part2_meantimers.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# **Implementation and optimization of the mean-timer technique in drift tube detectors**\n",
    "\n",
    "### *Students:* Barone Francesco Pio, Nagaro Gianmarco, Ninni Daniele, Valentini Lorenzo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Part 2** *Implementation of the mean-timer algorithm*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mean-timer equations relate the drift times produced by a track in consecutive layers of a superlayer to the maximum drift time $T_{max}$ in a semi-cell. They derive from Thales's theorem and hold under the assumption of a constant drift velocity.\n",
    "\n",
    "Let's use the following picture as reference:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "![](./img/angles.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mathematical expression of the mean-timer equations depends both on the track angle and on the pattern of cells hit by the track. In the simple case that the track crosses a semi-column of cells (i.e. the interested wires are at the same position for each couple of staggered cells), the corresponding mean-timer equations are the following:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- ***Layers 1-2-3***:\n",
    "\n",
    "$$\n",
    "T_{max} = \\frac{(t_1-t_0) + (t_3 - t_0)}{2} + (t_2 - t_0)   \\iff   t_0^{123} = \\frac{t_1 + 2t_2 + t_3 - 2T_{max}}{4}\n",
    "$$\n",
    "\n",
    "- ***Layers 1-2-4***:\n",
    "\n",
    "$$\n",
    "T_{max} = \\frac{3(t_2-t_0)}{2} + t_1 - \\frac{(t_4 - t_0)}{2}   \\iff   t_0^{124} = \\frac{2t_1 + 3t_2 - t_4 - 2T_{max}}{4}\n",
    "$$\n",
    "\n",
    "- ***Layers 1-3-4***:\n",
    "\n",
    "$$\n",
    "T_{max} = \\frac{3(t_3-t_0)}{2} + t_4 - \\frac{(t_1 - t_0)}{2}   \\iff   t_0^{134} = \\frac{-t_1 + 3t_3 + 2t_4 - 2T_{max}}{4}\n",
    "$$\n",
    "\n",
    "- ***Layers 2-3-4***:\n",
    "\n",
    "$$\n",
    "T_{max} = \\frac{(t_2-t_0) + (t_4 - t_0)}{2} + (t_3 - t_0)   \\iff   t_0^{234} = \\frac{t_2 + 2t_3 + t_4 - 2T_{max}}{4}\n",
    "$$\n",
    "\n",
    "- ***Layers 1-2-3-4***:\n",
    "\n",
    "$$\n",
    "t_0^{1234} = \\frac{t_0^{123} + t_0^{124} + t_0^{134} + t_0^{234}}{4} = \\frac{t_1 + 3t_2 + 3t_3 + t_4 - 4T_{max}}{8}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given the logic under the events selection algorithm implemented in the **Part 1** of this project, and also given that the particles in question usually hit the detector with a trajectory more or less perpendicular to the direction of the layers, it makes sense to implement only the above formulas in the mean-timer algorithm. The error introduced by this simplification will be evaluated in the **Part 3** of this project.\n",
    "\n",
    "It is important to note that, in the case of 4-hits events, the time pedestal $t_0$ is simply computed using the analytical expression of the mean of the 3-hits formulas. In this case, however, the mean-timer algorithm will exploit the extra hit in excess to perform a further events selection, i.e., it will be able to identify and, eventually, drop events corresponding to time pedestals that cannot be properly computed using the above formula.\n",
    "\n",
    "The performance of the mean-timer algorithm benefits from the vectorization capabilities provided by the *pandas* DataFrame structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import numpy.random as npr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from bin.plotters import plot_event_from_dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>L1_HIT</th>\n",
       "      <th>L1_TIME</th>\n",
       "      <th>L1_CELL</th>\n",
       "      <th>L2_HIT</th>\n",
       "      <th>L2_TIME</th>\n",
       "      <th>L2_CELL</th>\n",
       "      <th>L3_HIT</th>\n",
       "      <th>L3_TIME</th>\n",
       "      <th>L3_CELL</th>\n",
       "      <th>L4_HIT</th>\n",
       "      <th>L4_TIME</th>\n",
       "      <th>L4_CELL</th>\n",
       "      <th>DETECTOR</th>\n",
       "      <th>LAYERS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>1.915090e+07</td>\n",
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       "      <th>1</th>\n",
       "      <td>5076</td>\n",
       "      <td>2.207774e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>5074</td>\n",
       "      <td>2.207774e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>5075</td>\n",
       "      <td>2.207774e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>5072</td>\n",
       "      <td>2.207774e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1234</td>\n",
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       "      <th>2</th>\n",
       "      <td>5977</td>\n",
       "      <td>2.616131e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>5975</td>\n",
       "      <td>2.616131e+09</td>\n",
       "      <td>0</td>\n",
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       "      <td>&lt;NA&gt;</td>\n",
       "      <td>5976</td>\n",
       "      <td>2.616131e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>124</td>\n",
