03_singledataset_scatter_NIST-temperature-corrected.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "import pandas as pd\n",
    "import json\n",
    "import nibabel as nib\n",
    "import numpy as np\n",
    "\n",
    "from src.database import *\n",
    "from src.nist import get_reference_NIST_values, get_NIST_ids\n",
    "from src.tools import calc_error\n",
    "from src.nist import temperature_correction\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('custom_matplotlibrc')\n",
    "plt.rcParams[\"figure.figsize\"] = (10,10)\n",
    "fig_id = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configurations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "database_path = Path('databases/3T_NIST_T1maps_database.pkl')\n",
    "output_folder = Path(\"plots/03_singledataset_scatter_NIST-temperature-corrected/\")\n",
    "\n",
    "estimate_type = 'mean' # median or mean"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:5: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "<>:11: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "<>:16: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "<>:5: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "<>:11: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "<>:16: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "/var/folders/l1/1xswjffd73l8yp7dd7pq9lyw0000gn/T/ipykernel_97215/368739589.py:5: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "  if y_type is 'linear':\n",
      "/var/folders/l1/1xswjffd73l8yp7dd7pq9lyw0000gn/T/ipykernel_97215/368739589.py:11: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "  if y_type is 'log':\n",
      "/var/folders/l1/1xswjffd73l8yp7dd7pq9lyw0000gn/T/ipykernel_97215/368739589.py:16: SyntaxWarning: \"is\" with a literal. Did you mean \"==\"?\n",
      "  if y_type is 'error_t1':\n"
     ]
    }
   ],
   "source": [
    "def plot_single_scatter(x, y, y_std,\n",
    "                        title, x_label, y_label,\n",
    "                        file_prefix, folder_path, fig_id,\n",
    "                        y_type='linear'):\n",
    "    if y_type is 'linear':\n",
    "        plt.errorbar(x,y, y_std, fmt='o', solid_capstyle='projecting')\n",
    "        ax = plt.gca()\n",
    "        ax.axline((1, 1), slope=1, linestyle='dashed')\n",
    "        ax.set_ylim(ymin=0, ymax=2500)\n",
    "        ax.set_xlim(xmin=0, xmax=2500)\n",
    "    if y_type is 'log':\n",
    "        plt.loglog(x,y,'o')\n",
    "        ax = plt.gca()\n",
    "        ax.set_ylim(ymin=20, ymax=2500)\n",
    "        ax.set_xlim(xmin=20, xmax=2500)\n",
    "    if y_type is 'error_t1':\n",
    "        plt.errorbar(x,calc_error(x,y), fmt='o')\n",
    "        ax = plt.gca()\n",
    "        ax.axline((1, 0), slope=0, color='k')\n",
    "        ax.axline((1, -10), slope=0, linestyle='dashed', color='k')\n",
    "        ax.axline((1, 10), slope=0, linestyle='dashed', color='k')\n",
    "        ax.set_ylim(ymin=-100, ymax=100)\n",
    "        ax.set_xlim(xmin=0, xmax=2500)\n",
    "\n",
    "\n",
    "    \n",
    "    plt.title(title)\n",
    "    plt.xlabel(x_label)\n",
    "    plt.ylabel(y_label)\n",
    "\n",
    "    fig = plt.gcf()\n",
    "    \n",
    "\n",
    "    folder_path.mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "    if fig_id<10:\n",
    "        filename = \"0\" + str(fig_id) + \"_\" + file_prefix\n",
    "    else:\n",
    "        filename = str(fig_id) + \"_\" + file_prefix\n",
    "\n",
    "    fig.savefig(folder_path / (str(filename) + '.svg'), facecolor='white')\n",
    "    fig.savefig(folder_path / (str(filename) + '.png'), facecolor='white')\n",
    "    fig_id = fig_id + 1\n",
    "    plt.show()\n",
    "    return fig_id"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_pickle(database_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize variables, store mean and standard deviations of T1 in the ROIs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_estimate = np.array([])\n",
    "dataset_std = np.array([])\n",
    "\n",
    "index = 6.001\n",
    "\n",
    "serial_number = df.loc[index]['phantom serial number']\n",
    "\n",
    "\n",
    "for key in get_NIST_ids():\n",
    "    if estimate_type == 'mean':\n",
    "        dataset_estimate = np.append(dataset_estimate, np.mean(df.loc[index][key]))\n",
    "    elif estimate_type == 'median':\n",
    "        dataset_estimate = np.append(dataset_estimate, np.median(df.loc[index][key]))\n",
    "    else:\n",
    "        Exception('Unsupported dataset estimate type.')\n",
    "\n",
    "    dataset_std = np.append(dataset_std, np.std(df.loc[index][key]))\n",
    "\n",
    "ref_values = get_reference_NIST_values(serial_number)\n",
    "\n",
    "temperature = df.loc[index]['phantom temperature']\n",
    "temp_corrected_ref_values = temperature_correction(temperature, serial_number)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "23\n"
     ]
    }
   ],
   "source": [
    "print(serial_number)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_id = plot_single_scatter(x=temp_corrected_ref_values,\n",
    "                             y=dataset_estimate,\n",
    "                             y_std=dataset_std,\n",
    "                             title='Linear axes',\n",
    "                             x_label='Reference T$_1$ (ms)',\n",
    "                             y_label=\"T$_1$ estimate (ms)\",\n",
    "                             file_prefix=str(index),\n",
    "                             folder_path=output_folder,\n",
    "                             fig_id=fig_id,\n",
