def make_sfr_radius_mass_plots(msF,merF,rfiter=3):
for sk,fk in zip(snap_keys,fil_keys):
parameters, pcd, pc, pcd = make_pc_dict(msF,sk,fk)
pc1 = pc.X[:,0].flatten()
pc2 = pc.X[:,1].flatten()
pc3 = pc.X[:,2].flatten()
pc4 = pc.X[:,3].flatten()
pc5 = pc.X[:,4].flatten()
pc6 = pc.X[:,5].flatten()
pc7 = pc.X[:,6].flatten()
PCs=pandas.DataFrame(pc.X)
asym = get_all_morph_val(msF,sk,fk,'ASYM')
gini = get_all_morph_val(msF,sk,fk,'GINI')
m20 = get_all_morph_val(msF,sk,fk,'M20')
cc = get_all_morph_val(msF,sk,fk,'CC')
Mstat = get_all_morph_val(msF,sk,fk,'MID1_MPRIME')
Istat = get_all_morph_val(msF,sk,fk,'MID1_ISTAT')
Dstat = get_all_morph_val(msF,sk,fk,'MID1_DSTAT')
sfid = get_all_snap_val(msF,sk,'SubfindID')
S_GM20 = SGM20(gini,m20)
F_GM20 = FGM20(gini,m20)
latest_NumMajorMergersLastGyr = get_mergerinfo_val(merF,sk,'latest_NumMajorMergersLastGyr')
boolean_merger1 = latest_NumMajorMergersLastGyr >= 1.0
this_NumMajorMergersLastGyr = get_mergerinfo_val(merF,sk,'this_NumMajorMergersLastGyr')
boolean_merger2 = this_NumMajorMergersLastGyr >= 1.0
mhalo = get_all_snap_val(msF,sk,'Mhalo_Msun')
mstar = get_all_snap_val(msF,sk,'Mstar_Msun')
log_mstar_mhalo = np.log10( mstar/mhalo )
redshift = msF['nonparmorphs'][sk][fk]['CAMERA0']['REDSHIFT'].value[0]
#set up RF data frame above, run or save input/output for each loop iteration
rf_dict = {}
PARAMS_MOD=True
PARAMS_ONLY=False
PCS_ONLY=False
RUN_RF=True
RF_ITER=rfiter
rf_masscut = 10.0**(10.5)
if PCS_ONLY is True:
gi = np.where(np.isfinite(pc1)*np.isfinite(pc2)*np.isfinite(pc3)*np.isfinite(pc4)*np.isfinite(pc5)*np.isfinite(pc6)*np.isfinite(pc7)*(mstar >= rf_masscut) != 0)[0]
print(gi.shape, pc1.shape)
rf_dict['pc1']=pc1[gi]
rf_dict['pc2']=pc2[gi]
rf_dict['pc3']=pc3[gi]
rf_dict['pc4']=pc4[gi]
rf_dict['pc5']=pc5[gi]
rf_dict['pc6']=pc6[gi]
rf_dict['pc7']=pc7[gi]
rf_dict['mergerFlag']=boolean_merger1[gi]
rf_dict['SubfindID']=sfid[gi]
cols=['pc1','pc2','pc3','pc4','pc5','pc6','pc7']
rflabel='pcs'
if PARAMS_ONLY is True:
gi = np.where(np.isfinite(gini)*np.isfinite(m20)*np.isfinite(asym)*np.isfinite(Mstat)*np.isfinite(Istat)*np.isfinite(Dstat)*np.isfinite(cc)*(mstar >= rf_masscut) != 0)[0]
print(gi.shape, pc1.shape)
rf_dict['gini']=gini[gi]
rf_dict['m20']=m20[gi]
rf_dict['asym']=asym[gi]
rf_dict['Mstat']=Mstat[gi]
rf_dict['Istat']=Istat[gi]
rf_dict['Dstat']=Dstat[gi]
rf_dict['cc']=cc[gi]
rf_dict['mergerFlag']=boolean_merger1[gi]
rf_dict['SubfindID']=sfid[gi]
cols=['gini','m20','asym','Mstat','Istat','Dstat','cc']
rflabel='params'
if PARAMS_MOD is True:
gi = np.where(np.isfinite(S_GM20)*np.isfinite(F_GM20)*np.isfinite(asym)*np.isfinite(Mstat)*np.isfinite(Istat)*np.isfinite(Dstat)*np.isfinite(cc)*(mstar >= rf_masscut) != 0)[0]
