HackingStructBiology.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hacking Structural Biology with Python and Pandas\n",
    "### by Chris Ing, 2015, https://github.com/cing/HackingStructBiolTalk (reduced dataset version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "$(\"head\").append($(\"<link/>\").attr({\n",
       "  rel:  \"stylesheet\",\n",
       "  type: \"text/css\",\n",
       "  href: \"//lab.jakiestfu.com/contextjs/context.standalone.css\"\n",
       "}));\n",
       "\n",
       "require.config({\n",
       "    paths: {\n",
       "        'three': '//cdnjs.cloudflare.com/ajax/libs/three.js/r68/three.min',\n",
       "        'iview' : '/nbextensions/mdtraj/iview',\n",
       "        'surface' : '/nbextensions/mdtraj/surface.min',\n",
       "        'objexporter' : '/nbextensions/mdtraj/objexporter',\n",
       "        'filesaver' : '/nbextensions/mdtraj/filesaver',\n",
       "        'jqueryui': '//ajax.googleapis.com/ajax/libs/jqueryui/1.11.1/jquery-ui.min',\n",
       "        'contextmenu': '/nbextensions/mdtraj/context',\n",
       "    },\n",
       "    shim: {\n",
       "        three: {\n",
       "            exports: 'THREE'\n",
       "        },\n",
       "        iview: {\n",
       "            deps: ['three', 'surface'],\n",
       "            exports: 'iview'\n",
       "        },\n",
       "        surface: {\n",
       "            exports: 'ProteinSurface'\n",
       "        },\n",
       "        objexporter: {\n",
       "            deps: ['three'],\n",
       "            exports: 'THREE.OBJExporter'\n",
       "        },\n",
       "        jqueryui: {\n",
       "            exports: \"$\"\n",
       "        },\n",
       "        contextmenu: {\n",
       "            deps: ['jquery'],\n",
       "            exports: \"context\"\n",
       "        },\n",
       "    },\n",
       "});\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from __future__ import print_function\n",
    "import time\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams.update({'font.size': 22})\n",
    "\n",
    "import mdtraj as md\n",
    "from mdtraj.html import TrajectoryView, enable_notebook\n",
    "\n",
    "enable_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# RGB colors used for plotting later on!\n",
    "mode_color_dict = {'CC': (0.24309112394557281, 0.55515571552164411, 0.58454442129415629, 1.0),\n",
    " 'E': (1.0, 0.50591311045721465, 0.0031372549487095253, 1.0),\n",
    " 'EC': (0.89411765336990356, 0.10196078568696976, 0.10980392247438431, 1.0),\n",
    " 'EL': (0.88366013765335083, 0.77908497055371606, 0.18562091886997223, 1.0),\n",
    " 'LT': (0.86772780488519108, 0.45231836227809685, 0.5609227340011036, 1.0),\n",
    " 'NONE': (0.60000002384185791, 0.60000002384185791, 0.60000002384185791, 1.0),\n",
    " 'S': (0.49803923567136127, 0.43267975250879925, 0.52287583549817396, 1.0)}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* * *\n",
    "\n",
    "### 1)  What are proteins and what is structural biology?\n",
    "\n",
    "\n",
    "|  ![Protein Sequence in DNA](assets/LysozymeSequence.png) | ![Protein Structure](assets/LysozymeStructure.gif) | ![Protein Strucure with Sugar](assets/LysozymeRock.gif) |\n",
    "|:-:|:-:|:-:|\n",
    "|  Sequence | Structure | Function  |\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2) How do we do molecular dynamics?\n",
    "\n",
    "|  ![Building Molecular Models](assets/MDpdb.png) | ![Molecular Dynamics Force Fields](assets/MDforcefield.png) | ![Dog-Based Billiards Simulations](assets/MDsimulate.gif) |\n",
    "|:-:|:-:|:-:|\n",
    "| Build Molecular Model  | Define Parameters and Interactions | Simulation  |\n",
    "\n",
    "* * *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Building a molecular model\n",
    "from pdbfixer import PDBFixer\n",
    "from simtk.openmm.app import PDBFile\n",
    "\n",
    "fixer = PDBFixer(url=\"http://www.rcsb.org/pdb/files/3WVY.pdb\")\n",
    "fixer.findMissingResidues()\n",
    "fixer.findMissingAtoms()\n",
    "fixer.addMissingAtoms()\n",
    "fixer.removeHeterogens(False)\n",
    "fixer.addMissingHydrogens(7.0)\n",
    "PDBFile.writeFile(fixer.topology, fixer.positions,\n",
    "                  open('assets/3WVY_simulation.pdb', 'w'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#\"Progress (%)\"\t\"Step\"\t\"Temperature (K)\"\t\"Speed (ns/day)\"\t\"Time Remaining\"\n",
      "3.3%\t250\t223.750720342\t0\t--\n",
      "6.7%\t500\t251.312229415\t44.1\t0:27\n",
      "10.0%\t750\t274.548497163\t44.6\t0:26\n",
      "13.3%\t1000\t278.167108353\t44.2\t0:25\n",
      "16.7%\t1250\t282.952007316\t44.4\t0:24\n",
      "20.0%\t1500\t299.009790356\t44.3\t0:23\n",
      "23.3%\t1750\t296.151914463\t44.5\t0:22\n",
      "26.7%\t2000\t300.337820208\t44.5\t0:21\n",
      "30.0%\t2250\t300.431680216\t44.4\t0:20\n",
      "33.3%\t2500\t307.332308314\t44.4\t0:19\n",
      "36.7%\t2750\t301.587510278\t44.6\t0:18\n",
      "40.0%\t3000\t302.738097112\t44.6\t0:17\n",
      "43.3%\t3250\t297.181873233\t44.7\t0:16\n",
      "46.7%\t3500\t297.490553308\t44.7\t0:15\n",
      "50.0%\t3750\t301.58296237\t44.8\t0:14\n",
      "53.3%\t4000\t317.612161711\t44.8\t0:13\n",
      "56.7%\t4250\t301.61238856\t44.8\t0:12\n",
      "60.0%\t4500\t318.335221377\t44.8\t0:11\n",
      "63.3%\t4750\t302.334985014\t44.9\t0:10\n",
      "66.7%\t5000\t298.462579908\t44.9\t0:09\n",
      "70.0%\t5250\t298.015967148\t44.9\t0:08\n",
      "73.3%\t5500\t305.097821032\t44.9\t0:07\n",
      "76.7%\t5750\t313.194769668\t44.9\t0:06\n",
      "80.0%\t6000\t326.225738762\t44.9\t0:05\n",
      "83.3%\t6250\t317.691217746\t44.9\t0:04\n",
      "86.7%\t6500\t312.928771406\t44.9\t0:03\n",
      "90.0%\t6750\t305.877736116\t45\t0:02\n",
      "93.3%\t7000\t315.647018421\t45\t0:01\n",
      "96.7%\t7250\t313.936262106\t45\t0:00\n",
      "100.0%\t7500\t304.87761895\t45\t0:00\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "from simtk.openmm import app\n",
    "import simtk.openmm as mm\n",
    "from simtk import unit\n",
    "from sys import stdout\n",
    "\n",
    "# Load protein structure and force field\n",
    "pdb = app.PDBFile('assets/3WVY_simulation.pdb')\n",
    "forcefield = app.ForceField('amber99sbildn.xml', 'amber99_obc.xml')\n",
    "\n",
    "# Define system and integrator\n",
    "system = forcefield.createSystem(pdb.topology, \n",
    "                                 nonbondedMethod=app.CutoffNonPeriodic,\n",
    "                                 nonbondedCutoff=1.0*unit.nanometers,\n",
    "                                 constraints=app.HBonds)\n",
    "integrator = mm.LangevinIntegrator(300*unit.kelvin,\n",
    "                                   1.0/unit.picoseconds, \n",
    "                                   2.0*unit.femtoseconds)\n",
    "integrator.setConstraintTolerance(0.00001)\n",
    "\n",
    "# Select compute platform and energy minimize\n",
    "platform = mm.Platform.getPlatformByName('OpenCL')\n",
    "simulation = app.Simulation(pdb.topology, system, integrator, platform)\n",
    "simulation.context.setPositions(pdb.positions)\n",
    "simulation.minimizeEnergy()\n",
    "\n",
    "# Set initial velocities and output logging\n",
    "simulation.context.setVelocitiesToTemperature(300*unit.kelvin)\n",
    "simulation.reporters.append(app.DCDReporter('assets/3WVY_trajectory.dcd', 100))\n",
    "simulation.reporters.append(app.StateDataReporter(stdout, 250, step=True, \n",
    "    temperature=True, progress=True, remainingTime=True, \n",
    "    speed=True, totalSteps=7500, separator='\\t'))\n",
    "\n",
    "# Execute molecular dynamics simulation\n",
    "simulation.step(7500)\n",
    "print(\"Done!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3) What does molecular dynamics look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "lysozyme_traj = md.load(\"assets/3WVY_trajectory.dcd\",\n",
    "                        top=\"assets/3WVY_simulation.pdb\")\n",
    "\n",
    "#widget = TrajectoryView(lysozyme_traj, primaryStructure=\"sphere\")\n",
    "widget = TrajectoryView(lysozyme_traj, secondaryStructure=\"ribbon\")\n",
    "widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for i in range(lysozyme_traj.n_frames):\n",
    "    widget.frame = i\n",
    "    time.sleep(0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Protein is rendered here with ipywidget)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(74, 1958, 3)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lysozyme_traj.xyz.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* * *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4) What are ion channels?\n",
    "\n",
    "|  ![Brain Contains Neurons](assets/Synapse.gif) | ![Neurons Contain Ion Channels](assets/Synapse2.gif) |\n",
    "|:-:|:-:|\n",
    "|  Neuron in the brain  | Ions flow through proteins in the cell membrane |\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### 5) Building a molecular model of the sodium channel\n",
    "\n",
    "![Molecular Model of Sodium Channel](assets/NavAbSystemIsometric.gif)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6) A few months of molecular dynamics later..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "channel_traj = md.load(\"assets/prod_7_view.xtc\",\n",
    "                       top=\"assets/na_prod_view.gro\")\n",
    "widget2 = TrajectoryView(channel_traj, secondaryStructure=\"ribbon\")\n",
    "widget2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Protein is rendered here with ipywidget)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for i in range(channel_traj.n_frames)[0:100]:\n",
    "    widget2.frame = i\n",
    "    time.sleep(0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7) Extract ions within the channel\n",
    "\n",
    "![Reducing Dataset Complexity for Studies of Ion Channels](assets/NavAbSideViewRawData.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(501, 3)\n",
      "[ 3.9476254   3.95237541  3.96187544]\n"
     ]
    }
   ],
   "source": [
    "# Get the indices of eight atoms\n",
    "ref_residues = ['residue 175','residue 617', 'residue 396', 'residue 838',\n",
    "                'residue 178', 'residue 620', 'residue 399', 'residue 841']\n",
    "ref_indices = channel_traj.topology.select(\"name CA and (\"+\" or \".join(ref_residues)+\")\")\n",
    "\n",
    "# Extract the positions of all indices and take the mean\n",
    "ref_xyz = channel_traj.xyz[:,ref_indices,:].mean(axis=1)\n",
    "\n",
    "print(ref_xyz.shape)\n",
    "print(ref_xyz[0,:]) # This is the zeroth frames X,Y,Z center of mass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(47, 501)\n",
      "[[False False False ..., False False False]\n",
      " [False False False ...,  True False False]\n",
      " [False False False ..., False False False]\n",
      " ..., \n",
      " [False False False ..., False False False]\n",
      " [False False False ..., False False False]\n",
      " [False False False ..., False False False]]\n"
     ]
    }
   ],
   "source": [
    "# Get a timeseries of all ions and subtract the reference point\n",
    "ion_indices = channel_traj.topology.select(\"name NA\")\n",
    "\n",
    "# Subtract the reference point (swapaxes is needed for broadcast)\n",
    "ion_xyz = channel_traj.xyz[:,ion_indices,:].swapaxes(0,1) - ref_xyz\n",
    "\n",
    "# Do a boolean check to determine which ions are within the cylinder of radius 1.0\n",
    "ion_xyz2 = ion_xyz**2\n",
    "inside_cylinder = (ion_xyz2[:,:,0]+ion_xyz2[:,:,1]) < 1.0**2\n",
    "\n",
    "print(inside_cylinder.shape)\n",
    "print(inside_cylinder)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(1, 293), (1, 297), (1, 310), (1, 338), (1, 349), (1, 470), (1, 491), (1, 498), (2, 26), (2, 83), (2, 199), (2, 225), (2, 232), (2, 265), (2, 270), (2, 299), (2, 314), (2, 316), (2, 341), (2, 364)]\n"
     ]
    }
   ],
   "source": [
    "# Extract the unique ID for each ion\n",
    "ion_index, time_index = np.where(inside_cylinder)\n",
    "print(zip(ion_index, time_index)[30:50])\n",
    "\n",
    "ion_index_in_whole_system = ion_indices[ion_index]\n",
    "resids = [channel_traj.topology.atom(i).residue.resSeq for i in ion_index_in_whole_system]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8) Construct a dataframe with ion positions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>ResidID</th>\n",
       "      <th>Frame</th>\n",
       "      <th>Time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.013747</td>\n",
       "      <td>0.206249</td>\n",
       "      <td>1.191249</td>\n",
       "      <td>12051</td>\n",
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       "      <td>1.331248</td>\n",
       "      <td>12051</td>\n",
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       "      <th>16</th>\n",
       "      <td>0.149996</td>\n",
       "      <td>0.017498</td>\n",
       "      <td>1.331248</td>\n",
       "      <td>12051</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
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       "      <th>18</th>\n",
       "      <td>0.194998</td>\n",
       "      <td>0.166249</td>\n",
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       "      <td>12051</td>\n",
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       "      <td>10</td>\n",
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       "      <th>21</th>\n",
       "      <td>0.075002</td>\n",
       "      <td>0.102501</td>\n",
       "      <td>1.017499</td>\n",
       "      <td>12051</td>\n",
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       "      <td>12</td>\n",
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       "      <th>23</th>\n",
