alphapept_development.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compile the cython code is highly recommended!\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "\n",
    "# from mimas.file_io import spec_file\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "# from alphapept import feature_finding\n",
    "from alphapept.constants import averagine_aa, isotopes\n",
    "from mimas.external.features_by_alphapept.load_mzml_data import load_mzml_data\n",
    "# from mimas.external.features_by_alphapept.ms_spectrum import MSSpectrum\n",
    "# from mimas.helper.arguments import Arguments\n",
    "# from mimas.spectra.similarity.tools import clean_spectrum\n",
    "# from mimas.spectra.similarity.tools/\n",
    "# from mimas.tools.spectral_file.extract_ms1_feature import find_features\n",
    "from mimas.tools.spectral_file.extract_ms1_feature import process_mzml_file, extract_ms2_spectra\n",
    "# from mimas.file_io import spec_file\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "import toolsets.search as search\n",
    "import toolsets.spectra_operations as so\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "outputs": [],
   "source": [
    "# mzml_file = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/EAD/mzml/BACSMLS 1.mzML\"\n",
    "# mzml_file =\"/Users/fanzhoukong/Documents/GitHub/Libgen_data/casmi/mzml/A_M3_negPFP_03.mzml\""
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "outputs": [],
   "source": [
    "ms2df= process_mzml_file(mzml_file, ifSciex=False)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "outputs": [
    {
     "data": {
      "text/plain": "    scan_number  precursor_mz  charge  ms1_intensity_ratio  retention_time  \\\n0           238    293.123856      -1             0.969618        0.540066   \n1           460    197.080885      -1             0.990194        1.029794   \n2           465    243.086620      -1             0.956398        1.038621   \n3           465    243.086620      -1             0.956398        1.038621   \n4          1085    185.117214      -1             0.977382        2.394052   \n5          1173    575.270161      -1             1.000000        2.571720   \n6          1278    901.239950      -1             0.995077        2.800668   \n7          1331    575.270240      -1             1.000000        2.888530   \n8          1333    529.264315      -1             0.987404        2.891299   \n9          1351    901.239782      -1             1.000000        2.922067   \n10         1600    401.123581      -1             0.993886        3.453756   \n11         1629    447.128813      -1             0.977909        3.511706   \n12         1631    401.123297      -1             0.994348        3.514753   \n13         1635    399.165070      -1             0.915519        3.520378   \n14         1737    399.165280      -1             0.968200        3.702673   \n15         2286    531.126634      -1             1.000000        4.832797   \n16         2409    263.128328      -1             0.959102        5.057898   \n17         2543    607.347929      -1             0.986787        5.273424   \n18         2553    561.342286      -1             1.000000        5.288419   \n19         2651    263.128418      -1             0.517569        5.438041   \n20         2677    485.218956      -1             0.964088        5.485260   \n21         2718    439.213074      -1             0.733741        5.553630   \n22         2740    717.239425      -1             0.985107        5.591855   \n\n                                                peaks  ms1_index  query_idx  \n0   [[61.048378, 0.10726301], [87.92364, 0.1445572...        237          0  \n1   [[51.072353, 0.009219986], [53.002163, 0.01175...        450          9  \n2   [[54.126934, 0.022826573], [65.038055, 0.03455...        453         11  \n3   [[54.126934, 0.022826573], [65.038055, 0.03455...        453         11  \n4   [[53.72312, 0.0036466636], [63.656487, 0.00340...       1037         47  \n5   [[52.898094, 0.073964685], [56.200596, 0.07922...       1110         62  \n6   [[71.00753, 0.013150149], [145.02817, 0.009517...       1207         70  \n7   [[59.012444, 0.28170097], [71.01235, 0.0600962...       1231         98  \n8   [[58.004665, 0.005138994], [59.01245, 0.339829...       1232        100  \n9   [[81.00671, 0.04058004], [86.36419, 0.0381839]...       1242        108  \n10  [[58.920593, 0.021178715], [105.565605, 0.0235...       1466        133  \n11  [[52.088776, 0.031078203], [53.177685, 0.03332...       1489        139  \n12  [[73.201614, 0.0022110136], [83.033875, 0.0023...       1490        140  \n13  [[67.91126, 0.044901498], [101.05891, 0.063883...       1491        143  \n14  [[55.01745, 0.02343136], [59.012604, 0.0050966...       1557        179  \n15  [[54.50091, 0.1307397], [55.87064, 0.15739432]...       2028        257  \n16  [[54.78434, 0.017217001], [219.0789, 0.0114079...       2113        295  \n17  [[59.01256, 0.9358835], [137.02614, 0.01059899...       2187        355  \n18  [[59.012478, 0.9249525], [218.09305, 0.0212966...       2191        361  \n19  [[61.984955, 0.043104276], [88.35825, 0.044019...       2231        419  \n20  [[58.774345, 0.01889644], [60.31268, 0.0234256...       2249        427  \n21  [[69.24537, 0.021119047], [76.60359, 0.0250524...       2273        444  \n22  [[91.78018, 0.008650385], [298.0469, 0.0109973...       2287        452  ",
      "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>scan_number</th>\n      <th>precursor_mz</th>\n      <th>charge</th>\n      <th>ms1_intensity_ratio</th>\n      <th>retention_time</th>\n      <th>peaks</th>\n      <th>ms1_index</th>\n      <th>query_idx</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>238</td>\n      <td>293.123856</td>\n      <td>-1</td>\n      <td>0.969618</td>\n      <td>0.540066</td>\n      <td>[[61.048378, 0.10726301], [87.92364, 0.1445572...</td>\n      <td>237</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>460</td>\n      <td>197.080885</td>\n      <td>-1</td>\n      <td>0.990194</td>\n      <td>1.029794</td>\n      <td>[[51.072353, 0.009219986], [53.002163, 0.01175...</td>\n      <td>450</td>\n      <td>9</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956398</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n      <td>453</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956398</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n      <td>453</td>\n      <td>11</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1085</td>\n      <td>185.117214</td>\n      <td>-1</td>\n      <td>0.977382</td>\n      <td>2.394052</td>\n      <td>[[53.72312, 0.0036466636], [63.656487, 0.00340...</td>\n      <td>1037</td>\n      <td>47</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>1173</td>\n      <td>575.270161</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.571720</td>\n      <td>[[52.898094, 0.073964685], [56.200596, 0.07922...</td>\n      <td>1110</td>\n      <td>62</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>1278</td>\n      <td>901.239950</td>\n      <td>-1</td>\n      <td>0.995077</td>\n      <td>2.800668</td>\n      <td>[[71.00753, 0.013150149], [145.02817, 0.009517...</td>\n      <td>1207</td>\n      <td>70</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>1331</td>\n      <td>575.270240</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.888530</td>\n      <td>[[59.012444, 0.28170097], [71.01235, 0.0600962...</td>\n      <td>1231</td>\n      <td>98</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>1333</td>\n      <td>529.264315</td>\n      <td>-1</td>\n      <td>0.987404</td>\n      <td>2.891299</td>\n      <td>[[58.004665, 0.005138994], [59.01245, 0.339829...</td>\n      <td>1232</td>\n      <td>100</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>1351</td>\n      <td>901.239782</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.922067</td>\n      <td>[[81.00671, 0.04058004], [86.36419, 0.0381839]...</td>\n      <td>1242</td>\n      <td>108</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>1600</td>\n      <td>401.123581</td>\n      <td>-1</td>\n      <td>0.993886</td>\n      <td>3.453756</td>\n      <td>[[58.920593, 0.021178715], [105.565605, 0.0235...</td>\n      <td>1466</td>\n      <td>133</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>1629</td>\n      <td>447.128813</td>\n      <td>-1</td>\n      <td>0.977909</td>\n      <td>3.511706</td>\n      <td>[[52.088776, 0.031078203], [53.177685, 0.03332...</td>\n      <td>1489</td>\n      <td>139</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>1631</td>\n      <td>401.123297</td>\n      <td>-1</td>\n      <td>0.994348</td>\n      <td>3.514753</td>\n      <td>[[73.201614, 0.0022110136], [83.033875, 0.0023...</td>\n      <td>1490</td>\n      <td>140</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1635</td>\n      <td>399.165070</td>\n      <td>-1</td>\n      <td>0.915519</td>\n      <td>3.520378</td>\n      <td>[[67.91126, 0.044901498], [101.05891, 0.063883...</td>\n      <td>1491</td>\n      <td>143</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1737</td>\n      <td>399.165280</td>\n      <td>-1</td>\n      <td>0.968200</td>\n      <td>3.702673</td>\n      <td>[[55.01745, 0.02343136], [59.012604, 0.0050966...</td>\n      <td>1557</td>\n      <td>179</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>2286</td>\n      <td>531.126634</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>4.832797</td>\n      <td>[[54.50091, 0.1307397], [55.87064, 0.15739432]...</td>\n      <td>2028</td>\n      <td>257</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>2409</td>\n      <td>263.128328</td>\n      <td>-1</td>\n      <td>0.959102</td>\n      <td>5.057898</td>\n      <td>[[54.78434, 0.017217001], [219.0789, 0.0114079...</td>\n      <td>2113</td>\n      <td>295</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>2543</td>\n      <td>607.347929</td>\n      <td>-1</td>\n      <td>0.986787</td>\n      <td>5.273424</td>\n      <td>[[59.01256, 0.9358835], [137.02614, 0.01059899...</td>\n      <td>2187</td>\n      <td>355</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>2553</td>\n      <td>561.342286</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>5.288419</td>\n      <td>[[59.012478, 0.9249525], [218.09305, 0.0212966...</td>\n      <td>2191</td>\n      <td>361</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>2651</td>\n      <td>263.128418</td>\n      <td>-1</td>\n      <td>0.517569</td>\n      <td>5.438041</td>\n      <td>[[61.984955, 0.043104276], [88.35825, 0.044019...</td>\n      <td>2231</td>\n      <td>419</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>2677</td>\n      <td>485.218956</td>\n      <td>-1</td>\n      <td>0.964088</td>\n      <td>5.485260</td>\n      <td>[[58.774345, 0.01889644], [60.31268, 0.0234256...</td>\n      <td>2249</td>\n      <td>427</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2718</td>\n      <td>439.213074</td>\n      <td>-1</td>\n      <td>0.733741</td>\n      <td>5.553630</td>\n      <td>[[69.24537, 0.021119047], [76.60359, 0.0250524...</td>\n      <td>2273</td>\n      <td>444</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2740</td>\n      <td>717.239425</td>\n      <td>-1</td>\n      <td>0.985107</td>\n      <td>5.591855</td>\n      <td>[[91.78018, 0.008650385], [298.0469, 0.0109973...</td>\n      <td>2287</td>\n      <td>452</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms2df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[6.1984955e+01, 4.3104276e-02],\n       [8.8358253e+01, 4.4019349e-02],\n       [9.6316078e+01, 4.6266716e-02],\n       [1.3705995e+02, 4.6230551e-02],\n       [1.3981708e+02, 4.9609471e-02],\n       [2.0382788e+02, 4.8480310e-02],\n       [2.1913779e+02, 5.7808656e-01],\n       [2.2108090e+02, 5.8885422e-02],\n       [2.2133640e+02, 8.5317440e-02]], dtype=float32)"
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms2df.iloc[19]['peaks']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "outputs": [],
   "source": [
    "features_mapped = process_mzml_file(mzml_file, ifSciex=False, ifdebug=True)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "outputs": [],
   "source": [
    "ms2_selected =extract_ms2_spectra(load_mzml_data(mzml_file), features_mapped)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "outputs": [
    {
     "data": {
      "text/plain": "115     237\n27      450\n38      453\n48      453\n6      1037\n510    1110\n566    1207\n503    1231\n470    1232\n551    1242\n407    1466\n442    1489\n397    1490\n378    1491\n359    1557\n475    2028\n79     2113\n516    2187\n487    2191\n74     2231\n446    2249\n433    2273\n537    2287\nName: ms1_idx, dtype: int64"
     },
     "execution_count": 213,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_mapped_selected_sorted['ms1_idx']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "outputs": [],
   "source": [
    "ms2_df = pd.DataFrame.from_dict(ms2_selected)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "outputs": [
    {
     "data": {
      "text/plain": "    scan_number  precursor_mz  charge  ms1_intensity_ratio  retention_time  \\\n0           238    293.123856      -1             0.969617        0.540066   \n1           460    197.080885      -1             0.990193        1.029794   \n2           465    243.086620      -1             0.956397        1.038621   \n3           465    243.086620      -1             0.956397        1.038621   \n4          1085    185.117214      -1             0.977381        2.394052   \n5          1173    575.270161      -1             1.000000        2.571720   \n6          1278    901.239950      -1             0.995077        2.800668   \n7          1331    575.270240      -1             1.000000        2.888530   \n8          1333    529.264315      -1             0.987403        2.891299   \n9          1351    901.239782      -1             1.000000        2.922067   \n10         1600    401.123581      -1             0.993886        3.453756   \n11         1629    447.128813      -1             0.977908        3.511706   \n12         1631    401.123297      -1             0.994348        3.514753   \n13         1635    399.165070      -1             0.915517        3.520378   \n14         1737    399.165280      -1             0.968200        3.702673   \n15         2286    531.126634      -1             1.000000        4.832797   \n16         2409    263.128328      -1             0.959102        5.057898   \n17         2543    607.347929      -1             0.986787        5.273424   \n18         2553    561.342286      -1             1.000000        5.288419   \n19         2651    263.128418      -1             0.517569        5.438041   \n20         2677    485.218956      -1             0.964088        5.485260   \n21         2718    439.213074      -1             0.733739        5.553630   \n22         2740    717.239425      -1             0.985107        5.591855   \n\n                                                peaks  \n0   [[61.048378, 0.10726301], [87.92364, 0.1445572...  \n1   [[51.072353, 0.009219986], [53.002163, 0.01175...  \n2   [[54.126934, 0.022826573], [65.038055, 0.03455...  \n3   [[54.126934, 0.022826573], [65.038055, 0.03455...  \n4   [[53.72312, 0.0036466636], [63.656487, 0.00340...  \n5   [[52.898094, 0.073964685], [56.200596, 0.07922...  \n6   [[71.00753, 0.013150149], [145.02817, 0.009517...  \n7   [[59.012444, 0.28170097], [71.01235, 0.0600962...  \n8   [[58.004665, 0.005138994], [59.01245, 0.339829...  \n9   [[81.00671, 0.04058004], [86.36419, 0.0381839]...  \n10  [[58.920593, 0.021178715], [105.565605, 0.0235...  \n11  [[52.088776, 0.031078203], [53.177685, 0.03332...  \n12  [[73.201614, 0.0022110136], [83.033875, 0.0023...  \n13  [[67.91126, 0.044901498], [101.05891, 0.063883...  \n14  [[55.01745, 0.02343136], [59.012604, 0.0050966...  \n15  [[54.50091, 0.1307397], [55.87064, 0.15739432]...  \n16  [[54.78434, 0.017217001], [219.0789, 0.0114079...  \n17  [[59.01256, 0.9358835], [137.02614, 0.01059899...  \n18  [[59.012478, 0.9249525], [218.09305, 0.0212966...  \n19  [[61.984955, 0.043104276], [88.35825, 0.044019...  \n20  [[58.774345, 0.01889644], [60.31268, 0.0234256...  \n21  [[69.24537, 0.021119047], [76.60359, 0.0250524...  \n22  [[91.78018, 0.008650385], [298.0469, 0.0109973...  ",
      "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>scan_number</th>\n      <th>precursor_mz</th>\n      <th>charge</th>\n      <th>ms1_intensity_ratio</th>\n      <th>retention_time</th>\n      <th>peaks</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>238</td>\n      <td>293.123856</td>\n      <td>-1</td>\n      <td>0.969617</td>\n      <td>0.540066</td>\n      <td>[[61.048378, 0.10726301], [87.92364, 0.1445572...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>460</td>\n      <td>197.080885</td>\n      <td>-1</td>\n      <td>0.990193</td>\n      <td>1.029794</td>\n      <td>[[51.072353, 0.009219986], [53.002163, 0.01175...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956397</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956397</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1085</td>\n      <td>185.117214</td>\n      <td>-1</td>\n      <td>0.977381</td>\n      <td>2.394052</td>\n      <td>[[53.72312, 0.0036466636], [63.656487, 0.00340...</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>1173</td>\n      <td>575.270161</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.571720</td>\n      <td>[[52.898094, 0.073964685], [56.200596, 0.07922...</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>1278</td>\n      <td>901.239950</td>\n      <td>-1</td>\n      <td>0.995077</td>\n      <td>2.800668</td>\n      <td>[[71.00753, 0.013150149], [145.02817, 0.009517...</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>1331</td>\n      <td>575.270240</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.888530</td>\n      <td>[[59.012444, 0.28170097], [71.01235, 0.0600962...</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>1333</td>\n      <td>529.264315</td>\n      <td>-1</td>\n      <td>0.987403</td>\n      <td>2.891299</td>\n      <td>[[58.004665, 0.005138994], [59.01245, 0.339829...</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>1351</td>\n      <td>901.239782</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.922067</td>\n      <td>[[81.00671, 0.04058004], [86.36419, 0.0381839]...</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>1600</td>\n      <td>401.123581</td>\n      <td>-1</td>\n      <td>0.993886</td>\n      <td>3.453756</td>\n      <td>[[58.920593, 0.021178715], [105.565605, 0.0235...</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>1629</td>\n      <td>447.128813</td>\n      <td>-1</td>\n      <td>0.977908</td>\n      <td>3.511706</td>\n      <td>[[52.088776, 0.031078203], [53.177685, 0.03332...</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>1631</td>\n      <td>401.123297</td>\n      <td>-1</td>\n      <td>0.994348</td>\n      <td>3.514753</td>\n      <td>[[73.201614, 0.0022110136], [83.033875, 0.0023...</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1635</td>\n      <td>399.165070</td>\n      <td>-1</td>\n      <td>0.915517</td>\n      <td>3.520378</td>\n      <td>[[67.91126, 0.044901498], [101.05891, 0.063883...</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1737</td>\n      <td>399.165280</td>\n      <td>-1</td>\n      <td>0.968200</td>\n      <td>3.702673</td>\n      <td>[[55.01745, 0.02343136], [59.012604, 0.0050966...</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>2286</td>\n      <td>531.126634</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>4.832797</td>\n      <td>[[54.50091, 0.1307397], [55.87064, 0.15739432]...</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>2409</td>\n      <td>263.128328</td>\n      <td>-1</td>\n      <td>0.959102</td>\n      <td>5.057898</td>\n      <td>[[54.78434, 0.017217001], [219.0789, 0.0114079...</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>2543</td>\n      <td>607.347929</td>\n      <td>-1</td>\n      <td>0.986787</td>\n      <td>5.273424</td>\n      <td>[[59.01256, 0.9358835], [137.02614, 0.01059899...</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>2553</td>\n      <td>561.342286</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>5.288419</td>\n      <td>[[59.012478, 0.9249525], [218.09305, 0.0212966...</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>2651</td>\n      <td>263.128418</td>\n      <td>-1</td>\n      <td>0.517569</td>\n      <td>5.438041</td>\n      <td>[[61.984955, 0.043104276], [88.35825, 0.044019...</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>2677</td>\n      <td>485.218956</td>\n      <td>-1</td>\n      <td>0.964088</td>\n      <td>5.485260</td>\n      <td>[[58.774345, 0.01889644], [60.31268, 0.0234256...</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2718</td>\n      <td>439.213074</td>\n      <td>-1</td>\n      <td>0.733739</td>\n      <td>5.553630</td>\n      <td>[[69.24537, 0.021119047], [76.60359, 0.0250524...</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2740</td>\n      <td>717.239425</td>\n      <td>-1</td>\n      <td>0.985107</td>\n      <td>5.591855</td>\n      <td>[[91.78018, 0.008650385], [298.0469, 0.0109973...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms2_df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "outputs": [
