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. )