def readpsoutput(self,file,z): input=open(file,'r') mass=[] frac=[] for line in input: t=line.split() mass.append(float(t[2])) frac.append(float(t[3])) #try: #frac.append(float(t[3])) #except: # frac.append(1.e-10) input.close() mass=N.array(mass,'d') sigma=((mass/(1.2e15/h)*N.sqrt(.7+.3*(1+z)**3))**(1./3.))*1000. frac=N.array(frac,'d') sigma=N.log10(sigma) #maccret=(frac*mass) maccret=N.zeros(len(mass),'d') for i in range(len(mass)): maccret[i]=mass[i]*frac[i] print i,mass[i],frac[i],maccret[i] frac=N.log10(frac) self.sigma=sigma self.mass=mass self.frac=frac self.maccret=maccret
def makeplotsub(c):
plot(c.f24, c.fap4 * 1.67, 'bo', markersize=4)
#plot(c.f24,c.fap4,'ro',markersize=4)
#plot(c.f24,c.fap3,'go',markersize=2)
#plot(c.f24,c.fap2,'yo',markersize=2)
#plot(c.f24,c.fap1,'co',markersize=2)
x = N.arange(1., max(c.f24), 100.)
y = x
plot(x, y, 'k-')
y2 = y + N.log10(2.)
plot(x, y2, 'k--')
y2 = y + N.log10(.5)
plot(x, y2, 'k--')
y = 3. * x
#plot(x,y,'k-')
y = 4. * x
#plot(x,y,'k-')
y = 5. * x
#plot(x,y,'k-')
ax = gca()
text(.1,
.8,
c.prefix,
horizontalalignment='left',
verticalalignment='center',
transform=ax.transAxes)
#xlabel('Mopex F(24)',fontsize=fsize)
#ylabel('Ap Flux ',fontsize=fsize)
axis([20., 4000., 20., 4000.])
ax.set_xscale('log')
ax.set_yscale('log')
def gwritefiles(self,clusters,j):
outfile=clusters[:(len(clusters)-4)]+'2.dat'
out=open(outfile,'w')
infile=open(clusters,'r')
i=0
ds5=[]
ds10=[]
k=0
for line in infile:
if line.find('#') > -1:
out.write(line)
continue
if k < 1:
out.write('# 27 Sigma_5 calculated from spec sample \n')
out.write('# 28 Sigma_10 calculated from spec sample \n')
out.write('# 29 Sigma_5 calculated from phot sample \n')
out.write('# 30 Sigma_10 calculated from phot sample \n')
out.write('# 31 Sigma_5 calculated from spec sample extended to 2xR200 \n')
out.write('# 32 Sigma_10 calculated from spec sample extended to 2xR200\n')
out.write('# 33 M_V (h100 = 0.7) corrected to cluster redshift \n')
k=1
fields=line.split()
dLgal=my.dL(float(fields[4]),h100)
dm=5.*N.log10(dLgal/c.dL[j])#correct abs mag to cluster redshift
m=float(fields[22])+dm
m=m-0.77#convert to h100=0.7
if (m > mabscut):#keep only galaxies that meet mag cut
out.write(line)
#print "didn't make mag cut",m,mabscut,
continue
distmod=5.*N.log10(dLgal)+25.
g=float(fields[10])-0.77+ distmod
r=float(fields[11])-0.77+ distmod
if (g > 18.0):
#print "didn't make g cut, g = ",g,fields[10],m,distmod
continue
if (r > 17.7):
#print "didn't make r cut, g = ",r,fields[11],m
continue
if (abs(float(fields[25])/(c.z[j]+1)*3.e5) > 3*c.sigma[j]):#keep only galaxies w/in 3 sigma
out.write(line)
#print "didn't make vel cut"
continue
#print i, 'writing output ',len(self.sig5),len(self.sig5),len(self.sig10),len(self.sig5phot),len(self.sig10phot),len(line)
nline=line[:(len(line)-2)]+" %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f\n"%(self.sig5[i],self.sig10[i],self.sig5phot[i],self.sig10phot[i], self.sig52r200[i],self.sig102r200[i], self.V[i])
d5=(self.sig5phot[i]-self.sig5[i])
d10=(self.sig10phot[i]-self.sig10[i])
#print " %8.2f %8.2f %8.2f %8.2f %8.2f %8.2f \n"%((self.sig5phot[i]-self.sig5[i]),(self.sig10phot[i]-self.sig10[i]),self.sig5[i],self.sig10[i],self.sig5phot[i],self.sig10phot[i])
out.write(nline)
ds5.append(d5)
ds10.append(d10)
i=i+1
out.close()
infile.close()
return ds5, ds10
def greadfiles(self, clusters, i):
infile = open(clusters, 'r')
distmod = (5. * N.log10(c.dL[i]) + 25.)
for line in infile:
if line.find('#') > -1:
continue
fields = line.split()
#print fields[25]
dLgal = my.dL(float(fields[4]), h100)
dm = 5. * N.log10(
dLgal / c.dL[i]) #correct abs mag to cluster redshift
m = float(fields[22]) + dm
m = m - 0.77 #convert to h100=0.7
if (m > mabscut): #keep only galaxies that meet mag cut
continue
#apply color selection to mimic ediscs selection
distmod = 5. * N.log10(dLgal) + 25.
g = float(fields[10]) - 0.77 + distmod
r = float(fields[11]) - 0.77 + distmod
if (g > 18.0):
#print "didn't make g cut, g = ",g,fields[10],m,distmod
continue
if (r > 17.7):
#print "didn't make r cut, g = ",r,fields[11],m
continue
if (abs(float(fields[25]) / (c.z[i] + 1) * 3.e5) >
3 * c.sigma[i]): #keep only galaxies w/in 3 sigma
continue
self.z.append(float(fields[4]))
self.ra.append(float(fields[5]))
self.dec.append(float(fields[6]))
self.o2.append(float(fields[7]))
self.erro2.append(float(fields[8]))
self.u.append(float(fields[9]))
self.g.append(float(fields[10]))
self.r.append(float(fields[11]))
self.i.append(float(fields[12]))
self.zm.append(float(fields[13]))
self.gpetrext.append(float(fields[14]))
self.rpetrext.append(float(fields[15]))
self.ipetrext.append(float(fields[16]))
self.zpetrext.append(float(fields[17]))
self.V.append(m)
self.distBCG.append(float(fields[23]))
self.distBCGR200.append(float(fields[23]))
self.dz.append(float(fields[25]))
infile.close()
def calculate_spectrogram(input_array, framesize, hopsize, window_function = numarray.linear_algebra.mlab.hanning, keep_bands_until = 0, axis = 0): """Calculate the spectrogram.""" do_fft = lambda arr: abs(numarray.fft.real_fft(arr, axis = axis))[:keep_bands_until] keep_bands_until = keep_bands_until or int(framesize / 2) input_shape = map(None, numarray.shape(input_array)) window = window_function(framesize) if len(input_shape) > 1: window = transpose(array([list(window)] * input_shape[1])) # print "input_shape:", shape(input_array) zeros_shape = input_shape # this allows for both 1 and 2 dim inputs zeros_shape[0] = framesize / 2 input_array_plus_zeros = numarray.concatenate((numarray.zeros(zeros_shape), input_array, numarray.zeros(zeros_shape))) fft_range = range(0, len(input_array) - framesize, hopsize) fft_array = numarray.zeros(([len(fft_range)] + map(None, numarray.shape(do_fft(window)))), # do_fft(window) is used here because it gives the right shape numarray.Float32) * 1.0 # this *1.0 is necessary! for result_counter, input_counter in enumerate(fft_range): frame = window * input_array_plus_zeros[input_counter : input_counter + framesize] fft_array[result_counter] = 10 * numarray.log10(0.1 + do_fft(frame)) return fft_array
def getsdssspeccats(self): #get photometric sources within 2R200
print "elapsed time = ", time.clock() - starttime
self.mcut = N.zeros(len(self.z), 'f')
for i in range(len(self.z)):
dL = self.dL[i]
print "getting spec cat for cluster abell", self.id[i]
r200arcmin = self.r200deg[i] * 60.
