{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "47c34537",
   "metadata": {},
   "source": [
    "Tristan Hoellinger<br/>\n",
    "Institut d'Astrophysique de Paris</br>\n",
    "tristan.hoellinger@iap.fr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b31e6021",
   "metadata": {},
   "source": [
    "# Exploring baseline CONCEPT time step limiters for P3M\n",
    "\n",
    "## Set up the environment and parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0f8c355d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# pyright: reportWildcardImportFromLibrary=false\n",
    "from wip3m import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2c415aeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "workdir = ROOT_PATH + \"results/\"\n",
    "output_path = OUTPUT_PATH\n",
    "\n",
    "# L = 8  # Box size in Mpc/h\n",
    "# N = 8  # Density grid size\n",
    "# Np = 8  # Number of dark matter particles per spatial dimension\n",
    "# Npm = 16  # PM grid size\n",
    "# n_Tiles = 2  # Make sure Npm/n_Tiles >= 6\n",
    "\n",
    "# L = 16  # Box size in Mpc/h\n",
    "# N = 16  # Density grid size\n",
    "# Np = 16  # Number of dark matter particles per spatial dimension\n",
    "# Npm = 32  # PM grid size\n",
    "# n_Tiles = 4  # Make sure Npm/n_Tiles >= 6\n",
    "\n",
    "# L = 32  # Box size in Mpc/h\n",
    "# N = 32  # Density grid size\n",
    "# Np = 32  # Number of dark matter particles per spatial dimension\n",
    "# Npm = 256  # PM grid size\n",
    "# n_Tiles = 32  # Make sure Npm/n_Tiles >= 6\n",
    "\n",
    "# L = 64  # Box size in Mpc/h\n",
    "# N = 64  # Density grid size\n",
    "# Np = 64  # Number of dark matter particles per spatial dimension\n",
    "# Npm = 128  # PM grid size\n",
    "# n_Tiles = 16  # Make sure Npm/n_Tiles >= 6\n",
    "\n",
    "# STANDARD PARAMETERS:\n",
    "L = 32  # Box size in Mpc/h\n",
    "N = 64  # 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 = force_hard = True\n",
    "run_id = \"notebook4\"\n",
    "\n",
    "TimeStepDistribution = 1 # 0: constant time step, 1: log\n",
    "nsteps = 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "03aa3f4e",
   "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",
    "from pysbmy.timestepping import StandardTimeStepping\n",
    "\n",
    "from wip3m.tools import get_k_max, generate_sim_params, generate_white_noise_Field, run_simulation\n",
    "from wip3m.params import params_CONCEPT_kmax_missing, cosmo_small_to_full_dict, z2a, BASELINE_SEEDPHASE\n",
    "from wip3m.plot_utils import *  # type: ignore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "57436422",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "k_max = 10.883000000000001\n"
     ]
    }
   ],
   "source": [
    "corner = 0.0\n",
    "RedshiftLPT = 199.0\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 = params_CONCEPT_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 to the time step logs\n",
    "OutputTimestepsLog = simdir + \"timesteps_log.txt\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3bc340d",
   "metadata": {},
   "source": [
    "### Generate the parameter files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "012c5e01",
   "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",
    "p3m_params = common_params.copy()\n",
    "p3m_params[\"method\"] = \"p3m\"\n",
    "p3m_params[\"EvolutionMode\"] = 4\n",
    "p3m_params[\"TimeStepDistribution\"] = TimeStepDistribution\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\n",
    "p3m_params[\"n_Tiles\"] = n_Tiles\n",
    "p3m_params[\"RunForceDiagnostic\"] = False\n",
    "p3m_params[\"PrintOutputTimestepsLog\"] = True\n",
    "p3m_params[\"OutputTimestepsLog\"] = OutputTimestepsLog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a162fa70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[01:56:09|\u001b[1;36mINFO      \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n",
      "[01:56:09|\u001b[38;5;113mSTATUS    \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/example_lpt.sbmy'...\n",
      "[01:56:09|\u001b[38;5;113mSTATUS    \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/example_lpt.sbmy' done.\n",
      "[01:56:09|\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/results/notebook4/example_lpt.sbmy\n",
      "[01:56:09|\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/results/notebook4/p3m_nsteps30_ts_p3m.h5\n",
      "[01:56:09|\u001b[38;5;113mSTATUS    \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_ts_p3m.h5'...\n",
      "[01:56:09|\u001b[38;5;113mSTATUS    \u001b[00m]|Write timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_ts_p3m.h5' done.\n",
      "[01:56:09|\u001b[1;36mINFO      \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m TS.ai = 0.005000, TS.af = 1.000000, TS.nsteps = 30\n",
      "[01:56:09|\u001b[38;5;113mSTATUS    \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_ts_p3m.h5'...\n",
      "[01:56:09|\u001b[38;5;113mSTATUS    \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_ts_p3m.h5' done.\n",
      "[01:56:10|\u001b[1;36mINFO      \u001b[00m]|\u001b[38;5;147m(wip3m.tools)\u001b[00m Generating parameter file...\n",
      "[01:56:10|\u001b[38;5;113mSTATUS    \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_example_p3m.sbmy'...\n",
      "[01:56:10|\u001b[38;5;113mSTATUS    \u001b[00m]|Writing parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_example_p3m.sbmy' done.\n",
      "[01:56:10|\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/results/notebook4/p3m_nsteps30_example_p3m.sbmy\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 500x100 with 1 Axes>"
      ]
     },
     "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",
    "file_ext = f\"p3m_nsteps{p3m_params['nsteps']}\"\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",
   "id": "51aa0ec3",
   "metadata": {},
   "source": [
    "Load time stepping:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a8aa16b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[01:56:10|\u001b[38;5;113mSTATUS    \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_ts_p3m.h5'...\n",
      "[01:56:10|\u001b[38;5;113mSTATUS    \u001b[00m]|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_ts_p3m.h5' done.\n"
     ]
    }
   ],
   "source": [
    "TS = StandardTimeStepping.read(wd + file_ext + \"_ts_p3m.h5\")\n",
    "aKickBeg = TS.aKickBeg\n",
    "aKickEnd = TS.aKickEnd\n",
    "aDriftBeg = TS.aDriftBeg\n",
    "aDriftEnd = TS.aDriftEnd\n",
    "aiDrift = TS.aiDrift\n",
    "afDrift = TS.afDrift"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56d49527",