    {
     "data": {
      "text/plain": "1.0"
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "so.entropy_similarity_default(ms2df.iloc[2]['peaks'], ms2df.iloc[3]['peaks'], ifNIST=True)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "outputs": [],
   "source": [
    "features_mapped_selected.sort_values(by=\"query_idx\", ascending=True, inplace=True,ignore_index=True )"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "outputs": [
    {
     "data": {
      "text/plain": "          rt          mz  charge  mz_matched  query_idx  feature_idx  \\\n0   0.540066  293.123856    -1.0  293.123684          0         49.0   \n1   1.029794  197.080885    -1.0  197.080888          9        349.0   \n2   1.038621  243.086620    -1.0  243.072046         11         10.0   \n3   1.038621  243.086620    -1.0  243.086654         11          9.0   \n4   2.394052  185.117214    -1.0  185.117221         47        145.0   \n5   2.571720  575.270161    -1.0  575.270274         62        407.0   \n6   2.800668  901.239950    -1.0  901.240076         70         28.0   \n7   2.888530  575.270240    -1.0  575.270134         98         61.0   \n8   2.891299  529.264315    -1.0  529.264461        100         30.0   \n9   2.922067  901.239782    -1.0  901.240040        108        169.0   \n10  3.453756  401.123581    -1.0  401.123491        133        176.0   \n11  3.511706  447.128813    -1.0  447.128886        139        178.0   \n12  3.514753  401.123297    -1.0  401.123412        140         67.0   \n13  3.520378  399.165070    -1.0  399.165303        143        485.0   \n14  3.702673  399.165280    -1.0  399.165175        179         68.0   \n15  4.832797  531.126634    -1.0  531.126685        257         74.0   \n16  5.057898  263.128328    -1.0  263.128331        295         75.0   \n17  5.273424  607.347929    -1.0  607.348046        355         33.0   \n18  5.288419  561.342286    -1.0  561.342258        361        216.0   \n19  5.438041  263.128418    -1.0  263.092009        419        610.0   \n20  5.485260  485.218956    -1.0  485.218688        427        232.0   \n21  5.553630  439.213074    -1.0  439.213118        444        233.0   \n22  5.591855  717.239425    -1.0  717.239338        452         36.0   \n\n    n_isotopes       int_sum      int_apex  rt_start   rt_apex    rt_end  \\\n0          4.0  3.185037e+08  2.604713e+07  0.462098  0.485730  0.547763   \n1          2.0  5.872560e+07  3.080959e+06  0.969436  1.013511  1.096153   \n2          2.0  8.652044e+06  2.004301e+05  0.981798  1.017862  1.076967   \n3          3.0  2.691171e+08  2.777882e+07  0.969068  1.018452  1.095271   \n4          3.0  1.073909e+08  5.626948e+06  2.306116  2.397145  2.470669   \n5          2.0  3.334297e+07  7.456169e+05  2.492716  2.568866  2.657413   \n6          5.0  4.464346e+08  1.857238e+07  2.763218  2.799048  2.862177   \n7          4.0  1.476213e+08  8.163773e+06  2.826197  2.892673  2.966147   \n8          4.0  2.498112e+08  1.847013e+07  2.823975  2.890438  2.967127   \n9          3.0  2.422610e+07  6.407072e+05  2.898216  2.922430  3.052148   \n10         3.0  1.266844e+08  2.553891e+06  3.378084  3.424526  3.460872   \n11         3.0  4.796815e+07  2.113462e+06  3.460033  3.508233  3.604632   \n12         4.0  2.214789e+08  1.032683e+07  3.460645  3.509268  3.601395   \n13         2.0  1.553639e+07  4.104083e+05  3.435986  3.501480  3.565451   \n14         4.0  5.246759e+08  4.480775e+07  3.654622  3.702969  3.783549   \n15         4.0  1.986980e+07  5.050768e+05  4.746904  4.808225  4.877407   \n16         4.0  5.822129e+08  3.305191e+07  4.964282  5.058464  5.176191   \n17         5.0  9.489884e+08  7.218837e+07  5.206930  5.265741  5.328754   \n18         3.0  7.629101e+07  3.700553e+06  5.209898  5.265184  5.325276   \n19         2.0  2.428009e+07  6.765259e+05  5.286464  5.496199  5.528658   \n20         3.0  1.178318e+08  5.787977e+06  5.472038  5.495637  5.551265   \n21         3.0  1.157299e+08  4.069933e+06  5.472625  5.495192  5.553864   \n22         5.0  7.494613e+08  7.539418e+07  5.531435  5.555526  5.607148   \n\n    scan_number  rt_offset  ms1_idx  \n0           238   0.054336      237  \n1           460   0.016283      450  \n2           465   0.020759      453  \n3           465   0.020170      453  \n4          1085   0.003093     1037  \n5          1173   0.002854     1110  \n6          1278   0.001621     1207  \n7          1331   0.004143     1231  \n8          1333   0.000861     1232  \n9          1351   0.000362     1242  \n10         1600   0.029230     1466  \n11         1629   0.003473     1489  \n12         1631   0.005486     1490  \n13         1635   0.018898     1491  \n14         1737   0.000296     1557  \n15         2286   0.024572     2028  \n16         2409   0.000566     2113  \n17         2543   0.007682     2187  \n18         2553   0.023236     2191  \n19         2651   0.058158     2231  \n20         2677   0.010378     2249  \n21         2718   0.058439     2273  \n22         2740   0.036329     2287  ",
      "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>rt</th>\n      <th>mz</th>\n      <th>charge</th>\n      <th>mz_matched</th>\n      <th>query_idx</th>\n      <th>feature_idx</th>\n      <th>n_isotopes</th>\n      <th>int_sum</th>\n      <th>int_apex</th>\n      <th>rt_start</th>\n      <th>rt_apex</th>\n      <th>rt_end</th>\n      <th>scan_number</th>\n      <th>rt_offset</th>\n      <th>ms1_idx</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.540066</td>\n      <td>293.123856</td>\n      <td>-1.0</td>\n      <td>293.123684</td>\n      <td>0</td>\n      <td>49.0</td>\n      <td>4.0</td>\n      <td>3.185037e+08</td>\n      <td>2.604713e+07</td>\n      <td>0.462098</td>\n      <td>0.485730</td>\n      <td>0.547763</td>\n      <td>238</td>\n      <td>0.054336</td>\n      <td>237</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1.029794</td>\n      <td>197.080885</td>\n      <td>-1.0</td>\n      <td>197.080888</td>\n      <td>9</td>\n      <td>349.0</td>\n      <td>2.0</td>\n      <td>5.872560e+07</td>\n      <td>3.080959e+06</td>\n      <td>0.969436</td>\n      <td>1.013511</td>\n      <td>1.096153</td>\n      <td>460</td>\n      <td>0.016283</td>\n      <td>450</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1.038621</td>\n      <td>243.086620</td>\n      <td>-1.0</td>\n      <td>243.072046</td>\n      <td>11</td>\n      <td>10.0</td>\n      <td>2.0</td>\n      <td>8.652044e+06</td>\n      <td>2.004301e+05</td>\n      <td>0.981798</td>\n      <td>1.017862</td>\n      <td>1.076967</td>\n      <td>465</td>\n      <td>0.020759</td>\n      <td>453</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1.038621</td>\n      <td>243.086620</td>\n      <td>-1.0</td>\n      <td>243.086654</td>\n      <td>11</td>\n      <td>9.0</td>\n      <td>3.0</td>\n      <td>2.691171e+08</td>\n      <td>2.777882e+07</td>\n      <td>0.969068</td>\n      <td>1.018452</td>\n      <td>1.095271</td>\n      <td>465</td>\n      <td>0.020170</td>\n      <td>453</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2.394052</td>\n      <td>185.117214</td>\n      <td>-1.0</td>\n      <td>185.117221</td>\n      <td>47</td>\n      <td>145.0</td>\n      <td>3.0</td>\n      <td>1.073909e+08</td>\n      <td>5.626948e+06</td>\n      <td>2.306116</td>\n      <td>2.397145</td>\n      <td>2.470669</td>\n      <td>1085</td>\n      <td>0.003093</td>\n      <td>1037</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2.571720</td>\n      <td>575.270161</td>\n      <td>-1.0</td>\n      <td>575.270274</td>\n      <td>62</td>\n      <td>407.0</td>\n      <td>2.0</td>\n      <td>3.334297e+07</td>\n      <td>7.456169e+05</td>\n      <td>2.492716</td>\n      <td>2.568866</td>\n      <td>2.657413</td>\n      <td>1173</td>\n      <td>0.002854</td>\n      <td>1110</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2.800668</td>\n      <td>901.239950</td>\n      <td>-1.0</td>\n      <td>901.240076</td>\n      <td>70</td>\n      <td>28.0</td>\n      <td>5.0</td>\n      <td>4.464346e+08</td>\n      <td>1.857238e+07</td>\n      <td>2.763218</td>\n      <td>2.799048</td>\n      <td>2.862177</td>\n      <td>1278</td>\n      <td>0.001621</td>\n      <td>1207</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2.888530</td>\n      <td>575.270240</td>\n      <td>-1.0</td>\n      <td>575.270134</td>\n      <td>98</td>\n      <td>61.0</td>\n      <td>4.0</td>\n      <td>1.476213e+08</td>\n      <td>8.163773e+06</td>\n      <td>2.826197</td>\n      <td>2.892673</td>\n      <td>2.966147</td>\n      <td>1331</td>\n      <td>0.004143</td>\n      <td>1231</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2.891299</td>\n      <td>529.264315</td>\n      <td>-1.0</td>\n      <td>529.264461</td>\n      <td>100</td>\n      <td>30.0</td>\n      <td>4.0</td>\n      <td>2.498112e+08</td>\n      <td>1.847013e+07</td>\n      <td>2.823975</td>\n      <td>2.890438</td>\n      <td>2.967127</td>\n      <td>1333</td>\n      <td>0.000861</td>\n      <td>1232</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2.922067</td>\n      <td>901.239782</td>\n      <td>-1.0</td>\n      <td>901.240040</td>\n      <td>108</td>\n      <td>169.0</td>\n      <td>3.0</td>\n      <td>2.422610e+07</td>\n      <td>6.407072e+05</td>\n      <td>2.898216</td>\n      <td>2.922430</td>\n      <td>3.052148</td>\n      <td>1351</td>\n      <td>0.000362</td>\n      <td>1242</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>3.453756</td>\n      <td>401.123581</td>\n      <td>-1.0</td>\n      <td>401.123491</td>\n      <td>133</td>\n      <td>176.0</td>\n      <td>3.0</td>\n      <td>1.266844e+08</td>\n      <td>2.553891e+06</td>\n      <td>3.378084</td>\n      <td>3.424526</td>\n      <td>3.460872</td>\n      <td>1600</td>\n      <td>0.029230</td>\n      <td>1466</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>3.511706</td>\n      <td>447.128813</td>\n      <td>-1.0</td>\n      <td>447.128886</td>\n      <td>139</td>\n      <td>178.0</td>\n      <td>3.0</td>\n      <td>4.796815e+07</td>\n      <td>2.113462e+06</td>\n      <td>3.460033</td>\n      <td>3.508233</td>\n      <td>3.604632</td>\n      <td>1629</td>\n      <td>0.003473</td>\n      <td>1489</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>3.514753</td>\n      <td>401.123297</td>\n      <td>-1.0</td>\n      <td>401.123412</td>\n      <td>140</td>\n      <td>67.0</td>\n      <td>4.0</td>\n      <td>2.214789e+08</td>\n      <td>1.032683e+07</td>\n      <td>3.460645</td>\n      <td>3.509268</td>\n      <td>3.601395</td>\n      <td>1631</td>\n      <td>0.005486</td>\n      <td>1490</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>3.520378</td>\n      <td>399.165070</td>\n      <td>-1.0</td>\n      <td>399.165303</td>\n      <td>143</td>\n      <td>485.0</td>\n      <td>2.0</td>\n      <td>1.553639e+07</td>\n      <td>4.104083e+05</td>\n      <td>3.435986</td>\n      <td>3.501480</td>\n      <td>3.565451</td>\n      <td>1635</td>\n      <td>0.018898</td>\n      <td>1491</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>3.702673</td>\n      <td>399.165280</td>\n      <td>-1.0</td>\n      <td>399.165175</td>\n      <td>179</td>\n      <td>68.0</td>\n      <td>4.0</td>\n      <td>5.246759e+08</td>\n      <td>4.480775e+07</td>\n      <td>3.654622</td>\n      <td>3.702969</td>\n      <td>3.783549</td>\n      <td>1737</td>\n      <td>0.000296</td>\n      <td>1557</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>4.832797</td>\n      <td>531.126634</td>\n      <td>-1.0</td>\n      <td>531.126685</td>\n      <td>257</td>\n      <td>74.0</td>\n      <td>4.0</td>\n      <td>1.986980e+07</td>\n      <td>5.050768e+05</td>\n      <td>4.746904</td>\n      <td>4.808225</td>\n      <td>4.877407</td>\n      <td>2286</td>\n      <td>0.024572</td>\n      <td>2028</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>5.057898</td>\n      <td>263.128328</td>\n      <td>-1.0</td>\n      <td>263.128331</td>\n      <td>295</td>\n      <td>75.0</td>\n      <td>4.0</td>\n      <td>5.822129e+08</td>\n      <td>3.305191e+07</td>\n      <td>4.964282</td>\n      <td>5.058464</td>\n      <td>5.176191</td>\n      <td>2409</td>\n      <td>0.000566</td>\n      <td>2113</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>5.273424</td>\n      <td>607.347929</td>\n      <td>-1.0</td>\n      <td>607.348046</td>\n      <td>355</td>\n      <td>33.0</td>\n      <td>5.0</td>\n      <td>9.489884e+08</td>\n      <td>7.218837e+07</td>\n      <td>5.206930</td>\n      <td>5.265741</td>\n      <td>5.328754</td>\n      <td>2543</td>\n      <td>0.007682</td>\n      <td>2187</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>5.288419</td>\n      <td>561.342286</td>\n      <td>-1.0</td>\n      <td>561.342258</td>\n      <td>361</td>\n      <td>216.0</td>\n      <td>3.0</td>\n      <td>7.629101e+07</td>\n      <td>3.700553e+06</td>\n      <td>5.209898</td>\n      <td>5.265184</td>\n      <td>5.325276</td>\n      <td>2553</td>\n      <td>0.023236</td>\n      <td>2191</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>5.438041</td>\n      <td>263.128418</td>\n      <td>-1.0</td>\n      <td>263.092009</td>\n      <td>419</td>\n      <td>610.0</td>\n      <td>2.0</td>\n      <td>2.428009e+07</td>\n      <td>6.765259e+05</td>\n      <td>5.286464</td>\n      <td>5.496199</td>\n      <td>5.528658</td>\n      <td>2651</td>\n      <td>0.058158</td>\n      <td>2231</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>5.485260</td>\n      <td>485.218956</td>\n      <td>-1.0</td>\n      <td>485.218688</td>\n      <td>427</td>\n      <td>232.0</td>\n      <td>3.0</td>\n      <td>1.178318e+08</td>\n      <td>5.787977e+06</td>\n      <td>5.472038</td>\n      <td>5.495637</td>\n      <td>5.551265</td>\n      <td>2677</td>\n      <td>0.010378</td>\n      <td>2249</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>5.553630</td>\n      <td>439.213074</td>\n      <td>-1.0</td>\n      <td>439.213118</td>\n      <td>444</td>\n      <td>233.0</td>\n      <td>3.0</td>\n      <td>1.157299e+08</td>\n      <td>4.069933e+06</td>\n      <td>5.472625</td>\n      <td>5.495192</td>\n      <td>5.553864</td>\n      <td>2718</td>\n      <td>0.058439</td>\n      <td>2273</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>5.591855</td>\n      <td>717.239425</td>\n      <td>-1.0</td>\n      <td>717.239338</td>\n      <td>452</td>\n      <td>36.0</td>\n      <td>5.0</td>\n      <td>7.494613e+08</td>\n      <td>7.539418e+07</td>\n      <td>5.531435</td>\n      <td>5.555526</td>\n      <td>5.607148</td>\n      <td>2740</td>\n      <td>0.036329</td>\n      <td>2287</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_mapped_selected"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "outputs": [
    {
     "data": {
