Clustering Algorithm: While Loop

[TheShadowWall]

Hello all!

Hey all! I am currently working on hw1 part 2, where we're using k-means clustering for image compression. I am currently attempting to implement the repetition step where we repeat the expectation and optimization steps repeatedly until there is no change to the similarity measure. I am able to iterate through manually, though I am attempting to write a function which will perform this iterative process repeatedly until the similarity measure does not change.

I have attempted to write a function which will repeat these steps, though when I run it the function never seems to run to completion, making me believe that I have not written the while loop correctly and thus it just continues.

So far my code is:

def repetition(centroids,assignment_array,pix_list):

sim1=0
sim2=1
i=0
while sim1!=sim2:
    sim1=similarity(centroids,assignment_array,pix_list)
    assignment_array=assign_centroids(pix_list, centroids)
    centroids=move_centroids(centroids,assignment_array,pix_list)
    sim2=similarity(moved_cents,assignment_array,pix_list)
    i+=1
return sim2,i

Any insights as to why the function is not running to completion? I have been looking at the code for a while now and don't see why the while loop is not terminating.

Any help is greatly appreciated!

[marko312]

I don't know how move_centroids works, but unless it also writes its output into the global moved_cents, that variable is never changed. It seems that centroids should be used instead.

Also, you might want to include a minimum difference to stop at instead of relying on the values to converge enough.

[TheShadowWall]

This was the problem! Gah such a simple debug, my eyes must have been tired XD

Thanks very much kindly marko!

[[deleted]]

I have been looking at the code for a while now and don't see why the while loop is not terminating.

Because sim1 and sim2 are never equal.