{
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   "cell_type": "markdown",
   "id": "d0c9c1d0-ee11-48e5-9415-90d10b24d1fb",
   "metadata": {},
   "source": [
    "# Simulations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92423af7-7d23-47e7-96d0-abb6909fed85",
   "metadata": {},
   "source": [
    "A significant part of the [Stochastic Matching package](https://balouf.github.io/stochastic_matching/index.html) is devoted to simulations, allowing to check the practical value of theoretical results and to explore new conjectures."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1674e3bd-6197-4fd9-b2fa-94760b617c55",
   "metadata": {},
   "source": [
    "First, some settings that should apply to all our simulations.\n",
    "\n",
    ":::note\n",
    "The *refresh* parameter below tells if the simulation should run if a simulation file already exists.\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "386c92be-468f-45c8-aa13-d5208c237ae1",
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    "execution": {
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   "source": [
    "refresh = False\n",
    "n_steps = 10**10\n",
    "common = {\n",
    "        \"n_steps\": n_steps,\n",
    "        \"max_queue\": 50000,\n",
    "        \"seed\": 42,\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97a7eb06-c8f9-4204-80bb-3acde7ca1400",
   "metadata": {},
   "source": [
    "## Approaching vertices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd1f04b2-5f54-4348-9a14-a9adadde4b01",
   "metadata": {},
   "source": [
    "### Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22c414d8-68b1-4f05-9120-57f00bb98b01",
   "metadata": {},
   "source": [
    "First, we define the set of simulations we want to run. Let's make a small mixer of common and specific parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9679b7e7-c4d6-4819-8c58-5760df7567bc",
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    "execution": {
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    }
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   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from stochastic_matching import XP, Iterator, evaluate\n",
    "from multiprocess import Pool\n",
    "from numba import njit\n",
    "\n",
    "def xp_builder(common, specific):\n",
    "    return sum([XP(name=k, **common, **v) for k, v in specific.items()])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6581d4b3-e688-41b4-bf17-bea7395ee12e",
   "metadata": {},
   "source": [
    "Prepare specific parameters for each policy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8291582f-7714-43a4-9c84-2bead720a31d",
   "metadata": {
    "execution": {
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     "shell.execute_reply.started": "2025-09-28T07:11:23.541220Z"
    }
   },
   "outputs": [],
   "source": [
    "k_range = Iterator(\"k\", [2**i for i in range(14)])\n",
    "e_range = Iterator(\"epsilon\", np.logspace(-3, 0, 10), name=\"ϵ\")\n",
    "b_range = Iterator(\"beta\", np.logspace(-3, 1, 10), name=\"β\")\n",
    "def exp_fad(x):\n",
    "    return njit(lambda t: (t+1)**x)\n",
    "v_range = Iterator(\"fading\", [exp_fad(x) for x in np.linspace(0., 1., 10)], name=\"V\")\n",
    "\n",
    "specific = {\n",
    "    'k-filtering': {'simulator': \"longest\", 'forbidden_edges': True, \n",
    "                    'iterator': k_range},\n",
    "    'EGPD': {'simulator': \"virtual_queue\", \n",
    "             'iterator': b_range},\n",
    "    \"ϵ-filtering\": {'simulator': \"e_filtering\", \n",
    "                    'iterator': e_range},\n",
    "    \"EGPD+\": {'simulator': \"virtual_queue\", 'alt_rewards': 'gentle', \n",
    "              'iterator':  b_range},\n",
    "    \"CRPD\": {'simulator': 'constant_regret', \n",
    "             'iterator': v_range},\n",
    "    \"Taboo\": {'simulator': 'longest', 'forbidden_edges': True}\n",
    "           }"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebe7917e-4310-46e7-83a1-f85671ff9d50",
   "metadata": {},
   "source": [
    "Finally, a display function with a few options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "701aad9d-48a4-48c8-8e60-07ae125e7218",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "name_relabelling = {'Taboo': '$\\\\Phi_{E^*}$'}\n",
    "def display_res(res, view=\"loglog\", x_max=None, y_min=10**-8, y_max=None):\n",
    "    if view == \"loglog\":\n",
    "        plot = plt.loglog\n",
    "    elif view == \"logx\":\n",
    "        plot = plt.semilogx\n",
    "    else:\n",
    "        raise ValueError(f\"{view} is not a recognized display view.\")\n",
    "    names = [k for k in res] \n",
    "    colors = {k: v for k, v in zip(names, \n",
    "                                   plt.rcParams['axes.prop_cycle'].by_key()['color'])}\n",
    "    for k in sorted(names, key=lambda k: -np.average(res[k]['regret'])):\n",
    "        v = res[k]\n",
    "        name = name_relabelling.get(k, k)\n",
    "        delay, regret = np.array(v[\"delay\"]), np.array(v[\"regret\"])\n",
    "        if isinstance(v[\"delay\"], list):\n",
    "            mask = delay > 0\n",
    "            plot(np.abs(delay[mask]), np.abs(regret[mask]), marker=\"o\", \n",
    "                 label=name, color=colors[k])\n",
    "        else:\n",
    "            if y_max is None:\n",
    "                plot([delay], [regret], marker=\"o\", label=name, color=colors[k])\n",
    "            else:\n",
    "                plot([delay, delay], [y_min, y_max], '--', label=name, color=colors[k])\n",
    "                \n",
    "    plt.ylabel(\"Regret\")\n",
    "    plt.xlabel(\"Delay\")\n",
    "    if view == \"logx\":\n",
    "        plt.ylim([0, None])\n",
    "    plt.xlim([None, x_max])\n",
    "    if y_max:\n",
    "        plt.ylim([y_min, y_max])\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70b21ad4-ae75-4687-ab0f-791f7b362340",
   "metadata": {},
   "source": [
    "### Diamond"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f2a948e-8636-4130-9e8d-00aec9b0af8f",
   "metadata": {},
   "source": [
    "#### Injective-only vertex"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9042c3e-6552-4a7c-9681-fca6a6db3523",
   "metadata": {},
   "source": [
    "Let's reach an injective-only vertex."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3b8e3bc0-2960-4945-8a72-3a59976d35b0",
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    "execution": {
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     "shell.execute_reply.started": "2025-09-28T07:11:23.551896Z"
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   },
   "outputs": [
    {
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       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
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       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#af16b495-0883-46f7-a800-f26397e82523 {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"2\", \"title\": \"0\"}, {\"id\": 1, \"label\": \"3\", \"title\": \"1\"}, {\"id\": 2, \"label\": \"3\", \"title\": \"2\"}, {\"id\": 3, \"label\": \"2\", \"title\": \"3\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (0, 1)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (0, 2)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (1, 2)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (1, 3)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 1, \"to\": 3}, {\"title\": \"4: (2, 3)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 2, \"to\": 3}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\"};\n",
       "    const container = document.getElementById('af16b495-0883-46f7-a800-f26397e82523');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-af16b495-0883-46f7-a800-f26397e82523').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import stochastic_matching as sm\n",
    "diamond = sm.CycleChain()\n",
    "rewards = [1, 2.9, 1, -1, 1]\n",
    "diamond.show_flow(flow=diamond.optimize_rates(rewards))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90f43a35-6609-4725-b407-4dc3c6d4b00c",
   "metadata": {},
   "source": [
    ":::note\n",
    "The rewards are adversarial here: the largest reward corresponds to a taboo edge.\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b6ebb77-95bd-4afc-bac2-319e76372ac3",
   "metadata": {},
   "source": [
    "Let us compute the delay/regret trade-offs and display the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "586f533f-4649-46d6-8b11-468687834587",
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    "execution": {
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    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xps = xp_builder({'model': diamond, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"diamond-injective\", \n",
    "                   cache_overwrite=refresh)\n",
    "display_res(res, y_max=.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bc4c531-1225-43ac-8221-ac89c1f85ba5",
   "metadata": {},
   "source": [
    ":::important\n",
    "\n",
    "A simulation can only provide a finite-horizon estimate of the long-term behavior of a policy. In particular, it will always yield a finite delay even for policies that are proven to be unstable, i.e. those that have infinite long-term delay.\n",
    "\n",
    "This explains why some of the policies considered here seem to achieve finite delay and zero rate-regret (that is, constant global-regret) in simulations.\n",
    "\n",
    "For injective-only vertices, unstability stems from arrival deviations that behave roughly like an unbiased random walk, with magnitude on the order of $\\sqrt(T)$, where $T$ is the number of time steps simulated. If $\\sqrt(T)$ is small relative to the typical long-term delay of a policy (which is always the case for unstable policies), the trade-off between regret and delay cannot be observed through simulations.\n",
    "\n",
    "As a consequence, for injective-only vertices:\n",
    "\n",
    "- The regret values observed in the far right portion of the figures should be ignored, as they reflect discrepancies between long-term and finite-horizon values.\n",
    "- Simulations should be run over as many time steps as possible to broaden the parameter range over which long-term and finite-horizon estimates coincide.\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98f7abc3-f178-4169-9434-e58ab9efb098",
   "metadata": {},
   "source": [
    "Take-away:\n",
    "\n",
    "- EGPD has not a good trade-off;\n",
    "- $\\epsilon$-filtering and CRPD have average performance;\n",
    "- $k$-filtering and EGPD+ are the best here."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79a0b72a-6c5a-4a7d-a75d-5697c98ea1e3",
   "metadata": {},
   "source": [
    "#### Bijective vertex"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68109a21-1a81-4ba1-9c5e-f4c79567c390",
   "metadata": {},
   "source": [
    "We now change the rates and rewards so that the target is a bijective vertex."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "69d17ab3-89f3-4e91-9b2d-b7f317568898",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:23.949401Z",
     "iopub.status.busy": "2025-09-28T07:11:23.949401Z",
     "iopub.status.idle": "2025-09-28T07:11:23.957461Z",
     "shell.execute_reply": "2025-09-28T07:11:23.957461Z",
     "shell.execute_reply.started": "2025-09-28T07:11:23.949401Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-fdefef9d-50f2-4c86-8e9a-208a737979ac\">\n",
       "<div id=\"fdefef9d-50f2-4c86-8e9a-208a737979ac\"></div>\n",
       "<a href=\"#\" id=\"fit-fdefef9d-50f2-4c86-8e9a-208a737979ac\"\n",
       "  style=\"position: absolute; left: 10px; bottom: 10px; text-decoration: none; color: #888; font-size: min(2vw, 10px);\n",
       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-fdefef9d-50f2-4c86-8e9a-208a737979ac {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#fdefef9d-50f2-4c86-8e9a-208a737979ac {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"4\", \"title\": \"0\"}, {\"id\": 1, \"label\": \"4\", \"title\": \"1\"}, {\"id\": 2, \"label\": \"4\", \"title\": \"2\"}, {\"id\": 3, \"label\": \"2\", \"title\": \"3\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (0, 1)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (0, 2)\", \"label\": \"3\", \"color\": \"blue\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (1, 2)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (1, 3)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 1, \"to\": 3}, {\"title\": \"4: (2, 3)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 2, \"to\": 3}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\"};\n",
