[Numpy-discussion] element-wise logical operations on numpy arrays

Anne Archibald peridot.faceted@gmail....
Wed Jul 9 11:35:20 CDT 2008

2008/7/9 Catherine Moroney <Catherine.M.Moroney@jpl.nasa.gov>:

> I have a question about performing element-wise logical operations
> on numpy arrays.
> If "a", "b" and "c" are numpy arrays of the same size, does the
> following
> syntax work?
> mask = (a > 1.0) & ((b > 3.0) | (c > 10.0))
> It seems to be performing correctly, but the documentation that I've
> read
> indicates that "&" and "|" are for bitwise operations, not element-by-
> element operations in arrays.
> I'm trying to avoid using "logical_and" and "logical_or" because they
> make the code more cumbersome and difficult to read.  Are "&" and "|"
> acceptable substitutes for numpy arrays?

Yes. Unfortunately it is impossible to make python's usual logical
operators, "and", "or", etcetera, behave correctly on numpy arrays. So
the decision was made to use the bitwise operators to express logical
operations on boolean arrays. If you like, you can think of boolean
arrays as containing single bits, so that the bitwise operators *are*
the logical operators.

Confusing, but I'm afraid there really isn't anything the numpy
developers can do about it, besides write good documentation.

Good luck,

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