def smoothed_lightcone_dbt(id="", ht=""):
infile = open(setup_dirs.resultsdir() + "dbt_lightcone" + ht + ".bin", "rb")
outfile = setup_dirs.resultsdir() + "dbt_lightcone_smooth" + ht + ".bin"
zfile = open(setup_dirs.resultsdir() + "dbt_lightcone_redshifts.bin", "rb")
dT_box = np.load(infile)
log = open("stats.dat", "w")
zs = np.load(zfile)
dT_box3 = np.zeros((len(dT_box[:, 1, 1]) / 2, len(dT_box[1, :, 1]) / 2, len(dT_box[1, 1, :])))
dT_box2 = np.zeros((len(dT_box[:, 1, 1]) / 2, len(dT_box[1, :, 1]) / 2, len(dT_box[1, 1, :])))
for z in range(len(dT_box[1, 1, :]) - 1, -1, -1):
wl = 0.21 * (1 + zs[z])
c = 299792.458
omm = 0.27
oml = 0.73
omr = 0.0
omk = 1.0 - omm - oml - omr
H0 = 70.0
def integrand(x, omm, oml, omr, omk):
return 1.0 / np.sqrt(omr * ((1 + x) ** 4) + omm * ((1 + x) ** 3) + oml + omk * ((1 + x) ** 2))
def dc(z, omm, oml, omr, omk):
return quad(integrand, 0, z, args=(omm, oml, omr, omk))[0] # /(1.0+z)
vec_dc = np.vectorize(dc)
bw_r = wl / (2.0e3) # radians
bw = bw_r * 3437.74677 # arcminutesi
log.write("Wavelength of 21-cm from redshift " + str(zs[z]) + " is " + str(wl) + "m\n")
log.write("At redshift: " + str(zs[z]) + " smoothing with a " + str(bw) + " arc minute beam.\n")
rc = bw_r * c / H0 * vec_dc(zs[z], omm, oml, omr, omk) # comoving Mpc
Hz = H0 * np.sqrt(omr * (1 + zs[z]) ** 4 + omm * (1 + zs[z]) ** 3 + oml + omk * (1 + zs[z]) ** 2)
log.write("rc = " + str(rc) + "\n")
# dnu=nu0*Hz*rc/(c*(1+zs[z])**2)
dz = rc * Hz / c
log.write("$\Delta$ z = " + str(dz) + "\n")
ncs = rc * 250.0 * 0.7 / 244.0
log.write(str(ncs) + " cells in the z direction\n")
log.write("\n")
# rc_h=rc/0.7 # comoving Mpc/h
# print "This corresponds to "+str(rc_h)+"Mpc/h on the sky"
dT_box2[:, :, z] = c2t.beam_convolve(dT_box[:, :, z], zs[z], 244.0, beam_w=bw)
if z > ncs and z + ncs < zs[len(zs) - 1]:
for x in range(len(dT_box2)):
for y in range(len(dT_box2)):
dT_box3[x, y, z] = np.mean(dT_box2[x, y, z - ncs / 2.0 : z + ncs / 2.0])
else:
print "..."
