The Model class stores information about the function you wish to fit.
It stores the function itself, at the least, and optionally stores functions which compute the Jacobians used during fitting. Also, one can provide a function that will provide reasonable starting values for the fit parameters possibly given the set of data.
Parameters: | fcn : function
fjacb : function
fjacd : function
extra_args : tuple, optional
estimate : array_like of rank-1
implicit : boolean
meta : dict, optional
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Notes
Note that the fcn, fjacb, and fjacd operate on NumPy arrays and return a NumPy array. The estimate object takes an instance of the Data class.
Here are the rules for the shapes of the argument and return arrays of the callback functions:
Methods
set_meta(**kwds) | Update the metadata dictionary with the keywords and data provided here. |