# linear interpolate to lambdas of interest
specarr[n] = np.interp(lambdas, agnlamb, agnscfl)
# Finad median flux of all AGNs in sample
medflux = np.median(specarr, axis=0)
# Exposure time and SNR arrays
exptarr = np.zeros((len(zrange), lams.size, mags.size), np.float)
snrarr = np.zeros((len(zrange), lams.size, mags.size), np.float)
for i, z in enumerate(zrange):
print i, z
# Shift spectrum by redshift
agn = np.column_stack((lambdas*(1+z), medflux))
# Feed through telescope with wavelengths of interest shifted too
agnspec = sp.simspec(agn, lams*(1+z))
for j, l in enumerate(lams):
# Sky photons s-1 in diffraction limited core for filter
Rsky = agnspec['Rsky'][j]
Rn2n = agnspec['RN2n'][j]
if Rsky < 0:
continue
for k, m in enumerate(mags):
# m - Jmag = -2.5 log (Ragn/Rsrc)
# Source photons s-1 in slit given magnitude
Rsrc = agnspec['Rsrc'][j]
if Rsrc > 0:
Ragn = Rsrc * 10**(-(m-15.0)/2.5)
else:
lamKs= np.arange(Ks['start'], Ks['end']+space, space) lj = len(lamJ) lh = len(lamH) lks= len(lamKs) lams = np.hstack((lamJ, lamH, lamKs)) # mosfire #mlamJ = np.arange(MJ['start'], MJ['end']+space, space) #mlamH = np.arange(MH['start'], MH['end']+space, space) #mlamKs= np.arange(MKs['start'], MKs['end']+space, space) #mlams = np.hstack((mlamJ, mlamH, mlamKs)) #lmj = len(mlamJ) #lmh = len(mlamH) #lmks= len(mlamKs) # Send through the telescope vegaspec = ss.simspec(vega, lams) #vegamos = ss.simspec(vega, mlams, filts='mos') vegamos = ss.simspec(vega, lams, subaps=8) # Plot of spectroscopy magnitude limits ymin = 15 ymax = 19.5 mp.clf() mp.grid(True) mp.ylim(ymin, ymax) mp.xlim(J['start'],Ks['end']) pj, = mp.plot(lamJ, vegaspec['limmag'][0:lj], 'r-') pmj,= mp.plot(lamJ, vegamos['limmag'][0:lj], 'b-') #pmj,= mp.plot(mlamJ, vegamos['limmag'][0:lmj], 'b-')
def agnlines():
R = 500.0 # lambda/delta lambda
sn = 5.0 # 5 sigma detection
ft = 600.0 # fowler time in secs
lines = ["-","--","-.",":","-","--"]
linecycler = cycle(lines)
# Wavelength scale from start of J to end of K filters
xmin = 1100 # nm
xmax = 2400
# Rest frame wavelengths of interest
pasb = 1282.18072 # nm - Paschen beta line
fe2fb = 1256.68 # [FeII]
h2 = 2121.83 # H2
brg = 2166.12 # Br-gamma
#lams = np.array((pasb, fe2fb, h2, brg))
#lname= ['Paschen-$\beta$', '[FeII]', 'H$_2$', 'Br-$\gamma$']
lams = np.array((pasb, fe2fb))
lname= ['Paschen-$\beta$', '[FeII]']
# Read in AGN flux file
# From 2008 Landt et al. Mrk110 is a narrow-line Seyfert 1 galaxy
# z = 0.035 (from NED); J mag = 13.9 (from 2MASS); V mag = 16.4 (Veron-Cetty)
#mkn110 = np.loadtxt('spectra/AGN/mkn110.txt')
#agnz = 0.035 # mrk110 has z=0.035
#agnJ = 13.872 # J mag in Johnson system
#agnH = 13.159 # H mag
# convert from ergs s-1 cm-2 A-1 to ergs s-1 m-2 nm-1
#agnflux = mkn110[:,1]*1.0e5
#agnlamb = mkn110[:,0]*1000.0/(1+agnz) # table has wavelength in microns
# shift lambda to rest frame
# J-band magnitude range
mags = np.arange(15.0, 21.0, 1.0)
zrange = np.arange(0.01, 0.1, 0.01)
agns = at.read('spectra/AGN/properties-edit.txt')
fileroot = 'spectra/AGN/'
plotroot = 'figs/agns/'
# exposure time array redshift (rows) x wavelengths (columns) x mags
exptarr = np.zeros((len(agns.z), len(zrange), lams.size, mags.size),
np.float)
snrarr = np.zeros((len(agns.z), len(zrange), lams.size, mags.size),
np.float)
for n, gal in enumerate(agns.Name):
#if n == 1:
# break
print 'Reading AGN '+gal
agnspec = np.loadtxt(fileroot+gal+'.txt')
# convert from ergs s-1 cm-2 A-1 to ergs s-1 m-2 nm-1
agnflux = agnspec[:,1]*1.0e5
# table has wavelength in microns, convert to nm &
# shift lambda to rest frame
agnlamb = agnspec[:,0]*1000.0/(1+agns.z[n])
#exptarr = np.zeros((len(zrange), lams.size, mags.size), np.float)
#snrarr = np.zeros(len(zrange), lams.size, mags.size), np.float)
for i, z in enumerate(zrange):
# Shift spectrum by redshift
agn = np.column_stack((agnlamb*(1+z), agnflux))
# Feed through telescope with wavelengths of interest shifted too
agnspec = sp.simspec(agn, lams*(1+z))
for j, l in enumerate(lams):
# Sky photons s-1 in diffraction limited core for filter
Rsky = agnspec['Rsky'][j]
Rn2n = agnspec['RN2n'][j]
if Rsky < 0:
continue
for k, m in enumerate(mags):
# m - Jmag = -2.5 log (Ragn/Rsrc)
# Source photons s-1 in slit given magnitude
Rsrc = agnspec['Rsrc'][j]
if Rsrc > 0:
Ragn = Rsrc * 10**(-(m-agns.J[n])/2.5)
else:
continue
# Solve the SNR quadratic equation for t
exptarr[n,i,j,k] = ((sn**2*(Ragn + Rsky) +
np.sqrt(sn**4*(Ragn + Rsky)**2 +
4*sn**2*Ragn**2*Rn2n))
/(2*Ragn**2))
snrarr[n,i,j,k] = ((Ragn*ft)/
np.sqrt(Ragn*ft + Rsky*ft + Rn2n))
# return exptarr, snrarr
fig = mp.figure()
ax = fig.add_subplot(311)
ax.set_xlim(xmin, xmax)
ax.set_xticklabels([])
ax.grid(True)
ax.plot(agnlamb, agnflux)
ax.set_ylabel(r'Flux - ergs s$^{-1}$ m$^{-2}$ nm$^{-1}$')
ax.text(0.5, 0.9,'Spectrum and SNR for AGN '+gal, ha='center',
va='center', transform=ax.transAxes)
ax2 = ax.twiny()
lo_ticks = np.array([1400., 1600., 1800., 2000., 2200.])
