Use a.any () or a.all ()

x = np.arange(0,2,0.5)
valeur = 2*x

if valeur <= 0.6:
    print ("this works")
else:
    print ("valeur is too high")

here is the error I get:

if valeur <= 0.6:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

I have read several posts about a.any() or a.all() but still can’t find a way that really clearly explain how to fix the problem. I see why Python does not like what I wrote but I am not sure how to fix it.

If you take a look at the result of valeur <= 0.6
, you can see what’s causing this ambiguity:

>>> valeur <= 0.6
array([ True, False, False, False], dtype=bool)

So the result is another array that has in this case 4 boolean values. Now what should the result be? Should the condition be true when one value is true? Should the condition be true only when all values are true?

That’s exactly what numpy.any
and numpy.all
do. The former requires at least one true value, the latter requires that all values are true:

>>> np.any(valeur >> np.all(valeur <= 0.6)
False
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