drsearch = 3. * r200arcmin #2xR200 in arcmin for sdss query
#Vg=0.3556-0.7614*((self.avegr)-0.6148)#(V-g) from Blanton et al 2003
mr = mabscut - 0.1331 + 5. * N.log10(dL) + 25. + self.kcorr[i]
print i, self.z[i], dL, mr
self.mcut[i] = mr
dz = 3 * self.sigma[i] / (3.e5) * (1 + self.z[i])
zmax = self.z[i] + .5 * dz
zmin = self.z[i] - .5 * dz
print "ra, dec, dr, mr = %12.8f %12.8f %8.3f %5.2f" % (
self.ra[i], self.dec[i], drsearch, mr)
query = "select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z, g.objid, g.specObjID,g.extinction_u, g.extinction_g, g.extinction_r, g.extinction_i, g.extinction_z, l.ew, l.ewErr, l2.ew, l2.ewErr from galaxy g, specobj s, SpecLine l, SpecLine l2, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and g.objID = s.bestobjid and s.specobjID=l.specobjID and s.specobjID=l2.specobjID and (g.g < %5.2f) and (g.PrimTarget & 0x00000040) > 0 and (s.z > %6.4f) and (s.z < %6.4f) and l.LineID = 3727 and l2.LineID = 6565" % (
self.ra[i], self.dec[i], drsearch, (mr + 3), zmin, zmax)
# query="select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z, g.objid, g.specObjID,g.extinction_u, g.extinction_g, g.extinction_r, g.extinction_i, g.extinction_z, l.ew, l.ewErr, l2.ew, l2.ewErr from galaxy g, specobj s, SpecLine l, SpecLine l2, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and g.objID = s.bestobjid and s.specobjID=l.specobjID and s.specobjID=l2.specobjID and (g.g < %5.2f) and (g.PrimTarget & 0x00000040) > 0 and l.LineID = 3727 and l2.LineID = 6565" % (self.ra[i],self.dec[i],drsearch,(mr))
lines = sqlcl.query(query).readlines()
#print query
print "got number+1 spec objects w/in 2R200= ", len(lines)
#print lines
output = "abell" + str(self.id[i]) + ".spec2r200.dat"
outfile = open(output, 'w')
outfile.write("#%s " % (lines[0]))
for line in lines[1:]:
outfile.write("%s " % (line))
outfile.close()
def binitbinsmabs(xmin, xmax, nbin, x, y): #use equally spaced bins
y = 10.**(y)
dx = float((xmax - xmin) / (nbin))
xbin = N.arange(xmin, (xmax), dx) + dx / 2.
ybin = N.zeros(len(xbin), 'd')
ybinerr = N.zeros(len(xbin), 'd')
xbinnumb = N.array(len(x), 'd')
x1 = N.compress((x >= xmin) & (x <= xmax), x)
y1 = N.compress((x >= xmin) & (x <= xmax), y)
x = x1
y = y1
xbinnumb = ((x - xmin) * nbin / (xmax - xmin)
) #calculate x bin number for each point
j = -1
for i in range(len(xbin)):
ydata = N.compress(abs(xbinnumb - float(i)) < .5, y)
try:
ybin[i] = N.log10(N.average(ydata))
#ybin[i]=pylab.median(ydata)
ybinerr[i] = pylab.std(ydata) / N.sqrt(float(len(ydata)))
except ZeroDivisionError:
ybin[i] = -99.
ybinerr[i] = -99.
return xbin, ybin, ybinerr
def fig3b(t, m, w, p):
""" Plot image of age,metallicity weights -- nearest neighbor interpolation"""
NREP = 50
xi = pylab.linspace(0.1, 15, 512)
yi = pylab.linspace(-2.5, 0.9, 512)
z = numarray.zeros((len(xi), len(yi)),
numarray.Float) # create t, metallicity array
y = numarray.repeat(m, NREP)
dt = t[1] - t[0]
x = numarray.arange(t[0], t[-1] + 2 * dt, dt / NREP)
x = x[0:len(y)]
x = 10.**x / 1.e9
weight = numarray.repeat(w, NREP)
# Find the indices in the array
xindex = numarray.searchsorted(xi, x)
print "shape(x), shape(y), shape(weight)", numarray.shape(
x), numarray.shape(y), numarray.shape(weight)
if p.sigma > 0:
if p.dsigmadlogt == 0.:
for i in range(len(y)):
nstars = weight[i] * normgauss(yi, y[i], p.sigma)
j = xindex[i]
z[j, :] += nstars
if p.dsigmadlogt != 0.:
for i in range(len(y)):
logt0 = numarray.log10(x[0])
logt = numarray.log10(x[i])
sigma = p.sigma + p.dsigmadlogt * (logt - logt0)
nstars = weight[i] * normgauss(yi, y[i], sigma)
j = xindex[i]
z[j, :] += nstars
else:
sigma = 0.01
for i in range(len(y)):
nstars = weight[i] * normgauss(yi, y[i], sigma)
j = xindex[i]
z[j, :] += nstars
# yindex = numarray.searchsorted(yi,y)
# z[xindex,yindex] = z[xindex,yindex] + weight # increment the 2-d array
zz = numarray.transpose(z)
pylab.imshow(zz, extent=[0.1, 15, -2.5, 0.9], aspect='auto')
pylab.xlabel("Age (Gyr)")
pylab.ylabel("[Fe/H]")
return xi, yi, zz
def plotsig10sffall(sigspec, sigphot, sf, file, nbin):
psplot = file + ".ps"
psplotinit(psplot)
ppgplot.pgbox("", 0.0, 0, "L", 0.0, 0)
ymin = -.01
ymax = 1.01
#xmin=min(sigspec)-10.
#xmax=max(sig)-200.
