lib_parms['outlier_range_y']=[-2.5,1.5] n=100 X = gen_data.lines2D(n,lib_parms) gen_data.plotpt(X,ticks=False,savename='result_plots\EM\EM_compare_original_points') #%% #%% parms = {'n_clusters':2} parms['beta_ini'] = np.array([[0.,0.,5.,-4.],[0.,0.,1.,.5]]) a = EM_classify.EM_line_model(X,parms) a.run(tol=1e-3) #%% a.plot_result2D(MarkerSize=10,savename='EM_2lines_40outlier_n100') fig.tight_layout() #%% parms = {'beta':0.8,'lambda':30,'list_NumPt4Instance':[2],'dist_adj':True} b=RRclustering3.RRalg(X,parms) b.run() #%% plot_tool.plot_result(b,b.list_xid_found,savename='result_plots\EM\Xshape_easy_RRa') #%% plot_tool.plot_result(b,b.list_xid_found,MarkerSize=50,\ same_color=True) #%% plot_tool.plot_result(b,b.list_xid_found,MarkerSize=50,\ same_color=True,savename='tmp') #%% lam_set = [5,10,50,60] files = ['EM\RRA_result\mix_instance_b08_l%d' %lam for lam in lam_set] #%% plot_tool.plot_thr_result_files(files,figsize=(20,5),layout=[1,4])
parms['lambda'] = lam a = RRalg(X, parms) a.run() name = 'result_rra\M1R2\\'+data_name+'_n%d_b%1.1f_l%d' \ %(n,parms['beta'],parms['lambda']) save_result(a, name) #%% plot_result(a, a.list_xid_found) #%% lam_set = [50, 350] files = [ 'result_rra\M1R2\\' + data_name + '_n%d_b0.8_l%d' % (n, lam) for lam in lam_set ] plot_thr_result_files(files, figsize=(20, 5), layout=[1, 4], savename='result_plots\M1R2\\' + data_name + '_RRA') #%% #%% Exact Sol for m in [2, 3]: _, Zid = a.run_exactsol_with_C(m) name = 'result_plots\M1R2\\' + data_name + '_exact_m%d' % m plot_result(a, Zid, title='exact', savename=name) #%% data_name = 'Dice5' lib_parms={'ls_pts':[[-1,1],[-1,-1],[0,0],[1,-1],[1,1]],\ 'var':[0.01]*5} X = gen_data.points(200, lib_parms) gen_data.plotpt(X)
'dist_adj':True,'initial_method':'Local_Best',\ 'ini_seed':3} #%% for lam in [10,20,110,120]: parms['lambda']=lam a=RRalg(X,parms) a.run() name = 'result_rra\M2R2\\'+data_name+'_n%d_b%1.1f_l%d' \ %(n,parms['beta'],parms['lambda']) save_result(a,name) #%% lam_set = [10,20,110,120] files = ['result_rra\M2R2\\'+data_name+'_n%d_b0.8_l%d' %(n,lam) for lam in lam_set] #%% name = 'result_plots\M2R2\\'+data_name +'_RRA_'+parms['initial_method'] plot_thr_result_files(files,figsize=(20,5),layout=[1,4],savename = name) #%% Different seed parms['lambda']=110 #%% for seed in range(6): parms['ini_seed']=seed a=RRalg(X,parms) a.run() name = 'result_rra\M2R2\\'+data_name+'_n%d_b%1.1f_l%d_seed%d' \ %(n,parms['beta'],parms['lambda'],seed) save_result(a,name) #%% seed_set = np.arange(6) files = ['result_rra\M2R2\\'+data_name+'_n%d_b0.8_l%d_seed%d' %(n,parms['lambda'],seed) for seed in seed_set] name = 'result_plots\M2R2\\'+data_name +'_RRA_'+'Random' plot_thr_result_files(files,figsize=(30,5),layout=[1,6],savename = name)
#%% name = 'result_plots\M3R3\\'+data_name+'_n%d_b%1.1f_l%d_0' \ %(n,parms['beta'],parms['lambda']) plot_result(a,a.list_xid_found,savename=name,elev=18,azim=13) name = 'result_plots\M3R3\\'+data_name+'_n%d_b%1.1f_l%d_1' \ %(n,parms['beta'],parms['lambda']) plot_result(a,a.list_xid_found,savename=name,elev=-177,azim=0) #%% for lam in [5,40,50,60]: parms['lambda']=lam a=RRalg(X,parms) a.run() name = 'result_rra\M3R3\\'+data_name+'_n%d_b%1.1f_l%d' \ %(n,parms['beta'],parms['lambda']) save_result(a,name) #%% lam_set = [5,10,50,60] files = ['result_rra\M3R3\\'+data_name+'_n%d_b0.8_l%d' %(n,lam) for lam in lam_set] #%% name = 'result_plots\M3R3\\'+data_name+'_RRA_0' plot_thr_result_files(files,figsize=(20,5),layout=[1,4],savename = name,azim=18,elev=13) #%% name = 'result_plots\M3R3\\'+data_name+'_RRA_1' plot_thr_result_files(files,figsize=(20,5),layout=[1,4],savename = name,azim=-177,elev=0) #%% _, Zid = a.run_exactsol_with_C(2) #%% name = 'result_plots\M3R3\\'+data_name+'_exact_m2_0' plot_result(a,Zid,title='exact',savename=name,azim=18,elev=13) name = 'result_plots\M3R3\\'+data_name+'_exact_m2_1' plot_result(a,Zid,title='exact',savename=name,azim=-177,elev=0)