sim_by_peak.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from data import loader\n",
    "import pdb\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import matplotlib as mpl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Africa', 'Asia', 'Europe', 'NorthAmerica', 'SouthAmerica']\n"
     ]
    }
   ],
   "source": [
    "mpl.rcParams['figure.dpi'] = 1000\n",
    "d1 = loader.get_global_case_and_deaths_time_series_data()\n",
    "continent_list = loader.get_available_and_supported_continents()  # In case you want to see continents supported to pass into the call above\n",
    "print(continent_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "availableRegions = [\"Africa\", \"Asia\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get slices for each country\n",
    "def get_sliced_vectors(country_name, peak_sets, time_series_data, bucket_length):\n",
    "    \"\"\"\n",
    "    Input: \n",
    "        country_name (str): exist in both peak_set and time_series_data as an 'Admin0' entry\n",
    "        peak_sets (data frame): the set of all peak data\n",
    "        time_series_data (Tuple): case + death time series data\n",
    "    Returns:\n",
    "        sliced_case: a processed vector of case count\n",
    "        sliced_death: a processed vector of death count\n",
    "    \"\"\"\n",
    "    peak_points = peak_sets.loc[peak_sets['Admin0'] == country_name]\n",
    "    peak_num = np.array([\"X\" in x for x in peak_points.columns]).sum()\n",
    "    sliced_case = np.zeros([peak_num])\n",
    "    sliced_death = np.zeros([peak_num])\n",
    "    vectors = (sliced_case, sliced_death)\n",
    "    for df_idx, df in enumerate(time_series_data):\n",
    "        total_days = np.array([\"Day\" in x for x in df.columns]).sum()\n",
    "        groups = []\n",
    "        for bucket in range(peak_num):\n",
    "            # Get the columns for each bucket, which is centered at X_i (a peak)\n",
    "            begin = 0 if peak_points[\"X\" + str(bucket + 1)].item() - bucket_length / 2 <= 0 else peak_points[\"X\" + str(bucket + 1)].item() - int(bucket_length / 2)\n",
    "            end = total_days if peak_points[\"X\" + str(bucket + 1)].item() + bucket_length / 2 >= total_days else peak_points[\"X\" + str(bucket + 1)].item() + int(bucket_length / 2)\n",
    "            groups.append([\"Day \" + str(day) for day in range(begin, end)])\n",
    "        \n",
    "        # Compute the bucket values\n",
    "        for idx in range(peak_num):\n",
    "            vectors[df_idx][idx] = df.loc[df['Admin0']==country][groups[idx]].sum(axis=1)\n",
    "    return vectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_similarity(v1, v2, type=\"cosine\"):\n",
    "    \"\"\"\n",
    "    Compute similarity between two vectors, v1 and v2\n",
    "    type: str, can be 'cosine', 'euclidean', 'pearsonCorrelation'\n",
    "    Returns:\n",
    "        the similarity score (float) between v1 and v2\n",
    "    \"\"\"\n",
    "    if type == \"cosine\":\n",
    "        return v1.dot(v2)/(np.linalg.norm(v1) * np.linalg.norm(v2))\n",
    "    if type == \"euclidean\":\n",
    "        return np.linalg.norm(v1 - v2)\n",
    "    if type == \"pearsonCorrelation\":\n",
    "        return np.cov(np.numpy([v1, v2]))\n",
    "    return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_map = {}\n",
    "for region in availableRegions:\n",
    "    peak_data = loader.get_peak_data(region=region, peak_num=4)\n",
    "    for country in peak_data[\"Admin0\"]:\n",
    "        case_vec, death_vec = get_sliced_vectors(country, peak_data, d1, 40)\n",
    "        data_map[country] = (case_vec, death_vec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_sim_scores_for_paper(sim_matrix, terr_names, data_type, similarity_type, continent=\"Africa\"):\n",
    "    \"\"\"\n",
    "    Plot the similarity scores between given country\n",
    "    and save them to \"results/similarity scores/\"\n",
    "    Different from the scratch one, this one does not have title for figs\n",
    "    \"\"\"\n",
    "    if len(terr_names) > 35:\n",
    "        label_size = 5\n",
    "    else:\n",
    "        label_size = 7\n",
    "\n",
    "    plt.imshow(sim_matrix, vmin=0, vmax=1)\n",
    "    plt.colorbar()\n",
    "\n",
    "    ax = plt.gca()\n",
    "\n",
    "    ax.set_xticks([i for i in range(len(terr_names))])\n",
