def fit_from_centroids():
data_test = [178.75, 5.97390157]
data_height = [170., 186., 182., 177.]
data_size = [40, 42, 45, 47, 50]
data_injuries = [3, 4, 1, 0]
centers = [[175., 4.08], [44.8, 3.54], [2., 1.58]]
fcm = FCM(n_clusters=3, max_iter=1)
fcm.cluster_centers_ = np.array(centers)
fcm.fit(fcm.cluster_centers_, [0, 1, 2])
membership_height = fcm.predict(np.array([data_test]))
membership_height = fcm.predict(
np.array([[np.average(data_height),
np.std(data_height)]]))
membership_size = fcm.predict(
np.array([[np.average(data_size),
np.std(data_size)]]))
membership_injuries = fcm.predict(
np.array([[np.average(data_injuries),
np.std(data_injuries)]]))
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 test_2d():
X = np.array([[1, 1], [1, 2], [2, 2], [9, 10], [10, 10], [10, 9], [9, 9]])
fcm = FCM()
fcm.fit(X, [0, 0, 0, 1, 1, 1, 1])
assert len(fcm.cluster_centers_) == 2
assert fcm.cluster_centers_[0][0] == pytest.approx(1.33333333, 0.1)
assert fcm.cluster_centers_[0][1] == pytest.approx(1.66666667, 0.1)
testing_data = np.array([[0, 1.9], [3, 3], [4, 4], [8, 9], [9.5, 6.5]])
predicted_membership = fcm.predict(testing_data)
actual_membership = np.array([[0.98777232, 0.01222768],
[0.94884591, 0.05115409],
[0.82813688, 0.17186312],
[0.02482074, 0.97517926],
[0.0908581, 0.9091419]])
assert predicted_membership == pytest.approx(actual_membership, 0.01)
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)