diff --git a/notebooks/thesis_efficiencies.ipynb b/notebooks/thesis_efficiencies.ipynb
index 21d11c6..3562188 100644
--- a/notebooks/thesis_efficiencies.ipynb
+++ b/notebooks/thesis_efficiencies.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17,7 +17,10 @@
     "import itertools\n",
     "import awkward as ak\n",
     "from scipy.optimize import curve_fit\n",
-    "from utils.components import unique_name_ext_re\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "from matplotlib import colormaps\n",
+    "\n",
     "mplhep.style.use([\"LHCbTex2\"])\n",
     "plt.rcParams[\"savefig.dpi\"] = 600\n",
     "%matplotlib inline"
@@ -25,74 +28,84 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
     "file = uproot.open(\n",
-    "    \"/work/cetin/LHCb/reco_tuner/data/resolutions_and_effs_B_thesis.root:Track/MatchTrackChecker_8319528f/Match;1\",\n",
+    "    \"/work/cetin/LHCb/reco_tuner/data_matching/resolutions_and_effs_B_default_thesis.root:Track/MatchTrackChecker_8319528f/Match;1\",\n",
     ")\n",
     "\n",
-    "P_recoed = file[\"01_long_P_reconstructed;1\"].to_numpy()\n",
-    "P_recoable = file[\"01_long_P_reconstructible;1\"].to_numpy()\n",
+    "P_recoed = file[\"07_long_electrons_P_reconstructed;1\"].to_numpy()\n",
+    "P_recoable = file[\"07_long_electrons_P_reconstructible;1\"].to_numpy()\n",
     "\n",
-    "Pt_recoed = file[\"01_long_Pt_reconstructed;1\"].to_numpy()\n",
-    "Pt_recoable = file[\"01_long_Pt_reconstructible;1\"].to_numpy()"
+    "Pt_recoed = file[\"07_long_electrons_Pt_reconstructed;1\"].to_numpy()\n",
+    "Pt_recoable = file[\"07_long_electrons_Pt_reconstructible;1\"].to_numpy()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "control eff:  0.8626619913200968\n",
-      "new eff:  0.8626619913200968\n",
-      "control eff:  0.8629752409817771\n",
-      "new eff:  0.8629752409817771\n"
+      "control eff:  0.6145546589237905\n",
+      "new eff:  0.6155293168395326\n",
+      "control eff:  0.6173168233870217\n",
+      "new eff:  0.6176270902698983\n",
+      "212152\n",
+      "130379.0\n",
+      "213171.0\n",
+      "131213.0\n"
      ]
     }
    ],
    "source": [
-    "P_Velo_recoed = file[\"01_long_EndVelo_P_reconstructed;1\"].to_numpy()\n",
-    "P_Velo_recoable = file[\"01_long_EndVelo_P_reconstructible;1\"].to_numpy()\n",
+    "P_Velo_recoed = file[\"07_long_electrons_EndVelo_P_reconstructed;1\"].to_numpy()\n",
+    "P_Velo_recoable = file[\n",
+    "    \"07_long_electrons_EndVelo_P_reconstructible;1\"].to_numpy()\n",
     "\n",
     "print(\"control eff: \", np.sum(P_recoed[0]) / np.sum(P_recoable[0]))\n",
     "print(\"new eff: \", np.sum(P_Velo_recoed[0]) / np.sum(P_Velo_recoable[0]))\n",
     "\n",
-    "Pt_Velo_recoed = file[\"01_long_EndVelo_Pt_reconstructed;1\"].to_numpy()\n",
-    "Pt_Velo_recoable = file[\"01_long_EndVelo_Pt_reconstructible;1\"].to_numpy()\n",
+    "Pt_Velo_recoed = file[\"07_long_electrons_EndVelo_Pt_reconstructed;1\"].to_numpy(\n",
+    ")\n",
+    "Pt_Velo_recoable = file[\n",
+    "    \"07_long_electrons_EndVelo_Pt_reconstructible;1\"].to_numpy()\n",
     "\n",
     "print(\"control eff: \", np.sum(Pt_recoed[0]) / np.sum(Pt_recoable[0]))\n",
-    "print(\"new eff: \", np.sum(Pt_Velo_recoed[0]) / np.sum(Pt_Velo_recoable[0]))"
+    "print(\"new eff: \", np.sum(Pt_Velo_recoed[0]) / np.sum(Pt_Velo_recoable[0]))\n",
+    "\n",
+    "print(np.sum(P_recoable[0], dtype=int))\n",
+    "print(np.sum(P_recoed[0]))\n",
+    "print(np.sum(P_Velo_recoable[0]))\n",
+    "print(np.sum(P_Velo_recoed[0]))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(array([     0.,  39546., 175333., 205172., 179814., 156192., 131918.,\n",
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-       "         20994.,  19297.,  17662.,  16196.,  14804.,  13679.,  12636.,\n",
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-       "           408.,    392.,    349.,    328.,    328.,    289.,    308.,\n",
-       "           271.,    297.]),\n",
+       "(array([[0.0000e+00, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 0.0000e+00,\n",
+       "         0.0000e+00],\n",
+       "        [4.1620e+03, 2.4200e+02, 8.7000e+01, ..., 0.0000e+00, 0.0000e+00,\n",
+       "         0.0000e+00],\n",
+       "        [2.3471e+04, 2.7160e+03, 1.4720e+03, ..., 0.0000e+00, 0.0000e+00,\n",
+       "         0.0000e+00],\n",
+       "        ...,\n",
+       "        [1.3000e+01, 0.0000e+00, 0.0000e+00, ..., 0.0000e+00, 1.0000e+00,\n",
+       "         0.0000e+00],\n",
+       "        [1.3000e+01, 1.0000e+00, 1.0000e+00, ..., 0.0000e+00, 0.0000e+00,\n",
+       "         0.0000e+00],\n",
+       "        [9.0000e+00, 3.0000e+00, 1.0000e+00, ..., 0.0000e+00, 0.0000e+00,\n",
+       "         0.0000e+00]]),\n",
        " array([     0.,   1000.,   2000.,   3000.,   4000.,   5000.,   6000.,\n",
        "          7000.,   8000.,   9000.,  10000.,  11000.,  12000.,  13000.,\n",
        "         14000.,  15000.,  16000.,  17000.,  18000.,  19000.,  20000.,\n",
@@ -107,38 +120,567 @@
        "         77000.,  78000.,  79000.,  80000.,  81000.,  82000.,  83000.,\n",
        "         84000.,  85000.,  86000.,  87000.,  88000.,  89000.,  90000.,\n",
        "         91000.,  92000.,  93000.,  94000.,  95000.,  96000.,  97000.,\n",
-       "         98000.,  99000., 100000.]))"
+       "         98000.,  99000., 100000.]),\n",
+       " array([    0.,   100.,   200.,   300.,   400.,   500.,   600.,   700.,\n",
+       "          800.,   900.,  1000.,  1100.,  1200.,  1300.,  1400.,  1500.,\n",
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+       "         2400.,  2500.,  2600.,  2700.,  2800.,  2900.,  3000.,  3100.,\n",
+       "         3200.,  3300.,  3400.,  3500.,  3600.,  3700.,  3800.,  3900.,\n",
+       "         4000.,  4100.,  4200.,  4300.,  4400.,  4500.,  4600.,  4700.,\n",
+       "         4800.,  4900.,  5000.,  5100.,  5200.,  5300.,  5400.,  5500.,\n",
+       "         5600.,  5700.,  5800.,  5900.,  6000.,  6100.,  6200.,  6300.,\n",
+       "         6400.,  6500.,  6600.,  6700.,  6800.,  6900.,  7000.,  7100.,\n",
+       "         7200.,  7300.,  7400.,  7500.,  7600.,  7700.,  7800.,  7900.,\n",
+       "         8000.,  8100.,  8200.,  8300.,  8400.,  8500.,  8600.,  8700.,\n",
+       "         8800.,  8900.,  9000.,  9100.,  9200.,  9300.,  9400.,  9500.,\n",
+       "         9600.,  9700.,  9800.,  9900., 10000.]))"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "P_recoed"
+    "PdP_Velo_recoed = file[\"07_long_electrons_EndVelo_PdP_reconstructed;1\"].to_numpy()\n",
+    "PdP_Velo_recoable = file[\"07_long_electrons_EndVelo_PdP_reconstructible;1\"].to_numpy()\n",
+    "\n",
+    "PdP_Velo_recoable"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_733517/2776815717.py:1: RuntimeWarning: invalid value encountered in divide\n",
+      "  effs = np.divide(PdP_Velo_recoed[0], PdP_Velo_recoable[0])\n"
+     ]
+    },
+    {
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>0.777778</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>100 rows × 100 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          0         1         2         3         4         5         6   \\\n",
+       "0        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
+       "1   0.297453  0.351240  0.298851  0.466667  0.312500  0.000000  0.000000   \n",
+       "2   0.377146  0.362297  0.348505  0.342369  0.369942  0.291339  0.326471   \n",
+       "3   0.532556  0.543753  0.547119  0.547350  0.505400  0.514877  0.485997   \n",
+       "4   0.595858  0.616777  0.618738  0.601467  0.636095  0.606115  0.554913   \n",
+       "..       ...       ...       ...       ...       ...       ...       ...   \n",
+       "95  0.666667  1.000000  1.000000  1.000000  1.000000       NaN       NaN   \n",
+       "96  1.000000       NaN  1.000000       NaN  1.000000       NaN       NaN   \n",
+       "97  0.923077       NaN       NaN  1.000000  1.000000       NaN  0.000000   \n",
+       "98  0.846154  1.000000  1.000000       NaN       NaN  1.000000  1.000000   \n",
+       "99  0.777778  0.666667  1.000000  1.000000  1.000000  1.000000  1.000000   \n",
+       "\n",
+       "          7         8         9   ...  90  91   92  93   94  95  96  97   98  \\\n",
+       "0        NaN       NaN       NaN  ... NaN NaN  NaN NaN  NaN NaN NaN NaN  NaN   \n",
+       "1        NaN       NaN       NaN  ... NaN NaN  NaN NaN  NaN NaN NaN NaN  NaN   \n",
+       "2   0.328205  0.208333  0.237500  ... NaN NaN  NaN NaN  NaN NaN NaN NaN  NaN   \n",
+       "3   0.444846  0.426966  0.346939  ... NaN NaN  NaN NaN  NaN NaN NaN NaN  NaN   \n",
+       "4   0.496689  0.591224  0.518625  ... NaN NaN  NaN NaN  NaN NaN NaN NaN  NaN   \n",
+       "..       ...       ...       ...  ...  ..  ..  ...  ..  ...  ..  ..  ..  ...   \n",
+       "95       NaN  1.000000  1.000000  ... NaN NaN  NaN NaN  NaN NaN NaN NaN  NaN   \n",
+       "96       NaN       NaN       NaN  ... NaN NaN  NaN NaN  1.0 NaN NaN NaN  NaN   \n",
+       "97  1.000000  1.000000  0.000000  ... NaN NaN  NaN NaN  NaN NaN NaN NaN  1.0   \n",
+       "98       NaN  1.000000  1.000000  ... NaN NaN  NaN NaN  NaN NaN NaN NaN  NaN   \n",
+       "99       NaN  1.000000  1.000000  ... NaN NaN  1.0 NaN  NaN NaN NaN NaN  NaN   \n",
+       "\n",
+       "    99  \n",
+       "0  NaN  \n",
+       "1  NaN  \n",
+       "2  NaN  \n",
+       "3  NaN  \n",
+       "4  NaN  \n",
+       "..  ..  \n",
+       "95 NaN  \n",
+       "96 NaN  \n",
+       "97 NaN  \n",
+       "98 NaN  \n",
+       "99 NaN  \n",
+       "\n",
+       "[100 rows x 100 columns]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "effs = np.divide(PdP_Velo_recoed[0], PdP_Velo_recoable[0])\n",
+    "\n",
+    "df = pd.DataFrame(effs)\n",
+    "df"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x900 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# fig = plt.figure(figsize=(15, 7))\n",
+    "ax = sns.heatmap(\n",
+    "    effs,\n",
+    "    robust=True,\n",
+    "    square=False,\n",
+    "    cmap=colormaps[\"rainbow\"],\n",
+    "    xticklabels=False,\n",
+    "    yticklabels=False,\n",
+    "    vmax=1,\n",
+    "    cbar_kws={\n",
+    "        \"label\": \"Efficiency\",\n",
+    "        \"pad\": 0.005,\n",
+    "        \"shrink\": 1,\n",
+    "        \"ticks\": [0.2, 0.4, 0.6, 0.8, 1.0],\n",
+    "        \"aspect\": 15,\n",
+    "    },\n",
+    ")\n",
+    "ax.set_ylabel(f\"$P$ [MeV]\")\n",
+    "ax.set_xlabel(f\"$\\Delta P$ [MeV]\")\n",
+    "ax.patch.set_edgecolor(\"black\")\n",
+    "\n",
+    "ax.set_yticks([0, 19, 39, 59, 79, 99], [0, 20000, 40000, 60000, 80000, 100000])\n",
+    "ax.set_xticks([0, 19, 39, 59, 79, 99], [0, 2000, 4000, 6000, 8000, 10000])\n",
+    "ax.invert_yaxis()\n",
+    "# ax.set_ylim(0, 59)\n",
+    "# ax.set_xlim(0, 59)\n",
+    "\n",
+    "ax.patch.set_linewidth(2)\n",
+    "# ax.set_yticklabels([])\n",
+    "# ax.set_title(\"EndVELO to EndUT $x/X_0$\", size=35)\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()\n",
+    "# plt.savefig(\n",
+    "#     \"/work/cetin/Projektpraktikum/thesis/Efficiency_PdP_Velo_hist2d.pdf\",\n",
+    "#     format=\"PDF\")"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 58,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([6.4927e+04, 8.7210e+03, 5.4020e+03, 4.0560e+03, 3.3500e+03,\n",
+       "        2.8240e+03, 2.3990e+03, 2.0600e+03, 1.8280e+03, 1.5610e+03,\n",
+       "        1.5130e+03, 1.3480e+03, 1.2090e+03, 1.1250e+03, 1.0270e+03,\n",
+       "        9.3000e+02, 9.0200e+02, 8.2300e+02, 7.8100e+02, 6.7500e+02,\n",
+       "        6.8700e+02, 6.5400e+02, 6.6000e+02, 6.2300e+02, 5.3100e+02,\n",
+       "        5.1900e+02, 5.1200e+02, 4.4000e+02, 4.7200e+02, 4.6700e+02,\n",
+       "        4.1100e+02, 4.1300e+02, 3.7700e+02, 3.4600e+02, 3.5400e+02,\n",
+       "        3.3100e+02, 3.3400e+02, 2.8600e+02, 3.0600e+02, 2.8800e+02,\n",
+       "        2.7000e+02, 2.8100e+02, 2.5100e+02, 2.2500e+02, 2.7100e+02,\n",
+       "        2.3000e+02, 2.4100e+02, 2.1700e+02, 2.2900e+02, 2.0700e+02,\n",
+       "        2.2500e+02, 1.8500e+02, 1.9000e+02, 1.8600e+02, 1.9100e+02,\n",
+       "        1.9900e+02, 1.8400e+02, 1.8500e+02, 1.7200e+02, 1.5700e+02,\n",
+       "        1.5300e+02, 1.7100e+02, 1.3700e+02, 1.5200e+02, 1.4500e+02,\n",
+       "        1.4600e+02, 1.2900e+02, 1.3900e+02, 1.4300e+02, 1.3700e+02,\n",
+       "        1.1600e+02, 1.2200e+02, 1.2600e+02, 1.1900e+02, 1.1800e+02,\n",
+       "        1.3100e+02, 1.1400e+02, 1.0700e+02, 1.1700e+02, 1.1700e+02,\n",
+       "        1.1500e+02, 1.3000e+02, 8.7000e+01, 1.0300e+02, 9.9000e+01,\n",
+       "        1.0100e+02, 7.7000e+01, 8.6000e+01, 1.0500e+02, 7.6000e+01,\n",
+       "        8.5000e+01, 8.6000e+01, 7.4000e+01, 8.6000e+01, 7.9000e+01,\n",
+       "        6.8000e+01, 7.1000e+01, 7.9000e+01, 6.9000e+01, 6.3000e+01]),\n",
+       " array([    0.,   100.,   200.,   300.,   400.,   500.,   600.,   700.,\n",
+       "          800.,   900.,  1000.,  1100.,  1200.,  1300.,  1400.,  1500.,\n",
+       "         1600.,  1700.,  1800.,  1900.,  2000.,  2100.,  2200.,  2300.,\n",
+       "         2400.,  2500.,  2600.,  2700.,  2800.,  2900.,  3000.,  3100.,\n",
+       "         3200.,  3300.,  3400.,  3500.,  3600.,  3700.,  3800.,  3900.,\n",
+       "         4000.,  4100.,  4200.,  4300.,  4400.,  4500.,  4600.,  4700.,\n",
+       "         4800.,  4900.,  5000.,  5100.,  5200.,  5300.,  5400.,  5500.,\n",
+       "         5600.,  5700.,  5800.,  5900.,  6000.,  6100.,  6200.,  6300.,\n",
+       "         6400.,  6500.,  6600.,  6700.,  6800.,  6900.,  7000.,  7100.,\n",
+       "         7200.,  7300.,  7400.,  7500.,  7600.,  7700.,  7800.,  7900.,\n",
+       "         8000.,  8100.,  8200.,  8300.,  8400.,  8500.,  8600.,  8700.,\n",
+       "         8800.,  8900.,  9000.,  9100.,  9200.,  9300.,  9400.,  9500.,\n",
+       "         9600.,  9700.,  9800.,  9900., 10000.]))"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dP_Velo_recoed = file[\"07_long_electrons_EndVelo_dP_reconstructed;1\"].to_numpy()\n",
+    "dP_Velo_recoable = file[\"07_long_electrons_EndVelo_dP_reconstructible;1\"].to_numpy()\n",
+    "\n",
+    "dP_Velo_recoed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()\n",
+    "# plt.bar(\n",
+    "#     dP_Velo_recoable[1][1:],\n",