    "    # ax.set_xticklabels(terr_names, Rotation=90)\n",
    "    ax.set_xticklabels(terr_names)\n",
    "    for label in ax.get_xticklabels():\n",
    "        label.set_rotation(90)\n",
    "    ax.set_yticks([i for i in range(len(terr_names))])\n",
    "    ax.set_yticklabels(terr_names)\n",
    "    ax.tick_params(axis='both', which='major', labelsize=label_size)\n",
    "    \n",
    "    if continent not in availableRegions:\n",
    "        plt.savefig(\"results/similarity scores/\" + similarity_type + \"/countries/\" + data_type + \"_\" + continent + \".png\", transparent=False, facecolor='white')\n",
    "    else:\n",
    "        plt.savefig(\"results/similarity scores/\"  + similarity_type + \"/continents/\" + data_type + \"_\" + terr_names[0] + \".png\", transparent=False, facecolor='white')\n",
    "    plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Afghanistan:  [[1.         0.48402145 0.7899985  0.59416024 0.47056308]\n",
      " [0.48402145 1.         0.80819657 0.61137239 0.80607176]\n",
      " [0.7899985  0.80819657 1.         0.89881528 0.86280884]\n",
      " [0.59416024 0.61137239 0.89881528 1.         0.8584287 ]\n",
      " [0.47056308 0.80607176 0.86280884 0.8584287  1.        ]]\n",
      "Algeria:  [[1.         0.61784322 0.85796812 0.98887214 0.44459368 0.72193377\n",
      "  0.61355149]\n",
      " [0.61784322 1.         0.7963605  0.64552607 0.83125235 0.62655184\n",
      "  0.96613718]\n",
      " [0.85796812 0.7963605  1.         0.88986637 0.63787429 0.69674931\n",
      "  0.74595472]\n",
      " [0.98887214 0.64552607 0.88986637 1.         0.46697323 0.70522446\n",
      "  0.63973684]\n",
      " [0.44459368 0.83125235 0.63787429 0.46697323 1.         0.73349986\n",
      "  0.90252391]\n",
      " [0.72193377 0.62655184 0.69674931 0.70522446 0.73349986 1.\n",
      "  0.66715729]\n",
      " [0.61355149 0.96613718 0.74595472 0.63973684 0.90252391 0.66715729\n",
      "  1.        ]]\n",
      "Angola:  [[1.         0.94241743 0.74335055 0.86792156]\n",
      " [0.94241743 1.         0.63481076 0.82861114]\n",
      " [0.74335055 0.63481076 1.         0.6641044 ]\n",
      " [0.86792156 0.82861114 0.6641044  1.        ]]\n",
      "Armenia:  [[1.         0.75842878 0.85946102]\n",
      " [0.75842878 1.         0.81477594]\n",
      " [0.85946102 0.81477594 1.        ]]\n",
      "Azerbaijan:  [[1.         0.93380705]\n",
      " [0.93380705 1.        ]]\n",
      "Bangladesh:  [[1.]]\n",
      "Benin:  [[1.         0.45272822 0.39994964 0.43169074 0.91350968]\n",
      " [0.45272822 1.         0.41232276 0.37192216 0.76905944]\n",
      " [0.39994964 0.41232276 1.         0.9815822  0.42413081]\n",
      " [0.43169074 0.37192216 0.9815822  1.         0.43328562]\n",
      " [0.91350968 0.76905944 0.42413081 0.43328562 1.        ]]\n",
      "Bhutan:  [[1.         0.51824127]\n",
      " [0.51824127 1.        ]]\n",
      "Botswana:  [[1.         0.9698034  0.76835054 0.6064182  0.75919126]\n",
      " [0.9698034  1.         0.8560952  0.6641044  0.82263802]\n",
      " [0.76835054 0.8560952  1.         0.72439279 0.87357543]\n",
      " [0.6064182  0.6641044  0.72439279 1.         0.87254818]\n",
      " [0.75919126 0.82263802 0.87357543 0.87254818 1.        ]]\n",
      "Burkina Faso:  [[1.         0.45272822 0.78482381 0.80636855 0.91100753 0.41232276\n",
      "  0.76905944]\n",
      " [0.45272822 1.         0.51273909 0.64177963 0.60205379 0.39994964\n",
      "  0.91350968]\n",
      " [0.78482381 0.51273909 1.         0.86182933 0.8422743  0.70678182\n",
      "  0.69605857]\n",
      " [0.80636855 0.64177963 0.86182933 1.         0.91194554 0.7922599\n",
      "  0.78866105]\n",
      " [0.91100753 0.60205379 0.8422743  0.91194554 1.         0.69674931\n",
      "  0.82748922]\n",
      " [0.41232276 0.39994964 0.70678182 0.7922599  0.69674931 1.\n",
      "  0.42413081]\n",
      " [0.76905944 0.91350968 0.69605857 0.78866105 0.82748922 0.42413081\n",
      "  1.        ]]\n",
      "Burundi:  [[1.         0.73943607 0.73045557 0.80883133]\n",
      " [0.73943607 1.         0.77995919 0.56330497]\n",
      " [0.73045557 0.77995919 1.         0.76188669]\n",
      " [0.80883133 0.56330497 0.76188669 1.        ]]\n",
      "Cambodia:  [[1.         0.36649548 0.4566994  0.50956208]\n",
      " [0.36649548 1.         0.85735227 0.92711565]\n",
