Ejemplo n.º 1
0
def compare_mean_xfrac():
    wstars_xfrac = plot_1D.mean('xfrac','data_'+flag1+'/',redshifts1)
    wpls_xfrac = plot_1D.mean('xfrac','data_'+flag2+'/',redshifts2)
    wstars_xfracHe1 = plot_1D.mean('xfracHe1','data_'+flag1+'/',redshifts1)
    wpls_xfracHe1 = plot_1D.mean('xfracHe1','data_'+flag2+'/',redshifts2)
    wstars_xfracHe2 = plot_1D.mean('xfracHe2','data_'+flag1+'/',redshifts1)
    wpls_xfracHe2 = plot_1D.mean('xfracHe2','data_'+flag2+'/',redshifts2)

    length = min(len(wstars_xfrac),len(wpls_xfrac))

    means = np.zeros(6*length).reshape(length,6)
    for i in range(length):
        if i<len(wpls_xfrac):
            means[i,0] = wpls_xfrac[i]
            means[i,1] = wpls_xfracHe1[i]
            means[i,2] = wpls_xfracHe2[i]
        means[i,3] = wstars_xfrac[i]
        means[i,4] = wstars_xfracHe1[i]
        means[i,5] = wstars_xfracHe2[i]

    means[0,2] = means[1,2]
    means[0,5] = means[1,5]  
   #print means[:,2], means[:,5]
    #print redshifts_wstars[i], redshifts_wpls[i]

    plot_1D.plot_mean(means,"xfrac","log$_{10}$ (Ionised Fraction)",'compare_'+flag1+'_'+flag2+'/',redshifts1,redshifts2,"Stellar & X-ray binaries","Stellar only")
Ejemplo n.º 2
0
def compare_mean_temp():
    
    minmax = "min"

    data1 = plot_1D.mean('temp','tests/data_10/',redshifts)
    data2 = plot_1D.mean('temp','tests/data_200/',redshifts)
#    data3 = plot_1D.mean('temp','tests/data_121/',redshifts)
#    data4 = plot_1D.mean('temp','tests/data_201/',redshifts)
   

    length = max(len(data1),len(data2))

    means = np.zeros(2*length).reshape(length,2)
    for i in range(len(data1)):
        means[i,0] = data1[i]
        means[i,1] = data2[i]
#        means[i,2] = data3[i]
#        means[i,3] = data4[i]

    print means[:,0]
    print means[:,1]
#    print data3
#    print data4
        #print means[i,1]
    #print redshifts_wstars[i], redshifts_wpls[i]
    plot_1D.plot_mean(means,"Temperature","Temperature (K)",'tests/',redshifts,redshifts,"11","501")
Ejemplo n.º 3
0
def compare_rms():

    rmsdata=numpy.zeros(len(wpls)**2).reshape(len(wpls),len(wpls))
    for i in range(redshifts_wstars): 
        fr_wstars=np.loadtxt("../generate_data/data_wstars/powerSpectraFrequencies_dbt_"+str('%.3f' % redshifts[i]))
        data_wstars = np.loadtxt("../generate_data/data_wstars/powerSpectra_"+str('%.3f' % redshifts[i]))*1.0e-3
        rmsdata[0,i]=sci.simps(data_wstars,fr_wstars)/1.0e-3

        fr_wpls=np.loadtxt("../generate_data/data_wstars/powerSpectraFrequencies_dbt_"+str('%.3f' % redshifts[i]))
        data_wpls = np.loadtxt("../generate_data/data_wstars/powerSpectra_"+str('%.3f' % redshifts[i]))*1.0e-3
        rmsdata[1,i]=sci.simps(data_pls,fr_wpls)/1.0e-3

    plot_1D.plot_mean(rmsdata,"rms","rms (mK)",'compare_wstars_wpls/',redshifts_wpls,redshifts_wpls,"Stellar only","Stellar and X-ray")