+    "#     dP_Velo_recoable[0] / np.max(dP_Velo_recoable[0]),\n",
+    "#     alpha=0.5,\n",
+    "#     color=\"#107E7D\",\n",
+    "#     label=\"p distribution, e\",\n",
+    "# )\n",
+    "plt.errorbar(\n",
+    "    dP_Velo_recoable[1][1:],\n",
+    "    dP_Velo_recoed[0] / dP_Velo_recoable[0],\n",
+    "    color=\"#107E7D\",\n",
+    "    label=\"Efficiency\",\n",
+    "    fmt=\"^\",\n",
+    "    ms=10,\n",
+    ")\n",
+    "plt.ylim(0, 1)\n",
+    "plt.xlabel(r\"$dp$ [MeV]\")\n",
+    "plt.ylabel(\"Efficiency of Long Tracks\")\n",
+    "plt.legend(loc=\"best\")\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()\n",
+    "# plt.savefig(\"/work/cetin/Projektpraktikum/thesis/Efficiency_dP_Velo.pdf\",\n",
+    "#             format=\"PDF\")"
+   ]
   },
   {
    "cell_type": "code",
@@ -164,7 +706,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.1.0"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/thesis_electrons.ipynb b/notebooks/thesis_electrons.ipynb
index cd7b05b..4471c89 100644
--- a/notebooks/thesis_electrons.ipynb
+++ b/notebooks/thesis_electrons.ipynb
@@ -16,8 +16,10 @@
     "from mpl_toolkits import mplot3d\n",
     "import itertools\n",
     "import awkward as ak\n",
+    "import seaborn as sns\n",
     "from scipy.optimize import curve_fit\n",
     "from utils.components import unique_name_ext_re\n",
+    "\n",
     "mplhep.style.use([\"LHCbTex2\"])\n",
     "plt.rcParams[\"savefig.dpi\"] = 600\n",
     "%matplotlib inline"
@@ -25,23 +27,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "50501"
+       "38525"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "file = uproot.open(\n",
-    "    \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_thesis.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
+    "    \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_upstream.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
+    "    # \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_def.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
     ")\n",
     "\n",
     "# selektiere nur elektronen von B->K*ee\n",
@@ -54,7 +57,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -63,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -71,36 +74,32 @@
     "found = electrons[~electrons.lost]\n",
     "lost = electrons[electrons.lost]\n",
     "\n",
-    "eloss_found = (found[\"p\"] - found[\"p_end_scifi\"]) / found[\"p\"]\n",
-    "eloss_lost = (lost[\"p\"] - lost[\"p_end_scifi\"]) / lost[\"p\"]\n",
+    "eloss_found = (found[\"p\"] - found[\"p_upstream\"]) / found[\"p\"]\n",
+    "eloss_lost = (lost[\"p\"] - lost[\"p_upstream\"]) / lost[\"p\"]\n",
     "\n",
-    "eloss = (electrons[\"p\"] - electrons[\"p_end_scifi\"]) / electrons[\"p\"]\n",
-    "eloss_magnet_found = ak.to_numpy(\n",
-    "    (found[\"p_end_velo\"] - found[\"p_end_scifi\"]) / found[\"p_end_velo\"]\n",
-    ")\n",
-    "eloss_magnet_lost = ak.to_numpy(\n",
-    "    (lost[\"p_end_velo\"] - lost[\"p_end_scifi\"]) / lost[\"p_end_velo\"]\n",
-    ")"
+    "eloss = (electrons[\"p\"] - electrons[\"p_upstream\"]) / electrons[\"p\"]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
     "eloss_velo_found = (found[\"p\"] - found[\"p_end_velo\"]) / found[\"p\"]\n",
-    "eloss_velo_lost = (lost[\"p\"] - lost[\"p_end_velo\"]) / lost[\"p\"]"
+    "eloss_velo_lost = (lost[\"p\"] - lost[\"p_end_velo\"]) / lost[\"p\"]\n",
+    "\n",
+    "eloss_velo = (electrons[\"p\"] - electrons[\"p_end_velo\"]) / electrons[\"p\"]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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AAACQRTrCxtTpdKJcLkfE+9BrMAQbVK/XI+L90sTe8dP04sWLkY4rFos6wgAAAIBM0xE2pnK53F/ueFunVa8z7OjoKBqNRtRqtdje3p5KDbVaLTqdTuzt7d25/9fnn38+lTEBAAAeM1dnhMdNEDaGdrs9tAn+1tbWrcc/e/Ysjo6OIuJ9aDatIKxSqUQ+n49KpTKV8wEAAAA8ZpZGjmEweCoWi3fu+7W5udm/3el0+qHYJI6OjqLdbtv3CwAAAGBEgrAxDG5QXygURvqZwf25Xr58OXENL168iFwud2c3GgAAAADvCcLuqdVqDd3/4osvRvq5wcBs0o6wVqsVrVYrOp1OLC0txdraWuzs7Eyl0wwAAADgsbJH2D0N7g0WESNfifHqca1Wa+RusquuLodst9tRq9X6nWqbm5vx5Zdfjn1+AAAAJjfNjfeB6dARdk+vX78eun/X/mA9n3766dD9k5OTsca/ulH/TY6OjmJ9fT12dnbGGgMAAADgMdIRdk/tdnvo/rgdYaenp2ONn8/no1qtRqfTidPT02g0Gtdq6qnVanFychLNZnOssQAAAAAeE0HYPX0odLqvTqcz9s9ub29fO1etVosXL15cO2+r1YpSqRTHx8djjwcAAADwGFgaeU/jBlhXl1C+eze9teK5XC729vbi/Pw86vX6tbEajUYcHBxMbTwAAACANNIRlpBJOsJus7m5GcViMTY2NoaucPnixYvY29ub2jhnZ2exuro68Xl2d3djd3d3ChUBAAAAD+nw8DAODw8nPs/Z2dkUqhmPIOyecrncVEKsUTfZH/fczWYz1tfX+2FYp9OJRqMRxWJxKmNcXl7G27dvJz7PxcXFFKoBAAAAHtrFxcVUsoAkCcLuaXl5eSpB2PLy8uTF3OHrr7+O9fX1/v3j4+OpBWFPnjyJlZWVic+zuLg4hWoAAACAh7a4uBhPnz6d+DxnZ2dxeXk5hYruTxB2T+N2cl0Nzx6yI6ynUChEsViMRqMREdPb6D8iYmVlJd68eTO18wEAAADzbVrbG62uribWWWaz/Hv6/PPPh+6P2h12dXP8tbW1aZV0q1KpNJNxAAAAAOadIOyeBpcaRozeZXV6ejp0f1pLFO+Sz+f7t2exHBMAAABgXgnC7ulqR9ioQdhg51gulxsKqB7S4DizWI4JAAAAMK8EYfdUKBSGAqXXr1+P9HMnJyf921fDtIc0OK5lkgAAAECWCcLGsLW11b/darVG+pnB4/b396de04cMLsmc1XJMAAAAgHkkCBvDzs5O/3bvioy3GTwmn8/PNJA6OjqKiIi9vb2ZjQkAAAAwjwRhYygUCkNhVi9s+pB6vd6/fVc3WK1Wi/39/ZH3HrvN0dFRtNvtyOVy8eWXX058PgAAAIA0E4SNqVqt9m+/ePHig8d1Op2o1WoR8X5p4vb29gePLZVKsbOzEwcHB7G2tja0wX7E+86ypaWlWFhYiFKpdOuyzHa7Hc+fP4+IiG+++cZG+QAAAEDmCcLGlM/n+51erVYrDg4ObjxuY2MjIt5fsXGwM+wmV5dZvnr1auh+vV7vh2ONRiPW19eHlmkOnmd9fT2Wl5fj9PQ0CoXCSP8nAAAAgMdMEDaBzc3NOD4+jlwuF/v7+1Eul6PVakWn0+mHUa1WKwqFQnz77bd3dmVd/fd8Pj90v1wuX/uZWq0WS0tLUS6XY2dnJ9bX16NUKsX29nY0m81r5wAAAADIKkHYhIrFYpyfn0elUol2ux0bGxv9YGp5eTnq9Xo0m82RlibW6/XI5/ORy+Vib2/v2qb6xWIxTk9PY3t7u39cT6vVinfv3sWXX37Zr8dySAAAAIDfWuh2u92kiyA9VldX4+3bt/H06dN48+ZN0uXc2//+f/4fSZcAAACQqJ99tpx0CUzBx8/+a9IljC3JbEFHGAAAAACZ8FHSBQAAAACz89V376Z2Lt1lpI2OMAAAAAAyQRAGAAAAQCYIwgAAAADIBEEYAAAAAJlgs3wAAABgLDbeJ210hAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEm+UzlrOzs1hdXb31mN3d3djd3Z1RRQAAAEDSDg8P4/Dw8NZjzs7OZlTNdYIwxnJ5eRlv37699ZiLi4sZVQMAAADMg4uLizvzgiQJwhjLkydPYmVl5dZjFhcXZ1QNAAAAMA8WFxfj6dOntx5zdnYWl5eXM6pomCCMsaysrMSbN2+SLgMAAACYI6Nsk7S6uppY15jN8gEAAADIBEEYAAAAAJkgCAMAAAAgEwRhAAAAAGSCIAwAAACATBCEAQAAAJAJgjAAAAAAMkEQBgAAAEAmCMIAAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgiAMAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMiEj5IuAAAAAOCr795N7Vw/+2x5auficdERBgAAAEAmCMIAAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgqtGMpazs7NYXV299Zjd3d3Y3d2dUUUAAABA0g4PD+Pw8PDWY87OzmZUzXWCMMZyeXkZb9++vfWYi4uLGVUDAAAAzIOLi4s784IkCcIYy5MnT2JlZeXWYxYXF2dUDQAAADAPFhcX4+nTp7cec3Z2FpeXlzOqaJggjLGsrKzEmzdvki4DAAAAmCOjbJO0urqaWNeYzfIBAAAAyARBGAAAAACZIAgDAAAAIBMEYQAAAABkgiAMAAAAgExw1UgAAADgUfnqu3dTO9fPPlue2rlIno4wAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAQCYIwgAAAADIBEEYAAAAAJkgCAMAAAAgEwRhAAAAAGSCIAwAAACATBCEAQAAAJAJgjAAAAAAMuGjpAsgnc7OzmJ1dfXWY3Z3d2N3d3dGFQEAAABJOzw8jMPDw1uPOTs7m1E11wnCGMvl5WW8ffv21mMuLi5mVA0AAAAwDy4uLu7MC5IkCGMsT548iZWVlVuPWVxcnFE1AAAAwDxYXFyMp0+f3nrM2dlZXF5ezqiiYYIwxrKyshJv3rxJugwAAABgjoyyTdLq6mpiXWM2ywcAAAAgEwRhAAAAAGSCIAwAAACATBCEAQAAAJAJgjAAAAAAMkEQBgAAAEAmCMIAAAAAyARBGAAAAACZ8FHSBQAAAADMq6++eze1c/3ss+WpnYvx6AgDAAAAIBMEYQAAAABkgiAMAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAQCZ8lHQBpNPZ2Vmsrq7eeszu7m7s7u7OqCIAAAAgaYeHh3F4eHjrMWdnZzOq5jpBGGO5vLyMt2/f3nrMxcXFjKoBAAAA5sHFxcWdeUGSBGGM5cmTJ7GysnLrMYuLizOqBgAAAJgHi4uL8fTp01uPOTs7i8vLyxlVNEwQxlhWVlbizZs3SZcBAAAAzJFRtklaXV1NrGvMZvkAAAAAZIIgDAAAAIBMEIQBAAAAkAn2CAMAAACYga++eze1c/23qZ0pW3SEAQAAAJAJOsLIhMPDw7i4uIj/91f/X/znP/wvSZcDM/M3v/ir+J+/+U38h48/NvfJFHOfLDLvySpznyz6m1/8Vfxv3/8Qi4uLd16hkWGCMDLh8PAw3r59G4uffOLNkUz521/+dVz88IO5T+aY+2SReU9Wmftk0d/+8q/j//m//u94+vSpIOyeLI0EAAAAIBMEYQAAAABkgiBsSg4ODqJUKsXS0lIsLCzE2tpalMvlaDQaj3psAAAAgLQQhE2o0WjE0tJS7O/vR0REvV6P09PTqFQq0Wq1olQqRalUik6n86jGBgAAAEgbm+VPoNFoRKlUioiI7e3tqFar/X/L5/OxubkZ6+vr0Wg0Yn19PZrNZuRyudSPDQAAAJBGOsLG1Ol0olwuR8T74GkwiBpUr9cjIqLdbvePT/PYAAAAAGklCBtTuVzuLznsLU28Sa87K+J9F1etVkv12AAAAABpZWnkGNrt9tBG9FtbW7ce/+zZszg6OoqI98HV9vZ2KscmOX/zi7+K//mb38R/+Pjj+M9/+F+SLufe0lx/mmt/DNL8+Ke59oj0159maX/s1c+40v7Yp7n+NNeedml/7NVPGgnCxlCpVPq3i8XinXtv9bqyIt4vazw6Ohr6u7SMTXL+9pd/HRc//BCLn3ySyhfoNNef5tofgzQ//mmuPSL99adZ2h979TOutD/2aa4/zbWnXdofe/WTRpZGjmFwiWGhUBjpZ/L5fP/2y5cvUzk2AAAAQJoJwu6p1WoN3f/iiy9G+rnB0Kq3VDFNYwMAAACknSDsngb354oY7ra6zdXjroZa8z42AAAAQNoJwu7p9evXQ/fv2qOr59NPPx26f3JykqqxAQAAANJOEHZP7XZ76P64XVmnp6epGhsAAAAg7QRh93Q1jBpXp9NJ1dgAAAAAaScIu6dxQ6SryxjfvXuXqrEBAAAA0m6h2+12ky4iTRYWFobuj/rwNRqNKJVK/fvFYjGOj49TM3bP7/7u78a//uu/RkTEkyeT56i///u/H7/3e7838XnucnZ2FpeXl7GwsBC/v7j44ONN2z9cXES321V/AtJce4T6k5Tm2iPUn6Q01x6h/iSlufYI9ScpzbVHpLv+NNceof4k9Wp/8uRJrKyszGzcf/zHf4x/+Id/mPg8l5eXERHxO7/zO/Ev//IvE5/vPj6a6WiPQC6Xm8rSwlE3up+XsXv+/d//vX+7N3En8cMPP8QPP/ww8XlG1e1242KG402b+pOT5toj1J+kNNceof4kpbn2CPUnKc21R6g/SWmuPSLd9ae59gj1J+ny8jLevn2bdBljG8wYZkUQdk/Ly8tTCaOWl5dTNXbPxx9/HP/8z//cT54nNauOMAAAAGAy0+wIW1hYiI8//ngKVd2PIOyexu2muhpgjdsRltTYPf/0T/809s8CAAAAJMlm+ff0+eefD90ftUPr6gb1a2trqRobAAAAIO0EYfe0vr4+dL/dbo/0c6enp0P3i8ViqsYGAAAASDtB2D1d7coaNYwa7N7K5XKRz+dTNTYAAABA2gnC7qlQKAztsfX69euRfu7k5KR/+2qglYaxAQAAANJOEDaGra2t/u1WqzXSzwwet7+/n8qxAQAAANJsodvtdpMuIm1ardbQfl13PYSNRiNKpVJEROTz+Wt7dqVlbAAAAIA00xE2hkKhMLTh/NHR0a3H1+v1/u27OrJqtVrs7+9/cP+vhxwbAAAA4DHTETamdrsda2trEfE+nGo2mzce1+l0YmlpKSLeX63x+Pj4g+cslUrRaDT698/Pz4f2BHvIsQEAAAAeOx1hY8rn8/1uq1arFQcHBzcet7GxERHvr9Y42J11k8EQLCLi1atXMxsbAAAA4LEThE1gc3Mzjo+PI5fLxf7+fpTL5Wi1WtHpdKLRaMT6+nq0Wq0oFArx7bff3tjdNejqv+fz+ZmNDQAAAPDYCcImVCwW4/z8PCqVSrTb7djY2IilpaUol8uxvLwc9Xo9ms3mSEFUvV6PfD4fuVwu9vb2hvYCe+ix59XBwUGUSqVYWlqKhYWFWFtbi3K5fK177rGNDUnNv1arFTs7O7G2thYLCwv9sff396PT6Tzo2BAxn6+9vefDXftywrjmcd73tFqtODo6ioODg7moh8clqbnf6XRif38/SqVS/zW+N3atVnvQscm2drsdpVJpZp8p5vn9JVFdmEPHx8fdXC7XjYhusVjsHh8fd09PT7v1er2bz+f7f39+fv6oxoak5t/5+Xl3c3OzGxG3/qlWq1MdF3rm9bV3b2+vP//r9fpMx+bxm8d5f35+3q1UKt1CodCNiG4ul+vu7e11j4+PffZhapKc+5VKpT+3K5VK9/j4uNtsNrvVarU/7/P5fPf4+HjqY5NdVz9rP/Rn6nl8f5kngjDmzvHxcf8FYnt7+8ZjBt+kpvnkTXJsSGr+nZ+f998QR/nzodpgXPP62jtYlyCMaZu3eX9+ft7d3t7u11QoFAQBPIgk534viCgUCh88ZvB50Gw2pzY22XR+fj70S7VZBGHz9v4yjwRhzJXz8/N+cp3P5z943Onpaf/JXSwWUz82JDn/isVi/0NhvV7vnp6e9n9jdNMbt0CAaZrX197Busx7pm3e5n21Wh2a77p/eShJzv1eJ1hE3PnFv/cLwlwuN5WxyaZKpdLN5/P9z9qzCMLm7f1lXgnCmCuDLxJ3vThMu7U0ybEhqflXrVa7EdHd29v74DGnp6f93xr1/vhgyLTM62vv5uZmN5/PD4UDgjCmZZ7m/eAvPPL5fPf09HTqY0BPknN/sNvxLpbFM6lmsznUUdj7zP3Qn2Pm6f1lngnCmBuDqfQov6mp1+tT+1Ke5NiQ5Pzr/ZbqvjVGhCUzTGxeX3t7H1abzaYgjKmbp3k/+CUol8tlcnkMs5Pk3B9cKra5uXnn8YNj3/bLQhhVs9l88CBsnt5f5p2rRjI3KpVK/3axWLzzapebm5v9251OZ6IrbyQ5NiQ1/1qtVrTb7ajX63cem8/nh+rs/TxMYh5fe9vtduzs7MTe3l4UCoWpnx/mZd5fvWpZ2q80zvxLcu632+3+7ft+fvn000/HHhd6ZvH6Oi/vL2kgCGNuDF6qeNQvH/l8vn/75cuXqRwbkpp/L1++jO3t7ZHfmIvF4tD977//fqxxoWceX3vL5XIUCoVrwS9MyzzM+1qtFo1Go3+/Wq0OjQEPIcm5v7y83L/dbreHgrGbvH79+sYaYJ7Nw/tLWgjCmAtXfzPzxRdfjPRzg0/wSbpikhobkpx/z549u9eX/atvqGtra2ONCxHz+dq7v78frVZrpC5JGMc8zPte1+Pgube3tyc6J9wl6bl/NcwafA7cpDdWLpcb6pqBeZX0cyxtBGHMhcHfSkaM/puXq8eNs1QrybEhyflXKBTu1abd6XRurQHuY95ee1utVhwcHOiM4UHNw7wvl8tD97/88suxzwWjSnruFwqFoS/8jUbj2nOhp1ar9TvGdAeTFkk/x9JGEMZcGGw/jhh9DfXVNfsnJyepGhvSNP+uLiO4ulQS7mPe5v7GxkZsbm7qjOFBJT3v2+320Jcc3S7MStJzPyLi66+/Hrp/dHR0LQxrNBr9brFqteo9gdSYh+dYmgjCmAtXv2CPm2Cfnp6mamxI0/wbfGP0wZBJzdPc730RuvolCaYt6XlfrVaH7vd+odELBNbW1mJhYSGWlpZifX09Dg4OrnUDwziSnvsR77vCri59Pzo6irW1tX5XcKlUinw+H8fHxz7rkCrz8BxLk4+SLgAirj9xxzXOh7Ukx4Y0zb/BL1D7+/sPPh6P27zM/aOjozg6Oorj42NXzOPBJT3vBzdSjni/gfj6+vq1pTCdTidarVa0Wq3Y39+Per2uc4yJJD33ezY3N6NarQ7tEdZut2N9fT0iIvb29iyHJJXm5TmWFjrCmAvjPuGufml59+5dqsaGtMy/weU0lUrFHkpMbB7mfqfTiXK5HNvb25b6MhNJzvt2u31t/FevXsXOzk6cn59Ht9uNbrcbp6en1zphyuVypjZRZvrm4TW/Z3t7+1p3ZE+j0chMEMDjMk/PsTQQhPGoJPnG5U2TJD30/Ov9djSfz8fe3t6DjgX3Mcnc39jYiHw+/8EvRDCvptEBn8vl4ttvv43t7e2hL0K958TV58Xz58991iFx05qD29vbNy59bLVa8aMf/SgzG4bDVVl5nReEMRemtRxlnPMkOTakYf61Wq2o1WqRy+Xi+Pj4wcYhW5Ke+wcHB9Fqta7tFwMPKcl5fzUIuxqAXXU1KOh0OvHixYt7jwsRyb/mX7WzsxO1Wi22t7evdbl3Op1YX1+/dhU+mGfz9hybd4Iw5sLy8nJi50lybEjD/Hv+/HlERHzzzTeWRDI1Sc793r5HlUolCoXCVOqAUSQ5769ugPzFF1/c+TNX94M8ODi497gQMV+fd0qlUtRqtdjb24tqtXrjcuDeccIw0mKenmNpIAhjLoybPF9t3ZxlR9g0xoZ5n387Ozv9rhmBAdOU5Nwvl8tRKBQs82Xmkpz345wjn89fe+23ZIxxzMvnnV6nV7FYHNoUv1qt3tghXC6XM7NUjHSbl+dYWgjCmAuff/750P1R33Cubua3traWqrFhnudfrVaLWq0W1WrV1cKYuqTm/sHBQbTb7VheXo5yuXznn8G6Xrx4MfRvNg/nvpJ8zR/3feJqzdO6MhnZMg+fd8rlcj/IvWlvyM3NzWg2m0NBQKfTcaVsUmEenmNp8lHSBUBE9C9Z3NNut0fqPrna5j/OVb+SHBvmdf41Go3Y2dmJarV643IBmFRSc//777+PiBhruUur1Rrqhsnn80Ji7iXJ1/yrv+Uf9UvS1S9FWbmiGNOV9Oeddrvd/+VFoVD44FYPhUIhms3m0Lyv1WpRqVQy0ylDOiX9HEsbHWHMhXF/2zj4IS6Xy421f1GSY8M8zr9WqxWlUikqlYoQjAczj3MfHloaP+9c/fKflf1jmK6kX/MHO8Cu1nLVTVcTPjk5GWtcmJWkn2NpIwhjLhQKhaEPWq9fvx7p5wbflO56U5vHsWHe5l+73Y6NjY3Y29uzfxIPKqm5X6lUotvtjvxn8ANhvV4f+rfB/WVgFEl/3hl0tQtgVFn5ksR0Jf15Z/DL/ihLv67+ItCSYOZd0s+xtBGEMTe2trb6t0fdiHXwuEnW7yc5NszL/Gu327G+vh7b29sjf8Fvt9uuIsbY5mXuwywlOe8Hl7yMujz46hJKF05hXEnO/cElvaOGwOY6aeNz1egEYcyNnZ2d/u1RPpwNHpPP5ydaz5zk2DAP86/T6USpVIqtra17dbmUy2Xzn7HNw9yHWUty3g9+yWm32yPtEzYYGnjOMYkk5/5gJ+M43V06IUkDn6tGJwhjbhQKhaEn311X4xq8xPFd6XWtVov9/f0PvvE95NhwlyTnfsT7EGx9fT3y+Xz/2Lv+NBqN/qacfmPKuJKe+5CEJOd9sVgc+kL/4sWLO+sd/KJkOTCTSHLuP3v2rH/75ORkpBB48FxZCgh4GKNeoOQ2vtNOURfmyOnpaTciuhHRLRQKHzzu/Py8f1yxWLz1nMVisX9sRHTPz89nNjaMKsm5XygUho67z59qtTrJfxsSnfujyOfz/fPU6/WxzwODkpz3zWZz6LjT09MPnvP4+Lh/3Pb29kj/N7hNknN/8Li9vb1bzzk49yuVyp3/L7hLvV4fmqf3nVe+006XIIy5M/gi8aEXiN4X91wud+cXnPt8cZ/22HAfScz9SUIwv0thWpJ83b+LIIyHkuS8r1ar/ePy+fyN5z4/P+/P/9u+TMF9JTX3z8/Pu7lc7s7jTk9P+8dlMSBg+gZfT0cJqW7iO+10+RbDXDo+Pu6/AW1ubnabzWb3/Py8e3x83H/SFgqFkZ60g294EdE9Pj6e2dhwX7Oc+5ubmxOFYLoDmKYkX/dvIwjjIc3L551cLtetVCrdZrPZbTab3Uql0v83r/U8hKTm/vn5eXd7e3uoE6ZarXabzWb3+Pi4u7e3N3bHDgw6Pz/vbm5uXuvkuvqnWCz2nwO38Z12ugRhzLVKpdItFApDH9SKxeK9vowcHx938/l8N5fL3dkGPe2xYVxJzn1IkrlPFiU576vVardYLA6NXSgUunt7e7cum4RpSGruN5vN7vb29tAvO/L5fHdzc7O7t7eX2XCA+eU77XQtdLvdbgAAAADAI+eqkQAAAABkgiAMAAAAgEwQhAEAAACQCYIwAAAAADJBEAYAAABAJgjCAAAAAMgEQRgAAAAAmSAIAwAAACATBGEAAAAAZIIgDAAAAIBMEIQBAAAAkAmCMAAAAAAyQRAGAAAAkBKlUikWFhZiZ2cn6VJSSRAGAAAAPEqlUim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",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -144,6 +143,74 @@
     "# )"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sorted_eloss_found = ak.to_numpy(ak.sort(eloss_found))\n",
+    "sorted_eloss_lost = ak.to_numpy(ak.sort(eloss_lost))\n",
+    "sorted_eloss = ak.to_numpy(ak.sort(eloss))\n",
+    "sorted_eloss_velo = ak.to_numpy(ak.sort(eloss_velo))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "nbins = 50\n",
+    "plt.hist(\n",
+    "    ak.to_numpy(eloss_velo),\n",
+    "    bins=nbins,\n",
+    "    density=True,\n",
+    "    alpha=0.6,\n",
+    "    histtype=\"bar\",\n",
+    "    color=\"#2A9D8F\",\n",
+    "    label=\"electrons\",\n",
+    "    range=[0.001, 1],\n",
+    ")\n",
+    "mean_eloss = np.mean(ak.to_numpy(eloss_velo))\n",
+    "plt.vlines(\n",
+    "    mean_eloss,\n",
+    "    ymin=0,\n",
