lee6boy - 1 year ago 109
Python Question

How Do I put 2 matrix into scipy.optimize.minimize?

I work with the

`scipy.optimize.minimize`
function.
My purpose is get
`w,z`
which minimize
`f(w,z)`

Both
`w`
and
`z`
are n by m matrices:

``````[[1,1,1,1],
[2,2,2,2]]
``````

f(w,z) is receive parameter w and z.

I already tried the form given below:

``````def f(x):
w = x[0]
z = x[1]
...

minimize(f, [w,z])
``````

but, minimize does not work well.

What is the valid form to put two matrices (n by m) into
`scipy.optimize.minimize`
?

Optimize needs a 1D vector to optimize. You are on the right track. You need to flatten your argument to `minimize` and then in `f`, start with `x = np.reshape(x, (2, m, n))` then pull out `w` and `z` and you should be in business.

I've run into this issue before. For example, optimizing parts of vectors in multiple different classes at the same time. I typically wind up with a function that maps things to a 1D vector and then another function that pulls the data back out into the objects so I can evaluate the cost function. As in:

``````def toVector(w, z):
assert w.shape == (2, 4)
assert z.shape == (2, 4)
return np.hstack([w.flatten(), z.flatten()])

def toWZ(vec):
assert vec.shape == (2*2*4,)
return vec[:2*4].reshape(2,4), vec[2*4:].reshape(2,4)

def doOptimization(f_of_w_z, w0, z0):
def f(x):
w, z = toWZ(x)
return f_of_w_z(w, z)

result = minimize(f, toVec(w0, z0))
# Different optimize functions return their
# vector result differently. In this case it's result.x:
result.x = toWZ(result.x)
return result
``````
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