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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1.Functions useful to format strings and write doc\n",
+    "Exec in any case"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from itertools import chain\n",
+    "def remove_jk(l, c= None):\n",
+    "    if c:\n",
+    "        return re.sub(f'{c}[jk]', '', l)\n",
+    "    return re.sub(f'\\.[jk]', '', l)\n",
+    "\n",
+    "def rmdyn(v):\n",
+    "    \"\"\"For special name slike all or len, remove the dynamo_\"\"\"\n",
+    "    return v.replace('dynamo_', '')\n",
+    "    \n",
+    "def line_with_refs(ll, inout):\n",
+    "    for a in sorted(inout, key=len):\n",
+    "        ll = remove_jk(re.sub(f'(?<![\\`\\w]){a}(?!\\w)', f\" :doc:`{a}<{a}>` \", rmdyn(ll))).replace('`dynamo_', '`')\n",
+    "    if 'tabhl' in ll:\n",
+    "        ll = ll .replace('tabhl', ' :doc:`tabhl<../tabhl>` ')\n",
+    "    if 'clip' in ll:\n",
+    "        ll = ll .replace('clip', ' :doc:`clip<../clip>` ')\n",
+    "    return ll.replace('*', '\\*')\n",
+    "\n",
+    "# Get all sectors and variables and definitions \n",
+    "def to_rst(k, e, f):\n",
+    "    \"\"\"Convert a key, english and frensh version to rst syntax.\n",
+    "    \n",
+    "    Example:\n",
+    "    Arguments (key, def_en, def_fr) are converted to:\n",
+    "    \n",
+    "    :doc:`key`\n",
+    "    ~~~~~~~~~~\n",
+    "        def_fr\n",
+    "    \"\"\"\n",
+    "    name = f':doc:`variables/{k}`'\n",
+    "    return f\"{name}\\n{'~'*len(name)}\\n    {e}\\n\\n\"\n",
+    "\n",
+    "def write_all_variable_docs(filename, definitions, sector_vars):\n",
+    "    with open(filename, 'w+') as ff:\n",
+    "        ff.write('Sectors\\n=======\\n\\n')\n",
+    "        for sector, variables in sector_vars.items():\n",
+    "            ff.write(f'\\n\\n{sector}\\n{\"-\"*len(sector)}\\n\\n')\n",
+    "            for var in variables:\n",
+    "                try:\n",
+    "                    en, fr = definitions[var]\n",
+    "                    ff.write(to_rst(var, en, fr))\n",
+    "                except:\n",
+    "                    if var[-1] == 't':\n",
+    "                        ff.write(to_rst(var, f'Table to set {var[:-1]}', ''))\n",
+    "                        \n",
+    "# for i in {'helpicir2', 'icir2', 'icet', 'diop', 'dist', 'disi'}:\n",
+    "#     var_colors[i] = 'red'\n",
+    "\n",
+    "def get_el_infos(G, var, all_csts, var_color):\n",
+    "    \"\"\"Returns every useful informations about var. \n",
+    "    Parameters\n",
+    "    ----------\n",
+    "    G: nx.DiGraph\n",
+    "        System influence graph\n",
+    "    var: string\n",
+    "        variable\n",
+    "    all_csts: iterable(sitring)\n",
+    "        list of every constants of the system\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    iv = {a for (a, _) in G.in_edges(var)}\n",
+    "    ov = {b for (_, b) in G.out_edges(var)}\n",
+    "    Gq = G.subgraph(iv.union(ov).union({var}))\n",
+    "    bv = iv.intersection(ov)\n",
+    "    iv = iv.difference(bv)\n",
+    "    ov = ov.difference(bv)\n",
+    "    \n",
+    "    posi = {n: (-1/2, -i + (len(iv)-1)/2) for i, n in enumerate(iv)}\n",
+    "    poso = {n: (1/2, -i+(len(ov)-1)/2) for i, n in enumerate(ov)}\n",
+    "    posb = {n: (i/len(bv)/2 - 1/4, -1) for i, n in enumerate(bv)}\n",
+    "    pos = {**posi, **poso, **posb, var:(0, 0)}\n",
+    "    \n",
+    "    try:\n",
+    "        colors = [var_color[n] for n in Gq.nodes]\n",
+    "    except:\n",
+    "        colors = 'gray'\n",
+    "\n",
+    "    cs = [n for n in Gq.nodes if n in all_csts]\n",
+    "    vs = [n for n in Gq.nodes if n not in all_csts]\n",
+    "    ccs = [var_color[n] for n in cs]\n",
+    "    cvs = [var_color[n] for n in vs]\n",
+    "    \n",
+    "    return Gq, iv, ov, bv, pos, vs, cs, cvs, ccs\n",
+    "\n",
+    "def get_all_infos(s, var_color, var_sector):\n",
+    "    \"\"\"Returns a list of dictionnaries containing all relevant infos about every variables,\n",
+    "    and constants of the system s\n",
+    "    \"\"\"\n",
+    "    G = s.get_influence_graph()\n",
+    "    \n",
+    "   \n",
+    "    for var in s.nodes['var']:\n",
+    "        Gq, iv, ov, bv, pos, vs, cs, cvs, ccs = get_el_infos(G, var, s.nodes['cst'], var_color)\n",
+    "        dico_info = {\n",
+    "            'grafun': (Gq, pos,  vs, cs, cvs, ccs),\n",
+    "            'in': {rmdyn(v):s.get_comment(v) for v in iv},\n",
+    "            'out': {rmdyn(v):s.get_comment(v) for v in ov},\n",
+    "            'both': {rmdyn(v):s.get_comment(v) for v in bv},\n",
+    "            'def': s.get_comment(var),\n",
+    "            'unit': s.get_unit(var),\n",
+    "            'eq': s.eqs['update'][var]['raw_line'],\n",
+    "            'eltype': 'var',\n",
+    "            'sector': var_sector[var],\n",
+    "            'color': var_color[var]\n",
+    "        }\n",
+    "        argfun = s.eqs['update'][var]['args']['fun']\n",
+    "        if 'tabhl' in argfun:\n",
+    "            dico_info['tabhl'] = argfun['tabhl']\n",
+    "        yield rmdyn(var), dico_info\n",
+    "        \n",
+    "\n",
+    "    \n",
+    "    for cst in s.nodes['cst']:\n",
+    "        Gq, iv, ov, bv, pos,  vs, cs, cvs, ccs = get_el_infos(G, cst, s.nodes['cst'], var_color)\n",
+    "        yield rmdyn(cst), {\n",
+    "            'grafun': (Gq, pos,  vs, cs, cvs, ccs),\n",
+    "            'in': {rmdyn(v):s.get_comment(v) for v in iv},\n",
+    "            'out': {rmdyn(v):s.get_comment(v) for v in ov},\n",
+    "            'both': {rmdyn(v):s.get_comment(v) for v in bv},\n",
+    "            'def': s.get_comment(cst),\n",
+    "            'unit': s.get_unit(cst),\n",
+    "            'eq': s.eqs['cst'][cst]['raw_line'],\n",
+    "            'eltype': 'cst',\n",
+    "            'sector': var_sector[cst],\n",
+    "            'color': var_color[cst]\n",
+    "        }\n",
+    "\n",
+    "def write_file_var(path, var, infos, genfig=True):\n",
+    "    \"\"\"Write informations in rst format, in the path for the given variable. \n",
+    "    Also generate matplotlib network image, and tabhl if necesary.\n",
+    "    \"\"\"\n",
+    "    if genfig:\n",
+    "        Gq, pos, vs, cs, cvs, ccs = info['grafun']\n",
+    "        fig = plt.figure()\n",
+    "        nx.draw_networkx_nodes(Gq, pos, vs, node_size=1000, node_color=cvs, node_shape='o')\n",
+    "        nx.draw_networkx_nodes(Gq, pos, cs, node_size=1000, node_color=ccs, node_shape='s')\n",
+    "        nx.draw_networkx_edges(Gq, pos, node_size=1000, arrows=True)\n",
+    "\n",
+    "        nx.draw_networkx_labels(Gq, pos, {n:rmdyn(n) for n in Gq.nodes})\n",
+    "        plt.savefig(f'{path}{var}.png')\n",
+    "        plt.close(fig)\n",
+    "    \n",
+    "    to_add_tabhl = ''\n",
+    "    if genfig and 'tabhl' in infos:\n",
+    "        p = infos['tabhl']\n",
+    "        x_low = eval(p['x_low'])\n",
+    "        x_high = eval(p['x_high'])\n",
+    "        x_incr = eval(p['x_incr'])\n",
+    "        table = getattr(s, p['table'])\n",
+    "        fig = plt.figure()\n",
+    "        plt.plot(np.arange(x_low, x_high+x_incr/2, x_incr), table)\n",
+    "        plt.title(f'{var} in function of {remove_jk(p[\"val\"].strip())}')\n",
+    "        plt.xlabel(remove_jk(p[\"val\"].strip()))\n",
+    "        plt.ylabel(var)\n",
+    "        plt.savefig(f'{path}{var}_tabhl.png')\n",
+    "        plt.close(fig)\n",
+    "    \n",
+    "    if 'tabhl' in infos:\n",
+    "        to_add_tabhl = f\"\\n\\ntabhl\\n~~~~~\\n\\n.. image:: {var}_tabhl.png\\n\"\n",
+    "    subtitle = 'Variable' if infos['eltype'] == 'var' else 'Constant'\n",
+    "    iv = '\\n\\n'.join(f\":doc:`{v}<{v}>` : {c}\" for v, c in chain(infos['in'].items(), infos['both'].items()))\n",
+    "    ov = '\\n\\n'.join(f\":doc:`{v}<{v}>` : {c}\" for v, c in chain(infos['out'].items(), infos['both'].items()))\n",
+    "    line = infos['eq'].split('#')[0].strip()\n",
+    "    lineref = line_with_refs(line, set(infos['in']).union(set(infos['both'])))\n",
+    "    definition = ' '.join(i.capitalize() for i in infos['def'].replace('\"', '').split(\" \"))\n",
+    "    title = f\"{var}: {definition}\"\n",
+    "#     old_line = \"\"\"\n",
+    "# .. code-block:: python\n",
+    "   \n",
+    "#    {line}\n",
+    "# \"\"\"\n",
+    "    with open(f'{path}{var}.rst', 'w+') as f:\n",
+    "        f.write(f\"\"\"\n",
+    "\n",
+    "{title}\n",
+    "{'-'*len(title)}\n",
+    "\n",
+    "*{subtitle}*\n",
+    "\n",
+    ".. raw:: html\n",
+    "    \n",
+    "    <p style=\"color:{infos['color']}\">{infos['sector']}</p>\n",
+    "\n",
+    "{definition} [{infos['unit']}]\n",
+    "\n",
+    ".. parsed-literal:: {lineref}\n",
+    "\n",
+    ".. figure:: {var}.png\n",
+    "    \n",
+    "    {var} in the updating graph: ( :doc:`how to read<../readgraph>` )\n",
+    "\n",
+    "In nodes\n",
+    "~~~~~~~~\n",
+    "{iv}\n",
+    "\n",
+    "Out nodes\n",
+    "~~~~~~~~~\n",
+    "{ov}\n",
+    "\n",
+    "\"\"\" + to_add_tabhl)\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Write sectors files "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sector_var = {}\n",
+    "source_path = \"world3/docs/source\"\n",
+    "for var, sec in var_sector.items():\n",
+    "    if sec not in sector_var:\n",
+    "        sector_var[sec] = []\n",
+    "    sector_var[sec].append(var)\n",
+    "with open(f\"{source_path}/sectors.rst\", \"w+\") as f:\n",
+    "    f.write(\"\"\"All sectors\n",
+    "===========\n",
+    "\"\"\")\n",
+    "    for sec, vss in sector_var.items():\n",
+    "        f.write(f\"\"\"\n",
+    "{rmdyn(sec)}\n",
+    "{'-'*len(rmdyn(sec))}\n",
+    ".. toctree::\n",
+    "   :glob:\n",
+    "   :maxdepth: 1\n",
+    "\n",
+    "\"\"\")\n",
+    "        for v in vss:\n",
+    "            f.write(f\"   variables/{rmdyn(v)}\\n\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## FOR 72 CODE\n",
+    "Exec only to write 72 code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from world3 import translated_defs, sector_vars, get_w3_72, var_color\n",
+    "import matplotlib.pyplot as plt\n",
+    "import networkx as nx\n",
+    "import numpy as np\n",
+    "s = get_w3_72()\n",
+    "write_all_variable_docs(\"world3/docs_72/source/sectors.rst\", translated_defs, sector_vars)\n",
+    "infos = dict(get_all_infos(s, var_color))\n",
+    "for k, info in list(infos.items()):\n",
+    "    try:\n",
+    "        write_file_var('world3/docs_72/source/variables/', k, info, genfig=False)\n",
+    "    except Exception as e:\n",
+    "        print(k, info)\n",
+    "        raise e"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pydynamo as dno\n",
+    "dno.plot_system.show_pyvis(s, colors=var_color,notebook=False).show('world3/docs/source/sectormap2.html')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Vensim run\n",
+    "Exec only if you want to run vensim model for fun"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "import pydynamo as dno\n",
+    "import pysd "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = pysd.read_vensim('../from_vensim/wrld3-03+.mdl')\n",
+    "sp = dno.psdsystem.PsdSystem(model)\n",
+    "sp.run()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dno.plot_system.show_pyvis(sp, False, notebook=False).show('html/sp.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from world3 import plot_world_with_scales\n",
+    "vensim_plot_variables_scales = {\"Nonrenewable Resources\": [0,1e12],\n",
+    "                          \"industrial output per capita\": [0,1e3],\n",
+    "                          \"food per capita\": [0,1e3],\n",
+    "                          \"population\": [0,16e9],\n",
+    "                          \"persistent pollution index\": [0,32]\n",
+    "                         }\n",
+    "plot_world_with_scales(sp, vensim_plot_variables_scales,title='World3 standart model')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Informations and functions for World3 03 documentation\n",
+    "Execute every cells to get necessary infos to write World3 doc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pydynamo\n",
+    "from pydynamo.world3 import var_color, var_sector, sector_color\n",
+    "s = pydynamo.get_w3()\n",
+    "s.run(400, 0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pysd\n",
+    "model = pysd.read_vensim('../from_vensim/wrld3-03+.mdl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[autoreload of ../from_vensim/wrld3-03+786690 failed: Traceback (most recent call last):\n",
+      "  File \"/usr/lib/python3/dist-packages/IPython/extensions/autoreload.py\", line 245, in check\n",
+      "    superreload(m, reload, self.old_objects)\n",
+      "  File \"/usr/lib/python3/dist-packages/IPython/extensions/autoreload.py\", line 394, in superreload\n",
+      "    module = reload(module)\n",
+      "  File \"/usr/lib/python3.8/imp.py\", line 314, in reload\n",
+      "    return importlib.reload(module)\n",
+      "  File \"/usr/lib/python3.8/importlib/__init__.py\", line 159, in reload\n",
+      "    raise ImportError(msg.format(parent_name),\n",
+      "ImportError: parent '.' not in sys.modules\n",
+      "]\n"
+     ]
+    }
+   ],
+   "source": [
+    "sp = pydynamo.psdsystem.PsdSystem(model)\n",
+    "sp.run()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import re\n",
+    "pd_to_ven1 = {f[0].lower():n for n, f in ((n, re.findall('(\\w+)#', c['Comment'])) for n, c in sp.caracs.items()) if f}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def formatname(comment):\n",
+    "    return re.sub('[\\(\\)\\\"]', '', comment.replace(' ', '_').lower())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "name_and_defs = [(name, formatname(c)) for name, c in s.comments.items() if formatname(c) in sp.caracs]\n",
+    "get_on_hashtag = {n:(f[0].lower(), c) for n, f, c in ((n, re.findall('(\\w+)#', sp.caracs[c]['Comment']), c) for n, c in name_and_defs) if f}\n",
+    "new_small_names = {i: j[0] for i, j in get_on_hashtag.items()}\n",
+    "pd_to_ven2 = {i: j[1] for i, j in get_on_hashtag.items()}\n",
+    "pd_to_ven3 = {name: low_name for name, low_name in name_and_defs if low_name in sp.caracs}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pd_to_ven = {**pd_to_ven1, **pd_to_ven2, **pd_to_ven3,'dynamo_all':'average_life_of_land', 'dynamo_len':'life_expectancy_normal'}\n",
+    "ven_to_pd = {b:a for a, b in pd_to_ven.items()}\n",
+    "not_in_ven = {s for s in s.get_all_nodes() if s not in pd_to_ven}\n",
+    "not_in_pd = {s for s in sp.caracs if s not in ven_to_pd}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json \n",
+    "json.dump(pd_to_ven, open(\"pd_to_ven.json\", 'w+'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ven_eqs = {name:re.sub('(?<=\\w) (?=\\w)', '_', sp.caracs[name]['Original Eqn'].lower()) for name in ven_to_pd}\n",
+    "ven_deps = {name: set(re.findall('[a-z]\\w*',eq)) for name, eq in ven_eqs.items()}\n",
+    "ven_vars = {i for eq in ven_deps.values() for i in eq}\n",
+    "useless_words = {i for i in ven_vars if i not in ven_eqs}\n",
+    "ven_vars = ven_vars.difference(useless_words)\n",
+    "ven_deps = {i:j.difference(useless_words) for i, j in ven_deps.items()}\n",
+    "unused_ven_vars = set(ven_to_pd).difference(ven_vars)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import networkx as nx\n",
+    "G_ven = nx.DiGraph()\n",
+    "for n, dd in ven_deps.items():\n",
+    "    for d in dd:\n",
+    "        G_ven.add_edge(ven_to_pd[d], ven_to_pd[n])\n",
+    "G_pd = s.get_influence_graph()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(set(), 'YOUPI')"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "set(G_ven.nodes).difference(set(G_pd.nodes)), \"YOUPI\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "units = {ven_to_pd[i]: j['Units'] for i, j in sp.caracs.items() if i in ven_to_pd}\n",
+    "s.units = units\n",
+    "for i, j in ((np, sp.caracs[pd_to_ven[np]]['Real Name']) for np in s.get_all_nodes() if np in pd_to_ven):\n",
+    "    s.comments[i] = j"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "json.dump(s.comments, open('pydynamo_package/pydynamo/world3/definitions_w3.json', 'w+'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Write doc for 03\n",
+    "Excecute to write doc for World3 03 in thje appropriate file. Then make"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "infos = dict(get_all_infos(s, var_color, var_sector))\n",
+    "for k, info in list(infos.items()):\n",
+    "    try:\n",
+    "        write_file_var('pydynamo_package/documentation/source/variables/', k, info,\n",
+    "                       genfig=False)\n",
+    "    except Exception as e:\n",
+    "        print(k, info)\n",
+    "        raise e"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Write doc for world2\n",
+    "Excecute to write doc for World2 in the appropriate file. Then make"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pydynamo import get_w2\n",
+    "from collections import defaultdict\n",
+    "import matplotlib.pyplot as plt\n",
+    "import networkx as nx\n",
+    "import numpy as np\n",
+    "import re\n",
+    "w2 = get_w2()\n",
+    "infosw2 = dict(get_all_infos(w2, defaultdict(lambda :'#dddddd'), defaultdict(lambda: 'No sector')))\n",
+    "htmlhtmlhtml\n",
+    "for k, info in list(infosw2.items()):\n",
+    "    try:\n",
+    "        write_file_var('pydynamo_package/documentation/source/w2vars/', k, info, genfig=False)\n",
+    "    except Exception as e:\n",
+    "        print(k, info)\n",
+    "        raise e"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sector_var = {}\n",
+    "source_path = \"world3/docs/source\"\n",
+    "with open(f\"{source_path}/w2vars.rst\", \"w+\") as f:\n",
+    "    f.write(\"\"\"All w2 variables\n",
+    "================\n",
+    "\n",
+    ".. toctree::\n",
+    "   :glob:\n",
+    "   :maxdepth: 1\n",
+    "\n",
+    "\"\"\")\n",
+    "    for v in w2.get_all_nodes():\n",
+    "        f.write(f\"   variables/{rmdyn(v)}\\n\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Additional infos"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    <ui>\n",
+      "        <li style=\"color:#19D9FF\"> Persistent pollution sector </li>\n",
+      "        <li style=\"color:#CF4125\"> Population sector </li>\n",
+      "        <li style=\"color:#0073E6\"> Capital sector </li>\n",
+      "        <li style=\"color:#66CC00\"> Agricultural sector </li>\n",
+      "        <li style=\"color:#8080FF\"> Nonrenewable resource sector </li>\n",
+      "        <li style=\"color:#888888\"> World3 03 supplementary equations sector </li>\n",
+      "        <li style=\"color:#888888\"> World3 03 indicators sector </li>\n",
+      "    </ui>\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('    <ui>')\n",
+    "for sec, col in sector_color.items():\n",
+    "    print(f'        <li style=\"color:{col}\"> {sec} </li>')\n",
+    "print('    </ui>')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Generate graph"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pydynamo import show_pyvis\n",
+    "grafile = 'pydynamo_package/documentation/source/sectormap.html'\n",
+    "show_pyvis(s, colors=var_color).show(grafile)\n",
+    "options = \"\"\"        var options = {\n",
+    "    \"configure\": {\n",
+    "        \"enabled\": false\n",
+    "    },\n",
+    "    \"edges\": {\n",
+    "        \"color\": {\n",
+    "            \"inherit\": true\n",
+    "        },\n",
+    "        \"smooth\": {\n",
+    "            \"enabled\": false,\n",
+    "            \"type\": \"continuous\"\n",
+    "        }\n",
+    "    },\n",
+    "    \"interaction\": {\n",
+    "        \"dragNodes\": true,\n",
+    "        \"hideEdgesOnDrag\": false,\n",
+    "        \"hideNodesOnDrag\": false\n",
+    "    },\n",
+    "    \"physics\": {\n",
+    "        \"enabled\": true,\n",
+    "        \"stabilization\": {\n",
+    "            \"enabled\": true,\n",
+    "            \"fit\": true,\n",
+    "            \"iterations\": 1000,\n",
+    "            \"onlyDynamicEdges\": false,\n",
+    "            \"updateInterval\": 50\n",
+    "        },\n",
+    "        \"barnesHut\": {\n",
+    "          \"gravitationalConstant\": -12900,\n",
+    "          \"centralGravity\": 1.6,\n",
+    "          \"springLength\": 40,\n",
+    "          \"damping\": 0.3,\n",
+    "          \"avoidOverlap\": 0.2\n",
+    "        },\n",
+    "        \"minVelocity\": 0.01,\n",
+    "        \"timestep\": 0.4\n",
+    "    }\n",
+    "};\"\"\"\n",
+    "import re\n",
+    "ss = ''\n",
+    "with open(grafile, 'r') as f:\n",
+    "    ss = re.sub('var options = (.|\\n)*\\}\\;', options, f.read())\n",
+    "    ss = re.sub('width: 500px;', 'width: 1200px;', ss, count=2)\n",
+    "    ss = re.sub('height: 500px;', 'height: 900px;', ss, count=2)\n",
+    "    ss = re.sub('font-size:22px;', 'font-size:50px;', ss, count=1)\n",
+    "with open(grafile, 'w+') as f:\n",
+    "    f.write(ss)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Todo:\n",
+    "- [x] implémenter les variables bonus et créer le graphe\n",
+    "- [ ] Documenter pour explique tabhl, delay etc. et créer des liens\n",
+    "    - [x] tabhl\n",
+    "    - [ ] delay\n",
+    "- [ ] Mieux agencer les in out et tabhl\n",
+    "- [ ] Ajouter les courbes dans le scénario de base et les autres ?\n",
+    "- [ ] Ajouter doc sur les scénarios"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'final_time', 'initial_time', 'saveper', 'time_step'}"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Tout ce qui n'est pas dans pydynamo est inutile, c ok\n",
+    "set(filter(lambda s: not s.startswith('_'), not_in_pd))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "dnovenv",
+   "language": "python",
+   "name": "dnovenv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/01.12.Decomp.ipynb b/01.12.Decomp.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..469309cca849ccc1a1a45586e0e8a5fd22c6f341
--- /dev/null
+++ b/01.12.Decomp.ipynb
@@ -0,0 +1,356 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Décomposer  et complexifier au fur et à mesure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pydynamo as dno\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gdp = pd.read_csv('dataworld/gdp-world-regions-stacked-area.csv')\n",
+    "gdp = gdp[gdp.Entity == 'World'].groupby('Year').sum().filter(items=range(1850, 2018), axis=0)['GDP']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "co2f = pd.read_csv('dataworld/co2fuels.csv')\n",
+    "co2f = co2f[co2f.Entity == 'World'].groupby('Year').sum().filter(items=range(1850, 2018), axis=0)['Annual CO2 emissions (zero filled)']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "acpol = pd.read_csv('dataworld/cumulative-co-emissions.csv')\n",
+    "acpol = acpol[acpol.Entity == 'World'].groupby('Year').sum().filter(items=range(1850, 2018), axis=0)['Cumulative CO2 emissions']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "su"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def eq0_expgdp():\n",
+    "    a.k = a.j + dt*(a.j*c)\n",
+    "    a.i = ai\n",
+    "s = dno.parse_system.system_from_fun(eq0_expgdp)\n",
+    "s.initial_time = 1850\n",
+    "s.final_time = 2050\n",
+    "end_gdp = 2016\n",
+    "s.ai = 1\n",
+    "s.c = np.log(gdp[end_gdp]/gdp[s.initial_time])/(end_gdp - s.initial_time)\n",
+    "s.run()\n",
+    "(gdp/gdp[s.initial_time]).plot()\n",
+    "dno.plot_system.plot_system(s)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Simple lotka voltera"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.lines.Line2D at 0x7f9fa99e8ee0>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def eq0_lvgdp():\n",
+    "    s.k = s.j + dt*s.j*((r*s.j if s.j  < ss - a.k*al else 0) - a.k*p)\n",
+    "    a.k = a.j + dt*a.j*(c*s.j - d)\n",
+    "    a.i = ai\n",
+    "    s.i = ss\n",
+    "    al = 1.1\n",
+    "    p=0.05\n",
+    "s = dno.parse_system.system_from_fun(eq0_lvgdp)\n",
+    "s.initial_time = 1850\n",
+    "s.final_time = 2100\n",
+    "s.ai = 0.01\n",
+    "s.ss = 1\n",
+    "s.r = 0.02\n",
+    "s.c = 0.05\n",
+    "s.d = 0.02\n",
+    "s.run()\n",
+    "# (gdp/gdp[s.start_date]).plot()\n",
+    "dno.plot_system.plot_system(s, scales={'a':0.4})\n",
+    "(gdp/gdp[s.initial_time]/40).plot()\n",
+    "plt.axvline(x=2020, color='red')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Complete model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def cptm():\n",
+    "    A.k = A.j + dt*a*(CT.j + FT.j + ET.j + YT.j - NT.j) # Anthropo\n",
+    "    S.k = S.j + dt*(s*S.j*((HB - H.k)*VB > S.j) - CT.j - FT.j) - S.j*XT.j*xs # Nature\n",
+    "    R.k = R.j - dt*ET.j # Fossil resources\n",
+    "    H.k = H.j + FP.j - LP.k # Anthropo space\n",
+    "    X.k =  X.j + dt*(XT.k - ag*A.k*(1-ai*aix/X.j) - S.k*sg*X.j) # Accumulated pollution \n",
+    "    V.k = min(1/H.k*(H.j*VV.k + FP.k*vi - LP.k*V.j/low_V), 1)# Yield factor\n",
+    "    I.k = I.j + dt*ir*I.j*(MI - I.j) # Intrants efficiency\n",
+    "    \n",
+    "    A.i = ai\n",
+    "    S.i = si\n",
+    "    R.i = ri\n",
+    "    H.i = ai*aih\n",
+    "    X.i = ai*aix\n",
+    "    V.i = vi\n",
+    "    I.i = ii\n",
+    "    \n",
+    "    jdc = 0.3 # John Deer capacity, number of hectares that an anthropo can handle\n",
+    "    ai = 1 # initial ANthropo\n",
+    "    si = (HB - ai*aih)*VB # Initial Nature\n",
+    "    ri = 200*si # Initial Fossil Resources\n",
+    "    aih = 1 # Initial space occupied by an anthropo\n",
+    "    aix = 1 # Initial pollution generated by an anthropo\n",
+    "    vi = 1 # Initial yield capacity\n",
+    "    ii = 1 # initial intrant efficiency\n",
+    "    \n",
+    "    \n",
+    "    ir = 0.002 # Intrant efficiency growth rate\n",
+    "    er = 0.04 # Erosion rate\n",
+    "    a = 0.005 # Anthropo growth rate\n",
+    "    s = 0.01 # Nature growth rate\n",
+    "    c = cc/act # Nature consumption rate\n",
+    "    e = ee/act # Resource extraction rate\n",
+    "    f = ff/act # Deforestation rate\n",
+    "    cc = 5\n",
+    "    ee = 4\n",
+    "    ff = 5\n",
+    "    act = 1e5\n",
+    "    \n",
+    "    x = 3e-2 # Pollution generated by an anthropo\n",
+    "    ag = 0.0001 # Pollution cancelled by an anthropo\n",
+    "    sg = 0.0001 # Pollution cancelled by nature\n",
+    "    \n",
+    "    cag = 100 # Cost of pollution cancellation for an anthropo\n",
+    "    xv = 3e-4 # Effect of pollution on crops\n",
+    "    xs = 2e-4 # Effect of pollution on nature\n",
+    "    \n",
+    "    ic = 0.2 # Intrant cost\n",
+    "    n = 0.8 # Default needs for an anthropo\n",
+    "    \n",
+    "    low_V = 1.4 # We abandon the lowest efficient yields\n",
+    "    MI = 10 # Maximum intrant efficiency\n",
+    "    HB = 200 # Total space\n",
+    "    VB = 5*vi # Yield of nature space\n",
+    "\n",
+    "    YT.k = H.k*V.k*I.k # Total yields per year\n",
+    "    VV.k = max(V.j + dt*V.j*(- er)- XT.j*xv, 0) # Intermediate yields factor\n",
+    "    NT.k = H.k*I.k*ic + n*A.k + X.j*ag*A.k*cag # Total needs per year\n",
+    "    CT.k = A.k*S.k*c if S.k > critS else 0 # Total nature consumption per year\n",
+    "    ET.k = A.k*R.k*e  if R.k > critR else 0 # Total resource extraction per year\n",
+    "    FT.k = FP.k*S.k/(HB - H.k) # Total deforestation yields per year\n",
+    "    FP.k = A.k*(HB - H.k)*f  if HB - H.k > critH else 0 # Total deforestation space per year\n",
+    "    XT.k = A.k*x # Pollution produced per year\n",
+    "    LP.k = max(0, H.j + FP.j-A.j*jdc) # Lost place per year\n",
+    "    LP.i = 0 \n",
+    "    \n",
+    "    critS = si/5 # Critic nature\n",
+    "    critR = ri/100 # Critic resources\n",
+    "    critH = HB/100 # Critic space"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f9fa9934fa0>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = dno.parse_system.system_from_fun(cptm)\n",
+    "s.initial_time = 1850\n",
+    "s.final_time = 2100\n",
+    "s.run(dt=0.5)\n",
+    "plt.figure(figsize=(15, 10))\n",
+    "dno.plot_system.plot_system(s, v_names=scales, scales = scales, colors=colors)\n",
+    "plt.ylim([0, 1.2])\n",
+    "plt.plot(gdp/gdp[1850]*s.ai/scales['A']*4, color='red', label='GDP', linestyle='--')\n",
+    "plt.plot(acpol/acpol[1850]*s.ai/scales['X']/3, color='slateblue', label='acpol', linestyle='--')\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scales = {\n",
+    "    'A': max(s.A),\n",
+    "    'S': s.si,\n",
+    "    'R': s.R[0],\n",
+    "    'H': s.HB,\n",
+    "    'X': s.X[0]*400,\n",
+    "    'V': 1,\n",
+    "\n",
+    "#     'NT': max(s.NT),\n",
+    "#     'CT': s.si/100,\n",
+    "#     'ET': s.ri/100,\n",
+    "#     'YT': s.vi*s.HB*s.MI,\n",
+    "#     'FT': s.HB*s.V/10,\n",
+    "#     'XT': s.X[0]*400/30,\n",
+    "\n",
+    "#     'FP': s.HB/100,\n",
+    "#     'LP': s.HB/100,\n",
+    "\n",
+    "    'I': s.MI,\n",
+    "#     'VV': 1,\n",
+    "}\n",
+    "\n",
+    "colors = {\n",
+    "    'CT': 'darkolivegreen',\n",
+    "     'A': 'r',\n",
+    "     'S': 'g',\n",
+    "     'V': 'lime',\n",
+    "     'NT': 'black',\n",
+    "     'H': 'brown',\n",
+    "     'FP': 'peru',\n",
+    "     'LP': 'sandybrown',\n",
+    "     'ET': 'magenta',\n",
+    "     'YT': 'yellow',\n",
+    "     'R': 'gray',\n",
+    "     'I': 'orange',\n",
+    "     'XT': 'slateblue',\n",
+    "     'FT': 'darkorange',\n",
+    "     'VV': 'aquamarine',\n",
+    "     'X': 'purple'\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dno.plot_system.show_pyvis(s).show('haha.html')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "dnovenv",
+   "language": "python",
+   "name": "dnovenv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/01.17.article.ipynb b/01.17.article.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..f96f819e2c685702f55a1c44b7b5827850bb0d20
--- /dev/null
+++ b/01.17.article.ipynb
@@ -0,0 +1,217 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Figures pour l'article"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pydynamo as dno\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import networkx as nx\n",
+    "from pydynamo import get_w3, var_color\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = get_w3()\n",
+    "s.run(200, 1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Boucle de rétroaction positive pour le produit industriel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Coordonnées des noeuds de la figure\n",
+    "x = 1/np.sqrt(3)\n",
+    "d = (0, 0.5)\n",
+    "pos = {\n",
+    "    'ic': np.array((0, 1)),\n",
+    "    'io': np.array((-x, 0)),\n",
+    "    'icir': np.array((x, 0))\n",
+    "}\n",
+    "\n",
+    "# On récupère le graphique d'influence des noeuds\n",
+    "G = s.get_influence_graph()\n",
+    "\n",
+    "# On détermine les positions fixes et non fixes des noeuds\n",
+    "fixed = set(pos.keys())\n",
+    "non_fixed = {a for a, b in G.in_edges(pos)}.difference(fixed)\n",
+    "ioloop = nx.DiGraph(nx.subgraph(G, fixed.union(non_fixed)))\n",
+    "for f in fixed:\n",
+    "    aa = {a for a, b in ioloop.in_edges(f) if a not in fixed}\n",
+    "    for a, posa in nx.spring_layout(nx.subgraph(ioloop, aa), k=0.2).items():\n",
+    "        pos[a] = pos[f] + posa\n",
+    "pos = nx.spring_layout(ioloop, k=0.2, pos=pos, fixed=fixed)\n",
+    "\n",
+    "# On dessine le graphe\n",
+    "nx.draw(ioloop, pos = pos, with_labels=True, node_color= [var_color[i] for i in pos], node_size=1000, width=3, edge_color='gray')\n",
+    "nx.draw_networkx_edge_labels(ioloop, pos, edge_labels={(a, b): s.eqs['update'][b]['raw_line'].replace('/', '\\n/').replace('.k', '').replace('.j', '') for a,b in nx.subgraph(ioloop, fixed).edges() if a!=b}, rotate=False)\n",
+    "plt.title('Positive retroaction loop for industrial production');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "table = np.array([0.5, 0.05, 0.02, 0, 0.02, 0.05, 0.1, 0.15, 0.2, 0.25, 0.26]) + 0.2\n",
+    "\n",
+    "table = [round(i*20) for i in table]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[14, 5, 4, 4, 4, 5, 6, 7, 8, 9, 9]"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'How tabhl function works')"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# TABHL function\n",
+    "x = np.arange(0, 10.1, 1)\n",
+    "table = [14, 5, 4, 3, 4, 5, 6, 7, 8, 9, 9]\n",
+    "plt.scatter(x, table, label='Table points')\n",
+    "plt.plot(x, table, label='Function curve')\n",
+    "a= 4.48\n",
+    "b = 4.5\n",
+    "plt.plot([b, b], [0, a],linestyle='--', color='red', label='x to y value')\n",
+    "plt.plot([0, b], [a, a], linestyle='--', color='red')\n",
+    "plt.xlabel('x value')\n",
+    "plt.ylabel('tabhl result')\n",
+    "plt.legend()\n",
+    "plt.title('How tabhl function works')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# CLIP function\n",
+    "s.alai1 = 1\n",
+    "s.alai2 = 2\n",
+    "s.pyear=2002\n",
+    "s.run(200, 1)\n",
+    "plt.plot(s.time, s.alai)\n",
+    "plt.plot([s.pyear]*2, [0, s.alai1], color='r', linestyle='-.')\n",
+    "plt.plot([s.pyear, s.final_time], [s.alai1]*2, color='green', linestyle='--')\n",
+    "plt.plot([s.initial_time, s.pyear], [s.alai2]*2, color='orange', linestyle='--')\n",
+    "plt.ylim([0, 3])\n",
+    "plt.legend(['clip function', 'pyear', 'val1', 'val2']);\n",
+    "plt.xlabel('time')\n",
+    "plt.ylabel('value');"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/02.01.sdcomp.ipynb b/02.01.sdcomp.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..d9eb424202ea824afd6114f5fe98e225491bd38b
--- /dev/null
+++ b/02.01.sdcomp.ipynb
@@ -0,0 +1,316 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Compare with pysd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pydynamo import plot_world_03, get_w3, psdsystem"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Pdynamo model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x1080 with 11 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = get_w3()\n",
+    "s.run(400, 0.5)\n",
+    "plot_world_03(s)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Pysd model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pysd \n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = pysd.read_vensim('../from_vensim/wrld3-03+.mdl')\n",
+    "sp = psdsystem.PsdSystem(model)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import re\n",
+    "def formatname(comment):\n",
+    "    return re.sub('[\\(\\)\\\"]', '', comment.replace(' ', '_').lower())\n",
+    "import json\n",
+    "pd_to_ven = json.load(open('pd_to_ven.json', 'r'))\n",
+    "ven_to_pd = {j:i  for i, j in pd_to_ven.items()}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class gsp(object):\n",
+    "    def __init__(self, sp):\n",
+    "        self.sp = sp\n",
+    "        self.dfpdcol = None\n",
+    "\n",
+    "    def __getattribute__(self, name):\n",
+    "        if object.__getattribute__(self, 'dfpdcol') is not None:\n",
+    "            if name in object.__getattribute__(self, 'dfpdcol').columns:\n",
+    "                return np.array(object.__getattribute__(self, 'dfpdcol')[name])\n",
+    "        return object.__getattribute__(self, name)\n",
+    "    \n",
+    "    def majdf(self):\n",
+    "        if sp.df_run is not None:\n",
+    "            dfpdcol = self.sp.df_run.rename(columns={a: ven_to_pd[formatname(a)] for a in self.sp.df_run.columns if formatname(a) in ven_to_pd })\n",
+    "            self.dfpdcol= dfpdcol.reset_index().rename(columns={'index':'time'})\n",
+    "        \n",
+    "gg = gsp(sp)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/achille/.local/lib/python3.8/site-packages/pandas/core/internals/blocks.py:849: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
+      "  arr_value = np.array(value)\n"
+     ]
+    },
+    {
+     "ename": "FloatingPointError",
+     "evalue": "invalid value encountered in double_scalars",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFloatingPointError\u001b[0m                        Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-19-19916a16a6c6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mpar\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'nri'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'fcaor2t'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mxr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataArray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1.0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.05\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'fcaortm'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m2002\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mpar\u001b[0m  \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0mpd_to_ven\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0mj\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mpar\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0msp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpar\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0mgg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmajdf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mplot_world_03\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.local/lib/python3.8/site-packages/pysd/py_backend/statefuls.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, params, return_columns, return_timestamps, initial_condition, final_time, time_step, saveper, reload, progress, flatten_output, cache_output)\u001b[0m\n\u001b[1;32m   1636\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclean_caches\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1637\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1638\u001b[0;31m         \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_integrate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcapture_elements\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'step'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1639\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1640\u001b[0m         \u001b[0;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcomponents\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dependencies\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"OUTPUTS\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.local/lib/python3.8/site-packages/pysd/py_backend/statefuls.py\u001b[0m in \u001b[0;36m_integrate\u001b[0;34m(self, capture_elements)\u001b[0m\n\u001b[1;32m   2126\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0min_bounds\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2127\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0min_return\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2128\u001b[0;31m                 outputs.at[self.time()] = [getattr(self.components, key)()\n\u001b[0m\u001b[1;32m   2129\u001b[0m                                            for key in capture_elements]\n\u001b[1;32m   2130\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_euler_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/.local/lib/python3.8/site-packages/pysd/py_backend/statefuls.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m   2126\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0min_bounds\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2127\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0min_return\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2128\u001b[0;31m                 outputs.at[self.time()] = [getattr(self.components, key)()\n\u001b[0m\u001b[1;32m   2129\u001b[0m                                            for key in capture_elements]\n\u001b[1;32m   2130\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_euler_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/Bureau/couillet/world3/from_vensim/wrld3-03+.py\u001b[0m in \u001b[0;36mresource_use_intensity\u001b[0;34m()\u001b[0m\n\u001b[1;32m   6333\u001b[0m     ADAPTIVE TECHNOLOGICAL CONTROL CARDS nonrenewable                 resource usage intensity (RESINT#--)\n\u001b[1;32m   6334\u001b[0m     \"\"\"\n\u001b[0;32m-> 6335\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mresource_usage_rate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mindustrial_output\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   6336\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   6337\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mFloatingPointError\u001b[0m: invalid value encountered in double_scalars"
