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check_sample.py
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check_sample.py
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import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import astropy.io.fits as fitsio
import useful
import veff
import mk_sample
import conversions as conv
import uvudf_utils as utils
from plot_colcol import plot_colcol, plot_colcut_patches
from sample_selection import mk_dropout_cuts, mk_photoz_cuts
from selection import SelectionFunction
def check_photoz():
catalog = fitsio.getdata('catalogs/udf_cat_v2.0.hlr.fits')
catalog = catalog[(catalog['UVUDF_COVERAGE']==1) & (catalog['UVUDF_EDGEFLG']==0)]
fig,(ax1,ax2) = plt.subplots(2,1,figsize=(10,10),dpi=75,sharex=True)
fig.subplots_adjust(wspace=0,hspace=0)
ax1.scatter(catalog['MAG_B_F336W'],catalog['ODDS_B'],c='k',s=3,alpha=0.1)
ax2.scatter(catalog['MAG_B_F336W'],catalog['CHISQ_B'],c='k',s=3,alpha=0.1)
ax2.set_xlim(23,32)
ax1.set_ylim(0,1.1)
ax2.set_ylim(0,5)
ax2.set_xlabel('F336W MAG')
ax2.set_ylabel('CHI2')
ax1.set_ylabel('ODDS')
def check_cuts():
catalog = fitsio.getdata('catalogs/udf_cat_v2.0.hlr.fits')
catalog = catalog[(catalog['UVUDF_COVERAGE']==1) & (catalog['UVUDF_EDGEFLG']==0)]
fig, axes = plt.subplots(1,3,figsize=(20,7),dpi=75,tight_layout=True)
for ax,drop_filt in zip(axes,['f225w','f275w','f336w']):
drop = mk_dropout_cuts(catalog,drop_filt)
ccol = mk_dropout_cuts(catalog,drop_filt,do_sn_cut=False)
phot = mk_photoz_cuts( catalog,drop_filt)
drop_not = drop[np.array([i not in phot['ID'] for i in drop['ID']])]
ccol_not = ccol[np.array([i not in drop['ID'] for i in ccol['ID']])]
phot_not = phot[np.array([i not in drop['ID'] for i in phot['ID']])]
plot_colcut_patches(drop_filt, ax)
filt1,filt2,filt3 = utils.filt_colcol(drop_filt)
plot_colcol(drop_not, filt1, filt2, filt3, catalog=catalog, axis=ax,
marker='o', c='r', s=20, lw=2, alpha=1.0, label='%s Dropouts\n but wrong photo-z' % drop_filt.upper())
plot_colcol(ccol_not, filt1, filt2, filt3, catalog=catalog, axis=ax,
marker='o', c='limegreen', s=20, lw=2, alpha=1.0, label='%s Dropouts colors\n but wrong S/N' % drop_filt.upper())
plot_colcol(phot_not, filt1, filt2, filt3, catalog=catalog, axis=ax,
marker='o', c='b', s=20, lw=2, alpha=1.0, label='%.1f<photo-z<%.1f\n but wrong colors' % (utils.bpz_lims[drop_filt][0],utils.bpz_lims[drop_filt][1]))
ax.set_xlabel('%s - %s' % (filt2.upper(),filt3.upper()))
ax.set_ylabel('%s - %s' % (filt1.upper(),filt2.upper()))
ax.set_xlim(-1,3)
ax.set_ylim(-1,4)
ax.legend(fontsize=12)
fig.savefig('plots/check_cuts.png')
def check_sample_vols():
fig = plt.figure(figsize=(12,10),dpi=75)
gs1 = gridspec.GridSpec(2,3)
gs1.update(left=0.1,right=0.98,top=0.98,bottom=0.58,wspace=0,hspace=0)
axes1 = np.array([fig.add_subplot(ss) for ss in gs1]).reshape(2,3)
gs2 = gridspec.GridSpec(2,3)
gs2.update(left=0.1,right=0.98,top=0.50,bottom=0.10,wspace=0,hspace=0)
axes2 = np.array([fig.add_subplot(ss) for ss in gs2]).reshape(2,3)
for i,drop_filt in enumerate(['f225w','f275w','f336w']):
for j,sample_type in enumerate(['dropout','photoz']):
sample = mk_sample.mk_sample(drop_filt,sample_type=sample_type,return_all=True)
cond = (sample['SAMPLE_FLAG']==1)
volfn = veff.VEff_Func(drop_filt=drop_filt,sample_type=sample_type)