       "      <td>-0.368750</td>\n",
       "      <td>0.381250</td>\n",
       "      <td>1.408751</td>\n",
       "      <td>12051</td>\n",
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       "      <th>26</th>\n",
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       "      <td>0.193748</td>\n",
       "      <td>6.633751</td>\n",
       "      <td>12036</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
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       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.086250</td>\n",
       "      <td>0.293751</td>\n",
       "      <td>1.323752</td>\n",
       "      <td>12051</td>\n",
       "      <td>10</td>\n",
       "      <td>18</td>\n",
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       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-0.767500</td>\n",
       "      <td>-1.571250</td>\n",
       "      <td>7.193749</td>\n",
       "      <td>12036</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
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       "      <th>32</th>\n",
       "      <td>0.512502</td>\n",
       "      <td>0.028751</td>\n",
       "      <td>1.233747</td>\n",
       "      <td>12051</td>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>-1.289997</td>\n",
       "      <td>-1.037498</td>\n",
       "      <td>7.060001</td>\n",
       "      <td>12036</td>\n",
       "      <td>12</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.470004</td>\n",
       "      <td>-0.207498</td>\n",
       "      <td>1.280000</td>\n",
       "      <td>12051</td>\n",
       "      <td>12</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.188746</td>\n",
       "      <td>0.287497</td>\n",
       "      <td>1.158750</td>\n",
       "      <td>12051</td>\n",
       "      <td>13</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>-1.141253</td>\n",
       "      <td>-1.152503</td>\n",
       "      <td>7.068753</td>\n",
       "      <td>12036</td>\n",
       "      <td>13</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>-0.476253</td>\n",
       "      <td>0.056250</td>\n",
       "      <td>-1.912501</td>\n",
       "      <td>12051</td>\n",
       "      <td>14</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>-1.148748</td>\n",
       "      <td>1.294999</td>\n",
       "      <td>7.235003</td>\n",
       "      <td>12065</td>\n",
       "      <td>15</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.401249</td>\n",
       "      <td>-0.014999</td>\n",
       "      <td>1.525002</td>\n",
       "      <td>12051</td>\n",
       "      <td>15</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>-0.024998</td>\n",
       "      <td>0.236251</td>\n",
       "      <td>1.292500</td>\n",
       "      <td>12051</td>\n",
       "      <td>16</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2.444999</td>\n",
       "      <td>2.556252</td>\n",
       "      <td>6.402500</td>\n",
       "      <td>12065</td>\n",
       "      <td>16</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>0.647500</td>\n",
       "      <td>-0.557499</td>\n",
       "      <td>8.058748</td>\n",
       "      <td>12065</td>\n",
       "      <td>17</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>0.337498</td>\n",
       "      <td>-0.167499</td>\n",
       "      <td>1.348748</td>\n",
       "      <td>12051</td>\n",
       "      <td>17</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.083747</td>\n",
       "      <td>0.161247</td>\n",
       "      <td>1.243749</td>\n",
       "      <td>12051</td>\n",
       "      <td>18</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>0.191250</td>\n",
       "      <td>0.296252</td>\n",
       "      <td>1.406250</td>\n",
       "      <td>12051</td>\n",
       "      <td>19</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>0.613754</td>\n",
       "      <td>-0.156252</td>\n",
       "      <td>1.122501</td>\n",
       "      <td>12051</td>\n",
       "      <td>20</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>0.062499</td>\n",
       "      <td>-0.182500</td>\n",
       "      <td>1.368747</td>\n",
       "      <td>12051</td>\n",
       "      <td>21</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>0.208752</td>\n",
       "      <td>-0.053749</td>\n",
       "      <td>1.037500</td>\n",
       "      <td>12051</td>\n",
       "      <td>22</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>-0.395000</td>\n",
       "      <td>0.023749</td>\n",
       "      <td>2.146254</td>\n",
       "      <td>12044</td>\n",
       "      <td>23</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1960</th>\n",
       "      <td>1.109998</td>\n",
       "      <td>-0.619998</td>\n",
       "      <td>-1.025000</td>\n",
       "      <td>12044</td>\n",
       "      <td>491</td>\n",
       "      <td>980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1962</th>\n",
       "      <td>1.217499</td>\n",
       "      <td>-0.861249</td>\n",
       "      <td>-0.293751</td>\n",
       "      <td>12044</td>\n",
       "      <td>492</td>\n",
       "      <td>982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1963</th>\n",
       "      <td>-1.402500</td>\n",
       "      <td>0.458751</td>\n",
       "      <td>3.836253</td>\n",
       "      <td>12024</td>\n",
       "      <td>492</td>\n",
       "      <td>982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1966</th>\n",
       "      <td>-1.412501</td>\n",
       "      <td>-0.571251</td>\n",
       "      <td>-9.103751</td>\n",
       "      <td>12051</td>\n",
       "      <td>492</td>\n",
       "      <td>982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1967</th>\n",
       "      <td>-0.088751</td>\n",
       "      <td>-1.796246</td>\n",
       "      <td>-6.726253</td>\n",
       "      <td>12051</td>\n",
       "      <td>493</td>\n",
       "      <td>984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1968</th>\n",
       "      <td>0.331249</td>\n",
       "      <td>-1.306248</td>\n",
       "      <td>-1.106253</td>\n",
       "      <td>12044</td>\n",
       "      <td>493</td>\n",
       "      <td>984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1969</th>\n",
       "      <td>-1.318750</td>\n",
       "      <td>1.183753</td>\n",
       "      <td>3.693748</td>\n",
       "      <td>12024</td>\n",
       "      <td>493</td>\n",
       "      <td>984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1974</th>\n",
       "      <td>-0.103750</td>\n",
       "      <td>1.777501</td>\n",
       "      <td>5.877500</td>\n",
       "      <td>12024</td>\n",
       "      <td>494</td>\n",
       "      <td>986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>-0.063751</td>\n",
       "      <td>1.177502</td>\n",
       "      <td>-1.492500</td>\n",
       "      <td>12044</td>\n",
       "      <td>494</td>\n",
       "      <td>986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>2.276249</td>\n",
       "      <td>-4.082499</td>\n",
       "      <td>-7.012498</td>\n",
       "      <td>12051</td>\n",
       "      <td>494</td>\n",
       "      <td>986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1979</th>\n",
       "      <td>-0.203753</td>\n",
       "      <td>2.056255</td>\n",
       "      <td>6.171250</td>\n",
       "      <td>12024</td>\n",
       "      <td>495</td>\n",
       "      <td>988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>-0.223751</td>\n",
       "      <td>1.246252</td>\n",
       "      <td>-1.618750</td>\n",
       "      <td>12044</td>\n",
       "      <td>495</td>\n",
       "      <td>988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>-1.483753</td>\n",
       "      <td>-4.213748</td>\n",
       "      <td>-8.588751</td>\n",
       "      <td>12051</td>\n",
       "      <td>495</td>\n",
       "      <td>988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>0.495002</td>\n",
       "      <td>-0.611258</td>\n",
       "      <td>-2.477500</td>\n",
       "      <td>12044</td>\n",
       "      <td>496</td>\n",
       "      <td>990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>1.665003</td>\n",
       "      <td>-1.561255</td>\n",
       "      <td>7.272501</td>\n",
       "      <td>12024</td>\n",
       "      <td>496</td>\n",
       "      <td>990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>-0.385001</td>\n",
       "      <td>-0.449996</td>\n",
       "      <td>-4.167497</td>\n",
       "      <td>12044</td>\n",
       "      <td>497</td>\n",
       "      <td>992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>-0.745001</td>\n",
       "      <td>-0.839996</td>\n",
       "      <td>2.912502</td>\n",
       "      <td>12024</td>\n",
       "      <td>497</td>\n",
       "      <td>992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>5.715001</td>\n",
       "      <td>-3.419995</td>\n",
       "      <td>-8.987498</td>\n",
       "      <td>12051</td>\n",
       "      <td>497</td>\n",
       "      <td>992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>-0.501249</td>\n",
       "      <td>-0.361257</td>\n",
       "      <td>4.698753</td>\n",
       "      <td>12024</td>\n",
       "      <td>498</td>\n",
       "      <td>994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>0.498753</td>\n",
       "      <td>-0.501256</td>\n",
       "      <td>-2.811248</td>\n",
       "      <td>12044</td>\n",
       "      <td>498</td>\n",
       "      <td>994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>1.008751</td>\n",
       "      <td>0.388746</td>\n",
       "      <td>-8.971248</td>\n",
       "      <td>12051</td>\n",
       "      <td>498</td>\n",
       "      <td>994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>-0.626252</td>\n",
       "      <td>-1.028752</td>\n",
       "      <td>-5.027499</td>\n",
       "      <td>12051</td>\n",
       "      <td>499</td>\n",
       "      <td>996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>1.313748</td>\n",
       "      <td>0.461245</td>\n",
       "      <td>-0.937500</td>\n",
       "      <td>12044</td>\n",
       "      <td>499</td>\n",
       "      <td>996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>0.253749</td>\n",
       "      <td>-0.088754</td>\n",
       "      <td>5.882502</td>\n",
       "      <td>12024</td>\n",
       "      <td>499</td>\n",
       "      <td>996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>-0.458748</td>\n",
       "      <td>-0.624995</td>\n",
       "      <td>2.537503</td>\n",
       "      <td>12024</td>\n",
       "      <td>500</td>\n",
       "      <td>998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>0.281250</td>\n",
       "      <td>-0.534997</td>\n",
       "      <td>-3.852499</td>\n",
       "      <td>12044</td>\n",
       "      <td>500</td>\n",
       "      <td>998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>0.241251</td>\n",
       "      <td>2.085004</td>\n",
       "      <td>5.767503</td>\n",
       "      <td>12049</td>\n",
       "      <td>500</td>\n",
       "      <td>998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>-0.913751</td>\n",
       "      <td>2.033749</td>\n",
       "      <td>7.066252</td>\n",
       "      <td>12049</td>\n",
       "      <td>501</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>0.106249</td>\n",
       "      <td>-0.726252</td>\n",
       "      <td>-3.883748</td>\n",
       "      <td>12044</td>\n",
       "      <td>501</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>0.496249</td>\n",
       "      <td>1.083751</td>\n",
       "      <td>2.456253</td>\n",
       "      <td>12024</td>\n",
       "      <td>501</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1093 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             X         Y         Z  ResidID  Frame  Time\n",
       "2     0.013747  0.206249  1.191249    12051      1     0\n",
       "4     0.433745 -0.001249  1.331248    12051      2     2\n",
       "7     0.313749 -0.033751  1.747499    12051      3     4\n",
       "10    0.331249  0.117500  1.617501    12051      4     6\n",
       "16    0.149996  0.017498  1.331248    12051      5     8\n",
       "18    0.194998  0.166249  1.060004    12051      6    10\n",
       "21    0.075002  0.102501  1.017499    12051      7    12\n",
       "23   -0.368750  0.381250  1.408751    12051      8    14\n",
       "25    0.286250  0.048752  1.546249    12051      9    16\n",
       "26    1.526248  0.193748  6.633751    12036     10    18\n",
       "27    0.086250  0.293751  1.323752    12051     10    18\n",
       "28   -0.767500 -1.571250  7.193749    12036     11    20\n",
       "32    0.512502  0.028751  1.233747    12051     11    20\n",
       "33   -1.289997 -1.037498  7.060001    12036     12    22\n",
       "34    0.470004 -0.207498  1.280000    12051     12    22\n",
       "38    0.188746  0.287497  1.158750    12051     13    24\n",
       "41   -1.141253 -1.152503  7.068753    12036     13    24\n",
       "43   -0.476253  0.056250 -1.912501    12051     14    26\n",
       "46   -1.148748  1.294999  7.235003    12065     15    28\n",
       "47    0.401249 -0.014999  1.525002    12051     15    28\n",
       "49   -0.024998  0.236251  1.292500    12051     16    30\n",
       "50    2.444999  2.556252  6.402500    12065     16    30\n",
       "52    0.647500 -0.557499  8.058748    12065     17    32\n",
       "53    0.337498 -0.167499  1.348748    12051     17    32\n",
       "57    0.083747  0.161247  1.243749    12051     18    34\n",
       "61    0.191250  0.296252  1.406250    12051     19    36\n",