print(gi.shape, pc1.shape)
rf_dict['dGM20']=S_GM20[gi]
rf_dict['fGM20']=F_GM20[gi]
rf_dict['asym']=asym[gi]
rf_dict['Mstat']=Mstat[gi]
rf_dict['Istat']=Istat[gi]
rf_dict['Dstat']=Dstat[gi]
rf_dict['cc']=cc[gi]
rf_dict['mergerFlag']=boolean_merger1[gi]
rf_dict['SubfindID']=sfid[gi]
cols=['dGM20','fGM20','asym','Mstat','Istat','Dstat','cc']
rflabel='paramsmod'
if RUN_RF is True:
if redshift < 4.2:
df=pandas.DataFrame(rf_dict)
print("Running Random Forest... ", sk, fk)
result, labels, label_probability = PyML.randomForestMC(df,iterations=RF_ITER,cols=cols)
#result = summary statistics, feature importances (N iterations x N statistics/importances)
#labels = labels following random forest (N galaxies x N iterations)
#label_probability = probability of label following random forest (N galaxies x N iterations)
#saves the output as a file
if not os.path.lexists('rfoutput'):
os.mkdir('rfoutput')
labels['mergerFlag']=df['mergerFlag']
label_probability['mergerFlag']=df['mergerFlag']
labels['SubfindID']=df['SubfindID']
label_probability['SubfindID']=df['SubfindID']
df.to_pickle('rfoutput/'+rflabel+'_data_cut_{}_{}.pkl'.format(sk,fk))
result.to_pickle('rfoutput/'+rflabel+'_result_cut_{}_{}.pkl'.format(sk,fk))
labels.to_pickle('rfoutput/'+rflabel+'_labels_cut_{}_{}.pkl'.format(sk,fk))
label_probability.to_pickle('rfoutput/'+rflabel+'_label_probability_cut_{}_{}.pkl'.format(sk,fk))
PCs.to_pickle('rfoutput/'+rflabel+'_pc_cut_{}_{}.pkl'.format(sk,fk))
bins=18
xlim=[9.7,12.2]
ylim=[-2.0,3.0]
rlim=[0.1,1.7]
plot_filen = 'pc1/sfr_radius_mass_'+sk+'_'+fk+'_pc1.pdf'
if not os.path.lexists('pc1'):
os.mkdir('pc1')
f1 = pyplot.figure(figsize=(3.5,5.0), dpi=300)
pyplot.subplots_adjust(left=0.15, right=0.98, bottom=0.08, top=0.88,wspace=0.0,hspace=0.0)
colorobj = plot_sfr_radius_mass(msF,merF,sk,fk,f1,xlim=xlim,ylim=ylim,rlim=rlim,Cval=pc1,vmin=-2,vmax=3,bins=bins)
gth.make_colorbar(colorobj,title='PC1 morphology',ticks=[-2,-1,0,1,2,3])
f1.savefig(plot_filen,dpi=300)
pyplot.close(f1)
plot_filen = 'pc3/sfr_radius_mass_'+sk+'_'+fk+'_pc3.pdf'
if not os.path.lexists('pc3'):
os.mkdir('pc3')
f1 = pyplot.figure(figsize=(3.5,5.0), dpi=300)
pyplot.subplots_adjust(left=0.15, right=0.98, bottom=0.08, top=0.88,wspace=0.0,hspace=0.0)
colorobj = plot_sfr_radius_mass(msF,merF,sk,fk,f1,xlim=xlim,ylim=ylim,rlim=rlim,Cval=pc3,vmin=-1,vmax=3,bins=bins)
gth.make_colorbar(colorobj,title='PC3 morphology',ticks=[-1,0,1,2,3])
f1.savefig(plot_filen,dpi=300)
pyplot.close(f1)
plot_filen = 'asym/sfr_radius_mass_'+sk+'_'+fk+'_asym.pdf'
if not os.path.lexists('asym'):
os.mkdir('asym')
