GreyOrdinates

Import in python using from mcutils.utils.greyordinate import GreyOrdinates

Documentation

class mcutils.utils.greyordinate.GreyOrdinates(data, brain_model_axis: nibabel.cifti2.cifti2_axes.BrainModelAxis, other_axes: Sequence[nibabel.cifti2.cifti2_axes.Axis] = None, parent_file=None)

Represents data on voxels or vertices

__init__(data, brain_model_axis: nibabel.cifti2.cifti2_axes.BrainModelAxis, other_axes: Sequence[nibabel.cifti2.cifti2_axes.Axis] = None, parent_file=None)

Defines a new dataset in greyordinate space

Parameters

• data – (…, N) array for N greyordinates

• brain_model_axis – CIFTI axis describing the greyordinate space

• other_axes – sequence of CIFTI axes describing the other dimensions

• parent_file – file in which the dataset has been stored

Methods

as_dask([chunks, name])	Returns the greyordinates as a dask array
empty(filename, axes[, dtype])	Creates an empty file to store the greyordinates with the type determined by the extension:
empty_cifti(filename, axes[, dtype])	Creates an empty greyordinate object based on the axes
empty_hdf5(filename, axes[, dtype])	Creates an empty greyordinate object based on the axes
empty_zarr(filename, axes[, dtype])	Creates an empty greyordinate object based on the axes
from_cifti(filename[, writable])	Creates new greyordinate object from dense CIFTI file
from_filename(filename[, mask_values, writable])	Reads greyordinate data from the given file
from_gifti(filename[, mask_values])	Creates a new greyordinate object from a GIFTI file
from_hdf5(group)	Retrieves data from HDF5 group
from_nifti(filename[, mask_values])	Creates a new greyordinate object from a NIFTI file
surface(anatomy[, fill, partial])	Gets a specific surface
to_cifti([other_axes])	Create a CIFTI image from the data
to_filename(filename)	Stores the greyordinate data to the given filename.
to_hdf5(group[, compression])	Stores the image in the HDF5 group
transpose()	Transposes a dense connectome
volume()	Get the volumetric data as a Nifti1Image