mdreg.fit_exp_decay#
- mdreg.fit_exp_decay(signal, time=None, parallel=True, bounds=([0, 0], [inf, inf]), p0=[1, 1], **kwargs)[source]#
Fit to an exponential decay.
\[S(\mathbf{r},t) = S_0(\mathbf{r}) e^{-t/T(\mathbf{r})}\]- Parameters:
signal (numpy.ndarray | zarr.Array) – 3D or 4D array with signal intensities. Dimensions are (x, y, t) or (x, y, z, t).
time (numpy.ndarray) – Timepoints of the signal data
parallel (bool) – If True, use parallel processing. Default is False
bounds (tuple) – Bounds for the fit as (lower_bound, upper_bound) where lower_bound and upper_bound are either a scalar or a list of 2 values.
p0 (list) – Initial values as a 2-element list.
**kwargs – Additional keyword arguments accepted by fit_pixels.
- Returns:
fit (numpy.ndarray | zarr.Array) – Fitted to the signal data, with same dimensions as the signal array.
pars (numpy.ndarray | zarr.Array) – Fitted model parameters S0 and T. Dimensions are (x,y,2) or (x,y,z,2).