HW_FuzzyLogic_5_Medical.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/thanhtruongphan/HomeworkAI/blob/main/HW_FuzzyLogic_5_Medical.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Họ tên sinh viên : Phan Thanh Trường**\n",
        "## **Mã số sinh viên : 19146293**\n",
        "## **Bài tập về nhà Fuzzylogic - Medical**"
      ],
      "metadata": {
        "id": "B8CT60rEV0Jx"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h31CsX3wXeKS",
        "outputId": "c6e85ecb-cac2-4485-ea5e-97950ace1ba8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting scikit-fuzzy\n",
            "  Downloading scikit-fuzzy-0.4.2.tar.gz (993 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m994.0/994.0 KB\u001b[0m \u001b[31m17.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: numpy>=1.6.0 in /usr/local/lib/python3.9/dist-packages (from scikit-fuzzy) (1.22.4)\n",
            "Requirement already satisfied: scipy>=0.9.0 in /usr/local/lib/python3.9/dist-packages (from scikit-fuzzy) (1.10.1)\n",
            "Requirement already satisfied: networkx>=1.9.0 in /usr/local/lib/python3.9/dist-packages (from scikit-fuzzy) (3.0)\n",
            "Building wheels for collected packages: scikit-fuzzy\n",
            "  Building wheel for scikit-fuzzy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for scikit-fuzzy: filename=scikit_fuzzy-0.4.2-py3-none-any.whl size=894088 sha256=8c47d3c30a70546a7aec8c817d723a4de0a3ffc6d0458b4d15bbcc1a0ee5a903\n",
            "  Stored in directory: /root/.cache/pip/wheels/32/2c/a1/a90a7d7dd8448ec029f298a61f3490275e99b17aa348be675c\n",
            "Successfully built scikit-fuzzy\n",
            "Installing collected packages: scikit-fuzzy\n",
            "Successfully installed scikit-fuzzy-0.4.2\n"
          ]
        }
      ],
      "source": [
        "!pip install scikit-fuzzy\n",
        "import numpy as np \n",
        "import skfuzzy as fuzz \n",
        "from skfuzzy import control as  ctrl "
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 1**"
      ],
      "metadata": {
        "id": "uYMlAGt1-B2l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fever=ctrl.Antecedent(np.arange(0,0.9,0.1),'Fever')\n",
        "headache=ctrl.Antecedent(np.arange(0,0.9,0.1),'Headache')\n",
        "nausea=ctrl.Antecedent(np.arange(0,0.9,0.1),'Nausea')\n",
        "vomiting=ctrl.Antecedent(np.arange(0,0.9,0.1),'Vomiting')\n",
        "\n",
        "out1=ctrl.Consequent(np.arange(0,0.9,0.1),'Out1')\n",
        "\n",
        "ijaundice=ctrl.Antecedent(np.arange(0,0.9,0.1),'Ijaundice')\n",
        "enlarge_liver=ctrl.Antecedent(np.arange(0,0.9,0.1),'Enlarge_liver')\n",
        "joint_pain=ctrl.Antecedent(np.arange(0,0.9,0.1),'Joint_pain')\n",
        "body_weakness=ctrl.Antecedent(np.arange(0,0.9,0.1),'Body_weakness')\n",
        "\n",
        "out2=ctrl.Consequent(np.arange(0,0.9,0.1),'Out2')\n",
        "\n",
        "dizziness=ctrl.Antecedent(np.arange(0,0.9,0.1),'Dizziness')\n",
        "loss_of_appetite=ctrl.Antecedent(np.arange(0,0.9,0.1),'Loss_of_appetite')\n",
        "mp=ctrl.Antecedent(np.arange(0,0.9,0.1),'Mp')\n",
        "\n",
        "out3=ctrl.Consequent(np.arange(0,0.9,0.1),'Out3')\n",
        "\n",
        "conclu=ctrl.Consequent(np.arange(0,0.9,0.1),'Conclu')\n",
        "\n",
        "fever['Mild']=fuzz.trimf(fever.universe,[0 ,0.15, 0.3])\n",
        "fever['Moderate']=fuzz.trimf(fever.universe,[ 0.3, 0.45, 0.6])\n",
        "fever['Severe']=fuzz.trimf(fever.universe,[0.6, 0.7 ,0.8 ])\n",
        "\n",
        "headache['Mild']=fuzz.trimf(headache.universe,[0 ,0.15, 0.3])\n",
        "headache['Moderate']=fuzz.trimf(headache.universe,[ 0.3 ,0.45, 0.6])\n",
        "headache['Severe']=fuzz.trimf(headache.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "nausea['Mild']=fuzz.trimf(nausea.universe,[0 ,0.15 ,0.3])\n",
        "nausea['Moderate']=fuzz.trimf(nausea.universe,[ 0.3, 0.45, 0.6])\n",
        "nausea['Severe']=fuzz.trimf(nausea.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "vomiting['Mild']=fuzz.trimf(vomiting.universe,[0 ,0.15 ,0.3])\n",
        "vomiting['Moderate']=fuzz.trimf(vomiting.universe,[ 0.3, 0.45, 0.6])\n",
        "vomiting['Severe']=fuzz.trimf(vomiting.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "ijaundice['Mild']=fuzz.trimf(ijaundice.universe,[0 ,0.15 ,0.3])\n",
        "ijaundice['Moderate']=fuzz.trimf(ijaundice.universe,[ 0.3 ,0.45, 0.6])\n",
        "ijaundice['Severe']=fuzz.trimf(ijaundice.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "enlarge_liver['Mild']=fuzz.trimf(enlarge_liver.universe,[0, 0.15 ,0.3])\n",
        "enlarge_liver['Moderate']=fuzz.trimf(enlarge_liver.universe,[ 0.3, 0.45, 0.6])\n",
        "enlarge_liver['Severe']=fuzz.trimf(enlarge_liver.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "joint_pain['Mild']=fuzz.trimf(joint_pain.universe,[0 ,0.15 ,0.3])\n",
        "joint_pain['Moderate']=fuzz.trimf(joint_pain.universe,[ 0.3, 0.45, 0.6])\n",
        "joint_pain['Severe']=fuzz.trimf(joint_pain.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "body_weakness['Mild']=fuzz.trimf(body_weakness.universe,[0 ,0.15, 0.3])\n",
        "body_weakness['Moderate']=fuzz.trimf(body_weakness.universe,[ 0.3, 0.45, 0.6])\n",
        "body_weakness['Severe']=fuzz.trimf(body_weakness.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "dizziness['Mild']=fuzz.trimf(dizziness.universe,[0, 0.15 ,0.3])\n",
        "dizziness['Moderate']=fuzz.trimf(dizziness.universe,[ 0.3, 0.45, 0.6])\n",
        "dizziness['Severe']=fuzz.trimf(dizziness.universe,[0.6, 0.7 ,0.8 ])\n",
        "\n",
        "loss_of_appetite['Mild']=fuzz.trimf(loss_of_appetite.universe,[0 ,0.15, 0.3])\n",
        "loss_of_appetite['Moderate']=fuzz.trimf(loss_of_appetite.universe,[ 0.3, 0.45, 0.6])\n",
        "loss_of_appetite['Severe']=fuzz.trimf(loss_of_appetite.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "mp['Mild']=fuzz.trimf(mp.universe,[0 ,0.15, 0.3])\n",
        "mp['Moderate']=fuzz.trimf(mp.universe,[ 0.3, 0.45, 0.6])\n",
        "mp['Severe']=fuzz.trimf(mp.universe,[0.6 ,0.7 ,0.8 ])\n",
        "\n",
        "out1['Mild']=fuzz.trimf(out1.universe,[0 ,0.15, 0.3])\n",
        "out1['Moderate']=fuzz.trimf(out1.universe,[ 0.3, 0.45, 0.6])\n",
        "out1['Severe']=fuzz.trimf(out1.universe,[0.6, 0.7 ,0.8 ])\n",
        "\n",
        "out2['Mild']=fuzz.trimf(out2.universe,[0 ,0.15, 0.3])\n",
        "out2['Moderate']=fuzz.trimf(out2.universe,[ 0.3, 0.45, 0.6])\n",
        "out2['Severe']=fuzz.trimf(out2.universe,[0.6, 0.7 ,0.8 ])\n",
        "\n",
        "out3['Mild']=fuzz.trimf(out3.universe,[0 ,0.15, 0.3])\n",
        "out3['Moderate']=fuzz.trimf(out3.universe,[ 0.3, 0.45, 0.6])\n",
        "out3['Severe']=fuzz.trimf(out3.universe,[0.6, 0.7 ,0.8 ])\n",
        "\n",
        "conclu['Mild']=fuzz.trimf(conclu.universe,[0 ,0.15, 0.3])\n",
        "conclu['Moderate']=fuzz.trimf(conclu.universe,[ 0.3, 0.45, 0.6])\n",
        "conclu['Severe']=fuzz.trimf(conclu.universe,[0.6, 0.7 ,0.8 ])\n",
        "\n",
        "fever.view()\n",
        "headache.view()\n",
        "nausea.view()\n",
        "vomiting.view()\n",
        "ijaundice.view()\n",
        "enlarge_liver.view()\n",
        "joint_pain.view()\n",
        "body_weakness.view()\n",
        "dizziness.view()\n",
        "loss_of_appetite.view()\n",
        "mp.view()\n",
        "conclu.view()\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "03X8R5UuXlaw",
        "outputId": "8c2a8b9c-4b58-4706-cbd1-870e32f9fe42"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# concluing_ctrl = ctrl.ControlSystem([rule1,rule2,rule3,rule4,rule5,rule6,rule7,rule8,rule9,rule10,rule11,rule12,rule13,rule14,rule15,rule16,rule17,rule18,rule19,rule20,rule21,rule22,rule23,rule24,rule25,rule26,rule27,rule28,rule29,rule30,rule31,rule32,rule33,rule34,rule35,rule36,rule37,rule38,rule39,rule40,rule41,rule42,rule43,rule44,rule45,rule46,rule47,rule48,rule49,rule50,rule51,rule52,rule53,rule54])\n",
        "# concluing = ctrl.ControlSystemSimulation(concluing_ctrl)\n",
        "# concluing.input['fever'] = 0.4\n",
        "# concluing.input['headache'] = 0.2\n",
        "# concluing.input['nausea'] = 0.8\n",
        "# concluing.input['vomiting'] = 0.5\n",
        "# concluing.compute()\n",
        "# print(concluing.output['conclu'])\n",
        "# conclu.view(sim=concluing)\n",
        "\n"
      ],
      "metadata": {
        "id": "7jT-YgtqX1it"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 2 - Rules 1**"
      ],
      "metadata": {
        "id": "atAfjaWG-HJA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "rule1 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Mild'])\n",
        "rule2 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Mild'])\n",
        "rule3 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Mild'])\n",
        "\n",
        "rule4 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Mild'])\n",
        "rule5 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Mild'])\n",
        "rule6 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Mild'])\n",
        "\n",
        "rule7 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Mild'])\n",
        "rule8 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Mild'])\n",
        "rule9 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Mild'])\n",
        "rule10 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Mild'])\n",
        "rule11 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Mild'])\n",
        "rule12 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Mild'])\n",
        "\n",
        "rule13 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Mild'])\n",
        "rule14 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Mild'])\n",
        "rule15 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Mild'])\n",
        "\n",
        "rule16 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Mild'])\n",
        "rule17 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Mild'])\n",
        "rule18 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Mild'])\n",
        "\n",
        "rule19 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Mild'])\n",
        "rule20= ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Mild'])\n",
        "rule21 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Mild'])\n",