+    "    ymax=3.5,\n",
+    "    colors=\"#F05342\",\n",
+    "    label=f\"mean: {np.round(mean_eloss,2)} $E_0$\",\n",
+    ")\n",
+    "median_eloss = np.median(sorted_eloss_velo)\n",
+    "plt.vlines(\n",
+    "    median_eloss,\n",
+    "    ymin=0,\n",
+    "    ymax=3.5,\n",
+    "    colors=\"#0B3954\",\n",
+    "    label=f\"median: {np.round(median_eloss,2)} $E_0$\",\n",
+    ")\n",
+    "\n",
+    "plt.xlabel(r\"$E_\\gamma/E_0$\")\n",
+    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.legend()  # loc=\"upper center\")\n",
+    "# plt.show()\n",
+    "plt.savefig(\n",
+    "    \"/work/cetin/Projektpraktikum/thesis/emitted_energy_velo_mean.pdf\",\n",
+    "    format=\"PDF\",\n",
+    ")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 7,
@@ -376,41 +443,135 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# magnet kick position\n",
+    "input_tree = uproot.open({\n",
+    "    \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_upstream.root\":\n",
+    "    \"PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
+    "})\n",
+    "array = input_tree.arrays()\n",
+    "\n",
+    "array[\"dSlope_yEndT\"] = array[\"ideal_state_9410_ty\"] - array[\n",
+    "    \"ideal_state_770_ty\"]\n",
+    "array[\"dSlope_yEndT_abs\"] = abs(array[\"dSlope_yEndT\"])\n",
+    "\n",
+    "array[\"dSlope_xEndT\"] = array[\"ideal_state_9410_tx\"] - array[\n",
+    "    \"ideal_state_770_tx\"]\n",
+    "array[\"dSlope_xEndT_abs\"] = abs(array[\"dSlope_xEndT\"])\n",
+    "array[\"x_EndT_abs\"] = abs(array[\"ideal_state_9410_x\"])\n",
+    "array[\"x_EndVelo_abs\"] = abs(array[\"ideal_state_770_x\"])\n",
+    "\n",
+    "array[\"y_EndT_abs\"] = abs(array[\"ideal_state_9410_y\"])\n",
+    "array[\"y_EndVelo_abs\"] = abs(array[\"ideal_state_770_y\"])\n",
+    "\n",
+    "array[\"z_mag_xEndT\"] = (\n",
+    "    array[\"ideal_state_770_x\"] - array[\"ideal_state_9410_x\"] -\n",
+    "    array[\"ideal_state_770_tx\"] * array[\"ideal_state_770_z\"] +\n",
+    "    array[\"ideal_state_9410_tx\"] *\n",
+    "    array[\"ideal_state_9410_z\"]) / array[\"dSlope_xEndT\"]\n",
+    "\n",
+    "# array[\"yStraightOut\"] = array[\n",
+    "#     \"ideal_state_770_y\"] + array[\"ideal_state_770_ty\"] * (\n",
+    "#         array[\"ideal_state_10000_z\"] - array[\"ideal_state_770_z\"])\n",
+    "# array[\"yDiffOut\"] = array[\"ideal_state_10000_y\"] - array[\"yStraightOut\"]\n",
+    "\n",
+    "not_e = array[(array.isProton)]\n",
+    "\n",
+    "array = array[(array.isElectron) & (array.fromB)]\n",
+    "stretch_factor = ak.num(array[array.lost], axis=0) / ak.num(array[~array.lost],\n",
+    "                                                            axis=0)\n",
+    "# stretch_factor"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# not_e"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "image/png": 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       "text/plain": [
-       "0.24996287312509283"
+       "<Figure size 1200x900 with 1 Axes>"
       ]
      },
-     "execution_count": 13,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "# magnet kick position\n",
-    "input_tree = uproot.open(\n",
-    "    {\n",
-    "        \"/work/cetin/Projektpraktikum/tracking_losses_ntuple_B_zmag.root\": \"PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
-    "    }\n",
+    "xmin: float = 5100\n",
+    "xmax: float = 5800\n",
+    "nbins = 100\n",
+    "\n",
+    "fig = plt.figure()\n",
+    "# plt.hist(\n",
+    "#     array[\"match_zMag\"],\n",
+    "#     bins=nbins,\n",
+    "#     range=[xmin, xmax],\n",
+    "#     color=\"#712F79\",\n",
+    "#     alpha=0.5,\n",
+    "#     label=\"e pred\",\n",
+    "#     density=True,\n",
+    "# )\n",
+    "# plt.hist(\n",
+    "#     not_e[\"match_zMag_def\"],\n",
+    "#     bins=nbins,\n",
+    "#     range=[xmin, xmax],\n",
+    "#     color=\"#107E7D\",\n",
+    "#     alpha=0.5,\n",
+    "#     label=\"K pred\",\n",
+    "#     density=True,\n",
+    "# )\n",
+    "# 87A330\n",
+    "plt.hist(\n",
+    "    not_e[\"z_mag_xEndT\"],\n",
+    "    bins=nbins,\n",
+    "    range=[xmin, xmax],\n",
+    "    color=\"#F05342\",\n",
+    "    alpha=0.5,\n",
+    "    label=\"proton\",\n",
+    "    density=True,\n",
     ")\n",
-    "array = input_tree.arrays()\n",
-    "array = array[(array.isElectron) & (array.fromB)]\n",
-    "stretch_factor = ak.num(array[array.lost], axis=0) / ak.num(array[~array.lost], axis=0)\n",
-    "stretch_factor"
+    "plt.hist(\n",
+    "    array[\"z_mag_xEndT\"],\n",
+    "    bins=nbins,\n",
+    "    range=[xmin, xmax],\n",
+    "    color=\"#87A330\",\n",
+    "    alpha=0.5,\n",
+    "    label=\"electron\",\n",
+    "    density=True,\n",
+    ")\n",
+    "plt.xlabel(r\"$z_{\\mathrm{Mag}}$ [mm]\")\n",
+    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
+    "plt.legend(loc=\"best\")\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()\n",
+    "# plt.savefig(\n",
+    "#     \"/work/cetin/Projektpraktikum/thesis/match_true_zmag_e_kaon.pdf\", format=\"PDF\"\n",
+    "# )"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -425,45 +586,198 @@
     "\n",
     "fig = plt.figure()\n",
     "plt.hist(\n",
-    "    array[array.lost][\"match_zmag\"],\n",
+    "    array[\"match_zMag\"],\n",
     "    bins=80,\n",
     "    range=[xmin, xmax],\n",
     "    color=\"#F05342\",\n",
     "    alpha=0.5,\n",
-    "    label=\"lost\",\n",
+    "    label=\"new\",\n",
     "    density=True,\n",
     ")\n",
     "plt.hist(\n",
-    "    array[~array.lost][\"match_zmag\"],\n",
+    "    array[\"match_zMag_def\"],\n",
     "    bins=80,\n",
     "    range=[xmin, xmax],\n",
     "    color=\"#107E7D\",\n",
     "    alpha=0.5,\n",
-    "    label=\"found\",\n",
+    "    label=\"default\",\n",
     "    density=True,\n",
     ")\n",
-    "plt.xlabel(r\"z$_{Mag}$ [mm]\")\n",
+    "plt.hist(\n",
+    "    array[\"z_mag_xEndT\"],\n",
+    "    bins=80,\n",
+    "    range=[xmin, xmax],\n",
+    "    color=\"#712F79\",\n",
+    "    alpha=0.5,\n",
+    "    label=\"true\",\n",
+    "    density=True,\n",
+    ")\n",
+    "plt.xlabel(r\"$z_{\\mathrm{Mag}}$ [mm]\")\n",
     "plt.ylabel(\"Number of Tracks (normalised)\")\n",
     "plt.legend(loc=\"best\")\n",
     "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
-    "# plt.show()\n",
-    "plt.savefig(\"/work/cetin/Projektpraktikum/thesis/match_zmag_lost_found.pdf\",\n",
-    "            format=\"PDF\")"
+    "plt.show()\n",
+    "# plt.savefig(\n",
+    "#     \"/work/cetin/Projektpraktikum/thesis/match_zmag_lost_found.pdf\", format=\"PDF\"\n",
+    "# )"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 16,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x900 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "brem vtx 2d hists in trackinglosses_energy notebook\n"
+    "bins = np.linspace(5150, 5700, 50)\n",
+    "ax = sns.regplot(\n",
+    "    x=ak.to_numpy(array[\"z_mag_xEndT\"]),\n",
+    "    y=ak.to_numpy(array[\"z_mag_xEndT\"]) - ak.to_numpy(array[\"match_zMag\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    "    label=\"bla\",\n",
+    ")\n",
+    "ax.set_ylim(-150, 175)\n",
+    "ax2 = ax.twinx()\n",
+    "ax2.hist(\n",
+    "    ak.to_numpy(array[\"z_mag_xEndT\"]),\n",
+    "    bins=50,\n",
+    "    range=[5150, 5700],\n",
+    "    color=\"#2A9D8F\",\n",
+    "    alpha=0.5,\n",
+    "    align=\"mid\",\n",
+    "    density=True,\n",
+    ")\n",
+    "ax.set_xlabel(r\"$z_{\\mathrm{Mag}}$ [mm]\")\n",
+    "ax.set_ylabel(\n",
+    "    r\"$\\left\\langle z_{\\mathrm{Mag}}-z_{\\mathrm{Mag}}^{\\mathrm{pred}}\\right\\rangle$ [mm]\"\n",
+    ")\n",
+    "ax2.set_ylabel(\"Number of Tracks (normalised)\")\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()\n",
+    "# plt.savefig(\n",
+    "#     \"/work/cetin/LHCb/reco_tuner/parameterisations/plots/magnet_kink_regression_plot.pdf\",\n",
+    "#     format=\"PDF\",\n",
+    "# )"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x900 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bins = np.linspace(-40, 40, 41)\n",
+    "ax = sns.regplot(\n",
+    "    x=ak.to_numpy(array[\"yDiffOut\"]),\n",
+    "    y=ak.to_numpy(array[\"yDiffOut\"]) - ak.to_numpy(array[\"match_yCorr\"]),\n",
+    "    x_bins=bins,\n",
+    "    fit_reg=None,\n",
+    "    x_estimator=np.mean,\n",
+    "    label=\"bla\",\n",
+    ")\n",
+    "ax2 = ax.twinx()\n",
+    "ax2.hist(\n",
+    "    ak.to_numpy(array[\"yDiffOut\"]),\n",
+    "    bins=30,\n",
+    "    range=[-40, 40],\n",
+    "    color=\"#2A9D8F\",\n",
+    "    alpha=0.5,\n",
+    "    align=\"mid\",\n",
+    "    density=True,\n",
+    ")\n",
+    "ax.set_xlabel(r\"$y_{\\mathrm{corr}}$ [mm]\")\n",
+    "ax.set_ylabel(\n",
+    "    r\"$\\left\\langle y_{\\mathrm{corr}}-y_{\\mathrm{corr}}^{\\mathrm{pred}}\\right\\rangle$ [mm]\"\n",
+    ")\n",
+    "ax2.set_ylabel(\"Number of Tracks (normalised)\")\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()\n",
+    "# plt.savefig(\n",
+    "#     \"/work/cetin/LHCb/reco_tuner/parameterisations/plots/bend_y_regression_plot.pdf\",\n",
+    "#     format=\"PDF\",\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x900 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "xmin: float = -30\n",
+    "xmax: float = 30\n",
+    "\n",
+    "fig = plt.figure()\n",
+    "plt.hist(\n",
+    "    array[\"match_yCorr\"],\n",
+    "    bins=80,\n",
+    "    range=[xmin, xmax],\n",
+    "    color=\"#F05342\",\n",
+    "    alpha=0.5,\n",
+    "    label=\"new\",\n",
+    "    density=True,\n",
+    ")\n",
+    "plt.hist(\n",
+    "    array[\"match_yCorr_def\"],\n",
+    "    bins=80,\n",
+    "    range=[xmin, xmax],\n",
+    "    color=\"#107E7D\",\n",
+    "    alpha=0.5,\n",
+    "    label=\"default\",\n",
+    "    density=True,\n",
+    ")\n",
+    "plt.hist(\n",
+    "    array[\"yDiffOut\"],\n",
+    "    bins=80,\n",
+    "    range=[xmin, xmax],\n",
+    "    color=\"#712F79\",\n",
+    "    alpha=0.5,\n",
+    "    label=\"true\",\n",
+    "    density=True,\n",
+    ")\n",
+    "plt.xlabel(r\"$y_{\\mathrm{corr}}$ [mm]\")\n",
+    "plt.ylabel(\"Number of Tracks (normalised)\")\n",
+    "plt.legend(loc=\"best\")\n",
+    "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
+    "plt.show()\n",
+    "# plt.savefig(\n",
+    "#     \"/work/cetin/Projektpraktikum/thesis/match_zmag_lost_found.pdf\", format=\"PDF\"\n",
+    "# )"
+   ]
   },
   {
    "cell_type": "code",
diff --git a/notebooks/trackinglosses_energy.ipynb b/notebooks/trackinglosses_energy.ipynb
index 56018b8..c18cf55 100644
--- a/notebooks/trackinglosses_energy.ipynb
+++ b/notebooks/trackinglosses_energy.ipynb
@@ -2,17 +2,18 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import uproot\t\n",
+    "import uproot\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "from mpl_toolkits import mplot3d\n",
     "import awkward as ak\n",
     "from scipy.optimize import curve_fit\n",
     "import mplhep\n",
+    "\n",
     "mplhep.style.use([\"LHCbTex2\"])\n",
     "plt.rcParams[\"savefig.dpi\"] = 600\n",
     "%matplotlib inline"
@@ -20,30 +21,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "40402 10099\n",
-      "50501\n"
+      "31836 6689\n",
+      "38525\n"
      ]
     }
    ],
    "source": [
     "# file = uproot.open(\"tracking_losses_ntuple_Bd2KstEE.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\")\n",
     "file = uproot.open(\n",
-    "    \"/work/cetin/Projektpraktikum/tracking_losses_ntuple_B_zmag.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
+    "    \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_upstream.root:PrDebugTrackingLosses.PrDebugTrackingTool/Tuple;1\"\n",
     ")\n",
     "\n",
     "# selektiere nur elektronen von B->K*ee\n",
     "allcolumns = file.arrays()\n",
-    "found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) &\n",
-    "                   (allcolumns.fromB)]  # B: 9056\n",
-    "lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) &\n",
-    "                  (allcolumns.fromB)]  # B: 1466\n",
+    "found = allcolumns[\n",
+    "    (allcolumns.isElectron) & (~allcolumns.lost) & (allcolumns.fromB)\n",
+    "]  # B: 9056\n",
+    "lost = allcolumns[\n",
+    "    (allcolumns.isElectron) & (allcolumns.lost) & (allcolumns.fromB)\n",
+    "]  # B: 1466\n",
     "\n",
     "electrons = allcolumns[(allcolumns.isElectron) & (allcolumns.fromB)]\n",
     "\n",
@@ -54,7 +57,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -119,6 +122,12 @@
        "    fromPairProd: bool,\n",
        "    fromSignal: bool,\n",
        "    fromStrange: bool,\n",
+       "    ideal_state_5000_qop: float64,\n",
+       "    ideal_state_5000_tx: float64,\n",
+       "    ideal_state_5000_ty: float64,\n",
+       "    ideal_state_5000_x: float64,\n",
+       "    ideal_state_5000_y: float64,\n",
+       "    ideal_state_5000_z: float64,\n",
        "    ideal_state_770_qop: float64,\n",
        "    ideal_state_770_tx: float64,\n",
        "    ideal_state_770_ty: float64,\n",
@@ -145,7 +154,10 @@
        "    match_distY: float32,\n",
        "    match_fraction: float32,\n",
        "    match_teta2: float32,\n",
-       "    match_zmag: float32,\n",
+       "    match_yCorr: float32,\n",
+       "    match_yCorr_def: float32,\n",
+       "    match_zMag: float32,\n",
+       "    match_zMag_def: float32,\n",
        "    mcp_idx: int32,\n",
        "    mother_id: int32,\n",
        "    mother_key: int32,\n",
@@ -157,6 +169,7 @@
        "    p_end_scifi: float64,\n",
        "    p_end_ut: float64,\n",
        "    p_end_velo: float64,\n",
+       "    p_upstream: float64,\n",
        "    phi: float64,\n",
        "    pid: int32,\n",
        "    pt: float64,\n",
@@ -198,7 +211,7 @@
        "<Record {all_endvtx_types_length: 7, ...} type='{all_endvtx_types_length: i...'>"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -209,7 +222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -237,7 +250,7 @@
        "<Record {lost: True, rad_length_frac: ..., ...} type='{lost: bool, rad_leng...'>"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -274,7 +287,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -347,15 +360,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "63793\n",
-      "50501\n"
+      "48551\n",
+      "38525\n"
      ]
     },
     {
@@ -385,7 +398,7 @@