      "text/plain": "    scan_number  precursor_mz  charge  ms1_intensity_ratio  retention_time  \\\n0           238    293.123856      -1             0.969618        0.540066   \n1           460    197.080885      -1             0.990194        1.029794   \n2           465    243.086620      -1             0.956398        1.038621   \n3           465    243.086620      -1             0.956398        1.038621   \n4          1085    185.117214      -1             0.977382        2.394052   \n5          1173    575.270161      -1             1.000000        2.571720   \n6          1278    901.239950      -1             0.995077        2.800668   \n7          1331    575.270240      -1             1.000000        2.888530   \n8          1333    529.264315      -1             0.987404        2.891299   \n9          1351    901.239782      -1             1.000000        2.922067   \n10         1600    401.123581      -1             0.993886        3.453756   \n11         1629    447.128813      -1             0.977909        3.511706   \n12         1631    401.123297      -1             0.994348        3.514753   \n13         1635    399.165070      -1             0.915519        3.520378   \n14         1737    399.165280      -1             0.968200        3.702673   \n15         2286    531.126634      -1             1.000000        4.832797   \n16         2409    263.128328      -1             0.959102        5.057898   \n17         2543    607.347929      -1             0.986787        5.273424   \n18         2553    561.342286      -1             1.000000        5.288419   \n19         2651    263.128418      -1             0.517569        5.438041   \n20         2677    485.218956      -1             0.964088        5.485260   \n21         2718    439.213074      -1             0.733741        5.553630   \n22         2740    717.239425      -1             0.985107        5.591855   \n\n                                                peaks  ms1_index  \n0   [[61.048378, 0.10726301], [87.92364, 0.1445572...        NaN  \n1   [[51.072353, 0.009219986], [53.002163, 0.01175...        NaN  \n2   [[54.126934, 0.022826573], [65.038055, 0.03455...        NaN  \n3   [[54.126934, 0.022826573], [65.038055, 0.03455...        NaN  \n4   [[53.72312, 0.0036466636], [63.656487, 0.00340...        NaN  \n5   [[52.898094, 0.073964685], [56.200596, 0.07922...        NaN  \n6   [[71.00753, 0.013150149], [145.02817, 0.009517...     1037.0  \n7   [[59.012444, 0.28170097], [71.01235, 0.0600962...        NaN  \n8   [[58.004665, 0.005138994], [59.01245, 0.339829...        NaN  \n9   [[81.00671, 0.04058004], [86.36419, 0.0381839]...        NaN  \n10  [[58.920593, 0.021178715], [105.565605, 0.0235...        NaN  \n11  [[52.088776, 0.031078203], [53.177685, 0.03332...        NaN  \n12  [[73.201614, 0.0022110136], [83.033875, 0.0023...        NaN  \n13  [[67.91126, 0.044901498], [101.05891, 0.063883...        NaN  \n14  [[55.01745, 0.02343136], [59.012604, 0.0050966...        NaN  \n15  [[54.50091, 0.1307397], [55.87064, 0.15739432]...        NaN  \n16  [[54.78434, 0.017217001], [219.0789, 0.0114079...        NaN  \n17  [[59.01256, 0.9358835], [137.02614, 0.01059899...        NaN  \n18  [[59.012478, 0.9249525], [218.09305, 0.0212966...        NaN  \n19  [[61.984955, 0.043104276], [88.35825, 0.044019...        NaN  \n20  [[58.774345, 0.01889644], [60.31268, 0.0234256...        NaN  \n21  [[69.24537, 0.021119047], [76.60359, 0.0250524...        NaN  \n22  [[91.78018, 0.008650385], [298.0469, 0.0109973...        NaN  ",
      "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>scan_number</th>\n      <th>precursor_mz</th>\n      <th>charge</th>\n      <th>ms1_intensity_ratio</th>\n      <th>retention_time</th>\n      <th>peaks</th>\n      <th>ms1_index</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>238</td>\n      <td>293.123856</td>\n      <td>-1</td>\n      <td>0.969618</td>\n      <td>0.540066</td>\n      <td>[[61.048378, 0.10726301], [87.92364, 0.1445572...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>460</td>\n      <td>197.080885</td>\n      <td>-1</td>\n      <td>0.990194</td>\n      <td>1.029794</td>\n      <td>[[51.072353, 0.009219986], [53.002163, 0.01175...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956398</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956398</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1085</td>\n      <td>185.117214</td>\n      <td>-1</td>\n      <td>0.977382</td>\n      <td>2.394052</td>\n      <td>[[53.72312, 0.0036466636], [63.656487, 0.00340...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>1173</td>\n      <td>575.270161</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.571720</td>\n      <td>[[52.898094, 0.073964685], [56.200596, 0.07922...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>1278</td>\n      <td>901.239950</td>\n      <td>-1</td>\n      <td>0.995077</td>\n      <td>2.800668</td>\n      <td>[[71.00753, 0.013150149], [145.02817, 0.009517...</td>\n      <td>1037.0</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>1331</td>\n      <td>575.270240</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.888530</td>\n      <td>[[59.012444, 0.28170097], [71.01235, 0.0600962...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>1333</td>\n      <td>529.264315</td>\n      <td>-1</td>\n      <td>0.987404</td>\n      <td>2.891299</td>\n      <td>[[58.004665, 0.005138994], [59.01245, 0.339829...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>1351</td>\n      <td>901.239782</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.922067</td>\n      <td>[[81.00671, 0.04058004], [86.36419, 0.0381839]...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>1600</td>\n      <td>401.123581</td>\n      <td>-1</td>\n      <td>0.993886</td>\n      <td>3.453756</td>\n      <td>[[58.920593, 0.021178715], [105.565605, 0.0235...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>1629</td>\n      <td>447.128813</td>\n      <td>-1</td>\n      <td>0.977909</td>\n      <td>3.511706</td>\n      <td>[[52.088776, 0.031078203], [53.177685, 0.03332...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>1631</td>\n      <td>401.123297</td>\n      <td>-1</td>\n      <td>0.994348</td>\n      <td>3.514753</td>\n      <td>[[73.201614, 0.0022110136], [83.033875, 0.0023...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1635</td>\n      <td>399.165070</td>\n      <td>-1</td>\n      <td>0.915519</td>\n      <td>3.520378</td>\n      <td>[[67.91126, 0.044901498], [101.05891, 0.063883...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1737</td>\n      <td>399.165280</td>\n      <td>-1</td>\n      <td>0.968200</td>\n      <td>3.702673</td>\n      <td>[[55.01745, 0.02343136], [59.012604, 0.0050966...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>2286</td>\n      <td>531.126634</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>4.832797</td>\n      <td>[[54.50091, 0.1307397], [55.87064, 0.15739432]...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>2409</td>\n      <td>263.128328</td>\n      <td>-1</td>\n      <td>0.959102</td>\n      <td>5.057898</td>\n      <td>[[54.78434, 0.017217001], [219.0789, 0.0114079...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>2543</td>\n      <td>607.347929</td>\n      <td>-1</td>\n      <td>0.986787</td>\n      <td>5.273424</td>\n      <td>[[59.01256, 0.9358835], [137.02614, 0.01059899...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>2553</td>\n      <td>561.342286</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>5.288419</td>\n      <td>[[59.012478, 0.9249525], [218.09305, 0.0212966...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>2651</td>\n      <td>263.128418</td>\n      <td>-1</td>\n      <td>0.517569</td>\n      <td>5.438041</td>\n      <td>[[61.984955, 0.043104276], [88.35825, 0.044019...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>2677</td>\n      <td>485.218956</td>\n      <td>-1</td>\n      <td>0.964088</td>\n      <td>5.485260</td>\n      <td>[[58.774345, 0.01889644], [60.31268, 0.0234256...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2718</td>\n      <td>439.213074</td>\n      <td>-1</td>\n      <td>0.733741</td>\n      <td>5.553630</td>\n      <td>[[69.24537, 0.021119047], [76.60359, 0.0250524...</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2740</td>\n      <td>717.239425</td>\n      <td>-1</td>\n      <td>0.985107</td>\n      <td>5.591855</td>\n      <td>[[91.78018, 0.008650385], [298.0469, 0.0109973...</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms2df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "outputs": [],
   "source": [
    "ms2df['ms1_index']= features_mapped_selected['ms1_idx']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "outputs": [
    {
     "data": {
      "text/plain": "    scan_number  precursor_mz  charge  ms1_intensity_ratio  retention_time  \\\n0           238    293.123856      -1             0.969618        0.540066   \n1           460    197.080885      -1             0.990194        1.029794   \n2           465    243.086620      -1             0.956398        1.038621   \n3           465    243.086620      -1             0.956398        1.038621   \n4          1085    185.117214      -1             0.977382        2.394052   \n5          1173    575.270161      -1             1.000000        2.571720   \n6          1278    901.239950      -1             0.995077        2.800668   \n7          1331    575.270240      -1             1.000000        2.888530   \n8          1333    529.264315      -1             0.987404        2.891299   \n9          1351    901.239782      -1             1.000000        2.922067   \n10         1600    401.123581      -1             0.993886        3.453756   \n11         1629    447.128813      -1             0.977909        3.511706   \n12         1631    401.123297      -1             0.994348        3.514753   \n13         1635    399.165070      -1             0.915519        3.520378   \n14         1737    399.165280      -1             0.968200        3.702673   \n15         2286    531.126634      -1             1.000000        4.832797   \n16         2409    263.128328      -1             0.959102        5.057898   \n17         2543    607.347929      -1             0.986787        5.273424   \n18         2553    561.342286      -1             1.000000        5.288419   \n19         2651    263.128418      -1             0.517569        5.438041   \n20         2677    485.218956      -1             0.964088        5.485260   \n21         2718    439.213074      -1             0.733741        5.553630   \n22         2740    717.239425      -1             0.985107        5.591855   \n\n                                                peaks  ms1_index  \n0   [[61.048378, 0.10726301], [87.92364, 0.1445572...        237  \n1   [[51.072353, 0.009219986], [53.002163, 0.01175...        450  \n2   [[54.126934, 0.022826573], [65.038055, 0.03455...        453  \n3   [[54.126934, 0.022826573], [65.038055, 0.03455...        453  \n4   [[53.72312, 0.0036466636], [63.656487, 0.00340...       1037  \n5   [[52.898094, 0.073964685], [56.200596, 0.07922...       1110  \n6   [[71.00753, 0.013150149], [145.02817, 0.009517...       1207  \n7   [[59.012444, 0.28170097], [71.01235, 0.0600962...       1231  \n8   [[58.004665, 0.005138994], [59.01245, 0.339829...       1232  \n9   [[81.00671, 0.04058004], [86.36419, 0.0381839]...       1242  \n10  [[58.920593, 0.021178715], [105.565605, 0.0235...       1466  \n11  [[52.088776, 0.031078203], [53.177685, 0.03332...       1489  \n12  [[73.201614, 0.0022110136], [83.033875, 0.0023...       1490  \n13  [[67.91126, 0.044901498], [101.05891, 0.063883...       1491  \n14  [[55.01745, 0.02343136], [59.012604, 0.0050966...       1557  \n15  [[54.50091, 0.1307397], [55.87064, 0.15739432]...       2028  \n16  [[54.78434, 0.017217001], [219.0789, 0.0114079...       2113  \n17  [[59.01256, 0.9358835], [137.02614, 0.01059899...       2187  \n18  [[59.012478, 0.9249525], [218.09305, 0.0212966...       2191  \n19  [[61.984955, 0.043104276], [88.35825, 0.044019...       2231  \n20  [[58.774345, 0.01889644], [60.31268, 0.0234256...       2249  \n21  [[69.24537, 0.021119047], [76.60359, 0.0250524...       2273  \n22  [[91.78018, 0.008650385], [298.0469, 0.0109973...       2287  ",
      "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>scan_number</th>\n      <th>precursor_mz</th>\n      <th>charge</th>\n      <th>ms1_intensity_ratio</th>\n      <th>retention_time</th>\n      <th>peaks</th>\n      <th>ms1_index</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>238</td>\n      <td>293.123856</td>\n      <td>-1</td>\n      <td>0.969618</td>\n      <td>0.540066</td>\n      <td>[[61.048378, 0.10726301], [87.92364, 0.1445572...</td>\n      <td>237</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>460</td>\n      <td>197.080885</td>\n      <td>-1</td>\n      <td>0.990194</td>\n      <td>1.029794</td>\n      <td>[[51.072353, 0.009219986], [53.002163, 0.01175...</td>\n      <td>450</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956398</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n      <td>453</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956398</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n      <td>453</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1085</td>\n      <td>185.117214</td>\n      <td>-1</td>\n      <td>0.977382</td>\n      <td>2.394052</td>\n      <td>[[53.72312, 0.0036466636], [63.656487, 0.00340...</td>\n      <td>1037</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>1173</td>\n      <td>575.270161</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.571720</td>\n      <td>[[52.898094, 0.073964685], [56.200596, 0.07922...</td>\n      <td>1110</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>1278</td>\n      <td>901.239950</td>\n      <td>-1</td>\n      <td>0.995077</td>\n      <td>2.800668</td>\n      <td>[[71.00753, 0.013150149], [145.02817, 0.009517...</td>\n      <td>1207</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>1331</td>\n      <td>575.270240</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.888530</td>\n      <td>[[59.012444, 0.28170097], [71.01235, 0.0600962...</td>\n      <td>1231</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>1333</td>\n      <td>529.264315</td>\n      <td>-1</td>\n      <td>0.987404</td>\n      <td>2.891299</td>\n      <td>[[58.004665, 0.005138994], [59.01245, 0.339829...</td>\n      <td>1232</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>1351</td>\n      <td>901.239782</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.922067</td>\n      <td>[[81.00671, 0.04058004], [86.36419, 0.0381839]...</td>\n      <td>1242</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>1600</td>\n      <td>401.123581</td>\n      <td>-1</td>\n      <td>0.993886</td>\n      <td>3.453756</td>\n      <td>[[58.920593, 0.021178715], [105.565605, 0.0235...</td>\n      <td>1466</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>1629</td>\n      <td>447.128813</td>\n      <td>-1</td>\n      <td>0.977909</td>\n      <td>3.511706</td>\n      <td>[[52.088776, 0.031078203], [53.177685, 0.03332...</td>\n      <td>1489</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>1631</td>\n      <td>401.123297</td>\n      <td>-1</td>\n      <td>0.994348</td>\n      <td>3.514753</td>\n      <td>[[73.201614, 0.0022110136], [83.033875, 0.0023...</td>\n      <td>1490</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1635</td>\n      <td>399.165070</td>\n      <td>-1</td>\n      <td>0.915519</td>\n      <td>3.520378</td>\n      <td>[[67.91126, 0.044901498], [101.05891, 0.063883...</td>\n      <td>1491</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1737</td>\n      <td>399.165280</td>\n      <td>-1</td>\n      <td>0.968200</td>\n      <td>3.702673</td>\n      <td>[[55.01745, 0.02343136], [59.012604, 0.0050966...</td>\n      <td>1557</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>2286</td>\n      <td>531.126634</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>4.832797</td>\n      <td>[[54.50091, 0.1307397], [55.87064, 0.15739432]...</td>\n      <td>2028</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>2409</td>\n      <td>263.128328</td>\n      <td>-1</td>\n      <td>0.959102</td>\n      <td>5.057898</td>\n      <td>[[54.78434, 0.017217001], [219.0789, 0.0114079...</td>\n      <td>2113</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>2543</td>\n      <td>607.347929</td>\n      <td>-1</td>\n      <td>0.986787</td>\n      <td>5.273424</td>\n      <td>[[59.01256, 0.9358835], [137.02614, 0.01059899...</td>\n      <td>2187</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>2553</td>\n      <td>561.342286</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>5.288419</td>\n      <td>[[59.012478, 0.9249525], [218.09305, 0.0212966...</td>\n      <td>2191</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>2651</td>\n      <td>263.128418</td>\n      <td>-1</td>\n      <td>0.517569</td>\n      <td>5.438041</td>\n      <td>[[61.984955, 0.043104276], [88.35825, 0.044019...</td>\n      <td>2231</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>2677</td>\n      <td>485.218956</td>\n      <td>-1</td>\n      <td>0.964088</td>\n      <td>5.485260</td>\n      <td>[[58.774345, 0.01889644], [60.31268, 0.0234256...</td>\n      <td>2249</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2718</td>\n      <td>439.213074</td>\n      <td>-1</td>\n      <td>0.733741</td>\n      <td>5.553630</td>\n      <td>[[69.24537, 0.021119047], [76.60359, 0.0250524...</td>\n      <td>2273</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2740</td>\n      <td>717.239425</td>\n      <td>-1</td>\n      <td>0.985107</td>\n      <td>5.591855</td>\n      <td>[[91.78018, 0.008650385], [298.0469, 0.0109973...</td>\n      <td>2287</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms2df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "outputs": [],
   "source": [
    "features_mapped_selected.sort_values(by=['query_idx'], ascending=True, inplace=True)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "outputs": [
    {
     "data": {
      "text/plain": "           rt          mz  charge  mz_matched  query_idx  feature_idx  \\\n115  0.540066  293.123856    -1.0  293.123684          0         49.0   \n27   1.029794  197.080885    -1.0  197.080888          9        349.0   \n38   1.038621  243.086620    -1.0  243.072046         11         10.0   \n48   1.038621  243.086620    -1.0  243.086654         11          9.0   \n6    2.394052  185.117214    -1.0  185.117221         47        145.0   \n510  2.571720  575.270161    -1.0  575.270274         62        407.0   \n566  2.800668  901.239950    -1.0  901.240076         70         28.0   \n503  2.888530  575.270240    -1.0  575.270134         98         61.0   \n470  2.891299  529.264315    -1.0  529.264461        100         30.0   \n551  2.922067  901.239782    -1.0  901.240040        108        169.0   \n407  3.453756  401.123581    -1.0  401.123491        133        176.0   \n442  3.511706  447.128813    -1.0  447.128886        139        178.0   \n397  3.514753  401.123297    -1.0  401.123412        140         67.0   \n378  3.520378  399.165070    -1.0  399.165303        143        485.0   \n359  3.702673  399.165280    -1.0  399.165175        179         68.0   \n475  4.832797  531.126634    -1.0  531.126685        257         74.0   \n79   5.057898  263.128328    -1.0  263.128331        295         75.0   \n516  5.273424  607.347929    -1.0  607.348046        355         33.0   \n487  5.288419  561.342286    -1.0  561.342258        361        216.0   \n74   5.438041  263.128418    -1.0  263.092009        419        610.0   \n446  5.485260  485.218956    -1.0  485.218688        427        232.0   \n433  5.553630  439.213074    -1.0  439.213118        444        233.0   \n537  5.591855  717.239425    -1.0  717.239338        452         36.0   \n\n     n_isotopes       int_sum      int_apex  rt_start   rt_apex    rt_end  \\\n115         4.0  3.185037e+08  2.604713e+07  0.462098  0.485730  0.547763   \n27          2.0  5.872560e+07  3.080959e+06  0.969436  1.013511  1.096153   \n38          2.0  8.652044e+06  2.004301e+05  0.981798  1.017862  1.076967   \n48          3.0  2.691171e+08  2.777882e+07  0.969068  1.018452  1.095271   \n6           3.0  1.073909e+08  5.626948e+06  2.306116  2.397145  2.470669   \n510         2.0  3.334297e+07  7.456169e+05  2.492716  2.568866  2.657413   \n566         5.0  4.464346e+08  1.857238e+07  2.763218  2.799048  2.862177   \n503         4.0  1.476213e+08  8.163773e+06  2.826197  2.892673  2.966147   \n470         4.0  2.498112e+08  1.847013e+07  2.823975  2.890438  2.967127   \n551         3.0  2.422610e+07  6.407072e+05  2.898216  2.922430  3.052148   \n407         3.0  1.266844e+08  2.553891e+06  3.378084  3.424526  3.460872   \n442         3.0  4.796815e+07  2.113462e+06  3.460033  3.508233  3.604632   \n397         4.0  2.214789e+08  1.032683e+07  3.460645  3.509268  3.601395   \n378         2.0  1.553639e+07  4.104083e+05  3.435986  3.501480  3.565451   \n359         4.0  5.246759e+08  4.480775e+07  3.654622  3.702969  3.783549   \n475         4.0  1.986980e+07  5.050768e+05  4.746904  4.808225  4.877407   \n79          4.0  5.822129e+08  3.305191e+07  4.964282  5.058464  5.176191   \n516         5.0  9.489884e+08  7.218837e+07  5.206930  5.265741  5.328754   \n487         3.0  7.629101e+07  3.700553e+06  5.209898  5.265184  5.325276   \n74          2.0  2.428009e+07  6.765259e+05  5.286464  5.496199  5.528658   \n446         3.0  1.178318e+08  5.787977e+06  5.472038  5.495637  5.551265   \n433         3.0  1.157299e+08  4.069933e+06  5.472625  5.495192  5.553864   \n537         5.0  7.494613e+08  7.539418e+07  5.531435  5.555526  5.607148   \n\n     scan_number  rt_offset  ms1_idx  \n115          238   0.054336      237  \n27           460   0.016283      450  \n38           465   0.020759      453  \n48           465   0.020170      453  \n6           1085   0.003093     1037  \n510         1173   0.002854     1110  \n566         1278   0.001621     1207  \n503         1331   0.004143     1231  \n470         1333   0.000861     1232  \n551         1351   0.000362     1242  \n407         1600   0.029230     1466  \n442         1629   0.003473     1489  \n397         1631   0.005486     1490  \n378         1635   0.018898     1491  \n359         1737   0.000296     1557  \n475         2286   0.024572     2028  \n79          2409   0.000566     2113  \n516         2543   0.007682     2187  \n487         2553   0.023236     2191  \n74          2651   0.058158     2231  \n446         2677   0.010378     2249  \n433         2718   0.058439     2273  \n537         2740   0.036329     2287  ",