f1 = pyplot.figure(figsize=(3.5,5.0), dpi=300)
pyplot.subplots_adjust(left=0.15, right=0.98, bottom=0.08, top=0.88,wspace=0.0,hspace=0.0)
colorobj = plot_sfr_radius_mass(msF,merF,sk,fk,f1,xlim=xlim,ylim=ylim,rlim=rlim,Cval=asym,vmin=0.0,vmax=0.4,bins=bins)
gth.make_colorbar(colorobj,title='Asymmetry',ticks=[0.0,0.20,0.40])
f1.savefig(plot_filen,dpi=300)
pyplot.close(f1)
plot_filen = 'merger1/sfr_radius_mass_'+sk+'_'+fk+'_merger1.pdf'
if not os.path.lexists('merger1'):
os.mkdir('merger1')
f1 = pyplot.figure(figsize=(3.5,5.0), dpi=300)
pyplot.subplots_adjust(left=0.15, right=0.98, bottom=0.08, top=0.88,wspace=0.0,hspace=0.0)
colorobj = plot_sfr_radius_mass(msF,merF,sk,fk,f1,xlim=xlim,ylim=ylim,rlim=rlim,Cval=boolean_merger1,min_bin=3,gridf='fraction_grid',vmin=0.0,vmax=0.5,bins=bins)
gth.make_colorbar(colorobj,title='fraction major merger',ticks=[0.0,0.25,0.50],format='%.2f')
f1.savefig(plot_filen,dpi=300)
pyplot.close(f1)
plot_filen = 'merger3/sfr_radius_mass_'+sk+'_'+fk+'_merger3.pdf'
if not os.path.lexists('merger3'):
os.mkdir('merger3')
f1 = pyplot.figure(figsize=(3.5,5.0), dpi=300)
pyplot.subplots_adjust(left=0.15, right=0.98, bottom=0.08, top=0.88,wspace=0.0,hspace=0.0)
colorobj = plot_sfr_radius_mass(msF,merF,sk,fk,f1,xlim=xlim,ylim=ylim,rlim=rlim,Cval=boolean_merger1,min_bin=3,gridf='normed_proportion_grid',vmin=0.0,vmax=1.0,bins=bins)
gth.make_colorbar(colorobj,title='proportion of major mergers',ticks=[0.0,0.5,1.0],format='%.2f')
f1.savefig(plot_filen,dpi=300)
pyplot.close(f1)
plot_filen = 'mstar_mhalo/sfr_radius_mass_'+sk+'_'+fk+'_mstar_mhalo.pdf'
if not os.path.lexists('mstar_mhalo'):
os.mkdir('mstar_mhalo')
f1 = pyplot.figure(figsize=(3.5,5.0), dpi=300)
pyplot.subplots_adjust(left=0.15, right=0.98, bottom=0.08, top=0.88,wspace=0.0,hspace=0.0)
colorobj = plot_sfr_radius_mass(msF,merF,sk,fk,f1,xlim=xlim,ylim=ylim,rlim=rlim,Cval=log_mstar_mhalo,min_bin=3,gridf='median_grid',vmin=-2.0,vmax=-0.5,bins=bins)
gth.make_colorbar(colorobj,title='median $log_{10} M_*/M_{h}$',ticks=[-2,-1.5,-1,-0.5])
f1.savefig(plot_filen,dpi=300)
pyplot.close(f1)
plot_filen = 'mhalo/sfr_radius_mass_'+sk+'_'+fk+'_mhalo.pdf'
if not os.path.lexists('mhalo'):
os.mkdir('mhalo')
f1 = pyplot.figure(figsize=(3.5,5.0), dpi=300)
pyplot.subplots_adjust(left=0.15, right=0.98, bottom=0.08, top=0.88,wspace=0.0,hspace=0.0)
colorobj = plot_sfr_radius_mass(msF,merF,sk,fk,f1,xlim=xlim,ylim=ylim,rlim=rlim,Cval=np.log10(mhalo),min_bin=3,gridf='median_grid',vmin=11.5,vmax=14.0,bins=bins)
gth.make_colorbar(colorobj,title='median $log_{10} M_{h}$',ticks=[11.5,12.0,13.0,14.0])
f1.savefig(plot_filen,dpi=300)
pyplot.close(f1)
return locals()