   "metadata": {},
   "source": [
    "### Generate the initial phase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6969353d",
   "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": "af2c102d",
   "metadata": {},
   "source": [
    "### Generating the input power spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "eeddae78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[01:56:10|\u001b[38;5;113mSTATUS    \u001b[00m]|Setting up Fourier grid...\n",
      "[01:56:10|\u001b[38;5;113mSTATUS    \u001b[00m]|Setting up Fourier grid done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m][01:56:10|\u001b[38;5;113mSTATUS    \u001b[00m]|Write power spectrum in data file '/Users/hoellinger/WIP3M/notebook4/input_power.h5'...\n",
      "|Computing normalization of the power spectrum...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]|Computing normalization of the power spectrum done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]|Computing power spectrum...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]|Computing power spectrum done.\n",
      "[01:56:10|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mL0=32, L1=32, L2=32\u001b[00m\n",
      "[01:56:10|\u001b[38;5;246mDIAGNOSTIC\u001b[00m]==|\u001b[38;5;246mN0=64, N1=64, N2=64, N2_HC=33, N_HC=135168, NUM_MODES=1914\u001b[00m\n",
      "[01:56:10|\u001b[38;5;113mSTATUS    \u001b[00m]|Write power spectrum in data file '/Users/hoellinger/WIP3M/notebook4/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": "ed3ab1c8",
   "metadata": {},
   "source": [
    "## Running the simulations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e3ed21b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[01:56:10\u001b[00m|\u001b[38;5;227mCOMMAND   \u001b[00m]|\u001b[38;5;227msimbelmyne /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/example_lpt.sbmy /Users/hoellinger/WIP3M/notebook4/logs/lpt.txt\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|            .-~~-.--.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|           :         )\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|     .~ ~ -.\\       /.- ~~ .\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|     >       `.   .'       <\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|    (         .- -.         )\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|     `- -.-~  `- -'  ~-.- -'\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|       (        :        )           _ _ .-:        ___________________________________\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|        ~--.    :    .--~        .-~  .-~  }                    \u001b[1;38;5;157mSIMBELMYNË\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|            ~-.-^-.-~ \\_      .~  .-~   .~           (c) Florent Leclercq 2012 - SBMY_YEAR \n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|                     \\ '     \\ '_ _ -~              ___________________________________\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|                      `.`.    //\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|             . - ~ ~-.__`.`-.//\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|         .-~   . - ~  }~ ~ ~-.~-.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|       .' .-~      .-~       :/~-.~-./:\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|      /_~_ _ . - ~                 ~-.~-._\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|                                       ~-.<\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|2025-06-16 01:56:10: Starting SIMBELMYNË, commit hash bcdce9c1b02682972d65f1d3d414b5774015c141\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]|Reading parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/example_lpt.sbmy'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]|Reading parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/example_lpt.sbmy' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Initializing snapshot...\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Initializing snapshot done.\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|LPT snapshot initialization: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Returning initial conditions...\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Reading field in '/Users/hoellinger/WIP3M/notebook4/input_white_noise.h5'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Reading field in '/Users/hoellinger/WIP3M/notebook4/input_white_noise.h5' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Reading power spectrum...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Reading power spectrum in '/Users/hoellinger/WIP3M/notebook4/input_power.h5'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Reading power spectrum in '/Users/hoellinger/WIP3M/notebook4/input_power.h5' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Reading power spectrum done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Generating Gaussian random field (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Generating Gaussian random field (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing field to '/Users/hoellinger/WIP3M/notebook4/initial_density.h5'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing field to '/Users/hoellinger/WIP3M/notebook4/initial_density.h5' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Returning initial conditions done.\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|LPT initial conditions: 0.006 CPU - 0.006 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Evolving with Lagrangian perturbation theory (using 8 cores)...\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Computing Lagrangian potentials, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Computing Lagrangian potentials, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Computing Lagrangian displacement field (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Computing Lagrangian displacement field (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Changing velocities of particles...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Changing velocities of particles done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Displacing particles...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Displacing particles done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Evolving with Lagrangian perturbation theory (using 8 cores) done.\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|LPT evolution: 0.235 CPU - 0.071 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Computing outputs...