{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data management"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pyerrors as pe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data has been written using pyerrors 2.0.0.\n",
      "Format version 0.1\n",
      "Written by fjosw on 2022-01-06 11:11:19 +0100 on host XPS139305, Linux-5.11.0-44-generic-x86_64-with-glibc2.29\n",
      "\n",
      "Description:  Test data for the correlator example\n"
     ]
    }
   ],
   "source": [
    "correlator_data = pe.input.json.load_json(\"./data/correlator_test\")\n",
    "my_correlator = pe.Corr(correlator_data)\n",
    "my_correlator.gamma_method()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import autograd.numpy as anp\n",
    "def func_exp(a, x):\n",
    "    return a[1] * anp.exp(-a[0] * x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "rows = []\n",
    "for t_start in range(12, 17):\n",
    "    for t_stop in range(30, 35):\n",
    "        fr = my_correlator.fit(func_exp, [t_start, t_stop], silent=True)\n",
    "        fr.gamma_method()\n",
    "        row = {\"t_start\": t_start,\n",
    "               \"t_stop\": t_stop,\n",
    "               \"datapoints\": t_stop - t_start + 1,\n",
    "               \"chisquare_by_dof\": fr.chisquare_by_dof,\n",
    "               \"mass\": fr[0]}\n",
    "        rows.append(row)\n",
    "my_df = pd.DataFrame(rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>t_start</th>\n",
       "      <th>t_stop</th>\n",
       "      <th>datapoints</th>\n",
       "      <th>chisquare_by_dof</th>\n",
       "      <th>mass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12</td>\n",
       "      <td>30</td>\n",
       "      <td>19</td>\n",
       "      <td>0.057872</td>\n",
       "      <td>0.2218(12)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>20</td>\n",
       "      <td>0.063951</td>\n",
       "      <td>0.2221(11)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12</td>\n",
       "      <td>32</td>\n",
       "      <td>21</td>\n",
       "      <td>0.064960</td>\n",
       "      <td>0.2223(11)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "      <td>33</td>\n",
       "      <td>22</td>\n",
       "      <td>0.066495</td>\n",
       "      <td>0.2224(10)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12</td>\n",
       "      <td>34</td>\n",
       "      <td>23</td>\n",
       "      <td>0.066606</td>\n",
       "      <td>0.2225(10)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>30</td>\n",
       "      <td>18</td>\n",
       "      <td>0.051577</td>\n",
       "      <td>0.2215(12)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>13</td>\n",
       "      <td>31</td>\n",
       "      <td>19</td>\n",
       "      <td>0.060901</td>\n",
       "      <td>0.2219(11)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13</td>\n",
       "      <td>32</td>\n",
       "      <td>20</td>\n",
       "      <td>0.063551</td>\n",
       "      <td>0.2221(12)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>13</td>\n",
       "      <td>33</td>\n",
       "      <td>21</td>\n",
       "      <td>0.066406</td>\n",
       "      <td>0.2223(12)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>13</td>\n",
       "      <td>34</td>\n",
       "      <td>22</td>\n",
       "      <td>0.067237</td>\n",
       "      <td>0.2224(12)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14</td>\n",
       "      <td>30</td>\n",
       "      <td>17</td>\n",
       "      <td>0.052349</td>\n",
       "      <td>0.2213(13)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>14</td>\n",
       "      <td>31</td>\n",
       "      <td>18</td>\n",
       "      <td>0.063640</td>\n",
       "      <td>0.2218(13)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>14</td>\n",
       "      <td>32</td>\n",
       "      <td>19</td>\n",
       "      <td>0.066883</td>\n",
       "      <td>0.2220(14)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>33</td>\n",
       "      <td>20</td>\n",
       "      <td>0.070019</td>\n",
       "      <td>0.2223(15)</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>34</td>\n",
       "      <td>21</td>\n",
       "      <td>0.070775</td>\n",
       "      <td>0.2224(15)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>30</td>\n",
       "      <td>16</td>\n",
       "      <td>0.056088</td>\n",
       "      <td>0.2213(16)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>15</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>0.067552</td>\n",
       "      <td>0.2218(17)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>15</td>\n",
       "      <td>32</td>\n",
       "      <td>18</td>\n",
       "      <td>0.070170</td>\n",
       "      <td>0.2221(18)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>15</td>\n",
