curve_fit(f, xdata, ydata, p0=None, sigma=None, absolute_sigma=False, check_finite=True, bounds=(-inf, inf), method=None, jac=None, *, full_output=False, **kwargs)

Notes

Parameters

f : callable

xdata : array_like

ydata : array_like

p0 : array_like, optional

sigma : None or M-length sequence or MxM array, optional

absolute_sigma : bool, optional

check_finite : bool, optional

bounds : 2-tuple of array_like or `Bounds`, optional

method : {'lm', 'trf', 'dogbox'}, optional

jac : callable, string or None, optional

full_output : boolean, optional

**kwargs :

Raises

ValueError

RuntimeError

OptimizeWarning

Returns

popt : array

pcov : 2-D array

infodict : dict (returned only if `full_output` is True)

mesg : str (returned only if `full_output` is True)

ier : int (returnned only if `full_output` is True)

See Also

least_squares

scipy.stats.linregress

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.stats._stats_mstats_common:linregress

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GitHub : /scipy/optimize/_minpack_py.py#549
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