scipy.optimize.LbfgsInvHessProduct¶
- class scipy.optimize.LbfgsInvHessProduct(sk, yk)[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: sk : array_like, shape=(n_corr, n)
Array of n_corr most recent updates to the solution vector. (See [1]).
yk : array_like, shape=(n_corr, n)
Array of n_corr most recent updates to the gradient. (See [1]).
References
[R143] 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) adjoint() Hermitian adjoint. dot(x) Matrix-matrix or matrix-vector multiplication. matmat(X) Matrix-matrix multiplication. matvec(x) Matrix-vector multiplication. rmatvec(x) Adjoint matrix-vector multiplication. todense() Return a dense array representation of this operator. transpose() Transpose this linear operator.