def load_zeldovich_cholla(nSnap):
data_cholla = load_snapshot_data(nSnap, chollaDir, format='old')
current_z = data_cholla['current_z']
dens_dm_cholla = data_cholla['dm']['density'][...]
dens_ch = data_cholla['gas']['density'][...][:, j_indx, i_indx]
vel_x_ch = data_cholla['gas']['momentum_x'][...][:, j_indx,
i_indx] / dens_ch
vel_y_ch = data_cholla['gas']['momentum_y'][...][:, j_indx,
i_indx] / dens_ch
vel_z_ch = data_cholla['gas']['momentum_z'][...][:, j_indx,
i_indx] / dens_ch
E_ch = data_cholla['gas']['Energy'][...][:, j_indx, i_indx]
U_ch = data_cholla['gas']['GasEnergy'][...][:, j_indx, i_indx]
Ekin_ch = 0.5 * dens_ch * (vel_x_ch * vel_x_ch + vel_y_ch * vel_y_ch +
vel_z_ch * vel_z_ch)
temp_ch = get_temp(U_ch / dens_ch * 1e6, mu=1)
t_min = 0.1
temp_ch[temp_ch < t_min] = t_min
data_ch = [
dens_ch,
vel_x_ch,
temp_ch,
]
return data_ch, current_z
distribution[nSnap]['enzo'] = {}
data_enzo = load_snapshot_enzo(nSnap, enzo_dir, particles=True)
current_z_enzo = data_enzo['current_z']
dens_enzo = data_enzo['gas']['density'][...]
vel_enzo = np.abs(data_enzo['gas']['momentum_x'][...] /
dens_enzo).flatten()
vel_dm_enzo = np.abs(data_enzo['dm']['vel_x'][...]).flatten()
hist_vel_enzo, bin_egdes = np.histogram(vel_enzo, bins_vel, density=True)
hist_vel_dm_enzo, bin_egdes = np.histogram(vel_dm_enzo,
bins_vel,
density=True)
distribution[nSnap]['enzo']['vel_gas'] = hist_vel_enzo
distribution[nSnap]['enzo']['vel_dm'] = hist_vel_dm_enzo
distribution[nSnap]['cholla'] = {}
data_cholla = load_snapshot_data(nSnap, cholla_dir)
current_z_cholla = data_cholla['current_z']
distribution[nSnap]['current_z'] = current_z_cholla
dens_cholla = data_cholla['gas']['density'][...]
vel_cholla = np.abs(data_cholla['gas']['momentum_x'][...] /
dens_cholla).flatten()
vel_dm_cholla = np.abs(data_cholla['dm']['vel_x'][...]).flatten()
hist_vel_cholla, bin_egdes = np.histogram(vel_cholla,
bins_vel,
density=True)
hist_vel_dm_cholla, bin_egdes = np.histogram(vel_dm_cholla,
bins_vel,
density=True)
bin_centers = 0.5 * (bin_egdes[:-1] + bin_egdes[1:])
distribution[nSnap]['bin_centers'] = bin_centers
distribution[nSnap]['cholla']['vel_gas'] = hist_vel_cholla
]
field_labels = [
r'$\rho_{DM}$',
r'$\rho_{b}$',
r'$\rho_{HI}$',
r'$T$',
]
code_labels = [' (Enzo)', ' (Cholla)']
nSnap = 33
# n_snapshots = 10
# snapshots = range(0, n_snapshots)
# for nSnap in snapshots:
#
data_ch = {}
data_cholla = load_snapshot_data(nSnap, chollaDir_uv, cool=True)
current_z_ch = data_cholla['current_z']
current_a_ch = data_cholla['current_a']
for i, field in enumerate(fields):
# weight = data_cholla['gas'][field]
# if field == 'temperature': weight = data_cholla['gas']['density']
if field == 'density_dm':
data = data_cholla['dm']['density'][...]
weight = data_cholla['dm']['density'][...]
else:
data = data_cholla['gas'][field][...]
if field == 'HI_density':
data[data > data.mean() * 2000] = data.mean() * 2000
weight = data_cholla['gas']['density']
data_weight = data * weight
T0 = 231. #K
z_0 = 100.
scale_0 = 1. / (z_0 + 1)
# snapshots = range(0,36)
# catalogs = load_listFiles( snapshots, halosDir )
z_list = []
t_cosmo_list = []
t_vir_list = []
halo_fracc_list = []
nSnap = 35
for nSnap in range(36):
data_cholla = load_snapshot_data(nSnap, snapshotsDir, hydro=False)
dens_dm = data_cholla['dm']['density'][...]
