vis_run.ipynb

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   "source": [
    "import solara\n",
    "from mesa.experimental import JupyterViz\n",
    "from matplotlib.figure import Figure\n",
    "from model import CoastalModel\n",
    "import math\n",
    "\n",
    "\n",
    "def agent_portrayal(agent):\n",
    "    return {\n",
    "        \"color\": \"tab:blue\",\n",
    "        \"size\": 10,\n",
    "    }\n",
    "\n",
    "model_params = {\n",
    "    \"N\": {\n",
    "        \"type\": \"SliderInt\",\n",
    "        \"value\": 50,\n",
    "        \"label\": \"Number of agents:\",\n",
    "        \"min\": 10,\n",
    "        \"max\": 100,\n",
    "        \"step\": 1,\n",
    "    }\n",
    "}\n",
    "\n",
    "def make_histogram(model):\n",
    "    # Note: you must initialize a figure using this method instead of\n",
    "    # plt.figure(), for thread safety purpose\n",
    "    fig = Figure()\n",
    "    ax = fig.subplots()\n",
    "    adaptation = [agent.flood_preparedness for agent in model.schedule.agents]\n",
    "    # Note: you have to use Matplotlib's OOP API instead of plt.hist\n",
    "    # because plt.hist is not thread-safe.\n",
    "    ax.set_xlabel(\"Flood defenses\")\n",
    "    ax.set_ylabel(\"Number of agents\")\n",
    "    ax.hist(adaptation, bins=math.ceil(math.sqrt(len(adaptation))))\n",
    "    fig.suptitle(\"Number of agents with flood defenses\")\n",
    "    \n",
    "    solara.FigureMatplotlib(fig)\n",
    "\n",
    "page = JupyterViz(\n",
    "    CoastalModel,\n",
    "    model_params,\n",
    "    measures=[\"Sea Level\", make_histogram],\n",
    "    name=\"Coastal Model\",\n",
    "    agent_portrayal=agent_portrayal,\n",
    ")\n",
    "# This is required to render the visualization in the Jupyter notebook\n",
    "page"
   ]
  }
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