      " [0.4566994  0.85735227 1.         0.78211311]\n",
      " [0.50956208 0.92711565 0.78211311 1.        ]]\n",
      "Cameroon:  [[1.         0.68428998 0.70445844 0.78036074 0.63532482 0.68517553\n",
      "  0.74061583]\n",
      " [0.68428998 1.         0.64675446 0.84244658 0.98876023 0.90942622\n",
      "  0.77867695]\n",
      " [0.70445844 0.64675446 1.         0.78440388 0.60562526 0.83232851\n",
      "  0.5173357 ]\n",
      " [0.78036074 0.84244658 0.78440388 1.         0.82760908 0.9219783\n",
      "  0.72894115]\n",
      " [0.63532482 0.98876023 0.60562526 0.82760908 1.         0.9141575\n",
      "  0.70451075]\n",
      " [0.68517553 0.90942622 0.83232851 0.9219783  0.9141575  1.\n",
      "  0.64680206]\n",
      " [0.74061583 0.77867695 0.5173357  0.72894115 0.70451075 0.64680206\n",
      "  1.        ]]\n",
      "Central African Republic:  [[1.         0.68428998 0.64675446 0.70709054 0.84244658 0.61302224\n",
      "  0.78306154]\n",
      " [0.68428998 1.         0.70445844 0.64389126 0.78036074 0.62928287\n",
      "  0.81263661]\n",
      " [0.64675446 0.70445844 1.         0.67069656 0.78440388 0.93701812\n",
      "  0.7049161 ]\n",
      " [0.70709054 0.64389126 0.67069656 1.         0.87580123 0.52010837\n",
      "  0.84856749]\n",
      " [0.84244658 0.78036074 0.78440388 0.87580123 1.         0.5978556\n",
      "  0.82620179]\n",
      " [0.61302224 0.62928287 0.93701812 0.52010837 0.5978556  1.\n",
      "  0.62343787]\n",
      " [0.78306154 0.81263661 0.7049161  0.84856749 0.82620179 0.62343787\n",
      "  1.        ]]\n",
      "Chad:  [[1.         0.70445844 0.64675446 0.74728333 0.53277472 0.5173357\n",
      "  0.7049161 ]\n",
      " [0.70445844 1.         0.68428998 0.7391335  0.81799632 0.74061583\n",
      "  0.81263661]\n",
      " [0.64675446 0.68428998 1.         0.87605495 0.72755014 0.77867695\n",
      "  0.78306154]\n",
      " [0.74728333 0.7391335  0.87605495 1.         0.62655184 0.65994645\n",
      "  0.73825067]\n",
      " [0.53277472 0.81799632 0.72755014 0.62655184 1.         0.9815822\n",
      "  0.95655887]\n",
      " [0.5173357  0.74061583 0.77867695 0.65994645 0.9815822  1.\n",
      "  0.96423633]\n",
      " [0.7049161  0.81263661 0.78306154 0.73825067 0.95655887 0.96423633\n",
      "  1.        ]]\n",
      "Congo (Brazzaville):  [[1.         0.94241743 0.78036074 0.84244658 0.9219783 ]\n",
      " [0.94241743 1.         0.65978402 0.81628751 0.95896775]\n",
      " [0.78036074 0.65978402 1.         0.68428998 0.68517553]\n",
      " [0.84244658 0.81628751 0.68428998 1.         0.90942622]\n",
      " [0.9219783  0.95896775 0.68517553 0.90942622 1.        ]]\n",
      "Congo (Kinshasa):  [[1.         0.73943607 0.70709054 0.87580123 0.77995919 0.52010837\n",
      "  0.56330497 0.62890143 0.75359389]\n",
      " [0.73943607 1.         0.53027226 0.75046238 0.73045557 0.63993891\n",
      "  0.80883133 0.91941129 0.82551778]\n",
      " [0.70709054 0.53027226 1.         0.84244658 0.72289992 0.61302224\n",
      "  0.45567434 0.65621178 0.67591175]\n",
      " [0.87580123 0.75046238 0.84244658 1.         0.85669626 0.5978556\n",
      "  0.61465712 0.73433278 0.82861114]\n",
      " [0.77995919 0.73045557 0.72289992 0.85669626 1.         0.30835967\n",
      "  0.76188669 0.64136753 0.9254228 ]\n",
      " [0.52010837 0.63993891 0.61302224 0.5978556  0.30835967 1.\n",
      "  0.15168469 0.78518313 0.54586242]\n",
      " [0.56330497 0.80883133 0.45567434 0.61465712 0.76188669 0.15168469\n",
      "  1.         0.69630673 0.66045085]\n",
      " [0.62890143 0.91941129 0.65621178 0.73433278 0.64136753 0.78518313\n",
      "  0.69630673 1.         0.74877603]\n",
      " [0.75359389 0.82551778 0.67591175 0.82861114 0.9254228  0.54586242\n",
      "  0.66045085 0.74877603 1.        ]]\n",
      "Cote d'Ivoire:  [[1.         0.78482381 0.86182933 0.88607005 0.72752875 0.8422743 ]\n",
      " [0.78482381 1.         0.80636855 0.79621635 0.9345373  0.91100753]\n",
      " [0.86182933 0.80636855 1.         0.94741345 0.70439296 0.91194554]\n",
      " [0.88607005 0.79621635 0.94741345 1.         0.72793022 0.86081769]\n",
      " [0.72752875 0.9345373  0.70439296 0.72793022 1.         0.74774316]\n",
      " [0.8422743  0.91100753 0.91194554 0.86081769 0.74774316 1.        ]]\n",
      "Djibouti:  [[1.         0.8963012  0.85244125]\n",