dT_box3[:, :, z] = dT_box2[:, :, z]
IO.writebin(dT_box3[:, :, z], setup_dirs.resultsdir() + "smoothed_map_dbt_" + ht + str("%.3f" % zs[z]) + ".bin")
IO.writebin(dT_box3, outfile)
print "Written map to " + outfile
def min_temp():
file = open(setup_dirs.resultsdir()+'min_temp.dat', 'w')
for i in range(len(redshifts)):
filename = setup_dirs.path()+'Temper3D_'+str('%.3f' % redshifts[i]) + '.bin'
data = c2t.TemperFile(filename)
file.write(str(np.amin(data.temper)) + '\n')
file.close()
print "Written mean Temperature to "+setup_dirs.resultsdir()+'min_temp.dat'
def mean_xfrac(id):
file = open(setup_dirs.resultsdir()+'mean_xfrac'+id+'.dat', 'w')
for i in range(len(redshifts)):
xfrac_filename = setup_dirs.path()+'xfrac3d'+id+'_'+str('%.3f' % redshifts[i]) + '.bin'
xfile = c2t.XfracFile(xfrac_filename)
file.write(str(np.mean(xfile.xi)) + '\n')
file.close()
print "Written mean xfrac to "+setup_dirs.resultsdir()+'mean_xfrac'+id+'.dat'
def smooth_kurtosis(id=''):
file = open(setup_dirs.resultsdir()+'smooth_kurtosis'+id+'.dat','w')
for i in range(len(redshifts)):
print "Doing redshift: " + str(redshifts[i])
data=np.load(setup_dirs.resultsdir()+"smoothed_map_dbt_"+id+str('%.3f' % redshifts[i])+".bin")
data=data.flatten()
kurtosis=scipy.stats.kurtosis(data)
# kurtosis=c2t.statistics.kurtosis(data)
file.write(str(kurtosis)+'\n')
print "Written kurtosis to " + setup_dirs.resultsdir()+"smooth_kurtosis"+id+".dat"
def dbt_lightcone(ht=""):
filenames = ["" for x in range(len(redshifts))]
for i in range(0, len(redshifts)):
filenames[i] = setup_dirs.resultsdir() + "dbt" + ht + "/map_dbt_" + ht + str("%.3f" % redshifts[i]) + ".bin"
output = setup_dirs.resultsdir() + "dbt_lightcone" + ht + ".bin"
output2 = setup_dirs.resultsdir() + "dbt_lightcone_redshifts.bin"
lightcone, z = c2t.make_lightcone(filenames, redshifts[len(redshifts) - 1], redshifts[0], interpolation="linear")
lightcone2 = np.asarray(lightcone)
z2 = np.asarray(z)
IO.writebin(lightcone2, output)
IO.writebin(z2, output2)
print "written lightcone to " + output
def lightcone_stats(s='',ht=''):
infile = setup_dirs.resultsdir()+'dbt_lightcone_smooth'+ht+'.bin'
zfile = open(setup_dirs.resultsdir()+'dbt_lightcone_redshifts.bin','rb')
meanfile = open(setup_dirs.resultsdir()+s+'_'+'mean'+'_'+ht+'lightcone.dat','w')
skewnessfile = open(setup_dirs.resultsdir()+s+'_'+'skewness'+'_'+ht+'lightcone.dat','w')
kurtosisfile = open(setup_dirs.resultsdir()+s+'_'+'kurtosis'+'_'+ht+'lightcone.dat','w')
rmsfile = open(setup_dirs.resultsdir()+s+'_'+'rms'+'_'+ht+'lightcone.dat','w')
redshiftfile = open(setup_dirs.resultsdir()+s+'_'+'zs'+'_'+ht+'.dat','w')
lc = np.load(infile)
zs = np.load(zfile)
ratio=4. #smoothing ratio
Lbox=244./0.7 #boxsize in cMpc
SLbox=Lbox/ratio #size of smoothing box
Nbox=250 #number of cells
SNbox=int(Nbox/ratio)+1 #new number of cells
print Lbox, SLbox, Nbox, SNbox
for i in range(len(zs)-SNbox/2-2,SNbox/2,-1):
mapfile=setup_dirs.resultsdir()+s+'_map_'+ht+str('%.3f'%zs[i])+'.bin'
print "Doing redshift: " + str(zs[i])
data,dims = c2t.get_lightcone_subvolume(lc,zs,zs[i],depth_mpc=SLbox,subtract_mean=False)
IO.writebin(data,mapfile)
redshiftfile.write(str(zs[i])+'\n')
meanfile.write(str(np.mean(data))+'\n')
rmsfile.write(str(np.sqrt(np.var(data)))+'\n')
skewnessfile.write(str(c2t.statistics.skewness(data.flatten()))+'\n')
kurtosisfile.write(str(c2t.statistics.kurtosis(data.flatten()))+'\n')
print "Written statistics"
def rms(s='',ht=''):
file = open(setup_dirs.resultsdir()+s+'_'+'rms'+'_'+ht+'coeval.dat','w')
rds=redshifts
for i in range(len(rds)):
print "Doing redshift: " + str(rds[i])
if s=='':
print "opening "+setup_dirs.resultsdir()+"map_dbt_"+ht+str('%.3f' % rds[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"map_dbt_"+ht+str('%.3f' % rds[i])+".bin")
else:
if ht!='':
print "opening "+setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % rds[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % rds[i])+".bin")
else:
print "opening "+setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % rds[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % rds[i])+".bin")
mean=np.mean(data)
print "mean dbt: " + str(mean)
length=len(data.flatten())
rmsdata=0.0
print "summing..."
