bundles / scipy latest / scipy / optimize / _nonlin / Jacobian

class

`scipy.optimize._nonlin:Jacobian`

source: /scipy/optimize/_nonlin.py :383

Signature

class Jacobian ( ** kw )

Members

Summary

Common interface for Jacobians or Jacobian approximations.

Extended Summary

The optional methods come useful when implementing trust region etc., algorithms that often require evaluating transposes of the Jacobian.

Attributes

shape: Matrix dimensions (M, N)
dtype: Data type of the matrix.
func : callable, optional: Function the Jacobian corresponds to

Methods

solve: Returns J^-1 * v
update: Updates Jacobian to point x (where the function has residual Fx)
matvec : optional: Returns J * v
rmatvec : optional: Returns A^H * v
rsolve : optional: Returns A^-H * v
matmat : optional: Returns A * V, where V is a dense matrix with dimensions (N,K).
todense : optional: Form the dense Jacobian matrix. Necessary for dense trust region algorithms, and useful for testing.

Aliases

scipy.optimize._nonlin.Jacobian