+     ]
+    }
+   ],
+   "source": [
+    "import xarray as xr\n",
+    "par = {'nri':2, 'fcaor2t':xr.DataArray([1.0, 0.1, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05]), 'fcaortm':2002}\n",
+    "par  = {pd_to_ven[i]:j for i, j in par.items()}\n",
+    "sp.model.run(params=par)\n",
+    "gg.majdf()\n",
+    "plot_world_03(gg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get initial values dico\n",
+    "import networkx as nx\n",
+    "dicinit = {v:(getattr(s, v)[1], gg.dfpdcol.loc[1, v]) for v in s.nodes['var'] if v != 'lufdi'}\n",
+    "sdic = {v: dicinit[v] for v in nx.topological_sort(s.get_init_graph()) if v != 'lufdi'}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'state': array([1.2573448]), 'shape_info': None}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sp.model.components._smooth_delayed_labor_utilization_fraction.export()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(None, 6210132349.328245)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.run(1, 0.5)\n",
+    "s.smooth_ai.state, s.smooth_ai(s.cai[0], 2, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.5"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.dt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5302533087.332062"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.ai[0] + (s.cai[0]-s.ai[0])/2*0.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "IndexError",
+     "evalue": "index 1 is out of bounds for axis 0 with size 1",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-14-5da53f4a6eed>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m [(s.ai[0], s.cai[0], s.ai[1], s.cai[1]), \n\u001b[0m\u001b[1;32m      2\u001b[0m (gg.ai[0], gg.cai[0], gg.ai[1], gg.cai[1])]\n",
+      "\u001b[0;31mIndexError\u001b[0m: index 1 is out of bounds for axis 0 with size 1"
+     ]
+    }
+   ],
+   "source": [
+    "[(s.ai[0], s.cai[0], s.ai[1], s.cai[1]), \n",
+    "(gg.ai[0], gg.cai[0], gg.ai[1], gg.cai[1])]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "eps = 1e-6\n",
+    "{v: (a, b) for v, (a, b) in sdic.items() if abs(a-b) > eps}"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/02.02.DataTransformer.ipynb b/02.02.DataTransformer.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..34416e512fed2b907af4dea26acdddc1cd595885
--- /dev/null
+++ b/02.02.DataTransformer.ipynb
@@ -0,0 +1,342 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def lininterpol(df):\n",
+    "    df2 = df.copy()\n",
+    "    for k, i in enumerate(df.index[:-1]):\n",
+    "        v = df[i]\n",
+    "        if i + 1 != df.index[k+1]:\n",
+    "            i2 = df.index[k+1]\n",
+    "            v2 = df[i2]\n",
+    "            d = i2 - i\n",
+    "            for j in range(d):\n",
+    "                df2[i + j] = v + j/d*(v2-v)\n",
+    "    return df2.sort_index(ascending=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gdp = pd.read_csv('dataworld/gdp-world-regions-stacked-area.csv')\n",
+    "gdp = gdp[gdp.Entity == 'World'].groupby('Year').sum().filter(items=range(1850, 2018), axis=0)['GDP']\n",
+    "gdp = lininterpol(gdp)\n",
+    "#gdp = pd.read_csv('dataworld/world-gdp-over-the-last-two-millennia.csv')\n",
+    "#gdp = gdp.rename(columns = {'World GDP in 2011 Int.$ (OWID based on World Bank & Maddison (2017))': 'GDP'}).set_index('Year')['GDP'].filter(items=range(1850, 2018))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "co2f = pd.read_csv('dataworld/co2fuels.csv')\n",
+    "co2f = co2f[co2f.Entity == 'World'].groupby('Year').sum().filter(items=range(1850, 2018), axis=0)['Annual CO2 emissions (zero filled)']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "acpol = pd.read_csv('dataworld/cumulative-co-emissions.csv')\n",
+    "acpol = acpol[acpol.Entity == 'World'].groupby('Year').sum().filter(items=range(1850, 2018), axis=0)['Cumulative CO2 emissions']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pop = pd.read_csv('dataworld/population.csv')\n",
+    "pop = pop[pop.Entity == 'World'].set_index('Year').filter(items=range(1850, 2018), axis=0).rename(columns={'Population (historical estimates)':'population'})['population']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 206,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lu = pd.read_csv('dataworld/global-land-use-since-10000bc.csv')\n",
+    "lu = lu.set_index(['Year','Entity'])['area_aggregated_categories'].unstack(level=1)\n",
+    "lu = lu[['Cropland', 'Villages', 'Urban', 'Pasture']].filter(items=range(1850, 2018), axis=0)\n",
+    "crop = lininterpol(lu.Cropland)\n",
+    "vil = lininterpol(lu.Villages)\n",
+    "urb = lininterpol(lu.Urban)\n",
+    "past = lininterpol(lu.Pasture)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 207,
+   "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>population</th>\n",
+       "      <th>GDP</th>\n",
+       "      <th>Co2emissions</th>\n",
+       "      <th>Co2cummulative</th>\n",
+       "      <th>Cropland</th>\n",
+       "      <th>Villages</th>\n",
+       "      <th>Urban</th>\n",
+       "      <th>Pasture</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Year</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1850</th>\n",
+       "      <td>1.278698e+09</td>\n",
+       "      <td>1.446495e+12</td>\n",
+       "      <td>1.968960e+08</td>\n",
+       "      <td>4.759415e+09</td>\n",
+       "      <td>7.073558e+06</td>\n",
+       "      <td>2.521307e+06</td>\n",
+       "      <td>5.421520e+05</td>\n",
+       "      <td>2.022368e+07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1851</th>\n",
+       "      <td>1.281044e+09</td>\n",
+       "      <td>1.469191e+12</td>\n",
+       "      <td>1.988050e+08</td>\n",
+       "      <td>4.958220e+09</td>\n",
+       "      <td>7.166265e+06</td>\n",
+       "      <td>2.530926e+06</td>\n",
+       "      <td>5.448147e+05</td>\n",
+       "      <td>2.024616e+07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1852</th>\n",
+       "      <td>1.283605e+09</td>\n",
+       "      <td>1.491888e+12</td>\n",
+       "      <td>2.075509e+08</td>\n",
+       "      <td>5.165771e+09</td>\n",
+       "      <td>7.258972e+06</td>\n",
+       "      <td>2.540544e+06</td>\n",
+       "      <td>5.474774e+05</td>\n",
+       "      <td>2.026865e+07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1853</th>\n",
+       "      <td>1.285405e+09</td>\n",
+       "      <td>1.514584e+12</td>\n",
+       "      <td>2.172092e+08</td>\n",
+       "      <td>5.382980e+09</td>\n",
+       "      <td>7.351679e+06</td>\n",
+       "      <td>2.550163e+06</td>\n",
+       "      <td>5.501401e+05</td>\n",
+       "      <td>2.029114e+07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1854</th>\n",
+       "      <td>1.287318e+09</td>\n",
+       "      <td>1.537281e+12</td>\n",
+       "      <td>2.551390e+08</td>\n",
+       "      <td>5.638119e+09</td>\n",
+       "      <td>7.444386e+06</td>\n",
+       "      <td>2.559781e+06</td>\n",
+       "      <td>5.528028e+05</td>\n",
+       "      <td>2.031362e+07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2013</th>\n",
+       "      <td>7.210900e+09</td>\n",
+       "      <td>9.847079e+13</td>\n",
+       "      <td>3.528303e+10</td>\n",
+       "      <td>1.445959e+12</td>\n",
+       "      <td>1.929549e+07</td>\n",
+       "      <td>9.234276e+06</td>\n",
+       "      <td>2.196321e+06</td>\n",
+       "      <td>3.509707e+07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2014</th>\n",
+       "      <td>7.295610e+09</td>\n",
+       "      <td>1.013586e+14</td>\n",
+       "      <td>3.553444e+10</td>\n",
+       "      <td>1.481494e+12</td>\n",
+       "      <td>1.934339e+07</td>\n",
+       "      <td>9.300393e+06</td>\n",
+       "      <td>2.217320e+06</td>\n",
+       "      <td>3.499555e+07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2015</th>\n",
+       "      <td>7.380118e+09</td>\n",
+       "      <td>1.042464e+14</td>\n",
+       "      <td>3.549641e+10</td>\n",
+       "      <td>1.516990e+12</td>\n",
+       "      <td>1.937905e+07</td>\n",
+       "      <td>9.365333e+06</td>\n",
+       "      <td>2.237074e+06</td>\n",
+       "      <td>3.490057e+07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016</th>\n",
+       "      <td>7.464344e+09</td>\n",
+       "      <td>1.071343e+14</td>\n",
+       "      <td>3.545246e+10</td>\n",
+       "      <td>1.552443e+12</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2017</th>\n",
+       "      <td>7.548183e+09</td>\n",
+       "      <td>1.104307e+14</td>\n",
+       "      <td>3.592574e+10</td>\n",
+       "      <td>1.588368e+12</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>168 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        population           GDP  Co2emissions  Co2cummulative      Cropland  \\\n",
+       "Year                                                                           \n",
+       "1850  1.278698e+09  1.446495e+12  1.968960e+08    4.759415e+09  7.073558e+06   \n",
+       "1851  1.281044e+09  1.469191e+12  1.988050e+08    4.958220e+09  7.166265e+06   \n",
+       "1852  1.283605e+09  1.491888e+12  2.075509e+08    5.165771e+09  7.258972e+06   \n",
+       "1853  1.285405e+09  1.514584e+12  2.172092e+08    5.382980e+09  7.351679e+06   \n",
+       "1854  1.287318e+09  1.537281e+12  2.551390e+08    5.638119e+09  7.444386e+06   \n",
+       "...            ...           ...           ...             ...           ...   \n",
+       "2013  7.210900e+09  9.847079e+13  3.528303e+10    1.445959e+12  1.929549e+07   \n",
+       "2014  7.295610e+09  1.013586e+14  3.553444e+10    1.481494e+12  1.934339e+07   \n",
+       "2015  7.380118e+09  1.042464e+14  3.549641e+10    1.516990e+12  1.937905e+07   \n",
+       "2016  7.464344e+09  1.071343e+14  3.545246e+10    1.552443e+12           NaN   \n",
+       "2017  7.548183e+09  1.104307e+14  3.592574e+10    1.588368e+12           NaN   \n",
+       "\n",
+       "          Villages         Urban       Pasture  \n",
+       "Year                                            \n",
+       "1850  2.521307e+06  5.421520e+05  2.022368e+07  \n",
+       "1851  2.530926e+06  5.448147e+05  2.024616e+07  \n",
+       "1852  2.540544e+06  5.474774e+05  2.026865e+07  \n",
+       "1853  2.550163e+06  5.501401e+05  2.029114e+07  \n",
+       "1854  2.559781e+06  5.528028e+05  2.031362e+07  \n",
+       "...            ...           ...           ...  \n",
+       "2013  9.234276e+06  2.196321e+06  3.509707e+07  \n",
+       "2014  9.300393e+06  2.217320e+06  3.499555e+07  \n",
+       "2015  9.365333e+06  2.237074e+06  3.490057e+07  \n",
+       "2016           NaN           NaN           NaN  \n",
+       "2017           NaN           NaN           NaN  \n",
+       "\n",
+       "[168 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 207,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.DataFrame(data = [pop, gdp, co2f, acpol, crop, vil, urb, past]).T.rename(columns={\n",
+    "    'Annual CO2 emissions (zero filled)': 'Co2emissions',\n",
+    "    'Cumulative CO2 emissions': 'Co2cummulative'\n",
+    "}) \n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 208,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.to_csv('pydynamo_package/data/data.csv')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/11.19.tester.ipynb b/11.19.tester.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b243910911442cdc67c6d93e8d23d83b5cb24047
--- /dev/null
+++ b/11.19.tester.ipynb
@@ -0,0 +1,245 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Test the (old) pydynamo program"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import networkx as nx\n",
+    "import numpy as np\n",
+    "import sys\n",
+    "sys.path.append('./world3')\n",
+    "sys.path.append('/home/achille/Bureau/couillet/world3/pyworld3/pyworld3/')\n",
+    "import system\n",
+    "from dynamo_reader import read_dynamo\n",
+    "from world3_utils import variable_definitions\n",
+    "from plot_utils import plot_world_variables\n",
+    "from pyworld3 import World3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Simulate world3 model for comparison \n",
+    "# and exogenous inputs if needed\n",
+    "w = World3(dt=0.5)\n",
+    "w.init_world3_constants()\n",
+    "w.init_world3_variables()\n",
+    "w.set_world3_table_functions()\n",
+    "w.set_world3_delay_functions()\n",
+    "w.run_world3()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simulation\n",
+    "### Procedure:\n",
+    "- Write some new lines in the dynamo_file\n",
+    "- Run cells below which compares pydynamo run with pyworld3 run, using as exogenous inputs the ones of pyworld3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Get dynamo instructions\n",
+    "dynamo_file = 'world3/world3_dynamo_code.py'\n",
+    "instr = read_dynamo(dynamo_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Special parameters\n",
+    "N = 400\n",
+    "dt = 0.5\n",
+    "start_time = 1900\n",
+    "specials = {'dt': dt, 'N':N, 'start_time':start_time}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Init a first system\n",
+    "s = system.System(*instr, **specials, verbose=False)\n",
+    "\n",
+    "# Automatically get not updated variables\n",
+    "need_for_exogenous = set(s.yield_all_non_updated_vars())\n",
+    "\n",
+    "# Add exogenous from pyworld3 run in cas we need it\n",
+    "if len(need_for_exogenous) != 0:\n",
+    "    print('Need for exogenous inputs: ', need_for_exogenous)\n",
+    "    exogenous_dic = {var: getattr(w, var) for var in need_for_exogenous}\n",
+    "    s = system.System(*instr, **specials, exogenous=exogenous_dic, verbose=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# In case we want to plot the updating graph\n",
+    "# plt.figure(figsize=(20, 20))\n",
+    "# s.show_update_graph(k=False);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Run \n",
+    "s.run()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot variables and compare to world3 run\n",
+    "var_to_compare = ['ppolx', 'pop', 'fpc','iopc', 'nrfr']\n",
+    "s.plot_vars(var_to_compare, extern=w)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plot variables in world3 manner\n",
+    "plot_world_variables(s.time,\n",
+    "     [s.nrfr, s.iopc, s.fpc, s.pop,\n",
+    "      s.ppolx],\n",
+    "     [\"NRFR\", \"IOPC\", \"FPC\", \"POP\", \"PPOLX\"],\n",
+    "     [[0, 1], [0, 1e3], [0, 1e3], [0, 16e9], [0, 32]],\n",
+    "     figsize=(7, 5),\n",
+    "     grid=1,\n",
+    "     title=\"World3 standard run\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'arable land initial [hectares]. The default is 0.9e9.'"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "variable_definitions['ali']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[1.1, 0.6, 0.35, 0.2, 0.15, 0.15]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.tables['jpscut']"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/11.20.scenarios.ipynb b/11.20.scenarios.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..cca756478395ed91070ed570f3a6b68a70a2b606
--- /dev/null
+++ b/11.20.scenarios.ipynb
@@ -0,0 +1,222 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import system\n",
+    "from dynamo_reader import read_dynamo, Runs_reader\n",
+    "sys.path.append('./world3')\n",
+    "from plot_utils import plot_world_variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Each scenario and associated number:\n",
+      "\n",
+      "0 : Fig 35. Standart run\n",
+      "1 : Fig 36. Doubled ressources\n",
+      "2 : Fig 37. \"Unlimited\" ressources\n",
+      "3 : Fig 39. \"Unlimited\" ressources & pollution controls\n",
+      "4 : Fig 40. \"Unlimited\" ressources & pollution controls, & Increment agricultural productivity\n",
+      "5 : Fig 41. \"Unlimited\" ressources & pollution controls & birth controls\n",
+      "6 : Fig 42. \"Unlimited\" ressources & pollution controls & Birth controls & Increment agricultural productivity\n",
+      "7 : Fig 44. World model with stabilized population\n",
+      "8 : Fig 45. World model with stabilized pop. and cap.\n",
+      "9 : Fig 46. \"Stabilized world model 1\n",
+      "10 : Fig 47. \"Stabilized world model 2\n",
+      "11 : Fig 48. \"Stabilization policies in the year 2000\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Get dynamo instructions\n",
+    "base_file = 'world3/world3_dynamo_code.py'\n",
+    "runs_file = 'world3/limits_to_growth_code.py'\n",
+    "new_file = 'new_instr.py'\n",
+    "\n",
+    "reader = Runs_reader(runs_file, new_file, base_file)\n",
+    "print('Each scenario and associated number:\\n')\n",
+    "print('\\n'.join((f'{i} : {name}' for i, name in enumerate(reader.get_run_names()))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cbrcbr# Choose a scenario and get associated instructions\n",
+    "scenario_number = 0\n",
+    "fig_title, new_instructions = reader.write_instructions(scenario_number)\n",
+    "instr = read_dynamo(new_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Special parameters\n",
+    "N = 400\n",
+    "dt = 0.5\n",
+    "start_time = 1900\n",
+    "specials = {'dt': dt, 'N':N, 'start_time':start_time}\n",
+    "\n",
+    "# Init a first system\n",
+    "s = system.System(*instr, **specials, verbose=False)\n",
+    "\n",
+    "# Run \n",
+    "s.run()\n",
+    "\n",
+    "# plot variables in world3 manner\n",
+    "plot_world_variables(s.time,\n",
+    "     [s.nrfr, s.iopc, s.fpc, s.pop,\n",
+    "      s.ppolx],\n",
+    "     [\"NRFR\", \"IOPC\", \"FPC\", \"POP\", \"PPOLX\"],\n",
+    "     [[0, 1], [0, 1e3], [0, 1e3], [0, 16e9], [0, 32]],\n",
+    "     figsize=(7, 5),\n",
+    "     grid=1,\n",
+    "     title=fig_title)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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O7d8Ay4DExiSenZJQgX5Z4XqjVSyEEOIYXinCSanxGnAxMG3mjIxNwEagBPhrjZedNnNGxs4aj5ON9zxt7GMlMBd4uDExrVnO6pjOOGtdMVuE0QHrSuCftjTbBluazQmchX7rTuPZXcXovZIfw27egH7teyl6ka/vfWvQC+BH2M1OYC369eKG/Auoq5c0wFPAfZbk9Eb93GSnJOwCPkLvqCaEEOIYStM0X+cghBBCdEgyYpYQQgjhI62qCDvjrCc646wX1Hj+ojPO+pbxaMrAGk1mS7M9dcxzf1ua7QNvxsRufuqY5/7Yzd6NKYQQotWot3e00aHqZqAXMCcpNX5RjW2PJaXG/18d78us+TwpNX5KI/NJAf5R4/lZ6Le4hKJ32rqorjc646xHxbRmORsbs0pvW5rtEUei4x+2NFsQeiellfW9wZZmOyqmI9HR5JjYzY9gd/0Du7lRMbGbM49+7mpqzFpZktOnZ6ckHNszGkty+lHxslMSPBJPCCFEw7covYZeAH8HXpo5I2N+Ump81e0mlwC1FuFjKaXmaJp2diNeGmvNci6u8TzfmuX8HMAZZ721MbGaEbPKjcAHtjTbI+i32Mx2JDr+3RIxsZurY2J3eTtmXZ7kz7cn1RZPOhEIITo8TdOUJ/ZTb8esmTMy1iSlxp9kLAcAr6L3nr0KWJKUGj+iUUGUWqZp2uiGXueMs26wZjkH17FtozXLOagx8ZoS05Zmq3ma24T+j8cijMFIHImOFZ6Oid1cb0zsLs/HBCzJ6Wvq2g0wKDslIaihffQfOFj7et7vlFVWUlrhpqzqUXn0cmm58fWo11T+6fWlFce+pu7l5ggK8CMk0J8Qk/4INvkfeR7oT2igP+FBAdWPsKAAwoOPfh4RbKw3Hv5+x/e7l5mZyZQpU45rH94k+R2/1p6j5Hd8lFIeK8INtYQDqxaSUuMrgFtmzsj4G5CBPjmCp+U646zjrFnO32qudMZZxwO5XogH+m05NR1En4XpX+gzAcW3k5igz+h0lhGvJgUs/vPL/8zkB7ZeTRuRyxPcbq26qJeUV1JcVklxeSVFZZVHPS8ur2TNuix6W/pXPy+p3uamuOr15ZXsLyyjqKyCwtIKDpdUUFrRuEIfYvI3irI/kSEmzMc8okKrlgOPeh4VaiLE5O/lIyWEaEsaKsLLZs7IODspNX5O1Yqk1PgnZ87IyAHqmhDgeDwMfOKMs76DPnoT6CM/JQJXeCEejkTHVG/st152V8vH1H2HPk3hqmM3HHvtt7Xx81ME++ktWXOIqd7Xdi34gymnDmhyjPJKN4WlFRQYj6riXFhaSUFpOQWllRSUVFBYpq8vKK3gcEk5ruJycg4W4yrWlyvcdZ9dMvkrQvwhduUCosMDiQ4PIjoskC41lqPDg6qfhwX6o5RH/uEWQrRC9RbhpNT4a2fOyBg7c0bGmKTU+KUzZ2QMQR+UPyspNb7+v4TNYM1y/u6Ms45DnynoBmP1OmC8NcvZ1BmIxDGyUxJqHQ3L2HZ1S+bSGpn8/YgKDSQqNLDhF9dB0zQKyypxFZdzqKhML8xF5dUF+lBxOc7N2wg2h7GvoJS1OS72FZRyuKSi1v0FBfjRJTyImIggukcG091sPCKD6RZ5ZDkkUFrYQrRFDfWO/hv6LEUBM2dk/AiMA+YByTNnZIxISo2vc37g5rJmOfeg94QWos1RSlVfO+4ZFVLrazIzdzNlyqij1pVWVHKgsIz9BWXsKyhlf0EZ+wv1r3sLStmTX8rmvQUs2ryPw6V/LtiRwQF0NwcTaw6hV6cQencOpXen0OrlTqEmaVEL0Qo1dDr6MmA4EATsBnolpcbnz5yR8U/gN4whJtsrW5ptuiPR0WCPYY+ym6djd7VsTOFzQQH+xJpDiDXXXrhrKiytYHd+CXmuEna5SvTl/BJ2G89X7zzEoaLyo94TFuhP7856Ue7VKZQ+nY1HtF6spSUthG80VIQrklLjK4GimTMy/jDmBCYpNb545oyM5nVXbSJnnDXamuXc3xKxatGo23baQUzRhoQFBTAgJpwBMXX3jTxcUs7Og8XsOFDEDuPrzoPF7DxYxK9/7KewrPKo18dEBFUXZnd+GfsidtKrUwiRwSbCgvwJDdRb98EmP2lRC+FBDRXhspkzMkKNmY+qz5/NnJFhRp8/16OccdYU4J/WLOc+Z5x1NPrgFW5nnNUEXG/Ncs73dExbmq2+23aaOutR49jNLR9TdCgRwSassSassZF/2qZpGgeLytl+oIjtB4rYcaCI7fv15d+3HiD3UDlf/1H7LJh+CsICAwgN8icsUL91q+o2r9CgAMIC9Z7jVV8jgo/0Go8MCdC/BpuIDDEd961eQrQHDRXhyUmp8aUASanxNYuuiUZOaddECdYsZ7Kx/DxwhTXLudQZZx0EfAg06n7YJjru23baSEwhAP26deewQDqHBTK8d9Sftv+UMY8TThrLzoPFFJSWU1haSWGZ3ku8qEzvFV5UWklBWQVFpfr63fklFJVVGtsq/tTSrk14kFGUQ0xEBuvLncMC9V7jYUFEhwfSJTyoel3n0EAC/FvVSLtCHLeGekeX1rF+H7DPG/k446wB1ixnBRBizXIuBbBmOTc646wNDiTRTN8B4Y5Ex6pjNxw7LKWnY2J3/Snmn4alFKKFBfgpLF3CsHQJa/Y+3G6NovLK6lu48osrjK/G81rWb9tfxModhzhQWEZlHbd5dQo1EaIq6LPxV2LNIXSLDCa2Ro/xWHMw0eFB0soWbUZDLeGW9iow2zgtPccZZ/0P8AX64BWrvBHQkeio87YdR6LDO7ft2F11xsTu6vC3Com2z8/vSC/xxnQ2q8nt1nAVl7O/sJR9BWVGr3F9eX9hKVlbcyiv1Ph96wHy8kv+dF+2v5+iW0QQ3c3B9OoUSu/OIfTpHEpv45p3rDlEirRoNVpVEbZmOV92xlkdwG3AIPT8BgJf0chxqoUQbZufn6JTWCCdwgI5oeuft2dm7mfKlImAXrD3F5YZPcOLycs/0mN816ESVu44SLpj11Eta5O/omdUSHVR7h8TzoCYME7oGk4Pcwh+UqBFC2pVRRjAmuXMBDJ9nIYQog3w81PEROiDmdQ1nGpFpZtdrpLqjmg1O6R9t2YXruIjt3OFmPzpHxPGgJhwTuiq90CPi43AEh0mrWfhFa2uCNfFGWedbs1yyq07QogmCfD30wcv6RzKycds0zSNA4VlbN5TwB97C42vBSzfdpBvVh8Zrj7E5E9cbATW2EiGxEYypEckcd0jCA1sM39CRSvVln6C5P5ZIYRHKaX0MbvDgxjXP/qobUVlFWzZW4hzVz7rd+WzPjef71bn8uFv2433Qr8uYZzU08zw3lGM6NMJa2wkgQHSg1s0Xqsqws44q9w/K4RoFUIDAxja08zQnkdOc2uaRs6hYtbn5uPcdZh1uS5+3bKfr1bprebAAD+G9oikiyolv1Muo/t2okcdw5cKAa2sCCP3zwohWjGlFL06hdKrUyhnnti9ev0uVzErtx9i1Y5DrNx+kMztFfzw0UoA+nQOZVy/zozvH824/p3p1SnUV+mLVqi1FeHvgHBrlnPVsRuccdbMFs9GCCEaIdYcQqwthHNtsYA+4En3wSP5fesBftu6nx+decxavhOAnlEhjO8fzYQB0Uwe1IWuEcG+TF34WKsqwtYsZ533z1qznHL/rBCiTQjwU9Wnsm88pR9ut8bGPYdZ8sd+ftt6gHkb9vD5Cr0oD4mN5NTBMZw6KIaRfTrJNeUOplUVYSGEaI/8/BRx3SOJ6x7JDSfrRTlr92Hmb9zL/I17eH3BFv6b+Qdhgf5MPKELZ1i7cZq1K9Hh3hooULQWUoSFEKKF+fkphvTQb3W6bcoADpeU8+sf+5m/cS+ZG/by4/o8/BSMtnTmrBO7c+aQbvTuLNeS2yMpwkII4WMRwSbOPLE7Z57YHU3TWJebzw/rdvPD+jz+/t16/v7dek7sEck5Q7tzwbCe9ImWgtxeSBEWQohWRKkj15PvO3Mw2fsK+WH9buauy+OfP2zknz9sZESfKC4c1oOEk3oQEyGnrNsyKcJCCNGKWbqEccvkAdwyeQA5h4r5dnUuX6/Kxf7tep76bj0nn9CFC4f35FxbdxnBqw2S75gQQrQRPaNCmHHqAGacOoCNeYf5elUOX6/K5YFZq7F/s44LhvfgqjF9GNozEqVkrOu2QIqwEEK0QYO6RfDgWXE8cOZglmYf5OOl2/lixU4+/G07Q2IjuWpsby4Y3hNziMnXqYp6yA1pQgjRhimlGNuvMy9cPpzf/no6f7/wRAAe/3od4575iQdnrWZ9br6PsxR1kZawEEK0E+YQE9dNsHDdBAtrc1x8+Pt2vlyRw6zlOxnXrzPTT7ZwxpDuDe9ItBgpwkII0Q4N7WnmmYttPHxWHJ8s207a4m3MeH8FPaNCOKVbJaPGlxMRLKeqfU1ORwshRDtmDjVxy+QBzH9wCqnXjqRnpxA+2VDGxJQM/jl3A/sLSn2dYocmLWEhhOgAAvz9OHtoLGcPjeXtr3/mt/woZmZu5o2FW7hyTB9umdxfpl30ASnCQgjRwfQz+zP9wlFs3nOY/2Zu4f0l2/jgt21cMqIXd552gky32ILkdLQQQnRQJ3SN4F+XDyPzwSlcPbYPX67KYeo/M3ni67XsyS/xdXodghRhIYTo4Hp1CuXJC4cy/8EpTBvdmw9/286k5+bxzGwnBwrLfJ1euyZFWAghBACx5hCeudjGz/efSoItltd/2cKkZzN46edNFJdV+jq9dkmKsBBCiKP0jQ7jhSuG88M9k5k0MIYXftxI/L8y+XLlTtxuzdfptStShIUQQtRqYLcIUq8bxae3TqBLeBD3frKai19dxNLsA75Ord2QIiyEEKJeY/t15uukk/nXtGHszi9hWuqvJH2wgtxDxb5Orc2TIiyEEKJBfn6KS0f1Yt4DU7jn9IH8nJXH6S/M5/UFWyivdPs6vTZLirAQQohGCw0M4J7TB/HjvacyoX80T892cv7LC1m+TU5RN4cUYSGEEE3Wu3MobySO5rXrRuEqLufS//5K8udrOCi3NDWJFGEhhBDNopTirBO789N9p3LL5P7MWr6TM16cz5y1u3ydWpshRVgIIcRxCQsK4K/nWvn2jlPoFhnMjPdXcOdHK2Wgj0aQIiyEEMIjhvSI5Kukk7nvjEHMWbuLM6VV3CApwkIIITzG5O/HXacN5JsareI7Plwh14rrIEVYCCGEx1lj9Vbx/WcMYu663Zz9nwUs3rzP12m1OlKEhRBCeIXJ3487TxvIl7efTFhQANe8+Rsp32dRViH3FVeRIiyEEMKrhvY0892dp3DlmD6kzv+Dy1IXs3Vfoa/TahWkCAshhPC60MAA/nGJjdRrR7H9QBEJL/3CrGU70LSOPSGEFGEhhBAt5uyh3fn+7kkM6xXFg5+t4cHP1nToaRKlCAshhGhRseYQ3r95HHedNpDPlu/kkv8uJruDnp6WIiyEEKLF+fsp7jtjEG9PH8MuVzHnv7yQuet2+zqtFidFWAghhM9MHdyVb+84hX4xYdz63nL+8b2TSnfHuU4c4OsEWhtbmq0zgCPR0XJTgtjNnfWvLq/HtCSnRwHXAxZqfP+zUxLu8nZsIYSoTe/OocyaMYGnvl3Pa/O3sKCzHyPHldEpLNDXqXmdFGHAlmbrAzwHnAYcApQtzRYJZADJjkRHdh3vy2x2ULv5TzGxm6tjYnfVGhO7ufkxdbOBJYADaPBmPUty+lHxgo4zuBBC1CYowJ+nL7Yxok8nkj9bzYUzF/Fm4mgGdovwdWpeJUVY9wnwb+AaR6KjEsCWZvMHpgEfA+O9GRO7S+8aaDd7OyZAcHZKwn3NfbPb7SYzM9OD6XheQUFBq85R8js+rT0/aP05tub8ugB32zRezyrm/JcWMGNYEMO7tt9SpVriHi2l1DJN00Z7PVAzY9rSbJsciY6BTd12PDGxmzdhd9W+3/q2HU9MwJKcfi9QAHwHlFatz05JaNSp8MGDB2sbNmxobDifyMzMZMqUKb5Oo06S3/Fp7flB68+xLeQ3aPg4bnlvGety83n47DhundwfpZSvUwP0KRw1TfNIMu3334umWW5Ls70KpAE7jHW9gURgpbdiYje3dEyAMuB54FGg6j8wDejvxZhCCNEkPaJCmHXrRB74bDUp32excfdhnrnERrDJ39epeZQUYd31wE3Ak0BPY10O8A3wZjuKCXA/cEJ2SoKMpC6EaNVCAv155aoRxHWL4F8/bmTHwSL+d93odtVhS4ow4Eh0lAH/NR4tw+5q+Zi6zUBRC8cUQohmUUpx52kDsXQJ4/5PV3PpfxfzzvSx9IkO9XVqHiFFGLCl2QLQW6UXcXSr9GvgTUeio9zjQe3memNid3k+pq4QWGVJTp/H0deE5RYlIUSrdf6wHnQ3B/OXd5dx8auLeCNxNCP6dPJ1WsdNirDuPfTbhJ4EdhrreqFfn30fuKKdxAT4yngIIUSbMsbSmS9um8gNby/lqteX8O8rRnD20O6+Tuu4SBHWjXIkOgYds24nsMSWZtvorZjYXbXGxG72VkyyUxLSvLVvIYTwtv4x4Xx5+0RufncZt32wnMcShnDTKf18nVazSRHWHbCl2aYBnzsSHW4AW5rND/2e3YPeiondPA34HLtLHzTDbvZ2TCGEaPOiw4P46C/juefjVfz9u/XkHCzmsQQrfn6t4xamppAirLsSeBaYaUuzHTLWRQHzjG1ejYnd3FIxAbAkp3eGxt8bLIQQrU2wyZ+Z14zk/9LX89airRwoLOX5acMw+betKRGkCOty0YdzfANYAZwNnAys48j12jYd05Kc/qdhMi3J6dXDZGanJGR7OqYQQniTv5/iifOG0CU8iOfnbuBQcTmvXjOS0MC2U9raTqbe9Tb6sQgBXEAY8CV6wRqL3lmqrcesHiYzOyWhEsCSnN4Sw2QKIYTXKKVImnoCncMCefRLB9e+8Rtv3TCGqNC2cS9xk9vtM2dkdPVGIgDOOOuJzjjrBTWev+iMs75lPEZ6Ky5gcyQ6rgAuAc4EpjkSHe8B04ER3oqJ3XVUTOwub8bskp2S8ElVAQbITkmozE5J+BiI9kI8IYRoMVeN7cOr14xkbU4+l7/2K7tdJb5OqVHqbQnPnJHR+ZhVCvh95oyMEYBKSo2v9ZrizBkZmc3MJwX4R43nZwGPA6HAE+j31NbKGWdtbkwAP1uaLRC9NRoKmIED6JMGmY5jv/XGxG5uyZjLLcnpvhgmUwghWsTZQ2N5Z7qJv7y7jEv/u5j3bhpL/5hwX6dVr4ZOR+8Dth2zrif6NUxvjDcca81yLq7xPN+a5fwcwBlnvdXDsWp6E8gC/NHHVJ5lS7NtQT9F+3FLxcRu9mZMXw2TKYQQLWbiCV34+JYJ3PD270xL/ZV3bxrLiT3Mvk6rTg0V4QeBM4AHk1LjHQAzZ2RsTUqNr/emrKTU+Ck1n9/xGssamc9RE0das5w1r1PWexrcmuU8KiZKNTYmjkTHi7Y02yfGcq4tzfYucDrwuiPR8Xtj99MkdteL2M2fGMu52M3VMbG7PB4zOyXBV8NkCiFEi7L1MjNrxgSufeM3rvrfEt69aRzDe0f5Oq1a1VuEk1Lj/zVzRsYnwIszZ2TsAP7GkZl3vCHXGWcdZ81y/lZzpTPOOh69N7HXOBIduTWWDwGfeTMeoBffI8tejWlJTq93mMzslARvDZMphBAtrn9MOJ/cOoGr31jCtW/8xtvTxzDGcuwVVt9rsHd0Umr8TmDazBkZFwA/ol+/9JaHgU+ccdZ30E95A4xCv27prWEcOwpfDZMphBA+0btzKLNuncjVbyzh+jd/543E0Zx8Qhdfp3WUBovwzBkZcegtpwz0IjzAWH92Umr8HE8mY81y/u6Ms44D7gBuMFavA8Zbs5x5nozVAY3KTkmodZhMS3K614bJFEIIX+puDuaTWyZw3Zu/Mf2dpbx27SimxnntJp8ma6h39F1AEuBE77xzd1Jq/NfG5mcAjxZhAGuWcw96T2jhWQcsyenTgM+zUxLcAJbkdBkmUwjR7sVE6MNcXvfWb9zy3jJevmpk8yd+WO3ZfrMN3Sf8F2BUUmr8RcAU4PGZMzLuNra1vUE6O7YrgcuAPEty+kZLcvomIA/9PmWvDpMphBC+1ikskA9uHo+tp5mkD1fwzeomdjNyV8LcR+FLz96o09DpaL+k1PgCgKTU+OyZMzKmAJ/NnJHRFynCbYoxLOUVAJbk9Ghj3X5f5iSEEC3JHGLi3ZvGcdM7S7nn45Uo9HmKG1R8CD6/CTb/BGP+AvzLYzk11BLOmzkjY3jVE6Mgnwd0AWwey8LgjLNGOuOs/3DGWd9zxlmvPmbbq56O15FYktMDLcnp11uS008ziu9ZluT0VyzJ6UmW5HRvDUgihBCtSnhQAG9PH8NoS2fu+WQV361poEV8cBu8eQZsyYTz/g0J//RoPg0V4euB3TVXJKXGVySlxl8PTPZoJrq30VvYnwNXOuOsnzvjrEHGNhnb+Pi8DSQA91iS099Dvxb8GzAGfRIJIYToEEIDA3j7hjGM7BPF3R+vYrZjV+0vzF0Fb5wOBXlw/dcwerrHc2noPuE6Z/NJSo1f5PFsYIA1y3mpsfyVM876KJBRczxp0Wy27JSEk4z7hXOAHtkpCZWW5PT3gdU+zk0IIVpUWFAAb08fyw1v/c6dH+mnps+xxR55waaf4NPrIbQzJH4LXeO8kkdrm3gxyBlnrc7JmuV8GngdWIBMMnC8/CzJ6YHoo5JVjVUN3h0fWwghWq3woADeuXEsw3tHcedHK5mz1jjxu/ID+PBy6NwfbvrRawUYWl8R/haIr7nCmuV8B7gfKPNFQu1I1VjVqzDGqrYkp78OLMV742MLIUSrFh4UwDvTx3BSLzN3fLiCdd++BF/fDv0mwfTZEBnb8E6OQ6sqwtYs50PWLOdPtayfY81yDvRFTu1FdkrCi8ApwITslISXgEuBucBN2SkJT/o0OSGE8KGIYBNpN47lvuhfOXH54+yPPRWu+gSCI70eu8ERs1oLZ5x1ujXL+bav82jLslMScmssH6IlxscWQog2IGLdB9x++CWWmUYxfcdN/G97IRMGBHs9bqtqCTdAWmtCCCE8b/k78O3dcMIZ9L/jK7p3juLmtKWs3O79wQRbVUvYGWddU8cmBXRryVyEEEJ0ADUKMFe8T2dTMB/cPI5pr/1K4lu/8/EtExjSw3unpVtbS7gb+r3J59fykNGdhBBCeM7ytKMKMCb99HPXSL0QhwcFcN2bv7F5T4HXUmhtRfg7INya5dx2zCMbyPRtakIIIdqN5Wnw7V1/KsBVenUK5f2bx6GU4to3fmPHgSKvpNGqirA1y3mTNcu5sI5tV9e2XgghhGiS6gJ8eq0FuEr/mHDev3ksxeWVXP3GEna7SjyeSqsqwkIIIYRXHVWAP6izAFeJ6x7JuzeO5WBhOde8sYT9BaUeTUeKsBBCiI5hxbtNKsBVhvWO4s3E0eQcKibx7d89mpIUYSGEEO3finfhmzubXICrjOsfzX+vGUXWrsMeTUuKsBBCiPbtOAtwlalxXfnX5cM8mpoUYSGEEO2XhwpwlQuH9/RQYjopwkIIIdqn5e94tAB7gxRhIYQQ7c/SN/WBOAae2WoLMEgRFkII0d78/jqk3wcDz6r3PuDWQIqwEEKI9uO3/8HsB2DQOXDFexAQ5OuM6iVFWAghRPuw5L/w/YMwOAEuf7fVF2CQIiyEEKI9+HUmzEmGuPNg2jsQEOjrjBpFirAQQoi2bdFLMPevYL2gTRVgkCIshBCiLVv4b/jxcRhyEVz2FvibfJ1RkwT4OgEhhBCiWX75F/z8FAy9FC7+H/i3vZLW9jIWQgjRsWkazH8WMv8BtmlwUWqLFeDKggKP7k+KsBBCiLbD7YYfHoUlr8Kwq+HCV8DP37shy8ooXLAA17ffUTBvnkf3LUVYCCFE2+CuhG/uglXvw7gZcNY/wM97XZtK//iDQ5/OwvXVV1S6XPhHRxN1+eXgWOOxGFKEhRBCtH4VZfDFzbD+azj1YZjyCCjl8TBaeTn5c+Zy8JOPKV62HEwmIk4/jahLLiFswgRUQAA8/pjH4kkRFkII0bqVFcGn18Hmn+DMp2HiHR4PUXn4MIc+/ZQD771Pxe7dmPr2oeuDD2C+6CICoqM9Hq+KFOEOxpKc3g+4E7BQ4/ufnZJwga9yEkKIOpW44MMrYPsSOP8lGJXo0d1X7NvH/jff4tAnn+AuKiJ03Di62/9G+OTJKC+e6q4iRbgGW5qtG1A1WWSOI9GR5/WgdvNRMbG7vB3zK+BN4FvA7eVYQgjRfIX74L2LYc96/R7goZd4bNcVBw6w/803OfjBh2hlZUSeey7RN04neMgQj8VoDCnCgC3NNhxIBcxAjrG6ly3Ndgi43ZHoWFHH+zKbHdRurjUmdvMh4HbsrlpjYjc3P6auJDsl4aXGvtiSnH5UvNY/EqsQol1w5cB7F8Gh7XDlRzDoTI/stuLgQQ689TYHPvgAraSEyPMSiLn9dgItFo/sv6mkCOveAW51JDp+q7nSlmYbD7wNDPNWTOyuo2JiN3szJsB/LMnpfwN+AEqrVmanJNRe9I/hdrvJzMz0UmqeUVBQ0KpzlPyOT2vPD1p/jq09P/e+zZS8+hcCKg7jsD2BKzcQcjOPb6cVFYRmzidsdjqquITSUaMoSDiXvNhYNmVnQ3a2BzJvOqVpmveDKLVM07TRXg/UzJi2NNsmR6JjYB3bNjsSHSd4OiZ28ybsrlpjYjdvxu7yfEzAkpz+D+A64A+OnI7WslMS4hvz/sGDB2sbNmxobDifyMzMZMqUKb5Oo06S3/Fp7flB68+xVeeXt47SNxMI8ldw7efQc+Rx7U7TNArmZbLn2Wcp27aNsJNPputDDxE8eFCz96mUQtM0j3TNlpaw7ntbmi0deBfYYazrDVwPzPFWTOzmlo4JMA3on52SUObFGEII0XQ7l8P7lwB+MP176Bp3XLsr3bSJ3c88Q9GvSwjs14/er6USNnkyygu3NjWXFGHAkei4y5ZmOwe4kJqdpGCmI9Ex2ytB7a67sJtrjYnd5Z2YurVAFLDHizGEEKJpti6Aj66CsC6sHPRXxh9HAXYXF7Pv1f+y/+238Q8Lo9ujj9LpyitQptY3uYMUYYMj0fE98H2LBrW7Wj6mXoCzLMnpSzn6mrDcoiSE8I0N38OnidC5P1z3JSUrmn/Jq2D+fHY/9XfKc3IwX3IJXR98gIBOnTyYrGdJEQZsaTYz8Ah6q7QboKG3FL8GUhyJjkMeD2o31xsTu8vzMXV/89J+hRCi6dbMgi9vhdiT4NovILQz0PQiXLF3L7v/72kOz51L4IAB9H3vXULHjPF8vh4mRVj3KZABTHUkOnYD2NJs3YEbjG2e6RtfR0zsrt0A2M3ejkl2SsJ8b+xXCCGabOmbkH4/9D0ZrvoIgiObvAtN08j/7jt2/9/TaMXFxNxzN9E33ogKDPRCwp4nRVhncSQ6nq25wijGKbY023RvxcTuOiqmUYxTsJu9FVMIIVqHhS/CT3YYeBZcngamkCbvonzPHnbbn6QgI4OQ4cOJfeYZgvr383yuXiRFWLfNlmZ7CEirGiXLGD3rBo70XPZ4TOzmh4C06lGy9NGzvBkTS3L6USN0ZackeH9UMCGEqKJp8PNTsPAFGHopXPwa+Detw9RRrd+SEro+9BCdE69H+Xt3SkNvkCKsuwJIBuYbxVcD8oBvgMu9HdMovl6NaUlOH04tI3RZktMPAbc3drAOIYRoNrcbvn8Qlr4Bo26AhBeaPBdwxYED7Hr8CQp+/rnNtn5rkiKsGwQ840h0PGxLs4WiF8eqO8QrvRkTu+th7OaWiPkOcGt2SsJRI3RZktO9PUKXEEJAZTl8nQRrPoGJd8EZTzV5KsKChYvIfSQZ9yFXm2791uT9KSLahreAQmP530AEkAIUoReo9hAz7NgCDJCdkrAECPNCPCGE0JWX6LcgrfkE4h9vcgF2l5WR948Udtx8M/5mM5bPZhF94/Q2X4BBWsJV/ByJjgpjebQj0VHVIl1oS7Ot8lZM7K7qmNhd1TGxm70R83tLcrovRugSQnRkpYfh46v1wTjOeR7G3dK0t2/eTM4DD1KalUWnq6+m60MP4hcc7KVkW560hHVra/SCXm1Ls40GsKXZBgHl3opZoxf0auxmffxnu9krMbNTEu4CXgGmot+f/IixPDM7JcHzM2QLIUTRAXj3IshepHfAakIB1jSNAx9+yNZLL6MiL49e/32V7k883q4KMEhLuMrNwH9sabbHgH3Ar7Y02w70FuPN3oyJ3VwdE7vZqzGzUxJ8MUKXEKIjOrxbnwt4/2a4/F2wntfot6qiInLuuovDP/5E2Cmn0OMfzxAQE+PFZH1HijDgSHS4gBtsabZIoB/6cdlZdbuSV9hdLuAG7OajYlbfruRhluT0ekfoyk5JOOSNuEKIDujgNnj3QijYA9fMgv5TGv3W4rXr6PzMMxw+5KLrgw/SefoNKL/2e9JWinANjkRHPrC6RYPaXS0Vs3qEruyUhN0AluR0r4/QJYToYPZu0E9BlxfB9V9D78YNHalpGgc//JA9Kc+iwsP1YSdHjPBurq2AFOGOw5KdknDUCF1GMU6xJKfLCF1CiOOXuxLeu0QffGP6bOh2YqPeVllQwK7HH+fw93MImzyJrRdcwNAOUIBBinBHss2SnP4QkFY1SpYxetYNeHGELiFEB7FtMXxwOYR0guu/gugBjXpbSVYWOXffQ9nOncTcdx/RN9/ElgULvJtrKyJFuOOoHqHLkpzeFVDAbrw7KpgQoiPIXqgX4Mge+iloc88G36JpGodmzSLv/57GPyqKvmnvEDp6dAsk27pIEe4gslMSDgIPGw8hhGg0t+Zm1Z5VLMtbRm5BLmWVZUQERtAtrBuDS8sY/MNTdDH3gsRvIaJbw/srKWG3/UlcX31F2Mkn0+O5ZwmIjm6BT9L6SBHuICzJ6eMAZ3ZKQr4lOT2EI8NkrgeeyU5JcPk0QSFEq+Tc7+SxRY+x8eBGALqEdCHQL5DDZYc5XH5Yf1GPaCzhXTjZ+TYTe0xkTPcxhATUPitS2c4cdt51J6XrnXRJSqLL7be1i5GvmkuKcMfxFkfGh/4P+vCYzwKnoQ+TeYmP8hJCtFLLdi/jtp9uIzIokqdPeZrJPScTFRylb/xjHq5PrmJj596sG5vIkv1r+WzjZ3zg/IBg/2DG9xhPfO94JveaTHSI3sotXLyYnPvuR6uspNd/XyVi6lTffbhWQopwx+GXnZJQPUxmdkpC9TCZluT0VT7KSQjRilS4K9hwYAP5ZfmUVpby2KLH6BHegzfPepMuIV2OvHDzz/Dx1Zg7D2DMdd8wJqwLNwCllaUsz1vO/B3zmbdjHpk7MlEohscM4+oVofT58BeC+ven9yuvEGix+OZDtjJShDuOtZbk9OnZKQlvA6styemjs1MSllmS0705NKcQohXTNI2NBzeyZNcSft/9O8vzllNYXli9PdwUzsvxLx9TgH+Cj66GLgPh+m8g7Mi13CD/ICb2mMjEHhNJHpvMhoMbWLBhLp1f/JC+a/JZbFW8c0Eegzf8HyMOjWBE1xEMjxlOqCm0JT92q9Kqi7AzztoTqLpYkGvNclbU93pRr5uB/1iS06uHybQkp3t7aE4hRCuzv3g/SwuW8sMvP7A4dzH7S/YDYIm0kNAvgTGxY+ga0hU/5UeviF5HF+BNP8LH10DMIL0Ah3auM45Sin6uIExP/0jZlgJC77mNXmcNImHvKlbkreB/a/6HW3Pjr/wZ3HkwI7uOZETXEYzsNrLOfbZHXinCM2dkZDbnfc446yOAyZrlfMpY9StwCAgE0oB/1PPeZsXsKIyOVzdYktOPGiaz6p5hIUT7VNXa/Wn7T8zfMR/nAScAUQVRTIidwMSeExkfO57uYd3r39HGufDJtRATp9+GVE8BBjg8bx65Dz6ECgigz5tvEDZhAn2Bs/qdDUBBWQFr9q5hxZ4VrNizgs82fsb7zvcBiAmI4aeFPzEudhzn9DuHAL9W3V48Lk3+ZDNnZEQnpcbv90YywDRgUo3n+61ZzhHOOKs/MJ96irBonOyUhJYfmlMI0aI0TWPd/nX8uO1Hftr2E9sPb8dP+TE8Zjh3jriT4F3BXHvmtfipRo7JnDUbZiVC1yFw3Zf1FmBN09j/2mvs/c9LBFut9Hr5JUw9/3zfcHhgOBN7TmRiz4kAlFeW4zzgZEXeCn5Y/wPzd87n6z++5r317/H4+MexxdiadSxau3qL8MwZGSnAP5NS4/fNnJExGn2MYffMGRkm4Pqk1Pj5tb0vKTV+Ss3nd7zGssYmZM1yFtZ4+h9jXaUzzlp7f/cj7zsqJko1OqYQQrR1mqbh2Ofgh+wf+HHbj+QW5hKgAhgbO5Ybht5AfO/46l7KmQcyG1+A130Jn98M3U+C677QR8Sqg7uwkNy/PsrhuXOJPO88Yv/+FH4h9f7prmbyN3FSzEmcFHMSln0WTj31VOZum8tzvz/HNbOv4fLBl3PXyLuIDIxsXN5tREMt4YSk1PhkY/l54Iqk1PilM2dkDAI+BDw9vEm4M85qsmY5ywGsWc53AJxx1iCgfR15IYQ4TpXuSlbuWcnP238mY3uGXnj9ApjYYyK3D7+dKb2nYA4yNz/A6o/hq9ug9zi4+lMIrvvPcNnOney8PYnSzZv12Y9unI5SqtmhlVKcbTmbU3qcwssrX+bjDR/z8/afeWjMQ5xtOfu49t2aNFSEA2bOyAhISo2vAEKSUuOXAiSlxm+cOSMjyAv5fAa85oyz3mHNchYBOOOsYeiT0X/mhXhCCNGmlFaWsiR3CT9v/5nMHZkcLD1IoF8gE3pMIGlEElN6T/FMa3HZ2/DdvdBvElz1MQSG1fnSwl9/Jeeee9E0jd6vvUb4pFOOP74hPDCcR8Y9wgUDLuCpJU/x0IKH+HLTlzw6/lH6Rvb1WBxfaagIvwrMNk5Lz5k5I+M/wBdAPLDKC/k8DjwNbHfGWbcZ6/oAbxrbhBCiw8kvy2fBzgVkbM9gYc5CiiuKCTeFM7nXZOL7xHNKz1MIM9VdJJtsSSrMeRgGngmXvwum2k8pa5rGwXffJe+55wnsZ6H3zJkE9vVOYTyxy4l8eO6HfLLhE15e+TIXf30x04dO52bbzXWOztUW1FuEk1LjX545I8MB3AYMMl4/EPgK+Lunk7FmOSuBZGec9UngBGP1ZmuWs9jTsYQQojU7WHKwumPV0t1LqdAq6BLShfP6n8dpfU5jbPexmPxNng+88EX4yQ5x58Flb0FA7Sc93aWl7P6bHddXXxF++mn0SHkW/3AP/iNQC38/f662Xs0Zfc/gX8v/xf/W/I/v/viOh8c+zNTeU9vkKeoGe0cnpcZnApnHrp85I2M6+nCHHmcUXYc39i2EEK1VUXkR83bMY/bW2SzOWUyFVkGfiD5cN+Q64vvEc1LMSY3vUNVUmgaZKTA/BYZeBhen6vMC16I8L4+dd95FyZo1dLnjDn38Zz8v5VWLmNAYUialcOnAS3nmt2e4e97dTOo5iUfGPkLvyN4tlocnHM/NV0/ipSIshBAdRbm7nMU5i0nfmk7mjkyKK4rpFtqN64Zcx7n9z2Vwp8Heb+FpGvz0N1j0Hxh+LVzwEvjVPqlC0YqV7Lz7LrTCInq98jIRp5/u3dzqMab7GD49/1M+cn7EzFUzuejri7jRdiM3Db2J4IBgn+XVFA3dorSmjk0KaHi+qiZyxlkDgSvRR8f6yRlnvRqYCDiB/1X1mhZCiLbMrblZuWcls7fM5odtP3Co9BDmIDPn9T+Pc/udy8huI73X4v1TMm74/kFY+gaMuRnOeR5qadVqmsbBDz8kL+VZTD1i6f3WWwQNHNgyOdbD5Gfi+hOv5+x+Z/OvZf8idXUq3/7xLcljk5nSe4qv02tQQy3hbsBZwMFj1itgsRfyedvIKdQZZ00EwtE7gp0GjAUSvRBTCCG8TtM0NhzcwOyts/l+6/fsLtxNsH8wU/tMJaFfAhN7TPTONd76VJbrtyA5ZsHEu+CMp6CWVre7qIhdf7OT/+23hJ96Kj2eexZ/83Hc+uQFXUO78uzkZ7ls0GU8veRp7sy4k1N7ncrDYx+md0TrPUXdUBH+DghPSo1fdeyG5g5N2QCbNct5kjPOGgDkAD2MgTreR0Z5EkK0QX8c+oNv//iWH7f9yPbD2/FX/kzsMZG7R95NfO94301eUFYEs26ATXPhdDuccm+tLyvdupWcu+6mdPNmYu65m+hbbmnR679NNab7GGZdMIsP1n/Af1f/l4u+uoibbTczfej0VnmKuqHe0TfVs+1qz6eDn3FKOgwIBczAASAIaOF/EYUQonlK3aV8uelLvtj0Bav2rsJf+TO2+1gST0zk9L6n0zm4/nGXvc2/ohDevxS2/wrn/RtGT6/1dfk//MCuR/6KMpno/cbrhJ98cssm2kwmPxM3DL2Bc/qdw7+W/YtXV7/KN398wyPjHmFyr8m+Tu8orW1U7DeBLPSZkx4FZjnjrFuA8cDHvkxMCCHqo2ka6/ev5/NNn/Ptzm8p2VFCP3M/Hhj9AOf1P696yEifK9jD8FWPQtFO/RakoZf86SVaRQV7XnyRA2++RbDNRq///BtTjx4+SPb4dAvrxnOnPselgy7l6d+eJulnfTCTh8c8TK+IXr5OD2hlRdia5XzRGWf9xFjOdcZZ3wVOB163Zjl/9212QgjxZ65SF7O3zubzjZ+z4eAGgv2DOSn0JJImJTGi64jWde/qoe3w7kWEFuXoo2AN/HPP5oq9e8m5736Kli4l6qor6fbII/gFBvogWc8ZFzuOz8//nPed7/Pf1f/lgq8u4BrrNdxsu/n4hvX0gFZVhEEvvjWWDyHDVQohWpniimIW7FzAnK1z+CXnF0orS7F2tvLYuMc4t/+5LF+8vPXNi7t3A7x3MZQVsHrYU4yspQAXrVhBzt33UHn4MD2eTcF84YU+SNQ7TP4mpg+dzjn9zuGVla+Qti6NLzZ9wa0n3cqVcVcS6O+bfzRaXREWQojWqKyyjIU5C5mzdQ6ZO/X7eaODo7lk4CVcdMJFDIke4usU65azQr8G7BcAN8wmP2vfUZs1TePge++R99zzmHr0wPL6/wiOi/NRst7VPaw7/3fK/3HdkOt4YfkLPL/seT7M+pCk4Uk+mbtYirAQQtSh3F3OktwlzMmeQ8b2DArKC4gKiiKhfwLnWM5hVLdR+NcxqEWrsXUBfHSVPgfwdV9B9ADIyqzeXHn4MLsee5zDc+cSHh9Pj5R/4B/Z/ietG9x5MK+d8RqLchbxwvIX+OvCv/Lamtf4i+0vJPRPaLFiLEVYCCFqqHRXsjRvKXO2zuGn7T/hKnURYYrgtD6ncU6/cxgbOxaTXxu5WSNrtn4bUud+cN2XEHl056ridevIuedeynNzibn/PqJvuqlV337kDSf3PJkJPSaQsT2D1NWpPLboMVJXp3LLSbdw3oDzvP69liIshOjwNE1j9d7VfL/1e+Zmz2V/yX5CAkKY2nsqZ1vO5uSeJ/vsmmGzLU+D7+6B2OFw7ed6S7iKpnHggw/Yk/Is/tHR9H3vXUJHtrJr2C3IT/lxet/TOa3PaWTuyCR1TSpPLH6C1NWp3HzSzVw44EKvff+lCAshOqxNBzdVj2CVU5BDoF8gp/Y+lbMtZzOp16S2OUWepsH8ZyHzH3DC6TAtDYLCqzdXHj6M+fU3yFuxgrBTJ9MjJYWATp18mHDroZRiap+pTOk9hYU5C0ldncpTvz7F/9b8j5uG3sTFAy8myL/2WaWaS4qwEKJD2VWwi/St6aRvSWfzoc34K3/Gx47ntmG3cVqf0wgPDG94J61VZQWk3wcr0mDY1fpEDDWGwqw6/RyUk0PXB+6n8403drjTz42hlGJSr0mc0vMUft31K6mrU3n6t6d5fc3r3Gi70aOxpAgLIdq9ssoy5u2Yx5ebvmRx7mI0NIbHDOev4/7KmX3PbD0DaRyPsiL4/CbYMBsm3Q/xj1ePA101+ULV6eeD993HkJvrHBBRGJRSTOwxkQmxE1i6eympa1JJ+T3FozGkCAsh2q3NBzfzxeYv+O6P7zhYepBuod245aRbuOiEi1rNiEkeUXQAPrwCdi6Fc/8JY/9SvakyP59dT/yNw3PmVJ9+zlktQ/E3hVKKsbFjGRs7lmW7lzGGMR7btxRhIUS7crDkIHOz5/Ltlm9Zs3cNAX4BTO09lUsGXsKE2Amt/5aipjqYDe9fpo+GdXkaDDkywEbRipXkPvAA5Xl5cvrZQ0Z3H+3R/UkRFkK0eaWVpczfMZ9vt3zLwp0LqdAqOCHqhNY3brOnbV8CH18N7gr9FiSLPsGCVlnJvtdeY9/MVzHFxmL54H1Chg/3ba6iVlKEhRBtkltzsyJvBd9t+Y4fsn/gcPlhYkJiuMZ6DecPOJ9BnQa1rnGbPW31J/DNHWDuBVfPgi4nAFC+axe5Dz1M0dKlRJ53Ht3/9gT+ERE+TlbURYrwMWxpts4AjkTHgRYJaDfrN+/ZXS0Sz5KcHgVcD1io8f3PTkm4qyXiC3G88srzeGnFS6RvSSe3MJeQgBBO63Ma5/c/n3Gx49rf6eZjud2Q+QwseB4sk+Dyd6vvAc7/8Ud2PfY4lJcTm/IPzBde2L7/EWkHpAgDtjRbH+A54DTgEKBsabZIIANIdiQ6sut4X2azAtrNf4qH3VwdD7ur1njGe5sX84jZwBLAAbgberElOf2oeJ69Q06IxtlfvJ852XP49o9vWbd/HX67/BgfO547RtzBaX1OI9QU6usUW0ZZEXx1G6z/CkZcCwkvQkAg7uJi8lKe5dAnnxA8dCg9//VPAvv29XW2ohGkCOs+Af4NXONIdFQC2NJs/sA09HmMx3srHnZXJQB2szfj1RScnZJwX3Pf7Ha7yczM9GA6nldQUNCqc5T8GqfMXYaj2MHSwqU4i524cdPL1ItzQ89lYqeJmAPMsAN+39H6Zjn1xjEMLD3A0LXPEHF4M1v638COyItg4WICdu7E/OZbBOzaReGZZ5J3wfls27oVtm5t0fw8qbXn50lK0zTvB1FqmaZpnu1S5sGYtjTbJkeiY2BTtzU7pt28Cbur9n3Wt+14Yhosyen3AgXAd0Bp1frslIRGnQ4fPHiwtmHDhsaG84nMzEymTJni6zTqJPnVrWrc5vQt6fy47UcKywvpGtqVhP4JnN//fAZ2Gtjqjx944RjuWgMfXQnFB+HSNyAuQb/39/0P2PP88/iZI+mRkkL4ySf7Jj8Pa+35KaXQNM0j5/mlJaxbbkuzvQqkATuMdb2BRGClN+JhN7dkvJrKgOeBR4Gq/8A0oL+X4wpRK03TWH9gPelb0pmzdQ57i/cSZgrTr/MOOJ8x3ca0/+u89cmaDZ/fDCFRcOMciB1GxYED7PrroxRkZhJ+6qnE/uMZAjp3bnBXovWRIqy7HrgJeBLoaazLAb4B3mwH8Wq6HzghOyVhX4OvFMKLduTvqB4+Mjs/mwC/ACb1nMS5/c9lSq8pBAcE+zpF39I0+PUV+OFx6DEcrvoYIrpT+Ouv5D70MJUuF90efZRO114jna/aMCnCgCPRUQb813h4n93VsvGOthko8kFcIao7WM3eMps1+9YAMLrbaK4/8XrO7Hsm5iCzjzNsJcpL4Lt7YfWH+uAbF6WiKRN7//Uv9r/xJoH9+9P7jdcJHjzY15mK4yRFGLCl2QLQW6YXcXTL9GvgTUeio9yjAe3meuNhd3k23tEKgVWW5PR5HH1NWG5REl5RWF5IxvYM0remsyR3CZVaJYM6DeLeUfdybr9z6R7W3dcpti6H8+CTa/QhKKc8ApMfomzHDnIeeJASh4Ooyy+n2yPJ+IW0wRmexJ9IEda9h36r0JPATmNdL/RrtO8DV7TxeDV9ZTyE8JryynIW5y4mfUs683bMo6SyhB5hPZg+dDrn9juXgZ0a3fewY8ldCR9fo3fAmpaGNuRCDn3yCXnPPocKDKTnS/8h8swzfZ2l8CApwrpRjkTHoGPW7QSW2NJsG70RD7ur1njYzd6IVy07JSHNm/sXHdfhssMsyl1E5o5Mftn5C/ll+UQFRXHhCRdybr9zGd51OH5Kxi2u09rP4askCOsCN86l3K87u265lcJffiHs5JOJfeZpTN26+TpL4WFShHUHbGm2acDnjkSHG8CWZvNDv2/3oDfiYTdPAz7H7tIHzLCbvRlPCK/ILcglc0cmmTsyWZq3lAp3BVFBUUzpPYUz+57JxB4TMdWYz1bUwu2GeU/DL/+E3uPhivfJX7CUXU/eglZaSrcnHqfTVVdJ56t2Soqw7krgWeBVW5rtIKAAMzDP2Oa1eNjNLRHvKJbk9M7Q+HuDhaji1tys37+eeTvmMX/HfDYc1O8Z72fux3VDrmNKrykMixnWsW8paorSw/DFrbAhHUZcR+Upf2P3354lPz2d4GEn0SMlhaB+/XydpfAiKcKAMSzlFQC2NFvVdCv/cSQ6rvVKQH1YSv26r91cHQ+7yzvxAEty+p+GyrQkp1cPlZmdkpDtrdiibSupKOH33b9XF969xXvxU36M6DqCB0Y/wKm9TsVitvg6zbZn/x/wybWwdwOc8xwF5Sey6+LLqDhwgJh77ib65ptRAfInur2T7zBgS7N9U8vq+Kr1jkTHBR4NaDfXGq96vd3l2Xi66qEys1MSKgEsyektNVSmaGP2F+9nwc4FZO7I5Nddv1JcUUxoQCgn9zyZqb2nMqnnJKKCo3ydZtuVNRu+vBX8/HFf9gF7Pl/KwQ//TeAJA7D891VCTjzR1xmKFiJFWNcLWA+8gT56lALGAP9qJ/EAumSnJHxSc4VRjD+2JKf/3YtxRRugaRpbXVuZt2MeX+/+muxPs9HQ6BbajQsGXMDU3lMZ030Mgf6Bvk61bXNXwrxn9Ou/scMpHvIIuff9m7Lt2+l8ww3E3HsPfkEyTUpHIkVYNxq4G30oxwcdiY5VtjRbsSPRMb8l4mF3rcJuLsbu8lY8gOWW5HRfDZUpWqEKdwUr96ys7li1/fB2AHoH9ua24bcxpdcU4jrHSYcgTyncD5/fBFvmodmuYW/2APbfej8B3bvR5513CBs31tcZCh+QIgwYPaJftKXZZhlf8/DmsdF7RL+I3TzL+OrdeDpfDpUpWomCsoLq24gW7FxAflk+Jj8T42LHkXhiIpN7TSZraRZThk3xdartS84K+PR6KNhD6YjHyUlbTOn6eZgvvphuf30E/4gIX2cofESKcA2ORMdOYJotzZYA5Hs9oN21E5iG3ez1eNkpCb4cKlP4UH23EU3tPZUJPSYQZgqrfn0WWT7LtV1a8S6kP4AWGsOB0CT2Pv4efuHh9HrlZSJOP93X2QkfkyJcC0eiIx1Ib7GAdpfX41