How to add an if statement in an objective function in scipy.optimize

I have data (x) that represents some angles that looks like: [20, 30, 48, 46, 50, 70, 100], and a categorical ground truth which has two classes (0 and 1) e.g. [0, 0, 0, 0, 1, 1, 1]. I want to find a threshold that decides when an angle belongs to the class 0 or 1.

I was doing the following:

from scipy.optimize import curve_fit

def objective(x, threshold):
  if x > threshold:
    return 1
  else:
    return 0

# curve fit
threshold, _ = curve_fit(objective, x, y)

however, this code didn't work and I got this error:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

it seems that the problem was in having the if statement in the objective function, how could I use optimise to get the best threshold in such a case?

Thanks
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