{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preparations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "code_folding": [
     0
    ],
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "### Importing Matplotlib (cannot be repeated in a Kernel)\n",
    "#%matplotlib notebook\n",
    "#%matplotlib inline\n",
    "import matplotlib\n",
    "#matplotlib.use(\"Agg\")\n",
    "#matplotlib.use('ps')\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec\n",
    "import matplotlib._color_data as mcd\n",
    "from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_axes, mark_inset,TransformedBbox, BboxPatch, BboxConnector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [],
   "source": [
    "### Importing Other Packages\n",
    "\n",
    "from matplotlib import animation\n",
    "from jupyterthemes import jtplot\n",
    "import numpy as np\n",
    "import math\n",
    "from scipy import stats\n",
    "from scipy.stats import skewnorm\n",
    "import pandas as pd\n",
    "import netCDF4 as nc4\n",
    "from netCDF4 import Dataset\n",
    "from netCDF4 import num2date\n",
    "import pickle\n",
    "import datetime\n",
    "import sys\n",
    "sys.path.append('../misc')\n",
    "#from nc_dump import ncdump\n",
    "from nc_dump import ncdump\n",
    "import os\n",
    "import time\n",
    "from mpl_toolkits.basemap import Basemap, addcyclic, shiftgrid\n",
    "import importlib\n",
    "\n",
    "#my scripts:\n",
    "import tools_plot as jplt\n",
    "importlib.reload(jplt) \n",
    "import tools_analysis as jan\n",
    "importlib.reload(jan) \n",
    "# #my scripts:\n",
    "# import tools_plot as jplt\n",
    "# reload(jplt) \n",
    "# import tools_analysis as jan\n",
    "# reload(jan)  \n",
    "%matplotlib inline\n",
    "#matplotlib notebook\n",
    "#plt.style.use('dark_background')\n",
    "#jtplot.style(theme='onedork')\n",
    "#jtplot.reset()\n",
    "%load_ext ferretmagic\n",
    "import csv\n",
    "import scipy.stats as stats\n",
    "from scipy.stats import truncnorm\n",
    "#from __future__ import print_function\n",
    "from ipywidgets import interact, interactive, fixed, interact_manual\n",
    "import ipywidgets as widgets\n",
    "import glob\n",
    "from scipy.optimize import fsolve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/p/projects/ace/janlandw/publication_TrJu/plots',\n",
       " '/p/system/packages/intel/parallel_studio_xe_2017_update4/advisor_2017.1.3.510716/pythonapi',\n",
       " '/home/janlandw/.conda/envs/py3_jan/lib/python37.zip',\n",
       " '/home/janlandw/.conda/envs/py3_jan/lib/python3.7',\n",
       " '/home/janlandw/.conda/envs/py3_jan/lib/python3.7/lib-dynload',\n",
       " '',\n",
       " '/home/janlandw/.conda/envs/py3_jan/lib/python3.7/site-packages',\n",
       " '/home/janlandw/.conda/envs/py3_jan/lib/python3.7/site-packages/IPython/extensions',\n",
       " '/home/janlandw/.ipython',\n",
       " '../misc']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sys.path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [],
   "source": [
    "### Defining some Functions for Reading nc-files and Plotting\n",
    "def read_hist(path, hist_name, var_name, mean_opt=''):\n",
    "        nc_f = '../climber/'+path+'/'+hist_name+'.nc'\n",
    "        nc_fid = Dataset(nc_f, 'r')\n",
    "        #nc_attrs, nc_dims, nc_vars = ncdump(nc_fid)\n",
    "        if var_name=='ts_ann':\n",
    "            var=nc_fid.variables[var_name][:,::-1,:]\n",
    "        if var_name=='pco2diag':\n",
    "            var=nc_fid.variables[var_name][:]\n",
    "        if mean_opt=='global':\n",
    "            var=jan.global_mean(var)\n",
    "        times=np.arange(0,len(var),1)\n",
    "        return var, times\n",
    "\n",
    "def read_file(path):\n",
    "    nc_f = '../'+path+'/tmp/history_p2.nc'\n",
    "    nc_fid = Dataset(nc_f, 'r')\n",
    "    #nc_attrs, nc_dims, nc_vars = ncdump(nc_fid)\n",
    "    ts_ann=jan.global_mean(nc_fid.variables['ts_ann'][:,::-1,:])\n",
    "    times_ts=np.arange(0,len(ts_ann),1)\n",
    "    timesincemod=time.time()-os.stat('../'+path+'/tmp/history.nc').st_mtime\n",
    "    year=str(len(nc_fid.variables['ts_ann'][:,0,0]))\n",
    "    status=[]\n",
    "    if timesincemod<1800:\n",
    "        status=' (running)'    \n",
    "    else:\n",
    "        status=' (stopped)'\n",
    "    if path in paths_pulse_failed:\n",
    "        status=' (failed)'\n",
    "    elif path in paths_pulse_failed_13c:\n",
    "        status= status+ '(13C failed)'        \n",
    "#    if os.path.islink('../'+path+'/.workdir_locked_by_batchjob'):\n",
    "#        status=' (running)'\n",
    "#    else:\n",
    "#        status=' '  \n",
    "    return times_ts, ts_ann, status, year\n",
    "\n",
    "def plot_paths(ax_sel='', path_list='', xlims='', ylims='', statuslab='on'):\n",
    "    ax_sel.grid(linestyle=':', zorder=0)\n",
    "    for path in path_list:\n",
    "        times_ts, ts_ann, status, year=read_file(path)\n",
    "        if statuslab=='on':\n",
    "            labelstr=path+status+'(yr'+year+')'\n",
    "        elif statuslab=='off':\n",
    "            labelstr=path\n",
    "        ax_sel.plot(times_ts,ts_ann, '-',lw=1, c=colors_df.loc[path, 'color'] ,label=labelstr, alpha=0.8)\n",
    "    if xlims!='':\n",
    "        ax_sel.set_xlim(xlims)\n",
    "    if ylims!='':\n",
    "        ax_sel.set_ylim(ylims)\n",
    "    ax_sel.legend(loc='lower right',ncol=2, fontsize='x-small')\n",
    "    ax_sel.set_xlabel('Time (years)');\n",
    "    ax_sel.set_ylabel(r'ts_ann (${\\circ}C$)')\n",
    "    plt.tight_layout()\n",
    "    \n",
    "### Function for reading Snapshots-Timeseries and store them in pickle-File\n",
    "def read_allsnapshotsmom(var='', scenario='', paths=''):\n",
    "\n",
    "    #scenario='long'\n",
    "    #var='dp13'\n",
    "\n",
    "#     if scenario=='short':\n",
    "#         #paths_snapts=paths_pulse_control+paths_pulse_c_short\n",
    "#         paths_snapts=paths_pulse_control+paths_pulse_c_short+paths_pulse_c_short_extra_13c+paths_pulse_cs_short+paths_pulse_s_short\n",
    "#         #+paths_pulse_failed\n",
    "#     elif scenario=='long':\n",
    "#         paths_snapts=paths_pulse_long\n",
    "\n",
    "    var_ts_dfs=pd.DataFrame([], columns=[var+'_ts_globmean', 'years'], index=paths) #, dtype=float[], columns=['dp13_ts_globmean', 'years'], index=[]\n",
    "\n",
    "    for i in range(len(paths)): #_snapts\n",
    "        path=paths[i] #paths_snapts[i]\n",
    "        \n",
    "#         if path in paths_pulse_control+paths_pulse_c_long+paths_pulse_cs_long:\n",
    "#             sbx_range=1\n",
    "#         else:\n",
    "#             sbx_range=10\n",
    "#         %ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../$path/TIMERES/all_snapshots_mom_annual.nc\"; \\\n",
    "#                 let a=ph[i=@ave,j=@ave,k=1,l=@sbx:%(sbx_range)s]; let ph_mean_min_f=a[l=@min]-a[l=1]' % locals()\n",
    "#         %ferret_getdata ph_mean_min_f=ph_mean_min_f\n",
    "#         var_ts_dfs.loc[path, 'ph_mean_min']=ph_mean_min_f['data'] \n",
    "        \n",
    "        nc_f = '../'+path+'/TIMERES/all_snapshots_mom_annual.nc'\n",
    "        nc_fid = Dataset(nc_f, 'r')\n",
    "        #nc_attrs, nc_dims, nc_vars = ncdump(nc_fid)\n",
    "        var_ts=nc_fid.variables[var][:,0,::-1,:]\n",
    "        var_ts_globmean=jan.global_mean(var_ts, grid='ocean') #, restrict_lat='yes'\n",
    "\n",
    "        #exclude southpole using ferret for averaging\n",
    "        #%ferret_run 'define symbol path = %(path)s '\n",
    "        #%ferret_run 'use \"../$path/TIMERES/all_snapshots_mom_annual.nc\"'\n",
    "        #%ferret_run 'let var_fer=dp13[i=@ave,y=75S:90N@ave,k=1]'\n",
    "        #%ferret_getdata var_dict = var_fer\n",
    "        #var_nested=var_dict['data']\n",
    "        #dp13_ts_globmean=var_nested.flatten()\n",
    "\n",
    "        dates=num2date(nc_fid.variables['Time'][:], units=nc_fid.variables['Time'].units, calendar=nc_fid.variables['Time'].calendar)\n",
    "        years_strings=[time.strftime('%Y') for time in dates]\n",
    "        years=np.array(list(map(int,years_strings)))\n",
    "        #times=[time.timetuple().tm_year for time in test]\n",
    "\n",
    "        var_ts_dfs.loc[path, [var+'_ts_globmean','years'] ]= [var_ts_globmean,years]\n",
    "\n",
    "    var_ts_dfs.to_pickle('./'+var+'_ts_'+scenario+'_corr.pkl')\n",
    "    #return var_ts_dfs\n",
    "    # if scenario=='short':\n",
    "    #     dp13_ts_dfs.to_pickle('./dp13_ts.pkl')\n",
    "    # elif scenario=='long':\n",
    "    #     dp13_ts_dfs.to_pickle('./dp13_ts_long.pkl')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# draw a bbox of the region of the inset axes in the parent axes and\n",
    "# connecting lines between the bbox and the inset axes area\n",
    "# loc1, loc2 : {1, 2, 3, 4} \n",
    "def mark_inset(parent_axes, inset_axes, loc1a=1, loc1b=1, loc2a=2, loc2b=2, **kwargs):\n",
    "    rect = TransformedBbox(inset_axes.viewLim, parent_axes.transData)\n",
    "\n",
    "    pp = BboxPatch(rect, fill=False, **kwargs)\n",
    "    parent_axes.add_patch(pp)\n",
    "\n",
    "    p1 = BboxConnector(inset_axes.bbox, rect, loc1=loc1a, loc2=loc1b, **kwargs)\n",
    "    inset_axes.add_patch(p1)\n",
    "    p1.set_clip_on(False)\n",
    "    p2 = BboxConnector(inset_axes.bbox, rect, loc1=loc2a, loc2=loc2b, **kwargs)\n",
    "    inset_axes.add_patch(p2)\n",
    "    p2.set_clip_on(False)\n",
    "\n",
    "    return pp, p1, p2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [],
   "source": [
    "### Listing and Grouping the Pulse-Runs/Paths \n",
    "\n",
    "paths_pulse_control=[\n",
    "       'pulse_control_1000ppm',\n",
    "       'pulse_control_1500ppm',\n",
    "       'pulse_control_2000ppm']\n",
    "\n",
    "paths_pulse_c_short_base=[\n",
    "       'pulse_c_1000ppm_5300GtC_5ka', \n",
    "       'pulse_c_1500ppm_2500GtC_5ka',\n",
    "       'pulse_c_1500ppm_5300GtC_5ka',\n",
    "       'pulse_c_1500ppm_7500GtC_5ka',     \n",
    "       'pulse_c_2000ppm_5300GtC_5ka']\n",
    "paths_pulse_c_short_extra_13c=[\n",
    "       'pulse_c_1500ppm_5300GtC_5ka_13d13C',\n",
    "       'pulse_c_1500ppm_5300GtC_5ka_40d13C']\n",
    "paths_pulse_c_short_extra_Eppley=[    \n",
    "       'pulse_c_1500ppm_5300GtC_5ka_Eppley',\n",
    "       'pulse_c_1500ppm_7500GtC_5ka_Eppley']\n",
    "paths_pulse_c_long=['pulse_c_1500ppm_5300GtC_12ka']\n",
    "paths_pulse_c_short=paths_pulse_c_short_base+paths_pulse_c_short_extra_13c+paths_pulse_c_short_extra_Eppley\n",
    "paths_pulse_c=paths_pulse_c_short+paths_pulse_c_long\n",
    "\n",
    "paths_pulse_s_short=[\n",
    "        'pulse_rev_s_1500ppm_125GtS_5ka']\n",
    "paths_pulse_s_long=[]\n",
    "paths_pulse_s_failed=[ ]\n",
    "paths_pulse_s_failed_13c=[]\n",
    "paths_pulse_s=paths_pulse_s_short+paths_pulse_s_long+paths_pulse_s_failed\n",
    "\n",
    "paths_pulse_cs_short=[\n",
    "        'pulse_rev_cs_1000ppm_5300GtC_125GtS_5ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_10GtS_5ka_sparse',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_50GtS_5ka',    \n",
    "        'pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_250GtS_5ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_500GtS_5ka',\n",
    "        'pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka']\n",
    "paths_pulse_cs_long=[\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka']\n",
    "paths_pulse_cs_failed=['pulse_rev_cs_1500ppm_5300GtC_600GtS_5ka'] \n",
    "paths_pulse_cs_irreg=[\n",
    "        ]\n",
    "        #those two did not break, but show an anomalous bend in the pCO2 curve and anomalous\n",
    "paths_pulse_cs_failed_13c=[]\n",
    "paths_pulse_cs=paths_pulse_cs_short+paths_pulse_cs_long+paths_pulse_cs_failed\n",
    "\n",
    "paths_pulse_s_single=[       \n",
    "       'pulse_rev_s_single_1500ppm_9MtS',\n",
    "       'pulse_rev_s_single_1500ppm_50MtS',\n",
    "       'pulse_rev_s_single_1500ppm_100MtS',\n",
    "       'pulse_rev_s_single_1500ppm_200MtS',\n",
    "       'pulse_rev_s_single_1500ppm_250MtS',\n",
    "       'pulse_rev_s_single_1500ppm_500MtS',\n",
    "       'pulse_rev_s_single_1500ppm_1000MtS']\n",
    "#'pulse_corr_s_single_1000ppm_250MtS',\n",
    "#'pulse_corr_s_single_2000ppm_250MtS'\n",
    "\n",
    "paths_pulse_failed=paths_pulse_s_failed+paths_pulse_cs_failed\n",
    "paths_pulse_failed_13c=paths_pulse_cs_failed_13c+paths_pulse_s_failed_13c\n",
    "\n",
    "paths_pulse_long=paths_pulse_control+paths_pulse_c_long+paths_pulse_s_long+paths_pulse_cs_long\n",
    "paths_pulse=paths_pulse_control+paths_pulse_c+paths_pulse_s+paths_pulse_cs\n",
    "\n",
    "# paths_nobiogeo=['c3beta_tria_200Ma_700ppm','c3beta_tria_200Ma_1000ppm', 'c3beta_tria_200Ma_1500ppm', \n",
    "#       'c3beta_tria_200Ma_2000ppm', 'c3beta_tria_200Ma_3000ppm', 'c3beta_tria_200Ma_4000ppm']\n",
    "paths_nobiogeo=['c3beta_tria_200Ma_1000ppm', 'c3beta_tria_200Ma_1500ppm', \n",
    "      'c3beta_tria_200Ma_2000ppm']\n",
    "\n",
    "paths_all=paths_nobiogeo+paths_pulse\n",
    "\n",
    "paths_paper=['pulse_control_1500ppm',\n",
    "            'pulse_c_1000ppm_5300GtC_5ka', \n",
    "            'pulse_c_1500ppm_5300GtC_5ka',    \n",
    "            'pulse_c_2000ppm_5300GtC_5ka',\n",
    "            'pulse_c_1500ppm_5300GtC_12ka',\n",
    "            'pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka',   \n",
    "            'pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka']\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "###Colour list\n",
    "color_dict=mcd.TABLEAU_COLORS #XKCD_COLORS\n",
    "color_list=list(color_dict.keys())[:]*5\n",
    "colors_df=pd.DataFrame([], columns=['color'], index=paths_all+paths_pulse_s_single)\n",
    "colors_df.iloc[:,0]=color_list[0:len(paths_all+paths_pulse_s_single)] #color_list[0:37]\n",
    "colors_df.loc['pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka', 'color']='tab:purple'\n",
    "\n",
    "colors_paper_df=pd.DataFrame([], columns=['color'], index=paths_paper)\n",
    "colors_paper_df.loc['pulse_control_1500ppm', 'color']='tab:grey'\n",
    "colors_paper_df.loc['pulse_c_1000ppm_5300GtC_5ka', 'color']='tab:cyan'\n",
    "colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color']='tab:green'\n",
    "colors_paper_df.loc['pulse_c_1500ppm_7500GtC_5ka', 'color']='tab:brown'\n",
    "colors_paper_df.loc['pulse_c_2000ppm_5300GtC_5ka', 'color']='darkorange'\n",
    "colors_paper_df.loc['pulse_c_1500ppm_5300GtC_12ka', 'color']='tab:blue'\n",
    "colors_paper_df.loc['pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka', 'color']=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color']\n",
    "colors_paper_df.loc['pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka', 'color']=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_12ka', 'color']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "times=np.arange(1,12501,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Generate continental mask and store it\n",
    "nc_f = '../climber/c3beta_tria_200Ma_1500ppm/snapshots.004002.01.01.dta.nc'  \n",
    "nc_fid = Dataset(nc_f, 'r')  \n",
    "#nc_attrs, nc_dims, nc_vars = ncdump(nc_fid)\n",
    "temp = np.flipud(nc_fid.variables['temp'][0,0,:,:])\n",
    "mask=np.empty([48,96])\n",
    "mask[np.where(temp > -1000)]=1\n",
    "mask[np.where(temp < -1000)]=0\n",
    "with open('../climber/continental_mask.pickle', 'wb') as f:  \n",
    "   pickle.dump(mask, f)\n",
    "with open('../climber/continental_mask.pickle', 'rb') as f:  \n",
    "   continental_mask = pickle.load(f, encoding='latin1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. S3: Aerosol Forcing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_10yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_10yr_zonal_mean_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_1yr_zonal_mean_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_run 'cancel data/all; use \"../emission_scenarios/examples/aod_multi_1200y_125GtS_250MtS_rev_0p1.nc\"; \\\n",
    "    let aod_1yr_zonal_mean_f=aod550[j=@ave,l=1:60000:12@ave]; let aod_10yr_f=aod550[l=1:60000:120@ave]; let aod_10yr_zonal_mean_f=aod550[j=@ave,l=1:60000:120@ave]' % locals()  #,l=@sbx:100\n",
    "\n",
    "%ferret_getdata aod_10yr_f=aod_10yr_f\n",
    "%ferret_getdata aod_10yr_zonal_mean_f=aod_10yr_zonal_mean_f\n",
    "%ferret_getdata aod_1yr_zonal_mean_f=aod_1yr_zonal_mean_f\n",
    "\n",
    "aod_10yr=aod_10yr_f['data'][0,:,0,:,0,0]; \n",
    "aod_10yr_zonal_mean=aod_10yr_zonal_mean_f['data'][0,0,0,:,0,0]; \n",
    "aod_1yr_zonal_mean=aod_1yr_zonal_mean_f['data'][0,0,0,:,0,0]; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_1yr_zonal_mean_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_run 'cancel data/all; use \"../emission_scenarios/examples/aod_multi_1200y_125GtS_250MtS_rev_0p1.nc\"; \\\n",
    "    let aod_1yr_zonal_mean_f=aod550[j=@ave,l=1:60000:12@ave]' % locals()  #,l=@sbx:100\n",
    "\n",
    "%ferret_getdata aod_1yr_zonal_mean_f=aod_1yr_zonal_mean_f\n",
    "\n",
    "aod_1yr_zonal_mean=aod_1yr_zonal_mean_f['data'][0,0,0,:,0,0]; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "nc_f = '../emission_scenarios/examples/eruptions_multi_1200y_125GtS_250MtS.nc'\n",
    "nc_fid = Dataset(nc_f, 'r')\n",
    "injs=nc_fid.variables['ssi'][:] \n",
    "injs_yrs=nc_fid.variables['year'][:] \n",
    "years=np.arange(1,5000+1,1)\n",
    "\n",
    "window=10 #years\n",
    "n_10yr=np.empty(len(years)-window)\n",
    "ssi_10yr=np.empty(len(years)-window)\n",
    "for i in range(len(n_10yr)):\n",
    "    n_10yr[i]=len(injs_yrs[abs(injs_yrs-years[i+int(1./2*window-1)]) <= 1./2*window-1]) \n",
    "    ssi_10yr[i]=np.sum(injs[abs(injs_yrs-years[i+int(1./2*window-1)]) <= 1./2*window-1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_single_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: rad_forcing_single_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_run 'cancel data/all; use \"../emission_scenarios/examples/aod_single_250MtS_rev_0p1.nc\"; \\\n",
    "    let aod_single_f=aod550[j=@ave]; let rad_forcing_single_f=21*aod550[j=@ave,l=1:1200:12@ave]' % locals()  #,l=@sbx:100\n",
    "\n",
    "%ferret_getdata aod_single_f=aod_single_f\n",
    "%ferret_getdata rad_forcing_single_f=rad_forcing_single_f\n",
    "\n",
    "aod_single=aod_single_f['data'][0,0,0,:,0,0]; \n",
    "rad_forcing_single=rad_forcing_single_f['data'][0,0,0,:,0,0]; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x540 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(11,7.5))\n",
    "plt.clf()\n",
    "gs = GridSpec(2,4,height_ratios=[1,1], width_ratios=[1,0.075,0.075,1])\n",
    "\n",
    "\n",
    "ax_1_0 = plt.subplot(gs[1,0])\n",
    "ax_0_0_1 = plt.subplot(gs[0,0], sharex=ax_1_0)\n",
    "ax_0_0=ax_0_0_1.twinx()\n",
    "ax_0_2 = plt.subplot(gs[0,3])\n",
    "ax_0_2.set_zorder(10)\n",
    "ax_0_2.patch.set_visible(False)\n",
    "ax_0_2_1 = ax_0_2.twinx()\n",
    "\n",
    "ax_1_1 = plt.subplot(gs[1,1])\n",
    "ax_1_2 = plt.subplot(gs[1,3])#, ymargin=5\n",
    "#ax11 = plt.subplot(gs[:-1,1]) #sharey=ax1\n",
    "\n",
    "lats_eva=np.linspace(-90,90,aod_10yr.shape[0]) \n",
    "times_1yr_eva=np.arange(0,aod_1yr_zonal_mean.shape[0],1)\n",
    "times_10yr_eva=np.arange(0,aod_10yr.shape[1],1)\n",
    "x,y = np.meshgrid(times_10yr_eva, lats_eva)\n",
    "\n",
    "#ax_0_0.plot(times_1yr_eva,aod_1yr_zonal_mean)\n",
    "ax_0_0.plot(times_10yr_eva,aod_10yr_zonal_mean,lw=2)\n",
    "ax_0_0.set_ylim(0,1)\n",
    "ax_0_0.set_ylabel('AOD',fontsize=12, color='tab:blue')\n",
    "ax_0_0_1.plot(years[10:]/10,ssi_10yr,c='tab:orange',lw=2)\n",
    "ax_0_0_1.set_ylim(0,5000)\n",
    "ax_0_0_1.set_ylabel('S injection (MtS/10yr)',fontsize=12, color='tab:orange')\n",
    "\n",
    "ax_0_2.plot(np.arange(0,100,1./12),aod_single,c='tab:blue',lw=2)\n",
    "ax_0_2.set_xlim(0,14)\n",
    "ax_0_2.set_ylim(0,1)\n",
    "ax_0_2.set_xlabel('Time (years)',fontsize=12)\n",
    "ax_0_2.set_ylabel('AOD',color='tab:blue',fontsize=12)\n",
    "ax_0_2_1.plot(np.arange(0,100,1),rad_forcing_single,c='k',lw=2)\n",
    "ax_0_2_1.set_ylabel('$\\mathsf{-\\Delta F_a}$ ($W/m^2$)',color='k',fontsize=12)\n",
    "ax_0_2_1.set_ylim(0,16)\n",
    "\n",
    "aod_pcolor=ax_1_0.pcolor(x,y,aod_10yr,cmap='Blues')\n",
    "#ax_1_0.set_ylim(-90,90)\n",
    "ax_1_0.set_xlim(50,200)\n",
    "ax_1_0.set_xticks([50,100,150,200]);\n",
    "ax_1_0.set_xticklabels([500,1000,1500,2000]);\n",
    "ax_1_0.set_yticks([-90,-60,-30,0,30,60,90]);\n",
    "ax_1_0.set_xlabel('Time (years)',fontsize=12)\n",
    "ax_1_0.set_ylabel('Latitude',fontsize=12)\n",
    "#cbar=fig.colorbar(aod_pcolor,ax=ax_1_0, orientation='vertical')\n",
    "cbar=fig.colorbar(mappable=aod_pcolor, cax=ax_1_1, orientation='vertical', boundaries=np.arange(0,1.5,0.1))\n",
    "cbar.ax.tick_params(labelsize=10);\n",
    "cbar.set_label(r'AOD', fontsize=12)\n",
    "#ax_1_2.plot(np.average(aod[:,50:200],axis=1),lats_eva)\n",
    "ax_1_2.plot(aod_10yr[:,113],lats_eva,lw=2)\n",
    "ax_1_2.set_ylim(-90,90)\n",
    "ax_1_2.set_xlim(0,0.8)\n",
    "ax_1_2.set_yticks([-90,-60,-30,0,30,60,90]);\n",
    "ax_1_2.set_xlabel('AOD',fontsize=12)\n",
    "ax_1_2.set_ylabel('Latitude',fontsize=12)\n",
    "ax_1_2.text(0.05,0.9,'Years 1125:1135',transform=ax_1_2.transAxes,fontsize=12)\n",
    "\n",
    "ax_0_0.text(-0.13,1.06,'(a)',transform=ax_0_0.transAxes,fontsize=12)\n",
    "ax_0_2.text(-0.13,1.06,'(c)',transform=ax_0_2.transAxes,fontsize=12)\n",
    "ax_1_0.text(-0.13,1.06,'(b)',transform=ax_1_0.transAxes,fontsize=12)\n",
    "ax_1_2.text(-0.13,1.06,'(d)',transform=ax_1_2.transAxes,fontsize=12)\n",
    "\n",
    "plt.tight_layout(w_pad=-1.5) #h_pad=-4.25, w_pad=-2\n",
    "\n",
    "fig.savefig('./plot_pdf_files/FigS3_eva_forcing_illustration.pdf',bbox_inches='tight', pad_inches=0.05) #, dpi=900\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. S2: Reproducing aerosol forcing scenarios of Schmidt et al. 2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_schmidt_10yr_orig_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_schmidt_10yr_rev_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_schmidt_10yr_orig_ave_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: aod_schmidt_10yr_rev_ave_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_run 'set window/aspect=0.45; cancel data/all; \\\n",
    "            use \"../emission_scenarios/examples/aod_schmidt_12000MtS_0p44_10yrs.nc\"; \\\n",
    "            use \"../emission_scenarios/examples/aod_schmidt_12000MtS_0p44_10yrs_rev_0p1.nc\";\\\n",
    "            use \"../emission_scenarios/examples/aod_schmidt_60000MtS_0p44_50yrs_rev_0p1.nc\";\\\n",
    "            let aod_schmidt_10yr_orig_f=aod550[j=@ave,d=1] ; let aod_schmidt_10yr_orig_ave_f=aod550[j=@ave,l=1:1200:12@ave,d=1] ;\\\n",
    "            let aod_schmidt_10yr_rev_f=aod550[j=@ave,d=2] ; let aod_schmidt_10yr_rev_ave_f=aod550[j=@ave,l=1:1200:12@ave,d=2] ;' % locals()  #,l=@sbx:100\n",
    "\n",
    "#             set viewport left; plot aod550[j=@ave,d=1]; plot/over aod550[j=@ave,d=2]; plot/over aod550[j=@ave,d=3]; \\\n",
    "#             set viewport right; plot 21*aod550[j=@ave,l=0:360,d=2]; list 21*aod550[j=@ave,l=72:134@ave];\\\n",
    "\n",
    "%ferret_getdata aod_schmidt_10yr_orig_f=aod_schmidt_10yr_orig_f\n",
    "%ferret_getdata aod_schmidt_10yr_rev_f=aod_schmidt_10yr_rev_f\n",
    "\n",
    "%ferret_getdata aod_schmidt_10yr_orig_ave_f=aod_schmidt_10yr_orig_ave_f\n",
    "%ferret_getdata aod_schmidt_10yr_rev_ave_f=aod_schmidt_10yr_rev_ave_f\n",
    "\n",
    "aod_schmidt_10yr_orig=aod_schmidt_10yr_orig_f['data'][0,0,0,:,0,0]; \n",
    "aod_schmidt_10yr_rev=aod_schmidt_10yr_rev_f['data'][0,0,0,:,0,0]; \n",
    "\n",
    "aod_schmidt_10yr_orig_ave=aod_schmidt_10yr_orig_ave_f['data'][0,0,0,:,0,0]; \n",
    "aod_schmidt_10yr_rev_ave=aod_schmidt_10yr_rev_ave_f['data'][0,0,0,:,0,0]; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: tsann_schmidt_10yr_orig_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: tsann_schmidt_10yr_rev_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: tsann_schmidt_50yr_rev_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_run 'cancel data/all; \\\n",
    "            use \"../climber/pulse_corr_s_schmidt_12000MtS_0p44_10yrs/history_p2.nc\";\\\n",
    "            use \"../climber/pulse_rev_s_schmidt_12000MtS_0p44_10yrs/history_p2.nc\"; \\\n",
    "            use \"../climber/pulse_rev_s_schmidt_60000MtS_0p44_50yrs/history_p2.nc\"; \\\n",
    "            let tsann_schmidt_10yr_orig_f=ts_ann[i=@ave,j=@ave,l=501:600,d=1];\\\n",
    "            let tsann_schmidt_10yr_rev_f=ts_ann[i=@ave,j=@ave,l=501:600,d=2];\\\n",
    "            let tsann_schmidt_50yr_rev_f=ts_ann[i=@ave,j=@ave,l=501:600,d=3];\\\n",
    "            ' % locals()  #,l=@sbx:100\n",
    "\n",
    "#             plot ts_ann[i=@ave,j=@ave,l=500:700,d=4]; plot/over ts_ann[i=@ave,j=@ave,l=500:600,d=3]; plot/over ts_ann[i=@ave,j=@ave,l=500:600,d=1]; plot/over ts_ann[i=@ave,j=@ave,l=500:600,d=2];  \\\n",
    "#             list ts_ann[i=@ave,j=@ave,l=@min,d=3]-ts_ann[i=@ave,j=@ave,l=@max,d=3]; \\\n",
    "#             list ts_ann[i=@ave,j=@ave,l=@min,d=2]-ts_ann[i=@ave,j=@ave,l=@max,d=2]; \\\n",
    "#             list ts_ann[i=@ave,j=@ave,l=@min,d=1]-ts_ann[i=@ave,j=@ave,l=@max,d=1]; \\\n",
    "\n",
    "%ferret_getdata tsann_schmidt_10yr_orig_f=tsann_schmidt_10yr_orig_f\n",
    "%ferret_getdata tsann_schmidt_10yr_rev_f=tsann_schmidt_10yr_rev_f\n",
    "%ferret_getdata tsann_schmidt_50yr_rev_f=tsann_schmidt_50yr_rev_f\n",
    "\n",
    "tsann_schmidt_10yr_orig=tsann_schmidt_10yr_orig_f['data'][0,0,0,:,0,0]; \n",
    "tsann_schmidt_10yr_rev=tsann_schmidt_10yr_rev_f['data'][0,0,0,:,0,0]; \n",
    "tsann_schmidt_50yr_rev=tsann_schmidt_50yr_rev_f['data'][0,0,0,:,0,0]; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sbCxlZWUAxMfHB86JiYkJHBcTExM4pqKa/l9XVW6++eYaTSi9ZcsWHn/8cVatWkXTpk255ZZbOHbsWI3KXbJkCQ8//DDLly8PfF/p6el89NFHgWN27tyJx+M57XXS09Np1qwZycnJJCcnc/HFF7N27dp6k6CitomvJmOgjhw5EphQ9tixY2zevDnw2bZt2ygoKAC8K/T+97//DXy2c+fOQI+a0tJSNmzYEPgraO/evezduzdw7PTp03nxxRfp2bPKqQaNqfeys7PZuHFjYDsrK4v27dvzgx/8gN27d7Nq1SoADh8+XGWSqa2LL7440Bz33nvvceDAAQAaNWoUeN5V0dChQ3nzzTfJyckBYP/+/YFedfHx8ZU+vz506BDJyck0adKEffv28d5779Uozq+++orJkyezcOHCk2prl112GYsXL+bAgQMcOHCAxYsXc9lll532WmPGjOGTTz6hrKyMoqIivvjiC7p3716jeJwUtTWo080ikZubS1ZWFuvWrSM/P58nnniCkpIS+vfvz9q1awPJqkWLFoEf3HPPPfek9uBWrVoFEtA555zDgQMHAuelp6cHHnwmJSXxl7/8hcmTJ9fdN2uMSxQWFjJ16lQOHjxIXFwcnTt3ZtasWSQkJDB//nymTp3K0aNHSUpKYsmSJWEt+4EHHuD6669nwIABDBkyJNBx4JxzzuGiiy6iV69ejBo16qTnUD169OBPf/oTI0aM4Pjx48THx/O3v/2N9u3bM2nSJPr06cOAAQNOeg7Vt29f+vfvT8+ePTnvvPO46KKLKo3ntttu4/bbbycjI+Ok/XfddReFhYVcc801ALRr146FCxeSlpbGfffdF2huvP/++0lLSwPgqaee4tFHH2Xv3r306dOHyy+/nBdeeIHu3bszcuRI+vTpQ0xMDLfddhu9evUK302tY1JZu+bZICMjQ0833mDNmjUMHDiQ/v37s2bNmsD+0tJSunXrxpYtWyIRJgAdO3bk888/Z8+ePbRo0YLWrVtHrGxjjKkrIrJaVTPOfGTloraJr7IaVH5+PpMmTao0OfXv3z/wvkOHDif9FTJu3LjA+/POO4/BgwcHtkePHk1cnLeimp6ezqWXXhr47JJLLgG8bdYPP/ww/fr1q3e9bIwxpq5EbRPfj3/8Y44cOXJSG/LVV18deAh51VVX8eSTT7Jq1SrOP/982rdvT2FhIfv37w80DezevZu0tDQaNGhAcXEx+fn5gTEdOTk5pKSk0LBhQ8rKyti7dy/p6emANxEmJCTQqFEjunXrxnfffRdob7du5sYY4xWWBCUiSUAqcFBVj4bjmnVNRE5af2nTpk2B5DRixAjmzp1L48aN6dixY+CYlJSUkzpV+JMReHsaBW8HP9yMi4sLJCfwtnn7tW3blu+++47i4mLAupkbY4xfSE18InKJiHwJHAZ2AodF5EsRGRqW6EKQnZ3NnDlzAO9zJY/Hw7x58wAoKirC4/Ewf/58AAoKCgIPMm+66SZeeeUVRo8ezaJFiwBvjzuPxxMYtb1jxw48Hk/gIe7mzZvxeDyB8QrZ2dl4PB5WrFgBwPr16/F4PIEeSllZWXg8HrKysgK1MX9ZR44cYcWKFXg8HrKzswFYvnw5Ho8n0HtwyZIleDyewIDF999/H4/HE+iUsWjRIjweT6AH4dtvv43H4wn0Npw/fz4ej4eioiLAO97C4/EEapNz5sw5qfvq888/z7BhwwLbzzzzTGDwIMDMmTMZPXp0YPvxxx8/qdlzxowZjB8/PrD90EMPceONNwa277//fiZMmBDYnj59OpMmTQpsT5s2jSlTpgS277zzTu68887A9pQpU5g2bVpge9KkSUyfPj2wPWHChJMGbt5444089NBDge3x48czY8aMwPa4ceN4/PHHA9ujR49m5syZge1Ro0adNHfbsGHDeP755wPbHo+nRj97Ho8nMD4nLy8Pj8cTkZ898M7e4PF4WL9+PYD97NnPXlh/9kJV6xqUiGQA7wIvAHcDu4FzgbHAIhEZoqqrQo6wjuTm5vKHP/yBvLw8unbtSk5ODgkJCZWOQK9L/pHh/tksrInPGGN8ajuJHzAfeLCKzx4AXg9lksBQX2eaLHbGjBkK6F133aUPPPCAAjp16tTTnlMXXnjhBQXU4/EooGPGjIl4DMYYUxdwcLLYC4DnqvjseeDCEK5d5/zPelJSUgJV0fPPPz/icfi7lPsHCloNyhhjvELpJJGqqrsr+0BVd4tIkxCuXef8beANGzYMtK87sXBhy5YtAe9kmZ999hnNmzePeAzGGONGddnN3NUjgP0JqkGDBoEHwl26dIl4HP7efvn5+Vx4oasrncYYE1GhJKhkEdlexWcCNKziM1c4etTbG/7w4cMUFRWRnp4emDYkkvwJKicnh+PHjxMTE7Vjp40x5iShJKhLz3yIe/kT1L59+wDv/FlOSExMpEmTJhQUFDBp0iRSUlL461//6kgsxhjjJrVOUKq6PJyBRNqPfvQjYmNjOXToEOBcggLvc6iCggJmz55NcnKyJShjjCH0gbodRGSOiOwSkWLf17kicl64AqwrU6dO5dVXXw3MRu5kggqedaKoqCgw67kxxkSzWicoEekOrAFaAP8XGO372hzI9H1eneu8KCI5IlLpsGPxekpENonIOhEZUNuYK7N27VrA+RoUQEJCAqoa6MBhjDHRLJRnUDOAv6nqfRX2zxGRPwGPAj+pxnXmAE8DVU3jPQro4nudDzzr+xqS7OxsDh8+zM6dO0lKSnKki7mfP0ElJiZSUlLCoUOHqrWQojHGnM1CaeK7GHiiis+eAH5cnYuo6sfA/tMcMgZ42Tcw+XMgVURCXjDpqquuCiz81b59e2JjY0O9ZK35m/ji4+MBAs/FjDEmmoWSoGKBU9c79ir1fR4O5wI7grZ3+vaFJLgZzT8fnlP8g3P9SdISlDHGhJagVgETqvjsFqDq5WxrRirZV+kgYBGZJCKZIpKZm5t72ov6u5mDexJUw4YNGTRokKO1OWOMcYtQnkHdB/xHRLoBbwJ7gNbANcDNwGWhhwd4a0zBGSQd78zpp1DVWcAs8C75frqLuilBNWvWDPA2NfqnrjfGmGhX6xqUqq4ARgB9gaXAf31f++JNTp+HI0BgIfBzX2++wUCBqu4J5YIVe8oFLyboBH8N6ky1PmOMiSYhzcWnqiuBi30r6qYBB4DOwM/x1qranOZ0AETkNcADNBORnXiX6oj3Xf/veNecuhzYBBRRdbNitZWWlnL8+HFEBFUN9KJzir8GlZeXR3l5OeXl5SQkJDgakzHGOC1ck8WmAFfjbdrrC3wC/Lo6J6rq9Wf4XIEppzumpvzNe/4EFbwEuxP85efl5REXF8cf//hH7ruvYu99Y4yJLqEM1I0XkXEisgjYBUwGFgAFwLWq+kaYYgy7hg0bsnLlStq08VbwnE5Q8fHxpKam+hd7tF58xhhDaL349uFdsDAbGKyqPVT1IaA4LJHVofj4eAYPHhxYHNDpBAUnmvkACgoKHIzEGGPcIZQEtQ5IxTurww9FpGl4QoqM8vJyDh48CEDTps6HHrxQodWgjDEmtF58HqATsBiYBuz1Nfcl4+vk4FY7d+5k0qRJqCqpqamuGHcUXIOyBGWMMSHOZq6q21T1IVXtAgzFOxbqOLBWRB4NR4B1Yc+ePbz44ouAO5r3wGpQxhhTUdiWb1XVT1V1EtAKmAr0Dte1w62kpCTw3i0JympQxhhzsnB1Mw9Q1WPAa76XK7k5QQ0dOpSpU6c6HI0xxjgvbDWo+qS4+ERHQ7ckKH8TX5s2bRgzZozD0RhjjPOiMkG5uQaVl5fncCTGGOMOUZ+g0tLSHIzkBH8NKjs7m8ceeyzQBd4YY6JVVCao5OTkQGJyWw1qx44d/O53v2PHjh1nOMMYY85uUZmgRo0axdChQwH3Jajjx48D1tRnjDFRmaAA8vPzAfckqMaNG5OQkEB5eTlgCcoYYyxBuSRBichJy35YgjLGRLuoTFBPPPEEa9euBaBJkyYOR3NC69atA+8tQRljol1UJqjgcVCNGjVyMJKTtWrVKvDeX8MzxphoFZUJKribuRsTVFxcHGVlZQ5HY4wxzorKBOVfUTcmJoYGDRo4HM0J/gQ1ffp0nn76aYejMcYYZ0Vlgjp8+DAAiYmJiIjD0ZzgT1B79+51OBJjjHFeVCYo/0q6iYmJDkdyMktQxhhzQlQmqKKiIgCSkpIcjuRk/gS1bNkymjVrxrFjxxyOyBhjnBOVCeriiy8GTl6DyQ383cyPHTtGfn4+O3fudDgiY4xxTlQmqK5duwKcNDDWDdq0aYOIBGaTsARljIlmrkhQIjJSRLJFZJOI3FPJ5x4RKRCRLN/r/lDK83eScFMXc4CEhATS09MD2zZhrDEmmoV9Rd2aEpFY4G/AcGAnsEpEFqrqhgqHfqKqV4ajzJUrVwIQGxsbjsuFVYcOHQKJyWpQxpho5oYa1CBgk6puVtUS4B9AnS4p++677wK4shNCx44dA+8tQRljopkbEtS5QHBb1k7fvoouEJG1IvKeiPSs7EIiMklEMkUkMzc3t8oC/TNJNGzYsPZR15EOHToE3m/evNm5QIwxxmFuSFCVjZTVCttrgPaq2hf4X+Cdyi6kqrNUNUNVM/wr1FbGzQnKX4Pq3r07EydOdDgaY4xxjhsS1E6gbdB2OrA7+ABVPaSqhb737wLxIlLrPuL+ee7cmKD8NajU1FSuvvpqZ4MxxhgHuSFBrQK6iEhHEUkAxgMLgw8QkVbim5NIRAbhjbvW032XlpYCkJKSUttL1Jnu3bsDsGHDBlQrViSNMSZ6OJ6gVLUM+BXwH+Bb4HVV/UZEbheR232HXQ2sF5G1wFPAeA3ht7e/BpWcnBxS7HWhZcuWNG/enIKCAp588snAulXGGBNtHE9Q4G22U9WuqtpJVR/27fu7qv7d9/5pVe2pqn1VdbCqrgilPDcnKIDevXsDMG3aNBYsWOBwNMYY4wxXJKhIGz58OABt27Y9w5HO8CcogPXr1zsYiTHGOCcqE5R//JMbn0HByQnqq6++cjASY4xxTlQmKP+ChW6bzdxv8ODBgfebN2+moKDAwWiMMcYZUZmgVq9eDbhzqiPw9uRLS0sLbK9bt87BaIwxxhlRl6BUlcLCQsC9TXwxMTH8+Mc/DmxnZWU5GI0xxjgj6hKUvwcfuG8282BDhgwBvLW8Q4cOORyNMcZEXtQlqOAJYt36DArgJz/5CeDtCn/XXXc5HI0xxkRe1CWo4uLiwHs3J6jOnTvTu3dvDh06xNKlS50OxxhjIi7qElR9qUEBjBs3DoD58+eflFiNMSYaRF2CKioqCrxv0KCBg5Gc2fjx4wGYO3cuL774osPRGGNMZEVdgvJ3LY+LiyMmxt3ffrdu3QJLwM+fP9/haIwxJrLc/Ru6DjRu3BiAJk2aOBxJ9Vx77bUAfPnllw5HYowxkRV1CcrfxOfGtaAq8+tf/xrwzn5hM5sbY6JJ1CWoffv2ARAfH+9wJNXTrl07mjXzrs342GOPORyNMcZETtQlqJUrVwKQl5fncCTVN2bMGADeffddhyMxxpjIiboE5Z+VIS4uzuFIqu/ee+8F4MCBA3zzzTcOR2OMMZERdQnKPw9fQkKCw5FUX4cOHTj//PMBeOeddxyOxhhjIiPqEtSRI0eA+pWgAB588EEAnn766cByIcYYczaLugRVH2tQACNGjGDAgAHs3buX++67z+lwjDGmzkVdgvLXoNw+i0RFIhKYNPaJJ55g2bJlDkdkjDF1K+oSlL95LDEx0eFIau66666jbdu2AFx++eVs3LjR4YiMMabuRF2C6t27NwCDBg1yOJKaExE+/vhjEhISKC4uplevXrz11ltOh2WMMXXCFQlKREaKSLaIbBKReyr5XETkKd/n60RkQG3L8s/F17p16xAidk6HDh347LPPSExMpKSkhKuvvppOnToxd+5cm/HcGHNWcXwwkIjEAn8DhgM7gVUislBVNwQdNgro4nudDzzr+1ql3NxcHn300VP2f/zxx4B3IcD6KiMjgy1btjBixAjWr1/P5s2bueWWW5g8eTK9e/emvLwcEaFp06Y0btyYRo0a0bBhQxo0aECzZs3o3r07cXEaTuIiAAAgAElEQVRxlJWV8fXXXxMbG4uIBF7gra116tQpMGfhrl27ArNwVBQfH0+fPn0C2+vWrTtp5eJgrVu3DvxxcPDgQTZv3hwor6LevXsHZvzYtGlTlSsLN2nShE6dOiEilJSU8PXXX1d57zp37hz4nnbv3s3evXur/J78te2afE8HDhxgy5YtVZZf3e8pNTWV8847D4CSkhLWr19f5TWD/53se7LvyS3fU1hWLFdVR1/ABcB/granA9MrHPMccH3QdjbQ+gzX1dO97rnnHj0bLF26VC+++GLt1avXab9fe9nLXvZy4JWpIeQHx2tQwLnAjqDtnZxaO6rsmHOBPcEHicgkYBJ4Z4qoKoMnJydz/fXXhxa1S1x66aVceumlAOTn55Odnc0777zDN998w4EDBygqKqKoqIiSkhLKyspo2rQpnTt3pqysLDABrXoTOsBJ7yvWNvbs2UNlavsXn78GFVxmsD59+gRm/DjTX3wdO3YEvH/xnW62jU6dOgVmtN+9e/dpa4W9evUKbH/99den/Z5atWoV+J7O9Fes/3v6/vvvT1srDP4r1r4n+57q2/eUkpLCjh07qjq1WtyQoE5t2/Fm3poeg6rOAmYBZGRkaGZmZujR1SPnnHMOF154IRdeeKHToRhjTKVN9zXhhk4SO4G2QdvpwO5aHGOMMeYs4oYEtQroIiIdRSQBGA8srHDMQuDnvt58g4ECVa28vckYY8xZwfEmPlUtE5FfAf8BYoEXVfUbEbnd9/nfgXeBy4FNQBEwwal4jTHGRIbjCQpAVd/Fm4SC9/096L0CUyIdlzHGGOdIVT2o6jsROYy3O7o5VTOg/qzYGFl2b6pm96Zydl+q1k1Vaz0gyhU1qDqSraoZTgfhRiKSafemcnZvqmb3pnJ2X6omIiF1pXZDJwljjDHmFJagjDHGuNLZnKBmOR2Ai9m9qZrdm6rZvamc3ZeqhXRvztpOEsYYY+q3s7kGZYwxph6zBGWMMcaVzsoEdaYFEKOFiLQVkQ9F5FsR+UZEfu3bnyYiH4jIRt/Xpk7H6hQRiRWRr0TkX75tuzeAiKSKyJsi8l/fz88Fdm+8ROQ3vv9P60XkNRFpEK33RkReFJEcEVkftK/KeyEi032/l7NF5LIzXf+sS1BBCyCOAnoA14tID2ejckwZ8FtV7Q4MBqb47sU9wFJV7QIs9W1Hq18D3wZt273xmgm8r6o/APrivUdRf29E5Fzgf4AMVe2Fd3q28UTvvZkDjKywr9J74fvdMx7o6TvnGd/v6yqddQkKGARsUtXNqloC/AMY43BMjlDVPaq6xvf+MN5fMufivR9zfYfNBa5yJkJniUg6cAXwQtDuqL83ItIYuBiYDaCqJap6ELs3fnFAkojEAQ3xrqwQlfdGVT8G9lfYXdW9GAP8Q1WLVXUL3rlVB53u+mdjgqpqccOoJiIdgP7AF0BL/2zwvq8tnIvMUX8FfgccD9pn9wbOA3KBl3zNny+ISDJ2b1DVXcDjwHa8C6YWqOpi7N4Eq+pe1Ph389mYoKq1uGE0EZEU4C3gTlWtfBnNKCMiVwI5qrra6VhcKA4YADyrqv2BI0RPk9Vp+Z6njAE6Am2AZBG50dmo6o0a/24+GxOULW4YRETi8SanV1T1bd/ufSLS2vd5ayDHqfgcdBEwWkS24m0GvlRE5mH3Brz/h3aq6he+7TfxJiy7NzAM2KKquapaCrwNXIjdm2BV3Ysa/24+GxNUdRZAjAriXW95NvCtqj4Z9NFC4Gbf+5uBf0Y6Nqep6nRVTVfVDnh/Rpap6o3YvUFV9wI7RKSbb9dQYAN2b8DbtDdYRBr6/n8Nxfts1+7NCVXdi4XAeBFJFJGOQBfgy9Nd6KycSUJELsf7fMG/AOLDDofkCBH5EfAJ8DUnnrP8Hu9zqNeBdnj/w12jqhUfdEYNEfEA01T1ShE5B7s3iEg/vJ1HEoDNeBcJjcHuDSLyIHAd3l6yXwG3ASlE4b0RkdcAD94lR/YBDwDvUMW9EJH/C9yK997dqarvnfb6Z2OCMsYYU/+djU18xhhjzgKWoIwxxriSJShjjDGuZAnKGGOMK1mCMsYY40qWoIwxxriSJShjjDGuZAnKGGOMK1mCMsYY40qWoIwxxriSJShjjDGuZAnKGGOMK9U4QYnIn0XkTt97j4jsPM2xT4rI7aEEaIwxJjrF1eRgEWkO/BzoXM1THgO+FJEXVbWkpsEZY4yJXjWtQd0CvKuqR6tzsG89+v8Co2tYjjHGmChX0wQ1ClhecaeI/F5E8kRkq4jcUOHjj4ArahmfMcaYKFXTBNUbyK6wrxXe1RTPxbu876ygpaLBuxxy31pHaIwxJirVNEGlAocr2X+fqhar6nLg38C1QZ8d9p1njDHGVFtNE9QBoFHFfap6JGh7G9AmaLsRcLAWsRljjIliNU1Q64CuFfY1FZHkoO12wO6g7e7A2lrEZowxJorVNEG9CwypZP+DIpIgIj8GrgTeCPpsCPBeLeMzxhgTpWo0Dgp4GcgSkaSgruZ78Tb97QaKgNtV9b8AItIa6AG8E6Z4q61Zs2baoUOHSBdrjDHGZ/Xq1Xmq2ry254uq1uwEkUeAHFX9azWOfQL4XlWfqWV8tZaRkaGZmZmRLtYYY4yPiKxW1Yzanl/TGhSq+vsaHPvbml7fGGOMAZss1hhjjEvVuAZV10RkK96xU+VAmapmiEgaMB/oAGwFrlXVA07FaIwxpu65LkH5XKKqeUHb9wBLVXWGiNzj2747kgEVFxfz/fffU1RURHFxMSUlJZSVlZGWlsbAgQMBKC0tZdmyZVVeo2/fvrRq1SpSIRtjTL3m1gRV0RjA43s/F+/8fhFLUDfffDOvvvoqZWVlp3w2fPhwFi9eDMDhw4cZOXJkldd54403uPrqq+ssTmOMOZu4MUEpsFhEFHhOVWcBLX0zo6Oqe0SkRSQDSk5Opry8nPPOO4/U1FQSEhJITEwkLi6O/v37B46Li4tjxIgRVV6nZcuWABQWFjJv3jwmT56MiNR5/MYYUx/VuJt5XRORNqq625eEPgCmAgtVNTXomAOq2rSScycBkwDatWs3cNu2bbWKYdOmTXz00UdMnDgRESE3N5eGDRuSnJx85pPPQFUZMGAAWVlZvP7661xzzTUhX9MYY9wo1G7mruvFp6q7fV9zgAXAIGCfb9Cvf/BvThXnzlLVDFXNaN68dmPDjhw5wk9/+lN+8Ytf8NxzzwHQvHnzsCQnABFh8uTJAPz+97+ntLQ0LNc1xpizjasSlIgki0gj/3tgBLAeWIh3KQ98X/9ZF+WrKhMnTmT9+vV069aNn/3sZ3VRDBMnTqRr165s2rSJF154oU7KMMaY+s5VCQpoCXwqImuBL4F/q+r7wAxguIhsBIb7tsPulVdeYf78+aSkpLBgwQIaN25cF8UQHx/PI488AsCDDz5IYWFhnZRjjDH1masSlKpuVtW+vldPVX3Ytz9fVYeqahff1/11Uf5HH30EwP3330/37t3rooiAsWPHcv7557Nv3z7+8pe/1GlZxhhTH7kqQTlty5YtAPTq1avOyxIR7rvvPgD+/e9/13l5xhhT37ixm7ljtm7dCkDHjh0jUl7//v2566676NSpU0TKM8aY+sQSVJA//vGPbNy4kUgt09GmTRseffTRiJRljDH1jSWoIDfccIPTIRhjjPGxZ1AO+/DDD1mwYAHl5eVOh2KMMa5iNSifzMxMMjMzueCCC+jbt2/Eyh07diwHDx4kPz+ftLS0iJVrjDFuZzUon0WLFnHHHXfwxhtvRLRc/1irgoKCiJZrjDFuZwnKx9/FPFI9+PyaNGkCwKFDhyJarjHGuJ0lKB+nE5TVoIwx5mSWoHycSlDWxGeMMZWzBIV3tdzdu3cTExNDenp6RMu2Jj5jjKmcJShg+/btqCpt27YlPj4+omVbE58xxlTOEhSQl5dH06ZNI968B97ZK3bv3s3EiRMjXrYxxriZjYMCLrjgAvbv309xcXHEy67tworGGHO2sxpUkMTERKdDMMYY42MJymGffvopP/nJT/jTn/7kdCjGGOMqlqCAIUOG0K1bNzZs2BDxsvPz8/nXv/7Fl19+GfGyjTHGzewZFPDtt9+Sm5tLampqxMu2XnzGGFM5V9agRCRWRL4SkX/5ttNE5AMR2ej72jRcZRUWFpKbm0tiYiKtWrUK12WrzT9Q18ZBGWPMyVyZoIBfA98Gbd8DLFXVLsBS33ZY+FfR7dChAzExkb8dVoMyxpjKuS5BiUg6cAXwQtDuMcBc3/u5wFXhKs+pKY78bKojY4ypnOsSFPBX4HfA8aB9LVV1D4Dva4vKThSRSSKSKSKZubm51SrMn6Aitcx7RcFTHamqIzEYY4wbuaqThIhcCeSo6moR8dT0fFWdBcwCyMjIqNZve38Tn1M1qISEBH7yk5+QlJREWVlZxKdaMsYYt3JVggIuAkaLyOVAA6CxiMwD9olIa1XdIyKtgZxwFThmzBiaNm3KJZdcEq5L1tjChQsdK9sYY9xK3Nqs5KtBTVPVK0XkMSBfVWeIyD1Amqr+7nTnZ2RkaGZmZiRCNcYYUwkRWa2qGbU9343PoCozAxguIhuB4b7ts8aBAwf4/vvvOXLkiNOhGGOMa4SliU9EWgIjgL5AKnAQWAt8oKp7a3NNVf0I+Mj3Ph8YGo5Ygx07doxXX32VtLQ0rroqbB0Da+zqq69m2bJlLF68mOHDhzsWhzHGuElINSgR6S4ibwIbgJuAeGCv7+tNwDci8qaI9Ag50jqQl5fHxIkTmTJliqNx2KKFxhhzqlBrUHOAx4AbVPWUtSpEJAHvGKbZwAUhlhV2/ia15ORkR+OwwbrGGHOqkBKUqp5/hs9LgDd8L9dxS4KywbrGGHOq+tJJok64JUFZE58xxpyqVgnKN5nrWBG5SkTigvZfE77Q6p7bEpTVoIwx5oTa1qBeBgYA/YBPRaSzb/8dYYkqQtySoGxGc2OMOVVtn0G1UdUbAERkLvCSiPwhbFFFSFFREeB8gho5ciTvv/++Y9MtGWOMG9VqJgkRWQFc4u+5JyKNgNeAQapa6USukVadmSRUleLiYsrLyx1PUsYYc7YJdSaJ2tag/g/QFO+YJ1T1sIiMAa6vbSBOEBEaNGjgdBjGGGMqUasEpaqfV7KvHJgXckRRKD8/nyeffJKkpCTuvfdep8MxxhhXCFs3c1+PvkwRyRKRf4jIPSIyyjf7uCvNnDmTCy+8kH/84x+OxnH06FEeeeQRnn32WUfjMMYYNwnnOKhZeHv3/R/gU+A84A/AxjCWEVYbN25k5cqVVHdxw7pivfiMMeZU4VwP6ijwN19T3zL/ThGRMJYRVm7pZp6SkoKIUFhYSHl5ObGxsY7GY4wxbhDOGtQTwC8r7lS3LjiFexJUTEwMjRo1AqwWZYwxfuFMUB8AvxWRhSIySUQGiYiru8i5JUGBTXdkjDEVhTNBLQAygSy8a0O9ChwWkQ1hLCOs3JigbLojY4zxCuczqBbANcFNer4BvH3CWEZY+RNUw4YNHY4EOnfuTHl5OcePH3c6FGOMcYVwJqh/AEPwrYIL3gG8wGfVvYCvSfBjINEX25uq+oCIpAHzgQ7AVuBaVT0QasBXXnkl3bp1o1WrVqFeKmQLFixwOgRjjHGVWk11VOmFRN4HBgKPAP9W1e9qcQ0BklW1UETi8XZX/zUwFtivqjNE5B6gqarefbprVWeqI2OMMXUn1KmOwvkM6g28z53GAJ+LyGERWSEiz1T3AupV6NuM973Ud825vv1zgavCF7a7uLjTozHGRFTYEpSqzlbVX6uqR1XTgJ7An4HdNbmOb62pLCAH+EBVvwBaquoeXzl78D7vquzcSb7ZLDKrM/h29erVbNiwwRVJ4Y9//CMNGzbk0UcfdToUY4xxhZCfQYnIDuA94F28CeUIgKpuB7YDi2pyPd9A334ikgosEJFeNTh3Ft4ZLcjIyDht1ikvLycjIyPw3unxxLGxsRw9etR68RljjE84alCDgC+Am4CtIvKBiPxGRLqGclFVPYi3w8VIYJ9/Tj/f15zQQj6xFlTDhg2JiQlnS2ft+Kc7sgRljDFeIf9mVtU9vua9cUBrvM165wLviMgmEXlKREaKSOKZriUizX01J0QkCRgG/BdYCNzsO+xm4J+hxu2mMVBgA3WNMaaicDTxNVbVQwCqWoZ3Hr5lwDQR6QBcAUwFegGPn+FyrYG5IhKLN3m+rqr/EpGVwOsiMhFvs+E1ocbttgRlNShjjDlZOMZB7RSROcDTFbuWq+pW4G++1xmp6jqgfyX784GhIUcaxG0JympQxhhzsnA8fLkAb3fwTBF5V0RGhOGadc6tCcpqUMYY4xVyDUpVvwHuEJHpwK3AMyJSCvwvMEdVi0Itoy5UJ0Ht2rWLr776ipycHHJzc8nPz6ekpITjx48HpiWqTRf19PR0fvOb35xUdvv27Xnsscdo27Ztzb8ZY4w5C4VtJonABb39tf3PnTKAl1R1WlgLqYYzzSRx6NAhsrOzadCgAb179z7ps8OHD/Pwww/zl7/8hZKSkjqJb8CAASxcuJBzzz23Tq5vjDFOC3UmiZATlIjcCDTxvRoHvW8C9ANaqWrEV+CrzVRHqsq8efO4++672bNnDwCXXnop6enptGjRgnPOOYfExERiY2OJiYkhJiYGEanRGKrjx4/z5JNP8v3339O6dWsWLlwYGI9ljDFnEzckqOPAQeAlYAdwqOJLVSO+5EZtEtTf//537rjjDgDOP/98nnrqKQYNGhT22PLz8xk3bhzLly+nQYMGvP3224waNYo333yT/Px8JkyYQEJCQtjLNcaYSHLDXHz9gXfwDtQ9D/hEVd9U1cWq+rkTyak6Fi9ezO23337SLOKvvfYaAA8//DArVqyok+QEcM4557B48WImTJjAsWPHePDBBwH45S9/ye23386BAyFP1G6MMfVeOAbqrlXVW4EewD5gmYgsEpFhIUdXhzIzM3nuuef44osvACgsLGTlypXExMRwxx131PnsEgkJCTz00EMAbNmyBbCefMYYEyyck8XmqerDQEfgFeAhEVkvIreFq4xwqtiLb/ny5ZSWlvLDH/6Qpk2bRiSG1q1bEx8fT05ODkePHrXBusYYEyQcM0lcxYkOEsGvLcCPgeeAF0ItJ9wqJqjFixcDMGJE5IZxxcTEkJ6ezpYtW9ixY4fVoIwxJkg4ZpL4A95OEgVBr3xgM97JXl3527Zigvrggw8AGD58eETjaN++PVu2bGH79u2kpqYC2DMoY4whPAN1+4UjkEgLTlA7d+7k22+/JSUlhcGDB0c0jnbt2gGwbds2WrZsCcC+ffsiGoMxxriR8+tMOCQ4QflrT5dccgnx8fERjcOfoLZv3x5IUAcPHoxoDMYY40YhJSgR+Z8zLaMhIoki8j+hlFMXOnToQJ8+fWjevLljzXvgbeIDbw3q7rvvpqSkhHvvvTficRhjjNuE2sTXCtgkIu8Cy4Fs4DDQCOgKeIBRwMshlhN2M2fOBLwzO/z0pz8FIttBwi+4BpWUlBTx8o0xxq1CSlCq+nsReRK4BZgI9AZSgQPAOrzLwP/et1yGK61du5a8vDzatm1L164hLQJcK8E1KGOMMSeEo5NEHt6FCM+0GKGrlJaWEhcXF2jeGzFiRI3m1AsX/+zlO3bsYPfu3YwbN46EhASWL18e8ViMMcZNwtHNvF5q27YteXl5XHDBBYAzz58AGjZsSPPmzcnNzeXIkSN8/vnnJCUloaqOJExjjHELV/XiE5G2IvKhiHwrIt+IyK99+9NE5AMR2ej7GvJUD0eOHKG8vJxVq1YhIgwdGtYFe2vE/xwqLy+PpKQkjh49SmFhoWPxGGOMG7gqQQFlwG9VtTswGJgiIj2Ae4ClqtoFWOrbrjVVDXQzLy4upk2bNjRr1iy0yEPgT1A7duywsVDGGOMTcoISkVbhCARAVfeo6hrf+8PAt8C5wBhgru+wucBVoZRz7NgxVJW4OG8LZ/PmzUO5XMiCO0pYgjLGGK9w1KC+C94QkbfDcE1EpAPepTy+AFqq6h7wJjGgRRXnTBKRTBHJzM3NrfLa/tpTgwYNAOcTVGWDdS1BGWOiXTgSVMUn+Z6QLyiSArwF3Kmqh6p7nqrOUtUMVc04XdLxJyj/ooBONu+B1aCMMaYy4ejFF9qSvBWISDze5PSKqvprY/tEpLWq7hGR1kBOKGX4E1RsrHcleqcTVHAN6qabbiIpKYmePXs6GpMxxjgtHAkqTkQu4URNquI2qrqsOhcSb7/q2cC3qvpk0EcLgZuBGb6v/wwl4FatWjF79mwWLVrEO++843iCCq5BXXPNNVxzzTWOxmOMMW4QjgSVA7wYtJ1fYVvxLgVfHRfhXTr+axHJ8u37Pd7E9LqITAS2AyH9Bk9LS+PWW2/lyy+/BJx/BtWsWTOSkpI4ePAghw4dCixcaIwx0SwcM0l0ON3nIhJbg2t9yqnPtPzCPlApLy8PcL6JT0Ro164d2dnZfPfdd5SWllJaWsrFF1/saFzGGOOkOhsHJSK9ReQxvDUeV8nOzuZvf/sbGzduBJxPUHDiOdSaNWu48MILufXWWx2OyBhjnBXWqY5EpDnwM7yTx3YC3sM747mrrFy5kl/96leBJdadbuKDEwnKP4OE9eIzxkS7cAzUjReRcSKyCNgCXAo8ijcx3Rzq9euCvxdfSUkJ4I4alL+jRE5ODgkJCRQWFlJUVORwVMYY45xwNPHtBX6Dt2ddW1Udo6qvqWoRYe6CXhPZ2dnMmTMH8M5c7vF4mDdvHgAHDhwA4OjRowDExcXh8Xh4+21vr/a8vDw8Hg+LFi0CYO/evXg8Ht5//33AOyWRx+NhyZIlAGzevBmPxxOYgTw7OxuPx8OKFSsAWL9+PR6Ph1WrVgGQlZWFx+MhK8vbD2TVqlW88sorgWunpqYC3poewPLly/F4PGzevBmAJUuW4PF42LFjBwDvv/8+Ho+HvXv3ArBo0SI8Hk/gGdvbb7+Nx+OhoKAAgPnz5+PxeAIJcN68eXg8HkpLSwGYM2cOHo8ncC+ff/55hg0bFth+5plnGDVqVGB75syZjB49OrD9+OOPM27cuMD2jBkzGD9+fGD7oYce4sYbbwxs33///UyYMCGwPX36dCZNmhTYnjZtGlOmTAls33nnndx5552B7SlTpjBt2rTA9qRJk5g+fXpge8KECdx///2B7RtvvJGHHnoosD1+/HhmzJgR2B43bhyPP35icv7Ro0cH1g8DGDVqFM8880xge9iwYTz//POBbY/HU+XPXlFRER6Ph/nz5wNQUFDg+M+ex+Nh/fr1AKxYsQKPx0N2djZgP3v2sxfaz16owpGgvga6A+cD/aQeTMEdXDNJTU2N+DLvlfHParFt2zbS0tIAON1sGMYYc7YT1dArOSLSHvi579UQmA+8ijd5FalqtXvyhUtGRoZmZmZW+tldd90V+Culc+fOgc4STtq8eTOdOnWibdu29OnTh3//+98sWLCAq64KadpBY4xxjIisVtWM2p4fll58qrpNVR/yzTZ+HZACLAE2hOP64eZ/BgXueP4EkJ6ejoiwa9cuWrTwTjVoHSWMMdEs7N3MVfVTVZ2Et5PEvcDicJcRqrKyssB7N/TgA++8gK1bt+b48eNMnjyZrVu3cssttzgdljHGOKbOxkGp6jFfZ4lRZz46smbNmhV4sOiWGhSc6GpeXFxM+/btSUxMdDgiY4xxTp0kKBH5uC6uG05umUUiWKdOnQBc8UzMGGOcVlc1qIvq6Lph409QbmniAwIzmH/66adcc801TJ061eGIjDHGOWGdSaK+GDt2LB999BHgrhpUr169AO94gpUrV9K1a1eHIzLGGOfU2TMoN9uwYUNgsK4bE9T3338PWC8+Y0x0i8oEFdzN3E1NfO3btyc5OZmcnBzi4uIoKCjg2LFjTodljDGOiPoE5aYaVExMDD169AAITHdktShjTLSqqwTl6umO3Jqg4EQzX1JSEmAJyhgTveoqQS2vo+uGrKysLDCLeVxcXGDJDbfwJyj/lIaWoIwx0apOEpSqXlLbc0XkRRHJEZH1QfvSROQDEdno+9q0ttevWHty29y2/gQVGxvLuHHjAhPHGmNMtHHjM6g5wMgK++4Blvrm+lvq266VmJgYfvaznwHua96DEwmqoKCAN954g4sucv2QMmOMqROuS1Cq+jGwv8LuMcBc3/u5QK2n+G7UqFFgOXU3JqjWrVuTmprK/v37A2vsGGNMNHJdgqpCS1XdA+D72qKyg0Rkkohkikjm6dZScuMsEn4iEqhFLVu2LLBQnDHGRJv6kqCqRVVnqWqGqmZUlXwOHDjA559/DrizBgUnmvluvPHGQG3PGGOiTX1JUPtEpDWA72tObS+UmZnJX//6V8D9CQoILK1tjDHRpr4kqIXAzb73NwP/rO2F3DqLRLDgruabN2+2pd+NMVHJdQlKRF4DVgLdRGSniEwEZgDDRWQjMNy3XStuHqTr55/VPCbG+8/z2WefORmOMcY4wnWzmavq9VV8NDQc168PCapZs2a0bNkyMEj3008/5aqrat1x0Rhj6iXX1aDqWn1o4oOTn0N9+umnDkZijDHOiOoE5dYaFJz8HGrdunUUFxc7HJExxkRW1CWowsLCwPv6kKAuu+wycnNzSUxMdDgiY4yJrKhLUJMnTwYgOTmZBg0aOBxN1fwJatu2bSQnJzscjTHGRF7UJShVBdz9/Amgf//+nHPOOXz77besWbPG6XCMMSbioi5B+ac5cnPzHkBiYiI33ngjAOPGjaNTp06Ul5c7HJUxxkROVCWonTt3ctNNNwHur0EBTJw4EYDt27ezefNmvv76a4cjMsaYyImqBPX555/z3XffAe6vQQH07t2bQYMGcfz4ccC6mxtjokvUJSi/+pCgAG677bbAe0tQxphoErUJqj408QFcd911JJe7DZcAACAASURBVCUlAfDhhx8GOnkYY8zZLmoSVElJCatXrw5st2rVysFoqq9x48Zce+21AOTk5LBt2zaHIzLGmMiImgS1bt06jh07hoggIowcWXFVeff6xS9+EXi/cOFCByMxxpjIiZoE5W/eU1UuvfRSWrdu7XBE1XfhhReSnp4OYIN2jTFRI2oSVP/+/QO/5H/2s585HE3NiAgPPvggANOmTbNFDI0xUSFqElTHjh3ZtWsXCQkJjB071ulwamzChAlceeWVHDx4kBtuuMHGRBljznpRk6D+8Y9/oKpceeWVpKamOh1OjYkIs2fPJi0tjU8++YRLL73UZjg3xpzVoiJBrV27lv/93/8F6l/zXrAWLVowe/ZswDtl0y9/+Uvrdm6MOWtFRYJ69tln2bp1K4mJiVxxxRVOhxOSq666itGjRwPw4osv0qFDB5YsWeJwVMYYE371KkGJyEgRyRaRTSJyT3XP+89//gPAj370I1cvsVFdr732Gt26dQO88/QNHz6c7t2789577wUmwzXGmPpO6ksTkYjEAt8Bw4GdwCrg/7N33uFRFWsD/00aIaQREgIECKF3AoTeFikiRaQpIAqocFG+i16vDUUR+72CiNcGiKAiiAKCIqiAIlUg9AAJCTWhhEBISG873x+TXRJIyKZsNmV+zzPPnjlnzsx7Jpvz7sy8877jpJQn8irv6ekpTS/x/fv3I6Vk1apV5k2v5R0pJWvXruWZZ54hKioq1zUfHx/S0tIwGo04OztTtWpVHBwczKlx48Y0btwYOzs7rl+/zpEjRwC1zpXzE6BXr15mpX7kyBFiYmLylMfb25vAwEBAbYrevn17vrK3a9fO7Mnj7NmznD59Os9yTk5O9O7d25zfuXMnqampeZYNCAigUaNGgJr+PHz4cL7t5/yhop9JP5N+ppJ7poSEBB544AH69+8PgBDigJQyKN+bC0JKWS4S0A34LUd+JjDzLuVlzmRvby8zMzNlRcNoNMrvv/9e9ujRQ3bq1Em6urrK259dJ5100qm00uzZs83vJyBYFuO970D5wQ/IuQEoCuiSs4AQYiowFcDFxYU+ffqYr02ePBl7e/tSELN0EUIwZswYxowZA4CUkqioKIKDg7l06RJXr14lNjaW1NRU0tPTSU9Px9fXl3r16iGl5Nq1a5w8edJsbGH6NB0HBQWZw82fPHmS2NjYO8oBVK9enVatWgHqF9++ffvylblFixbUqFEDUFOUFy5cyLOco6MjXbrc+hPv378/X8vFevXq4e/vD0BsbCwnTuQ5sAagU6dOuZ7p+vXreZbTz6SfST9T4Z4pMTGRfv365Vu2sJQnBSXyOJfrLSmlXAQsAggKCpIbN24sDbnKFEII6tWrR7169Wwtikaj0RSL8mQkEQXkfOvWBS7ZSBaNRqPRWJnypKD2A02EEAFCCCdgLKA9p2o0Gk0FpdxM8UkpM4UQ/wf8BtgDX0opj9tYLI1Go9FYiXKjoACklBuByrewpNFoNJWQcrMPqrAIIRKAMFvLUUbxBvSO3rzRfZM/um/yRvdL/jSTUroV9eZyNYIqJGGyOBvEKjBCiGDdN3mj+yZ/dN/kje6X/BFCBBfn/vJkJKHRaDSaSoRWUBqNRqMpk1RkBbXI1gKUYXTf5I/um/zRfZM3ul/yp1h9U2GNJDQajUZTvqnIIyiNRqPRlGO0gtJoNBpNmaRCKqiiBjasaAgh6gkh/hRCnBRCHBdCPJ193ksIsVkIEZ79Wd3WstoKIYS9EOKQEGJDdl73DSCE8BRCrBZChGZ/f7rpvlEIIf6V/f8UIoRYKYRwrqx9I4T4UghxVQgRkuNcvn0hhJiZ/V4OE0LcW1D9FU5BZQc2/AS4D2gJjBNCtLStVDYjE/i3lLIF0BWYnt0XLwFbpZRNgK3Z+crK08DJHHndN4oFwK9SyuZAO1QfVfq+EUL4ATOAIClla5TbtbFU3r5ZBgy67VyefZH97hkLtMq+59Ps93W+VDgFBXQGIqSUZ6SU6cB3wHAby2QTpJSXpZQHs48TUC8ZP1R/fJVd7CvgAdtIaFuEEHWBIcAXOU5X+r4RQrgDvYElAFLKdCllHLpvTDgAVYUQDoALKqpCpewbKeV2IPa20/n1xXDgOyllmpTyLBCBel/nS0VUUHkFNvSzkSxlBiFEA6A9sBfwlVJeBqXEgJq2k8ymfAi8ABhznNN9Aw2BGGBp9vTnF0KIaui+QUp5EZgLXAAuA/FSyt/RfZOT/Pqi0O/miqigCgxsWNkQQrgCa4BnpJQ3bS1PWUAIMRS4KqU8YGtZyiAOQAfgMylleyCJyjNldVey11OGAwFAHaCaEGKCbaUqNxT63VwRFZQObJgDIYQjSjl9K6Vcm306WghRO/t6beCqreSzIT2A+4UQ51DTwPcIIZaj+wbU/1CUlHJvdn41SmHpvoH+wFkpZYyUMgNYC3RH901O8uuLQr+bK6KC0oENsxFCCNQ6wkkp5Qc5Lv0ETMw+ngisL23ZbI2UcqaUsq6UsgHqO/KHlHICum+QUl4BIoUQzbJP9QNOoPsG1NReVyGES/b/Vz/U2q7um1vk1xc/AWOFEFWEEAFAE2Df3SqqkJ4khBCDUesLpsCGb9tYJJsghOgJ7ACOcWud5WXUOtT3QH3UP9wYKeXtC52VBiGEAXhOSjlUCFED3TcIIQJRxiNOwBlgMuoHre4bIeYAD6GsZA8BTwCuVMK+EUKsBAyokCPRwGxgHfn0hRDiFeAxVN89I6XcdNf6K6KC0mg0Gk35pyJO8Wk0Go2mAqAVlEaj0WjKJFpBaTQajaZMohWURqPRaMokWkFpNBqNpkyiFZRGo9FoyiRaQWk0Go2mTKIVlEaj0WjKJFpBaTQajaZMohWURqPRaMokWkFpNBqNpkyiFZRGo9FoyiSFVlBCiHeFEM9YUG6tEOL2WPUajUaj0VhEobyZCyF8gMNAYyllSgFlO6MicnYsnogajUajqYwUdgQ1CdhYkHICkFLuA9yFEEFFEUyj0Wg0lZvCKqj7gL9ynhBCDBdCHBZC3BRCnL5tWm8bMKSYMmo0Go2mEuJQyPJtgDBTJnsa72tgNLAVqA245Sh/EuhZTBk1Go1GUwkprILyBBJy5B9HhVTfnJ2/eFv5hOx7NBqNRqMpFIWd4rtB7hFSPeD0Xcq7AXGFFUqj0Wg0msIqqKNA0xz5SKDRXcq3AI4UViiNRqPRaAqroDYCfXLklwCThRD9hBB2Qgg/IUTzHNf7AJuKK6RGo9FoKh+FXYP6GjgshKgqpUyRUu4TQkwG5gMBQDQwHQgVQnQCkrLNzUsdb29v2aBBA1s0rdFoNBrgwIED16SUPkW9v1AbdQGEEO8AV6WUHxZQbg2wREq5sajCFYegoCAZHBxsi6Y1Go1GAwghDkgpi7wXtrAjKKSUL1tYblThxdFoNBqNRlGunMUKIQYJIcKEEBFCiJdsLY9Go9ForEe5UVBCCHvgE5Q3i5bAOCFES9tKpdFoNBprUegpPhvSGYiQUp4BEEJ8BwwHTuRV+Mb543zzaAMEIIGq7ccw+l/vl5qwGo1Goyke5UlB+aH2XZmIArrkLCCEmApMBehY245HGt4wX0uPXcjOb7zo+cjMUhBVo9FoKj5SSnMyGo0YjUbs7e1xcCgZ1VKeFJTI41wuE0Qp5SJgEUDDmq7yywv+SMAz9QKjmkLr4+8Ssactjbtp/7WayoeUkszMTDIzM8nKyiIrK4vMzEwyMjJyfZrS7fmsrCzzS8h0v6mOnOdMx6ayeeVvT6YX3N1kN33mPDZ95lVfXi/P29vLq1xB1/K7nvMZbpf3drktTXm1aYncOT9vf+a7HVtaLmcbt/P6668ze/bsEvnOlicFFYVyrWSiLnApv8Je9Zvz2JfKzPxA8D7Wvm9gZAtHElY/zFXfHdRs2Ma60mo02WRlZZGSkmJxSk1NvePTlNLS0khLS8t1nJaWRnp6Ounp6ebjjIwM8zmTgrmbAtBoioMQavxgb2+PnV3JmTaUJwW1H2gihAhAOaUdC4y35MaOQZ1ZYDeEuhc30dnPnhMf9cN1zglcPLytKa+mnCClJCUlhaSkJBITE0lOTiYpKcmccuYTExNJTEw0H+f8TE5OzjOlp6fb+hHNmKZf7O3tsbe3x9HREQcHhzs+TcmUN5U3vYDs7OxyTeWYXlBCCKSU5rybmxvOzs7Y2dmRmJhIfHw8cOdIyNHRkZYtW5rvO3DgABkZGXmOiho2bEhAQAAA0dHRHDhwIFedOdOoUaNwcXHBzs6OTZs2ceHChTxHcM2aNePBBx/Ezs6OuLg43n777XxHgi+88AKBgYEIIfjuu+9Yv359nn3t7e3N4sWLEUIghGDChAkkJCTkWXbixImMHz8eIQQ7d+7kjTfeyPdvuHHjRqpXr44Qgqeffpq9e/fmWa5fv3589NFH2Nvbc+nSJe6555586/z222/p168fdnZ2vPPOO3z4Yd7bXOvVq0dERIT5O+Dj40NsbKz5b/nKK6/w6quv5ttOYSk3CkpKmSmE+D/gN8Ae5UX9uKX3z13wCclXz3Nh6UBaeqaxY9lL9Hr6C6vJq7EuGRkZZmWRkJBg/swv3bx5M89kurewG9YLS9WqVc3JxcUlV96UnJ2d88w7OzubU5UqVcwpZ97Z2RlHR0ecnJxwdHSkSpUqODo6ms85ODgQHx/PyZMnzc+d8/kTExOZPXs2Li4uALz66qvs2bMn16jOlAYOHMiyZcsAOH/+PHfz2LJp0yYGDVIh4l555RXeeeedPMvVrVuXn376yZyvWbMmMTExeZYdMmQIs2bNAuDHH3/kiy/y/z/esmULvr6+AGzdupWIiIg8y3Xq1Ilp06YBEBUVxYsvvphvnX369GHw4MEAhIeHs3Xr1lwK3JT8/Px44IEHzPe1adOGuLg4s5LPqfD79OnDwIEDAfVd2bVrV64fA6bydnZ2dO/eHQ8PDwBGjBhBo0aNsLe3NytCU7n27dvTsmVLc3/+85//zFVnzrJBQUHmfho+fDje3t7mMkII8z3u7u44OTmZn+k///kPaWlp5usdO5ZsAPVCe5IoL+TnSWLbu6MxpG1me3ITev9Xe5qwFVlZWcTGxnL16lViY2PN6caNG9y4cYO4uDji4uKIj483J9MLNSEhgbS0tBKVx9nZmWrVquHq6kq1atWoVq0aLi4uuY5zXjOVvf2ci4uL+T6TMqpSpYp5ZFBcpJQkJSXh6upqPrdw4UIiIyOJiYkhJiaGa9eucf36dWJjY3n22Wd5/vnnAVi3bh0jRozIt+6LFy9Sp04dAIYNG8aGDRvyLDdkyBDztcuXLxMQEGBWiDkVZJUqVfj444/p00e57/z6669ZuXKlWXGaRmiOjo54eXkxb948cxuvv/46KSkpuUZ8ps9evXrRo0cPAM6ePctvv/2Wp4Kwt7dn2LBhVK1aFYCDBw9y48aNXKNC07Gnpyf169cH1HczOjo612gyZ/umF7emYIrrSaLSKag9y9+mW8R/OXitCh0+vmoDySo+WVlZXLx4kbNnz3Lu3DnOnz9PVFQUFy9eJCoqiujoaGJiYoq1JmJvb4+bm5tZSbi6uubKu7u74+bmZk4eHh7mc6ZjU97V1RV7e/sS7IHic/LkSbZv305kZCQXLlwgMjLS3Idubm5ER0ebyzZo0IDz58/nWc+zzz5rfvHv37+fGTNm5OqLnH02bdo0PD1V+Lbg4GBu3LiRazRnSq6uruZf8BrN3Sh1V0flnTU7TtKtNjR0TUUajYgSXNCrbGRmZhIeHs6RI0cICQkhNDSU0NBQwsPDLVp38fLywsfHhxo1auDl5UWNGjXw9PSkevXqVK9eHQ8PDzw9PXF3d79DqTg7O5e7X7FGo5FTp07lUtZRUVFERkYSGRnJ7NmzGTlyJACbN2/m6aefzrMeBwcHMjIycHR0BOCpp54iJSUFHx8fatasibe3N97e3uY+NdGpUyf27NljkaxBQUV+p2g0JUalU1DeDVpx7cZ6vF3suBQWTJ0WnW0tUrkgKyuL48ePExwczP79+wkODiYkJITU1NQ8y9euXZsGDRoQEBBAgwYNqFu3Ln5+fvj5+VG7dm18fHzML9iKQnJyMufPnzePHM+ePYuDgwPvvvsuoKbn2rRpQ2ZmZp73h4eHm487duzIY489Rv369alXrx716tUz96Gbm1su5fzCCy9Y98E0GhtR6RRUHT8/joUa6Rtgx8VDm7WCyof09HT27t3L9u3b2bFjB7t3787TAsnf35927drRpk0bWrRoQYsWLWjatGmuNZKKQlZWFlFRUZw7d47mzZubF5U/+ugj3nnnnVzTbiZ8fHzMCsq0fiKlpG7dumaFY1JADRs2NN/Xo0cP8zqLRlNZqXQKqnbt2hy7mkXfAAeSzuy3tThlijNnzvDLL7/w+++/8+eff5KUlJTreoMGDejcuTOdOnUiKCiIwMBA85pFRSCneXRaWhrz5s3j7Nmz5nThwgXz6Gf58uU8/PDDgFI8pkX1+vXrExAQYB45BgQE5Kr3jz/+sM3DaTTWJDUebpyHuPPg3RR8mpVItZVOQdWpU4dV0Wpx3vHGKRtLY3tOnTrF6tWrWb16NYcOHcp1rUWLFvTt25fevXvTq1cvs4VXeSY2NpbQ0FBOnz7N6dOnOXv2LOfPn+fChQv4+vqa12gcHR2ZM2fOHWtppqlLkzk2wLhx47j//vupU6dOmTO20GhKBCkhKQauhUPsaYg9CzfOZn+eg9S4W2X7zoI+z5dIs5VOQakRlFJQPsbKacV348YNVq1axbJly3Jt8nNzc+O+++5j0KBBDBgwgLp169pQyqIhpeTSpUuEh4eb06RJk8z7Qd577z3efz9vp8E3b940H9vZ2TFnzhzc3d3NIyJ/f3+zyXJOvLy88PLyss4DaTSlidGoRkFXT8K1MIjJTtcjIO1m/vc5VAXP+lDdX6USotIpqOrVqxMep37lNnBNJyM1GUdnlwLuqhgcPnyYefPm8cMPP5j3Ebm5uTFixAhGjx7NgAEDcHZ2trGUBSOlJCEhAXd3dwASExOZPHkyp06dIiIiguTk5FzlW7VqZVZQrVu3pmPHjjRq1IhGjRrRsGFDGjRoQP369e9QyC+9pEOOaSowaYkQfRyij8GVY+r46klIT8y7vLMH1GgCNRqBV0Oo3gCqB6hP15pgBavaSrcPCiAhIYHY1+vj72YkfMA3NOlxfylLV3pIKdmyZQvvv/8+mzdvBpQ7mn79+jFp0iRGjBiRa7qqLGE0Gjl79izHjx/n+PHjnDx5ktDQUMLCwmjUqBEHDx40l3N1dSUlJQVQLmaaNm1KkyZNaNy4McOHD6dNG+17UVOJSbwKl4/ClSNKGV0+CrFnuM3ftsLVF2q2AJ8W4NMUfJorxVTNu9BKSO+DKgJubm6cMHrhzzViQrZVWAV1/PhxZsyYYV6Yr1atGlOmTOHpp5++q3saW5CUlMTBgwdp0qQJtWrVAuDll1/mP//5T57lY2Njzcd2dnasWrWKWrVq0aRJkwpluKHRFAop1RTd5aNw5ShcPqKOE6/cWdbOEWo2B982UKs1+LYG31ZKEZURKqWCAkhxCwCukR51qMCy5Y24uDhef/11Pv74Y7KysvDy8uK5555j2rRpVK9e3dbiIaUkIiKCnTt3snv3bvbt20dISAhGo5ElS5bw2GOPAcpIw8/Pj1atWtGqVSuzGXuzZs3w9s79TzRs2DBbPIpGYzukhJsX4eJBuHQILh2ES4dzGyyYcHKDWm2gdluo1VYd+zQHB6c7y5YhKqWC+vjjjzm+LQTDPeCScM7W4pQo+/fvZ8SIEVy8eBE7Ozueeuop3njjjVweBUqb9PR0s4NJo9FIw4YN73DNY29vT2BgYC4jhEcffZSJEyeWqqwaTZklLREuHoCo/UopXQyGxDv33lHNRykhkzKq3U6tFZVDrzmVUkHdvHmTbSdj4B5X6jjk8WujnPLNN98wZcoU0tLS6Nq1K5999hmBgYGlLsf169fZsWMHO3bsYPv27YSHh3Pt2jUcHByws7PD39+flJQUevbsSffu3enatSvt27e/Yy2svLky0mhKDNNU3YW9EPk3RO6DqydA3ua/0tkT/DpAnQ5Qp71K7nWsYrBgCyqlgqpduzbh142kZkrquhq5GXMRdx8/W4tVZDIzM3nppZfMTkGnTZvGggULcrnFtzbnzp3j008/ZcuWLXfsp7K3tyciIoLmzZsDsH79ejw8PLQC0mhMGI0QcxLO71bpwh5IuJy7jJ2DGg3V7aSSX0dlTVeB/48qrYLKkhB6HQJ94fz+TbQZ/IStxSoSUkqefPJJvvjiCxwcHPjf//5njmtjTaKjo7ly5Qrt2rUDlGWkaX9RlSpV6NatG7169aJXr15069Ytl+sjbcSgqfSYFNLZHXBuB5zfBSk3cpepWh3qdbmV6rQHp7JpcWstKq2CAjh5XRDoCzdCd0E5VVCffvopX3zxBc7OzmzatAmDwWC1tpKTk1m3bh1fffUVW7ZsoXPnzmbPC61bt+a1114zx+rJa0OrRlOpibsAp/+Es3/Bmb8g+Vru6+5+4N8D/LtB/e7KZVA5XDcqSSq1gjoancW4lvbI6BAbS1Q0tm3bZg7JsGTJEqspp0OHDvHpp5/y3XffkZioNvE5Ojri7e1NZmYmDg4OCCGYM2eOVdrXaMolWRlqqi78dwjfDDGhua+71YGAXtCgFzToqTa8VuDpuqJQKRWUt7c3Dg4OHLyYClTDM+2irUUqNOfOnWP06NFkZWXxwgsvMH78eKu0s3r1asaMGWPOd+3alUcffZQHH3zQppaBGk2ZJD0JIrZC6C9w6tfcJt9V3CGgNzQ0qFSjsVZIBVApFZSdnR0zZsygmjEBWEWDqkkYszKxsy8f3ZGRkcEDDzzA9evXue+++3jnnXdKrO7ExERCQkLo2rUrAIMGDaJ+/fqMGDGCadOmmQ0dNBpNNqk34dRvcHI9hG+BzJRb17ybQtNB0GQg1O8K9hUrBpq1KR9vZCtgsni79Nz31HGVnA7+nUZdBttYKstYunQpR44coWHDhqxYsaJEPGjHx8ezYMECFixYAMCFCxeoVq0arq6unDlzRnvp1mhyknpTjZCO/wgRWyArh9d7v47QfCi0GAbeTWwnYwWg0iooE+eMvtThCpf+/rFcKKjU1FTefPNNAN59991iW8TdvHmTjz76iHnz5hEXp6YjunXrxpUrV2jUqBGAVk4aDaiNsialFL4ZstKyLwhl3NDifmgxFDzKXxSAskqlVVBRUVGcOHGCdJfGwBW1Ea4csGjRIqKiomjbti2jR48ucj1ZWVksWrSIWbNmmf3aGQwGXn/9dXr37q33KGk0AJlpysjh2Go1jWeevstWSq1GKMXk5mtTMSsqlVZBffnll8yePZs5U+9naG2oY4yytUgFkpSUZF5vevPNN7ErhgmqlJLPPvuM2NhYevbsyRtvvEHfvn1LSlSNpvwiJUTuhSPfqdFSTkOHel2g1UhoORzca9tOxkpCpVVQJlPz82keJGdIGrlnEhsVgVfdxjaWLH8++eQToqOj6dSpU5GcoyYlJWE0GnFzc8PBwYGFCxdy6dIlRo4cqUdMGk3MKTj2PRz9XrkZMuHbBto+qEZLnvVsJ18lpNIrqEvRMZzydCXQM4nTf32H18OzbCxZ3ty8edMceuKtt94qtEI5ePAg48aNo0uXLnz99deAWmvSaCo1KXEQsgYOLVfewE241YE2o6HdWBWCQmMTKr2Cunz5MnEdmwKHSAr9AyibCup///ufeTpuwIABFt9nNBqZP38+M2fOJCMjA0dHR+Lj4/Hw8LCitBpNGUZKtYE2+Es4+TNkpqrzVdyh5f3Q9iG1vmSnjYNsjcUKSgjhCwwE2gGeQBxwBNgspcwjGlbZxjyCunQJl2Yj4PQhPBLCbCxV3kgpWbZsGQCzZs2yePSUlpbGxIkTWbVqFQDTp0/n/fff126INJWTtAQ4ugr2L1GewU0E9IH2jygLPEf9v1GWKFBBCSFaAG8CfYEDwEngCuAGPAJ8KIT4E3hNSnki34rKGDVr1kQIQUxMDPV7jIHTH9DUJYGM1GQcncuWQ8YDBw4QERGBr68v/fv3t+ie+Ph4HnjgAbZt24abmxvLly/n/vsrZuRgjSZfTAYPB79RBg8ZSep8tZrQcaJSTNX9bSujJl8sGUEtA94HHpZSpt1+UQjhBAwHlgDlZlHDwcEBX19frly5QqaTO2dv2hPgnsXJXetp0W+crcXLxcqVKwF48MEHLd6T9Pbbb7Nt2zZq1arFpk2bbBIXSqOxGUnX4PAKOPg1XA+/dd6/B3R6HJoPK/PRZDUWKCgpZZcCrqcDP2SncsWuXbuoXr06np6e7LLzI4ALXD3wc5lSUEaj0TxFN26c5XLNmTOHmJgYZs+eTYMGDawknUZThjAalafwA0shdCMYM9R5V19oN06NlrzLrpWu5k4qrZEEQMOGDc3HRr9OEH8BxysH73JH6bNjxw4uXryIv7+/2T9efqSnp5uj1latWpWlS5eWkpQajQ1JiYMjK2H/F3A9Qp0TdsoHXoeJyg9eOfGzqcmNRX81IUQP4H4p5Yt5XHsPWCel/LukhcvRxuvAFCAm+9TLUsqNJdlG7c4PwOY11LcrW/Yepum9sWPH3tU4QkrJtGnTuH79OsuXL8fNza20RNRobMPlI8rg4dgPkJGszrn7QcdJEPgweJTfKNkahaU/K14GPs3n2jbgFaDwO0cLx3wp5dySrHDt2rV8/vnnjBgxgn9MnUL8BqjrKrkcFkztZkEl2VSRyMjIYPXq1UDB03vz589n6dKlVK1alTNnzpgj3Wo0FYqMVDixTo2WovbfOh/QGzpNgWaD9WipAmHpXzIQ+DWfa1uAL0tGnNLlypUrbN68mQYNGmBn70B4igdBVeI5u31VmVBQmzdv5vr167Ro0YK2VbhAGAAAIABJREFUbdvmW27Lli08//zzAHz11VdaOWkqHrFnIHip2lCbonxHUsUDAsdD0GPg09S28mmsgqUKyh1wAlLyuOaIMjm3Nv8nhHgUCAb+LaW8cXsBIcRUYCpA/fr1C6ywTp06gNqsC5BYIxCy/kKcWI8yXLQt3333HaBGT/lN72VlZTFjxgyMRiOvvvpqruCCGk25xmiE03/AvoXKezhSna/dDoIeV54enKrZVESNdbFUQYWiNumuz+PawOzrxUIIsQWolcelV4DPUHuxZPbnPOCx2wtKKRcBiwCCgoJkQW3m9CYB0HzsG2R83ZtObldsPs2XkpLCunXrgLtP73399decPHmSgIAAZs0qm14wNJpCkZaoTMT3Lbxl9GBfBVqPgk5PgF8HHYm2kmCpgpoPLBRC2KMMIoxCCDvgAeAT4NniCiKltGgHqhBiMbChuO1Bbm8SALWaBLInsRbdPKIJWzGT2nM2l0QzRWLXrl0kJCQQGBhI48Z5m8ampqYye/ZsQHk3d3LS+zo05Zi4SKWUDnwNafHqnLufUkodJkK1GraVT1PqWKSgpJQrhBC1gK+AKkKIa4A3kArMllKutKKMCCFqSykvZ2dHACElUW/t2rWxs7PjypUrpKen4+TkRNU+T8Phl2mZso/0lEScqrqWRFOF5q+//gLgnnvuybdMZmYm48aN46+//irUHimNpkwRfQJ2zldOW2WWOlevC3R9Um2o1UYPlRYhZYEzYbcKC+GO8hZRA7gO7JFS3rSSbDnb/QZlqCGBc8A/ciisPAkKCpLBwcEF1l2/fn0iIyM5ffo0DRs2RBqNRPzbhyYemeyu8wTdp84riUcoNH369GH79u2sX7++QBdFRqOxWLGhNBqbEBUMOz6AsF9UXthDqweg63So29G2smlKBCHEASllkddKCvXTJFsZ/VbUxoqKlPIRa9U9atQoEhISzC94YWfH5XrDaHLzR6qdWIFa7ipdUlNT2bt3L0IIevbsmWcZKaXZcEIrJ025QUo486dSTOd2qHMOztDhUej+T/As2LhJU3mwdKPuPJSl3nYp5XLrilS6zJ8//45zHSb9h/j3f6SdZzJh29fQrPeoUpVp7969pKWl0bZtW7y8vO64fvPmTbp3785zzz3HxIkTdbBBTdnHaITQDbDzA7h0SJ2r4q784nV9Clxr2lY+TZnE0p/ebYDnsP5m3DKBq5cvh2VzAKJ/fqvU2zetP/Xp0yfP6xs3buT48eMsWbJEKydN2SYrAw6vhE+7wvePKOXk4g39XoN/hUD/17Vy0uSLpVN8HwCzgVetKItNSE1N5fTp02RmZuba4Fpv5BzY+BCdnE5z/tCf+LfvW2oyFaSgfvzxRwBGjhxZajJpNIUiK0OZim+fC/EX1DmPemoar/0j4FS2QtpoyiaFMpIoT1hqJLF161b69+9P7969zYrBxK5/t6SH20WOxrnQ6v3z2Dta34w7PT0dT09PUlJSiI6OpmbN3L8uU1NT8fHxITExkbNnz2pP5ZqyRVamCgr4138g7rw6V6MJ9HoW2owBe0fbyqcpVYprJFHpV9dNL/hz587dca3lvzdwJUnQ1jOZHXPHl4o8wcHBpKSk0KJFizuUE8Aff/xBYmIigYGBWjlpyg5SQugv8Fk3WP+UUk41msCoJTB9r3JJpJWTppAUqKCEEDOEEFUKKFNFCDGj5MQqPerVq4cQgqioKDIyMnJdq16nIZGBzwHQNel3Tu8tUQfqeWLp9N6IESOsLotGYxFRwbB0MHw3Hq6dguoBMGKhUkxtRoOdZUE2NZrbsWQEVQuIEEIsFEKMF0J0FEI0zf4cJ4RYCIQDZWqlMywsjGXLlgHKK7jBYGD5cmWAmJycjMFgYNWqVTg5OVGrVi2MRiNLliwB4Nq1axgMBn7++Wc6PTyLddF1GLQ8mS3vjiczPZXIyEgMBgNbtmwB4MyZMxgMBrNyCQsLw2AwsHv3bgBCQkIwGAzs36+8Lx8+fBiDwcDhw4cB2L9/PwaDgZCQEHMdf/31F2FhYeZjg8FAeHg469crb1M///wzkZGRAPz6668YDAauXLlivmYwGLh27RqgvLYbDAbi49Xu/FWrVmEwGEhOViEKli9fjsFgMCvoZcuWYTAYzH25ePHiXKHmP/30U+677z5zfsGCBbn2as2dO5dRo25ZPr733nuMHTvWnH/zzTeZMGGCOf/aa68xefJkc37mzJlMnTrVnH/uueeYPn26Of/MM8/wzDPPmPPTp0/nueeeM+enTp3KzJkzzfnJkyfz2muvmfMTJkzgzTffNOfHjh3Le++9Z86PGjWKuXNvOc6///77WbBggTl/33338emnt5z79+/fn8WLF5vzBoPBou8eQHx8PAaDgbVr1wK5v3ugHBobDAZ+/VX5arbmdw9g9+7dGAyGO757Z86cAZRjYoPBoL57Sdf59bVhGHp25cqJneBSg59dJ2BY68E1v/5gZ6+/e5X8u1dcClRQUsqXgfYoJfQ4sAnlyWEjyh9eKNBeSlluHcGZHMtevXo1z+stpy8nLQv8XTPYOWeg1eTIzMxk165dAHh6et5x3Wg08uGHHzJs2DCqVdNOMjU25Nga+LgjnPlD+cXr/A+YcQiaDdJ+8jQlRqU3kgD1q+bbb79l6dKlTJo0Kc8yh9Z8SJsjr+FgJ9jm1B/Dy2tKUFrF/v376dy5M40bNyY8PLzE69dois3NS7B26q1NtgF9YOh8qNHItnJpyiTaSKIEuJuhhIn2o55hb201FWBI38KO/00rcTkKWn/SaGzKqd/h855KOVXzgZFfwKPrtXLSWA2toIB//OMfHD9+nBdeeOGu5Xo8uYC/XAYD0D1mBXuXley2sD/++APIW0GFhITwxBNPsHXr1hJtU6MpkKwM+O0VWDEGkq9Do3vgyd3QdoyeztNYFa2gUJZ8LVu2xMWl4M2DfV5YyTbZBXs7QWDEAnZ9/kyB91hCYmIif/zxB0IIBg68c51rzZo1LFmyxLzAqdGUCmmJsOIh2POxcuba/3V4eI32/qApFSxSUEIIHcshB31m/8q29NZUcRD0uLKUbW8NRxqNxapz8+bNpKWl0bVrV3x9fe+4brKMGTRoULHa0WgsJukafDUMTm9V7okmb4Se/wLtnFhTSlj6TVtoVSlsjJSSKVOmMHDgQDIzMwssL+zsMLyzi23O92KUEkPmNna81InM9NQiy/DTTz8B5Bta48iRIwAEBgYWuQ2NxmJunIMlA+HSQfD0h8d/h/pdbS2VppJhqYKq0BPNQgg2bNjA5s2bzdF1LcHw0vfsrf8UqZmS3i4RHHuhEZdPHSx0+1lZWWzYoIIE56WgoqOjiY6Oxs3NTXuP0Fif+Ivw5X0Qexp828Djm7UhhMYmWKqg7IUQfYUQ9+SXrCplKWCJJV9edHv8PcK7f8DVZGjvmYjTkr7s+2ZOoerYs2cP165do1GjRrRo0eKO66bRU9u2bXXsJ411SY2Hb8dAwiWo1xUm/wJud045azSlgaVvuyrAkrukL6wiXSlSVAUF0GbwE4gndxMc50GNqtD59Af89WJnEmOjLbo/5/ReXuEzTAoqp7d1jabEycqA7yfC1ePKj964leDsYWupNJUYSxVUkpSyoZQyIJ/U0KpSlgImBXX+/Pki3e8T0IoO886wrcoA0rMkfaqGEfdOM/Z/W3A8qYLWn3x8fOjevTtdu+o1AI2VkBJ+fkZFu63mAw//AC53BsvUaEoTPV+Ujb+/P1C0EZQJO3sHDDNXc+aeLzgZV4W6rpJO4e+z519N812bCgsLIywsjOrVq9OjR488y0yaNIldu3bxyCOPFFk2jeau7PkEDi8Hh6owfhV4BdhaIo1GG0mYKO4IKifN+z5Ik/9eYJvzvSSmS7p5ROO+zMC2OfeRHH8tV1mTY8bBgwfj6KjDEWhswNWTsDV73XTkIvDraFt5NJpsLFJQUko3awtia5o0acLAgQPp3r17idTn4OSM4aXviZ+wmb/jfajmJDDI3cS/1Zg/5k/l2NHDpKWlmaf3hg8fnmc9sbGxnDhxwiLzd42m0GRlwI//gKx06PAotMx7mlmjsQUWOYsVQnQE0qSUIdl5H+BDoDWwB3hOSploTUELS2GcxZYGR9Z/gtOfc2jhmQbAiZgs3tqRwaqQdOwdHLl27Rru7u533Lds2TImT57M2LFjWblyZWmLrano/PmOin7rWV+5L6pS4X+LakqR0nIW+yEqLpSJL4CmwCKUkvpvUQWoLLQbPp1m8y6xy2cC0WnOtPSxZ8VIZ45Oq8b7j3bGvVrVPO8zWfC1bt26NMXVVAYuHoDtcwEBD3ymlZOmzGGpgmoB7AAQQngC9wEPSyk/AcYBw6wjXumSkJDAsWPHuH79ulXqt7N3oMf0T/B9MxKGLUC616VVTXuernsMPmqvFqrTEnLdo03MNVYhKwN+nAYyC7o+BQ162loijeYOLFVQDkB69nFX4IqU8hSAlDISuDO6XjnkiSeeoG3btuYIklbDwQk6TkLMOATDPlJ7TuIj4beX4YNW8OtMuH4aKaVWUBrrcGSlCs/u1Qj6laxXfo2mpLBUQR0HxmQfjwW2mC4IIfyA+BKWq/hcC4dD36rjrAxYOgSOZHsCT09W+ZDsoIOp8bB0CEMbqfW4qFNH1PWwTep6QrTKh2c/dnyUyp/+U+Vjz6r8uZ232l46BC7sVfnoEyp/8YDKXz6q8jGh0HEiPPA51GwBtdpBWjz8/Sn8rwPpn/elh/dN7m/tQd0t/1DtgGp36RAlByi5lg5RcoKSe+kQSMoeCZ74SeVTs/9MIWtUPl2F3ebIKpXPUmG3OfStyps4sAy+yrF4vm8xLL8VVpu/P4MVt8Jqs+sjWHUrrDY7PoAfboXV5q//wpopt/J/vA3rnrqV3/I6/DTjVv63V+CXf9/Kb3pJJRO//FuVMfHTDFWHiXVPqTZMrJmiZDDxw2Qlo4lVE9QzmFgxVj2jieWjVB+Y+Op+1Ucmlg4p9HePE8pYhqTrpfDdu+9Wf7QdC8tHq3Kg7ls6RNUDqt6lQ/R3z4T+7hXuu1dMLFVQLwILhRCxwBDgPzmuPQTsKrYkZYBGjZS/sVI3rrATULUGjPgc/rEdmtwLCKpEH+KncS58NcwOEXdBRTPVaIpL4lVIvKJG7o362loajSZfLA75LoRwQxlGnJJSJuQ43wxIkFKWqbdnUaz4Ll26hJ+fH+7u7sTGxmJvb28l6SwgOZat8x6jbvQWmnmb5BDQuB90nARNB4G93jelKSRZGfC/jhB3XkXEbTum4Hs0miJSXCs+BwsbqZ99GANUF0JUz3E5xdJ6yjp16tTB39+f8+fPc+LECdq0aWM7YVy86PXi94SePMnFpDD8Lv8OJ9ZDxBaVXGtB+4ch8GHtaVpjOUe+U8qpRhNoPdLW0mg0d8VSxXIOMA218vIqIQEbDjdKju7du3P+/Hl2795tWwUFODk50bZdO6Ad8CDc91+1uH1gmVrg3jFPJf+eSlm1HA5O1Wwqs6YMk5UBO+aq4z4vgF2F+JfVVGAsXYM6CoQDswB/wPG25FRcQYQQY4QQx4UQRiFE0G3XZgohIoQQYUKIe4vb1t0weZI4eLDwcZ2sjosXdJsO0/fB5E3Qbjw4usD5nbDuSZjbTC3SRgUr558aTU6Ofq8CEdZoDK1HFVhco7E1lro6CgRGA17ATmAjyprPSUqZJaXMKgFZQoCRwPacJ4UQLbPbagUMAj4VQljtp99DDz1EaGgon3/+ubWasIiQkBD69OnDe++9d+dFIcC/O4z4DP4dpkzV63aC9AQ4+BV80Q8W9VHWN1pRaUwcWKo+e/1bj5405QKLvZlLKUOklM8DAcAHwFDgshCiQ0kIIqU8KaUMy+PScOA7KWWalPIsEAF0Lok288LHx4dmzZrlGZepNAkPD2f79u3s2lWAgaSzuzJVf2ILPLUXuv0fuHjD5SPw7ShYNhQi95eO0Jqyy/XTELUfnFyh5QO2lkajsYiihNtoAvQBugGHgBslKtGd+AGROfJR2ecqNGfPqn0nhQrxXrM53Ps2/CsEBrwJzp5q+m9Jf1g5vkT2JWjKKUez98K0uB+cXGwri0ZjIRYpKCGElxBiuhBiH7AOSAR6Syn7Zo9qLEIIsUUIEZJHytuVd/ZteZzLc95KCDFVCBEshAiOiYmxVKw72LBhA506dWLWrFlFrqO4mBRUQEAR4vI4VoUeM+DpI9DrObVOFfYLfNYd1k69telSUzmQ8paCavugbWXRaAqBpVZ8l4CzwDfA39nnGgshGpsKSCn/KKgSKWX/QkuoRkz1cuTrZsuTV/2LUA5sCQoKKvLiixCC4OBgqlbN24FraWAKnFgkBWWiqqdyY9N5qrLeCl6qXlTHf1TGFr2egyquJSOwpuwSuU8ZR7jVhoDetpZGo7EYS6f4rgDOwBRgSR7pC6tIp/gJGCuEqCKECEBNMe6zYnvm0Or79+8nPT29gNLWoVgjqNtx84XB78M/DyjXNlnpsHM+fBwER3/QhhQVnaPfqc82Y7RxhKZcYakVXwMpZcBdUsPiCiKEGCGEiEKtbf0ihPgtu+3jwPfACeBXYHoJWQ3mS40aNWjevDmpqakcPnzYmk3liZTSPIIq1BpUQVT3h5EL4YmtUKcDJFyGtU8o32yXj5ZcO5qyQ2YahKxVx20fsq0sGk0hsdhIQgjhmOO4pxCid45UbE8SUsofpZR1pZRVpJS+Usp7c1x7W0rZSErZTEq5qbhtWUK3bt0A2L17d2k0l4v09HTGjx/P8OHD8fS0gqP4ukFKSQ3/BKr5wIU9yix9w7OQHFvy7WlsR/hmSI0D39ZQS8cU05QvLDWSeBL4Msep34Fvs9OPwMSSF822mDbs2kJBValShUWLFrFu3TrrNWJnB+0nqGm/rk8BAoKXKD9tJm/HmvKPaXpPj5405RBLR1CPAnNz5NOklPWklPWAfsATJS6ZjcmpoCx1qFsucfaAQe+qcN8BvSElFlY/Bj9MuhUyQVM+SY2HU78BAtqMtrU0Gk2hsVRBBUgpj+TI59xQcwQo9hpUWaN58+ZMmTKFRYsWlXrbERERHD16lKSkpNJrtGZzePQnGDofHKspS79Pu0DoL6Ung6ZkObtDGcTU7wrudWwtjUZTaCxVUK5CCLMXUilljxzXXIAK56HUzs6ORYsWMXjw4FL3KjF37lzatWvHl19+WXDhkkQICHoMntwF/j0gKQa+Gw8/Pnkr4Jym/HA222tYQ4MtpdBoioylCioEGJjPtUGoiLuaEqJETcyLglcATNwA974LDs5wZAV82v1WJE1N+eDsX+pT733SlFMsVVAfopy0PiCEsAMQQtgJIUYAH2dfr5Bs3bqV0aNHs2XLloILlxBWMTEvLHZ20O0p+McOZZJ+Mwq+eUCFt85Ms51cGstIiIaYUOVFxK/I8eI0Gpti6T6o71BGEsuBVCHEJSAV+Br4QEq50noi2pbdu3ezZs0avvrqq1Jpz2g0lg0FZcKnKTy+GfrOAmEPez5W3tJjTtlaMs3dME3v1e8GDsWOhqOxgMGDBxMXF3fXMq+99lqRf+xu27aNoUOHFune8kphvJnPA+oAw4DngfuBulLK960kW5ng4YcfBmDt2rUkJiZavb3Lly+Tnp6Oj48Prq5lxA2RvQP0eR4e/x2qN4Arx2BhbxU4sSJbOJZnTNN7DfvYVo5KgJQSo9HIxo0bC9y3+MYbb9C/f1E8vlVOCuXNXEp5U0r5m5TyWynlr1LKCr9y3rBhQ7p3705ycjLr16+3ensl4oPPWtQNUlN+bcdCZgr8/DT8MBFSrO3QXlNoKvD6kxAi35TT6nbRokV3LVsYPvjgA1q3bk3r1q358MMPOXfuHC1atOCpp56iQ4cOREZG0qBBA65duwbAm2++SfPmzRkwYADjxo1j7ly1S2fSpEmsXr0aUDMks2fPpkOHDrRp04bQ0FAA9u3bR/fu3Wnfvj3du3cnLCyvKESVg6KE26h0TJgwAYDly5dbva0ihdkoTZzdlbukkYvByQ1OrIfPe8H5PbaWTGPixjmIu6DCrdRqa2tpyj0HDhxg6dKl7N27l7///pvFixdz48YNwsLCePTRRzl06BD+/v7m8sHBwaxZs4ZDhw6xdu1agoOD863b29ubgwcP8uSTT5qVWPPmzdm+fTuHDh3ijTfe4OWXX7b6M5ZViu2iqDLw4IMPMmPGDH7//Xeio6Px9fW1WlujR48mKCgIO7sy/tuh7YNqRLXmCbh4AJYNVpFa+7wI9o4F36+xHmeyR08NelZI57CWbpyfOnUqU6dOLXZ7O3fuZMSIEVSrpnbTjBw5kh07duDv7292LH17+eHDh5ujIQwbNizfukeOHAlAx44dWbtW+UyMj49n4sSJhIeHI4QgIyOj2M9QXimRt6DJsq+iUqNGDQYPHozRaOTbb7+1alvOzs40b96cpk2bWrWdEsGrITz2G/T8l1qL2v4+LBkA18JtLVnlRu9/KlHyU4gmhWVp+byoUqUKAPb29mRmZgLw6quv0rdvX0JCQvj5559JTU0tpMQVh2IpFiFEGyHEXHJHvK2QPPnkk7z22mtMmjTJ1qKULewdof/rMOkX8KgPlw6pKb+/P4OsTFtLV/mQ8paCqoDrT7agd+/erFu3juTkZJKSkvjxxx/p1atXvuV79uxpViyJiYn88kvhvLHEx8fj56eChi9btqw4opd7Cq2ghBA+QoinhRCHgF2oYIK1SlyyMsagQYOYM2cOXl5eVm1n3LhxPPbYY9y4Uc4MDxr0gCd3QrtxyoDi15dgkQEu/F3grZoSJCYUkq6Cay3wLgej8HJAhw4dmDRpEp07d6ZLly488cQTVK9ePd/ynTp14v7776ddu3aMHDmSoKAgPDw8LG7vhRdeYObMmfTo0YOsLKtGFirzCEuGo9mhNu4HJgF9ga3Ad8B6wAgkSSnL1GR3UFCQvNviZHFIS0vD3t4eB4eSXcLLzMzE2dkZo9FISkqKefhf7gjdCJtehPgLKt9uPPSfDW4V/neM7fn7c/j1RWjzIIxabGtpKi2JiYm4urqSnJxM7969WbRoER06dLC1WKWOEOKAlLLIO8ULE1H3XyiFVE9KOVxKuVJKmQxUqo0wK1eupFGjRlZZi4qMjCQrK4s6deqUX+UE0HwwTN8LvV8AeyflKumjDrDtPUgvRQe4lZHzO9Wnnt6zKVOnTiUwMJAOHTowatSoSqmcSgJLFdQxoAXQBQgUpe09tQyRkZHBxYsXeeedd0p8+F2mPEgUFycXuOcVeOpvaD4UMpJg27tKUR1YptenrMXFQ+qzXmfbylHJWbFiBYcPHyY0NJSZM2faWpxyi6WujgxAB+ACsAiIEkJ8IISodE6+xo8fT8OGDTl16hTff/99idZtcyex1qBGIxj7LUzaqHz6JV5RG3w/7aJCehiNtpaw4pAYo3wmOlaDGo1tLY1GU2wK4+rovJTyTSllE+AhwBXYQu7YUBUeBwcH8y+it956q0RHURVSQZlo0EOFmR+1RJmnX49QQREX94Xj6/SIqiS4fFh91m5XIfc/aSofRTIzl1LulFJORVnvzUKFgK80PProo/j7+3PixIkSDWhY5r1IFBc7OxXZdfo+FRjRtZZ6qf4wET5qD7v/Byl3d7apuQuXshVUnUDbyqHRlBDF2gclpUzNNpa4r6QEKg84OTkxb948AF5++WWuXr1aIvUGBQXRv39/WrduXSL1lVnsHVVgxBmHYPBc8GqkLP5+nwUftIQN/4LoSjUwLxkuZa8/1WlvWzk0mhKiQnuAsCYjR47k3nvvpVatWkRHR5dInc888wybN2+mc+dKssDt5AKdp8D/BcP47yGgjzKmCP4SPusGy4bC0e8hPdnWkpYPzFN8egRV1rAkFEdBnDt3ruL/eL0N7YuviAgh+Oabb/Dw8MDJScfbKRZ2dtD0XpWuhsL+xXB4JZzboZKTG7R6ANpPgHpdVGh6TW4Sr8LNi+Dkqg0krIyUEillofxlbty40YoSVVz0CKoY+Pj4lJhyioyM5MCBAyQnV/LRQs3mMGQe/Puk+vQLgvQEOPQNfHkvfN5TjbDSrB+bq1xxKcfoqaw7Gi4GdwufUZxUELeH1/jmm2/o1q0bHTp0YMyYMSQmJrJp0yYefPBB8z3btm0zO4o1heJISkpiyJAhtGvXjtatW7Nq1SpAeUzv06cPHTt25N577+Xy5cvm8+3ataNbt2588sknVujRsk3F/SaXIjExMTz++OPMnz+/yHUsX76coKAgXnnllRKUrBzj7AGdnoApW2H6fuWQtpoPRIeoNaoPWihvFdcibC1p2cC8/qSn96yFKbzG5s2bWbJkCVu2bOHgwYMEBQXxwQcfMGDAAP7++2+SktRm9FWrVvHQQw/lquPXX3+lTp06HDlyhJCQEAYNGkRGRgb//Oc/Wb16NQcOHOCxxx4zvwcmT57MRx99xJ49lTOcjVZQJcD+/fv58ssvmTlzJseOHStSHSEhIQCVbo7ZInyaKoe0/zquzNTrd4O0m7D3c/i4IywfBad+r9x7qkzrTxXcQMI0vVbSyRJM4TX+/vtvTpw4QY8ePQgMDOSrr77i/PnzODg4MGjQIH7++WcyMzP55ZdfGD58eK462rRpw5YtW3jxxRfZsWMHHh4ehIWFERISwoABAwgMDOStt94iKiqK+Ph44uLi6NNHRUV+5JFHSrw/yzp6DaoEGDx4MFOmTGHx4sWMHz+e/fv34+zsXKg6tIKyAIcqyky9zWgVdn7vQjj2A0RsUcmnOXT/J7QZo8pWJkwjKG0gYTVM4TWklAwYMICVK1feUeahhx7ik08+wcvLi06dOuHm5pbretOmTTlw4AAbN25k5syZDBw4kBEjRtCqVas7RklxcXGFjvxb0dAjqBJi/vz5NG3alJCQEF566aVC3ZuZmWkO99yyZUtriFfxqNUGhn8Mz54ko8fJAAASX0lEQVSEAW+Au5/y5L1+OnzYFnZ+CKk3bS1l6ZBwBRIuQxV3tQlaY1W6du3Krl27iIhQ08vJycmcOnUKAIPBwMGDB1m8ePEd03sAly5dwsXFhQkTJvDcc89x8OBBmjVrRkxMjFlBZWRkcPz4cTw9PfHw8GDnTuVf0dqx6MoiWkGVENWqVePbb7/FwcGBBQsW8Ouvv1p8b0REBOnp6fj7+9/xi0tTAC5e0ONpePoIjFgIvq2VO6Uts+HD1rD1TUi6ZmsprculnB4k9L+0tfHx8WHZsmWMGzeOtm3b0rVrV/MPTHt7e4YOHcqmTZsYOnToHfceO3aMzp07ExgYyNtvv82sWbNwcnJi9erVvPjii7Rr147AwEB2794NwNKlS5k+fTrdunUzR+itTFgUbqM8Ys1wG3fjvffeY+bMmfj6+nLkyBGLwsOvXr2aMWPGMGTIEDZs2FAKUlZgpITTW2HH/FuevR2cVYj6LtPAt5Vt5bMG295Tjni7/xMGvmVraTQaM8UNt6HXoEqY559/nt9++42mTZtaHKTsxAnlNUGvP5UAQkDj/ipd2As7P4BTv8LBr1UK6A2dp0LTQcqjRUVArz9pKihlZgQlhBgDvI4K69FZShmcfb4BcBIIyy76t5RyWkH12WoEBZCSklKo4XhWVhZnzpzB2dmZevXqWVGySsq1CNi3EA59qzxVgPID2OFR6DgRPOraVr7iMreZmtb850HlPV6jKSOUVsDC0iAEGAlsz+PaaSllYHYqUDnZmpzK6ebNm2zfntcj3cLe3p4mTZpo5WQtvBvD4PfV5t9731Wh0BOvwPb/wodtYMVYCN8MxnIYXvvmZfUsVTy0gYSmwlFmpviklCeBCmVWef36dbp3787FixfZu3cvrVpVwPWP8oSzB3R7Cro+Ced2Ko8UJ3+GU5tU8qwPrUdDkwFQt1P5mAK8oBbT8WuvXUBpKhxlaQR1NwKEEIeEEH8JIXrlV0gIMVUIESyECI6JiSlN+fLEy8uLzp07k5SUxLBhw8hLphMnTtClSxdeffVVG0hYSRECAnrBmKXw7AnoN1spp7gLas1q6X3w34bw3cOw/X21CfjmZWWAUdY485f6DOhjWzk0GitQqiMoIcQWVAyp23lFSrk+n9suA/WllNeFEB2BdUKIVlLKOza5SCkXoSL+EhQUZPO3iRCChQsXEhoaSnBwMMOHD+ePP/7ItYn3yJEj7Nu3Dz8/PxtKWolxrQm9noUez8DZvyD8d7Xp99opCN2gkgknN/DwU2tW7qbPOir5NFefpc3ZbAXVUCsoTcWjVBWUlLJ/Ee5JA9Kyjw8IIU4DTQHbWEAUEhcXF3766Se6dOnCnj17mDRpEitWrDB7QjZ5kNDTfzbGzg4a9VWJd9Vo6twuuHIULh9VnivS4tVm4JjQvOvwbgoN+0Kje1Q91vZmceM83Dinpi61BV+ZZvDgwaxYsQJPT88i13Hu3DmGDh1qfmfk5PLly0yZMoUNGzaYHds2a9YMUBuLP//8c0A5n500aRIpKSkMHjyYBQsWFGpZ5eOPP6ba/7d3/9FR1Wcex98fESMJQeSXjUSNBLDiAiJWwaBglaMoRVQEc3RRWVzl7Lp1xa6lHteu2vYsZ+Usx3a1/mhEVFCxRi1Ft1stUvyBRNwKtQTFiEEKiPxeIxKe/eN7EyYxk5BIZi4zz+ucOeTeuXPnmeeQeXLv/d7vk5fHdddd1+bP0RqxuQaVjKSewOdmViupD9APWJvmsFqloKCAhQsXUlJSwlNPPUX//v256667AJ/iKLa6Hg+nHg+UhmUz+GIrbK8ObS22V8OOT8Nje3WYC++zyvBY9kvI7Q6DS2HotdCjX/vEWHf0VHS2t3hPkba02oD2b7cxa9Ysrr/++vrl4uJi3n333a9tN23aNB588EGGDRvGRRddxEsvvcSYMQfWb3bv3r1MmTKFkpKS7CtQki4F7gN6AgslvWtmFwDnAHdJ2gvUAjea2edpDLVNBg4cyDPPPMPFF19Mjx496tevWrUK8AIVe1KYtSK3GxQM+vrztV9B9XJY+4dwWnDjSnjj5+Fx4kg45wdQNOLgDmTIxutPPz6wewtbv9/tSZ+qqqpizJgxnHvuubzxxhuUl5ezevVq7rzzTr788kuKi4spKytjyZIllJWV8fTTTwOh3ca9997Liy++SFFREcuXL6dTp05MnDiR6upqamtrueOOO5g0aRIVFRXccsst7Nq1ix49evDoo49SUFBQP7t5bm4uI0aMSBrjs88+yz33NH+T9oYNG9ixYwfDhw8HYPLkyZSXlzNixAgGDRpEZWUlHTt2ZMeOHQwaNIg1a9YwevRozjrrLJYuXcq4ceOYPn06RUVFLFu2LCWNVWMzSMLMnjOzQjPLMbNjouKEmT1rZqeY2WAzO83MXkx3rG11wQUXUF5ezrRp0wDYvXs3H374IQD9+rXTX9kuNTp0hBOGw7kz4MY/wvWvhPusOuaFI505Y6HsIvjw1YMz2MLMrz+lUF2rjRUrVpCXl8c999wTm3YbH330EUcffTQ5OTkN1g0ZMoSRI0eyZMkSANavX09h4f57/goLC1m/fj35+fmMGjWKhQsXAjB//nwuv/xyOnYMo1i3bdvG4sWLmT59OgCnn356/T7bW2yOoLJF4vxcdcVpwIAB3pU3k0jQe2h4jL4blj0UjqTWvQ5zx0PhGTDyNuh7XtuPqDb9GXZvDjcc9+h/cOOPs2aOdNpTXasNoEG7DYA9e/YwfPjwBu02JkyYwMKFC5k5c2aD/QwcOJBbb72V2267jbFjx3L22WezcuXK+nYbEG7cLygoaLLdxqJFi74W24YNG+jZs2f9ckFBAevWraN79+5UVFQwfvx4Vq1a1WRbkbrrT1OnTmXmzJmMHz+esrIyHnroofptGhfZXr161c892N68QKVRbm4ukyZN4rLLLkt3KK69dOoKI38AZ94Abz8Mr98H1cvgicvh2NNg1Ixw31VrC1Xd6b0+o/z+pxSoa7UB8Wu30alTJ2pqauqXc3Jy6o+mhg4dSnFxMZWVlRQWFlJdXV2/XXV1NcceG0aelpSUUFVVxeLFi6mtrW1wySHxswPU1NSkbOLa2Jziy0Z9+/Zl/vz5DdpEuwx1ZJcwnP3m90J7kLye8Ok78OQVMO/KMCKvNfz0XtrErd1G//79qaqqql/evHkztbVhVpS1a9eyZs0a+vTpQ0FBAfn5+bz55puYGY899liDhoqTJ0+mtLS0xQEQlZWVKbtm7gXKuVTK6Ry1B/lTmHk8p0uYzPYXZ8KSWbB3T8v7qN0bhsBDdg2QiIm4tdvIy8ujuLi4vmC+9tprDBo0iMGDBzNhwgQeeOABunXrBsD999/P1KlT6du3L8XFxQ1G8F111VVs3bqV0tLSZj//0qVLOf/8Vt8x1CaxmSz2YEvnZLHOHbCdf4WXb4eVC8Jyl94w/B/DAIuczk2/5pNl8Mho6N4XbqpIXawutp577jkqKipaHMnXnAULFvD8888zd+7cpNusWLGCWbNmNbtNIm+34dyhLP9bMOERGHI1vDQDNr8PL88IE9medk0Ymt57aBjebga7NsF7UTHzoycXufTSS9myZUubX3/TTTexaNGiFu/X+uyzz7j77rvb/D6t5UdQzsXFvn2w5uVwqq96WcPnuh4fWtjXbNu/buJcGDAutTE61wp+BOVcpjjsMDhpTGim+PHrsPq3sL4itHTfti5sc+RR0PNkKDw9bOtcBvMC5VzcSFBUEh4QZqnY8gF06hYmt/Vh5S5LeIFyLu46dIReJ6c7CudSzoeZO+eciyUvUM4552LJC5RzzrlY8gLlnHMuljL2PihJO4HV6Y4jpnoAn6U7iJjy3CTnuWma5yW5k8wsv+XNmpbJo/hWf5MbxDKZpOWem6Z5bpLz3DTN85KcpG80W4Kf4nPOORdLXqCcc87FUiYXqAfTHUCMeW6S89wk57lpmucluW+Um4wdJOGcc+7QlslHUM455w5hXqCcc87FUkYWKEkXSlot6QNJP0x3POki6ThJr0p6X9IqSd+P1neT9DtJa6J/j053rOkiqYOkFZJ+Ey17bgBJXSUtkPSX6P/PcM9NIOmfo9+nlZLmSToyW3Mj6VeSNklambAuaS4kzYi+l1dLuqCl/WdcgZLUAfgFMAYYAJRKGpDeqNJmLzDdzE4GhgH/EOXih8Dvzawf8PtoOVt9H3g/YdlzE8wGXjKzbwODCTnK+txI6g38E3C6mf0N0AG4kuzNzaPAhY3WNZmL6LvnSuCU6DX/FX1fJ5VxBQo4A/jAzNaa2R5gPnBJmmNKCzPbYGbvRD/vJHzJ9CbkY0602RxgfHoiTC9JhcDFwMMJq7M+N5K6AOcAjwCY2R4z24bnps7hQCdJhwO5wKdkaW7M7DXg80ark+XiEmC+mX1pZh8BHxC+r5PKxALVG/gkYbk6WpfVJBUBQ4C3gGPMbAOEIgb0Sl9kafWfwL8A+xLWeW6gD7AZKItOfz4sKQ/PDWa2HvgPYB2wAdhuZv+N5yZRsly0+rs5EwtUU+1Gs3osvaTOwLPAzWa2I93xxIGkscAmM6tIdywxdDhwGnC/mQ0BdpM9p6yaFV1PuQQ4ETgWyJN0dXqjOmS0+rs5EwtUNXBcwnIh4RA8K0nqSChOT5jZr6PVGyUVRM8XAJvSFV8alQDjJFURTgN/V9LjeG4g/A5Vm9lb0fICQsHy3MD5wEdmttnMvgJ+DZyF5yZRsly0+rs5EwvU20A/SSdKOoJwUe6FNMeUFpJEuI7wvpnNSnjqBeCa6OdrgOdTHVu6mdkMMys0syLC/5FXzOxqPDeY2V+BTySdFK06D/gznhsIp/aGScqNfr/OI1zb9dzslywXLwBXSsqRdCLQD1jW3I4yciYJSRcRri90AH5lZj9Jc0hpIWkEsAR4j/3XWX5EuA71NHA84RfuCjNrfKEza0gaBdxqZmMldcdzg6RTCYNHjgDWAtcR/qD13Ej/BkwijJJdAUwFOpOFuZE0DxhFaDmyEbgTKCdJLiTdDkwh5O5mM1vU7P4zsUA555w79GXiKT7nnHMZwAuUc865WPIC5ZxzLpa8QDnnnIslL1DOOediyQuUcy2Q9CNJD7e85UF7v6WShqTq/Voi6ZhoRvOcdMfissvh6Q7AuXSTtCthMRf4EqiNlm8ws5+mMJbvATvNbEWq3rMlZrZR0qvA3wP3pTselz38CMplPTPrXPcg3Fj4vYR1T6Q4nBuBuSl+T6KZuZvzBHBDKmJxro4XKOdaIOnH0Tx9SCqSZJKuk/SJpK2SbpT0HUl/krRN0s8bvX5KdIpsq6SXJZ2Q5H2OAL4LLI6WvyXp/6LZLeq2GSppczTHYrP7ljQ7inGHpApJZzf6TAskPS5pB3CtpDMkLY+23ygpcXqst4A+yWJ3rj14gXKubc4kzCU2iTCt1u2EiURPASZKGgkgaTxheqnLgJ6EqafmJdlnP2CfmVVD/Zx4fwAmJmxzNaGnzlcHsO+3gVOBbsCTwDOSjkx4/hLCRLBdCUdIs4HZZtYFKCZMV0MUy15C/57BB5Qd5w4CL1DOtc3dZlYT9QLaDcwzs01Rv6AlhN5bEE6L/czM3o++5H8KnJrkSKQrsLPRujmEolTXLbqU/acAm923mT1uZlvMbK+Z3QvkACcl7PsNMys3s31m9gXwFdBXUg8z22VmbzaKZWcUo3Mp4QXKubbZmPDzF00sd45+PgGYHZ3620boPiqabtS2FchvtO55YICkPsBoQoO8uhmgm923pOnR6b/t0fNHESb1rJPYPA7g74D+wF8kvR31zEqUD2xrIm7n2oWP4nOufX0C/OQAB1usIXRJ6R0diWFmNZKeBq4Cvk3DARRJ9x1db7qN0A5ilZntk7SVhk3jGswUbWZrgFJJhxFOGy6Q1N3MdkeDKPoC/3tgH9u5b86PoJxrXw8AMySdAiDpKElXNLVh1ADvf4CRjZ56DLgWGAc8foD7zie0NNgMHC7pX4EuzQUq6WpJPc1sH/uPlOqG258BVJnZxy18XucOGi9QzrUjM3sO+HdgfjRabiUwppmX/BL420b7WEro5/WOmVUd4L5fBhYBlcDHQA1fP6XX2IXAqui+sNnAlWZWEz13FaEgOpcy3g/KuZiR9EfgpsSbdSW9AjxpZimb0SLhvXsRhr4PSShYzrU7L1DOxZyk7wC/A44zs8aj/JzLWH6Kz7kYkzSHcF3qZi9OLtv4EZRzzrlY8iMo55xzseQFyjnnXCx5gXLOORdLXqCcc87Fkhco55xzsfT/oLTxXCG5p8QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(6,8))\n",
    "plt.clf()\n",
    "gs = GridSpec(3,1) #,height_ratios=[1,1], width_ratios=[1,0.075,0.075,1]\n",
    "\n",
    "ax2 = plt.subplot(gs[2,0])\n",
    "ax1 = plt.subplot(gs[1,0],sharex=ax2)\n",
    "ax0 = plt.subplot(gs[0,0],sharex=ax2)\n",
    "\n",
    "#ax0.axes.xaxis.set_ticklabels([])\n",
    "#ax1.axes.xaxis.set_ticklabels([])\n",
    "#ax0.axes.get_xaxis().set_visible(False)\n",
    "#ax1.axes.get_xaxis().set_visible(False)\n",
    "\n",
    "\n",
    "years=np.arange(0,100,1)\n",
    "\n",
    "ax0.plot(np.arange(0,100,1./12),aod_schmidt_10yr_orig,'k--',lw=2)\n",
    "ax0.plot(np.arange(0,100,1./12),aod_schmidt_10yr_rev,'k-',lw=2)\n",
    "ax0.axhline(y=1.2, c='k', linestyle=':')\n",
    "ax0.text(65,1.3,'Schmidt et al. 2016',fontsize=10)\n",
    "ax0.set_ylabel('AOD',fontsize=12)\n",
    "\n",
    "\n",
    "ax1.plot(years,24*aod_schmidt_10yr_orig_ave,'k--',lw=2)\n",
    "ax1.plot(years,21*aod_schmidt_10yr_rev_ave,'k-',lw=2)\n",
    "ax1.axhline(y=16.25, c='k', linestyle=':')\n",
    "ax1.set_ylabel('$-\\Delta$F ($W/m^2$)',fontsize=12)\n",
    "\n",
    "ax2.plot(years,tsann_schmidt_10yr_orig-tsann_schmidt_10yr_orig[0],'k--',lw=2, label='original')\n",
    "ax2.plot(years,tsann_schmidt_10yr_rev-tsann_schmidt_10yr_rev[0],'k-',lw=2, label='revised')\n",
    "ax2.plot(years,tsann_schmidt_50yr_rev-tsann_schmidt_50yr_rev[0],'-',c='tab:orange',lw=2, label='revised (50yr)')\n",
    "ax2.axhline(y=-6.6, c='k', linestyle=':')\n",
    "ax2.axhline(y=-9, c='tab:orange', linestyle=':')\n",
    "ax2.set_xlabel('Time (years)',fontsize=12)\n",
    "ax2.set_ylabel('$\\Delta$ GMST ($^{\\circ}$C)',fontsize=12)\n",
    "ax2.legend(frameon=False)\n",
    "ax2.set_xlim(0,100)\n",
    "\n",
    "ax0.text(-0.125,1,'(a)',transform=ax0.transAxes,fontsize=12)\n",
    "ax1.text(-0.125,1,'(b)',transform=ax1.transAxes,fontsize=12)\n",
    "ax2.text(-0.125,1,'(c)',transform=ax2.transAxes,fontsize=12)\n",
    "\n",
    "\n",
    "plt.tight_layout() #h_pad=-4.25, w_pad=-2\n",
    "\n",
    "fig.savefig('./plot_pdf_files/FigS2_forcing_revision.pdf',bbox_inches='tight', pad_inches=0.05) #, dpi=900\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "toc-hr-collapsed": true
   },
   "source": [
    "### Fig. 1: Pulse Forcings and GMST response timeseries "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Read ts_ann (from history_p2) and pco2diag (from history) calculate maximal changes and store them to pickle-file\n",
    "\n",
    "scenario='short'\n",
    "if scenario=='short':   \n",
    "    paths=paths_pulse_control+paths_pulse_c_short_base+['pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka','pulse_rev_s_1500ppm_125GtS_5ka']\n",
    "    #paths=paths_pulse_control+paths_pulse_c_short_base+paths_pulse_cs_short #+paths_pulse_s_short #+paths_pulse_s_short #['pulse_c_1000ppm_5300GtC_5ka']\n",
    "    \n",
    "    #+paths_pulse_cs_short_extra\n",
    "    len_scen=5000\n",
    "elif scenario=='long':\n",
    "    paths=paths_pulse_long\n",
    "    len_scen=10000\n",
    "\n",
    "ts_anns_minmax=np.empty((len(paths),8))\n",
    "ts_anns_runmeans=np.empty((len(paths),len_scen))\n",
    "pco2_minmax=np.empty((len(paths),6))\n",
    "pco2_runmeans=np.empty((len(paths),len_scen))\n",
    "\n",
    "for i in range(len(paths)):\n",
    "    path=paths[i]\n",
    "    ts_anns, times=read_hist(path, hist_name='history_p2', var_name='ts_ann', mean_opt='global')\n",
    "    df=pd.DataFrame(ts_anns)\n",
    "    test=df.rolling(window=100).mean()\n",
    "    ts_anns_runmean=np.array(test)[:,0]\n",
    "    ts_anns_runmeans[i,:]=ts_anns_runmean[500:len_scen+500]        \n",
    "\n",
    "    idx_GtC=path.find('GtC')\n",
    "    idx_GtS=path.find('GtS')\n",
    "    idx_ppm=path.find('ppm')\n",
    "    if path in paths_pulse_control+paths_pulse_s_short+paths_pulse_s_long:\n",
    "        c_emission=0\n",
    "    else:\n",
    "        c_emission=path[idx_GtC-4:idx_GtC]\n",
    "    if path in paths_pulse_control+paths_pulse_c_short+paths_pulse_c_short_extra_Eppley+paths_pulse_c_long:\n",
    "        s_injection=0\n",
    "    elif path in paths_pulse_cs_short+paths_pulse_cs_long:\n",
    "        #s_injection=path[idx_GtS-3:idx_GtS]\n",
    "        s_injection=path[idx_GtC+4:idx_GtS]\n",
    "    elif path in paths_pulse_s_short+paths_pulse_s_long:\n",
    "        #s_injection=path[idx_GtS-3:idx_GtS]\n",
    "        s_injection=path[idx_ppm+4:idx_GtS]\n",
    "\n",
    "    ts_ini=ts_anns_runmean[499]\n",
    "    ts_end=ts_anns_runmean[len_scen+499]\n",
    "    ts_min=np.min(ts_anns_runmean[499:len_scen+499])\n",
    "    ts_max=np.max(ts_anns_runmean[499:len_scen+499])\n",
    "    ts_diff_warm=ts_max-ts_ini\n",
    "    ts_diff_cool=ts_min-ts_ini\n",
    "    ts_anns_minmax[i,:]=[c_emission,s_injection, ts_ini, ts_end, ts_min, ts_max, ts_diff_warm, ts_diff_cool]\n",
    "\n",
    "    pco2, times=read_hist(path, hist_name='history', var_name='pco2diag')\n",
    "    #df=pd.DataFrame(pco2)\n",
    "    #runningmean_window=100\n",
    "    #test=df.rolling(window=runningmean_window).mean()\n",
    "    pco2_runmean=pco2[:] #np.array(test)\n",
    "    pco2_runmeans[i,:]=pco2_runmean[500:len_scen+500]\n",
    "\n",
    "    pco2_ini=pco2_runmean[499]\n",
    "    pco2_end=pco2_runmean[len_scen+499]\n",
    "    pco2_min=np.min(pco2_runmean[499:len_scen+499])\n",
    "    pco2_max=np.max(pco2_runmean[499:len_scen+499])\n",
    "    pco2_diff=pco2_max-pco2_ini\n",
    "    pco2_minmax[i,:]=[c_emission,pco2_ini, pco2_end, pco2_min, pco2_max, pco2_diff]\n",
    "\n",
    "ppms_nobiogeo=[1000,1500,2000] #700,,3000,4000\n",
    "ts_anns_nobiogeo=np.empty((len(paths_nobiogeo)))\n",
    "for i in range(len(paths_nobiogeo)):\n",
    "    path=paths_nobiogeo[i]\n",
    "    nc_f = '../climber/'+path+'/history_p2.nc'\n",
    "    nc_fid = Dataset(nc_f, 'r')\n",
    "    #nc_attrs, nc_dims, nc_vars = ncdump(nc_fid)\n",
    "    ts_ann=np.mean(jan.global_mean(nc_fid.variables['ts_ann'][-100:-1,::-1,:]), axis=0) \n",
    "    ts_anns_nobiogeo[i]=ts_ann\n",
    "\n",
    "if scenario=='short':\n",
    "    with open('historyp2_tsann_pco2diag_rev.pickle', 'wb') as f:  \n",
    "        pickle.dump([ts_anns_minmax, ts_anns_runmeans, pco2_minmax,pco2_runmeans, ts_anns_nobiogeo,ppms_nobiogeo], f)\n",
    "elif scenario=='long':\n",
    "    with open('historyp2_long_tsann_pco2diag_rev.pickle', 'wb') as f:  \n",
    "        pickle.dump([ts_anns_minmax, ts_anns_runmeans, pco2_minmax,pco2_runmeans, ts_anns_nobiogeo,ppms_nobiogeo], f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
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     "metadata": {},
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    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_raw_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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     "metadata": {},
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     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_raw_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Read out example Temp.-Timeseries\n",
    "\n",
    "path='pulse_c_1500ppm_5300GtC_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_c_1500ppm_5300GtC_5ka=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "path='pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "        let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "%ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "%ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n",
    "Tcolor='tab:green'\n",
    "path='pulse_c_1000ppm_5300GtC_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_c_1000ppm_5300GtC_5ka=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "path='pulse_c_2000ppm_5300GtC_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_c_2000ppm_5300GtC_5ka=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "\n",
    "path='pulse_rev_cs_1500ppm_5300GtC_10GtS_5ka_sparse'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_f=a' % locals()\n",
    "%ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_10GtS_5ka_sparse=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "\n",
    "\n",
    "path='pulse_c_1500ppm_5300GtC_12ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_c_1500ppm_5300GtC_12ka=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:10500,0,0], -1e34)\n",
    "path='pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "        let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "%ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "%ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n",
    "Tcolor='tab:purple'\n",
    "path='pulse_control_1500ppm'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_control_1500ppm=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:10500,0,0], -1e34)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 684x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Example Timeseries for Paper\n",
    "%matplotlib inline\n",
    "fig=plt.figure(figsize=(9.5,6))\n",
    "plt.clf()\n",
    "ax2=fig.add_subplot(212)\n",
    "ax1=fig.add_subplot(211,sharex=ax2)\n",
    "\n",
    "#ax1.grid(linestyle=':', zorder=0)\n",
    "\n",
    "years=np.arange(1,5001,1)\n",
    "#filename='../pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka/carbon_emission_1200y_5300GtC.dat'\n",
    "#years_c, c_rate=np.loadtxt(filename, unpack=True)\n",
    "#ax2.plot(years,10+c_rate*0.5, '--',c='k',lw=1, zorder=2, label='Forcing (a.u.)')\n",
    "\n",
    "\n",
    "# paths_forcing_example=['pulse_c_1500ppm_2500GtC_5ka',\n",
    "#        'pulse_c_1500ppm_5300GtC_5ka',       \n",
    "#        'pulse_c_1500ppm_7500GtC_5ka',\n",
    "#        'pulse_corr_cs_1500ppm_2500GtC_125GtS_12ka', \n",
    "#        'pulse_c_1500ppm_5300GtC_12ka',\n",
    "#        'pulse_corr_cs_1500ppm_7500GtC_125GtS_12ka']\n",
    "labels=['2500GtC_5ka', '5300GtC_5ka', '7500GtC_5ka',\n",
    "\t'2500GtC_12ka','5300GtC_12ka', '7500GtC_12ka']\n",
    "#ax1.grid(linestyle=':', zorder=0)\n",
    "paths_forcing_carb_short=['pulse_c_1500ppm_5300GtC_5ka'] #'pulse_c_1500ppm_2500GtC_5ka', , 'pulse_c_1500ppm_7500GtC_5ka'\n",
    "paths_forcing_carb_long=['pulse_c_1500ppm_5300GtC_12ka'] #'pulse_corr_cs_1500ppm_2500GtC_125GtS_12ka',,'pulse_corr_cs_1500ppm_7500GtC_125GtS_12ka'\n",
    "for i in range(len(paths_forcing_carb_short)):\n",
    "    times, c_rate=np.loadtxt('../climber/'+paths_forcing_carb_long[i]+'/c_emission.dat', unpack=True)\n",
    "    ax1.plot(times, c_rate , '-', c='tab:gray', lw=1.5, label=labels[i]) #+500\n",
    "    times, c_rate=np.loadtxt('../climber/'+paths_forcing_carb_short[i]+'/c_emission.dat', unpack=True)\n",
    "    ax1.plot(times, c_rate , '-', c='k', lw=1.5, label=labels[i]) #+500\n",
    "\n",
    "#ax1.legend(loc='lower right', fontsize='x-small')\n",
    "#ax1.set_xlabel('Time (years)');\n",
    "#ax1.set_ylabel(r'c_emission (GtC/y)');\n",
    "ax1.set_ylabel(r'Carbon Emission (GtC/yr)', fontsize=12);\n",
    "ax1.yaxis.set_label_coords(0.3, -0.1)\n",
    "ax1.set_ylim((-0.5,15))\n",
    "ax1.set_yticks([0,2,4,6,8])\n",
    "ax1.yaxis.label.set_color('k')\n",
    "ax1.set_zorder(10)\n",
    "ax1.patch.set_visible(False)\n",
    "\n",
    "ax12 = ax1.twinx()\n",
    "paths_sulf_forcing_short=['pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka'] #'pulse_rev_cs_1500ppm_5300GtC_500GtS_5ka','pulse_rev_cs_1500ppm_5300GtC_250GtS_5ka',\n",
    "paths_sulf_forcing_long=['pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka'] #'pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka', ,'pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka'\n",
    "alphas=[1.0] #[0.4,0.7,1.0]\n",
    "for i in range(len(paths_sulf_forcing_short)):\n",
    "    times, solar_forced =np.loadtxt('../climber/'+paths_sulf_forcing_long[i]+'/solarv.dat', unpack=True)\n",
    "    ax12.plot(times, (1339.-solar_forced)*(-0.7/4) , '-', c='tab:gray', lw=1.5, label='125GtS_5ka', alpha=1) #+500    \n",
    "    times, solar_forced =np.loadtxt('../climber/'+paths_sulf_forcing_short[i]+'/solarv.dat', unpack=True)\n",
    "    ax12.plot(times, (1339.-solar_forced)*(-0.7/4) , '-', c='k', lw=1.5, label='125GtS_5ka', alpha=1) #+500\n",
    "\n",
    "#path='pulse_corr_s_1500ppm_125GtS_12ka'\n",
    "#times, solar_forced =np.loadtxt('../'+path+'/solarv.dat', unpack=True)\n",
    "#ax12.plot(times, solar_forced , '-', c='tab:purple', lw=2, label='125GtS_12ka', alpha=0.5) #+500\n",
    "#ax12.legend(loc='upper right', fontsize='x-small')\n",
    "#ax12.set_ylabel('Forced $S_0$ ($W/m^2$)');\n",
    "ax12.set_ylabel(r'$\\mathsf{\\Delta F_a}$ (W/m$\\mathsf{^2}$)', fontsize=12);\n",
    "ax12.set_ylim((-70,2))\n",
    "ax12.set_yticks([0,-10,-20,-30,-40])\n",
    "ax12.yaxis.label.set_color('k')\n",
    "ax12.yaxis.set_label_coords(1.065, 0.66)\n",
    "\n",
    "times=np.arange(0,5000,1)  \n",
    "\n",
    "#ax1.plot(times, ts_ann, c=Tcolor, label=path, lw=2)  #color_list[i] , alpha=0.8\n",
    "ax2.plot(times, ts_ann_pulse_c_2000ppm_5300GtC_5ka, linestyle=(0,(3,1,1,1,1,1)), c=colors_paper_df.loc['pulse_c_2000ppm_5300GtC_5ka', 'color'], label='2000ppm_5300GtC', lw=2, zorder=3)\n",
    "ax2.plot(times, ts_ann_pulse_c_1500ppm_5300GtC_5ka, '-.', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], label='1500ppm_5300GtC', lw=2, zorder=4)\n",
    "ax2.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka,'-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], label='1500ppm_5300GtC+125GtS', lw=2, zorder=4)\n",
    "ax2.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw, c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=1, alpha=0.5, zorder=4)\n",
    "ax2.plot(times, ts_ann_pulse_c_1000ppm_5300GtC_5ka, linestyle='--', c=colors_paper_df.loc['pulse_c_1000ppm_5300GtC_5ka', 'color'], label='1000ppm_5300GtC', lw=2, zorder=3)\n",
    "\n",
    "times=np.arange(0,10000,1)  \n",
    "\n",
    "ll=len(ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka_raw)\n",
    "#ax1.plot(times, ts_ann, c=Tcolor, label=path, lw=2)  #color_list[i] , alpha=0.8\n",
    "ax2.plot(times, ts_ann_pulse_c_1500ppm_5300GtC_12ka, linestyle=(0,(3,1,1,1)), c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_12ka', 'color'], label='1500ppm_5300GtC_6kyr', lw=2, zorder=2)\n",
    "ax2.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka_raw, c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_12ka', 'color'], lw=1, alpha=0.5, zorder=2)\n",
    "ax2.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka,linestyle='-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_12ka', 'color'], label='1500ppm_5300GtC+250GtS_6kyr', lw=2, zorder=2)\n",
    "ax2.plot(times, ts_ann_pulse_control_1500ppm, linestyle=':', c=colors_paper_df.loc['pulse_control_1500ppm', 'color'], label='1500ppm_control', lw=2, zorder=1)\n",
    "\n",
    "\n",
    "times, solar_forced =np.loadtxt('../climber/pulse_rev_s_1500ppm_125GtS_5ka/solarv.dat', unpack=True)\n",
    "axins2 = inset_axes(ax12, width=\"100%\", height=\"100%\", loc='lower left',bbox_to_anchor=(.25, .225, .2, .425), bbox_transform=ax1.transAxes)\n",
    "yr_l=900; yr_u=yr_l+50;\n",
    "axins2.set_zorder(10)\n",
    "axins2.patch.set_visible(False)\n",
    "axins21=axins2.twinx()\n",
    "axins21.plot(times[yr_l:yr_u+1], ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw[yr_l:yr_u+1], '-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=1.5)\n",
    "axins2.plot(times[yr_l:yr_u+1], (1339.-solar_forced[yr_l:yr_u+1])*(-0.7/4) , '-', c='k', lw=1.5, alpha=1, zorder=10)\n",
    "mark_inset(ax12, axins2, loc1a=2, loc2a=3, loc1b=1, loc2b=4, fc=\"none\", ec=\"0.5\", zorder=11)\n",
    "#mark_inset(ax1, axins3, loc1a=2, loc2a=3, loc1b=1, loc2b=4, fc=\"none\", ec=\"0.75\")\n",
    "axins2.tick_params(axis='y',left=False,right=True,labelleft=False, labelright=True) #, colors='tab:red'\n",
    "axins21.tick_params(axis='y',left=True,right=False,labelleft=True, labelright=False)\n",
    "axins2.tick_params(labelsize=10)\n",
    "#axins2.tick_params(axis='x',labelbottom=False)\n",
    "axins2.set_xlim([yr_l,yr_u])\n",
    "axins2.set_ylim((-35,2))\n",
    "axins2.set_xticks(np.arange(yr_l,yr_u+10,10))\n",
    "axins2.set_xticklabels([yr_l,'','','','', yr_u])\n",
    "axins2.set_yticks([0,-10,-20,-30])\n",
    "#axins2.set_yticklabels(['',1200,'',1300,''])\n",
    "axins2.yaxis.label.set_color('tab:red')\n",
    "axins21.set_yticks([14,16,18])\n",
    "axins21.set_yticklabels([14,16,18])\n",
    "plt.setp(axins2.get_yticklabels(), color=\"k\")\n",
    "plt.setp(axins21.get_yticklabels(), color=\"tab:green\")\n",
    "axins2.text(0.025,0.05,r'$(\\mathsf{^{\\circ}C})$',fontsize=10, color='tab:green',transform=axins2.transAxes) #,fontweight='bold' , horizontalalignment='center'\n",
    "axins2.text(0.65,0.05,r'$(\\mathsf{W/m^2})$',fontsize=10, color='k',transform=axins2.transAxes) #,fontweight='bold' , horizontalalignment='center'\n",
    "\n",
    "#ax2.legend(loc='lower right', fontsize=10, ncol=1, labelspacing=0.25, frameon=False)\n",
    "ax2.legend(bbox_to_anchor=(0.615,-0.034,0.4,0.6),loc='center', fontsize=10, ncol=1, labelspacing=0.25, frameon=False)\n",
    "#ax2.set_title('Global Mean Temperature in selected scenarios (100yr moving ave.)', fontsize=10);\n",
    "ax2.set_xlim([0,10000]); \n",
    "ax2.set_ylim([7,23]);\n",
    "ax2.set_xticks(np.arange(0,11000,1000))\n",
    "ax2.set_yticks(np.arange(6,24+2,2))\n",
    "ax2.set_xlabel('Time (years)', fontsize=12); \n",
    "ax2.set_ylabel(r'GMST ($\\mathsf{^{\\circ}C}$)', fontsize=12);\n",
    "ax2.tick_params(labelsize=12)\n",
    "#ax2.tick_params(labelsize=12)\n",
    "\n",
    "#ax1.axes.get_xaxis().set_visible(False)\n",
    "ax1.tick_params(axis='x', direction='out',labelbottom=False)\n",
    "ax1.tick_params(labelsize=12)\n",
    "ax12.tick_params(labelsize=12)\n",
    "ax2.tick_params(axis='y',right=True)\n",
    "\n",
    "ax1.text(0,1.025,'(a) Pulse Forcing Examples',transform=ax1.transAxes,fontsize=13)\n",
    "ax2.text(0,1.025,'(b) Response',transform=ax2.transAxes,fontsize=13)\n",
    "ax1.yaxis.set_label_coords(-0.035, 0.475)\n",
    "plt.tight_layout() #h_pad=-0.0h_pad=+0.01\n",
    "\n",
    "fig.savefig('./plot_pdf_files/Fig1_pulse_rev_rev_Forcing_SATTimeseries.pdf',bbox_inches='tight', pad_inches=0.05, dpi=900)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. 6: Illustration of three pulse cases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 396x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "fig=plt.figure(figsize=(5.5,4)) #figsize=(9.5,6)\n",
    "plt.clf()\n",
    "ax=fig.add_subplot(111)\n",
    "\n",
    "times=np.arange(0,5000,1) \n",
    "\n",
    "#colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color']\n",
    "ax.plot(times, ts_ann_pulse_c_1500ppm_5300GtC_5ka, '-', c='k', label='Case 1: no injections', lw=3.5, zorder=3)\n",
    "ax.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_10GtS_5ka_sparse, '-', c='tab:blue', label='Case 2: sporadic injections', lw=1.5, zorder=6)\n",
    "#ax.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka,'-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], label='Case 3: frequent sulfur injections', lw=2, zorder=4)\n",
    "ax.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw, c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], label='Case 3: frequent injections', lw=1.5, alpha=1, zorder=5)\n",
    "\n",
    "ax.legend(loc='lower right', fontsize=10, ncol=1, labelspacing=0.25, frameon=False)\n",
    "\n",
    "ax.set_xlabel('Time (years)', fontsize=12); \n",
    "ax.set_ylabel(r'GMST ($\\mathsf{^{\\circ}C}$)', fontsize=12);\n",
    "ax.tick_params(labelsize=12)\n",
    "ax.set_ylim(6,24)\n",
    "\n",
    "ax.set_xlim([0,3000]);\n",
    "\n",
    "plt.tight_layout(h_pad=-0.1)\n",
    "\n",
    "fig.savefig('./plot_pdf_files/Fig6_pulse_rev_cases_illustration.pdf',bbox_inches='tight', pad_inches=0.05, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. 2: Pulse warming and cooling amplitudes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_100yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
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   ],
   "source": [
    "paths_corr_long=['pulse_corr_cs_1500ppm_5300GtC_50GtS_12ka','pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka','pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka']\n",
    "paths=paths_pulse_c_short_base+paths_pulse_cs_short+paths_pulse_cs_long+paths_pulse_s_single+paths_corr_long\n",
    "ts_ann_maxchange_df=pd.DataFrame([], columns=['ts_ann','ts_ann_100yr','maxwarm','maxcool'], index=paths) \n",
    "\n",
    "for path in paths:\n",
    "    if path not in paths_pulse_s_single:\n",
    "        %ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "                    let ts_ann_f=ts_ann[i=@ave,j=@ave]; let ts_ann_100yr_f=ts_ann[i=@ave,j=@ave,l=@sbx:100]' % locals()  \n",
    "        %ferret_getdata ts_ann_f=ts_ann_f\n",
    "        %ferret_getdata ts_ann_100yr_f=ts_ann_100yr_f\n",
    "        ts_ann=np.ma.masked_values(ts_ann_f['data'][0,0,0,:,0,0], -1e34)\n",
    "        ts_ann_100yr=np.ma.masked_values(ts_ann_100yr_f['data'][0,0,0,:,0,0], -1e34)\n",
    "        ts_ann_maxchange_df.loc[path, ['ts_ann','ts_ann_100yr','maxwarm','maxcool']]=[ts_ann, ts_ann_100yr, np.max(ts_ann_100yr)-ts_ann_100yr[499], np.min(ts_ann_100yr)-ts_ann_100yr[499]]\n",
    "    \n",
    "    if path in paths_pulse_s_single:\n",
    "        %ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "            let ts_ann_f=ts_ann[i=@ave,j=@ave]' % locals()  \n",
    "        %ferret_getdata ts_ann_f=ts_ann_f\n",
    "        ts_ann=np.ma.masked_values(ts_ann_f['data'][0,0,0,:,0,0], -1e34)\n",
    "        ts_ann_maxchange_df.loc[path, ['ts_ann','maxcool']]=[ts_ann, np.min(ts_ann)-ts_ann[0]]\n",
    "ts_ann_maxchange_df.to_pickle('./ts_ann_maxchange_df.pkl')    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_ann</th>\n",
       "      <th>ts_ann_100yr</th>\n",
       "      <th>maxwarm</th>\n",
       "      <th>maxcool</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>pulse_c_1000ppm_5300GtC_5ka</th>\n",
       "      <td>[16.85038367554098, 16.84901557841778, 16.8490...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>4.44068</td>\n",
       "      <td>-0.0184598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_1500ppm_2500GtC_5ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>1.81135</td>\n",
       "      <td>-0.00797755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_1500ppm_5300GtC_5ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>3.22512</td>\n",
       "      <td>-0.00584173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_1500ppm_7500GtC_5ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>4.05203</td>\n",
       "      <td>-0.00497495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_2000ppm_5300GtC_5ka</th>\n",
       "      <td>[19.920550604166774, 19.920583598918174, 19.92...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>2.55295</td>\n",
       "      <td>-0.00572629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1000ppm_5300GtC_125GtS_5ka</th>\n",
       "      <td>[16.85038367554098, 16.84901557841778, 16.8490...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>4.30342</td>\n",
       "      <td>-9.19396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_10GtS_5ka_sparse</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>3.19955</td>\n",
       "      <td>-0.124225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_50GtS_5ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>3.06352</td>\n",
       "      <td>-3.55948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>3.12206</td>\n",
       "      <td>-8.08216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_250GtS_5ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>3.11566</td>\n",
       "      <td>-14.7962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_500GtS_5ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>3.10868</td>\n",
       "      <td>-25.3997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka</th>\n",
       "      <td>[19.920550604166774, 19.920583598918174, 19.92...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>2.45218</td>\n",
       "      <td>-7.18048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>1.87604</td>\n",
       "      <td>-2.4305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>1.49817</td>\n",
       "      <td>-4.01945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>0.958737</td>\n",
       "      <td>-6.99463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_s_single_1500ppm_9MtS</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.293623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_s_single_1500ppm_50MtS</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.12369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_s_single_1500ppm_100MtS</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.46992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_s_single_1500ppm_200MtS</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.95894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_s_single_1500ppm_250MtS</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-2.17848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_s_single_1500ppm_500MtS</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-3.12908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_s_single_1500ppm_1000MtS</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-4.58406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_corr_cs_1500ppm_5300GtC_50GtS_12ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>3.02897</td>\n",
       "      <td>-1.97186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>2.99794</td>\n",
       "      <td>-4.73114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka</th>\n",
       "      <td>[18.71531715984677, 18.71468980565674, 18.7140...</td>\n",
       "      <td>[--, --, --, --, --, --, --, --, --, --, --, -...</td>\n",
       "      <td>2.9728</td>\n",
       "      <td>-8.42058</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                          ts_ann  \\\n",
       "pulse_c_1000ppm_5300GtC_5ka                    [16.85038367554098, 16.84901557841778, 16.8490...   \n",
       "pulse_c_1500ppm_2500GtC_5ka                    [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_c_1500ppm_5300GtC_5ka                    [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_c_1500ppm_7500GtC_5ka                    [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_c_2000ppm_5300GtC_5ka                    [19.920550604166774, 19.920583598918174, 19.92...   \n",
