CODEWITHSUNDEEP
pythonnumpyscipy
Daniel Chepenko
Daniel Chepenko

Reputation: 2268

SciPy minimization of two-dimentional function

I want to minimize my two-dimentional function:

def error(w0, w1):
    sum = 0
    for index, row in data.head(5).iterrows():
        sum += (row['Height'] - (w0 + w1*row['Weight']))**2
    return sum

with scipy optimize package, using minimize function.

I set my initial variables:

w0 = 0
w1 = 0

And had described the boundaries:

bnds = ((-100, 100), (-5, 5))

But, when I try to minimize my function

res = opt.minimize(error,w0,w1,method='L-BFGS-B', bounds=bnds)

I receive an error:

ValueError: length of x0 != length of bounds

How should I minimize properly?

Upvotes: 0

Views: 132

Answers (1)

sascha
sascha

Reputation: 33522

Your call to minimize is wrong:

res = opt.minimize(error, [w0, w1], method='L-BFGS-B', bounds=bnds)

x0 needs to be some array. The way you did it, your second dimension of the initial-point is being interpreted as some other argument in this function's signature (meaning: only w0 is interpreted as x0, which is a scalar and not a array of size 2 -> incompatible with those bounds).

The same principle applies to your function:

def error(x):
    w0, w1 = x
    sum = 0
    for index, row in data.head(5).iterrows():
        sum += (row['Height'] - (w0 + w1*row['Weight']))**2
    return sum

Upvotes: 1

Related Questions