       "63    0.613754 -0.156252  1.122501    12051     20    38\n",
       "67    0.062499 -0.182500  1.368747    12051     21    40\n",
       "68    0.208752 -0.053749  1.037500    12051     22    42\n",
       "70   -0.395000  0.023749  2.146254    12044     23    44\n",
       "...        ...       ...       ...      ...    ...   ...\n",
       "1960  1.109998 -0.619998 -1.025000    12044    491   980\n",
       "1962  1.217499 -0.861249 -0.293751    12044    492   982\n",
       "1963 -1.402500  0.458751  3.836253    12024    492   982\n",
       "1966 -1.412501 -0.571251 -9.103751    12051    492   982\n",
       "1967 -0.088751 -1.796246 -6.726253    12051    493   984\n",
       "1968  0.331249 -1.306248 -1.106253    12044    493   984\n",
       "1969 -1.318750  1.183753  3.693748    12024    493   984\n",
       "1974 -0.103750  1.777501  5.877500    12024    494   986\n",
       "1975 -0.063751  1.177502 -1.492500    12044    494   986\n",
       "1976  2.276249 -4.082499 -7.012498    12051    494   986\n",
       "1979 -0.203753  2.056255  6.171250    12024    495   988\n",
       "1981 -0.223751  1.246252 -1.618750    12044    495   988\n",
       "1983 -1.483753 -4.213748 -8.588751    12051    495   988\n",
       "1985  0.495002 -0.611258 -2.477500    12044    496   990\n",
       "1986  1.665003 -1.561255  7.272501    12024    496   990\n",
       "1988 -0.385001 -0.449996 -4.167497    12044    497   992\n",
       "1990 -0.745001 -0.839996  2.912502    12024    497   992\n",
       "1991  5.715001 -3.419995 -8.987498    12051    497   992\n",
       "1992 -0.501249 -0.361257  4.698753    12024    498   994\n",
       "1993  0.498753 -0.501256 -2.811248    12044    498   994\n",
       "1994  1.008751  0.388746 -8.971248    12051    498   994\n",
       "1998 -0.626252 -1.028752 -5.027499    12051    499   996\n",
       "1999  1.313748  0.461245 -0.937500    12044    499   996\n",
       "2001  0.253749 -0.088754  5.882502    12024    499   996\n",
       "2004 -0.458748 -0.624995  2.537503    12024    500   998\n",
       "2005  0.281250 -0.534997 -3.852499    12044    500   998\n",
       "2007  0.241251  2.085004  5.767503    12049    500   998\n",
       "2008 -0.913751  2.033749  7.066252    12049    501  1000\n",
       "2009  0.106249 -0.726252 -3.883748    12044    501  1000\n",
       "2010  0.496249  1.083751  2.456253    12024    501  1000\n",
       "\n",
       "[1093 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Construct a dataframe with this positional data\n",
    "ion_positions_df = pd.DataFrame(ion_xyz[inside_cylinder]*10, columns=[\"X\",\"Y\",\"Z\"])\n",
    "ion_positions_df[\"ResidID\"] = resids\n",
    "ion_positions_df[\"Frame\"] = time_index+1\n",
    "ion_positions_df[\"Time\"] = (time_index)*2.0\n",
    "time_sorted_ions = ion_positions_df.sort_values(\"Frame\").reset_index(drop=True)\n",
    "time_sorted_ions[(time_sorted_ions[\"Z\"] > -10) & (time_sorted_ions[\"Z\"] < 10)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9) Load a dataframe with the full ion dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "coord_1st = pd.read_pickle(\"assets/NAVAB_XTAL_PD-NORES-0kcal-CHARMM_NONB_WT_SOD150_DEMO_COORD1ST.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Frame</th>\n",
       "      <th>Time</th>\n",
       "      <th>ResidID</th>\n",
       "      <th>X</th>\n",
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       "      <td>0.1300</td>\n",
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       "      <th>771491</th>\n",
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       "      <td>0.6812</td>\n",
       "      <td>-6.7262</td>\n",
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       "      <th>773818</th>\n",
       "      <td>5000</td>\n",
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       "      <th>773819</th>\n",
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       "      <td>-0.6025</td>\n",
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       "    <tr>\n",
       "      <th>776251</th>\n",
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       "    <tr>\n",
       "      <th>777768</th>\n",
       "      <td>6500</td>\n",
       "      <td>130</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.5275</td>\n",
       "      <td>-0.0462</td>\n",
       "      <td>-1.2338</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>777769</th>\n",
       "      <td>6500</td>\n",
       "      <td>130</td>\n",
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       "      <td>0.2025</td>\n",
       "      <td>-0.1762</td>\n",
       "      <td>5.0163</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>777770</th>\n",
       "      <td>6500</td>\n",
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       "      <td>1.6737</td>\n",
       "      <td>-3.6937</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>867657</th>\n",
       "      <td>45000</td>\n",
       "      <td>900</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.3900</td>\n",
       "      <td>-0.9300</td>\n",
       "      <td>10.8450</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>867658</th>\n",
       "      <td>45000</td>\n",
       "      <td>900</td>\n",
       "      <td>12039</td>\n",
       "      <td>0.6800</td>\n",
       "      <td>-1.0700</td>\n",
       "      <td>-5.1850</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>869158</th>\n",
       "      <td>45500</td>\n",
       "      <td>910</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.4463</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>-3.5925</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>869159</th>\n",
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       "      <td>-0.0600</td>\n",
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       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>870382</th>\n",
       "      <td>46000</td>\n",
       "      <td>920</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.7400</td>\n",
       "      <td>-0.2525</td>\n",
       "      <td>-2.8638</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>870383</th>\n",
       "      <td>46000</td>\n",
       "      <td>920</td>\n",
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       "      <td>-0.3825</td>\n",
       "      <td>3.9263</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>871416</th>\n",
       "      <td>46500</td>\n",
       "      <td>930</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>0.9237</td>\n",
       "      <td>-3.3013</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>871417</th>\n",
       "      <td>46500</td>\n",
       "      <td>930</td>\n",
       "      <td>12053</td>\n",
       "      <td>0.8113</td>\n",
       "      <td>-4.2562</td>\n",
       "      <td>-12.4713</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>871418</th>\n",
       "      <td>46500</td>\n",
       "      <td>930</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.2312</td>\n",
       "      <td>0.0238</td>\n",
       "      <td>3.7088</td>\n",
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       "    <tr>\n",
       "      <th>872463</th>\n",
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       "      <td>940</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.8313</td>\n",
       "      <td>0.2063</td>\n",
       "      <td>-3.3800</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>872464</th>\n",
       "      <td>47000</td>\n",
       "      <td>940</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.1513</td>\n",
       "      <td>-0.6738</td>\n",
       "      <td>3.0700</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>873493</th>\n",
       "      <td>47500</td>\n",
       "      <td>950</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.0388</td>\n",
       "      <td>-0.4488</td>\n",
       "      <td>-2.5588</td>\n",
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       "    <tr>\n",
       "      <th>873494</th>\n",
       "      <td>47500</td>\n",
       "      <td>950</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.4812</td>\n",
       "      <td>-0.6387</td>\n",
       "      <td>3.9612</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>874574</th>\n",
       "      <td>48000</td>\n",
       "      <td>960</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.5862</td>\n",
       "      <td>-0.5363</td>\n",
       "      <td>-2.7200</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>874575</th>\n",
       "      <td>48000</td>\n",
       "      <td>960</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.0162</td>\n",
       "      <td>-0.2962</td>\n",
       "      <td>3.2300</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875832</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>-0.5937</td>\n",
       "      <td>2.8688</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>875833</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>12024</td>\n",
       "      <td>0.7125</td>\n",
       "      <td>-1.0537</td>\n",
       "      <td>-5.1313</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875834</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>12028</td>\n",
       "      <td>5.7925</td>\n",
       "      <td>0.4463</td>\n",
       "      <td>-14.3013</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>875835</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>12051</td>\n",
       "      <td>2.0725</td>\n",
       "      <td>-3.8638</td>\n",
       "      <td>7.8588</td>\n",
       "      <td>7</td>\n",
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       "    <tr>\n",
       "      <th>877380</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>12048</td>\n",
       "      <td>-4.3000</td>\n",
       "      <td>5.4750</td>\n",
       "      <td>-12.6625</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877381</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.7900</td>\n",
       "      <td>-0.8050</td>\n",
       "      <td>1.2075</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877382</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>12024</td>\n",
       "      <td>-1.1400</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>-4.5625</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877383</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.9300</td>\n",
       "      <td>2.0950</td>\n",
       "      <td>10.9875</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878912</th>\n",
       "      <td>49500</td>\n",
       "      <td>990</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>-0.4750</td>\n",
       "      <td>2.4925</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878913</th>\n",
       "      <td>49500</td>\n",
       "      <td>990</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.6500</td>\n",
       "      <td>-2.1450</td>\n",
       "      <td>9.5125</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878914</th>\n",
       "      <td>49500</td>\n",
       "      <td>990</td>\n",
       "      <td>12024</td>\n",
       "      <td>1.5800</td>\n",
       "      <td>-0.8050</td>\n",
       "      <td>-7.4575</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880560</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.4237</td>\n",
       "      <td>-0.7300</td>\n",
       "      <td>4.0238</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880561</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>12024</td>\n",
       "      <td>0.6038</td>\n",
       "      <td>1.2900</td>\n",
       "      <td>-2.5563</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880562</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>12049</td>\n",
       "      <td>-0.1363</td>\n",
       "      <td>2.1500</td>\n",
       "      <td>-6.6363</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880563</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>12051</td>\n",
       "      <td>1.5437</td>\n",
       "      <td>-0.5900</td>\n",
       "      <td>10.2938</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Frame  Time  ResidID       X       Y        Z  TrajNum\n",
       "764793    500    10    12051 -0.1825  0.3075  -1.3900        7\n",
       "764794    500    10    12043 -0.4525  9.5175 -13.3700        7\n",
       "765561   1000    20    12036 -0.4013 -0.8813  -7.5663        7\n",
       "765562   1000    20    12051  0.2288  0.0088  -1.4563        7\n",
       "766581   1500    30    12051 -0.0525  0.2775  -1.3612        7\n",
       "766582   1500    30    12065  2.2375  2.6775  -6.2813        7\n",
       "767300   2000    40    12044  4.9838 -0.9163 -13.3287        7\n",
       "767301   2000    40    12051  0.1238  0.1538  -1.7688        7\n",
       "768216   2500    50    12044  0.6975 -0.5800  -2.2963        7\n",
       "768217   2500    50    12051 -0.3625 -0.0600   3.5538        7\n",
       "769235   3000    60    12044  0.3375 -0.2150  -1.1187        7\n",
       "769236   3000    60    12051 -0.1725 -1.1650   4.8712        7\n",
       "770416   3500    70    12044  0.0163 -0.2100  -1.8938        7\n",
       "770417   3500    70    12045  0.2363  0.1300  -8.7537        7\n",
       "770418   3500    70    12051  0.0862  0.3400   3.3062        7\n",
       "771491   4000    80    12044  0.2175 -0.0725  -2.2837        7\n",
       "771492   4000    80    12051  0.1775 -0.6425   3.8362        7\n",
       "772565   4500    90    12044  0.1400 -0.4488  -1.6163        7\n",
       "772566   4500    90    12051 -0.1400 -0.2888   3.4637        7\n",
       "772567   4500    90    12030  1.3400  0.6812  -6.7262        7\n",
       "773818   5000   100    12044 -0.0500 -0.1025  -1.2325        7\n",