rmsdata=np.sum((data-mean)**2)
rmsdata=np.sqrt(rmsdata/length)
print rmsdata, np.sqrt(np.var(data))
#rmsdata=(rmsdata/length**3)
file.write(str(rmsdata)+'\n')
print(str(rmsdata)+'\n')
print "Written rms to " + setup_dirs.resultsdir()+s+" rms"+ht+"coveal.dat"
def rms():
rmsdata=np.zeros(len(redshifts))
for i in range(len(redshifts)):
print "opening ../generate_data/"+setup_dirs.resultsdir()+"map_dbt_"+str('%.3f' % redshifts[i])+".bin"
data=np.load("../generate_data/"+setup_dirs.resultsdir()+"map_dbt_"+str('%.3f' % redshifts[i])+".bin")
mean=np.mean(data)
length=len(data)
sum=0.0
print "summing..."
for x in range(length):
for y in range(length):
for z in range(length):
rmsdata[i]=rmsdata[i]+(data[x,y,z]-mean)**2
rmsdata[i]=np.sqrt(rmsdata[i]/length**3)
plot_mean(rmsdata,"rms_500b","rms (mK)")
def map_dbt_lightcone():
for i in range(0, len(redshifts)):
# print 'filename: setup_dirs.resultsdir()+'map_dbt_lightcone_'+str('%.3f' % redshifts[i])+'.dat'
filename = setup_dirs.resultsdir() + "map_dbt_lightcone_" + str("%.3f" % redshifts[i]) + ".dat"
temp_filename = setup_dirs.path() + "Temper3D_" + str("%.3f" % redshifts[i]) + ".bin"
xfrac_filename = setup_dirs.path() + "xfrac3d_" + str("%.3f" % redshifts[i]) + ".bin"
if i % 2 == 0:
density_filename = (
"/research/prace/244Mpc_RT/244Mpc_f2_8.2pS_250/coarser_densities/"
+ str("%.3f" % redshifts[i])
+ "n_all.dat"
)
else:
density_filename = (
"/research/prace/244Mpc_RT/244Mpc_f2_8.2pS_250/coarser_densities/"
+ str("%.3f" % redshifts[i - 1])
+ "n_all.dat"
)
tfile = c2t.TemperFile(temp_filename)
xfile = c2t.XfracFile(xfrac_filename).xi
if ss == " ":
dfile = c2t.DensityFile(density_filename).cgs_density
else:
dfile = np.ones(ss ** 3).reshape(ss, ss, ss) * 1.981e-10 * (1 + redshifts[i]) ** 3
dT_box = c2t.calc_dt_full_lightcone(xfile, tfile, dfile, redshifts[i])
IO.writemap(dT_box, filename)
print "Written map to " + filename
def map_temp():
for i in range(start, len(redshifts)):
filename = setup_dirs.resultsdir() + "map_temper_" + str("%.3f" % redshifts[i]) + ".dat"
temp_filename = setup_dirs.path() + "Temper3D_" + str("%.3f" % redshifts[i]) + ".bin"
tfile = c2t.TemperFile(temp_filename)
IO.writemap(tfile.temper, filename)
print "Writen map to " + filename
def readoned(name):
file = open('../generate_data/'+setup_dirs.resultsdir()+name+'.dat','r')
cnt=0
for line in file:
cnt = cnt+1
data=np.zeros(cnt)
file.close()
file = open('../generate_data/'+setup_dirs.resultsdir()+name+'.dat','r')