for axes,mag_label in zip([axes1,axes2],['M_1500','m_1500']):
axes[j,i].scatter(sample[mag_label][cond],sample['Vfrac'][cond],c='k',s=15,lw=0,alpha=0.5)
axes[j,i].scatter(sample[mag_label][~cond],sample['Vfrac'][~cond],c='r',s=15,lw=0,alpha=0.5)
axes[j,i].axhline(0.50,lw=0.5,ls=':',c='k')
axes[j,i].axhline(0.25,lw=0.5,ls='--',c='k')
axes[j,i].axhline(0.10,lw=0.5,ls='-',c='k')
axes[j,i].set_yscale('log')
axes1[j,i].axvline(volfn.mag_limit(hlr=8),lw=0.5,c='k')
axes1[j,i].set_xlim(-21.9,-14.5)
axes1[j,i].set_ylim(3e-2,2e0)
axes2[j,i].set_xlim(23.2,30)
axes2[j,i].set_ylim(3e-2,2e0)
if j!=1:
axes1[j,i].set_xticklabels([])
axes2[j,i].set_xticklabels([])
if i!=0:
axes1[j,i].set_yticklabels([])
axes2[j,i].set_yticklabels([])
axes1[1,1].set_xlabel("Rest 1500$\\AA$ Absolute Mag")
axes2[1,1].set_xlabel("Rest 1500$\\AA$ Apparent Mag")
axes1[1,0].set_ylabel("Vmax Correction")
axes2[1,0].set_ylabel("Vmax Correction")
fig.savefig('plots/check_sample_vols.png')
def check_sample_selfrac():
fig,axes = plt.subplots(2,3,figsize=(12,9),dpi=75,sharex='col',sharey=True)
fig.subplots_adjust(left=0.1,right=0.98,bottom=0.2,top=0.98,wspace=0,hspace=0)
for i,drop_filt in enumerate(['f225w','f275w','f336w']):
for j,sample_type in enumerate(['dropout','photoz']):
selfn = SelectionFunction(drop_filt=drop_filt,sample_type=sample_type)
xx,yy = np.arange(0.5,5,.01), np.arange(-22,-14,0.1)
(gy,gx),gz = np.meshgrid(yy,xx), selfn.get_func(hlr=-99.)(xx,yy)
im = axes[j,i].pcolormesh(gx,gy,gz,lw=0,cmap=plt.cm.inferno,vmin=0,vmax=1)
sample = mk_sample.mk_sample(drop_filt=drop_filt,sample_type=sample_type,return_all=True)
cond = (sample['SAMPLE_FLAG']==1)
selfr = np.array([selfn(entry['M_1500'],entry['z'],hlr=entry['HLR_IN']) for entry in sample])
axes[j,i].scatter(sample['BPZ'][cond],sample['M_1500'][cond],facecolor=selfr[cond],edgecolor='w',s=50,lw=0.2,cmap=plt.cm.inferno,vmin=0,vmax=1)
axes[j,i].scatter(sample['BPZ'][~cond],sample['M_1500'][~cond],facecolor=selfr[~cond],edgecolor='r',s=50,lw=0.5,cmap=plt.cm.inferno,vmin=0,vmax=1)
axes[1,0].set_ylabel("Absolute Magnitude")
axes[0,0].set_ylim(-14.1,-21.9)
axes[1,1].set_xlabel("Photo-z")
axes[0,0].set_xlim(0.5,2.35)
axes[0,1].set_xlim(0.9,2.9)
axes[0,2].set_xlim(0.9,4.1)
cbax = fig.add_axes([0.2,0.08,0.6,0.02])
cbar = fig.colorbar(mappable=im,cax=cbax,orientation='horizontal')
cbar.set_label('Relative Effiency')
fig.savefig('plots/check_sample_selfrac.png')
def check_sample_volfrac():
fig,axes = plt.subplots(2,3,figsize=(12,9),dpi=75,sharex='col',sharey=True)
fig.subplots_adjust(left=0.1,right=0.98,bottom=0.2,top=0.98,wspace=0,hspace=0)
for i,drop_filt in enumerate(['f225w','f275w','f336w']):
for j,sample_type in enumerate(['dropout','photoz']):
sample = mk_sample.mk_sample(drop_filt=drop_filt,sample_type=sample_type,return_all=True)
cond = (sample['SAMPLE_FLAG']==1)
im = axes[j,i].scatter(sample['BPZ'][cond],sample['M_1500'][cond],c=sample['Vfrac'][cond],s=50,lw=0.2,cmap=plt.cm.inferno,vmin=0,vmax=1)
im = axes[j,i].scatter(sample['BPZ'][~cond],sample['M_1500'][~cond],c=sample['Vfrac'][~cond],s=50,marker='x',lw=1,cmap=plt.cm.inferno,vmin=0,vmax=1)
axes[1,0].set_ylabel("Absolute Magnitude")
axes[0,0].set_ylim(-14.1,-21.9)
axes[1,1].set_xlabel("Photo-z")
axes[0,0].set_xlim(0.5,2.35)
axes[0,1].set_xlim(0.9,2.9)
axes[0,2].set_xlim(0.9,4.1)
cbax = fig.add_axes([0.2,0.08,0.6,0.02])
