{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6b34fd9c-84fa-4f1d-bdbe-419016ade8d2",
   "metadata": {},
   "source": [
    "# Figure 4: Boxplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "da212a9f-0bd0-451a-be28-9fd7cb882825",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR 1: PROJ: proj_create_from_database: Open of /srv/conda/envs/notebook/share/proj failed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from scipy.interpolate import InterpolatedUnivariateSpline\n",
    "\n",
    "import smpsite as smp\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "101d210c-f045-4ebf-a2de-35a5caee146d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>plong</th>\n",
       "      <th>plat</th>\n",
       "      <th>total_samples</th>\n",
       "      <th>samples_per_sites</th>\n",
       "      <th>S2_vgp</th>\n",
       "      <th>error_angle</th>\n",
       "      <th>S2_vgp_real</th>\n",
       "      <th>n_tot</th>\n",
       "      <th>N</th>\n",
       "      <th>n0</th>\n",
       "      <th>kappa_within_site</th>\n",
       "      <th>site_lat</th>\n",
       "      <th>site_long</th>\n",
       "      <th>outlier_rate</th>\n",
       "      <th>secular_method</th>\n",
       "      <th>kappa_secular</th>\n",
       "      <th>ignore_outliers</th>\n",
       "      <th>hash</th>\n",
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       "      <td>89.231872</td>\n",
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       "      <td>0.768128</td>\n",
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       "      <th>2</th>\n",
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       "      <td>100.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>-8335591600388957984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>330.248972</td>\n",
       "      <td>87.105972</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2</td>\n",
       "      <td>163.079929</td>\n",
       "      <td>2.894028</td>\n",
       "      <td>191.7229</td>\n",
       "      <td>100</td>\n",
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       "      <td>True</td>\n",
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       "      <td>vandamme</td>\n",
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       "      <th>524997</th>\n",
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       "      <td>96.0</td>\n",
       "      <td>6</td>\n",
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       "      <td>6</td>\n",
       "      <td>50</td>\n",
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       "    <tr>\n",
       "      <th>524999</th>\n",
       "      <td>4999</td>\n",
       "      <td>315.637990</td>\n",
       "      <td>86.584133</td>\n",
       "      <td>90.0</td>\n",
       "      <td>6</td>\n",
       "      <td>58.631713</td>\n",
       "      <td>3.415867</td>\n",
       "      <td>191.7229</td>\n",
       "      <td>102</td>\n",
       "      <td>17</td>\n",
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       "      <td>50</td>\n",
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       "      <td>0.4</td>\n",
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       "      <td>vandamme</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>525000 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0       plong       plat  total_samples  samples_per_sites  \\\n",
       "0                0  231.233958  89.078084          100.0                  2   \n",
       "1                1   63.804499  89.231872          100.0                  2   \n",
       "2                2  291.665245  87.059161          100.0                  2   \n",
       "3                3  330.248972  87.105972          100.0                  2   \n",
       "4                4   38.224125  87.075199          100.0                  2   \n",
       "...            ...         ...        ...            ...                ...   \n",
       "524995        4995  148.732544  84.169662           96.0                  6   \n",
       "524996        4996   57.944083  88.316125           84.0                  6   \n",
