{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Figure S3 and S8\n",
    "\n",
    "### S3: Time series of CO2 concentration in SSP5-8.5\n",
    "### S8: FOCI difference in cumulative NBP and LCC flux"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import copy\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import netCDF4 as nc\n",
    "import pandas as pd\n",
    "import sys\n",
    "import xarray as xr\n",
    "\n",
    "\n",
    "from my_io import Figure1\n",
    "\n",
    "ppm2GtCO2 = 2.124/0.272912\n",
    "ppm2PgC =  2.124/0.272912 * 12.01 / 44.0095\n",
    "fontsize = 18\n",
    "def ens_values(df_list,var_name,yrstart=2015):\n",
    "    # df_list: a list of DataFrame\n",
    "    diff_realizaions = [] # (nreal,nyear)\n",
    "    for ireal in range(len(df_list)):\n",
    "        diff_realizaions.append([])\n",
    "    for iyear in range(yrstart,2100):\n",
    "        for ireal in range(len(df_list)):\n",
    "            diff_realizaions[ireal].append(df_list[ireal][var_name].loc[iyear])           \n",
    "    diff_realizaions = np.array(diff_realizaions)\n",
    "    ens_mean = np.average(diff_realizaions,axis=0)\n",
    "    ens_min = np.min(diff_realizaions,axis=0)\n",
    "    ens_max = np.max(diff_realizaions,axis=0)\n",
    "    ens_stddev = np.std(diff_realizaions,axis=0)\n",
    "    yrindex = np.array(range(yrstart,2100)) \n",
    "    df_ens = pd.DataFrame(data=ens_max - ens_min, index=yrindex, columns=['ens_range'])\n",
    "    df_ens['ens_mean'] = ens_mean\n",
    "    df_ens['ens_min'] = ens_min\n",
    "    df_ens['ens_max'] = ens_max\n",
    "    df_ens['ens_stddev'] = ens_stddev\n",
    "    return df_ens"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* A/R (LUMIP)\n",
    "    * except for NorESM\n",
    "    * no treeFrac\n",
    "        * CESM2, MIROC-ES2L\n",
    "    * no co2 concentration\n",
    "        * CanESM5\n",
    "* OAE (CDRMIP)\n",
    "    * FOCI, MPI-ESM, NorESM2-LM, UKESM1-0-LL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACCESS-ESM1-5 C0\n",
      "CESM2 C1\n",
      "CanESM5 C2\n",
      "FOCI C3\n",
      "MIROC-ES2L C4\n",
      "MPI-ESM1-2-LR C5\n",
      "NorESM2-LM C6\n",
      "UKESM1-0-LL C7\n"
     ]
    }
   ],
   "source": [
    "model_list = ['ACCESS-ESM1-5', 'CESM2', 'CanESM5', \n",
    "              'FOCI', 'MIROC-ES2L', 'MPI-ESM1-2-LR',\n",
    "              'NorESM2-LM','UKESM1-0-LL']\n",
    "# model_list = ['ACCESS-ESM', 'CESM', 'CanESM', \n",
    "#               'FOCI', 'MIROC', 'MPI-ESM',\n",
    "#               'NorESM2','UKESM']\n",
    "color_list = []\n",
    "for imodel in range(len(model_list)):\n",
    "    color_list.append('C'+str(imodel))\n",
    "    print(model_list[imodel],color_list[imodel])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fig 1c no CanESM5\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,5))\n",
    "# fig SI co2 REF\n",
    "ax = fig.add_subplot(111)\n",
    "for imodel in range(len(model_list)):\n",
    "    if model_list[imodel]=='FOCI':\n",
    "        fig1=Figure1('co2_concentration','AFF')\n",
    "        fig1.read_FOCI()\n",
    "        yrstart = 2015\n",
    "        for ii in range(3):\n",
    "            diff = fig1.dflist[0][ii]['co2_concentration']\n",
    "#             ax.plot(range(2015,2100),diff,'--',linewidth=1,color=color_list[imodel])\n",
    "        df_ens = ens_values([fig1.dflist[0][0],\n",
    "                             fig1.dflist[0][1],\n",
    "                             fig1.dflist[0][2]],'co2_concentration')\n",
    "        ax.fill_between(range(yrstart,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.3, facecolor=color_list[imodel])\n",
    "        ax.plot(range(yrstart,2100),df_ens['ens_mean'],'-',linewidth=2,color=color_list[imodel],label='FOCI')\n",
    "    elif model_list[imodel]=='MPI-ESM1-2-LR':\n",
    "        ########\n",
    "        fig1.read_MPIESM()\n",
    "        for ii in range(3):\n",
    "            diff = fig1.dflist[0][ii]['co2_concentration']\n",
    "#             ax.plot(range(2015,2100),diff,'--',linewidth=1,color=color_list[imodel])\n",
    "        df_ens = ens_values([fig1.dflist[0][0],\n",