mS0+sdKjM7JcGbQ2WKFlTprsSxz8GCnQtYsHNB9W1ElkgL11mvY0pvuY2oRZQWwOwHYPVHlEZOZNevYRQ7Pib89NOIffJJAqKjG96HaPekCHccvhwqU3iRpmnkFeWxIm8FC3IWsChnEYdKD+Gv/BkWM4z7R93Pqb1PpZ9Z7jdtKWEF2fD6g2h7NnGg8nz2vuPALySEHs8/T+R5CXKdXVSTItxxjMpOSah1qExLcrpXh8oU3lFQVsAXm77go6yP2Fmg/1/VKagTk3pOYnKvyUzoMUFmJWppmgYr0hi54kFKyzuxa+3JFDuXE37aacTa/0ZATIyvMxStjBThjuOAJTl9GvB5dkqCG8CSnC5DZbZBuwt38/769/l80+cUlBcwsutIrhtyHcNihhHXOU5OM/tKST58dw/ams/J3TmIwuVlqOD99HjuWSLPP19av6JWUoQ7juqhMi3J6VVFtxP6iFleHypTHD/nfidp69OYu3UuGhpnWs4kcUgiJ3aRgR18btdqmHUDZdt3kOscTvEfewifOpXuT9oxde3q6+xEKyZFuIMwhqW8AsCSnB5trNvvy5xEwzRNY1HuIt5Z9w6/7fqN0IBQrrJexXXW64gNj/V1esLtht//h/bD4xzcGs2eFT1RQSW4bkgk7uGHpfUrGiRFuAOqKr6W5PR3s1MSrvd1PuLPyivLmb11Nu+se4fNhzbTNaQr9466l8sGXUZkYKSv0xMA+bvgq9soW72AXEc/ircXEX7qBLo/9RSLnOulAItGkSLcQViS048dr1oBUy3J6VEA2SkJ3hivWjRRflk+szbM4kPnh+wp3sPATgN5+pSnOcdyjkwJ2Jqs+wrtm3s4uE5jz5qeqCB/Yp95BvPFF+nF17ne1xmKNkKKcMdR23jVo/HueNWikbblb+OjrI/4ctOXFFUUMSF2An8/+e9M6DFBWlStSUk+fP8wpQs+ZdeqnhTvKifs1InEPvUUpm7dfJ2daIOkCHccR41XnZ2SsMqSnF6cnZLgzfGqRT3cmpvFuYv5wPkBC3MWEuAXwDmWc0g8MZHBnQf7Oj1xrG2/on32F/b/doh967vjFxZKj+f+Kj2fxXGRItxBGLclvWhJTp9lfG2J8apFLUrcJXzo/JCPsj4iOz+bLiFduH347UwbNI0uIV18nZ44VlkRZPydku9fJ3d5V0r3RRBx1hl0f/wxArrI90scH/kj3MFkpyTsBKZZktNbZnxsUW17/nY+yvqIz3Z+RsmOEk7qchIpk1I4s++Zcr23tcpeiPuLJPYt3M/+rK74d+pEz5f+RuSZZ/o6M9FOSBHuoLJTElp2fOwOqtJdyaLcRXyc9TELcxbi7+fPiNAR3HvqvdhibL5OT9SltAB+slP8/TvkLu9K2cEIzBdeQLdHkvGPivJ1dqIdkSIshBfsK97Hl5u+5LONn5FbmEuXkC7cNuw2pg2extrf1koBbs22ZOL+/A72LnRxYGMMAd260vt/TxE+ebKvMxPtkBRhITyk0l3J0rylfLbxM37e/jMV7grGxY7j/tH3M7XPVEx+csq5VSvJhx8fp3D2h+xaHkN5fjhRV15B1wcewD883NfZiXZKirAQx8GtuVm5ZyVzts7hx20/sr9kP5GBkVwddzWXDbpMZi5qK7JmU/nF/exZVMShP7pg6t2TPi8/Tdi4sb7OTLRzUoSFaKKCsgKW7l7K4tzFZOzIYE/RHoL9g5nUaxJnW85mcq/JBAcE+zpN0Rj5u9BmP0j+nJ/IW92ZytJwOt94AzF33oFfSIivsxMdgBRhIRppb9Fe3lz7JrM2zKLMXUZIQAjjY8dz/6j7mdJ7CqGmUF+nKBrL7Yblb1H2xVPs+jWQot2dCD5pKH2eeorguDhfZyc6ECnCQjRgX/E+3nS8yayNs6hwV3DBgAs4f8D5DIsZRqB/oK/TE02Vtx7t67vZ/+N69q03o4JD6PbE/XS64gqUv0wDKVqWFGEh6pBXmEfa+jRmbZhFubuc8weczy0n3ULviN6+Tk00R3kJLHieoi9nsmupmTJXJBFnn0W3Rx7B1E2mGxS+IUVYiGNsz9/OW2vf4ps/vsGtuUnon8CtJ91Kn8g+vk5NNNeW+VR8eg97Mg/gyu6EKbY7vZ+zE37qqb7OTHRwUoSFMGw4sIE3HW8yd9tcAlQAlwy8hBtOvIFeEb18nZporvxctPRHOPD1j+xbZ0bTIon+y3S63DYDv1C5hi98T4qw6PBW7lnJG443WLBzAaEBoSSemMh11uuICY3xdWqiuSrLYcl/Kfjwn+QtDaYs30z45El0++tfCbRYfJ2dENXqLcIzZ2QEAlcCuUmp8T/NnJFxNTARcAL/S0qNL/dmcs44a0+gqqdErjXLWeHNeKLjqHBX8NO2n3hv/Xus2beGqKAokoYncVXcVZiDzL5OTxyPrQso++h+8n7eS0FOGKZePej13ONETJni68yE+JOGWsJvG68JnTkjIxEIB74ATgPGAomeTMYZZ30EMFmznE8Zq34FDgGBQBrwD0/GEx1Pflk+X2z8gg+zPmRX4S56R/QmeWwyF59wsdxi1Nbl78L93SPs++wnDmyIAJOZmPvvoHNiIn6B0otdtE4NFWFbUmr8STNnZAQAOUCPpNT4ypkzMt4HVtf1ppkzMjKbmc80YFKN5/utWc4RzjirPzCfeoqwM87a3JiiA9iRv4P3ne/z5eYvKa4oZnS30SSPTebUXqfi7ye3pbRpFaVov6aSn/YCe1YEUVEUQeS559D14Ycxdevm6+yEqFdDRdjPOCUdBoQCZuAAEAR4ZSBca5azsMbT/xjrKp1xVhm+RjSJpmn8tvs3PnR+SOaOTPz9/DnHcg7XDrmWIdFDfJ2eOF6aBlnfUfTOo+T9UkjJgVCCBw+g5xNPEjpqlK+zE6JRGirCbwJZ6NdlHwVmzZyRsQUYD3xc15uSUuOn1Hx+x2ssa2Q+4c44q8ma5SwHsGY53wFwxlmDgMj63mjNch4VE6UaG1O0M8XuYj5wfsDHWR+TnZ9NVFAUN9tu5sq4K+kaKveDtgu7VlP24YPs+X4jh3eGENClKz2eTSby/PNRfn6+zk6IRqu3CCelxr84c0bGJ8Zy7swZGe8CpwOvJ6XG/+6FfD4DXnPGWe+wZjmLAJxx1jDgFWObEHXaeHAjH2d9zNc7v6ZsRxm2LjaePuVpzrKcRZB/kK/TE55weDcDV77A7hdWcXBTKH5BkcTcNYPO06fLWM+iTWrwFqWk1PjcGsuH8G4xfBx4GtjujLNuM9b1QW+RP+7FuKKNOlRyiDnZc/h2y7es2buGIP8gRoaO5J4p93BilxN9nZ7wlPJi3Av+w8G3UilYE4S7IoyoSy4k5p77CYiRW8lEy1mavtWj+2tV9wlbs5yVQLIzzvokcIKxerM1y1nsw7REK1NWWcaCnQv49o9vWZCzgAp3BSdEncADox/gwgEXsmrJKinA7UVlBdrKD8l/8x/s/b2C8sIQyuMGMOi5FwgeNMjX2YkOZvmcbH7/th0X4SpG0XX4Og/Remiaxuq9q/n2j2+Zkz2H/LJ8uoR04eq4qzl/wPkM7jQYpZSv0xSeomlo67+h4G07excepvSQiaAB/ej9yN9YVlEuBVi0uFU/bWfJV1sYOKYbvOa5/bbKIixElX3F+/h689d8uflLtuVvI9g/mPg+8Zw/4HzGx44nwE9+hNudLfMpSnuUPT/nUrwvCFNsd3o89giR556jd7rKzPR1hqKDWTNvB4s+28yAkTGcfoMVbvbcvlv9XzBnnPVda5bzel/nIVqOpmkszl3Mpxs+Zf7O+VRqlYzqNoqbbTdzRt8zCDOF+TpF4Q25Kyn58K/sSc+icFcwAVHRdP/bvURdNg1l8sodkUI0aO2CHH75ZBP9hnXhjJtOxM/fs73vW1URdsZZvzlmlQKmOuOsUQDWLOcFLZ6UaDHlleV8n/0976x7h00HNxEdHE3iiYlcfMLFWMwWX6cnvGXfZso+e4y9X/xK/vZQ/ELNdL13Bp2uT5Qez8Kn1i/KZf6HG+hri+asm4fi7+ECDK2sCAO9gPXAG4CGXoRHA//yZVLCuyrdlXy75VteXfUquwp3cULUCTx9ytOcYzkHk7+0gNqtQ9sp++JJ9s36GVd2MCoggugbryX61tvwN8v43cK31i/KZd77WfQZ0pmzbxmKv8k795+3tiI8GrgbfWCQB61ZzlXOOGuxNcs538d5CS/QNI35O+fznxX/YfOhzQyNHsrj4x/nlJ6nSCer9iw/l7IvnmLfJ3NxZQeh/MPofOWldL7tDkxdZTAV4XuOzJ0s+HgjfYZ05pwZNgJM3hvatlUVYWuW0w286IyzzjK+5tHKchSekVOQwzO/PcOCnQuwRFp4YcoLnN7ndCm+7VnBHko/f4p9H80mf1sgKiCUzldeTPTtd8u9vqLVWPnjdhZ/vhnLSV04+y/eawFXaZUFzprl3AlMc8ZZE4D8loprS7N1A3oaT3MciY48rwe1m4+Kid3l1ZiW5PR+wJ2AhRrf/+yUhBa53q5pGh9v+JgXl78IwIOjH+Rq69XSy7k9KzpAyawn2f/Rd+RvM6ECQuh85UVEJ91LQJcuvs5OiGrLZm/lt2+2MmBkV864aYhXrgEfq1X/5bNmOdOBdG/HsaXZhgOp6BNU5Bire9nSbIeA2x2JjhV1vC+z2UHt5lpjYjcfAm7H7qo1JnZz82PqvkIfgexbwN3Qiy3J6UfFO57BHw+VHOKJxU8wb8c8Tul5Ck+Mf4LY8Njj2KNozbSigxS9+zf2z/qewpwAVGAwna+6iOik+wiIjvZ1ekJU0zSN377ewvI52xg8rjvx18d5vBd0XVp1EW5B7wC3OhIdv9VcaUuzjUefU3mYt2Jidx0VE7vZmzEBSrJTEl5q7pvdbjeZzbhPM7csl9Q9qeRX5nNJp0uY4j+FDcs2sIENzU2lTgUFBc3KsaW09/z8ywqInZeG3y+rKN0XgAoJpPScU3CdfgG7w8LAcXzj8LT24wetP0fJ7whN08hbpbF/A3TqD/6WPBb8sqdFYgMoTdO8H0SpZZqmjfZ6oGbGtKXZNjkSHQPr2LbZkeg4obZtxxMTu3kTdletMbGbN2N3eT4mYElOvxoYCPwAlFatz05JqL3lfYzBgwdrGzY0rXAu3b2UuzPuJjggmJfjX/b6kJKZmZlMmTLFqzGOR3vNz30oD9crf+XANwspy/fD1CmQ6Buux5yYhF9wsM/za0mtPUfJT1dZ6Wbeu1ls+G03J03txSmXD2xUvxSlFJqmeaQDi7SEdd/b0mzpwLvADmNdb+B6YI63YmI3t3RMABtwHRDPkdPRmvHc45buXsrtP91Oj/AepJ6eKqef26GK7Rs5+J/HOJixmspiP4Jjw+h5z81EXHEryt97vUqFOB7lpZXM+d9atq/bz7gL+jHqHItPOoZKEQYciY67bGm2c4ALqdlJCmY6Eh2zvRLU7roLu7nWmNhd3ompmwb0z05JKPNiDADW7ltL0s9J9AzvyZtnvUl0iFwHbE+Kly7g4MtPk79sG5pbETawE9Ez7iL03Kukl7to1UoKyvlu5mr2ZOcz5ZrBnDipZ8Nv8hIpwgZHouN74PsWDWp3tXxMWAtEAV696LGrYBd3ZtxJ5+DOvHHWG1KA2wmtooLD33zCgddnUrz1ICrATdTYXnS681GCRnnlZIoQHnX4QAnfvrSK/H0lnH2Ljf4jfHt7nBRhwJZmMwOPoLdKu6Gfnt0DfA2kOBIdhzwe1G6uNyZ2l+dj6qKALEty+lKOvibssVuUSitLuWveXZRUlPDGmW/QJURuQ2nryvP24Hr/dQ5+OosKVymmsEq6nhdH1J3/h3/fk3ydnhCNsj+3gO9eXk1ZSSUX3D2MHgM7+TolKcKGT4EMYKoj0bEbwJZm6w7cYGw705sxsbt2A2A3ezsmwN+8tN9q/17+b7IOZPFy/MsMiBrg7XDCSzS3m8JFiziU9j8OL14GbgjtVk73SycQftPfUdEWX6coRKPtWH+AOf9zEBDkz8X3j6RLr3BfpwRIEa5icSQ6nq25wijGKbY023RvxcTuOiqmUYxTsJu9FZPslASvDgG6OGcx7zvf5+q4q5nSe4o3Qwkv8Tt0iH3//S+HPnqf8j0H8A+qJHpIJVGXXkLg+Q9CuAwtKdqWdb/kMP+jjXSODSMh6SQiOnuut/7xkiKs22ZLsz0EpFWNkmWMnnUDR3ouezwmdvNDQFr1KFn66FnejOlVJRUl/H3J37FEWrhv9H2+Tkc0gbusjIJ5mbi++pKYzPns1TRCu5bS9bQgwi9Pwm/8jRAU4es0hWgSt1vj1y82s+qnHfQ5MZqz/nIigcGtq+y1rmx85wogGZhvFF8NyAO+AS73dkyj+LZETCzJ6UcNk5mdkuCxYTLfcLzBzoKdvHHmGwT5H8/YWqIlaJpG8apVuL7+mvzZ3+POzycgFKIHHyZqTCyBCU/A0EshINDXqQrRZOWllfz41jq2rt6HbUovTpl2QouNgtUUUoQBR6LjoC3N9jbwI7DEkegoqNpmS7OdjTfu27W7DmI3V8fE7io4ss3s8ZiW5PTh1DJMpiU5/RBwe2MH66jLroJdvLX2LRL6JzAudtxx5Sq8q2znTlzffIPr668p37YdZfInoncp5hEuwsaOwhF1Gl0vvg/8Wt8fLCEa4/CBEr5PdbBvx2EmXTGQk6b29nVKdZIiDNjSbHcBSYATeMOWZrvbkej42tj8DF4pwuajYmI3343d5c2Y7wC3ZqckHDVMpiU53SPDZL625jUA7hl5z/HsRnhJeW4u+XPmkj9nDiVr1gAQ2j+KLuMPE9GzEH/buXDyPdB7DAcyM6UAizYrd9NB5vxvLRXlbs69/SQsttZ9d4YUYd1fgFGOREeBLc1mAT6zpdksjkTHfwBvjTrwF2AUdlcBdrMF+Ay72YLd5a2YYccWYIDslIQlluT0sOPZ8fb87Xy1+SuuGHwF3cO6H8+uhAeV797N4blzyf9+DsWrVgEQPKAXXadGExm+HlPUIRh2FYy/DbrUPoKqEG2Fpmk4MneyaNZmImNCuPg2G526H9efthYhRVjnV3UK2pHoyLal2aagF+K+eK8I+1Wfgra7srGbp6AXYm/F/N6SnO6VYTJfd7yOyc/EzbabjzNFcbzKc3I4/HMG+XPnUrx8OQBBgwcRM+0UIgOXElj5O0T2hLGPw8hECO3s44yFOH4V5ZXM/2ADWUt2YzmpC6dPH0JQSNsob20jS+/Ls6XZhjsSHasAjBbxecBb6GMteyUmdvNw7K5VAEaL2Gsxs1MS7rIkp9c6TGZ2SkKzh8k8VHKI2Vtmc9EJFxETKhOztzRN0yh1Ojn8cwaHMzIodToBCBo4kJhbEomI2U1QzhdQ4oLuo2D8YzDkQvA3+ThzITzDtbeYua+vZe/2w4xJsDAmoR/Kr+0MmypFWHc9UFFzhSPRUQFcb0uzvdZSMbG7KoDrsZu9EjM7JcHjw2R+uflLytxlXBl3pSd3K+qhlZdTtGwZh3/6mcPzMqjI3QVKETJyJF0ffICIQREE5n4DWc/BYQ2sF8CEJOg91tepC+FRf6zYQ8a7TlCKc2bY6D+87TUEpAgDjkTHznq2LfJKULurzpjYXR6PaUlOr3eYzOyUhENN3Welu5JPNnzCqG6jGNhJril6U3lODgULF1G4cCGFS5bgPnwYFRxM2MSJRCQlET5hJAE7foClqfDzRgjpDBPvgDE3Q1QfX6cvhEdVlrtZ9PlmHJk76do3grP+MpTILiG+TqtZpAh3HNXDZGanJOwGsCSnH9cwmYtyF5FTkMM9o+7xYJoCwF1SQtHSZRQu/IWCXxZStmULAAGxsUSefRbhU6YQNnEifq4/YOkb8PadUF4IPUfDRalw4sVgaj2jAgnhKa69Rcx9fR17tx9m2Gm9mXDxAPwD2m5vfinCHYclOyXhqGEyjWKcYklOb9YwmR9lfURMSAyn9TnNIwl2ZFpFBSXOLIqWLqVw8WKKli5FKy1FBQUROmYMUZdPI3zSJAL790dVlELWd/DRxbD9VwgIBttlequ3xwhffxQhvELTNJyLd7Hw0034+bfd08/HkiLccWyzJKc/BKRVjZJljJ51A80YJnNP0R4W5Szi1mG3YvKTTj5NpZWXU7JuHYVLl1K0dCnFy1fgLiwEILB/fzpdeQVhp0widMxo/IKNFu2uNfD9w7DmEyg5BJ37w5lPw/CrpZezaNeK8suY934W2Wv20XNwFKclDmlV4z8fDynCHUf1MJmW5PSqEfibPUzmvO3z0NA423K2B1Nsv9xlZZQ4HBQtXUrU3B/YcN/9aEVFAAQOGEDk+ecROmYMoWPGYOpaY4KE4oPw+3uw4l3YvQb8g8B6Hoy4DvqdKoNqiHZvy6q9ZH6QRVlxJSdfdgLD4nu3qd7PDZEi3EFkpyQcBB42Hsftp+0/0TeyL/3N/T2xu3bHXVJC8eo1FFW1dFetQivVp2/269mTqIsvNoruaAKio49+c2U5bJkPqz8C57dQWQrdbXDO8/ppZ2n1ig6gpKCchZ9tYsOS3XTpHc6F9w4hukfrmH7Qk6QIdyCW5PQ49HuEl2SnJBTWWH92dkpCowfsWL13NUt2LeGO4XegVPv5j/R4uIuKKF61qvr0csnqNWjl5aAUQdY4Ol15BaFjxhAyahQLV6/mpClTjt6BpsGO38ExC9Z9CUX7INgMI6+HEddCj+G++FhCtDhN0ziUrfHBd0soK6pg1Dl9GZPQr013vqqPFOEOwpKcXnOs6jctyel3Z6ckNGus6k+yPsEcZOa6Idd5IdO2obKgkOKVKyj63Wjprl0LFRXg70/wkCF0uu46QseMJnTUKPwjI+veUd56vfCu/QwObdc7WQ06G2zTYOAZECCzUYmOI39fMfM/2kDOOo1u/UKYem0c0T3bX+u3JinCHcdfgFHZKQkFluR0C/CZJTndkp2S0OSxqg+WHqRXeC9CTaHeyLNV0DQN9+HDlOfmUp67i/JduVTs2kVpdjZlmzZTtmMHuN0QEEDI0KFET59O6NgxhIwYiX94PePVahoR+Zvg51/0Hs57s0D5w4CpMPVRGHwuBNdTtIVohyrL3azO2MHS9K2gFN1HKi6+eRR+7ejab12kCHccftkpCQUA2SkJ2Zbk9CnohbjJY1UXlhcSbmrb/51qFRVU7NlD+a5dRxXa8ly92Jbn7qrurVxFmUyYevcmaPBgIs87j9BRIwkZPhy/0Ab+GamsgO2LwfkdZKUzKn+nXnj7TtRvKxpyEYS3/VsthGgqTdPIXrOPhZ9tJn9vMZaTujD5ykEsX7OkQxRgkCLckeRZktOHZ6ckrAIwWsRNHqt6lB8cLnbRJ8rinSw9xF1aqhfXnTmU5xiPXbuqi25FXp7ekq3BPyoKU48emPr2JXT8BH05NhZTj1hMsbH4R0ejGtsbuegA/JEBm3+CjXOh+IB+qnlAPFmxlxB34b3SwUp0aAdyC1n42SZ2rD9Ap+6hnH/XMPoMiW74je2MFOGO409jVWenJFQA11uS0xs9VvXjmh+7n9vIzjODqBydX//1Ti/Sysr0gpqTQ1lOzlHFtsuWLWxwuY5+Q0AApu7dMfXoQdjYsQQYhdXUo6deZLt3b7hFWx93JeSs0Ivu5p8gZzmgQUgnOOEM/baiE06HwDB2Z2YSJwVYdFCHD5SwbHY2zsW7MAX5c8q0gQyd0hN///bZ8aohUoQ7iOyUhDrHqs5OSWj0WNUvXOTH2cvdjP7UwabvphJ+8kRCJ0wgdNRogvr3Q5k8M3CHu7CQ8rw8ynftomL37uoCW2YU24q8PL1HcRV/f72o9uxJ2YlD6D16NIE9e2Lq2RNTr14ExMSg/P09klu1wn2w6UfY9IPe6i05BMoPeo6CKcl60e0xAvw8HFeINqgov4wVc7axdkEOmqYxdHJPxiRYCIkI9HVqPiVFWDTJEqsfS6x+3BtxEees9qfwl184/ONP+kaTiaD+/QkaMICA7t0J6BqDf3g4KigYFRQISkF5Oe6yMrTyctyFhVS6XLhdLioPuag8dIiKvXsp370b9+HDRwf28yOgezcCe/QkbPx4vbj27ImpV08Ce/YkoFs3VID+47w1M5OYY28B8gS3G3atMgrvXL3liwbh3SAuAU44DfpPldPMQtRQfLiM1Rk7WJ2xk8qySuImxDI6wUJkdNuccMHTpAiLZnEP7EvsJTejaRrlO3ZQvHoNpRs3ULJxI8Vr1lDx009oZWUN70gp/CMj8Y+Kws9sxtSnD6FjxxLQvRum7rGYuncjoHt3TN27e6yV3SQlLvhjnt7a3fQjFO4BFPQaDVP/CgPPhO4nychVQhzDtbeYVT9tx7l4F5Xlbk4Y3ZWx5/WjU/d67h7ogKQIi2ap6h2tlCKwTx8C+/QBzqvermka7vx83IWFuEtLq0eLUiZT9cMvJAS/yMjGd3ZqCZoGeeuOXNvd/iu4KyA4Sm/pDjxL/xrWxdeZCtEq7dmWz8oft/PH8j0oP8Xg8d0ZcUYfKb51kCIsmiXMVP8vlFIKf7MZf7O5hTI6DkUHYMs82Gz0Zi7Yra/vNhQm3qW3dnuNAX/5dRGiNuWllWxalse6BTns2XaYwGB/hp/Rh2HxvQmLkgFn6iN/VUSzNFSEW7WSfNjxG2T/AtkLIXclaG69tTsgXu9QNSAeImN9nakQrdr+nALWLcxlw5LdlBVX0Ck2jElXDGLw+O4EhUh5aQw5SqJZ2tRgHYX7YefvesHdtgh2rdaLrp9J78k8+SG98PYcKT2ZhWhA4aFSNi7NY8Nvu9m/swC/AMWAEV0ZOrknsSeYZTz5JpIiLJpEq9RQ/oqwwFbaEq4oJSJ/AyzJgpxlsHMZHNyqb/MP1E8rT3oALKfoy4Htd+hNITylrLiCrav3suG33ezMOoimQde+EUy6YiADR3fr8LcZHQ8pwqJp3IB/K2gJuyvhYLY+9vLeDcbDCXucjKo0emVH9IBeo2DUDXpv5p6jwdQ+JgIXwttKi8rZumYff6zYy471B6iscBMRHcyocywMGttNOlp5iBRh0TSVgKkFrwlXlMGBLXqx3bfxSNHdt0mfZ7dKZE+IGQzjb2PtoRCGnpUIkT1aJkch2onigjK2rtYL786sA7grNcI7BTF0ck/6j4whtr8Z1UHGdG4pUoRFk7hXuvGf4O/5IlxRCvs3wx6n0ao1iu2BP/RbhABQ0KkvdBmsd5yKidMfXQYeNfPQvsxMKcBCNIKmaezbWcA2x362rd1H3tZ8NA0iuwQzLL43/UfG0K1vpBReL5IiLJqkcl4ly15eRkhAM0e7qSjTi+1eJ+zJ0r/u3QD7/wCtUn+N8ofO/fWWrfU8o9gOhuiBcg1XiONUVlJB/k6Nee9nsW3tfgoP6WeUuvaNYPS5FvoNi6FL73DpYNVCpAiLJmv0PMJlRZC3Vr8FKHcl5K6C/ZuOtGyVn1Fs42DIhUe3bGUyeyE8orLCTd5WFzuzDrJzw0HytubjrtQIDM6j95DO9B3ahb5DowmNlM5VviBFWHhGRemfC+4e55HWbVhXfTKDuHMhxgpd4/SWrXSUEsKjKivd7NtRQM4Gveju2nSIinI3SkFMnwiGndabg+U7OPvSSfgHtKLR6jooKcKiSUx+ml5c923UO0ft26SfUs5bD+5y/UWh0XrBHXyO/rXHCIiI1SdwEEJ4VElhObu3uPTHHy7ysvOpKNPnyu7cI4whp/Sg5+BO9BgYRXCYPv56ZuZOKcCthBRh0SSrp+XBq+OPrIjsCV0GwcQ7jhRcc28puEJ4QWWFmwO5hezZls+e7Hx2bcnn4K5CAJSfokuvcIac3IPuA8z0HNRJTjG3AVKERZOkrg8j6Yn/6Ndto0+AoDY0cpYQbUjNgrt3+2H2bDvM/twC3BX6PNpBoQF062dm0JhudB9gppslElOQjPjW1kgRFk3ykiOCpJOm+ToNIdqNyko3rj3FHMgt5EBuAQd2FXIgt5BDe4rR3EcKbpfeEQyb2puYvhHE9InA3CVEbh1qB6QICyGEl2lujYJDpbj2FuPaU4RrTzGH9hTh2qt/rWrdosDcJYTOPcLoPyKG6J7hdO0bQWSXELllqJ2SIiyEaBJN0ygvqaS4oIyKMjfuSo3KCjfuSjfKzw//AIV/gB/+AX4EhgQQFBaAv3/77gSkaRrFh8spOFhCwYFS9m/QWLhvE/l7i/XCu7eYynJ39ev9AhTmLiGYu4bSd2g00T3C6NwjnKjuoZgC5ZRyRyJFWAgBQHlZJUWuMor2aWxZtZei/DKKXKUUHS7Xv+aXUXy4jCJXGRU1CkpjmIL8CQoNICjMRHBYAMFhgYSEmwg2HiHhJkLCA496HtAKipG70k1xQbn+ufPLKM4vo+hwufG1jMJDpRw+UELBwdKjiizAPlMOEdHBmLuG0mdIZ8xdQzHHhGDuGkJ4p2D85FSyQIqwEO1WZYWbksJySgsrKCkqp6Sg/EghzT9SVAqNr+WlldXv3fqTo3o5ONxEaGQgoZGBmGPMhEYGEhIZSGhEIAGB/vgHKPwC/PDzV2iVGpWVGpXlbior3JQVV+g5FFVQWlhOifH1QG4BxYfLKSkqB632/AMC/YyCbBTnML1A5+12s7RwKwEmfwIC/YyHP37+elFTKDDqW9UZ3MoKjcrySiorNCqM3GrmWFZcQWktX0uLKmrNzz/Aj5AIE2FRQcT0jqDfsBgiOgcR3imYiM7BrHYu47QzT5VTyKJBUoSFaIUqK9yUl1ZSXlpJRVll9XLNR3VhKyynpLCC0qKqZb3w1iyqxwoKCyA0MojQSBPd+kYQGhlESKSJ0MggNmdnMf6U0YRGBhIcYfLqqWS3W9PzLiinuED/qi+XHfO8HNeeIkoKyikrhX3OrZ5JQEFgkD+BoQEEhQQQGBJAeFQQgT3CCAoOqP4HJCTiyD8eIZGBBAb711tgA7YoKcCiUaQIC9FMmqZRUVZ/say5rqKskvKSSnK2u5mz0UF5qftP76l6jdtdR/PwGMpPERwWQFCo3lIMjwoiumc4waEmgsOPrA8OMxmFVy8o9Q3UkFe2gZg+EZ46TPXy81OEhAcSEh5Ip0a+JzMzk8mTJlNR7qaiTD+GFWVu3G79dLCmUd161TR9wd/kV32dOqBq2aS33qVYCl+SIiyaJCzQ7OsUmsxdWVUo/1z0ai2exvOKul5jFN6Ksso6T6XWxi9AYQr0xw2o4kJMQf4EBPoTGhmoLwf5YwryxxTojynID1NQAAGBfpiC9XVHb/cnKMzUYIusvfLz9yPQ349AGfVUtHENFuGZMzLigAuBnsaqHOCbpNR4p7eScsZZa41pzXJ6LaYtzVZrTEeiw2sxsZtrjYnd5bWYluT0WmNmpyQ0KuaNE5/h63+vZMDIrnSzRGLuGkJg8PH9L6dpeu/aijL9Ol1Fud6yKS8zCmGZm/LSCipK3XUXSqMFWVFWieugm21zF1W/pvr2j0YKCPLHFOinFzyjUJqC/AmJqK1YHv0a/VGjgAYFYAryIyDIv/q0bmZmJlOmjG8gCyFER1DvX8+ZMzIeBq4CPgZ+N1b3Aj6aOSPj46TU+JQ63pfZ3ISccdY6YzrjrB9bs5y1xnTGWZsd05ZmqzOmLc32sSPRUWtMW5qt2TGxm+uMid38MXZXrTGxm5sd05KcXmdMS3L6x9kpCX+KaUlOPyre5OwMzDGXMv/DDdXrAoP9CY4IJMBknOoz+eHnp3C7NTS3XmQ1t1b9vKK8Ui+2ZUbBLXc3qUUJ+mlMU/DRxU/vyBNIiRt69Op0dOux1mL553UBJj8ZAEEI0WIaasLcBJyYlBpfXnPlzBkZLwDrgNoLxZ/ta0JONwEnWrOcR8V0xlm9HtOR6Dgqpi3N5vWY2F1HxcRu9nrM7JSEo2JaktMbFbN09+bh7/3wAu/98EITQgohhKhLQ0XYDfQAth2zPtbYVquk1PgpRz9vUjOnWTGtWc6jYjaxYdWsmI5Ex1ExSfR+TOyuo2Jqdu/GzE5JqI6nlMoE0DRtSm2vbQ1ae46S3/Fp7flB689R8js+Vfl5SkNF+B7g55kzMjYBO4x1fYATgDs8mcixMZ1x1haPaUuztXhM7OYWj2lJTm/JmEIIIeqgqrrw12XmjAw/YCxHd+RZmpQaX/dNiMfJGWetNaY1y+m1mLY0W60xHYkOr8XEbq41JnaX12JaktNrjZmdktBgzNb+Hyq0/hwlv+PT2vOD1p+j5Hd8PJ1fg0VYCCGEEN7RvkdVF0IIIVoxKcJCCCGEj0gRFkIIIXxEirBAKfWWUmqPUmptjXXDlFK/KqUcSqlvlVKRNbY9opTarJTaoJQ6q8b6s411m5VSyb7ITyl1hlJqubF+uVIqvsZ7Mo38VhmPrj7Iz6KUKq6RQ2qN94wyXr9ZKfWS8tB4lE3M75oaua1SSrmVUsONbd46fr2VUvOUUuuVUuuUUncb6zsrpX5USm0yvnYy1ivj+GxWSq1RSo2ssa9E4/WblFJNu2nQszleY+TmUEotVkoNq7GvbGP9KqXUMh/lN0Up5arxvXyixr48/nvcjPwerJHbWqVUpVKqs7GtJY/fNOO5Wyk1+pj3eObvoKZp8ujgD2AyMBJYW2PdUuBUY/lG4O/G8hBgNRAE9AP+APyNxx9AfyDQeM0QH+Q3AuhhLA8Fcmq8JxMY7ePjZ6n5umP28zswHn0ivu+Bc1o6v2PeZwP+aIHjFwuMNJYjgI3Gz9lzQLKxPhl41lg+1zg+yjhevxnrOwNbjK+djOVOPspxYlVs4JyqHI3n2UAXHx/DKcB3tezHK7/HTc3vmPeeD2T46PhZgcHH/uzjwb+D0hIWaJq2ADhwzOpBwAJj+UfgUmP5QuBjTdNKNU3bCmxGv+VpLLBZ07QtmqaVoQ+NeWFL56dp2kpN03KN9euAEKVUkCfy8ER+dVFKxQKRmqYt0fTf8neBi3ycX9UQp16ladouTdNWGMuHASf6LXQXAmnGy9I4cjwuBN7VdEuAKOP4nQX8qGnaAU3TDqJ/rrN9kaOmaYuNHACWoA8P6zXNOIZ18crv8XHmdxXw0fHm0Jz8NE1zapq2oZa3eOzvoBRhUZd1HPnhmQb0NpZ7cmSgD4Cdxrq61rd0fjVdCqzQNK20xrq3jdNYj3vqdG8z8uunlFqplJqvlJpkrOuJfsyqtIbjdwV//uPn1eOnlLKgn834DeimadouY9NuoJux7NOfwUbmWNNN6C33Khrwg9Ivl9ziw/wmKKVWK6W+V0qdaKzz+jFsyvFTSoWi/yP1eY3VLXn86uKxn0EpwqIuNwK3K6WWo5+eKfNxPseqNz/jj8qzwK01Vl+jaZoNmGQ8rvNBfruAPpqmjQDuAz5UNa63t6CGjt84oEjTtLU1Vnv1+CmlwtH/2N6jaVp+zW3G2QGfD2rQ1ByVUlPRi/DDNVafomnaSPTT1ElKqck+yG8F0FfTtGHAy8BXnsrBQ/lVOR9YpGlazTM5Pjl+3iJFWNRK07QsTdPO1DRtFHpr6A9jUw5Ht5p6GevqWt/S+aGU6gV8CVyvadofNd6TY3w9DHyIfuqoRfMzTl/tN5aXG+sHoR+rmqcsfXb8DFdyTCvYm8dPKWVC/+P3gaZpXxir84zTzFWn6/cY633yM9jEHFFKnQS8AVxY9T2Ho47jHvSfU48cx6bkp2lavqZpBcbybMCklOqCF49hU4+fob6fw5Y4fnXx2M+gFGFRK2X0fFVK+QGPAVW9eL8BrlRKBSml+gED0TsULQUGKqX6KaUC0X95vmnp/JRSUUA6emePRTVeH2D8kan6ZTsPWIuX1JNfjFLK31juj378thin5PKVUuON07zXA1+3dH411l1OjevB3jx+xud9E3BqmlZziq5vODItSiJHjsc3wPVKNx5wGcdvLnCmUqqT0cv2TGNdi+eolOoDfAFcp2naxhr7CVNKRVQtGzke93FsRn7dqy4nKKXGoteC/Xjp97gZ32OUUmbg1GPWtfTxq4vn/g7W12tLHh3jgf6f5i6gHP0axk3A3eg9BDeiT3Goarz+UfSW0wZq9OBF77W60dj2qC/yQy8ohcCqGo+uQBiwHFiDfj30P4C/D/K71Ii/Cv2U4Pk19jMa/Q/KH8ArNY95C39/pwBLjtmHN4/fKeinIdfU+J6dC0QDPwObgJ+AzsbrFTDTOE4Oju61eiN6J5nNwHQP/gw2Ncc3gIM1XrvMWN8fvcfsauM4euT3pBn53WHEX43ecWyiN3+Pm5qf8Z4b0Ds/1dxPSx+/i9F/Z0qBPGBujfd45O+gjB0thBBC+IicjhZCCCF8RIqwEEII4SNShIUQQggfkSIshBBC+IgUYSGEEMJHpAgLIZpFKRWllLq9xvMeSqnPvBDHrpTKUUo95el9NzL+PKVUgTpmFh0hPEGKsBCiuaKA6iKsaVqupmmXeSnWi5qmPdHwy5pHKRVQ1zZN06YCHpkyT4hjSREWQjRXCjDAmNDheaXPlbwWQCl1g1LqK6XPEZutlLpDKXWf0ieuWKKOzA07QCk1xxiM/xelVFx9AZVSfkqfezamxvPNxkhkMUqpz5VSS43HycZrxip97uSVSp/bd3CNHL9RSmUAPyulYpVSC9SROWwn1ZOKEB4hRVgI0VzJ6PMND9c07cFatg8FLgHGAE+jTwgxAvgVfVhOgP8Bd2r6GNYPAK/WF1DTNDfwPnCNsep0YLWmaXvRR/F6UdO0Megjk71hvCYLmGTEfgJ4psYuRwKXaZp2KnA1+ohIw4Fh6KMmCeFVdZ6CEUKI4zRP0yd7OKyUcgHfGusdwElKn7FmIjBLHZkVsTFzP7+FPp7wv9GHqXzbWH86MKTGviKNGGYgTSk1EH1oQlONff2oHZmhZynwljE29leapq1qwmcVolmkCAshvKXmPM7uGs/d6H97/IBDRsuz0TRN26GUylNKxaPPoFPVKvYDxmuaVlLz9UqpV9D/IbhY6XPFZtbYXFhjvwuUPi1eAvCOUuoFTdPebUpuQjSVnI4WQjTXYfS5iJtF0+dr3aqUmgb6TDZKqWGNfPsb6KelZ2maVmms+wG4s+oFSqnhxqKZI9PJ3VDXDpVSfYE8TdNeN/Y/spG5CNFsUoSFEM2i6XPkLjI6MT3fzN1cA9yklKqaFefCRr7vGyCcI6eiAe4CRiul1iil1gMzjPXPAf9QSq2k/rN/U4DVxuuuQL/GLIRXySxKQohWTSllBwo0TftnjXWj0TthtUgPZqVUJvCApmlyq5LwKGkJCyFauwLglqrBOpRSycDnwCMtEVwpNQ99HtvylognOhZpCQshhBA+Ii1hIYQQwkekCAshhBA+IkVYCCGE8BEpwkIIIYSPSBEWQgghfESKsBBCCOEj/w+/AGJaIM5L5wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# We custom some constants here, \n",
+    "# Otherwise write an other scenario in the file 'world3/limits_to_growth_code.py'\n",
+    "\n",
+    "# Example: 5 times less arable land initial\n",
+    "s.ali = s.ali/5\n",
+    "s.run()\n",
+    "# plot variables in world3 manner\n",
+    "plot_world_variables(s.time,\n",
+    "     [s.nrfr, s.iopc, s.fpc, s.pop,\n",
+    "      s.ppolx],\n",
+    "     [\"NRFR\", \"IOPC\", \"FPC\", \"POP\", \"PPOLX\"],\n",
+    "     [[0, 1], [0, 1e3], [0, 1e3], [0, 16e9], [0, 32]],\n",
+    "     figsize=(7, 5),\n",
+    "     grid=1,\n",
+    "     title=fig_title)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from inspect import getcallargs, getmembers, getdoc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class UpdateFunGen:\n",
+    "    \"\"\"I update var\"\"\"\n",
+    "    class Var:\n",
+    "        def __init__(self, name, index):\n",
+    "            self.name = name\n",
+    "            self.index = index\n",
+    "            \n",
+    "    def __init__(self, line):\n",
+    "        var, index, (all_vars, all_names, all_func), right_eq = get_pars_update_eq(line)\n",
+    "        self.fun = gen_update_fun(line)\n",
+    "        self.vars = list()\n",
+    "        for var, index in all_vars.items():\n",
+    "            v = self.Var(var, index)\n",
+    "            self.vars.append(v)\n",
+    "        self.__doc__ = f\"I update {var}\"\n",
+    "#         self.__name__ = f\"update_{var}\"\n",
+    "            \n",
+    "    def __call__(self, *args):\n",
+    "        for arg, var in zip(args, self.vars):\n",
+    "            setattr(var, var.index, arg) \n",
+    "        return self.fun(*self.vars)\n",
+    "    def get_fun(self):\n",
+    "        f = self.__call__\n",
+    "        f.__doc__ = self.__doc__\n",
+    "        f.__name__ = self.__name_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "ff =UpdateFunGen(\"ac.k = bc.k +abc.j*ad.k\")\n",
+    "ff(np.ones(5), np.arange(5), 2)\n",
+    "ff.__doc__ = 'rpout'\n",
+    "help(ff)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.01.Some_notes.ipynb b/12.01.Some_notes.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..bdd5c8558c809fe6bc36b3ad15044e5e6db5519b
--- /dev/null
+++ b/12.01.Some_notes.ipynb
@@ -0,0 +1,62 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Notes\n",
+    "- Trucs qui dérangent dans les équations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A ifpc1.k = tabhl(ifpc1t, iopc.k, 0, 1600, 200)\n",
+    "plt.plot([230, 480, 690, 850, 970, 1070, 1070, 1150, 1210, 1250])\n",
+    "plt.title('Et l agro écologie tu connais ?')\n",
+    "plt.xlabel('Industrial output per capita')\n",
+    "plt.ylabel('Indicated food per capita')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TODO:\n",
+    "\n",
+    "- parenthèse pour les fonctions spéciales "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.01.collapse_tracker.ipynb b/12.01.collapse_tracker.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..d4f885ec4148db5e2378d36d1bf9b2eae0f30f78
--- /dev/null
+++ b/12.01.collapse_tracker.ipynb
@@ -0,0 +1,438 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Track why did it collapse"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import system\n",
+    "from dynamo_reader import read_dynamo, Runs_reader\n",
+    "sys.path.append('./world3')\n",
+    "from plot_utils import plot_world_variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Get dynamo instructions\n",
+    "base_file = 'world3/world3_dynamo_code.py'\n",
+    "runs_file = 'world3/limits_to_growth_code.py'\n",
+    "new_file = 'new_instr.py'\n",
+    "\n",
+    "reader = Runs_reader(base_file, runs_file, new_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fig 35. Standart run\n",
+      "SIM\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Write next instructions\n",
+    "fig_title, new_instructions = reader.next()\n",
+    "instr = read_dynamo(new_file)\n",
+    "print(fig_title)\n",
+    "for l in new_instructions: \n",
+    "    print(l)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Special parameters\n",
+    "N = 400\n",
+    "dt = 0.5\n",
+    "start_time = 1900\n",
+    "specials = {'dt': dt, 'N':N, 'start_time':start_time}\n",
+    "\n",
+    "# Init a first system\n",
+    "s = system.System(*instr, **specials, verbose=False)\n",
+    "\n",
+    "# Run \n",
+    "s.run()\n",
+    "\n",
+    "# plot variables in world3 manner\n",
+    "plot_world_variables(s.time,\n",
+    "     [s.nrfr, s.iopc, s.fpc, s.pop,\n",
+    "      s.ppolx],\n",
+    "     [\"NRFR\", \"IOPC\", \"FPC\", \"POP\", \"PPOLX\"],\n",
+    "     [[0, 1], [0, 1e3], [0, 1e3], [0, 16e9], [0, 32]],\n",
+    "     figsize=(7, 5),\n",
+    "     grid=1,\n",
+    "     title=fig_title)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import importlib\n",
+    "import system\n",
+    "importlib.reload(system)\n",
+    "s = system.System(*instr, **specials, verbose=False)\n",
+    "f = s.get_update_fun('pop.k')\n",
+    "s.run()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 309,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for i in name_inter:\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 306,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s.nr[230] = s.nr[230]  + 2e12 + 0.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 310,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2477608696665.404"
+      ]
+     },
+     "execution_count": 310,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.nr[230]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 295,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s.k = 230\n",
+    "for vi in nx.topological_sort(sG):\n",
+    "    v, i = vi.split('.')\n",
+    "    getattr(s, v)[s.k] = s.eval(s.all_updates[vi])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 305,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2593709238088.7515"
+      ]
+     },
+     "execution_count": 305,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.io[230]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def merge_fun(a, b):\n",
+    "    aa = a.split('.')[0]\n",
+    "    bb = b.split('.')[0] \n",
+    "#     if re.sub('[0-9]', '', aa) == re.sub('[0-9]', '', bb):\n",
+    "#         return True\n",
+    "    return  aa == bb \n",
+    "def rename_fun(a):\n",
+    "    for i in a:\n",
+    "        return i.split('.')[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gg = nx.relabel_nodes(nx.quotient_graph(G, merge_fun), rename_fun)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "' (self.p2[k] + self.p3[k])*self.lfpf'"
+      ]
+     },
+     "execution_count": 102,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.all_updates['lf.k']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 166,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def all_influenced_by(G, var, n):\n",
+    "    v, i = var.split('.')\n",
+    "#     if i in {'j', 'jk'}:\n",
+    "#         n = n - 1\n",
+    "    for a, b in G.out_edges(var):\n",
+    "        for bb in all_influenced_by(G, b, n):\n",
+    "            yield bb\n",
+    "    if i in {'k', 'kl'} and n > 0:\n",
+    "        i = 'j' if i == 'k' else 'jk'\n",
+    "        for bb in all_influenced_by(G, v + '.' + i, n-1):\n",
+    "            yield bb\n",
+    "    yield var\n",
+    "\n",
+    "def all_influences(G, var, n):\n",
+    "    v, i = var.split('.')\n",
+    "    for a, b in G.in_edges(var):\n",
+    "        for aa in all_influences(G, a, n):\n",
+    "            yield aa\n",
+    "        yield a\n",
+    "        \n",
+    "    if i in {'j', 'jk'} and n > 0:\n",
+    "        i = 'k' if i == 'j' else 'kl'\n",
+    "        for aa in all_influences(G, v + '.' + i, n-1):\n",
+    "            yield aa\n",
+    "    yield var\n",
+    "\n",
+    "def all_between(G, a, b, n):\n",
+    "    t = set(all_influenced_by(G, a, n))\n",
+    "    b = set(all_influences(G, b, n))\n",
+    "    return t.intersection(b)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 197,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<networkx.classes.digraph.DiGraph at 0x7f07e8244520>"
+      ]
+     },
+     "execution_count": 197,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def extended_G(G, n):\n",
+    "    eG = nx.DiGraph()\n",
+    "    for a, b in G.edges():\n",
+    "        va, ia = a.split('.')\n",
+    "        vb, ib = b.split('.')\n",
+    "        eG.add_edge(a, b)\n",
+    "        for i in range(n):\n",
+    "            if ia == 'j':\n",
+    "                eG.add_edge(va + 'k', vb + ib + str(n))\n",
+    "            if ia == 'jk':\n",
+    "                eG.add_edge(va + 'kl', vb + ib + str(n))  \n",
+    "            else:\n",
+    "                eG.add_edge(va + ia + str(n), vb + ib + str(n))\n",
+    "    return eG\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 267,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "select = all_between(eG, 'nr.k', 'io.k', 0)\n",
+    "sG = nx.subgraph(G,select)\n",
+    "nx.draw(sG, with_labels=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_last(G, k, var):\n",
+    "    if k == 0:\n",
+    "        return []\n",
+    "    for a, b in G.in_edges(var):\n",
+    "        for i in get_last(G, k-1, a):\n",
+    "            yield i\n",
+    "        yield a"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 115,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_eq(var):\n",
+    "    try:\n",
+    "        return s.all_updates[var + '.k']\n",
+    "    except:\n",
+    "        try: \n",
+    "            return s.all_updates[var + '.kl']\n",
+    "        except:\n",
+    "            return 'Not updated'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 147,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pyvis.network import Network\n",
+    "net = Network(notebook=False, directed=True)\n",
+    "for a in G.nodes:\n",
+    "    net.add_node(a, title = get_eq(a))\n",
+    "for a,b in G.edges:\n",
+    "    net.add_edge(a, b)\n",
+    "net.show('ex.html')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "nx.draw(G, with_labels = True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "nx.draw(gg, with_labels = True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.04.Hubbert.ipynb b/12.04.Hubbert.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..1ae1044798a533833757ef17cfb872f5e81e5d1d
--- /dev/null
+++ b/12.04.Hubbert.ipynb
@@ -0,0 +1,144 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Hubbert model with (old) pydynamo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new_file = 'hubbert/nh.py'\n",
+    "rr = Runs_reader('hubbert/hubbert.py', new_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "to_plot = {2, 4}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "to_plot = range(rr.get_nb_runs() - 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in to_plot:\n",
+    "    plt.figure()\n",
+    "    title, ll = rr.write_instructions(i)\n",
+    "    instr = read_dynamo(new_file)\n",
+    "    s = System(*instr, dt=0.1, N=200)\n",
+    "    s.run()\n",
+    "    s.plot_vars(title=title)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.show_update_graph()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.04.new_system.ipynb b/12.04.new_system.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..7e133e24494f0ad32d9a2cea2c0c79028a907d05
--- /dev/null
+++ b/12.04.new_system.ipynb
@@ -0,0 +1,307 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# New system"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pydynamo.dynamo_converter import convert_dynamo_file\n",
+    "convert_dynamo_file('world3/world3_DYNAMO_code.py', \n",
+    "                    'world3/world3_pydynamo_code.py')\n",
+    "convert_dynamo_file('hubbert/hubbert_nr_r_dynamo.py', \n",
+    "                    'hubbert/hubbert_nr_r_py.py')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hubbert model from file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pydynamo\n",
+    "s = pydynamo.parse_system.system_from_file('hubbert/hubbert_nr_r_py.py')\n",
+    "s.run(100, 0.2)\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.plot(s.capital, label='capital');\n",
+    "plt.plot(s.resource, label='resource');\n",
+    "plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hubbert model from function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def hubbert_eqs():\n",
+    "    # Hubbert model\n",
+    "    capitali = 0.01 # Initial captial\n",
+    "    resourcei = 1 # Initial resource\n",
+    "\n",
+    "    rcr = 4/3 # Resource consumption rate\n",
+    "    rrr = 0 # Resource reprodution rate\n",
+    "    crr = 4 # Capital reproduction rate\n",
+    "    cdr = 1 # Capital dissipation rate\n",
+    "\n",
+    "    resource.k = resource.j + dt*(-rcr*capital.k*resource.j + rrr*resource.j) # Resource\n",
+    "    capital.k = capital.j + dt*(crr*capital.j*resource.j - cdr*capital.j) # Capital\n",
+    "    \n",
+    "    capital.i = capitali \n",
+    "    resource.i = resourcei"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pydynamo\n",
+    "s = pydynamo.parse_system.system_from_fun(hubbert_eqs)\n",
+    "s.run(100, 0.2)\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.plot(s.capital, label='capital');\n",
+    "plt.plot(s.resource, label='resource');\n",
+    "plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# World3 model from file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "from world3.plot_utils import plot_world_with_scales\n",
+    "s = pydynamo.parse_system.system_from_file('world3/world3_pydynamo_code.py')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 927 ms, sys: 7.05 ms, total: 934 ms\n",
+      "Wall time: 929 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%time s.run(400, 0.5)\n",
+    "import matplotlib.pyplot as plt\n",
+    "plot_world_with_scales(s)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Tests and comparisons"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pydynamo\n",
+    "import importlib\n",
+    "import numpy as np\n",
+    "import networkx as nx\n",
+    "import ast"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "importlib.reload(pydynamo)\n",
+    "# filename = 'world3/world3_py_code.py'\n",
+    "filename = 'hubbert/hubbert_py.py'\n",
+    "# nodes, eqs = parse_system.get_nodes_eqs_dicts(filename)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = pydynamo.parse_system.system_from_file(filename)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fb9ffde82b0>]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def ff(capital_j, resource_j, dt, cdr):\n",
+    "    return capital_j + (dt * (((4 * capital_j) * resource_j) - (cdr * capital_j)))\n",
+    "\n",
+    "s.update_capital = ff\n",
+    "s.capitali = 0.4\n",
+    "s.run(100, 0.2)\n",
+    "plt.plot(s.capital)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def print_node(x, j, show_type):\n",
+    "    a = '.'.join(x) if isinstance(x, tuple) else x \n",
+    "    b = '\\n' + j if show_type else ''\n",
+    "    return a + b\n",
+    "\n",
+    "def draw_graph(G, show_type=False):\n",
+    "    pos = nx.spring_layout(G)\n",
+    "    nx.draw(G, pos)#, node_size=1000)\n",
+    "    nodes_labels = {i:  print_node(i, j, show_type) for i, j in G.nodes(data='type')}\n",
+    "    nx.draw_networkx_labels(G, pos, nodes_labels);\n",
+    "    edges_labels = {(i, j):k for i, j, k in G.edges(data='type')}\n",
+    "    nx.draw_networkx_edge_labels(G, pos, edges_labels);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "draw_graph(s.get_update_graph())"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.06.HANDY.ipynb b/12.06.HANDY.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..31efb9d56a314bf22683af022068f2c58038abae
--- /dev/null
+++ b/12.06.HANDY.ipynb
@@ -0,0 +1,201 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import importlib\n",
+    "import numpy as np\n",
+    "import networkx as nx\n",
+    "import ast\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pydynamo as dno\n",
+    "importlib.reload(dno.parse_equations)\n",
+    "importlib.reload(dno.parse_system)\n",
+    "importlib.reload(dno.parse_dynamo_functions)\n",
+    "importlib.reload(dno.system)\n",
+    "importlib.reload(dno);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "s = dno.parse_system.system_from_file('handy/handy.py')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.xei = 0\n",
+    "s.d = s.d_s \n",
+    "s.run(1000, 1)\n",
+    "dno.plot_system(s, ['y', 'xc', 'w','xm'], scales = {'y':s.l, 'w':4*s.l, 'xc':s.xm, 'xm':s.xm})\n",
