tedana.metrics.dependence_metrics

dependence_metrics(catd, tsoc, mmix, adaptive_mask, tes, ref_img, reindex=False, mmixN=None, algorithm=None, label=None, out_dir='.', verbose=False)[source]

Fit TE-dependence and -independence models to components.

Parameters

  • catd ((S x E x T) array_like) – Input data, where S is samples, E is echos, and T is time

  • tsoc ((S x T) array_like) – Optimally combined data

  • mmix ((T x C) array_like) – Mixing matrix for converting input data to component space, where C is components and T is the same as in catd

  • adaptive_mask ((S) array_like) – Array where each value indicates the number of echoes with good signal for that voxel. This mask may be thresholded; for example, with values less than 3 set to 0. For more information on thresholding, see make_adaptive_mask.

  • tes (list) – List of echo times associated with catd, in milliseconds

  • ref_img (str or img_like) – Reference image to dictate how outputs are saved to disk

  • reindex (bool, optional) – Whether to sort components in descending order by Kappa. Default: False

  • mmixN ((T x C) array_like, optional) – Z-scored mixing matrix. Default: None

  • algorithm ({‘kundu_v2’, ‘kundu_v3’, None}, optional) – Decision tree to be applied to metrics. Determines which maps will be generated and stored in seldict. Default: None

  • label (str or None, optional) – Prefix to apply to generated files. Default is None.

  • out_dir (str, optional) – Output directory for generated files. Default is current working directory.

  • verbose (bool, optional) – Whether or not to generate additional files. Default is False.

Returns

  • comptable ((C x X) pandas.DataFrame) – Component metric table. One row for each component, with a column for each metric. The index is the component number.

  • seldict (dict or None) – Dictionary containing component-specific metric maps to be used for component selection. If algorithm is None, then seldict will be None as well.

  • betas (numpy.ndarray)

  • mmix_corrected (numpy.ndarray) – Mixing matrix after sign correction and resorting (if reindex is True).

See also

tedana.utils.make_adaptive_mask()

The function used to create the adaptive_mask parameter.