commit ae8bacd6a60138be2fa9cad93d68a6ca5f072cb5 Author: hoellinger Date: Sat May 17 17:26:25 2025 +0200 initial commit diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..ed7b6b0 --- /dev/null +++ b/.gitignore @@ -0,0 +1,64 @@ +################### +# Compiled source # +################### +*.com +*.class +*.dll +*.exe +*.o +*.so +*/build/* + +############ +# Packages # +############ +# Better to unpack these files and commit the raw source +# git has its own built in compression methods +*.7z +*.dmg +*.gz +*.iso +*.jar +*.rar +*.tar +*.zip + +###################### +# Logs and databases # +###################### +*.log +*.sql +*.sqlite + +###################### +# OS generated files # +###################### +.DS_Store +.DS_Store? +._* +.Spotlight-V100 +.Trashes +ehthumbs.db +Thumbs.db + +##################### +# IDE-related files # +##################### +.vscode* +__pycache__* +*.code-workspace +*.egg-info* + +######## +# Runs # +######## +data/ +examples/ +*.npy +*.h5 +*.fits + +############ +# Notebook # +############ +*.ipynb_checkpoints* diff --git a/README.md b/README.md new file mode 100644 index 0000000..2eeb987 --- /dev/null +++ b/README.md @@ -0,0 +1,3 @@ +# Particle–Particle Particle–Mesh in Simbelmynë + +Personal package for debugging and non-regression tests whilst implementing the P3M algorithm in Simbelmynë. \ No newline at end of file diff --git a/notebooks/0_nonreg.ipynb b/notebooks/0_nonreg.ipynb new file mode 100644 index 0000000..f08f22c --- /dev/null +++ b/notebooks/0_nonreg.ipynb @@ -0,0 +1,1046 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Tristan Hoellinger
\n", + "Institut d'Astrophysique de Paris
\n", + "tristan.hoellinger@iap.fr" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Non-regression tests towards implementing P3M gravity" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set up the environment and parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from wip3m.params import *" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "workdir = ROOT_PATH\n", + "output_path = OUTPUT_PATH\n", + "\n", + "# L = 64 # Box size in Mpc/h\n", + "# L = 32 # Box size in Mpc/h\n", + "L = 16 # Box size in Mpc/h\n", + "# L = 8 # Box size in Mpc/h\n", + "N = 32 # Density grid size\n", + "Np = 32 # Number of dark matter particles per spatial dimension\n", + "Npm = 64 # PM grid size\n", + "n_Tiles = 8\n", + "\n", + "go_beyond_Nyquist_ss = True # for the summary statistics\n", + "\n", + "force = True\n", + "force_hard = True\n", + "\n", + "run_id = \"run13\"\n", + "\n", + "# Good set of parameters for the force diagnostic\n", + "# nPairsForceDiagnostic_pm = nPairsForceDiagnostic_spm = nPairsForceDiagnostic_p3m = 5\n", + "# nBinsForceDiagnostic = 30\n", + "# maxTrialsForceDiagnostic = int(2e9)\n", + "\n", + "# Faster force diagnostic\n", + "nPairsForceDiagnostic_pm = nPairsForceDiagnostic_spm = nPairsForceDiagnostic_p3m = 3\n", + "nBinsForceDiagnostic = 20\n", + "maxTrialsForceDiagnostic = int(1e8)\n", + "\n", + "# Simulation parameters\n", + "# nsteps_cola = 20\n", + "# nsteps_pm = 200\n", + "# nsteps_spm = 200\n", + "# nsteps_p3m = 200\n", + "nsteps_cola = 20\n", + "nsteps_pm = 50\n", + "nsteps_spm = 50\n", + "nsteps_p3m = 50\n", + "# nsteps_cola = 10\n", + "# nsteps_pm = 20\n", + "# nsteps_spm = 20\n", + "# nsteps_p3m = 20" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In principle nothing needs to be changed below this cell." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Automatic reloading of modules\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "from os.path import isfile\n", + "from pathlib import Path\n", + "import numpy as np\n", + "\n", + "from pysbmy.power import PowerSpectrum\n", + "from pysbmy.fft import FourierGrid, read_FourierGrid\n", + "from pysbmy.field import read_field\n", + "from pysbmy.correlations import get_autocorrelation\n", + "\n", + "from wip3m.tools import get_k_max, generate_sim_params, generate_white_noise_Field\n", + "from wip3m.params import params_planck_kmax_missing, cosmo_small_to_full_dict, z2a, BASELINE_SEEDPHASE\n", + "from wip3m.plot_utils import *" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "k_max = 10.883000000000001\n" + ] + } + ], + "source": [ + "corner = -L / 2.0\n", + "RedshiftLPT = 19.0\n", + "RedshiftFCs = 0.0\n", + "ai = z2a(RedshiftLPT)\n", + "af = z2a(RedshiftFCs)\n", + "k_max = get_k_max(L, N) # k_max in h/Mpc\n", + "print(f\"k_max = {k_max}\")\n", + "cosmo = params_planck_kmax_missing.copy()\n", + "cosmo[\"k_max\"] = k_max\n", + "\n", + "wd = workdir + run_id + \"/\"\n", + "simdir = output_path + run_id + \"/\"\n", + "logdir = simdir + \"logs/\"\n", + "if force_hard:\n", + " import shutil\n", + " if Path(simdir).exists():\n", + " shutil.rmtree(simdir)\n", + " if Path(wd).exists():\n", + " shutil.rmtree(wd)\n", + "Path(wd).mkdir(parents=True, exist_ok=True)\n", + "Path(logdir).mkdir(parents=True, exist_ok=True)\n", + "\n", + "input_white_noise_file = simdir + \"input_white_noise.h5\"\n", + "input_seed_phase_file = simdir + \"seed\"\n", + "ICs_path = simdir + \"initial_density.h5\"\n", + "simpath = simdir\n", + "\n", + "# Path to the input matter power spectrum (generated later)\n", + "input_power_file = simdir + \"input_power.h5\"\n", + "\n", + "# Paths the the force diagnostic CSVs\n", + "OutputForceDiagnostic_pm = simdir + \"force_diagnostic_pm.txt\"\n", + "OutputForceDiagnostic_cola = simdir + \"force_diagnostic_cola.txt\"\n", + "OutputForceDiagnostic_spm = simdir + \"force_diagnostic_spm.txt\"\n", + "OutputForceDiagnostic_p3m = simdir + \"force_diagnostic_p3m.txt\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generate the parameter files" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The first preparatory step is to generate all the parameter files required for all the simulations.\n", + "\n", + "To this end we use the `generate_sim_params` function defined in `params.py`." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "common_params = {\n", + " \"Np\": Np,\n", + " \"N\": N,\n", + " \"L\": L,\n", + " \"corner0\": corner,\n", + " \"corner1\": corner,\n", + " \"corner2\": corner,\n", + " \"h\": cosmo[\"h\"],\n", + " \"Omega_m\": cosmo[\"Omega_m\"],\n", + " \"Omega_b\": cosmo[\"Omega_b\"],\n", + " \"n_s\": cosmo[\"n_s\"],\n", + " \"sigma8\": cosmo[\"sigma8\"],\n", + "}\n", + "\n", + "lpt_params = common_params.copy()\n", + "lpt_params[\"method\"] = \"lpt\"\n", + "lpt_params[\"InputPowerSpectrum\"] = input_power_file\n", + "lpt_params[\"ICsMode\"] = 1\n", + "# 0 : the codes generates white noise, then initial conditions\n", + "# 1 : external white noise specified, the code multiplies by the power spectrum\n", + "# 2 : external initial conditions specified\n", + "lpt_params[\"InputWhiteNoise\"] = input_white_noise_file\n", + "\n", + "pm_params = common_params.copy()\n", + "pm_params[\"method\"] = \"pm\"\n", + "pm_params[\"TimeStepDistribution\"] = 0\n", + "pm_params[\"ai\"] = ai\n", + "pm_params[\"af\"] = af\n", + "pm_params[\"RedshiftLPT\"] = RedshiftLPT\n", + "pm_params[\"RedshiftFCs\"] = RedshiftFCs\n", + "pm_params[\"Npm\"] = Npm\n", + "pm_params[\"nsteps\"] = nsteps_pm\n", + "pm_params[\"RunForceDiagnostic\"] = True\n", + "pm_params[\"nPairsForceDiagnostic\"] = nPairsForceDiagnostic_pm\n", + "pm_params[\"nBinsForceDiagnostic\"] = nBinsForceDiagnostic\n", + "pm_params[\"OutputForceDiagnostic\"] = OutputForceDiagnostic_pm\n", + "pm_params[\"maxTrialsForceDiagnostic\"] = maxTrialsForceDiagnostic\n", + "\n", + "cola_params = common_params.copy()\n", + "cola_params[\"method\"] = \"cola\"\n", + "cola_params[\"TimeStepDistribution\"] = 0\n", + "cola_params[\"ai\"] = ai\n", + "cola_params[\"af\"] = af\n", + "cola_params[\"RedshiftLPT\"] = RedshiftLPT\n", + "cola_params[\"RedshiftFCs\"] = RedshiftFCs\n", + "cola_params[\"Npm\"] = Npm\n", + "cola_params[\"nsteps\"] = nsteps_cola\n", + "cola_params[\"RunForceDiagnostic\"] = False\n", + "cola_params[\"RunForceDiagnostic\"] = True\n", + "cola_params[\"nPairsForceDiagnostic\"] = nPairsForceDiagnostic_pm\n", + "cola_params[\"nBinsForceDiagnostic\"] = nBinsForceDiagnostic\n", + "cola_params[\"OutputForceDiagnostic\"] = OutputForceDiagnostic_cola\n", + "cola_params[\"maxTrialsForceDiagnostic\"] = maxTrialsForceDiagnostic\n", + "\n", + "spm_params = common_params.copy()\n", + "spm_params[\"method\"] = \"spm\"\n", + "spm_params[\"EvolutionMode\"] = 5\n", + "spm_params[\"TimeStepDistribution\"] = 0\n", + "spm_params[\"ai\"] = ai\n", + "spm_params[\"af\"] = af\n", + "spm_params[\"RedshiftLPT\"] = RedshiftLPT\n", + "spm_params[\"RedshiftFCs\"] = RedshiftFCs\n", + "spm_params[\"Npm\"] = Npm\n", + "spm_params[\"nsteps\"] = nsteps_spm\n", + "spm_params[\"n_Tiles\"] = n_Tiles\n", + "spm_params[\"RunForceDiagnostic\"] = True\n", + "spm_params[\"nPairsForceDiagnostic\"] = nPairsForceDiagnostic_spm\n", + "spm_params[\"nBinsForceDiagnostic\"] = nBinsForceDiagnostic\n", + "spm_params[\"OutputForceDiagnostic\"] = OutputForceDiagnostic_spm\n", + "spm_params[\"maxTrialsForceDiagnostic\"] = maxTrialsForceDiagnostic\n", + "\n", + "p3m_params = common_params.copy()\n", + "p3m_params[\"method\"] = \"p3m\"\n", + "p3m_params[\"EvolutionMode\"] = 4\n", + "p3m_params[\"TimeStepDistribution\"] = 0\n", + "p3m_params[\"ai\"] = ai\n", + "p3m_params[\"af\"] = af\n", + "p3m_params[\"RedshiftLPT\"] = RedshiftLPT\n", + "p3m_params[\"RedshiftFCs\"] = RedshiftFCs\n", + "p3m_params[\"Npm\"] = Npm\n", + "p3m_params[\"nsteps\"] = nsteps_p3m\n", + "p3m_params[\"n_Tiles\"] = n_Tiles\n", + "p3m_params[\"RunForceDiagnostic\"] = True\n", + "p3m_params[\"nPairsForceDiagnostic\"] = nPairsForceDiagnostic_p3m\n", + "p3m_params[\"nBinsForceDiagnostic\"] = nBinsForceDiagnostic\n", + "p3m_params[\"OutputForceDiagnostic\"] = OutputForceDiagnostic_p3m\n", + "p3m_params[\"maxTrialsForceDiagnostic\"] = maxTrialsForceDiagnostic" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[17:15:43|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n", + "[17:15:43|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/example_lpt.sbmy'...\n", + "[17:15:43|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/example_lpt.sbmy' done.\n", + "[17:15:43|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Parameter file written to /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/example_lpt.sbmy\n", + "PM nsteps = 50:\n", + "[17:15:43|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Time-stepping distribution file: /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_pm.h5\n", + "[17:15:43|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_pm.h5'...\n", + "[17:15:43|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_pm.h5' done.\n", + "[17:15:43|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_pm.h5'...\n", + "[17:15:43|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_pm.h5' done.\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_pm.sbmy'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_pm.sbmy' done.\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Parameter file written to /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_pm.sbmy\n", + "COLA nsteps = 20:\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Time-stepping distribution file: /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps20_ts_cola.h5\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps20_ts_cola.h5'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps20_ts_cola.h5' done.\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps20_ts_cola.h5'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps20_ts_cola.h5' done.\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps20_example_cola.sbmy'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps20_example_cola.sbmy' done.\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Parameter file written to /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps20_example_cola.sbmy\n", + "SPM nsteps = 50:\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Time-stepping distribution file: /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_spm.h5\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_spm.h5'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_spm.h5' done.\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_spm.h5'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_spm.h5' done.\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_spm.sbmy'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_spm.sbmy' done.\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Parameter file written to /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_spm.sbmy\n", + "P3M nsteps = 50:\n", + "[17:15:44|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Time-stepping distribution file: /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_p3m.h5\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_p3m.h5'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_p3m.h5' done.\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_p3m.h5'...\n", + "[17:15:44|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_ts_p3m.h5' done.\n", + "[17:15:45|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n", + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_p3m.sbmy'...\n", + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_p3m.sbmy' done.\n", + "[17:15:45|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Parameter file written to /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/run13/nsteps50_example_p3m.sbmy\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "reset_plotting() # Default style for Simbelmynë\n", + "generate_sim_params(lpt_params, ICs_path, wd, simdir, None, force)\n", + "\n", + "print(f\"PM nsteps = {nsteps_pm}:\")\n", + "file_ext = f\"nsteps{nsteps_pm}\" # \"pm\" is already in the filename\n", + "generate_sim_params(pm_params, ICs_path, wd, simdir, file_ext, force)\n", + "\n", + "print(f\"COLA nsteps = {nsteps_cola}:\")\n", + "file_ext = f\"nsteps{nsteps_cola}\" # \"cola\" is already in the filename\n", + "generate_sim_params(cola_params, ICs_path, wd, simdir, file_ext, force)\n", + "\n", + "print(f\"SPM nsteps = {nsteps_spm}:\")\n", + "file_ext = f\"nsteps{nsteps_spm}\" # \"spm\" is already in the filename\n", + "generate_sim_params(spm_params, ICs_path, wd, simdir, file_ext, force)\n", + "\n", + "print(f\"P3M nsteps = {nsteps_p3m}:\")\n", + "file_ext = f\"nsteps{nsteps_p3m}\" # \"p3m\" is already in the filename\n", + "generate_sim_params(p3m_params, ICs_path, wd, simdir, file_ext, force)\n", + "setup_plotting() # Reset plotting style for this project" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generate the initial phase" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "generate_white_noise_Field(\n", + " L=L,\n", + " size=N,\n", + " corner=corner,\n", + " seedphase=BASELINE_SEEDPHASE,\n", + " fname_whitenoise=input_white_noise_file,\n", + " seedname_whitenoise=input_seed_phase_file,\n", + " force_phase=force,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generating the input power spectrum" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The second preparatory step is to compute the initial power spectrum to be used in the simulations, given the cosmological parameters and prescription specified in ``params.py``. The power spectrum is saved in `input_power_file`." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Setting up Fourier grid...\n", + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Setting up Fourier grid done.\n", + "[17:15:45\u001b[00m|[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Write power spectrum in data file '/Users/hoellinger/WIP3M/run13/input_power.h5'...\n", + "\u001b[38;5;113mSTATUS \u001b[00m]|Computing normalization of the power spectrum...\n", + "[17:15:45\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Computing normalization of the power spectrum done.\n", + "[17:15:45\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Computing power spectrum...\n", + "[17:15:45\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Computing power spectrum done.\n", + "[17:15:45|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mL0=16, L1=16, L2=16\u001b[00m\n", + "[17:15:45|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mN0=32, N1=32, N2=32, N2_HC=17, N_HC=17408, NUM_MODES=464\u001b[00m\n", + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Write power spectrum in data file '/Users/hoellinger/WIP3M/run13/input_power.h5' done.\n" + ] + } + ], + "source": [ + "# If cosmo[\"WhichSpectrum\"] == \"class\", then the module classy is required.\n", + "if not isfile(input_power_file) or force:\n", + " Pk = PowerSpectrum(L, L, L, N, N, N, cosmo_small_to_full_dict(cosmo))\n", + " Pk.write(input_power_file)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Setting up Fourier grid...\n", + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Setting up Fourier grid done.\n", + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Write Fourier grid in data file '/Users/hoellinger/WIP3M/run13/input_ss_k_grid.h5'...\n", + "[17:15:45|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mL0=16, L1=16, L2=16\u001b[00m\n", + "[17:15:45|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mN0=32, N1=32, N2=32, N2_HC=17, N_HC=17408, NUM_MODES=40\u001b[00m\n", + "[17:15:45|\u001b[38;5;113mSTATUS \u001b[00m]|Write Fourier grid in data file '/Users/hoellinger/WIP3M/run13/input_ss_k_grid.h5' done.\n" + ] + } + ], + "source": [ + "# k grid used to compute the final overdensity power spectrum\n", + "Pinit = 100\n", + "trim_threshold = 100 # Merge bins until this minimum number of modes per bin is reached\n", + "log_kmin = np.log10(2 * np.pi / (np.sqrt(3) * L)) # Minimum non-zero k in h/Mpc\n", + "if go_beyond_Nyquist_ss:\n", + " k_max_ss = get_k_max(L, N)\n", + "else:\n", + " k_max_ss = get_k_max(L, N) / np.sqrt(3) # 1D Nyquist frequency\n", + "Pbins_left_bnds = np.logspace(log_kmin, np.log10(k_max_ss), Pinit + 1, dtype=np.float32)\n", + "Pbins_left_bnds = Pbins_left_bnds[:-1]\n", + "input_ss_file = simdir + \"input_ss_k_grid.h5\"\n", + "Gk = FourierGrid(\n", + " L,\n", + " L,\n", + " L,\n", + " N,\n", + " N,\n", + " N,\n", + " k_modes=Pbins_left_bnds,\n", + " kmax=k_max_ss,\n", + " trim_bins=True,\n", + " trim_threshold=trim_threshold,\n", + ")\n", + "Gk.write(input_ss_file)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Running the simulations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We are now ready to run the actual simulations using the Simbelmynë executable. Warning: the following may take some time, even in relatively low dimension, and should not be run on a login node." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "vscode": { + "languageId": "shellscript" + } + }, + "outputs": [], + "source": [ + "%%capture\n", + "\n", + "if not isfile(ICs_path) or not isfile(simdir + \"lpt_density.h5\") or not isfile(simdir + \"lpt_particles.gadget3\") or force:\n", + " !simbelmyne {wd}example_lpt.sbmy {logdir}lpt.txt\n", + "\n", + "file_ext = f\"nsteps{nsteps_pm}\" # \"pm\" is already in the filename\n", + "if not isfile(simdir + f\"{file_ext}_final_density_pm.h5\") or force:\n", + " !simbelmyne {wd}{file_ext}_example_pm.sbmy {logdir}{file_ext}_pm.txt\n", + "\n", + "file_ext = f\"nsteps{nsteps_cola}\" # \"cola\" is already in the filename\n", + "if not isfile(simdir + f\"{file_ext}_final_density_cola.h5\") or force:\n", + " !simbelmyne {wd}{file_ext}_example_cola.sbmy {logdir}{file_ext}_cola.txt\n", + "\n", + "file_ext = f\"nsteps{nsteps_spm}\" # \"spm\" is already in the filename\n", + "if not isfile(simdir + f\"{file_ext}_final_density_spm.h5\") or force:\n", + " !simbelmyne {wd}{file_ext}_example_spm.sbmy {logdir}{file_ext}_spm.txt\n", + "\n", + "file_ext = f\"nsteps{nsteps_p3m}\" # \"p3m\" is already in the filename\n", + "if not isfile(simdir + f\"{file_ext}_final_density_p3m.h5\") or force:\n", + " !simbelmyne {wd}{file_ext}_example_p3m.sbmy {logdir}{file_ext}_p3m.txt" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "vscode": { + "languageId": "shellscript" + } + }, + "source": [ + "The logs can be monitored in the corresponding files in the `logdir` directory." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plot results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot the evolved dark matter density fields" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/lpt_density.h5'...\n", + "[17:16:31|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/lpt_density.h5' done.\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps20_final_density_cola.h5'...\n", + "[17:16:31|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps20_final_density_cola.h5' done.\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_pm.h5'...\n", + "[17:16:31|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_pm.h5' done.\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_spm.h5'...\n", + "[17:16:31|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_spm.h5' done.\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_p3m.h5'...\n", + "[17:16:31|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:31|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_p3m.h5' done.\n" + ] + } + ], + "source": [ + "slice_ijk = (N // 2, slice(None), slice(None))\n", + "DELTA_LPT = read_field(simdir + \"lpt_density.h5\").data[slice_ijk]\n", + "DELTA_COLA = read_field(simdir + f\"nsteps{nsteps_cola}_final_density_cola.h5\").data[slice_ijk]\n", + "DELTA_PM = read_field(simdir + f\"nsteps{nsteps_pm}_final_density_pm.h5\").data[slice_ijk]\n", + "DELTA_SPM = read_field(simdir + f\"nsteps{nsteps_spm}_final_density_spm.h5\").data[slice_ijk]\n", + "DELTA_P3M = read_field(simdir + f\"nsteps{nsteps_p3m}_final_density_p3m.h5\").data[slice_ijk]\n", + "diff_p3m_pm = DELTA_P3M - DELTA_PM\n", + "diff_p3m_spm = DELTA_P3M - DELTA_SPM" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "max(DELTA_PM) = 70.734375, min(DELTA_PM) = -1.0\n", + "max(DELTA_P3M) = 64.60250091552734, min(DELTA_P3M) = -1.0\n", + "max(diff) = 3.7952804565429688, min(diff) = -14.139030456542969\n" + ] + } + ], + "source": [ + "print(f\"max(DELTA_PM) = {np.max(DELTA_PM)}, min(DELTA_PM) = {np.min(DELTA_PM)}\")\n", + "print(f\"max(DELTA_P3M) = {np.max(DELTA_P3M)}, min(DELTA_P3M) = {np.min(DELTA_P3M)}\")\n", + "print(f\"max(diff) = {np.max(diff_p3m_pm)}, min(diff) = {np.min(diff_p3m_pm)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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6C+vFwub2IrMr9bhiAV2M7Qwv8lG8f8v3a7cFlKdOnVrmLQMYf+VxaPud34c93q0a6+Nv9HvSK06UtRfGj20c5iKwWMTfnn2ibcXoYXDdMtmzzz6b+ndiv+88bol9t/0imOUUF81UFaAGoLvIXdevX29d1B9zNuXNjNqzXXwdeS0yafxM/Gz8Tnw9bCGAdjImMA5kbQB6JWsD45BNo0hdnO+PvJfV71TdgDH+RnaWlZkBJoPcDNC/9nVk+haYXvoCAKaB8Q4I+gJgWAr+AcCEL4YrDxIyijEsp1iQUN5dtixaCMDyFPKJBdSjUBSv/NtZhQarChlmFxTs53HFArx2MbnX753t6V7Ir1y43p4p2rl7CkD/jh492upXM3NBHKtWHa/2e9Irtq395zMuYGovvh9tx98ABhN9R9W+XhZrzlS1/8eFjcutfGzd5vUA6G3uJOZuyoslm81m6yO+vnz5cnHu3LnWz1Qd92eQMYFxIGsD0C9ZGxjlbFrmyzhPtGnTpsp1Hv3qtm6yjiwrMwNMDrkZYLAi253FSoHpoS8AYBoY74CgLwCGpeAfAEzwYrjyJH/nnQXHRfmYVTYHWB4xrlRNLj333HPFSsooKhTF3ToLGcbC5rhr7UppXzxXeuaZZ4x7Ca91Z3aqWuwYz/P58+eXeesAxrt/jb6zavwaVlX+iL91+vTpvooWl2J8zxjjO4+lFYuF4XS70CX7YsfIgZ3zYHEssNw5Ox5X1bYAMD5kTGBcyNoAjBtZGybXsNn0woULrc+RMeMj8ubu3buH3q6q7FjHDRllZgAyyc3AuNi3b99D/46+xfpcmD76AgCmgfEOCPoCYFgK/gHABC+Gu3btWuvzShYzGsbOnTsfehwA1OvZZ5995HtRFK+uO9D2KsaxPXv2pBcSyigkOIxYONd5N3V3zR1OTIzGc9g5adr571LcgRmA3pTHnp1jV4ZuFxz1evFX5wL0YXND57aVYoyx2B2Gn+fp1FmYO0NV/uuniGiG+Hvtd+8DYLzImMA4kbUBGCeyNky2YbNpVWG8uCHysMX5qtZPLnaj5WHIzABkkJuBcRLrvjrXmsujMH30BQBMA+MdEPQFwLAU/AOACV4MVy6A6/a7o65caLfcd7gFmEYxnlQtkK4qlLcSjhw5MtSdbjvHklgANwp3Mq96fqu2l96UBfwOHjz40Pfjta5a9Ljci+oBxlWMS5ETOu/0nql9QXkp/mYvY2JnYcDMY+DOthSLhcF1uyFFHRdVdubBfoqIZh1fRf9VR5FUAJaHjAmME1kbgHEia8NkqyubjtMNg2VmADLIzcC46VznHZlUsQOYPvoCAKaB8Q4I+gJgGAr+AcAEL4YrF7p1+91RV1Y3v3z58kpvCsDEqyo8FwXSRmUMGabA0NGjR1MLCGaK57eqEF3VNrO0uNtwPKedd0gJ+/fvf+R7MZG6WPFkAL7s/PnzD76OE1BxoVJVoeBh7N69u/L7Fy5c6KkYYbvM/NI5psRzoTAvDGaxPJ+9X8W+29kXRF9RR8GTbhfgVOV8AMaDjAmMG1kbgHEha8PkGzabdusTduzYUWSr6yZXMjMAw5KbgXFUdSP2WJ9rjS5MF30BANPAeAcEfQEwDAX/AGCCF8OV3x+VYk2DPu5xukMvwDiKSaSqhcVVdx1fSYPcfTwKwHWOkzG2VBWEWylVz3NsN/0pJ0O7LVzv9v1Tp07Vul0Ak6DMCbGgPPrbGKe2b9+eeiJqkCL3ncUIS5njfNUFZFV/Exg9VTl7OU6gx/FH9BOjdjwFQO9kTIDFydoADErWBpZy5syZR7537NixoYvzVZ1vqnNNpcwMwDDkZmBcVa3zjpvLLlfxa2A06AsAmAbGOyDoC4BBKfgHABOsPCAY54J/mzdvdtdAgJodPnz4ke/FYuldu3YVo2T//v0pj23fvn3FKKl6nmPsO378+Ipsz7gqC/cttnC9ahLVXVMAlnb16tWex9lhjv2qLHU8eO7cuYf+PewFX52q2nvhhRdS/wZMi8X25+x9t1v2O3HiRFG306dPj+TxFAC9kzGBcSNrAzAuZG2YfMNm0yhmdP369Va+jI/Lly8Xhw4dqmW7qoodZZGZARiG3AyMqyNHjlR+f/fu3cu+LcDK0RcAMA2Md0DQFwCDUvAPACZ4MVxZlKGOCzmWSxQrvHbt2kpvBsDEunTpUuUdI0atKN4gd6mNu85WjZ9xl4xRU7XYejkWe0+SKNwX75HFCh13e+0V/QMYTOZdp5Y6ru3mwoULD/27joL3ndsW+QnoX7f5nbpuVFF1UWP0W3Xvw5Hjqy7mBGB8yJjAuJG1ARgXsjZMvoxsGvtx5L74yOgnuvUDda4dkZkBGIbcDIyr6FuqCnZHFh7FtdtAPfQFAEwD4x0Q9AXAoBT8A4AJXgwXRY7GudhfiO3PLCIBQG9F5UZ1Qqmfon+dd7pdjru0D6rqrh0x/i1W8JevOHnyZOvz/v37F/25WFBflY0UVwRY3NatWyu/n3m82W3Me+qppxb9vc5F55s3by6ydR53dy6uB3rT7SKRfgt796PquKbO7FdesHnw4MHa/gYA9ZMxgXEjawMwLmRtmHwrkU2XcurUqZ4K8mWTmQEYlNwMjLMjR450vTF3udYXmHz6AgCmgfEOCPoCYBAK/gHABC+Gi6IM+/btK8ZZFECqe3EdwDQ7ffr02BTF63e7YlKsaqHaKBbD7Taed3t9eNiZM2dan3u5U33Vz5w/f15xRYBFxHFl1fjZS7/bq26F3hcrcl91nFzHON+5eD7GDOMG9O+FF16o/H6dFx9W9VN1Zuy4WDP6rcX6LgBGm4wJjCNZG4BxIGvDdFiJbLqUqoupjh07VvvflZkBGITcDIy76LP27NnT9big2xoxYLLoCwCYBsY7IOgLgEEo+AcAE7wY7tChQ7XeFXY5xMK3sogPALlisqhqkdaoFsUL27dv7+nn4nFVTYat5F3jBylkeO7cuWXflnETr3UU7IsCwb28b/fv3z9VxRWPHz/e2m8ajUarGPTevXsHujtMPMeHDx9utRXtRHtlm1GgOf6ORZ8wuaJ/ff755x8UY49/x4VQmRdDDVLwr+p36rizfdX44u72UAyUJ6r28bpv9NB5Aj0yS1Vx8AyRs1bywtXlImMCk0zGhPFV5rzIY2W+2LRp00MZY7HcEr8X+WMcydqTQ9YGJpmsDdNhpbLpYtvTmXtiezJvarUYmTmfzAxMOrkZGOf+KzJU5KnFMm/kN2By6QsAmAbGOyDoC4BhKPgHAGNi1BbDATCZY8soF8ULMe7F9i21jd0e26jeyTwW0FUtouv2OPiKcuF2r5Of8d6peh+Me5HkTrHwPCaMY4F6TCDHvnPt2rUHFz3H/1XdEbpTTDzHhdHlgvZoK96r0V48j/HvciF8/Fx8BiZT9J9RiLbZbBbXr19vFZhfjiL3i4350a91Wq6ixe6yBf2JDFJ1YVxm4dBuqi5wrCP7lReOLteFoitBxgSmgYwJ4yf2ncgikRtijjD+HTf9iKwZNxW7ePFi63g2MkVcHB2fo4hDe3G/+DrmGS9fvlyMG1l7MsjawDSQtWHyrWQ27aYq7yznzYdl5jwyMzAt5GZg3ETfEdmqM6t1Fr8uRWarqwg2sHL0BQBMA+MdEPQFQAYF/wBgDIziYjgAxl9c5DhORfHKbYsLNJcqeNvtscVE2qiquhNvjP+9LEieZqdOnWp97mfhetWi+nieJ2nRYtyFPh5P5MUozBX7RHwuJ4/j/8qfqRLPRznxHKKduOA52igvki7/3V6MKxbEx6Q1QL+qitwuNd4vVyGGbmM00LujR48+8r3IJd1ObGeKvqTzIpjy4sdMcZFo1d+aJDImsJKiD4n+o1woFcW64iO+Li/QzujbZUwYL1GkL/qB06dPt7JFFKmPTBFF6iOjlDeQic8xfxiFNSJrxOeyT4nzsONcwEHWngyyNrCSZG1gErJpt+OFzvUWcSywnDfBlJnzyMzASpObAR7tM8rCy+W6r5iHL7NaZNRu+XSc5+SBh+kLAJgGxjsg6AuATAr+AcAYGLXFcABMhm6LXEe5KF6vLly4MJbFDKtMUhG6bPHcxGLKfjNRt5+flLullHeHiQXqcXHzYgWjqxamx4UPnYvlo52q92hMRMfi9/b/i0nrqqKKAN1EX161cHypvqTqd5566qliOVy9enVZ/g5Mgri4pfOiysgOzz333LJtQ1Vx6CgKkyky1CRnIBkTWCnRf2zatKnVh0RfEH1D9AdxgX58xDF+9C3RT8XP7d27d6i5FBkTxkfs99EflDeJ6cwoS+XD+J2YR45+Y1zJ2pNB1gZWiqwNTFo2bVf2X+2ib+vnRoJZZObhyczASpKbAR4V/eHTTz/d6iPLDBUFS6NfbC9ucOTIkcrfj36y/F1gfOkLAJgGxjsg6AuAbAr+AcCIG7XFcABMjm4Ly0a5KN6wj63qzrSjotsdPF544YVl35ZxEZOiYf/+/X39XrzH2+/I3tneuL/3Iz/GY6y6yLlz/y5/vvNC6XIRe68XSndeLBGT0IpVAr2q6n+jH1qqoOty9TNVY7Q+Dno/ud2ZE8qCLN3ybx2qLsTLzH5l4ehJvTmHjAmshDgvEjeliP4jFkHF4qjoQ6L/jn4kLpaPj7hIO/6vvDtq9Mnxe+39UD9kTBgPsa+X+3ncIXmQOe2YH3z++eeLcSVrTwZZG1gJsjYwqdm0fZ+Pom/tBZOiL1uJYn9BZh6OzAysFLkZoFrkova8HXPtL774YuU8/WIZfBLW68I00xcAMA2Md0DQFwB1UPAPAEbYqC2GA2CyVN0NdtSL4g372EZ5/Oz2vFtIV8/C9apF9fFcdxZaHjfl5G9nhlxsPzh16tSDCehyoXxMPFcVRexm3759j3wvFrQC9OL06dOPfK/bna3aXbt2rRi1rAE8enK7XeSLlZjXinzTeVI9cl9W1o4MtlIXiy4HGRNYieP97du3t/qO69evty6eXKqYV8wNxBhT/lz0WXv37u37b8uYMB6effbZ1ufIYMPcwCaySa/FHkaJrD05ZG1gucnawCRn03J7op8r8+iuXbta/d1KFsOTmYcjMwMrQW4G6L7utn3tbdn3dcv+8f1uc/CZmRhYXvoCAKaB8Q4I+gKgLgr+AcCIGrXFcABMlsUWZ437ODOuC8/G/XlfbuUk56AL16sWZ7cv/B7nDBkWe14695F4LuOjvKv9uXPn+n4/Vv18FK8G6KXf6uyXYgH8qBdcWMlF9jDqIlfEnFZngeXYr1dyXquq4HPGnfKiD4vcM8gFO+NCxgSWU/TN0afGuNFv3xE5Mn6n/aLMceqfZUzoTezbZfbI2Md7KTg/KmTtySNrA8tJ1gYmMZvGmoHypspbt25tbU/kp1hnGf3WIFmpDjLz4GRmYLnJzQDVInOX2SxE5j5z5sxAWbjzpt/A+NAXADANjHdA0BcAdZqrtXUAoG+x0CgOAjoXB8XCAXcIBSDLJC/OWuyxbd68uRg341rAsG5lYb5BF0XGYsxdu3Y9krliInZcM1d5sXM/C91LzzzzTOtz+52mB3lO29t31xlGQXlsFe/NcR37YuyK/TIeS/RbkyYeVx0XOAHLP58V/W1cwNKZr6LvinwVJ7lXUmSkzj4nI/tFG2W2nEQyJlSTM+sdU6LPGbR/jscUebJcNBX9WDzGcT3WBxa/YceOHTuGbq/bPOGokLVl7SqyNpNKzq6XrA2MezYtC/tFbumWk8psOmhGqovMPBiZGarJzfWSmwGqc+fx48cfyknPP/98z/1itzn4mO8f9ZvCAl+hLwBgGhjvgKAvAOqm4B8AjICVXgwHAONeFK9XschxFO7e3s8i5HFdmFm3jIXrsbCyM3vF6xDfG7XFpFlFEC9cuFD5/Xjcsdh0mAsfqt7D8b1R3eeYfPH+az/BMs6Po7x4ZBz7psXEovbOviNOXvX6OBXFhTzPPvtsX8cBkVHLi4iq9sUY//ft2zdSF1ZWFXLJyH6RoRa72HDcyZjwKDmzXrEtwxaALi/GLB9fvF779+/v6TyLjAnjcV41W2Sdugr+ydqydjeyNjxMzq6frA2MezYtL5Cq2pbol+Ij1hHER/RLsR4gtm8U8o3MPBiZGR4lN9dPbgZ4WGTWsohp6cyZM31loqq1unXN9wP10BcAMA2Md0DQFwDLQcE/AEgw7ovhAGBciuINa5QXxHUr7DfJBRgHVd6letg7muzZs6fy+zEJO2qLSXtRTgQvtu3dJobjd+q4EGBS+xLGQ3nhTFzkMcr9f6+PpfOE0biLhe2dFyKUBe+B5TfoyePon2Luqvy8c+fO1r48qjeuqDp5Pkz2Ky8inbQ+up2MCY+SM+u9iDKr34jHFedYSnFh+OXLl1PaBkZnHjX64ox5vB07dhR1kbVl7W5kbXiYnF0fWRuYlGwaf3up80gxhkTBv6NHj7b6q/iIdQHPPffcimcdmbl/MjM8Sm6uj9wM8KgYazqLL0e+7jfDdlurGyLTVl0zFX1odpHb8rgmzgns3r279TjGId/F89A+pnQTj+XFF19clse0devWB4VtFxPHcMOu9Wbl6Quq2TcBJovxbjQYX5nmvqAuo9zH2OeZZgr+AUCCcV8MB8D0meQicos9tm5F9UbBuC/CXE6x6D3EnY+HFROoZ8+efeh7p0+fHvpOzSuRR+M9tNQE8gsvvFD5/WEfrzvMMKrOnTu30ptAF50nweKY2OsFKyfz4pVRVnXyPC7+HDQLxe/FPN6k3rBDxoTu5JZ6ZI5F0Vb7QqBYgBN9/jSMdzDpYv63nEuNvJFR8K/Oc7OytqxdRdaGanJ2fWRtYFqyaazDjItr4nHGuagoGBfrAeJjpS+8kZn7IzNDd3JzfeRmgIc9++yzj6xtHvRmrpFdqzJWt0IHcYF9mQVj7Xf8XLd11mWRgfLrdvE78fvxubxgP7Yj+uT2/jorV8ffiCwaf6O9QG95zVg8plj73M95ifjZXp6L+F4UP6/7hrvx3HUrflA+znIt/6Qer0wbfUH3x2LfBJgcxrv+yb7G10m0kn1BXUa5j7HPM81mVnoDAGASxEFps9ns++P69eutu/VdvHixVbgmFpQp9gfAcljsbgbjXnhuXB9bt2KE43AHneUWk2cxKZaRm6ruFB3vk84igONyZ/vOAlrdfq5dZNBhJxnj5EwnE5fAYv14+4mrGOtclAAsl6qLaAbNftGfVeXJSSFjAuMsMmbnvEHdi32A5dGeB8rCHYwGWbt3sjYwzmRtYByU557ai8XFRUa7d+9e0e2SmXsnMwPjTm4Gxl1ZPLszzw6aiboVcu62rjv+VmT6+IjrreLaq6oC3tHXxv+VPxvXZbV/lL8f123FNVzxdbRTrs2OXB3FD9qLtA4iCgJEdo222osdxLVm0f/H44/1csePHy+2b9/eOjbptch0/G7nc1GOKZ1jTfm36xR/u6qgeXw/ti22sdzeqp9jvOgLFn8s9k2AyWC864/sa3ydVCvdF9RllPsY+zzTTME/AACAKdWtkFy3wnOTYJQfW7fJOguGH1ZOnGYtXI+Jwap94dSpU8U4KQtlLXZ3+3iPVb3Pjhw5MvTfjwnLTgpZA91O8Hb24XHyx3gHLJeqiwNjkckgJ/UjW+3bt6+YVDImMO46+6/IolUXgQPjpbNAR+S7jAV9sQhvpYt/jDtZu3eyNjDuZG1gnHJX+zmo6KviYqOVulmkzNw7mRmYBHIzMM6q1ugOU7h0586dQ25Rdc7bsWNHX21EpovH8eKLLz7UT5fFSAY5VojfjeOM6OdjHVxZICH+ThRWiAII5ffLIuAxHsTfW6rAdTdlcYb9+/c/tAY6tr/OsSYKtcRa/Pi