SciPy

scipy.optimize.LbfgsInvHessProduct

class scipy.optimize.LbfgsInvHessProduct(*args, **kwargs)[source]

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]).

References

1

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

Attributes
H

Hermitian adjoint.

T

Transpose this linear operator.

Methods

__call__(x)

Call self as a function.

adjoint()

Hermitian adjoint.

dot(x)

Matrix-matrix or matrix-vector multiplication.

matmat(X)

Matrix-matrix multiplication.

matvec(x)

Matrix-vector multiplication.

rmatmat(X)

Adjoint matrix-matrix multiplication.

rmatvec(x)

Adjoint matrix-vector multiplication.

todense()

Return a dense array representation of this operator.

transpose()

Transpose this linear operator.

__mul__

Previous topic

scipy.optimize.line_search

Next topic

scipy.optimize.LbfgsInvHessProduct.__call__