Final_Gerrymandering_CP.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/OptimizationExpert/Pyomo/blob/main/Final_Gerrymandering_CP.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fntyf_g_YElb"
      },
      "source": [
        "Developed by Alireza Soroudi\n",
        "alireza.soroudi@gmail.com\n",
        "\n",
        "Linkedin News letter : https://www.linkedin.com/newsletters/optimization-in-open-source-6874020019009859585/\n",
        "\n",
        "Git hub: https://github.com/OptimizationExpert/Pyomo"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FwTzUa-VH1ro",
        "outputId": "8f4b5828-665a-461a-df8d-48fa30f96529"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting ortools\n",
            "  Downloading ortools-9.11.4210-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.0 kB)\n",
            "Collecting absl-py>=2.0.0 (from ortools)\n",
            "  Downloading absl_py-2.1.0-py3-none-any.whl.metadata (2.3 kB)\n",
            "Requirement already satisfied: numpy>=1.13.3 in /usr/local/lib/python3.10/dist-packages (from ortools) (1.26.4)\n",
            "Requirement already satisfied: pandas>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from ortools) (2.2.2)\n",
            "Collecting protobuf<5.27,>=5.26.1 (from ortools)\n",
            "  Downloading protobuf-5.26.1-cp37-abi3-manylinux2014_x86_64.whl.metadata (592 bytes)\n",
            "Requirement already satisfied: immutabledict>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from ortools) (4.2.0)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->ortools) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->ortools) (2024.2)\n",
            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->ortools) (2024.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas>=2.0.0->ortools) (1.16.0)\n",
            "Downloading ortools-9.11.4210-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (28.1 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m28.1/28.1 MB\u001b[0m \u001b[31m24.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading absl_py-2.1.0-py3-none-any.whl (133 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m133.7/133.7 kB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading protobuf-5.26.1-cp37-abi3-manylinux2014_x86_64.whl (302 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.8/302.8 kB\u001b[0m \u001b[31m10.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: protobuf, absl-py, ortools\n",
            "  Attempting uninstall: protobuf\n",
            "    Found existing installation: protobuf 3.20.3\n",
            "    Uninstalling protobuf-3.20.3:\n",
            "      Successfully uninstalled protobuf-3.20.3\n",
            "  Attempting uninstall: absl-py\n",
            "    Found existing installation: absl-py 1.4.0\n",
            "    Uninstalling absl-py-1.4.0:\n",
            "      Successfully uninstalled absl-py-1.4.0\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-cloud-datastore 2.19.0 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 5.26.1 which is incompatible.\n",
            "google-cloud-firestore 2.16.1 requires protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5, but you have protobuf 5.26.1 which is incompatible.\n",
            "tensorboard 2.17.0 requires protobuf!=4.24.0,<5.0.0,>=3.19.6, but you have protobuf 5.26.1 which is incompatible.\n",
            "tensorflow 2.17.0 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 5.26.1 which is incompatible.\n",
            "tensorflow-metadata 1.16.1 requires protobuf<4.21,>=3.20.3; python_version < \"3.11\", but you have protobuf 5.26.1 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed absl-py-2.1.0 ortools-9.11.4210 protobuf-5.26.1\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "!pip install ortools\n",
        "from ortools.sat.python import cp_model\n",
        "import matplotlib.pyplot as plt # Data visualization\n",
        "import random\n",
        "import numpy as np\n",
        "import time"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "![Screenshot 2024-10-24 at 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)"
      ],
      "metadata": {
        "id": "dSCDLUOx2NFc"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "PCA1dBYJH8wz",
        "outputId": "49221dc8-fdb6-41a8-fbe3-2ca35ea6ca0a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1: (0, 0, 0),\n",
              " 2: (1, 0, 0),\n",
              " 3: (2, 0, 1),\n",
              " 4: (3, 0, 1),\n",
              " 5: (4, 0, 1),\n",
