{
 "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": [
    "# Fit the P3M limiter from existing simulation data\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": "31d95b9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "workdir = ROOT_PATH + \"results/\"\n",
    "output_path = OUTPUT_PATH"
   ]
  },
  {
   "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, join\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import json\n",
    "\n",
    "from pysbmy.timestepping import P3MTimeStepping\n",
    "\n",
    "from wip3m.plot_utils import *  # type: ignore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "57436422",
   "metadata": {},
   "outputs": [],
   "source": [
    "run_id = \"COLAr7/CV2_cola_Pf_L80_N160_Np160\"\n",
    "# run_id = \"COLAr6/V3cola_Pf_L1024_N512_Np512\"\n",
    "# run_id = \"COLAr6/V3cola_Pf_L1024_N1024_Np512\"\n",
    "# run_id = \"COLAr6/V3cola_Pf_L512_N1024_Np512\"\n",
    "# run_id = \"COLAr6/V3cola_Pf_LNNp512\"\n",
    "# run_id = \"COLAr3/cola_2_07_05_L1024_N1024_Np512\"\n",
    "# run_id = \"COLAr3/cola_L512_N1024_Np512\"\n",
    "wd = workdir + run_id + \"/\"\n",
    "simdir = output_path + run_id + \"/\"\n",
    "outdir = simdir + \"plots/\"\n",
    "\n",
    "OutputTimestepsLog_list = [\n",
    "    simdir + \"colap3m1_timestep_log.txt\",\n",
    "    simdir + \"colap3m2_timestep_log.txt\",\n",
    "]\n",
    "TSpath_list = [\n",
    "    wd + f\"p3m1_rscale0_35_ts_p3m.h5\",\n",
    "    wd + f\"p3m2_rescale0_7_ts_p3m.h5\",\n",
    "]\n",
    "\n",
    "# OutputTimestepsLog_list = [\n",
    "#     simdir + \"colap3m1_timestep_log.txt\",\n",
    "#     simdir + \"colap3m2_timestep_log.txt\",\n",
    "# ]\n",
    "# TSpath_list = [\n",
    "#     wd + f\"p3m1_relax2_0_ts_p3m.h5\",\n",
    "#     wd + f\"p3m2_relax0_7_ts_p3m.h5\",\n",
    "#     # wd + f\"p3m2_relax1_0_ts_p3m.h5\",\n",
    "# ]\n",
    "\n",
    "# run_id = \"notebook8\"\n",
    "# wd = workdir + run_id + \"/\"\n",
    "# simdir = output_path + run_id + \"/\"\n",
    "# OutputTimestepsLog_list = [\n",
    "#     simdir + \"timesteps_log_sim0.txt\",\n",
    "#     simdir + \"timesteps_log_sim1.txt\",\n",
    "#     simdir + \"timesteps_log_sim2.txt\",\n",
    "# ]\n",
    "# SimParams_list = [\n",
    "#     simdir + f\"sim_params_p3m_sim0.json\",\n",
    "#     simdir + f\"sim_params_p3m_sim1.json\",\n",
    "#     simdir + f\"sim_params_p3m_sim2.json\",\n",
    "# ]\n",
    "# TSpath_list = [\n",
    "#     wd + f\"sim0_ts_p3m.h5\",\n",
    "#     wd + f\"sim1_ts_p3m.h5\",\n",
    "#     wd + f\"sim2_ts_p3m.h5\",\n",
    "# ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7126d1c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "N_sim_fit = len(OutputTimestepsLog_list)\n",
    "all_sim_params_p3m = []\n",
    "\n",
    "# Load simulation parameters from JSON files\n",
    "# fac_hubble_list = []\n",
    "# fac_bend_list = []\n",
    "# da_early_list = []\n",
    "# for sim_idx in range(N_sim_fit):\n",
    "#     sim_params_path = SimParams_list[sim_idx]\n",
    "#     if not isfile(sim_params_path):\n",
    "#         raise FileNotFoundError(f\"Simulation parameters file not found: {sim_params_path}\")\n",
    "#     with open(sim_params_path, \"r\") as f:\n",
    "#         params = json.load(f)\n",
    "#     print(f\"Loaded simulation parameters for sim_idx=={sim_idx}: {len(params)} keys\")\n",
    "#     all_sim_params_p3m.append(params)\n",
    "#     fac_hubble = all_sim_params_p3m[sim_idx][\"fac_H_custom\"]\n",
    "#     fac_bend = all_sim_params_p3m[sim_idx][\"fac_bend\"]\n",
    "#     da_early = all_sim_params_p3m[sim_idx][\"da_max_early_custom\"]\n",
    "\n",
    "# Alternatively, let the user specify the parameters directly:\n",
    "fac_hubble_list = [DEFAULT_FAC_H_CUSTOM_COLA]*2\n",
    "fac_bend_list = [DEFAULT_FAC_BEND]*2\n",
    "da_early_list = [DEFAULT_DA_MAX_EARLY_CUSTOM]*2\n",
    "# fac_hubble_list = [0.02, 0.02]\n",
