Dtype mismatch in sklearn on k-means

Question

I am trying to run the first answer to this Python question Associate a k-means cluster with an instance , but I get the following error:

Traceback (most recent call last): File "test.py", line 16, in <module> model = sklearn.cluster.k_means(a, clust_centers) File "/usr/local/lib/python2.7/dist-packages/scikit_learn-0.14.1-py2.7-linux-i686.egg/sklearn/cluster/k_means_.py", line 267, in k_means x_squared_norms=x_squared_norms, random_state=random_state) File "/usr/local/lib/python2.7/dist-packages/scikit_learn-0.14.1-py2.7-linux-i686.egg/sklearn/cluster/k_means_.py", line 386, in _kmeans_single centers = _k_means._centers_dense(X, labels, n_clusters, distances) File "_k_means.pyx", line 280, in sklearn.cluster._k_means._centers_dense (sklearn/cluster/_k_means.c:4268) ValueError: Buffer dtype mismatch, expected 'DOUBLE' but got 'float' 

When I started this program for the first time, it worked. But subsequent runs fail with this error.

System Specifications:

Python 2.7.3 (default, Sep 26 2013, 20:08:41) [GCC 4.6.3] on linux2

numpy.__version__ '1.8.0'

sklearn.__version__ '0.14.1'

ubuntu 12.04

Answer 1

I ran into this problem while trying to run k-tools for my own data. Creating a new array with the "double" data type solved my problem.

 array_double = np.array(a, dtype=np.double) 

My data was previously saved as "float32".