# 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

 [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. rmatvec(x) Adjoint matrix-vector multiplication. todense() Return a dense array representation of this operator. transpose() Transpose this linear operator.

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