# dens_gas = data_cholla['gas']['density'][...]
current_a = data_cholla['current_a']
current_z = data_cholla['current_z']
M_total = dens_dm.sum() * dv
t_cosmo = T0 * (scale_0 / current_a)**2
z_list.append(current_z)
t_cosmo_list.append(t_cosmo)
halosData = load_parents_list_file(nSnap, halosDir)
nHalos = halosData['nHalos']
if nHalos == 0:
M_halos = 0
T_halos = 0
# snapshots = [ 0, 2, 4]
n_snapshots = len(snapshots)
if rank >= n_snapshots: exit()
nSnap = snapshots[rank]
# nSnap = 0
n_power_data = 6
ps_all = np.ones([n_power_data, n_kSamples])
# ps_all *= rank
print(" Cholla: ", nSnap)
# if i not in [9]: continue
data_cholla = load_snapshot_data(nSnap, chollaDir_0, cool=True)
current_z_ch = data_cholla['current_z']
dens_dm_cholla = data_cholla['dm']['density'][...]
dens_gas_cholla = data_cholla['gas']['density'][...]
dens_gas_H_cholla = data_cholla['gas']['HI_density'][...]
ps_dm_cholla, k_vals, count_dm_cholla = get_power_spectrum(
dens_dm_cholla, Lbox, nx, ny, nz, dx, dy, dz, n_kSamples=n_kSamples)
ps_gas_cholla, k_vals, count_gas_cholla = get_power_spectrum(
dens_gas_cholla, Lbox, nx, ny, nz, dx, dy, dz, n_kSamples=n_kSamples)
ps_gas_H_cholla, k_vals, count_gas_cholla = get_power_spectrum(
dens_gas_H_cholla, Lbox, nx, ny, nz, dx, dy, dz, n_kSamples=n_kSamples)
# # ps_gas_HII_cholla, k_vals, count_gas_cholla = get_power_spectrum( dens_gas_HII_cholla, Lbox, nx, ny, nz, dx, dy, dz, n_kSamples=n_kSamples)
#
ps_all[0] = ps_dm_cholla
ps_all[1] = ps_gas_cholla
cholla_dir_1 = data_dir + 'cosmo_sims/256_cool_uv_50Mpc/data_hm12_cloudy_single/'
cholla_dir_2 = data_dir + 'cosmo_sims/256_cool_uv_50Mpc/data_pw18_cloudy_single/'
cholla_dir_all = [cholla_dir_0, cholla_dir_1, cholla_dir_2]
# cholla_dir_all = [ cholla_dir_0 ]
n_data = len(cholla_dir_all)
titles = ['HM12 Grackle', 'HM12 Cloudy', 'Puchwein18 Cloudy']
data_all = []
for i, cholla_dir in enumerate(cholla_dir_all):
n_snapshots = 60
z_list, frac_HII_list, frac_HeII_list, frac_HeIII_list = [], [], [], []
for nSnap in range(n_snapshots):
data = load_snapshot_data(nSnap, cholla_dir, single_file=True)
current_z = data['current_z'][0]
dens = data['gas']['density'][...]
dens_HI = data['gas']['HI_density'][...]
dens_HII = data['gas']['HII_density'][...]
dens_HeI = data['gas']['HeI_density'][...]
dens_HeII = data['gas']['HeII_density'][...]
dens_HeIII = data['gas']['HeIII_density'][...]
