{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Profile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:31.942873Z",
     "start_time": "2023-09-28T09:20:30.378685Z"
    }
   },
   "outputs": [],
   "source": [
    "import svvamp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define a random generator of profiles using the Spheroid model (which extends Impartial Culture to utilities), with 9 voters and 5 candidates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:31.975022Z",
     "start_time": "2023-09-28T09:20:31.942873Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<svvamp.preferences.generator_profile_spheroid.GeneratorProfileSpheroid at 0x227236d1310>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_profile = svvamp.GeneratorProfileSpheroid(n_v=9, n_c=5)\n",
    "random_profile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the generator to create a random profile:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:31.991443Z",
     "start_time": "2023-09-28T09:20:31.975022Z"
    }
   },
   "outputs": [],
   "source": [
    "profile = random_profile()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you wish, you can give a label to each candidate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.007414Z",
     "start_time": "2023-09-28T09:20:31.991443Z"
    }
   },
   "outputs": [],
   "source": [
    "profile.labels_candidates = ['Alice', 'Bob', 'Catherine', 'Dave', 'Ellen']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Basic information about the profile:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.023426Z",
     "start_time": "2023-09-28T09:20:32.007414Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.n_v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.039934Z",
     "start_time": "2023-09-28T09:20:32.023426Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.n_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.056049Z",
     "start_time": "2023-09-28T09:20:32.039934Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Alice', 'Bob', 'Catherine', 'Dave', 'Ellen']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.labels_candidates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Voters' rankings of preference:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.072018Z",
     "start_time": "2023-09-28T09:20:32.056049Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 3, 1, 2, 4],\n",
       "       [2, 0, 1, 3, 4],\n",
       "       [3, 0, 2, 1, 4],\n",
       "       [2, 3, 0, 4, 1],\n",
       "       [0, 4, 1, 2, 3],\n",
       "       [4, 2, 1, 3, 0],\n",
       "       [2, 1, 3, 0, 4],\n",
       "       [3, 1, 4, 2, 0],\n",
       "       [3, 2, 4, 0, 1]])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.preferences_rk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Voters' utilities for the candidates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.088063Z",
     "start_time": "2023-09-28T09:20:32.072018Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.56962423,  0.23147669, -0.10420753,  0.46170276, -0.63080752],\n",
       "       [-0.10565873, -0.38552417,  0.22279825, -0.55394695, -0.6954934 ],\n",
       "       [-0.26048526, -0.43251655, -0.41065507,  0.28538753, -0.70355756],\n",
       "       [ 0.26890645, -0.52263056,  0.58980142,  0.55356667,  0.01564742],\n",
       "       [ 0.04576047, -0.46090844, -0.48370682, -0.59680883, -0.44194607],\n",
       "       [-0.27629285,  0.37454992,  0.44890641,  0.25299888,  0.71961741],\n",
       "       [-0.02726965,  0.30157615,  0.75419276,  0.13546169, -0.56670239],\n",
       "       [-0.13770358,  0.62540861, -0.0909895 ,  0.73785947,  0.192837  ],\n",
       "       [-0.03753725, -0.29808471,  0.34075518,  0.88258878,  0.12107605]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.preferences_ut"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the restriction of the population to 3 candidates, for example [0, 2, 3] (Alice, Catherine and Dave), in the utility space:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.344417Z",
     "start_time": "2023-09-28T09:20:32.088063Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "profile.plot3(indexes=[0, 2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the restriction of the population to 4 candidates, for example [0, 1, 2, 4] (Alice, Bob, Catherine and Ellen), in the utility space:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.545873Z",
     "start_time": "2023-09-28T09:20:32.344417Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "profile.plot4(indexes=[0, 1, 2, 4])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plurality score, Borda score and total utility of each candidate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.562121Z",
     "start_time": "2023-09-28T09:20:32.546487Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 0, 3, 3, 1])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.plurality_scores_ut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.570372Z",
     "start_time": "2023-09-28T09:20:32.562864Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([18., 15., 23., 22., 12.])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.borda_score_c_ut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.586899Z",
     "start_time": "2023-09-28T09:20:32.571311Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.03934382, -0.56665305,  1.2668951 ,  2.15881001, -1.98932905])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.total_utility_c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Matrix of duels (weighted majority graph) and matrix of victories (unweighted majority graph):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.603394Z",
     "start_time": "2023-09-28T09:20:32.586899Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 6, 3, 3, 6],\n",
       "       [3, 0, 3, 4, 5],\n",
       "       [6, 6, 0, 5, 6],\n",
       "       [6, 5, 4, 0, 7],\n",
       "       [3, 4, 3, 2, 0]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.matrix_duels_ut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.619937Z",
     "start_time": "2023-09-28T09:20:32.604210Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 1., 0., 0., 1.],\n",
       "       [0., 0., 0., 0., 1.],\n",
       "       [1., 1., 0., 1., 1.],\n",
       "       [1., 1., 0., 0., 1.],\n",
       "       [0., 0., 0., 0., 0.]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.matrix_victories_ut_abs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-07-12T04:50:36.477149Z",
     "start_time": "2021-07-12T04:50:36.465742Z"
    }
   },
   "source": [
    "Condorcet winner:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-28T09:20:32.635979Z",
     "start_time": "2023-09-28T09:20:32.619937Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profile.condorcet_winner_ut_abs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By convention, if there is no Condorcet winner, then SVVAMP returns nan (not a number)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}