labs.datasets.volumes.volume_data

Module: labs.datasets.volumes.volume_data

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

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The volume data class

This class represents indexable data embedded in a 3D space

VolumeData

class nipy.labs.datasets.volumes.volume_data.VolumeData[source]

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.

__init__($self, /, *args, **kwargs)

Initialize self. See help(type(self)) for accurate signature.

interpolation = 'continuous'
get_data()[source]

Return data as a numpy array.

like_from_data(data)[source]

Returns an volumetric data structure with the same relationship between data and world space, and same metadata, but different data.

Parameters

data: ndarray

resampled_to_img(target_image, interpolation=None)[source]

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.

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.

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.

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 = {}
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.

world_space = ''