tutorials/plot_your_results.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2d4eb02f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Inside covid19_components.py: 1 GPUs are available.\n",
      "Inside covid19_env.py: 1 GPUs are available.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
     ]
    }
   ],
   "source": [
    "import argparse\n",
    "import logging\n",
    "import os\n",
    "import sys\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython import display\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from ai_economist.foundation import landmarks, resources\n",
    "\n",
    "import ray\n",
    "from rllib.utils import remote, saving\n",
    "from utils import plotting\n",
    "import rllib.tf_models\n",
    "import rllib.fcnet\n",
    "import yaml\n",
    "from rllib.env_wrapper import RLlibEnvWrapper\n",
    "from ray.rllib.agents.ppo import PPOTrainer\n",
    "from ray.tune.logger import NoopLogger, pretty_print"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4afe731b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_map(maps, locs, ax=None, cmap_order=None):\n",
    "    world_size = np.array(maps.get(\"Wood\")).shape\n",
    "    max_health = {\"Wood\": 1, \"Stone\": 1, \"House\": 1}\n",
    "    n_agents = len(locs)\n",
    "\n",
    "    if ax is None:\n",
    "        _, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
    "    else:\n",
    "        ax.cla()\n",
    "    tmp = np.zeros((3, world_size[0], world_size[1]))\n",
    "    cmap = plt.get_cmap(\"jet\", n_agents)\n",
    "\n",
    "    if cmap_order is None:\n",
    "        cmap_order = list(range(n_agents))\n",
    "    else:\n",
    "        cmap_order = list(cmap_order)\n",
    "        assert len(cmap_order) == n_agents\n",
    "\n",
    "    scenario_entities = [k for k in maps.keys() if \"source\" not in k.lower()]\n",
    "    for entity in scenario_entities:\n",
    "        if entity == \"House\":\n",
    "            continue\n",
    "        elif resources.has(entity):\n",
    "            if resources.get(entity).collectible:\n",
    "                map_ = (\n",
    "                    resources.get(entity).color[:, None, None]\n",
    "                    * np.array(maps.get(entity))[None]\n",
    "                )\n",
    "                map_ /= max_health[entity]\n",
    "                tmp += map_\n",
    "        elif landmarks.has(entity):\n",
    "            map_ = (\n",
    "                landmarks.get(entity).color[:, None, None]\n",
    "                * np.array(maps.get(entity))[None]\n",
    "            )\n",
    "            tmp += map_\n",
    "        else:\n",
    "            continue\n",
    "\n",
    "    if isinstance(maps, dict):\n",
    "        house_idx = np.array(maps.get(\"House\")[\"owner\"])\n",
    "        house_health = np.array(maps.get(\"House\")[\"health\"])\n",
    "    else:\n",
    "        house_idx = maps.get(\"House\", owner=True)\n",
    "        house_health = maps.get(\"House\")\n",
    "    for i in range(n_agents):\n",
    "        houses = house_health * (house_idx == cmap_order[i])\n",
    "        agent = np.zeros_like(houses)\n",
    "        agent += houses\n",
    "        col = np.array(cmap(i)[:3])\n",
    "        map_ = col[:, None, None] * agent[None]\n",
    "        tmp += map_\n",
    "\n",
    "    tmp *= 0.7\n",
    "    tmp += 0.3\n",
    "\n",
    "    tmp = np.transpose(tmp, [1, 2, 0])\n",
    "    tmp = np.minimum(tmp, 1.0)\n",
    "\n",
    "    ax.imshow(tmp, vmax=1.0, aspect=\"auto\")\n",
    "\n",
    "    bbox = ax.get_window_extent()\n",
    "\n",
    "    for i in range(n_agents):\n",
    "        r, c = locs[cmap_order[i]]\n",
    "        col = np.array(cmap(i)[:3])\n",
    "        ax.plot(c, r, \"o\", markersize=bbox.height * 20 / 550, color=\"w\")\n",
    "        ax.plot(c, r, \"*\", markersize=bbox.height * 15 / 550, color=col)\n",
    "\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "\n",
    "\n",
    "def plot_env_state(env, ax=None, remap_key=None):\n",
    "    maps = env.world.maps\n",
    "    locs = [agent.loc for agent in env.world.agents]\n",
    "\n",
    "    if remap_key is None:\n",
    "        cmap_order = None\n",
    "    else:\n",
    "        assert isinstance(remap_key, str)\n",
    "        cmap_order = np.argsort(\n",
    "            [agent.state[remap_key] for agent in env.world.agents]\n",
    "        ).tolist()\n",
    "\n",
    "    plot_map(maps, locs, ax, cmap_order)\n",
    "\n",
    "\n",
    "def plot_log_state(dense_log, t, ax=None, remap_key=None):\n",
    "    maps = dense_log[\"world\"][t]\n",
    "    states = dense_log[\"states\"][t]\n",
    "\n",
    "    n_agents = len(states) - 1\n",
    "    locs = []\n",
    "    for i in range(n_agents):\n",
    "        r, c = states[str(i)][\"loc\"]\n",
    "        locs.append([r, c])\n",
    "\n",
    "    if remap_key is None:\n",
    "        cmap_order = None\n",
    "    else:\n",
    "        assert isinstance(remap_key, str)\n",
    "        key_val = np.array(\n",
    "            [dense_log[\"states\"][0][str(i)][remap_key] for i in range(n_agents)]\n",
    "        )\n",
    "        cmap_order = np.argsort(key_val).tolist()\n",
    "\n",
    "    plot_map(maps, locs, ax, cmap_order)\n",
    "\n",
    "\n",
    "def _format_logs_and_eps(dense_logs, eps):\n",
    "    if isinstance(dense_logs, dict):\n",
    "        return [dense_logs], [0]\n",
    "    else:\n",
    "        assert isinstance(dense_logs, (list, tuple))\n",
    "\n",
    "    if isinstance(eps, (list, tuple)):\n",
    "        return dense_logs, list(eps)\n",
    "    elif isinstance(eps, (int, float)):\n",
    "        return dense_logs, [int(eps)]\n",
    "    elif eps is None:\n",
    "        return dense_logs, list(range(np.minimum(len(dense_logs), 16)))\n",
    "    else:\n",
    "        raise NotImplementedError\n",
    "\n",
    "\n",
    "def vis_world_array(dense_logs, ts, eps=None, axes=None, remap_key=None):\n",
    "    dense_logs, eps = _format_logs_and_eps(dense_logs, eps)\n",
    "    if isinstance(ts, (int, float)):\n",
    "        ts = [ts]\n",
    "\n",
    "    if axes is None:\n",
    "        fig, axes = plt.subplots(\n",
    "            len(eps),\n",
    "            len(ts),\n",
    "            figsize=(np.minimum(3.2 * len(ts), 16), 3 * len(eps)),\n",
    "            squeeze=False,\n",
    "        )\n",
    "\n",
    "    else:\n",
    "        fig = None\n",
    "\n",
    "        if len(ts) == 1 and len(eps) == 1:\n",
    "            axes = np.array([[axes]]).reshape(1, 1)\n",
    "        else:\n",
    "            try:\n",
    "                axes = np.array(axes).reshape(len(eps), len(ts))\n",
    "            except ValueError:\n",
    "                print(\"Could not reshape provided axes array into the necessary shape!\")\n",
    "                raise\n",
    "\n",
    "    for ti, t in enumerate(ts):\n",
    "        for ei, ep in enumerate(eps):\n",
    "            plot_log_state(dense_logs[ep], t, ax=axes[ei, ti], remap_key=remap_key)\n",
    "\n",
    "    for ax, t in zip(axes[0], ts):\n",
    "        ax.set_title(\"T = {}\".format(t))\n",
    "    for ax, ep in zip(axes[:, 0], eps):\n",
    "        ax.set_ylabel(\"Episode {}\".format(ep))\n",
    "\n",
    "    return fig\n",
    "\n",
    "\n",
    "def vis_world_range(\n",
    "    dense_logs, t0=0, tN=None, N=5, eps=None, axes=None, remap_key=None\n",
    "):\n",
    "    dense_logs, eps = _format_logs_and_eps(dense_logs, eps)\n",
    "\n",
    "    viable_ts = np.array([i for i, w in enumerate(dense_logs[0][\"world\"]) if w])\n",
    "    if tN is None:\n",
    "        tN = viable_ts[-1]\n",
    "    assert 0 <= t0 < tN\n",
    "    target_ts = np.linspace(t0, tN, N).astype(np.int)\n",
    "\n",
    "    ts = set()\n",
    "    for tt in target_ts:\n",
    "        closest = np.argmin(np.abs(tt - viable_ts))\n",
    "        ts.add(viable_ts[closest])\n",
    "    ts = sorted(list(ts))\n",
    "    if axes is not None:\n",
    "        axes = axes[: len(ts)]\n",
    "    return vis_world_array(dense_logs, ts, axes=axes, eps=eps, remap_key=remap_key)\n",
    "\n",
    "\n",
    "def vis_builds(dense_logs, eps=None, ax=None):\n",
    "    dense_logs, eps = _format_logs_and_eps(dense_logs, eps)\n",
    "\n",
    "    if ax is None:\n",
    "        _, ax = plt.subplots(1, 1, figsize=(16, 3))\n",
    "    cmap = plt.get_cmap(\"jet\", len(eps))\n",
    "    for i, ep in enumerate(eps):\n",
    "        ax.plot(\n",
    "            np.cumsum([len(b[\"builds\"]) for b in dense_logs[ep][\"Build\"]]),\n",
    "            color=cmap(i),\n",
    "            label=\"Ep {}\".format(ep),\n",
    "        )\n",
    "    ax.legend()\n",
    "    ax.grid(b=True)\n",
    "    ax.set_ylim(bottom=0)\n",
    "\n",
    "\n",
    "def trade_str(c_trades, resource, agent, income=True):\n",
    "    if income:\n",
    "        p = [x[\"income\"] for x in c_trades[resource] if x[\"seller\"] == agent]\n",
    "    else:\n",
    "        p = [x[\"cost\"] for x in c_trades[resource] if x[\"buyer\"] == agent]\n",
    "    if len(p) > 0:\n",
    "        return \"{:6.2f} (n={:3d})\".format(np.mean(p), len(p))\n",
    "    else:\n",
    "        tmp = \"~\" * 8\n",
    "        tmp = (\" \") * 3 + tmp + (\" \") * 3\n",
    "        return tmp\n",
    "\n",
    "\n",
    "def full_trade_str(c_trades, resource, a_indices, income=True):\n",
    "    s_head = \"{} ({})\".format(\"Income\" if income else \"Cost\", resource)\n",
    "    ac_strings = [trade_str(c_trades, resource, buyer, income) for buyer in a_indices]\n",
    "    s_tail = \" | \".join(ac_strings)\n",
    "    return \"{:<15}: {}\".format(s_head, s_tail)\n",
    "\n",
    "\n",
    "def build_str(all_builds, agent):\n",
    "    p = [x[\"income\"] for x in all_builds if x[\"builder\"] == agent]\n",
    "    if len(p) > 0:\n",
    "        return \"{:6.2f} (n={:3d})\".format(np.mean(p), len(p))\n",
    "    else:\n",
    "        tmp = \"~\" * 8\n",
    "        tmp = (\" \") * 3 + tmp + (\" \") * 3\n",
    "        return tmp\n",
    "\n",
    "\n",
    "def full_build_str(all_builds, a_indices):\n",
    "    s_head = \"Income (Build)\"\n",
    "    ac_strings = [build_str(all_builds, builder) for builder in a_indices]\n",
    "    s_tail = \" | \".join(ac_strings)\n",
    "    return \"{:<15}: {}\".format(s_head, s_tail)\n",
    "\n",
    "\n",
    "def header_str(n_agents):\n",
    "    s_head = (\"_\" * 15) + \":_\"\n",
    "    s_tail = \"_|_\".join([\" Agent {:2d} ____\".format(i) for i in range(n_agents)])\n",
    "    return s_head + s_tail\n",
    "\n",
    "\n",
    "def report(c_trades, all_builds, n_agents, a_indices=None):\n",
    "    if a_indices is None:\n",
    "        a_indices = list(range(n_agents))\n",
    "    print(header_str(n_agents))\n",
    "    resources = [\"Wood\", \"Stone\"]\n",
    "    if c_trades is not None:\n",
    "        for resource in resources:\n",
    "            print(full_trade_str(c_trades, resource, a_indices, income=False))\n",
    "        print(\"\")\n",
    "        for resource in resources:\n",
    "            print(full_trade_str(c_trades, resource, a_indices, income=True))\n",
    "    print(full_build_str(all_builds, a_indices))\n",
    "\n",
    "\n",
    "def breakdown(log, remap_key=None):\n",
    "    fig0 = vis_world_range(log, remap_key=remap_key)\n",
    "\n",
    "    n = len(list(log[\"states\"][0].keys())) - 1\n",
    "    trading_active = \"Trade\" in log\n",
    "\n",
    "    if remap_key is None:\n",
    "        aidx = list(range(n))\n",
    "    else:\n",
    "        assert isinstance(remap_key, str)\n",
    "        key_vals = np.array([log[\"states\"][0][str(i)][remap_key] for i in range(n)])\n",
    "        aidx = np.argsort(key_vals).tolist()\n",
    "\n",
    "    all_builds = []\n",
    "    for t, builds in enumerate(log[\"Build\"]):\n",
    "        if isinstance(builds, dict):\n",
    "            builds_ = builds[\"builds\"]\n",
    "        else:\n",
    "            builds_ = builds\n",
    "        for build in builds_:\n",
    "            this_build = {\"t\": t}\n",
    "            this_build.update(build)\n",
    "            all_builds.append(this_build)\n",
    "\n",
    "    if trading_active:\n",
    "        c_trades = {\"Stone\": [], \"Wood\": []}\n",
    "        for t, trades in enumerate(log[\"Trade\"]):\n",
    "            if isinstance(trades, dict):\n",
    "                trades_ = trades[\"trades\"]\n",
    "            else:\n",
    "                trades_ = trades\n",
    "            for trade in trades_:\n",
    "                this_trade = {\n",
