sklearn.cluster.KMeans issue with kmeans_single() and threadpool_limits() about harmonypy HOT 4 CLOSED

I guess this is related to sklearn.cluster.KMeans()

Could I please ask if you could try this instead?

from scipy.cluster.vq import kmeans2
import harmonypy as hm

def cluster_fn(data, K):
        centroid, label = kmeans2(data, K, minit='++')
        return centroid

hm.run_harmony(data_mat,
                   meta_data, ['donor'],
                   cluster_fn=cluster_fn)

from harmonypy.

Feel free to re-open this issue if you can provide a minimal reproducible example.

from harmonypy.

Ah yes, this method worked. Thank you so much!

from harmonypy.

@shivamjgandhi You're welcome!

Thank you for commenting that it worked. Very much appreciated. Others will be happy to know there is a solution when they land on this page.

from harmonypy.