#xmax=400.
xmin = -1.
xmax = 2.7
ppgplot.pgenv(xmin, xmax, ymin, ymax, 0, 10)
ppgplot.pglab("\gS\d10\u (gal/Mpc\u2\d)", "Fraction EW([OII])>4 \(2078)",
"")
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
tot = N.ones(len(sf), 'f')
(sigbin, sfbin) = my.binitsumequal(sigspec, sf, nbin)
(sigbin, totbin) = my.binitsumequal(sigspec, tot, nbin)
(sff, sfferr) = my.ratioerror(sfbin, totbin)
#sig=N.array(sig,'f')
#sff=N.array(sff,'f')
ppgplot.pgsci(2)
sigbin = N.log10(sigbin)
ppgplot.pgline(sigbin, sff)
ppgplot.pgsci(1)
ppgplot.pgpt(sigbin, sff, 17)
my.errory(sigbin, sff, sfferr)
(sigbin, sfbin) = my.binitsumequal(sigphot, sf, nbin)
(sigbin, totbin) = my.binitsumequal(sigphot, tot, nbin)
(sff, sfferr) = my.ratioerror(sfbin, totbin)
#sig=N.array(sig,'f')
#sff=N.array(sff,'f')
ppgplot.pgslw(4) #line width
ppgplot.pgsci(4)
sigbin = N.log10(sigbin)
ppgplot.pgline(sigbin, sff)
ppgplot.pgsci(1)
ppgplot.pgpt(sigbin, sff, 21)
#my.errory(sigbin,sff,sfferr)
ppgplot.pgend()
def plotsighaall(sig, psig, o2b, file, nbin):
o2b = N.array(o2b, 'f')
sig = N.array(sig, 'f')
psig = N.array(psig, 'f')
#o2b=o2b+4.
o2 = N.compress(o2b > -500., o2b)
sig = N.compress(o2b > -500., sig)
psig = N.compress(o2b > -500., psig)
psplot = file + ".ps"
psplotinit(psplot)
#ppgplot.pgsch(0.7)
ppgplot.pgslw(7)
(sigbin, o2bin) = my.binit(sig, o2, nbin)
#print 'dude', sigbin, o2bin
sigbin = N.log10(sigbin)
ppgplot.pgswin(-2., 2., -5., 20.)
ppgplot.pgbox('blcnst', 0.0, 0.0, 'bcvnst', 0.0,
0.0) #tickmarks and labeling
ppgplot.pgsch(1.0)
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "\gS\d10\u (gal/Mpc\u2\d)") #xlabel
ppgplot.pgsch(1.2)
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, 'EW(H\ga) (\(2078))')
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
ppgplot.pgpt(sigbin, o2bin, 17)
ppgplot.pgpt(N.log10(sig), o2, 1)
#my.errory(sigbin,o2bin,yerr)
#print 'dude2', sigbin, o2bin
ppgplot.pgsci(2)
ppgplot.pgline(sigbin, o2bin)
(sigbin, o2bin) = my.binit(psig, o2, nbin)
#print 'dude', sigbin, o2bin
sigbin = N.log10(sigbin)
ppgplot.pgsci(1)
ppgplot.pgpt(sigbin, o2bin, 21)
#my.errory(sigbin,o2bin,yerr)
ppgplot.pgsci(4)
ppgplot.pgline(sigbin, o2bin)
ppgplot.pgsci(1)
ppgplot.pgend()
def isovalues(isos,isow):
x = numarray.zeros(len(isos))*0. # age
y = numarray.zeros(len(isos))*0. # metallicity
z = numarray.zeros(len(isos))*0. # metallicity
for i in range(len(isos)):
feh,age = iso.scaled2real(isos[i][0],isos[i][1])
y[i] = feh
x[i] = numarray.log10(age)
z[i] = isow[i]
return x,y,z
def isovalues(isos, isow):
x = numarray.zeros(len(isos)) * 0. # age
y = numarray.zeros(len(isos)) * 0. # metallicity
z = numarray.zeros(len(isos)) * 0. # metallicity
for i in range(len(isos)):
feh, age = iso.scaled2real(isos[i][0], isos[i][1])
y[i] = feh
x[i] = numarray.log10(age)
z[i] = isow[i]
return x, y, z
def fig3b(t,m,w,p):
""" Plot image of age,metallicity weights -- nearest neighbor interpolation"""
NREP = 50
xi = pylab.linspace(0.1,15,512)
yi = pylab.linspace(-2.5,0.9,512)
z = numarray.zeros((len(xi),len(yi)),numarray.Float) # create t, metallicity array
y = numarray.repeat(m,NREP)
dt = t[1]-t[0]
x = numarray.arange(t[0],t[-1]+2*dt,dt/NREP)
x = x[0:len(y)]
x = 10.**x/1.e9
weight = numarray.repeat(w,NREP)
# Find the indices in the array
xindex = numarray.searchsorted(xi,x)
print "shape(x), shape(y), shape(weight)", numarray.shape(x),numarray.shape(y), numarray.shape(weight)
if p.sigma > 0:
if p.dsigmadlogt == 0.:
for i in range(len(y)):
nstars = weight[i]*normgauss(yi,y[i],p.sigma)
j = xindex[i]
z[j,:] += nstars
if p.dsigmadlogt != 0.:
for i in range(len(y)):
logt0 = numarray.log10(x[0])
logt = numarray.log10(x[i])
sigma = p.sigma + p.dsigmadlogt*(logt-logt0)
nstars = weight[i]*normgauss(yi,y[i],sigma)
j = xindex[i]
z[j,:] += nstars
else:
sigma = 0.01
for i in range(len(y)):
nstars = weight[i]*normgauss(yi,y[i],sigma)
j = xindex[i]
z[j,:] += nstars
# yindex = numarray.searchsorted(yi,y)
# z[xindex,yindex] = z[xindex,yindex] + weight # increment the 2-d array
zz = numarray.transpose(z)
pylab.imshow(zz,extent=[0.1,15,-2.5,0.9],aspect='auto')
pylab.xlabel("Age (Gyr)")
pylab.ylabel("[Fe/H]")
return xi,yi,zz
def azmr(self):
x=N.compress((self.mpaflag > 0.1) & (self.ew > 4.) & (self.Mabs < -18.),self.Mabs)
y=N.compress((self.mpaflag > 0.1) & (self.ew > 4.) & (self.Mabs < -18.),self.ar)
x1=N.compress((self.mpaflag > 0.1) & (self.ew > 4.) & (self.Mabs < -20.38),self.Mabs)
y1=N.compress((self.mpaflag > 0.1) & (self.ew > 4.) & (self.Mabs < -20.38),self.ar)
y=2.5*N.log10(y)
#pylab.plot(x,y,'k.',markersize=0.1,zorder=1)
print "average Ar for Mr < -20.38 = %5.2f +/- %5.2f"%(N.average(y1),pylab.std(y1))
(xbin,ybin)=my.binit(x1,y1,20)
#(xbin,ybin,ybinerr)=my.biniterr(x,y,20)
for i in range(len(xbin)):
print i,xbin[i],ybin[i]
print "Average of binned values = ",N.average(ybin)
print "average Ar for Mr < -20.38 = %5.2f +/- %5.2f"%(N.average(N.log10(y1)),pylab.std(N.log10(y1)))
#pylab.axis([-26.,-12.,0.1,30.])
pylab.xlabel(r'$\rm{M_r}$',fontsize=28.)
pylab.ylabel(r'$\rm{A_r}$',fontsize=28.)