       "pulse_rev_cs_1000ppm_5300GtC_125GtS_5ka        [16.85038367554098, 16.84901557841778, 16.8490...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_10GtS_5ka_sparse  [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_50GtS_5ka         [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka        [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_250GtS_5ka        [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_500GtS_5ka        [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka        [19.920550604166774, 19.920583598918174, 19.92...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka       [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka       [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka       [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_s_single_1500ppm_9MtS                [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_s_single_1500ppm_50MtS               [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_s_single_1500ppm_100MtS              [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_s_single_1500ppm_200MtS              [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_s_single_1500ppm_250MtS              [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_s_single_1500ppm_500MtS              [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_rev_s_single_1500ppm_1000MtS             [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_corr_cs_1500ppm_5300GtC_50GtS_12ka       [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka      [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka      [18.71531715984677, 18.71468980565674, 18.7140...   \n",
       "\n",
       "                                                                                    ts_ann_100yr  \\\n",
       "pulse_c_1000ppm_5300GtC_5ka                    [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_c_1500ppm_2500GtC_5ka                    [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_c_1500ppm_5300GtC_5ka                    [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_c_1500ppm_7500GtC_5ka                    [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_c_2000ppm_5300GtC_5ka                    [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1000ppm_5300GtC_125GtS_5ka        [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_10GtS_5ka_sparse  [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_50GtS_5ka         [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka        [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_250GtS_5ka        [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_500GtS_5ka        [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka        [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka       [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka       [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka       [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_rev_s_single_1500ppm_9MtS                                                              NaN   \n",
       "pulse_rev_s_single_1500ppm_50MtS                                                             NaN   \n",
       "pulse_rev_s_single_1500ppm_100MtS                                                            NaN   \n",
       "pulse_rev_s_single_1500ppm_200MtS                                                            NaN   \n",
       "pulse_rev_s_single_1500ppm_250MtS                                                            NaN   \n",
       "pulse_rev_s_single_1500ppm_500MtS                                                            NaN   \n",
       "pulse_rev_s_single_1500ppm_1000MtS                                                           NaN   \n",
       "pulse_corr_cs_1500ppm_5300GtC_50GtS_12ka       [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka      [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka      [--, --, --, --, --, --, --, --, --, --, --, -...   \n",
       "\n",
       "                                                maxwarm     maxcool  \n",
       "pulse_c_1000ppm_5300GtC_5ka                     4.44068  -0.0184598  \n",
       "pulse_c_1500ppm_2500GtC_5ka                     1.81135 -0.00797755  \n",
       "pulse_c_1500ppm_5300GtC_5ka                     3.22512 -0.00584173  \n",
       "pulse_c_1500ppm_7500GtC_5ka                     4.05203 -0.00497495  \n",
       "pulse_c_2000ppm_5300GtC_5ka                     2.55295 -0.00572629  \n",
       "pulse_rev_cs_1000ppm_5300GtC_125GtS_5ka         4.30342    -9.19396  \n",
       "pulse_rev_cs_1500ppm_5300GtC_10GtS_5ka_sparse   3.19955   -0.124225  \n",
       "pulse_rev_cs_1500ppm_5300GtC_50GtS_5ka          3.06352    -3.55948  \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka         3.12206    -8.08216  \n",
       "pulse_rev_cs_1500ppm_5300GtC_250GtS_5ka         3.11566    -14.7962  \n",
       "pulse_rev_cs_1500ppm_5300GtC_500GtS_5ka         3.10868    -25.3997  \n",
       "pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka         2.45218    -7.18048  \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka        1.87604     -2.4305  \n",
       "pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka        1.49817    -4.01945  \n",
       "pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka       0.958737    -6.99463  \n",
       "pulse_rev_s_single_1500ppm_9MtS                     NaN   -0.293623  \n",
       "pulse_rev_s_single_1500ppm_50MtS                    NaN    -1.12369  \n",
       "pulse_rev_s_single_1500ppm_100MtS                   NaN    -1.46992  \n",
       "pulse_rev_s_single_1500ppm_200MtS                   NaN    -1.95894  \n",
       "pulse_rev_s_single_1500ppm_250MtS                   NaN    -2.17848  \n",
       "pulse_rev_s_single_1500ppm_500MtS                   NaN    -3.12908  \n",
       "pulse_rev_s_single_1500ppm_1000MtS                  NaN    -4.58406  \n",
       "pulse_corr_cs_1500ppm_5300GtC_50GtS_12ka        3.02897    -1.97186  \n",
       "pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka       2.99794    -4.73114  \n",
       "pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka        2.9728    -8.42058  "
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts_ann_maxchange_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x554.4 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### for Paper: short and long scenarios together (runmean of global mean ts_ann)\n",
    "ts_ann_maxchange_df=pd.read_pickle('./ts_ann_maxchange_df.pkl')\n",
    "\n",
    "fig1=plt.figure(figsize=(5.0,7.7))\n",
    "plt.clf()\n",
    "ax1 = fig1.add_subplot(211) \n",
    "ax2 = fig1.add_subplot(212) \n",
    "#ax1.grid(linestyle=':', zorder=0) \n",
    "#ax2.grid(linestyle=':', zorder=0) \n",
    "ax1.spines['right'].set_visible(False)\n",
    "ax1.spines['top'].set_visible(False)\n",
    "ax2.spines['right'].set_visible(False)\n",
    "ax2.spines['bottom'].set_visible(False)\n",
    "#fig1.subplots_adjust(hspace=0.001)\n",
    "\n",
    "times=np.arange(0,10500,1)\n",
    "line_warm_t=[]; line_warm_c=[]\n",
    "line1_cool_t=[]; line1_cool_s=[]\n",
    "line2_cool_t=[]; line2_cool_s=[]\n",
    "\n",
    "line_warm=np.zeros((4,2))\n",
    "line_cool_s=np.zeros((5,2))\n",
    "line_cool_l=np.zeros((4,2))\n",
    "\n",
    "paths=paths_pulse_c_short_base\n",
    "c_emissions=[5300,2500,5300,7500,5300]\n",
    "for ii in range(len(paths)):\n",
    "    path=paths[ii]\n",
    "    c_emission=c_emissions[ii]\n",
    "    maxwarm=float(ts_ann_maxchange_df.loc[path, ['maxwarm']])  \n",
    "    if path in colors_paper_df.index:\n",
    "        cc=colors_paper_df.loc[path, 'color']\n",
    "    else: \n",
    "        cc='k' \n",
    "    ax1.scatter(c_emission, maxwarm, marker='o', edgecolors='k', facecolors=cc, s=80, zorder=10)\n",
    "    ax1.annotate('+'+str(np.round(maxwarm,1)) ,xy=(c_emission,maxwarm), xytext=(-35, -2), textcoords='offset pixels', fontsize=12,color='k') \n",
    "    \n",
    "    if path in paths_pulse_c_short_base[1:-1]:\n",
    "        line_warm[ii,0]=c_emission\n",
    "        line_warm[ii,1]=maxwarm\n",
    "ax1.scatter(0, 0, marker='o', edgecolors='k', facecolors='k', s=80, zorder=10)\n",
    "line_warm[0,:]=0\n",
    "ax1.plot(line_warm[:,0],line_warm[:,1],'--', c='k', lw=1.5,zorder=0)\n",
    "\n",
    "\n",
    "paths=['pulse_rev_cs_1500ppm_5300GtC_50GtS_5ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_250GtS_5ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_500GtS_5ka']\n",
    "s_emissions=[50,125,250,500]\n",
    "for ii in range(len(paths)):\n",
    "    path=paths[ii]\n",
    "    s_emission=s_emissions[ii]\n",
    "    maxcool=float(ts_ann_maxchange_df.loc[path, ['maxcool']])  \n",
    "    if path in colors_paper_df.index:\n",
    "        cc=colors_paper_df.loc[path, 'color']\n",
    "    else: \n",
    "        cc='k' \n",
    "    ax2.scatter(s_emission, maxcool, marker='D', edgecolors='k', facecolors=cc, s=80, zorder=10)\n",
    "    ax2.annotate(str(np.round(maxcool,1)) ,xy=(s_emission,maxcool), xytext=(-35, -13), textcoords='offset pixels', fontsize=12,color='k') \n",
    " \n",
    "    \n",
    "    line_cool_s[ii+1,0]=s_emission\n",
    "    line_cool_s[ii+1,1]=maxcool\n",
    "ax2.scatter(0, 0, marker='D', edgecolors='k', facecolors='k', s=80, zorder=10)\n",
    "line_cool_s[0,:]=0\n",
    "ax2.plot(line_cool_s[:,0],line_cool_s[:,1],'--', c='k', lw=1.5,zorder=0)\n",
    "\n",
    "paths=['pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka',\n",
    "        'pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka']\n",
    "s_emissions=[125,250,500]\n",
    "for ii in range(len(paths)):\n",
    "    path=paths[ii]\n",
    "    s_emission=s_emissions[ii]\n",
    "    maxcool=float(ts_ann_maxchange_df.loc[path, ['maxcool']])  \n",
    "    if path in colors_paper_df.index:\n",
    "        cc=colors_paper_df.loc[path, 'color']\n",
    "    else: \n",
    "        cc='k' \n",
    "    ax2.scatter(s_emission, maxcool, marker='^', edgecolors='k', facecolors=cc, s=80, zorder=10)\n",
    "    ax2.annotate(str(np.round(maxcool,1)) ,xy=(s_emission,maxcool), xytext=(+2.5, +7.5), textcoords='offset pixels', fontsize=12,color='k') \n",
    "    \n",
    "    line_cool_l[ii+1,0]=s_emission\n",
    "    line_cool_l[ii+1,1]=maxcool\n",
    "#ax2.scatter(0, 0, marker='^', edgecolors='k', facecolors='k', s=80, zorder=10)\n",
    "line_cool_l[0,:]=0\n",
    "ax2.plot(line_cool_l[:,0],line_cool_l[:,1],':', c='k', lw=1.5,zorder=0)\n",
    "\n",
    "\n",
    "\n",
    "ax1.set_xticks([0,2500,5300,7500]);\n",
    "ax1.set_ylim([-0.5,4.7])  \n",
    "ax1.set_ylabel(r'$\\mathsf{\\Delta T_{max,w}}$ ($\\mathsf{^{\\circ}C}$)', fontsize=12, color='tab:red'); #$\\Delta$ SAT\n",
    "ax1.tick_params(labelsize=12)\n",
    "#ax1.tick_params(axis='x', direction='in', pad=-15)\n",
    "#ax1.tick_params(axis='x', direction='in', pad=-15)\n",
    "#ax1.set_xticklabels(['0','2500','5300', '7500 GtC  '])\n",
    "ax1.set_xlabel('$\\mathsf{M_{c,t}}$ (GtC)', fontsize=13)\n",
    "ax1.set_yticks([0,1,2,3,4])\n",
    "ax1.set_yticklabels(['0','$+1$','$+2$', '$+3$', '$+4$'])\n",
    "ax2.set_xticks([0,50,125,250,500]);\n",
    "ax2.set_yticks([0,-5,-10,-15,-20,-25,-30])\n",
    "ax2.set_yticklabels(['0','$-5$','$-10$', '$-15$', '$-20$', '$-25$', '$-30$'])\n",
    "ax2.set_ylim([-30,2.5])\n",
    "ax2.set_xlim([-30,525])\n",
    "ax2.set_xlabel('$\\mathsf{M_{s,t}}$ (GtS)', fontsize=13)\n",
    "ax2.xaxis.set_label_position('top') \n",
    "ax2.set_ylabel(r'$\\mathsf{\\Delta T_{max,c}}$ ($\\mathsf{^{\\circ}C}$)', fontsize=12, color='tab:blue'); #$\\Delta$ SAT\n",
    "#ax2.set_xticklabels(['0','50','125', '250','500 GtS'])\n",
    "ax2.tick_params(labelsize=12)\n",
    "#ax2.tick_params(axis='x', direction='in', top=True, bottom=False, labeltop=True, labelbottom=False, pad=-20)\n",
    "ax2.tick_params(axis='x', direction='out', top=True, bottom=False, labeltop=True, labelbottom=False)\n",
    "\n",
    "# arrow=matplotlib.patches.FancyArrowPatch(posA=(5600,4.55),posB=(5600,2.3),arrowstyle=matplotlib.patches.ArrowStyle.CurveFilledB(head_length=.15, head_width=.028), lw=2.5, mutation_scale=100, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "# ax1.add_patch(arrow)\n",
    "# #ax1.text(5700, 3.075, 'initial $\\mathsf{pCO_2}$', rotation=0, fontsize=12)\n",
    "# ax1.text(5500, 4.65, 'initial $\\mathsf{pCO_2}$', rotation=0, fontsize=12)\n",
    "# ax1.text(5750, 2.44, '2000$\\,$ppm', rotation=0, fontsize=10)\n",
    "# ax1.text(5750, 4.35, '1000$\\,$ppm', rotation=0, fontsize=10)\n",
    "\n",
    "arrow=matplotlib.patches.FancyArrowPatch(posA=(5600,2.5),posB=(5600,4.6),arrowstyle=matplotlib.patches.ArrowStyle.CurveFilledB(head_length=.15, head_width=.028), lw=2.5, mutation_scale=100, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "ax1.add_patch(arrow)\n",
    "#ax1.text(5700, 3.075, 'initial $\\mathsf{pCO_2}$', rotation=0, fontsize=12)\n",
    "ax1.text(5525, 2.2, 'initial $\\mathsf{pCO_2}$', rotation=0, fontsize=12)\n",
    "ax1.text(5725, 4.35, '1000$\\,$ppm', rotation=0, fontsize=10)\n",
    "ax1.text(5725, 2.55, '2000$\\,$ppm', rotation=0, fontsize=10)\n",
    "\n",
    "arrow=matplotlib.patches.FancyArrowPatch(posA=(325, -17.25),posB=(370,-5.0),arrowstyle=matplotlib.patches.ArrowStyle.CurveFilledB(head_length=.15, head_width=.03), lw=2.5, mutation_scale=100, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "ax2.add_patch(arrow)\n",
    "ax2.text(350, -13.9, ' pulse \\n duration', rotation=0, fontsize=12)\n",
    "\n",
    "ax2.text(375, -8.5, '6000$\\,$yr', rotation=0, fontsize=10)\n",
    "ax2.text(340, -17.2, '1200$\\,$yr', rotation=0, fontsize=10)\n",
    "ax2.text(275, -33.5, '********************\\n    Snowball Earth', rotation=0, fontsize=12)\n",
    "\n",
    "ax1.text(-0.175,0.985,'(a)',transform=ax1.transAxes,fontsize=13)\n",
    "ax2.text(-0.175,0.985,'(b)',transform=ax2.transAxes,fontsize=13)\n",
    "\n",
    "\n",
    "ax1.arrow(-470, 0, 0, 4.2 ,fc='tab:red', ec='tab:red', alpha=1, width=110, head_width=300, head_length=0.5,length_includes_head=True,) # shape='right'\n",
    "ax2.arrow(-29, 0, 0, -24 ,fc='tab:blue', ec='tab:blue', alpha=1, width=6, head_width=17, head_length=3.5,length_includes_head=True,)\n",
    "\n",
    "fig1.tight_layout(h_pad=0.00) #h_pad=0.1\n",
    "\n",
    "\n",
    "fig1.savefig('./plot_pdf_files/Fig2_pulse_rev_warmingcooling.pdf',bbox_inches='tight', pad_inches=0.1, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. S14: Pulse Change of precipitation-evaporation difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/history_p2.nc\"\n",
    "let a=ts_ann[i=@ave,j=@ave, l=@sbx:100]\n",
    "let b=a[l=@min]-a\n",
    "!list b[l=@loc:0]\n",
    "!shade ts_ann[l=1656]-ts_ann[l=1]\n",
    "let ts_ini_f=ts_ann[l=1]\n",
    "let ts_diff_maxcool_f=ts_ann[l=1606:1706@ave]-ts_ann[l=1] !1656\n",
    "!shade ts_ann[l=1606:1706@ave]\n",
    "!contour/over/levels=(-15) ts_ann[l=1614:1714@ave]\n",
    "\n",
    "let c=a[l=@max]-a\n",
    "!list c[l=@loc:0]\n",
    "!shade ts_ann[l=5450]-ts_ann[l=1]\n",
    "let ts_maxwarm_f=ts_ann[l=5400:5500@ave]\n",
    "let ts_diff_maxwarm_f=ts_ann[l=5400:5500@ave]-ts_ann[l=1] !5450\n",
    "!let prc_diff_maxwarm_f=360*(prc_ann[l=5400:5500@ave]-prc_ann[l=1]) !5450\n",
    "!shade slp_jja[l=5400:5500@ave]-slp_jja[l=1]\n",
    "!contour/over ts_jja[l=5400:5500@ave]-ts_jja[l=1]\n",
    "let prc_diff_maxwarm_f=((prc_ann[l=5400:5500@ave]-e_ann[l=5400:5500@ave])-(prc_ann[l=1]-e_ann[l=1])) !5450\n",
    "let prc_diff_maxcool_f=((prc_ann[l=1606:1706@ave]-e_ann[l=1606:1706@ave])-(prc_ann[l=1]-e_ann[l=1]))\n",
    "let prc_end_f=prc_ann[l=5400:5500@ave]\n",
    "let prc_cool_f=prc_ann[l=1606:1706@ave]\n",
    "\n",
    "!set viewport ul\n",
    "!shade ts_diff_maxwarm_f\n",
    "!set viewpoert ur\n",
    "!plot ts_diff_maxwarm_f[y=23N]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ini_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_maxwarm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_diff_maxwarm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_diff_maxcool_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: prc_diff_maxwarm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: prc_diff_maxcool_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: prc_end_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: prc_cool_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata ts_ini_f = ts_ini_f\n",
    "%ferret_getdata ts_maxwarm_f = ts_maxwarm_f\n",
    "%ferret_getdata ts_diff_maxwarm_f = ts_diff_maxwarm_f\n",
    "%ferret_getdata ts_diff_maxcool_f = ts_diff_maxcool_f\n",
    "%ferret_getdata prc_diff_maxwarm_f = prc_diff_maxwarm_f\n",
    "%ferret_getdata prc_diff_maxcool_f = prc_diff_maxcool_f\n",
    "%ferret_getdata prc_end_f = prc_end_f\n",
    "%ferret_getdata prc_cool_f = prc_cool_f\n",
    "\n",
    "ts_ini_1500ppm=np.rot90(ts_ini_f['data'][:,:,0,0,0,0])\n",
    "ts_maxwarm=np.rot90(ts_maxwarm_f['data'][:,:,0,0,0,0])\n",
    "ts_diff_maxwarm=np.rot90(ts_diff_maxwarm_f['data'][:,:,0,0,0,0])\n",
    "ts_diff_maxcool=np.rot90(ts_diff_maxcool_f['data'][:,:,0,0,0,0])\n",
    "prc_diff_maxwarm=np.rot90(prc_diff_maxwarm_f['data'][:,:,0,0,0,0])\n",
    "prc_diff_maxcool=np.rot90(prc_diff_maxcool_f['data'][:,:,0,0,0,0])\n",
    "prc_end=np.rot90(prc_end_f['data'][:,:,0,0,0,0])\n",
    "prc_cool=np.rot90(prc_cool_f['data'][:,:,0,0,0,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1=jplt.plot_world(360*prc_diff_maxwarm, varname='$\\Delta$(PRC-E)',  units='mm/a', lim_l=-500., lim_u=700, cbar_delta=100, cbar_tick_freq=1,\\\n",
    "                     projection='moll', title='Precipitation-Evaporation Change', var_digits=0, colourmap='Spectral_shifted', \\\n",
    "                     cont='on', var_cont=360*prc_end, cont_levs=[600, 1800], var_cont_digits=0, var_cont_name='ann. $\\mathsf{PRC_{end}}$', var_cont_unit='mm/a', cont_label_fmt='%d', linestyle='dashed')[1] \n",
    "# , cbar_tick_freq=2, lim_l=1.5, lim_u=6, cbar_delta=0.25, var_cont=ts_diff_maxcool\n",
    "fig1.savefig('./plot_pdf_files/FigS14_pulse_rev_1500ppm_PRC_EVAP_Change.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %%ferret\n",
    "# cancel data/all\n",
    "# use \"./climber/pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka/TIMERES/all_snapshots_mom_annual.nc\"\n",
    "\n",
    "# let temp_diff_maxcool_f=temp[i=0,l=111:121@ave]-temp[i=0,l=1] !116\n",
    "# let temp_diff_maxwarm_f=temp[i=0,l=490:500@ave]-temp[i=0,l=1] !495\n",
    "\n",
    "# let a=temp[l=490:500@ave]-temp[l=1] \n",
    "# !shade a[k=@max] !!! max warming in the water column\n",
    "# !list a[i=@ave,j=@ave,k=@ave]\n",
    "\n",
    "# !list temp[i=0,y=30S:30N@ave,k=1,l=490:500@ave]-temp[i=0,y=30S:30N@ave,k=1,l=1]\n",
    "# !list temp[i=0,y=30S:30N@ave,k=1,l=111:121@ave]-temp[i=0,y=30S:30N@ave,k=1,l=1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: temp_diff_maxcool_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: temp_diff_maxwarm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# %ferret_getdata temp_diff_maxcool_f=temp_diff_maxcool_f\n",
    "# %ferret_getdata temp_diff_maxwarm_f=temp_diff_maxwarm_f\n",
    "# temp_diff_maxcool=np.ma.masked_values(np.rot90(temp_diff_maxcool_f['data'][0,:,::-1,0,0,0]), -1e34);\n",
    "# temp_diff_maxwarm=np.ma.masked_values(np.rot90(temp_diff_maxwarm_f['data'][0,:,::-1,0,0,0]), -1e34);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. 19: Change of marine export production in response to aerosol induced cooling and ocean mixing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_rev_s_schmidt_12000MtS_0p44_10yrs/history_p2.nc\"\n",
    "use \"../climber/pulse_rev_s_schmidt_12000MtS_0p44_10yrs/all_snapshots_mom_annual.nc\"\n",
    "use \"../climber/pulse_rev_s_schmidt_12000MtS_0p44_10yrs/history.nc\"\n",
    "!sh da\n",
    "let tsann_schmidt_10yr_f=ts_ann[i=@ave,j=@ave,l=501:600,d=1]\n",
    "let phosph_schmidt_10yr_f=tracer_06[i=@ave,j=@ave,z=1:100@ave,d=2]\n",
    "let proyear_schmidt_10yr_f=proyear[i=@din,y=@din,l=1:100,d=2]\n",
    "let proyear_lowlat_schmidt_10yr_f=proyear[i=@din,y=45S:45N@din,l=1:100,d=2]\n",
    "let proyear_hilat_schmidt_10yr_f=proyear[i=@din,y=90S:45S@din,l=1:100,d=2]+proyear[i=@din,y=45N:90N@din,l=1:100,d=2]\n",
    "\n",
    "let a=abs(glb_over[d=3])\n",
    "!let glob_over_f=a[k=@ave,j=@ave,l=501:5500@sbx:100,d=1]\n",
    "!Georg: MOC usually measured as strength below 500m; Black 2018 also measured it like the maximum strength on NH below 500m ->  for our continental config. on SH\n",
    "let glob_over_schmidt_10yr_f=a[z=500:4000@max, y=90S:0S@max,l=501:600@sbx:10]\n",
    "\n",
    "!set viewport ul\n",
    "!plot ts_ann[i=@ave,j=@ave,l=500:600,d=1]\n",
    "!set viewport ll\n",
    "!plot glob_over_schmidt_10yr_f\n",
    "!plot hmxl[i=@ave,j=@ave,l=1:100,d=2]\n",
    "!set viewport lr\n",
    "!plot proyear_hilat_schmidt_10yr_f\n",
    "!plot proyear[i=@din,y=@din,l=1:100,d=2]\n",
    "!plot/over proyear[i=@din,y=40S:40N@din,l=1:100,d=2]\n",
    "!!plot tracer_06[i=@ave,j=@ave,z=1:100@ave,d=2]\n",
    "\n",
    "!shade temp[k=1,l=1,d=2]-temp[k=1,l=1,d=1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: tsann_schmidt_10yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: phosph_schmidt_10yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: proyear_schmidt_10yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: proyear_lowlat_schmidt_10yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: proyear_hilat_schmidt_10yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: glob_over_schmidt_10yr_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata tsann_schmidt_10yr_f=tsann_schmidt_10yr_f\n",
    "%ferret_getdata phosph_schmidt_10yr_f=phosph_schmidt_10yr_f\n",
    "%ferret_getdata proyear_schmidt_10yr_f=proyear_schmidt_10yr_f\n",
    "%ferret_getdata proyear_lowlat_schmidt_10yr_f=proyear_lowlat_schmidt_10yr_f\n",
    "%ferret_getdata proyear_hilat_schmidt_10yr_f=proyear_hilat_schmidt_10yr_f\n",
    "%ferret_getdata glob_over_schmidt_10yr_f=glob_over_schmidt_10yr_f\n",
    "\n",
    "tsann_schmidt_10yr=tsann_schmidt_10yr_f['data'][0,0,0,:,0,0]; \n",
    "phosph_schmidt_10yr=phosph_schmidt_10yr_f['data'][0,0,0,:,0,0]; \n",
    "proyear_schmidt_10yr=proyear_schmidt_10yr_f['data'][0,0,0,:,0,0]; \n",
    "proyear_lowlat_schmidt_10yr=proyear_lowlat_schmidt_10yr_f['data'][0,0,0,:,0,0]; \n",
    "proyear_hilat_schmidt_10yr=proyear_hilat_schmidt_10yr_f['data'][0,0,0,:,0,0]; \n",
    "glob_over_schmidt_10yr=glob_over_schmidt_10yr_f['data'][0,0,0,:,0,0]; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure(figsize=(5,6))\n",
    "plt.clf()\n",
    "gs = GridSpec(2,1) #,height_ratios=[1,1], width_ratios=[1,0.075,0.075,1]\n",
    "\n",
    "ax2 = plt.subplot(gs[1,0])\n",
    "ax1 = plt.subplot(gs[0,0],sharex=ax2)\n",
    "\n",
    "ax1_1=ax1.twinx()\n",
    "ax2_1=ax2.twinx()\n",
    "\n",
    "years=np.arange(0,100,1)\n",
    "\n",
    "ax1.plot(years,tsann_schmidt_10yr,'k-',lw=2)\n",
    "ax1_1.plot(years[:-10],glob_over_schmidt_10yr[:-10],'-', c='tab:blue',lw=2)\n",
    "ax1.set_ylabel('GMST ($^{\\circ}$C)',fontsize=12)\n",
    "ax1_1.set_ylabel('Overturning (Sv)',fontsize=12, color='tab:blue')\n",
    "\n",
    "\n",
    "ax2.plot(years,proyear_schmidt_10yr,'k-',lw=2, label='global')\n",
    "ax2.plot(years,proyear_lowlat_schmidt_10yr,'k-.',lw=2, label='$\\leq 45^{\\circ} lat$')\n",
    "#ax2.plot(years,proyear_hilat_schmidt_10yr,'-',c='tab:orange',lw=2, label='revised (50yr)')\n",
    "ax2_1.plot(years,phosph_schmidt_10yr, color='tab:blue',lw=2, label='original')\n",
    "\n",
    "ax2.set_xlabel('Time (years)',fontsize=12)\n",
    "ax2.set_ylabel(r'Production ($g/{m^2}\\cdot yr$)',fontsize=12)\n",
    "ax2.legend(frameon=False)\n",
    "ax2.set_xlim(0,100)\n",
    "ax2_1.set_ylabel(r'Phosphate ($\\mu mol/l$)',fontsize=12, color='tab:blue' )\n",
    "\n",
    "#ax0.text(-0.125,1,'(a)',transform=ax0.transAxes,fontsize=12)\n",
    "ax1.text(-0.2,1,'(a)',transform=ax1.transAxes,fontsize=12)\n",
    "ax2.text(-0.2,1,'(b)',transform=ax2.transAxes,fontsize=12)\n",
    "\n",
    "\n",
    "plt.tight_layout() #h_pad=-4.25, w_pad=-2\n",
    "\n",
    "fig.savefig('./plot_pdf_files/FigS19_overturning_productivity.pdf',bbox_inches='tight', pad_inches=0.05) #, dpi=900\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. S12: Pulse pCO2 timeseries and maximum increase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plot pco2diag Timeseries and maximal pco2diag-change for all short pulse runs\n",
    "\n",
    "with open('historyp2_tsann_pco2diag_rev.pickle', 'rb') as f:  \n",
    "        ts_anns_minmax, ts_anns_runmeans, pco2_minmax,pco2_runmeans, ts_anns_nobiogeo, ppms_nobiogeo = pickle.load(f, encoding='latin1')\n",
    "\n",
    "fig1=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax1=fig1.add_subplot(111)\n",
    "ax1.grid(linestyle=':', zorder=0)\n",
    "\n",
    "fig2=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax2=fig2.add_subplot(111)\n",
    "ax2.grid(linestyle=':', zorder=0)\n",
    "\n",
    "times=np.arange(0,12500,1)\n",
    "line_co2_inc=[]; line_co2_em=[]\n",
    "\n",
    "years=np.arange(1,5001,1)\n",
    "filename='../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/carbon_emission_1200y_5300GtC.dat'\n",
    "years_c, c_rate=np.loadtxt(filename, unpack=True)\n",
    "ax1.plot(years,c_rate*100, '--',c='k',lw=1, zorder=2, label='Forcing (a.u.)')\n",
    "\n",
    "for scenario in ['short']: #, 'long'\n",
    "    if scenario=='short':\n",
    "        with open('historyp2_tsann_pco2diag_rev.pickle', 'rb') as f:  \n",
    "            ts_anns_minmax, ts_anns_runmeans, pco2_minmax,pco2_runmeans, ts_anns_nobiogeo, ppms_nobiogeo = pickle.load(f, encoding='latin1')\n",
    "            #paths=paths_pulse_control+paths_pulse_c_short_base+paths_pulse_cs_short+paths_pulse_s_short\n",
    "            paths=paths_pulse_control+paths_pulse_c_short_base+['pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka','pulse_rev_s_1500ppm_125GtS_5ka']\n",
    "            paths_sel=['pulse_control_1500ppm', 'pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka','pulse_rev_s_1500ppm_125GtS_5ka']+paths_pulse_c_short_base\n",
    "\n",
    "#     elif scenario=='long':\n",
    "#         with open('historyp2_long_tsann_pco2diag_corr.pickle', 'rb') as f:  \n",
    "#             ts_anns_minmax, ts_anns_runmeans, pco2_minmax,pco2_runmeans, ts_anns_nobiogeo, ppms_nobiogeo = pickle.load(f, encoding='latin1')\n",
    "#         paths=paths_pulse_long\n",
    "        #x_lim=12500\n",
    "#paths=paths_pulse_control+paths_pulse_c_short_base+paths_pulse_cs_short+paths_pulse_s_short\n",
    "#paths_sel=['pulse_control_1500ppm', 'pulse_cs_1500ppm_5300GtC_100GtS_5ka','pulse_s_1500ppm_100GtS_5ka']+paths_pulse_c_short_base\n",
    "    for i in range(len(paths)):\n",
    "        path=paths[i]\n",
    "\n",
    "#         if path in paths_pulse_cs_short:\n",
    "#             mark='^'; linestyle='-'\n",
    "#         elif path in paths_pulse_s_short:\n",
    "#             mark='x'; linestyle='--'\n",
    "#         elif path in paths_pulse_control:\n",
    "#             linestyle='--'; mark='*'\n",
    "#         else:\n",
    "#             mark='o'; linestyle='-'\n",
    "            \n",
    "        if path in paths_pulse_control:\n",
    "            mark='*'; linestyle='--'\n",
    "        elif path in paths_pulse_c_short_base+paths_pulse_c_long:\n",
    "            mark='o'; linestyle='-.' \n",
    "        elif path in paths_pulse_s_short:\n",
    "            mark='x'; linestyle='--'\n",
    "        elif path in paths_pulse_s_long:\n",
    "            mark='+'; linestyle='--'\n",
    "        elif path in paths_pulse_cs_short:\n",
    "            mark='^'; linestyle='-'\n",
    "        elif path in paths_pulse_cs_long:\n",
    "            mark='v'; linestyle='-'       \n",
    "            \n",
    "        \n",
    "\n",
    "        c_emission=ts_anns_minmax[i,0]; pco2_diff=pco2_minmax[i,5]\n",
    "        pco2_ini=pco2_minmax[i,1]; pco2_end=pco2_minmax[i,2]\n",
    "        ts_ini=ts_anns_minmax[i,2]; ts_end=ts_anns_minmax[i,3]\n",
    "        \n",
    "        if path in ['pulse_control_1500ppm','pulse_c_1500ppm_2500GtC_5ka','pulse_c_1500ppm_5300GtC_5ka', \\\n",
    "                    'pulse_c_1500ppm_7500GtC_5ka']:\n",
    "            if path in ['pulse_control_1500ppm']:\n",
    "                line_co2_inc.append(pco2_minmax[i,3]-pco2_minmax[i,1]); line_co2_em.append(c_emission);\n",
    "            else:\n",
    "                line_co2_inc.append(pco2_diff); line_co2_em.append(c_emission);\n",
    "        ax2.plot(line_co2_em[:],line_co2_inc[:],'--', c='tab:gray', lw=1,zorder=0)\n",
    "\n",
    "        if path in colors_paper_df:\n",
    "            ccc=colors_paper_df.loc[path, 'color']\n",
    "        else:\n",
    "            ccc=colors_df.loc[path, 'color']\n",
    "        \n",
    "        if path in paths_sel and scenario=='short':\n",
    "            if path in paths_pulse_cs or path in paths_pulse_s:\n",
    "                path_label='pulse'+path[9:]\n",
    "            else:\n",
    "                path_label=path\n",
    "                \n",
    "            if path in colors_paper_df.index:\n",
    "                ccc=colors_paper_df.loc[path, 'color']\n",
    "            else:\n",
    "                ccc=colors_df.loc[path, 'color']\n",
    "            ax1.plot(times[0:5000], pco2_runmeans[i,:], label=path_label, alpha=0.8, c=ccc, linestyle=linestyle, lw=2)\n",
    "                \n",
    "        if path=='pulse_control_1500ppm': \n",
    "            ax2.scatter(c_emission, pco2_minmax[i,3]-pco2_minmax[i,1], c=ccc, marker=mark) \n",
    "            \n",
    "         \n",
    "        if path in paths_pulse_c_short+paths_pulse_cs_short+paths_pulse_c_long+paths_pulse_cs_long and path not in paths_pulse_cs_irreg:\n",
    "            ax2.scatter(c_emission, pco2_diff, c=ccc, marker=mark)\n",
    "            #ax33.scatter(pco2_ini, ts_ini, c=color_list[i], marker=mark)\n",
    "            #ax33.scatter(pco2_end, ts_end, c=color_list[i], marker=mark)\n",
    "            if path in ['pulse_c_1500ppm_2500GtC_5ka','pulse_c_1500ppm_5300GtC_5ka', 'pulse_c_1500ppm_7500GtC_5ka']:\n",
    "                anno_pos=(-40, 0) #ax2.annotate('%d' % (pco2_diff) ,xy=(c_emission,pco2_diff),xytext=(-40, 0), textcoords='offset pixels', fontsize=12,color=colors_df.loc[path, 'color'])            \n",
    "            #elif path in ['pulse_c_1500ppm_5300GtC_12ka','pulse_c_1000ppm_5300GtC_5ka','pulse_c_2000ppm_5300GtC_5ka']:\n",
    "            #    anno_pos=(+7, -15)\n",
    "            if path in ['pulse_c_1500ppm_2500GtC_5ka','pulse_c_1500ppm_5300GtC_5ka', 'pulse_c_1500ppm_7500GtC_5ka']:\n",
    "            #['pulse_c_1500ppm_2500GtC_5ka', 'pulse_c_1500ppm_7500GtC_5ka','pulse_c_1500ppm_5300GtC_5ka',\\\n",
    "             #          'pulse_c_2000ppm_5300GtC_5ka','pulse_c_1500ppm_5300GtC_12ka']: #'pulse_c_1000ppm_5300GtC_5ka',\n",
    "                ax2.annotate('%d' % (pco2_diff) ,xy=(c_emission,pco2_diff),xytext=anno_pos, textcoords='offset pixels', fontsize=12,color=ccc) \n",
    "        #if path in paths_pulse_control+paths_pulse_s_short+paths_pulse_s_long:\n",
    "        #    ax2.scatter(c_emission, pco2_minmax[i,3]-pco2_minmax[i,1], c=ccc, marker=mark)\n",
    "        #if path=='pulse_s_2000ppm_250GtS_5ka':\n",
    "        #    ax2.annotate('%d' % (pco2_minmax[i,3]-pco2_minmax[i,1]) ,xy=(ts_anns_minmax[i,0],pco2_minmax[i,5]),xytext=(+7, -15), textcoords='offset pixels', fontsize=12,color=colors_df.loc[path, 'color'])\n",
    "            #ax2.annotate('%d' % (pco2_minmax[-1,3]-pco2_minmax[-1,1]) ,xy=(ts_anns_minmax[-1,0],pco2_minmax[-1,5]),xytext=(+7, -15), textcoords='offset pixels', fontsize=12,color='k')\n",
    "#ax2.annotate('%d' % (pco2_minmax[0,3]-pco2_minmax[0,1]) ,xy=(ts_anns_minmax[0,0],pco2_minmax[0,5]),xytext=(+7, 0), textcoords='offset pixels', fontsize=12,color='k')\n",
    "\n",
    "# for i in range(len(paths_nobiogeo)):\n",
    "#     ax33.scatter(ppms_nobiogeo[i], ts_anns_nobiogeo[i], marker='+', c='k')\n",
    "#     ax33.text(ppms_nobiogeo[i],ts_anns_nobiogeo[i]-0.75,'{:.2f}'.format(ts_anns_nobiogeo[i]),fontsize=8)\n",
    "\n",
    "ax1.set_title('Selected $pCO_2$ Timeseries', fontsize=13);\n",
    "ax1.legend(loc='lower right',ncol=1, fontsize=10, labelspacing=0.1)\n",
    "ax1.set_xlim([0,5000]); ax1.set_ylim([0,4500]);\n",
    "ax1.set_xlabel('Time (years)', fontsize=12); ax1.set_ylabel(r'$pCO_2$ (ppm)', fontsize=12);\n",
    "ax2.set_title('Maximal $pCO_2$ Changes', fontsize=12);\n",
    "ax2.set_xticks([0,2500,5300,7500]);\n",
    "ax2.set_xlabel('Total Carbon Emission (GtC)', fontsize=12);  ax2.set_ylabel(r'$\\Delta\\ pCO_2$ (ppm)', fontsize=12);\n",
    "ax2.text(200,1700,r'$\\bigcirc$=c only'+'\\n'+r'$\\bigtriangleup$=c+s short'+'\\n'+r'$\\bigtriangledown$=c+s long'+'\\n' \\\n",
    "         +r'$\\times$=s only short'+'\\n'+r'$+$=s only long'+'\\n'+r'$\\ast$=control', fontsize=12) #+r'$\\Box$=control'+'\\n'\n",
    "\n",
    "#ax2.text(100,2000,r'$\\bigcirc$=c only'+'\\n'+r'$\\bigtriangleup$=c+s'+'\\n'+r'$\\times$=s only'+'\\n'+r'$\\ast$=control'+'\\n'+r'$\\plus$=no biogeo', fontsize=12)\n",
    "ax1.tick_params(labelsize=12)\n",
    "ax2.tick_params(labelsize=12)\n",
    "#ax33.set_title('Dependence of Equilibrium ts_anns on pco2diag', fontsize=8);\n",
    "#ax33.set_xticks([0,100,250]);\n",
    "#ax33.set_xlabel('pco2diag (ppm)'); ax33.set_ylabel(r'ts_ann (${\\circ}C$)');\n",
    "fig2.tight_layout()\n",
    "fig1.tight_layout()\n",
    "\n",
    "fig1.savefig('./plot_pdf_files/FigS12a_pulse_rev_pco2_timeseries.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)\n",
    "fig2.savefig('./plot_pdf_files/FigS12b_pulse_rev_pco2_change.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figs. S13 and S18: Pulse ocean and marine biogeochemistry change timeseries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/all_snapshots_mom_annual.nc\"\n",
    "let sst_trop_f=temp[i=@ave,y=23S:23N@ave,k=1,l=@sbx:10]\n",
    "let ocean_meantemp_f=temp[i=@ave,j=@ave,k=@ave,l=@sbx:10]\n",
    "let hmxl_ts_f=hmxl[i=@ave,j=@ave,l=@sbx:10]\n",
    "let omega_trop_cs_f=omegaplo_a[i=@ave,y=23S:23N@ave,k=1,l=@sbx:10]\n",
    "!sh da\n",
    "!plot tracer_05[i=@ave,y=@ave,k=1,l=@sbx:10]\n",
    "let proyear_trop_cs_f=proyear[i=@din,y=40S:40N@din,k=1,l=@sbx:10]\n",
    "let proyear_extratrop_cs_f=proyear[i=@din,y=40N:90N@din,k=1,l=@sbx:10]+proyear[i=@din,y=90S:40S@din,k=1,l=@sbx:10]\n",
    "let calex_trop_cs_f=calex[i=@din,y=23S:23N@din,k=1,l=@sbx:10]\n",
    "let calex_extratrop_cs_f=calex[i=@din,y=23N:90N@din,k=1,l=@sbx:10]+calex[i=@din,y=90S:23S@din,k=1,l=@sbx:10]\n",
    "let oxy_cs_f=tracer_05[i=@ave,j=@ave,k=@ave,l=@sbx:10]\n",
    "\n",
    "let oxy_cs_ini_f=tracer_05[k=@min,l=1:10@ave]\n",
    "let oxy_cs_cool_f=tracer_05[k=@min,l=110:120@ave]\n",
    "let oxy_cs_warm_f=tracer_05[k=@min,l=490:500@ave]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sst_trop_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ocean_meantemp_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: hmxl_ts_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: omega_trop_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: proyear_trop_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: proyear_extratrop_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: calex_trop_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: calex_extratrop_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: oxy_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: oxy_cs_ini_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: oxy_cs_cool_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: oxy_cs_warm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata sst_trop_f = sst_trop_f\n",
    "%ferret_getdata ocean_meantemp_f = ocean_meantemp_f\n",
    "%ferret_getdata hmxl_ts_f = hmxl_ts_f\n",
    "%ferret_getdata omega_trop_cs_f = omega_trop_cs_f\n",
    "%ferret_getdata proyear_trop_cs_f = proyear_trop_cs_f\n",
    "%ferret_getdata proyear_extratrop_cs_f = proyear_extratrop_cs_f\n",
    "%ferret_getdata calex_trop_cs_f = calex_trop_cs_f\n",
    "%ferret_getdata calex_extratrop_cs_f = calex_extratrop_cs_f\n",
    "%ferret_getdata oxy_cs_f = oxy_cs_f\n",
    "\n",
    "%ferret_getdata oxy_cs_ini_f = oxy_cs_ini_f\n",
    "%ferret_getdata oxy_cs_cool_f = oxy_cs_cool_f\n",
    "%ferret_getdata oxy_cs_warm_f = oxy_cs_warm_f\n",
    "\n",
    "#sst_trop_f\n",
    "#np.ma.masked_values(np.rot90(omegaplo_a_f['data'][:,:,0,0,0,0]), -1e34)\n",
    "sst_trop=np.ma.masked_values(sst_trop_f['data'][0,0,0,:,0,0], -1e34)\n",
    "ocean_meantemp=np.ma.masked_values(ocean_meantemp_f['data'][0,0,0,:,0,0], -1e34)\n",
    "hmxl_ts=np.ma.masked_values(hmxl_ts_f['data'][0,0,0,:,0,0], -1e34)/100\n",
    "omega_trop_cs=np.ma.masked_values(omega_trop_cs_f['data'][0,0,0,:,0,0], -1e34)\n",
    "proyear_trop_cs=np.ma.masked_values(proyear_trop_cs_f['data'][0,0,0,:,0,0], -1e34)\n",
    "proyear_extratrop_cs=np.ma.masked_values(proyear_extratrop_cs_f['data'][0,0,0,:,0,0], -1e34)\n",
    "calex_trop_cs=np.ma.masked_values(calex_trop_cs_f['data'][0,0,0,:,0,0], -1e34)\n",
    "calex_extratrop_cs=np.ma.masked_values(calex_extratrop_cs_f['data'][0,0,0,:,0,0], -1e34)\n",
    "oxy_cs=np.ma.masked_values(oxy_cs_f['data'][0,0,0,:,0,0], -1e34)\n",
    "\n",
    "oxy_cs_ini=np.ma.masked_values(np.rot90(oxy_cs_ini_f['data'][:,:,0,0,0,0]), -1e34); \n",
    "oxy_cs_cool=np.ma.masked_values(np.rot90(oxy_cs_cool_f['data'][:,:,0,0,0,0]), -1e34); \n",
    "oxy_cs_warm=np.ma.masked_values(np.rot90(oxy_cs_warm_f['data'][:,:,0,0,0,0]), -1e34); "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_c_1500ppm_5300GtC_5ka/all_snapshots_mom_annual.nc\"\n",
    "let sst_trop_c_f=temp[i=@ave,y=23S:23N@ave,k=1,l=@sbx:10]\n",
    "let ocean_meantemp_c_f=temp[i=@ave,j=@ave,k=@ave,l=@sbx:10]\n",
    "let hmxl_ts_c_f=hmxl[i=@ave,j=@ave,l=@sbx:10]\n",
    "let omega_trop_c_f=omegaplo_a[i=@ave,y=23S:23N@ave,k=1,l=@sbx:10]\n",
    "let proyear_trop_c_f=proyear[i=@din,y=40S:40N@din,k=1,l=@sbx:10]\n",
    "let proyear_extratrop_c_f=proyear[i=@din,y=40N:90N@din,k=1,l=@sbx:10]+proyear[i=@din,y=90S:40S@din,k=1,l=@sbx:10]\n",
    "let calex_trop_c_f=calex[i=@din,y=23S:23N@din,k=1,l=@sbx:10]\n",
    "let calex_extratrop_c_f=calex[i=@din,y=23N:90N@din,k=1,l=@sbx:10]+proyear[i=@din,y=90S:23S@din,k=1,l=@sbx:10]\n",
    "let oxy_c_f=tracer_05[i=@ave,j=@ave,k=@ave,l=@sbx:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sst_trop_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ocean_meantemp_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: hmxl_ts_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: omega_trop_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: proyear_trop_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: proyear_extratrop_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: calex_trop_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: calex_extratrop_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: oxy_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata sst_trop_c_f = sst_trop_c_f\n",
    "%ferret_getdata ocean_meantemp_c_f = ocean_meantemp_c_f\n",
    "%ferret_getdata hmxl_ts_c_f = hmxl_ts_c_f\n",
    "%ferret_getdata omega_trop_c_f = omega_trop_c_f\n",
    "%ferret_getdata proyear_trop_c_f = proyear_trop_c_f\n",
    "%ferret_getdata proyear_extratrop_c_f = proyear_extratrop_c_f\n",
    "%ferret_getdata calex_trop_c_f = calex_trop_c_f\n",
    "%ferret_getdata calex_extratrop_c_f = calex_extratrop_c_f\n",
    "%ferret_getdata oxy_c_f = oxy_c_f\n",
    "#sst_trop_f\n",
    "#np.ma.masked_values(np.rot90(omegaplo_a_f['data'][:,:,0,0,0,0]), -1e34)\n",
    "sst_trop_c=np.ma.masked_values(sst_trop_c_f['data'][0,0,0,:,0,0], -1e34)\n",
    "ocean_meantemp_c=np.ma.masked_values(ocean_meantemp_c_f['data'][0,0,0,:,0,0], -1e34)\n",
    "hmxl_ts_c=np.ma.masked_values(hmxl_ts_c_f['data'][0,0,0,:,0,0], -1e34)/100\n",
    "omega_trop_c=np.ma.masked_values(omega_trop_c_f['data'][0,0,0,:,0,0], -1e34)\n",
    "proyear_trop_c=np.ma.masked_values(proyear_trop_c_f['data'][0,0,0,:,0,0], -1e34)\n",
    "proyear_extratrop_c=np.ma.masked_values(proyear_extratrop_c_f['data'][0,0,0,:,0,0], -1e34)\n",
    "calex_trop_c=np.ma.masked_values(calex_trop_c_f['data'][0,0,0,:,0,0], -1e34)\n",
    "calex_extratrop_c=np.ma.masked_values(calex_extratrop_c_f['data'][0,0,0,:,0,0], -1e34)\n",
    "oxy_c=np.ma.masked_values(oxy_c_f['data'][0,0,0,:,0,0], -1e34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/history.nc\"\n",
    "use \"../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/history_isis.nc\"\n",
    "let eta_steric_f=eta_steric[l=501:5500@sbx:100, d=1]\n",
    "let a=abs(glb_over)\n",
    "!let glob_over_f=a[k=@ave,j=@ave,l=501:5500@sbx:100,d=1]\n",
    "! 06/2019: new definition of MOC measure\n",
    "!Georg: MOC usually measured as strength below 500m; Black 2018 also measured it like the maximum strength on NH below 500m ->  for our continental config. on SH\n",
    "let glob_over_f=a[z=500:4000@max, y=90S:0S@max,l=501:5500@sbx:100, d=1]\n",
    "!let ocean_meantemp_f=temp[i=@ave,j=@ave,k=@ave,l=@sbx:10]\n",
    "!sh da\n",
    "!plot ocean_meantemp_f\n",
    "!let max_ini=a[z=500:4000@max, y=90S:0S@max,l=500 ]\n",
    "!set viewport ul\n",
    "!plot/vlimits=0:50 a[z=500:4000@max, y=90S:0S@max,l=501:5500@sbx:100, d=1]\n",
    "!plot/over a[z=500:4000@max, y=0N:90N@max,l=501:5500@sbx:100, d=1]\n",
    "!set viewport ur\n",
    "!plot a[z=500:4000@max,l=500, d=1]\n",
    "!plot/over a[z=500:4000@max,l=5500, d=1]\n",
    "!set viewport lr\n",
    "!plot a[y=90S:0S@max,l=500, d=1]\n",
    "!plot/over a[y=90S:0S@max,l=5500, d=1]\n",
    "\n",
    "!list a[z=500:4000@max, y=90S:0S@max,l=500, d=1]\n",
    "!list a[z=500:4000@max, y=90S:0S@max,l=5500, d=1]\n",
    "\n",
    "!set viewport ll\n",
    "!plot con_g[x=@ave,y=90S:0S@ave, d=2,l=501:5500@sbx:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: eta_steric_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: glob_over_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata eta_steric_f = eta_steric_f\n",
    "%ferret_getdata glob_over_f=glob_over_f\n",
    "eta_steric=np.ma.masked_values(eta_steric_f['data'][0,0,0,:,0,0], -1e34)/100\n",
    "glb_over=np.ma.masked_values(glob_over_f['data'][0,0,0,:,0,0], -1e34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_control_1500ppm/history.nc\"\n",
    "let eta_steric_control_1500ppm_f=eta_steric[l=501:5500@sbx:100]\n",
    "let a=abs(glb_over)\n",
    "!let glob_over_control_1500ppm_f=a[k=@ave,j=@ave,l=501:5500@sbx:100]\n",
    "! 06/2019: new definition of MOC measure\n",
    "!Georg: MOC usually measured as strength below 500m; Black 2018 also measured it like the maximum strength on NH below 500m ->  for our continental config. on SH\n",
    "let glob_over_control_1500ppm_f=a[z=500:4000@max, y=90S:0S@max,l=501:5500@sbx:100]\n",
    "!plot glob_over_control_1500ppm_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: eta_steric_control_1500ppm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: glob_over_control_1500ppm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata eta_steric_control_1500ppm_f = eta_steric_control_1500ppm_f\n",
    "%ferret_getdata glob_over_control_1500ppm_f = glob_over_control_1500ppm_f\n",
    "eta_steric_control_1500ppm=np.ma.masked_values(eta_steric_control_1500ppm_f['data'][0,0,0,:,0,0], -1e34)/100\n",
    "glob_over_control_1500ppm=np.ma.masked_values(glob_over_control_1500ppm_f['data'][0,0,0,:,0,0], -1e34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_c_1500ppm_5300GtC_5ka/history.nc\"\n",
    "let eta_steric_c_f=eta_steric[l=501:5500@sbx:100]\n",
    "let a=abs(glb_over)\n",
    "!let glob_over_c_f=a[k=@ave,j=@ave,l=501:5500@sbx:100]\n",
    "! 06/2019: new definition of MOC measure\n",
    "!Georg: MOC usually measured as strength below 500m; Black 2018 also measured it like the maximum strength on NH below 500m ->  for our continental config. on SH\n",
    "let glob_over_c_f=a[z=500:4000@max, y=90S:0S@max,l=501:5500@sbx:100]\n",
    "!plot glob_over_c_f\n",
    "!list glob_over_c_f[l=@min]/glob_over_c_f[l=501]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: eta_steric_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: glob_over_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata eta_steric_c_f = eta_steric_c_f\n",
    "%ferret_getdata glob_over_c_f=glob_over_c_f\n",
    "eta_steric_c=np.ma.masked_values(eta_steric_c_f['data'][0,0,0,:,0,0], -1e34)/100\n",
    "glb_over_c=np.ma.masked_values(glob_over_c_f['data'][0,0,0,:,0,0], -1e34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/history_p2.nc\"\n",
    "let prc_times_f=(prc_ann[i=@ave,j=@ave,l=501:5500@sbx:100])*360"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: prc_times_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata prc_times_f = prc_times_f\n",
    "prc_times=np.ma.masked_values(prc_times_f['data'][0,0,0,:,0,0], -1e34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_c_1500ppm_5300GtC_5ka/history_p2.nc\"\n",
    "let prc_times_c_f=(prc_ann[i=@ave,j=@ave,l=501:5500@sbx:100])*360"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: prc_times_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata prc_times_c_f = prc_times_c_f\n",
    "prc_times_c=np.ma.masked_values(prc_times_c_f['data'][0,0,0,:,0,0], -1e34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/history_isis.nc\"\n",
    "!shade con_g[i=@ave,l=501:5500@sbx:100]\n",
    "let ice_lat_f=con_g[i=@ave,y=90S:0S@loc:0.1,l=501:5500@sbx:100] \n",
    "!plot ice_lat_f\n",
    "!let con_g_times_f=(con_g[i=@ave,j=@ave,l=501:5500@sbx:100])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ice_lat_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata ice_lat_f = ice_lat_f\n",
    "#ice_lat=np.ma.masked_values(ice_lat_f['data'][0,0,0,:,0,0], -1e34)\n",
    "ice_lat=ice_lat_f['data'][0,0,0,:,0,0]\n",
    "ice_lat[ice_lat==-1e34]=-90"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_c_1500ppm_5300GtC_5ka/history_isis.nc\"\n",
    "let ice_lat_c_f=con_g[i=@ave,y=90S:0S@loc:0.1,l=501:5500@sbx:100] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ice_lat_c_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata ice_lat_c_f = ice_lat_c_f\n",
    "ice_lat_c=ice_lat_c_f['data'][0,0,0,:,0,0]\n",
    "ice_lat_c[ice_lat_c==-1e34]=-90"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %%ferret\n",
    "# cancel data/all\n",
    "# use \"./climber/pulse_c_1500ppm_5300GtC_5ka_Eppley/all_snapshots_mom_annual.nc\"\n",
    "# let proyear_trop_c_eppley_f=proyear[i=@din,y=23S:23N@din,k=1,l=@sbx:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %ferret_getdata proyear_trop_c_eppley_f= proyear_trop_c_eppley_f\n",
    "# proyear_trop_c_eppley=np.ma.masked_values(proyear_trop_c_eppley_f['data'][0,0,0,:,0,0], -1e34)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plot\n",
    "fig10=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax10 = fig10.add_subplot(111) \n",
    "ax10.patch.set_visible(False)\n",
    "ax10.set_zorder(10)\n",
    "ax11 = ax10.twinx()\n",
    "ax10.grid(linestyle=':', zorder=0) \n",
    "\n",
    "years=np.arange(1,5001,1)\n",
    "filename='../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/carbon_emission_1200y_5300GtC.dat'\n",
    "years_c, c_rate=np.loadtxt(filename, unpack=True)\n",
    "\n",
    "ax10.plot(years[::10],sst_trop, '-',lw=2, zorder=2, c='tab:red', label='trop. SST ($\\leq 23^{\\circ}$ lat.)')  \n",
    "ax10.plot(years[::10],ocean_meantemp, '-',lw=2, zorder=2, c='tab:blue', label='ave. Seawater Temp.')\n",
    "#ax11.plot(years[::10],omega_trop_cs, '-',lw=2, zorder=2, c='tab:orange', label='trop. surf. $\\Omega_{Ar}$')\n",
    "ax10.plot(years,c_rate*0.6, '--k',lw=1, zorder=2, label='Forcing (a.u.)')\n",
    "ax11.plot(years,eta_steric, '-',lw=2, zorder=2, c='tab:green', label='Steric Sea Level Change')\n",
    "\n",
    "\n",
    "ax10.plot(years[::10],sst_trop_c, '--',lw=1, zorder=2, c='tab:red')  \n",
    "ax10.plot(years[::10],ocean_meantemp_c, '--',lw=1, zorder=2, c='tab:blue')\n",
    "#ax11.plot(years[::10],omega_trop_c, '--',lw=1, zorder=2, c='tab:orange')\n",
    "ax11.plot(years,eta_steric_c, '--',lw=1, zorder=2, c='tab:green')\n",
    "\n",
    "for var in [sst_trop, ocean_meantemp,eta_steric]:\n",
    "    fac=1; ax=ax10\n",
    "    if var is eta_steric:\n",
    "        fac=10; ax=ax11\n",
    "    ax.annotate('%.1f' % (np.round(var[5*fac],1)), xy=(years[5*fac],var[5*fac]), xytext=(+10,-16), textcoords='offset pixels', fontsize=12, color='k') \n",
    "    ax.annotate('%.1f' % (np.round(var[116*fac],1)), xy=(years[1160],var[116*fac]), xytext=(0,-16), textcoords='offset pixels', fontsize=12, color='k') \n",
    "    ax.annotate('%.1f' % (np.round(var[494*fac],1)), xy=(years[4950],var[494*fac]), xytext=(-40,-16), textcoords='offset pixels', fontsize=12, color='k') \n",
    "\n",
    "h2, l2 = ax10.get_legend_handles_labels()\n",
    "h1, l1 = ax11.get_legend_handles_labels()\n",
    "ax10.legend(h1+h2, l1+l2, loc='center right', ncol=1, fontsize=10) #(0.25,0.25)\n",
    "\n",
    "ax10.tick_params(labelsize=12)\n",
    "ax11.tick_params(labelsize=12)\n",
    "ax10.set_xlim([0,5000]); ax10.set_ylim([0,31]) \n",
    "#plt.xticks([700,1000,1500,2000,3000,4000]);\n",
    "#ax10.set_yticks(np.arange(8,32,2))\n",
    "ax10.set_title('Seawater Temperature and Sea Level', fontsize=13)\n",
    "ax10.set_ylabel('Temperature ($^{\\circ}$C)', fontsize=12)\n",
    "ax10.set_xlabel('Time (years)', fontsize=12); \n",