+    "plt.title('Egalitarian society: Soft Landing to Optimal Equilibrium');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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n7Lvvvss777xDdXU1ffr04eOPP2bbtm0sWbKE1atX89xzz7Fw4UJ+//vfM2fOHNLS0sjPzyctLY2MjAzmzp3L119/TWlpKWazmaVLl3L//feza9cuTCYTTz/9NJdffjkAl112GfPnz+ePf/zj2b1Qig5Jayj0JcB9Qoj5wHCg6Gz5z88FQgiMBj1Gg57IAKPL8sWVJo6friDrdAWH8ko5kFNCem4p8zcco8JkBsDboGdQbCCpPYIZ3jOEEb1CMRr0Z/tU2j3PfLubPSeKW7XNgdEB/OWyRKf5t912G1deeSUPPvggFouF+fPns2HDhjplqqurOXz4MPWDxz322GNcfPHF3HbbbXXSr7zySpuSf+qpp3j//fe5//77mTZtGpdeeilXX321S7m3bNnCjh07CAkJ4YknnuCCCy7ggw8+oLCwkPPOO49Jkybh6+tLWloaL7zwglLoCoe4VOhCiM+B8UCYECILbcUgA4CU8i20NT6nAulAOdo6hF2GAKOBgCgDA6ICmEykLd1ikRw7Xc62Y4VszSxkS+Zp3v35MG+uOoSXh47hvUIZ1zecKUndiAnybsMz6FrEx8cTGhrK1q1bycnJISUlhdDQ0Dpl8vPzCQoKalC3V69eDB8+vI7lDrBr1y6eeuopCgsLKS0t5aKLLmqyXJMnTyYkRFsu9ccff2TJkiXMmTMH0IZ6ZmZmMmDAACIiIjhx4kRjTSm6MO6McrnBRb4E7m01iToJOp2gR6gvPUJ9uXxIDAAV1WY2ZJxi9f48Vh/I5dnv9vDsd3s4Lz6Ey4ZEc9mgKIJ83PPPdgYas6TPJrfffjtz584lOzu7gbUN4O3t7XT87xNPPMHVV1/NuHHjbGkzZ85k0aJFDB48mLlz57Jq1SqHdT08PLBYLAAN2vf19bVtSylZuHAh/fr1a9BGZWUl3t7KAFA4Rjl2zyHennrG9Q1n9mUDWf7weFY9Mp6HJ/fldHk1f160i+HPL+ePX21n94mitha1U3PFFVfwv//9j40bNzq0poODgzGbzQ6Vev/+/Rk4cCDffvutLa2kpISoqChMJhOffvqpLd3f35+SkhLbfnx8PJs3bwbgq6++cirfRRddxGuvvUbtamJbt2615R04cICkpKQmnK2iK6EUehsSH+bL/RMT+PGhsfx31vlcNTSWb7ef5JJ/r+GGd9bz2+GCthaxU+Lp6cmECRO49tprbaNY6nPhhReyZs0ah3lPPvkkWVlZtv1nn32W4cOHM3r0aPr3729Lv/7663nppZdISUnh0KFDPPLII7z55pukpKSQn5/vVL4///nPmEwmBg0aRGJiIn/+859teStXruSSSy5p6ikrughttqZoWlqaVAtcNKSowsSXG4/xzi+HySupYnSfUB6fMoDk2LM3sudcsnfvXgYMGNCmMlgsFlJTU1mwYAEJCQkOy2zZsoWXX36Zjz/++BxL55yqqirGjRvHmjVrnA5tVHQuHP1ehBCbpZRpjsorC72dEeht4I6xvfj50Qk8dckA9p0sYdoba3jym50Ulle3tXgdnj179tCnTx8mTpzoVJkDpKamMmHCBMxm8zmUrnEyMzN54YUXlDJXOEVZ6O2cogoTL/90gHm/ZhDk48nzVyQxJSmqrcVqNu3BQlcoOgrKQu9kBHobeHpaIv+dNYbYYG/u/mQLjyzYTkmlqa1FUygU7Qyl0DsIA6ICWPiHUdx/QR++3pLF9DfWcjivtK3FUigU7Qil0DsQBr2Ohy/sx2d3jOB0uYnL31jLqv25bS2WQqFoJyiF3gEZ0SuUxfeOJjbYh9vmbuSrzVmuKykUik6PUugdlLgQH766eySjeofxyILtzPs1o61F6hI8+OCD/Pzzz4C2Purjjz9OQkICqampjBw5ku+//76NJeyY+Pn5NZpfWFjIf/7zH9v+iRMn3IqR44xJkyZx+vTpZtdvryiF3oHx9fLgvRlpTB4YyezFu3nvl8NtLVKnpqCggPXr1zN27FhAmwB08uRJdu3axZYtW1i0aFGdmaEdkZqaGteF2oD6Cj06OrrR2bau+N3vflenvc6CUugdHKNBz39uSmVqcjee++9eFir3S6Ns3LiRQYMGUVlZSVlZGYmJiezatQuz2cwjjzxCUlISgwYN4rXXXmtQd+HChUyZoq3GWF5ezrvvvstrr72Gl5cXAJGRkVx77bUAfP755yQnJ5OUlMRjjz1ma8PPz49HH32UxMREJk2axIYNGxg/fjy9evViyZIlAMydO5fp06czefJk4uPjef311/nXv/5FSkoKI0aM4NSpUwBs27aNESNGMGjQIK644gqbxTl+/Hgee+wxzjvvPPr27csvv/wCgNls5tFHH2XYsGEMGjSIt99+G4BVq1YxZswYpk2b5jB2u5+fHw899BCJiYlMnDiRvLw8l8d/4IEHGDJkCElJSbZolk8//bQt4BhAUlISGRkZdY5VWlrKxIkTSU1NJTk5mcWLFwPw+OOPc+jQIYYMGcKjjz5KRkaGLQRCZWUlt956K8nJyaSkpLBy5UrbdbzyyiuZMmUKCQkJdSJUTps2jc8//9zpc9JRUTMUOgEGvY6XrxtCccUm/rhwB0E+BiYOiHRdsa35/nHI3tm6bXZLhotfcJo9bNgwpk2bxlNPPUVFRQU333wzSUlJvPnmm2RkZLBt2zY8PDxsStOetWvX2l7z09PT6d69OwEBAQ3KnThxgscee4zNmzcTHBzMhRdeyKJFi5g+fTplZWVccMEFvPTSS1xxxRU89dRT/PTTT+zZs4cZM2Ywbdo0QIvguHXrViorK+nTpw8vvvgiW7du5aGHHmLevHk8+OCD3HLLLbz22muMGzeO2bNn88wzz/DKK68AmqW9YcMGli5dyjPPPMOyZct4//33CQwMZOPGjVRVVTF69GguvPBCQJsZu2vXLocrzJeVlZGWlsbLL7/MX//6V5555hlef/31Ro9fXl7Otm3b+Pnnn7ntttvYtcvhGvMNMBqNfPPNNwQEBJCfn8+IESOYNm0aL7zwArt27WLbtm0Adf4I3njjDYQQ7Ny5k3379nHhhRdy4MABQPvT2bp1K15eXvTr14/777+fuLg4goODqaqqoqCgoEG0zY6MstA7CV4eet763VAGRgUw6/OtHMzp2K/+Z5PZs2fz008/sWnTJpvVtmzZMu666y7bLMzaULb2nDx5kvDwcJftb9y4kfHjxxMeHo6Hhwc33XSTze/u6elps/KTk5MZN24cBoOB5OTkOkpqwoQJ+Pv7Ex4eTmBgIJdddpmtTkZGBkVFRRQWFtqiPs6YMcN2DNBitAMMHTrU1u6PP/7IvHnzGDJkCMOHD6egoICDBw8CcN555zlU5gA6nY7rrrsOgJtvvpk1a9a4PP4NN2hBWseOHUtxcTGFhYUurxtokSafeOIJBg0axKRJkzh+/Dg5OTmN1lmzZg0333wzoAVP69Gjh02hT5w4kcDAQIxGIwMHDuTo0aO2ep0xFLGy0DsRfl4evHPLUC57bS13zNvE4nvPJ9CnHS+J14glfTYpKCigtLQUk8lEZWVlndC1jWEfVrdPnz5kZmZSXFzs0Ep3hsFgsK3mrtPpbO4anU5Xx39dm+6qnDNqy+v1elt5KSWvvfZagwiTq1atcvsagHur0dcvI4SoEz4YGoYQBm2lqLy8PDZv3ozBYCA+Pt5pKGN3sL+O9tei9vidLRSxstA7GVGB3rx1cyrHCyt46MtttFVoh/bMXXfdxbPPPstNN91k829PnjyZt99+2/aDd+RyGTBgAOnp6QD4+Pjw+9//ngceeIDqai3GTl5eHgsWLOC8885j9erV5OfnYzab+fzzz+vET28NAgMDCQ4OtvnHP/74Y5fHuOiii3jzzTcxmbRZxgcOHKCsrMzlsSwWi60D8rPPPuP88893efwvvvgC0KznwMBAAgMDiY+PZ8uWLYDm4jlypOFC70VFRURERGAwGFi5cqXNoq4fitieMWPG2MIWHzhwgMzMTIex5O2RUpKdnd1gVaqOjlLonZC0+BCenDqAFfty+Xj9UdcVuhDz5s3DYDBw44038vjjj7Nx40ZWrFjB7bffTvfu3Rk0aBCDBw9usCoRwCWXXFJn8YrnnnuO8PBwBg4cSFJSEpdeeikBAQFERUXxwgsvMGHCBAYPHszQoUNta4K2Jh999BGPPvoogwYNYtu2bcyePbvR8rfffjsDBw4kNTWVpKQk7rrrLresfV9fXzZs2EBSUhIrVqywHaex4xuNRlJSUrj77rt5//33Abjqqqs4deoUiYmJvP766/Tt27fBsW666SY2bdpEcnIy8+bNs4UjDg0NZfTo0SQlJfHoo4/WqXPPPfdgsVhITk7muuuuY+7cuXUsc0ds3ryZESNGdL5AZ1LKNvkMHTpUKs4eFotFzvjgN9n3yaXyQHZxW4tjY8+ePW0tQosYPXq0PH36dFuLcU7x9fVtUvlx48bJjRs3niVpWodZs2bJZcuWtbUYLnH0ewE2SSd6VVnonRQhBP+4ehB+Xh48MH8bJrPFdSWFS/75z3+SmZnZ1mIoWkhSUhITJ05sazFaHaXQOzER/kb+dkUSe04W8+Hahv5KRdMZPnw4gwYNamsxzimlpU0LArdq1SrS0hxGd2033HHHHW0twllBKfROzkWJ3Zg0IIKXfzpI1unythZHoVCcRZRC7+QIIXh6WiIATy/Z3cbSKBSKs4lS6F2A2GAfHpyUwLK9ufx8IK+txVEoFGcJpdC7CDNHxxMb7M0L3+/DYlFj0xWKzohS6F0ELw89j17Ujz0ni1m8/Xhbi6NQKM4CSqF3IS4bFE1yTCBzfjhApan9rGbf3rn66qs5fPgwr776Kg8++KAt/a677mLSpEm2/ddee41Zs2Y1uf25c+dy3333AbBo0SL27Nljyxs/fjyOFlPfuXMnM2fObPKxFJ0bpdC7EDqd4LEp/TleWMECFWbXLXbv3o3ZbKZXr16MHj2adevW2fK2b99OUVERZrP257hu3TpGjRrVouPVV+jOSE5OJisrS42JV9Shk817VbhidJ9QUroH8daqQ1w/LA6Dvu3+01/c8CL7Tu1r1Tb7h/TnsfMec5r/0ksv4eXlxaxZs3jooYfYvn07K1asYMWKFbz//vu2mCC1fPrpp7Zp+0OGDOHAgQNUVFRQXV2Nt7c3ffr0YefOnQwZMoR169bxj3/8g0OHDnHvvfeSl5eHj48P7777Lv379+fbb7/lueeeo7q6mtDQUD799FMiI8+EOV63bh1Llixh9erVPPfccyxcuBCABQsWcM8991BYWMj777/PmDFjALjsssuYP39+nTjfiq6NstC7GEII7pvQh+OFFSzZ1rlCh7rDmDFjbAGlNm3aZIu6+Msvv9hWIrJn7dq1DB06FAAPDw9SUlLYuHEj69evZ/jw4YwYMYJ169Zx/PhxpJTExcVx55138tprr7F582bmzJnDPffcA8D555/P+vXr2bp1K9dffz3/+Mc/6hxr1KhRTJs2jZdeeolt27bRu3dv4Exs81deeYVnnnnGVj4tLc12LgoFKAu9S3JB/wj6d/PnP6vSuSIlBp3OdTjUs0FjlvTZYujQoWzevJni4mK8vLxITU1l06ZN/PLLL/z73/9uUL5+DPRRo0axbt06KioqGDlyJAkJCTz//POEh4czatQoSktLWbduHddcc42tTlVVFQBZWVlcd911nDx5kurqaqfxx+vjKLY5dM543oqWoSz0LogQgnsn9OFQXhk/7ml88YDOhsFgoGfPnsydO5dRo0YxZswYVq5cSXp6OgMGDGhQ3j4GOmDzo//666+MHDmSAQMGsGfPHpv/3GKxEBQUxLZt22yfvXv3AnD//fdz3333sXPnTt5++22343w7im0OnTOet6JluKXQhRBThBD7hRDpQojHHeR3F0KsFEJsFULsEEJMbX1RFa3JxUndiAny5qN1GW0tyjlnzJgxzJkzh7FjxzJmzBjeeustUlJSHC7cYB8DHWDkyJGsX7+evLw8IiIiEEIQHh7O4sWLGT16NAEBAfTs2ZMFCxYAWjTT7du3A1qs75iYGEALPeuIxuJ+1+fAgQO2dTUVCnBDoQsh9MAbwMXAQOAGIUT9lWSfAr6UUqYA1wOdbzntToaHXsfNI3rw6+EC9md3reXqxowZw8mTJxk5ciSRkZEYjUZbR2N96sdADw4OJjw8nMTERFvayJEjyc3NZfDgwYDWkfr+++8zePBgEhMTbQsdP/3001xzzTUMHTqUsLAwh8e7/vrreemll0hJSeHQoUONnsfKlSu55JJLmnLqik6OkC5WtBFCjASellJeZN3/E4CU8u92Zd4GDkspX7SW/6eUstHxW2lpadLR+FrFueN0WTUj/r6cq4bG8vwVyefkmHv37nXo2mivVFRUMGHCBNauXYter29rcWxUVVUxbtw41qxZ0/kWaVDYcPR7EUJsllI6DGfpjsslBjhmt59lTbPnaeBmIUQWsBS431FDQog7hRCbhBCb8vJUTJG2JtjXk8uHRPPNluMUVZjaWpx2ibe3N8888wzHj7ev2bWZmZm88MILSpkr6tBanaI3AHOllLHAVOBjIUSDtqWU70gp06SUae6snq44+/xuRDwVJjPfblejJZxx0UUX0b1797YWow4JCQmMHz++rcVQtDPcUejHgTi7/Vhrmj2/B74EkFL+ChgBx05CRbsiKSaA/t381cxRhaIT4I5C3wgkCCF6CiE80To9l9QrkwlMBBBCDEBT6Mqn0gEQQnD10Fi2HyvkQE7X6hxVKDobLhW6lLIGuA/4AdiLNppltxDir0KIadZiDwN3CCG2A58DM6Wr3lZFu+GKlBg8dIIFm465LqxQKNotbvnQpZRLpZR9pZS9pZR/s6bNllIusW7vkVKOllIOllIOkVL+eDaFVrQuoX5eTBwQwTdbj1OjFpNuEosWLeKvf/0roA1LFELUGbf+yiuvIIRwGDHRHaZOnUphYWFriNosNmzYwNixY+nXrx8pKSncfvvtlJe3/lKGmzZtalakSmfMmzePpKQkkpOTSUlJYc6cOa3WdmPMnj2bZcuWAdq9d3WtqqurGTt2bJ0JYy1CStkmn6FDh0pF++H7nSdkj8e+k78cyDurx9mzZ89Zbf9cM3LkSJmXp12zv/zlLzI5OVk+++yztvxRo0bJxMREuXHjxrYSsdlkZ2fL7t27y3Xr1tnSFixYILOzs92qbzKZGt0/WyxdulSmpKTI48ePSymlrKyslO+88845ObY9PXr0sD0bjfH000/LTz75xGGeo98LsEk60atq6r8CgPH9IvD11Hf60S4bN25k0KBBVFZWUlZWRmJiIrt27WLVqlWMGzeOyy+/nF69evH444/z6aefct5555GcnOxwks+BAwfw8vKqM0lo+vTptolEhw4dIjAwsE7+H/7wB9LS0khMTOQvf/kLoM0g7devH/v37wfghhtu4N133wUgPj6e/Px8MjIy6N+/PzNnzqRv377cdNNNLFu2jNGjR5OQkMCGDRsA7S3B3hpNSkoiIyPD7fr2vPHGG8yYMYORI0fa0q6++moiIyPZsGEDI0eOJCUlhVGjRtlknzt3LtOmTeOCCy5g4sSJDfZvueUWFi1aZGvvpptuYvHixaxatYpLL73Udg633XYb48ePp1evXnVi7Dz77LP069eP888/nxtuuMGh5f33v/+dOXPmEB0dDWihE+644w4A3n33XYYNG8bgwYO56qqrbBb0zJkzufvuu0lLS6Nv37589913AGRkZDBmzBhSU1NJTU2tEz75xRdfJDk5mcGDB/P444/b2vnqq6/497//zYkTJ5gwYQITJkzggw8+qBNL/9133+Whhx6yPTP1o3w2FzWIVQGA0aDnwsRu/G93Ns9OT8LT4+z/12c//zxVe1s3fK7XgP50e+IJp/nDhg1j2rRpPPXUU1RUVHDzzTeTlJTEqlWr2L59O3v37iUkJIRevXpx++23s2HDBl599VVee+01XnnllTptrV27ltTU1DppAQEBxMXFsWvXLhYvXsx1113Hhx9+aMv/29/+RkhICGazmYkTJ7Jjxw4GDRrE66+/zsyZM3nggQc4ffq0TQHZk56ezoIFC/jggw8YNmwYn332GWvWrGHJkiU8//zzdRSlI5paf9euXcyYMcNhW/379+eXX37Bw8ODZcuW8cQTT9jC/W7ZsoUdO3YQEhLC3Llz6+yvXr2al19+menTp1NUVMS6dev46KOPWLNmTZ329+3bx8qVKykpKaFfv3784Q9/YNu2bSxcuJDt27djMplITU21RcKsL7ejdNACndVe26eeeor333+f++/Xps1kZGSwYcMGDh06xIQJE0hPTyciIoKffvoJo9HIwYMHueGGG9i0aRPff/89ixcv5rfffsPHx4dTp07VOc6sWbP417/+xcqVKwkLC6O0tJS//e1vvPTSSxgMBj788EPefvttQPvT3bhxY6P3zl2UQlfYuHRQFN9sPc7a9Hwm9I9oa3HOGrNnz2bYsGEYjcY61t+wYcOIiooCoHfv3lx44YWAtpjEypUrG7RTPxJjLddffz3z58/nhx9+YPny5XUU+pdffsk777xDTU0NJ0+eZM+ePQwaNIjJkyezYMEC7r33Xlvsl/r07NmT5GRtRm9iYiITJ05ECEFycnKdKIzOaGl9e4qKipgxYwYHDx5ECIHJdGZi2uTJkwkJCXG4P27cOO655x7y8vJYuHAhV111lcPJUZdccgleXl54eXkRERFBTk4Oa9eu5fLLL8doNGI0GrnsssuaJDNoyv6pp56isLCQ0tJSLrroIlvetddei06nIyEhgV69erFv3z569uzJfffdx7Zt29Dr9Rw4cACAZcuWceutt+Lj4wNQ53wd4efnxwUXXMB3333HgAEDMJlMtnuh1+vx9PSkpKQEf3//Jp+TPUqhK2yMSQgnwOjBt9tPnBOF3pglfTYpKCiwxUGvrKzE19cXOBPVEECn09n2dTqdw04rb29vioqKGqRfeumlPProo6SlpREQEGBLP3LkCHPmzGHjxo0EBwczc+ZMW8RFi8XC3r178fHx4fTp08TGxjZo1x35PDw8sFjOdGzbR3Rs6vklJiayefNm2wIf9vz5z39mwoQJfPPNN2RkZNSZ5FR7PZ3t33LLLXzyySfMnz+/zp+ds3OtH2XSFbVyX3DBBQ3yZs6cyaJFixg8eDBz586tE6enfnA2IQQvv/wykZGRbN++HYvFgtFodFuO+tx+++08//zz9O/fn1tvvbVOXlVVVYvarkX50BU2PD10TB7YjWV7czB14tEud911F88++yw33XQTjz3W/Jjs9SMx1uLj48OLL77Ik08+WSe9uLgYX19fAgMDycnJ4fvvv7flvfzyywwYMIDPPvuMW2+9tY7F2xTi4+PZsmULoLk+jhw50qx2AO677z4++ugjfvvtN1va119/TU5OTp3IkXPnzm1SuzNnzrS5rwYOrB/nzzmjR4/m22+/pbKyktLSUpufuz5/+tOfePTRR8nOzga0kSTvvfceACUlJURFRWEymRr4rRcsWIDFYuHQoUMcPnyYfv36UVRURFRUFDqdjo8//ti23ODkyZP58MMPbT74+i4XaBg5c/jw4Rw7dozPPvuMG264wZZeUFBAWFgYBoPB7WvhDGWhK+oweWAkC7dksTHjFKN6d77JvvPmzcNgMHDjjTdiNpsZNWoUK1asQKdrum0zduxYHn74YaSUDay766+/vkH5wYMHk5KSQv/+/YmLi2P06NEA7N+/n/fee48NGzbg7+/P2LFjee655+qsTuQuV111FfPmzSMxMZHhw4fTt2/fJrdRS2RkJPPnz+eRRx4hNzcXnU7H2LFjmTJlCn/84x+ZMWMGzz33XJMjPkZGRjJgwACmT5/epHq1/R+DBg0iMjKS5ORkAgMDG5SbOnUqOTk5TJo0yXZvbrvtNkDrVB0+fDjh4eEMHz68jsLt3r075513HsXFxbz11lsYjUbuuece2zWdMmWK7W1jypQpbNu2jbS0NDw9PZk6dSrPP/98HTnuvPNOpkyZQnR0tM1ld+2117Jt2zaCg4Nt5Vo1aqaz4S9n+6OGLbZPSitNMuHJpfKZJbvPSvudbdjirFmz5E8//dTWYnQoysrKZK9evWRhYWGT65aUlNjaGDp0qNy8eXOryDRjxgy5YMGCVmmrMS655BK5bNmyOmlXXHGF3L9/v8PyatiiokX4enlwfp8wftqbjVSTfV3yxBNPnJWJNp2VZcuWMWDAAO6//36H1rUr7rzzToYMGUJqaipXXXVVg1FG7ZXCwkL69u2Lt7c3EydOtKVXV1czffr0Fr1J2eMyHvrZQsVDb7989lsmT3yzkx8eHEu/bi3rda9PR4uHrlC0JWcjHrqiizFxgDbC5ac92WelfWX5KxSuac7vRCl0RQMiA4wkxwSy+kDrB8w0Go0UFBQopa5QNIKUkoKCgiYPZVSjXBQOGds3jLdWH6ak0oS/seXDqWqJjY0lKysLtWKVQtE4RqPR4XyExlAKXeGQMQnhvLHyEL8eKuDCxG6t1q7BYKBnz56t1p5CoTiDcrkoHJLaPRgfTz2/HMxva1EUCoWbKIWucIinh46RvUL55aByjSgUHQWl0BVOGZMQRkZBOZkFapy1QtERUApd4ZSxfbVIgr+kKytdoegIKIWucErPMF8iA7xYf7hh4CGFQtH+UApd4RQhBMN7hvLbYTVuXKHoCCiFrmiU4b1CyC2pIkP50RWKdo9S6IpGGd4zFIDfDhe0sSQKhcIVSqErGqV3uC9hfl78dkT50RWK9o5S6IpG0fzoIcqPrlB0AJRCV7hkeK8QThRVknW6oq1FUSgUjaAUusIlw+K1Fc03ZrSy28VU6bqMQqFwG6XQFS7pG+mPn5cHWzMLW6/RLR/D89GwY0HrtalQdHGUQle4RK8TDI4LZOux063X6Pr/gDTD2ldar02FooujFLrCLVLigtl7soTy6pqWN1ZZBLl7wOALObugXI2gUShaA6XQFW6R2iMIs0WyM6uo5Y3lH9S+027VvrM2Nql6caWp5TIoFJ0QtxS6EGKKEGK/ECJdCPG4kzLXCiH2CCF2CyE+a10xFW3NkLhgALa0hh/91BHtO+kqEDo4vtntqsv25DD4mR/59LejLZdDoehkuFToQgg98AZwMTAQuEEIMbBemQTgT8BoKWUi8GDri6poS0J8PekZ5svWzFbwo586DAiIGAhBPSD/gNtV/7c7Gynh/TVHWi6HQtHJcMdCPw9Il1IellJWA/OBy+uVuQN4Q0p5GkBKmdu6YiraAyndg9h6rLDlE4xOH4GAaDAYISwB8tPdrnogpwSAw3ll5JdWtUwOhaKT4Y5CjwGO2e1nWdPs6Qv0FUKsFUKsF0JMcdSQEOJOIcQmIcQmtUhwxyOlezB5JVUcL2zhBKNThyGkl7YdmgAF6WCxuFW1oLSa+FAfALYcbcVRNwpFJ6C1OkU9gARgPHAD8K4QIqh+ISnlO1LKNCllWnh4eCsdWnGuSI4JBGDX8RZ2jJ46AsHx2nZYH6ipgJITblUtKKtibN9wDHrB5tZw/ygUnQh3FPpxIM5uP9aaZk8WsERKaZJSHgEOoCl4RSeifzd/PHSCnS1R6FUlUJYLIT21/dA+2nftyJdGqKg2U2my0C3QSGJ0oLLQFYp6uKPQNwIJQoieQghP4HpgSb0yi9Csc4QQYWgumMOtJ6aiPWA06EmI9GfX8eLmN1JwSPsOTaj7XeDaj366vBqAIG9PhsQFsftEMWaLChimUNTiUqFLKWuA+4AfgL3Al1LK3UKIvwohplmL/QAUCCH2ACuBR6WUKoB2JyQ5JoBdx4ua3zFaq7hDe2vffpGg94SiY87rWCmvNgPg66UnMTqA8mozR/LLmieHQtEJ8XCnkJRyKbC0Xtpsu20J/J/1o+jEJMcE8uWmLE4WVRId5N30Bk5ZX9xqO0V1OgiMhULXCr3SpCl0b4OehAh/AHafKKJPhF/T5VAoOiFqpqiiSSRaO0ab7UcvSIfAODDY/RkExjXJQvf21JMQ6YenXsfuEy1w/ygUnQyl0BVNYmBUAHqdaP5Il4L0M+6WWgLj3LLQK6wWuo+nHoNeR79u/uw+0QqhCBSKToJS6IomYTToSYjwa56FLqVVofepmx4UB6XZUNP4RKEKq4VuNOgBSIoJYNfxYrWSkkJhRSl0RZNJigls3kiX8gIt0mKIAwsdoLj+aNi6VJi0SI8+nlrXz8DoQIoqTC2f6KRQdBKUQlc0mQFRAeSXVpFX0sSp97Yhi/Us9MBY7duF26WiWptN6l1roUcHALRsGKVC0YlQCl3RZPp300aY7M8usaUVVRXxzcFvWH50OWaL2XHF+kMWawmyWuguOkara7R2PT20x3aA1Z+/R/nRFQrAzWGLCoU9tQp9X3Yx5yeEcbjoMHf8eAe55VpMtvFx43l5/Mt46Oo9XgXpoPPQIizaE2ANDVSU1ehxa6yTiDz0AtB86b3CfNVIF4XCirLQFU0m1M+LMD8v9mWXUFpdyqwVs6ix1PDRlI/4v6H/x6pjq/hi/xcNKxakQ3BP0NdT9B5e4NfNpcvFZNYUukF35rHt182fA7klzqooFF0KpdAVzWJAlD/7s0t4Z+c7HC0+ypxxc0iNTGVm4kxGRI3g7e1vU2Wu52MvONTQ3VJLYCwUN26hm8yaD73WQgfoF+nPsVMVlFa1wtJ4CkUHRyl0RbPoF+nPgYKjfLLnE6b1nsawbsMAEEJwW9JtnK46zY8ZP56pYK7RLPSwvo4bDIxx7XKpVeg6O4Vudf8czFFWukKhFLqiWfSPCoCgFQgEs1Jm1ckbETWCaN9ofsj44Uxi4VEwV0F4f8cNBsRC0XFtrLoTTBaJQS8QoqFCP6AUukKhFLqieUSF1GAI3EJK8GQifSPr5AkhmNhjIutOrKPcVK4l5u7Vvp0p9MAYLS56hfOQuDVmCx66uo9sXLAPRoOO/dmlzT4XhaKzoBS6ollsOf1fhK6GaN2FDvPPjz4fk8XEttxtWkLePu073InLxY2RLiazrOM/B9DpBH0j/ZWFrlAAoq2mTaelpclNmzY1uV72889TtXffWZBI4S4SyY68HdTUGPDTxdEv0r9BGbO0sDV3C918o4j1i4H8/VBZDLHDHDdaVQInt0PkQPAOcVjkSH4ZBWXVpPUIrpN+KK+UwgoTQ7sHO6ynULQ3vAb0p9sTTzSrrhBis5QyzVGestAVTaa4uoRqSzVGXZAtAmJ99EKHr8GXkmqr5VxdDgYf5416eGnfjcRzkYAQDdN9PD0w1VgwqcUuFF2cDjexqLn/aorW448//5G1x/O4OvxVXl2Wwe5nLsLXq+GjtHDTv/h478dsuP4dDC/2gGG3w0V/c9yoxQLPRcCo0TDpaYdF/v3ldtYfLmDt4xfUST96II/HPtjA53eMYGTv0JaenkLRYVEWuqJJFFcXsyJzBVN7TmVAN801cjjP8apBA0MHUmOp4XDWGqipdN4hCtpCFwFR2kgXJ9RYLA186KBGuigUtSiFrmgSq4+tpspcxaW9L6V3uLZSUHqeY0XaL6QfAPuyftUSIgY03nhAbKOdojVmWWcMei0R/l4EehvYrxS6ooujFLqiSSzPXE6EdwTJYcn0CPVFrxMcynVsoXf3745Rb2Rf/i4twdmkoloCYxqdLWoyWzDoGz6yQghtolO2UuiKro1S6Aq3qaipYO3xtUzoPgGd0OHpoaNHqA/puY7HgOt1evoG92V/WZZmfRsDGj9AQAwUn9T86Q6osTQctlhL7wg/DuWpseiKro1S6Aq3WXdiHZXmSiZ2n2hL6x3euCJNCE7gQE2Ja3cLaPFcLCYoy3WYbXIwseiMHL6cLjdxqqza9XEUik6KUugKt1mRuYIAzwDSup0ZAtsnwo+MgjJbnJX69PTvTpGQFIYnuD6AbXKR447RGrM29d8Rtf78w8pKV3RhlEJXuIXJYmLVsVWMix2HQWewpfcO98NklmSeKndYr4dFe8SOBkY6zK9D7cpFTvzoNZbGLHRNoSu3i6IroxS6wi225GyhuLq4jrsFNAsdcOpH71GhdVQe9WpkUlEttQrdiYXuaOp/LTHB3nh66DjkZAilQtEVUApd4RbLM5dj1BsZFTOqTnqvcF8Ap4o09vRx9FKSYXFjIWfvYPDwdrpYtLNRLgB6naBnqK9yuSi6NEqhK1wipWRF5gpGRY/C28O7Tl6A0UBkgJdTC92Qs4sYPDhakun6QEJY46I7XrnI2Tj0WnpH+CoLXdGlUQpd4ZLdBbvJKc/hgu4XOMzv42zIoJSQs4vuhkAy3VHooHWMOnO5WCwYPJw/sr3C/Mg8VU51jeMOWoWis6MUusIlyzOXoxd6xseNd5jfO9yPQ7mlNIjcWXwCKk4T4xfDidIT7h0sMNapy6XGLDG4sNDNFknmKWWlK7omSqErXLI8czlpkWkEegU6zO8T4UdJVQ15JfUiJWbvBCAqJIHi6mLKTG4o2oAYKMkGs6lBVo3ZgocTHzpoFjo49+crFJ0dpdAVjXK46DBHio44dbdAI4o0R1Po0ZGDAdyz0gNjAAklJxtk1S5B51QOWwetA/dPSTZ8NA1eGQSbPnAth0LRAVEKXdEoKzJXADSq0OPDtCGJGQX1FPrxrRDSm6igXgCcLGuopBvQyNBFR0vQ2eNvNBDh79Uw+qOU8NXv4dgGbSTNdw/BjgWuZVEoOhhuKXQhxBQhxH4hRLoQ4vFGyl0lhJBCCIeraSg6HsuPLicpNIluvt2clokK9MZTr2uo0E9sgZhUov2itV13LPSA2slFjhS683HotTgMRZCxBo6ugQufhduXQ9wI+O5BLW6MQtGJcKnQhRB64A3gYmAgcIMQYqCDcv7AA8BvrS2kom3ILstmV8EuJvaY2Gg5vU7QPdSHjHw7hV58UnObRKcS5h2GQWfgRJm7LhcchtE1WZyPQ6+lV7hvQwt9//fgYYSUm0HvAVe8BeZqWPGca3kUig6EOxb6eUC6lPKwlLIamA9c7qDcs8CLQGUryqdoQ1YeWwk07m6pJT7Uh6MFdtP/T2zRvmNS0Qkd3Xy7cbLUDYvYyx+8Ap1b6I2McgHoGeZLUYWJwnK7IF1H12hrmRqsY+hDesLwu2Hbp9o6pgpFJ8EdhR4D2M/0yLKm2RBCpAJxUsr/NtaQEOJOIcQmIcSmvLy8JgurOLcsz1xOfEA8vQJ7uSwbH+pLRkEZltp1PY9vAaGHboMA6ObbjZzyHPcOHBjTwEKXUlrD5zb+yHYP0fz5tj+XyiJttE2P0XULjn1E86f/+GfNx65QdAJa3CkqhNAB/wIedlVWSvmOlDJNSpkWHh7e0kMrziJFVUVsyt7UIHaLM3qE+VJpspBbO3TxxBYtZK6npmDDvcPJK3fzTzygoUKvsf5RNDYOHSA+TBvpYvPnZ/4G0gI96oYswBgI4x6DI6shfZl7cikU7Rx3FPpxIM5uP9aaVos/kASsEkJkACOAJapjtGOzOms1Zml2W6HHh2qK+0h+mWbxntgK0Sm2/HDvcPIq8hpOPnJEYEwDl0uNWavXZAv96FrQGTSXS33SboOQXvDTbLCYXculULRzGi7V3pCNQIIQoieaIr8euLE2U0pZBITV7gshVgGPSCk3ta6oinPJ8qPLifCJIDEs0a3y8aGaZXy0oIyRwcVQcRpiUm354T7hVJmrKDGVEODpYuWiwFgoLwBThc3vbbKuYtTYOHQAo0FPtwBjXYUek2p7U6iDhydM/AssmKH501NvcX2iUkL+Ac2NU5Slda7q9OATBr7h2sfP+u3p67o9haIVcanQpZQ1Qoj7gB8APfCBlHK3EOKvwCYp5ZKzLaTi3FJRU8G6E+uY3mc6OuGeVy46SBu6eKSgDLx3WxPtFLq35mLLK89zrdBtQxdPQGhvwM5Cd+FyAegR6sPRgjKoLtPeFEbd77zwwMshbrjmS+99wZlx8PUpPwUb34MtH0ORm3FpDL7gHaQpfJ2H1qcAmgsIqX1LC0jObNvSpYO0euUUHZcpL8DQGa3erDsWOlLKpcDSemmznZQd33KxFG3JuuPWpeZcDFe0R68TxIV4czS/HORvmjKLTLLlh/tYFXpFHr2DejfemP3QRZtC1yx0Vy4X0N4Wlu/L1SYSWWqgx/nOCwsB09+Et8fC59fDLUvAJ+RM/ukMWP8mbJkHpnLoPRHGPqy5cIJ6aMMhLSYoy9eWzivLh7I87VOap3XKWmq0jzQDQjum0Gkf7LYFDtKE47Ra2RUdE3eWZGwGbil0RddieeZyAjwDGBo5tEn1ake6ULYeYtO0Md9W7C10l9QuRWfnR682u+dyAege6kN+aRXVh7fgKXQQd17jFUJ7w7Ufwec3wJujYdhtYPCBw6vh4I+ahZ18rWbpRzaYgqGdZ1Cc9lEo2hCl0BV1MFlMrMpaxfjY8XWWmnOH+DBfth06hvTYhRj7aJ08ewvdJQ7WFj3jcnHPQgcwHf4Fz6jBYHTh4gHoMwlu+x98//iZCUcBMdrwxqG3nnlrUCjaMUqhK+qwMXsjJdUlTOoxqcl140N9GGA+gNBbNL+0Hb4GX3w8fNyz0A1GrZPRbqGLmtpO0UbiodfSI9QHL6ox5myF4Xe6fwIxQ+H2n7QOXYsZfEKVW0PRoVAKXVGH5UeX4+3hzajoUa4L1yM+zJc03X6k0CEcDBOM8Ilwz0KHBkMXTWb3xqGDptAHi0PoLdUNJxS5g3dw0+soFO0ApdAVNswWM8szlzMmZgxGD2OT6/cI8UWI/RT69yXYgZsjzDusCZOLYuHUYduuu+PQQYu6OMF4AIsU6LqPcO94CkUnQIXPVdjYnredgsqCZrlbAKICPEjRpZPhnewwP9wn3H0LPShOc7lYJyLVjkN3FW2xltEe+8g09Kw7YkWh6OQoha6wsSxzGQadgTExY5pV35C7C19RxQ59f4f54d7h5Ffku9dYcDxUl2rDADljoRvc6BSlpor+NXv5zeLepCiForOgFLoC0IJfLT+6nFHRo/Dz9GteI0d+BuDnqn4Os4ONwVTUVFBRU+G6reCe2vfpDMB+HLobFnrWJjxlNcsrE6g0qSn9iq6DUugKAPae2suJshNux25xyJGfyfaKZ3uRt8PsEKPm/jhdedp1WyG1Cv0IoC0/B+6NQydjDRLBenN/sk678eehUHQSlEJXALDs6DL0Qs+EuAnNa6CmGjJ/JSfkPPJLq6iobmgZB3tpo0fcUuhBPQABpzSFbrPQ3XG5ZPxCRchAivEj85RaMFrRdVAKXYGUkp+O/kRaZBpBxqDmNXJ8E5jKqYrTptlnnS5vUCTYqCn0U5WnXLdnMEJA9BkL3TbKxYWFbqqEYxsQPTU56iy6oVB0cpRCV7Dv1D4yijO4qOdFzW/kyM+AwLPPOACOOVDoocZQwE2FDpofvdZCt0VbdPHIZm0EcxXGhHH4euqVQld0KZRCV/D9ke/xEB5M7j65+Y0cXg1Rg4mO0haTznSgSGstdLdcLqCNdDld63JxM9rioeWg80DEj6F7qC+Zp5RCV3QdlELv4likhf9l/I+R0SOb726pKtUs455jCffzwmjQccxBZ6SvwReDzsCpKjct9JB4KM2B6jJMZjct9PRlEDcCjAH0CPE5s3KRQtEFUAq9i7M9bzsny05ycc+Lm9/IkdVaCNk+kxBCEBfswzEHlrEQgmBjcBMs9DNDF2uXoGvUh16Soy080Udb1LpHmA9ZpyowW1TscEXXQCn0Ls7Sw0vx0ntxQfcLmt/IwR/B0x+6jwQgLsTHqasj1Bjqvg+9dujiqSPujXI5tEL77qPNdO0R4ku12UJ2caV7x1MoOjhKoXdhaiw1/Hj0R8bFjsPX0Mzl0qSEgz9B7/Hakm5o63pmna5wuH5okyz0kF7a96nDVJvdGIeevgx8IyBSCz3QI7R2fVHldlF0DZRC78JsOLmBU5WnmNpzavMbydmtRUVMuNCWFBvsTWlVDYXlpgbFg43B7lvo3sHa2pz5+12vWGQxaxZ6n4lgteJrF4x21EHrikqT2eFYeoWiPaOiLXZh/nvkv/gZ/Dg/tpEl2lxx8Eftu8+ZETJxVkV67HQ5wb6edYoHezXBQgcI6wd5B6gJcGGhZ22EilM2dwto65wa9IKjTRjpYrFIXvpxP+//coQai4UpSd34y2WJRAY0PfqkQnGuURZ6F6XMVMZPR3/ioviL8NJ7Nb+hgz9Ct0EQEGVLslnGDhRpiDGE8ppyKmvc9GuH94P8/ZhqNGvZaXCufd+BzgAJZ/5Y9DpBbLBPkyz0N1cf4s1Vh5ia3I3bRvdk5b48pr76C+sPF7jdhkLRViiF3kX5MeNHKmoqmN5nevMbKc2FzPXQr67Lxmahn2o4dLFJ8VxAU+iVRXhV5qMToHM0Dl1K2Psd9BoHxsA6Wd1DfDjq5vT/3OJKXltxkIuTuvHydUN46tKBfHv/aIJ8DPzu/d/4cuMx140oFG2IUuhdlEXpi4gPiGdw+ODmN7LvO0DCwGl1kv28PAj2MTicLWqb/u/uWPSwvgAElh127j/P3atNQOp/SYOsHqE+HC0od9hBW5+3Vh/GZJY8fnF/hHXpuT4R/nx9z2hG9Arljwt38Pele9UwSEW7RfnQuyBHi4+yJXcLD6Y+aFNczWLPEgjpDREDG2R1D3E8Fr1WoRdWFrp3jHAttnpw+REMunDHZfZ9Bwjo11Chdw/xoaRS66Ct78+3p7rGwtdbs7g4qRs9QuuO+An0NvDhzGE88+0e3v75MIfzy3jxqkGENNKexSI5drqc9NxSTpVVU1huotpswUMn0OsEBr0OTw8dXh7at6deh5dBb/3WOXUtSZz/mTT2n+Usq7E/Oud1nB/HWa3myNZYvdaX+9zSK9z3rPTLKIXeBVmcvhid0HFZ78ua30j5Kcj4BUbd73Ah5dgQH/acKG6Qbou4WOWmy8W/G3gFEFp+BA+9k+Xk9n0HscPAP7JBVq1yPnqqYQetPSv351JYbuKqobEO8z30Op6dnkSfCD/++t0exv5jJdNTohnRK5QQX08qqs0cyS/jYE4p+3JKOJhTQrkaJaNwwnPTk7h5RI9Wb1cp9C6G2WJmyaEljI4eTYRPRPMb2v89WGpgwDSH2bHB3vy0OweLRdbxezc5nosQENaX0KIMxyNcCg7Bye1w4XMOq9uPRR8SF+T0MEt3niTU15MxfcIaFWfGqHhG9Q7ltRXpLNx8nE/WZ9bJD/X1pG+kP9cNi6N/N38SIv0J9/MiwNuAl4cOs0VSY5HUmC1Umy1U11ioqqn9Ntu2TWaJs3enxl6qnOUJp61Bc7Iae7NrltyNCOH8nBqhOdfhHNIrvJnzPlygFHoXY3XWanLKc3j8vMdb1tDubyCwO0SnOMyOC/ah2mwhp6SSqMAzC174e/qjF/qmDV0M709EzlLHs0R3LgAEJF3lsKo7Y9HNFsnPB/KY0D/CrUWoEyL9+fcNKVSaNKu8sNyEt6eeuGBvQv1aMGJIoWghSqF3Mebvm0+ETwTj48Y3v5HSXG0Sz+hZTs2n2pEuWacr6ih0ndAR6BXovssFIHIg/ts+IcJYWDddSk2hx5+vxU53gNGgJzLAq9Gx6DuyCjldbmJcXyc+eicYDXoGRAU0qY5CcTZRo1y6EBlFGfx68leu6XsNHroW/Jfv/AqkGQZd77RIbLCmxB12jHoFu98pChA1BIBEcaRu+sltUJAOydc0Wr1HiG+jFvqq/XnoBIxNaJpCVyjaG0qhdyG+2P8FHjoPru57dcsa2jEfogZDRH+nRWKCahV6w7HoTZr+DxA1CAuCAfJw3fSdX2mTiQY69uPX0j208bHoqw7kMTguqNFOU4WiI6AUeheh3FTO4vTFTO4+mTDvxjv+GiV3n9YJ2Yh1DmdcHc6WoiusKnT/mF7+5HjEkmCxU+g11bDjC+h7kRbzpRF6hPiQU1xFpanhqJOC0ip2ZBUyvm8LOogVinaCWwpdCDFFCLFfCJEuhGjQmyaE+D8hxB4hxA4hxHIhROuPx1G0iP8e+S8lphKu639dyxra9ikIPSS7tvJjg30cTy5qajwX4JAhgX41+88MJj7wPZTlQeotLuv2CNNGFDgKRbAmPR8pYVw/5W5RdHxcKnQhhB54A7gYGAjcIISoP5NkK5AmpRwEfAX8o7UFVTQfs8XMvN3zGBAygNSI1OY3VFOlKfR+F4Ofa4s2LtjbocslyBhEUXURZov747R3GxIJsZzShikCbP4I/KPrBONyRg9rB21GfkO3y8p9uYT6ejIoJrBBnkLR0XDHQj8PSJdSHpZSVgPzgcvtC0gpV0opa82f9YDj2RmKNmHlsZVkFGdwW9JtLZsZuvdbKC+AtNvcKh4X4kN2caUt9G0tIcYQLNJCSXWJ24feptdinHNkFZw+qo2ySbkZdHqXdeOtFvrB3NI66WaLZPWBPMb1DXccI0ah6GC4o9BjAPuoRFnWNGf8HvjeUYYQ4k4hxCYhxKa8vDz3pVQ0GyklH+z6gFi/WCb1cG3NNsqmD7SFm3tNcKt4bLA3ZovkZFHdyIpBXkFAE+K5AEcs3ThpiNM6Qjd9oCWm/s6tuoHeBnqG+bL9WGGd9NrhiuP7K/+5onPQqp2iQoibgTTgJUf5Usp3pJRpUsq08HDlszwXbMrZxM78ncxMnNmyoYq5++DoWhh6q20BCVfEBddGXazru25yPBfAZJGsD5wKmb/C2le0iURB3d2uPyQuiK3HCuvEAFm5L9c6XLEFncQKRTvCnV/mcSDObj/WmlYHIcQk4ElgmpSyqnXEU7SUD3Z9QIgxhMv7XO66cGOs/w94GDU3h5vYTy6yxxbPpQkdo9VmC7+GXqkF4OpxPlz0vNt1AdLig8krqeJQnuZ2kVLy7Y6TnNczhCAfNVxR0Tlwx2TbCCQIIXqiKfLrgRvtCwghUoC3gSlSytxWl1LRLHbk7WDN8TU8kPoARo8WRHYrzYXt82HIjeDrvjXbLdCITtBgpIstnksTZotW11gQBh+4+jO369gzvp/mVlmxL5c+Ef5sPVbIkfwy/jC+d7PaUyjaIy4tdCllDXAf8AOwF/hSSrlbCPFXIUTtjI6XAD9ggRBimxBiyVmTWOE2r299nWCvYG7sf6Prwo2x4R0wV8PI+5pUzaDXERXo3cDlUutDb4qFbjJLDB7N77iMCfImOSaQhZuPI6Xko3UZeBv0XJzUrdltKhTtDbecqlLKpcDSemmz7bZb2NumaG02Zm/k15O/8kjaI/gYfJrfUHUZbHxPWzwirE+Tq8eFeHOsnsvF6GHE28O7yRa6p971iJbGmDEqnkcWbOf/vtzOku0nuGtsb/yNhha1qVC0J9RM0U6IlJLXt75OuHc41/Vr4USiDe9AxWkY/WCzqscG+zicLRpiDGlSp2h1jQVPj5Y9rtOHRDOhXzjfbD3OoNggZk1s+h+UQtGeUdEWOyErj61kS+4Wnhz+ZMt855XFsPZVSLgQ4oY1q4m44DPT7o2GMxZ2kFeQ28MWpZRUmy14OoqH3gQ89DremzGM9NxSeoX7YnAjVK5C0ZFQCr2TUW2uZs6mOfQO7N3yIFzr39Ss8wlPNLuJuBAtSNfxwgp6h/vZ0oON7k//N5m1oYbuWOi55bl8vOdjykxl3ND/BhKCE+rk63WCft383RVfoehQKIXeyfhs72ccKznG25Pebtm484rT8Osb0P9Sp4tYuENs8Jmhi3UUulcwhwsPO6tWB5N1pqkrhX6s+Bi3/Xgb+eX5GPQGlh5ZykdTPqJfSL9mSq9QdCzUO2cnIr8in7d3vM3Y2LGMihnVssZWvQjVJS2yzuGMhe5ocpG7naLVNZpCb8xFYrKYeOTnR6ioqeDzSz/n2+nfYtQbeXrd040uKKxQdCaUQu9EvLDhBarN1Tya9mjLGsrdq3WGDp0JkYktairS34inXtdgLHq4dzgVNRVuxXOpdsNC/2zvZ+wp2MPTI5+mf0h/In0jmZU6i10Fu9iYvbFF56BQdBSUQu8krD62mh8yfuDOQXcSHxjf/IakhO8fAy8/mPBUi+XS6QQxwd4NZot289PGf58sO+myDVcWepmpjPd2vsfo6NF14tVM7TmVIK8gPtvXvMlICkVHQyn0TkCZqYznfnuOPkF9uC3JvUiITtmzGI6shglPgm9oq8gXG+xNVj2XS5RvFADZZdku69da6F5OLPTP9n5GYVUh96XUnfhk9DByZcKVrDy2kpOlrv84FIqOjlLonYAXNrxAbnkuT496GoO+BRNlygpg6SPQbRCk/b7V5NMWuqhroUf7aos6u6Noay10TwcWusliYv6++YyOHk1SWFKD/Gv7XQvAggMLmiy3QtHRUAq9g/NDxg8sSl/E7cm3Mzh8cMsaW/oIVBTCFW+BvvUGQMWFeHOqrJqyqhpbWqh3KB46D7dcLrWjXBy5XFYdW0VuRS439L/BYd0YvxjGxY5j4cGFVJurm3cCCkUHQSn0Dkx2WTZ//fWvDAobxN2D725ZY7sXwe6vYdxjLe4IrY/90MVadEJHN59uTfKhO+oU/WLfF0T7RnN+zPlO61/f/3pOVZ7ih4wfmiq6QtGhUAq9g1Jtrub/Vv0fNZYa/j7m7xh0LXC1nDoCS2ZBdCqc/2CryVhLXLDjoYtRflFu+dArTZpCt59pCnC0+Ci/Zf/GNf2uQd/IykUjokYQHxDPx3s+VkMYFZ0apdA7IFJK/vbb39iZv5Pnz3+e7gHuL/TQAFMlLJgBArjmQ2iJD94JZ+KiN+wYPV7aILR+A8qrNVeNj2ddpb308FIEgst6XdZofZ3QcVvSbew9tZdfjv/SFNEVig6FUugdkPn75/P1wa+5c9CdTOwxsfkNSQnfPwont8P0t7Tl5c4Cob6eeBv0DTpGu/t3J6c8h3JTw+Bd9lSYtMWk7S10KSX/PfJfzut2HpG+kS5luLT3pUT7RvPW9reabKVrsWSqlXWvaPeoqf8djJ+O/sTff/s74+PGc++Qe1vW2NpXYMs8GPMI9J/aKvI5QghBbHDDuOi9gnoBcKT4CImhzv32FdWaQre30HcX7OZo8VG3h2kadAbuHnw3s9fNZvGhxUzvM73R8vtO7WNx+mLWn1xPVkkWlWZtXVR/gz9RflFE+0bTzbcb4T7hhHmHEWoMxdvDG71Obwu5IKXEIi1YpAWJ1Pax7lvzJHZl7PNry1u3uwJd6Q8zOSy5ZfNFnKAUegdiY/ZGHvv5MQaHD+YfY/+BTrTgBWvXQlj2tLY254QnW01GZ8SH+ZJRUFYnrVegptAPFx5uVKGXO1Do/z38Xww6Q5MWvr68z+V8ffBr/rXpX5wfcz5h3g1XXzpWfIzXtr3G90e+x0vvRVpkGqOjRxPoFYjJYqKwqpCTpSc5UXaCzbmb3ZrpqlDU588j/qwUeldmW+427l9xP939u/P6xNfx9vBufmP7lsLXd0L3kXD5f9xe9Lkl9Ar3ZfX+PGrMFjysww+7+3dHL/QcKTrSaN1al4u3VaGbLWb+l/E/xsaOJcAzwG0ZdELH7JGzuWnpTdy//H7enPQmQcYgQIuD886Od1iwfwEeOg/uSL6DmUkzXbZfZa6ioKKA/Ip8qsxV1FhqqLHUIIRAh077FjoEwrZdu2/btpat3a7Ns9/uKghaFiK5o1C7DGNroxR6B2Bj9kbuXX4vET4RvDX5LQK9Apvf2IEf4MtbIGow3PgFGFoQL70J9A73o9psIet0BfFhvgAY9Abi/OM4XNR41MXy6hp04szEou1528mvyOei+IuaLEdCcAIvjnmRh1c/zJVLrmRyj8mcrjzN8szlmKWZKxOu5O7BdxPhE+FWe156L6L9oon2i26yLApFa6MUejtn9bHVPLz6YWL9Ynn3wncJ9wlvfmPb58Pi+6BbEtz8NRhb8MfQRGpD5x7KK7UpdIDeQb05ePpgo3XLqsz4enoghGa9LctchkFnYGzs2GbJMqH7BOZdPI9/b/k336R/g5/Bj8v7XM7MxJktGzGkULQxSqG3U6SUzNszj39u+if9Q/rz1uS3CDGGNLcx+GUOrHgOeo6Faz8G76BWldcVvcM1JX44r4yJA86kJ4UlsTxzOYWVhTb3R31KKmsI8NaGU0opWX50OaOiR+Fr8HVY3h2SwpJ458J3ml1foWiPdB3nXAeisqaSp399mjmb5jCx+0TmTpnbfGVeVQILb9eU+aDr4KaF51yZAwT5eBLq68mhvNI66bXhCnbk73Bat7jShL9Rsz0OnD7AibITTOzeguGaCkUnRVno7Yz00+k8+vOjpBemc0fyHdyXcl/zO8VydsOXM+DUIbjgzzDmYRBt1+nUO9yvgUJPDE1EJ3TsyNvh1IVSUmkiwKhZ6FtytwAwPGr42RVWoeiAKIXeTqix1PDp3k95fevr+Bh8eHPSm43GJ2kUs0kbY776H+AdDLcsgZ5jWlXe5tA7wpf/7cpGSmnzh/sYfOgb3JetuVud1iuuqCEqUOu83ZqzlUifSFv4XYVCcQblcmkH7CnYw43/vZE5m+ZwXtR5fHXZV81X5kd/hXcnaC6W/pfA3WvbhTIHGBAVwOlyEyeLKuukj4weyZacLZRWlzqsV1RhItDbgJSSzbmbSY1Itf0hKBSKMyiF3oacLD3Jk2ue5Prvrie3PJc54+bw+gWvN28kS8Eh+OJm+HCKFtf8uk/gmrng14JRMa1MYrQ2qmbX8aI66eNjx1Mja1h7Ym2DOlJK8kqrCPP34mTZSXLLc0mJbP6i1QpFZ0a5XNqAE6Un+HjPx3y5/0sAZiTO4I5BdzRpkoyN7J2w9lXY9TV4GLVl40beC54+rSx1yxkYFYBOaAr9wsRutvRB4YMI9Apk+dHlDcaWl1TVUF1jIczP0+Y/T41IPadyKxQdBaXQzxFSSnbm7+STPZ/w49EfEQgu7X0p9w65l26+3Vw3YE9NNRz4HjbPhUMrwNMPRt4DI+8Hf9eBqtoKb089fSL82FnPQvfQeTC151S+OvAVpypP1RnRk19SBUCYnxdbc7biZ/CjT1Cfcyq3QtFRUAr9LJNfkc+3h75lcfpiDhUdwtfgy+8G/o6bBtzUNEVuscDxzdoiFDu+gPIC8I+CC56CYbdrnZ8dgMGxQfy0NwezRaLXnfGDX9v3Wj7f9zkLDyzkjkF32NJrF8WICfLm451bGBwxuNHY5wpFV0Yp9LPAkaIjrDq2ilXHVrEtbxsWaWFw+GBmj5zNxfEX4+fp515DlUVwdB3s/x4O/A9Kc0Bn0CIjpvwOel8AHUy5nZ8QxoLNWew8XsSQuCBbep/gPoyNHcuHuz7kqr5X2az0TGuExgC/KtIL07m458VtIbZC0SFQCr2FSCnJKs1ic85mNudsZlP2JrJKswAYEDKAOwfdydSeU+kZ2NNVQ1B4VItNnrkejq7V/OPSorlUEiZDv0sgYVKHscYdcX6fMISAnw/k1VHoAA8P1eKr/G3935gzbg5CCPZnl+Dn5cGhEs1/Pip6VBtIrVB0DJRCbwImi4ljJcfYf2o/+07ts30XVBYAEOQVRGpEKrck3sL42PFE+TkYK20xQ/FxOHVY++QdgOwdkL0Lqqy+ZQ8jxA6DsX+E+NEQNxw8vM7hmZ49Qv28SI4J5Kc9OcyamFAnr1dQL2alzuLlzS/z8paXeSj1IbZkniYpJoBlmV8Q7BXMwNCBbSS5QtH+cUuhCyGmAK8CeuA9KeUL9fK9gHnAUKAAuE5KmdG6op59KmoqyC/PJ68ij7yKPLLLsjlWcoxjJcfILM7kZNlJzFIL5eqh86BPUB/OjzmfpLAk0iJS6OUViq6qGEpz4ehvmouk5CSU5EBpNhQe06xw+9XnDT4QmQTJV0O35DOfTqLAHXFlSgxPf7uHzUdPM7RH3beNWxNv5UTpCT7c9SFbsnexryiZy3uHsixzBbcn396lQskqFE1FuFolRAihBw4Ak4EsYCNwg5Ryj12Ze4BBUsq7hRDXA1dIKa9rrN20tDS5adOmlsqPNJuprCmjvLqE8upSyqtLqDCVU1ZdQrmplHJTOeWmMsprKigzlVFRU055TYX1U0lZTQWnTMXkVxVRYq5o0L6/zpMeel/idN7E6bzoIT3oVyPpVV2FobIYKgs1X3dVsWMBdR7gG6GNPgmMhZBedT/+0eckHnl7oqTSxAX/XE2A0YNXr09hQFRAnQ5SU42Zt7d+xru7X8ciNB9678DefHTxRy0LHaxQdAKEEJullGkO89xQ6COBp6WUF1n3/wQgpfy7XZkfrGV+FUJ4ANlAuGyk8eYq9K//dx8fZi2nXAjKdYJyIbC4OWtQJyU+UuJjseBjkfhI7TvYYiG8xky42UyYWfsOrzETaTYTaLGA0GuWtMEIHt5gDNBCzxqDrN/Wj7d1v1aB+3UDn9Aup7DdYf3hAu6Yt4mSSi3Wub9Rmwkq0VYoMlskBg8Td14oSO3hx8jokfgY2t/YeoXiXNOYQnfH5RIDHLPbzwLqR0aylZFS1gghioBQIL+eIHcCdwJ07968uNPBYQPoX5SOj86Aj84Tb50BX70XPjpPfPRe+Oi98PUw4qPzwtvDiI+HNz56I74GH7x0ngi9QRsZovPQFLXO+tF7gsFbU9gGo6bAPYxamt7QLFkVzhnRK5TVj05g2d4cjp0qp7jCZJvO7+flQWywNxcMiCDC/9wswKFQdAbOaaeolPId4B3QLPTmtDEh7V4mpLVwcWRFuyDE15Nr0+LaWgyFotPgji/gOGD/q4u1pjksY3W5BKJ1jioUCoXiHOGOQt8IJAghegohPIHrgSX1yiwBZli3rwZWNOY/VygUCkXr49LlYvWJ3wf8gDZs8QMp5W4hxF+BTVLKJcD7wMdCiHTgFJrSVygUCsU5xC0fupRyKbC0Xtpsu+1K4JrWFU2hUCgUTUGNp1MoFIpOglLoCoVC0UlQCl2hUCg6CUqhKxQKRSfB5dT/s3ZgIfKAo82sHka9WahdAHXOXQN1zl2DlpxzDymlw8WC20yhtwQhxCZnsQw6K+qcuwbqnLsGZ+uclctFoVAoOglKoSsUCkUnoaMq9HfaWoA2QJ1z10Cdc9fgrJxzh/ShKxQKhaIhHdVCVygUCkU9lEJXKBSKTkKHU+hCiClCiP1CiHQhxONtLU9rIYSIE0KsFELsEULsFkI8YE0PEUL8JIQ4aP0OtqYLIcS/rddhhxAitW3PoHkIIfRCiK1CiO+s+z2FEL9Zz+sLa8hmhBBe1v10a358mwreTIQQQUKIr4QQ+4QQe4UQI7vAPX7I+kzvEkJ8LoQwdsb7LIT4QAiRK4TYZZfW5HsrhJhhLX9QCDHD0bGc0aEUunXB6jeAi4GBwA1CiIFtK1WrUQM8LKUcCIwA7rWe2+PAcillArDcug/aNUiwfu4E3jz3IrcKDwB77fZfBF6WUvYBTgO/t6b/HjhtTX/ZWq4j8irwPyllf2Aw2rl32nsshIgBZgFpUsoktBDc19M57/NcYEq9tCbdWyFECPAXtGU+zwP+Uvsn4BZSyg7zAUYCP9jt/wn4U1vLdZbOdTEwGdgPRFnTooD91u23gRvsytvKdZQP2upXy4ELgO8AgTZ7zqP+/UaLxz/Suu1hLSfa+hyaeL6BwJH6cnfye1y73nCI9b59B1zUWe8zEA/sau69BW4A3rZLr1PO1adDWeg4XrA6po1kOWtYXzNTgN+ASCnlSWtWNhBp3e4M1+IV4I+AxbofChRKKWus+/bnVGchcqB2IfKORE8gD/jQ6mZ6TwjhSye+x1LK48AcIBM4iXbfNtO577M9Tb23LbrnHU2hd3qEEH7AQuBBKWWxfZ7U/rI7xThTIcSlQK6UcnNby3IO8QBSgTellClAGWdewYHOdY8BrO6Cy9H+zKIBXxq6JboE5+LedjSF7s6C1R0WIYQBTZl/KqX82pqcI4SIsuZHAbnW9I5+LUYD04QQGcB8NLfLq0CQdaFxqHtOnWEh8iwgS0r5m3X/KzQF31nvMcAk4IiUMk9KaQK+Rrv3nfk+29PUe9uie97RFLo7C1Z3SIQQAm1t1r1Syn/ZZdkvwD0Dzbdem36Ltbd8BFBk92rX7pFS/klKGSuljEe7jyuklDcBK9EWGoeG59uhFyKXUmYDx4QQ/axJE4E9dNJ7bCUTGCGE8LE+47Xn3Gnvcz2aem9/AC4UQgRb324utKa5R1t3IjSj02EqcAA4BDzZ1vK04nmdj/Y6tgPYZv1MRfMfLgcOAsuAEGt5gTbi5xCwE20UQZufRzPPfTzwnXW7F7ABSAcWAF7WdKN1P92a36ut5W7muQ4BNlnv8yIguLPfY+AZYB+wC/gY8OqM9xn4HK2fwIT2Nvb75txb4Dbr+acDtzZFBjX1X6FQKDoJHc3lolAoFAonKIWuUCgUnQSl0BUKhaKToBS6QqFQdBKUQlcoFIpOglLoCoVC0UlQCl2hUCg6Cf8PGhLhdkM4kc4AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.xei = 0\n",
+    "s.d = 2*s.d_s\n",
+    "s.run(1000, 1)\n",
+    "dno.plot_system(s, ['y', 'xc', 'w','xm'], scales = {'y':s.l, 'w':20*s.l, 'xc':2*s.xm, 'xm':2*s.xm})\n",
+    "plt.title('Egalitarian society: Oscillatory Approach to Equilibrium');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.xei = 0\n",
+    "s.d = 4*s.d_s\n",
+    "s.run(1000, 1)\n",
+    "dno.plot_system(s, ['y', 'xc', 'w','xm'], scales = {'y':s.l, 'w':20*s.l, 'xc':2*s.xm, 'xm':2*s.xm})\n",
+    "plt.title('Egalitarian society: Cycles of Prosperity, Overshoot, Collapse, and Revival');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.xei = 25\n",
+    "s.k = 1.0\n",
+    "s.d = s.d_ss\n",
+    "s.run(1000, 1)\n",
+    "dno.plot_system(s, ['y', 'xc', 'w','xe','xm'], scales = {'y':s.l, 'w':4*s.l, 'xc':s.xm, 'xm':s.xm, 'xe':s.xm})\n",
+    "plt.title('Equitable Society: Soft Landing to Optimal Equilibrium');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"500px\"\n",
+       "            height=\"500px\"\n",
+       "            src=\"handy.html\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x7fbf500c05e0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dno.show_pyvis(s, quotient=False,notebook=True).show('handy.html')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.07.progressive.ipynb b/12.07.progressive.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..70889cfb0ee224f7b44da7ee41904bbbe9cb0d89
--- /dev/null
+++ b/12.07.progressive.ipynb
@@ -0,0 +1,249 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import importlib\n",
+    "import numpy as np\n",
+    "import networkx as nx\n",
+    "import ast\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pydynamo as dno"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Birth rate dynamics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def comb_neg(a, b):\n",
+    "    \"\"\"\n",
+    "    Combinaison of two effects,\n",
+    "    where the negative constraint is leading.\n",
+    "    \n",
+    "    If both a and b have the same sign, their effects combine.\n",
+    "    Otherwise, only the negative term has an effect.\n",
+    "    \"\"\"\n",
+    "    return (  (a - 1 if (a < 1 or b > 1) else 0)\n",
+    "            + (b - 1 if (b < 1 or a > 1) else 0))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = dno.parse_system.system_from_file('custom/birth_rate.py')\n",
+    "s.comb_neg = comb_neg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# import itertools\n",
+    "# ', '.join(f'({p}, {d})' for p, d in itertools.combinations_with_replacement((0.8, 1, 1.2), 2))\n",
+    "for prodi, d_br, label in ((0.8, 0.8, '- and -'), \n",
+    "                           (0.8, 1, '- and (+ or 0)'), \n",
+    "                           (1, 1, '0 and (+ or 0)'),\n",
+    "                           (1.2, 1.2, '+ and +')):\n",
+    "    s.prodi = prodi\n",
+    "    s.d_br = d_br\n",
+    "    s.run(500, 0.01)\n",
+    "    plt.plot(s.br, label=label)\n",
+    "    plt.title('Birth rate depending on desired birth rate and output\\n Param values: 1 ±0.2')\n",
+    "plt.legend(loc='right');\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Resource and production dynamics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def comb_neg_a(a, b, m=1):\n",
+    "    \"\"\"\n",
+    "    Combinaison of two effect, \n",
+    "    where the negative constraint is leading.\n",
+    "    \n",
+    "    If both a and b have the same sign, their effects combine.\n",
+    "    Otherwise, only the negative term has an effect.\n",
+    "    \"\"\"\n",
+    "    return (  (a - m if (a < m) else 0)\n",
+    "            + (b - m if (b < m or a > m) else 0))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = dno.parse_system.system_from_file('custom/prod.py')\n",
+    "s.prepare()\n",
+    "s.comb_neg_a = comb_neg_a"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.ri = 6\n",
+    "s.n_ra_prod = 1\n",
+    "s.d_prod_pc = 3\n",
+    "s.run(10000, 0.001)\n",
+    "plt.plot(s.r, label='Resources')\n",
+    "plt.plot(s.prod, label='Production')\n",
+    "plt.plot(s.d_prod_pc*s.pop, label='Desired production')\n",
+    "plt.title('resource and production dynamics, for fixed pop')\n",
+    "plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Pop and prod dynamics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = dno.parse_system.system_from_file('custom/pop_prod.py')\n",
+    "s.prepare()\n",
+    "s.comb_neg = comb_neg\n",
+    "s.comb_neg_a = comb_neg_a"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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3b1/FWB6pqakVy9c0hOqePXv45ZdfcHZ2pkePHjz66KP4+/vX73fUREmLug7s7BSjevnw+YOD+PKhwQwM9mBB3BFiXlnP01/tJSUrz9olClEn5cOcRkdHExAQUDEedf/+/QkKCgLMw5jeddddwKXDmMbHx1dMDwsLIywsrNbXW79+PQ899BBg7h9v27bmHfTVvTbAqFGjaNu2LS4uLvTu3Ztjx45dwW+gaZIWdT317dKeRTOiScnK451NR/lydxqf/Xyc0b19eGBYV6IC2lu7RNEU1LHl29DK+6grc3Nzu6r1Wl7X1HJ404bk7Hzx26u9vf016U+3FdKivkLBXq35x82hbHlqJH8cfh3bkrO5+T9buXXhNn46kIlJTlEXTVR1w5jGxsbyySefALBv3z4SExMrnuPj48PBgwcxmUysWLGiYvqoUaN4++23AfNVZc6fP4+7u3u1l9Oq7rVbOgnqq+Tl7syfx/Rg69Oj+OvE3qSfK+S+D3Yy+o14Pv/5BMWlcoq6aFqqG8b0oYceIi8vj169evHss8/St2/fiue8/PLLTJw4kcGDB9OpU6eK6W+++SYbNmwgNDSUvn37cuDAATp06EBMTAwhISHMmTOnTq/d0jW7YU6traTMxPeJGSyKT+FgRg7e7s7cHRPEHQMCaNvK0drlCSuSYU5FufoOcyp91A3M0d6OmyL9mBzhy6akMyyOT+GVHw6xYMMRbu/vzz1DgujUtpW1yxRCNCES1I1EKUVsdy9iu3tVXMxgyZZU3t+SyqQIX2bHBtOzYxtrlymEaAKkj/oaqOpiBmPf2MSs9xPYmnxGTlEXQtRIgvoaqnwxg71p57njnR1MXrCF7xJPUiqnqAshqiBBbQWWFzN4aUoIuUWlPPLJL4x8bSMfbEul8IIcKSKEuEiC2opcHO25c0AXfnpiGAvvisLDzYlnv97P4JfX8a8fD5OdV2ztEoUQNkCC2gbY2ynGhnRixcOD+fyBQfTt0p431yUR88p6/rpyH8ey861domgmyoc57dOnD+Hh4bz22muYTFfW5TZ+/HjOnTt3xbU8//zzzJs374qfX1eBgYGcOXOm3s9LTU2tOMEHYOfOnTz22GMNWVqdyVEfNkQpRf8gD/oHeZCUmcs7m1L47OfjfLzjGONCOjE7Nphw/3bWLlM0YZankJ8+fZo77riDnJwcXnjhhXqva9WqVZdN01qjtcbOrnHbgKWlpTg4NG58lQf1HXfcAUB0dDTR0VUe5tzopEVto7r5uPPPqeFsfmoks2O7Ep+UxeQFW5i+eBsbfjstR4qIq+bt7c3ixYv597//jdaasrIy5syZQ79+/QgLC2PRokUAZGRkEBsbW3HBgU2bNgEXW6qpqan06NGDmTNnEhISwokTJ3j11Vcr1vPcc89VvOZLL71E9+7dGTJkCL/99luVdc2aNYsHH3yQ6OhounfvznfffQeYhzqdNGkSI0eOZNSoUZw9e5abbrqJsLAwBg4cWHFKe3Z2NqNHj6ZPnz7cd999Ff9XLIdTBZg3bx7PP/88AEeOHOH6668nPDycqKgokpOTmTt3Lps2bSIiIoJ//etfxMXFMXHiRIBqX/v555/nnnvuYfjw4QQHBzN//vwGea+kRW3jfNq4MHdcT/44oiufJZxgyZaj3P3+z/TwcWd2bDA3hvvi5CCft03NKwmvcOjsoQZdZ0+PnjzV/6l6PSc4OJiysjJOnz7N119/Tdu2bfn5558pLi4mJiaG0aNH89VXXzFmzBieeeYZysrKqrwqTFJSEsuWLWPgwIGsXbuWpKQkEhIS0FozadIk4uPjcXNz47PPPmPPnj2UlpYSFRV1yWnollJTU0lISCA5OZkRI0Zw5MgRwDwca2JiIh4eHjz66KNERkaycuVK1q9fz8yZM9mzZw8vvPACQ4YM4dlnn+X777/nvffeq/X3cOeddzJ37lymTJlCUVERJpOJl19+mXnz5lV8UMTFxVUs/9xzz1X52gCHDh1iw4YN5Obm0qNHDx566CEcHa/urGQJ6ibC3cWR+2OD+cPgQL799SSL41N4cvmvvLrmN+4dEsT0/v64u8gp6uLKrV27lsTExIqrrZw/f56kpCT69evHPffcQ0lJCTfddBMRERGXPbdLly4MHDiwYj1r164lMjISgLy8PJKSksjNzWXKlCm4upovHj1p0qRqa7n11luxs7OjW7duBAcHc+iQ+UPthhtuwMPDAzAPifrll18CMHLkSLKzs8nJySE+Pp6vvvoKgAkTJtC+fc0jWubm5pKens6UKVMAcHFxqfV3Vd1rl7+ms7Mzzs7OeHt7k5mZSefOnWtdZ00kqJsYJwc7bunbmZuj/Ig7nMWijcm8tOog89clccfAAO6JCcKnTe1/aMK66tvybSwpKSnY29vj7e2N1pq33nqLMWPGXLZcfHw833//PbNmzeKJJ55g5syZl8y3HCZVa83TTz/NAw88cMkyb7zxRp3rshw21fLnqxmO1cHB4ZIdp01pOFb5ztxEKaUY0cObz2YP4us/xhDb3Yt34lMY8sp65iz/laTMqoeRFKJcVlYWDz74II888ghKKcaMGcPbb79NSUkJYB5mND8/n2PHjuHj48P999/Pfffdx+7du2tc75gxY1iyZAl5eeYLaqSnp3P69GliY2NZuXIlhYWF5Obm8u2331a7juXLl2MymUhOTiYlJaXKoU4th0SNi4vD09OTNm3aXDIc6+rVq/n9998B81Csp0+fJjs7m+Li4oouDXd3dzp37szKlSsBKC4upqCgoM7DsVq+dmORFnUzEO7fjgV3RnEsO5/3Nh/l850nWL4rjVE9vXlgWFf6Bba/rIUiWqbyK7yUlJTg4ODAjBkzeOKJJwC47777SE1NJSoqCq01Xl5erFy5kri4OF599VUcHR1p3bo1H3zwQY2vMXr0aA4ePMigQYMA8/UUP/roI6KiorjtttsIDw/H29ubfv36VbuOgIAA+vfvT05ODgsXLqyyO6J8x11YWBiurq4sW7YMMPcf33777fTp04fBgwcTEBAAgKOjI88++yz9+/fHz8+Pnj17Vqzrww8/5IEHHuDZZ5/F0dGR5cuXExYWhr29PeHh4cyaNauiK6em124sdR7mVCllD+wE0rXWE2tatiUPc2oLzuZf4INtqSzbmsrvBSVE+LfjwWHB3NC7I/Z2EtjWIsOc1s2sWbOYOHEiU6dOtXYpjaa+w5zWp+vjceDgVdQmrhEPNyf+dH13ts4dxf9N7sPZ/As8+NFurn99Ix/vOEZRiZyiLkRTUqegVkp1BiYA7zZuOaIhtXKyZ8agQDb8eTgL7ojC3cWBZ1bsI+bl9by1LolzBResXaIQl1m6dGmzbk1fibr2Ub8B/AVwr24BpdRsYDZQ0SckbIO9nWJCWCfGh3Zke8pZFsUn89qPh/lPXDK39fPn3iFB+Hu4WrtMIUQ1ag1qpdRE4LTWepdSanh1y2mtFwOLwdxH3VAFioajlGJQ1w4M6tqBQ6dyWByfwkfbj/Hh9mNMCDWfoh7i19baZQohKqlLizoGmKSUGg+4AG2UUh9pre9q3NJEY+rZsQ2v3xrBn0f34P0tR/k04QTf/HqSIdd5Mjs2mKHdPOVIESFsRK191Frrp7XWnbXWgcB0YL2EdPPh264Vz0zozZa5I3lqbE8OZ+Yyc0kC4+dvZuUv6ZTIxQyEsDo54UUA0LaVIw8N78qmp0bwz6lhlJSZ+NN/9zD81Tje23yU/OKrP7tKWF/5MKchISFMmzatynE7rsbw4cOp7dDcN95445LXvdrhUluCegW11jqutmOoRdPm7GDPrdH+rP1TLO/9IRq/dq34v+8OMPjl9by65hCncxvntFtxbZQPc7pv3z6cnJxYuHDhNa+hclCvWrWKdu3aXfM6mhJpUYsq2dkpRvXy4fMHB/HVw4MZFNyB/8QlM+SVDTz9VSLJWXnWLlFcpaFDh3LkyJEah+ycMWMGgwYNolu3brzzzjsAlwz3CfDII4+wdOnSy9b/0EMPER0dTZ8+fSqGOp0/fz4nT55kxIgRjBgxArh0YP/XX3+dkJAQQkJCKsYGSU1NpVevXtx///306dOH0aNHU1hY2Fi/Fpskp5CLWkUFtGfhjL6kZOXx7uajfLErjc9+PsENvXx4YFgwfbt4WLvEJufU3/9O8cGGHebUuVdPOv7v/9Zp2dLSUlavXs3YsWNrHLIzMTGR7du3k5+fT2RkJBMmTKhzPS+99BIeHh6UlZUxatQoEhMTeeyxx3j99dfZsGEDnp6elyy/a9cu3n//fXbs2IHWmgEDBjBs2DDat29PUlISn376Ke+88w633norX375JXfd1XJ2lUmLWtRZsFdr/j4llC1PjeSREdex4+hZbnl7G1Pf3sra/acwmeSoTFtXPtZHdHQ0AQEB3HvvvWzevJkZM2YAlw/ZOXnyZFq1aoWnpycjRowgISGhzq/1+eefExUVRWRkJPv37+fAgQM1Lr9582amTJmCm5sbrVu35uabb664SEFQUFDF8Kp9+/YlNTW1/hvfhEmLWtSbl7szT47uwYPDuvL5zhO8u+kosz/cRbCXG7OHBnNTpB8ujvbWLtOm1bXl29AsL8VVF1UNN1qX4UKPHj3KvHnz+Pnnn2nfvj2zZs26qmFFKw8d2tK6PqRFLa6Ym7MDd8cEsXHOcN6cHkErR3vmfrWXof/cwIINRzhfUGLtEkUd1DRk59dff01RURHZ2dnExcXRr18/unTpwoEDByguLubcuXOsW7fusnXm5OTg5uZG27ZtyczMZPXq1RXzqhs+dOjQoaxcuZKCggLy8/NZsWIFQ4cObaStblqkRS2umoO9HZMj/JgU7suWI9ksik/m1TW/8Z8NR5jeP4B7hgTh166VtcsU1ahpyM6wsDBGjBjBmTNn+Otf/4qvry9gvgJLSEgIQUFBlwz/WS48PJzIyEh69uyJv78/MTExFfNmz57N2LFj8fX1ZcOGDRXTo6KimDVrFv379wfMw65GRka2uG6OqtR5mNP6kGFOxf6T53knPoVvEzNQwI3hvsyODaZXp8YbXN3WNbVhTp9//nlat27Nn//8Z2uX0uw05jCnQtRZH9+2vDE9ko1zhjNzUCBr9p9i3JubmLkkga1HzshV1IWoB2lRi2viXMEFPt5xnPe3HOVM3gVC/NrwQGxXxoV0xMG+ZbQXmlqLWjQeaVELm9TO1Yk/jriOzU+N5B83h1JQXMajn/7C8HlxLN1ylIILLeMUdfkmIa7kb0CCWlxTLo723N4/gJ+eGMaiGX3xdnfm+W/Np6i/vvY3zuQVW7vERuPi4kJ2draEdQumtSY7O7vKa0DWRLo+hNXtTD3LovgUfjyQibODHVP7dub+ocEEerpZu7QGVVJSQlpa2lUdTyyaPhcXFzp37oyjo+Ml02vq+pCgFjbjyOk83t2Uwle70ykxmRgX0pHZsV2J8G9n7dKEaHQS1KJJOZ1TxPtbU/lo+zFyi0rpH+TBg8OCGd7dGzu5irpopiSoRZOUV1zKZwnHeW/zUTLOF9HNuzWzY4OZHOGHk4PsXhHNiwS1aNJKykx8l3iSRRtTOHQqF582ztwTE8TtAwJo4+JY+wqEaAIkqEWzoLUmPukMizYmszU5m9bODtw5IIC7Y4Lo2LZ+e9GFsDUS1KLZ2Zt2nkXxyazam4G9nWJyhB+zY4Pp7uNu7dKEuCIS1KLZOnG2gHc3pfDfnScoKjExsqc3s2ODGRDkIVdRF02KBLVo9s7mX+DDbcdYti2Vs/kXCPdvxwOxwYzp0xF7OVJENAES1KLFKLxQxhe703h3UwrHsgvo0sGV+4YGM61vZ7mYgbBpEtSixSkzadbsP8Wijcn8mnaeDm5OzBwUyMxBXWjv5mTt8oS4jAS1aLG01uw4epbF8SmsP3QaF0c7bov2576hwfh7uFq7PCEq1BTUcoUX0awppRgY3IGBwR04nJnL4vgUPkk4zofbjzE+tBMPxHYltHNba5cpRI2kRS1anFPni3h/y1E+2XGc3OJSBnftwAPDuhLbzVOOFBFWI10fQlQhp6iET3ccZ8mWo2TmFNOzozv3DgnixnBf2fEorjkJaiFqcKHUxNd70nlnUwqHM/Po4ObEHQMCuGtgF3zayBmP4tqQoBaiDrTWbDmSzdKtR1l36DT2SjEhrBN3xwTJUKui0cnORCHqQCnFkG6eDOnmSeqZfJZtS2X5zjS+3nOSCP923B0TyPjQTji2kGs8CtshLWohapBbVMKXu9JYujWV1OwCfNo4c9eALtwxIIAOrZ2tXZ5oRqTrQ4irZDJpNh7OYsmWo2xKOoOTgx2Tw32ZFRNIH185vE9cPen6EOIq2dkpRvT0ZkRPb46czmXp1lS+3JXO8l1p9Atsz10DuzA2pCPODnK0iGh4tbaolVIuQDzgjDnYv9BaP1fTc6RFLVqC8wUlfL7zBB/tOMax7AI8WztxWz9/bu8fQOf2ctajqJ+r6vpQ5jMA3LTWeUopR2Az8LjWent1z5GgFi2JyaTZdOQMH247xvpDmQCM7OnDjEFdGHqdp1znUdTJVXV9aHOS5xk/Ohq3hu/YFqKJsrNTDOvuxbDuXqT9XsCnCcf5788n+OlgJl06uHLngACm9fWXwaDEFavTzkSllD2wC7gOWKC1fqqm5aVFLVq6C6Umfth/io+2HSMh9SxODnbcGObLjEFdCO/cVk5VF5dpsKM+lFLtgBXAo1rrfZXmzQZmAwQEBPQ9duzYFRcsRHNy6FQOH20/xord6eRfKCPUry13DgjgxnBf3Jxlf74wa9DD85RSzwIFWut51S0jLWohLpdbVMLKX9L5cPsxDmfm4eZkz6QIP+7oHyAj+Imr3pnoBZRorc8ppVoBa4FXtNbfVfccCWohqqe1Zvfx3/k04QTfJZ6kqMREH982TO8fwOQIX9q4OFq7RGEFVxvUYcAywB6wAz7XWr9Y03MkqIWom/OFJXyzJ51PE05wICOHVo72TAzrxPT+AUQFtJO+7BZEzkwUwsZprdmbfp5PE47zzZ6T5F8oo7tPa27vH8CUSD/aucoRI82dBLUQTUhecSnf/XqSTxOO82vaeZwc7Bgf0pHp/QMYEOQhrexmSoJaiCZq/8nzfJZwgpW/pJNbXEqXDq5MjerMLX0749uulbXLEw1IglqIJq7wQhmr92WwfGca21KyUQqGXOfJ1L6dGdOno1yRphmQoBaiGTlxtoAvdqXxxa400s8V4u7iwI3hvkzr25kIf9kB2VRJUAvRDJlMmu0p2SzflcbqfRkUlZjo5t2aqX07MyXKD293uYxYUyJBLUQzl1NUwveJGSzfeYLdx89hb6cY3t2LadGdGdnTBycHuSqNrZOgFqIFSc7K44tdaXy1O43MnGLauzoyMcyXmyL95NhsGyZBLUQLVFpmYtORM3y1O521+09RXGqiSwdXborwY0qkH4GebtYuUViQoBaihcstKuGHfadY8Us621Ky0RoiA9pxc6QfE8J88ZAhWK1OgloIUSHjfCHf7DnJil/SOXQqFwc7xfAe3kyJ9GNUL2851M9KJKiFEFU6mJHDil/S+XpPOpk5xbi7ODA+pBNTovzoH+ghV6e5hiSohRA1KjNptiVns+KXdH7Yl0H+hTJ827owMdyXG8N8CfFrIzshG5kEtRCizgoulPLjgUy+2XOSjYezKDVpgjzduDGsEzeG+9LNx93aJTZLEtRCiCtyruACP+w7xbeJJ9mWnI1JQ8+O7txotLQDOsjV1huKBLUQ4qqdzi1iVWIG3yZmsOvY7wCE+7djUrgvE0I70bGtnAl5NSSohRANKu33Ar5LzODbX0+y/2QOSkH/QA9uDPdlfGgnOdzvCkhQCyEaTXJWHt/9msE3v6aTnJWPvZ1iUHAHxod2YnQfHzxbO1u7xCZBgloI0ei01hzMyOXbxJOs3ptBanYBdgoGBHVgfGhHxvTpiHcb6R6pjgS1EOKa0lpz6FQuq/dm8P3eDJKz8lEK+nXxYFxoR8aGdKRTW7nwgSUJaiGEVR3OzGXV3gxW7z3Fb5m5APTt0p5xIR0ZF9oJP7lajQS1EMJ2HDmdxw/7Mli19xQHMnIA89Ej40M6Mi6kU4s95E+CWghhk1LP5LNqn7mlvTf9PGA+Tnt0n46M7u1DH9+Wc0akBLUQwuadOFvAmv2nWHsgk52pZzFp8GvXiht6+zC6jw/9Az1wsG++F0CQoBZCNCnZecWsO3iatQdOEZ90hgulJtq5OjKypzeje3cktrsnrk4O1i6zQUlQCyGarPziUjYlZbF2fyY/Hcwkp6gUF0c7hnbzYnRvH0b18mkWJ9jUFNTN6yNJCNHsuDk7MDakE2NDOlFSZiLh6FnWGl0kPx7IxE5Bv0APbjBCO6gZXrlGWtRCiCZJa82+9BzWHjjFmv2nOJyZB0Cwpxsje3ozqpcP0YHtcWwi/drS9SGEaPZOnC1g3cFM1h06zY6Us1woM+Hu4sCw7l6M6uXN8O7etLfhLhIJaiFEi5JXXMrmpDOsP5TJ+kNZnMkrxk6ZT7IZ2dOHUb286ebd2qYO/ZOgFkK0WCaTZm/6+YrW9v6T5pNs/D1aMaqnDyN7ejMg2ANnB+teK1KCWgghDBnnC9lwKIt1BzPZfOQMxaUmXJ3sGdy1A8O6ezG8hzf+Htf+7EgJaiGEqELhhTK2pZxh/aHTbDycxYmzhYB5h+SwHl4M6+7FwOAO1+TK7BLUQghRC601R8/kE/dbFhsPZ7E9JZviUhPODnYMDC5vbXsR5OnWKH3bVxXUSil/4APAB9DAYq31mzU9R4JaCNHUFZWUsT0lm42HzcGdkpUPmPu2h3f3Zlh3LwZ17YCbc8OcjnK1Qd0J6KS13q2Ucgd2ATdprQ9U9xwJaiFEc3M8u4CNSVls/O00W5OzKbhQhpO9Hf2C2hPbzYuh3bzo1cn9ilvbDdr1oZT6Gvi31vrH6paRoBZCNGfFpWXsSv2duMNZxP12uuJkG792rdg4Z/gVDR7VYEGtlAoE4oEQrXVOpXmzgdkAAQEBfY8dO1bvQoUQoik6db6ITUlZZOYU8cjIble0jgYJaqVUa2Aj8JLW+qualpUWtRBC1E9NQV2n9rlSyhH4Evi4tpAWQgjRsGoNamXuGX8POKi1fr3xSxJCCGGpLi3qGGAGMFIptce4jW/kuoQQQhhqPQBQa70ZsJ2RS4QQooVpGgO1CiFECyZBLYQQNk6CWgghbJwEtRBC2DgJaiGEsHES1EIIYeMkqIUQwsZJUAshhI2ToBZCCBsnQS2EEDZOgloIIWycBLUQQtg4CWohhLBxEtRCCGHjJKiFEMLGSVALIYSNk6AWQggbJ0EthBA2ToJaCCFsnAS1EELYOAlqIYSwcRLUQghh4ySohRDCxklQCyGEjZOgFkIIGydBLYQQNk6CWgghbJwEtRBC2DgJaiGEsHES1EIIYeMkqIUQwsZJUAshhI2rNaiVUkuUUqeVUvuuRUFCCCEuVZcW9VJgbCPXIYQQohq1BrXWOh44ew1qEUIIUYUG66NWSs1WSu1USu3MyspqqNUKIUSL12BBrbVerLWO1lpHe3l5NdRqhRCixZOjPoQQwsZJUAshhI2ry+F5nwLbgB5KqTSl1L2NX5YQQohyDrUtoLW+/VoUIoQQomrS9SGEEDZOgloIIWycBLUQQtg4CWohhLBxEtRCCGHjJKiFEMLGSVALIYSNk6AWQggbJ0EthBA2ToJaCCFsnAS1EELYOAlqIYSwcRLUQghh4ySohRDCxklQCyGEjZOgFkIIGydBLYQQNk6CWgghbJwEtRBC2DgJaiGEsHG1Xtz2Wvr7jr9TYiqpeqZJw4U8uJALJUVQdsF8M5WBNgEatL70cb3Ud/m6ULXMrmV+fdZlOb/W1dawwGWz6lNjbeu+inVdTV3KDuwczDd7497O8eK0S6Y7XEGdQpi1dmzNk9FPNvh6bSqo49PiKS4rvjhBaygphLJicyjXlKWq4h/LCTasMT4YGtpV1NgUNq865X9Lys64V8Y9lX6u4b7GZURz1d6lPU/SzIP6h1t+MD/QGnZ/AD8+C0XnwLMHBI+GjqHgEQStfcClLTi3AUcXq9YsbEDlb0+VfzaVwIV8KCmACwVQkm/+ueJxgTEvv9J9pfkV0wrN00sKobSo/vU6uIBjK3B0NW6twMnt0mlOrtXMN+6dLOaVT3NsZV63gwvYSa9mc2JTQQ2AyQSrnoSdS6DLELjhBfDrKy0RUb3KfxuVf7ZzBgdnwKPhX9tUZgS3RXhbBntFuJffCo0PgsLLpxXlQO6pyz8QtKn+ddk7mxsxjq4XPxiqu691Xivzuqq8byUfDNeA7QV13N/NIR3zJxj1nPwBCNtmZw/Orc03vBp+/Vqbu/0qh3vl8C8pMO+7KS28+MFRWlTFfREU/g65GZfPu5JvB+XKPxgqh/llHxTGPAfni61/Byfj3rnqe3vnGuY5tohGnG0F9fHtEP8qRN4F1z/fIt4AIWqklBFKzo3/WiaTeX9QjUFffm/5wVDFfUnBxQ+GonPmbwqWy5ReMN9fybeFS6hawt54XFPYl/9+Kz/nkg8Ep4uvU74ue6eL942cVbYT1GWlHL3rPkwlvvBzKrxzo7UrEkJcNQW4GrcqaCodtaWNx5WnmS6fX/G48vJlQD7o3BqWsVhng2ymeWexvZsTgev3Ncw6LdhOUJcW4uTriW7lA206WbsaIURLUB7g2jjMt/xw3/JppurmmaqcZu/WOAc32E5QO7vj91mctasQQgibI3vqhBDCxklQCyGEjZOgFkIIG1enoFZKjVVK/aaUOqKUmtvYRQkhhLio1qBWStkDC4BxQG/gdqVU78YuTAghhFldWtT9gSNa6xSt9QXgM2By45YlhBCiXF2C2g84YfFzmjHtEkqp2UqpnUqpnVlZWQ1VnxBCtHgNtjNRa71Yax2ttY728mqEMQ+EEKKFqssJL+mAv8XPnY1p1dq1a9cZpdSxqynMCjyBM9Yu4hqTbW4ZZJubhi7VzVC6lnPdlVIOwGFgFOaA/hm4Q2u9vyErtDal1E6tdbS167iWZJtbBtnmpq/WFrXWulQp9QiwBrAHljS3kBZCCFtWp7E+tNargFWNXIsQQogqyJmJFy22dgFWINvcMsg2N3G19lELIYSwLmlRCyGEjZOgFkIIG9esg1optUQpdVoptc9iWrhSaptSaq9S6lulVBuLeWHGvP3GfBdjel/j5yNKqflK2e7FHOuzzUopR6XUMmP6QaXU0xbPaRIDcSml/JVSG5RSB4z37XFjuodS6kelVJJx396Yroz38IhSKlEpFWWxrj8Yyycppf5grW2qzRVs853Gtu5VSm1VSoVbrKtZvs8Wz+unlCpVSk21mNYk3udLaK2b7Q2IBaKAfRbTfgaGGY/vAf7PeOwAJALhxs8dAHvjcQIwEPMF4FYD46y9bQ20zXcAnxmPXYFUIBDzYZjJQDDgBPwK9Lb2tlWzvZ2AKOOxO+Zj/nsD/wTmGtPnAq8Yj8cb76Ey3tMdxnQPIMW4b288bm/t7WugbR5cvi2YB1cr3+Zm+z5bbN96zEesTW1q77PlrVm3qLXW8cDZSpO7A/HG4x+BW4zHo4FErfWvxnOztdZlSqlOQBut9XZtfqc/AG5q9OKvUD23WQNuxklNrYALQA5NaCAurXWG1nq38TgXOIh5LJrJwDJjsWVcfM8mAx9os+1AO+M9HgP8qLU+q7X+HfPvaey125K6q+82a623GtsEsB3z2cXQvN9ngEeBL4HTFtOazPtsqVkHdTX2c/GPcRoXT4/vDmil1Bql1G6l1F+M6X6YB6IqV+WgVDauum3+AsgHMoDjwDyt9VnqOBCXrVFKBQKRwA7AR2udYcw6BfgYj6vbtua8zZbuxfyNAprxNiul/IApwNuVnt4kt7klBvU9wMNKqV2Yv0JdMKY7AEOAO437KUqpUdYpscFVt839gTLAFwgCnlRKBVunxKujlGqNufX0J611juU845tQszsOtb7brJQagTmon7pmRTawemzzG8BTWmvTta2wcdjOVcivEa31IczdHCilugMTjFlpQLzW+owxbxXmvt6PuPhVEeowKJWtqWGb7wB+0FqXAKeVUluAaMwtjnoNxGVNSilHzP95P9Zaf2VMzlRKddJaZxhdG+Vff6sbZCwdGF5pelxj1n016rnNKKXCgHcx71/JNibXe8A1a6rnNkcDnxn7/T2B8UqpUprY+1yuxbWolVLexr0d8P+AhcasNUCoUsrV6LMdBhwwvlblKKUGGkd7zAS+tkLpV6yGbT4OjDTmuWHeuXYI887HbkqpIKWUEzAd+OZa110XxnvyHnBQa/26xaxvgPI9+n/g4nv2DTDTOPpjIHDeeI/XAKOVUu2NIwdGG9NsTn23WSkVAHwFzNBaH7ZYvtm+z1rrIK11oNY6EHMX38Na65U0off5Etbem9mYN+BTzP2vJZhbzPcCj2PeY3wYeBnj7Exj+bsw9+fuA/5pMT3amJYM/NvyObZ2q882A62B5cY2HwDmWKxnvLF8MvCMtberhu0dgvnrbiKwx7iNx3zUzjogCfgJ8DCWV5gvLZcM7AWiLdZ1D3DEuN1t7W1rwG1+F/jdYtmdzf19rvTcpRhHfTSl99nyJqeQCyGEjWtxXR9CCNHUSFALIYSNk6AWQggbJ0EthBA2ToJaCCFsnAS1EELYOAlqIYSwcf8fx/nwUNfdwAgAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.ri = 5\n",
