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plot_matching_stats.py
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import os
import re
import sys
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import yaml
helpers_path = os.path.abspath(sys.path[0]+'/..')
sys.path.append(helpers_path)
import helpers
from helpers import log
def get_old_1p_name(name):
_, param_i, param_value = name.split('_')
j = ['n5', 'n4', 'n3', 'n2', 'n2', '0', '1', '2', '3', '4', '5'].index(param_value)
return f'1P_{(int(param_i)-1)*11 + j}'
base_dir = helpers.Config.get_base_dir()
for sim in ['IllustrisTNG', 'SIMBA']:
run_names = sorted(os.listdir(f'{base_dir}generated/baryon_tree_ml/camels/{sim}/'))
with open(f'{base_dir}downloaded/camels/{sim}_params.txt', 'r') as txt_file:
lines = [line.strip() for line in txt_file]
file_run_names = [line.split(' ')[0] for line in lines]
file_params = np.array([list(map(float, line.split(' ')[1:-1])) for line in lines])
param_names = ['$\Omega_m$', '$\sigma_8$', '$A_{SN1}$', '$A_{AGN1}$', '$A_{SN2}$', '$A_{AGN2}$']
params = np.zeros((len(run_names), 6), dtype=float) # Ω_m, σ_8, A_sn1, A_agn1, A_sn2, A_agn2
matching_stats = []
for i_run, run_name in enumerate(run_names):
log(f'Loading data for {sim}/{run_name}')
data_dir = f'{helpers.Config.get_base_dir()}generated/baryon_tree_ml/camels/{sim}/{run_name}/matching/'
with open(data_dir+'stats.yaml', 'r') as yaml_file:
matching_stats.append(yaml.safe_load(yaml_file))
params[i_run] = file_params[file_run_names.index(run_name)]
# Extract the mass_cuts and snapshots which are available
mass_cuts, plot_snaps = set(), set()
for key in matching_stats[0].keys():
mass_match = re.search('n_matched_(.*)$', key)
if mass_match:
mass_cuts.add(int(float(mass_match.group(1))))
snap_match = re.search('^(\d*)_n_matched', key)
if snap_match:
plot_snaps.add(int(snap_match.group(1)))
log(f'{sim}: Snapshots to plot for: {plot_snaps}')
for plot_snap in plot_snaps:
log(f'{sim}: Plotting for snapshot {plot_snap}')
# TODO: This loop has a memory leak. See https://github.com/matplotlib/matplotlib/issues/20490
for mass_cut in mass_cuts:
n_matched = np.zeros(len(run_names), dtype=int)
n_rockstar = np.zeros(len(run_names), dtype=int)
n_subfind = np.zeros(len(run_names), dtype=int)
for i_run, run_matching_stats in enumerate(matching_stats):
n_matched[i_run] = run_matching_stats[f'{plot_snap}_n_matched_{mass_cut:.2g}']
n_rockstar[i_run] = run_matching_stats[f'{plot_snap}_n_rockstar_{mass_cut:.2g}']
n_subfind[i_run] = run_matching_stats[f'{plot_snap}_n_subfind_{mass_cut:.2g}']
plot_dir = f'/home/rmcg/camels_matching/{sim}/snapshot_{plot_snap}/n_match/'
if not os.path.exists(plot_dir):
os.makedirs(plot_dir)
_, ax = plt.subplots(1, dpi=400)
sorted_args = np.argsort(n_rockstar)
ax.plot(np.arange(len(run_names)), n_rockstar[sorted_args], '-', label='N rockstar')
ax.plot(np.arange(len(run_names)), n_subfind[sorted_args], '-', label='N subfind')
ax.plot(np.arange(len(run_names)), n_matched[sorted_args], '-', label='N matched')
ax.legend()
ax.set_xlabel('Simulation (sorted by N rockstar)')
ax.set_ylabel('N')
ax.set_title(f'{sim} data, Mass cut: {mass_cut:.2g}')
plt.savefig(f'{plot_dir}mass_cut_{mass_cut:.2g}.png')
plt.close()
for i, param_name in enumerate(param_names):
nice_param_name = param_name.replace('$', '').replace('\\', '').replace('{', '').replace('}', '')
plot_dir = f'/home/rmcg/camels_matching/{sim}/snapshot_{plot_snap}/n_match_v_{nice_param_name}/'
if not os.path.exists(plot_dir):
os.makedirs(plot_dir)
_, ax = plt.subplots(1, dpi=400)
sorted_args = np.argsort(params[:, i])
ax.plot(params[:, i][sorted_args], n_rockstar[sorted_args], '-', label='N rockstar')
