I have a very large 2D array which looks something like this:
a=
[[a1, b1, c1],
[a2, b2, c2],
...,
[an, bn, cn]]
Using numpy, is there a
Another option is to create a random mask if you just want to down-sample your data by a certain factor. Say I want to down-sample to 25% of my original data set, which is currently held in the array data_arr
:
# generate random boolean mask the length of data
# use p 0.75 for False and 0.25 for True
mask = numpy.random.choice([False, True], len(data_arr), p=[0.75, 0.25])
Now you can call data_arr[mask]
and return ~25% of the rows, randomly sampled.