partitions2 = np.transpose(partitions)
ensemble2 = Ensemble(partitions=partitions2, n_cluster=3, partitions_format='PE')
e2, ts2, pr2 = ensemble2.mcla(times=True, partial_results=True)
for t in ts2:
print(f'{t[0]}: {t[1]}s')
for r in pr2:
print(r[0])
print(r[1])
"""
print('\n___PARTITIONS 3___')
partitions3 = np.random.randint(8, size=(8, 100000))
ensemble3 = Ensemble(partitions=partitions3,
n_cluster=8,
partitions_format='PE')
e3, ts3, _pr3 = ensemble3.mcla(times=True)
for t in ts3:
print(f'{t[0]}: {t[1]}s')
"""
hypergraph4 = np.array([
[1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 0, 1, 1],
[1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0, 0],
[1, 1, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 1],
[1, 0, 0, 1, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0]
import numpy as np
import scipy.sparse
import networkx as nx
import time
from ensemble import Ensemble
start_t = time.time()
partitions = np.random.randint(0, 4, size=(8, 5000000), dtype=np.int8)
print(f"n={partitions.shape[1]} r={partitions.shape[0]}")
print(f"Data generated in {round(time.time() - start_t, 2)} sec")
start_t = time.time()
ensemble = Ensemble(partitions=partitions, n_cluster=4, partitions_format='PE')
labels, _, _ = ensemble.mcla(dtype=np.int8)
print(f"Consensus computed in {round(time.time() - start_t, 2)} sec")
print(f"Labels: {np.lib.arraysetops.unique(labels)}")