        "\n",
        "rule22 = ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Mild'])\n",
        "rule23= ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Mild'])\n",
        "rule24= ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Mild'])\n",
        "\n",
        "rule25= ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Mild'])\n",
        "rule26= ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Mild'])\n",
        "rule27= ctrl.Rule(fever['Mild']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Mild'])\n",
        "rule28= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Mild'])\n",
        "rule29= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Mild'])\n",
        "rule30= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Mild'])\n",
        "\n",
        "rule31= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Mild'])\n",
        "rule32= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Mild'])\n",
        "rule33= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Mild'])\n",
        "\n",
        "rule34= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Mild'])\n",
        "rule35= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Mild'])\n",
        "rule36= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Mild'])\n",
        "rule37= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Mild'])\n",
        "rule38= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Mild'])\n",
        "rule39= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Mild'])\n",
        "\n",
        "rule40= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule41= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule42= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule43= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule44= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule45= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "\n",
        "rule46= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule47= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule48= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule49 = ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule50 = ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule51 = ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule52 = ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule53 = ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule54= ctrl.Rule(fever['Mild']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule55 = ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "rule56= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "rule57= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule58= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule59= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule60= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule61= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule62= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule63= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule64= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "rule65= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "rule66= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule67= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule68= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule69= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule70= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule71= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule72= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "\n",
        "rule73= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule74= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule75= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule76= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule77= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule78= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule79= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule80= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule81= ctrl.Rule(fever['Mild']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule82= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "rule83= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "rule84= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule85= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule86= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule87= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule88= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule89= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule90 = ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule91= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "rule92= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "rule93= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule94= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule95= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule96= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule97= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule98= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule99= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "\n",
        "rule100= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule101= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule102= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule103= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule104= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule105= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule106= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule107 = ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule108= ctrl.Rule(fever['Moderate']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule109 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "rule110 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "rule111 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule112 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule113 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule114 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule115 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule116 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule117 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule118 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "rule119 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "rule120 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule121 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule122 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule123 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule124 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule125 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule126 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "\n",
        "rule127 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule128 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule129 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule130 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule131 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule132 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule133 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule134 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule135 = ctrl.Rule(fever['Moderate']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule136 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "rule137 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "rule138 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule139 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule140 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule141 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule142 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule143 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule144 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Moderate'])\n",
        "rule145 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "rule146 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "rule147 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule148 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule149 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule150 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule151 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule152 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "rule153 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Moderate'])\n",
        "\n",
        "rule154 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule155 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "rule156 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Moderate'])\n",
        "\n",
        "rule157 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule158 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "rule159 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Moderate'])\n",
        "\n",
        "rule160 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule161 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "rule162 = ctrl.Rule(fever['Moderate']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Moderate'])\n",
        "\n",
        "rule163 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "rule164 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "rule165 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule166 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "rule167 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "rule168 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule169 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule170 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule171 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule172 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "rule173 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "rule174 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule175 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "rule176 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "rule177 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule178 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "rule179 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "rule180 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "\n",