c=-1
for line in file:
if (c!=-1):
data[c] = float(line)
c=c+1
file.close()
print 'read data from ../generate_data/'+setup_dirs.resultsdir()+name+'.dat'
return data
def smoothed_lightcone_dbt2(id="", ht=""):
print "hello"
infile = open(setup_dirs.resultsdir() + "dbt_lightcone" + ht + ".bin", "rb")
outfile = setup_dirs.resultsdir() + "dbt_lightcone_smooth" + ht + ".bin"
zfile = open(setup_dirs.resultsdir() + "dbt_lightcone_redshifts.bin", "rb")
dT_box = np.load(infile)
log = open("stats.dat", "w")
zs = np.load(zfile)
dT_box3 = np.zeros((len(dT_box[:, 1, 1]) / 2, len(dT_box[1, :, 1]) / 2, len(dT_box[1, 1, :])))
dT_box2 = np.zeros((len(dT_box[:, 1, 1]) / 2, len(dT_box[1, :, 1]) / 2, len(dT_box[1, 1, :])))
for z in range(len(dT_box[1, 1, :])):
wl = 0.21 * (1 + zs[z])
c = 299792.458
omm = 0.27
oml = 0.73
omr = 0.0
omk = 1.0 - omm - oml - omr
H0 = 70.0
print 1
def integrand(x, omm, oml, omr, omk):
return 1.0 / np.sqrt(omr * ((1 + x) ** 4) + omm * ((1 + x) ** 3) + oml + omk * ((1 + x) ** 2))
def dc(z, omm, oml, omr, omk):
return quad(integrand, 0, z, args=(omm, oml, omr, omk))[0] # /(1.0+z)
vec_dc = np.vectorize(dc)
print 2
bw_r = wl / (2.0e3) # radians
bw = bw_r * 3437.74677 # arcminutesi
stats.write("Wavelength of 21-cm from redshift " + str(zs[z]) + " is " + str(wl) + "m")
stats.write("At redshift: " + str(zs[z]) + " smoothing with a " + str(bw_r) + " radian beam")
stats.write("At redshift: " + str(zs[z]) + " smoothing with a " + str(bw) + " arc minute beam")
stats.write("\n")
print 3
dT_box2[:, :, z] = c2t.beam_convolve(dT_box[:, :, z], zs[z], 244.0, beam_w=bw)
print 4
dT_box3 = lightcone_smooth.frequency_direction_same(dT_box2, zs[0], 244.0, 2)
print 5
IO.writebin(dT_box3[:, :, z], setup_dirs.resultsdir() + "smoothed_map_dbt_" + ht + str("%.3f" % zs[z]) + ".bin")
IO.writebin(dT_box3, outfile)
print "Written map to " + outfile
def readmap(name,resultdir=setup_dirs.resultsdir()):
map = np.zeros(mesh**3).reshape(mesh,mesh,mesh)
#if
file = open('../generate_data/'+resultdir+'map_'+name+'.dat', 'r')
c=0
for line in file:
x = int((c)/(mesh**2))
y = int(c/mesh)%(mesh)
# y = int(c%(mesh/2.0))
z = c%mesh
map[x,y,z] = float(line)
c=c+1
#if (True):
# print x+1,y+1,z+1
#print map
print 'Read map from ../generate_data/'+setup_dirs.resultsdir()+'map_'+name+'.dat'
return map
def mean_dbt(id='',ht=''):
rds=redshifts
if id=='smooth_':
rds=lc_zs
file=open(setup_dirs.resultsdir()+id+'mean_dbt'+ht+'.dat', 'w')
