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]). 
 
- Attributes:
 - 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__ - References [1]- Nocedal, Jorge. “Updating quasi-Newton matrices with limited storage.” Mathematics of computation 35.151 (1980): 773-782.