new_tick_locations = (lo_ticks-xmin)/(xmax-xmin)
ax2.set_xticks(new_tick_locations)
ax2.set_xticklabels(lo_ticks)
ax2.set_xlabel(r"Wavelength $(nm)$")
# Paschen beta plot
ax1 = fig.add_subplot(312)
ymin = 1e-2
ymax = 1e3
ax1.grid(True)
ax1.set_title(r'Paschen-$\beta$ (Top), [FeII] (Bot) SNR v. $z$')
ax1.set_xlim(xmin, xmax)
#ax1.set_xlabel(r'Wavelength ($nm$)')
def pb_tick_function(X):
V = ((xmin + X * (xmax-xmin))/ pasb)-1.0
return ["%.2f" % z for z in V]
lo_ticks = np.array([1400., 1600., 1800., 2000., 2200.])
new_tick_locations = (lo_ticks-xmin)/(xmax-xmin)
ax1.set_xticks(lo_ticks)
ax1.set_xticklabels(pb_tick_function(new_tick_locations))
#ax1.set_xticklabels([])
ax1.set_ylim(ymin, ymax)
ax1.set_yscale('log')
ax1.set_ylabel('SNR')
# reduce number of y-axis ticks
#ax1.locator_params(axis='y',tight=True, nbins=4)
ax1.set_yticks([1e-2,1,1e2])
# Plot Paschen-beta SNR vs. z for each mag
curves = []
for k,m in enumerate(mags):
p, = ax1.plot(pasb*(1+zrange), snrarr[n,:,0,k]+1e-9, lines[k])
curves.append(p)
ax1.plot([xmin,xmax],[5,5],'k-',linewidth=2)
ax1.text(xmax-160, 5.5, 'SNR=5')
#ax1.plot([H['start'],H['start']],[ymin,ymax],'--',color='0.75',linewidth=1)
ax1.plot([H['start'],H['start']],[ymin,ymax],'b--',linewidth=1)
ax1.plot([H['end'],H['end']],[ymin,ymax],'b--',linewidth=1)
ax1.text(H['cwvl']*1e9, 0.1, 'H', color='b')
ax1.plot([Ks['start'],Ks['start']],[ymin,ymax],'r--',linewidth=1)
ax1.plot([Ks['end'],Ks['end']],[ymin,ymax],'r--',linewidth=1)
ax1.text(Ks['cwvl']*1e9, 0.1, 'Ks', color='r')
mp.legend(curves, mags, loc='upper left', title='J-band mags',
prop={'size':10})
# [FeII] plot
ax3 = fig.add_subplot(313)
ax3.grid(True)
#ax4 = ax3.twiny()
#ax3.set_title(r'[FeII] SNR')
ax3.set_xlim(xmin, xmax)
def fe_tick_function(X):
V = ((xmin + X * (xmax-xmin))/ fe2fb)-1.0
return ["%.2f" % z for z in V]
ax3.set_xticks(lo_ticks)
ax3.set_xticklabels(fe_tick_function(new_tick_locations))
ax3.set_xlabel(r'Redshift ($z$)')
ax3.set_ylim(ymin, ymax)
ax3.set_yscale('log')
ax3.set_ylabel('SNR')
ax3.set_yticks([1e-2,1,1e2])
# Plot [FeII] SNR vs. z for each mag
curves = []
for k,m in enumerate(mags):
p, = ax3.plot(fe2fb*(1+zrange), snrarr[n,:,1,k]+1e-9, lines[k])
curves.append(p)
ax3.plot([xmin,xmax],[5,5],'k-',linewidth=2)
ax3.text(xmin+100, 5.5, 'SNR=5')
ax3.plot([H['start'],H['start']],[ymin,ymax],'b--',linewidth=1)
ax3.plot([H['end'],H['end']],[ymin,ymax],'b--',linewidth=1)
ax3.text(H['cwvl']*1e9, 0.1, 'H', color='b')
ax3.plot([Ks['start'],Ks['start']],[ymin,ymax],'r--',linewidth=1)
ax3.plot([Ks['end'],Ks['end']],[ymin,ymax],'r--',linewidth=1)
ax3.text(Ks['cwvl']*1e9, 0.1, 'Ks', color='r')
#ax4.set_xticks(new_tick_locations)
#ax4.set_xticklabels(tick_function(new_tick_locations))
#mp.tight_layout()
#mp.show()
mp.savefig(plotroot+gal+'.png')
return exptarr, snrarr