       "    const container = document.getElementById('fdefef9d-50f2-4c86-8e9a-208a737979ac');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-fdefef9d-50f2-4c86-8e9a-208a737979ac').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diamond.rates = [4, 4, 4, 2]\n",
    "rewards = [-1, 1, 1, 1, 2.9]\n",
    "diamond.show_flow(flow=diamond.optimize_rates(rewards))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf45af88-6474-41f0-9a5a-cf013ebc6487",
   "metadata": {},
   "source": [
    ":::note\n",
    "The rewards are even more adversarial here: the largest reward corresponds the unique taboo edge, while a live edge has a negative reward.\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eead15bd-56f9-4eaf-84fb-c5fec9350776",
   "metadata": {},
   "source": [
    "As before, let's see the trade-offs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1a7e53f8-98c0-411a-a0ad-b8f30755b8c4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:23.958466Z",
     "iopub.status.busy": "2025-09-28T07:11:23.958466Z",
     "iopub.status.idle": "2025-09-28T07:11:24.204345Z",
     "shell.execute_reply": "2025-09-28T07:11:24.204345Z",
     "shell.execute_reply.started": "2025-09-28T07:11:23.958466Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xps = xp_builder({'model': diamond, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"diamond-bijective\", \n",
    "                   cache_overwrite=refresh)\n",
    "display_res(res, view=\"logx\", x_max=1, y_max=.15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f404f5d7-0325-4afa-8d3a-95490c73c4ab",
   "metadata": {},
   "source": [
    "### Codomino"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fa295b0-0f42-4e53-a1c4-f9cd53453973",
   "metadata": {},
   "source": [
    "#### Injective-only vertex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e46d6039-d12a-4172-b3ac-94e991f8d405",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:24.205482Z",
     "iopub.status.busy": "2025-09-28T07:11:24.205482Z",
     "iopub.status.idle": "2025-09-28T07:11:24.210423Z",
     "shell.execute_reply": "2025-09-28T07:11:24.210423Z",
     "shell.execute_reply.started": "2025-09-28T07:11:24.205482Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-2e83ee14-76af-4bd9-a2fb-658b144d6151\">\n",
       "<div id=\"2e83ee14-76af-4bd9-a2fb-658b144d6151\"></div>\n",
       "<a href=\"#\" id=\"fit-2e83ee14-76af-4bd9-a2fb-658b144d6151\"\n",
       "  style=\"position: absolute; left: 10px; bottom: 10px; text-decoration: none; color: #888; font-size: min(2vw, 10px);\n",
       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-2e83ee14-76af-4bd9-a2fb-658b144d6151 {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#2e83ee14-76af-4bd9-a2fb-658b144d6151 {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"2\", \"title\": \"0\"}, {\"id\": 1, \"label\": \"4\", \"title\": \"1\"}, {\"id\": 2, \"label\": \"2\", \"title\": \"2\"}, {\"id\": 3, \"label\": \"2\", \"title\": \"3\"}, {\"id\": 4, \"label\": \"4\", \"title\": \"4\"}, {\"id\": 5, \"label\": \"2\", \"title\": \"5\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (0, 1)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (0, 2)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (1, 2)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (1, 4)\", \"label\": \"4\", \"color\": \"blue\", \"from\": 1, \"to\": 4}, {\"title\": \"4: (2, 3)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 2, \"to\": 3}, {\"title\": \"5: (3, 4)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 3, \"to\": 4}, {\"title\": \"6: (3, 5)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 3, \"to\": 5}, {\"title\": \"7: (4, 5)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 4, \"to\": 5}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\"};\n",
       "    const container = document.getElementById('2e83ee14-76af-4bd9-a2fb-658b144d6151');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-2e83ee14-76af-4bd9-a2fb-658b144d6151').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "codomino = sm.Codomino(rates=[2, 4, 2, 2, 4, 2])\n",
    "rewards = [-1, 1, -1, 1, 4.9, 4.9, 1, -1]\n",
    "codomino.show_flow(flow=codomino.optimize_rates(rewards))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4f87f712-1745-4184-96fd-60b94f7112f4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:24.210423Z",
     "iopub.status.busy": "2025-09-28T07:11:24.210423Z",
     "iopub.status.idle": "2025-09-28T07:11:24.660965Z",
     "shell.execute_reply": "2025-09-28T07:11:24.660965Z",
     "shell.execute_reply.started": "2025-09-28T07:11:24.210423Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xps = xp_builder({'model': codomino, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"codomino-injective\", \n",
    "                   cache_overwrite=refresh)\n",
    "display_res(res, y_max=5 )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8668950f-620e-4295-a895-05a91fb263a9",
   "metadata": {},
   "source": [
    "#### Bijective-only vertex"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff558d43-1957-437d-a70f-e5b885d2eb31",
   "metadata": {},
   "source": [
    "Here, we choose rewards so that all taboo edge have a positive weight, while two live edges have a negative weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a1c3944d-d0b4-4072-b87c-dd4c1c52612e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:24.661975Z",
     "iopub.status.busy": "2025-09-28T07:11:24.661975Z",
     "iopub.status.idle": "2025-09-28T07:11:24.667027Z",
     "shell.execute_reply": "2025-09-28T07:11:24.667027Z",
     "shell.execute_reply.started": "2025-09-28T07:11:24.661975Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-c9524755-879f-4635-9869-8a3e7a975577\">\n",
       "<div id=\"c9524755-879f-4635-9869-8a3e7a975577\"></div>\n",
       "<a href=\"#\" id=\"fit-c9524755-879f-4635-9869-8a3e7a975577\"\n",
       "  style=\"position: absolute; left: 10px; bottom: 10px; text-decoration: none; color: #888; font-size: min(2vw, 10px);\n",
       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-c9524755-879f-4635-9869-8a3e7a975577 {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#c9524755-879f-4635-9869-8a3e7a975577 {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"4\", \"title\": \"0\"}, {\"id\": 1, \"label\": \"5\", \"title\": \"1\"}, {\"id\": 2, \"label\": \"5\", \"title\": \"2\"}, {\"id\": 3, \"label\": \"3\", \"title\": \"3\"}, {\"id\": 4, \"label\": \"3\", \"title\": \"4\"}, {\"id\": 5, \"label\": \"2\", \"title\": \"5\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (0, 1)\", \"label\": \"3\", \"color\": \"blue\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (0, 2)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (1, 2)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (1, 4)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 1, \"to\": 4}, {\"title\": \"4: (2, 3)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 2, \"to\": 3}, {\"title\": \"5: (3, 4)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 3, \"to\": 4}, {\"title\": \"6: (3, 5)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 3, \"to\": 5}, {\"title\": \"7: (4, 5)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 4, \"to\": 5}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\"};\n",
       "    const container = document.getElementById('c9524755-879f-4635-9869-8a3e7a975577');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-c9524755-879f-4635-9869-8a3e7a975577').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "codomino.rates = [4, 5, 5, 3, 3, 2]\n",
    "rewards = [3.1, -1, 1,  1, -1, 0,  1, 0]\n",
    "codomino.show_flow(flow=codomino.optimize_rates(rewards))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0a470a5e-ddef-4a16-a72c-634a49d6362a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:24.668388Z",
     "iopub.status.busy": "2025-09-28T07:11:24.668388Z",
     "iopub.status.idle": "2025-09-28T07:11:24.919928Z",
     "shell.execute_reply": "2025-09-28T07:11:24.919928Z",
     "shell.execute_reply.started": "2025-09-28T07:11:24.668388Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xps = xp_builder({'model': codomino, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"codomino-bijective\", \n",
    "                   cache_overwrite=refresh)\n",
    "display_res(res, view='logx', x_max=3, y_max=1.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad92fcbe-0c66-49e4-8412-d82a50204abf",
   "metadata": {},
   "source": [
    "### Larger graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "957a934b-811f-4f7b-b831-6c69705e1d47",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:24.919928Z",
     "iopub.status.busy": "2025-09-28T07:11:24.919928Z",
     "iopub.status.idle": "2025-09-28T07:11:25.727831Z",
     "shell.execute_reply": "2025-09-28T07:11:25.727831Z",
     "shell.execute_reply.started": "2025-09-28T07:11:24.919928Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1006"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n, d = 100, 20\n",
    "er = sm.ErdosRenyi(n=n, d=d, seed=42)\n",
    "er.m"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2c21a19-8c55-4a99-9db6-b071b7f55859",
   "metadata": {},
   "source": [
    "To select a vertex, we draw random rewards, which are optimized at a unique point w.h.p."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "30ff420c-4116-41ef-937d-1291723f7afe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:25.728839Z",
     "iopub.status.busy": "2025-09-28T07:11:25.728839Z",
     "iopub.status.idle": "2025-09-28T07:11:25.732298Z",
     "shell.execute_reply": "2025-09-28T07:11:25.732298Z",
     "shell.execute_reply.started": "2025-09-28T07:11:25.728839Z"
    }
   },
   "outputs": [],
   "source": [
    "rewards = np.random.rand(er.m)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "661842e9-1aa3-4a66-a418-a0821a44d767",
   "metadata": {},
   "source": [
    "#### Injective-only vertex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9641f7d3-527b-489d-a4da-b5a5c17ec29f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:25.733303Z",
     "iopub.status.busy": "2025-09-28T07:11:25.733303Z",
     "iopub.status.idle": "2025-09-28T07:11:25.772922Z",
     "shell.execute_reply": "2025-09-28T07:11:25.772922Z",
     "shell.execute_reply.started": "2025-09-28T07:11:25.733303Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(97)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vertex = er.optimize_rates(rewards)\n",
    "np.sum(vertex>0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ff0667d8-df02-45dd-af46-447a74f536a5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:25.773932Z",
     "iopub.status.busy": "2025-09-28T07:11:25.773932Z",
     "iopub.status.idle": "2025-09-28T07:11:26.155338Z",
     "shell.execute_reply": "2025-09-28T07:11:26.154829Z",
     "shell.execute_reply.started": "2025-09-28T07:11:25.773932Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xps = xp_builder({'model': er, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"er-injective\", \n",
    "                   cache_overwrite=refresh)\n",
    "display_res(res, y_max=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59f78b7c-981a-4416-92db-75d50d54b6d6",
   "metadata": {},
   "source": [
    "#### Bijective vertex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "49166629-3df8-4946-942c-c4cae7386105",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:26.156343Z",
     "iopub.status.busy": "2025-09-28T07:11:26.156343Z",
     "iopub.status.idle": "2025-09-28T07:11:26.194049Z",
     "shell.execute_reply": "2025-09-28T07:11:26.194049Z",
     "shell.execute_reply.started": "2025-09-28T07:11:26.156343Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(100)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.seed(42)\n",
    "er.rates = er.rates + 5*np.random.rand(n)\n",
    "vertex = er.optimize_rates(rewards)\n",
    "np.sum(vertex>0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8c628d21-052a-4a98-8e3c-da795a390ada",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:26.195056Z",
     "iopub.status.busy": "2025-09-28T07:11:26.195056Z",
     "iopub.status.idle": "2025-09-28T07:11:26.554000Z",
     "shell.execute_reply": "2025-09-28T07:11:26.554000Z",
     "shell.execute_reply.started": "2025-09-28T07:11:26.195056Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xps = xp_builder({'model': er, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"er-bijective\", \n",
    "                   cache_overwrite=refresh)\n",
    "display_res(res, y_max=800)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd252188-b40a-45ce-98a7-c7d459e865ac",
   "metadata": {},
   "source": [
    "## Approaching vertices of hypergraphs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b354c350-fa87-465b-a68e-4d2e3d7c0b95",
   "metadata": {},
   "source": [