(xbin,ybin)=my.binit(x,y,20)
#(xbin,ybin,ybinerr)=my.biniterr(x,y,20)
for i in range(len(xbin)):
print i,xbin[i],ybin[i]
pylab.plot(xbin,ybin,'r-',lw=5)
ax=pylab.gca()
xmin=-24.
xmax=-18.
ymin=-1.
ymax=3.
my.contourf(x,y,xmin,xmax,ymin,ymax)
pylab.axvline(x=-20.6,linewidth=3,ls='--',c='g')
xl=N.arange(-23.,-20.5,.2)
yl=0.76*N.ones(len(xl),'f')
pylab.plot(xl,yl,'b-',lw=3)
pylab.axis([-24.,-18,-1.,2.4])
#ax.set_yscale('log')
#pylab.show()
pylab.savefig('armr.eps')
print "fraction w/MPA stellar mass and Az = ",N.sum(self.mpaflag)/(1.*len(self.mpaflag))
def plotsigo2all(sig, psig, o2b, file, nbin):
#o2=N.zeros(len(o2b),'f')
#for i in range(len(o2b)):
#print i, sig[i], psig[i], o2b[i]
# if o2b[i] < 0:
# o2[i]=-1*o2b[i]
#print "hey", o2[i]
o2 = o2b
psplot = file + ".ps"
psplotinit(psplot)
ppgplot.pgsch(0.7)
(sigbin, o2bin) = my.binit(sig, o2, nbin)
#print 'dude', sigbin, o2bin
sigbin = N.log10(sigbin)
ppgplot.pgswin(-1., 3., -.5, 10.)
ppgplot.pgbox('bcnst', 0.0, 0.0, 'bcvnst', 0.0,
0.0) #tickmarks and labeling
ppgplot.pgsch(1.0)
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "\gS\d10\u (gal/Mpc\u2\d)") #xlabel
ppgplot.pgsch(1.2)
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, 'EW([OII]) (\(2078))')
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
ppgplot.pgsci(2)
ppgplot.pgpt(sigbin, o2bin, 17)
#print 'dude2', sigbin, o2bin
ppgplot.pgline(sigbin, o2bin)
(sigbin, o2bin) = my.binit(psig, o2, nbin)
#print 'dude', sigbin, o2bin
sigbin = N.log10(sigbin)
ppgplot.pgsci(4)
ppgplot.pgpt(sigbin, o2bin, 21)
ppgplot.pgline(sigbin, o2bin)
ppgplot.pgsci(1)
ppgplot.pgend()
def greadphotfiles(self, gphotfile, dL, kcorr):
self.photra = []
self.photdec = []
self.phu = []
self.phMv = []
for line in open(gphotfile):
if line.find('#') > -1:
continue
if len(line) < 10: #phot files have blank line at end - skip it
continue
#print line
fields = line.split(',')
#print fields[0], fields[1], line
#need to implement a mag cut
g = float(fields[3])
r = float(fields[4])
if (g > 18.0):
continue
if (r > 17.7):
continue
g01 = g + 0.3134 + 0.4608 * ((g - r) * -0.6148)
g01 = g01 + .01 #convert to vega
r01 = g - 0.4118 - .8597 * ((g - r) * -0.6148)
r01 = r01 - .04 #convert to vega
V = g01 - 0.6689 - 0.9264 * ((g01 - r01) - 0.7252)
g = g - (-0.08) #convert to vega
r = r - (.16) #convert to vega
#g=g-float(fields[10])#correct for extinction
#r=r-float(fields[11])#correct for extinction
V = g - 0.3556 - 0.7614 * ((g - r) - 0.6148)
#mv=V - (5.*N.log10(dL)+25.+kcorr)
mv = V - (5. * N.log10(dL) + 25.)
if ((mv) < mabscut):
self.photra.append(float(fields[0]))
self.photdec.append(float(fields[1]))
self.phu.append(float(fields[2]))
self.phMv.append(float(mv))
#self.photra.append(float(fields[0]))
#self.photdec.append(float(fields[1]))
#self.phu.append(float(fields[2]))
#self.phMv.append(float(mv))
self.photra = N.array(self.photra, 'f')
self.photdec = N.array(self.photdec, 'f')
self.phu = N.array(self.phu, 'f')
self.phMv = N.array(self.phMv, 'f')
def eblPlot(model=pySources.Primack05):
atten = pySources.EblAtten(model)
tau = []
for z in zvalues:
foo = FunctionWrapper(lambda energy: atten(energy, z))
tau.append(foo(energies))
tau = num.array(tau)
disp = plot.image(tau,
num.log10(energies) - 3,
num.log10(zvalues),
xname='log10(E/GeV)',
yname='log10(z)',
zname='tau',
aspect=1)
disp.setPointRep(plot.prf.create('Contour'))
disp.setContourLevels((0.5, 1, 2, 3, 5))
disp.setRange('z', 0, 6)
plot.canvas.selectDisplay(disp)
for id in blazars:
plot.hline(num.log10(blazars[id]))
plot.vline(num.log10(20. / 2e3))
plot.vline(num.log10(2e5 / 2e3))
return disp
def getsdssspeccats(self): #get photometric sources within 2R200
print "elapsed time = ",time.clock()-starttime
self.mcut=N.zeros(len(self.z),'f')
for i in range(len(self.z)):
dL = self.dL[i]
print "getting spec cat for cluster abell",self.id[i]
r200arcmin=self.r200deg[i]*60.
drsearch=3.*r200arcmin#2xR200 in arcmin for sdss query
#Vg=0.3556-0.7614*((self.avegr)-0.6148)#(V-g) from Blanton et al 2003
mr=mabscut - 0.1331 + 5.*N.log10(dL)+25.+self.kcorr[i]
print i, self.z[i], dL, mr
self.mcut[i]=mr
dz=3*self.sigma[i]/(3.e5)*(1+self.z[i])
zmax=self.z[i]+.5*dz
zmin=self.z[i]-.5*dz
def azhist(self):
x=N.compress((self.mpaflag > 0.1) & (self.ew > 4.),self.Mabs)
y=N.compress((self.mpaflag > 0.1) & (self.ew > 4.),self.ar)
y=2.5*N.log10(y)
m1=-18.
self.azhistsub(x,y,m1,'b')
#m1=-19.
#self.azhistsub(x,y,m1,'r')
m1=-20.
self.azhistsub(x,y,m1,'g')
#m1=-21.
#self.azhistsub(x,y,m1,'k')
m1=-22.
self.azhistsub(x,y,m1,'y')
#m1=-23.
#self.azhistsub(x,y,m1,'c')
#pylab.show()
#ax=pylab.gca()
#ax.set_xscale('log')
pylab.legend(loc='upper right')
pylab.savefig('azhist.eps')
def getsdssphotcats(self): #get photometric sources within 2R200
print "elapsed time = ",time.clock()-starttime
self.mcut=N.zeros(len(self.z),'f')
cl=N.arange(17,len(self.z),1)
self.nphot=N.zeros(len(self.z),'f')
self.nspec=N.zeros(len(self.z),'f')
for i in range(len(self.z)):
#for i in cl:
dL = self.dL[i]
print "getting phot cat for cluster abell",self.id[i]
r200arcmin=self.r200deg[i]*60.