        "rule181 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "rule182 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "rule183 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule184 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "rule185 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "rule186 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule187 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n",
        "rule188 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n",
        "rule189 = ctrl.Rule(fever['Severe']&headache['Mild']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n",
        "rule190 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "rule191 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "rule192 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule193 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "rule194 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "rule195 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule196 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule197 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule198 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule199 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "rule200 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "rule201 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule202= ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "rule203= ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "rule204= ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule205= ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "rule206= ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "rule207= ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "\n",
        "rule208= ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "rule209= ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "rule210 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule211 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "rule212 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "rule213 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule214 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n",
        "rule215 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n",
        "rule216 = ctrl.Rule(fever['Severe']&headache['Moderate']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n",
        "rule217 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "rule218 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "rule219= ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule220 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "rule221 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "rule222 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule223 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule224 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule225 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Mild']&vomiting['Severe'],out1['Severe'])\n",
        "rule226 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "rule227 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "rule228 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule229 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "rule230 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "rule231 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule232 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "rule233 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "rule234 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Moderate']&vomiting['Severe'],out1['Severe'])\n",
        "\n",
        "rule235 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "rule236 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "rule237 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Mild'],out1['Severe'])\n",
        "\n",
        "rule238 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "rule239 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "rule240 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Moderate'],out1['Severe'])\n",
        "\n",
        "rule241 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n",
        "rule242 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n",
        "rule243 = ctrl.Rule(fever['Severe']&headache['Severe']&nausea['Severe']&vomiting['Severe'],out1['Severe'])\n"
      ],
      "metadata": {
        "id": "E2v7eYdBX9M_"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 2 - Rules 2**"
      ],
      "metadata": {
        "id": "j1mATlra-QtD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "rule1_1 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_2 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_3 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Mild'])\n",
        "\n",
        "rule1_4 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Mild'])\n",
        "rule1_5 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Mild'])\n",
        "rule1_6 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Mild'])\n",
        "\n",
        "rule1_7 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Mild'])\n",
        "rule1_8 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Mild'])\n",
        "rule1_9 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Mild'])\n",
        "   \n",
        "rule1_10 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_11 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_12 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Mild'])\n",
        "\n",
        "rule1_13 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Mild'])\n",
        "rule1_14 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Mild'])\n",
        "rule1_15 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Mild'])\n",
        "\n",
        "rule1_16 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Mild'])\n",
        "rule1_17 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Mild'])\n",
        "rule1_18 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Mild'])\n",
        "\n",
        "   \n",
        "rule1_19 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_20= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_21 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Mild'])\n",
        "\n",
        "rule1_22 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Mild'])\n",
        "rule1_23= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Mild'])\n",
        "rule1_24= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Mild'])\n",
        "\n",
        "rule1_25= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Mild'])\n",
        "rule1_26= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Mild'])\n",
        "rule1_27= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Mild'])\n",
        "                          \n",
        "                     \n",
        "rule1_28= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_29= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_30= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Mild'])\n",
        "\n",
        "rule1_31= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Mild'])\n",
        "rule1_32= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Mild'])\n",
        "rule1_33= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Mild'])\n",
        "\n",
        "rule1_34= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Mild'])\n",
        "rule1_35= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Mild'])\n",
        "rule1_36= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Mild'])\n",
        "   \n",
        "rule1_37= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_38= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Mild'])\n",
        "rule1_39= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Mild'])\n",
        "\n",
        "rule1_40= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_41= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_42= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_43= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_44= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_45= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "\n",
        "   \n",
        "rule1_46= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_47= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_48= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_49 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_50 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_51 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_52 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_53 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_54= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "                \n",
        "       \n",
        "rule1_55 = ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_56= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_57= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_58= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_59= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_60= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_61= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_62= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_63= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "   \n",
        "rule1_64= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_65= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_66= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_67= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_68= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_69= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_70= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_71= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_72= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "\n",
        "   \n",
        "rule1_73= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_74= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_75= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_76= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_77= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_78= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_79= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_80= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_81= ctrl.Rule(ijaundice['Mild']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "                  \n",