for i in range(len(rds)):
if id=='':
filename = setup_dirs.resultsdir()+'map_dbt_'+ht+str('%.3f' % rds[i]) + '.bin'
else:
if ht!='':
filename = setup_dirs.resultsdir()+'smoothed_map_dbt'+ht+str('%.3f' % rds[i]) + '.bin'
else:
filename = setup_dirs.resultsdir()+'smoothed_map_dbt'+ht+'_'+str('%.3f' % rds[i]) + '.bin'
data = np.load(filename)
file.write(str(np.mean(data)) + '\n')
print np.mean(data)
file.close()
print "Written mean Temperature to "+setup_dirs.resultsdir()+id+'mean_dbt'+ht+'.dat'
def map_xfrac(id):
# for i in range(len(redshifts)-6,len(redshifts)-4):
print len(redshifts)
for i in range(start, len(redshifts)):
filename = setup_dirs.resultsdir() + "map_xfrac" + id + "_" + str("%.3f" % redshifts[i]) + ".dat"
xfrac_filename = setup_dirs.path() + "xfrac3d" + id + "_" + str("%.3f" % redshifts[i]) + ".bin"
xfile = c2t.XfracFile(xfrac_filename)
IO.writemap(xfile.xi, filename)
print "Written map to " + filename
def map(name):
map = np.zeros(mesh**3).reshape(mesh,mesh,mesh)
file = open('../generate_data/'+setup_dirs.resultsdir()+'/map_'+name+'.dat', 'r')
c=0
for line in file:
x = int((c)/(mesh**2))
y = int(c%(mesh)/2.0)
z = c%3
map[x,y,z] = float(line)
c=c+1
return map
def mean_dbt_hightemp():
file = open(setup_dirs.resultsdir()+'mean_dbt_hightemp.dat','w')
for i in range(len(redshifts)):
filename = setup_dirs.resultsdir()+'map_dbt_hightemp'+str('%.3f' % redshifts[i])+'.dat'
temp_filename = setup_dirs.path()+'Temper3D_'+str('%.3f' % redshifts[i]) + '.bin'
xfrac_filename = setup_dirs.path() +'xfrac3d_'+str('%.3f' % redshifts[i]) + '.bin'
if i%2==0:
density_filename='/research/prace/244Mpc_RT/244Mpc_f2_8.2pS_250/coarser_densities/' + str('%.3f' % redshifts[i]) + 'n_all.dat'
else:
density_filename='/research/prace/244Mpc_RT/244Mpc_f2_8.2pS_250/coarser_densities/' + str('%.3f' % redshifts[i-1]) + 'n_all.dat'
tfile = c2t.TemperFile(temp_filename)
xfile = c2t.XfracFile(xfrac_filename).xi
if ss!=' ':
dfile = np.ones(ss**3).reshape(ss,ss,ss)*1.981e-10*(1+redshifts[i])**3
else:
dfile = c2t.DensityFile(density_filename).cgs_density
dT_box = c2t.calc_dt(xfile, dfile, redshifts[i]) #returned in micro kelvin! update plots
file.write(str(np.mean(dT_box))+'\n')
print "Written mean dbt to " + setup_dirs.resultsdir()+'mean_dbt_hightemp.dat'
def plotdbt():
mini = -457
maxi=83
print mini,maxi
for i in range(start,len(redshifts)):
print "Doing redshift " + str(redshifts[i])+"..."
