fitting.amares

fitting.amares

Functions¶

Name	Description
fit_amares	Apply AMARES time-domain fitting to an N-dimensional Free Induction Decay (FID).

fit_amares¶

fitting.amares.fit_amares(
    da,
    prior_knowledge_file,
    dim='time',
    mhz=None,
    sw=None,
    deadtime=None,
    method='leastsq',
    initialize_with_lm=True,
    num_workers=4,
    init_fid=None,
    verbose=False,
)

Apply AMARES time-domain fitting to an N-dimensional Free Induction Decay (FID).

This function isolates the stateful pyAMARES API to perform parallelized batch fitting across spatial or repetition dimensions. It automatically scans the dataset to initialize the fitting template using the voxel with the highest Signal-to-Noise Ratio (SNR), ensuring robust prior knowledge instantiation.

The numerical results and the reconstructed time-domain fits are packed into an aligned xarray Dataset, preserving all physical coordinates.

Parameters¶

Name	Type	Description	Default
da	xr.DataArray	Input FID data. Must contain the specified time dimension.	required
prior_knowledge_file	str \| Path	Path to the CSV or XLSX file containing the prior knowledge constraints.	required
dim	str	The time dimension along which to fit, by default “time”.	`'time'`
mhz	float	Spectrometer frequency in MHz. If None, attempts to read from da.attrs[‘MHz’].	`None`
sw	float	Spectral width in Hz. If None, attempts to calculate from `dim` coordinates.	`None`
deadtime	float	Time delay before the first point in seconds. If None, defaults to 0.0.	`None`
method	(leastsq, least_squares)	Fitting method. Defaults to ‘leastsq’ (Levenberg-Marquardt).	`"leastsq"`
initialize_with_lm	bool	Run an internal Levenberg-Marquardt initializer before fitting. Defaults to True.	`True`
num_workers	int	Number of parallel processes to spawn. Defaults to 4.	`4`
init_fid	np.ndarray	A 1D complex array to use as the template for pyAMARES initialization. If None, the function automatically selects the spectrum with the highest SNR.	`None`
verbose	bool	If True, sets logging level to INFO. Default is False -> log level ERROR.	`False`

Returns¶

Name	Type	Description
	xr.Dataset	A dataset containing the original data, the fitted FIDs, the residuals, and quantified parameters (amplitude, chem_shift, linewidth, phase, CRLB, SNR) mapped across the original dimensions and the new ‘Metabolite’ dimension.