# labs.datasets.volumes.volume_field¶

## Module: labs.datasets.volumes.volume_field¶

Inheritance diagram for nipy.labs.datasets.volumes.volume_field:

The base volumetric field interface

This defines the nipy volumetric structure interface.

## VolumeField¶

class nipy.labs.datasets.volumes.volume_field.VolumeField

Bases: object

The base volumetric structure.

This object represents numerical values embedded in a 3-dimensional world space (called a field in physics and engineering)

This is an abstract base class: it defines the interface, but not the logics.

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 consistency of this information is not maintained as the data is modified.
__init__()

x.__init__(…) initializes x; see help(type(x)) for signature

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. 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.

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. remapped_image : nipy image An image containing the same data, expressed in the new world space.
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
metadata = {}
resampled_to_img(target_image, interpolation=None)

Resample the volume to be sampled similarly than the target volumetric structure.

Parameters: target_image : nipy volume Nipy volume structure onto the grid of which the data will be resampled. interpolation : None, ‘continuous’ or ‘nearest’, optional Interpolation type used when calculating values in different word spaces. If None, the volume’s interpolation logic is used. 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.

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. 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.
world_space = ''