This method is also known as "Broyden's bad method".
This algorithm implements the inverse Jacobian Quasi-Newton update
$$H_+ = H + (dx - H df) df^\dagger / ( df^\dagger df)$$corresponding to Broyden's second method.
Find a root of a function, using Broyden's second Jacobian approximation.
root
Interface to root finding algorithms for multivariate functions. See method=='broyden2'
in particular.
The following functions define a system of nonlinear equations
>>> def fun(x):
... return [x[0] + 0.5 * (x[0] - x[1])**3 - 1.0,
... 0.5 * (x[1] - x[0])**3 + x[1]]
A solution can be obtained as follows.
>>> from scipy import optimizeSee :
... sol = optimize.broyden2(fun, [0, 0])
... sol array([0.84116365, 0.15883529])
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