#drsearch=2.*r200arcmin#2xR200 in arcmin for sdss query
drsearch=1.*r200arcmin#2xR200 in arcmin for sdss query
#Vg=0.3556-0.7614*((self.avegr)-0.6148)#(V-g) from Blanton et al 2003
mr=mabscut - 0.1331 + 5.*N.log10(dL)+25.+self.kcorr[i]
print i, self.z[i], dL, mr
self.mcut[i]=mr
print "ra, dec, dr, mr = %12.8f %12.8f %8.3f %5.2f" % (self.ra[i],self.dec[i],drsearch,mr)
#query="select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z, g.plate_ID, g.MJD, from galaxy g, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and (g.g < %5.2f) and ((0.384*g.g + 0.716*g.r)< %5.2f)" % (self.ra[i],self.dec[i],drsearch,(mr+1.5),mr)
query="select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z, g.objid, g.specObjID,g.extinction_u, g.extinction_g, g.extinction_r, g.extinction_i, g.extinction_z from galaxy g, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and (g.g < %5.2f) and (g.PrimTarget & 0x00000040) > 0 " % (self.ra[i],self.dec[i],drsearch,(mr))
lines=sqlcl.query(query).readlines()
#print query
print "got number+1 phot objects = ",len(lines)
#print lines
self.nphot[i]=1.*len(lines)
query="select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z, g.objid, g.specObjID,g.extinction_u, g.extinction_g, g.extinction_r, g.extinction_i, g.extinction_z, l.ew, l.ewErr, l2.ew, l2.ewErr from galaxy g, specobj s, SpecLine l, SpecLine l2, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and g.objID = s.bestobjid and s.specobjID=l.specobjID and s.specobjID=l2.specobjID and (g.g < %5.2f) and (g.PrimTarget & 0x00000040) > 0 and l.LineID = 3727 and l2.LineID = 6565" % (self.ra[i],self.dec[i],drsearch,(mr))
lines=sqlcl.query(query).readlines()
#print query
print "got number+1 spec objects w/in R200= ",len(lines)
#print lines
self.nspec[i]=1.*len(lines)
self.compl=self.nspec/self.nphot
print "average completeness of sdss spectroscopy is = ",N.average(self.compl), pylab.std(self.compl)
def getsdssphotcats(self): #get photometric sources within 2R200
print "elapsed time = ", time.clock() - starttime
self.mcut = N.zeros(len(self.z), 'f')
cl = N.arange(17, len(self.z), 1)
for i in range(len(self.z)):
#for i in cl:
dL = self.dL[i]
print "getting phot cat for cluster abell", self.id[i]
r200arcmin = self.r200deg[i] * 60.
#drsearch=2.*r200arcmin#2xR200 in arcmin for sdss query
drsearch = 3. * r200arcmin #2xR200 in arcmin for sdss query
#Vg=0.3556-0.7614*((self.avegr)-0.6148)#(V-g) from Blanton et al 2003
mr = mabscut - 0.1331 + 5. * N.log10(dL) + 25. + self.kcorr[i]
print i, self.z[i], dL, mr
self.mcut[i] = mr
print "ra, dec, dr, mr = %12.8f %12.8f %8.3f %5.2f" % (
self.ra[i], self.dec[i], drsearch, mr)
#query="select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z, g.plate_ID, g.MJD, from galaxy g, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and (g.g < %5.2f) and ((0.384*g.g + 0.716*g.r)< %5.2f)" % (self.ra[i],self.dec[i],drsearch,(mr+1.5),mr)
query = "select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z, g.objid, g.specObjID,g.extinction_u, g.extinction_g, g.extinction_r, g.extinction_i, g.extinction_z from galaxy g, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and (g.g < %5.2f) and (g.PrimTarget & 0x00000040) > 0 " % (
self.ra[i], self.dec[i], drsearch, (mr))
#line from sdssinter.py code
#query="select n.distance from galaxy g, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and g.r< %5.2f and (g.PrimTarget & 0x00000040) > 0 order by distance" % (self.ra[i],self.dec[i],drsearch,mr)#added flags to get rid of saturated objects, stars, etc
#query="select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z from galaxy g, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID" % (self.ra[i],self.dec[i],drsearch)#no mag cut
#query="select g.ra, g.dec, g.u, g.g, g.r, g.i, g.z from galaxy g, dbo.fGetNearbyObjEq(%12.8f,%12.8f,%8.3f) n where g.objID = n.objID and g.r<17.7 and g.g<18.0" % (self.ra[i],self.dec[i],drsearch)
lines = sqlcl.query(query).readlines()
#print query
print "got number+1 phot objects = ", len(lines)
#print lines
output = "abell" + str(self.id[i]) + ".phot.dat"
outfile = open(output, 'w')
outfile.write("#%s " % (lines[0]))
for line in lines[1:]:
outfile.write("%s " % (line))
outfile.close()
def mratiopg():
ppgplot.pgbeg("maccratio.ps/vcps",1,1) #color port.
ppgplot.pgpap(8.,1.)
ppgplot.pgpage
ppgplot.pgsch(1.3) #font size
ppgplot.pgslw(7) #line width
# 1st panel with symbols w/ stddev errorbars
#ylabel="SFR (M\d\(2281) \u yr\u-1\d)"
ylabel="L(H\ga) (10\u41\d erg s\u-1\d)"
xlabel="M\dr\u "
x1=.15
x2=.5
x3=.5
x4=.85
y1=x1
y2=x2
y3=x3
y4=x4
emarker=18
smarker=23
xmin=N.log10(1.e14)
xmax=N.log10(2.5e15)
#ymin=-1.
#ymax=3.
ymin=0.
ymax=25.
ppgplot.pgsvp(x1,x4,y1,y4) #sets viewport
ppgplot.pgswin(xmin,xmax,ymin,ymax) #axes limits
ppgplot.pgbox('blncst',1.,2,'bcvnst',2.,2) #tickmarks and labeling
for i in range(len(lz1lm.mass)):
m=lz1lm.mass[i]
l=lz1lm.maccret[i]
h=hz1lm.maccret[i]
r=h/l
print i,m,l,h,r
#print lz1lm.maccret
#print hz1lm.maccret
#print hz3lm.maccret
r3lm=(hz3lm.maccret)/(lz3lm.maccret)
r3hm=(hz3hm.maccret)/(lz3hm.maccret)
#for i in range(len(r3)):
# print i,lz3.sigma[i],hz3.sigma[i],lz3.mass[i],hz3.mass[i]
# print i,lz01.sigma[i],hz01.sigma[i],lz01.mass[i],hz01.mass[i]
r1lm=hz1lm.maccret/lz1lm.maccret
r1hm=hz1hm.maccret/lz1hm.maccret
#ra=N.array(hz01.maccret,'d')
#rb=N.array(lz01.maccret,'d')
#r01=ra/rb
#for i in range(len(r01)):
#print "ratio ",hz01.maccret[i],lz01.maccret[i],ra[i],rb[i],r01[i]
ppgplot.pgsci(14)
ppgplot.pgsls(1)
ppgplot.pgline(N.log10(lz3lm.mass),r3lm)
ppgplot.pgsls(2)
ppgplot.pgline(N.log10(lz3hm.mass),r3hm)
ppgplot.pgsci(1)
ppgplot.pgsls(1)
ppgplot.pgline(N.log10(lz1lm.mass),r1lm)
ppgplot.pgsls(2)
ppgplot.pgline(N.log10(lz1hm.mass),r1hm)
xlabel='M\dcl\u (M\d\(2281)\u)'
ylabel='M\dacc\u(z=0.75) / M\dacc\u(z=0.07)'
ppgplot.pgsch(1.8)
ppgplot.pgslw(7)
ppgplot.pgmtxt('b',2.2,0.5,0.5,ylabel) #xlabel
ppgplot.pgmtxt('l',2.5,0.5,0.5,xlabel)
ppgplot.pgend()
def greadspecfiles(self, gphotfile, dL, kcorr, j):
self.sra = []
self.sdec = []
self.su = []
self.sg = []
self.sr = []
self.sV = []
self.so2 = []
self.sha = []
for line in open(gphotfile):
if line.find('#') > -1:
continue
if len(line) < 10: #phot files have blank line at end - skip it
continue
#print line
fields = line.split(',')
#print fields[0], fields[1]
#need to implement a mag cut
g = float(fields[3])
r = float(fields[4])
if (g > 18.0):
continue
if (r > 17.7):
continue
g01 = g + 0.3134 + 0.4608 * ((g - r) * -0.6148)
g01 = g01 + .01 #convert to vega
r01 = g - 0.4118 - .8597 * ((g - r) * -0.6148)
r01 = r01 - .04 #convert to vega
V = g01 - 0.6689 - 0.9264 * ((g01 - r01) - 0.7252)
g = g - (-0.08) #convert to vega
r = r - (.16) #convert to vega
#g=g-float(fields[10])#correct for extinction
#r=r-float(fields[11])#correct for extinction
V = g - 0.3556 - 0.7614 * ((g - r) - 0.6148)
#mv=V - (5.*N.log10(dL)+25.+kcorr)
mv = V - (5. * N.log10(dL) + 25.)