    "We now have hypergraphs. We need to adjust some policy settings accordingly, switching from *longest queue* to *virtual queue* to ensure stability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ee41b836-de30-4023-bc29-a876a3181d73",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:26.555006Z",
     "iopub.status.busy": "2025-09-28T07:11:26.555006Z",
     "iopub.status.idle": "2025-09-28T07:11:26.559004Z",
     "shell.execute_reply": "2025-09-28T07:11:26.559004Z",
     "shell.execute_reply.started": "2025-09-28T07:11:26.555006Z"
    }
   },
   "outputs": [],
   "source": [
    "for k in ['k-filtering', 'Taboo']:\n",
    "    specific[k]['simulator'] = 'virtual_queue'\n",
    "    specific[k]['alt_rewards'] = 'gentle'\n",
    "specific['ϵ-filtering']['base_policy'] = 'virtual_queue'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a721725-6463-41f6-b31d-40f94ba45866",
   "metadata": {},
   "source": [
    "### Abandonment"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b0c7bae-9001-4393-9a11-50a6fff0e579",
   "metadata": {},
   "source": [
    "We now conside a diamond where one item class can be abandonned and where the optional solution is to abandon it entirely. As usual, we pick adversarial rewards so that the resulting vertex looks a bit counter-intuitive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1331d864-2455-42b4-a046-31b18804c119",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:26.560302Z",
     "iopub.status.busy": "2025-09-28T07:11:26.560302Z",
     "iopub.status.idle": "2025-09-28T07:11:26.573337Z",
     "shell.execute_reply": "2025-09-28T07:11:26.573337Z",
     "shell.execute_reply.started": "2025-09-28T07:11:26.560302Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-ab2ab184-98c2-45cc-8244-6210f5678135\">\n",
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       "<a href=\"#\" id=\"fit-ab2ab184-98c2-45cc-8244-6210f5678135\"\n",
       "  style=\"position: absolute; left: 10px; bottom: 10px; text-decoration: none; color: #888; font-size: min(2vw, 10px);\n",
       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-ab2ab184-98c2-45cc-8244-6210f5678135 {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#ab2ab184-98c2-45cc-8244-6210f5678135 {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"4\", \"title\": \"0\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 1, \"label\": \"4\", \"title\": \"1\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 2, \"label\": \"4\", \"title\": \"2\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 3, \"label\": \"2\", \"title\": \"3\", \"x\": 0, \"group\": \"Node\"}, {\"title\": \"0: (0, 1)\", \"label\": \"2\", \"color\": \"blue\", \"id\": 4, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"1: (0, 2)\", \"label\": \"2\", \"color\": \"blue\", \"id\": 5, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"2: (1, 2)\", \"label\": \"2\", \"color\": \"blue\", \"id\": 6, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"3: (1, 3)\", \"label\": \"0\", \"color\": \"orange\", \"id\": 7, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"4: (2, 3)\", \"label\": \"0\", \"color\": \"orange\", \"id\": 8, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"5: (3)\", \"label\": \"2\", \"color\": \"blue\", \"id\": 9, \"group\": \"HyperEdge\", \"x\": 600}]);\n",
       "    const edges = new DataSet([{\"from\": 0, \"to\": 4, \"title\": \"0 <-> 0: (0, 1)\"}, {\"from\": 0, \"to\": 5, \"title\": \"0 <-> 1: (0, 2)\"}, {\"from\": 1, \"to\": 4, \"title\": \"1 <-> 0: (0, 1)\"}, {\"from\": 1, \"to\": 6, \"title\": \"1 <-> 2: (1, 2)\"}, {\"from\": 1, \"to\": 7, \"title\": \"1 <-> 3: (1, 3)\"}, {\"from\": 2, \"to\": 5, \"title\": \"2 <-> 1: (0, 2)\"}, {\"from\": 2, \"to\": 6, \"title\": \"2 <-> 2: (1, 2)\"}, {\"from\": 2, \"to\": 8, \"title\": \"2 <-> 4: (2, 3)\"}, {\"from\": 3, \"to\": 7, \"title\": \"3 <-> 3: (1, 3)\"}, {\"from\": 3, \"to\": 8, \"title\": \"3 <-> 4: (2, 3)\"}, {\"from\": 3, \"to\": 9, \"title\": \"3 <-> 5: (3)\"}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\", \"groups\": {\"HyperEdge\": {\"fixed\": {\"x\": false}, \"color\": {\"background\": \"black\"}, \"shape\": \"dot\", \"size\": 5}, \"Node\": {\"fixed\": {\"x\": false}}}};\n",
       "    const container = document.getElementById('ab2ab184-98c2-45cc-8244-6210f5678135');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-ab2ab184-98c2-45cc-8244-6210f5678135').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "incidence = np.hstack([diamond.incidence, np.array([[0, 0, 0, 1]]).T])\n",
    "modified_diamond = sm.Model(incidence=incidence, rates=[4, 4, 4, 2])\n",
    "rewards = [-1, 1, 1, 1, 3, 2]\n",
    "modified_diamond.show_flow(flow=modified_diamond.optimize_rates(rewards))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "eba87199-595a-4ab9-a07f-36c7c5b7a4d2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:26.577343Z",
     "iopub.status.busy": "2025-09-28T07:11:26.576343Z",
     "iopub.status.idle": "2025-09-28T07:11:27.200214Z",
     "shell.execute_reply": "2025-09-28T07:11:27.200214Z",
     "shell.execute_reply.started": "2025-09-28T07:11:26.577343Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xps = xp_builder({'model': modified_diamond, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"abandonment\", \n",
    "                   cache_overwrite=refresh)\n",
    "display_res(res, x_max=10, y_max=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2dab574-da4f-4851-a36a-d55c3c23ecc4",
   "metadata": {},
   "source": [
    "### Nazari & Stolyar example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0ac78e0-625e-4fa9-a6ff-7c85b181dcae",
   "metadata": {},
   "source": [
    "See https://arxiv.org/abs/1608.01646 for details."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3a38898-85ec-47a0-8680-75eeb015504b",
   "metadata": {},
   "source": [
    "#### First arrival rates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5d9fdad5-b63a-4747-83ed-36c930680535",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.201445Z",
     "iopub.status.busy": "2025-09-28T07:11:27.200214Z",
     "iopub.status.idle": "2025-09-28T07:11:27.210244Z",
     "shell.execute_reply": "2025-09-28T07:11:27.210244Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.201445Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-01770143-69a2-4f0a-a89a-97391d4ea42d\">\n",
       "<div id=\"01770143-69a2-4f0a-a89a-97391d4ea42d\"></div>\n",
       "<a href=\"#\" id=\"fit-01770143-69a2-4f0a-a89a-97391d4ea42d\"\n",
       "  style=\"position: absolute; left: 10px; bottom: 10px; text-decoration: none; color: #888; font-size: min(2vw, 10px);\n",
       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-01770143-69a2-4f0a-a89a-97391d4ea42d {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#01770143-69a2-4f0a-a89a-97391d4ea42d {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"1.2\", \"title\": \"0\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 1, \"label\": \"1.5\", \"title\": \"1\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 2, \"label\": \"2\", \"title\": \"2\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 3, \"label\": \"0.8\", \"title\": \"3\", \"x\": 0, \"group\": \"Node\"}, {\"title\": \"0: (0)\", \"label\": \"0\", \"color\": \"orange\", \"id\": 4, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"1: (1)\", \"label\": \"0\", \"color\": \"orange\", \"id\": 5, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"2: (2)\", \"label\": \"1.7\", \"color\": \"blue\", \"id\": 6, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"3: (3)\", \"label\": \"0.5\", \"color\": \"blue\", \"id\": 7, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"4: (0, 1)\", \"label\": \"1.2\", \"color\": \"blue\", \"id\": 8, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"5: (1, 2)\", \"label\": \"0\", \"color\": \"orange\", \"id\": 9, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"6: (1, 2, 3)\", \"label\": \"0.3\", \"color\": \"blue\", \"id\": 10, \"group\": \"HyperEdge\", \"x\": 600}]);\n",
       "    const edges = new DataSet([{\"from\": 0, \"to\": 4, \"title\": \"0 <-> 0: (0)\"}, {\"from\": 0, \"to\": 8, \"title\": \"0 <-> 4: (0, 1)\"}, {\"from\": 1, \"to\": 5, \"title\": \"1 <-> 1: (1)\"}, {\"from\": 1, \"to\": 8, \"title\": \"1 <-> 4: (0, 1)\"}, {\"from\": 1, \"to\": 9, \"title\": \"1 <-> 5: (1, 2)\"}, {\"from\": 1, \"to\": 10, \"title\": \"1 <-> 6: (1, 2, 3)\"}, {\"from\": 2, \"to\": 6, \"title\": \"2 <-> 2: (2)\"}, {\"from\": 2, \"to\": 9, \"title\": \"2 <-> 5: (1, 2)\"}, {\"from\": 2, \"to\": 10, \"title\": \"2 <-> 6: (1, 2, 3)\"}, {\"from\": 3, \"to\": 7, \"title\": \"3 <-> 3: (3)\"}, {\"from\": 3, \"to\": 10, \"title\": \"3 <-> 6: (1, 2, 3)\"}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\", \"groups\": {\"HyperEdge\": {\"fixed\": {\"x\": false}, \"color\": {\"background\": \"black\"}, \"shape\": \"dot\", \"size\": 5}, \"Node\": {\"fixed\": {\"x\": false}}}};\n",
       "    const container = document.getElementById('01770143-69a2-4f0a-a89a-97391d4ea42d');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-01770143-69a2-4f0a-a89a-97391d4ea42d').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ns19 = sm.NS19(rates=[1.2, 1.5, 2, 0.8])\n",
    "rewards = [-1, -1, 1, 2, 5, 4, 7]\n",
    "ns19.show_flow(flow=ns19.optimize_rates(rewards))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b881ef38-07fd-42e2-a97a-b86847fddbcc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.211536Z",
     "iopub.status.busy": "2025-09-28T07:11:27.211536Z",
     "iopub.status.idle": "2025-09-28T07:11:27.517702Z",
     "shell.execute_reply": "2025-09-28T07:11:27.517198Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.211536Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xps = xp_builder({'model': ns19, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"ns19-a\", cache_overwrite=refresh)\n",
    "display_res(res, view='logx', x_max=10, y_max=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c953fb1-5cac-4da3-89b5-d635a9c58ab1",
   "metadata": {},
   "source": [
    "#### Second arrival rates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d807219c-9954-4581-b125-05418a405f68",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.518713Z",
     "iopub.status.busy": "2025-09-28T07:11:27.517702Z",
     "iopub.status.idle": "2025-09-28T07:11:27.526749Z",
     "shell.execute_reply": "2025-09-28T07:11:27.526749Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.518713Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-39cc4f86-1b5d-48ba-b5df-f1db0b1d41c8\">\n",
       "<div id=\"39cc4f86-1b5d-48ba-b5df-f1db0b1d41c8\"></div>\n",
       "<a href=\"#\" id=\"fit-39cc4f86-1b5d-48ba-b5df-f1db0b1d41c8\"\n",
       "  style=\"position: absolute; left: 10px; bottom: 10px; text-decoration: none; color: #888; font-size: min(2vw, 10px);\n",
       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-39cc4f86-1b5d-48ba-b5df-f1db0b1d41c8 {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#39cc4f86-1b5d-48ba-b5df-f1db0b1d41c8 {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"1.8\", \"title\": \"0\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 1, \"label\": \"0.8\", \"title\": \"1\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 2, \"label\": \"1.4\", \"title\": \"2\", \"x\": 0, \"group\": \"Node\"}, {\"id\": 3, \"label\": \"1\", \"title\": \"3\", \"x\": 0, \"group\": \"Node\"}, {\"title\": \"0: (0)\", \"label\": \"1\", \"color\": \"blue\", \"id\": 4, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"1: (1)\", \"label\": \"0\", \"color\": \"orange\", \"id\": 5, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"2: (2)\", \"label\": \"1.4\", \"color\": \"blue\", \"id\": 6, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"3: (3)\", \"label\": \"1\", \"color\": \"blue\", \"id\": 7, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"4: (0, 1)\", \"label\": \"0.8\", \"color\": \"blue\", \"id\": 8, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"5: (1, 2)\", \"label\": \"0\", \"color\": \"orange\", \"id\": 9, \"group\": \"HyperEdge\", \"x\": 600}, {\"title\": \"6: (1, 2, 3)\", \"label\": \"0\", \"color\": \"orange\", \"id\": 10, \"group\": \"HyperEdge\", \"x\": 600}]);\n",
       "    const edges = new DataSet([{\"from\": 0, \"to\": 4, \"title\": \"0 <-> 0: (0)\"}, {\"from\": 0, \"to\": 8, \"title\": \"0 <-> 4: (0, 1)\"}, {\"from\": 1, \"to\": 5, \"title\": \"1 <-> 1: (1)\"}, {\"from\": 1, \"to\": 8, \"title\": \"1 <-> 4: (0, 1)\"}, {\"from\": 1, \"to\": 9, \"title\": \"1 <-> 5: (1, 2)\"}, {\"from\": 1, \"to\": 10, \"title\": \"1 <-> 6: (1, 2, 3)\"}, {\"from\": 2, \"to\": 6, \"title\": \"2 <-> 2: (2)\"}, {\"from\": 2, \"to\": 9, \"title\": \"2 <-> 5: (1, 2)\"}, {\"from\": 2, \"to\": 10, \"title\": \"2 <-> 6: (1, 2, 3)\"}, {\"from\": 3, \"to\": 7, \"title\": \"3 <-> 3: (3)\"}, {\"from\": 3, \"to\": 10, \"title\": \"3 <-> 6: (1, 2, 3)\"}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\", \"groups\": {\"HyperEdge\": {\"fixed\": {\"x\": false}, \"color\": {\"background\": \"black\"}, \"shape\": \"dot\", \"size\": 5}, \"Node\": {\"fixed\": {\"x\": false}}}};\n",