    "                    \"t\": t,\n",
    "                    \"t_ask\": t - trade[\"ask_lifetime\"],\n",
    "                    \"t_bid\": t - trade[\"bid_lifetime\"],\n",
    "                }\n",
    "                this_trade.update(trade)\n",
    "                c_trades[trade[\"commodity\"]].append(this_trade)\n",
    "\n",
    "        incomes = {\n",
    "            \"Sell Stone\": [\n",
    "                sum([t[\"income\"] for t in c_trades[\"Stone\"] if t[\"seller\"] == aidx[i]])\n",
    "                for i in range(n)\n",
    "            ],\n",
    "            \"Buy Stone\": [\n",
    "                sum([-t[\"price\"] for t in c_trades[\"Stone\"] if t[\"buyer\"] == aidx[i]])\n",
    "                for i in range(n)\n",
    "            ],\n",
    "            \"Sell Wood\": [\n",
    "                sum([t[\"income\"] for t in c_trades[\"Wood\"] if t[\"seller\"] == aidx[i]])\n",
    "                for i in range(n)\n",
    "            ],\n",
    "            \"Buy Wood\": [\n",
    "                sum([-t[\"price\"] for t in c_trades[\"Wood\"] if t[\"buyer\"] == aidx[i]])\n",
    "                for i in range(n)\n",
    "            ],\n",
    "            \"Build\": [\n",
    "                sum([b[\"income\"] for b in all_builds if b[\"builder\"] == aidx[i]])\n",
    "                for i in range(n)\n",
    "            ],\n",
    "        }\n",
    "\n",
    "    else:\n",
    "        c_trades = None\n",
    "        incomes = {\n",
    "            \"Build\": [\n",
    "                sum([b[\"income\"] for b in all_builds if b[\"builder\"] == aidx[i]])\n",
    "                for i in range(n)\n",
    "            ],\n",
    "        }\n",
    "\n",
    "    incomes[\"Total\"] = np.stack([v for v in incomes.values()]).sum(axis=0)\n",
    "\n",
    "    endows = [\n",
    "        int(\n",
    "            log[\"states\"][-1][str(aidx[i])][\"inventory\"][\"Coin\"]\n",
    "            + log[\"states\"][-1][str(aidx[i])][\"escrow\"][\"Coin\"]\n",
    "        )\n",
    "        for i in range(n)\n",
    "    ]\n",
    "\n",
    "    n_small = np.minimum(4, n)\n",
    "\n",
    "    report(c_trades, all_builds, n, aidx)\n",
    "\n",
    "    cmap = plt.get_cmap(\"jet\", n)\n",
    "    rs = [\"Wood\", \"Stone\", \"Coin\"]\n",
    "\n",
    "    fig1, axes = plt.subplots(1, len(rs) + 1, figsize=(16, 4), sharey=False)\n",
    "    for r, ax in zip(rs, axes):\n",
    "        for i in range(n):\n",
    "            ax.plot(\n",
    "                [\n",
    "                    x[str(aidx[i])][\"inventory\"][r] + x[str(aidx[i])][\"escrow\"][r]\n",
    "                    for x in log[\"states\"]\n",
    "                ],\n",
    "                label=i,\n",
    "                color=cmap(i),\n",
    "            )\n",
    "        ax.set_title(r)\n",
    "        ax.legend()\n",
    "        ax.grid(b=True)\n",
    "\n",
    "    ax = axes[-1]\n",
    "    for i in range(n):\n",
    "        ax.plot(\n",
    "            [x[str(aidx[i])][\"endogenous\"][\"Labor\"] for x in log[\"states\"]],\n",
    "            label=i,\n",
    "            color=cmap(i),\n",
    "        )\n",
    "    ax.set_title(\"Labor\")\n",
    "    ax.legend()\n",
    "    ax.grid(b=True)\n",
    "    \n",
    "    fig3, axes = plt.subplots(1, 4, figsize=(16, 4), sharey=False)\n",
    "\n",
    "    houses = [0] * n\n",
    "    hs = [[] for _ in houses]\n",
    "\n",
    "    for bs in dense_logs['Build']:\n",
    "        for b in bs:\n",
    "            houses[b['builder']] += 1\n",
    "\n",
    "        for h, house in zip(hs, houses):\n",
    "            h.append(house)\n",
    "         \n",
    "    ax = axes[0]\n",
    "    for i in range(n):\n",
    "        ax.plot(\n",
    "            hs[i],\n",
    "            label=i,\n",
    "            color=cmap(i),\n",
    "        )\n",
    "        \n",
    "    ax.set_title(\"House\")\n",
    "    ax.legend()\n",
    "    ax.grid(b=True)\n",
    "\n",
    "    productivity = list(map(lambda x: x['social/productivity'], log[\"scenario_metrics\"]))\n",
    "    equality = list(map(lambda x: x['social/equality'], log[\"scenario_metrics\"]))\n",
    "    welfare = list(map(lambda x: x['social_welfare/coin_eq_times_productivity'], log[\"scenario_metrics\"]))\n",
    "\n",
    "    ts = {'Productivity': productivity, 'Equality': equality, 'Social welfare': welfare}\n",
    "\n",
    "    for i, ((k, v), ax) in enumerate(zip(ts.items(), axes[1:])):\n",
    "        ax.plot(v, color=cmap(i))\n",
    "        ax.set_title(k)\n",
    "        ax.grid(True)\n",
    "\n",
    "    tmp = np.array(log[\"world\"][0][\"Stone\"])\n",
    "    fig2, axes = plt.subplots(\n",
    "        2 if trading_active else 1,\n",
    "        n_small,\n",
    "        figsize=(16, 8 if trading_active else 4),\n",
    "        sharex=\"row\",\n",
    "        sharey=\"row\",\n",
    "        squeeze=False,\n",
    "    )\n",
    "    for i, ax in enumerate(axes[0]):\n",
    "        rows = np.array([x[str(aidx[i])][\"loc\"][0] for x in log[\"states\"]]) * -1\n",
    "        cols = np.array([x[str(aidx[i])][\"loc\"][1] for x in log[\"states\"]])\n",
    "        ax.plot(cols[::20], rows[::20])\n",
    "        ax.plot(cols[0], rows[0], \"r*\", markersize=15)\n",
    "        ax.plot(cols[-1], rows[-1], \"g*\", markersize=15)\n",
    "        ax.set_title(\"Agent {}\".format(i))\n",
    "        ax.set_xlim([-1, 1 + tmp.shape[1]])\n",
    "        ax.set_ylim([-(1 + tmp.shape[0]), 1])\n",
    "        \n",
    "    global some, what\n",
    "\n",
    "    if trading_active:\n",
    "        for i, ax in enumerate(axes[1]):\n",
    "            for r in [\"Wood\", \"Stone\"]:\n",
    "                tmp = [\n",
    "                    (s[\"t\"], s[\"income\"]) for s in c_trades[r] if s[\"seller\"] == aidx[i]\n",
    "                ]\n",
    "                if tmp:\n",
    "                    ts, prices = [np.array(x) for x in zip(*tmp)]\n",
    "                    ax.plot(\n",
    "                        np.stack([ts, ts]),\n",
    "                        np.stack([np.zeros_like(prices), prices]),\n",
    "                        color=resources.get(r).color,\n",
    "                    )\n",
    "                    ax.plot(\n",
    "                        ts, prices, \".\", color=resources.get(r).color, markersize=12\n",
    "                    )\n",
    "\n",
    "                tmp = [\n",
    "                    (s[\"t\"], -s[\"cost\"]) for s in c_trades[r] if s[\"buyer\"] == aidx[i]\n",
    "                ]\n",
    "                \n",
    "                if tmp:\n",
    "                    ts, prices = [np.array(x) for x in zip(*tmp)]\n",
    "                    some, what = ts, prices\n",
    "                    ax.plot(\n",
    "                        np.stack([ts, ts]),\n",
    "                        np.stack([np.zeros_like(prices), prices]),\n",
    "                        color=resources.get(r).color,\n",
    "                    )\n",
    "                    ax.plot(\n",
    "                        ts, prices, \".\", color=resources.get(r).color, markersize=12\n",
    "                    )\n",
    "            ax.plot([-20, len(log[\"states\"]) + 19], [0, 0], \"w-\")\n",
    "            # ax.set_ylim([-10.2, 10.2]);\n",
    "            ax.set_xlim([-20, len(log[\"states\"]) + 19])\n",
    "            ax.grid(b=True)\n",
    "            ax.set_facecolor([0.3, 0.3, 0.3])\n",
    "            \n",
    "    return (fig0, fig1, fig2, fig3), incomes, endows, c_trades, all_builds\n",
    "\n",
    "\n",
    "def plot_for_each_n(y_fun, n, ax=None):\n",
    "    if ax is None:\n",
    "        _, ax = plt.subplots(1, 1, figsize=(5, 5))\n",
    "    cmap = plt.get_cmap(\"jet\", n)\n",
    "    for i in range(n):\n",
    "        ax.plot(y_fun(i), color=cmap(i), label=i)\n",
    "    ax.legend()\n",
    "    ax.grid(b=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e49dc36f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_config(config_dir):\n",
    "    config_path = os.path.join(config_dir, \"custom.yaml\")\n",
    "    with open(config_path, \"r\") as f:\n",
    "        run_configuration = yaml.safe_load(f)\n",
    "\n",
    "    return config_dir, run_configuration\n",
    "\n",
    "def build_trainer(run_configuration):\n",
    "    \"\"\"Finalize the trainer config by combining the sub-configs.\"\"\"\n",
    "    trainer_config = run_configuration.get(\"trainer\")\n",
    "\n",
    "    # === Env ===\n",
    "    env_config = {\n",
    "        \"env_config_dict\": run_configuration.get(\"env\"),\n",
    "        \"num_envs_per_worker\": trainer_config.get(\"num_envs_per_worker\"),\n",
    "    }\n",
    "\n",
    "    # === Seed ===\n",
    "    if trainer_config[\"seed\"] is None:\n",
    "        try:\n",
    "            start_seed = int(run_configuration[\"metadata\"][\"launch_time\"])\n",
    "        except KeyError:\n",
    "            start_seed = int(time.time())\n",
    "    else:\n",
    "        start_seed = int(trainer_config[\"seed\"])\n",
    "\n",
    "    final_seed = int(start_seed % (2 ** 16)) * 1000\n",
    "    logger.info(\"seed (final): %s\", final_seed)\n",
    "\n",
    "    # === Multiagent Policies ===\n",
    "    dummy_env = RLlibEnvWrapper(env_config)\n",
    "\n",
    "    # Policy tuples for agent/planner policy types\n",
    "    agent_policy_tuple = (\n",
    "        None,\n",
    "        dummy_env.observation_space,\n",
    "        dummy_env.action_space,\n",
    "        run_configuration.get(\"agent_policy\"),\n",
    "    )\n",
    "    planner_policy_tuple = (\n",
    "        None,\n",
    "        dummy_env.observation_space_pl,\n",
    "        dummy_env.action_space_pl,\n",
    "        run_configuration.get(\"planner_policy\"),\n",
    "    )\n",
    "\n",
    "    policies = {\"a\": agent_policy_tuple, \"p\": planner_policy_tuple}\n",
    "\n",
    "    def policy_mapping_fun(i):\n",
    "        if str(i).isdigit() or i == \"a\":\n",
    "            return \"a\"\n",
    "        return \"p\"\n",
    "\n",
    "    # Which policies to train\n",
    "    if run_configuration[\"general\"][\"train_planner\"]:\n",
    "        policies_to_train = [\"a\", \"p\"]\n",
    "    else:\n",
    "        policies_to_train = [\"a\"]\n",
    "\n",
    "    # === Finalize and create ===\n",
    "    trainer_config.update(\n",
    "        {\n",
    "            \"env_config\": env_config,\n",
    "            \"seed\": final_seed,\n",
    "            \"multiagent\": {\n",
    "                \"policies\": policies,\n",
    "                \"policies_to_train\": policies_to_train,\n",
    "                \"policy_mapping_fn\": policy_mapping_fun,\n",
    "            },\n",
    "            \"metrics_smoothing_episodes\": trainer_config.get(\"num_workers\")\n",
    "            * trainer_config.get(\"num_envs_per_worker\"),\n",
    "        }\n",
    "    )\n",
    "\n",
    "    def logger_creator(config):\n",
    "        return NoopLogger({}, \"/tmp\")\n",
    "\n",
    "    ppo_trainer = PPOTrainer(\n",
    "        env=RLlibEnvWrapper, config=trainer_config, logger_creator=logger_creator\n",
    "    )\n",
    "\n",
    "    return ppo_trainer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "90114b1a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-05-24 11:24:08,994\tINFO resource_spec.py:212 -- Starting Ray with 7.37 GiB memory available for workers and up to 3.7 GiB for objects. You can adjust these settings with ray.init(memory=<bytes>, object_store_memory=<bytes>).\n",
      "2023-05-24 11:24:09,299\tINFO services.py:1148 -- View the Ray dashboard at \u001b[1m\u001b[32mlocalhost:8265\u001b[39m\u001b[22m\n",
      "2023-05-24 11:24:09,866 seed (final): 42625000\n",
      "2023-05-24 11:24:09,892\tINFO trainer.py:428 -- Tip: set 'eager': true or the --eager flag to enable TensorFlow eager execution\n",
      "2023-05-24 11:24:09,893\tINFO trainer.py:585 -- Current log_level is WARN. For more information, set 'log_level': 'INFO' / 'DEBUG' or use the -v and -vv flags.\n",
      "2023-05-24 11:24:28,162\tINFO trainable.py:180 -- _setup took 18.269 seconds. If your trainable is slow to initialize, consider setting reuse_actors=True to reduce actor creation overheads.\n",
      "2023-05-24 11:24:28,163\tINFO trainable.py:217 -- Getting current IP.\n"
     ]
    }
   ],
   "source": [
    "ray.init(log_to_driver=False)\n",
    "\n",
    "logging.basicConfig(stream=sys.stdout, format=\"%(asctime)s %(message)s\")\n",
    "logger = logging.getLogger(\"main\")\n",
    "logger.setLevel(logging.DEBUG)\n",
    "\n",
    "run_dir, run_config = load_config('/home/akash/GitHub/ai-economist/tutorials')\n",
