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