       "773819   5000   100    12051 -0.1500 -0.5425   5.4575        7\n",
       "774916   5500   110    12044 -0.1063  1.5663  -4.2088        7\n",
       "774917   5500   110    12051 -0.3162 -0.3238   2.9212        7\n",
       "776249   6000   120    12044  0.0275 -0.4625  -1.1788        7\n",
       "776250   6000   120    12051  0.0575 -0.6025   3.5512        7\n",
       "776251   6000   120    12036 -0.4325  1.5475  -4.5088        7\n",
       "777768   6500   130    12044 -0.5275 -0.0462  -1.2338        7\n",
       "777769   6500   130    12051  0.2025 -0.1762   5.0163        7\n",
       "777770   6500   130    12036 -0.1175  1.6737  -3.6937        7\n",
       "...       ...   ...      ...     ...     ...      ...      ...\n",
       "867657  45000   900    12051  0.3900 -0.9300  10.8450        7\n",
       "867658  45000   900    12039  0.6800 -1.0700  -5.1850        7\n",
       "869158  45500   910    12044  0.4463 -0.0000  -3.5925        7\n",
       "869159  45500   910    12051 -0.6537 -0.0600   4.2975        7\n",
       "870382  46000   920    12044  0.7400 -0.2525  -2.8638        7\n",
       "870383  46000   920    12051 -0.4200 -0.3825   3.9263        7\n",
       "871416  46500   930    12044  0.7813  0.9237  -3.3013        7\n",
       "871417  46500   930    12053  0.8113 -4.2562 -12.4713        7\n",
       "871418  46500   930    12051  0.2312  0.0238   3.7088        7\n",
       "872463  47000   940    12044 -0.8313  0.2063  -3.3800        7\n",
       "872464  47000   940    12051 -0.1513 -0.6738   3.0700        7\n",
       "873493  47500   950    12044  0.0388 -0.4488  -2.5588        7\n",
       "873494  47500   950    12051 -0.4812 -0.6387   3.9612        7\n",
       "874574  48000   960    12044 -0.5862 -0.5363  -2.7200        7\n",
       "874575  48000   960    12051 -0.0162 -0.2962   3.2300        7\n",
       "875832  48500   970    12044 -0.1875 -0.5937   2.8688        7\n",
       "875833  48500   970    12024  0.7125 -1.0537  -5.1313        7\n",
       "875834  48500   970    12028  5.7925  0.4463 -14.3013        7\n",
       "875835  48500   970    12051  2.0725 -3.8638   7.8588        7\n",
       "877380  49000   980    12048 -4.3000  5.4750 -12.6625        7\n",
       "877381  49000   980    12044  0.7900 -0.8050   1.2075        7\n",
       "877382  49000   980    12024 -1.1400  0.1650  -4.5625        7\n",
       "877383  49000   980    12051  0.9300  2.0950  10.9875        7\n",
       "878912  49500   990    12044  0.5000 -0.4750   2.4925        7\n",
       "878913  49500   990    12051 -0.6500 -2.1450   9.5125        7\n",
       "878914  49500   990    12024  1.5800 -0.8050  -7.4575        7\n",
       "880560  50000  1000    12044  0.4237 -0.7300   4.0238        7\n",
       "880561  50000  1000    12024  0.6038  1.2900  -2.5563        7\n",
       "880562  50000  1000    12049 -0.1363  2.1500  -6.6363        7\n",
       "880563  50000  1000    12051  1.5437 -0.5900  10.2938        7\n",
       "\n",
       "[244 rows x 7 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coord_reduced = coord_1st[[\"Frame\",\"Time\",\"ResidID\",\"X\",\"Y\",\"Z\",\"TrajNum\"]]\n",
    "coord_subset = coord_reduced[coord_reduced[\"TrajNum\"] == 7]\n",
    "coord_subset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 10) Detail of the ion channel pore\n",
    "\n",
    "![Ion Orderings within the Channel](assets/NavAbSideViewOccupancy.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 11) Timeseries of ordered ions inside the channel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Frame</th>\n",
       "      <th>Time</th>\n",
       "      <th>ResidID</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>TrajNum</th>\n",
       "      <th>TotalCount</th>\n",
       "      <th>RepeatCumSum</th>\n",
       "      <th>Order</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>764793</th>\n",
       "      <td>500</td>\n",
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       "      <th>765562</th>\n",
       "      <td>1000</td>\n",
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       "      <th>765561</th>\n",
       "      <td>1000</td>\n",
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       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>766581</th>\n",
       "      <td>1500</td>\n",
       "      <td>30</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.0525</td>\n",
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       "      <td>-1.3612</td>\n",
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       "      <td>4</td>\n",
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       "      <th>766582</th>\n",
       "      <td>1500</td>\n",
       "      <td>30</td>\n",
       "      <td>12065</td>\n",
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       "      <td>4</td>\n",
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       "      <th>767301</th>\n",
       "      <td>2000</td>\n",
       "      <td>40</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1538</td>\n",
       "      <td>-1.7688</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>767300</th>\n",
       "      <td>2000</td>\n",
       "      <td>40</td>\n",
       "      <td>12044</td>\n",
       "      <td>4.9838</td>\n",
       "      <td>-0.9163</td>\n",
       "      <td>-13.3287</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>768217</th>\n",
       "      <td>2500</td>\n",
       "      <td>50</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.3625</td>\n",
       "      <td>-0.0600</td>\n",
       "      <td>3.5538</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>768216</th>\n",
       "      <td>2500</td>\n",
       "      <td>50</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.6975</td>\n",
       "      <td>-0.5800</td>\n",
       "      <td>-2.2963</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>769236</th>\n",
       "      <td>3000</td>\n",
       "      <td>60</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.1725</td>\n",
       "      <td>-1.1650</td>\n",
       "      <td>4.8712</td>\n",
       "      <td>7</td>\n",
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       "      <td>10</td>\n",
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       "      <th>769235</th>\n",
       "      <td>3000</td>\n",
       "      <td>60</td>\n",
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       "      <td>-0.2150</td>\n",
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       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>770418</th>\n",
       "      <td>3500</td>\n",
       "      <td>70</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.0862</td>\n",
       "      <td>0.3400</td>\n",
       "      <td>3.3062</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>770416</th>\n",
       "      <td>3500</td>\n",
       "      <td>70</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.0163</td>\n",
       "      <td>-0.2100</td>\n",
       "      <td>-1.8938</td>\n",
       "      <td>7</td>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>770417</th>\n",
       "      <td>3500</td>\n",
       "      <td>70</td>\n",
       "      <td>12045</td>\n",
       "      <td>0.2363</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>-8.7537</td>\n",
       "      <td>7</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>771492</th>\n",
       "      <td>4000</td>\n",
       "      <td>80</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.1775</td>\n",
       "      <td>-0.6425</td>\n",
       "      <td>3.8362</td>\n",
       "      <td>7</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>771491</th>\n",
       "      <td>4000</td>\n",
       "      <td>80</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.2175</td>\n",
       "      <td>-0.0725</td>\n",
       "      <td>-2.2837</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>772566</th>\n",
       "      <td>4500</td>\n",
       "      <td>90</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.1400</td>\n",
       "      <td>-0.2888</td>\n",
       "      <td>3.4637</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>772565</th>\n",
       "      <td>4500</td>\n",
       "      <td>90</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>-0.4488</td>\n",
       "      <td>-1.6163</td>\n",
       "      <td>7</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>772567</th>\n",
       "      <td>4500</td>\n",
       "      <td>90</td>\n",
       "      <td>12030</td>\n",
       "      <td>1.3400</td>\n",
       "      <td>0.6812</td>\n",
       "      <td>-6.7262</td>\n",
       "      <td>7</td>\n",
       "      <td>19</td>\n",
       "      <td>17</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>773819</th>\n",
       "      <td>5000</td>\n",
       "      <td>100</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.1500</td>\n",
       "      <td>-0.5425</td>\n",
       "      <td>5.4575</td>\n",
       "      <td>7</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>773818</th>\n",
       "      <td>5000</td>\n",
       "      <td>100</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.0500</td>\n",
       "      <td>-0.1025</td>\n",
       "      <td>-1.2325</td>\n",
       "      <td>7</td>\n",
       "      <td>21</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>774917</th>\n",
       "      <td>5500</td>\n",
       "      <td>110</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.3162</td>\n",
       "      <td>-0.3238</td>\n",
       "      <td>2.9212</td>\n",
       "      <td>7</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>774916</th>\n",
       "      <td>5500</td>\n",
       "      <td>110</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.1063</td>\n",
       "      <td>1.5663</td>\n",
       "      <td>-4.2088</td>\n",
       "      <td>7</td>\n",
       "      <td>23</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>776250</th>\n",
       "      <td>6000</td>\n",
       "      <td>120</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.0575</td>\n",
       "      <td>-0.6025</td>\n",
       "      <td>3.5512</td>\n",
       "      <td>7</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>776249</th>\n",
       "      <td>6000</td>\n",
       "      <td>120</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.0275</td>\n",
       "      <td>-0.4625</td>\n",
       "      <td>-1.1788</td>\n",
       "      <td>7</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>776251</th>\n",
       "      <td>6000</td>\n",
       "      <td>120</td>\n",
       "      <td>12036</td>\n",
       "      <td>-0.4325</td>\n",
       "      <td>1.5475</td>\n",
       "      <td>-4.5088</td>\n",
       "      <td>7</td>\n",
       "      <td>26</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>777769</th>\n",
       "      <td>6500</td>\n",
       "      <td>130</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.2025</td>\n",
       "      <td>-0.1762</td>\n",
       "      <td>5.0163</td>\n",
       "      <td>7</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>777768</th>\n",
       "      <td>6500</td>\n",
       "      <td>130</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.5275</td>\n",
       "      <td>-0.0462</td>\n",
       "      <td>-1.2338</td>\n",
       "      <td>7</td>\n",
       "      <td>28</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>777770</th>\n",
       "      <td>6500</td>\n",
       "      <td>130</td>\n",
       "      <td>12036</td>\n",
       "      <td>-0.1175</td>\n",
       "      <td>1.6737</td>\n",
       "      <td>-3.6937</td>\n",
       "      <td>7</td>\n",
       "      <td>29</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867656</th>\n",
       "      <td>45000</td>\n",
       "      <td>900</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.2300</td>\n",
       "      <td>-0.3000</td>\n",
       "      <td>3.5750</td>\n",
       "      <td>7</td>\n",
       "      <td>214</td>\n",
       "      <td>213</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867658</th>\n",
       "      <td>45000</td>\n",
       "      <td>900</td>\n",
       "      <td>12039</td>\n",
       "      <td>0.6800</td>\n",
       "      <td>-1.0700</td>\n",
       "      <td>-5.1850</td>\n",
       "      <td>7</td>\n",
       "      <td>215</td>\n",
       "      <td>213</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869159</th>\n",
       "      <td>45500</td>\n",
       "      <td>910</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.6537</td>\n",
       "      <td>-0.0600</td>\n",
       "      <td>4.2975</td>\n",
       "      <td>7</td>\n",
       "      <td>216</td>\n",
       "      <td>216</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869158</th>\n",
       "      <td>45500</td>\n",
       "      <td>910</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.4463</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>-3.5925</td>\n",
       "      <td>7</td>\n",
       "      <td>217</td>\n",
       "      <td>216</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>870383</th>\n",
       "      <td>46000</td>\n",
       "      <td>920</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.4200</td>\n",
       "      <td>-0.3825</td>\n",
       "      <td>3.9263</td>\n",
       "      <td>7</td>\n",
       "      <td>218</td>\n",
       "      <td>218</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>870382</th>\n",
       "      <td>46000</td>\n",
       "      <td>920</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.7400</td>\n",
       "      <td>-0.2525</td>\n",