dens_H = dens_HI + dens_HII
dens_He = dens_HeI + dens_HeII + dens_HeIII
frac_HII = dens_HII.sum() / dens_H.sum()
frac_HeII = dens_HeII.sum() / dens_He.sum()
frac_HeIII = dens_HeIII.sum() / dens_He.sum()
z_list.append(current_z)
frac_HII_list.append(frac_HII)
frac_HeII_list.append(frac_HeII)
# dataDir = '/home/bruno/Desktop/data/'
# dataDir = '/raid/bruno/data/'
Lbox = 50.0 #Mpc/h
nPoints = 2048
chollaDir = dataDir + 'cosmo_sims/{0}_dm_50Mpc/snapshots/'.format(nPoints)
outDir = dataDir + 'cosmo_sims/{0}_dm_50Mpc/power_spectrum/delta_density/'.format(
nPoints)
create_directory(outDir)
nSnap = 0
# snapshots = [ 0, 5, 30, 60, 90, 120, 150, 169 ]
snapshots = [90, 120, 150, 169]
for nSnap in snapshots:
data_cholla = load_snapshot_data(nSnap, chollaDir, hydro=False, cool=False)
current_z = data_cholla['current_z']
dens = data_cholla['dm']['density'][...].astype(np.float32)
# dens_mean = dens.mean()
dens_mean = 87.04988
delta_dens = (dens - dens_mean) / dens_mean
filename = outDir + 'delta_density_{0}.h5'.format(nSnap)
file = h5.File(filename, 'w')
file.create_dataset('delta_density', data=delta_dens)
file.attrs['current_z'] = current_z
print('Saved file: ', filename)
nPoints = 256
nx = nPoints
ny = nPoints
nz = nPoints
ncells = nx * ny * nz
nbins = 1000
n_snapshots = 60
for nSnap in range(n_snapshots):
data_all = []
min_val, max_val = 1e100, -1e100
for i in range(n_data):
data_cholla = load_snapshot_data(nSnap,
cholla_dir_all[i],
single_file=True)
current_z = data_cholla['current_z'][0]
dens = data_cholla['gas']['density'][...].reshape(ncells)
dens /= dens.mean()
temp = data_cholla['gas']['temperature'][...].reshape(ncells)
x_ch, y_ch, z_ch = get_phase_diagram(dens, temp, nbins, ncells)
data_all.append([x_ch, y_ch, z_ch])
min_val = min(min_val, np.min(np.log10(z_ch)))
max_val = max(max_val, np.max(np.log10(z_ch)))
nrows = 1
ncols = n_data
fig, ax_l = plt.subplots(nrows=nrows,
ncols=ncols,
figsize=(9 * ncols, 8 * nrows))
import sys, os import numpy as np # import matplotlib.pyplot as plt import h5py as h5 cosmo_tools = '/home/brvillas/cosmo_tools/' subDirectories = [x[0] for x in os.walk(cosmo_tools)] sys.path.extend(subDirectories) from load_data_cholla import load_snapshot_data, load_snapshot_data_particles from tools import * dataDir = '/data/groups/comp-astro/bruno/data/' nSnap = 0 inDir = dataDir + '1024_cool_uv_50Mpc/snapshots/' data = load_snapshot_data(nSnap, inDir) dens_gas_0 = data['gas']['density'][...] dens_dm_0 = data['dm']['density'][...] pot_0 = data['dm']['grav_potential'][...] inDir = dataDir + '1024_cool_uv_50Mpc/snapshots_summit/' data = load_snapshot_data(nSnap, inDir) dens_gas_1 = data['gas']['density'][...] dens_dm_1 = data['dm']['density'][...] pot_1 = data['dm']['grav_potential'][...]
Lx = Lbox
Ly = Lbox
Lz = Lbox
dx, dy, dz = Lx / (nx), Ly / (ny), Lz / (nz)
n_kSamples = 20
z_list = []
ps_list = []
n_snapshots = 10
snapshots = list(range(n_snapshots))
nSnap = 0
for nSnap in snapshots:
data = load_snapshot_data(nSnap, input_dir, single_file=True)
current_z = data['current_z'][0]
dens = data['gas']['density'][...]
power_spectrum, k_vals, count = get_power_spectrum(dens,
Lbox,
nx,
ny,
nz,
dx,
dy,
dz,
n_kSamples=n_kSamples)
z_list.append(current_z)
ps_list.append(power_spectrum)
z_array = np.array(z_list)