      "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>rt</th>\n      <th>mz</th>\n      <th>charge</th>\n      <th>mz_matched</th>\n      <th>query_idx</th>\n      <th>feature_idx</th>\n      <th>n_isotopes</th>\n      <th>int_sum</th>\n      <th>int_apex</th>\n      <th>rt_start</th>\n      <th>rt_apex</th>\n      <th>rt_end</th>\n      <th>scan_number</th>\n      <th>rt_offset</th>\n      <th>ms1_idx</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>115</th>\n      <td>0.540066</td>\n      <td>293.123856</td>\n      <td>-1.0</td>\n      <td>293.123684</td>\n      <td>0</td>\n      <td>49.0</td>\n      <td>4.0</td>\n      <td>3.185037e+08</td>\n      <td>2.604713e+07</td>\n      <td>0.462098</td>\n      <td>0.485730</td>\n      <td>0.547763</td>\n      <td>238</td>\n      <td>0.054336</td>\n      <td>237</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>1.029794</td>\n      <td>197.080885</td>\n      <td>-1.0</td>\n      <td>197.080888</td>\n      <td>9</td>\n      <td>349.0</td>\n      <td>2.0</td>\n      <td>5.872560e+07</td>\n      <td>3.080959e+06</td>\n      <td>0.969436</td>\n      <td>1.013511</td>\n      <td>1.096153</td>\n      <td>460</td>\n      <td>0.016283</td>\n      <td>450</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>1.038621</td>\n      <td>243.086620</td>\n      <td>-1.0</td>\n      <td>243.072046</td>\n      <td>11</td>\n      <td>10.0</td>\n      <td>2.0</td>\n      <td>8.652044e+06</td>\n      <td>2.004301e+05</td>\n      <td>0.981798</td>\n      <td>1.017862</td>\n      <td>1.076967</td>\n      <td>465</td>\n      <td>0.020759</td>\n      <td>453</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>1.038621</td>\n      <td>243.086620</td>\n      <td>-1.0</td>\n      <td>243.086654</td>\n      <td>11</td>\n      <td>9.0</td>\n      <td>3.0</td>\n      <td>2.691171e+08</td>\n      <td>2.777882e+07</td>\n      <td>0.969068</td>\n      <td>1.018452</td>\n      <td>1.095271</td>\n      <td>465</td>\n      <td>0.020170</td>\n      <td>453</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2.394052</td>\n      <td>185.117214</td>\n      <td>-1.0</td>\n      <td>185.117221</td>\n      <td>47</td>\n      <td>145.0</td>\n      <td>3.0</td>\n      <td>1.073909e+08</td>\n      <td>5.626948e+06</td>\n      <td>2.306116</td>\n      <td>2.397145</td>\n      <td>2.470669</td>\n      <td>1085</td>\n      <td>0.003093</td>\n      <td>1037</td>\n    </tr>\n    <tr>\n      <th>510</th>\n      <td>2.571720</td>\n      <td>575.270161</td>\n      <td>-1.0</td>\n      <td>575.270274</td>\n      <td>62</td>\n      <td>407.0</td>\n      <td>2.0</td>\n      <td>3.334297e+07</td>\n      <td>7.456169e+05</td>\n      <td>2.492716</td>\n      <td>2.568866</td>\n      <td>2.657413</td>\n      <td>1173</td>\n      <td>0.002854</td>\n      <td>1110</td>\n    </tr>\n    <tr>\n      <th>566</th>\n      <td>2.800668</td>\n      <td>901.239950</td>\n      <td>-1.0</td>\n      <td>901.240076</td>\n      <td>70</td>\n      <td>28.0</td>\n      <td>5.0</td>\n      <td>4.464346e+08</td>\n      <td>1.857238e+07</td>\n      <td>2.763218</td>\n      <td>2.799048</td>\n      <td>2.862177</td>\n      <td>1278</td>\n      <td>0.001621</td>\n      <td>1207</td>\n    </tr>\n    <tr>\n      <th>503</th>\n      <td>2.888530</td>\n      <td>575.270240</td>\n      <td>-1.0</td>\n      <td>575.270134</td>\n      <td>98</td>\n      <td>61.0</td>\n      <td>4.0</td>\n      <td>1.476213e+08</td>\n      <td>8.163773e+06</td>\n      <td>2.826197</td>\n      <td>2.892673</td>\n      <td>2.966147</td>\n      <td>1331</td>\n      <td>0.004143</td>\n      <td>1231</td>\n    </tr>\n    <tr>\n      <th>470</th>\n      <td>2.891299</td>\n      <td>529.264315</td>\n      <td>-1.0</td>\n      <td>529.264461</td>\n      <td>100</td>\n      <td>30.0</td>\n      <td>4.0</td>\n      <td>2.498112e+08</td>\n      <td>1.847013e+07</td>\n      <td>2.823975</td>\n      <td>2.890438</td>\n      <td>2.967127</td>\n      <td>1333</td>\n      <td>0.000861</td>\n      <td>1232</td>\n    </tr>\n    <tr>\n      <th>551</th>\n      <td>2.922067</td>\n      <td>901.239782</td>\n      <td>-1.0</td>\n      <td>901.240040</td>\n      <td>108</td>\n      <td>169.0</td>\n      <td>3.0</td>\n      <td>2.422610e+07</td>\n      <td>6.407072e+05</td>\n      <td>2.898216</td>\n      <td>2.922430</td>\n      <td>3.052148</td>\n      <td>1351</td>\n      <td>0.000362</td>\n      <td>1242</td>\n    </tr>\n    <tr>\n      <th>407</th>\n      <td>3.453756</td>\n      <td>401.123581</td>\n      <td>-1.0</td>\n      <td>401.123491</td>\n      <td>133</td>\n      <td>176.0</td>\n      <td>3.0</td>\n      <td>1.266844e+08</td>\n      <td>2.553891e+06</td>\n      <td>3.378084</td>\n      <td>3.424526</td>\n      <td>3.460872</td>\n      <td>1600</td>\n      <td>0.029230</td>\n      <td>1466</td>\n    </tr>\n    <tr>\n      <th>442</th>\n      <td>3.511706</td>\n      <td>447.128813</td>\n      <td>-1.0</td>\n      <td>447.128886</td>\n      <td>139</td>\n      <td>178.0</td>\n      <td>3.0</td>\n      <td>4.796815e+07</td>\n      <td>2.113462e+06</td>\n      <td>3.460033</td>\n      <td>3.508233</td>\n      <td>3.604632</td>\n      <td>1629</td>\n      <td>0.003473</td>\n      <td>1489</td>\n    </tr>\n    <tr>\n      <th>397</th>\n      <td>3.514753</td>\n      <td>401.123297</td>\n      <td>-1.0</td>\n      <td>401.123412</td>\n      <td>140</td>\n      <td>67.0</td>\n      <td>4.0</td>\n      <td>2.214789e+08</td>\n      <td>1.032683e+07</td>\n      <td>3.460645</td>\n      <td>3.509268</td>\n      <td>3.601395</td>\n      <td>1631</td>\n      <td>0.005486</td>\n      <td>1490</td>\n    </tr>\n    <tr>\n      <th>378</th>\n      <td>3.520378</td>\n      <td>399.165070</td>\n      <td>-1.0</td>\n      <td>399.165303</td>\n      <td>143</td>\n      <td>485.0</td>\n      <td>2.0</td>\n      <td>1.553639e+07</td>\n      <td>4.104083e+05</td>\n      <td>3.435986</td>\n      <td>3.501480</td>\n      <td>3.565451</td>\n      <td>1635</td>\n      <td>0.018898</td>\n      <td>1491</td>\n    </tr>\n    <tr>\n      <th>359</th>\n      <td>3.702673</td>\n      <td>399.165280</td>\n      <td>-1.0</td>\n      <td>399.165175</td>\n      <td>179</td>\n      <td>68.0</td>\n      <td>4.0</td>\n      <td>5.246759e+08</td>\n      <td>4.480775e+07</td>\n      <td>3.654622</td>\n      <td>3.702969</td>\n      <td>3.783549</td>\n      <td>1737</td>\n      <td>0.000296</td>\n      <td>1557</td>\n    </tr>\n    <tr>\n      <th>475</th>\n      <td>4.832797</td>\n      <td>531.126634</td>\n      <td>-1.0</td>\n      <td>531.126685</td>\n      <td>257</td>\n      <td>74.0</td>\n      <td>4.0</td>\n      <td>1.986980e+07</td>\n      <td>5.050768e+05</td>\n      <td>4.746904</td>\n      <td>4.808225</td>\n      <td>4.877407</td>\n      <td>2286</td>\n      <td>0.024572</td>\n      <td>2028</td>\n    </tr>\n    <tr>\n      <th>79</th>\n      <td>5.057898</td>\n      <td>263.128328</td>\n      <td>-1.0</td>\n      <td>263.128331</td>\n      <td>295</td>\n      <td>75.0</td>\n      <td>4.0</td>\n      <td>5.822129e+08</td>\n      <td>3.305191e+07</td>\n      <td>4.964282</td>\n      <td>5.058464</td>\n      <td>5.176191</td>\n      <td>2409</td>\n      <td>0.000566</td>\n      <td>2113</td>\n    </tr>\n    <tr>\n      <th>516</th>\n      <td>5.273424</td>\n      <td>607.347929</td>\n      <td>-1.0</td>\n      <td>607.348046</td>\n      <td>355</td>\n      <td>33.0</td>\n      <td>5.0</td>\n      <td>9.489884e+08</td>\n      <td>7.218837e+07</td>\n      <td>5.206930</td>\n      <td>5.265741</td>\n      <td>5.328754</td>\n      <td>2543</td>\n      <td>0.007682</td>\n      <td>2187</td>\n    </tr>\n    <tr>\n      <th>487</th>\n      <td>5.288419</td>\n      <td>561.342286</td>\n      <td>-1.0</td>\n      <td>561.342258</td>\n      <td>361</td>\n      <td>216.0</td>\n      <td>3.0</td>\n      <td>7.629101e+07</td>\n      <td>3.700553e+06</td>\n      <td>5.209898</td>\n      <td>5.265184</td>\n      <td>5.325276</td>\n      <td>2553</td>\n      <td>0.023236</td>\n      <td>2191</td>\n    </tr>\n    <tr>\n      <th>74</th>\n      <td>5.438041</td>\n      <td>263.128418</td>\n      <td>-1.0</td>\n      <td>263.092009</td>\n      <td>419</td>\n      <td>610.0</td>\n      <td>2.0</td>\n      <td>2.428009e+07</td>\n      <td>6.765259e+05</td>\n      <td>5.286464</td>\n      <td>5.496199</td>\n      <td>5.528658</td>\n      <td>2651</td>\n      <td>0.058158</td>\n      <td>2231</td>\n    </tr>\n    <tr>\n      <th>446</th>\n      <td>5.485260</td>\n      <td>485.218956</td>\n      <td>-1.0</td>\n      <td>485.218688</td>\n      <td>427</td>\n      <td>232.0</td>\n      <td>3.0</td>\n      <td>1.178318e+08</td>\n      <td>5.787977e+06</td>\n      <td>5.472038</td>\n      <td>5.495637</td>\n      <td>5.551265</td>\n      <td>2677</td>\n      <td>0.010378</td>\n      <td>2249</td>\n    </tr>\n    <tr>\n      <th>433</th>\n      <td>5.553630</td>\n      <td>439.213074</td>\n      <td>-1.0</td>\n      <td>439.213118</td>\n      <td>444</td>\n      <td>233.0</td>\n      <td>3.0</td>\n      <td>1.157299e+08</td>\n      <td>4.069933e+06</td>\n      <td>5.472625</td>\n      <td>5.495192</td>\n      <td>5.553864</td>\n      <td>2718</td>\n      <td>0.058439</td>\n      <td>2273</td>\n    </tr>\n    <tr>\n      <th>537</th>\n      <td>5.591855</td>\n      <td>717.239425</td>\n      <td>-1.0</td>\n      <td>717.239338</td>\n      <td>452</td>\n      <td>36.0</td>\n      <td>5.0</td>\n      <td>7.494613e+08</td>\n      <td>7.539418e+07</td>\n      <td>5.531435</td>\n      <td>5.555526</td>\n      <td>5.607148</td>\n      <td>2740</td>\n      <td>0.036329</td>\n      <td>2287</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_mapped_selected"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "outputs": [
    {
     "data": {
      "text/plain": "           rt          mz  charge  mz_matched  query_idx  feature_idx  \\\n115  0.540066  293.123856    -1.0  293.123684          0         49.0   \n27   1.029794  197.080885    -1.0  197.080888          9        349.0   \n38   1.038621  243.086620    -1.0  243.072046         11         10.0   \n48   1.038621  243.086620    -1.0  243.086654         11          9.0   \n6    2.394052  185.117214    -1.0  185.117221         47        145.0   \n510  2.571720  575.270161    -1.0  575.270274         62        407.0   \n566  2.800668  901.239950    -1.0  901.240076         70         28.0   \n503  2.888530  575.270240    -1.0  575.270134         98         61.0   \n470  2.891299  529.264315    -1.0  529.264461        100         30.0   \n551  2.922067  901.239782    -1.0  901.240040        108        169.0   \n407  3.453756  401.123581    -1.0  401.123491        133        176.0   \n442  3.511706  447.128813    -1.0  447.128886        139        178.0   \n397  3.514753  401.123297    -1.0  401.123412        140         67.0   \n378  3.520378  399.165070    -1.0  399.165303        143        485.0   \n359  3.702673  399.165280    -1.0  399.165175        179         68.0   \n475  4.832797  531.126634    -1.0  531.126685        257         74.0   \n79   5.057898  263.128328    -1.0  263.128331        295         75.0   \n516  5.273424  607.347929    -1.0  607.348046        355         33.0   \n487  5.288419  561.342286    -1.0  561.342258        361        216.0   \n74   5.438041  263.128418    -1.0  263.092009        419        610.0   \n446  5.485260  485.218956    -1.0  485.218688        427        232.0   \n433  5.553630  439.213074    -1.0  439.213118        444        233.0   \n537  5.591855  717.239425    -1.0  717.239338        452         36.0   \n\n     n_isotopes       int_sum      int_apex  rt_start   rt_apex    rt_end  \\\n115         4.0  3.185037e+08  2.604713e+07  0.462098  0.485730  0.547763   \n27          2.0  5.872560e+07  3.080959e+06  0.969436  1.013511  1.096153   \n38          2.0  8.652044e+06  2.004301e+05  0.981798  1.017862  1.076967   \n48          3.0  2.691171e+08  2.777882e+07  0.969068  1.018452  1.095271   \n6           3.0  1.073909e+08  5.626948e+06  2.306116  2.397145  2.470669   \n510         2.0  3.334297e+07  7.456169e+05  2.492716  2.568866  2.657413   \n566         5.0  4.464346e+08  1.857238e+07  2.763218  2.799048  2.862177   \n503         4.0  1.476213e+08  8.163773e+06  2.826197  2.892673  2.966147   \n470         4.0  2.498112e+08  1.847013e+07  2.823975  2.890438  2.967127   \n551         3.0  2.422610e+07  6.407072e+05  2.898216  2.922430  3.052148   \n407         3.0  1.266844e+08  2.553891e+06  3.378084  3.424526  3.460872   \n442         3.0  4.796815e+07  2.113462e+06  3.460033  3.508233  3.604632   \n397         4.0  2.214789e+08  1.032683e+07  3.460645  3.509268  3.601395   \n378         2.0  1.553639e+07  4.104083e+05  3.435986  3.501480  3.565451   \n359         4.0  5.246759e+08  4.480775e+07  3.654622  3.702969  3.783549   \n475         4.0  1.986980e+07  5.050768e+05  4.746904  4.808225  4.877407   \n79          4.0  5.822129e+08  3.305191e+07  4.964282  5.058464  5.176191   \n516         5.0  9.489884e+08  7.218837e+07  5.206930  5.265741  5.328754   \n487         3.0  7.629101e+07  3.700553e+06  5.209898  5.265184  5.325276   \n74          2.0  2.428009e+07  6.765259e+05  5.286464  5.496199  5.528658   \n446         3.0  1.178318e+08  5.787977e+06  5.472038  5.495637  5.551265   \n433         3.0  1.157299e+08  4.069933e+06  5.472625  5.495192  5.553864   \n537         5.0  7.494613e+08  7.539418e+07  5.531435  5.555526  5.607148   \n\n     scan_number  rt_offset  ms1_idx  \n115          238   0.054336      237  \n27           460   0.016283      450  \n38           465   0.020759      453  \n48           465   0.020170      453  \n6           1085   0.003093     1037  \n510         1173   0.002854     1110  \n566         1278   0.001621     1207  \n503         1331   0.004143     1231  \n470         1333   0.000861     1232  \n551         1351   0.000362     1242  \n407         1600   0.029230     1466  \n442         1629   0.003473     1489  \n397         1631   0.005486     1490  \n378         1635   0.018898     1491  \n359         1737   0.000296     1557  \n475         2286   0.024572     2028  \n79          2409   0.000566     2113  \n516         2543   0.007682     2187  \n487         2553   0.023236     2191  \n74          2651   0.058158     2231  \n446         2677   0.010378     2249  \n433         2718   0.058439     2273  \n537         2740   0.036329     2287  ",