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       "      <th>3</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>8354</td>\n",
       "      <td>3.655548e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>8356</td>\n",
       "      <td>3.655548e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>8355</td>\n",
       "      <td>3.655548e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8595</td>\n",
       "      <td>3.765115e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>8596</td>\n",
       "      <td>3.765115e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>8597</td>\n",
       "      <td>3.765116e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>124</td>\n",
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       "      <th>109859</th>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>1300161</td>\n",
       "      <td>5.243584e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1300160</td>\n",
       "      <td>5.243584e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1300162</td>\n",
       "      <td>5.243584e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
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       "      <th>109860</th>\n",
       "      <td>1303356</td>\n",
       "      <td>5.257448e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1303355</td>\n",
       "      <td>5.257448e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1303354</td>\n",
       "      <td>5.257448e+11</td>\n",
       "      <td>15</td>\n",
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       "      <td>&lt;NA&gt;</td>\n",
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       "      <td>15</td>\n",
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       "      <td>5.264188e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1304865</td>\n",
       "      <td>5.264188e+11</td>\n",
       "      <td>15</td>\n",
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       "      <td>234</td>\n",
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       "      <td>5.269320e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1306056</td>\n",
       "      <td>5.269320e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>234</td>\n",
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       "      <th>109863</th>\n",
       "      <td>1307673</td>\n",
       "      <td>5.276306e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1307672</td>\n",
       "      <td>5.276306e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1307674</td>\n",
       "      <td>5.276306e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>1307671</td>\n",
       "      <td>5.276306e+11</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>1234</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>109864 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         L1_HIT       L1_TIME  L1_CELL   L2_HIT       L2_TIME  L2_CELL  \\\n",
       "0            47  1.915090e+07        0       49  1.915103e+07        0   \n",
       "1          5076  2.207774e+09        0     5074  2.207774e+09        0   \n",
       "2          5977  2.616131e+09        0     5975  2.616131e+09        0   \n",
       "3          <NA>           NaN     <NA>     8354  3.655548e+09        0   \n",
       "4          8595  3.765115e+09        0     8596  3.765115e+09        0   \n",
       "...         ...           ...      ...      ...           ...      ...   \n",
       "109859     <NA>           NaN     <NA>  1300161  5.243584e+11       15   \n",
       "109860  1303356  5.257448e+11       15  1303355  5.257448e+11       15   \n",
       "109861     <NA>           NaN     <NA>  1304864  5.264188e+11       15   \n",
       "109862     <NA>           NaN     <NA>  1306057  5.269320e+11       15   \n",
       "109863  1307673  5.276306e+11       15  1307672  5.276306e+11       15   \n",
       "\n",
       "         L3_HIT       L3_TIME  L3_CELL   L4_HIT       L4_TIME  L4_CELL  \\\n",
       "0            45  1.915083e+07        0       48  1.915104e+07        0   \n",
       "1          5075  2.207774e+09        0     5072  2.207774e+09        0   \n",
       "2          <NA>           NaN     <NA>     5976  2.616131e+09        0   \n",
       "3          8356  3.655548e+09        0     8355  3.655548e+09        0   \n",
       "4          <NA>           NaN     <NA>     8597  3.765116e+09        0   \n",
       "...         ...           ...      ...      ...           ...      ...   \n",
       "109859  1300160  5.243584e+11       15  1300162  5.243584e+11       15   \n",
       "109860  1303354  5.257448e+11       15     <NA>           NaN     <NA>   \n",
       "109861  1304866  5.264188e+11       15  1304865  5.264188e+11       15   \n",
       "109862  1306058  5.269320e+11       15  1306056  5.269320e+11       15   \n",
       "109863  1307674  5.276306e+11       15  1307671  5.276306e+11       15   \n",
       "\n",
       "        DETECTOR LAYERS  \n",
       "0              1   1234  \n",
       "1              1   1234  \n",
       "2              1    124  \n",
       "3              1    234  \n",
