# read snapshot and find number of subfiles snapshot_root = '%s/output/'%run snapshot = snapshot_root + 'snapdir_%03d/snap_%03d'%(snapnum,snapnum) header = rs.snapshot_header(snapshot) redshift = header.redshift h = header.hubble if halo_num is not(None): xmin = x_max = y_min = y_max = z_min = z_max = None # only master reads halo catalogue if myrank==0: # read number of particles in halos and subhalos and number of subhalos print '\nReading halo catalogue...' halos = groupcat.loadHalos(snapshot_root, snapnum, fields=['GroupPos','GroupMass','Group_R_TopHat200']) halo_pos = halos['GroupPos']/1e3 #Mpc/h halo_R = halos['Group_R_TopHat200']/1e3 #Mpc/h halo_mass = halos['GroupMass']*1e10 #Msun/h del halos # find the coordinates of the region if halo_num is not (None): x_max, y_max, z_max = halo_pos[halo_num] + BoxSize_image/2.0 x_min, y_min, z_min = halo_pos[halo_num] - BoxSize_image/2.0 print 'M_halo = %.3e Msun/h'%(halo_mass[halo_num]) print 'R_halo = %.3e Mpc/h\n'%(halo_R[halo_num]) print '%6.3f < X < %6.3f'%(x_min, x_max) print '%6.3f < Y < %6.3f'%(y_min, y_max) print '%6.3f < Z < %6.3f'%(z_min, z_max)
filenum = header.filenum
Omega_m = header.omega0
Omega_L = header.omegaL
h = header.hubble
print '\n'
print 'BoxSize = %.3f Mpc/h'%BoxSize
print 'Number of files = %d'%filenum
print 'Omega_m = %.3f'%Omega_m
print 'Omega_l = %.3f'%Omega_L
print 'redshift = %.3f'%redshift
if os.path.exists(fout[:-4]+'_z=%.3f.hdf5'%redshift): continue
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(snapshot_root, num,
fields=['GroupLenType','GroupVel'])
halo_len = halos['GroupLenType'][:,0]
halo_vel = halos['GroupVel']*(1.0+redshift) #km/s
del halos
# read HI bulk velocity of halos
f = h5py.File('../HI_bulk_velocity/V_HI_75_1820_z=%d.hdf5'%round(redshift),
'r')
V_HI = f['V_HI'][:] #km/s
f.close()
V_HI = V_HI.astype(np.float32)
# define the M_HI and sigma_HI array
M_HI = np.zeros(len(halo_len), dtype=np.float64)
sigma2_HI = np.zeros(len(halo_len), dtype=np.float64)
Omega_m = 0.3089
Omega_l = 0.6911
h = 0.6774
z = 1.0
#######################################################################
H0 = 100.0 #km/s/(Mpc/h)
Hz = 100.0*np.sqrt(Omega_m*(1.0+z)**3 + Omega_l)
V_cell = BoxSize**3*(5.0/BoxSize)/dims**2 #(Mpc/h)^3
print '\nReading halo catalogue...'
snapshot_root = '%s/output/'%run
halos = groupcat.loadHalos(snapshot_root, snapnum,
fields=['GroupPos','GroupMass','GroupVel'])
halo_pos = halos['GroupPos']/1e3 #Mpc/h
halo_vel = halos['GroupVel']*(1.0+z) #km/s
halo_mass = halos['GroupMass']*1e10 #Msun/h
del halos
# move halo positions to redshift-space
RSL.pos_redshift_space(halo_pos, halo_vel, BoxSize, Hz, z, axis)
print np.min(halo_pos[:,0]),np.max(halo_pos[:,0])
print np.min(halo_pos[:,1]),np.max(halo_pos[:,1])
print np.min(halo_pos[:,2]),np.max(halo_pos[:,2])
indexes = np.where((halo_pos[:,2]>=0.0) & (halo_pos[:,2]<5.0))[0]
ratio = np.sqrt(np.dot(V1,V1)/np.dot(V2,V2))
return cos_a,ratio
############################## INPUT ########################################
run = '/n/hernquistfs3/IllustrisTNG/Runs/L75n1820TNG'
snapshot_root = '%s/output/'%run
snapnum = 17
#############################################################################
z_dict = {99:0, 17:5}
FoF = groupcat.loadHalos(snapshot_root, snapnum,
fields=['GroupLenType','GroupNsubs','GroupVel',
'GroupFirstSub','GroupMass'])
halo_len = FoF['GroupLenType'][:,0]
Nsubs = FoF['GroupNsubs']
halo_vel = FoF['GroupVel']*(1.0+z_dict[snapnum])
first_sub = FoF['GroupFirstSub']
halo_mass = FoF['GroupMass']*1e10 #Msun/h
subhalos = groupcat.loadSubhalos(snapshot_root, snapnum,
fields=['SubhaloGrNr','SubhaloMass',
'SubhaloVel'])
sub_FoF = subhalos['SubhaloGrNr'][:]
sub_mass = subhalos['SubhaloMass'][:]*1e10 #Msun/h
sub_vel = subhalos['SubhaloVel'][:]
del subhalos
if myrank==0:
print '\nBoxSize = %.1f Mpc/h'%BoxSize
print 'Number of files = %d'%filenum
print 'Omega_m = %.3f'%Omega_m
print 'Omega_l = %.3f'%Omega_L
print 'redshift = %.3f'%redshift
# find the output name
fout1 = 'HI_profiles_%.1e-%.1e_%d_z=%.2f.hdf5'%(Mmin,Mmax,bins,redshift)
fout2 = 'HI_profile_new_%.1e-%.1e-z=%.1f.txt'%(Mmin,Mmax,redshift)
# read number of particles in halos and subhalos and number of subhalos
if myrank==0: print '\nReading halo catalogue...'
