plotting_dsmc.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a5c30af3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import yt\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9d9dd345",
   "metadata": {},
   "outputs": [],
   "source": [
    "def return_pltcu(folder,time,nbins,field):\n",
    "    ds = yt.load(folder+'/pltcu'+time+'/')\n",
    "    ad = ds.all_data()\n",
    "    plot = yt.ProfilePlot(ad,\"x\",[field],weight_field=\"cell_volume\",x_log=False,y_log={field:False},n_bins=nbins)\n",
    "    profile = plot.profiles[0]\n",
    "    x = np.array(profile.x)\n",
    "    y = np.array(profile[field])\n",
    "    return x, y\n",
    "\n",
    "def return_pltprim(folder,time,nbins,field):\n",
    "    ds = yt.load(folder+'/pltprim'+time+'/')\n",
    "    ad = ds.all_data()\n",
    "    plot = yt.ProfilePlot(ad,\"x\",[field],weight_field=\"cell_volume\",x_log=False,y_log={field:False},n_bins=nbins)\n",
    "    profile = plot.profiles[0]\n",
    "    x = np.array(profile.x)\n",
    "    y = np.array(profile[field])\n",
    "    return x, y\n",
    "\n",
    "def return_pltvar(folder,time,nbins,field):\n",
    "    ds = yt.load(folder+'/pltvar'+time+'/')\n",
    "    ad = ds.all_data()\n",
    "    plot = yt.ProfilePlot(ad,\"x\",[field],weight_field=\"cell_volume\",x_log=False,y_log={field:False},n_bins=nbins)\n",
    "    profile = plot.profiles[0]\n",
    "    x = np.array(profile.x)\n",
    "    y = np.array(profile[field])\n",
    "    return x, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "3ae2660d",
   "metadata": {},
   "outputs": [],
   "source": [
    "time = \"{:012d}\".format(int(2000000))\n",
    "x, rhoMean = return_pltcu('~/coriProject/dladiges/dsmc_tests/conc_gradient',time,nbins=64,field=\"rhoMean\")\n",
    "x, rho0Mean = return_pltcu('~/coriProject/dladiges/dsmc_tests/conc_gradient',time,nbins=64,field=\"rhoMean_00\")\n",
    "x, rho1Mean = return_pltcu('~/coriProject/dladiges/dsmc_tests/conc_gradient',time,nbins=64,field=\"rhoMean_01\")\n",
    "x, TMean = return_pltprim('~/coriProject/dladiges/dsmc_tests/conc_gradient',time,nbins=64,field=\"TMean\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "id": "3070a4f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "yt : [INFO     ] 2021-08-27 16:16:51,027 Parameters: current_time              = 9.999950000015862e-06\n",
      "yt : [INFO     ] 2021-08-27 16:16:51,029 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 16:16:51,031 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 16:16:51,032 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 16:16:54,577 Parameters: current_time              = 9.999950000015862e-06\n",
      "yt : [INFO     ] 2021-08-27 16:16:54,578 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 16:16:54,579 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 16:16:54,581 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 16:16:56,084 Parameters: current_time              = 9.999950000015862e-06\n",
      "yt : [INFO     ] 2021-08-27 16:16:56,085 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 16:16:56,086 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 16:16:56,086 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 16:17:00,048 Parameters: current_time              = 9.999950000015862e-06\n",
      "yt : [INFO     ] 2021-08-27 16:17:00,049 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 16:17:00,050 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 16:17:00,052 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 16:17:01,617 Parameters: current_time              = 9.999950000015862e-06\n",
      "yt : [INFO     ] 2021-08-27 16:17:01,619 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 16:17:01,620 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 16:17:01,621 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n"
     ]
    }
   ],
   "source": [
    "time = \"{:012d}\".format(int(200000))\n",
    "pth='~/gigan/projects/FHDeX/exec/DSMC'\n",
    "x, rhoMean = return_pltcu(pth,time,nbins=64,field=\"rhoMean\")\n",
    "x, rho0Mean = return_pltcu(pth,time,nbins=64,field=\"rhoMean_00\")\n",
    "#x, rho1Mean = return_pltcu(pth,time,nbins=64,field=\"rhoMean_01\")\n",
    "x, TMean = return_pltprim(pth,time,nbins=64,field=\"TMean\")\n",