       "      <td>-2.8638</td>\n",
       "      <td>7</td>\n",
       "      <td>219</td>\n",
       "      <td>218</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>871418</th>\n",
       "      <td>46500</td>\n",
       "      <td>930</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.2312</td>\n",
       "      <td>0.0238</td>\n",
       "      <td>3.7088</td>\n",
       "      <td>7</td>\n",
       "      <td>220</td>\n",
       "      <td>220</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>871416</th>\n",
       "      <td>46500</td>\n",
       "      <td>930</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.7813</td>\n",
       "      <td>0.9237</td>\n",
       "      <td>-3.3013</td>\n",
       "      <td>7</td>\n",
       "      <td>221</td>\n",
       "      <td>220</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>871417</th>\n",
       "      <td>46500</td>\n",
       "      <td>930</td>\n",
       "      <td>12053</td>\n",
       "      <td>0.8113</td>\n",
       "      <td>-4.2562</td>\n",
       "      <td>-12.4713</td>\n",
       "      <td>7</td>\n",
       "      <td>222</td>\n",
       "      <td>220</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872464</th>\n",
       "      <td>47000</td>\n",
       "      <td>940</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.1513</td>\n",
       "      <td>-0.6738</td>\n",
       "      <td>3.0700</td>\n",
       "      <td>7</td>\n",
       "      <td>223</td>\n",
       "      <td>223</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872463</th>\n",
       "      <td>47000</td>\n",
       "      <td>940</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.8313</td>\n",
       "      <td>0.2063</td>\n",
       "      <td>-3.3800</td>\n",
       "      <td>7</td>\n",
       "      <td>224</td>\n",
       "      <td>223</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>873494</th>\n",
       "      <td>47500</td>\n",
       "      <td>950</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.4812</td>\n",
       "      <td>-0.6387</td>\n",
       "      <td>3.9612</td>\n",
       "      <td>7</td>\n",
       "      <td>225</td>\n",
       "      <td>225</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>873493</th>\n",
       "      <td>47500</td>\n",
       "      <td>950</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.0388</td>\n",
       "      <td>-0.4488</td>\n",
       "      <td>-2.5588</td>\n",
       "      <td>7</td>\n",
       "      <td>226</td>\n",
       "      <td>225</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>874575</th>\n",
       "      <td>48000</td>\n",
       "      <td>960</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.0162</td>\n",
       "      <td>-0.2962</td>\n",
       "      <td>3.2300</td>\n",
       "      <td>7</td>\n",
       "      <td>227</td>\n",
       "      <td>227</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>874574</th>\n",
       "      <td>48000</td>\n",
       "      <td>960</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.5862</td>\n",
       "      <td>-0.5363</td>\n",
       "      <td>-2.7200</td>\n",
       "      <td>7</td>\n",
       "      <td>228</td>\n",
       "      <td>227</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875835</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>12051</td>\n",
       "      <td>2.0725</td>\n",
       "      <td>-3.8638</td>\n",
       "      <td>7.8588</td>\n",
       "      <td>7</td>\n",
       "      <td>229</td>\n",
       "      <td>229</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875832</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>12044</td>\n",
       "      <td>-0.1875</td>\n",
       "      <td>-0.5937</td>\n",
       "      <td>2.8688</td>\n",
       "      <td>7</td>\n",
       "      <td>230</td>\n",
       "      <td>229</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875833</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>12024</td>\n",
       "      <td>0.7125</td>\n",
       "      <td>-1.0537</td>\n",
       "      <td>-5.1313</td>\n",
       "      <td>7</td>\n",
       "      <td>231</td>\n",
       "      <td>229</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875834</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>12028</td>\n",
       "      <td>5.7925</td>\n",
       "      <td>0.4463</td>\n",
       "      <td>-14.3013</td>\n",
       "      <td>7</td>\n",
       "      <td>232</td>\n",
       "      <td>229</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877383</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>12051</td>\n",
       "      <td>0.9300</td>\n",
       "      <td>2.0950</td>\n",
       "      <td>10.9875</td>\n",
       "      <td>7</td>\n",
       "      <td>233</td>\n",
       "      <td>233</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877381</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.7900</td>\n",
       "      <td>-0.8050</td>\n",
       "      <td>1.2075</td>\n",
       "      <td>7</td>\n",
       "      <td>234</td>\n",
       "      <td>233</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877382</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>12024</td>\n",
       "      <td>-1.1400</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>-4.5625</td>\n",
       "      <td>7</td>\n",
       "      <td>235</td>\n",
       "      <td>233</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877380</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>12048</td>\n",
       "      <td>-4.3000</td>\n",
       "      <td>5.4750</td>\n",
       "      <td>-12.6625</td>\n",
       "      <td>7</td>\n",
       "      <td>236</td>\n",
       "      <td>233</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878913</th>\n",
       "      <td>49500</td>\n",
       "      <td>990</td>\n",
       "      <td>12051</td>\n",
       "      <td>-0.6500</td>\n",
       "      <td>-2.1450</td>\n",
       "      <td>9.5125</td>\n",
       "      <td>7</td>\n",
       "      <td>237</td>\n",
       "      <td>237</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878912</th>\n",
       "      <td>49500</td>\n",
       "      <td>990</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>-0.4750</td>\n",
       "      <td>2.4925</td>\n",
       "      <td>7</td>\n",
       "      <td>238</td>\n",
       "      <td>237</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878914</th>\n",
       "      <td>49500</td>\n",
       "      <td>990</td>\n",
       "      <td>12024</td>\n",
       "      <td>1.5800</td>\n",
       "      <td>-0.8050</td>\n",
       "      <td>-7.4575</td>\n",
       "      <td>7</td>\n",
       "      <td>239</td>\n",
       "      <td>237</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880563</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>12051</td>\n",
       "      <td>1.5437</td>\n",
       "      <td>-0.5900</td>\n",
       "      <td>10.2938</td>\n",
       "      <td>7</td>\n",
       "      <td>240</td>\n",
       "      <td>240</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880560</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>12044</td>\n",
       "      <td>0.4237</td>\n",
       "      <td>-0.7300</td>\n",
       "      <td>4.0238</td>\n",
       "      <td>7</td>\n",
       "      <td>241</td>\n",
       "      <td>240</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880561</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>12024</td>\n",
       "      <td>0.6038</td>\n",
       "      <td>1.2900</td>\n",
       "      <td>-2.5563</td>\n",
       "      <td>7</td>\n",
       "      <td>242</td>\n",
       "      <td>240</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880562</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>12049</td>\n",
       "      <td>-0.1363</td>\n",
       "      <td>2.1500</td>\n",
       "      <td>-6.6363</td>\n",
       "      <td>7</td>\n",
       "      <td>243</td>\n",
       "      <td>240</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Frame  Time  ResidID       X       Y        Z  TrajNum  TotalCount  \\\n",
       "764793    500    10    12051 -0.1825  0.3075  -1.3900        7           0   \n",
       "764794    500    10    12043 -0.4525  9.5175 -13.3700        7           1   \n",
       "765562   1000    20    12051  0.2288  0.0088  -1.4563        7           2   \n",
       "765561   1000    20    12036 -0.4013 -0.8813  -7.5663        7           3   \n",
       "766581   1500    30    12051 -0.0525  0.2775  -1.3612        7           4   \n",
       "766582   1500    30    12065  2.2375  2.6775  -6.2813        7           5   \n",
       "767301   2000    40    12051  0.1238  0.1538  -1.7688        7           6   \n",
       "767300   2000    40    12044  4.9838 -0.9163 -13.3287        7           7   \n",
       "768217   2500    50    12051 -0.3625 -0.0600   3.5538        7           8   \n",
       "768216   2500    50    12044  0.6975 -0.5800  -2.2963        7           9   \n",
       "769236   3000    60    12051 -0.1725 -1.1650   4.8712        7          10   \n",
       "769235   3000    60    12044  0.3375 -0.2150  -1.1187        7          11   \n",
       "770418   3500    70    12051  0.0862  0.3400   3.3062        7          12   \n",
       "770416   3500    70    12044  0.0163 -0.2100  -1.8938        7          13   \n",
       "770417   3500    70    12045  0.2363  0.1300  -8.7537        7          14   \n",
       "771492   4000    80    12051  0.1775 -0.6425   3.8362        7          15   \n",
       "771491   4000    80    12044  0.2175 -0.0725  -2.2837        7          16   \n",
       "772566   4500    90    12051 -0.1400 -0.2888   3.4637        7          17   \n",
       "772565   4500    90    12044  0.1400 -0.4488  -1.6163        7          18   \n",
       "772567   4500    90    12030  1.3400  0.6812  -6.7262        7          19   \n",
       "773819   5000   100    12051 -0.1500 -0.5425   5.4575        7          20   \n",
       "773818   5000   100    12044 -0.0500 -0.1025  -1.2325        7          21   \n",
       "774917   5500   110    12051 -0.3162 -0.3238   2.9212        7          22   \n",
       "774916   5500   110    12044 -0.1063  1.5663  -4.2088        7          23   \n",
       "776250   6000   120    12051  0.0575 -0.6025   3.5512        7          24   \n",
       "776249   6000   120    12044  0.0275 -0.4625  -1.1788        7          25   \n",
       "776251   6000   120    12036 -0.4325  1.5475  -4.5088        7          26   \n",
       "777769   6500   130    12051  0.2025 -0.1762   5.0163        7          27   \n",
       "777768   6500   130    12044 -0.5275 -0.0462  -1.2338        7          28   \n",
       "777770   6500   130    12036 -0.1175  1.6737  -3.6937        7          29   \n",
       "...       ...   ...      ...     ...     ...      ...      ...         ...   \n",
       "867656  45000   900    12044 -0.2300 -0.3000   3.5750        7         214   \n",
       "867658  45000   900    12039  0.6800 -1.0700  -5.1850        7         215   \n",
       "869159  45500   910    12051 -0.6537 -0.0600   4.2975        7         216   \n",
       "869158  45500   910    12044  0.4463 -0.0000  -3.5925        7         217   \n",
       "870383  46000   920    12051 -0.4200 -0.3825   3.9263        7         218   \n",
       "870382  46000   920    12044  0.7400 -0.2525  -2.8638        7         219   \n",
       "871418  46500   930    12051  0.2312  0.0238   3.7088        7         220   \n",
       "871416  46500   930    12044  0.7813  0.9237  -3.3013        7         221   \n",
       "871417  46500   930    12053  0.8113 -4.2562 -12.4713        7         222   \n",
       "872464  47000   940    12051 -0.1513 -0.6738   3.0700        7         223   \n",
       "872463  47000   940    12044 -0.8313  0.2063  -3.3800        7         224   \n",
       "873494  47500   950    12051 -0.4812 -0.6387   3.9612        7         225   \n",
       "873493  47500   950    12044  0.0388 -0.4488  -2.5588        7         226   \n",
       "874575  48000   960    12051 -0.0162 -0.2962   3.2300        7         227   \n",
       "874574  48000   960    12044 -0.5862 -0.5363  -2.7200        7         228   \n",
       "875835  48500   970    12051  2.0725 -3.8638   7.8588        7         229   \n",
       "875832  48500   970    12044 -0.1875 -0.5937   2.8688        7         230   \n",
       "875833  48500   970    12024  0.7125 -1.0537  -5.1313        7         231   \n",
       "875834  48500   970    12028  5.7925  0.4463 -14.3013        7         232   \n",
       "877383  49000   980    12051  0.9300  2.0950  10.9875        7         233   \n",
       "877381  49000   980    12044  0.7900 -0.8050   1.2075        7         234   \n",
       "877382  49000   980    12024 -1.1400  0.1650  -4.5625        7         235   \n",
       "877380  49000   980    12048 -4.3000  5.4750 -12.6625        7         236   \n",
       "878913  49500   990    12051 -0.6500 -2.1450   9.5125        7         237   \n",
       "878912  49500   990    12044  0.5000 -0.4750   2.4925        7         238   \n",
       "878914  49500   990    12024  1.5800 -0.8050  -7.4575        7         239   \n",
       "880563  50000  1000    12051  1.5437 -0.5900  10.2938        7         240   \n",
       "880560  50000  1000    12044  0.4237 -0.7300   4.0238        7         241   \n",
       "880561  50000  1000    12024  0.6038  1.2900  -2.5563        7         242   \n",
       "880562  50000  1000    12049 -0.1363  2.1500  -6.6363        7         243   \n",
       "\n",
       "        RepeatCumSum  Order  \n",
       "764793             0      0  \n",