73baJyaIv6I99E2A8Ge96J/s+vE1MllHsC+oyqn1MsM8zLeZWegMAAABYGbGoueoOKTHpOu5iwqjqscUdJMatGGFMhPNoIb7Mu2DEIvjOi4I778gy6uLuJ/G+X6xgVtWkZvx8t+Kf/ahq2wXSQJXOviFO8C52oc6o2rx580pvAjBkwef2k8jlxZH95KK4CLNb8ehJIWMC465qTiUWFI5q/pQxoTexILjzTsCx4DLyWSxGHHTeMPoHhiNr907WBsadrA2Mk+if4sKi9jUxzzzzTGVBt7rJzL2TmYFJIDcD4yrWz3auJR82f3b73X7arPrZQbcpfi/WrUXGK7NfrDuPY4c4Vui13citUcwgMnpZ0GSxv1kW/C7XLMdzXf7NQcXfjW3oPF6oQy+Pc5TE+3hcr4uIcTnr+GZQ+oLe+4Iq9k2A8WC8k30nZXyVfSezL6jLKPYxVezzTDIF/wAAAKZUt4J/o1wUb9jHtlJ3ae9Ft23r9+4Yky4mUMsF3VkT0TGh2FnwL8T3xmWiLiYrl5qwjMnTqt/LeO9WvRajuji1/ULw2O6q5wWoR/S37f3FsMX+RuFEFzCeOk/+ltmvn7uvRS6d9KIwMmb/ZEwYLVVzKkvd4VPGhNEX+2nkts48F/PB5d3AI+/FMeikF8AYRbJ2b2Tt/snaMFpkbWCcRNG4yDrt/VQcP5SFw5ebzNwbmbl/MjOMHrkZGFdHjx6tzBp1FBVd6WKjkas3bdr04N+Rp5599tme8nYcV0S2j5/t52ZEx44de2jNcrQTxVPi+/0ox4x4bdqPMeq84fnp06dbBRuq1uiPYuHdcS14Mio3VNYX9NYXdLJvAowX453sOwnjq+w7vGnqC+oiU0N/Zvr8eQAAACZEtztPT8IEX7fHduHChWIULTYRFIvPx11WocVykj/eozEZnfVRXgjcadIWyNd1B/qqdmNitSzMOKomoa+DcRInWdr7i4yTcVUnuq5evVosxzhmkT2Mt6oT8P1c2Bm5NPqBfhatTCoZ82EyJoyWqj4j9tPF5ilkTBgPsfB3sSwWeS3m/GIRYcz/Rf6LBX+jfEOYSSFr55G1HyZrw2iRtYFxExcQVmXPlbhoR2bOIzM/TGaG0SM3A+MoMnJnTs7In936mJXue+Lvd94YPM4n9FJEoCwIEecjtm/f3vPxRfzNznVznUXB+x1vOteaV90EPeuG7aOeiyctH69UsQl9Qe99QTf2TYDRZ7yTfSdlfJV9h/+709QX1EWmhv4o+AfAVHIxBwB0v/P0qN+FICaHl9rGcXts3QoRjvrdwXtRTuZnWO4CfLGIe1JyY513oD916lQt7dbt2rVrK70JMDXi5Ef7hVRZd95ayRNdk3pXLZgWVSd/Iyv1uuAhcum+ffuKaSdjPkrGhNHSLS8udkMIGRPGR2SyzkWCVSKvVBUArCrgwPBk7Ryy9qNkbRgtsjYwbiLvVPVDzz777LJvi8ycQ2Z+lMwMo0duBsbRcmehUeh7qm4aXhY0WUz7eYZYn/7MM8/0/DerbgY/zHmLzsLi/RQV71W0WVXAfFQdOnRorIs1RCaI98lKFXvXF/TeFyzGvgkw2ox3Xyb7jv/4KvsOZxr7grrI1NA7Bf8AmDqZRWcAYJzFRF7VArGl7iI7CkWDlprYXeyOCqNY9C8KH1XJuPP4Sov3U8ZCxHhPxuseE6bNZjP94+LFi5V/9/Tp08UkqNpnuvUBGW3v37+/GHWTcgcjGHUx7raftIn+NuvkV9WJruXKMFEgAhhvVSdlezkBXOZSJ3VlzCoyJoyHxTKjjAnjJfJbFLvoZ9FqWQAw5l77ues4vZO1hydrP0rWhvEgawOjrOr8VBwPrMQxgcw8PJn5UTIzjA+5GRhldWWhqr4ssttKFjpd6lhhqXzV+Zi6FaWu8tRTT6Xmuc4bJPWy/f0oj0XGqfj4sWPHisuXL9ey5nw5Pq5fv95aa7lShVv0BTn7kn0TYLQZ775M9h3/8VX2Hc409gV1kamhdwr+ATB1sorOAMAk6DYRsdhdZFdSudC6lwm8bsWEhrkLTF26LSBfqTuTZGevjAnXuAg31LVwPe4EU7Wdddz1Y1SKSmYU3Ir3btUE9Kjf3T62eZQLm8KkiDGg/e5tcRKu6g5tg6o6tr927Vpa+4u1aV4BJvNYqMyci4mfidyY2Z+NKxnzYTImjI/FFvvImDB+Yg41Fq1G4b9+80Lkjij610sOpHey9vBk7YfJ2jA+ZG1glO3cubPy+6dOnVr2bZGZhyczP0xmhvEiNwOjKvJE1XrmjCxU1e/s2LGjGGVLFQevWnNcVbh1uXSuOc9c/xzHItG+sWI66AseNuyNAuybAKPJePcw2fcrjK/TRV+wPGRqeJSCfwBMnayiMwAwCboVT4uLI0d5sVsvEyh79+6t/P4LL7xQjJJud7WJxzgJmSUeX8YkfrnIvs4iiFX7Q/ZdP1bK6dOnH/ne7t27h2636uKHuLhg1Cc5XcQNy9P/Rz9TXliSXeyv24VZdVzIUtXmSp6gBnJEXuk8GV/eoW0xcYK4riLU40bGfJiMCYMp+966jr2r+o6rV692/XkZE8ZXzBtGwYe463PMb8fdfXs9Do18d/z48dq3cVrI2sOTtR8ma8NgZO2vkLWB0O344OzZs8u+LTLz8GTmh8nMMDi5+SvkZqAqj8Y65owsVNXPZuS3LFWPcamxobPAwLFjx3p+ruJGRp2GXTPeeayQmREdi0wXfcHDhs2J9k2A0WS8e5js+xXG1+kyzX1BXWRq6I2CfwBMnayiMwAwCWJRatUkadXC2FFQTu70MrEbi6OrJoiWWiC93LptT1yQOu7KhYFbt24d+nWPwnt1FvsL3dpfiQX+meL5q+sO9FXPzThMcmbeyQWo9swzzzwYt+so9heWqzBu1Z216ng8wPKryi2L5YSyGHTduXQcyJiPkjGhf4cPHy42bdrUWsQUcwfdbt6Q7amnnur6fzImjL+YE468FmNzHI82m83W51hsvFhWiT5JgYQ8svbgZO1HydrQP1n7YbI2ELqtGV2pGwDKzIOTmR8lM8Ng5OaHyc1AVTbO6htinr6utuuyVIGHyJ9xE6LyZkSHDh0a6rkeNs/G77ePI70UFe9FHIvEuJGRtxkP+oKHDVvsxb4JMJqMdw+Tfb/M+Dp99AXLQ6aGRyn4B8BUySo6AwCTJC507JQ16ZHthRdeaE3w9Lqw7ciRI5WPbZQKuHVbdFu17eM66TnspFz5HNW9iDreV1UTp+O+MLquu82UFxR02rdvXzHKYptX6qINmBaxCD76iDqL/YWqdqsWpQ+r6oKh5VpkD9QrLozszESLHStELuxWNH3ayJgPkzFhsH7k+PHjj/TB2cW2qrLcYn2VjAmTKfbtWGwcC4+jAOCZM2cq9/eYfzSm55C1BydrP0zWhv7J2rI2jHvRpUajUWzfvv3BuaYsi/VRVX1H3WTmwcnMD5OZYTBys9wMPOrq1au19Q0XLlx45HujdEH9oP1i9OndblDfT6bNKuzduc46Y/1ztDEJN7Gnd/qC/Mdu3wQYPca7h8m+X2nD+DpdprkvqItMDb2Z6/HnAGAiZBWdAYBJEhOlMWnSufgzJixGbRIpFtX1M7EbF3HGovBO8dhG4a7n8ZxXLUSOiaJJyCvlxOSwk3LxupcnBuoWk3+dE4DxOsXC7nG9i0pcyNwp47GcOnWqst1Rf+8u1924GQ2xP0dfNM4XOGzevLm1X0WB3lEbl7s95+XFSHUW+yt1Zpg6XuvONsd1PACqxYV6nRfudDvuOH36dGXB9GkkYz5Mxpw+cmY9/Ui3u5pmW2qeQsaE0RbZbceOHUPtN5H14iPmjjsv7I5+cdxvADIqZO3ByNoPk7Wni5ydQ9aWtWFcx4D27Bjn56Po3+XLl9MurIo+erG+YyX6C5l5MDLzw2Tm6SM355Cb5WbgUVX9zc6dO1Pa7izoPQpruJcqAF7XGFVV3DzrJvGx/rx93XwcX8TjGybTxjFLHJsxPfQF+X2BfRNg9BjvHib7fpnxdfpMa19QF5kaeqfgHwBTJavoDABMmlg817kANCY9YtJqVMbNsnjQ/v37+/q9KPrXedFmFNkbhcfW7cLRSVmkXS6MXGzhfK93UF+uu2XEgvrOgn/lwu5xXdhYdYJk9+7daftku373z+UWE7tVzweTKSbus++8vpInPMah4F+Mt+VzvhzF/qoWunc7QTSoqvaisAQwuReSdisQHscQ0Se4i9uXyZhfIWNOHzkz9+93yryAutvfWGqeQsaEYuTH3ui3zpw5M3Rb0Qc+9dRTDy0GjD5ewb8csvZgZO2vkLWni5ydvw2dZG1glHUbAzILcl+7dq3r/61UQTeZeTAy81fIzNNHbs7fhk5yM8DDMtZZV90YvWqd7krpduP2unTeyD7+VtY6u/Lm6u2PKYqHD/p4IiPHtq30entWnr5gOPZNgPFgvMsn+zKORqUviDbi2tzyOuiyuF1sX3zE+YvyfFK8f2N/W+nidTI19G6mj58FgLGXUXQGACZRTO5UTZiOUuG58k7a/S7y63bnl1G4aLNqAWZMMo363cF7VU6gDTPxVb5Oy3WCo5z86zSui2VjMrfqbjPDLpYtCzF2WmqSNH6vswDnYu+fmGzevn17sWnTpqLRaLQ+x7+jQGn7Yvv4euvWrYs+D/E7vf7tYcVz023be11wH23E+y5+Pt7/sf1xkUI8zmirs0hriMcXP9P5N+P3Mxb5Z74my7U/x/g2CX1q9KOjdKK3SnmCKLPYX7y/ltpvq/aFzLvblzcOyL5gCBgdVSdqy4snl7rIclrJmF8mY05nxgxyZo5ur2XmRdTdcuFSWVXGhNFXtThwUHHDmKpiGgxP1u6frP1lsvZ0Zm05O4+s/TBZG0bfYuNeZh+xWLGklbqYR2bun8z8ZTLzdGbmIDfnkZsfJjcD3a6zyhhzyuu42tscpRvfVq0n7yxMkiUyTPs5iHgestezd46vw1wLcPTo0a7r8Jlc+oJ6+gL7JsBoMd59hez7ZcbX6TSKfUHsOzFHHfN1MScY78u4Ruv69evFiy++WDz33HPFzp07H8xtx7x7zCdmzh8OSqaGPjQBYBldvny5GcNP58eZM2eW5e9v3Lix9feuX78+cBtV23/ixInmtPE8AEyec+fOVfbvFy9eHJkMceDAgYF+/9ixY488rsgFw2SCYcW4Wfc2rWT2av/bw4jnJD5W+rWJj9hHxk281lXvs2HFvtjZ7q5du5b8vS1btiz5nog+Z9u2ba2f27NnT+sxxPsp9o34iP+PfTraip9rf706HTp0qLVdVa9nrx/9iO2LbS5/N56neN/ENsfjaH/eYrsW29+rXrtuz3c8B+W+Eo85/h2/Xz5P5e/E8zVIn575mjCZ4j2QnRvKcWSpMSveg3WOc1VjAoy7SZvTKcenYVQdL8T3OvuaYfNgVS5ZrnnRTDKmjCljkqF8TcvzNvFaZ/eJVVmulzFDxoTRVvYbmfPWnfOog+ZjWftRsnZ/ZG1ZW9Ymg6wta8O4ZdNu6xrK8bnuNTHD5C2ZefnJzDKzzEwWuVluBnrLpjFGDqt9/I6PGN8H1bl9w7TVue6t7pwc/Xv7czHssUSMYe3HDu06H9Mgmak8Vus12zE59AXD9QX2TYDxYLyTfdsZX6fXqPUF5bms+P1etqPz3Mak9DH2eaaBdxYAy2oSis6M02K4OnkeAKZnkioWLq60cvHoMMXwqha8Zi4O70c8jnKxYJ0F5VYye5UThsMsrC4nKYedMBxE1fO2Uu+X7EXpw54oCVXv36WyYPl+XGxRfPbEdDzW9o/OfiAeR+fPdH4McoFI9Jvdtj8mksvnLz53+7n4fjyn0S+3L6DvXCwffyvaWWy/7lyo223Se6VPFjCe4n1RR7GF8iRJL++78mKMrBNNi72nM/pQWGmTNqeTsW9W5eYY+zovLBvWpFxQKWPKmEHGZFjl/tvPe6dfVe/zXvtdGRNGVznmZfcf7WP6oPu8rP0oWbs/srasHWRthiVry9owjtm0anuzLqpabD3MsH2FzLz8ZGaZOcjMZJCb5Wagt4vah10PVnXB/zBrwTvbGqZ/bF/3VvdxUzwP7QUfMtYjL1YAobOvH+TvxXPb7fcUQJhs+oLh+gL7JsB4MN7Jvu2Mr9NrlPqC9puA9LMN7XOQk9LH2OeZBt5ZACyrcS86E8ZtMVxdPA8Ak6tqodlKFFzrnOQadoK3W5G9zOJEo/Ycr1T2ap9gbF+IPmh+y1zEP8xrNI4TdJ13hMnIbO2Luvt5bsoLKLr9/eWamG7f5sUW3vejfTK3l/d8++T9YgveF3veY2FveTf5Xib+O3+/lz51uU8WMH7a77yWXbS27DP6+dmMsWepfnQcL3yCSZ/TyboIpfOimfbxL/4vI69PygWVMuajZEwZk8HEe7XOG01UzQP1uohSxoTRVe7bWWNuKfLesHO1snY1Wbt3svajZG1Zm8HI2uM7FkCWccum7cXC4iPG/ey1HN3WAAzTV8jMy09mfpTMLDMzOLl5fMcDoB7tY2X5MeyasM4L8YfNtp3bN2h70fe199NLFRzuR2SheN7KYsftWTxyRdaxzmIFEDoLTAxyHV38TrdtVQBhsukLhusL7JsA48F4J/t2tm98nU6j1BeUa9f6nedvv354UvoY+zzTYKYAgClw48aN4uTJk62vN2/evNKbAwAj7cyZM8WWLVse+t7x48eLs2fPrsj27N27t9i4cWNx7NixodqJNp5//vnK9pfT+fPnH3kut23bNvTjGyVHjx598HXne6kfkd/i94dpY1D79++v/P5K7QeDZuArV6488v1du3YN1e6JEyce+d6ePXuW/L1Tp061Pu/bt2/R901sX+wTvVrpfefSpUsP9SPnzp1b8nfi8R06dOjB63Tw4MElf6fzdYu/e+3atVa/Fv1bL7/f/lzF/hV9+2LG9TVh+TzzzDOtfibe98P2LZ2izV7e2+HAgQMP/Tu2KfatOvrRXvo7YDxVjceRe6IfiHG3Wz6cNjLm8pAxR+81oR6x78b7Lj7qmH/pzITxPpIxYXLEfp5p69atD75+6qmnUtuedrJ2b2Tt5SFrj95rQj1k7S+TtWF8lH1D9CfXr19vjdH9jGfDHEOMQl8hM/dGZl4eMvPovSbUR24enbEQGA3RR3WOkVX5a5DruEpHjhwZuL1htiMeR/TNhw8fLjZt2tTKO2W/Gv3giy++mNIfxuON8w27d+9uZaL4e+WxSDy3O3fu7HksGEb8rfa11/FY+1n/HNsc195lH5cxHvQF9WUj+ybA6DDeyb4l4+t0G6W+oNx/+r2ONn5+ud6/MjXkUfAPgKmQVXQGAKZFVZGdmHzJvohyKTHpG5NAUYQwY5K3qrBetN/LQtMMMYHUWWAwHlc8vkkRCyDbF9AO+rqVE23L9dp0ionFqm0vF2yPg6r9NR7TsHm4apHrUq9TuTg2Fk13e0+Mw8R0lfZ9Ot43vW5/+4R9PPZB+td++8ZYYN++fTG5vtii5XF9TVi+MTreP/E+zC72Fy5cuFDs2LGjp5+N/aBzsfvp06eH3obONsqLVIDRk3FxS9UFedEPxIV+xravkDGXh4w5eq8J9Yj3S/vnOtouxfu6nzwnY8J46FwgOYzLly8/+NqY8xWy9vKRtZeHrD16rwn1kLVlbRg3ZT6pq6hWVdGlrL8nMy8fmXl5yMyj95pQH7lZbgaKJXPQMOubO/vCyLfZBT9ivXKj0Vj0IwoQlIVI4ucjw8f4Hn1gFBzPWqMeou9uNpsPfZRFzeNvxnNSbksdBWcXey2rCl13Ez+7Uuu3GQ36gvrYNwFGh/FuOLIvk2JU+oJyP4kb4/Qr48ZRo9bHLMY+z0RoAsAyunz5cjOGn86PM2fO1PY3L168+NDf2rNnz1DtVW3/iRMnmtPG8wAwHeP2li1blnXcbnfo0KHW3zt27Fh62zFmdT6u+Ht1un79+iPPZ/w7nudJyV7xGDdu3JjyvG7btq31+5HlVsqBAwcqn79xUbX9u3btGrrdQZ6TyOBLvZ7D5PXoJ3p9bTKfj/Lvlh/9vl/L93mvj7uz/xhE7P/t7cQ2rPRrwvgp+5e6xpNz58612o+/088Y1Ot7u1ft43aMbzApJmlOp9z3M/b59szS+ZF1TBLZY6WOr7LImIv/HRlTxmQ0smXneaFBxzoZE0ZT+/xjVg7szGqDkrW7k7WXJmsv/ndkbVmb/snaMN3GMZuW/VYdazeq8uKg43NJZl5+MvPif0dmlpkZjNwM8KjOdcDRHw27fnnY67hKnf1r9I3Rx/byEX199NGDPJ7sdXEZeT9ep8V+v3Mc6fW1LH9vsZ/tzGBy0mTSFwzGvgkwXox39ZF9GScr3Rd0vof7/fvl+3RS+hj7PNPAOwuAZTXORWdK47gYrg6eB4DpEGNp+2LM8qOfAjzDLKTLmuTudfKljuKC3Z7HWDxX98T5cmavbgUiB3lO21+bmOAflZML45Z5sl6PXiZ0e3kfLvZzyzkxnbnYvf1YY5BFsJ0XJCyln+d9MZ3HSFWL9FfiZAHjobyQoa6+MPqMcszs92+UxYIXe28POgaMS98PS6k6uTnO7/H2fTW7vWFP2k/qBZUy5tLbL2PKmAx+HifrpgidfdUw81gyJoyezjEnK0+V7Q46lsvavbcna1eTtZfefllb1qY/sjZMr3HOpmW/lbmt3bLosDcflJmXn8y89PbLzDIz/ZObAZZeXz3INVjta6aHLba9WHarc515XTr748hwg+T+pQogVB0H9JKfY3xYKlcqgDAd9AWDsW8CjBfjXb1kX8bFKPQF7fPc8fv9zFWW12FNSh9jn2cazBQAMKGuXLlSbN++vbhx48ZD33/qqacGbrOzrWnV7Xnw/ABMno0bNxYXL14s9uzZ89D3T5482RpnY7zNFGNJtBvtHzhwoDhz5kxRl3hM586de+h7hw8fLo4fP57+mJ555pni0qVLD763bdu24vLly63nt07LNTbH67V169bK98OWLVv6aivaePbZZx/8u873wFJ27dpV+f0TJ04Uoy5e+6rXo9tj6kfn+3ap1/jgwYOtz88999yibba322//EvtUfCyns2fPPrSPDfLc7t69+6F/nz9/vlgO+/bte+jfR48enYjXhOV538dYWfaF8b4Y9iPGj/hoNBqtj/i6HDP7HUOOHTv20PuufTzp1969ex/KDJFLYBJcu3ZtouZ0yj4pZOT4GM87s07V9zKf/26vySiSMesnYy5OxpxM8Z4oj/3jPdE+fzJojmt/X8V7ZpjjeBkTRt8w+2XVGBz7/SBk7cXJ2ouTtesnay9O1p5MsjZMr3HOps8//3yr/4pMkpFD4zG39xGl6B+HHftk5uUlM9dPZl6czDy55GaAR3X2EZF3++kfIy+VPx/9bOda7WkXOau9b4/MVHXckqHMrqVexqT4mc7fYzrpC+pj3wQYHca7esm+jItR6Ava57ljfjGurYpzUb3MY8d5jbgGfJrY5xl7K11xEIDpEneVq7oLafadQqPCctXfGfZvlXfmrOMuoeOk2/MwSMVyAMZHjK+dd0Qu796QcXfbGE/L9pdzTCnvYNF51+iMxxS5o/M5W87c0Hnn7OwxOx5f53PX+RF34+mnvar32ErdVb7zTkLjlP+qtn2Qu6/3cgeUxd5P8Tz1+p6rer/G72XdPbvUeXeoQUXfN+x7ojNXL9VGZz81qM67zXR7byzXa8J4H8/X+THI3dvid9rHkkHGvPb3ftwZa5DtgFEV+0TV/pZ5R8nl0jkWx0ccswyrc/zLyqLd5tOGGdOXm4zZnYwpY5J7XmfQvrdzHxr0jsCdZEwYLZ13Mx52/G3fx2NfHZSsvTRZuztZuztZW9ZmeLI2TJ9xz6ZxTqrsG6K/GXQsi/6gPGYYNgd0kpmXn8zcncwsM5NDbgZYPCdFPxRZvd/+ps7sEx/R946jzvwySP8er0kvma1zXfZir2O8Xr3k7KrtZ3LpC/pj3wQYT8a7+si+jJOV7Au6ncsp240+IPaDXrZp3PsY+zzTwDsLgGU1bkVnJm0xXN2vowUAAJMv+vlu40BM6vQ7zkZ77YUEYywZZqweleJ8MQHUuSB4mIXovTyP0XZ8xMRUPIfdXqdywjGe9/J3evmIduM5iuek87Et9rHYYy63NdqsWmjf/hGPJ362zqzR/jirFuh3fsTzEM9j/E75PI1KFqrKrcMs7F5sIX23Cd1ygrPXRdnLNTGd9Zx09heDLvbt57goa7F71XNd9bwu98kCRld5YqPXvj/rY1CdF3D1M55b5M6kqMqH3ea12sfFGM/as82oXOAUj6fMabGfLtYnxRgZ+3085kHGqM4Cp4PozNHdiqePw3PfTsbsTsaUMcnRvlAm9qVe3wfxc53zCsMU7aoiY8LoaB8vy4y4WH5YTIxL/RYNlLVl7TrI2t3J2rI2OWRtmEyTlk0Xu3Fj7O/9jGHxXHSO//HvQdajyMyjQWbuTmaWmckjNwMsncPi31X9SGdfGGN7Hf3NKBck6FdVTu/nOeu1AELna7jYGBU/28sYpgDC9NEX9M6+CTC+jHf1kX0ZJyvZF1Td/Gip8zuT2MfY55kG3lkA1GJci85Mw2K4fh5753MQz/VSBRXjtYznquq5GKUiOAAMp6qgXdUi5hgPyoXM8TvxdYz5MVZ0jikZd1HPUDXm97p4PB5v5/OyHEUMlxqfV/Kj29gf3x+kvbomDwfdns6PUXkfV+2fse9laS+IGPmv/XVuLwza74Ls5ZiY7mwj6/0S2xLf7/ejs69ZjsXunW2V27/SJwsYXYsdz9f1Mex7PPav9r4q3p+LHY92Xjg2SierYBD9zJUt9THu/dAgWbw8+T5IX1B1knecn/t2MmZ3MuajbcmYDKpqEVR5kW3ZL5QX2kcf1DknEr9b13tGxoTRWgTcPsaVGayfudjoWwa5OZ2sLWvXQdbuTtZ+tC1Zm0HJ2jB5Ji2bLpXby74oxuD2tYml+Lqq/yr7iUHXcsrMo0Fm7k5mfrQtmZlhyM0Aj4o+r2ptdHwvPtr7zfLasLpUZf1xVZVx+1mD3GsBhKqix4u12et6+VE/hiCfvqA39k2A8Wa8q4fsy7hZyb6g6qZWi33E/N8g58BGuY+xzzMN5goAqMEzzzxTXLp0qeefv3HjRnHw4MFiOWzevHnJn9m7d29x/vz5vtqNn6/6nS9n3vFx8uTJ4vDhwwP/fryWx48f7/r/W7ZsKS5fvjxw+wCMhujPz507V1y5cqU4ceJEcfbs2dbXpcgBvWSBbdu2Ffv37y8OHDhQbNy4sRgFx44dK44cOVKcPn269djiccT4GB+xjfHYy48Qjzs+Oh/vnj17Wvlm165dxTRb6nUt/3+xjHbt2rUHOWM5t7eX3Ljc2zfo8x7/3rdvX1r7Z86cab2/Y7+Ix/3000+33uvt+0Ls17E/9SPaiL4l8vhSz2eZv6Mfie0p98nlUL7m7WKbh7WS/WDVYxqn14TJM+z7J/aneB9GRjl69Gjrvblp06bWe3r37t2t9uN9H8en8X9l3xXv3+i7pn38ZnL0krUWGxNGKd/083iGzWfRD8T8WL9ZJitXjuJzH2TMesmY1WTM6ROvdWS0OM8QOa7XOaZ4b0QfcujQodq2TcaE0RH7Y3smiLnY2PeiH4j9scwpW7dufTB2VO2fsV9GO7GfDrINQdbuj6xdTdaul6xdTdaePrI2TK5Jy6btou+Jj+i7Yv1G5Jdy/UYvhsn8nWTmlSUz10tmriYzTye5GeBR0Y+Ua8ajDzp16lRrHC2vn4r+J+bpYz14fKY3VdkintvssST+TryG7eNZvI6dr1W8nuXPQhV9QS77JsBoMt7VQ/Zl3KxkXxBzeNevX2+dryivbV5M/H+skbt48eLUvaft84yzRlT9W+mNAGDybN++va+Cf8upl6EvTnpHeMtYDDduQ20sUOgs+Fe16KbqOalaINO5IEbBP4DJFRNYMX7G5FBZBC/GhhgLYiyJsaMslBeTSDFxMg4LIcvJuHKSrv1xhfKxxYTPzp07W58tjmOlxfs0FifH5x07drQmeOvY32LfiAWhFy5ceLCvx/s/imYOOwna68R0qdeJ6Uaj8chC7n7FNsUxT7vIuHX3ae3bHo81HvOgYsFve1aP13Gpk2V1vSawHOJ9GyfZot+KvrF8/5fZpCxC7D0L0J2M2Z2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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# fields = [\"pm\", \"spm\", \"p3m\", \"diff_p3m_pm\"] # fields to plot\n", + "fields = [\"lpt\", \"cola\", \"pm\", \"spm\", \"p3m\", \"diff_p3m_pm\", \"diff_p3m_spm\"] # fields to plot\n", + "\n", + "figname = \"_\".join(fields)\n", + "slices_dict = {\n", + " \"lpt\": DELTA_LPT,\n", + " \"cola\": DELTA_COLA,\n", + " \"pm\": DELTA_PM,\n", + " \"spm\": DELTA_SPM,\n", + " \"p3m\": DELTA_P3M,\n", + " \"diff_p3m_pm\": diff_p3m_pm,\n", + " \"diff_p3m_spm\": diff_p3m_spm,\n", + "}\n", + "titles_dict = {\n", + " \"lpt\": \"LPT\",\n", + " \"cola\": f\"COLA $n_\\\\mathrm{{steps}}={nsteps_cola}$\",\n", + " \"pm\": f\"PM $n_\\\\mathrm{{steps}}={nsteps_pm}$\",\n", + " \"spm\": f\"sPM $n_\\\\mathrm{{steps}}={nsteps_spm}$\",\n", + " \"p3m\": f\"P3M $n_\\\\mathrm{{steps}}={nsteps_p3m}$\",\n", + " \"diff_p3m_pm\": r\"$\\delta_{\\rm P3M}-\\delta_{\\rm PM}$\",\n", + " \"diff_p3m_spm\": r\"$\\delta_{\\rm P3M}-\\delta_{\\rm sPM}$\",\n", + "}\n", + "\n", + "npanels = len(fields)\n", + "fig, axs = plt.subplots(1, npanels, figsize=(3 * npanels, 4), sharey=True)\n", + "\n", + "ims = []\n", + "for i, key in enumerate(fields):\n", + " ax = axs[i]\n", + " data = slices_dict[key]\n", + " title = titles_dict[key]\n", + "\n", + " if key.startswith(\"diff\"):\n", + " norm = TwoSlopeNorm(vmin=-np.log(1 + np.abs(np.min(data))), vcenter=0, vmax=np.log10(1 + np.abs(np.max(data))))\n", + " im = ax.imshow(\n", + " np.sign(data) * np.log(1 + np.abs(data)), cmap=\"RdBu_r\", norm=norm\n", + " )\n", + " else:\n", + " im = ax.imshow(np.log10(2 + data), cmap=cmap)\n", + "\n", + " ims.append((im, key))\n", + " ax.set_title(title, fontsize=fs_titles)\n", + " for spine in ax.spines.values():\n", + " spine.set_visible(False)\n", + "\n", + "axs[0].set_yticks([0, N // 2, N])\n", + "axs[0].set_yticklabels([f\"{-L/2:.0f}\", \"0\", f\"{L/2:.0f}\"], fontsize=fs)\n", + "axs[0].set_ylabel(r\"Mpc/$h$\", size=GLOBAL_FS_SMALL)\n", + "\n", + "for i, ax in enumerate(axs):\n", + " ax.set_xticks([0, N // 2, N])\n", + " ax.set_xticklabels([f\"{-L/2:.0f}\", \"0\", f\"{L/2:.0f}\"], fontsize=fs)\n", + " ax.set_xlabel(r\"Mpc/$h$\", size=GLOBAL_FS_SMALL)\n", + "\n", + "for ax, (im, key) in zip(axs, ims):\n", + " divider = make_axes_locatable(ax)\n", + " cax = divider.append_axes(\"bottom\", size=\"5%\", pad=0.6)\n", + " cb = fig.colorbar(im, cax=cax, orientation=\"horizontal\")\n", + " if key.startswith(\"diff\"):\n", + " cb.set_label(r\"$\\textrm{sgn}\\left(\\Delta\\delta\\right)\\log_{10}(1 + |\\Delta\\delta|)$\", fontsize=fs)\n", + " else:\n", + " cb.set_label(r\"$\\log_{10}(2 + \\delta)$\", fontsize=fs)\n", + " cb.ax.tick_params(labelsize=fs)\n", + " cax.xaxis.set_ticks_position(\"bottom\")\n", + " cax.xaxis.set_label_position(\"bottom\")\n", + "fig.savefig(\n", + " simdir + f\"{figname}.png\",\n", + " bbox_inches=\"tight\",\n", + " dpi=300,\n", + " transparent=True,\n", + ")\n", + "fig.savefig(\n", + " simdir + f\"{figname}.pdf\",\n", + " bbox_inches=\"tight\",\n", + " dpi=300,\n", + ")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "full_field_p3m = np.log10(2+read_field(simdir + f\"nsteps{nsteps_p3m}_final_density_p3m.h5\").data)\n", + "\n", + "if N <= 128:\n", + " fig = plotly_3d(full_field_p3m, size=N, L=L, colormap=thermal_plotly, limits=\"default\")\n", + "else:\n", + " # Downsample the grid for visualisation\n", + " downsample_factor = N // 128\n", + " downsampled_field = full_field_p3m[\n", + " ::downsample_factor, ::downsample_factor, ::downsample_factor\n", + " ]\n", + " fig = plotly_3d(downsampled_field, size=N, L=L, colormap=thermal_plotly, limits=\"default\")\n", + "\n", + "fig.show()\n", + "clear_large_plot(fig) # Uncomment to clear the Plotly figure to avoid memory issues" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Compute and plot the power spectra of the evolved dark matter fields" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read Fourier grid in data file '/Users/hoellinger/WIP3M/run13/input_ss_k_grid.h5'...