    "                             y_type='linear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkiqrb74bIEmSpMl27x3m0qGdbNu+h+H9owws72PDulVcMLiW1SsH5rt5C0pk5ny3odIiYtIH6OcpSZJacc2OW7nw8usYGRtndPxgrujrCfp7e9iyaT1nnX78PLaweyJi0uvMjEPKGL5aY5iVJEntsnvvMOdeMsS+kbEpy6zo7+WqiwaXRA9tM2HWMbOSJEkLxKVDOxkZG5+2zMjYOFuHdnWpRQufYVaSJGmB2LZ9z6ShBY2MjidXbr+5Sy1a+AyzkiRJC8Tw/tHmyh1ortxSYJiVJElaIAaWNzfR1MAyJ6SaYJiVJElaIDasW0VfzyH3OE3S1xNsXHdSl1q08BlmJUmSFogLBtfS3zt9POvv7WHz4JoutWjhM8xKkiQtEKtXDrBl03pW9Pce0kPb1xOs6O9ly6b1S2JarmY5z2yLnGdWkiS12+69w2wd2sWV229m+MAoA8v62LjuJDYPrllSQdZFE7rAMCtJktQZLpogSZKkRc0wK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLN1IqIvIv4+Im6OiNsj4p0RMTDf7ZIkSdKh+ua7AQvQXwPfBtYBvwJcAfwQ+Kv5bJQkSZIOZZitUfbAXpeZHy93fSIirgLOmMdmSZIkaQoOM6iRmcM1QXbC0cC/zUNzJEmSNIPKh9mIeHhEXBURj56mzMMi4uMRcW25/WdEnN3EtR8HfD0zt7S10ZIkSWqLyobZiHhEOQTgS8A5TDFkIiKeCHwe+GxmnpmZZwKXAp+MiM1TnLM6It4OfAz4g4h4QkfehCRJkloSmTnfbZi1iLg3cBKwE7gJOBw4KzM/W1duDfAN4JuZ+fC6Y1cATwYelJnXN6jjCODRwJvL66/OzLsalJv0AVbx85QkaTHZvXeYS4d2sm37Hob3jzKwvI8N61ZxweBaVq90gqIqiYhJrzMz6stUsmc2M3+QmV/OzB8DP56m6F8CA8BlDY79C9APvHSKOu7IzKuA84HjgdNbabMkSeq8a3bcyrmXDPG+a7/PHftHSeCO/aO879rvc+4lQ1yz49b5bqLarJJhthlRRPmnlS+HGhT5ApDAkyLiyGkudW35ONLG5kmSpDbbvXeYCy+/jn0jY4yOT/5L6eh4sm9kjAsvv47de4fnqYXqhEUbZil6Uo+hCKw31h/MzJ8BtwCHAQ+Z5jonAnsaXUOSJC0clw7tZGRsfNoyI2PjbB3a1aUWqRsWc5g9pXy8PTMPTFHmR+Xj/QAi4tiIeF1E3L98HcDfAM/PTHtmJUlawLZt33NIj2y90fHkyu03d6lF6obFvGjCMeXjvmnKTBw7unzsB84GnhURHwJ2AZdlZqNhCkTEH7WhnZIkqQ2G9482V+5Ac+VUDYs5zE6Y7le0sfIxADLzFuBBTV84820R8dYW2iZJktpkYHkfdzQRaAeWLYX4s3Qs5mEGt5WPK6YpM3Hsp51tiiRJ6rQN61bR13PIzE2T9PUEG9ed1KUWqRsWc5iduGHrmIiY6lewE8rHG7rQHkmS1EEXDK6lv3f6aNPf28PmwTVdapG6YdGG2czcCfyQ4j2eWn88IgYoZioY4eD0W5IkqaJWrxxgy6b1rOjvPaSHtq8nWNHfy5ZN6104YZFZtGG29OHy8dENjj0K6AWuzsxfdK9JkiSpU846/XiuumiQ8848mSOW9xEBRyzv47wzT+aqiwY56/Tj57uJarNKLmdbKyJuBlbReDnbX6JYzvYrmTlYd+y9FIsqPDYzP9dC/S5nK0mS1AGLdjnbCRHxQOBe5cuH1h/PzBuB5wGPjIjn15z3NIog+4pWgqwkSZLmVyV7ZiPiZGAbcAbF3LATdgCXZOZb6sr/OnAxcBTFdFzjwBsy84o2tMWeWUmSpA5opme2kmF2ITHMSpIkdcaiH2YgSZKkpc0wK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKqtvvhsgSZIWvt17h7l0aCfbtu9heP8oA8v72LBuFRcMrmX1yoH5bp6WsMjM+W5DpUXEpA/Qz1OStNhcs+NWLrz8OkbGxhkdP/jvXF9P0N/bw5ZN6znr9OPnsYVarCJi0uvMjEPKGL5aY5iVJC1mu/cOc+4lQ+wbGZuyzIr+Xq66aNAeWrVdM2HWMbOSJGlKlw7tZGRsfNoyI2PjbB3a1aUWSZMZZiVJ0pS2bd8zaWhBI6PjyZXbb+5Si6TJDLOSJGlKw/tHmyt3oLlyUrsZZiVJ0pQGljc38dHAMidI0vwwzEqSpCltWLeKvp5D7rmZpK8n2LjupC61SJrMMCtJkqZ0weBa+nunjwv9vT1sHlzTpRZJkxlmJUnSlFavHGDLpvWs6O89pIe2rydY0d/Llk3rnZZL88Z5ZlvkPLOSpKVg995htg7t4srtNzN8YJSBZX1sXHcSmwfXGGTVMS6a0AWGWUmSpM5w0QRJkiQtaoZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZXVN98NkCRpKdq9d5hLh3aybfsehvePMrC8jw3rVnHB4FpWrxyY7+ZJlRGZOd9tqLSImPQB+nlKkmZyzY5bufDy6xgZG2d0/OC/G309QX9vD1s2rees04+fxxZKC0NETHqdmXFIGcNXawyzkqTZ2L13mHMvGWLfyNiUZVb093LVRYP20GrJaybMOmZWkqQuunRoJyNj49OWGRkbZ+vQri61SKq2tvTMRsRK4GHAg4DjgCOBO4C9wP8AX8nMm1uuaAGyZ1aSNBtnvPhq7tg/OmO5I5b38c2XntOFFkkLVzM9s3O+ASwieoDzgD8AfpUZenkj4qvAZcDbM/PAXOuVJKnKhpsIsgDDB5orJy11cxpmEBEbgRuAdwFnAb1AzLD9CvAmYGdEPLXllkuSVEEDy5vrRxpY5oRDUjNmFWYjYiAiPgB8CBgA/hV4LkWgvR9wLHA4RbhdARwD/BLwGODZwOXAcuADEbE1Inrb9D4kSaqEDetW0ddzyF9KJ+nrCTauO6lLLZKqrekxsxFxInBV+fIlwLacwwDRiOgDngm8FPgG8OQqDztwzKwkaTaczUBqXttmM4iIo4F/Bz4BPCQzr5xLkC0bMZqZb6e4WewARe+uJElLwuqVA2zZtJ4V/b2H9ND29QQr+nvZsmm9QVZqUlM9sxHxceDDmfmOtlZexO0twE2Z+ep2Xrtb7JmVJM3F7r3DbB3axZXbb2b4wCgDy/rYuO4kNg+uMchKpbYsmhARvwOcmJlvaGvrJtdxKfDqzPxOp+roFMOsJElSZ7QrzMZchxQ0qxt1dIphVpIkqTPaMma2GyGzqkFWkiRJ86ujk9iVY2IfQ7Eq2Fcy86ZO1idJkqSlpaUwGxFPqn2dmR+tOXYicDXwwHLXeES8ODNf0UqdkiRJ0oSm55lteHLEOJDAe4E3ZOZXyv0BfB54RFn02xSLJawBnpaZH2yl0QuJY2YlSZI6o23zzM7ghZm5aSLIlp5HEWQT2JyZD8zM+wIvB/6yDXVKkiRJLffM7gcGMnO0Zt8JwA7gSOADmXlezbFe4NbMXDn3Ji8s9sxKkiR1Rjd6Zn9QG2RLrwHuQbG61wvqGjAG1JeXJEmS5qTVMHtnRKyaeBERG4BnUAwveHX97AURcSpwzxbrlCRJkoDWp+b6OPCpiHgrcCJwUbn/axTjY+8WEYcD/9JifZIkSdLdWh0zew+KWQvOqNl9LfCEzPxJWWYt8BTgucB9KNZI6J1zpQuMY2YlSZI6o5kxsy31zGbmzyPiIcBGimm3vg18rG5Fr98uH7e0UpckSZJUr6We2TlVGHFOZl7d1Uo7yJ5ZSZKkzmimZ3Y+wuztmXlMVyvtIMOsJElSZ3R8mEFdZfcC7g2sAA6pCOgHzqaYtkuSJElqWcthNiL+hGIWg9Utt0aSJEmahZbCbES8EHjpxMsmT/Pv8JIkSWqLVqfm+j5wEvBd4J+B7wC/mKL4ERQzGzzDqbkkSZI0k47fABYRdwDLgTWZ+YMmyi8Dfp6Zh8250gXGMCtJktQZ3bgB7NvAcc0E2bIBByLiUS3WKUmSJAHQ0+L5lwFHR31snt49W6xTkiRJAloPs28Brgee2kzhMvS+v8U6JUmSJKD15WzHIuIpwAcj4mfAjmmKHwU8HTiylTolSZKkCe1YNOE+wD7gqjZcS5IkSWpaq/PMPgV4H9CL88xKkiSpy1qdmutbwP2AnwDvYfp5Zg8DHoHzzEqSJKkJ3Zhn9k6K3t3TMvOmJsoHcFtmHjPnShcYw6wkSVJndGOe2ZuAFc0E2bIBGREXtlinJEmSBLQ+Ndf7gRMjYmAW53ypxTolSZIkoPUw+1qK6bjOm8U5X2yxTkmSJAlofZ7ZOyPibOADEXEDxbCDqfQAjwFOaKVOSZIkaUKrN4DdCKyd7XnOZiBJkqSZNHMDWKvDDN5NMb/sbDZJkiSpLVrtmT0F+C7wIeDTwP5pig8ATwDOsWdWkiRJM+n4PLNlJZ8BnpSZw02UPQzYm5mzmf1gQTPMSpIkdUY3hhkAPB8Ya6ZgZt4F/Fkb6pQkSZJm7pmNiCMzc6olatvTiKLHdn9WsFvTnllJkqTOaFfP7MMj4p/a1ah6EbEM+CDwS52qQ5IkSYvTjGE2Mz8F9EXEP0V9PG5RRBwJfBT4Ymbe0M5rS5IkafFrdszs84AHAx+PiOPaUXFErKNY2va2zHxFO64pSZKkpaWpMJuZB4AnA8cD34qI50fEEXOpMCIeEBGXAl8Gvgk8cy7XkSRJkmY1NVdEDFAslPAk4C7gs8C1wLeBPcBeirlmx4DlFHPLngispujZ/VXgtPL4yzPzZW16H/PGG8AkSZI6o2PzzEbE+cArgROAZi8wUfl/AM/PzG/MuuIFyDArSQvH7r3DXDq0k23b9zC8f5SB5X1sWLeKCwbXsnrlopniXFoyOrpoQkQsB34fOA94FNMPWbgV+AiwNTO/MqcKFyjDrCQtDNfsuJULL7+OkbFxRscPfhf39QT9vT1s2bSes04/fh5bKGm2urICWFnRURTDCE4DjgaWAb8AfgT8N3BjFeeQbYZhVpLm3+69w5x7yRD7RqZew2dFfy9XXTRoD61UIc2E2b52VJSZPwM+V26SJHXVpUM7GRkbn7bMyNg4W4d28XcbzuhSqyR1QzuWs5UkaV5t275n0tCCRkbHkyu339ylFknqFsOsJKnyhvePNlfuQHPlJFWHYVaSVHkDy5sbNTewrC2j6yQtIIZZSVLlbVi3ir6e6Vdc7+sJNq47qUstktQthllJUuVdMLiW/t7p/0nr7+1h8+CaLrVIUrcYZiVJlbd65QBbNq1nRX/vIT20fT3Biv5etmxa77Rc0iLUlnlmlzLnmZWkhWP33mG2Du3iyu03M3xglIFlfWxcdxKbB9cYZKUK6tqiCUuZYVaSJKkzmgmzbR1mEBE9da8fFhEXRsSKdtYjSZIkQRvCbEQcHhEviYhdwA9qj2Xml4EEvhURG1utS5IkSarV0jCDiOgHPgM8CgjgJ5l5fINyvwl8FPiLzHzTnCtcgBxmIEmS1BndGGbwXODRFEF2BGi4MHZmfgp4C/CPEbGuxTolSZIkoPUw+3vA9cATgaOA26cp+z6gD/jzFuuUJEmSgCJctuI04CGZeSMc+if3Oj8sHx/bYp2SJEkS0HrP7C0TQbYJv1Q+3rPFOiVJkiSg9TB7a9SPzJ3a88vH21qsU5IkSQJaD7MfA/5ougIR0R8RbwIeTzFN1+darFOSJEkCWh8z+wbgqxFxCnAZQNlTewRwMsX42OcBp5blx4HXtFinJEmSBLRhOduIOBn4OPDA6YpRTN31x5n5Ly1VuMA4z6wkSVJndGU528z8HvBQ4GLgBorgWrvdBXwQOHOxBVlJkiTNr5Z7Zg+5YMRxwH2A5RTzzn4nM0cj4vTM3NHWyhYAe2YlSZI6o+M9sxHxj/X7MvPHmXldZn4pM6/PzNHy0DkR8bZW6pMkSZJqtdQzGxE3ZOZpTZYNYA/w+sxcNDeB2TMrSZLUGV0ZMzsLJ1AsefusLtYpSZKkRWxWU3NFxHOA9TW7jo+Id8xwWg/Fql+PBg4D7jGrFkqSJElTmNUwg4g4DHgjsJliAYRZ1VU+bs3MaRdaqBKHGUiSJHVGM8MM5jRmNiI2A1soAu2eJk65syz3UeAtmTky60oXKMOspMVs995hLh3aybbtexjeP8rA8j42rFvFBYNrWb1yYL6bJ2mR61iYLS/+f4AXNnsD2GJlmJW0WF2z41YuvPw6RsbGGR0/+N3W1xP09/awZdN6zjr9+HlsoaTFrqNhtqzgqZn5oSbLHgscm5nfmXOFC5BhVtJitHvvMOdeMsS+kbEpy6zo7+WqiwbtoZXUMR2fzaDZIFvaD3wxIgZbqVOS1HmXDu1kZGx82jIjY+NsHdrVpRZJUmNdmZorInqB+1PMZvD6btQpSZq7bdv3TBpa0MjoeHLl9pu71CJJamxWU3M1EhGPA14MPAA4nIOzFkzl9FbrlCR11vD+0ZkLAcMHmisnSZ3SUpiNiMcAH5nldS5rpU5JUucNLO/jjiYC7cCylvtEJKklrX4L/RUwDLwFuBEYAy4CLqkrdyrwdOD3MvPLLdYpSeqwDetW8b5rvz/tUIO+nmDjupO62CpJOlSrYfZM4Dcy82sTOyLifsB/ZeaO2oIR8RXgVRHxa+kt/5K0oF0wuJYPfe1mRsenns2gv7eHzYNrutgqSTpUqzeA/aI2yJa2UvTOTpKZHwP+F/CsFuuUJHXY6pUDbNm0nhX9vfT1TL4Voq8nWNHfy5ZN652WS9K8a3We2a8Dv5KZ++v2f4RiQYVv1O3/IfDDzFw/50oXGOeZlbSY7d47zNahXVy5/WaGD4wysKyPjetOYvPgGoOspI7rxqIJ7wHuAP4VWAl8IjNHyhvD3gn8bmb+V1n2/wJvBu7MzCPmXOkCY5iVJEnqjG6E2UcBQ8DERV6XmReXxz4OPA64tTx2PMW0Xbszc9EMsjLMSpIkdUY3VgD7AvByipAaQO08Lr8P3AScUG4Tlb+jlTolSZKkCS31zN59kWIGg/sAn8nM8Zr9xwIvAn4NuBP4EPCPtWWqzp5ZSZKkzuj4MAMZZiVJkjql48MM5iIizul2nZIkSVqcut4zGxG3Z+YxXa20g+yZlSRJ6oxmembbtqh2RNwLuDewgoM3e9XqB84G7tGuOiVJkrS0tRxmI+JPKFb8Wt1yayRJkqRZaCnMRsQLgZdOvGzyNP8OL0mSpLZoddGE7wMnAd8F/hn4DvCLKYofAfw28IzM7J1zpQuMY2YlSZI6oxsrgN0BLAfWZOYPmii/DPh5Zh4250oXGMOsJElSZ3TjBrBvA8c1E2TLBhwol8CVJEmSWtbqPLOXAUdHfWye3j1brFOSJEkCWg+zbwGuB57aTOEy9L6/xTolSZIkoMVhBpk5FhFPAT4YET8DdkxT/Cjg6cCRrdQpSZIkTWjHogn3AfYBV7XhWpIkSVLTWp1n9inA+4BenGdWkpqye+8wlw7tZNv2PQzvH2VgeR8b1q3igsG1rF45MN/Nk6RKaXVqrm8B9wN+AryH6eeZPQx4BM4zK2kJu2bHrVx4+XWMjI0zOn7w+6KvJ+jv7WHLpvWcdfrx89hCSVo4ujHP7J0UvbunZeZNTZQP4LbMPGbOlS4whllJzdq9d5hzLxli38jYlGVW9Pdy1UWD9tBKEs2F2VZnM7gJuLmZIFs2IIELW6xTkirp0qGdjIyNT1tmZGycrUO7utQiSaq+VsPs+4ETI2I2XQhfarFOSaqkbdv3TBpa0MjoeHLl9pu71CJJqr5Ww+xrKabjOm8W53yxxTolqZKG9482V+5Ac+UkSa3PM3tnRJwNfCAibqAYdjCVHuAxwAmt1ClJVTWwvI87mgi0A8vaMWuiJC0NrU7NdSOwtnx5TevNkaTFa8O6Vbzv2u9PO9SgryfYuO6kLrZKkqqt1WEG76aYX3Y2myQtSRcMrqW/d/qv3f7eHjYPrulSiySp+lqdmusU4LvAh4BPA/unKT4APAE4x3lmJS1VzjMrSc3r+DyzZSWfAZ6UmcNNlD0M2JuZi2YCRcOspNnavXeYrUO7uHL7zQwfGGVgWR8b153E5sE1zi8rSTW6FWYfBNyQmXc1Wf6PM/MtLVW6gBhmJUmSOqOZMNvyLbOZ+fVZnnJUq3VKkiRJ0Iae2VlV5jADSZIkNaktPbMRcRTwa8B/ZuZtNfvvBZw9i/YcSXED2GGzOEeSJEma0ow9sxHxVWAdsD0zH1qz/wjgFmYXTgNIZzOQJEnSTJrpmW1mntlVFCF00izemXkH8AmcY1aSJEnzpJkbwDYAzwDe3+DY5cDDyuPfB8anuEZQDDPYCLx41q2UJEmSGmh10YR+4F2Zed4szrktM4+dc6ULjMMMJEmSOqNdwwymlJkjwKuabMzp5dMXtlKnJEmSNKGlMBsR/5iZ/91k8XMi4m2ZuaWVOiVJkqQJrQ4zuCEzT2uybAB7gNdn5mvmXOkC4zADSZKkzuj4MINZOoFi9a9ndbFOSZIkLWKzWs42Ip4DrK/ZdXxEvGOG03qAewKPppiT9h6zaqEkSZI0hVkNMyiXo30jsBmY7d/TJ7qFt2bmH83y3AXLYQaSJEmd0cwwgzmNmY2IzcAWikC7p4lT7izLfRR4SzkLwqJgmJUkSeqMZsLsrIYZ1Fxoa0QcAF7Y7A1gkiRJUrvNKcwCZOa7ImK4nY2RJEmSZqOlqbnkMANJkqRO6dgwg1k0IIDHAMcBX8nMmzpZnyRJkpaWlsJsRDyp9nVmfrTm2InA1cADy13jEfHizHxFK3VKkiRJE1pdAWycYkaD9wJvyMyvlPsD+DzwiLLot4HlwBrgaZn5wVYavZA4zECSJKkzurUC2Aszc9NEkC09jyLIJrA5Mx+YmfcFXg78ZRvqlCRJklrumd0PDGTmaM2+E4AdwJHABzLzvJpjvcCtmbly7k1eWOyZlSRJ6oxu3AD2g9ogW3oNxZK1+4EX1DVgLCLqy0tSW+zeO8ylQzvZtn0Pw/tHGVjex4Z1q7hgcC2rVw7Md/MkSR3Qas/sN4BzMnNP+XoD8GGK4QV/l5kvqSt/KnBDZvbOudIFxp5ZaWG4ZsetXHj5dYyMjTM6fvD/w76eoL+3hy2b1nPW6cfPYwslSbPVseVsayp4JfAk4K3AicBFFDd6fRV4ZN3wg8OBq4BHGWYltdPuvcOce8kQ+0bGpiyzor+Xqy4atIdWkiqkGzeAvRIYAy4BLqYIstcCj58IshGxNiL+nGJGg0e3WJ8kHeLSoZ2MjI1PW2ZkbJytQ7u61CJJUre0vAJYRPQDGymm3fo28LGsuWhEXFx/Tma+uqVKFxB7ZqX5d8aLr+aO/TMPxz9ieR/ffOk5XWiRJKkdurICWGaOAB+Y5viiCa6SFqbhJoIswPAB7z+VpMWmHfPM3i0ieupePywiLoyIFe2sR5JqDSxv7vfygWUdXcFbkjQPWg6zEXF4RLwkInYBP6g9lplfppjZ4FsRsbHVuiSpkQ3rVtHXc8hfnibp6wk2rjupSy2SJHVLS2G2HC97FfAiYDUNhi1k5puBPwLeExHPaaU+SWrkgsG19PdO/3XW39vD5sE1XWqRJKlbWu2ZfS7FDAUBjAANbyfOzE8BbwH+MSLWtVinJE2yeuUAWzatZ0V/7yE9tH09wYr+XrZsWu+0XJK0CLU6z+xXgcOBvwA+A2zPzPtPUfZhwJeA92bm0+dc6QLjbAbSwrF77zBbh3Zx5fabGT4wysCyPjauO4nNg2sMspJUQd1YNOHnwEMy88by9bcy8wFTlD0ZuAn4YWYumoFrhllJkqTO6MaiCbdMBNkm/FL5eM8W65QkSZKA1sPsrVEfmaf2/PLxthbrlCRJkoDWw+zHKGYqmFJE9EfEm4DHU0zT9bkW65QkSZKA1lcAewPw1Yg4BbgMoOypPQI4GXgs8Dzg1LL8OPCaFuuUJEmSgBZvAIO7b+z6OPDA6YpRTN31x5n5Ly1VuMB4A5gkSVJndOMGMDLze8BDgYuBGyiCa+12F/BB4MzFFmQlSZI0v1rumT3kghHHAfcBlgO3A9/JzNG2VrKA2DMrSZLUGR2fZ1aGWUmSpE7pyjADSZIkab4YZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZ8xpmI+Ke81m/JEmSqm2+e2afOs/1S5IkqcIiM1u/SMQvA/eY5WmHA6/IzPUtN2AeRcSkD7Adn6ckSZIgIia9zsyoL9PXpro2Ai9s07UkSZKkprSrZ/YewHeATwA3NXnaCcCmzJxtj+6CYs+sJElSZ3StZzYzfx4Rfw+8OzN/0ux5EfGjdtQvSZKkpamdN4BtAe4zy3O2tbF+SZIkLTFtGWawlDnMQJIkqTOaGWYw31NzSZIkSXPW1JjZiHgNMFCzfSczX9DJhkmSJEkzaWqYQUSMAwl8FHg78J+Z+YsOt60SHGYgSZLUGe2ezeBlmfnSVhslSZIktctsxsz+U8dasUBExLERcVlE3FJubyvn0JUkSdIC1GyY/Ulm3taOCiPiue24TrtF0Y/9duB/gOcAVwEXAJfOZ7skSZI0tWbHzH43M09tS4URP8zME9txrXaKiEHg5Mx8d82+bcATgSMz884pznPMrCRJUge0c2qusTY16H7A8e24Voe8t+71pyk+oyPmoS2SJEmaQbM3gJ0QEe9ooZ4AjgV+tYVrHHrRiIcDLwFenpmfn6LMw4AXcTBE7wP+PjP/vbZcZg41OP0wYFdm3tq2RkuSJKltmg2zRwLPbEN9QTHFV2sXiXgE8GLgnHLXq6Yo90Tgw8ALMvN15b5NwCcj4v9m5tYZqnoM8PpW2ytJkqTOmM1sBtGGrWURcW9gHHgG0HAca1luDcWwga9NBFmAzLycIuBuKYc9THX+GcBRwJZ2tFuSJEnt12zP7K3AxS3U0wscBzwVeEgL1yEzfwD8ACAifgysnqLoX1KsVnZZg2P/AvwW8FLgafUHI2I5xfCF38nMtowXliRJUvs1O5vBDZl5WsuVRRwD3JKZy1q9Vnm9myjC7FmZ+dma/QHsBY4BzsjM/6k77yjgdmA/cHz9amYRcQnwtsz8VhNtcDYDSZKkDmjnbAa97WhQZt4O/Kgd15rB6RRBNoEbG7TjZ8AtFDd4TeopjogXAlfUBtmIeGBHWytJkqQ5aXaYwTFtrPPsNl5rKqeUj7dn5oEpyvwIuBdwP+CzABHxx8CpwPUR8VtluROBk4G/6FRjJUmSNDfNhtmjI+LkzPxeqxVm5vWtXqMJE+F73zRlJo4dDRARjwfeRNELfX5d2d9sdIGI+KM5t1CSJEktm81sBq+KiGbD70Ix3QDWiRu7AiAz/y0z+zIzGmyfbnjxzLe1u8GSJElq3mzC7O8C34mIV0TEIzvVoDa5rXxcMU2ZiWM/7WxTJEmS1CnN9rT+b4olXSe2k4EvdqpRbTBx09cxEdGXmaMNypxQPt7QpTZJkiSpzZoKs5n5yU43pJ0yc2dE/JDi5q1TgR21xyNioDw2Alzb/RZKkiSpHWYzzKBqPlw+PrrBsUdR3Oh1df0cs5IkSaqOqofZ/mmOvYFiUYTzGxz7fYqbw17bgTZJkiSpSyobZsuFDO5Vvnxo/fHMvBF4HvDIiHh+zXlPo1jC9hWZ+blutFWSJEmd0dRytgtJRJwMbAPOYHLP7A7gksx8S135XwcuBo6imI5rHHhDZl7Rpva4nK0kSVIHNLOcbeXC7EJjmNVitnvvMJcO7WTb9j0M7x9lYHkfG9at4oLBtaxeOTDfzZMkLXKG2S4wzGqxumbHrVx4+XWMjI0zOn7w57qvJ+jv7WHLpvWcdfrx89hCSdJiZ5jtAsOsFqPde4c595Ih9o2MTVlmRX8vV100aA+tJKljmgmzlb0BTFLnXDq0k5Gx8WnLjIyNs3VoV5daJElSY4ZZSYfYtn3PpKEFjYyOJ1duv7lLLZIkqTHDrKRDDO9vtAJ0g3IHmisnSVKnGGYlHWJgeVMrXTOwrLlykiR1imFW0iE2rFtFX88hY+wn6esJNq47qUstkiSpMcOspENcMLiW/t7pvx76e3vYPLimSy2SJKkxw6ykQ6xeOcCWTetZ0d97SA9tX0+wor+XLZvWOy2XJGneOc9si5xnVovZ7r3DbB3axZXbb2b4wCgDy/rYuO4kNg+uMchKkjrORRO6wDArSZLUGS6aIEmSpEXNMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsvrmuwFaeHbvHebSoZ1s276H4f2jDCzvY8O6VVwwuJbVKwfmu3mSJEl3i8yc7zZUWkRM+gCr/nles+NWLrz8OkbGxhkdP/he+nqC/t4etmxaz1mnHz+PLZQkSUtFREx6nZlxSJmqh6/5tpjC7O69w5x7yRD7RsamLLOiv5erLhq0h1aSJHVcM2HWMbO626VDOxkZG5+2zMjYOFuHdnWpRZIkSdMzzOpu27bvmTS0oJHR8eTK7Td3qUWSJEnT8wawLqjKDVXD+0ebK3eguXKSJEmdZs9sh12z41bOvWSI9137fe7YP0oCd+wf5X3Xfp9zLxnimh23zncT7zawvLnfbQaW+TuQJElaGAyzHbR77zAXXn4d+