    "\n",
    "# Create a trainer object\n",
    "trainer = build_trainer(run_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "63ecacbe",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-05-24 11:24:28,205 Not restoring trainer...\n",
      "2023-05-24 11:24:28,207 Restoring agents TF weights...\n",
      "2023-05-24 11:24:28,539 loaded tf model weights:\n",
      "\t./rllib/phase1/ckpts/agent.tf.weights.global-step-25040000\n",
      "\n",
      "2023-05-24 11:24:28,540 Restoring planner TF weights...\n",
      "2023-05-24 11:24:28,773 loaded tf model weights:\n",
      "\t./rllib/phase1/ckpts/planner.tf.weights.global-step-25040000\n",
      "\n"
     ]
    }
   ],
   "source": [
    "logger.info(\"Not restoring trainer...\")\n",
    "# === Trainer-specific counters ===\n",
    "training_step_last_ckpt = 0\n",
    "epis_last_ckpt = 0\n",
    "\n",
    "# For new runs, load only tf checkpoint weights\n",
    "starting_weights_path_agents = run_config[\"general\"].get(\n",
    "    \"restore_tf_weights_agents\", \"\"\n",
    ")\n",
    "if starting_weights_path_agents:\n",
    "    logger.info(\"Restoring agents TF weights...\")\n",
    "    saving.load_tf_model_weights(trainer, starting_weights_path_agents)\n",
    "else:\n",
    "    logger.info(\"Starting with fresh agent TF weights.\")\n",
    "\n",
    "starting_weights_path_planner = run_config[\"general\"].get(\n",
    "    \"restore_tf_weights_planner\", \"\"\n",
    ")\n",
    "if starting_weights_path_planner:\n",
    "    logger.info(\"Restoring planner TF weights...\")\n",
    "    saving.load_tf_model_weights(trainer, starting_weights_path_planner)\n",
    "else:\n",
    "    logger.info(\"Starting with fresh planner TF weights.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cfebf7a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "env_obj = trainer.workers.local_worker().env"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d04b736d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def do_plot(env, ax, fig):\n",
    "    \"\"\"Plots world state during episode sampling.\"\"\"\n",
    "    plotting.plot_env_state(env, ax)\n",
    "    ax.set_aspect('equal')\n",
    "    display.display(fig)\n",
    "    display.clear_output(wait=True)\n",
    "\n",
    "def play_episode(plot_every=100, do_dense_logging=False):\n",
    "    global actions\n",
    "    fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
    "    \n",
    "    # Set initial states\n",
    "    scenario_metrics = []\n",
    "    agent_states = {}\n",
    "    for agent_idx in range(env_obj.env.n_agents):\n",
    "        agent_states[str(agent_idx)] = trainer.get_policy(\"a\").get_initial_state()\n",
    "    planner_states = trainer.get_policy(\"p\").get_initial_state()   \n",
    "\n",
    "    # Play out the episode\n",
    "    obs = env_obj.reset(force_dense_logging=True)\n",
    "    for t in range(env_obj.env.episode_length):\n",
    "        actions = {}\n",
    "        for agent_idx in range(env_obj.env.n_agents):\n",
    "            # Use the trainer object directly to sample actions for each agent\n",
    "            actions[str(agent_idx)], agent_states[str(agent_idx)], _ = trainer.compute_action(\n",
    "                obs[str(agent_idx)],\n",
    "                agent_states[str(agent_idx)],\n",
    "                policy_id=\"a\",\n",
    "                full_fetch=False\n",
    "            )\n",
    "\n",
    "        # Action sampling for the planner\n",
    "        actions[\"p\"] = trainer.compute_action(\n",
    "            obs['p'], \n",
    "            planner_states, \n",
    "            policy_id='p',\n",
    "            full_fetch=False\n",
    "        )\n",
    "\n",
    "        obs, rew, done, info = env_obj.step(actions)  \n",
    "        scenario_metrics.append(env_obj.env.scenario_metrics())\n",
    "        if done['__all__']:\n",
    "            break\n",
    "            \n",
    "        if ((t+1) % plot_every) == 0:\n",
    "            do_plot(env_obj.env, ax, fig)\n",
    "\n",
    "    if ((t+1) % plot_every) != 0:\n",
    "        do_plot(env_obj.env, ax, fig)\n",
    "        \n",
    "    env_obj.env.dense_log['scenario_metrics'] = scenario_metrics\n",
    "    return env_obj.env.dense_log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c8712461",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "obs = env_obj.env.reset()\n",
    "dense_logs = play_episode(plot_every=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "50cfc212",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/akash/miniconda3/envs/ai_economist/lib/python3.7/site-packages/ipykernel_launcher.py:173: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
      "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_______________:_ Agent  0 _____|_ Agent  1 _____|_ Agent  2 _____|_ Agent  3 ____\n",
      "Cost (Wood)    :   2.67 (n=  3) |    ~~~~~~~~    |    ~~~~~~~~    |   2.99 (n=113)\n",
      "Cost (Stone)   :   3.00 (n= 12) |   3.00 (n=  1) |   2.50 (n=  2) |   3.10 (n= 98)\n",
      "\n",
      "Income (Wood)  :   3.00 (n= 42) |   2.97 (n= 74) |    ~~~~~~~~    |    ~~~~~~~~   \n",
      "Income (Stone) :   2.97 (n= 30) |   3.00 (n=  9) |   3.14 (n= 73) |   3.00 (n=  1)\n",
      "Income (Build) :  16.47 (n= 27) |  11.33 (n=  2) |    ~~~~~~~~    |  22.25 (n=128)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x216 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = breakdown(dense_logs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "97cb8ed7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[16.472372947006132,\n",
       " 11.331640623590097,\n",
       " 13.267112338979295,\n",
       " 22.249614304395735]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[env_obj.env.world.agents[i].state['type'] for i in range(4)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "72cab2f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.11391710331709559, 13.267112338979295),\n",
       " (0.3619481561020035, 16.472372947006132),\n",
       " (0.3949931226438046, 11.331640623590097),\n",
       " (0.5462958764998518, 22.249614304395735)]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = sorted(env_obj.env.world.agents, key=lambda x: x.state['build_skill'])\n",
    "[(x[i].state['build_skill'], x[i].state['build_payment']) for i in range(4)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5f153ca7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Woods: [69 85  0 28]\n",
      "Stones: [51 10 72 34]\n",
      "Total: [120  95  72  62]\n"
     ]
    }
   ],
   "source": [
    "woods = []\n",
    "for gs in dense_logs['Gather']:\n",
    "    wood = [0] * 4\n",
    "    for g in gs:\n",
    "        wood[g['agent']] += g['n'] * (g['resource'] == 'Wood')\n",
    "    woods.append(wood)\n",
    "stones = []\n",
    "for gs in dense_logs['Gather']:\n",
    "    stone = [0] * 4\n",
    "    for g in gs:\n",
    "        stone[g['agent']] += g['n'] * (g['resource'] == 'Stone')\n",
    "    stones.append(stone)\n",
    "print('Woods:', np.array(woods).sum(axis=0))\n",
    "print('Stones:', np.array(stones).sum(axis=0))\n",
    "print('Total:', np.array(woods).sum(axis=0) + np.array(stones).sum(axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0cb864e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "rews = list(map(np.cumsum, zip(*map(lambda x: x.values(), dense_logs['rewards']))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a1acb659",
   "metadata": {},
   "outputs": [],
   "source": [
    "labor = list(zip(*map(lambda x: [v['endogenous']['Labor'] for k, v in x.items() if k != 'p'], dense_logs['states'])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "56558ae1",
   "metadata": {},
   "outputs": [],
   "source": [
    "coins = list(zip(*map(lambda x: [v['inventory']['Coin']+v['escrow']['Coin'] for k, v in x.items() if k != 'p'], dense_logs['states'])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f591af7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7eff3889b290>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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sB06tfE5YWBiDBw9m2bJldOvWzaHnEsITrDVfXN79rrucHIl7kpa+DU6dOkVWVhYA+fn5LF++nE6dOjk5KiFc36lduzi2ejUAl159tZOjcU8u3dJ3luTkZCZMmIDFYsFqtXLLLbcwevRoZ4clhEvLPXWKmeZN207jxuHt5+fkiNyTJH0bdO/enc2bNzs7DCHcytaPPwbg0hEjGPrKK06Oxn1J0hdCOJ2lqIjlf/sbAGM//LB0IjVhf9KnL4Rwqj2LFjHN3x+AYf/8pyR8B3PJpO8Kb61yhRiFaAj2Ll5c+rnDtdc6MRLP4HJJPyAggPT09AadVLXWpKenExAQ4OxQhGiwrBYLcwYOZPu8ecQMGMBjJ0/SvEsXZ4fl9lyuTz86OpqkpCROnTpV7bYFBQVOS7wBAQFER0c75dxCNES/vfkmCc89R9thw+gwejRRfftyfM0a2gwZwsCnnpJunXricknf19eXNm3a1GjbhIQEevbs6eCIhBA1cWj5coqys9n//ffsWbiwtDz+hRe4ZMAAJ0bmWVwu6QshXEtxfj5njh7lwLJldLvtNq7/+GP2LFrE0V9+wb9xY6Jl3qp6VW3SV0rNAUYDaVrrbmbZc8D9wLk+lqe11kvMdU8B9wEW4CGt9Q9m+UjgLcAb+K/Werp9qyKEaGhKCguZcckl5J0+DUDnG2/E28+PrjffTNebb3ZydJ6pJi39j4B3gbkXlP9La/162QKlVBfgNqAr0Ar4SSnVwVz9HnA1kARsUEot1lrvqkPsQogGbN9333F09erShA/Q8brrnBiRgBokfa31KqVUbA2PNxb4XGtdCBxWSh0ArjDXHdBaHwJQSn1ubitJXwg3lLZjB5+NGVO6fH9iIqGRkTK1QgNQlz79yUqpu4BE4HGtdSYQBZR9U3GSWQZw/ILySjvylFITgYkAERERJCQk2BxgTk5OnfZ3RZ5WZ0+rLzT8Oh+dO5dj8+cD0PWFF/AOCWFfdjZkZ8O+fTYds6HX2REcVWdbk/4s4EVAm9/fAO61R0Ba69nAbIC4uDgdHx9v87ESEhKoy/6uyNPq7Gn1hYZZ56LcXJSXF5aiIn4ZPBgA/8aNGfvEE/gGBtb5+A2xzo7mqDrblPS11qnnPiul/gN8Zy6eAGLKbBptlnGRciGEi/tmwgR2f/116fJNX35JuxEj7JLwhX3ZlPSVUpFa62RzcRxw7rVRi4H5Sqk3MW7ktgfWAwpor5Rqg5HsbwNur0vgQoiGYe+335Ym/F73309OcjJthw7Fv1EjJ0cmKlOTIZufAfFAuFIqCfgHEK+U6oHRvXME+DOA1nqnUupLjBu0JcAkrbXFPM5k4AeMIZtztNY77V4bIUS9yjh4kM/NETnj5s2j+x13ODkiUZ2ajN4ZX0nxBxfZ/iXgpUrKlwBLahWdEKJBmz9qFAA97r1XEr6LkCdyhRC1duSXX9j68cek79tHcIsWDJo61dkhiRqSpC+EqLVfnn+eIytXAjDuk09oUsP5sITzudzUykII51r60EMcWbmSyydM4MnMTC4dPtzZIYlakKQvhKix7JMnWf/OOwB0GD2agLAwJ0ckakuSvhCiRnLT0ngzynjA/vq5c+ly001OjkjYQpK+EKJGVr/8MgDNu3alvTlqR7geSfpCiGrlZ2ay7q23ALjrp58IatbMyREJW0nSF0JcVH5GBv/u3h2AIS+9REjLlk6OSNSFJH0hxEUdXrmSs0lJAPS45x4nRyPqSsbpCyEqVZyXx7udOnH2uDEr+lM5OfgFBzs5KlFXkvSFEJXavXAhZ48fp9011xBx+eWS8N2EJH0hRAWW4mIW3nknAFe/9hotunZ1ckTCXiTpCyFKaa1Z889/cmzVKgA6jBkjCd/NSNIXwg3lpKSwYeZMLMXF5cqVUrTs0YPAMkMuQ1u1onnnzgAcX7OGFVOmlK4bMm1a/QQs6o0kfSHc0OYPP2TViy9WeBG5paio0u1j4+PpNn483/35zwDcu3YtgU2bEt6xo8NjFfVLkr4QLuzgjz/y05QpaKu1XHnq1q0ATC0sLFdemJ1NypYtpcsl+fkkzprFnm++4Yj5Eu7IXr1o2aOHvOrQTUnSF8JFZZ88ybwRIwDoOHZsuXXefn5cMnBghX38Q0Np/Yc/lCu7dPhwjvzyCx/HxxPYrBkTN250XNDC6STpC+GiEt9/H4DI3r257Ztv6nSs2Kuu4v7ERJRS9ghNNGCS9IVwMQUpKbx96aVkHjoEwC3mS8nrqlXv3nY5jmjYJOkL4WJSf/yRzEOHaHv11cTGxxPWurWzQxIuRJK+EC4k89Ahjnz4IQC3f/ddhdE5QlRHkr4QDVje6dNs/vBDrOZ4+z0LFwLQ/4knJOELm0jSF8KJ8jMyWPPaa2irlchevfALCQHAx9+f1oMGsXnOHH568skK+1317LP1HapwE5L0hXCi7Z99xprp0ytd59+oEYVnzwLnx9sX5+ez8vvv8Q8NrbcYhXuRpC+Ek6Ru28bSyZMB+NupU2QePly6Lm3HDnZ//TWnd++mzdChpV053n5+BLZq5ZR4hXuQpC+EAxWcOcMPjz1GULNmNOvQody6xFmzAIjq25eg8HCCwsNL10X16UNPeWGJcABJ+kLYidViIXXbttKbrgDH1qxhy5w5F93v3jVrHB2aEKUk6QthJ1s+/JBv77+/0nUPHTqEt69vubKCM2fQVite3t71EZ4QgCR9IWyWn5HBxtmzS2euTPjHPwC4/fvvAaPlf2j5crTVSpM2bSrs3yg6uv6CFcIkSV8IG2379FNWPPVUubLofv1oP2pU6XLHMWPqOywhLkqSvhA22L1wIcseegifwECeys5GKUV+ZmaFKY6FaGgk6Qthg60ffwxAh2uvLe2TDyrzNiohGiovZwcghKs5tGIFexctovMNN3DzV185OxwhakWSvhC1tPWjjwDoVcVIHSEaMkn6QtTCzi+/ZNu8eTSKjqbdyJHODkeIWpM+fSEu4mxSEr+8+CJWc1jmFrOVP2rmTCdGJYTtqk36Sqk5wGggTWvdzSxrCnwBxAJHgFu01pnKeNfaW8AoIA+4W2u9ydxnAjDVPOw0rfXH9q2KEHVXnJfH1rlz0VYrreLi2Pvtt2yaPZtGMTGlrxLseN11MhRTuKyatPQ/At4F5pYpmwKs0FpPV0pNMZefBK4B2ptffYFZQF/zl8Q/gDhAAxuVUou11pn2qogQ9rDzq6/4/sEHK5Q/euwYANpqxVJmmgUhXE21SV9rvUopFXtB8Vgg3vz8MZCAkfTHAnO11hr4XSkVppSKNLddrrXOAFBKLQdGAp/VuQZC2EleejqL7r4bgPsTEzm1axcHly0jrMzTtMrLCx9/fydFKETd2dqnH6G1TjY/pwAR5uco4HiZ7ZLMsqrKK1BKTQQmAkRERJCQkGBjiJCTk1On/V2Rp9XZnvU9ZR4nqHVr9mVnQ0wMTc0ROg3pZ+pp1xikzvZU5xu5WmutlNL2CMY83mxgNkBcXJyOj4+3+VgJCQnUZX9X5Gl1trW+e7/9li/GjUNbLBXWPbxzJ37BwXaIzjE87RqD1NmebE36qUqpSK11stl9k2aWnwBiymwXbZad4Hx30LnyBBvPLUSdHfrpJ7x8fBg4dWppWUFWFn4hIQ064QtRV7Ym/cXABGC6+X1RmfLJSqnPMW7knjF/MfwAvKyUamJuNxx4CiGc4OdnnmH9228T0b078c895+xwhKhXNRmy+RlGKz1cKZWEMQpnOvClUuo+4Chwi7n5EozhmgcwhmzeA6C1zlBKvQhsMLd74dxNXSHq044vvmD1tGmAjLUXnqkmo3fGV7FqaCXbamBSFceZA1z8FUJCONj3DzwAQJuhQ7lkwAAnRyNE/ZMncoVb2/f99yx/4gm01Up+RgYFWVm0GTKE6z74wNmhCeEUkvSFW8pJTaU4L48N777LmePH6ThmDNaSEjIOHGDk228T1rq1s0MUwikk6Qu3k7x5M7N79SpdbtK2LTd+Js8BCgGS9IWbObpqFQd//BGAETNmUJybS3T//k6OSoiGQ5K+cBvZJ0/y0VVXAeAXEkLfv/4V5SWzhwtRlvyPEG5jzyLjcZEe997LXStWSMIXohLS0hduY5f56sKrX32VoPBwJ0cjRMMkSV+4vDPHj/N+z57kp6fTcexYSfhCXIT8/StcmrWkhLWvv05+ejrNOnSg/+OPOzskIRo0aekLl5ayZAn7334bgImbNslkaUJUQ5K+aDAyDhxg03//i7Zaa7zP/n/9C4Dx334rCV+IGpCkLxqMde+8w/q338YnMLBW+7UZMoQOo0c7KCoh3IskfeEUG2bOJHHWrHJlaTt2ENyiBU+kptb4OCuWLmXAlVfaOzwh3JYkfVFvinJy+Oy66+h+551s/fhj8tLTiSnztKxPYCCdb7ihVsf0DgwkoHFje4cqhNuSpC/qRdLvv7N5zhyOrFzJkZUrAYj7y1+49r33nByZEJ5Fkr5wOKvFwtxhwyjOzQWg3ciR+DduTM9773VyZEJ4Hkn6wuH2LFxIcW4ufSZPpknbtvR75BGUUs4OSwiPJElfONySScbL1Hrddx8te/RwcjRCeDZ5Ilc41JaPPiI3LY1+jz4qCV+IBkCSvnCoRffcA0D7UaOcHIkQAiTpCwf6acoUAPpMmkTbYcOcHI0QAiTpCwfJz8xkzauvAtD9j390cjRCiHMk6QuHWPrXvwLGnDjRffs6ORohxDmS9IXdnTl2jO3z5wMQI1MkCNGgyJBNYTdaa7JPnmRG69YAjPnvfwls2tTJUQkhypKWvrCbn6dO5V/R0QB4+fjIzVshGiBp6Qu7yEtP59eXXwaMhP94SgpBzZo5OSohxIUk6Qu7WPXii4AxPPOKyZMl4QtRjfT0PFavPsamTclYLMaLg4qKLCQmJpOXV0zTphbi4+Ptfl5J+sIudnz+OaFRUYx86y28vL2dHY4QDcbZs4UcOZJFbm4R69adYO3a42RnF5GYeJLTp/MA8PE539PesmUI3bq1ICQk3yHxSNIXldo8Zw4FZ87Q4+67CWzSpNJtktatIyg8nOK8PHJTU+k0bpwkfOExsrIKyMkpQmtNYuJJsrIK2L49jdRUYzbZHTvSSE7O5vTpPLQ+v19goA/durWgV69IHnroCq68MoYmTSq+LS4hIcEhcUvSFxXkpqWx+L77APjxscfwCQggslcvAsLCSrexWiwc/OEHwOjDBxj0zDP1H6wQdma1agoKSli9+ijLlh1g69ZUkpNzym1jsVjZvz+j0v1bt26Mr683QUG+jBnTgdBQf3r1iiQkxI/27ZvSqVM4vr7OaxxJ0hcVfHnjjQAMfOopUIrsEyc4tXMnuWlppducTEws/WwtKcG/cWOad+5c77EKUVc7d6Zx6lQes2YlkpR0lr17T5OebnStKAVRUY3o3TsSf//y6XLYsLb07NkSpRRhYQH07m0k9ubNg51RjRqTpC/KKcjK4tivvwLQ79FHCW7evNLtivPz+e2NN+j78MNYS0pQSuETEFCfoQpRIydPZrNs2QHOni1k69ZUTp/OY/fuUyQlncVi0ZSUGDdRAwN9uPLKGPr3j6FPn1a0aBHM7bdfRqNG/k6ugX1J0hcUZGWBUgQ0bsy7nToBcPOCBVUmfADfwEAGTZ1aXyEKN5KbW0R2dlG5sn370jl27EyFbTMz89m0KYWTJ5P58MOsix43PT2PLVtSyvWfa63Ldc14eyu6dm1BREQIo0d3ICDAh6ZNA+nZsyUdOjSjdeuwSo7sXiTpC/7Tpw8ZBw7QbuRIclNTAbh0+HAnRyVcTXGxpTThnjyZza5dp8jLKyYx8SSpqbmlQxP37DmNxaIvfrAygoJ8adTIm337CqvdtmfPSFq2LN+90qiRP6NGtadXr0gCAnwIDPStVb3cTZ2SvlLqCJANWIASrXWcUqop8AUQCxwBbtFaZyrj/XhvAaOAPOBurfWmupxf1F1+ZiYZBw4AcGDZMgDGffIJ/qGhzgxLNFBFRRa2bEnBatWlyxs2nGDHjlPMnbu1tPxCjRr506VLc1q1CuWKK6KIi2uFl9f5V2YGBPgQF9eKgICKKal168asWbPaIWPWPZE9WvqDtdanyyxPAVZoracrpaaYy08C18hCeVoAABijSURBVADtza++wCzzu3CiNf/8JwDjv/uOqD59SFq3jvbXXOPkqISzFBaWcPSo0c2Sm1vExo3JJCdns3ZtEuvXnyAjo/Kx40rBnXd2p1OncMAYd967dyShof7ExobRokXDvrnpSRzRvTMWiDc/fwwkYCT9scBcrbUGfldKhSmlIrXWyQ6IQdRQ0tq1ALQbORIvb286jhnj5IhEbZSUWMnKKqhQfq575UIpKTls355auqw1bNqUzNatqcTENOLUqTwKCkoq7BcREcyAATF06NCstMV+TuvWjenQoRne3jKVlytQWte8b63CzkodBjIBDbyvtZ6tlMrSWoeZ6xWQqbUOU0p9B0zXWv9qrlsBPKm1TrzgmBOBiQARERG9P//8c5vjy8nJISQkxOb9XVFN6mwpLCTpiy8Iad+eHU8/TVivXlz+xhv1FKF9ues11lpT2X/NoiIrCQknOXKkiFOnCtmwIZPs7IpJ+mICArwIDT3frx0Y6I2vryImJoigIG86dAglONgYR96qVSCRkQGEhfli/Hd2Dne9zhdTlzoPHjx4o9Y6rrJ1dW3pD9Ran1BKtQCWK6X2lF2ptdZKqVr9VtFazwZmA8TFxem69OMlJCR4XD9gTeq8d/Fifv3ww9LlYU8+SVcX/Tk56hpnZOSza9cpEhNPVtrytbeDBzM4dOj86JR9+9JJSjp70X1CQ/3o3781gwfHEhLiV26dt7eid+9WFYYbKgXt2jV1uVa5/F+2nzolfa31CfN7mlJqIXAFkHqu20YpFQmce6LnBBBTZvdos0zUo8KzZ/l87FgAmnXsSNbhw8QOHuzkqOynsLCEEyeyq1yvtWbOnM3s21f505QpKTns2JFWaZeJI3l5Kbp3jyhN3h07NuOOOy4jKKjiSBOLJZW//e36ColeiJqwOekrpYIBL611tvl5OPACsBiYAEw3vy8yd1kMTFZKfY5xA/eM9OfXny0ffUR+ZiaFZ43WY6OYGB7YsoUzx49fdDy+veXmFvHKK79y6pQxP0mnTuHExDS2+XgrVyYxa9YCNm1KxmrVJCdnk59ffcu8cWN/oqIaVShXCq69tj2RkSH07t2Kbt1a0K6d418E4+Wl8POr2aP5CQkJkvCFzerS0o8AFpr9fD7AfK31MqXUBuBLpdR9wFHgFnP7JRjDNQ9gDNm8pw7nFrVgtVhYdE/5H/d9v/2GT0AAzdq3r9Ox09Pz+OCDzWRmnh/VkZlZwObNKZUO30tJySEp6SxNmwZSUFBCXl5xnc4PEBzsS9++0bRqFYqv7/lRI1Vp2jSQUaPalxsyKISnsDnpa60PAZdXUp4ODK2kXAOTbD2fsN38UaMAY1qFJm3bUpyXR2irVnU65tGjWfTo8X5pN4iPj1e5JHrhCI9zWrQIZurUP/DnP8dhtWr27q3dgzoX2rhxA3/84yhJ4ELUkDyR6+YOLFvGwR9/BIyk3zgmppo9zsvPL2b9+hMkJZ2tMPxvz550srIKeOyxftxwQ2cGDLik1rF5eSk6d65b19Lp08GS8IWoBUn6bspSVMSqadNK32g1/I03qkz4Wmu2bElhxox1pKYa85RYrZpffz1Wrn+87IseALp1a8Frrw2XpCuEC5Gk76b2L11amvDbXXMNPc358cHoh//99yR++y2JjRuT2b8/nYMHMwkI8OHyyyNKt7vqqlj++MfuxMQ0ok+fqEofkRdCuBb5X+yGJk9eQs77T9IGOOrTnnfX9mdy7L9L15cdjhgd3Yj27Zty9909uPXWrrRvL++2FcKdSdJ3YQcPZnDmzPmZBwsKSvj66yTmzUtikk5Ce/sR+pe3uP2C/fz9fejTpxVXXRVL8+ZBTn3SUghRvyTpu6h9+9Lp2PHdCuWhnOUP/IofuQx/8036PyqTpwkhzpOk76Kef/4XAP7znzG0aBFMSc5Z8vZv4/TONZz5aj2NYmJo40ZP2goh7EOSfgNhsVhZt+4EhYU1m+dl5crDBAX5cu+9PfHyUix75BG2v/UWAIHNmvHosWOODFcI4aIk6dej1NQc1qw5TufO4URHN8LPz7v0Zctff72bW29dUKvjvfee8VDS9vnzWWcm/IBWreh6/fV2j10I4R4k6dejv/51KV99tat02cfHi8sua4GvrzcnTpwlKMiX77+/nZrcV/Xx8eKKK6IAWPvaawD0ffhhAq6/3uNmIxRC1Jwk/Xpy7NgZvvpqF506hfPgg3EUFVnYvj2NtDRj4rGmTQOJj29NfHxsrY67ato0UrZsIe7BBxnx5pv8smqVA6IXQrgLSfr1QGvNI48Y75996aUh3HBDZ7sctzgvj9UvvQRAj3vuQXm51hzpQoj6J1miHsyevZGFC/fg7+/NuHGd7HbchOeeo6SggG7jxxPVp4/djiuEcF+S9B3s+PEzPPDA9wBs2fKA3R6EOnPsWGlf/tBXXrHLMYUQ7k+6d+ykuNjCli0ptGoVSlRUI5KTsxk6dC6nT+cB8Kc/9aRjR/tNcZD4b2NahV4TJxLWurXdjiuEqB8ZFthbCAeKzpftL4Ij5ismvINaE++A80rSt5MZM37n//7vJwC6dm3O7t2nsVo1t97alTZtwpg2bYhdWvlaa74eP56dX3wBwIg336zzMYUQjrO3EN7PhBMlsNOcNSXfCoeqeH9QhDcEeUG0j2NeBC9J3w6Kiy08/fTPADz2WD9Wrz5GQIAPYWEBfPrpDXV+CfXXt9+Ot68vg555hqLc3NKE/4epU/ELDq5z/EII+ynRoIHf8yDFAg8kQ5YFGntBzwBoYr4Vc2woXBYAvQMg2EwR/gqizdciJyTsBAe09SXp28H8+dspKbEycWIv3nhjBGD8IrBYdJ0TfkFWFjs++wyArXPnlpbfsWwZ7UaMqNOxhRB1c7AIFp6FQg0FGr7Nhq2FFbd7shlMj6hY7gyS9OsoP7+Yu+823v0+deqg0nJfX298fet+/PXvvQfA4GnTCAoPJ+/UKTIPH+aSgQPrfnAhRDlaw+FiyLbC/87CjkJILYHtlSRygLPW8sstfeCJJiU08dZE+EA3f+jgl0sT6zoosBgbWTOgZDNwwc4lR8Gyv3Sxc2QE0tJvgGbM+B2Af/5zGDExje1+/NQtWwDo/+ij+AYF2f34QniqIg17Co0vgOMl8NkZ2Hj+dRNc4mt0y4wNhWbe4KvziWQbCuO9zgFemjEBW2mpUlAlG1CWVFTJFrBYwAJU8csCANXoggIf8O0FXkZ5YbG/3ep6wVmErX7++XDptAoPPmj/cfJ5p0+za8ECOoweLQlfCBsVWvL5Jus4x4qNtvXOQqOFfqjI6JLxo4g4n0QiVCpTfTdyWdNsovRGfMnHu8LYi5zyi1Ygz/ysmoLvZRB4F3hfWn473y7gFVVmuRuoi/+fPrQ1gdq/ebp6kvRttG9fOkOHGn3sjz7aj5AQP7sdW2vNiqefJu/0aQDaDh9ut2MLUSldArmvQ8n+6re9kDUVSrbbP6Yy+rUthLTqW75aQzHG6Jg8q9Gaj/BK5VZVpsl97r9qQCX7qyYo7xjwjgOfyp6cV+DTHbxanC/yagy+cYA3qIb/6JMkfRvccMMXrF17HIClS+9g2LC2dju21WIhJzmZNdOnl5Z1u/VWux1fuCGt67Z/yWbI/jsULjNbo7UdWqzAtwd4Oe5Vm5kZKUQ2agkYjetcM6Gnm93kOVbItBj974XmjyPEyxgJc1r54OXbm8sDG+FVVdW8WoFPF5RXU1DunRbdu3YO8PTTK1i4cA9XXhnDPff0YPjwS/Gq8l9S7eRnZPD2pZdSkJUFQOtBg+h8000Et2hRzZ7CZVlSwJJU9XprEpTsKVd0SdNDkPM7YIXCn6AoAahj4scLGs2C4AfqeBzbWLTxUNKRIthnPqyUbTX614s1nM47RXh2cwC2FBg3Wy8U5QPt/WBUCAwIgv6B1GjGWk8jSb8WMjLyeeWVXwF4//3RdOtmv2RcmJ3NNxMmUJCVxeUTJuDt58eIN9/EL8QxD2gIB9BFFRN46UiNSpKyNQOynwcKKq67iLbNgWxzQQVD4J/AO+piu1ycV2PwHw0+7Ww/Rg3kWSExH5JK4Mcc+CXv/E8lw2Ik+QuFeUGML+T6BJJl/jJo4QN/bWqMd+/qD5E+4KOMkTOievJjqkJWVgGHD2fSs2dkadnIkfMAmDdvnF0TPsD2Tz9l33ffATBk2jQaRUfb9fjCTqy5kPc+WPZC8XajP7t0XQrovKr3rYxvPwh5mqq7VLzBr2+5m36rVq1i0KBzw4N9QXnX7pwOZNXwW76R4EvLgB9y4N0Mo7/9nOHBRsIGo/bdA4zlPoFG1wwYI2Z8FCQkJBLfPb5+KuHmJOlXYdKkJcyfb9ycUgqioxuRnJzDgAEx3HprN7ufb8PMmQCMmzdPEr4jFW8Ga2bl66wZxvqyrXLrSSjZeX7ZkmJ0uagQ42aebx9Q5x7I8Abf3qAuGLrre8GNv7K8Wtb65p9V+4Gq5C6kg1m1MW49uQS2FhhPnm4ogLQSSCww+tgv5roQuC7USOqRPtBcso9TyI+9EsnJ2aUJ/5lnBlFQUEJi4kliY8OYMWMkPj72vUNfUlhI2vbtNG3Xju533GHXY7sUaxZYjtRqlxD/A1AcZiwUrjRuRpZlOWR8GSeo4VHLPlXnZY6dbmIuRkLgDAi4weEdxmkl5VvM56R4BXCkqGJ5Xe0shL1FsKkAThYbT5aWvUecqysm9hAv6O4PN4ZCB3NUTLQvdL5goE1zb+jgmGHnopYk6VfinXfWAzB//g2MH3+Zw8+3Z+FCAK567jmHn6s+WLUxmgIAXYJXyXbAgpflKAUF35JrMYbP+XKGMOsmlDaGYPhzutbniouFsrudUV0pUaHnY6EVWT5jKFHGHEVFqhlZXj2pqjsly6sHJRUemrlAMeX7Kapg0UYLOK3EaBEXVpLADxbDpZU8uV2kjYeFKhXeDw5Uf35bhXpBtI/R/XJha7y9H7TxhV7mHDK+yuh+Ea5Dkn4lZs/eiFI4pBunrJLCQg799BP7lywBcOjUCtkWWJVXsz/DayNUJ+NDPgC+1hT6WF6mq9evpS3EEJWDj7KUbh8EnLJ0KF1eb7mC49YYAIrwY6OlNznatpvXZ3UjEkri0Q3sNRHNvSHWF3pe8CxOkQZ/L+jiZ3y/UEtv6FZJL86ePXvo1Ml+L+M5J0jBFYEQ5Wskc+GeJOlf4H//2016ej7PPjvIbkMxq7Lpv/9l6eTJAMQOHmz3efG3F8Arp+GHXGN0xDn2uuhPB7zIlMBny5WVeHnzs76HRt7B+Jk/vgzViWxl3KfI8OpD18CI0lkF25hf5wyrZQwbNmygTwN+a1hzH/uPKkkoSCE+zP5JX3gGSfpl5OUV89hjPwDwwANxDj3X+vfeK034Tdq2pctNN1W5rVUb83H/epGBIQeLjcfKi8OvxHevUZZpMXqxhwRD30DoEQADAiGyuongSg5B8bqLb1O8BXL/Cf7XQ8A4s1Dh4zeI4T7191KXdEsul9X/PU0hXJYkfVNRkYV3313P0aNnuP76TkRGhla/k40sRUWsevFFANqNHMkdS5dW2GZPIfw52XjCMK0EMq3GwyeBVfRc+CkYGQJnkk8R1cwYsx3iBQ83Nf5cr0BryH0NCleA8js/RrtoLRSvr1lFVBiEzQUvx/2shBD2JUnf9PTTK3jjjd8ICPDhyy+rbnXbw5rXXiM3NZUuN9/MmPmf8VueMSHf0hxYmWtMArW5AMK9YWiwcctxSDDcG0YlE0CVl7B/P/GR5oM62mK02HO3QXEi6FzQZ6BwKcZRNfhcBjobilYa+3g1g6C/QOCd4NX04ifzCpeEL4SLkaQPnD1byBtv/AbA3LnX4+vruIddNsyaxcqpUwEoeeI5Bh7zLjeV65WBRrK/LwymhkNsdfO46RKjZW45AYVLuKLNCkgz+zusp0BnmRt6g3dbjAmjOoNPV/AfAYH3ybPqQngQj076Z88WsnVrSunkaa+/fjU339zVYedLT05lyV/+AsCBMXfwXEgX/AthVkto52cMgesdWM1BrDnGY/0lh6Hwe2Ncuj5burqguDdBjc6NjlHG7H/+w8G7NXjJlA5CeLp6T/pKqZHAW4A38F+t9fRqdrGLtWuPk56eR79+0TRvbozZnjRpCfPmbQMgONiXyZOvKLdPtgWyrMasfRvyjW6X6jS27iLSmkCYdRch+jBg3ExNTS1k+ZDVALSd2ZNBQ9KY2SiaENJQhZx/2UJWpYcto+wAcS/wvxr8rwW/K8Erim2r9xDfLr76QIUQHqlek75Syht4D7gaSAI2KKUWa613OfK8Bw5kMGDAHEAzIv4Q/a7wwdvbiwB9hunPNmH0mA6EN/NiX9aDHCo639eSbSk/TZYP4KeK6OO9gSBVcSiNH0U09TIe8bdqxR5rJ3J1MNZiK0e+TKMk3XiMckS8lRbNMkG1A9/xlH8CtDoKfC8H70jw7WvchC1nT6V7CSEE1H9L/wrggNb6EIBS6nNgLGDXpL9n3w6Wju4NwGaz7M324K0s+Jy0wDdGWTOADfDL58ayBkrwLfespirz/dznJcqHSt/AAGjVHK1C0fiZe+SReyKJ4rNGF8zfCwrw8Zfn0YUQzlHfST8KOF5mOQnoW3YDpdREYCJAREQECQkJtT7JqdMpeLVugqbMw/ZK4e2jyLI2JcPSAl3JY/jF+NOqpIhQXdXz7+aharmuSWRLAqKi8GvShF9/+62GtbBNTk6OTT8zV+Vp9QWps6dwVJ0b3I1crfVsYDZAXFycjo+Pt+1AN91GQkICNu/vojytzp5WX5A6ewpH1bm+Jyk5AcSUWY42y4QQQtSD+k76G4D2Sqk2Sik/4DZgcT3HIIQQHqteu3e01iVKqcnADxhDNudorXdWs5sQQgg7qfc+fa31EmBJfZ9XCCFE/XfvCCGEcCJJ+kII4UEk6QshhAeRpC+EEB5EaW3HF6bamVLqFHC0DocIBxvetu3aPK3OnlZfkDp7irrUubXWunllKxp00q8rpVSi1tqx7z1sYDytzp5WX5A6ewpH1Vm6d4QQwoNI0hdCCA/i7kl/trMDcAJPq7On1Rekzp7CIXV26z59IYQQ5bl7S18IIUQZkvSFEMKDuGXSV0qNVErtVUodUEpNcXY89qKUilFKrVRK7VJK7VRKPWyWN1VKLVdK7Te/NzHLlVLqbfPnsE0p1cu5NbCNUspbKbVZKfWdudxGKbXOrNcX5jTdKKX8zeUD5vpYZ8ZdF0qpMKXUAqXUHqXUbqVUf3e+zkqpR81/0zuUUp8ppQLc8TorpeYopdKUUjvKlNX6uiqlJpjb71dKTahNDG6X9Mu8fP0aoAswXinVxblR2U0J8LjWugvQD5hk1m0KsEJr3R5YYS6D8TNob35NBGbVf8h28TCwu8zyq8C/tNbtgEzgPrP8PiDTLP+XuZ2regtYprXuBFyOUX+3vM5KqSjgISBOa90NY9r123DP6/wRMPKCslpdV6VUU+AfGK+avQL4x7lfFDWitXarL6A/8EOZ5aeAp5wdl4Pqugi4GtgLRJplkcBe8/P7wPgy25du5ypfGG9XWwEMAb7DeA3xacDnwuuN8Z6G/uZnH3M75ew62FDnxsDhC2N31+vM+XdnNzWv23fACHe9zkAssMPW6wqMB94vU15uu+q+3K6lT+UvX49yUiwOY/5J2xNYB0RorZPNVSlAhPnZHX4WM4D/A6zmcjMgS+vSt9eXrVNpfc31Z8ztXU0b4BTwodmt9V+lVDBuep211ieA14FjQDLGdduI+1/nc2p7Xet0vd0x6bs9pVQI8DXwiNb6bNl12vjV7xbjcJVSo4E0rfVGZ8dSz3yAXsAsrXVPIJfzf/IDbnedmwBjMX7ZtQKCqdgF4hHq47q6Y9J365evK6V8MRL+p1rr/5nFqUqpSHN9JJBmlrv6z2IAcJ1S6gjwOUYXz1tAmFLq3FvfytaptL7m+sZAen0GbCdJQJLWep25vADjl4C7XudhwGGt9SmtdTHwP4xr7+7X+ZzaXtc6XW93TPpu+/J1pZQCPgB2a63fLLNqMXDuDv4EjL7+c+V3maMA+gFnyvwZ2eBprZ/SWkdrrWMxruPPWus7gJXATeZmF9b33M/hJnN7l2sNa61TgONKqY5m0VBgF256nTG6dfoppYLMf+Pn6uvW17mM2l7XH4DhSqkm5l9Jw82ymnH2TQ0H3SgZBewDDgJ/d3Y8dqzXQIw//bYBW8yvURj9mSuA/cBPQFNze4UxkukgsB1jdITT62Fj3eOB78zPbYH1wAHgK8DfLA8wlw+Y69s6O+461LcHkGhe62+AJu58nYHngT3ADuATwN8drzPwGcZ9i2KMv+jus+W6Avea9T8A3FObGGQaBiGE8CDu2L0jhBCiCpL0hRDCg0jSF0IIDyJJXwghPIgkfSGE8CCS9IUQwoNI0hdCCA/y/+MYbfHMtrO8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = plt.get_cmap(\"jet\", len(rews)-1)\n",
    "for i, r in enumerate(coins):\n",
    "#     if i == 0: continue\n",
    "    plt.plot(r, c=cmap(i), label=i)\n",
    "plt.grid(True)\n",
    "plt.title('Coins')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cdcafc36",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7eff3889ba10>"
      ]
     },
     "execution_count": 18,
     "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": [
    "cmap = plt.get_cmap(\"jet\", len(rews)-1)\n",
    "for i, r in enumerate(rews[:-1]):\n",
    "#     if i == 0: continue\n",
    "    plt.plot(r, c=cmap(i), label=i)\n",
    "plt.grid(True)\n",
    "plt.title('Rewards')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0a3e644f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['world', 'states', 'actions', 'rewards', 'Build', 'Trade', 'Gather', 'scenario_metrics'])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dense_logs.