    "                             fig1.dflist[0][1],\n",
    "                             fig1.dflist[0][2]],'co2_concentration')\n",
    "        ax.fill_between(range(yrstart,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.3, facecolor=color_list[imodel])\n",
    "        ax.plot(range(yrstart,2100),df_ens['ens_mean'],'-',linewidth=2,color=color_list[imodel],label='MPI-ESM')\n",
    "    else:\n",
    "        try:\n",
    "            var_name, exp = 'co2_concentration', 'AFF' \n",
    "            fig1=Figure1(var_name,exp)\n",
    "            fig1.read_model(model_list[imodel])\n",
    "#             ax.plot(fig1.dflist[2][0].index,fig1.dflist[2][0]['co2_concentration'].loc[:]-fig1.dflist[0][0]['co2_concentration'].loc[fig1.dflist[2][0].index],'-',color='C'+str(imodel),label=model_list[imodel],linewidth=2)\n",
    "            ax.plot(fig1.dflist[0][0]['co2_concentration'],'-',color='C'+str(imodel),label=model_list[imodel],linewidth=2)\n",
    "#             ax.plot(fig1.dflist[2][0]['co2_concentration'],'--',color='C'+str(imodel),label=model_list[imodel],linewidth=2)\n",
    "        except:\n",
    "            print(f'fig 1c no {model_list[imodel]}')\n",
    "#######\n",
    "ax.tick_params(labelsize=fontsize)\n",
    "ax.set_ylabel('ppm', fontsize = fontsize)\n",
    "ax.grid()\n",
    "# ax.legend(loc = 'best', fontsize=fontsize)\n",
    "# fig.suptitle('(a) Forest area',fontsize=fontsize)\n",
    "ax.set_title('CO$_2$ concentration',fontsize=fontsize)\n",
    "# plt.savefig('fig/figure1a.png',bbox_inches='tight')\n",
    "# for legend\n",
    "import matplotlib.patches as mpatches\n",
    "handles = []\n",
    "for imodel in range(len(model_list)):\n",
    "    patch = mpatches.Patch(color=color_list[imodel], label=model_list[imodel])\n",
    "    handles.append(patch) \n",
    "fig.legend(handles=handles, loc='lower right',fontsize=fontsize)\n",
    "fig.tight_layout()\n",
    "fig.subplots_adjust(right=0.73)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lcc -8.164288208524429\n",
      "nbp 47.015741089616576\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x14b0250ac890>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,5))\n",
    "# fig SI FOCI lcc flux\n",
    "ax = fig.add_subplot(111)\n",
    "fig1=Figure1('lcc','AFF')\n",
    "yrstart = 2015\n",
    "fig1.read_FOCI()\n",
    "for ii in range(3):\n",
    "    diff = fig1.dflist[0][ii]['lcc']\n",
    "#             ax.plot(range(2015,2100),diff,'--',linewidth=1,color=color_list[imodel])\n",
    "df_ens = ens_values([(fig1.dflist[2][0]-fig1.dflist[0][0]).cumsum(),\n",
    "                     (fig1.dflist[2][1]-fig1.dflist[0][1]).cumsum(),\n",
    "                     (fig1.dflist[2][2]-fig1.dflist[0][2]).cumsum()],'lcc')\n",
    "print('lcc',df_ens['ens_mean'].loc[2060])\n",
    "ax.fill_between(range(yrstart,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.3, facecolor='C0')\n",
    "ax.plot(range(yrstart,2100),df_ens['ens_mean'],'-',linewidth=2,color='C0',label='LCC flux')\n",
    "fig1=Figure1('nbp','AFF')\n",
    "fig1.read_FOCI()\n",
    "for ii in range(3):\n",
    "    diff = fig1.dflist[0][ii]['nbp']\n",
    "#             ax.plot(range(2015,2100),diff,'--',linewidth=1,color=color_list[imodel])\n",
    "df_ens = ens_values([(fig1.dflist[2][0]-fig1.dflist[0][0]).cumsum(),\n",
    "                     (fig1.dflist[2][1]-fig1.dflist[0][1]).cumsum(),\n",
    "                     (fig1.dflist[2][2]-fig1.dflist[0][2]).cumsum()],'nbp')\n",
    "print('nbp',df_ens['ens_mean'].loc[2060])\n",
    "ax.fill_between(range(yrstart,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.3, facecolor='C1')\n",
    "ax.plot(range(yrstart,2100),df_ens['ens_mean'],'-',linewidth=2,color='C1',label='NBP')\n",
    "\n",
    "\n",
    "ax.tick_params(labelsize=fontsize)\n",
    "ax.set_ylabel('Pg', fontsize = fontsize)\n",
    "ax.grid()\n",
    "# ax.legend(loc = 'best', fontsize=fontsize)\n",
    "# fig.suptitle('(a) Forest area',fontsize=fontsize)\n",
    "ax.set_title('FOCI cumulative NBP and LCC flux',fontsize=fontsize)\n",
    "ax.legend(loc='best',fontsize=fontsize)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