       "      <td>33</td>\n",
       "      <td>19</td>\n",
       "      <td>0.072516</td>\n",
       "      <td>0.2224(18)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>15</td>\n",
       "      <td>34</td>\n",
       "      <td>20</td>\n",
       "      <td>0.072509</td>\n",
       "      <td>0.2225(18)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>16</td>\n",
       "      <td>30</td>\n",
       "      <td>15</td>\n",
       "      <td>0.059969</td>\n",
       "      <td>0.2214(21)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>16</td>\n",
       "      <td>31</td>\n",
       "      <td>16</td>\n",
       "      <td>0.070874</td>\n",
       "      <td>0.2220(20)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>16</td>\n",
       "      <td>32</td>\n",
       "      <td>17</td>\n",
       "      <td>0.072437</td>\n",
       "      <td>0.2223(21)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>16</td>\n",
       "      <td>33</td>\n",
       "      <td>18</td>\n",
       "      <td>0.073684</td>\n",
       "      <td>0.2225(21)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>16</td>\n",
       "      <td>34</td>\n",
       "      <td>19</td>\n",
       "      <td>0.072767</td>\n",
       "      <td>0.2227(20)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    t_start  t_stop  datapoints  chisquare_by_dof        mass\n",
       "0        12      30          19          0.057872  0.2218(12)\n",
       "1        12      31          20          0.063951  0.2221(11)\n",
       "2        12      32          21          0.064960  0.2223(11)\n",
       "3        12      33          22          0.066495  0.2224(10)\n",
       "4        12      34          23          0.066606  0.2225(10)\n",
       "5        13      30          18          0.051577  0.2215(12)\n",
       "6        13      31          19          0.060901  0.2219(11)\n",
       "7        13      32          20          0.063551  0.2221(12)\n",
       "8        13      33          21          0.066406  0.2223(12)\n",
       "9        13      34          22          0.067237  0.2224(12)\n",
       "10       14      30          17          0.052349  0.2213(13)\n",
       "11       14      31          18          0.063640  0.2218(13)\n",
       "12       14      32          19          0.066883  0.2220(14)\n",
       "13       14      33          20          0.070019  0.2223(15)\n",
       "14       14      34          21          0.070775  0.2224(15)\n",
       "15       15      30          16          0.056088  0.2213(16)\n",
       "16       15      31          17          0.067552  0.2218(17)\n",
       "17       15      32          18          0.070170  0.2221(18)\n",
       "18       15      33          19          0.072516  0.2224(18)\n",
       "19       15      34          20          0.072509  0.2225(18)\n",
       "20       16      30          15          0.059969  0.2214(21)\n",
       "21       16      31          16          0.070874  0.2220(20)\n",
       "22       16      32          17          0.072437  0.2223(21)\n",
       "23       16      33          18          0.073684  0.2225(21)\n",
       "24       16      34          19          0.072767  0.2227(20)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "pe.input.pandas.to_sql(my_df, \"mass_table\", \"my_db.sqlite\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = df = pe.input.pandas.read_sql(f\"SELECT t_start, t_stop, mass FROM mass_table WHERE t_start > 13\"\n",
    "                                       ,\"my_db.sqlite\"\n",
    "                                       ,auto_gamma=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>30</td>\n",
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       "      <td>0.2225(21)</td>\n",
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       "      <th>14</th>\n",
       "      <td>16</td>\n",
       "      <td>34</td>\n",
       "      <td>0.2227(20)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    t_start  t_stop        mass\n",
       "0        14      30  0.2213(13)\n",
       "1        14      31  0.2218(13)\n",
       "2        14      32  0.2220(14)\n",
       "3        14      33  0.2223(15)\n",
       "4        14      34  0.2224(15)\n",
       "5        15      30  0.2213(16)\n",
       "6        15      31  0.2218(17)\n",
       "7        15      32  0.2221(18)\n",
       "8        15      33  0.2224(18)\n",
       "9        15      34  0.2225(18)\n",
       "10       16      30  0.2214(21)\n",
       "11       16      31  0.2220(20)\n",
       "12       16      32  0.2223(21)\n",
       "13       16      33  0.2225(21)\n",
       "14       16      34  0.2227(20)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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