    wstars_temp = plot_1D.mean('temp','data_wstars/',redshifts_wstars)
    wpls_temp = plot_1D.mean('temp','data_wpls/',redshifts_wpls)

    length = min(len(wstars_temp),len(wpls_temp))
    print length
    means = np.zeros(2*length).reshape(length,2)
    for i in range(length):
        means[i,0] = wstars_temp[i]
    for i in range(length):
        means[i,1] = wpls_temp[i]
        #print means[i,1]
    #print redshifts_wstars[i], redshifts_wpls[i]
    plot_1D.plot_mean(means,"Temperature","Temperature (K)",'compare_wstars_wpls/',redshifts_wpls,redshifts_wpls,"Stellar only","Stellar and X-ray")
Ejemplo n.º 4
0
def compare_mean_dbt():
    wstars_temp = plot_1D.mean('dbt','data_'+flag1+'/',redshifts1)
    wpls_temp = plot_1D.mean('dbt','data_'+flag2+'/',redshifts2)
    print wstars_temp
    print wpls_temp
    print "--------------"
    length = min(len(wstars_temp),len(wpls_temp))/2
    if (length%2!=0):
        length=length-1
    means = np.zeros(2*length).reshape(length,2)
    redshifts3 = np.zeros(length)
    redshifts4 = np.zeros(len(wpls_temp)/2)
    for i in range(length*2):
        if i%2==0:
            means[i/2,0] = wstars_temp[i]
            if (i<len(wpls_temp)):
                means[i/2,1] = wpls_temp[i]
            redshifts3[i/2]=redshifts1[i]
    for i in range(length): 
        redshifts4[i/2]=redshifts2[i]
    print means[:,1]
    print means[:,0]
    print "-----------"
    #print redshifts_wstars[i], redshifts_wpls[i]
    plot_1D.plot_mean(means,"dbt","$\delta T_b$",'compare_'+flag1+'_'+flag2+'/',redshifts3,redshifts4,label1,label2)
Ejemplo n.º 5
0
def compare_rms():

    length=min(len(redshifts1),len(redshifts2))
    if length%2!=0:
        length=length-1
    rmsdata=np.zeros(length).reshape(length/2,2)
    redshifts_short=np.zeros((length)/2)
    for i in range(0,length,2):
        redshifts_short[i/2]=redshifts2[i] 
        print "opening ../generate_data/data_"+flag1+"/map_dbt_"+str('%.3f' % redshifts1[i])+".bin and ../generate_data/data_"+flag2+"/map_dbt_"+str('%.3f' % redshifts2[i])+".bin" 
        data1=np.load("../generate_data/data_"+flag1+"/map_dbt_"+str('%.3f' % redshifts1[i])+".bin")
        data2=np.load("../generate_data/data_"+flag2+"/map_dbt_"+str('%.3f' % redshifts2[i])+".bin")
        mean1=np.mean(data1)
        mean2=np.mean(data2)
      #  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/2,0]=rmsdata[i/2,0]+(data1[x,y,z]-mean1)**2
                    rmsdata[i/2,1]=rmsdata[i/2,1]+(data2[x,y,z]-mean2)**2
        rmsdata[i/2,:]=np.sqrt(rmsdata[i/2,:]/(length**3)/2.0)
#        rmsdata[:,i]=np.sqrt(rmsdata[:,i]/(length**3)/2.0)
    plot_1D.plot_mean(rmsdata,"rms_100b","rms (mK)","compare_"+flag1+"_"+flag2+"/",redshifts_short,redshifts_short,label1,label2)
Ejemplo n.º 6
0
def compare_mean_temp():
    wstars_temp = plot_1D.mean('temp','data_wstars/',redshifts_wstars)
    wpls_temp = plot_1D.mean('temp','data_wpls/',redshifts_wpls)

    length = min(len(wstars_temp),len(wpls_temp))

