Pythonic way to constrain variable ranges?
Is there a better way to do this?
if a > 1:
a = 1
if a < 0:
a = 0
I was thinking about using a function because I have a lot of them in my code.I was curious if there was a clearer way to do this.
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
I will always use something like max(0, min(1, x))
. If x is greater than 1, it min(1, x)
will be equal to 1, and max(0, 1)
- 1. If x is less than 0, it min(1, x)
will be x
, but it max(0, x)
will be 0.