if ((mv) < mabscut):
self.sra.append(float(fields[0]))
self.sdec.append(float(fields[1]))
self.su.append(float(fields[2]))
self.sg.append(float(fields[3]))
self.sr.append(float(fields[4]))
self.sV.append(float(mv))
self.so2.append(float(fields[14])) #14-o2, 16 - Halpha
self.sha.append(float(fields[16])) #14-o2, 16 - Halpha
self.sra = N.array(self.sra, 'f')
self.sdec = N.array(self.sdec, 'f')
self.su = N.array(self.su, 'f')
self.sg = N.array(self.sg, 'f')
self.sr = N.array(self.sr, 'f')
self.sV = N.array(self.sV, 'f')
self.so2 = N.array(self.so2, 'f')
self.sha = N.array(self.sha, 'f')
self.sdistBCGR200 = N.sqrt((c.ra[j] - self.sra)**2 +
(c.dec[j] - self.sdec)**2) / c.r200deg[j]
self.smemb = N.zeros(len(self.sdistBCGR200), 'f')
self.ssf = N.zeros(len(self.sdistBCGR200), 'f')
self.stot = N.ones(len(self.sdistBCGR200), 'f')
for i in range(len(self.smemb)):
if (self.sdistBCGR200[i] < 4):
self.smemb[i] = 1.
if (self.so2[i] > 4.):
self.ssf[i] = 1.
if (self.so2[i] < -50.):
self.smemb[i] = 0.
def stellarmr(self):
pylab.cla()
x=N.compress((self.mpaflag > 0.1),self.Mabs)
y=N.compress((self.mpaflag > 0.1),self.stellarmass)
print "len x,y,Mabs = ",len(x),len(y),len(self.Mabs)
#x=[]
#y=[]
#for i in range(len(self.Mabs)):
# if self.mpaflag[i] > 0.1:
# x.append(self.Mabs[i])
# y.append(self.stellarmass[i])
#print "len x,y,Mabs =",len(x),len(y),len(self.Mabs)
#x=N.array(x,'d')
#y=N.array(y,'d')
y=N.log10(y/1.e11)
xmin=-24.
xmax=-18.
ymin=-3.
ymax=2.
#my.contour(x,y,xmin,xmax,ymin,ymax)
#pylab.plot(x,y,'k.',markersize=.01,zorder=1)
pylab.xlabel(r'$\rm{M_r}$',fontsize=28.)
pylab.ylabel(r'$\rm{log_{10}(M_* / 10^{11} \ M_\odot)}$',fontsize=28.)
#(a,b)=fitpowerlaw(x,y)
xtrans=-21.5
b=-13.8
m=-.63
xl=N.arange(xtrans,-18.,.05)
xl=N.array(xl,'f')
yl=N.zeros(len(xl),'f')
yl=m*(xl)+b
#xl=-1.*xl
#print xl
#print yl
pylab.plot(xl,yl,'b-',lw=4,label='_nolegend_')
m2=-.47
b2=(m-m2)*xtrans+b
print "b2 = ",b2
xl=N.arange(-24.,(xtrans+.05),.05)
xl=N.array(xl,'f')
yl=N.zeros(len(xl),'f')
yl=m2*(xl)+b2
#xl=-1.*xl
#print xl
#print yl
pylab.plot(xl,yl,'c-',lw=4,label='_nolegend_')
pylab.axvline(x=-20.6,linewidth=3,ls='--',c='g')
#(xbin,ybin,ybinerr)=my.binitbinsfix(xl,(xl+0.5),x,y)
#pylab.plot(xbin,ybin,'b-',linewidth=4.)
pylab.hold()
my.contourf(x,y,xmin,xmax,ymin,ymax)
ax=pylab.gca()
#ax.set_yscale('log')
pylab.axis([-24.5,-17.5,-3.,1.2])
pylab.savefig('stellarmr.eps')
def gotoit():
nbin = 10
#c=Cluster()
#g=Galaxy()
clusterfile = "clusters.spec.dat"
print "reading in cluster file to get cluster parameters"
c.creadfiles(clusterfile)
print "got ", len(c.z), " clusters"
c.convarray()
c.Kcorr()
go2 = [] #combined arrays containing all galaxies
gsf = [] #combined arrays containing all galaxies
gsig5 = []
gsig10 = []
gsig52r200 = [] #spec catalogs extended out to 2xR200
gsig102r200 = [] #spec catalogs extended out to 2xR200
gsig5phot = []
gsig10phot = []
sgo2 = [] #combined arrays containing all galaxies
sgha = [] #combined arrays containing all galaxies
sgsf = [] #combined arrays containing all galaxies
sgsig5 = []
sgsig10 = []
sgsig52r200 = [] #spec catalogs extended out to 2xR200
sgsig102r200 = [] #spec catalogs extended out to 2xR200
sgsig5phot = []
sgsig10phot = []
if (mode < 1):
c.getsdssphotcats()
c.getsdssspeccats()
gr = [] #list of median g-r colors
psplotinit('summary.ps')
x1 = .1
x2 = .45
x3 = .6
x4 = .95
y1 = .15
y2 = .45
y3 = .55
y4 = .85
ppgplot.pgsch(1.2) #font size
ppgplot.pgslw(2)
#for i in range(len(c.z)):
cl = [10]
(xl, xu, yl, yu) = ppgplot.pgqvp(0)
print "viewport = ", xl, xu, yl, yu
complall = []
for i in range(len(c.z)):
#for i in cl:
gname = "g" + str(i)
gname = Galaxy()
gspecfile = "abell" + str(c.id[i]) + ".spec.dat"
gname.greadfiles(gspecfile, i)
print "number of members = ", len(gname.z)
if len(gname.z) < 10:
print "less than 10 members", len(gname.z)
continue
gname.convarray()
#gname.cullmembers()
#gname.getmemb()#get members w/in R200
#gr.append(N.average(gname.g-gname.r))
gspec2r200file = "abell" + str(c.id[i]) + ".spec2r200.dat"
gname.greadspecfiles(gspec2r200file, c.dL[i], c.kcorr[i], i)
print i, c.id[i], " getnearest, first call", len(gname.ra), len(
gname.sra), sum(gname.smemb)
#gname.getnearest(i)
(gname.sig52r200, gname.sig102r200) = gname.getnearestgen(
gname.ra, gname.dec, gname.sra, gname.sdec, i
) #measure distances from ra1, dec1 to members in catalog ra2, dec2
sig52r200 = N.compress(gname.memb > 0, gname.sig52r200)
