`scipy.optimize._numdiff:_eps_for_method`

source: /scipy/optimize/_numdiff.py:93

Signature

def _eps_for_method(x0_dtype, f0_dtype, method)

Summary

Calculates relative EPS step to use for a given data type and numdiff step method.

Extended Summary

Progressively smaller steps are used for larger floating point types.

Parameters

f0_dtype: np.dtype: dtype of function evaluation
x0_dtype: np.dtype: dtype of parameter vector
method: {'2-point', '3-point', 'cs'}

Returns

: EPS: float: relative step size. May be np.float16, np.float32, np.float64

Notes

The default relative step will be np.float64. However, if x0 or f0 are smaller floating point types (np.float16, np.float32), then the smallest floating point type is chosen.

Aliases

scipy.optimize._numdiff._eps_for_method