       "4              1    124  \n",
       "...          ...    ...  \n",
       "109859         4    234  \n",
       "109860         4    123  \n",
       "109861         4    234  \n",
       "109862         4    234  \n",
       "109863         4   1234  \n",
       "\n",
       "[109864 rows x 14 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the dataset containing the events identified in PART 1\n",
    "source_file = './tmp/262_0000_preprocessed.txt' # '/home/lab/dat/262_0000_preprocessed.txt'\n",
    "events = pd.read_csv(source_file, sep=\",\")\n",
    "events['LAYERS'] = events['LAYERS'].astype(str)\n",
    "for i in range(1, 5):\n",
    "    events['L'+str(i)+'_HIT'] = events['L'+str(i)+'_HIT'].astype('Int64')\n",
    "    events['L'+str(i)+'_CELL'] = events['L'+str(i)+'_CELL'].astype('Int64')\n",
    "events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "604 ms ± 7.91 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "# define the function that computes the crossing angle\n",
    "#         ti : time recorded by the i-th layer's cell\n",
    "#         tj : time recorded by the (i+2)-th layer's cell\n",
    "#    v_drift : drift velocity\n",
    "#          h : height of each cell\n",
    "# angle_sign : sign of the crossing angle (deduced by applying the mean-timer technique)\n",
    "def crossing_angle(ti, tj, v_drift, h, angle_sign):\n",
    "    \n",
    "    dx = np.abs(v_drift * (ti-tj))   # projection of the distance between the two hits along the direction of the layers\n",
    "    angle_tan = dx / (2*h)   # tangent of the crossing angle\n",
    "    angle = angle_sign * np.rad2deg(np.arctan(angle_tan))\n",
    "    \n",
    "    return angle\n",
    "\n",
    "# define the functions that apply the mean-timer technique to the dataset containing the events\n",
    "#    tmax : maximum drift time\n",
    "# v_drift : drift velocity\n",
    "#       h : height of each cell\n",
    "def meantimer_123(dataframe, tmax, v_drift, h):   # case layers 1-2-3\n",
    "    \n",
    "    df = dataframe.copy()\n",
    "    t1, t2, t3 = df['L1_TIME'], df['L2_TIME'], df['L3_TIME']\n",
    "    c1, c2, c3 = df['L1_CELL'], df['L2_CELL'], df['L3_CELL']\n",
    "    \n",
    "    df['PEDESTAL'] = (t1 + 2*t2 + t3 - 2*tmax) / 4\n",
    "    \n",
    "    mask = (c2 == c1)\n",
    "    \n",
    "    df.loc[mask, 'PATTERN'] = 'LRL_'\n",
    "    df.loc[mask, 'ANGLE'] = crossing_angle(t1, t3, v_drift, h, np.sign(t1-t3))\n",
    "    \n",
    "    df.loc[~mask, 'PATTERN'] = 'RLR_'\n",
    "    df.loc[~mask, 'ANGLE'] = crossing_angle(t1, t3, v_drift, h, np.sign(t3-t1))\n",
    "    \n",
    "    return df\n",
    "\n",
    "def meantimer_124(dataframe, tmax, v_drift, h):   # case layers 1-2-4\n",
    "    \n",
    "    df = dataframe.copy()\n",
    "    t1, t2, t4 = df['L1_TIME'], df['L2_TIME'], df['L4_TIME']\n",
    "    c1, c2, c4 = df['L1_CELL'], df['L2_CELL'], df['L4_CELL']\n",
    "    \n",
    "    df['PEDESTAL'] = (2*t1 + 3*t2 - t4 -2*tmax) / 4\n",
    "    \n",
    "    mask = (c2 == c1)\n",
    "    \n",
    "    df.loc[mask, 'PATTERN'] = 'LR_R'\n",
    "    df.loc[mask, 'ANGLE'] = crossing_angle(t2, t4, v_drift, h, np.sign(t4-t2))\n",
    "    \n",
    "    df.loc[~mask, 'PATTERN'] = 'RL_L'\n",
    "    df.loc[~mask, 'ANGLE'] = crossing_angle(t2, t4, v_drift, h, np.sign(t2-t4))\n",
    "    \n",
    "    return df\n",
    "\n",
    "def meantimer_134(dataframe, tmax, v_drift, h):   # case layers 1-3-4\n",
    "    \n",
    "    df = dataframe.copy()\n",
    "    t1, t3, t4 = df['L1_TIME'], df['L3_TIME'], df['L4_TIME']\n",
    "    c1, c3, c4 = df['L1_CELL'], df['L3_CELL'], df['L4_CELL']\n",
    "    \n",
    "    df['PEDESTAL'] = (-t1 + 3*t3 + 2*t4 -2*tmax) / 4\n",
    "    \n",
    "    mask = (c4 == c1)\n",
    "    \n",
    "    df.loc[mask, 'PATTERN'] = 'L_LR'\n",
    "    df.loc[mask, 'ANGLE'] = crossing_angle(t1, t3, v_drift, h, np.sign(t1-t3))\n",
    "    \n",
    "    df.loc[~mask, 'PATTERN'] = 'R_RL'\n",
    "    df.loc[~mask, 'ANGLE'] = crossing_angle(t1, t3, v_drift, h, np.sign(t3-t1))\n",
    "    \n",
    "    return df\n",
    "\n",
    "def meantimer_234(dataframe, tmax, v_drift, h):   # case layers 2-3-4\n",
    "    \n",
    "    df = dataframe.copy()\n",
    "    t2, t3, t4 = df['L2_TIME'], df['L3_TIME'], df['L4_TIME']\n",
    "    c2, c3, c4 = df['L2_CELL'], df['L3_CELL'], df['L4_CELL']\n",
    "    \n",
    "    df['PEDESTAL'] = (t2 + 2*t3 + t4 -2*tmax) / 4\n",
    "    \n",
    "    mask = (c3 == c2)\n",
    "    \n",
    "    df.loc[mask, 'PATTERN'] = '_RLR'\n",
    "    df.loc[mask, 'ANGLE'] = crossing_angle(t2, t4, v_drift, h, np.sign(t4-t2))\n",
    "    \n",
    "    df.loc[~mask, 'PATTERN'] = '_LRL'\n",
    "    df.loc[~mask, 'ANGLE'] = crossing_angle(t2, t4, v_drift, h, np.sign(t2-t4))\n",
    "    \n",
    "    return df\n",
    " \n",
    "def meantimer_1234(dataframe, tmax, v_drift, h):   # case layers 1-2-3-4\n",
    "    \n",
    "    df = dataframe.copy()\n",
    "    t1, t2, t3, t4 = df['L1_TIME'], df['L2_TIME'], df['L3_TIME'], df['L4_TIME']\n",
