interpolation : None, ‘continuous’ or ‘nearest’, optional
Interpolation type used when calculating values in different word spaces. If None, the image’s interpolation logic is used.
Returns: resampled_image : nipy VolumeImg
New nipy VolumeImg with the data sampled on the grid defined by the affine and shape.
Notes
The coordinate system of the image is not changed: the returned image points to the same world space.
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composed_with_transform
(w2w_transform)¶ Return a new image embedding the same data in a different word space using the given world to world transform.
Parameters: w2w_transform : transform object
The transform object giving the mapping between the current world space of the image, and the new word space.
Returns: remapped_image : nipy image
An image containing the same data, expressed in the new world space.
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get_data
()¶ Return data as a numpy array.
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get_transform
()¶ Returns the transform object associated with the volumetric structure which is a general description of the mapping from the values to the world space.
Returns: transform : nipy.datasets.Transform object
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interpolation
= 'continuous'¶
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like_from_data
(data)¶ Returns an volumetric data structure with the same relationship between data and world space, and same metadata, but different data.
Parameters: data: ndarray :
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metadata
= {}¶
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resampled_to_img
(target_image, interpolation=None)¶ Resample the data to be on the same voxel grid than the target volume structure.
Parameters: target_image : nipy image
Nipy image onto the voxel grid of which the data will be resampled. This can be any kind of img understood by Nipy (datasets, pynifti objects, nibabel object) or a string giving the path to a nifti of analyse image.
interpolation : None, ‘continuous’ or ‘nearest’, optional
Interpolation type used when calculating values in different word spaces. If None, the image’s interpolation logic is used.
Returns: resampled_image : nipy_image
New nipy image with the data resampled.
Notes
Both the target image and the original image should be embedded in the same world space.
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values_in_world
(x, y, z, interpolation=None)¶ Return the values of the data at the world-space positions given by x, y, z
Parameters: x : number or ndarray
x positions in world space, in other words milimeters
y : number or ndarray
y positions in world space, in other words milimeters. The shape of y should match the shape of x
z : number or ndarray
z positions in world space, in other words milimeters. The shape of z should match the shape of x
interpolation : None, ‘continuous’ or ‘nearest’, optional
Interpolation type used when calculating values in different word spaces. If None, the image’s interpolation logic is used.
Returns: values : number or ndarray
Data values interpolated at the given world position. This is a number or an ndarray, depending on the shape of the input coordinate.
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world_space
= ''¶
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