       "764794             0      1  \n",
       "765562             2      0  \n",
       "765561             2      1  \n",
       "766581             4      0  \n",
       "766582             4      1  \n",
       "767301             6      0  \n",
       "767300             6      1  \n",
       "768217             8      0  \n",
       "768216             8      1  \n",
       "769236            10      0  \n",
       "769235            10      1  \n",
       "770418            12      0  \n",
       "770416            12      1  \n",
       "770417            12      2  \n",
       "771492            15      0  \n",
       "771491            15      1  \n",
       "772566            17      0  \n",
       "772565            17      1  \n",
       "772567            17      2  \n",
       "773819            20      0  \n",
       "773818            20      1  \n",
       "774917            22      0  \n",
       "774916            22      1  \n",
       "776250            24      0  \n",
       "776249            24      1  \n",
       "776251            24      2  \n",
       "777769            27      0  \n",
       "777768            27      1  \n",
       "777770            27      2  \n",
       "...              ...    ...  \n",
       "867656           213      1  \n",
       "867658           213      2  \n",
       "869159           216      0  \n",
       "869158           216      1  \n",
       "870383           218      0  \n",
       "870382           218      1  \n",
       "871418           220      0  \n",
       "871416           220      1  \n",
       "871417           220      2  \n",
       "872464           223      0  \n",
       "872463           223      1  \n",
       "873494           225      0  \n",
       "873493           225      1  \n",
       "874575           227      0  \n",
       "874574           227      1  \n",
       "875835           229      0  \n",
       "875832           229      1  \n",
       "875833           229      2  \n",
       "875834           229      3  \n",
       "877383           233      0  \n",
       "877381           233      1  \n",
       "877382           233      2  \n",
       "877380           233      3  \n",
       "878913           237      0  \n",
       "878912           237      1  \n",
       "878914           237      2  \n",
       "880563           240      0  \n",
       "880560           240      1  \n",
       "880561           240      2  \n",
       "880562           240      3  \n",
       "\n",
       "[244 rows x 10 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf = coord_subset.sort_values([\"TrajNum\",\"Time\",\"Z\"], ascending=(False,True,False))\n",
    "sizes = gdf.groupby([\"TrajNum\",\"Time\"]).size().values\n",
    "gdf[\"TotalCount\"] = np.arange(len(gdf))\n",
    "gdf[\"RepeatCumSum\"] = np.repeat(sizes.cumsum() - sizes, sizes)\n",
    "gdf[\"Order\"] = np.arange(len(gdf)) - np.repeat(sizes.cumsum() - sizes, sizes)\n",
    "gdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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m1PToYXckOZfMpxFCCCGE8C9DhphkTcuWMG8e1Kp17f0rV5qdgF1VurSp1ElM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Jzkm+ZMzNSVi1vrrpV27tgeN0qfCkoK+Dn2Zx5o9YCVo6rZGHtRrj9vNH8a09EnauLS4zQj4Vvo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CSf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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112f59ed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_ts_by_order(coord_df, skip=1):\n",
    "    f1, ax = plt.subplots(1)\n",
    "    \n",
    "    gdf = coord_df.sort_values([\"TrajNum\",\"Time\",\"Z\"], ascending=(False,True,False))\n",
    "    sizes = gdf.groupby([\"TrajNum\",\"Time\"]).size().values\n",
    "    gdf[\"Order\"] = np.arange(sizes.sum()) - np.repeat(sizes.cumsum() - sizes, sizes) # <-- Wizardry\n",
    "    ordcolors=[\"red\",\"green\",\"blue\",\"purple\",\"orange\",\"pink\",\"aqua\",\"maroon\"]\n",
    "    for ordatom, data in gdf.groupby(\"Order\"):\n",
    "        points = data[[\"Time\",\"Z\"]].values\n",
    "        ax.plot(points[:,0][::skip], points[:,1][::skip], color=ordcolors[ordatom])\n",
    "    \n",
    "    ax.set_xlim([0,1000])\n",
    "    ax.set_ylim([-8,10])\n",
    "    ax.grid(True)\n",
    "    ax.set_xlabel(\"Time (ns)\")\n",
    "    ax.set_ylabel(\"Ion Position (Angstrom)\")\n",
    "    \n",
    "    f1.gca().invert_yaxis()\n",
    "    f1.set_size_inches(18.5, 5.5)\n",
    "\n",
    "plot_ts_by_order(coord_subset)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 13) Ion coordination inside the channel\n",
    "\n",
    "![Ion Coordination in Water and in an Ion Channel](assets/NavAbSideViewCoordination.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Frame</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "      <th>S178</th>\n",
       "      <th>E177</th>\n",
       "      <th>E177p</th>\n",
       "      <th>L176</th>\n",
       "      <th>T175</th>\n",
       "      <th>W</th>\n",
       "      <th>TrajNum</th>\n",
       "      <th>ResidID</th>\n",
       "      <th>RowID</th>\n",
       "      <th>Time</th>\n",
       "      <th>CoordLabel</th>\n",
       "      <th>CoordLabel_2nd</th>\n",
       "      <th>ModeLabel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>669</th>\n",
       "      <td>500</td>\n",
       "      <td>0.0687</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>-1.4200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>10</td>\n",
       "      <td>0000</td>\n",
       "      <td>1110</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1601</th>\n",
       "      <td>1000</td>\n",
       "      <td>-0.4813</td>\n",
       "      <td>0.0538</td>\n",
       "      <td>-1.1650</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>20</td>\n",
       "      <td>0000</td>\n",
       "      <td>0110</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1602</th>\n",
       "      <td>1000</td>\n",
       "      <td>3.8488</td>\n",
       "      <td>-0.3862</td>\n",
       "      <td>-7.1050</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>20</td>\n",
       "      <td>1000</td>\n",
       "      <td>1100</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2709</th>\n",
       "      <td>1500</td>\n",
       "      <td>-0.6425</td>\n",
       "      <td>-0.8100</td>\n",
       "      <td>3.2613</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>30</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2710</th>\n",
       "      <td>1500</td>\n",
       "      <td>0.4675</td>\n",
       "      <td>-0.0600</td>\n",
       "      <td>-2.1487</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>30</td>\n",
       "      <td>0000</td>\n",
       "      <td>1110</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3794</th>\n",
       "      <td>2000</td>\n",
       "      <td>5.5337</td>\n",
       "      <td>-3.0650</td>\n",
       "      <td>-13.9875</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12033</td>\n",
       "      <td>NA+</td>\n",
       "      <td>40</td>\n",
       "      <td>0000</td>\n",
       "      <td>0000</td>\n",
       "      <td>EC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3795</th>\n",
       "      <td>2000</td>\n",
       "      <td>0.5837</td>\n",
       "      <td>1.6950</td>\n",
       "      <td>0.5725</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>40</td>\n",
       "      <td>0110</td>\n",
       "      <td>0111</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3796</th>\n",
       "      <td>2000</td>\n",
       "      <td>0.3737</td>\n",
       "      <td>0.8150</td>\n",
       "      <td>-3.1575</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>40</td>\n",
       "      <td>0100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4845</th>\n",
       "      <td>2500</td>\n",
       "      <td>0.1825</td>\n",
       "      <td>1.3175</td>\n",
       "      <td>1.6613</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>50</td>\n",
       "      <td>0110</td>\n",
       "      <td>0011</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4846</th>\n",
       "      <td>2500</td>\n",
       "      <td>0.7225</td>\n",
       "      <td>-0.1625</td>\n",
       "      <td>-1.6487</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>50</td>\n",
       "      <td>0100</td>\n",
       "      <td>1110</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5905</th>\n",
       "      <td>3000</td>\n",
       "      <td>-0.1225</td>\n",
       "      <td>0.6350</td>\n",
       "      <td>1.8025</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>60</td>\n",
       "      <td>0100</td>\n",
       "      <td>0011</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5906</th>\n",
       "      <td>3000</td>\n",
       "      <td>0.9375</td>\n",
       "      <td>-0.4050</td>\n",
       "      <td>-1.3075</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>60</td>\n",
       "      <td>0100</td>\n",
       "      <td>1110</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6922</th>\n",
       "      <td>3500</td>\n",
       "      <td>0.6000</td>\n",
       "      <td>1.1037</td>\n",
       "      <td>1.1662</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>70</td>\n",
       "      <td>0110</td>\n",
       "      <td>0111</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6923</th>\n",
       "      <td>3500</td>\n",
       "      <td>0.5300</td>\n",
       "      <td>-0.9362</td>\n",
       "      <td>-1.4438</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>70</td>\n",
       "      <td>0100</td>\n",
       "      <td>1110</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7968</th>\n",
       "      <td>4000</td>\n",
       "      <td>0.4975</td>\n",
       "      <td>1.2838</td>\n",
       "      <td>1.4462</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>80</td>\n",
       "      <td>0110</td>\n",
       "      <td>0011</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7969</th>\n",
       "      <td>4000</td>\n",
       "      <td>-1.5725</td>\n",
       "      <td>0.0338</td>\n",
       "      <td>-1.1938</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>80</td>\n",
       "      <td>0100</td>\n",
       "      <td>1110</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9036</th>\n",
       "      <td>4500</td>\n",
       "      <td>0.7100</td>\n",
       "      <td>-3.5813</td>\n",
       "      <td>-13.9662</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12031</td>\n",
       "      <td>NA+</td>\n",
       "      <td>90</td>\n",
       "      <td>0000</td>\n",
       "      <td>0000</td>\n",
       "      <td>EC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9037</th>\n",
       "      <td>4500</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.2787</td>\n",
       "      <td>1.3037</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>90</td>\n",
       "      <td>0110</td>\n",
       "      <td>0111</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9038</th>\n",
       "      <td>4500</td>\n",
       "      <td>0.5400</td>\n",
       "      <td>-1.2613</td>\n",
       "      <td>-1.6162</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>90</td>\n",
       "      <td>0100</td>\n",
       "      <td>1110</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10096</th>\n",
       "      <td>5000</td>\n",
       "      <td>-1.2425</td>\n",
       "      <td>-0.1988</td>\n",
       "      <td>4.0200</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>100</td>\n",
       "      <td>0100</td>\n",
       "      <td>0011</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10097</th>\n",
       "      <td>5000</td>\n",
       "      <td>0.8975</td>\n",
       "      <td>0.3413</td>\n",
       "      <td>1.0700</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>100</td>\n",
       "      <td>0110</td>\n",
       "      <td>0111</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11122</th>\n",
       "      <td>5500</td>\n",
       "      <td>-0.6000</td>\n",
       "      <td>0.1388</td>\n",
       "      <td>3.8263</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>110</td>\n",
       "      <td>0100</td>\n",
       "      <td>0011</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11123</th>\n",
       "      <td>5500</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.4163</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>110</td>\n",
       "      <td>0100</td>\n",
       "      <td>0111</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12130</th>\n",
       "      <td>6000</td>\n",
       "      <td>0.5775</td>\n",
       "      <td>-0.9550</td>\n",
       "      <td>6.5538</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>120</td>\n",
       "      <td>0000</td>\n",
       "      <td>0101</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12131</th>\n",
       "      <td>6000</td>\n",
       "      <td>2.5075</td>\n",
       "      <td>0.4850</td>\n",
       "      <td>1.1037</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>120</td>\n",
       "      <td>0111</td>\n",
       "      <td>0100</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13152</th>\n",
       "      <td>6500</td>\n",
       "      <td>6.6138</td>\n",
       "      <td>2.7900</td>\n",
       "      <td>-14.3663</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>12064</td>\n",
       "      <td>NA+</td>\n",
       "      <td>130</td>\n",
       "      <td>0000</td>\n",
       "      <td>0000</td>\n",
       "      <td>EC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13153</th>\n",
       "      <td>6500</td>\n",