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8db68cac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7eff38598f90>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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miVj6yRYA5nOlcC61dR7B5beuw3cvORNXv/00Y97XP7oNtz+3B8987d049VXzXGP2q/5L4CFn8DAbbtyqd5xqM9bvPoyXu4eKhplnl7MU33MOyzKPmtRui9fuOgQAGClTcpmt9JJc294jnr+j74una1TdNKjdRe07Ml0yPzg8YRk3CmD6+G7dc8S4A3x25yFPy9nRWyht6z88os97MpPDoaOTAIAX9g4Ufad3uDB8r3bXsPnAENbtOgw7m/YP2Q63o99JtncWlrflQOkdSEffiBb3dEnZfN5kcoW/zfFYTyN9m262xKav5+HRSc8x+zELEnitIyjPTy8UY5zLvK0XB2tCL/s9bTq9oYrsVXJcOV08q8l8PLmFlE4mPB8z1plajz0F0/FaZsFGbKp8bH42YzpV/qUlXueXNp0L1q8YYZdbL2+L8K3uz9IoN2K67d0gPU6y1hK4w8zMmyhr3D5OHxor+NNcgVScCCMgnRTf585Mre3DLx3A2FQWP1+1E/0j3kq25uPYr3Ry+iIQtXRS9wk8Ytu7iFsvFKfxAkAcXolm7Q7oWIVi/p42XcI0789pP447NJbBD/+8BZNZvsSokrfRRSWBm48Xt/gbUsmSQoCHBQAoTXJ5pSCWaaz06gqIc2yX/mIN/t/jO/Dr5/Z4CqnBIYF73YcNRSXw4pXT51HuXJzplxayEbOG3M4Pt/F2B0c+r5BISEnS8Nq/W/9e1qYC/oa/bMfv1u/FX//VcZ7mRQUee2ZGSkOy9Bjyylqd4GX9xzPeCgU7tR5VC+elPU2fSgZPoeZSfNTySf2XwKO2xU3cYvMTu15qspa4natQVMl0dpPrXeeiUqdbTV4vgHbiuL0aUgnf61zS/uJh/Sc8JnBdmQ5VJZKJ4CnOXIqP2p6s/wRe6wAcuHYjdCuB2xzEesnZWuqptAolSMIKg1KqKhdfz3cmAWKJShVKJdLJhO91LqlC8bD+kxUmcK+heU30Tooa9CN2Ma7/BO6wvQ8OTaB58Qrb7l29w4Vxq7f3zVhsd7jU4x0enSo7rvPwGB7aeKBkuF6XaD35vN7G670k58/xXrv223WdJcO+dt9LuOD6Jz3Pw+r/3L0Bf3f9k0Un/7cf3ISW/3jC+Hz6N1egefEKfPjWtSXff3pHP5oXryh66Oq36zrRvHiFcSfxx+f34fRvPWLM42O3rzemve3pXWhevMK4iLgl4XJd34DiEmnz4hUlD7OYxzUvXoGtPaVd3qotnQxSAi/+7OUC5rUKRXfdo4XnHy5bsgZX3fE8vnLvRmP7mT21ffrcbl68As/uLBwX5geMdP93uf2PiaWTCZx37RP4yr0b8d2HtgAAnt9zGM2LVxjdCB98cT/Ov24VmhevKHrw6UO/XFt2f4eh7hO4U0v6hn2Fvpr3tO4rGae/42Pp07tnJjAAv3xqV+jz1A+WihoxTaP07XXB608omiafV6YuU8Xfv2Fl6Yv972vvNp6w8+PRzQfRMzRR1JB2d+s+oz9xIdbC/y90Dli/jt+v3wsARe9q0eMcmyycYI9tOWiMe6FzAGs6ppOwniCmq5QsXeMs2+Detq6y62JNYJMuj6A/8Uqv4/hqSCak8hK4Nr31zimnlGt7jtGI6dCN0M7GrkE8vaPf9sEfOz9/sgMAsGbX4ZLllGsYTScFvcOTRcsYnig8D2C+cOtPqPaNFD+pPZMv/ar7BB70hmfd7sOxet+Hniwqa8S0qQO3TF+rN8/ZNaYGVclL+bNltmfJPB2yTsm+cMlQyRAa3oIS+K/6sX4rl1eu61zpqwn0+VZKL+CkK6hbceqKaNdTx7gYaWayCq3uE7hT4nLaheZxrXvK3x5HTcboRVK83l67hJVLWFO5fE1+yNV6MujcTgqnUPV19LI6WeOCZpm/5cvmaEpKoNZ9UWaddOkQGt7cWPOp9bOIVN57xuhGWLr+bvvLGO/SjdDMT9LXn9BMJmS6C6DLkeDUFdHuvMrlVdEc3fZ3EHWfwJ14K5PGi1GFUlEvlOm/9Que9fZ5MlN8spgP0JncVuXqD91OXuXwl74tvMSd9djzxrx5rZNav+v2xscwur65KemlZPks4r/h1q4O3K0+vdyF2omfkq3+KoSiroEuR4LTU8l2x+dUNl80R69v+PSj7hN4GI3GEWt4dlSuBO10C2seo5+0TlUo1hLSTKabcidpkNvSSkpuWeOOxuWCYdq+1m1d0h7hEnsqhKcH3bjFlBAg5zPxlKy/Uq4XAz/L8lOyHZkovJ+lkouk0/6wi8HaIMsqlACcEpfXKpQ40Q+okpdZVfguFOtxaX33c7WuaZkycbudvOLwl/5dT1UoOfsqFKvihuDicdbk5V6FUoUSuGsCF/ht9rCrA3c7/srtZ+fvVB6gXgJPVlAf6NS+YReDtU87q1ACCGPT1aLu169MwCqUco2YtXp83u4WNZ9XgW5LK3lE3OvDS+btbb0lt257tzuAcq/9DcrpLsE+gZeus5e++SVPYir3Rkw/Xe38lGzLdbN14pSAvZTA/dTVexXbBL6xaxBn/WAlWneXNjCa+2HqB86S1R1o3zuAiUwO335wEwbHpjzXgT+66SDub+8OKXIY8cyEyWwOX/7TRuO94bpvP7gJly1Zg/a9R/CLJ3cWjTMnnNuf24PW3YdLGzFNJXC7Y39wbArffnBTSemjkr7EL+4bwI/+/Aq+89+bjGG/XF3a1TKTz7uWavSx1z26FWs7DuH2Z3cbXb/06hBPdeBlLmhOjYDP7zmC256ejvs5y+tY9XmOT+Xwubs34PN/2FDU3dG67Xf0juAnj20rSYw9Q+P4wcNbjOTnllx/tPwVbDkwhG89uMnoz1xumSs29aDz8Kjx+acrC8u//rFtKMuofisenMtPP1/wUtcgjtg832B0rVTeqywf2eT/JWvZnCpajlM3UKfCi/kVvTrrObB6+8z1YottAr9syRoMT2TxkaXrS8aZd4a+k366cjv+6Za1WNbejbtb9+GmJ3aWfM/MfDLsPjSKr973UjiBYzqemfDE1j48+OL+kiqPl7qHsLFrEP90yzrc8Jcdjif7R5auLymlWvsum8uI73hDE258fAfubt2H+zcUX+gqKe1+6JdrcceaPfj9+ul++X+yObGyOeW5e+Hew2P46O2t+I8VW4u+75VeN+tW2jOXMD/x6+eNfuQAiv42L39ZexdWbOrB8pd7cNmSNdPjLcv6+O2tuOWpXRiw/DrSN+7fhN+s7UTrniNaDM7rMjKRxQf/6zn8oXVfydv87EqJfzH1k1+yehf2D47jNg/PRZRUGeXzRXXcP11Z/CMkQGkjuRc//LP9gzdeWNdX/5EKO2799kumt6xLuQeEwhDbBO6k+AQorn8zv6zJKblU/Ca2iPD6s13mVn+7XG695TVfEKzjUgkx6jCtJdWZ6MedzasK6sDtv+82ja7cLbdTN0I3+jYpd4xZqxP0BGLdlpmsXvIufDYf505d3+xM2WxPa3xjbseWtlGsyTFvKoEDxRdQ/a2XRiN5Bd0Ig8jlleduhJUm8PFMrmptaHWZwM3yqvwtkFO920w2PMwkr3XVE6bp7NbUqQolr4preZ22lZ/uYaXzKN5P2VzevVeIwzijysHDsqcbMV2qbGxGl6v7dNsm5banWynVfGGd25B0nLY0JrvGuOJhAw6vdjCz3v3lHHqh6Imu2m0slTSaVvrjzZW+mCuIuk/gSpUvlTonnhi+AxTeb0UnXEpT1lK2+QSzbjenbRXGeyBKWvXzKtCFIVOmp47ttHoVio83R5Z7v4fbNinXQFtufvrl1Lw+8ypN4DZJamyq+Of0rFU4ZedVUgIv3w9cL4FXUoVybGPwt2Bnc3nPP5hS6cWl0ve6BFGXCdx8+5JXChOmg9N82+RUTRLHN8gBHm5zNebSlV3ycXp/Ry6vSnqulHthfxjb0VoSzHrolubEqEbzcBEo92oCK7teFuVKYjmXKpycJS59k1rnpw/XS4i5kEvgo5bfQx0ccy6B68eRtTrG2o3QfIgYdeAVlHKPreBFa+WYY3J7kKfSKhTr8TqTAiVwEblIRLaLSIeILA4rqKCKasBV8YFvvJAJzg1hfvqlRsHQuLdS0oRLqcKpCsV6S5zJm06BkqcOw0jg1n61+ZKEU0lCzxh10O4nmtEt0zJpSS8Um++WK1VmjMRRLj77Hi/WxGAdng9QArd7183RycpK4Po+cKtCMW+76QSu7WMPvVCOCaEEnslNd210u5BX2sA6kclV7TkJ3wlcRJIAlgD4BwBnArhSRM4MK7AgzLeoCqqoCsV8cDndhtvd5sahWmXQYwJ3a+x0K4Gbk4V5W1lLKzNRhZLJqZK7p4qertT2u93+L2mEzU03ejuxu364VaGUi7ncNis3P314tiiBV5bk7EqZo5PFy3MrgevHjN3FtdwFVm9ArKSUW8mrjssptKMUYhq1VBVZVVqFUs068CBb4q0AOpRSuwFARP4I4FIAofeZeeKVXsdXk961trPos96tCij8EKr5lnS91m98W88I+oYLXal29R8tmcd6m/7ld67ZU2noVef1XdIPbTxg9D1+qXuwZPzB4eJXYq7pOGQMa+s8UnTC7R8cNz6v33246D0Ty9q7ccL8xspWwmLZhm6ctGCu8fmBDd0lVUW/W7e36J0Vdu971j3xSi8ODI6jz7KOAHDn2k6kTA/SrNxyEHsOjaLL0t+3a2Cs6JjZcXCkZF73W+I2lr+1F90D42jdfaRkHFDYH+Z563dVj23uQeeh6b7Zej/tp3f0Y3QyW1RirrQEvrO3dHsNjhcn7La9pa/tNdu0fwh3re0s6ee9eltf0cVnR++IsX56yV9/xe/OvqMlx57VsXO8/Zyak/Z9A8bFedN+53Nm1GO1pG5rzzC6Borz1V1rO3HZ2SdjgcefgvNK/P7qiYhcDuAipdRntM+fAHCeUurzlumuAXANAJx66qlv2bt3b8XL+tSdz89oZ/iZ1nRsI97zxlfb9mkOy4fOORnPdRzy/GvdVnPSiZJb9HNPXYgN+0qTO0Xf1z7wxhl71qDW/v3CN+DmVTsrbsg+65QFeLl7qKLvhHkOPPGVv8frXz3f13dFpF0p1VIyfKYTuFlLS4tqa2ureFnDExnbeqpF89Jl6+WOaUwik1NGlUlDKmH83ZhKGCVG899WjVqJLptTgBRuBRMCnP2jx41pOq//YNF3JjI5NCQTSCQE+bzC4HgG8xqSaEwVEqTeuDQykUEmp7Bwbhojk1ksmDt9ZR6fyuHFrgF89Fet+Kvj5mDll95pXLmVUpjI5KFQaEj8m++vBADsue5ijExmcdYP/gIA2PDd92NOOoGESKHbnyq8QnNsKle0LXRz00nMbUhCKYXBsQwUgIVz05jMFl4jq5d4zdtrfmMKqYQY1TbmcYLCC4MqPckaUonCu6iVQjpR+FmvqTLzbEglHBsZ9f03lc0jnUogKQIFVXShWjQvjdGpXOH7qrgh0HpsNKQSSGk/GG09ZvpGJnDRTc8CKGx78zYWAAvmpjE4nimZpx7jZDaPhXPTyOZVSd2zXSzlhqeSgnQigbkNSQxPZDAnlcTRyWzRchpt3q43mc0jnRSktO9mc3kMT2SN+Zv/zymFYxtTGJ7IGv3Nkwkx4hYA8xqTGJ3MlZxr+rJ0gkKD69hU6bQp7YeVs3mFuekkprKFJ3AXzEtjdDKLbE4VtnOuEHsurzCvIYXJbA4CMc41/ZxJJwUjE1kjNvP2SyUFSgHHzUkVHR+NqQQGxzNIJwUigqQI0knB8EQW8xtTmMjmjNiSCUFCprdDYyqBuekkhsYL59Nxc1K+X1RWLoEHqULZD+C1ps+naMNCd5zDLdPxxzSUHdeYAmC+ezf9fUyZv4Oak56+dU0kpCg+c88A822gOXnr0+kv21k4L1102yUitj0MRATzTfWex85J2b6I3oivzDqLCBbZxGxeL+v2Mq9jmNvSEHCe1pjmWQ6Z+Q6NYuXWxzpcbxCb35ia3h5ltpPdPPVhDQnB8Sn7Y9prLDr9vDHPz+s8UslESbzWaazHrTXuxlTS9nt2MejHl9PxYz6ezQ2Zc1F8Pljr/83njH5s67HZLdN6ftnlGH2YXm1njs26HRY55KiggvRCeQHAGSJymog0AIQ23v8AAAYXSURBVLgCwMPhhEVJrR7W6ddArMwvQUpV4Y12NE2/4Fbjh5iJdL5L4EqprIh8HsBKAEkAdyiltrh8jTzS04DTy+SdSJxeoVgH9ItnTHufUkwF6o+jlHoEwCMhxUIm+pNx6Qj8PiK50++YKvm9TaKg6vJJzHowmdMbXyvrDka1oVehsARO1cQEHlFGCZx12bFg/A4xEzhVERN4RL1Ke/jlzJOOq3Ek5IVeAj/71IU1joRmk+DPpM5CaR/9myv1ltctwr2fPR/nMiHEQiqZwPJ/ezte96p5tQ6FZhEmcB/SyQQyuZl/38FbTzt+xpdB4XnzyQtqHQLNMkzgPjSkEp5f21ptC+am2XOFaJZgAvfhc+96PX78yFb3CWug/Tvvq3UIRFQlbMT04V/eeToA4OSFpW+aq7VUMuH7fQtEFC8sgfv08g8uRDrBRElEtcME7pPTC7aIiKqBRUgiophiCTzm7vznv63qTzgRUXQwgcfcu9/06lqHQEQ1wioUIqKYYgInIoopJnAiophiAiciiikmcCKimGICJyKKKSZwIqKYYgInIoopUap6P+InIv0A9vr8+gkADoUYThxwnWcHrvPsEGSdX6eUarIOrGoCD0JE2pRSLbWOo5q4zrMD13l2mIl1ZhUKEVFMMYETEcVUnBL40loHUANc59mB6zw7hL7OsakDJyKiYnEqgRMRkQkTOBFRTMUigYvIRSKyXUQ6RGRxreMJg4i8VkRWi8grIrJFRL6oDT9eRB4XkZ3a/4u04SIi/6Vtg5dF5NzaroF/IpIUkRdFZLn2+TQRadXW7U8i0qANb9Q+d2jjm2sZt18islBElonINhHZKiLn1/t+FpEva8f1ZhG5R0Tm1Nt+FpE7RKRPRDabhlW8X0XkKm36nSJyVSUxRD6Bi0gSwBIA/wDgTABXisiZtY0qFFkAX1VKnQngbQA+p63XYgCrlFJnAFilfQYK63+G9u8aALdUP+TQfBHAVtPnnwC4USn1egADAK7Whl8NYEAbfqM2XRzdDOAxpdSbAPxPFNa9bveziJwM4AsAWpRSbwaQBHAF6m8//wbARZZhFe1XETkewPcBnAfgrQC+ryd9T5RSkf4H4HwAK02fvwngm7WOawbW8yEA7wewHcBrtGGvAbBd+/s2AFeapjemi9M/AKdoB/Z7ACwHICg8nZay7m8AKwGcr/2d0qaTWq9Dheu7AMAea9z1vJ8BnAygC8Dx2n5bDuAD9bifATQD2Ox3vwK4EsBtpuFF07n9i3wJHNMHg65bG1Y3tFvGcwC0AjhRKdWjjToI4ETt73rZDjcB+DqAvPb5VQAGlVJZ7bN5vYx11sYPadPHyWkA+gHcqVUb3S4ix6CO97NSaj+AGwDsA9CDwn5rR33vZ12l+zXQ/o5DAq9rIjIfwP0AvqSUGjaPU4VLct308xSRSwD0KaXaax1LFaUAnAvgFqXUOQBGMX1bDaAu9/MiAJeicPE6CcAxKK1qqHvV2K9xSOD7AbzW9PkUbVjsiUgaheR9t1LqAW1wr4i8Rhv/GgB92vB62A4XAPhHEekE8EcUqlFuBrBQRFLaNOb1MtZZG78AwOFqBhyCbgDdSqlW7fMyFBJ6Pe/n9wHYo5TqV0plADyAwr6v5/2sq3S/BtrfcUjgLwA4Q2vBbkChMeThGscUmIgIgF8D2KqU+plp1MMA9Jboq1CoG9eHf1JrzX4bgCHTrVosKKW+qZQ6RSnVjMJ+fFIp9TEAqwFcrk1mXWd9W1yuTR+rkqpS6iCALhF5ozbovQBeQR3vZxSqTt4mIvO041xf57rdzyaV7teVAC4UkUXancuF2jBvat0I4LGh4GIAOwDsAvDtWscT0jq9HYXbq5cBbNT+XYxC3d8qADsBPAHgeG16QaE3zi4Am1Bo4a/5egRY/3cBWK79fTqA5wF0ALgPQKM2fI72uUMbf3qt4/a5rmcDaNP29X8DWFTv+xnADwFsA7AZwO8ANNbbfgZwDwp1/BkU7rSu9rNfAXxaW/cOAJ+qJAY+Sk9EFFNxqEIhIiIbTOBERDHFBE5EFFNM4EREMcUETkQUU0zgREQxxQRORBRT/x9GZCoTWrX40QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([x[\"p\"] for x in dense_logs['rewards']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "1aa6700c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f6c35ebad50>]"
      ]
     },
     "execution_count": 57,
     "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": [
    "window = 30\n",
    "plt.plot(np.convolve([x[\"p\"] for x in dense_logs['rewards']], np.ones(window), 'valid') / window)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "08434fd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "periodic_income = np.diff(np.array(list(zip(*map(lambda x: [v['inventory']['Coin']+v['escrow']['Coin'] for k, v in x.items() if k != 'p'], dense_logs['states'][0::100])))), axis=1).T\n",
    "tax_paid = np.array([[x[str(i)]['tax_paid'] for i in range(4)] for x in filter(lambda x: not not x, dense_logs['PeriodicTax'])])\n",
    "ubi = np.array([[x[str(i)]['lump_sum'] for i in range(4)] for x in filter(lambda x: not not x, dense_logs['PeriodicTax'])])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "6c3bd4f1",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  0.      9.7    39.475  84.2   160.725 204.1   510.3  ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x2880 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = env_obj.env.components[-1].bracket_cutoffs\n",
    "print(x)\n",
    "fig, axes = plt.subplots(10, 3, figsize=(4*3, 4*10))\n",
    "prev_coins = np.array([0, 0, 0, 0])\n",
    "for i, [ax1, ax2, ax3] in enumerate(axes):\n",
    "    coins = np.array(list(zip(*map(lambda x: [v['inventory']['Coin']+v['escrow']['Coin'] for k, v in x.items() if k != 'p'], dense_logs['states'][i*100+1:(i+1)*100]))))\n",
    "    coins = coins - coins[:, 0].reshape(-1, 1)\n",
    "    taxes = list(filter(lambda x: not not x, dense_logs['PeriodicTax']))[i]['schedule']\n",
    "    \n",
    "    cmap = plt.get_cmap(\"jet\", 4)\n",
    "    for j, r in enumerate(coins):\n",
    "        ax1.plot(np.arange(i*100, (i+1)*100-1), r, c=cmap(j), label=j)\n",
    "    ax1.grid(True)\n",
    "    for j in x:\n",
    "        ax1.axhline(y=j, color='green', linestyle='--', lw=0.8)\n",
    "    ax1.set_title('Coins')\n",
    "    ax1.legend()\n",
    "    \n",
    "    ax2.fill_between(x, taxes, step='post', alpha=0.4)\n",
    "    ax2.step(x, taxes, where='post')\n",
    "    ax2.set_title('Taxes')\n",
    "    ax2.set_yticks(np.linspace(0, 1, 6))\n",
    "    ax2.grid(True)\n",
    "    \n",
    "    ax3.bar(np.arange(4), tax_paid[i], color ='orange',\n",
    "            width = 0.5, ec='red', alpha=0.5, lw=2)\n",
    "    ax3.set_title('Taxe paid')\n",
    "    plt.xticks(np.arange(4))\n",
    "    ax3.grid(True, axis='y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0d6653a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 28.26711234, 155.42781324, 296.05531324, 328.05343824,\n",
       "       451.31093824, 531.35843824, 612.09281324, 696.75906324,\n",
       "       791.54843824, 852.19218824])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(list(zip(*map(lambda x: [v['inventory']['Coin']+v['escrow']['Coin'] for k, v in x.items() if k != 'p'], dense_logs['states'][99::100]))))[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ffd07559",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.        ,  57.42781324, 189.05531324, 288.05343824,\n",
       "       380.31093824, 495.35843824, 583.09281324, 660.75906324,\n",
       "       747.54843824, 826.19218824])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(list(zip(*map(lambda x: [v['inventory']['Coin']+v['escrow']['Coin'] for k, v in x.items() if k != 'p'], dense_logs['states'][0::100]))))[0][:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "19151520",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 28.26711234,  98.        , 107.        ,  40.        ,\n",
       "         71.        ,  36.        ,  29.        ,  36.        ,\n",
       "         44.        ,  26.        ],\n",
       "       [476.        , 242.        ,  68.        , 390.        ,\n",
       "        284.        , 166.        , 351.        , 209.        ,\n",
       "        112.        , 208.        ],\n",
       "       [  0.        , 389.        , 320.        , 263.        ,\n",
       "        345.        , 299.        , 171.        , 355.        ,\n",
       "        323.        ,  49.        ],\n",
       "       [ 40.33164062, 111.        ,  25.        ,  67.        ,\n",
       "        100.        ,  59.        ,   9.        ,  40.        ,\n",
       "         41.        ,  37.        ]])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(list(zip(*map(lambda x: [v['inventory']['Coin']+v['escrow']['Coin'] for k, v in x.items() if k != 'p'], dense_logs['states'][99::100])))) - np.array(list(zip(*map(lambda x: [v['inventory']['Coin']+v['escrow']['Coin'] for k, v in x.items() if k != 'p'], dense_logs['states'][0::100]))))[:,:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c0a27d81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 57.42781324, 425.31531324,  40.42781324,  61.42781324],\n",
       "       [131.6275    , 216.7725    , 355.7725    , 135.8275    ],\n",
       "       [ 98.998125  ,  84.758125  , 260.343125  ,  75.900625  ],\n",
       "       [ 92.2575    , 345.8425    , 218.8425    , 103.0575    ],\n",
       "       [115.0475    , 250.2325    , 311.2325    , 123.4875    ],\n",
       "       [ 87.734375  , 125.496875  , 250.876875  ,  95.891875  ],\n",
       "       [ 77.66625   , 293.50875   , 153.50875   ,  75.31625   ],\n",
       "       [ 86.789375  , 159.931875  , 305.931875  ,  87.346875  ],\n",
       "       [ 78.64375   , 100.28375   , 263.62875   ,  77.44375   ],\n",
       "       [ 59.285625  , 133.028125  ,  65.043125  ,  62.643125  ]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "periodic_income"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7860c500",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "380.3109382406423"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(list(zip(*map(lambda x: [v['inventory']['Coin']+v['escrow']['Coin'] for k, v in x.items() if k != 'p'], dense_logs['states']))))[0][400]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6d3ae2d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 57.42781324, 425.31531324,  40.42781324,  61.42781324],\n",