    "# fac_bend_list = [0.3125 / 2, 0.3125]\n",
    "# da_early_list = [0.0013, 0.0013]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "69dcd0c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "aa = []\n",
    "da_p3m_list = []\n",
    "for sim_idx in range(N_sim_fit):\n",
    "    OutputTimestepsLog = OutputTimestepsLog_list[sim_idx][:-4] + \"_custom.txt\"\n",
    "    a, _, _, _, _, da_p3m, da_p3m_fit, _, _, _ = np.loadtxt(\n",
    "        OutputTimestepsLog, delimiter=\",\", unpack=True, skiprows=0\n",
    "    )\n",
    "    aa.append(a)\n",
    "    da_p3m_list.append(da_p3m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "701572ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x1050 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simulation 0: Coefficients: [-3.74659557  0.39041298  1.90821078  1.10022755  0.5597775   0.09604354]\n",
      "Coefficients saved to /home/hoellinger/wip3m/results/COLAr7/CV2_cola_Pf_L80_N160_Np160/coeffs_p3m_sim0.json\n",
      "Simulation 1: Coefficients: [-3.74967124  0.32498523  1.68724927  0.84016171  0.45636105  0.08504407]\n",
      "Coefficients saved to /home/hoellinger/wip3m/results/COLAr7/CV2_cola_Pf_L80_N160_Np160/coeffs_p3m_sim1.json\n"
     ]
    }
   ],
   "source": [
    "# For each sim_idx, fit the P3M time step distribution and plot the results\n",
    "amin_fit=1e-1\n",
    "amin_plot = 1e-1\n",
    "# amin_plot = 5e-2\n",
    "deg_fit = 5  # Degree of the polynomial fit for the P3M limiter\n",
    "\n",
    "coeffs_list = []  # List to store the coefficients of each polynomial fit\n",
    "for sim_idx in range(N_sim_fit):\n",
    "    # Fit the P3M time step distribution\n",
    "    a = aa[sim_idx]\n",
    "    da_p3m = da_p3m_list[sim_idx]\n",
    "    coeffs = fit_p3m(a, da_p3m, degree=deg_fit, amin=amin_fit)\n",
    "    coeffs_list.append(coeffs)\n",
    "\n",
    "fig = plt.figure(figsize=(6, 3.5))\n",
    "gs = GridSpec(2, 1, height_ratios=[3, 1], hspace=0.05)\n",
    "ax1 = fig.add_subplot(gs[0])\n",
    "ax2 = fig.add_subplot(gs[1], sharex=ax1)\n",
    "\n",
    "for sim_idx in range(N_sim_fit):\n",
    "    a = aa[sim_idx]\n",
    "    da_p3m = da_p3m_list[sim_idx]\n",
    "    coeffs = coeffs_list[sim_idx]\n",
    "    mask = a > amin_plot  # Filter out values below amin_plot\n",
    "    a = a[mask]\n",
    "    da_p3m = da_p3m[mask]\n",
    "    ratio = da_p3m / a\n",
    "    a_dense = np.logspace(np.log10(a.min()), np.log10(a.max()), 500)\n",
    "    fit_vals = evaluate_polynomial_log(coeffs, a_dense)\n",
    "    fit_interp = evaluate_polynomial_log(coeffs, a)\n",
    "    residuals = np.log(ratio / fit_interp)\n",
    "\n",
    "    # P3M limiter and fit\n",
    "    if sim_idx == 0:\n",
    "        ax1.plot(a, ratio, \".\", alpha=0.7, color=f\"C{sim_idx}\", label=r\"$\\Delta t \\propto x_s/\\sqrt{\\langle v^2 \\rangle}$\")\n",
    "        ax1.plot(a_dense, fit_vals, \"-\", lw=1.8, color=f\"C{sim_idx}\", label=rf\"Fit for $a > {amin_fit}$\")\n",
    "    else:\n",
    "        ax1.plot(a, ratio, \".\", alpha=0.7, color=f\"C{sim_idx}\")\n",
    "        ax1.plot(a_dense, fit_vals, \"-\", lw=1.8, color=f\"C{sim_idx}\")\n",
    "    ax1.set_yscale(\"log\")\n",
    "    ax1.set_xscale(\"log\")\n",
    "    ax1.set_ylabel(r\"$\\Delta a/a$\")\n",
    "    ax1.legend(loc=\"upper right\", frameon=False)\n",
    "    ax1.tick_params(which=\"both\", direction=\"in\", top=True, right=True)\n",
    "    ax1.grid(True, which=\"major\", ls=\":\", lw=0.5)\n",
    "\n",
    "    # Residuals\n",
    "    ax2.plot(a, residuals, \"o\", color=\"grey\", alpha=0.6, markersize=3)\n",
    "\n",
    "ax2.axhline(0.0, color=\"black\", lw=1, ls=\"--\")\n",
    "ax2.set_ylabel(\"res\", labelpad=2)\n",
    "ax2.set_xlabel(r\"Scale factor $a$\")\n",
    "ax2.set_xscale(\"log\")\n",
    "ax2.set_yscale(\"symlog\")\n",
    "\n",
    "ax2.tick_params(which=\"both\", direction=\"in\", top=True, right=True)\n",