        "<Record {event_id: 0, lost: True, ...} type='{event_id: int64, lost: bool, ...'>"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -405,7 +418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -423,7 +436,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -458,14 +471,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "50501\n"
+      "31836\n",
+      "6689\n"
      ]
     },
     {
@@ -495,7 +509,7 @@
        "<Record {event_id: 1, lost: False, ...} type='{event_id: int64, lost: bool,...'>"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -505,13 +519,14 @@
     "\n",
     "length_found = ak.num(ntuple[~ntuple.lost][\"brem_photons_pe\"], axis=0)\n",
     "length_lost = ak.num(ntuple[ntuple.lost][\"brem_photons_pe\"], axis=0)\n",
-    "print(length_found + length_lost)\n",
+    "print(length_found)\n",
+    "print(length_lost)\n",
     "ntuple[1]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -525,12 +540,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1200x900 with 1 Axes>"
       ]
@@ -572,15 +587,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "found:  44660 , lost:  19133\n",
-      "0.4284146887595163\n"
+      "found:  7000\n",
+      "lost:  6689\n",
+      "found:  7910 , lost:  12529\n",
+      "1.583944374209861\n"
      ]
     },
     {
@@ -588,40 +605,44 @@
       "text/html": [
        "<pre>[-3.61,\n",
        " -61.5,\n",
-       " -33.8,\n",
-       " -133,\n",
-       " -799,\n",
        " 65.2,\n",
        " -5.73,\n",
        " -26.6,\n",
        " -4.26,\n",
        " -396,\n",
+       " 10.7,\n",
+       " 26.2,\n",
+       " 19.6,\n",
        " ...,\n",
-       " -13.1,\n",
-       " -25.6,\n",
-       " -140,\n",
-       " -4.27,\n",
-       " -4.27,\n",
-       " -103,\n",
-       " 8.82,\n",
-       " 12.8,\n",
-       " -17.8]\n",
-       "---------------------\n",
-       "type: 44660 * float64</pre>"
+       " -38.9,\n",
+       " 17.6,\n",
+       " -168,\n",
+       " -74.7,\n",
+       " -500,\n",
+       " -566,\n",
+       " 4.2,\n",
+       " -20.3,\n",
+       " -59.9]\n",
+       "--------------------\n",
+       "type: 7910 * float64</pre>"
       ],
       "text/plain": [
-       "<Array [-3.61, -61.5, -33.8, ..., 8.82, 12.8, -17.8] type='44660 * float64'>"
+       "<Array [-3.61, -61.5, 65.2, ..., 4.2, -20.3, -59.9] type='7910 * float64'>"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "tuple_found = ntuple[~ntuple.lost]\n",
+    "tuple_found = tuple_found[:7000]\n",
     "tuple_lost = ntuple[ntuple.lost]\n",
     "\n",
+    "print(\"found: \", ak.num(tuple_found[\"brem_vtx_x\"], axis=0))\n",
+    "print(\"lost: \", ak.num(tuple_lost[\"brem_vtx_x\"], axis=0))\n",
+    "\n",
     "brem_x = ak.to_numpy(ak.flatten(ntuple[\"brem_vtx_x\"]))\n",
     "brem_z = ak.to_numpy(ak.flatten(ntuple[\"brem_vtx_z\"]))\n",
     "\n",
@@ -641,12 +662,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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       "text/plain": [
        "<Figure size 2000x800 with 3 Axes>"
       ]
@@ -656,8 +677,8 @@
     }
    ],
    "source": [
-    "vmax = 350\n",
-    "nbins = 200\n",
+    "vmax = 150\n",
+    "nbins = 150\n",
     "\n",
     "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20, 8))\n",
     "\n",
@@ -683,7 +704,7 @@
     "    density=False,\n",
     "    bins=nbins,\n",
     "    cmin=1,\n",
-    "    vmax=vmax * stretch_factor,\n",
+    "    vmax=vmax,  # * stretch_factor,\n",
     "    range=[[-200, 9500], [-3200, 3200]],\n",
     ")\n",
     "ax1.vlines([770, 990, 2700, 7500], -3200, 3200, colors=\"red\", lw=1.5)\n",
@@ -697,21 +718,21 @@
     "# plt.suptitle(\"brem vtx of photons w/ $E>0.1E_0$\")\n",
     "plt.colorbar(a0[3], ax=ax1)\n",
     "\n",
-    "# plt.show()\n",
-    "plt.savefig(\n",
-    "    \"/work/cetin/Projektpraktikum/thesis/brem_vtx_found_lost_hist2d.pdf\",\n",
-    "    format=\"PDF\",\n",
-    ")"
+    "plt.show()\n",
+    "# plt.savefig(\n",
+    "#     \"/work/cetin/Projektpraktikum/thesis/brem_vtx_found_lost_hist2d.pdf\",\n",
+    "#     format=\"PDF\",\n",
+    "# )"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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ZS2A0l8sNHW8Yhly/fl1EDp93o4KPbh/3/nMa9nMFAADgJFhaWhJN04b+E9RJuVyWTCYjc3NzommaLC0tSS6X8/UP+3HMOTYmAEf5fN4UkYGvdDpttlotx/vv7u6a9XrdLBQKZiKRGJinVquNvG+r1Rq6bxExd3d3j3Q8yWRy6HyVSsXTPIVCYeg8yWTSrNfrrubY3d01S6WSGY/He+fU6bjU/cbjccf99J/HdDrtam2qSqUy9Hiz2axZKBTMSqVi5vN5y2Ps9jmiPiajnhO7u7sD53qUbDbr6vGt1+uWcfl8fuS+u4+T+hWPx3uPef+YZDJptlqtgcfU7drUcf1fpVLJNM3hv5/ZbNYyz6jn6rBjdftYdNVqtd4xx+Nxs1KpmK1Wy2y1WmalUuk9H7rrHcbtY6COO+pzGQAAAO70v490el/Yr16vWz7j1Ot1s9VqmbVarff+0M1nn3HPOW4EnQAbW1tbth96g/oa9kdhd3fXrFQqIz/ki4iZSCTMSqXi+o/K1taWmU6nbddSKBRcBUm66vX6yCBWPB43s9msWalUzHq9bm5tbZn1et2sVCpmqVSy3C8ej7v+Iz4sEJdIJEYGuvqDAmowwovuH/larWbWajUzn8+b6XTaTCaTlsepe9xOgbfu82vUY5xMJnuBCruxiUTCzGazveeBGvhSgxTdOev1+sjnQyKRGBr42N3dtcyfTCbNQqFgGdP9mfo82t3ddTzeYfsslUq9/SUSCbNQKFie87u7u73j6D9nqv6gbzKZtDzfvDwWo1QqFTOdTlsCUN37jfodtfud7H8MWq2W7TintQEAAMA79R9+bj+v9N9v1D8Tu5+FEomEq89z45hzEjTTNE0BYFGtVsfSxHqYZDIpW1tblp9pmuZ5nng8Lru7u0Nvy+VyR0oFrdfrrkvQNjY25ObNm72SQbcSiYSsrq5KPp/31Oem2z9IPa54PC7Ly8sSj8fFMAzZ3Nzs9c2q1WqeS+oAAAAAnDyGYcgLL7xgaWdQq9UcL0TUf79EImG5gnE/Xdd7vWzT6bRtO45xzDkpBJ0ABMowDGk0GrK+vi66rvd654g8vex9IpGQl19+WbLZrOcG6k776+6zu5/l5WXJ5XIEmwAAAAC4lsvlpNlsyp07d3qBJzdBp0wm0+utVKlUJJ/P2+6j+090u7HjmHNSCDoBAAAAAAB8S7fyZWtrq3fFcRHnoFN/ppGIyO7urm01x8bGhuRyOREZXbkyjjkniavXAQAAAAAAiPSucFwoFAaupuyk/8rG6XTasX1IfwDLMIyhLVHGMeckEXQCAAAAAACQw/K0ZDJpCfa4Va1We9+7DVj1txtZX1+fyJyTRNAJAAAAAACceMViUZrNptRqNc/3VS+o9PLLL7u6X38gSc1KGseck0bQCQAAAAAAnGjNZlPK5bJUKpUjXeyo2+i7y+0c6rj+QNM45pw0gk4AAAAAAOBEW1lZkWw2e+Srvd2+fduy7dR7qevy5cuW7c3NzbHOOWkEnQAAAAAAwInVvdrba6+9duQ5dF23bB81K6nVao11zkk7FdqeAQAAAAAAQrSxsSEbGxtSr9ddZxINowaIjsowjLHOOWlkOgEAAAAAgBPHMAzJ5XKSz+clnU77nuso1EDXnTt3xjrnpJHpBCjOnz8vDx48ENM0JRazj8s+++yzcuHChQmtDAAAAECU3Lt3T9577z3bMZ1ORzRNk3Pnzsn9+/cntLLgLS8vy9e+9jVfc7g5X249++yz8r3f+72++hWtrKxIIpGQSqUSyJqCMI6spDAznQg6AYqHDx+KaZoicvgCYefu3bty9+7dSSwLAAAAwJQyTVMePHgQ9jJ8+drXviY7OzthL6Pn7t27voJg5XJZms2mbG1tBbKeeDweSHCnP0tpHHNOGkEnQDEzM9MLNh0106ndbkun05FYLCYLCwtjWacfY1mfaYr8wR8cfv9d3yWiab7n+QMR0SJ6DkWi/ziLnIA1BvW8cxD18xj19YmwxqCwRv+ivj4R1hiIvteHr8Vi8p1RXKNE/zxGfX0i4a/RbaaTiPT+sT3tYjGRhe84Wijh3r2OvHff/h/7bjjkBjhqNptSLBalVCpJMpn0vR4Rkfn5+UACRPPz82Odc9IIOgGKb//2b5ednR25cuWKbG9vH2mOxcVF2dnZkYWFhSPPMU5jWd/9+yLdANyXvyxy/rzvec6LyFxEz6FI9B9nkROwxqCedw6ifh6jvj4R1hgU1uhf1NcnwhoD0ff68OJ3fIf8fhTXKNE/j1Ffn8h0rLH7T22nf2hPi4XvOCVfbb4Q6hq+J/mW7LT3j3z/XC4nyWRSCoVCYGs6ajaRGlRSM52CnnPSCDoBAAAAAACXTOmI/2wlv2s4qnK5LLquSzqdllwu5zi+P4Bz8+ZNWV9f721fu3ZNstmsiBz2vGo2m5b7uQn2qE2+l5aWet+PY85JCzXo9OKLL4a5ewtN0+TLX/5y2MsAAAAAAABj8u6774qISKPR8HzfZrNpCQIlEole0CmVSlnG6rruqnSv1WpZtvuvojeOOSct1KBTq9USTdNCrW3t7l8bUx8QAAAAAACOkwMz7Eyn6FleXrZsuw0Q9WdSxeNxSSQSY51z0o5HUakPx6WZGwAAAAAAsFcqlcQ0Tddf/QGbWq1mua1UKvVuSyaTltK327dvu1rP5uZm73s1yDSOOSct9J5OpmlKNpsNLfJmGIZUq9VQ9g0AAAAAAI6Hq1ev9uIL/WV4dvrHFYvFicw5SaEHnarVqnziE58IdQ3ZbFY++MEPhroGJ7quS6lUkkajIbqu91LklpeXpVgsHjloVy6XpV6vy+bmphiGIYlEQpLJpKyurh657nNa5gQAAAAAeGOKSMdHI++g1hBFq6urvQCRm55R/WMSicTQz7bjmHOSQi+vC/sEiIi8/PLLYS/BVrlclqWlJalWq6LruogcZmg1m02pVquytLQk5XLZ05yNRkPm5uZ6Uc9arSatVktKpZI0m03JZDKSyWQGLrV4HOYEAAAAACBoyWTSEuPY2NiwHV+r1Xrfj8pIGseckxR6ptP8/HzYS4i0TCYjjUZD4vG4pNNpSSQSouu6NJvNXgBKRHrZTt3O+XYajYZkMhkREcnn81KpVHq3dedIpVLSaDQklUrJ1taW42UZp2VOHFpbW5O9vT25ePFi2Eux9bM3bsi5554LexkjTct5jLppOI9RX2PU1zctpuE8ssaTYRrO4TSssetv/I2/EfYSptY0PM7TsMZnn31W7t69K88++2zYS8EEVCoVWVpaEhGRmzdvjvyM3t/qJ51OSz6fn+icE2OGKBaLmXfv3g1zCaZpmqZhGGYsFgt7GQMKhYIpImapVBp6e6lUMuUws7D35WR3d9eMx+OmiJiJRGLkuFar1ZsznU4fizndunLliiki5pUrV0KdY+rcu2eaIodf9+6FPw9M0zwBz0WeL1Pj2D8XMTV4Lp4QU/L6wPPxZDguj3P3OL5rYca89wffE+rXdy3MTOycJhKJ3mfOWq3m6j61Wq13n1Gf55PJpCkiZjweN3d3d0OZcxJCLa8zI3TluCitReSwh1O3j1GhUBg6plAoDEQunRqL5XK5XimaXapdf9ZUo9GwbbY+LXMCAAAAADBu2WxW6vW6xONxKRaLksvlpNlsimEYvUqdZrMpyWRS3nrrLVcVO+OYcxJCDTqVSqVIpEFeunTJcqnDKCgWi1IqlRx7Xqnrtmsspuu65farV6/azn3t2jXLeqZ5TgAAAAAAvGq1WmKappim6aqdTVc6nZbd3V0plUqi67qsrKzI3Nyc5HI5mZ+fl1qt5rlFzDjmHLdQezp98pOfnOj+3n77bfnABz4QibU4MQxjZIZTv+5V7Lr9neyeXP0BqnQ67fhE7P+FMgxDNjY2Bn7JpmVOAAAAAAhKJpazbNc7tREjjyFT5CDsSqFoFSrZKhQKrj7bhz3nuIR+9bpJWl1dDXsJrtXrdddj79y50/t+eXl55Lj+0rNkMulq7kQi0ft+fX19aucEAAAAAACTdaKCTpubm2EvIXCGYfR6H6XT6ZFBGrXX08svv+xq/v751EszTsucAAAAAABg8kItrzuqt99+uxdocUPXdalUKp7uMy1ef/11ETnM9KnVRqd0qr2e+jOD7Kjjuo3JpmlOAAAAAEBwOmOsb/tHlffkf6zesx3zta8fjG3/CNZUBJ3efvttKZVK0mg0er2LvDJNUzRNC3hl4TIMQ1ZXVyWZTEqtVrPtfXT79m3LttvGYpcvX7Zsb25u9oI50zInAAAAAGA6vHevI3/wNYJKx0Xkg043btyQcrksIoeBIxzSdV0ymYzE43G5deuWY3BGDdYdNYOo1WpN3ZxhWFtbk729vUhcnREnG89FRAXPRUQFz0VECc9HTCNTTDkYY6bT+QuaLHynfSegP/x6RzqdsS0BAYp00OlXf/VXe1cy0zRNNE0j8CSHPYtyuadXS5ibm5NSqWTbvf6oGWKq/hLFaZkzDGtra6HuH+jiuYio4LmIqOC5iCjh+QgM+unVZ+WnV5+1HfNHUm1pf42o0zSIdNDp5s2bIiK9YFMikZBkMtnLalFLqoZ59913xTAMef311+Xu3btjXe84GYYh1WpVKpXK0MBMsViU27dvj+zrdNQgjJpB1X+lvGmZ86ja7bYsLi76nmdtbY03FAAAAECEZGI5y3a9M/g56jOf+Yx85jOfERGRb+7Yf76w+9zQbrePsELgeIh00KnZbPb6MNXrdVlZWTnyXIVCQV588cWgljZxjUZDWq2WpNNp0XV9oOG2yGEGVLlcts148mscGURRnbPT6cjOzo7vefb29nzPAQAAAGCy9vb2XH8eCOJzwzQZZyNxHC+RDjrF43G5e/euFAoFXwEnkcOePy+88EJAK5u8bDYr2WzW8rNqtSrFYtESYCkWi5LP5wcyf+LxeCCBmP55p2XOo4rFYrKwsOB7Hmr0AQAAgOlz8eJFuXLliog4Zzo9d2V+5G3tdls6NCDCCRXpoFMikZA333xTXn755UDmq1QqgcwTFfl8XtLptKRSKUugplqtDmQ7zc/PBxLMmZ+ft3w/DXMe1cLCgmxvb/ueBwAAAMD06W+ToZbjqerbw9uciByW3p20TCigK9JBp5WVFXnzzTcD6c/Tne+4SSQScuvWLUmlUr2f3b59e2DcUTN/1ACQmpU0DXMCAAAAgBeOQaYhPaBOkgMu8AWX7K9DGLKf/dmfFdM0pdlsBjLfL/zCLwQyT9Qkk0lL6d2wRuPLy8uWbbfZRGrAb2lpaermBAAAAAAAkxfpoNOlS5fk537u52R9fV3ee+893/Mdt/K6fteuXet9PyxQ058JJTI8MDVMq9WybKfT6ambEwAAAAAATF6kg04ih1edSyaTksvZpzc6eeuttwLLmIqiZDLZ+35YaZmaQeQ2mNMfwIrH45JIJKZuTgAAAABAMEwR6YT8RXHf9Ih0T6euer0uy8vL8uKLL0qxWHTdJPrOnTtiGIa0Wi15/fXXx7zK6FADNyKHQan+K8Pdvn174Gp4w2xubo6cd1rmBAAAAIB+Tj2Z1NvVHk/q9knv8QSMMhVBp9/8zd8UkcMSqtXV1SPNYZqmaJoW5LIipT8jKJPJDB1z9epVqVarIiKus776xxWLxamdEwAAAAAATFbky+t+6qd+SjKZjLz55puiaZqYpun56yToBl3i8fjIzKD+gF2j0XCcs39MIpEY2idpWuYEAAAAAATjQMxQvzA9Ip3p9Nprr/Waf3cDTkdxEgJPN2/eFJHDczZKMpmUdDrdC9JsbGzYlq7Vak9TREdlD03LnAAAAADQpZbHqQbK5TRrvkb9YD3oJQHHUqSDTmrAKZ1OSyaTkXg87rmv06uvvipvv/32GFcbrHK5LOvr65JOp+XGjRtDm4N3FYtFMQxDCoWCY/+jSqUiS0tLInIYqBo13jCMXolbOp2WfD4/9XMCAAAAAPw7OP55HQhIpINOzWZTNE2TeDwum5ub8sILLxx5ruvXr8vly5cDXN34GIbRy9hpNptSLpelUChIqVQaGJvL5WRjY0NKpZIUCgXHuROJhNRqNcnlcpa5VSsrKyJyWK7Xn0k0zXMCAAAAAIDJiXRPp252z40bN3wFnLpzvfTSSwGsavzi8bgkEgnLz8rlsszNzUkul5NisSiZTEbm5uZE5LDBupuAU1c2m5V6vS7xeFyKxWIvsGMYhjQaDUmlUtJsNiWZTMpbb71lm2U1bXMCAAAAAKLrF6r35U++/HXbr69/vRP2MuFSpDOdUqmU/OZv/uZAAOao7PodRc3W1pbcvHlTGo2G6LouhmGIyNOG4blcTmq12pEDLel0WnZ3d3tlfCsrK2IYhsTjcVleXpZareZYqjetcwIAAABAP7WHk9rzyevtx904Qz7v3evI175GUOm4iHTQaXV1VW7duiW6rgcy37RkOokcZjsNK6cLWqFQ8JQldZzmBAAAAABEy4ULMfnO77Qvyvr61zvSIS41FSIddMpms/LSSy/J+vq6/MzP/Izv+T7/+c/LRz7ykQBWBgAAAAAAgvZf58/Lf50/bzvmT7/8dbKhpkSkg04iIrVaTb73e79Xfu3Xfk1+/Md/3NdcN2/eJOgEAAAAALDlVE6nOknldqaIHIgW+howHSLdSFzk8Cpmr776qnziE5/wNc/du3d7/ZAAAAAAAAAwXpHOdPr85z8vIiLPPfeczM3NyYsvvnikptGGYcjrr78e9PIAAAAAAAAwQqSDTp/+9KflzTff7G2bpinlcvlIc5mmKZoWbgogAAAAAADTrkN9G1yKdNDp6tWrvZI4TdMIGgEAAAAA/NOsnWYGejZp9p1ojnPPJiBIkQ46ra6uyqc+9SnRNE1Mk1AqJqvdbsvi4qLtmLW1NVlbW5vQigAAAABEyWc+8xn5zGc+Yzum3W5PaDVA9EQ66HTp0iVJJpPy5ptvSqlUkmQyKfPz857n0XVdPv3pT8sXv/jF4BeJY6vT6cjOzo7tmL29vQmtBgAAAEDU7O3tOX5mOI7Cvnodpkekg04iIteuXZOlpSX55Cc/eeQ5XnrpJfmJn/iJIwWscHLFYjFZWFiwHXPx4sUJrQYAAABAYMyOr9u75XjvmF+WM3JOnrsy+rNmu92WTsdhf8AxFfmgUzqdltu3bwcy1/LyciDz4GRYWFiQ7e3tsJcBAAAAIKKe175Pnpfvk/r26B5Pi4uLJzIbChCZgqDTSy+9JKVSKZC5/ubf/JuBzAMAAAAAwElkSvjldXR8nh72Lfkj4oUXXghknn/4D/9hIPMAAAAAAADAXuQznYK0ubkZ9hIAAAAAACGrd0aXww3T7eF01PsfL5p0zLAbiYe9f7g1lUGnt99+WwzDcD1e13WpVCqe7gMAAAAAAICjm4qg09tvvy2lUkkajYboun6kOUzTFE0jGgoAAAAAADAJkQ863bhxQ8rlsogcBo4AAAAAAEB4xtlI/LOvvSf//Bfesx3zza8fjG3/CFakg06/+qu/2rtynaZpomkagScAAAAAgC+ZmWuW7frBurf70+NpbO7f68jXv0ZQ6biIdNDp5s2bIiK9YFMikZBkMimJREJERC5fvuw4x7vvviuGYcjrr78ud+/eHet6AQAAAADA0Z2/EJNv/84Z2zHf/PqBdDoTWhB8iXTQqdls9vow1et1WVlZOfJchUJBXnzxxaCWBgAAAADAiXQgsbHN/V9dvyT/1fVLtmP+j//ZNtlQUyLSQad4PC53796VQqHgK+AkIpJIJOSFF14IaGUAAAAAcLL5LVELk7pWtVwOQDDGF54MQLeM7uWXXw5kvkqlEsg8AAAAAAAAsBfpoFM3u+nOnTuBzgcAAAAAALwzRaRjaqF+cXmx6RHpoNPP/uzPimma0mw2A5nvF37hFwKZBwAAAAAAAPYi3dPp0qVL8nM/93NSKpWkVCrJs88+62u+SqUin/jEJwJaHQAAAACcXNPUw8lJvVOzbNPjCQhGpDOdRA6vOpdMJiWX8/dL/9ZbbwWWMQUAAAAAwEl1IFqoX5gekc506qrX67K8vCwvvviiFItFmZ+fd3W/O3fuiGEY0mq15PXXXx/zKgEAAAAAANA1FUGn3/zN3xQRkVarJaurq0eawzRN0TQiogAAAAAwDk4laWoJW5g8l89pSpGQ2bGdL0rHOg4HZuSLphARkQ86/dRP/ZRUq1UREdE0TUzTe596gk0AAAAAAACTFemg02uvvSaVSkVEjh5wEpEj3w8nW7vdlsXFRdsxa2trsra2NqEVAQAAAIiSd8wvy1fl9wd+3v85ot1uT3JJQKREOuikBpzS6bRkMhmJx+Oe+zq9+uqr8vbbb49xtThuOp2O7Ozs2I7Z29ub0GoAAAAARM2+PJFH8mDg506fI6aZKZp0Qr4mmUkz8akR6aBTs9kUTdMkHo/L5uamvPDCC0ee6/r163L58uUAV4fjLhaLycLCgu2YixcvTmg1AAAAwGR57lOk9D2qH6wHvaTgOPRoUo91VA+oUzIrZ+TcwM+fu/I0SaLdbkun0xkYA5wEkQ46xeNxuXv3rty4ccNXwKk710svvRTQynASLCwsyPb2dtjLAAAAABBRz2vfJ8/L9w38vL79NGi1uLh4rDOfADuRbjmfSqVERCSRSAQy32uvvRbIPAAAAAAAnFQHooX6hekR6Uyn1dVVuXXrlui6Hsh8ZDoBAAAAABBdtV/YlY1f3LUdc+fr+xNaDfyKdNApm83KSy+9JOvr6/IzP/Mzvuf7/Oc/Lx/5yEcCWBkAAAAAHG+OPZzU8VHu4aTwulanHk9ezxVGe//egXzzawSVjotIl9eJiNRqNdna2pJf+7Vf8z3XzZs3A1gRAAAAAAAn14EZG9vX2fOn5LnvtP+KRT6Sga5IZzqJHPZzevXVV+UTn/iE/PiP//iR57l79640m80AVwYAAAAAAIKU/cS8ZD8xbzvmY3/qK2RDTYlIB50+//nPi4jIc889J3Nzc/Liiy9KNpv1PI9hGPL6668HvTwAAAAAOLacSsjU21VRLjnzunbK6Y43XdelVCpJo9EQXdclHo9LIpGQ5eVlKRaLgV3cbNS+V1dXpV6vuxpfLpelXq/L5uamGIYhiURCksmkrK6uSjqdHts6jyrSQadPf/rT8uabb/a2TdOUcrl8pLlM0xRNo8s9AAAAAAB+dI7RFeTK5bIUi0XLzwzDkGazKc1mU6rVqpRKJSkUCp7mNQxD5ubmXI3N5/OOYxqNhuRyOTEMQ9LptNRqNUkkEtJsNqVYLEomk+n9PB6Pe1rrOEU66HT16tVeSZymaQSNAAAAAABAIDKZjDQaDYnH45JOpyWRSIiu69JsNkXX9d64braTl8qrarXqeqwa9FI1Gg3JZDIichigqlQqvdu660qlUtJoNCSVSsnW1lZkAk+Rbr+1uroqIocBJ9M0fX0BAAAAAAB/TBE5kFioX0F8wi8Wi9JoNKRUKsnu7q7UajUplUpSq9Wk1WpJqVSyjM/l7EsyVW4vZNYNdo1iGEZv34lEwhJw6lerHZZ86rruea3jFOlMp0uXLkkymZQ333xTSqWSJJNJmZ+3byg2jK7r8ulPf1q++MUvBr9IAAAAAIggv32Igu7hFKm+SJqSf2F2LJuZmWuWbXo8HS+6rvd6I43qg1QoFKTValkylprNpiSTScf5q9WqGIYhhUKhl6E0yvLysu3t3ZI6EfuMqG7G08bGhjQaDalWq67K9sYt0kEnEZFr167J0tKSfPKTnzzyHC+99JL8xE/8xJECVgAAAAAA4PgoFotSKpUcG2+XSiVL0KnRaLgKOpVKJUkkEgPZUl7pui6NRqO3ffXqVdvx165dk42NDRE5PMYoBJ0iXV4ncphqFlR5nFMEEQAAAAAA2DswY6F++dXNQnLSvYpd/7aTjY0N0XXdsU+TG/1Bq3Q67bj//p5ThmH0AlBhinym00svveQ7OtgV1DwAAAAAELSgS7b83t9riZnT/R33F6GStfrBumU7SmuDf/V63fXYO3fu9L53k8hy8+ZNicfjjllJbvRnWbnJsBKRXjN0EZH19XVPzc/HIfKZTiIiL7zwQiDzvPTSS4HMAwAAAAAAjjfDMHr9lNLptGPgp9lsSrPZFMMwZG5uTpaWlmR1dfVIGUfNZtOy/fLLL7u6X/8ao5DpFGrQKUqNvaO0FgAAAAAAokmTjsRC/RLRJnKkr7/+uogcZg91rw5nRy2p03VdqtWq5HI50TRNcrncQDBplP5eTt01uKGOc7u/cQk16JRKpWRvby/MJYiIyN27dyWVSoW9DAAAAAAAEAGGYcjq6qokk0mp1+uO/ZTUpt/DbGxsSCqVktXVVcf9375927Ltpp+UiMjly5ct25ubm67uNy6h9nQKqkF4EKK0FgAAAADHX+T7BJkdX3dX+yI5jp/k8fs8Nhxvuq5LJpOReDwut27dchXwSSQSUqlUxDAMabVa0mg0er2VVNVqVTY3N2Vra8t2Der8bqjjWq2Wq/uNS6hBJ02bTEqcG1FaCwAAAAAAUWSaIgdmuJ+fx5kzsrGxIbnc04Dw3NyclEolV1e7y+fzlm3DMKRarcrNmzd7vaG6ms2mZDKZkU3NRwWsvFL3O2mhlteRXQQAAAAAAMJkGIaUy2VZWlqyBJy6isXi0J87icfjUigUZHd3V2q12kDGVKPRkHK5PHJNR6Huo//qe2EINdNJROStt96SP/pH/2ioawi7xhHR1G63ZXFx0XbM2tqarK2tTWhFAAAAAKLkM5/5jHzmM5+xHdNutye0muj7l7/4dfnCP/mG73l2v/EkgNU81Wg0pNVqSTqdHtmbaWNjQ8rlsquMp2Gy2ayk02lZWVmxNPe+efPmked0I+xMp9CDTtevX5dPfepTEo/HZX5+fqL7vnPnjui6PtYHGNOr0+nIzs6O7ZgoNMIHAADAdIpcDyeF0/qcbo98z6o+6trUtY+yt7fn+JnhODo4YtHU/XsdufOHwQaMgpDNZiWbzVp+Vq1WpVgsWoI2xWJR8vm866beqng8LltbW5JKpXqBJ8MwpNFoSDqdHhgbRMDoqGsNSuhBp62trSOlqQXJNE16OmFALBaThYUF2zEXL16c0GoAAAAARM3FixflypUrtmPa7bZ0OjQuFxF55sKMzH/HrO95dr/xZOy94PP5vKTTaUmlUpbgT7Va9Z248tprr0kqlept1+v1gaDT/Px8IEGnSSf3qEIPOnWF1d+JYBNGWVhYkO3t7bCXAQAAACCi3LTbWFxcPHbZUB3zaJlOf/avLcif/Wv2/9h346d/+N9NJGMqkUjIrVu3LAGi27dv+543mUxKOp3ulfENaxp+1AwlNVB14jOdwm4mHvb+AQAAABxP01ReNozT+h2PTwv1ulWeOJbTTdGxIFjJZFKy2axsbGyISHBXlctkMkN7R3UtLy9bej8ZhuEqgKQ2Dl9aWjryGoMQatBpd3c3zN0DAAAAAADYunbtWi/oFFRj7kQi0ft+WAlcf3aVyGGwK5lMOs7barUs22rZ3qSFGnS6dOlSmLsHAAAAAAAemHL0RuJBrmGS+oM9QZWr9Qedhs25vLxs2XYbdOoPisXjcct+wkCOIAAAAAAAgAtqMOioNjc3e99nMpmB25PJpCUY5baXVP+8Qa3Vj9B7OgEAAADAtOrvBaT2NHLq4RT5nk8OfYwGejzNXLMOGPPlxezOvVeOj5VybJF/7BCo/j5OwwJER9FfBjeqBO7q1atSrVZFRCz9nez0jysWiz5WGAwynQAAAAAAgGsHphbq16R1AznxeFyy2Wwgc3Z7RBUKhZFjVldXe9/bNR0fNiaRSITez0mEoBMAAAAAAMBIN2/eFBGR1157LZD5NjY2RNd1icfjcuPGjZHjksmkJXDUDVSNUqs9zbiLQpaTCOV1AAAAAHBkfsqqol6SVT9Yt71dLTFTy/HGfXxBnvuBY8GxVi6XZX19XdLptNy4ccO2OXixWBTDMKRQKIzMcmo0GpLL5cQwDEmn01IqlUY2/dZ1Xa5fvy4iIrdu3XJsTF6pVGRpaUlEDoNfo9ZgGEavFC+dTks+n7edd1LIdAIAAAAAAC5p0pFYqF8iRy+xMwxDisWiNJtNKZfLMjc3NzIrKJfLSblcllKpJKVSaeSctVqtd9W4RqMhqVTKUhrX1b1tfn5eWq2Wq6vRJRKJXgZTd83DrKysiMhhCWB/xlPYCDoBAAAAAIATIR6PSyKRsPysG3zK5XJSLBYlk8nI3NyciBw2/LbruyRyGJxSVavV3pyrq6uSSqUkk8lIPp+Xra2tgTXYyWazUq/XJR6PS7FYlFwuJ81mUwzD6AWyms2mJJNJeeuttxyzpyaJoBMAAAAAADgxtra2pFAoSDKZtARoms2m6LouuVxO3nrrLanVaq6CQ+l0WlqtluTzeUkkEgNz3rlzR27cuCG7u7tSKpWOFBRKp9O9++u6LisrK72g1vz8vNRqNdna2opUwEmEnk4AAAAAcGT9vYCcegypfYOi3tPJab1OfZGifLxOa1Nv12ZmLNvmwcF4FjYlDszpzl+Jx+O25XJHkUgkpFKpBDrnMIVCwTHzKkqm+5kCAAAAAACASCLTCQAAAAAAuGKKSMdHI++g1oDpQNAJAAAAAL7Fa0mYl5KxKJWXHUWUy+U807wV/Zgd+zDHsTo3IXvjn+5I/Z/u2I65+43HE1oN/CLoBAAAAAAAIuHhvX0x/pCg0nFxooJOb7/9tnzgAx8IexkAAAAAAEytcTYSP3N+VuLfcdp2zN1vPBazM7YlIEAnKuiUy+Xk9u3bYS8DAAAAAAAMkf6ri5L+q4u2Yz71I/+GbKgpEfmg097enly8eNH3PG+++aY0m80AVoSTot1uy+Ki/R+7tbU1WVtbm9CKAAAAMG7j7MUz9X1/lD5I6vGot2uxcJtN23JIk1Efmw+e/UnLdufxYcDjHfPL8lX5/YH793+OaLfbR10lMPUiH3RKpVLy+78/+EvsxRe/+EVZWVkJaEU4KTqdjuzs2Dew29vbm9BqAAAAAETNvjyRR/Jg4OdOnyOm3YGMr7wOx0vkg06tVkvee+89efbZZ490/5//+Z+XT33qU2KapmhahCPtiJxYLCYLCwu2Y4LIwgMAAAAwnU7JrJyRcwM/f+7KfO/7drstnQ4NiHAyRT7oJCKysrIiv/d7v+fpPm+//bbkcjlpNptimvaXtwSGWVhYkO3t7bCXAQAAACCinte+T56X7xv4eX37aXne4uLisc98AkaZiqDT1taWfOhDH5LXX3/dVWZJN7tJRHoZTgSeAAAAAIRJ7RM0bT2e6gfrlu2B9TvcHmV+1xr1xy5YmnTMsKuIwt4/3JqKQkzTNOWNN96QRCIhv/VbvzVy3Be/+EV58cUXe+V0IkLACQAAAAAAIASRDzrF43HZ2tqSV199VQ4ODiSdTstP//RPD4y7ceOGpFIpabValuymF154QZrNpty5c0deeOGFEI4AAAAAAADg5Il8ed3Vq1flpZdekpdeekmuXbsmn/jEJ+TVV1+VRqMhtVpNTNOUXC4nuq5bgk2maUqpVJJPfvKTvblWV1dDPBIAAAAAx5nXcrmTVZIVbU6lj3jKlPCvXkct0/SIfNDp1Vdf7X1/6dIlqdVqUq1W5VOf+pQkk0kRkYFSumQyKbVabSCzqT8ABQAAAAAAgPGJfHnd22+/PfCzpaUlEZFeRpOmPW0iVqlUZHNz89iV0jWbTVldXZWlpSXRNE00TZOlpSUpFotiGMaR5y2Xy5LJZGRubq43Zy6Xk0ajceznBAAAAAB41zFjoX5hekT+0crlnqY17u3tybVr1+SVV16Ru3fv9oIv3UynbDYr165dC2upY2EYhuRyOUmlUlKtVkXX9d5tuq5LuVyWubk5qVarnuZtNBoyNzcnxWJRRERqtZq0Wi0plUrSbDYlk8lIJpPxFNCaljkBAAAAAMD4Rb68bmtrS/7BP/gH8pWvfKUXWOnv3dQtpXv11Vfl53/+5+XWrVvy2muvyY//+I+HvHL/DMOQVCplCTSNsrq6KltbW1KpVBzHNhoNyWQyIiKSz+ct90kkEpLNZiWVSkmj0ZBUKiVbW1sSj8ePxZwAAAAYL699jU6SaT83Tn2Oonx8Xtc+QFPyNcyOzxUBJ0PkM51ERAqFglSr1V5Gk4j0GoV3S+m631+6dEmy2ax86EMfkvfee88yz97e3qSX7ku3QXo3sNZqtaTVakmtVpNCoTAwvlqtysbGhu2c3cwpkcPAzaggVa12+AKh67ol22ya5wQAAAAA+HcgWqhfmB5TEXQSsWY3pdNpabVaA43Bk8mktFot+cQnPiFvvPGGzM3NyS/+4i/2bp+moES1WpVGoyGFQkG2trYkm81KIpHoZfiUSiVptVq9Zupd169ft503l8v1StG6JWvDdPcjcphxZFe+Ny1zAgAAAACAydHM/vShCIrFYpa+TZVKxTGwInIYgMjlcrK3tydLS0vyEz/xE1Iul+Xg4GDcSw7E0tKSJBIJqdfrtuN0Xe81Vu+q1+uSTqcdx+7u7tqWo21sbPQCdfF4XHZ3d6d2Ti8WFxdlZ2dHrly5Itvb277mOlHu3xe5cOHw+3v3RM6fD3cenAw8XwAAw0zw9aG/LMupnCzK5WfDOJWcHbfj7Tdw7A7ldXbHdlw+X3SP49J3nJG//Vs/Mrb9/M4/e1t+9//5ju2YvW88ErMjU39OT4KpyXRKp9Oyu7vrKuDUP/4jH/mIfOUrX5FyuTzmFQan2WyKruu90jE7iURCSqXSwP2H6R+XTqcd+x91M4hEDsvdhpXuTcucAAAAAAD/TBnv1ese3juQu3/4yPaLllrTYyqCTvl8Xt544w25dOmS5/vWajV5/fXXJeIJXRbr6+uSz+ddN8VWs5refffdoeP6S8/UsrxREomEZV3TOicAAAAAIPrOnD8lF7/jjO2XmniG6Ir81evi8bj843/8j33Nkc1m5Y033pAPfvCDAa1qvK5du2YJojhRAzNquZ3IYPbTyy+/7Hru7tXz1AyiaZkTAAAAADAd/sxfeUH+zF95wXbM3/8vf0v2/vDRhFYEPyIfdBrWm+io87z00kuBzDVubrN7uroNt7uGBawajYbjmGHUcc1ms7e+aZkTAAAAGJf+Xj5OPZCmndq3yKlnk9fxYXJ87KjnsuAKcnAr8klpr7/+emBzuemRNI26GT5dwwJ1t2/ftmy7Ld27fPmyZXtzc3Pq5gQAAAAAAJMX+aBTkF54wT5Fb1r1B1jy+fzQMWpg6qgZRK1Wa+rmBAAAAAAAkxf58jo4q1Qqve+LxeLQMWow56j6S/mmZU4AAAAAQFA06Zhh569Q3jctCDpNOV3Xe823S6XSyMygowZh1PK2O3fuTN2cR9Vut2VxcdH3PGtra7K2tuZ7HgAAAPjnta+Q0/j+2516GA3MPXPN+gOlb1CUeh6JDFmvcgmx49bT6h3zy/JV+X1XY89qz1i2n7sy3/u+3W4Hui5gmhB0mnKlUklEDsvLCoXC2Pc3jgyiqM7Z6XRkZ2fH9zx7e3u+5wAAAAAwWfvyRB7JgyPdN4jPEZFlihyEnelkhrt7uEfQaYo1m02pVqsSj8elXq/bjo3H44EEYvoziqZlzqOKxWKysLDge56LFy/6ngMAAADAZJ2SWTkj5450XzXTqdPh6nc4mQg6TbHr16+LiMitW7ccG27Pz88HEsyZn5+3fD8Ncx7VwsKCbG9v+54HAAAA0eG1ZM1pvN3tUSuP88qpXNBvaWKY3JRNPq99nzwv33f4A6WUUC2FVNW3n863uLh4vDOfABsEnabU6uqqNJtNqdVqkkwmHccfNfNHDQCpWUnTMCcAAAAAIBimiHRCbuRNdd30CLvlPI6gWq1KtVqVSqUi2WzW1X2Wl5ct226zidSG3EtLS1M3JwAAAAAAmDyCTlOm0WjI6uqqVCoVyefzru+XSqUs27quu7pfq9WybKfT6ambEwAAAAAATB7ldVOk2WxKJpORUqnkKeAkMphBpOu6q7K8/kyjeDxu6R01LXMCAAAAUZCZuWb9gVNfoJB7IA2sV+lrpPZFGuh7pM4XpR5PDmsd4PBYnTShX70OU4NnypTQdV1WVlakUChIoVDwfP9kMmnpc3T79m1X99vc3Ox9rwaEpmVOAAAAAAAweQSdpoCu65JKpSSfz0upVHJ9n3K5bPnZ1atXe983m01X8/SPKxaLA7dPy5wAAAAAAGCyKK+LOMMwJJPJyNWrV10HnEREcrmcvPbaa5afra6uSrVaFZHD3lBO+sckEomhfZKmZU4AAABgHPpLxhzLxaasRKt+sG57+0B5nXJ8YZcH2lLW6rVUcNoey6B1zPFdve7f/tLvy+/98ldsx9z75sOx7R/BItMpwgzDkFQqJYlEQorFoui67vjVaDR6zbjVXkjJZNISkNnY2LDdf6329EViVPbQtMwJAAAAAIi+R/f35b2vP7T9OuExv6lCplOErays9IJJS0tLnu5bqVRG/rw7182bNyWbzQ4dZxhGL9sonU7bNi6fljkBAAAAANF25vwpefbbz9qOufdNAk/TgkyniEqlUq77GQ0zKviSSCR6mUHNZnOg71PXysqKiBxeCa4/k2ia5wQAAAAA+GOKJgcSG9vX8l/6fvnp+p+z/Tr/3LmwTwNcItMpgnK53FgCTl3ZbFbq9brkcjkpFoty+/ZtuXHjhiQSCdnc3JRisSjNZlOSyaTcunXLcjW5aZ8TAAAACJJd3yK1T1CkexwNkZm5Zv2BU2qJ0gdpoE+SItTzoaxV7V/ltcfTtD22wKQQdIqgSWTspNNp2d3dlXK5LOvr67KysiKGYUg8Hpfl5WWp1WojS9qmfU4AAAAAwNGNs5E4jheCTidcoVCQQqFwIucEAAAAAADjQ9AJAAAAAI6ovwxLLbFyKrmKevmdWnLmxLEkzWPn57GeH2Utr8x+1Hq7QzkdAHcIOgEAAAAAANc6XJMMLvFMAQAAAAAAQOAIOgEAAAAAACBwlNcBAAAAwFEd494/vnsqeezhpAqyh9NAvymFeXDgaS1O8x13B1y9Di4d37+QAAAAAAAACA2ZTsAI7XZbFhcXbcesra3J2trahFYEAAAAIEreMb8sX5Xft/3c0G63J7giIFoIOgEjdDod2dnZsR2zt7c3odUAAAAAiJp9eSKP5IHj54bjxBSRTsjldWaoe4cXBJ2AEWKxmCwsLNiOuXjx4oRWAwAAgEjq61t03Pr8OPVUcjxetd+Vzx5PfnjuyaSsfdT4UzIrZ+ScPHdlfuRU7XZbOp3wjh0IE0EnYISFhQXZ3t4OexkAAAAAIup57fvkefk+qW+PDtAtLi6eqEwooB9BJwAAAAAA4FrH5JpkcIegEwAAAICpoZY5OZWATZLfcrSoHZvTehxL1pRyurCPxw9tZsaybXboKjQub372P8gX//mXbMe8/80HE1oN/CLoBAAAAAAAXDuQ8TUSf3R/X+5/naDScUHQCQAAAAAARMLp87Ny/tvP2Y55/5sPwuxLDw8IOgEAAAAAgEj4ox//QfmjH/9B2zG/9GOfJxtqShB0AgAAADA1otYXqH89Az2NNPtmy1E7FieZmWvWH6ipJsrx1g/WrfefYM8qv/tS1/7K7Ed9r+n40KRjjq+8zu0agqTrupRKJWk0GqLrusTjcUkkErK8vCzFYlESicSR5i2Xy1Kv12Vzc1MMw5BEIiHJZFJWV1clnU5HZs5xouU8AAAAAAA4kcrlsiwtLUm1WhVd10VExDAMaTabUq1WZWlpScrlsqc5G42GzM3NSbFYFBGRWq0mrVZLSqWSNJtNyWQykslkxDCMUOecBDKdAAAAAADAiZPJZKTRaEg8Hpd0Oi2JREJ0XZdms9kLQIlIL9spm806ztloNCSTyYiISD6fl0ql0rutO0cqlZJGoyGpVEq2trYkHo9PfM5JIegEAAAAACM4lWn1l5wN3DbBcrKJcOrcrNw+UG44QZ7PtVIa6Lh2h/FT/1g76JjTXzRVLBal0WhIqVSSQqEwcHu5XO5lFYmI5HI5MU3Tdk7DMCSXO3wuJBIJS3CoX61Wk6WlJdF1XXK5nNTr9YnOOUnT/0wBAAAAAABwSdf1Xm+kYQEnEZFCoSD5fN7ys2azaTtvLpfrlbf1B6xU/VlTjUZDqtXqROecJIJOAAAAAADgxCgWi1IqlRwbb5dKJct2o9EYOVbXdcvtV69etZ372rWnWZKjgknjmHPSCDoBAAAAAABXTBHpiBbql32RmzPDMEZmOPXrXsWuf3uU/gBVOp127KnU3x/KMAzZ2NiYyJyTRk8nAAAAABjBsTePU58jG8etD5B2ataybR4cWAf4OFcTpznkZyjHMu2P3Unjpd/RnTt3et8vLy+PHNdfzpZMJl3N3W1cLiKyvr4+0Kh8HHNOGplOAAAAAAAACsMwev2U0un0yMCP2uvp5ZdfdjV//3xqVtI45gwDQScAAAAAAODagamF+jUpr7/+uogcZg/VaqOz2dReT/0leXbUcf2BpnHMGQaCTgAAAAAAAH0Mw5DV1VVJJpNSr9dt+yndvn3bsu3Ue6nr8uXLlu3Nzc2xzhkGejoBAAAAPh233jxwr/+xVp8Hal+ggdsVUX8eaTMzlm21Z9NADydFpI5H7dmk9ptSbtdi1uwas2P/2EbqWINminTMkPNX/HYSd6DrumQyGYnH43Lr1i3HgE+3h1LXUbOSWq3WWOcMA5lOAAAAAAAActgHaWlpSXRdF8MwZG5uTsrlsu191ADRUXX7R41rzjCQ6QSM0G63ZXFx0XbM2tqarK2tTWhFAAAAAKLkHfM/ylfNLw/8vP9zRLvdnuSScASGYUi1WpVKpTI02FMsFuX27dsj+zodNbCjZlD1XylvHHOGgaATMEKn05GdnR3bMXt7exNaDQAAiLJjXUqDo1NLtqaNUmL2xpPPWbYHygUdjjdKJWhquZzIzNBxTvbNJ/JIHgz83OlzxLTrHLGZ97//lf9NvvT/+v/63v+DdwfPuR+NRkNarZak02nRdX2gibfIYQZUuVyWQqEQ6L77jSMriUwnIKJisZgsLCzYjrl48eKEVgMAAAAgak5ps3LGPCfPXZkfOabdbkunM+UByIA8uf9E3v/G+2EvY0A2m5VsNmv5WbValWKxaAnaFItFyefzA9lE8Xg8kOBO/7zjmDMMBJ2AERYWFmR7ezvsZQAAAACIqOe175fnte+X+vb6yDGLi4vHPvPJrdnzs/LMtz3je54H7z4QszPebuL5fF7S6bSkUilL8KdarQ5kO83PzwcSIJqfn7d8H/ScYSDoBAAAAAAAXDFFpCNHK6/7gY/9p/IDH/tPfa/h1z78K/JgAhlTiURCbt26JalUqvez27dvD4w7ajaRGlRSM52CnjMMBJ0AAAAA4IgyM9eebig9kAZ6HCm31w+s2TEDPZKc9j3uHknK+h3X53T8EWIeHNgPUI5F7QGlbkepXxWClUwmJZvNysbGhogMv6rc8vKyNJvN3rZhGK6CPWqT76WlpbHOGYaY8xAAAAAAAICT6dq1p8HlYSVv/ZlQIsMDU8O0Wi3LdjqdHuucYSDoBAAAAAAAXNKkY4b7JUcs7zuqZDLZ+35YttHy8rJl222AqD+AFY/HJZFIjHXOMFBeBwAAAGBqhV7WZFdC5lBu5rWcTjXuY9VmZizbA42b1WN3KKdT1xvmY6edmrVsm/tPbMc7leNRTndyqMEgkcOgVP/V5m7fvj1wNbxhNjc3R847jjnDQKYTAAAAAADACP1ZRplMZuiYq1ev9r7v78Vkp39csVicyJyTRtAJAAAAAAC41jFjoX5NWjeQE4/HR2Ybra6u9r5vNBqOc/aPSSQSQ3svjWPOSSPoBAAAAAAAMMLNmzdFROS1114bOSaZTFqCPN2r3Y1Sqz0tyRyVkTSOOSeNnk4AAABAxITep2iKRPrcOPQ4UkXtWAb6GKk9qhw4Hc84j9fxd0h5bNT+VQM0bz2gjrvDZt7Tq1wuy/r6uqTTablx48bQ5uBdxWJRDMOQQqHg2FOpUqnI0tKSiBwGqkaNNwxDqtWqiBxeXS6fz090zkki0wkAAAAAAJwIhmFIsViUZrMp5XJZ5ubmRmYF5XI5KZfLUiqVpFQqOc6dSCR62Ubd+YdZWVkRkcNyvf7spEnNOUkEnQAAAAAAwIkQj8clkUhYftYNPuVyOSkWi5LJZGRubk5ERFqtlhQKBdfzZ7NZqdfrEo/HpVgsSi6Xk2azKYZhSKPRkFQqJc1mU5LJpLz11lu2WVbjnHNSCDoBAAAAAABXTBHpiBbql+nzGLa2tqRQKEgymbQEaJrNpui6LrlcTt566y2p1WoDASo30um07O7uSqlUEl3XZWVlpRfUmp+fl1qtJltbW56CQ+OYcxI00zT9Pl7AsbK4uCg7Ozty5coV2d7eDns50+P+fZELFw6/v3dP5Pz5cOfBycDzBQAwzARfHzIz155ueOzh5CTonkdee4Wp4wcoPZ7UvkhqT6j6wbrDCifH8rjJ4NrU29Vje+Pxr1jH25zb4/L5onscZ7/tvPzZf/GXQl3L//sv/JI8/Mb9qT+nJwGZTgAAAAAAAAgcV68DAAAAAACuTfvV6zA5BJ0AAAAATC2vJWNB398PdV+O5WwB78+R5lAYo5QTmvv25YVOxzfJc6+uXS2nU29/47FSfjfmx+ok+8rnvihfWf93tmMevvv+hFYDvwg6AQAAAACASHhy/7E8/Mb9sJeBgBB0AgAAAAAAro2zvO7UM2fk7LfZN/9/+O77Ih2uiTYNCDoBAAAAAIBIWProH5Olj/4x2zFvfOSfkQ01JQg6ASO0221ZXFy0HbO2tiZra2sTWhEAAABUfvsA+e4j1Nf7x6lHkzYzY3v7RHsaudm/0tfIqceTdmrWeveDA+v8B9a+SJGmHOsrsx+13vytY33n4EvyTudLA3fv/xzRbrfHsEBgOhB0AkbodDqys7NjO2Zvb29CqwEAAAAQNfvyRB7Jg4GfO32OmHZcvQ5uEXQCRojFYrKwsGA75uLFixNaDQAAAICoOSWzckbODfz8uSvzve/b7bZ0OvZX9gOOK4JOwAgLCwuyvb0d9jIAAAAwJTIz12xvN9XGx0oJ16TL7RznV9bnVB6nrn+Sx+d5bodjU8vpBh4784mIiHyPLMn3aEu2+1tcXDx2mU9kOsEt+6JcAAAAAAAA4AgIOgEAAAAAACBwlNcBAAAAAABXTBHpSLjldabzEEQEQScAAAAAOKL+Xj5OfYXUnk9OPZLCpsXsAwtOPZxU4+xR5Xlu09rY2+lY1HNhHliHT7ofFzAtKK8DAAAAAABA4Mh0AgAAAAAA7pha+FevC3v/cI2gEwAAAADXTnoZkZfjHyjZ8jFXGMyOtXOOWh7oRJuZsb2/1/LCIM+XurY3nnzOsv3K6Y9ZxyvlddqpWcv2bzz45SOvBTjOKK8DAAAAAABA4Mh0AgAAAAAAroVeXoepQaYTAAAAAAAAAkemEwAAAADXotZ3KGyWPkWa8j99s2N/Z2W8355HQVP7GKk9npyO19y3bvt97gT53BvoV+XQf0uUHk7mwWPb+/N7cnTvvN6Ur9aatmMe3bk/odXAL4JOAAAAAADAtXGW1z25/1geffPe2ObHZBF0AgAAAAAAkXDq/Gk589wF2zGP7twXUTPvEEkEnQAAAAAAgCumjDfTaTG7LIvZZdsx/+u1qjwmG2oqEHQCAAAAEJqo9cJxWo+6bRmv9jhSaDMzlm21r1DYPZy8Uter9qRSRemxVh8LUYIo5sGBdfzsKdvbw37eAlHF1esAAAAAAAAQODKdAAAAAACAa+YYy+twvBB0AgAAAMYsSmVFqrDXFvT+MrGcnDX35QuTWo9DSV2/N558zrKtnvuoUUvIVI7rV85NlJ73Ynasm+qxKmvvPHxkvVkpz1NLC6etVBIYF4JOwAjtdlsWFxdtx6ytrcna2tqEVgQAAAAgSt45+JK80/nSwM/7P0e02+1JLgmIFIJOwAidTkd2dnZsx+zt7U1oNQAAAACiZl+eyCN5MPBzp88R064jlNfBHYJOwAixWEwWFhZsx1y8eHFCqwEAAAAQNadkVs7IuYGfP3dlvvd9u92WTqczMAY4CQg6ASMsLCzI9vZ22MsAAADHwCR72Xjt0RSpPjsBqHdqIvfvi1y4EMh8Xs6n2sdHve9ADyQP/aCiQO1jpK5/oC+S0jcp6L5H/efT6/NYOzVr2TY7pig/sB//rWP9HnlRvif24sD4+vbT9SwuLh77zCdgFIJOAAAAAADAtQ5Xr4NL0xVaBwAAAAAAwFQg0wkAAOCIwr7UPJ7isXjqJB/7ODiez76yqoHyOZVaTmdOV5+fgfI5sW6r5Xdmx3q8fsvpVHaPjdPfhM6jh/aTK4+VFrNm9pj70/XYAWEh6AQAAAAAAFwzKa+DS5TXAQAAAAAAIHAEnaaIruuSyWRkY2PD1zzlclkymYzMzc2JpmmytLQkuVxOGo3GsZ8TAAAAAOBPx9RC/cL0oLxuChiGIdevX+8Fm3I5h1rxERqNhuRyOTEMQ9LptNRqNUkkEtJsNqVYLEomk+n9PB6PH6s5AQDHl59LZvtF75zo4LFAUJx6AQ30berr/aP2LMrMXFOGKn2BOlOeA6D0PRrs+WQ1yd5rjnM79Gwa6L+ljj81a9k29594Wh9Ga//q70n787dtxzy+c39Cq4FfBJ0izDAMuXnzppTLZd9zNRoNyWQyIiKSz+elUqn0bkskEpLNZiWVSkmj0ZBUKiVbW1uOAZ1pmRMAAAAAMB32338sj795L+xlICBTHlo/vsrlsqRSKWk2m77nMgyjlx2VSCQsgZx+tdrhfwN0XXfMppqWOQEAAAAAwTFFE9Mc39fMuTMy+9yztl+iZqYhsgg6RVCz2ZR0Oi2tVkvq9frI4Itb3VI1EZFisThyXDeTSOQw46harU79nAAAAACA6bHwE39ckp/967Zfs/MXwl4mXNJM0zTDXgTsNZtNSaVSve1KpSL5fN7VfXVdl6Wlpd727u6ubTnaxsZGL3soHo/L7u7u1M55VIuLi7KzsyNXrlyR7e3twOY99u7fF7nwrT/+9+6JnD8f7jw4GXi+AIGaZL+V44ZzFzETfH2w9G0yO/aDlb5Aag+oqFF7UvmmnJ9x/p4M9N5SaDMzlm2nflSx06ct250n+9YBNsd2XD5fdI9j9rlnJfnZvx7qWpof/0fy5JvvTf05PQnIdJoCfnoWlUql3vfpdNpxrm4GkchhuduwK+VNy5wAAAAAgICZEbh6HakzU4Og0zHXX3qWTCZd3SeRSPS+X18f/O/LtMwJAAAAAADCw9XrjjG1CfnLL7/s6n7JZFJ0XRcRGcggmpY5AQCAd5SEHR3n7imnsqZpP1cDx9dfMqc5/E9fKcGK+rnSlGbNZkdJL1GOZ6BkTR3vdH486j9/6rlyOndq6aA6/pXZj9ref+Dc2FfnAScWmU7HWKPRsGz3ZwbZUcf1B4WmZU4AAAAAwHiYZrhfmB4EnY6x27dvW7bd9oa6fPmyZXtzc3Pq5gQAAAAAAOEi6HSMdUvPuo6aQdRqtaZuTgAAAAAAEC56Oh1jajDnqAzDmLo5AQAAEI6w+xCNm3p8/b2BBnoa7T+x3lntaaT0RIoatSdTbNb68bHzZN86/iDYxkZqzyuvfZv87Et9rLRT1m2zYz324/68V3VEcx4ECEGnY+2oQRi1vO3OnTtTN2cQ2u22LC4u+p5nbW1N1tbWAlgRAAAAgEl5x/yP8lXzy4cbD9UgizUgZ/e5od1uB7wyYHoQdIKjcWQQTcOcnU5HdnZ2fM+zt7cXwGoAAAAATNK++UQeyQNXY4P43DBNTJNMJ7hD0OkYi8fjgQRi+jOKpmXOIMRiMVlYWPA9z8WLFwNYDYDjzKl8AMDx5+fvQNh/Q8Lef5So5WXquXhl9qPKeOv9B0r3HM7tuM997PRpy/ZvPPhl6/77SgtFZLAkLWYNTDiV34X5XIqdOWvZ7jx+LKe0WTljnht+B00JuiiXVHvuynzv+3a7LZ1OtEspgXEh6HSMzc/PBxLMmZ+ft3w/DXMGYWFhQba3twOdEwAAAMB0eF77fnle+/6ht8XOnrFsdx5YM6Lq208DZouLiycuEwroIuh0jB0180cNAKlZSdMwJwAAAABgPDqU18GlmPMQTKvl5WXLtttsIrUh99LS0tTNCQAAAAAAwkWm0zGWSqUs27quSzKZdLxfq9WybKfT6ambE8Dxl4nl5Ky5L18IeyEBOMn9T4CTKsjeNX7/hvhdy3H/G+bp/JjWvj3qfbVTs8odrD2OvD4W4z73ag8mtSeVerwDPZ2U43Xq6TTJ55JTvyltZsZ223yyP56FQb7xa/9GvvEv/q3tmCe79ya0GvhFptMxpmYQ6bru6n79mUbxeFwSicTUzQkAAAAAGA/THN/X/vuP5Mm779l+Scd0XiQigaDTMZZMJi19jm7fvu3qfpubm73v1YDQtMwJAAAAAJg+M8+ckdnLz9p+SYyeUtOC8rpj7urVq1KtVkVEpNlsurpP/7hisTi1cwI43uqdmsj9+yIXLoS9FGBsuBT98RV0SZyfuXleeTNw7vtLypTysoHyM3VbEbXHQpu1flxUr9A2UE6nBAI6jx562p/T37wg/ybGzp2zbHcePrJsO5UCOt2Oo/u2v/An5Nv+wp+wHfMf/sr/cJjxhMgj0+mYW11d7X3faDQcx