    "x, uMean = return_pltprim(pth,time,nbins=64,field=\"uMean\")\n",
    "x, PMean = return_pltprim(pth,time,nbins=64,field=\"PMean\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "id": "777a327b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "yt : [INFO     ] 2021-08-27 15:19:16,602 Parameters: current_time              = 4.999900000002942e-07\n",
      "yt : [INFO     ] 2021-08-27 15:19:16,604 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 15:19:16,605 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 15:19:16,607 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 15:19:20,125 Parameters: current_time              = 4.999900000002942e-07\n",
      "yt : [INFO     ] 2021-08-27 15:19:20,126 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 15:19:20,127 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 15:19:20,127 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 15:19:21,499 Parameters: current_time              = 4.999900000002942e-07\n",
      "yt : [INFO     ] 2021-08-27 15:19:21,500 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 15:19:21,501 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 15:19:21,501 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 15:19:22,959 Parameters: current_time              = 4.999900000002942e-07\n",
      "yt : [INFO     ] 2021-08-27 15:19:22,960 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 15:19:22,960 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 15:19:22,961 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 15:19:26,428 Parameters: current_time              = 4.999900000002942e-07\n",
      "yt : [INFO     ] 2021-08-27 15:19:26,429 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 15:19:26,429 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 15:19:26,430 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n",
      "yt : [INFO     ] 2021-08-27 15:19:28,705 Parameters: current_time              = 4.999900000002942e-07\n",
      "yt : [INFO     ] 2021-08-27 15:19:28,706 Parameters: domain_dimensions         = [128   1   1]\n",
      "yt : [INFO     ] 2021-08-27 15:19:28,707 Parameters: domain_left_edge          = [0. 0. 0.]\n",
      "yt : [INFO     ] 2021-08-27 15:19:28,708 Parameters: domain_right_edge         = [3.84e-04 3.00e-06 3.00e-06]\n"
     ]
    }
   ],
   "source": [
    "time = \"{:012d}\".format(int(50000))\n",
    "pth='~/gigan/projects/FHDeX/exec/DSMC'\n",
    "x, rhoMean = return_pltcu(pth,time,nbins=64,field=\"rhoInstant\")\n",
    "x, rho0Mean = return_pltcu(pth,time,nbins=64,field=\"rhoInstant_00\")\n",
    "x, rho1Mean = return_pltcu(pth,time,nbins=64,field=\"rhoInstant_01\")\n",
    "x, TMean = return_pltprim(pth,time,nbins=64,field=\"TInstant\")\n",
    "x, uMean = return_pltprim(pth,time,nbins=64,field=\"uInstant\")\n",
    "x, PMean = return_pltprim(pth,time,nbins=64,field=\"PInstant\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "54a2cf81",
   "metadata": {},
   "outputs": [],
   "source": [
    "y6=[]\n",
    "x6=x6b\n",
    "for (item1, item2) in zip(y6a, y6b):\n",
    "    y6.append((item1+item2)/2)\n",
    "\n",
    "y7=[]\n",
    "x7=x7b\n",
    "for (item1, item2) in zip(y7a, y7b):\n",
    "    y7.append((item1+item2)/2)\n",
    "\n",
    "y8=[]\n",
    "x8=x8b\n",
    "for (item1, item2) in zip(y8a, y8b):\n",
    "    y8.append((item1+item2)/2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "id": "cb3cd6d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2232x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['mathtext.fontset'] = 'cm'\n",
    "plt.rc('text', usetex=True)\n",
    "plt.rc('xtick', labelsize=13) \n",
    "plt.rc('ytick', labelsize=13) \n",
    "plt.rc('axes', linewidth=1.5)\n",
    "fig = plt.figure(figsize=[31,15])\n",
    "plt.subplots_adjust(wspace=0.20)\n",
    "\n",
    "rhoR = [0.0025]*len(x)\n",
    "\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "ax1.plot(x,rhoR,color='black', linestyle='dotted',linewidth=2, label='rho mean')\n",
    "ax1.plot(x,rhoMean,color='black',linewidth=2, label='rho mean')\n",
    "ax1.plot(x,rho0Mean,color='red',linewidth=2, label='rho 0 mean')\n",
    "ax1.plot(x,rho1Mean,color='blue',linewidth=2, label='rho 1 mean')\n",
    "# ax1.plot(x2,y2,color='blue',linewidth=2, label='50\\% wet, wet part only')\n",