      " [0.8963012  1.         0.8771621 ]\n",
      " [0.85244125 0.8771621  1.        ]]\n",
      "Egypt:  [[1.         0.72763294 0.82747096 0.90223414]\n",
      " [0.72763294 1.         0.85047681 0.68619027]\n",
      " [0.82747096 0.85047681 1.         0.73825067]\n",
      " [0.90223414 0.68619027 0.73825067 1.        ]]\n",
      "Equatorial Guinea:  [[1.         0.63532482 0.9141575 ]\n",
      " [0.63532482 1.         0.68517553]\n",
      " [0.9141575  0.68517553 1.        ]]\n",
      "Eritrea:  [[1.         0.8963012  0.8771621  0.72216535]\n",
      " [0.8963012  1.         0.85244125 0.71871945]\n",
      " [0.8771621  0.85244125 1.         0.71839459]\n",
      " [0.72216535 0.71871945 0.71839459 1.        ]]\n",
      "Eswatini:  [[1.         0.89093782 0.91211366]\n",
      " [0.89093782 1.         0.90502599]\n",
      " [0.91211366 0.90502599 1.        ]]\n",
      "Ethiopia:  [[1.         0.85244125 0.8771621  0.89834637 0.94584294 0.90915056\n",
      "  0.71839459]\n",
      " [0.85244125 1.         0.8963012  0.85706239 0.82182146 0.90123263\n",
      "  0.71871945]\n",
      " [0.8771621  0.8963012  1.         0.88811825 0.87012325 0.91545113\n",
      "  0.72216535]\n",
      " [0.89834637 0.85706239 0.88811825 1.         0.85283675 0.80862147\n",
      "  0.88660478]\n",
      " [0.94584294 0.82182146 0.87012325 0.85283675 1.         0.86526593\n",
      "  0.5782161 ]\n",
      " [0.90915056 0.90123263 0.91545113 0.80862147 0.86526593 1.\n",
      "  0.62343787]\n",
      " [0.71839459 0.71871945 0.72216535 0.88660478 0.5782161  0.62343787\n",
      "  1.        ]]\n",
      "Gabon:  [[1.         0.68517553 0.78477851 0.9141575 ]\n",
      " [0.68517553 1.         0.64389126 0.63532482]\n",
      " [0.78477851 0.64389126 1.         0.68811948]\n",
      " [0.9141575  0.63532482 0.68811948 1.        ]]\n",
      "Gambia:  [[1.         0.79444919]\n",
      " [0.79444919 1.        ]]\n",
      "Georgia:  [[1.         0.75842878 0.93380705]\n",
      " [0.75842878 1.         0.78610239]\n",
      " [0.93380705 0.78610239 1.        ]]\n",
      "Ghana:  [[1.         0.80636855 0.86182933 0.78866105]\n",
      " [0.80636855 1.         0.78482381 0.76905944]\n",
      " [0.86182933 0.78482381 1.         0.69605857]\n",
      " [0.78866105 0.76905944 0.69605857 1.        ]]\n",
      "Guinea:  [[1.         0.88607005 0.83063587 0.72793022 0.86081769 0.88854245\n",
      "  0.96259497]\n",
      " [0.88607005 1.         0.87625579 0.72752875 0.8422743  0.69124694\n",
      "  0.79336642]\n",
      " [0.83063587 0.87625579 1.         0.86622474 0.7954569  0.56106219\n",
      "  0.70826459]\n",
      " [0.72793022 0.72752875 0.86622474 1.         0.74774316 0.51063865\n",
      "  0.54348602]\n",
      " [0.86081769 0.8422743  0.7954569  0.74774316 1.         0.75670395\n",
      "  0.80761286]\n",
      " [0.88854245 0.69124694 0.56106219 0.51063865 0.75670395 1.\n",
      "  0.91842595]\n",
      " [0.96259497 0.79336642 0.70826459 0.54348602 0.80761286 0.91842595\n",
      "  1.        ]]\n",
      "Guinea-Bissau:  [[1.         0.83063587 0.56106219]\n",
      " [0.83063587 1.         0.88854245]\n",
      " [0.56106219 0.88854245 1.        ]]\n",
      "Indonesia:  [[1.         0.93952257 0.87619748]\n",
      " [0.93952257 1.         0.85174221]\n",
      " [0.87619748 0.85174221 1.        ]]\n",
      "Iran:  [[1.         0.48402145 0.85946102 0.92382517 0.80819657]\n",
      " [0.48402145 1.         0.47373135 0.5982559  0.7899985 ]\n",
      " [0.85946102 0.47373135 1.         0.8278134  0.83210975]\n",
      " [0.92382517 0.5982559  0.8278134  1.         0.89748986]\n",
      " [0.80819657 0.7899985  0.83210975 0.89748986 1.        ]]\n",
      "Iraq:  [[1.         0.92382517 0.66535562 0.98591179 0.69540179]\n",
      " [0.92382517 1.         0.61443638 0.90768656 0.60917029]\n",
      " [0.66535562 0.61443638 1.         0.62730343 0.65594305]\n",
      " [0.98591179 0.90768656 0.62730343 1.         0.71348682]\n",
      " [0.69540179 0.60917029 0.65594305 0.71348682 1.        ]]\n",
      "Israel:  [[1.         0.72763294 0.61903902]\n",
      " [0.72763294 1.         0.86667376]\n",
      " [0.61903902 0.86667376 1.        ]]\n",
      "Jordan:  [[1.         0.66535562 0.61903902 0.65594305]\n",
      " [0.66535562 1.         0.86244544 0.69540179]\n",
