CODEWITHSUNDEEP
pythonscipy
Giiovanna
Giiovanna

Reputation: 442

Using "infinite bounds" in scipy.optimize.minimize?

I need to maximize a 3 variable function, which is defined in the following space:

]0, ∞[ x ]1, ∞[ x [0, ∞[

I am going to use SLSQP algorithm from scipy.optimize.minimize and I was thinking it should be done defining bounds for the function. But I don't know how to write "infinity" in python or this limits. Maybe it should be done using, then, constraints, but I couldnt find a way to define it.

I would be glad if I could get some help doing this.

Thanks in advance!

Upvotes: 3

Views: 5911

Answers (1)

Bakuriu
Bakuriu

Reputation: 101959

The scipy.optimize.minimize's documentation states that:

bounds : sequence, optional

Bounds for variables (only for L-BFGS-B, TNC and SLSQP). (min, max) pairs for each element in x, defining the bounds on that parameter. Use None for one of min or max when there is no bound in that direction.

So you don't have to represent infinity, just pass None. Passing the floating point infinity may not work as intended.

The standard way to represent infinity in python is using float('inf') for plus infinity and float('-inf') for minus infinity. These represent the standard IEEE 754 infinity values.

numpy also offers numpy.inf.

Upvotes: 9

Related Questions