\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing field to '/Users/hoellinger/WIP3M/notebook4/lpt_density.h5'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing field to '/Users/hoellinger/WIP3M/notebook4/lpt_density.h5' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing header in '/Users/hoellinger/WIP3M/notebook4/lpt_particles.gadget3'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing header in '/Users/hoellinger/WIP3M/notebook4/lpt_particles.gadget3' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing snapshot in '/Users/hoellinger/WIP3M/notebook4/lpt_particles.gadget3' (32768 particles)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'POS '...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'POS ' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'VEL '...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'VEL ' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'ID  '...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'ID  ' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing snapshot in '/Users/hoellinger/WIP3M/notebook4/lpt_particles.gadget3' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Computing outputs done.\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|LPT output: 0.015 CPU - 0.006 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|ModuleLPT: 0.256 CPU - 0.083 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|Simbelmynë: 0.257 CPU - 0.084 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|Everything done successfully, exiting.\n"
     ]
    }
   ],
   "source": [
    "run_simulation(\"lpt\", lpt_params, wd, logdir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "39c97bc2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[01:56:10\u001b[00m|\u001b[38;5;227mCOMMAND   \u001b[00m]|\u001b[38;5;227msimbelmyne /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_example_p3m.sbmy /Users/hoellinger/WIP3M/notebook4/logs/p3m_nsteps30p3m.txt\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|            .-~~-.--.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|           :         )\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|     .~ ~ -.\\       /.- ~~ .\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|     >       `.   .'       <\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|    (         .- -.         )\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|     `- -.-~  `- -'  ~-.- -'\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|       (        :        )           _ _ .-:        ___________________________________\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|        ~--.    :    .--~        .-~  .-~  }                    \u001b[1;38;5;157mSIMBELMYNË\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|            ~-.-^-.-~ \\_      .~  .-~   .~           (c) Florent Leclercq 2012 - SBMY_YEAR \n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|                     \\ '     \\ '_ _ -~              ___________________________________\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|                      `.`.    //\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|             . - ~ ~-.__`.`-.//\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|         .-~   . - ~  }~ ~ ~-.~-.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|       .' .-~      .-~       :/~-.~-./:\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|      /_~_ _ . - ~                 ~-.~-._\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|                                       ~-.<\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|\n",
      "[01:56:10\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|2025-06-16 01:56:10: Starting SIMBELMYNË, commit hash bcdce9c1b02682972d65f1d3d414b5774015c141\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]|Reading parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_example_p3m.sbmy'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]|Reading parameter file in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_example_p3m.sbmy' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Initializing snapshot...\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Initializing snapshot done.\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|LPT snapshot initialization: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Returning initial conditions...\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Reading field in '/Users/hoellinger/WIP3M/notebook4/initial_density.h5'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Reading field in '/Users/hoellinger/WIP3M/notebook4/initial_density.h5' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Returning initial conditions done.\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|LPT initial conditions: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Evolving with Lagrangian perturbation theory (using 8 cores)...\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Computing Lagrangian potentials, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Computing Lagrangian potentials, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Computing Lagrangian displacement field (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Computing Lagrangian displacement field (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Changing velocities of particles...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Changing velocities of particles done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Displacing particles...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Displacing particles done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleLPT: Evolving with Lagrangian perturbation theory (using 8 cores) done.\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|LPT evolution: 0.223 CPU - 0.060 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|ModuleLPT: 0.224 CPU - 0.060 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleP3M: Evolving with P3M...\u001b[00m\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_ts_p3m.h5'...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Read timestepping configuration in '/Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/p3m_nsteps30_ts_p3m.h5' done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|OutputForceDiagnostic: force_diagnostic.csv\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|OutputSnapshotsBase: particles_\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 1/30, time_kick:0.005000, time_drift=0.005000.