What you are describing is usually called clipping. There are several ways to do cropping.

Library ( numpy

)

You can use numpy.clip

for this:

numpy.clip (a, a_min, a_max, out = None)

So:

import numpy

numpy.clip(x,0,1)

      

        
        
        
      

    

Although, since Python function calls are expensive and numpy

typically batch process data, for a single value it will introduce computational overhead.

For example:

>>> x = -2.5
>>> numpy.clip(x,0,1)
0.0
>>> x = 2.5
>>> numpy.clip(x,0,1)
1.0
>>> x = 0.5
>>> numpy.clip(x,0,1)
0.5

      

        
        
        
      

    

You usually use numpy

to do operations on (large) matrices , for example if you need to process a 1000x1000 matrix and using numpy

it will definitely pay off.

Pure Python

A pure python approach can be obtained with

max(0,min(1,x))

      

        
        
        
      

    

But here you have two calls , as a result it will be slower than using operators if

.

Finally, if you stick with the code if

, you can optimize it with elif

:

if x < 0:
    x = 0
elif x > 1:
    x = 1

      

        
        
        
      

    

Or a more general function:

def clip(x,min,max):
    if x < min:
        return min
    elif x > max:
        return max
    return x