\n", + "[17:16:32|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mL0=16.0, L1=16.0, L2=16.0\u001b[00m\n", + "[17:16:32|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mN0=32, N1=32, N2=32, N2_HC=17, N_HC=17408, NUM_MODES=40\u001b[00m\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read Fourier grid in data file '/Users/hoellinger/WIP3M/run13/input_ss_k_grid.h5' done.\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/initial_density.h5'...\n", + "[17:16:32|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/initial_density.h5' done.\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores)...\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/lpt_density.h5'...\n", + "]|Getting auto-correlation in Fourier space (using 8 cores) done.\n", + "[17:16:32|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/lpt_density.h5' done.\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores)...\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_pm.h5'...\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores) done.\n", + "[17:16:32|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_pm.h5' done.\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores)...\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps20_final_density_cola.h5'...\n", + "Getting auto-correlation in Fourier space (using 8 cores) done.\n", + "[17:16:32|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps20_final_density_cola.h5' done.\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores)...\n", + "[17:16:32\u001b[00m|\u001b[38;5;113m[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_spm.h5'...\n", + "STATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores) done.\n", + "[17:16:32|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_spm.h5' done.\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores)...\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores) done.\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_p3m.h5'...\n", + "[17:16:32|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.float64(-8.0), np.float64(8.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:16:32|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/run13/nsteps50_final_density_p3m.h5' done.\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores)...\n", + "[17:16:32\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Getting auto-correlation in Fourier space (using 8 cores) done.\n" + ] + } + ], + "source": [ + "G = read_FourierGrid(simdir + \"input_ss_k_grid.h5\")\n", + "k = G.k_modes[1:]\n", + "AliasingCorr = False\n", + "\n", + "DELTA = read_field(simdir + \"initial_density.h5\")\n", + "Pk_INI, Vk_INI = get_autocorrelation(DELTA, G, AliasingCorr)\n", + "Pk_INI, Vk_INI = Pk_INI[1:], Vk_INI[1:]\n", + "Sk_INI = np.sqrt(Vk_INI)\n", + "\n", + "DELTA = read_field(simdir + \"lpt_density.h5\")\n", + "Pk_LPT, Vk_LPT = get_autocorrelation(DELTA, G, AliasingCorr)\n", + "Pk_LPT, Vk_LPT = Pk_LPT[1:], Vk_LPT[1:]\n", + "Sk_LPT = np.sqrt(Vk_LPT)\n", + "\n", + "DELTA = read_field(simdir + f\"nsteps{nsteps_pm}_final_density_pm.h5\")\n", + "Pk_PM, Vk_PM = get_autocorrelation(DELTA, G, AliasingCorr)\n", + "Pk_PM, Vk_PM = Pk_PM[1:], Vk_PM[1:]\n", + "Sk_PM = np.sqrt(Vk_PM)\n", + "\n", + "DELTA = read_field(simdir + f\"nsteps{nsteps_cola}_final_density_cola.h5\")\n", + "Pk_COLA, Vk_COLA = get_autocorrelation(DELTA, G, AliasingCorr)\n", + "Pk_COLA, Vk_COLA = Pk_COLA[1:], Vk_COLA[1:]\n", + "Sk_COLA = np.sqrt(Vk_COLA)\n", + "\n", + "DELTA = read_field(simdir + f\"nsteps{nsteps_spm}_final_density_spm.h5\")\n", + "Pk_sPM, Vk_sPM = get_autocorrelation(DELTA, G, AliasingCorr)\n", + "Pk_sPM, Vk_sPM = Pk_sPM[1:], Vk_sPM[1:]\n", + "Sk_sPM = np.sqrt(Vk_sPM)\n", + "\n", + "DELTA = read_field(simdir + f\"nsteps{nsteps_p3m}_final_density_p3m.h5\")\n", + "Pk_P3M, Vk_p3m = get_autocorrelation(DELTA, G, AliasingCorr)\n", + "Pk_P3M, Vk_p3m = Pk_P3M[1:], Vk_p3m[1:]\n", + "Sk_p3m = np.sqrt(Vk_p3m)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "kmin = 1.3454698324203491, kmax = 10.072183609008789\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Pk_ref = Pk_PM\n", + "\n", + "fig, ax = plt.subplots(figsize=(7, 4))\n", + "\n", + "ax.set_xscale(\"log\")\n", + "k = G.k_modes[1:]\n", + "kmin, kmax = k.min(), k.max()\n", + "print(f\"kmin = {kmin}, kmax = {kmax}\")\n", + "log_pad = 0.02\n", + "log_k_min = np.log10(kmin)\n", + "log_k_max = np.log10(kmax)\n", + "log_range = log_k_max - log_k_min\n", + "xlim_min = 10 ** (log_k_min - log_pad * log_range)\n", + "xlim_max = 10 ** (log_k_max + log_pad * log_range)\n", + "\n", + "plt.xlim(xlim_min, xlim_max)\n", + "ax.set_ylim([0.2, 1.8])\n", + "# ax.set_ylim([0.5, 1.5])\n", + "dark_grey_bnd = 0.05\n", + "light_grey_bnd = 0.1\n", + "\n", + "label_ref = f\"PM with $n_\\\\mathrm{{steps}}={nsteps_pm}$\"\n", + "\n", + "line1 = ax.plot([kmin, kmax], [1, 1], color=\"black\", linestyle=\"-\", label=label_ref)\n", + "\n", + "# line2 = ax.plot(k, Pk_LPT / Pk_ref, label=\"2LPT\", color=cols[0], linestyle=\"-\")\n", + "\n", + "ax.plot(\n", + " k,\n", + " Pk_COLA / Pk_ref,\n", + " label=f\"COLA with $n_\\\\mathrm{{steps}}={nsteps_cola}$\",\n", + " linestyle=\"-\",\n", + " color=cols[2],\n", + ")\n", + "# ax.plot(\n", + "# k,\n", + "# Pk_PM / Pk_ref,\n", + "# label=f\"PM with $n_\\\\mathrm{{steps}}={nsteps_pm}$\",\n", + "# linestyle=\"-\",\n", + "# color=cols[3],\n", + "# )\n", + "ax.plot(\n", + " k,\n", + " Pk_sPM / Pk_ref,\n", + " label=f\"sPM with $n_\\\\mathrm{{steps}}={nsteps_p3m}$\",\n", + " linestyle=\"--\",\n", + " color=cols[4],\n", + ")\n", + "ax.plot(\n", + " k,\n", + " Pk_P3M / Pk_ref,\n", + " label=f\"P3M with $n_\\\\mathrm{{steps}}={nsteps_p3m}$\",\n", + " linestyle=\"--\",\n", + " color=cols[5],\n", + ")\n", + "\n", + "ax.axhspan(1 - dark_grey_bnd, 1 + dark_grey_bnd, color=\"grey\", alpha=0.2)\n", + "ax.axhspan(1 - light_grey_bnd, 1 + light_grey_bnd, color=\"grey\", alpha=0.1)\n", + "\n", + "for i in range(1, len(k)):\n", + " ax.axvline(k[i], color=\"black\", linestyle=\":\", linewidth=1, alpha=0.1)\n", + "ax.axvline(np.pi * N / L, color=\"grey\", linestyle=\"--\", linewidth=1) # 1D Nyquist\n", + "ax.yaxis.set_major_locator(plt.MaxNLocator(6))\n", + "ax.yaxis.get_major_ticks()[0].label1.set_visible(False)\n", + "ax.set_xlabel(\"$k$ [$h/\\\\mathrm{Mpc}$]\", fontsize=fs)\n", + "ax.set_ylabel(\"$P(k)/P_\\\\mathrm{ref}(k)$\", fontsize=fs)\n", + "ax.tick_params(which=\"both\", direction=\"in\")\n", + "ax.tick_params(axis=\"both\", which=\"major\", labelsize=fs)\n", + "ax.tick_params(axis=\"both\", which=\"minor\", labelsize=fs)\n", + "\n", + "empty_patch = mpatches.Patch(color=\"none\", label=\"\")\n", + "handles, labels = plt.gca().get_legend_handles_labels()\n", + "# handles = [empty_patch, *handles]\n", + "# labels = [\"\", *labels]\n", + "plt.legend(\n", + " handles,\n", + " labels,\n", + " loc=\"upper center\",\n", + " ncol=2,\n", + " bbox_to_anchor=(0.5, -0.2),\n", + " fontsize=fs,\n", + ")\n", + "fig.savefig(\n", + " simdir + \"power_spectrum.png\",\n", + " bbox_inches=\"tight\",\n", + " dpi=300,\n", + " transparent=True,\n", + ")\n", + "fig.savefig(\n", + " simdir + \"power_spectrum.pdf\",\n", + " bbox_inches=\"tight\",\n", + " dpi=300,\n", + ")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Force exerted by particles on other particles" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Newton prefactor = 9.95e-03\n", + "Nyquist: 0.50 Mpc/h\n", + "Particle length: 0.03 Mpc/h\n", + "Split scale: 0.31 Mpc/h\n", + "Short-range reach: 1.41 Mpc/h\n", + "Figure saved to: /Users/hoellinger/WIP3M/run13/force_diagnostic_comparison.png\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "r1, fmag1, _ = load_force_diagnostic(OutputForceDiagnostic_pm)\n", + "r4, fmag4, _ = load_force_diagnostic(OutputForceDiagnostic_cola)\n", + "r2, fmag2, _ = load_force_diagnostic(OutputForceDiagnostic_spm)\n", + "r3, fmag3, _ = load_force_diagnostic(OutputForceDiagnostic_p3m)\n", + "\n", + "rr = np.array([r1, r4, r2, r3], dtype=object)\n", + "ff = np.array([fmag1, fmag4, fmag2, fmag3], dtype=object)\n", + "ll = np.array([\"PM\", \"COLA\", \"sPM\", \"P3M\"])\n", + "\n", + "ix = [0, 1, 2, 3]\n", + "\n", + "Newton_prefactor = (L / Np)**3 / (4*np.pi)\n", + "print(f\"Newton prefactor = {Newton_prefactor:.2e}\")\n", + "plot_force_distance_comparison(rr=rr[ix], ff=ff[ix], ll=ll[ix], L=L, Np=Np, Npm=Npm, a=Newton_prefactor, title=\"Particle's contributions to total force\", save_path=simdir + \"force_diagnostic_comparison.png\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "p3m", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/1_force_diagnostic.ipynb b/notebooks/1_force_diagnostic.ipynb new file mode 100644 index 0000000..c745326 --- /dev/null +++ b/notebooks/1_force_diagnostic.ipynb @@ -0,0 +1,679 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "340c92c6", + "metadata": {}, + "source": [ + "Tristan Hoellinger
\n", + "Institut d'Astrophysique de Paris
\n", + "tristan.hoellinger@iap.fr" + ] + }, + { + "cell_type": "markdown", + "id": "94047ef1", + "metadata": {}, + "source": [ + "# P3M force diagnostic" + ] + }, + { + "cell_type": "markdown", + "id": "cd240b53", + "metadata": {}, + "source": [ + "## Set up the environment and parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "1dfed55e", + "metadata": {}, + "outputs": [], + "source": [ + "from wip3m.params import *" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "aea2278a", + "metadata": {}, + "outputs": [], + "source": [ + "workdir = ROOT_PATH\n", + "output_path = OUTPUT_PATH\n", + "\n", + "L = 64 # Box size in Mpc/h\n", + "N = 32 # Density grid size\n", + "Np = 32 # Number of dark matter particles per spatial dimension\n", + "Npm = 64 # PM grid size\n", + "n_Tiles = 8 # Make sure Npm/n_Tiles >= 6\n", + "\n", + "go_beyond_Nyquist_ss = True # for the summary statistics\n", + "\n", + "force = True\n", + "force_hard = True\n", + "run_id = \"forcediag7\"\n", + "\n", + "# Good set of parameters for the force diagnostic\n", + "# nPairsForceDiagnostic_spm = nPairsForceDiagnostic_p3m = 3\n", + "# nBinsForceDiagnostic = 30\n", + "# maxTrialsForceDiagnostic = int(1e9)\n", + "\n", + "# Faster force diagnostic\n", + "nPairsForceDiagnostic_spm = nPairsForceDiagnostic_p3m = 3\n", + "nBinsForceDiagnostic = 20\n", + "maxTrialsForceDiagnostic = int(1e8)\n", + "\n", + "# Simulation parameters\n", + "# nsteps_spm = 200\n", + "# nsteps_p3m = 200\n", + "nsteps_spm = 20\n", + "nsteps_p3m = 20" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "28a4e070", + "metadata": {}, + "outputs": [], + "source": [ + "# Automatic reloading of modules\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "from os.path import isfile\n", + "from pathlib import Path\n", + "import numpy as np\n", + "\n", + "from pysbmy.power import PowerSpectrum\n", + "from pysbmy.field import read_field\n", + "\n", + "from wip3m.tools import get_k_max, generate_sim_params, generate_white_noise_Field\n", + "from wip3m.params import params_planck_kmax_missing, cosmo_small_to_full_dict, z2a, BASELINE_SEEDPHASE\n", + "from wip3m.plot_utils import *" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "3f0eaa51", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "k_max = 2.721\n" + ] + } + ], + "source": [ + "corner = 0.0\n", + "RedshiftLPT = 19.0\n", + "RedshiftFCs = 0.0\n", + "ai = z2a(RedshiftLPT)\n", + "af = z2a(RedshiftFCs)\n", + "k_max = get_k_max(L, N) # k_max in h/Mpc\n", + "print(f\"k_max = {k_max}\")\n", + "cosmo = params_planck_kmax_missing.copy()\n", + "cosmo[\"k_max\"] = k_max\n", + "\n", + "wd = workdir + run_id + \"/\"\n", + "simdir = output_path + run_id + \"/\"\n", + "logdir = simdir + \"logs/\"\n", + "if force_hard:\n", + " import shutil\n", + " if Path(simdir).exists():\n", + " shutil.rmtree(simdir)\n", + " if Path(wd).exists():\n", + " shutil.rmtree(wd)\n", + "Path(wd).mkdir(parents=True, exist_ok=True)\n", + "Path(logdir).mkdir(parents=True, exist_ok=True)\n", + "\n", + "input_white_noise_file = simdir + \"input_white_noise.h5\"\n", + "input_seed_phase_file = simdir + \"seed\"\n", + "ICs_path = simdir + \"initial_density.h5\"\n", + "simpath = simdir\n", + "\n", + "# Path to the input matter power spectrum (generated later)\n", + "input_power_file = simdir + \"input_power.h5\"\n", + "\n", + "# Paths the the force diagnostic CSVs\n", + "OutputForceDiagnostic_spm = simdir + \"force_diagnostic_spm.txt\"\n", + "OutputForceDiagnostic_p3m = simdir + \"force_diagnostic_p3m.txt\"" + ] + }, + { + "cell_type": "markdown", + "id": "4f013d1f", + "metadata": {}, + "source": [ + "### Generate the parameter files" + ] + }, + { + "cell_type": "markdown", + "id": "88742aca", + "metadata": {}, + "source": [ + "The first preparatory step is to generate all the parameter files required for all the simulations.\n", + "\n", + "To this end we use the `generate_sim_params` function defined in `params.py`." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "dd3f8a0c", + "metadata": {}, + "outputs": [], + "source": [ + "common_params = {\n", + " \"Np\": Np,\n", + " \"N\": N,\n", + " \"L\": L,\n", + " \"corner0\": corner,\n", + " \"corner1\": corner,\n", + " \"corner2\": corner,\n", + " \"h\": cosmo[\"h\"],\n", + " \"Omega_m\": cosmo[\"Omega_m\"],\n", + " \"Omega_b\": cosmo[\"Omega_b\"],\n", + " \"n_s\": cosmo[\"n_s\"],\n", + " \"sigma8\": cosmo[\"sigma8\"],\n", + "}\n", + "\n", + "lpt_params = common_params.copy()\n", + "lpt_params[\"method\"] = \"lpt\"\n", + "lpt_params[\"InputPowerSpectrum\"] = input_power_file\n", + "lpt_params[\"ICsMode\"] = 1\n", + "lpt_params[\"InputWhiteNoise\"] = input_white_noise_file\n", + "\n", + "spm_params = common_params.copy()\n", + "spm_params[\"method\"] = \"spm\"\n", + "spm_params[\"EvolutionMode\"] = 5\n", + "spm_params[\"TimeStepDistribution\"] = 0\n", + "spm_params[\"ai\"] = ai\n", + "spm_params[\"af\"] = af\n", + "spm_params[\"RedshiftLPT\"] = RedshiftLPT\n", + "spm_params[\"RedshiftFCs\"] = RedshiftFCs\n", + "spm_params[\"Npm\"] = Npm\n", + "spm_params[\"nsteps\"] = nsteps_spm\n", + "spm_params[\"n_Tiles\"] = n_Tiles\n", + "spm_params[\"RunForceDiagnostic\"] = True\n", + "spm_params[\"nPairsForceDiagnostic\"] = nPairsForceDiagnostic_spm\n", + "spm_params[\"nBinsForceDiagnostic\"] = nBinsForceDiagnostic\n", + "spm_params[\"OutputForceDiagnostic\"] = OutputForceDiagnostic_spm\n", + "spm_params[\"maxTrialsForceDiagnostic\"] = maxTrialsForceDiagnostic\n", + "\n", + "p3m_params = common_params.copy()\n", + "p3m_params[\"method\"] = \"p3m\"\n", + "p3m_params[\"EvolutionMode\"] = 4\n", + "p3m_params[\"TimeStepDistribution\"] = 0\n", + "p3m_params[\"ai\"] = ai\n", + "p3m_params[\"af\"] = af\n", + "p3m_params[\"RedshiftLPT\"] = RedshiftLPT\n", + "p3m_params[\"RedshiftFCs\"] = RedshiftFCs\n", + "p3m_params[\"Npm\"] = Npm\n", + "p3m_params[\"nsteps\"] = nsteps_p3m\n", + "p3m_params[\"n_Tiles\"] = n_Tiles\n", + "p3m_params[\"RunForceDiagnostic\"] = True\n", + "p3m_params[\"nPairsForceDiagnostic\"] = nPairsForceDiagnostic_p3m\n", + "p3m_params[\"nBinsForceDiagnostic\"] = nBinsForceDiagnostic\n", + "p3m_params[\"OutputForceDiagnostic\"] = OutputForceDiagnostic_p3m\n", + "p3m_params[\"maxTrialsForceDiagnostic\"] = maxTrialsForceDiagnostic" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "1d617059", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[17:03:15|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n", + "[17:03:15|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/example_lpt.sbmy'...\n", + "[17:03:15|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/example_lpt.sbmy' done.\n", + "[17:03:15|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Parameter file written to /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/example_lpt.sbmy\n", + "SPM nsteps = 20:\n", + "[17:03:15|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Time-stepping distribution file: /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_spm.h5\n", + "[17:03:15|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_spm.h5'...\n", + "[17:03:15|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_spm.h5' done.\n", + "[17:03:15|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_spm.h5'...\n", + "[17:03:15|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_spm.h5' done.\n", + "[17:03:16|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_example_spm.sbmy'...\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_example_spm.sbmy' done.\n", + "[17:03:16|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Parameter file written to /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_example_spm.sbmy\n", + "P3M nsteps = 20:\n", + "[17:03:16|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Time-stepping distribution file: /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_p3m.h5\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_p3m.h5'...\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_p3m.h5' done.\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_p3m.h5'...\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_ts_p3m.h5' done.\n", + "[17:03:16|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_example_p3m.sbmy'...\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_example_p3m.sbmy' done.\n", + "[17:03:16|\u001b[1;36mINFO \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Parameter file written to /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/forcediag7/nsteps20_example_p3m.sbmy\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "reset_plotting() # Default style for Simbelmynë\n", + "\n", + "generate_sim_params(lpt_params, ICs_path, wd, simdir, None, force)\n", + "\n", + "print(f\"SPM nsteps = {nsteps_spm}:\")\n", + "file_ext = f\"nsteps{nsteps_spm}\" # \"spm\" is already in the filename\n", + "generate_sim_params(spm_params, ICs_path, wd, simdir, file_ext, force)\n", + "\n", + "print(f\"P3M nsteps = {nsteps_p3m}:\")\n", + "file_ext = f\"nsteps{nsteps_p3m}\" # \"p3m\" is already in the filename\n", + "generate_sim_params(p3m_params, ICs_path, wd, simdir, file_ext, force)\n", + "\n", + "setup_plotting() # Reset plotting style for this project" + ] + }, + { + "cell_type": "markdown", + "id": "4cbfc7f9", + "metadata": {}, + "source": [ + "### Generate the initial phase" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "ac1596ef", + "metadata": {}, + "outputs": [], + "source": [ + "generate_white_noise_Field(\n", + " L=L,\n", + " size=N,\n", + " corner=corner,\n", + " seedphase=BASELINE_SEEDPHASE,\n", + " fname_whitenoise=input_white_noise_file,\n", + " seedname_whitenoise=input_seed_phase_file,\n", + " force_phase=force,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "b1dfa6e3", + "metadata": {}, + "source": [ + "### Generating the input power spectrum\n", + "\n", + "The second preparatory step is to compute the initial power spectrum to be used in the simulations, given the cosmological parameters and prescription specified in ``params.py``. The power spectrum is saved in `input_power_file`." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "3c2cf19b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Setting up Fourier grid...\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Setting up Fourier grid done.\n", + "[17:03:16\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m][17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Write power spectrum in data file '/Users/hoellinger/WIP3M/forcediag7/input_power.h5'...\n", + "|Computing normalization of the power spectrum...\n", + "[17:03:16\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Computing normalization of the power spectrum done.\n", + "[17:03:16\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Computing power spectrum...\n", + "[17:03:16\u001b[00m|\u001b[38;5;113mSTATUS \u001b[00m]|Computing power spectrum done.\n", + "[17:03:16|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mL0=64, L1=64, L2=64\u001b[00m\n", + "[17:03:16|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mN0=32, N1=32, N2=32, N2_HC=17, N_HC=17408, NUM_MODES=464\u001b[00m\n", + "[17:03:16|\u001b[38;5;113mSTATUS \u001b[00m]|Write power spectrum in data file '/Users/hoellinger/WIP3M/forcediag7/input_power.h5' done.\n" + ] + } + ], + "source": [ + "# If cosmo[\"WhichSpectrum\"] == \"class\", then classy is required.\n", + "if not isfile(input_power_file) or force:\n", + " Pk = PowerSpectrum(L, L, L, N, N, N, cosmo_small_to_full_dict(cosmo))\n", + " Pk.write(input_power_file)" + ] + }, + { + "cell_type": "markdown", + "id": "5f00a570", + "metadata": {}, + "source": [ + "## Running the simulations\n", + "\n", + "We are now ready to run the actual simulations using the Simbelmynë executable. Warning: the following may take some time, even in relatively low dimension, and should not be run on a login node." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "6f714f19", + "metadata": {}, + "outputs": [], + "source": [ + "%%capture\n", + "\n", + "if not isfile(ICs_path) or not isfile(simdir + \"lpt_density.h5\") or not isfile(simdir + \"lpt_particles.gadget3\") or force:\n", + " !simbelmyne {wd}example_lpt.sbmy {logdir}lpt.txt\n", + "\n", + "file_ext = f\"nsteps{nsteps_spm}\" # \"spm\" is already in the filename\n", + "if not isfile(simdir + f\"{file_ext}_final_density_spm.h5\") or force:\n", + " !simbelmyne {wd}{file_ext}_example_spm.sbmy {logdir}{file_ext}_spm.txt\n", + "\n", + "file_ext = f\"nsteps{nsteps_p3m}\" # \"p3m\" is already in the filename\n", + "if not isfile(simdir + f\"{file_ext}_final_density_p3m.h5\") or force:\n", + " !simbelmyne {wd}{file_ext}_example_p3m.sbmy {logdir}{file_ext}_p3m.txt" + ] + }, + { + "cell_type": "markdown", + "id": "acd604ca", + "metadata": {}, + "source": [ + "The logs can be monitored in the corresponding files in the `logdir` directory." + ] + }, + { + "cell_type": "markdown", + "id": "3060305c", + "metadata": {}, + "source": [ + "## Plot results" + ] + }, + { + "cell_type": "markdown", + "id": "fafb43e2", + "metadata": {}, + "source": [ + "### Plot the evolved dark matter density fields" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "73d9e5cd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[17:03:35|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/forcediag7/nsteps20_final_density_spm.h5'...\n", + "[17:03:35|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(0.0), np.float64(64.0), np.float64(0.0), np.float64(64.0), np.float64(0.0), np.float64(64.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:03:35|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/forcediag7/nsteps20_final_density_spm.h5' done.\n", + "[17:03:35|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/forcediag7/nsteps20_final_density_p3m.h5'...\n", + "[17:03:35|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mranges=[np.float64(0.0), np.float64(64.0), np.float64(0.0), np.float64(64.0), np.float64(0.0), np.float64(64.0), np.int32(32), np.int32(32), np.int32(32)]\u001b[00m\n", + "[17:03:35|\u001b[38;5;113mSTATUS \u001b[00m]|Read field in data file '/Users/hoellinger/WIP3M/forcediag7/nsteps20_final_density_p3m.h5' done.\n" + ] + } + ], + "source": [ + "slice_ijk = (N // 2, slice(None), slice(None))\n", + "DELTA_SPM = read_field(simdir + f\"nsteps{nsteps_spm}_final_density_spm.h5\").data[slice_ijk]\n", + "DELTA_P3M = read_field(simdir + f\"nsteps{nsteps_p3m}_final_density_p3m.h5\").data[slice_ijk]\n", + "diff_p3m_spm = DELTA_P3M - DELTA_SPM" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "cd6e5652", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "max(DELTA_P3M) = 13.531244277954102, min(DELTA_P3M) = -1.0\n", + "max(diff) = 9.856795310974121, min(diff) = -6.477081298828125\n" + ] + } + ], + "source": [ + "print(f\"max(DELTA_P3M) = {np.max(DELTA_P3M)}, min(DELTA_P3M) = {np.min(DELTA_P3M)}\")\n", + "print(f\"max(diff) = {np.max(diff_p3m_spm)}, min(diff) = {np.min(diff_p3m_spm)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c9da7aa9", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib.colors import TwoSlopeNorm\n", + "\n", + "fields = [\"spm\", \"p3m\", \"diff_p3m_spm\"] # fields to plot\n", + "\n", + "slices_dict = {\n", + " \"spm\": DELTA_SPM,\n", + " \"p3m\": DELTA_P3M,\n", + " \"diff_p3m_spm\": diff_p3m_spm,\n", + "}\n", + "titles_dict = {\n", + " \"spm\": f\"sPM $n_\\\\mathrm{{steps}}={nsteps_spm}$\",\n", + " \"p3m\": f\"P3M $n_\\\\mathrm{{steps}}={nsteps_p3m}$\",\n", + " \"diff_p3m_spm\": r\"$\\delta_{\\rm P3M}-\\delta_{\\rm sPM}$\",\n", + "}\n", + "\n", + "npanels = len(fields)\n", + "fig, axs = plt.subplots(1, npanels, figsize=(3 * npanels, 4), sharey=True)\n", + "\n", + "ims = []\n", + "for i, key in enumerate(fields):\n", + " ax = axs[i]\n", + " data = slices_dict[key]\n", + " title = titles_dict[key]\n", + "\n", + " if key.startswith(\"diff\"):\n", + " vmin = -np.log(1 + np.abs(np.min(data)))\n", + " vmax = np.log10(1 + np.abs(np.max(data)))\n", + " if vmin < 0 < vmax:\n", + " norm = TwoSlopeNorm(vmin=vmin, vcenter=0, vmax=vmax)\n", + " else:\n", + " norm = plt.Normalize(vmin=vmin, vmax=vmax)\n", + " im = ax.imshow(\n", + " np.sign(data) * np.log(1 + np.abs(data)), cmap=\"RdBu_r\", norm=norm\n", + " )\n", + " else:\n", + " im = ax.imshow(np.log10(2 + data), cmap=cmap)\n", + "\n", + " ims.append((im, key))\n", + " ax.set_title(title, fontsize=fs_titles)\n", + " for spine in ax.spines.values():\n", + " spine.set_visible(False)\n", + "\n", + "axs[0].set_yticks([0, N // 2, N])\n", + "axs[0].set_yticklabels([f\"{-L/2:.0f}\", \"0\", f\"{L/2:.0f}\"], fontsize=fs)\n", + "axs[0].set_ylabel(r\"Mpc/$h$\", size=GLOBAL_FS_SMALL)\n", + "\n", + "for i, ax in enumerate(axs):\n", + " ax.set_xticks([0, N // 2, N])\n", + " ax.set_xticklabels([f\"{-L/2:.0f}\", \"0\", f\"{L/2:.0f}\"], fontsize=fs)\n", + " ax.set_xlabel(r\"Mpc/$h$\", size=GLOBAL_FS_SMALL)\n", + "\n", + "for ax, (im, key) in zip(axs, ims):\n", + " divider = make_axes_locatable(ax)\n", + " cax = divider.append_axes(\"bottom\", size=\"5%\", pad=0.6)\n", + " cb = fig.colorbar(im, cax=cax, orientation=\"horizontal\")\n", + " if key.startswith(\"diff\"):\n", + " cb.set_label(r\"$\\textrm{sgn}\\left(\\Delta\\delta\\right)\\log_{10}(1 + |\\Delta\\delta|)$\", fontsize=fs)\n", + " else:\n", + " cb.set_label(r\"$\\log_{10}(2 + \\delta)$\", fontsize=fs)\n", + " cb.ax.tick_params(labelsize=fs)\n", + " cax.xaxis.set_ticks_position(\"bottom\")\n", + " cax.xaxis.set_label_position(\"bottom\")\n", + "figname = f\"fields\"\n", + "fig.savefig(\n", + " simdir + f\"{figname}.png\",\n", + " bbox_inches=\"tight\",\n", + " dpi=300,\n", + " transparent=True,\n", + ")\n", + "fig.savefig(\n", + " simdir + f\"{figname}.pdf\",\n", + " bbox_inches=\"tight\",\n", + " dpi=300,\n", + ")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "228340be", + "metadata": {}, + "outputs": [], + "source": [ + "full_field_p3m = np.log10(2+read_field(simdir + f\"nsteps{nsteps_p3m}_final_density_p3m.h5\").data)\n", + "\n", + "if N <= 128:\n", + " fig = plotly_3d(full_field_p3m, size=N, L=L, colormap=thermal_plotly, limits=\"default\")\n", + "else:\n", + " # Downsample the grid for visualisation\n", + " downsample_factor = N // 128\n", + " downsampled_field = full_field_p3m[\n", + " ::downsample_factor, ::downsample_factor, ::downsample_factor\n", + " ]\n", + " fig = plotly_3d(downsampled_field, size=N, L=L, colormap=thermal_plotly, limits=\"default\")\n", + "\n", + "fig.show()\n", + "clear_large_plot(fig) # Uncomment to clear the Plotly figure to avoid memory issues" + ] + }, + { + "cell_type": "markdown", + "id": "7d0df151", + "metadata": {}, + "source": [ + "### Force exerted by particles on other particles" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "684477ec", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Newton prefactor = 6.37e-01\n" + ] + } + ], + "source": [ + "r1, fmag1, _ = load_force_diagnostic(OutputForceDiagnostic_spm)\n", + "r2, fmag2, _ = load_force_diagnostic(OutputForceDiagnostic_p3m)\n", + "Newton_prefactor = (L / Np)**3 / (4*np.pi)\n", + "print(f\"Newton prefactor = {Newton_prefactor:.2e}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "6a6b4e9c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Nyquist: 2.00 Mpc/h\n", + "Particle length: 0.12 Mpc/h\n", + "Split scale: 1.25 Mpc/h\n", + "Short-range reach: 5.62 Mpc/h\n" + ] + }, + { + "data": { + "image/png": 