gsig52r200[len(gsig5phot):] = sig52r200
sig102r200 = N.compress(gname.memb > 0, gname.sig102r200)
gsig102r200[len(gsig10phot):] = sig102r200
gphotfile = "abell" + str(c.id[i]) + ".phot.dat"
gname.greadphotfiles(gphotfile, c.dL[i], c.kcorr[i])
gname.getnearest(i)
#print "len of local density arrays = ",len(gname.sig5),len(gname.sig5phot)
#print gspecfile, c.z[i],c.kcorr[i]
(ds5, ds10) = gname.gwritefiles(gspecfile, i)
o2 = N.compress(gname.memb > 0, gname.o2)
go2[len(go2):] = o2
sf = N.compress(gname.memb > 0, gname.sf)
gsf[len(gsf):] = sf
sig5 = N.compress(gname.memb > 0, gname.sig5)
gsig5[len(gsig5):] = sig5
sig10 = N.compress(gname.memb > 0, gname.sig10)
gsig10[len(gsig10):] = sig10
sig5phot = N.compress(gname.memb > 0, gname.sig5phot)
gsig5phot[len(gsig5phot):] = sig5phot
sig10phot = N.compress(gname.memb > 0, gname.sig10phot)
gsig10phot[len(gsig10phot):] = sig10phot
ds5 = N.array(ds5, 'f')
ds10 = N.array(ds10, 'f')
#print len(ds5),len(ds10)
#ppgplot.pgsvp(xl,xu,yl,yu)
ppgplot.pgsvp(0.1, .9, .08, .92)
ppgplot.pgslw(7)
label = 'Abell ' + str(
c.id[i]) + ' (z=%5.2f, \gs=%3.0f km/s)' % (c.z[i], c.sigma[i])
ppgplot.pgtext(0., 1., label)
ppgplot.pgslw(2)
ppgplot.pgsvp(x1, x2, y1, y2) #sets viewport
#ppgplot.pgbox("",0.0,0,"",0.0)
ppgplot.pgswin(-1., 3., -1., 3.) #axes limits
ppgplot.pgbox('bcnst', 1, 2, 'bcvnst', 1, 2) #tickmarks and labeling
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5,
"\gS\d10\u(phot) (gal/Mpc\u2\d)") #xlabel
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, "\gS\d10\u(spec) (gal/Mpc\u2\d)")
x = N.arange(-5., 10., .1)
y = x
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
ppgplot.pgline(x, y)
x = N.log10(sig10phot)
y = N.log10(sig10)
ppgplot.pgsch(.7)
ppgplot.pgpt(x, y, 17)
xp = N.array([-0.5], 'f')
yp = N.array([2.5], 'f')
ppgplot.pgpt(xp, yp, 17)
ppgplot.pgtext((xp + .1), yp, 'spec(1.2xR200) vs phot')
ppgplot.pgsci(4)
xp = N.array([-0.5], 'f')
yp = N.array([2.2], 'f')
ppgplot.pgpt(xp, yp, 21)
ppgplot.pgtext((xp + .1), yp, 'spec(2xR200) vs phot')
y = N.log10(sig102r200)
ppgplot.pgsch(.9)
ppgplot.pgpt(x, y, 21)
ppgplot.pgsch(1.2)
ppgplot.pgslw(2) #line width
ppgplot.pgsci(1)
#ppgplot.pgenv(-200.,200.,-1.,20.,0,0)
#ppgplot.pgsci(2)
#ppgplot.pghist(len(ds5),ds5,-200.,200.,30,1)
#ppgplot.pgsci(4)
#ppgplot.pghist(len(ds10),ds10,-200.,200.,30,1)
#ppgplot.pgsci(1)
#ppgplot.pglab("\gD\gS","Ngal",gspecfile)
#ppgplot.pgpanl(1,2)
g = N.compress(gname.memb > 0, gname.g)
r = N.compress(gname.memb > 0, gname.r)
V = N.compress(gname.memb > 0, gname.V)
dmag = N.compress(gname.memb > 0, gname.dmagnearest)
dnearest = N.compress(gname.memb > 0, gname.nearest)
dz = N.compress(gname.memb > 0, gname.dz)
#ppgplot.pgsvp(x3,x4,y1,y2) #sets viewport
#ppgplot.pgenv(-.5,3.,-1.,5.,0,0)
#ppgplot.pgpt((g-V),(g-r),17)
#ppgplot.pgsci(1)
#ppgplot.pglab("g - M\dV\u",'g-r',gspecfile)
ppgplot.pgsvp(x1, x2, y3, y4) #sets viewport
#ppgplot.pgbox("",0.0,0,"",0.0)
ppgplot.pgswin(
(c.ra[i] + 2. * c.r200deg[i] / N.cos(c.dec[i] * N.pi / 180.)),
(c.ra[i] - 2 * c.r200deg[i] / N.cos(c.dec[i] * N.pi / 180.)),
(c.dec[i] - 2. * c.r200deg[i]), (c.dec[i] + 2. * c.r200deg[i]))
ppgplot.pgbox('bcnst', 0.0, 0.0, 'bcvnst', 0.0,
0.0) #tickmarks and labeling
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "RA") #xlabel
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, "Dec")
#ppgplot.pglab("RA",'Dec',gspecfile)
ppgplot.pgsfs(2)
ppgplot.pgcirc(c.ra[i], c.dec[i], c.r200deg[i])
ppgplot.pgsls(4)
ppgplot.pgcirc(c.ra[i], c.dec[i], 1.2 * c.r200deg[i])
ppgplot.pgsls(1)
#ppgplot.pgcirc(c.ra[i],c.dec[i],c.r200deg[i]/N.cos(c.dec[i]*N.pi/180.))
ppgplot.pgsci(2)
ppgplot.pgpt(gname.ra, gname.dec, 17)
ppgplot.pgsci(4)
ppgplot.pgpt(gname.photra, gname.photdec, 21)
ppgplot.pgsci(1)
#calculate completeness w/in R200
dspec = N.sqrt((gname.ra - c.ra[i])**2 + (gname.dec - c.dec[i])**2)
dphot = N.sqrt((gname.photra - c.ra[i])**2 +
(gname.photdec - c.dec[i])**2)
nphot = 1. * len(N.compress(dphot < c.r200deg[i], dphot))
nspec = 1. * len(N.compress(dspec < c.r200deg[i], dspec))
s = "Completeness for cluster Abell %s = %6.2f (nspec=%6.1f,nphot= %6.1f)" % (
str(c.id[i]), float(nspec / nphot), nspec, nphot)
print s
complall.append(float(nspec / nphot))
ppgplot.pgsvp(x3, x4, y3, y4) #sets viewport
#ppgplot.pgsvp(x1,x2,y3,y4) #sets viewport
#ppgplot.pgbox("",0.0,0,"",0.0)
ppgplot.pgswin(-0.005, .05, -1., 1.)
