scipy.optimize.

LbfgsInvHessProduct

class scipy.optimize.LbfgsInvHessProduct(*args, **kwargs)

Linear operator for the L-BFGS approximate inverse Hessian.

This operator computes the product of a vector with the approximate inverse of the Hessian of the objective function, using the L-BFGS limited memory approximation to the inverse Hessian, accumulated during the optimization.

Objects of this class implement the scipy.sparse.linalg.LinearOperator interface.

Parameters:

skarray_like, shape=(n_corr, n)

Array of n_corr most recent updates to the solution vector. (See [1]).

ykarray_like, shape=(n_corr, n)

Array of n_corr most recent updates to the gradient. (See [1]).

Attributes:

H

Hermitian adjoint.

T

Transpose.

Methods

__add__(x)	Linear operator addition.
__call__(x)	Apply this linear operator.
__matmul__(other)	Matrix Multiplication.
__mul__(x)	Multiplication.
__rmatmul__(other)	Matrix Multiplication from the right.
__rmul__(x)	Multiplication from the right.
__truediv__(other)	Scalar Division.
adjoint()	Hermitian adjoint.
dot(x)	Multi-purpose multiplication method.
matmat(X)	Matrix-matrix multiplication.
matvec(x)	Matrix-vector multiplication.
rdot(x)	Multi-purpose multiplication method from the right.
rmatmat(X)	Adjoint matrix-matrix multiplication.
rmatvec(x)	Adjoint matrix-vector multiplication.
todense()	Return a dense array representation of this operator.
transpose()	Transpose.

__pow__

References

[1]

Nocedal, Jorge. “Updating quasi-Newton matrices with limited storage.” Mathematics of computation 35.151 (1980): 773-782.