dbt = np.load("../generate_data/"+setup_dirs.resultsdir()+"map_dbt_"+str('%.3f' % redshifts[i])+".bin")
#IO.readmap("dbt_"+str('%.3f' % redshifts[i]))
print np.min(dbt)
plot(dbt[len(dbt[:,0,0])/2,:,:],i,"$\delta T_b$","dbt",mini,maxi,'seismic')
print "Complete"
def mean_temp_igm():
file = open(setup_dirs.resultsdir()+'mean_temp_igm.dat', 'w')
file2= open(setup_dirs.resultsdir()+'fraction_ionised.dat','w')
for i in range(len(redshifts)):
filename = setup_dirs.path()+'Temper3D_'+str('%.3f' % redshifts[i]) + '.bin'
data = c2t.TemperFile(filename)
xfrac_filename = setup_dirs.path()+'xfrac3d_'+str('%.3f' % redshifts[i]) + '.bin'
xfile = c2t.XfracFile(xfrac_filename)
igm_data=[]
ionisedpoints=0
for i in range(len(data.temper[1,:,1])):
for j in range(len(data.temper[1,:,1])):
for k in range(len(data.temper[1,:,1])):
if xfile.xi[i,j,k] < 1e3:
igm_data.append(data.temper[i,j,k])
else:
ionisedpoints=ionisedpoints+1
file.write(str(np.mean(igm_data)) + '\n')
file.write(str(ionisedpoints/250**3))
file.close()
print "Written mean Temperature to "+setup_dirs.resultsdir()+'mean_temp_igm.dat'
def plot_smoothed_dbt():
mini = -457
maxi=83
# print mini,maxi
for i in range(start,len(redshifts)):
print "Doing redshift " + str(redshifts[i])+"..."
dbt = np.load("../generate_data/"+setup_dirs.resultsdir()+"map_dbt_"+str('%.3f' % redshifts[i])+".bin")
dbt = c2t.beam_convolve(dbt[len(dbt[:,0,0])/2,:,:],redshifts[i],244.,beam_w=3.)
#IO.readmap("dbt_"+str('%.3f' % redshifts[i]))
# print np.min(dbt)
plot(dbt,i,"$\delta T_b$","smoothed_dbt",mini,maxi,'seismic')
print "Complete"
def coeval_stats(s='smooth',ht=''):
skewnessfile = open(setup_dirs.resultsdir()+s+'_'+'skewness'+'_'+ht+'coeval.dat','w')
kurtosisfile = open(setup_dirs.resultsdir()+s+'_'+'kurtosis'+'_'+ht+'coeval.dat','w')
rmsfile = open(setup_dirs.resultsdir()+s+'_'+'rms'+'_'+ht+'coeval.dat','w')
for i in range(len(redshifts)):
infile = setup_dirs.resultsdir()+'smooth_coevalmap_dbt_'+ht+str('%.3f'%redshifts[i]+'.bin')
data = np.load(infile)
print "Doing redshift: " + str(redshifts[i])
rmsfile.write(str(np.sqrt(np.var(data)))+'\n')
skewnessfile.write(str(c2t.statistics.skewness(data.flatten()))+'\n')
kurtosisfile.write(str(c2t.statistics.kurtosis(data.flatten()))+'\n')
print 'written to ' + setup_dirs.resultsdir()+s+'_'+'rms'+'_'+ht+'coeval.dat'
print 'written to ' + setup_dirs.resultsdir()+s+'_'+'skewness'+'_'+ht+'coeval.dat'
print 'written to ' + setup_dirs.resultsdir()+s+'_'+'kurtosis'+'_'+ht+'coeval.dat'
def kurtosis(s='',ht=''):
file = open(setup_dirs.resultsdir()+s+'_kurtosis_'+ht+'_coeval.dat','w')
rds=redshifts
for i in range(len(rds)):
print "Doing redshift: " + str(rds[i])
if s=='':
print "opening "+setup_dirs.resultsdir()+"map_dbt_"+ht+str('%.3f' % rds[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"map_dbt_"+ht+str('%.3f' % rds[i])+".bin")
else:
if ht!='':
print "opening "+setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % rds[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % rds[i])+".bin")
