smpl.fit

Simplified Fitting.

Uses scipy.curve_fit (no x errors) or scipy.odr (with x errors).

auto(datax, datay[, funcs])	Automatically loop over functions and fit the best one.
data_split(datax, datay, **kwargs)	Split data + errors
fit(datax, datay, function, **kwargs)	Returns a fit of function to datax and datay.
fit_kwargs(kwargs)	Set default fit_kwargs if not set.
fit_split(datax, datay, **kwargs)	Splits datax and datay into (x,y,xerr,yerr).

Functions

smpl.fit.auto(datax, datay, funcs=None, **kwargs)

Automatically loop over functions and fit the best one.

Parameters

funcsfunction array

functions to consider as fit. Default all smpl.functions.

**kwargsoptional

see fit_kwargs().

Returns

The best fit function and it’s parameters and a lambda where the parameters are already applied to the function.

smpl.fit.data_split(datax, datay, **kwargs)

Split data + errors

smpl.fit.fit(datax, datay, function, **kwargs)

Returns a fit of function to datax and datay.

Parameters

dataxarray_like

X data either as unp.uarray or np.array or list

datayarray_like

Y data either as unp.uarray or np.array or list

functionfunc

Fit function with parameters: x, params

**kwargsoptional

see fit_kwargs().

smpl.fit.fit_kwargs(kwargs)

Set default fit_kwargs if not set.

fit_kwargs	default	description
params	None	Initial fit parameters
frange	None	Limit the fit to given range. First integer is the lowest and second the highest index.
fselector	None	Function that takes x and y as parameters and returns an array mask in order to limit the data points for fitting. Alternatively a mask for selecting elements from datax and datay.
fixed_params	True	Enable fixing parameters by choosing the same-named variables from kwargs.
sortbyx	True	Enable sorting the x and y data so that x is sorted.
maxfev	10000	Maximum function evaluations during fitting.
epsfcn	0.0001	Suitable step length for jacobian approximation.
xvar	None	Variable in fit function parameters that corresponds to the x axis. If it is None the last of the alphabetical sorted parameters is used.
bins	0	Number of bins for histogram
binunc	poisson_dist	Number of bins for histogram
autotqdm	True	Auto fitting display tqdm
xerror	True	enable xerrors
yerror	True	enable yerrors

smpl.fit.fit_split(datax, datay, **kwargs)

Splits datax and datay into (x,y,xerr,yerr).

Parameters

**kwargsoptional

see fit_kwargs().