halos = groupcat.loadHalos(snapshot_root, snapnum,
fields=['GroupPos','GroupMass',
'Group_R_TopHat200','Group_M_TopHat200'])
halo_pos = halos['GroupPos']/1e3 #Mpc/h
halo_R = halos['Group_R_TopHat200']/1e3 #Mpc/h
halo_mass = halos['Group_M_TopHat200']*1e10 #Msun/h
#halo_mass = halos['GroupMass']*1e10 #Msun/h
del halos
# consider only halos in the mass range and with R>0
indexes = np.where((halo_mass>Mmin) & (halo_mass<Mmax) & (halo_R>0.0))[0]
halo_pos = halo_pos[indexes]
halo_R = halo_R[indexes]
halo_mass = halo_mass[indexes]
if myrank==0:
print 'Found %d halos with masses %.2e < M < %.2e'\
def __init__(self, snapshot_root, snapnum, halo_number, TREECOOL_file,
ptype):
# read header
snapshot = snapshot_root + 'snapdir_%03d/snap_%03d'%(snapnum, snapnum)
f = h5py.File(snapshot+'.0.hdf5', 'r')
scale_factor = f['Header'].attrs[u'Time']
redshift = f['Header'].attrs[u'Redshift']
BoxSize = f['Header'].attrs[u'BoxSize']/1e3 #Mpc/h
filenum = f['Header'].attrs[u'NumFilesPerSnapshot']
Omega_m = f['Header'].attrs[u'Omega0']
Omega_L = f['Header'].attrs[u'OmegaLambda']
h = f['Header'].attrs[u'HubbleParam']
Masses = f['Header'].attrs[u'MassTable']*1e10 #Msun/h
f.close()
print '\nBoxSize = %.1f Mpc/h'%BoxSize
print 'Number of files = %d'%filenum
print 'Omega_m = %.3f'%Omega_m
print 'Omega_l = %.3f'%Omega_L
print 'redshift = %.3f'%redshift
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(snapshot_root, snapnum,
fields=['GroupLenType','GroupPos',
'GroupMass'])
halo_len = halos['GroupLenType'][:,ptype]
halo_pos = halos['GroupPos']/1e3
halo_mass = halos['GroupMass']*1e10
del halos
# find where the halo starts and ends in the file
begin = np.sum(halo_len[:halo_number], dtype=np.int64)
end = begin + halo_len[halo_number]
length = end-begin
print begin,end
self.pos = np.zeros((length,3), dtype=np.float32)
self.vel = np.zeros((length,3), dtype=np.float32)
if ptype==0:
self.M_HI = np.zeros(length, dtype=np.float32)
begin_subfile, particles = 0, 0
for i in xrange(filenum):
# find subfile name and read the number of particles in it
snapshot = snapshot_root + 'snapdir_%03d/snap_%03d.%d.hdf5'%(snapnum, snapnum, i)
f = h5py.File(snapshot, 'r')
npart = f['Header'].attrs[u'NumPart_ThisFile']
f.close()
end_subfile = begin_subfile + npart[ptype]
# if all particles in the halo has been read exit loop
if end<begin_subfile: break
# if the subfile does not contain any particle move to next subfile
if begin>end_subfile:
begin_subfile = end_subfile; continue
print i
f = h5py.File(snapshot, 'r')
print 'Working with subfile %03d'%i
pos_i = (f['PartType%d/Coordinates'%ptype][:]/1e3).astype(np.float32)
vel_i = f['PartType%d/Velocities'%ptype][:]*np.sqrt(scale_factor)
if ptype==0:
pos_i, M_HI_i = HIL.HI_mass_from_Illustris_snap(snapshot, TREECOOL_file)
# find the indexes of current subfile that contribute to halo
begin_array = begin - begin_subfile
end_array = begin_array + length
if end>end_subfile:
end_array = end_subfile - begin_subfile
begin = end_subfile
length_array = end_array-begin_array
self.pos[particles:particles+length_array] = pos_i[begin_array:end_array]
self.vel[particles:particles+length_array] = vel_i[begin_array:end_array]
if ptype==0:
self.M_HI[particles:particles+length_array] = M_HI_i[begin_array:end_array]
particles = particles+length_array
begin_subfile = end_subfile
f.close()
print 'Halo mass = %.3e'%halo_mass[halo_number]
print 'Halo pos =',halo_pos[halo_number]
print 'Number of particles in the halo = %ld'%particles
import groupcat as GC
import sublink as SL
import numpy as np
import lhalotree as LH
import h5py
import matplotlib.pyplot as plt
basePath = '/home/illustris/Desktop/trabajo/Illustris-3lht'
