Python, opposite of conditional array

Question

I have two numpy arrays, let's say A and B

In [3]: import numpy as np

In [4]: A = np.array([0.10,0.20,0.30,0.40,0.50])

In [5]: B = np.array([0.15,0.23,0.33,0.41,0.57])

I apply a condition like this:

In [6]: condition_array = A[(B>0.2)*(B<0.5)]

In [7]: condition_array
Out[7]: array([ 0.2,  0.3,  0.4])

Now how do I get the opposite of condition_array?

i.e. the values of array A for which array B is NOT GREATER THAN 0.2 and NOT LESS THAN 0.5 ?

In [8]: test_array = A[(B<0.2)*(B>0.5)]

In [9]: test_array
Out[9]: array([], dtype=float64)

The above doesn't seem to work !

NOT GREATER THAN is the same thing as LESS THAN OR EQUAL TO and NOT LESS THAN is the same thing as GREATER THAN OR EQUAL TO — Eli Sadoff
– Eli Sadoff, Commented May 26, 2016 at 18:52
@EliSadoff: Yes I am aware of that, so what is the solution? — Srivatsan
– Srivatsan, Commented May 26, 2016 at 18:55
It's working fine, but there does not exist a value that is both < 0.2 and >0.5 which is what your code is asking for. — Eli Sadoff
– Eli Sadoff, Commented May 26, 2016 at 18:57

mgilson · Accepted Answer · 2016-05-26 18:59:17Z

3

You can use the ~ operator to invert the array ...

A[~((B>0.2)*(B<0.5))]

Note that your use of * seems like it's meant to do a logical "and". Many people would prefer that you use the binary "and" operator (&) instead -- Personally, I prefer to be even more explicit:

A[~np.logical_and(B > 0.2, B < 0.5)]

Alternatively, the following work too:

A[(B <= 0.2) | (B >= 0.5)]
A[np.logical_or(B <= 0.2, B >= 0.5)]

edited May 26, 2016 at 18:59

answered May 26, 2016 at 18:56

mgilson

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4 Comments

Srivatsan Over a year ago

Oh!! What is this sorcery!! I was never aware of the invert operator ! Only the not operator seems to be available in the docs, why haven't they mentioned about ~ ? Any idea?

mgilson Over a year ago

Python supports a full suite of "bitwise" operators (|, &, ~, ^, >>, <<). For builtin types, they're only implemented to work with int, long. (Some of the operators work on set objects too). For boolean numpy arrays, ~, | and & are overloaded to perform the logical equivalents -- Otherwise, I think they only work on integer arrays.

Srivatsan Over a year ago

What was the reason you said not to use * and instead use np.logical_and ? Aren't they the same?

mgilson Over a year ago

@ThePredator -- It does the same thing, but when reading the code, if I see a *, I don't think of logical "and" so it forces me to step back and try to figure out the expression to get an understanding of what it does.

piRSquared · Accepted Answer · 2016-05-26 19:02:26Z

1

By De Morgan's Law

A[np.logical_or(~(B > 0.2), ~(B < 0.5)]

Or

A[np.logical_or(B <= 0.2, B >= 0.5)]

answered May 26, 2016 at 19:02

piRSquared

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