    "ax2.grid(True, which=\"major\", ls=\":\", lw=0.5)\n",
    "ax1.tick_params(labelbottom=False)\n",
    "ax2.yaxis.set_major_formatter(plt.FuncFormatter(lambda y, _: f\"{y:.3g}\"))\n",
    "plt.show()\n",
    "\n",
    "for sim_idx, coeffs in enumerate(coeffs_list):\n",
    "    print(f\"Simulation {sim_idx}: Coefficients: {coeffs}\")\n",
    "    coeffs_path = wd + f\"coeffs_p3m_sim{sim_idx}.json\"\n",
    "    with open(coeffs_path, \"w\") as f:\n",
    "        json.dump(coeffs.tolist(), f)\n",
    "    print(f\"Coefficients saved to {coeffs_path}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c1c096bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[14:11:00|\u001b[38;5;113mSTATUS    \u001b[00m]|Read custom timestepping configuration in '/home/hoellinger/wip3m/results/COLAr7/CV2_cola_Pf_L80_N160_Np160/p3m1_rscale0_35_ts_p3m.h5'...\n"
     ]
    },
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] Unable to synchronously open file (unable to open file: name = '/home/hoellinger/wip3m/results/COLAr7/CV2_cola_Pf_L80_N160_Np160/p3m1_rscale0_35_ts_p3m.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mFileNotFoundError\u001b[39m                         Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[8]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m      1\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m sim_idx \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(N_sim_fit):\n\u001b[32m      2\u001b[39m     TSpath = TSpath_list[sim_idx]\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m     TS = \u001b[43mP3MTimeStepping\u001b[49m\u001b[43m.\u001b[49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43mTSpath\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m      4\u001b[39m     aiDrift = TS.aiDrift\n\u001b[32m      5\u001b[39m     nsteps = TS.nsteps\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/simbelmyne2025/DEV_simbelmyne_private/build/__editable__.pysbmy-0.5-py3-none-any/pysbmy/timestepping.py:1064\u001b[39m, in \u001b[36mP3MTimeStepping.read\u001b[39m\u001b[34m(fname)\u001b[39m\n\u001b[32m   1062\u001b[39m PrintMessage(\u001b[32m3\u001b[39m, \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mRead custom timestepping configuration in \u001b[39m\u001b[33m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfname\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m'\u001b[39m\u001b[33m...\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m   1063\u001b[39m INDENT()\n\u001b[32m-> \u001b[39m\u001b[32m1064\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mh5\u001b[49m\u001b[43m.\u001b[49m\u001b[43mFile\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mr\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m hf:\n\u001b[32m   1065\u001b[39m     ai = hf.attrs[\u001b[33m'\u001b[39m\u001b[33m/info/scalars/ai\u001b[39m\u001b[33m'\u001b[39m]\n\u001b[32m   1066\u001b[39m     af = hf.attrs[\u001b[33m'\u001b[39m\u001b[33m/info/scalars/af\u001b[39m\u001b[33m'\u001b[39m]\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.conda/envs/p3m/lib/python3.13/site-packages/h5py/_hl/files.py:564\u001b[39m, in \u001b[36mFile.__init__\u001b[39m\u001b[34m(self, name, mode, driver, libver, userblock_size, swmr, rdcc_nslots, rdcc_nbytes, rdcc_w0, track_order, fs_strategy, fs_persist, fs_threshold, fs_page_size, page_buf_size, min_meta_keep, min_raw_keep, locking, alignment_threshold, alignment_interval, meta_block_size, **kwds)\u001b[39m\n\u001b[32m    555\u001b[39m     fapl = make_fapl(driver, libver, rdcc_nslots, rdcc_nbytes, rdcc_w0,\n\u001b[32m    556\u001b[39m                      locking, page_buf_size, min_meta_keep, min_raw_keep,\n\u001b[32m    557\u001b[39m                      alignment_threshold=alignment_threshold,\n\u001b[32m    558\u001b[39m                      alignment_interval=alignment_interval,\n\u001b[32m    559\u001b[39m                      meta_block_size=meta_block_size,\n\u001b[32m    560\u001b[39m                      **kwds)\n\u001b[32m    