0bGDvnz/eh4sm9kjAsvv47de4fnqYWTbVi3ir6eQ8ZVT9LXE2xcd1KXWiRJkjQ9w2wHVe2GqgsG19LfO/2PRH9vD5sH13SpRZIkSdMzzHZQ1W6oWr1ygC2b1rOiv/eQHtq+nmBFfy9bNq1fUON8JUnS0ubgxw6q4g1VZ51+PFddNMjWoV1cuf1mhg+MMrCsj43rTmLz4BqDbBtU5YZASZKqwEUTWjTdoglnvPhq7mgi0B6xvI9vvvSc9jduialCSHSFNUmSmueiCfPMG6q6pwqzRlTthkBJkqrAMNtB3lDVHVUJiVW7IVCSpCowzHaQN1R1R1VCYtVuCJQkqQoMsx02cUPVeWeezBHL+4goxsied+bJXHXRoOMj26AqIbGKNwRKkrTQOZtBF6xeOcDfbTiDv9twxnw3ZVGqSkgcWN7X1A2BrrAmSVLz7JlV5VVlGV5vCJQkqf0Ms6q8qoREbwiUJKn9DLOqvKqERG8IlCSp/Vw0oUXTLZqg7qnSYgS79w67wpokSU1oZtEEw2yLDLMLhyFRkqTFxTDbBYZZSZKkznA5W0mSJC1qhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmUZZiVJklRZhllJkiRVlmFWkiRJlWWYlSRJUmX1zXcDFpuImO8mSJIkLRn2zEqSJKmyDLOSJEmqLMOsJEmSKisyc77bsChExBMz82Pz3Y52WGjvpdvt6VR97bxuO67VyjXmcm5EfDUzHzqX+jS1hfb/aysW2nvpZns6WZffPX73dMJC+v/VMCupK/wHRdJ88Ltn8XOYgaRuedt8N0DSkuR3zyJnz6wkSZIqy55ZSZIkVZZhVtKCERHHRsRlEXFLub0tIu4x3+2StLhFRF9E/H1E3BwRt0fEOyNiYL7bpea4ApikBSGK5fPeDnwR+ATwBOAC4CjgafPYNEmL318D3wbWAb8CXAH8EPir+WyUmuOYWUkLQkQMAidn5rtr9m0DnggcmZl3zlfbJC1eZQ/sWZn58Zp9HwaWZeYT5q9lapbDDCQtJO+te/1piu+pI+ahLZKWgMwcrg2ypaOBf5uH5mgODLOS5iwiHh4RV0XEo6cp87CI+HhEXFtu/xkRZ9eXy8yhzByv230YsCszb2132yVVVzu/exqc9zjg65m5pa2NVscYZiXNWkQ8IiKuAr4EnMMU4+8j4onA54HPZuaZmXkmcCnwyYjY3ERVjwFe36ZmS6q4Tn73RMTqiHg78DHgDyLCIQYV4ZhZSbMSEfcGTgJ2AjcBh1OMN/tsXbk1wDeAb2bmw+uOXQE8GXhQZl4/RT1nAFvKa4+1+W1IqphufPdExBHAo4E3l9dfnZl3tf3NqK3smZU0K5n5g8z8cmb+GPjxNEX/EhgALmtw7F+AfuCljU6MiOXAS4DfMchKgu5892TmHZl5FXA+cDxweittVncYZiW1XTnN1sR0WkMNinwBSOBJEXFkg+OvBv42M3/UoSZKWoTa8N0z4drycaSNzVOHGGYldcLpwDEU/2jcWH8wM38G3EJxg9dDao9FxAuBKzLzWzX7HtjR1kpaLOb83VPnRGBPo2to4THMSuqEU8rH2zPzwBRlJnpd7zexIyL+GDgVODEifqvcnkvxJz9Jmskp5WPT3z3lyoOvi4j7l68D+Bvg+Zlpz2wFuAKYpE44pnzcN02ZiWNHA0TE44E3Ab0cGl5/s41tk7R4zfq7h2IM7dnAsyLiQ8Au4LLMbDRMQQuQYVZSJ003XcrEjV0BkJn/ht9JktpjNt89twAP6niL1DEOM5DUCbeVjyumKTNx7KedbYqkJcTvniXIMCupEyZumjgmIqbqbT2hfLyhC+2RtDT43bMEGWYltV1m7gR+SPEdc2r98YgYoLhbeISDU+BIUkv87lmaDLOSOuXD5WOjtdMfRXGj19WZ+YvuNUnSEuB3zxJjmJXUiv5pjr0B2E/jabV+n+IGjdd2oE2SFj+/e3Q3w6ykOSkXMrhX+fKh9ccz80bgecAjI+L5Nec9jWKFnldk5ue60VZJi4ffPaoXmdPNXiFJk0XEycA24Awm947sAC7JzLfUlf914GLgKIopccaBN2TmFV1psKRFwe8eTcUwK0mSpMpymIEkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IWpYh4ZER8KCL+JyLuiogbI+IFERHz3TYtDBFxdkQcNd/tqBURPRHxtPluh1QlhllJLYmIp0fEJyNiOCKywTYeET+PiF0R8ZGIeF5ErOxwm34b+DTwt8AZwBuB+wKvAJ7ZybqXooh4fN1/85+W/72/ExG31Oz/eblvZ0T8uO6c13Wxvcsj4i3Ak4Gfd6veZmTmOHBiRHwiIo6Z7/ZIVWCYldSSzHx3Zj4OeELdoWcDpwEPBp4BfAz4NeAS4HsRcVEn2hMRxwJbgS9k5v9kZgIvoAi3o8DNnah3iTuifPwAsDYzj87MNZl5X+DimnIfzsz7ZubazDwOOA54WXlsoBsNLX8+Pg2MZ+azy5+PBSUzLwE+DAxFxEnz3Bxpweub7wZIWjS+XPf6rZk5Vj7/BvCRiHgtcA1wKvD6iBjIzL9vczv+ALgH8MOJHZk5FhFnA0dk5i/aXJ+KMPt94BmZeaDZkzLzJ8CLI+LBdCHMRsQRwNXAXuC5na6vFZn59oi4L/DJiHiUP7fS1OyZldQWmXln3euxBmW+D1xYs+tvIuIebW7KY8vH8bq600DQMUcA75lNkK3zdrrTM3s5sBY4v9HP5wL0t+Xjv8xrK6QFzjArqds+A+wrn68AHt7m69+nzdfTzH4CfLyF8/8T+E6b2tJQRJxPMUb2lZn5o07W1S6ZOQK8BHhqRDx1npsjLViGWUldVfaI/bRm1z3bXEVXxl7qoMx8T2Z+voXzf56ZF89ccm4i4jDglcB+4G2dqqdDtgG3AK+NCIcGSg0YZiV1VUT0A7WzGfx4mrKHl9NpfbG8C/4XEfG1iPiziFhWU+7c8vh3gNXl7qdM7Cu3wblcu6b8AyPiHyLijeXrx0XENyLijoh4+VyvHYXBiNgaEZ8s990rIt4SET8qZ4n4eEScMsPnenZEfDQiri9nErg+Iv4pIta0+vkuAucD9wI+m5lTzl4QEWsi4iXlzxERMRARL46Ib0fEvvLxqTXl+yLi2RHx1fK/0w8i4kURh07/FhFHRcQrI+Kb5WwOB2pmctgwVZvK2Q2uBtYA5835E5AWs8x0c3Nza8sG5MQ2TZkn1pS7HRiYotzJwLeAZwG95b7TgW+X536e4oau+vNuKo9fNk0bmr428H+B/6pp8/vK97CvZt/wHK99bvl64jr/BaynuHntRxTTRk0cux5Y1uC99APvKut8ZM3+l0y0DfiNdn2+c/iZOL/mPUz536TDP5efK+t/2RTHHwz8B8U464m23gv4OnAA2E0xE0aWj48AVlHc9Phz4HvAWM25F9Vdf1l5rW8D96nZ9zdl+Q0ztP85Zblr5uPzc3Nb6Nu8N8DNzW3xbMwQZil6l3bWlDt/inLLKWZAeE2DY7Vh+JBwwgxhdrbXpri56QiKHuSJwPkR4NgyjN4EXDHXdgMBfLXcvxv42kT4pPjr2ZtrztvY4LrvBW4FTqjbf2xNwPp6uz7fOfxMnM8cwyzFrBQvA9a3UP/RNZ/DeVOUORw4Eriipq1DFL/IHFmWWVvzM/Af5c/B0zj4i8DJFON+E7ip7vq/Q4OQWx57DzOH2ceW548Bx7X638TNbbFtDjOQ1FERcVhEPKycFP/rFIF2N/CUzLxsitOeS7HYQaO7uD8FjJTP57IAwqyunZl3ZOYdwI5y/wOBzZl5W2ZelZmnZOZvz7XdmTnR6wpFeHtSZn66PDbOwd47gIfVXjAiNgK/C7w2M2+pPZaZt1GEboBJM03MpZ3dFBHLynmIvwu8iOJzmasHc3BI3Z5GBTLzzixmuvh0ze6/zcy3lvvJzJ0UwRPgLOAlmfn+LGdFyMzvAf9cHl8dEatqrrW2fDyxQfVvaOI9TEwz10Pdz4Ak55mV1CERsYOit6v2H/DXA5+k+HPp6DSnby4fr2ww/BCKG8h6gMMiom+Ga7Xr2hOP/y8zpxrn2+q1f5aZkxZ1yMzbIuInFAsM1N8s96fl41QzCfweMEjRi9iOdnbL/6IIjr9M64H6tJrne2cou7/m+a4Gx2tnXLh+huP35mB4/nb5eFFE/FdmXjlRKDPr52du5Naa5w+itZkjpEXHMCupIzLz9IhYQTH2cn25+4TM/NR050XE8RRjNwHOaGeQatO1G85P2sl2c7Bn9e7v7HJ+3keULxsFLzLzLoqe1m61sy0y82sAEXFTGy53dM3z/VMVatJM8xTXHl9R8/xjwLXAmcCHI+Jfgb/M5qcIu6vm+XFNniMtGQ4zkNQxmbkPeArFPKQAvxcRfz3DabXzxLZ7mq2qXruRk4He8vlslmTtdjvnW+2sDN1cKOHuLu9yuMgTKMZDQ7G8846IeH5ENPPvcG0IP7J9TZQWB8OspI7KzN0U4zongsTLp5uKiOLmpAknt7k5Vb12I0fVPD9pFud1u53zrba3dPmUpTqsHJrySODvKGZIuAfwj8Dn68bXNlIbyO/oTAul6jLMSuq4zPwM8FflywAuj4gHTVH89prnj53p2hExmxXEqnrtmeo7a47nPXamwm1o53yr/VP+vPZEZ+aBzPxb4P7AB8rdjwD+PSJ6pz6Tw2qezzTuV1pyDLOSuiIzXwe8v3w5AHysHL9Z7zscXO72eRExZW9aRFwIPHQWzajqtRu5kWIOWYA/mS4MRcRzI+J+89TO+fbfNc8bzSbQcRHxVxFx34nXmbkzM58GXFDueiDwmGkuUXvj3/90oIlSpRlmJbXFDD1LE/6AYnouKP7E/eH6laayWI/+E+XLUylmQGhU328CF3Po9FJR99jOa0+pk9eepr4Ply8fBPzDFPU9CRjMzOvno50cHNcLDf6bdMGNHJwNYPU81D9hY/2OzNzKwZkOpruxq3YYwlfa2ShpMTDMSmqXSdNGRcRR9QUy806Kf9Qn/tT9KOBtDa719xyc6/RZEfGJiPiNiFgdEQ+PiNdTTE/0Z5k5XHfuRL1HT9HOuV574u70Q95XG64901jOI8rH+l8YXsbB3tnnRcR/RMRvRcSDI+LXIuKfgbcCF7WpnXNRG9KObfFas1befDUx3+6DZyheOwyh0b+PtX/ub/RzcETN8/66Y38SEUdwqOUUK49NF1LPKB+/lpnfn6actDTN96oNbm5u1d8o/uGfmNx/Yns2EFOUP5fJy3++hbqlUyl6ccfqrjmxjQLPm+K6E2VuA9ZOUf+srk0xUf2d5fEDwJnTfBZzafd2Di49e3jdsZM5uMzqlxqc+3gmL61bu+0FHt6uds7h5+IYiimpJq77M+D+szj/JeV5j22xHWeW19kxTZnDgH+raev5dccDuKzm+KuBnprjy+qOv2bi559ivPjEqmL3Lff1AS8t979ohva/qyz3nE78/+vmVvVt3hvg5uZW7Y1i4v6fThGKfgZsneK8v64rexfwr3VlfoViidFbKHoSfwi8D3hoXbknU/wpuVEbfkiDZUxnce2vTHHdHwFnTfHemr32r1IsIlF73a9NhBbgD4Eb6o5/HHhk3XVOKwPPHoqwvRv4J+DEGf7bNdXOOfxM3B/4PkUobvTZ3UITYZk2hdnyWp8pr3VGg2PP4uAvK/X/jddSLD7R6Gf858DjKMYV75/i5/9xHAyzE9uPKf468VXgaTO0u59iarsfAofN9//vbm4LcZv4rVGSpAUlIl4CvJjil4bPtnitB1H8ovCuzPzD1lvXHRHxh8BWitD7gZnKS0uRY2YlSQvVxGwXh7d6ocz8OvBy4JkR8ZBWr9cNEXEsxbjoywyy0tTsmZUkLSgR8WBgA/AXFDdl/TfFjWwfysxbpzl1pusGxfRwZwCPyMyftd7azihXBruS4sbD/53FLBSSGjDMSpKWjHIquHdRzKzwxMzcP8MpXVeG7jcDK4FnZOZd89wkaUFzmIEkacnIzAPAecB/AldGRMtDGNqp7JG9lOImvt8xyEozs2dWkrQklaui3ZiZY/PdlloRcVpm3jDf7ZCqwjArSZKkynKYgSRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsv4/188lvJKQYMIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_id = plot_single_scatter(x=temp_corrected_ref_values,\n",