ax.plot(params[:, i][sorted_args], n_subfind[sorted_args], '-', label='N subfind')
ax.plot(params[:, i][sorted_args], n_matched[sorted_args], '-', label='N matched')
ax.set_xlabel(param_name)
ax.set_ylabel('N')
ax.set_title(f'{sim} data, Mass cut: {mass_cut:.2g}')
ax.legend()
plt.savefig(f'{plot_dir}mass_cut_{mass_cut:.2g}.png')
plt.close()
# There's no point in plotting these for all the simulations
for run_matching_stats, run_name in zip(matching_stats[:10], run_names[:10]):
plot_dir = f'/home/rmcg/camels_matching/{sim}/snapshot_{plot_snap}/mass_comparisons/{run_name}/'
if not os.path.exists(plot_dir):
os.makedirs(plot_dir)
data_dir = f'{helpers.Config.get_base_dir()}generated/baryon_tree_ml/camels/{sim}/{run_name}/matching/'
r_matched_mass = np.load(f'{data_dir}{plot_snap}_r_matched_mass.npy')
s_matched_mass = np.load(f'{data_dir}{plot_snap}_s_matched_mass.npy')
r_unmatched_mass = np.load(f'{data_dir}{plot_snap}_r_unmatched_mass.npy')
r_matched_gas = np.load(f'{data_dir}{plot_snap}_r_matched_gas.npy')
s_matched_gas = np.load(f'{data_dir}{plot_snap}_s_matched_gas.npy')
r_unmatched_gas = np.load(f'{data_dir}{plot_snap}_r_unmatched_gas.npy')
r_matched_stellar = np.load(f'{data_dir}{plot_snap}_r_matched_stellar.npy')
s_matched_stellar = np.load(f'{data_dir}{plot_snap}_s_matched_stellar.npy')
r_unmatched_stellar = np.load(f'{data_dir}{plot_snap}_r_unmatched_stellar.npy')
# TODO: Raise the dpi if I'm going to use these plots for something
_, ax = plt.subplots(1)
ax.plot(r_matched_mass, s_matched_mass, '.')
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_xlabel('Subfind mass [$M_\odot$]', fontsize=13)
ax.set_ylabel('Rockstar mass [$M_\odot$]', fontsize=13)
ax.plot([10**9, 10**14], [10**9, 10**14], 'k--')
frac = r_matched_mass.shape[0] / (r_matched_mass.shape[0]+r_unmatched_mass.shape[0])
log(f'Fraction of snapshot {plot_snap} rockstar halos with match: {frac:.3g}')
plt.savefig(plot_dir+'halo_mass.pdf', dpi=400, bbox_inches='tight')
plt.close()
_, ax = plt.subplots(1)
ax.plot(s_matched_stellar, r_matched_stellar, '.')
ax.plot([np.min(s_matched_stellar), np.max(s_matched_stellar)],
[np.min(s_matched_stellar), np.max(s_matched_stellar)], 'k--')
ax.set_xlabel('Subfind Stellar mass [$M_\odot$]', fontsize=13)
ax.set_ylabel('Rockstar Stellar mass [$M_\odot$]', fontsize=13)
ax.set_xscale('log')
ax.set_yscale('log')
plt.savefig(plot_dir+'stellar_mass.pdf', dpi=400, bbox_inches='tight')
plt.close()
_, ax = plt.subplots(1)
ax.plot(s_matched_gas, r_matched_gas, '.')
ax.plot([np.min(s_matched_gas), np.max(s_matched_gas)],
[np.min(s_matched_gas), np.max(s_matched_gas)], 'k--')
ax.set_xlabel('Subfind Gas mass')
ax.set_ylabel('Rockstar Gas mass')
ax.set_xscale('log')
ax.set_yscale('log')
plt.savefig(plot_dir+'gas_mass.png', dpi=400)
plt.close()
_, ax = plt.subplots(1)
bins = np.arange(8.5, 14.5, 0.5)
with np.errstate(divide='ignore'): # Surpress warnings from log10(0)
ax.hist(np.log10(r_matched_mass), bins=bins, histtype='step',
label='Matched halos', density=True)
ax.hist(np.log10(r_unmatched_mass), bins=bins, histtype='step',
label='Unmatched halos', density=True)
ax.set_xlabel('Halo mass')
ax.set_ylabel('Density')
ax.set_title('Distribution of masses for matched and unmatched halos')
ax.legend()
plt.savefig(plot_dir+'mass_dist.png', dpi=400)
plt.close()
_, ax = plt.subplots(1)
bins = np.arange(6.5, 11.5, 0.5)
with np.errstate(divide='ignore'): # Surpress warnings from log10(0)
ax.hist(np.log10(r_matched_stellar), bins=bins, histtype='step',
label='Matched halos', density=True)
ax.hist(np.log10(r_unmatched_stellar), bins=bins, histtype='step',
label='Unmatched halos', density=True)
ax.set_xlabel('Stellar mass')
ax.set_ylabel('Density')
