Find the average co-ordinates for each classifier in a list

Question

I want to write a function that takes two inputs:

points is a list of co-ordinate points and;

classiification is a list of 1s or 0s of n-by-m length, where n is the number of values in points , and m is is the number of classifications.

The function would return the average of the co-ordinates assigned to each classification. In the example there are 2 classifications, and each co-ordinate in points can only be assigned to one classification (labelled with a 1, all others labelled a 0).

Example below:

points = np.array([[1,1], [2,4], [4,6], [5,6], [6,6]])
classification = np.array([[1, 0],[1, 0],[0, 1],[0, 1],[0, 1]])

my_func(points, classification) #--> np.array([[1.5 , 2.5],
                                #              [5. , 6. ]])

So the first point, (1,1) has been assigned to the first classifier (1,0) and the third point (4,6) has been assigned to the second classifier (0,1).

What is the best way to approach this? Thanks

Answer 1

1. create two arrays, result and count , both with the number of classifications as their size, initialize each value to [0, 0] for result and 0 for count.
2. take the next point and classification until there are none left
3. use classification.index(1) to find the index for the result and count array
4. add the values of the point to the corresponding result and increment the corresponding count
5. repeat step 2
6. divide each value in result by it's corresponding count value
7. return result

I'll leave it up to you to write the code for it.

Answer 2

Since dictionaries are the easiest way to operate on the data involving mapping. I've used a dictionary to solve your question.

points = np.array([[1,1], [2,4], [4,6], [5,6], [6,6]])
classification = np.array([[1, 0],[1, 0],[0, 1],[0, 1],[0, 1]])

I'm converting the list of lists to list of tuples in the below step as lists cannot act as keys for dictionaries due to their mutable nature.

classification =[tuple(i) for i in classification]
dic={}
for i,j in zip(classification,points):
    if i not in dic.keys():
        dic[i]=[list(j)]
    else:
        dic[i].append(list(j))
[[sum(elem)/len(elem) for elem in zip(*j)] for i,j in dic.items()]

Hope that helps.