        "                          \n",
        "                               \n",
        "rule1_82= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_83= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_84= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_85= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_86= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_87= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_88= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_89= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_90 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "   \n",
        "rule1_91= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_92= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_93= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_94= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_95= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_96= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_97= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_98= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_99= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "\n",
        "   \n",
        "rule1_100= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_101= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_102= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_103= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_104= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_105= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_106= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_107 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_108= ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "                          \n",
        "                     \n",
        "rule1_109 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_110 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_111 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_112 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_113 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_114 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_115 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_116 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_117 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "   \n",
        "rule1_118 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_119 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_120 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_121 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_122 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_123 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_124 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_125 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_126 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "\n",
        "   \n",
        "rule1_127 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_128 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_129 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_130 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_131 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_132 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_133 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_134 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_135 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "                \n",
        "       \n",
        "rule1_136 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_137 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_138 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_139 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_140 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_141 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_142 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_143 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_144 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Moderate'])\n",
        "   \n",
        "rule1_145 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_146 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_147 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_148 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_149 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_150 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_151 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_152 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_153 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Moderate'])\n",
        "\n",
        "   \n",
        "rule1_154 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_155 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "rule1_156 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Moderate'])\n",
        "\n",
        "rule1_157 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_158 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "rule1_159 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Moderate'])\n",
        "\n",
        "rule1_160 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_161 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "rule1_162 = ctrl.Rule(ijaundice['Moderate']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Moderate'])\n",
        "\n",
        "                       \n",
        "                       \n",
        "                        \n",
        "rule1_163 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_164 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_165 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_166 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_167 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_168 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_169 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_170 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_171 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "   \n",
        "rule1_172 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_173 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_174 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_175 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_176 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_177 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_178 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_179 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_180 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "\n",
        "   \n",
        "rule1_181 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_182 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_183 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_184 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_185 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_186 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_187 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_188 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_189 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Mild']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])\n",
        "                          \n",
        "                     \n",
        "rule1_190 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_191 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_192 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_193 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_194 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_195 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_196 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_197 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_198 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "   \n",
        "rule1_199 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_200 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_201 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_202= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_203= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_204= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_205= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_206= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_207= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "\n",
        "   \n",
        "rule1_208= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_209= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_210 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_211 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_212 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_213 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_214 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_215 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_216 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Moderate']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])\n",
        "                \n",
        "       \n",
        "rule1_217 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_218 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_219= ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_220 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_221 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_222 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_223 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_224 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_225 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Mild']&body_weakness['Severe'],out2['Severe'])\n",
        "   \n",
        "rule1_226 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_227 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_228 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_229 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_230 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_231 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_232 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_233 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_234 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Moderate']&body_weakness['Severe'],out2['Severe'])\n",