+    "s.n_ra_prod = 2\n",
+    "s.d_br = 1\n",
+    "s.d_prod_pc = 1.7\n",
+    "s.rrs = 0\n",
+    "s.popi = 0.2\n",
+    "s.start_date = 1950\n",
+    "s.run(10000, 0.01)\n",
+    "plt.plot(s.time, s.r, label='Resources')\n",
+    "plt.plot(s.time, s.prod, label='Production')\n",
+    "plt.plot(s.time, s.d_prod_pc*s.pop, label='Desired production')\n",
+    "plt.plot(s.time, s.pop, label='Population')\n",
+    "plt.title('World dynamics')\n",
+    "plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dno.plot_system(s)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.08.World3Exam.ipynb b/12.08.World3Exam.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..fb6fbb6d98879ac9beef25feed562f85394ef679
--- /dev/null
+++ b/12.08.World3Exam.ipynb
@@ -0,0 +1,569 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
+   "source": [
+    "import importlib\n",
+    "import numpy as np\n",
+    "import networkx as nx\n",
+    "import ast\n",
+    "import json\n",
+    "import matplotlib.pyplot as plt\n",
+    "defs = json.load(open('../definitions.json', 'r'))\n",
+    "from world3.plot_utils import plot_world_with_scales\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "import pydynamo as dno\n",
+    "from world3.colors import var_colors\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 227 ms, sys: 0 ns, total: 227 ms\n",
+      "Wall time: 228 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = dno.parse_system.system_from_file('world3/world3_pydynamo_code.py')\n",
+    "s.add_comments(defs)\n",
+    "s.start_date=1900\n",
+    "%time s.run(400, 0.5)\n",
+    "plot_world_with_scales(s)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Graph explore"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = dno.parse_system.system_from_file('world3/world3_pydynamo_code.py')\n",
+    "s.add_comments(defs)\n",
+    "dno.plot_system.show_pyvis(s, notebook=False, colors=var_colors, options=['physics']).show('w3.html')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Why is population linear ?\n",
+    "\n",
+    "Only way to influence birth rate:\n",
+    "- IOPC -> Fertility -> birth rate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s.start_date=1900\n",
+    "s.run(400, 0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dno.plot_system.plot_system(s, ['dtf', 'sfsn', 'iopc', 'pop'], rescale=True)\n",
+    "plt.title('Evolution of birth-rate related factors');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "x = np.linspace(0, 1000, 100)\n",
+    "plt.plot(x, s.update_sfsn(x, None, s.tabhl_sfsn, None))\n",
+    "plt.title('More Industrial Output means less desired children')\n",
+    "plt.xlabel('Delayed Industrial Output per capita')\n",
+    "plt.ylabel('Social Family Size Norm');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Observe patterns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from world3.plot_utils import plot_world_with_scales"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "''"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure()\n",
+    "plt.plot(s.time, s.tf)\n",
+    "plt.figure()\n",
+    "plt.plot(s.time, s.diopc)\n",
+    "plt.figure()\n",
+    "plt.plot(s.time, s.fce)\n",
+    "s.get_comment('')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<function pydynamo.system.<lambda>(ali)>"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.init_al"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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IAuWrXNNu3l2yjxyL5qUBTS4sc3dx57UOrxFUPojPtn9GTHIMH/X4yG7JUqqGSrgXXnjhwq2op0+f5o033nBwREJcmdaav0/8zeAFg/l428eEVw1n3sB5vNX5rVKcBFZZk0BtGLXompPA5qNnmL8jlv91rUPNAJ+LXlNKMbbFWN7v9j4Hzh5g2KJh7E3cW/zYC0GGoS6D5HgIRzmSdISJmyeyJmYNoX6hPNv2WToFdXJ0WMVzbD1MHwz+oXDXQih/bfMV51o0N322hnNpWfz1ZDd8PC5fIbP/zH4eWfEIZzLOML7jePrX6X+t0V8gw1ALIUyVlJnEpF2T+GnfT3i5efF0+NMMbzzcrnMCmCJ2h7VNIKhYSQBg1ubjRMSd5/M7wq6YBAAa+Tdi1o2zeGLVEzz7z7PsP7ufR8Iewc3FnFO2JAIhxDXLzM1k1v5ZTNo1ieSsZAbXH8wjYY8Q4F0G2rESDsKMW8DLD+5aUKwkcC4ti/eXHeC6UH8GNK9eqG38vfz5ts+3vLvpXb7b8x0RpyOY0HWCKcdWEoEQosgs2sLiI4v5bNtnxKbG0jmoM4+3eZwGlRo4OjTbOHsMpg0C5WokAb/itW18+OdBktKzeW1g0yLdJuvu6s7LHV6meWBz3tzwJkuOLGFkk5HFiuVSJBEIIYpkY9xGPtjyAfvO7KOxf2Ne7/Q67au3d3RYtpN8yhg2IjsV7l4MAXWLtbt9ceeZseEYI9vXonH1Cte0j5vr3UxYlTBCfEOKFcvlyF1DNvLpp5/SuHFjRowYUex9ffzxx0ybNg2Ap556ihUrVhR7n0IU16Gzh3jgrwe49497OZd5jne6vMOsG2eVrSSQftZoGE4+BSPmQrXidd7UWvPqgr34ebvzRJ/iXS3VqlALF2XOKVuuCGzkyy+/5K+//iI4uHiXkDk5OUydOpVt27YB8PDDD3PffffRs2dPW4QpRJGdTD3Jlzu+ZMHhBZRzL8eTbZ5keOPheLp6Ojo028rOgJl3QOIhGPELhLQt9i7nbYth09EzvHtLcyr62K+DWFFJIrCB+++/n6ioKPr168fo0aNJSkri8OHDREZGcvr0aZ555hnuu+8+ACZMmMCMGTNwcXGhX79+vPvuxWMjrVixgtatW+PmZvxratWqRWJiIidPnqRatWp2/9uE8zp49iDTI6azKGoRCsXIxiMZ22Isfp5+jg7N9iy5MO8+OL4OhnwHdboXe5dJadm8s2QfYTUrclu4OVU6tlLmEsGETRPYf2a/TffZyL8Rz7Z79rKvf/311yxdupSVK1dSuXJlXnvtNXbt2sWGDRtITU0lLCyMAQMGsHPnThYsWMDGjRvx8fHhzJkz/9nX2rVradOmzUXLWrduzdq1a7n11ltt+ncJUVCuJZe/o//mx30/sunkJrxcvRjaYCijmo4iqHyQo8Mzh9aw9DnYtxBueAea3WKT3b7/xwHOpGbx/T3tHDbhTGGVuURQUgwaNAhvb2+8vb3p0aMHmzZt4p9//uGee+7Bx8foUejv7/+f7eLi4v7TGUyGnhZmS85K5tdDvzJz/0yiU6KpVq4aj7d5nFvr31o2rwDyW/MRbJoEHR+GDg/aZJe7o5OYsfEYozrUpllQyT9+ZS4RXOmbuz1dy7DUYAw9nZGRcdEyGXpamGVf4j7mHJzDoqhFpOWkEVYljMfaPEavmr1M67xUouyYaUw233wo9B5vk13mWjQvzd9NQDlPnri+dNxOK3cNmWTBggVkZGSQmJjIqlWraNu2LX369OG77767MHbQpaqGZOhpYbbU7FTmHJzDsEXDuG3RbSw4vIDetXoz68ZZTOs3jRtq3+AcSSDyL1g4DkK7waAvwcU2p8NZm4+zMzqJlwY0poJX6ehZ7QT/bcdo0aIFPXr04PTp07z88svUqFGDGjVqsGPHDsLDw/Hw8KB///68/fbbF23Xr18/7rzzzgvPs7OziYyMJDz8kkOECFEoFm1h66mtLIpadGFCmHoV6/F8u+cZUGdA2a/+KSh2O8y+CwIbw+0zwM02d/QkpmQycekB2tfxZ1CrGjbZpz2YmgiUUn2BTwBXYLLW+t0Cr9cEfgAqWtd5Tmu92MyYzHL06NGLnrdo0eJCX4D8nnvuOZ577rnL7qdWrVoEBARw6NAh6tevz6JFixgyZMiFu4iEKIrD5w6zKGoRv0f9TlxqHN5u3lxf63qGNBhCy8CWpWcyGFs6cwR+HAo+ATByDnhdWyevS5mwdD+pmTm8MahZqTq2pp1dlFKuwBdAHyAa2KyUWqi1jsi32kvAz1rrr5RSTYDFQG2zYiot3n33XeLi4qhfvz45OTk8+eSTjg5JlCLxafEsO7qM3w7/xr4z+3BVrnSo0YFHWz9Kj5Ae+Lj7XH0nZVVqIsy4FSw5xmTzvra7JXtDVCI/b4nmf93qUL+qr832aw9mfs1sB0RqraMAlFKzgEFA/kSggbx07AeUiVtjijuDWMOGDWnYsCEAQ4cOtUFEoqyLTYnlz2N/8texv9iRsAOApgFNebbts/QN7Vs6ZwOztex0mDUckqJh1EIItF1DbkZ2Li/M202IvzeP9SodDcT5mZkIgoAT+Z5HA9cVWOc14A+l1MNAOaD3pXaklBoLjAWoWbPmJQvLP52jMytt80uIa3fs/DH+PPYnfx77k4hE4/tVI/9GjGs1jj61+1DHr46DIyxBLBaYNxZObILbfoCath0W4/MVkUSdTmX6mHZ4e7jadN/24OiK5+HA91rrD5RSHYDpSqlmWmtL/pW01pOASWBMTFNwJ15eXiQmJhIQEODUyUBrTWJiIl5eXo4ORZggLTuNzSc3sy52Heti13H0/FEAWlRuwRNtnqB3zd6EVCjZPVgd5s+XrR3G3oYmg2y66/0nz/P134e5JSyILvWvfahqRzIzEcQA+d+VwdZl+Y0B+gJordcrpbyAykB8UQoKDg4mOjqahISEYoRbNnh5eRV7vCPhOLmWXHaf3o1FW1BKEZcSx+7Tu9mZsJN9Z/aRY8nBy9WL8GrhDGs0jF41e1GtnAw9ckUbvob1n8N190N723QYy5Nr0Tw3dzcVvN156cYmV9+ghDIzEWwG6iulQjESwDDgjgLrHAd6Ad8rpRoDXkCRz+bu7u6EhoYWM1whHOtsxlmeXf0s6+PWX7Tcy9WLppWbcleTu2hfvT2tq7YuewO+mWXfImP4iEY3GlcDNq4xmL7+KDtOnOOj21viX67kDip3NaYlAq11jlJqHLAM49bQqVrrvUqp8cAWrfVC4EngW6XU4xgNx3drqeQWTmhv4l4eX/k4iemJPBX+FHUr1kWhCPQJJNQvtPRP+egIJzbD3DEQ1AZu+RZcbFt3H3sunfeWHaBrg0BublW6x2EytY3A2idgcYFlr+R7HAGU8pmthSieXw/9ypsb3iTAO4Bp/abRtHJTR4dU+p2Jgpm3g291uGM2eNj2llmtNS/P34NFw1s3l64+A5fi6MZiIZxWVm4W72x6hzkH59C+ensmdp1IJa9Kjg6r9EtNhBlDjFFFR8yBcra/dfa3XXEs3x/Pi/0bE+Jf+vtlSCIQwgFOpp7kiVVPsPv0bsY0G8PDYQ/jauOqC6d0UV+B36ByPZsXkZCcyasL9tAypCL3dKpt8/07giQCIexs66mtPLHqCTJzM/m4+8f0qtXL0SGVDf/pK1Cw21LxaW2MLJqalcsHQ1vg5lo2xu2URCCEHf184Gfe2fgOQb5BfNfjO+pUlE5fNmNiX4E8C3fGsmzvKZ7r14h6VUrXMBJXIolACDvIzs3m7U1vM+fgHDoHdWZC1wlU8LDdYGdOz8S+AnnikzN4deFeWoVU5L4uZSuBSyIQwmSn00/z+MrH2ZGwQ9oDzGByXwGwVgn9uoe0rFzeH9oS1xI+9WRRlY0KrkJYdnQZ9/5xL9m52Y4ORTiRvaf3cvui2zlw9gDvdXuPx9o8JknAlkzuK5Bn4c5Y/og4xZN9GlCvSnlTynAkp0kEp1JPsTFuI2k5aY4ORTiJVSdWcc+ye3BTbkzvN52+tfs6OqSy5XSkqX0F8uRVCYXVrMi9ZaxKKI/TJAJvd2PO3/ScdAdHIpzBzP0zeXTlo9Txq8OPA36koX9DR4dUtiSfghm3GI9HzjWlrwBcXCX03pCyVyWUx2naCLzdJBEI81m0hQ+3fMgPET/QPbg7E7pOcO6JYMyQmQw/DYXUBBi1CALqmlbUgh1GldAL/RuVySqhPE6XCDJyMhwciSirMnMzeeGfF/jj2B8MbzScZ9s+K+0BtpaTBbPvhJN7jOqg4DamFRV7Lp2XF+yhTa1KjOlcNquE8jhdIpArAmGGcxnneGTlI2yP385T4U9xV5O7Sv34MyWOxQILx0HUShj0JdTvY2JRmqfn7CTXovnwtrJbJZTHaRKBj5txeS6JQNhadHI0D/z1ADEpMbzX7T1pFDbL8tdg12zo+RKEjTC1qO/XHWVtZCLv3NKcWgHlTC2rJHCaRCBXBMIMe0/v5cHlD5JjyeHb67+lTVXzqiqc2oavYe0n0PZe6PKUqUVFxiczYel+ejWqwrC2zjHj21XvGlJKTVRKVVBKuSulliulEpRSI+0RnC1JIhC2tiByAXcvvRtvN2+m958uScAse+b922Gs30RTOozlyc618Pjsnfh4uPLOrc2dpnqvMLePXq+1Pg/cCBwF6gFPmxmUGSQRCFvJzM3k9fWv89Lal2ge2JwZ/WfIRPFmOfIP/Po/CLkObp1sWoexPJ8tP8TumCTeuaU5VXydZ+7vwlQN5a0zAPhFa51UGrOkJAJhC9HJ0Tyx6gn2ndnHmGZjGBc2DjcXp6lhta+YbTBzGPjXgeEzwdoXyCzbjp/l85WR3No6mL7NqptaVklTmHfwIqXUfiAdeEApFQiUunsw8xKB9CwW12rJkSW8sf4NAD7t8Sk9avZwcERlWPx+mHEr+PjDnb8av02UlpXDE7N3UN3Pm1cHlt5J6K/VVROB1vo5pdREIElrnauUSgPMGePVRK4urni4eMgVgSiy1OxU3t74NgsPL6RFYAve7fIuIb7O0YjoEGePwvSbwdUd7loAFWqYXuQbi/Zx7EwaP93bngpezjc/9FUTgVLKB3gQqAmMBWoADYFF5oZme97u3qRnSyIQhbcrYRfPrn6W2NRY7m95P/9r8T+pCjJT8kmYdrMx09g9i41qIZP9viuOmZuO879udehQN8D08kqiwryjvwO2Ah2tz2OAXyiNicDNW64IRKHkWnKZsmcKX+74kio+Vfjuhu9oXbW1o8Mq29LOwPRbICUeRi2Eqk1NL/LEmTSem7eLViEVeep65x0PqjCJoK7W+nal1HAArXWaKo2txUgiEIUTlxLH82ueZ+uprfSr3Y+XOrwkk8iYLTMFfroNEg/BiF8gONz0IrNzLTwyazto+Gx4GO5lZNrJa1GYRJCllPIGNIBSqi6QaWpUJpFEIK5Ea83iI4t5a+Nb5FpyeavzW9xU5yanuZfcYXIyYfZIiNkKt02DOt3tUuyHfx5k+/FzfH5HGCH+zj0wYGESwavAUiBEKfUj0Am428ygzOLt5s0/Mf/wytpXiEmJISMng3Lu5ahXqR5tq7alc1Bn3F2dr6FIQGJ6Im9ueJO/jv9lNAh3fpeQCtIgbLrcHGNimaiVcPNX0PgmuxT798EEvv77MMPbhXBjC/Mbo0u6wtw19KdSahvQHlDAo1rr06ZHZoJsizE72fLjywn1C6WcezmSs5L5+cDPTI+YTkXPigxtMJS7mtxFRa+Kjg1W2M1fx/7ijQ1vkJyVzONtHmdUk1Eyaqg9WCyw4EHY9xv0fRda3WGXYk+cSeORmdtpWNWXV240vx2iNCjMXUNdrQ+Trb+bKKXQWq82LyxzPNHmCQ6fO8zg+oNxd/n3m3+2JZsNsRuYe2guk3dP5sd9PzKi8QjGNB9DOfeyP+CUs0rKTOLtjW+z+MhiGvs3ZvL1k6lfqb6jw3IOWsOix6yDyL0M7R+wS7HpWbmMnb4VrTXf3NkGbw9J+ABKa33lFZT6Ld9TL6AdsFVr3dPMwC4nPDxcb9myxbT9R56NZNKuSSw5uoQArwAeDnuYm+vdLN8Qy5hVJ1Yxfv14zmacZWzLsdzb/N6LvhwIE2ltjB208Wvo8iT0esVOxWoen72DBTtjmXp3W3o0rGKXcksKpdRWrfUlW+GvmggusbMQ4GOt9a22CK6ozE4EeXYn7Gbi5onsSNhBw0oNebrt01xX/TrTyxXmSkhL4J1N7/DnsT+pX6k+b3Z6kyYBzteT1GG0huWvw5qPoP2DcMPbpg4il993a4/w+m8RPNmnAQ/3cr4rP1snAgXs1Vo75NNjr0QAxjeIZceW8dGWj4hNjaV7cHceD39cBhgrhSzawrxD8/hwy4dk5mZyf8v7ubvp3XJzgL39/R6sfBPa3AM3fmS3JLAxKpE7Jm+kR8MqTLqzDS5lfKKZSylWIlBKfYb11lGM0UpbAUe11g4ZitqeiSBPZm4m0yOmM3n3ZDJyMhjaYCgPtHoAfy9zxz8RthGVFMX49ePZemorbau15ZX2r1Dbr7ajw3I+6z6HP16EFsOMO4Rc7HPf/smkDG787B8qeLkzf1wnpxxCAoqfCEble5qDkQTW2jC+InFEIsiTmJ7IVzu/Ys7BOXi7eXNv83sZ2WQknq6eDolHXFlWbhZT90xl0q5JeLl58VT4UwyuN1j6BTjC5snw+5PQZBDcOhVc7TNMR1pWDsMmbeBwfArzH+pE/aq+dim3JLJp1VARC+4LfAK4ApO11u9eYp3bgNcwrjp2aq2veA+ZIxNBnqhzUXy09SNWRa+iernqjG0xloF1B+Lh6uHQuMS/VkevZuLmiRw7f4y+tfvybLtnqexd2dFhOacdP8H8B6BBX7htOrjZ53OSk2th7PStrDoQz7d3hdOrcVW7lFtSXVMiUErt5t8qoYteArTWusVVCnUFDgJ9gGhgMzBcax2Rb536wM9AT631WaVUFa11/JX2WxISQZ5NcZv4aOtH7EncQ1WfqtzT7B4G1xuMj7tz91J0pGPnjzFx80RWR6+mdoXaPNvuWToHdXZ0WM5rz1yYey+EdoXhs8HdPpO9aK15af4eftx4nDdvbsbI9rXsUm5Jdq2J4IpHTmt97CqFdgBe01rfYH3+vHW7d/KtMxE4qLWefMW/IJ+SlAjAeMOti13HpF2T2Ba/DR83H/qF9uOW+rfQvLLzTHXnaEmZSUzZM4XpEdPxdPXk/hb3M6LxCGkMdqT9i+HnOyG4LYycCx7265Pz5apIJi49wAPd6/Js30Z2K7cku1IiuGxF3dVO9IUQBJzI9zwaKHj/ZQNrgGsxqo9e01ovLWa5dqWUolNQJzoFdWJH/A7mHJzD4iOLmXtoLvUq1qNfaD/61OpDqF+oo0Mtk9Ky0/hp/09M3TOVlKwUbqp7E4+1foxAn0BHh+bcIpfDL6OgWgu442e7JoEFO2KYuPQAA1vW4GknHlG0KArTWNwe+AxoDHhgnLBTtdZXHI5RKTUE6Ku1vtf6/E7gOq31uHzrLAKygduAYGA10Fxrfa7AvsZizIVAzZo12xw7VtwcZa6UrBSWHF3CwsiF7EjYAUC9ivW4vtb19KzZkwaVGsiVQjFl52Yz59Acvtn5DYkZiXQP7s64sHE09JcPvsNF/W2MJBpQD0b9ZvrsYvmtO3yaUVM30aZWJX4Y3Q5PN+kImqe4dw1tAYZhzEEQDtwFNNBaP3+V7QpTNfQ1sFFr/Z31+XLgOa315svtt6RVDV3NydSTLD++nD+O/sH2+O1oNFW8q1y4imhfvT1+nn6ODrPUSM1OZc7BOUyLmEZ8WjzhVcN5tPWjtKrSytGhCYCja+HHIVCxFty9CMrZr4E+IvY8t09aT7UKXsy5vyN+PlItmF+xE4HWOlwptSuvgVgptV1rHXaV7dwwGot7YUxmsxm4Q2u9N986fTEakEcppSoD24FWWuvEy+23tCWC/BLSElgTs4Y1MWtYH7ee5KxkXJQLzSs3J7xqOK2rtqZVlVYy9v0lnMk4w0/7fmLm/pmczzrPddWuY3Tz0XSo3kGurkqK4xuMiWX8guDu36G8/YZwOHI6laFfr8fdVTHngY4EVTR3ovvS6JraCPJJU0p5ADusjbtxGB3LrkhrnaOUGgcsw6hOmqq13quUGg9s0VovtL52vVIqAsgFnr5SEijtAn0CGVx/MIPrDybHksOe03uMpBC7nh/2/sCUPVNQKOpXqk/rKq1pXbU1zQKaEewb7LQnuz2n9zBr/yyWHl1KVm4WvWr2YnSz0TQPbO7o0ER+JzbDjCHgW82oDrJjEjiZlMHIyRuxaM30Me0lCVyDwlwR1AJOYbQPPA74AV9qrSPND++/SvMVwZWk56SzO2E3W+O3su3UNnYm7LwwiY6vhy9NAppc+Gnq35Qg3yBcVNmcUSktO41lR5cx68AsIhIj8HHz4cY6NzKiyQgZ3qMkitkG0wYZbQF3LzauCOzkTGoWt32znpNJGcy8rz3Ng6Wa9XKKWzV0C/C71rpEzEpWVhNBQdmWbA6ePUhEYgR7T+8lIjGCQ+cOkWPJAYxJdkL9QqlXsR51/OpQt2Jd6vrVpUb5GqVypNQcSw4b4jbwe9TvLD++nPScdOpVrMftDW/nxjo3Ut6jvKNDFJcStxN+uAm8/IwkUNF+k/mkZOYw4tsN7DuZzLTR7Whfxzknni+s4iaC74CeGHf0zAaWaq1zbB5lITlLIriUrNwsDp07xL7EfRw+d9j4STpMfNq/ffA8XT0JLh9MSIUQQnyNnyYBTWhRuUWJq17SWrP79G5+j/qdpUeXcibjDL4evlxf63oG1h1IWJWwEhezyOfkHvjhRvAob7QJVLJfp62M7FxGf7+ZjUfO8M3INvRu4ty9hgujWG0EWut7lFLuQD9gOPCFUurPvNtChf14uHrQNKApTQMunlXpfNZ5os5FEZUUxeFzhzmRfIITySfYELuBjNwMAILKB3FD7RvoEtSFloEtHdbRSmvNwbMH+ePYHyw9spTjycfxcPGgW0g3BtQZQJegLjJUR2kQvw+mDQQ3bxi10K5JICfXwiMzt7PucCIf3d5SkoANFHqsIWsy6AvcA3TVWjtk4BZnviIoKq01p9NPsyFuA4uPLGZ97HpydS4+bj60q96O9tXb06JyCxr5NzI1MWTmZrIrYRdrY9by1/G/OHb+GC7KhbZV2zKgzgB61eold0qVJgkH4fsBoFzgnsUQUNduRVssmqfn7GLutmheu6kJd3eSjpqFVdyqoX7A7UB3YBXG2EB/OKp6SBLBtUvOSmbTyU2si1nH2ti1xKTEAODh4kGjgEY09m9MvYr1qFuxLnX86uDv5V+kqhmtNeezzhOdHM3Bswc5dO4QEYkR7ErYRbYlG1flSrtq7ehTuw89Q3oS4C11uqVO4mH4rj9oi1EdFNjAbkVrrXlx/h5+2nicx3s34NHezje5THEUNxHMxGgbWFISGowlEdjOydST7ErYxe7Tu9mVsIuDZw+Skp1y4XVvN28CvQOp4lOFQJ9AyruXx8vNCy9XL3IsOWTkZpCRk0FCegJxKXHEpcaRlpN2YXtPV0/qV6xPm6ptaFutLWFVw+Sbf2l2Jgq+GwC5WUZnsSqN7Va01prXf4vg+3VHeaB7XZ65oaG0HxWRw4ahNoMkAvNorYlPi+dw0mGizkURlxpHfFo88WnxJKQnkJadduHk7+bihqerJ15uXlT2rkz1ctWpXq461cpVI6h8EPUq1iPEN6RU3sEkLiHxsHF3UHa60U+gWjO7Fa215t0l+/lmdRRjOofy0oDGkgSuQXE7lAknoZSiarmqVC1XlY41Ojo6HFFSnI407g7KzbJ7EgD46M+DfLM6ipHta0oSMIkkAiHE5Z0+BN/fCJYcGLUIqtp3qvLPVxzi0xWR3B4ewviBzSQJmEQSgRDi0hIOGNVB2mL3NgGAb1dH8f4fBxkcFsTbtzR3ygnn7eWyieAKM5QBcLUZyoQQpVj8fiMJgHElUMW+k7v8sO4oby3ex4Dm1XlvSAtcJQmY6kpXBDdafz9k/T3d+nuEeeEIIRzuVISRBFzcjDYBO94iCjBz03FeXbiXPk2q8vGwVri5ls0xtUqSq85QppTqU2DI6eeUUtuA58wOTghhZ6f2GknA1cO4Eqhcz67F/7zlBC/8upvuDQP5/I4w3CUJ2EVhjrJSSnXK96RjIbcTQpQmJ3cbDcOunkZnMXsngc0neHbuLjrXq8zXI9vI7GJ2VJjG4jHAVKVU3viu54DRpkUkhLC/uJ3GUNLuPkZ1kB2HjQCYvfk4z87dTdcGgUy6sw1e7pIE7Kkwg85tBVrmJQKtdZLpUQkh7Cd2O0y7GTx9jSTgb9/xe2ZuOs7z83bTrUEg30gScIirVvEopaoqpaYAs7TWSUqpJkqpMXaITQhhtrxJZTwrGLeI2jkJ/LTRSAI9GkoScKTC1PV/jzGlZA3r84PAYybFI4Swl+itxpWAl5+RBCrVtmvxP248xgu/Gknga0kCDlWYRFBZa/0zYAFjLmKM+YWFEKXVic0w/WbwqWTMLGbH+QQAZmw4xou/7qFnoyp8fac0DDtaYRJBqlIqAGvnMqVUe0DaCYQorY6usSaBAOPuIDtOLwkwZc0RXpq/h96Nq/DVyNaSBEqAwtw19ASwEKirlFoLBAJDTI1KCGGOyOUwawRUrAl3LYAK1e1WtNaaz1ZE8uGfB+nXrBqfDAvDw03uRC8JCnPX0DalVDegIaCAA1rrbNMjE0LY1oEl8PNdULkh3PkrlA+0W9Faa95Zsp9Jq6O4tXUwE25tLj2GS5ArjTV0y2VeaqCUQms9z6SYhBC2tvdXmHsvVGsBI+eCj7/dis61aF6av4eZm44zqkMtXr2pqQwgV8Jc6Yrgpiu8pgFJBEKUBjtnwfwHIOQ6uONn8LLfLHHZuRae+mUnC3bE8mD3ujwtM4uVSFcaa+geewYihDDBlu9g0eMQ2hWGzwSPcnYrOiM7l4dnbufPiFM807chD3a375AVovAKNR+BUmoA0BTwylumtR5vVlBCCBvY8BUsfQ7q3wC3TQN3r6tvYyNJ6dncN20Lm46cYfygptzVobbdyhZFd9VEoJT6GvABegCTMe4Y2mRyXEKIa6U1rPkQlo+HxgPh1ing5mG34uOS0rl76maiTqfw6fAwBrascfWNhEMV5oqgo9a6hVJql9b6daXUB8ASswMTQlwDreHPl2HdZ9B8KNz8NbjabyLCQ6eSGTV1E+czcvj+nnZ0qlfZbmWLa1eYd0i69XeaUqoGkAjY7+ZjIUTh5ObAokdh+wxoex/0mwgu9rtFc8vRM4z5YQsebi7M/l97mtbwu/pGokQoTCJYpJSqCLwHbMO4Y2iymUEJIYooJxPmjoF9v0HXZ6DHC2DHu3OW7T3JIzO3U6OiN9NGtyPE38duZYviK0yHsjesD+cqpRYBXjIUtRAlSGay0Vv4yN9wwzvQ4UG7Fa21ZtLqKN5dup+WwRWZMiqcgPKeditf2EZhhqF+yHpFgNY6E3BRStnvnSaEuLy0M/DDQGP8oJu/tmsSyMqx8OzcXbyzZD/9m1dn1tj2kgRKqcJUIN6ntT6X90RrfRa4rzA7V0r1VUodUEpFKqUuO8exUupWpZRWSoUXZr9CCCApBqb2NeYZvn0GtBput6LPpWVx19SN/Lwlmod71uOzYWEyjHQpVpg2AlellNJa540+6gpc9V4063pfAH2AaGCzUmqh1jqiwHq+wKPAxqIGL4TTOh0J0wdD+lljyIjQLnYr+sjpVEZ/v5mYs+l8dHtLBocF261sYY7CXBEsBWYrpXoppXoBM63LrqYdEKm1jtJaZwGzgEGXWO8NYAKQUciYhXBuJzbDlD6QnQp3/2bXJLD+cCI3f7GWpPRsfrrvOkkCZURhEsGzwArgAevPcuCZQmwXBJzI9zzauuwCpVRrIERr/fuVdqSUGquU2qKU2pKQkFCIooUoo/Yvhh9uMmYVG/Mn1AizW9GzNh3nrqkbCfT1ZP6DnQivbb+B64S5CnPXkAX4GvhaKeUPBGutiz1DmVLKBfgQuLsQMUwCJgGEh4fr4pYtRKm0eQosfgqqtzIGj7PTMNJZORbeWBTB9A3H6NogkM+Gh+Hn7W6XsoV9FGaIiVXAQOu6W4F4pdQ6rfXjV9k0Bsg/9VGwdVkeX6AZsMo6GmE1YKFSaqDWekuh/wIhyjqtYcUb8M8HxrhBQ7+z2+Bxp1MyeXDGNjYdPcP/utbhmb6NcJUhpMucwjQW+2mtzyul7gWmaa1fVUrtKsR2m4H6SqlQjAQwDLgj70VrX4QL/c+tCecpSQJC5JObDQsfhp0zofUoGPCh3YaM2B2dxP+mbyExNYtPhrViUKugq28kSqXCtBG4KaWqA7cBiwq7Y+sk9+OAZcA+4Get9V6l1Hil1MBrilYIZ5JxHn66zUgC3V+Amz6xWxKYvz2GIV+vQynF3Ac6ShIo4wrzrhqPcTJfq7XerJSqAxwqzM611ouBxQWWvXKZdbsXZp9COIWzx2DmMEg4AAM/h9Z32qXYnFwLE5cdYNLqKNqF+vPliNZUlk5iZV5hGot/AX7J9zwKuNXMoIRwaic2waw7ICfL6CNQt4ddio1PzuCRmdvZEHWGuzrU4uUbm+Au8wo7hcI0FjcAvgKqaq2bKaVaAAO11m+aHp0Qzmb3HJj/IFSoAXf/DIEN7FLs+sOJPDJrO8kZ2bw/tCVD2kj/AGdSmHT/LfA8kA2gtd6F0fArhLAVrWHVu8YIokFt4N7ldkkCFovmi5WRjJi8AV8vN+Y/1EmSgBMqTBuBj9Z6U4EJp3NMikcI55OZAgvHwd5fodUIuPEjcDO/Xv5cWhZP/LyTFfvjubFFdd69tQXlPe03iY0oOQrzXz+tlKqLMQ8BSqkhQJypUQnhLBIPw+yRkLAf+oyHjo/YZR6BHSfO8dCP24hPzmD8oKbc2b4Wyo7zF4iSpTCJ4CGMXr2NlFIxwBFghKlRCeEMDiyFeWPBxRVGzrNLo7DFopm69ggTlu6niq8Xv9zfkVYhFU0vV5RshblrKArorZQqh9GmkIbRRnDM5NiEKJssFlg9EVa9A9VaGENIV6plerEJyZk8+ctOVh9MoE+Tqrw3pAUVfew3qb0ouS6bCJRSFTCuBoKABcBf1udPAruAH+0RoBBlStoZmP8AHFwKLYcb7QHu3qYX+/fBBJ78eQfJGTm8cXMzRl5XU6qCxAVXuiKYDpwF1mNMRPMioIDBWusd5ocmRBlzfAPMGQMpp6D/+9D2XtPbAzJzcnlv6QEmrzlCg6rl+fHe9jSs5mtqmaL0uVIiqKO1bg6glJqM0UBcU2st8wYIURQWC6z9GFa8CRVDYMwfENTa9GKjElJ4ZNZ29sScZ2T7mrw0oInMIiYu6UqJIDvvgdY6VykVLUlAiCJKSYBf/weHl0PTwcZ4QV5+phapteaXrdG8tnAvHm4ufHNnG25oWs3UMkXpdqVE0FIpdd76WAHe1ucK0FrrCqZHJ0RpduQfmHsvZJyDGz+GNnebXhV0OiWTF+bt5o+IU1wX6s/Hw1pR3c/8NghRul02EWit5RpSiGuRkwkr34K1n0Ll+sZ4QdWamV7snxGneH7eLs6n5/BC/0aM6VxH5g4QhSLdCIWwpZN7jL4B8XuNK4Dr3wLP8qYWmZyRzRuLIvh5SzSNq1fgx3tbSYOwKBJJBELYgiUX1n0KK94C70rGVJINbjC92I1RiTz5y05iz6XzUI+6PNqrAR5uMmKoKBpJBEIUV+JhWPAQHF8PjQca7QHlAkwtMiM7lw/+MG4Lrenvwy/3d6BNLZlMXlwbSQRCXKvcbFj/uTFqqKsHDP4GWtxueoPw3tgknpi9kwOnkhlxXU1e6N+YcjJYnCgGefcIcS1itsHCR+DUbmh0I/R/z5hDwETZuRa+XHmYz1Ycwr+cB9/d05YeDauYWqZwDpIIhCiKzBRY+TZs/ArKVTHGCWp8k+nFRsSe56lfdhIRd55BrWrw2k1NqVROxgkStiGJQIjC0NqYL+CPl+F8NLS5B3q/Bt4VTS02/1VARR8P6RwmTCGJQIirObUXljwLR/+Bqs3h1slQq4PpxcpVgLAXSQRCXE7aGaMhePNk8KoAAz4wrgRczO1rKVcBwt4kEQhRUFYqbPgK1n4CWSkQPhp6vAg+5t+eKVcBwhEkEQiRJzcbtv0Af080hopu2B96vQJVGptetFwFCEeSRCBEThbsmgX/fAhnj0DNDnDbNKjZ3i7Fy1WAcDRJBMJ5ZWfA9ulGFVDSCajeCobPNoaGsMPsXRnZuXyxMpKvVh2WqwDhUJIIhPPJTIZt04zRQVNOQsh1xrAQ9XrZJQGAMUbQ87/uJiohlVvCgnj5xiZyFSAcRhKBcB5nj8GmSUYSyDwPoV3h1m+hdhe7JYCk9GzeXbKPmZtOEOLvzbTR7ejaINAuZQtxOZIIRNmmNZzYCOu/gP2LAAVNb4b2D0FwGzuGoVmy5ySvLtxLYkomY7vW4bHe9fHxkI+gcDx5F4qyKeM87P4Ftn4PJ3eBV0Xo+Ai0Gwt+QXYNJfpsGq8tjOCvfadoWqMC393dlmZB5k5XKURRSCIQZYfWxmBwW7+DPXMhO83oCTzgQ2g5DDzK2TWczJxcJv9zhM9WHEKheL5fI8Z0DsXNVeYLECWLJAJR+iXFwJ45sHO2MTOYezloPsSYIaxGa7vV/+f3z6EEXl2wl6jTqfRtWo2Xb2pCUEWZO1iUTKYmAqVUX+ATwBWYrLV+t8DrTwD3AjlAAjBaa33MzJhEGZF+DvYthF0/w9E1gIbgtsa3/+ZDjSEhHCAuKZ03F+3j991x1Arw4ft72tJdhooWJZxpiUAp5Qp8AfQBooHNSqmFWuuIfKttB8K11mlKqQeAicDtZsUkSrmM83DoD4hYAAeXQW4m+NeF7s8bVwABdR0WWmZOLt+tPcqnyw+Ra9E80acBY7vWwcvd3HGJhLAFM68I2gGRWusoAKXULGAQcCERaK1X5lt/AzDSxHhEaZR2Bg4shoiFELUScrOMeQDa3G3MBhbkmKqfPFprlu09yduL93P8TBq9GlXhtYFNCfH3cVhMQhSVmYkgCDiR73k0cN0V1h8DLLnUC0qpscBYgJo1a9oqPlFSnT0KB/+A/b/B0bWgc8GvJrS9D5oMNKqATB4BtDD2xCTxxqIINh45Q/0q5flhdDu6SZ8AUQqViMZipdRIIBzodqnXtdaTgEkA4eHh2o6hCXvIzTYmfj+4DA79CacPGMsD6kPnx4wZwKq3cug3//ziz2fw3rIDzNkWTSUfD964uRnD24bI3UCi1DIzEcQAIfmeB1uXXUQp1Rt4Eeimtc40MR5RkiSfgsg/jZN/1Cqjp6+rB9TqZFT7NLjBoXX+l5KamcOUNUf4+u/DZOdauK9LHR7qUQ8/b3dHhyZEsZiZCDYD9ZVSoRgJYBhwR/4VlFJhwDdAX611vImxCEfLyYQTm+DI38a3/rgdxnLfGtB0sHHiD+0GnuUdGualZOVYmLX5OJ8uj+R0SiY3NK3K8/0aU7uyffslCGEW0xKB1jpHKTUOWIZx++hUrfVepdR4YIvWeiHwHlAe+EUZl/3HtdYDzYpJ2JEl1zjZR/1tnPyPb4CcDFCuEBwOPV82Tv5Vm5WYKp+CLBbNb7ti+eCPgxw/k0a7UH++ubMNbWpVcnRoQtiUqW0EWuvFwOICy17J97i3meULO8rJgridcHydcdI/thYykozXqjQ1pnis0w1qdQSvkj28gtaaVQcSmLjsAPviztO4egW+u6ct3RsEokpo0hKiOEpEY7EohTJTIHoTHFtvNPRGb4GcdOO1gHrQZJBR1RPaFcqXng5VW4+dZcLS/Ww6coaa/j58MqwVN7WogYuLJABRdkkiEFeXkwmn9hjj+MTugNjtkLAPtAWUC1RrbjTw1upgzO5Vik78eXacOMfHfx1k1YEEKpf35I1BTbm9bU083OROIFH2SSIQF0s/Bwn7IX6fUccfux1ORYAl23jdJ8AYv6fRAGMqx5B24OnryIiLZceJc3zy10FWHkigko87z/RtyKgOtSnnKR8N4Tzk3e6sslL/PeHn/STsh/P57vD18oMaYdDxYeN3jTDwCy6xjbtFsfPEOT5ZfogV++OpaE0Ad3WoTXlJAMIJybu+LMtKg+Q4OB8LSdFGR628k/65fGP7uXlB5QbGTF1VGkGVJhDYCCrWLBMn/fwKJoCnb2jIqI6SAIRzk3d/aaQ1pJ81vr2fj4PkWONkfz723xP/+VjIOHfxdi5uRm/doDYQdue/J/1KtUvEkA1m0Vqz/nAiX646zJrI05IAhChAPgUljdbGCTwp2hhnP+mE8fh8jPUEHwPJJ4178i+ijEZa3+pQKdS4TdO3OlQIggrW3xVrgZvzTJBusWj+3HeKL1cdZueJcwT6evJ8v0aMaF9LEoAQ+cinwd5yMo2TeVL0pU/2SdGQlXLxNi7uUKGGcTIPamM89q3x7wnetzr4VgNXGeoAIDvXwsIdsXz992EOxadQ09+HtwY349bWwTIstBCXIInAliwWSE2A89H5TvQFflIvMZJGuUCjETagHtTpYTz2CwK/EONxuSrgIrcxXk1yRjY/b4lm6pojxJxLp1E1Xz4Z1ooBzavLgHBCXIEkgqLITLF+c7/MSf58jDFefn7uPtYTezBUawYVgv997hdsfLt3lykMi+NYYirfrzvKL1uiScnMIbxWJcYPakrPRlWkJ7AQheDciUBrYwjk7DSjzj0t0WhsTT5pbXSNu7gap2Djq3Ixqmj8gowJUpoMNL7FVwj690TvXanM3XlTEmitWR+VyNQ1R1m+/xRuLoobW9Tgnk61aRFc0dHhCVGqOE8i2PcbbPgazh3/98SfnWb0jr0cr4rW6pkQo/OUX/DFJ3rf6uDqPIewJDibmsW87THM3HScyPgU/Mt5MK5HPUa2r0XVCl6ODk+IUsl5zmJZqcaJv3YnoyrG3ce4f97d2/hx8wIf/38bXstXlSqbEkJrzcYjZ5i16TiL95wkK8dCq5CKTBzSgoEta0gDsBDF5DyJoOUw40eUGrHn0lmwI5Zftp4gKiEVXy83hrcNYVi7mjSuXsHR4QlRZjhPIhClwvmMbJbuPsmv22PYcCQRraFNrUq8P7QeA5pXx9tDvv0LYWuSCITDZeVYWH0wgV93xPBXxCkycyyEVi7HY70acHNYDWoFyExgQphJEoFwCItFs+XYWRbujOH3XXGcTcsmoJwHw9vV5OawIFoG+8mtn0LYiSQCYTdaa/bFJbNgZwy/7YglNikDb3dXejepyuCwGnSpH4i7dPwSwu4kEQjTnTiTxsKdsczfHsOh+BTcXBRdGwTybL9G9G5cVcb+F8LB5BMoTHE4IYUV++JZuvckW4+dBSC8ViXeuLkZA5pXx7+c8wx+J0RJJ4lA2ERGdi5bj51lxf54VuyP58jpVAAaVfPl6RsaMrBlDUL8fRwcpRDiUiQRiGuitebgqRT+OZTAP4dOs/FIIhnZFjzcXOhYN4DRnWrTo1EVgivJyV+Ikk4SgSiUnFwL+08ms/3EObYfO8uayNPEJ2cCUDewHMPa1qRL/cp0qBuAj4e8rYQoTeQTK/7jfEY2h04lc+hUCgdPpbAnNond0UmkZ+cCULm8B+3rBNC1fiCd61emRkUZikOI0sxpEoHWmuNn0py+c1JGdi7n0rJJSs/mdEom0WfTiD6bTvTZdGLOpnP8TBonz/87+5m3uysNq/kyrF0IYTUrERZSkeBK3nKPvxBliNMkgk+WH+KLlZFsf+X6Uj1NodaajGwLyZnZnE/PISk9m/Pp2ZxLzyIpLZuk9BzjcXq29bnxc876Oyvnv6Otuiio7udNUCVvOtYLoF6V8jSo4kuDqr4EV/LGxUVO+kKUZaX3jFhE7esE8PFfh1hzKIG+zarbvXyLRZOalUNaVi4pmTmkZuaQkpFDcmYOyRk5pGRkk5KZ/3kOKdZ1zltfy3ueY9FXLMvX040K3u74ebtT0cedelXKU9HH/d9l3h74ebvjX86D4EreVPPzko5cQjgxp0kEbWpVooKXGz9viaZpDb8rVm9orcnKtZCRbSHVetJOzco1Tt6ZOaRl5ZCSaTxPy/z3cWqWdd3M3AuPUzJzSbMmgMLwcHOhgpcb5T3dKG/9HeLvg6/1ua+XG+U93Snv5UYFLzf8rCd346TvQQUvN5mWUQhRJE6TCNxdXbgtPITJa46wYn88nm4uVC7viZurwlUpMnMspGfnkmH9ucqX7ouU83ClnKdx0vbxdKWchxvVKnjh4+lGeevzC4893Sjn4UY5z7yTuvHb18udcp6ueLrJ6JpCCPtymkQA8OKAxgxrV5P1UYkcT0zlTGo2ORYLuRaNp5sr3h4ueLm54uXuireHK55uLsaJ23oS9/EwTtzGydw4qXu7u0oduhCiVHOqRKCUol6V8tSrUt7RoQghRIlhamWyUqqvUuqAUipSKfXcJV73VErNtr6+USlV28x4hBBC/JdpiUAp5Qp8AfQDmgDDlVJNCqw2Bjirta4HfARMMCseIYQQl2bmFUE7IFJrHaW1zgJmAYMKrDMI+MH6eA7QS0lPJSGEsCszE0EQcCLf82jrskuuo7XOAZKAABNjEkIIUUCpuOFcKTVWKbVFKbUlISHB0eEIIUSZYmYiiAFC8j0Pti675DpKKTfAD0gsuCOt9SStdbjWOjwwMNCkcIUQwjmZmQg2A/WVUqFKKQ9gGLCwwDoLgVHWx0OAFVrrInTlEkIIUVym9SPQWucopcYBywBXYKrWeq9SajywRWu9EJgCTFdKRQJnMJKFEEIIO1Kl7Qu4UioBOHaNm1cGTtswHFspqXFByY1N4ioaiatoymJctbTWl6xbL3WJoDiUUlu01uGOjqOgkhoXlNzYJK6ikbiKxtniKhV3DQkhhDCPJAIhhHByzpYIJjk6gMsoqXFByY1N4ioaiatonCoup2ojEEII8V/OdkUghBCiAEkEQgjh5Ep9IlBKTVVKxSul9uRb1lIptV4ptVsp9ZtSqkK+1563zn9wQCl1Q77lV5w7wcy4lFJ9lFJbrcu3KqV65ttmlTWuHdafKnaMq7ZSKj1f2V/n26aNdf1IpdSnxR01tohxjcgX0w6llEUp1cr6mq2PV4hSaqVSKkIptVcp9ah1ub9S6k+l1CHr70rW5cp6PCKVUruUUq3z7WuUdf1DSqlRlyvTpLhGWOPZrZRap5RqmW9fR63Ldyilttg5ru5KqaR8/69X8u3LZp/Ja4jr6Xwx7VFK5Sql/K2v2ex4XSW2odbnFqVUeIFtbHse01qX6h+gK9Aa2JNv2Wagm/XxaOAN6+MmwE7AEwgFDmP0ena1Pq4DeFjXaWLHuMKAGtbHzYCYfNusAsIddLxq51+vwH42Ae0BBSwB+tkrrgLbNQcOm3i8qgOtrY99gYPW99FE4Dnr8ueACdbH/a3HQ1mPz0brcn8gyvq7kvVxJTvG1TGvPIw5Qjbm29dRoLKDjld3YNEl9mPTz2RR4yqw7U0Yw9/Y/HhdJbbGQMOC72lMOI/Z5A9x9A8FTlgYw1nnNYSHABHWx88Dz+dbbxnQwfqzLN/yi9YzO64C2yiM4TY8rc8vehPY+XhdtF6BN+7+fM+HA9846Hi9DbyV77nNj1eB8hYAfYADQPV8x+OA9fE3wPB86x+wvn7RMSq4ntlxFVi3Ehd/2TiKDU9sRTxe3bl0IjDlM3mNx+sn4D57HK/8seV7ftF7uuCxwAbnsVJfNXQZe/l3Epyh/DsK6uXmSCjM3AlmxpXfrcA2rXVmvmXfWS9DXy5uFcw1xBWqlNqulPpbKdXFuiwI4xjlceTxuh2YWWCZKcdLGVOphgEbgapa6zjrSyeBqtbHdn+PFTKu/MZgXLXk0cAfyqiWHGuLmIoYVwel1E6l1BKlVFPrshJxvJRSPkBfYG6+xaYcr0vEdjk2f4+V1UQwGnhQKbUV41Iry8Hx5LliXNYPwQTgf/kWj9BaNwe6WH/utGNccUBNrXUY8ATwk8rX3mIHVzte1wFpWus9+RabcryUUuUxTgaPaa3P539NG1+/HHIfdlHjUkr1wEgEz+Zb3Flr3RqjyughpVRXO8a1DWMMnJbAZ8D84pZto7jy3ASs1VqfybfM5sfrarGZrUwmAq31fq319VrrNhjfFg9bX7rcHAmFmTvBzLhQSgUDvwJ3aa0P59smxvo7GeMStZ294tJaZ2qtE62Pt1qXN8A4NsH5dmH342U1jAJXA2YcL6WUO8YH9Eet9Tzr4lNKqerW16sD8dbldnuPFTEulFItgMnAoLz/K1x0zOIx3oPFOmZFiUtrfV5rnWJ9vBhwV0pVpgQcL6srvcdscryuENvl2P49ZlY9lz1/+G/dchXrbxdgGjDa+rwpFzeyRGE0sLhZH4fybyNLUzvGVdFa5i0FtnfDWhcJuGPM63y/HeMKBFytj+tY31T+1ucFG4v72yuufMtigDpmHi/r3zcN+LjA8ve4uJFxovXxAC5uLN5kXe4PHMGon69kfexvx7hqApFAxwLrlwN88z1eB/S1Y1zV+LcdqB1w3LoPm34mixqX9bkfRntdObOO15Viy/f6Ki5uI7D5eaxYH9yS8IORreOAbIw6sTHAoxgt7weBd/PeaNb1X8T4ZnmAfHe6YNztcdD62ov2jAt4CUgFduT7qWJ9o20FdmHUl3+C9cRsp7hutZa7A+MS/qZ8+wkH9liP1+f5j7Gd/o/dgQ0F9mHG8eqMUV2wK9//pj/G3NrLgUPAX/ybIBXwhfW47C7wAR6NcTKOBO6xc1yTgbP51t1iXV4H44Sx03rMivXev4a4xlnL3QlsIF+iwoafyaLGZd3mbmBWgf3Y9HhdJbbBGJ+FTOAUFzcE2/Q8JkNMCCGEkyuTbQRCCCEKTxKBEEI4OUkEQgjh5CQRCCGEk5NEIIQQTk4SgRCXoZQKyDcC5UmlVIz1cYpS6ktHxyeErcjto0IUglLqNSBFa/2+o2MRwtbkikCIIrKOob/I+vg1pdQPSql/lFLHlFK3KKUmWserX2odOiBv/oa/rQOVLcsb1kCIkkASgRDFVxfoCQwEZgArtTHwXTowwJoMPgOGaGPcpKnAW44KVoiC3BwdgBBlwBKtdbZSajfGmC9Lrct3Y4yf1BBjwqE/raNiu2IMpyFEiSCJQIjiywTQWluUUtn634Y3C8ZnTAF7tdYdHBWgEFciVUNCmO8AEKiU6gDGkMP5JmARwuEkEQhhMq11FjAEmKCU2okxumRHhwYlRD5y+6gQQjg5uSIQQggnJ4lACCGcnCQCIYRwcpIIhBDCyUkiEEIIJyeJQAghnJwkAiGEcHL/BwBCHnwK9i43AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "scales = {\n",
+    "    \"nrfr\": 1,\n",
+    "    \"iopc\": 1e3,\n",
+    "    \"fpc\": 1e3,\n",
+    "    \"pop\": 16e9,\n",
+    "    \"ppolx\": 32\n",
+    "}\n",
+    "s = dno.parse_system.system_from_file('world3/world3_pydynamo_code.py')\n",
+    "s.ali = s.ali*2\n",
+    "s.update_ppolx = lambda: 0\n",
+    "s.update_nrfr = lambda: 1\n",
+    "s.update_ler = lambda: 0\n",
+    "s.run(400, 0.5)\n",
+    "dno.plot_system.plot_system(s, ['iopc', 'pop', 'fpc'], rescale=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fd737bdd880>]"
+      ]
+     },
+     "execution_count": 86,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(np.log(s.pop))\n",
+    "plt.plot(np.log(s.iopc))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dno.plot_system.plot_system(s, ['f', 'al', 'ly'], rescale=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# PERFS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 89,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%reload_ext autoreload\n",
+    "%autoreload 2\n",
+    "import pydynamo as dno\n",
+    "from world3.plot_utils import plot_world_with_scales"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 422 ms, sys: 0 ns, total: 422 ms\n",
+      "Wall time: 422 ms\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "dno.dynamo_converter.convert_dynamo_file(\n",
+    "    'world3/world3_DYNAMO_code.py',\n",
+    "    'world3/world3_pydynamo_code.py')\n",
+    "s = dno.parse_system.system_from_file('world3/world3_pydynamo_code.py')\n",
+    "%time s.run(N=800, dt=0.25)\n",
+    "plot_world_with_scales(s)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " \n",
+      "*** Profile stats marshalled to file '/tmp/tmp7yno8j8h'. \n",
+      "Embedding SnakeViz in this document...\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<iframe id='snakeviz-450402dc-61a6-11ec-888f-dd1588b97d85' frameborder=0 seamless width='100%' height='1000'></iframe>\n",
+       "<script>document.getElementById(\"snakeviz-450402dc-61a6-11ec-888f-dd1588b97d85\").setAttribute(\"src\", \"http://\" + document.location.hostname + \":8080/snakeviz/%2Ftmp%2Ftmp7yno8j8h\")</script>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%load_ext snakeviz\n",
+    "%snakeviz s.run(800, 0.25)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 190,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Thu Dec 16 17:39:45 2021    stats\n",
+      "\n",
+      "         629552 function calls in 1.802 seconds\n",
+      "\n",
+      "   Ordered by: cumulative time\n",
+      "\n",
+      "   ncalls  tottime  percall  cumtime  percall filename:lineno(function)\n",
+      "        1    0.000    0.000    1.880    1.880 {built-in method builtins.exec}\n",
+      "        1    0.001    0.001    1.880    1.880 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/system.py:473(run)\n",
+      "      799    0.178    0.000    1.858    0.002 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/system.py:382(_update_all_fast)\n",
+      "   119200    0.154    0.000    1.601    0.000 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/system.py:416(update)\n",
+      "    36798    0.096    0.000    1.195    0.000 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/specials.py:86(__call__)\n",
+      "    36965    0.993    0.000    0.993    0.000 {built-in method builtins.dir}\n",
+      "    36798    0.109    0.000    0.109    0.000 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/specials.py:90(call_i)\n",
+      "    16800    0.075    0.000    0.075    0.000 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/specials.py:30(clip)\n",
+      "     3200    0.070    0.000    0.070    0.000 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/delays.py:130(__call__)\n",
+      "   119051    0.069    0.000    0.069    0.000 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/system.py:390(<dictcomp>)\n",
+      "   120606    0.021    0.000    0.021    0.000 {built-in method builtins.getattr}\n",
+      "   119200    0.013    0.000    0.013    0.000 {method 'items' of 'dict' objects}\n",
+      "     3998    0.006    0.000    0.006    0.000 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/delays.py:52(__call__)\n",
+      "        1    0.001    0.001    0.006    0.006 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/system.py:335(_init_all)\n",
+      "        1    0.000    0.000    0.004    0.004 /home/achille/Bureau/couillet/world3/pydynamo/pydynamo/system.py:446(change_functions_in_dict)\n",
+      "      676    0.000    0.000    0.003    0.000 /home/achille/.local/lib/python3.8/site-packages/networkx/algorithms/dag.py:182(topological_sort)\n",
+      "       96    0.001    0.000    0.003    0.000 /home/achille/.local/lib/python3.8/site-packages/networkx/algorithms/dag.py:105(topological_generations)\n",
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+      "\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<pstats.Stats at 0x7fa59e2d25e0>"
+      ]
+     },
+     "execution_count": 190,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import cProfile\n",
+    "import pstats\n",
+    "from pstats import SortKey\n",
+    "cProfile.run('s.run(800, 0.25)', 'stats')\n",
+    "p = pstats.Stats('stats')\n",
+    "p.sort_stats(SortKey.CUMULATIVE)\n",
+    "p.print_stats()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.09.BTmodel.ipynb b/12.09.BTmodel.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..13bb812ee9ae1bfb9cf849205c7c1af2c594893c
--- /dev/null
+++ b/12.09.BTmodel.ipynb
@@ -0,0 +1,323 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Brand and Taylor model\n",
+    "- Brander, James A., Taylor, M. Scott, 1998. The simple economics of Easter Island\n",
+    "- From several hypothesis:\n",
+    "    - Schaefer harvest production\n",
+    "    - Fertility prop to consumption/labor\n",
+    "    - Ricardo production structure\n",
+    "    - Logistic (or compensatory) eqs for nature regeneration\n",
+    "- Leads to Lotka Voltera equation\n",
+    "- Applied to Easter Island population"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pydynamo\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def BTmodel_eqs():\n",
+    "    beta = 0.4 # Proportion of labor dedicated to harvest\n",
+    "    r = 0.04 # Nature repoduction speed rate\n",
+    "    b_d = -0.1 # Default birth rate minus death rate\n",
+    "    phi = 4 # Fertility per consumption per worker\n",
+    "    K = 12_000 # Nature maximal carrying capacity\n",
+    "    alpha = 1e-5 # Harvest labor efficiency per resource avalability\n",
+    "\n",
+    "    S.i = K\n",
+    "    L.i = 50\n",
+    "    S.k = S.j + dt*(S.j*r*(1 - S.j/K) - H.j) # Resource\n",
+    "    L.k = L.j + dt*L.j*(b_d + F.k) # Labor force (~ population)\n",
+    "    H.k = alpha*beta*L.j*S.k # Harvest\n",
+    "    F.k = phi*H.k/L.j # Fertility\n",
+    "    \n",
+    "    W.k = L.k/H.k # Welath per capita"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = pydynamo.parse_system.system_from_fun(BTmodel_eqs)\n",
+    "s.run(N=300, dt=1)\n",
+    "pydynamo.plot_system(s, ['S', 'L'])\n",
+    "plt.title('Nature and population dynamics on Easter Island');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Add user defined functions and change constants"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def update_F(H_k, L_j, phi, d_br_k, b_d):\n",
+    "    \"\"\"Fertility\n",
+    "    Fertility is designed to reach -b_d when the desired birth_rate is null.\n",
+    "    \"\"\"\n",
+    "    return (H_k*phi/L_j + b_d)*d_br_k - b_d\n",
+    "\n",
+    "def update_d_br(L_j, o_L):\n",
+    "    \"\"\"Desired Birth Rate\n",
+    "    A normalized distance to the optimal population value.\"\"\"\n",
+    "    return (o_L - L_j)/o_L"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s.update_F = update_F\n",
+    "s.update_d_br = update_d_br\n",
+    "\n",
+    "s.o_L = 7000\n",
+    "s.run(300, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pydynamo.plot_system(s, ['S', 'L', 'd_br'], rescale = True)\n",
+    "plt.title('Optimal Desired Population scenario');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"500px\"\n",
+       "            height=\"500px\"\n",
+       "            src=\"ex.html\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x7fa308a352e0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pydynamo.show_pyvis(s, notebook=True, options=[], quotient=True).show('ex.html')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Add birth rate depending one industrial ouput"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = pydynamo.parse_system.system_from_fun(BTmodel_eqs)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def update_F(H_k, L_j, phi, d_br_k, b_d):\n",
+    "    \"\"\"Fertility\n",
+    "    Fertility is designed to reach -b_d when the desired birth_rate is null.\n",
+    "    \"\"\"\n",
+    "    return (H_k*phi/L_j + b_d)*d_br_k - b_d\n",
+    "\n",
+    "import numpy as np\n",
+    "def bmw(W, CW):\n",
+    "    bws = 8\n",
+    "    bwa = 2\n",
+    "    return -np.tanh((W - CW)/bws + bwa)/2 + 0.5\n",
+    "\n",
+    "def update_d_br(W_j, n_br, i_br, cw):\n",
+    "    \"\"\"Desired Birth Rate\n",
+    "    Depends on welfare, normal and ideal birth rate.\"\"\"\n",
+    "    return i_br + (n_br - i_br)*bmw(W_j, cw)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s.update_F = update_F\n",
+    "s.update_d_br = update_d_br\n",
+    "s.n_br = 2\n",
+    "s.i_br = 1\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "<ipython-input-11-e1868c25e298>:11: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
+      "  plt.subplot(2, 1, 1)\n",
+      "<ipython-input-11-e1868c25e298>:13: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
+      "  plt.subplot(2, 1, 2)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x720 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s.cw = 100\n",
+    "s.run(300, 1)\n",
+    "plt.figure(figsize=(7, 10))\n",
+    "plt.subplot(2, 1, 1)\n",
+    "pydynamo.plot_system(s, ['L', 'S'],rescale = False)\n",
+    "plt.title('Desired birth rate decreasing with wealth scenario');\n",
+    "plt.subplot(2, 1, 2)\n",
+    "pydynamo.plot_system(s, ['W', 'cw'],rescale = False)\n",
+    "s.cw = 40\n",
+    "s.run(300, 1)\n",
+    "plt.subplot(2, 1, 1)\n",
+    "pydynamo.plot_system(s, ['L', 'S'],rescale = False)\n",
+    "plt.subplot(2, 1, 2)\n",
+    "pydynamo.plot_system(s, ['W', 'cw'],rescale = False)\n",
+    "\n",
+    "# plt.legend('')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Wt = np.linspace(0, 100, 100)\n",
+    "plt.plot(Wt, update_d_br(Wt, s.n_br, s.i_br, s.cw))\n",
+    "plt.axvline(s.cw, linestyle='--')\n",
+    "plt.title('Desired fertility and wealth')\n",
+    "plt.xlabel('Wealth per capita')\n",
+    "plt.ylabel('Desired birth rate');"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.10.python_roue_libre.ipynb b/12.10.python_roue_libre.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..4c5dfa8cfbc2c06c132df4ef2611ff00793090d7
--- /dev/null
+++ b/12.10.python_roue_libre.ipynb
@@ -0,0 +1,212 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Bi dictionnary\n",
+    "- TODO: init with inverse : {a: {b, c}} -> {b:a, c:a}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class bidic(dict):\n",
+    "    def __init__(self, *args, **kwargs):\n",
+    "        super(bidic, self).__init__(*args, **kwargs)\n",
+    "    def __setitem__(self, index, values):\n",
+    "        if index.__hash__:\n",
+    "            super(bidic, self).__setitem__(index, values)\n",
+    "        else:\n",
+    "            for i in index:\n",
+    "                super(bidic, self).__setitem__(i, values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'a': 2, 'b': 3, 'c': 4, 'd': 4}"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "d = bidic(a=2)\n",
+    "d['b']  =3\n",
+    "d[{'c', 'd'}] = 4\n",
+    "d"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Special assignement fcts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class S:\n",
+    "    class V:\n",
+    "        def __init__(self, v):\n",
+    "            self.v = v\n",
+    "        def __repr__(self):\n",
+    "            return f'#{self.v}'\n",
+    "            \n",
+    "    def __init__(self):\n",
+    "        pass\n",
+    "    \n",
+    "    def __setattr__(self, name, expr):\n",
+    "        print(expr)\n",
+    "        if isinstance(expr, S.V):\n",
+    "            print(\"Assignement variable\")\n",
+    "            super.__setattr__(self, name, expr)\n",
+    "        else:\n",
+    "            print(\"Assignement normal\")\n",
+    "            super.__setattr__(self, name, expr)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3\n",
+      "Assignement normal\n",
+      "#4\n",
+      "Assignement variable\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(3, #4)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a = S()\n",
+    "a.rien = 3\n",
+    "a.v1 = S.V(4)\n",
+    "a.rien, a.v1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Write equations in function"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Inspect given function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def upeq():\n",
+    "    c = 1.01\n",
+    "    d.i = 1\n",
+    "    d.k = d.j*c"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pydynamo.parse_equations as pe \n",
+    "import re\n",
+    "import ast\n",
+    "def get_pars_fun(f):\n",
+    "    ls = [re.sub('^ *', '', l) for l in inspect.getsource(f).split('\\n')[1:]]\n",
+    "    pars = {t:{} for t in ('cst', 'update', 'init')}\n",
+    "    for l in ls:\n",
+    "        for t in pars:\n",
+    "            try:\n",
+    "                node, args = pe.get_pars_eq(l, t)\n",
+    "                pars[t][node] = args\n",
+    "            except Exception as e:\n",
+    "                pass\n",
+    "    return pars"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'cst': {'c': {'args': {'cst': set(), 'var': set(), 'fun': {}},\n",
+       "   'line': '1.01'}},\n",
+       " 'update': {'d': {'args': {'cst': {'c'}, 'var': {('d', 'j')}, 'fun': {}},\n",
+       "   'line': '(d_j * c)'}},\n",
+       " 'init': {'d': {'args': {'cst': set(), 'var': set(), 'fun': {}}, 'line': '1'}}}"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "get_pars_fun(upeq)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.12.from_diff_eqs.ipynb b/12.12.from_diff_eqs.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..04d1d7dd2795672f07e8855f5b35263df65e973f
--- /dev/null
+++ b/12.12.from_diff_eqs.ipynb
@@ -0,0 +1,208 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# En fait, ça change tout\n",
