def powerSpec():
''' plotmap.plotdbt() '''
for i in range(len(redshifts)):
fr=IO.readoned("powerSpectraFrequencies_dbt_100b_"+str('%.3f' % redshifts[i]))
data = IO.readoned("powerSpectra_100b_"+str('%.3f' % redshifts[i]))
ps=data*fr**3./(4.*np.pi**2.)
ps=np.sqrt(ps)
plot_powerspectra(fr,ps,"ps_dbt_100b_notsquare"+str(i+10)+'_'+str(redshifts[i]),i)
def allPowerSpec():
fr=IO.readoned("powerSpectraFrequencies_dbt_100b_"+str('%.3f' % redshifts[0]))
ps=np.zeros(len(redshifts)*len(fr)).reshape(len(redshifts),len(fr))
for i in range(0,len(redshifts),10):
ps[i,:] = IO.readoned("powerSpectra_100b_"+str('%.3f' % redshifts[i]))
#print len(data), len(fr)
ps=ps*fr**3./(4.*np.pi**2.)
ps=np.sqrt(ps)
plot_powerspectra(fr,ps,"ps_dbt_100b_notsquare_all",'null')
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)