    means = np.zeros(2*length).reshape(length,2)
    for i in range(length):
        means[i,0] = wstars_temp[i]
    for i in range(length):
        means[i,1] = wpls_temp[i]
        #print means[i,1]
    #print redshifts_wstars[i], redshifts_wpls[i]
    plot_1D.plot_mean(means,"Temperature","Temperature (K)",'compare_wstars_wpls/',redshifts_wpls,"Stellar only","Stellar and X-ray")
Ejemplo n.º 7
0
def compare_mean_dbt():
    wstars_temp = plot_1D.mean('dbt','data_wstars/',redshifts_wstars)
    wpls_temp = plot_1D.mean('dbt','data_wpls/',redshifts_wpls)

    length = max(len(wstars_temp),len(wpls_temp))/2
    means = np.zeros(2*length).reshape(length,2)
    redshifts2 = np.zeros(length)
    for i in range(length*2):
        if i%2==0:
            means[i/2,0] = wstars_temp[i]
            if (i<len(wpls_temp)):
                means[i/2,1] = wpls_temp[i]
            redshifts2[i/2]=redshifts_wstars[i]
        #print means[i,1]
    #print redshifts_wstars[i], redshifts_wpls[i]
    plot_1D.plot_mean(means,"dbt","$\delta T_b$",'compare_wstars_wpls/',redshifts2,"Stellar only","Stellar and X-ray")
Ejemplo n.º 8
0
def compare_mean_temp():
    
    minmax = "min"
  #  print redshifts1
   # print '-----------------------------'
   # print redshifts2
    data1 = plot_1D.mean('temp','data_'+flag1+'/',redshifts1)
    data2 = plot_1D.mean('temp','data_'+flag2+'/',redshifts2)

    #print redshifts1
    #print '-----------------------------'
    #print redshifts2

    if minmax=="max":
        length = max(len(data1),len(data2))

        means = np.zeros(2*length).reshape(length,2)
        for i in range(len(data1)):
            means[i,0] = data1[i]
        for i in range(len(data2)):
            means[i,1] = data2[i]
        print redshifts1
        print '-----------------------------'
        print redshifts2

        #print means[i,1]
    #print redshifts_wstars[i], redshifts_wpls[i]
        print np.shape(means)
    #    print len(redshifts1), len(redshifts2)
    #    print redshifts2
#        print len(redshifts2)
     #   plot_1D.plot_mean(means,"Temperature","Temperature (K)",'compare_'+flag1+'_'+flag2+'/',redshifts2,redshifts2,label1,label2)

    elif minmax=="min":
        length = min(len(data1),len(data2))
        means = np.zeros(2*length).reshape(length,2)
        for i in range(length):
            means[i,0] = data1[i]
        for i in range(length):
            means[i,1] = data2[i]
        print means[i,1]
        print means[i,0]
    #prin redshifts_wstars[i], redshifts_wpls[i]
        plot_1D.plot_mean(means,"Temperature","Temperature (K)",'compare_'+flag1+'_'+flag2+'/',redshifts2,redshifts2,label1,label2)
Ejemplo n.º 9
0
def compare_mean_test():
    wstars_temp = plot_1D.mean('temp','data_wstars/',redshifts_wstars)
    wpls_temp = plot_1D.mean('temp','data_wpls/',redshifts_wpls)

    length = max(len(wstars_temp),len(wpls_temp))
    
    wstars_tcmb = 2.725*(np.ones(len(redshifts_wstars))+redshifts_wstars)
    wpls_tcmb = 2.725*(np.ones(len(redshifts_wpls))+redshifts_wpls)

    wstars_test = (wstars_temp-wstars_tcmb)/wstars_temp
    wpls_test = (wpls_temp-wpls_tcmb)/wpls_temp