      "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>rt</th>\n      <th>mz</th>\n      <th>charge</th>\n      <th>mz_matched</th>\n      <th>query_idx</th>\n      <th>feature_idx</th>\n      <th>n_isotopes</th>\n      <th>int_sum</th>\n      <th>int_apex</th>\n      <th>rt_start</th>\n      <th>rt_apex</th>\n      <th>rt_end</th>\n      <th>scan_number</th>\n      <th>rt_offset</th>\n      <th>ms1_idx</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>115</th>\n      <td>0.540066</td>\n      <td>293.123856</td>\n      <td>-1.0</td>\n      <td>293.123684</td>\n      <td>0</td>\n      <td>49.0</td>\n      <td>4.0</td>\n      <td>3.185037e+08</td>\n      <td>2.604713e+07</td>\n      <td>0.462098</td>\n      <td>0.485730</td>\n      <td>0.547763</td>\n      <td>238</td>\n      <td>0.054336</td>\n      <td>237</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>1.029794</td>\n      <td>197.080885</td>\n      <td>-1.0</td>\n      <td>197.080888</td>\n      <td>9</td>\n      <td>349.0</td>\n      <td>2.0</td>\n      <td>5.872560e+07</td>\n      <td>3.080959e+06</td>\n      <td>0.969436</td>\n      <td>1.013511</td>\n      <td>1.096153</td>\n      <td>460</td>\n      <td>0.016283</td>\n      <td>450</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>1.038621</td>\n      <td>243.086620</td>\n      <td>-1.0</td>\n      <td>243.072046</td>\n      <td>11</td>\n      <td>10.0</td>\n      <td>2.0</td>\n      <td>8.652044e+06</td>\n      <td>2.004301e+05</td>\n      <td>0.981798</td>\n      <td>1.017862</td>\n      <td>1.076967</td>\n      <td>465</td>\n      <td>0.020759</td>\n      <td>453</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>1.038621</td>\n      <td>243.086620</td>\n      <td>-1.0</td>\n      <td>243.086654</td>\n      <td>11</td>\n      <td>9.0</td>\n      <td>3.0</td>\n      <td>2.691171e+08</td>\n      <td>2.777882e+07</td>\n      <td>0.969068</td>\n      <td>1.018452</td>\n      <td>1.095271</td>\n      <td>465</td>\n      <td>0.020170</td>\n      <td>453</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2.394052</td>\n      <td>185.117214</td>\n      <td>-1.0</td>\n      <td>185.117221</td>\n      <td>47</td>\n      <td>145.0</td>\n      <td>3.0</td>\n      <td>1.073909e+08</td>\n      <td>5.626948e+06</td>\n      <td>2.306116</td>\n      <td>2.397145</td>\n      <td>2.470669</td>\n      <td>1085</td>\n      <td>0.003093</td>\n      <td>1037</td>\n    </tr>\n    <tr>\n      <th>510</th>\n      <td>2.571720</td>\n      <td>575.270161</td>\n      <td>-1.0</td>\n      <td>575.270274</td>\n      <td>62</td>\n      <td>407.0</td>\n      <td>2.0</td>\n      <td>3.334297e+07</td>\n      <td>7.456169e+05</td>\n      <td>2.492716</td>\n      <td>2.568866</td>\n      <td>2.657413</td>\n      <td>1173</td>\n      <td>0.002854</td>\n      <td>1110</td>\n    </tr>\n    <tr>\n      <th>566</th>\n      <td>2.800668</td>\n      <td>901.239950</td>\n      <td>-1.0</td>\n      <td>901.240076</td>\n      <td>70</td>\n      <td>28.0</td>\n      <td>5.0</td>\n      <td>4.464346e+08</td>\n      <td>1.857238e+07</td>\n      <td>2.763218</td>\n      <td>2.799048</td>\n      <td>2.862177</td>\n      <td>1278</td>\n      <td>0.001621</td>\n      <td>1207</td>\n    </tr>\n    <tr>\n      <th>503</th>\n      <td>2.888530</td>\n      <td>575.270240</td>\n      <td>-1.0</td>\n      <td>575.270134</td>\n      <td>98</td>\n      <td>61.0</td>\n      <td>4.0</td>\n      <td>1.476213e+08</td>\n      <td>8.163773e+06</td>\n      <td>2.826197</td>\n      <td>2.892673</td>\n      <td>2.966147</td>\n      <td>1331</td>\n      <td>0.004143</td>\n      <td>1231</td>\n    </tr>\n    <tr>\n      <th>470</th>\n      <td>2.891299</td>\n      <td>529.264315</td>\n      <td>-1.0</td>\n      <td>529.264461</td>\n      <td>100</td>\n      <td>30.0</td>\n      <td>4.0</td>\n      <td>2.498112e+08</td>\n      <td>1.847013e+07</td>\n      <td>2.823975</td>\n      <td>2.890438</td>\n      <td>2.967127</td>\n      <td>1333</td>\n      <td>0.000861</td>\n      <td>1232</td>\n    </tr>\n    <tr>\n      <th>551</th>\n      <td>2.922067</td>\n      <td>901.239782</td>\n      <td>-1.0</td>\n      <td>901.240040</td>\n      <td>108</td>\n      <td>169.0</td>\n      <td>3.0</td>\n      <td>2.422610e+07</td>\n      <td>6.407072e+05</td>\n      <td>2.898216</td>\n      <td>2.922430</td>\n      <td>3.052148</td>\n      <td>1351</td>\n      <td>0.000362</td>\n      <td>1242</td>\n    </tr>\n    <tr>\n      <th>407</th>\n      <td>3.453756</td>\n      <td>401.123581</td>\n      <td>-1.0</td>\n      <td>401.123491</td>\n      <td>133</td>\n      <td>176.0</td>\n      <td>3.0</td>\n      <td>1.266844e+08</td>\n      <td>2.553891e+06</td>\n      <td>3.378084</td>\n      <td>3.424526</td>\n      <td>3.460872</td>\n      <td>1600</td>\n      <td>0.029230</td>\n      <td>1466</td>\n    </tr>\n    <tr>\n      <th>442</th>\n      <td>3.511706</td>\n      <td>447.128813</td>\n      <td>-1.0</td>\n      <td>447.128886</td>\n      <td>139</td>\n      <td>178.0</td>\n      <td>3.0</td>\n      <td>4.796815e+07</td>\n      <td>2.113462e+06</td>\n      <td>3.460033</td>\n      <td>3.508233</td>\n      <td>3.604632</td>\n      <td>1629</td>\n      <td>0.003473</td>\n      <td>1489</td>\n    </tr>\n    <tr>\n      <th>397</th>\n      <td>3.514753</td>\n      <td>401.123297</td>\n      <td>-1.0</td>\n      <td>401.123412</td>\n      <td>140</td>\n      <td>67.0</td>\n      <td>4.0</td>\n      <td>2.214789e+08</td>\n      <td>1.032683e+07</td>\n      <td>3.460645</td>\n      <td>3.509268</td>\n      <td>3.601395</td>\n      <td>1631</td>\n      <td>0.005486</td>\n      <td>1490</td>\n    </tr>\n    <tr>\n      <th>378</th>\n      <td>3.520378</td>\n      <td>399.165070</td>\n      <td>-1.0</td>\n      <td>399.165303</td>\n      <td>143</td>\n      <td>485.0</td>\n      <td>2.0</td>\n      <td>1.553639e+07</td>\n      <td>4.104083e+05</td>\n      <td>3.435986</td>\n      <td>3.501480</td>\n      <td>3.565451</td>\n      <td>1635</td>\n      <td>0.018898</td>\n      <td>1491</td>\n    </tr>\n    <tr>\n      <th>359</th>\n      <td>3.702673</td>\n      <td>399.165280</td>\n      <td>-1.0</td>\n      <td>399.165175</td>\n      <td>179</td>\n      <td>68.0</td>\n      <td>4.0</td>\n      <td>5.246759e+08</td>\n      <td>4.480775e+07</td>\n      <td>3.654622</td>\n      <td>3.702969</td>\n      <td>3.783549</td>\n      <td>1737</td>\n      <td>0.000296</td>\n      <td>1557</td>\n    </tr>\n    <tr>\n      <th>475</th>\n      <td>4.832797</td>\n      <td>531.126634</td>\n      <td>-1.0</td>\n      <td>531.126685</td>\n      <td>257</td>\n      <td>74.0</td>\n      <td>4.0</td>\n      <td>1.986980e+07</td>\n      <td>5.050768e+05</td>\n      <td>4.746904</td>\n      <td>4.808225</td>\n      <td>4.877407</td>\n      <td>2286</td>\n      <td>0.024572</td>\n      <td>2028</td>\n    </tr>\n    <tr>\n      <th>79</th>\n      <td>5.057898</td>\n      <td>263.128328</td>\n      <td>-1.0</td>\n      <td>263.128331</td>\n      <td>295</td>\n      <td>75.0</td>\n      <td>4.0</td>\n      <td>5.822129e+08</td>\n      <td>3.305191e+07</td>\n      <td>4.964282</td>\n      <td>5.058464</td>\n      <td>5.176191</td>\n      <td>2409</td>\n      <td>0.000566</td>\n      <td>2113</td>\n    </tr>\n    <tr>\n      <th>516</th>\n      <td>5.273424</td>\n      <td>607.347929</td>\n      <td>-1.0</td>\n      <td>607.348046</td>\n      <td>355</td>\n      <td>33.0</td>\n      <td>5.0</td>\n      <td>9.489884e+08</td>\n      <td>7.218837e+07</td>\n      <td>5.206930</td>\n      <td>5.265741</td>\n      <td>5.328754</td>\n      <td>2543</td>\n      <td>0.007682</td>\n      <td>2187</td>\n    </tr>\n    <tr>\n      <th>487</th>\n      <td>5.288419</td>\n      <td>561.342286</td>\n      <td>-1.0</td>\n      <td>561.342258</td>\n      <td>361</td>\n      <td>216.0</td>\n      <td>3.0</td>\n      <td>7.629101e+07</td>\n      <td>3.700553e+06</td>\n      <td>5.209898</td>\n      <td>5.265184</td>\n      <td>5.325276</td>\n      <td>2553</td>\n      <td>0.023236</td>\n      <td>2191</td>\n    </tr>\n    <tr>\n      <th>74</th>\n      <td>5.438041</td>\n      <td>263.128418</td>\n      <td>-1.0</td>\n      <td>263.092009</td>\n      <td>419</td>\n      <td>610.0</td>\n      <td>2.0</td>\n      <td>2.428009e+07</td>\n      <td>6.765259e+05</td>\n      <td>5.286464</td>\n      <td>5.496199</td>\n      <td>5.528658</td>\n      <td>2651</td>\n      <td>0.058158</td>\n      <td>2231</td>\n    </tr>\n    <tr>\n      <th>446</th>\n      <td>5.485260</td>\n      <td>485.218956</td>\n      <td>-1.0</td>\n      <td>485.218688</td>\n      <td>427</td>\n      <td>232.0</td>\n      <td>3.0</td>\n      <td>1.178318e+08</td>\n      <td>5.787977e+06</td>\n      <td>5.472038</td>\n      <td>5.495637</td>\n      <td>5.551265</td>\n      <td>2677</td>\n      <td>0.010378</td>\n      <td>2249</td>\n    </tr>\n    <tr>\n      <th>433</th>\n      <td>5.553630</td>\n      <td>439.213074</td>\n      <td>-1.0</td>\n      <td>439.213118</td>\n      <td>444</td>\n      <td>233.0</td>\n      <td>3.0</td>\n      <td>1.157299e+08</td>\n      <td>4.069933e+06</td>\n      <td>5.472625</td>\n      <td>5.495192</td>\n      <td>5.553864</td>\n      <td>2718</td>\n      <td>0.058439</td>\n      <td>2273</td>\n    </tr>\n    <tr>\n      <th>537</th>\n      <td>5.591855</td>\n      <td>717.239425</td>\n      <td>-1.0</td>\n      <td>717.239338</td>\n      <td>452</td>\n      <td>36.0</td>\n      <td>5.0</td>\n      <td>7.494613e+08</td>\n      <td>7.539418e+07</td>\n      <td>5.531435</td>\n      <td>5.555526</td>\n      <td>5.607148</td>\n      <td>2740</td>\n      <td>0.036329</td>\n      <td>2287</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_mapped_selected_sorted['ms1']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "outputs": [
    {
     "data": {
      "text/plain": "23"
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(features_mapped_selected['feature_idx'].unique())"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "outputs": [
    {
     "data": {
      "text/plain": "23"
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(features_mapped_selected)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "outputs": [
    {
     "data": {
      "text/plain": "3.7033706"
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms_file['rt_list_ms1'][1557]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i am ms2 spectra plotter, and I have been sideloaded successfully\n",
      "I have 2 functions, head to tail plot and ms2 plot\n"
     ]
    }
   ],
   "source": [
    "import toolsets.ms2_spectra_plotter as plotter"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "outputs": [
    {
     "data": {
      "text/plain": "<module 'matplotlib.pyplot' from '/opt/homebrew/Caskroom/miniforge/base/envs/alphapept_env/lib/python3.8/site-packages/matplotlib/pyplot.py'>"
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 504x360 with 1 Axes>",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotter.ms2_plot(so.pack_spectra(mass_list_ms1[2113], int_list_ms1[2113]))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "outputs": [
    {
     "data": {
      "text/plain": "263.12835693359375"
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_list_ms1[2113][pd.Series(int_list_ms1[2113]).idxmax()]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "outputs": [
    {
     "data": {
      "text/plain": "529.2646484375"
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_list_ms1[1242][169]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[1.50981430e+02, 4.61390625e+04],\n       [1.52001022e+02, 4.04322406e+05],\n       [1.52977173e+02, 5.01647070e+04],\n       [1.53054611e+02, 1.84432203e+05],\n       [1.57153458e+02, 2.62128145e+04],\n       [1.58977249e+02, 5.08505531e+05],\n       [1.60840729e+02, 2.91247875e+05],\n       [1.60974808e+02, 5.38492891e+04],\n       [1.62837799e+02, 2.04366391e+05],\n       [1.64834610e+02, 3.42989297e+04],\n       [1.64925980e+02, 1.23340289e+05],\n       [1.68835159e+02, 3.28015547e+04],\n       [1.70832001e+02, 5.59698555e+04],\n       [1.70869461e+02, 6.31650547e+04],\n       [1.72005859e+02, 3.03255664e+04],\n       [1.72643173e+02, 2.97577930e+04],\n       [1.72829697e+02, 2.98577480e+04],\n       [1.72866852e+02, 3.30556367e+04],\n       [1.74950455e+02, 3.67168906e+04],\n       [1.74954880e+02, 1.24343088e+06],\n       [1.75958176e+02, 5.52373828e+04],\n       [1.78976669e+02, 5.46181500e+05],\n       [1.80898209e+02, 1.10490180e+05],\n       [1.80971939e+02, 1.12502117e+05],\n       [1.84006271e+02, 2.11735469e+05],\n       [1.87859756e+02, 4.49078398e+04],\n       [1.87927719e+02, 5.41418359e+04],\n       [1.88865540e+02, 2.62975996e+04],\n       [1.88931854e+02, 4.00986289e+04],\n       [1.89856842e+02, 4.50372461e+04],\n       [1.90927292e+02, 6.27230812e+05],\n       [2.05838669e+02, 3.10773574e+04],\n       [2.06163589e+02, 2.50499043e+04],\n       [2.06971878e+02, 2.72028594e+05],\n       [2.07917648e+02, 3.60955586e+04],\n       [2.07930191e+02, 1.60623844e+05],\n       [2.12074020e+02, 3.93981523e+04],\n       [2.15766571e+02, 2.58230684e+04],\n       [2.16188797e+02, 2.75422812e+05],\n       [2.16196152e+02, 1.07584789e+05],\n       [2.16200806e+02, 1.22716469e+05],\n       [2.16205414e+02, 5.15932461e+04],\n       [2.17864380e+02, 3.35097656e+04],\n       [2.25682709e+02, 2.59758750e+04],\n       [2.26053513e+02, 3.37995039e+04],\n       [2.26965195e+02, 3.59999414e+04],\n       [2.28159958e+02, 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[3.36858521e+02, 4.52830547e+04],\n       [3.61186066e+02, 3.17339785e+04],\n       [3.62874512e+02, 4.63428516e+04],\n       [3.71112915e+02, 4.23466172e+04],\n       [3.78917969e+02, 6.09628906e+04],\n       [3.85149567e+02, 2.71764656e+05],\n       [3.88101318e+02, 2.91911504e+04],\n       [3.94890045e+02, 1.27034852e+05],\n       [3.97150024e+02, 4.25106602e+04],\n       [3.99018738e+02, 1.76574031e+05],\n       [3.99125397e+02, 9.66882656e+04],\n       [3.99134125e+02, 2.33587094e+05],\n       [3.99165100e+02, 3.61924120e+07],\n       [3.99189575e+02, 2.47965781e+05],\n       [3.99195953e+02, 2.62590906e+05],\n       [3.99303162e+02, 1.04915594e+05],\n       [3.99318939e+02, 6.64007031e+04],\n       [4.00168549e+02, 7.64949850e+06],\n       [4.01123169e+02, 1.60869094e+05],\n       [4.01170563e+02, 1.25156400e+06],\n       [4.02172821e+02, 1.94904219e+05],\n       [4.14159973e+02, 3.02888496e+04],\n       [4.35141724e+02, 2.81093300e+06],\n       [4.36145447e+02, 6.10292062e+05],\n       [4.37138367e+02, 8.88622500e+05],\n       [4.38142303e+02, 1.50880719e+05],\n       [4.45170746e+02, 4.97144375e+04],\n       [4.57124512e+02, 1.93790266e+05],\n       [4.61201477e+02, 1.46951719e+05],\n       [4.62160950e+02, 3.27714250e+06],\n       [4.62175568e+02, 4.17351367e+04],\n       [4.62205109e+02, 3.17512793e+04],\n       [4.63164154e+02, 7.02225875e+05],\n       [4.64166656e+02, 1.48857953e+05],\n       [4.67152283e+02, 1.64820838e+06],\n       [4.68156128e+02, 3.55996625e+05],\n       [4.69158508e+02, 6.68064141e+04],\n       [4.72350891e+02, 2.63921699e+04],\n       [4.83126312e+02, 1.79683203e+05],\n       [4.84142792e+02, 6.17823516e+04],\n       [4.89164124e+02, 2.99540391e+04],\n       [4.97132172e+02, 3.58720703e+04],\n       [5.03129059e+02, 1.08766492e+05],\n       [5.13160645e+02, 3.29737344e+05],\n       [5.14162476e+02, 5.15446797e+04],\n       [5.15135193e+02, 6.50218086e+04],\n       [5.25038025e+02, 3.43936688e+05],\n       [5.27034424e+02, 1.68448516e+05],\n       [5.29123108e+02, 1.83420938e+05],\n       [5.29264832e+02, 3.43637227e+04],\n       [5.35065979e+02, 1.77726141e+05],\n       [5.35087036e+02, 2.80830352e+04],\n       [5.35139587e+02, 1.65197422e+05],\n       [5.36070007e+02, 1.02770180e+05],\n       [5.40092163e+02, 3.63585898e+04],\n       [5.42095947e+02, 3.58666328e+04],\n       [5.43100830e+02, 2.81631621e+04],\n       [5.44086670e+02, 3.60141094e+04],\n       [5.45095703e+02, 4.04235781e+05],\n       [5.46098206e+02, 5.54230391e+04],\n       [5.64309082e+02, 5.03644062e+04],\n       [5.72032349e+02, 3.10999609e+04],\n       [5.81133606e+02, 4.20169883e+04],\n       [6.00285645e+02, 1.08326633e+05],\n       [6.05051147e+02, 3.52593828e+04],\n       [6.07296753e+02, 4.61828938e+05],\n       [6.08299316e+02, 1.34969234e+05],\n       [6.09300537e+02, 3.18533555e+04],\n       [6.10314941e+02, 1.85383200e+06],\n       [6.11318604e+02, 5.48766062e+05],\n       [6.12320251e+02, 1.04737711e+05],\n       [6.13083496e+02, 1.42561922e+05],\n       [6.14088684e+02, 2.80240117e+04],\n       [6.27305603e+02, 3.02006777e+04],\n       [6.32296448e+02, 4.03677344e+04],\n       [6.93427307e+02, 2.95719062e+04],\n       [7.08728210e+02, 2.96040391e+04],\n       [7.12572998e+02, 3.76259961e+04],\n       [7.18915588e+02, 2.91406406e+04],\n       [7.54387085e+02, 3.05488066e+04],\n       [7.99338379e+02, 1.00102750e+06],\n       [8.00340210e+02, 3.38021406e+05],\n       [8.01344971e+02, 1.05111773e+05],\n       [8.35314331e+02, 2.23169281e+05],\n       [8.36318359e+02, 1.15617305e+05],\n       [8.37313904e+02, 6.22587578e+04],\n       [9.64875854e+02, 3.90598867e+04],\n       [1.20631897e+03, 3.30029414e+04],\n       [1.33899316e+03, 3.08733535e+04],\n       [1.39683862e+03, 3.51961133e+04],\n       [1.43477515e+03, 2.94748770e+04]], dtype=float32)"
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "so.convert_string_to_nist(so.pack_spectra(mass_list_ms1[1557], int_list_ms1[1557]))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "outputs": [],
   "source": [
    "ms_file = load_mzml_data(mzml_file)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "outputs": [],
   "source": [
    "mapped_ms2_idx = set(features_mapped[\"query_idx\"].tolist())"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "outputs": [
    {
     "data": {
      "text/plain": "215"
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(features_mapped['query_idx'].unique())"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "outputs": [
    {
     "data": {
      "text/plain": "215"
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(mapped_ms2_idx)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "outputs": [],
   "source": [
    "selected_ms2_idx = features_mapped_selected.loc[:, \"query_idx\"].tolist()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "outputs": [],
   "source": [
    "selected_ms2_idx.sort()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "outputs": [],
   "source": [
    "idx_to_ms1_intensity_ratio = {int(row[\"query_idx\"]): row[\"ms1_intensity_ratio\"]\n",
    "                                  for i, row in features_mapped_selected.iterrows()}"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "outputs": [
    {
     "data": {
      "text/plain": "157"
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms_file['indices_ms1'][1559]-ms_file['indices_ms1'][1558]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "outputs": [
    {
     "data": {
      "text/plain": "238"
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms_file['scan_list_ms2'][0]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "outputs": [],
   "source": [
    "mass_list, intensity_list = load_mzml_data(mzml_file, nested_array = True, ifSciex = False)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "outputs": [
    {
     "data": {
      "text/plain": "array([ 150.98143005,  152.00102234,  152.97717285,  153.05461121,\n        157.15345764,  158.97724915,  160.84072876,  160.97480774,\n        162.83779907,  164.83460999,  164.92597961,  168.8351593 ,\n        170.83200073,  170.86946106,  172.00585938,  172.64317322,\n        172.82969666,  172.86685181,  174.95045471,  174.95487976,\n        175.95817566,  178.97666931,  180.89820862,  180.97193909,\n        184.00627136,  187.85975647,  187.92771912,  188.86553955,\n        188.93185425,  189.85684204,  190.92729187,  205.83866882,\n        206.16358948,  206.97187805,  207.91764832,  207.93019104,\n        212.07402039,  215.76657104,  216.188797  ,  216.19615173,\n        216.20080566,  216.20541382,  217.86437988,  225.68270874,\n        226.05351257,  226.9651947 ,  228.15995789,  228.9591217 ,\n        230.95515442,  231.93086243,  232.91394043,  235.92530823,\n        237.11201477,  242.94267273,  249.12228394,  256.95428467,\n        258.91513062,  263.59472656,  265.84994507,  267.84762573,\n        288.93597412,  299.91815186,  304.28463745,  310.92947388,\n        314.69537354,  316.8737793 ,  316.94683838,  320.88549805,\n        326.90274048,  333.66122437,  336.85852051,  361.18606567,\n        362.87451172,  371.11291504,  378.91796875,  385.14956665,\n        388.10131836,  394.89004517,  397.15002441,  399.01873779,\n        399.12539673,  399.13412476,  399.1651001 ,  399.1895752 ,\n        399.19595337,  399.30316162,  399.31893921,  400.16854858,\n        401.12316895,  401.17056274,  402.17282104,  414.15997314,\n        435.14172363,  436.14544678,  437.1383667 ,  438.14230347,\n        445.17074585,  457.12451172,  461.20147705,  462.16094971,\n        462.17556763,  462.20510864,  463.16415405,  464.16665649,\n        467.15228271,  468.15612793,  469.1585083 ,  472.35089111,\n        483.12631226,  484.14279175,  489.16412354,  497.13217163,\n        503.12905884,  513.16064453,  514.16247559,  515.13519287,\n        525.0380249 ,  527.03442383,  529.12310791,  529.26483154,\n        535.065979  ,  535.08703613,  535.1395874 ,  536.07000732,\n        540.09216309,  542.09594727,  543.10083008,  544.08666992,\n        545.09570312,  546.09820557,  564.30908203,  572.03234863,\n        581.13360596,  600.28564453,  605.05114746,  607.29675293,\n        608.29931641,  609.30053711,  610.31494141,  611.31860352,\n        612.32025146,  613.08349609,  614.08868408,  627.30560303,\n        632.29644775,  693.42730713,  708.72821045,  712.57299805,\n        718.91558838,  754.38708496,  799.33837891,  800.34020996,\n        801.3449707 ,  835.31433105,  836.31835938,  837.31390381,\n        964.87585449, 1206.31896973, 1338.99316406, 1396.83862305,\n       1434.77514648])"