ax.set_title('Distribution of masses for matched and unmatched halos')
ax.legend()
plt.savefig(plot_dir+'stellar_dist.png', dpi=400)
plt.close()
# https://physics.stackexchange.com/a/559650/180586
fig, axs = plt.subplots(2, dpi=300)
for run_name in run_names[:10]:
log(f'Loading ages and redshifts for {sim}/{run_name}')
generated_data_dir = f'{helpers.Config.get_base_dir()}generated/baryon_tree_ml/camels/{sim}/{run_name}/'
with open(generated_data_dir+'redshifts.yaml', 'r') as yaml_file:
redshifts = yaml.safe_load(yaml_file)
with open(generated_data_dir+'ages.yaml', 'r') as yaml_file:
ages = yaml.safe_load(yaml_file)
axs[0].plot(range(34), [redshifts[i] for i in range(34)])
axs[1].plot(range(34), [ages[i] for i in range(34)])
axs[0].set_xlabel('Snapshot')
axs[0].set_ylabel('z')
axs[1].set_xlabel('Snapshot')
axs[1].set_ylabel('Ages')
plt.tight_layout()
plt.savefig(f'/home/rmcg/camels_matching/{sim}_redshift_range.png')
plt.close()
# TODO: For each set of cosmological parameters plot n_subfind_Illustris vs n_subfind_simba
# This data is taken from compare/fraction_trackable using TNG100-2
snaps = [4, 10, 18, 33]
redshifts = [3, 2, 1, 0]
tng_mass_cuts = {
10**9: {
'frac_has_merger_tree': [0.44, 0.56, 0.7, 1],
'frac_has_stellar_mass': [0.08, 0.11, 0.13, 0.13],
},
10**10: {
'frac_has_merger_tree': [0.95, 0.98, 0.99, 1],
'frac_has_stellar_mass': [0.31, 0.4, 0.47, 0.53],
},
}
for sim in ['IllustrisTNG', 'SIMBA']:
log(f'Tracking {sim} halos')
data_dir = f'{base_dir}generated/baryon_tree_ml/camels/{sim}/'
run_names = sorted(os.listdir(data_dir))
frac_has_merger_tree, frac_has_stellar_mass = {}, {}
for mass_cut in tng_mass_cuts:
frac_has_merger_tree[mass_cut] = {snap: [] for snap in snaps}
frac_has_stellar_mass[mass_cut] = {snap: [] for snap in snaps}
for run_name in run_names:
histories = pd.read_pickle(f'{data_dir}/{run_name}/histories.pickle')
for mass_cut in tng_mass_cuts:
mass_cut_histories = histories[histories['33dm_sub_mass'] > mass_cut]
for snap in snaps:
merger_tree_frac = np.sum(mass_cut_histories['lowest_snap'] <= snap) / mass_cut_histories.shape[0]
frac_has_merger_tree[mass_cut][snap].append(merger_tree_frac)
stellar_mass_frac = np.sum(mass_cut_histories[str(snap)+'stellar_mass'] != 0)
stellar_mass_frac /= mass_cut_histories.shape[0]
frac_has_stellar_mass[mass_cut][snap].append(stellar_mass_frac)
for mass_cut in tng_mass_cuts:
_, ax = plt.subplots(1, dpi=400)
sorted_args = np.argsort(frac_has_stellar_mass[mass_cut][33])
for i_snap, snap in enumerate(snaps):
p = ax.plot(range(len(run_names)), np.array(frac_has_merger_tree[mass_cut][snap])[sorted_args],
'-', label=f'$z={redshifts[i_snap]}$')
ax.plot(range(len(run_names)), np.array(frac_has_stellar_mass[mass_cut][snap])[sorted_args],
'--', color=p[0].get_color())
ax.plot(range(len(run_names)),
tng_mass_cuts[mass_cut]['frac_has_merger_tree'][i_snap]*np.ones(len(run_names)),
'-', color=p[0].get_color(), alpha=0.5)
ax.plot(range(len(run_names)),
tng_mass_cuts[mass_cut]['frac_has_stellar_mass'][i_snap]*np.ones(len(run_names)),
'--', color=p[0].get_color(), alpha=0.5)
ax.plot([0], [0], 'k-', label='Fraction with merger trees')
ax.plot([0], [0], 'k--', label='Fraction with stellar mass')
ax.plot([0], [0], 'r-', label='Camels')
ax.plot([0], [0], 'r-', label='TNG100-2', alpha=0.5)
ax.set_ylim(-0.15, 1.05)
ax.legend(ncol=4, loc=(0.015, 0.01), fontsize=8.5)
ax.set_xlabel('Simulation (sorted by frac stellar mass at $z=0$)')
ax.set_ylabel('Fraction')
ax.set_title(f'Halo tracking information, $z=0$ mass cut: {mass_cut:.2g}')
if not os.path.exists('/home/rmcg/camels_matching'):
os.makedirs('/home/rmcg/camels_matching')
plt.savefig(f'/home/rmcg/camels_matching/{sim}_trackable_{mass_cut:.2g}.png')
plt.close()
log('Job finished')