+    "- Voir pysindy et odeint "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<module 'pydynamo.parse_equations' from '/home/achille/Bureau/couillet/world3/pydynamo/pydynamo/parse_equations.py'>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pydynamo as dno\n",
+    "import networkx as nx\n",
+    "from importlib import reload\n",
+    "reload(dno)\n",
+    "reload(dno.parse_equations)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def hubbert_eqs():\n",
+    "    # Hubbert model\n",
+    "    capitali = 0.01 # Initial captial\n",
+    "    resourcei = 1 # Initial resource\n",
+    "\n",
+    "    rcr = 4/3 # Resource consumption rate\n",
+    "    rrr = 0 # Resource reprodution rate\n",
+    "    crr = 4 # Capital reproduction rate\n",
+    "    cdr = 1 # Capital dissipation rate\n",
+    "\n",
+    "    resource.d = (-rcr*capital*resource + rrr*resource) # Resource\n",
+    "    capital.d = (crr*capital*resource - cdr*capital) # Capital\n",
+    "    \n",
+    "    capital.i = capitali \n",
+    "    resource.i = resourcei"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "('resource',\n",
+       " {'args': {'fun': {}, 'var_cst': {'capital', 'rcr', 'resource', 'rrr'}},\n",
+       "  'line': '((((- rcr) * capital) * resource) + (rrr * resource))'})"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "line = 'resource.d = (-rcr*capital*resource + rrr*resource) # Resource'\n",
+    "dno.parse_equations.get_pars_diff_eq(ast.parse(line))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'cst': {'capitali': {'args': {'cst': set(), 'var': set(), 'fun': {}},\n",
+       "   'line': '0.01'},\n",
+       "  'resourcei': {'args': {'cst': set(), 'var': set(), 'fun': {}}, 'line': '1'},\n",
+       "  'rcr': {'args': {'cst': set(), 'var': set(), 'fun': {}}, 'line': '(4 / 3)'},\n",
+       "  'rrr': {'args': {'cst': set(), 'var': set(), 'fun': {}}, 'line': '0'},\n",
+       "  'crr': {'args': {'cst': set(), 'var': set(), 'fun': {}}, 'line': '4'},\n",
+       "  'cdr': {'args': {'cst': set(), 'var': set(), 'fun': {}}, 'line': '1'}},\n",
+       " 'update': {},\n",
+       " 'init': {'capital': {'args': {'cst': {'capitali'}, 'var': set(), 'fun': {}},\n",
+       "   'line': 'capitali'},\n",
+       "  'resource': {'args': {'cst': {'resourcei'}, 'var': set(), 'fun': {}},\n",
+       "   'line': 'resourcei'}}}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import inspect\n",
+    "import re\n",
+    "import ast\n",
+    "lines =[re.sub('^ *', '', l)\n",
+    "            for l in inspect.getsource(hubbert_eqs).split('\\n')[1:]]\n",
+    "n, e, c = dno.parse_system.get_nodes_eqs_dicts(lines)\n",
+    "e"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "G = nx.DiGraph()\n",
+    "G.add_edges_from([('b', 'a'),\n",
+    "                  ('c', 'a'),\n",
+    "                  ('a', 'd'),\n",
+    "                  ('e', 'c'),\n",
+    "                  ('d', 'b'),\n",
+    "                  ('a', 'c'),\n",
+    "                  ('a', 'a')])\n",
+    "nx.draw(G, with_labels=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "807 µs ± 256 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from utils import get_updating_scheme\n",
+    "%timeit -n 100 gg = get_updating_scheme(G, T=10)\n",
+    "nx.draw(gg, with_labels=True)\n",
+    "nx.is_directed_acyclic_graph(gg)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.15.Footprint.ipynb b/12.15.Footprint.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..9d8e74decba207df5f342bd2e3947cedeabea401
--- /dev/null
+++ b/12.15.Footprint.ipynb
@@ -0,0 +1,453 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# World model with footprint"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<module 'pydynamo.parse_system' from '/home/achille/Bureau/couillet/world3/pydynamo/pydynamo/parse_system.py'>"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pydynamo as dno\n",
+    "import importlib\n",
+    "importlib.reload(dno.system)\n",
+    "importlib.reload(dno.parse_system)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Base equations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def eqs():\n",
+    "    Ai = 1# Initial Antropo\n",
+    "    Ci = 1 # Initial earth biocapacity\n",
+    "    Ri = 200*Ci # Earth biocapacity stock\n",
+    "    \n",
+    "    cm = 0.04/Ai # Minimum required consumption\n",
+    "    cu = 0.07/Ai # Usual consumption\n",
+    "    cM = 0.15/Ai # Maximal labor\n",
+    "    \n",
+    "    A.i = Ai\n",
+    "    R.i = Ri\n",
+    "    C.i = 1\n",
+    "    \n",
+    "    start_date=1900\n",
+    "\n",
+    "    C.k = C.j # Earth biocapacity\n",
+    "    A.k = A.j + Y.k - A.j*cm # Antropo\n",
+    "    Y.k = yr(g.k*E.k, C.j, Ci) + yn((1-g.k)*E.k, R.j, Ri) # Wealth\n",
+    "    R.k = R.j - (1-g.k)*E.k # Resource stock\n",
+    "    g.k = choose_g(A.j, R.j, Ri, C.j, Ci, cm, cu, cM) # Prop in renewable\n",
+    "    E.k = choose_E(A.j, R.j, Ri, C.j, Ci, cm, cu, cM) # Energy invested"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def choose_g(A, R, Ri, C, Ci, cm, cu, cM):\n",
+    "    return choose_gE(A, R, Ri, C, Ci, cm, cu, cM)[0]\n",
+    "\n",
+    "def choose_E(A, R, Ri, C, Ci, cm, cu, cM):\n",
+    "    return choose_gE(A, R, Ri, C, Ci, cm, cu, cM)[1]\n",
+    "\n",
+    "def choose_gE(A, R, Ri, C, Ci, cm, cu, cM):\n",
+    "    \"\"\"\n",
+    "    Choose Energy invested and gamma parameter,\n",
+    "    according to some strategy.\n",
+    "    \"\"\"\n",
+    "    if A*cu < C:\n",
+    "        return (1, A*cu)\n",
+    "    E = (A*cu - C)*R/Ri + C\n",
+    "    return (C/E, E)\n",
+    "\n",
+    "def yr(e, c, ci):\n",
+    "    \"\"\"Get obtained renewable resources \n",
+    "    if we invest energy e, \n",
+    "    and earth has biocapacity c\"\"\"\n",
+    "    return min(e, c)\n",
+    "\n",
+    "def yn(e, r, ri):\n",
+    "    \"\"\"Get obtained non renewable resources \n",
+    "    if we invest energy e, \n",
+    "    its remaining n resources over ni at initial\"\"\"\n",
+    "    return e*r/ri"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Base simulation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = dno.parse_system.system_from_fun(eqs)\n",
+    "s.add_functions(choose_g, choose_E, yr, yn)\n",
+    "\n",
+    "s.run(300, 1)\n",
+    "dno.plot_system.plot_system(s, scales={'R':s.Ri/40, 'g':1/40, 'Y':1/10, 'E':1/10, 'C':1/40})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Add pollution term"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def add_pol():\n",
+    "    regen = 0.1\n",
+    "    pol = 0.03\n",
+    "    C.i = Ci\n",
+    "    C.k = max(C.j + dt*(regen*C.j*(1 - C.j/Ci)) - E.k/Ci*pol, 0.1) # Earth biocapacity"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = dno.parse_system.system_from_fun(add_pol, s)\n",
+    "s.run(300, 1)\n",
+    "dno.plot_system.plot_system(s, scales={'R':s.Ri/40, 'g':1/40, 'Y':1/10, 'E':1/10, 'C':1/40, 'Ci':1/40})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy.optimize import minimize as mn"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def choose_gE(A, R, Ri, C, Ci, cm, cu, cM):\n",
+    "    \"\"\"\n",
+    "    Startegy for the optimal solution.\n",
+    "    \"\"\"\n",
+    "    beta = 0.001\n",
+    "    def rich_and_lazy(x):\n",
+    "        g, e = x\n",
+    "        Y = yr(e*g, C, Ci) + yn((1-g)*e, R, Ri)\n",
+    "        try:\n",
+    "            return (Y - A*cu)**2 + beta*1/(1 - A*cM/e)**2\n",
+    "        except:\n",
+    "            return 1e16\n",
+    "    e0 = A*cu\n",
+    "    g0 = 1\n",
+    "    opt =  mn(rich_and_lazy, (g0, e0), bounds=([0, 1], [0, A*cM]))\n",
+    "    g, e = opt.x\n",
+    "    return g, e"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 50.0)"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = dno.parse_system.system_from_fun(add_pol, s)\n",
+    "s.cm = 0.06\n",
+    "s.cu = 0.15\n",
+    "s.cM = s.cu + 0.002\n",
+    "s.run(200, 1)\n",
+    "dno.plot_system.plot_system(s, scales={'R':s.Ri/40, 'g':1/40, 'Y':1/10, 'E':1/10, 'C':1/40})\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.ylim([0, 50])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# New Footprint"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Base equations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 168,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def eqs():\n",
+    "    BM = 1\n",
+    "    B.i = BM\n",
+    "    B.k = max(B.j - A.k*dt + 1.989*B.j*(1 - B.j/BM)*dt, 0)\n",
+    "    AM = 0.01\n",
+    "    A.k = A.j + (B.j-A.j)*dt*0.01\n",
+    "    A.i = AM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 171,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = dno.parse_system.system_from_fun(eqs)\n",
+    "s.run(700, 1)\n",
+    "dno.plot_system.plot_system(s)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 311,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def eqs():\n",
+    "    aug = 0.1\n",
+    "    ptime = 5\n",
+    "    \n",
+    "    ai = 0.01\n",
+    "    a.i = ai\n",
+    "    v.k = 0.003\n",
+    "    e.k = (a.k - o.k + v.k)*nos.k\n",
+    "    a.k = a.j + e.j\n",
+    "    o.k = o.j + dt*(a.j - o.j)\n",
+    "    o.i = ai\n",
+    "    \n",
+    "    no.k = noi - o.k\n",
+    "    nos.k = nos.j + nos.j*(1-nos.j/no.j)*dt - max(e.j, 0)*dt\n",
+    "    nos.i = noi\n",
+    "    noi = 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 316,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = dno.parse_system.system_from_fun(eqs)\n",
+    "s.run(800, 1)\n",
+    "dno.plot_system.plot_system(s)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 397,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (<ipython-input-397-5bbd89179b88>, line 4)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-397-5bbd89179b88>\"\u001b[0;36m, line \u001b[0;32m4\u001b[0m\n\u001b[0;31m    a.k = a.j + dt*a.j*(e.k + 0*o.k/2 - 1*2.a.j)\u001b[0m\n\u001b[0m                                            ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
+     ]
+    }
+   ],
+   "source": [
+    "def eqs():\n",
+    "    ai = 0.01\n",
+    "    a.i = ai\n",
+    "    a.k = a.j + dt*a.j*(e.k + 0*o.k/2 - 1a.j)\n",
+    "    e.k = a.j*3*nos.j\n",
+    "    dol.k = a.j*0.1*no.j # Differential land occupation\n",
+    "    \n",
+    "    l = 1\n",
+    "    nos.i = 1\n",
+    "    o.i = ai\n",
+    "    o.k = o.j + dol.j # Occupied land\n",
+    "    no.k = l - o.k #  Non occupied land\n",
+    "    efto.k = dol.k*nos.k/no.k # Extraction from transformation to occupied\n",
+    "    \n",
+    "    nos.k = nos.j + dt*(- e.k + nos.j*(1 - nos.j/no.j)) - efto.j # Non occupied resources"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 396,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fe8b2184160>"
+      ]
+     },
+     "execution_count": 396,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x504 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = dno.parse_system.system_from_fun(eqs)\n",
+    "s.ptime = 3\n",
+    "s.run(1000, 0.1)\n",
+    "plt.figure(figsize=(15, 7))\n",
+    "dno.plot_system.plot_system(s, scales= {'a':1})\n",
+    "plt.legend(loc='upper right')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.17.Negawatt.ipynb b/12.17.Negawatt.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e5ded42cb6f48ce26762d0a0944d2417015c1a8a
--- /dev/null
+++ b/12.17.Negawatt.ipynb
@@ -0,0 +1,192 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Voir si le scenario correspond a ce qui se passe adj"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pydynamo import get_w3, plot_world_with_scales\n",
+    "s = get_w3()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Explore differences with reality"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Current population is about 7.8B, standart models one is 8,056,890,754.954897'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.run(400, 0.5)\n",
+    "pop_st = s.pop[s.time == 2020][0]\n",
+    "f'Current population is about 7.8B, standart models one is {pop_st:,}'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Current population is about 7.8B, x2 resource one is 8,121,341,444.105893'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.nri = 2e12\n",
+    "s.ppgf2 = 0.25\n",
+    "s.run(400, 0.5)\n",
+    "pop_st = s.pop[s.time == 2020][0]\n",
+    "f'Current population is about 7.8B, x2 resource one is {pop_st:,}'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Iopc started from 5 (1970) to 15 (2020)\n",
+      "But is from 194 to 357 with x2 resource scenario\n"
+     ]
+    }
+   ],
+   "source": [
+    "# https://ourworldindata.org/grapher/maddison-data-gdp-per-capita-in-2011us-single-benchmark?time=1900..latest&country=~OWID_WRL\n",
+    "iopc_2_70 = int(s.iopc[s.time == 1970][0])\n",
+    "iopc_2_20 = int(s.iopc[s.time == 2020][0])\n",
+    "print(f\"\"\"Iopc started from 5 (1970) to 15 (2020)\n",
+    "But is from {iopc_2_70} to {iopc_2_20} with x2 resource scenario\"\"\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# See how to impact on pollution and renewables (voir cahier)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Design scenario"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'plot_world_with_scales' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-5-02fa24ab07a8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;31m# s.pet = 2020\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m400\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mplot_world_with_scales\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m: name 'plot_world_with_scales' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "s.set_all_csts()\n",
+    "pyear = 2020\n",
+    "s.nri=2e12\n",
+    "s.pyear = 2020\n",
+    "s.ppgf2 = 1/4\n",
+    "s.icet = 2020\n",
+    "# s.pet = 2020\n",
+    "s.run(400, 0.5)\n",
+    "plot_world_with_scales(s)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "clip(icir2_k, (io_k * fioai_k), time_k, icet)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "v = ''\n",
+    "print(s.eqs['update'][v]['line'])\n",
+    "# print(s.get_comment(v))\n",
+    "dno.plot_system.plot_system(s, v)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "dnovenv",
+   "language": "python",
+   "name": "dnovenv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/12.20.TP.ipynb b/12.20.TP.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..83fa60fb936e26e1f98bc8cef41419b501ff65c0
--- /dev/null
+++ b/12.20.TP.ipynb
@@ -0,0 +1,52 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TP World3\n",
+    "## Comprendre monde\n",
+    "* croissance -> + conso + pop\n",
+    "* conso -> extraction, pollution\n",
+    "    * standart model\n",
+    "    * courbes PIB et extraction et émissions\n",
+    "* resources finies\n",
+    "    * cahrbon etc\n",
+    "* fin de resource -> plus cher de produire\n",
+    "    * pétrole schiste\n",
+    "* +pol -> plus cher de produire\n",
+    "    * nettoyage etc\n",
+    "* -terres dispo -> plus cher de produire\n",
+    "    * voir dans w3\n",
+    "## Voir solutions\n",
+    "* réduction part\n",
+    "\n",
+    "## À faire\n",
+    "* +mecanisme: limite des renouvelables\n",
+    "* conversion scénatio negawatt en terme de resources\n",
+    "* faire avec footprint"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/experiments.ipynb b/experiments.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..7358947788c31693d6fd3a71007d7992799d0e6c
--- /dev/null
+++ b/experiments.ipynb
@@ -0,0 +1,277 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# Expériences"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pydynamo import get_w3, plot_world_with_scales, var_color,  plot_world_03, parse_system, plot_system\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Changement de pratiques agricoles\n",
+    "## Passage au bio\n",
+    "Le passage au bio se différencie de l'agriculture conventionelle par ces aspects:\n",
+    "1. Intrants agricoles moins polluants\n",
+    "2. Moins d'intrants agricoles\n",
+    "3. Plus grande part des investissements agricoles allouées à la maintenance (légère)\n",
+    "\n",
+    "Des mesures sont a réaliser pour quantifier ces variables, mais c'est l'idée\n",
+    "\n",
+    "1. Les variables **fipm**: *fraction of inputs as persistent materials* et **amti**: *agricultural materials toxicity index* sont à baisser \n",
+    "2. et 3. Une plus grande part des investissements agricoles sont alloués à la maintenance (augmenter **falm**: *fraction of inputs alocated to land maintenance*) à partir d'un moment, ce qui baisse mécaniquement les intrants agricoles.\n",
+    "\n",
+    "- introduire une **bioyear**\n",
+    "- à partir de **bioyear**, **fipm** et **amti** changent pour des valeurs plus faibles\n",
+    "- à partir de **bioyear**, on augmente **falm**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.001 1\n"
+     ]
+    }
+   ],
+   "source": [
+    "w3 = get_w3()\n",
+    "w3.run(400, 0.5)\n",
+    "print(w3.fipm, w3.amti)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def bio_equations():\n",
+    "    fipm.k = clip(fipm_bio, fipm_conv, time.k, bio_year) # Fraction of inputs as persistent materials\n",
+    "    fipm_conv = 0.001\n",
+    "    fipm_bio = fipm_conv/2\n",
+    "    \n",
+    "    amti.k = clip(amti_bio, amti_conv, time.k, bio_year) # Agricultural materials toxicity index\n",
+    "    amti_conv = 1\n",
+    "    amti_bio = amti_conv/2\n",
+    "    \n",
+    "    ppgao.k = aiph.k * al.k * fipm.k * amti.k # Persistent pollution generation from agriculture\n",
+    "    bio_year = 2020 # Année de passage au bio\n",
+    "    \n",
+    "    falm.k = clip(falm_bio.k, falm_conv.k, time.k, bio_year) # Fraction of inputs alocated to land maintenance\n",
+    "    falm_bio.k = tabhl(falmt, pfr.k, 0, 4, 1)*2\n",
+    "    falm_conv.k = tabhl(falmt, pfr.k, 0, 4, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = parse_system.system_from_fun(bio_equations, get_w3())\n",
+    "w3.nri = 2e12\n",
+    "s.nri = 2e12\n",
+    "w3.run(400, 0.5)\n",
+    "s.run(400, 0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_world_with_scales(w3)\n",
+    "plot_world_with_scales(s, title='Organic transition in 2020')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 1.0)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure()\n",
+    "plot_system(w3, ['falm', 'ppgao', 'ai'], scales={'ai':5e11, 'ppgao':5e8, 'falm': 0.4})\n",
+    "plt.ylim([0, 1])\n",
+    "plt.figure()\n",
+    "plot_system(s, ['falm', 'ppgao', 'ai'], scales={'ai':5e11, 'ppgao':5e8, 'falm': 0.4})\n",
+    "plt.ylim([0, 1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "on a donc legèrement plus de nourriture par personne"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Agro-écologie\n",
+    "En plus du bio, ces pratiques diffèrent cette fois radicalement des partiques conventionelles. Les intrants agricoles sont quasiment nuls, la regénration de la terre est cette fois indifférente à la présence ou non de cultures et la prodctivité par hectare est ... réduite. Implémenter ce scénario est plus difficile."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Test avec new politic"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "s = get_w3()\n",
+    "def reduce_tox():\n",
+    "    amti.k = clip(amti_bio, amti_conv, time.k, bio_year) # Agricultural materials toxicity index\n",
+    "    amti_conv = 1\n",
+    "    amti_bio = amti_conv/2\n",
+    "\n",
+    "s.run(400, 0.5)\n",
+    "scales={'f':1e12, 'fpc':200, 'pop':1e9, 'ppgao':1e8}\n",
+    "plt.figure(figsize=(15,5))\n",
+    "plt.subplot(1, 3, 1)\n",
+    "plot_system(s, scales, scales=scales)\n",
+    "\n",
+    "plt.subplot(1, 3, 2)\n",
+    "s = parse_system.system_from_fun(reduce_tox, s)\n",
+    "s.bio_year = 2020\n",
+    "s.run(400, 0.5)\n",
+    "plot_system(s, scales, scales=scales)\n",
+    "\n",
+    "plt.subplot(1, 3, 3)\n",
+    "s2 = get_w3()\n",
+    "parse_system.new_cst_politic(s2, 'amti', 2020, 0.5)\n",
+    "s2.run(400, 0.5)\n",
+    "plot_system(s2, scales, scales=scales)\n",
+    "all(s.ppgao == s2.ppgao)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "dnovenv",
+   "language": "python",
+   "name": "dnovenv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/wrld3-03+.mdl b/wrld3-03+.mdl
new file mode 100644
index 0000000000000000000000000000000000000000..5d1d64a89c526477b009d71ada9dd89aad724688
--- /dev/null
+++ b/wrld3-03+.mdl
@@ -0,0 +1,3893 @@
+{UTF-8}
+********************************************************
+	.wrld3-03+
+********************************************************~
+		 THE DYNAMICS OF GROWTH IN A FINITE WORLD
+		 Copyright © 1971-1992 Dennis L. Meadows et al
+		 Laboratory for Interactive Learning
+		 IPSSR - Hood House UNH
+		 Durham, NH 03825
+		 603 862 2186
+		 Fax 603 862 1488
+		 e-mail:MEADOWS@UNHH.UNH.EDU
+	|
+
+GDP pc unit=
+	1
+	~	$/Person/year
+	~		|
+
+unit agricultural input=
+	1
+	~	$/hectare/year
+	~		|
+
+unit population=
+	1
+	~	Person
+	~		|
+
+"Absorption Land (GHA)"=
+	persistent pollution generation rate*ha per unit of pollution/ha per Gha
+	~	Ghectares
+	~		|
+
+"Arable Land in Gigahectares (GHA)"=
+	Arable Land/ha per Gha
+	~	Ghectares
+	~		|
+
+Education Index=
+	Education Index LOOKUP(GDP per capita/GDP pc unit)
+	~	Dmnl
+	~		|
+
+Education Index LOOKUP((0,0),(1000,0.81),(2000,0.88),(3000,0.92),(4000,0.95)
+,(5000,0.98),(6000,0.99),(7000,1))
+	~	Dmnl
+	~		|
+
+GDP Index=
+	LOG(GDP per capita/Ref Lo GDP,10)/LOG(Ref Hi GDP/Ref Lo GDP,10)
+	~	Dmnl
+	~		|
+
+GDP per capita=
+	GDP per capita LOOKUP(industrial output per capita/GDP pc unit)
+	~	$/(year*Person)
+	~		|
+
+GDP per capita LOOKUP((0,120),(200,600),(400,1200),(600,1800),(800,2500),(1000,3200)
+)
+	~	$/(year*Person)
+	~		|
+
+ha per Gha=
+	1e+09
+	~	hectare/Ghectare
+	~		|
+
+ha per unit of pollution=
+	4
+	~	hectares/(Pollution units/year)
+	~		|
+
+Human Ecological Footprint=
+	("Arable Land in Gigahectares (GHA)"+"Urban Land (GHA)"+"Absorption Land (GHA)"
+	)/Total Land
+	~	Dmnl
+	~	See Appendix 2 of Limits to Growth - the 30-Year Update for discussion of \
+		this index
+	~	:SUPPLEMENTARY
+	|
+
+Human Welfare Index=(Life Expectancy Index+Education Index+GDP Index)/3
+	~	Dmnl
+	~	See Appendix 2 of Limits to Growth - the 30-Year Update for discussion of \
+		this index
+	~	:SUPPLEMENTARY
+	|
+
+Life Expectancy Index=
+	Life Expectancy Index LOOKUP(life expectancy/one year)
+	~	Dmnl
+	~		|
+
+Life Expectancy Index LOOKUP((25,0),(35,0.16),(45,0.33),(55,0.5),(65,0.67)
+,(75,0.84),(85,1))
+	~	Dmnl
+	~		|
+
+one year=
+	1
+	~	year
+	~		|
+
+Ref Hi GDP=
+	9508
+	~	$/(year*Person)
+	~		|
+
+Ref Lo GDP=
+	24
+	~	$/(year*Person)
+	~		|
+
+Total Land=
+	1.91
+	~	Ghectares
+	~		|
+
+"Urban Land (GHA)"=
+	Urban and Industrial Land/ha per Gha
+	~	Ghectares
+	~		|
+
+********************************************************
+	.Agriculture
+********************************************************~
+
+		AGRICULTURAL SECTOR
+	|
+
+********************************************************
+	.Agriculture.Loop1
+********************************************************~
+
+		LOOP 1: FOOD FROM INVESTMENT IN LAND DEVELOPMENT
+	|
+
+Arable Land  =
+        INTEG( land development rate
+                  - land erosion rate
+                  - land removal for urban and industrial use ,
+             initial arable land )
+	~	hectare
+	~	  Arable land (AL#85).
+	|
+
+initial arable land  = 9e+08
+	~	hectare
+	~	  The initial amount of land that is arable.
+		         (ALI#85.2).
+	|
+
+development cost per hectare  =
+        development cost per hectare table ( Potentially Arable Land
+                  / potentially arable land total )
+	~	$/hectare
+	~	  Development cost per hectare (DCPH#97).
+	|
+
+development cost per hectare table  (
+            (0,100000),(0.1,7400),(0.2,5200),(0.3,3500),(0.4,2400),(0.5,1500)
+            ,(0.6,750),(0.7,300),(0.8,150),(0.9,75),(1,50) )
+	~	$/hectare
+	~	  Table relating undeveloped land to the cost of land
+		         development (DCPHT#97.1).
+	|
+
+food  =
+        land yield
+             * Arable Land
+             * land fraction harvested
+             * ( 1
+                  - processing loss )
+	~	Veg eq kg/year
+	~	  The total amount of usable food (F#87).
+	|
+
+food per capita  =
+        food
+             / population
+	~	Veg eq kg/(Person*year)
+	~	  Food per capita (FPC#88)
+	|
+
+land development rate  =
+        total agricultural investment
+             * fraction of agricultural inputs allocated to land development
+             / development cost per hectare
+	~	hectare/year
+	~	  The land developmen rate (LDR#96).
+	|
+
+land fr cult  =
+        Arable Land
+             / potentially arable land total
+	~	Dmnl
+	~	  Land fraction under cultivarion (LFC#84).
+	~	:SUPPLEMENTARY
+	|
+
+land fraction harvested  = 0.7
+	~	Dmnl
+	~	  Land fraction harvested (LFH#87.1).
+	|
+
+fraction of industrial output allocated to agriculture 1  =
+        fraction industrial output allocated to agriculture table 1 ( food per capita\
+
+                  / indicated food per capita )
+	~	Dmnl
+	~	  Fraction of industrial output allocated to
+		         agriculture before policy time (FIOAA1#94).
+	|
+
+fraction industrial output allocated to agriculture table 1  (
+            (0,0.4),(0.5,0.2),(1,0.1),(1.5,0.025),(2,0),(2.5,0) )
+	~	Dmnl
+	~	  Table relating food per capita to the fraction of
+		        industrial output allocated to agriculture
+		         (FIOAA1T#94.1).
+	|
+
+fraction of industrial output allocated to agriculture 2  =
+        fraction industrial output allocated to agriculture table 2 ( food per capita\
+
+                  / indicated food per capita )
+	~	Dmnl
+	~	  Fraction of industrial output allocated to
+		         agriculture after policy time (FIOAA2#95).
+	|
+
+fraction industrial output allocated to agriculture table 2  (
+            (0,0.4),(0.5,0.2),(1,0.1),(1.5,0.025),(2,0),(2.5,0) )
+	~	Dmnl
+	~	  Table relating food per capita to the fraction of
+		        industrial output allocated to agriculture
+		         (FIOAA2T#95.1).
+	|
+
+indicated food per capita 1=
+	indicated food per capita table 1 ( industrial output per capita/GDP pc unit )
+	~	Veg eq kg/(Person*year)
+	~	  Indicated foord per capita befor policy time
+		         (IFPC1#90).
+	|
+
+indicated food per capita table 1  (
+            (0,230),(200,480),(400,690),(600,850),(800,970),(1000,1070)
+            ,(1200,1150),(1400,1210),(1600,1250) )
+	~	Veg eq kg/(Person*year)
+	~	  Table relating industrial output to indicated food
+		         requirements 1 (IFPC1T#90.1).
+	|
+
+indicated food per capita 2=
+	indicated food per capita table 2 ( industrial output per capita/GDP pc unit )
+	~	Veg eq kg/(Person*year)
+	~	  Indicated foord per capita after policy time
+		         (IFPC2#90).
+	|
+
+indicated food per capita table 2  (
+            (0,230),(200,480),(400,690),(600,850),(800,970),(1000,1070)
+            ,(1200,1150),(1400,1210),(1600,1250) )
+	~	Veg eq kg/(Person*year)
+	~	  Table relating industrial output to indicated food
+		         requirements 2 (IFPC2T#90.2).
+	|
+
+Potentially Arable Land  =
+        INTEG( ( - land development rate  ) ,
+             initial potentially arable land )
+	~	hectare
+	~	  POTENTIALLY ARABLE LAND (PAL#86).
+	|
+
+initial potentially arable land  = 2.3e+09
+	~	hectare
+	~	  The initial amount of potentially arable land
+		         (PALI#86.2).
+	|
+
+potentially arable land total  = 3.2e+09
+	~	hectare
+	~	  POTENTIALLY ARABLE LAND TOTAL (PALT#84.1).
+	|
+
+processing loss  = 0.1
+	~	Dmnl
+	~	  PROCESSING LOSS (PL#87.2)
+	|
+
+fraction of industrial output allocated to agriculture  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             fraction of industrial output allocated to agriculture 2 ,
+             fraction of industrial output allocated to agriculture 1 )
+	~	Dmnl
+	~	  FRACTION OF INDUSTRIAL OUTPUT ALLOCATED TO
+		         AGRICULTURE (FIOAA#93).
+	|
+
+indicated food per capita  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             indicated food per capita 2 ,
+             indicated food per capita 1 )
+	~	Veg eq kg/(Person*year)
+	~	  Indicated food per capita (IFPC#89).
+	|
+
+total agricultural investment  =
+        industrial output
+             * fraction of industrial output allocated to agriculture
+	~	$/year
+	~	  TOTAL AGRICULTURAL INVESTMENT (TAI#92)
+	|
+
+********************************************************
+	.Agriculture.Loop2
+********************************************************~
+
+		LOOP 2: FOOD FROM INVESTMENT IN AGRICULTURAL INPUTS
+	|
+
+Agricultural Inputs  =
+        SMOOTH (current agricultural inputs,
+             average life agricultural inputs )
+	~	$/year
+	~	AGRICULTURAL INPUTS (AI#99)
+	|
+
+average life agricultural inputs  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             average life of agricultural inputs 2 ,
+             average life of agricultural inputs 1 )
+	~	year
+	~	AVERAGE LIFETIME OF AGRICULTURAL INPUTS (ALAI#100)
+	|
+
+agricultural input per hectare  =
+        Agricultural Inputs
+             * ( 1
+                  - fraction of agricultural inputs for land maintenance )
+             / Arable Land
+	~	$/(year*hectare)
+	~	  AGRICULTURAL INPUTS PER HECTARE (AIPH#101)
+	|
+
+current agricultural inputs  =
+        ACTIVE INITIAL( total agricultural investment
+                  * ( 1
+                       - fraction of agricultural inputs allocated to land development\
+		 ) ,
+             5e+09)
+	~	$/year
+	~	  CURRENT AGRICULTURAL INPUTS (CAI#98).
+	|
+
+desired food ratio  = 2
+	~	Dmnl
+	~	  desired food ratio (DFR#--)
+	|
+
+IND OUT IN 1970  = 7.9e+11
+	~	$/year
+	~	  INDUSTRIAL OUTPUT IN 1970 (IO70#107.2)
+	|
+
+land yield  =
+        land yield multiplier from technology
+             * Land Fertility
+             * land yield multiplier from capital
+             * land yield multiplier from air pollution
+	~	Veg eq kg/(year*hectare)
+	~	  LAND YIELD (LY#103)
+	|
+
+land yield multiplier from capital=
+	land yield multiplier from capital table (
+	agricultural input per hectare/unit agricultural input )
+	~	Dmnl
+	~	  LAND YIELD MULTIPLIER FROM CAPITAL (LYMC#102)
+	|
+
+land yield multiplier from capital table  (
+            (0,1),(40,3),(80,4.5),(120,5),(160,5.3),(200,5.6),(240,5.9)
+            ,(280,6.1),(320,6.35),(360,6.6),(400,6.9),(440,7.2),(480,7.4)
+            ,(520,7.6),(560,7.8),(600,8),(640,8.2),(680,8.4),(720,8.6)
+            ,(760,8.8),(800,9),(840,9.2),(880,9.4),(920,9.6),(960,9.8)
+            ,(1000,10) )
+	~	Dmnl
+	~	  Table relating agricultural inputs to land yeild
+		         (LYMCT#102.1).
+	|
+
+average life of agricultural inputs 1  = 2
+	~	year
+	~	  The average life of agricultural inputs before
+		         policy time (ALAI1#100.1)
+	|
+
+average life of agricultural inputs 2  = 2
+	~	year
+	~	  The average life of agricultural inputs after policy
+		         time (ALAI2#100.2)
+	|
+
+land yield factor 1  = 1
+	~	Dmnl
+	~	  Land yield factor before policy year (LYF1#104.1).
+	|
+
+land yield factor 2  =
+        SMOOTH3 ( Land Yield Technology ,
+             technology development delay )
+	~	Dmnl
+	~	  Land yield factor after policy year (LYF2#104.2).
+	|
+
+land yield multipler from air pollution 1  =
+        land yield multipler from air pollution table 1 ( industrial output
+                  / IND OUT IN 1970 )
+	~	Dmnl
+	~	  Land yield multiplier from air pollution before air
+		         poll time (LYMAP1#106).
+	|
+
+land yield multipler from air pollution table 1  (
+            (0,1),(10,1),(20,0.7),(30,0.4) )
+	~	Dmnl
+	~	  Table relating non-persistent pollution from
+		         industry to agricultural output (LYMAP1T#106.1).
+	|
+
+land yield multiplier from air pollution 2  =
+        land yield multipler from air pollution table 2 ( industrial output
+                  / IND OUT IN 1970 )
+	~	Dmnl
+	~	  Land yield multiplier from air pollution after air
+		         poll time (LYMAP2#107).
+	|
+
+land yield multipler from air pollution table 2  (
+            (0,1),(10,1),(20,0.98),(30,0.95) )
+	~	Dmnl
+	~	  Table relating non-persistent pollution from
+		         industry to agricultural output (LYMAP2T#107.1).
+	|
+
+land yield technology change rate multiplier  =
+        land yield technology change rate multiplier table ( desired food ratio
+                  - food ratio )
+	~	1/year
+	~	  Land yield from technology change multiplier
+		         (LYCM#--)
+	|
+
+land yield technology change rate multiplier table  (
+            (0,0),(1,0) )
+	~	1/year
+	~	  Table relating the food ratio gap to the change in
+		         agricultural technology (LYCMT#--).
+	|
+
+land yield multiplier from technology=
+	IF THEN ELSE ( Time >= POLICY YEAR ,
+	             land yield factor 2 ,
+	             land yield factor 1 )
+	~	Dmnl
+	~	  Land Yield factor (LYF#104)
+	|
+
+land yield multiplier from air pollution  =
+        IF THEN ELSE ( Time
+                  >= air pollution policy implementation time ,
+             land yield multiplier from air pollution 2 ,
+             land yield multipler from air pollution 1 )
+	~	Dmnl
+	~	  Land yield multiplier from air pollution
+		         (LYMAP#105).
+	|
+
+air pollution policy implementation time  = 4000
+	~	year
+	~	  Air Pollution switch time (ARPTM#--)
+	|
+
+Land Yield Technology= INTEG (
+	  land yield technology change rate ,
+
+		             1)
+	~	Dmnl
+	~	  LAND YIELD TECHNOLOGY INITIATED (LYTD#--)
+	|
+
+land yield technology change rate  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             Land Yield Technology
+                  * land yield technology change rate multiplier ,
+             0)
+	~	1/year
+	~	  Land yield from technology change rate (LYTDR#--)
+	|
+
+********************************************************
+	.Agriculture.Loop3
+********************************************************~
+
+		LOOP 3: LAND EROSION AND URBAN-INDUSTRIAL USE
+	|
+
+average life of land  =
+        average life of land normal
+             * land life multiplier from land yield
+	~	year
+	~	  Average life of land (ALL#112).
+	|
+
+average life of land normal  = 1000
+	~	year
+	~	  AVERAGE LIFE OF LAND NORMAL (ALLN#112.1).
+	|
+
+land erosion rate  =
+        Arable Land
+             / average life of land
+	~	hectare/year
+	~	  Land erosion rate (LER#
+	|
+
+land removal for urban and industrial use=
+	MAX(0, urban and industrial land required
+	             - Urban and Industrial Land )
+	             / urban and industrial land development time
+	~	hectare/year
+	~	  LAND REMOVAL FOR URBAN-INDUSTRIAL USE (LRUI#119).
+	|
+
+land life multiplier from land yield 1  =
+        land life multiplier from land yield table 1 ( land yield
+                  / inherent land fertility )
+	~	Dmnl
+	~	  Land life multiplier from yield before switch time
+		         (LLMY1#114).
+	|
+
+land life multiplier from land yield table 1  (
+            (0,1.2),(1,1),(2,0.63),(3,0.36),(4,0.16),(5,0.055),(6,0.04)
+            ,(7,0.025),(8,0.015),(9,0.01) )
+	~	Dmnl
+	~	  Table relating yield to the effect on land life
+		         (LLMY1T#114.1).
+	|
+
+land life multiplier from land yield 2  =
+        land life multiplier from land yield table 2 ( land yield
+                  / inherent land fertility )
+	~	Dmnl
+	~	  Land life multiplier from yield after switch time
+		         (LLMY2#115).
+	|
+
+land life multiplier from land yield table 2  (
+            (0,1.2),(1,1),(2,0.63),(3,0.36),(4,0.29),(5,0.26),(6,0.24)
+            ,(7,0.22),(8,0.21),(9,0.2) )
+	~	Dmnl
+	~	  Table relating yield to the effect on land life
+		         (LLMY2T#115.1).
+	|
+
+land life multiplier from land yield=
+	IF THEN ELSE ( Time
+	                  >= land life policy implementation time ,
+	             ( 0.95 ^ (( Time - land life policy implementation time )/one year ) )
+	                  * land life multiplier from land yield 1
+	               + ( 1 - 0.95 ^ (( Time - land life policy implementation time )/one year\
+		))
+	                       * land life multiplier from land yield 2 ,
+	             land life multiplier from land yield 1 )
+	~	Dmnl
+	~	  LAND LIFE MULTIPLIER FROM YIELD (LLMY#113).
+	|
+
+land life policy implementation time  = 4000
+	~	year
+	~	  Land life multiplier from yield switch time
+		         (LLMYTM#--)
+	|
+
+urban and industrial land development time  = 10
+	~	year
+	~	  Urban industrial land development time
+		         (UILDT#119.1).
+	|
+
+urban and industrial land required per capita=
+	urban and industrial land required per capita table (
+	industrial output per capita/GDP pc unit )
+	~	hectare/Person
+	~	  Urban industrial land per capita (UILPC#117).
+	|
+
+urban and industrial land required per capita table  (
+            (0,0.005),(200,0.008),(400,0.015),(600,0.025),(800,0.04),(1000,0.055)
+            ,(1200,0.07),(1400,0.08),(1600,0.09) )
+	~	hectare/Person
+	~	  Table relating industrial output to urban industrial
+		         land (UILPCT#117.1)
+	|
+
+urban and industrial land required  =
+        urban and industrial land required per capita
+             * population
+	~	hectare
+	~	  Urban industrial land required (UILR#118).
+	|
+
+Urban and Industrial Land  =
+        INTEG( ( land removal for urban and industrial use ) ,
+             initial urban and industrial land )
+	~	hectare
+	~	  URBAN-INDUSTRIAL LAND (UIL#120).
+	|
+
+initial urban and industrial land  = 8.2e+06
+	~	hectare
+	~	  URBAN-INDUSTRIAL LAND INITIAL (UILI#120.1).
+	|
+
+********************************************************
+	.Agriculture.Loop4
+********************************************************~
+
+		LOOP4 : LAND FERTILITY DEGRADATION
+	|
+
+land fertility degredation  =
+        Land Fertility
+             * land fertility degredation rate
+	~	Veg eq kg/(year*year*hectare)
+	~	  LAND FERTILITY DEGRADATION (LFD#123).
+	|
+
+land fertility degredation rate  =
+        land fertility degredation rate table ( persistent pollution index )
+	~	1/year
+	~	  Land fertility degradation rate (LFDR#122).
+	|
+
+land fertility degredation rate table  (
+            (0,0),(10,0.1),(20,0.3),(30,0.5) )
+	~	1/year
+	~	  Table relating persistent pollution to land
+		         fertility degradation (LFDRT#122.1).
+	|
+
+Land Fertility  =
+        INTEG( ( land fertility regeneration
+                  - land fertility degredation ) ,
+             initial land fertility )
+	~	Veg eq kg/(year*hectare)
+	~	  Land fertility (LFERT#121).
+	|
+
+initial land fertility  = 600
+	~	Veg eq kg/(year*hectare)
+	~	  LAND FERTILITY INITIAL (LFERTI#121.2)
+	|
+
+********************************************************
+	.Agriculture.Loop5
+********************************************************~
+
+		LOOP 5: LAND FERTILITY REGENERATION
+	|
+
+inherent land fertility  = 600
+	~	Veg eq kg/(year*hectare)
+	~	  INHERENT LAND FERTILITY (ILF#124.1).
+	|
+
+land fertility regeneration  =
+        ( inherent land fertility
+             - Land Fertility )
+             / land fertility regeneration time
+	~	Veg eq kg/(year*year*hectare)
+	~	  Land fertility regeneration (LFR#124).
+	|
+
+land fertility regeneration time  =
+        land fertility regeneration time table ( fraction of agricultural inputs for land maintenance
+ )
+	~	year
+	~	  LAND FERTILITY REGENERATION TIME (LFRT#125)
+	|
+
+land fertility regeneration time table  (
+            (0,20),(0.02,13),(0.04,8),(0.06,4),(0.08,2),(0.1,2) )
+	~	year
+	~	  Table relating inputs to land maintenance to land
+		         fertility regeneration (LFRTT#125.1).
+	|
+
+********************************************************
+	.Agriculture.Loop6
+********************************************************~
+
+		LOOP 6: DISCONTINUING LAND MAINTENANCE
+	|
+
+Perceived Food Ratio  =
+        SMOOTH (food ratio,
+             food shortage perception delay )
+	~	Dmnl
+	~	PERCEIVED FOOD RATIO (PFR#128).
