Masking numpy arrays

Masking is the term used for selecting entries in arrays, e.g. depending on its content. In order to do this, we need to use numpy arrays.

First, we define a numpy array. Per definition it contains numbers:

import numpy
measurements = numpy.asarray([1, 17, 25, 3, 5, 26, 12])
measurements

array([ 1, 17, 25,  3,  5, 26, 12])

Next, we create a mask, e.g. a mask that defines all measurements which are above a given threshold:

mask = measurements > 10
mask

array([False,  True,  True, False, False,  True,  True])

We can apply that mask to our data to retrieve a new array that only contains masked values.

measurements[mask]

array([17, 25, 26, 12])

Exercises

Create a new mask for all measurements below 20.

Apply the mask to retrieve a new array with numbers below 20.

Compute the average of all numbers below 20.