Hi,
I try to run the exemple (also to other datas), but I get always this error.
Do you have some idea how can I solve?
`cluster_runs = np.random.randint(0, 50, (50, 15000))
consensus_clustering_labels = CE.cluster_ensembles(cluster_runs, verbose = True, N_clusters_max = 50)
INFO: Cluster_Ensembles: cluster_ensembles: due to a rather large number of cells in your data-set, using only 'HyperGraph Partitioning Algorithm' (HGPA) and 'Meta-CLustering Algorithm' (MCLA) as ensemble consensus functions.
INFO: Cluster_Ensembles: HGPA: consensus clustering using HGPA.
INFO: Cluster_Ensembles: wgraph: writing wgraph_HGPA.
INFO: Cluster_Ensembles: wgraph: 15000 vertices and 2500 non-zero hyper-edges.
INFO: Cluster_Ensembles: sgraph: calling shmetis for hypergraph partitioning.
Traceback (most recent call last):
File "", line 1, in
consensus_clustering_labels = CE.cluster_ensembles(cluster_runs, verbose = True, N_clusters_max = 50)
File "/usr/local/lib/python2.7/dist-packages/Cluster_Ensembles/Cluster_Ensembles.py", line 300, in cluster_ensembles
cluster_ensemble.append(consensus_functions[i](hdf5_file_name, cluster_runs, verbose, N_clusters_max))
File "/usr/local/lib/python2.7/dist-packages/Cluster_Ensembles/Cluster_Ensembles.py", line 648, in HGPA
return hmetis(hdf5_file_name, N_clusters_max)
File "/usr/local/lib/python2.7/dist-packages/Cluster_Ensembles/Cluster_Ensembles.py", line 973, in hmetis
labels = sgraph(N_clusters_max, file_name)
File "/usr/local/lib/python2.7/dist-packages/Cluster_Ensembles/Cluster_Ensembles.py", line 1201, in sgraph
with open(out_name, 'r') as file:
IOError: [Errno 2] No such file or directory: 'wgraph_HGPA.part.50'`