[Python] How to get a python function to work on an np.array or a float, with conditional logic

I have a function that I'd like to take numpy arrays or floats as input. I want to keep doing an operation until some measure of error is less than a threshold.

A simple example would be the following to divide a number or array by 2 until it's below a threshold (if a float), or until it's maximum is below a threshold (if an array).

def f(x): #float version
while x>1e-5:
x = x/2
return x

def f(x): #np array version
while max(x)>1e-5:
x = x/2
return x


Unfortunately, max won't work if I've got something that is not iterable, and x>1e-5 won't work if x is an array. I can't find anything to do this, except perhaps vectorize, but that seems to not be as efficient as I would want. How can I get a single function to handle both cases?

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