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.LinearOperatorinterface.- 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.
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 this linear operator.
__mul__