fix: model name in visualization tutorial (projectmesa#2591)

Updated the model name to a more descriptive name in visualization tutorial

Author: Sahil-Chhoker

docs/tutorials/visualization_tutorial.ipynb

@@ -128,13 +128,13 @@
    "outputs": [],
    "source": [
     "# Create initial model instance\n",
-    "model1 = MoneyModel(n=50, width=10, height=10) #keyword arguments\n",
+    "money_model = MoneyModel(n=50, width=10, height=10) #keyword arguments\n",
     "\n",
     "SpaceGraph = make_space_component(agent_portrayal)\n",
     "GiniPlot = make_plot_component(\"Gini\")\n",
     "\n",
     "page = SolaraViz(\n",
-    "    model1,\n",
+    "    money_model,\n",
     "    components=[SpaceGraph, GiniPlot],\n",
     "    model_params=model_params,\n",
     "    name=\"Boltzmann Wealth Model\",\n",
@@ -207,13 +207,13 @@
    "outputs": [],
    "source": [
     "# Create initial model instance\n",
-    "model = MoneyModel(n=50, width=10, height=10)\n",
+    "money_model = MoneyModel(n=50, width=10, height=10)\n",
     "\n",
     "SpaceGraph = make_space_component(agent_portrayal)\n",
     "GiniPlot = make_plot_component(\"Gini\")\n",
     "\n",
     "page = SolaraViz(\n",
-    "    model1,\n",
+    "    money_model,\n",
     "    components=[SpaceGraph, GiniPlot],\n",
     "    model_params=model_params,\n",
     "    name=\"Boltzmann Wealth Model\",\n",
@@ -318,7 +318,7 @@
    "outputs": [],
    "source": [
     "# Create initial model instance\n",
-    "model = MoneyModel(n=50, width=10, height=10)\n",
+    "money_model = MoneyModel(n=50, width=10, height=10)\n",
     "\n",
     "SpaceGraph = make_space_component(agent_portrayal)\n",
     "GiniPlot = make_plot_component(\"Gini\")"
@@ -354,7 +354,7 @@
    ],
    "source": [
     "page = SolaraViz(\n",
-    "    model,\n",
+    "    money_model,\n",
     "    components=[SpaceGraph, GiniPlot, Histogram],\n",
     "    model_params=model_params,\n",
     "    name=\"Boltzmann Wealth Model\",\n",
@@ -399,7 +399,7 @@
     }
    ],
    "source": [
-    "Histogram(model)"
+    "Histogram(money_model)"
    ]
   },
   {

mesa/examples/advanced/pd_grid/analysis.ipynb

@@ -17,17 +17,17 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "import pandas as pd\n",
     "\n",
     "%matplotlib inline\n",
     "\n",
     "from model import Schelling"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -38,10 +38,14 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
-   "source": "model = Schelling(height=10, width=10, homophily=3, density=0.8, minority_pc=0.2)",
    "outputs": [],
-   "execution_count": null
+   "source": [
+    "schelling_model = Schelling(\n",
+    "    height=10, width=10, homophily=3, density=0.8, minority_pc=0.2\n",
+    ")"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -52,14 +56,14 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
-   "source": [
-    "while model.running and model.steps < 100:\n",
-    "    model.step()\n",
-    "print(model.steps)  # Show how many steps have actually run"
-   ],
    "outputs": [],
-   "execution_count": null
+   "source": [
+    "while schelling_model.running and schelling_model.steps < 100:\n",
+    "    schelling_model.step()\n",
+    "print(schelling_model.steps)  # Show how many steps have actually run"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -70,21 +74,21 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
-   "source": [
-    "model_out = model.datacollector.get_model_vars_dataframe()"
-   ],
    "outputs": [],
-   "execution_count": null
+   "source": [
+    "model_out = schelling_model.datacollector.get_model_vars_dataframe()"
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
     "model_out.head()"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -95,12 +99,12 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
     "model_out.happy.plot()"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "markdown",
@@ -115,10 +119,12 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
-   "source": "from mesa.batchrunner import batch_run",
    "outputs": [],
-   "execution_count": null
+   "source": [
+    "from mesa.batchrunner import batch_run"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -129,52 +135,52 @@
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
     "fixed_params = {\"height\": 10, \"width\": 10, \"density\": 0.8, \"minority_pc\": 0.2}\n",
     "variable_parms = {\"homophily\": range(1, 9)}\n",
     "all_params = fixed_params | variable_parms"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
     "results = batch_run(\n",
     "    Schelling,\n",
     "    parameters=all_params,\n",
     "    iterations=10,\n",
     "    max_steps=200,\n",
     ")"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
-   "metadata": {},
    "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "df = pd.DataFrame(results)\n",
     "df"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
     "plt.scatter(df.homophily, df.happy)\n",
     "plt.xlabel(\"Homophily\")\n",
     "plt.ylabel(\"Happy Agents\")\n",
     "plt.grid()\n",
     "plt.title(\"Effect of Homophily on segregation\")\n",
     "plt.show()"
-   ],
-   "outputs": [],
-   "execution_count": null
+   ]
   }
  ],
  "metadata": {