    "    c1, c2, c3, c4 = df['L1_CELL'], df['L2_CELL'], df['L3_CELL'], df['L4_CELL']\n",
    "    \n",
    "    df['PEDESTAL'] = (t1 + 3*t2 + 3*t3 + t4 - 4*tmax) / 8\n",
    "    \n",
    "    mask = (c4 == c1)\n",
    "    angles_tol = 5   # tolerance (deg) on the differences between [crossing angles computed using layers 1-3] and [crossing angles computed using layers 2-4]\n",
    "    \n",
    "    df.loc[mask, 'PATTERN'] = 'LRLR'\n",
    "    angles_13 = crossing_angle(t1, t3, v_drift, h, np.sign(t1-t3))\n",
    "    angles_24 = crossing_angle(t2, t4, v_drift, h, np.sign(t4-t2))\n",
    "    d_angles = np.abs(angles_13 - angles_24)\n",
    "    angles_mask = (d_angles < angles_tol)\n",
    "    df.loc[mask & angles_mask, 'ANGLE'] = ((angles_13 + angles_24) / 2)\n",
    "    df.loc[mask & ~angles_mask, 'ANGLE'] = 'FAIL'\n",
    "    \n",
    "    df.loc[~mask, 'PATTERN'] = 'RLRL'\n",
    "    angles_13 = crossing_angle(t1, t3, v_drift, h, np.sign(t3-t1))\n",
    "    angles_24 = crossing_angle(t2, t4, v_drift, h, np.sign(t2-t4))\n",
    "    d_angles = np.abs(angles_13 - angles_24)\n",
    "    angles_mask = (d_angles < angles_tol)\n",
    "    df.loc[~mask & angles_mask, 'ANGLE'] = ((angles_13 + angles_24) / 2)\n",
    "    df.loc[~mask & ~angles_mask, 'ANGLE'] = 'FAIL'\n",
    "\n",
    "    return df\n",
    "    \n",
    "def meantimer(dataframe):\n",
    "    \n",
    "    df = dataframe.copy()\n",
    "    \n",
    "    # dictionary used to select the appropriate function\n",
    "    meantimers = {'123'  : meantimer_123,\n",
    "                  '124'  : meantimer_124,\n",
    "                  '134'  : meantimer_134,\n",
    "                  '234'  : meantimer_234,\n",
    "                  '1234' : meantimer_1234}\n",
    "\n",
    "    # dictionary used to convert the pattern of the trajectory into signs of the positions in the cells\n",
    "    LR_to_sign = {'L' : -1,\n",
    "                  'R' : +1,\n",
    "                  '_' : 0}\n",
    "    \n",
    "    # detector parameters\n",
    "    tmax = 390   # maximum drift time (ns)\n",
    "    L = 42   # length of each cell (mm)\n",
    "    h = 13   # height of each cell (mm)\n",
    "    v_drift = L / (2*tmax)   # drift velocity (mm/ns)\n",
    "    \n",
    "    # apply the mean-timer functions to the dataset\n",
    "    df['PEDESTAL'] = pd.Series(dtype='float')\n",
    "    df['PATTERN'] = pd.Series(dtype='str')\n",
    "    df['ANGLE'] = pd.Series(dtype='float')\n",
    "    \n",
    "    for i in meantimers:\n",
    "        mask = (df['LAYERS'] == i)\n",
    "        df[mask] = (meantimers[i])(df[mask], tmax, v_drift, h)\n",
    "        \n",
    "    df = df[df['ANGLE'] != 'FAIL']   # reject 4-hits events for which it is not possible to compute the crossing angle properly\n",
    "    \n",
    "    for i in range(1, 5):\n",
    "        df['L'+str(i)+'_DRIFT'] = df['L'+str(i)+'_TIME'] - df['PEDESTAL']\n",
    "        df = df[((df['L'+str(i)+'_DRIFT'] < tmax) & (df['L'+str(i)+'_DRIFT'] > 0)) | (np.isnan(df['L'+str(i)+'_DRIFT']))]   # reject events with drift times >= 'tmax' or <= 0\n",
    "        df['L'+str(i)+'_X'] = v_drift * df['L'+str(i)+'_DRIFT'] * (df['PATTERN'].str[i-1]).replace(LR_to_sign)\n",
    "    \n",
    "    df = df.reset_index(drop=True)\n",
    "    \n",
    "    return df\n",
    "\n",
    "%timeit meantimer(events)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "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>PEDESTAL</th>\n",
       "      <th>PATTERN</th>\n",
       "      <th>ANGLE</th>\n",
       "      <th>L1_DRIFT</th>\n",
       "      <th>L1_X</th>\n",
       "      <th>L2_DRIFT</th>\n",
       "      <th>L2_X</th>\n",
       "      <th>L3_DRIFT</th>\n",
       "      <th>L3_X</th>\n",
       "      <th>L4_DRIFT</th>\n",
       "      <th>L4_X</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.207773e+09</td>\n",
       "      <td>LRLR</td>\n",
       "      <td>-8.9732</td>\n",
       "      <td>166.562500</td>\n",
       "      <td>-8.968750</td>\n",
       "      <td>189.062500</td>\n",
       "      <td>10.180288</td>\n",
       "      <td>239.062500</td>\n",
       "      <td>-12.872596</td>\n",
       "      <td>109.062500</td>\n",
       "      <td>5.872596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.655548e+09</td>\n",
       "      <td>_RLR</td>\n",
       "      <td>20.5313</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.708333</td>\n",
       "      <td>1.222756</td>\n",
       "      <td>276.875000</td>\n",
       "      <td>-14.908654</td>\n",
       "      <td>203.541667</td>\n",
       "      <td>10.959936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.305668e+09</td>\n",
       "      <td>_RLR</td>\n",
       "      <td>22.668</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>22.500000</td>\n",
       "      <td>1.211538</td>\n",
       "      <td>266.666667</td>\n",
       "      <td>-14.358974</td>\n",
       "      <td>224.166667</td>\n",
       "      <td>12.070513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.527147e+09</td>\n",
