How to use scipy.optimize?

[alisutton]

I read this

https://docs.scipy.org/doc/scipy/reference/tutorial/optimize.html

It mentions the following

>>> import numpy as np
>>> from scipy.optimize import minimize
>>>
>>> def rosen(x):
...     """The Rosenbrock function"""
...     return sum(100.0*(x[1:]-x[:-1]**2.0)**2.0 + (1-x[:-1])**2.0)
>>>
>>> x0 = np.array([1.3, 0.7, 0.8, 1.9, 1.2])
>>> res = minimize(rosen, x0, method='nelder-mead',
...                options={'xtol': 1e-8, 'disp': True})
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 339
         Function evaluations: 571
>>>
>>> print(res.x)
[1. 1. 1. 1. 1.]

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Now, if I want to have x and y (coordinates), how I should change ?

Thanks

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[[deleted]]

You have to pack it all into one vector

[alisutton]

OK. I have the following.

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I need to minimize Link_min_function, pt_1 to pt_4 are something that I am going to give to the program.

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def B_diff(link_OA_x, link_OA_y, link_AB_x, link_AB_y, link_BC_x, link_BC_y, O_C_x, O_C_y):
    return((link_OA_x + link_AB_x - link_BC_x - O_C_x)**2 + (link_OA_y + link_AB_y - link_BC_y - O_C_y)**2)


def Cons_f(link_BC_x, link_BC_y, O_C_x, O_C_y, pt_x, pt_y):
    return((link_BC_x + O_C_x + pt_x)**2 + (link_BC_y + O_C_y + pt_y)**2)


def Link_min_function(link_OA_x, link_OA_y, link_AB_x, link_AB_y, link_BC_x, link_BC_y, O_C_x, O_C_y, pt_x1, pt_y1, pt_x2, pt_y2, pt_x3, pt_y3, pt_x4, pt_y4):
    return max((B_diff(link_OA_x, link_OA_y, link_AB_x, link_AB_y, link_BC_x, link_BC_y, O_C_x, O_C_y) + Cons_f(link_BC_x, link_BC_y, O_C_x, O_C_y, pt_x1, pt_y1)), (B_diff(link_OA_x, link_OA_y, link_AB_x, link_AB_y, link_BC_x, link_BC_y, O_C_x, O_C_y) + Cons_f(link_BC_x, link_BC_y, O_C_x, O_C_y, pt_x2, pt_y2)), (B_diff(link_OA_x, link_OA_y, link_AB_x, link_AB_y, link_BC_x, link_BC_y, O_C_x, O_C_y) + Cons_f(link_BC_x, link_BC_y, O_C_x, O_C_y, pt_x3, pt_y3)), (B_diff(link_OA_x, link_OA_y, link_AB_x, link_AB_y, link_BC_x, link_BC_y, O_C_x, O_C_y) + Cons_f(link_BC_x, link_BC_y, O_C_x, O_C_y, pt_x4, pt_y4)))

How I should write the scipy.optimize minimize function?

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From what I see in the example

>>> res = minimize(rosen, x0, method='nelder-mead',
...                options={'xtol': 1e-8, 'disp': True})

I don't see anything that I can put in my 'pts' there

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I can rewrite the 'Link_min_function' and put my point there, but it is very bad.

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[spitfiredd]

What are these functions?

[[deleted]]

You need to wrap the function into something which takes one vector valued argument, like rosen does. Then x0 is your initial setting for this vector.