        "\n",
        "   \n",
        "rule1_235 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_236 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "rule1_237 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Mild'],out2['Severe'])\n",
        "\n",
        "rule1_238 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_239 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "rule1_240 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Moderate'],out2['Severe'])\n",
        "\n",
        "rule1_241 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_242 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])\n",
        "rule1_243 = ctrl.Rule(ijaundice['Severe']&enlarge_liver['Severe']&joint_pain['Severe']&body_weakness['Severe'],out2['Severe'])"
      ],
      "metadata": {
        "id": "htOJwXCuy2va"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Part 2 - Rules 3**"
      ],
      "metadata": {
        "id": "F0MnQzLx-UbW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "rule2_1 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Mild'],out3['Mild'])\n",
        "rule2_2 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Mild'],out3['Mild'])\n",
        "rule2_3 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Mild'],out3['Mild'])\n",
        "\n",
        "rule2_4 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Moderate'],out3['Mild'])\n",
        "rule2_5 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Moderate'],out3['Mild'])\n",
        "rule2_6 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Moderate'],out3['Mild'])\n",
        "\n",
        "rule2_7 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Severe'],out3['Mild'])\n",
        "rule2_8 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Severe'],out3['Mild'])\n",
        "rule2_9 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Mild']&mp['Severe'],out3['Mild'])\n",
        "   \n",
        "rule2_10 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Mild'],out3['Mild'])\n",
        "rule2_11 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Mild'],out3['Mild'])\n",
        "rule2_12 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Mild'],out3['Mild'])\n",
        "\n",
        "rule2_13 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Mild'])\n",
        "rule2_14 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Mild'])\n",
        "rule2_15 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Mild'])\n",
        "\n",
        "rule2_16 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Severe'],out3['Mild'])\n",
        "rule2_17 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Severe'],out3['Mild'])\n",
        "rule2_18 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Moderate']&mp['Severe'],out3['Mild'])\n",
        "\n",
        "   \n",
        "rule2_19 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Mild'],out3['Mild'])\n",
        "rule2_20= ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Mild'],out3['Mild'])\n",
        "rule2_21 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Mild'],out3['Mild'])\n",
        "\n",
        "rule2_22 = ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Moderate'],out3['Mild'])\n",
        "rule2_23= ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Moderate'],out3['Mild'])\n",
        "rule2_24= ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Moderate'],out3['Mild'])\n",
        "\n",
        "rule2_25= ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Severe'],out3['Mild'])\n",
        "rule2_26= ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Severe'],out3['Mild'])\n",
        "rule2_27= ctrl.Rule(dizziness['Mild']&loss_of_appetite['Severe']&mp['Severe'],out3['Mild'])\n",
        "                          \n",
        "                     \n",
        "rule2_28= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Mild'],out3['Mild'])\n",
        "rule2_29= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Mild'],out3['Mild'])\n",
        "rule2_30= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Mild'],out3['Mild'])\n",
        "\n",
        "rule2_31= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Moderate'],out3['Moderate'])\n",
        "rule2_32= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Moderate'],out3['Moderate'])\n",
        "rule2_33= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Moderate'],out3['Moderate'])\n",
        "\n",
        "rule2_34= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Severe'],out3['Moderate'])\n",
        "rule2_35= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Severe'],out3['Moderate'])\n",
        "rule2_36= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Mild']&mp['Severe'],out3['Moderate'])\n",
        "   \n",
        "rule2_37= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Mild'],out3['Moderate'])\n",
        "rule2_38= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Mild'],out3['Moderate'])\n",
        "rule2_39= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Mild'],out3['Moderate'])\n",
        "\n",
        "rule2_40= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Moderate'])\n",
        "rule2_41= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Moderate'])\n",
        "rule2_42= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Moderate'])\n",
        "\n",
        "rule2_43= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Severe'],out3['Moderate'])\n",
        "rule2_44= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Severe'],out3['Moderate'])\n",
        "rule2_45= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Moderate']&mp['Severe'],out3['Moderate'])\n",
        "\n",
        "   \n",
        "rule2_46= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Mild'],out3['Moderate'])\n",
        "rule2_47= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Mild'],out3['Moderate'])\n",
        "rule2_48= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Mild'],out3['Moderate'])\n",
        "\n",
        "rule2_49 = ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Moderate'],out3['Moderate'])\n",
        "rule2_50 = ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Moderate'],out3['Moderate'])\n",
        "rule2_51 = ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Moderate'],out3['Moderate'])\n",
        "\n",
        "rule2_52 = ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Severe'],out3['Moderate'])\n",
        "rule2_53 = ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Severe'],out3['Moderate'])\n",
        "rule2_54= ctrl.Rule(dizziness['Moderate']&loss_of_appetite['Severe']&mp['Severe'],out3['Moderate'])\n",
        "                \n",
        "       \n",
        "rule2_55 = ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Mild'],out3['Severe'])\n",
        "rule2_56= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Mild'],out3['Severe'])\n",
        "rule2_57= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Mild'],out3['Severe'])\n",
        "\n",
        "rule2_58= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Moderate'],out3['Severe'])\n",
        "rule2_59= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Moderate'],out3['Severe'])\n",
        "rule2_60= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Moderate'],out3['Severe'])\n",
        "\n",
        "rule2_61= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Severe'],out3['Severe'])\n",
        "rule2_62= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Severe'],out3['Severe'])\n",
        "rule2_63= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Mild']&mp['Severe'],out3['Severe'])\n",
        "   \n",
        "rule2_64= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Mild'],out3['Severe'])\n",
        "rule2_65= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Mild'],out3['Severe'])\n",
        "rule2_66= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Mild'],out3['Severe'])\n",
        "\n",
        "rule2_67= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Severe'])\n",
        "rule2_68= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Severe'])\n",
        "rule2_69= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Moderate'],out3['Severe'])\n",
        "\n",
        "rule2_70= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Severe'],out3['Severe'])\n",
        "rule2_71= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Severe'],out3['Severe'])\n",
        "rule2_72= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Moderate']&mp['Severe'],out3['Severe'])\n",
        "\n",
        "   \n",
        "rule2_73= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Mild'],out3['Severe'])\n",
        "rule2_74= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Mild'],out3['Severe'])\n",
        "rule2_75= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Mild'],out3['Severe'])\n",
        "\n",
        "rule2_76= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Moderate'],out3['Severe'])\n",
        "rule2_77= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Moderate'],out3['Severe'])\n",
        "rule2_78= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Moderate'],out3['Severe'])\n",
        "\n",
        "rule2_79= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Severe'],out3['Severe'])\n",
        "rule2_80= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Severe'],out3['Severe'])\n",
        "rule2_81= ctrl.Rule(dizziness['Severe']&loss_of_appetite['Severe']&mp['Severe'],out3['Severe'])\n"
      ],
      "metadata": {
        "id": "NOyh6hT80lXv"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "rule3_1 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Mild'],conclu['Mild'])\n",
        "rule3_2 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Mild'],conclu['Mild'])\n",
        "rule3_3 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Mild'],conclu['Mild'])\n",
        "\n",
        "rule3_4 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Moderate'],conclu['Mild'])\n",
        "rule3_5 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Moderate'],conclu['Mild'])\n",
        "rule3_6 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Moderate'],conclu['Mild'])\n",
        "\n",