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qyaWpZWRu11SwGd127969vX1nrUGSdetpLmmk2jFJUKodmMp9ddsUwrm2ci4zHfYpy720fZ/ZNPVzLfekqaaenXOU7r5GUzaDtMWpjj4GAPZHUBMAAGa0biRDDaOr0viYV4J6aYxft6/rGkkT7MvnutaXq10ayBOYvH///nuN5QnSJlCRUVTrglu1Br2mtC7QPfcoxq5ARhkld2qsp1mX3CPaQc3cU7YFNfOeU83D2+6jmwKXtdyThmp2msm5n6szwj5HUzaDtLV02AIAjo81NQEAYEZdo3HSmFtTg3YCmwmYvH37djXyIkHKXfcvjfoPHz48W5KMtMyaofl/aWROcCjnKq8c/ykELoeQLodjPc36roV2ULmMwtwkHUHmnHr02C3lntRcc/X27duL7wyRjk1dQehTn1YZAJieoCYAAMyoayRDrY1+aRxOgDONrwnunZ+fr/6fkUebGkGXMh1rRvpcvXr1vSBsjjmB3DT81hRorjVQMPcUkF2jmY5hGsq+rKdZp67gZDN41VbW6TVFZ/d1vClAWcs9aajMiFDMObvBvjpDZMr2rvvRUoLMAMByCGoCAMBM1o1kSBBwKRLou3v37irolyBnAoBdwb807u+6NuchlOlym/uYgFmCtgIMu0/puGnNu33oaiCfex9q7RxhPc3Dy72jnUebwauugOecU4/WrOs63pQutdyThmjmiZz/OQN/+1pPsyuff/nll6O3CwDQJqgJAAAz6RrJkEbwQzVoZzRlVwNnH9n/BAIT6Gzbtpbc1C5cuLDTCNEEMm/cuPFegDmNyjkOwYW6R0VlZO2h96EG1tOsV9fI+3WBzQSnTT27/jretD5mLfeksWWBOc//vtbTzDO1qxNTrbNQAADLJqgJAAAz6Qq43bt37+xQMkL0/v37k2wrAcx2ELPWKWgzeqTd8J0Rp6bJ26wr4Dv3aNzr168ffB9q0NUZwXqay5qCNgGm3IfmnHq0Vus612wLttVwTxqiGeSeM/DX1RliimnWu/K3qWcBgH0R1AQAgBkkwNcOpKXR79DrNq4buTFERmu2p26dcvtTNSa3G9Czz0a5bdeVRs+fP591H7qmalxCEGNK1tOsW9d0siWA2Q4Emer6H7x48WJQfq7hnjQmoDl34K/reXyoqWdzPaRj1RJG1gIAdRHUBACAGXStm9k1umFuaVAcOwVtU3u0Zm0Bp66RqWNHy/ZplH348OFqmtwl6mqkPkTQuqsRfso8XLuuNLeeZv2jNZsj13PPSCDI1LP/IFN/Dxl5XMs9qY/mc3/uNSf3McI72+x6zm8bgZxncZ6HtZ8vAKA+gpoAALBnabjumu60liDElI2KOaZm0OnVq1dntUjDa7tRN8GgsaNl37x5c3YKagkm3r59e6eRXvvKM4dmPc36dY3AbAazspZm7j3O2x/So22XUay13JN2lXJA83k759Sz657zY/NgV+esXc5dGd3pGgAA+hLUBACAPUoDa3ttyTT41TTtYFeQZIxDTKm7y2jJrkbdKRqVT2n6vK7RN/sYaZMRTNeuXev8W66ddoeAdBLYV4eEr7766qwmXQHczz777CD7Qrfkz/Z9sBkgTyDIWprrp+ZNoGvXTj813JOGBG/nnnp2X+tpdgWkt41AzrWQV9d04gAA2whqAgDAnqSh9saNG+/9Lg1433333VlNpm4Avnr16rt/X758eefPXbp0aXCwsEx/195GU9eo0ea+DrWvUYKnPI1yRvFcv3595/1IHp56quMyqqqmkUTrpouuaR9ZH9jJtVKCm10jjpdg6pHpXfeP9jTmS7gn7aLZ+WLuqYf3sZ5mV0B6lxHIZZSm6ZcBgCEENQEAYA/S0JdRHc0GvzT2Ze2wGkcmtEeTjtEMHvYZCdIemdOn8bwEtDaN7ukKeo09F9lmu1H3mKejTfq2RxmngXrK0aolL25q8M7orPa56xMI6bP+ak0N7+vW0zzE6OhjNkV+7hoFnlFtCbh1jeRciimnd839swS4igTE+j43argn9Z16du7ZGvaxnmbX6M9dZj8o99Y5p98FAI6HoCYAAEwsDbWffPLJe0G0NLwmoFnLOpr7HNnSbDztMxKka7rGXZVA4qbG8K60H9vwnXSrMUi9Txlp3D7mrtFSQyU4mfO4LbDx448/fhB4mCqQke08fPiwc6rbQ+oKIowdPcYflPwzRceEXCPtwFXJVzUFyvvKfXmq0f3rRrMu9Z606zStcwc097WeZtczelugtAScuzqmAADsQlATAICjdYi1DhNYyZSmze/eZ0BzqmNMILI9YmbsdKx9G0zbjaF9RgQl2LMtfbummn3+/PnZUCVA0V7PcdM5ef369eIbcrP/7WNOvp8i0JH0TEP5LqMuE2Bovy/r3k2hBESmHv05Vlcajx1txYf3rqlGI64LXi59Pc0pgrLJy+38nPvKkOdkLfekTZrB2rmnHt7Xeppdz7ptz/1a760AwHIIagIAcLTWjbbZx/SgaQRPcKHd2JsRGfuccrZ9LGOCnF999dXo/WlO+9e30TKNoe102jXQmvdta2jvmupuzDSFaZzNPufVbohfN8o0+WSXkXXtfZoieN21jaHbzTHfvXv3vd8l/cfsZ9IsaZqAz64B8exD870JYiQIMUaCIXmVaUJrkbTtylfW05xOc3Tf2Hy07p7W9buhup5l+57+OsGw5MMxHQi6Pp9recwIxlruSbushVvDSM0p7htdgdFNeTv31aRpztPSO/cAAIcjqAkAwNFaN41dn2lNd2ksTDAz62c2Gw7TYJfRERk9ss/Gu3ZjZRlp1FeCN2l4HTPqK58vgdE0Ag8ZCdIOhO4yFWEJPmwb/ZTz0G70jiGN883AV1cj9boRQvn9tu9LOrbPY/Ls2HzbtU9dI3j6nKtmemb/2uvI9l2DNnmm7/STOYZm+icIMXSN2BIcT16qbTTdumt7qWsz1ibXZTPwNCYfbepMMdXUs7neukaUTjmVeJd0ysg1l2tlSOC3PGea94ncR6YYuVfLPamtmY/mDmhGVz757LPPRm+3PfvBprJOzkXyfsoaRmkCAKOcAwDAwr19+/b81atXq9fLly/Pnz17dn737t3zFHe7Xh9//PH5o0eP3n1m11e2/fTp0/MHDx6cf/7556vtdG0/370P7f3IPnR9f36fv+d9eX/Sp0tz/8s28++bN28O2rcrV668+/4xPv300/eOJ/u16Xv7pnlXuuWc7irvTdolnxVJ4+b2khZt2cd8btN5Tb5sH39zm/l7Oa95bbsmyvVQ9rlruznfzfyyabvr0qO9n9nWrvLe7Fs+ty6v7uLOnTvv7Ud+7qPcM/p+bi5d97Sx19oSJb808+4QyWflnpfzve7ayCvXY/J4rqM++bprf4c2wbSfQ7kPbNrn9jNgyHVdtO9H5foo132f66X5nCivHMvUarkndaVh87kxh3xfVx6Z4riinQ/XnffyvqH5sNj0jAUAToOgJgAAi7cuuDfnKw1saUidqqFwXfBuyGtd4KM0MjYbpUtgM8eza+NrswF5ioBu0rDd8N0V2CwN5GkwnipAtKnBNQ3dJZjd1UCexvmuIGTSMcGXruNY1+C862tdQKB839BXX0mP9jlLvtqUnvlb2c+hwam2pGdzP3KutgWsc07KZ/YRYNnnfa7m/a05qNkOgPd5DQlKlfw1ZH/LPXmK15RBzUha5BrLezalS+7p7UBjPjMkSLy0e1Lz2d3VqWXf2s+l8myaSjt/tp9x+bmUNaY43/s4BgBgWX41bpwnAACcnkyxlinUMg1fpqfrWlNxn98dly5d2vreXdZWy/aaU8FlarxXr16tponLFIH5e6ZPzDRz5Riz3bwn05mWae2SBtnOFFNh5juzDmmmsi1ramZqyHx/tp//53vz/fneTPHbV/b19u3bZ/fv33/3HdlejjNpkGNPGrePNVOSrptSOH/LZ8r0smW6vXJM+dy6qQeHnNddplTc13bbcl6STplmMWmbYy9T9OZvuVayL2VdyPLK3zalS1/JD9mPTIuZKSPLmnh5de1HmZI3n8uUmjWtodnWznP5ubYpcpdm1+tjzLURuSaSB8dMu9k8/7tcz+1nwBTr8rbluvn5559X9+rcM3P95FrOfTT7mGvs+fPn762NnOvw3r17e5+GtZZ7UvPYu9Z13reue9qU078mnXKvLc+6PP/Kep2ZMjvpmzT97rvvTJUNAEziQiKb02wKAABYkjRCpyFyXeNtGiPTAJxgT3NNxzQEp8E6DZTZxj6DuvnONJgmoFj2Id+fBulN+95HjjPBreZxJhhQGmNzbFl/LAGkXdZHLemWBvVI4PvUgk85X48fP37vvEXSsgSny/pqc+9H6ZSQPJz8u+t5PbTse1n3Mddcrouag7D7kuPPNRW5/od0amB3Sevmmoy5XrrWmOx6XpRnRfJprrWcr0Pl2UPdkxLgLd+VtCkBvznluHJucmwJru/jeZRjTLA0z9LmfbasUTyVCxcurP6fbZdnLABwWgQ1AQAAgEUQ1KwzqMmHEtxLUDMS5Hv79u2hd2nxBDUBgI8OvQMAAAAAcEyawd9DTD0LAHCMBDUBAAAAYELN9TTLmpMAAIwjqAkAAAAAEylrd5apZ7NmJwAA4wlqAgAAAMBEHj9+/N46pAAATENQEwAAAAAm8u2337779+3btw+6LwAAx0RQEwAAAAAmmnr2l19+Wf37ypUrpp4FAJiQoCYAAAAATODRo0fv/n3z5s2D7gsAwLER1AQAAACACTx58uTdv7/++uuD7gsAwLER1AQAAACAkX744Yf3pp7NCwCA6QhqAgAAAPCB3//+9+/9/ObNm4PtyxI8ffr03b+N0gQAmJ6gJgAAAAAfBDTLqMPip59+Otj+LG3qWetpAgBM71d72CYAAAAACxyVmUDmixcvzh48eND5ni+++GI1CjFTq3788cer35tm9f2pZz/99FNpAgCwB4KaAAAAACfs22+/3Xm61ATv8mp6+fLlKpB3yh49evTu37dv3z7ovgA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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_force_distance_comparison(rr=[r1, r2], ff=[fmag1, fmag2], ll=[\"PM (smoothed)\", \"P3M\"], L=L, Np=Np, Npm=Npm, a=Newton_prefactor, title=\"Particle's contributions to total force\")#, ss=[\"o\", \".\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f26ada41", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "p3m", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/src/setup.py b/src/setup.py new file mode 100644 index 0000000..634cfc2 --- /dev/null +++ b/src/setup.py @@ -0,0 +1,51 @@ +#!/usr/bin/env python3 +# ---------------------------------------------------------------------- +# Copyright (C) 2024 Tristan Hoellinger +# Distributed under the GNU General Public License v3.0 (GPLv3). +# See the LICENSE file in the root directory for details. +# SPDX-License-Identifier: GPL-3.0-or-later +# ---------------------------------------------------------------------- + +__author__ = "Tristan Hoellinger" +__version__ = "0.1.0" +__date__ = "2025" +__license__ = "GPLv3" + +""" +Setup script for the WIP-P3M package. + +Personal package for debugging, testing and non-regression whilst +implementing P3M gravity in Simbelmynë. +""" + +from setuptools import setup, find_packages +import os + +# Read the long description from README.md +here = os.path.abspath(os.path.dirname(__file__)) +with open(os.path.join(here, "../README.md"), encoding="utf-8") as f: + long_description = f.read() + +setup( + name="wip3m", + version="0.1.0", + author="Tristan Hoellinger", + author_email="tristan.hoellinger@iap.fr", + description="Personal package for debugging, testing and non-" \ + "regression whilst implementing P3M gravity in Simbelmynë", + long_description=long_description, + long_description_content_type="text/markdown", + packages=find_packages(), + include_package_data=True, + package_data={"wip3m": ["preamble.tex"]}, + classifiers=[ + "Development Status :: 3 - Alpha", + "Intended Audience :: Science/Research", + "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", + "Programming Language :: Python :: 3", + "Topic :: Scientific/Engineering :: Astronomy", + ], + python_requires=">=3.7", + license="GPLv3", + keywords="cosmology large-scale-structure N-body", +) \ No newline at end of file diff --git a/src/wip3m/__init__.py b/src/wip3m/__init__.py new file mode 100644 index 0000000..a51e270 --- /dev/null +++ b/src/wip3m/__init__.py @@ -0,0 +1,21 @@ +#!/usr/bin/env python3 +# ---------------------------------------------------------------------- +# Copyright (C) 2025 Tristan Hoellinger +# Distributed under the GNU General Public License v3.0 (GPLv3). +# See the LICENSE file in the root directory for details. +# SPDX-License-Identifier: GPL-3.0-or-later +# ---------------------------------------------------------------------- + +__author__ = "Tristan Hoellinger" +__version__ = "0.1.0" +__date__ = "2025" +__license__ = "GPLv3" + +""" +WIP-P3M package. + +Personal package for debugging, testing and non-regression whilst +implementing the P3M algorithm in Simbelmynë. +""" + +from .params import * diff --git a/src/wip3m/logger.py b/src/wip3m/logger.py new file mode 100644 index 0000000..d7a4502 --- /dev/null +++ b/src/wip3m/logger.py @@ -0,0 +1,229 @@ +#!/usr/bin/env python3 +# ---------------------------------------------------------------------- +# Copyright (C) 2025 Tristan Hoellinger +# Distributed under the GNU General Public License v3.0 (GPLv3). +# See the LICENSE file in the root directory for details. +# SPDX-License-Identifier: GPL-3.0-or-later +# ---------------------------------------------------------------------- + +__author__ = "Tristan Hoellinger" +__version__ = "0.1.0" +__date__ = "2025" +__license__ = "GPLv3" + +""" +Logger routines for this project. + +The printing routines and colours are adapted from the Simbelmynë +cosmological solver (https://simbelmyne.readthedocs.io/en/latest), for +enhanced logging compatibility with Simbelmynë. +""" + +import sys +from typing import cast +import logging +from wip3m import DEFAULT_VERBOSE_LEVEL + +# Global variables for fonts +FONT_BOLDRED = "\033[1;31m" +FONT_BOLDGREEN = "\033[1;32m" +FONT_BOLDYELLOW = "\033[1;33m" +FONT_BOLDCYAN = "\033[1;36m" +FONT_BOLDGREY = "\033[1;37m" +FONT_LIGHTPURPLE = "\033[38;5;147m" + +FONT_NORMAL = "\033[00m" + +# Global variables for verbosity +ERROR_VERBOSITY = 0 +INFO_VERBOSITY = 1 +WARNING_VERBOSITY = 2 +DIAGNOSTIC_VERBOSITY = 3 +DEBUG_VERBOSITY = 4 +DIAGNOSTIC_LEVEL = 15 +logging.addLevelName(DIAGNOSTIC_LEVEL, "DIAGNOSTIC") + +G__ind__ = 0 # Global variable for logger indentation + + +def INDENT(): + """Indents the current level of outputs.""" + global G__ind__ + G__ind__ += 1 + return G__ind__ + + +def UNINDENT(): + """Unindents the current level of outputs.""" + global G__ind__ + G__ind__ -= 1 + return G__ind__ + + +def PrintLeftType(message_type, FONT_COLOR): + """Prints the type of output to screen. + + Parameters + ---------- + message_type (string) : type of message + FONT_COLOR (string) : font color for this type of message + + """ + from time import localtime, strftime + + sys.stdout.write( + "[" + + strftime("%H:%M:%S", localtime()) + + "|" + + FONT_COLOR + + message_type + + FONT_NORMAL + + "]" + ) + sys.stdout.write("==" * G__ind__) + sys.stdout.write("|") + + +def PrintInfo(message): + """Prints an information to screen. + + Parameters + ---------- + message (string) : message + + """ + if DEFAULT_VERBOSE_LEVEL >= INFO_VERBOSITY: + PrintLeftType("INFO ", FONT_BOLDCYAN) + sys.stdout.write("{}\n".format(message)) + sys.stdout.flush() + + +def PrintDiagnostic(verbosity, message): + """Prints a diagnostic to screen. + + Parameters + ---------- + verbosity (int) : verbosity of the message + message (string) : message + + """ + if DEFAULT_VERBOSE_LEVEL >= verbosity: + PrintLeftType("DIAGNOSTIC", FONT_BOLDGREY) + sys.stdout.write("{}\n".format(message)) + + +def PrintWarning(message): + """Prints a warning to screen. + + Parameters + ---------- + message (string) : message + + """ + if DEFAULT_VERBOSE_LEVEL >= WARNING_VERBOSITY: + PrintLeftType("WARNING ", FONT_BOLDYELLOW) + sys.stdout.write(FONT_BOLDYELLOW + message + FONT_NORMAL + "\n") + + +def PrintError(message): + """Prints an error to screen. + + Parameters + ---------- + message (string) : message + + """ + if DEFAULT_VERBOSE_LEVEL >= ERROR_VERBOSITY: + PrintLeftType("ERROR ", FONT_BOLDRED) + sys.stdout.write(FONT_BOLDRED + message + FONT_NORMAL + "\n") + + +class CustomLoggerHandler(logging.Handler): + """ + Custom logging handler to redirect Python logger messages to custom + print functions, with support for verbosity levels in debug + messages. + """ + + def emit(self, record): + """ + Emit a log record. + """ + try: + log_message = self.format(record) + log_level = record.levelno + + if log_level >= logging.ERROR: + PrintError(log_message) + elif log_level >= logging.WARNING: + PrintWarning(log_message) + elif log_level >= logging.INFO: + PrintInfo(log_message) + elif log_level == DIAGNOSTIC_LEVEL: + # Retrieve verbosity level from the record + verbosity = getattr(record, "verbosity", DIAGNOSTIC_VERBOSITY) + PrintDiagnostic(verbosity=verbosity, message=log_message) + elif log_level >= logging.DEBUG: + PrintDiagnostic(verbosity=DEBUG_VERBOSITY, message=log_message) + else: + # Fallback for other levels + PrintInfo(log_message) + except Exception: + self.handleError(record) + + +class CustomLogger(logging.Logger): + """ + Custom logger class supporting custom verbosity levels in diagnostic + messages. + """ + + def diagnostic(self, msg, *args, verbosity=DIAGNOSTIC_VERBOSITY, **kwargs) -> None: + """ + Log a message with DIAGNOSTIC level. + + Parameters + ---------- + msg : str + The message to log. + verbosity : int, optional + The verbosity level required to log this message. + """ + if self.isEnabledFor(DIAGNOSTIC_LEVEL): + # Pass verbosity as part of the extra argument + extra = kwargs.get("extra", {}) + extra["verbosity"] = verbosity + kwargs["extra"] = extra + self.log(DIAGNOSTIC_LEVEL, msg, *args, **kwargs) + + +logging.setLoggerClass(CustomLogger) + + +def getCustomLogger(name: str) -> CustomLogger: + """ + Get as CustomLogger instance to use the custom printing routines. + + Parameters + ---------- + name : str + The name of the logger. + + Returns + ------- + logger : logging.Logger + The custom logger instance. + """ + logging.setLoggerClass(CustomLogger) + logger = cast(CustomLogger, logging.getLogger(name)) # cast for type checkers and PyLance + logger.setLevel(logging.DEBUG) # Set the desired base logging level + + handler = CustomLoggerHandler() + formatter = logging.Formatter(f"{FONT_LIGHTPURPLE}(%(name)s){FONT_NORMAL} %(message)s") + handler.setFormatter(formatter) + + # Attach the handler to the logger if not already present + if not logger.handlers: + logger.addHandler(handler) + + return logger diff --git a/src/wip3m/low_level.py b/src/wip3m/low_level.py new file mode 100644 index 0000000..d52c1b4 --- /dev/null +++ b/src/wip3m/low_level.py @@ -0,0 +1,127 @@ +#!