       "    const container = document.getElementById('39cc4f86-1b5d-48ba-b5df-f1db0b1d41c8');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-39cc4f86-1b5d-48ba-b5df-f1db0b1d41c8').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ns19.rates = [1.8, .8, 1.4, 1]\n",
    "ns19.show_flow(flow=ns19.optimize_rates(rewards))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e82f6c7f-4748-44e9-8a7e-19590f7b6698",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.528759Z",
     "iopub.status.busy": "2025-09-28T07:11:27.527762Z",
     "iopub.status.idle": "2025-09-28T07:11:27.648571Z",
     "shell.execute_reply": "2025-09-28T07:11:27.648571Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.528759Z"
    }
   },
   "outputs": [],
   "source": [
    "xps = xp_builder({'model': ns19, 'rewards': rewards, **common}, specific)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, cache_name=\"ns19-b\", cache_overwrite=refresh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0d76a3c5-2c2e-464d-a98b-d594b2100aa3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.649578Z",
     "iopub.status.busy": "2025-09-28T07:11:27.649578Z",
     "iopub.status.idle": "2025-09-28T07:11:27.819943Z",
     "shell.execute_reply": "2025-09-28T07:11:27.819943Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.649578Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_res(res, view='logx', x_max=10, y_max=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac800f91-80cc-48f6-bafa-3a8fcdaeb309",
   "metadata": {},
   "source": [
    "## Flexibility of greedy policies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f18165f-7807-48e1-bb54-568ddfef101a",
   "metadata": {},
   "source": [
    "### Complete graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec5aa04a-44df-4a03-a7e4-15c1f3bf0a64",
   "metadata": {},
   "source": [
    "For complete graphs, all greedy policies are equivalent because there is never any true choice to make in that case. Let us check that by running a few greedy policies.\n",
    "\n",
    "We will use the graph $K_4$, which has a 2-D kernel. With uniform arrival rates, its polytope is a triangle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e44ba259-f450-415c-a106-773604ed2f57",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.820950Z",
     "iopub.status.busy": "2025-09-28T07:11:27.820950Z",
     "iopub.status.idle": "2025-09-28T07:11:27.834335Z",
     "shell.execute_reply": "2025-09-28T07:11:27.833325Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.820950Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'kernel_coordinates': array([-1., -1.]),\n",
       "  'edge_coordinates': array([0., 0., 3., 3., 0., 0.]),\n",
       "  'null_edges': [0, 1, 4, 5],\n",
       "  'bijective': False},\n",
       " {'kernel_coordinates': array([-1.,  2.]),\n",
       "  'edge_coordinates': array([3., 0., 0., 0., 0., 3.]),\n",
       "  'null_edges': [1, 2, 3, 4],\n",
       "  'bijective': False},\n",
       " {'kernel_coordinates': array([ 2., -1.]),\n",
       "  'edge_coordinates': array([0., 3., 0., 0., 3., 0.]),\n",
       "  'null_edges': [0, 2, 3, 5],\n",
       "  'bijective': False}]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "complete = sm.Complete(n=4)\n",
    "complete.vertices"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4a2f228-2d1d-4b5c-988c-b13cd1d0e9e7",
   "metadata": {},
   "source": [
    "For the comparison, we will consider the following greedy policies:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "9d0a567c-490c-4d90-8e44-e5a840e8d029",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.835334Z",
     "iopub.status.busy": "2025-09-28T07:11:27.834335Z",
     "iopub.status.idle": "2025-09-28T07:11:27.839835Z",
     "shell.execute_reply": "2025-09-28T07:11:27.839331Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.834335Z"
    }
   },
   "outputs": [],
   "source": [
    "complete_policies = {\n",
    "    \"Longest\": {\"simulator\": \"longest\"},\n",
    "    \"FCFM\": {\"simulator\": \"fcfm\"},\n",
    "    \"Random Edge\": {\"simulator\": \"random_edge\"},\n",
    "    \"Random Item\": {\"simulator\": \"random_item\"},\n",
    "    \"Priority\": {\"simulator\": \"priority\", \"weights\": [1, 10, 0, -1, 3, 4]},\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8d1c926-80d9-4777-af27-87241a5c3ec2",
   "metadata": {},
   "source": [
    "We run the simulation, gathering the resulting matching rate in edge and kernel coordinates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e543ad0f-ac72-45d0-9393-51a55ba130e9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.840839Z",
     "iopub.status.busy": "2025-09-28T07:11:27.840839Z",
     "iopub.status.idle": "2025-09-28T07:11:27.892820Z",
     "shell.execute_reply": "2025-09-28T07:11:27.892820Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.840839Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Longest': {'flow': array([1.00000059, 1.0000066 , 1.00001283, 1.0000111 , 1.00000862,\n",
       "         0.99996026]),\n",
       "  'flow_kernel_coordinates': array([0., 0.])},\n",
       " 'FCFM': {'flow': array([1.00000059, 1.0000066 , 1.00001283, 1.0000111 , 1.00000862,\n",
       "         0.99996026]),\n",
       "  'flow_kernel_coordinates': array([0., 0.])},\n",
       " 'Random Edge': {'flow': array([1.00003558, 1.00002742, 0.99995652, 0.99996954, 0.99997213,\n",
       "         1.00003881]),\n",
       "  'flow_kernel_coordinates': array([0., 0.])},\n",
       " 'Random Item': {'flow': array([1.00003558, 1.00002742, 0.99995652, 0.99996954, 0.99997213,\n",
       "         1.00003881]),\n",
       "  'flow_kernel_coordinates': array([0., 0.])},\n",
       " 'Priority': {'flow': array([1.00000059, 1.0000066 , 1.00001283, 1.0000111 , 1.00000862,\n",
       "         0.99996026]),\n",
       "  'flow_kernel_coordinates': array([0., 0.])}}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def flow_kernel_coordinates(simu):\n",
    "    flow = simu.flow\n",
    "    return simu.model.edge_to_kernel(flow)\n",
    "xps = xp_builder({'model': complete, **common}, complete_policies)\n",
    "with Pool(5) as p:\n",
    "    res = evaluate(\n",
    "        xps, [\"flow\", flow_kernel_coordinates], pool=p, cache_name=\"complete\", \n",
    "        cache_overwrite=refresh\n",
    "    )\n",
    "res"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01a45ee6-e2a2-4542-9a8d-0eccae8aed8b",
   "metadata": {},
   "source": [
    ":::tip\n",
    "In the results above, the randomized policies (on Items and Edges) have not exactly the same rate than the deterministic policies, despite the use of a seed. The reason is that there is one unique random generator per simulator, so having a randomized policy impacts the drawing of arrivals (even if the number of possibilities is always reduced to 1).\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "583c4863-e55e-4171-99fc-6dd9bc95a83b",
   "metadata": {},
   "source": [
    "### Diamond"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4dbc2e5-0587-4bb9-b881-5c9ee8a35545",
   "metadata": {},
   "source": [
    "For the diamond, the capacity of greedy policies to affect the matching rates depends on the traffic $\\beta$ on the central edge, which corresponds to the unbalance between the two opposite pairs of nodes. Roughly speaking, when the central traffic is scarse, greedy policies get to choose more, leading to a greater influence."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "970475da-f9d6-4ad7-8136-8337a1463dbd",
   "metadata": {},
   "source": [
    "First, let us build the experiments for various $\\beta$. Note that all models are symmetric so we can focus on targeting one vertex."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "273ae97b-7d56-4f74-a8a2-7653650f6540",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.893828Z",
     "iopub.status.busy": "2025-09-28T07:11:27.893828Z",
     "iopub.status.idle": "2025-09-28T07:11:27.898388Z",
     "shell.execute_reply": "2025-09-28T07:11:27.898388Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.893828Z"
    }
   },
   "outputs": [],
   "source": [
    "def beta_to_model(beta):\n",
    "    return sm.CycleChain(\n",
    "        names=[str(i) for i in range(1, 5)],\n",
    "        rates=[1 / 4, 1 / 4 + beta, 1 / 4 + beta, 1 / 4],\n",
    "    )\n",
    "\n",
    "n_points = 30\n",
    "β_vect = np.logspace(-3, 1, n_points)\n",
    "model_iter = Iterator(\"model\", β_vect, \"β\", beta_to_model)\n",
    "\n",
    "xps = XP(\"Greedy vertex\", simulator=\"priority\", weights=[1, 0, 0, 0, 1], iterator=model_iter, **common)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "474f0213-c703-4eb9-b2ac-9b913b40248c",
   "metadata": {},
   "source": [
    "What we want to measure are the kernel coordinate $\\alpha$ of the matching rates of the policy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5b18666f-32d3-429d-a54e-031826df878e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.899396Z",
     "iopub.status.busy": "2025-09-28T07:11:27.899396Z",
     "iopub.status.idle": "2025-09-28T07:11:27.904490Z",
     "shell.execute_reply": "2025-09-28T07:11:27.904490Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.899396Z"
    }
   },
   "outputs": [],
   "source": [
    "def alpha(simu):\n",
    "    flow = simu.flow\n",
    "    return (flow[0] + flow[-1] - flow[1] - flow[3]) / 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bc83baa4-0edc-4f33-a279-b0ea1f873ccf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:27.906495Z",
     "iopub.status.busy": "2025-09-28T07:11:27.905495Z",
     "iopub.status.idle": "2025-09-28T07:11:28.046635Z",
     "shell.execute_reply": "2025-09-28T07:11:28.046635Z",
     "shell.execute_reply.started": "2025-09-28T07:11:27.906495Z"
    }
   },
   "outputs": [],
   "source": [
    "with Pool() as p:\n",
    "    res = evaluate(xps, alpha, pool=p, cache_name=\"greedy-diamond\", cache_overwrite=refresh)\n",
    "res = np.array(res[\"Greedy vertex\"][\"alpha\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b89291b-c418-475b-9524-09a3c6cbff5f",
   "metadata": {},
   "source": [
    "Theoretical bounds:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "bfb595f2-153a-4713-aa39-8454e283dd6e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:28.047640Z",
     "iopub.status.busy": "2025-09-28T07:11:28.047640Z",
     "iopub.status.idle": "2025-09-28T07:11:28.053023Z",
     "shell.execute_reply": "2025-09-28T07:11:28.052012Z",
     "shell.execute_reply.started": "2025-09-28T07:11:28.047640Z"
    }
   },
   "outputs": [],
   "source": [
    "def min_flow2(beta):\n",
    "    q13 = 1 / (4 * beta)\n",
    "    q2 = 1 / 2 + 2 * beta\n",
    "    p0 = 1 / (1 + q13 + 2 * q2)\n",
    "    return p0 * q2 / 4 + p0 / (1 + 8 * beta) * (1 / 4 + beta) - 1 / 8\n",
    "\n",
    "\n",
    "lbi = [min_flow2(β) for β in β_vect]\n",
    "ubi = [-min_flow2(β) for β in β_vect]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5b3ec24-1088-464a-befc-ee2e95511cc6",
   "metadata": {},
   "source": [
    "Results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "25428b47-c9e6-47e5-b8d8-737760ea5942",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:28.053023Z",
     "iopub.status.busy": "2025-09-28T07:11:28.053023Z",
     "iopub.status.idle": "2025-09-28T07:11:28.270687Z",
     "shell.execute_reply": "2025-09-28T07:11:28.269677Z",
     "shell.execute_reply.started": "2025-09-28T07:11:28.053023Z"
    }
   },
   "outputs": [
    {
     "data": {
