#-----------------------------------
if __name__ == "__main__":
random.seed( 12345 )
# step = 2000
step = 100
#-----------------------------------
# data = Data("datasets\\data_MSL.mat", "array_slip_ratio", randomize = True)
data = Data("2D", randomize = False)
# data = Data("GEARS_2C_2D", randomize = False)
data.rescale() # data.standardize()
print "nb features in data:", data.nb_features
data_train = data.X[:10000]; random.shuffle(data_train)
r = IGNG.estimate_radius(data.X)
#-----------------------------------
# gng = GNG(period = 100)
# gng.train(data.X, step = step, directory = "___NG\\gng\\")
# print len( gng.get_ccn() )
# print len( gng.get_nodes_positions() )
#-----------------------------------
# igng = IGNG( data = data, radius = r/3. )
# igng.train(data.X, step = step, directory = "___NG\\igng\\")
# print len( igng.get_ccn() )
# print len( igng.get_nodes_positions() )
#-----------------------------------
# sgng = SGNG( data = data, radius = r/3., period = 1000, alpha = 1. )