       "      <td>_RLR</td>\n",
       "      <td>12.457</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.416666</td>\n",
       "      <td>2.983974</td>\n",
       "      <td>281.250000</td>\n",
       "      <td>-15.144231</td>\n",
       "      <td>162.083333</td>\n",
       "      <td>8.727564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.472991e+09</td>\n",
       "      <td>LR_R</td>\n",
       "      <td>10.367</td>\n",
       "      <td>275.833333</td>\n",
       "      <td>-14.852564</td>\n",
       "      <td>158.333333</td>\n",
       "      <td>8.525641</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>246.666666</td>\n",
       "      <td>13.282051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94750</th>\n",
       "      <td>5.243584e+11</td>\n",
       "      <td>_RLR</td>\n",
       "      <td>17.7072</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>213.958313</td>\n",
       "      <td>11.520832</td>\n",
       "      <td>98.958313</td>\n",
       "      <td>-5.328525</td>\n",
       "      <td>368.125000</td>\n",
       "      <td>19.822115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94751</th>\n",
       "      <td>5.257448e+11</td>\n",
       "      <td>LRL_</td>\n",
       "      <td>18.3332</td>\n",
       "      <td>202.500000</td>\n",
       "      <td>-10.903846</td>\n",
       "      <td>267.500000</td>\n",
       "      <td>14.403846</td>\n",
       "      <td>42.500000</td>\n",
       "      <td>-2.288462</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94752</th>\n",
       "      <td>5.264188e+11</td>\n",
       "      <td>_RLR</td>\n",
       "      <td>22.4994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>3.769231</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>-11.846154</td>\n",
       "      <td>270.000000</td>\n",
       "      <td>14.538462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94753</th>\n",
       "      <td>5.269320e+11</td>\n",
       "      <td>_RLR</td>\n",
       "      <td>2.07564</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.041687</td>\n",
       "      <td>0.863783</td>\n",
       "      <td>365.208374</td>\n",
       "      <td>-19.665066</td>\n",
       "      <td>33.541687</td>\n",
       "      <td>1.806091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94754</th>\n",
       "      <td>5.276306e+11</td>\n",
       "      <td>LRLR</td>\n",
       "      <td>-10.0147</td>\n",
       "      <td>198.437500</td>\n",
       "      <td>-10.685096</td>\n",
       "      <td>128.437500</td>\n",
       "      <td>6.915865</td>\n",
       "      <td>304.270874</td>\n",
       "      <td>-16.383816</td>\n",
       "      <td>63.437500</td>\n",
       "      <td>3.415865</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>94755 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           PEDESTAL PATTERN    ANGLE    L1_DRIFT       L1_X    L2_DRIFT  \\\n",
       "0      2.207773e+09    LRLR  -8.9732  166.562500  -8.968750  189.062500   \n",
       "1      3.655548e+09    _RLR  20.5313         NaN        NaN   22.708333   \n",
       "2      4.305668e+09    _RLR   22.668         NaN        NaN   22.500000   \n",
       "3      5.527147e+09    _RLR   12.457         NaN        NaN   55.416666   \n",
       "4      8.472991e+09    LR_R   10.367  275.833333 -14.852564  158.333333   \n",
       "...             ...     ...      ...         ...        ...         ...   \n",
       "94750  5.243584e+11    _RLR  17.7072         NaN        NaN  213.958313   \n",
       "94751  5.257448e+11    LRL_  18.3332  202.500000 -10.903846  267.500000   \n",
       "94752  5.264188e+11    _RLR  22.4994         NaN        NaN   70.000000   \n",
       "94753  5.269320e+11    _RLR  2.07564         NaN        NaN   16.041687   \n",
       "94754  5.276306e+11    LRLR -10.0147  198.437500 -10.685096  128.437500   \n",
       "\n",
       "            L2_X    L3_DRIFT       L3_X    L4_DRIFT       L4_X  \n",
       "0      10.180288  239.062500 -12.872596  109.062500   5.872596  \n",
       "1       1.222756  276.875000 -14.908654  203.541667  10.959936  \n",
       "2       1.211538  266.666667 -14.358974  224.166667  12.070513  \n",
       "3       2.983974  281.250000 -15.144231  162.083333   8.727564  \n",
       "4       8.525641         NaN        NaN  246.666666  13.282051  \n",
       "...          ...         ...        ...         ...        ...  \n",
       "94750  11.520832   98.958313  -5.328525  368.125000  19.822115  \n",
       "94751  14.403846   42.500000  -2.288462         NaN        NaN  \n",
       "94752   3.769231  220.000000 -11.846154  270.000000  14.538462  \n",
       "94753   0.863783  365.208374 -19.665066   33.541687   1.806091  \n",
       "94754   6.915865  304.270874 -16.383816   63.437500   3.415865  \n",
       "\n",
       "[94755 rows x 11 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "events = meantimer(events)\n",
    "#events = events[events['ANGLE'] == 'FAIL']\n",
    "events[['PEDESTAL', 'PATTERN', 'ANGLE', 'L1_DRIFT', 'L1_X', 'L2_DRIFT', 'L2_X', 'L3_DRIFT', 'L3_X', 'L4_DRIFT', 'L4_X']]\n",
