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)