mne.SourceMorph

class mne.SourceMorph(subject_from, subject_to, kind, zooms, niter_affine, niter_sdr, spacing, smooth, xhemi, morph_mat, vertices_to, shape, affine, pre_affine, sdr_morph, src_data, verbose=None)[source]

Morph source space data from one subject to another.

Note

This class should not be instantiated directly. Use mne.compute_source_morph() instead.

Parameters
subject_fromstr | None

Name of the subject from which to morph as named in the SUBJECTS_DIR.

subject_tostr | array | list of array

Name of the subject on which to morph as named in the SUBJECTS_DIR. The default is ‘fsaverage’. If morphing a volume source space, subject_to can be the path to a MRI volume. Can also be a list of two arrays if morphing to hemisphere surfaces.

kindstr | None

Kind of source estimate. E.g. ‘volume’ or ‘surface’.

zoomsfloat | tuple

See mne.compute_source_morph().

niter_affinetuple of int

Number of levels (len(niter_affine)) and number of iterations per level - for each successive stage of iterative refinement - to perform the affine transform.

niter_sdrtuple of int

Number of levels (len(niter_sdr)) and number of iterations per level - for each successive stage of iterative refinement - to perform the Symmetric Diffeomorphic Registration (sdr) transform 1.

spacingint | list | None

See mne.compute_source_morph().

smoothint | str | None

See mne.compute_source_morph().

xhemibool

Morph across hemisphere.

morph_matscipy.sparse.csr_matrix

The sparse surface morphing matrix for spherical surface based morphing 2.

vertices_tolist of ndarray

The destination surface vertices.

shapetuple

The volume MRI shape.

affinendarray

The volume MRI affine.

pre_affineinstance of dipy.align.imaffine.AffineMap

The dipy.align.imaffine.AffineMap transformation that is applied before the before sdr_morph.

sdr_morphinstance of dipy.align.imwarp.DiffeomorphicMap

The dipy.align.imwarp.DiffeomorphicMap that applies the the symmetric diffeomorphic registration (SDR) morph.

src_datadict

Additional source data necessary to perform morphing.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

Notes

New in version 0.17.

References

1

Brian B. Avants, Charles L. Epstein, Murray C. Grossman, and James C. Gee. Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1):26–41, 2008. doi:10.1016/j.media.2007.06.004.

2

Douglas N. Greve, Lise Van der Haegen, Qing Cai, Steven Stufflebeam, Mert R. Sabuncu, Bruce Fischl, and Marc Brysbaert. A surface-based analysis of language lateralization and cortical asymmetry. Journal of Cognitive Neuroscience, 25(9):1477–1492, 2013. doi:10.1162/jocn_a_00405.

Methods

__hash__(/)

Return hash(self).

apply(stc_from[, output, mri_resolution, …])

Morph source space data.

save(fname[, overwrite, verbose])

Save the morph for source estimates to a file.
apply(stc_from, output='stc', mri_resolution=False, mri_space=None, verbose=None)[source]

Morph source space data.

Parameters
stc_fromVolSourceEstimate | VolVectorSourceEstimate | SourceEstimate | VectorSourceEstimate

The source estimate to morph.

outputstr

Can be ‘stc’ (default) or possibly ‘nifti1’, or ‘nifti2’ when working with a volume source space defined on a regular grid.

mri_resolutionbool | tuple | int | float

If True the image is saved in MRI resolution. Default False. WARNING: if you have many time points the file produced can be huge. The default is mri_resolution=False.

mri_spacebool | None

Whether the image to world registration should be in mri space. The default (None) is mri_space=mri_resolution.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only. Defaults to self.verbose.

Returns
stc_toVolSourceEstimate | SourceEstimate | VectorSourceEstimate | Nifti1Image | Nifti2Image

The morphed source estimates.

Examples using apply:

save(fname, overwrite=False, verbose=None)[source]

Save the morph for source estimates to a file.

Parameters
fnamestr

The stem of the file name. ‘-morph.h5’ will be added if fname does not end with ‘.h5’.

overwritebool

If True, overwrite existing file.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only. Defaults to self.verbose.