    "#events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write the DataFrame 'events' to a csv file\n",
    "output_file = './tmp/262_0000_meantimers.txt' #'/home/lab/dat/262_0000_meantimers.txt'\n",
    "events.to_csv(output_file, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load the DataFrame 'events' from file\n",
    "events = pd.read_csv(output_file, sep=\",\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## **2.1** *Visualization of the resulting tracks*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x240 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x240 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x240 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x240 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x240 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot 5 random events\n",
    "for i in range(5):\n",
    "    j = npr.randint(0, len(events))\n",
    "    plot_event_from_dataframe(events, index=j, title=f'Event #{j}', focus_area=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## **2.2** *Distributions of the drift times*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1584x792 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = ['tomato', 'gold', 'seagreen', 'dodgerblue']\n",
    "fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(22, 11))\n",
    "for i in range(ax.shape[0]):\n",
    "    for j in range(ax.shape[1]):\n",
    "        layer = str(i+2*j+1)\n",
    "        plot = sns.histplot(data=events, x='L'+layer+'_DRIFT', hue='DETECTOR', hue_order=[4, 3, 1, 2], stat='count', bins=40, kde=True, palette=cmap, ax=ax[i][j])\n",
    "        plot.set(title='LAYER '+layer+' - DRIFT TIMES', xlabel='drift time $(ns)$', ylabel='count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1584x792 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(nrows=2, ncols=2, figsize=(22, 11))\n",
    "for i in range(ax.shape[0]):\n",
    "    for j in range(ax.shape[1]):\n",
    "        layer = str(i+2*j+1)\n",
    "        plot = sns.histplot(data=events, x='L'+layer+'_DRIFT', stat='count', bins=40, kde=True, ax=ax[i][j])\n",
    "        plot.set(title='LAYER '+layer+' - DRIFT TIMES', xlabel='drift time $(ns)$', ylabel='count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **2.3** *Distributions of the crossing angles*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 9))\n",
    "plot = sns.histplot(data=events, x='ANGLE', hue='DETECTOR', hue_order=[4, 3, 1, 2], stat='count', bins=80, kde=True, palette=cmap, ax=ax)\n",
    "plot.set(title='CROSSING ANGLES', xlabel='crossing angle $(deg)$', ylabel='count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 9))\n",
    "plot = sns.histplot(data=events, x='ANGLE', stat='count', bins=80, kde=True, ax=ax)\n",
    "plot.set(title='CROSSING ANGLES', xlabel='crossing angle $(deg)$', ylabel='count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Appendix** *Previous versions of the algorithms*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **1)** Event detection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "def find_events(data):\n",
    "    \n",
    "    # find candidates corresponding to the 'left' configuration\n",
    "    print('Finding candidates corresponding to the \"left\" configuration ...')\n",
    "    left_size = data.groupby(['ORBIT_CNT', 'tile']).size().to_frame('size')\n",
    "    left = data.join(left_size, on=['ORBIT_CNT', 'tile'])\n",
    "    data_reduced = left[~left['size'].between(3, 4)].drop('size', 1)\n",
    "    left = left[left['size'].between(3, 4)]\n",
    "    left['event_id'] = left['ORBIT_CNT'].astype(str) + '_' + left['tile'].astype(str) + '_L'\n",
    "\n",
    "    # find candidates corresponding to the 'right' configuration\n",
    "    print('Finding candidates corresponding to the \"right\" configuration ...')\n",
    "    data_reduced.loc[data_reduced['layer'].isin([1, 3]), 'tile'] += 1\n",
    "    right_size = data_reduced.groupby(['ORBIT_CNT', 'tile']).size().to_frame('size')\n",
    "    right = data_reduced.join(right_size, on=['ORBIT_CNT', 'tile'])\n",
    "    right = right[right['size'].between(3, 4)]\n",
    "    right['event_id'] = right['ORBIT_CNT'].astype(str) + '_' + right['tile'].astype(str) + '_R'\n",
    "    right.loc[data_reduced['layer'].isin([1, 3]), 'tile'] -= 1\n",
    "   \n",
    "    # build dataframe of events\n",
    "    print('Building dataframe of events ...')\n",
    "    events = pd.concat([left, right], ignore_index=True, sort=False)\n",
    "    events = events.groupby('event_id').agg(list).reset_index()\n",
    "    \n",
    "    return events\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **2)** \"Serial\" mean-timer technique"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "# define the function that computes the crossing angle\n",
    "#         ti : time recorded by the i-th layer's cell\n",
    "#         tj : time recorded by the (i+2)-th layer's cell\n",
    "#    v_drift : drift velocity\n",
    "#          h : height of each cell\n",