      " [0.61903902 0.86244544 1.         0.65288039]\n",
      " [0.65594305 0.69540179 0.65288039 1.        ]]\n",
      "Kazakhstan:  [[1.         0.46240156 0.84115291]\n",
      " [0.46240156 1.         0.64213761]\n",
      " [0.84115291 0.64213761 1.        ]]\n",
      "Kenya:  [[1.         0.89834637 0.85283675 0.80862147 0.54873141 0.89393682]\n",
      " [0.89834637 1.         0.94584294 0.90915056 0.36523224 0.82066879]\n",
      " [0.85283675 0.94584294 1.         0.86526593 0.42160751 0.86056779]\n",
      " [0.80862147 0.90915056 0.86526593 1.         0.15168469 0.78518313]\n",
      " [0.54873141 0.36523224 0.42160751 0.15168469 1.         0.69630673]\n",
      " [0.89393682 0.82066879 0.86056779 0.78518313 0.69630673 1.        ]]\n",
      "Kuwait:  [[1.         0.98591179 0.71348682]\n",
      " [0.98591179 1.         0.69540179]\n",
      " [0.71348682 0.69540179 1.        ]]\n",
      "Kyrgyzstan:  [[1.         0.46240156]\n",
      " [0.46240156 1.        ]]\n",
      "Laos:  [[1.         0.36649548 0.85735227 0.92711565]\n",
      " [0.36649548 1.         0.4566994  0.50956208]\n",
      " [0.85735227 0.4566994  1.         0.78211311]\n",
      " [0.92711565 0.50956208 0.78211311 1.        ]]\n",
      "Lebanon:  [[1.]]\n",
      "Lesotho:  [[1.         0.74958253]\n",
      " [0.74958253 1.        ]]\n",
      "Liberia:  [[1.         0.72793022 0.72752875 0.54348602]\n",
      " [0.72793022 1.         0.88607005 0.96259497]\n",
      " [0.72752875 0.88607005 1.         0.79336642]\n",
      " [0.54348602 0.96259497 0.79336642 1.        ]]\n",
      "Libya:  [[1.         0.61784322 0.74728333 0.82747096 0.62655184 0.73825067\n",
      "  0.96613718]\n",
      " [0.61784322 1.         0.89433669 0.84972276 0.72193377 0.79217597\n",
      "  0.61355149]\n",
      " [0.74728333 0.89433669 1.         0.89750785 0.53277472 0.7049161\n",
      "  0.6642739 ]\n",
      " [0.82747096 0.84972276 0.89750785 1.         0.76160907 0.90223414\n",
      "  0.73998827]\n",
      " [0.62655184 0.72193377 0.53277472 0.76160907 1.         0.95655887\n",
      "  0.66715729]\n",
      " [0.73825067 0.79217597 0.7049161  0.90223414 0.95655887 1.\n",
      "  0.7221158 ]\n",
      " [0.96613718 0.61355149 0.6642739  0.73998827 0.66715729 0.7221158\n",
      "  1.        ]]\n",
      "Malawi:  [[1.         0.84655978 0.50175691 0.9384656 ]\n",
      " [0.84655978 1.         0.24400437 0.66274964]\n",
      " [0.50175691 0.24400437 1.         0.66045085]\n",
      " [0.9384656  0.66274964 0.66045085 1.        ]]\n",
      "Mali:  [[1.         0.85796812 0.91100753 0.8422743  0.86081769 0.88986637\n",
      "  0.69674931 0.75670395]\n",
      " [0.85796812 1.         0.84730517 0.88556699 0.84885647 0.98887214\n",
      "  0.72193377 0.56244746]\n",
      " [0.91100753 0.84730517 1.         0.78482381 0.79621635 0.87990646\n",
      "  0.41232276 0.6521041 ]\n",
      " [0.8422743  0.88556699 0.78482381 1.         0.88607005 0.89007502\n",
      "  0.70678182 0.69124694]\n",
      " [0.86081769 0.84885647 0.79621635 0.88607005 1.         0.85244488\n",
      "  0.64506374 0.88854245]\n",
      " [0.88986637 0.98887214 0.87990646 0.89007502 0.85244488 1.\n",
      "  0.70522446 0.60015891]\n",
      " [0.69674931 0.72193377 0.41232276 0.70678182 0.64506374 0.70522446\n",
      "  1.         0.49779559]\n",
      " [0.75670395 0.56244746 0.6521041  0.69124694 0.88854245 0.60015891\n",
      "  0.49779559 1.        ]]\n",
      "Mauritania:  [[1.         0.98887214 0.88986637 0.60015891]\n",
      " [0.98887214 1.         0.85796812 0.56244746]\n",
      " [0.88986637 0.85796812 1.         0.75670395]\n",
      " [0.60015891 0.56244746 0.75670395 1.        ]]\n",
      "Mongolia:  [[1.]]\n",
      "Morocco:  [[1.         0.44459368]\n",
      " [0.44459368 1.        ]]\n",
      "Mozambique:  [[1.         0.89093782 0.84655978 0.24400437 0.66274964 0.82720326]\n",
      " [0.89093782 1.         0.94104196 0.40646532 0.85115398 0.99096936]\n",
      " [0.84655978 0.94104196 1.         0.50175691 0.9384656  0.92933523]\n",
      " [0.24400437 0.40646532 0.50175691 1.         0.66045085 0.44242976]\n",
      " [0.66274964 0.85115398 0.9384656  0.66045085 1.         0.87254818]\n",
      " [0.82720326 0.99096936 0.92933523 0.44242976 0.87254818 1.        ]]\n",
      "Namibia:  [[1.         0.74335055 0.9698034  0.8560952  0.6641044 ]\n",