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms_file['mass_list_ms1'][532732:532893]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "outputs": [],
   "source": [
    "ms_file = load_mzml_data(mzml_file)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "outputs": [
    {
     "data": {
      "text/plain": "          rt          mz  charge  mz_matched  query_idx  feature_idx  \\\n1   1.512300  232.154520     1.0  232.154576         24       1777.0   \n2   1.480900  232.154450     1.0  232.154576         21       1777.0   \n3   1.266450  246.186731     1.0  246.170122         17       1758.0   \n4   1.196733  246.170474     1.0  246.206173         16       1705.0   \n6   0.180317  401.341391     1.0  401.341101          0        588.0   \n7   0.212917  401.340957     1.0  401.341101          4        588.0   \n12  0.184617  415.320512     1.0  415.274728          2       7450.0   \n13  1.427850  415.316400     1.0  415.316686         18       1781.0   \n14  1.465817  415.316349     1.0  415.316686         20       1781.0   \n15  0.184617  415.320512     1.0  415.320120          2       1197.0   \n17  0.271650  425.336854     1.0  425.336393          9       2743.0   \n18  0.271650  425.336854     1.0  425.368938          9       7263.0   \n20  0.241283  431.315000     1.0  431.315408          7        587.0   \n21  0.216350  431.315108     1.0  431.315408          5        587.0   \n23  0.281567  437.299257     1.0  437.298340         11       2843.0   \n25  0.920817  450.322010     1.0  450.272929         13      11747.0   \n26  0.955683  450.321296     1.0  450.272929         15      11747.0   \n27  0.955683  450.321296     1.0  450.321087         15       1600.0   \n28  0.920817  450.322010     1.0  450.321087         13       1600.0   \n29  0.936900  472.303743     1.0  472.303258         14       3689.0   \n30  0.898433  472.302746     1.0  472.303258         12       3689.0   \n32  1.484317  522.286535     1.0  522.285645         22       4435.0   \n33  1.664650  554.255985     1.0  554.254703         25        899.0   \n34  0.244717  666.636178     1.0  666.635455          8       7549.0   \n\n    ms1_int_sum_area  ms1_int_sum_apex  ms1_int_max_area  ms1_int_max_apex  \\\n1      151814.412198      3.934944e+06     142440.300493         3542254.0   \n2      151814.412198      3.934944e+06     142440.300493         3542254.0   \n3      286922.937773      4.260896e+06     258744.230017         3993974.0   \n4         204.892760      3.303564e+03        163.135383            2838.0   \n6       31472.678215      1.588007e+06      25057.052391         1263813.0   \n7       31472.678215      1.588007e+06      25057.052391         1263813.0   \n12        225.658070      2.366243e+04        195.072400           23361.0   \n13        394.272152      9.375710e+03        316.794383            7552.0   \n14        394.272152      9.375710e+03        316.794383            7552.0   \n15       3467.531816      2.446890e+05       2525.293475          185139.0   \n17        202.201929      1.054553e+04        173.796758            8015.0   \n18         74.094758      1.557165e+03         46.978708             880.0   \n20      32891.303335      1.596745e+06      25820.347850         1238406.0   \n21      32891.303335      1.596745e+06      25820.347850         1238406.0   \n23        133.689768      5.494483e+03         99.789517            4063.0   \n25          5.992708      1.617585e+02          5.274092             128.0   \n26          5.992708      1.617585e+02          5.274092             128.0   \n27        573.708013      7.991003e+03        435.958683            5953.0   \n28        573.708013      7.991003e+03        435.958683            5953.0   \n29       2284.025262      3.027051e+04       1725.037133           23722.0   \n30       2284.025262      3.027051e+04       1725.037133           23722.0   \n32        474.189130      2.148207e+04        375.030433           17907.0   \n33        161.189743      9.286187e+03        112.234942            6480.0   \n34         23.328151      1.946977e+03         18.251758            1544.0   \n\n    rt_start   rt_apex    rt_end  scan_number  \n1   1.460963  1.493265  1.544948          498  \n2   1.460963  1.493265  1.544948          490  \n3   1.227336  1.284583  1.382721          418  \n4   1.064172  1.106920  1.208445          395  \n6   0.174182  0.188105  0.219432           66  \n7   0.174182  0.188105  0.219432           76  \n12  0.178538  0.192750  0.217621           68  \n13  1.409096  1.447830  1.502300          475  \n14  1.409096  1.447830  1.502300          485  \n15  0.175902  0.187727  0.217289           68  \n17  0.201650  0.261241  0.288445           93  \n18  0.163861  0.208442  0.282745           93  \n20  0.200202  0.220060  0.251265           84  \n21  0.200202  0.220060  0.251265           77  \n23  0.255306  0.273662  0.317882           96  \n25  0.884703  0.945201  0.975450          306  \n26  0.884703  0.945201  0.975450          315  \n27  0.885911  0.959291  1.056152          315  \n28  0.885911  0.959291  1.056152          306  \n29  0.889992  0.961692  1.057291          310  \n30  0.889992  0.961692  1.057291          300  \n32  1.453211  1.486544  1.525433          491  \n33  1.635635  1.650804  1.676808          549  \n34  0.234650  0.237342  0.261574           85  ",
      "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>rt</th>\n      <th>mz</th>\n      <th>charge</th>\n      <th>mz_matched</th>\n      <th>query_idx</th>\n      <th>feature_idx</th>\n      <th>ms1_int_sum_area</th>\n      <th>ms1_int_sum_apex</th>\n      <th>ms1_int_max_area</th>\n      <th>ms1_int_max_apex</th>\n      <th>rt_start</th>\n      <th>rt_apex</th>\n      <th>rt_end</th>\n      <th>scan_number</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>1.512300</td>\n      <td>232.154520</td>\n      <td>1.0</td>\n      <td>232.154576</td>\n      <td>24</td>\n      <td>1777.0</td>\n      <td>151814.412198</td>\n      <td>3.934944e+06</td>\n      <td>142440.300493</td>\n      <td>3542254.0</td>\n      <td>1.460963</td>\n      <td>1.493265</td>\n      <td>1.544948</td>\n      <td>498</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1.480900</td>\n      <td>232.154450</td>\n      <td>1.0</td>\n      <td>232.154576</td>\n      <td>21</td>\n      <td>1777.0</td>\n      <td>151814.412198</td>\n      <td>3.934944e+06</td>\n      <td>142440.300493</td>\n      <td>3542254.0</td>\n      <td>1.460963</td>\n      <td>1.493265</td>\n      <td>1.544948</td>\n      <td>490</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1.266450</td>\n      <td>246.186731</td>\n      <td>1.0</td>\n      <td>246.170122</td>\n      <td>17</td>\n      <td>1758.0</td>\n      <td>286922.937773</td>\n      <td>4.260896e+06</td>\n      <td>258744.230017</td>\n      <td>3993974.0</td>\n      <td>1.227336</td>\n      <td>1.284583</td>\n      <td>1.382721</td>\n      <td>418</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1.196733</td>\n      <td>246.170474</td>\n      <td>1.0</td>\n      <td>246.206173</td>\n      <td>16</td>\n      <td>1705.0</td>\n      <td>204.892760</td>\n      <td>3.303564e+03</td>\n      <td>163.135383</td>\n      <td>2838.0</td>\n      <td>1.064172</td>\n      <td>1.106920</td>\n      <td>1.208445</td>\n      <td>395</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>0.180317</td>\n      <td>401.341391</td>\n      <td>1.0</td>\n      <td>401.341101</td>\n      <td>0</td>\n      <td>588.0</td>\n      <td>31472.678215</td>\n      <td>1.588007e+06</td>\n      <td>25057.052391</td>\n      <td>1263813.0</td>\n      <td>0.174182</td>\n      <td>0.188105</td>\n      <td>0.219432</td>\n      <td>66</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>0.212917</td>\n      <td>401.340957</td>\n      <td>1.0</td>\n      <td>401.341101</td>\n      <td>4</td>\n      <td>588.0</td>\n      <td>31472.678215</td>\n      <td>1.588007e+06</td>\n      <td>25057.052391</td>\n      <td>1263813.0</td>\n      <td>0.174182</td>\n      <td>0.188105</td>\n      <td>0.219432</td>\n      <td>76</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>0.184617</td>\n      <td>415.320512</td>\n      <td>1.0</td>\n      <td>415.274728</td>\n      <td>2</td>\n      <td>7450.0</td>\n      <td>225.658070</td>\n      <td>2.366243e+04</td>\n      <td>195.072400</td>\n      <td>23361.0</td>\n      <td>0.178538</td>\n      <td>0.192750</td>\n      <td>0.217621</td>\n      <td>68</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1.427850</td>\n      <td>415.316400</td>\n      <td>1.0</td>\n      <td>415.316686</td>\n      <td>18</td>\n      <td>1781.0</td>\n      <td>394.272152</td>\n      <td>9.375710e+03</td>\n      <td>316.794383</td>\n      <td>7552.0</td>\n      <td>1.409096</td>\n      <td>1.447830</td>\n      <td>1.502300</td>\n      <td>475</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1.465817</td>\n      <td>415.316349</td>\n      <td>1.0</td>\n      <td>415.316686</td>\n      <td>20</td>\n      <td>1781.0</td>\n      <td>394.272152</td>\n      <td>9.375710e+03</td>\n      <td>316.794383</td>\n      <td>7552.0</td>\n      <td>1.409096</td>\n      <td>1.447830</td>\n      <td>1.502300</td>\n      <td>485</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>0.184617</td>\n      <td>415.320512</td>\n      <td>1.0</td>\n      <td>415.320120</td>\n      <td>2</td>\n      <td>1197.0</td>\n      <td>3467.531816</td>\n      <td>2.446890e+05</td>\n      <td>2525.293475</td>\n      <td>185139.0</td>\n      <td>0.175902</td>\n      <td>0.187727</td>\n      <td>0.217289</td>\n      <td>68</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>0.271650</td>\n      <td>425.336854</td>\n      <td>1.0</td>\n      <td>425.336393</td>\n      <td>9</td>\n      <td>2743.0</td>\n      <td>202.201929</td>\n      <td>1.054553e+04</td>\n      <td>173.796758</td>\n      <td>8015.0</td>\n      <td>0.201650</td>\n      <td>0.261241</td>\n      <td>0.288445</td>\n      <td>93</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>0.271650</td>\n      <td>425.336854</td>\n      <td>1.0</td>\n      <td>425.368938</td>\n      <td>9</td>\n      <td>7263.0</td>\n      <td>74.094758</td>\n      <td>1.557165e+03</td>\n      <td>46.978708</td>\n      <td>880.0</td>\n      <td>0.163861</td>\n      <td>0.208442</td>\n      <td>0.282745</td>\n      <td>93</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>0.241283</td>\n      <td>431.315000</td>\n      <td>1.0</td>\n      <td>431.315408</td>\n      <td>7</td>\n      <td>587.0</td>\n      <td>32891.303335</td>\n      <td>1.596745e+06</td>\n      <td>25820.347850</td>\n      <td>1238406.0</td>\n      <td>0.200202</td>\n      <td>0.220060</td>\n      <td>0.251265</td>\n      <td>84</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>0.216350</td>\n      <td>431.315108</td>\n      <td>1.0</td>\n      <td>431.315408</td>\n      <td>5</td>\n      <td>587.0</td>\n      <td>32891.303335</td>\n      <td>1.596745e+06</td>\n      <td>25820.347850</td>\n      <td>1238406.0</td>\n      <td>0.200202</td>\n      <td>0.220060</td>\n      <td>0.251265</td>\n      <td>77</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>0.281567</td>\n      <td>437.299257</td>\n      <td>1.0</td>\n      <td>437.298340</td>\n      <td>11</td>\n      <td>2843.0</td>\n      <td>133.689768</td>\n      <td>5.494483e+03</td>\n      <td>99.789517</td>\n      <td>4063.0</td>\n      <td>0.255306</td>\n      <td>0.273662</td>\n      <td>0.317882</td>\n      <td>96</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>0.920817</td>\n      <td>450.322010</td>\n      <td>1.0</td>\n      <td>450.272929</td>\n      <td>13</td>\n      <td>11747.0</td>\n      <td>5.992708</td>\n      <td>1.617585e+02</td>\n      <td>5.274092</td>\n      <td>128.0</td>\n      <td>0.884703</td>\n      <td>0.945201</td>\n      <td>0.975450</td>\n      <td>306</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>0.955683</td>\n      <td>450.321296</td>\n      <td>1.0</td>\n      <td>450.272929</td>\n      <td>15</td>\n      <td>11747.0</td>\n      <td>5.992708</td>\n      <td>1.617585e+02</td>\n      <td>5.274092</td>\n      <td>128.0</td>\n      <td>0.884703</td>\n      <td>0.945201</td>\n      <td>0.975450</td>\n      <td>315</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>0.955683</td>\n      <td>450.321296</td>\n      <td>1.0</td>\n      <td>450.321087</td>\n      <td>15</td>\n      <td>1600.0</td>\n      <td>573.708013</td>\n      <td>7.991003e+03</td>\n      <td>435.958683</td>\n      <td>5953.0</td>\n      <td>0.885911</td>\n      <td>0.959291</td>\n      <td>1.056152</td>\n      <td>315</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>0.920817</td>\n      <td>450.322010</td>\n      <td>1.0</td>\n      <td>450.321087</td>\n      <td>13</td>\n      <td>1600.0</td>\n      <td>573.708013</td>\n      <td>7.991003e+03</td>\n      <td>435.958683</td>\n      <td>5953.0</td>\n      <td>0.885911</td>\n      <td>0.959291</td>\n      <td>1.056152</td>\n      <td>306</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>0.936900</td>\n      <td>472.303743</td>\n      <td>1.0</td>\n      <td>472.303258</td>\n      <td>14</td>\n      <td>3689.0</td>\n      <td>2284.025262</td>\n      <td>3.027051e+04</td>\n      <td>1725.037133</td>\n      <td>23722.0</td>\n      <td>0.889992</td>\n      <td>0.961692</td>\n      <td>1.057291</td>\n      <td>310</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>0.898433</td>\n      <td>472.302746</td>\n      <td>1.0</td>\n      <td>472.303258</td>\n      <td>12</td>\n      <td>3689.0</td>\n      <td>2284.025262</td>\n      <td>3.027051e+04</td>\n      <td>1725.037133</td>\n      <td>23722.0</td>\n      <td>0.889992</td>\n      <td>0.961692</td>\n      <td>1.057291</td>\n      <td>300</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>1.484317</td>\n      <td>522.286535</td>\n      <td>1.0</td>\n      <td>522.285645</td>\n      <td>22</td>\n      <td>4435.0</td>\n      <td>474.189130</td>\n      <td>2.148207e+04</td>\n      <td>375.030433</td>\n      <td>17907.0</td>\n      <td>1.453211</td>\n      <td>1.486544</td>\n      <td>1.525433</td>\n      <td>491</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>1.664650</td>\n      <td>554.255985</td>\n      <td>1.0</td>\n      <td>554.254703</td>\n      <td>25</td>\n      <td>899.0</td>\n      <td>161.189743</td>\n      <td>9.286187e+03</td>\n      <td>112.234942</td>\n      <td>6480.0</td>\n      <td>1.635635</td>\n      <td>1.650804</td>\n      <td>1.676808</td>\n      <td>549</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>0.244717</td>\n      <td>666.636178</td>\n      <td>1.0</td>\n      <td>666.635455</td>\n      <td>8</td>\n      <td>7549.0</td>\n      <td>23.328151</td>\n      <td>1.946977e+03</td>\n      <td>18.251758</td>\n      <td>1544.0</td>\n      <td>0.234650</td>\n      <td>0.237342</td>\n      <td>0.261574</td>\n      <td>85</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "outputs": [
    {
     "data": {
      "text/plain": "(532732, 532893)"
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "outputs": [
    {
     "data": {
      "text/plain": "array([ 150.91430664,  150.94595337,  150.97840881, ..., 1200.35681152,\n       1350.33520508, 1428.63903809])"
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms_file['mass_list_ms1']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "selected_ms2 = {\n",
    "        \"scan_number\": [ms_file[\"scan_list_ms2\"][i] for i in selected_ms2_idx],\n",
    "        \"precursor_mz\": [ms_file[\"mono_mzs2\"][i] for i in selected_ms2_idx],\n",
    "        \"charge\": [ms_file[\"charge2\"][i] for i in selected_ms2_idx],\n",
    "        \"ms1_intensity_ratio\": [idx_to_ms1_intensity_ratio[i] for i in selected_ms2_idx],\n",
    "        \"retention_time\": [ms_file[\"rt_list_ms2\"][i] for i in selected_ms2_idx],\n",
    "        \"peaks\": [np.array([ms_file[\"mass_list_ms2\"][i], ms_file[\"int_list_ms2\"][i]]).T for i in selected_ms2_idx],\n",
    "    }"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "outputs": [],
   "source": [
    "mass_list,int_list, mass_list_ms1, int_list_ms1 = load_mzml_data(mzml_file, nested_array=True)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "outputs": [
    {
     "data": {
      "text/plain": "4183"
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(mass_list_ms1)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "outputs": [
    {
     "data": {
      "text/plain": "array([ 150.91430664,  150.94595337,  150.97840881, ..., 1200.35681152,\n       1350.33520508, 1428.63903809])"
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms_file['mass_list_ms1']"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "outputs": [
    {
     "data": {
      "text/plain": "array([ 61.04837799,  87.92363739,  94.60292053, 124.14083862,\n       146.15480042, 170.18513489, 221.30213928, 277.8835144 ])"
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mass_list[237]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "outputs": [
    {
     "data": {
      "text/plain": "4183"
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ms_file['rt_list_ms1'])"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "outputs": [
    {
     "data": {
      "text/plain": "4732"
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(mass_list)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "outputs": [
    {
     "data": {
      "text/plain": "1428379"
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ms_file['_list_ms1']))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "outputs": [
    {
     "data": {
      "text/plain": "4184"
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ms_file['indices_ms1'])"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "outputs": [
    {
     "data": {
      "text/plain": "0.14282985"