       "       [131.6275    , 216.7725    , 355.7725    , 135.8275    ],\n",
       "       [ 98.998125  ,  84.758125  , 260.343125  ,  75.900625  ],\n",
       "       [ 92.2575    , 345.8425    , 218.8425    , 103.0575    ],\n",
       "       [115.0475    , 250.2325    , 311.2325    , 123.4875    ],\n",
       "       [ 87.734375  , 125.496875  , 250.876875  ,  95.891875  ],\n",
       "       [ 77.66625   , 293.50875   , 153.50875   ,  75.31625   ],\n",
       "       [ 86.789375  , 159.931875  , 305.931875  ,  87.346875  ],\n",
       "       [ 78.64375   , 100.28375   , 263.62875   ,  77.44375   ],\n",
       "       [ 59.285625  , 133.028125  ,  65.043125  ,  62.643125  ]])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "periodic_income"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "811360c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 88.54778132, 213.51703132, 222.56078132,  89.83428132])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "periodic_income.mean(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "abe9b679",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "153.61496882406422"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "periodic_income.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "35096984",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 11, 131,   0,  19],\n",
       "       [ 68, 127, 127,  85],\n",
       "       [ 75,  42, 127,  24],\n",
       "       [ 30, 127, 127,  47],\n",
       "       [ 49, 127, 127,  70],\n",
       "       [ 27, 119, 127,  42],\n",
       "       [ 21, 127, 127,   3],\n",
       "       [ 27, 127, 127,  30],\n",
       "       [ 33,  79, 127,  31],\n",
       "       [ 13, 127,  36,  32]])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tax_paid.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f4ddc829",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Net amount received [ 37.62107009 -40.28296868 -32.03921868  34.70111726]\n"
     ]
    }
   ],
   "source": [
    "print('Net amount received', (ubi - tax_paid).mean(axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "d745589d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "36.16109367593577"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ubi - tax_paid).mean(axis=0)[[0,3]].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "f61aec51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'social/productivity': 6456.260877151826,\n",
       " 'social/equality': 0.5196175777458727,\n",
       " 'social_welfare/coin_eq_times_productivity': 838.6966595702688,\n",
       " 'social_welfare/inv_income_weighted_coin_endow': 940.4312541933429,\n",
       " 'social_welfare/inv_income_weighted_utility': 234.43630242285542,\n",
       " 'endow/0/Coin': 2166.0,\n",
       " 'endow/0/Stone': 12.0,\n",
       " 'endow/0/Wood': 3.0,\n",
       " 'endogenous/0/Labor': 1212.0,\n",
       " 'util/0': 469.7436313673738,\n",
       " 'endow/1/Coin': 692.6026740338757,\n",
       " 'endow/1/Stone': 3.0,\n",
       " 'endow/1/Wood': 10.0,\n",
       " 'endogenous/1/Labor': 549.5,\n",
       " 'util/1': 194.11626778746702,\n",
       " 'endow/2/Coin': 3104.0,\n",
       " 'endow/2/Stone': 2.0,\n",
       " 'endow/2/Wood': 2.0,\n",
       " 'endogenous/2/Labor': 1479.0,\n",
       " 'util/2': 621.0832308565991,\n",
       " 'endow/3/Coin': 493.65820311795045,\n",
       " 'endow/3/Stone': 5.0,\n",
       " 'endow/3/Wood': 0.0,\n",
       " 'endogenous/3/Labor': 574.0,\n",
       " 'util/3': 148.0532000498358,\n",
       " 'endow/p/Coin': 0,\n",
       " 'endow/p/Stone': 0,\n",
       " 'endow/p/Wood': 0,\n",
       " 'util/p': 838.6966595702688,\n",
       " 'labor/weighted_cost': 0.008052546834350466,\n",
       " 'labor/warmup_integrator': 391}"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.scenario_metrics()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "830de408",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Build': 0,\n",
       " 'ContinuousDoubleAuction.Buy_Stone': 0,\n",
       " 'ContinuousDoubleAuction.Sell_Stone': 0,\n",
       " 'ContinuousDoubleAuction.Buy_Wood': 0,\n",
       " 'ContinuousDoubleAuction.Sell_Wood': 0,\n",
       " 'Gather': 0}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.world.agents[0].action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a3c14f48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: ['Build', 1],\n",
       " 2: ['ContinuousDoubleAuction.Buy_Stone', 1],\n",
       " 3: ['ContinuousDoubleAuction.Buy_Stone', 2],\n",
       " 4: ['ContinuousDoubleAuction.Buy_Stone', 3],\n",
       " 5: ['ContinuousDoubleAuction.Buy_Stone', 4],\n",
       " 6: ['ContinuousDoubleAuction.Buy_Stone', 5],\n",
       " 7: ['ContinuousDoubleAuction.Buy_Stone', 6],\n",
       " 8: ['ContinuousDoubleAuction.Buy_Stone', 7],\n",
       " 9: ['ContinuousDoubleAuction.Buy_Stone', 8],\n",
       " 10: ['ContinuousDoubleAuction.Buy_Stone', 9],\n",
       " 11: ['ContinuousDoubleAuction.Buy_Stone', 10],\n",
       " 12: ['ContinuousDoubleAuction.Buy_Stone', 11],\n",
       " 13: ['ContinuousDoubleAuction.Sell_Stone', 1],\n",
       " 14: ['ContinuousDoubleAuction.Sell_Stone', 2],\n",
       " 15: ['ContinuousDoubleAuction.Sell_Stone', 3],\n",
       " 16: ['ContinuousDoubleAuction.Sell_Stone', 4],\n",
       " 17: ['ContinuousDoubleAuction.Sell_Stone', 5],\n",
       " 18: ['ContinuousDoubleAuction.Sell_Stone', 6],\n",
       " 19: ['ContinuousDoubleAuction.Sell_Stone', 7],\n",
       " 20: ['ContinuousDoubleAuction.Sell_Stone', 8],\n",
       " 21: ['ContinuousDoubleAuction.Sell_Stone', 9],\n",
       " 22: ['ContinuousDoubleAuction.Sell_Stone', 10],\n",
       " 23: ['ContinuousDoubleAuction.Sell_Stone', 11],\n",
       " 24: ['ContinuousDoubleAuction.Buy_Wood', 1],\n",
       " 25: ['ContinuousDoubleAuction.Buy_Wood', 2],\n",
       " 26: ['ContinuousDoubleAuction.Buy_Wood', 3],\n",
       " 27: ['ContinuousDoubleAuction.Buy_Wood', 4],\n",
       " 28: ['ContinuousDoubleAuction.Buy_Wood', 5],\n",
       " 29: ['ContinuousDoubleAuction.Buy_Wood', 6],\n",
       " 30: ['ContinuousDoubleAuction.Buy_Wood', 7],\n",
       " 31: ['ContinuousDoubleAuction.Buy_Wood', 8],\n",
       " 32: ['ContinuousDoubleAuction.Buy_Wood', 9],\n",
       " 33: ['ContinuousDoubleAuction.Buy_Wood', 10],\n",
       " 34: ['ContinuousDoubleAuction.Buy_Wood', 11],\n",
       " 35: ['ContinuousDoubleAuction.Sell_Wood', 1],\n",
       " 36: ['ContinuousDoubleAuction.Sell_Wood', 2],\n",
       " 37: ['ContinuousDoubleAuction.Sell_Wood', 3],\n",
       " 38: ['ContinuousDoubleAuction.Sell_Wood', 4],\n",
       " 39: ['ContinuousDoubleAuction.Sell_Wood', 5],\n",
       " 40: ['ContinuousDoubleAuction.Sell_Wood', 6],\n",
       " 41: ['ContinuousDoubleAuction.Sell_Wood', 7],\n",
       " 42: ['ContinuousDoubleAuction.Sell_Wood', 8],\n",
       " 43: ['ContinuousDoubleAuction.Sell_Wood', 9],\n",
       " 44: ['ContinuousDoubleAuction.Sell_Wood', 10],\n",
       " 45: ['ContinuousDoubleAuction.Sell_Wood', 11],\n",
       " 46: ['Gather', 1],\n",
       " 47: ['Gather', 2],\n",
       " 48: ['Gather', 3],\n",
       " 49: ['Gather', 4]}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.world.agents[0].single_action_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "467d18ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['world', 'states', 'actions', 'rewards', 'Build', 'Trade', 'Gather', 'PeriodicTax'])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dense_logs.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1391879c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.  , 0.05, 0.1 , 0.15, 0.2 , 0.25, 0.3 , 0.35, 0.4 , 0.45, 0.5 ,\n",
       "       0.55, 0.6 , 0.65, 0.7 , 0.75, 0.8 , 0.85, 0.9 , 0.95, 1.  ])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dr = np.arange(\n",
    "0,1+0.05, 0.05\n",
    "            )\n",
    "dr[dr <= 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bbfdb66f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "4e9f01ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'PeriodicBracketTax.TaxIndexBracket_000': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_009': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_039': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_084': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_160': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_204': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_510': 0}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.world.planner.action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2857648a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'PeriodicBracketTax.TaxIndexBracket_000': 22,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_009': 22,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_039': 22,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_084': 22,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_160': 22,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_204': 22,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_510': 22}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.world.planner.action_dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "8f6bb376",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Build': 1,\n",
       " 'ContinuousDoubleAuction.Buy_Stone': 11,\n",
       " 'ContinuousDoubleAuction.Sell_Stone': 11,\n",
       " 'ContinuousDoubleAuction.Buy_Wood': 11,\n",
       " 'ContinuousDoubleAuction.Sell_Wood': 11,\n",
       " 'Gather': 4}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.world.agents[0].action_dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "81aafbdc",
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = env_obj.env.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cfde9d8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3.0, 0.001, 0.1518079417266478, 0.1721806210797443]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[env_obj.env.world.agents[i].state['build_skill'] for i in range(4)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "45eef12e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[40.0, 1.0, 13.267112338979295, 16.472372947006132]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[env_obj.env.world.agents[i].state['build_payment'] for i in range(4)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4d7217ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'AI'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.world.agents[0].state['type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0f723408",
   "metadata": {},
   "outputs": [],
   "source": [
    "planner_rews = list(map(lambda x: x['p'], dense_logs['rewards']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "914b9d4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['world', 'states', 'actions', 'rewards', 'Build', 'Trade', 'Gather', 'PeriodicTax'])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dense_logs.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "8c40fd89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'0': {'ContinuousDoubleAuction.Buy_Wood': 1},\n",
       " '1': {},\n",
       " '2': {},\n",
       " '3': {'ContinuousDoubleAuction.Sell_Stone': 11},\n",
       " 'p': {'PeriodicBracketTax.TaxIndexBracket_000': 2,\n",
       "  'PeriodicBracketTax.TaxIndexBracket_009': 3,\n",
       "  'PeriodicBracketTax.TaxIndexBracket_039': 2,\n",
       "  'PeriodicBracketTax.TaxIndexBracket_160': 3,\n",
       "  'PeriodicBracketTax.TaxIndexBracket_204': 1,\n",
       "  'PeriodicBracketTax.TaxIndexBracket_510': 3}}"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dense_logs['actions'][900]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "3108efed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'PeriodicBracketTax.TaxIndexBracket_000': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_009': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_039': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_084': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_160': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_204': 0,\n",
       " 'PeriodicBracketTax.TaxIndexBracket_510': 0}"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.get_agent('p').action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3fdfd24b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'social/productivity': 5381.084999999999,\n",
       " 'social/equality': 0.057153281664697464,\n",