GroupFirstSub = GC.loadHalos(basePath, 135, fields=['GroupFirstSub'])
Halos = GC.loadHalos(basePath,
135,
fields=['Group_M_Crit200', 'GroupPos', 'GroupNsubs'])
GroupNsubs = GC.loadHalos(basePath, 135, fields=['GroupNsubs'])
Halo_mass = Halos['Group_M_Crit200']
Halo_Pos = Halos['GroupPos']
print(len(GroupNsubs))
fields = ['SnapNum', 'Group_M_Crit200']
start = 0
for i in range(start, start + 5):
#if GroupNsubs[i] == 0:
# continue
tree = LH.loadTree(basePath,
135,
GroupFirstSub[i],
fields=fields,
onlyMPB=True)
import numpy as np
import sys, os, h5py
import groupcat
import HI_library as HIL
################################ INPUT ######################################
snapshot_root = '/n/hernquistfs3/IllustrisTNG/Runs/L75n1820TNG/output/'
TREECOOL_file = '/n/home09/fvillaescusa/Illustris/HI/TREECOOL_fg_dec11'
#############################################################################
for snapnum in [99, 50, 33, 25, 21, 17]:
# read number of particles in halos and subhalos and number of subhalos
print '\nReading halo catalogue...'
halos = groupcat.loadHalos(
snapshot_root,
snapnum,
fields=['GroupPos', 'GroupMass', 'GroupLenType'])
halo_pos = halos['GroupPos'] / 1e3 #Mpc/h
halo_mass = halos['GroupMass'] * 1e10 #Msun/h
halo_len = halos['GroupLenType'][:, 0]
del halos
Nparticles = np.sum(halo_len)
print 'Number of halos = %d' % len(halo_pos)
print 'Number of particles in all halos = %d' % Nparticles
# read snapshot header
snapshot = '%s/snapdir_%03d/snap_%03d.0.hdf5'\
%(snapshot_root, snapnum, snapnum)
f = h5py.File(snapshot, 'r')
redshift = f['Header'].attrs[u'Redshift']
z_dict = {99: 0.000, 50: 0.997, 33: 2.002, 25: 3.008, 21: 4.008, 17: 4.996}
for snapnum in [17, 21, 25, 33, 50, 99]:
# read header
snapshot = root + 'snapdir_%03d/snap_%03d' % (snapnum, snapnum)
header = readgadget.header(snapshot)
BoxSize = header.boxsize / 1e3 #Mpc/h
redshift = header.redshift
print 'L = %.1f Mpc/h' % BoxSize
print 'z = %.1f' % redshift
halos = groupcat.loadHalos(
root,
snapnum,
fields=['GroupMassType', 'GroupMass', 'Group_R_TopHat200'])
halo_mass = halos['GroupMassType'][:] * 1e10 #Msun/h
Mass = halos['GroupMass'][:] * 1e10 #Msun/h
R = halos['Group_R_TopHat200'][:] / 1e3 #Mpc/h
f = h5py.File(
'../HI_mass/HI_FoF_galaxies/M_HI_new_75_1820_z=%.3f.hdf5' %
z_dict[snapnum], 'r')
M_HI = f['M_HI'][:]
f.close()
indexes = np.where((R > 0.0) & (halo_mass[:, 0] > 0.0))[0]
halo_mass = halo_mass[indexes]
Mass = Mass[indexes]
M_HI = M_HI[indexes]
import groupcat as GC
import sublink as SL
import numpy as np
import matplotlib.pyplot as plt
###2###
basePath = '/media/ycamargo/ILLUSTRIS-3/Illustris-2'
GroupFirstSub = GC.loadHalos(basePath, 135, fields=['GroupFirstSub'])
###3###
fields = ['SubhaloMass', 'SubfindID', 'SnapNum']
start = 0
for i in range(start, start + 5):
tree = SL.loadTree(basePath,
135,
GroupFirstSub[i],
fields=fields,
onlyMPB=True)
###4###
def find_formation_time(sublinktree):
final_mass = sublinktree['SubhaloMass'][0]
initial_mass = sublinktree['SubhaloMass'][-1]
n_points = len(sublinktree['SubhaloMass'])
formation_snap = -1
for i in range(n_points - 1, -1, -1):
if sublinktree['SubhaloMass'][i] > final_mass / 2.0:
formation_snap = sublinktree['SnapNum'][i]
#fout = 'ratio_g_75Mpc_1820_UVB'
################################################################################
for snapnum in [17,21,25,33,50,99]:
# read header
snapshot = root + 'snapdir_%03d/snap_%03d'%(snapnum,snapnum)
header = readgadget.header(snapshot)
BoxSize = header.boxsize/1e3 #Mpc/h
redshift = header.redshift
print 'L = %.1f Mpc/h'%BoxSize
print 'z = %.1f'%redshift
halos = groupcat.loadHalos(root, snapnum,
fields=['GroupMassType','GroupMass',