        "rule3_7 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Severe'],conclu['Mild'])\n",
        "rule3_8 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Severe'],conclu['Mild'])\n",
        "rule3_9 = ctrl.Rule(out1['Mild']&out2['Mild']&out3['Severe'],conclu['Mild'])\n",
        "rule3_10 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Mild'],conclu['Mild'])\n",
        "rule3_11 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Mild'],conclu['Mild'])\n",
        "rule3_12 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Mild'],conclu['Mild'])\n",
        "\n",
        "rule3_13 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Moderate'],conclu['Mild'])\n",
        "rule3_14 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Moderate'],conclu['Mild'])\n",
        "rule3_15 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Moderate'],conclu['Mild'])\n",
        "\n",
        "rule3_16 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Severe'],conclu['Mild'])\n",
        "rule3_17 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Severe'],conclu['Mild'])\n",
        "rule3_18 = ctrl.Rule(out1['Mild']&out2['Moderate']&out3['Severe'],conclu['Mild'])\n",
        "\n",
        "rule3_19 = ctrl.Rule(out1['Mild']&out2['Severe']&out3['Mild'],conclu['Mild'])\n",
        "rule3_20= ctrl.Rule(out1['Mild']&out2['Severe']&out3['Mild'],conclu['Mild'])\n",
        "rule3_21 = ctrl.Rule(out1['Mild']&out2['Severe']&out3['Mild'],conclu['Mild'])\n",
        "\n",
        "rule3_22 = ctrl.Rule(out1['Mild']&out2['Severe']&out3['Moderate'],conclu['Mild'])\n",
        "rule3_23= ctrl.Rule(out1['Mild']&out2['Severe']&out3['Moderate'],conclu['Mild'])\n",
        "rule3_24= ctrl.Rule(out1['Mild']&out2['Severe']&out3['Moderate'],conclu['Mild'])\n",
        "\n",
        "rule3_25= ctrl.Rule(out1['Mild']&out2['Severe']&out3['Severe'],conclu['Mild'])\n",
        "rule3_26= ctrl.Rule(out1['Mild']&out2['Severe']&out3['Severe'],conclu['Mild'])\n",
        "rule3_27= ctrl.Rule(out1['Mild']&out2['Severe']&out3['Severe'],conclu['Mild'])\n",
        "rule3_28= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Mild'],conclu['Mild'])\n",
        "rule3_29= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Mild'],conclu['Mild'])\n",
        "rule3_30= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Mild'],conclu['Mild'])\n",
        "\n",
        "rule3_31= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Moderate'],conclu['Moderate'])\n",
        "rule3_32= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Moderate'],conclu['Moderate'])\n",
        "rule3_33= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Moderate'],conclu['Moderate'])\n",
        "\n",
        "rule3_34= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Severe'],conclu['Moderate'])\n",
        "rule3_35= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Severe'],conclu['Moderate'])\n",
        "rule3_36= ctrl.Rule(out1['Moderate']&out2['Mild']&out3['Severe'],conclu['Moderate'])\n",
        "rule3_37= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Mild'],conclu['Moderate'])\n",
        "rule3_38= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Mild'],conclu['Moderate'])\n",
        "rule3_39= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Mild'],conclu['Moderate'])\n",
        "\n",
        "rule3_40= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Moderate'],conclu['Moderate'])\n",
        "rule3_41= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Moderate'],conclu['Moderate'])\n",
        "rule3_42= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Moderate'],conclu['Moderate'])\n",
        "\n",
        "rule3_43= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Severe'],conclu['Moderate'])\n",
        "rule3_44= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Severe'],conclu['Moderate'])\n",
        "rule3_45= ctrl.Rule(out1['Moderate']&out2['Moderate']&out3['Severe'],conclu['Moderate'])\n",
        "\n",
        "rule3_46= ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Mild'],conclu['Moderate'])\n",
        "rule3_47= ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Mild'],conclu['Moderate'])\n",
        "rule3_48= ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Mild'],conclu['Moderate'])\n",
        "\n",
        "rule3_49 = ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Moderate'],conclu['Moderate'])\n",
        "rule3_50 = ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Moderate'],conclu['Moderate'])\n",
        "rule3_51 = ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Moderate'],conclu['Moderate'])\n",
        "\n",
        "rule3_52 = ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Severe'],conclu['Moderate'])\n",
        "rule3_53 = ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Severe'],conclu['Moderate'])\n",
        "rule3_54= ctrl.Rule(out1['Moderate']&out2['Severe']&out3['Severe'],conclu['Moderate'])\n",
        "rule3_55 = ctrl.Rule(out1['Severe']&out2['Mild']&out3['Mild'],conclu['Severe'])\n",
        "rule3_56= ctrl.Rule(out1['Severe']&out2['Mild']&out3['Mild'],conclu['Severe'])\n",
        "rule3_57= ctrl.Rule(out1['Severe']&out2['Mild']&out3['Mild'],conclu['Severe'])\n",
        "\n",
        "rule3_58= ctrl.Rule(out1['Severe']&out2['Mild']&out3['Moderate'],conclu['Severe'])\n",
        "rule3_59= ctrl.Rule(out1['Severe']&out2['Mild']&out3['Moderate'],conclu['Severe'])\n",
        "rule3_60= ctrl.Rule(out1['Severe']&out2['Mild']&out3['Moderate'],conclu['Severe'])\n",
        "\n",
        "rule3_61= ctrl.Rule(out1['Severe']&out2['Mild']&out3['Severe'],conclu['Severe'])\n",
        "rule3_62= ctrl.Rule(out1['Severe']&out2['Mild']&out3['Severe'],conclu['Severe'])\n",
        "rule3_63= ctrl.Rule(out1['Severe']&out2['Mild']&out3['Severe'],conclu['Severe'])\n",
        "rule3_64= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Mild'],conclu['Severe'])\n",
        "rule3_65= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Mild'],conclu['Severe'])\n",
        "rule3_66= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Mild'],conclu['Severe'])\n",
        "\n",
        "rule3_67= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Moderate'],conclu['Severe'])\n",
        "rule3_68= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Moderate'],conclu['Severe'])\n",
        "rule3_69= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Moderate'],conclu['Severe'])\n",
        "\n",
        "rule3_70= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Severe'],conclu['Severe'])\n",
        "rule3_71= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Severe'],conclu['Severe'])\n",
        "rule3_72= ctrl.Rule(out1['Severe']&out2['Moderate']&out3['Severe'],conclu['Severe'])\n",
        "\n",
        "rule3_73= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Mild'],conclu['Severe'])\n",
        "rule3_74= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Mild'],conclu['Severe'])\n",
        "rule3_75= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Mild'],conclu['Severe'])\n",
        "\n",
        "rule3_76= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Moderate'],conclu['Severe'])\n",
        "rule3_77= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Moderate'],conclu['Severe'])\n",
        "rule3_78= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Moderate'],conclu['Severe'])\n",
        "\n",
        "rule3_79= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Severe'],conclu['Severe'])\n",
        "rule3_80= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Severe'],conclu['Severe'])\n",
        "rule3_81= ctrl.Rule(out1['Severe']&out2['Severe']&out3['Severe'],conclu['Severe'])\n",
        "\n"
      ],
      "metadata": {
        "id": "9ipwfX4tR6A5"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "concluing_ctrl = ctrl.ControlSystem([rule1, rule2, rule3, rule4, rule5, rule6, rule7, rule8, rule9, rule10, rule11, rule12, rule13, rule14, rule15, rule16, rule17, rule18, rule19, rule20, rule21, rule22, rule23, rule24, rule25, rule26, rule27, rule28, rule29, rule30, rule31, rule32, rule33, rule34, rule35, rule36, rule37, rule38, rule39, rule40, rule41, rule42, rule43, rule44, rule45, rule46, rule47, rule48, rule49, rule50, rule51, rule52, rule53, rule54, rule55, rule56, rule57, rule58, rule59, rule60, rule61, rule62, rule63, rule64, rule65, rule66, rule67, rule68, rule69, rule70, rule71, rule72, rule73, rule74, rule75, rule76, rule77, rule78, rule79, rule80, rule81, rule82, rule83, rule84, rule85, rule86, rule87, rule88, rule89, rule90, rule91, rule92, rule93, rule94, rule95, rule96, rule97, rule98, rule99, rule100, rule101, rule102, rule103, rule104, rule105, rule106, rule107, rule108, rule109, rule110, rule111, rule112, rule113, rule114, rule115, rule116, rule117, rule118, rule119, rule120, rule121, rule122, rule123, rule124, rule125, rule126, rule127, rule128, rule129, rule130, rule131, rule132, rule133, rule134, rule135, rule136, rule137, rule138, rule139, rule140, rule141, rule142, rule143, rule144, rule145, rule146, rule147, rule148, rule149, rule150, rule151, rule152, rule153, rule154, rule155, rule156, rule157, rule158, rule159, rule160, rule161, rule162, rule163, rule164, rule165, rule166, rule167, rule168, rule169, rule170, rule171, rule172, rule173, rule174, rule175, rule176, rule177, rule178, rule179, rule180, rule181, rule182, rule183, rule184, rule185, rule186, rule187, rule188, rule189, rule190, rule191, rule192, rule193, rule194, rule195, rule196, rule197, rule198, rule199, rule200, rule201, rule202, rule203, rule204, rule205, rule206, rule207, rule208, rule209, rule210, rule211, rule212, rule213, rule214, rule215, rule216, rule217, rule218, rule219, rule220, rule221, rule222, rule223, rule224, rule225, rule226, rule227, rule228, rule229, rule230, rule231, rule232, rule233, rule234, rule235, rule236, rule237, rule238, rule239, rule240, rule241, rule242, rule243,rule1_1, rule1_2, rule1_3, rule1_4, rule1_5, rule1_6, rule1_7, rule1_8, rule1_9, rule1_10, rule1_11, rule1_12, rule1_13, rule1_14, rule1_15, rule1_16, rule1_17, rule1_18, rule1_19, rule1_20, rule1_21, rule1_22, rule1_23, rule1_24, rule1_25, rule1_26, rule1_27, rule1_28, rule1_29, rule1_30, rule1_31, rule1_32, rule1_33, rule1_34, rule1_35, rule1_36, rule1