/ePSSQSQ/skTcucAAAAAIBgmSJimlq4XwEfU7PZlNXVVVlaWhJN00TTNFlaWpJisej6QldHpeu6ZDIZ1+PL5bJkMhmZm5vrrTOXy7n6HB0Ggk5TwM+TPJlMWgIyGxsbtuNrtaf/LRiVPTQtcwIAAAAAMIphGJLL5SSVSkm1WrX0F9Z1XcrlsszNzfWqcrzO3Q1g2X0tLS256k/caDRkbm6u9/m3VqtJq9WSUqkkzWZTMpmMZDKZsQfJvCLoNAXUxtpen0SVSqX3/c2bN0eOMwyj98uUTqcln89P/ZwAAAAAAKgMw5BUKuWY8CByWJnTX53jhpdAlVMiRaPR6AWU8vm81Ot1SafTkkgkJJvNSqvVkmQyKY1GQ1KpVKQCT5ppmrR9j7DuL0J/4CmZTMrW1paneTY2NiSXO6yBLpVKUigUBsakUilpNpsSj8flrbfesjT3nuY5vVpcXJSdnR25cuWKbG9vBzr3sdbfW+fePZHz58OdB75FvZdMJpaTs+a+fEH+xeEPeL6cGH6em1F/Xk8a5wNR4Pd5OPT+E3w/Ydm/0uOofrA+eqyIaKdmLdvm/hPr/UP+nczMXPM0XpuZsWwP9D1SelqFeXyvnP6YZVtdq9qfylSuljZwu3L//mM7Lp8vusdx6vKz8gP/5L8JdS1f+mv/vey/+56vc5rJZKTRaEgymZQbN25IMpkUkcNSu9u3b0u5XB64T61Wk2w262r+ubk5V8GfdDot9Xp95O2GYcgLL7wghmFIIpGQVqs1dJyu67K0tORqzkki0ymCuil+3TpNNdOp2WyKpmmSyWQkl8u5arydzWalXq9LPB6XYrHYu59hGL1oaLPZlGQy6TqQMy1zAgAAAADQVa1WpdFoSKFQkK2tLclms5JIJHqZQ6VSqZc91O/69euu5zcMQwqFgtTrdduv/tYxw+RyuV7wyi4jqrt2kcPMqKOUBI4DV6+LoHg87vjEO4p0Oi27u7tSLpdlfX1dVlZWxDAMicfjsry87ClqO21zAgAAAACC0TE150ERViqVJJ1OS6lUGjkmkUhIrVbrZQ+JSC8ZwulCVqVSSRKJhO38bui6bmkQfvXqVdvx165d65ULFovFSLSiIeh0AhUKhaFlaydhTgAAAADAydVsNkXXdVcta7qBo/4Mo2azaRt02tjYEF3XLT2Lj6o/aJVOpx0rffqTMwzDkI2NjdATNgg6AQCGcuqzMO5eME7zD/TswInh57kWdn8Ur8b9exbl8+F07JPuRxX237xp5urvuQ9O9//whY/LQ+3px57Az21/HyelZ9FATySl55NdH6AwqI+Vul6nPkeqgR5P+50RI8fPqZ/WAE3tRHPg7XZE1vr6uuTzedetWtQA07vvvms7/ubNmxKPxx2zktzoL5FTS/1GSSQSvRY96+vrBJ0AAAAAAMD0mObLkV27dk0SiYTr8Wqwp7/cTtVsNns9l+fm5iSRSEg6nZZMJuM5+KP2bn755Zddr7cbdHJzZb5xo5E4AAAAAAA4EZLJpKcLUqlXoLMLWKmNvnVdl2q1KrlcTjRNc30hMBGx9HJy2q/dOLf7GxcynQAARzLuEoCwSwymGWVAx8dJPrdOxz7pc8PfvKML+9i+cO+zIufPj23+/hIy06HCarDc7IllO+y/rwNlrEp5oFoOqB6PSj2+SXI6l6+c/pj1DkpppCiNsgdKC0M8NkyWejX5Uf2c1Kbfw2xsbMjGxobk83nHnk+3b9+2bLsNlF2+fNmyvbm56bo0bxwIOgEAAAAAAHdMETPsq9dNsLxvc3Oz973d1eASiYRUKhUxDENarZY0Go2BgFVXtVqVzc1N22bm6n2PmunUarVc3W9cCDoBAAAAAAAM0Z+RpJbPqdSglGEYUq1W5ebNmwNles1mUzKZjNTr9aFzjQpYeaXud9IIOgEjtNttWVxctB2ztrYma2trE1oRAAAAgCh5x/yyfFV+f+Dn/Z8j2u32JJeEAOm63uuJVCqVPDUgFzksiSsUClIoFGRjY0OuX79uCQI1Gg0pl8tSKBQG7nvUYJFahnfnzp0jzRMUgk7ACJ1OR3Z2dmzH7O3tTWg1QPSE3XcCo9F7ZnoMXJ5cwbkGovd6Y/d7q52atWy/8fhX7O+rKdd1UvsKOex70udioCdVx1Rut46PnT5t2e482fe1fy/H73hulHOtrnXg2JSeTt1zcbDfkUcHDwamd/ocMd20I5fX3fmX/6vsfuFf+17B/u4933O4USqVROSwZG1YYMiLbDYr6XRaVlZWLM29b9686XtuO2Q6AREVi8VkYWHBdszFixcntBoAAAAAUXNKZuWMnBv4+XNX5nvft9tt6XTsA4onRefBI9m/Mx3/uG82m1KtViUej48sgfMqHo/L1taWpFKpXuDJMAxpNBoDDcrj8XggASMvV+obB4JOwAgLCwuyvb0d9jIAAAAARNQHTv2gfODUD0rn8WPLz+vbTzOtFhcXj3nmk3uxc2fk1Lz/f9zv774nYo63m/j169dFROTWrVuey+qcvPbaa5JKpXrb9Xp9IOg0Pz8fSNBpfn7eedAYEXQCAESSU9mRiMhZc1++MIG1AOMSdpkQMA2i9nuirueV2Y/2vh8op5u5Zr2zUk4Xm7V+HDMPDjzt22u5ndfxA+V0+09sb1epgZgoUcvnRJRzrzxWTuV2J81Rwz1zf/5Pydyf/1O+969f/wdjzZhaXV2VZrMptVpNkslk4PMnk0lJp9PSaDREZHjT8KNmKKmBqrAznWLOQwAAAAAAAI6/arUq1WpVKpWKZLPZse0nk8nY3r68vGzZdpv1pDYOX1pa8rSuoBF0AgAAAAAArpmmFurXuDQaDVldXZVKpSL5fH5s+xERS8nesBK4/vI7keHZUMO0Wi3Ltlq2N2kEnQAAAAAAwInWbDYlk8lIqVQae8BJxBp0GlYCp2Y6uQ069WdExePxwPtReUVPJwA4IfxeZlm9v9rHIfDLOHu8jPRxEvYlsREdPBemxzQ9VkG/HkT5WCei7/XqldMfs96mvHZpp2Yt250n+7527fXcB/3arPY5ip1VPl4qx+/Us8qJl/U7Pk8H1ma9OXbG+lhpSv+tzsNH1juo71swVXRdl5WVFSkUClIoFCayz83Nzd73w0rtksmk5Qp2t2/fdlXu1z+vGrgKA78ZAAAAAADAPTPkrwDpui6pVEry+byUSiXX9ymXy772218GN6oE7urVq73vm82mq3n7xxWLxSOuLjgEnQAAAAAAwIljGIZkMhm5evWq64CTiEgul/PdK2ljY0NExDazanV1tfd990p3dvrHJBKJ0Ps5iVBeBwAAAAAAThjDMCSVSkkikZBiseiqZ5Ku673soWQyeeR9b2xsiK7rEo/H5caNGyPHJZNJSafTvWDSxsaGbYldrfa0jDQKWU4iBJ0A4MTw28dBvX9m5prteN89P05QDyfVie+Pcoz4/T2Y5ueC12Of9j5B07TeoF8Pwhb2c0eLPb2SltqzSO3h1D9WRESbOW3Z7jx6GPDq/FHXq/Y9cjGB8gN/PZ38cOpNqfanUqk9nAb6U52g9y2myFivIOd2DX6trKyIruui67osLS15um+lUrFsNxoNyeVyYhiGpNNpKZVKI4NSuq7L9evXRUTk1q1bQ5uIq/vqru/mzZsjg06GYUi1WhWRw3K9STRDd4PyOgAAAAAAcGKkUinXPZKGUQM6tVqt1/C70WhIKpWylMZ1dW+bn5+XVqvlKlsqkUj0MpiazebIXlIrKysicnjFuv6Mp7ARdAIAAAAAACdCLpcLNODUnVNVrVZlbm5OcrmcrK6uSiqVkkwmI/l8Xra2tiSRSLjeZzablXq9LvF4XIrFYu8YDMPoBbKazaYkk0l56623HLOnJonyOgDA0TikkQd9Web6wbplW02T92uc5Rlhl374Ne3rD9NJPlcnqZQQ4Qr7udN5st/7PjZr/XjVefzYsm0OlJtZeS1DdeL33KglZwMlaWqJmTJ+4HYHTsfn5XgG2gIocw8cm1JK6PQ+Z+Bc7J+c8joRETPgK8hN0jiygNLptLRaLSmVStJoNOTOnTu9zKduMOjGjRuSTqePHBBKp9Oyu7sr5XJZ1tfXZWVlRQzDkHg8LsvLy1Kr1Wz7PYWFoBMAAAAAAIAPiURioNfTOBQKBdsr3kUN5XUAAAAAAAAIHJlOAAAAAADAtXFevc74n/6V3P2f/pXtmIPd98a2fwSLoBMAnFB+L2euUu//yuxHLdtvPPmch9XJQC+FoHs4qcbZEyTsfiN+Tfv6ARHnv3knqXfZSTrWSRvoE3Rq1rqt9g1S+gJ5fWycnsdeqfePnT5t2VaPb4Dy2q0er6m0eArzuaj2ZNKUflxmX68udxNSRBSUzvsP5eDOXtjLQEAIOgEAAAAAAPfGmOkUO3dWZuYv2o452H1vuruZnyAEnQAAAAAAQCTE/9wPS/zP/bDtmHf+eolsqClB0AkYod1uy+Liou2YtbU1WVtbm9CKAH/8prA7lt/NXLP+wOFSw47UNHW/8/kU5GWcMTlBl25QljS9vJYpHWdRO9awf6+C3L+5/8SyrZZwdZ4o5XcH1nozv89Tv+dOvf8Hz/6kZdtU1qvS1HK8h4+st1tPh+fSez+P1UApovq+ReFUftd58EBERN7p/Ed5p/Mf5bkr85bb+z9HtNtt1+sEjhuCTsAInU5HdnZ2bMfs7RFdBwAAAE6qffOJPJIHjp8bjhsq2+AWQSdghFgsJgsLC7ZjLl60rzUGAAAAcHyd0mbljHluINOpX7vdlk4n3IxtICwEnYARFhYWZHt7O+xlAAAAAIio52PfL8/Hvl/e2B5dKri4uHjiMqGALoJOAHBCBH158FdmP2rZdrosslfqZZo7jx5atuudmsj9+yIXLgy9f9A9mKLWA2WSprkvUtDP+5P8PMD0CrtnkpOw1+N3/9beP0rTIqUfYUzpC6T2L1T7DNUP1n2tzbdT1vXGlPV2Hj+2bJtP9q3bag8on/0Z7f6me30c1Z5NA5T3NR2lP9XAYxfx37NAmd/6CnsNmAox5yEAAAAAAACANwSdAAAAAAAAEDjK6wAAAAAAgGumqTkPAoSgEwBM1CR74wTd00idTzs1a9k29594ms+J2idi2HrOmvvyhRG3T1PfoagL+tj9Pvf8rOckP46witrv+DjXE/axRZ3fc9/f01DtYaRuD/QRUvoG+e15pPL7XsB8ZO1jZHasjXTU49GUnlWaej72o3MFt9jZM5ZtU7m6nPnY+r7G6bEL+n0QcFxQXgcAAAAAAIDAkekEAAAAAADc4+pxcImgEwD44DUlP+iSLy/78nJfN+MH0syVkoA3nnzO0/6cDJTzHRyISOzIb3qcHruTVI4StTIjVdTWEyVRf+yiLGrnyk/ZadSOZdr4PX/9JWfqa5VosZFjRUTkwL6U3MnY34co69eUl371vUDnoVKOp5TXBc3PY6eW06nUYxsolRTr7fweAsMRdAIAAAAAAK7RSBxu0dMJAAAAAAAAgSPTCQAAAAAARMLe//y7svfr/x/bMQfGexNaDfwi6ATgRAm6/4nT/f1eqtjr/r32bfI098w1y3bnsdKHQunp9Mrpj1m233j8K9b5HNYaO3PWur9HDwdu18yYyLfaR3z4wsflofb0ZW3c/bWOE87FaE5/M8LuqcRjN1rYj40Tv+uL2vFESSaWk7PmvnxhUjvse/3rPHpiuUnt8aTFrCVJps+WR+N+rRvoa7RvPb7OY6XPkTI+Nmv9uDnw3sEjP7836n1jzzxj2e48UN5nnD5t3T57xrJtKsfyyuxHLdtB97aMnDE2Eu88eCQHu3vj2wEmiqATAAAAAACIhNi5MzIzd9F2zIHxnojJJfSmAUEnAAAAAAAQCRc/9J/LxQ/957Zjtv/PN8mGmhIEnQCcaOMunfFzCexh9/eTJu/12NRyOrV8Tk2hF81aQqBeWtjrufzg2Z+0vV3MjmVNX7j3WZHz5+3vM0ZBXr7c7/Mu6mVFqiitd+yXH484r8cf5PM+aF7LnymNfCrsc+NXvVMTuX9f5MKFI90/0ONXXjvV10rtlPW6TmbHmrkx7jJ9R+r6FWoJmvraL1rMfnuC1HOlvs9Q39eopYCxGfvH6tiX0w3g6nVwh6vXAQAAAAAAIHAEnQAAAAAAABA4yusAAAAAAIB79PCGSwSdAJwo09aXwo+g+wAN9HhS+jIM9HhSvPF43dN6VLEzZ4f99Mjz+e3nNc6eJ1HvRePXJNcftXMVen8WB+PuWxclYa89Ss/NqPeRm/S58vo3OPbMM083Hj+xDlZ6Iqk9j5xeO8N+ng681p+xfnw0lePVTlt7VqlXF9Ni/voA2b0Wez5XA/2lrI/NQL8q9bFVROl3GogSgk7ACO12WxYXF23HrK2tydra2oRWBAAAACBK3jn4krzT+dLAz/s/R7Tb7UkuCYgUgk7ACJ1OR3Z2dmzH7O1xmU4AAADgpNqXJ/JIHgz83OlzxNSjvA4uEXQCRojFYrKwsGA75uLFixNaDY7KbymL3zInp/173p9a4uZwKWMv+1LX6rT22NlnLNvmk33rtnrZZI+0c+esP1DmO7j/vpimdZ/9nB4bv2nvYabN+33eejXNJQNRKxebpnPnVdSeJ5Nej9f9hX1+7ETtWKL+2L0y+9GnG0rJltmxfjKPzVrLyzqPH1u2ncrtnAT+vFfL4fZHv+6KiMjB0d+XHIWf49NmHT4KK8cemz1j2e6+zzklZ+SM+cxAKeFzV+Z737fbbel0JntugKgg6ASMsLCwINvb22EvAwAAAEBEfWD2h+QDsz8knQfWbKf69tOA2OLi4vHLfDL99efCyXH0DqwAAAAAAADACASdAAAAAAAAEDjK6wCMldqDqH6wbr1d7T3w3j8LdP9+exl47Y3gd7zXHlCq/v157TfldPvMhQvWnSl9JwaSrB89dFitvc79963zK5dhjp0+LZoZE3nkazc9436s/axFNeleMEHvL8zLsUet71DUeXkuTvpcjrtvm1eTfr0J0rj7wI17f+Pm9Nhop0/3vlf7Gw70aDpl/filZgD47YfoldNjNXPpkmXbVErI1PXGzp213v74iWXbb8+qQGnKO5cZ66OhxZRHR1m7+VB5A6KdrHwOk0bicOlk/WYAAAAAAABgIgg6AQAAAAAAIHCU1wEAAAAAAPfGWF6398b/Iu/Vf9d2zIHx3vgWgEARdAIQuA9f+Lg81A7/vGinrH14HHtW3L8f6Fq89pXw2ufIL699gwb6BZgd+/F9Xjn9Mfu5HJgd675E3T5Qtn32NlB7OA2s5+BAxBzd+8JrzxC/PZz6b/c717ifd+PuHeO3n5gqyPVNWy+ZsHl5Lke9h1LQz/ug55vmXmVef+eD7jkY5rlXqT2LBno0qa+VSo+nNx7+c1/793qunI79gxf+smXb7FgjDbG+flaHA6y3m/vWnk7q/cfJ6djVx6bzwNqLUu1PJWq/LuV9ivm+9VhxdJ0Hj+Rgdy/sZSAgBJ0AAAAAAEAkxM6dkZm5i7ZjDoz36GY+JQg6AQAAAAAAd0zt8GtMLmZ+RC5mfsR2zM4n/74cGHfHtgYEh6ATgMBpZ85K7FvldRIb3wtSEDIz1+xv91rWpJSUqfPXD9Z97U+9v235nVJ6p6a4e9237Ktp5UpKvXJp4djMeK9VETt3VjTziciESvr9lIB5fR55LR0Julxt3KU649x/1EuogjbpMiRV1M5Hv5P0XBj34+61VN3r7X7Hj5vTevpL6jpPHllvU98HqdsH7svk3azFabzn54ZDJsnAewvltX/gvYJSojZOXh63oZRjV8vp1HI8v20FgOOK3wwAAAAAAAAEjkwnAAAAAADgmkY7JbhEphMAAAAAAAACR6YTgMD9y3d/QeT8+aG3vXL6Y57m8trbYKBHk1pfr/Q58tpjyfFS9sr8TtT7a6eUy+8ql/NVj8/20swOx+54bpRj/dDcJ8SO+cTa1yF2/hnb8U6P7cz8nHV+tXfC7CnbXhPj7ovkxbj7mYTdp8fvuQvysQp631HrLaMad/+uMPtr+b1/1H4vnOYL8m9Q2Mful9ffy7D7bZmdp6+fsXNnLbepfX80sb6uyynrxzH1df2NJ5/ztTa/v+MDfY80a08q87H1tV+L2ec0dB48sL19opT3EOpjN3Dss8pj9djmPdhJQKYTXCLTCQAAAAAAAIEj6AQAAAAAAIDAUV4HwFGQaeuxC9ayO3Xus9KRL3zr+w8/+5fEKTY+UE7ntbxNvb/CsXxP5XC5XKf7D1x62KEEzlQyuS2p4Mp9bccOuV19bGYuXBhccB/1sTXft0+hd3oe/dgH/hvrD9QU/jNnROu4/9+J53INj88tu+MJ+hLYTsZZMjXMpO8fZunjceP3+PufS5Mu6Rr38zxqvyd2wi4nnvS58rq/D1/4uDzUnn7sCbpUMnbmaVmWqZRsqa+1mlKi5VRuNu7nudP4/tJBERE5sG5rMWu5neP9nd4nTbDkt/9xExl8bNTyO/PhI+vtDsd+7Jkn/PjhGplOAAAAAAAACByZTsAI7XZbFhcXbcesra3J2trahFYEAAAAIErefvLv5Z39/zCQGdX/OaLdbk96WUBkEHQCRuh0OrKzs2M7Zm9vb0KrAQAAABA1++YTeWS+P/Bzp88RU4+r18Elgk7ACLFYTBYWFmzHXLx4cUKrCZbaq6Z+sG693amefkivm7Pmfq8X05+//Al59K3eCb/x4JctQ7Uzp23X9oX3fknkwud732ee/Su24x17OCm9A5x7D1hfQQf6OKi9CNT51T5Jao8mh/UNWZB1+KlZ6802l+d1unSv0+1Ol0mW77H+fpjtb1i3n+zbzu/Yl2HWeqzafNx6+/0HIqbN+XXoh+V1PV5vtxvrl9f+VF7XM+leOH7OrdP84+6nFfal2lWT7q3Tf7vTuVaNuxdN2D2Y/B6Pl/Pj9XfMK79/c4Lm5m9E//sSldfnntP+BnoB9TE71tdC9bXX6XW93vmcp7V5vd3xXCg9nAZeS9X+keprv/K+a+C9hcLvY2E3Vt3+4Lm/aNk2Hz+2TuD0Hu1bx3ZKm5Uz2jMDmU7PXZnvfd9ut6Wj9rcCTgiCTsAICwsLsr29HfYyAAAAAETUB2Z/SD4w+0PSURqN17ef/lN3cXHx+Gc+ASMQdAIAAAAAAO5RXgeXCDoBAAAAAIBI2Lv1O7J363dtxxzcpbfutCDoBJwAjn2JvN5foZ2aFc3URLpl/GZHREbUrcetfbC0d3ct2x++8PFeD4YPX/i4xM5esNzeUevtVQ59e9SeTbHT1h5T5qOH1vWpPZoc+yRZt9X51XOvHs9grwP73gcD++87Pqf+UrEzZ23Xop4rTT1Xyr41pcfZwR3rY+u5p4jaR2JfOblnz4h0bJ7LynMhyD4Rw26fZF+hcfdY8jvfJHvZeJ3bL7+9ccYt6OeGl+fuuJ/HkzbOXmNu7h+ksPtbjdvQ9d2/L3Lh8D3EF+59VuT8+bHt366H4UAPJ1Ppj3jK+nFsoK+QR377VTkZeG+gtn887b73ZBD8PDfVXlxqeZx2Wu0LqvSvUo/Nqc8oXOs8eCQHxt2wl4GAEHQCAAAAAADujbG8Lnb2jMzEL9mOObi7N9C8HdFE0AkAAAAAAETCxZUfkYsrP2I7Zvu//XtkQ00Jgk6YGuVyWer1umxubophGJJIJCSZTMrq6qqk0+mwlzdWXlP4Xzn9MdvbMzPXbOePPfOMZdt8bHNZevlWGZdpPi2v02K9MrIfW/jr1sFKGrk27FK6B0+/V1OXY2oqtJLSrl56WJ3fqbTQ6dLFA/MrJWwD5X/K8XYe2JfvDVBStdXx2oxS8maTxq6W06lmziuPu1ou8Ky11PHJt1m3Txv3rPM9+6xl+9fv/hPb/avPw5k/8gOWbe2ucmz7B7b/4VIfq6Avzx71Mqt+Qa993KU2Qc4fdGmhym9poN/1jXt/US6rmvRj6/V2v/NH+W/MuM+91/0Pc9bc75XrB0093g9e+Mu97wfeM6klV6fOKLdbX8fqB+viR+B/Q9T3Icr7MFHK7cz9fdvbx8nr89LsdNQfWDfVx1IpHRRNeY950qilosAI3hq7ACFoNBoyNzcnxWJRRERqtZq0Wi0plUrSbDYlk8lIJpMRwzDCXSgAAAAAYOo0m01ZXV2VpaUl0TRNNE2TpaUlKRaLvj5nlstlyWQyMjc315szl8tJo9GI1JzjRNAJkdZoNHoBpXw+L/V6XdLptCQSCclms9JqtSSZTEqj0ZBUKkXgCQAAAADgimEYksvlJJVKSbVaFV3Xe7fpui7lclnm5uakWq16mncciRPTmoxB0AmR1f0DICKSSCSkUqkMHVerHabO6rreGw8AAAAAGA/NDPcrCIZhSCqVko2NDcexq6ursrq66mrecSROTHMyBj2dEFm5XK73y9KN5g7T/UXb2NiQRqMh1WpV8vn8hFZ5NGrN+WCfHuv2qW97zjpBzD5ePPNtl21vP/Xd32XZ3v///YF1+u/8dsu2eeGcdVupYTfPnhI5eCxy+3BbO39WNO2w7n3vT79gGXvxX7+jLFbtaTTb6+kkp2ZFBsrt1Uv12p87UXo6qZciVvv+qGJnz9jertbzx05beyypl9cd6JvkdClhtVeC2mNKvZyv3dwDfSUcLhWsnrtz1nMx+w1rD6fOd8xZ538uLnacei986D/5b23vf/Dd3yadg8ci7cPtD1/4uDzUnh6TY78sh/U43u7QH6yfU9+foC+97rUXjdfeMV7396H565btA4c3QpPsDxP0uRt3rzB1vN/9OfFyfF7XHvS5C9qk+xY57S/sPkpR2beb/fvth+X1sYide/o+SX3tMR1e5kV5rQ76cXaaz3F+9bVU7dE0o7wPUd73mKKcAGXT7/N+nL3PNKWH08CxqT2hPLwvQDTkcjnRdV2SyaTcuHFDksmkiByW2t2+fVvK5bJlfLValUwmI9lsduScXhInlpaWeokT9Xp9onNOEr8ZiCRd1y01qVevXrUdf+3a08bYdgEqAAAAAMDJVq1WpdFoSKFQkK2tLclms5JIJHoJDaVSqZc91O/69esjZjzkNXFCRHqJE5Occ5IIOiGSSqVS7/t0Oi3xeNx2fH+02TAMVymSAAAAAACPzIh8+VAqlSSdTls+d6oSiUSvlUuXYRgjG3aPI3HiOCRjUF6HSOqPyqrR5VESiUSv8dv6+rpt2uOkvXL6Y5ZttVzu4PkFy/b7V6wlWO8/Z01tvvAH1ku4qqnFez/5Jy3bHzz7k5btb/7FZcv2c5/9pmXb+OPfaV3faWuZ1akH1r/ys/cORNt/Osb8ngUxZw7LzN79I9a1fyOZsGzP/+/W1OTv+JdvinyrykubnZFYzFquJuqlep9YL807UH6mpEJrFy5Y76+mhSvzDaSVqyVnDx7azqemXmuzSjmfUu43kJqt7C927rz1drWErm9+Tb2Ur3oZY6W8Tr00sKaWCiq3dy5Zn6favvVYDy5Yy/E8p8j/qT9m2VSL5R7Hz0hsf/Tlep/8ly9Ztk81mpZt9fdSLYl448nnbNenXta6/3b12H7s2/5P1vt6LA/wXR7hcb7MzDWx43V/5iNr6WbszFnL9m88+GVP83kRdKlG0KWOXuf3uz+/5YRBjT3KeK+iXr7nd392f3OCNu7nWdDqnZrI/fsi6mv+t/j9m6re/sELf7lvy+MnYY+l4Kqg/2apZp591rKtvleQA6XETH2fo7yvUkv33/D5N8hLya/TXAMtF0zlsVTL7dRzobYxQGQ1m03RdV22trYcxyYSCSmVSpYATrPZlHQ6PTA2iMQJ9TPsOOacNDKdEDnNpvWD4csvv+zqfv3BKTKdAAAAAACq9fV1yefzjgGcLjXA9O677w4dd9TEif51TWLOSSPohMhR0xX7f2nsqOPU4BUAAAAA4GS7du2abVmdSg32LC0tDYwZR+LEcUnGIOiEyLl9+7Zl220E+vJl6xXbNjc3g1oSAAAAAOAYSCaTrj9jikiviXfXsKSIcSROHJdkDHo6IXK6fZm6jvrL1Wq1AlvTQH8TpWb7YCVl2X72/7Zt2f71r443APZH/oefsmz/b3/rH1u2/8SMtZ/M7f/OevsP761atv/+p61XOnivc86y/dt7P2DZ3n5/Ts48eCLyxuH21/+zi/Jw9rCfz5Pvf2AZ+zf/2G9atv/GX/uqZfs/+ZN/WeRvHH7/5Zs/KN/zi9aeR7GvWftPyQVrjyNN7S2gUvsaKUz1UsBqPf8T+2sfqz2bzCfWen/zobW3jdpXSV2fNmPtq9S5d1+5Xbk08/7T/cWesfZcUnXee8/6A82hH5XSI6pz2rr2zkXrWmbuKcfucClh9VgOZq3jTyl9Ic5884GcPlB6YvV5eNm6vovnrH2E1H5fHfWxceClV4T6uKn89vFx4rlfyUGwqdi/cf+XLNvjvMS1k6AvQx/1S8f7HT9JfnvTeB0fdt8hvya5Xr/nPujH1q/Ae6ep7xX6qK9t6nbn/fdtbw+6p5/K6f7WflWDvTNV5n3leNRemOr7rDFyPDfKe0ZN6dk00L9K7fupvC9SHzscH+rn02H9nIJMnOhmKo1jzjAQdELkqL/UR6VGpAEAAAAA/mmTix+Grr+CJp/PDx0zjsSJKCZjHAVBJ0TOUYNFauT3zp07vtbRbrdlcXFRRES+2XGY63ffsGxqH3n6X6Clq39M5G/7WgoAAACACXt7/9/LO/tfOtxwSohWMt66nyNEDj9XYHpVKpXe9/1Xses3jsSJ45KMQdAJx5bfX65OpyM7OzvuBj+ylpDJN55+e2Hf3zrc2LevopL9c6MvKy8iYirZwGc1azrxzsGcZfvKmV3L9m/tvChnHz4tc5p5JDLzrYzlg0fWyT9wWimPU5z+5ozle01NWVdKogZSndXUZvX+SsnYQJq4kgYuB/b7105by98GyucU2nlrqaJjuZ16/1nldiVNXTtzpm9y620D5XL9Y4ftSzk2lfED1ifexbesxzKz8w3L9oFybtWy1YGSA6W87snCJcv2qW/eF60zurzu7DfVyzQ7lA+q51bhq4Rhxr600Kl8wm85nV9e1+d3/5PcX9RKqqJWhqTycu69Pk5BP2+c5p/074nf8UGe66A5nfuY8nryGw//+Vj3rx7/hy98XB5qp0be7nU+9XbtlLUsy3Kb8trXefBQHWDZVN+XjLtM1OmxU49NLUFTS9QGKC0pIlWCprw2Hyil8LHZU7JvPpZH8q2SQY+ZPa4/R0wr0/7zxSh3f+t35O5v/47v3R/s7fmeww1d13s9kUql0shso3EkTkQlGcMvgk6InHg8Hkg01ktzuGFisZgsLCyIiMg3d+6oN1o2TaW3zemLTz8Inzk/KyKjPxgDAAAAiJ5TMitn5Fv/MFR6ONn18hIRee7KfO/7drstnY5DgO6E6Dx8KAd374a9DNe6V7lLJBJSKBTGvr9xZCWR6QQo5ufnA/nFmJ+fdx5kY2FhQba3DxuCq/8FmpmzZv68/6detGyn/u6WMlu4VwwAAAAA4M0HTv2gfODUD4qIiHbOmq3eUZqmD2SpbT+9KMfi4uLxz3xyKXb2rMxcuuQ80MHB3p5j4M+vZrMp1WpV4vG41Ot127HjSJyISjKGXwSdEDlH/aVQfyHD/uUCAAAAgGPpiPGeSz/6I3LpR3/E9+6/+n//u2PPmLp+/bqIiNy6dcuxifc4EieikozhF0EnRM7y8nKvblbkMJjkJoCk1qouLS0FtibP9fFKr5ofO/cnLdux7/pOy/ZArxrD2iPqD3/Y+ofi7B1reu7zv2q9nOZ/8XvXLdvP/fq/tWz/8Lurlu2LX/iiZfv/In/dul7lirGxfeurzJkLMTmz/7Sfz+Wtu/Jo5rB/w+7/4aJl7N/6nY9Ztv/e71r/DD3/K0+P5fmf+3fy+MKzltvVS+2aSm8E7azSp8ihh9PAeKU3gflEOXiFNqv0OlD7Aqm9C9TL8zr0GRpI5XZgubyv0ndBPVbzvvV5pq5d7btgKrfP3lP6SSnHtt/+mnVxSt+K+sG6ZVvNKDx1z3rutX3l3L3/QLTO0zFfuPdZkfPne9v/xQdL1vUr/b86j72VvXrqq6Qca+zcWdu5xt3rxknQfYTU+WLKf4fV/i5+z4fd+sfdf0oV9PxB92eZZK+fwC9LH/D+gjbp9fafr0mfayeTfiyc9qe+PvidT739g+f/0tMN5X2K155GA70mfXJ6rJ3+RsYuWM9bR+l75ETtaWXu27+vmiT1PVxMfQ+ovmdU3qPFlPdVB/fuBbg6hG11dVWazabUajVJJpOO48eROHFckjHsO5sCIUilUpZtt1371UtBptPpwNYEAAAAADj+qtWqVKtVqVQqks1mXd1neXnZsu02Q8kucWIcc4aBoBMiR/3lcht06v8ljMfjjimQAAAAAIAjMEP+GpNGoyGrq6tSqVQkn8+7vt84EieOSzIGQSdETjKZtKQA3r59e/TgPpubm73v1cAVAAAAAACjNJtNyWQyUiqVPAWcRMaTOHFckjHo6YRIunr1qlSrVRERS38nO/3jisXiWNblltqrRqXWy2stpa+P0v/lO//gG9bblRrzX3/8K5btH/vuv2XZ3lf6C1z8360pl7/+4Jet9//eTyrrsfZfUfsMPTMzI2cOnvbH0d7eFk07rJP/7l//AevYr7xr2e7stMVOZ89aHz/QZ0jtfaD0YLL0OJLB+nvz4SOx/kD514lyrAP7f2Dti6TSnnnGOv6Rsj+1R9VAz6mj/2+g8771qiozDn0kOuq5ULZn4tb+XDOPrb0NTu0p979wwbKp9jpw6j0zc8/ar0ti9ufiwxc+Lg+1py9rp89Yf486j6zzOfWxGHfPE7t9qcbdl8jp/l57gqg+dPGvWrYPHH5vvLLbv9dzFXZfoaj31hnn70HYPZlUYffH8vt7Z2fcz4uwz51Xvv+mWt4rqO8jlPd4Tj2blB5QqnH3BFTHv3La2otzYH1qD8Pzyvse9X2Z0l9xkgb6VSnvEwZ6W6p9OhUD75sw1XRdl5WVFSkUClIoFDzfv5s40Q343L5921Vpnl3ixDjmDAOZToik1dWnja4bjYbj+P4xiUQi9BRCAAAAADiuNDPcryDpui6pVEry+byUSiXnO3zrPuVy2fKzq1ev9r4PKnFiHHNOGkEnRFIymbQEjjY2NmzH12pP/ysThV8sAAAAAEC0GYYhmUxGrl696jrgJCKSy+UGEh3GkThxHJIxKK9DZFUqlV6n/Zs3b45MJTQMo1eKl06nPdffhmHclzbe/wPlUvVKKvTBl75ie/+Dr+5Ytl1d3td8mi5t7u+L+a1U82fe2rUOvrtn3VYvLdyfdn5wINpppUTKIZVZO/BWQjZwbGra+Cnrn8kD5VL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2jNqGU+D4OOHk02QXBO723IMqcvZc3zbr6RPX+1tPbYLUAbSxvA4AAAAAAACeY6YTAAAAAABwLWKxvg3uMNMJAAAAAAAAnmOmE+Cg0WhoeXl5YJuNjQ1tbGxMaUQAAADwm9uspaGyjiLBmwswVqaUZZ9zFMTsqrcff6FvW+rM9b5tdnlWknT79m3dvn27a1vvZ4hGozHGCIFwo+gEOGg2m9rf3x/Y5vDwcEqjAQAAABA0h4eHJ35mmEmsroNLFJ0AB3Nzc1paWhrYZn5+fkqjAQAAABA08/Pzunz58sA2jUZDzSZ3ucPpRNEJcLC0tKS9vT2/hwEAAAAgoNzEbSwvL5/O2VCAKDoBAAAAAIAhRFheB5coOgEAAACAx+wCsp3Cxf0O03bLbTh6WM5Hsg8NdwpCt90/gOHoQJAE7zYJAAAAAAAACD1mOgEAAAAAAPdYXgeXmOkEAAAAAAAAzzHTCQAAAAAAuEaQONyi6AQAAAAAY7ALo64cbfVvcwiYDksYdRDH5JZtYLhkHxoe6V8QFPYQeMAvLK8DAAAAAACA55jpBAAAAAAA3Jvg8rpv/9uv6Nv/9isD2zx5eDi5AcBTFJ0AAAAAAEAgHD3+SE++d9/vYcAjFJ0AAAAAAEAgnDn/rM79wMWBbZ48PJQs0szDgKITAAAAAExBmMKoxwk3dwrttgtXnxq7wPBh2tqEi0vSa+c/3bft7cdfcH+skJrk3euW/txPaunP/eTANu/+1n/JbKiQIEgcAAAAAAAAnqPoBAAAAAAAAM+xvA4AAAAAALhHnBJcYqYTAAAAAAAAPMdMJwAAAAAYxzAh1TPGKRw9aIYJa7cNQnd4ja2np/e1B9yg6AQAAAAAANyxJnv3OrdjQDhQdAIcNBoNLS8vD2yzsbGhjY2NKY0IAAAAQJB80/q6vqVvdG3r/QzRaDSmOSQgUCg6AQ6azab29/cHtjk8PJzSaAAAAAAEzVM90SM97Np20meImWCdrqlGKysrMgxD5XJZ6XR6qH0LhYIqlYp2dnZkmqZisZji8biy2aySyeSERhwcFJ0AB3Nzc1paWhrYZn5+fkqjAQAAQNg55QrZ5SINk0E0CWMdP2J/v6ognucw+U12zuqcntFzXdtevLzY9bzRaKjZJPsprHK5nAzDGHq/arWqTCYj0zSVTCZVLpcVi8VUq9WUy+WUSqXa26PRqPcDDwiKToCDpaUl7e3t+T0MAAAAAAH1UuQVvaRXurZV9roLacvLy6dj9tMMqlarKhQKI+2XSqUkSevr6yoWi+1/i8ViSqfTSiQSqlarSiQS2t3dndnCk30JGgAAAAAAoEdEx0Hivj6mcJ6maSqTGf7ujJ37xWKxroJTp3L5uDhpGMZIxwkLik4AAAAAAAAdbty4ocXFxaFnILWW1EnHS/OctGY8Scczo0ql0qhDDTSKTgAAAAAAAN9XKpW0vb3dno3klmEYqlar7efXrl0b2P769Y8zxQYVqMKMTCcAAAAA8Ni4odmBDN22GZNtaLhDELef47cdu+QYet5rmBD4U2GGb15nGIay2aw2NzcVj8eH2jefz7e/TiaTJ86S6rwTnmma2t7eHvrueEHHTCcAAAAAAAAdL4+Lx+NdBSS3OpfIuS1YxWKx9tdbW1tDHzPomOkEAAAAAABOvVwup1qtpnq9PvS+tVqt6/nVq1dd7RePx2UYhiRpe3t76OMGHTOdAAAAAACAa5Gmv49JqNVqKhQKKhaLXbOP3OrMcpLkuo/edr3Fq7Cj6AQAAAAAAE61tbU1pdNpra+vj7T/nTt3up67vevdpUuXup7v7OyMdPygYnkdAAAAAIzBLmR6mIBpvwPC7aTOXO/faBO6XTkKRwbNpK5xEF87DC+TOf5+ffPNN0fuo7VErmXUmU6jLO0LMopOAAAAAADAvRm6e9329ra2t7dVqVRcz06y01t0GpVpmp70ExQUnQAAAAAAwMT9h69/RY2v/8ux+3n88NCD0RwXeDKZjNbX15VMJsfuaxS9ha579+6NNY6goegEAAAAAABci4w40+no8Ud6/PC+t4MZw9rammKxmIrFot9DaWOmEwAAAAAAwJDOnntW55+7OHY/xzOdxlvjVygUVKvVtLu7O/Z4pOMZS14UjMZZ4hdEFJ0AAAAAwGOhD5i2+u9L7/acnELUQ39NbNid6yyep1d+5JWf1I+88pNj97Pz3//fxpoxVavVlMvllM/nFY/Hxx6PJC0uLnpSdFpcXBx/MAFC0QkAAAAAALhnhTtJPJPJKB6Pa3Nz07M+R52h1FuoYqYTAAAAAABACBUKBRmGoWQyqUzGflZep86i0K1bt7S1tdV+fv36daXTaUnS6uqqarVa135uCki9weErKysn7hMmFJ0AAAAAAMCp8P7770uSqtXq0PvWarWuwlIsFmsXnRKJRFdbwzBcLd2r1+tdz8e9i17QUHQCAAAAgDG4zfVxyjqyE8RcILfjD+LYhzFUTlNkbsKjCSBr9LvXeTmGoFldXe167rbo1DmTKhqNKhaLeT00X53C7xAAAAAAAHAa5fN5WZbl+tFZBCqXy13/ls/n2/8Wj8e7ltPduXPH1Xh2dnbaX/cWrmYBM50AB41GQ8vLywPbbGxsaGNjY0ojAgAAABAk37T+SN+yvt61rfczRKPRmOaQ4KNr166pVCpJUtcyvEE62+VyuYmMy08UnQAHzWZT+/v7A9scHh5OaTQAAAAAguap9USP9LBr20mfIWZCAJe3BUE2m20XndxkRnW2icViM5fnJFF0AhzNzc1paWlpYJv5+fkpjQYAAABA0JyNnNMz1nNd2168vNj1vNFoqNlsTnNY8Ek8HlcymWwXk7a3t9tB43bK5Y+zwmZxlpNE0QlwtLS0pL29Pb+HAQAAgIBzGxruFEY9TMD4tLgNAw/i2IeROnPdXTuH83xJL+ulyMtd2yp73ddueXn5dMx+giSpWCxqZWVFknTr1i3HopNpmu1ZUclkUuvr61Mb4zQRJA4AAAAAAFyLWP4+giwWi7VnMNVqNRUKBdt2a2trko7vWNc542nWUHQCAAAAAADwSDqdVqVSUTQaVS6XUyaTUa1Wk2maqlarSiQSqtVqisfjunv3btdd72YNy+sAAAAAAIB7VsCnG3moXq+PtF8ymdTBwYEKhYK2tra0trYm0zQVjUa1urqqcrk8MO9pVlB0AgAAAAAAmIDNzU1tbm76PQzfUHQCAAAAAI+5DeIetu20uA1CD+LY7TgFgbsOTHcIHK8cbY08JuA0oOgEAAAAAABcC3qYN4KDIHEAAAAAAAB4jqITAAAAAAAAPMfyOgAAAAAA4B7L6+ASRScAAAAAmIJxw6ynKtK/KOa185/u2/b24y/0bQvieY59bKvpzUCAU4bldQAAAAAAAPAcM50AAAAAAIBrk7x73Z7xL7Vn/KuBbR5/dDi5AcBTFJ0AAAAAAEAgPH3ykR5/dN/vYcAjFJ0AAAAAAEAgnD33rM4/e3Fgm+OZTqSZhwFFJwAAAABwyS4k221IdSADwx1Ujrb6tjkFhPftG6LztDPOa3w6WFJzcgWf5R/7K1r+sb8ysM3/5/f+K5bYhQRB4gAAAAAAAPAcM50AAAAAAIA7lvxf2eb38eEaM50AAAAAAADgOWY6AQ4ajYaWl5cHttnY2NDGxsaURgQAAIBpccovmkS2T1gyhII4JrecXs/I2XN924Y5z1ciP6Fv6Rtd2168vNj1vNFouO4PmDUUnQAHzWZT+/v7A9scHhJeBwAAAJxWT/VEj/Swa9tJnyFmQYTlbXCJohPgYG5uTktLSwPbzM/PT2k0AAAAAILmrM7pGT3Xtc1uptP/v737iW0kTe87/qN6dmfXOytT6j2sLDm7W0QM+GSgqIYRw8mlyUNuCUB2A7k3ectBBxJzCbwHo0Mi6YNzIvuYUw+JIPCV1XDi2AkMiQX4YgQ2WLO7kVYBstMqaGe97p0ZVg4yuSz+LYpFsl7q+wGIIam3Xr4iH0yrHj7vU/1+f5PLAhKDpBMww9HRkS4vL7e9DAAAAAAJ9b3U7+h7+p3Qc53L8Pa8k5OTB1H9BExD0gkAAAAAAEQXsL8O0ZB0AgAAAIAxqzbNXqY5eBIbdK/S3HxW0+5pNvW7L/M6+UfPJ55LPXq08rzAQ7S37QUAAAAAAABg91DpBAAAAAAAIuPqdYiKSicAAAAAAADEjqSTAVzXVblcViaTUSqVUiqVUiaTUbVale/79563Xq8rn8/r4OBgOGexWJTjODs/JwAAAAAAWC+21yWY7/t68eKF2u32xM88z1O9Xle9Xlej0VCpVIo8r+M4KhaL8n1fuVxOrVZLlmXJdV1Vq1Xl8/nh8+l0eqfmBAAAAOK2StPtpJq2/qi/5yZ/91Xf+20fbyy21yEikk4J5fu+stmsPM9bOLZcLqvb7arRaCwc6ziO8vm8JKlUKoWOsSxLhUJB2WxWjuMom82q2+0uTOiYMicAAAAAANgcttclVLFYlOd5sm1brVZLvV5PvV5PrVZLlUplYnyz2ZxaETXK930Vi3eZeMuyZiapWq27zLznecPxps8JAAAAAFhdSlIqCLZ72/abgMhIOiVQs9mU4ziqVCrqdrsqFAqyLGtY4VOr1dTr9WTbdui4Fy9ezJ13sFVNkqrV6sxxg9eR7iqOms2m8XMCAAAAAIDNIumUQLVaTblcTrVabeYYy7KGlT4Dvu/PbK7teV7oZ8+ePZu7hufPnw/vz0r8mDInAAAAAADYPHo6JYzruvI8T91ud+FYy7JUq9VCyRbXdZXL5SbGjiawcrncwv5Hgwoi6S6Z1W63Q8+ZNCcAAACwTqs2jjalGfUurinq8dM+ozhe31j9bS8ApqDSKWHevHmjUqkUuSn2eILps88+mzpudOvZ+La8WSzLCq3L1DkBAAAAAMDmkXRKmOfPn8/dVjduPDGTyWQmxriuG3r85MmTpeceb1JuypwAAAAAAGA72F6XMFGrewYGDbcHRqt+Bsb7PE0bM834ONd1h+szZU4AAAAAQLxSQbC2uX/yk7/Q/7n8i7lj3r//+dpeH/Ei6WQ4z/NCj6f1czo/Pw89jrp17/Hjx6HHFxcXw2SOKXMCAAAAcVpH/yVT+gLN6ms0zpTfR1r9dzKlH5dJvvzqH/T+/e22l4GYkHQy3MXFxfB+qVSaOmY8MXXfCqJer2fcnAAAAAAAc3zw6Bv68MP9uWPuKp3WV22F+JB0Mlyj0RjeH72K3ajxZM59jW7lM2VOAAAAAECMAq013/NPfvsP9U9++w/njvnL//nv9f5XVEOZgEbiBvM8b9h8u1arzawMum8SZnx727t374ybEwAAAAAAbAeVTgYbXOXOsixVKpW1v946KoiSPOf19bVOTk5Wnufs7ExnZ2cxrAgAAADApvw4+Fv9RH8nSTPPC34WTH7hPT72+vo6/sUBhiDpZCjXddVsNpVOp9XpdOaOTafTsSRiRiuKTJlzFf1+X1dXVyvPc3tL2ScAAMCuiNokepkG00lsRr3KmvKPnk99vvPVm5XWtA7zfqc/+qM/0g9/+ENJWuq8II5ziMRb49XrsFtIOi2h2WyqXC7HOqdt2+p2u0sf9+LFC0nS27dvFzbcPjw8jCWZc3h4aNycq9jb29PR0dHK8+zvz2+CBwAAACB59vf3dXx8PHfMz64mK52+cxw+H7m+vla/3491bYApSDoZqFwuy3VdtVot2ba9cPx9K3/GE0DjVUkmzLmKo6MjXV5exjIXAAAAALNEaZMxtSLsMlw9dXJysnPVTykKnRARSacl5HI5tVrxlrkumyBpNptqNptqNBoqFAqRjjk9PR02HJfukjRRXne8IXcmkzFuTgAAAAAAsB0knZZgWdbCrWzr5DiOyuWyGo2GSqVS5OOy2Wzosed5kSqker1e6HEulzNuTgAAAAAAsB0knQzhuq7y+bxqtdpSCSfproJoVNRkzui2tXQ6HUq4mTInAAAAsA3LNALfdtPwaaatKWpz8SQ2DJ+29llM/+w2gkbiiGhv2wvAYp7n6enTp6pUKqpUKksfb9t2aJva+fl5pOMuLi6G98cTQqbMCQAAAAAAtoOkU8J5nqdsNqtSqaRarRb5mHq9Hnru2bNnw/ujfZPmGR1XrVYnfm7KnAAAAAAAYPNIOiWY7/vK5/N69uxZ5ISTJBWLxYm+RuVyeXjfcZyFc4yOsSxrap8kU+YEAAAAAMQn1d/uDeYg6ZRQvu8rm83KsixVq1V5nrfw5jjOsBn3eC8k27ZDCZl2uz339Uev0jeresiUOQEAAAAAwOalgoAOYEmUzWYjby8bN+vqdp7nKZPJSLpL7nS73anH+76vg4MDSXdXgut0OjNfy5Q5l3FycqKrqysdHx/r8vIyljkfhF/8Qvroo7v7n38ufetb250HDwPxAgCYJgH/PuQfPZ94LokNtlcVtbn4Q7Yr5xeD3+PDr+/rnz9ZvtdwnP7HeV3vf3Vr/Hv6EFDplECrJJwkzby6nWVZw8og13Un+j4NPH36VNLdleBGK4lMnhMAAAAAEJMg2O4NxiDplDDFYnEtCaeBQqGgTqejdDqtarU6fD3f94fb81zXlW3b+vTTT0NXkzN9TgAAAAAAsDkfbHsBCNtExU4ul9PNzY3q9brevHmjp0+fyvd9pdNpnZ6eqtVqqVAo7OScAAAAAABgM0g6PWCVSkWVSrx7cU2ZEwAAAABwT+xwQ0QknQAAAABgBdOaaZsuaoPwbTcNX7WRedTPbtu/J2Aqkk4AAAAAACCyFM28ERGNxAEAAAAAABA7Kp0AAAAAAEAi/Pj6L/Xj6/81d8z7X/18Q6vBqkg6AQAAAMAKdrHfz7TfadX+Seuwjtff9u+UeIGkNW6v+/LL93r/q9u1zY/NIukEAAAAAAAS4YNHH+rDr+3PHfP+i5+LS+iZgaQTMMP19bVOTk7mjjk7O9PZ2dmGVgQAAAAgSV69eqVXr17NHXN9fb2h1eyG7x39gb539Adzx/y5+x/1/guqoUxA0gmYod/v6+rqau6Y21v+RwcAAAA8VLe3twvPGXZSf9sLgClIOgEz7O3t6ejoaO6Y/f35ZZ8AAAAAdtf+/r6Oj4/njrm+vla/T5YGDxNJJ2CGo6MjXV5ebnsZAAAAQCJEbbA9reH4Msdv0qpritJu4+Tk5GFWQwEi6QQAAAAAACILlFrj1euirgFm2Nv2AgAAAAAAALB7SDoBAAAAAAAgdiSdAAAAAABAdEGw3VvMXNdVuVxWJpNRKpVSKpVSJpNRtVqV7/v3nrderyufz+vg4GA4Z7FYlOM48S0+4ejpBAAAAAARTWuSPa0ZddRx2K5ZTc/Hzfrs+JzN5vu+Xrx4oXa7PfEzz/NUr9dVr9fVaDRUKpUiz+s4jorFonzfVy6XU6vVkmVZcl1X1WpV+Xx++Hw6nY7xN0oekk4AAAAAACC6rTcSX53v+8pms/I8b+HYcrmsbrerRqOxcKzjOMrn85KkUqkUOsayLBUKBWWzWTmOo2w2q263u9OJJ7bXAQAAAACAB6VYLMrzPNm2rVarpV6vp16vp1arpUqlMjG+2WxOrYga5fu+isW76jfLsmYmqVqtu2o4z/OG43cVSScAAAAAAPBgNJtNOY6jSqWibrerQqEgy7KGlUi1Wk29Xk+2bYeOe/Hixdx5B1vqJKlarc4cN3gd6a4yqtlsrvYLJRhJJwAAAAAAEF1/y7cV1Wo15XI51Wq1mWMsyxpWJA34vj+zCbjneaGfPXv2bO4anj9/Prw/L0FlOno6AQAAAEBEUZtE72Iz6fyj5xPPdb56M/mcQb971CbwyxyPZHNdV57nqdvtLhxrWZZqtVooKeS6rnK53MTY0QRWLpdb2KdpUOkk3SWz2u126LldQaUTAAAAAAB4EN68eaNSqRS5efd4gumzzz6bOm50i9z4trxZLMsKrWsXUekEAAAAAAAiSxl89brnz5+Hkj2LjCeQMpnMxBjXdUOPnzx5EnnuwdXzFjUpNxWVTgAAAAAA4EGwbTtylZOkYWPwgWkJq/E+T1GTWuPjxpNXu4BKJwAAAADYgFm9gkzpCzStf9MuWubzmPaZmvJ5IppBJdLAtH5O5+fnocdRk1qPHz8OPb64uIi8Nc8UJJ0AAAAAAEB0Bm+vW9bFxcXwfqlUmjpmPDF130qnXq+35OqSj+11AAAAAAAAUzQajeH90avYjRpPOt3X+Fa+XUDSCQAAAAAAYIznecM+S7VabWYF032TRePb8N69e3eveZKM7XUAAAAAACCaQPfeXvej//dX+tHP/mrlJbz/8vOV54iiVqtJutsGV6lU1v56u1jpRNIJmOH6+lonJydzx5ydnens7GxDKwIAAIDJZjWYTmIz6qhrSuLap1lXE/d/+R/+mV69ehV6bvwc4vr6eqXX2CVf9t/r/Zc/3/YyInFdV81mU+l0Wp1OZ+7YdDodS8JomavqmYKkEzBDv9/X1dXV3DG3t7cbWg0AAACApLm9vV14zrCT7lnp9MHe1/XhB99e+eXvKp3W28z8xYsXkqS3b98ubAx+eHgYS9Lp8PBw5TmShqQTMMPe3p6Ojo7mjtnf39/QagAAAAAkzf7+vo6Pj+eOub6+Vr/f39CKku373/l9ff87v7/yPP/tf/+ntVZMlctlua6rVqsl27YXjr9vhdJ4oopKJ+ABOTo60uXl5baXAQAAACChorTbODk5eZjVUIZqNptqNptqNBoqFAqRjjk9PR02HJfukklREkjjjcMzmcxSazUBV68DAAAAAADR9bd8WxPHcVQul9VoNFQqlSIfl81mQ489z4t0XK/XCz3O5XKRX9MUVDoBAAAAwBYlsfF21DUlce3TmLJObI/rusrn86rVakslnKS7SqdRnudF2pY3ur0unU4v7B1lIiqdAAAAAADAg+V5np4+fapKpaJKpbL08bZth7bTnZ+fRzru4uJieH88cbUrSDoBAAAAAIDIUkGw1VucPM9TNptVqVRSrVaLfEy9Xg899+zZs+H90f5O84yOq1arkY4xDUknAAAAAADw4Pi+r3w+r2fPnkVOOElSsVic6L9ULpeH9x3HWTjH6BjLsnayn5NETycAAAAAAPDA+L6vbDYry7JUrVYjNf/2PG9YkTTes8m2beVyuWEyqd1uz736Xav16z5ju1rlJJF0AgAAAACMye8VJ56L2ow7/+j51Oc7X71ZaU2bssrv/mDEvMVtG54+fSrP8+R5njKZzFLHNhqNmc8P5nr58uXMpJPv+2o2m5Lurli3bONyk7C9DgAAAAAAPBjZbDZy36VpZiWJLMsaVjC5rjvR92ng6dOnku6uWDda8bSLSDoBAAAAAIAHoVgsriXhNFAoFNTpdJROp1WtVoev5/u+HMcZJrxs29ann34auurdLmJ7HQAAAAAAiCiQ+tveXnf/199EZVEul9PNzY3q9brevHmjp0+fyvd9pdNpnZ6eqtVqze33tEtIOgEAAAAAAMSsUqmoUqlsexlbRdIJAAAAABCySuNsUxqGS9Gbhs9qjq6gH+n4nbMDjcSxGfR0AgAAAAAAQOxIOgEAAAAAACB2bK8DAAAAAADRBNr+9jp29xmDpBMAAAAA4EGK3H9pSu8mAIuxvQ4AAAAAAACxo9IJAAAAAABEt+3tdTAGlU4AAAAAAACIHZVOwAzX19c6OTmZO+bs7ExnZ2cbWhEAAACAJPlx8Lf6if4u9Nz4OcT19fUml2S8T/0L/ci/mDvm/Ve/2NBqsCqSTsAM/X5fV1dXc8fc3t5uaDUAAAAA7iu/V5z6fORG4qnpm4T+zb/71/rhD38Yem7ROcRO6K9ve92XX73X+68+X9v82CySTsAMe3t7Ojo6mjtmf39/Q6sBAAAAkDT7+/s6Pj6eO+b6+lr9Ple/i+qDva/rw0cfzR1zV+lEXykTkHQCZjg6OtLl5eW2lwEAAAAgoaK02zg5OXkY1U8x+cFvnuoHv3k6d8yf/aRBNZQhSDoBAAAAAIDoAiq3EA1XrwMAAAAAAEDsqHQCAAAAAOy0WQ3D84+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       "text/plain": [
        "<Figure size 1200x900 with 2 Axes>"
       ]
@@ -721,8 +742,8 @@
     }
    ],
    "source": [
-    "nbins = 200\n",
-    "vmax = 400\n",
+    "nbins = 150\n",
+    "vmax = 150\n",
     "\n",
     "a1 = plt.hist2d(\n",
     "    brem_z_found,\n",
@@ -753,12 +774,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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ihikti9dO9dqrrpGpE5yX2KQ/m6l/tZFd3QWiWCwmkUikU0S6ceOGpFKpA8fY3NzsfN5fuJoWrHQCAAAAAACHRvc2tmq1auuY/m14/cWrixcvdj7vDhkfpLtfLpezdUzQUHQCAAAAAACHRneBR9M0W7lO3SuiVNlL2Wy287mdQlZ3n2g0OpV5TiIUnQAAAAAAwBCCfPc6kf2iUff2uKtXrx54THeRKJ/Pm/49Fov1FI42NjYGjlcuP92WPK2rnEQoOgEAAAAAgEOmu+hTKBQGhn9Xq9XOv2cyGdPWurZisdj5fFAhS9d1KZVKIrJfAMtkMkPNPUj8l1gHAMCPWAXTtkNsTxhP5O1JTgjASKxuCqASlEBqr+eZnLlkaqvsrU/k3OMIJ3eq/xob5+8H1XOvEj52bEwzGJ3TEHhVQPZLx171dE62z2PxuoWOHDW1vfvoTdfPP3UCHCTeFovFpFgsdrbFJZNJqdVqprvU6bre6dM+xko0GpVyuSzpdFrq9boUCgVZW1sz9VtZWRGR/TvWdRe/phErnQAAAAAAwKGTyWSkUqlIJBIRTdPk/PnzUigUpF6vd4pG58+fF03TJJPJSK1WO3DMVCrVGTOXy3UKULquS7ValXg8LvV6XWKxmNy8edNU5Jo2rHQCLDSbTVlcXBzYZ3V1VVZXVyc0IwAAAAB+cu3aNbl27drAPs1mc0KzwSgSiYTs7OxIqVSScrksV69elVwuJ5FIRKLRqGQyGclmsz0ZUHbHLBQKsr6+LisrK6LrukQiEVleXpZyuSypVGqMj8o/KDoBFlqtlmxvbw/ss7u7O6HZAAAAAPCb3d3dA98zTKUp2F7XL5PJuJ6ttLa2ptxed5hQdAIshMNhWVhYGNhndnZ2QrMBDqdhcmCAIPI6F2hS/Pg4nebITCqHxsqk8puCwvTc37sncvq0iIh8+pnPyYPQ07c9Tp871fEvn/ysvYPDIWXz3r2PnEzJtmGuUePJY1ObKhcpfOK4+eCWuiLh5feN09fd6m+S7xrfkuNysqft2XPzPV83m01ptVqOzg8EFUUnwMLCwoJsbW15PQ0AAAAAPvVc6AV5Tl7oaats9RbSFhcXD+dqKEAoOgEAAAAAgCGo1+wBZty9DgAAAAAAAK6j6AQAAAAAAADXsb0OABA4ndDRrqBYAO4YJsDfjwHhdjmde5Af+2Hz9p0vi5w65dp4qu+R0JGj5rajirdaFgHboZkZx/NyW/j4CVNb69Ejc0fFYzL29pRjjuP7xm44udXPNtXjVFG9xiLWj3XqTeHd6zAerHQCAAAAAACA61jpFECapkk2m5VsNiupVGrkcQqFglQqFdnc3BRd1yUajUosFpNsNiuJRGKqxwQAAAAA+M8P6n8sP6x/Y2CfJ/d2JzQbOMVKpwDRdV3S6bQsLS1JtVqVW7dujTROtVqVubk5yeVyIiJSLpel0WhIPp+Xer0uyWRSksmk6Lo+dWMCAAAAAEYXEpGQMb6P1sMH8uTu7YEfYrC/LyhY6RQAuq7L1atXpVAoOB6rWq1KMpkUEZFMJiPFYrHzb9FoVFKplMTjcalWqxKPx6VWq0kkEpmKMQEAAAAA/jZz7IQcPX1mYJ/H93YpPAUERSefKxQKUiwWJRqNOh6rvVJKZL9w013I6VYul2VpaUk0TZN0Oi2VSiXwYwIIJoJ6gcHsBugOg++7w2sc15OTc1vx+hpVnf/lU5+zd3A4pGwOif+CxFsPH5jalI/95GdNbZMMRrd7PVj1S85cMvfdW7fVz6rv1DNkrEHiH3/xU/LxFz81sM//77/+dXl87/b4JgHXsL3Ox+r1uiQSCWk0GlKpVCyLL3al0+nOVrT2ljWV9koikf0VR6VSKfBjAgAAAACAyaLo5GOxWExisVjn6+Xl5ZHH0jRNqtVq5+uLFy8O7H/p0tNKvlXhJyhjAgAAAACAyaPoFCBOMovy+Xzn80QiceBY3XfF03VdNjY2AjsmAAAAAMBFhscfCAyKTodE99az7tVTg3TnSK2vm/cqB2VMAAAAAAAweQSJHwL1er3n6wsXLtg6LhaLiaZpIiKmFURBGRMAJsXLAF4cXlxjcJPd6ynoAfbjmL8qOLv14KG531H12y9VaLdTjh9nyN76hNajR+ZGozWeOY3BoQwCByaIlU6HQHdGkojYvhNef7/uolBQxgQAAAAAuCtkePuB4KDodAjcuHGj52u72VBnz57t+XpzczNwYwIAAAAAAG9QdDoE2lvP2kZdQdRoNAI3JgAAAAAA8AaZTodAfzFnVLquB25MAJgUrzMpgsyPGR/AKLiWg8Hpa6J6nWdOnza1GU8eT2xOTsZUPR4RUWY6JWcumdrCx46Z2pQ5TxOkfEw2M6pE1DlPqsdpda5D8X3PFjfYxEqnQ2DUIkz/9rZbt24FbkwAAAAAAOANVjrBtnGsIPLzmM1mUxYXFx2Ps7q6Kqurqy7MCAAAAMCkXLt2Ta5duyYiIj98sGPRy7zkp/89RLPZdHtqQGBQdDoEIpGIK4WY7hVFQRnTiVarJdvb247H2d3ddWE2AAAAACZpd3d3pPcDbryH8DvuIAe7KDoNoVQqSTabdXXMWCwmtVrN1TH7zc/Pu1LMmZ+fD9yYToTDYVlYWHA8zuzsrAuzAQAAADBJs7Ozcu7cORER+eG2/ZVOz57rfT/SbDal1Wq5PT0gECg6HQKjrvzpLwD1r0oKwphOLCwsyNbWlitjAQCsHYrAVZhYhRd7eT1YBiorqOZ5WK5l1eOc5Os5qeDmYa6HvXsfmdpUc3pl9vPK418+9TlT2zv3vmz7/E5YPXd256QKF7dkTKbwMsw1GjpydGDfn5Kf3f8kbBGHrHhMla3e8y8uLk7f6idWOsEmik5DSCQSUi67+wvNrQLJIMvLy1Kv1ztf67pu67z9gdxLS0uBGxMAAAAAAHiDotMQotGoRKNRr6cxtHg83vO1pmkSi8UOPK7RaPR8nUgkAjcmAAAAAADwhsUaQUyT5eXlnq81TbN1XPe2tUgk0lNwC8qYAAAAAAB3hQxvPxAcFJ0OgVgs1rNN7caNG7aO29zc7HzeXxAKypgAAAAAAMAbbK87JC5evCilUklEpCc3aZDufrlcLrBjAgBwmDgNWZ5USLMfQ7f9OKegmORzN6lzWZ1H9T0SmpkxtalCw1sPHirHDB3139sy1VxVjz18/IT52IcPxjInR0Lq9RbvPnrT1PbSsVdNbcaTx0ONC2Af3yGHRDab7XxerVYP7N/dJxqNKnOSgjImAAAAAMBFhscfCAz/ldRhqTu7aFixWEwSiUSnSLOxsSGpVMqyf/dd+qxWDwVlTAAAAABAMHz/T/9Yvv+n3xjY5/FHuxOaDZxipVOA9AdrD1uEKhaLnc+vXr1q2U/X9c4Wt0QiIZlMJvBjAgAAAAD8b+/RA3l87/bADzFY7hQUFJ0CQtd100qe9fX1ocaIRqOdlUH1el0KhYKy38rKiojs3wmueyVRkMcEAAAAALhkjFvnZo6ekKOnzgz8kFBoko8WDrC9zsd0XZfLly+LruvKfKN6vS6hUEgSiYREIhG5cuWKxGKxgWOmUimpVCqSTqcll8vJjRs35MqVKxKNRmVzc1NyuZzU63WJxWJy/fr1nrvJBX1MAIDapIKjMRlOXztee4xC9XNE5HBfT1/f/R1T28snP6vu3JqyVRsW4dqVveH+p7mbhjm3sbdnagsdOWq7L5z5xE9/Sj7x058a2Oe//29+fX/FE3yPopOPjWsFTyKRkJ2dHSkUCrK+vi4rKyui67pEIhFZXl6Wcrk8MEcpyGMCAAAAAIDJoOh0iK2trcna2tqhHBMAAAAAMJrQlC3Ow/iQ6QQAAAAAAADXsdIJAAAAAADY0w799noOCASKTgAAHHKHOeg36AiBB/zrpWOvmtqMJ4+Vfa1Cqn1HERD+zv2vmNqSM5eUh6vaJxUubjUnMVrmNsXjfPfRmy7PCDgc2F4HAAAAAAAA17HSCQAAAAAA2BYy2N8Ge1jpBAAAAAAAANex0gmw0Gw2ZXFxcWCf1dVVWV1dndCMAAB+43WmEvlN/qe6RqwE+fUM8tzdYOztmdpCMzOmNqvnaZjrZFJUWUsvn/ysqc2P1/gwP5vtZm9ZPc7vGt+S78m3e9qePTff83Wz2bScKzDtKDoBFlqtlmxvbw/ss7u7O6HZAAAAAPCbJ/JYHsr9nraD3kNMBXbXwSaKToCFcDgsCwsLA/vMzs5OaDYAAAAA/OaIHJXjcrKnTbXSqdVS3CUPOAQoOgEWFhYWZGtry+tpAAAAAPCp50IvyHPyQk9bZat3K9/i4uLhWP0EKFB0AgAAAAAAtoXYXgebKDoBAACM6LCHJ+NgQQqOxuhmZp8xtbXufWRqS85cUg8Qcv+m4k5vdPDK7OdNbarA9PDxE6a21qNHY5nTOMZUhYarqB6niMg7979i+1zAYeT+TzcAAAAAAAAceqx0AgAAAAAA9rG9Djax0gkAAAAAAACuY6UTAAAAAACwjSBx2EXRCQAAABDrcO9xBMYTQj9dDEVwtip0W4yW8ng/XmN7d+/a6jfM4xyHsXwvKYLdlY9TRF469qqp7d1Hb7o+JSCo2F4HAAAAAAAA17HSCQAAAAAA2DfG7XUf/NtvyAf/9hsD+zy+vzu+CcBVFJ0AAAAAAIAv7D16II8/uu31NOASik4AAAAAAMAXZo6dkKMfOzOwz+P7uyIGaeZBQNEJAABgiqjCsAmttofnCbYoQqZb9+/b6hc+fkI5ZHLmkqmtsrduazqTDMAPHTlqbjtqfktpPH6iPN548tj1OTnl9HlSBYkfBuO8e93CT/28LPzUzw/s897v/ueshgoIgsQBAAAAAADgOopOAAAAAAAAcB3b6wAAAAAAgH3EKcEmVjoBAAAAAADAdax0AgAAmCKEYWPaeR2Wrwr4thsm3Xr0SNkempkZfT4ef8+/c+/LpjZVMLqI93NVefnU50xtdoPhRewHvgOHFUUnAAAAAABgjzHeu9fZnQO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       "text/plain": [
