Here’s an explanation of the code you’ve used:
np.bincount() function takes a 1D integer array as input and returns a new array of non-negative integers representing the count of each element in the input array.
In your code, it creates a new NumPy array
C using the following input array:
[2, 2, 2, 4, 4, 6, 8, 8, 8, 8, 8]
C array contains the counts of each integer from 0 to 8 since 8 is the maximum value in the input array. For example, the count of 0 is 0, the count of 1 is 0, the count of 2 is 3, and so on up to the count of 8 being 5. Here is how the output of it looks:
[0 0 3 0 2 0 1 0 5]
np.repeat() function is then used which repeats each element of an input array a certain number of times, specified by a second array.
In your code, it creates a new array
A that contains the repeated elements of
np.arange(len(C)), which is an array of integers from 0 to the length of
C minus 1 (in this case, 9). The output of
np.arange(len(C)) would look like this:
[0 1 2 3 4 5 6 7 8]
The second array is
C, which specifies how many times each element of
np.arange(len(C)) should be repeated. So, for example, since the count of 2 in
C is 3, the first three elements of
A will be 2, and since the count of 8 in
C is 5, the last five elements of
A will be 8.
In summary, this code demonstrates how to use
np.repeat() to create a new array that repeats each element of an input array according to the count of that element in the input array. I hope this explanation helped you!