tedana.utils.make_adaptive_mask

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

Makes 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
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