cbar = fig.colorbar(mappable=im,cax=cbax,orientation='horizontal')
cbar.set_label('Effective Volume Fraction')
fig.savefig('plots/check_sample_volfrac.png')
def check_z():
bins = np.arange(0,5,0.1)
zz = np.arange(0.5,5,0.05)
mag_range = [25,26,27,28,29]
colors = ['b','c','limegreen','r','m']
catalog = fitsio.getdata('catalogs/udf_cat_v2.0.hlr.fits')
catalog = catalog[(catalog['UVUDF_COVERAGE']==1) & (catalog['UVUDF_EDGEFLG']==0)]
for sample_type in ['dropout','photoz']:
fig,axes = plt.subplots(1,3,figsize=(16,5),dpi=75)
fig.subplots_adjust(left=0.055,right=0.94,bottom=0.14,top=0.95,hspace=0,wspace=0.3)
daxes = []
axes[0].text(0.95,0.95,"F225W Dropouts\n(z~1.65)",va='top',ha='right', fontsize=14,fontweight=600,transform=axes[0].transAxes)
axes[1].text(0.50,0.95,"F275W Dropouts (z~2.2)",va='top',ha='center',fontsize=14,fontweight=600,transform=axes[1].transAxes)
axes[2].text(0.05,0.95,"F336W Dropouts\n(z~3)",va='top',ha='left', fontsize=14,fontweight=600,transform=axes[2].transAxes)
axes[0].set_xlim(0.5,2.45)
axes[1].set_xlim(0.9,2.9)
axes[2].set_xlim(0.9,4.1)
if sample_type=='dropout':
axes[0].set_ylim(0,20)
axes[1].set_ylim(0,25)
axes[2].set_ylim(0,50)
for ax,drop_filt,det_filt,filt_1500 in zip(axes,['f225w','f275w','f336w'],['f275w','f336w','f435w'],['f336w','f435w','f435w']):
sample = mk_sample.mk_sample(drop_filt=drop_filt,sample_type=sample_type)
selfunc = SelectionFunction(drop_filt=drop_filt,sample_type=sample_type)
if sample_type=='dropout':
cond = (conv.calc_sn(catalog[utils.filt_key[det_filt]],catalog[utils.dfilt_key[det_filt]]) > 5)
elif sample_type=='photoz':
cond = (conv.calc_sn(catalog[utils.filt_key[filt_1500]],catalog[utils.dfilt_key[filt_1500]]) > 5)
#ax.hist(catalog['ZB_B'][cond], bins=bins,color='k',lw=1,histtype='step',alpha=0.8)
ax.hist(sample['BPZ'], bins=bins,color='k',lw=0,alpha=0.2,label='Photo-z')
ax.hist(sample['GRISMZ'],bins=bins,color='b',lw=0,alpha=0.5,label='Grism-z')
ax.hist(sample['SPECZ'], bins=bins,color='r',lw=0,alpha=0.5,label='Spec-z')
dax = ax.twinx()
daxes.append(dax)
dax.set_ylim(0,1)
dax.set_xlim(ax.get_xlim())
if sample_type=='dropout':
_mag_range = mag_range[:-1]
else: _mag_range = mag_range
for m,c in zip(_mag_range,colors):
absM = np.array([conv.get_abs_from_app(m,_z) for _z in zz])
selfr = selfunc.get_func(hlr=-99.)(zz,absM,grid=False)
dax.plot(zz,selfr,c=c,lw=2,label='$m_{UV}$ = %i'%m)
if sample_type=='photoz':
norm = 1./np.max(selfunc.get_func(hlr=-99.)(zz,-22,grid=False))
ax.set_ylim(0,0.9*norm*ax.get_ylim()[1])
ax.set_xlabel('Redshift',fontsize=24)
if ax==axes[0]: ax.set_ylabel('Number',fontsize=24)
if ax==axes[2]: dax.set_ylabel('Completeness',fontsize=24)
_ = [label.set_fontsize(20) for label in ax.get_xticklabels()+ax.get_yticklabels()]
axes[0].legend(fontsize=14,loc=2,frameon=False)
leg = daxes[2].legend(fontsize=14,loc=1,frameon=False,handlelength=0,handletextpad=0)
for txt,hndl in zip(leg.get_texts(),leg.legendHandles):
txt.set_fontweight(600)
txt.set_color(hndl.get_color())
hndl.set_visible(False)
fig.savefig('plots/check_z_%s.png'%sample_type)
fig.savefig('plots/check_z_%s.pdf'%sample_type)
if __name__ == '__main__':
# check_photoz()
# check_cuts()
# check_sample_vols()
# check_sample_selfrac()
# check_sample_volfrac()
check_z()
# check_size()
# check_mag_size()
plt.show()