      " [0.74335055 1.         0.71690324 0.87268986 0.86792156]\n",
      " [0.9698034  0.71690324 1.         0.76835054 0.6064182 ]\n",
      " [0.8560952  0.87268986 0.76835054 1.         0.72439279]\n",
      " [0.6641044  0.86792156 0.6064182  0.72439279 1.        ]]\n",
      "Nepal:  [[1.         0.51267405]\n",
      " [0.51267405 1.        ]]\n",
      "Niger:  [[1.         0.72193377 0.39994964 0.41232276 0.53277472 0.62655184\n",
      "  0.69674931 0.9815822 ]\n",
      " [0.72193377 1.         0.31360594 0.84730517 0.89433669 0.61784322\n",
      "  0.85796812 0.67150868]\n",
      " [0.39994964 0.31360594 1.         0.45272822 0.48661925 0.86480092\n",
      "  0.60205379 0.43169074]\n",
      " [0.41232276 0.84730517 0.45272822 1.         0.95368097 0.62442483\n",
      "  0.91100753 0.37192216]\n",
      " [0.53277472 0.89433669 0.48661925 0.95368097 1.         0.74728333\n",
      "  0.93350457 0.5173357 ]\n",
      " [0.62655184 0.61784322 0.86480092 0.62442483 0.74728333 1.\n",
      "  0.7963605  0.65994645]\n",
      " [0.69674931 0.85796812 0.60205379 0.91100753 0.93350457 0.7963605\n",
      "  1.         0.68933004]\n",
      " [0.9815822  0.67150868 0.43169074 0.37192216 0.5173357  0.65994645\n",
      "  0.68933004 1.        ]]\n",
      "Nigeria:  [[1.         0.43169074 0.74061583 0.5173357  0.9815822 ]\n",
      " [0.43169074 1.         0.48925657 0.48661925 0.39994964]\n",
      " [0.74061583 0.48925657 1.         0.70445844 0.81799632]\n",
      " [0.5173357  0.48661925 0.70445844 1.         0.53277472]\n",
      " [0.9815822  0.39994964 0.81799632 0.53277472 1.        ]]\n",
      "Oman:  [[1.         0.64940074 0.80864258]\n",
      " [0.64940074 1.         0.74841826]\n",
      " [0.80864258 0.74841826 1.        ]]\n",
      "Papua New Guinea:  [[1.         0.87619748]\n",
      " [0.87619748 1.        ]]\n",
      "Qatar:  [[1.         0.61583305]\n",
      " [0.61583305 1.        ]]\n",
      "Rwanda:  [[1.         0.73045557 0.76188669 0.64136753]\n",
      " [0.73045557 1.         0.80883133 0.91941129]\n",
      " [0.76188669 0.80883133 1.         0.69630673]\n",
      " [0.64136753 0.91941129 0.69630673 1.        ]]\n",
      "Saudi Arabia:  [[1.         0.69540179 0.65594305 0.71348682 0.64940074 0.61583305\n",
      "  0.7736261  0.74841826]\n",
      " [0.69540179 1.         0.66535562 0.98591179 0.9682468  0.52183034\n",
      "  0.88881823 0.85324524]\n",
      " [0.65594305 0.66535562 1.         0.62730343 0.68673723 0.79413856\n",
      "  0.53694042 0.51422266]\n",
      " [0.71348682 0.98591179 0.62730343 1.         0.95624819 0.50168965\n",
      "  0.93309614 0.8411992 ]\n",
      " [0.64940074 0.9682468  0.68673723 0.95624819 1.         0.63942758\n",
      "  0.86084475 0.80864258]\n",
      " [0.61583305 0.52183034 0.79413856 0.50168965 0.63942758 1.\n",
      "  0.41267184 0.4683681 ]\n",
      " [0.7736261  0.88881823 0.53694042 0.93309614 0.86084475 0.41267184\n",
      "  1.         0.87842147]\n",
      " [0.74841826 0.85324524 0.51422266 0.8411992  0.80864258 0.4683681\n",
      "  0.87842147 1.        ]]\n",
      "Senegal:  [[1.         0.79444919 0.88854245 0.56106219 0.75670395 0.60015891]\n",
      " [0.79444919 1.         0.81093646 0.68189027 0.6486918  0.61207554]\n",
      " [0.88854245 0.81093646 1.         0.83063587 0.86081769 0.85244488]\n",
      " [0.56106219 0.68189027 0.83063587 1.         0.7954569  0.96536611]\n",
      " [0.75670395 0.6486918  0.86081769 0.7954569  1.         0.88986637]\n",
      " [0.60015891 0.61207554 0.85244488 0.96536611 0.88986637 1.        ]]\n",
      "Sierra Leone:  [[1.         0.96259497 0.54348602]\n",
      " [0.96259497 1.         0.72793022]\n",
      " [0.54348602 0.72793022 1.        ]]\n",
      "Somalia:  [[1.         0.82182146 0.94584294 0.85283675]\n",
      " [0.82182146 1.         0.85244125 0.85706239]\n",
      " [0.94584294 0.85244125 1.         0.89834637]\n",
      " [0.85283675 0.85706239 0.89834637 1.        ]]\n",
      "South Africa:  [[1.         0.76835054 0.91211366 0.74958253 0.8560952  0.87357543]\n",
      " [0.76835054 1.         0.82652112 0.54856689 0.9698034  0.75919126]\n",
      " [0.91211366 0.82652112 1.         0.72966583 0.88844713 0.99096936]\n",
      " [0.74958253 0.54856689 0.72966583 1.         0.5311294  0.74228895]\n",