_37, rule1_38, rule1_39, rule1_40, rule1_41, rule1_42, rule1_43, rule1_44, rule1_45, rule1_46, rule1_47, rule1_48, rule1_49, rule1_50, rule1_51, rule1_52, rule1_53, rule1_54, rule1_55, rule1_56, rule1_57, rule1_58, rule1_59, rule1_60, rule1_61, rule1_62, rule1_63, rule1_64, rule1_65, rule1_66, rule1_67, rule1_68, rule1_69, rule1_70, rule1_71, rule1_72, rule1_73, rule1_74, rule1_75, rule1_76, rule1_77, rule1_78, rule1_79, rule1_80, rule1_81, rule1_82, rule1_83, rule1_84, rule1_85, rule1_86, rule1_87, rule1_88, rule1_89, rule1_90, rule1_91, rule1_92, rule1_93, rule1_94, rule1_95, rule1_96, rule1_97, rule1_98, rule1_99, rule1_100, rule1_101, rule1_102, rule1_103, rule1_104, rule1_105, rule1_106, rule1_107, rule1_108, rule1_109, rule1_110, rule1_111, rule1_112, rule1_113, rule1_114, rule1_115, rule1_116, rule1_117, rule1_118, rule1_119, rule1_120, rule1_121, rule1_122, rule1_123, rule1_124, rule1_125, rule1_126, rule1_127, rule1_128, rule1_129, rule1_130, rule1_131, rule1_132, rule1_133, rule1_134, rule1_135, rule1_136, rule1_137, rule1_138, rule1_139, rule1_140, rule1_141, rule1_142, rule1_143, rule1_144, rule1_145, rule1_146, rule1_147, rule1_148, rule1_149, rule1_150, rule1_151, rule1_152, rule1_153, rule1_154, rule1_155, rule1_156, rule1_157, rule1_158, rule1_159, rule1_160, rule1_161, rule1_162, rule1_163, rule1_164, rule1_165, rule1_166, rule1_167, rule1_168, rule1_169, rule1_170, rule1_171, rule1_172, rule1_173, rule1_174, rule1_175, rule1_176, rule1_177, rule1_178, rule1_179, rule1_180, rule1_181, rule1_182, rule1_183, rule1_184, rule1_185, rule1_186, rule1_187, rule1_188, rule1_189, rule1_190, rule1_191, rule1_192, rule1_193, rule1_194, rule1_195, rule1_196, rule1_197, rule1_198, rule1_199, rule1_200, rule1_201, rule1_202, rule1_203, rule1_204, rule1_205, rule1_206, rule1_207, rule1_208, rule1_209, rule1_210, rule1_211, rule1_212, rule1_213, rule1_214, rule1_215, rule1_216, rule1_217, rule1_218, rule1_219, rule1_220, rule1_221, rule1_222, rule1_223, rule1_224, rule1_225, rule1_226, rule1_227, rule1_228, rule1_229, rule1_230, rule1_231, rule1_232, rule1_233, rule1_234, rule1_235, rule1_236, rule1_237, rule1_238, rule1_239, rule1_240, rule1_241, rule1_242, rule1_243, rule2_1, rule2_2, rule2_3, rule2_4, rule2_5, rule2_6, rule2_7, rule2_8, rule2_9, rule2_10, rule2_11, rule2_12, rule2_13, rule2_14, rule2_15, rule2_16, rule2_17, rule2_18, rule2_19, rule2_20, rule2_21, rule2_22, rule2_23, rule2_24, rule2_25, rule2_26, rule2_27, rule2_28, rule2_29, rule2_30, rule2_31, rule2_32, rule2_33, rule2_34, rule2_35, rule2_36, rule2_37, rule2_38, rule2_39, rule2_40, rule2_41, rule2_42, rule2_43, rule2_44, rule2_45, rule2_46, rule2_47, rule2_48, rule2_49, rule2_50, rule2_51, rule2_52, rule2_53, rule2_54, rule2_55, rule2_56, rule2_57, rule2_58, rule2_59, rule2_60, rule2_61, rule2_62, rule2_63, rule2_64, rule2_65, rule2_66, rule2_67, rule2_68, rule2_69, rule2_70, rule2_71, rule2_72, rule2_73, rule2_74, rule2_75, rule2_76, rule2_77, rule2_78, rule2_79, rule2_80, rule2_81,rule3_1, rule3_2, rule3_3, rule3_4, rule3_5, rule3_6, rule3_7, rule3_8, rule3_9, rule3_10, rule3_11, rule3_12, rule3_13, rule3_14, rule3_15, rule3_16, rule3_17, rule3_18, rule3_19, rule3_20, rule3_21, rule3_22, rule3_23, rule3_24, rule3_25, rule3_26, rule3_27, rule3_28, rule3_29, rule3_30, rule3_31, rule3_32, rule3_33, rule3_34, rule3_35, rule3_36, rule3_37, rule3_38, rule3_39, rule3_40, rule3_41, rule3_42, rule3_43, rule3_44, rule3_45, rule3_46, rule3_47, rule3_48, rule3_49, rule3_50, rule3_51, rule3_52, rule3_53, rule3_54, rule3_55, rule3_56, rule3_57, rule3_58, rule3_59, rule3_60, rule3_61, rule3_62, rule3_63, rule3_64, rule3_65, rule3_66, rule3_67, rule3_68, rule3_69, rule3_70, rule3_71, rule3_72, rule3_73, rule3_74, rule3_75, rule3_76, rule3_77, rule3_78, rule3_79, rule3_80, rule3_81 ])\n",
        "concluing = ctrl.ControlSystemSimulation(concluing_ctrl)\n",
        "concluing.input['Fever'] = 0.5\n",
        "concluing.input['Headache'] = 0.6\n",
        "concluing.input['Nausea'] = 0.4\n",
        "concluing.input['Vomiting'] = 0.5\n",
        "concluing.input['Ijaundice'] = 0.4\n",
        "concluing.input['Enlarge_liver'] = 0.3\n",
        "concluing.input['Joint_pain'] = 0.7\n",
        "concluing.input['Body_weakness'] = 0.5\n",
        "concluing.input['Dizziness'] = 0.6\n",
        "concluing.input['Loss_of_appetite'] = 0.5\n",
        "concluing.input['Mp'] = 0.6\n",
        "concluing.compute()\n",
        "print(concluing.output['Conclu'])\n",
        "conclu.view(sim=concluing)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "wDTdjQMq3l1E",
        "outputId": "fc7502c0-e039-4df4-d9ba-ba04752f6067"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.1999999999999999\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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p6miK2zmdoklCKaUmiPd4RETAl5jtOTRJKKXUBA2hhlntaR1NwBdIyL0lNEkopdQEdcE6e+4kEnTwWpOEUkqFjZtxGjsa47pGIqKquIrjXccZHhuO+7ntpElCKaXC3ul+h6LsIuZnz4/7uedlzKO8oJyWzpa4n9tOmiSUUiqsIdRAwBf/UlNEIg5ea5JQSqmwupA94xERkfYciUSThFJKhdUH622/k0i0GU6aJJRSCqsTcn3InjUSEX6fn+aOZsbGx2y7RrxpklBKKeBs31my0rIozSm17Rr5WfmU5ZRxovuEbdeIN00SSikFtt9FRCTauIQmCaWUwv7xiIhEG5fQJKGUUoTvJJxIEgm28lqThFJKYV9jv8kCvgCNoUbGzbjt14oHTRJKqZTXPtDO8Pgwi/MW236t4nnF5GXlcbrntO3Xioek2L7Ua0J9wxxv73U7jKg2riy5+LUxxsVIksS5t2G4z+0oostfAL5VbkfhKZHxCBFx5HoBX4C6UB3LCpc5cr250CRhgz/+P2/TeK6Hwnn69qaMrlb4/g5YuNbtSKZnxqHrFHy5AdK0kBDh1HhERGRc4taVtzp2zdnST7E4Gxkb5+WmNn75lS0sKJjndjjTki+6HUESaXoW/B+Cj/2D25FE972NcPYgLL3W7Ug8oz5Yz46VOxy7XsAX4MmGJx273lzorxJxduBkBytK8jyfIFScNT8PVd7/rRCw4mx+3u0oPMXxO4nwNNhEKPNqkoiz2oYLbPMvcDsM5aSRQTixB9ZsdzuS2FTugOZn3Y7CM7qGuugc6mR54XLHrrkg1/qMON9/3rFrzpYmiTjb1XCBbdVlboehnHRijzUWketzO5LYLH8ftLdAb5vbkXhCQ6iB6uJq0sS5j0MRSZj1Epok4uhUqJ9Q3zDry4vcDkU5qfk5qHKunj1nGVmwejO0/NLtSDzBqfURkyXKymtNEnG0u/ECW6rLSEtzZhpdPJ3pHHA7hMRkjFW6qUyQ8YiIylu15BTm9HhERFImCREpFJECu4JJdLWNbWyrTszxiN2NWnqYlWALjI14f+rrZJW3wNFaGBt1OxLXOdXYb7KkKjeJyCYReQs4DLwtIodE5D32hpZYBkfGeP14iM1ViTkesavhgtshJKamZ60PXIcWYcVNwSIoXgGnXnM7Elf1j/Rzru8cq+evdvza5fnl9I/0ExwIOn7tmYj1TuL7wBeMMSuNMSuALwL/bF9YiWfv0SA1SwqZn5Ppdiiz8tqxIIMjibMRimckYqkpQktONHY0smb+GjLSnF8yFhm89vqe17EmiTFjzMuRJ8aYPYDep05Q23ghYUtNAFWLCnj9eMjtMBLLYDecfgNWbXY7ktmp3JHy6yXqgvbuaR2N3+f3/LhErEniRRH5exHZKiJbRORvgN0icq2ITLlsU0RuE5FGEWkRkQenOOYTIlInIkdE5Mez+UO4zRjDroYLbE/g9RHb/Qu05DRTx3bDsusgO9/tSGZn6bXQewE6T7kdiWsaQg2uJolEGJeINUmsB6qArwEPAwHgGuB/At+50g+ISDrwKPBBoAa4W0RqJh1TCfw34EZjzFrggRn/CTyg5UIv4+OGqoUJ+mEBbKteQG3jhYRYAeoZiVxqAkhLh4oPpHTJqT5YT42vJvqBNqnx1Xj+TiKmQpwxZtsszn0d0GKMOQYgIk8CHwEm7tv3eeBRY0xH+DoJ+atsbaO1ytqpDpJ2CCwuYGhknOPtfawuS9xk5xhjrFLNTV92O5K5qbwF3vo32PQ5tyNx3NDYECe7T1JRXOFaDCsKV9A+0E7PcA8FWd6cODrtnYSI3BP+75ev9Ihy7qXAxPvY1vBrE1UBVSLyioi8KiK3zfQP4AWJXmoCaxBtm79MS06xOnsIsgugZI3bkcxNxc1w4hUYSb11Mi0dLSwvXE52erZrMaSnpVNVXOXpweto5aa88H8LpnjMVQZQCWwF7gb+QUSKJh8kIveKyH4R2d/W5q35/N2DI7zV2sX71pREP9jjtoZLTioGzc9ZA7+JLqcYFl1ltRZJMW4topss4PP2uMS05SZjzN+H//v1WZz7NDBxR43y8GsTtQKvGWNGgOMi0oSVNPZNiuMx4DGAjRs3eqpovqe5nY0rfeRmJX7X9ZsqSvnyUwfpHRolPzvx/zy2an4Otj3kdhTxUbkjnPRucTsSR7nVjmOympIaXj/3utthTCnWxXRlIvLfReQxEfmnyCPKj+0DKkVklYhkAXcBT0865n9j3UUgIqVY5adjM/kDuC0ZSk0RedkZXLuimD3N7W6H4m197dDWCCtucDuS+Ki61VoUmGKTFjxzJ+HxGU6xzm76P8B84JfAzyY8pmSMGQXuA54F6oGfGGOOiMgjInJH+LBngaCI1AG1wP9rjPH28sMJxscNuxO4FceVbK1eQK2OS0yv5ZfW2ogM92rZcbWgBsZHob3J7UgcMzo+SktnC9W+ardDYc38NZzuPc3AqDfHhWKtKeQaY74605MbY54Bnpn02p9M+NoAXw4/Es7bZ7qYn5PB8pJct0OJm+3+Bfz9i0cxxiT0bC1bJct4RITIuyWnMvc/NJ1wvOs4C3MXkpeZF/1gm2WmZ7Jq/iqaOppYX7be7XAuE+udxE9F5HZbI0lAyVRqilhVmkdedgZHznS7HYo3jY1CywvJlSTg3ZJTinCrqd9UakpqPFtyijYFtkdEuoH/ipUoBkSke8LrKa22IbFbcUxla3WZlpym0vo6FC2DwsVuRxJfqzbDmTdhsMvtSBxRH/TGeESEl9uGT5skjDEFxpjC8H/TjDE5E54XOhWkF7X1DHGsvY+NKxNkN7IZ2O7XqbBTan4usVdZTyUrD5Zdb7UaSQFu92yazMuD17HObrpRRPLCX98jIt8VEec2hPWgF5vauKmilKyM5Nu36bpVPprP9xLqG3Y7FO9pes4qzSSjqlutP1+SGzfjNHY0eupOorK4kuNdxxkZG3E7lMvE+gn3t0C/iKwHvgIcBf7VtqgSQLKWmgCyM9J575oSXmzSu4lLdJ6CnrOwNEm3Uqm8xbpTGh93OxJbneo5RVF2EfOz57sdykU5GTmUF5TT0tnidiiXiTVJjIZnIn0E+GtjzKPEZ8V1QhoZG+fl5ja2+hNzg6FYbPcvoLbBW6vbXdfyvNUQLy3d7Ujs4VsN8+bDuUNuR2Irr41HRHh1XCLWJNEjIv8NuAf4mYikAYm5u04cHDjZwYqSPBYUzHM7FNtsq17AS81tjI4l92+VM5LMpaaIFCg51YXq8Pv8bodxmUBJgLpgXfQDHRZrkrgTGAI+a4w5h9Vi49u2ReVx1gZDyXsXAbBo/jwWz8/h4KlOt0PxhpFBq7/Rmu1uR2KvSMkpiXmlHcdkfp/fk43+oiaJ8L4QTxhjvhvZnc4Y844x5l9sj86jahus1uDJbrt2hX3XyT2wcC3kJt9stkssvwHam63WI0nIGENDqIGaEvf2kJiK3+enqaOJsXFvbSMcNUkYY8aAcRHxziiPi1o7+gn2DrOuvMjtUGynu9VN0PQcVCXZAroryciC1ZuTdlvTc33nyEzLpDSn1O1QLlOQVUBZThknuk+4HcolYi039QJvicj3ReSvIg87A/Oq2sY2tlSVkZ6W/C0rNiwr5nz3IGe7vNlTxjHGhHehS4EkAe+26EhCXh2PiPDiuESsSeI/gD8GXgIOTHiknFQpNQGkpwmbq8p0llOwBUaHYeFVbkfijIpb4OguqwVJkvHqeESEF8clYkoSxpgfAD8BXjXG/CDysDc07xkcGeP14yE2Vyb3oPVE26q15ETTs9aAbqo0PCxcDEXL4dRrbkcSdw2hBlf3tI7Gi3tex7ri+sPAQeAX4ecbRGTy3hBJb++xIDWLC5mfmzqzf7dUlfHasSBDo94aTHNUcwpMfZ2s6takLDl5/k6ixE9DsIFx452p57GWmx4GrgM6AYwxB4HVtkTkYalUaooozsuialEBrx0LuR2KO4Z64PQBWLXF7UicVZl8SaJ9oJ3BsUEW53m3OaNvno+8rDxO90zexNM9sSaJEWPM5PaQ3kl1DjDGsKvhAtuSeJX1VLZVp/BU2KO1UL4JsvPdjsRZS6+F3vNWK5IkEbmL8Po+KV5beR1rkjgiIr8FpItIpYh8D/iVjXF5ztG2XsbHDdULU68byTb/AnanalfYVCw1gdV6pOIDSXU34fXxiIhETRJfAtZirbp+AugGHrApJk/aFS41ef23EDvULC5kYGSMY229bofiLGOs9QKpMvV1siSbCuu1jYam4rW24bHObuo3xjwE3AxsM8Y8ZIwZtDc0b9mVxF1foxGR1JzldPaQtc9CyRq3I3HHmu1w4hUYSY51MnVBb6+RiIjcSVg9Vd0X6+ymTSLyFnAYa1HdIRFJ0n7Jl+seHOGt1i5uqChxOxTXWCWnFFsv0fx8apaaInJ9sOgqK1EkuK6hLjoGO1hRuMLtUKJakGv9Mnq+/7zLkVhiLTd9H/iCMWalMWYl8EXgn22LymP2NLezcaWP3KwMt0NxzU0Vpbz5Tge9Q8m3wGpKqbTKeiqVO6z3IcE1hBrw+/ykifc3CRMRAr6AZxbVxfqOjUWa+wEYY/YAKfNpYZWaUm9W00R52Rlcs7yYPc3J2fjtMn3t0NYIK25wOxJ3Ve6wFhN6pPQxWw2hhoQYj4jw0rjEtElCRK4VkWuBF0Xk70Vkq4hsEZG/AXY7EqHLxscNuxvb2O5f6HYorkupWU4tL8CqzZCR7XYk7lq4FsZHrc6wCawuWOfJjYamEvAFqAt5o4dTtDuJ/xl+rAeqgK9hLawLABvsDMwr3j7TRWFOBstLct0OxXXb/QuobbzgmQE1W2mpySKSFCWn+lB9QgxaR3jpTmLaIrsxZptTgXhVbUMb21N0VtNkq0rzyMlMp+5sN2uXJHHn+LFRq8Hdjj91OxJvqNwBr/0t3PAltyOZlf6Rfs71nWN1UeI0iSjPL6d/pJ/QYAjfPHf3MIl1dlORiNwvIt9NtVbhuxovsD3FWnFMZ5t/AbXJPhW2dR/ML4fCJW5H4g2rt8DpN2Gw2+1IZqWpo4k189eQmZY4PddE5GIfJ7fFOnD9DLASeIsUahXe3jvEsbZeNq5M8t3IZiAlNiJqftbqXaQsWXmw7Do4Vut2JLNSF6xLqEHrCK+MS8Q6p3OeMebLtkbiQS82tnHjmlKyMrw/bc4p163y0Xy+l1DfML68LLfDsUfz8/Ch77odhbdEVl/XfMTtSGasPlTP1aVXux3GjAVKAtS+435ijvXT719F5PMislhEfJGHrZF5gJaaLpedkc5715TwUlOSLqzraoXuM1C+0e1IvKXyFit5jideX8/6YL0n97SOpsZX44m1ErEmiWHg28Be3i017bcrKC8YGRvn5aY2tqb4+ogrSeoWHc3PQcXNVoM79a6SNZBdAOcOuR3JjAyPDXOy+ySVxZVuhzJjKwpX0DbQRs9wj6txxJokvgJUhFdcrwo/EmeqwCy8cbKD5SW5LCic53YonrPNX8ZLzW2MjSfhVNjm53U8YiqVt1rvTwJp7mxmeeFystMTb71Lelo6VcVVrt9NxJokWoB+OwPxml2NF3Tq6xQWz89h8fwc3nynw+1Q4mtkEE7sse4k1OWqwquvE0h9MLHWR0wW8Lm/XiLWJNEHHAyvuk6JKbC1DRfYquMRU0rKjYhO7oEFAauxnbrc8hugvclqWZIgEnU8IqKmxP1xiViTxP8G/gxro6GknwLb2tFPsHeY9eVFbofiWdbq6yQbvE7lvSNikZFltSpp+aXbkcSsPlSfUO04JvP7/K5vQBTrfhI/AH4CvGqM+UHkEe3nROQ2EWkUkRYReXCa4z4mIkZEPDGlpLaxjS1VZaSnpd4GQ7G6ZnkxZ7sGONuVHHsNYIxVSknl1uCxqLo1YUpOo+OjtHS2UO2rdjuUWasoqqC1p5WBUff+ncW64vrDwEHgF+HnG0Tk6Sg/kw48CnwQqAHuFpHL7vtEpAD4r8BrM4rcRlpqii49TdhcWUZtQ5LcTQRbYHQIFl7ldiTeVnGL1bJkzPtNoI93HWdh7kLyMvPcDmXWMtMzWTV/FU0dTa7FEGu56WHgOqATwBhzEIg2u+k6oMUYc8wYMww8CVxpJc43gP8BeGKnu8GRMV4/HmJLpU59jSbS8C8pND9nrQVIwe1pZ6RwMRQth9bX3Y4kqkQvNUXUlNS4Ongda5IYMcZ0TXot2qqapcCpCc9bw69dFG5DvswY87MY47Dd3mNBAosLmJ+bOH1e3LKlqoxXjwYZGh1zO5S501JT7BKk5FQfTIw9raPx+/yuDl7HmiSOiMhvAekiUiki38MaxJ41EUkDvou1BiPasfeKyH4R2d/WZm95o7bhAtu01BST4rwsKhfm89qxkNuhzM1QD5w+AKu2uB1JYoi06PC4+lByJIlASYC6oHs9nGJNEl8C1gJDwBNAN/BAlJ85DSyb8Lw8/FpEAXAVsFtETgDvBZ6+0uC1MeYxY8xGY8zGsjL7ykDGGHY1aCuOmUiKktOx3VC+CbLz3Y4kMSx9D/Seh85T0Y91ybgZpzHUmBTlpqriKo53HWdkbMSV68c6u6nfGPOQMWZT+MP6IWNMtDGEfUCliKwSkSzgLuDiYLcxpssYUzph3+xXgTuMMa61+zja1svYuKF6YYFbISScpGgdrqWmmUlLh4oPePpu4lTPKQqzCpmfnfj7nuRk5FBeUE5LZ4sr15+2C2y0GUzGmDum+d6oiNwHPAukA/9kjDkiIo8A+40x057bDbvCpSbRwcuY1SwuZGBkjGNtvawuS8DfxI2x1kfc9P+4HUliqdwBb/0bbPqs25FcUbKMR0QEfAHX9umO1ir8fViDz09gTVGd0aenMeYZrL0oJr72J1Mcu3Um57ZDbUMbn71pldthJBQRYVu1tbAuIZPEucPWfgkla9yOJLGs2Q7/9wGrlUmm9/qbJcvMpgi/z09dsI6PVn7U8WtHKzctAv471tjBXwK3AO3GmBeNMS/aHZyTugdHONzayQ0VJW6HknASuuTU9JyWmmYj1weLrrJ6XXlQ0t1JlARcW3k9bZIwxowZY35hjPkU1sByC9ZA832OROegV5rbec9KH7lZse7DpCJurCjlzXc66Bvy/gKry0TWR6iZq7zFk+MSxpikvJNo6mhibNz56eZRB65FJFtEfgP4IfBF4K+A/7Q7MKftarjAdt07YlbyszO4Znkxe1oSp/EbAH1BaGuAFTe6HUliqrzV2urVeKtl/Lm+c2SkZVCWmzz/nguyCijLKeNk90nHrz1tkhCRf8HaaOha4Ovh2U3fMMacnu7nEs34uKG2sU3XR8zB1uqyxCs5tfwSVr4fMhJvrwFPWLgWxkagvdntSC6RbHcREX6f35U9r6PdSdwDVGL1VvqViHSHHz0i0m1/eM44cqabwpwMVpQkbo8Xt0XWSxiP/VY5rebnrD0S1OyIeLLklCyL6CYLlLizt0S0MYk0Y0xB+FE44VFgjCl0Kki7WaUmvYuYi9Vl+eRkplN3NkF+dxgbhaMvaGvwuYqUnDykPpicdxI1vhpXBq9jXXGd1HY1aiuOeNhanUCznFr3QWE5FC5xO5LEtmoznH4DBr3zy0GyzWyK8Jf4aQg2OH63nvJJor13iGMXetm0Uncjm6uE2ohIS03xkZ0Py66zWpt4QPtAO4NjgyzJS77k75vnIzczl9beVkevm/JJ4sXGNm6oKCErI+Xfijm7frWPpnM9dPQNux1KdM3PWaUSNXceKjlFViUna9cEN8YlUv6TcVejNvSLl+yMdK5fXcKLTR6/m+hqhe4zUO6JjRATX+UtVmuT8Wi7B9gvWccjItwYl0jpJDE6Ns7LTW1s1UHruEmIrrDNz0PFzVajOjV3JWsgu8BqceKyZJ3+GqF3Eg47cLKDZb5cFhZ6r/dMotrmL+OlpjbGxj08FVZLTfFXeasnpsLWBeuSctA6wu/zUx+qd3TwOqWThJaa4m/x/BwWFs7jzXc63A7lykYG4fjL1p2Eip/KW1zfra5rqIvOoU5WFK5wNQ47LcxdCMCFfufu1lM6Sexu0FXWdvB0yenkK7CwxmpQp+JnxY3Q3gR97rVmaQw1Ul1cTZok78eaiBDwOdvsL3nfzShOdw7Q1jvE+vIit0NJOtv9C9jV4NHB6+bndAGdHTKyrDUTLb90LYT6UD1+n9+16zvF6XGJlE0SuxousKWqjPS05Jwq56YNy4o42zXA2a4Bt0O5lDFWSUSThD0qd7hackr28YgIvZNwyO4GXWVtl4z0NDZXlrHbawvrgkdhdBAWXe12JMmpcgcc3WW1PHFBQ6ghqWc2RWiScMDgyBivHQ+xubLU7VCS1jZ/Gbu81qKj+VlrgDVJF1q5rnAxFC2D1tcdv3T/SD9n+86yumi149d2WnlBOX3DfYQGQ45cLyWTxKvHggQWF1CUm+V2KElrS9UCXj0aZGjU+U1SpqRTX+3n0lTYpo4mVs9fTWZapuPXdpqIXOzj5ISUTBK1WmqynS8vi8qF+bx+3JnfdqIa6oHW/bB6q9uRJLeqW60tYR2WKuMREU6WnFIuSRhjrK6vusradtuqF3in5HRst9WGIzvf7UiS29L3QM9Z6Dzl6GWTfaX1ZJFFdU5IuSRxtK2P0TGDf1GB26EkvW3+Bd4ZvNZSkzPS0qHiA9DyvKOXbQg1UFNS4+g13VRTUuPYNNiUSxKRUlOydon0krVLCukbGuV4e5+7gRhj9Wuq0iThCIdLTsNjw5zoOkFlcaVj13TbysKVtA200TPcY/u1Ui5J7GrQUpNTRMQbJadzhyEzx2pEp+y3Zjuc2GO1QHFAc2czywqXkZ2eOnuVp6elU1VcRWOo0fZrpVSS6Bkc4XBrJzdWlLgdSsqwSk4uJwktNTkr1wcL18LJPY5cLtnbg0/FqXGJlEoSe5rbuXZFMblZGW6HkjJuqizljZMd9A25s8AKsEofuguds6p2OFZySrXxiAinxiVSKknsatCur07Lz85gw/Ii9rS41PitLwhtDVYDOuWcyh3W4kUHWlrXB1OjZ9NkTk2DTZkkMT5u2N3UpuMRLthW7WLJ6egLsPL9kJE69WpPWHgVjI1AsMXWy4yOj9Lc2ZySSaKiqILWnlYGRu3tkZYySeLImW4KsjNYWZrndigpZ7t/AbUNbY5ulHJR07NaanKDiCN7TBzvOs7C3IXkZabev+vM9ExWzV9Fc0ezrddJmSSxS1dZu2ZVaR7ZmWnUne129sJjo9adRMUtzl5XWSIlJxulSlO/qTjRNjxlkkSt7kLnmshUWMcX1p3eD4XlMH+ps9dVllVb4PQbMGjfLwep1o5jMifGJVIiSQR7hzh6oZdNK3U3MrdYGxE5PC6hpSZ3ZefDsuuslig2SZWNhqYSKAlQF6yz9RopkSR2N7ZxQ0UJWRkp8cf1pOtW+Wg610NH37BzF9Vd6NxnY8lp3IzTGGpM6XJTVXEVx7uOMzI2Yts1UuJTU0tN7puXmc71q0t4qdmhklPXaeg+DeWbnLmeurLKHVZLFBsmLbT2tFKYVUjRvKK4nztR5GTksDR/KUe7jtp2DVuThIjcJiKNItIiIg9e4ftfFpE6ETksIi+IyIp4xzA6Ns7Lze1s1amvrnN0I6Lm52DNzVbDOeWekjWQlQ9nD8X91HWh1B6PiLB78Nq2JCEi6cCjwAeBGuBuEZm8LPJNYKMxZh2wE/hWvON4451OyotzWFg4L96nVjO0rXoBLzW1MTbuwFTY5ue0oZ9XVNmzEVGqLqKbLOCzd1zCzjuJ64AWY8wxY8ww8CTwkYkHGGNqjTH94aevAuXxDkJXWXvHkiIrWR881WHvhUaH4PjLVstq5b7KHbYliVRsxzFZoCRAQ8i+XersTBJLgYk7j7SGX5vKZ4GfxzuI2oYLWmrykG1OzHI6sQcWBKxGc8p9K26Atkboi19rFmNMym00NBW/z09jRyNj4/ZsFeyJgWsRuQfYCHx7iu/fKyL7RWR/W1vsA5+nOwe40DPIhmVF8QlUzVlk9bWtmp/Xqa9ekpENqzZDywtxO+X5/vNkpGVQllsWt3MmqoKsAkpzSjnZfdKW89uZJE4DyyY8Lw+/dgkR+QDwEHCHMWboSicyxjxmjNlojNlYVhb7/xS1DRfYUlVGeppuMOQV1ywr4kzXAOe6bNxroPlZbQ3uNXGeClsXrNPxiAkCvgB1IXvGJexMEvuAShFZJSJZwF3A0xMPEJFrgL/HShBxr0HUaisOz8lIT+P9lWXU2tXwr70FRgZg0dX2nF/NTuUt1p3EWHxaxmup6VKBkgANQXvGJWxLEsaYUeA+4FmgHviJMeaIiDwiIneED/s2kA/8m4gcFJGnpzjdjA2OjPHa8RBbqvR21Gu2+8uotWtcovk56wNJt6f1lsIlULQMWvfF5XQ6aH2pGl+Nbe05bB2TMMY8Y4ypMsasMcb8Wfi1PzHGPB3++gPGmIXGmA3hxx3TnzF2rx4L4l9UQFFuVrxOqeJkS9UC9h4NMjRqw0Cblpq8q/LWuJWc6kP1ukZiAn+Jn/pgvS2dlj0xcG0HLTV5ly8vi4qF+bx+PBTfEw/1QOt+WL0lvudV8VEZn93q2gfaGRwdZEnekjgElRx883zkZubS2tsa93MnZZIwxlDb2KbrIzxse7UNs5yOvQjlGyG7IL7nVfFRvhF6zkLX3D7IIu3BRUuKl7BrvURSJomjbX2MjI3jX6QfFl61zb8g/oPXWmrytrR0a4HjHBfW1Qe11HQlNT579rxOyiQRWUCnv2l419olhfQNjXK8vS8+JzTGWh+hXV+9LQ4lJ53ZdGV+n9+WabDJmSS066vnRTYiitssp3NvQWYOlFbE53zKHhU3WyviR2a/TkbvJK4s0ugv3oPXSZckegZHOHSqkxvWlLgdiooiriUnLTUlhlwfLFwLJ/fM6se7hroIDYZYURj3htEJb2HuQgAu9Me3jJt0SWJPczvXrigmLzvD7VBUFDdVlvLGyQ76huKwwKopvD5CeV/lLbMuOTWGGqn2VZMmSffRNWciQsAX/8HrpHuntdSUOPKzM9iwvIhXWubY+K0vCBfqYeVN8QlM2asqvF5iFmURHY+Ynh3jEkmVJMbHramv27Tra8LYVh2HktPRF2DV+61Gcsr7Fl4Fo8MQbJnxj+oiuunZsQFRUiWJI2e6KcjOYGVpntuhqBhtC3eFndNgW9OzOqspkYiES04zX31dH9Q7ienY0Z4jqZJEbaPuHZFoVpfmkZ2ZRv3ZntmdYHzMupPQJJFYZrFbXf9IP2d6z7C6aLVNQSW+8oJy+ob76BiM38ZeSZUkdBe6xHNxKuxsS06t+6BwKcyfbj8r5TmrtsDpA1YrlRg1dTSxpmgNmWmZNgaW2ETE6uMUx7uJpEkSwd4hjl7oZdOqYrdDUTNklZxmmSSan9O7iESUnQ/lm+DY7ph/RMcjYuP3+eM6LpE0SeLFpjbet6aE7Ix0t0NRM3T9Kh8N53ro6Bue+Q83PWeVLlTiqbp1RuMSOh4Rm4AvoHcSV6KlpsQ1LzOd96728VLzDBv+dZ2G7lZYutGewJS9KndYrVRinLSg019jU1NSE9e1EkmRJEbHxnm5uV1bgyewWZWcWp6HNTdDui6cTEglayArD84djnro8NgwJ7pOUFlc6UBgiW1l4Uou9F+gd7g3LudLiiTxxjudLC3KYWHhPLdDUbO0rXoBLza1MTY+g6mwWmpKfFW3xrT6uqWzhWWFy5iXof/Go0lPS6eyuDJudxNJkSS01JT4loST/MFTMU7dGx2CEy9bdxIqcVXeEtNudToeMTPxHJdIiiSxu1F3oUsGkYV1MTn5CpT5IU8bOSa0FTdCW6PVWmUaOh4xM/Ecl0j4JHG6c4Dz3YNsWFbkdihqjrb7F7Ar1nGJpuegSqe+JryMbFi1GVp+Oe1h2h58ZgK+AHXB+PRwSvgkUdtwgS1VZaSn6QZDie6aZUWc6RrgXFcMew00ayuOpBGl5DQ6PkpzZzN+n9/BoBJbRVEFrT2tDIwOzPlcCZ8ktNSUPDLS03h/ZRm7o62+Dh6FkQFYtM6ZwJS9KnfA0V0wduWW8Se6TrAwdyF5mdqTLVaZ6Zmsmr+K5o7mOZ8roZPE4MgYrx4LsaWqzO1QVJxs95dFLzk1PWv99qnb0yaHwiUwv9xqsXIF9aF6vYuYhXh1hE3oJPHqsSD+RQUU5Wa5HYqKk82VZew9GmRodGzqg7TUlHwqd0xZcqoL1ul4xCzEa4ZTQieJ3Y1tWmpKMiX52VQszGff8Smmwg71Qut+WL3V0biUzSpvtVZfX4HObJqdQEmKJwljDLsaLugGQ0loW/U0s5yO7Yal74HsAkdjUjYr3wjdZ6Cr9ZKXx804jaFGTRKzUFVcxbHOY4yMjczpPAmbJI629TE8Ok5gsX5YJJvt/mlahzc/q6usk1FaOlTcfNkeE609rRRkFVA0r8iduBJYTkYOS/OXcrTr6JzOk7BJwprVVIbo4GXSWbukkL6hUY639136DWOskkSlJomkdIWSU12oTu8i5iAeg9cJmyS01JS8RISt1WWXN/w79xZkzLMaw6nkU3EzHH8ZRt5dJ6OL6OYmHoPXCZkkegZHOHSqkxsrSt0ORdnkiiWnSKlJ7x6TU64PFtbAyT0XX2oINVBTUuNiUIktZe8kXmlp59oVxeRla4voZHVjRSlvnOygb2jCAqvm53Xqa7KL7DGBNTmlPqhrJOai2ldNY0cjY+PTTCmPIiGThJaakl/BvEzWLyvilZZ264X+EFyotxrCqeRVucNaLGkM5/vPkyZplOXoYtnZKswqpDSnlJM9J2d9joRMErWNbdoaPAVYJadwV9iWF2DlTZCp+wkktUVXW23gg0cvLqLTySlzE/DNreSUcEliYGSM/OwMVpZqH5dkt82/gN2NFzDG6CrrVCFyseFfQ6hBZzbFwVzHJWxNEiJym4g0ikiLiDx4he9ni8hT4e+/JiIro52zZ3BUS00pYnVpHpnpadSf7rTuJCpvcTsk5YRwyUlnNsXHXGc42ZYkRCQdeBT4IFAD3C0ik6cpfBboMMZUAP8L+B/RztszOKKlphQhImz3L6B+/653m8Cp5Ld6K5w+QF3wiN5JxIHf5/dmkgCuA1qMMceMMcPAk8BHJh3zEeAH4a93AjdLlALk4Mg4m1YVxz1Y5U3b/Au01JRqsvNpX3oNA8M9LM1f6nY0Ca8kp4TcjNxZ/7ydc0iXAqcmPG8Frp/qGGPMqIh0ASVA+1Qnzc08zVd+fFOcQ1X3/cv73A7hioyBkbwOHnuniv7H73E7HOWQ/LFu1gwOcOhbt7kdSlJYWtQ1658VY0wcQ5lwYpGPA7cZYz4Xfv47wPXGmPsmHPN2+JjW8POj4WPaJ53rXuDe8NOrgLdtCTq+Spkm2XmIxhk/iRAjaJzxlihxzjPGXDXTH7LzTuI0sGzC8/Lwa1c6plVEMoD5wGU7ohtjHgMeAxCR/caYjbZEHEcaZ3wlQpyJECNonPGWSHHO5ufsHJPYB1SKyCoRyQLuAp6edMzTwKfCX38c2GXsurVRSik1Y7bdSYTHGO4DngXSgX8yxhwRkUeA/caYp4HvA/8qIi1ACCuRKKWU8ghbmx8ZY54Bnpn02p9M+HoQ+M0ZnvaxOITmBI0zvhIhzkSIETTOeEvqOG0buFZKKZX4Eq4th1JKKed4NknY0dLDDjHEuVlE3hCR0fC0YC/G+GURqRORwyLygois8Gicvy8ib4nIQRHZc4UV/J6Ic8JxHxMRIyKuzHyJ4f38tIi0hd/PgyLyOS/GGT7mE+H/R4+IyI+djjEcQ7T3839NeC+bRKTThTBjiXO5iNSKyJvhf/O3T3tCY4znHlgD3UeB1UAWcAiomXTMF4C/C399F/CUR+NcCawD/gX4uEdj3Abkhr/+Lx5+LwsnfH0H8Asvxhk+rgB4CXgV2OjFOIFPA3/tdGyziLMSeBMoDj9f4MU4Jx3/JazJOp6LE2ts4r+Ev64BTkx3Tq/eSdjS0sMGUeM0xpwwxhwGxh2OLSKWGGuNMf3hp69irWlxWixxdk94mge4MaAWy/+bAN/A6kU2eIXvOSHWON0WS5yfBx41xnQAGGMmbVnoiJm+n3cDTzgS2aViidMAheGv5wNnpjuhV5PElVp6TG7icklLDyDS0sNJscTptpnG+Fng57ZGdGUxxSkiXwyvzP8WcL9DsU0UNU4RuRZYZoz5mZOBTRLr3/vHwiWHnSKy7Arft1sscVYBVSLyioi8KiJu9OqI+d9RuFy7CtjlQFyTxRLnw8A9ItKKNfv0S9Od0KtJQrlARO4BNgLfdjuWqRhjHjXGrAG+CvyR2/FMJiJpwHeBr7gdSwz+L7DSGLMOeJ5378y9JgOr5LQV6zf0fxCRIjcDiuIuYKcxZvZ7htrrbuBxY0w5cDvWWrUpc4FXk8RMWnowXUsPm8USp9tiilFEPgA8BNxhjBlyKLaJZvpePgn8up0BTSFanAVY/cV2i8gJ4L3A0y4MXkd9P40xwQl/1/8IvMeh2CaK5e+9FXjaGDNijDkONGElDSfN5P/Pu3Cn1ASxxflZ4CcAxpi9wDys/lNX5vTASoyDLxnAMaxbtsjgy9pJx3yRSweuf+LFOCcc+zjuDFzH8l5egzXYVenxv/PKCV9/GGvlvufinHT8btwZuI7l/Vw84euPAq96NM7bgB+Evy7FKqeUeC3O8HF+4AThNWgefT9/Dnw6/HUAa0xiyngd/0PM4A97O9ZvDEeBh8KvPYL1my5Y2e/fgBbgdWC1R+PchPWbUB/Wnc4RD8b4S+A8cDD8eNqj7+VfAkfCMdZO9+HsZpyTjnUlScT4fv5F+P08FH4//R6NU7BKeHXAW8BdXowz/Pxh4JtuxDeD97MGeCX8934Q2DHd+XTFtVJKqSl5dUxCKaWUB2iSUEopNSVNEkoppaakSUIppdSUNEkopZSakiYJpSYQkUUi8qSIHBWRAyLyjIhUxencW0Xkp/E4l1JOsXVnOqUSSbhB5H9iLdy6K/zaemAh1rxzpVKO3kko9a5twIgx5u8iLxhjDgF7ROTbIvJ2eD+LO+HincHucHO8BhH5UaQTsYhsEpFficghEXldRAomXkhEHhaRP5jw/G239kRRajp6J6HUu64CDlzh9d8ANgDrsdpC7BORl8LfuwZYi9Xa4BXgRhF5HXgKuNMYs09ECoEBm2NXyhaaJJSK7ibgCWN19TwvIi9itVvpBl43xrQCiMhBrE2muoCzxph98O4+GM5vd6LU3Gm5Sal3HWHmnVAndswdI/ZfvEa59N/fvBleVylHaJJQ6l27gGwRuTfygoisAzqBO0UkXUTKgM1YTSWn0ggsFpFN4XMUhNvZT3QCuDb8/WuxunYq5TlablIqzBhjROSjwP8nIl/F2nr0BPAAkI/VNdMAf2iMOSci/inOMxwe3P6eiORgjUd8YNJh/w58UkSOAK+hs6eUR2kXWKWUUlPScpNSSqkpaZJQSik1JU0SSimlpqRJQiml1JQ0SSillJqSJgmllFJT0iShlFJqSpoklFJKTen/Bz9sZorF9LtzAAAAAElFTkSuQmCC\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# for i in range(81):\n",
        "#   print(\"rule3_{0},\".format(i+1))"
      ],
      "metadata": {
        "id": "KT_pT8EE4snh"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "IzswTqMXSPT1"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}