Fixed issues

quillotm
1 parent e72cf05267
Showing 1 changed file with 6 additions and 6 deletions Side-by-side Diff
volia/clustering_modules/kmeans_multidistance.py
@@ -3,7 +3,7 @@
 from abstract_clustering import AbstractClustering
 from KMeans_Multidistance.KMeans_Class import KMeans
 from random import seed
-from random import random
+from random import randint
 import numpy as np
 from sklearn.metrics import pairwise_distances
  
@@ -61,7 +61,7 @@
  
         # Compute seeds before using seeds
         seed()
-        self.seeds = [random() for i in range(ninit)]
+        self.seeds = [randint(1, 100000) for i in range(ninit)]
  
         # Learning k-means model
         results = []
@@ -70,7 +70,7 @@
                            maxiter=maxiter,
                            distance=self.distance,
                            record_heterogeneity=[],
-                           verbose=True,
+                           verbose=debug,
                            seed=self.seeds[i])
             centroids, closest_cluster = model.fit(features)
  
@@ -92,7 +92,7 @@
             })
         losses = [result["loss"] for result in results]
         best = results[losses.index(min(losses))]
-        self.kmeans_model = results[best]["model"]
-        self.centroids = results[best]["centroids"]
-        self.seed = results[best]["seed"]
+        self.kmeans_model = best["model"]
+        self.centroids = best["centroids"]
+        self.seed = best["seed"]
...	...	@@ -3,7 +3,7 @@
3	3	from abstract_clustering import AbstractClustering
4	4	from KMeans_Multidistance.KMeans_Class import KMeans
5	5	from random import seed
6		-from random import random
	6	+from random import randint
7	7	import numpy as np
8	8	from sklearn.metrics import pairwise_distances
9	9
...	...	@@ -61,7 +61,7 @@
61	61
62	62	# Compute seeds before using seeds
63	63	seed()
64		- self.seeds = [random() for i in range(ninit)]
	64	+ self.seeds = [randint(1, 100000) for i in range(ninit)]
65	65
66	66	# Learning k-means model
67	67	results = []
...	...	@@ -70,7 +70,7 @@
70	70	maxiter=maxiter,
71	71	distance=self.distance,
72	72	record_heterogeneity=[],
73		- verbose=True,
	73	+ verbose=debug,
74	74	seed=self.seeds[i])
75	75	centroids, closest_cluster = model.fit(features)
76	76
...	...	@@ -92,7 +92,7 @@
92	92	})
93	93	losses = [result["loss"] for result in results]
94	94	best = results[losses.index(min(losses))]
95		- self.kmeans_model = results[best]["model"]
96		- self.centroids = results[best]["centroids"]
97		- self.seed = results[best]["seed"]
	95	+ self.kmeans_model = best["model"]
	96	+ self.centroids = best["centroids"]
	97	+ self.seed = best["seed"]