       "      <td>-3.4762</td>\n",
       "      <td>-0.7200</td>\n",
       "      <td>3.7738</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>130</td>\n",
       "      <td>0011</td>\n",
       "      <td>0111</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13154</th>\n",
       "      <td>6500</td>\n",
       "      <td>0.6237</td>\n",
       "      <td>0.7000</td>\n",
       "      <td>1.0637</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>130</td>\n",
       "      <td>0100</td>\n",
       "      <td>0111</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14189</th>\n",
       "      <td>7000</td>\n",
       "      <td>-3.1738</td>\n",
       "      <td>-0.3688</td>\n",
       "      <td>9.0863</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>140</td>\n",
       "      <td>0000</td>\n",
       "      <td>0000</td>\n",
       "      <td>CC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14190</th>\n",
       "      <td>7000</td>\n",
       "      <td>-2.1838</td>\n",
       "      <td>-0.2988</td>\n",
       "      <td>-0.3637</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>12043</td>\n",
       "      <td>NA+</td>\n",
       "      <td>140</td>\n",
       "      <td>0110</td>\n",
       "      <td>0111</td>\n",
       "      <td>EL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2298939</th>\n",
       "      <td>43500</td>\n",
       "      <td>0.1587</td>\n",
       "      <td>-0.4650</td>\n",
       "      <td>3.9637</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>870</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2299960</th>\n",
       "      <td>44000</td>\n",
       "      <td>-0.5463</td>\n",
       "      <td>0.0350</td>\n",
       "      <td>3.4075</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>880</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2299961</th>\n",
       "      <td>44000</td>\n",
       "      <td>-0.1263</td>\n",
       "      <td>-6.0850</td>\n",
       "      <td>-14.2425</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12023</td>\n",
       "      <td>NA+</td>\n",
       "      <td>880</td>\n",
       "      <td>0000</td>\n",
       "      <td>0000</td>\n",
       "      <td>EC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2299962</th>\n",
       "      <td>44000</td>\n",
       "      <td>-0.1662</td>\n",
       "      <td>-0.5050</td>\n",
       "      <td>-2.8725</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>880</td>\n",
       "      <td>0100</td>\n",
       "      <td>1110</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2301035</th>\n",
       "      <td>44500</td>\n",
       "      <td>-0.1512</td>\n",
       "      <td>0.2025</td>\n",
       "      <td>3.1112</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>890</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2301036</th>\n",
       "      <td>44500</td>\n",
       "      <td>0.1488</td>\n",
       "      <td>0.7225</td>\n",
       "      <td>-3.8188</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>890</td>\n",
       "      <td>0100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2302114</th>\n",
       "      <td>45000</td>\n",
       "      <td>0.0088</td>\n",
       "      <td>-0.3975</td>\n",
       "      <td>3.2800</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>900</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2302115</th>\n",
       "      <td>45000</td>\n",
       "      <td>-0.3613</td>\n",
       "      <td>1.0925</td>\n",
       "      <td>-4.2300</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>900</td>\n",
       "      <td>1100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2303232</th>\n",
       "      <td>45500</td>\n",
       "      <td>0.0788</td>\n",
       "      <td>0.1788</td>\n",
       "      <td>3.5875</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>910</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2303233</th>\n",
       "      <td>45500</td>\n",
       "      <td>-0.2713</td>\n",
       "      <td>1.0988</td>\n",
       "      <td>-4.0425</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>910</td>\n",
       "      <td>1100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2304262</th>\n",
       "      <td>46000</td>\n",
       "      <td>-0.2287</td>\n",
       "      <td>-0.0538</td>\n",
       "      <td>3.4950</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>920</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2304263</th>\n",
       "      <td>46000</td>\n",
       "      <td>0.1212</td>\n",
       "      <td>-0.3137</td>\n",
       "      <td>-2.7450</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>920</td>\n",
       "      <td>0100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2305325</th>\n",
       "      <td>46500</td>\n",
       "      <td>-0.0325</td>\n",
       "      <td>-0.5437</td>\n",
       "      <td>3.1013</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>930</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2305326</th>\n",
       "      <td>46500</td>\n",
       "      <td>-0.2525</td>\n",
       "      <td>1.5263</td>\n",
       "      <td>-4.1687</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>930</td>\n",
       "      <td>1100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2305327</th>\n",
       "      <td>46500</td>\n",
       "      <td>0.1675</td>\n",
       "      <td>1.1363</td>\n",
       "      <td>-13.1888</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12036</td>\n",
       "      <td>NA+</td>\n",
       "      <td>930</td>\n",
       "      <td>0000</td>\n",
       "      <td>0000</td>\n",
       "      <td>EC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2306391</th>\n",
       "      <td>47000</td>\n",
       "      <td>-0.2675</td>\n",
       "      <td>-0.1475</td>\n",
       "      <td>3.9137</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>940</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2306392</th>\n",
       "      <td>47000</td>\n",
       "      <td>-0.3675</td>\n",
       "      <td>1.2125</td>\n",
       "      <td>-3.8662</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>940</td>\n",
       "      <td>1100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2307466</th>\n",
       "      <td>47500</td>\n",
       "      <td>0.2563</td>\n",
       "      <td>-1.2562</td>\n",
       "      <td>4.3612</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>950</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2307467</th>\n",
       "      <td>47500</td>\n",
       "      <td>-0.3937</td>\n",
       "      <td>0.5237</td>\n",
       "      <td>-2.0588</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>950</td>\n",
       "      <td>0100</td>\n",
       "      <td>1110</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2308530</th>\n",
       "      <td>48000</td>\n",
       "      <td>0.1112</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>3.5762</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>960</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2308531</th>\n",
       "      <td>48000</td>\n",
       "      <td>-0.5087</td>\n",
       "      <td>0.9300</td>\n",
       "      <td>-3.9738</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>960</td>\n",
       "      <td>1100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2309551</th>\n",
       "      <td>48500</td>\n",
       "      <td>-0.0888</td>\n",
       "      <td>0.0850</td>\n",
       "      <td>3.1625</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>970</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2309552</th>\n",
       "      <td>48500</td>\n",
       "      <td>-2.1087</td>\n",
       "      <td>-6.4450</td>\n",
       "      <td>-12.8675</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12033</td>\n",
       "      <td>NA+</td>\n",
       "      <td>970</td>\n",
       "      <td>0000</td>\n",
       "      <td>0000</td>\n",
       "      <td>EC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2309553</th>\n",
       "      <td>48500</td>\n",
       "      <td>-0.1787</td>\n",
       "      <td>1.0550</td>\n",
       "      <td>-3.7775</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>970</td>\n",
       "      <td>0100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2310679</th>\n",
       "      <td>49000</td>\n",
       "      <td>-0.3163</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>2.9588</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>980</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2310680</th>\n",
       "      <td>49000</td>\n",
       "      <td>-0.3362</td>\n",
       "      <td>1.0800</td>\n",
       "      <td>-3.8712</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>980</td>\n",
       "      <td>1100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2311694</th>\n",
       "      <td>49500</td>\n",
       "      <td>-0.7925</td>\n",
       "      <td>0.8288</td>\n",
       "      <td>4.0700</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>990</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2311695</th>\n",
       "      <td>49500</td>\n",
       "      <td>-0.1225</td>\n",
       "      <td>1.3988</td>\n",
       "      <td>-3.8600</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>990</td>\n",
       "      <td>1100</td>\n",
       "      <td>1100</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2312775</th>\n",
       "      <td>50000</td>\n",
       "      <td>0.1387</td>\n",
       "      <td>-0.4162</td>\n",
       "      <td>3.8613</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "      <td>12051</td>\n",
       "      <td>NA+</td>\n",
       "      <td>1000</td>\n",
       "      <td>0000</td>\n",
       "      <td>0011</td>\n",
       "      <td>LT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2312776</th>\n",
       "      <td>50000</td>\n",
       "      <td>-0.7312</td>\n",
       "      <td>1.4338</td>\n",
       "      <td>-2.1687</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>12032</td>\n",
       "      <td>NA+</td>\n",
       "      <td>1000</td>\n",
       "      <td>0100</td>\n",
       "      <td>1110</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4659 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Frame       X       Y        Z  S178  E177  E177p  L176  T175  W  \\\n",
       "669        500  0.0687  0.1812  -1.4200     0     0      0     0     0  6   \n",
       "1601      1000 -0.4813  0.0538  -1.1650     0     0      0     0     0  5   \n",
       "1602      1000  3.8488 -0.3862  -7.1050     1     0      0     0     0  5   \n",
       "2709      1500 -0.6425 -0.8100   3.2613     0     0      0     0     0  6   \n",
       "2710      1500  0.4675 -0.0600  -2.1487     0     0      0     0     0  6   \n",
       "3794      2000  5.5337 -3.0650 -13.9875     0     0      0     0     0  4   \n",
       "3795      2000  0.5837  1.6950   0.5725     0     1      0     1     0  4   \n",
       "3796      2000  0.3737  0.8150  -3.1575     0     1      0     0     0  4   \n",
       "4845      2500  0.1825  1.3175   1.6613     0     1      0     1     0  3   \n",
       "4846      2500  0.7225 -0.1625  -1.6487     0     1      0     0     0  4   \n",
       "5905      3000 -0.1225  0.6350   1.8025     0     1      0     0     0  4   \n",
       "5906      3000  0.9375 -0.4050  -1.3075     0     1      0     0     0  4   \n",
       "6922      3500  0.6000  1.1037   1.1662     0     1      0     1     0  4   \n",
       "6923      3500  0.5300 -0.9362  -1.4438     0     2      0     0     0  4   \n",
       "7968      4000  0.4975  1.2838   1.4462     0     1      0     1     0  4   \n",
       "7969      4000 -1.5725  0.0338  -1.1938     0     2      0     0     0  3   \n",
       "9036      4500  0.7100 -3.5813 -13.9662     0     0      0     0     0  4   \n",
       "9037      4500  0.4100  0.2787   1.3037     0     1      0     1     0  4   \n",
       "9038      4500  0.5400 -1.2613  -1.6162     0     2      0     0     0  4   \n",
       "10096     5000 -1.2425 -0.1988   4.0200     0     1      0     0     0  3   \n",
       "10097     5000  0.8975  0.3413   1.0700     0     1      0     1     0  3   \n",
       "11122     5500 -0.6000  0.1388   3.8263     0     1      0     0     0  5   \n",
       "11123     5500  1.0000  0.0187   0.4163     0     1      0     0     0  3   \n",
       "12130     6000  0.5775 -0.9550   6.5538     0     0      0     0     0  6   \n",
       "12131     6000  2.5075  0.4850   1.1037     0     1      0     1     1  1   \n",
       "13152     6500  6.6138  2.7900 -14.3663     0     0      0     0     0  3   \n",
       "13153     6500 -3.4762 -0.7200   3.7738     0     0      0     1     1  4   \n",
       "13154     6500  0.6237  0.7000   1.0637     0     1      0     0     0  4   \n",
       "14189     7000 -3.1738 -0.3688   9.0863     0     0      0     0     0  6   \n",
       "14190     7000 -2.1838 -0.2988  -0.3637     0     2      0     1     0  3   \n",
       "...        ...     ...     ...      ...   ...   ...    ...   ...   ... ..   \n",
       "2298939  43500  0.1587 -0.4650   3.9637     0     0      0     0     0  6   \n",
       "2299960  44000 -0.5463  0.0350   3.4075     0     0      0     0     0  6   \n",
       "2299961  44000 -0.1263 -6.0850 -14.2425     0     0      0     0     0  4   \n",
       "2299962  44000 -0.1662 -0.5050  -2.8725     0     1      0     0     0  4   \n",
       "2301035  44500 -0.1512  0.2025   3.1112     0     0      0     0     0  6   \n",
       "2301036  44500  0.1488  0.7225  -3.8188     0     1      0     0     0  4   \n",
