Efficient way to count unique elements in array in numpy/scipy in Python

Question

I have a scipy array, e.g.

a = array([[0, 0, 1], [1, 1, 1], [1, 1, 1], [1, 0, 1]])

I want to count the number of occurrences of each unique ele

Answer 1

You can sort the array lexicographically by rows and the look for points where the rows change:

In [1]: a = array([[0, 0, 1], [1, 1, 1], [1, 1, 1], [1, 0, 1]])

In [2]: b = a[lexsort(a.T)]

In [3]: b
Out[3]: 
array([[0, 0, 1],
       [1, 0, 1],
       [1, 1, 1],
       [1, 1, 1]])

...


In [5]: (b[1:] - b[:-1]).any(-1)
Out[5]: array([ True,  True, False], dtype=bool)

The last array says that the first three rows differ and the third row is repeated twice.

For arrays of ones and zeros you can encode the values:

In [6]: bincount(dot(a, array([4,2,1])))
Out[6]: array([0, 1, 0, 0, 0, 1, 0, 2])

Dictionaries can also be used. Which of the various methods will be fastest will depend on the sort of arrays you are actually working with.