    "# angle_sign : sign of the crossing angle (deduced by applying the mean-timer technique)\n",
    "def crossing_angle(ti, tj, v_drift, h, angle_sign):\n",
    "    dx = np.abs(v_drift * (ti-tj))   # projection of the distance between the two hits along the direction of the layers\n",
    "    angle_tan = dx / (2*h)   # tangent of the crossing angle\n",
    "    angle = angle_sign * np.rad2deg(np.arctan(angle_tan))\n",
    "    return angle\n",
    "\n",
    "# define the functions that apply the mean-timer technique to the single event\n",
    "#       t : list of times recorded by the cells hit by the particle\n",
    "#       c : list of indices of the cells hit by the particle\n",
    "#    tmax : maximum drift time\n",
    "# v_drift : drift velocity\n",
    "#       h : height of each cell\n",
    "def meantimer_123(t, c, tmax, v_drift, h):   # case layers 1-2-3\n",
    "    t1, t2, t3, t4 = t\n",
    "    c1, c2, c3, c4 = c\n",
    "    t0 = (t1 + 2*t2 + t3 - 2*tmax) / 4   # time pedestal\n",
    "    if c2 == c1:\n",
    "        pattern = 'LRL_'\n",
    "        angle_sign = np.sign(t1-t3)   \n",
    "    else:\n",
    "        pattern = 'RLR_'\n",
    "        angle_sign = np.sign(t3-t1)\n",
    "    angle = crossing_angle(t1, t3, v_drift, h, angle_sign)\n",
    "    return t0, pattern, angle\n",
    "\n",
    "def meantimer_124(t, c, tmax, v_drift, h):   # case layers 1-2-4\n",
    "    t1, t2, t3, t4 = t\n",
    "    c1, c2, c3, c4 = c\n",
    "    t0 = (2*t1 + 3*t2 - t4 -2*tmax) / 4   # time pedestal\n",
    "    if c2 == c1:\n",
    "        pattern = 'LR_R'\n",
    "        angle_sign = np.sign(t4-t2)   \n",
    "    else:\n",
    "        pattern = 'RL_L'\n",
    "        angle_sign = np.sign(t2-t4)  \n",
    "    angle = crossing_angle(t2, t4, v_drift, h, angle_sign)\n",
    "    return t0, pattern, angle\n",
    "\n",
    "def meantimer_134(t, c, tmax, v_drift, h):   # case layers 1-3-4\n",
    "    t1, t2, t3, t4 = t\n",
    "    c1, c2, c3, c4 = c\n",
    "    t0 = (-t1 + 3*t3 + 2*t4 -2*tmax) / 4   # time pedestal\n",
    "    if c4 == c1:\n",
    "        pattern = 'L_LR'\n",
    "        angle_sign = np.sign(t1-t3)\n",
    "    else:\n",
    "        pattern = 'R_RL'\n",
    "        angle_sign = np.sign(t3-t1)\n",
    "    angle = crossing_angle(t1, t3, v_drift, h, angle_sign)\n",
    "    return t0, pattern, angle\n",
    "\n",
    "def meantimer_234(t, c, tmax, v_drift, h):   # case layers 2-3-4\n",
    "    t1, t2, t3, t4 = t\n",
    "    c1, c2, c3, c4 = c\n",
    "    t0 = (t2 + 2*t3 + t4 -2*tmax) / 4   # time pedestal\n",
    "    if c3 == c2:\n",
    "        pattern = '_RLR'\n",
    "        angle_sign = np.sign(t4-t2)\n",
    "    else:\n",
    "        pattern = '_LRL'\n",
    "        angle_sign = np.sign(t2-t4)\n",
    "    angle = crossing_angle(t2, t4, v_drift, h, angle_sign)\n",
    "    return t0, pattern, angle\n",
    "    \n",
    "def meantimer_1234(t, c, tmax, v_drift, h):   # case layers 1-2-3-4\n",
    "    t0_123, pattern_123, angle_123 = meantimer_123(t, c, tmax, v_drift, h)\n",
    "    t0_124, pattern_124, angle_124 = meantimer_124(t, c, tmax, v_drift, h)\n",
    "    t0_134, pattern_134, angle_134 = meantimer_134(t, c, tmax, v_drift, h)\n",
    "    t0_234, pattern_234, angle_234 = meantimer_234(t, c, tmax, v_drift, h)\n",
    "    \n",
    "    pedestals, angles = [], []   # lists of plausible time pedestals and crossing angles\n",
    "    pattern = ''\n",
    "    sampling = 25   # sampling period of the acquisition system (ns)\n",
    "    \n",
    "    # case layers 1-2-3 + layers 1-2-4\n",
    "    if np.abs(t0_123 - t0_124) < sampling:\n",
    "        pedestals += [t0_123, t0_124]\n",
    "        angles += [angle_123, angle_124]\n",
    "        if pattern == '':\n",
    "            pattern = pattern_123[:-1] + pattern_124[-1]\n",
    "    \n",
    "    # case layers 1-2-3 + layers 1-3-4\n",
    "    if np.abs(t0_123 - t0_134) < sampling:\n",
    "        pedestals += [t0_123, t0_134]\n",
    "        angles += [angle_123, angle_134]\n",
    "        if pattern == '':\n",
    "            pattern = pattern_123[:2] + pattern_134[2:]\n",
    "    \n",
    "    # case layers 1-2-3 + layers 2-3-4\n",
    "    if np.abs(t0_123 - t0_234) < sampling:\n",
    "        pedestals += [t0_123, t0_234]\n",
    "        angles += [angle_123, angle_234]\n",
    "        if pattern == '':\n",
    "            pattern = pattern_123[:2] + pattern_234[2:]\n",
    "    \n",
    "    # case layers 1-2-4 + layers 1-3-4\n",
    "    if np.abs(t0_124 - t0_134) < sampling:\n",
    "        pedestals += [t0_124, t0_134]\n",
    "        angles += [angle_124, angle_134]\n",
    "        if pattern == '':\n",
    "            pattern = pattern_124[:2] + pattern_134[2:]\n",
    "    \n",
    "    # case layers 1-2-4 + layers 2-3-4\n",
    "    if np.abs(t0_124 - t0_234) < sampling:\n",
    "        pedestals += [t0_124, t0_234]\n",
    "        angles += [angle_124, angle_234]\n",
    "        if pattern == '':\n",
    "            pattern = pattern_124[:2] + pattern_234[2:]\n",
    "    \n",