      " [0.8560952  0.9698034  0.88844713 0.5311294  1.         0.82263802]\n",
      " [0.87357543 0.75919126 0.99096936 0.74228895 0.82263802 1.        ]]\n",
      "South Sudan:  [[1.         0.61302224 0.90915056 0.80862147 0.62343787 0.78518313]\n",
      " [0.61302224 1.         0.76693459 0.82183433 0.78306154 0.65621178]\n",
      " [0.90915056 0.76693459 1.         0.89834637 0.71839459 0.82066879]\n",
      " [0.80862147 0.82183433 0.89834637 1.         0.88660478 0.89393682]\n",
      " [0.62343787 0.78306154 0.71839459 0.88660478 1.         0.62799756]\n",
      " [0.78518313 0.65621178 0.82066879 0.89393682 0.62799756 1.        ]]\n",
      "Sudan:  [[1.         0.78306154 0.7049161  0.90223414 0.72216535 0.71839459\n",
      "  0.73825067 0.62343787]\n",
      " [0.78306154 1.         0.64675446 0.77357693 0.58663195 0.76693459\n",
      "  0.87605495 0.61302224]\n",
      " [0.7049161  0.64675446 1.         0.89750785 0.92098779 0.97712704\n",
      "  0.74728333 0.93701812]\n",
      " [0.90223414 0.77357693 0.89750785 1.         0.80473528 0.91331316\n",
      "  0.82747096 0.77917739]\n",
      " [0.72216535 0.58663195 0.92098779 0.80473528 1.         0.8771621\n",
      "  0.66593131 0.91545113]\n",
      " [0.71839459 0.76693459 0.97712704 0.91331316 0.8771621  1.\n",
      "  0.83730142 0.90915056]\n",
      " [0.73825067 0.87605495 0.74728333 0.82747096 0.66593131 0.83730142\n",
      "  1.         0.59032563]\n",
      " [0.62343787 0.61302224 0.93701812 0.77917739 0.91545113 0.90915056\n",
      "  0.59032563 1.        ]]\n",
      "Syria:  [[1.         0.86244544 0.66535562]\n",
      " [0.86244544 1.         0.61903902]\n",
      " [0.66535562 0.61903902 1.        ]]\n",
      "Tajikistan:  [[1.         0.59416024]\n",
      " [0.59416024 1.        ]]\n",
      "Tanzania:  [[1.         0.80883133 0.54873141 0.50175691 0.24400437 0.76188669\n",
      "  0.69630673 0.66045085]\n",
      " [0.80883133 1.         0.82430037 0.84131423 0.70035149 0.73045557\n",
      "  0.91941129 0.82551778]\n",
      " [0.54873141 0.82430037 1.         0.85069918 0.88945015 0.73913802\n",
      "  0.89393682 0.8010399 ]\n",
      " [0.50175691 0.84131423 0.85069918 1.         0.84655978 0.75686152\n",
      "  0.83175572 0.9384656 ]\n",
      " [0.24400437 0.70035149 0.88945015 0.84655978 1.         0.46545774\n",
      "  0.83886157 0.66274964]\n",
      " [0.76188669 0.73045557 0.73913802 0.75686152 0.46545774 1.\n",
      "  0.64136753 0.9254228 ]\n",
      " [0.69630673 0.91941129 0.89393682 0.83175572 0.83886157 0.64136753\n",
      "  1.         0.74877603]\n",
      " [0.66045085 0.82551778 0.8010399  0.9384656  0.66274964 0.9254228\n",
      "  0.74877603 1.        ]]\n",
      "Thailand:  [[1.         0.4566994  0.85735227 0.97539655]\n",
      " [0.4566994  1.         0.36649548 0.59991435]\n",
      " [0.85735227 0.36649548 1.         0.83166025]\n",
      " [0.97539655 0.59991435 0.83166025 1.        ]]\n",
      "Togo:  [[1.         0.91350968 0.76905944 0.78866105]\n",
      " [0.91350968 1.         0.45272822 0.64177963]\n",
      " [0.76905944 0.45272822 1.         0.80636855]\n",
      " [0.78866105 0.64177963 0.80636855 1.        ]]\n",
      "Tunisia:  [[1.         0.61355149 0.96613718]\n",
      " [0.61355149 1.         0.61784322]\n",
      " [0.96613718 0.61784322 1.        ]]\n",
      "Turkey:  [[1.         0.78610239 0.75842878 0.85946102 0.8278134 ]\n",
      " [0.78610239 1.         0.93380705 0.71862651 0.84622831]\n",
      " [0.75842878 0.93380705 1.         0.81477594 0.87275559]\n",
      " [0.85946102 0.71862651 0.81477594 1.         0.92382517]\n",
      " [0.8278134  0.84622831 0.87275559 0.92382517 1.        ]]\n",
      "Uganda:  [[1.         0.89393682 0.64136753 0.78518313 0.69630673]\n",
      " [0.89393682 1.         0.73913802 0.80862147 0.54873141]\n",
      " [0.64136753 0.73913802 1.         0.30835967 0.76188669]\n",
      " [0.78518313 0.80862147 0.30835967 1.         0.15168469]\n",
      " [0.69630673 0.54873141 0.76188669 0.15168469 1.        ]]\n",
      "United Arab Emirates:  [[1.        0.7736261]\n",
      " [0.7736261 1.       ]]\n",
      "Uzbekistan:  [[1.         0.47056308 0.84115291]\n",
      " [0.47056308 1.         0.40548913]\n",
      " [0.84115291 0.40548913 1.        ]]\n",
      "Vietnam:  [[1.         0.50956208 0.92711565]\n",
      " [0.50956208 1.         0.36649548]\n",
