numpy.array boolean to binary?

Question

I am trying to rewrite a matlab code in python27. There is a matlab line as follows:

vector_C = vector_A > vector_B;

If I try to write this in python using numpy it will be the same, but the result will be an array of booleans instead of binaries. I want the result to be in binaries. Is there a way to make it return binary or should I convert manually each time? Is there a quick way of converting it? I am new to python. Thanks.

I believe matlab binary and python boolean are equivalent. Is there something you do in the matlab code with the binary vector that you cannot do with the numpy boolean vector? — Bi Rico
– Bi Rico, Commented May 10, 2012 at 1:11
I did not try doing anything with the boolean vector yet. But, I just divided the boolean vector by "1" so it is now binary. I guess I could use it without any modification also. Thanks — delete_this_account
– delete_this_account, Commented May 10, 2012 at 1:34
If that works for you answer your own question to close it off. — dtlussier
– dtlussier, Commented May 10, 2012 at 16:56

Steve Tjoa · Accepted Answer · 2012-05-10 02:12:18Z

22

Even though vector_C may have dtype=bool, you can still do operations such as the following:

In [1]: vector_A = scipy.randn(4)

In [2]: vector_B = scipy.zeros(4)

In [3]: vector_A
Out[3]: array([ 0.12515902, -0.53244222, -0.67717936, -0.74164708])

In [4]: vector_B
Out[4]: array([ 0.,  0.,  0.,  0.])

In [5]: vector_C = vector_A > vector_B

In [6]: vector_C
Out[6]: array([ True, False, False, False], dtype=bool)

In [7]: vector_C.sum()
Out[7]: 1

In [8]: vector_C.mean()
Out[8]: 0.25

In [9]: 3 - vector_C
Out[9]: array([2, 3, 3, 3])

So, in short, you probably don't have to do anything extra.

But if you must do a conversion, you may use astype:

In [10]: vector_C.astype(int)
Out[10]: array([1, 0, 0, 0])

In [11]: vector_C.astype(float)
Out[11]: array([ 1.,  0.,  0.,  0.])

answered May 10, 2012 at 2:12

Steve Tjoa

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Rob Falck · Accepted Answer · 2012-05-10 02:11:22Z

8

You can force numpy to store the elements as integers. It treats 0 as false and 1 as true.

import numpy

vector_C = numpy.array( vector_A > vector_B, dtype=int) ;

answered May 10, 2012 at 2:11

Rob Falck

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