def plotCovarDifferentMethod(): ''' ''' dim = '1D' path = '/home/gpfs/manip/mnt0607/bao/hdumasde/Results/Txt/FitsFile_DR12_Guy/' listPath = [ path+'subSampling_LYA_QSO_cov_'+dim+'.npy', path+'shuffleQSO_LYA_QSO_cov_'+dim+'.npy', path+'randomQSO_LYA_QSO_cov_'+dim+'.npy', path+'shuffleForest_LYA_QSO_cov_'+dim+'.npy', '/home/gpfs/manip/mnt0607/bao/hdumasde/Mock_JMLG/v1547/Results_RandomPosInCell/xi_delta_QSO_result_cov_'+dim+'.npy', '/home/gpfs/manip/mnt0607/bao/hdumasde/Mock_JMLG/v1547/Results_RandomPosInCell/xi_delta_QSO_result_cov_'+dim+'_meanSubSampling.npy', ] listPath2 = [ path+'subSampling_LYA_QSO_'+dim+'.npy', path+'shuffleQSO_LYA_QSO_'+dim+'.npy', path+'randomQSO_LYA_QSO_'+dim+'.npy', path+'shuffleForest_LYA_QSO_'+dim+'.npy', '/home/gpfs/manip/mnt0607/bao/hdumasde/Mock_JMLG/v1547/Results_RandomPosInCell/xi_delta_QSO_result_'+dim+'.npy', ] listName = ['Data \, subsampling', 'Data \, shuffle \, QSO', 'Data \, random \, QSO', 'Data \, shuffle \, forest', 'Mocks', '< Mock \, subsampling >', ] real = [ numpy.load(i) for i in listPath2 ] cov = [ numpy.load(i) for i in listPath ] ### Plot the realisation for i in numpy.arange(len(real)): print listName[i] for j in numpy.arange(real[i][0,:].size): plt.errorbar(numpy.arange(real[i][:,j].size), real[i][:,j],fmt='o',color='blue',alpha=0.1) plt.errorbar(numpy.arange(real[i][:,j].size), numpy.mean(real[i],axis=1),fmt='o',color='red',label=r'$Mean$') plt.xlabel(r'$bin \, index$', fontsize=40) plt.ylabel(r'$\xi(|s|)$', fontsize=40) plt.title(r'$'+listName[i]+'$', fontsize=40) myTools.deal_with_plot(False,False,True) plt.xlim([ -1., cov[i][0,:].size+1 ]) plt.show() ### Plot diagonal for i in numpy.arange(len(cov)): plt.errorbar(numpy.arange(cov[i][0,:].size), numpy.diag(cov[i]),fmt='o',label=r'$'+listName[i]+'$') plt.xlabel(r'$bin \, index$', fontsize=40) plt.ylabel(r'$Var(|s|)$', fontsize=40) myTools.deal_with_plot(False,False,True) plt.xlim([ -1., cov[i][0,:].size+1 ]) plt.show() myTools.plotCovar(cov,listName) return
plt.xlim([ numpy.min(xxx)-10., numpy.max(xxx)+10. ])
plt.show()
return b1b2
path = '/home/gpfs/manip/mnt0607/bao/hdumasde/Results/Txt/FitsFile_DR12_Guy/xi_delta_QSO_distortionMatrix_2D_LYA_QSO.txt'
print path
data = numpy.loadtxt(path)
print data
print numpy.diag(data)
myTools.plot2D(data)
a = myTools.plotCovar([data],['a'])
#nbPixel = nbBin1D__
nbPixel = nbBin2D__
'''
#### Matrix from Nicolas
data = numpy.loadtxt("/home/gpfs/manip/mnt0607/bao/hdumasde/Code/CrossCorrelation/chain_annalys_delta/Correlation/run/xcf_v5_8_guy_c2_baseline.dmat")
distortionMatrix = numpy.zeros( shape=(nbBin2D__,nbBin2D__) )
save0 = data[:,0].astype(int)
save1 = data[:,1].astype(int)
save2 = data[:,2]
size = save2.size
for i in numpy.arange(size):
