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# scipy.optimize.BFGS.update

BFGS.update(delta_x, delta_grad)

  Update internal matrix.

  Update Hessian matrix or its inverse (depending on how ‘approx_type’ is defined) using information about the last evaluated points.

  Parameters:
    delta_x ndarray

      The difference between two points the gradient function have been evaluated at: `delta_x = x2 - x1`.

    delta_grad ndarray

      The difference between the gradients: `delta_grad = grad(x2) - grad(x1)`.