'Group_R_TopHat200'])
halo_mass = halos['GroupMassType'][:]*1e10 #Msun/h
Mass = halos['GroupMass'][:]*1e10 #Msun/h
R = halos['Group_R_TopHat200'][:]/1e3 #Mpc/h
indexes = np.where(R>0.0)[0]
halo_mass = halo_mass[indexes]
Mass = Mass[indexes]
#ratio = (halo_mass[:,0]+halo_mass[:,4]+halo_mass[:,5])/Mass
ratio = (halo_mass[:,0])/Mass
M_bins = np.logspace(np.log10(Mmin), np.log10(Mmax), bins+1)
M_mean = 10**(0.5*(np.log10(M_bins[1:]) + np.log10(M_bins[:-1])))
h = header.hubble
if myrank == 0:
print '\n'
print 'BoxSize = %.3f Mpc/h' % BoxSize
print 'Number of files = %d' % filenum
print 'Omega_m = %.3f' % Omega_m
print 'Omega_l = %.3f' % Omega_L
print 'redshift = %.3f' % redshift
if os.path.exists(fout[:-4] + '_z=%.3f.hdf5' % redshift):
continue
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(snapshot_root,
num,
fields=['GroupLenType', 'GroupNsubs'])
halo_len = halos['GroupLenType'][:, 0]
gal_in_halo = halos['GroupNsubs']
subhalos = groupcat.loadSubhalos(
snapshot_root, num, fields=['SubhaloLenType', 'SubhaloMassType'])
gal_len = subhalos['SubhaloLenType'][:, 0]
mass_ratio = subhalos['SubhaloMassType'][:] * 1e10 #Msun/h
total_mass = np.sum(mass_ratio, axis=1) #M_matter
mass_ratio = mass_ratio[:, 1] / total_mass #M_CDM / M_matter
del halos, subhalos
# define the M_HI array
M_HI = np.zeros(len(halo_len), dtype=np.float64)
M_HI_gal = np.zeros(len(halo_len), dtype=np.float64)
M_HI_cen = np.zeros(len(halo_len), dtype=np.float64)
dims = 64
#############################################################################
num = {0:99, 1:50, 2:33, 3:25, 4:21, 5:17}
snapshot_root = '%s/output/'%run
bins_histo = np.logspace(-3,3,100)
dbins = bins_histo[1:] - bins_histo[:-1]
bins_mean = 10**(0.5*(np.log10(bins_histo[1:]) + np.log10(bins_histo[:-1])))
for z in [0,1,2,3,4,5]:
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(snapshot_root, num[z],
fields=['GroupMass','GroupPos'])
halo_mass = halos['GroupMass'][:]*1e10 #Msun/h
halo_pos = halos['GroupPos'][:]/1e3 #Mpc/h
del halos
if z==0:
alpha, M0, Mmin = 0.24, 4.3e10, 2e12
elif z==1:
alpha, M0, Mmin = 0.53, 1.5e10, 6e11
elif z==2:
alpha, M0, Mmin = 0.60, 1.3e10, 3.6e11
elif z==3:
alpha, M0, Mmin = 0.76, 2.9e9, 6.7e10
elif z==4:
alpha, M0, Mmin = 0.79, 1.4e9, 2.1e10
elif z==5:
def Illustris_halo(snapshot_root,
snapnum,
halo_number,
TREECOOL_file,
fout,
ptype=0):
# find snapshot name and read header
snapshot = snapshot_root + 'snapdir_%03d/snap_%03d' % (snapnum, snapnum)
header = rs.snapshot_header(snapshot)
redshift = header.redshift
BoxSize = header.boxsize / 1e3 #Mpc/h
filenum = header.filenum
Omega_m = header.omega0
Omega_L = header.omegaL
h = header.hubble
massarr = header.massarr * 1e10 #Msun/h
print '\nBoxSize = %.1f Mpc/h' % BoxSize
print 'Number of files = %d' % filenum
print 'Omega_m = %.3f' % Omega_m
print 'Omega_l = %.3f' % Omega_L
print 'redshift = %.3f' % redshift
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(
snapshot_root,
snapnum,
fields=['GroupLenType', 'GroupPos', 'GroupMass'])
halo_len = halos['GroupLenType'][:, ptype]
halo_pos = halos['GroupPos'] / 1e3
halo_mass = halos['GroupMass'] * 1e10
del halos
# find where the halo starts and ends in the file
begin = np.sum(halo_len[:halo_number], dtype=np.int64)
end = begin + halo_len[halo_number]
print begin, end
# do a loop over all snapshot subfiles
f = h5py.File(fout, 'w')
pos_f = f.create_dataset('pos', (0, 3), maxshape=(None, 3))
vel_f = f.create_dataset('vel', (0, 3), maxshape=(None, 3))
if ptype == 0:
mass_f = f.create_dataset('mass', (0, ), maxshape=(None, ))
MHI_f = f.create_dataset('M_HI', (0, ), maxshape=(None, ))
radii_f = f.create_dataset('radii', (0, ), maxshape=(None, ))