ppgplot.pgbox('bcnst', .02, 2, 'bcvnst', 1, 4) #tickmarks and labeling
ppgplot.pgsch(1.0)
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5,
"Dist to nearest phot neighbor (deg)") #xlabel
ppgplot.pgsch(1.2)
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, 'M\dV\u(phot) - M\dV\u(spec)')
ppgplot.pgsci(2)
ppgplot.pgpt(dnearest, dmag, 17)
ppgplot.pgsci(1)
x = N.arange(-30., 30., 1.)
y = 0 * x
ppgplot.pgsci(1)
ppgplot.pgsls(2)
ppgplot.pgline(x, y)
ppgplot.pgsls(1)
ppgplot.pgsci(1)
dm = N.compress(dnearest < 0.01, dmag)
std = '%5.3f (%5.3f)' % (pylab.mean(dm), pylab.std(dm))
#ppgplot.pgslw(7)
#label='Abell '+str(c.id[i])
#ppgplot.pgtext(0.,1.,label)
ppgplot.pgslw(2)
label = '\gDM\dV\u(err) = ' + std
ppgplot.pgsch(.9)
ppgplot.pgtext(0., .8, label)
#label = "z = %5.2f"%(c.z[i])
#ppgplot.pgtext(0.,.8,label)
ppgplot.pgsch(1.2)
#ppgplot.pgsvp(x3,x4,y3,y4) #sets viewport
#ppgplot.pgenv(-.15,.15,-3.,3.,0,0)
#ppgplot.pgsci(2)
#ppgplot.pgpt(dz,dmag,17)
#ppgplot.pgsci(1)
#ppgplot.pglab("z-z\dcl\u",'\gD Mag',gspecfile)
ppgplot.pgsvp(x3, x4, y1, y2) #sets viewport
ppgplot.pgswin(-3., 3., -1., 1.)
ppgplot.pgbox('bcnst', 1, 2, 'bcvnst', 1, 4) #tickmarks and labeling
ppgplot.pgmtxt('b', 2.5, 0.5, 0.5, "\gDv/\gs") #xlabel
ppgplot.pgmtxt('l', 2.6, 0.5, 0.5, 'M\dV\u(phot) - M\dV\u(spec)')
ppgplot.pgsci(2)
dv = dz / (1 + c.z[i]) * 3.e5 / c.sigma[i]
ppgplot.pgpt(dv, dmag, 17)
ppgplot.pgsci(1)
x = N.arange(-30., 30., 1.)
y = 0 * x
ppgplot.pgsci(1)
ppgplot.pgsls(2)
ppgplot.pgline(x, y)
ppgplot.pgsls(1)
ppgplot.pgsci(1)
#ppgplot.pgsvp(x1,x2,y1,y2) #sets viewport
#ppgplot.pgenv(0.,3.5,-3.,3.,0,0)
#ppgplot.pgsci(4)
#ppgplot.pgpt((g-r),dmag,17)
#ppgplot.pgsci(1)
#ppgplot.pglab("g-r",'\gD Mag',gspecfile)
#ppgplot.pgsvp(x1,x2,y1,y2) #sets viewport
#ppgplot.pgenv(-25.,-18.,-1.,1.,0,0)
#ppgplot.pgsci(4)
#ppgplot.pgpt((V),dmag,17)
#x=N.arange(-30.,30.,1.)
#y=0*x
#ppgplot.pgsci(1)
#ppgplot.pgsls(2)
#ppgplot.pgline(x,y)
#ppgplot.pgsls(1)
#ppgplot.pgsci(1)
#ppgplot.pglab("M\dV\u(spec)",'M\dV\u(phot) - M\dV\u(spec)',gspecfile)
#ppgplot.pgpage()
#ppgplot.pgpage()
#combine galaxy data
ppgplot.pgpage()
(sssig5,
sssig10) = gname.getnearestgen(gname.sra, gname.sdec, gname.sra,
gname.sdec,
i) #get spec-spec local density
(spsig5,
spsig10) = gname.getnearestgen(gname.sra, gname.sdec, gname.photra,
gname.photdec,
i) #get spec-phot local density
o2 = N.compress(gname.smemb > 0, gname.so2)
sgo2[len(sgo2):] = o2
ha = N.compress(gname.smemb > 0, gname.sha)
sgha[len(sgha):] = ha
sf = N.compress(gname.smemb > 0, gname.ssf)
sgsf[len(sgsf):] = sf
sig5 = N.compress(gname.smemb > 0, sssig5)
sgsig5[len(sgsig5):] = sig5
sig10 = N.compress(gname.smemb > 0, sssig10)
sgsig10[len(sgsig10):] = sig10
sig5phot = N.compress(gname.smemb > 0, spsig5)
sgsig5phot[len(sgsig5phot):] = sig5phot
sig10phot = N.compress(gname.smemb > 0, spsig10)
sgsig10phot[len(sgsig10phot):] = sig10phot
#gr=N.array(gr,'f')
#c.assigncolor(gr)
#for i in range(len(c.z)):
# print c.id[i],c.z[i],c.r200[i],c.r200deg[i]
print "Average Completeness w/in R200 = ", N.average(N.array(
complall, 'f'))
print "sig o2", len(gsig10), len(gsig10phot), len(go2)
print "sig o2 large", len(sgsig10), len(sgsig10phot), len(sgo2)
plotsigo2all(gsig10, gsig10phot, go2, 'o2vsig10spec', nbin)
#plotsigo2(gsig5phot,-1*go2,'o2vsig5phot',nbin)
plotsigsff(gsig5, gsf, 'sffvsig5spec', nbin) #sf frac versus sigma
plotsigsff(gsig5phot, gsf, 'sffvsig5phot', nbin) #sf frac versus sigma
plotsigsffall(gsig5, gsig5phot, gsf, 'sffvsig5all',
nbin) #sf frac versus sigma
plotsig10sffall(gsig10, gsig10phot, gsf, 'sffvsig10all',
nbin) #sf frac versus sigma
#plotsighaall(gsig10,gsig10phot,gha,'havsig10spec',20)
#plotsigo2all(sgsig10,sgsig10phot,sgo2,'o2vsig10spec.large',30)
plotsighaall(sgsig10, sgsig10phot, sgha, 'havsig10spec.large', 10)
#plotsigsffall(sgsig5,sgsig5phot,sgsf,'sffvsig5.large',nbin)#sf frac versus sigma
#plotsig10sffall(sgsig10,sgsig10phot,sgsf,'sffvsig10.large',nbin)#sf frac versus sigma
psplotinit('one2one.ps')
ppgplot.pgenv(-1.5, 2.5, -1.5, 2.5, 0)
ppgplot.pglab("\gS\d10\u(phot) (gal/Mpc\u2\d)",
"\gS\d10\u(spec) (gal/Mpc\u2\d)", "")
x = N.arange(-5., 10., .1)
y = x
ppgplot.pgsls(1) #dotted
ppgplot.pgslw(4) #line width
ppgplot.pgline(x, y)
x = N.log10(gsig10phot)
y = N.log10(gsig10)
ppgplot.pgsch(.7)
ppgplot.pgpt(x, y, 17)
ppgplot.pgsch(1.)
ppgplot.pgsci(1)
ppgplot.pgend()