       "524997        4997  332.897508  82.935519           96.0                  6   \n",
       "524998        4998  289.433482  82.479833           96.0                  6   \n",
       "524999        4999  315.637990  86.584133           90.0                  6   \n",
       "\n",
       "            S2_vgp  error_angle  S2_vgp_real  n_tot   N  n0  \\\n",
       "0       258.092561     0.921916     191.7229    100  50   2   \n",
       "1       181.571799     0.768128     191.7229    100  50   2   \n",
       "2       179.071413     2.940839     191.7229    100  50   2   \n",
       "3       163.079929     2.894028     191.7229    100  50   2   \n",
       "4       218.421320     2.924801     191.7229    100  50   2   \n",
       "...            ...          ...          ...    ...  ..  ..   \n",
       "524995 -155.962415     5.830338     191.7229    102  17   6   \n",
       "524996 -296.623262     1.683875     191.7229    102  17   6   \n",
       "524997  205.145417     7.064481     191.7229    102  17   6   \n",
       "524998  -27.928311     7.520167     191.7229    102  17   6   \n",
       "524999   58.631713     3.415867     191.7229    102  17   6   \n",
       "\n",
       "        kappa_within_site  site_lat  site_long  outlier_rate secular_method  \\\n",
       "0                      50      30.0        0.0           0.0              G   \n",
       "1                      50      30.0        0.0           0.0              G   \n",
       "2                      50      30.0        0.0           0.0              G   \n",
       "3                      50      30.0        0.0           0.0              G   \n",
       "4                      50      30.0        0.0           0.0              G   \n",
       "...                   ...       ...        ...           ...            ...   \n",
       "524995                 50      30.0        0.0           0.4              G   \n",
       "524996                 50      30.0        0.0           0.4              G   \n",
       "524997                 50      30.0        0.0           0.4              G   \n",
       "524998                 50      30.0        0.0           0.4              G   \n",
       "524999                 50      30.0        0.0           0.4              G   \n",
       "\n",
       "        kappa_secular ignore_outliers                 hash  \n",
       "0                 NaN            True -8335591600388957984  \n",
       "1                 NaN            True -8335591600388957984  \n",
       "2                 NaN            True -8335591600388957984  \n",
       "3                 NaN            True -8335591600388957984  \n",
       "4                 NaN            True -8335591600388957984  \n",
       "...               ...             ...                  ...  \n",
       "524995            NaN        vandamme  2995613283241899664  \n",
       "524996            NaN        vandamme  2995613283241899664  \n",
       "524997            NaN        vandamme  2995613283241899664  \n",
       "524998            NaN        vandamme  2995613283241899664  \n",
       "524999            NaN        vandamme  2995613283241899664  \n",
       "\n",
       "[525000 rows x 19 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"../../outputs/fig4_5000sim_total.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "28d022d4-816f-4fe0-838f-44e61b49e5d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_3098/4131771631.py:17: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_[\"Sampling Strategy\"] = df_.apply(lambda row : rename_outlier_method(row.ignore_outliers), axis=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(14,6))\n",
    "\n",
    "outlier_rate = .10\n",
    "\n",
    "df_ = df[df.outlier_rate == outlier_rate]\n",
    "\n",
    "def rename_outlier_method(x):\n",
    "    if x == \"vandamme\": \n",
    "        return \"Vandamme\"\n",
    "    elif x == \"False\":\n",
    "        return \"No detection\"\n",
    "    elif x == \"True\":\n",
    "        return \"Perfect detection\"\n",
    "    else: \n",
    "        raise ValueError()\n",
    "\n",