    "    # case layers 1-3-4 + layers 2-3-4\n",
    "    if np.abs(t0_134 - t0_234) < sampling:\n",
    "        pedestals += [t0_134, t0_234]\n",
    "        angles += [angle_134, angle_234]\n",
    "        if pattern == '':\n",
    "            pattern = pattern_134[0] + pattern_234[1:]\n",
    "    \n",
    "    if len(pedestals) == 0:\n",
    "        return 0, 'FAIL', 0\n",
    "    else:\n",
    "        t0, angle = np.mean(pedestals), np.mean(angles)\n",
    "        return t0, pattern, angle\n",
    "\n",
    "# define the function that applies the mean-timer technique to the dataset containing the events\n",
    "def meantimer(dataframe):\n",
    "    df = dataframe.copy()\n",
    "    \n",
    "    # dictionary used to select the appropriate function\n",
    "    meantimers = {'123'  : meantimer_123,\n",
    "                  '124'  : meantimer_124,\n",
    "                  '134'  : meantimer_134,\n",
    "                  '234'  : meantimer_234,\n",
    "                  '1234' : meantimer_1234}\n",
    "\n",
    "    # dictionary used to convert the pattern of the trajectory into signs of the positions in the cells\n",
    "    LR_to_sign = {'L' : -1,\n",
    "                  'R' : +1,\n",
    "                  '_' : 0}\n",
    "    \n",
    "    # detector parameters\n",
    "    tmax = 390   # maximum drift time (ns)\n",
    "    L = 42   # length of each cell (mm)\n",
    "    h = 13   # height of each cell (mm)\n",
    "    v_drift = L / (2*tmax)   # drift velocity (mm/ns)\n",
    "    \n",
    "    # apply the mean-timer functions to the dataset\n",
    "    df[['PEDESTAL', 'PATTERN', 'ANGLE']] = df.apply(lambda row: meantimers[row['LAYERS']](row[['L1_TIME', 'L2_TIME', 'L3_TIME', 'L4_TIME']],\n",
    "                                                                                          row[['L1_CELL', 'L2_CELL', 'L3_CELL', 'L4_CELL']],\n",
    "                                                                                          tmax, v_drift, h), axis=1, result_type=\"expand\")\n",
    "    df = df[df['PATTERN'] != 'FAIL']   # reject 4-hits events for which it is not possible to compute the time pedestal properly\n",
    "    for i in range(1, 5):\n",
    "        df['L'+str(i)+'_DRIFT'] = np.abs(df['L'+str(i)+'_TIME'] - df['PEDESTAL'])\n",
    "        df = df[(df['L'+str(i)+'_DRIFT'] < tmax) | (np.isnan(df['L'+str(i)+'_DRIFT']))]   # reject events with drift times >= 'tmax'\n",
    "        df['L'+str(i)+'_X'] = v_drift * df['L'+str(i)+'_DRIFT'] * (df['PATTERN'].str[i-1]).replace(LR_to_sign)\n",
    "    \n",
    "    df = df.reset_index(drop=True)\n",
    "    return df\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **3)** \"Vectorized\" mean-timer technique, case layers 1-2-3-4 (v1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "def meantimer_1234(dataframe, tmax, v_drift, h):   # case layers 1-2-3-4\n",
    "    df = dataframe.copy()\n",
    "    temp = meantimer_123(df, tmax, v_drift, h)\n",
    "    temp.rename(columns={'PEDESTAL':'PEDESTAL_123', 'PATTERN':'PATTERN_123', 'ANGLE':'ANGLE_123'}, inplace=True)\n",
    "    temp = meantimer_124(temp, tmax, v_drift, h)\n",
    "    temp.rename(columns={'PEDESTAL':'PEDESTAL_124', 'PATTERN':'PATTERN_124', 'ANGLE':'ANGLE_124'}, inplace=True)\n",
    "    temp = meantimer_134(temp, tmax, v_drift, h)\n",
    "    temp.rename(columns={'PEDESTAL':'PEDESTAL_134', 'PATTERN':'PATTERN_134', 'ANGLE':'ANGLE_134'}, inplace=True)\n",
    "    temp = meantimer_234(temp, tmax, v_drift, h)\n",
    "    temp.rename(columns={'PEDESTAL':'PEDESTAL_234', 'PATTERN':'PATTERN_234', 'ANGLE':'ANGLE_234'}, inplace=True)\n",
    "    df['PEDESTAL'] = (temp['PEDESTAL_123'] + temp['PEDESTAL_124'] + temp['PEDESTAL_134'] + temp['PEDESTAL_234']) / 4\n",
    "    df['ANGLE'] = (temp['ANGLE_123'] + temp['ANGLE_124'] + temp['ANGLE_134'] + temp['ANGLE_234']) / 4\n",
    "    df['PATTERN'] = temp['PATTERN_123'].str[:2] + temp['PATTERN_234'].str[2:]\n",
    "    return df\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **4)** \"Vectorized\" mean-timer technique, case layers 1-2-3-4 (v2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "def meantimer_1234(dataframe, tmax, v_drift, h):   # case layers 1-2-3-4\n",
    "    \n",
    "    df = dataframe.copy()\n",
    "    t1, t2, t3, t4 = df['L1_TIME'], df['L2_TIME'], df['L3_TIME'], df['L4_TIME']\n",
    "    c1, c2, c3, c4 = df['L1_CELL'], df['L2_CELL'], df['L3_CELL'], df['L4_CELL']\n",
    "    \n",
    "    df['PEDESTAL'] = (t1 + 3*t2 + 3*t3 + t4 - 4*tmax) / 8\n",
    "    \n",
    "    mask = (c4 == c1)\n",
    "    \n",
    "    df.loc[mask, 'PATTERN'] = 'LRLR'\n",
    "    df.loc[mask, 'ANGLE'] = (crossing_angle(t1, t3, v_drift, h, np.sign(t1-t3)) + crossing_angle(t2, t4, v_drift, h, np.sign(t4-t2))) / 2\n",
    "    \n",
    "    df.loc[~mask, 'PATTERN'] = 'RLRL'\n",
    "    df.loc[~mask, 'ANGLE'] = (crossing_angle(t1, t3, v_drift, h, np.sign(t3-t1)) + crossing_angle(t2, t4, v_drift, h, np.sign(t2-t4))) / 2\n",
    "    \n",
    "    return df\n",
    "```"
   ]
  }
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