+	|
+
+food ratio  =
+        ACTIVE INITIAL( food per capita
+                  / subsistence food per capita ,
+             1)
+	~	Dmnl
+	~	  FOOD RATIO (FR#127)
+	|
+
+food shortage perception delay  = 2
+	~	year
+	~	  FOOD SHORTAGE PERCEPTION DELAY (FSPD#128.2)
+	|
+
+fraction of agricultural inputs for land maintenance  =
+        fraction of agricultural inputs for land maintenance table ( Perceived Food Ratio\
+		 )
+	~	Dmnl
+	~	  FRACTION OF INPUTS ALLOCATED TO LAND MAINTENANCE
+		         (FALM#126).
+	|
+
+fraction of agricultural inputs for land maintenance table  (
+            (0,0),(1,0.04),(2,0.07),(3,0.09),(4,0.1) )
+	~	Dmnl
+	~	  Table relating the perceived food ratio to the
+		        fraction of input used for land maintenance
+		         (FALMT#126.1).
+	|
+
+subsistence food per capita  = 230
+	~	Veg eq kg/(Person*year)
+	~	  Subsistence food per capita (SFPC#127.1).
+	|
+
+********************************************************
+	.Agriculture.Loops1&2
+********************************************************~
+
+		LOOPS 1 & 2: THE INVESTMENT ALLOCATION DECISION
+	|
+
+fraction of agricultural inputs allocated to land development  =
+        fraction of agricultural inputs allocated to land development table ( ( marginal productivity of land development
+
+                  / marginal productivity of agricultural inputs ) )
+	~	Dmnl
+	~	  Fraction of inputs allocated to land devlelopment
+		         (FIALD#108).
+	|
+
+fraction of agricultural inputs allocated to land development table  (
+            (0,0),(0.25,0.05),(0.5,0.15),(0.75,0.3),(1,0.5),(1.25,0.7)
+            ,(1.5,0.85),(1.75,0.95),(2,1) )
+	~	Dmnl
+	~	  Table relating the marginal productivity of land to
+		        the fraction of inputs allocated to new land
+		         development (FIALDT#108.1).
+	|
+
+marginal land yield multiplier from capital=
+	marginal land yield multiplier from capital table (
+	agricultural input per hectare/unit agricultural input )
+	~	hectare/$
+	~	  MARGINAL LAND YIELD MULTIPLIER FROM CAPITAL
+		         (MLYMC#111).
+	|
+
+marginal land yield multiplier from capital table  (
+            (0,0.075),(40,0.03),(80,0.015),(120,0.011),(160,0.009),(200,0.008)
+            ,(240,0.007),(280,0.006),(320,0.005),(360,0.005),(400,0.005)
+            ,(440,0.005),(480,0.005),(520,0.005),(560,0.005),(600,0.005)
+             )
+	~	hectare/$
+	~	  Table relating agricultural inputs to marginal land
+		         yield (MLYMCT#111.1).
+	|
+
+marginal productivity of agricultural inputs  =
+        average life agricultural inputs
+             * land yield
+             * marginal land yield multiplier from capital
+             / land yield multiplier from capital
+	~	Veg eq kg/$
+	~	  MARGINAL PRODUCTIVITY OF AGRICULTURAL INPUTS
+		         (MPAI#110).
+	|
+
+marginal productivity of land development  =
+        land yield
+             / ( development cost per hectare
+                  * social discount )
+	~	Veg eq kg/$
+	~	  The marginal productivity of land development
+		         (MPLD#109)
+	|
+
+social discount  = 0.07
+	~	1/year
+	~	  SOCIAL DISCOUNT (SD#109.1)
+	|
+
+********************************************************
+	.Capital
+********************************************************~
+
+		CAPITAL SECTOR
+	|
+
+********************************************************
+	.Capital.Industry
+********************************************************~
+
+		INDUSTRIAL SUBSECTOR
+	|
+
+industrial capital output ratio multiplier from resource conservation technology=
+	industrial capital output ratio multiplier from resource table ( resource use factor
+	 )
+	~	year
+	~	  Technology driven industrial capital output ratio
+		         (ICOR2T#--)
+	|
+
+industrial capital output ratio multiplier from pollution technology=
+	industrial capital output ratio multiplier from pollution table ( persistent pollution generation factor
+	 )
+	~	Dmnl
+	~	  Pollution control technology multiplier for capital
+		         output ratio (COPM#--).
+	|
+
+industrial capital output ratio multiplier from land yield technology=
+	industrial capital output ratio multiplier table ( land yield multiplier from technology\
+		 )
+	~	Dmnl
+	~	  CAPITAL OUTPUT YIELD MULTIPLIER (COYM#--)
+	|
+
+fraction of industrial output allocated to investment  =
+        ( 1
+             - fraction of industrial output allocated to agriculture
+             - fraction of industrial output allocated to services
+             - fraction of industrial output allocated to consumption )
+	~	Dmnl
+	~	  Fraction of industrial output allocated to industry
+		         (FIOAI#56).
+	|
+
+industrial capital depreciation  =
+        Industrial Capital
+             / average life of industrial capital
+	~	$/year
+	~	  Industrial capital depreciation rate (ICDR#53).
+	|
+
+industrial capital investment  =
+        ( ( industrial output ) )
+             * ( fraction of industrial output allocated to investment )
+	~	$/year
+	~	  Industrial capital investment rate (ICIR#55).
+	|
+
+industrial capital output ratio multiplier from resource table  (
+            (0,3.75),(0.1,3.6),(0.2,3.47),(0.3,3.36),(0.4,3.25),(0.5,3.16)
+            ,(0.6,3.1),(0.7,3.06),(0.8,3.02),(0.9,3.01),(1,3) )
+	~	year
+	~	  CAPITAL OUTPUT FROM RESOURCES technology multiplier
+		         TABLE (ICOR2TT#--)
+	|
+
+industrial output per capita  =
+        industrial output
+             / population
+	~	$/(Person*year)
+	~	  INDUSTRIAL OUTPUT PER CAPITA (IOPC#49)
+	|
+
+industrial output per capita desired  = 400
+	~	$/(Person*year)
+	~	  Industrial output per capita desired (IOPCD#59.2).
+	|
+
+Industrial Capital  =
+        INTEG( ( industrial capital investment
+                  - industrial capital depreciation ) ,
+             initial industrial capital )
+	~	$
+	~	  INDUSTRIAL CAPITAL (IC#52).
+	|
+
+initial industrial capital  = 2.1e+11
+	~	$
+	~	  INDUSTRIAL CAPITAL INITIAL (ICI#52.1).
+	|
+
+industrial output  =
+        ( ( ( Industrial Capital ) )
+             * ( 1
+                  - fraction of industrial capital allocated to obtaining resources )\
+		 )
+             * ( capacity utilization fraction )
+             / industrial capital output ratio
+	~	$/year
+	~	  Industrial output (IO#50)
+	|
+
+average life of industrial capital 1  = 14
+	~	year
+	~	  Average life of industrial capital before policy
+		         year (ALIC1#54.1).
+	|
+
+average life of industrial capital 2  = 14
+	~	year
+	~	  Average life of industrial capital after policy year
+		         (ALIC2#54.2)
+	|
+
+fraction of industrial output allocated to consumption constant  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             fraction of industrial output allocated to consumption constant 2 ,
+             fraction of industrial output allocated to consumption constant 1 )
+	~	Dmnl
+	~	  Fraction of output allocated to consumption CONSTANT
+		         (FIOACC#58).
+	|
+
+fraction of industrial output allocated to consumption constant 1  = 0.43
+	~	Dmnl
+	~	  Fraction of output allocated to consuption constant
+		         1 (FIOAC1#58.1).
+	|
+
+fraction of industrial output allocated to consumption constant 2  = 0.43
+	~	Dmnl
+	~	  Fraction of output allocated to consuption constant
+		         2 (FIOAC2#58.2).
+	|
+
+fraction of industrial output allocated to consumption variable  =
+        fraction of industrial output allocated to consumption variable table ( industrial output per capita
+
+                  / industrial output per capita desired )
+	~	Dmnl
+	~	  Fraction industrial output allocated to consumption
+		         variable (FIOACV#59)
+	|
+
+fraction of industrial output allocated to consumption variable table  (
+            (0,0.3),(0.2,0.32),(0.4,0.34),(0.6,0.36),(0.8,0.38),(1,0.43)
+            ,(1.2,0.73),(1.4,0.77),(1.6,0.81),(1.8,0.82),(2,0.83) )
+	~	Dmnl
+	~	  Fraction of industrial output allocated to
+		         consumption variable TABLE (FIOACVT#59.1)
+	|
+
+industrial capital output ratio 1  = 3
+	~	year
+	~	  Industrial capital output ratio prior to the policy
+		         year (ICOR1#51.1)
+	|
+
+industrial capital output ratio 2  =
+        industrial capital output ratio multiplier from resource conservation technology\
+
+             * industrial capital output ratio multiplier from land yield technology
+             * industrial capital output ratio multiplier from pollution technology
+	~	year
+	~	  Industrial capital output ratio after the policy
+		         year (ICOR2#51.2)
+	|
+
+industrial capital output ratio multiplier from pollution table  (
+            (0,1.25),(0.1,1.2),(0.2,1.15),(0.3,1.11),(0.4,1.08),(0.5,1.05)
+            ,(0.6,1.03),(0.7,1.02),(0.8,1.01),(0.9,1),(1,1) )
+	~	Dmnl
+	~	  Table relating pollution correction technology to
+		         the capital output ratio (COPMT#--)
+	|
+
+average life of industrial capital  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             average life of industrial capital 2 ,
+             average life of industrial capital 1 )
+	~	year
+	~	  AVERAGE LIFETIME OF INDUSTRIAL CAPITAL (ALIC#54).
+	|
+
+fraction of industrial output allocated to consumption  =
+        IF THEN ELSE ( Time
+                  >= industrial equilibrium time ,
+             fraction of industrial output allocated to consumption variable ,
+             fraction of industrial output allocated to consumption constant )
+	~	Dmnl
+	~	  Fraction of industrial output allocated to
+		         consumption (FIOAC#58)
+	|
+
+industrial capital output ratio  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             industrial capital output ratio 2 ,
+             industrial capital output ratio 1 )
+	~	year
+	~	  INDUSTRIAL CAPITAL-OUTPUT RATIO (ICOR#51)
+	|
+
+industrial equilibrium time  = 4000
+	~	year
+	~	  INDUSTRIAL EQUILIBRIUM TIME (IET#57.1).
+	|
+
+industrial capital output ratio multiplier table(
+	[(1,0.8)-(2,2)],(1,1),(1.2,1.05),(1.4,1.12),(1.6,1.25),(1.8,1.35),(2,1.5))
+	~	Dmnl
+	~	  Table relating the yield of technology to the effect
+		         on the capital output ratio (COYMT#--)\!\!
+	|
+
+********************************************************
+	.Capital.Jobs
+********************************************************~
+
+		JOB SUBSECTOR
+	|
+
+Delayed Labor Utilization Fraction=
+	SMOOTHI (labor utilization fraction,
+	             labor utilization fraction delay time
+	,1 )
+	~	Dmnl
+	~	LABOR UTILIZATION FRACTION DELAYED (LUFD#82)
+	|
+
+capacity utilization fraction  =
+        ACTIVE INITIAL( capacity utilization fraction table ( Delayed Labor Utilization Fraction\
+		 )
+             ,
+             1)
+	~	Dmnl
+	~	  CAPITAL UTILIZATION FRACTION (CUF#83)
+	|
+
+capacity utilization fraction table  (
+            (1,1),(3,0.9),(5,0.7),(7,0.3),(9,0.1),(11,0.1) )
+	~	Dmnl
+	~	  Table relating labor utilization to capacity
+		         utilization (CUFT#83.2).
+	|
+
+jobs  =
+        potential jobs industrial sector
+             + potential jobs agricultural sector
+             + potential jobs service sector
+	~	Person
+	~	  JOBS (J#73).
+	|
+
+jobs per hectare=
+	jobs per hectare table ( agricultural input per hectare/unit agricultural input )
+	~	Person/hectare
+	~	  Jobs per hectare in agriculture (JPH#79).
+	|
+
+jobs per hectare table  (
+            (2,2),(6,0.5),(10,0.4),(14,0.3),(18,0.27),(22,0.24),(26,0.2)
+            ,(30,0.2) )
+	~	Person/hectare
+	~	  Table relating agricultural input intensity to the
+		        number of jobs per hectare in agriculture
+		         (JPHT#79.1).
+	|
+
+jobs per industrial capital unit=
+	( jobs per industrial capital unit table ( industrial output per capita/GDP pc unit \
+		) )
+	             * 0.001
+	~	Person/$
+	~	  Jobs per industrial capital units (JPICU#75).
+	|
+
+jobs per industrial capital unit table  (
+            (50,0.37),(200,0.18),(350,0.12),(500,0.09),(650,0.07),(800,0.06)
+             )
+	~	Person/$
+	~	  Table relating industrial output per capita to job
+		         per industrial capital unit (JPICUT#75.1).
+	|
+
+jobs per service capital unit=
+	( jobs per service capital unit table ( service output per capita/GDP pc unit ) )
+	             * 0.001
+	~	Person/$
+	~	  Jobs per service capital unit (JPSCU#77).
+	|
+
+jobs per service capital unit table  (
+            (50,1.1),(200,0.6),(350,0.35),(500,0.2),(650,0.15),(800,0.15)
+             )
+	~	Person/$
+	~	  Table relating service output per capita to job per
+		         service capital unit (JPSCUT#77.1).
+	|
+
+labor force  =
+        ( Population 15 To 44
+             + Population 45 To 64 )
+             * labor force participation fraction
+	~	Person
+	~	  LABOR FORCE (LF#80).
+	|
+
+labor force participation fraction  = 0.75
+	~	Dmnl
+	~	  LABOR FORCE PARTICIPATION FRACTION (LFPF#80.1)
+	|
+
+labor utilization fraction  =
+        jobs
+             / labor force
+	~	Dmnl
+	~	  Labor utilization fraction (LUF#81).
+	|
+
+labor utilization fraction delay time  = 2
+	~	year
+	~	  Labor utilization fraction delay time (LUFDT#82.1)
+	|
+
+potential jobs agricultural sector  =
+        ( ( jobs per hectare ) )
+             * ( Arable Land )
+	~	Person
+	~	  Potential jobs in the agricultural sector (PJAS#78).
+	|
+
+potential jobs industrial sector  =
+        Industrial Capital
+             * jobs per industrial capital unit
+	~	Person
+	~	  POTENTIAL JOBS IN INDUSTRIAL SECTOR (PJIS#74).
+	|
+
+potential jobs service sector  =
+        ( ( Service Capital ) )
+             * ( jobs per service capital unit )
+	~	Person
+	~	  Potential jobs in the service sector (PJSS#76).
+	|
+
+********************************************************
+	.Capital.Service
+********************************************************~
+
+		SERVICE SUBSECTOR
+	|
+
+average life of service capital 1  = 20
+	~	year
+	~	  Average lifetime of service capital before policy
+		         time (ALSC1#69.1).
+	|
+
+average life of service capital 2  = 20
+	~	year
+	~	  Average lifetime of service capital after policy
+		         time (ALSC2#69.2).
+	|
+
+fraction of industrial output allocated to services 1  =
+        fraction of industrial output allocated to services table 1 ( service output per capita\
+
+                  / indicated services output per capita )
+	~	Dmnl
+	~	  FRACTION OF INDUSTRIAL OUTPUT ALLOCATED TO SERVICES
+		         before policy year (FIOAS1#64).
+	|
+
+fraction of industrial output allocated to services table 1  (
+            (0,0.3),(0.5,0.2),(1,0.1),(1.5,0.05),(2,0) )
+	~	Dmnl
+	~	  Table relating service output to the fraction of
+		        industrial output allocated to service
+		         (FIOAS1T#64.1).
+	|
+
+fraction of industrial output allocated to services 2  =
+        fraction of industrial output allocated to services table 2 ( service output per capita\
+
+                  / indicated services output per capita )
+	~	Dmnl
+	~	  FRACTION OF INDUSTRIAL OUTPUT ALLOCATED TO SERVICES
+		         after policy year (FIOAS2#65).
+	|
+
+fraction of industrial output allocated to services table 2  (
+            (0,0.3),(0.5,0.2),(1,0.1),(1.5,0.05),(2,0) )
+	~	Dmnl
+	~	  Table relating service output to the fraction of
+		        industrial output allocated to service
+		         (FIOAS2T#65.1).
+	|
+
+indicated services output per capita 1=
+	indicated services output per capita table 1 ( industrial output per capita/GDP pc unit\
+		 )
+	~	$/(Person*year)
+	~	  Indicated service output per capita before policy
+		         year (ISOPC1#61).
+	|
+
+indicated services output per capita table 1  (
+            (0,40),(200,300),(400,640),(600,1000),(800,1220),(1000,1450)
+            ,(1200,1650),(1400,1800),(1600,2000) )
+	~	$/(Person*year)
+	~	  Table relating industrial output per capita to the
+		        indicated service output per capita before policy
+		         year (ISOPC1T#61.1).
+	|
+
+indicated services output per capita 2=
+	indicated services output per capita table 2 ( industrial output per capita/GDP pc unit\
+		 )
+	~	$/(Person*year)
+	~	  Indicated service output per capita after policy
+		         year (ISOPC2#62).
+	|
+
+indicated services output per capita table 2  (
+            (0,40),(200,300),(400,640),(600,1000),(800,1220),(1000,1450)
+            ,(1200,1650),(1400,1800),(1600,2000) )
+	~	$/(Person*year)
+	~	  Table relating industrial output per capita to the
+		        indicated service output per capita afte policy
+		         year (ISOPC2T#62.2).
+	|
+
+service capital output ratio 1  = 1
+	~	year
+	~	  Service capital output ratio before policy year
+		         (SCOR1#72.1).
+	|
+
+service capital output ratio 2  = 1
+	~	year
+	~	  Service capital output ratio after policy year
+		         (SCOR2#72.2).
+	|
+
+average life of service capital  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             average life of service capital 2 ,
+             average life of service capital 1 )
+	~	year
+	~	  AVERAGE LIFETIME OF SERVICE CAPITAL (ALSC#69)
+	|
+
+fraction of industrial output allocated to services  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             fraction of industrial output allocated to services 2 ,
+             fraction of industrial output allocated to services 1 )
+	~	Dmnl
+	~	  FRACTION OF INDUSTRIAL OUTPUT ALLOCATED TO SERVICES
+		         (FIOAS#63).
+	|
+
+indicated services output per capita  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             indicated services output per capita 2 ,
+             indicated services output per capita 1 )
+	~	$/(Person*year)
+	~	  Indicated service output per capita (ISOPC#60).
+	|
+
+service capital output ratio  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             service capital output ratio 2 ,
+             service capital output ratio 1 )
+	~	year
+	~	  Service capital output ratio (SCOR#72).
+	|
+
+service capital depreciation  =
+        Service Capital
+             / average life of service capital
+	~	$/year
+	~	  SERVICE CAPITAL DEPRECIATION RATE (SCDR#68).
+	|
+
+service capital investment  =
+        ( ( industrial output ) )
+             * ( fraction of industrial output allocated to services )
+	~	$/year
+	~	  SERVICE CAPITAL INVESTMENT RATE (SCIR#66).
+	|
+
+service output per capita  =
+        service output
+             / population
+	~	$/(Person*year)
+	~	  SERVICE OUTPUT PER CAPITA (SOPC#71).
+	|
+
+Service Capital  =
+        INTEG( ( service capital investment
+                  - service capital depreciation ) ,
+             initial service capital )
+	~	$
+	~	  Service capital (SC#67).
+	|
+
+initial service capital  = 1.44e+11
+	~	$
+	~	  The initial level of service capital (SCI#67.2)
+	|
+
+service output  =
+        ( ( Service Capital ) )
+             * ( capacity utilization fraction )
+             / service capital output ratio
+	~	$/year
+	~	  Service output (SO#70).
+	|
+
+********************************************************
+	.Control
+********************************************************~
+
+		CONTROL CARDS FOR SIMULATION
+	|
+
+FINAL TIME  = 2100
+	~	year
+	~	  The time at which simulation stops.
+	|
+
+INITIAL TIME  = 1900
+	~	year
+	~	  The time at which the simulation begins.
+	|
+
+SAVEPER  =
+        TIME STEP
+	~	year
+	~	  The frequency with which results are saved.
+	|
+
+POLICY YEAR=
+	1995
+	~	year
+	~	  The time at which policies are implemented
+		         (PYEAR#150.1).
+	|
+
+TIME STEP  = 0.5
+	~	year
+	~	  The time step for computing the model
+	|
+
+********************************************************
+	.Pollution
+********************************************************~
+
+		PERSISTENT POLLUTION SECTOR
+	|
+
+agricultural material toxicity index  = 1
+	~	Pollution units/$
+	~	  Agricultural material toxicity index (AMTI#140.2).
+	|
+
+assimilation half life  =
+        assimilation half life in 1970
+             * assimilation half life multiplier
+	~	year
+	~	  ASSIMILATION HALF-LIFE (AHL#146).
+	|
+
+assimilation half life in 1970  = 1.5
+	~	year
+	~	  Assimilation half life of persistent pollution int
+		         1970 (AHL70#146.1).
+	|
+
+assimilation half life multiplier  =
+        assimilation half life mult table ( persistent pollution index )
+	~	Dmnl
+	~	  Assimilation half life of multiplier of persistent
+		         pollution (AHLM#145)
+	|
+
+assimilation half life mult table  (
+            (1,1),(251,11),(501,21),(751,31),(1001,41) )
+	~	Dmnl
+	~	  Table relating the level of persisten pollution to
+		         its assimilation rate (AHLMT#145.1).
+	|
+
+desired persistent pollution index  = 1.2
+	~	Dmnl
+	~	  Desires persistent pollution index (DPOLX#--).
+	|
+
+fraction of agricultural inputs from persistent materials  = 0.001
+	~	Dmnl
+	~	  Fraction of inputs as persistent materials
+		         (FIPM#140.1).
+	|
+
+fraction of resources from persistent materials  = 0.02
+	~	Dmnl
+	~	  Fraction of resources as persistent materials
+		         (FRPM#139.1)
+	|
+
+industrial material toxicity index  = 10
+	~	Pollution units/Resource unit
+	~	  Industrial materials toxicity index (IMTI#139.3)
+	|
+
+industrial material emissions factor  = 0.1
+	~	Dmnl
+	~	  Industrial materials emission factor (IMEF#139.2).
+	|
+
+persistent pollution generation factor 1  = 1
+	~	Dmnl
+	~	  Persistent pollution generation factor before policy
+		         time (PPGF1#138.1).
+	|
+
+persistent pollution generation factor 2  =
+        SMOOTH3 ( Persistent Pollution Technology ,
+             technology development delay )
+	~	Dmnl
+	~	  Persistent pollution generation factor after policy
+		         time (PPGF2#138.2).
+	|
+
+persistent pollution technology change multiplier  =
+        persistent pollution technology change mult table ( 1
+                  - persistent pollution index
+                       / desired persistent pollution index )
+	~	1/year
+	~	  POLLUTION CONTROL TECHNOLOGY CHANGE MULTIPLIER
+		         (POLGFM#--).
+	|
+
+persistent pollution technology change mult table  (
+            (-1,0),(0,0) )
+	~	1/year
+	~	  Table relating persisten pollution to changes due to
+		         technology (POLGFMT#--).
+	|
+
+Persistent Pollution  =
+        INTEG( ( persistent pollution appearance rate
+                  - persistent pollution assimilation rate ) ,
+             initial persistent pollution )
+	~	Pollution units
+	~	  Persistent pollution (PPOL#142).
+	|
+
+initial persistent pollution  = 2.5e+07
+	~	Pollution units
+	~	  persistent pollution initial (PPOLI#142.2)
+	|
+
+persistent pollution generation industry  =
+        per capita resource use multiplier
+             * population
+             * fraction of resources from persistent materials
+             * industrial material emissions factor
+             * industrial material toxicity index
+	~	Pollution units/year
+	~	  Persistent pollution generated by industrial output.
+		         (PPGIO#139)
+	|
+
+persistent pollution generation agriculture  =
+        agricultural input per hectare
+             * Arable Land
+             * fraction of agricultural inputs from persistent materials
+             * agricultural material toxicity index
+	~	Pollution units/year
+	~	  Persistent pollution generated by agriculture
+		         (PPGAO#140)
+	|
+
+persistent pollution generation rate  =
+        ( persistent pollution generation industry
+             + persistent pollution generation agriculture )
+             * ( persistent pollution generation factor )
+	~	Pollution units/year
+	~	  PERSISTENT POLLUTION GENERATION RATE (PPGR#137).
+	|
+
+persistent pollution appearance rate  =
+        DELAY3 ( persistent pollution generation rate ,
+             persistent pollution transmission delay )
+	~	Pollution units/year
+	~	  Persistent pollution appearance rate (PPAPR#141)
+	|
+
+persistent pollution assimilation rate  =
+        Persistent Pollution
+             / ( assimilation half life
+                  * 1.4)
+	~	Pollution units/year
+	~	  PERSISTENT POLLUTION ASSIMILATION RATE (PPASR#144).
+	|
+
+persistent pollution in 1970  = 1.36e+08
+	~	Pollution units
+	~	  PERSISTENT POLLUTION IN 1970 (PPOL70#143.1).
+	|
+
+persistent pollution index  =
+        Persistent Pollution
+             / persistent pollution in 1970
+	~	Dmnl
+	~	  Persistent pollution index relative to 1970
+		         (PPOLX#143).
+	|
+
+Persistent Pollution Technology  =
+        INTEG( persistent pollution technology change rate ,
+             1)
+	~	Dmnl
+	~	  Pollution control technology initiated (PTD#--)
+	|
+
+persistent pollution technology change rate  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             Persistent Pollution Technology
+                  * persistent pollution technology change multiplier ,
+             0)
+	~	1/year
+	~	  pollution control technology change rate (PTDR#--)
+	|
+
+persistent pollution transmission delay  = 20
+	~	year
+	~	  Persistent pollution transmission delay
+		         (PPTD#141.1).
+	|
+
+persistent pollution generation factor  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             persistent pollution generation factor 2 ,
+             persistent pollution generation factor 1 )
+	~	Dmnl
+	~	  PERSISTENT POLLUTION GENERATED FACTOR (PPGF#138).
+	|
+
+********************************************************
+	.Population
+********************************************************~
+
+		POPULATION SECTOR
+	|
+
+deaths 0 to 14  =
+        Population 0 To 14
+             * mortality 0 to 14
+	~	Person/year
+	~	  The number of deaths per year among people 0 to 14
+		         years of age (D1#3).
+	|
+
+deaths 15 to 44  =
+        Population 15 To 44
+             * mortality 15 to 44
+	~	Person/year
+	~	  The number of deaths per year among people 15 to 44
+		         years of age (D2#7).
+	|
+
+deaths 45 to 64  =
+        Population 45 To 64
+             * mortality 45 to 64
+	~	Person/year
+	~	  The number of deaths per year among people 55 to 64
+		         years of age (D3#11).
+	|
+
+deaths 65 plus  =
+        Population 65 Plus
+             * mortality 65 plus
+	~	Person/year
+	~	  The number of deaths per year among people 65 and
+		         older (D4#15).
+	|
+
+maturation 14 to 15  =
+        ( ( Population 0 To 14 ) )
+             * ( 1
+                  - mortality 0 to 14 )
+             / 15
+	~	Person/year
+	~	  The fractional rate at which people aged 0-14 mature
+		         into the next age cohort (MAT1#5).
+	|
+
+maturation 44 to 45  =
+        ( ( Population 15 To 44 ) )
+             * ( 1
+                  - mortality 15 to 44 )
+             / 30
+	~	Person/year
+	~	  The fractional rate at which people aged 15-44
+		         mature into the next age cohort (MAT2#9).
+	|
+
+maturation 64 to 65  =
+        ( ( Population 45 To 64 ) )
+             * ( 1
+                  - mortality 45 to 64 )
+             / 20
+	~	Person/year
+	~	  The fractional rate at which people aged 45-64
+		         mature into the next age cohort (MAT3#13).
+	|
+
+mortality 45 to 64=
+	mortality 45 to 64 table ( life expectancy/one year )
+	~	1/year
+	~	  The fractional mortality rate for people aged 45-64
+		         (M3#12).
+	|
+
+mortality 45 to 64 table  (
+            (20,0.0562),(30,0.0373),(40,0.0252),(50,0.0171),(60,0.0118)
+            ,(70,0.0083),(80,0.006) )
+	~	1/year
+	~	  The table relating average life to mortality in the
+		         45 to 64 age group (M3T#12.1).
+	|
+
+mortality 65 plus=
+	mortality 65 plus table ( life expectancy/one year )
+	~	1/year
+	~	  The fractional mortality rate for people over 65
+		         (M4#16).
+	|
+
+mortality 65 plus table  (
+            (20,0.13),(30,0.11),(40,0.09),(50,0.07),(60,0.06),(70,0.05)
+            ,(80,0.04) )
+	~	1/year
+	~	  The table relating average life expectancy to
+		         mortality among people over 65 (M4T#16.1)
+	|
+
+mortality 0 to 14=
+	mortality 0 to 14 table ( life expectancy/one year )
+	~	1/year
+	~	  The fractional mortality rate for people aged 0-14
+		         (M1#4).
+	|
+
+mortality 0 to 14 table  (
+            (20,0.0567),(30,0.0366),(40,0.0243),(50,0.0155),(60,0.0082)
+            ,(70,0.0023),(80,0.001) )
+	~	1/year
+	~	  The table relating average life to mortality in the
+		         0 to 14 age group (M1T#4.1).
+	|
+
+mortality 15 to 44=
+	mortality 15 to 44 table ( life expectancy/one year )
+	~	1/year
+	~	  The fractional mortality rate for people aged 15-44
+		         (M2#8).
+	|
+
+mortality 15 to 44 table  (
+            (20,0.0266),(30,0.0171),(40,0.011),(50,0.0065),(60,0.004),
+            (70,0.0016),(80,0.0008) )
+	~	1/year
+	~	  The table relating average life to mortality in the
+		         15 to 44 age group (M2T#8.1).
+	|
+
+Population 0 To 14  =
+        INTEG( ( births
+                  - deaths 0 to 14
+                  - maturation 14 to 15 ) ,
+             initial population 0 to 14 )
+	~	Person
+	~	  World population, AGES 0-14 (P1#2)
+	|
+
+initial population 0 to 14  = 6.5e+08
+	~	Person
+	~	  The initial number of people aged 0 to 14 (P1I#2.2).
+	|
+
+Population 15 To 44  =
+        INTEG( ( maturation 14 to 15
+                  - deaths 15 to 44
+                  - maturation 44 to 45 ) ,
+             initial population 15 to 44 )
+	~	Person
+	~	  World population, AGES 15-44 (P2#6)
+	|
+
+initial population 15 to 44  = 7e+08
+	~	Person
+	~	  The initial number of people aged 15 to 44
+		         (P2I#6.2).
+	|
+
+Population 45 To 64  =
+        INTEG( ( maturation 44 to 45
+                  - deaths 45 to 64
+                  - maturation 64 to 65 ) ,
+             initial population 54 to 64 )
+	~	Person
+	~	  The world population aged 0 to 14 (P3#10).
+	|
+
+initial population 54 to 64  = 1.9e+08
+	~	Person
+	~	  The initial number of people aged 45 to 64
+		         (P3I#10.2).
+	|
+
+Population 65 Plus  =
+        INTEG( ( maturation 64 to 65
+                  - deaths 65 plus ) ,
+             initial population 65 plus )
+	~	Person
+	~	  The world population aged 65 and over (P4#14).
+	|
+
+initial population 65 plus  = 6e+07
+	~	Person
+	~	  The initial number of people aged 65 and over
+		         (P4I#14.2)
+	|
+
+population  =
+        Population 0 To 14
+             + Population 15 To 44
+             + Population 45 To 64
+             + Population 65 Plus
+	~	Person
+	~	  Total world population in all age groups (POP#1).
+	|
+
+********************************************************
+	.Population.Births
+********************************************************~
+
+		BIRTH RATE SUBSECTOR
+	|
+
+average industrial output per capita  =
+        SMOOTH ( industrial output per capita ,
+             income expectation averaging time )
+	~	$/(Person*year)
+	~	  Average industrial output per capita (AIOPC#43).
+	|
+
+birth rate  =
+        THOUSAND
+             * births
+             / population
+	~	C/year
+	~	  The crude birth rate measured in people per thousand
+		         people per year (CBR#31).
+	~	:SUPPLEMENTARY
+	|
+
+births  =
+        IF THEN ELSE ( Time
+                  >= population equilibrium time ,
+             deaths ,
+             ( total fertility
+                  * Population 15 To 44
+                  * 0.5
+                  / reproductive lifetime ) )
+	~	Person/year
+	~	  The total number of births in the world (B#30).
+	|
+
+completed multiplier from perceived lifetime=
+	completed multiplier from perceived lifetime table ( perceived life expectancy/one year\
+		 )
+	~	Dmnl
+	~	  COMPENSATORY MULTIPLIER FROM PERCEIVED LIFE
+		         EXPECTANCY (CMPLE#36).
+	|
+
+completed multiplier from perceived lifetime table  (
+            (0,3),(10,2.1),(20,1.6),(30,1.4),(40,1.3),(50,1.2),(60,1.1)
+            ,(70,1.05),(80,1) )
+	~	Dmnl
+	~	  Table relating perceived life expectancy to birth
+		         rate compensation (CMPLET#36.1).
+	|
+
+delayed industrial output per capita  =
+        SMOOTH3 ( industrial output per capita ,
+             social adjustment delay )
+	~	$/(Person*year)
+	~	  Delayed industrial output per capita (DIOPC#40).
+	|
+
+desired completed family size  =
+        IF THEN ELSE ( Time
+                  >= zero population growth time ,
+             2,
+             desired completed family size normal
+                  * family response to social norm
+                  * social family size normal )
+	~	Dmnl
+	~	  Desired completed family size (DCFS#38)
+	|
+
+desired completed family size normal  = 3.8
+	~	Dmnl
+	~	  DESIRED COMPLETED FAMILY SIZE NORMAL (DCFSN#38.2).
+	|
+
+desired total fertility  =
+        desired completed family size
+             * completed multiplier from perceived lifetime
+	~	Dmnl
+	~	  DESIRED TOTAL FERTILITY (DTF#35).
+	|
+
+family income expectation  =
+        ( industrial output per capita
+             - average industrial output per capita )
+             / average industrial output per capita
+	~	Dmnl
+	~	  Family income expectations (FIE#42).
+	|
+
+family response to social norm  =
+        family response to social norm table ( family income expectation )
+	~	Dmnl
+	~	  FAMILY RESPONSE TO SOCIAL NORM (FRSN#41).
+	|
+
+family response to social norm table  (
+            (-0.2,0.5),(-0.1,0.6),(0,0.7),(0.1,0.85),(0.2,1) )
+	~	Dmnl
+	~	  The table relating income expectations to family
+		         size (FRSNT#41.1).
+	|
+
+fecundity multiplier=
+	fecundity multiplier table ( life expectancy/one year )
+	~	Dmnl
+	~	  FECUNDITY MULTIPLIER (FM#34).
+	|
+
+fecundity multiplier table  (
+            (0,0),(10,0.2),(20,0.4),(30,0.6),(40,0.7),(50,0.75),(60,0.79)
+            ,(70,0.84),(80,0.87) )
+	~	Dmnl
+	~	  Table relating life expectancy to fecundity
+		         (FMT#34.1).
+	|
+
+fertility control allocation per capita  =
+        fraction services allocated to fertility control
+             * service output per capita
+	~	$/(Person*year)
+	~	  FERTILITY CONTROL ALLOCATIONS PER CAPITA (FCAPC#47).
+	|
+
+fertility control effectiveness=
+	IF THEN ELSE ( Time >= fertility control effectiveness time
+	,  1
+	,  ( fertility control effectiveness table (
+	     fertility control facilities per capita/GDP pc unit ) ) )
+	~	Dmnl
+	~	  Fertility control effectiveness (FCE#45).
+	|
+
+fertility control effectiveness table  (
+            (0,0.75),(0.5,0.85),(1,0.9),(1.5,0.95),(2,0.98),(2.5,0.99)
+            ,(3,1) )
+	~	Dmnl
+	~	  Fertility control effectiveness table (FCET#45.2).
+	|
+
+fertility control facilities per capita  =
+        SMOOTH3 ( fertility control allocation per capita ,
+             health services impact delay )
+	~	$/(Person*year)
+	~	  FERTILITY CONTROL FACILITIES PER CAPITA (FCFPC#46).
+	|
+
+fraction services allocated to fertility control  =
+        fraction services allocated to fertility control table ( need for fertility control\
+		 )
+	~	Dmnl
+	~	  FRACTION OF SERVICES ALLOCATED TO FERTILITY CONTROL
+		         (FSAFC#48).
+	|
+
+fraction services allocated to fertility control table  (
+            (0,0),(2,0.005),(4,0.015),(6,0.025),(8,0.03),(10,0.035) )
+	~	Dmnl
+	~	  Table relating the need for fertility control to
+		         services allocated. (FSAFCT#48.1).
+	|
+
+income expectation averaging time  = 3
+	~	year
+	~	  Income expectation averaging time (IEAT#43.1)
+	|
+
+lifetime perception delay  = 20
+	~	year
+	~	  Lifetime perception delay (LPD#37.1)
+	|
+
+maximum total fertility  =
+        maximum total fertility normal
+             * fecundity multiplier
+	~	Dmnl
+	~	  MAXIMUM TOTAL FERTILITY (MTF#33).
+	|
+
+maximum total fertility normal  = 12
+	~	Dmnl
+	~	  The normal maximum fertility that would be realized
+		        if people had sufficient food and perfect health.
+		         (MTFN#33.1)
+	|
+
+need for fertility control  =
+        ( maximum total fertility
+             / desired total fertility )
+             - 1
+	~	Dmnl
+	~	  NEED FOR FERTILITY CONTROL (NFC#44).
+	|
+
+perceived life expectancy  =
+        SMOOTH3 ( life expectancy ,
+             lifetime perception delay )
+	~	year
+	~	  Perceived life expectancy (PLE#37)
+	|
+
+reproductive lifetime  = 30
+	~	year
+	~	  The number of years people can reproduce (RLT#30.1)
+	|
+
+social family size normal=
+	social family size normal table ( delayed industrial output per capita/GDP pc unit )
+	~	Dmnl
+	~	  SOCIAL FAMILY SIZE NORM (SFSN#39).
+	|
+
+social family size normal table(
+	(0,1.25),(200,0.94),(400,0.715),(600,0.59),(800,0.5))
+	~	Dmnl
+	~	  Table relating material well being to family size
+		         (SFSNT#39.1)
+	|
+
+social adjustment delay  = 20
+	~	year
+	~	  SOCIAL ADJUSTMENT DELAY (SAD#40.1).
+	|
+
+fertility control effectiveness time  = 4000
+	~	year
+	~	  FERTILITY CONTROL EFFECTIVENESS SET TIME
+		         (FCEST#45.1).
+	|
+
+population equilibrium time  = 4000
+	~	year
+	~	  The time at which, as a model test, the population
+		         is forced to remain constant. (PET#30.2)
+	|
+
+zero population growth time  = 4000
+	~	year
+	~	  TIME WHEN DESIRED FAMILY SIZE EQUALS 2 CHILDREN
+		         (ZPGT#38.1)
+	|
+
+THOUSAND  = 1000
+	~	C
+	~	  Units converted for /1000 rates (--).
+	|
+
+total fertility  =
+        MIN ( maximum total fertility ,
+             ( maximum total fertility
+                  * ( 1
+                       - fertility control effectiveness )
+                  + desired total fertility
+                       * fertility control effectiveness ) )
+	~	Dmnl
+	~	  TOTAL FERTILITY (TF#32).
+	|
+
+********************************************************
+	.Population.Death
+********************************************************~
+
+		DEATH RATE SUBSECTOR
+	|
+
+crowding multiplier from industry=
+	crowding multiplier from industry table ( industrial output per capita/GDP pc unit )
+	~	Dmnl
+	~	  CROWDING MULTIPLIER FROM INDUSTRIALIZATION (CMI#27).
+	|
+
+crowding multiplier from industry table  (
+            (0,0.5),(200,0.05),(400,-0.1),(600,-0.08),(800,-0.02),(1000,0.05)
+            ,(1200,0.1),(1400,0.15),(1600,0.2) )
+	~	Dmnl
+	~	  Table relating industrial output to crowding
+		         (CMIT#27.1).
+	|
+
+death rate  =
+        THOUSAND
+             * deaths
+             / population
+	~	C/year
+	~	  CRUDE DEATH RATE (CDR#18)
+	~	:SUPPLEMENTARY
+	|
+
+deaths  =
+        deaths 0 to 14
+             + deaths 15 to 44
+             + deaths 45 to 64
+             + deaths 65 plus
+	~	Person/year
+	~	  The total number of deaths per year for all age
+		         groups (D#17).
+	|
+
+effective health services per capita  =
+        SMOOTH ( health services per capita ,
+             health services impact delay )
+	~	$/(Person*year)
+	~	  Effective health services per capita - delayed from
+		         allocation (EHSPC#22)
+	|
+
+fraction of population urban=
+	fraction of population urban table ( population/unit population )
+	~	Dmnl
+	~	  FRACTION OF POPULATION URBAN (FPU#26).
+	|
+
+fraction of population urban table  (
+            (0,0),(2e+09,0.2),(4e+09,0.4),(6e+09,0.5),(8e+09,0.58)
+            ,(1e+10,0.65),(1.2e+10,0.72),(1.4e+10,0.78),(1.6e+10,0.8)
+             )
+	~	Dmnl
+	~	  Table relating population to the fraction of
+		         population that is urban (FPUT#26.1).
+	|
+
+health services per capita=
+	health services per capita table ( service output per capita/GDP pc unit )
+	~	$/(Person*year)
+	~	  Health services allocation per capita (HSAPC#21).
+	|
+
+health services per capita table  (
+            (0,0),(250,20),(500,50),(750,95),(1000,140),(1250,175),(1500,200)
+            ,(1750,220),(2000,230) )
+	~	$/(Person*year)
+	~	  The table relating service output to health services
+		         (HSAPCT#21.1).
+	|
+
+health services impact delay  = 20
+	~	year
+	~	  The delay between allocating health services, and
+		         realizing the benefit (HSID#22.1).
+	|
+
+life expectancy normal  = 28
+	~	year
+	~	  The normal life expectancy with subsistance food, no
+		         medical care and no industrialization (LEN#19.1)
+	|
+
+life expectancy  =
+        life expectancy normal
+             * lifetime multiplier from food
+             * lifetime multiplier from health services
+             * lifetime multiplier from persistent pollution
+             * lifetime multiplier from crowding
+	~	year
+	~	  The average life expectancy (LE#19).
+	|
+
+lifetime multiplier from crowding  =
+        1
+             - ( crowding multiplier from industry
+                  * fraction of population urban )
+	~	Dmnl
+	~	  LIFETIME MULTIPLIER FROM CROWDING (LMC#28)
+	|
+
+lifetime multiplier from food  =
+        lifetime multiplier from food table ( food per capita
+                  / subsistence food per capita )
+	~	Dmnl
+	~	  The life expectancy multiplier from food (LMF#20)
+	|
+
+lifetime multiplier from food table  (
+            (0,0),(1,1),(2,1.43),(3,1.5),(4,1.5),(5,1.5) )
+	~	Dmnl
+	~	  The table ralating relative food to the life
+		         expectancy multiplier for food (LMFT#20.1)
+	|
+
+lifetime multiplier from health services=
+	IF THEN ELSE ( Time
+	                  > 1940,
+	             lifetime multiplier from health services 2 ,
+	             lifetime multiplier from health services 1 )
+	~	Dmnl
+	~	  The life expectancy multiplier from health services
+		         (LMHS#23).
+	|
+
+lifetime multiplier from health services 1=
+	lifetime multiplier from health services 1 table (
+	effective health services per capita/GDP pc unit )
+	~	Dmnl
+	~	  The life expectancy multiplier from health services
+		         before 1940 (LMHS1#24).
+	|
+
+lifetime multiplier from health services 1 table  (
+            (0,1),(20,1.1),(40,1.4),(60,1.6),(80,1.7),(100,1.8) )
+	~	Dmnl
+	~	  Table relating effective health care to life
+		         expectancy (LMHS1T#24.1).
+	|
+
+lifetime multiplier from health services 2=
+	lifetime multiplier from health services 2 table (
+	effective health services per capita/GDP pc unit )
+	~	Dmnl
+	~	  The life expectancy multipier from health services
+		         value after 1940 (LMHS2#25).
+	|
+
+lifetime multiplier from health services 2 table  (
+            (0,1),(20,1.5),(40,1.9),(60,2),(80,2),(100,2) )
+	~	Dmnl
+	~	  Table relating effective health care to life
+		         expectancy (LMHS2T#25.1)
+	|
+
+lifetime multiplier from persistent pollution  =
+        lifetime multiplier from persistent pollution table ( persistent pollution index\
+		 )
+	~	Dmnl
+	~	  LIFETIME MULTIPLIER FROM PERSISTENT POLLUTION
+		         (LMP#29)
+	|
+
+lifetime multiplier from persistent pollution table  (
+            (0,1),(10,0.99),(20,0.97),(30,0.95),(40,0.9),(50,0.85),(60,0.75)
+            ,(70,0.65),(80,0.55),(90,0.4),(100,0.2) )
+	~	Dmnl
+	~	  Table relating persistent pollution to life
+		         expectancy (LMPT#29.1)
+	|
+
+********************************************************
+	.Resource
+********************************************************~
+
+		NONRENEWABLE RESOURCE SECTOR
+	|
+
+desired resource use rate  = 4.8e+09
+	~	Resource units/year
+	~	  Desired non-renewable resource usage rate (DNRUR#--)
+	|
+
+fraction of resources remaining  =
+        Nonrenewable Resources
+             / initial nonrenewable resources
+	~	Dmnl
+	~	  Non-renewable resource fraction remaining
+		         (NRFR#133).
+	|
+
+resource usage rate  =
+        ( ( ( population ) )
+             * ( per capita resource use multiplier ) )
+             * ( resource use factor )
+	~	Resource units/year
+	~	  Non-renewable resource use rate (NRUR#130).
+	|
+
+initial nonrenewable resources  = 1e+12
+	~	Resource units
+	~	  NONRENEWABLE RESOURCE INITIAL (NRI#129.2).
+	|
+
+Nonrenewable Resources  =
+        INTEG( ( - resource usage rate  ) ,
+             initial nonrenewable resources )
+	~	Resource units
+	~	  Non-renewable resource (NR#129)
+	|
+
+fraction of capital allocated to obtaining resources 1  =
+        fraction of capital allocated to obtaining resources 1 table ( fraction of resources remaining
+ )
+	~	Dmnl
+	~	  Fraction of capital allocated to obtaining resources
+		         before switch time (FCAOR1#135).
+	|
+
+fraction of capital allocated to obtaining resources 1 table  (
+            (0,1),(0.1,0.9),(0.2,0.7),(0.3,0.5),(0.4,0.2),(0.5,0.1),(0.6,0.05)
+            ,(0.7,0.05),(0.8,0.05),(0.9,0.05),(1,0.05) )
+	~	Dmnl
+	~	  Table relating the fraction of resources remaining
+		        to capital allocated to resource extraction
+		         (FCAOR1T#135.1).
+	|
+
+fraction of capital allocated to obtaining resources 2  =
+        fraction of capital allocated to obtaining resources 2 table ( fraction of resources remaining
+ )
+	~	Dmnl
+	~	  Fraction of capital allocated to obtaining resources
+		         after switch time (FCAOR2#136).
+	|
+
+fraction of capital allocated to obtaining resources 2 table  (
+            (0,1),(0.1,0.2),(0.2,0.1),(0.3,0.05),(0.4,0.05),(0.5,0.05)
+            ,(0.6,0.05),(0.7,0.05),(0.8,0.05),(0.9,0.05),(1,0.05) )
+	~	Dmnl
+	~	  Table relating the fraction of resources remaining
+		        to capital allocated to resource extraction
+		         (FCAOR2T#136.1).
+	|
+
+resource use factor 1  = 1
+	~	Dmnl
+	~	  The nonrenewable resource usage factor before the
+		         policy year (NRUF1#131.1).
+	|
+
+resource use fact 2  =
+        SMOOTH3 ( Resource Conservation Technology ,
+             technology development delay )
+	~	Dmnl
+	~	  The nonrenewable resource usage factor after the
+		         policy year (NRUF2#131.2).
+	|
+
+resource technology change rate multiplier  =
+        resource technology change mult table ( 1
+                  - resource usage rate
+                       / desired resource use rate )
+	~	Dmnl/year
+	~	  Resource technology change multiplier (NRCM#--)
+	|
+
+resource technology change mult table  (
+            (-1,0),(0,0) )
+	~	Dmnl/year
+	~	  Table relating resource use to technological change.
+		         (NRCMT#--)
+	|
+
+per capita resource use multiplier=
+	per capita resource use mult table ( industrial output per capita/GDP pc unit )
+	~	Resource unit/(Person*year)
+	~	  Per capita resource usage multiplier (PCRUM#132).
+	|
+
+per capita resource use mult table  (
+            (0,0),(200,0.85),(400,2.6),(600,3.4),(800,3.8),(1000,4.1),
+            (1200,4.4),(1400,4.7),(1600,5) )
+	~	Resource units/(Person*year)
+	~	  Table relating industrial output to resource usage
+		         per capita (PCRUMT#132.1).
+	|
+
+Resource Conservation Technology= INTEG (
+	  resource technology change rate ,
+
+		             1)
+	~	Dmnl
+	~	  Non-renewable resource technology (NRTD#--)
+	|
+
+resource technology change rate  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             Resource Conservation Technology
+                  * resource technology change rate multiplier ,
+             0)
+	~	1/year
+	~	  RESOURCE TECHNOLOGY IMPROVEMENT RATE (NRATE#--).
+	|
+
+fraction of industrial capital allocated to obtaining resources  =
+        IF THEN ELSE ( Time
+                  >= fraction of industrial capital allocated to obtaining resources switch time\
+		 ,
+             fraction of capital allocated to obtaining resources 2 ,
+             fraction of capital allocated to obtaining resources 1 )
+	~	Dmnl
+	~	  FRACTION OF CAPITAL ALLOCATED TO OBTAINING RESOURCES
+		         (FCAOR#134).
+	|
+
+resource use factor  =
+        IF THEN ELSE ( Time
+                  >= POLICY YEAR ,
+             resource use fact 2 ,
+             resource use factor 1 )
+	~	Dmnl
+	~	  NONRENEWABLE RESOURCE USAGE FACTOR (NRUF#131).
+	|
+
+fraction of industrial capital allocated to obtaining resources switch time  = 4000
+	~	year
+	~	  Time at which to switch between alternative fraction
+		        of capital alocated to obtaining resources
+		         (FCAORTM#--).
+	|
+
+technology development delay  = 20
+	~	year
+	~	  The technology development delay (TDD#--)
+	|
+
+********************************************************
+	.Supplementary
+********************************************************~
+
+		SUPPLEMENTARY EQUATIONS
+	|
+
+consumed industrial output  =
+        industrial output
+             * fraction of industrial output allocated to consumption
+	~	$/year
+	~	  Consumed industrial output (CIO#--).
+	|
+
+consumed industrial output per capita  =
+        consumed industrial output
+             / population
+	~	$/(Person*year)
+	~	  Consumption Industrial Output per Capita (CIOPC#--)
+	~	:SUPPLEMENTARY
+	|
+
+fraction of output in agriculture  =
+        ( PRICE OF FOOD
+             * food )
+             / ( PRICE OF FOOD
+                  * food
+                  + service output
+                  + industrial output )
+	~	Dmnl
+	~	  FRACTION OF OUTPUT IN AGRICULTURE (FAO#147)
+	~	:SUPPLEMENTARY
+	|
+
+fraction of output in industry  =
+        industrial output
+             / ( PRICE OF FOOD
+                  * food
+                  + service output
+                  + industrial output )
+	~	Dmnl
+	~	  Fraction of output that is industrial output
+		         (FOI#148).
+	~	:SUPPLEMENTARY
+	|
+
+fraction of output in services  =
+        service output
+             / ( PRICE OF FOOD
+                  * food
+                  + service output
+                  + industrial output )
+	~	Dmnl
+	~	  FRACTION OF OUTPUT IN SERVICES (FOS#149).
+	~	:SUPPLEMENTARY
+	|
+
+persistent pollution intensity industry  =
+        persistent pollution generation industry
+             * persistent pollution generation factor
+             / industrial output
+	~	Pollution units/$
+	~	  pollution intensity indicator (PLINID#--).
+	~	:SUPPLEMENTARY
+	|
+
+PRICE OF FOOD  = 0.22
+	~	$/Veg eq kg
+	~	  The price of food used as a basis for comparing
+		         agricultural and industrial output. (--).
+	|
+
+resource use intensity  =
+        resource usage rate
+             / industrial output
+	~	Resource units/$
+	~	  ADAPTIVE TECHNOLOGICAL CONTROL CARDS nonrenewable
+		         resource usage intensity (RESINT#--)
+	~	:SUPPLEMENTARY
+	|
+
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Title Page
+$192-192-192,0,Times New Roman|12||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+12,1,0,299,247,86,19,8,4,0,0,0,0,0,0
+Developed from the World model by Jay W. Forrester
+12,2,0,284,160,2,11,0,0,0,0,-1,0,0,0
+12,3,0,294,37,142,19,0,4,0,58,-1,0,0,0,0-0-0,0-0-0,Arial|24|U|0-0-255
+World3-2003 Model
+12,4,0,90,280,2,10,0,0,0,24,-1,0,0,0,0-0-0,0-0-0,|11|B|0-0-0
+12,5,0,301,307,193,9,0,4,0,56,-1,0,0,0,0-0-0,0-0-0,Arial|11|B|0-0-0
+Use Page Down / Page Up keys to move through views
+12,6,0,299,327,151,9,0,4,0,56,-1,0,0,0,0-0-0,0-0-0,Arial|11|B|0-0-0
+(or button at bottom that says "Title Page")
+12,7,0,289,96,230,11,0,4,0,8,-1,0,0,0,-1--1--1,0-0-0,|14||0-0-0
+By Donella H. Meadows, Dennis L. Meadows, Jorgen Randers
+12,8,0,290,142,75,20,8,4,0,24,-1,0,0,0,0-0-0,0-0-0,|14|I|0-0-0
+Limits to Growth - the 30-Year Update
+12,9,0,290,190,97,28,8,4,0,0,-1,0,0,0
+Chelsea Green Publishing Co., White River Junction VT 05001, 2004
+12,10,0,293,364,31,11,8,4,0,0,-1,0,0,0
+See Also:
+12,11,0,299,433,148,47,8,4,0,0,-1,0,0,0
+Dennis L. Meadows, William W. Behrens III, Donella H. Meadows, Roger F. Naill, Jorgen Randers, Erich K.O. Zahn, 1974 "Dynamics of Growth in a Finite World," Cambridge MA: Wright-Allen Press
+12,12,0,299,525,103,28,8,4,0,0,-1,0,0,0
+Jay W. Forrester, 1971, "World Dynamics," Cambridge MA: Wright-Allen Press
+12,13,0,296,689,109,28,8,4,0,0,-1,0,0,0
+Donella H. Meadows et al., 1972, "The Limits to Growth," New York: Universe Books
+12,14,0,293,608,139,38,8,4,0,0,-1,0,0,0
+Donella H. Meadows, Dennis L. Meadows, Jorgen Randers, 1992, "Beyond the Limits," White River Junction VT: Chelsea Green Publishing Co.