    means = np.zeros(2*length).reshape(length,2)
    for i in range(length):
        means[i,0] = wstars_test[i]
    for i in range(length):
        if (i<len(wpls_temp)):
            means[i,1] = wpls_test[i]
        #print means[i,1]
    #print redshifts_wstars[i], redshifts_wpls[i]
    plot_1D.plot_mean(means,"Test","$(T_S - T_{CMB}) / T_S$",'compare_wstars_wpls/',redshifts_wstars,redshifts_wpls,"Stellar only","Stellar and X-ray")
Ejemplo n.º 10
0
def compare_rms():

    length=min(len(redshifts1),len(redshifts2))
    if length%2!=0:
       length=length-1
    #rmsdata=np.zeros(length).reshape(length/2,2)
    rmsdata=np.zeros((length/2,2))#length**2).reshape(length,2)
    #redshifts_short=np.zeros((length)/2)
    redshifts_short=np.zeros(length/2)
#   for i in range(0,length,2):
#        redshifts_short[i/2]=redshifts2[i] 
 #       print "opening ../generate_data/data_"+flag1+"/map_dbt_"+str('%.3f' % redshifts1[i])+".bin and ../generate_data/data_"+flag2+"/map_dbt_"+str('%.3f' % redshifts2[i])+".bin" 
    data1=IO.readoned("rms",path="../generate_data/data_"+flag1+"/")#"../generate_data/data_"+flag1+"/rms.dat")
    data2=IO.readoned("rms",path="../generate_data/data_"+flag2+"/")#"../generate_data/data_"+flag2+"/rms.da")
    for i in range(0,length/2):
        print i
        rmsdata[i,0]=data1[i*2]
        rmsdata[i,1]=data2[i*2]
#    for i in range(length/2):
        redshifts_short[i] = redshifts1[i*2]
#        mean1=np.mean(data1)
#        mean2=np.mean(data2)
#      #  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/2,0]=rmsdata[i/2,0]+(data1[x,y,z]-mean1)**2
#                    rmsdata[i/2,1]=rmsdata[i/2,1]+(data2[x,y,z]-mean2)**2
#        rmsdata[i/2,:]=np.sqrt(rmsdata[i/2,:]/(length**3)/2.0)
#        rmsdata[:,i]=np.sqrt(rmsdata[:,i]/(length**3)/2.0)
    print rmsdata[:,0]
    print '-----------------------------------'
    print rmsdata[:,1]
    plot_1D.plot_mean(rmsdata,"rms_100b","rms (mK)","compare_"+flag1+"_"+flag2+"/",redshifts_short,redshifts_short,label1,label2)
Ejemplo n.º 11
0
plot_2D.plottemp()
plot_2D.plotxfrac('')
plot_2D.plotxfrac('He1')
plot_2D.plotxfrac('He2')
plot_2D.equation_of_state()

##these need information from generate_data so leave until last
plot_2D.plotdbt()
plot_2D.plot_smoothed_dbt()
#
plot_2D.lightcone_temp()
plot_2D.lightcone_xfrac()
plot_2D.lightcone_xfrac(rsd='rsd')
plot_2D.lightcone_temp('rsd')
#
plot_1D.plot_mean(plot_1D.mean("temp"),"Tempererature","Temperature (K)")

means = np.zeros(len(redshifts)*3).reshape(len(redshifts),3)
means[:,0] = plot_1D.mean('xfrac')
means[:,1] = plot_1D.mean('xfracHe1')
means[:,2] = plot_1D.mean('xfracHe2')
plot_1D.plot_mean(np.log10(means),"x-frac","Log (Ionised Fraction)")
##
meantemp=plot_1D.mean('temp')
plot_1D.plot_mean(meantemp,"Temper","Temperature (K)")

#meantemp_igm=plot_1D.mean('temp_igm')
#plot_1D.plot_mean(meantemp_igm,"igm_temper","Temperature (K)")

###CMBtemp=2.725*(np.ones(len(redshifts))+redshifts)
###meantest=(meantemp-CMBtemp)/meantemp