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 1/30 done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 1/30, time_kick:0.005462, time_drift=0.005966.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Density: 0.008 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Accelerations (long-range): 0.092 CPU - 0.021 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Accelerations (short-range): 0.254 CPU - 0.041 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 1/30: Total Evolution: 0.367 CPU - 0.069 wallclock seconds used.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 2/30, time_kick:0.005462, time_drift=0.005966.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 2/30 done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:10\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 2/30, time_kick:0.006517, time_drift=0.007118.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Density: 0.010 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Potential: 0.007 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Accelerations (long-range): 0.096 CPU - 0.036 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Accelerations (short-range): 0.256 CPU - 0.069 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Kick: 0.007 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 2/30: Total Evolution: 0.378 CPU - 0.114 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 3/30, time_kick:0.006517, time_drift=0.007118.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 3/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 3/30, time_kick:0.007775, time_drift=0.008493.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Density: 0.011 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Potential: 0.006 CPU - 0.004 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Accelerations (long-range): 0.097 CPU - 0.027 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Accelerations (short-range): 0.252 CPU - 0.053 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Kick: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 3/30: Total Evolution: 0.374 CPU - 0.090 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 4/30, time_kick:0.007775, time_drift=0.008493.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 4/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 4/30, time_kick:0.009277, time_drift=0.010134.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Density: 0.012 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Potential: 0.006 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Accelerations (long-range): 0.095 CPU - 0.025 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Accelerations (short-range): 0.258 CPU - 0.050 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Kick: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 4/30: Total Evolution: 0.378 CPU - 0.083 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 5/30, time_kick:0.009277, time_drift=0.010134.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 5/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 5/30, time_kick:0.011069, time_drift=0.012091.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Density: 0.011 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Accelerations (long-range): 0.091 CPU - 0.021 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Accelerations (short-range): 0.245 CPU - 0.041 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 5/30: Total Evolution: 0.360 CPU - 0.069 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 6/30, time_kick:0.011069, time_drift=0.012091.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 6/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 6/30, time_kick:0.013208, time_drift=0.014427.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Density: 0.012 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Potential: 0.005 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Accelerations (long-range): 0.095 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Accelerations (short-range): 0.250 CPU - 0.037 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Kick: 0.005 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Drift: 0.001 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 6/30: Total Evolution: 0.369 CPU - 0.063 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 7/30, time_kick:0.013208, time_drift=0.014427.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 7/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 7/30, time_kick:0.015759, time_drift=0.017214.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Density: 0.013 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Accelerations (long-range): 0.094 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Accelerations (short-range): 0.251 CPU - 0.037 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 7/30: Total Evolution: 0.371 CPU - 0.064 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 8/30, time_kick:0.015759, time_drift=0.017214.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 8/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 8/30, time_kick:0.018803, time_drift=0.020539.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Density: 0.012 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Accelerations (long-range): 0.091 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Accelerations (short-range): 0.253 CPU - 0.037 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Drift: 0.001 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 8/30: Total Evolution: 0.370 CPU - 0.063 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 9/30, time_kick:0.018803, time_drift=0.020539.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 9/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 9/30, time_kick:0.022435, time_drift=0.024506.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Density: 0.012 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Accelerations (long-range): 0.095 CPU - 0.019 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Accelerations (short-range): 0.256 CPU - 0.036 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Drift: 0.001 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 9/30: Total Evolution: 0.375 CPU - 0.061 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 10/30, time_kick:0.022435, time_drift=0.024506.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 10/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 10/30, time_kick:0.026769, time_drift=0.029240.