A function containing a truth check applied to an array returns an error [duplicate]

Question

If I define the following function:

def f(x):
    if x<1.:
        return 0.
    else:
        return x

and I try to apply it to an array (in order to have another array as output)

import numpy as np
X=np.linspace(0.,2.,100)
print f(X)

it returns the following error:

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

Of course I could solve the problem by applying the function to each component of the array separately, but it doesn't seem to be the most efficient way. What is the right way to define the function?

Why is applying the function to each component of the array separately not the most efficient way? You need to access each element in order to apply the function on them — Devesh Kumar Singh
– Devesh Kumar Singh, Commented Jul 17, 2019 at 17:42
Look at X<1. Could you use that 'mask' as a way of setting many values to 0 at once? To avoid loops in numpy you have to step outside of the box a bit; instead of focusing on changing one element at a time, think about how you can select and change a whole set of elements at once. — hpaulj
– hpaulj, Commented Jul 17, 2019 at 17:42
Just in case it wasn't clear from the duplicates, use np.where — DeepSpace
– DeepSpace, Commented Jul 17, 2019 at 17:44
There are 2 problems with f(X). A python if is a simple True/False test; it does not iterate in any way. X<1 produces a boolean array, many True/False values. The error says it can't use a such an array in the scalar if context. — hpaulj
– hpaulj, Commented Jul 17, 2019 at 18:04

Devesh Kumar Singh · Accepted Answer · 2019-07-17 17:47:38Z

3

Use a map to apply that function on each item of the list

print(list(map(f, X)))

You can also define the function as a lambda function inside the map itself

print(list(map(lambda x: 0. if x<1. else x, X)))

Or just use numpy masking to select the indexes where x<1. and set them to 0.

X[X<1.] = 0.

edited Jul 17, 2019 at 17:47

answered Jul 17, 2019 at 17:39

Devesh Kumar Singh

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3 Comments

hpaulj Over a year ago

That is applying the function to each component of the array!

DeepSpace Over a year ago

And you just killed vectorization

hpaulj Over a year ago

That's more like it! Now I don't have to search for a better duplicate link.

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