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66CIMGDCgxd+rsz2fM2DAIjpF2JL9EmXbHjmki3xcXJxq+6B1vVanEDPuPSMKtwwJx7d7C1Stlmw+LdOHH2/PxchEP1zdPxTdw701fV4i0p6MgEuB+7x589R1qYEaM2aMCl2WgPXee+/h1VdfxQcffKDCUWlpKR599NFGGybL6mc5tCC/y2RESYKchTyn/M6bPXu2Js+hxfO9++676vL666+HK3K5KcIXX3wRHTt2hLe3N4YPH44//vijyfvKijFJ/HJ/WQ6/aNGiNj8meba8vDz170p+cR4+fNguvXhki57Lj08fzhkTg4GW6cMjxbjni6N44oc0pORXaP68RKQdCVI9e/bEkCFDrLddd911qsVEfn6+OmbNmqVChGXkSYrRZSrQ3lOEe/bsUZcDBw603rZv3z51rn379m3jd+7453MWLjWCJT0uZHjxlVdeUUFIAtOFF16oXjxZBdZQSUkJOnfurIZop02bpsljEgkZzpeAJYf8YpNRLRnd0rKvlUwfjkj0V8fh3HJ89Gcuvj9QqHprSSPT8T2CcN2AUIT5utSPMZHbkxKDpUuXYsqUKfVuv/jiizF16lR89NFHqqeW/M3p0KFDsx5TyylCCXfSC9Dy+0oW9sjfvn79+sEe8tv5+ZyFS/1mlnlqaSp28803q+sSir766iu88cYbmDlz5gn3Hzp0qDpEY59vzWMSNST9tOSQEdD4+HhVryU1F1rqGGLGg2dHq5GtNzdmYd3REtUhftX+AlzWOxhXnhYCP5P2zVOJqOW+/vpr1QrmmmuuqXe7/I6QkCSjWzJdKCsLLf72t79h+/bt6m/Wa6+9ZtcpQlnBJ4t65O+f1EXdf//9KujJKuojR46cEPokCEpobOjLL79sVqjr34LnkzevZ555pvrYsufsCy+8oC6lfs1kMsFVuMwUofxHlyWd8o/SQmpg5PratWvb9TFlWsiyJYvlICorK8P+/fvVCkT5xWGPfxedQ814/Pw4PDM+Hr0jvVFeVYv3/6xr8fDJ9lxUcNUhuTlZlWePfnUnI88nz9tcslpw9OjR6g1XQzJNuGnTJvV4tiPe0sJB3uwnJCTA3rp06YJHHnlElcecfvrpiImJsYalSy655IT7S/2U/K1seDQMVzLdKdOcbXk+k8mknk8O+Ro5LNddKVy51AiWjBBIApbRAVtyXf6YtedjSqHenDlzWvWc5P6kcFPaPaSnp6tpAJk+lOlmLbfn6Rftg4UT4vFbUjHe3JiNpLwKLP4jC5/tyMONg8JwXpcAbi5Nbkl+pmTbGmfei1DaMzRl5MiRqph9w4YNauZEphGl2bGMEP3yyy9qtWF7kPovOWzJm8O2kJIJy+hTezyfs3OZgOVM5B+JZampkJGK9njXQa63AlEaDUo9n4xsybs1+Xei1bswefcr7R1OT/BTU4XvbM7BseIqzP85Ax9vy8UtQ8LU57jfIbkbCTuuuC+gLSnwlqky6QslvxOkrEBWF55zzjmaP9fixYvVtOSPP/5o16Lyb7/9FgsXLkR7mjp1Kt5//304I5cJWFJILCMAMjJgS663dguA1j6mvJtpyXAxkYyUHj16VC1XlqCVmJio2b8hGaka2z0I53QOwOe78vHh1hwcyavAo9+loU+kt+oY3yfqxGF7InIs6QMlhz29+eabqnxB2HsgQEbgtHR9M9ozSJuH++67T33sbNsBuUwNliT8wYMH4/vvv7feJtuZyPURI0Y4zWMSnWpkKyUlRbV5kD45ll98WjAb9ao7/NtXdMRVp4XAbNBhR2YZpn2VjEdWpapGpkTkWaREQWqg5HC1GqbmkPILy/fn5+cHZ+IyI1hCpuUk7cvQ6rBhw9Qyz+LiYusKwBtuuEH9Y7I0M5Mi9p07d1o/lj9sW7ZsUUPLXbt2bdZjEtkraEmXeOkWLzV/soqmseLQ1vA3G3DrkHBM6h2MdzdnY8XeAvx+tBjrjhbj/G4BqkYrwo9d4YmI7MmlAtZVV12llr7KqgIpIJb2+itWrLAWqUuTNdvVJfIHzLax2fz589Vx9tlnq7no5jwmkb2Dlvy7k8MStLTajkf6Y8nG0pP7SmuHbLXP4cp9hfjlcLGaNhzfIxB61mcREdmFrtYeO9l6GClyDwoKUqNfWo1CkOeRYnT5cZQhbwlaWg937z5Whpd/P4Zdx+qmJftH++C+UZGIC3S/aQNyj7pF2aZKfhZY80ptIStOpd+WLCRouJpbFiJJqZA0Qw0MDIRH1mARuTvLex0ZUZXd5qXpoPzwa6VnhDcWTIjHXcPDYTbqsDW9FHd+loRPtuWiWvbiISIizTBgETlp0MrOzla9crZt24bCwkLNVhxe2icEiyd1UHscllfXYvH6LNy3/CiL4ImINMSAReTkQUu2i5CuyVu3btWsO3xMoBeeGhuHaaMi4WfSY09WOaZ8nqSK4iurOZpFRNRWDFhELhK08vLy1BYbsjJWi/YOUvM1rnsQXr+sA0Yk+kF22Xl3cw6mfJGEPcfrtIiIqHUYsIhcLGhlZmaqfblkWwopBNZiteG/z4vBQ6OjEeRtwOHcCty7/CgW/3EMZdzbkMhjrFmzRi3Ukjdzzujdd991umaiJ8OAReSiYUsClgQt2XmgrYuBZTRrdOcANZp1bpcASM37J9vzcOeyJPyZVqLZeRN5ggsuuEBtg+PqAYHahgGLyIVJA91du3apqUNZZtxWMoI18+xoPH5+LMJ9jUgtqMT936Tgud8yUVzR9tEyInI8GfmWXUvIvhiwiNyArDLcvHmzZvVZwxP88NpliZjQo64vzPLd+bj9syT8cbRYg7Mlah0ZqS2pqHbIYY+WkbfffjuuuOIK/Oc//1H7BEoPPNm8WN442Y6GyV57ckgz4vj4eMyZM6fe+Uifp5kzZ6Jz584ICwvDmWeeqab7Go6cLV++XDXflr6NsjdqU9auXYuhQ4ciODhYbUC9Y8eOep//7LPPMGjQIPU4PXr0UD0gbck04xdffFHvNnl+OQ8hPankPsuWLcOFF16I0NBQtZOKbCFmS+7frVs39fkrr7xSrax2JS7VyZ2ITk7qs6SPljRnlF/YDZvqtYSfyYB7z4jC2Z0DsOiXTKQWVuLhVak4r0sA7hoegUDv1j82UWuUVtZg0JN1u3C0t00PjYavSft/87KriLe3N7799lsVPP7+97+rQCEhyuK9995TW7r9/PPPakXxPffco36+b7nlFvX5adOmqZHsd955R20m//nnn2PixImqzYtlW7iSkhI888wzeOmll1QIi4iIaPKcHnroIbXriQS6Rx99FJMnT1btYqRRp4yW/+1vf8PDDz+Myy+/XIWie++9Vz1mczZntvXvf/9bbW0n5yjPI9+jhDmj0Yg//vgDd955Jx577DH1vaxcuRJPPPEEXAlHsIjcjNb1WQNifPHKpYm4vG8w9Drg+wOFqjZrR0apZudM5KlkA+ZXX30VvXv3xrhx4zB79mwVgmyn8GTUat68eejevTuuueYa3HXXXXj++eetW8RJsJIQNmrUKDWKJYFr5MiR6nYL6Yr/7LPPYsSIEepxTrYllwSs8847D3379sVrr72m3rhJaBPPPfcczjnnHMyaNUuNLkmokiC0cOHCFn/v9913n/qe5XHk+5bv5cCBA+pzL774ohq9mzFjhvr8lClTMGbMGLgSjmARuXl9VnJysnqHKMP5reVt1OOOYRE4q1MA5q1Jx9H8Ssz4Ohm3DQnH5L7BqkieyN58vPRqJMlRz20P/fr1qxd2hg8frnZwkCk8GYkWMn1m+zMm95GwJLVUMuIjl6eddlq9x5VpQxkJsw1y8lzNIY9vIY8hgWzPnj3qulxedNFF9e4voe2FF15Q59GSUfO+fftaP7YU/8sIvEw7yvPIyFXD81q1ahVcBQMWkYfUZ0l9h7y7lemItmy388LERCz6NQOrDxapLvDbM0px/5lR8DdzypDsS0KGPabptCZ72jXWFFjaH2i9352EMQk1v/322wnhxnY/U6l5aq83QpZ9VW3JCFpDMuVoYTk3dyq+5xQhkYew7Z/Vll9i8k5eVhpOHREBL70OvyUVY8oXR7E/m81JiYRMaW3ZsuWE2+U2+ZwtqW0qLf1rul1qj/z9/VWNlYXsTWpL7iOj0hKoBgwYoEaO5Oe7S5cu9Y7WtoSQx7fIzc3Fvn371KiSkEspgrcl1+X7sgQ8qe9KT0+3fn7//v2qBqwl5Hka+75dCQMWkQfWZ8kvrrZsuyPvNi/uFYyFF8Ujyt+ItMJK3Ls8GV/tzrfLaisiV3LHHXeoUDJ9+nQVoPbu3aum9D766CNVEN5wKl9qmGQ6f8WKFaqQW67r9X/9eZbpwgcffFA9zocffoiXX35Z1SQJCTZXX301brvtNrUqz/LzLTVb33zzTavOXwrPV69eraYf5XuRAnbLdJ2cv3xO7iPf4//+9z+88sorqp7K4uyzz1a3SaCUonxZGWk7WtUcd999typsl9ouCWjyPbvS9KBgwCLyQPKOWVYDyS+utnSD7x7ujZcuSVRb7cgehs/+lon/rslQq72IPFWnTp1UGJBANGHCBNXq4NNPP1WF6FK4bWv06NFqNOr8889XBeNyf1mhZ+u6665T7Vek/YIUsEu4uvXWW62fX7x4sbqPtGqQWixpaSArCG1HwVri8ccfV41SpVBeRqLk3KWGS0ibBwlVH3/8MQYPHqxW+UmBuu0KwqeeekoV5ktR+k033aTC18mK6hsj9VZS7C/F7lKD9v333+Of//wnXImulm8320xGAqSAWHqByDw3kSsxm83o2bMnQkJCWv0Y8mvk4+15eGNDluoC3yHYhNnnxiAxuO6XMlFLSfCXuh0p9JZ/o+5I+mBJXZaElaZIIJPQJG0TqHWk4F9aYMgoWsM6Nalhk6AojZq1ro/jCBaRh5NfPlu3blWrdqqqqlo9ZXhlvxDMGxePUB8DjuRV4J4vkvDDgdZPQxIRuTIGLCJS0tLSVBF8W7ol94v2wcuTEjEgxgdlVbV46qcMtc1ORTWnDInIs3CKUAOcIiR3Iy0dpC7EUnfRUtU1tfjflhws3ZID+QXTLcyMh8+NQUxAywpdyXN5whQhtQ9OERKR05Al37IkurWd4A16HW4cFIYnLohFoFmPfdnlmPJ5EtYmFdnlfImInA0DFhE1SuqxZOn49u3b1TvA1hga76dWGfaK8EZRRQ0e/S4Nr63PQpVUwhMRuTEGLCI6KanJktEsqdFqzWhWpL8X5o+Px6V9gtX1j7fl4sFvkpFV3LqCeiIiV8CARUTNqoeRVYay2tC263RzeRl0uGt4BGafGw1fLz22Z5SpVYZ7jrH7OxG5JwYsImo26dkjXaJlA+nWjGad2TEAL16SgE4hJuSUVuP+r5Pxy2HWZRGR+2HAIqIWkX0MpQO8jGa1pjYrLtCEBRPiMTTeF+XVtXjshzR89GcOt9ghIrfCgEVEbRrNak3fLD+TAY+NicUlvYLU9dc3ZGPRr5ksficit8GARURtWmkom9nKpq8t3dNQWjlMGRGJu0+PgF4HfLO3AA99m4LC8tbvjUjkiWRj5R49eiA4OFjtVyhvfMjxGLCIqM1SUlKwceNGFBcXt/hrJ/UOxpwxsfAx6rAlrRT3LT+KtIJKu5wnkbuRfQxlE+R//etfWLt2rdq3cOLEiaqXHTkWAxYRaaKkpAQbNmxAampqi+uphif4YcGEBIT7GXE0vxL/WH4UOzJavlqR3Jz8u6oodszRihpBGUmSzZplI/X+/furNyFLlizB5Zdfrtl/kueeew4333wzbrjhBvTq1QvPP/+82lHk7bff1uw5qHWMrfw6IqITSLDau3evqsvq2bOn2pqiubqEmfH8xQl4ZFWq6vz+4IoU3D8qCud0CbDrOZMLqSyB94LODnnqsukHAZNfs+8v+3qOHTsWs2fPxksvvYSHHnoIc+fOxc6dO7F06dJ69/3vf/+rjpPZtGkTEhMT691WUVGBzZs344EHHrDeptfrce6556redeRYDFhEZLfmpL1791bv3psrzNeompI+/VM6fksqxtyf0pFSUIHrBoRCp9PZ9ZyJtCTTdpdddhmmT5+url955ZW48cYbcdFFF2HAgAH17nvbbbdh8uTJJ3282NjYE27LyspStY+yd6gtuS5968ixGLCIyC5ko15p5SDvujt27KjeWTeHj5cej5wXg9fXZ+GT7Xl4Z3MOUgoqMW1UJEwGVjV4NC/fupEkBz13c0mfOBnBkhErC6PRqEZ4ZUSrodDQUHWQe2HAIiK7SkpKQk5ODvr06aNqQ5pDr9PhjmERqmfW82sz8f2BQmQUVeLR82IR5G2w+zmTk5JRzBZM0zmKZfRo4MCB1ttkpe2QIUPQt2/fE+7f2inC8PBwGAyGEwra5Xp0dHQbvwtqKwYsIrK7oqIiVfDbvXv3Fv3in9AzCNEBRjyxOl1tr3Pvl0fx+AWxSAgy2fV8idoiPz9fBR/LtLa8wVi0aBH69evX6P1bO0VoMplUiFu9erVaOWhpBCzX77zzTk2+F2o9Biwiahfyi3/37t3qj40ELZkyaY7BcX5YNCEeD69KRWphpQpZMoU4IKb5UzZE7UlWDEpt1IIFC1Qd1v33348OHTqof/9HjhxRH2s1RfiPf/wDt99+OwYPHqxGyF544QW1oldWFZJjsaCBiNqVTF/IaJa8y2+uDiFmPHdxAnpFeKOoogazVqTg273N/3qi9tSlSxc88sgjePHFF3H66acjJiYGX375pRqFuuSSSzR9riuuuELVej322GMYPny4qnv8/PPPERUVpenzUMvparkBWJsVFBQgKChIDQE3t8aEiOr+EMXHxzd7hWB5VQ3m/5yBnw7VbRB99WkhuHlwGFcYuiEZAZKFEjLaYzabHX065MLKy8vVyKG0jZGp24blCzL6J2/4AgMDNX1ejmARkcMcOHAAO3bsUFvuNIfZqMes0dG4tn/ddMoHf+Zi3s8Z3MOQiJwOAxYROZT08pEO8PJOsrkrDG8aHIYZoyLVHobf7S/Eo9+lorSyxu7nSkTUXAxYRORwZWVlahuR9PT0Zn/Nhd2D8O/zYmA26LA+uQT/XJGC/DJuFE1EzoEBi4icgpSDyior6SEkKw6b4/REfzw9Lg4BZj12HyvDtK+Oqn5ZRESOxoBFRE4lLS1NNVUsLW3eZs+9I32wcEICIvyMSM6vxH3Lj+JQTrndz5OI6GQYsIjI6RQXF6u6LNnTsDkSg01YdFE8OgSbkF1SjelfJ+PP9OYFNCIie2DAIiKnnC6UZfrbtm3DoUOH1PVTifDzwoIJ8egT6Y1i6ZX1bQp+Ody8wnkiIq0xYBGRU5P+NdI8saKi4pT3DTAb8NTYOIxI9ENldS2eWJ2G5bvZkJSI2h8DFhE5vby8PDVl2Jzu79Ir65FzYzCueyCkPdZzv2Xif5uzmzUKRkSkFQYsInIJMoK1efNmJCcnnzIsGfQ63HdGJK4bUNeQ9J3NOXh+7TFUsyEpUZMuuOACtW+is+rRoweef/55uAoGLCJyKfv378fOnTtP2f1dts+5cVAY7hkRAdlIR6YK/7M6DRVVbEhK9iWbL8segeTZGLCIyOUcO3ZMNSaV1YanMrFXMP51TjS89Dr8cqQYs1amoqicDUnJczWnnpHajgGLiFyS9MmSkJWZmXnK+57VKQD/uTAWvl56bEsvxYyvk5Fd0rz9D8l5yNRwaVWpQw4ta/h+/vlnjBo1CkFBQejUqRMefvhh64js119/jejoaLWKVsgCDx8fH3Ufi7vuugs333yz9fqvv/6K8847DyEhIejatSumT59e782HTK3NnTsXt956KyIjIzFlypQmz03O47777kNUVJTaiH3OnDn1vvfc3Fz1ODExMQgNDcUll1yiRpUtnnjiCQwfPrzeY8q0npxDwxG+hQsXqu8/Li5OPads7m0hP9eTJ09W31PPnj3x/vvvw9UYHX0CREStJR3fZbqwoKAAnTt3hl7f9HvGATG+eGZ8PP61MgWHcitUQ9InL4xDQpCpXc+ZWq+sugxnfXqWQ557zeQ18DH6tPlxUlJSMGnSJFx//fVYsmSJ2rlAAo+3t7cKUWeccQYKCwuxZcsWDB48WIWx8PBwrFmzxvoYctuMGTPUxwcPHlQh59FHH8Wrr76qRnclYE2bNg2LFy+2fs2iRYswa9Ys/Otf/zrp+b333nu48cYb1XPIG5h77rkHCQkJuOWWW9Tn77jjDhWoPv74YwQGBqpzlu9H6iO9vLya/d9hzZo1KqStWLFCbfou/z1OO+20es8jTYfl8/K48v3K9+ZKOIJFRC5PCt+b08qhS5gZCy9KQFygFzKKqjBt+VHsyixrt/MkktAjI0MyeiOjOhMnTlQh5dlnn1VvGGRUq3///tZAJZdTp05V/75lQ3QJaBJIzjzzTPX5efPm4eqrr1b3kdGrESNGYP78+SooyR6fFmeffbYaJZI3InI0Rc5NHrN79+645ppr1GiZpbBcgtXy5cvx0ksvqRE4CURvvvkmUlNT8cUXX7Tov0NwcLD1v8H48eMxduxYrF69Wn1u3759+Pbbb/Hiiy+q0bBBgwbhlVdeafbuDs6CI1hE5BakhYO0cujbt696Z92UmAAvLJwQj4dXpWJvVjkeXJGM2efEYFiCX7ueL7Wct8FbjSQ56rm1IPttSmiQRRgWEookPMkbhcTERBVeZARJAtFvv/2Gxx9/HJ9++qn6OCcnR438SJgSf/75J7Zv344PPvjA+ngypSdh7fDhw2p6TchoWHMMGzas3rnJuUr4kylLOXej0ajuYxEWFqbCmIzEtUTv3r1hMBis12VadMeOHdb/RvI8EqwsJIhJKHMlDFhE5HatHLp164bY2Ngm7xfsY8S8cfF47Ic0bEwpwSPfpWL6qChc0K3pYEaOJ3/4tZimc3ZnnXUW3nnnHRWeZHpMwoWMWMlolvSEs4xeCam1kpqoxuqqZGrPwtfXt13OXabpG9arVdrUVllIgGr42jZ3k3dXwSlCInIr8st979696h31yX5h+3jp8diYWJzbJUA1JJ3/cwY++jOHDUnJrmREad26dfX+na1duxYBAQFqek5Y6rBkak5GsyyhSwKWHPKxxYABA9SIT5cuXU44TKaW1xeuX7++3vU//vhDjZbJaJOcuxTBy20Wsl+o/LxZRsqkXiwjI6Pe9ydBsSUkUMrzyKbvFvIcEi5dCQMWEbklKZCVX9C2dSgNeRl0ePCsKFzet27q4fUN2XjljyzUMGRRG8nCC6mbsj2OHj2qirdlKlCK0OVNwJdffqlW3v3jH/+wLtKQlXP9+vVT036WMCVBSwrfpT7JdgRLir9///13NZ0ozyF1UvKYcr015BwffPBBFWg+/PBDvPzyy9bRMQlaF110kbouKxclOElRuowWX3zxxeo+cr5SjP7MM8+oAnypnVq5cmWLzkGmHKXpqdSVSZiTn2OpBZPVlK7E5QKWFL117NhRrbiQuWHbJN0YWekgyVruL/9gZQmsrZtuukkNTdoeUmxHRK5P6lqkLkuWljdFr9PhjmERuGNouLr+2Y48PPVjOiqq3Wu6gtqXjDSdfvrp9Y4nn3xStSRYtmyZ+ncptUwSrGTV3syZM+t9vQQqqXuyBCxpidCrVy9VqyQBxEL+rkmAkWA1ZswY9TxSs3WyKfKTue6669SbEglxEgIlTMkUpG2R/sCBA1ULhdGjR6uRKvl+LCsI5e+t1Gy9+uqr6vuT77M1YU++XmrNJGhJEb+cQ0REBFyJrtaFxsMlTd9www0qEUu4kmWnEqDkXYD09mhICgLlH6f0/5DUvXTpUjz99NMqDUshrCVgyXCmrISwMJvN6h1ES96pyMoPOR9XS9hEnkKmTGQKxraAt6HvDxRg/poMVNcCA2N88Mh5MfAz/VWIS+1HwoXU7nTo0EH9TiZqrfLycrVpvIRA28J6y5swWQAgi2ROtjjG7UewFixYoBqUSYM1WYEgQUsK9954441G7y8pWkajHnjgAZX8JdXLqoQXXnih3v3kh1feFViOloQrInINsrRdemZZGjg25rwugXj8glh4G3XYnFaKB75JQW4pG5ISkRsHLFkdJE3PZAjUQuar5boUCDZGbre9v7jwwgtPuP+PP/6oRsCksE7meaVo71RpWEatbA8icp0tdkpKSpq8z5A4P8wfH48gbwP2Z5fjvuXJSCng1iJE5KYBKysrS73zlPb9tuR6enp6o18jt5/q/jLCJcthv//+ezV9+NNPP2HcuHEnfZcrU44yJWg5bJfCEpFzk3AlIUt+pzSle7g3Fl0Ur3pmpRVWqpC1N4sNSYnIDQOWvUjxnHTSlUJBafcvXWplmaqMajVFthuQ+VrLIasuiMh1yBsoac546NChJtsyxAWaVEPSrmFm5JdV4/6vk7Eh5dSbSxMRuVTAkt4aUpwmBem25LrUTTVGbm/J/YVsISDPZbt5ZUNSsyXFcLYHEbkeKXzdtm1bo40QRaivNCSNUwXvZVW1mL0yVRXCk/1ZFiO40DosclK1x/8NnWyBi0cHLGmYJpX+MpVnIU0E5bpsM9AYud32/mLVqlVN3l9IfxKpwZLloUTk/mTrEVlKLo0dGyOrCKXwfXQnf7W68OmfMvDJ9qbbPpA25I+h/GE8WR8zouaQf0Pyb6m9A5ZLbZUjO4RLv5AhQ4ao/hrSFkG2CZBVhUJaOEiPEamREvfee6/a4FIank2YMEE1bZNfpJYdxmV55pw5c1Q/DxnVklVG0mBNmqlJMTwReQZZuCLtW6S/UGNvrkwGPWaOjkaIb5bqk7X4jyzklFThtqHhqo8WaU/+GMpCJlmYIKSXYXv/gSTXVns8oMu/Ifm3xIB1EldddZX6D/XII4+oQnXZImDFihXWQvakpCRrJ1wxcuRI1ftKdip/6KGH1P5k0hDN0gNLphylE+3bb7+tWvBLYzZpaibtHNh3hcjzfhlLTz2pq5TfFQ375UiQunNYOMJ8DKrj+yfb85BTWo0Zo6JUR3iyz8yFrCCX0g6GK2rtz7XkgtZsG+RRjUadFRuNErkX6a8nb8Sa2iB31b4CPPNLhtrDcHCcLx45N0btbUj2IX+mLAdRc9nu0NIUezYadakRLCKi9lBaWqrKCaRBcWPbc5zfLVD1yXp8dRo2ppSoFYaPnx+riuJJe6f6I0nkjPiWi4ioARkpkUU0O3bsULWZ8nFDwxL8MG9cXUPSfdnlmPrlURzILnfI+RKR82HAIiI6Celzt2XLFlUI31DPiLqGpPFBXjhWXIVpXx3F2qQih5wnETkXBiwiolOQFg4yZSiLYRprSPrsRQkYGFvXK+vf36Xhoz9zWC9E5OEYsIiITkHCkjQjlZEsWa3cMDwFmA34zwVxuKhnEOQzsspwwS+ZqJTGWUTkkRiwiIha4ODBg2qbnaqqqnq3G/U6TB0RgbtPj4BeB3y7rwAzv01R2+wQkedhwCIiaiHZ7UGmDGWJty1Z6TapdzAeGxMLXy89tqWX4h9fHkVSXoXDzpWIHIMBi4ioFaRD9MaNG5GWltboCkMpfo/2NyKtsBL3Lj/KjaKJPAwDFhFRG7u/7969G9XV9acCO4aY8dzFCegb5Y3iiho8vDIVX+w8sUieiNwTAxYRURvJ1l0ymtVwyjDYx4inxsZhTNcA1fX9hd+P4YW1maiWK0Tk1hiwiIg0UFJSokJWcnJyvVWGslH0A2dG4ZbBYer6F7vy8fCqVBRXsPidyJ0xYBERaUSC1f79+9Um8rJJsW3x+9X9Q9WehWajTm2vc+/yZKQWsPidyF0xYBERaSw3Nxd//PGHWm1oa1RHfyycEI9wX6NaWSgrDP9ML3XYeRKR/TBgERHZgfTJ2rZtG/bu3VuvAL5rmDeen5iA7uFmFJTXYOaKZKzcV+DQcyUi7TFgERHZUWpq6gk9s8J8jZg/Ph5ndfRHVQ0w/+cMvL4+i8XvRG6EAYuIyM5KS0tVAbxsHG0pgPc26vHQOdG4bkCouv7RtlzMXJGCrOL6HeKJyDUxYBERtQMJVgcOHMDWrVtRXl6ubtPrdLhxUBhmnR0Nb6MOW9NLceeyI1ibVL/dAxG5HgYsIqJ2lJeXpwrgs7KyrLed0yUAL12SiK5hdXVZj36Xhpd+P4YKmT8kIpfEgEVE1M6k6F02jJYu8JYC+Pggk9pe57I+wer6sp15qpXD0Xy2ciByRQxYREQOIvsYrl+/HoWFhdampHcOj8AT58ciyNuAAznluPvzJHy7N79e81Iicn4MWEREDt40etOmTUhKSrKGKNks+pVJiRgQ44Pyqlo880smnvopnd3fiVwIAxYRkYNJsDp48CA2b95sbecgrRzmXhiHmweHQa8DVh8swl3LkrD7WJmjT5eImoEBi4jISRQUFKieWbLaUGqzDHodrukfigUT4hHlb0R6URWmLT+Kj/7MQQ2nDImcGgMWEZGTkX5Ztlvt9I70wcuXJOLsTv6orgVe35CNh75NRU4Je2YROSsGLCIiJyS9smSrHVltKB/7mw14aHQ0pp0RCbNBh02pJbhzWRI2JBc7+lSJqBEMWERETkz6Za1btw7Jycnq+rgeQXhhYgI6hZiQV1aNh1amYvEfx1ApQ1tE5DQYsIiInFxNTQ3279+v6rOkpUOHEDOeuzgBF/cMUp//ZHsepn11FCkF7JlF5CwYsIiIXERxcbHa03Dfvn0woAZTR0bi0fNiEGDSY29WOe5eloTPduRx02giJ8CARUTkYlJSUtS0YWZmJkYm+uHlSYnoG+WN0qpavLzuGO76PAlb00ocfZpEHo0Bi4jIBVVWVmLnzp2qED7AUIV54+Lxj5GRCDDrcTi3Ag98k4L/rE5DZlGlo0+VyCMxYBERubDc3FzV0iEl+SjGdw/Am5d3VLVZ0pz0p0NFuPX/jmDplhxuHE3UzhiwiIhcvAu8pRO87GtYXVKgarNenFg3bShb7by1KRu3f5aEtUlF3NOQqJ0wYBERuYnS0lJs3bpVbbkTZijFM+PjMfPsKIT5GpBWWIlHv0vDv1amIjmfqw2J7I0Bi4jIzeTn52PLli0qbA0Or8WSyR1xVb8QGPXAhpQS3PHZEby+PgsllZw2JLIXBiwiIjeVl5enRrP27dyGK3qYsPjSDhga7wspx/poWy5u/fQwvj9QwGlDIjtgwCIi8oCgtWnTJuQc2Y1/nh6AOWNiEBPgheySajz9UwZmfJ2MA9nljj5NIrfCgEVE5OYsI1Q5OTkqaPnnH8KC80Nx06AwmI06bM8ow5QvkvDcb5koKKt29OkSuQUGLCIiDyNBa9uWTTjNmIrnx0bg7E7+kObvy3fn4+ZPD6u2DgxaRG3DgEVE5KEjWtnZ2Ti8czMuicjG4+eEoWOICYXlNaqtw3UfHlIjWke54pCoVYyt+zIiInKXoJWVlSX/h6ndI5GECHy1vxT7s8vViJYcwxP8MLlvMPpH+0Cn0zn6tIlcAgMWEREpOVnH4Febibs6hyO/VwRWHqnGuqPF1qNzqAmT+4RgdOcAeBkYtIhOhlOERETUoBg+G1WpuzDW7zAeO92I8d38VTH8wZwKzPs5A9d/dAjvb2WdFtHJcASLiIgaDVoVFRVA5hEMADC8Twh2lIfg+6Qq1d7hzY3Zqhj+/G6BuLRPMBKCTI4+bSKnwoBFRESnVF6Yi67IRbc4I1L0UViT6YWDuZWs0yJqAgMWERE1W211FWKrU3BVMJAVGowNhYHYkll9Qp3WWZ1kWpFVKOS5GLCIiKjFZJAqojYP4/zzMMLbC9sqwvHHMb21Tuu5tZkYGueLkR381ehWgNng6FMmalcMWERE1CbBxkqc5ZWOIWZge2kwNhX4IrusFr8cKVaHXgc1dShha2QHP0T4eTn6lInsjgGLiIg0KYz3MQBD/XMxxC8XGRVeOFQZiD3F3kgtBjanlarjxd+PoXu4GWdI2Er0Q2KwiTVb5JYYsIiISFOSl6LNlYg2Z2OEP5BTacD+Ul8cKPPH4SI99maVq0NWIsYFetWFrQ5+6BnhDT3DFrkJBiwiIrKrUK9qDPMqxLDAQhSF6rGvxBsHyvxwsNiElIJKfLQtVx2hPgaMSPRTU4n9Y3xgMrBInlwXAxYREbUbf2MNBgaWqKOiVo/9xea6wFXig5zSany1p0Advl569I3yRo8Ib/QI91bTisE+/JNFroP/WomIyCFMuhr09i9VR3VtLo6UmlXN1r4SHxRVAn8kl6jDItrfaA1cctk1zAwfL45ykXNiwCIiIoeTrQ07+5arY2xtPtIrTEgu80JauUkd2ZVGpBdVIb2oCD8dKlJfI6sTOwSbVNjqHu6NnhFmdAwxwyifIHIwBiwiInIqUuceY65QB1Csbiur1qnQlVrmhdTjoauw2oBDuRXqWLG3QN3PZNCpka26Ua66wBUd4KWmHInaEwMWERE5PW9DLTr6lKvDorBKj7QK8/HQVTfaVV6tx87MMnXYCvI2ICbACzEBRhW4YmyOMF8jDBz1Io0xYBERkUsKMNYgwFiK7r6l6rrsUZ1TaURauWWUy0tdL60xIL+sWh27j534ODK4FeXvVS94WT8O5OgXeUjAevHFFzFv3jykp6ejf//+eP755zFs2LAm7//xxx9j9uzZOHz4MLp164ann34a48ePr9cc79FHH8Vrr72GvLw8nHHGGXj55ZfVfYmIyLWmFsNMVeroG1AXukRZjQ75lUbkVhmQX2VEbqUBuZVG5FUakV9lQGWNDskFlepojASsYG8DAr0NaiQs+PhlY4d8ztuoY/NUannAmjRpEh577DGcdtppaG8ffvghpk+fjldeeQXDhw/HokWLcOGFF2LPnj2IjIw84f6//fYbrrnmGsydOxcXXXQRli5dqs5/06ZN6Nu3r7rPf//7Xzz33HN4++230alTJxXG5DF37twJb2/vdv8eiYhIW976WnibKxFlPjFA1dTKVKNBhS8JXHlVclgCmEGNfpVU1qgjtbDxANaQ1IEFmg0I9vkreAWY9GrFoxzeRrnUqeBW93HddR/rx3qYjTo2XXVxuloZwmmBxYsXqxGkAQMGYM6cOejdu7e6PSkpCePGjcOOHTvsda4qVA0dOhQvvPCCul5TU4OEhARMnToVM2fOPOH+V111FYqLi7F8+XLrbaeffro6dwlp8q3HxsZixowZuP/++9Xn8/PzERUVhbfeegtXX311s86roKAAQUFBeGHBf+Hj46PZ90tERI5VVgOUVBtQUqNHabUeJcePMgle1cdvs3yuRo+qWu1CkYyEqQB2PHiZjDp4GXTw0ttcWj4+ft1o0KmAV3cdakWl7eflUoKbXi8rN3Wq9kxWcKpLWc2pl88fv64+3/A2Wb1Zd11nvay7zRUVFRVh0PBR6m9/YGCgY0ewBg8erELVZ599pg6ZnvP19VUjPhJW7KWiogIbN27ErFmzrLfp9XqMGTMGa9eubfRr5HYZ8bIlo1PLli1THx86dEhNNcpjWEhQkiAnX9tUwCovL1eHbcAS12c+jkCza/4jIyKiVpISLXuWaVUdP1qoRv526nSo0AEV0KFSV3dU6YBq6FB9/FKuy32rdDpUA6g+fin3LTt+vcrmdrmfjMzI19Sor9Wpj+U2ecza49dr1Md1z2H5WN1uc90ywiO3qevHb7ecf919JMX9dX/L7RbyeUuutX3M+vdp5PM6HcpL5dHso8UB6/rrr0evXr3w/vvvw2g0Yvfu3XjmmWfU9NrKlSvtc5YAsrKyUF1drUaXbMl1OYfGSHhq7P5yu+Xzltuauk9jZMpRRu+IiIhaSsJKiV6HEp2+3mWxXo8Sna7Rz5Xo9ShVYanuqJTQJB/Dcv14kLJ+XoIT3/CfSrVeIqOTBCwpFv/yyy/RpUsX621///vfce211+KBBx7A66+/Dncno2i2I2MygiVTle9GzuYUIRGRh6hBDcpRjhJdGUp1pSiFXNYdJfWul6IcFajUVcr/o1pnvz/qJ2OoNUBv/Z+u7rJWPjr+sfXy+G21f92ms7lNhpMs/4PtZe2J13XHP4btx0rdkF/d16iPbC4tw1F1X1HvtuO3W27T2YxIyTX5WKduOP6x5Uus52W9Qakqq8Qu7HKOgCXTZ59//nm9gBEaGopnn30WgwYNslvACg8Ph8FgQEZGRr3b5Xp0dHSjXyO3n+z+lku5LSYmpt59pE6rKWazWR0NVelN6iAiItdVjWoU6gqRL//T5aNEV3I8QJXWu5RwVVv317xVJKyYYIKX/K/WC146L5hhhklngllnhllfd3jrvdUhH3vpvayHUWeEyWBSH5v0phM+tlw3G8zwMnipv6GqbkqvV5e2h/DElY9FRUX4BIudI2BJm4PRo0dj27ZtuPPOOzFw4ED1onzyySfw8/ODvZhMJlX/9f3336uVgJYid7l+zz33NPo1I0aMUJ+/7777rLetWrVK3S5kWlNCltzHEqhkNGrdunW466677Pa9EBGR49SiFmUoU+GpQFdwwmUhCusNmJyKudYMH/jAV+cLP50f/PX+CDAGqCPQGIggUxACTYHwNfrC18tXXfp5+cHsZVahRwKPHOReWhywpKj9hx9+UCvvJKhIuJJ/IFVVVXj88cdhTzJqduONN2LIkCHqPKRNg6wSvPnmm9Xnb7jhBsTFxakaKXHvvffi7LPPVjViEyZMwAcffIANGzaolZBCzl3C1xNPPKH6XlnaNEixviXEERGRa4aoAhQgT5fXaJCS6bqTMdYaEYxghBhCEGIMUUEpwCsAQV5BCDYFqyPEOwQhPiHwMfkwIJE2jUal1cGvv/6KlJQU7Nq1Sy1vlBEg27ose5C2C8eOHcMjjzyiitDlOVesWGEtUpdWEbb/yEeOHKl6Xz388MN46KGHVIiSFYSWHljiwQcfVCHtjjvuUI1GR40apR6TPbCIiFxHCUqQoc9Ahi5DXWbqMlGmq79dTkP+8EeILgThXuGIMkUhyicKsb6xiPePR4RfhBo8IGq3PljUdB8sGVFjkTsRkX1VoEIFKEugytRnqpqpxoq6Q/WhCDeGI9IUiUjvSGuAiguIU7VJ5NmKiopU+ZFT9MEiIiJqz4LzLF2WNUjJZY4up9EaqQh9BDqaO6Krf1f0Ce2DLkFdVKE3kSMwYBERkVMFqhRdCg7rDyNdn45jumOo0Z3YDDJIF4SO3nVhqndIb3QP6q6Kx4mcBQMWERE5VCUqcUR/BAf1B1WwKtf9tVOG8NH5qJGpbgHd0DO4J7oHdkeIKcRh50vUHAxYRETU7qSX1CH9IRWqkvRJ9Zpv+un9MChgEAaFD1JhKsoc5ZE9msi1MWAREVG7kLYJBw0HcUB/AGm6tHpNOqUQfVjoMIyMGInuAd1h0HEFH7k2BiwiIrJbLyopUJdRKjmy9Fn1Pt/BuwNODz8dw0OHI9E3kaNU5FYYsIiISNNQJaNTMkolo1XS2NNC9oLrFdALw8OGq9GqSHOkQ8+VyJ4YsIiIqM2qUIW9+r3YYtiCbH229XbZX29A8AAVqIaEDEGgl7a9hoicFQMWERG1qVh9m2Eb/jT8qTZAFrIxsUz7ydE/uD+8DdwZgzwPAxYREbWYNPvcbNiMPfo91hWA4aZwjI8ZjzGRY+Bn9HP0KRI5FAMWERE1u74qWZ+MTYZNqrWCRVe/rpgYO1GNWBn1/LNCJPiTQEREzauvMm5Btq6uvkoPPYaGDsXEmInoEdCDKwCJGmDAIiKik9ZXbTduRzGKrfVV50Wep6YCo72jHX2KRE6LAYuIiE6or9rqtRW7dbvV6JVgfRVRyzBgERGRkqHLwAbzBhysPVivvuri2ItxeujprK8iagH+tBAReTiZClzvvR5/1v6J2tpa1RBU+laxvoqo9RiwiIg8VA1qsMdnD37FryitqethdVb4Wbgq4SrWVxG1EQMWEZEHyvLJwk/Gn5Bakaqud/LthNs63YaegT0dfWpEboEBi4jIg1R6V2K973psLN4IVAD+Rn9cm3AtxkSNgUFncPTpEbkNBiwiIg9gNBuxP2Q/VuavRHlxuepjdX7U+bgm4RoEeAU4+vSI3A4DFhGRGzObzSiKKsJHeR8hIzdD3dYroBdu7XQrOvl1cvTpEbktBiwiIjcNVr7xvviy8Etsztisbgv1CsUNHW7AqPBRXBlIZGcMWEREbhasYhJjsKZyDb5K+QpVtVUw6oy4KOYiXB5/OXwMPo4+RSKPwIBFROTiLKNRiYmJSPJLwn+S/oOcyhx128Dggbil4y2I9Yl18FkSeRYGLCIiFxcUFAS/RD8sSV2CXem71G1R5ijc3PFmDAkZwulAIgdgwCIiclFGoxFdu3bFn/gTb+57ExU1FTDrzbgs7jJMjJ0Ik97k6FMk8lgMWERELig2NhYRCRFYkrQEa3PWqtv6B/XH3V3uRrg53NGnR+TxGLCIiFyIr68vevTogTR9GmbunImsiizVIFSahcqolV6nd/QpEhEDFhGRa9Dr9ejUqROiY6Pxedrn+PDoh2ovQam1mt59Orr6d3X0KRKRDQYsIiInFxYWhm7duqFYV4wndj+B7QXb1e1nhp+JOzrdAV+jr6NPkYgaYMAiInJSJpNJBauIiAhsyN2AF/a/gMKqQnjrvdXGzKMjRnOFIJGTYsAiInJC8fHx6NixI2r1tVhyaAm+Tv9a3S7b20zrNg1xPnGOPkUiOgkGLCIiJ+Lv76+K2AMCApBSmoKFexfiUMkh9bkJ0RNwfYfr4aX3cvRpEtEpMGARETmYTPPJ0aVLF9V+QfyQ+YMauSqrKUOgMRBTuk5RTUOJyDUwYBEROZifnx969+6tWjCUVJXg1YOv4pfsX9Tn+gb2xb3d7kWoKdTRp0lELcCARUTkQLJ/oNRaSRuGfYX7sHDfQmSUZ0APPa5OuBqT4iapPldE5FoYsIiIHLRCUEatgoODUVNbg2Upy7D06FJU11Yj3BSOad2noWdAT0efJhG1EgMWEVE7k7YL3bt3h5eXF0qrS9Wo1cbcjepzp4eejru63AV/o7+jT5OI2oABi4ioncg0oASrqKgoVdSeWZ6JubvnIqkkCV46L9zS6RacH3k+e1sRuQEGLCKidmq/0KdPH/j4+Kjrewr34Ok9TyO/Mh/BXsH4Z49/ontAd0efJhFphAGLiMjOOnTooA4ZwRJrjq3BSwdeQmVtJTr6dsSsnrMQbg539GkSkYYYsIiI2qGQXUgxu2zS/EnKJ+r60JChqgWDj6FuVIuI3AcDFhGRnQvZRXl1OZ4/8DzWZq9V1y+JvQTXJV7HFgxEbooBi4hI447sstWNFLJb5FTk4KndT+FA8QEYdUb8vfPfcW7kuQ49VyKyLwYsIiKNSCG7TAlaCtnFweKDaqWghCxpvfBgjwfRJ7CPQ8+TiOyPAYuISAPSjV26slsK2cW67HV4dv+zKK8pR5xPHB7q+RCivaMdep5E1D4YsIiI2sBoNKr2CyEhIdbbamtrsSx1Gf6X9D91vX9Qf8zoPgN+Rj8HnikRtScGLCKiVgoMDFThymw2W2+rrKnEKwdfwY/HflTXx0aNVQ1EWcxO5FkYsIiIWiE+Ph6dO3euNyUoTUPn7ZmHXYW71GbNEqzGRY9z6HkSkWMwYBERtYAEqp49eyIyMrLe7UdLjuLJ3U+q7W98Db5qSnBA8ACHnScRORYDFhFRM8nqwH79+sHX17fe7ZtzN2PBvgUoqS5BlDlKdWZP8E1w2HkSkeMxYBERNYOMWEl/K4Ohfi3VN+nf4I1Db6AGNegV0Eu1YQj0CnTYeRKRc2DAIiI6CWkc2rVrV8TGxqqPbVcKLj26FP+X8n/q+jkR56gGol76us7tROTZGLCIiE6yl2Dfvn3VakFbVTVVaqXg6mOr1fVrEq7B5LjJ9QIYEXk2BiwiokZIXyvpym7ZS9CirLoMz+x9BpvyNqmVgjJqNSZqjMPOk4icEwMWEVEjXdk7dOhwwohUQWWBWim4r2gfTDoTpnefjqGhQx12nkTkvBiwiIiOkwJ2aRwaGhp6wuek/cLjOx9Halkq/A3+mNVrFnoG9HTIeRKR8/urQ56Ty8nJwXXXXadqIYKDg3HrrbeiqKjopF9TVlaGKVOmICwsTG3COnnyZGRkZNS7j7xDbXh88MEHdv5uiMjZBAQEYOjQoY2Gq8PFh/HQtodUuAo3heM/ff/DcEVE7hGwJFzt2LEDq1atwvLly7FmzRrccccdJ/2aadOm4csvv8THH3+Mn376CampqbjssstOuN+bb76JtLQ06zFp0iQ7fidE5GxkheDAgQPh7e19wud25O/A7B2zkVuZiwSfBDzZ90nE+8Y75DyJyHW4xBThrl27sGLFCqxfvx5DhgxRtz3//PMYP3485s+fr345NpSfn48lS5Zg6dKlOPfcc61BqlevXvj9999x+umnW+8rI2LR0dzhnsjTyIi1dGWPiopq9PNrs9fi2X3PorK2UvW4mtlzJvyN/u1+nkTkelxiBGvt2rUqBFnClRgzZozasmLdunWNfs3GjRtRWVmp7mchv0gTExPV49mSacTw8HAMGzYMb7zxhupvczLl5eUoKCiodxCRa5ENmgcPHtxkuFqRvkKtFpRwNSxkGGb3ms1wRUTuNYKVnp5+wr5fRqNR1UrI55r6GulhI8HMlvwytf2axx57TI1wydYXK1euxN13361qu/7xj380eT5z587FnDlz2vx9EZFztWAQ8gbrg6Mf4JOUT9T1C6IuwG2dboNBV7+DOxGR0wasmTNn4umnnz7l9KA9zZ492/qx1GAUFxdj3rx5Jw1Ys2bNwvTp063XZQQrIYH7jhG5Amm/IG0YGmsKWl1bjcUHF+O7zO/U9avir8IV8VewgSgRuVbAmjFjBm666aaT3qdz586qPiozM7Pe7VVVVWplYVO1U3J7RUUF8vLy6o1iySrCk9VbDR8+HI8//riaBpQphMbI7U19joick5QUyKiVlAM0pry6HAv3LcT63PWqgejtnW9Xo1dERC4XsCIiItRxKiNGjFBBSeqqpGZC/PDDD6ipqVGBqDFyPxn+//7771V7BrFnzx4kJSWpx2vKli1b1PQBAxSR+/Dx8UG/fv1UKUBjCisLMXfPXOwp3AMvnRemdZuG4WGN/24hInKbGixZ+Td27FjcfvvteOWVV1Tx+j333IOrr77auoIwJSUF5513Ht555x1VrB4UFKR6ZclUntRqSf+sqVOnqnBlWUEoLRxkREuuy/JsaQHx5JNP4v7773fwd0xEWpERK1ngInWbjckqz8Ljux5Hcmky/Ax+aqVg78De7X6eROReXCJgiffee0+FKglRMtQvo1LPPfec9fMSumSEqqSkxHrbwoULrfeVKb8LL7wQL730kvXzMsL14osvqn5ZUtjatWtXLFiwQAU5InJ9UmIg9ZFN1VAllSSpcJVTkYNQU6haKZjom9ju50lE7kdXe6qeBHRKUuQuI2aLFi1SUxFE5FgyWiVb3sh0f1N2FezC3N1zUVxdjDifOBWuIsynLlkgIvdRVFSkSoqkd6bMdHnkCBYRUXPItlh9+/ZttCu7xfqc9ViwdwEqaivQw78HZvWchQCvgHY9TyJybwxYROQ2ZIVwt27d1KbNTfku4zu8evBV1KAGg0MGY0a3GTAbuKiFiLTFgEVELk9qrCRYxcTENFlvJdUQn6Z8ivePvq+unxtxLu7scicbiBKRXTBgEZFLk8UqMiUodZBNkQaibxx6AysyVqjrl8VdhmsTrmUDUSKyGwYsInJZEqqkmF22xWpKRU0Fntv3HNbmrIUOOtzS8RaMjxnfrudJRJ6HAYuIXJK0X+jUqZNqxdKU4qpiPL3naewo2AGjzoh/dP0Hzgg/o13Pk4g8EwMWEbkUKWCX5sNNbXljkVuRiyd2PYHDJYfhY/DBgz0exGlBp7XbeRKRZ2PAIiKX4efnp+qtTtVvLrU0VTUQzSzPRLBXMP7V61/o7Ne53c6TiIgBi4jcpgWD2F+0H//Z9R8UVBUg2hyN2b1nI9q76Q3eiYjsgQGLiJyarPTr3r27asFwKpvzNmP+nvkoqylTI1b/6vkvBJuC2+U8iYhsMWARkdMym81qSjAg4NRd1tccW4MXDrygWjJIrZXUXEntFRGRIzBgEZFTCgsLQ8+ePVWfq1P5IvULvH3kbfXxGWFnYGrXqfDSn/rriIjshQGLiJxO586dVRuGUzUCramtwf+S/ofPUz9X1y+KuQg3drgRel3TrRuIiNoDAxYROQUJU1LALo1DQ0JCTnn/qpoqvHTgJfyU9ZO6fn3i9bgk9hJ2Zycip8CARUROQeqsJFxJ3dWplFaX4pm9z6iidj30uLvL3Tgn8px2OU8iouZgwCIil+jKbnGs/Bie3P0kkkqSYNKbcH/3+zE4ZHC7nCcRUXMxYBGRw0igkq7sERERzbq/9Liau3su8irzVAPRWT1noat/V7ufJxFRSzFgEZFD+Pr6qhYMctkcv2f/jmf3P6s2b070TcRDPR9ChLl5wYyIqL0xYBFRu4uPj1crBZszJVhbW6tWCb6b9K66PjB4IKZ3mw5fY/OCGRGRIzBgEVG7rhKUKUHpcdUcslLwtUOv4bvM79T1sVFjcUunW2DQnXy7HCIiR2PAIqJ2ERwcrMKVyWRq1v2Lqoowf+98bMvfplYK3tTxJkyImWD38yQi0gIDFhHZfeRKpgNlWrC5ParSy9LVSsGU0hR4670xrfs0DAkZYvdzJSLSCgMWEdmNt7e36m3VnL0ELXYX7sbTu59GQVUBwkxhqpi9o19Hu54nEZHWGLCIyC5iYmLQtWtXVXfVXD9n/YwX97+IytpKdPbrrNowhJpC7XqeRET2wIBFRJqRKUBZGdijRw9ERkY2++tkpeDHyR/jw+QP1fVhIcNwb7d74W3wtuPZEhHZDwMWEWlGpgJ79+6tpgabq7KmUu0puCZrjbo+MWYiru9wPTdsJiKXxoBFRJro2LEjOnTo0KLNlgsqC/DfPf/FrsJdaqXg7Z1vxwVRF9j1PImI2gMDFhG1iWzOLKNWQUFBLfo6WSH45K4nkV6eDl+Dr9pTsH9wf7udJxFRe2LAIqJWkzqr7t27w2hs2a+S7fnbMW/PPBRVFyHSHKlWCib4JtjtPImI2hsDFhG1iEwByiHBKioqqkVTglLMvjxtudr2prq2Gt39u2Nmz5kI8mrZ6BcRkbNjwCKiFpGpQFkl6OPj06KvK64qxosHXsS6nHXq+qiwUbi7y90wG8x2OlMiIsdhwCKiZpF+VtLXKjo6ukWjVuJQ8SHM3zNf1VsZdUa17Y3sK9jSxyEichUMWER0SrI5s0wJSkF7S8iUoGzUvOTQEtU8NMIcoYrZu/p3tdu5EhE5AwYsImqSFK9LsIqIiGjxaFNZdRleO/Qafjz2o7o+OHgwpnadigCv5m+bQ0TkqhiwiKhRUsAuU4JeXl4t/trk0mQ1JXi09Kjqb3VN4jWYFDuJzUOJyGMwYBFRPSaTSRWxy7Rga/yS9QtePvAyymrKEOwVjOndpqNPUB/Nz5OIyJkxYBGRVWxsLDp37tzivlaWLW/eOvwWVmSsUNf7BvbFfd3uQ4gpxA5nSkTk3BiwiEjtHdizZ08EBwe36uszyzIxf+98HCg+oK5PjpuMqxKugkFn0PhMiYhcAwMWkYdLSEhQ+whKG4bW2JC7Ac/ve151Zfc3+uPervdiUMggzc+TiMiVMGAReShfX181ahUYGNiqr5dO7EuTlmJZ6jJ1vZt/N8zoPkO1YiAi8nQMWEQeRtotdOjQAYmJidDrW7eqL7ciFwv2LsDOwp3q+vjo8bihww3w0rd8xSERkTtiwCLyICEhIar1gp+fX6sfY1v+NizctxD5lfnwMfio7W5Gho3U9DyJiFwdAxaRB5B9AyVYtbb1gqVx6PtH38dXaV+hFrXo4NtBdWWP9YnV9FyJiNwBAxaRG5PC9U6dOqn2C62dDhR/5v+peltllmeq62Mix+CWjrdwo2YioiYwYBG5qbi4OLU6sDWd2C2Kq4rxzpF31H6CItwUjjs734mBIQM1PFMiIvfDgEXkZrSosxLrc9Zj8cHFyKnMUdfHRo3F3zr8TdVdERHRyTFgEbkJLeqshBSvLzm0BL9m/6qux3jHqEL23oG9NTpTIiL3x4BF5OK0qrOqra3FL9m/4I1Db6CgqkBt0jwxdiKujL+StVZERC3EgEXk4XVWIrs8G68eehUbczeq67JCcEqXKeji30WjMyUi8iwMWEQeXGclo1arMlfh3SPvoqS6BEadEVfEX4FLYi9h01AiojZgwCLywDorkV6WrlovbC/Ybt3qRkatEnwTNDhTIiLPxoBF5CLBSqYCIyMj1VY3bSF7CEqzUGkaWlFTAZPehGsTrsX4mPEw6Fq34TMREdXHgEXk5BsyS7CKiIhoc7ASSSVJeOnAS9hXtE9d7xfYD3d2uRPR3tEanC0REVkwYBE5IamtkpWBMhWoRbCS1gufJH+ClRkrUVVbBV+DL27scCPOizxPk8cnIqL6GLCInEhAQIAasQoNDdUk+JRWl+LL1C/xeernKKspU7cNDRmK2zvdjjBz2+u4iIiocQxYRE4gMDBQBStZHahFsKqsqcSqjFX4OPlj1dNKdPHrgusSr0P/4P4anDEREZ1M67sStrOcnBxcd9116g9RcHAwbr31VhQVFZ30axYvXozRo0err5E/Wnl5eZo8LlFbWUKU/JsbMGAABg0apMmoVU1tDX4+9jPu3XIvlhxeosKV1FdN7zYdT/V7iuGKiKiduMwIloSgtLQ0rFq1CpWVlbj55ptxxx13YOnSpU1+TUlJCcaOHauOWbNmafa4RG0lwUpGrIKCgjR5POlntSVvC95Leg+HSg7VPYdXsOrCLnVWRr3L/KgTEbkFXa38ZnZyu3btQu/evbF+/XoMGTJE3bZixQqMHz8eycnJaouQk/nxxx9xzjnnIDc3V/1h0+pxLQoKCtQfykWLFqnl9EQNyciU/KhJ0XqHDh3UiKlW9hXuw7tJ72JHwQ51XQrYpVHoRTEXwdvgrdnzEBG5m6KiIgwePBj5+fma/l4WLvG2du3atSoYWUKQGDNmjNp3bd26dbj00kvb9XHLy8vVYRuwiE4WrqKiohAfHw9/f3/NHjelNAVLk5bi95zf1XXpwj4uehwmx01GgFeAZs9DRERuGrDS09NVg0VbRqNR1azI59r7cefOnYs5c+a0+nnJM3h7e6tQJeGqrXsFNtw38KPkj/BD5g+oQQ100OHsiLNxVcJViDTX//dMREQeGLBmzpyJp59++qT3kWk8ZyP1XNOnT683gpWQwO1FqE54eLjahFlGR7XsMVVUVYTPUj7D12lfo6K2Qt02JGSIWhmY6Juo2fMQEZGLB6wZM2bgpptuOul9OnfujOjoaGRmZta7vaqqSq0AlM+1Vmsf12w2q4PIwmQyqZq9mJgYzf9tZJVnYUX6CtV2oai6boVrj4AeuD7xevQK7KXpcxERkRsELNn+Q45TGTFihGqxsHHjRlWMJn744QfU1NRg+PDhrX5+ez0ueQ7pWyWjVTKtLLV7WpGC+J2FO/FN2jdYl7NOTQWKBJ8ENWIlI1fswE5E5LxcogarV69eqtXC7bffjldeeUW1U7jnnntw9dVXW1f6paSk4LzzzsM777yDYcOGqdukjkqO/fv3q+vbtm1TnbITExPVH8TmPC5RQwaDwTpaJXsFaqm8uhy/ZP+ipgEPlxy23t4nsA8mRE/AkNAh3JCZiMgFuETAEu+9954KPxKiZKRg8uTJeO6556yfl3C0Z88e1fvKQkKTbTH6WWedpS7ffPNN69TkqR6XyNJiQcK5jFbJqKuELC0dKz+Gb9O/xXeZ36GwqlDdZtKbcFb4WRgfPR4d/Dpo+nxERGRfLtEHy9mxD5b7hipZ/SerAOWQgKUlyzSgjFb9kfOHdRowwhyBsVFjVYNQtlsgIrIfj++DRdTeoUrad8hh2WZJ62nAn7N+xtfpX+NIyRHr7X0D+2J8zHhVX8VpQCIi18aARR7NEqqk/5kEKpn+07q9gu00oKwGlGlAablgmQY8O/xs1SCU04BERO6DAYs8NlRJHZVtqNJyFaBFZU2l2iNw9bHVWJ+zvt40oISqcyPO5TQgEZEbYsAijwtV0ghUgpW0WLBnqFqbvRbrc9ejpPqvhRf9AvupacDBIYM5DUhE5MYYsMjtQ5WEKEuo0rpflW2o2pq/Fb9l/XZCqAo1hWJE6AiMiRrDjutERB6CAYvcdh/AsLAwFahk+k/rtgq2oUpGqmQVYL1Q5RWKEWEjMDJsJLoHdIdep32oIyIi58WARW5BApRM+Umgkkt7tcuQUPVn/p/4Lfu3E0JViFeINVTJVjYMVUREnosBi1xy2k/4+/tbR6mkR5U9pv4ahiopVC+uLrZ+jqGKiIgaw4BFLkP6U1kClYxSyXV7kACXWpaKbfnbsD1/uwpXjYUqOXoG9GSoIiKiEzBgkVOPVkn9lAQqOWTfP3ttcJxRlqEC1Y6CHeoytzK33ueDvYLrhSquACQiopNhwCKnmfIzm81qyyHpni6Xfn5+dpv2yy7PxvaC7WqESi4zyzPrfd5L56Wm/PoG9VWtFboFdGOoIiKiZmPAIocFK6mbsgQqOSRg2Ut+Zb41TMmlTAHakvDU1b+rClMSqiRcSZd1IiKi1mDAonYZnTKZTGq6zxKmpEDdXqNTNbU1SC9Lx8Hig9hTuEeFqqSSpPrnBh06+3W2jlD1DOwJHwM36iYiIm0wYJFdWibI9F57jE5V1VQhuTRZhalDxYesR1lN2Qn3lSaflhGq3oG94W/0t8s5ERERMWBRq0el5GPpNyWjUXJIqJJDwpQ9itHLq8vVSJQlTMmlXK+srTzhviadSW2e3MWvC/oE9UGfwD4I8grS/JyIiIgaw4BFpwxSQloiSM2UBChLmJJVffaa5iusLERSaZJ1ROpg0UE1UmXZLNmWr8EXnfw6WQ+Z+ovziWNROhEROQwDlgdrGKKE0WhsdFTKHj2nSqpKkFaWpo7U0lTrx3IUVRU1+jWBxkAVoFSQ8u+MTr6dEOUdxV5URETkVBiwPDBESViSECUjUHJpe0jA0lJZdZkqOLeGp9LjgaosVa3sO5lwU7h1RMpyKRsn26sXFhERkVYYsFycJWw0DFGyaq+pEKXVxsfynIVVhcipyEF2RXbdUZ6trmeUZ6ggJR+fjDTwjPGOqTt8jl96xyDaOxreBm9NzpOIiKi9MWC5YHiSuicpJPf29q53aTnkeltDVHVtNfIq8qzByRKi1GX5X7c1VmDekKzWswSnWJ/YvwKVdwx8jb5tOk8iIiJnxIDlRMGpYXhqGJwsR2um8aQ3VHFVMfKr8lUBeUFlAQqqCtQIlEzVqduqCtTtsk2MhKvGCsobI6vzZOouzBRmvQw3hyPWuy5MBXgFtPh8iYiIXBkDVjuQQCR1TzJtZzks1xtenio8VdRUqPBTUl2iDglNtpdSHG4JT3IpAUou5fbmBiYLPfT1g5M5rF6IkiPEFAIvvX02XSYiInJVDFga6ty5s+pWbhuYoAcqUamKvctrylUDTOnnVFRTpC7V9dJylBeX14WmqrrgZPtxcXWx9eOq2qo2naO0NAj0ClSr8WwvA4wBdde9AlVdlIQn+ZitDoiIiFqOAUtDL+W+hJqSGmuIkkDV1kDUGNnmRbZ1kbCkDuPxS4Ovmo47ITTZXDfq+ZITERHZG//aauhIyREYag1NTrfJqjiz3gyzwQxvvfdfl3qz+pwcfgY/a2Cy/dg2SEm4Yt8nIiIi58WApaH7u9+PkMCQRsOTUWdk/yYiIiIPwYCloQHBA1T3cyIiIvJsDFgaio+PR2BgoKNPg4iIiJqhoKAA9sKApSFL7yoiIiJyfhUVFXZ7bFZKExEREWmMAYuIiIhIYwxYRERERBpjwCIiIiLSGAMWERERkcYYsIiIiIg0xoBFREREpDEGLCIiIiKNMWARERERaYwBi4iIiEhjDFhEREREGmPAIiIiItIYAxYRERGRxoxaP6Anqq2tVZcFBQWOPhUiIiJqJsvfbcvfcS0xYGkgOztbXSYkJDj6VIiIiKgVf8eDgoKgJQYsDYSGhqrLpKQkzV+gthg6dCjWr1/vVI/b0q9t7v1Pdb/Wfr6x2+Udj4Tpo0ePIjAwEM6Cr3fbP8/Xm683X2/Per3z8/ORmJho/TuuJQYsDej1daVsEq6c6QfSYDDY5Xza8rgt/drm3v9U92vt50/2dXI7X29tv5avd/Px9W775/l68/Vu+HdcSyxyd2NTpkxxusdt6dc29/6nul9rP2+v/4b2wNe77Z/n683X21nx9Xa911tXa4/KLg8jQ8oyeiVDjc70jofsg6+3Z+Hr7Vn4enuWAju+3hzB0oDZbMajjz6qLsn98fX2LHy9PQtfb89ituPrzREsIiIiIo1xBIuIiIhIYwxYRERERBpjwCIiIiLSGAMWERERkcYYsIiIiIg0xoDVjvLy8jBkyBAMGDAAffv2xWuvveboUyI7kq02Ro8ejd69e+O0007Dxx9/7OhTIju79NJLERISgssvv9zRp0J2sHz5cvTo0QPdunXD66+/7ujTISf/eWabhnZUXV2N8vJy+Pr6ori4WIWsDRs2ICwszNGnRnaQlpaGjIwMFajT09MxePBg7N27F35+fo4+NbKTH3/8EYWFhXj77bfxySefOPp0SENVVVXqzdLq1atVY0r5ef7tt9/4+9uN/djGn2eOYLUj2QdJwpWQoCXZlvnWfcXExKhwJaKjoxEeHo6cnBxHnxbZkYxYBgQEOPo0yA7++OMP9OnTB3FxcfD398e4ceOwcuVKR58WOfHPMwOWjTVr1uDiiy9GbGwsdDodli1bdsJ9XnzxRXTs2BHe3t4YPny4+qFr6TRh//79ER8fjwceeED90SX3fb0tNm7cqEYwExISNDhzcvbXm9zv9U9NTVXhykI+TklJabfzJ9f7eWfAsiHTdhJ+5D96Yz788ENMnz5dtdXftGmTuu+FF16IzMxM630s9VUND/nhFMHBwdi6dSsOHTqEpUuXqikkct/XW8io1Q033IDFixe3y/dFjn29yX1ff3Idxc7weksNFp1I/tN89tln9W4bNmxY7ZQpU6zXq6ura2NjY2vnzp3bque46667aj/++OM2nys57+tdVlZWe+aZZ9a+8847mp4vOe/P9+rVq2snT56s2bmSc7z+v/76a+2kSZOsn7/33ntr33vvvXY8a3LEz3tbfp45gtVMFRUVappnzJgx1tv0er26vnbt2mY9hoxWScGckJ27ZQhTVqSQe77e8nN900034dxzz8X1119vx7MlZ3i9yb1f/2HDhmH79u1qWrCoqAjffPONGvEg11PRTj/vRs0eyc1lZWWpGpqoqKh6t8v13bt3N+sxjhw5gjvuuMNa3D516lT069fPTmdMjn69f/31VzUMLS0aLPP/7777Ll9zN329hfyClhIAmZ6QOktpzTFixAg7nDG19+tvNBrxzDPP4JxzzkFNTQ0efPBBriB085/3MW38eWbAakfyDmjLli2OPg1qJ6NGjVK/iMlzfPfdd44+BbKjiRMnqoM8w3dt/HnmFGEzyWo/abPQsChdrssSfHIvfL09C19vz8bX37OEt9PrzYDVTCaTSTWW+/777623yeiEXOcUgPvh6+1Z+Hp7Nr7+nsXUTq83pwhtSOHi/v37rdellYJM6YWGhiIxMVEt6bzxxhvVdjcy3bdo0SI1N3vzzTc79Lypdfh6exa+3p6Nr79nKXKG17uVqx7dkizHlP8kDY8bb7zRep/nn3++NjExsdZkMqllnr///rtDz5laj6+3Z+Hr7dn4+nuW1U7wenMvQiIiIiKNsQaLiIiISGMMWEREREQaY8AiIiIi0hgDFhEREZHGGLCIiIiINMaARURERKQxBiwiIiIijTFgEREREWmMAYuIiIhIYwxYRERERBpjwCIiasJbb72F3r17w9fXF7169cJXX33l6FMiIhfBgEVE1IhPP/0U99xzD2bPno3t27fjwgsvxJ133uno0yIiF8HNnomIGnHGGWdgzJgxmDNnjrq+atUqXHHFFcjLy3P0qRGRC+AIFhFRA4WFhfj9998xfvx4623ffvstBg4c6NDzIiLXYXT0CRAROZutW7dCr9ejf//+KCkpwdKlS/Hcc8/hs88+c/SpEZGLYMAiImpgy5Yt6NmzJzZu3IhRo0ap2y677DKMGzfO0adGRC6CU4RERI0ErEGDBqFfv35Yt24dFixYgBUrVuCxxx5z9KkRkYvgCBYRUSMB6/rrr0dgYCCGDRumjj179qiwRUTUHBzBIiKyUVVVhR07dqi+Vw3rsizThUREp8IRLCIiG7t370ZZWZmaDoyIiFBNRl9++WUcPnwYt956q6NPj4hcBAMWEVGD6cGYmBj4+PjgzDPPhJ+fnxq5Wr16NaKjox19ekTkIhiwiIgaBKzhw4ezJQMRtQlrsIiIGgSs0047zdGnQUQujgGLiKhBMTsDFhG1FfciJCIiItIYR7CIiIiINMaARURERKQxBiwiIiIijTFgEREREWmMAYuIiIhIYwxYRERERBpjwCIiIiLSGAMWERERkcYYsIiIiIg0xoBFREREpDEGLCIiIiJo6/8BLMW9tpAgPjwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.fill_between(\n",
    "    β_vect,\n",
    "    -1 / 8 * np.ones(n_points),\n",
    "    1 / 8 * np.ones(n_points),\n",
    "    label=\"$\\\\Lambda_{\\\\geqslant 0}$\",\n",
    "    color=[0.85, 0.85, 0.85, 1],\n",
    ")\n",
    "plt.fill_between(\n",
    "    β_vect,\n",
    "    -res,\n",
    "    res,\n",
    "    label=\"$\\\\Lambda_G = [\\\\alpha_-, \\\\alpha_+]$\",\n",
    "    color=[0.6, 0.6, 0.6, 1],\n",
    ")\n",
    "\n",
    "plt.semilogx(β_vect, ubi, label=\"Upper bound\")\n",
    "plt.semilogx(β_vect, np.zeros(n_points), label=\"$\\\\alpha=0$\")\n",
    "plt.semilogx(β_vect, lbi, label=\"Lower bound\")\n",
    "\n",
    "plt.xlabel(\"$\\\\beta$\")\n",
    "plt.ylabel(\"$\\\\alpha$\")\n",
    "plt.legend()\n",
    "plt.xlim([β_vect[0], β_vect[-1]])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c9ec7e0-4477-480c-9820-2c2cf6b4ea83",
   "metadata": {},
   "source": [
    "### Fish graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4738490-bafd-42ba-b294-57f07eb78ada",
   "metadata": {},
   "source": [
    "The Fish graph, with properly designed arrival rates, is a counter-example to the lack of flexibility of greedy policies in surjective-only graphs, as it is feasible for a family of greedy policies to converge to the vertex. There, however, a price to pay in terms of delay, despite the fact that the vertex is bijective."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "807083cb-4e21-49c0-938e-795965edfb09",
   "metadata": {},
   "source": [
    "Here is the graph:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "452cda04-a35c-42f4-bbc3-5ec267d8e6a1",
   "metadata": {
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     "shell.execute_reply.started": "2025-09-28T07:11:28.270687Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-8c5e50ba-740e-4431-9eb1-6ac87fa22e1a\">\n",
       "<div id=\"8c5e50ba-740e-4431-9eb1-6ac87fa22e1a\"></div>\n",
       "<a href=\"#\" id=\"fit-8c5e50ba-740e-4431-9eb1-6ac87fa22e1a\"\n",
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       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-8c5e50ba-740e-4431-9eb1-6ac87fa22e1a {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#8c5e50ba-740e-4431-9eb1-6ac87fa22e1a {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"1\", \"title\": \"0: 1\"}, {\"id\": 1, \"label\": \"2\", \"title\": \"1: 2\"}, {\"id\": 2, \"label\": \"3\", \"title\": \"2: 3\"}, {\"id\": 3, \"label\": \"4\", \"title\": \"3: 4\"}, {\"id\": 4, \"label\": \"5\", \"title\": \"4: 5\"}, {\"id\": 5, \"label\": \"6\", \"title\": \"5: 6\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (1, 2)\", \"label\": \"3\", \"color\": \"black\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (1, 3)\", \"label\": \"1\", \"color\": \"black\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (2, 3)\", \"label\": \"1\", \"color\": \"black\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (3, 4)\", \"label\": \"0.5+\\u03b11\", \"from\": 2, \"to\": 3}, {\"title\": \"4: (3, 6)\", \"label\": \"0.5-\\u03b11\", \"from\": 2, \"to\": 5}, {\"title\": \"5: (4, 5)\", \"label\": \"1.5-\\u03b11\", \"from\": 3, \"to\": 4}, {\"title\": \"6: (5, 6)\", \"label\": \"1.5+\\u03b11\", \"from\": 4, \"to\": 5}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\"};\n",
       "    const container = document.getElementById('8c5e50ba-740e-4431-9eb1-6ac87fa22e1a');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-8c5e50ba-740e-4431-9eb1-6ac87fa22e1a').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fish = sm.KayakPaddle(\n",
    "    3, 0, 4, names=[str(i) for i in range(1, 7)], rates=[4, 4, 3, 2, 3, 2]\n",
    ")\n",
    "fish.show_kernel(disp_rates=False, disp_flow=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dceb49b5-9100-4085-b9b5-e09e6ead7f42",
   "metadata": {},
   "source": [
    "Our target is the bijective vertex $\\alpha=1/2$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "135a5126-ad12-4446-89dc-124314683119",
   "metadata": {
    "execution": {
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     "shell.execute_reply.started": "2025-09-28T07:11:28.280324Z"
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   "outputs": [
    {
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      "text/html": [
       "\n",
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       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-8e492d33-df9b-4579-b54d-4d089bd2834d {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
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       "max-height: 100vh !important;\n",
       "}\n",
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       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"1\", \"title\": \"0: 1\"}, {\"id\": 1, \"label\": \"2\", \"title\": \"1: 2\"}, {\"id\": 2, \"label\": \"3\", \"title\": \"2: 3\"}, {\"id\": 3, \"label\": \"4\", \"title\": \"3: 4\"}, {\"id\": 4, \"label\": \"5\", \"title\": \"4: 5\"}, {\"id\": 5, \"label\": \"6\", \"title\": \"5: 6\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (1, 2)\", \"label\": \"3\", \"color\": \"blue\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (1, 3)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (2, 3)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (3, 4)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 2, \"to\": 3}, {\"title\": \"4: (3, 6)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 2, \"to\": 5}, {\"title\": \"5: (4, 5)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 3, \"to\": 4}, {\"title\": \"6: (5, 6)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 4, \"to\": 5}]);\n",
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       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-8e492d33-df9b-4579-b54d-4d089bd2834d').addEventListener('click', function(event) {\n",
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       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
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       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "fish.show_flow(disp_rates=False, flow=fish.kernel_to_edge([1/2]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69dce7e2-ea01-40b2-a15b-408f67ee9632",
   "metadata": {},
   "source": [
    "#### Rate limitation lemma"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a0f575c-3efa-43a5-a431-1fe9135457a5",
   "metadata": {},
   "source": [
    "To build the policy, the first part consists in noticing that if nodes 3 is forced to prioritize the *tail* of the fish (nodes 1 and 2), then the rate that 3 can send to the *body* is at most $9/11\\approx 0.818$. This result does not depend on the body shape so we heck it on a simple frying pan (the body reduced to one node outside of 3)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "b092b043-fb55-40b0-8cc8-593d17165009",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:28.287107Z",
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     "shell.execute_reply": "2025-09-28T07:11:28.294107Z",
     "shell.execute_reply.started": "2025-09-28T07:11:28.287107Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "paw = sm.Tadpole(names=[str(i) for i in range(1, 5)], rates=[4, 4, 3, 1])\n",
    "paw.stabilizable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "5ac88703-7840-437e-8d5e-04b61da196be",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:28.295626Z",
     "iopub.status.busy": "2025-09-28T07:11:28.295626Z",
     "iopub.status.idle": "2025-09-28T07:11:28.301624Z",
     "shell.execute_reply": "2025-09-28T07:11:28.301624Z",
     "shell.execute_reply.started": "2025-09-28T07:11:28.295626Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3., 1., 1., 1.])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "paw.base_flow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "01cc1c60-b1bb-4ccf-9925-fea37d1efaff",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:28.302770Z",
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     "shell.execute_reply.started": "2025-09-28T07:11:28.302770Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "paw.run(\"priority\", weights=[0, 1, 1, 0], max_queue=10**7, n_steps=10**7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "171ab489-ab0d-4c66-89ca-14f9f1bc7690",
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     "shell.execute_reply": "2025-09-28T07:11:37.009553Z",
     "shell.execute_reply.started": "2025-09-28T07:11:37.004393Z"
    }
   },
   "outputs": [
    {
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       "\n",
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       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
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       "#box-c0c21308-537c-46c9-b381-5d3c84469ca9 {\n",