    "ax11.set_ylabel(r'Steric Sea Level Change (m)', fontsize=12)\n",
    "ax11.set_ylim([-2,2])\n",
    "ax11.set_yticks([-2,-1,0,1,2])\n",
    "#ax10.set_yticks(np.arange(8,32,2))\n",
    "plt.tight_layout()\n",
    "\n",
    "fig10.savefig('./plot_pdf_files/FigS13a_pulse_rev_1500ppm_SeaTemp_Level_Timeseries.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plot\n",
    "fig10=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax10 = fig10.add_subplot(111) \n",
    "ax10.patch.set_visible(False)\n",
    "ax10.set_zorder(10)\n",
    "ax11 = ax10.twinx()\n",
    "ax10.grid(linestyle=':', zorder=0) \n",
    "\n",
    "years=np.arange(1,5001,1)\n",
    "filename='../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/carbon_emission_1200y_5300GtC.dat'\n",
    "years_c, c_rate=np.loadtxt(filename, unpack=True)\n",
    "\n",
    "ax10.plot(years[::10],hmxl_ts, '-k',lw=2, zorder=2, c='tab:red', label='Mixed Layer Depth (in m)')  \n",
    "ax11.plot(years,c_rate*2.7-90, '--k',lw=1, zorder=2, label='Forcing (a.u.)')\n",
    "ax11.plot(years,ice_lat, '-k',lw=2, zorder=2, c='tab:blue', label='Max. Latitude of Southern Sea Ice')\n",
    "ax10.plot(years,glb_over, '-k',lw=2, zorder=2, c='tab:green', label='Glob. Overturning (in Sv)')\n",
    "ax10.plot(years,prc_times/10, '-k',lw=2, zorder=2, c='tab:cyan', label='Glob. Mean Precipitation (in 10 mm/yr)')\n",
    "\n",
    "ax10.plot(years[::10],hmxl_ts_c, '--',lw=1, zorder=2, c='tab:red')  \n",
    "ax11.plot(years,ice_lat_c, '--',lw=1, zorder=2, c='tab:blue')\n",
    "ax10.plot(years,glb_over_c, '--',lw=1, zorder=2, c='tab:green')\n",
    "ax10.plot(years,prc_times_c/10, '--',lw=1, zorder=2, c='tab:cyan')\n",
    "\n",
    "# for var in [sst_trop, ocean_meantemp,eta_steric]:\n",
    "#     fac=1; ax=ax10\n",
    "#     if var is eta_steric:\n",
    "#         fac=10; ax=ax11\n",
    "#     ax.annotate('%.1f' % (np.round(var[5*fac],1)), xy=(years[5*fac],var[5*fac]), xytext=(+10,-25), textcoords='offset pixels', fontsize=12, color='k') \n",
    "#     ax.annotate('%.1f' % (np.round(var[116*fac],1)), xy=(years[1160],var[116*fac]), xytext=(0,-25), textcoords='offset pixels', fontsize=12, color='k') \n",
    "#     ax.annotate('%.1f' % (np.round(var[494*fac],1)), xy=(years[4950],var[494*fac]), xytext=(-60,-25), textcoords='offset pixels', fontsize=12, color='k') \n",
    "\n",
    "h2, l2 = ax10.get_legend_handles_labels()\n",
    "h1, l1 = ax11.get_legend_handles_labels()\n",
    "ax10.legend(h1+h2, l1+l2, ncol=1, fontsize=10, bbox_to_anchor=(0.38, 0.53)) #(, loc='best'\n",
    "\n",
    "ax10.tick_params(labelsize=12)\n",
    "ax11.tick_params(labelsize=12)\n",
    "ax10.set_xlim([0,5000]); ax10.set_ylim([0,120]) \n",
    "#plt.xticks([700,1000,1500,2000,3000,4000]);\n",
    "ax11.set_yticks([-90,-75,-60,-45,-30,-15,0,15,30,45])\n",
    "ax10.set_title('Overturning, Sea Ice Extent, Precipitation', fontsize=13)\n",
    "ax10.set_ylabel('(a.u.)', fontsize=12)\n",
    "ax10.set_xlabel('Time (years)', fontsize=12); \n",
    "ax11.set_ylabel(r'Latitude ($^{\\circ}$)', fontsize=12)\n",
    "ax11.set_ylim([-90,45])\n",
    "#ax10.set_yticks(np.arange(8,32,2))\n",
    "plt.tight_layout()\n",
    "\n",
    "fig10.savefig('./plot_pdf_files/FigS13b_pulse_rev_1500ppm_OverturningIcePrecipitation_Timeseries.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plot\n",
    "fig10=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax10 = fig10.add_subplot(111) \n",
    "ax10.patch.set_visible(False)\n",
    "ax10.set_zorder(10)\n",
    "ax11 = ax10.twinx()\n",
    "ax10.grid(linestyle=':', zorder=0) \n",
    "\n",
    "years=np.arange(1,5001,1)\n",
    "filename='../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/carbon_emission_1200y_5300GtC.dat'\n",
    "years_c, c_rate=np.loadtxt(filename, unpack=True)\n",
    "\n",
    "ax10.plot(years[::10],proyear_trop_cs, '-',lw=2, zorder=2, c='tab:red', label=r'Biomass Export Prod. ($<40^{\\circ}$ lat.)')  \n",
    "ax10.plot(years[::10],proyear_extratrop_cs, '-',lw=2, zorder=2, c='tab:blue', label=r'Biomass Export Prod. ($>40^{\\circ}$ lat.)') \n",
    "ax10.plot(years[::10],12*calex_trop_cs, '-',lw=2, zorder=2, c='tab:green', label='trop. Carbonate Export Prod.') \n",
    "#ax10.plot(years[::10],10*calex_extratrop_cs, '-',lw=2, zorder=2, c='tab:olive', label='extratroptrop. Carbonate Export') \n",
    "ax11.plot(years[::10],omega_trop_cs, '-',lw=2, zorder=2, c='tab:orange', label='trop. surf. $\\Omega_{Ar}$ (a.u.)')\n",
    "ax11.plot(years[::10],0.01*oxy_cs, '-',lw=2, zorder=2, c='tab:cyan', label='ave. $[O_2]$ (in 100 $\\mu mol/l$)')\n",
    "ax11.plot(years,c_rate*0.08+1, '--k',lw=1, zorder=2) #, label='Forcing (a.u.)'\n",
    "#ax11.plot(years,eta_steric, '-',lw=2, zorder=2, c='tab:green', label='Steric Sea Level Change')\n",
    "\n",
    "\n",
    "ax10.plot(years[::10],proyear_trop_c, '--',lw=1, zorder=2, c='tab:red')  \n",
    "ax10.plot(years[::10],proyear_extratrop_c, '--',lw=1, zorder=2, c='tab:blue')\n",
    "#ax10.plot(years[::10],proyear_trop_c_eppley[:-1], '--',lw=1, zorder=2, c='tab:pink', label='trop. prim. Prod. (Eppley)') \n",
    "ax11.plot(years[::10],omega_trop_c, '--',lw=1, zorder=2, c='tab:orange')\n",
    "ax10.plot(years[::10],12*calex_trop_c, '--',lw=1, zorder=2, c='tab:green') \n",
    "ax11.plot(years[::10],0.01*oxy_c, '--',lw=1, zorder=2, c='tab:cyan')\n",
    "#ax10.plot(years[::10],calex_extratrop_c, '--',lw=1, zorder=2, c='tab:olive') \n",
    "#ax11.plot(years,eta_steric_c, '--',lw=1, zorder=2, c='tab:green')\n",
    "\n",
    "for var in [omega_trop_cs]:\n",
    "    fac=1; ax=ax11\n",
    "    #if var is eta_steric:\n",
    "       # fac=10; ax=ax11\n",
    "    ax.annotate('%.2f' % (np.round(np.max(var),2)), xy=(years[5*fac],var[5*fac]), xytext=(+10,-14), textcoords='offset pixels', fontsize=12, color='k') \n",
    "    ax.annotate('%.2f' % (np.round(np.min(var),2)), xy=(years[1439],var[144*fac]), xytext=(-30,-12), textcoords='offset pixels', fontsize=12, color='k') \n",
    "    ax.annotate('%.2f' % (np.round(var[494*fac],2)), xy=(years[4950],var[494*fac]), xytext=(-40,-14), textcoords='offset pixels', fontsize=12, color='k') \n",
    "for var in [oxy_cs]:\n",
    "    fac=1; ax=ax11\n",
    "    #if var is eta_steric:\n",
    "       # fac=10; ax=ax11\n",
    "    ax.annotate('%d' % (np.round(var[5*fac])), xy=(years[5*fac],0.01*var[5*fac]), xytext=(+10,+5), textcoords='offset pixels', fontsize=12, color='k') \n",
    "    ax.annotate('%d' % (np.round(np.max(var[144*fac]))), xy=(10*years[np.where(var==np.max(var))],0.01*var[144*fac]), xytext=(0,+6), textcoords='offset pixels', fontsize=12, color='k') \n",
    "    ax.annotate('%d' % (np.round(var[494*fac])), xy=(years[4950],0.01*var[494*fac]), xytext=(-40,+5), textcoords='offset pixels', fontsize=12, color='k') \n",
    "\n",
    "    \n",
    "h2, l2 = ax10.get_legend_handles_labels()\n",
    "h1, l1 = ax11.get_legend_handles_labels()\n",
    "ax10.legend(h1+h2, l1+l2, loc='upper right', ncol=1, fontsize=10, labelspacing=0.0, frameon=False) #(0.25,0.25)\n",
    "\n",
    "ax10.tick_params(labelsize=12)\n",
    "ax11.tick_params(labelsize=12)\n",
    "ax10.set_xlim([0,5000]); \n",
    "ax10.set_ylim([-1.0e14,3.5e14]) \n",
    "ax10.set_yticks(np.arange(0.5e14,4e14,0.5e14))\n",
    "ax11.set_yticks([1,2,3])\n",
    "#plt.xticks([700,1000,1500,2000,3000,4000]);\n",
    "#ax10.set_yticks(np.arange(8,32,2))\n",
    "ax10.set_title('Marine Biogeochemistry Characteristics', fontsize=13)\n",
    "ax10.set_ylabel('Production $g/(m^2\\cdot yr)$', fontsize=12)\n",
    "ax10.set_xlabel('Time (years)', fontsize=12); \n",
    "ax11.set_ylabel(r'(a.u.)', fontsize=12)\n",
    "ax11.set_ylim([1,6])\n",
    "#ax10.set_yticks(np.arange(8,32,2))\n",
    "plt.tight_layout()\n",
    "\n",
    "fig10.savefig('./plot_pdf_files/FigS18_pulse_rev_1500ppm_BiogeoCharacteristicTimeseries.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figs. S15, S16 and S17: Pulse change of ocean pH and carbonate saturation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "code_folding": [
     0
    ],
    "scrolled": true
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: dc13_mean_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: dc13_mean_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: omega_trop_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: dc13_mean_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: omega_trop_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: dc13_mean_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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   ],
   "source": [
    "### read out biogeo_df from all_snapshots_mom_annual.nc\n",
    "paths=paths_pulse_control+paths_pulse_c_short_base+['pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka']\n",
    "#paths=paths_pulse_control+paths_pulse_c_short_base+\\\n",
    "#    paths_pulse_cs_short+paths_pulse_cs_long\n",
    "#+\\\n",
    "#    paths_pulse_s_short+paths_pulse_s_long #+paths_pulse_s_long\n",
    "#+paths_pulse_c_short_extra_13c+paths_pulse_c_long\n",
    "\n",
    "#paths=paths_pulse_control+paths_pulse_c_short_base\n",
    "biogeo_df=pd.DataFrame([], columns=['ph_mean','omega_trop','dp13', 'dc13', 'years'], index=paths) #, dtype=float[], columns=['dp13_ts_globmean', 'years'], index=[]\n",
    "\n",
    "for path in paths: \n",
    "    #nc_f = '../'+path+'/TIMERES/all_snapshots_mom_annual.nc'\n",
    "    #nc_fid = Dataset(nc_f, 'r')\n",
    "    #nc_attrs, nc_dims, nc_vars = ncdump(nc_fid)\n",
    "    #var_ts=nc_fid.variables[var][:,0,::-1,:]\n",
    "    #dates=num2date(nc_fid.variables['Time'][:], units=nc_fid.variables['Time'].units, calendar=nc_fid.variables['Time'].calendar)\n",
    "    #years_strings=[time.strftime('%Y') for time in dates]\n",
    "    #years=np.array(list(map(int,years_strings)))\n",
    "    #times=[time.timetuple().tm_year for time in test]\n",
    "    \n",
    "    if path in paths_pulse_control:\n",
    "        years=np.arange(0,13000,100)\n",
    "    else:\n",
    "        years=np.arange(0,5000,10)\n",
    "\n",
    "    #path='c3beta_tria_200Ma_'+str(pco2[i])+'ppm'\n",
    "    if path in paths_pulse_control+paths_pulse_c_long+paths_pulse_cs_long:\n",
    "        sbx_range=1\n",
    "    else:\n",
    "        sbx_range=10\n",
    "    %ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/all_snapshots_mom_annual.nc\"; \\\n",
    "            let ph_mean_f=ph[i=@ave,j=@ave,k=1,l=@sbx:%(sbx_range)s];\\\n",
    "            let omega_trop_f=omegaplo_a[i=@ave,y=30S:30N@ave,k=1,l=@sbx:%(sbx_range)s]; \\\n",
    "            let dp13_mean_f=dp13[i=@ave,j=@ave,k=1,l=@sbx:%(sbx_range)s];\\\n",
    "            let dc13_mean_f=dc13[i=@ave,j=@ave,k=1,l=@sbx:%(sbx_range)s]' % locals() #,l=@sbx:%(sbx_range)s; let ph_mean_min_f=a[l=@min]-a[l=1]\n",
    "    %ferret_getdata ph_mean_f=ph_mean_f\n",
    "    %ferret_getdata omega_trop_f=omega_trop_f\n",
    "    %ferret_getdata dp13_mean_f=dp13_mean_f\n",
    "    %ferret_getdata dc13_mean_f=dc13_mean_f\n",
    "    #; let ph_mean_min_f=a[l=@min]-a[l=1]\n",
    "    biogeo_df.loc[path, ['ph_mean','omega_trop', 'dp13', 'dc13','years']]=[np.ma.masked_values(ph_mean_f['data'][0,0,0,:,0,0], -1e34), \\\n",
    "                                                                           np.ma.masked_values(omega_trop_f['data'][0,0,0,:,0,0], -1e34),\\\n",
    "                                                                           np.ma.masked_values(dp13_mean_f['data'][0,0,0,:,0,0], -1e34),\\\n",
    "                                                                           np.ma.masked_values(dc13_mean_f['data'][0,0,0,:,0,0], -1e34),\\\n",
    "                                                                           years] \n",
    "biogeo_df.to_pickle('./biogeo_df_rev.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ph_mean</th>\n",
       "      <th>omega_trop</th>\n",
       "      <th>dp13</th>\n",
       "      <th>dc13</th>\n",
       "      <th>years</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>pulse_control_1000ppm</th>\n",
       "      <td>[7.692365494273341, 7.692418192014194, 7.69248...</td>\n",
       "      <td>[2.1402375027570915, 2.1403875684754743, 2.140...</td>\n",
       "      <td>[-31.29110385755809, -31.30119427309537, -31.3...</td>\n",
       "      <td>[2.380788883810344, 2.3707240694663034, 2.3608...</td>\n",
       "      <td>[0, 100, 200, 300, 400, 500, 600, 700, 800, 90...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_control_1500ppm</th>\n",
       "      <td>[7.599261800261874, 7.599298033430007, 7.59932...</td>\n",
       "      <td>[2.1590793760514018, 2.159360761094911, 2.1593...</td>\n",
       "      <td>[-31.323277377828866, -31.33133327158101, -31....</td>\n",
       "      <td>[2.2949177903995395, 2.2869032675658723, 2.278...</td>\n",
       "      <td>[0, 100, 200, 300, 400, 500, 600, 700, 800, 90...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_control_2000ppm</th>\n",
       "      <td>[7.540781661862346, 7.540805836926754, 7.54083...</td>\n",
       "      <td>[2.234722172930214, 2.2347825376277384, 2.2349...</td>\n",
       "      <td>[-31.395471334122607, -31.401882977014306, -31...</td>\n",
       "      <td>[2.179267471096057, 2.172760368786869, 2.16633...</td>\n",
       "      <td>[0, 100, 200, 300, 400, 500, 600, 700, 800, 90...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_1000ppm_5300GtC_5ka</th>\n",
       "      <td>[--, --, --, --, --, 7.692641980468145, 7.6926...</td>\n",
       "      <td>[--, --, --, --, --, 2.1413078963628323, 2.141...</td>\n",
       "      <td>[--, --, --, --, --, -31.340202648896852, -31....</td>\n",
       "      <td>[--, --, --, --, --, 2.330949477294082, 2.3210...</td>\n",
       "      <td>[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_1500ppm_2500GtC_5ka</th>\n",
       "      <td>[--, --, --, --, --, 7.599416611320305, 7.5994...</td>\n",
       "      <td>[--, --, --, --, --, 2.159836008275365, 2.1599...</td>\n",
       "      <td>[--, --, --, --, --, -31.36303197281804, -31.3...</td>\n",
       "      <td>[--, --, --, --, --, 2.2547347527334023, 2.246...</td>\n",
       "      <td>[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_1500ppm_5300GtC_5ka</th>\n",
       "      <td>[--, --, --, --, --, 7.599414540799288, 7.5994...</td>\n",
       "      <td>[--, --, --, --, --, 2.159826179385031, 2.1599...</td>\n",
       "      <td>[--, --, --, --, --, -31.362791064371436, -31....</td>\n",
       "      <td>[--, --, --, --, --, 2.2546921627365992, 2.246...</td>\n",
       "      <td>[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_1500ppm_7500GtC_5ka</th>\n",
       "      <td>[--, --, --, --, --, 7.5994103871487315, 7.599...</td>\n",
       "      <td>[--, --, --, --, --, 2.1598087698205033, 2.159...</td>\n",
       "      <td>[--, --, --, --, --, -31.363187318675195, -31....</td>\n",
       "      <td>[--, --, --, --, --, 2.254644007776559, 2.2466...</td>\n",
       "      <td>[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_c_2000ppm_5300GtC_5ka</th>\n",
       "      <td>[--, --, --, --, --, 7.540918989623301, 7.5409...</td>\n",
       "      <td>[--, --, --, --, --, 2.235381377225876, 2.2355...</td>\n",
       "      <td>[--, --, --, --, --, -31.42702337386836, -31.4...</td>\n",
       "      <td>[--, --, --, --, --, 2.1472770848886555, 2.140...</td>\n",
       "      <td>[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka</th>\n",
       "      <td>[--, --, --, --, --, 7.599407730803535, 7.5994...</td>\n",
       "      <td>[--, --, --, --, --, 2.159988611596877, 2.1601...</td>\n",
       "      <td>[--, --, --, --, --, -31.362535179917643, -31....</td>\n",
       "      <td>[--, --, --, --, --, 2.254759682422845, 2.2467...</td>\n",
       "      <td>[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                   ph_mean  \\\n",
       "pulse_control_1000ppm                    [7.692365494273341, 7.692418192014194, 7.69248...   \n",
       "pulse_control_1500ppm                    [7.599261800261874, 7.599298033430007, 7.59932...   \n",
       "pulse_control_2000ppm                    [7.540781661862346, 7.540805836926754, 7.54083...   \n",
       "pulse_c_1000ppm_5300GtC_5ka              [--, --, --, --, --, 7.692641980468145, 7.6926...   \n",
       "pulse_c_1500ppm_2500GtC_5ka              [--, --, --, --, --, 7.599416611320305, 7.5994...   \n",
       "pulse_c_1500ppm_5300GtC_5ka              [--, --, --, --, --, 7.599414540799288, 7.5994...   \n",
       "pulse_c_1500ppm_7500GtC_5ka              [--, --, --, --, --, 7.5994103871487315, 7.599...   \n",
       "pulse_c_2000ppm_5300GtC_5ka              [--, --, --, --, --, 7.540918989623301, 7.5409...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka  [--, --, --, --, --, 7.599407730803535, 7.5994...   \n",
       "\n",
       "                                                                                omega_trop  \\\n",
       "pulse_control_1000ppm                    [2.1402375027570915, 2.1403875684754743, 2.140...   \n",
       "pulse_control_1500ppm                    [2.1590793760514018, 2.159360761094911, 2.1593...   \n",
       "pulse_control_2000ppm                    [2.234722172930214, 2.2347825376277384, 2.2349...   \n",
       "pulse_c_1000ppm_5300GtC_5ka              [--, --, --, --, --, 2.1413078963628323, 2.141...   \n",
       "pulse_c_1500ppm_2500GtC_5ka              [--, --, --, --, --, 2.159836008275365, 2.1599...   \n",
       "pulse_c_1500ppm_5300GtC_5ka              [--, --, --, --, --, 2.159826179385031, 2.1599...   \n",
       "pulse_c_1500ppm_7500GtC_5ka              [--, --, --, --, --, 2.1598087698205033, 2.159...   \n",
       "pulse_c_2000ppm_5300GtC_5ka              [--, --, --, --, --, 2.235381377225876, 2.2355...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka  [--, --, --, --, --, 2.159988611596877, 2.1601...   \n",
       "\n",
       "                                                                                      dp13  \\\n",
       "pulse_control_1000ppm                    [-31.29110385755809, -31.30119427309537, -31.3...   \n",
       "pulse_control_1500ppm                    [-31.323277377828866, -31.33133327158101, -31....   \n",
       "pulse_control_2000ppm                    [-31.395471334122607, -31.401882977014306, -31...   \n",
       "pulse_c_1000ppm_5300GtC_5ka              [--, --, --, --, --, -31.340202648896852, -31....   \n",
       "pulse_c_1500ppm_2500GtC_5ka              [--, --, --, --, --, -31.36303197281804, -31.3...   \n",
       "pulse_c_1500ppm_5300GtC_5ka              [--, --, --, --, --, -31.362791064371436, -31....   \n",
       "pulse_c_1500ppm_7500GtC_5ka              [--, --, --, --, --, -31.363187318675195, -31....   \n",
       "pulse_c_2000ppm_5300GtC_5ka              [--, --, --, --, --, -31.42702337386836, -31.4...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka  [--, --, --, --, --, -31.362535179917643, -31....   \n",
       "\n",
       "                                                                                      dc13  \\\n",
       "pulse_control_1000ppm                    [2.380788883810344, 2.3707240694663034, 2.3608...   \n",
       "pulse_control_1500ppm                    [2.2949177903995395, 2.2869032675658723, 2.278...   \n",
       "pulse_control_2000ppm                    [2.179267471096057, 2.172760368786869, 2.16633...   \n",
       "pulse_c_1000ppm_5300GtC_5ka              [--, --, --, --, --, 2.330949477294082, 2.3210...   \n",
       "pulse_c_1500ppm_2500GtC_5ka              [--, --, --, --, --, 2.2547347527334023, 2.246...   \n",
       "pulse_c_1500ppm_5300GtC_5ka              [--, --, --, --, --, 2.2546921627365992, 2.246...   \n",
       "pulse_c_1500ppm_7500GtC_5ka              [--, --, --, --, --, 2.254644007776559, 2.2466...   \n",
       "pulse_c_2000ppm_5300GtC_5ka              [--, --, --, --, --, 2.1472770848886555, 2.140...   \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka  [--, --, --, --, --, 2.254759682422845, 2.2467...   \n",
       "\n",
       "                                                                                     years  \n",
       "pulse_control_1000ppm                    [0, 100, 200, 300, 400, 500, 600, 700, 800, 90...  \n",
       "pulse_control_1500ppm                    [0, 100, 200, 300, 400, 500, 600, 700, 800, 90...  \n",
       "pulse_control_2000ppm                    [0, 100, 200, 300, 400, 500, 600, 700, 800, 90...  \n",
       "pulse_c_1000ppm_5300GtC_5ka              [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...  \n",
       "pulse_c_1500ppm_2500GtC_5ka              [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...  \n",
       "pulse_c_1500ppm_5300GtC_5ka              [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...  \n",
       "pulse_c_1500ppm_7500GtC_5ka              [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...  \n",
       "pulse_c_2000ppm_5300GtC_5ka              [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...  \n",
       "pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka  [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 1...  "
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biogeo_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "code_folding": [
     0
    ],
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### short scenarios: Plot pH-Timeseries, calculate Fit for Control Runs, Determine excursion Amplitude relative to Control runs\n",
    "### and Plot Map of dp13 and dp13-Change for Example-Run \n",
    "\n",
    "biogeo_df = pd.read_pickle(\"./biogeo_df_rev.pkl\")\n",
    "\n",
    "fig1=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax1=fig1.add_subplot(111)\n",
    "ax1.grid(linestyle=':', zorder=0)\n",
    "\n",
    "fig3=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax3=fig3.add_subplot(111)\n",
    "ax3.grid(linestyle=':', zorder=0)\n",
    "\n",
    "ph_regress_df=pd.DataFrame([], columns=['slope', 'intercept'], index=paths_pulse_control, dtype=float) #[], columns=['dp13_ts_globmean', 'years'], index=[]\n",
    "for path in paths_pulse_control:\n",
    "    [ph_mean,years]=biogeo_df.loc[path, ['ph_mean','years'] ]\n",
    "    years=np.arange(0,13000-100,100)\n",
    "    x=np.array(years).astype(np.int); y=np.array(ph_mean).astype(np.float)\n",
    "    slope, intercept, r_value, p_value, std_err = stats.linregress(x,y)\n",
    "    ph_regress_df.loc[path, ['slope','intercept'] ]= [slope,intercept]\n",
    "    #ax1.plot(x,slope*x+intercept, 'k--', alpha=0.8)\n",
    "ppms=np.array([1000,1500,2000])\n",
    "\n",
    "paths_plot=paths_pulse_control+paths_pulse_c_short_base+['pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka']\n",
    "#paths_plot=paths_pulse_c_short_base\n",
    "# paths_plot=paths_pulse_control+paths_pulse_c_short_base+paths_pulse_c_long+\\\n",
    "#         paths_pulse_cs_short+paths_pulse_cs_long+\\\n",
    "#         paths_pulse_s_short+paths_pulse_s_long\n",
    "\n",
    "line_ph=[]; line_co2=[]\n",
    "\n",
    "for path in paths_plot:\n",
    "#for i in range(len(paths_plot)):    \n",
    "#    path=paths_plot[i]\n",
    "    #if path not in paths_pulse_failed_13c:\n",
    "    if path in paths_pulse_control:\n",
    "        mark='*'; linestyle='--'\n",
    "    elif path in paths_pulse_c_short_base+paths_pulse_c_long:\n",
    "        mark='o'; linestyle='-' \n",
    "    elif path in paths_pulse_s_short:\n",
    "        mark='x'; linestyle='--'\n",
    "    elif path in paths_pulse_s_long:\n",
    "        mark='+'; linestyle='--'\n",
    "    elif path in paths_pulse_cs_short:\n",
    "        mark='^'; linestyle='-'\n",
    "    elif path in paths_pulse_cs_long:\n",
    "        mark='v'; linestyle='-' \n",
    "    \n",
    "    if path in colors_paper_df.index:\n",
    "        ccc=colors_paper_df.loc[path, 'color']\n",
    "    else:\n",
    "        ccc=colors_df.loc[path, 'color']\n",
    "\n",
    "    [ph_ts_globmean,years]=biogeo_df.loc[path, ['ph_mean','years'] ] \n",
    "    \n",
    "    \n",
    "    if path in paths_pulse_control:\n",
    "        years=np.arange(0,13000-100,100)\n",
    "    else:\n",
    "        years=np.arange(0,5000,10)\n",
    "      \n",
    "    ax1.plot(years,ph_ts_globmean, label=path, alpha=0.8, c=ccc, linestyle=linestyle) \n",
    "\n",
    "    if path in paths_pulse_c+paths_pulse_cs: # and path not in paths_pulse_failed_13c\n",
    "        idx_GtC=path.find('GtC')\n",
    "        GtC=int(path[idx_GtC-4:idx_GtC])\n",
    "    else:\n",
    "        GtC=0\n",
    "\n",
    "    idx_ppm=path.find('ppm')\n",
    "    ppm=int(path[idx_ppm-4:idx_ppm])\n",
    "\n",
    "    [slope,intercept]=ph_regress_df.loc[paths_pulse_control[int(np.where(ppms==ppm)[0])], ['slope','intercept']]\n",
    "    diff_ph=ph_ts_globmean-(np.array(slope).astype(np.float)*np.array(years).astype(np.int)+np.array(intercept).astype(np.float))\n",
    "    ph_amplitude=np.min(diff_ph)\n",
    "    \n",
    "    #ax1.plot(years,diff_ph, label=path, alpha=0.8, c=colors_df.loc[path, 'color'], linestyle=linestyle) \n",
    "    \n",
    "\n",
    "    \n",
    "    if path in ['pulse_control_1500ppm','pulse_c_1500ppm_2500GtC_5ka','pulse_c_1500ppm_5300GtC_5ka', \\\n",
    "            'pulse_c_1500ppm_7500GtC_5ka']:\n",
    "        line_ph.append(ph_amplitude); line_co2.append(GtC); \n",
    "    ax3.plot(line_co2[:],line_ph[:],'--', c='tab:gray', lw=1,zorder=0)\n",
    "    \n",
    "    ax3.scatter(GtC, ph_amplitude, c=ccc, marker=mark)\n",
    "    if path in paths_pulse_c_short_base:\n",
    "        ax3.annotate('%.2f' % (ph_amplitude) ,xy=(GtC,ph_amplitude),xytext=(-40, -10), \\\n",
    "                     textcoords='offset pixels', fontsize=12 ,color=ccc)\n",
    "\n",
    "ax1.set_title('surface ocean pH Timeseries (from MOM-Snapshots)', fontsize=8)\n",
    "ax1.legend(loc='lower right', fontsize='6')\n",
    "#ax1.set_xlim([0,5000]); #ax71.set_ylim([0,5000]);\n",
    "ax1.set_xlabel('Time (years)'); ax1.set_ylabel(r'pH');\n",
    "#ax3.set_ylim([-0.5,0]);\n",
    "ax3.tick_params(labelsize=12)\n",
    "ax3.set_title('Max. surface pH Reduction', fontsize=13); \n",
    "ax3.set_xticks([0,2500,5300,7500]); \n",
    "ax3.set_xlim([-300,8300])\n",
    "ax3.set_ylim([-0.5,0.025])\n",
    "ax3.set_xlabel('Total Carbon Emission (GtC)', fontsize=12); \n",
    "ax3.set_ylabel(r'$\\Delta$ pH', fontsize=12);\n",
    "#ax73.text(0,-0.5,r'$\\bigcirc$=c only'+'\\n'+r'$\\bigtriangleup$=c+s'+'\\n'+r'$\\times$=s only'+'\\n'+r'$\\ast$=control', fontsize=8)\n",
    "ax3.text(200,-0.47,r'$\\bigcirc$=c only'+'\\n'+r'$\\bigtriangleup$=c+s short'+'\\n'+r'$\\bigtriangledown$=c+s long'+'\\n' \\\n",
    "         +r'$\\times$=s only short'+'\\n'+r'$+$=s only long'+'\\n'+r'$\\ast$=control', fontsize=12) #+r'$\\Box$=control'+'\\n'\n",
    "plt.tight_layout()\n",
    "\n",
    "fig3.savefig('./plot_pdf_files/FigS15a_pulse_rev_PH_diff.pdf' ,bbox_inches='tight', pad_inches=0.01, dpi=900)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x370.8 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### short scenarios: Plot pH-Timeseries, calculate Fit for Control Runs, Determine excursion Amplitude relative to Control runs\n",
    "### and Plot Map of dp13 and dp13-Change for Example-Run \n",
    "\n",
    "biogeo_df = pd.read_pickle(\"./biogeo_df_rev.pkl\")\n",
    "\n",
    "fig1=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax1=fig1.add_subplot(111)\n",
    "ax1.grid(linestyle=':', zorder=0)\n",
    "\n",
    "fig3=plt.figure(figsize=(7.0,5.15))\n",
    "plt.clf()\n",
    "ax3=fig3.add_subplot(111)\n",
    "ax3.grid(linestyle=':', zorder=0)\n",
    "\n",
    "ph_regress_df=pd.DataFrame([], columns=['slope', 'intercept'], index=paths_pulse_control, dtype=float) #[], columns=['dp13_ts_globmean', 'years'], index=[]\n",
    "for path in paths_pulse_control:\n",
    "    [ph_mean,years]=biogeo_df.loc[path, ['omega_trop','years'] ]\n",
    "    years=np.arange(0,13000-100,100)\n",
    "    x=np.array(years).astype(np.int); y=np.array(ph_mean).astype(np.float)\n",
    "    slope, intercept, r_value, p_value, std_err = stats.linregress(x,y)\n",
    "    ph_regress_df.loc[path, ['slope','intercept'] ]= [slope,intercept]\n",
    "    ax1.plot(x,slope*x+intercept, 'k--', alpha=0.8)\n",
    "ppms=np.array([1000,1500,2000])\n",
    "\n",
    "paths_plot=paths_pulse_control+paths_pulse_c_short_base+['pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka']\n",
    "#paths_plot=paths_pulse_c_short_base\n",
    "# paths_plot=paths_pulse_control+paths_pulse_c_short_base+paths_pulse_c_long+\\\n",
    "#         paths_pulse_cs_short+paths_pulse_cs_long+\\\n",
    "#         paths_pulse_s_short+paths_pulse_s_long\n",
    "line_ph=[]; line_co2=[]\n",
    "\n",
    "for path in paths_plot:\n",
    "#for i in range(len(paths_plot)):    \n",
    "#    path=paths_plot[i]\n",
    "    #if path not in paths_pulse_failed_13c:\n",
    "    if path in paths_pulse_control:\n",
    "        mark='*'; linestyle='--'\n",
    "    elif path in paths_pulse_c_short_base+paths_pulse_c_long:\n",
    "        mark='o'; linestyle='-' \n",
    "    elif path in paths_pulse_s_short:\n",
    "        mark='x'; linestyle='--'\n",
    "    elif path in paths_pulse_s_long:\n",
    "        mark='+'; linestyle='--'\n",
    "    elif path in paths_pulse_cs_short:\n",
    "        mark='^'; linestyle='-'\n",
    "    elif path in paths_pulse_cs_long:\n",
    "        mark='v'; linestyle='-' \n",
    "    \n",
    "    if path in colors_paper_df.index:\n",
    "        ccc=colors_paper_df.loc[path, 'color']\n",
    "    else:\n",
    "        ccc=colors_df.loc[path, 'color']\n",
    "\n",
    "    [ph_ts_globmean,years]=biogeo_df.loc[path, ['omega_trop','years'] ] \n",
    "    \n",
    "    if path in paths_pulse_control:\n",
    "        years=np.arange(0,13000-100,100)\n",
    "    else:\n",
    "        years=np.arange(0,5000,10)\n",
    "      \n",
    "    ax1.plot(years,ph_ts_globmean, label=path, alpha=0.8, c=ccc, linestyle=linestyle) \n",
    "\n",
    "    if path in paths_pulse_c+paths_pulse_cs: # and path not in paths_pulse_failed_13c\n",
    "        idx_GtC=path.find('GtC')\n",
    "        GtC=int(path[idx_GtC-4:idx_GtC])\n",
    "    else:\n",
    "        GtC=0\n",
    "\n",
    "    idx_ppm=path.find('ppm')\n",
    "    ppm=int(path[idx_ppm-4:idx_ppm])\n",
    "\n",
    "    [slope,intercept]=ph_regress_df.loc[paths_pulse_control[int(np.where(ppms==ppm)[0])], ['slope','intercept']]\n",
    "    diff_ph=ph_ts_globmean-(np.array(slope).astype(np.float)*np.array(years).astype(np.int)+np.array(intercept).astype(np.float))\n",
    "    ph_amplitude=np.min(diff_ph)\n",
    "    \n",
    "    #ax1.plot(years,diff_ph, label=path, alpha=0.8, c=colors_df.loc[path, 'color'], linestyle=linestyle) \n",
    "    \n",
    "    if path in ['pulse_control_1500ppm','pulse_c_1500ppm_2500GtC_5ka','pulse_c_1500ppm_5300GtC_5ka', \\\n",
    "            'pulse_c_1500ppm_7500GtC_5ka']:\n",
    "        line_ph.append(ph_amplitude); line_co2.append(GtC); \n",
    "    ax3.plot(line_co2[:],line_ph[:],'--', c='tab:gray', lw=1,zorder=0)\n",
    "    \n",
    "    ax3.scatter(GtC, ph_amplitude, c=ccc, marker=mark)\n",
    "    if path in paths_pulse_c_short_base+paths_pulse_cs_short:\n",
    "        if path in paths_pulse_c_short_base:\n",
    "            anno_pos=(-40, -10)\n",
    "        else:\n",
    "            anno_pos=(0, -10)\n",
    "        ax3.annotate('%.2f' % (ph_amplitude) ,xy=(GtC,ph_amplitude),xytext=anno_pos, \\\n",
    "                     textcoords='offset pixels', fontsize=12 ,color=ccc)\n",
    "\n",
    "ax1.set_title('surface ocean $\\Omega_{Ar}$ Timeseries (from MOM-Snapshots)', fontsize=8)\n",
    "ax1.legend(loc='lower right', fontsize='6')\n",
    "#ax1.set_xlim([0,5000]); #ax71.set_ylim([0,5000]);\n",
    "ax1.set_xlabel('Time (years)'); ax1.set_ylabel(r'$\\Omega_{Ar}$');\n",
    "#ax3.set_ylim([-0.5,0]);\n",
    "ax3.tick_params(labelsize=12)\n",
    "ax3.set_title('Max. trop. surface $\\Omega_{Ar}$ Reduction', fontsize=13); \n",
    "ax3.set_xticks([0,2500,5300,7500]); \n",
    "ax3.set_xlim([-300,8300])\n",
    "ax3.set_xlabel('Total Carbon Emission (GtC)', fontsize=12); \n",
    "ax3.set_ylabel(r'$\\Delta$ $\\Omega_{Ar}$', fontsize=12);\n",
    "#ax73.text(0,-0.5,r'$\\bigcirc$=c only'+'\\n'+r'$\\bigtriangleup$=c+s'+'\\n'+r'$\\times$=s only'+'\\n'+r'$\\ast$=control', fontsize=8)\n",
    "ax3.text(5500,-0.5,r'$\\bigcirc$=c only'+'\\n'+r'$\\bigtriangleup$=c+s short'+'\\n'+r'$\\bigtriangledown$=c+s long'+'\\n' \\\n",
    "         +r'$\\times$=s only short'+'\\n'+r'$+$=s only long'+'\\n'+r'$\\ast$=control', fontsize=12) #+r'$\\Box$=control'+'\\n'\n",
    "plt.tight_layout()\n",
    "\n",
    "fig3.savefig('./plot_pdf_files/FigS15b_pulse_rev_OMEGA_diff.pdf' ,bbox_inches='tight', pad_inches=0.01, dpi=900)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#ECF6CE; border-radius: 4px 4px 4px 4px; font-size: smaller\">             VARIABLE : T (days) of 0 in A[L=@MIN]-A (days)\n",
       "             LONGITUDE: 0E to 0E(360)\n",
       "             LATITUDE : 30S to 30N\n",
       "             DEPTH (m): 12.5\n",
       "             T (days) : 3269.5 to 1800000 (location of 0) 360_DAY\n",
       "          557834.\n",
       "</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "use \"../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/all_snapshots_mom_annual.nc\"\n",
    "use \"../climber/c3beta_tria_200Ma_1500ppm/topog.dta.nc\"\n",
    "let a=omegaplo_a[i=@ave,y=30S:30N@ave,k=1,l=@sbx:10,d=1]\n",
    "let b=a[l=@min]-a\n",
    "list b[l=@loc:0] !year 1539; 1939 mistakenly because of @sbx:100\n",
    "!plot omegaplo_a[i=@ave,y=30S:30N@ave,k=1,l=@sbx:10,d=1]\n",
    "!shade omegaplo_a[k=1,l=149:159@ave,d=1]\n",
    "!contour/over/levels=(1) omegaplo_a[k=1,l=149:159@ave,d=1]\n",
    "!shade omegaplo_a[k=1,l=189:199@ave,d=1]-omegaplo_a[k=1,l=1,d=1]\n",
    "let omega_maxdiff_f=omegaplo_a[k=1,l=149:159@ave,d=1]-omegaplo_a[k=1,l=1,d=1]\n",
    "let omega_min_f=omegaplo_a[k=1,l=149:159@ave,d=1]\n",
    "\n",
    "let c=ph[i=@ave,j=@ave,k=1,l=@sbx:10,d=1]\n",
    "let d=c[l=@min]-c\n",
    "!list d[l=@loc:0] ! year 2059; erroneously year 1939\n",
    "!shade ph[k=1,l=201:211@ave,d=1]-ph[k=1,l=1,d=1]\n",
    "let ph_maxdiff_f=ph[k=1,l=201:211@ave,d=1]-ph[k=1,l=1,d=1]\n",
    "let ph_min_f=ph[k=1,l=201:211@ave,d=1]\n",
    "\n",
    "let h_ini=10^(-1*ph[k=1,l=1,d=1])\n",
    "let h_end=10^(-1*ph[k=1,l=201:211@ave,d=1])\n",
    "let h_diff=h_end-h_ini\n",
    "!let h_diff=(h_end-h_ini)/h_ini*100\n",
    "!shade h_diff\n",
    "\n",
    "!let ccd_ini_f=missing(omegaplo_a[l=1,z=@loc:1],0)\n",
    "!let ccd_end_f=missing(omegaplo_a[l=500,z=@loc:1],0)\n",
    "!let ccd_diff_f\n",
    "!shade ccd_end_f-ccd_ini_f\n",
    "let ccd_unchanged_f=omegaplo_a[l=1,z=@loc:1,d=1]\n",
    "let a=omegaplo_a[l=1,z=@loc:1,d=1]\n",
    "!shade a\n",
    "let b=if(ht[d=2]/100 le 1000 and i ge 48 and i le 64 and j ge 16 and j le 34) then ht[d=2]/100 else a\n",
    "let ccd_ini_f=missing(b,0)\n",
    "!shade ccd_ini_f\n",
    "let ccd_end_f=missing(omegaplo_a[l=500,z=@loc:1,d=1],0)\n",
    "!shade omegaplo_a[l=500,z=@loc:1,d=1]\n",
    "!set window 2\n",
    "!shade omegaplo_a[l=1,k=1,d=1]\n",
    "!shade ccd_end_f-ccd_ini_f\n",
    "!shade ccd_ini_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: omega_maxdiff_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: omega_min_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ph_maxdiff_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ph_min_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ccd_ini_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ccd_end_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ccd_unchanged_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata omega_maxdiff_f = omega_maxdiff_f\n",
    "%ferret_getdata omega_min_f = omega_min_f\n",
    "%ferret_getdata ph_maxdiff_f = ph_maxdiff_f\n",
    "%ferret_getdata ph_min_f = ph_min_f\n",
    "%ferret_getdata ccd_ini_f = ccd_ini_f\n",
    "%ferret_getdata ccd_end_f = ccd_end_f\n",
    "%ferret_getdata ccd_unchanged_f = ccd_unchanged_f\n",
    "#%ferret_getdata ccd_diff_f = ccd_diff_f\n",
    "omega_maxdiff=np.ma.masked_values(np.rot90(omega_maxdiff_f['data'][:,:,0,0,0,0]), -1e34); \n",
    "omega_min=np.ma.masked_values(np.rot90(omega_min_f['data'][:,:,0,0,0,0]), -1e34); \n",
    "ph_maxdiff=np.ma.masked_values(np.rot90(ph_maxdiff_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "ph_min=np.ma.masked_values(np.rot90(ph_min_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "ccd_ini=np.ma.masked_values(np.rot90(ccd_ini_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "ccd_end=np.ma.masked_values(np.rot90(ccd_end_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "ccd_unchanged=np.ma.masked_values(np.rot90(ccd_unchanged_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "#ccd_end=np.ma.masked_values(np.rot90(ccd_end_f['data'][:,:,0,0,0,0]), -1e34);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hgdzcXJqbm/Hx8SExMRGVSjWg/ppMJvbv398pkUl/r8/NzaW+vh6A2NhYAgMD+3y9VqtFrVZTU1ODRqMB2qIOqlQqfH198fPz6xRn32g0Ul1dTWVlJSUlJRQXF1NSUkJ5eTnV1dXU1dVRX19PY2Mj/v7+hIeHExERQWRkJBEREYSHhxMeHk5gYKAk/BIXHZKwS1yQiKJIdXU1+fn55Ofnk5eXx/Hjx23CbbVaCQoKIiAggLCwMKKiooiPjyc6Oprw8HA8PDy6TPrRjtVqpaGhgYqKCmpra23eqLe3N76+vnh6ep4lKHUVarK2HeXfz25ArG8EUcRs13m4WRRFDFYdOnMDckGBs50ndrKzvXLBaAKTmdYlM9j75Z293o9zFfYzbczPz6eyshKFQsHEiRNxcHAYUF16vd7mvbe0tNjuY7tX3ltSHaPRSGlpKQUFBRw/fpwTJ05QVFREeXk5lZWVqNVq/Pz8CA8PJyYmhri4OOLj44mNjSUyMrLLMMYSEuc7krBLnNe0tLSQm5tLXl4eeXl5tv8/efIkCoWC0NBQIiMjiYuLIykpiYSEBMLDw3F3d+9RuM/EarVSXl5OcXExra2tyGQyPDw8CAwMxMfHp8vhc6PBRNb2oxz46RDfr9uH2NBkOycqFYjyzte0WDXoxWaUggNOgjsyoeu1rQIg6A0AtC6Ywu6tD/Vq/2AKe0cMBgPp6emYTCbb1MO5YrFYqKyspLy8HJ1OhyiKuLi4EBoaip+fX78+t3bhz8vLIzs7m5ycHAoLCykuLqaqqgp/f39iY2NJSEiwCX5CQgKBgYH9akdCYjQhCbvEeYHJZOLEiRNkZ2dz9OhRDh8+zNGjR6moqCAsLIyIiAhiY2MZN24cSUlJxMbGnpXMoz9YrVZOnTpFWVkZFosFmUxGQEAAoaGhPXqnZpOZg9uOsvOrfWz5dC8Yf0khaifHFBGIJTIYc3QQVl9P+GXeXVeRj9Wgx97DD3uPgF5tkxdX4vT+D1iCfPmp4BUUSkWv1wyVsLfTnnmtubmZKVOm4O7uPmh1i6KIRqOhuLiY6upqoC03e1hYGP7+/gMWYJPJxKlTpzhy5AiHDx/m+PHjnDp1iqKiIsxmM4mJiYwbN45x48YxduxYxo4di5eX16D1S0JiqJCEXWLUUV9fT1ZWFpmZmWRlZXHkyBEKCgrw9/cnJiaGsWPHMnXqVCZMmEBMTMxZObAHgiiKVFRUUFhYaBPy8PBwgoODu/TGoU388zIKSP0hg/rKBox6I5lbj6BRa9sKODliGB+NOS4MS4gfdBh2F0URXXkeFkMLzsHxyO0d+2yr6rsUlAfzGDMzjqCYs18EkmYlsPi2SzsdG2phb6elpYWMjAxkMhmzZs0aMq9Xq9VSVFREZWUlgiAQEBBAREQEjo59v489UVNTw9GjR0lLS+Pw4cPk5eVRUFCAk5MTY8aMYcKECUyaNImJEycSGxsrreCXGFVIwi4xolRVVXHw4EEyMzPJyMjg4MGDNDY22obOp06dyrRp00hISBi0h3Y7zc3N5OXlodW2CXFQUBCRkZE9LrYyGU0cTslh7//S2fDxHmjRdzpvdXHENCYS89goLMF+IGsTNrdAg61Mq7qO5qJ83KISsHfz6Latpoqu538dvtyKIruw+47JZGxqWdfJkx8uYW+ntbWVtLQ05HL5kAo8nH4pO3XqFHq9HkdHR2JjY/H29h7UdkVRpLS0lKysLPbt28ehQ4c4fvw4dXV1JCUlMWnSJCZPnszEiRNJTEzs844FCYnBRhJ2iWFDq9Vy4MAB0tLS2LdvH+np6RgMBuLj4xk3bhwzZ85kxowZREVFdeslnytlZWUUFBRgtVpxcXEhPj4eZ2fnHq8RRZHsPblsXbuTHz/edXp4XWWPMSEMc0IEFl9PkAmIrs42MYfOgi6KIg15R5HZKXCLjEPopo/dCboNqxWhSXvWYc9qHZb9h7GeLOa/WS8QNT7cdm64hb0dg8HATz/9RGxsLPHx8cPSpk6nIz8/H7VajVwuJzo6muDg4CFrr7GxkaysLHbt2sWBAwfIycmhvLycMWPGkJyczIwZM5g+fToRERHSvL3EsCAJu8SQYLVaycvLs4l4amoqBQUFxMTEMHHiRObMmcP8+fMJDw8f0oedxWKhrLRNzFtbWwkKCiI2NrZPw/c1JXVsX7ebrR/vpLKwbW4XJ0dkkSFoJsdiCfUHedfi3FHQATQlhZhatLhFxCK3737LWq+i3gPeFRosuQVYUtK588Vl/PovV9rOjZSwQ9sLzeHDh6mvr2f27NnD6smKosjJkycpKytDEAT8/f2Ji4sbcoHV6XRkZmayfft2UlNTOXToEGazmWnTpjFjxgySk5OZOnUqrq6uQ2qHxMWJJOwSg4LJZCIrK4udO3eyc+dO9u7di6OjI+PGjWP69OksWrSISy65ZMi3F4miSMnxMnZ8s4e3XvsGo7oGlVWFA87IhYHNg4oKO0yJEZgmxGKJCAKZcJZwd4V/oA6TvpX8PSU4B4f3OOzeG30VfEGjw+WFdZgjAtlR8Krt+EgKezsNDQ0cOnSIhIQE/P39R8SGyspK8vLyAPDz8yMuLm7IRofOpKysjL1797J9+3YyMjLIy8sjOjqauXPnMnfuXGbPnj0ouwokJCRhlxgQ7XOoKSkppKSkkJGRQWBgIJMnT2bhwoUsWrSIoKCgYbHF2Gok6+dsUjcc4Iu1GzHo1MixwwlXZIGBiA4De5kQlQrMCeGYEiPBvs3D76ugA5QVCKjzjuIeFY/SxW1ANkD/vXjHd79DXlbNp6fexDfUBxgdwt5OdnY29fX1zJw5c0SDx1RWVpKTk4MgCISGhhIVFTWsQ+UGg4G0tDS2bNnC7t27OXToED4+Pjahnz9/PqGhocNmj8SFgyTsEn3CYrHYhha3bNnC/v37iYyMZNq0aVxxxRXMmzfvnLaXDYTKU9VseGsLa1/7lhaDGgAnpScOIZHoxkdijglFdB5Y4JSu6I+o5+0pQ7RYcI9JPKc2BzI0r8jMxeH7ndy6+gZ+/9SNwOgSdoDa2lp27tzJkiVLeg1CM9S0b3s7efIkPj4+xMfH9zn07mBisVg4cuQImzZtYufOnWRkZODu7s5ll13GwoULmT9/Pj4+PsNul8T5hyTsEl0iiiJHso7y06YtpKSkkJaehre3F9OmTuPyyxcxa9Ys3NyGdn7QxdP5rD3aVquVAz8d5otXvmXnlt2IiKjs3XGOH4dmUgyWUD8Y5K1H/RF0s8FI3s5TuEbGoXA8d8Ea0Jy7wYTLi+vwcFHxxoHnsFPIcXBVcTDr4KgRdmiLOpeWlkZSUlK3MeiHm9raWo4fP05LSwvjx4/Hz8+v26H6prpmLGbLkNlitYrk5OSwadNG9uzdw7HsbIKDQ5k7dy7z5s5l6XVXDDjin8SFjSTsEja0Wi07duzgzY0GTK3N6NP3Q24xKhy7jYI2lAgebihuWsrGN6+lWa1h85odvPy3DzBo61GgxCE4FvO0sZjGRIKi9yHdvgh0d7QLd1cEe5oBsJjNnNyTRXBSLMcrBz6Eei4L6Nqx35KO/Z5Dtn+b/D2oWRJPzvt/Pee6B5vMzEwMBgMzZswYaVNsWK1WsrOzqaurw9PTk/Hjx3capp91zWs4rN89/HaJVvToMMutGO9fhp2jKzKFio9vDCU2NlZadS8BSMJ+0ZOXl8f69evZmhuIQd+E1WLC3sENhcqZ5rpq7PJK+lyXvd40cENEsBZ2bks2IZHX31vGN6+u57tPNmGw6HC0c0eeNA7T9CSsgX0blhwqQYfTot5cXU9DaRWhkxLJPDbwqGuDIeoAQksr9lvSEYwmZOomhPIa6qYFcjjtP4NS/2Bz/PhxNBoNU6ZMGXXi1NDQwOHDhxFFkcTERPz8/Ej+8+c4v/VNp3LmiEBEp+HxoEWZQOv1C7AY9BgaqxAEGXaOrtg5uLJqopEFCxYMetwHifMHSdgvMiwWC6mpqTz7STVGfTNGfROCzA4HF28aQvs/HOpdoTlnm6z1jVh2piPW1IMgIIQF8evrLiFrxxEyD2ZiwYKDeyCyaVMwTYxDdOxbhrNzEXTou6irS6rQ1jcQMj6OzJyhX/neXwSdHodXP0NjqWVf00aUqtEZOKWgoICSkhLmzZs36sQd2qanjh07RkVFBYGBgcTFxrF17S5efHAdsiYtolJB68KpmKaM6RTLYDgxaRswadTIHVywc3TlztAqrrrqKmm1/UWGJOwXAS0tLfz000+8s9mMQd+IqVWDXKHC0cWX+uCBeZeDIeiixYLl4DGsWcfAKqJUKQiKCeDU8WIaTHWIAjhEjUVMnog5OqRfD8uhFPV2QQdorKhFU11PyCXxHMge+Mp3GDphB7D/fDP6Y5lsqf4OD99zs3MoaQ9os3DhwlE7f2y1WikuLubo0aPExcURFhrO5vd/5vWHP0HQGzCH+NH6q7lYfQb+kjcodppNGBoqQZChcHLjeudcrrvuOuLi4kbULomhRxL2CxSdTsemTZt4/pgTJm0DQeGlqNzccPLx6iRM/aFMffY8dlVFzwvEuhUrqxWn/3yJvP50xjO9qEOPDsHTE9XUmZjHxyI6nx5OlFWrUR7IQVbXhKyusctqZfIzvs7OKvjr5QjOfRPNjoLe230qO5KPytkR78hg270RzVaq1hTC3pNgsfapTQCrpW8vLVZPV+weXoBg17cFgu33/3wRdmjbhnbw4EGWLl060qb0iCiKTFrwBOKOnTjijEruisx6+vunW3EVloiec9YP9AW5LtClX9dbLWb02jqsZgP2jh4oVC68cE8ciYmJo3J0ROLcGLlNpBKDjkajYcOGDbyU64pJ24ClVceY+VqUzk4Ee7Yv5uqfqHcl5nAOgt6OIGD1cUde30SLyoJW0YIiMgZF8gzEQB9ss/UmM4rsAhQHjmNXWm273D/Ct8fqG6oaMeiNYDS35TntA/0R9YbyGpSOqk6ibjrZQOMrGVDYhKOrA65eg7tlStfUguZUBeRWwdjhiREwEgQEBLBkyRK2bdvGjBkzRu1csSAIODl6oxICaBG1NFqqsXPxwFX7y06ObqISjgQyuR1Obm1BgSwWE7qmSu58ugR7xwyUKlf+eWcU48aNk0T+AkHy2M9zDAYDmzdv5pmDdm1ibmwl6TIVdvZt86iD6Z3DIAh6BywGPZqSbBSObjj4RSCz67C1TRRR7jmM/e4shFYjogBTF01g6R0LmX7lJOQ9eKw5afmsnLsaBAEeWIQQ2fsiu/6IevnRE8js7AhIiKBMbYdosqL9NAftV7lgFVl826X86d+/x9l9cPdnH045xgOXPgVz4xBuTe7TNeejx96OWq3m559/5pprrhmUDH5Dxcyb38Hh+50IrUZa4gNRJ3kjc3fHKaj7fABncq6e+0DrsFhM6BorAFD94sn/54HxREVFDcgeidGBJOznIRaLhV27dvHQLgMmTT1Wk5Gky+yR/7Lla7jFHPon6FazEW3pcRAEnIPikSnOXsxl//MB7FMysTo58Nv7FnPFHy/DP7xnLx1Ar9VzddSfoU4LKxcgjO09+Ue7qPflvtWXtKUJ9Qzxp0xth6mkmcZ/p2M+2Yjcx5F/rPsrkxaO77WegWAxW1jstRxEEf59Y5+G489nYYfTe91H64K6dqqKarh5zt+wK6tBVNqhTY5H7Sdi7xOMg29Yn20/l7Ur5yryVqsFXWMFgiBg7+jB0nH13HTTTSMW/ldi4EjCfh6Rn5/P7z4vwqRVY25pJn6WgIN720N6oGIOwyjoJiPasuMIMjnOIYndejPKPYdRbUkD4MYHrsY72OusMoIgMG3pRAIiT6/2vXzNRsSP98HOfAj2gNmxMC4YwafrIfH+eOkAmho1DWXVhE5MoLROTsv6kzR/cASMVhwWhvPZV3/DyXVoh40XXv4kbMuByxLA26VtQeEloQgeXX9W57uwQ9sU065du1iyZMmwxXUfCBaLhZ/W7ODFv36ETNeK1cOFhuQItK5WXCMnIFf1bwTHq7QR68ni09kEu0MmQxbkh+DeFjCqrwIvmi1Y8woRW/QIqs6/Y6sg0uJoRu7phcrJgz9cbsdVV12FStW3HSkSI4sk7KOcpqYm7tm3GVOLnpa6emRyOYumeyEhQDG2AAAgAElEQVQbhPm7UKe+L+4CKNF13Wax5rQ30tVLgtVioT6/AJO+Ff/xY3u0XRRFqn/zA6LG2LtBM6MRVsxiy21ti6wWvrcB7v0EDB1EelYMwvKzo611FPWZYacfnB3vScf+VhVWoG3QED0pDm2pjgOrDlKXUY/MVYnbfZP58um/9G7vILDwbx/D337ofDAhAOH/FvV4neXN7TRnZp2Xwg5QWFhIcXEx8+fPH2lTekXbqGPd37/m61c3IVitmMIDqJvog8XNEaegOOTKvomjvKQKp/e+73O7grcHsuhwZNGhCM69v0RYy6swr/+550KuzhDqj95LgSIwEJWLN0/fHsbkyZNH9QjKxY4k7KMQURTZu3cv/20soaVejVGjY/EsXxT2g7P/eLgEHaBF3UBd7km8Y6Nw9O5bLHlTURPm8rM9jUa1Chp08Pl+UMjh8SvZuvp3ncoUHC6i/EQlr939Lk11GnjkCoTozkP4/RV1q9VKfnoOsVMTKfyiiKMvHcOitzDjmimsfOuPePoP77amnLR86isaAPjm5fUc25sHj16BENX9VMX5LuzQlvc8Pz+fqVOnjrQpfaI0r5y3H1hL+saDiIKAcVI89fEuWBUynIJikSt72c4nitjvOIBy50EEEcbMjOO6lUvPGunSqLXs/S6dzC1HbCFuBX8fZNFhyKJCERy6fpEQRRHL7gNYc07Yjs29MZm5N8xA19RCxk+HyPgxC722ta28UoE5yB2jrxOOUfEsndTMsmXLhj1HhETvSMI+ilCr1axM34pRo6WlvgEHD3cWjB+cvbz9FXM4N0G3GE3U5OShdHLEKyay3213pH1KQBRFeHkr5FTArcls/ajr8Kg7v0rlmZtegqkRCHfM7XSuL6IOp/veqmvlxIFckuZO4Mi/s8n/4CQuHk78+bXbufSWWSPutRzeeYwH5j8FYwIR/nJ5l2VEUcT6rw00n8xje90Pg75afzjZu3cv4eHhw5Y5cDDY/2MWjyx7E3ldI6LSDv34SOoDBZQhEah8Qnv9DskLy3H45mdkmhbm3pjMw2vvPSuHArTFrt/zbTo7Pt/L4ZRjbQdlAkJoEPK4SITQQIQuRsvEVgOWg9lYs0+A1crEy5L4v/fuwjfUB6PBxJGdOaT+kEHq+gPUltYDYLGX05oUhCIqAkdXPx77nT+zZo3870GiDUnYRxhRFElPT+c/NQW01KsRZAKLpg6eBzhUgg7dD7vXHstDsJPjk3Dusas7zvOLR8vg1W1Munw8//zx8W7rXphwL+RVwTPXIvif9k77K+oAR1KyCE+KRJetZ+/daTiHO/Pe3pfwChjZ4CMdWZh4H+RWwoOLEeLOXugk7j2Jdc0umsMEMoq+HgELB5edO3cSFBREdHT0SJvSZ8wmM+vf2sLrq79E1qxDlAk0RrqgjfHCZeqlyOQ97zwWtHocPt+CXUkV5qhgNmU9i0MPmQvrKtTs+jKV/z77PWJd2+gOKntkseHI4qKQeZ0dmEps0mDecwCxtBKUCuQzJvLj9v+z/c5EUaTgcBG7v07j0+e/B7MFIcAX4yVhWJwUqJy8WDpOzYoVK3BzOz9HhS4UJGEfIVpbW/nDz99haNKgqazCwd2NmXGDt6Un2LH/gl7W0v3cd5n2tIhWNHT9ENLV1tNYVIzv2EQU3Qz/9Yea6s4L0cTnf4SKJgIi/XD3dWXigiSuXdk5iMn1r3wLz24EuQBh3m172C9LxG/e6QfN1JDOi5E63quO96AgK5+Q+DCsWpGU5Xuw6M08t3k1EWNHV47s65/9DF7ZBq6qtgV1Z1KuxoqI5uZYtj7/4PAbOMhYLBZ27tzJ/PnzzzsP0WQ0se/7A7zyt6+R1zQiItLgbgKlHS5Kvx77I5gsyKvaPGZzsC/6Wxbx0wPzem3zVHYJD9+zDmthKbS2rV0R3F2gq6k9EcQ6NfwSaEcWEYxszhSeu20CHz35BabWtt+OuqqR6qLatmtkAvLkiQhRIeiaKrB3cMfB1ZeXVo4lMfHc0hZLDAxJ2IeZsrIy3ihLobm6ntrCMiICnLF37HpleYDD8Hw0vg7nkLyFX2JoZxWhtFcQkxh0zg/bGn3nF5xKvYAoiqTdn4G2WAu/3BbXaBemvTiFGyOvBOCOb3ciqnXw3m5oMdjKJVwbzJS7YoCe+9qx3ZNVOprrmvAPD+TA6iwasxu55fFfM/83oyftaTt3fLsT8ftDkFXcdQGFHOtVSejczXx+/23Da9wQIYoiqampJCcnn3fiDm323/rE9yiy8pCX12C1WmiiHhWOOAh9WPjm5oz+5kV8dnffv48mk4l77/kCa1EZYlUdWHt/+Re83JEvmIFYVYtlV8bZ/fjl1psmJ2B/ZaztuMVsRq5QoPL04b4gBVdddRXyQU6nLNE9krAPE1lZWXzecpSmqjosRhOTxncvgAMZPh8oQU59WH3eA6dOVFJX3cTYiRE4dPOC0h/KdZ29iK6mBbJfzSH3nXwuWT2e5596otu63n5gLV+/tJ5rP5hGxPy2bXHd9bdju0eLmqk4UUbCjLEce/04x9/KY+a1U3ny6wfOSxGBtof6/v37R1U+9nOlPW/6pEmTRtqUQUEURQ4ePIher2f69OnY2Y2uwKBLrvkv5pQ00OgQPN2QXzoDmXfblFTHLXYd8zRYDK201FRi7+bB9XYNrFixAienwQ3cJHE2krAPIaIosnnzZrapKtDUqHHycic+qPt9zueToOs0rRw9WEhIhC9BA8gK1xUdxbW7eX7RIrJh/mZEs5Vvyj9A1cXLRGuLgY+f+pKvXl6PwlHOnRmLsFPJ+yTqoijyww8HSZg6lpxX8in84hSOAQ6sy34TFw/nc+zhyHEhCjvA0aNHAUhKShphSwaPqqoqcnNziY+PH3XBYVo0eq5NfhprzkmQy5HPm4Y8Jtx2vluBNxlpqSzDztEJlZcvHy+dPOr6diExul4JLxDMZjOfffYZmf4t6Jqa8PYIZNK47pNBnE+CDtDc1MLB1HwmTI3G3XNwxK4vog5Qf0SNod7AktsXdCnqB7cd4ZU736GysBq3UEcuf35Cj6J+JttS8ggLiWb3slSa8ptxi3Xl5e+fPq9F/UJm7NixbN++nTFjxozq4DX9wd/fH39/f44dO0Zubi4zZ84cNSF1HV0c+Cn7n6SuP8Dq61/Esn0foroJ+dS2OPPtAXHqAl06Ba9yCwSX0EhEqxVNSSHXf1SNytOH/85PPK8WQZ4vSB77INLa2sqHhV/TXNeErkmHd7AP0V4De3caDAEeKH49BE/bn9q253Vqcsyw2FLd0vnfm/91gq0vFqByscPeufOcnShCc5UBmVxgzl3hLHowGqVjz/N6HV8otE06Nr51hKqP1Fj0FiJvCue1Nc9g7zB06VSHiwvVY4e2OAMpKSlceumlI23KoFNXV0dKSgoLFy4cdSvNi3NKuW3OU8jUzZjiw9Fffyl02IbX0WOfPLap07VhLiLqynpMBiOegd7MlU26oEZdRhrJYx8EWlpaWFv0LY01DWjqmwmKCSYp3HVAdY1WQa8sbyD7SClzLk3A3n54vIczRR0geLwrPlGOWC1dXxM925OrnooneFzv97+jqDdWavj0vp9ozVDi5ObIXz74E3NvnDFQ0yWGEZlMhru7O6dOnSIiImKkzRlUvL29ueaaa9i7dy/+/v7Ex8ePtEk2whJD0N5xLY5fbEWRW4Ts/R9o+e1iRNe+zaF7BrSFija0tPJV2UZSzAdItiQxefLkoTT7okDy2M8BvV7PR6e+obmusU3Q40IJcx7Y7RxJQYfeRf1kfhVTkqNRqUZO1AeTjqJenlHPh3duQFbnwMRZ43nk4/v6lHDmfOJC9tjb2bZtG2PHjr1g524rKirIzc1l+vTpoyqVrdlkZkHy31AezMXq6kTL75Zg9T+d36E3z72d5rommmob8Y8KZIZlHBMnThx64y9QJGEfAKeH3BsxtprwCfEd8Dz5SAs69CzqaXvzsbdXcMnk4fOEhlrUoU3YRatIxlsn+fHf+1Bgzx2rl3PL49f1mBL2fOViEPaWlhb27t3LwoULR9qUIaO5uZktW7awYMECPDxGT5AkURT56t8/8O7D67A62NNy29VY/TqHmu2rwNeWVGMymPAJ82OWOIEJEyYMrfEXIJKw9wOLxcK7eZ/RWNOA2WDCK8iHAY64AyMv6j0Jem1NM4cyi5i7IBGlcvhmbIZL1FvqDfz4l4MU76pF79HIf79/jbGzEoa+8RHiYhB2gOrqaurq6hgzZsxImzJkmM1m9uzZQ2hoKJGR5xauebDZ/MEOXrz9TazOjuhuvxrRq/O6gI7iDr178C3NOryCfVjsNEtaZNcPJGHvA6Io8vbxT9A1aVFX1BMQHUSUx8C9upEWdOhZ1DXNetL3nSB5VixOzsOXpnG4RL00tY5N9x9EV92K40QLv3n9Mm6efvfQNz6CXCzCDrBjxw7mzp17wayS745Tp05RXFzM7NmzR1Xwl/+9tok37/8Aq7szuj/8qss59/4IvF7TQkN1A37h/lznc/kFO9UymEjC3gupqalUuB2lqqSWkKgAwj1H5nb1JMSDyYkjavR6IzNmjh7vVWtuGJR6LGYr3z5bwPfPFyDIBCbeE47ndDseuunZQal/NHMxCXtzczMHDx5k3rx5I23KkFNdXc3evXu54oorRk2u9N9v/hLNZzloPz6GXZgr6luug192lvRH0OH0VmBRFKkurcNsMhMU6c9sz2txcTl/kxkNNZKwd0NxcTGHDNuoKqklKCoAuVw2Yp72cIi61WrlcFoVsXFB+PmdnSBipBgsUa8r1fPmisPkpzbiH+7DI5+sJK/yGFdfffWoi/A1FFxMwg6Qnp6On58f4eHhI23KkKPRaMjMzGTq1KmjZlGdKIr86trHaPnhJIox3tRfdw0oTv/O+iPwHdcvWa1WCo4V4+nrjuGIE8uXLx9VoxWjhQt7rGoAaDQaNhZ9xOaTn2EwmAiNDSLU1Twiou7nODyiLooi+7YVERDgMapEfbDI+rGGx5P3kZ/ayNwbk3nr4AtoZY1MnTr1ohD1i5EpU6Zw6NAhLga/xcXFhblz57Jnzx6OHTs20uYAIAgC//v2H6jmhGA6Vodf2nbiJqtt55sq7DsFsDmQ3XkuvmMmyRKdzBa0SiaTEZMUgYePG/qACr7NeZeUlJSh7cx5iOSx/4IoivxY8jH11Q1oGrSEx4cQ7HxuyVHOheEaem9uauHEUTXTk+OHbX96XzlXb91itvLV306w4aVTKOxl3PPaH1nyhwWIosjWrVtZtGjRIFk6+rnYPHaA+vp6CgoKmDp16kibMiy0J8YJDQ0lODh4pM0BwGgwcf/Mxzlx8BTuj07HYXYIAHkHTq+YH+jwPIDFYqUot5TQ6EAuUS0kJCRksLtwXiIJO5CdnU2+PJWqkhrC4oKRyS7sYfd29A0y9u05zpKlk1AqR17Us7ZWcmx3DTevTkJPU+8X9IC6opU3Vxwmd08DflGO3PfxBKZO/wsAu3fvZvr06aMmTOdwcDEKO7QtpJs/f/5ImzGsZGVl0dLSMqKftdFg4v1HPqGpvpnqolqy9+QiOCvw+e8i5J5teeQ7ijsMfHgeoKa8DoPeSHBUAJcF/AalsouUtBcRF/U4pFarJaXma8qrqgiODiAiIfScBX04hdnZbuD7WLVaPTnHTnLFlZNRKIb+a+Ck8Oz2nKahlf/+3162fJgLwOTrPQhO7H5hTG/9PvBjBa/+YR+aOhNTfuXHH98cS4T/nUDbHJ3Var2oRP1iZsqUKWRkZDBlypSRNmXYuOSSS6ipqWHv3r3MmDFj2DMS/n7zl5grtdS++mOn46LOhKVSZxP29qH5qorOq+b9A3UAlKnbnkvBnmbg9PB8mItoG5pvF3jfIG+sVisnjpxC2/Q+XrWxLFiwYCi6d15w0Qr7hg0baPQrxNhqJDQ26LwSdDg3Uc8+UoS6QcvcecMTm7knUd/3fSGv3rUTdVULgtCWd11m1/2DqKd