+12,15,0,301,281,149,11,0,4,0,0,-1,0,0,0
+wrld3-03.vmf revision date September 29, 2005
+12,16,0,745,176,53,53,6,135,0,4,-1,0,2,0,-1--1--1,192-192-192,|12||0-0-0
+Demographics
+12,17,0,799,263,46,46,6,135,0,4,-1,0,3,0,-1--1--1,192-192-192,|12||0-0-0
+Fertility
+12,18,0,693,268,49,49,6,135,0,4,-1,0,4,0,-1--1--1,192-192-192,|12||0-0-0
+Life Expectancy
+12,19,0,973,410,42,42,6,135,0,4,-1,0,5,0,-1--1--1,192-192-192,|12||0-0-0
+Pollution
+12,20,0,877,535,49,49,6,135,0,4,-1,0,6,0,-1--1--1,192-192-192,|12||0-0-0
+Resources
+12,21,0,1005,261,49,49,6,135,0,4,-1,0,7,0,-1--1--1,192-192-192,|12||0-0-0
+Food
+12,22,0,1128,265,51,51,6,135,0,4,-1,0,8,0,-1--1--1,192-192-192,|12||0-0-0
+Agriculture
+12,23,0,1072,172,46,46,6,135,0,4,-1,0,9,0,-1--1--1,192-192-192,|12||0-0-0
+Land
+12,24,0,815,454,42,42,6,135,0,4,-1,0,10,0,-1--1--1,192-192-192,|12||0-0-0
+Industry
+12,25,0,718,453,42,42,6,135,0,4,-1,0,11,0,-1--1--1,192-192-192,|12||0-0-0
+Services
+12,26,0,764,536,46,46,6,135,0,4,-1,0,12,0,-1--1--1,192-192-192,|12||0-0-0
+Jobs
+12,27,0,1115,530,45,45,6,135,0,4,-1,0,13,0,-1--1--1,192-192-192,|12||0-0-0
+Welfare & Footprint
+12,28,0,1214,530,39,39,6,135,0,4,-1,0,14,0,-1--1--1,192-192-192,|12||0-0-0
+Output
+12,29,0,295,771,93,28,8,7,0,0,-1,0,0,0
+Interface upgrades, Tom Fiddaman, Ventana Systems, Inc., 2013
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Demographics
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,Population 0 To 14,237,218,40,20,3,3,0,3,0,2,0,0,130-130-130,0-0-0,|10||1-1-1
+12,2,48,232,332,10,8,0,3,0,0,-1,0,0,0
+11,3,48,413,283,7,4,33,3,0,0,4,0,0,0
+10,4,deaths 15 to 44,462,283,42,9,32,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,5,initial population 0 to 14,183,156,66,9,0,3,0,3,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,6,Population 15 To 44,413,216,40,20,3,3,0,3,0,2,0,0,130-130-130,0-0-0,|10||1-1-1
+10,7,deaths,250,486,20,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+11,8,4508,689,215,4,7,34,3,0,0,1,0,0,0
+10,9,maturation 64 to 65,689,235,31,13,40,3,0,3,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,10,initial population 15 to 44,340,155,69,9,0,3,0,3,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,11,Population 45 To 64,597,216,40,20,3,3,0,3,0,2,0,0,130-130-130,0-0-0,|10||1-1-1
+10,12,reproductive lifetime,111,177,37,13,8,3,0,3,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+12,13,48,412,339,10,8,0,3,0,0,-1,0,0,0
+10,14,population equilibrium time,89,337,46,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,15,initial population 54 to 64,672,159,69,9,0,3,0,3,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,16,Population 65 Plus,777,216,40,20,3,3,0,3,0,2,0,0,130-130-130,0-0-0,|10||1-1-1
+10,17,Time,78,297,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,18,total fertility,132,383,42,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,19,initial population 65 plus,838,159,68,9,0,3,0,3,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+12,20,48,101,220,10,8,0,3,0,2,-1,0,0,0,-1--1--1,0-0-0,|10||1-1-1
+11,21,48,505,216,4,7,34,3,0,0,1,0,0,0
+10,22,maturation 44 to 45,505,237,31,14,40,3,0,3,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+12,23,48,598,336,10,8,0,3,0,0,-1,0,0,0
+10,24,mortality 0 to 14,341,321,45,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+12,25,48,918,219,10,8,0,3,0,2,-1,0,0,0,-1--1--1,0-0-0,|10||1-1-1
+10,26,mortality 15 to 44,493,338,48,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+11,27,4108,157,221,4,7,34,3,0,0,1,0,0,0
+10,28,births,157,237,18,9,32,3,0,3,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+11,29,4316,321,216,4,7,34,3,0,0,1,0,0,0
+10,30,maturation 14 to 15,321,237,31,14,40,3,0,3,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+11,31,4204,235,278,7,4,33,3,0,0,4,0,0,0
+10,32,deaths 0 to 14,281,278,39,9,32,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+11,33,4044,599,270,7,4,33,3,0,0,4,0,0,0
+10,34,deaths 45 to 64,648,270,42,9,32,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+11,35,4124,862,217,4,7,34,3,0,0,1,0,0,0
+10,36,deaths 65 plus,862,233,41,9,32,3,0,3,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,37,mortality 45 to 64,693,325,48,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,38,mortality 65 plus,885,318,46,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,39,mortality 45 to 64 table,657,375,48,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,40,mortality 15 to 44 table,517,392,48,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,41,mortality 0 to 14 table,332,373,48,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,42,mortality 65 plus table,822,370,46,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,43,labor force,506,157,31,9,0,3,0,0,-1,0,0,0
+10,44,labor force participation fraction,506,102,63,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,45,population,509,33,31,9,0,3,0,0,-1,0,0,0
+1,46,5,1,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(199,176)|
+1,47,10,6,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(364,175)|
+1,48,15,11,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(647,177)|
+1,49,19,16,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(818,177)|
+1,50,27,1,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(179,221)|
+1,51,27,20,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(132,221)|
+1,52,29,6,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(349,216)|
+1,53,29,1,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(297,216)|
+1,54,21,11,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(533,216)|
+1,55,21,6,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(477,216)|
+1,56,8,16,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(715,215)|
+1,57,8,11,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(661,215)|
+1,58,35,25,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(887,217)|
+1,59,35,16,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(837,217)|
+1,60,31,2,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(235,303)|
+1,61,31,1,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(235,256)|
+1,62,3,13,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(413,309)|
+1,63,3,6,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(413,257)|
+1,64,33,23,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(599,301)|
+1,65,33,11,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(599,251)|
+1,66,7,28,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(187,365)|
+1,67,6,27,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(261,168)|
+1,68,12,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(133,199)|
+1,69,14,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(120,290)|
+1,70,17,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(111,271)|
+1,71,18,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(142,316)|
+1,72,24,32,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(316,303)|
+1,73,1,32,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(258,247)|
+1,74,26,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(480,316)|
+1,75,6,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(436,249)|
+1,76,37,34,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(674,302)|
+1,77,11,34,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(622,243)|
+1,78,39,37,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(671,353)|
+1,79,40,26,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(506,368)|
+1,80,41,24,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(335,351)|
+1,81,26,22,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(497,296)|
+1,82,6,22,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(462,246)|
+1,83,37,9,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(691,288)|
+1,84,11,9,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(649,247)|
+1,85,24,30,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(333,288)|
+1,86,1,30,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(278,250)|
+1,87,38,36,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(875,282)|
+1,88,16,36,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(819,258)|
+1,89,42,38,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(850,346)|
+1,90,32,7,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(278,376)|
+1,91,4,7,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(403,403)|
+1,92,34,7,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(547,423)|
+1,93,36,7,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(680,440)|
+1,94,44,43,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(506,124)|
+1,95,6,43,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(461,184)|
+1,96,11,43,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(548,184)|
+1,97,1,45,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(322,93)|
+1,98,6,45,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(430,111)|
+1,99,11,45,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(581,107)|
+1,100,16,45,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(693,100)|
+1,101,102,24,1,0,0,0,0,0,0,-1--1--1,,1|(387,364)|
+10,102,one year,357,407,32,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,103,one year,920,354,32,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,104,103,38,0,0,0,0,0,0,0,-1--1--1,,1|(907,340)|
+10,105,life expectancy,354,245,49,9,8,2,1,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,106,105,24,0,1,0,0,0,0,0,-1--1--1,,1|(348,276)|
+10,107,life expectancy,515,214,49,9,8,2,1,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,108,107,26,0,1,0,0,0,0,0,-1--1--1,,1|(505,269)|
+10,109,life expectancy,704,223,49,9,8,2,1,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,110,109,37,0,1,0,0,0,0,0,-1--1--1,,1|(699,267)|
+10,111,life expectancy,876,168,49,9,8,2,1,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,112,111,38,0,1,0,0,0,0,0,-1--1--1,,1|(879,236)|
+10,113,one year,731,352,32,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,114,one year,559,365,32,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,115,113,37,0,0,0,0,0,64,0,-1--1--1,,1|(717,342)|
+1,116,114,26,0,0,0,0,0,64,0,-1--1--1,,1|(532,354)|
+12,117,0,111,61,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,118,1771044,1186,202,193,165,3,156,0,0,1,0,0,0
+Population
+12,119,1247406,1186,521,192,149,3,188,0,0,1,0,0,0
+Population_Rates
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Fertility
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,5,0
+10,1,total fertility,431,31,35,9,0,3,0,0,-1,0,0,0
+10,2,desired total fertility,593,29,63,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,3,fertility control effectiveness,327,68,45,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,4,maximum total fertility,565,69,60,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,5,fertility control effectiveness table,179,98,93,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,6,fertility control facilities per capita,349,138,57,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,7,fertility control effectiveness time,189,34,91,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,8,Time,177,61,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,9,fertility control allocation per capita,385,200,58,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,10,health services impact delay,170,137,84,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,11,fraction services allocated to fertility control,456,263,73,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,12,service output per capita,207,200,75,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,13,fecundity multiplier,642,117,54,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,14,maximum total fertility normal,768,67,80,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,15,fecundity multiplier table,796,144,68,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,16,life expectancy,663,168,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,17,fraction services allocated to fertility control table,236,259,75,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,18,need for fertility control,522,140,45,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,19,desired total fertility,604,237,38,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,20,completed multiplier from perceived lifetime,665,337,67,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,21,desired completed family size,461,324,54,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,22,desired completed family size normal,211,324,99,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,23,family response to social norm,400,392,54,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,24,social family size normal,549,372,66,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,25,zero population growth time,235,348,77,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,26,Time,326,304,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,27,completed multiplier from perceived lifetime table,819,377,72,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,28,perceived life expectancy,727,232,40,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,29,delayed industrial output per capita,554,432,52,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,30,lifetime perception delay,809,187,67,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,31,social family size normal table,685,406,48,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,32,industrial output per capita,649,500,81,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,33,social adjustment delay,718,458,65,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,34,family income expectation,445,460,43,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,35,family response to social norm table,281,445,98,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,36,average industrial output per capita,474,528,38,23,3,3,0,1,0,2,0,0,130-130-130,0-0-0,|10||0-255-128
+10,37,income expectation averaging time,278,529,94,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-255-128
+1,38,2,1,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(504,29)|
+1,39,3,1,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(395,62)|
+1,40,4,1,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(475,60)|
+1,41,5,3,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(245,84)|
+1,42,6,3,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(331,100)|
+1,43,7,3,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(246,47)|
+1,44,8,3,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(233,63)|
+1,45,9,6,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(361,177)|
+1,46,10,6,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(266,137)|
+1,47,11,9,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(407,232)|
+1,48,12,9,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(297,200)|
+1,49,13,4,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(609,96)|
+1,50,14,4,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(663,67)|
+1,51,15,13,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(725,131)|
+1,52,16,13,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(655,148)|
+1,53,17,11,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(340,260)|
+1,54,18,11,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(516,202)|
+1,55,19,18,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(568,185)|
+1,56,4,18,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(553,98)|
+1,57,20,19,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(621,302)|
+1,58,21,19,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(539,311)|
+1,59,22,21,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(351,324)|
+1,60,23,21,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(442,363)|
+1,61,24,21,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(502,357)|
+1,62,25,21,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(352,335)|
+1,63,26,21,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(370,310)|
+1,64,27,20,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(714,370)|
+1,65,28,20,1,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(708,299)|
+1,66,16,28,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(687,192)|
+1,67,30,28,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(778,203)|
+1,68,29,24,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(551,406)|
+1,69,31,24,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(617,389)|
+1,70,32,29,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(610,472)|
+1,71,33,29,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(640,445)|
+1,72,34,23,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(426,432)|
+1,73,35,23,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(327,424)|
+1,74,36,34,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(460,495)|
+1,75,32,34,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(552,480)|
+1,76,37,36,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(397,528)|
+1,77,32,36,0,0,0,0,1,0,0,0-0-255,|10||0-255-128,1|(559,513)|
+10,78,one year,801,334,32,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,79,78,20,0,0,0,0,0,0,0,-1--1--1,,1|(757,334)|
+10,80,one year,780,107,32,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,81,80,13,0,0,0,0,0,0,0,-1--1--1,,1|(728,110)|
+10,82,GDP pc unit,407,99,41,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,83,82,3,0,0,0,0,0,0,0,-1--1--1,,1|(380,88)|
+10,84,GDP pc unit,559,338,41,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,85,84,24,0,0,0,0,0,0,0,-1--1--1,,1|(556,348)|
+12,86,0,45,59,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,87,0,1043,164,150,150,3,44,0,0,2,0,0,0
+total fertility,graph
+12,88,0,1043,474,150,150,3,44,0,0,1,0,0,0
+Fertility_Drivers
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Life Expectancy
+$192-192-192,0,Times New Roman|12||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,life expectancy,564,20,47,11,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,2,life expectancy normal,736,30,69,11,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,3,lifetime multiplier from crowding,513,180,53,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,4,lifetime multiplier from food,628,190,53,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,5,lifetime multiplier from health services,433,94,70,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,6,lifetime multiplier from persistent pollution,682,104,70,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,7,lifetime multiplier from persistent pollution table,863,150,77,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||1-1-1
+10,8,persistent pollution index,860,96,85,11,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,9,crowding multiplier from industry,457,276,60,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,10,fraction of population urban,597,322,54,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,11,fraction of population urban table,739,446,102,11,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,12,population,741,388,43,11,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,13,crowding multiplier from industry table,549,462,60,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,14,industrial output per capita,419,412,91,11,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,15,lifetime multiplier from health services 1,246,100,70,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,16,lifetime multiplier from health services 2,367,202,70,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,17,Time,285,58,26,11,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,18,food per capita,814,220,57,11,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,19,lifetime multiplier from food table,837,272,101,11,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,20,subsistence food per capita,761,316,93,11,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,21,effective health services per capita,189,246,40,21,3,3,0,1,0,2,0,0,130-130-130,0-0-0,|10||130-130-130
+10,22,lifetime multiplier from health services 1 table,78,136,70,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,23,health services per capita,190,388,59,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,24,health services impact delay,71,342,46,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,25,health services per capita table,125,486,94,11,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,26,service output per capita,338,478,85,11,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,27,lifetime multiplier from health services 2 table,313,316,70,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,28,2,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(645,24)|
+1,29,3,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(540,84)|
+1,30,4,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(577,76)|
+1,31,5,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(497,51)|
+1,32,6,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(620,55)|
+1,33,7,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(777,127)|
+1,34,8,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(770,99)|
+1,35,9,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(481,234)|
+1,36,10,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(558,257)|
+1,37,11,10,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(677,392)|
+1,38,12,10,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(683,361)|
+1,39,13,9,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(506,375)|
+1,40,14,9,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(434,354)|
+1,41,15,5,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(333,86)|
+1,42,16,5,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(380,150)|
+1,43,17,5,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(330,68)|
+1,44,18,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(725,205)|
+1,45,19,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(749,237)|
+1,46,20,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(704,261)|
+1,47,21,15,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(205,160)|
+1,48,22,15,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(155,119)|
+1,49,23,21,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(175,330)|
+1,50,24,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(123,299)|
+1,51,25,23,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(150,446)|
+1,52,26,23,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(243,462)|
+1,53,21,16,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(256,208)|
+1,54,27,16,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(337,265)|
+10,55,GDP pc unit,360,365,49,11,8,2,0,2,0,0,0,0,0-0-0,0-0-0,|12||92-92-92
+1,56,55,9,0,0,0,0,0,64,0,-1--1--1,,1|(398,329)|
+10,57,unit population,597,388,55,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+1,58,57,10,0,0,0,0,0,0,0,-1--1--1,,1|(597,366)|
+10,59,GDP pc unit,62,434,49,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+10,60,GDP pc unit,124,193,49,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+10,61,GDP pc unit,290,257,49,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+1,62,59,23,0,0,0,0,0,64,0,-1--1--1,,1|(107,417)|
+1,63,60,15,0,0,0,0,0,64,0,-1--1--1,,1|(173,154)|
+1,64,61,16,0,0,0,0,0,64,0,-1--1--1,,1|(316,237)|
+12,65,0,57,51,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|12||0-0-0
+Home
+12,66,19270038,1135,161,150,150,3,12,0,0,2,0,0,0
+life expectancy,graph
+12,67,3542832,1136,466,150,150,3,44,0,0,1,0,0,0
+Lifetime_Multipliers
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Persistent Pollution
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,Persistent Pollution Technology,628,116,40,20,3,3,0,1,0,2,0,0,130-130-130,0-0-0,|10||0-0-0
+10,2,persistent pollution technology change multiplier,727,217,87,17,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+12,3,48,843,122,10,8,0,3,0,0,-1,0,0,0
+11,4,48,756,119,6,8,34,3,0,0,1,0,0,0
+10,5,persistent pollution technology change rate,756,141,69,14,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,6,POLICY YEAR,864,190,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,7,Time,877,166,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,8,desired persistent pollution index,897,241,50,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,9,persistent pollution technology change mult table,802,284,84,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,10,persistent pollution index,622,310,70,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,11,Persistent Pollution,513,412,40,20,3,3,0,1,0,2,0,0,130-130-130,0-0-0,|10||128-128-128
+10,12,persistent pollution in 1970,440,305,74,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,13,initial persistent pollution,454,362,70,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,14,persistent pollution generation rate,263,290,57,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,15,persistent pollution transmission delay,494,495,59,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,16,48,330,410,10,8,0,3,0,0,-1,0,0,0
+10,17,assimilation half life,785,435,55,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,18,48,696,411,10,8,0,3,0,0,-1,0,0,0
+10,19,assimilation half life in 1970,878,402,75,9,0,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,20,3628,405,410,6,8,34,3,0,0,1,0,0,0
+10,21,persistent pollution appearance rate,405,430,62,13,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,22,3868,620,411,6,8,34,3,0,0,1,0,0,0
+10,23,persistent pollution assimilation rate,620,431,56,13,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,24,assimilation half life multiplier,758,357,81,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,25,assimilation half life mult table,858,324,82,9,0,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,26,persistent pollution generation industry,182,212,60,18,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,27,persistent pollution generation agriculture,120,330,65,16,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,28,persistent pollution generation factor,358,211,55,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,29,fraction of resources from persistent materials,184,109,68,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,30,industrial material toxicity index,78,94,53,12,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,31,industrial material emissions factor,73,161,50,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,32,per capita resource use multiplier,74,261,57,13,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,33,population,55,191,38,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,34,persistent pollution generation factor 1,361,118,73,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,35,persistent pollution generation factor 2,473,153,55,18,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,36,Time,484,196,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,37,technology development delay,638,179,85,9,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,38,agricultural input per hectare,269,476,86,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,39,agricultural material toxicity index,76,412,56,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,40,Arable Land,250,389,40,20,3,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,41,fraction of agricultural inputs from persistent materials,151,449,63,18,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,42,POLICY YEAR,515,243,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,43,industrial capital output ratio multiplier from pollution technology,465,36,70,20,8,3,0,0,0,0,0,0
+10,44,industrial capital output ratio multiplier from pollution table,244,37,82,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,45,4,1,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(709,119)|
+1,46,4,3,68,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(797,119)|
+1,47,2,5,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(744,176)|
+1,48,1,4,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(692,85)|
+1,49,6,5,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(821,170)|
+1,50,7,5,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(845,159)|
+1,51,8,2,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(823,244)|
+1,52,9,2,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(771,256)|
+1,53,10,2,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(678,277)|
+1,54,11,10,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(574,362)|
+1,55,12,10,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(526,307)|
+1,56,13,11,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(471,376)|
+1,57,20,11,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(442,410)|
+1,58,20,16,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(369,410)|
+1,59,22,18,4,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(656,411)|
+1,60,22,11,100,0,0,22,1,0,0,1-1-1,|10||128-128-128,1|(583,411)|
+1,61,14,20,1,0,0,0,3,1,0,0-0-255,|10||0-0-0,1|(312,357)|
+1,62,15,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(453,465)|
+1,63,17,23,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(714,459)|
+1,64,11,22,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(570,383)|
+1,65,19,17,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(838,416)|
+1,66,24,17,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(777,381)|
+1,67,25,24,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(814,338)|
+1,68,10,24,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(690,325)|
+1,69,26,14,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(228,243)|
+1,70,27,14,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(164,297)|
+1,71,28,14,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(306,231)|
+1,72,29,26,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(183,151)|
+1,73,30,26,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(122,144)|
+1,74,31,26,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(115,181)|
+1,75,32,26,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(115,241)|
+1,76,33,26,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(100,198)|
+1,77,34,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(359,157)|
+1,78,35,28,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(409,177)|
+1,79,36,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(444,200)|
+1,80,1,35,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(546,117)|
+1,81,37,35,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(561,166)|
+1,82,38,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(203,411)|
+1,83,39,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(93,378)|
+1,84,40,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(188,361)|
+1,85,41,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(137,395)|
+1,86,42,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(448,229)|
+1,87,44,43,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(353,36)|
+10,88,persistent pollution intensity industry,266,162,55,15,8,3,0,0,-1,0,0,0
+10,89,industrial output,281,87,54,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,90,89,88,0,0,0,0,0,0,0,-1--1--1,,1|(275,114)|
+1,91,28,88,0,0,0,0,0,0,0,-1--1--1,,1|(319,190)|
+1,92,26,88,0,0,0,0,0,0,0,-1--1--1,,1|(220,189)|
+1,93,28,43,1,0,0,0,0,64,0,-1--1--1,,1|(417,133)|
+12,94,0,62,39,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,95,0,1123,474,150,150,3,44,0,0,1,0,0,0
+Pollution_Flows
+12,96,0,1122,168,150,150,3,44,0,0,2,0,0,0
+Persistent Pollution,Graph
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Nonrenewable Resources
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,Resource Conservation Technology,459,179,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,2,per capita resource use multiplier,251,412,90,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,3,Nonrenewable Resources,181,328,41,21,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,4,population,427,405,38,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,5,initial nonrenewable resources,66,266,41,18,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,6,48,360,330,10,8,0,3,0,0,-1,0,0,0
+10,7,resource use factor,220,236,53,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,8,48,670,179,10,8,0,3,0,0,-1,0,0,0
+10,9,resource technology change rate multiplier,553,312,61,18,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,10,5564,292,328,6,8,34,3,0,0,1,0,0,0
+10,11,resource usage rate,292,349,31,14,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,12,5436,588,180,6,8,34,3,0,0,1,0,0,0
+10,13,resource technology change rate,588,202,61,14,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,14,POLICY YEAR,139,193,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,15,fraction of industrial capital allocated to obtaining resources,393,574,90,15,8,3,0,0,0,0,0,0
+10,16,desired resource use rate,574,406,69,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,17,resource technology change mult table,662,362,65,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,18,industrial output per capita,456,442,81,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,19,per capita resource use mult table,308,464,91,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,20,resource use factor 1,166,145,58,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,21,resource use fact 2,298,165,52,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,22,Time,116,216,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,23,technology development delay,394,239,92,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,24,fraction of resources remaining,89,411,40,20,8,3,0,0,0,0,0,0
+10,25,fraction of capital allocated to obtaining resources 1,99,512,77,14,8,3,0,0,0,0,0,0
+10,26,fraction of capital allocated to obtaining resources 1 table,99,569,85,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,27,fraction of capital allocated to obtaining resources 2,290,511,79,14,8,3,0,0,0,0,0,0
+10,28,fraction of capital allocated to obtaining resources 2 table,505,507,86,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,29,fraction of industrial capital allocated to obtaining resources switch time,648,569,109,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,30,Time,230,573,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,31,industrial capital output ratio multiplier from resource conservation technology,367,62,85,21,8,3,0,0,0,0,0,0
+10,32,industrial capital output ratio multiplier from resource table,620,70,83,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,33,POLICY YEAR,693,247,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,34,Time,649,262,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,35,5,3,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(114,292)|
+1,36,10,3,4,0,0,22,0,0,0,-1--1--1,,1|(254,328)|
+1,37,10,6,68,0,0,22,0,0,0,-1--1--1,,1|(324,328)|
+1,38,12,1,4,0,0,22,0,0,0,-1--1--1,,1|(540,180)|
+1,39,12,8,68,0,0,22,0,0,0,-1--1--1,,1|(627,180)|
+1,40,2,11,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(257,378)|
+1,41,4,11,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(332,379)|
+1,42,7,10,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(226,271)|
+1,43,9,13,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(583,269)|
+1,44,1,12,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(517,142)|
+1,45,16,9,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(566,370)|
+1,46,11,9,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(413,362)|
+1,47,17,9,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(619,342)|
+1,48,18,2,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(313,431)|
+1,49,19,2,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(284,442)|
+1,50,20,7,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(188,184)|
+1,51,21,7,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(246,187)|
+1,52,14,7,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(172,211)|
+1,53,22,7,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(148,222)|
+1,54,1,21,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(380,143)|
+1,55,23,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(351,206)|
+1,56,5,24,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(75,330)|
+1,57,3,24,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(120,349)|
+1,58,24,25,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(79,452)|
+1,59,26,25,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(99,547)|
+1,60,24,27,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(160,469)|
+1,61,28,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(400,508)|
+1,62,25,15,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(221,551)|
+1,63,27,15,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(319,540)|
+1,64,29,15,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(517,571)|
+1,65,30,15,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(270,573)|
+1,66,32,31,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(528,55)|
+1,67,33,13,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(652,229)|
+1,68,34,13,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(626,239)|
+1,69,7,31,1,0,0,0,0,64,0,-1--1--1,,1|(225,176)|
+10,70,GDP pc unit,205,444,41,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,71,70,2,0,0,0,0,0,0,0,-1--1--1,,1|(221,431)|
+12,72,0,74,76,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,73,0,926,182,150,150,3,44,0,0,2,0,0,0
+Nonrenewable Resources,graph
+12,74,0,926,493,150,150,3,44,0,0,2,0,0,0
+resource usage rate,graph
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Food Production
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,Perceived Food Ratio,133,303,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,2,Time,860,137,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,3,food shortage perception delay,146,374,50,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,4,48,265,304,10,8,0,3,0,0,-1,0,0,0
+11,5,48,218,305,6,8,2,3,0,0,0,0,0,0
+10,6,food per capita,344,405,42,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,7,subsistence food per capita,254,475,76,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,8,food,296,271,15,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,9,population,366,321,38,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,10,Arable Land,258,149,40,20,3,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,11,land fraction harvested,348,186,64,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,12,land yield,223,206,35,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,13,processing loss,388,228,44,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,14,Agricultural Inputs,535,69,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||128-128-128
+10,15,current agricultural inputs,702,147,71,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,16,indicated food per capita 1,326,508,44,13,8,3,0,0,0,0,0,0
+12,17,48,715,68,10,8,0,3,0,0,-1,0,0,0
+11,18,48,641,69,6,8,2,3,0,0,0,0,0,0
+10,19,average life of agricultural inputs 1,777,31,94,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,20,average life of agricultural inputs 2,856,57,62,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,21,POLICY YEAR,594,544,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,22,fraction of agricultural inputs allocated to land development,492,141,91,15,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,23,total agricultural investment,714,223,77,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,24,industrial output,532,224,54,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,25,fraction of industrial output allocated to agriculture,701,304,83,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,26,fraction of industrial output allocated to agriculture 1,530,364,80,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,27,fraction of industrial output allocated to agriculture 2,656,430,77,17,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,28,Time,557,570,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,29,fraction industrial output allocated to agriculture table 2,743,489,88,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,30,POLICY YEAR,847,162,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,31,fraction industrial output allocated to agriculture table 1,492,310,86,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,32,indicated food per capita,462,498,44,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,33,industrial output per capita,178,575,59,13,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,34,indicated food per capita 2,363,595,42,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,35,indicated food per capita table 1,189,523,50,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,36,indicated food per capita table 2,184,612,53,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,37,agricultural input per hectare,363,71,50,14,8,3,0,0,0,0,0,0
+10,38,fraction of agricultural inputs for land maintenance table,175,40,86,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,39,fraction of agricultural inputs for land maintenance,174,99,78,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,40,food ratio,229,419,28,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,41,average life agricultural inputs,800,107,83,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,42,POLICY YEAR,821,351,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,43,Time,760,366,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,44,3,5,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(181,339)|
+1,45,5,1,4,0,0,22,0,0,0,-1--1--1,,1|(192,305)|
+1,46,5,4,68,0,0,22,0,0,0,-1--1--1,,1|(239,305)|
+1,47,8,6,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(300,315)|
+1,48,9,6,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(349,358)|
+1,49,10,8,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(276,208)|
+1,50,11,8,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(325,222)|
+1,51,12,8,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(253,233)|
+1,52,13,8,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(346,247)|
+1,53,18,14,4,0,0,22,0,0,0,-1--1--1,,1|(605,69)|
+1,54,18,17,100,0,0,22,2,0,0,-1--1--1,|10||0-0-0,1|(676,69)|
+1,55,22,15,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(600,143)|
+1,56,23,15,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(718,187)|
+1,57,24,23,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(604,223)|
+1,58,25,23,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(714,266)|
+1,59,26,25,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(609,325)|
+1,60,27,25,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(692,368)|
+1,61,29,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(707,464)|
+1,62,31,26,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(506,331)|
+1,63,16,32,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(380,491)|
+1,64,34,32,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(421,556)|
+1,65,21,32,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(542,525)|
+1,66,28,32,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(518,540)|
+1,67,14,37,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(460,69)|
+1,68,10,37,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(307,104)|
+1,69,39,37,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(267,79)|
+1,70,38,39,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(174,62)|
+1,71,1,39,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(141,168)|
+1,72,40,5,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(216,355)|
+1,73,41,18,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(690,90)|
+1,74,6,40,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(297,436)|
+1,75,7,40,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(244,453)|
+1,76,15,18,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(682,99)|
+1,77,19,41,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(785,62)|
+1,78,20,41,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(830,80)|
+1,79,2,41,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(836,125)|
+1,80,30,41,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(828,139)|
+1,81,42,25,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(775,333)|
+1,82,43,25,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(738,343)|
+1,83,33,16,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(245,544)|
+1,84,35,16,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(253,515)|
+1,85,33,34,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(272,584)|
+1,86,36,34,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(272,603)|
+1,87,6,26,2,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(454,407)|
+1,88,6,27,2,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(514,446)|
+1,89,32,26,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(492,437)|
+1,90,32,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(547,467)|
+10,91,GDP pc unit,322,548,41,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,92,91,16,0,0,0,0,0,0,0,-1--1--1,,1|(322,536)|
+1,93,91,34,0,0,0,0,0,0,0,-1--1--1,,1|(334,563)|
+12,94,0,55,70,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,95,6688696,1145,173,211,150,3,188,0,0,2,0,0,0
+agricultural input per hectare,graph
+12,96,18025026,1145,491,212,160,3,188,0,0,1,0,0,0
+Agriculture
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Agriculture Productivity
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,land yield,329,204,34,9,0,3,0,0,-1,0,0,0
+10,2,Land Fertility,121,165,40,20,3,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,3,land yield multiplier from technology,406,268,55,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,4,land yield multiplier from air pollution,271,267,55,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,5,land yield factor 1,567,268,50,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,6,land yield factor 2,536,364,40,20,3,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,7,Time,532,312,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,8,technology development delay,459,421,85,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,9,Land Yield Technology,657,463,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||128-128-128
+10,10,land yield technology change rate multiplier,351,510,65,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,11,48,436,462,10,8,0,3,0,0,-1,0,0,0
+11,12,48,528,463,6,8,34,3,0,0,1,0,0,0
+10,13,land yield technology change rate,528,483,63,13,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,14,land yield multipler from air pollution 1,115,306,54,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,15,land yield multiplier from air pollution 2,253,336,55,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,16,air pollution policy implementation time,370,366,56,18,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,17,Time,356,313,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,18,desired food ratio,176,497,49,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,19,industrial output,111,426,54,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,20,land yield multipler from air pollution table 2,265,411,69,16,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,21,IND OUT IN 1970,137,383,49,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,22,land yield technology change rate multiplier table,159,531,76,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,23,land yield multipler from air pollution table 1,107,241,67,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,24,POLICY YEAR,561,292,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,25,POLICY YEAR,642,544,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,26,Time,655,522,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,27,marginal productivity of agricultural inputs,417,146,62,18,8,3,0,0,0,0,0,0
+10,28,land yield multiplier from capital,569,216,58,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,29,marginal land yield multiplier from capital,571,129,61,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,30,agricultural input per hectare,761,182,53,15,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,31,marginal land yield multiplier from capital table,736,108,79,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,32,land yield multiplier from capital table,729,242,72,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,33,food ratio,185,470,35,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,34,average life agricultural inputs,476,91,90,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,35,industrial capital output ratio multiplier from land yield technology,750,327,67,21,8,3,0,0,0,0,0,0
+10,36,industrial capital output ratio multiplier table,814,402,72,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,37,land life multiplier from land yield 1,193,117,95,9,0,3,0,0,-1,0,0,0
+10,38,inherent land fertility,126,43,65,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,39,land life multiplier from land yield table 1,256,77,67,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,40,land life multiplier from land yield 2,369,40,95,9,0,3,0,0,-1,0,0,0
+10,41,land life multiplier from land yield table 2,597,55,67,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,42,2,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(221,183)|
+1,43,3,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(358,245)|
+1,44,4,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(305,244)|
+1,45,5,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(496,268)|
+1,46,6,3,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(480,311)|
+1,47,7,3,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(477,291)|
+1,48,8,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(483,402)|
+1,49,9,6,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(589,397)|
+1,50,12,9,4,0,0,22,0,0,0,-1--1--1,,1|(575,463)|
+1,51,12,11,68,0,0,22,0,0,0,-1--1--1,,1|(484,463)|
+1,52,10,13,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(456,515)|
+1,53,9,12,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(576,434)|
+1,54,14,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(185,288)|
+1,55,15,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(259,308)|
+1,56,16,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(323,319)|
+1,57,17,4,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(325,296)|
+1,58,21,15,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(182,364)|
+1,59,19,15,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(185,398)|
+1,60,20,15,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(260,379)|
+1,61,21,14,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(128,353)|
+1,62,19,14,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(82,373)|
+1,63,23,14,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(109,266)|
+1,64,18,10,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(248,501)|
+1,65,22,10,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(253,520)|
+1,66,24,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(493,281)|
+1,67,25,13,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(595,518)|
+1,68,26,13,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(608,508)|
+1,69,1,27,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(396,188)|
+1,70,28,27,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(477,182)|
+1,71,29,27,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(505,143)|
+1,72,30,29,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(671,157)|
+1,73,31,29,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(638,108)|
+1,74,30,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(674,196)|
+1,75,32,28,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(627,233)|
+1,76,33,10,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(247,484)|
+1,77,34,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(456,109)|
+1,78,36,35,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(789,372)|
+1,79,38,37,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(154,74)|
+1,80,1,37,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(260,165)|
+1,81,39,37,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(227,95)|
+1,82,38,40,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(225,42)|
+1,83,1,40,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(335,128)|
+1,84,41,40,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(503,49)|
+1,85,28,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(432,225)|
+1,86,3,35,1,0,0,0,0,64,0,-1--1--1,,1|(578,246)|
+1,87,88,28,0,0,0,0,0,0,0,-1--1--1,,1|(600,192)|
+10,88,unit agricultural input,623,176,48,15,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,89,88,29,0,0,0,0,0,0,0,-1--1--1,,1|(601,156)|
+12,90,0,47,99,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,91,32509948,1123,179,204,152,3,188,0,0,2,0,0,0
+land yield,graph
+12,92,10422986,1124,488,204,150,3,188,0,0,1,0,0,0
+Land_Yield
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Land Development, Loss, Fertility
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,Arable Land,357,247,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,2,initial arable land,284,195,47,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,3,urban and industrial land development time,106,336,66,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,4,urban and industrial land required,255,338,60,16,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,5,average life of land,585,318,53,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,6,Land Fertility,576,483,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,7,inherent land fertility,569,556,58,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,8,land fertility regeneration time,364,553,48,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,9,initial land fertility,544,418,50,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,10,Potentially Arable Land,602,246,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,11,development cost per hectare,606,136,57,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,12,initial potentially arable land,709,203,77,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,13,Urban and Industrial Land,107,248,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,14,fraction of agricultural inputs allocated to land development,424,131,84,16,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,15,initial urban and industrial land,128,196,85,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+11,16,2028,361,315,8,6,33,3,0,0,4,0,0,0
+10,17,land erosion rate,416,315,47,9,32,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+12,18,48,360,357,10,8,0,3,0,0,-1,0,0,0
+10,19,total agricultural investment,322,164,84,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,20,1004,483,246,6,8,34,3,0,0,1,0,0,0
+10,21,land development rate,483,268,52,15,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,22,764,234,247,6,8,34,3,0,0,1,0,0,0
+10,23,land removal for urban and industrial use,234,268,64,13,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,24,development cost per hectare table,736,100,95,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,25,potentially arable land total,784,129,75,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,26,fraction of agricultural inputs allocated to land development table,239,96,66,18,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,27,marginal productivity of agricultural inputs,314,45,64,16,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,28,marginal productivity of land development,535,47,63,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-255-128
+10,29,land yield,702,30,35,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,30,social discount,708,57,43,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,31,average life of land normal,722,281,72,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,32,land life multiplier from land yield,704,350,52,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,33,land life multiplier from land yield 1,805,402,102,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,34,land life multiplier from land yield 2,862,373,102,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,35,land life policy implementation time,861,307,62,18,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,36,Time,844,336,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,37,48,397,482,10,8,0,3,0,0,-1,0,0,0
+10,38,land fertility degredation rate,773,564,47,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,39,48,752,485,10,8,0,3,0,0,-1,0,0,0
+10,40,land fertility regeneration time table,164,600,72,16,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,41,2188,469,483,6,8,34,3,0,0,1,0,0,0
+10,42,land fertility regeneration,469,507,35,16,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,43,2124,679,485,6,8,34,3,0,0,1,0,0,0
+10,44,land fertility degredation,679,509,34,16,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,45,fraction of agricultural inputs for land maintenance,171,560,91,15,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,46,land fertility degredation rate table,890,516,64,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,47,persistent pollution index,846,481,60,15,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,48,population,328,402,38,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,49,urban and industrial land required per capita,163,403,68,17,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,50,industrial output per capita,267,462,81,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,51,urban and industrial land required per capita table,82,460,75,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,52,2,1,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(306,211)|
+1,53,9,6,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(553,438)|
+1,54,12,10,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(671,218)|
+1,55,15,13,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(122,210)|
+1,56,20,1,4,0,0,22,0,0,0,-1--1--1,,1|(437,246)|
+1,57,20,10,100,0,0,22,0,0,0,-1--1--1,,1|(525,246)|
+1,58,22,13,4,0,0,22,0,0,0,-1--1--1,,1|(187,247)|
+1,59,22,1,100,0,0,22,0,0,0,-1--1--1,,1|(278,247)|
+1,60,16,18,4,0,0,22,0,0,0,-1--1--1,,1|(361,335)|
+1,61,16,1,100,0,0,22,0,0,0,-1--1--1,,1|(361,288)|
+1,62,3,23,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(191,305)|
+1,63,4,23,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(234,307)|
+1,64,13,22,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(166,219)|
+1,65,1,17,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(386,281)|
+1,66,5,17,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(504,316)|
+1,67,11,20,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(563,201)|
+1,68,14,20,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(427,186)|
+1,69,19,20,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(392,196)|
+1,70,24,11,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(688,113)|
+1,71,10,11,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(615,188)|
+1,72,25,11,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(692,131)|
+1,73,26,14,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(320,101)|
+1,74,27,14,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(362,83)|
+1,75,28,14,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(441,72)|
+1,76,11,28,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(601,90)|
+1,77,29,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(639,35)|
+1,78,30,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(638,53)|
+1,79,31,5,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(660,297)|
+1,80,32,5,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(604,330)|
+1,81,33,32,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(765,381)|
+1,82,34,32,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(785,361)|
+1,83,35,32,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(783,327)|
+1,84,36,32,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(795,340)|
+1,85,41,6,4,0,0,22,0,0,0,-1--1--1,,1|(505,483)|
+1,86,41,37,100,0,0,22,0,0,0,-1--1--1,,1|(435,483)|
+1,87,43,39,4,0,0,22,0,0,0,-1--1--1,,1|(713,485)|
+1,88,43,6,100,0,0,22,0,0,0,-1--1--1,,1|(644,485)|
+1,89,7,42,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(497,542)|
+1,90,8,42,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(427,545)|
+1,91,6,41,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(513,457)|
+1,92,38,44,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(711,551)|
+1,93,6,43,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(623,458)|
+1,94,40,8,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(267,575)|
+1,95,45,8,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(282,555)|
+1,96,46,38,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(822,546)|
+1,97,47,38,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(814,517)|
+1,98,48,4,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(283,373)|
+1,99,49,4,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(216,378)|
+1,100,50,49,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(210,443)|
+1,101,51,49,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(133,437)|
+10,102,one year,660,403,32,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,103,102,32,0,0,0,0,0,0,0,-1--1--1,,1|(675,384)|
+10,104,GDP pc unit,167,498,41,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,105,104,49,0,0,0,0,0,0,0,-1--1--1,,1|(165,461)|
+12,106,0,80,74,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,107,1311686,1200,166,236,150,3,188,0,0,1,0,0,0
+Land
+12,108,722766,1114,475,150,150,3,44,0,0,2,0,0,0
+Land Fertility,graph
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Industrial Output
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,Industrial Capital,412,261,40,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,2,fraction of industrial output allocated to investment,294,367,77,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,3,industrial output,359,133,47,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,4,initial industrial capital,508,197,62,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+12,5,48,204,262,10,8,0,3,0,0,-1,0,0,0
+10,6,average life of industrial capital,620,346,85,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+12,7,48,614,262,10,8,0,3,0,0,-1,0,0,0
+11,8,48,529,261,6,8,34,3,0,0,1,0,0,0
+10,9,industrial capital depreciation,529,282,55,14,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+11,10,2604,292,262,6,8,34,3,0,0,1,0,0,0
+10,11,industrial capital investment,292,283,55,14,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,12,average life of industrial capital 1,756,404,90,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,13,average life of industrial capital 2,679,428,90,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,14,POLICY YEAR,778,381,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,15,industrial capital output ratio multiplier from resource conservation technology,683,188,86,20,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,16,fraction of industrial output allocated to agriculture,469,410,83,13,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,17,fraction of industrial output allocated to consumption,244,457,77,19,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,18,fraction of industrial output allocated to services,423,447,84,13,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,19,capacity utilization fraction,272,63,81,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,20,fraction of industrial capital allocated to obtaining resources,433,64,63,19,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,21,industrial capital output ratio,555,124,79,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,22,industrial capital output ratio 1,616,76,84,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,23,industrial capital output ratio 2,796,129,84,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,24,Time,778,358,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,25,industrial capital output ratio multiplier from pollution technology,863,194,82,20,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,26,industrial capital output ratio multiplier from land yield technology,767,237,83,19,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,27,fraction of industrial output allocated to consumption constant,242,545,66,22,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,28,fraction of industrial output allocated to consumption variable,123,324,65,20,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,29,industrial equilibrium time,68,474,47,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,30,Time,105,521,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,31,fraction of industrial output allocated to consumption constant 1,487,541,105,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,32,fraction of industrial output allocated to consumption constant 2,485,571,105,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,33,industrial output per capita desired,55,391,40,20,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,34,industrial output per capita,176,187,51,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,35,fraction of industrial output allocated to consumption variable table,61,237,48,28,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,36,population,136,109,38,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,37,POLICY YEAR,438,514,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,38,POLICY YEAR,759,90,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,39,Time,699,144,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,40,4,1,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(474,219)|
+1,41,10,1,4,0,0,22,0,0,0,-1--1--1,,1|(335,262)|
+1,42,10,5,100,0,0,22,0,0,0,-1--1--1,,1|(250,262)|
+1,43,8,7,4,0,0,22,0,0,0,-1--1--1,,1|(569,261)|
+1,44,8,1,100,0,0,22,0,0,0,-1--1--1,,1|(487,261)|
+1,45,2,11,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(309,331)|
+1,46,3,10,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(283,184)|
+1,47,1,8,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(478,237)|
+1,48,6,9,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(559,319)|
+1,49,12,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(694,377)|
+1,50,13,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(653,392)|
+1,51,14,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(705,364)|
+1,52,24,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(737,355)|
+1,53,16,2,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(392,391)|
+1,54,17,2,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(278,420)|
+1,55,18,2,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(366,411)|
+1,56,19,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(309,93)|
+1,57,1,3,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(411,188)|
+1,58,20,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(395,98)|
+1,59,21,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(447,128)|
+1,60,22,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(591,95)|
+1,61,23,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(679,126)|
+1,62,15,23,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(743,156)|
+1,63,25,23,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(829,160)|
+1,64,26,23,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(780,184)|
+1,65,27,17,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(242,506)|
+1,66,28,17,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(144,395)|
+1,67,29,17,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(134,467)|
+1,68,30,17,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(156,496)|
+1,69,31,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(351,542)|
+1,70,32,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(350,556)|
+1,71,30,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(144,527)|
+1,72,33,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(83,362)|
+1,73,34,28,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(130,249)|
+1,74,35,28,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(89,278)|
+1,75,3,34,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(266,146)|
+1,76,36,34,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(151,139)|
+1,77,38,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(666,105)|
+1,78,39,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(654,137)|
+1,79,37,27,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(355,526)|
+12,80,0,52,81,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,81,0,485,756,150,150,3,44,0,0,2,0,0,0
+industrial output,graph
+12,82,0,171,756,150,150,3,44,0,0,2,0,0,0
+fraction of industrial output allocated to investment,graph
+12,83,0,801,756,150,150,3,44,0,0,2,0,0,0
+industrial output per capita,graph
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Services Output
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,Service Capital,372,393,43,20,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||0-0-0
+10,2,industrial output,154,469,54,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,3,fraction of industrial output allocated to services,149,296,81,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,4,initial service capital,312,345,56,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,5,48,182,393,10,8,0,3,0,0,-1,0,0,0
+10,6,fraction of industrial output allocated to services 1,292,225,78,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,7,48,569,395,10,8,0,3,0,0,-1,0,0,0
+11,8,48,483,393,6,8,34,3,0,0,1,0,0,0
+10,9,service capital depreciation,483,416,40,15,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+11,10,3500,252,394,6,8,34,3,0,0,1,0,0,0
+10,11,service capital investment,252,415,41,13,40,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,12,fraction of industrial output allocated to services 2,181,173,78,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,13,POLICY YEAR,86,222,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,14,service capital output ratio 1,781,344,78,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,15,fraction of industrial output allocated to services table 2,102,116,82,16,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,16,indicated services output per capita,301,67,56,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,17,service output per capita,466,167,68,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||130-130-130
+10,18,population,650,167,38,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,19,service output,503,287,41,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,20,capacity utilization fraction,623,244,81,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,21,service capital output ratio,654,304,73,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,22,average life of service capital,566,475,79,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,23,average life of service capital 1,772,455,84,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,24,average life of service capital 2,772,480,84,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,25,Time,65,248,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,26,service capital output ratio 2,702,364,78,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,27,Time,787,287,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,28,POLICY YEAR,777,269,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,29,POLICY YEAR,674,415,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,30,Time,688,434,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,31,industrial output per capita,670,74,81,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,32,fraction of industrial output allocated to services table 1,345,268,80,13,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,33,indicated services output per capita 1,477,37,54,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,34,indicated services output per capita 2,480,119,53,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,35,Time,155,68,22,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,36,indicated services output per capita table 1,711,38,116,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,37,indicated services output per capita table 2,705,119,116,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,38,POLICY YEAR,143,44,49,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,39,4,1,0,0,0,0,1,0,1,0-0-255,|10||128-128-128,1|(329,359)|
+1,40,10,1,4,0,0,22,0,0,0,-1--1--1,,1|(293,394)|
+1,41,10,5,100,0,0,22,0,0,0,-1--1--1,,1|(219,394)|
+1,42,8,7,4,0,0,22,0,0,0,-1--1--1,,1|(524,393)|
+1,43,8,1,100,0,0,22,0,0,0,-1--1--1,,1|(446,393)|
+1,44,2,11,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(192,447)|
+1,45,3,10,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(182,359)|
+1,46,6,3,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(170,250)|
+1,47,12,3,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(144,227)|
+1,48,13,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(110,251)|
+1,49,25,3,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(95,266)|
+1,50,15,12,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(137,141)|
+1,51,16,12,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(245,116)|
+1,52,17,12,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(346,139)|
+1,53,18,17,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(580,167)|
+1,54,19,17,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(504,266)|
+1,55,20,19,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(569,263)|
+1,56,21,19,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(589,288)|
+1,57,1,19,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(453,352)|
+1,58,22,9,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(520,454)|
+1,59,1,8,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(423,376)|
+1,60,23,22,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(673,464)|
+1,61,24,22,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(673,477)|
+1,62,14,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(724,326)|
+1,63,26,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(682,339)|
+1,64,27,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(751,290)|
+1,65,28,21,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(722,284)|
+1,66,29,22,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(626,441)|
+1,67,30,22,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(635,451)|
+1,68,16,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(296,139)|
+1,69,32,6,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(324,251)|
+1,70,17,6,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(337,189)|
+1,71,33,16,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(396,50)|
+1,72,34,16,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(397,95)|
+1,73,35,16,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(204,67)|
+1,74,31,33,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(584,57)|
+1,75,36,33,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(569,37)|
+1,76,31,34,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(589,92)|
+1,77,37,34,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(568,119)|
+1,78,38,16,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(211,53)|
+10,79,GDP pc unit,521,78,41,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,80,79,33,0,0,0,0,0,0,0,-1--1--1,,1|(507,64)|
+1,81,79,34,0,0,0,0,0,0,0,-1--1--1,,1|(508,90)|
+12,82,0,43,51,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,83,0,499,657,150,150,3,44,0,0,2,0,0,0
+service output,graph
+12,84,0,185,657,150,150,3,44,0,0,2,0,0,0
+fraction of industrial output allocated to services,graph
+12,85,0,815,657,150,150,3,44,0,0,2,0,0,0
+service output per capita,graph
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Jobs
+$192-192-192,0,Times New Roman|10||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,labor utilization fraction,346,283,65,9,0,3,0,0,-1,0,0,0
+10,2,jobs,390,219,14,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||0-0-0
+10,3,labor force,280,228,38,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,4,Delayed Labor Utilization Fraction,516,346,47,22,3,3,0,1,0,2,0,0,128-128-128,0-0-0,|10||128-128-128
+10,5,labor utilization fraction delay time,332,398,94,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+12,6,48,318,345,10,8,0,3,0,0,-1,0,0,0
+11,7,48,397,345,6,8,2,3,0,0,0,0,0,0
+10,8,potential jobs agricultural sector,326,150,54,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,9,potential jobs industrial sector,464,151,46,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,10,potential jobs service sector,521,196,41,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,11,Arable Land,314,71,40,20,3,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,12,jobs per hectare,178,148,45,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,13,Industrial Capital,577,77,40,20,3,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,14,jobs per industrial capital unit,629,144,50,16,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,15,jobs per service capital unit,620,254,47,14,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,16,Service Capital,696,201,40,20,3,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,17,industrial output per capita,768,103,81,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,18,jobs per industrial capital unit table,781,146,52,15,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,19,jobs per service capital unit table,783,290,46,16,8,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,20,service output per capita,795,253,75,9,0,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,21,agricultural input per hectare,145,68,57,15,8,2,0,3,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,22,jobs per hectare table,167,196,59,9,0,3,0,1,0,0,0,0,128-128-128,0-0-0,|10||128-128-128
+10,23,capacity utilization fraction,746,347,74,9,0,3,0,0,-1,0,0,0
+10,24,capacity utilization fraction table,654,397,89,9,0,3,0,1,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,25,2,1,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(360,244)|
+1,26,3,1,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(307,251)|
+1,27,8,2,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(382,185)|
+1,28,9,2,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(421,177)|
+1,29,10,2,1,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(445,198)|
+1,30,11,8,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(319,106)|
+1,31,12,8,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(240,148)|
+1,32,13,9,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(521,113)|
+1,33,14,9,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(551,147)|
+1,34,15,10,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(576,228)|
+1,35,16,10,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(615,198)|
+1,36,17,14,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(715,118)|
+1,37,18,14,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(710,145)|
+1,38,19,15,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(708,273)|
+1,39,20,15,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(700,253)|
+1,40,21,12,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(159,104)|
+1,41,22,12,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(170,178)|
+1,42,24,23,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(693,375)|
+1,43,4,23,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(610,346)|
+1,44,7,4,4,0,0,22,0,0,0,-1--1--1,,1|(436,345)|
+1,45,7,6,68,0,0,22,0,0,0,-1--1--1,,1|(359,345)|
+1,46,1,7,2,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(364,317)|
+1,47,5,7,0,0,0,0,1,0,0,0-0-255,|10||128-128-128,1|(362,372)|
+10,48,unit agricultural input,239,113,48,15,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,49,48,12,0,0,0,0,0,0,0,-1--1--1,,1|(209,130)|
+10,50,GDP pc unit,681,73,41,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,51,50,14,0,0,0,0,0,0,0,-1--1--1,,1|(661,99)|
+10,52,GDP pc unit,676,310,41,9,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|10||128-128-128
+1,53,52,15,0,0,0,0,0,0,0,-1--1--1,,1|(655,289)|
+12,54,0,71,134,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|10||0-0-0
+Home
+12,55,0,207,576,150,150,3,44,0,0,2,0,0,0
+jobs,Graph
+12,56,0,524,576,150,150,3,44,0,0,2,0,0,0
+labor utilization fraction,Graph
+12,57,0,839,576,150,150,3,44,0,0,2,0,0,0
+capacity utilization fraction,Graph
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Welfare & Footprint
+$192-192-192,0,Times New Roman|12||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+10,1,life expectancy,158,315,56,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+10,2,industrial output per capita,331,369,55,19,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+10,3,Arable Land,122,694,40,20,3,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+10,4,Urban and Industrial Land,236,691,40,20,3,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+10,5,persistent pollution generation rate,353,692,64,19,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+10,6,Human Ecological Footprint,240,447,58,19,8,3,0,0,-1,0,0,0
+10,7,"Absorption Land (GHA)",353,596,55,19,8,3,0,0,-1,0,0,0
+1,8,7,6,1,0,0,0,0,0,0,-1--1--1,,1|(316,523)|
+10,9,"Arable Land in Gigahectares (GHA)",122,589,66,19,8,3,0,0,-1,0,0,0
+1,10,9,6,1,0,0,0,0,0,0,-1--1--1,,1|(160,513)|
+10,11,"Urban Land (GHA)",237,594,39,19,8,3,0,0,-1,0,0,0
+1,12,11,6,0,0,0,0,0,0,0,-1--1--1,,1|(237,527)|
+1,13,3,9,0,0,0,0,0,0,0,-1--1--1,,1|(122,648)|
+1,14,4,11,0,0,0,0,0,0,0,-1--1--1,,1|(236,649)|
+10,15,ha per unit of pollution,486,595,48,19,8,3,0,0,-1,0,0,0
+1,16,15,7,0,0,0,0,0,0,0,-1--1--1,,1|(430,595)|
+1,17,5,7,0,0,0,0,0,0,0,-1--1--1,,1|(353,651)|
+10,18,ha per Gha,181,645,36,11,8,3,0,0,-1,0,0,0
+1,19,18,9,0,0,0,0,0,0,0,-1--1--1,,1|(161,625)|
+1,20,18,11,0,0,0,0,0,64,0,-1--1--1,,1|(199,628)|
+10,21,Total Land,369,447,35,11,8,3,0,0,-1,0,0,0
+1,22,21,6,0,0,0,0,0,0,0,-1--1--1,,1|(323,447)|
+10,23,Human Welfare Index,256,66,50,19,8,3,0,0,-1,0,0,0
+10,24,Education Index,269,157,51,11,8,3,0,0,-1,0,0,0
+1,25,24,23,1,0,0,0,0,0,0,-1--1--1,,1|(268,119)|
+10,26,GDP Index,407,163,37,11,8,3,0,0,-1,0,0,0
+1,27,26,23,1,0,0,0,0,0,0,-1--1--1,,1|(347,111)|
+10,28,Life Expectancy Index,142,158,52,19,8,3,0,0,-1,0,0,0
+1,29,28,23,1,0,0,0,0,0,0,-1--1--1,,1|(186,105)|
+1,30,1,28,0,0,0,0,0,0,0,-1--1--1,,1|(150,247)|
+10,31,Life Expectancy Index LOOKUP,92,267,55,19,8,3,0,0,-1,0,0,0
+1,32,31,28,0,0,0,0,0,0,0,-1--1--1,,1|(113,218)|
+10,33,Education Index LOOKUP,286,256,52,19,8,3,0,0,-1,0,0,0
+1,34,33,24,1,0,0,0,0,0,0,-1--1--1,,1|(284,206)|
+10,35,GDP per capita,397,262,50,11,8,3,0,0,-1,0,0,0
+1,36,35,24,1,0,0,0,0,0,0,-1--1--1,,1|(343,206)|
+10,37,GDP per capita LOOKUP,455,371,50,19,8,3,0,0,-1,0,0,0
+1,38,37,35,0,0,0,0,0,0,0,-1--1--1,,1|(426,318)|
+1,39,2,35,0,0,0,0,0,0,0,-1--1--1,,1|(362,317)|
+1,40,35,26,1,0,0,0,0,0,0,-1--1--1,,1|(415,216)|
+10,41,Ref Lo GDP,497,208,41,11,8,3,0,0,-1,0,0,0
+1,42,41,26,0,0,0,0,0,0,0,-1--1--1,,1|(458,188)|
+10,43,Ref Hi GDP,526,154,39,11,8,3,0,0,-1,0,0,0
+1,44,43,26,0,0,0,0,0,0,0,-1--1--1,,1|(472,157)|
+10,45,GDP pc unit,206,216,49,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+1,46,45,24,1,0,0,0,0,0,0,-1--1--1,,1|(228,184)|
+10,47,one year,47,208,37,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+1,48,47,28,0,0,0,0,0,0,0,-1--1--1,,1|(79,190)|
+10,49,GDP pc unit,499,320,49,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+1,50,49,35,0,0,0,0,0,0,0,-1--1--1,,1|(454,294)|
+10,51,ha per Gha,452,649,45,11,8,2,0,3,-1,0,0,0,128-128-128,0-0-0,|12||128-128-128
+1,52,51,7,0,0,0,0,0,64,0,-1--1--1,,1|(416,629)|
+12,53,0,64,81,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|12||0-0-0
+Home
+12,54,0,762,183,150,150,3,44,0,0,2,0,0,0
+Human Welfare Index,Graph
+12,55,0,762,523,150,150,3,44,0,0,2,0,0,0
+Human Ecological Footprint,Graph
+\\\---/// Sketch information - do not modify anything except names
+V300  Do not put anything below this section - it will be ignored
+*Output Graphs
+$192-192-192,0,Times New Roman|12||0-0-0|0-0-0|0-0-255|-1--1--1|-1--1--1|96,96,100,0
+12,1,0,361,228,345,213,3,188,0,0,1,0,0,0
+STATE_OF_WORLD
+12,2,0,1061,229,345,213,3,188,0,0,1,0,0,0
+MATERIAL_STANDARD_LIVING
+12,3,0,358,669,345,213,3,188,0,0,1,0,0,0
+HUMAN_WELFARE
+12,4,0,846,543,80,20,3,124,0,0,0,0,0,0
+initial nonrenewable resources,1e+009,4e+012,5e+010
+12,5,0,846,760,80,20,3,124,0,0,0,0,0,0
+land life policy implementation time,1900,2100,5
+10,6,persistent pollution technology change mult table,846,624,62,28,8,131,0,0,-1,0,0,0
+10,7,land yield technology change rate multiplier table,846,693,59,29,8,131,0,0,-1,0,0,0
+10,8,resource technology change mult table,846,839,64,19,8,3,0,0,-1,0,0,0
+12,9,0,1112,541,80,20,3,124,0,0,0,0,0,0
+technology development delay,1,40,1
+12,10,0,1112,603,80,20,3,124,0,0,0,0,0,0
+fertility control effectiveness time,1900,2100,5
+12,11,0,1112,671,80,20,3,124,0,0,0,0,0,0
+zero population growth time,1900,2100,5
+12,12,0,1112,748,80,20,3,124,0,0,0,0,0,0
+industrial output per capita desired,100,2000,10
+12,13,0,1112,828,80,20,3,124,0,0,0,0,0,0
+industrial equilibrium time,1900,2100,5
+12,14,0,847,475,88,11,0,4,0,0,-1,0,0,0
+Click on the SyntheSim Icon
+30,15,wrld3-03+0000.bmp,948,477,8,8,8,0,0,0,-1,0,0,0
+12,16,0,1120,476,115,11,0,4,0,0,-1,0,0,0
+and move sliders to see what changes
+12,17,0,1366,819,30,30,6,135,0,4,-1,0,1,0,-1--1--1,192-192-192,|12||0-0-0
+Home
+30,18,wrld3-03+0001.bmp,981,477,15,14,8,3,0,0,-1,0,0,0
+///---\\\
+:GRAPH STATE_OF_WORLD
+:TITLE State of the World
+:X-DIV 2
+:Y-DIV 1
+:SOFT-BOUNDS
+:SCALE
+:VAR population
+:Y-MIN 0
+:Y-MAX 1.2e+10
+:SCALE
+:VAR food
+:Y-MIN 0
+:Y-MAX 6e+12
+:SCALE
+:VAR industrial output
+:Y-MIN 0
+:Y-MAX 4e+12
+:SCALE
+:VAR persistent pollution index
+:Y-MIN 0
+:Y-MAX 40
+:SCALE
+:VAR nonrenewable resources
+:Y-MIN 0
+:Y-MAX 2e+12
+
+:GRAPH MATERIAL_STANDARD_LIVING
+:TITLE Material standard of living
+:X-DIV 2
+:Y-DIV 1
+:SOFT-BOUNDS
+:SCALE
+:VAR food per capita
+:Y-MIN 0
+:Y-MAX 1000
+:SCALE
+:VAR consumed industrial output per capita
+:Y-MIN 0
+:Y-MAX 250
+:SCALE
+:VAR service output per capita
+:Y-MIN 0
+:Y-MAX 1000
+:SCALE
+:VAR life expectancy
+:Y-MIN 0
+:Y-MAX 90
+
+:GRAPH WIP_STATE_OF_WORLD
+:TITLE State of the World
+:WIP
+:X-DIV 2
+:Y-DIV 1
+:X-MIN 1900
+:X-MAX 2100
+:SOFT-BOUNDS
+:MAX-POINTS 200
+:SCALE
+:VAR population
+:Y-MIN 0
+:Y-MAX 1.2e+10
+:DATASET *
+:SCALE
+:VAR food
+:Y-MIN 0
+:Y-MAX 6e+12
+:DATASET *
+:SCALE
+:VAR industrial output
+:Y-MIN 0
+:Y-MAX 4e+12
+:DATASET *
+:SCALE
+:VAR persistent pollution index
+:Y-MIN 0
+:Y-MAX 40
+:DATASET *
+:SCALE
+:VAR Nonrenewable Resources
+:Y-MIN 0
+:Y-MAX 2e+12
+:DATASET *
+
+:GRAPH HUMAN_WELFARE
+:TITLE Human Welfare and Ecological Footprint
+:X-DIV 2
+:Y-DIV 1
+:SCALE
+:VAR Human Welfare Index
+:Y-MIN 0
+:Y-MAX 1
+:SCALE
+:VAR Human Ecological Footprint
+:Y-MIN 0
+:Y-MAX 4
+
+:GRAPH Land
+:TITLE Land
+:SCALE
+:VAR Potentially Arable Land
+:LINE-WIDTH 1
+:VAR Potentially Arable Land
+:DATASET *2
+:LINE-WIDTH 1
+:VAR Arable Land
+:LINE-WIDTH 3
+:VAR Arable Land
+:DATASET *2
+:LINE-WIDTH 3
+:VAR Urban and Industrial Land
+:LINE-WIDTH 2
+:VAR Urban and Industrial Land
+:DATASET *2
+:LINE-WIDTH 2
+
+:GRAPH Population
+:TITLE Population
+:SCALE
+:VAR population
+:LINE-WIDTH 3
+:VAR population
+:DATASET *2
+:LINE-WIDTH 3
+:SCALE
+:VAR births
+:LINE-WIDTH 1
+:VAR births
+:DATASET *2
+:LINE-WIDTH 1
+:VAR deaths
+:LINE-STYLE DASH
+:VAR deaths
+:DATASET *2
+:LINE-STYLE DASH
+
+:GRAPH Population_Rates
+:TITLE Population Rates
+:SCALE
+:VAR birth rate
+:LINE-WIDTH 2
+:VAR birth rate
+:DATASET *2
+:LINE-WIDTH 2
+:VAR death rate
+:LINE-WIDTH 1
+:VAR death rate
+:DATASET *2
+:LINE-WIDTH 1
+
+:GRAPH Lifetime_Multipliers
+:TITLE Lifetime Multipliers
+:SCALE
+:VAR lifetime multiplier from crowding
+:VAR lifetime multiplier from food
+:VAR lifetime multiplier from health services
+:VAR lifetime multiplier from persistent pollution
+
+:GRAPH Fertility_Drivers
+:TITLE Fertility Drivers
+:SCALE
+:VAR total fertility
+:LINE-WIDTH 1
+:VAR maximum total fertility
+:LINE-STYLE DASH
+:VAR desired total fertility
+:LINE-STYLE DOT
+:SCALE
+:VAR fertility control effectiveness
+:LINE-WIDTH 2
+:SCALE
+:VAR desired completed family size
+:LINE-WIDTH 3
+
+:GRAPH Pollution_Flows
+:TITLE Pollution Flows
+:SCALE
+:VAR persistent pollution generation rate
+:VAR persistent pollution appearance rate
+:VAR persistent pollution assimilation rate
+
+:GRAPH Agriculture
+:TITLE Agriculture
+:SCALE
+:VAR food
+:SCALE
+:VAR Perceived Food Ratio
+:SCALE
+:VAR fraction of industrial output allocated to agriculture
+:SCALE
+:VAR Agricultural Inputs
+
+:GRAPH Land_Yield
+:TITLE Land Yield
+:SCALE
+:VAR land yield
+:SCALE
+:VAR land yield multiplier from air pollution
+:VAR land yield multiplier from capital
+:VAR land yield multiplier from technology
+:SCALE
+:VAR land life multiplier from land yield
+:L<%^E!@
+1:experiment.vdf
+9:experiment
+22:Ghectare,Ghectares
+22:hectare,hectares
+22:Pollution unit,Pollution units
+22:Resource unit,Resource units
+23:0
+15:0,0,0,0,0,0
+19:100,1
+27:0,
+34:0,
+4:Time
+5:population
+35:Date
+36:YYYY-MM-DD
+37:2000
+38:1
+39:1
+40:2
+41:0
+42:0
+24:1900
+25:2100
+26:2100