tedana.utils.make_adaptive_mask

make_adaptive_mask(data, mask=None, getsum=False, threshold=1)[source]

Make map of data specifying longest echo a voxel can be sampled with.

Parameters:

  • data ((S x E x T) array_like) – Multi-echo data array, where S is samples, E is echos, and T is time

  • mask (str or img_like, optional) – Binary mask for voxels to consider in TE Dependent ANAlysis. Default is to generate mask from data with good signal across echoes

  • getsum (bool, optional) – Return masksum in addition to mask. Default: False

  • threshold (int, optional) – Minimum echo count to retain in the mask. Default is 1, which is equivalent not thresholding.

Returns:

  • mask ((S,) numpy.ndarray) – Boolean array of voxels that have sufficient signal in at least one echo

  • masksum ((S,) numpy.ndarray) – Valued array indicating the number of echos with sufficient signal in a given voxel. Only returned if getsum = True