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(ms2_selected.iloc[16]['peaks'][:,1]).max()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "outputs": [
    {
     "data": {
      "text/plain": "          rt          mz  charge  mz_matched  query_idx  feature_idx  \\\n14  1.465817  415.316349     1.0  415.316686         20       1781.0   \n\n    ms1_int_sum_area  ms1_int_sum_apex  ms1_int_max_area  ms1_int_max_apex  \\\n14        394.272152       9375.709626        316.794383            7552.0   \n\n    rt_start  rt_apex  rt_end  scan_number  rt_offset  \n14  1.409096  1.44783  1.5023          485   0.017986  ",
      "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>rt</th>\n      <th>mz</th>\n      <th>charge</th>\n      <th>mz_matched</th>\n      <th>query_idx</th>\n      <th>feature_idx</th>\n      <th>ms1_int_sum_area</th>\n      <th>ms1_int_sum_apex</th>\n      <th>ms1_int_max_area</th>\n      <th>ms1_int_max_apex</th>\n      <th>rt_start</th>\n      <th>rt_apex</th>\n      <th>rt_end</th>\n      <th>scan_number</th>\n      <th>rt_offset</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>14</th>\n      <td>1.465817</td>\n      <td>415.316349</td>\n      <td>1.0</td>\n      <td>415.316686</td>\n      <td>20</td>\n      <td>1781.0</td>\n      <td>394.272152</td>\n      <td>9375.709626</td>\n      <td>316.794383</td>\n      <td>7552.0</td>\n      <td>1.409096</td>\n      <td>1.44783</td>\n      <td>1.5023</td>\n      <td>485</td>\n      <td>0.017986</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search.num_search(features_mapped, \"scan_number\", 485, \"==\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [
    {
     "data": {
      "text/plain": "          rt          mz  charge  mz_matched  query_idx  feature_idx  \\\n32  1.484317  522.286535     1.0  522.285645         22       4435.0   \n15  0.184617  415.320512     1.0  415.320120          2       1197.0   \n27  0.955683  450.321296     1.0  450.321087         15       1600.0   \n21  0.216350  431.315108     1.0  431.315408          5        587.0   \n34  0.244717  666.636178     1.0  666.635455          8       7549.0   \n6   0.180317  401.341391     1.0  401.341101          0        588.0   \n23  0.281567  437.299257     1.0  437.298340         11       2843.0   \n12  0.184617  415.320512     1.0  415.274728          2       7450.0   \n17  0.271650  425.336854     1.0  425.336393          9       2743.0   \n26  0.955683  450.321296     1.0  450.272929         15      11747.0   \n2   1.480900  232.154450     1.0  232.154576         21       1777.0   \n33  1.664650  554.255985     1.0  554.254703         25        899.0   \n14  1.465817  415.316349     1.0  415.316686         20       1781.0   \n3   1.266450  246.186731     1.0  246.170122         17       1758.0   \n1   1.512300  232.154520     1.0  232.154576         24       1777.0   \n13  1.427850  415.316400     1.0  415.316686         18       1781.0   \n20  0.241283  431.315000     1.0  431.315408          7        587.0   \n25  0.920817  450.322010     1.0  450.272929         13      11747.0   \n29  0.936900  472.303743     1.0  472.303258         14       3689.0   \n7   0.212917  401.340957     1.0  401.341101          4        588.0   \n28  0.920817  450.322010     1.0  450.321087         13       1600.0   \n18  0.271650  425.336854     1.0  425.368938          9       7263.0   \n30  0.898433  472.302746     1.0  472.303258         12       3689.0   \n4   1.196733  246.170474     1.0  246.206173         16       1705.0   \n\n    ms1_int_sum_area  ms1_int_sum_apex  ms1_int_max_area  ms1_int_max_apex  \\\n32        474.189130      2.148207e+04        375.030433           17907.0   \n15       3467.531816      2.446890e+05       2525.293475          185139.0   \n27        573.708013      7.991003e+03        435.958683            5953.0   \n21      32891.303335      1.596745e+06      25820.347850         1238406.0   \n34         23.328151      1.946977e+03         18.251758            1544.0   \n6       31472.678215      1.588007e+06      25057.052391         1263813.0   \n23        133.689768      5.494483e+03         99.789517            4063.0   \n12        225.658070      2.366243e+04        195.072400           23361.0   \n17        202.201929      1.054553e+04        173.796758            8015.0   \n26          5.992708      1.617585e+02          5.274092             128.0   \n2      151814.412198      3.934944e+06     142440.300493         3542254.0   \n33        161.189743      9.286187e+03        112.234942            6480.0   \n14        394.272152      9.375710e+03        316.794383            7552.0   \n3      286922.937773      4.260896e+06     258744.230017         3993974.0   \n1      151814.412198      3.934944e+06     142440.300493         3542254.0   \n13        394.272152      9.375710e+03        316.794383            7552.0   \n20      32891.303335      1.596745e+06      25820.347850         1238406.0   \n25          5.992708      1.617585e+02          5.274092             128.0   \n29       2284.025262      3.027051e+04       1725.037133           23722.0   \n7       31472.678215      1.588007e+06      25057.052391         1263813.0   \n28        573.708013      7.991003e+03        435.958683            5953.0   \n18         74.094758      1.557165e+03         46.978708             880.0   \n30       2284.025262      3.027051e+04       1725.037133           23722.0   \n4         204.892760      3.303564e+03        163.135383            2838.0   \n\n    rt_start   rt_apex    rt_end  scan_number  rt_offset  \n32  1.453211  1.486544  1.525433          491   0.002228  \n15  0.175902  0.187727  0.217289           68   0.003110  \n27  0.885911  0.959291  1.056152          315   0.003607  \n21  0.200202  0.220060  0.251265           77   0.003710  \n34  0.234650  0.237342  0.261574           85   0.007374  \n6   0.174182  0.188105  0.219432           66   0.007788  \n23  0.255306  0.273662  0.317882           96   0.007905  \n12  0.178538  0.192750  0.217621           68   0.008133  \n17  0.201650  0.261241  0.288445           93   0.010409  \n26  0.884703  0.945201  0.975450          315   0.010482  \n2   1.460963  1.493265  1.544948          490   0.012365  \n33  1.635635  1.650804  1.676808          549   0.013846  \n14  1.409096  1.447830  1.502300          485   0.017986  \n3   1.227336  1.284583  1.382721          418   0.018133  \n1   1.460963  1.493265  1.544948          498   0.019035  \n13  1.409096  1.447830  1.502300          475   0.019980  \n20  0.200202  0.220060  0.251265           84   0.021224  \n25  0.884703  0.945201  0.975450          306   0.024384  \n29  0.889992  0.961692  1.057291          310   0.024792  \n7   0.174182  0.188105  0.219432           76   0.024812  \n28  0.885911  0.959291  1.056152          306   0.038474  \n18  0.163861  0.208442  0.282745           93   0.063208  \n30  0.889992  0.961692  1.057291          300   0.063258  \n4   1.064172  1.106920  1.208445          395   0.089813  ",
      "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>rt</th>\n      <th>mz</th>\n      <th>charge</th>\n      <th>mz_matched</th>\n      <th>query_idx</th>\n      <th>feature_idx</th>\n      <th>ms1_int_sum_area</th>\n      <th>ms1_int_sum_apex</th>\n      <th>ms1_int_max_area</th>\n      <th>ms1_int_max_apex</th>\n      <th>rt_start</th>\n      <th>rt_apex</th>\n      <th>rt_end</th>\n      <th>scan_number</th>\n      <th>rt_offset</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>32</th>\n      <td>1.484317</td>\n      <td>522.286535</td>\n      <td>1.0</td>\n      <td>522.285645</td>\n      <td>22</td>\n      <td>4435.0</td>\n      <td>474.189130</td>\n      <td>2.148207e+04</td>\n      <td>375.030433</td>\n      <td>17907.0</td>\n      <td>1.453211</td>\n      <td>1.486544</td>\n      <td>1.525433</td>\n      <td>491</td>\n      <td>0.002228</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>0.184617</td>\n      <td>415.320512</td>\n      <td>1.0</td>\n      <td>415.320120</td>\n      <td>2</td>\n      <td>1197.0</td>\n      <td>3467.531816</td>\n      <td>2.446890e+05</td>\n      <td>2525.293475</td>\n      <td>185139.0</td>\n      <td>0.175902</td>\n      <td>0.187727</td>\n      <td>0.217289</td>\n      <td>68</td>\n      <td>0.003110</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>0.955683</td>\n      <td>450.321296</td>\n      <td>1.0</td>\n      <td>450.321087</td>\n      <td>15</td>\n      <td>1600.0</td>\n      <td>573.708013</td>\n      <td>7.991003e+03</td>\n      <td>435.958683</td>\n      <td>5953.0</td>\n      <td>0.885911</td>\n      <td>0.959291</td>\n      <td>1.056152</td>\n      <td>315</td>\n      <td>0.003607</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>0.216350</td>\n      <td>431.315108</td>\n      <td>1.0</td>\n      <td>431.315408</td>\n      <td>5</td>\n      <td>587.0</td>\n      <td>32891.303335</td>\n      <td>1.596745e+06</td>\n      <td>25820.347850</td>\n      <td>1238406.0</td>\n      <td>0.200202</td>\n      <td>0.220060</td>\n      <td>0.251265</td>\n      <td>77</td>\n      <td>0.003710</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>0.244717</td>\n      <td>666.636178</td>\n      <td>1.0</td>\n      <td>666.635455</td>\n      <td>8</td>\n      <td>7549.0</td>\n      <td>23.328151</td>\n      <td>1.946977e+03</td>\n      <td>18.251758</td>\n      <td>1544.0</td>\n      <td>0.234650</td>\n      <td>0.237342</td>\n      <td>0.261574</td>\n      <td>85</td>\n      <td>0.007374</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>0.180317</td>\n      <td>401.341391</td>\n      <td>1.0</td>\n      <td>401.341101</td>\n      <td>0</td>\n      <td>588.0</td>\n      <td>31472.678215</td>\n      <td>1.588007e+06</td>\n      <td>25057.052391</td>\n      <td>1263813.0</td>\n      <td>0.174182</td>\n      <td>0.188105</td>\n      <td>0.219432</td>\n      <td>66</td>\n      <td>0.007788</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>0.281567</td>\n      <td>437.299257</td>\n      <td>1.0</td>\n      <td>437.298340</td>\n      <td>11</td>\n      <td>2843.0</td>\n      <td>133.689768</td>\n      <td>5.494483e+03</td>\n      <td>99.789517</td>\n      <td>4063.0</td>\n      <td>0.255306</td>\n      <td>0.273662</td>\n      <td>0.317882</td>\n      <td>96</td>\n      <td>0.007905</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>0.184617</td>\n      <td>415.320512</td>\n      <td>1.0</td>\n      <td>415.274728</td>\n      <td>2</td>\n      <td>7450.0</td>\n      <td>225.658070</td>\n      <td>2.366243e+04</td>\n      <td>195.072400</td>\n      <td>23361.0</td>\n      <td>0.178538</td>\n      <td>0.192750</td>\n      <td>0.217621</td>\n      <td>68</td>\n      <td>0.008133</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>0.271650</td>\n      <td>425.336854</td>\n      <td>1.0</td>\n      <td>425.336393</td>\n      <td>9</td>\n      <td>2743.0</td>\n      <td>202.201929</td>\n      <td>1.054553e+04</td>\n      <td>173.796758</td>\n      <td>8015.0</td>\n      <td>0.201650</td>\n      <td>0.261241</td>\n      <td>0.288445</td>\n      <td>93</td>\n      <td>0.010409</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>0.955683</td>\n      <td>450.321296</td>\n      <td>1.0</td>\n      <td>450.272929</td>\n      <td>15</td>\n      <td>11747.0</td>\n      <td>5.992708</td>\n      <td>1.617585e+02</td>\n      <td>5.274092</td>\n      <td>128.0</td>\n      <td>0.884703</td>\n      <td>0.945201</td>\n      <td>0.975450</td>\n      <td>315</td>\n      <td>0.010482</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1.480900</td>\n      <td>232.154450</td>\n      <td>1.0</td>\n      <td>232.154576</td>\n      <td>21</td>\n      <td>1777.0</td>\n      <td>151814.412198</td>\n      <td>3.934944e+06</td>\n      <td>142440.300493</td>\n      <td>3542254.0</td>\n      <td>1.460963</td>\n      <td>1.493265</td>\n      <td>1.544948</td>\n      <td>490</td>\n      <td>0.012365</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>1.664650</td>\n      <td>554.255985</td>\n      <td>1.0</td>\n      <td>554.254703</td>\n      <td>25</td>\n      <td>899.0</td>\n      <td>161.189743</td>\n      <td>9.286187e+03</td>\n      <td>112.234942</td>\n      <td>6480.0</td>\n      <td>1.635635</td>\n      <td>1.650804</td>\n      <td>1.676808</td>\n      <td>549</td>\n      <td>0.013846</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1.465817</td>\n      <td>415.316349</td>\n      <td>1.0</td>\n      <td>415.316686</td>\n      <td>20</td>\n      <td>1781.0</td>\n      <td>394.272152</td>\n      <td>9.375710e+03</td>\n      <td>316.794383</td>\n      <td>7552.0</td>\n      <td>1.409096</td>\n      <td>1.447830</td>\n      <td>1.502300</td>\n      <td>485</td>\n      <td>0.017986</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1.266450</td>\n      <td>246.186731</td>\n      <td>1.0</td>\n      <td>246.170122</td>\n      <td>17</td>\n      <td>1758.0</td>\n      <td>286922.937773</td>\n      <td>4.260896e+06</td>\n      <td>258744.230017</td>\n      <td>3993974.0</td>\n      <td>1.227336</td>\n      <td>1.284583</td>\n      <td>1.382721</td>\n      <td>418</td>\n      <td>0.018133</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1.512300</td>\n      <td>232.154520</td>\n      <td>1.0</td>\n      <td>232.154576</td>\n      <td>24</td>\n      <td>1777.0</td>\n      <td>151814.412198</td>\n      <td>3.934944e+06</td>\n      <td>142440.300493</td>\n      <td>3542254.0</td>\n      <td>1.460963</td>\n      <td>1.493265</td>\n      <td>1.544948</td>\n      <td>498</td>\n      <td>0.019035</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1.427850</td>\n      <td>415.316400</td>\n      <td>1.0</td>\n      <td>415.316686</td>\n      <td>18</td>\n      <td>1781.0</td>\n      <td>394.272152</td>\n      <td>9.375710e+03</td>\n      <td>316.794383</td>\n      <td>7552.0</td>\n      <td>1.409096</td>\n      <td>1.447830</td>\n      <td>1.502300</td>\n      <td>475</td>\n      <td>0.019980</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>0.241283</td>\n      <td>431.315000</td>\n      <td>1.0</td>\n      <td>431.315408</td>\n      <td>7</td>\n      <td>587.0</td>\n      <td>32891.303335</td>\n      <td>1.596745e+06</td>\n      <td>25820.347850</td>\n      <td>1238406.0</td>\n      <td>0.200202</td>\n      <td>0.220060</td>\n      <td>0.251265</td>\n      <td>84</td>\n      <td>0.021224</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>0.920817</td>\n      <td>450.322010</td>\n      <td>1.0</td>\n      <td>450.272929</td>\n      <td>13</td>\n      <td>11747.0</td>\n      <td>5.992708</td>\n      <td>1.617585e+02</td>\n      <td>5.274092</td>\n      <td>128.0</td>\n      <td>0.884703</td>\n      <td>0.945201</td>\n      <td>0.975450</td>\n      <td>306</td>\n      <td>0.024384</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>0.936900</td>\n      <td>472.303743</td>\n      <td>1.0</td>\n      <td>472.303258</td>\n      <td>14</td>\n      <td>3689.0</td>\n      <td>2284.025262</td>\n      <td>3.027051e+04</td>\n      <td>1725.037133</td>\n      <td>23722.0</td>\n      <td>0.889992</td>\n      <td>0.961692</td>\n      <td>1.057291</td>\n      <td>310</td>\n      <td>0.024792</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>0.212917</td>\n      <td>401.340957</td>\n      <td>1.0</td>\n      <td>401.341101</td>\n      <td>4</td>\n      <td>588.0</td>\n      <td>31472.678215</td>\n      <td>1.588007e+06</td>\n      <td>25057.052391</td>\n      <td>1263813.0</td>\n      <td>0.174182</td>\n      <td>0.188105</td>\n      <td>0.219432</td>\n      <td>76</td>\n      <td>0.024812</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>0.920817</td>\n      <td>450.322010</td>\n      <td>1.0</td>\n      <td>450.321087</td>\n      <td>13</td>\n      <td>1600.0</td>\n      <td>573.708013</td>\n      <td>7.991003e+03</td>\n      <td>435.958683</td>\n      <td>5953.0</td>\n      <td>0.885911</td>\n      <td>0.959291</td>\n      <td>1.056152</td>\n      <td>306</td>\n      <td>0.038474</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>0.271650</td>\n      <td>425.336854</td>\n      <td>1.0</td>\n      <td>425.368938</td>\n      <td>9</td>\n      <td>7263.0</td>\n      <td>74.094758</td>\n      <td>1.557165e+03</td>\n      <td>46.978708</td>\n      <td>880.0</td>\n      <td>0.163861</td>\n      <td>0.208442</td>\n      <td>0.282745</td>\n      <td>93</td>\n      <td>0.063208</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>0.898433</td>\n      <td>472.302746</td>\n      <td>1.0</td>\n      <td>472.303258</td>\n      <td>12</td>\n      <td>3689.0</td>\n      <td>2284.025262</td>\n      <td>3.027051e+04</td>\n      <td>1725.037133</td>\n      <td>23722.0</td>\n      <td>0.889992</td>\n      <td>0.961692</td>\n      <td>1.057291</td>\n      <td>300</td>\n      <td>0.063258</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1.196733</td>\n      <td>246.170474</td>\n      <td>1.0</td>\n      <td>246.206173</td>\n      <td>16</td>\n      <td>1705.0</td>\n      <td>204.892760</td>\n      <td>3.303564e+03</td>\n      <td>163.135383</td>\n      <td>2838.0</td>\n      <td>1.064172</td>\n      <td>1.106920</td>\n      <td>1.208445</td>\n      <td>395</td>\n      <td>0.089813</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features_mapped"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "outputs": [],
   "source": [
    "mass_list, int_list  = load_mzml_data(mzml_file, ifdebug=True)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [],
   "source": [
    "features_mapped[\"rt_offset\"] = abs(features_mapped[\"rt\"]-features_mapped[\"rt_apex\"])\n",
    "features_mapped.sort_values(by=[\"rt_offset\"], inplace=True)\n",
    "features_mapped_selected = features_mapped.drop_duplicates(subset=[\"feature_idx\"], keep=\"first\", inplace=False).copy()\n",
    "\n",
    "ms1_ppm = 20\n",
    "df_ms1_idx_next = np.searchsorted(ms_file[\"rt_list_ms1\"], features_mapped_selected[\"rt\"], side='left')\n",
    "df_ms1_idx_pre = np.where(df_ms1_idx_next > 0, df_ms1_idx_next-1, df_ms1_idx_next)\n",
    "df_ms1_rt_next = ms_file[\"rt_list_ms1\"][df_ms1_idx_next]\n",
    "df_ms1_rt_pre = ms_file[\"rt_list_ms1\"][df_ms1_idx_pre]\n",
    "df_ms1_idx = np.where(abs(features_mapped_selected[\"rt\"]-df_ms1_rt_next) < abs(features_mapped_selected[\"rt\"]-df_ms1_rt_pre),\n",
    "                                      df_ms1_idx_next, df_ms1_idx_pre)\n",
    "features_mapped_selected[\"ms1_idx\"] = df_ms1_idx"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "outputs": [],
   "source": [
    "ms2_selected = process_mzml_file(mzml_file)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "outputs": [
    {
     "data": {