      " [0.92711565 0.36649548 1.        ]]\n",
      "Yemen:  [[1.         0.80864258 0.74841826]\n",
      " [0.80864258 1.         0.64940074]\n",
      " [0.74841826 0.64940074 1.        ]]\n",
      "Zambia:  [[1.         0.86792156 0.6064182  0.9384656  0.66274964 0.6641044\n",
      "  0.66045085 0.87254818]\n",
      " [0.86792156 1.         0.71690324 0.86783832 0.73470458 0.74335055\n",
      "  0.67105899 0.84768129]\n",
      " [0.6064182  0.71690324 1.         0.82572693 0.92198091 0.9698034\n",
      "  0.31006438 0.75919126]\n",
      " [0.9384656  0.86783832 0.82572693 1.         0.84655978 0.87108133\n",
      "  0.50175691 0.92933523]\n",
      " [0.66274964 0.73470458 0.92198091 0.84655978 1.         0.96940441\n",
      "  0.24400437 0.82720326]\n",
      " [0.6641044  0.74335055 0.9698034  0.87108133 0.96940441 1.\n",
      "  0.21758214 0.82263802]\n",
      " [0.66045085 0.67105899 0.31006438 0.50175691 0.24400437 0.21758214\n",
      "  1.         0.44242976]\n",
      " [0.87254818 0.84768129 0.75919126 0.92933523 0.82720326 0.82263802\n",
      "  0.44242976 1.        ]]\n",
      "Zimbabwe:  [[1.         0.75919126 0.82720326 0.87357543 0.87254818]\n",
      " [0.75919126 1.         0.92198091 0.76835054 0.6064182 ]\n",
      " [0.82720326 0.92198091 1.         0.90502599 0.66274964]\n",
      " [0.87357543 0.76835054 0.90502599 1.         0.72439279]\n",
      " [0.87254818 0.6064182  0.66274964 0.72439279 1.        ]]\n",
      "India:  [[1.         0.36844762 0.51824127 0.51267405 0.60524954 0.33436034]\n",
      " [0.36844762 1.         0.79767933 0.6583752  0.83201973 0.95066975]\n",
      " [0.51824127 0.79767933 1.         0.86237779 0.81542364 0.90206949]\n",
      " [0.51267405 0.6583752  0.86237779 1.         0.81810776 0.76980873]\n",
      " [0.60524954 0.83201973 0.81542364 0.81810776 1.         0.81063805]\n",
      " [0.33436034 0.95066975 0.90206949 0.76980873 0.81063805 1.        ]]\n",
      "Russia:  [[1.         0.93380705 0.72061341 0.69286403]\n",
      " [0.93380705 1.         0.83077178 0.84934718]\n",
      " [0.72061341 0.83077178 1.         0.95047183]\n",
      " [0.69286403 0.84934718 0.95047183 1.        ]]\n",
      "Pakistan:  [[1.         0.7899985  0.60524954 0.80819657]\n",
      " [0.7899985  1.         0.32241832 0.48402145]\n",
      " [0.60524954 0.32241832 1.         0.45041442]\n",
      " [0.80819657 0.48402145 0.45041442 1.        ]]\n",
      "Malaysia:  [[1.         0.93952257 0.97539655]\n",
      " [0.93952257 1.         0.92152733]\n",
      " [0.97539655 0.92152733 1.        ]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 6000x4000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute similarity\n",
    "neighbors = pd.read_csv(\"data/neighbor_map/neighbors_world.csv\")\n",
    "for base_country in d1[0][\"Admin0\"]:\n",
    "    if neighbors.loc[neighbors[\"Country or territory\"]==base_country][\"neighbor list\"].tolist() and type(neighbors.loc[neighbors[\"Country or territory\"]==base_country][\"neighbor list\"].tolist()[0]) is str:\n",
    "                list_of_neighbors = neighbors.loc[neighbors[\"Country or territory\"]==base_country][\"neighbor list\"].tolist()[0].split(\",\")\n",
    "    else:\n",
    "        continue\n",
    "    list_of_neighbors.insert(0, base_country)\n",
    "    # Remove the neighbors not in the list and leading white space\n",
    "    actual_list = []\n",
    "    for idx in range(len(list_of_neighbors)):\n",
    "        list_of_neighbors[idx] = list_of_neighbors[idx].lstrip()\n",
    "        if list_of_neighbors[idx] in data_map:\n",
    "            actual_list.append(list_of_neighbors[idx])\n",
    "    list_of_neighbors = actual_list\n",
    "    sim_mat = np.zeros([len(list_of_neighbors), len(list_of_neighbors)])\n",
    "    for country_idx, country in enumerate(list_of_neighbors):\n",
    "        for target_country_idx, target_country in enumerate(list_of_neighbors):\n",
    "            sim_mat[country_idx, target_country_idx] = compute_similarity(data_map[country][0], data_map[target_country][0])\n",
    "    if len(list_of_neighbors) > 0:\n",
    "        print(base_country + \": \", sim_mat)\n",
    "        plot_sim_scores_for_paper(sim_mat, list_of_neighbors, \"case\", \"cosine\", base_country)"
   ]
  }
 ],
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