How to mask numpy structured array on multiple columns?

Question

I have a numpy structured array with a dtype such as:

A = numpy.empty(10, dtype=([('segment', '<i8'), ('material', '<i8'), ('rxN', '<i8')]))

I know I can create a mask such as:

A[A['segment'] == 42] = ...

Is there a way to create a mask on multiple columns? For example (I know this doesn't work, but I wish it did):

A[A['segment'] == 42 and A['material'] == 5] = ...

Sven Marnach · Accepted Answer · 2011-07-22 15:42:25Z

up vote 6 down vote accepted

You can use the & operator instead of and:

A[(A['segment'] == 42) & (A['material'] == 5)]

Note that extra parantheses are required.

answered Jul 22 '11 at 15:42

Sven Marnach
154k16407488

Simple, I love it. Thanks! – Jeremy Jul 22 '11 at 16:04

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