      "text/plain": "    scan_number  precursor_mz  charge  ms1_intensity_ratio  retention_time  \\\n0           238    293.123856      -1             0.969618        0.540066   \n1           460    197.080885      -1             0.990194        1.029794   \n2           465    243.086620      -1             0.956398        1.038621   \n3           465    243.086620      -1             0.956398        1.038621   \n4          1085    185.117214      -1             0.977382        2.394052   \n5          1173    575.270161      -1             1.000000        2.571720   \n6          1278    901.239950      -1             0.995077        2.800668   \n7          1331    575.270240      -1             1.000000        2.888530   \n8          1333    529.264315      -1             0.987404        2.891299   \n9          1351    901.239782      -1             1.000000        2.922067   \n10         1600    401.123581      -1             0.993886        3.453756   \n11         1629    447.128813      -1             0.977909        3.511706   \n12         1631    401.123297      -1             0.994348        3.514753   \n13         1635    399.165070      -1             0.915519        3.520378   \n14         1737    399.165280      -1             0.968200        3.702673   \n15         2286    531.126634      -1             1.000000        4.832797   \n16         2409    263.128328      -1             0.959102        5.057898   \n17         2543    607.347929      -1             0.986787        5.273424   \n18         2553    561.342286      -1             1.000000        5.288419   \n19         2651    263.128418      -1             0.517569        5.438041   \n20         2677    485.218956      -1             0.964088        5.485260   \n21         2718    439.213074      -1             0.733741        5.553630   \n22         2740    717.239425      -1             0.985107        5.591855   \n\n                                                peaks  \n0   [[61.048378, 0.10726301], [87.92364, 0.1445572...  \n1   [[51.072353, 0.009219986], [53.002163, 0.01175...  \n2   [[54.126934, 0.022826573], [65.038055, 0.03455...  \n3   [[54.126934, 0.022826573], [65.038055, 0.03455...  \n4   [[53.72312, 0.0036466636], [63.656487, 0.00340...  \n5   [[52.898094, 0.073964685], [56.200596, 0.07922...  \n6   [[71.00753, 0.013150149], [145.02817, 0.009517...  \n7   [[59.012444, 0.28170097], [71.01235, 0.0600962...  \n8   [[58.004665, 0.005138994], [59.01245, 0.339829...  \n9   [[81.00671, 0.04058004], [86.36419, 0.0381839]...  \n10  [[58.920593, 0.021178715], [105.565605, 0.0235...  \n11  [[52.088776, 0.031078203], [53.177685, 0.03332...  \n12  [[73.201614, 0.0022110136], [83.033875, 0.0023...  \n13  [[67.91126, 0.044901498], [101.05891, 0.063883...  \n14  [[55.01745, 0.02343136], [59.012604, 0.0050966...  \n15  [[54.50091, 0.1307397], [55.87064, 0.15739432]...  \n16  [[54.78434, 0.017217001], [219.0789, 0.0114079...  \n17  [[59.01256, 0.9358835], [137.02614, 0.01059899...  \n18  [[59.012478, 0.9249525], [218.09305, 0.0212966...  \n19  [[61.984955, 0.043104276], [88.35825, 0.044019...  \n20  [[58.774345, 0.01889644], [60.31268, 0.0234256...  \n21  [[69.24537, 0.021119047], [76.60359, 0.0250524...  \n22  [[91.78018, 0.008650385], [298.0469, 0.0109973...  ",
      "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>scan_number</th>\n      <th>precursor_mz</th>\n      <th>charge</th>\n      <th>ms1_intensity_ratio</th>\n      <th>retention_time</th>\n      <th>peaks</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>238</td>\n      <td>293.123856</td>\n      <td>-1</td>\n      <td>0.969618</td>\n      <td>0.540066</td>\n      <td>[[61.048378, 0.10726301], [87.92364, 0.1445572...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>460</td>\n      <td>197.080885</td>\n      <td>-1</td>\n      <td>0.990194</td>\n      <td>1.029794</td>\n      <td>[[51.072353, 0.009219986], [53.002163, 0.01175...</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956398</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>465</td>\n      <td>243.086620</td>\n      <td>-1</td>\n      <td>0.956398</td>\n      <td>1.038621</td>\n      <td>[[54.126934, 0.022826573], [65.038055, 0.03455...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1085</td>\n      <td>185.117214</td>\n      <td>-1</td>\n      <td>0.977382</td>\n      <td>2.394052</td>\n      <td>[[53.72312, 0.0036466636], [63.656487, 0.00340...</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>1173</td>\n      <td>575.270161</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.571720</td>\n      <td>[[52.898094, 0.073964685], [56.200596, 0.07922...</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>1278</td>\n      <td>901.239950</td>\n      <td>-1</td>\n      <td>0.995077</td>\n      <td>2.800668</td>\n      <td>[[71.00753, 0.013150149], [145.02817, 0.009517...</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>1331</td>\n      <td>575.270240</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.888530</td>\n      <td>[[59.012444, 0.28170097], [71.01235, 0.0600962...</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>1333</td>\n      <td>529.264315</td>\n      <td>-1</td>\n      <td>0.987404</td>\n      <td>2.891299</td>\n      <td>[[58.004665, 0.005138994], [59.01245, 0.339829...</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>1351</td>\n      <td>901.239782</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>2.922067</td>\n      <td>[[81.00671, 0.04058004], [86.36419, 0.0381839]...</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>1600</td>\n      <td>401.123581</td>\n      <td>-1</td>\n      <td>0.993886</td>\n      <td>3.453756</td>\n      <td>[[58.920593, 0.021178715], [105.565605, 0.0235...</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>1629</td>\n      <td>447.128813</td>\n      <td>-1</td>\n      <td>0.977909</td>\n      <td>3.511706</td>\n      <td>[[52.088776, 0.031078203], [53.177685, 0.03332...</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>1631</td>\n      <td>401.123297</td>\n      <td>-1</td>\n      <td>0.994348</td>\n      <td>3.514753</td>\n      <td>[[73.201614, 0.0022110136], [83.033875, 0.0023...</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1635</td>\n      <td>399.165070</td>\n      <td>-1</td>\n      <td>0.915519</td>\n      <td>3.520378</td>\n      <td>[[67.91126, 0.044901498], [101.05891, 0.063883...</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1737</td>\n      <td>399.165280</td>\n      <td>-1</td>\n      <td>0.968200</td>\n      <td>3.702673</td>\n      <td>[[55.01745, 0.02343136], [59.012604, 0.0050966...</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>2286</td>\n      <td>531.126634</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>4.832797</td>\n      <td>[[54.50091, 0.1307397], [55.87064, 0.15739432]...</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>2409</td>\n      <td>263.128328</td>\n      <td>-1</td>\n      <td>0.959102</td>\n      <td>5.057898</td>\n      <td>[[54.78434, 0.017217001], [219.0789, 0.0114079...</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>2543</td>\n      <td>607.347929</td>\n      <td>-1</td>\n      <td>0.986787</td>\n      <td>5.273424</td>\n      <td>[[59.01256, 0.9358835], [137.02614, 0.01059899...</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>2553</td>\n      <td>561.342286</td>\n      <td>-1</td>\n      <td>1.000000</td>\n      <td>5.288419</td>\n      <td>[[59.012478, 0.9249525], [218.09305, 0.0212966...</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>2651</td>\n      <td>263.128418</td>\n      <td>-1</td>\n      <td>0.517569</td>\n      <td>5.438041</td>\n      <td>[[61.984955, 0.043104276], [88.35825, 0.044019...</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>2677</td>\n      <td>485.218956</td>\n      <td>-1</td>\n      <td>0.964088</td>\n      <td>5.485260</td>\n      <td>[[58.774345, 0.01889644], [60.31268, 0.0234256...</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>2718</td>\n      <td>439.213074</td>\n      <td>-1</td>\n      <td>0.733741</td>\n      <td>5.553630</td>\n      <td>[[69.24537, 0.021119047], [76.60359, 0.0250524...</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>2740</td>\n      <td>717.239425</td>\n      <td>-1</td>\n      <td>0.985107</td>\n      <td>5.591855</td>\n      <td>[[91.78018, 0.008650385], [298.0469, 0.0109973...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms2_selected"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "outputs": [],
   "source": [
    "def msdial_eva(ms_dial_result, std_list):\n",
    "    picked = pd.DataFrame()\n",
    "    reference_name = []\n",
    "    for index, row in std_list.iterrows():\n",
    "        temp = search.num_search(ms_dial_result, \"Precursor m/z\", row['[M+H]+'], 'between', step =0.01, inclusion=True)\n",
    "        if len(temp)>0:\n",
    "            temp['reference_name']=row['Name']\n",
    "            picked = pd.concat([picked, temp], axis=0)\n",
    "    picked = picked[['reference_name','PeakID', 'RT (min)','Precursor m/z','MSMS spectrum']]\n",
    "    picked.dropna(subset=['MSMS spectrum'], inplace=True)\n",
    "    return(picked)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "outputs": [
    {
     "data": {
      "text/plain": "Index(['PeakID', 'Title', 'Scans', 'RT left(min)', 'RT (min)',\n       'RT right (min)', 'Precursor m/z', 'Height', 'Area', 'Model masses',\n       'Adduct', 'Isotope', 'Comment', 'Reference RT', 'Reference m/z',\n       'Formula', 'Ontology', 'InChIKey', 'SMILES', 'Annotation tag (VS1.0)',\n       'RT matched', 'm/z matched', 'MS/MS matched', 'RT similarity',\n       'Dot product', 'Reverse dot product', 'Fragment presence %',\n       'Total score', 'S/N', 'MS1 isotopes', 'MSMS spectrum',\n       'reference_name'],\n      dtype='object')"
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "picked_msdial.columns"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "70.76114511489868\n"
     ]
    }
   ],
   "source": [
    "\n",
    "def msdial_eva(ms_dial_result, std_list):\n",
    "    picked = pd.DataFrame()\n",
    "    reference_name = []\n",
    "    for index, row in std_list.iterrows():\n",
    "        temp = search.num_search(ms_dial_result, \"Precursor m/z\", row['[M+H]+'], 'between', step =0.01, inclusion=True)\n",
    "        if len(temp)>0:\n",
    "            temp['reference_name']=row['Name']\n",
    "            picked = pd.concat([picked, temp], axis=0)\n",
    "    picked = picked[['reference_name','PeakID', 'RT (min)','Precursor m/z','MSMS spectrum']]\n",
    "    return(picked)\n",
    "\n",
    "\n",
    "def alphapept_eva(ms2_selected_df, std_list):\n",
    "    picked = pd.DataFrame()\n",
    "    reference_name = []\n",
    "    for index, row in std_list.iterrows():\n",
    "        temp = search.num_search(ms2_selected_df, \"precursor_mz\", row['[M+H]+'], 'between', step =0.01, inclusion=True)\n",
    "        if len(temp)>0:\n",
    "            temp['reference_name']=row['Name']\n",
    "            picked = pd.concat([picked, temp], axis=0)\n",
    "    return(picked)\n",
    "def convert_msdial_to_string(msms):\n",
    "    return(msms.replace(' ', '\\n').replace(':', '\\t'))\n",
    "std_list = pd.read_csv(\"/Users/fanzhoukong/Documents/GitHub/Libgen_data/dipep/std_list_corrected.csv\")\n",
    "\n",
    "# path_to_msdial = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/dipep/ms_dial_result/Dipeptides-pos-G3.csv\"\n",
    "# path_to_msdial = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/dipep/ms_dial_result/Dipeptides-pos-G1.csv\"\n",
    "path_to_msdial = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/dipep/ms_dial_result/Dipeptides-pos-G2.csv\"\n",
    "filename_msdial= path_to_msdial.split(\"/\")[-1]\n",
    "mix_name = filename_msdial.split(\".\")[0]\n",
    "std_list_temp  =search.string_search(std_list, \"Mix label\", mix_name)\n",
    "# path_to_msdial = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/dipep/ms_dial_result/Dipeptides-pos-G1.csv\"\n",
    "ms_dial_result = pd.read_csv(path_to_msdial)\n",
    "picked_msdial = msdial_eva(ms_dial_result, std_list_temp)\n",
    "# path_to_mzml = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/dipep/dipeptide/Dipeptides-pos-G3.mzML\"\n",
    "path_to_mzml = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/dipep/dipeptide/Dipeptides-pos-G2.mzML\"\n",
    "\n",
    "# path_to_mzml = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/casmi/mzml/A_M5_posPFP_01.mzml\"\n",
    "# path_to_mzml = \"/Users/fanzhoukong/Documents/GitHub/Libgen_data/dipep/dipeptide/Dipeptides-pos-G1.mzML\"\n",
    "filename_mzml= path_to_mzml.split(\"/\")[-1]\n",
    "mix_name = filename_mzml.split(\".\")[0]\n",
    "start = time.time()\n",
    "ms2_selected = process_mzml_file(path_to_mzml)\n",
    "end = time.time()\n",
    "print(end-start)\n",
    "# raw = load_mzml_data(path_to_mzml)\n",
    "# picked_alphapept =alphapept_eva(ms2_selected_df, search.string_search(std_list, \"Mix label\", mix_name))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [],
   "source": [
    "picked_msdial = msdial_eva(ms_dial_result, std_list_temp)\n",
    "picked_alpha = alphapept_eva(ms2_selected, std_list_temp)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [],
   "source": [
    "simiarlity =[]\n",
    "for name in picked_alpha['reference_name'].unique():\n",
    "    alpha_temp = search.string_search(picked_alpha, \"reference_name\", name)\n",
    "    msdial_temp = search.string_search(picked_msdial, \"reference_name\", name)\n",
    "    if len(alpha_temp)==1 and len(msdial_temp)==1:\n",
    "        simiarlity.append(so.entropy_similarity_default(so.convert_nist_to_string(alpha_temp.iloc[0]['peaks']),convert_msdial_to_string(msdial_temp.iloc[0]['MSMS spectrum']))\n",
    "                          )"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "[0.79272486151663,\n 0.9492946237627955,\n 0.9733692663507344,\n 0.9581749089252862,\n 0.8227189686270303]"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simiarlity"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "outputs": [
    {
     "data": {
      "text/plain": "     reference_name PeakID  RT (min)  Precursor m/z  \\\n2           Ala-Pro   1954  1.986100       187.1065   \n1731        Ala-Pro   1722  1.864117       187.1104   \n1           Ala-Gln   2098  2.217750       218.1136   \n979         Ala-Gln    969  0.257567       218.1112   \n0           Ala-Arg   2207  2.414917       246.1555   \n3           Ala-Ser   2085  2.207083       177.0850   \n4           Ala-Thr   2048  2.119933       191.1030   \n7           Ala-Val   1723  1.864117       189.1217   \n5           Ala-Trp   1651  1.806117       276.1327   \n6           Ala-Tyr   1874  1.917450       253.1171   \n1511        Ala-Tyr   1501  1.494967       253.1234   \n8           Asp-Ala   2153  2.254267       205.0820   \n281         Asp-Ala    271  0.214567       205.0816   \n9           Asp-Asp   2200  2.399583       249.0700   \n\n                                          MSMS spectrum  \n2     42.03305:131 42.03578:66 42.03669:66 43.02413:...  \n1731  42.03485:14 43.02135:14 44.04909:16 44.05002:1...  \n1     41.04637:56 42.03218:66 42.03582:66 43.91421:6...  \n979   41.03909:14 42.03938:14 43.01489:16 43.01581:1...  \n0     43.01769:56 44.04725:66 44.04818:66 44.04911:6...  \n3     42.03218:16 42.03309:33 42.034:16 42.03491:16 ...  \n4     42.03308:33 42.03581:33 42.03945:33 43.0435:28...  \n7     41.02743:56 42.0303:66 42.03121:66 42.03212:66...  \n5     41.03736:11 42.03398:11 43.01679:13 43.01863:1...  \n6     42.034:44 43.91235:22 43.91793:22 43.92723:22 ...  \n1511  42.03391:26 42.03755:26 45.30214:11 46.06375:1...  \n8     41.03557:13 41.03737:26 41.03827:39 41.03917:1...  \n281   45.03242:11 55.05302:11 57.06711:11 59.05266:1...  \n9     43.01493:16 43.01677:33 43.01769:33 43.01861:3...  ",
      "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>reference_name</th>\n      <th>PeakID</th>\n      <th>RT (min)</th>\n      <th>Precursor m/z</th>\n      <th>MSMS spectrum</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2</th>\n      <td>Ala-Pro</td>\n      <td>1954</td>\n      <td>1.986100</td>\n      <td>187.1065</td>\n      <td>42.03305:131 42.03578:66 42.03669:66 43.02413:...</td>\n    </tr>\n    <tr>\n      <th>1731</th>\n      <td>Ala-Pro</td>\n      <td>1722</td>\n      <td>1.864117</td>\n      <td>187.1104</td>\n      <td>42.03485:14 43.02135:14 44.04909:16 44.05002:1...</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Ala-Gln</td>\n      <td>2098</td>\n      <td>2.217750</td>\n      <td>218.1136</td>\n      <td>41.04637:56 42.03218:66 42.03582:66 43.91421:6...</td>\n    </tr>\n    <tr>\n      <th>979</th>\n      <td>Ala-Gln</td>\n      <td>969</td>\n      <td>0.257567</td>\n      <td>218.1112</td>\n      <td>41.03909:14 42.03938:14 43.01489:16 43.01581:1...</td>\n    </tr>\n    <tr>\n      <th>0</th>\n      <td>Ala-Arg</td>\n      <td>2207</td>\n      <td>2.414917</td>\n      <td>246.1555</td>\n      <td>43.01769:56 44.04725:66 44.04818:66 44.04911:6...</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Ala-Ser</td>\n      <td>2085</td>\n      <td>2.207083</td>\n      <td>177.0850</td>\n      <td>42.03218:16 42.03309:33 42.034:16 42.03491:16 ...</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Ala-Thr</td>\n      <td>2048</td>\n      <td>2.119933</td>\n      <td>191.1030</td>\n      <td>42.03308:33 42.03581:33 42.03945:33 43.0435:28...</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Ala-Val</td>\n      <td>1723</td>\n      <td>1.864117</td>\n      <td>189.1217</td>\n      <td>41.02743:56 42.0303:66 42.03121:66 42.03212:66...</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Ala-Trp</td>\n      <td>1651</td>\n      <td>1.806117</td>\n      <td>276.1327</td>\n      <td>41.03736:11 42.03398:11 43.01679:13 43.01863:1...</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Ala-Tyr</td>\n      <td>1874</td>\n      <td>1.917450</td>\n      <td>253.1171</td>\n      <td>42.034:44 43.91235:22 43.91793:22 43.92723:22 ...</td>\n    </tr>\n    <tr>\n      <th>1511</th>\n      <td>Ala-Tyr</td>\n      <td>1501</td>\n      <td>1.494967</td>\n      <td>253.1234</td>\n      <td>42.03391:26 42.03755:26 45.30214:11 46.06375:1...</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Asp-Ala</td>\n      <td>2153</td>\n      <td>2.254267</td>\n      <td>205.0820</td>\n      <td>41.03557:13 41.03737:26 41.03827:39 41.03917:1...</td>\n    </tr>\n    <tr>\n      <th>281</th>\n      <td>Asp-Ala</td>\n      <td>271</td>\n      <td>0.214567</td>\n      <td>205.0816</td>\n      <td>45.03242:11 55.05302:11 57.06711:11 59.05266:1...</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Asp-Asp</td>\n      <td>2200</td>\n      <td>2.399583</td>\n      <td>249.0700</td>\n      <td>43.01493:16 43.01677:33 43.01769:33 43.01861:3...</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "convert_msdial_to_string(picked_msdial.iloc[])"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
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  "kernelspec": {
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