from sklearn.neighbors import NearestNeighbors
#-----------------------------------
if __name__ == "__main__":
random.seed( 12345 )
# como_extract.computeHistogramsAllBuses(); exit(0)
(all_buses, periods_all_buses) = Util.pickleLoad(DATA_FILE_NAME+"_"+SIGNAL_CODE+".txt")
dates_all_buses = [ [ Util.getDate(tm) for tm in times ] for times in periods_all_buses ]
# como_ploting.Ploting.vizualize_buses(all_buses, dates_all_buses, m = '.'); exit(0)
#-----------------------------------
for id_bus in range( len(all_buses) ): # for each test bus
h = IGNG( radius = 2*PARAMS["R"] ); h.train( [Util.centroid( Util.flatList(all_buses) )] ); dir_imgs = "cosmo_IGNG_deriv_mature/"
# h = GNG(period = 200); h.train( [Util.centroid( Util.flatList(all_buses) )] ); dir_imgs = "cosmo_GNG/"
own_test = all_buses[id_bus]
fleet_test = all_buses[:id_bus] + all_buses[id_bus+1 :]
filename = DBFILES[id_bus]
busname = filename.split("_")[0]
dates = dates_all_buses[id_bus]
Z1 = []; Z2 = []; S1 = []; S2 = []
#--------------------------
for i, his_test in enumerate( own_test ): # for each day
sys.stdout.write( "\r%s" % "---------------------------- progress = " + str(i*100./len(own_test)) + " " + DBFILES[id_bus] + " " ); sys.stdout.flush()
#-----------------------------------
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. )