if ptype == 1:
radii_f = f.create_dataset('radii', (0, ), maxshape=(None, ))
mass_f = f.create_dataset('mass_c', (0, ), maxshape=(None, ))
begin_subfile, particles = 0, 0
for i in xrange(filenum):
# find subfile name and read the number of particles in it
snapshot = snapshot_root + 'snapdir_%03d/snap_%03d.%d' % (snapnum,
snapnum, i)
header = rs.snapshot_header(snapshot)
npart = header.npart
end_subfile = begin_subfile + npart[ptype]
# if all particles in the halo has been read exit loop
if end < begin_subfile: break
# if the subfile does not contain any particle move to next subfile
if begin > end_subfile:
begin_subfile = end_subfile
continue
print 'Working with subfile %03d' % i
pos = rs.read_block(snapshot, 'POS ', parttype=ptype,
verbose=False) / 1e3
pos = pos.astype(np.float32)
vel = rs.read_block(snapshot, 'VEL ', parttype=ptype,
verbose=False) / np.sqrt(1.0 + redshift) #km/s
if ptype == 0:
MHI = rs.read_block(snapshot, 'NH ', parttype=0,
verbose=False) #HI/H
mass = rs.read_block(snapshot, 'MASS', parttype=0,
verbose=False) * 1e10
SFR = rs.read_block(snapshot, 'SFR ', parttype=0, verbose=False)
indexes = np.where(SFR > 0.0)[0]
del SFR
# find the metallicity of star-forming particles
metals = rs.read_block(snapshot, 'GZ ', parttype=0, verbose=False)
metals = metals[indexes] / 0.0127
# find densities of star-forming particles: units of h^2 Msun/Mpc^3
rho = rs.read_block(snapshot, 'RHO ', parttype=0,
verbose=False) * 1e19
Volume = mass / rho #(Mpc/h)^3
radii = (Volume / (4.0 * np.pi / 3.0))**(1.0 / 3.0) #Mpc/h
# find density and radius of star-forming particles
radii_SFR = radii[indexes]
rho = rho[indexes]
# find HI/H fraction for star-forming particles
MHI[indexes] = HIL.Rahmati_HI_Illustris(rho,
radii_SFR,
metals,
redshift,
h,
TREECOOL_file,
Gamma=None,
fac=1,
correct_H2=True) #HI/H
MHI *= (0.76 * mass)
if ptype == 1:
radii = rs.read_block(snapshot, 'SFHS', parttype=1,
verbose=False) / 1e3 #Mpc/h
mass = np.ones(len(radii)) * massarr[1]
# find the indexes of current subfile that contribute to halo
begin_array = begin - begin_subfile
end_array = begin_array + (end - begin)
if end > end_subfile:
end_array = end_subfile - begin_subfile
begin = end_subfile
new_size = particles + (end_array - begin_array)
pos_f.resize((new_size, 3))
pos_f[particles:] = pos[begin_array:end_array]
vel_f.resize((new_size, 3))
vel_f[particles:] = vel[begin_array:end_array]
if ptype == 0:
mass_f.resize((new_size, ))
mass_f[particles:] = mass[begin_array:end_array]
MHI_f.resize((new_size, ))
MHI_f[particles:] = MHI[begin_array:end_array]
radii_f.resize((new_size, ))
radii_f[particles:] = radii[begin_array:end_array]
if ptype == 1:
radii_f.resize((new_size, ))
radii_f[particles:] = radii[begin_array:end_array]
mass_f.resize((new_size, ))
mass_f[particles:] = mass[begin_array:end_array]
particles = new_size
begin_subfile = end_subfile
f.close()
print 'Halo mass = %.3e' % halo_mass[halo_number]
print 'Halo pos =', halo_pos[halo_number]
print 'Number of particles in the halo = %ld' % particles
dims = 64
#############################################################################
num = {0: 99, 1: 50, 2: 33, 3: 25, 4: 21, 5: 17}
snapshot_root = '%s/output/' % run
bins_histo = np.logspace(-3, 3, 100)
dbins = bins_histo[1:] - bins_histo[:-1]
bins_mean = 10**(0.5 * (np.log10(bins_histo[1:]) + np.log10(bins_histo[:-1])))
for z in [0, 1, 2, 3, 4, 5]:
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(snapshot_root,
num[z],
fields=['GroupMass', 'GroupPos'])
halo_mass = halos['GroupMass'][:] * 1e10 #Msun/h
halo_pos = halos['GroupPos'][:] / 1e3 #Mpc/h
del halos
if z == 0:
alpha, M0, Mmin = 0.24, 4.3e10, 2e12