              " 6: (0, 1, 0),\n",
              " 7: (1, 1, 0),\n",
              " 8: (2, 1, 1),\n",
              " 9: (3, 1, 1),\n",
              " 10: (4, 1, 1),\n",
              " 11: (0, 2, 0),\n",
              " 12: (1, 2, 0),\n",
              " 13: (2, 2, 1),\n",
              " 14: (3, 2, 1),\n",
              " 15: (4, 2, 1),\n",
              " 16: (0, 3, 0),\n",
              " 17: (1, 3, 0),\n",
              " 18: (2, 3, 1),\n",
              " 19: (3, 3, 1),\n",
              " 20: (4, 3, 1),\n",
              " 21: (0, 4, 0),\n",
              " 22: (1, 4, 0),\n",
              " 23: (2, 4, 1),\n",
              " 24: (3, 4, 1),\n",
              " 25: (4, 4, 1),\n",
              " 26: (0, 5, 0),\n",
              " 27: (1, 5, 0),\n",
              " 28: (2, 5, 1),\n",
              " 29: (3, 5, 1),\n",
              " 30: (4, 5, 1),\n",
              " 31: (0, 6, 0),\n",
              " 32: (1, 6, 0),\n",
              " 33: (2, 6, 1),\n",
              " 34: (3, 6, 1),\n",
              " 35: (4, 6, 1),\n",
              " 36: (0, 7, 0),\n",
              " 37: (1, 7, 0),\n",
              " 38: (2, 7, 1),\n",
              " 39: (3, 7, 1),\n",
              " 40: (4, 7, 1),\n",
              " 41: (0, 8, 0),\n",
              " 42: (1, 8, 0),\n",
              " 43: (2, 8, 1),\n",
              " 44: (3, 8, 1),\n",
              " 45: (4, 8, 1),\n",
              " 46: (0, 9, 0),\n",
              " 47: (1, 9, 0),\n",
              " 48: (2, 9, 1),\n",
              " 49: (3, 9, 1),\n",
              " 50: (4, 9, 1)}"
            ]
          },
          "metadata": {},
          "execution_count": 2
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 300x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "Nr = 10\n",
        "Nc = 5\n",
        "KOLOR = ['gold','grey']\n",
        "data={}\n",
        "counter =0\n",
        "plt.figure(figsize=(3,5))\n",
        "for r in range(Nr):\n",
        "  for c in range(Nc):\n",
        "    counter +=1\n",
        "    if c<=1:\n",
        "      val=0\n",
        "    else:\n",
        "      val = 1\n",
        "    data[counter] = (c,r,val)\n",
        "    plt.scatter(c,r,s=400, marker = 's', color = KOLOR[val])\n",
        "    plt.text(c,r,s=str(counter), fontsize=8, c='w')\n",
        "\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.axis('off')\n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def check(n,m,data):\n",
        "  wi = (data[n][0],data[n][1])\n",
        "  wj = (data[m][0],data[m][1])\n",
        "  return n!=m and ((wi[0]== wj[0] and abs(wi[1]-wj[1])==1 ) or (wi[1]== wj[1] and abs(wi[0]-wj[0])==1 ) )\n",
        "\n"
      ],
      "metadata": {
        "id": "jPInUR7VouYV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AeesyXV7Q-yP"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 657
        },
        "id": "3-7GCM8FgGYj",
        "outputId": "0a0b9f9e-c708-443e-8b7a-8d700838a1c4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "OPTIMAL\n",
            "0.0 0.0\n",
            "Time  6.598106145858765\n",
            "Min of objective function: 0.0\n",
            "\n",
            "Region 0: 1\n",
            "Region 1: 0\n",
            "Region 2: 1\n",
            "Region 3: 1\n",
            "Region 4: 0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 320x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "\n",
        "regions = range(5)\n",
        "nodes = range(1,50+1)\n",
        "def main() -> None:\n",
        "    # Creates the model.\n",
        "    model = cp_model.CpModel()\n",
        "\n",
        "    assign = {(n,r): model.NewBoolVar(f\"assign_{n}_{r}\") for n in nodes\n",
        "              for r in regions}\n",
        "\n",
        "    source = {(n,r): model.NewBoolVar(f\"source_{n}_{r}\") for n in nodes\n",
        "              for r in regions}\n",
        "    win = {r: model.NewBoolVar( f\"win_{r}\")\n",
        "              for r in regions}\n",
        "\n",
        "\n",
        "    flow = {(i,j,r): model.NewIntVar(0,10,f\"flow_{i}_{j}_{r}\") for i in nodes\n",
        "              for j in nodes for r in regions if check(i,j,data)}\n",
        "\n",
        "    for r in regions:\n",
        "      expressions = [source[n,r] for n in nodes]\n",
        "      model.AddExactlyOne(expressions)\n",
        "\n",
        "      expressions_assign = [assign[n,r] for n in nodes]\n",
        "      model.Add(sum(expressions_assign) == 10)\n",
        "\n",
        "      expressions_winD = [assign[n,r] for n in nodes if data[n][2]==0]\n",
