scalar_search_wolfe1(phi, derphi, phi0=None, old_phi0=None, derphi0=None, c1=0.0001, c2=0.9, amax=50, amin=1e-08, xtol=1e-14)

alpha > 0 is assumed to be a descent direction.

Notes

Uses routine DCSRCH from MINPACK.

Parameters

phi : callable phi(alpha)

Function at point alpha

derphi : callable phi'(alpha)

Objective function derivative. Returns a scalar.

phi0 : float, optional

Value of phi at 0

old_phi0 : float, optional

Value of phi at previous point

derphi0 : float, optional

Value derphi at 0

c1 : float, optional

Parameter for Armijo condition rule.

c2 : float, optional

Parameter for curvature condition rule.

amax, amin : float, optional

Maximum and minimum step size

xtol : float, optional

Relative tolerance for an acceptable step.

Returns

alpha : float

Step size, or None if no suitable step was found

phi : float

Value of :None:None:`phi` at the new point alpha

phi0 : float

Value of :None:None:`phi` at :None:None:`alpha=0`

Scalar function search for alpha that satisfies strong Wolfe conditions

Examples

See :

Back References

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

scipy.optimize._linesearch.line_search_wolfe1

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