/usr/bin/env python3 +# ---------------------------------------------------------------------- +# Copyright (C) 2025 Tristan Hoellinger +# Distributed under the GNU General Public License v3.0 (GPLv3). +# See the LICENSE file in the root directory for details. +# SPDX-License-Identifier: GPL-3.0-or-later +# ---------------------------------------------------------------------- + +__author__ = "Tristan Hoellinger" +__version__ = "0.1.0" +__date__ = "2025" +__license__ = "GPLv3" + +""" +Tools to deal with low-level operations. +""" + +from contextlib import contextmanager +import platform +import ctypes +import io +import os, sys +import tempfile + +libc = ctypes.CDLL(None) +if platform.system() == "Darwin": # macOS + stdout_symbol = "__stdoutp" + stderr_symbol = "__stderrp" +else: + stdout_symbol = "stdout" + stderr_symbol = "stderr" +c_stdout = ctypes.c_void_p.in_dll(libc, stdout_symbol) +c_stderr = ctypes.c_void_p.in_dll(libc, stderr_symbol) + + +# Taken from: +# https://eli.thegreenplace.net/2015/redirecting-all-kinds-of-stdout-in-python/ +@contextmanager +def stdout_redirector(stream): + """A context manager that redirects stdout to the given stream. For + instance, this can be used to redirect C code stdout to None (to + avoid cluttering the log, e.g., when using tqdm). + + Args: + stream (file-like object): The stream to which stdout should be + redirected. + Example: + >>> with stdout_redirector(stream): + >>> print("Hello world!") # Will be printed to stream + >>> # instead of stdout. + """ + # The original fd stdout points to. Usually 1 on POSIX systems. + original_stdout_fd = sys.stdout.fileno() + + def _redirect_stdout(to_fd): + """Redirect stdout to the given file descriptor.""" + # Flush the C-level buffer stdout + libc.fflush(c_stdout) + # Flush and close sys.stdout - also closes the file descriptor (fd) + sys.stdout.close() + # Make original_stdout_fd point to the same file as to_fd + os.dup2(to_fd, original_stdout_fd) + # Create a new sys.stdout that points to the redirected fd + sys.stdout = io.TextIOWrapper(os.fdopen(original_stdout_fd, "wb")) + + # Save a copy of the original stdout fd in saved_stdout_fd + saved_stdout_fd = os.dup(original_stdout_fd) + try: + # Create a temporary file and redirect stdout to it + tfile = tempfile.TemporaryFile(mode="w+b") + _redirect_stdout(tfile.fileno()) + # Yield to caller, then redirect stdout back to the saved fd + yield + _redirect_stdout(saved_stdout_fd) + # Copy contents of temporary file to the given stream + tfile.flush() + tfile.seek(0, io.SEEK_SET) + stream.write(tfile.read()) + finally: + tfile.close() + os.close(saved_stdout_fd) + + +# Adapted from: +# https://eli.thegreenplace.net/2015/redirecting-all-kinds-of-stdout-in-python/ +@contextmanager +def stderr_redirector(stream): + """A context manager that redirects stderr to the given stream. + For instance, this can be used to redirect C code stderr to None (to + avoid cluttering the log, e.g., when using tqdm). + + Use with caution. + + Args: + stream (file-like object): The stream to which stdout should be + redirected. + """ + # The original fd stdout points to. Usually 1 on POSIX systems. + original_stderr_fd = sys.stderr.fileno() + + def _redirect_stderr(to_fd): + """Redirect stderr to the given file descriptor.""" + # Flush the C-level buffer stderr + libc.fflush(c_stderr) + # Flush and close sys.stderr - also closes the file descriptor (fd) + sys.stderr.close() + # Make original_stderr_fd point to the same file as to_fd + os.dup2(to_fd, original_stderr_fd) + # Create a new sys.stderr that points to the redirected fd + sys.stderr = io.TextIOWrapper(os.fdopen(original_stderr_fd, "wb")) + + # Save a copy of the original stdout fd in saved_stdout_fd + saved_stderr_fd = os.dup(original_stderr_fd) + try: + # Create a temporary file and redirect stdout to it + tfile = tempfile.TemporaryFile(mode="w+b") + _redirect_stderr(tfile.fileno()) + # Yield to caller, then redirect stdout back to the saved fd + yield + _redirect_stderr(saved_stderr_fd) + # Copy contents of temporary file to the given stream + tfile.flush() + tfile.seek(0, io.SEEK_SET) + stream.write(tfile.read()) + finally: + tfile.close() + os.close(saved_stderr_fd) diff --git a/src/wip3m/params.py b/src/wip3m/params.py new file mode 100644 index 0000000..8016571 --- /dev/null +++ b/src/wip3m/params.py @@ -0,0 +1,109 @@ +#!/usr/bin/env python3 +# ---------------------------------------------------------------------- +# Copyright (C) 2025 Tristan Hoellinger +# Distributed under the GNU General Public License v3.0 (GPLv3). +# See the LICENSE file in the root directory for details. +# SPDX-License-Identifier: GPL-3.0-or-later +# ---------------------------------------------------------------------- + +__author__ = "Tristan Hoellinger" +__version__ = "0.1.0" +__date__ = "2025" +__license__ = "GPLv3" + +"""Global parameters for this project.""" + +import os +from pathlib import Path +import numpy as np + +WHICH_SPECTRUM = "eh" # available options are "eh" and "class" + +# Load global paths from environment variables +ROOT_PATH = os.getenv("WIP3M_ROOT_PATH") +if ROOT_PATH is None: + raise EnvironmentError("Please set the 'WIP3M_ROOT_PATH' environment variable.") +OUTPUT_PATH = os.getenv("WIP3M_OUTPUT_PATH") +if OUTPUT_PATH is None: + raise EnvironmentError("Please set the 'WIP3M_OUTPUT_PATH' environment variable.") + +# Default verbose level +# 0: errors only, 1: info, 2: warnings+, 3: all diagnostics, 4+: debug +DEFAULT_VERBOSE_LEVEL = 2 + +# Baseline seeds for reproducibility +BASELINE_SEEDNORM = 100050599 +BASELINE_SEEDNOISE = 200050599 +BASELINE_SEEDPHASE = 300050599 + +# Fiducial cosmological parameters +h_planck = 0.6766 +Omega_b_planck = 0.02242 / h_planck**2 +Omega_m_planck = 0.3111 +nS_planck = 0.9665 +sigma8_planck = 0.8102 + +TAU_REIO = 0.066 + +planck_mean = np.array([h_planck, Omega_b_planck, Omega_m_planck, nS_planck, sigma8_planck]) +planck_cov = np.diag(np.array([0.0042, 0.00030, 0.0056, 0.0038, 0.0060]) ** 2) + +# Mapping from cosmological parameter names to corresponding indices +cosmo_params_names = [r"$h$", r"$\Omega_b$", r"$\Omega_m$", r"$n_S$", r"$\sigma_8$"] +cosmo_params_name_to_idx = {"h": 0, "Omega_b": 1, "Omega_m": 2, "n_s": 3, "sigma8": 4} + +# Minimum k value used in the normalisation of the summaries +MIN_K_NORMALISATION = 4e-2 + +params_planck_kmax_missing = { + "h": h_planck, + "Omega_r": 0.0, + "Omega_q": 1.0 - Omega_m_planck, + "Omega_b": Omega_b_planck, + "Omega_m": Omega_m_planck, + "m_ncdm": 0.0, + "Omega_k": 0.0, + "tau_reio": TAU_REIO, + "n_s": nS_planck, + "sigma8": sigma8_planck, + "w0_fld": -1.0, + "wa_fld": 0.0, + "WhichSpectrum": WHICH_SPECTRUM, +} + + +def z2a(z): + return 1.0 / (1 + z) + + +def cosmo_small_to_full_dict(cosmo_min): + """Return a full cosmology dictionary from a minimal one. + + Parameters + ---------- + cosmo_min : dict + Minimal cosmology dictionary. + + Returns + ------- + cosmo_full : dict + Full cosmology dictionary. + + """ + cosmo_full = { + "h": cosmo_min["h"], + "Omega_r": 0.0, + "Omega_q": 1 - cosmo_min["Omega_m"], + "Omega_b": cosmo_min["Omega_b"], + "Omega_m": cosmo_min["Omega_m"], + "m_ncdm": 0.0, + "Omega_k": 0.0, + "tau_reio": TAU_REIO, + "n_s": cosmo_min["n_s"], + "sigma8": cosmo_min["sigma8"], + "w0_fld": -1.0, + "wa_fld": 0.0, + "k_max": cosmo_min["k_max"], + "WhichSpectrum": cosmo_min["WhichSpectrum"], + } + return cosmo_full diff --git a/src/wip3m/plot_params.py b/src/wip3m/plot_params.py new file mode 100644 index 0000000..79df159 --- /dev/null +++ b/src/wip3m/plot_params.py @@ -0,0 +1,80 @@ +#!/usr/bin/env python3 +# ---------------------------------------------------------------------- +# Copyright (C) 2025 Tristan Hoellinger +# Distributed under the GNU General Public License v3.0 (GPLv3). +# See the LICENSE file in the root directory for details. +# SPDX-License-Identifier: GPL-3.0-or-later +# ---------------------------------------------------------------------- + +__author__ = "Tristan Hoellinger" +__version__ = "0.1.0" +__date__ = "2025" +__license__ = "GPLv3" + +""" +Plotting parameters and custom colormaps for the WIP-P3M package. + +This module provides custom Matplotlib settings, formatter classes, and +colormaps used for visualising results in the SelfiSys project. +""" + + +# Global font sizes +GLOBAL_FS = 18 +GLOBAL_FS_LARGE = 20 +GLOBAL_FS_XLARGE = 22 +GLOBAL_FS_SMALL = 16 +GLOBAL_FS_TINY = 14 +COLOUR_LIST = ["C{}".format(i) for i in range(10)] + + +def reset_plotting(): + import matplotlib as mpl + + mpl.rcParams.update(mpl.rcParamsDefault) + + +def setup_plotting(): + """ + Configure Matplotlib plotting settings for consistent appearance. + """ + import matplotlib.pyplot as plt + import importlib.resources + + with importlib.resources.open_text("wip3m", "preamble.tex") as f: + preamble = f.read() + + # Dictionary with rcParams settings + rcparams = { + "font.family": "serif", + "font.size": GLOBAL_FS, # Base font size + "axes.titlesize": GLOBAL_FS_XLARGE, + "axes.labelsize": GLOBAL_FS_LARGE, + "axes.linewidth": 1.0, + "xtick.labelsize": GLOBAL_FS_SMALL, + "ytick.labelsize": GLOBAL_FS_SMALL, + "xtick.major.width": 1.2, + "ytick.major.width": 1.2, + "xtick.minor.width": 1.0, + "ytick.minor.width": 1.0, + "xtick.direction": "in", + "ytick.direction": "in", + "xtick.major.pad": 5, + "xtick.minor.pad": 5, + "ytick.major.pad": 5, + "ytick.minor.pad": 5, + "legend.fontsize": GLOBAL_FS_SMALL, + "legend.title_fontsize": GLOBAL_FS_LARGE, + "figure.titlesize": GLOBAL_FS_XLARGE, + "figure.dpi": 300, + "grid.color": "gray", + "grid.linestyle": "dotted", + "grid.linewidth": 0.6, + "lines.linewidth": 2, + "lines.markersize": 8, + "text.usetex": True, + "text.latex.preamble": preamble, + } + + # Update rcParams + plt.rcParams.update(rcparams) diff --git a/src/wip3m/plot_utils.py b/src/wip3m/plot_utils.py new file mode 100644 index 0000000..a52cf9f --- /dev/null +++ b/src/wip3m/plot_utils.py @@ -0,0 +1,368 @@ +#!/usr/bin/env python3 +# ---------------------------------------------------------------------- +# Copyright (C) 2025 Tristan Hoellinger +# Distributed under the GNU General Public License v3.0 (GPLv3). +# See the LICENSE file in the root directory for details. +# SPDX-License-Identifier: GPL-3.0-or-later +# ---------------------------------------------------------------------- + +__author__ = "Tristan Hoellinger" +__version__ = "0.1.0" +__date__ = "2025" +__license__ = "GPLv3" + +"""Plotting utilities for the WIP-P3M package.""" + +import numpy as np +import matplotlib.pyplot as plt +import matplotlib.patches as mpatches +from matplotlib.colors import TwoSlopeNorm +from mpl_toolkits.axes_grid1 import make_axes_locatable +import cmocean.cm as cm + +from wip3m.plot_params import * + +# Configure global plotting settings +setup_plotting() + +fs = GLOBAL_FS_SMALL +fs_titles = GLOBAL_FS_LARGE +cols = COLOUR_LIST +cmap = cm.thermal + +def plotly_3d(field, size=128, L=None, colormap="RdYlBu", limits="max"): + """ + Create an interactive 3D plot of volume slices using Plotly. + + Parameters + ---------- + field : array-like + 3D data field to visualise. + size : int, optional + Size of the field along one dimension. Default is 128. + L : float, optional + Physical size of the field in Mpc/h. Used for axis labels only. + colormap : str, optional + Colour map for visualisation. Default is 'RdYlBu'. + limits : str, optional + Colour scale limits ('max', 'truncate', or 'default'). Default + is 'max'. + + Returns + ------- + go.Figure + Plotly figure object. + """ + import numpy as np + import plotly.graph_objects as go + + volume = field.T + rows, cols = volume[0].shape + + # Define colour scale limits + if limits == "max": + maxcol = np.max(np.abs(volume)) + mincol = -maxcol + elif limits == "truncate": + maxcol = min(np.max(-volume), np.max(volume)) + mincol = -maxcol + else: + maxcol = np.max(volume) + mincol = np.min(volume) + midcol = np.mean(volume) + + # Generate frames for the animation + nb_frames = size + frames = [ + go.Frame( + data=go.Surface( + z=(size - k) * np.ones((rows, cols)), + surfacecolor=np.flipud(volume[cols - 1 - k]), + cmin=mincol, + cmid=midcol, + cmax=maxcol, + ), + name=str(k), # Frames must be named for proper animation + ) + for k in range(nb_frames) + ] + + # Initial plot configuration + fig = go.Figure( + frames=frames, + data=go.Surface( + z=size * np.ones((rows, cols)), + surfacecolor=np.flipud(volume[cols // 2]), + colorscale=colormap, + cmin=mincol, + cmid=midcol, + cmax=maxcol, + colorbar=dict(thickness=20, ticklen=4), + ), + ) + + def frame_args(duration): + """Helper function to set animation frame arguments.""" + return { + "frame": {"duration": duration}, + "mode": "immediate", + "fromcurrent": True, + "transition": {"duration": duration, "easing": "linear"}, + } + + # Add animation slider + sliders = [ + { + "pad": {"b": 10, "t": 60}, + "len": 0.9, + "x": 0.1, + "y": 0, + "steps": [ + { + "args": [[f.name], frame_args(0)], + "label": str(k), + "method": "animate", + } + for k, f in enumerate(fig.frames) + ], + } + ] + + # Configure layout with or without physical size + layout_config = dict( + title="Slices in density field", + width=600, + height=600, + scene=dict( + zaxis=dict(range=[0, size - 1], autorange=False), + xaxis_title="x [Mpc/h]", + yaxis_title="y [Mpc/h]", + zaxis_title="z [Mpc/h]", + aspectratio=dict(x=1, y=1, z=1), + ), + updatemenus=[ + { + "buttons": [ + {"args": [None, frame_args(50)], "label": "▶", "method": "animate"}, + {"args": [[None], frame_args(0)], "label": "◼", "method": "animate"}, + ], + "direction": "left", + "pad": {"r": 10, "t": 70}, + "type": "buttons", + "x": 0.1, + "y": 0, + } + ], + sliders=sliders, + ) + if L is not None: + layout_config["scene"]["xaxis"] = dict( + ticktext=[0, L / 2, L], + tickvals=[0, size / 2, size], + title="x [Mpc/h]", + ) + layout_config["scene"]["yaxis"] = dict( + ticktext=[0, L / 2, L], + tickvals=[0, size / 2, size], + title="y [Mpc/h]", + ) + layout_config["scene"]["zaxis"]["ticktext"] = [0, L / 2, L] + layout_config["scene"]["zaxis"]["tickvals"] = [0, size / 2, size] + + fig.update_layout(**layout_config) + return fig + +def matplotlib_to_plotly(cmap, n=255): + """Convert a matplotlib colormap to a Plotly colorscale.""" + colorscale = [] + for i in range(n): + norm = i / (n - 1) + r, g, b, _ = cmap(norm) + colorscale.append([norm, f'rgb({int(r*255)}, {int(g*255)}, {int(b*255)})']) + return colorscale + +thermal_plotly = matplotlib_to_plotly(cm.thermal) + +def clear_large_plot(fig): + """ + Clear a figure to free up memory. + + Parameters + ---------- + fig : matplotlib.figure.Figure + The figure to clear. + """ + from IPython.display import clear_output + + del fig + clear_output() + +def load_force_diagnostic(filename): + """ + Load force diagnostic data. + + Parameters + ---------- + filename : str + Path to the CSV file written by `run_force_subtraction_test` + from p3m.c. + + Returns + ------- + r : ndarray + Bin-centred distances. + fmag : ndarray + Total force magnitudes |f_after - f_before|. + data : recarray + Full structured array with all columns. + """ + data = np.genfromtxt(filename, delimiter=",", names=True) + # Append the magnitude of force difference to the data + fmag = np.sqrt(data["fx"]**2 + data["fy"]**2 + data["fz"]**2) + data = np.lib.recfunctions.append_fields(data, "fmag", fmag, usemask=False, asrecarray=True) + + return data["distance"], data["fmag"], data + +def plot_force_distance(r, fmag, f_max=1e-1, a=None, title=None, save_path=None): + """ + Plot total force magnitude vs distance and a theoretical 1/r² profile. + + Parameters + ---------- + r : array_like + Distance values (bin centers or actual distances). + fmag : array_like + Corresponding force magnitudes. + f_max : float, optional + Maximum force magnitude for including points in the plot (default: 1e-1). + a : float or None, optional + If provided, the theoretical prefactor for the 1/r² profile. + title : str, optional + Plot title. + save_path : str or None, optional + If provided, path to save the figure as a PDF. + """ + from scipy.optimize import curve_fit + + # Select points to include in the plot + mask = fmag < f_max + rs = r[mask] + fmag_select = fmag[mask] + + fig, ax = plt.subplots() + ax.scatter(rs, fmag_select, s=10, alpha=0.8, label="Particle/hole pairs", color="tab:blue") + + # If a is provided, plot the theoretical curve + if a is not None: + def inverse_square(r, a): + return a / r**2 + r = np.linspace(np.min(rs), np.max(rs), 300) + f_th = inverse_square(r, a) + ax.plot(r, f_th, "r-", label=r"$\propto 1/r^2$") + + ax.set_xscale("log") + ax.set_yscale("log") + ax.set_xlabel(r"Distance $r$ [Mpc/$h$]") + ax.set_ylabel(r"Force magnitude [code units]") + if title is not None: + ax.set_title(title) + ax.legend() + ax.grid(True, which="both", ls=":", lw=0.5) + + plt.tight_layout() + if save_path: + plt.savefig(save_path) + print(f"Figure saved to: {save_path}") + plt.show() + +def plot_force_distance_comparison(rr, ff, ll, L, Np, Npm, ss=None, a=None, title=None, save_path=None): + """ + Plot force magnitude vs distance. + + Parameters + ---------- + rr : list of array_like + List of distance arrays. + ff : list of array_like + List of force magnitude arrays corresponding to each distance array. + ll : list of str + List of labels for each dataset. + ss : list of str or None, optional + List of symbols for each dataset (default: None). + L : float + Physical size of the field in Mpc/h. + Np : int + Number of particles per dimension. + Npm : int + Number of PM cells per dimension. + a : float or None, optional + If provided, the theoretical prefactor for the 1/r² profile. + title : str, optional + Plot title. + save_path : str or None, optional + If provided, path to save the figure as a PDF. + """ + fig, ax = plt.subplots() + + colours = plt.rcParams["axes.prop_cycle"].by_key()["color"] + handles1 = [] + + if ss is None: + ss = ["o"] * len(rr) + for i, (r, f, label, symbol) in enumerate(zip(rr, ff, ll, ss)): + scatter = ax.scatter(r, f, alpha=0.8, s=20, label=label, + color=colours[i % len(colours)], marker=symbol) + handles1.append(scatter) + + loc1="lower right" + + # Theoretical curve + theory_line = None + if a is not None and len(rr) > 0: + loc1="upper right" + def inverse_square(r, a): + return a / r**2 + r_min = min(np.min(r) for r in rr) + r_max = max(np.max(r) for r in rr) + r_plot = np.linspace(r_min, r_max, 300) + f_th = inverse_square(r_plot, a) + theory_line, = ax.plot(r_plot, f_th, "k-", label=r"theory $\propto 1/r^2$") + handles1.append(theory_line) + + # Characteristic vertical reference scales + nyquist = 2 * L / Npm + epsilon = 0.03 * L / Np + xs = 1.25 * L / Npm + xr = 4.5 * xs + line1 = ax.axvline(x=nyquist, color="black", linestyle="-", lw=1, label="Nyquist") + line2 = ax.axvline(x=2*epsilon, color="gray", linestyle="--", lw=2, label=r"Particle length $2\epsilon$") + line3 = ax.axvline(x=xs, color="gray", linestyle="-.", lw=2, label=r"Split scale $x_s$") + line4 = ax.axvline(x=xr, color="gray", linestyle=":", lw=2, label=r"Short-range reach $x_r$") + print(f"Nyquist: {nyquist:.2f} Mpc/h") + print(f"Particle length: {2*epsilon:.2f} Mpc/h") + print(f"Split scale: {xs:.2f} Mpc/h") + print(f"Short-range reach: {xr:.2f} Mpc/h") + + # Set log-log axes and labels + ax.set_xscale("log") + ax.set_yscale("log") + ax.set_xlabel(r"Distance $r$ [Mpc/$h$]") + ax.set_ylabel(r"Force magnitude [code units]") + if title is not None: + ax.set_title(title) + + # Legend for data + legend1 = ax.legend(handles=handles1, loc=loc1, frameon=True, fontsize=GLOBAL_FS_TINY) + ax.add_artist(legend1) + + # Legend for vertical lines + handles2 = [line1, line2, line3, line4] + fig.subplots_adjust(bottom=0.3) + legend2 = fig.legend(handles=handles2, loc='lower center', ncol=2, frameon=False) + + ax.grid(True, which="both", ls=":", lw=0.5) + + if save_path: + plt.savefig(save_path) + print(f"Figure saved to: {save_path}") + plt.show() \ No newline at end of file diff --git a/src/wip3m/preamble.tex b/src/wip3m/preamble.tex new file mode 100644 index 0000000..32428d8 --- /dev/null +++ b/src/wip3m/preamble.tex @@ -0,0 +1,14 @@ +% ---------------------------------------------------------------------- +% Copyright (C) 2025 Tristan Hoellinger +% Distributed under the GNU General Public License v3.0 (GPLv3). +% See the LICENSE file in the root directory for details. +% SPDX-License-Identifier: GPL-3.0-or-later +% ---------------------------------------------------------------------- + +% Author: Tristan Hoellinger +% Version: 0.1.0 +% Date: 2025 +% License: GPLv3 + +\usepackage{amsmath,amsfonts,amssymb,amsthm} +\usepackage{upgreek} diff --git a/src/wip3m/tools.py b/src/wip3m/tools.py new file mode 100644 index 0000000..fbb87eb --- /dev/null +++ b/src/wip3m/tools.py @@ -0,0 +1,424 @@ +#!/usr/bin/env python3 +# ---------------------------------------------------------------------- +# Copyright (C) 2025 Tristan Hoellinger +# Distributed under the GNU General Public License v3.0 (GPLv3). +# See the LICENSE file in the root directory for details. +# SPDX-License-Identifier: GPL-3.0-or-later +# ---------------------------------------------------------------------- + +__author__ = "Tristan Hoellinger" +__version__ = "0.1.0" +__date__ = "2025" +__license__ = "GPLv3" + +""" +Various tools for the WIP3M project. +""" + +import os +import gc +import numpy as np + +from wip3m.logger import getCustomLogger + +logger = getCustomLogger(__name__) + + +def none_bool_str(value): + """Convert a string to None, bool, or str. + + Parameters + ---------- + value : str + String to convert. + + Returns + ------- + None, bool, or str + Converted value. + """ + if value == "None" or value == None: + return None + elif value == "True": + return True + elif value == "False": + return False + return value + + +def get_k_max(L, size): + """ + Compute the maximum wavenumber for a given box size. + + Parameters + ---------- + L : float + Size of the box in Mpc/h. + size : int + Number of grid cells along each dimension. + + Returns + ------- + float + Maximum wavenumber in h/Mpc. + """ + from numpy import pi, sqrt + + # If kx = ky = kz = k_Nyquist, then |k| = sqrt(3) * k_Nyquist + return int(1e3 * sqrt(3) * pi * size / L + 1) * 1e-3 + +def joinstrs(list_of_strs): + """Join a list of strings into a single string. + + Parameters + ---------- + list_of_strs : list of str + List of strings to join. + + Returns + ------- + str + Concatenated string. + """ + return "".join([str(x) for x in list_of_strs if x is not None]) + + +def generate_sim_params(params_dict, ICs, workdir, outdir, file_ext=None, force=False): + """Write the parameter file. + + Parameters + ---------- + params_dict : dict + Dictionary containing the parameters for the simulation. + ICs : str + Path to the initial conditions. + workdir : str + Directory where to store the parameter file. + outdir : str + Directory where to store the simulation outputs. + file_ext : str, optional + Prefix for the output files. + + Returns + ------- + sbmy_path : str + Path to the parameter file generated. + + """ + from os.path import isfile + from pysbmy import param_file + from pysbmy.timestepping import StandardTimeStepping + + method = params_dict["method"] + path = workdir + file_ext + "_" if file_ext else workdir + simpath = outdir + file_ext + "_" if file_ext else outdir + sbmy_path = joinstrs([path, "example_", method, ".sbmy"]) + + # Parameters shared by all methods for this run + Particles = params_dict["Np"] + Mesh = params_dict["N"] + BoxSize = params_dict["L"] + corner0 = params_dict["corner0"] + corner1 = params_dict["corner1"] + corner2 = params_dict["corner2"] + h = params_dict["h"] + Omega_m = params_dict["Omega_m"] + Omega_b = params_dict["Omega_b"] + n_s = params_dict["n_s"] + sigma8 = params_dict["sigma8"] + + # Generate the time-stepping distribution + if method in ["pm", "cola", "spm", "p3m"]: + ts_filename = path + "ts_" + method + ".h5" + logger.info("Time-stepping distribution file: %s", ts_filename) + if not isfile(ts_filename) or force: + TimeStepDistribution = params_dict["TimeStepDistribution"] + ai = params_dict["ai"] + af = params_dict["af"] + nsteps = params_dict["nsteps"] + snapshots = np.full((nsteps), False) + TS = StandardTimeStepping(ai, af, snapshots, TimeStepDistribution) + TS.write(ts_filename) + else: + logger.info("Time-stepping distribution file already exists: %s", ts_filename) + StandardTimeStepping.read(ts_filename).plot(savepath=path + "ts_" + method + ".png") + elif method in ["lpt"]: + pass + else: + raise ValueError("Method not supported: {}".format(method)) + + # Write the parameter file + logger.info("Generating parameter file...") + if params_dict["method"] == "lpt": + S = param_file( + OutputRngStateLPT=simpath + "dummy.rng", + # Basic setup: + Particles=Particles, + Mesh=Mesh, + BoxSize=BoxSize, + corner0=corner0, + corner1=corner1, + corner2=corner2, + # Initial conditions: + ICsMode=params_dict["ICsMode"], + InputWhiteNoise=params_dict["InputWhiteNoise"], # None or str + WriteInitialConditions=1, + OutputInitialConditions=ICs, + # Power spectrum: + InputPowerSpectrum=params_dict["InputPowerSpectrum"], + # Final conditions for LPT: + OutputLPTSnapshot=simpath + "lpt_particles.gadget3", + OutputLPTDensity=simpath + "lpt_density.h5", + ############################# + ## Cosmological parameters ## + ############################# + h=h, + Omega_m=Omega_m, + Omega_b=Omega_b, + n_s=n_s, + sigma8=sigma8, + Omega_q=1.0 - Omega_m, + Omega_k=0.0, + w0_fld=-1.0, + wa_fld=0.0, + ) + if params_dict["method"] == "pm": + S = param_file( + # Basic setup: + Particles=Particles, + Mesh=Mesh, + BoxSize=BoxSize, + corner0=corner0, + corner1=corner1, + corner2=corner2, + # Initial conditions: + ICsMode=2, + InputInitialConditions=ICs, + # Final conditions for LPT: + RedshiftLPT=params_dict["RedshiftLPT"], + WriteLPTSnapshot=0, + WriteLPTDensity=0, + #################### + ## Module PM/COLA ## + #################### + ModulePMCOLA=1, + EvolutionMode=1, + ParticleMesh=params_dict["Npm"], + TimeStepDistribution=ts_filename, + # Final snapshot: + RedshiftFCs=params_dict["RedshiftFCs"], + WriteFinalSnapshot=1, + OutputFinalSnapshot=simpath + "pm_snapshot.gadget3", + WriteFinalDensity=1, + OutputFinalDensity=simpath + "final_density_pm.h5", + RunForceDiagnostic=params_dict["RunForceDiagnostic"], + nPairsForceDiagnostic=params_dict["nPairsForceDiagnostic"], + nBinsForceDiagnostic=params_dict["nBinsForceDiagnostic"], + maxTrialsForceDiagnostic=params_dict["maxTrialsForceDiagnostic"], + OutputForceDiagnostic=params_dict["OutputForceDiagnostic"], + ############################# + ## Cosmological parameters ## + ############################# + h=h, + Omega_m=Omega_m, + Omega_b=Omega_b, + n_s=n_s, + sigma8=sigma8, + Omega_q=1.0 - Omega_m, + Omega_k=0.0, + w0_fld=-1.0, + wa_fld=0.0, + ) + if params_dict["method"] == "cola": + S = param_file( + # Basic setup: + Particles=Particles, + Mesh=Mesh, + BoxSize=BoxSize, + corner0=corner0, + corner1=corner1, + corner2=corner2, + # Initial conditions: + ICsMode=2, + InputInitialConditions=ICs, + # Final conditions for LPT: + RedshiftLPT=params_dict["RedshiftLPT"], + WriteLPTSnapshot=0, + WriteLPTDensity=0, + #################### + ## Module PM/COLA ## + #################### + ModulePMCOLA=1, + EvolutionMode=2, + ParticleMesh=params_dict["Npm"], + TimeStepDistribution=ts_filename, + # Final snapshot: + RedshiftFCs=params_dict["RedshiftFCs"], + WriteFinalSnapshot=1, + OutputFinalSnapshot=simpath + "cola_snapshot.gadget3", + WriteFinalDensity=1, + OutputFinalDensity=simpath + "final_density_cola.h5", + RunForceDiagnostic=params_dict["RunForceDiagnostic"], + nPairsForceDiagnostic=params_dict["nPairsForceDiagnostic"], + nBinsForceDiagnostic=params_dict["nBinsForceDiagnostic"], + maxTrialsForceDiagnostic=params_dict["maxTrialsForceDiagnostic"], + OutputForceDiagnostic=params_dict["OutputForceDiagnostic"], + ############################# + ## Cosmological parameters ## + ############################# + h=h, + Omega_m=Omega_m, + Omega_b=Omega_b, + n_s=n_s, + sigma8=sigma8, + Omega_q=1.0 - Omega_m, + Omega_k=0.0, + w0_fld=-1.0, + wa_fld=0.0, + ) + elif params_dict["method"] == "p3m" or params_dict["method"] == "spm": + S = param_file( + # Basic setup: + Particles=Particles, + Mesh=Mesh, + BoxSize=BoxSize, + corner0=corner0, + corner1=corner1, + corner2=corner2, + # Initial conditions: + ICsMode=2, + InputInitialConditions=ICs, + # Final conditions for LPT: + RedshiftLPT=params_dict["RedshiftLPT"], + WriteLPTSnapshot=0, + WriteLPTDensity=0, + #################### + ## Module PM/COLA ## + #################### + ModulePMCOLA=1, + EvolutionMode=params_dict["EvolutionMode"], + ParticleMesh=params_dict["Npm"], + TimeStepDistribution=ts_filename, + # Final snapshot: + RedshiftFCs=params_dict["RedshiftFCs"], + WriteFinalSnapshot=1, + OutputFinalSnapshot=simpath + "{}_snapshot.gadget3".format(method), + WriteFinalDensity=1, + OutputFinalDensity=simpath + "final_density_{}.h5".format(method), + n_Tiles=params_dict["n_Tiles"], + RunForceDiagnostic=params_dict["RunForceDiagnostic"], + nPairsForceDiagnostic=params_dict["nPairsForceDiagnostic"], + nBinsForceDiagnostic=params_dict["nBinsForceDiagnostic"], + maxTrialsForceDiagnostic=params_dict["maxTrialsForceDiagnostic"], + OutputForceDiagnostic=params_dict["OutputForceDiagnostic"], + ############################# + ## Cosmological parameters ## + ############################# + h=h, + Omega_m=Omega_m, + Omega_b=Omega_b, + n_s=n_s, + sigma8=sigma8, + Omega_q=1.0 - Omega_m, + Omega_k=0.0, + w0_fld=-1.0, + wa_fld=0.0, + ) + + if not isfile(sbmy_path) or force: + S.write(sbmy_path) + logger.info("Parameter file written to %s", sbmy_path) + else: + logger.info("Parameter file already exists at %s", sbmy_path) + + return sbmy_path + + +def read_field(*args): + """ + Read a field from a file. + + Parameters + ---------- + args : tuple + Arguments to pass to the read_field function from pysbmy. + + Returns + ------- + field : str + The field read from the file. + """ + from io import BytesIO + from wip3m.low_level import stdout_redirector + from pysbmy.field import read_field as _read_field + + with BytesIO() as f: + with stdout_redirector(f): + return _read_field(*args) + + +def generate_white_noise_Field( + L, + size, + corner, + seedphase, + fname_whitenoise, + seedname_whitenoise, + force_phase=False, +): + """ + Generate a white noise realisation in physical space and write it to + disk. + + Parameters + ---------- + L : float + Size of the simulation box (in Mpc/h). + size : int + Number of grid points along each axis. + corner : float + Position of the corner (in Mpc/h). + seedphase : int or list of int + User-provided seed to generate the initial white noise. + fname_whitenoise : str + File path to write the white noise realisation. + seedname_whitenoise : str + File path to write the seed state of the RNG. + force_phase : bool, optional + If True, forces regeneration of the random phases. Default is + False. + + Raises + ------ + OSError + If file writing fails or directory paths are invalid. + RuntimeError + For unexpected issues. + """ + if not os.path.exists(fname_whitenoise) or force_phase: + from pysbmy.field import BaseField + + try: + logger.debug("Generating white noise for L=%.2f, size=%d", L, size) + rng = np.random.default_rng(seedphase) + + logger.debug("Saving RNG state to %s", seedname_whitenoise) + np.save(seedname_whitenoise, rng.bit_generator.state) + with open(seedname_whitenoise + ".txt", "w") as f: + f.write(str(rng.bit_generator.state)) + + data = rng.standard_normal(size=size**3) + wn = BaseField(L, L, L, corner, corner, corner, 1, size, size, size, data) + del data + + wn.write(fname_whitenoise) + logger.debug("White noise field written to %s", fname_whitenoise) + del wn + except OSError as e: + logger.error("Writing white noise failed at '%s': %s", fname_whitenoise, str(e)) + raise + except Exception as e: + logger.critical("Unexpected error in generate_white_noise_Field: %s", str(e)) + raise RuntimeError("generate_white_noise_Field failed.") from e + finally: + gc.collect()