    "                             y=dataset_estimate,\n",
    "                             y_std=dataset_std,\n",
    "                             title='Log-log axes',\n",
    "                             x_label='Reference T$_1$ (ms)',\n",
    "                             y_label=\"T$_1$ estimate (ms)\",\n",
    "                             file_prefix=str(index),\n",
    "                             folder_path=output_folder,\n",
    "                             fig_id=fig_id,\n",
    "                             y_type='log')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Htyn3KIoZrmplb6EYG/NvgadT/Ct+UVlmnUH5WXsWqY0btn2lbtuFwCbl+m2B71BcJa29VjtShLrNyjKvqm8fiiC0AXASsEHdOe4vy1zV4etSP0j9u8YoO67XZoxj188q9aVy3aMpZt+qzTx1eF2ZDzU5xlyKqU5XAH/Xw3vk9LrjP71NudfVlUuK0Hog8BTg74B/o7gJ7bQm+25Zt9+1bc5R/15ZSTE28L7lOQ6gmFZ2JXB4w34dfY4p/mC6uq7s3cAHKMbF3ZNiZryLKWbme0rDvgfU7ffRJsfetG77Lxu2TaeY6re2fRnFz5PnUUyM8UqKP6gupG6iFYrQ/ZO6/R6imK53PkU3ppdTBO5VwAvH87PCxaVxGXoFXFwm8wI8puGX6kXAo1uU3bL8JVT7hb0c2LDctinF1bTacR6mGH6p2XGexJopWWvnbDdb2EzWzO60BHhF7ZdU+QvsxvKX6s4N+81i7Vl9kiI4zejhddqK4l/OtePcDuzapvwzWDM1a7PlJuBJDfsEcHCT+kZdmeexZharWhvcSjE+5usppgOubbufItxuXddGD9RtX0IRmF5bd/wD67avpMNpPYHvleGgZTuO57XpsA67sGbq4lob3d34HCgG0l9elv0gZZCnGDrsQor+oC/q8txBMdD+PXXn/wZ1fyQ02ad+Frxmy7dYd2asmcDRDeUW0GR2PIqZxH7c5vgraPjjgy4+x2X5x5Xt1eocS2jyRwHw4boy32myvf4PxztpmG2P4mfRb9qc92Jg0ybH3YJiOt5W+z0EvKbb956Ly1jL0CswlCcNe1HME/2cNmWeAfwAuKxcLgZe0K/yLpN7obhC8wHgdy1+qNdPa1u76aKxzE/KY72aIvg0O86DwAF15/1hi3KrgZvHqPN+FKFpMUVQu4HiSsubgZkNZbcvfzE1O9cy4N+7eK3ew9oBsvF1ekqL/bai+BfxHylCwQMU/QzfT/lHQF3Zp5bHavUL9vV1ZQ+kmK3oIYog+1XKYE3xS/7ScttPG+tGMVvXn8rtlwD7l+sPogjEzc5/b6vnWHfc+cBnunhNO35tunxfv6F8fzxIMU1q06ujFDeAfZHiKuyDFH8QXUHRh3XMQN7keL9v8dqtAha22e/vgLMogveK8vFs6j4zdWVPZM00t83e082u4k6j+INuYdmOyyk+N18BntxQtuPPccN+G5Wv2+/K99BD5defALZo8rk8jTVX8mvLuZRXQyn61zZ+Fn4HHNZwrNnAuymu5C8t6/jL8vk2nfq6br93le+3Byi6nlwLHAfs1Ot7z8Wl3VL719CUEBHPpPiru3Z36D6Z+dMm5V5KMZXl+zPzM+W6QyhumHhzZp48nvKSJEnqjykTZsshd7YFrqe4SrA+TcJseQf57yj6s+3VsO27wMso/uK+ppfykiRJ6p8pM5pBZv45M3+VmXdS9BFq5T0UNymc0mTbVyn6VH10HOUlSZLUJ1MmzHaiHK7k4PLbhU2K1O7w/PuI2LDb8v2uryRJ0lQ3Y9gVGDG7sGbIkusaN2bmfRFxO8XNFXtS3LzTTfmfNpaJiKnRz0OSJE16mTmoWStb8srs2nYsH+/J1jPC3FY+7tpDeUmSJPWRYXZttfnnH25TprZtkx7KryUijuiibpIkSWpgmG2u3b/+V5WP9ZfRuy1f7JTpdH6SJEnjYJ/Ztd1dPs5pU6a27d4eyo9pqgyVJkmSqq+4F364vDK7ttpNXJtGRKugv2X5+MceykuSJKmPDLN1MvN64C8Ur8tjG7dHxFxga4qpAi/rtvzgai5JkjQ1GWbXdUb5+Jwm254NTAfOz8wHeiwvSZKkPpmqYXZmm22fB5YBhzbZ9gaKm70+PY7ykiRJ6pMpF2YjYjeKSQwAnta4PTOvA94BPCsi3lm338EUs319IjN/1mt5SZIk9U9MlbvnI2J74Cxgd9a+MnstcGxmfqmh/L7Ae4GNKYbXWg18PjO/2+L4XZWv22+tBpgq7SFJkqqvcTSDYcwANmXC7KgyzEqSpKoahTA75boZSJIkafIwzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMOsJEmSKsswK0mSpMoyzEqSJKmyDLOSJEmqLMPsgEXEdhGx27DrIUmSNBkZZpuIiAURkWMs32/YZ4eIWNFYDrgauGU4z0SSJGlymzHsCoyoI4AVwJ+B5Q3bZgE7Aec0rH8XcC+wrG5dAl/JzPsHU01JkqSpzTDbICJ2ALYAtsvM25tsfy3wVeCsunWbA68AHpeZ901QVSVJkqY8uxmsax5wcLMgW3oVcHFm3lW37u3AaQZZSZKkiRWZOew6VEZEbAzcARyVmV8s160P3AxsBlwLXAScDlyYHby4Zb/av7I9JElSVUTEWt9nZrQoOjBeme3OAoquGWfWrXs5sAkQwK7AW4ELgAsjYtsJrp8kSdKU4pXZLkTED4CNMvO5DesD2BZ4HsXNY7XtfwCenZn3tDmmV2YlSVIleWW2QiJiE+D5wPcat2Xhz5l5WmY+D3g18BDwROAjE1pRSZKkKcQw27kFwEzgjLEKZua3gYPLbw9tVS4ijuhHxSRJkqYquxl0KCJ+BGyamc/sYp9LgWcAm7XqamA3A0mSVFV2M6iIiNgU2I8mXQzGcEntEP2tkSRJksBJEzp1IEUXg9O73G8a8CDQ8gawVm5aspSTFl7PWYsWs3TZSubOnsGCedtw+Pyd2WHzud0eTpIkaVKym0EHIuI84FGZ+bQu9/s5cHNm/kObMut0M7jo2js48tQrWbFqNStXr9k8Y1owc/o0jj9kD/bZZYsun4UkSVJ/2c2gAiJiM+DvaNLFICKmR8SCiJjXZNt+wFOBD3dzvpuWLOXIU6/k4RWr1gqyACtXJw+vWMWRp17JTUuWdnNYSZKkSckwO7aX07qLwXMoJlC4MiK+GRFbAUTE3sBxwP6Z+aduTnbSwutZsWp12zIrVq3m5IU3dHNYSZKkSckwO7ZXAr/NzOuabPsl8EngRuAg4NqIOB/YB5ifmb/o9mRnLVq8zhXZRitXJ2cuurXbQ0uSJE063gA2hszcv822FcD7yqUvli5b2Vm55Z2VkyRJmsy8Mjti5s7u7O+LubP8O0SSJMkwO2IWzNuGGdPa3wg4Y1pw4LxtJ6hGkiRJo8swO2IOn78zM6e3b5aZ06dx2PydJqhGkiRJo8swO2J22Hwuxx+yB3NmTl/nCu2MacGcmdM5/pA9nDhBkiQJJ00YumaTJkAx3uzJC2/gzEW3snT5SubOmsGB87blsPk7GWQlSdJIGIVJEwyzQ9YqzEqSJI26UQizdjOQJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmJUmSVFmGWUmSJFWWYVaSJEmVZZiVJElSZRlmexAR20XEbsOuhyRJ0lRnmG0jInaIiBURkfULcDVwS0PZZ0TEDyLisnK5OCJeMJyaS5IkTQ2G2fbeBdwL3Fq3/Bn4j8y8v1YoIl4K/Bz4aWY+PTOfDpwEnBsRh014rSVJkqaIyMxh12EkRcTmwO+AJ2bmfW3K7VSWuyoz92rY9l3gZcCTM/OaFvuv1QC2hyRJqoqIWOv7zIwWRQfGK7OtvR04rV2QLb0HmAuc0mTbV4GZwEf7WzVJkiSBV2abioj1gZuBzYBrgYuA04ELs+4Fi+LPkSXApsDumfn7huNsDNwDLAO2yMwHmpzLK7OSJKmSvDI7ul4ObAIEsCvwVuAC4MKI2Lau3C4UQTaB6xoPUl7VvR1YD9hzsFWWJEmaegyzTWTmqRTdA7YDDgF+Vm7aG/hxRGxafr9j+XhPZi5vcbjbysdd+19TSZKkqc0w20IW/pyZp2Xm84BXAw8BTwQ+UharhdqH2xyqtm2TgVRUkiRpCjPMdigzvw0cXH57aOPmNruuKh/X6UMSEUeMv2aSJElTl2G2C5n5A+BXwCZlV4O7y01z2uxW23Zvk+Od2NcKSpIkTTGG2e5dUj4Ga2762jQiZrQov2X5+MeB1kqSJGkKMsx2bxrwIMVNX9cDfynXPbaxYETMBbYGVgCXTWQlJUmSpgLDbPf2BM6pG2/2jPLxOU3KPhuYDpzfbIxZSZIkjY9htkFETI+IBRExr8m2/YCnAh+uW/15ikkRDm1yuDdQ3Bz26f7XVJIkSYbZdT0HOBO4MiK+GRFbAUTE3sBxwP6Z+ada4cy8DngH8KyIeGdtfUQcTDH6wScy82dIkiSp75zOtkFEzAQ+ThFEt6UYJ/bScjkuM5e02G9f4L3AxhTDca0GPp+Z3x3jfE5nK0mSKmkUprM1zA6ZYVaSJFXVKIRZuxlIkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMDtgEbFdROw27HpIkiRNRobZFiJiZkR8ICKujohHIuLeiPhhRDyjRfkdImJFRGT9AlwN3DKxtZckSZoaZgy7AiPsDOAlwGJgBbAx8GLg+RGxIDN/1FD+XcC9wLK6dQl8JTPvH3x1JUmSph7DbBMR8WZgfWDHzLy5XLcfcAqwLXBiROyQmavKbZsDrwAel5n3DafWkiRJU4/dDJo7GDioFmQBMvMC4E3lt9sC9f1g3w6cZpCVJEmaWF6ZbRARjwZOz8x7m2y+gKIbwWxgell+feCfgM0i4gDgIuB04MLMzAmptCRJ0hQV5q3uRMSdwEbA5pn5YEQcQtH9YHpD0Z8Ch2TmrWMcb60GsD0kSVJVRMRa32dmtCg6MHYz6EJEbAg8CjgjMx8EyMxTgZnAdsAhwM/K4nsDP46ITYdQVUmSpCnBMNudA4FHgKPrV2bhz5l5WmY+D3g18BDwROAjE19NSZKkqcEw26GImAm8G/hAZv6xXdnM/DbFTWQAh7Y55hF9q6AkSdIUZJ/ZDkXER4BtM/PNXexzKfAMYLPMvKdFGfvMSpKkSrLPbEVExEHA7sCRXe56Se0Q/a2RJEmSwKG5xhQRtT6w/1CbJKEL04AHgaZXZSVJkjQ+XpltIyL2At4BvDYzVzRsmx4Rjx3jEHsC5zjerCRJ0mAYZluIiHnAByjGin2kYdt04DPAehGxoCzbuP9+wFOBD09AdSVJkqYkuxk0ERG7Af9DMbzWlY2dm4EtgKuBs4Azy32+BbwzM2+LiL2B44D9M/NPE1NrSZKkqcfRDBpExLbA5cBWYxR9PfBN4OMUw3BtCzwMXFoux2Xmkg7O52gGkiSpkkZhNAPD7JAZZiVJUlWNQpi1z6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqy3Fmp5iblizlpIXXc9aixSxdtpK5s2ewYN42HD5/Z3bYfO6wqydJktQVh+Yasokcmuuia+/gyFOvZMWq1axcveY8M6YFM6dP4/hD9mCfXbYY2PklSdLkMgpDcxlmh2yiwuxNS5bywmMX8vCKVS3LzJk5nfOOmu8VWkmS1JFRCLP2mZ0iTlp4PStWrW5bZsWq1Zy88IYJqpEkSdL49S3MRsSGEbFNRGzUr2Oqf85atHitrgXNrFydnLno1gmqkSRJ0vj1fANYRMwHDgKeBewOzK7bthL4A/Br4EzgfzJz5fiqqvFYuqyzl3/pcptJkiRVR1dhNiKmAa8H3gs8vra6SdGZwJOBJwFvBG6NiE8Dx2dm606bGpi5s2fwYAeBdu4sB7iQJEnV0XFyiYinAicDe5Sr7gJ+D/wFuAN4BFgGzALWAx4FbENx1fYxwLHAoRFxSGb+oT/VV6cWzNuGb112S9uuBjOmBQfO23YCayVJkjQ+HYXZiHgdcCJwDfA24NzMvLHTk0TETsAC4J+ASyLi5Zl5Yde1Vc8On78zp19xKytXt74wPnP6NA6bv9ME1kqSJGl8xhyaKyKOAj4A/FNmfmdcJ4uYDvw/4P3AyzLzp+M53mTgOLOSJKmqRmForrZhNiJeRRFkX5yZi/t20ohnA18DXpSZ1/XruFU0kWEWivFmT154A2cuupWly1cyd9YMDpy3LYfN38nxZSVJUldGOsxGxPbAacABmXlf308csTvwGeAlU/mmsIkOs5IkSf0y6mH2WcCN/bwi2+Qcfwvc2U3/28nGMCtJkqpqpMOsJoZhVpIkVdUohFmns5UkSVJl9WWE/IjYDvgHYDtgJXAj8LPMvLIfx5ckSZKaGfeV2Yh4AfAtigkUjgO+DNwCHB4RF0fEC8d7DkmSJKmZpn1my0kNzujoABEXAwdm5t1Ntm0CfAJ4MDPfM866Tkr2mZUkSVU1Cn1mW4XZ+4DLgHdk5tVtDxDxJ+CpmflAmzLHUIxa8IXxVXfyGeUwe9OSpZy08HrOWrSYpctWMnf2DBbM24bD5+/smLSSJGmkw+xewPnATOAk4COtxpqNiLPLLw/JzPtblJkF/Coz5/Wl1pPIqIZZZwuTJEljGYUw27TPbGZeCvw98CDwAHBpRBzW4hjHAgcAv42IN5bBtZmtxllXTZCblizlyFOv5OEVq9YKsgArVycPr1jFkadeyU1Llg6phpIkSYWWN4Bl5sUU/V0fBTwbeHpE/LqcTKG+3IXAx4DtKa7i3hoRp0XEmyPixRGxAPgR8JsBPQf12UkLr2fFqtVty6xYtZqTF94wQTWSJElqru2kCRGxMfDLzNyt/H4v4AvAH4B3Z+ZtdWXfAnwWmAM0HvQ24HmZ+X/9rX71jWI3g92PPp8Hl60cs9wGs2dw1Uf3n4AaSZKkUTSy3Qxqyn6y0+u+vxT4W4qbwy6PiPdGxMxy25eAnYGjgYXA/wFXAp+muEHMIFsRSzsIsgBLl3dWTpIkaVDahtmImA6sdeNXZq7OzOOApwFPBq6OiAPKbbdn5sczc+/M3CUz/zYz35eZdw7qCaj/5s7ubC6NubP6MueGJElSz8aaNOEpwOKIeGVEHBARu9U2ZOZtmfmPwBHAJyPi3Ih4/CArq4mxYN42zJjW/r8EM6YFB87bdoJqJEmS1NxYYfaVwOOBTShu8Do0Is6KiKMjYkOAzLyIIvT+DLgsIj4VERsMsM4asMPn78zM6e3fGjOnT+Ow+TtNUI0kSZKaG+sGsKuBf8zMRQ3r5wEfAD5b9qOtrd+BYqiuvYD3ZebXBlHpyWQUbwADx5mVJEljG4UbwMYKs8dl5j+32DYdOIUi0P5vw7aXAMcBdwL/lJmX96vCk82ohlkoxps9eeENnLnoVpYuX8ncWTM4cN62HDZ/J2cAkyRJIxFmycyWC3ApsH2b7VsB57TYth7wceAh4MvAFu3ONVUXimHM2i4zNtkqN33+W3O7o76T27/n7Nz5/52ZHzzzt3njXQ9mzeGHHz7mcWrL0UcfnY0OOOCAjvc/4YQT1tl/jz326Hj/s88+e539t9566473v/zyy9fZv9N9gbz11lvX2vfWW2/tav9Gl19+ecf7br311uvsf/bZZ3e8/x577LHO/ieccELH+x9wwAHr7H/00Ud3vP/hhx++zv6+93zv+d7zved7z/de3XtlwrPUWH1mLwB+EREvarH9dmDXZhsy85HM/DBFf9rtgD+OcS41sd7Oe7L1G/6LDZ/yAqbNXp+IaayaNpNvXXYLLzx2IRdde8ewqyhJkjQ0Y4XZTwErgR9ExM/K6WofFxGzywkV/g24q90BMvO6zHwBcHh/qjx1zNhkKx79svczbdZ6xPSZa21zWllJkqQx+swCRMQuwLnAjhSXkOslcFBmfn8gtZsC2vWZ/dBZv+Nbl92y1g1YjWZMC17z9O35+ILdB1dJSZKkJkahz+xYV2bJzGuBPYDPUHQriHK5AXi1QXZwzlq0uG2QheIK7ZmLbp2gGkmSJI2WjqZwysx7gfcA74mIzSmu6LbtXqDxc1pZSZKk9sa8MtsoM5cYZCeG08pKkiS11zLMRmMnCE04p5WVJElqr92V2ZdFxHsGefKIOCUinjjIc1SZ08pKkiS11zIpZeZZwDMi4l39PmlETI+IrwD3ZuYf+n38yWKHzedy/CF7MGfm9HWu0M6YFsyZOZ3jD9nD2bgkSdKUNdZ0tpsAPy+XozLzkXGfMGJb4L8phvXaPzOn9N1LnUxn67SykiRpFI3C0FydjDO7I/ATiskT3peZZ/Z0oiIYvw34f8BvgQMy8/5ejjWZdBJmJUmSRlElwixARGwFnEMx3uzi8uvLgD+U3y8BlmXmqoiYDcwFtgZ2oJjO9rnA3sBs4BTgLZm5vM/PpZIMs5IkqaoqE2YBImIG8CGK8WbXY93ZwNruDlwHvCMzz+u2kpOZYVaSJFVVpcLsX3eI2BJ4J/BqYPsxiq8AfgqcDHwvTWrrMMxKkqSqqmSYXWvniN0puh48AdgEmAU8ANwG/Ab4VWbeN/5qTl6GWUmSVFWVD7MaP8OsJEnt3bRkKSctvJ6zFi1m6bKVzJ09gwXztuHw+Ts7qs+QGWZlmJUkqY2Lrr2DI0+9khWrVrNy9ZrfkTOmBTOnT+P4Q/Zgn122GGINpzbDrAyzkiS1cNOSpbzw2IU8vGJVyzJzZk7nvKPme4V2SEYhzLafK1WSJGlITlp4PStWrW5bZsWq1Zy88IYJqpFGkWFWkiSNpLMWLV6ra0EzK1cnZy66dYJqpFFkmJUkSSNp6bLOZrxfuryzcpqcZgy7ApNJRDwD+DBQ64n+MPBvmfk/E3F+7/aUNJn5M27qmTt7Bg92EGjnzjLOTGXeANYnEfFS4Azg/Zn5mXLdIcDXgDdn5skt9uvLDWDe7aluGQxUJf6Mm5o+dNbv+NZlt7TtajBjWvCap2/PxxfsPoE1U80o3ADWU5iNiI2B/YArM3PK97qOiJ2A3wFXZeZeDdu+C7wMeHJmXtNk33GH2VG923Oyh6UqPz+DgapkVH/GafBs+9E3CmG21z6zPwa+A1zcx7pU2XuAucApTbZ9FZgJfHRQJx/Fuz0vuvYOXnjsQr512S08uGwlCTy4bCXfuuwWXnjsQi669o4Jq8sgVPn53bRkKUeeeiUPr1i1ztWOlauTh1es4shTr+SmJUuHVMOJc9OSpXzorN+x+9Hns9P7fsjuR5/Ph8763ZR47lUyij/jNDF22Hwuxx+yB3NmTmfGtLUz0oxpwZyZ0zn+kD0MslNcr2F21/Lxt/2qSFVF8SfJweW3C5sU+QWQwN9HxIaDqMOo3e052cNS1Z+fwaBQ5T9IpppR+xmnibXPLltw3lHzec3Tt2eD2TOIgA1mz+A1T9+e846a73+RNK4rsyuBN3S6Q0T8Z4/nGnW7AJtSBNbrGjdm5n3A7cB6wJ6DqMCo3e052cNS1Z+fwaD6f5BMNaP2M04Tb4fN5/LxBbtz1Uf354Z/fwlXfXR/Pr5gd6/ICug9zL4NuJ41V2jbiohpwOt7PNeo27F8vCczl7coc1v52NHr1a25szu7i3Oi7vac7GGp6s/PYFD9P0immlH7GSdptPT6yV8C7AMcFxG7AhcArXpnb0wRZCfrn0+blo8PtylT27bJWAdr7EjdUQWe/1Y2fMoLiOkzW5bJVStY/MsfEPHCro/fre3fczbF3y/tPfDI8p6e77BV/fltd9R3mDZ7/THLrXpk6UjWvx86eQ1Wrk6+dvHV/OuBT5qgWqmVUfsZJ2m09Bpmf8Gaf5kf1Ke6VF27S3W1oL9WMoiII/px4gd+fSYb7L7vGD/oV/HA5Wf143RjyuWPEB2EpVzeLv+Prqo/vwd/f1FHweDBqy6awFpNrJi1Xofl5gy4JurEqP2MkzRaeu1m8BWKYNbNMlndXT62+61X23Zv/crMPLEfFVh5723c+f1/Z/XyR8hVK9balqtWsHr5I9z5/X9n5b23tThCfz34+4vWqUejKoelqj+/B359Jrmq9TA3MPmDQS5/pMNyo/kHyVQzaj/jJI2WXseZ3YjipqZTgMspbgZrZQ7wcmDfzJzeQx1HWkTsDPwJWA3Mzsx1XouIuAV4DLBfZv6kYVtfJk2A4qaWkxfewJmLbmXp8pXMnTWDA+dty2Hzd5rw8WUn87iAk+H5TfVxZh2IvZpG5WecpDVGYZzZnmcAi4hvZOY/dFh2c+C2zGz9P6IKi4jFwNbArpl5bcO2ucB9FGF388x8oGF738LsKJnsYWkyPL+pHAwmwx8kkjQKqh5mnwJcm5kd/b8uIt6emZNyeK6I+C+KER4Oy8wvN2x7AXA+8IPMfGmTfSdlmIXJH5Ym+/Ob7CbDHySSNGyVDrNrHSTiccCzgK2A5cBNwMWZeXfbHSeJiHg8xXS2v87M+Q3bvkkxqcLemfmzJvtO2jArjTr/IJGk8al8mI2I3YD/BJ7XZPNK4BvAezLzzp5PUhER8WbgeODdmfm5ct3BwDeBT2Tmh1rsZ5iVJEmVVOkwGxF7A+cA69N+tIJbKW7++mNPJ6qQiNgXeC/F2LqrKPrJfj4zv9tmH8OsJEmqpMqG2fKGrmuBzYClwBkUY89eDzwAzKaYGevvgFdRBNrdM3NZX2o9iRhmJUlSVVU5zP4b8H7gq8C7MvPeNmW3B74PfC0zj+2tmpOXYVaSJFVVlcPsb4BLMvMtHZbfBTi58eYoGWYlSVJ1jUKY7XU62+2BvTstnJnXRsTGPZ5LkiRJaqrX6Wxvy8x7Oi0cEdMphu2SJEmS+qbXMPtIRKzfRfk3UcyCJUmSJPVNr2F2IfCxsQpFxIyIeA/FWLTn9XguSZIkqalebwDbGfgDcCHwWWBRZi4pt20GPBnYFziEon/tI8ATM/PmPtV70vAGMEmSVFWjcAPYeCZNOBL4L6B2gOXATNaeQCEoJg54TbuJA6Yyw6wkSaqqUQizvXYzIDOPB15H0Rc2KCZKmFZ+XVtuAV5okJUkSdIg9Hxl9q8HiNgAeCUwn2LEgtXAzRRdEM7KzJXjreRk5pVZSZJUVaNwZbbXPrMbA/sBV2bmDX2v1RRimJUkSVU1CmG210kTfgzsCdxKcYOXJEmSNOF67TO7a/n4235VRJIkSepWr90MTgcOAB6TmXd2uM9/Zubbuz7ZJGc3g97dtGQpJy28nrMWLWbpspXMnT2DBfO24fD5O7PD5nOHXT1Jkia9Uehm0GuY3Qq4CDgiMxd2UH4acG9mbtR9FSc3w2xvLrr2Do489UpWrFrNytVrXrMZ04KZ06dx/CF7sM8uWwyxhpIkTX5VDrMzgc2B4yj6z14ArGpRfGPg9cA7M3N6j/WctAyz3btpyVJeeOxCHl7R6i0Hc2ZO57yj5nuFVpKkARqFMNvrDWC/oLgBDOCgPtVF6shJC69nxarVbcusWLWakxfewMcX7D5BtZIkScPQ6w1gX2HtyRE6WaS+OGvR4rW6FjSzcnVy5qJbJ6hGkiRpWHq9MvsN4HPAKcDlQLuJEeYALwf27fFc0lqWLutsHo6ly52vQ5Kkya6nK7OZeT9wZma+NTO/nJlfa7N8CXgNxcxgGkNEjLkcccQR6+x3xBFHdLRvRHDMMcess/9LX/rSjvc/8cQT19l/zz337