pyFTS/partitioners/CMeans.py

@@ -15,14 +15,14 @@ def distance(x, y):
 
 
 def c_means(k, dados, tam):
-    # Инициализирует центроиды, выбирая случайные элементы из множества
+    # Inicializa as centróides escolhendo elementos aleatórios dos conjuntos
     centroides = [dados[rnd.randint(0, len(dados)-1)] for kk in range(0, k)]
 
     grupos = [-1 for x in range(0, len(dados))]
 
     it_semmodificacao = 0
 
-    # для каждого экземпляра
+    # para cada instância
     iteracoes = 0
     while iteracoes < 1000 and it_semmodificacao < 10:
         inst_count = 0
@@ -31,7 +31,7 @@ def c_means(k, dados, tam):
 
         for instancia in dados:
 
-            # проверяет расстояние до каждого центроида
+            # verifica a distância para cada centroide
             grupo_count = 0
             dist = 10000
 
@@ -41,7 +41,7 @@ def c_means(k, dados, tam):
                 tmp = distance(instancia, grupo)
                 if tmp < dist:
                     dist = tmp
-                    # ассоциирует центроид с наименьшим расстоянием до экземпляра
+                    # associa a a centroide de menor distância à instância
                     grupos[inst_count] = grupo_count
                 grupo_count = grupo_count + 1
 
@@ -55,7 +55,7 @@ def c_means(k, dados, tam):
         else:
             it_semmodificacao = 0
 
-        # обновляет каждый центроид на основе средних значений всех связанных с ним экземпляров
+        # atualiza cada centroide com base nos valores médios de todas as instâncias à ela associadas
         grupo_count = 0
         for grupo in centroides:
             total_inst = functools.reduce(operator.add, [1 for xx in grupos if xx == grupo_count], 0)

pyFTS/partitioners/Util.py

@@ -18,7 +18,7 @@ all_methods = [Grid.GridPartitioner, Entropy.EntropyPartitioner, FCM.FCMPartitio
 mfs = [Membership.trimf, Membership.gaussmf, Membership.trapmf]
 
 
-def plot_sets(sets: dict, titles : list, size=[12, 10], save=False, file=None, axis=None):
+def plot_sets(data, sets: dict, titles : list, size=[12, 10], save=False, file=None, axis=None):
     """
     Plot all fuzzy sets in a Partitioner
     
@@ -26,7 +26,7 @@ def plot_sets(sets: dict, titles : list, size=[12, 10], save=False, file=None, a
     num = len(sets)
 
     if axis is None:
-        fig, axes = plt.subplots(nrows=num, ncols=1, figsize=size)
+        fig, axes = plt.subplots(nrows=num, ncols=1,figsize=size)
     for k in np.arange(0,num):
         ticks = []
         x = []
@@ -54,7 +54,7 @@ def plot_sets(sets: dict, titles : list, size=[12, 10], save=False, file=None, a
         Util.show_and_save_image(fig, file, save)
 
 
-def plot_partitioners(objs, tam=[12, 10], save=False, file=None, axis=None):
+def plot_partitioners(data, objs, tam=[12, 10], save=False, file=None, axis=None):
     sets = [k.sets for k in objs]
     titles = [k.name for k in objs]
     plot_sets(sets, titles, tam, save, file, axis)