data = nlab.ArrayCatalog(data)
print "stacked data"
# Convert to MeshSource object, BoxSize in Mpc/h
mesh = data.to_mesh(window='tsc',
Nmesh=Nmesh,
BoxSize=BoxSize,
compensated=True,
position='Position')
print "converted data"
# Get void correlation function from the simulation
# Do the Fourier transform
t = nlab.FFTCorr(mesh, mode='1d', Nmesh=Nmesh,
BoxSize=BoxSize) #, dr = 9.0)
gg = t.corr
Xigg = gg['corr']
Xir = gg['r']
xi[w + str(realization)] = Xigg
# Voids
# Do correlation function
os.chdir('/')
#print(type(realization))
#if not (os.path.exists('/tigress/isk/Documents/research/projects/COLA_runs/plot_data/'+cola+'z'+redshift+sim+'/Xivv_'+crazy+w+d+'_nbodykit_'+sim+realization+c+'_'+scale+binlab+'.dat')):
if not os.path.exists(os.path.dirname(filewrite)):
data = {}
data['Position'] = da.from_array(np.column_stack((gadget_format[1], gadget_format[2], gadget_format[3])), chunks=(100,3))
data['Velocity'] = da.from_array(np.column_stack((gadget_format[4], gadget_format[5], gadget_format[6])), chunks=(100,3)) #transform.StackColumns
data = nlab.ArrayCatalog(data)
print "stacked data"
# Convert to MeshSource object, BoxSize in Mpc/h
mesh = data.to_mesh(window='tsc', Nmesh=Nmesh, BoxSize = BoxSize, compensated=True, position='Position')
# Halos
# Do correlation function
t = nlab.FFTCorr(mesh, mode='1d', Nmesh=Nmesh, BoxSize = BoxSize, dr = 1.0)
gg = t.corr
Xigg = gg['corr']
Xir = gg['r']
if not os.path.exists(os.path.dirname(file4)):
os.makedirs(os.path.dirname(file4))
f = open(file4, 'w+')
f.write('# r Xi(r) Xi(r)-ShotNoise\n')
f.write('# z = '+zlab +'\n')
datacc = np.array([gg['r'],gg['corr'].real,gg['corr'].real - gg.attrs['shotnoise']])
datacc = datacc.T
np.savetxt(f, datacc)