    "df_[\"Sampling Strategy\"] = df_.apply(lambda row : rename_outlier_method(row.ignore_outliers), axis=1) \n",
    "        \n",
    "my_pal = {\"Vandamme\": \"#e84118\", \n",
    "          \"No detection\": \"#ecf0f1\",\n",
    "          \"Perfect detection\": \"#0097e6\"}\n",
    "\n",
    "hue_order = [\"Vandamme\", \"Perfect detection\", \"No detection\"]\n",
    "\n",
    "# create grouped boxplot \n",
    "sns.boxplot(data = df_,\n",
    "            x = 'samples_per_sites',\n",
    "            y = 'error_angle',\n",
    "            hue = 'Sampling Strategy',\n",
    "            hue_order = hue_order, \n",
    "            palette=my_pal,\n",
    "            fliersize=0.4, \n",
    "            boxprops=dict(alpha=.9),\n",
    "            width=0.8, \n",
    "            #orient = \"h\",\n",
    "            ax=ax)\n",
    "\n",
    "plt.legend(loc='upper left', fontsize=16)\n",
    "ax.set_ylim(0,10)\n",
    "\n",
    "plt.xlabel(\"Samples per site ($n_0$)\", fontsize=20)\n",
    "plt.ylabel(\"Angular error (degrees)\", fontsize=20)\n",
    "plt.yticks(fontsize=18)\n",
    "plt.xticks([0,1,2,3,4,5,6,7], fontsize=18)\n",
    "\n",
    "ax.spines[['right', 'top']].set_visible(False)\n",
    "\n",
    "#plt.savefig(\"Figure4_{}.pdf\".format(outlier_rate), format=\"pdf\", bbox_inches='tight')\n",
    "#plt.savefig(\"Figure4_{}.png\".format(outlier_rate), format=\"png\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23df9919-5a97-48f4-b3d7-7d2817143a9b",
   "metadata": {},
   "source": [
    "## VGP scatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e5d9e666-2ee5-42c8-a07e-a52ccc7ae62f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_3098/2634743452.py:19: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_[\"Sampling Strategy\"] = df_.apply(lambda row : rename_outlier_method(row.ignore_outliers), axis=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(14,6))\n",
    "\n",
    "df[\"error_S_vgp\"] = (df.S2_vgp ** .5 - df.S2_vgp_real ** .5) / df.S2_vgp_real ** .5 * 100\n",
    "\n",
    "outlier_rate = .4\n",
    "\n",
    "df_ = df[df.outlier_rate == outlier_rate]\n",
    "\n",
    "def rename_outlier_method(x):\n",
    "    if x == \"vandamme\": \n",
    "        return \"Vandamme\"\n",
    "    elif x == \"False\":\n",
    "        return \"No detection\"\n",
    "    elif x == \"True\":\n",
    "        return \"Perfect detection\"\n",
    "    else: \n",
    "        raise ValueError()\n",
    "\n",
    "df_[\"Sampling Strategy\"] = df_.apply(lambda row : rename_outlier_method(row.ignore_outliers), axis=1) \n",
    "        \n",
    "my_pal = {\"Vandamme\": \"#e84118\", \n",
    "          \"No detection\": \"#ecf0f1\",\n",
    "          \"Perfect detection\": \"#0097e6\"}\n",
    "\n",
    "hue_order = [\"Vandamme\", \"Perfect detection\", \"No detection\"]\n",
    "\n",
    "plt.axhline(y=0, color = 'black', ls=\"--\", lw=1)\n",
    "\n",
    "# create grouped boxplot \n",
    "sns.boxplot(data = df_,\n",
    "            x = 'samples_per_sites',\n",
    "            y = 'error_S_vgp',\n",
    "            hue = 'Sampling Strategy',\n",
    "            hue_order = hue_order, \n",
    "            palette=my_pal,\n",
    "            fliersize=0.4, \n",
    "            boxprops=dict(alpha=.9),\n",
    "            width=0.8, \n",
    "            #orient = \"h\",\n",
    "            ax=ax)\n",
    "\n",
    "plt.legend(loc='upper right', fontsize=16)\n",
    "ax.set_ylim(-1,1)\n",
    "\n",
    "plt.xlabel(\"Samples per site ($n_0$)\", fontsize=20)\n",
    "plt.ylabel(\"Percentual error for $S_b$\", fontsize=20)\n",
    "plt.yticks(fontsize=18)\n",
    "plt.xticks([0,1,2,3,4,5,6,7], fontsize=18)\n",
    "plt.yticks([-100, -75, -50, -25, 0, 25, 50, 75, 100], [ \"-100%\", \"-75%\", \"-50%\",\"-25%\",\"0%\",\"25%\",\"50%\",\"75%\", \"100%\"])\n",
    "\n",
    "\n",
    "ax.spines[['right', 'top']].set_visible(False)\n",
    "\n",
    "plt.savefig(\"Figure5_{}.pdf\".format(outlier_rate), format=\"pdf\", bbox_inches='tight')\n",
    "plt.savefig(\"Figure5_{}.png\".format(outlier_rate), format=\"png\", bbox_inches='tight')"
   ]
  }
 ],
 "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}