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Density: 0.013 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Accelerations (long-range): 0.093 CPU - 0.024 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Accelerations (short-range): 0.239 CPU - 0.038 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Kick: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 10/30: Total Evolution: 0.359 CPU - 0.069 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 11/30, time_kick:0.026769, time_drift=0.029240.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 11/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 11/30, time_kick:0.031940, time_drift=0.034888.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Density: 0.011 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Accelerations (long-range): 0.092 CPU - 0.021 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Accelerations (short-range): 0.260 CPU - 0.039 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 11/30: Total Evolution: 0.376 CPU - 0.067 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 12/30, time_kick:0.031940, time_drift=0.034888.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 12/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 12/30, time_kick:0.038109, time_drift=0.041628.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Density: 0.012 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Accelerations (long-range): 0.095 CPU - 0.023 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Accelerations (short-range): 0.248 CPU - 0.043 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Kick: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 12/30: Total Evolution: 0.368 CPU - 0.073 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 13/30, time_kick:0.038109, time_drift=0.041628.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 13/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 13/30, time_kick:0.045471, time_drift=0.049669.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Density: 0.013 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Potential: 0.007 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Accelerations (long-range): 0.088 CPU - 0.031 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Accelerations (short-range): 0.244 CPU - 0.060 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Kick: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 13/30: Total Evolution: 0.360 CPU - 0.099 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 14/30, time_kick:0.045471, time_drift=0.049669.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 14/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 14/30, time_kick:0.054254, time_drift=0.059263.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Density: 0.008 CPU - 0.006 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Potential: 0.007 CPU - 0.005 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Accelerations (long-range): 0.092 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Accelerations (short-range): 0.252 CPU - 0.052 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Kick: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 14/30: Total Evolution: 0.367 CPU - 0.086 wallclock seconds used.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 15/30, time_kick:0.054254, time_drift=0.059263.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 15/30 done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:11\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 15/30, time_kick:0.064734, time_drift=0.070711.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Density: 0.012 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Accelerations (long-range): 0.096 CPU - 0.021 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Accelerations (short-range): 0.258 CPU - 0.037 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Kick: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 15/30: Total Evolution: 0.379 CPU - 0.065 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 16/30, time_kick:0.064734, time_drift=0.070711.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 16/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 16/30, time_kick:0.077239, time_drift=0.084370.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Density: 0.011 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Accelerations (long-range): 0.089 CPU - 0.022 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Accelerations (short-range): 0.258 CPU - 0.036 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Kick: 0.005 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 16/30: Total Evolution: 0.371 CPU - 0.065 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 17/30, time_kick:0.077239, time_drift=0.084370.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 17/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 17/30, time_kick:0.092159, time_drift=0.100667.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Density: 0.013 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Accelerations (long-range): 0.093 CPU - 0.019 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Accelerations (short-range): 0.264 CPU - 0.036 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 17/30: Total Evolution: 0.383 CPU - 0.061 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 18/30, time_kick:0.092159, time_drift=0.100667.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 18/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 18/30, time_kick:0.109961, time_drift=0.120112.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Density: 0.013 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Accelerations (long-range): 0.099 CPU - 0.022 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Accelerations (short-range): 0.267 CPU - 0.037 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Kick: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 18/30: Total Evolution: 0.393 CPU - 0.066 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 19/30, time_kick:0.109961, time_drift=0.120112.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 19/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 19/30, time_kick:0.131201, time_drift=0.143314.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Density: 0.014 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Accelerations (long-range): 0.095 CPU - 0.018 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Accelerations (short-range): 0.272 CPU - 0.037 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 19/30: Total Evolution: 0.395 CPU - 0.061 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 20/30, time_kick:0.131201, time_drift=0.143314.