+m01W1q0+zHcv5aJQ2nHv63/gqrsu7/Rg27Vr10XntV7MODs7o9PpMJlMF9XLnK+vLzU1NezYsWPYY+ivXXwjv9/8JY5LImn5sRDHpVE43xiPYC9H5np23gX/QF0nca+qcLKJO7QJfLu4Q5vAt3vvHQVeJpMROz4Si9lCXlU6upMlzHC/Cm/vwck+eT5x0S2eq6qq4oeTH1CiPIKzmxMBYX7nlag723mck6jX1jahazEwe87wBPDoSdQ/eeYAT177Ixq1kdv+cQuX3jILADtl/7+Woijy3E17+O6lXIJiAngt9VmuvntRJ1FvampCEISL6gEv0ZbSNSMjY6TNGHbGjh1LcnIyP//8M2azufcLBpG1i2/k009XI/NS0fJTIaLZ2qWot9NRyOFsL77de2+n4+I66JwRUm4nJyI+BE2jlg15a/n4448vikWUHblohF0URTYVr2VL0ecY9AYi4kOI9Dq3YDHDtWq9nXMRdICjh4s4eaKSadPjhmV4ridRz95Twdqn9uMX5sJbWS9w86PXgkMRAKbWrsPz9tT/zM2VZGwsJ2lOAm8eeI7oS84Ogbt//34pwcRFiJeXF0ajkYaGwdk6eT7h4OBAXFwcP/74I1br8KWHBnByc+KR/9wJZhHtl7m9lvcP1HUS+KoKp04CX6a26yTwxRqh29XzAJ6+7rh5u9LoWcT6kx9QVlZ2rl06b7gohuIrKyvZr9lEVWktQRH+yO36np+7O86noXeAwoIqRFEkecbwZIfqSdR1zUae+/02AB75+EHCEoKp1r+Po3ubJ61rOHs3Qk/9t5itrH3sEDKZwL3/uR1HF4ezypSWluLh4YGTU98yT0lcWEyYMIGsrKwBLaSrPFVNWV5Fv64JiQ8aNYmEgoKCcHBwYNeuXcydO/ecX+pFUSQv4yQatbbXso4uKpzcHNFtL8LllkTkPr0/OM9laB7aBL597l3lYE90Uji1FfX8zNd4WzxZEnrrsK87GG4uaGFv38JWU16PxWwhNCbIdq49u9dABP5cRf1cRfpMehJRgJKSatTVRubOnTSo7Q6UN1bupqpIwy2PXdcpPruzR5uwa+qNZ92jM/uoM53eE/vz2lOU5DSxeMV8IpLCumwzNzeX2bNnD1YXJM4z3N3dUalU1NXV9WvOtarlPe6ZvoPm2v49J+yUMn771Diuvj8OV9X1/TV30PH09GTy5Mls2LCBxYsXD3g6Six7lWMHmvnLdUf6fe1v8g5w5fyYHssIrn6//J8GgGpF5yH6n4+34u7dOUFHRy8dzl4xD+AT6IUoipw6XsoPhjVMcV5CYGBgP3tw/nDBCntjYyO7ar+l7FQV4XHBXb6h9VfUB8NLH25RP3ToJFarlblzR0eGpJ1fnWTrR7nETo7i1idvsB33c7idsNDdQB6ttZ2/lj2JeqvOzKdPH0XpIGfZ0zd12WZtbS0+Pj6jJuSmxMgwZcoUdu/e3S+vvb6sleZaI+ETXJl6rT/28rNHg87EbLTy49sn+OixQ2RsKueRj2YTEOHX63VDjbOzM+PHjyclJWXAGfCE4JUE1r6ATA6OTnJuvCsYdL0nebC3F5i70BVq68Cn+xcrsbm6g7iDn8mJaoUOg8HE15+m8tG7KTTprUyYmcgfnrgFubzvs8mCIBCZGEplcTWbaz7DPS2C6667rs/Xn09ckMK+a9cuShwO4eCoIiK+64AFF4Ooa7V6NJoWZs8eN6jtDpS6ci2v3pmCytGOR9fdh90Z2+w8/Nui3qkr9X2u8/tXcmmo1PPbJ36Nd5BXl2Wys7MvirjhEj1jZ2eHXC7HYrH0OQxp+fG24eZJV/py9QORff4NL74jmrfuySDtuzLuGH8/f37ljyxaMX/Eh4BDQ0Px8/Njx44dzJs3b0D2eF7yIBNn38GBlAZmLfEmONKhTbCBVoMZlX3PsqItrqBJ6UhQQNdRLrsS95c//4lPP9rD+5//GYvZwqOrNpCdnsv4GYmEOlkp0cmwWq1o6psowaPHNNoBYX5YzBZKdMfZUPgh83yvx9nZud/3YTRzQS2eM5vNbCpeyzHDXhwcVV3OtcLwi/q5rmTvit5EvaCgnPT0nFEj6gCv37sLTYOBO/69guDYzsNgp7JLeP3e9wGQyU8/bHry1rUNRr57+ThuPvbc+OA1XbbZ/hAf6QeqxOigfV97X6nPiQMgOLHtwd/XaIhuPioe/nwWK9+fjkwm8OIf3uIfN7+MtlHX+8VDjL29Pb6+vuzbt2/AdcxfdgsAadvbfo9WL0/e+eYg4Uv/Q1l1c4/Xph8tJzz5bwRNWs2qFzZ1WUZsrrb9v9lsYdv/DnHN9VMICfUiPNKXUG8lBbvbPkeLxUqokxWHxlrWPvEe/7xxFc/c/x6ff7ybukp1l/XL7eREJITSUNfEhpNrOXjwYL/vwWjmgvHYKyoqSGvaSHVZHeFxXYdTvBDm06F3UdfrDRw/XsKSJaMnlObe7wrZ+90pkuYkcOWfOg8D/vThDv7z5/cw6I1cfV8c1z3YNu/eWz83vJGHXmPm1lU3d/sSl5GRIa2El7Dh4OCAXq9HFMU+vewd3XMcgNjpp3/HWnNDn37XgiAw/3cRjJnty0vL9rHzy1Ry00/y6CcrGTMjbuCdGATGjBlDRUUFu3btYs6cOf2+PmlO22/0eGYz1b9y5fo/raGiupmPnr6aYD/XHq9dMC2Cpl0PcSi/CotL92Xbxb28UUZtnYYb5k+xDc0Xn6pl4ZLxTPQxklnTtl7AL8SHF9b9H4cLGyk6WsAnT65hxzpPnv/0QWR2ck4ePUVgmB9+IT62Nrz9PWmobSKt7keqirMvmIV1F4SwbypeS3VpHV7+HoMm6qNx6B16F7vWViNpaTksXTp91HxBWzRG3rhvNwqljPv/+yebXXqtnv/c+z5bP9qJk5sjf/loGtOv6T7GdUdvvaXZxPr/5OHipeTKO7ueLzSbzej1+lGT8Uqiez775//Y/W3aOdUhCAKzfz2dmx66psfvfmRkJCdOnEDQ2vH6fWswGbrPCVF0tISgmADc/Lrfg90bvmFO/GPbAr589hhf/fMYf527mt+tup5bHrsOud3IZSYLDAxErVZTWlra7xjr/uG+ePi5cfywiKe7I79aNI67fj8TRwelbVi+JxwdFMwY37c2a4qLqKvXEB/btvjZz+REg1pHXGLbqN8kXxMHa5WIoojVKjI+0h1DSxDBcaHMumE+TSp3KtMy+fC5r9DrWvHwcSN6bDjX/XExAWF+ePi44e7tSkF2MetNHzLP99e4uvb8cjLaOa+F3Wq10mL+H95qNVPHBeDg0NOPr/ttTgNJNtJf0e5NkAcDk8nMxo2pLF489fSDrblqyNvtjQ8fOUxtmZZbV99AaHzbj/PYwfd54Za9lOdriJ7kyeovriAg0q3Hejrewx/eyUTXaGLFMzfj4Ny1t37ixAkiIyMHryMSQ0LRu3fw4aq236BSCZwZS6SP76dmM+QfKKBk+9esvNcF+6ve6rJcWFgY321YRfbnenL2FWPv2P1UjVwJC5b7dvl77+033fFFVG4n4+bVSYyb78fLK1JZ+9SX7P/pZ/7yQTKRsb/vWweHgLFjx7J79270ej2xsbF9vk786c/ERehJSzPSlJrH/eGOsCsLyy/nTaU9D8crQjoKZ0GPZQsOlOAts2D+6gcADharaSmvZ3ZTHd47MwE4M53T4/d9xa2zo7j/qlAcHOp4s6KUWxYm8OTqW2lo1LEvPZ9pPo4EhXZ4uQgLpbpajcm0g5ycGBITE/twJ0Yn562wNzc3YxI2UVhQxZixoQOu50IRdYA9e44ye/Y4nJx+EbpRIOp5WQ18/85JgqOd+c0jv0IURb5543nWPHgQk8HK1ffFces/xuPu1LOod0SvNfL1S4dwdrfnmnsWd1uusLCQpUuXDkY3JIaQTz5twWqF1U+4MnOGPdbyxk7nZUF9SyXc2Ghl9VNNbN1moK7OypNzW3By7Xq0xsPDmT0bsvEKduW9k1cjCEKP6zkGgpPC86w6xsz25ZWMJbx1TwZ7vy7h/ik/8qfXarni938dsRG2WbNmsXnzZvz9/fvsqcoWv0nMp8tISzNSUGBm6hT3Tp+bIsS1R3E3lTafIe7dMz7EgyhfZ3Ycr2JCqCevb89nZowPnloDoquq031raTXx/k/HMZgsPHj9BOQFp9BHRXAsv4ryykZMDZX4+4dy3dW/TFM2V4Grv+16Pz9PystrkckO8M03x/n1r3/dJxtHG+fl4rn8/HwadN9iNJpJHCOJOkBmZh7jxkXi6/uLfaNA1K1Wkdf+moXVCivf/j+UKiXrnv6at+87gMrZjse/ncNtL0zE3cmn98o6sOOzEzTXt/Kre6/q9sFdVlY2alJXSnTPqaPF7NxlIDrKjhnJ55aRy91dxvP/cmf6NCVZh0w8dd0L3ZZ1al1ETVMd064MGrCgDlT4nT2UPLBuBivfn44owisr0nju9/+hRdP33SCDiSAILF68mMzMzH6Fno2OavML9+9vm+Y88wWsK+E+Ua/lrh+OcNcPR0hPL+1TOzF+LiRHefPwV4eY+ewWYnxdeP6GS2jWmxAr2jLAWSxtq+C/3F3Az4fLefzmScjlMkRRxHgkj6kTQjEYzcz59X946JF3beWBs56VQUE+REcHERfXjNX6MxaLhfON807Yt23bhontWCxWXLt5qPeF4RD14aK4uAqDwYSXV9+93uHg569Kyc9q4NJbZjFh/ljqyuv5/Llv8Ap25OX9S5iyNKj3SrrA3rHtgdLT/GROTg4JCQndnpcYHbz78DpEEZb93rFbgT3Tg+8JlUpg9ROuJI1VcOjnbCoKun7B9Qv2QY4dp3Jru61rMF7Ku6ujfWHdy/sXEzPFi+2f7ObPUx6m4HDRObc5EARBYNq0aWzcuLHPcdUveeANAvxlrN/Yys87WoHexb3VbGVhlA+fHC5jR2HdWbtmq/cAACAASURBVF59e9utJgtW62k77r40lv2rF7Pv8ct56IoEPJyU3LMug63HKrGUNSCXy6hvbuVfXxxk0aRQbpwTbeuXq5OS3ye48eO6O9n59b3knazhs3WdM8/RXNVJ4O3s5IwdG8GJE2WYzdvRanuPsjeaOK+EXWv8Bk+/HMIj/PDz69vwXJf1DJOoD4e3XllZz4kT5cyYMfb0wVHgrRv0Ftb8PRuFvYzb/tG2NWbd37/B2GrhN0+MxTu47aVsIPdo+lURKOwV7Po6tcvzDQ0NODk5XfQ5mYeShpomTmadOqe/rR/vJGPzISaMVzBlshKDsc0z6uvQe3fI5QILL2sLRrTzy66/IyFxQUyaOonUlBPUlrRtQRuIB36uw/UBUS48+/MCrrk/nrL8Su6d/hjr/7tlRJKWODo6Mm7cOPbs2dOn8g5OKv6+/UWcnAReelnDsZyuFyF2FPd4b2euGxPAhAA3xvm3He8o7oIgYDJbeXbDMSY/vZn4R9fzeXqR7X64OyqRy9pka+0fZ7AgwR9BELCUNfDhN4eIDXLn9kXxyGSnXxLbvXMxOw9np7Z1WNW1mk5b6mz88uw0GIw0NWmJiwslL68UUdx1XsWaPy/m2K1WK5Yf76aorBF3eztK09MI9XVGpexsvuB3RoCSbiIc9eTndwyM0AlTD6vqO8zR9JlBEt/jB7KZkxzfbX1dfnnPoNs+97Oejnz7Rim1ZXpufPAa/P6fvfOMjqpaG/Bzpk/KpPeEkBAIvffeRJqAFxELfIKCBSzYUVBAxIIo6FXBdhUEFFAQREDp0kPvCSUhISG9TTLJ9PP9mAApk2TSADHPWln34ulnzt7vfnuoD4kXk9n83TZCGrtw3wNBSAuL3mdh1d+DM9CxvzcHNicQf/hrQiM1oHnoxvYzZ87Qvn37Kp+3nsqxbplCdLSJV6fnYKxZuwUAjKKeLPUZmo+/St8wb57qHEozH9eyO9rx11bko+3aUEQmhV1LVtoaDNlh5JNDOBR1iD0rkhn/drHU0GJjyRmqN76LUeniVQ7PfjKAjv0bMX/CNj6b8g0ndu7gxa/64eJeOiysbgkLC8NoNBIXF0dYWNlGSqUJbRbMzF9nMGPou8yZk8Onb8rw87YJ1byD9qPj880WUnP1+Btk6JNsH5E+6ea+n528wvHUbDb0a0uORuTxtSfo5upEoKttsbZg7yU2X0jDVSljZt8mdCxaCD7bLJBJjf2wHklCX5TOmG808/a2aJo38aF/Mz+Eowns3X+BF9r6YfnzULnPtS8mjQEfbcfbRcni/+uEVyNvBOBY37f+EXPLHS/YDQYD4l/PczY+i3YRPry78ggfrD5OocGMn4eaN8d24NmRrVh+OAm9MZ7wIA8ahXgQ0jKcqiaSOCLgylBs0IuieGNlKZGUNYaYTGYsFitibsqN/ZRKOVKpBKPRjF5vRBRt55HLpTg7V1wCdcfuM/ToGolCUf2fsS6Eek6miZ+/TETjIbsxqS6dtQqrRWTCzBZIZTU3FPUdHcKBzcnsWHOViTNLtqA1GAz1zV7qCKNRZMHCPIxGGDZUhUJR1nwu5hscPt/J3KtoLQXseKI7C/Zc5p2dF3itVwTtAtwczjW3h6uzQPvmAlGnRRIvXCtTEAmgz4Pd8XzenV+/ieLRmZ1KaHm3g67DG7Lk+Fg+GLeVv9dcJiYqjTdXZtO820OVH1yLREZGsmvXLgICAhwqw9xxUBumfjaJ/z77LbP+a+bj6TKc1eW/y8u5BTjJpPioy1rUsvRGNiekM6tTBG5KORq9iIdazsWMfAJdVSw+FMffVzJZNKwlR5JymLf7Aj892AFVkVvu+v9e/27UMimDGvuyJTGb5Qfi8HBSMGdUa3pHVtygp3ekL5n/fYDL6XkEuqnxc1NTaDSTvelttma+UO2SvLeKO1qwa7VaJDteptBooV2ELcBq5iMdmfFwBzJy9SSk5+PhokTw8yIxLZo9xxK4nJjNleRcfvvuCQb3bcajzy4jNMSTFk0CaNHEn1ZNA5DZ8c3WVKifPRvHxInzyc3V4evrztKl0wkPvzmZWK1WJkz4gOjoBASrGbPFyqkzCfy5djr39G/NzLmr+HbZThoV1ZTu06MZC+aNK/fS0ReScHdzRqksv5lDVQVybbHi0wQK8ixM/fRxXNyduXQ8jl0/76NxW3d6jaieX7003YcGoHaRsWNNAhM+fOdGRlRycjJBQbVzjXrKsuxHHVevWhg5Qs2Up+2X4bQmlQ3ASs4pZPHOi0glAiPbBdO2gQe5BUZO/JJPv4b+eKoVvNgjnE/3x7LuXDLtAtwqFepWq1ihMO7VUULUaQu71xzg0Rllo5udXNUMfnAwP/+wmpO7kmjX//YHW/qGuPLR9lEsn3uYlfOO8mLvtTw2R8FD00fZVRbqip49e7J+/XpGjRrlUPndEVPu5Wp0Er99vpkPvrYw+zkprl29S2jt1xdqJzO1+DspURebh69vi87WIYoiEW62hXmm3kSkkxMXM3U083VlQ3Qqr/eOoJWfhjAPJ74+HE9CTiFNvO1/i1KJwODGvgxu7Is8REOBwYxTJSVvr6NRy2nX4Ka1Ra2QEeShRoj6lBVpaTz66KMOned2cMf62NPT0zH/9SLJWQV4aUquGgVBwMddTYfGPjRqazMXvfF4DzZ9/jAx+96m4OJH3NMrEovFSo9O4eTkFvLNiv3c++hiDEYzF+PSefqN1Xz70wEOHrtCHnZMf1XAbLYwdeqnvP76Q8TELOPJJ4czefKCEvtIJBJWrJjJ0Z3vcGT3e3z/xVMEBnhwT//WWK1W1GoF06YM4fCueRzeNa9CoX4tOYvUtFzaty3fVHb+2Cl27LvA8rVH+O7ng+TrDOTrDPz462F++eME+w7HciWrcg2lssVBVraOgkIjugIDr767HoDta9Nw85Qx7KmBAOxebStd+eDzTWotpUflJKNFFy9S4gtIv3pz8oiJiaFp01vTmvbfxpl90fy6rpCAAAmPT3DcInIlI5/x3+wnM9+Ak0LKI1/t4/y1XJyVMq5mFRDm44zFKuLjrKSVv4aUPAMXMioPVjqXnFvh9qbhtm/t/MEL5e4zZNIAAD6ZvIPEi+UE6d3imBWpTMJjc7owf/tIPP2d+H7mT8wc/j7azLxbdg8ymYyuXbuyb98+h495+pPHaD+wFUfOiJy9aLNIunYt6w69pjPQxluDslgDF3ORBfNiro5gFxWqIqtetsFEgdmCv6uK6PR8BAHa+NuChLMLTXQL8eDgVVvMVGVxCaarWoeFenm4quRE+muIvLAc07cP1+hcdckdqbFfu3YN5b63MFmsNAosP9K7PJ968Y4/UyfcbNV5fVUol0lw16hZteE4sy79ScMGPuzf+g6r1x5g87aTBAV4EBTgSddOEbRrU47wLKatp6Zmcfp0HKNH9wHgwQf78sILn5Obm4+bW7GVZNEEYbFY+eKbrfzfQ7Z7EwQBq1UkJzcfrbYAUQQ3t/IjAaIvXKNnN5vwWrlmH4eOXCL2Shpx8WksfG889/RvzcCHvsTZSUGgnwa1Ss7IQS0xmSwsXRNFQaGR5DQtRrPItZjFbNl2gldmriDAz50Afw+6dWrMM5Pu4eSh48TGZ+Dp7ozJbCHAV0PzJv4sX3uE/Ufi2H8kjjMxyfz+w2SG9GvOsAG2gg4NI505eySPAm0hbt5yGkXaellfvVB7E5O+wMy5qEz8QpzwDr75HdTEfFtP+RTkFTL/sc8RRXjlJQ0qlePvOCZFi7NSxhfjOwGQbzDz+fYLfPJQewLc1ey9kE63tiGAQISXM3uuZHElp6BcLew6TSwV38PmPbagqc6eJ8vdp2WPpkx4uRc/fXyYF3uu5d2Nw4js5H9HBKC26RPEkuNj+fD/tnF4ywmebv8qb61+mWZdKm59WlsEBQWRnZ3tcOqoVCalde8WHNt2GnOxDLHrmvuWhHS+OXeVvdey6RPkyc7ETPoEeSIRBORF1gilVIKTTEq+yYKLXEactgCjRaShRcGetFwauKlxkhcJ/UITBosV1yoI66rkz1dEyyA3jsVn0/7bh5FP+qnG56tt7jjBHh8fj3zfLFTOCtTK8ivJORooV+KYogm/YYgXH7xx3w3zu6GopGSDEG/CG/qSdC2Lk2cSsIqifcFeKpgmKSmDoKCb15fJpAQGepGQkEarVkWTU7GJorDQyLqNhzm4/Z0b96VQyNi89QR7D8Tg7eXKq88PZ2C/VmUuffjoZTq2C7/hV7+amIlCLmPIwDaENfSlQ9twRG0qiUfm2H0H236earumxu/GCrdju3A+fncc11KySU7JuWHejDoRz9fL95OVU4BcLuXJR7vTvIk/udpCXF2UzHpxML26hOPtaXvGvt1sE06nfh6cOazl6F8n6f9ILzoN9EcmF9j3xzXGTy+/mlP0hSROnIqnaZNAIhsHoi7ywel0evYciGb7rrNs332GpUueITNGoCDPzIip990wUVanNGY9jvH1K8tIjk3lwTFqWrYo6f4xmS38EZVA9+Z++LqXXZAej8+mbQMP8vQmXFVyBrcK5Nvdl9h/KZ2Hu4Ty/h9neaxnOIEFFiI8nTmclM3LPRuVey8mC/x5VEqBQUDiVk6OsQibdlvxcoeB3SpeADy34F3yrS+w67NkXun/G6OntUUulM4pjwZlzTqAeQc5M3B8pMOtRo1GEx9/9hNPLxlO86X+LJt9mJd6v8XIZ4fg6nnzXhRKOf0e6Yl3YO1n4bRs2fKGv90Rk7yh0BZfoSjlIXTt6s0AixVvtYLzYfmcyNDy3tHLdPV3Z/qBGIY39OGeEB/6BXnxy+UU4rQF+DspWXI2ge7+HkS4OfNnQgaeagUFJitKmZSE3EIsVpEG7raCXI4u6GtDuMukEjo09OREQjatv3kY+aSVd5RCcUcJ9vj4ePh8EoVWEQ9XFeWF4MhDNFAmt7XisoQVIQXMQEegY5gMwnwBX0CPdf/flZ8gw4BYmId4fLvt31YRa0E+RB9CNMeVWXT8+ksUkeHeRPhIbpi6pz7UjplP9wBgb1QsoyYs4sLfM/D0uGnyzMzWUZCZimtjF0StTft9bUSpCTA73qFnFovqOYuAFzCosz9QLBBQm8qkh7sx6eFuZY4tbgWxR+f+Hnw/P56Da36iX+9jOGv8aNfHl8PbUkm+oiOgoe2ZrFYrh45c4tjJK0ydPIgjx2P54putXLiUTE6ujhmv3M87M8YwdMyHJCZlMaBPS6a/OILQEG9Wv3McgIHjbt7L5cuX6dOnj0PPX49jWLdM4cBBA398oyUsTMr4cc4l8sp/PZLA3N/PcO5aLl+O78Skovxh01UtVlFEIgj4WQV+OZlKrocPKOUEG0x46kT27L7KC20a4m2S8P4Px/igW1OS8grxkMoR083oC+yH3W+Mc2LZjuuSo/z2nAAT7pegkFc+4XYbEUavXq15/9GtrJh3xLGXUw12rbrEmyvvwdWj/KA0q9XKmqXrmTF3Fc7OSl6e3JdHJypoFtGC95+L5teFG8scs+qDn3htUSSd+nogBL9Qq/fcvn17du3axYABAyrcz/zdIxQeti20lAqhTI66poGKTlIJnXzduV5EV5uu4PVGLRER0abLUaOgv2cA03ZHY7BY6eHjxYSmNmtBzwAP3jp0AX0jI3qVyFd74+gV4EmoUXEjur4iVEE3g/UqK3nrKM2RcPRIIq0Th+M0e+MdI9zvGMGemJgIn0/CS61AWkFATG2YURzFkXxawc+LEGk+SWk3zcxmi5XkjHxC7HQ5EkWRpWsOlxGYHsU0nZ6dwwkN9iT6chrdO9osBmazhV0HLjHq3mJavAPNFhzCAWtHVQhv5oxfsJKonVmYjFYUmofo+aAPh7ctYc+GRIY9Ecrzry3lzx2nKCw0MnpEZ6xWK+PG9mLc2F6Iokhaeu6N/NONq17DtVj3ttxMA4e3pxLRLozQ5iU19DtlYN0tZGZZWLgoD4UCpr+mQSEXSojSlsHurJnSiz9OJrH1bAoTe4bfyDOWFP0WwyL9+OTvS1zMLaCttyvuSjl6ixU3hW2fV9uF8+25q9z7exQpBQZeb98Ifyf71jqtXuCXIxo0XjKm//gckgq0X4VKQYsekQ4FnYWH/weTycT30SO4GnPN8RfkIKIIaz/9g8Obj/Nsl1+Ys24IwZHunD0bh8FgIjNTi06n54EH+vD55+tY8NFPzJ0xhnFjexVp+E607wXf7erAxVMl4w9iz+v44aN4ZvzfWcY+E8yERWZk8tqb2jUaDe7u7ly4cKHSevIFhTYroLMa5L4Vl5UF0PgYIb1kdPy4sFDGhYWSYzQil0hQ5MtAbaSNt4ZWXq4M2XgYT6UcL5Wc8ZFBuNTis1YVQRBo46/hRIqWtrOHo75DhPsdIdivXbuGedFELKL4jxPqAH5ezrRt4seKTad5eHBLVmw6TecWgbi5qjB7eJR4ybHxmRw+mcCG7yeVONfFuHT8vF0RRZGjp6+SnplP88Y3I/X3H7lC7y6NHDbj3U4EQaD7IC/W/e8apw7m0jEceozqxKfPfM3fvyUx5rkmhDbw5ocvn6ZPz2bISw1MQRDw8735/l1LtWTdvS4Ri1lkwKM3tfWMjAy8vEq5Z+qpEVarlY8/ySNXKzLlGRcahpadLhr7uiIpinT/cscFrmToaOR7MxjVKtrSlbr4ubMuNgUftYJQVzV5RjN+Ra6Wxu7OzOrcmGSdnkZuFQflrTuhpEBbyDOfTKDT4Ha19qwNGjRg586d9OvXD98GVStx7CjtBrTkh7dW8fMH63i+269M/KQ9T7z2Dmq1Ei8vDYGBXjzwQB+eeGIoTz55Hypj2eI3Gnc5HXqXLJbVobcH7Xq48+6UaFYtTuR01JPMWDsf35DaW7C3b9+eDRs2EB4ejkxmX2zInliJbvGDADiVY5BQBTmmXQO42ykwNa9rJM8XGIjVFhDh5oyHqvysoNLok4wltPbaQhAE2gW4cTIll1azh+M8549av0ZVue1SIisrC+GziWiUshsFCOxRnlCviwpNVRHqYPthv3xzKJ//fIQWDyzhf+tPsHjGEPDx5v5J33H8zM2KRas3HufB+9rhXEoj+eCLbfQd818GPvQlcz7Zws9fPoZ7UQCdNk+PUinFx6uYj+8O1dav02Ow7f3s3m7LF3Xz1tCujzcxx7K5ejGPt18fzcB+rcoIdUdITSgAwKfYxHXu3Ln6aPha5tdPNnL0mIlOHRWMGG5/bF6PxwjzcSHQw4mtZ2/GkohFpniAZ1uFIhUEXtp7nhF/HOF8dj7DG97MJXaSSSsV6gDRqVIEQbyRcVHbWK0Vm/ZrglQq5Yn3HmHmzy8iWkUWP3WIL1+fTWLiak6d+o4tW+YD4OysRqUqK4AqSsmNaOnCl5va0m+kD+eO5jGlw2sc23661u5dEASGDh1aaVW6HC1IBHAuMkDam7dLC1eNT+WCXltMq/dzUtLN38NuHnxptl3NYO3lFM5n52OyWh1eVFSH1n4aTqVoKZh1+xtPCeLtqF1YhE6nQ/fuaApMFvxcypreLmbm8+Kms+xLyGLG8Ja8MbxkIZLrEdCpuYXsu5SBzmCmQ0NPmheLpBdFEaso3jAPVoaj5SzLBO/ZoxaEpiiK7D546UZgGlB7Qh3qTLBbrSKP9TqCNltgVfI3qJ1V7F66gHcnHmL01MY8Pa91tc8dH61lUtetNO3SmM/2zwNsPQTu9KIRtxOTyURUVBQ9evRwaP+Yw5d4ocdMNK5Wlnzhibv7zfFTunb79XzyhX9Fs+1sMr+/0BdLks01ZTBbMFisaJRyChMNrI1NxVUuZVA1teIv/laz+6KCb88uJLRZ7eadx8TEoFaradCg+o2lHOXS8TjeGjGHjCQdgyY0ZdqSvsgVdoLTSkXnV5Z+Kooiv/+YwpI5sVgtMHHeI5X2p68KUVFRtGjRotwCUGP8nkCNlv+9VyrAspRJ3p6A1aZXLqgdWQQUZ8mZBNbGphCdnY/RYuWLPi0Z3cifz2ITUEolhLipCXZT0cpPg1pe1ZJm9jmdqqWlrytOt1Fzv22meJPJROG80SRpC2no4YTeXDa6VSoIfPZ4F15ZdYysAgN6U9l9DCYLn/wVzZmkXNRyKasPx/PmsBa0C7VFiK6OiufLHRdJyNIxukMIrw9rgbedRcR1JMbKuxsJvl5gqGQ/by/Q26+dXBUSk3NwdVahL36uyq7tKLV0j+XRd/xgVs5by7aVu7lnfB/a9ffCxVPKxmWXSLpScqD3/U8wPYaVrQ5mD7+GKjoPb8uB349yeOtxglv64+TkhF6vr4vHuCswmUwYDAaH3pFOW8DchxZgNBl5/nkNKicreuNNTdZqZxxigcm9G/Ht35c4lZjN2bOpDI/049nfT/NAy0D6hXlhsFgZFmoT6PbGuyMEexixiFLO7D+HX1jtLkpDQkLYvXs3vr4VVyWrDYKbBfDR7pHMfXALm78/y9WLmcz46V7cvEu6ndCXEmQKD0RtWoXnHvSgNw2aKHh/WhJfT1/Gmf1nefHrp3F2wCJynd+X/MWpv8+WvLRKwcgpg9mxYwcDBw4ss1jQZuaRmZZNl6Ht0JvOlNhmKvV7W30l/H0snU6+bjfcrwqPQrQZFQt3fYoUjbfjwn1C0yAmNA3CKook6Qy4yKXozRZyMvVcMRr49dw1EnML2TCuC+5qOfd8f4AGGjXBbmoCNEpm9GlMRoGRCxk6fJyVeDvLcVfJb1ii7NHATc2RpBy0GzcyfPhwh++1NrktGrsoimRMuod9ydklqg8pfUqu8q5H1c7ddYFwDycebRNcZtvWS+nsv5rF5A6hBGpUvP/3RXycFEzqGMqZVC3LTybyQItAOga58/qf5+ga4sH9zQPq9PmkfmUHkCVVV+k+pTGYLByLz6JbRMXajcSnemk4gkctdYOzd57sXDIyTMx99RrhTZS88IY/QnAYm3+8wuZlV8rs7uImY/Y3zZDbKVFqjysXClj42iWatHGh/zgngltNdLiX9L8Rs9nMuXPnaN26YkuJecPb/LjeyvHzIv27CAxpoSc138DpVC0DG5X/HRrSTZzPzuelvedxkUvxVSuZ3bkxnio50ipoi7qcin2mSVqBZScV9HmwG6On1f6kGRUVRadOnW5ZAJRBH8WKd49wYkcSXoHOPDmn+Y2skeuIulK+9uyKC/NcJy/PwtLFGVw8r8fHT8bEZ30IHvBshceIMV9jNFqZPuUq9rqVSqXQcYBAz35uhPZ59eZzfPsKsSkCizcp6NPKzPBOFS/cLKLIgz8f4bW24bT1vjluK/v9r+PsXvsKickqEp2dR1qBkdRCIzqThcktQjiVoWXhyTiyDWb0FistPFz4uGczNsensfVqJu5KGW4KGR193egR4EmSTo+/WkmAsxLx9c9uS23526KxZ08eRHS2jj5BN83Z9oIargtvuVSgmY8LXUJuBo1YrLZAu++OJTAowod7m/jiJJfycOsgdsdl0spfw8aYVPqH+/Bo22DcVXIeaBlIfE4BYZ5O+DqXr7XXlNJ+JdNVLYQoKtzHHvsupvNQl1AC7eQGX6e6nbAcciU4SmlzfnoGNLAFUO3rKuXYoQKCND6EDnybbgPh1UX5WIv1Q/75g9/45ZPfKUhwYvBYxxpudOsAJ34XOb43B6tOyb333tpmGf80TCYTEomEbt3Kpi8WZ8MSL+KiLXSLEOjZOY35u66w/VwKQ5v48kafxuVqKtH5OXx+OpN3uzbh4caBuFdQ6rgitJKKNbaWGth4WoX5mlDps1QHhUJBaGgo3t5146IqSzd697Hy45w1LJ/7C0tfTuaNb9rRdfBN5cOu+d1Bd9yArg344ct0Vi3NYuk8E89Zf+Letz+r4Ha6cfK7l3G1FjB8jDuPPX3zPVw4r+fj2cnEbLWQmpDFpw81JLCh7T4L//QgM0WKu6Cgf4QRhSyLzw7EojdbMZithHk48fGQFiUKSD3aJpgzmXk82aKY68OvbkzyjtIjoGwXz85+7kwqusdCs4VCswVPlQJPlZxWXhqyDCbSC400dnehs5876+NS6Rbggc5kIXfBNJI++umWl7m+5cFzWZPu4Xy2jpZeNyNnK4tU1BktuJYzUWTojGiUctRFJQgVUgl6swWJAFdyCvBzUaIpqkwU6KpCazBTaM+UWIwzqVrm77nEJ/su8+n+WDZE2/xcMRn57IjN4HBSDpezdOTZMYk7IrAd2Sc1txCJRKhQqN8RVOKjH3q/beHxx9qbfllXDxfcvDU3/u5/YSgSqYTf/netSsGQjz4fgkW0sHdj1dvw1lOW2FPxfPWzBRcnmD5ZyrnkXLpHeHPuhX6sfLBDhebHhhonlg1swzMtQ6st1B1BKYNAV5GLB6MpzC9dRKbmNGrUiNjY2Fo/b0VIJBIemzOWGT9Nw2wy8/bD+9n60816FNXqY1GEVCbwxPO+zPkkCJlcYMHsZBY+uQSjoXyN9+wJ23tt19kJNw/Zjb9O3V1Y/HMYnXo4kx7twiNtHiXutO0+1bM3ciXNNgc38LGiUcpo7aehd6gnwyP9GNLE5t54dcs57vvxECtOJvJAy0B+j08r45apajDdrUQtk+JZFNgY4ebMfxr5M6l5CG90aHQjGHRkUb8PZ7kUo8WK+c1x6HS6cs9ZF9xSwX7u3Dmu5utpUkxYOZJ+UGCy4CSX3pj0raKIiO3/CwKo5RLMVvHGvjKpBIVUQqHJgrNCeqNBiKko4lVRScqYzmjhUpaOs2l5HL2WQ3S6LW9026V0Xt58hodWHaHz4r+Zv+cSAON/OUbTRTvo+r999J+/jZ3nbQuBd9afZubSwyzaf5nvjyWQVWjEYhU5eiWL2PR8tIXlD67zyVo6Nay4ktQdoa2XppQm0a2vK55eUv7cqEenLbB7iG+IN72HeRJ7voDDOx0X0i06arAoCtFn1p0g+beg0xbwzpiPMZrg5YlSfL0EXh7cjOnDWlSYrXI7aO1nwWgRaBI2egAAIABJREFUeHvkhzcqndUW7u7u5OSUUzO+juk7tgdTFk1EFOHc4cyKd65i0Gu3Pq58sbwhjSKVbPp2O68OmENWiv2xJgkeBEBGWlnFxcNTxtxFwUyZFoROK/L5S/+7sc2510gArqRJaOTpzIs9GvFMlzAe79DghhtnWvdwBjf25b3dF5m59Tydgj0o8Lz9ed91RUONEwVmK7rnR9ZJBld53DLBnpubi/y9KQS7qJAVRahXJtSvawhWUSTEXX3DhCMRhBvn6BjozuHEHORFwnp3XCaNPZ2RCAIBriqyC02YioR+fE4hXmoFzvaiT4vRJcSDr0e24bv727Lsgfa81stWTWtq1zCOT+3L5ZcGkjljCHMGRALwzoCm/DC6Le/e34bJfSIILapxLeYZySgwcjxZy2/nU8g3mNF5qRj52W5avfUHXs/9gv+0X7FaRc5dy+W5FUdY+Od5Vh26QqbOgOxOz1l3YHKRywVGPuRBgbaQTV9vK3e/h5+1FZpZ/ulVhwfAxTP55BsL6FxJRax6KkYURRY99RVJF5MZPUhC17a377tzRFsbEWmmnb+FEzvPMvs/H1WofVYHtVpNYWHtWwMc4cDvtqp3g8dX3gu9qgSGKFj4XSh9Brlybn8MUztNJ+ZI2Yqdgx/vh1Ip8MuPWZhMZceiRCIw5v+86NslhF3bdnFmXzQA/5k2DJlU5KddMkzlxPcGu6mZ2jWMqKd70buhFz+P7WB34Xgna+1Vxd9JydmsfLInD7pl17wlPnZRFCmY9h9yjCa8Hcg9vM6Hf19k+clEYrMKGL/mGP6uSnY+3p1Z22N4oGUgrf01jGsbzDMbTrH4UByeTgpOJOfyelFZy/ubBzB/z0Ueah2Et5OCpcevsnhEazS1ZCq8vvAI83CiSeuyvuE3+5Rt1iB3UZL4yf2Iooi20ERyrh6JREAuleCqlBEVl8nxhGya+msY3aEBP+yN5e8LaXRr5E23CG+aB7ghkQh3prZeDsMf8OCnH/JY++kfjHp+CPLShaSBsKbOdL/Xk/1/ZnFsT06ZIhz2OLk/FxGR9gPa1MVt35UkXkzmy2nfk5d1s3qZyWDi8okrtOgRyYT7q1+a+VYhk8BTHY38z9qdqE3HmdzqJTReVe/QGN6qAVM+nYhSXTLeJiQkhMTERBo3rrtmK6Io8t+p33LxeFzx/0jM4cs079aEyHYlv39B41duqps2x8IXH6XS5x5Xuvet+D2o1BLefC+QiMgs/vd5Bi/1fosXv36ageN639jH3ceNoU8NYd1nm9i5OZdBI+zPNY897cPOQwn8MOtnFmybjW8DH+6bOox1n23ir+NShlUQQOeskDGj780qdsUL1+y5JOd8ipQhoVbcKjEWadMVdeZvr03aeLlyKjMPsagIUl1zS6Li40YOI6mwkBCniv3FpX8gURTJM9mCFbRGM3kmM+193NiVlElTD5cbZSf/SkhnfVwaeUYzk1uE0KtYM4R3D19iw5VUTFaR8ZFBPN869Ia2fzuDNMpDZ7JwOjOPrv62wXQqQ8um+HSi0nI4kpbLtDZhvNQ2jF8z0vBUy+kc7IGXk/3nsOfLr2rxndpi8ceprFuZzcuz/Ll3hDtCu7kltouJn3LxdD5Th52geQdXFn4VWDYyuZSF4KWHjrJvXxJbkn/B07/yhcC/GZPJxNbH+/DLnwFczZAgl5Yc9oFeIrMeMeBtJ/yjLot62MPeuMxJLWllc/ezYLLAN8cUnEqtuoVBFMEiCjT1tvBcZyNNNt6sv24wGDh06BC9e/eu4AzVRzz+FsejdLz+zFUkUpBKBa77C+UKCW/+N5LO/R1v6LLi/WiWLra5wCZM8ebhx70ciuqP2pvP+zOuocu3cv8jHjz5gi+yTu8CkHY1g8caPYN/kIJv1oTZ7tEOr0+JZ/vBeP6360va9GlBdmoO/9dgEmolfP2cnus6lL25qLxys5MXKkjNk+KmtvJ4GxMtfOuuaNCtJNdoQm+x0PDHlXWeUlnnGvvRo0fJ1xUQ6lw1oQ62akcahQyNQoZfsUptfYNKCp5BDXzKLXgxs1MEMztFYLJakSDcyJm8U804B1Ky6Vfs+Vp7a2hdNNtarCJ6ixVVkIJTZ7RsvZTOhcx8mvm4smpsBxp6OJGjN+FZBavIrWL0o578vjqbVT9kMXCYW5kPTwh+gSbB0H3kfPavP8zRgwV07FZ+SqDZZOXYsVQiwjzrhboDiKLImr1yEjMkjOxi5ol7665+wa1CLoUpnaq36DBb4asjCo6nSFl0UMGCvEKcikoXK5VKDIba9d2XZs0yWwrbp9+HEtlCXe1CUVaryJ+bBVTOSlw9XfjhywziY4289JY/SlXFC57OPV3477KGzH45kXUrs4mNMTBzUy7uPm74hngzcHw/tny/k3078+g90H7A74RnfNlxMIFvZy7nv3vex8PPnf+8OpqV761lY5SM0T2qVnMjRwepeVK8gzzJSctl4UEJgyNMjGpqRnaHeyYrw00hRzBB9hOP4b3+D4d6GFSXOn1VOp0OYeZ0Gjg7VbiCvBVasVwiqbAOvT1utbaeqTfiqpCVe59SiYBzUXWkD+9tzrGpfUh49R5m9m1CoEZFTEY+oR9tY9SKKA4Vli1EUl3zfW3g6y9nwDA3EuON7L9SfsnF8bPGALBsSXpJX3upie/4vlzyC/V0vre+2pwj/PH1Vs5ckdAy1MJjA//5Qr20Bl9VrpvzOwWauZgl5cWG40oEdyoUCozGuhn/sZInOHJAR+sOaptQL8WVq5ksXRPl0LlOHsgl5Uo6fcf24IuoD2jerQk7t2h59akEsrNuClWD0cyRc9f46pej7DtxFYAL8Zm4+8BnS0Pp0c+Fk0cLmNrmaS6fvALA2NdHIQjwy49la9Zfp1krNX26BnJg7wFO7LQVpRnzygicVSK/7pORmGGby+xp5/a0+JhEm0gaOmkgi/bNIzDCny2X5CzYr8B622qk1h4auZyLefkk3H9fnV6nTgV7ysNjyDYaK0yTuR3cqdr6mcw8WnpWzVfoqVYwspk/KpmUZj6uRE/rT5dgD+77dDfzN52r8j3UpQ9+7GNeSKSwbPZqLPaqXwARbcPoOcCV6DN69u7Is7vP+eN5zJsajSARGfBIxS1k67FxcrftW3j2PhOy2qmc+Y9HJoFJ7U10DTYTmy3hjcHv3hDuDRo0ICEhoU6u++M7awB48LFiY61YNklympbX39vAE6/8RGFhxYuLQp1tHLn7aPDwc+ej7bMYMK4X0Wf0vDAhnqtXDLz8yVZce85nyLM/sW5HDE5FjVNGTFuFpud8Ikd/TpRhD/eNV5GWYubFXm9xcONR3H3dkCvlFOgqNoU/8YytYuSK+b8A4OLuzMSPJpGvF3jlOyVHLjouZo5ftn2crXo3I7JjIxYfnY+rhzMJuRJuX/Hz2qWFm4YLefmcP3++zq5RZ4I9ftRw4nUFRLhWLKju1MCHW31fGYVG1DLpDY28PCrLJAjSqHijT2OOzR7CoJYBiKLIzvMpCIG1VGWuBgSHKhg03I34c4lsX76n3P2eeNYHqRS++yy9TFTuuaNa3nj0DPk6PRNfakSrXs3q+rbvKpyUd8nsWEtIJfB4O5twP3/wIm8OmYdOW0BwcDBJSUm1fr0LRy+zb10UzVur6dTdvqupW4cwjm1+lYux6XQftYiUtPJbn7bv5Y5SLeHvVVsQRRGFSsHrS59j3GQvUpJMTHs8nn7NmnNp/VTStr/Eli8foV1TW6Bv9LoppO94iVUf/od7uobz1NQQ3pofiNVk4O2RHzJ37CcY9SYGDK147mjWSk375n7s+nMX1y7bUn1HTh3Mi6OMmC0w9ycFv+yVYUyoWGu3inAwRoqrWiRi53QAslJyyMvW0dzHyp2eJOQoEkHAXS7H8so0zOZaKg9eijrxsefn55NhMBBSDb96XXMnBswBRGfn09G3doSvPETD9WSZlNxCJnx3kIabz7Ngcne6NC2/2MWtiJgf96Q327cUsGz2avo+1AOFnQyFoAYK7hvjwW8/ZzN5TCwqlQRkNu0p6Yoek9HKYzMD6DfMsSp19fyz0PgYb6lVTSLYhLtzn35sX7GHJ5pPw81bQ1JePCtdf6/Va2Wl2HLkH/v4VQRhdbn7Bfq7sX3VVL5esR8vD2eMRjMKRdnpWqWW0nWAJ7s3ZnD5xBUi2oUhCAL/97QPvgFyFs1LYfE7+bw2x5UGAWUtp17uTnR3d6J7G1u6aa8BGvwC5Lz9mpZjW08hkUoYdJ8bX/1yFKVCxvhhrey2jh77qB9HZlzjt/9uYsqixwEYunY9IU/ex3urFSzbIWfbCSlKp7JuINFki5+yWCErT6B/G/MNIX6wKP2v/9yp8PvCil7tPwo/tYq4fB2Jo0fScH3tN4upE8Ge9uhYJAgoKgkOuFNN4rV5X44sEkRRxAqoKrGRVqeXsL+bmnPzhrPwr2gGTd/Ay4ObMfO+lnb3rc0Fsb1FgpiaiY8A9w2VsXZdOhtemMx/RjkhGfxlmX0fneTFicMFZKSZ0GIBwbaydXWX8cyscKweOQS0m1GLd/zvQB7oilxTvmusvEjl2sLeN2wv6t4RH7qjfnZ3v8obzrj7Gpls3Yi0qYp9sZnoM7LItqYhk5SycDgwSIRKYnn6dhZoFfceoqlU0GdqZolxIwemDmsGcikjJ35D43Bfpk8dgLelZPxM794Kdm+E3WsOENHOtqQX2s1lMG/h7SPj3enXmPfGNVKumRgzWKw0Yr6xF3z2ocDCRXIaNZLhac3Fz8uFVxdu45PlBxk7qAXPPdSJvIRUHvlgK80aePDZ070Jdfdm9dc/MfHdh1G72GIHIgJFPp5k4NP1CmKSJFAg2nk/EsQiB7qni8i97W2/V/yo4ezcp0BAQtCahXBn1UmqMWEuzlzVFWCNjSU8PLxWz13r6W4nT54k6+UXCHepXmOSuw1HBPu5rDz8nJR42enBXBxHBXt5JWuv5RSQpjXQtoEHM349weBWgfRs7HOz8E8tBteVJ9gBtForjz2ehUwGP3znievoJVU+/44dO+jfv3+N7/PfwuwxH/HHL5vY/Ik/7lUU7LWZ7uaoYE84UzaorLo4ItjtjdOTGVoauqpxK2ZVqukYLI698WbXaubjzeUrGUx8aSX7j8bRMjKAnYsfRq2UozeaUckUPHjPRTy9ZPwQv6KM4I49Fc/M4e+TnpjJ0CEqnp3iUm76WnkIfl4YTRa+XXec/SevsuDFe3DV5fPbgTiaBLnTsYkvPy7P57MV8cxePIP7nq55MZYzQ4bz0p8qwj2svNHrznTZ1pSkgkK8lQoab9hUq42HatVrIYoikjdfw1tZdw1W/kk4atLP1JsqFeqOUtGEEujuRNsGHlisVmRSCaM/30PP97ey8UTSLS13qNFIGDvGCa1WZNVq+2VmK+NWdd+62yivIti/HXtWugAnJckFdZv25iiNGnrz99rnST3xLu+8MhR3VxV7TyTQZOSXKJQCXXq5cC3RxPEdZ8ocG946lM8OzKNR24Zs2qzn7dm5FBZWbbyLqZko5FKmPNiR5fPux9/bBSeVnEf6NaFjUR34YUOdUMkUrF60rlbmk5OpUkQE2gfcHXns9ghyUnMxL59ff/21Vs9bq4I9ftRw0vQGNPL62t2Okm8yVxowB9Uzw5eHVCJhzqjWxM4fwdjOoXzz9yWEQHfMlrobQNe19euMGqnG21vC2vUmki4lV+lceXl5uFYSlFlPSRq1aQjA4p8sWO+GvKFbgI9aQXolUek1wZpUtiZ96XFSGi8PZ0YMaokgCAzsEs6lDVORSATue8ADiRRmjfqQY9tOlTnOO8iLT3a/Q6ch7Thy1MTrb+SQm1uz8V7auuDpKWFwd1/OxZzjwtGaN9I54mJrMdw+oHKLyz+ZUGcnGn77Va3WTqg1wa7X60nTGwhzqbzP+L8BR7X1s1n5tKhiilt5OGL+K46LSs7zAyNZ/3wfJBKBUXM28+Snu0jLqZ4WfR1HgvBUKoHJTzhjMppZ8tLSKp3/2rVrBAQEVL5jPTcY8/J9RDQQOHBC5OdNd68GZBFFtGYTyYYCMo02X7TRaq2WBmnPKnSrq/ABFbZo1bjYrKOtOzjx1odBWEwWZg5/nz2/Hiyzr5Ormnd+e417BiqJuWDmpVdzSE2tXaE5oL/NEb5zZflZL44QdyaBM3ujaeFjwcf57l6IusrlaE0mkh/8T62ds9Z87HEjh5FlNNab4YtwNGhuX3I2PQMrLh9Zm3698pAEuROXouW1bw+w82QS703syqTBzZBUsagPVOxfv86CX47z3IhWvLUokJO7zhLRLgxJJfks7r4apv/4PCfPnqBr167IZLek1cFdgclk4q+Xh7BypQdpWdA41P7vKhZraezlKjJlmBF1bu0KM1WQgpRsgagLEnadliEaby40NCqRJ7oXoo8vP1Lqz8wk5saeRIKAIEBbV08+jezCN0kX+OKqrSGJFIFHA8J5KbQFL184zN/ZKbgpFHgpFExv0ZR+fr7oLRZU0pvWMntjds+1rBIlqq/fvyPUtp+9DHYE/vEoHbNfTcdQYKBRUYT8dZRqBeNnjaG14Uu++5+ONb8W4u0lYd5cNxo2dGwsVTa2TSaR4Q9fQa2Qsy59HVJp9YomfP7cd6z/Yguzfn2FkKVzKz/gH47ZaiVVb6Dpz2vw9HS8nHB51Ipgz8vL49wD9+OnUtb7Piug9MSRYzBxJa+QtvYKdBejJmb46gj7LaevsWxfHD8+2Q2wme6hZsF11qQcUnML2XImmcd6hHP+Wi4BhRYyc+W8/aMSnQFbD95yEEUwmmBobwmtOmUw8KPt1b6XfyMmk4n9bw3FT+nNvCVmsnPL2bFoOhBFMJoFIoOszHvMgJ1MqzLY02bt+a5NFvjgsJL4ov7dSrkIYtE1LQIBGgtPRVhwqcCjF6PLRSIIiKKIWiojROWM1mzEaLXiLJWhkkhvzEUFFjPZJiNai5E0o54ItSt+SjX9j20h3MWF3j7ePNAghAZ20nOPZmXR0s0NZSULALAt1IvPf46M25osxu1huqrlYpLAgnUKsvJKjiejCaRSeOl+Iz2bW9mQ5M233+lwcRGYM8uNli1KvvDqpr8umpfM8l8v8O32L2jXv1WVjo0fNRy9GV79S4VCCh/eo//Hl5J1lMSCAgLVasJqIf2tVgR73MhhpOsN+KnvsnyEWqQ8baCznzvKSjTV6gr22pg07lu0C41azsAW/gzqH0mIT9WyHURRZO/uSyzZeZF1x67Sr6kfPz3dA2V62baYFd2vySzy3Fwz8dfg4YczeXzFjio/y78Zk8lEVFQUPXr0cGh/URT58LH/sn35Hvq0MvPSKFNF6y7AccG+8rScHXEyhj91Dy8sfrLEtu/eWMHPH/5GiLOVp5uZURZT+ExWKzMuHeOFBs0IUtXc5Wd007EvPYNtKWkcysxk3z39EQQBuSDcENBx+TpUUgkB6ptR+uUJ9lMZWj4+EUd3fw+eatnglljaSlNRuuKpOAnzVinQG+GpISZG/7GerT/u5uMnFiOVSXjjVTXdu5W0uFZHuJ86VsDjk44wdsIDvPb9c1U+flnbkfx4SsGISBMjIv9d0Z6JBQU0WbEKHx/7vU8cpcZroby8PFL1+nqhXkVEUcRkFSsV6rebjx9qT/NAN5btiyNi4gpOxmagN5pZfyCO1Gz7vnirVeRqej6J6bbWoLPXnyLAXc3Jd4by+7S+uKiqHlwplwk8N942y6/darmlUfz/RgRB4KWvn6ZZ18bsPi3jl3214/Y4ly5hR5yM0ObBPPXxY2W2P/7eI9zzWB+u6iT8fLnkNZenXCa2MA9fRe2kwvmqVNwfEswXndrz98B+KKVSPo+5yIjd+1gdf5VsoxFPpYJMg2OuCLlUwn8a+fPmwRjWxabUyj3WJq3DrLz3mAGNMyzZrODHd9YwcFxv5m54HYlEwtx5Wrb8WfM+9C3bqgnwdmXrmi2YjFXrSyCKIjuvyJAIIr1D/11CHSDPZEY3aUKNz1NjqZI57iHy63NoqkyG3oS3AwKuNqPhq0MTfw0z7mvJ7s8eIGP1RFo19CI5q4BZy6IIHreMiInLmfr53wCs2XOZts+swvX+b2g0YTmfrD2JIAj89XJ/5j/Yjka+NQsSbBEhoWGomYwMOeb6b67OUagUzF77Kt4aKz/ukHMwpuaL0Fy9UHRuud3FmSAI9BnTHYCMYkHC8YX5fJ14gbfC2yCvg65YTkXxGk83bsSDoSGsuJJA5y3bOJiRidZUUjiVV8CqmYcLLnIp7Xw09AyouZ+0OlSm/TcKEPlwogE/dyvLZq/m29eX0/Hetny0YxYuLgILP81n3W81C541GETUojN55vwq13eP2nSMRK2EDgEW3P+FumJTjSuJhYVotTUrFFWjEWIymUjVG4hwrS9GUxH2THex2gLCNBWX3L3TcHVSIJEIhPlrOLF4LJmrH+er5/vSvbmttGvrME/mTezK8S8eRLd+Mp88ZTP71mbcRXK2Hn83JXJFfUrlrcDT34MZY40o5SKfrFUQl1Kz37JrsIWeDcxcPBbHe48sKtMMKDs1h4+f+BKZXMrY8JvbNmcm8R/fUNq41q3AdJLJGB8Wyvo+Pdg1sB9dvR0zRV9fpHx68grDG/rio1aUcU2YLFau5tZcI64pgZ4iH0wwEORlZfWCDXz+3Hc06diIBfPd8fSUsORrHT+t0lX7/BtWZZOTZaVnP1dkDqTyXkcUxRsNcoY1+Xcu3AVBINdoImv8wzU6T43sa9fG3E++2Yy/8C9cWtWQfJMZV0cikqpJbQfl2EPjrGBAu+Ab/44M9iAyuHq90R25X4NRJC3XSLe+Xat1jXqqR6MAkRdHGflgjZJZK5SE+5dMl/N1F5kw0OSQliAIMK61iYIm7Tj4+1Fe6D4DjddNS05ybCrZqbk8teD/CF7zLaIokm028lRQEyzcWvdLkJNjJn+rKCIRBA6n5ZCsMzA63H4PgyNJOXx6IJYcvYmnOzdkVDNbyqbpqvaWjNfieGngvccMzN4ayYYv/8RYaGTa14tZIJvC9Ddy+GFpAUeOmFCpckBZNavhuZOFuGokPPRwIIl/TqPBkM8cOi5q83FiDl+m1wNdCTburM5j3RU0dnUh3WAgxGKpdlZBjSRLnslEsIMf/7+Z0qY7rcmEVKcu89/tafbVzZvVJ5Wf+1oce6Z+e5OMvWIa9qhurXFHjktME7BgpmHjkGpdo57q072ZlYkDTSzbIePY5bKTTYZWYMZYynTg0qaXPdffGwsJ52/icSXm8OUy20MxkPPyQlZ5ZbFaG4eLRMYHvp1r/AwBpb51h3u621mx2DPHLzx8lT7efrjp3dDqr+93c7tzoRMfRbRjX3oGi7bHcum8gf8Lb2jbeKLs91+bzajsjXMPF5h7bwyzM5Rs+X4nBYe3Mm2kiY8/CuKtWbmcOXvdBVE1PznA1Nf8aN7YhSPnkmngwP5XRg7n2z1KQEL/9F1w+5tR3jaUUimZ+To2b97M8OHDq3WOagv26Oho0g2G+prw1SCpoJAQp5Jm+Du1fW1VqOsGIteybWbgwIj64jS3EvXsjQA8AjxgMCFab2rsVouVOQ98zJG/TvL9VjmT7nVMCCgQGWRr71MGg2hiBkeQ5MBo1zDucQ6qhaeoPi4yGfkmMy7ystNlvsnMhqRrNNO4cjEvj5kty28j7K9WIYoi/f39CHRS8/Kxk4wNDUEplRKjzcNfpcLtFruYNE4wd7yBOSsV/H1GhsEk8PaJz/l6vAyjvnpzkiCR3OjaaNRtc+iYk6kSruRI6BhoJsStPjA2yEmNfMkXUE3BXm0fu+L1l/FV1pvgq0OW0YhXFc1b9UBylu1zDWxUfuvZeuoWhVKOUq288ad2UfPWqhcJbR7MhkMyNh+pmk8V0YoMSvw5C3LGE8m3Ab0Y7toApaR65sjaQiOXozXbX7AIAlzQ5vHI/kNkGY3klBMFft0Hfz3eZHV8Im5yOUqplJRCPV9dvEzf7TuZcfI0l/Lyav0ZKrL8OavgnXFG2oRZOBQjZWaLsRj1xhK/c1X+irdiVqlUFBZWHFdgtVrZECNHQPzXpbeVh0YuJ6mwkGvXrlXr+GoJdqvVSqbBYHcFW0/liCJI7oBCPo6a4e8UlHLb5Bi16dhtvpN6iuPs5szc36fj5iTy1WY5J2Idm1ZERGSC/X1bCJ5Iy9l2y8lRkVuOwHaWyZjdugVHBw9kQngYkw4dIU2vJ15XMvhMEATyTWZOZOcw9fAx9mdk8EYLm3Z/IjsbjVzOe21aEebizOsnTrMm4WqdP1ZxVAp462EjnRpbOB4rZdb9H1VbYy9OSEgICQkJFe6z7ce/SciV0DnIQqBrvbZ+HblE4Oeff67WsdUaOXv37qXQcncX5q8rcozGW25uu1vo1cpIiJfAlu93snfdodt9O/UUIyDMjzceNCKRwIe/KEjMqHzhmoWBVLFmqVW3AleZvEzKW2mcZDJeiGzMwXsH4K1UMv9cDCezbXEpOUYjP8TG8czho3x8PoamGlfW9OxGK3c38k1mDmRkkqLXMyQwgEmNwvm1V3f6+9k6pt3Keg0KGUx/0Cbcj/51ktn/qblwDwwMJCWl/Jx+nbaAb6cvR6lWMLp5vbZenAZOTgzc9me1jq2Wyh244ANQ1wfNVYdUvQE/VcnqTnXlX8/IF3BRilSjHswdSaHZzOR74Mv1chY++RXNujbBK6B6Ufj11D7NG1h5driJResVzF6poF24lcJiLQI0SpHBETcn710kYcTKozS5DXfrOFJBwFIFASsRBL7o1B6AK/k6Htp3kFS9nt9696CNR8myzFZE2nq4883lOB4/eJgpjRvR0csTL6USMN7yEt1yKUwfY+TDE92J2nScVwfMIaylI+Fv5XMhKZrjK6Ptbku8mEx2ai4T3nkIzyPf1+g6dxuCIJBhMBAbG0t4eHjVjq1qSVlRFDk6ZBBI5t/JAAAgAElEQVQ+qsqbvdwNAWG1zd5rWXTz90BaSXOV8opgOEpUpsjX+2wBerOH5hMsK+unrMnv49rVTlMKO9RmQF1cdgFSAU5fdOWrzQrahVuY9agR5zkba+0adytVLSlbHQpn2wJ9lu+UsXqP/dVkS18LLdNykQC/ipcpxMw4IZL2XcoG4Sbfjk5qlI2eBzicm0EnN8e++dJcLNDyS+oVzutyaeniwROBETQKKft+VlyJ50q+juktmiGtA4FelfFuNMPH2504nlhzrSBLTMUD33IXKQEaCx/dn48+uz7uqDSx+fmEOTvTsIr146ussZ88eZJck8khwV5PWSyiWKlQryl7E6T8cOLmIPnuchPejLhMFWpF3JHkG80EuqoY2tHC0YsWjlySsjFKytjbfWP1ADej5yfPhpFXMzAU3CwdJ4qw5OWlHN58HCNOdMRmgv83eFQbO2l4I6w16UY931+7xM7sFBqFhHCtsJDAYpbPbt5ezD8Xw7ORjXGT176ZTZuucFi4K2QwfVABqXkSrDXs8huTY8FblYlXOTLD09mKQgb6ml3mriTEyQmduepu7yoLdvdZMzA5EDRXr63bp65Na4cSpSw9IUfj5cqCHbPY9M12fvt8M3+IMkY1rR0f1u3Q1gF0RjPOCimCAM+NMPL8EhU/bJPT+UxCjc2F9dQuviFlv5EZP01jWs+ZXDhzFVcsuKFAUfOq1v8YfBQqXmvYsuhfFn6Miydaq+Xx8DB6+fqw8koCPX28kXL7A2vBFvHvr6mhVAeUKjnJOj2B7neJT/AWIpdISCnUk5+fj0sVUsurPKp0Zgu+qvo0t+qgNZpwrWO1eU+CFBGByfPHE9YqlMYdbL6ZM2klr/tPXHgZLSKqIpeChwtMuteE2SKwe9X+23xn9TiCs8aJd39/AxVWjuFEcyGc+4Qwu/tqzaa7vtHP682bcn9wMEsuXmbMnv1Ea/N4KiL8rss28lDKyTZUXt/gnzgn3QryzGb276/aHFclwW4ymcitJDq0nvLJ0pvwUlXuR6qJf31EpBlBEFg571f2rjvEwieXoJKJjG99awbNgcsZfPDH2TqZlEuf00Vt+7dCXe+b+6fgF+rD/AMfIAD7cCa3nCnojUtHGZ+8i1ijFlEUybIY7O53q5BLJBittZ8JNCI4kBU9urKgfRu+7dKR1qWC6+4GJILwr3C51BUuMhmNv/i0SsdUaWl44sQJdOb6lITqkm0wEeFW8z7SFdHEy8qYV0aw+qP1zBm9ALlSzrMdjIS61/3QEkWRt9ae5Fh8Fl4uSiaE21J2TGaQSMqWG60qpd0YuqJOYa4edftO66ldmnVpTFd07MeFXbjSBAPnD5kJamBboCkk8EF4Zy7os/HMVZNmKeSplL0s9O1GmKJmHQKri5NESoHFgqKOiuWEOt/d3/Cd4Vz4Z+KvVpFfRblbJcEe8fUMEv2saFzqTvu73W1K6xKTSYJ3qLpSP7vKTgVNR2vGa9MV9Dv3Mwc0ShK1Ak+2zqdzs7JhKY6+Z0cL1hREBv8/e+cZHUd1NuBnyvai3qslN7l34wa2sbGBgAMpQBIIJZCQQhqBAMlHCJBAgBRCSAgtld67IVTbGBdwL8hyU+9t+87OzPdjJduyZEsrrar3OcfnWLNT7s7O3Pe+HZvFyFv/zGfDjgrOve4plj7xLTyvlnPj4+GgmXuv8pNL7zWvYJ2C33D0PjRXh7+DPSFW1ni4kU+QVnzsxMIWwtkbW46pY7K1QeSa8UnITgArXxMKeMy9l4fz51Nd2dlqWFXe+f3IyO7dXNJVNH6LohIU/fi6ketdRdR3RVd16uPTOlsEdF2nzOsj1xadTpB9zbbpLZ5mmRbZMODpe4NFtN0K5W4fagRNYSIS7EFVI80ai4bvLbquD8iDbZDgxoUBWvwCafb+19R9wRArv/ckXzt7Et+7aBanz8zj/YcvxaTauOmlRCBcheu+9/P47YJirFGaWzzB8L20xw+v9rcx4ArtXXRdZ88nxbTUdyyhuvrx91j30ibem3gWy3e/jSDA1VljWbX1Pd5urGQKKQM+XoMgouh9DySLlBKXm/M/WsfmlcuwycPX9x4uyxvql2j/UwG3olJcXExR0Yl7ERxLRE+KWwmR2AMfcYzBxyyDeQCEuqbpXPnYJ4giXPXFaUe2j0pJ4YeXH8bVFOL6x75LeXEVT931Io8IFq5b3Lue1Md/G0+gTbDHNPZhiSAITJg3rtP26WdO5volt/L2Pz5AzhFZmqlhlWR+WTBl0OrGGwQRt9a9ObSqIthjrf14mmukTlr7GKeDfJuN1VXVXJiTfYIjhz52WcYTE+y9JqBqbN26tceCPSKvp08d+BVrjKHNfav3sLW0iRfv+ypm09F14psvtlBbHWLJJQtYcfkSvvqz8zFZjKzdb6TV1zurxfFHedusXba4mMY+kjBbTdz20o2kZCfxRpnMzsbwL396Qjpz41Lw9kDARhuDIA2Kxg7wldxsHtp3YFjHN1llCY8yfMc/2Fhlic8//7zH+0cm2HuRKB8jzECZ4QealZMzeerahSQndBSuy8+LwxEnsvaFjXy+eT+/u/wBAr4gy8YFcFoityR0FWUfVMP30xwt236MIUNSRgK/fuVGDKLOE/tlKj3h3/rthkpurts04OMxMDimeIDLRuUxOylhWGck2WUZzynUXyTasQwpFiPfKV3b4/0jEuyqFkta6C0eRcU63Eu/HUOjO8A/1x1gcnY8U3M612tPyzBw4+2ZKAGFHy/6JZ+8+ikzlk3myvm9qy8VUDWMx4XVB9vmCUPMPTQiGT1tFF8rDBHUBB4rlnEpMMeZzP5gK3Wh3rlzestg+dgBZFHkjqmTyTCbeaW8MqK69UMFiyTFGof1gTijjFfp+f2LyMd+/MQaCYMV7T5U2pAqrX4cZhFDVm/H07Mqbl1F1EPv731X1eN8yRbO/eMH5CbZuHTeKERRQK9p6LTflPpSvrpI5pk1kJOicf2Mjcidd+vR6tYTChFwGWkVj+7r9YYXSqZYHvuIZXKizsrsEG+Vy/yjWObaIphsSmSdr4YvOvKP7NfbCPieIgkC+gBkY3cVLd+OO6Twp90lvH6ohgfmT8UgDp+qfSPRWjmQCIJAIILavhE9Gb0V7CM5ha2nBEOdNc7hiCcY4vz7PyTVaebfV89D7Kbu/SVnhLjhS0HuuDSAvQ8FCzVd79TDvn0Baxwp7etidGLq+pf5yeEXWHLJAg67Rd4tWs4CSxqHFfeAj2Ww9WS7bOCRCfM57PPwvU2fERhmGvBIryTY3ygRxLhFJGnsXXQIG8oMFW0dwj+KUR7+gn1zRTMOk8zT1y7E2M3zcPPbe/jPtjIWTlTpa+C6psPxa4iQBgI60jB7LmNEhiAI/PSRaxk3u5B3/vUhKXoBP0yc1P2B0R7HgF+xMwkGE3+fMB93KMQ+18AvbvpCTGvvG8GhprHHgEBIw9RLARTtZip9odod4KlrF2LuJl5AVTU2lDfR6o9OwI+q651aWbaHfFQfrI3KNWIMXUwWE7968QaSsxJZ02rCrQ68kBgq+qZTNvDf+XOZFB/HK+WVfFLfhX9rCBLT2PtGKIIYt4gktaGf242OZIIhddhr7P6QyqOfljLzV2/y0ecnFqa6rvP9B9fQ5FP42tTo5N6qut6p69WiPBUdgVsv+B0+98AGU8UYeJIzE1nwxTmAgE8b+LloKM1+7dpvUzDINRs3842PN7ClsWmQRxWjP1EjWBdFJGnkYRSsESP6mGWJt755Gj9YPo5V93/IH9/eC3Reibt9CrXNPl65dA5JUUpF07pIF1yYq7IkP8TBHaXcc8VfYhpBjH5lKD5d3yzIZ83ypUxPiOeqDZtpCASG7HsQM8X3jUh+V0GPYO83zpvdqwENBMbkoR1AdbDJQ5LFiDNKgV7B+sHJaW2/z1UuP5UuPzMz47n5nd2oGkzLcJLpMLMwP6mT2bwdw8TULrd/+Eg9DV4Bm1FnekZnX1JjIIhfVcm0WjpsVzV4epdMWYvIwlyVBbnhgKL039zdl6854giFQuzZs4fJkycP9lD6xPN/fI21L2zg4kKVJJN+JKiyYQDeh5JgK6ONHeN2kno47/R0fD09X1cEdQ2jILK6oYKDPhcXpOaRZrR02s+eODhpe7uaW5gYHzco1x7K2OJ79mxous4XXtvco30jSnebkzp0WwoO9ch7h1EizWEmOUoarF8cnN7FXd3nv50/lQ8PNbD2cAMby5u5cGIGY5K6jpYzFaWjaTq7ShuZmJuIKArsK1FYt9+IGgpPOOf/6eek/v3WDsfV+v24lBCFjs7nLToN7vzIxM5SkdPTA0xL18ibPz8K33bkoCgKkiQxf5jfly1P7WUn+ymyKuzxV1Dq83B51hiqWvv/fVA0jSJjx5oNGY6evc89HV9Pz3cy0k0WHikv5taSLZyfmsu3s8eRaDja4yM+cXCi6RVNY2Zi55oXpzrO5J49G7ubXN3v1EZEgl0awj72oTw2AFEUkNr+RYPB+r5KldJJuBelOihKdfCdOfknPVbTdV74+CC/efJTdh1u5LZLZ/OdFdO5/U43ugbf/NVFPHnXi9z1jT9z00yR9GNq3cuCiABdWgLizfCDuQp3rTXx+BYTNy8KUNDDLkinCpqmIUlSj7tDDVVEUUQQBCRBYGF8GsbEcKlXkf439Ypt1z2WE1mmjifa+52MTJOV/yucxmWZo/lr+V6CmoaqawQ0DYdsiMo1ekNX9y9Gz+dyMYIoj4ic5toQ9d0MByRROOUr96073MiNj6zn2+dOpP6ZK/neeZP5y19d1NdrXHHHJVx661f48UPfxtPi5dHPOi4eRAFOZkDMjdO5fJqCPyTw8KdD23oTo+94FLBIMpIgcEvJZ/yhaSdVIe9gD2tIkW+xc/eYWWSZrbzXWM05W/7HHw/v5oB7eKXJxQgTiTIXkWAPxJrA9BqTJBKM4v0b6q6H4wmEVBbmJfL5o5fwnXMn4rQZcdqMVFVpmExw8c+/CMDyy86gcFo+Fa6OD7EoCN0uLOdkqeTHa1S6YlrBSGXuuTMAePagjK+tp8iPcieg6BrfrlrLbXWfEdDUIRtANlisTM7i/nFzqA76OPv9NTyy/wAQNo/HGB7IEQj2iEzxvpCKJVYMpFcYZRG/cuq+RBc8sYkrZuTyjXl5HbabTHB8bwuL3Yyigq5Du+VOoGdRyWZZR9VFVFUd9mbnGJ2ZvXI6SzNV3quUeGK/zBVjQ+SYbdyYNJWGeD/ve6owCiIb/HX8tWk3k0yJTDQlUGhwMs4UR13Ij0dTMIkSJkHCJsiD1gp2oJnuTGK6MwkSfChaOPBw0TvvM9phZ2laKmemp5Jnsw32MGOcADkCN0ZEgr2hVkYeonW5W+sGewQnpzUg0hgI4YxqMbz+/y2cKZ0DO/wVnbd1ZUFor/zX4g2ytrSRR7+zACEtqcM+JocHTQsRUkIYjOGIYJPVhI5AfbWEoc2m5ArJtAZEmv0dJ+Hj+1e3lwpQAiEk66kxYZ9qrMxWKXcL7GkW+V+FyFnZGkUzJMDGQkYDUKCmMq7RwMaGRj5trMHn8PLFSYm8uLmSp2oP4tNUFF3j6qyxfC9rPD/Yu4FtrkZmOJM4LyWbRfFpGI8T+OUtBjLievfO9bRHe1UX71ZfztclTRYMhLtPPDp+IWuaa3i3rIb79hTzzoyzaFACfNBUTaHFwWirkxSDKSrxC+4WkWZ16L6Tx88lA0VPO8H5ff3UBCY4SN2NRgJGUYyoJOBI4n+7qxmf7iQ3qbM2YDKHJXHAGzwq2NsWj4rGEcFuEEWCWvcPdvv+QX8Qs9V08p1jDEumf/Iyv21w8d1ZN/JOaT2n/+1GeLhjFoVZkpifksz8lOQO27+bM57v5owHwkWP2t07vyyYSqMSYE1TDX8q3UOWyUahxcFuTzNT7AlDMoc9GmSZrVycPoqL00cR1FSMokSp38NWVyPP1RyizO9hQXwafx4/l9fry1nfXEuiwUSSwcQ0RyJTHYnsdjfj1ULYJBmjIJFmNGOXDTQpASRBQBLEAWuiM5IxRlBHJiLBHvPH9B67LOMOhQZ7GIPCpoMNnDMls8vPzG2C3e8NYI8PC37jMYK9nXDbzO4nBoMU3kcJnJr3+lTBmeTg1uev50cLf8Fdl/6Zm2cKpNoiExzSMVHaqUYzqUYz421xfCtrDIIgsM/byvf3bmC2M4kb8idFNLEOR9otFONtcdw3NlyzxK+ptITCVoQsk5VRFgcNSoA9nhYSDSamOhJ5sa6UT5pr8WghgprGL0dNZUVyFhfv+JCa4NE2zbcXTMMdUjh985sYRQmTKGISJd6YvoyDPjd3HdxBnGwgzmAkz2zn8szRVAa8VAd8pBnNpBotw6qjXTRRdR1Tfwn2WKpC7xEF4ZRdr971lekooa4XhSZz+JnyewJHtpm7EOxSD4Ln4Kgp3tXoJikjljM7khkzo4DrHryae698kAc3GblpYQBTRDNa17SbncdYnbw67UzuOrSDi7d/yLU545nqSOz7BYYRZlHC3FbkZpojkWldfP9bRk3p8tjXpy9D0TRUXadRCeDVQlglmTemLyegqW3/NGRBJMlg4sK0PFqUIM2h4JHgx+2uJv5ctoeaoI+QrvOV1DxuKZjKvypL+GfVfm4ZNYWliRn9dwOGCM3BIHGGnhcviug1sMSCkfrEqRqpW1zdykMflHDPV6dz/BNktYclsbf1aKqSxRGeSAJqT0PmjlKYoPFxGdxzxV+49/1fYbH1oVdsjCHPisuXsHfDPl576B2e2GHgiunRrUAXbzBy15iZvFx7mHg55tqJBFkQkdsahzWFgjhlI6IgkG7qXA0v0WDi3OTOfSVWJmexMjkLTdepCHgJ6RqKpvH70t0A1B5jEegLg+Vf7ykuJcTas8/juh7uH5FdwyJJp6xwiganaq3kJLuJ17ZV8JvXd3X6zBkXFvUt9UerKjmTHAB4emFNPz1PZX5OiOLN+/nt1/+EOsx6VseInGv/cDm5cRrrymTWlvaP8nFafCrZZhtrmmr65fwwQIFzg4RXDfvge8M+b2vYarLjQz5rbcQgiqyesZytp53PxemjojzSoYlfUykqKurx/hEJdpss441NlDEiJMlu4oXvn84f3t7LC+/u7fCZMz48EbceI9gdieGysd5Q5AshQYDLpipMP3My61/ZzN9+/M8+jDzGcMBoNnLtrCAWWee/2w38bp2xw78HNhqpdvdtUR3SdHyqws0ln7GuOdYmOFJcqoJD6rkpud3t9mzNIS7duQZF1/h70Xy+lBZOl+2qBv5IxiiKzJgxo8f7R7SEEgWBpmAQmxwFR9YpiEkU8asq5l64NJpreq+J9MXM1NNUDOhK2zjaR34sAo+umsqLL2xmVcLRF9zRGHaktzZ0r7HbEzXik7v/LrIIVxg3Uusw8dIDb2L+4GWWFajkvfRaD79LjOFGik3n6plBHvnMSHFD53el1iNw1wUuclM6bu/p873/oEqm2caP8yZwx4FtvDB1CZYuNNCeat19YThq9roelh/dUeJt5YXaUj5oqua5KYtZkZTJiqQsnHL/Nvnqy/za3+i6jqqYSEpK6n7nNiJr2/qXh07ZlK1okGA00hQcnOYtQ4Fzx6Xx+JWn4fYrNLjDwXLOtp4uLfVHFwHOtgYyvj4EtlsNcN3cIHEmnad3GthSdWpG054q5L30Guetf4WXA8/xjvZsh39f/MHZVLpEHl3fey3Pp4UwixJfTMklxWjmH5UlURx9DF3XuXbPer6xcw1uVeHO0dOxiBJO2djvQn2o49PUiO9BRKp3VlYWlTFtvdckGo1U+HxkWE4tM9KxCILA3W/sZl1JHat/spQ4e3gV39qlj71v5tMkq84P5gb43ToTD39mZOqOw4yanNf9gTFGFNfccyl7Pinmw037mZAeYsnYyAPs/JqKRZQQBIFbC6ZFVAXsVEbXdYK6hldVaFICJBhMVAd8FHtbOOBzs76llhmOJL6dPY6rssYwzhqH4xQX5MdTG/RTcc2XmBPBMRGrMfFGI/6Yn71XOA0yLcfXT+0hfTGnDzUz003nTsTlD/HLF7cR11aJr7G66cjncSnhje7jbpVA5JkF+fE6l05RCKoCHz6zvi/DjjFMMRgN/OLpn2Az6jy23kJFc+TWm3B547AwL7Q6yLPY+VdlCRX+U6/xjKbr1Ab9bHM14lNDuEIKvzm4nZ8Vb+aa3R/z9R0foes6G1rqmLHhVeZufJ0fFm/i2j2fALChpY6/lO1lu6uRMxMy+EJyDgCznMkxod4Fiq6xZMmSiI6JWP3efMml5Dz2MDk2a6SHnvIIgjBiswpa64xdlp/tCqtJ5ulrF+INhoizg9EAtWUNRz5PTI9HQKc52FErskgSXlWNOMYjPz7sPmqubYnouBgjh/T8VK5Z6OUP79m4/wMrd5znxtCH9a6u61QH/Vy5ey0PFc0n32KP3mCHELquUxbwYBZlUo1mfvj5Bja01BPQVFKNZh4cP48csxW7ZCDHbCNeNhInh337Ux2JvDV9OXVBP06DkRxTWGasSs1lVWruYH6tYYOu6zhlA+PHj4/ouIgF+8qVK9n+6N8jPSzGKYi/ItiphrxS1oohx0lBytGJMCURaosPHPlbNsg4DNBynGC3ShLeUOSC3WEKL6aa62KC/VRm3qgQ28YGea/YyJObzVw2t/c50IIg8LO8idglmSt2reX+8XOZbB85BZE2tNTxfM1hNrTW4VNVfj5qMhem5vGN9EJ+nDuRLJO1QxW463I7p2KZBQmzyUJ5wEuWyXrKpvv2hXolQKIcea3+iAV7QkICYouFBrcYq0TXG9wmyoMa9gE2OUXbHN+Va6DrCOOumsjUd/g7UbJS4TIQ8AUwWcJFQDKnj6Fk8z6yJ/po71YounUUzYfTGdlzZ9dBFMw017V2v3OMEc3lp/nYWyPx2k4TU7NCjOpDzZnqSoULxAIku0RZjY/kFhuqrvfrvNgfke66rrPf5+L9xmoaQwFuzJ9Ma0hhtNXBZZmFjLPGHRHis+OSuzlbZ7R+vicjmUYlgP+2H0R8XK9ChR2STFXg1PMtRYMUo5k6JTrVkkYKyfawRl13jDk+JSeJkCbg8h+dEJxGmZZg5KHyogAOs05zbUywn8okPPw2Gf94m1++dx+yQeKv27JwBbo/rjvOd+Qx3ZzMFn8DP65Zz2HF3feTDgB6m6/8S9vf5xs71/C5t4VJbVaH5UmZXJM9jkn2hFO2PvtQwC7JnHnmmREf16tfLO3Fh1BHqK+4v0k2mKgPRmE2GUEk2cI+8NrSo5p8clY4Z7PBc1SwOwwS7l4IdoA4s07jocoRG+MQo+eMnj6KK+/8Go3VzTy+1Uh3j4QnFOpROe1JpgRmWpL5Uc16XnQdQh1i3TCrAz4+bKrmT6W7uXDbe2xqrSfZYOL7OUW8P3MF946d3WVZ177gUcP14WNETk3AR6rRgqUXWVS9EuwZGRkkGUyxbm+9IOZn6kxuQtis/8hN/8XT4kHXdQ5sPwyArh+9X0IfGulkxGn4FIGn736pr8ONMQL40k++wIxlk9leI7GmmzK0LiXUqWpaV0ViDILIN+PG8puUWbzhLmNPsAVd1/H3oN1wT9F1nWYlfO1yv4enqw/yeOU+Hizby3M1hwBYXV/BdXs38K3d6/jajg95pKIYgD+U7uL+0j20hBSuzR7PZHsCoiCwNDGjy2I70aDC7yHLFAu07g2NoQD1t32vV8f2+te0STL7fS5GW529PcUpiyQI/e6LG07MyQ+xdGyQ9z49wM3n/pZFF85l2we7mJmrUNCDSnNdoWga+5q97G50savRzeUzCiipi+fRm5/AmezknG9Fbt6KMXIQRZHrH/seVxV8m6d3GihK1kg5QdvXimqN+AhiYopMCfwtfSEisDPQxB0NW/iCPZel1kwyZGuPKrABuNQgFlHGr6v8t6WEg4qL0io3iq6xZtbZ1CsB1rfUYZUkrKJMoqEtPsVkZVFCGlZJxiJKFFrCdSHuHjOrx98hWrSEFMba4gb8usMdXddJMphZ3AszPPRBsI97/2lqF6zq7eGnNBkmC5UBLzlm22APpdc010hR64gkCnDNAh/MWsp7T6xl98efY4uzcvX8arqbAzVdp9ztZ2+Tm73NHhZnJjIl2cm0p9biUkJMSLAzKcmB1azyi5Uebv0gkz995yGcSXYWXjA3KuOPMTzxfv+bfG2yxKNbjDy+1cD184NHAjWPxaUq5Jgj0zrbF+2TTAnckjSNZ10Hebb1IKdb07k+aQofeCpp0oLICPh0lenmJMYY43is+XP2BJspUzy0aEH+nDafXEM4g2SpNZPZWYkUWB0IgsA0RyJ/HNe5bMlkRwKTHSMnQv9UZL/PRaHFgSGCVq3H0mvBbrFYSDKaaA0pp2zJv97WhdZ1id2BRmTz4N+3/q4n3dP8dlGEq02v4863svGQgcum1JM5tvP9MSkGamwhqlx+TstJ5KoXt/LczkrGJtspSrGzMCEZc5aRjbefTarDjHjcTP3rcV5+fp/Oby66lzt+JDFlnIh81RNR+74xhhenZat8VqWypVrivYMSF871ddrHWKeQmgJw7EK25+9NJhmsIIOQruFVQzhlI7Y6kc1NLWi6jk2WsSQmkxFnZJzsYJoYT77FQb7FfqQj2q+yp/bti3ZBV/NXNOcDnxrqVV+MGGG3TsLTf+718YLeh2ii4uJi9n71WvJGaHGG7uhLw4dt/gammBIH3efelxe5pxp7TwvXAGg61LpE0p1ahxx4f0jl1b01PLjhIJ9VtvDt2fn8buUEGn1BHEYZg9QxXMSQc2IX0We7NW69X8VohHt+JjP2V0/2eHzDFUVR2LhxIwsWLBjsoQw5mmpbuHrSj/F7Atx9bgOZcR1jh97a3cr8lI5pXkOtmmNv6G/BvsfTTLbJFqsmFyEeNYQsCMzZ0PumVX3KYxg7diypRvMpG5bDdKoAACAASURBVGncl5fALMh49cEvzTsQ3agiQRQg3RmeWEs+b+WRzYdpDSiUt/i5+6N9LClI5o3L5vK7lRMASLQYOwn17pgxQeSnV0h4ffCLP4WoPhRrw3kqk5Aaxw/+cjUBX5AHP7JwKsQE97dQB3CFlJhQ7wVVAS/+e27o0zn6nKCo/uFmSv2evp7mlCPbYKN8mOS7DgbPllQx99l1PL+rilp3kNFJNjZdezo3nT4mKlaOxXNFrvmqSFMLPP/7WDvXU50zvjKPxRfNp7hW5q3dRwWcommxPO5eoGgaArHg4EhRNI00o4VFixb16Tx9fmIXLFhAksEU1ZSOUwGbKOPW+9CXdAjQX+bINw/Xcv26vTy5YjpvfvM0RieFgwwFQcAgiShq9yqVUtZ9MZoVi8KPf0VJVd8GHGNE8N0/XYndpPHkp2bq3WGhdLgi3G75WEaCGb6/KQ94yI4w4DAGHPS5qL/lmj4rL1FZiir33EBNoHPQyalAX8xXFkHCo/Wu29twoutSs50JqhoeReWMrCTePG8Wp2cmdrlftOISrGYBpx2qDtRE5Xwxhjm3fIXL5voJhAQe+NDK23uMvHVAZXe1mfcPSuytj2nuPaUy4CPdeOq2p+4NzUqQdJOVVav6nm0WlaoEixcv5sX6OynGg0OM+VR6Sq7BTqnipsg0uKkpVRXBfo+O747mgMI3/7eNmfkJ/OasIhI58aTQVUzHyYLlTkZGisD+A1WoqooUi+A95TljtMKakhA7KmV2V8s06i4SsCMIAgI6vzwjwKRJnZWYni5eh4q235/vuzukYJWkQQ8MHmrxQ91REmyl4LFbonLfolZuKOO529l2wc9igj0C7KIBjxZC1/VBfwkGk4OtXi5evYVx8XZuWTym2/2dZgMtfoW4KKQLpifD5wehobKJ1JzIG1zEGDkkPPw2AL/1Bdj45lZUJcTWXZ8xbeIM6soa+PsN/+bZwGQm6Ju7zHfvjqEi1PubQ343+eZTM1OqtzSofrJlG2effXZUzhc1wX7aaadRK1vxaCFsYqw2cE9JlS3Uqj7S5OHpj4pGoZo7N5ewJCuJ38wbh9XY/bOTbjdR7Q5ER7CnCIBO1YGamGCPAYDJYmLRheHiRfr7QRYvCacIfr65hA+fWc97koFl44+60HqqrZ8qNCvBI81kYvQMjxZi7Cu/i5qCF1Wn0dS1f6dVG17mj8EmXbZSGTq1O+U9eMYk7jhtbI9LbabZTdS6OzbS6UmwXFfkZoSv+dx9rxJShncwY4zo4vV6OzTg+M7vL8di0Hlisxl3rI9Tl1QGvKSbBt+3PpzM8I2qn0zZyuzZs6N2zqgK9ry8PFIlC63q8Lmpg41REJERBz2roL9eBL8a/l4n02qMkogcQUqRKAhoUaqdsHCmwIwJAp+89il3X/ZnVDWW3REjTFVVFRkZGUf+Ts5M5EvT/LgDIs9vMQ/iyIYu5X4PeTEzfI9RdQ1F15m2/tGonjfqNvMz973Ei4XnoOgaBiEWRdoTxpniKA62MmmQg+iiRaXPxwPFJXxcV8+85CSuLBjFGKejR8f6K4IdKs6djGjEJhgNAr/8rsT/PT2GD57+GIAZy6Z02Cd/Ui5Fc7v3/ccYWVRVVTFnTsda7GdPDPLOXiNv7TaS5tQwSjo+V/e+c2/r0bkw166TYR15Rb0UTUMSxEHP+x9O2nplyEu2bCM7O7rtcqMu2M1mMwmSCW9CgFxrzybzocZAPxhGQULr597N/RkFe7yf/bnSckKaxjtLz+B3u/fyx8/38e3RBSxMsUYtUNCR7SSYasUeBT+72SRw61f2cUu5wAdPf3xEwLcjCHDDVRKL58bqyp9KBAIBjMflsBsk+MYcP/e9a+Ox9b0zOVtlnZunKoyd1n2KcDT99/0dvLfH08xEe3y/XqMnDHaGT0+pDvgokhzM++TVqJ+7X6LcVpa+yea551Hm9wzLDmYZWcYBF+7JsoXakI9UefD9U93RLpwrA16eqj6ISZRYZUplUnwcLUGFMq+X+clJGESRa0YX8sj+A6yuqmbh2IKoBYek+zXKGr0UZUanJaTNIvDbn0hs2qFzrKs9oMCjz6nc+7iK1Qrzo3K1GEMd7QR1ZRMefpsVuk7S6q0010Ue17H9w9289dh7bNc1xvZ1kEOMgKZhFk+NyP9o4FFDpD56d7+k2fZb+Pro1f+m9cyL+uv0I45M2co2f0O/CfZo5qoLgsBhn5vbDmxloj0eqyRx3adbeGj2TPLsNqp8fjItFjRdJ8VsYrzTwdq6BrYdVJg6KjrpkBl2E2tbfFET7AAWs8DpszsvPHIz4Bd/VLnzryp3f3kPkxYWRe2aMYYmzc3NJCR07RoTBIHZK6f36rwLL5jD+lc28eoOnZUTgthNI8MkXzVEguaGC597WhhrdTJteu+eo+7oN2dIfHw8ym9+wiHf8KyHPhjmHJMg4dOGR2T2QZ8bp2zkp3mTuCJzDMvisvjHwUMIQJrZzIaGRtqnrAK7HaMoUOnrWXVCfw+sJYIgMFC9hyaNEbn5OxIhFR66/l8Dc9EYg0ppaSm5ublRP6/FbuGiGy/Apwi8sevkc8xwMsOXDlPr7GAQ1FQyTVYmrnm+367Rr1EOK1asINtsPWXLzUbKWGMcuwNNgz0MIBwI835jFc1K10J2r7eFIlscXjW8EJkXn4Jf1fissYlV2ZlsqG84Isjz7TY2NzYxyh7dF98ki/iVgYlinzNZJD8TDm4tOaGZNsbIob6+nuTk/qlr8IXvLMdu0li920hgeKzjT0qTEjjSNz7GyQlqKuUBL0n/ug+Dof+KufX7rzHxg2fZuOgCmpUg8YbhEdTQzkD72kVBwCTKuNQgDin696qn5vg368t5uGIfB30ubiucxvkpRzUXTdcRBYE0o5kPmqpR29TmUWYHKQETW5qauWZ0AS+WVfBg8X5+NXkCZR4v6WYzsiDQWmeMqD/7ychKsFLR5KUwdWCCNHMyBA6U69SVNZCWlzIg14wxOPRnJUj/j87nrCITL2w18/h6C/lJXS9O/e6+adlOk87MDI2W2v7V1ne4m1gYn9av1xgplHhdFNniKCrqX3devwt2s9lM+n//xP6Lv0c8Q0uw96RiWnzawAaD5IcS2NDQwJy01H66QvffeZbFzvz8mbxZWc3Glhq+kZrZqXjMFxNSeWrtARqtrWTEOYkXJbyNITLtIvGpCrfMy+eRPWVc/MnHNAUUbpk1msJsAUHoWqj3JMXt+HrwmYrKhgMNvRLsXRW06a7efE56uEpd6d6KmGAfwbS0tGC3928u9tkTgry2w8R7xf07J/5sfoBxXcxzPTHN92R+LPN4KTAZSYwfGCvWcC7LW+JtZZwtjqnrX+73aw2I/WTs2LF4jRYO+dzkW4ZO8YJolEONNhZZIs1s5rDHQ54t+j4rVdep9PpIt5hPmG9a6LAjCgIrMtJ54lApFV4fObajJW81XSfBaGRGYgKvVFSSaDSSY7PiCalHFgAFcVb+b9Zo6v0K2fb+KeZhMkgEQwP3++W0Vakr21PB7BXTBuy6MQaWAwcOUFhY2G/nT3j4bRKAB248TNnnlf1yjeqDtTx843/YMW4l4xre6PBZNIXj3lYXS9P7SwkZOQQ1lVSjmTHv/HdA+oIMmGNk2ievoJ52HhV+D1mxIIuTMtphZ0N9Y68Eu67rNCsKZR4v5T4fE+Oc5NlsXLd5C7taWijzhv3eby5eRKGj60VWu3AeZbeRbDKytq6eS2y5R87f/vk1owt46nApN2/bgScUdhb+Ij//yHnMskS2PXqTiFLW2kmrdlgMtPoUnJb+bz7ULthL91b0+7ViDB719fVM76do5WMZNTmPUZPz+uXcmqbx0gNv8uG/3+P8FWCM8DXsicKzt7WVSfFOpAFqYDVctXV3SKFBCTD+mb/icAyM23BASwRNXfsiiQYTFf6hUxt9KD4sBlEkx2ahwtsx6FDXdbxtAvSg28PzpeX8pbiEW7bt4OnDpQBc9+lWpr/5Dldu2MRD+w5w0O0BYGVmOrdOnsi7S89gzxdWnlCot9NesnVFRjqrq6qPtEoVBAG/qtKqKIyy27hpYhEX5+Xyk/HjeOH0BST4e5d+1pNI+K4YlWznYP3AZF5kpYHJCO8/uZa9G/cNyDVjDCyapiEOcuW0aCCKIksvWYgvJLCr9uj3iZYJHqAxECTdPDCldYfiPN1TKgJe9NuuY+zYgatcMKChjLIsM/atf7PjrK8PqValg2WS13QdVyiETZJQdZ2P6xtoCgZpDAZpVUKclpRIvd/P/+3YTX0gQF0gwDiHg1cXL2RLUxPPl5WTbjGTYTaT0das4tbJE/jdtClY5I4vwjmZGV0N4YS0a+VXFo7imdIy9rncFLtcnJOZwc3bdnBhdjYLUpIQBIFzsyI7dzRJcZjYUd4c8XGGHGfEjWOMBoGfXilx10M+blp5J/e8dyujp42K+Noxhi7l5eVkZWUN9jCiwqiPnwFM7KiVmJ4RXR/4AbebQrt9yMzhQ5Uj+eqrVg3odQc8RyExMZGsp/5M8Ve+Q5LRPGQqFUUq3HVdR9V1ZFGk1u+n0ufHpSi4QiFyrVYmxcfxzOEydrW04FJCtIZCXFmQz/yUZFZ9uJYDbg/uUAgdeGPxInKsFu7evZcEo5EEo4Eko4k0s5lWReE7YwpINplINZtINpkAuDAnmwtzOtcXbv88WmxvbuaA28NF69aTbbEyKzGRe6dP7XEntv4mnM+uD9hCcdFMEeVKuPcxLzcuv537PriN/Ik5/X7dGAPD4cOHmTVr1mAPIyoUJGhYDTo7a0V0nR5Fx/dkDgxqGtU+P/NTep4OGNI0PCEVQQDnCdK8WhSF1yoq2dLYzMQ4J1/KzcZpMNBcI3HY5+aBsr1sczcy3ZHINVnjKLQ6hpSCeDwVfg8FFseABMsdj6DrA1XmoyPb5q1im1CFcYAEuy0u3D9Z03V8qopRlJBF2NPowauqeBUVX0hlaXYyLiXE8/ur8YVUfCENoyTw46mj2FTbzEM7S/GpGt6QypQkJ7fNGcOT+ypZXVqPVZawGSTOzE5iZW4Kb5XWUeMNHNk+LTmOTJuJkhYvBknALkvYDDImSUCg64dzS10rRQk2zPLA3CdjytGXrrLVz6OfljIl3cmywmRsPeiVHglySnR60Jc3epFEgYz4vle+CtV1dBOdaIwbd+g8t1rFYYNrL5FIjheQzv1ln6/fX4RCIfbs2cPkyZMHeyhDmk2bNkW1feZgUv2Lm3j1c4m99RJXTg+SdNyj7G7s7HJIG9V9P9o9TW7SrSYSTCeOa/G0HP3MpSj8dd9+tjY1MyHOyc0TixAF4cic3M7bZfWsr25iblo8uxvdxBllLs4qwK+qvFRegV/VuLwgnxfKytnv8vCzCeO6HetgUerxsCork4IXX+3XfPUTMWhVBaauf5m4Veey/xiTjjcUwh0KEdQ0VF0nz2ajORhkT6sLXyiEV1WxyTJL0lL5tLGJtXX1+EIqfk1lekI8q7KzeHz/QdbW1eNXVXyqyuUFozg/O5NL1n3CtuYmvKGwSerlc2ayMCOBH67Zg1WWcBhlnEaZn81w4g9pbKptwWGQsBtkks1GFmYmMjbexrz0RByG8P5xRpk4k4GFmYldfsdIt3fF2Hgb+1o8LMjo+TF94fi0s4un9J9Zsrv0sp4SDKl8XFLPGeP7nkur2Dqa5080xjPGw9hElb89pfHKS3DvDTIZixf3+fr9haIoWCwWFixYMNhDGbLU19fjdDqZMWPGYA8lOqxdT9yj7/L7q/+GORRkXnJHbbxZ7ags5E7yAScP2C13+zFKInPSTt7spfWYmiV+VaUozsmnDWH34ZykRAyi2KGexb5mD5UeP9dNyee8UWmsr27iD1sPkmE2E9Q0/KrKt0cXMiMxAadB5tGSg/hVlSVpqUNOa3cpCpPj4sh44plBEeowiIIdIP/l12HVuRxweyh02LlvbzGP7j+ILAg4DQY+O3s5u1tauXnbDiySjFWWmBjnZElaKi3BIJVeH2ZJxCxJmNo0/0KHHVkUsUoSlrb9Ae6YMglBgPQ0HbtBwiZLCILAZxct7DQupxFun9s50CHVaiLVGl1Td3ekWk3U+IIcavWS74yOhjtU6CrKvTcYZQlV6x/D08nGuOpMCa8f/vWSxk2/D/Hnb7lxJAyddM4YkVFcXMy0aSMrjXHm8nAL4t11EssKjgr23gaj7WlycXpm0kn3Ob4UrkkUybFaKXG58YRCaLp+RKi3C+V6f5CmQIjZbQuGHLuZTIOd7c0tjHbYaQoq5LdlCSUZTTiNBko93Qdh721tZU1tPSFdZ7zTwZK0VF4oK+ezxib8qoZfU/lSTjZL0lK5edsODrjdhDSdkK7z68kTmZIQz9nvryGgqW3bNV5fvIimYJBVH64j1OaSjTMY2LRyGVU+H2ZJIuPxf+F0Rkdx6Q2DXgcw/+XX0Vedy66WFm6aMJ6bJxZ1SJ+Yn5LMB8uWdDpuaXoaS9M7a2inp3ZdOKQ9CtxpHT69etuZkGBnXXXTgAj2SPqhDyXS4szUtvpJdQ5MlG47F58j0uKCl9/VWPPcJ5xz9bIBvX6M6BEIBLBaR9bi2dPiRUDHp5x8v7C2fnK21LUwOzUek3TirIGu6tu3a9MOWSagaViTgkDHhYVRFHEpIQxieN9gc7jOhiukYJEk/KqK3tZ9wiAKyIKA0oPSzo2BIDuaW5AEgaS2FrySIBBnMJBuljBJEqnmsLK2JDWVuUmJSEL4/FnWsGvvponjj2yTRRGbLGOVJF5YNB9ZFJEFAYMo0hJUEBFwPvA30tIGtxLfoAt2gFFtmvthjzfq9cSPJ5olTQcKSRSYmuRge30rU5IHbxXYH0RLax+f7uST/fV9FuyRRssLgsCZ80ReflejZMvBPl07xuARDAY79V4f7ui6zgPXPYaOwDljjhal7422ruk6HkUl/hi/+v4WD2+V1lPotLKyB5UYrbKMKqptAllqOy9IAjiNMpIg4FZUDC4jAgFUXccgiNhkCassUeMPkGQyoenQqihMjg+n1p7MDD8/JblTkN+q7K7di8szuhbGJ1IWxziP5qR7QyE8IZX4Pz9IQUHBCcczUAyZhM38l14j12ZlX6ur368Vza5JA0WcyUBrMIQr2P9dI3qbUz6YyJLYb+b47sjLBEmC/dsODcr1Y/SdvXv3Mn78+MEeRlT58JmP2f7hbqalq0xOC2u3XQn1nmjr75Y3cFp62Ey+urSOOc+uY+ELn/BRZSPtCnx386rTIKNqdKh4KbVp6MlmI6OcFl47VHvks7W19cxPScJpMDA1Pp7/HDoMQFMwyIaGRpZ3YbEdDKp9fhqDQWx/uH9Ac9VPxpDQ2CG86hr10mvEXX0W+5obGRehrzJy8/HwE+6np6fyRnEN5+enR5RuFq0gtcFEzDp5sA6A06vgSbDisB79bbWK3uW4R4LRIJCTDvs/LUZVVSRpaKRwxug5jY2NTJkyZbCHETV8bh8PXvEHZBEumqicNMCsdGfHbJLjU96KW13IITM3frCfH40fS0oojhvHTWBBShJWuV2EBLu1hBpbAriVENvqW0kyGxgbb+Pj6iYmJzlJMBv4xtgs7vy0hCqPn3KPn6W5CUzIkwGV7zuy+OnaPSz/4AMkEW6aVUB6hgb0XgnpTmb0RMEJaRp2XxD95gf7vbFLJAwZjR3Cwj3x4bcZHWdjX7MnomOHo5YZKUZJ5LScBD4ubYzouEgLsQxFeiKgJ+UlsuNQZPcmWhTmCgSCULGvelCuH6P3hEKhEbcYe+LOF2jyC6wcHWJTSyU/+mxrr6rONQaC7G1t5Zfbd1HiciMQLnm9PCPtiFDviWvzR2t288U3PgXgx2t386u2yo0v7K+hORAOAJifkcCPpuaTYjGyLDuZG2YcNWln2cw8eMZEXj53JqvPm8NXx/StKFY0hPrBVi8NfgX51oeZNGlSn8YTbYaMxt6OIAgkP/oO4reWs7vRRVFCz6sbDdfAr0hIt5upcQeo8wRIsQ1shH5/s/lQAxVNPmpa/XgCIa5aVIiiatz+yk5CmoZuNWKQRO7/7iJ2H27k4Td3YzHJWE0yuakOLls2jtpmLxX1btITrEgnCfKJNoW5Au+u1ynZcpDc8SOjctmpwu7du5kwYcJgDyNqlH1ewbO/e5FEi87Zo0O41ERu2rqDt8wVrEw+8bPZVXGaj2pruXPnHs7KTOe2yRORe1lu94+Lur6/9y3sqOUuz0lheU7XPu1Ec3Tm9mgI9ZaAgt0gY7j9cUaNGnrVJ4ecYG8n8ZF3KPrWcvY0eRgXbzvii+mOduGu6TqNPgWfomIxSCRbO/6YdZ4Ab5fU0eRTCIQ0mnxB4swGrpiZiyQI3L/+ABvKmzC0CYdLp2bz5UmZQyJncmp6HB8erGdergFjD4VXtILUosHHJXV8vK+ObWXNbCtr4rdfnsa5U7O46rFPMBtk0uPM2E0yXz8tH6MsYjFKGCQDktOMyRDWOkRRwGiQcPkUapt9tJdZWrOjii/fsRpJFBmXHcf1X57ON4rS+v13G50bPnfx5v0svaRzCmWMoctIMsOrqsod869D1UUunhTEJINJNvHrgunce2gnixLSEACzKHVy5x32eNje3MKnDeEaIf83uYhJ8XH8dMI4LsrN6fL9OZG27lZC3PDxXj6tbcVmELlvQRHTU8LBbu3v4sO7SllX3YQsCNgNMm4lxIWF6ZyTl8rOBhf/K69H18Esi6RbTZyVk4LN0DfLSjSEeqnLR5xRxnrXf8jO7lz9cygwZAU7HBXuh1w+8h2WiDT3Z+tquGfNfoySwLSMOP5vyVhy461obd3JPEGVz+vd6DokWQ18WtnCgSYvP1s0mgONHoob3ExIcXDVrFw0HXLiwtHWgy3U25mc7uTDgw0sH93zvuADLdw1Tae4xsWGA/V8XFLP+AwnPz5rPC9vKaeswcvU3Hi+Pi+f0wrDUavbfn1ul+f57ZeP5ha3+9rH5yRw91XzOu37mytO4/x5+YxKd/JZST3JbVHyZ933HhaDzCWn5fHV2blIUW70MSZPQBRhz4ZYc5jhhKIoI8oM/9x9r3GgSWROVogZGUcD5s5ISGd+XCoGUeT+0t28VFfKgrg0kgwm5sWnsGJsIhe//ykmUWJ6QjxXFxYgIjDa4WD0CTqSncwEf+PHe8m2m7l97ljWVDZxz5YD/H7hBNKtpiNz6OKsJEbH2QioGgFN48p3t7MiNzyfra9u4tmSahZlJGCRJRQ1nC/eF6Ih1Pc0ucl3WLD8/jkSEhL6NJ7+ZEgLdggL911r1lC/7h5sRom0uO7Lhm44UM9/PqrirRvPJC/Jxu2v7ODmtSU8fe1CNE1HFAXG5Dj57ZT0I8dob+yistmHIceJ0SySkxnHmRPSmNKPldf6QhowLt7EplY/87sR7j0JPOsOIe3kRSk0TedQZTPbimuorHPzvYtm8Y+XtnDd71YzqyiD+dNymLdoDNK0HO6dcbTXtV7T0OexHYvJKBFSdbKSbOSmHp2Q/vKTpby5qZTbXtvJnW/uYd3vLyTBcXJXRnd+/WPvqxUYld9EyebPCSkhZMOQf7ViAJ999tmIKbN7eHcZ/7j538RZdL692IvD3C4IjxVoKt/Vx7MoIY01TbW4QkFSksOC9s3FixAEAZei8El9IwuOSROLNEX4w8pGXrp0Dllpdi4utHPrp/uotYTIzzr6Tk7OMtJ+59cdbmRpQTLLZqRhdhgxVxlYNTmd2y8buPK+hm5aPuyubKFAtRL/4GuYB6irXW8ZFrPPokWL2JOcjPDWLfgVFXM35pjyRi8uf4i8pHBO/NKidJ7ZGG5rKh5j0ldCGgZZZFtZE89tLuOvbQ+RxShR0eTlB//ZzIOZ+5icHc+N50wg3tq9j2dXRQt+RWVmfiLVLT62ljYRUnV0dJIdZuYVJlNc3crBene4uIEokJ1opTDVwb4aFy2+IJIoIAoCOQlWEu0mSmpcKKqGKApIQnh/kyxiNkh4/CH2VbeSFmfBYT76c0bbstBuPispbaSm0cOhymYOVDTz3a/MJKCoFF34VwJBlYmFKcwsykDXdb5+9mS++YWpyPLAxmhmJds4XOumIOOodWJ8TgLjcxL4warJrP60jASHife3VVDV6OGi00dHxR8/frzM/gMhDmw/zNiZhd0fEGNQUVWV5uZm4uP7vvAdbNSQym8XX0dIk7lmwVGhfnwKWnONhCzAdEcS0x1JHfzq7XPGjuYWzkhLOfJ3pEK9yuMn0WYk8Zj5MsVmpLGLKjkhTUMWRW753x4umpxFUtsx3qDK6wfq0Z7fyqgUOxfMyCHJPjgxRZqms6OimclZ8Ug3/2dYWHiGhWAHKCoqoj7l74Sevpa99R7GZ5zYpOxTVFKO0cbirAYcFgOVzV4y449WljK0CZz9tW6UkMas/LBWGm81cu2SMXzvzLEYZZHXtlbwlQfX8M71Z3brq73or2uwmQxs+OUKtpc1c/Pz25BFAUEQmJWfyLzCZN7dU8NDH+xD03RCms435uVz8xcmce9be3hzeyVqW638ey+awTfmjeLrf/+YfTWtaDqoms471y9lZl4i+T/r2DWo8YEvU1LrYs6vVyOJArIoMCrZzq7Hv86za/bz/Qc+QpLCi4al07L518/O5J5nt/C313cdOcfVZ0/g5xfN4PJ732X1p2WEVI2AovKX75/OZV+bzxd/8gwub5D8jDgKsxPw+hWyUp2se/xyxuUlYThm0WU2Dc7jNS47njc3lXYQ7O3Iksi5c/IA8PgVbv3XJu5+Zgt/u+4M5hWld9r/ZGgVzR209vHjDLz+hp89n+yLCfZhwKFDh8jLyxvsYUSFp+5+if31MqePDjI7L1zroiuh3h2bGxqZGB+Hsc1V1ZtiXoa0cBEbwzFKlCx23eZKFkUONnmpbPWzckzqkZih2VMz0J1GfEGVTQcb2VbWzG++NBWHeWBrr7v92lDBuQAAIABJREFUCvtqXUzLScDwrScH9Np9YdgIdoDk5GQC3/oPo//5TXZVtDAh09mlkLUYJLzBoytRm1HGE1AwdrHScvkV3tlVxRemhU3uuq5jNkgdGook2028tbOK4upWxqaf3Ee9844vHPn/WZMyOGtS57SMa5eM4dolYzptf+ibc7o854Zfruhye/Dhi9F0nWavwuodlZhlkUmZ8ZTe+0UUVSPUVrBFq2hm2bRs3v7teaiajq6DwxJ+Qb56+mgWTDw6xsy2FlC3XDKTH35xCrIkYjJIZCWHrR87n/tOl2OZNDq1y+3dIaQlRd0cLwgCyXFm6lt8JJ/EdfOFufmsmJnDn17azoqbX2Xj/V9mfE7v/Wbjx4dfpz0biln1vZW9Pk+MgaG4uJiVK4f/77R34z7+feuTJFh1Lj8tXGymJ0W4jo+C/7zVhUEUiWtrXOJMCaLrOvV+hTpfgHq/QkjTWZp9YrecOctIqqpR5fJ3CHg+3Owj+wTv4sObDrOsMIWstngYQ46TM3AemYNDqsaYn7/KJXPzunU7thNQVOpcAercfmpa/OQm2ZiQGccfVu/hs9ImXD6FFp/C7RdOZeGYFCbe8hrN3iCqrqNqOptvPZtUh4kmb5CWRddjWDa8SkUPK8EOYDKZ0K9+kqJHvsbuytYuhXteso1D9e4jf/sVlSaPQnIXPtVWn8L/dlfzzvVLga5N2K1+hYomL1kJQ6uOtCCETfNJdhPLJmawrqSexePTumxfGtfqY2pB5/7JeWkO8tI6B8eM6cIvr9c0dOtrHyoU5SSw9UA9i7qJyTDIEtd/eTqXnjmOtAQr/9tSzq5DDXz3vEkYsuIjKnCTnSXhdArsWL0OuK6P3yBGf1JXV0dycvKQCYbtLa2NLn697OdomsAV811Iksrxddihs7Z+vFA/5Pawob6BkK7zQlk55V4f/zlnMjsaXJz1ykbiTeEulxMS7ScU7O3BaUZJZHK6k7eKa/na1GzWHGog1WYi7wRtlZ/YXsEzF8/EKIldBvfKkojZIBIMnbw2/Pr99Tz5ySHu//osfv7cVh58bx+JNiNpcWZ+uHwcEzLjcFqMTM2Ox2k14jTLFKSEFZZ/XzMfCFfCk0SB6mYv8RYD2oW/Z1nh8LO+DTvBDmGBZrz6SZo++ICqT/8I0MHEPjbNybh0J//++CCLx6fy5IbDXDAznJawdl8dU7LjcVoM6LrOmzsqMUoi+cn2I2b2gKJy/TNbKGvwEFQ1AorG7y+egW2QTMs9IdVpRhDgs8ONzMjrusXr8abj3tAfwr0/tHaH1YgvoBJUVIw9SJFJa1u0WYwSj729l4ff3MN/blzGFHPPf3NRFJg8ycC6j4PUHK4jrQf1s2MMDrt27Rr2fdc1TeOey/9CnVvky9P97PWVc94/97IyI52/zJ7BzuYWyr0+4vw20o0WnLIRSRDYLdawd7+LMq+XEpeb740pRAX+e+gweTYbo+w2zhmdiKbrTEt2UHXFmSdt/AKdI87/dO4krn5pG/et249BEvn92ROxG2WueGEL180rYHpGOPXt4c2HSbIamJ4R10Go/+HtvbT6FKxGiXp3gDFpTmbmn7x19fh0J9csHg2EM2nuu2hGh5gqgKtO71pIt8+Zqqaxs6KFmflJqF9/lEJb//Yu6S8EXe9jDsEgU1paStzhB2hs9ZGfeVRo7T1YzzW3v47LG2RMbiL/uO18JEngh/e8zQ3fnEdBdgKapvPKh8WYjBJnLxjd4byfbC8noKjYLAbi7GYKsxM6PSRDkY+3lZEcb2Vs3gBr1imdrQERU1ff93Mcg8sTYEdJLfOndhPuegx6TQMhVeOeZ7dw1zNb2PnQxeSknLy88bELnRefaOSv99Vywz++z/LLzuj12KONoihs3Lgx1o+dcKW5jz76iKVLlw72UPrEU3e/xKM3/Zfp0wzceXscoggV9R7qW/1MK0zm0dV7+NuL2ylr9FDnCvDzcyZw5w/O4Md/W0tpnZu8VAf5aQ5sZgNXrhh/xHoR8cL9BO++36/gDyiomk5SQlhA7j9UT3qqA1tb++viA7UoisrEcR1dls8/tYbPDzUQVFREUeDqC6aTkdJ12l20UFWNfaWNjG5sRr7qiWFtzRn2gh3CnZmEbbfx+eEGJhbGtKSNOytIdFoYnXvyFW5UGYKCHeC9jQdZOqfnlaGOtRzsq2hmTFY8n5c3MSrNeULN/9iJsGSvn+9+/RArr1jCTx/9bu8HHmVigv0o69evZ9q0aVgs3afODlW2f7Sbny29lYQEkQf/nEB8fGeN+lg3ki8YQtV0nMfNj29uOszc8WkkOtrqdERJqPeJfpgHumNbcQ3pSTYO2r7KvHmd62MMN4ZUrfjeYjQaMcy+kwkFyZRVt1BeM/xro/eF2RMzKa9txR/o/05wR4jGy9gPk0RhdgIHypt6vP+xE1t7nMENj6xnyQ0vU17nPtFhRxg1xoTNLrL17bWoaucSnTEGn0AgMKyFemN1E3deeBsAN//c2aVQPx6LUe4g1FVV490t5SyfkXNKC/VQSGN7cQ3j85MwTP/FiBDqMEIEezvijDvQin5CvMPMvggbpYwkBEFg8ax83v//9u48Pqry3h/4Z/Z9sieTZJKQELKSBRIICoEAKsulIIgsFQqirYLW2tbrfsVeC8Kv7VVaq9daa0HB7eKCC6Dsi0AISzYC2SEJWSfL7Pvz+2NMTMg2k1kTnvfrlReQOXPOdx5m5nOe5zznnIJa3Gjs8tyGvbCnPZyYCH/caHKuDT5+/h6kxwUhc9MneP/wtX6P9+7ls1gMTJ0uRlODCX9a/3dYzDTcfcloP8VNrzXgv/I2ob3dig0PijAxdeDTv26d9Nl7bg0hBEcKGxArk4L947Hz2zHUjSYLam52Im1CKLhTtiAoaHRMDLbHmAp2ABg3bhyE07ZivDwAV6pbMQaONIzY3KmxKKpogXmY2aQ+xQ1fGEI+B2qt/efj3volx+ey8davZ+Ffv5+N8nrbF2Zzh3bQ99YTz4UhJV2Aw7tPYtvav8Js8uDICTUoQgiqq6t98qYd9rBardj+i7+hvNyMu+/iYfmygUcdhgp1ADhefBOZccE913m43UKdEIKCKzeh1Zugj30EzMl/BNPFl5j2tjFxjH0w586dQ5zmEzQLZZiYYv8EqrGAKJttfxKCoz9UICstCn7SXl8Ezn6QhvlwM6RhQz5+q+563YEQgu+OX8W8vCHul+xAexBCkPXzfyLIT4BtT8xFVkr/axU0W/nYvqkaJeeVmLEgCM+/kQhO7G9HUr5L0GPsQEtLC+rq6pCVleXtUkbknaffxyd/3gf5tCDct+sOsLhMRIr67rCGDXNGbkVRO4KDpYiKtm8ukojj5nk6Ss/e5lip1KL8+A+YlCSDMeWFUX1IZihjazflFjk5ORDm/DdSkiJRXHoDKpXO2yV5HIPBQM6kGHx34ho0WoO3y/EKBoMBiZiPVsXwx8jtXd/Rf6zF1ImRmPXwLvzsiY9ACEGnSg9FpxYXrjRi8sL/h2X/KUH6NClO7Vdg2xPlMNe+7pLtUyNz9uxZTJ482dtljMjXb3+PT/68DwFxYix+e8qIQr04vxksJvO2DfW6egX0BhNUEQ+AlfXHMRvqwBgPdgAQiURg+v8c7cYcaHUGKNpV3i7JI3r3mEVCHhbfPRH5l2/AaPxxWNjZ4bRheriO9sAd7eE7akpGNM4X3hh8AQfbw0/Cx5bHZ6P8y01YvyQDDAYDXx67htC5/4PpD/4bT/9iGmZMi8Ur/05FWo4UJ75pw/Ynr9Fj7l5SVVWFuLi4UXkK0/mDl/HXx9+BIJCLpe/lgO/HdTjUS843IyExEumZ9h2GGEuhrlRqUXKlDhHhARCE/hyzZ8/22La9ZUwPxd9KrVaDb/wSldVNiI0JBY/n2esOe0PvgLVarfjiYDFmTIlDaPCP54S6cUjel4bjAaCo7CbEQi7iYgap2QXH+TqUOnQo9YiTB/S0jU5jwQu/KEXJeSUe/9tDXrnc7O0+FL9v3z4sWrRo1B1LLTtXgd/f9V+wmgiW77kDkdlBDod6aUELBHyub4S6BwOdEILSsnqEhkhRVDMed42yy8I6Y3S9y50kFovBDnwASmsutFoDLhXWjPnJdb3DlclkYn5eMi4W18Ni+XFCnTsmwvzI13rtyfFhqKwdIrxd0BYBUoEt1HsRiFh44e+JAIAzXxU4vQ3KMZcvX0ZWVtaoC/XKSzX4z3mbYdZZsGDHZIdDnRCCi6cbEDdedtuFutFoRnHpDSQnRkIcvva2CnXgNgv2blOnToU4Yh0y08eh7FoDlEqtt0tyq96BKRRwMX92Mo7+UIGq7pBzJtBG0ZA8h8NC4vhQVNa0um0bffRqmyAZD3HJQhQfL4ZBd3vOdfCW9vZ2REREeLsMh9SW1uG3d70Ig8qEeX+ZhIQFEQ6Futlswdkj1zF+fDhCQvyG3Z6IEzgmQp0QgkuFNdDrjbAI7gEr4OcQCn3rHh+e4LsXP3czDocD+K0GP7gaBsk5FNQ0IylZPuqOwdn7YWRIZX0+XHPmh+DYySuQhvMRGuIHSMOcGgp3OJClt9witVdt7gz3cSlhOHrwFOJjB5lA5OIRjN6vJeuuSFT/rQLFJ68i+54Ml26HGlhJSQnS0tJG1ee6vvwmHs97DoYOI7L+kAnxPTGIFOn7Ldc8SH+EEILKggokpIbDT8aE2jz8BZqGWkbMHvkdD3sIhr/bnLNKiq9DIhEgM30crOIVmCT3/fumu8tt2WPvLS4uDiF+q9F4Iw5tbUoUXqoeVcPzGpMDF+LpFaYsFhNz8ybiytUGVFQ1AnAuUB3eKfDwjNjeosIDUHPDtTedsUf2XFv7Fhy87PFt344sFgtaW1sREjJ6LjPdWNOMTXnPwqAwIPP5NMQuH4c7QvuH+mCUnRpcOnwZ06ZPQKhs+J76cFwS6m7W1aVB4aVqJCXLEeJ/Hxh+q8Ea4Bbdt5PbPti7/exnP0NYwCqkZ8ai/FoD6m54aLjWBUYa7gCQl5sCBhj44Vy57e523gr3W3vwbhSfnoqKmlbo9Sa3b6t3m0ycFgyegIULB064fbsUcOnSJSQkJHi7DLs1Vjfj0ZlPQ9ekQ9rvUhH/wHiHQj2QY0ZtYRWmz0oEm+1csInZAaMi1EuKrwMAmNYZ8BPcP6p24tyJBnsvAoEAYu59CAu8D2Eyf1wpvQHzKDk9yeFw7xWk8eNlCPAX4fCxEs+H+611ecjErDRcKK7z2PYAgMtnISM3BLVlSjTWuPcMgNtdY2MjdDodIiMjvV2KXaqLruNX034PbYMWKY8nIfGhCQ6FuqKqDvlnKnH3gnRI/Zw7puzrgU4IQeGlajQ3d6K8NBiywAcwbdo0b5flU2iwDyAyMhIBopWAaTp0OiNKiq/DavX9y7JqTO0j7r0nJ0ZickYsjp28AoPB5Llwv3VI3kPhHhkRCB6Xjdo6zw7J37nQdpW6M1/S2fHudPHixVFzv/WS01fx+MznoG8zIOO5NKRsTHI41JksJqbPTHKqDl/vpRNCUHalDpUVjUjPjIUscBXWrl076s528ITb6jz2kSCE4IsvvkD2nUpcr23BxLQYcDj95xw6M/nE7RNX7NA9Cc9stmDfvtOYOjUZcvmPw1qOHA/3YK/bboPUbzKZceL0VczNm+jyTd66c9O9o6Ro0mFV0rfIyEvFn4+87PLtDuZ2Oo/98uXLkMlkkMl88L14i/z9l/DSfdthNVkxZetkRC+KcijUC05fg1DEQ0rmOIe2O9y5776g93dfR4caDfUKJCXLoemYPurOcvA0uqszDAaDgaVLlyI86AFkTopDS3MXrpbV9+vBDxXA9sxKdcdzR4LNZmHx4umorGxAXV2LR7ftaRwOG8mJEbhWcdNj2wySCZA8JRDFJ69AeZtcBdHTOjo6RkWoH/nwFF5c8ioIIbjzbzkOhbqiVYlzJ8owcXLsmAv13iMHWq0BZVfqIBBwESD+D/gJ7qehbgca7HZis9kQc+9DlGwNEpMiUXejDQ31ij4z6IcaylKbOwYN6eGGwDwR7r2H8dlsFvLyMqFW63Ds2GVYxaH298SVTV6d8T6gIWqPCA/EzcYOGAyunUg31KGMOxdGwGohOLLnlEu3SQEnTpzw+eOt6k4N3n1uN15dswMsPgu579yJZff72x3qLY2dKCu8jsyp8eA7cBpZmNC3Q73392BzUwdKS2yXgCbGOxEkWTWqJkJ6Gw12B3VPsIuSPYDwiADcbGhHdVXfIBsupEcS8EM9z5V6H6NPTo5BTk4yPvvsJNrauhwbZve1cB/C1KzxOHSs2K3b6D00n7dMDr6Ihbd++28c+ZCGu6vU1dWBzWb77M09dBo9Ptr2OdbGPYaPtn8BQSgfef+egcULxHavo/RSLeprWzB97kTw+PZfEnu0BPrNBgWKC2sh9RPCpJ2CEL/Vo2auhC+hx9idpFQqweR/j5sN7WhXqDAxPabPxTBGevx8uBB397H33he+0Wr1+OGHUqSmjkN4eNDoPeY+RN3llY1QKrXInjzeZZsb7Dg7AFzJV+D55aehVZnx4B9XIzrZNnubzWEhY/ZE8IW8Idfd1qDAtfNVPf8WiPnImJ066Pm7Y/0Yu06nw8GDB7FkyRKfuxiN0WDCt+8cwp4te9HR3AWOlIOkhxMw/uexyI0x27WODoUK5aX1SM6IcXjWu6+Geu/vMJVKh5qqJoyfEI6rRXLMnDnTi5WNfjTYXaQ74K/VVkHVpUN8omzASXae5Orwv1J6A5pOYMaMNLDZLMdm4LuBqy+B+f33BZg5Mx08npNXybJzx6ficgeeXXYKyva+lwpNnByA7V/kQiRfO+DzGpTv4NnsU2iq7HvpsdT7o3DP/8vEwphf9HvOWA/2Y8eOYcqUKRCJRN4upYfFYsHGP/4JDf8og7FRC46IhayHxiPr4fHgSTn9LhE7mJt1CtSUNyLrzgSHht7dwdU7CRq1HnU3FEgeH49rxVHIzc117QZuU7ftJWVdTSqVArgPyXItlPI9aG7sgkqlQ0xsCLhc7zSz2tzh0nBPSY0Gh0iwb99pZGcnIjo6zOvh7kp33ZWFY8cuIy8v0yO9vgmZAfj70Tk4s78RxGrbvy45q8DJfQ14ceVpbP3ufghE/H7PO/F+A5oqtZi0IAR+2aEAgNK9dSj9tA7hkwKw8Fm3l+5T6uvrERER4TOhTghB/rcXseXJN6GrUoLBYWLyhjhMfWwChEG8HwPdvlC/8EM5OFwWps91/ZkbjnB1oF+vaYXZbEFkVBAkjEUI9Z+MUJrpLkN77G5iNBrxwQcf4I57VGhtUSI+QQYWy3tTGlwZ8FarFYXnGyES8ZGZGQ+th2fu9+bqXntVVQO0WgPS0uJGvhIn5hdYLATbfpmPY5/VY9KsELzy7WvgCX4aljfqjVgTvwGaDhP+UjwTAeF8XGzlQlmvxQc/OwGTxoy3L/4ZMSlRfdY7VnvsXV1duHjxok/cY5sQgstHS/Dfv/871IUKgAEELYjG0ucTIJXbktHeXnptZROab3ZgUk48uF68vbQrA91qteJKcT1EYh6ix4Wgq24GkpOTXbcBqgedPOcmXC4XGzZsQFLkE9C2TIFeZ8S1sptobuz0Sj2unHjHZDIxKScSMlkgjh8vhLKNuPfOUENw9YjB+PGRUKt1KC934qp0TswrYLEYeObtKbhjQTguHW/FH5b/BcZeM/YP/OsoOm4acPcjMQgI/6k3L5ULkftMMixGKy4dKRl57aOIxWLBoUOHvD4LnhCCi4eL8btZL+Hpu/4b6kIF/GfI8IsDeVj3ZqZDoW40mHDxTDlMRjOmzEj0Wqi7cga9VmtAWUk96uvakZImx7jgDYgQ/5KGuhvRoXg3YzAYmD9/PgBA2XAZgcHnUFPVDJ3WiMSUSI/24rvD3VW9d2kwA9lBUagobUdFRT3uuCMVRihdsm5HaEztLt2xyMlJxjffnEVcXITT19weCTaHiRf/nYOXHziD8/svYfO925F1t+1ucJ/t+AZcPgcLnxjX73kBsbbZ1e2N3htB8aRTp04hLy/Pa7PgCSG4dKQE7//hE5ScugoA8J8hQ8RDSZg/W9qznL29dLVKh0tnKzAhRQ5ZpHd2lF3ZQ9frTagqb0KozA9Xzodg/fr1tluo+sYRkzGNDsV7QXNzM4jkK5QW16PyWiPEEj4EQs9MihGwJHYtp7M4dvGUdoUa5WU3kT4pBkLR0DO67WVvre5gtVpRXHQdaekx/S5ZKWBLB3kWoDMPvGMz1HMGYzRY8N4LZ1B+oe8NiXLvG4+Zvwzqt3x7gx5vPVSEqfMnYeUz9/Z5zGw2o6ysDGlpaQ7X4YtaWlqg1+sRHR3tle3v2LcXbV9fh7aiCwAQkRWI1PuiEBAnRjDfsWsimM0WVJY1gMfnIHZCuDvKdUhA/2kdDulo1yAoSIz0yeNQXhCHe+65h1721cNosHuRyWTC3r17kT27DfV17QiP8Id/gPt3Z+3tsTs6fE8IwfmzlTCbrci5c4LToxHevm51fV0bGhoUyJmW2O+xwUYIhjo0MJJRBZPRgsJjDTDqbTcjYrEZmDRHjg5yvd+yerUZD4cdwpT5mdj67Qt91zOGjrG3tLTgypUryMvL8/i2r5wtx3/95nUoz9t2tmLnhOHO3yYiLM3f7p55N0IIygqvo71NhTtmp3p1Dg7gXG9dqzWg8loTgkIkkIX7Q9s0G/Hx8a4rjnIIHYr3Ig6Hg1WrVgEANE2FEEvOob5OAb3OhLj4ULft5fYO7KHCs/sxewOewWBg6h0TYLVaceZUObhcNrJzxo94hrmrDx04Sh4VDKVSi4LzFcieMqHPY4MN/4s4gS497s/hspB9zwC9Ut0Ay/KZYHMZ6Gjuctn2fY1Go8HJkyexZMkSj22TEIKi41ew59XPcPH7IgCAdGooFj6bgIjJtveAo6Gu0xpw5tgVxCdFOHxJWFcbaaATQlBZ3gSz2Qp5VCDqro7DnRkrbWcn0Ez3KhrsPiIjIwNABvyZGnz88ccICdWgqbETQhEPUdH9h11dxZ7wdDTgmUzbnaYUbSp8++VFZOeMR1i4v1M1eivcU1KjUXC+Am1tSgQHOz6c3pur5wLc6tjOepiNBOOmjI5bDTuKEIL8/HwsXLgQbLb7v7qsVivOfXMRH776GcrOVgAAJFnBWPB0IuQ5ts/kSHrpl/MrYTZZMPOedK/M4QCc652rlDrcqG2DWMpHXHwYWqumIj4sA/EbXFcf5Rw6FO/DioqKEBx3Di1NXWhrVUEW7oeQMD+3btOeAHVkiN5iseLi+WrotEZMn5Xk1HCjN4fmjx8rRlr6OAQG9j3u7+iQvCuDvVn305Xn9Bozfj/xBPQaC/5SNBOJsZv6LDvah+IJIfjuu++Qm5trm4DlonWe/iIfX/3vd9Cr+1+nvbOlCzerbFcP9J8ZjvBfJGDBXT99/hwJddspolUwGS3InDreq7PdR8JisaKpsRMqpQ6R8kCc/FaEFStW+My1A6i+aI/dh6WnpwNIR3C0Ed+WfAtJUhMqy5tgMpqRmpAA4QCXHXX2tDZHnt+sHX4ZgIno9HiYTGYcOFIBBoOBzJx4REgcD3hP3+mut8w7InDs21LkzkrtE+6ODrs7O0zfe8eg947O4feuoqvFiCXPjIe/zDWTF33JyZMnERMT45JQJ4Qgf/8l/PnpN9F5xXbYgsG2HS7qfdSIxWZg8vJwzHkiDuHJ3f/njvXQAds56dXljZgyIxES6cjr98alYRVtKjQ3diIkVGqbA8S6D3FhcYh/0PO1UPajPfZRpqWlBVbxPnR1atF4sxPhgTKERwT0u0a4J0PQvoC3sVisKDh9DRwuG2lZsZD7jZ59S53OiNKCFszKm+i165H3DvbunQSDzoxHk76CXg18UPsmpIH9zyYYzT32c+fOIS4uDiEhIU6thxCCi4eK8Kdn3oTisq3tohZEIuWxJEhiJYgW/XQrZkeH2AeiVeuRf+oqIqODEZ8cOeL3jKcDvatTixu1bQgMFiM0TIrKi4mYOXMmndk+ioyeb1UKABAaGgrgYciEAENdDknYcdxoroeiTYWY8CiEhNiGCnv35twd8t1fPPYEPIvFRM7MZHR1qHHm6BWEywMxLTPca8caHSEQcDF5egS++eo8Zs1Og0TiG3cRu1mhQkeTHlGJEeDyvXstcVe7evUqmEymU6FutVrxw5fn8eGrn6O8wHb4ImJuOFIeS4J/ot+PgW4LdVcEeleHGuWl9eBw2Zh5T/qIAtHTYa5oU6HuugIBQSKEyfyhbMzAjEkLwefzIc/zbC2U82iPfQwghODixYsIT7yIthYl2hVqRIZEICKy/6Q7T/TkHenB36huRl1NK6JiQzBl4uD3MPclijYVSs43Y+GibK/03Lt77d09dkII/r4xH4feq8b0pVMx94H+d8Yym80oqyxFWlLGkOtmMhlIn5UCSYD9txJ1l1OnTiE0NNTh+3CXX6hC8/U2ALbj5F/87VvcKGsAGEDkXRFI+mUCAlJtkzld2UtvuNGGhutt8AsQIXFi1PBPGIAnA71doUbd9TaIJXyERwbg2D4Bli1bBj8/987jodyPBvsYY7VakZ+fj+iJxWhvU6GtVQWRhI+o6KCeEBoueAf7cnEksB1Vf70VN28oIPUXInFilM/devNWVqsV509dQ3p2HATD3GJ1MCP9Eh9oEqHJYMFL84+g7Ie2AZ9jJVYo0Q5/RvCw65+6TIYn3s9EmOChkRXoApWVlTAajUhJSbH7OaU/XMPW/9yBljN9L+jDZDOQtTwCs5+IRXpG/x0WZ9/XLY2dqLhSj9CIAMQlhPebIOpLt01Vq2x3U+Px2JBF+OPIFzzce++9CApy35k3lOfRYB/DCCEoKCiAPOUyFG1qKNpUIASIiQ2GUMgbUcC7M9wB2zDm1eI6sNksJGe47ip27qDs0uLM0VLMmpcx4ttpjuRLf7CzAzRU+QKTAAAgAElEQVRdRpz+vxsw6vqf7ma2WFB1ox6JsTGDrtdg1eL7t2+g9boOn9x8F9Ig71z578yZM2Cz2ZgyZYpdy5edq8CWp15H8+kWAEBMbghiZ4fBn2cGk81E8t0hSE7sf9jEmfcyIQQdCjWKL1QjONQPE1Ii+81094VAJ4RA2aXDzYYOCAQchMr8cOJrERYvXoyAAO9eAIpyHxrstwlCCMrKyhA47gcou3Roae6C0WCGPDoIfv5Cnwt5ndaAooJqcDgsxKfIIfXzgW/JARj0JhSer0J6dtyIwt2VvfahmExmFJyvxB13Jg34ePchmm931GDP89fw6zcexuJN80ZW3AgRQnDq1CmkpKQM24MkhKDgu0J88qcvcfnHm95ETw/GHb9NRGR2UM+wujtGnxputKG+thViiQDJGdH9jqH7QqA33exER7sa/gEiBIVIUHAkFPfccw89Pe02QYP9NtXU1ISvv/4ac5ca0dqshFZrRGCgCCFhUrTqh57s48mQV3ZqUHGlAUajCRMnxzp1upC7EEJw/EAh4lMiIY9xfJKXK3vtg7E32NvqdHgy6TgmzU3DU//aNOCyzvAP9Rv0HO5Dhw4hPDwcqamp/R7TdGmgUeoAQlB88io++dOXqC6yXVY39I4QzPrNBERNC+5znNyV71OjwYQrhddhNJgRER3U7//Z22Gu1RpQf0MBJpMJ/wARAoNEqL6cgmnTpvU7Y4Ya+2iwU9Dr9Thx4gQm3nkd7QrbkL3SwkZEVBA43J9OnGjQeG/GtcloRlVJLfQ6I0IiAhEZO/Jbo7qDxWJFaf41RE+IhP8gV6hzxYzrgQJkoJC/dZKkyWTGpYIaTL1jwrA7BU9m70dtsXtuLxw1yQ9PfncH0oN+On6vVCpx4cIF5OTk9DtPvbGmGX/fvA3nP2qA1fzTVxWDCeQsk2HRb+MwLtPW3u7YuezunXM4LEycHOvVe6P3ZrFY0XC9FRq1AfGRIgQGibH/Y2D+/PmIi4vzdnmUl9Fgp/qpqanBgQMHMOk/CLo61FCr9PDzF8EoCfGJSW1tje1oqGkCk8XEuEQ5JP7en8HdrbK4FjqtHmk5/XvGoyXYi4424cj7NXDkm8Fs7f/a9L0O9XfU61B9pgPxuYHY+NnUnmBvbW3FyZMnsWDBgj63X71Z1YQ3XtqGC5/chNVCIJsgxPgs20x2fxkPc38ZhdBxtsZwdaCbjGZcr25Gw/U2REQHY9z4sD47uN5ACEFrUxfamjshFPHhFyiCX4AIiqI4zJgxAzye785FoTyPBjs1pO4Lm4gTy6BS6qDq0kKt1EHqL4TFX+bVoLdarai9Wo+udiWEYgFik6J84jxuVZcGVy9UYmJOIgSivvfAdEe4uzrYHTXQKZS9w5YQgp0PXkbxN83441fPIuc/sgAAVVVVqKurQ25ubs9w8ZUz17D39W9wcu8ZECsQkSjCvc+Mx7Tl4WCyGINuwxVUSi3KCm/AarUiKjYUEVFBXnt/E0LQ3qZCa1Mn2BwW/PxF8A8S4+phMWbPno2IiAiv1EWNDjTYKYdotVrb+cWTrkPVpYWqSwe1SgexVABrQP9TfTxF1alG9ZUbIFaCiNgwhER470sZALoUSlQU12JiTiL4gr69KWfD3Z5euzeD/dbAvbj3JnY/WoSI8WH4r09+D6PJiItFFxEdGYXICDkAoO5qAz7b8U3PzVai0yRY/FQcpi6VuTXQu++F3tWhgUDEQ2JqFHh87wy3Kzs1aGnqBCGA1E+AgCAJLnzFwNy5czF+/MjvkkjdfmiwU05RqVQ4c+YMwibfgEqpg1qpw+kaM5gsFvzDAiCUenYWrsloQsv1JnQ2d4Av4kMWFwmR38hr6H0Bk5Eou1ABi8WK1CkJI/pidlUPv3ewO2OwnYKhLnz0m8RjUNTbbrJiJAZ0oBVBCAOb0T9AJy0MwbRfjsP46YE97TXY3A5H2qb3OkxGM26U10Oj0oHJYiImUQ7JCN4jNzQj34m1WqxQtSuh7lRhcogJUj/b0Pqlb1jIzc1FQsLI3i8UBdBgp1zMYDCgoKAAxQE1MOmN0HSpoVPpYDaZIQmUwC8kAEwP9er1Gh0aKxug0+ggEAkQmRg9oqF6Z8Ndp9Hj0skSJGTGIVjm2N3dfCnYRxLqAHBqTwOqLypxo7kRJrMZspBIMJlMCHodthZIWEheFomQ8T8FrLOB3vv5Br0R18vroVPrweawEZMQCbGDYe5MkFvMFnQ0t0Ov1oHL50IoFUEgESKghIPc3FzI5fIRr5uibkWDnXIrQgiqqqpw7tw5KDOs0Ko00Kl0MGj1YDKZkAb7QeQvdnvvRK/R42ZlPUx6I5gsJkKiw+Af6tiQtDMBbzKacfVSJYRiAeJSoh16va4Yunc22Eca6gBQU9WMhvoOhCfFQCwR9DuUcOvQ+kCBPpIwV3Wq0VDdBK1aB56Ai5gEOURSod1tP9Igt1qs6GrtgFapBYvDgkAsAF8kgP6wAtOmTUNWVhY9n5xyKxrslMfp9XpcunQJZ86cAW9uELQqDQwaPYx6I1gcFqRBfhBI7P8CdpTVYkXLjSZ0tdpO6ZIESBEaIwPbzpnPzgR8W2M7btY2I0gW4NApe86Eu7PBPtJQ72hXo/DidfBDAhEzPgzh4r5B2TvQnemddz+XEILONiUar7dAr9VD7CdCZKwMIjuvfTCSILeYLehq6YBWpQWbywZPyAdfxAdPyEfoVSFycnJob5zyOBrslE/QaDQoKirCxYsXgRli6DW6H39sPXuBVAhJgNTu8HWEsq0LLTeaYTGZAQYQKAtCkDzEZbepHGhHoPWmAnVVjYgcF4awKOduRzqcSJERJpMZJRdrMClnZD12Ry7AYrVacaW4HtWNGqRkxvRcVKh3ePcOUWd2lIx6I5putOLK9U4wwIA4QIKQ6FDwRa698x4hBOoOFdQdKpgMJvCEvB9DXACekAdZuRiTJ09GVJTv3+eAGvtosFM+y2Aw4MqVKygpKYF6MmDUGWDQ6qHXGGA2msDhcSCUiiD0E7kshK0WK9ob29BW3wqr1QqegIegyBBIg/2c3satAWYymnGjogEdrV1IyIiFNMA912Z3NtjtDXVCCIouXUddmx7RcaEIiwgcNMyBkQW6xWxB6812FFcpQCxWsDhsBMtD4B8W6JJAJYRA26WBulMNo87Q0wvnCXjgi/jQH1IgLS0NaWlpkMl86yJJFNWNBjs16nR1daG0tBQlJSUw38G3Bb7OAJPeCOOPx9B5Qj7EARKnz2vXa/Rob1RA2dYJq9UKLp8H/7AA+IX4g8Md2WlRtwaaUW9EeVENjHojkibFQ+ji+7w7E+z2hLpapUfR5eto1xEkZ9iOo7uqd67u0qD1pgKVTVqAAEwWEwHhQQiUBTk1CdOoN0LdoYJOpYXFbAFXwAWXzwOXzwVPxEfX1w1IS0vDxIkTMW7cOJftOFKUJ9Bgp8YMtVqNyspKlJeX4+rVqwhcHAWjzgij3oAahQlmvRFMNgscPhd8iQg8sf3H8WMkto+JUWdAR3MHlG2dtqF7AEI/MfxC/CEOkIDFHvl1ua1WK+qu1EKv0UMS5Ifw8RFO90K7g9RsMuPa5WqkThn63uZDHdO+9Th4W1M76ipvgsvjQBA/wenDJDqVFl2tnVAqutCktrU3TyyEVBYMob9joxmEEBjUWuhVGhi1elhMFnB4HMQEcWwBLuCBK+CCcVKDhIQEJCYmIiLC+famKF9Ag50a8wghaGtrQ3l5OWpra1FTUwPVnGiY9EZYDCaYjUaYDSZYTGYwWUywuBzwRAJwRQKwB+iVd4d897o1XWp0tXZC06mG1WwBGAwIxAKIA6SQBErA4XMdDgxlWxcaqxsAAP6hgQiNCRtR6Ngb7PYGul5nQF3lTVTUq+Ef6o+w2HBweI6NipiMJqjblVC1q1Dbouv5PU8kgDjYH6JAPzCG6SFbTGYYtDoYNTqY9EZYzbZrJ7C4HLC5HLD5XHB4PLC5bERdVCImJgbx8fGIjY0Fl+v9qxNSlDvRYKdue1arFY2Njaitre0J/pqaGgSsnQ6z0Rb4th/b3xlMJphsFtgcNjgCPjh8Htg8DhgMRk/o61Ra2wVIOlQw6m2hyWAwbOcw+4lscwOkomF7+IQQdDQq0FzbBAYDEAdKERodBq7A/muDR4usQwb7YKHeoOGCEAKdWo/66kZUt+jA4XIQFhsOaZDfkNu0mC3QKjU//mhR124ECAEYDLA4bAj9pRAGSMCX9D3ty2Iyw6gzwKTTw2Qwwmq2gFisYLKYYHLYYHM5YLHZYPFsAY59pYiNjcW4ceMwbtw4REdH01PJqNseDXaKsoPZbEZraysaGxtx8+bNnj+1d8fCYjLDbDTBarbYfiwWWMwWELMFVosVDBYTjB8DzWI2w2I0w2wwwmQwQnbLMWwOnwuekAe+UACeyDbzuvtYvtVqhUrRhda6Vtv5+GwmJAFS+IX4QyAV9jkOfOuxbHuH4s0mM67Ua9DR1A6jzgAA4Iv4CI2RoQW2wOzuLZu0ehh1Bhg1OpiNJvS5awyD8eMODxcsDgtMFgtWi609iMUKBpMBJosFJptlC202G0wW0xbcXA5YbBbCzrYhPDwc4eHhiIiIQHh4OA1tirIDDXaKcjGz2Yyuri60t7ejvb0dHR0dPX9XKBQ9f3b/vaOjA1qtFkvffg4WkwlmkxkWowkWowkmoxlWkxlWqxUhPAuCI0NgtVoBYgtYnUYP/1B/6DV6W+8WALHaQp3JZEIuZYLNtYVmeWE1VJETYDGaf9zBMAE/7gwwmUyAAbDYbGg6usATCm2HEJgMgMGArksNk14PBpMJFvvHnjOPCzaHBTaXCyabhc8eeRVcLhf+/v4ICAhAYGAggoODERQUhMDAwJ6f7se6/y4QCOixbYpyIRrsFEVRFDWG0HM4KIqiKGoM8elgf/PNN1FeXu7tMiiKoihq1PDpYN+0aRMSEoae7NMbg8GASCTCCy+84MaqKHvNmTMHfD4fM2bM8HYpFEVRtw23Bvs777yDlJQUCIVCyOVyPPXUU9DpfjpvdfLkyXjyySeRnJyM999/H4888ggSEhLwzTffAAByc3MBAFOnTsXvfvc7ZGZm4q9//euQ2ywsLMSWLVsAAO3t7Vi6dClEIhFiYmKwZ8+eIZ/7xhtvIDs7GzweD+vXr+/3uFgs7vPDYrHw61//2q62cKSW2tpaLFy4EAEBAZDJZHj88cdhNpvtftyZ13irNWvWIDw8HFKpFAkJCfjnP/8JwHa514ceeggxMTGQSCSYNGkS9u/f3+e5R44cwf/+7//aVRdFOYLuxI8OdOfeS4ibbNmyhSQnJ5OzZ88Ss9lMysrKSG5uLrnrrruI1Wolra2tJC4ujiiVSnLhwgWSnJxM1Go1+eGHH8gTTzxBWltbybJly/os197eTu65555BtwmAVFRU9Px71apVZMWKFUSlUpGTJ08SqVRKSkpKBn3+3r17yeeff04effRRsm7duiFfn1qtJiKRiBw/ftyu9nCklgULFpB169YRnU5HGhsbycSJE8mOHTvsfnwojrxGQggpKSkher2eEEJIWVkZCQsLIwUFBUStVpPNmzeTmpoaYrFYyFdffUXEYjGpqanp8/z33nuPTJ8+3a7aqNFj1qxZxN/fv+e9MZR//OMfJDk5mQgEAhIZGUl+//vfE61W69T2b/2sD+Rvf/sbycrKIlwud9j3ul6vJxs2bCDR0dFELBaTzMxM8u233464PoVCQe69914iFApJdHQ02b1795DL19TUkAULFhB/f38SFhZGHnvsMWIymQghtrbm8XhEJBIRkUhEEhISRlyXo7UN14bdNXX/MJlM8vjjj/dZhn4HeJ5beuzt7e3YsmULPv74Y+Tk5IDFYiEpKQl79+5Ffn4+vv76axQVFWH16tWQSCRoa2vDihUrIBKJ0NbWhujoaBQVFSE9PR1FRUVYtWoVJBIJWltbERcXZ1cNGo0Ge/fuxSuvvAKxWIwZM2Zg8eLFeP/99wd9zrJly3DvvfciKCho2PX/3//9H0JDQ3tGFVxZS01NDVasWAE+nw+ZTIb58+ejtLTU7seH4shrBIDU1FTweLaLoTAYDDAYDFRVVUEkEuHll1/uuY72okWLEBsbiwsXLti1Xmr0qq2tRVFREZKTk7Fv374hl926dStee+01vPfee1CpVDh06BDy8/OxePFiEDefkBMREYEXX3wRGzZsGHZZs9mMqKgoHD9+HF1dXXjllVewYsUK1NbWjmjbjz32GLhcLpqbm7F7925s3LhxyM/opk2bEBoaisbGRly+fBnHjx/Hm2++2fP4G2+8AbVaDbVajWvXro2oppHUNlwbdtekVqvR3NwMgUCA+++/36n6KOe5JdhPnz4NmUyGtLS0Pr8PCQlBTk4Ojh49iqKiIkyaNAmAbfg8Kyur5+/dgd795+TJkwEAly5dQnp6ul01lJeXg8Vi9TlGn5GRYXcADmfnzp34xS9+Ydf5t47W8pvf/AYfffQRtFotGhoasH//fsyfP9/ux11t06ZNEAqFSEpKQnh4OBYuXNhvmebmZpSXlyM1NdVtdVC+YdeuXVi6dCnWr1+PnTt3DrqcPTv47uTITqwrd1RH0qlwZmfdnbW5q7NDuZdbgl2tVsPPb+BLTvr7+0Or1aK4uBiZmZkAbGHeHfLFxcVIT0/v82f3co4E+0A1+Pn5QaVSjfRl9bhx4waOHz+OdevWuaWWWbNmobS0FFKpFHK5HNnZ2bj33nvtftzV3nzzTahUKpw8eRLLli3r6cF3M5lMeOCBB7Bu3TokJSW5rQ7KN+zatQurV6/G8uXLcfToUTQ3Nw+4nD07+L7KmR3VkXQqhttZf+655xAcHIzp06fj2LFjDtfkTG32cqSzQ7mXW4I9Li4OlZWV0Ov1/R4rLS1FfHw83n33XYwfPx4A8MEHH0AulwMAPv74Y4SFhfU83nu5bdu2Yfr06XbVIBaLoVQq+/xOqVRCInH+nte7du3CjBkzEBsb6/JarFYr5s2bh2XLlkGj0aCtrQ0dHR145pln7HrcXVgsFmbMmIH6+nq89dZbfepdu3YtuFwu3njjDbfWQHnfqVOnoNFoMHv2bAQGBmLOnDmDTgS1Zwe/W2lpKVgsFurr691StyOc3VEdSadiqJ317du3o7q6Gg0NDfjVr36Fn/3sZ6iqqnK4rpHWZg9HOzuUe7kl2KdOnQq5XI533323z++PHDmC2tparFq1qud37vpAJyQkwGw2o6Kioud3hYWFLhkq3rVrl0NvYEdqaW9vR11dHR5//HHweDwEBQXhwQcfxLfffmvX4+5mNpt7vlQIIXjooYfQ3NyMvXv3gsMZ2f3JqdFj586dWLlyJVgs281rVq9ePehwvD07+N22b9+OtWvXoqysrN+yVuvw93DfvXt3z9kqCxYssPflDLgtR3dUb922o52K4XbWc3JyIJFIwOPxsG7dOkyfPt3uz7uztdnL0c4O5V5uCXYGg4GdO3fi5Zdfxueffw7AFmTr1q3D22+/3dM7B5z/QA9GJBJh2bJleOmll6DRaHD69Gl8+eWXWLt27aDPMZvN0Ov1sFgssFgs0Ov1/U4j++GHH9DQ0NBvgsj69esHPX3MkVqCg4MRGxuLt956C2azGZ2dndi5cycyMjLseny4Wux5jd1aWlrw0UcfQa1Ww2Kx4ODBg/jwww8xZ84cAMDGjRtRVlaGr776CgKBYMB1UGOHTqfDJ598gtWrV/f8bsmSJaisrERhYWG/5e3dwS8qKkJ4eDjmzZvX53tg8uTJ2LhxIx5++OFha3vggQd6JnHdetqlvUa6o3rrth3tVDi6s85gMOyeeOhsbfZytLNDuZk7ptpv2bKFiEQiwmKxSPcm8vLyCIPBICKRiMyfP58QQkhhYSF5+umnyZ49e/qcrjVp0iTy6KOPkgcffNCh7eKWU2AUCgVZsmQJEQqFJCoqqt9pHfPnzydbtmzp+ffmzZsJgD4/mzdv7vOcX/3qV2TNmjX9tj1nzhzyj3/8Y9Dahqrl1jouXbrUczpRUFAQWb58OWlubrb78aFqGe419q6lpaWFzJw5k/j5+RGJREImTpzYs97a2loCoM9pOCKRiHzwwQd9tkdPdRk79uzZQ8aNG0d0Ol2fn/vvv5/87ne/G/A5+fn5JDg4mHz22WeEEEIuX75M5HI5ef/993uWWb9+PVEoFOTy5cvk0UcfJYQQ0traSuRyOVEoFAOu99bP+kBMJhPR6XTk2WefJWvWrCE6na7nFLKBPPLIIyQnJ4eoVKp+j61bt86u00O7rVy5kqxatYqo1Wpy6tSpYU+1jY2NJa+++ioxmUyko6OD3HvvveTnP/856ejoIAcOHOip/YMPPiBCoZBcvXrVI7XZ04anT58mQqGQKJXKAddBvwM8z23nsdtjJB/oofB4PCKVSsmLL77o6lKHZDAYSFJSEjEajR7drq/XctdddxGxWEzmzJnj7VIoF5g3b16/ncLun7CwsH5f+Pbs4F+6dIlMmDCBzJs3j9x1111k9uzZhBBCDh8+TJ5++ulBa7En2B3ZiR1uR3W4HfdbOdqpGGxnvaWlhWRnZxOxWEz8/PxITk4O+e677/qsy521OdPZ6UaD3fO8dne3y5cvY8WKFYiLi+sZFj5y5AiOHDmCgwcPYvv27d4oi6IoD1q1ahXeeustBAQEALAN3+fn5+P111+HXC7H8uXLB3wen88Hj8fDE088gVdeecWtNRqNRmRkZKCoqMjn5pH4cm0AcPfdd+Ps2bOYOnUqDh8+7O1ybhtsb21427ZtOHfuXJ8PNGA73jZlyhRvlUVRlIdcuHABAoGg5zsAsAW2QqFAcXExFi1aNOhzB5qQ5y5cLnfAOUC+wJdrA4Dvv//e2yXclrwS7M58oCmKGhuysrLw3nvv9fndiRMnAKDfhDuKouzntaF4iqIoiqJcz2tD8Z6UxgiCCian1sHluOZqShyua9bDcsH/HIsz8tMJe2NwXHPWJIPL8ol1AADYLmhgV6wDcM1/NgAr0/n/Jwux7y6CwzG75q0Ho9X5z5Mr1gEARotLVgOjxfl6TEbXfCYtJudrYZtc85/NcVEDZ09LxIEDB1yyLl91WwS7CiZsZjh33D5cxnVJLeGRrlmPf5jzb3JpiNEFlQB8F70mTpTU6XUwI/1dUAnACLPvJjlDCgl2fh0AGNIwl6xHI3D+/0lt7nBBJUCzdvhl7NGgcf413dC4JgSvq1yzg1Df7vzXctNNkQsqAbpu8oZfaBjBN52/jLdtPWqXrKe0fodL1uPL3Ho/doqiKIqiPIsGO0VRFEWNITTYKYqiKGoMocFOURRFUWMIDXaKoiiKGkNosFMURVHUGEKDnaIoiqLGEBrsFEVRFDWG0GCnKIqiqDGEBjtFURRFjSE02CmKoihqDKHBTlEURVFjCA12iqIoihpDaLBTFEVR1BhCg52iKIqixhAa7BRFURQ1htBgpyiKoqgxhAY7RVEURY0hDEII8XYR7paamgqBQODtMnxSa2srQkJCvF2Gz6HtMjjaNgOj7TI4X2qb4OBgHDhwwNtluBXb2wV4gkAgQEFBgbfL8EnZ2dm0bQZA22VwtG0GRttlcLRtPIsOxVMURVHUGEKDnaIoiqLGENbLL7/8sreL8ISsrCxvl+CzaNsMjLbL4GjbDIy2y+Bo23jObTF5jqIoiqJuF3QonqIoiqLGEBrsFEVRFDWGjMlgf+ONN5CdnQ0ej4f169cPuezOnTuRlZUFqVQKuVyOp59+Gmaz2TOFepgj7QIAr732GmQyGfz8/LBhwwYYDAb3F+kl7e3tWLp0KUQiEWJiYrBnz55BlyWE4MUXX0RkZCT8/PyQl5eH0tJSD1brWY60DQBUV1dj0aJFkEgkCA4OxtNPP+2hSj3L0XbpNmfOHDAYjDH7PQM41ja303ewp4zJYI+IiMCLL76IDRs2DLusVqvF66+/jra2Npw7dw6HDx/Gn//8Zw9U6XmOtMvBgwexbds2HD58GLW1taiursbmzZs9UKV3PPbYY+ByuWhubsbu3buxcePGQcP6008/xb/+9S+cPHkS7e3tuOOOO7B27VoPV+w5jrSN0WjE3XffjTlz5qCpqQn19fVYs2aNhyv2DEfapdvu3btvi9BypG1up+9gjyFj2AsvvEDWrVvn0HP+8pe/kEWLFrmnIB9hT7usXr2aPPfccz3/PnToEAkLC3NzZd6hVqsJh8Mh165d6/ndmjVryDPPPDPg8tu2bSP3339/z79LSkoIj8dze53e4GjbvP3222TGjBmeKs9rHG0XQgjp7OwkEyZMIGfOnCEAiMlk8kSpHjeStuntdvgOdrcx2WN3xokTJ5CamurtMryutLQUGRkZPf/OyMhAc3MzFAqFF6tyj/LycrBYLCQkJPT8LiMjY9AexqpVq1BZWYny8nKYTCbs3LkT8+fP91S5HuVo25w9exbjxo3DggULEBwcjLy8PBQXF3uqXI9xtF0A4Pnnn8fGjRshk8k8UaLXjKRteqPfwc67LS4pa6/33nsPBQUF+Oc//+ntUrxOrVbDz8+v59/df1epVAgKCvJWWW5x62sFbK9XpVINuHx4eDhyc3ORmJgIFouFqKgoHDlyxBOlepyjbVNfX4+jR49i3759mDt3Lnbs2IElS5bg6tWr4HK5nijZIxxtl4KCApw+fRo7duxAfX29J0r0Gkfbpjf6Hewao67HnpeXBwaDMeDPjBkzRrzeL774As8++yz279+P4OBgF1bsGa5uF7FYDKVS2fPv7r9LJBKX1ewpw7XNra8VsL3ewV7rH/7wB5w/fx51dXXQ6/XYvHkz5syZA61W64mX41KubhuBQIAZM2ZgwYIF4HK5eOqpp6BQKFBWVuaJl+MyrmwXq9WKTZs2YceOHWCzR39fytXvmW6j/TvYl4y6d9mxY8dcvs4DBw7gl7/8Jb755hukpaW5fFHHHpwAAAZISURBVP2e4Op2SU1NRWFhIVasWAEAKCwsRFhY2KjsrQ/XNhqNBmazGRUVFZgwYQIA2+sdbDiwsLAQK1euhFwuBwCsX78eTz75JK5cuYLs7GyX1u5urm6b9PR0nD592tVlepwr20WpVKKgoAArV64EAFgsFgCAXC7Hp59+itzcXNcW72aufs8AY+M72Kd4+yC/O5hMJqLT6cizzz5L1qxZQ3Q63aATVQ4fPkwCAwPJ8ePHPVyl5znSLvv37ydhYWGktLSUtLe3k9mzZ9s9+WU0WrlyJVm1ahVRq9Xk1KlTRCqVkpKSkgGXffnll8n06dNJU1MTsVgsZNeuXUQoFJKOjg4PV+0ZjrTN1atXiUAgIN9//z0xm83kf/7nf0hcXBwxGAwertr97G0Xq9VKGhsbe37y8/MJAFJfXz8m24UQx94zt9N3sKeMyWDfvHkzAdDnZ/PmzYQQQq5fv05EIhG5fv06IYSQvLw8wmKxiEgk6vmZP3++F6t3H0fahRDb7NTQ0FAikUjI+vXriV6v91Ll7qdQKMiSJUuIUCgkUVFRZPfu3T2P3do2Op2ObNq0ichkMiKRSMikSZPI/v37vVW62znSNoQQsnfvXjJ+/HgikUjIrFmzBv1CH+0cbZduNTU1Y3pWPCGOtc3t9B3sKfRa8RRFURQ1hoy6yXMURVEURQ2OBjtFURRFjSE02CmKoihqDKHBTlEURVFjCA12iqIoihpDaLBTFEVR1BhCg52iKIqixhAa7BRFDeq5557D66+/PujjU6dOtfuuXRRFeQYNdoryUXl5eQgICIDBYBh22XfeeQcpKSkQCoWQy+V46qmnoNPpnNp+a2srdu3ahUceeWTQZZ566im89NJLTm2HoijXosFOUT6otrYWRUVFSE5Oxr59+4ZcduvWrXjttdfw3nvvQaVS4dChQ8jPz8fixYvhzIUl//3vf2PhwoUQCASDLrN48WIcPXoUjY2NI94ORVGuRYOdonzQrl27sHTpUqxfvx47d+4cdLn29nZs2bIFH3/8MXJycsBisZCUlIS9e/ciPz8fX3/99Yhr2L9/P2bNmjXkMnw+H1lZWfjuu+9GvB2KolyLBjtF+aBdu3Zh9erVWL58OY4ePYrm5uYBlzt9+jRkMlm/W12GhIQgJycHR48eHXENxcXFSExMHHa55ORkFBYWjng7FEW5Fg12ivIxp06dgkajwezZsxEYGIg5c+Zgz549Ay6rVqvh5+c34GP+/v7QarU9/y4tLQWLxUJ9fb1ddXR2dkIikQy7nEQiQWdnp13rpCjK/WiwU5SP2blzJ1auXAkWiwUAWL169aDD8XFxcaisrIRer+/3WGlpKeLj43v+vX37dqxduxZlZWX9lrVarf1+FxAQAJVKNWy9KpUK/v7+wy5HUZRn0GCnKB+i0+nwySefYPXq1T2/W7JkCSorKwcc7p46dSrkcjnefffdPr8/cuQIamtrsWrVKgBAUVERwsPDMW/evD7BPnnyZGzcuBEPP/xwv3Wnp6ejvLx82JrLysqQkZFh92ukKMq9aLBTlA/54osvEBgYiIyMDOj1euj1erBYLCxcuBC7du3qtzyDwcDOnTvx8ssv4/PPPwcAFBYWYt26dXj77bchl8sBAK+99hqeeeYZpKSk9AR7W1sbWltbsWXLFvzrX//qt+6FCxfi+PHjQ9ZrMBhw4cIF3H333c6+dIqiXIRBnDkfhqIol5o/fz4OHjw44GNhYWGor68Hm83u+d3WrVuxdetW6PV6WCwWEEIwe/ZsHD9+HEKhELm5uXj11VexYsUKxMXFwWKxwGKx4MiRIzhy5AgOHjyI7du3D7i9trY2ZGZmoqKiYtBT3j799FN8+OGH+Oyzz5x/8RRFuQQNdooa41atWoW33noLAQEBAGzD9/n5+Xj99dchl8uxfPnyQZ/7/PPPIzQ0FE8++eSAj+fk5ODdd9/FxIkT3VI7RVGOYw+/CEVRo9WFCxcgEAh6Qh2wnXuuUChQXFyMRYsWDfn8rVu3Dvn4uXPnXFInRVGuQ3vsFEVRFDWG0MlzFEVRFDWG0GCnKIqiqDGEBjtFURRFjSE02CmKoihqDKHBTlEURVFjCA12iqIoihpDaLBTFEVR1BhCg52iKIqixhAa7BRFURQ1hvx/Xe2fPNa5V9gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1=jplt.plot_world(omega_maxdiff, varname='$\\Delta$ $\\Omega_{Ar}$',  units=' ', cbar_tick_freq=4, lim_l=-1.2, lim_u=-0.1, cbar_delta=0.05,\\\n",
    "                     projection='moll', title='Max. surface $\\Omega_{Ar}$ Reduction', colourmap='Spectral', continents='on',\\\n",
    "                     cont='on',var_cont=omega_min, var_cont_name='$\\Omega_{Ar}^{min}$',cont_levs=[0.75,1,1.25], cont_anno='on', \\\n",
    "                     var_cont_unit=' ', cont_label_fmt='%.2f', linestyle='dashed', cont_labels='on')[1] \n",
    "# cont_levs=[-18,-12,-10,-8, -6]\n",
    "fig1.savefig('./plot_pdf_files/FigS16a_pulse_rev_1500ppm_OMEGA_MaxDecrease.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1=jplt.plot_world(ccd_end-ccd_ini, varname='$\\Delta$ASH',  units='m', lim_l=-1000, lim_u=0, cbar_delta=50, cbar_tick_freq=4,\\\n",
    "                     projection='moll', continents='on', title='Shallowing of the Aragonite Saturation Horizon', colourmap='Oranges_r', var_digits=0, extend='min',\\\n",
    "                     cont='on',var_cont=ccd_end, var_cont_name='ASH$_{\\mathrm{end}}$', cont_levs=[50,200], var_cont_digits=0, var_cont_unit='m', cont_label_fmt='%d', linestyle='dashed')[1] \n",
    "# , lim_l=-1000, lim_u=0, cbar_delta=50, cbar_tick_freq=2,var_cont=ccd_ini\n",
    "fig1.savefig('./plot_pdf_files/FigS16b_pulse_rev_1500ppm_CCD.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1=jplt.plot_world(ph_maxdiff, varname='$\\Delta$ pH',  units=' ', cbar_tick_freq=2, lim_l=-0.36, lim_u=-0.28, cbar_delta=0.005,\\\n",
    "                     projection='moll', title='Max. surface pH Reduction', colourmap='Spectral', continents='on',\\\n",
    "                     cont='on',var_cont=ph_min, var_cont_name='$pH$',cont_levs=[7.2,7.3], cont_anno='on', \\\n",
    "                     var_cont_unit=' ', cont_label_fmt='%.2f', linestyle='dashed', cont_labels='on')[1] \n",
    "# cont_levs=[-18,-12,-10,-8, -6]\n",
    "fig1.savefig('./plot_pdf_files/FigS17_pulse_rev_1500ppm_PH_MaxDecrease.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. 4: Coral reef susceptibility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "!use \"../climber/pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka/all_snapshots_mom_annual.nc\"\n",
    "use \"../climber/pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka/all_snapshots_mom_annual.nc\"\n",
    "\n",
    "let a=temp[i=@ave,j=@ave,k=1,l=@sbx:10,d=1]\n",
    "let b=a[l=@min]-a\n",
    "!list b[l=@loc:0] !year 1239\n",
    "let nep_cold_f=proyear[l=119:129@ave,d=1]/360*12 \n",
    "! /360*12 to get per day\n",
    "let sst_cold_f=temp[k=1,l=119:129@ave,d=1]\n",
    "let sss_cold_f=salt[k=1,l=119:129@ave,d=1]\n",
    "let nep_warm_f=proyear[l=500,d=1]/360*12\n",
    "let sst_warm_f=temp[k=1,l=500,d=1]\n",
    "let sss_warm_f=salt[k=1,l=500,d=1]\n",
    "let nep_ini_f=proyear[l=1,d=1]/360*12\n",
    "let sst_ini_f=temp[k=1,l=1,d=1]\n",
    "let sss_ini_f=salt[k=1,l=1,d=1]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: nep_cold_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sst_cold_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sss_cold_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: nep_warm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sst_warm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sss_warm_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: nep_ini_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sst_ini_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sss_ini_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata nep_cold_f=nep_cold_f\n",
    "%ferret_getdata sst_cold_f=sst_cold_f\n",
    "%ferret_getdata sss_cold_f=sss_cold_f\n",
    "#%ferret_getdata omegaplo_a_f=omegaplo_a_f\n",
    "%ferret_getdata nep_warm_f=nep_warm_f\n",
    "%ferret_getdata sst_warm_f=sst_warm_f\n",
    "%ferret_getdata sss_warm_f=sss_warm_f\n",
    "%ferret_getdata nep_ini_f=nep_ini_f\n",
    "%ferret_getdata sst_ini_f=sst_ini_f\n",
    "%ferret_getdata sss_ini_f=sss_ini_f\n",
    "\n",
    "nep_cold=np.ma.masked_values(np.rot90(nep_cold_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "sst_cold=np.ma.masked_values(np.rot90(sst_cold_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "sss_cold=np.ma.masked_values(np.rot90(sss_cold_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "#omegaplo_a=np.ma.masked_values(np.rot90(omegaplo_a_f['data'][:,:,0,0,0,0]), -1e34)\n",
    "nep_warm=np.ma.masked_values(np.rot90(nep_warm_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "sst_warm=np.ma.masked_values(np.rot90(sst_warm_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "sss_warm=np.ma.masked_values(np.rot90(sss_warm_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "nep_ini=np.ma.masked_values(np.rot90(nep_ini_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "sst_ini=np.ma.masked_values(np.rot90(sst_ini_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "sss_ini=np.ma.masked_values(np.rot90(sss_ini_f['data'][:,:,0,0,0,0]), -1e34);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "# Get Coral locations\n",
    "# Download Scleractinia occurences from fossilworks (when downloaded directly from PBDB, plate reconstruction a little different)\n",
    "def read_pdbd_csv(csv_file):\n",
    "    with open(csv_file) as csvfile: #'pbdb_data_Scleractinia.csv' 'pbdb_data_Scleractinia_220_180Ma.csv'\n",
    "         next(csvfile,None) #skip header\n",
    "         spamreader = csv.reader(csvfile, delimiter=',')\n",
    "         lon_col= []   \n",
    "         lat_col= []\n",
    "         row_prev=[0]\n",
    "         for row in spamreader: #include each collection only once\n",
    "             if row[0]!=row_prev[0]:    \n",
    "                lon_col.append(row[9]) #33 18\n",
    "                lat_col.append(row[8]) #34 19\n",
    "             row_prev=row\n",
    "         lon_paleo=np.array(list(filter(None, lon_col[0:])),dtype=float) #19\n",
    "         lat_paleo=np.array(list(filter(None, lat_col[0:])),dtype=float) #19\n",
    "         lonlat_paleo=np.transpose(np.array([lon_paleo,lat_paleo]))\n",
    "    return lonlat_paleo\n",
    "\n",
    "lonlat_paleo_norian=read_pdbd_csv('../coral_data/fossilworks_scleractinia_Norian_reef.csv')\n",
    "lonlat_paleo_rhaetian=read_pdbd_csv('../coral_data/fossilworks_scleractinia_Rhaetian_reef.csv')\n",
    "lonlat_paleo=np.append(lonlat_paleo_norian, lonlat_paleo_rhaetian,axis=0)\n",
    "\n",
    "def filter_reef_loc(locs): #filter out locations which are very close to each other to avoid overwight of well-sampled regions\n",
    "    locs_filt=np.zeros((2,2))\n",
    "    for a in locs:\n",
    "        #dist=r*np.arccos(np.sin(lat_c*np.pi/180)*np.sin(latos_2d*np.pi/180)+np.cos(lat_c*np.pi/180)*np.cos(latos_2d*np.pi/180)*np.cos((lon_c-lonos_2d)*np.pi/180)) \n",
    "        dist_min=np.min(6371*np.arccos(np.sin(a[1]*np.pi/180)*np.sin(locs_filt[:,1]*np.pi/180)+np.cos(a[1]*np.pi/180)*np.cos(locs_filt[:,1]*np.pi/180)*np.cos((a[0]-locs_filt[:,0])*np.pi/180))) \n",
    "        #condi=(np.min(abs(a[0]-locs_filt[:,0]))>0.2) & (np.min(abs(a[1]-locs_filt[:,1]))>0.2)\n",
    "        if dist_min>250:\n",
    "            locs_filt=np.vstack((locs_filt,a)) #,axis=1\n",
    "    locs_filt=locs_filt[2:,:]\n",
    "    return locs_filt\n",
    "\n",
    "lonlat_paleo_norian_sel=filter_reef_loc(lonlat_paleo_norian)\n",
    "lonlat_paleo_rhaetian_sel=filter_reef_loc(lonlat_paleo_rhaetian)\n",
    "lonlat_paleo_sel=np.append(lonlat_paleo_norian_sel, lonlat_paleo_rhaetian_sel,axis=0)\n",
    "\n",
    "a=np.copy(lonlat_paleo_norian_sel)\n",
    "b=np.copy(lonlat_paleo_rhaetian_sel)\n",
    "\n",
    "lonlat_paleo_norian_sel_tethys=a[(a[:,1]>=-40) & (a[:,1]<=40) & (a[:,0]>=0) & (a[:,0]<=150)]\n",
    "lonlat_paleo_rhaetian_sel_tethys=b[(b[:,1]>=-40) & (b[:,1]<=40) & (b[:,0]>=0) & (b[:,0]<=150)]\n",
    "lonlat_paleo_sel_tethys=np.append(lonlat_paleo_norian_sel_tethys, lonlat_paleo_rhaetian_sel_tethys,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "code_folding": [
     0
    ]
   },
   "outputs": [],
   "source": [
    "# Coral Susceptibility Functions\n",
    "def sst_sens(sst):\n",
    "    sst_mean=27\n",
    "    sst_sigma=4.5\n",
    "    sst_sensi_rudists=1./(1+np.exp(-1*(sst-18)))\n",
    "    sst_sensi_corals=1./(np.sqrt(2*np.pi*sst_sigma**2))*np.exp(-1*((sst-sst_mean)**2)/(2*sst_sigma**2))\n",
    "    sst_sensi_corals_norm=sst_sensi_corals/np.max(sst_sensi_corals)\n",
    "    \n",
    "    skewness=-6.5 #-2.5 #-2.5\n",
    "    sst_mean_skew=30. #30.5 #29.5\n",
    "    sst_sigma_skew=6 #5 #5.5  \n",
    "    #mean, var, skew, kurt = skewnorm.stats(skewness, loc=sst_mean, scale=sst_sigma, moments='mvsk')    \n",
    "    sst_sensi_corals_skewed = skewnorm.pdf(sst, skewness, loc=sst_mean_skew, scale=sst_sigma_skew) \n",
    "    \n",
    "    dummy_ssts=np.arange(-2,40,0.01)\n",
    "    dummy_sst_sensi_corals_skewed = skewnorm.pdf(dummy_ssts, skewness, loc=sst_mean_skew, scale=sst_sigma_skew)\n",
    "    \n",
    "    sst_sensi_corals_skewed_norm=sst_sensi_corals_skewed/np.max(dummy_sst_sensi_corals_skewed)\n",
    "    \n",
    "    \n",
    "    return sst_sensi_corals_norm, sst_sensi_rudists, sst_sensi_corals_skewed_norm\n",
    "\n",
    "def sss_sens(sss):\n",
    "    sss_sigma=4.3\n",
    "    sss_sensi=1./(np.sqrt(2*np.pi*sss_sigma**2))*np.exp(-1*((sss-35.25)**2)/(2*sss_sigma**2)) \n",
    "    sss_sensi_norm=sss_sensi/np.max(sss_sensi)\n",
    "    return sss_sensi_norm\n",
    "\n",
    "def npp_sens(npp):\n",
    "    npp_sigma=0.22 #0.175\n",
    "    npp_mean=0.125\n",
    "    npp_sensi=1./(np.sqrt(2*np.pi*npp_sigma**2))*np.exp(-1*((npp-npp_mean)**2)/(2*npp_sigma**2))\n",
    "    npp_sensi_norm=npp_sensi/np.max(npp_sensi)\n",
    "    \n",
    "    lower, upper = 0., 1000.\n",
    "    a=(lower-npp_mean)/npp_sigma\n",
    "    b=(upper-npp_mean)/npp_sigma \n",
    "    pdf_trunc=truncnorm.pdf(npp, a, b, loc=npp_mean, scale=npp_sigma)\n",
    "    npp_sensi_trunc_norm=pdf_trunc/np.max(pdf_trunc)\n",
    "    return npp_sensi_norm, npp_sensi_trunc_norm\n",
    "\n",
    "ssts=np.arange(-2,40,0.1)\n",
    "ssts_sens, ssts_sens_rudists, ssts_sens_skewed=sst_sens(ssts)[:]\n",
    "\n",
    "ssss=np.arange(30,40,0.01)\n",
    "ssss_sens=sss_sens(ssss)\n",
    "\n",
    "npps=np.linspace(0,0.5,100)\n",
    "npps_sens, npps_sens_trunc=npp_sens(npps)\n",
    "\n",
    "# fig=plt.figure(figsize=(13,5))\n",
    "# plt.clf()\n",
    "# ax1 = fig.add_subplot(131)\n",
    "# ax2 = fig.add_subplot(132)\n",
    "# ax3 = fig.add_subplot(133)\n",
    "# ax1.hist(sst_coralloc[sst_coralloc>5], bins=50, density=True)\n",
    "# ax1.plot(ssts,ssts_sens)\n",
    "# ax1.plot(ssts,ssts_sens_rudists)\n",
    "# ax1.plot(ssts,ssts_sens_skewed)\n",
    "# ax1.plot(ssts,0.4*ssts_sens_skewed,)\n",
    "# ax2.plot(ssss,ssss_sens)\n",
    "# ax3.plot(npps,npps_sens)\n",
    "# ax3.plot(npps,npps_sens_trunc)\n",
    "# plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "#nep_npp_ratio=0.4756*nep**(-0.307/(1+0.307))\n",
    "npp_cold=1./0.04756*nep_cold**(1./(1+0.307)) #following Laws 2011\n",
    "npp_warm=1./0.04756*nep_warm**(1./(1+0.307))\n",
    "npp_ini=1./0.04756*nep_ini**(1./(1+0.307))\n",
    "\n",
    "a=1 #0.66\n",
    "b=0 #0.062\n",
    "c=0 #0.278\n",
    "coral_suscept_cold=a*sst_sens(sst_cold)[2]+b*sss_sens(sss_cold)+c*npp_sens(npp_cold)[1]\n",
    "coral_suscept_warm=a*sst_sens(sst_warm)[2]+b*sss_sens(sss_warm)+c*npp_sens(npp_warm)[1]\n",
    "coral_suscept_ini=a*sst_sens(sst_ini)[2]+b*sss_sens(sss_ini)+c*npp_sens(npp_ini)[1]\n",
    "\n",
    "kmt_225Ma=np.loadtxt('../climber/depth_adj_225Ma.dat', dtype=int)[:,:]\n",
    "kmt_225Ma[kmt_225Ma>0]=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "csv_file='../coral_data/ReefLocations_Kopie.csv' #from reefbase.org \n",
    "with open(csv_file) as csvfile: #'pbdb_data_Scleractinia.csv' 'pbdb_data_Scleractinia_220_180Ma.csv'\n",
    "     next(csvfile,None) #skip header\n",
    "     spamreader = csv.reader(csvfile, delimiter=',')\n",
    "     lon_col_reef= []   \n",
    "     lat_col_reef= []\n",
    "     #row_prev=[0]\n",
    "     for row in spamreader: #include each collection only once\n",
    "         #if row[0]!=row_prev[0]:    \n",
    "        lon_col_reef.append(row[6]) #33 18\n",
    "        lat_col_reef.append(row[5]) #34 19\n",
    "         #row_prev=row\n",
    "lon_reef=np.array(list(filter(None, lon_col_reef[0:])),dtype=float) #19\n",
    "lat_reef=np.array(list(filter(None, lat_col_reef[0:])),dtype=float) #19\n",
    "lonlat_reef=np.transpose(np.array([lon_reef,lat_reef]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "lon_reef_round=np.around(lon_reef)\n",
    "lon_reef_round[lon_reef_round>=0]=lon_reef_round[lon_reef_round>=0]-0.5\n",
    "lon_reef_round[lon_reef_round<0]=lon_reef_round[lon_reef_round<0]+0.5\n",
    "#lon_reef_round[lon_reef_round!=0]=lon_reef_round-lon_reef_round/abs(lon_reef_round)*0.5\n",
    "lat_reef_round=np.around(lat_reef)\n",
    "lat_reef_round[lat_reef_round>=0]=lat_reef_round[lat_reef_round>=0]-0.5\n",
    "lat_reef_round[lat_reef_round<0]=lat_reef_round[lat_reef_round<0]+0.5\n",
    "#lat_reef_round[:]=lat_reef_round-lat_reef_round/abs(lat_reef_round)*0.5\n",
    "lonlat_reef_round=np.transpose(np.array([lon_reef_round,lat_reef_round]))\n",
    "lonlat_reef_uniq=np.unique(lonlat_reef_round, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%ferret\n",
    "cancel data/all\n",
    "CANCEL MODE LOGO\n",
    "use \"../coral_data/woa18_decav_t00_01.nc\"\n",
    "!sh da\n",
    "!show axis depth\n",
    "!shade t_an[k=1]\n",
    "!let sst_an_f=t_an[k=1]\n",
    "let sst_an_f=t_an[z=0:25@ave]\n",
    "!plot t_an[k=1]\n",
    "!plot/over t_an[z=0:25@ave]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: sst_an_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%ferret_getdata sst_an_f=sst_an_f\n",
    "sst_an_f\n",
    "nooa_mask=(np.rot90(sst_an_f['data'][:,:,0,0,0,0])==-1e34)\n",
    "sst_an=np.ma.masked_values(np.rot90(sst_an_f['data'][:,:,0,0,0,0]), -1e34);\n",
    "lon_nooa=sst_an_f['axis_coords'][0]\n",
    "lat_nooa=sst_an_f['axis_coords'][1]\n",
    "lat_nooa=lat_nooa[::-1]\n",
    "lon_nooa_2d,lat_nooa_2d=np.meshgrid(lon_nooa,lat_nooa)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/janlandw/.conda/envs/py3_jan/lib/python3.7/site-packages/ipykernel_launcher.py:18: RuntimeWarning: invalid value encountered in arccos\n"
     ]
    }
   ],
   "source": [
    "sst_coralloc=[]\n",
    "sst_coralloc_lon=[]\n",
    "sst_coralloc_lat=[]\n",
    "coral_suscept_coralloc=[]\n",
    "r=6371\n",
    "\n",
    "for i in range(len(lonlat_reef_uniq[:,0])):\n",
    "            lon_r=lonlat_reef_uniq[i,0]\n",
    "            lat_r=lonlat_reef_uniq[i,1] \n",
    "            sst_an_loc=sst_an[((lat_nooa_2d==lat_r) & (lon_nooa_2d==lon_r))]\n",
    "            sst_loc=sst_an_loc.data\n",
    "            sst_loc_mask=sst_an_loc.mask\n",
    "            #sst_loc=sst_an[((lat_nooa_2d==lat_r) & (lon_nooa==lon_r))].data\n",
    "            #if sst_loc.size>0 and sst_loc<100 and sst_loc>-100:\n",
    "            if sst_loc.size>0:\n",
    "                if sst_loc_mask==True:\n",
    "                    #lon_c, lat_c=lonlat_paleo_sel[i,0:1+1]\n",
    "                    dist=r*np.arccos(np.sin(lat_r*np.pi/180)*np.sin(lat_nooa_2d*np.pi/180)+np.cos(lat_r*np.pi/180)*np.cos(lat_nooa_2d*np.pi/180)*np.cos((lon_r-lon_nooa_2d)*np.pi/180)) #calculate distance to ocean cells, https://en.wikipedia.org/wiki/Great-circle_distance\n",
    "                    dist_masked=np.ma.MaskedArray(dist, mask=nooa_mask)\n",
    "                    #dist_min=np.ma.min(dist_p1_masked)\n",
    "                    dist_min_idx=np.unravel_index(np.ma.argmin(dist_masked, axis=None), dist_masked.shape)\n",
    "                    sst_coral_closest=sst_an[dist_min_idx] #corals_suscept at closest ocean cell\n",
    "                    sst_loc=sst_coral_closest\n",
    "                coral_suscept_coralloc=np.append(coral_suscept_coralloc,sst_sens(sst_loc)[2])\n",
    "                sst_coralloc=np.append(sst_coralloc,sst_loc) \n",
    "                sst_coralloc_lon=np.append(sst_coralloc_lon,lon_r)\n",
    "                sst_coralloc_lat=np.append(sst_coralloc_lat,lat_r)\n",
    "\n",
    "sst_coralloc_lonlat=np.transpose(np.array([sst_coralloc_lon,sst_coralloc_lat]))\n",
    "with open('coral_SSTatCoralLocs_modern.pickle', 'wb') as f:  \n",
    "    pickle.dump(sst_coralloc, f)\n",
    "#sst_coralloc_lonlat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1=jplt.plot_world(sst_an, varname='SST', lim_l=-2, lim_u=32, cbar_delta=1, cbar_tick_freq=2, units=' ',\\\n",
    "                     projection='moll', title='Modern ann. mean SST (WorldOceanAtlas 2018)', axes='on',\\\n",
    "                     cont='off', var_cont_name='pH', cont_anno='off', var_cont_unit=' ', cont_levs=[0.4], cont_labels='off', linestyle='dashed',\\\n",
    "                    scat='on', var_scat=sst_coralloc_lonlat, scat_colored='on', scat_colors=sst_coralloc)[1] #, lim_l=0, lim_u=32 , var_cont=np.ma.masked_array(kmt_225Ma) , var_scat=lonlat_paleo_norian_sel , var_scat2=lonlat_paleo_rhaetian_sel , continents='off'\n",
    "#fig1.savefig('./PlotsForPaper/equi_1500ppm_CoralReefSusceptibility.pdf',bbox_inches='tight', pad_inches=0.01, dpi=900) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_sst_atproxyloc(sst): #calculate average of the susceptibility in ocean cells closest to the proxy locations\n",
    "    latos, lonos, lonos_2d, latos_2d=jan.grid_gen(region='ocean', cell='T')\n",
    "    r=6371\n",
    "    with open('../climber/continental_mask.pickle', 'rb') as f:  \n",
    "        continental_mask = pickle.load(f, encoding='latin1' ) #Python3: , encoding='latin1' \n",
    "\n",
    "    sst_atproxyloc=np.zeros(lonlat_paleo.shape[0])\n",
    "    #coral_suscept_atproxyloc_tethys=np.zeros(lonlat_paleo_sel_tethys.shape[0])\n",
    "    for i in range(lonlat_paleo.shape[0]):\n",
    "        lon_c, lat_c=lonlat_paleo[i,0:1+1]\n",
    "        dist=r*np.arccos(np.sin(lat_c*np.pi/180)*np.sin(latos_2d*np.pi/180)+np.cos(lat_c*np.pi/180)*np.cos(latos_2d*np.pi/180)*np.cos((lon_c-lonos_2d)*np.pi/180)) #calculate distance to ocean cells, https://en.wikipedia.org/wiki/Great-circle_distance\n",
    "        dist_masked=np.ma.MaskedArray(dist, mask=1-continental_mask)\n",
    "        #dist_min=np.ma.min(dist_p1_masked)\n",
    "        dist_min_idx=np.unravel_index(np.ma.argmin(dist_masked, axis=None), dist_masked.shape)\n",
    "        sst_atproxyloc[i]=sst[dist_min_idx] #corals_suscept at closest ocean cell\n",
    "               \n",
    "    #condi_tethys=(lonlat_paleo_sel[:,1]>=-40) & (lonlat_paleo_sel[:,1]<=40) & (lonlat_paleo_sel[:,0]>=0) & (lonlat_paleo_sel[:,0]<=120)    \n",
    "    \n",
    "    #coral_suscept_score=np.mean(coral_suscept_atproxyloc)\n",
    "    #coral_suscept_score_tethys=np.mean(coral_suscept_atproxyloc[condi_tethys])\n",
    "    \n",
    "    return sst_atproxyloc #coral_suscept_score, coral_suscept_atproxyloc, coral_suscept_score_tethys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "with open('coral_SSTatCoralLocs_modern.pickle', 'rb') as f:  \n",
    "    sst_coralloc=pickle.load(f, encoding='latin1')\n",
    "\n",
    "sst_ini_atproxyloc=calc_sst_atproxyloc(sst_ini)\n",
    "sst_warm_atproxyloc=calc_sst_atproxyloc(sst_warm)\n",
    "sst_cold_atproxyloc=calc_sst_atproxyloc(sst_cold)    \n",
    "    \n",
    "fig=plt.figure(figsize=(6,4.5))\n",
    "plt.clf()\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax1.hist(sst_coralloc[sst_coralloc>5], bins=50, density=True, color='slategrey', label='modern coral reef occurrences')\n",
    "ax1.plot(ssts,ssts_sens_skewed*0.5,'-k', lw=2, label='coral reef susceptibility function')\n",
    "ax1.axvline(x=ssts[np.argmax(ssts_sens_skewed)], c='k', ls=':')\n",
    "ax1.set_yticks([0,0.25,0.5])\n",
    "ax1.set_yticklabels(['0','0.5','1.0'])\n",
    "#ticks = ax1.get_yticks()*2\n",
    "#ax1.set_yticklabels(np.round(ticks,1))\n",
    "xlim_l=-2.\n",
    "xlim_u=40.\n",
    "ax1.set_xlim(xlim_l,xlim_u)\n",
    "ax1.set_ylim(-0.175,0.55)\n",
    "ax1.set_xlabel('SST ($\\mathsf{^{\\circ}C}$)', fontsize=12)\n",
    "ax1.set_ylabel('Coral Reef Susceptibility (a.u.)', fontsize=12)\n",
    "\n",
    "\n",
    "ax1.plot((np.min(sst_ini),np.max(sst_ini)),(-0.1,-0.1),'-',c='tab:green', lw=3, solid_capstyle='round', label='initial state', zorder=11)\n",
    "hist, bins_ = np.histogram(sst_ini_atproxyloc,bins=50) #, density=True\n",
    "freq = 0.5*hist/np.sum(hist)\n",
    "ax1.bar(bins_[:-1], freq, align=\"edge\", width=np.diff(bins_), color='tab:green', bottom=-0.1, zorder=11)\n",
    "#v_ini=ax1.violinplot(sst_ini_atproxyloc, positions=[-0.07], showmeans=False, showmedians=False, showextrema=False, vert=False, widths=0.03)\n",
    "#for pc in v_ini['bodies']:\n",
    "#    pc.set_facecolor('tab:green')\n",
    "#    pc.set_edgecolor('tab:green')\n",
    "#    pc.set_alpha(1)\n",
    "#ax1.plot((np.min(sst_ini_atproxyloc),np.max(sst_ini_atproxyloc)),(-0.07,-0.07),'-',c='tab:green', lw=5, solid_capstyle='round')\n",
    "\n",
    "ax1.plot((np.min(sst_cold),np.max(sst_cold)),(-0.15,-0.15),'-',c='tab:blue', lw=3, solid_capstyle='round', label='cold state')\n",
    "hist, bins_ = np.histogram(sst_cold_atproxyloc,bins=50) #, density=True\n",
    "freq = 0.5*hist/np.sum(hist)\n",
    "ax1.bar(bins_[:-1], freq, align=\"edge\", width=np.diff(bins_), color='tab:blue', bottom=-0.15)\n",
    "#v_cold=ax1.violinplot(sst_cold_atproxyloc, positions=[-0.11], showmeans=False, showmedians=False, showextrema=False, vert=False, widths=0.03)\n",
    "#for pc in v_cold['bodies']:\n",
    "#    pc.set_facecolor('tab:blue')\n",
    "#    pc.set_edgecolor('tab:blue')\n",
    "#    pc.set_alpha(1)\n",
    "#ax1.plot((np.min(sst_cold_atproxyloc),np.max(sst_cold_atproxyloc)),(-0.11,-0.11),'-',c='tab:blue', lw=5, solid_capstyle='round')\n",
    "\n",
    "ax1.plot((np.min(sst_warm),np.max(sst_warm)),(-0.05,-0.05),'-',c='darkorange', lw=3, solid_capstyle='round', label='warm state')\n",
    "#ax1.hist(sst_warm_atproxyloc,bins=100, color='tab:red', density=True, histtype='stepfilled', bottom=-0.03)\n",
    "hist, bins_ = np.histogram(sst_warm_atproxyloc,bins=50) #, density=True\n",
    "freq = 0.5*hist/np.sum(hist)\n",
    "ax1.bar(bins_[:-1], freq, align=\"edge\", width=np.diff(bins_), color='darkorange', bottom=-0.05)\n",
    "#v_warm=ax1.violinplot(sst_warm_atproxyloc, positions=[-0.03], showmeans=False, showmedians=False, showextrema=False, vert=False, widths=0.03)\n",
    "#for pc in v_warm['bodies']:\n",
    "#    pc.set_facecolor('tab:red')\n",
    "#    pc.set_edgecolor('tab:red')\n",
    "#    pc.set_alpha(1)\n",
    "#ax1.plot((np.min(sst_warm_atproxyloc),np.max(sst_warm_atproxyloc)),(-0.03,-0.03),'-',c='tab:red', lw=5, solid_capstyle='round')\n",
    "\n",
    "handles, labels = ax1.get_legend_handles_labels()\n",
    "order = [4,0,1,2,3]\n",
    "ax1.legend([handles[idx] for idx in order],[labels[idx] for idx in order],frameon=False)\n",
    "#ax1.legend(frameon=False)\n",
    "#ax1.axhline(y=-0.05, xmin=np.min(sst_ini)/(xlim_u-xlim_l), xmax=np.max(sst_ini))\n",
    "\n",
    "ax1.tick_params(labelsize=12)\n",
    "plt.tight_layout()\n",
    "fig.savefig('./plot_pdf_files/Fig4_coral_susceptibility_function_rev.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. 3: Pulse Synthesis Plot "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x540 with 14 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "var_scat=lonlat_paleo_norian_sel\n",
    "var_scat2=lonlat_paleo_rhaetian_sel\n",
    "with open('../climber/continental_mask.pickle', 'rb') as f:  \n",
    "    continental_mask = pickle.load(f, encoding='latin1') #Python3: , encoding='latin1'\n",
    "\n",
    "fig=plt.figure(figsize=(11,7.5))\n",
    "plt.clf()\n",
    "gs = GridSpec(5, 5,height_ratios=[1,0.1,1,1,0.1], width_ratios=[0.3,0.3,1,0.15,1])\n",
    "ax1 = plt.subplot(gs[:-1,0]) #, ymargin=5\n",
    "ax11 = plt.subplot(gs[:-1,1]) #sharey=ax1\n",
    "\n",
    "#ax112 = ax11.twiny()\n",
    "\n",
    "ax21 = plt.subplot(gs[3,2])\n",
    "ax22 = plt.subplot(gs[2,2])\n",
    "ax23 = plt.subplot(gs[0,2])\n",
    "\n",
    "ax24 = plt.subplot(gs[1,2]) #; ax24.axis('off')\n",
    "ax25 = plt.subplot(gs[4,2])\n",
    "\n",
    "ax31 = plt.subplot(gs[3,4])\n",
    "ax32 = plt.subplot(gs[2,4])\n",
    "ax33 = plt.subplot(gs[0,4])\n",
    "\n",
    "ax34 = plt.subplot(gs[1,4])\n",
    "ax35 = plt.subplot(gs[4,4])\n",
    "\n",
    "ax_text = plt.subplot(gs[:,3]); ax_text.axis('off')\n",
    "#ax_text1 = plt.subplot(gs[0,2]); ax_text1.axis('off')\n",
    "#ax_text2 = plt.subplot(gs[2,2]); ax_text2.axis('off')\n",
    "#ax_text3 = plt.subplot(gs[3,2]); ax_text3.axis('off')\n",
    "#ax21.grid(linestyle=':', zorder=0)\n",
    "\n",
    "lim_l=-10.\n",
    "lim_u=6.\n",
    "mycmap = jplt.shiftedColorMap(matplotlib.cm.RdBu_r, midpoint=abs(lim_l)/(lim_u+abs(lim_l)))\n",
    "#mycmap = jplt.shiftedColorMap(matplotlib.cm.RdBu_r, stop=(abs(lim_l)+lim_u)/(2.*abs(lim_l)))\n",
    "\n",
    "times=np.arange(0,5000,1)  \n",
    "ax1.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka[0:3000],times[0:3000],'-', c='tab:green', lw=2) \n",
    "#ax1.scatter(ts_ann_pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka[0:2800],times[0:2800], c=ts_ann_pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka[0:2800], marker='.', cmap=mycmap, alpha=0.2, zorder=3)\n",
    "ax1.plot(ts_ann_pulse_control_1500ppm[0:3000],times[0:3000], '--', c='tab:grey', zorder=1)\n",
    "#ax1.set_aspect(0.04)\n",
    "#ax1.set_ymargin(0.1)\n",
