for j in numpy.arange(nbPixel):
data2[i][j] -= cov[j][i]
data2[ data2==0. ] = numpy.float('nan')
myTools.plot2D(data2)
#plt.hist(data[data!=0.],bins=100)
#plt.hist(numpy.diag(data),bins=100)
#plt.show()
if (nbPixel==nbBin1D__):
xi1D = xi1D_[:,1]
else:
xi1D = myTools.convert2DTo1D(xi2D_[:,:,1], 50,100)
xi1D_2 = numpy.dot(data,xi1D)
plt.errorbar(numpy.arange(nbPixel),xi1D,fmt='o',label='Before correction')
plt.errorbar(numpy.arange(nbPixel),xi1D_2,fmt='o',label='After correction')
myTools.deal_with_plot(False,False,True)
plt.show()
if (nbPixel==nbBin1D__):
xi1D_[:,1] = xi1D_2
plotXi(0)
plotXi(1)
plotXi(2)
pathToCamb = '/home/gpfs/manip/mnt0607/bao/hdumasde/Results/Txt/CAMB_2_4/xi-z2.4.dat'
fitCamb(xi1D_,pathToCamb,0)
def saveListRealMocks(ni,nj,distortion=False):
'''
- ni: Box
- nj: Simu
- distortion: Flag to use or not the distortion matrix (defalut=False)
Usage example:
cov = numpy.load('/home/gpfs/manip/mnt0607/bao/hdumasde/Mock_JMLG/v1547/Results_NicolasDistortion/xi_delta_QSO_result_cov_1D.npy')
cor = myTools.getCorrelationMatrix(cov)
myTools.plot2D(cor)
a = myTools.plotCovar([cor],['a'])
'''
### Where to get correlation
path = '/home/gpfs/manip/mnt0607/bao/hdumasde/Mock_JMLG/v1547/Box_00'
### Where to save the results
pathToSave = '/home/gpfs/manip/mnt0607/bao/hdumasde/Mock_JMLG/v1547/Results_NicolasDistortionWithDistortion/xi_delta_QSO_result_'
list1D = numpy.zeros( shape=(nbBin1D__,ni*nj) )
list2D = numpy.zeros( shape=(nbBin2D__,ni*nj) )
listMu = numpy.zeros( shape=(nbBin1D__*nbBinM__,ni*nj) )
listWe = numpy.zeros( shape=(nbBin1D__,3,ni*nj) )
listMultipol = numpy.zeros( shape=(nbBin1D__,5,ni*nj) )
for i in numpy.arange(ni):
for j in numpy.arange(nj):
tmpPath = path + str(i)+'/Simu_00'+str(j)+'/Results_NicolasDistortion/xi_delta_QSO_'
try:
xi1D, xi2D, xiMu, xiWe = loadData(tmpPath+'Mu_LYA_QSO.txt',tmpPath+'2D_LYA_QSO.txt')
list1D[:,i*10+j] = xi1D[:,1]
list2D[:,i*10+j] = xi2D[:,:,1].flatten()
listMu[:,i*10+j] = xiMu[:,:,2].flatten()
listWe[:,:,i*10+j] = xiWe[:,:,1]
listMultipol[:,:,i*10+j] = plotMultipol(xiMu)[:,:,1]
except:
print ' ERROR:: ', tmpPath
if (distortion):
tmp_command = " echo " + str(i) + " " + str(j)
subprocess.call(tmp_command, shell=True)
### distortion matrix 1D
data = numpy.loadtxt(tmpPath+'distortionMatrix_1D_LYA_QSO.txt')
list1D[:,i*10+j] = numpy.dot(data,xi1D[:,1])
#myTools.plot2D(data)
#myTools.plot1D([xi1D[:,1],list1D[:,i*10+j]],'-','-','-',['before','after'])
### distortion matrix 2D
data = numpy.loadtxt(tmpPath+'distortionMatrix_2D_LYA_QSO.txt')
xi1D = myTools.convert2DTo1D(xi2D[:,:,1], nbBinX2D__,nbBinY2D__)
list2D[:,i*10+j] = numpy.dot(data,xi1D)
numpy.save(pathToSave+'1D',list1D)
numpy.save(pathToSave+'2D',list2D)
numpy.save(pathToSave+'Mu',listMu)
numpy.save(pathToSave+'We',listWe)
numpy.save(pathToSave+'Multipol',listMultipol)
cov1D = numpy.cov(list1D)
cov2D = numpy.cov(list2D)
covMu = numpy.cov(listMu)
numpy.save(pathToSave+'cov_1D',cov1D)
numpy.save(pathToSave+'cov_2D',cov2D)
numpy.save(pathToSave+'cov_Mu',covMu)
return