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 20/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 20/30, time_kick:0.156545, time_drift=0.170998.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Density: 0.015 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Accelerations (long-range): 0.092 CPU - 0.019 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Accelerations (short-range): 0.269 CPU - 0.037 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 20/30: Total Evolution: 0.389 CPU - 0.062 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 21/30, time_kick:0.156545, time_drift=0.170998.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 21/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 21/30, time_kick:0.186784, time_drift=0.204029.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Density: 0.012 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Accelerations (long-range): 0.089 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Accelerations (short-range): 0.277 CPU - 0.038 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 21/30: Total Evolution: 0.390 CPU - 0.064 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 22/30, time_kick:0.186784, time_drift=0.204029.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 22/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 22/30, time_kick:0.222865, time_drift=0.243440.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Density: 0.013 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Potential: 0.005 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Accelerations (long-range): 0.091 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Accelerations (short-range): 0.275 CPU - 0.094 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Kick: 0.005 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Drift: 0.001 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 22/30: Total Evolution: 0.391 CPU - 0.121 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 23/30, time_kick:0.222865, time_drift=0.243440.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 23/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 23/30, time_kick:0.265915, time_drift=0.290464.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Density: 0.010 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Accelerations (long-range): 0.095 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Accelerations (short-range): 0.299 CPU - 0.066 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Kick: 0.007 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 23/30: Total Evolution: 0.418 CPU - 0.094 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 24/30, time_kick:0.265915, time_drift=0.290464.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 24/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 24/30, time_kick:0.317281, time_drift=0.346572.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Density: 0.013 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Potential: 0.007 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Accelerations (long-range): 0.092 CPU - 0.019 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Accelerations (short-range): 0.322 CPU - 0.052 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Drift: 0.001 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 24/30: Total Evolution: 0.441 CPU - 0.078 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 25/30, time_kick:0.317281, time_drift=0.346572.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 25/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 25/30, time_kick:0.378569, time_drift=0.413519.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Density: 0.016 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Accelerations (long-range): 0.087 CPU - 0.021 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Accelerations (short-range): 0.354 CPU - 0.051 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Drift: 0.001 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 25/30: Total Evolution: 0.470 CPU - 0.079 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 26/30, time_kick:0.378569, time_drift=0.413519.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 26/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 26/30, time_kick:0.451695, time_drift=0.493396.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Density: 0.014 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Accelerations (long-range): 0.093 CPU - 0.019 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Accelerations (short-range): 0.394 CPU - 0.058 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Drift: 0.001 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 26/30: Total Evolution: 0.513 CPU - 0.084 wallclock seconds used.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 27/30, time_kick:0.451695, time_drift=0.493396.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 27/30 done.\n",
      "[01:56:12\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 27/30, time_kick:0.538948, time_drift=0.588704.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Density: 0.017 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Accelerations (long-range): 0.094 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Accelerations (short-range): 0.446 CPU - 0.070 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Drift: 0.002 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 27/30: Total Evolution: 0.570 CPU - 0.096 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 28/30, time_kick:0.538948, time_drift=0.588704.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 28/30 done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 28/30, time_kick:0.643054, time_drift=0.702422.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Density: 0.009 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Potential: 0.007 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Accelerations (long-range): 0.095 CPU - 0.020 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Accelerations (short-range): 0.508 CPU - 0.096 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Kick: 0.006 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Drift: 0.002 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 28/30: Total Evolution: 0.626 CPU - 0.124 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 29/30, time_kick:0.643054, time_drift=0.702422.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 29/30 done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 29/30, time_kick:0.767270, time_drift=0.838106.