#Frahst_alg = FRAHST('F-7.A-recS.R-static', p) Frahst_alg = FRAHST('F-3.A-eng.R-eng', p) for i in xrange(initial_conditions): D = gen_funcs[anomaly_type](**a) # so tidy! #data = load_ts_data('isp_routers', 'full') data = D['data'] #data = zscore_win(data, 100) z_iter = iter(data) numStreams = data.shape[1] '''Initialise''' Frahst_alg.re_init(numStreams) print 'data set ', i '''Begin Frahst''' # Main iterative loop. for zt in z_iter: zt = zt.reshape(zt.shape[0],1) # Convert to a column Vector if Frahst_alg.st['anomaly'] == True: Frahst_alg.st['anomaly'] = False # reset anomaly var '''Frahst Version ''' Frahst_alg.run(zt) # Calculate reconstructed data if needed st = Frahst_alg.st
data_list = [] #Frahst_alg = FRAHST('F-7.A-recS.R-static', p) Frahst_alg = FRAHST('F-3.A-eng.R-eng', p) for i in xrange(initial_conditions): D = gen_funcs[anomaly_type](**a) # so tidy! #data = load_ts_data('isp_routers', 'full') data = D['data'] #data = zscore_win(data, 100) z_iter = iter(data) numStreams = data.shape[1] '''Initialise''' Frahst_alg.re_init(numStreams) print 'data set ', i '''Begin Frahst''' # Main iterative loop. for zt in z_iter: zt = zt.reshape(zt.shape[0], 1) # Convert to a column Vector if Frahst_alg.st['anomaly'] == True: Frahst_alg.st['anomaly'] = False # reset anomaly var '''Frahst Version ''' Frahst_alg.run(zt) # Calculate reconstructed data if needed st = Frahst_alg.st Frahst_alg.st['recon'] = np.dot(st['Q'][:, :st['r']], st['ht'][:st['r']])