else:
print "opening "+setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % rds[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % rds[i])+".bin")
data=data.flatten()
# kurtosis=scipy.stats.kurtosis(data)
kurtosis=c2t.statistics.kurtosis(data)
file.write(str(kurtosis)+'\n')
print "Written kurtosis to " + setup_dirs.resultsdir()+s+"kurtosis"+ht+"coeval.dat"
def skewness(s='',ht=''):
file = open(setup_dirs.resultsdir()+s+'_skewness_'+ht+'coeval.dat','w')
for i in range(len(redshifts)):
print "Doing redshift: " + str(redshifts[i])
if s=='':
print "opening "+setup_dirs.resultsdir()+"map_dbt_"+ht+str('%.3f' % redshifts[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"map_dbt_"+ht+str('%.3f' % redshifts[i])+".bin")
else:
if ht!='':
print "opening "+setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % redshifts[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % redshifts[i])+".bin")
else:
print "opening "+setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % redshifts[i])+".bin"
data=np.load(setup_dirs.resultsdir()+"smooth_coevalmap_dbt_"+ht+str('%.3f' % redshifts[i])+".bin")
data=data.flatten()
# print scipy.stats.skew(data), c2t.statistics.skewness(data)
#skewness=scipy.stats.skew(data)
skewness=c2t.statistics.skewness(data)
file.write(str(skewness)+'\n')
print "Written skewness to " + setup_dirs.resultsdir()+s+"skewness"+ht+"coeval.dat"
def map_dbt():
for i in range(start, len(redshifts)):
filename = setup_dirs.resultsdir() + "map_dbt_" + str("%.3f" % redshifts[i]) + ".bin"
temp_filename = setup_dirs.path() + "Temper3D_" + str("%.3f" % redshifts[i]) + ".bin"
xfrac_filename = setup_dirs.path() + "xfrac3d_" + str("%.3f" % redshifts[i]) + ".bin"
if i % 2 == 0:
density_filename = (
"/research/prace/244Mpc_RT/244Mpc_f2_8.2pS_250/coarser_densities/"
+ str("%.3f" % redshifts[i])
+ "n_all.dat"
)
else:
density_filename = (
"/research/prace/244Mpc_RT/244Mpc_f2_8.2pS_250/coarser_densities/"
+ str("%.3f" % redshifts[i - 1])
+ "n_all.dat"
)
tfile = c2t.TemperFile(temp_filename)
xfile = c2t.XfracFile(xfrac_filename).xi
if ss != " ":
abu_he = 0.074
G_grav = 6.674e-11
pc = 3.086e16
Mpc = 1e6 * pc
H0 = 0.7 * 100.0 * 1.0e5 / Mpc
rho_crit_0 = 3.0 * H0 * H0 / (8.0 * np.pi * G_grav)
Omega_B = 0.044
mu = (1.0 - abu_he) + 4.0 * abu_he
m_p = 1.672661e-24
dfile = np.ones(ss ** 3).reshape(ss, ss, ss)
dfile = dfile * rho_crit_0 * Omega_B / (mu * m_p) * (1.0 + redshifts[i]) ** 3
dfile = dfile * 1.23581719037e-35
else:
dfile = c2t.DensityFile(density_filename).cgs_density
dT_box = c2t.calc_dt_full(xfile, tfile, dfile, redshifts[i])
# IO.writemap(dT_box,filename)
IO.writebin(dT_box, filename)
print "Written map to " + filename
def lightcone():
filenames = ["" for x in range(len(redshifts))]
# filenames[0] = len(redshifts)
mini = -457
maxi=83
for i in range(len(filenames)):
#filenames[i] = setup_dirs.path() + 'lightcone_temp/Temper3D_'+str('%.3f' % redshifts[i]) + '.bin'