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Density: 0.014 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Potential: 0.006 CPU - 0.002 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Accelerations (long-range): 0.094 CPU - 0.019 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Accelerations (short-range): 0.618 CPU - 0.113 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Kick: 0.007 CPU - 0.001 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Drift: 0.001 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 29/30: Total Evolution: 0.740 CPU - 0.138 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: Begin P3M step 30/30, time_kick:0.767270, time_drift=0.838106.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|ModuleP3M: Compute time step limiters for step 30/30 done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Drifting particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Getting gravitational potential, periodic boundary conditions (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Kicking particles (using 8 cores) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|ModuleP3M: End P3M step 30/30, time_kick:1.000000, time_drift=1.000000.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Density: 0.031 CPU - 0.006 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Potential: 0.012 CPU - 0.004 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Accelerations (long-range): 0.184 CPU - 0.039 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Accelerations (short-range): 1.513 CPU - 0.289 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Kick: 0.012 CPU - 0.003 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Drift: 0.001 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Step 30/30: Total Evolution: 1.753 CPU - 0.341 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Density: 0.386 CPU - 0.085 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Potential: 0.186 CPU - 0.070 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Accelerations (long-range): 2.882 CPU - 0.665 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Accelerations (short-range): 10.111 CPU - 1.780 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Kick: 0.183 CPU - 0.050 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Drift: 0.045 CPU - 0.018 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Inputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Diagnostic: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Outputs: 0.000 CPU - 0.000 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]==|Box: Total Evolution: 13.793 CPU - 2.668 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModuleP3M: Evolving with P3M done.\u001b[00m\n",
      "[01:56:13\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModulePMCOLA: Computing outputs...\u001b[00m\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Getting density contrast (using 8 cores and 8 arrays, parallel routine 1) done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing field to '/Users/hoellinger/WIP3M/notebook4/p3m_nsteps30_final_density_p3m.h5'...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing field to '/Users/hoellinger/WIP3M/notebook4/p3m_nsteps30_final_density_p3m.h5' done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing header in '/Users/hoellinger/WIP3M/notebook4/p3m_nsteps30_p3m_snapshot.gadget3'...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing header in '/Users/hoellinger/WIP3M/notebook4/p3m_nsteps30_p3m_snapshot.gadget3' done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing snapshot in '/Users/hoellinger/WIP3M/notebook4/p3m_nsteps30_p3m_snapshot.gadget3' (32768 particles)...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'POS '...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'POS ' done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'VEL '...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'VEL ' done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'ID  '...\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]====|Writing block: 'ID  ' done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;113mSTATUS    \u001b[00m]==|Writing snapshot in '/Users/hoellinger/WIP3M/notebook4/p3m_nsteps30_p3m_snapshot.gadget3' done.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;147mMODULE    \u001b[00m]|\u001b[38;5;147mModulePMCOLA: Computing outputs done.\u001b[00m\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|PMCOLA output: 0.013 CPU - 0.005 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|ModulePMCOLA: 14.043 CPU - 2.919 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;159mTIMER     \u001b[00m]|Simbelmynë: 14.268 CPU - 2.980 wallclock seconds used.\n",
      "[01:56:13\u001b[00m|\u001b[38;5;117mINFO      \u001b[00m]|Everything done successfully, exiting.\n"
     ]
    }
   ],
   "source": [
    "run_simulation(\"p3m\", p3m_params, wd, logdir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7d24f105",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[01:56:13|\u001b[1;36mINFO      \u001b[00m]|\u001b[38;5;147m(wip3m.plot_utils)\u001b[00m Plotting timestep limiters from /Users/hoellinger/WIP3M/notebook4/timesteps_log.txt...\n",
      "[01:56:14|\u001b[1;36mINFO      \u001b[00m]==|\u001b[38;5;147m(wip3m.plot_utils)\u001b[00m Figure saved to: /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/simbelmyne/simbelmyne2025/WIP_P3M/results/notebook4/time_step_diagnostics.pdf\n",
      "[01:56:14|\u001b[1;36mINFO      \u001b[00m]|\u001b[38;5;147m(wip3m.plot_utils)\u001b[00m Plotting timestep limiters from /Users/hoellinger/WIP3M/notebook4/timesteps_log.txt done.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1650x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_timestepping_diagnostics(\n",
    "    log_path=OutputTimestepsLog,\n",
    "    aiDrift=aiDrift,\n",
    "    TimeStepDistribution=TimeStepDistribution,\n",
    "    nsteps=nsteps,\n",
    "    save_path=wd+\"time_step_diagnostics.pdf\",\n",
    "    show=False,\n",
    ")\n",
    "a = aiDrift\n",
    "plt.loglog(a, 0.1 * 0.031 * np.ones_like(a) / a)\n",
    "plt.loglog(a, 1e-2 * np.ones_like(a))\n",
    "fac_p3m_concept = 0.14\n",
    "lambda_p3m = lambda x, eta: eta * np.maximum(0.1 * 0.031 / x, 0.01)/fac_p3m_concept\n",
    "approx_P3Mlim = lambda_p3m(a, fac_p3m_concept)\n",
    "plt.loglog(a, approx_P3Mlim, color=\"black\")\n",
    "approx_P3Mlim_eta01 = lambda_p3m(a, 0.1)\n",
    "plt.loglog(a, approx_P3Mlim_eta01, color=\"red\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1c096bb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dadb9198",
   "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
}