    "# ax1.plot(x4,y4,color='red',linewidth=2, label='50\\% wet, dry part only')\n",
    "# ax1.plot(x7,y7,color='purple',linewidth=2, label='100\\% wet')\n",
    "\n",
    "#ax1.set_xlabel(r'$y$', fontsize=30)\n",
    "#ax1.set_ylabel(r\"$\\varrho\\,(\\mathrm{C}/\\mathrm{cm}^3)$\", fontsize=30,rotation=90, labelpad=10)\n",
    "ax1.set_ylim([0,0.004])\n",
    "ax1.tick_params(labelsize=20)\n",
    "ax1.legend(loc=(0.65,0.04),fontsize=20)\n",
    "ax1.xaxis.set_tick_params(width=1.5)\n",
    "ax1.yaxis.set_tick_params(width=1.5)\n",
    "\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "#ax2.plot(x,TMean,color='black',linewidth=2, label='T mean')\n",
    "ax2.plot(x,PMean,color='red',linewidth=2, label='P mean')\n",
    "# ax2.plot(x,n1Mean,color='blue',linewidth=2, label='n 1 mean')\n",
    "# ax2.set_xlabel(r'$y$', fontsize=30)\n",
    "# ax2.set_ylabel(r\"$\\varrho\\,(\\mathrm{C}/\\mathrm{cm}^3)$\", fontsize=30,rotation=90, labelpad=10)\n",
    "# ax2.set_ylim([0,1.7e19])\n",
    "ax2.tick_params(labelsize=20)\n",
    "ax2.legend(loc=(0.65,0.04),fontsize=20)\n",
    "ax2.xaxis.set_tick_params(width=1.5)\n",
    "ax2.yaxis.set_tick_params(width=1.5)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "ee13a363",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2232x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['mathtext.fontset'] = 'cm'\n",
    "plt.rc('text', usetex=True)\n",
    "plt.rc('xtick', labelsize=13) \n",
    "plt.rc('ytick', labelsize=13) \n",
    "plt.rc('axes', linewidth=1.5)\n",
    "fig = plt.figure(figsize=[31,15])\n",
    "plt.subplots_adjust(wspace=0.20)\n",
    "\n",
    "rhoR = [1.6175622327610146e-3]*len(x)\n",
    "\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "ax1.plot(x,rhoR,color='black', linestyle='dotted',linewidth=2, label='rho mean')\n",
    "ax1.plot(x,rhoMean,color='black',linewidth=2, label='rho mean')\n",
    "ax1.plot(x,rho0Mean,color='red',linewidth=2, label='rho 0 mean')\n",
    "ax1.plot(x,rho1Mean,color='blue',linewidth=2, label='rho 1 mean')\n",
    "# ax1.plot(x2,y2,color='blue',linewidth=2, label='50\\% wet, wet part only')\n",
    "# ax1.plot(x4,y4,color='red',linewidth=2, label='50\\% wet, dry part only')\n",
    "# ax1.plot(x7,y7,color='purple',linewidth=2, label='100\\% wet')\n",
    "\n",
    "ax1.set_xlabel(r'$y$', fontsize=30)\n",
    "ax1.set_ylabel(r\"$\\varrho\\,(\\mathrm{C}/\\mathrm{cm}^3)$\", fontsize=30,rotation=90, labelpad=10)\n",
    "ax1.set_ylim([0,0.002])\n",
    "ax1.tick_params(labelsize=20)\n",
    "ax1.legend(loc=(0.65,0.04),fontsize=20)\n",
    "ax1.xaxis.set_tick_params(width=1.5)\n",
    "ax1.yaxis.set_tick_params(width=1.5)\n",
    "\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "#ax2.plot(x,rho1rho1,color='black',linewidth=2, label='corr')\n",
    "ax2.plot(x,n0Mean,color='red',linewidth=2, label='n 0 mean')\n",
    "ax2.plot(x,n1Mean,color='blue',linewidth=2, label='n 1 mean')\n",
    "ax2.set_xlabel(r'$y$', fontsize=30)\n",
    "ax2.set_ylabel(r\"$\\varrho\\,(\\mathrm{C}/\\mathrm{cm}^3)$\", fontsize=30,rotation=90, labelpad=10)\n",
    "ax2.set_ylim([0,1.7e19])\n",
    "ax2.tick_params(labelsize=20)\n",
    "ax2.legend(loc=(0.65,0.04),fontsize=20)\n",
    "ax2.xaxis.set_tick_params(width=1.5)\n",
    "ax2.yaxis.set_tick_params(width=1.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "505102d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0016181238024691063\n",
      "0.001618123802469108\n"
     ]
    }
   ],
   "source": [
    "print(rhoMean[63])\n",
    "print(rho0Mean[63]+rho1Mean[63])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "id": "b4954012",
   "metadata": {},
   "outputs": [],
   "source": [
    "kb=1.38e-16\n",
    "m0=3.35e-23\n",
    "m1=1.39e-22\n",
    "\n",
    "pL=2*((rho0Mean[0]/m0)*kb*TMean[0] + (rho1Mean[0]/m1)*kb*TMean[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "id": "040c37cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1212178.5037077896"
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 313,
   "id": "4417f6d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1226399.8953423095"
      ]
     },
     "execution_count": 313,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PMean[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a36f89e2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}