561\u001b[39m     fcpl = make_fcpl(track_order=track_order, fs_strategy=fs_strategy,\n\u001b[32m    562\u001b[39m                      fs_persist=fs_persist, fs_threshold=fs_threshold,\n\u001b[32m    563\u001b[39m                      fs_page_size=fs_page_size)\n\u001b[32m--> \u001b[39m\u001b[32m564\u001b[39m     fid = \u001b[43mmake_fid\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muserblock_size\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfapl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfcpl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mswmr\u001b[49m\u001b[43m=\u001b[49m\u001b[43mswmr\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    566\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(libver, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[32m    567\u001b[39m     \u001b[38;5;28mself\u001b[39m._libver = libver\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.conda/envs/p3m/lib/python3.13/site-packages/h5py/_hl/files.py:238\u001b[39m, in \u001b[36mmake_fid\u001b[39m\u001b[34m(name, mode, userblock_size, fapl, fcpl, swmr)\u001b[39m\n\u001b[32m    236\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m swmr \u001b[38;5;129;01mand\u001b[39;00m swmr_support:\n\u001b[32m    237\u001b[39m         flags |= h5f.ACC_SWMR_READ\n\u001b[32m--> \u001b[39m\u001b[32m238\u001b[39m     fid = \u001b[43mh5f\u001b[49m\u001b[43m.\u001b[49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mflags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfapl\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfapl\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    239\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m mode == \u001b[33m'\u001b[39m\u001b[33mr+\u001b[39m\u001b[33m'\u001b[39m:\n\u001b[32m    240\u001b[39m     fid = h5f.open(name, h5f.ACC_RDWR, fapl=fapl)\n",
      "\u001b[36mFile \u001b[39m\u001b[32mh5py/_objects.pyx:54\u001b[39m, in \u001b[36mh5py._objects.with_phil.wrapper\u001b[39m\u001b[34m()\u001b[39m\n",
      "\u001b[36mFile \u001b[39m\u001b[32mh5py/_objects.pyx:55\u001b[39m, in \u001b[36mh5py._objects.with_phil.wrapper\u001b[39m\u001b[34m()\u001b[39m\n",
      "\u001b[36mFile \u001b[39m\u001b[32mh5py/h5f.pyx:102\u001b[39m, in \u001b[36mh5py.h5f.open\u001b[39m\u001b[34m()\u001b[39m\n",
      "\u001b[31mFileNotFoundError\u001b[39m: [Errno 2] Unable to synchronously open file (unable to open file: name = '/home/hoellinger/wip3m/results/COLAr7/CV2_cola_Pf_L80_N160_Np160/p3m1_rscale0_35_ts_p3m.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)"
     ]
    }
   ],
   "source": [
    "for sim_idx in range(N_sim_fit):\n",
    "    TSpath = TSpath_list[sim_idx]\n",
    "    TS = P3MTimeStepping.read(TSpath)\n",
    "    aiDrift = TS.aiDrift\n",
    "    nsteps = TS.nsteps\n",
    "    OutputTimestepsLog = OutputTimestepsLog_list[sim_idx]\n",
    "    plot_custom_timestepping_diagnostics(\n",
    "        log_path=OutputTimestepsLog,\n",
    "        aiDrift=aiDrift,\n",
    "        TimeStepDistribution=3,\n",
    "        nsteps=nsteps,\n",
    "        ymin=3e-3,\n",
    "        ymax=0.5,\n",
    "        fac_hubble=fac_hubble_list[sim_idx],\n",
    "        fac_bend=fac_bend_list[sim_idx],\n",
    "        da_max_early=da_early_list[sim_idx],\n",
    "        da_max_late=DEFAULT_DA_MAX_LATE_CUSTOM,\n",
    "        show=False,\n",
    "    )\n",
    "    fit_interp = evaluate_polynomial_log(coeffs_list[sim_idx], aa[sim_idx])\n",
    "    plt.plot(aa[sim_idx], fit_interp, label=r\"$\\Delta t \\propto x_s/\\sqrt{\\langle v^2 \\rangle}$\", color=\"black\", alpha=0.7, zorder=10)\n",
    "    plt.title(f\"Simulation {sim_idx}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f225b2f9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85b01324",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dadb9198",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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