        "<Figure size 1200x900 with 2 Axes>"
       ]
@@ -768,10 +789,10 @@
     }
    ],
    "source": [
-    "import matplotlib\n",
+    "# import matplotlib\n",
     "\n",
-    "nbins = 200\n",
-    "vmax = 400\n",
+    "# nbins = 200\n",
+    "# vmax = 400\n",
     "\n",
     "a1 = plt.hist2d(\n",
     "    brem_z_lost,\n",
@@ -779,7 +800,7 @@
     "    density=False,\n",
     "    bins=nbins,\n",
     "    cmin=1,\n",
-    "    vmax=vmax * stretch_factor,\n",
+    "    vmax=vmax,  # * stretch_factor,\n",
     "    # norm=matplotlib.colors.Normalize(vmin=1, vmax=vmax * stretch_factor),\n",
     "    range=[[-200, 9500], [-3200, 3200]],\n",
     ")\n",
@@ -791,11 +812,11 @@
     "\n",
     "plt.colorbar(a1[3])\n",
     "mplhep.lhcb.text(\"Simulation\", loc=0)\n",
-    "plt.show()\n",
-    "# plt.savefig(\n",
-    "#     \"/work/cetin/Projektpraktikum/thesis/brem_vtx_hist2d_lost.pdf\",\n",
-    "#     format=\"PDF\",\n",
-    "# )"
+    "# plt.show()\n",
+    "plt.savefig(\n",
+    "    \"/work/cetin/Projektpraktikum/thesis/brem_vtx_hist2d_lost.pdf\",\n",
+    "    format=\"PDF\",\n",
+    ")"
    ]
   },
   {
@@ -877,8 +898,9 @@
     "        if ntuple[jelec, \"brem_vtx_z\", jphoton] <= 770:\n",
     "            tmp_velo += ntuple[jelec, \"brem_photons_pe\", jphoton]\n",
     "            tmp_velo_length += 1\n",
-    "        elif (ntuple[jelec, \"brem_vtx_z\", jphoton]\n",
-    "              > 770) and (ntuple[jelec, \"brem_vtx_z\", jphoton] <= 2700):\n",
+    "        elif (ntuple[jelec, \"brem_vtx_z\", jphoton] > 770) and (\n",
+    "            ntuple[jelec, \"brem_vtx_z\", jphoton] <= 2700\n",
+    "        ):\n",
     "            tmp_richut += ntuple[jelec, \"brem_photons_pe\", jphoton]\n",
     "            tmp_richut_length += 1\n",
     "        else:\n",
@@ -894,14 +916,16 @@
     "    energy_emissions.field(\"neither_length\").integer(tmp_neither_length)\n",
     "    energy_emissions.field(\"downstream\").real(tmp_neither)\n",
     "\n",
-    "    energy_emissions.field(\"photon_length\").integer(tmp_neither_length +\n",
-    "                                                    tmp_richut_length +\n",
-    "                                                    tmp_velo_length)\n",
+    "    energy_emissions.field(\"photon_length\").integer(\n",
+    "        tmp_neither_length + tmp_richut_length + tmp_velo_length\n",
+    "    )\n",
     "\n",
     "    # if (tmp_velo == 0) and (tmp_richut == 0):\n",
-    "    if (False  # (tmp_velo >= 0.5 * ntuple[jelec, \"energy\"])\n",
-    "            or ((tmp_velo == 0) and (tmp_richut == 0)) or\n",
-    "        (ntuple[jelec, \"energy\"] - tmp_velo < 3000)):\n",
+    "    if (\n",
+    "        False  # (tmp_velo >= 0.5 * ntuple[jelec, \"energy\"])\n",
+    "        or ((tmp_velo == 0) and (tmp_richut == 0))\n",
+    "        or (ntuple[jelec, \"energy\"] - tmp_velo < 3000)\n",
+    "    ):\n",
     "        energy_emissions.field(\"quality\").integer(0)\n",
     "    else:\n",
     "        energy_emissions.field(\"quality\").integer(1)\n",
@@ -1027,8 +1051,7 @@
     "\n",
     "eff_rich = num_rich_found / denom\n",
     "\n",
-    "eff_other = ak.num(electrons_found[electrons_found.quality == 0],\n",
-    "                   axis=0) / denom\n",
+    "eff_other = ak.num(electrons_found[electrons_found.quality == 0], axis=0) / denom\n",
     "\n",
     "print(\"VELO energy emission, eff: \", eff_velo)\n",
     "\n",
@@ -1104,24 +1127,28 @@
     "# energyspektren angucken von velo und rich\n",
     "\n",
     "velo_found = ak.to_numpy(\n",
-    "    energy_emissions[(~energy_emissions.lost)\n",
-    "                     & (energy_emissions.quality == 1)][\"velo\"])\n",
+    "    energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\"velo\"]\n",
+    ")\n",
     "rich_found = ak.to_numpy(\n",
-    "    energy_emissions[(~energy_emissions.lost)\n",
-    "                     & (energy_emissions.quality == 1)][\"rich\"])\n",
+    "    energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\"rich\"]\n",
+    ")\n",
     "energy_found = ak.to_numpy(\n",
-    "    energy_emissions[(~energy_emissions.lost)\n",
-    "                     & (energy_emissions.quality == 1)][\"energy\"])\n",
+    "    energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
+    "        \"energy\"\n",
+    "    ]\n",
+    ")\n",
     "\n",
     "velo_lost = ak.to_numpy(\n",
-    "    energy_emissions[(energy_emissions.lost)\n",
-    "                     & (energy_emissions.quality == 1)][\"velo\"])\n",
+    "    energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\"velo\"]\n",
+    ")\n",
     "rich_lost = ak.to_numpy(\n",
-    "    energy_emissions[(energy_emissions.lost)\n",
-    "                     & (energy_emissions.quality == 1)][\"rich\"])\n",
+    "    energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\"rich\"]\n",
+    ")\n",
     "energy_lost = ak.to_numpy(\n",
-    "    energy_emissions[(energy_emissions.lost)\n",
-    "                     & (energy_emissions.quality == 1)][\"energy\"])\n",
+    "    energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
+    "        \"energy\"\n",
+    "    ]\n",
+    ")\n",
     "\n",
     "diff_found = velo_found - rich_found  # / energy_found\n",
     "diff_lost = velo_lost - rich_lost  # / energy_lost\n",
@@ -1199,9 +1226,11 @@
     "# number of brem vtx with E>x*E_0\n",
     "\n",
     "number_velo = ak.to_numpy(\n",
-    "    energy_emissions[energy_emissions.quality == 1][\"velo_length\"])\n",
+    "    energy_emissions[energy_emissions.quality == 1][\"velo_length\"]\n",
+    ")\n",
     "number_rich = ak.to_numpy(\n",
-    "    energy_emissions[energy_emissions.quality == 1][\"rich_length\"])\n",
+    "    energy_emissions[energy_emissions.quality == 1][\"rich_length\"]\n",
+    ")\n",
     "\n",
     "plt.hist(\n",
     "    number_velo,\n",
diff --git a/notebooks/trackinglosses_rad_length_endVelo2endUT.ipynb b/notebooks/trackinglosses_rad_length_endVelo2endUT.ipynb
index 8c84b78..b906e87 100644
--- a/notebooks/trackinglosses_rad_length_endVelo2endUT.ipynb
+++ b/notebooks/trackinglosses_rad_length_endVelo2endUT.ipynb
@@ -515,14 +515,135 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>phi</th>\n",
+       "      <th>eta</th>\n",
+       "      <th>rad_length_frac</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-87.0</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>0.1286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>72.0</td>\n",
+       "      <td>5.6</td>\n",
+       "      <td>0.1478</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>55.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.1660</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>55.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.1660</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>11.0</td>\n",
+       "      <td>8.4</td>\n",
+       "      <td>0.1065</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48285</th>\n",
+       "      <td>-81.0</td>\n",
+       "      <td>7.7</td>\n",
+       "      <td>0.1921</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48286</th>\n",
+       "      <td>35.0</td>\n",
+       "      <td>7.6</td>\n",
+       "      <td>0.2407</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48287</th>\n",
+       "      <td>63.0</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>0.2418</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48288</th>\n",
+       "      <td>13.0</td>\n",
+       "      <td>6.2</td>\n",
+       "      <td>0.1719</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48289</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.8</td>\n",
+       "      <td>0.1334</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>48290 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        phi  eta  rad_length_frac\n",
+       "0     -87.0  7.0           0.1286\n",
+       "1      72.0  5.6           0.1478\n",
+       "2      55.0  5.0           0.1660\n",
+       "3      55.0  5.0           0.1660\n",
+       "4      11.0  8.4           0.1065\n",
+       "...     ...  ...              ...\n",
+       "48285 -81.0  7.7           0.1921\n",
+       "48286  35.0  7.6           0.2407\n",
+       "48287  63.0  7.2           0.2418\n",
+       "48288  13.0  6.2           0.1719\n",
+       "48289   0.0  4.8           0.1334\n",
+       "\n",
+       "[48290 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df = pd.DataFrame({\n",
     "    \"phi\": phi_a * 90.0 / np.pi,\n",
     "    \"eta\": eta_a * 2.0,\n",
     "    \"rad_length_frac\": rad_length_frac_a,\n",
     "})\n",
-    "df = df.round({\"phi\": 0, \"eta\": 1, \"rad_length_frac\": 4})"
+    "df = df.round({\"phi\": 0, \"eta\": 1, \"rad_length_frac\": 4})\n",
+    "df"
    ]
   },
   {
@@ -956,38 +1077,40 @@
    ],
    "source": [
     "fig = plt.figure(figsize=(15, 7))\n",
-    "ax = sns.heatmap(df_pivoted,\n",
-    "                 robust=True,\n",
-    "                 square=False,\n",
-    "                 cmap=colormaps[\"rainbow\"],\n",
-    "                 xticklabels=False,\n",
-    "                 yticklabels=False,\n",
-    "                 vmax=0.7,\n",
-    "                 cbar_kws={\n",
-    "                     'label': r'$x/X_0$',\n",
-    "                     'pad': 0.005,\n",
-    "                     'shrink': 1,\n",
-    "                     'ticks': [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7],\n",
-    "                     'aspect': 15\n",
-    "                 })\n",
+    "ax = sns.heatmap(\n",
+    "    df_pivoted,\n",
+    "    robust=True,\n",
+    "    square=False,\n",
+    "    cmap=colormaps[\"rainbow\"],\n",
+    "    xticklabels=False,\n",
+    "    yticklabels=False,\n",
+    "    vmax=0.7,\n",
+    "    cbar_kws={\n",
+    "        \"label\": r\"$x/X_0$\",\n",
+    "        \"pad\": 0.005,\n",
+    "        \"shrink\": 1,\n",
+    "        \"ticks\": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7],\n",
+    "        \"aspect\": 15,\n",
+    "    },\n",
+    ")\n",
     "# ax.set_yticks([5, 15, 25, 35], [2, 3, 4, 5])\n",
     "ax.set_yticks([0, 20, 40, 60], [2, 3, 4, 5])\n",
-    "ax.set_xticks([39, 89, 139],\n",
-    "              [-100, 0, 100])  # ([79, 179, 279], [-100, 0, 100])\n",
+    "ax.set_xticks([39, 89, 139], [-100, 0, 100])  # ([79, 179, 279], [-100, 0, 100])\n",
     "ax.set_xlabel(f\"$\\phi$ [deg]\")\n",
     "ax.set_ylabel(f\"$\\eta$\")\n",
-    "ax.patch.set_edgecolor('black')\n",
+    "ax.patch.set_edgecolor(\"black\")\n",
     "\n",
     "ax.patch.set_linewidth(2)\n",
     "# ax.set_yticklabels([])\n",
     "ax.invert_yaxis()\n",
     "# ax.set_title(\"EndVELO to EndUT $x/X_0$\", size=35)\n",
     "mplhep.lhcb.text(\n",
-    "    \"Simulation    \\qquad \\qquad \\qquad    EndVELO to EndUT $x/X_0$\", loc=0)\n",
+    "    \"Simulation    \\qquad \\qquad \\qquad    EndVELO to EndUT $x/X_0$\", loc=0\n",
+    ")\n",
     "# plt.show()\n",
     "plt.savefig(\n",
-    "    \"/work/cetin/Projektpraktikum/thesis/rad_length_frac_eta_phi_2.pdf\",\n",
-    "    format=\"PDF\")"
+    "    \"/work/cetin/Projektpraktikum/thesis/rad_length_frac_eta_phi_2.pdf\", format=\"PDF\"\n",
+    ")"
    ]
   },
   {
diff --git a/thesis/Efficiency_PdP_Velo_hist2d.pdf b/thesis/Efficiency_PdP_Velo_hist2d.pdf
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diff --git a/thesis/brem_vtx_hist2d_found.pdf b/thesis/brem_vtx_hist2d_found.pdf
index 2a6498a..5a27fd4 100644
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diff --git a/thesis/brem_vtx_hist2d_lost.pdf b/thesis/brem_vtx_hist2d_lost.pdf
index da5c5bd..6d57a0f 100644
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diff --git a/thesis/emitted_energy_upstream.pdf b/thesis/emitted_energy_upstream.pdf
new file mode 100644
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diff --git a/thesis/emitted_energy_upstream_mean.pdf b/thesis/emitted_energy_upstream_mean.pdf
new file mode 100644
index 0000000..e4d861d
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diff --git a/thesis/emitted_energy_velo_mean.pdf b/thesis/emitted_energy_velo_mean.pdf
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diff --git a/thesis/match_true_zmag_e_kaon.pdf b/thesis/match_true_zmag_e_kaon.pdf
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