    "#ax1.axis('off')\n",
    "ax1.spines['right'].set_visible(False)\n",
    "#ax1.spines['left'].set_visible(False)\n",
    "ax1.spines['top'].set_visible(False)\n",
    "#ax1.axes.get_yaxis().set_visible(False)\n",
    "ax1.set_xlim([5,25])\n",
    "ax1.set_ylim([-100,3050])\n",
    "ax1.set_xticks([5,10,15,20,25])\n",
    "for tick in ax1.get_yticklabels():\n",
    "    tick.set_rotation(45)\n",
    "ax1.set_xlabel(r'T ($\\mathsf{^{\\circ}C}$)', fontsize=11)\n",
    "ax1.set_ylabel(r'Time (years)', fontsize=11)\n",
    "\n",
    "ax11.plot(eta_steric[0:3000],times[0:3000], '-', c='k', zorder=4, lw=2)\n",
    "ax11.plot(eta_steric_control_1500ppm[0:3000],times[0:3000], '--', c='tab:grey', zorder=1)\n",
    "#ax11.set_aspect(0.04*((1.5-(-1.5))/(25-5)))\n",
    "\n",
    "ax11.spines['right'].set_visible(False)\n",
    "ax11.spines['left'].set_visible(False)\n",
    "ax11.spines['top'].set_visible(False)\n",
    "ax11.axes.get_yaxis().set_visible(False)\n",
    "ax11.set_xlim([-1.5,1.5])\n",
    "ax11.set_ylim([-100,3050])\n",
    "ax11.set_xticks([-1.5,0,1.5])\n",
    "ax11.set_xticklabels(['$-1.5$','$0$','$+1.5$'])\n",
    "ax11.set_xlabel('Steric Sea Level \\n Change (m)', fontsize=11)\n",
    "ax11.xaxis.label.set_color('k')\n",
    "\n",
    "ax11.set_zorder(10)\n",
    "ax11.patch.set_visible(False)\n",
    "ax112 = ax11.twiny()\n",
    "\n",
    "ax112.plot(glb_over[0:3000],times[0:3000], '-', c='tab:blue', zorder=3, lw=2) #c='teal'\n",
    "ax112.plot(glb_over_c[0:3000],times[0:3000], '-.', c='tab:blue', zorder=3, lw=2)\n",
    "#ax112.set_aspect(0.04*((1.5-(-1.5))/(25-5))*(6-1/(25-5)), adjustable='box-forced')\n",
    "ax112.spines['right'].set_visible(False)\n",
    "ax112.spines['left'].set_visible(False)\n",
    "ax112.spines['bottom'].set_visible(False)\n",
    "ax112.axes.get_yaxis().set_visible(False)\n",
    "ax112.set_xlim([12,40])\n",
    "ax112.set_xticks([20,30,40])\n",
    "#ax112.set_xlim([1,6])\n",
    "#ax112.set_xticks([1,2,3,4,5,6])\n",
    "ax112.set_ylim([-100,3050])\n",
    "#ax112.set_xticklabels(['$-1.5$','$0$','$+1.5$'])\n",
    "ax112.set_xlabel('Overturning (Sv)', fontsize=11) #Average Meridional #,fontweight='bold'\n",
    "ax112.xaxis.label.set_color('tab:blue')\n",
    "\n",
    "latso, lonso, xo, yo=jan.grid_gen(region='ocean', cell='T')\n",
    "\n",
    "xpa, ypa=jan.grid_gen(region='atmo', cell='p')[2:4]\n",
    "xua,yua=jan.grid_gen(region='atmo', cell='u')[2:4]\n",
    "xta,yta=jan.grid_gen(region='atmo', cell='T')[2:4]\n",
    "\n",
    "xpo, ypo=jan.grid_gen(region='ocean', cell='p')[2:4] \n",
    "xuo,yuo=jan.grid_gen(region='ocean', cell='u')[2:4]\n",
    "xto,yto=jan.grid_gen(region='ocean', cell='T')[2:4]           \n",
    "\n",
    "xtac,ytac=jan.grid_gen(region='atmo', cell='T')[2:4]\n",
    "xtoc,ytoc=jan.grid_gen(region='ocean', cell='T')[2:4]\n",
    "\n",
    "x_1deg, y_1deg=jan.grid_gen(region='atmo_1deg', cell='p')[2:4] \n",
    "xu_1deg,yu_1deg=jan.grid_gen(region='atmo_1deg', cell='u')[2:4]\n",
    "xt_1deg,yt_1deg=jan.grid_gen(region='atmo_1deg', cell='T')[2:4]\n",
    "\n",
    "for axi in [ax21, ax22, ax23, ax31, ax32, ax33]:\n",
    "    m = Basemap(projection='moll', llcrnrlat=-90, urcrnrlat=90,llcrnrlon=-180, urcrnrlon=180, resolution='c', lon_0=0, ax=axi)\n",
    "    m.drawmapboundary()  \n",
    "    m.drawparallels(np.arange(-90.,120.,30.), linewidth=0.5)\n",
    "    m.drawmeridians(np.arange(0.,420.,60.), linewidth=0.5)\n",
    "\n",
    "xpam, ypam = m(xpa, ypa)\n",
    "xom, yom = m(xo, yo)\n",
    "xpom, ypom = m(xpo, ypo)\n",
    "\n",
    "#xtm,ytm=m(xt,yt)   \n",
    "#xtcm,ytcm=m(xtc,ytc)\n",
    "\n",
    "x_scat, y_scat=m(var_scat[:,0],var_scat[:,1])\n",
    "x_scat2, y_scat2=m(var_scat2[:,0],var_scat2[:,1])\n",
    "\n",
    "a21=ax21.pcolor(xpam, ypam, ts_ini_1500ppm, cmap='Spectral_r',vmin=-15, vmax=35)\n",
    "ax21.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75, colors='k')\n",
    "cbar=fig.colorbar(mappable=a21, cax=ax25, orientation='horizontal', boundaries=np.arange(-15,35+2.5,2.5), ticks=np.arange(-15,35+2.5,5)) #, boundaries=np.arange(-11,6+1,1) drawedges=True, #cbar.dividers.set_color('white')  , pad=-0.5 ax=[ax21, ax22, ax23, ax24], c\n",
    "#cbar.ax.set_xticklabels(['$-10$','$-8$','$-6$','$-4$','$-2$','$0$','$+2$', '$+4$', '$+6$'])\n",
    "cbar.set_label(r'Annual Mean Surface Air Temperature T($\\mathsf{^{\\circ}C}$)', labelpad=-45, fontsize=11)\n",
    "cbar.ax.tick_params(labelsize=10);\n",
    "\n",
    "\n",
    "a22=ax22.pcolor(xpam, ypam, ts_diff_maxcool, cmap=mycmap, vmin=lim_l, vmax=lim_u) # , cmap=mycmap\n",
    "ax22.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75, colors='k')\n",
    "\n",
    "a23=ax23.pcolor(xpam, ypam, ts_diff_maxwarm, cmap=mycmap, vmin=lim_l, vmax=lim_u) #, vmin=1.5, vmax=6\n",
    "ax23.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75, colors='k')\n",
    "cbar=fig.colorbar(mappable=a23, cax=ax24, orientation='horizontal', extend='min', boundaries=np.arange(-11,6+1,1)) #, boundaries=boundaries, ticks=ticks drawedges=True, #cbar.dividers.set_color('white')  , pad=-0.5 ax=[ax21, ax22, ax23, ax24], c\n",
    "cbar.ax.set_xticklabels(['$-10$','$-8$','$-6$','$-4$','$-2$','$0$','$+2$', '$+4$', '$+6$'])\n",
    "cbar.set_label(r'$\\Delta$T ($\\mathsf{^{\\circ}C}$)', labelpad=-45, fontsize=11)\n",
    "#cbar.set_label(\"%s (%s)\" % (varname, units), fontsize=12) , \\\n",
    "#           shrink=0.7 , pad=0.06\n",
    "cbar.ax.tick_params(labelsize=10);\n",
    "\n",
    "a31=ax31.pcolor(xpom, ypom, coral_suscept_ini, cmap='Spectral_r') #,vmin=-15, vmax=35\n",
    "ax31.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75, colors='k')\n",
    "ax31.contour(xom,yom,kmt_225Ma,  levels=[0.5], colors='k',linestyles='dashed', linewidths=1.75)\n",
    "ax31.scatter(x_scat, y_scat,edgecolors='k', c='gold', zorder=5, s=35, alpha=0.8) #, marker='*', s=125\n",
    "ax31.scatter(x_scat2, y_scat2,edgecolors='k', c='gold', zorder=5, s=35, alpha=0.8) \n",
    "cbar=fig.colorbar(mappable=a31, cax=ax35, orientation='horizontal', boundaries=np.arange(0,1+0.05,0.05), ticks=np.arange(0,1+0.2,0.2)) #, boundaries=np.arange(-11,6+1,1) drawedges=True, #cbar.dividers.set_color('white')  , pad=-0.5 ax=[ax21, ax22, ax23, ax24], c\n",
    "#cbar.ax.set_xticklabels(['$-10$','$-8$','$-6$','$-4$','$-2$','$0$','$+2$', '$+4$', '$+6$'])\n",
    "cbar.set_label('Coral Reef Suceptibility S', labelpad=-45, fontsize=11)\n",
    "cbar.ax.tick_params(labelsize=10);\n",
    "\n",
    "ax32.pcolor(xpom, ypom, coral_suscept_cold-coral_suscept_ini, cmap='RdBu_r', vmin=-0.7, vmax=0.7) #,vmin=-15, vmax=35\n",
    "ax32.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75,colors='k')\n",
    "ax32.contour(xom,yom,kmt_225Ma,  levels=[0.5], colors='k',linestyles='dashed', linewidths=1.75)\n",
    "ax32.scatter(x_scat, y_scat,edgecolors='k', c='gold', zorder=5, s=35, alpha=0.8) #, marker='*', s=125\n",
    "ax32.scatter(x_scat2, y_scat2,edgecolors='k', c='gold', zorder=5, s=35, alpha=0.8) \n",
    "\n",
    "a33=ax33.pcolor(xpom, ypom, coral_suscept_warm-coral_suscept_ini, cmap='RdBu_r', vmin=-0.7, vmax=0.7) #,vmin=-15, vmax=35\n",
    "ax33.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75, colors='k')\n",
    "ax33.contour(xom,yom,kmt_225Ma,  levels=[0.5], colors='k',linestyles='dashed', linewidths=1.75)\n",
    "ax33.scatter(x_scat, y_scat,edgecolors='k', c='gold', zorder=5, s=35, alpha=0.8) #, marker='*', s=125 'xkcd:bright blue'\n",
    "ax33.scatter(x_scat2, y_scat2,edgecolors='k', c='gold', zorder=5, s=35, alpha=0.8)  #'xkcd:green'\n",
    "\n",
    "cbar=fig.colorbar(a33, cax=ax34, orientation='horizontal', boundaries=np.arange(-0.8,0.9,0.1), ticks=[-0.8,-0.4,0,0.4,0.8]) #drawedges=True, #cbar.dividers.set_color('white')  \n",
    "cbar.ax.set_xticklabels(['$-0.8$', '$-0.4$','$0$','$+0.4$', '$+0.8$'])\n",
    "cbar.set_label(r'$\\Delta$S', labelpad=-45, fontsize=11)\n",
    "#,boundaries=boundaries, ticks=ticks,, extend=extend\n",
    "#cbar.set_label(\"%s (%s)\" % (varname, units), fontsize=12) , \\\n",
    "#           shrink=0.7 , pad=0.06\n",
    "cbar.ax.tick_params(labelsize=10);\n",
    "\n",
    "matplotlib.rcParams['hatch.color']='navy' #whitesmoke\n",
    "#ax21.pcolor(xom, yom, np.ma.masked_greater(oxy_cs_ini, 100), hatch='xxx', alpha=0.)\n",
    "#ax21.pcolor(xom, yom, np.ma.masked_less(oxy_cs_ini, 200), hatch='...', alpha=0. )\n",
    "ax21.contourf(xom, yom, oxy_cs_ini, hatches=['xxx',None], levels=[0,100], colors='none')\n",
    "ax21.contourf(xom, yom, oxy_cs_ini, hatches=['...',None], levels=[200,1000], colors='none')\n",
    "matplotlib.rcParams['hatch.color']='w'\n",
    "#ax22.pcolor(xom, yom, np.ma.masked_greater(oxy_cs_cool, 100), hatch='xxx', alpha=0.)\n",
    "#ax22.pcolor(xom, yom, np.ma.masked_less(oxy_cs_cool, 200), hatch='...', alpha=0. )\n",
    "ax22.contourf(xom, yom, oxy_cs_cool, hatches=['xxx',None], levels=[0,100], colors='none')\n",
    "ax22.contourf(xom, yom, oxy_cs_cool, hatches=['...',None], levels=[200,1000], colors='none')\n",
    "matplotlib.rcParams['hatch.color']='w'\n",
    "#ax23.pcolor(xom, yom, np.ma.masked_greater(oxy_cs_warm, 100), hatch='xxx', alpha=0.)\n",
    "#ax23.pcolor(xom, yom, np.ma.masked_less(oxy_cs_warm, 200), hatch='...', alpha=0. )\n",
    "ax23.contourf(xom, yom, oxy_cs_warm, hatches=['xxx',None], levels=[0,100], colors='none')\n",
    "ax23.contourf(xom, yom, oxy_cs_warm, hatches=['...',None], levels=[200,1000], colors='none')\n",
    "\n",
    "\n",
    "ax_text.text(0.5,0.18,'Initial',fontsize=13, horizontalalignment='center', color='tab:green',fontweight='bold')\n",
    "ax_text.text(0.5,0.49,'Cool',fontsize=13, horizontalalignment='center', color='tab:blue',fontweight='bold')\n",
    "ax_text.text(0.5,0.84,'Warm',fontsize=13, horizontalalignment='center', color='darkorange',fontweight='bold')\n",
    "\n",
    "arrow=matplotlib.patches.FancyArrowPatch(posA=(0.5,0.25),posB=(0.5,0.45),arrowstyle=matplotlib.patches.ArrowStyle.Fancy(head_length=.3, head_width=.2, tail_width=.1), mutation_scale=50, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "ax_text.add_patch(arrow)\n",
    "arrow2=matplotlib.patches.FancyArrowPatch(posA=(0.5,0.58),posB=(0.5,0.78),arrowstyle=matplotlib.patches.ArrowStyle.Fancy(head_length=.3, head_width=.2, tail_width=.1), mutation_scale=50, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "ax_text.add_patch(arrow2)\n",
    "#ax_text.arrow(0.5, 0.25, 0, 0.2,fc='k', ec='k', alpha=1, width=0.05, head_width=0.2, head_length=0.05,length_includes_head=True)\n",
    "#ax_text.arrow(0.5, 0.58, 0, 0.2,fc='k', ec='k', alpha=1, width=0.05, head_width=0.2, head_length=0.05,length_includes_head=True)\n",
    "\n",
    "ax1.text(-0.35,1.01,'(a)',transform=ax1.transAxes,fontsize=11)\n",
    "ax11.text(-0.35,1.01,'(b)',transform=ax11.transAxes,fontsize=11)\n",
    "\n",
    "ax21.text(0,0.85,'(c)',transform=ax21.transAxes,fontsize=11)\n",
    "ax22.text(0,0.85,'(d)',transform=ax22.transAxes,fontsize=11)\n",
    "ax23.text(0,0.85,'(e)',transform=ax23.transAxes,fontsize=11)\n",
    "\n",
    "ax31.text(0,0.85,'(f)',transform=ax31.transAxes,fontsize=11)\n",
    "ax32.text(0,0.85,'(g)',transform=ax32.transAxes,fontsize=11)\n",
    "ax33.text(0,0.85,'(h)',transform=ax33.transAxes,fontsize=11)\n",
    "\n",
    "ax23.text(0.5,1.15,'Surface Air Temperature \\n & Oxygen Minima',transform=ax23.transAxes,fontsize=14, horizontalalignment='center')\n",
    "ax33.text(0.5,1.25,'Coral Reef Susceptibility',transform=ax33.transAxes,fontsize=14, horizontalalignment='center')\n",
    "\n",
    "plt.tight_layout(h_pad=-4.25, w_pad=-2) #h_pad=-2,\n",
    "\n",
    "fig.savefig('./plot_pdf_files/Fig3_pulse_rev_Overview_InitialColdWarm.pdf',bbox_inches='tight', pad_inches=0.05, dpi=900)\n",
    "#fig.savefig('./PlotsForPaper/pulse_corr_Overview_InitialColdWarm.png',bbox_inches='tight', pad_inches=0.05, dpi=900)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. S20: Phytoplankton growth rate temperature characteristic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Dependence of maximal growth rate on Temperature:\n",
    "Ts=np.linspace(-2,40,200)    \n",
    "#classical Eppley curve:\n",
    "a_epp=0.59; b_epp=0.0633    \n",
    "mumax_eppley=a_epp*np.exp(b_epp*Ts) \n",
    "#different proposed curves:   \n",
    "mumax_six=0.6*1.066**Ts #=ft\n",
    "mumax_biss=0.81*np.exp(0.0613*Ts) #see Bissinger 2008 and Kremer 2017 \n",
    "mumax_mte=0.5*np.exp(0.0498*Ts) #see Kremer 2017; intercept is chosen arbitrarily\n",
    "\n",
    "#Introduce new dependence with thermal limitation:\n",
    "#load equilibrium SST's to determine T. in the tropics, which is approx. the optimal T.:\n",
    "nc_f = '../climber/c3beta_tria_200Ma_1500ppm/snapshots.004002.01.01.dta.nc' \n",
    "\n",
    "nc_fid = Dataset(nc_f, 'r')\n",
    "#nc_attrs, nc_dims, nc_vars = ncdump(nc_fid)\n",
    "temp=np.flipud(np.ma.mean(nc_fid.variables['temp'][:,0,:,:], axis=0))\n",
    "#temp_zonalmean=jan.global_mean(temp,region='global',grid='ocean',axis='zonal')\n",
    "#jplt.plot_world(temp,projection='moll')\n",
    "\n",
    "#Determine parameters for the new curve:\n",
    "Topttrop=np.max(temp)-0.25 #~the annual mean T. in the Tropics, because there it is approximately equal to the opt. T.\n",
    "Topttrop=31.1-2.5 #31.1 is max. SST for 1500ppm; and 27degC of M. Thomas is 2.5 degC lower than modern max. SST of 29.5 (WOA)\n",
    "Tmax=Topttrop+6 #the T., where growth becomes zero; in Thomas 2017 the difference between Topt and Tmax is ~5 degC\n",
    "#in Thomas 2015 in Tropics Topt is ~28degC and Tmax ~35degC\n",
    "#a=0.59; b=0.0633\n",
    "a=0.65; b=0.065\n",
    "#a=0.64; b=0.064 #we can slightly increase the Eppley-coefficients to compensate for the decreased optimal growth rate\n",
    "mumax_eppley_new=a*np.exp(b*Ts) \n",
    "#determine Parameters c and numerically to fulfill the two boundary conditions (Maximum at Topt, Zero at Tmax)\n",
    "def equations(p):\n",
    "    c, d = p\n",
    "    return (c-a*b/d*np.exp(b*Topttrop), d-(b*Tmax-np.log(c/a))/(Tmax-Topttrop))\n",
    "c, d =  fsolve(equations, (1, 1))\n",
    "mumax_new=mumax_eppley_new-c*np.exp(d*(Ts-Topttrop))\n",
    "mumax_new[mumax_new<0]=0\n",
    "\n",
    "#modern:\n",
    "Topttrop_modern=27\n",
    "Tmax_modern=Topttrop_modern+6\n",
    "def equations(p):\n",
    "    c_modern, d_modern = p\n",
    "    return (c_modern-a*b/d_modern*np.exp(b*Topttrop_modern), d_modern-(b*Tmax_modern-np.log(c_modern/a))/(Tmax_modern-Topttrop_modern))\n",
    "c_modern, d_modern =  fsolve(equations, (1, 1))\n",
    "mumax_new_modern=mumax_eppley_new-c_modern*np.exp(d_modern*(Ts-Topttrop_modern))\n",
    "mumax_new_modern[mumax_new_modern<0]=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot:\n",
    "fig1=plt.figure(figsize=(6,4.5))\n",
    "plt.clf()\n",
    "ax1 = fig1.add_subplot(111) \n",
    "#ax1.plot(Ts,mumax_six,'--k',lw=1.5, label=r'modern (Eppley)', zorder=3) #label=r'Eppley/Six&Maier-Reimer 1996: $\\mu_{max}=0.6\\cdot 1.066^T$'\n",
    "ax1.plot(Ts,mumax_new_modern,'-k',lw=1.5, label=r'modern', zorder=3) # (limited)\n",
    "ax1.plot(Ts,mumax_new,'--k',lw=1.5, label=r'adapted to warmer climate', zorder=3)\n",
    "\n",
    "def smooth(x,window_len=11,window='hanning'):\n",
    "    s=np.r_[x[window_len-1:0:-1],x,x[-2:-window_len-1:-1]]\n",
    "    #print(len(s))\n",
    "    if window == 'flat': #moving average\n",
    "        w=np.ones(window_len,'d')\n",
    "    else:\n",
    "        w=eval('np.'+window+'(window_len)')\n",
    "\n",
    "    y=np.convolve(w/w.sum(),s,mode='valid')\n",
    "    return y\n",
    "\n",
    "ss=sst_warm.data; sst_warm_dummy=ss[ss!=-1e+34].flatten()\n",
    "nn=nep_warm.data; nep_warm_dummy=nn[nn!=-1e+34].flatten()\n",
    "sst_nep_warm=pd.DataFrame({'sst': sst_warm_dummy, 'nep':nep_warm_dummy.flatten()})\n",
    "sst_nep_warm_sort=sst_nep_warm.sort_values(by=['sst'])\n",
    "#sst_nep_warm_smooth=sst_nep_warm_sort.rolling(100, on='nep').mean()\n",
    "\n",
    "ss=sst_ini.data; sst_ini_dummy=ss[ss!=-1e+34].flatten()\n",
    "nn=nep_ini.data; nep_ini_dummy=nn[nn!=-1e+34].flatten()\n",
    "sst_nep_ini=pd.DataFrame({'sst': sst_ini_dummy, 'nep':nep_ini_dummy.flatten()})\n",
    "sst_nep_ini_sort=sst_nep_ini.sort_values(by=['sst'])\n",
    "\n",
    "ss=sst_cold.data; sst_cold_dummy=ss[ss!=-1e+34].flatten()\n",
    "nn=nep_cold.data; nep_cold_dummy=nn[nn!=-1e+34].flatten()\n",
    "sst_nep_cold=pd.DataFrame({'sst': sst_cold_dummy, 'nep':nep_cold_dummy.flatten()})\n",
    "sst_nep_cold_sort=sst_nep_cold.sort_values(by=['sst'])\n",
    "#sst_nep_cold_smooth=sst_nep_cold_sort.rolling(100, on='nep').mean()\n",
    "\n",
    "ax1.fill_between(sst_nep_warm_sort.loc[:,'sst'], sst_nep_warm_sort.loc[:,'nep']*3, 0, interpolate=True, color='tab:orange')\n",
    "ax1.fill_between(sst_nep_ini_sort.loc[:,'sst'], sst_nep_ini_sort.loc[:,'nep']*3-0.6, -0.6, interpolate=True, color='tab:green')\n",
    "ax1.fill_between(sst_nep_cold_sort.loc[:,'sst'], sst_nep_cold_sort.loc[:,'nep']*3-1.2, -1.2, interpolate=True, color='tab:blue')\n",
    "\n",
    "ax1.scatter([Topttrop, Topttrop_modern], [np.max(mumax_new), np.max(mumax_new_modern)], c='k', zorder=4)\n",
    "\n",
    "ax1.axvline(x=Topttrop, c='k', ls=':')\n",
    "ax1.axvline(x=Topttrop_modern, c='k', ls=':')\n",
    "ax1.set_xlim([-2,40])\n",
    "ax1.set_ylim([-1.4,4])\n",
    "ax1.tick_params(labelsize=12)\n",
    "ax1.legend(frameon=False)\n",
    "ax1.set_xlabel(r'SST ($\\mathrm{^{\\circ}C}$)', fontsize=13); \n",
    "ax1.set_ylabel(r'Max. Phytoplankton Growth Rate (day$\\mathsf{^{-1}}$)', fontsize=13)\n",
    "ax1.set_yticks([0,1,2,3,4])\n",
    "#ax1.set_yticklabels(['0','0.5','1.0'])\n",
    "\n",
    "plt.tight_layout()\n",
    "fig1.savefig('./plot_pdf_files/FigS20_growthrate_rev.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fig. 5: Synthesis of CAMP effects across timescales "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: pco2_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_raw_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
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     "data": {
      "text/html": [
       "<pre style=\"background-color:#F2F5A9; border-radius: 4px 4px 4px 4px; font-size: smaller\">Message: ts_ann_cs_raw_f is now available in python as a dictionary containing the variable's metadata and data array.</pre>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Read out example Temp.-Timeseries\n",
    "\n",
    "path='pulse_c_1500ppm_5300GtC_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_c_1500ppm_5300GtC_5ka=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "path='pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "        let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "%ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "%ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n",
    "Tcolor='tab:green'\n",
    "path='pulse_c_1000ppm_5300GtC_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_c_1000ppm_5300GtC_5ka=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "path='pulse_c_2000ppm_5300GtC_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_c_2000ppm_5300GtC_5ka=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "\n",
    "path='pulse_c_1500ppm_5300GtC_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history.nc\"; \\\n",
    "        let a=pco2diag[i=@ave,j=@ave]; let pco2_f=a' % locals()\n",
    "%ferret_getdata pco2_f=pco2_f\n",
    "pco2_c_1500ppm_5300GtC_5ka=np.ma.masked_values(pco2_f['data'][0,0,0,:,0,0], -1e34)\n",
    "path='pulse_c_2000ppm_5300GtC_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history.nc\"; \\\n",
    "        let a=pco2diag[i=@ave,j=@ave]; let pco2_f=a' % locals()\n",
    "%ferret_getdata pco2_f=pco2_f\n",
    "pco2_c_2000ppm_5300GtC_5ka=np.ma.masked_values(pco2_f['data'][0,0,0,:,0,0], -1e34)\n",
    "\n",
    "path='pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "        let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "%ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "%ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "ts_ann_pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "ts_ann_pulse_rev_cs_2000ppm_5300GtC_125GtS_5ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n",
    "\n",
    "\n",
    "path='pulse_c_1500ppm_5300GtC_12ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_c_1500ppm_5300GtC_12ka=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:10500,0,0], -1e34)\n",
    "path='pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "        let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "%ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "%ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n",
    "Tcolor='tab:purple'\n",
    "path='pulse_control_1500ppm'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_f=a' % locals()\n",
    "%ferret_getdata ts_ann_f=ts_ann_f\n",
    "ts_ann_pulse_control_1500ppm=np.ma.masked_values(ts_ann_f['data'][0,0,0,500:10500,0,0], -1e34)\n",
    "\n",
    "path='pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "        let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "%ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "%ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n",
    "path='pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka'\n",
    "%ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "        let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "        let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "%ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "%ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_12ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n",
    "\n",
    "\n",
    "# path='pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka'\n",
    "# %ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "#         let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "#         let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "# %ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "# %ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "# ts_ann_pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "# #ts_ann_pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n",
    "# path='pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka'\n",
    "# %ferret_run 'cancel data/all; define symbol path = %(path)s; use \"../climber/($path)/history_p2.nc\"; \\\n",
    "#         let a=ts_ann[i=@ave,j=@ave,l=@sbx:100]; let ts_ann_cs_f=a; \\\n",
    "#         let b=ts_ann[i=@ave,j=@ave]; let ts_ann_cs_raw_f=b ' % locals()\n",
    "# %ferret_getdata ts_ann_cs_f=ts_ann_cs_f\n",
    "# %ferret_getdata ts_ann_cs_raw_f=ts_ann_cs_raw_f\n",
    "# ts_ann_pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka=np.ma.masked_values(ts_ann_cs_f['data'][0,0,0,500:,0,0], -1e34)\n",
    "# #ts_ann_pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka_raw=np.ma.masked_values(ts_ann_cs_raw_f['data'][0,0,0,500:,0,0], -1e34) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%matplotlib inline\n",
    "# filename='./carbon_emission_1Myr_22100GtC.dat'\n",
    "# years_c_multi,c_rate_multi=np.loadtxt(filename, unpack=True)\n",
    "\n",
    "# geocarb_out=np.loadtxt('./geocarb_out.dat', skiprows=1)\n",
    "# #geocarb_out=geocarb_out[200000:,:]\n",
    "# names=['year', 'tco2', 'alk', 'd13Cocn', 'pCO2', 'd13Catm', 'CO3', 'WeatC', 'WeatS', 'TotW', 'BurC', 'Degas', 'Tatm', 'Tocn']\n",
    "# geocarb_out_df = pd.DataFrame(geocarb_out, columns=names) #, index=names\n",
    "\n",
    "# years_geocarb=geocarb_out[:,0]\n",
    "# temp_geocarb=geocarb_out[:,12]\n",
    "# pCO2_geocarb=geocarb_out[:,4]\n",
    "\n",
    "start_2=int(np.round((201.565-201.5035)*1e6))\n",
    "start_3=int(np.round((201.565-201.2895)*1e6))\n",
    "start_4=int(np.round((201.565-200.916)*1e6)) #following Paris et al. 2016\n",
    "\n",
    "spin=int(2000000./10)\n",
    "\n",
    "loscar_pco2a=np.loadtxt('../loscar/loscar_new_pco2a.dat')\n",
    "loscar_years=np.loadtxt('../loscar/loscar_new_tmv.dat')\n",
    "loscar_temp=2.86/np.log(2)*np.log(loscar_pco2a/1500)+18.7\n",
    "\n",
    "loscar_pco2a_ext=np.loadtxt('../loscar/loscar_4Myr_pco2a.dat')\n",
    "loscar_years_ext=np.loadtxt('../loscar/loscar_4Myr_tmv.dat')\n",
    "loscar_temp_ext=2.86/np.log(2)*np.log(loscar_pco2a_ext/1500)+18.7\n",
    "\n",
    "#loscar_new_pco2a=np.loadtxt('./loscar_new_pco2a.dat')\n",
    "#loscar_new_years=np.loadtxt('./loscar_new_tmv.dat')\n",
    "#loscar_new_temp=3./np.log(2)*np.log(loscar_new_pco2a/1500)+18.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3KKXatCQ3ED3Tq1ev5vHHH+fLL78kdEgog6cNJnh4MLVB7rlQBaFPeB+Sw5KJCY0hNiSWuSfOdf6BeH/P++SW5XJqzKmoCkVBQQHrctaxp2wPJTUllNeUU1lfSY29hlp7LXWqjjqpwy52VJBCggUJEupL60FAgoSgiCBMFhP2OrvhHQ4yDkxokdEKwRLMQ7EPMW3aNK+Md/jwYU595lQix0YSZYnis4s+Y/Zts1m8eDGXXXYZCxcuJCYmxivXCgSuuuoqfvjhB2YsncGg6EHMGD6DMHOYx7aVlZWsWLGCjz/+mE8++cQZIhIXF8dJJ53E2LFjGTVqFKNGjWL48OFYrdbuvBVNB1FKERYWxu//+Hv2nLyHswacxW3jb8MSZOnUmHl5eezbt4/9+/ezb98+cnNzyc3NJS8vz+1ndXV1q+NFREQQFRVFREREq0d4eHib2vQmgf7RRx95bY7tKWgxbaDFdANiqK3FGAsNL1BKVbnUHYMhpB9TSr3U1jEDSUxnZGRw9913895775GSksLYP43lYMzRhS8DIgdwQt8TOC7pOEbEjWBA1ABCgkLaNPaOwh28s/MdNuRs4GDpQepUXdfchN04lF0ZYRX1CmVXUI/zHHuj1/aGNnaOltUb/U0N/xwhI65hKEGmIONnUNDR86Aggk3BxhF09DCbzAQHG2Eg5mCz8TPITFBQEJZgi1EXbD56mI16i9lCiDkEi9mCOdiMiGASE8FBwU67HOEkgDMUxSTGUgmRhnASBeHmcObMmMPq1au98lZnZmYybfU0xCSsuHQFKREpKKV4+umnuffee0lJSeGVV17hrLPO8sr1/J1zzz2XUlMplTMrCQ0KZcWlK4i3xrfaz263s2vXLr777jvWrVvH+vXr2blzp9sC0OTkZAYMGMCAAQNITU0lOTmZhIQEtyMxMZGYmJheJWx6GsXFxcTGxnLNC9ewMXwjA6MG8u5v3u2UmG4P1dXVlJSUUFpaSklJSbNHWVkZ5eXlLR51dW2fw61Wa6uCvL0/w8LCeuRn+cwzz/TaHNtT0GLaQIvpBkTkJWA8MEUpVe5SngJ8A7yklHqyPWMGgpiuq6vjwQcf5IknnsAcYubeP9/LXXfdxdrctTzywyNcOvRSzh94PsfGHNtu729tfS1rD61l9urZ2DmaSi0mJIZ4azwJ1gQSrYnEhsQSYYkg0hJJuDmccHM4YcFhhASFYAmyYDY1iEuTxXnuLDeZnSK3OWw2GxUVFVRVVVFZWek8qqqqnGWO165HTU0NVVVVVFdXu5VVV1dTXV3t8XVNTY3ztWv6OG9gMpmwWCyYzeYmP10PT2Vms5mHHnqItLQ053bGnWHn7p1ctu4yBGHLNVvc6n788UdmzpxJRkYG06dP5+9//zuDBg3q9DX9mbFjxxL16yhKhpUA8PM1Hd+kw2azsXv3brZt28aOHTs4cOCA21FZWdls3/DwcKKiooiKiiIyMtL5uvHRFrETHh6ut8JuB7/88gsjR45k9JLRAB5/d/yF2traVgV3W46Kigrnz/b+LbVarR0W4y397Mw6hfz8fBISEjrcvyeixbSBFtM4Pc/7gBrA9Sv1zcCxwDzA7TdZKRXR2rj+LqZzc3OZPn06a39ay4n3nchpE07jsXOM1cj19nrsyu5cVNcWymrL2FW0ix+zfgQgvyqf9/e8j81u44Q+J3DLuFsYFjfMufgv0Kmrq6Ompoba2lqnyHYctbW1znLXepvN5qxzlDvKbDZbs+eOw1Hu6SgsLOSss85i2bJlnQ6L2bJtC1elX0UQQWy+ZnOT+qqqKh5//HEee+wx6urquPLKK7n99ts5/vjje2VITp8+fUh8PNF53hkx3RqVlZXk5+e7HXl5eU6vZGtHfX19m68VEhLSJtHdXkFjsVgC7nOycuVKpkyZ4hTT0LWfA3/DbrdTVVXlUWh35Kfr6/boIIvF0mEx7giTmTx5che+U92LFtMG2m0AKKX2Ay3NzA92ly09hfT0dC655BLy8vJ47KXHeM30Gmty1lBQVUC8Nd4IW6Dtj9Gq6qq499t72ZSzidTIVESE7QXbUSiOjTmWp894mpjQ3hVDGxwcTHBwcJPsDb5ixowZvP7664wcOZK5c+d2aqzqWiP+0tRM9k2r1cq8efOYNWsWzzzzDC+99BKvv/46w4cPZ+bMmUydOpUJEyZgMgV+9s76+nry8vJIJLH1xl4gLCzMGfbRXpRSVFZWevQatiZgXF8fPny4SZv2iHSTyUR4eDhhYWFuR0fLPLUJCQnpVsGu80W3jOP/PDw83JlC0hsopaiuru6wEHf8zMrKatLG02c6LCyMV155hSuuuMJr96DxPVpMa5rw1ltvcc0115CcnMzatWuZOHEiIzNHMj5xfJviOBtTYavg6wNf882hb1Aothdud9YNjBrIq1Nf7TXe6J5MVlYWM2fO5L777sNqtTJ79uwOj1VjM7LYNCemHfTr14+nnnqKv/71r7zzzjssXbqU+++/n/vvv5+EhASOP/54Jk6cyLhx4xg8eDBpaWlER0d32K6eSGFhoddDfroKEXEKGm+ilHKGBrRFnDvCryoqKtxCsyoqKsjNzXU7d7xu71NYk8nUbhEeEhJCaGgooaGhzteNfzZX9+OPPxIS0rZ1JhrvISJYrVZnlhNv4fhMu352r776akJCQpg+fTqrV6/m6aef1guEAwQtpjVuLFu2jOtmXceYv4zhL7/5CxPHTgRg6qCpHR5zydYlfLn/S2ceZTDiAU/ocwLXjLpGC+kewgcffEB4eDi1tbXcddddVFdXc88993TIO+cQ00HStqcX0dHR3Hjjjdx4443k5uby5ZdfsnLlStLT0/niiy/cPDxxcXH079/fLa1XUlISCQkJzhRejY/IyMgeG7975MgRX5vgc0SEkJAQQkJCiI9v/xf21lBKUVNT06wAb895ZWUleXl5Htt0Nmxy2rRpZJIJwMTkid64dY2PcP1Mx8UZKV9XrVqF1Wrlvvvu46mnnmLNmjUsWbKE448/3sfWajpLz/zr0gFEJAToB1iBPKWU3n+3nSxZsoQbb72RsQ+OxZZsY9GeRfx29G+dG4u0h0pbJWaTGZvdxt7ivewt2QsYOZAHxwymzl5HmDmsXTHXmq7F4fF94403sFgszJ07l8OHD/PPf/6z3Svja2obPNMtLPxsjqSkJK666iquuuoqwIjx3bFjB5mZmWRkZJCRkcGRI0fIy8sjMzOT3NxcysrKWh3XarUSGRnZxNvYnsNqtbq9dngaXb2MZrO5XV9AduzY0XojTacQEef/k0PYeBulFHV1dS0uPm6pTinFzJkzOeezcwCYPmx6l9ip8R2OOfbJJ5/knHPO4cYbb+Skk07i7rvv5sEHHyQ0tH25xTU9B78W0yISCVwNzABOAMwYsc9KRI4AK4AFSqkNvrPSP3j55Zf5/R2/Z+zfxmJLsJEUlsQL57zQISH90d6POFh2kH4R/RifON4ppE/ocwIj4kcAONM9tRYGoOk+3nrrLaZPn47ZbGbZsmXOEIwDBw6wdOlSYmNj2zyWM8yjA2K6MWFhYUyYMIEJEyY026a6upr8/HxKS0spKytrdvFcWVlZk6wthYWFHDp0yC2LS2VlpVt6ufbgKtw8ie3Gx/r16/Wj3gBARJyZcSIjO/+0rU94YO2Upzk6xwKcf/75bNu2jbvvvpsnnniCDz74gFdeeYWTTz7Zx1ZqOoLfimkRmQ38BcgAPgQeAY4AVUAcMBo4HfhSRH4A/qiU2u0jc3s0r776Kr+f/XvGPjIWW6yNlIgUFv5qoXNL7vZysMxYSHOk/AhHyo+QXZENwJ0T7+TbQ+4bRwbainx/Zv78+c6J3mQy8eSTTzJw4EDuvPNOJkyYwNtvv93mx5E1de0L8+gsoaGh9O/f36tj2my2JsLb9bG+pxSIrR2OtoWFhc6y+vp6/va3v7GEJQD0C+/n1fvQ+Cd25R9x9Jq24zrHguGpXrhwIVdccQU33ngjp512GnPmzGHevHk6ft7P8FsxDZwCnKGU2tpM/XpgsYj8HrgBOAPQYroRH374ITfdeRNj/jYGW6yNAZEDWHTeog57RRrHDJbUlFBZV4nFZGFAZNPsAdJiEhVNd/Lpp582KfvDH/7AxIkTueKKKzj55JO58847mTdvHhERLWeGdHh1u0tMdwUOL2NUVFS3XG/J0iUADI0b2i3X0/Q8XOdPf/7d0XjG0xwLxqZNW7du5a677uKxxx7j008/5bXXXmPMmDHdbKGmo/jtM3al1OUtCGnXdjVKqReVUi93h13+xOrVq5k5aybD7h9GXWwdadFpLDl/SYeF9OqDq5n/3/luZZklxmKaAVEDPP5x8EYYgMY7NLdZy0knncTmzZu5/vrrefrppxkyZAjPPvtsi5t/OMI8gsWfv6/7Bh361HtxXaQ9NnGsDy3RdAUtbYgVGRnJwoUL+fDDD8nOzmbSpEk88cQT7dpNUuM79KyNsXhRRBaJyH4RKRORn0Rkqkv9OSKyQ0QqReTrhk1e/JqNGzdy8bUXM/DegahYxbDYYSw+bzGJYR1PDbS9YHuTsn2l+wAYFOV5hzstpnsOr732WrN1cXFxLFiwgO+++44RI0Zw11130b9/f26//XY2bdrU5IlEVU0VAMFBWky3F9fdQDW9C9fQDj03Bh4tzbEOpk2bxtatW7nwwgv585//zMSJE1m7dm03WKfpDH792yoiU0Vkn4g0STwrItENdb9qw1DBwEGMUJBo4K/A2yIyUEQSgOUNZXFAOvCW127CB2zbto0LrrqAfnf1Q2KE0fGjWXTeog7lkG4JpRR5lUZSlZTIFI/x0Tpmuufw8sutP7w55ZRTWLVqFd9++y3nnXceCxYsYOLEifTv358bbriBxYsX89///pfS8lKADi1g7e3oXWl7L0fKdZrEQKYtcyxAYmIi7777Lv/5z38oKiri9NNP53e/+x2ZmZldbKGmo/i1mAZuA55USpU0rmgoexy4o7VBlFIVSql5Sql9Sim7UupjIBOYCFwCbFNKvaOUqsbYWnyciAz35o10F3v27OG8K88j4Q8JmKJNjE8cz4JfLSA6xPsbYaTnpFOn6giSIKzBVo8iQT/S7jl8+eWXbW572mmn8eabb3LkyBEWLVrEqaeeyvLly7nhhhsYP348j/z9EQDMwTr1YXsZlTDK1yZofERxTbGvTdB0Ie2ZY0WESy+9lF9++YW5c+fyzjvvMHToUG666SZ279bLv3oa/q5kxgJftVC/ChjX3kFFJBkYCmwDRgH/ddQppSqAvQ3lnvrOEpF0EUnvabFOBw4c4JxzzqGmsIahfYdyQp8T+Ne5//LKpinF1e5/BJRSpOeku5e5xAPGhBhbh2vPdM/BbG6/8I2Li+P666/n7bffpqCggB07dvDGG29wzXXXABASrFektxXHmoKpAzu+QZLGv9EZPAKbjsyx4eHhPPLII+zdu5dbbrmFZcuWMXToUM4++2zefPNNqqqqusBSTXvxdzGdCC0GGCqgXbELImIGXgeWKqV2ABFAY893CeBRgSqlFiilJimlJvWkHdcOHTrElClTKCkp4fOPPmfJtCW8cM4LhJmbXxDRHt7Y8QYANfU15FflO88Bzkw9E3AX0w50No+ew5IlSzrV32QyMWzYMGbMmMHvb/k9ANX11V6wrHfg+FKrszj0XursPcsBo/EunZljU1JSeO6559i3bx+PPPIImZmZzJw5k+TkZK677jq++uort51iNd2Lv4vpQxje6eYYCxxu62AiYgKWAbUYISQA5UDj3FhRQOtbrvUQtm/fzuTrJmM728bHn3zMhAkTiA6JJjTYO7st2eqPbm7x1f6veGfXO5TWGjGzQ2KGMDTWSPXlMe2T1tI9hs6KaVccTyX2FO/x2piBjuMRf6291seWaHyFflIX2Hhjju3Tpw9z585l7969fPXVV1x22WW8++67nHvuuaSmpvK///u//PTTT3rtRTfj72L6E+BvItJk+zARCQMeamjTKmLMYouAZOBSpZRDIW7DJVRERMKBwQ3lPZ7vvvuO0885HevFViJOjqCwT6HXr1FYbYxZU1/DgbIDzvIhMUM4NeXUJu2nD5vOhWkXAtoz3ZNYvXq118ZKDksiyxVKAAAgAElEQVT22li9jaLqIl+boPERCdYEX5ug6UK8OceaTCbOOeccFi9eTE5OjnNTreeff54JEyYwatQoHn30Ufbt2+e1a2qax9/F9CMY2Td2i8ifReS3Dcc9wK6GukfbONZ8YAQwTSnlGoT0HjBaRC4VkVDgfmBLQwhIj+bdd99lypQpxEfG88hJj/DH4/7ItLRp3r/O7ncB+DHrR2dZQmgCZw84G2vw0e85IUFG/Gy8NZ4Ii7HphxbTgYlDFJzY90QfW+J/6JRovZc9RfpJjqb9WK1WLr/8cj744AOysrJ46aWXiI+P57777mPQoEGMGzeOe+65hzVr1jg31NJ4F7+etZVSuRg7IW7BEM3vNRyPNJSdqpTKaW2chrzRNwPjgWwRKW84rlJK5QGXNoxZBJwIXNkV9+MtiouLufSOS5k1fxZjx47lu+++46IJFzFr7CyvPkastFVSbz8ao+XYRjwlIoWLjr2oiSgIDQ7l1vG3eu36Gu+ycOFCr43lKT5e0za0mO69vL/3fV+boOlCvDnHNkd8fDw333wz3377LZmZmTz++OPExcXx9NNPc+aZZ5KQkMDUqVN5+OGHWbVqFeXl5V1uU2+g56yQ6yBKqf3ABSISCxyLEYW7WynV5melDWM0qzKVUl8BfpEK781P3mTeynlYJljod1w//nXev0hM7PhGLC2xZNsS+ob3dZ7X1huxnmenno05qG2rlnWMYM/hrbfe4qabbvLOYA1aWj95aD/6d6L3ohefBjZenWPbwMCBA5kzZw5z5syhtLSUlStX8vnnn7N27Vr++te/AhAUFMSIESMYO3YsY8aMcf5MSUnBZNJf7NuK34tpBw3ieYOv7fAFtjob89+fz9ItS6kZWINlnAWzmLlx3I2MSuranLVZFVmA4aWurq/GbDITbg53a2M2mbHZPT9a8kZaPo13+OqrlrJMtg+HZ1qL6fajBVXvRT+VCGy8Oce2l6ioKC6++GIuvvhiAIqKivjhhx9Yt24dP/30E99++y1vvHE0C1dISAiDBg0iLS3NeaSmptK3b1/69OlD3759W9wevbfht2JaRIKBaxpOlymles0S+Hp7PfuL9/NR+kes2b2GnfU7MUWbYDCYlInzjjmP2ZNm0y+iX7fZ5Fg0FRsa28SzZgmyeBTTN4+9mSCTFg6BiFNMay9ru9GCqvfSnNNBo/E2sbGxTJ06lalTj+a1LyoqYuvWrWzdupXMzEwyMjLIyMhg7dq1lJaWNhkjKqpxorPei9+KaeAJYA3GA+XHgdm+Nacp9hg7N6y4oWVB4VLVN6wvqRGpxFpiGRk1kg/2foDYBFuNjbySPCx5Fr4J/YZqczU4NGiEsYtglERx8fCLuWrkVfSN6OvxUl3J3pK9AMRYYprUNZeiRwvpnsWLL77Irbd6J6b9we8fBHTe3NbYkreFrw9+zczhM51lQ2KH+NAijS9YdWAVu4t2s/rgal+boulCvDnHdgWxsbGcfvrpnH766W7lSimKioo4dOgQWVlZbsfzzz/vI2t7Fv4spgWwYojpnun+ssD6nPUd6lpXXkdwhPt/T1VxFaEDQhGTYK41M8g6iMmDJ3PG4DMYmzjWpx6tHYVGcpN4a9M9cvRiNP/go48+8tpEn12RDcD67I59/nsLy3cv593d7/Lyzy87y3SYR+/j6fSn3dKKagITb86x3YmIEBcXR1xcHGPHum/tocW0gT+L6TnATIyMJH/2sS0eUTWKuOo457lje/Hg4GDnAi27sqOUwmQyYa23UhtUS741v4mQBohOi2Za32ls3baVPpV9SKhJ4NThpzI+aTzz5s1zthsyZAjnnnsuX375Jbt373aWz5s3j/T0dD7++GNn2YwZM+jbty/PPPOMs2zChAn85je/4V//+hdZWUZMdEREBHfffTdff/01a9asAWB7zHYmTpxIQU0B9crI6lHwSwGZFZkMGjSIdevWUVtbi8VuwRJtgfHw4YcfsmnTJue17rrrLrKysnjzzTedZb/+9a+ZNGmS2z0NHTqUmTNn8sYbb7Br164uuyeAWbNmAbBgwQJn2RlnnMFZZ53FU0895Vz93LdvX26++eaAuac5c+a42dep92GQs4vbmP7wPjR7T3j///aLlC/AghsPPvggEydM9Nt7gsD7f+rqe/IkpP39ngLx/6mz93TiiScG3HuoMRC9S07XER4erioqKtrdL7Mkk3/v+Dc5lTlMHTSVk/qexO2rbmdT7ib6R/TnwrQLSYtOY0DUAEbFj2oSRlJWVsY//vEP7HY7JpOJ4cOHk5iYSFJSEklJScTFxXllle6Lm18E4Kfcn/gh6wcAbhl3S5N21466lnpVrxcb9iLGLB3jfP3zNT/70JKezf+u/l++2P+FW5l+v3ofrr8vDvTnQOMPiEilUiq89ZaBjV7p0oCI3CYi6SJSIyJLGtVdISK/iEiZiGwXkYu60pZB0YM4NvZYhsYO5byB5xEdEs3siUZI+KHyQ2SUZLCvdB/fHPqG7YXb3XI919nrCI8Ix263c99992G32xk+fDj19fVs2bKFN954g7///e/Mnz+fd999l2+++YYdO3ZQUFCA3W7vkL0FVQUATE6Z7LE+zBymhbQf8M9//tPXJvQ6XFNLajSawEbPsYGL34Z5iMggpVRmG9sK0F8pdbCFZkeAh4HzMGKxHX1TgNeA3wIrgAuAd0RkYMOmMV1C4ycG45PGc9WIq3j9l9fJLMnk2JhjAVhzcA35lfmckXoGAC///DJ2ZaciqMIIJwHGjHH3ethsNvLz88nNzSU3N5dNmzaRl5dHRUUF8fHxJCUlOT3ZiYmJxMTEuHm/bXYbC7ccTT6fV5UHQGJY1+Sz1nQPK1eu5I477vC1Gb0KvQhXA5AWnUZGSYavzdB0MXqODVz8VkwD34vIJ8DLSqnvPTVo2MjlSuB24AXg/5obTCm1vKHPJKC/S1V/oFgp9VnD+SciUgEMBrpMTDtikF0ZE2+IYocn2EFlXSUAtnobdmV4l0ssJc2ObTab6du3L337unvFamtrycvLc4rs9evXk5eXR1VVlZu4joqLor6qHlOoiXpVT0mNca24UCM+PMGaQH5VfgfvXOMrPvzwQ1+b0OtonJNd0ztZdN4iznr7LF+boeli9BwbuPizmB4O3IchbuuBjUAWUA3EAiOBEcB64E6l1OcdvE468IuI/Ab4BJgG1GBsV94EEZkFzAKwWCyemrQJhyh2pX+UofGLa4qpra/FEmSMH2wy/htLao8K6DpT+1OSWSwWUlJSSElJcSuvrq52E9k7d++kOKsYVa+otdZynDqOurA67Pl26qPqCY8MJx8tpjWa1rhy+JU8/5NeDd/bCQvWm19oNP6M38ZMK6WKlVJ/AlKAW4AdQAxGHoE6YClwnFLq1E4IaZRS9cCrwBsYIvoN4GallMeVhUqpBUqpSUqpSY4wiw5et0mZxWQhOSwZhWLR1kXOWOndRUbGjpzKHGfbMnMZn2Z82uHruxIaGkpqaioTJ05k6tSpmCaZiD8/nrhz49gUvYliSzEpkkLlrkqKvi7ip7d/omRtCWX/LaMqo4rMzEw6shBT07089dRTvjah1xFl0ZseaHS4T29Bz7GBiz97pgFQSlUB/2k4vI6ITMHYIOZMYBMwEfhQRKYqpTZ3xTXBs2fajp1T+p3Ce3veA4wcvif3O9lZv+bgGrf2+0r3sS1mW6dsqLPXOT3gDipshjCuD6rnYPBBiILJoyYTGxpLdV01qZZUcvJyKCkooa6sjtWrV5Obm4vJZHKGirhmF7FarZ4ur+lmvv/eY7SURqPpYvSul70DPccGLn4vpruB8cA3Sqn0hvMNIvIjMAXoMjHtaaMTpRR9wvs4zzfnbWZi8sQmYtdb/HDkBzbnbebW8Z6TzBdUG7HbcaFxWIOtmBoedJjDzIQlhVEbbezwft3461BKUV5e7gwVycrKYsuWLeTm5mKxWJqI7MTEREJDQ7vkvjSeeffdd31tgkbTKzGbzL42QdMN6Dk2cNFiugERCcZ4P4KAIBEJxQgX2QDcIyLjlVKbReQ44HTgxa60x5Nn2hH6cf3o63l126vUqToOlB7g2NhjWfTzIq/b4BqDnVWe1WSb8pwKI6wkITQBoMVt00WEyMhIIiMjGTx4sLNcKUVpaalTZB88eNCZXcRqtZKYmMiYMWMYN26cN29No9FoNBqNxitoMX2UvwAPuJxfDTyolJonIvOA/4hIMpAHPKqU+sLDGF7Dk5h2EBIUwvik8aTnpPPlgS85NvZYauprvG6DNOzSbqu38d6e95p4qNdlrQMgwhLh1l5cdnf/ddqvW76GCNHR0URHRzNkyBBnuVKK4uJicnNzCQ0NJSEhgYEDB3b6nnoL+/btIz+/fYtAH3vsMe65554uskij0Wh6N3qODVy0mG5AKTUPmNdM3f/RQlq9LrHHU5iHS9mAyAGk5xiRJ0qpFr3CncVOU2Ffaat0vh4YNRA4GvfnKqYHRA3o0DVFhNjYWGJjY41rDBxIenp6K700DiZNmtTuPps3d1nUkkaj0fR69BwbuPj1qgcRWSwivWZrPVcxnRSWRGiQEVPsmsWjM2RXZLO3eG+b2mZVZAEQExJDcniym33Hxhobyiybt4ykpCRGjx7t7Ld582ZOOukkxo8fz6RJk1i/fr1XbNd0nn//+9++NkGj0WgCFj3HBi5+LaaBa3DZrTCQ8JQazxURYVjsMOBoajwwQjJ2Fe3y6NnOKM7gla2vNDvmygMr+Xxfy1kEl+9eDuAU3WnRac66stoyLht6GWnRaSgUJ007iRUrVrj1nzNnDg888ACbN2/moYceYs6cOS1eT6PRaDQajaYn4+9iuutiG3xMamQqKRHum6c0FtipUanA0e28AZbvWc7KAyvJD2kaL3uw7CBVdVWtXvvFzS9SVF3k8brZFdkAFNUUOe10JSksCTA2IRgycQhxcXFu9SJCaWkpACUlJfTr169VezTdw9/+9jdfm6DRaNDZPQIVPccGLoEQM92yC9dPOX/Q+a22SbAaWTQKqgqcOaELqwsByLe6i+mFWxa2a+tiRy5pT9iVneLqYjcbAM5IPcP5+oK0C6iz15F3OM+t7z/+8Q/OO+887r77bux2O+vWrWuzTZquZefOnb42QaPRADa7zdcmaLoAPccGLv7umQbIFpH6lg5fG+gtBscMdju3BlsJN4dTp+oorSnlSPkRj/1W7FuBzW6juKa4xfFbCy3Zmr8VMMI57NgJCw5zy3E9Kn6U83VIUIhH8T5//nyeffZZDh48yLPPPssNN9zQ7PUWLFjApEmTmDRpEnl5ec226yoySjLYV7Kv26/rK1577TVfm6DRaIBT+p3iaxM0XYCeYwOXQBDTs4ArWjkCgkhL07WWsSFGtovimmI+2/eZW111XTVgxEq3Bdc465KaEjJKjH4Okf7NoW+c1wKIDY1tj/kALF26lEsuuQSAyy+/vMUFiLNmzSI9PZ309HQSExPbfa3O8N3h75jx8Qxe2dZ8jHlnKagq4J1d73TZ+BqNxj8JEr29uEbjTwSCmP5IKfVuS0dbBhGR20QkXURqRGRJo7owEXlRRPJFpEREvumSO+kA0SHRwNFYZle2FXR8K/G9JUezepTZytzqHPHUMSExzrK2pubr168fa9YY256vWrXKLbd0T2Fjzkbmrp3LjWNubHN2k/aSX5XPDZ/fwKM/POr80uNr7r//fl+boNFooF0heRr/Qc+xgYu/x0x7M176CPAwcB5NM4QswHivRgCFGFuM9wgcgvanvJ+cZaPjR7O1YCvrs9czghFtHqu1MA8HTs90SMue6RkzZrB69Wry8/Pp378/Dz74IAsXLuSOO+6grq6O0NBQFixY0Gb7OopSioNlB0mwJhBmDmuxbXZFNn9a8ycePe1RRsaP5JVtr3g9j3dtfS23rbyNKcdMYc2hNewq2sXYxLFeG7+jHDx40NcmaDQaoLS21NcmaLoAPccGLv4upr2mcJRSywFEZBLQ33kBkWHAb4D+SinHDLfRW9dtLwOjBrKvdJ/z3NU7DEbc8gl9T2BrgRHfbJO2L2Qpt5U7Xx8qO+R83VhkOyZ6h1e8Od58802P5Rs3du/b98q2V3j555epqavhmTOfcVso2ZhHfniE6cOmc2rKqYCxqj6/Kp/EMM9hJvX2eqrrq9vlSXpm4zP0Ce/DH8b/gbyqPLYXbO8RYvqVV7oupEWj0bSdlnbA1fgveo4NXPw6zEMpZVJK5TYuF5FgEYnw0mVOBPYDDzaEefwsIpc211hEZjWEi6TX1dV5yYSjXJB2ARemXQiAJcjilk0jNTKVyf0nExIUQmidsaGLzdRUTLfVA90cZbVG2IdjG/GezI9ZP7Js+zKW/2Y5lwy5hEPlh5ptuzl3MzuKdnDt6GudZYOiB7mFvDTm7V1v88C6B5qtb8zGnI2sOrCKh059CBFhZNzIToXjaDSawCPKEuVrEzQaTTvwazEtIueIyBWNyu4ByoFiEVkhIjGee7eZ/sBooAToB9wGLBURj/ETSqkFSqlJSqlJwcFd4/h3bNdtEhNh5jCuHnE104dN58JBFzrbmO1GntI6U9sE/ds7325TO6WUM21ehLlni+na+loeWPcAj5z6CH3C+xATGkNJTUmz7Z//6XluGXcLIUEhzrLB0YNbXMD5/p73yatse6aR+Zvnc8u4W5x/LEcljGJ7wfY29+9K7r33Xl+boNFogP8Z9T++NkHTBeg5NnDxazEN3It7SMYJwKPAMmAOMA64r5PXqAJswMNKqVql1Brga+BXnRy30zhWfEdaIokLjUNE6BveFzgqpmtNtU36edodMb+q6SYvntpX11dTr+qxmCxuafF6Im/ueJMhMUM4JcVIMxVtiW5WTO8t3su+0n38ZvBv3MrTYtKcWU0as6doD3uK9jhze7fGxpyNHC4/zK8H/9pZNiR2CAdKD/SIRYgFBQW+NqFX0vgzp9FYTD17btV0DD3HBi7+LqZHA2tczi8H1imlblJKPQPcjhHv3Bm2dLK/13GI20Rr0zhea7CxdjLEbnhXy83lTdp0JszDIUY9penrSZTVlrF462LunHinsyw6JJqSWs9ieuWBlZwz4ByCTe5PE9Ki05rN6PHh3g/59eBfO3eDbI0l25Zw45gb3XY3CwkKYWD0QHYV7WrTGF1JdywG1TTFsWuoRuPAJP7+p1njCT3HBi7+/hsbA7jGTJ8KrHA53wC478ndDA1x1qFAEBAkIqEiEgx8AxwA7m1ocypwJvC5F+zvFJ4WxTm8qJE2Q+xWB1V3OkbaVUw60uJ1JMd0d/JZ5mdMSp7kttFNdEh0sxvXrDywkikDpjQpHxwzuFnP9Of7Pmfm8JmU15ZTZ285nKbCVsGG7A38amDTBxrDYof1CDGt8Q3ivXXUmgBB55nWaPwLfxfTWcBgABEJAY4DvnepjwRq2jjWXzBCOu4Brm54/RellA34LXABRtz0QuB/lFI7vHEDHSE+NJ4EawJDY4cyMXmixzZBKoiw4DCUqCZpljyFebREbuXR7yuOkIa40Di3Nj1NEHya+alzoaaD6JBoSmuappzKKs8iqzyLCckTmtQlWhOpqa9p8h4eKT9CdX01Q2OHEmWJanV3ye8Of8f4xPEePfrRIdGU1zZ9gtDd3H333b42oVeivZCaxtTUt/XPlsaf0HNs4OLvs/hnwBMicjbwOFABfOtSPxbY05aBlFLzlFLS6JjXULdNKXWyUipcKTVSKfWel++jXURYIrhi2BVEh0RzYt8Tm23nELyNY3rbK6ZdcYQ0tJZj2pdkV2Szp3gPp6Wc5lbeXMz0qoOrmNx/cpMQDzA2o0m0JpJf6R5TvjFnIxOTJyIixIbGtho3vergKs4ecLbHOmuwlcq6ytZuq0Vmfz27xbj3tlBVVdWp/pqOUVvfdF2Dpnfj+kRNEzjoOTZw8XcxfT9QDXwFXA/cpJRy/ct0PfClLwzrCThCMdq6QK4tNA7zuPjYi4kLjetRcZ+fZX7GlAFTmiyQjAmJ8ehBXp+13plX2hPx1vgmQnVT7iYmJBme7NjQWOf74gmb3ca3h77lzNQzPdaHmcOoquv4JJtbmctXB75ybvveUV544YVO9dd0jK7csl7jn4QGh/raBE0XoOfYwMWvxbRSKl8pNRmIBWI9eIwvBx7qfst6BvGh8QAcLGu061IHHdO2ehvltnIEISrESO3WN6Ivlw29rEdlJFh1YBW/OqZpbHKkJZIKWwX19npnmVKKn/N/ZkzCmGbHS7AmUFDtvgp7Y85GZ1hIXGhci2L657yfSYlIafYLhzXYSqWt457pH7N+BPSuaRqNP5MWneZrEzQaTQfxazHtQClVopSq91Be2MhTHfA4BDQc9R5nVWRhsx/dvKWjYR6OEI+YkBi3BTLBpmCPIRK+wFZvY2fRTsYljWtSF2QKIswc5rbTY05lDvWqnpSI5tepJlgT3DzThdWF5FXmMSx2GGCI6Za8/1vzt7a4w2FYcOc80z9m/YhJTC3m0G4Ld955Z+uNNBpNl9DS0zFNYKDn2MClZyigDiIiH7alnVKq57hNu5hTUk7ho70fAUZ4goP07HRO7neyxz4/ZP3QprH9IZPHrqJdpESkNLu9tyPUw7EV+pa8LYxJGINI8wsoG4vpn3J/YlziOIJMxheK2NDYFtPjbS/czol9mo9t70zMtFKK9dnrOT75eO2Z1mj8mM5mXdJoNL7D3z3TvwbGAAWtHL2GRGuicwc/s8lMdK0hGl3DFFw90+uz1rMpZ1Oz42UUZ/D+nvcpqi5izSEjpXdMiLGp5E1jb/K6/Z1lS/6WFr3AjRchbslruT0Y3n5XMb0tfxtjEo+GhcSGtBwzvb1gOyPjRzZb35mY6YNlB6m31zM2cWynPdP/+Mc/OtVfo9F0nOtHX0+f8D7cPUlnfAhU9BwbuPi1Zxp4CiON3WTgFWCJUuqQb03yLSLiJpbjauIosZRwsOwgX+3/iinHuOdSTs9J9ziOUoqquio+32+k0/4s8zPqGyJp+kcYm066bj7SU/g57+dm0wVCw8YtLqLz5/yf+f2437c4ZoI1gYKqo19GthduZ/rQ6c7zuNC4Zt/HClsF2RXZpMU0Hw/Zlpjp93a/R1ltWZNthjfmbGRSn0lEh0STU5nT4hgajabnkhiWyBeXftHiUzKNRtMz8WvPtFJqDpAKzAYmAbtF5DMRuUxE2qX0ROQ2EUkXkRoRWdJMmwdERIlI0909egiN8z2H1Ic4X+8u3k2dva7VDUaUUry35z2Wbl/qLHPdOTAlMoUrh1/pJYu9y5b8LW5e48a4btxSZ6/jl8JfGJ0wusUxXcM8lFL8UvALI+JHOOtbyuaxo3AHx8Yc2+IXj7bETKfnpLOjsGlq8x2FOxgZP5IoS1SnPdN/+MMfOtVfo9F0Di2kAxs9xwYufi2mAZRS9UqpD5VSFwGDgK+Bh4HDIhLRjqGONPRb7KlSRAYDl2FsFNNjaSymG58XVhfyxb4vWhyjoLqgWS9namQq0HTTlp5ASU0J+VX5DI5uPkdrdEi0M7Z4b/FeksOSW90a3VVMO96X5LBkZ31LYrq1EA8wPNOtiek9xXvIq8prUr6raJexcUxIVKdjpq1Wa6f6azQajaZ59BwbuPi9mG5EOMYW4xFAOe1IAqeUWq6Uep/mY6z/D/gz4HfZQYbGDHW+zq/KJ6sii4xiz1tkA02EoSMGG2hRqDbm+uuvJykpidGj3T2/zz//PMOGDWPUqFHMmTOnzeO1xvaC7QyPG+5cGOgJ1zCPbQXbWvVKgyGWS2pKqLfXO73Srh6kuNC4Zhcgbi/Yzqj4US2OH2YOa3EBol3ZySzJbJLrWinFzqKdDI0dSrTF8+6O7eGpp57qVH+NRqPRNI+eYwMXvxfTImIVkWtE5BvgZ+AY4BqlVJpSqsJL17gcqFVKfeqN8boUD08JT+9/OkNihgA4Bdk3h75pdgiHMIwPjeeG0Te4eVZbiv1tzLXXXsuKFSvcyr7++ms++OADtmzZwrZt29q1vapd2Vus31+6n0HRg1ps47pxy7b8tonpYFMwUSFRFNUU8UvhL4yMc/c0OwS6J/v2FO9hSOyQFsdvzTN9uPwwgjQR0zmVOYQEhRBvjfeKZ1qj0Wg0Gk378WsxLSILgGzgj8CbQD+l1FVKqZVevEYE8CjQpgSRIjKrIfY6va6u5djkrqBxWAeAJcjiFHQOIdlSbF5xtdFmXOI4LEEWxieOZ0LSBK4cdqWbl7o1Jk+eTFycezjI/PnzueeeewgJMcZJSmrbzoklNSXcuvLWFtNH7S/dzzGRx7Q4jmts8baCba16jR04Qj0ax0uDsRAz3BzeJGbZruzsL93PwKiBLY7tENPN3dve4r2MTxpPua0cW/3RfOE7Cw2vNDS/VXp7mDVrVqf6azQajaZ59BwbuPi1mAZuBIow4pinAq+KyIeNj05e40FgmVIqsy2NlVILlFKTlFKTgoO7P1mKJzENhtgCWhRc2RXZzP/vfPaW7AWO5pMODQ7lxL4neiW/9K5du/j222858cQTOeOMM9iwYUOzbRcsWMCkSZOYNGkSBWUF/HDkBz7f93mz7feX7ueYqJbFdHRINCW1JdTW15JRksGwuGFtsjvBmsCR8iNsyd/iUYB72gUxpyKHCHMEEZaWQ/eDTcEESzA19TUe6/cU72Fo7FDiQuPcUhw64qUBr3im4+PjW2+k0Wg0mg6h59jAxd/F9KsYCw7z6bo80+cAt4tItohkY2QPeVtE/tzJcbsEEXFuSOKKY5Fdha2i2XCJ9/a478buyCfdmM6I6rq6OoqKivjhhx948sknueKKK5r1yM6aNYv09HTS09PBDLMnzubJ9CebDYloi5iOCYmhpLqE3UW7SY1MxRrctgUhCdYEFm9dzMj4kfSL6NekPjk8mawK97WpmaWZDIwe2KbxW4qb3lO8h8Exg0m0Jl4ryjIAACAASURBVJJXeXQRoquYDg0KRSlFdV11m67nib///e8d7qvRaDSaltFzbODi13mmlVLXemssEQnGeD+CgCARCQXqMMS0a16zDcBdwGfeurY3EYSLBl/ElpItbuVBpiDCgg3BVmGraJLBwpPAtgRZPF7j2JhjO2xf//79ueSSSxARTjjhBEwmE/n5+SQmJrbYr6a+hunDprPm0Bo2ZG9gcv/JbvU2u43simz6R/ZvcZzYkFgOlR/ivT3vtTnEA4zdJD/c+yHLpi7zfF8R/TlU5p7ifF/JvlZDPBy0FDe9t3gvV4+4mgRrgltGj51FO7lxzI3A0S9RpbWlhAaHtumaGo1Go9FoOo9fe6ZFJExErnQ5f1FEFrscC0TE877STfkLUAXcg7ERTBXwF6VUgVIq23EA9UCRUqrc2/fTUWYMn+EmfM1BZoJV0+9JDk9zYXUhtfW11NvrnXWum4ac2f9MLh96ebPX68y2txdddBGrVq0CjJCP2tpaEhISWu1nMVkIDQ7lhD4nsD5rfZP6I+VHSAxLbPYLgIP+kf25fcLt/Jj1I8f3Ob7NdieHJXNy35MZnzTeY31qZCoHyw66le0rbbuYDgsO87hxi13Z2Veyj7ToNLcUfdV11RwpP0Ja9NEFoZ3NNX3dddd1uK9Go9FoWkbPsYGLX4tp4HrgCpfz32Fk80hsOM4HbmvLQEqpeUopaXTM89BuoFLqq86b7j1iQ2Od4relhYWO8IySmhJsdhtb8o96rx2bsiSHJTMifgQJ1tYFbmvMmDGDk08+mZ07d9K/f38WLVrE9ddfT0ZGBqNHj+bKK69k6dKlbdqowBGOcWLfE1mf3VRMtyXEA4z35/Khl/PRxR8xbfC0Nt/LZUMv49mznm22vn9k/6ZiumRfm8M8mvNM51bmEmmJJMwc5iam9xbv5ZioYzAHHX1o4ppDuyOkpqZ2uK9Go9FoWkbPsYGLX4d5AFdibCnuyk1KqQwAEZmBkYXj8e42rLtpS+xvuNlw0lfYjIyBrvG1h8sOA3iMt+4ob775psfy1157rd1jOUIXRseP5kDZAUpqStxsbauY7ighQSEtZjJJjUzlULl7mEdmaWarqfocNBczfajskDN0JdGayI4iYxfEnUU7GRbrvniys57phx56qMN9NRqNRtMyeo4NXPzdMz0E2OVyXowRhuEgHXDPYxagKJf9aaqqDA+nvdY9Dtohpstt5U36OIRgorXl2GVf4fiyYA4yMz5pPOnZ6W71XS2mW8MR5uEIgam0VVJUXUS/8KaLFT1hDbZSZWvqmT5Ufoj+EYaYTgg76pneWbizSSYSnWvaP2kuA49Go9Fo/AN/F9NRgFMxKqVSlVL7XeqDcV88GLAEydFd/5RSmM1mclbkkFyXjKo3BF5jz7RDvBVWFzq3yW5tAR+4i/DuIjTo6KK6E/qcwI/ZP7rV7y/dz4DIAd1tlpNISySWIAuF1YUAHCg7QGpkaou7MboSFhzmMczD1TOdYE0gv9IQ066ZPBx01jN99dVXd7ivpuP86fg/+doEjUbTDeg5NnDxdzF9EBjTQv24hjYBT7ApmFvH3wpAWFgYc+fOJfHMRPpF9KNwVSHVh6oJDzbEtGOh286inQBuuZubS4fna1zjqgdHD26SOSOrIouUyJTuNsuN1IijixD3Fu9tc4gHgNVs9RzmUe4e5pFfne+2jbgrnY2ZHjasbTm3Nd7Fm6FVGo2m56Ln2MDF38X0J8C8hjR2bjRk8XigoU2vJDgqmOgTo4k8LpKqvVWoHxWJVYn/z955x0dZbP//PdlN3/QACS0JxBAITboVRIrAVRCUK0XlouJVpIheG/yEK2K9FgREAS+gAvpFUEQply4IoghIM6C0JJBO2qaX+f2xxU3fTTZsyrxfr3nts8/MM3t2CbOfPc+Zc9AX6ktl5DBVRQRwEvX/T8LH1aeUzVJKErMTCfIIcqBVBq++KVzmfPp5cwl3a6jSM20M8whwDyA1N5X47HhzGXFLauuZ/n//7//V+FpFzbG8q6RQKBovao1tvNR/5VQ1rwO+wFkhxL+EECON7XkgGkMYSJPPku4S6ILv7b543uBJr9Re9EvoR076X15QnbOhQt897e8pd+2UrvWv/Kmfm18pMZ2en46zxhkPZw8HWlU6Pd4f6X8Q7md9Pm53rXuFqfHisuJo42XYAe6qcaWdTzue2v1Uuc2HYPRM56uY6YaGEtMKhULRsGnQYlpKmQTcDJwB3gC+NrbXgFPArcYx1SKEeEoIcUQIkS+EWGVxvp8QYocQ4poQIlkIsV4IEWz3N1MHPNjpQfNxsC4Yt1Zu/NLuFxLdE8k+lE3WsSwKsgvQF+oRCII8y3t2tU5ac6y1qd8RMdOW+Lr6kp73l5hOyE6o0PbrTWuvvwq3/JlmqFpoLR7O5T3TOYWGAjuWaQrXjFjD6PDRjIkYU24OLxcv8+bSmvDAAw9UP0hhd6yNq1coFA0btcY2Xhq0mAaQUl6WUg4DAoF+xtZMSjlMSnnRhqmuAq8C/y1z3g9YBoRiyGGdBaysrd3XA8sqh50DOwOgc9Pxp/efZPXJQrgIMvZlEJUWhY+TT6UeMlO2gfqSdcDLxYucohwKSwoBSMxxfIgHQAf/DvyW/Bs5hTkk5ybbtCHSXVs+ZjpOH0crXatS8eKuGlcmdprI4JDB5ebQOetqJaa7d6+4IE1tKFtpU1GehhBapVAoak9drLGK+kFDzzNtRkqZBpSv5mH99RsBhBC9gNYW50uVDRdCLAb21fR1rjcaoaFYFptjpM0ZPWQ2uigd6c3Tcf/Nndsv306uZy5uoW4Ip/ohmivDSTiZ44MD3QPrjWe6k38nCooL+N/l/xHqHYrWyfr/XhXFTFtm8rAGT2fPWonpF154ocbXVkZtqmU2FSx/xA4LG+ZASxQKRV1SF2uson6gXCK2cztw2tFG2IrJ+1U2PV62JpsjzY5wIfwC+Yn5pO1OI/9qPlJKWni0ABwf1lERvm6+5s129UVMCyG4s+2dLD+x3KYQD6g4ZtpWMa1z0ZFdkG3T69Y1JbKk+kFNHEvP9HO9n3OgJQqFQqGoCUpM24AQoivwMlBpYlghxBRj7PWRoqKi62dcJYztMJYHIh8wizsPrWGTnimkwOTJ1Hpr8b3JF11XHdlns0nfn04Plx6OMdoKfF19SctLAyAhp36IaYDBIYOJyYrhBj/rM3lAxTHTpjAPa6ltmMeYMeXjsGtLffwhVt+wFNOW8fEKhaJxURdrrKJ+0GjCPOoaIUQ4sBWYIaXcX9k4KeUyDDHWeHp6OlxJ+Ln5lXpezjNtfDSdd2nugl8zP/Lj8tn0zSaCg4MpDCmEcskHHYuva2nPtMmL7mi6NetGgFsA7X1q4JkuGzOdFcfNLW+2eg4PZw+yC7NrHFpx00031ei6qlCe6epRMdMKRdOgLtZYRf1AreJWIIQIAXYC86WUnznantpQVkybinzoXHTmMUII3Nq48dRTT9G6dWvi98ST9VsWBbkFAET6RV5nq8vj6+pLWr7BM52YnVhvPNMaJw0fDvqQW1rdYtN17lr3cp7p2KxYc1o8a3B2csbZybnCfNXW8Oyzz9bouqpQMdPVc2PzG/Fz9ePOtnc62hSFQlGH1MUaq6gfKM+0ESGEFsPnoQE0xkIwRUALYDewREr5kQNNtAvuWncA8oryAMwp5vxc/QjyDCIhO8E8VqvVcsstt3DO/RzJZ5L54/s/cG3nikcnx+ZzBkPMdHp+OiWyhKScpHrjmQboFNDJ5mvKbkAskSVc1V+lpa6lTfPoXHTmH0r1gRKUZ7o63LXu7P37XuWhVigUigaKWr3/Yg6QC7wATDQezwEeBdoBc4UQelNznJm1w1XrCkBecR5FJUVkFWYBhup5rhrXCq/RuGrQddYRflc4xVnFLFq0iF9//ZWSEscJJVOYx7W8a3g6e+KmrWdxKDZSdgNiUk4SPq4+5h8/1lKbuOl77ilftKe2KM+0dTRGIb127Vp69eqFTqcjODiYYcOGceDAAQBCQ0PZuXNnhddZ9oWGhuLi4kJKSkqpMd27d0cIwaVLl8zj3N3d0el0+Pn5MWLECGJjY8vNaxpjak899VS5vqCgICZNmoReX/X/o4kTJxIcHIy3tzcRERGsWLHC5s+oKVDZv3V6ejpPPPEEQUFBeHh40KVLF1auLJ119sCBA9x88834+Pjg7+/PLbfcwi+//GLuj4+P55FHHiE4OBgvLy8iIyOZO3cu2dl/ORSklLRr145Onco7OQYMGICbmxs6nY7AwEBGjx5NfHy8Hd99aepijVXUDxrfCl5DpJTzpJSiTJsnpfy38Vhn2Rxtb03RCA3OTs4AJOcmA+CucUfjpKl2s5izpzPevbwZN24cp06dYunSpZw9e7ZSwTR58mSaN29O586dy/X95z//QQhR7kvSWvxc/UjLS6tXIR61QeeiI7Mg0/xZ2prJw4Sns2eNPdN33mn/MAMVM900effdd5k5cyYvvfQSiYmJxMTE8OSTT7Jp0yab5woLC2PdunXm5ydPniQ3t3wo0+bNm9Hr9cTHx9OiRQumTZtW6RhTW7x4cbm+48ePc+zYMV5/veriuS+++CKXLl0iMzOTb7/9ljlz5vDrr7/a/P6aIgUFBQwaNIjLly9z6NAhMjIyePvtt3nhhRd49913AcjMzORvf/sb06ZN49q1a1y5coW5c+fi6mpw+ly7do2bbrqJ3NxcDh06RFZWFjt27CA9PZ3z58+bX+uHH34gKSmJCxculBLiJhYvXoxer+fPP/9Er9fXaShGXayxivqBEtNNEDeNwYsbnRoNQEGJIRbaWi9iy5YteeihhxgyZAi7du1i9erVXLlypdy4SZMmsW3btnLnY2Nj2bFjB23bWl/UpCw+rj5k5GcQkxVjcyhEfcTLxQsfVx9zOfLYrFha62wX07XxTM+YMaNG11WFyubR9MjIyODll19myZIljB49Gk9PT5ydnbn77rt5++23bZ7vwQcf5NNPPzU/X716NQ899FCl493c3Ljvvvs4c+ZMjewPCgpi6NChHD9+vMpxUVFRZmEnhEAIUUrEFRUVMX/+fEJDQwkICGDt2rW89dZbLFiwoEZ2NSY+++wzYmJiWL9+PWFhYTg7O3PXXXfxwQcf8PLLL5OZmcm5c+cAGDduHBqNBnd3d4YMGULXrl0Bww82Ly8vPv/8c0JDQwFo06YNCxcuNI8Bw9/LyJEjGT58OKtXr67UJl9fX0aNGlXtv3ttqIs1VlE/UGK6CTE0dCiAOZwjOs0gpk2izbLISAe/DlXOJYTghhtu4J///Cddu3blyy+/5KuvvuLatWvmMbfffjv+/v7lrn366ad56623SlX2sxU/Nz/S8tM4lnSMbs261Xie+kRUQBRnUg0CIE4fZ9PmQxOezp7oCxpsFJKiEXDo0CHy8vK499577TJfv379yMzM5Pfff6e4uJgvv/ySiRMnVjo+JyeHL7/8kn79+tXo9eLi4ti6dSvh4eHVjn3yySfx8PAgMjKS4OBghg8fbu6bM2cO+/bt47fffmPVqlXMnz+fVatWMX369BrZ1ZjYsWMHw4YNw9PTs9T5MWPGkJeXx6FDh4iIiECj0fDwww+zdetW0tLSSo3duXMno0ePxsmpchmTk5PDV199xYQJE5gwYQJffPEFBQUFFY5NTU1l48aNVv27K2xDCLFXCJFnESp71qLvTiFEtBAiRwixx5jwwdQnhBBvCiFSje0tYSEchBChxmtyjHMMut7vzYTagNiEMOWaLhtfbCo1bsr0AXBnyF+3o3xcfcgrzqvQy+jk5ESPHj3o3LkzP/30EytWrKBLly70798fD4/yGxW//fZbWrVqRbdu1QvgZcuWsWzZMgCSk5NL9Zk808eSjjGi34hq52oIdAroxOnU09wVdhdxWXHc2upWm+fQudTcMz1s2DC2bt1a/UArcBJOKsTjOtFldZfr8jonHz5p1bjU1FQCAwPRau339WLyTvfv35/IyEhatSqff33UqFFotVr0ej3Nmzdn+/btlY4x8fbbb/PYY4+Z+4QQ6PV6Bg4cyL///e9q7frwww9ZtGgRhw4dYu/evWZPdWZmJu+//z5nzpzBx8eHvn37Eh0dzYIFC/Dy8qrpx2A1M2fOrFMPKxji1t9///0aXZuSkkKvXr3KnddqtQQGBpKSkoK3tzcHDhzgzTff5LHHHiMhIYHhw4ezfPlyWrRoQWpqKsHBwVW+zsaNG3F1dWXIkCEUFxdTVFTE999/X+qH3vTp03nmmWfIzMykW7du/Pe//63Re7IGe66xDZCnpJSlNhYIIQKBjRj2pm0G5gNfAqZfwlOAUUA3QAI7gAuAKRnEOuAQMNzYvhJC3CClLC0YrgPKM90EKbvZycvFsLi39Kw4XGJ42HAejnq4yjldXFy4/fbbmTp1KlJKFi9ezIEDBygsLDSPycnJYcGCBbzyyitW2TllyhSOHDnCkSNHaNasWak+P1c/EnMSuZx5mU7+tmfPqI90Cuj0l2e6hjHTOueaZ/O4++67a3RdRTippaXJEhAQQEpKCvYsWvXggw+ydu1aVq1aVWmIxzfffEN6ejr5+fksXryY/v37k5CQUOEYUzMJaVNfVlYWe/fuJTo6utR+jjVr1pg3LQ4bVrrku0aj4dZbbyUuLo6lS5cCsHv3biIiImjXrh1giBH28fGpMI67KRIYGFjhRr+ioiJSUlIIDDQUL+rYsSOrVq0iLi6OU6dOcfXqVWbOnAkY/s6q2yy4evVqxo4di1arxdXVldGjR5cL9fjggw/IyMjgxIkTpKWlERcXZ6d3WR57rrGNhNHAaSnleillHjAP6CaEMOXffRh4R0oZJ6W8ArwDTAIQQkQAPYC5UspcKeUG4CRgdWUcIYSrECJMCNFJCNGs+isqR3mmmyBlxbS3izcA4X7h7IjZUS522lnjbPXcnp6eDB8+nL59+7Jr1y62b99OXl4eJSUlnD9/nosXL5q90nFxcfTo0YOff/6ZoCDbNhF6u3iTV5RHzxY9bbKvPtMpoBO/p/5OiSwhTh9Xo5jp2oR5PPnkkzW6riL83PxIzk0udbdDUTdY6zG+Xtx00024ubnxzTffcN9999llzpCQEMLCwtiyZQuffPJJlWM1Gg2jR4/m8ccf58CBAzbb0L9/fyZNmsSzzz7LN998A2AOE6iKoqIic8z01atXadnyL+fEsmXLaNWq1XXxSgM19hhfLwYNGsRLL71EdnZ2qVCPDRs24OrqWmGITmRkJJMmTeLjjz82z/H1118zd+7cCkM94uLi2L17Nz///DMbNmwADA6dvLy8UoLdRJcuXZgzZw5Tp07l6NGjtQpDrAx7rrENkNeFEG8AZ4HZUsq9QBTwm2mAlDJbCHHeeD66bL/xOMp4HAVckFJmVdJfIUIILwwZ28YBfQBnQABSCHEV2AYsk1KW361aBcp91ATp37q/+fgfUf9A46Sx6jpbNpMFBAQwduxYhg0bRm5uLh9//DHu7u4kJiZy6dIlLl26ROvWrTl69KjNQhoMxVG8Xb25sfmNNl9bX/F380fnomPV6VVonbQ1Ki1dX/JMLx20lN5BvflkaNXCR9H48PHx4ZVXXmHq1Kl888035OTkUFhYyNatW3nuuefM4woLC8nLyzO36jzZn3zyCbt37y4XZ1sWKSWbNm0iLS2Njh071ug9zJw5kx07dlQaKpGUlMQXX3yBXq+nuLiY7du3s27dOgYOHAhA69atOX78OPHx8Rw+fJjPPvuMpKSkSuN1Gztl/60ffPBBWrduzf3338+lS5coLCxk+/btTJ8+nXnz5uHj40N0dDTvvPOO2VMcGxvLunXrzEJ71qxZZGZm8vDDD3P58mUArly5wqxZszhx4gSfffYZERERnD17luPHj3P8+HHOnTtH69atS2WHseThhx8mKSmJb7/99vp8MI0DrRDiiEWbUsGY5zGkGG6FoUL0ZiFEe0AHZJQZmwGYfnWW7c8AdMa46equLYcQ4mngEjAZQ8jISKA7EAHcBMzF4GTeIYTYJoS4oao3bokS00aEEE8Z/xDyhRCryvRVGiDfEPFw9uCJbk/wRLcnysVPe7t4282bOG7cOMaMGUNSUhL//ve/mTt3Lp999pnd8nj6ufrRo0UPu8xVX4gKiOKj3z7ig4Ef1MgzonPWmXOH28qgQfbbu9HBvwP/HfpfogKqdBIoGimzZs3i3Xff5dVXX6VZs2a0adOGxYsXM2rUKPOY4cOH4+7ubm7z5s2rcs727dtXGGdr4u6770an0+Ht7c3s2bNZvXo1UVFRFY4xtco2STZr1oyHHnqI+fPnV9gvhGDp0qW0bt0aPz8/nn32Wd5//31GjhwJwF133cWQIUPo2LEj48aNY+PGjXTv3t0stpsaZf+t58+fz86dO2nTpg19+/bF29ubWbNmsWDBAv71r38B4OXlxeHDh+nbty+enp7069ePzp0788477wDg7+/PwYMHcXZ2pm/fvnh5eXHnnXfi4+NDeHg4q1ev5sknnyQoKKhU++c//1lpVg8XFxemT59e6b97bbHnGluPKJJS9rJoy8oOkFIellJmSSnzpZSrgR8xxDjrAe8yw70B05dY2X5vQC8Nt8+ru7Yibgb6Syl7SynnSym3SylPSin/lFL+LKX8r5TyH0AQ8C3Qv4q5SiFUUQUDQojRQAkwFHCXUk4yng8EzlM6QP42KWW1W8U9PT2lZfL4+sCHxz+stO/J7k+SX5yPlLLCIijrz60nOSeZJ7vX7FZVcXExR48e5YcffqBdu3bccccd+Pr6WnVtr169OHLkSKlzZ1LPEOEXUSoLSUPn10RDntqeLXrW6PrvL3zPvth97H5md7nPqzqWL19eKoZUoVAoFPajMa6xQogcKaVNHjghxFZgK5AHPCylvMV43hNIBnpIKaOFEAeBlVLK5cb+ycAUKWU/Y8z0CaCZKdRDCPEDsNYR1aobjwqpJVLKjQBCiF6AZbCqOUDe2D8PSBFCREopo6+7oXWEKdNHZVUQAbSidn8uGo2G3r1707VrVw4ePMiyZcvo3r07t912G+7utlX6g5qV7a7v1FREm6hNnunGtsgrFApFfaIprrFCCF+gL7APKAL+DtwOzASuAW8LIcYA3wMvAycstNWnwCwhxBYM2TyeARYBSCnPCSGOY6hOPQcYBnTFtg2IQRi81c0pE6khpazc81gBSkxXT3UB8o0CUw7q6sYUFNc+5s/V1ZU77riDXr16sXfvXhYvXswtt9xCnz597JpOqylSX2KmFQqFQqHAsMHvVSASKMagm0ZJKc8CGIX0YuBz4DDwgMW1H2OItTbtsl5hPGfiAWAVkAbEAPdZmxZPCDHROJ8wXm8ZpiEBJabtjA7DbQdLKg1yNwbfTwFD/FVjwsPZAw/n8rmja4qXlxd33303/fr1Y+fOnfzyyy8MHDiQzp0718lO6qZAbWKmBwwYwN69e+1rkEKhUCiAprnGGsVt7yr6d2IQ2hX1SeA5Y6uo/xIwoIamLQDeAl6RUtY6j6cS09VjU5C7Mfh+GRhipuvWtMZBs2bNGDduHJcuXWLHjh0cOnSIwYMHExYW5mjTGhyezp5kF9TMMz1p0iT7GqNQKBQKM2qNrVd4A6vsIaRBZfOwhtMYqu8A5gD59sbzDY6+wX0dbUKlhIaG8uijj3LLLbewefNm1qxZQ2JioqPNalDUJmZaLfQKhUJRd6g1tl6xBrBb+WTlmTYihNBi+Dw0gEYI4YYhWP5rqg6Qb1D0bNGTw/GHHW1GpQghiIqKokOHDhw5coRPP/20ynRYitJ4uniSXZiNtgb/tQsLC3F2bhwFcBQKhaK+odbYesUs4BshxJ0YYrILLTullNaVajaixPRfzMGQsNvERODfUsp51QTIK+oArVZLv3796N69OxkZGURHRytRbSVatERH2/5bb/DgwU0unk+hUCiuF2qNrVc8DtwFpADhlN+AqMR0TZBSzsNQF76ivkoD5BV1i5ubG25ubkRGRtqcN7kpU5MfHo8++mgdWKJQKBQKUGtsPeP/Ac9IKd+zx2QqZlqhUAAwceJER5ugUCgUjRa1xtYrNBiqHNoFJaYVCgUAOTk5jjZBoVAoGi1qja1XrAQm2GsyFeahaBBMmTLF0SY0KGryeQ0fPlzF8ykUCkUdodbYeoUH8KgQYiiGsuRlNyBOt2UyJaYVDQIlpm2jJp/XE088UQeWKBQKhQLUGlvP6AgcMx6X3RNnc40QJaYVCgUAf//73x1tgkLR5Ll48SL5+flERqo9740NtcbWH6SUd9hzPhUzrVAoAMjIyHC0CQpFk2fEiBF07NiR3NxcR5uisDNqja2fCCF0QghdbeZQYroJMrbDWEebUCHbtm2jQ4cOhIeH88Ybb5TrT0tL495776Vr16706dOHU6dOOcBKx1Kbzyg0NJQuXbrQvXv3ClPnjRw5sk5tVygU1fP7778DsGXLFgdborA3ao2tXwghZgohYoAMIEMIESuEeFoIIWydS4lpKxFChAohtggh0oQQCUKIxcaqiQ0OF42Lo00oR3FxMVOnTmXr1q2cOXOGdevWcebMmVJjXnvtNbp3786JEyf49NNPmTFjhoOsdQz2+Iz27NnD8ePHK8zZPX26TfstFAqFnSkuLjYfr1+/3oGWKOqCpr7GCiFuEELkCSE+tzh3pxAiWgiRI4TYI4QIsegTQog3hRCpxvaWpdA16rI9xmujhRCDbLDlLQy1RT4GBhvbRxiqXL9p63tTYtp6PgSSgGCgO9AfeNKhFjUifv75Z8LDw2nXrh0uLi488MADbNq0qdSYM2fOcOeddwIQGRnJpUuXSExMdIS5DqGuP6PRo0fb3WaFQmE9lqnTNm/erFKpNTLUGssS4BfTEyFEILARQwEVf+AI8KXF+CnAKKAb0BX4G4bKhSbWYdhEGADMBr4SQjSz0pZHgUelycfJqAAAIABJREFUlAuklLuNbQHwGPCIrW9MiWnrCQP+T0qZJ6VMALYBUQ62yS6MjxzvaBO4cuUKbdq0MT9v3bo1V65cKTWmW7dubNy4ETAIy8uXLxMXF3dd7XQktf2MhBAMGTKEnj17smzZsnLzp6Sk1KH1iur49ttveeaZZ5DS5o3kikaCXq8HDBvVcnJy+OKLLxxskcKeNOU1VgjxAJAO7LI4PRo4LaVcL6XMw+Ap7iaEMO2+fRh4R0oZJ6W8ArwDTDLOFwH0AOZKKXOllBuAk8AYG8w6Uck5m7WxEtPWsxB4QAjhIYRoBQzDIKhLIYSYIoQ4IoQ4UlRUdN2NtAUfVx8AfN18HWwJFQqIsmFLL7zwAmlpaXTv3p1FixZx4403otU2yEibGlHbz+jHH3/k6NGjbN26lSVLlvDDDz+Uuva+++6zq707d+4sJ/YVlTNt2jTeffdd9u3b52hTFA7CJKZHjBjBjTfeyOuvv059/x5RWI+919h6gtakeYytXF5WIYQ38ArwTJmuKOA30xMpZTZwnr8claX6jceWfReklFmV9FfHp8DUCs4/AXxm5Rxmmo4SqT37MLj/MzGUoVwNfFN2kJRyGbAMwNPTs166mEyiTGBzjH2d0bp1a2JjY83P4+LiaNmyZakx3t7erFy5EjC8h7CwMMLCwq6rnY6ktp+RaWzz5s259957+fnnn7n99tvN1z7zTNl1rnYMHjwYf39/UlNT7TpvY6WkpASAzz//nAEDBjjWGIVDMIlpLy8v5syZw5gxY1i9ejWPPGLzXWdFPcTea2w9oUhKWX5He2nmA59IKWPLOIB0QHKZsRmAl0V/Rpk+nTFuumyfqb+VlXa7AuONRVt+Mp7rC7QE1gghPjANtKaAi/JMW4EQwgnYjiG2xxMIBPyoQZB6fcC0AbEGG1brjN69e/PHH39w8eJFCgoK+OKLL7jnnntKjUlPT6egoACAFStWcPvtt+Pt7e0Icx1CbT6j7OxssrIMP+Czs7P53//+R+fOnUtde/fdd9vd5mvXrtl9zsaKSUx/9dVX5OXlOdgahSMwiWmdTse9997LzTffzIsvvkh6erqDLVPYg7pYY+s7QojuwCDgvQq69UDZL3FvIKuSfm9ALw0ewequrY5I4CgQD4QYW4LxXEegi7F1rmwCS5SYtg5/oA2wWEqZL6VMxVDXfbhjzaoZ7lp3nuz+ZL3yTGu1WhYvXszQoUPp2LEjY8eOJSoqio8++oiPPvoIMKSMioqKIjIykq1bt7Jw4UIHW319qc1nlJiYyK233kq3bt3o06cPI0aM4K677io1f0JCwnV/T4q/0Ov1dOrUiYyMDJUWrYliKaaFECxatIiUlBTmzp3rYMsU9qCJrrEDgFAgRgiRADwLjBFCHAVOY9hcCIAQwhNobzxP2X7jsWVfOyGEVyX9VSKlvMPKNtCa+YTa7GIdQogLGMI3/oPh9sJKIEdKOaGyazw9PWV2dvZ1stB2voj+gmt513iyu0pKooABAwawd+9eu81nuvOh1pjqkVKi1Wp57rnnWLVqFd26dWPbtnJbMhSNnPXr1zN27FhOnjxpvnM0bdo0lixZws6dOxk40KrvdUU9xd5rbH1ACJEjpfSsot+D0h7kZzGIa1Nt9T+BycD3wL+B/lLKfsZr/wnMwODZlsAOYJGU8iNj/0/AAWAOhn1sK4EbpJRlQ0eqew86ACml3pbrLFGeaesZDdyFIb7nT6AIeNqhFtWS+uSZVjieF154wW5zmUIWQIlpa8jLy6OkpARfX19mzJjB9u3b+eWXX6q/UNGosPRMm3jzzTeJiIjgoYceatLZIBoD9lxjGwpSyhwpZYKpYQjPyJNSJhtF7xhgAZCGIWb5AYvLPwY2Y8jScQqD4P7Yov8BoJfx2jeA+2wR0qpoiwOQUh6XUg6QUvpJKQOllPdLKZMcbVdtqE8x0wrHUzbsozZYimlVQrd6LEXU1KlT8ff3Z968eY41SnHdqUhMe3h4sGbNGlJSUhg9ejT5+fmOMk9RS+y5xjZUpJTzpJQTLZ7vlFJGSindjRrrkkWflFI+J6X0N7bnpIV3Rkp5yXiNu5Syg5Ryp7V2qKItCrsxOGQw97S/p/qBiiaBZaaQ2mJZya1slUZFeUybQ3U6HV5eXjz//PNs2bKFrVu3OtgyxfWkIjEN0LNnT1auXMn+/fv5xz/+odLlNVDsucYqao0q2qKwD35ufrT2au1oMxT1hAcffNBuc1l6po8ePWq3eRsrZUXUzJkziYiIYPr06SqzRxNCr9ej0WhwdXUt1zdu3DjefPNN1q1bx7hx48xZexQNB3uusQq7oIq2KBQK+zJnzhy7zWXpmS5bHEZRnrJi2sXFhcWLF/Pnn382yTjLpoperzdn8qiI5557jnfffZevvvqKQYMGNdXsEA0We66xilqjirYo6j/JOclczrxMcm4ymfmZlFBCiSzBQ+uBl4sXOhcdvq6+NHNvhp+bH05C/a5zNIMGDbLbXJZieuvWreTl5eHm5ma3+RsbFd3eHzx4MNOmTWPhwoUMGTKE4cMbZCZOhQ2YxHRVPP300wQFBfHII4/Qs2dPVq1axeDBg6+ThYraYM81VlFr7Fq0RYlphV0oLinmUPwhtl7cyuH4wyTmJFp9rVZoCfQIpLl7c5p7NKeZRzOauTcj0D2QQPdAmnkYjv3d/JXorkMuXLhAu3bt7DKXKcxj2LBhbN26le+++66xltK1C5XFyr711lv88MMPjB8/noMHD9KpUydHmKe4TlgjpsEQ8hEVFcXYsWMZMmQIjzzyCG+++SYBAQHXwUpFTbHnGquoNaaiLWAo2AKGoi0JGIq2mLAqHZUS04paUSJL+Pb8t6w4uYLLmZfN53XOOsJ9w2nm0QwfVx80QoNAkFuUS1ZBFvpCPdfyrpGcm0xGfgYJ2QkkZFd9y1IjNAS4BRDgHmAW3P5u/vi6+uLr5ouPiw8+robm6+qLl4sXWif1J24tkydPtlsOVJNnesiQIZw5c4YlS5YoMV0FlYlpNzc3Nm3aRL9+/Rg+fDg//vgjrVpZWy1X0dCwVkwDdO3alWPHjjFv3jz+85//sH79el544QWmTZtm9RyK64s911hF7ZBS3mHP+VTRljqkvhdtqS0XMy4y9+BcjiUdA6CVrhUjw0cyqO0ggpyDiI2JJSMjA09PT3MLDAxEqy0tcPOL80nOSSYpJ4mk3CSSspNIyUshJSeF5NxkUnJTSMlNIT3f9pK6Xi5eZpGtc9bh4eyBp7OnuVmeszx207jhpnXDVeOKm8YNV60rrhrXRu0Z37dvH/3797fLXElJSbRo0YIlS5aQmZnJiy++WKoQhaI0H374IVOnTiUhIYEWLVqU6z9y5AgDBw4kICCAnTt30r59ewdYqahr+vfvjxDCZsF16tQpXnrpJTZv3oy3tzeTJ0/mscceU3cy6hn2XGPrC9UVbWkqKDFdhzRmMb07Zjcv7n+RnKIcAt0DmRw+mYQ9CWxYv4E//viDa9euVXidRqOhdevWhISEEBYWRkREBJGRkXTo0IHw8PAKd7GbKCguIDU3tZTATs1NJaMgg4z8DNLz08nMzyQ9P530/HSyCrKQ1t2hsRoXJxdctUaBrXE1C25XjSsuGhecnZzROmnROmnNx5aPpY41zmiFtvSjkxaN0KARGpyE01+PToZH0zmN0JjPlRtr+ej013Mn4YRWaEuds3y0Z97x+Ph4WrZsydKlS7n//vsJDQ1lxIgRfPHFF3Z7jcbEW2+9xfPPP49er8fTs+LvpSNHjnDXXXfh5OTEmjVrVJxsI6Rnz54EBwfz3Xff1ej6w4cPs3DhQtavX09RUREdO3ZkzJgxDB48mL59+1a5vioUNaEhiWkhRJiU8qKVYwXQWkppVT5DJabrkMYqptf8voY3fn4DgB4ePUhbn8bWr7dSVFREnz596NGjByEhIbRt2xZfX19ycnLIzs4mOzub+Ph4Ll++zKVLlzh//jxXr141z+vk5ERYWBiRkZFmgX3DDTcQERFBcHCwzWKvuKSYrIIss9jOLswmpzAHfaGe7MLsKltecR55RXnkF+eTV5xHflE+BSWNOxWVQHDi4YoyBdlOXFwcbdq0YdmyZTz22GO89NJLvPHGG5w8eZKoqCi7vEZj4uWXX+bVV1+lqKgIJ6fK735ER0czZswYfv/9d5555hnmzp2rbuk3Ijp06MCNN95Y6x+diYmJbNiwgfXr1/PDDz9QUlKCu7s7/fr1o2fPntx444306NGDG264AY1GYyfrFdVx9uxZOnTo4Ggz7EoDE9MJGKoorpBSHqpkjB+GyorTgSVSysVWza3EdN3RGMW0pZDukNSBDc9toHnz5jz00EP84x//sPm2ol6v59y5c0RHR3P27Fmio6PNx5aVvjw9PWnfvj3t2rWjXbt2hIWFERoaSkhICCEhIXh7e9v1fVZEiSwhvzif/CKjwC7ONwvu/OJ8CosLKZJFFBYXUigLDc9Liigsqfqx7LnikmKKZTElsqTCx+KSyvtKSio5Lw3ZVIpKiirtAzj58Em7fFYxMTGEhITwySefMHnyZFJTUwkLC+POO+/k66+/tstrNCZmzZrF8uXLzcVbqiI7O5tZs2axbNkyWrVqxWuvvcb48ePLhU8pGh6tWrVi2LBhrFixwm5zXrt2jf3797Nnzx4OHDjAyZMnzTmqXV1dCQ8PJyIigoiICG644QbCw8MJCQmhVatWODs7280OBQwYMKDRxUw3MDHtC8zGUJSlGPgViAfyAD+gE4bNhz8Dr0gpt1s9txLTdUdjE9NbLmzh+f3PA+C635VfP/mVKVOm8P777+Pu7m7X1youLiY2NpY//viDP/74g3PnznHhwgVzy83NLTXex8eH1q1bm1urVq0IDg4mODiYli1bEhwcTPPmzXFxcbGrnY0FKSU/HvyRW2+51S7zXbx4kXbt2rFy5UomTZoEwGuvvcbs2bPZtm0bQ4cOtcvrNBamTJnC5s2biY+Pt/qaQ4cO8dRTT3H06FHat2/P888/z/jx4ysNE1HUf3x8fJg8eTLvvfdenb1GYWEhv//+O0ePHuX06dOcO3eOc+fOcf78eQoLC83jhBAEBwfTpk0b2rRpQ9u2bWnTpo15bQ0KCiI4OFj9vdnAwYMHufnmmx1thl1pSGLahBDCHRgB3Iohk4c7kAIcA7ZLKU/ZPKcS03VHYxLTJ5NPMmnbJApKCsj4JoP0XeksX76cv//979fdFiklCQkJXL582dxiY2OJi4szt8TERCr62/bz86NFixa0aNGC5s2b06xZM3MLDAw0t4CAAAICAuz+I6GpcP78ecLDw/n000/NVb/y8/Pp2rUrJSUlnDx5UuWdtmD8+PH88ssv/PHHHzZdV1JSwubNm5k/fz6//vor3t7eTJgwgYkTJ9KvX78qQ0YU9QspJVqtlpdeeon58+df99cvKioiJiaGP//8k9jYWGJjY4mJiSn1WNaJAYYMNJbiurLHwMBA9ffYCLFGTAshPgfuBDwxpJ57S0q5wth3J7AEaAscBiZJKS8b+wTwBobS3wCfAM9L45e7ECIUWIkhP3QM8JSUcqc935+1qPuCimpJzU1lxp4ZFJQUkHUgC91ZHXuO7XFYRgGTxyQ4OJh+/fpVOKaoqIikpCSuXr1KfHw88fHxJCYmlmonT54kKSmp0s2SAO7u7vj7+xMQEIC/vz/+/v74+fnh7++Pr68vfn5++Pr6mo99fHzw9fXFx8cHd3d3u27qq2tOnTplt2wbptR4ll+erq6uLFmyhMGDB/P888+zcOFCu7xWY8CWlGiWODk5MXLkSO655x4OHjzIsmXLWLlyJUuXLqVFixbcfffdDBo0iNtuu42WLVvWgeUKe5Gbm0tJSYnDYuC1Wq05jK4ipJSkpqZy9epVEhISiI+PL/d47NgxEhISKgxX0mg0NGvWjObNm5dyaJiOLZ83b968UYaY2HONbWC8DjwipcwXQkQCe4UQx4DLwEYMYnkzMB/4EjB9sU8BRgHdMOR73gFcAD4y9q8DDgHDje0rIcQNUsrk6/KuLFCe6TqkMXimpZRM3TWV/Vf2U3ihEP1KPYd+PESbNm0cbZrdKCoqIjU1ldTUVFJSUswtNTWVa9eumfvS0tK4du2a+TEvL6/KebVarVlYe3t7mx9Nx15eXnh7e+Pl5VXu2NR0Oh1eXl7XJR7WnvF8v//+O506dWLdunU88MADpfpmzpzJwoUL+e677xgxYoRdXq+hM3DgQAoLC9m/f3+t58rIyGDLli1s2rSJLVu2mIVNWFgYPXv2pEuXLuYWGhqqYq3rCaZ0kosWLeKpp55ytDm1Ijs7u0LBnZSUVM6pUdk66u/vX6nYLnvs4eFxnd9hzVAx0yCE6ADsBWYAvhg80Tcb+zwxhFvcKKWMFkIcBFZJKZcZ+x8BHpNS9hNCRAAngUApZZaxfz+wRkr5UdnXrWvUKqqoknXR69h/ZT8yV5K8Kpm93+9tVEIaDKLXtCjbQl5eHunp6eaWlpZGRkYG6enp5kfTcWZmJpmZmVy+fNn8PCMjo1TZ7apwdXU1i2tPT090Op35uLrm4eFhfrRs7u7ueHh44ObmhhCCt99+uyYfX4WYKiBWdFv3jTfeYO/evUyYMIEff/xRZffA4Jm2V/U6Hx8fxo0bx7hx4ygsLOT48ePs37+fH3/8kWPHjrFhwwZzCJRGo6Ft27aEhYURFhZGu3btCAkJKbXXwNvbu0HdYWmoZGZmAlyXzdR1jWnDeHV3L6WU6PV6s7C2FNuWx8eOHSMpKYmMjIwK59HpdFYLbx8fH4f9PdtzjW1oCCE+BCZhiE8+BmwBFgC/mcZIKbOFEOeBKCDa+PibxTS/Gc9hfLxgEtIV9F9XlJhWVMqljEu8c+QdAOJXx7Nh9Qa6dOniYKvqD25ubgQFBREUFFSj66WU5Ofnk5mZSVZWFllZWeZjvV5f6aNeryc7Oxu9Xk9ycrI57aCpmYSsre/Fw8ODlJQUu3zRmH4kVJR2q2xVv/3799O2bdtav2ZDRq/XExISUv1AG3F2dqZ379707t2bWbNmAQav4enTpzl16hTnz5/n4sWLXLx4ke+++47ExMRyc3h4eJiFtekxKCiI5s2bl2tqj0HNMYlpHx8fB1ty/RBCmO/ChYeHVzs+Ly/PLLIrE95//PEHP/74IykpKRXum3FxcalQeFvun7Fs9vR69+7d225z1SO0QogjFs+XmTzJlkgpnxRCTANuAgYA+YAOKBuSkQF4GY91xueWfTpjLHXZPlO/Q0rEKjGtqBApJa///DoFJQWkHUjjvSfeY8CAAY42q1EhhMDNzQ03NzeaN29ulzmllBQUFJQS17m5uaVyfZuem5rp+Zo1a3jvvffMoqs2mAR9ZTlsQ0JC+P777xk4cCC33HILO3bsIDIystav21Cpacx0TfD09KRPnz706dOnXF9OTg6xsbHEx8eb9xtcvXrV3I4ePcqVK1fIycmpcG6dTmeOi62oWfYFBgY2yrjYmmLyujYGz3Rd4ebmRtu2ba368V1UVERKSkq50BLL5wkJCfz2228kJSWVymRiiaenZ4UiuzIB7unpWalD4vjx43Tv3r1Wn0E9pEhK2cuagVLKYuCAEGIi8ASgB8r+wXsDJm9z2X5vQC+llEKI6q69rigxraiQXTG7OHj1IMXZxfTL78dDDz3kaJMUViCEwNXVFVdXV/z9/W26dvny5SxatIgZM2bUupBDRRsQy9KjRw/27dvHkCFDuOmmm1i9ejX33HNPrV63oZKVlVUviq94eHjQoUOHKgtLSCnJzs4mOTmZpKSkcs10PiYmhiNHjpCcnExRUVGFc/n5+ZXKomOZTaei876+vo22yEhT9EzXJVqt1uo7h1JKMjMzzX+7ycnJFbaEhAROnDhBcnJyqToIlpicIxUJ7VWrVvHOO++ovSIG7dkeOA08bDppjJk2ncf42A1D3meMx5Z97YQQXhahHt2AtbYaI4RwwxB7HVfmfJSU8nQll5V7QwpFKXIKc3jz5zcByN2Zy7IV5e7YKBohs2fP5rnnnmPTpk2MHj26VnNV55k20a1bN3766Sfuu+8+Ro4cyRNPPMFrr72Gr69vrV6/IWH6Im8oIkoIYY7ZDwsLq3Z8SUkJ6enplYpv08bfmJgYjh07VqVQEULg7+9frfC2POfr69sgUrIpz7TjEELg4+ODj4+PVeEmpljvigR3WTH++++/k5ycbL6bM27cOKKjo5tMdh0hRHNgIPAdkAsMAsYB44GDwNtCiDEYKhO+DJyQUkYbL/8UmCWE2IIhm8czwCIAKeU5IcRxYK4QYg4wDOgKjLHRvnuBhUCaEEILTJZSHjZ2fwb0sGYeJaYV5VhxcgUJOQnkXsplyWNLbPZwKhomTz/9NMuXL+fll19m5MiRtfIAWuOZNhEWFsaPP/7Iiy++yAcffMDGjRt56aWXePTRRxvMLv3akJOTQ0lJSaMVUU5OTua0ktaUUpZSkpOTUyqrjmWWHctzFy9e5JdffiElJcVc1a+i1zfljbdMbWnN4/UMQ0lISACweSO04vpjGetdWSrBsuTk5JCcnEzHjh15+OGH2b59e4P4kWcHJIaQjo8AJwzp8GZKKTcBGIX0YuBzDHmmLdM/fQy0w5C1A2CF8ZyJB4BVQBqGPNP31SAt3stATyllshCiF7BaCLFASrkWsHoDkRLTilJczrzMypMrAeiX3Y/hw4Y72CLF9eLYsWMsWLCAsWPH8tlnn5krF9aEqjYgVoSbmxvvvfceDz74IE8//TQzZsxg/vz5TJgwgQkTJtCrV69Gm1GiMWVxsAdCCHMmGms3ZZpCTyoT3aaWlpbG1atXOX36NNeuXTN/9pWh0+mqFd2mY8sUmD4+PuYsOdYSGxtrTpmpaHx4eHiQlJTEBx98wGOPPcbrr7/O7NmzHW1WnWMUt/2r6N8JVLhhxlic5Tljq6j/EobNjLXBxSTApZRHhBC3AxuFEOEYfghYhRLTCjNSSl776TWKKKLoeBEfv/px9RcpGg3/+te/2LNnD7179+all17i3nvvrXHogbVhHmUxxVHv37+f999/n6VLl7Jw4UKCgoIYOHAgAwYM4MYbbyQqKqrRZI5QYrr2WIaehIaGWn1dUVGROa2lZQ75yh7Pnj3LtWvXuHbtWqWhKCa0Wq1ZWFvmmS97znS8a9cuIiIiavlJKOozpjV2z549vPzyy/Tu3ZshQ4Y42qymTpIQoquU8gSAlDJVCDEYWI0hbMQqlJhWmNkdu5uD8Qcpzilm/uD5eHpanYdd0QhYvHgxQgiWLFlCv379mD17NosXL67RXLaEeVTEbbfdxm233UZaWhpff/01O3fuZNeuXaxdu9Y8b0REBOHh4eYcyaGhoYSEhDS4Cmrp6emA2njmCLRarTm22lZyc3NLie2MjIxSOeQrOo6Jiakyz7yqCtq4Ma2xH330EadOnWLUqFFs27aN22+/3dGmNWUeBErtkJZSFgDjhBBWfwGqCoh1SEOqgJhblMuIr0aQnJ9M0Okgdry1w9EmKRzIjBkzWLRoEQcPHqy0ZHtV7Nq1i0GDBrFv3z67fVFIKTl//jy//fYbJ06c4OTJk+Y8yRWVLw4ICCiVSzYwMNB8S97ULJ/7+/vj5uZmF1tt4ZtvvuHee+/lyJEj9OzZ87q/vsIxmGLDTcIaoEOHDo02nElRmqSkJPr378+VK1fYtWtXg81BbWsFxPqEEMIHuAFDOMd5KWV6jedSYrruaEhietHRRSw7uYyCuAJ2PryTNq0bV5VDRfUcPHiQm2++GTCkaouKisLV1ZWjR4/aHMe5Y8cOhgwZwoEDB7jlllvqwlwzUkquXbvGxYsXiYuLM+ePtcwlm5iYSGpqKhkZGRUWcjDh5uZmFtemW/Blb8lXds703MXFxSb7P/zwQ6ZOncqVK1eazA5/haIpYrnGAly5coXbbruNjIwM9u3bR+fOnR1oXc1oiGJaCNEWWIIhA4jp16vEUJVxmpTyss1zKjFddzQUMR2TGcM9X99DMcXcrb+b16a+5miTFA5gwIAB7N271/x8//79DBgwgPHjx/PZZ5/ZNNe2bdsYNmwYhw4dqpFnu64oLi4mIyODtLQ0czPdpi97zvIWvenWfG5ubrWv4ebmVqXYLvv8k08+4dChQ6SlpTWV3f0KRZOk7BoLcOHCBW699VacnJw4ePBgg6sG29DEtBCiFfALUAJ8CJzBIKg7AU8ah/WWUl61ZV4VM93EkVIy/+B8iinG6YwTryx4xdEmKRzExx+X3nB62223MXfuXObOnUufPn2YNm2a1XPVNma6rtBoNOYMDDWhoKDALLIrEtuVPU9ISCh1XVkeffTRevdZKRQK+1J2jQVo166dOW566NChHDhwgICAAAdY12SYC1wEBkkpLb0jXwsh3gP+ZxzzuC2TKjHdxNkTu4efEn+iOKeY90a9h1ar/iSaKhXlAJ49ezZHjx5l5syZhISEWF2h0NbUeA0FFxeXGm9YM1FSUkJWVpZZXOfl5TXGEsMKhaIMleVZ79q1K5s2bWLo0KGMGDGCXbt2qQQAdcdwYEIZIQ2AlDLHWADmc1snVa6QJkxOYQ6vHDB4oiNTIhl00yAHW6RwJPv27St3TqPRsGbNGnr06MHYsWP5/vvvrZqrpqnxmgJOTk74+PjQpk0bOnfuTK9evdSPWIWiCVDRGmuif//+rF27ll9++YWxY8dSWFh4HS1rUjQDzlfR/6dxjE0oMd2E+ej4R6QWplJ0tYgV01Y42hyFg5k7d26F5z09Pdm2bRtdunRh1KhRrFy5stq5GqtnWqFQKGpKZWusidGjR/Phhx+yZcsWJk2aRFFRUZXjFTUiCaiqZvwNxjE2ocR0E+VC+gVWn16NLJE8Ef4E/r6qZHhT57///W+lfQEBAezatYv+/fszefJkHnnkkQrT0ZlQYlqhUChKU9W4omyQAAAWeUlEQVQaa+Lxxx/n9ddfZ+3atdx///3VFgdS2MxW4FUhhGvZDiGEGzAfQ1YPm1BiugkipWTO3jmUiBK8L3sz7T7rN5YpGi/t2rWrst/b25vt27czZ84cVq5cSWRkJGvXri1XeAL+CvNQm+oUCoXCQHVrrIkXXniBDz74gG+++Ya//e1v5jzkCrswD2gH/CmEeF4IMVIIcY8Q4kXgD6A9YHMmBvVN1wTZcG4DJzNOUpxVzPIHl6siAQoAdu7cWe0YjUbD/Pnz+emnnwgODmbChAl06tSJZcuWmSv5AebbkyoWWKFQKAxYs8aamDZtGqtXr2bv3r306dOH6OjoOrSs6WBMeXczcBJ4Dfga+AZ41XjuFinlFVvnVWK6iXFFf4UFhxYAMNRlKFHtoxxskaK+8Oqrr1o9tk+fPhw+fJgvv/wST09PHn/8cVq0aMHIkSNZtGgRhw8fBsDd3b2uzFUoFIoGhS1rLMBDDz3E7t27SU9Pp0+fPnz++edVFp2qjwghXIUQnwghLgshsoQQx4QQwyz67xRCRAshcoQQe4QQIRZ9QgjxphAi1djeEhbePyFEqPGaHOMcVmVRkFJeklIOBwKBfsYWKKUcLqW8UKP32dD+YRoS9a1oS4ks4YEND/B79u94XvHk4AsH1W14hZnY2FjatLG98qWUkp9//pl169axadMmLl26ZO7LyspCp9PZ0UqFQqFomNR0jY2NjeWBBx7g4MGDjBo1ikWLFtG6des6sNB2qivaIoTwBP4FrAJiMKSmWwd0AfQYMms8CmzGEK98m5Syn/Hax4FZwJ0YKhTuAD6QUn5k7D8EHAJmG+f9BLhBSpls9zdaDUpM1yH1TUx/fPRjFp9cTIm+hE2jNhHeqqoNrQpFzbh06RIHDhzA29vb6rzUCoVCoaic4uJi3nvvPebMmYMQgunTp/Pcc885vMBLTSogCiFOAP8GAoBJUsqbjec9gRTgRilltBDiILBKSrnM2P8I8JiUsp8QIgJDWEaglDLL2L8fWGMS25W89jBgKdBNSplRps8H+A2YIqX8ny3vSbklmwhHEo6w+MRiAB4PfVwJaUU5tm3bZpd5QkNDmThxohLSCoVCYUFt1liNRsOzzz7L2bNnGTt2LG+//TZt27ZlxowZXL582Y5W2oxWCHHEok2parAQogUQAZwGojCIVwCklNkYPNWm+NNS/cZjy74LJiFdQX9lPAW8XVZIG18/A3gTmFHNHOVQYroJkJCdwNRtU0FA+9T2TB8x3dEmKeohb7zxhqNNUCgUikaLPdbYkJAQVq9ezalTp7j//vv58MMPad++PQ8++CAnT560g5U2UySl7GXRllU2UAjhDKwBVkspowEdUFbUZgBexuOy/RmAzhg3Xd21ldEVqGon6G6gWzVzlEOJ6UZORn4G4zeMJ0fk4Jroyrqp6xxtkqKe8sUXXzjaBIVCoWi02HON7dSpE6tWreLChQtMnz6dr7/+mq5duzJ8+HC2bNlSYcpSRyKEcAI+AwoweIfBEDPtXWaoN5BVSb83oJeG+OTqrq2MZkBJFf0SQ/iJTSgx3YjRF+iZuGEiyTIZpzQnvpvyHe6uKruComKCgoIcbYJCoVA0WupijW3Tpg3vvvsuMTExzJ8/n6NHjzJixAjat2/Pa6+9Rnx8vN1f01aMnuRPgBbAGCmlqVb6aSy8wMaY6fbG8+X6jceWfe2EEF6V9FdGHAbvdGV0BVRqPIWBtLw0/r7x71wqvARZsP7v6wnyVWJJUTmbN292tAkKhULRaKnLNdbf3585c+YQExPD//3f/9G+fXtmz55Nq1atuOOOO/joo49ISrK5Sra9WAp0BO6WUuZanP8a6CyEGGOsPvgycMIYAgLwKTBLCNFKCNESeAZDVhCklOeA48BcIYSbEOJeDEJ4QzW2fA/MF0KU8ywKITwwFGz53tY3qLJ51CGOyuZxOuU0j25+FL2THpkmWXvvWrqGVPVDTKGAAQMGsHfvXkeboVAoFI2S673Gnjt3jrVr1/Lll18SHR2Nk5MTffv2ZciQIQwZMoQ+ffrUurCWFanxQoBLQD5QZNH1uJRyjTE39GIgBDiMIbvHJeO1AsOGwEeN16wAnjeGeSCECMUgrvtiSLs3VUpZZWUcIURz4BiGcI5FgEm4d8QQfiKAHlLKxGrfvOW8SkzXHddbTBcWF7L0yFJWnF6B1Ehcrrmw5v41RLaOvG42KBouKSkpBAYGOtoMhUKhaJQ4ao2VUnLq1Cm++uor/ve///Hzzz9TUlKCTqejV69e9O3bl759+9KnTx9atmxpU1XkmqTGczRGgb8UGIpBPINBXG8HnjSJeZvmVGK67rheYrqwpJBvz33Lwp8WkibSAOiQ14HPH/kcN61bnb++QqFQKBSKhkFaWhq7d+9mz549HD58mN9++43CQkMYs4+PD506dTK39u3bExISQtu2bfHz8ysntBuimDYhhPADwgE34KKUMq7GcykxXXfUpZjOKczhRMoJtpzbwtbzW8nT5Bk60uCZbs8w6Y5JdfK6isbLxo0bGT16tKPNUCgUikZJfV1j8/LyOHbsGEePHuXMmTPmVjbGWqfT0bZtW9q0aUNwcDBBQUG88cYbDVlMz8RQYbGV8dRV4F3gfWmjOFZiug7xj/KXe/buKXXOls+7oLiArMIssgqy0BfoicuI48/kP7mccZnE4kSk+GsubYaW+0Pu59m/PYuLxsVu70HRdFAx0wqFQlF3NLQ1NjU1lYsXL3L58mViYmLMj7GxsSQkJJCQkEBRUVGDFNNCiLeAKcDbGEqSA9wEPAssl1I+Z9N8SkzXHV1Wd6mzD1cWS5zTnGnv3J6JvScyst9Im+KcFIqyZGRk4OPj42gzFAqFolHS2NbYkpISNBpNQxXT1zCUDf+qzPn7gI+llDblmq7dNk5FleRfyic4KNj8PDklGYBmgc3M57L0Wej1elo0a4GTxpCpsKioiIz0DLx13uicdTiXOONc4oyH8KCle0sKkgrwLvRGK7X87W9/o1evXsybN888Z0REBOPHj2ft2rWcO3fOfH7evHkcOXKE7777znxu3LhxBAcH8+6775rP9ejRg3vuuYePP/7YnKNSp9Px7LPPsmfPHvbt22ceO2WKoXLosmV/FT3q378/d9xxB//5z3/Q6/UABAcH8/jjj/Ptt99y9OhR89hZs/5/e/cebFdZ3nH8+yMnmJxcaCMBIXaIOFymwYBK9Y+WQjXqaFGkSSUNqHhDtFRnkCnOgBoiVBOFtIJYgWCooWm4D45Uhz8S5DIIMWggY6AmtRhJFFIgIScJSJ/+8a4zWdln73NyLnu/e+/1+8ysOfusd629nvc5a639nLXX5UK2bt3KypX7HibjPuXrU1mV8+A+uU/uk/s01n1aunQpp556alflsMOtbzBu2LeN9pHpJsp1azyzkVi1ahVnnXVW7jDMzLpSN+5jO/UCREn/TKqBP18zfikwLiI+N6z3czHdPC6mrZN02vl8ZmadpBv3sR1cTH8HWABsBR4uRr8dOBK4mdI9sQ+ksHYx3UQupq2T9PX10dvbmzsMM7Ou1I372A4uplcPPRUAERHvGPL9XEw3j4tpMzMz61adWkyPtWGfZG1m3WnFihW5QzAz61rex3YvF9NmBsANN9yQOwQzs67lfWz3cjFtZgDce++9uUMwM+taVdzHSrpA0lpJeyUtr2l7p6SNkvokrZZ0VKlNkhZL2l4MS1R6mIakmcU8fcV7zGlhtwZwMW1mAIwfPz53CGZmXaui+9hngMuBG8sjJR0K3AF8CZgGrAVWlSY5D/ggcCIwGzgd+HSpfSXwGPBa4BLgNknTycTFtJkBsHz58twhmJl1rSruYyPijoi4C9he0/Q3wIaIuDUi9gALgRMlHV+0fxS4MiK2RMRvgSuBcwEkHQu8BfhKROyOiNuBx4G5Te9QAy6mzQyo5o7ezKxVvI/dzyzgF/2/RMQuYFMxfkB78brctjkidjZobzk/TryJ+vr6QtLu3HGQ/s5/GHKq1nAsA7VLHL2SAmiHdbYdtMvfpd04LwM5J/U5LzUkTaS79rG9ktaWfr8uIq5rOPU+k4Fna8a9CEwptb9Y0za5OG+6tq2/fcYBRz3GXEw317qIODl3EJLWtkMc4FgcR+dwPupzXgZyTupzXgbqtpyMoj8vAVNrxk0FdjZonwq8FBEhaah5W86neZiZmZlZK20gXVwIgKRJwBuL8QPai9fltqMlTWnQ3nIups3MzMxszEnqkTQBGAeMkzRBUg9wJ3CCpLlF+5eB9RGxsZj134ALJc2QdCTwBWA5QEQ8Bfwc+ErxfmeS7vhxe0s7V+JiurkO5LyhVmiXOMCx1OM42pPzUZ/zMpBzUp/zMlC35WSo/lxKOkf8i8A5xetLI+JZ0t03rgCeB94OzC/N913gB6S7dDwB/LAY128+cHIx79eBecV7ZqGIyLVsMzMzM7OO5iPTZmZmZmYj5GLazMzMzGyEXEw3gaRpku6UtEvS/0hakCmOCyStlbRX0vIcMRRxvEbSsiIXOyU9Jum9GeNZIWmrpB2SnpL0yVyxFPEcI2mPpBUZY1hTxPBSMTyZK5ZmG2p9lPROSRsl9UlaLemoUpskLZa0vRiWFPc97Rr11kfnRPMl/bLYp2+SdEoxvpJ5kTRT0j2Snpe0TdI1xUVllcnJYJ+vo8lBkdvVxbwbJc1pYbfGfPvP3Z9WcTHdHN8GXgYOB84GviMpx5N5ngEuB27MsOyyHuA3wKnAIcCXgFskzcwUz9eAmRExFfgAcLmkt2aKBdL68mjG5fe7ICImF8NxuYNpoobro6RDgTuKcdOAtcCq0rznAR8k3YZpNnA68OnWhd4S+62PVc+JpHcBi4GPkR4o8ZfA5orn5Vrg98ARwEmkbemzFctJ3c/XMcjBSuAx4LXAJcBtkqY3pwt1jfX2n7s/rRERHsZwACaRCuljS+O+D3w9Y0yXA8tz56YmpvXA3DaI4zhgK/ChTMufD9wCLARWZMzDGuCTuf8eGfu/nnRl+XnAQ6Xxk0hXnx9f/P4QcF6p/RPAw7njH8M8DFgfnRMeAj5RZ3xl8wL8Enhf6fdvkO60ULmc1H6+jiYHwLHAXmBKqf1+4PwW9WVMt//c/Wnl4CPTY+9Y4NVI90Hsl/WZ8e1G0uGkPGW7wbqkayX1ARtJxfQ9GWKYCiwi3T+zHXxN0nOSHpR0Wu5gWqVmfZxF2l4BiIhdwCb2bb/7tdNF2/Yg62OVczKOdPut6ZJ+JWlLcUrDRCqcF+BfgPmSeiXNAN4L/Ihq56TfaHIwC9gcETsbtDdNk7b/bP1pNRfTY6/RM+On1Jm2ciSNB24Gbop9N2dvuYj4LOlvcgrpK6y9GcL4KrAsIn6TYdm1LgaOBmaQ7hv6A0lvzBtS89VZH4fafmvbXwQmd+p5nzUarY9VzsnhwHhgHmlfcRLwZtK9c6ucl/tIBdEOYAvpq/+7qHZO+o0mBznrh2Zs/5Wph1xMj722e2Z8u5B0EOmUl5eBCzKHQ0S8GhEPAK8HPtPKZUs6CZgDLG3lchuJiJ9GxM6I2BsRNwEPAu/LHVczNVgfh9p+a9unAi9F8f1lpxpifaxkTgq7i59XR8TWiHgOuIq0bVQyL8V282PSQYhJwKHAH5POK69kTmqMJgdZ6ocmbv+VqYdcTI+9p4AeSceUxmV9Znw7KP5LXUY60jM3Il7JHFJZD9Dqo7CnATOBpyVtAy4C5kpa1+I4Ggmgm44W7WeQ9XEDaXvtn24Sad3YUK+d7tm2T6Px+ljVnBARz5OOvNYr9qqal2nAnwDXFP98bwe+R/oHo6o5KRtNDjYAR0ua0qC9WU6jOdt/rv60Xu6TtrtxAP6DdAXrJODPSV9rzMoQRw8wgXT3iu8Xr3sy5eRfgYeByZn/NoeRLrKYDIwD3gPsAs5ocRy9wOtKwzeB24DpGXLyR0UeJhTrzNlFTo7L+bdqcp/rro/A9GJ7nVvkYzGlC6SA80kXX80AjiR9KHT8xTSDrY9VzUmpf4tIdzc4jHQE9n7SV+KVzQuwmfR46J5i/3En6XSpyuSk0efraHNQ7Je+Wcx7JvBCsz8Xmrn95+hPlvUhdwDdOJD+c7+LVJA8DSzIFMdC0hGV8rAwQxxHFcveQ/rap384O0Ms00nn+71AOt/vceBTbbDOLCTT3TyKnDxK+urthWLn967cOWlifwddH0lfd24kfcW/hnQbxf55BSwB/rcYlgDK3acm5Gi/9bHKOSGdM31tsW1sA74FTKhyXkjnjq8BngeeA24FDqtSTgb7fB1NDkhHiNcU8z4JzMnUtzHZ/tuhP60YVHTWzMzMzMyGyedMm5mZmZmNkItpMzMzM7MRcjFtZmZmZjZCLqbNzMzMzEbIxbSZmZmZ2Qi5mDYzMzMzGyEX02ZmLSApJM3LuPzlkr5c+v3Xki5qwnJuk3ThWL+vmVm76skdgJlZJ5M01M36b4qIc4EjSA+5aDlJbwLOID2wptkuA+6TtCwiXmzB8szMsnIxbWY2OkeUXp8OXF8zbjdARGxrZVA1/gG4PSJ2NGsBknqAVyPicUmbgXOAbzdreWZm7cKneZiZjUJEbOsfSI+c3m9c/9HZ8mkekmYWv8+XdJ+k3ZIekzRb0gmSHpK0S9IDkt5QXp6k90v6maQ9kv5b0hWSDm4Un6RxwIeAuwfrh6RzJO2Q9AFJH5G0XdJraqa5WdLdxeuFkp6QdK6kTcBeYFIx6d3A3w0jjWZmHcvFtJlZPpcBi4E3kwrxfweuBi4B3gZMAL7VP7Gk9wA3A9cAs4CPA/OAfxpkGbOBQ4C1jSaQ9LliuadHxN3AraTPhzNK0xwCnAksK836BmAB8LfAicCeYvwjwNskTRys82Zm3cDFtJlZPldFxD0RsRG4klQgXx0RqyNiA6lo/qvS9JcA34iI70XEpohYDVwMnC9JDZZxFBBA3dNMJC0q3vcdEfETgIjYTSraP16adAGwA/hhadzBwIcjYl1EPBERfyjGPwOMB448sDSYmXUunzNtZpbP+tLr3xU/H68ZN0lSb0T0AW8lHfG9uDTNQcBE4HXA1jrLmAi8EhH/V6ft88AU4M8i4r9q2q4H1kl6fURsIRXWN5UKZoAtEfE7BtpdWraZWVfzkWkzs3xeKb2OQcYdVPp5GXBSaZgNHAM822AZzwEHS+qt0/ZAsYwB5zdHxC+AdcC5kk4ATgZurJlsV4NlTit+NorJzKxr+Mi0mVnnWAccHxG/GsY8Py9+/ikDz5v+GXAVcK+kiIiv1rRfD/wjcCjwYEQ8eYDLPAF4psFRazOzruIj02ZmnWMRsEDSouKuH8dLmidpSaMZIuJZUhH+Fw3aHwXeDXxB0qU1zStJp498hv0vPBzKKcCPhjG9mVnHcjFtZtYhIuLHwF+TLkp8pBi+CDw9xKzXAWcP8r6PkArqi8oFdUTsBG4BXi5+DknSBNJdP64/kOnNzDqdIoZ6eJeZmXWy4n7RG4GPRMT9w5z3P0kXGn7qAKf/e+CMiHj38CM1M+s8PmfazKzLRcReSR9l34WBQ5I0DZhDOmJ94jAW9wrpiYtmZpXgI9NmZjaApF+Tiu8rImJx5nDMzNqWi2kzMzMzsxHyBYhmZmZmZiPkYtrMzMzMbIRcTJuZmZmZjZCLaTMzMzOzEXIxbWZmZmY2Qi6mzczMzMxG6P8BZMEaK46UDFoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x270 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_axes, mark_inset\n",
    "#from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar\n",
    "\n",
    "fig7=plt.figure(figsize=(10,3.75)) \n",
    "plt.clf()\n",
    "gs = GridSpec(1, 3, width_ratios=[0.5,1,0.15])\n",
    "ax1 = plt.subplot(gs[0]) #, ymargin=5\n",
    "ax2 = plt.subplot(gs[1]) #sharey=ax1\n",
    "ax3 = plt.subplot(gs[2]) \n",
    "\n",
    "#ax2=fig7.add_subplot(121) \n",
    "ax1_2=ax1.twinx()\n",
    "#ax3=fig7.add_subplot(122, sharey=ax2) \n",
    "ax2_2=ax2.twinx()\n",
    "ax3_2=ax3.twinx()\n",
    "ax1.get_shared_y_axes().join(ax1, ax2, ax3)\n",
    "ax1_2.get_shared_y_axes().join(ax1_2, ax2_2, ax3_2)\n",
    "\n",
    "#ax2.tick_params(axis='y',labelleft=False)\n",
    "ax2.tick_params(axis='y',labelleft=False, left=False)\n",
    "ax1_2.tick_params(axis='y',labelright=False, right=False)\n",
    "ax2_2.tick_params(axis='y',labelright=False, right=False)\n",
    "ax3.tick_params(axis='y',labelleft=False, left=False)\n",
    "\n",
    "#ax3_2.tick_params(axis='y',labelright=False)\n",
    "#ax2_2.get_shared_y_axes().join(ax2_2, ax3_2)\n",
    "ax1.spines['right'].set_visible(False); ax1_2.spines['right'].set_visible(False)\n",
    "ax2.spines['left'].set_visible(False); ax2_2.spines['left'].set_visible(False)\n",
    "ax2.spines['right'].set_visible(False); ax2_2.spines['right'].set_visible(False)\n",
    "ax3.spines['left'].set_visible(False); ax3_2.spines['left'].set_visible(False)\n",
    "#ax3.spines['right'].set_visible(False); ax3_2.spines['right'].set_visible(False)\n",
    "#years_geocarb_scaled=np.copy(years_geocarb)\n",
    "#years_geocarb_scaled[200500:]=years_geocarb_scaled[200500]+years_geocarb_scaled[200500:]/40\n",
    "\n",
    "#ax1.plot(years_geocarb_scaled, geocarb_out_df['pCO2'],'--', lw=2,c='k')\n",
    "#ax2.plot(years_geocarb_scaled, geocarb_out_df['Tatm'],'--', lw=2,c='tab:blue')\n",
    "\n",
    "l=spin ; u=spin+500;\n",
    "#ax2.plot(years_geocarb[l:u], geocarb_out_df['pCO2'][l:u],'--', lw=2,c='k')\n",
    "#ax2_2.plot(years_geocarb[l:u], geocarb_out_df['Tatm'][l:u],'--', lw=2,c='tab:cyan')\n",
    "#ax2.set_xlim(years_geocarb[l],years_geocarb[u])\n",
    "\n",
    "times=np.arange(0,5000,1)\n",
    "times_long=np.arange(0,10000,1)\n",
    "l1,=ax1_2.plot(times, pco2_c_1500ppm_5300GtC_5ka[500:], '-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=2, zorder=4, label=r'CLIMBER-3$\\alpha$')\n",
    "ax1.plot(times, ts_ann_pulse_c_1500ppm_5300GtC_5ka, '-.', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=2, zorder=4, label=r'T_Climber3$\\alpha$')\n",
    "ax1.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka,'-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], label='1500ppm_5300GtC+50GtS', lw=2, zorder=4)\n",
    "ax1.plot(times, ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw, c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=1, alpha=0.5, zorder=4)\n",
    "#ax2_2.plot(times+start_2, ts_ann_pulse_c_2000ppm_5300GtC_5ka, '-', c=colors_paper_df.loc['pulse_c_2000ppm_5300GtC_5ka', 'color'], label='2000ppm_5300GtC', lw=2, zorder=3)\n",
    "l2,=ax1_2.plot(loscar_years[0:50+1], loscar_pco2a[0:50+1],'-', lw=1.5,c='k', label='LOSCAR')\n",
    "ax1.plot(loscar_years[0:50+1], loscar_temp[0:50+1],'-', lw=1.5,c='k', label=r'T_Loscar (simply scaled with $\\mathsf{1/ln(pCO_2)}$)')\n",
    "#$T_{1500ppm}+\\frac{2.86^{\\circ}C}{ln(2)}\\frac{pCO_2}{1500ppm}$\n",
    "#ax1_2.plot(loscar_new_years[0:50+1], loscar_new_pco2a[0:50+1],'-.', lw=2,c='tab:red')\n",
    "\n",
    "l=spin+500 ; u=spin+100000-1 ;\n",
    "#ax3.plot(years_geocarb[l:u], geocarb_out_df['pCO2'][l:u],'--', lw=2,c='k', label='Archer_pCO2')\n",
    "#ax3_2.plot(years_geocarb[l:u], geocarb_out_df['Tatm'][l:u],'--', lw=2,c='tab:cyan', label='Archer_Temp')\n",
    "#ax3.set_xlim(years_geocarb[l],years_geocarb[u])\n",
    "ax2_2.plot(loscar_years[50:], loscar_pco2a[50:],'-', lw=1.5,c='k')\n",
    "ax2.plot(loscar_years[50:], loscar_temp[50:],'-', lw=1.5,c='k')\n",
    "#ax2_2.plot(loscar_new_years[50:], loscar_new_pco2a[50:],'-.', lw=2,c='tab:red', label='Loscar_new_pCO2')\n",
    "#ax3.plot(times+start_2, pco2_c_2000ppm_5300GtC_5ka[500:], '-', c='k', label='Climber_pCO2', lw=2, zorder=4)\n",
    "#ax3_2.plot(times+start_2, ts_ann_pulse_c_2000ppm_5300GtC_5ka, '-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], label='Climber_Temp', lw=2, zorder=4)\n",
    "#ax3.plot(times+start_2, pco2_cs_2000ppm_5300GtC_5ka[500:], '-', c='k', label='Climber_pCO2', lw=2, zorder=4)\n",
    "#ax3_2.plot(times+start_2, ts_ann_pulse_corr_cs_2000ppm_5300GtC_125GtS_5ka, '-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], label='Climber_Temp', lw=2, zorder=4)\n",
    "#ax3_2.plot(times_long+start_2, ts_ann_pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka, '-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], label='Climber_Temp', lw=2, zorder=4)\n",
    "ax2.plot(times+start_2, ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka,'-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=2, zorder=4)[0]\n",
    "\n",
    "\n",
    "ll1=len(ts_ann_pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka)\n",
    "ll2=len(ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka)\n",
    "\n",
    "ax2.plot(times_long[:ll1]+start_3, ts_ann_pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka,'-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=2, zorder=4)\n",
    "#ax2.plot(times+start_4, ts_ann_pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka,'-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=2, zorder=4)\n",
    "ax2.plot(times_long[:ll2]+start_4, ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka,'-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=2, zorder=4)\n",
    "\n",
    "\n",
    "ax3_2.plot(loscar_years_ext[:], loscar_pco2a_ext[:],'-', lw=1.5,c='k')\n",
    "ax3.plot(loscar_years_ext[:], loscar_temp_ext[:],'-', lw=1.5,c='k')\n",
    "\n",
    "#ax1.set_xlim(0,1000000/30)\n",
    "ax1.set_ylim(0,24)\n",
    "ax1.set_ylabel(r'GMST ($\\mathsf{^{\\circ}C}$)', fontsize=14, position=(0.5,0.7))\n",
    "ax1.set_yticks([8,10,12,14,16,18,20,22])\n",
    "ax1.set_yticklabels([8,10,12,14,16,18,20,22])\n",
    "#ax1.yaxis.label.set_color('tab:blue')\n",
    "ax1.set_xlim(0,5000)\n",
    "ax1.set_xticks([0,1000,2000,3000,4000])\n",
    "ticks = ax1.get_xticks()//10**3\n",
    "#ax1.set_xticklabels(ticks.astype(int))\n",
    "ax1.set_xticklabels(['0','1','2','3','4'])\n",
    "ax1_2.set_ylim(1000,10000)\n",
    "#ax1_2.set_xticks([0,1000,2000,3000,4000])\n",
    "ax1_2.axvline(x=5000, c='k', ls=':')\n",
    "ax2_2.axvline(x=1000000, c='k', ls=':')\n",
    "ax1.axhline(y=ts_ann_pulse_c_1500ppm_5300GtC_5ka[0], c='tab:grey', ls='--', lw=1)\n",
    "ax2.axhline(y=ts_ann_pulse_c_1500ppm_5300GtC_5ka[0], c='tab:grey', ls='--', lw=1)\n",
    "ax3.axhline(y=ts_ann_pulse_c_1500ppm_5300GtC_5ka[0], c='tab:grey', ls='--', lw=1)\n",
    "ax1_2.axhline(y=pco2_c_1500ppm_5300GtC_5ka[500], c='tab:grey', ls='--', lw=1)\n",
    "ax2_2.axhline(y=pco2_c_1500ppm_5300GtC_5ka[500], c='tab:grey', ls='--', lw=1)\n",
    "ax3_2.axhline(y=pco2_c_1500ppm_5300GtC_5ka[500], c='tab:grey', ls='--', lw=1)\n",
    "\n",
    "#axins2 = inset_axes(ax1, width=\"35%\", height=\"35%\", loc='center right')\n",
    "axins2 = inset_axes(ax1, width=\"100%\", height=\"100%\", loc='lower left',bbox_to_anchor=(.45, .37, .44, .33), bbox_transform=ax1.transAxes)\n",
    "#axins2 = zoomed_inset_axes(ax1, 1, loc='center right')  # zoom = 6 , aspect=5\n",
    "#yr_l=1300; yr_u=1350;\n",
    "yr_l=900; yr_u=yr_l+50;\n",
    "axins2.plot(times[yr_l:yr_u+1], ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw[yr_l:yr_u+1], c='tab:green', lw=1)\n",
    "#axins2.plot(times[1550:1600], ts_ann_pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka_raw[1550:1600], c='tab:green')\n",
    "mark_inset(ax1, axins2, loc1a=2, loc2a=3, loc1b=2, loc2b=3, fc=\"none\", ec=\"0.5\")\n",
    "#axins2.tick_params(axis='y',labelleft=False)\n",
    "#axins2.tick_params(axis='x',labelbottom=False)\n",
    "axins2.set_xlim([yr_l,yr_u])\n",
    "#axins2.set_ylim([10,18])\n",
    "axins2.set_ylim([13,18.5])\n",
    "axins2.set_xticks([yr_l,yr_u])\n",
    "axins2.set_xticklabels([yr_l/1000, yr_u/1000])\n",
    "#axins2.set_yticks([10,12,14,16,18])\n",
    "\n",
    "#ax2.set_xlabel('Time (kyr)')\n",
    "ax2.set_ylim(0,24)\n",
    "#ax2.set_xlabel('Time (kyr) +$\\,$201.56$\\,$Ma', fontsize=14, position=(0.33,0.5))\n",
    "ax2.set_xlabel('Time (kyr)', fontsize=14, position=(0.33,0.5))\n",
    "\n",
    "#ax2.legend(loc='lower right')\n",
    "#ax2_2.legend(loc='lower left')\n",
    "ax3_2.set_ylabel(r'$\\mathsf{pCO_2}$ (ppm)', fontsize=14, position=(0.5,0.25))\n",
    "ax2_2.set_xlim(5000,1000000)\n",
    "ax2_2.set_xticks([5000,200000,400000,600000,800000])\n",
    "ticks = ax2_2.get_xticks()//10**3\n",
    "ax2_2.set_xticklabels(ticks.astype(int))\n",
    "#ax2_2.set_yticks([1000,2000,3000,4000,5000])\n",
    "\n",
    "ax3_2.set_xlim(1000000,4000000)\n",
    "ax3_2.set_xticks([1000000,4000000])\n",
    "ticks = ax3_2.get_xticks()//10**3\n",
    "ax3_2.set_xticklabels(ticks.astype(int))\n",
    "ax3_2.set_yticks([1000,2000,3000,4000,5000])\n",
    "\n",
    "ax1.tick_params(labelsize=12)\n",
    "ax2_2.tick_params(labelsize=12)\n",
    "ax2.tick_params(labelsize=12)\n",
    "ax3_2.tick_params(labelsize=12)\n",
    "ax3.tick_params(labelsize=12)\n",
    "\n",
    "\n",
    "#ax1.annotate('', xy=(0, 1.1), xycoords='axes fraction', xytext=(1.5, 1.1), arrowprops=dict(arrowstyle=\"<->\", color='b'))\n",
    "#ax1.text(-0.25,-0.07,r'',transform=ax1.transAxes,fontsize=12, horizontalalignment='center')\n",
    "#arrow=matplotlib.patches.FancyArrowPatch(posA=(0, 24),posB=(5000,24),arrowstyle=matplotlib.patches.ArrowStyle.CurveFilledB(head_length=.15, head_width=.03), lw=2.5, mutation_scale=100, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "#ax1.add_patch(arrow)\n",
    "#ax2.arrow(105, -15.5, 55, 9, fc='k', ec='k', alpha=1, width=0.25, head_width=1, head_length=10,length_includes_head=True)\n",
    "#ax1.text(-120., -1.975, '201.56$\\,$Ma$\\,-$', rotation=0, fontsize=12, horizontalalignment='right')\n",
    "#ax1.text(-125., -1.96, '201.56\\n Ma$\\,-$', rotation=0, fontsize=12, horizontalalignment='right')\n",
    "ax1.text(-0.46,1.03,r'$\\sim$201.56$\\,$Ma$\\,$$\\mapsto$',transform=ax1.transAxes,fontsize=12)\n",
    "#ax1.text(-125., -1.96, '201.56\\n Ma$\\,-$', rotation=0, fontsize=12, horizontalalignment='right')\n",
    "ax1.text(1000, 24.75, 'ETE', rotation=0, fontsize=12) \n",
    "ax2.text(150000, 24.75, 'TJB', rotation=0, fontsize=12) \n",
    "\n",
    "ax0tr = ax1.transData # Axis 0 -> Display\n",
    "ax1tr = ax2.transData # Axis 1 -> Display\n",
    "figtr = fig7.transFigure.inverted() # Display -> Figure\n",
    "# 2. Transform arrow start point from axis 0 to figure coordinates\n",
    "ptB = figtr.transform(ax0tr.transform((1700, 25.75))) #25.8\n",
    "# 3. Transform arrow end point from axis 1 to figure coordinates\n",
    "ptE = figtr.transform(ax1tr.transform((50700., 25.75))) #25.8\n",
    "# 4. Create the patch\n",
    "arrow = matplotlib.patches.FancyArrowPatch(\n",
    "    ptB, ptE, transform=fig7.transFigure,  # Place arrow in figure coord system\n",
    "    fc = \"k\", arrowstyle='<|-|>', alpha = 1,\n",
    "    mutation_scale = 15.,lw=2) #, connectionstyle=\"arc3,rad=0.2\"\n",
    "fig7.patches.append(arrow)\n",
    "\n",
    "#linelabels=[r'pCO2_Climber3$\\alpha$','pCO2_Loscar',r'T_Climber3$\\alpha$','T_Loscar']\n",
    "#ax2.legend(handles=[l1,l2], loc='center right', fontsize=12, ncol=2, frameon=False)\n",
    "ax2.legend(handles=[l1,l2], bbox_to_anchor=(0.53,0.4,0.2,0.1),loc='center', fontsize=12, ncol=2, frameon=False)\n",
    "#ax2.legend(bbox_to_anchor=(0.615,-0.034,0.4,0.6),loc='center', fontsize=10, ncol=1, labelspacing=0.25, frameon=False)\n",
    "\n",
    "\n",
    "plt.tight_layout(w_pad=-1.9) #w_pad=-0.6\n",
    "fig7.savefig('./plot_pdf_files/Fig5_loscar_climber_synthesis_rev.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Graphical Abstract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x540 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#var_scat=lonlat_paleo_norian_sel\n",
    "#var_scat2=lonlat_paleo_rhaetian_sel\n",
    "with open('../climber/continental_mask.pickle', 'rb') as f:  \n",
    "    continental_mask = pickle.load(f, encoding='latin1') #Python3: , encoding='latin1'\n",
    "\n",
    "fig=plt.figure(figsize=(10,7.5))\n",
    "plt.clf()\n",
    "gs = GridSpec(7, 4,height_ratios=[0.15,1,0.11,1,1,0.1,0.1], width_ratios=[0.45,0.45,0.1,0.675]) #,1\n",
    "\n",
    "ax0=plt.subplot(gs[0,:]); ax0.axis('off')\n",
    "ax1 = plt.subplot(gs[1:-2,0]) #, ymargin=5\n",
    "#ax11 = plt.subplot(gs[1:-1,1]) #sharey=ax1\n",
    "\n",
    "#ax112 = ax11.twiny()\n",
    "\n",
    "ax21 = plt.subplot(gs[4,3])\n",
    "ax22 = plt.subplot(gs[3,3])\n",
    "ax23 = plt.subplot(gs[1,3])\n",
    "\n",
    "ax24 = plt.subplot(gs[2,3]) #; ax24.axis('off')\n",
    "ax25 = plt.subplot(gs[5,3])\n",
    "\n",
    "# ax31 = plt.subplot(gs[3,4])\n",
    "# ax32 = plt.subplot(gs[2,4])\n",
    "# ax33 = plt.subplot(gs[0,4])\n",
    "\n",
    "# ax34 = plt.subplot(gs[1,4])\n",
    "# ax35 = plt.subplot(gs[4,4])\n",
    "\n",
    "ax_text = plt.subplot(gs[1:-1,2]); ax_text.axis('off')\n",
    "#ax_text1 = plt.subplot(gs[0,2]); ax_text1.axis('off')\n",
    "#ax_text2 = plt.subplot(gs[2,2]); ax_text2.axis('off')\n",
    "#ax_text3 = plt.subplot(gs[3,2]); ax_text3.axis('off')\n",
    "#ax21.grid(linestyle=':', zorder=0)\n",
    "ax_anno = plt.subplot(gs[-1,:]); ax_anno.axis('off')\n",
    "\n",
    "lim_l=-10.\n",
    "lim_u=6.\n",
    "mycmap = jplt.shiftedColorMap(matplotlib.cm.RdBu_r, midpoint=abs(lim_l)/(lim_u+abs(lim_l)))\n",
    "#mycmap = jplt.shiftedColorMap(matplotlib.cm.RdBu_r, stop=(abs(lim_l)+lim_u)/(2.*abs(lim_l)))\n",
    "\n",
    "times=np.arange(0,5000,1)  \n",
    "#times=np.arange(0,5000,1)\n",
    "times_long=np.arange(0,10000,1)\n",
    "#ax1.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka[0:3000],times[0:3000],'-', c='tab:green', lw=2) \n",
    "#ax1.plot(ts_ann_pulse_control_1500ppm[0:3000],times[0:3000], '--', c='tab:grey', zorder=1)\n",
    "#ax1.plot(loscar_pco2a[:],201.56-(loscar_years[:]/10**6),'-', lw=1.5,c='k') #\n",
    "ax1.plot(loscar_temp[:],201.56-(loscar_years[:]/10**6),'-', lw=1.5,c='k')\n",
    "ax1.plot(loscar_temp_ext[:],201.56-1-((loscar_years_ext[:]/10**6)-1),'-', lw=1.5,c='k')\n",
    "ax1.plot(np.repeat(18.7,50),201.56+np.linspace(0,0.5,50),'-', lw=1.5,c='k')\n",
    "ax1.plot(np.repeat(18.7,100),201.56-np.linspace(0,0.8,100),'--', lw=1.0,c='tab:gray')\n",
    "\n",
    "ax1.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka,201.56-(times)/10**6, '-', c='k', lw=2, zorder=4)[0]\n",
    "ax1.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka,201.56-(times+start_2)/10**6, '-', c='k', lw=2, zorder=4)[0]\n",
    "#colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color']\n",
    "\n",
    "ll1=len(ts_ann_pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka)\n",
    "ll2=len(ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka)\n",
    "\n",
    "ax1.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_500GtS_12ka,201.56-(times_long[:ll1]+start_3)/10**6, '-', c='k', lw=2, zorder=4)\n",
    "#ax2.plot(times+start_4, ts_ann_pulse_corr_cs_1500ppm_5300GtC_50GtS_5ka,'-', c=colors_paper_df.loc['pulse_c_1500ppm_5300GtC_5ka', 'color'], lw=2, zorder=4)\n",
    "ax1.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_250GtS_12ka,201.56-( times_long[:ll2]+start_4)/10**6,'-', c='k', lw=2, zorder=4)\n",
    "\n",
    "#ax1.plot(ts_ann_pulse_corr_cs_1500ppm_5300GtC_250GtS_12ka[ll1:],201.56-(times_long[ll1:]+start_3)/10**6, '-', c='tab:gray', lw=2, zorder=4)\n",
    "#ax1.plot(ts_ann_pulse_corr_cs_1500ppm_5300GtC_125GtS_12ka[ll2:],201.56-(times_long[ll2:]+start_4)/10**6, '-', c='tab:gray', lw=2, zorder=4)\n",
    "\n",
    "#ax1.scatter(pco2_schaller2011[:,1],pco2_schaller2011[:,0]) #,'-', lw=1.5,c='k'\n",
    "#ax1.scatter(pco2_schaller2012[:,1],pco2_schaller2012[:,0])\n",
    "##ax1.set_aspect(0.04)\n",
    "##ax1.set_ymargin(0.1)\n",
    "##ax1.axis('off')\n",
    "ax1.spines['right'].set_visible(False)\n",
    "##ax1.spines['left'].set_visible(False)\n",
    "ax1.spines['top'].set_visible(False)\n",
    "##ax1.axes.get_yaxis().set_visible(False)\n",
    "ax1.set_xlim([0,24])\n",
    "ax1.set_ylim([201.7,200.8])\n",
    "#ax1.set_xticks([5,10,15,20,25])\n",
    "for tick in ax1.get_yticklabels():\n",
    "    tick.set_rotation(45)\n",
    "ax1.set_xlabel(r'GMST ($\\mathsf{^{\\circ}C}$)', fontsize=11)\n",
    "ax1.set_ylabel(r'Age (Ma)', fontsize=11)\n",
    "\n",
    "axins3 = inset_axes(ax1, width=\"100%\", height=\"100%\", loc=2,bbox_to_anchor=(1.3, 0.12, 0.8, .9),borderpad=2, bbox_transform=ax1.transAxes)\n",
    "axins3.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka[0:3000],201.56-times[0:3000]/10**6, '-', c='k', label='1500ppm_5300GtC+50GtS', lw=2, zorder=4)\n",
    "axins3.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw[0:3000],201.56-times[0:3000]/10**6,  c='tab:gray', lw=1, alpha=0.75, zorder=2)\n",
    "axins3.plot(ts_ann_pulse_control_1500ppm[0:3000],201.56-times[0:3000]/10**6, '--',lw=1.0, c='tab:grey', zorder=1)\n",
    "axins3.scatter(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka[0:3000],201.56-times[0:3000]/10**6,c=ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka[0:3000], cmap='Spectral_r',zorder=3, vmin=18,vmax=22)\n",
    "axins3.set_ylim([201.56,201.557])\n",
    "axins3.set_yticks([201.56,201.559,201.558,201.557])\n",
    "axins3.set_yticklabels(['0','1','2','3'])\n",
    "axins3.set_ylabel('Time (kyr)')\n",
    "axins3.set_xticks([10,15,20])\n",
    "axins3.set_xlabel('GMST ($\\mathsf{^{\\circ}C}$)')\n",
    "mark_inset(ax1, axins3, loc1a=2, loc2a=3, loc1b=1, loc2b=4, fc=\"none\", ec=\"0.75\") #, ec=\"0.5\"\n",
    "\n",
    "# ax11.plot(ts_ann_pulse_control_1500ppm[0:3000],times[0:3000], '--', c='tab:grey', zorder=1)\n",
    "# ax11.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka,times, '-', c='k', label='1500ppm_5300GtC+50GtS', lw=2, zorder=4)\n",
    "# ax11.plot(ts_ann_pulse_rev_cs_1500ppm_5300GtC_125GtS_5ka_raw,times,  c='tab:gray', lw=1, alpha=0.5, zorder=4)\n",
    "\n",
    "#ax11.plot(eta_steric[0:3000],times[0:3000], '-', c='k', zorder=4, lw=2)\n",
    "#ax11.plot(eta_steric_control_1500ppm[0:3000],times[0:3000], '--', c='tab:grey', zorder=1)\n",
    "##ax11.set_aspect(0.04*((1.5-(-1.5))/(25-5)))\n",
    "\n",
    "# ax11.spines['right'].set_visible(False)\n",
    "# #ax11.spines['left'].set_visible(False)\n",
    "# ax11.spines['top'].set_visible(False)\n",
    "# #ax11.axes.get_yaxis().set_visible(False)\n",
    "# ax11.set_xlim([8,24])\n",
    "# ax11.set_ylim([-100,3050])\n",
    "# #ax11.set_xticks([-1.5,0,1.5])\n",
    "# #ax11.set_xticklabels(['$-1.5$','$0$','$+1.5$'])\n",
    "# ax11.set_xlabel('GMST ($\\mathsf{^{\\circ}C}$)', fontsize=11)\n",
    "# ax11.set_ylabel('Time (years)', fontsize=11)\n",
    "# ax11.xaxis.label.set_color('k')\n",
    "# for tick in ax11.get_yticklabels():\n",
    "#     tick.set_rotation(45)\n",
    "\n",
    "# ax11.set_zorder(10)\n",
    "# ax11.patch.set_visible(False)\n",
    "# ax112 = ax11.twiny()\n",
    "\n",
    "# ax112.plot(glb_over[0:3000],times[0:3000], '-', c='tab:blue', zorder=3, lw=2) #c='teal'\n",
    "# ax112.plot(glb_over_c[0:3000],times[0:3000], '-.', c='tab:blue', zorder=3, lw=2)\n",
    "# ##ax112.set_aspect(0.04*((1.5-(-1.5))/(25-5))*(6-1/(25-5)), adjustable='box-forced')\n",
    "# ax112.spines['right'].set_visible(False)\n",
    "# ax112.spines['left'].set_visible(False)\n",
    "# ax112.spines['bottom'].set_visible(False)\n",
    "# ax112.axes.get_yaxis().set_visible(False)\n",
    "# ax112.set_xlim([12,40])\n",
    "# ax112.set_xticks([20,30,40])\n",
    "# ax112.set_ylim([-100,3050])\n",
    "# ax112.set_xlabel('Overturning (Sv)', fontsize=11) #Average Meridional #,fontweight='bold'\n",
    "# ax112.xaxis.label.set_color('tab:blue')\n",
    "\n",
    "latso, lonso, xo, yo=jan.grid_gen(region='ocean', cell='T')\n",
    "\n",
    "xpa, ypa=jan.grid_gen(region='atmo', cell='p')[2:4]\n",
    "xua,yua=jan.grid_gen(region='atmo', cell='u')[2:4]\n",
    "xta,yta=jan.grid_gen(region='atmo', cell='T')[2:4]\n",
    "\n",
    "xpo, ypo=jan.grid_gen(region='ocean', cell='p')[2:4] \n",
    "xuo,yuo=jan.grid_gen(region='ocean', cell='u')[2:4]\n",
    "xto,yto=jan.grid_gen(region='ocean', cell='T')[2:4]           \n",
    "\n",
    "xtac,ytac=jan.grid_gen(region='atmo', cell='T')[2:4]\n",
    "xtoc,ytoc=jan.grid_gen(region='ocean', cell='T')[2:4]\n",
    "\n",
    "x_1deg, y_1deg=jan.grid_gen(region='atmo_1deg', cell='p')[2:4] \n",
    "xu_1deg,yu_1deg=jan.grid_gen(region='atmo_1deg', cell='u')[2:4]\n",
    "xt_1deg,yt_1deg=jan.grid_gen(region='atmo_1deg', cell='T')[2:4]\n",
    "\n",
    "for axi in [ax21, ax22, ax23]: #, ax31, ax32, ax33\n",
    "    m = Basemap(projection='moll', llcrnrlat=-90, urcrnrlat=90,llcrnrlon=-180, urcrnrlon=180, resolution='c', lon_0=0, ax=axi)\n",
    "    m.drawmapboundary()  \n",
    "    m.drawparallels(np.arange(-90.,120.,30.), linewidth=0.5)\n",
    "    m.drawmeridians(np.arange(0.,420.,60.), linewidth=0.5)\n",
    "\n",
    "xpam, ypam = m(xpa, ypa)\n",
    "xom, yom = m(xo, yo)\n",
    "xpom, ypom = m(xpo, ypo)\n",
    "\n",
    "#xtm,ytm=m(xt,yt)   \n",
    "#xtcm,ytcm=m(xtc,ytc)\n",
    "\n",
    "#x_scat, y_scat=m(var_scat[:,0],var_scat[:,1])\n",
    "#x_scat2, y_scat2=m(var_scat2[:,0],var_scat2[:,1])\n",
    "\n",
    "a21=ax21.pcolor(xpam, ypam, ts_ini_1500ppm, cmap='Spectral_r',vmin=-15, vmax=35)\n",
    "ax21.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75, colors='k')\n",
    "cbar=fig.colorbar(mappable=a21, cax=ax25, orientation='horizontal', boundaries=np.arange(-15,35+2.5,2.5), ticks=np.arange(-15,35+2.5,5)) #, boundaries=np.arange(-11,6+1,1) drawedges=True, #cbar.dividers.set_color('white')  , pad=-0.5 ax=[ax21, ax22, ax23, ax24], c\n",
    "#cbar.ax.set_xticklabels(['$-10$','$-8$','$-6$','$-4$','$-2$','$0$','$+2$', '$+4$', '$+6$'])\n",
    "cbar.set_label(r'SAT ($\\mathsf{^{\\circ}C}$)', labelpad=-45, fontsize=11)\n",
    "cbar.ax.tick_params(labelsize=10);\n",
    "\n",
    "\n",
    "a22=ax22.pcolor(xpam, ypam, ts_diff_maxcool, cmap=mycmap, vmin=lim_l, vmax=lim_u) # , cmap=mycmap\n",
    "ax22.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75, colors='k')\n",
    "\n",
    "a23=ax23.pcolor(xpam, ypam, ts_diff_maxwarm, cmap=mycmap, vmin=lim_l, vmax=lim_u) #, vmin=1.5, vmax=6\n",
    "ax23.contour(xom,yom,continental_mask,levels=[0.5], linewidths=1.75, colors='k')\n",
    "cbar=fig.colorbar(mappable=a23, cax=ax24, orientation='horizontal', extend='min', boundaries=np.arange(-11,6+1,1)) #, boundaries=boundaries, ticks=ticks drawedges=True, #cbar.dividers.set_color('white')  , pad=-0.5 ax=[ax21, ax22, ax23, ax24], c\n",
    "cbar.ax.set_xticklabels(['$-10$','$-8$','$-6$','$-4$','$-2$','$0$','$+2$', '$+4$', '$+6$'])\n",
    "cbar.set_label(r'$\\Delta$SAT ($\\mathsf{^{\\circ}C}$)', labelpad=-45, fontsize=11)\n",
    "#cbar.set_label(\"%s (%s)\" % (varname, units), fontsize=12) , \\\n",
    "#           shrink=0.7 , pad=0.06\n",
    "cbar.ax.tick_params(labelsize=10);\n",
    "\n",
    "\n",
    "\n",
    "ax_text.text(0.5,0.18,'Initial',fontsize=13, horizontalalignment='center', color='tab:green',fontweight='bold')\n",
    "ax_text.text(0.5,0.49,'Cool',fontsize=13, horizontalalignment='center', color='tab:blue',fontweight='bold')\n",
    "ax_text.text(0.5,0.84,'Warm',fontsize=13, horizontalalignment='center', color='darkorange',fontweight='bold')\n",
    "\n",
    "arrow=matplotlib.patches.FancyArrowPatch(posA=(0.5,0.25),posB=(0.5,0.45),arrowstyle=matplotlib.patches.ArrowStyle.Fancy(head_length=.3, head_width=.2, tail_width=.1), mutation_scale=50, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "ax_text.add_patch(arrow)\n",
    "arrow2=matplotlib.patches.FancyArrowPatch(posA=(0.5,0.58),posB=(0.5,0.78),arrowstyle=matplotlib.patches.ArrowStyle.Fancy(head_length=.3, head_width=.2, tail_width=.1), mutation_scale=50, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "ax_text.add_patch(arrow2)\n",
    "#ax_text.arrow(0.5, 0.25, 0, 0.2,fc='k', ec='k', alpha=1, width=0.05, head_width=0.2, head_length=0.05,length_includes_head=True)\n",
    "#ax_text.arrow(0.5, 0.58, 0, 0.2,fc='k', ec='k', alpha=1, width=0.05, head_width=0.2, head_length=0.05,length_includes_head=True)\n",
    "\n",
    "ax0.text(0.45,0.0,'end-Triassic climate perturbations by Central Atlantic Magmatic Province volcanism \\n simulated for pulsed carbon emissions and stratospheric sulfur injections',fontweight='bold',transform=ax0.transAxes,fontsize=14, ha='center')\n",
    "#ax1.text(-0.35,1.01,'(a)',transform=ax1.transAxes,fontsize=11)\n",
    "#ax11.text(-0.35,1.01,'(b)',transform=ax11.transAxes,fontsize=11)\n",
    "\n",
    "#ax21.text(0,0.85,'(c)',transform=ax21.transAxes,fontsize=11)\n",
    "#ax22.text(0,0.85,'(d)',transform=ax22.transAxes,fontsize=11)\n",
    "#ax23.text(0,0.85,'(e)',transform=ax23.transAxes,fontsize=11)\n",
    "\n",
    "arrow = matplotlib.patches.FancyArrowPatch(\n",
    "    posA=(2.5, 201.65), posB=(2.5,200.85), #transform=fig7.transFigure,  # Place arrow in figure coord system\n",
    "    fc = \"k\", arrowstyle='<|-|>', alpha = 1,\n",
    "    mutation_scale = 15.,lw=2) #, connectionstyle=\"arc3,rad=0.2\"\n",
    "#fig7.patches.append(arrow)\n",
    "#arrow=matplotlib.patches.FancyArrowPatch(posA=(102, -15.75),posB=(165,-6.0),arrowstyle=matplotlib.patches.ArrowStyle.CurveFilledB(head_length=.15, head_width=.03), lw=2.5, mutation_scale=100, edgecolor='k', facecolor='k') #, shrinkA=10                    #\n",
    "ax1.add_patch(arrow)\n",
    "ax1.text(3.0, 200.95,'$\\sim$CAMP emplacement',fontsize=11, rotation=90) #,transform=ax1.transAxes\n",
    "ax1.text(2.5, 201.56-0.01,'$\\sim$ETE',fontsize=11) #'end-Triassic \\nextinction horizon'\n",
    "ax1.text(2.5, 201.36,'$\\sim$TJB',fontsize=11) #'Triassic-Jurassic \\nboundary'\n",
    "\n",
    "#ax23.text(0.5,1.15,'Surface Air Temperature \\n & Oxygen Minima',transform=ax23.transAxes,fontsize=14, horizontalalignment='center')\n",
    "\n",
    "ax_anno.text(0.4,-0.8,'(GMST=Global Mean Surface Air Temperature, SAT=Surface Air Temperature, ETE=end-Triassic Extinction Horizon, TJB=Triassic-Jurassic Boundary)',transform=ax_anno.transAxes,fontsize=8, ha='center')\n",
    "\n",
    "plt.tight_layout(h_pad=-1.75) #h_pad=-4.25, w_pad=-2\n",
    "\n",
    "fig.savefig('./plot_pdf_files/GraphicalAbstract.pdf',bbox_inches='tight', pad_inches=0.05, dpi=900)\n"
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     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "oldHeight": 476,
   "position": {
    "height": "40px",
    "left": "1165px",
    "right": "22px",
    "top": "168.8px",
    "width": "733px"
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "varInspector_section_display": "none",
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}