        "      expressions_winR = [assign[n,r] for n in nodes if data[n][2]==1]\n",
        "\n",
        "      model.Add(sum(expressions_winD) != sum(expressions_winR))\n",
        "\n",
        "      model.Add(sum(expressions_winD) > sum(expressions_winR)).OnlyEnforceIf(win[r])\n",
        "      model.Add(sum(expressions_winD) < sum(expressions_winR)).OnlyEnforceIf(win[r].Not())\n",
        "\n",
        "\n",
        "\n",
        "    for n in nodes:\n",
        "      expressions_nodal = [source[n,r] for r in regions]\n",
        "      model.AddAtMostOne(expressions_nodal)\n",
        "\n",
        "      expressions_assign = [assign[n,r] for r in regions]\n",
        "      model.Add(sum(expressions_assign) ==1)\n",
        "\n",
        "\n",
        "    for (n,r) in assign:\n",
        "      model.Add( 10*source[n,r] - assign[n,r] == sum(flow[n,j,r]-flow[j,n,r] for j in nodes if check(n,j,data) ) )\n",
        "      model.Add(source[n,r]<= assign[n,r])\n",
        "\n",
        "    for (i,j,r) in flow:\n",
        "      model.Add(flow[i,j,r] <= 10*assign[i,r])\n",
        "      model.Add(flow[i,j,r] <= 10*assign[j,r])\n",
        "\n",
        "    model.Add(sum(win[r] for r in regions)== 3)\n",
        "\n",
        "    for n in nodes:\n",
        "      for m in nodes:\n",
        "        for r in regions:\n",
        "           wi = (data[n][0],data[n][1])\n",
        "           wj = (data[m][0],data[m][1])\n",
        "           if (wi[0]-wj[0])**2 + (wi[1]-wj[1])**2 > 24:\n",
        "              model.Add(assign[n,r]+assign[m,r] <= 1)\n",
        "\n",
        "\n",
        "    solver = cp_model.CpSolver()\n",
        "    solver.parameters.subsolvers[:] = ['core', 'pseudo_costs', 'no_lp']\n",
        "    solver.parameters.max_time_in_seconds = 1200\n",
        "    solver.parameters.num_search_workers = 4\n",
        "    status = solver.solve(model)\n",
        "    print(solver.StatusName(status))\n",
        "    print(solver.ObjectiveValue(), solver.BestObjectiveBound())\n",
        "\n",
        "    if status == cp_model.OPTIMAL or status == cp_model.FEASIBLE:\n",
        "        return solver , source, assign, flow,win\n",
        "\n",
        "    else:\n",
        "        print(\"No solution found.\")\n",
        "\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "  st= time.time()\n",
        "  solver , source, assign, flow, win = main()\n",
        "  print(\"Time \", time.time()-st)\n",
        "  print(f\"Min of objective function: {solver.objective_value}\\n\")\n",
        "\n",
        "  counter =0\n",
        "  plt.figure(figsize=(3.2,5))\n",
        "  for r in range(Nr):\n",
        "    for c in range(Nc):\n",
        "      counter +=1\n",
        "      if c<=1:\n",
        "        val=0\n",
        "      else:\n",
        "        val = 1\n",
        "      data[counter] = (c,r,val)\n",
        "      plt.scatter(c,r,s=500, marker = 's', color = KOLOR[val], alpha = 0.4)\n",
        "      plt.text(c,r,s=str(counter), fontsize=8, c='w')\n",
        "\n",
        "\n",
        "  plt.tight_layout()\n",
        "  plt.axis('off')\n",
        "\n",
        "  KOLORS = [\n",
        "      \"red\", \"brown\", \"blue\", \"teal\", \"purple\", \"cyan\", \"magenta\",\n",
        "      \"yellow\", \"lime\", \"pink\", \"brown\", \"gray\", \"olive\", \"navy\", \"teal\"]\n",
        "  for r in regions:\n",
        "    print(f\"Region {r}:\", solver.value(win[r]))\n",
        "    for n in nodes:\n",
        "      if solver.value(assign[n,r]):\n",
        "        x,y = data[n][0], data[n][1]\n",
        "        plt.scatter(x,y,s=60, marker = 'o', color = KOLORS[r])\n",
        "      if solver.value(source[n,r]):\n",
        "        x,y = data[n][0], data[n][1]\n",
        "        #plt.scatter(x,y,s=300, marker = 'p', color = KOLOR[r])\n",
        "        #print(n,r)\n",
        "  for (i,j,r),v in flow.items():\n",
        "    if solver.value(v):\n",
        "      x1,y1 = data[i][0], data[i][1]\n",
        "      x2,y2 = data[j][0], data[j][1]\n",
        "      plt.plot([x1,x2],[y1,y2],color = KOLORS[r])\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "n,m = 25, 3\n",
        "wi = (data[n][0],data[n][1])\n",
        "wj = (data[m][0],data[m][1])\n",
        "if (wi[0]-wj[0])**2 + (wi[1]-wj[1])**2 > 25:\n",
        "  print(\"catch\")\n"
      ],
      "metadata": {
        "id": "ZBfRQjiwZZJb"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
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