def example():
X = np.array([[1, 1], [1, 2], [2, 2], [9, 10], [10, 10], [10, 9], [9, 9],
[20, 20]])
fcm = FCM(n_clusters=3)
fcm.fit(X, [0, 0, 0, 1, 1, 1, 1, 2])
# fcm.fit(X)
testing_data = np.array([[0, 1.9], [5, 3], [4, 4], [8, 9], [9.5, 6.5],
[5, 5], [15, 15], [12, 12], [14, 14], [19, 10]])
predicted_membership = fcm.predict(testing_data)
print("\n\ntesting data")
print(testing_data)
print("predicted membership")
print(predicted_membership)
print("\n\n")
draw_model_2d(fcm, data=testing_data, membership=predicted_membership)
def example():
X = np.array([[1, 1], [1, 2], [2, 2], [9, 10], [10, 10], [10, 9], [9, 9],
[20, 20]])
fcm = FCM(n_clusters=3)
fcm.set_logger(tostdout=True, level=logging.DEBUG)
fcm.fit(X, [0, 0, 0, 1, 1, 1, 1, 2])
# fcm.fit(X)
testing_data = np.array([[0, 1.9], [5, 3], [4, 4], [8, 9], [9.5, 6.5],
[5, 5], [15, 15], [12, 12], [14, 14], [19, 10]])
predicted_membership = fcm.predict(testing_data)
print "\n\ntesting data"
print testing_data
print "predicted membership"
print predicted_membership
print "\n\n"
draw_model_2d(fcm, data=testing_data, membership=predicted_membership)
def example():
X = np.array([[1, 1], [1, 2], [2, 2], [9, 10], [10, 10], [10, 9], [9, 9],
[20, 20]])
fcm = FCM(n_clusters=4)
fcm.set_logger(tostdout=True, level=logging.DEBUG)
fcm.fit(X, [0, 0, 0, 1, 1, 1, 1, 2])
# fcm.fit(X)
testing_data = np.array([[0, 1.9], [0.5, 2], [-1, 2], [1.9, 0.8],
[9.5, 6.5], [8, 5], [15, 13], [16, 12], [14, 14],
[10, 7]])
predicted_membership = fcm.predict(testing_data)
print("\n\ntesting data")
print(testing_data)
print("predicted membership")
print(predicted_membership)
print("\n\n")
draw_model_2d(fcm, data=testing_data, membership=predicted_membership)
def example_single_known():
X = np.array([[1, 1], [1, 2], [2, 2], [0, 0], [0, 0]])
fcm = FCM(n_clusters=3, max_iter=1)
fcm.fit(X, [0, 0, 0, 1, 2])
draw_model_2d(fcm, data=X, membership=fcm.u)
print fcm.u
@author: Sehgals
"""
import numpy as np
import logging
import sys
sys.path.append('..')
from fuzzy_clustering import FCM
from fuzzycmeans.visualization import draw_model_2d
# X = np.array([[1, 1], [1, 2], [2, 2], [9, 10], [10, 10], [10, 9], [9, 9], [20,20]])
X = np.random.randint(20, size=(200, 2))
fcm = FCM(n_clusters=3)
fcm.set_logger(tostdout=True, level=logging.DEBUG)
classes = np.random.randint(3, size=200)
fcm.fit(X, classes) #[0, 0, 0, 1, 1, 1, 1, 2]
# fcm.fit(X)
testing_data = np.random.randint(20, size=(50, 2))
# testing_data = np.array([[0, 1.9], [5, 3], [4, 4], [8, 9], [9.5, 6.5], [5, 5], [15,15], [12,12], [14,14], [19,10]])
predicted_membership = fcm.predict(testing_data)
np.savetxt('test_data_membership.csv', predicted_membership, delimiter=',')
# print ("\n\ntesting data")
# print (testing_data)
print("predicted membership")
print(predicted_membership)
print("\n\n")
draw_model_2d(fcm, data=testing_data, membership=predicted_membership)