elif z == 1:
alpha, M0, Mmin = 0.53, 1.5e10, 6e11
elif z == 2:
alpha, M0, Mmin = 0.60, 1.3e10, 3.6e11
elif z == 3:
alpha, M0, Mmin = 0.76, 2.9e9, 6.7e10
elif z == 4:
alpha, M0, Mmin = 0.79, 1.4e9, 2.1e10
def __init__(self, snapshot_root, snapnum, halo_number, TREECOOL_file,
ptype):
# read header
snapshot = snapshot_root + 'snapdir_%03d/snap_%03d' % (snapnum,
snapnum)
f = h5py.File(snapshot + '.0.hdf5', 'r')
scale_factor = f['Header'].attrs[u'Time']
redshift = f['Header'].attrs[u'Redshift']
BoxSize = f['Header'].attrs[u'BoxSize'] / 1e3 #Mpc/h
filenum = f['Header'].attrs[u'NumFilesPerSnapshot']
Omega_m = f['Header'].attrs[u'Omega0']
Omega_L = f['Header'].attrs[u'OmegaLambda']
h = f['Header'].attrs[u'HubbleParam']
Masses = f['Header'].attrs[u'MassTable'] * 1e10 #Msun/h
f.close()
print '\nBoxSize = %.1f Mpc/h' % BoxSize
print 'Number of files = %d' % filenum
print 'Omega_m = %.3f' % Omega_m
print 'Omega_l = %.3f' % Omega_L
print 'redshift = %.3f' % redshift
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(
snapshot_root,
snapnum,
fields=['GroupLenType', 'GroupPos', 'GroupMass'])
halo_len = halos['GroupLenType'][:, ptype]
halo_pos = halos['GroupPos'] / 1e3
halo_mass = halos['GroupMass'] * 1e10
del halos
# find where the halo starts and ends in the file
begin = np.sum(halo_len[:halo_number], dtype=np.int64)
end = begin + halo_len[halo_number]
length = end - begin
print begin, end
self.pos = np.zeros((length, 3), dtype=np.float32)
self.vel = np.zeros((length, 3), dtype=np.float32)
if ptype == 0:
self.M_HI = np.zeros(length, dtype=np.float32)
begin_subfile, particles = 0, 0
for i in xrange(filenum):
# find subfile name and read the number of particles in it
snapshot = snapshot_root + 'snapdir_%03d/snap_%03d.%d.hdf5' % (
snapnum, snapnum, i)
f = h5py.File(snapshot, 'r')
npart = f['Header'].attrs[u'NumPart_ThisFile']
f.close()
end_subfile = begin_subfile + npart[ptype]
# if all particles in the halo has been read exit loop
if end < begin_subfile: break
# if the subfile does not contain any particle move to next subfile
if begin > end_subfile:
begin_subfile = end_subfile
continue
print i
f = h5py.File(snapshot, 'r')
print 'Working with subfile %03d' % i
pos_i = (f['PartType%d/Coordinates' % ptype][:] / 1e3).astype(
np.float32)
vel_i = f['PartType%d/Velocities' %
ptype][:] * np.sqrt(scale_factor)
if ptype == 0:
pos_i, M_HI_i = HIL.HI_mass_from_Illustris_snap(
snapshot, TREECOOL_file)
# find the indexes of current subfile that contribute to halo
begin_array = begin - begin_subfile
end_array = begin_array + length
if end > end_subfile:
end_array = end_subfile - begin_subfile
begin = end_subfile
length_array = end_array - begin_array
self.pos[particles:particles +
length_array] = pos_i[begin_array:end_array]
self.vel[particles:particles +
length_array] = vel_i[begin_array:end_array]
if ptype == 0:
self.M_HI[particles:particles +
length_array] = M_HI_i[begin_array:end_array]
particles = particles + length_array
begin_subfile = end_subfile
f.close()
print 'Halo mass = %.3e' % halo_mass[halo_number]
print 'Halo pos =', halo_pos[halo_number]
print 'Number of particles in the halo = %ld' % particles
# find output name
if R_field=='Group_R_Crit200':
M_field = 'Group_M_Crit200'
fout = 'M_HI_SO_Crit200_z=%.1f.hdf5'%redshift
elif R_field=='Group_R_TopHat200':
M_field = 'Group_M_TopHat200'
fout = 'M_HI_SO_TopHat200_z=%.1f.hdf5'%redshift
elif R_field=='Group_R_Mean200':
M_field = 'Group_M_Mean200'
fout = 'M_HI_SO_Mean200_z=%.1f.hdf5'%redshift
else: raise Exception("%s not allowed!"%R_field)
# read number of particles in halos and subhalos and number of subhalos
if myrank==0: print '\nReading halo catalogue...'