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       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"1\", \"title\": \"0: 1\"}, {\"id\": 1, \"label\": \"2\", \"title\": \"1: 2\"}, {\"id\": 2, \"label\": \"3\", \"title\": \"2: 3\"}, {\"id\": 3, \"label\": \"4\", \"title\": \"3: 4\", \"color\": \"red\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (1, 2)\", \"label\": \"2.91\", \"color\": \"blue\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (1, 3)\", \"label\": \"1.09\", \"color\": \"blue\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (2, 3)\", \"label\": \"1.09\", \"color\": \"blue\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (3, 4)\", \"label\": \"0.819\", \"color\": \"blue\", \"from\": 2, \"to\": 3}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\"};\n",
       "    const container = document.getElementById('c0c21308-537c-46c9-b381-5d3c84469ca9');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-c0c21308-537c-46c9-b381-5d3c84469ca9').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "paw.show_flow(disp_rates=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f8353da-b9ec-4b1e-b09c-f8e89a9f7e9b",
   "metadata": {},
   "source": [
    "#### Unstable greedy policy lemma"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb854565-6cb5-4d61-9432-1bce4ad9a3d7",
   "metadata": {},
   "source": [
    "Building on the rate limitation, one can craft an instable greedy policy that *starves* the body of the fish. Starvation induces a constantly growing number of waiting items. Using priorities, we can shape the policy so that waiting items are mostly of type 4. As a side-effect, that would nullify the edge $(3, 6)$, which is what we want."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c13f7765-e130-44e3-b1e1-c7fde616a709",
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     "iopub.status.idle": "2025-09-28T07:11:39.796106Z",
     "shell.execute_reply": "2025-09-28T07:11:39.795598Z",
     "shell.execute_reply.started": "2025-09-28T07:11:37.010563Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-eba0d604-799d-4528-bcdc-eecf08ebcf9a\">\n",
       "<div id=\"eba0d604-799d-4528-bcdc-eecf08ebcf9a\"></div>\n",
       "<a href=\"#\" id=\"fit-eba0d604-799d-4528-bcdc-eecf08ebcf9a\"\n",
       "  style=\"position: absolute; left: 10px; bottom: 10px; text-decoration: none; color: #888; font-size: min(2vw, 10px);\n",
       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-eba0d604-799d-4528-bcdc-eecf08ebcf9a {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#eba0d604-799d-4528-bcdc-eecf08ebcf9a {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"1\", \"title\": \"0: 1\"}, {\"id\": 1, \"label\": \"2\", \"title\": \"1: 2\"}, {\"id\": 2, \"label\": \"3\", \"title\": \"2: 3\"}, {\"id\": 3, \"label\": \"4\", \"title\": \"3: 4\", \"color\": \"red\"}, {\"id\": 4, \"label\": \"5\", \"title\": \"4: 5\"}, {\"id\": 5, \"label\": \"6\", \"title\": \"5: 6\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (1, 2)\", \"label\": \"2.91\", \"color\": \"blue\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (1, 3)\", \"label\": \"1.09\", \"color\": \"blue\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (2, 3)\", \"label\": \"1.09\", \"color\": \"blue\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (3, 4)\", \"label\": \"0.818\", \"color\": \"blue\", \"from\": 2, \"to\": 3}, {\"title\": \"4: (3, 6)\", \"label\": \"0\", \"color\": \"orange\", \"from\": 2, \"to\": 5}, {\"title\": \"5: (4, 5)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 3, \"to\": 4}, {\"title\": \"6: (5, 6)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 4, \"to\": 5}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\"};\n",
       "    const container = document.getElementById('eba0d604-799d-4528-bcdc-eecf08ebcf9a');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-eba0d604-799d-4528-bcdc-eecf08ebcf9a').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fish.run(\"priority\", weights=[0, 3, 3, 2, 0, 0, 2], max_queue=10**7, n_steps=10**7, seed=42)\n",
    "fish.show_flow(disp_rates=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b79de939-408b-4f72-9de7-7f7574b91a59",
   "metadata": {},
   "source": [
    "We can check that the queue is concentrated on node 4."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "0166281b-42c5-4994-8455-ad56d4a3756a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:39.797116Z",
     "iopub.status.busy": "2025-09-28T07:11:39.796106Z",
     "iopub.status.idle": "2025-09-28T07:11:39.871979Z",
     "shell.execute_reply": "2025-09-28T07:11:39.871979Z",
     "shell.execute_reply.started": "2025-09-28T07:11:39.797116Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([8.51466300e-01, 8.47361100e-01, 2.00000000e-07, 5.01960123e+04,\n",
       "       3.00000000e-07, 1.98790250e+00])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fish.simulator.avg_queues"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09140fa3-6e1b-49e4-ad8e-bed8b5c67af7",
   "metadata": {},
   "source": [
    "To finalize, all what we need is relax the unstable greedy policy into a stable policy when queues are too high."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "e5615a03-946d-4708-93ae-e901299f1a45",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:39.872985Z",
     "iopub.status.busy": "2025-09-28T07:11:39.872985Z",
     "iopub.status.idle": "2025-09-28T07:11:42.210182Z",
     "shell.execute_reply": "2025-09-28T07:11:42.209664Z",
     "shell.execute_reply.started": "2025-09-28T07:11:39.872985Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<div class=\"sm-graph\" id=\"box-3db08db2-ce16-40c4-825b-3408f6a48352\">\n",
       "<div id=\"3db08db2-ce16-40c4-825b-3408f6a48352\"></div>\n",
       "<a href=\"#\" id=\"fit-3db08db2-ce16-40c4-825b-3408f6a48352\"\n",
       "  style=\"position: absolute; left: 10px; bottom: 10px; text-decoration: none; color: #888; font-size: min(2vw, 10px);\n",
       "  z-index: 10; pointer-events: auto;\"\n",
       "> Reload\n",
       "</a>\n",
       "<style>\n",
       "#box-3db08db2-ce16-40c4-825b-3408f6a48352 {\n",
       "position: relative;\n",
       "width: 100%;\n",
       "height: 50vh !important;\n",
       "max-width: 100vw;\n",
       "max-height: 100vh !important;\n",
       "}\n",
       "#3db08db2-ce16-40c4-825b-3408f6a48352 {\n",
       "  height: 100%;   /* Make the inner div fill the parent */\n",
       "}\n",
       "</style>\n",
       "</div>\n",
       "<script type=\"module\">\n",
       "import { DataSet, Network } from \"https://unpkg.com/vis-network/standalone/esm/vis-network.min.js\";\n",
       "// CSS will be automatically injected into the page.\n",
       "function render () {\n",
       "    const nodes = new DataSet([{\"id\": 0, \"label\": \"1\", \"title\": \"0: 1\"}, {\"id\": 1, \"label\": \"2\", \"title\": \"1: 2\"}, {\"id\": 2, \"label\": \"3\", \"title\": \"2: 3\"}, {\"id\": 3, \"label\": \"4\", \"title\": \"3: 4\"}, {\"id\": 4, \"label\": \"5\", \"title\": \"4: 5\"}, {\"id\": 5, \"label\": \"6\", \"title\": \"5: 6\"}]);\n",
       "    const edges = new DataSet([{\"title\": \"0: (1, 2)\", \"label\": \"3\", \"color\": \"blue\", \"from\": 0, \"to\": 1}, {\"title\": \"1: (1, 3)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 0, \"to\": 2}, {\"title\": \"2: (2, 3)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 1, \"to\": 2}, {\"title\": \"3: (3, 4)\", \"label\": \"0.996\", \"color\": \"blue\", \"from\": 2, \"to\": 3}, {\"title\": \"4: (3, 6)\", \"label\": \"0.00031\", \"color\": \"blue\", \"from\": 2, \"to\": 5}, {\"title\": \"5: (4, 5)\", \"label\": \"1\", \"color\": \"blue\", \"from\": 3, \"to\": 4}, {\"title\": \"6: (5, 6)\", \"label\": \"2\", \"color\": \"blue\", \"from\": 4, \"to\": 5}]);\n",
       "    const data = {\n",
       "            nodes: nodes,\n",
       "            edges: edges,\n",
       "    };\n",
       "    const options = {\"interaction\": {\"navigationButtons\": false}, \"width\": \"100%\", \"height\": \"100%\"};\n",
       "    const container = document.getElementById('3db08db2-ce16-40c4-825b-3408f6a48352');\n",
       "    const network = new Network(container, data, options);\n",
       "    network.fit({maxZoomLevel: 10});\n",
       "    network.redraw();\n",
       "}\n",
       "\n",
       "render();\n",
       "document.getElementById('fit-3db08db2-ce16-40c4-825b-3408f6a48352').addEventListener('click', function(event) {\n",
       "    event.preventDefault();  // Prevent page jump\n",
       "    render(); // Adjust zoom limit as needed\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fish.run(\n",
    "    \"priority\",\n",
    "    weights=[0, 3, 3, 2, 0, 0, 2],\n",
    "    threshold=100,\n",
    "    counterweights=[0, 1, 1, 2, 0, 0, 2],\n",
    "    n_steps=10**7,\n",
    "    seed=42\n",
    ")\n",
    "fish.show_flow(disp_rates=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6f3c548-6529-4b21-b366-e9b67f4c9a1e",
   "metadata": {},
   "source": [
    "#### Evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1508e915-1dd5-4b57-a2fd-55395ccde3d2",
   "metadata": {},
   "source": [
    "As often, we have a delay/regret trade-off."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "adaa80d9-dd09-4764-94c4-0e5a98b6c1a5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:42.211192Z",
     "iopub.status.busy": "2025-09-28T07:11:42.210182Z",
     "iopub.status.idle": "2025-09-28T07:11:42.215189Z",
     "shell.execute_reply": "2025-09-28T07:11:42.215189Z",
     "shell.execute_reply.started": "2025-09-28T07:11:42.211192Z"
    }
   },
   "outputs": [],
   "source": [
    "rewards = [2, 2, 2, 1, -1, 0, 1]\n",
    "t_range = Iterator(\"threshold\", 2 ** (np.arange(14)), \"k\")\n",
    "name = '$\\\\Phi_k^+$'\n",
    "fish_policies = {name: {'simulator': 'priority', 'weights': [0, 3, 3, 2, 0, 0, 2],\n",
    "                                'counterweights': [0, 1, 1, 2, 0, 0, 2], 'iterator': t_range},\n",
    "                 'Taboo': specific['Taboo']}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "527cdeec-7b2e-41e6-9db5-2e3e64de90b7",
   "metadata": {},
   "source": [
    ":::note\n",
    "The priority policy has no built-in regret management, so we need to post-compute it.\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "4deb9b82-bcbe-413d-a63d-972cd55349de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:42.216663Z",
     "iopub.status.busy": "2025-09-28T07:11:42.216663Z",
     "iopub.status.idle": "2025-09-28T07:11:42.366789Z",
     "shell.execute_reply": "2025-09-28T07:11:42.366789Z",
     "shell.execute_reply.started": "2025-09-28T07:11:42.216663Z"
    }
   },
   "outputs": [],
   "source": [
    "fish.simulator = None\n",
    "xps = xp_builder({'model': fish, **common}, fish_policies)\n",
    "with Pool() as p:\n",
    "    res = evaluate(xps, pool=p, metrics=[\"delay\", \"regret\", \"flow\"], cache_name=\"fish\", \n",
    "                   cache_overwrite=refresh)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "0a189648-dea0-4b40-8a15-e8895981fdfd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:42.368796Z",
     "iopub.status.busy": "2025-09-28T07:11:42.367796Z",
     "iopub.status.idle": "2025-09-28T07:11:42.373302Z",
     "shell.execute_reply": "2025-09-28T07:11:42.372795Z",
     "shell.execute_reply.started": "2025-09-28T07:11:42.368796Z"
    }
   },
   "outputs": [],
   "source": [
    "def regret(model, flow, rewards):    \n",
    "    original_rates = model.rates\n",
    "    model.rates = model.incidence @ flow\n",
    "    best_flow = model.optimize_rates(rewards)\n",
    "    model.rates = original_rates\n",
    "    return rewards @ (best_flow - flow)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "540837e1-3b8d-46d6-8500-81014d006071",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:42.374311Z",
     "iopub.status.busy": "2025-09-28T07:11:42.374311Z",
     "iopub.status.idle": "2025-09-28T07:11:42.402736Z",
     "shell.execute_reply": "2025-09-28T07:11:42.402736Z",
     "shell.execute_reply.started": "2025-09-28T07:11:42.374311Z"
    }
   },
   "outputs": [],
   "source": [
    "res[name]['regret'] = [regret(fish, flow, rewards) for flow in res[name]['flow']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "046ddf5c-d3ac-468b-9a94-ebcc888a670a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-28T07:11:42.404159Z",
     "iopub.status.busy": "2025-09-28T07:11:42.404159Z",
     "iopub.status.idle": "2025-09-28T07:11:42.992753Z",
     "shell.execute_reply": "2025-09-28T07:11:42.992753Z",
     "shell.execute_reply.started": "2025-09-28T07:11:42.404159Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_res(res, x_max=100, y_max=1.5)"
   ]
  }
 ],
 "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": "3.12.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}