bundles / scipy latest / scipy / optimize / _numdiff / _eps_for_method
_lru_cache_wrapper
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.dtypedtype of function evaluation
x0_dtype: np.dtypedtype of parameter vector
method: {'2-point', '3-point', 'cs'}
Returns
: EPS: floatrelative 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