halos = groupcat.loadHalos(snapshot_root, snapnum,
fields=['GroupPos','GroupMass',
R_field, M_field])
halo_pos = halos['GroupPos']/1e3 #Mpc/h
halo_R = halos[R_field]/1e3 #Mpc/h
halo_mass = halos['GroupMass']*1e10 #Msun/h
halo_mass2 = halos[M_field]*1e10 #Msun/h
del halos
####### CAUTION ######
#halo_R = halo_R*1.7
######################
# consider only halos with radii larger than 0
indexes = np.where(halo_R>0.0)[0]
halo_pos = halo_pos[indexes]
halo_R = halo_R[indexes]
Omega_L = header.omegaL
h = header.hubble
if myrank==0:
print '\n'
print 'BoxSize = %.3f Mpc/h'%BoxSize
print 'Number of files = %d'%filenum
print 'Omega_m = %.3f'%Omega_m
print 'Omega_l = %.3f'%Omega_L
print 'redshift = %.3f'%redshift
if os.path.exists(fout[:-4]+'_z=%.3f.hdf5'%redshift):
continue
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(snapshot_root, num,
fields=['GroupLenType','GroupNsubs'])
halo_len = halos['GroupLenType'][:,0]
gal_in_halo = halos['GroupNsubs']
subhalos = groupcat.loadSubhalos(snapshot_root, num,
fields=['SubhaloLenType','SubhaloMassType'])
gal_len = subhalos['SubhaloLenType'][:,0]
mass_ratio = subhalos['SubhaloMassType'][:]*1e10 #Msun/h
total_mass = np.sum(mass_ratio, axis=1) #M_matter
mass_ratio = mass_ratio[:,1]/total_mass #M_CDM / M_matter
del halos, subhalos
# define the M_HI array
M_HI = np.zeros(len(halo_len), dtype=np.float64)
M_HI_gal = np.zeros(len(halo_len), dtype=np.float64)
M_HI_cen = np.zeros(len(halo_len), dtype=np.float64)
M_HI_sat = np.zeros(len(halo_len), dtype=np.float64)
basePath = '../../data/illustris_3' ssNumber = 99 # snapshotnumber zl = 0.6 zs = 2.0 ''' cosmopara ''' class cosmopara: h = 0.704 OM = 0.27 mlow = 1e12 mhigh = 1e14 GroupFirstSub = groupcat.loadHalos(basePath,ssNumber,fields = ['GroupFirstSub']) GroupMass = groupcat.loadHalos(basePath,ssNumber,fields = ['GroupMass'])*1e10/cosmopara.h GroupFirstSub = GroupFirstSub[GroupMass>mlow] GroupMass = GroupMass[GroupMass>mlow] GroupFirstSub = GroupFirstSub[GroupMass<mhigh] #SubhaloMass = groupcat.loadSubhalos(basePath,ssNumber,fields = ['SubhaloMass']) SubhaloVelDisp = groupcat.loadSubhalos(basePath,ssNumber,fields = ['SubhaloVelDisp']) #mass_msun = np.zeros(len(GroupFirstSub)) sigma = np.zeros(len(GroupFirstSub)) j = 0 for i in GroupFirstSub:
import sys,os,h5py
import groupcat
############################### INPUT ######################################
run = '/n/hernquistfs3/IllustrisTNG/Runs/L75n1820TNG'
bins = 35
############################################################################
snapshot_root = '%s/output/'%run
for snapnum,z in zip([17,21,25,33,50,99],[4.996,4.008,3.008,2.002,0.997,0.000]):
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(snapshot_root, snapnum,
fields=['GroupLenType','GroupMass'])
halo_len = halos['GroupLenType'][:,1]
halo_mass = halos['GroupMass']*1e10 #Msun/h
del halos
f_HI = 'sigma_HI_75_1820_z=%.3f.hdf5'%z
f_m = 'sigma_matter_75_1820_z=%.3f.hdf5'%z
f = h5py.File(f_HI, 'r')
M_HI = f['M_HI'][:]
sigma2_HI = f['sigma2_HI'][:]
f.close()
# only consider halos with HI masses above 1e5
indexes = np.where(M_HI>1e5)[0]
M_HI = M_HI[indexes]
def Illustris_halo(snapshot_root, snapnum, halo_number, TREECOOL_file, fout,
ptype=0):
# find snapshot name and read header
snapshot = snapshot_root + 'snapdir_%03d/snap_%03d'%(snapnum, snapnum)
header = rs.snapshot_header(snapshot)
redshift = header.redshift
BoxSize = header.boxsize/1e3 #Mpc/h
filenum = header.filenum
Omega_m = header.omega0
Omega_L = header.omegaL
h = header.hubble
massarr = header.massarr*1e10 #Msun/h
print '\nBoxSize = %.1f Mpc/h'%BoxSize
print 'Number of files = %d'%filenum
print 'Omega_m = %.3f'%Omega_m
print 'Omega_l = %.3f'%Omega_L
print 'redshift = %.3f'%redshift
