""" Created on Fri Mar 11 05:36:13 2011 @author: musselle """ import scipy.io as sio from utils import analysis from PedrosFrahst import frahst_pedro from Frahst_v3 import FRAHST_V3 from artSigs import genCosSignals_no_rand , genCosSignals #AbileneMat = sio.loadmat('C:\DataSets\Abilene\Abilene.mat') #data = AbileneMat['F'] data = genCosSignals_no_rand() data = genCosSignals(0,-3.0) e_high = 0.98 e_low = 0.96 alpha = 0.96 holdTime = 0 # My version res_me = FRAHST_V3(data, alpha=0.96, e_low=0.96, e_high=0.98, sci = -1, \ holdOffTime = holdTime, r = 1, evalMetrics = 'T') #metric_me_5, sets_me, anom_det_tab_me = analysis(res_me, AbileneMat['F_g_truth_tab']) # Pedros Version
figure() plot(f_qq) title('Deviation from orthonormality') figure() plot(e_qq) title('Deviation of true tracked subspace') return e_qq, f_qq, g_qq if __name__ == '__main__' : streams = genSimSignalsA(0, -3.0) # streams = array([[0,0,0], [1,2,2], [1,3,4], [3,6,6], [5,6,10], [6,8,11]]) streams = genCosSignals_no_rand() streams2 = genCosSignals(0, -3.0) energyThresh = [0.96, 0.98] alpha = 0.96 # rr = 4 sci = -1 Q_t, S_t, RSRE, rr, E_t, E_dash_t, z_dash, hidden_var \ = frhh_A(streams, energyThresh, alpha, sci) e_qq, f_qq, g_qq = plotEqqFqqA(streams, Q_t, alpha, p = 1) figure(); plot(RSRE) figure(); plot(rr)
plot(f_qq) title('Deviation from orthonormality') figure() plot(e_qq) title('Deviation of true tracked subspace') return e_qq, f_qq, g_qq if __name__ == '__main__': streams = genSimSignalsA(0, -3.0) # streams = array([[0,0,0], [1,2,2], [1,3,4], [3,6,6], [5,6,10], [6,8,11]]) streams = genCosSignals_no_rand() streams2 = genCosSignals(0, -3.0) energyThresh = [0.96, 0.98] alpha = 0.96 # rr = 4 sci = -1 Q_t, S_t, RSRE, rr, E_t, E_dash_t, z_dash, hidden_var \ = frhh_A(streams, energyThresh, alpha, sci) e_qq, f_qq, g_qq = plotEqqFqqA(streams, Q_t, alpha, p=1) figure() plot(RSRE)
""" Created on Fri Mar 11 05:36:13 2011 @author: musselle """ import scipy.io as sio from utils import analysis from PedrosFrahst import frahst_pedro from Frahst_v3 import FRAHST_V3 from artSigs import genCosSignals_no_rand, genCosSignals #AbileneMat = sio.loadmat('C:\DataSets\Abilene\Abilene.mat') #data = AbileneMat['F'] data = genCosSignals_no_rand() data = genCosSignals(0, -3.0) e_high = 0.98 e_low = 0.96 alpha = 0.96 holdTime = 0 # My version res_me = FRAHST_V3(data, alpha=0.96, e_low=0.96, e_high=0.98, sci = -1, \ holdOffTime = holdTime, r = 1, evalMetrics = 'T') #metric_me_5, sets_me, anom_det_tab_me = analysis(res_me, AbileneMat['F_g_truth_tab']) # Pedros Version res_ped = frahst_pedro(data, r=1, alpha=0.96, energy_low=0.96, energy_high=0.98, \