Hj/c845Z539t9lmm473X29GZxf6Vz2ytOn+ixcvXqvc4sWLOz53Y98ggCuuuKLjfbfZZpt19j/nnHM63n/PPfdcZ/8TTzyx4/1f+tKXrrP/Mccc0/H+U/29d8UVV6yzfzfvHd97a/O953vP917133ujoKcwG8UMYFdExBM7KZ+ZS4B/6eVcUqPn7rAeM6a1/wDlqhU8eNVFE1QjSZI0LL32mf0x8Cng/E53yMz/7PFc0lr+/glzmTm9/Vs3V63igcvPmpgKSZKkoel1aK77gbnAuZl5QN9rNYWEQ3P1xHFmJUkavsauBlUaZ9YZwPrEMNu7m5Ys5eSFN3DmoltZunwlc2fN4MB523LY/J0cX1aSpAlQ5TDrDGB9YpiVJElVNQphttehuZYA+wDHRcSudDYDmJfKJEmS1Fe9Xpm9jDUzgHXM6WzX5ZVZSZJUVaNwZdYZwCRJklRZvV6Z3Qi4nS5nAPPK7Lq8MitJkqpqFK7M9hRmASLiG5n5Dx2W3Ry4LTNn9nSyScwwK0mSqmoUwmyv3QwAPhkR63VS0BnAJEmSNAg9X5lte9CIDYCfUswU9j/AzzNzRd9PNAl4ZVaSJFXVKFyZbRtmI+J1DasuyczrOjpwxOOAjwGvBpYCFztb2LoMs5IkqaqqEGZXAwncCXwNODEz/9TVCSJeTzH6gUNzNWGYlSRJVVWVMPsX4CmZeVfd+jMpQu46MvPlTY7zRYrZwgyzDQyzkiSpqkYhzHZyA9jp9UG29Bbge8DuwMuAJwDfLNc389WeayhJkiS10Ml0tut0K8jM24FvRMQfgCuAV2Xm1W2OsQhY3VsVJUmSpOY6uTJ7f6sNmbkIuG+MIEs5ksGSLusmSZIktdVJmF01xvbbOzzX0g7LSZIkSR0Zz6QJNZ12HxgrFEuSJEld6UeYHcVzSZIkaQqYyIC52QSeS5IkSVNAJ6MZ7DSeE0QxANmBwMbjOY4kSZLUqNMZwPrCSRPW5aQJkiSpqkZh0oROrswCtKtYjrG9vpwkSZLUN530mR0rqE54ApckSZKgszD7PuDRwPTMnNbtAqwHzAPaTqwgSZIkdWusbgYPZOanxnOCzFwO/CYivj6e40iSJEmNxroye3wfz/XLPh5LkiRJaj+agQbP0QwkSVJVjcJoBs7KJUmSpMoyzEqSJKmyDLOSJEmqrE4nTdAIuWnJUk5aeD1nLVrM0mUrmTt7BgvmbcPh83dmh83nDrt6kiRJE8YbwIas2xvALrr2Do489UpWrFrNytVrys6YFsycPo3jD9mDfXbZYjCVlSRJqjMKN4AZZoesmzB705KlvPDYhTy8YlXLMnNmTue8o+Z7hVaSJA3cKIRZ+8wOUETMiIj9+nW8kxZez4pVq9uWWbFqNScvvKFfp5QkSRpphtkmImKPiDgrIpZExLKI+GNEHBMRs9vsc3JEZP0CrACe2696nbVo8VpdC5pZuTo5c9Gt/TqlJEnSSPMGsAYR8RzgAmAlcA+wKfB44Ghg74h4fmauaNhna+BVQGOKfBA4oV91W7psZWfllndWTpIkqeq8MlsnIuYAJwJvATbMzO2Azcp1AM8D3thk16OA/8jMxzQsu2Zm3y6Tzp3d2d8ec2f5N4okSZoaDLNrewlwamaekuWdWJl5L0W4/WVZZv/6HSJiI+D1wH8NunIL5m3DjGnt+1XPmBYcOG/bQVdFkiRpJBhm1/ZY4HONK8tg+6Py2+kNm98KbAn8KSLOi4ijImLLQVTu8Pk7M3N6+yabOX0ah83faRCnlyRJGjmG2TqZ+cnMfLjF5nvLx983rH9D+bgRxVXbz1EE2yP6Xb8dNp/L8YfswZyZ09e5QjtjWjBn5nSOP2QPh+WSJElThuPMdigiPgv8C/DEzLymYdt6wDxgAXA4xU1jAG/NzC+NcdyuJk2AYrzZkxfewJmLbmXp8pXMnTWDA+dty2HzdzLISpKkCTMK48waZjsUEX8CLs7MZjeA1ZfbAvgq8GLgEWDHzLy9RdkjaBjtwPaQJElVMQph1m4GHYiIV1O8Vu8aq2xm3kFxhfZSYD3g1W3KnthqmyRJksY26cJsOblBdrnc2OZ4jwaOAV6Smfd0UodyHNqPlt/uPN7nJEmSpOYm44CklwFf6HKfJc1WluPOfhM4LDOv7vKYl9QO0+V+kiRJ6tCkC7OZ+SPWDKPVs4iYAZwCfCIzf97DIWpXvW8eb10kSZLU3KTrZtAPETEd+Arwtcy8sMn2XTo4zJ5AAuf0uXqSJEkqGWYbRHFb3peAM8urvI3b/wZ4W/n1LhGxoJwFrPEYxwAnZOa1g6+1JEnS1OTQXA0i4niK6WlvabJ5FrADsH9mXhARFwF7A7cBRwHfATagmDhhFvCm8mawdufrepxZSZKkUTAKQ3MZZutExMeBD41R7HrgcZmZEbEX8AmKLgVzgOuA/wVOzcxzOzynYVaSJFWSYVaGWUmSVFmjEGbtMytJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDbBciYkZE7DfsekiSJKlgmG0hIk6OiKxfgBXAc5uUnR0RH4mIKyPi5xFxVUR8NiI2nPiaS5IkTR2RmcOuw8iJiK2Ba4H7GzY9COybmbfWlZ0N/BjYCtg7MxdHxKbA+cAc4NmZ2Xic+nOt1QC2hyRJqoqIWOv7zIwWRQdXB8PTuiLik8DDmXlMB2W/ABwJvCgzz6tbvzvwO+DUzHxtm/0Ns5IkqZIMsyMoIjYC/gjsnpl3jVH2McD1wF3AttnwYkbEZcDTymNd3eIYhllJklRJoxBm7TO7rrcCWwJ/iojzIuKoiNiyRdlXADOBXzQG2dJCIIB/HExVJUmSpjbD7LreUD5uBOwPfI4i2B7RpOxe5eO1LY71x/Lx2f2rniRJkmoMsw0yc1eKG7eeBXwKuAeYC5wQEW9pKL5j+Xh7i8PdVj7u2udqSpIkCcNsU5n5SGZekpnvpQiiPyo3fa6hy8Gm5ePDLQ5VW79Js40trvZKkiSpQ4bZMWTmHcAC4FJgPeDVzYq12H1V+di0M3Rmnjje+kmSJE1lky7MRsQxjZMddLDc2O6YmbkC+Gj57c51m+4uH+e02LW2/t5en48kSZJamzHsCgzAZcAXutxnSQdlLikf66+yXkdxE9gWLfapdUn4Y4vtkiRJGodJF2Yz80es6ePaT7Wr2DfXrfsF8Frg8S32qa3/+QDqI0mSNOVNum4GA7QnRd/Yc+rWfR9YSeuht55bPp4+wHpJkiRNWYbZOhGxS0QsKGcBq18fwDHACZn51zFlM/M24L+B7SJi34Z9dqXognBhZl4+8MpLkiRNQU5nWyciLgL2phgf9ijgO8AGFBMnzALeVN4MVr/PpsDPKGYC2ycz/xIRGwPnAtsDz8nMG9uc0+lsJUlSJY3CdLaG2ToRsRfwCYouBXMobvD6X+DUzDy3zX4bAe8DXgLcRzGu7ELg4+XV23bnNMxKkqRKMszKMCtJkiprFMKsfWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmJUkSVJlGWYlSZJUWYZZSZIkVZZhVpIkSZVlmB2giJgREfsNux6SJEmTlWG2QUQsiogcY5nXZL+TG8sBK4DnTvyzkCRJmhoiM4ddh5EREU8HfgUsAe5qUmQb4D5g+6x74SJia+Ba4P6G8g8C+2bmrW3OuVYD2B6SJKkqImKt7zMzWhQdXB0MT2tExMnAZZl5Yovt/wf8IDOPalj/SeDhzDymh3MaZiVJUiWNQpidMdEnHHFXtwmyewKPBU5vWL8R8Hpg98FXT5IkSfXsM1snM/+jzeZXAbcBv2hY/1ZgS+BPEXFeRBwVEVsOqo6SJElaw24GHYqIPwHnZebbGtZfA+zSUHwp8C+trvI27G83A0mSVEmj0M3AK7MdiIinATvT0MUAIDN3BeYAzwI+BdwDzAVOiIi3TGQ9JUmSphrDbGdeBdwJXNxsY2Y+kpmXZOZ7gV2BH5WbPteuy0FEHNH3mkqSJE0hhtnOvBI4KzNXjVUwM+8AFgCXAusBr25TdsxuCJIkSWpt0oXZiDimg0kPGpcb2xzv6cCONOli0EpmrgA+Wn6783iejyRJklqbjENzXQZ8oct9lrTZ9iqKfrAXdnnMS8rHCe8ILUmSNFVMujCbmT9iTZ/VfngFcHZ5tbUbtaveN/exLpIkSaoz6boZ9FNE7AXsAHyvh933BBI4p6+VkiRJ0l8ZZtt7FXA/8ONmGyNil4hYUM4CVr8+gGOAEzLz2oHXUpIkaYoyzLZQBtJXAD/IzGUtin0JOBO4NiIOjsKGwEnA9cA/T0xtJUmSpibDbGt7AdvRvovB+4GLgPWB/wauogi4p2fm63roZytJkqQuOJ3tkDmdrSRJqiqns5UkSZLGwTArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaqsKRVmI2KDiHhfRHxrjHKzI+IjEXFlRPw8Iq6KiM9GxIb9KC9JkqT+iMwcdh0GLiI2AN4OvAvYHLg4M/duUXY28GNgK2DvzFwcEZsC5wNzgGdn5v29lm9yvrUaYCq0hyRJmhwiYq3vMzNaFB2YqXJl9m+Bk4ATOyj7H8B84J8zczFAZt4DvBHYHfjCOMtLkiSpT6bEldmaiDgU+CotrsxGxGOA64G7gG2z4cWJiMuApwG7Z+bV3ZZvUSevzEqSpEryyuzoeQUwE/hFYzAtLQQC+Mcey0uSJKmPDLNr26t8vLbF9j+Wj8/usbwkSZL6aMawKzBidiwfb2+x/bbycdcey4+p8XK9JEmSWvPK7No2LR8fbrG9tn6THstLkiSpjwyzzbW6C2tV+dh4+bTb8sXKiCO6rJckSZLqjHyYjYhjIiK7XG7s8XR3l49zWmyvrb+3x/JrycxOhgqTJElSC1XoM3sZ3Y/VuqTHc11HcVPXFi22b1k+1m7s6rb8OmpDWETE5Zn5tK5qq5FiG1ab7Vdttl/12YbVNsz2G/kwm5k/An40Qaf7BfBa4PEtttfW/7zH8pIkSeqjke9mMMG+D6yk9VBazy0fT++xfDt2Oag+27DabL9qs/2qzzastqG131SbAexwihe76QxgZZmvAG8A9svMn9St3xW4GrgoM/fttbwkSZL6Z8qE2SgGcP0G8GrgL8AumflAk3KbAj+jmNlrn8z8S0RsDJwLbA88JzNv7LW8qikitgM2yszfD7sukgp+LqXhGpXP4JToZhARHwNuoQiyAFsDf46IX0XErPqymXkPRbeBM4DzIuJnFNPSLgKe1hhMuy3fpG7PiIgfRMRl5XJxRLxgfM9YvYqIHSJiReMIGRRX2W9pKNtV29nWgxERe0XEeRHxnDZlBtpWtm3vOmy/jj+XZXnbb4AiYmZEfCAiro6IRyLi3oj4YUQ8o0V5P38jpoc2HO3PYGa6DGkBXgqsAN5dt+4QivFpDxt2/abiAhwH3An8uW65BfjoeNrOth5IWz0TOI9inOcE9m5RbqBtZdsOtv3Ksh19Lm2/CWu7c4DVZTs8UNeGy4EXT2R72H6Db8Oy/Eh/Bof+gk7VBdgJeBC4tMm275ZvqF2HXc+ptACbA4uBjfvZdrb1QNrqMcAzgEcDS1uFoUG3lW072PYry3b0ubT9Jqzt3gz8BNi+bt1+ZbjJ8nH6RLSH7Tf4Niy3jfxncEp0MxhR7wHmAqc02fZVij64H53ICom3A6dl5n1jlOu27WzrPsvMP2fmrzLzToqrBa0Muq1s2x500X7Q+ecSbL+JcDBwUGbeXFuRmRcAbyq/3RbYrfzaz99o6qYNoQqfwWH/hTAVF4rpbe+m+AtotybbN6a4/P8wsOGw6zsVFmB94K7ydf8DcDywL+VNkr22nW09IW13I02u7A26rWzbwbZfua2jz+VEtPewX6dRWCiupL+txbbpwCPl6znPz99oLt20YbmuEp9Br8wOxy7AphQNeF3jxiz++rkdWA/Yc2KrNmW9HNiE4sO1K/BW4ALgwojYtq5ct21nWw/PoNvKth28Tj+XYPsNXGbemZlNZ+TMzFUUfS+XU7yefv5GUJdtCBX5DBpmh2PH8vGezFzeosxt5eOug6+OMvNUin9nbEfR8fxn5aa9gR9HMQQbdN923ZZX/+xYPg6qrbotry518bkE22+oImJD4FHAGZn5IH7+KqdJG1bmM2iYHY5a4z/cpkxt2yaDrYpqsvDnzDwtM59HMZTbQ8ATgY+UxbptO9t6eAbdVrbtBOjwcwm237AdSPEv6qPL7/38VU9jGwLV+AwaZocr22xbVT7GRFRE68rMb1N0lAc4tHFzm12btZ1tPTyDbivbdgKN8bkE22/CRcRM4N3ABzLzjw2b/fxVwBhtuJZR/AwaZofj7vJxTpsytW33DrYqaiczfwD8Ctik/HdKt21nWw/PoNvKth2SJp9LsP2G6f3AJZn5ubp1fv6qpVkbtjRqn0HD7HDUOjpvGhEzWpTZsnxs+xeSJsQl5WPQfdvZ1sMz6LaybYer/nMJtt9QRMRBwO7AkQ2b/PxVRJs2HMvIfAYNs0OQmdcDf6F4/R/buD0i5lJMubsCuGxia6cmplEM6nxPt21nWw/PoNvKth26v34uYfDtPZinUG0RUes/+Y/lnfB/5eevGtq1YQdG5jNomB2eM8rHZvORP5tivLfzM/OBiauSWtgTOCfLge/ovu1s6+EZdFvZtsPT+LkE22/CRMRewDuA12bmioZt0yPisfj5G2kdtmE7o/MZbDcIrctABy5+PMVdgwubbPsmxUDBzx12PafCUn5YFlAOEt2wbT+Kvzwf22vb2dYDb79baT3o/kDbyrYdXPt1+7m0/Sa0zeYBZwPrN9k2Hfgc8Dd+/kZ36bANd6vKZ3DoL+hUXijmR14FvLNu3cFl4/3rsOs3VRbgeeUv0yw/PFuV6/cGrgaePd62s60H1na7la9rAu9uUWagbWXbDqb9evlc2n4T1mZ3AjcB1zRZ7gZ+PlHtYfsNrg2r9BmMcicNSUTsC7yXYtq2VRSN9/nM/O5QKzaFlEOSfJziw7Mtxbh2l5bLcZm5pMV+XbWdbd0/EbE9cBbFTQsz6zZdCxybmV9qKD/QtrJtu9NJ+/X6uSyPb/sNQDnj0+XAVmMUfX1mfr1uPz9/I6KbNqQIsJX4DBpmJUmSVFneACZJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiRJqizDrCRJkirLMCtJkqTKMsxKkiSpsgyzkiaFiHhWRJweEb+PiEci4rqIeH9ExLDrptEQES+IiI2HXY96ETEtIg4edj2kKjPMSupKRPxjRJwbEUsjIpssqyPi/oi4ISK+HxHviIjNB1ynVwIXAB8BdgeOAx4HfAJ4/SDPPRVFxIsb2vzesr3/LyJur1t/f7nu+oi4s2Gfz0xgfWdHxJeAlwH3T9R5O5GZq4GtI+KHEbHpsOsjVZFhVlJXMvO0zHwRcEDDprcBTwCeArwWOAf4O+BY4OaIOGoQ9YmIzYCTgV9k5u8zM4H3U4TblcCtgzjvFLdB+fgdYOfM3CQzd8rMxwHvrSt3RmY+LjN3zsxHA48GPlZumzsRFS3fHxcAqzPzbeX7Y6Rk5rHAGcDCiNh2yNWRKmfGsCsgqbJ+1fD9CZm5qvz6d8D3I+LTwEXAY4HPRcTczPy3PtfjjcBGwF9qKzJzVUS8ANggMx/o8/lUhNlbgNdm5vJOd8rMu4CjI+IpTECYjYgNgPOBJcDbB32+8cjML0fE44BzI+LZvm+lznllVlJPMvOhhu9XNSlzC3Bk3aoPRsRGfa7K3uXj6oZzp4FgYDYAvtFNkG3wZSbmyuypwM7Aoc3enyPoI+XjV4daC6liDLOSBu0nwMPl13OAvfp8/O36fDyN7S7gB+PY/2Lg//pUl6Yi4lCKPrL/npm3DfJc/ZKZK4BjgIMi4qAhV0eqDMOspIEqr4jdW7fqUX0+xYT0vdQamfmNzPz5OPa/PzPfO3bJ3kTEesC/A8uAEwd1ngE5C7gd+HRE2BVQ6oBhVtJARcRMoH40gzvblF2/HE7rl+Vd8A9ExBUR8a6ImFVX7oXl9v8DdihXv7y2rlzm93LsuvK7RcRnI+K48vsXRcTvIuLBiPjXXo8dhfkRcXJEnFuu2yoivhQRt5WjRPwgInYc43V9QUScHRHXlCMJXBMR/xkRO4339Z0EDgW2An6amS1HL4iInSLimPJ9RETMjYijI+IPEfFw+XhQXfkZEfG2iLi8bKc/R8SHI9Yd/i0iNo6If4+Iq8rRHJbXjeSwoFWdytENzgd2Al7T8ysgTSWZ6eLi4tLTAmRtaVPmpXXl7gHmtii3PXA18FZgerluF+AP5b4/p7ihq3G/G8vtp7SpQ8fHBt4MXFpX52+Vz+HhunVLezz2C8vva8e5FNiD4ua12yiGjaptuwaY1eS5zAS+Xp7zWXXrj6nVDdivX69vD++JQ+ueQ8s2GfD78mfl+T/WYvtTgAsp+lnX6roV8FtgOXATxUgYWT4+E9iG4qbH+4GbgVV1+x7VcPxZ5bH+AGxXt+6DZfkFY9T/n8pyFw3j9XNxqdoy9Aq4uLhUd2GMMEtxden6unKHtig3m2IEhE812VYfhtcJJ4wRZrs9NsXNTRtQXEGuBc7vA5uVYfRG4Lu91hsI4PJy/U3AFbXwSfHfsi/W7Xdgk+N+E7gD2LJh/WZ1Aeu3/Xp9e3hPHEqPYZZiVIqPAXuM4/yb1L0Or2lRZn1gQ+C7dXVdSPGHzIZlmZ3r3gMXlu+Dg1nzh8D2FP1+E7ix4fivoknILbd9g7HD7N7l/quAR4+3TVxcJvtiNwNJfRUR60XEM8pB8X9LEWhvAl6emae02O3tFJMdNLuL+8fAivLrXiZA6OrYmflgZj4IXFuu3w04LDPvzszzMnPHzHxlr/XOzNpVVyjC299n5gXlttWsuXoH8Iz6A0bEgcCrgU9n5u312zLzborQDbDWSBO91HMiRcSschziPwEfpnhdevUU1nShW9ysQGY+lMVIFxfUrf5IZp5Qriczr6cIngD7AMdk5rezHBUhM28GvlBu3yEitqk71s7l49ZNTv/5Dp5DbZi5aTS8BySty87lkvoiIq6luNpV/wv8c8C5FP8uXdlm98PKxzObdD+E4gayacB6ETFjjGP169i1x//NzFb9fMd77Psyc61JHTLz7oi4i2KCgcab5f6lfGw1ksA/APMpriL2o54T5UkUwfGpjD9QP6Hu6yVjlF1W9/UNTbbXj7hwzRjbH8Oa8PyH8vGoiLg0M8+sFcrMxvGZm7mj7usnM76RI6RJzzArqS8yc5eImEPR93KPcvWWmfnjdvtFxBYUfTcBdu9nkOrTsZuOTzrIerPmyupff0aX4/M+s/y2WfAiMx+huNI6UfXsi8y8AiAibuzD4Tap+3pZq0IdGmuc4vrtc+q+Pge4DHg6cEZE/Dfwnux8iLBH6r5+dIf7SFOW3Qwk9U1mPgy8nGIcUoB/iIgPjLFb/Tix/R5mq6rHbmZ7YHr5dTdTsk50PYetflSGiZwo4a+XvMvuIgdQ9IeGYnrnayPinRHRye/d+hC+Yf+qKE1OhllJfZWZN1H066wFiX9tNxQRxc1JNdv3uTpVPXYzG9d9vW0X+010PYet/mrp7JalBqzsmvIs4OMUIyRsBPwH8POG/rXN1AfyBwdTQ2nyMMxK6rvM/AnwvvLbAE6NiCe3KH5P3dd7j3XsiOhmBrGqHnus8+3T4357j1W4D/Uctvp/5Q/1SnRmLs/MjwBPBL5Trn4m8D8RMb31nqxX9/VY/X6lKc8wK2kgMvMzwLfLb+cC55T9Nxv9H2umu31HRLS8mhYRRwJP66IaVT12M9dRjCEL8M/twlBEvD0idh1SPYftN3VfNxtNYOAi4n0R8bja95l5fWYeDBxertoNeF6bQ9Tf+Pf7AVRRmlQMs5J6MsaVpZo3UgzPBcW/uM9onGkqi/nof1h++1iKERCane/5wHtZd3ipaHjs57FbGuSx25zvjPLbJwOfbXG+vwfmZ+Y1w6gna/r1QpM2mQDXsWY0gB2GcP6aAxtXZObJrBnpoN2NXfXdEH7dz0pJk5FhVlKv1ho2KiI2biyQmQ9R/FKv/av72cCJTY71b6wZ6/StEfHDiNgvInaIiL0i4nMUwxO9KzOXNuxbO+8mLerZ67Frd6ev87z6cOyx+nJuUD42/sHwMdZcnX1HRFwYEa+IiKdExN9FxBeAE4Cj+lTPXtSHtM3GeayulTdf1cbbfcoYxeu7ITT7fVj/7/5m74MN6r6e2bDtnyNiA9Y1m2LmsXYhdffy8YrMvKVNOUngDGAuLi7dLxS/+GuD+9eWtwHRovwLWXv6zy/RMHUqxVXcVQ3HrC0rgXe0OG6tzN3Azi3O39WxKQaqf6jcvhx4epvXopd6L2LN1LPrN2zbnjXTrF7SZN8Xs/bUuvXLEmCvftWzh/fFphRDUtWOex/wxC72P6bcb+9x1uPp5XGubVNmPeBHdXU9tGF7AKfUbf8kMK1u+6yG7Z+qvf8p+ovXZhV7XLluBvDRcv2Hx6j/18ty/zSIz6+Ly2Rbhl4BFxeXai0UA/ff2yIU3Qec3GK/DzSUfQT474Yyf0sxxejtFFcS/wJ8C3haQ7mXUfwruVkd/kKTaUy7OPavWxz3NmCfFs+t02M/l2ISifrjXlELLcCbgD82bP8B8KyG4zyhDDyLKcL2TcB/AluP0XYd1bOH98QTgVsoQnGz1+52OgjL9CnMlsf6SXms3Ztseytr/lhpbOOdKSafaPYevx94EUW/4mUt3v8vYk2YrS13Uvx34nLg4DHqPZNiaLu/AOsN+/Pu4lKFpfZXpCRJQxURxwBHU/zR8NNxHuvJFH8ofD0z3zT+2k2MiHgTcDJF6P3OWOUl2WdWkjQ6aqNdrD/eA2Xmb4F/BV4fEXuO93gTISI2o+gXfYpBVuqcV2YlSUMVEU8BFgD/j+KmrN9Q3Mh2embe0WbXsY4bFMPD7Q48MzPvG39tB6OcGexMihsPX5LFKBSSOmCYlSRNWuVQcF+nGFnhpZm5bIxdJlwZur8IbA68NjMfGXKVpEqxm4EkadLKzOXAa4CLgTMjYtxdGPqpvCJ7EsVNfK8yyErd88qsJGlKKGdFuy4zVw27LvUi4gmZ+cdh10OqKsOsJEmSKstuBpIkSaosw6wkSZIqyzArSZKkyjLMSpIkqbIMs5IkSaosw6wkSZIqyzArSZKkyvr/ATr9boeMhtcEAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_id = plot_single_scatter(x=temp_corrected_ref_values,\n",
    "                             y=dataset_estimate,\n",
    "                             y_std=dataset_std,\n",
    "                             title='Error relative to reference',\n",
    "                             x_label='Reference T$_1$ (ms)',\n",
    "                             y_label=\"Error (%)\",\n",
    "                             file_prefix=str(index),\n",
    "                             folder_path=output_folder,\n",
    "                             fig_id=fig_id,\n",
    "                             y_type='error_t1')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "analysis_arm",
   "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": "3.8.13"
  },
  "vscode": {
   "interpreter": {
    "hash": "021e32979ba0b507138b043ad23cc6ba88d193e810337e0e3a2521ed1faaaccb"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}