# read number of particles in halos and subhalos and number of subhalos
halos = groupcat.loadHalos(snapshot_root, snapnum,
fields=['GroupLenType','GroupPos','GroupMass'])
halo_len = halos['GroupLenType'][:,ptype]
halo_pos = halos['GroupPos']/1e3
halo_mass = halos['GroupMass']*1e10
del halos
# find where the halo starts and ends in the file
begin = np.sum(halo_len[:halo_number], dtype=np.int64)
end = begin + halo_len[halo_number]
print begin,end
# do a loop over all snapshot subfiles
f = h5py.File(fout,'w')
pos_f = f.create_dataset('pos', (0,3), maxshape=(None,3))
vel_f = f.create_dataset('vel', (0,3), maxshape=(None,3))
if ptype==0:
mass_f = f.create_dataset('mass', (0,), maxshape=(None,))
MHI_f = f.create_dataset('M_HI', (0,), maxshape=(None,))
radii_f = f.create_dataset('radii', (0,), maxshape=(None,))
if ptype==1:
radii_f = f.create_dataset('radii', (0,), maxshape=(None,))
mass_f = f.create_dataset('mass_c', (0,), maxshape=(None,))
begin_subfile, particles = 0, 0
for i in xrange(filenum):
# find subfile name and read the number of particles in it
snapshot = snapshot_root + 'snapdir_%03d/snap_%03d.%d'%(snapnum, snapnum, i)
header = rs.snapshot_header(snapshot)
npart = header.npart
end_subfile = begin_subfile + npart[ptype]
# if all particles in the halo has been read exit loop
if end<begin_subfile: break
# if the subfile does not contain any particle move to next subfile
if begin>end_subfile:
begin_subfile = end_subfile; continue
print 'Working with subfile %03d'%i
pos = rs.read_block(snapshot, 'POS ', parttype=ptype,
verbose=False)/1e3
pos = pos.astype(np.float32)
vel = rs.read_block(snapshot, 'VEL ', parttype=ptype,
verbose=False)/np.sqrt(1.0+redshift) #km/s
if ptype==0:
MHI = rs.read_block(snapshot, 'NH ', parttype=0,
verbose=False)#HI/H
mass = rs.read_block(snapshot, 'MASS', parttype=0,
verbose=False)*1e10
SFR = rs.read_block(snapshot, 'SFR ', parttype=0,
verbose=False)
indexes = np.where(SFR>0.0)[0]; del SFR
# find the metallicity of star-forming particles
metals = rs.read_block(snapshot, 'GZ ', parttype=0, verbose=False)
metals = metals[indexes]/0.0127
# find densities of star-forming particles: units of h^2 Msun/Mpc^3
rho = rs.read_block(snapshot, 'RHO ', parttype=0,
verbose=False)*1e19
Volume = mass/rho #(Mpc/h)^3
radii = (Volume/(4.0*np.pi/3.0))**(1.0/3.0) #Mpc/h
# find density and radius of star-forming particles
radii_SFR = radii[indexes]
rho = rho[indexes]
# find HI/H fraction for star-forming particles
MHI[indexes] = HIL.Rahmati_HI_Illustris(rho, radii_SFR, metals,
redshift, h, TREECOOL_file,
Gamma=None, fac=1,
correct_H2=True) #HI/H
MHI *= (0.76*mass)
if ptype==1:
radii = rs.read_block(snapshot, 'SFHS', parttype=1,
verbose=False)/1e3 #Mpc/h
mass = np.ones(len(radii))*massarr[1]
# find the indexes of current subfile that contribute to halo
begin_array = begin - begin_subfile
end_array = begin_array + (end-begin)
if end>end_subfile:
end_array = end_subfile - begin_subfile
begin = end_subfile
new_size = particles + (end_array - begin_array)
pos_f.resize((new_size,3))
pos_f[particles:] = pos[begin_array:end_array]
vel_f.resize((new_size,3))
vel_f[particles:] = vel[begin_array:end_array]
if ptype==0:
mass_f.resize((new_size,))
mass_f[particles:] = mass[begin_array:end_array]
MHI_f.resize((new_size,))
MHI_f[particles:] = MHI[begin_array:end_array]
radii_f.resize((new_size,))
radii_f[particles:] = radii[begin_array:end_array]
if ptype==1:
radii_f.resize((new_size,))
radii_f[particles:] = radii[begin_array:end_array]
mass_f.resize((new_size,))
mass_f[particles:] = mass[begin_array:end_array]
particles = new_size
begin_subfile = end_subfile
f.close()
print 'Halo mass = %.3e'%halo_mass[halo_number]
print 'Halo pos =',halo_pos[halo_number]
print 'Number of particles in the halo = %ld'%particles