       " 'social_welfare/coin_eq_times_productivity': 76.88666666666963,\n",
       " 'social_welfare/inv_income_weighted_coin_endow': 105.58805748259728,\n",
       " 'social_welfare/inv_income_weighted_utility': -25.08405685574391,\n",
       " 'endow/0/Coin': 5139.124999999999,\n",
       " 'endow/0/Stone': 35.0,\n",
       " 'endow/0/Wood': 25.0,\n",
       " 'endogenous/0/Labor': 2165.25,\n",
       " 'util/0': 479.1760727360579,\n",
       " 'endow/1/Coin': 93.22500000000001,\n",
       " 'endow/1/Stone': 0.0,\n",
       " 'endow/1/Wood': 0.0,\n",
       " 'endogenous/1/Labor': 490.75,\n",
       " 'util/1': -61.69341490559155,\n",
       " 'endow/2/Coin': 78.11000000000001,\n",
       " 'endow/2/Stone': 1.0,\n",
       " 'endow/2/Wood': 1.0,\n",
       " 'endogenous/2/Labor': 277.0,\n",
       " 'util/2': -22.23867131890109,\n",
       " 'endow/3/Coin': 70.62499999999997,\n",
       " 'endow/3/Stone': 0.0,\n",
       " 'endow/3/Wood': 1.0,\n",
       " 'endogenous/3/Labor': 190.5,\n",
       " 'util/3': -6.8522684050719604,\n",
       " 'endow/p/Coin': 0,\n",
       " 'endow/p/Stone': 0,\n",
       " 'endow/p/Wood': 0,\n",
       " 'util/p': 76.88666666666963,\n",
       " 'labor/weighted_cost': 0.21,\n",
       " 'labor/warmup_integrator': 217}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "env_obj.env.scenario_metrics()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a9f6f21",
   "metadata": {},
   "outputs": [],
   "source": [
    "dense_logs['PeriodicTax']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "12637be5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'inventory': {'Coin': 0, 'Stone': 0, 'Wood': 0},\n",
       " 'escrow': {'Coin': 0, 'Stone': 0, 'Wood': 0},\n",
       " 'endogenous': {}}"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dense_logs['states'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "7d28b2b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fa2ea58c2d0>]"
      ]
     },
     "execution_count": 32,
     "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(planner_rews)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "fff42546",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fa2eac998d0>]"
      ]
     },
     "execution_count": 34,
     "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.cumsum(planner_rews))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "46ad0622",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'0': {'loc': [0, 24],\n",
       "  'inventory': {'Coin': 0.0, 'Stone': 0, 'Wood': 0},\n",
       "  'escrow': {'Coin': 0, 'Stone': 0, 'Wood': 0},\n",
       "  'endogenous': {'Labor': 0},\n",
       "  'build_payment': 11.331640623590097,\n",
       "  'build_skill': 0.44778981015931585,\n",
       "  'bonus_gather_prob': 0.09415288361427865},\n",
       " '1': {'loc': [24, 0],\n",
       "  'inventory': {'Coin': 0.0, 'Stone': 0, 'Wood': 0},\n",
       "  'escrow': {'Coin': 0, 'Stone': 0, 'Wood': 0},\n",
       "  'endogenous': {'Labor': 0},\n",
       "  'build_payment': 13.267112338979295,\n",
       "  'build_skill': 0.24016402586070829,\n",
       "  'bonus_gather_prob': 0.4175093544471118},\n",
       " '2': {'loc': [0, 0],\n",
       "  'inventory': {'Coin': 0.0, 'Stone': 0, 'Wood': 0},\n",
       "  'escrow': {'Coin': 0, 'Stone': 0, 'Wood': 0},\n",
       "  'endogenous': {'Labor': 0},\n",
       "  'build_payment': 16.472372947006132,\n",
       "  'build_skill': 0.1127071377001283,\n",
       "  'bonus_gather_prob': 0.23151670592770612},\n",
       " '3': {'loc': [24, 24],\n",
       "  'inventory': {'Coin': 0.0, 'Stone': 0, 'Wood': 0},\n",
       "  'escrow': {'Coin': 0, 'Stone': 0, 'Wood': 0},\n",
       "  'endogenous': {'Labor': 0},\n",
       "  'build_payment': 22.249614304395735,\n",
       "  'build_skill': 0.6298338467385278,\n",
       "  'bonus_gather_prob': 0.08805986332542548},\n",
       " 'p': {'inventory': {'Coin': 0, 'Stone': 0, 'Wood': 0},\n",
       "  'escrow': {'Coin': 0, 'Stone': 0, 'Wood': 0},\n",
       "  'endogenous': {}}}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dense_logs['states'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "4cf224e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'agent': 3, 'resource': 'Wood', 'n': 2, 'loc': [0, 0]},\n",
       " {'agent': 1, 'resource': 'Stone', 'n': 2, 'loc': [24, 0]}]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dense_logs['Gather'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "5f9902af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fdad3167f50>"
      ]
     },
     "execution_count": 55,
     "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": [
    "cmap = plt.get_cmap(\"jet\", len(rews)-1)\n",
    "for i, r in enumerate(rews[:-1]):\n",
    "    r = np.cumsum(r)\n",
    "    plt.plot(r, c=cmap(i), label=i)\n",
    "plt.grid(True)\n",
    "plt.title('Cumulative Rewards')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "339c77d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fdad2f789d0>"
      ]
     },
     "execution_count": 58,
     "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": [
    "cmap = plt.get_cmap(\"jet\", len(rews)-1)\n",
    "for i, r in enumerate(rews[:-1]):\n",
    "    plt.plot(labor[i][1:], r, c=cmap(i), label=i)\n",
    "plt.grid(True)\n",
    "plt.title('Reward vs Labor')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "e0d9cb60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fdad2baf0d0>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xTdjOxYsBmtTV1lDPJCEifwHKgTf9E06d45gKTAWIjY0lISHhoOXR0dHk5eXV2I7P56tVvYZSXFz8i9gbUn5+fqNuz0utqa/QuvrbUvq64YsvCOnQgXWpqZCaeth6jd3fOicJEbkO54T22aqqbnEKcHSlavFuGYcpzwDaiUiQuzdRuf7+tpJFJAiIduv/gqq+ALwAMGzYMB11yF2bNm7cWKsT0g15j+vaCAsL48QTT2y07SUkJHDoe9VStaa+Quvqb3Pua9aOHaRv2kTGli2kffklAy+/vMa+NHZ/65Qk3JFKdwNnqGphpUUfA2+JyBNAV6Av8D0gQF93JFMKzsntK1VVReRL4BKc8xSTgI8qtTUJ+M5d/kWlZGSMMc1a0rffMmvkyJ9fR8TGctpf/uJhRFWrzRDY2cAooKOIJAMP4IxmCgUWuueSl6rqzaq6XkTeATbgHIaapqo+t51bgAU4Q2Bnqep6dxN/AuaIyCPAKmD/Gd2ZwOsikohz4nyiH/prjDGeK8rMZMkjjwAw/pVX6HPeeUTExtIUx+bUmCRU9Yoqig87NEdVHwUeraJ8LjC3ivLtOKOfDi0vBi6tKT5jjGkOflqyhC/vv5+MrVvJ37MHgHP+/ncGT5rkcWTVa3XTchhjTGPLTU7mnQkT8JWWctzFF9O+d2+OHjmSnmee6XVoNbIk0UiSkpK49tpr2bt3LyLC1KlTuf32270OyxjTwMpLSnhjzBgK09O5bskSujexi+VqYkmikQQFBfHPf/6TIUOGkJeXx9ChQxk9ejT9+/eveWVjTLO1Y9Ei0tav55zHH292CQJsgr9G06VLF4YMGQJAZGQkxx13HCkpKTWsZYxp7j7/058ICgvj+Cuv9DqUOml9exI5d0D56ioXtSn3QWkdZmAMGgzRT9W6+s6dO1m1ahUjRow48m0ZY5q0wvR09qxaRdb27ez54Qf2rVvHOY8/TlR8fM0rN0GtL0l4LD8/nwkTJvDUU08RFRXldTjGGD97acQIsrZvByAwJIRB117LiNtu8ziqumt9SaKab/xFDXzFdVlZGRMmTOCqq67i4osvbrDtGGO8seSRR8javp3Bkycz6qGHiOzatcndROhItb4k4RFV5YYbbuC4447jzjvv9DocY4yflBYUkLV9O1nbtvHl/fdz1Ikncv7zzxMYHOx1aH5hSaKRfPPNN7z++uscf/zxDB48GIDHHnuMcePGeRyZMeZIlBUVsX3hQjK3bWPf2rWsfestfCUlAAQEBXHWo4+2mAQBliQazamnnopNPWVM86YVFXxx330sfeIJAEIiI+k2ciRDpkyhfe/edOjThzbt23scpX9ZkjDGmBosuPNOts6dS/bOnfhKSojp14/rv/6aNjExTXK+JX+yJGGMMdWo8Pn4/pln0IoKTr7zTtr37En/Sy9tcneQayiWJIwxphpZ27dTUV7Ob2bN4sTJk70Op9HZFdfGGFONtPXOXQ06DxzocSTesCRhjBfy7oOCGV5HYWohMzERgJhjjvE4Em9YkjCmsRW+BvmPQlnV08OYpqW0oACAUA9vbewlSxKNpLi4mOHDhzNo0CAGDBjAAw884HVIxgtaBrm3QUAcRP7V62hMLRSmpxMaFYUEtM6PSztx3UhCQ0P54osvaNu2LWVlZZx66qmMHTuWk08+2evQTGMq3wKaA9EzIPAor6MxtZCVmEj73r29DsMzrTM1ekBEaNu2LeDM4VRWVtbix1ebKpS7t3aXDt7GYWqtKCuLiE6dvA7DM61uT2L+HXeQurrqY8E+n4/AOkzGddTgwYx5quapwn0+H0OHDiUxMZFp06bZVOGtUcn/gDYQcorXkZhaKisoILJLF6/D8EyNexIiMktE9onIukplHURkoYhsdR/bu+UiIv8SkUQRWSMiQyqtM8mtv1VEJlUqHyoia911/iXu1+vDbaM5CwwMZPXq1SQnJ/P999+zbt26mlcyLUtFOgQPgIB2XkdiaqkwI4OwDq13z682exKvAP8GXqtUdg+wSFWni8g97us/AWOBvu7PCOA5YISIdAAeAIYBCqwUkY9VNcutMwVYBswFxgDzqtlGvVT3jT+vgacK369du3aceeaZzJ8/n4GtdOx1q6QK5dsgoHVcqdtSVJSVERQa6nUYnqlxT0JVlwCZhxSPB151n78KXFip/DV1LAXaiUgX4DxgoapmuolhITDGXRalqkvVmf3utUPaqmobzVJaWhrZ2dkAFBUVsXDhQo499liPozKNqmQe+DZDQOscStlcVfh8BAS1uiPzP6trz2NVdY/7PBWIdZ/HAUmV6iW7ZdWVJ1dRXt02mqU9e/YwadIkfD4fFRUVXHbZZZx//vleh2UaS/kWyL7WeR71H29jMUekorwcaeY3DqqPeqdHVVURadA5sGvahohMBaYCxMbGkpCQcNDy6Oho8vLyatyOz+erVb266NmzJ0uWLDmo7NBtFRcX/yL2hpSfn9+o2/OSl30NDsxkRK+rCQooYlfm5WzfvAPY0aDbtN+t/5SXlZGyZ0+TeT8b+3db1ySxV0S6qOoe95DRPrc8BTi6Ur14tywFGHVIeYJbHl9F/eq28Quq+gLwAsCwYcN01KhRBy3fuHFjrc41NNY5icMJCwvjxBNPbLTtJSQkcOh71VJ52tfs66GoCNrPo1uXMXRrhE3a77buVJWUZctI27jRmdyvuJgevXo1mfezsX+3db1O4mNg/wilScBHlcqvdUc5nQzkuIeMFgDnikh7d5TSucACd1muiJzsjmq69pC2qtqGMc1LxW4IGgxhY7yOxNRAVfnuiSeYecopfHz99Xz92GN0PPZYjr/ySq9D80yNexIiMhtnL6CjiCTjjFKaDrwjIjcAPwGXudXnAuOARKAQmAygqpki8ldguVvvYVXdfzL8dzgjqNrgjGqa55Yfbht1oqpN+uI1u2tdC1a+FYKH1FzPNKqK8nJyU1LI3rmTbQsWsOXTT8neuZPSvDyi4uOZlJBA9NFHExgS4nWonqoxSajqFYdZdHYVdRWYdph2ZgGzqihfAfxiHKiqZlS1jboICwsjIyODmCZ6FylVJSMjg7CwMK9DMQ2hIgsCbAqOpqQwPZ0XTzqJ7J07fy7rMmQIgydPpl2PHvQ65xw6tOKpOCprFeO64uPjSU5OJi0trdp6xcXFnn1Qh4WFER8fX3NF07xoEWguBDT7a0FbjPLiYta/+y7ZO3dy2n330f3002nXowcd+vRpkl8ivdYqkkRwcDA9e/assV5CQkKjnjg2rUD5ZsAHgX29jqTVS1ywgI+vv5683bsBCAwN5bQ//5ngNm08jqxpaxVJwhhPaClkuierA+Oqr2sa3Ib33qMkL49RDz1EdPfudBkyxBJELViSMKahlK2Bir0QfhuEnuV1NK1e6qpVxA0fzhn/939eh9Ks2FThxjSUvD8BQRA+1etIWj1fWRn71q3jqMGDvQ6l2bEkYUxDyL0LSr+A8OudWV+NpzK2bMFXUmJJog4sSRjjbxUFUPAcBA+HyCe8jsbAzyero7s1xvXuLYudkzDG38qWA0UQfisERHgdTaulFRXk7NpF9s6drH3zTQCibJj5EbMkYYy/VaQ6j8EneBtHK/fxjTey+uWXf34dN2IE7Xr08C6gZsqShDH+Vu7ecTCon7dxtEK7vvmGtPXrSd+0idUvv0xk165c+OqrRHfvTvuePZEAO8J+pCxJGONvJZ87d5+T1ns3s8ZSXlJC5ooV/JCYSOrq1SyfMQMACQykfe/eXPbee3ayup4sSRjjT1oBZT9C+GSvI2kVvp4+nbUPPshaQAICiB00iIvfeIOOxx1HQCu+UZA/WZIwxp80DyiGwF5eR9JirZszh+2LFpG7axc7ExIIDA/nlg0biOzalcDgYK/Da3EsSRjjT/tPWgd28TaOFmzutGn4ysroeOyxHHP++YSccQbtunf3OqwWy5KEMf6kxe4TmxOooWhFBYMnT2bs008DNJnbirZUliSM8af9exJ20tpvyouLWf7ss6Rv2kRuUhLF2dkE2b1XGo0lCWP8qehdQOxOdH5S4fOx5NFH+eqRRwjv2JHobt0YcPnlDJ9W5b3NTAOwJGGMP1XscRKEnZOol6+nT2f5jBnk7dmD+nx0GTqUqStWeB1Wq2RJwhh/Kt8OQTXf4MpUrcLnI33TJhbdey8hkZGceu+9RMXH0+tsv9zJ2NSBJQlj/KXsR/BtgrCLvI6kWSjJzSXpu+/ITU4mfeNGNr7/PjlJSajPB8Cl775Ln/PO8zhKY0nCGH8pW+k8WpKolU9vvpl1s2f//LrrsGEcf/XVRMXH03nAALqdeqqH0Zn96pUkROT3wI2AAmuByUAXYA4QA6wErlHVUhEJBV4DhgIZwOWqutNt517gBsAH3KaqC9zyMcDTQCDwkqpOr0+8xjSo4g9BIm3OplpQVXYsWkS/8eM578kniezalaBQGxHWFNV5tisRiQNuA4ap6kCcD/KJwOPAk6raB8jC+fDHfcxyy5906yEi/d31BgBjgGdFJFBEAoEZwFigP3CFW9eYpkfLoDQBQs6GgCivo2nySnJyKNi3j+6nn077nj0tQTRh9Z0SMQhoIyJBQDiwBzgLeM9d/ipwoft8vPsad/nZIiJu+RxVLVHVHUAiMNz9SVTV7apairN3Mr6e8Rrjf1oEWZc6U3IED/Q6mmYhfdMmANr1tJP8TV2dDzepaoqI/APYBRQBn+EcXspW1XK3WjIQ5z6PA5LcdctFJAfnkFQcsLRS05XXSTqkfERVsYjIVGAqQGxsbJ2vwMzPz29VV2+2pv42VF8DAwo4qccNhAXvJT3/FDZtHU55hf+3c6Sa+u82+f33AdhVXs7eesbZ1Pvqb43d3zonCRFpj/PNvieQDbyLc7io0anqC8ALAMOGDdNRo0bVqZ2EhATqum5z1Jr622B9zfs/yN8L0a/QscskTu3r/03URVP/3X7w0ktExsVx3qWX1rutpt5Xf2vs/tbnxPU5wA5VTQMQkQ+AkUA7EQly9ybigRS3fgpwNJDsHp6KxjmBvb98v8rrHK7cGG9oBZRvhIp0KF0E+X+F4F9Bm2u8jqxZyUxMpFN/O8XYHNTnnMQu4GQRCXfPLZwNbAC+BC5x60wCPnKff+y+xl3+haqqWz5RREJFpCfQF/geWA70FZGeIhKCc3L743rEa0z9Fb4A6QMhc5STIADazwaxO54difLiYoLb2CSIzUF9zkksE5H3gB+AcmAVziGf/wFzROQRt2ymu8pM4HURSQQycT70UdX1IvIOToIpB6apqg9ARG4BFuCMnJqlquvrGq8xflHyP+deEdEvQEB7COwOATFeR9XslBcX2yR9zUS9rpNQ1QeABw4p3o4zMunQusVAlQcgVfVR4NEqyucCc+sTozF+oz4o+x6CR0KoTRNRH4VpabSJseTaHNg+sjG1VfY9VOyDkF95HUmzVl5cTFFmJqHR0V6HYmrBpuUwpiYV+aBZUPic8zrEpouoj00ffghA7AkneByJqQ1LEsZUJ+tqKH7zwGvpAMFVXq5jaumnr75CAgLod8EFXodiasGShDHVKX7HSQrhN4K0g+BBIOJ1VM3O2tmz2TZ/PrnJyexcvJjo7t0JadvW67BMLViSMOZwKvKAMgi9wEkSps7mTptGcVYW8aecwnEXXcSQqVO9DsnUkiUJYw4n+3LnMXiQt3G0AGWFhYz80584Z7pN5Nzc2OgmYw6nbAWEnAZh53sdSbOmqvhKSwkMCfE6FFMHliSMqUpFDlSkQYjdGa2+1OcDVQKCg70OxdSBHW4ypiolnzqPdqipzlSVkpwcdn3zDQCRXbp4HJGpC0sSxlSlbK3zGHqut3E0U+vefptPbryR0vx8AAKCg+l++ukeR2XqwpKEMZWpQtEsKH4fCAOx4+h1kfTNN1T4fIz+xz+Iioujy5AhxBxzjNdhmTqwJGFMZcXvQ86NENgXop70OppmK3PrVjr06cOv7rrL61BMPVmSMGa//Ccg/yGQKOi4EgIivY6oWVJVUr7/nmMvusjrUIwf2OgmYwDKVkHeXU6CiPm6QRJEUVEZTz+9lM2b0/3edlOStX07RZmZxI2w6UtaAksSxgDk3gkEQcxiCD6+QTbx0ks/cDLAfY8AACAASURBVMcdC1ixYneDtN9UpG/cCEDnAQM8jsT4gyUJY1ShfB20uRqCejXIJlJT87nttvl06hTOeef1aZBtNBWpq1cD0HngQI8jMf5gScIYzXHuWR3UcN98d+3KAeCll35Dx47hDbYdr1WUl7Ph3XeJ7t6d0Kgor8MxfmAnro0pdw6PENQwQzTz8kq44475AHTr1vJutKOqvHvppSR9+y35qamgyq/++EevwzJ+YknCGC1yHqVdgzS/ZMlPfPddMmee2YOBAzs3yDYai6+sjPzUVDK2bGHzRx+RvXMn2Tt3sm/tWiK7duX0++4j6uijGXBplXcqNs2QJQljtNR5bKAL57ZtywLg9dcvIiio+R7h/fzee/nm8cedcziABATQeeBAouLj6TV6NGc+/DAhEREeR2n8rV5JQkTaAS8BAwEFrgc2A28DPYCdwGWqmiUiAjwNjAMKgetU9Qe3nUnAfW6zj6jqq275UOAVoA0wF7hd1f0LNcZf1DlfgLRpkOazspw9ldjY5nWTneKcHJbPmEHOrl3kJiWxde5cOvTty6/++Eciu3aly5AhNh9TK1DfPYmngfmqeomIhADhwJ+BRao6XUTuAe4B/gSMBfq6PyOA54ARItIBeAAYhpNoVorIx6qa5daZAizDSRJjgHn1jNmYg/m2O49Bff3e9Lp1+3jwwcVER4c2u72Ije+/zxd/+QsBwcF0Ou44Blx+OeNmzCA8Jsbr0EwjqnOSEJFo4HTgOgBVLQVKRWQ8MMqt9iqQgJMkxgOvuXsCS0WknYh0cesuVNVMt92FwBgRSQCiVHWpW/4acCGWJIw/aQnkP4bzr+C/PQlV5e67F/KPf3wHwMyZv/Fb240lNyUFgHtzcwkKC/M4GuOV+uxJ9ATSgJdFZBCwErgdiFXVPW6dVCDWfR4HJFVaP9ktq648uYryXxCRqcBUgNjYWBISEurUofz8/Dqv2xy1pv4erq/dOrxBr0757MkZw+bNi/22vUcf3cjnn+8D4PnnhxATs4+EhH1+a78m/vjdblu/noDQUL5eutQ/QTWQ1vR3DI3f3/okiSBgCHCrqi4TkadxDi39TFVVRBr8HIKqvgC8ADBs2DAdNWpUndpJSEigrus2R62pv1X2Vcth7wUQcAxd+n1Kl2MD/bKtL77YweefL2bcuL7MmTOByMhQv7R7JPzxu81++WXSw8Ob/N9Ia/o7hsbvb30OkiYDyaq6zH39Hk7S2OseRsJ93P/1KQU4utL68W5ZdeXxVZQb4x8l80Dzoe3dIP5JEP/970bOPvs1wsKCuP/+0z1JEP6yc/FiOvXv73UYxmN1ThKqmgokiUg/t+hsYAPwMTDJLZsEfOQ+/xi4VhwnAznuYakFwLki0l5E2gPnAgvcZbkicrI7MuraSm0ZU3+l7mGU0F/7pbm0tAIuvvgdAL76ajInnxxfwxpNW3FWFl2GDPE6DOOx+o5uuhV40x3ZtB2YjJN43hGRG4CfgMvcunNxhr8m4gyBnQygqpki8ldguVvv4f0nsYHfcWAI7DzspLXxp6JXIXgoBB5V76ZSU/MZO/ZNAJ577tcMG9a13m02Nl9ZGbuXLydv9252r1xJSW4u4Z06eR2W8Vi9koSqrsYZunqos6uoq8C0w7QzC5hVRfkKnGswjPE/zYGQy2quVwtTpnzC6tWpPPPMWG6+uap/iabJV1ZGXkoKeXv2sPSJJ9jw3ns/L2vfqxcn/fa3HkZnmgK74tq0TuU7nPMRUr+5lIqLy7n44reZNy+RgQM7c8stw/0UYMNTVV4cNoy9a9b8XBbTrx+XvP02kV26EN6xIxLQvK7tMP5nScK0bKrg20VEaCIUpULJZ1CRBr6dzvKQk+vV/KOPLmHevER+//uTueOO+rXV2Iqzsti7Zg09Ro3iV3ffTdujjiL2+OMJCLKPBXOA/TWYli3nWih6g5N6ANkAwRA0EAI6QZtrIHhknZsuLi7nX//6nqFDu/DEE+f5KeCGVVZUxI5Fi8jbvZs1r78OwPBbb6Xv2LEeR2aaKksSpuUqXQZFb4BEsi75Dww8fiQE9YdA/8w3tGNHFrm5Jc3mEFPK8uV8OnXqzzcFAujUvz99f+2f0V2mZbIkYVqmksWQOcp53uEz0jcVQ+govzVfVubj8sudk7zN4SZC5SUlvHHuuQQEB3PxW2/R/bTTiOjcmcCQhpn51rQcliRMy+NLhpypQAB02uRO3Jfg1028+eZa1q7dx1ln9eTMM3v4te2GkPTttxRnZzPxo4/o95vmN4+U8Y4lCdPy5D8Ovi3Q7p0GmdkV4O231xMWFsSCBVc3+dldy4uLWTVzJgFBQfQ480yvwzHNjCUJ0/KULIDQsdCmYe6OtmdPHvPnJ3LFFQObfILYvWIFcy68kLyUFIZMmUJoZKTXIZlmxpKEaXkq9kDQ+Q3SdFJSDkOHvgDAxIlN9zpPVWX9O+/w6c03U15UxGUffMCxF17odVimGbIkYVoGLYGKHCj51LlILuDomtepgxkzlpOWVsjChddwzjm9GmQbdbVt4UKSvvmG/NRUtiQkkLd5M7EnnMDFb71F5wEDvA7PNFOWJEzzl/8k5N15cFn4tX7fTG5uCc8/v5JBg2I5++yefm+/PlSVdyZMoDQvz7lSOjKSc//5T4bfcouNYDL1YknCNG9aAfnu7dGj/u1MsxF8HAT4/xabK1fuJju7mNmzJ+BMTNx0lBUWUpqXx5l//Sun33cfCQkJnNKK7rFgGo4lCdO8Fb0OWghtH4aIKueP9Ivi4nKuvvq/AHTuHNFg26mrn5YsASAqvnlPT26aHksSpvmqKICcmwCBsIa9anjWrFXs3p3H+ecfw/HHd27QbdVW9s6dbPn0U+ccxCefANgQV+N3liRM8+X7CSiB6FcguOFujpOXV8I993xO9+7RfPLJFQ22nSOhqrwxZgwZmzcjAQFEdO7MoEmTiO7WzevQTAtjScI0XxV7ncfAX45kKqhwHiPqeRlDXl4JvXr9i7y8Um66aWj9GvOjnxYvJmPzZk77y18Y9dBDBAT65/arxhzKkoRpvkoXOY9B/X6xaOQO6BIE87rXbxOnnfYy6emFPPzwKO677/T6NVZPmz78kK//9jfy9+4l56efCI6I4Fd//KMlCNOgLEmY5qtoDgQNgoCDbxW6uQR+LIHx9bi4ODOziEcfXcKPP+7loYdGcf/9Z9Qz2Ppb//bbpG3YwLEXXkjEJZfQ8+yzCYuu302TjKmJJQnTPKmCLwkiboNKw1ELKuDhNOf5JVF1b/6qqz5g/vxETjutW5M4zJS2YQNb/vc/Yk84gYvc+0AY0xgsSZjmSXOAUgiIPaj4mUx4Kxduag8DQ+vWdEZGIfPnJzJp0iBeecX7qSzy9+7l+SFDUJ+PMx580OtwTCtT79nJRCRQRFaJyKfu654iskxEEkXkbREJcctD3deJ7vIeldq41y3fLCLnVSof45Ylisg99Y3VtCAV2c5jQEfnpcJVyfBQGvQJgf90OWgHo9YKCkqZOPF9AMaO7eOvaOtl+8KF+EpKuHLuXHqPHu11OKaV8ccUlrcDGyu9fhx4UlX7AFnADW75DUCWW/6kWw8R6Q9MBAYAY4Bn3cQTCMwAxgL9gSvcusY4F9ABSBiqcN1uZw8iVGBeHUaBlpX5mDNnHT16PM3nn2/n+usHM378sf6NuY7WzZ5NUFgYPc7w/ryIaX3qlSREJB74NfCS+1qAs4D33CqvAvv318e7r3GXn+3WHw/MUdUSVd0BJALD3Z9EVd2uqqXAHLeuMVD6pfMYGM8tqfB6DlwSCVn9nD2JI3XaaS9zxRXvExoayN//fg4vvfQbwsK8Pxq7b/16tn/+OQMuv9zmYDKeqO9/wVPA3cD+cSQxQLaqlruvk4E493kckASgquUikuPWjwOWVmqz8jpJh5SPqCoIEZkKTAWIjY0lISGhTp3Jz8+v87rNUXPu78C4t2gfHsbrywJ5NgYGlOZw3fY1LN7mq7J+dX0tLa1g2bIURo/uzD33HEtAQBmLFy9uwOhrb9uzz+IrLSV09Ogj+l0159/tkWpNfYXG72+dk4SInA/sU9WVIjLKfyEdOVV9AXgBYNiwYTqqjhObJSQkUNd1m6Nm3d99eyF4HJ/2OAXy4MP+0fQJOe2w1avr6zXXOHMyXXbZCM46q+Gu3K6LPU88QVR8PGOvuuqI1mvWv9sj1Jr6Co3f3/ocbhoJ/EZEduIcCjoLeBpoJyL7k088kOI+TwGOBnCXRwMZlcsPWedw5aa1K10Kvm34gs/gwzyYGFW3Q0wA6emFfPLJZgYNiuX660/0b5x+kDh/PvGnnOJ1GKYVq3OSUNV7VTVeVXvgnHj+QlWvAr4ELnGrTQI+cp9/7L7GXf6FqqpbPtEd/dQT6At8DywH+rqjpULcbXxc13hNC5LzOwCWlI3AB5zbtm7NqCqjRr1CTk4JN9xwIgEBTWv674rycirKyog94QSvQzGtWEOcmfsTMEdEHgFWATPd8pnA6yKSCGTifOijqutF5B1gA1AOTFNVH4CI3AIsAAKBWaq6vgHiNc2JFkP5jxQEj2P0nhHEBMJZ4UfWhM9XQU5OCd99l8T69Wk88MAZ3HLL8IaJtx72rFoFQFCbNh5HYlozvyQJVU0AEtzn23FGJh1apxio8s70qvoo8GgV5XOBuf6I0bQQeX8BKvi8bDQ+YFF36F6LQ005OWXcfvs8Zs9eR3p6IapOeUREMJMmDWpyNxEqSEvj7YsuIrxTJ/pPmOB1OKYV836MnzG15dsFBU+QJ724NetihoTV/qrqu+9ew5Yt+Zx6ajduvrkHMTFtiIkJ58wzexAXV4/5O/zIV1ZG1vbtFOzbR8IDD5CXksIVn3xCux49vA7NtGKWJEzz4dsNwDv6NHu0G9t6QmAtdgDy8krYujWfW245iWeeGdfAQdZNWVERzw8eTMaWLT+X9TjzTI45/3wPozLGkoRpTko+A2C9rxfdgiG4lkeIfvhhD6owenTvBgyu7sqKivh6+nQytmzhpGnTnFleO3cm5phjvA7NGEsSphkp+RiC+rOk6Di6HMFfbkZGEQDduzedabVTV6/mg6uvJuennyjNzweg++mnM+bpp+3+EKZJsSRhmgdfKpStojziz6xKE/4YU/MqxcXlPPfccl544QcAoqLqOC1sA1jxn/+Qtn49I+64g4hOnYg6+mgGXHaZJQjT5FiSMM1CWfkugqngtxknUwGMjqi+fmJiJied9CLZ2cUEBwdw99396NGjXaPEWpOdixez8vnn6TtuHGOefNLrcIypliUJ0+SVVMDf00u5PwCyfaG83BXOruECusce+4rs7GJeeOF8Jk8+ka+/XuLpMNeU5cvZ+r//UZiezs6EBCQggPOff96zeIypLUsSpsmbmZlOTOlbEAZvHx1CQDVHjVSV3/9+AS+/vJqxY/swZYo3d5VTVX548UX2rVtHfmoqG959F4Cw9u2J6NyZMx58kKj4eE9iM+ZIWJIwTU6FQm4FZJUXkJn7HFPK7iU4rJyK4OEEBB1X7bozZizn6aeXMWRIF15//aJGivhgWlHBmjfe4NObbgKgQ58+HD1yJOc9+SRxJ53kSUzG1JUlCdOkPJ0B9+yDYoVHwh7jL20eY4VvKBmht3Fex2urXffjjzdz663z6NGjHd9+ez2hoQ3/57113jxSV6+mMD2djE2b2L1iBYUZGajPR1R8PLds2UKwTathmjFLEqZJUIW5+XDvPugSBL9vX8hNZTPICRhC/7gVhNdiKspPPtkM0GgJoiQvj7fGORfnBUdEEN6xI73PPZfo7t0J79iRnmedZQnCNHuWJIznSirgihT4b56TIOZ2g2PlB8jIIST6gVrNVbx9exYvvbSKk0+Op0uXyJpX8IMfX3sNgAlz5jDw8ssbZZvGNDZLEsZziwqcBDE0DL7tCSEC5Mx2Fgb1q3H91NR8Bg36D8HBAUyffnbDButK27CBebfeSnT37gy4tMp5K41pESxJGM+tLnYe53ZzE4RvHxQ+C22urTFJpKbmc/PNn5KfX8rSpTcwYkTjjBhaO3s2qDLxww+RgHrdKt6YJs2ShPHUnjJ4Pw9iA6Hz/r/GYud2orSp/padd921gGee+Z6ysgqmTBnSaAmiND+fH158kQ59+3LU4MGNsk1jvGJJwngmzwcnbId0HzzWudKC8jXOY1D1H8AzZixn5MhuPP/8+RxzTC3m6fCT3StXUrB3L6fff3+jbdMYr1iSMJ5ZUugkiDfi4KrKc+/5dgChEHD4D/6SknJKSnyMGtW9URMEwL61awE4dvz4Rt2uMV6wg6nGEz8Ww/+lOc9//YspNiog+ASQw092N3Omc2vPfv06NkyA1ShIcwJve9RRjb5tYxqb7UmYRuVTuCwZPsiDtgHwSCdoVzkXVORB6XcQVvW39MTETP71r2U888z3AIwYEdcIUR9QVlTE6pdfJqJzZwKC7N/HtHz2V24a1QtZToKYEAkzukBs5b/Asg2QMxU0F8KnHbReSUk5c+as49Zb51FUVM7FFx/HE0+cS/fujTezq6ryyhlnkJuUxLlPPNFo2zXGS3U+3CQiR4vIlyKyQUTWi8jtbnkHEVkoIlvdx/ZuuYjIv0QkUUTWiMiQSm1NcutvFZFJlcqHishad51/SVO7W705Ivfvg9+lQlwQvBJXKUFoGWRPhfQBUPYNRPwRQkb8vN6LL64kLu4JrrvuI+Lioti4cRrvv39ZoyYIgIwtW9i9fDnDb7uNk++4o1G3bYxX6rMnUQ7cpao/iEgksFJEFgLXAYtUdbqI3APcA/wJGAv0dX9GAM8BI0SkA/AAMAxQt52PVTXLrTMFWAbMBcYA8+oRs2kkO0thWZEzUV9yGbybCxtLYWQb+Kw7B0+zkfsHKHoR2lwDbR+CoJ4/L1JVbrttPmFhQcybdxXnntubgABvviuUFRQAzh3k7PuKaS3qnCRUdQ+wx32eJyIbgThgPDDKrfYqkICTJMYDr6mqAktFpJ2IdHHrLlTVTAA30YwRkQQgSlWXuuWvARdiSaLJeykL7kiFAj1QFi5wVwd4sDOESxGULIGKbCh6A0o+hZCzIfoVkAPZo7TUx5IlP1FcXM5DD41izJg+jd6XnF272JmQQGFGBtvmzwfgqEGDGj0OY7zil3MSItIDOBHnG3+sm0AAUoFY93kckFRptWS3rLry5CrKq9r+VGAqQGxsLAkJCXXqR35+fp3XbY4aor9FEsgdMadQKgHMyFpNp4oSwrWcNuojYC+s2AT9jnqcLtHzf15HNYCv1/8eX8USAMrLK/jb3zbx1VfplJUpwcFChw5Z9Yq1rn394be/JW/TJudFQAAxp57Kj0lJSHJy9St6rDX9LbemvkLj97feSUJE2gLvA3eoam7l3XBVVRHRw67sJ6r6AvACwLBhw3TUqFF1aichIYG6rtsc+bu/c3KcifoAXu8KVw8YcmBh2Voo+84ZvVS4E7QjdFgMAVFIQAyndT0wW+r06V/zxRdpXHjhsVxxxUBOPbUbXbvWb9K+uvQ1eelSFm/axDEXXMBFr71GaFRUs5mCozX9LbemvkLj97deSUJEgnESxJuq+oFbvFdEuqjqHvdw0j63PAU4utLq8W5ZCgcOT+0vT3DL46uob5qgdcXw/N4vuTtsNZdEFnBS+TxIywHNg4p8cI4mHtDmagjuf1DRjz+mct11H7F6dSq9erXn/fcv8+z8Q1FmJq+PHk1gSAi/mTmTsHZN4/7YxjS2OicJd6TRTGCjqlYeD/gxMAmY7j5+VKn8FhGZg3PiOsdNJAuAx/aPggLOBe5V1UwRyRWRk3EOY10LPFPXeE3D2FYKn+TBqxlbWdH2HAKlwhnSgEDQQAg5E6QtBBwFYRdAYE+QiF9cKPfZZ9uYOPE9srOLuffeU/nDH37V6AkiffNmkr79lqKMDJY+9RSl+fmMefppIjp1atQ4jGlK6rMnMRK4BlgrIqvdsj/jJId3ROQG4CfgMnfZXGAckAgUApMB3GTwV2C5W+/h/Sexgd8BrwBtcE5Y20lrD2X5nJsCLSlwTkqnlkOpQoyk80HbW50EEbMMgk8ECa51u0lJOUyd+glZWcV8/fVkRo7s1oC9qFqFz8fro0eTm3Tg9NiJN9zA8FtvbfRYjGlK6jO66WvgcF/1fjGpvzuqaVoVdVHVWcCsKspXAAPrGqPxj7Ry+Ms+eDXHSQrnRjg3B4oIUE6RD5mo1xFELoTfBsEnQS2Hh5aV+bjkknf5+GPnjnJ/+MMpjZogti9axPzbbqMgLY1Cd6qN859/noETJxISGWnDXI3Brrg2rlKFD3PhswJILIU95VBQAfkVkFPhXHV5aRT8vgOMCAcKnoeCx8C3CwJ7QLtFEDKsVtvatCmd11//keeeW0FWVjGnntqNJ588j6FDuzRY/yrKysjbs4dF995L6urVFGVm/rzXMPSmm2gTE0PHfv044eqrm83JaWMagyUJQ5lCv0TYWea8Hh4GJ4ZBRIDz0ynQmYRvyP4BSEXvQe7NQAhEzYCwSyCw8+GaP8irr65m6tRPKS31cc45vbj22hO45hr/XndQWlBA5tatFGVmsnfNGhY//DDFWVl85S7veNxx9Dr7bMI6dGDAZZcRP2JEte0Z05pZkjDsKnMSxI3t4J+xEHW4yVe10Jk+o/hN53XHZRBcu5vubNmSwaWXvsuaNXuJigrlxx9v5thj6z6Da0V5OXtWraIwPZ2cXbtY99ZbFGVlUZyVRf7evVSUlf1cNzg8nO6TJjFg+HCiu3en77hxdijJmFqyJNHKZftgym7n+e0dqkkQAEXvOwmizTUQfkutEwTAo49+xZo1e7nppqH87W9n0759m5pXqmTvmjV8+49/sPPLLynOzqY0P/8XdXqNHk3XoUMJ69CBuJNOou1RRxHWvj0xffvyzfffc1IrGktvjL9YkmilFuTDX6MH8o1zzpg/xMDAsGpWqCiAvD+ARELkdAjsWqvtFBWV8fe/f8Nrr/3IhRcey3/+c36t1lNV3pkwgaRvvqEkN5fy4mICgoPpP2ECbbt0ITQ6mg69e9OhTx/C2rVzEoJdy2CM31mSaAXK1TkJvaoYZudAQiFsKQVCOzK5HYxrCxfVdEFz+Wqo2AfRL9Q6QQBcffV/+eCDjZxwQizPPjuu1uvt+uorNv33vxxzwQV0PPZYQqOiGHD55cT07VvrNowx9WdJooUqqXCGrD6UBrvLD5SHiDOEdUo76LP+Gy7sP7J2DRY8C4RA2KW1juGDDzbywQcbueaaE3j11Qt/cR5AKypY9/bbZG7dSkluLjm7dpG9YwfFOTlkbt1KSGQkl8yZQ3B4eK23aYzxL0sSLdSde+HZLIgKgPs7Ond/ax8I57eFTu5vPUHLqm+ksuLZEDoOAmp3SGfNmr1cd92HDB3ahb/d1Yetc+dSmp9PYVoaGVu3UpqXR/qmTSR/9x3gnFwOa9+e2OOPp0OfPvQ480z6T5hgCcIYj1mSaIGWFDgJYkgYLO0JwX4ZyKMQXLvrIArT05nxu7/TJy+R2/vG8NLgmw5aHhwRQZv27QmJjOT4K6/kN7NmERQa6o8gjTF+ZkmiBSlV+K4QLkhy7/7WtZ4JwrcXNBsqMqutlrNrFytffJGd63awNymNojVf07WskPHA9jlw1ODBjJsxg7B27QiJjCQqLs4uWDOmmbAk0QK8nO3cO3pVMZQoBAOLusPx1Y1WqknBM5B728FlQQfP2rpv/Xp+ePFFlj3zb6jwkU8EpYRQHhxD8ZBrufWJmzlmYDxh7doREFjd2FpjTFNlSaKZ21sON+12rm+4pb0zZcbINtC19vPr/VJFnpMgAuIh8m8Q0NZ57k67UV5czDsTJrB17lwAkgJ6sCBiAvc/cQXnnNOLnj3b2cVqxrQQliSaMVW4JgWCBOZ2g+FHdn1apYZKoegV8KVARQYUveaURz8DYRceVPWHmTP55MYbAQjr0IGw22fx4AOrmTNzApdfbnMxGtPSWJJohsoV8irg0zxYWOBMulfnBAGQcwul6S+S/AOU5EdQWhhJSemvKSnZSEnOUvasXElucjIlubnk7XYuz/465gq+zOiD74HV9O7dnnPO6eWfzhljmhRLEs1IWjlcngxfFh4oE+DWDvVotPQ7yrNf5OWL25K6Nh8ocH/mAHOQoCDadO5C9HEnsEuLWcPR7Go3nBNGn8H/HdeR/v07MW5cX8LD63N8yxjTVFmSaMJ8Cj8Ww9eFsLEUXsuGQoXftodjQqBtgDNba8+QKlZWhfJV7gilfOc2oj/fSjQLfD9xfFwSmraMd6ZA6tp8xs2YQczgYcx+fztzF6Wwcl0OJeUBsFvAnd9pypQhvPrIWXTuHNGo74UxxhuWJJoQVfhfPiwqgCWFsL7EGa0EEO0mhMnt4Ib2Va1cDgX/hPKNUJEN5WvBt73K7eSnBfPGlUJ2UjkluU5Zds+zeHheez6dduDmf/fcczp9+8YQERFMeHgwPXq04/jjY/3ca2NMU2ZJognwKTySDi9mQUo5hAv0CnGm7h4SBoPd+zscNGBIy6BkIVSkOdcyFL0HZV9DQEcqOIri0s7sSLmCzRtiSdlRyO5lGyjatgNffhEhealEFSX///buP7aqswzg+Pfpj3tv772Ftqz0FooUAnGrGMaPUYgSC8iGy+L+IXFsUSIs/KHTaUzMiH8s/qVG4mTJRoZzaoiB6bZshKBEcTUSDWM4fg2otOscRaCFltJfty308Y/zll663WT9eW7veT7JSe/7nrft+9znJs8957z3Hv5HORdYiMaKuZKzmoJLN1m9+jNs2bKExx//PKGQLVs1JuisSPjgtsI/uuGf3XCyF97pGbrhz64EPFnsrVgCQPvoab1I24fHSV7+Fckb7fS0dZBsayZ5o5Wedujrgr7uXD5oTHDy5AwGenvI5yZl7CBCLwARt3UVJBgIxWmb+wiyeiM/n4tF7QAAB0lJREFU2bqOFStm25JVY8wnsiIxwfZ3wM+vQdJ9E2uXejf5GXRvRwurTx5he28ri263crvjFG+dbqD9YjN9HRfpbO6jqyX9379NDn0Sol/zuS39VBR1EiqNEokXM73ifuasrCYxbxbTEjOZt3YteZGhT9jV1tZSXV0xgdEbY6a6jC8SIrIB2AnkAi+r6k99ntKn0tXbz47Gdl6su0JZ3Skq608x/8ZVQh3txHqvE+9tIdzawvXz1wC47DaA6Awouw8KZsGMBbm05CzhVrSI5q5i9rwZJ0mEmXMTfOmhRRQUxogXhllWVUpNTSWlpXZB2RgzfjK6SIhILvACsB5oAo6JyH5VPevvzDzdPUneq2vk+oU6OhvO0N1wltbaIySbrqLJPgC+5cbm5OUQLokSLhwgWthNfgTyymD28ggli2IUVBbSnhT2HljGkeMJuhvy6e7Jp/1mhFAoRCIRJxrNp7w6RFVVKTt3bqCw0L4UzxgzsTK6SAArgHpV/QBARPYBjwLjXiRe/M56kn/6O/9WYMC7M1rqT1TRgaF9/Z3KreTdfyNcCInPwax1EJnutaPFMPM+uGfBALn5nVxvLWDP69X87g9LudI4i1jTNOKnQ8RiIeLxEEVFEb72RAmxWIhoNJ/Fi8t44IHZ9jkEY4wvRFX9nkNaIrIR2KCqT7r214FqVX1q2LhtwDaAsrKyZfv27Rvx/zpx8Hk48S9EBBWBHPGWEw22JWeonSOAQDiPgrnT0OIiktMSdEkJvb2F9PdEiXYp+flhwpGI28JEIgVECmLE43lEIjm+Xyzu7OwkHo/7OofJEqRYIVjxBilWmLh416xZc1xVP3Y/gEw/kvhUVHU3sBtg+fLlWjOKG97X1NRQW1vLaH53qgpSvEGKFYIVb5BihcmPN9O/1P8SMCelXeH6jDHGTIJMLxLHgIUiMk9EQsBjwH6f52SMMYGR0aebVPWWiDwFHMJbAvuKqr7v87SMMSYwMrpIAKjqQeCg3/MwxpggyvTTTcYYY3xkRcIYY0xaViSMMcakZUXCGGNMWhn9ievREJEW4L+j/PV7gGvjOJ1MF6R4gxQrBCveIMUKExfvXFUtHd6ZdUViLETk3U/6WHq2ClK8QYoVghVvkGKFyY/XTjcZY4xJy4qEMcaYtKxI3G233xOYZEGKN0ixQrDiDVKsMMnx2jUJY4wxadmRhDHGmLSsSBhjjEnLigQgIhtEpE5E6kXkGb/nMx5EZI6IvC0iZ0XkfRF52vWXiMhfROSC+1ns+kVEnnfPwSkRWepvBCMnIrki8p6IHHDteSJy1MX0qvu6eUQk7Nr1bn+ln/MeDREpEpHXROS8iJwTkVVZntvvu9fxGRHZKyKRbMqviLwiIs0icialb8T5FJHNbvwFEdk8HnMLfJEQkVzgBeArQBWwSUSq/J3VuLgF/EBVq4CVwLddXM8Ah1V1IXDYtcGLf6HbtgG7Jn/KY/Y0cC6l/TPgOVVdALQBW13/VqDN9T/nxk01O4E/q+q9wGK8uLMytyIyG/gusFxVF+HdNuAxsiu/vwU2DOsbUT5FpAR4FqgGVgDPDhaWMVHVQG/AKuBQSns7sN3veU1AnG8B64E6oNz1lQN17vFLwKaU8XfGTYUN766Fh4G1wAFA8D6Vmjc8z3j3J1nlHue5ceJ3DCOIdTrQOHzOWZzb2cBFoMTl6wDwULblF6gEzow2n8Am4KWU/rvGjXYL/JEEQy/AQU2uL2u4w+0lwFGgTFUvu11XgDL3eKo/D78EfggMuPYM4Iaq3nLt1HjuxOr2t7vxU8U8oAX4jTu99rKIxMjS3KrqJWAH8BFwGS9fx8ne/A4aaT4nJM9WJLKciMSB14HvqerN1H3qvd2Y8mugReQRoFlVj/s9l0mSBywFdqnqEqCLoVMRQPbkFsCdMnkUrzjOAmJ8/NRMVvMzn1Yk4BIwJ6Vd4fqmPBHJxysQv1fVN1z3VREpd/vLgWbXP5Wfhy8AXxWRD4F9eKecdgJFIjJ498XUeO7E6vZPB65P5oTHqAloUtWjrv0aXtHIxtwCfBloVNUWVe0H3sDLebbmd9BI8zkhebYiAceAhW6lRAjvgth+n+c0ZiIiwK+Bc6r6i5Rd+4HBVQ+b8a5VDPZ/w62cWAm0pxzqZjRV3a6qFapaiZe/v6nqE8DbwEY3bHisg8/BRjd+yrzrVtUrwEUR+azrWgecJQtz63wErBSRqHtdD8ablflNMdJ8HgIeFJFid/T1oOsbG78v1mTCBjwM/AdoAH7k93zGKaYv4h2engJOuO1hvHOzh4ELwF+BEjde8FZ5NQCn8VaS+B7HKOKuAQ64x/OBd4B64I9A2PVHXLve7Z/v97xHEef9wLsuv28CxdmcW+DHwHngDLAHCGdTfoG9eNdb+vGOFLeOJp/AFhd3PfDN8ZibfS2HMcaYtOx0kzHGmLSsSBhjjEnLioQxxpi0rEgYY4xJy4qEMcaYtKxIGGOMScuKhDHGmLT+DyRopUpfdcvfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = plt.get_cmap(\"jet\", len(rews)-1)\n",
    "for i, r in enumerate(rews[:-1]):\n",
    "    r = np.cumsum(r)\n",
    "    plt.plot(labor[i][1:], r, c=cmap(i), label=i)\n",
    "plt.grid(True)\n",
    "plt.title('Cumulative Reward vs Labor')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf9444a6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}