filenames[i] = '../generate_data/'+setup_dirs.resultsdir()+'dbt/map_dbt_'+str('%.3f' % redshifts[i]) + '.bin'
noreds=10
redshifts_many = np.zeros(len(redshifts)*noreds)
for i in range(len(redshifts)-1):
for j in range(noreds):
redshifts_many[i+j]=redshifts[i]-(redshifts[i+1]-redshifts[i])*j/noreds
print redshifts_many
im,z=c2t.make_lightcone(filenames,redshifts[len(redshifts)-1],redshifts[0],interpolation='step_cell')
im=np.asarray(im)
print(im[125,:,::-1])
print(im[1,1,1])
plot_lightcone(im[125,:,::-1],i,"$\delta$ T [mK]","lightcone_dbt",mini,maxi,z,cmap='Blues_r')
def xfrac_power_spectrum(id):
for i in range(len(redshifts)):
print "Doing redshift: " + str(redshifts[i])
data=c2t.XfracFile(setup_dirs.path()+"xfrac3d"+id+'_'+str('%.3f' % redshifts[i])+".bin").xi
powerspec=ps.power_spectrum_1d(data,100)
IO.write2data(powerspec[0],powerspec[1],setup_dirs.resultsdir()+'/powerSpectra_xfrac_'+id+'_'+str('%.3f' % redshifts[i])+'.dat',setup_dirs.resultsdir()+'/powerSpectraFrequencies_dbt_100b_'+str('%.3f' % redshifts[i])+'.dat')
def readbin(filename):
f = open('../generate_data/'+setup_dirs.resultsdir()+filename,'rb')
return np.load(f)
def power_spectrum(id=''):
for i in range(len(redshifts)):
print "Doing redshift: " + str(redshifts[i])
data=np.load(setup_dirs.resultsdir()+"map_dbt_"+id+str('%.3f' % redshifts[i])+".bin")
powerspec=ps.power_spectrum_1d(data,100)
IO.write2data(powerspec[0],powerspec[1],setup_dirs.resultsdir()+'/powerSpectra_100b_'+id+str('%.3f' % redshifts[i])+'.dat',setup_dirs.resultsdir()+'/powerSpectraFrequencies_dbt_100b_'+str('%.3f' % redshifts[i])+'.dat')
import scipy.integrate as sci
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from matplotlib.ticker import MultipleLocator
mpl.rc('xtick', labelsize=25)
mpl.rc('ytick', labelsize=25)
mpl.rc('font',family='serif')
fontsize=26
numberfontsize=25
tickwidth=1.5
start=0
#print plotsdir()
redshifts = setup_dirs.read_redshifts()
path_data = setup_dirs.resultsdir()
path_plots = setup_dirs.plotsdir()
def mean(name,pathd = path_data,redshifts1=redshifts):
mean = np.zeros(len(redshifts1))
print 'Reading mean from ../generate_data/'+pathd+'mean_'+name+'.dat'
file = open('../generate_data/'+pathd+'mean_'+name+'.dat', 'r')
i=0
for line in file:
mean[i] = float(line)
i=i+1
return mean
def plot_mean(data,title,ylabel,pathp = path_plots, redshifts1=redshifts, redshifts2=redshifts,legend1='',legend2='',legend3='',legend4=''):
#plt.figure()
fig=plt.figure(figsize=(10.25, 10.25), dpi= 300)
def temp_power_spectrum():
for i in range(len(redshifts)):
print "Doing redshift: " + str(redshifts[i])
data=c2t.TemperFile(setup_dirs.path()+"Temper3D_"+str('%.3f' % redshifts[i])+".bin").temper
powerspec=ps.power_spectrum_1d(data,100)
IO.write2data(powerspec[0],powerspec[1],setup_dirs.resultsdir()+'/powerSpectra_temp_'+str('%.3f' % redshifts[i])+'.dat',setup_dirs.resultsdir()+'/powerSpectraFrequencies_dbt_100b_'+str('%.3f' % redshifts[i])+'.dat')
