#### Previous topic

scipy.optimize.show_options

#### Next topic

scipy.optimize.LbfgsInvHessProduct.H

# scipy.optimize.LbfgsInvHessProduct

class `scipy.optimize.``LbfgsInvHessProduct`(sk, yk)

  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.

  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

  [R126] | 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.