       "2302114  45000  0.0088 -0.3975   3.2800     0     0      0     0     0  6   \n",
       "2302115  45000 -0.3613  1.0925  -4.2300     1     1      0     0     0  4   \n",
       "2303232  45500  0.0788  0.1788   3.5875     0     0      0     0     0  6   \n",
       "2303233  45500 -0.2713  1.0988  -4.0425     1     1      0     0     0  4   \n",
       "2304262  46000 -0.2287 -0.0538   3.4950     0     0      0     0     0  6   \n",
       "2304263  46000  0.1212 -0.3137  -2.7450     0     1      0     0     0  4   \n",
       "2305325  46500 -0.0325 -0.5437   3.1013     0     0      0     0     0  6   \n",
       "2305326  46500 -0.2525  1.5263  -4.1687     1     1      0     0     0  4   \n",
       "2305327  46500  0.1675  1.1363 -13.1888     0     0      0     0     0  6   \n",
       "2306391  47000 -0.2675 -0.1475   3.9137     0     0      0     0     0  6   \n",
       "2306392  47000 -0.3675  1.2125  -3.8662     1     1      0     0     0  4   \n",
       "2307466  47500  0.2563 -1.2562   4.3612     0     0      0     0     0  6   \n",
       "2307467  47500 -0.3937  0.5237  -2.0588     0     1      0     0     0  4   \n",
       "2308530  48000  0.1112  0.1500   3.5762     0     0      0     0     0  6   \n",
       "2308531  48000 -0.5087  0.9300  -3.9738     1     1      0     0     0  4   \n",
       "2309551  48500 -0.0888  0.0850   3.1625     0     0      0     0     0  6   \n",
       "2309552  48500 -2.1087 -6.4450 -12.8675     0     0      0     0     0  4   \n",
       "2309553  48500 -0.1787  1.0550  -3.7775     0     1      0     0     0  4   \n",
       "2310679  49000 -0.3163  0.0100   2.9588     0     0      0     0     0  6   \n",
       "2310680  49000 -0.3362  1.0800  -3.8712     1     1      0     0     0  4   \n",
       "2311694  49500 -0.7925  0.8288   4.0700     0     0      0     0     0  6   \n",
       "2311695  49500 -0.1225  1.3988  -3.8600     1     1      0     0     0  4   \n",
       "2312775  50000  0.1387 -0.4162   3.8613     0     0      0     0     0  6   \n",
       "2312776  50000 -0.7312  1.4338  -2.1687     0     2      0     0     0  3   \n",
       "\n",
       "         TrajNum  ResidID RowID  Time CoordLabel CoordLabel_2nd ModeLabel  \n",
       "669            1    12051   NA+    10       0000           1110        EL  \n",
       "1601           1    12051   NA+    20       0000           0110        EL  \n",
       "1602           1    12043   NA+    20       1000           1100         S  \n",
       "2709           1    12051   NA+    30       0000           0011        LT  \n",
       "2710           1    12043   NA+    30       0000           1110        EL  \n",
       "3794           1    12033   NA+    40       0000           0000        EC  \n",
       "3795           1    12051   NA+    40       0110           0111        EL  \n",
       "3796           1    12043   NA+    40       0100           1100         E  \n",
       "4845           1    12051   NA+    50       0110           0011        EL  \n",
       "4846           1    12043   NA+    50       0100           1110         E  \n",
       "5905           1    12051   NA+    60       0100           0011        EL  \n",
       "5906           1    12043   NA+    60       0100           1110         E  \n",
       "6922           1    12051   NA+    70       0110           0111        EL  \n",
       "6923           1    12043   NA+    70       0100           1110         E  \n",
       "7968           1    12051   NA+    80       0110           0011        EL  \n",
       "7969           1    12043   NA+    80       0100           1110         E  \n",
       "9036           1    12031   NA+    90       0000           0000        EC  \n",
       "9037           1    12051   NA+    90       0110           0111        EL  \n",
       "9038           1    12043   NA+    90       0100           1110         E  \n",
       "10096          1    12051   NA+   100       0100           0011        EL  \n",
       "10097          1    12043   NA+   100       0110           0111        EL  \n",
       "11122          1    12051   NA+   110       0100           0011        EL  \n",
       "11123          1    12043   NA+   110       0100           0111        EL  \n",
       "12130          1    12051   NA+   120       0000           0101        LT  \n",
       "12131          1    12043   NA+   120       0111           0100        EL  \n",
       "13152          1    12064   NA+   130       0000           0000        EC  \n",
       "13153          1    12051   NA+   130       0011           0111        LT  \n",
       "13154          1    12043   NA+   130       0100           0111        EL  \n",
       "14189          1    12051   NA+   140       0000           0000        CC  \n",
       "14190          1    12043   NA+   140       0110           0111        EL  \n",
       "...          ...      ...   ...   ...        ...            ...       ...  \n",
       "2298939       20    12051   NA+   870       0000           0011        LT  \n",
       "2299960       20    12051   NA+   880       0000           0011        LT  \n",
       "2299961       20    12023   NA+   880       0000           0000        EC  \n",
       "2299962       20    12032   NA+   880       0100           1110         E  \n",
       "2301035       20    12051   NA+   890       0000           0011        LT  \n",
       "2301036       20    12032   NA+   890       0100           1100         E  \n",
       "2302114       20    12051   NA+   900       0000           0011        LT  \n",
       "2302115       20    12032   NA+   900       1100           1100         E  \n",
       "2303232       20    12051   NA+   910       0000           0011        LT  \n",
       "2303233       20    12032   NA+   910       1100           1100         E  \n",
       "2304262       20    12051   NA+   920       0000           0011        LT  \n",
       "2304263       20    12032   NA+   920       0100           1100         E  \n",
       "2305325       20    12051   NA+   930       0000           0011        LT  \n",
       "2305326       20    12032   NA+   930       1100           1100         E  \n",
       "2305327       20    12036   NA+   930       0000           0000        EC  \n",
       "2306391       20    12051   NA+   940       0000           0011        LT  \n",
       "2306392       20    12032   NA+   940       1100           1100         E  \n",
       "2307466       20    12051   NA+   950       0000           0011        LT  \n",
       "2307467       20    12032   NA+   950       0100           1110         E  \n",
       "2308530       20    12051   NA+   960       0000           0011        LT  \n",
       "2308531       20    12032   NA+   960       1100           1100         E  \n",
       "2309551       20    12051   NA+   970       0000           0011        LT  \n",
       "2309552       20    12033   NA+   970       0000           0000        EC  \n",
       "2309553       20    12032   NA+   970       0100           1100         E  \n",
       "2310679       20    12051   NA+   980       0000           0011        LT  \n",
       "2310680       20    12032   NA+   980       1100           1100         E  \n",
       "2311694       20    12051   NA+   990       0000           0011        LT  \n",
       "2311695       20    12032   NA+   990       1100           1100         E  \n",
       "2312775       20    12051   NA+  1000       0000           0011        LT  \n",
       "2312776       20    12032   NA+  1000       0100           1110         E  \n",
       "\n",
       "[4659 rows x 17 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coord_merge = pd.read_pickle(\"assets/NAVAB_XTAL_PD-NORES-0kcal-CHARMM_NONB_WT_SOD150_DEMO_MERGE.pkl\")\n",
    "coord_merge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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X/opGo9hQd1LHvrQxzDNPPDLj88plMCiPwaFcJi/fCzBXrD3vlMfKhscZHh72IRpJl67J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\n3ZNPPEVHo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FTw5IsvMWXiRPbdezZ3X3EtP5o4izhn6HO++pZm5tVt4g8X/R+vvvkm7y9Z\nSkN8IhkTJnZbm8PjdlP2xpscm17IxNzC0Mt5vSzZtpGlTdW4k0KPaOd1CNkHHUhiauTdydTQUbt8\nGRKfQObk3WMdyqASzRYwMU/AiMgoYAvQDmQaY9qDLFMCFAAHGWM+7e/tRSsBs37dat5+5QpOOnrX\nLypjDE+83IwjcX/a6jzk5+R3WdcYw+qNq5hz4CxOPuVkwPonecWlcykaMXqXIklqcDHGUFFVQXVD\nJeVrPuFf3/FRlBX6H9qGylZeWNZOeWsa+SMnEe+Kp2TbGtIctRwzxcmsMSnaT1cNqDs+2cLJp2bs\ncvKsVE8qmoWcMXvidA3fmwODSUurhyce2sz+qdMZlx16BJB2t5tPt66jnO1MmJ7A/vvnEReisLbb\n7eOzzypYt6ydPJPH/sUTSYqg24gaXIyBimoYVTy5y42mlpZm6moqwLSRngoINDQCkkhmVj7J3dS/\nC6WmppL21u1kZwb/Dmhr99HSnsbIgtAjpFRWltPRWkZKioA4EBGMz4sgxLmctLQKXjLIzy/akcjx\ner1s2roVd1w8zrjQn1efx42zvY1xxcVBu+lEQ011Je1t20lPFRoaDT6TSFpGNm+sWc7C1mpkwgTS\nJk6mtbqKmnlvcO6MQ5lQXNxtN6WW1hYWr1vDw1u/YeQx3yc1p+cRf1pqa2l4611+MmEvMpOjkzBp\nd3fw+Oov4YA5ZIwauqPcKNUbwy0BcxzwErDYGBO0Yo+IvACcAJxjjOl2XLZobC8aCZi6ujruu+Ns\nfnZiYtCLmPkflvHme+kcfMD3u219UVpRSmJGHH8+90/cecddeJsgK1jmX3Wxau1Kdp8Uu5oEtTVV\nmJoNbN++nnjPdg6ZYDhscioup4N2t483VzSysMSJiS9g7KhxxHU6GfD5fGwpK6WtcQt75LZz4l6p\npCd9O1vFaA2YgVPZ0MGr5RUcc2RGv2xfa8AMD8GOY4fHUO/KJ3dk6DutKjpKtzXz6uPbOXHcfqRH\ncENmY1U1i6rX4Mpp5+AjcxhVmMrHC8sYW5zOh+9W0rE9gdm5kxifHbvaIar3/DVgArk9htqGeEYV\nT8Dn9VJTU0Vbax2J8R7SUp1dGqMYA41NXto6XCQmZZCVlYujh1YxgfVeuisQDNa2HXH5jMja+Rkz\nxlBXX09F5XZc0kBudgIEucwxPh8Yg8cNzW1JjCqeiNvtZlNpKY6UVMTRc/LX+Hz4mhujXhcm2Htg\njKGjw01Dk5v6Fgcramp517Qy+thjKZu/gFNSCihIz8Tb2kqcQHZGJpmZGXy69hv2mziFqupq6pqa\n8IoDV1ISS8o283l2InkzZ3YbS8369SQt+prTp8zBFeXW8sYY5q37ii3FueQNopFLB6uhVANGdS+a\nCZjBcDXn/0+xuZtlttjPY2OwvYi53W7u/c9FnPr9uKDJl/WbGvh0oYM508ezrXQjRcUTgv2fAaAo\nv4jq2hpOP/lUJo+byu4To5tQ8Hg81NZUkZySRkpKZHc7jDHU1tbQ1ha6j7GIg4zMbJKDNAftb1tK\nNscsAWOAlrrtFKXGk5U6BWN254vqKt58bT3pcS00uNPIG7kXEyeHTio4HA7GFhUDxdQ2NXPNu2vI\ncNVxzB4u9ipOHrBWMcYYvilrZfGWdn4wLZURKQNfF2TplkZNwAyAmiY3D36xjR+e2j/JF4Dl61o0\nATMMBDuO8S7B3VwLpjDoxVNf+Xw+6qqrcMbFkZExol/2EUrJtiYWf1HDnP2yKciPbde8RYuqWLnA\ny092OyTii6txOdmMy9mfNrebT59fy9ts4qNlWzhp+my+U3wAyVna2mUoMsbgdnv4emtplwRMnEtI\nT25n86bVxDm9pKVCerYDCP7ZEYH0NCfpGDo6aijfVoORRBzdJDfc7jZGpHtJiO+6jNvtwevz7own\nDqprN1NdV09cfALGGNrcbrwOJ07TTG5O8OQLgNg3LOMckOpoYc3qpbiNE0d8PNLYEWwNnMnpu7SK\nEYfDqgtTUUGSyxXyXEqAjPR0MtLSeuwy5fF42Fa6gRHpHhLinXg8XtweDwaDOJykpseTmg75OTmM\nKavnvjtu4ohJ+1BYlAUIrpRUDIbypiYqamv44KtFZLmSICERZ0rajou1mYXjqFj3FavK5oW8eetz\ndzBdkjl86r79cp4oIhwzaQbLyjax4M03KTrqqB4TdP3J09FO5bKvcKalkTt58o7PSDiMz0f1unV0\n1NaSO2NGvxQjrty0URMwqovBkIDxt4tr7mYZ/xV+OGft0d5eRIwx3Hf31Xz/oEaSk7r+IdfVt/Po\nU9VM331/HA4hPaWdivISRgYZLrCpqZH6ukqENo6cswdtHT5Ktq4mISGdrOy8XvfTNUBTYwMN9ZU4\naCc9TWhtqqa2xkViYqbdBzj0F1hbezu11RX4vM2kphhyQjQ1BTA+Q0N9AzVVcSQlZTIiKydq9VZ6\n0tIau4KQ9TXVZLra8Z9FiAgFObkUhNFsNJiM1BQyJs/E5/Px4oZSnlq6mT3zOjhhRipp/dQqprnd\ny2tfN7F0mwtXSjE5WXn86/11pEgNR+/mYM7YlAHrolLX4u15IdUrPp/hyy0NfL6tnuQsOP6H6aT1\ncAezLxqa9VgOB6GOY5qzncbGetLSo5fEa21tpb6yDDqayEzw4GmBsupSnInpjMgtIC6+f5LC/u44\n67/qIM/kMjt/Nouf2UylbGbSzET2mZMbsitPfzDG8PKLJSSV5XHylN36tK3EuDgOH78HsAfl697j\nyAlabHEo8nq9uN0efBhwOKhraaG1rQ2nw0l8wN9FYqKDgkRDpGNvxMc7yMkCCJbc6Gzntn0+Hx1u\nNz5jrG5Enc77srLiKa9qxOtMweF04YhPwFtXRn6uK7zEqoAr3kXhjsZ2wb+PfD5oaKygucUFrhTi\nkv3JFMGVkkbwwZr9DNvq6ymvqiY1KZH83Nygw1m3tDRTVbmZnBHg9XpoafOBCOJ0dHkpLpewW3Em\nN4z6Ls0tXhrqt+FzJBGXkoE4nLgSEiEhkQavD2dqetCovjdxOt/r/t0ZEDMKxlLQUMtTz79EzjFH\nkxDhTdy+qi8ro2nJUvJbPZxcOJ76siY+Xf4KjVnpZO09m6T04O8fWEMuV3+5iNTqOg7KLCAnJZ0P\nXnuH0kQHKXtNJ7MoekO4tzd3dzmqvq0GQxeki4FrgEeNMb8Iscy1wEXAPcaYs/p7eyJiFi5cGNkL\nsb339kukx3/OuOKuLT48Hh+PPF3K6IJpxLlcGKz3vrnZh8M1gvSMTLxeHw31NbjdzSTEeUlKcnTJ\nYHs8hqYWA8STmpbVYz0Y/zH2er3U19ficTeTmOAjOcHZ5R+d2+2luRWQBFLTski0s8HGQFNTPa0t\nDbicHlJTHDg6xeV/PaF0dPhoaQUkkfT0LBISQtdF6fb19LAfvw8+XcAh+x/Wq30AfaoGX7VtEzmJ\n3f9r37mj3u2jqbWVyqqtpDmb2H+sk4n5iT3dpMH/kgJfmtkxz/ppU1U7H2/0UO9OJju7mDT78xW4\nXGVtNW1NFYxKb+fACUmkJTp3bnuX/ZmAn4PND7JckPmPf1bBj/fL32XZ4K8hxL6Dze8mxp62GSzG\nnrbZm9cd7L0Mtr+ethlsnZZ2L99UNNPkc5M3Mo7CvDhEQnxGdsQT4r0Ksk7nuP3zP1zcwMGz0oPG\nFijwsyzBpgX5sPsndX62tiFdpwVdLsj2u12ua0zdLddTTN3va+fELq/V/llEdpmG7Jy+63Jd9xOJ\nF+fXcOLhwQphQo07gay8vnVDMsbQ1NBAR2sj8dJBikuQTteOXp+huUPwOBJITMmwalYE67YQ4Xd5\nTW07K79uwNPgYnxaAflp1om8//NvDFQ0NrCxqYy4DC9TpqUzIiP8/2e9+crv6PDy0YJKJiWMJj8t\nY5d4+ur1Zcs5Znrf7tBGK5ZonZIGHqvO39u7fiftnBdsuS7rmE7bDvjZv98u35fBlguy7cAY6G4f\nxuDxevHZ2xCRHet9vmHTjhYwYgwOEVwuJw5x2H/rYn1H2Hvx/+z/3hDE+s5g5++dn5FO6wU8e30+\nq5uQCOJwBF3Ov18M1DYYXKlZeFvqyUozO27+WfvauR4h9hdqeuB+/N9xHR3WubPXxOFITMXRTfHa\nzozPi6+9nTiHkJmWRkpyMojQ0FBHa3MVKcn2sXA4Im6Z5/VAY4sPt9eFJKTgjIvn9cWfcMysA3tc\ndzBUaevweHhry0pk2lRS83p3kzGoIC/O6/ZQt3Ytzu1VTEhIZUruqC6tAFva21i6fStlxoNz7Cgy\nikcjDsH4DPXbSvFu2MxI42SvvGJSEne9fvL6vKyu3MbatgbcudlkTpqEq48J/hXvvsPUI4/q+cUN\nE8O5ZuXTl/x9WNWA+TNwK/CCPVR0sGVuwxo2+kZjzAX9vT0Rif3QUEoppZRSSimllIq5aCVgBq7t\nbGgb7ecx3SzjL7W9KQbbU0oppZRSSimllOqTwVADZon9PFVEEo0xbUGWmdNp2X7dXrSyW0oppZRS\nSimllFIwCFrAGGNKgMVAAnBq5/kicihQBJQZYz4d6O0ppZRSSimllFJK9VXMEzC2f9rP14nIBP9E\nEckD7rR//VfgCiLyTxFZJSL/iMb2lFJKKaWUUkoppfrLoEjAGGOeA+4CRgJfi8grIvI8sBaYArwA\n3NFptQJgsr1ONLYXlIg4ReQsEflYROpEpENEKkTkdRE5oVcvWMWUiBwtIi+ISJmItInINhFZICJ/\ni3VsKnIisqeItIuIT0S+jnU8Knz2sbtMRN4RkQ3232OdiHwiIn8RkfhYx6h2JSI/EZEPRaReRBpF\n5AsR+aMM56EPhhERiRORH4jIXSLypX0+0yEipSLyjN1KWA1RIvIP+3+hT0TOi3U8KjIikiQiF9jf\nq3Ui0iwia0XkSRE5INbxqfCIyCgR+beIrBaRVvux1v7eHRfr+JRFRHazzzUftRt1+L87gw7i02nd\nPp0LxXwUpEAi8mPgbGAaVnJoFfCAMeauIMs+CPwCeNgYc0ZftxdifRcwDzgSaAM+AqqACeysI3Or\nMUYv3IcAEXEAdwO/xTqenwJlWIm66UCdMWZy7CJUkbL/Rj8H9sIa12+5MWZ6bKNS4RKREqAQaAW+\nBEqAfOAAIBGrTtdRxpjamAWpdhCR/wBnYR2vdwE3cBSQhnVj4xQzmE4qVBcichTwlv1rGbAIaAam\nAv6xqK82xlwRg/BUH4jIHKzzGrEf5xtjbo5tVCpc9oX5W1jXGNuwzm08wFisc5wrjTHBWv2rQURE\nZgLvARnAVqzvWLCuG4uAJuBoLYMReyJyK/Bn+1fDzvHBTzHGPN/Nen0+FxpUCZjBRkR+h3XBvhk4\n2K4v45/3XeBVrELGs40x4RQIVjEkIv8CLsD6YvyZMaY8YJ4DmGWM+TJW8anIicjlwFysFm3noAmY\nIUVE3gEeBZ42xrQETB+D9f06FfifMeZXsYlQ+dl3hJ7Bumg/xBiz3p6eB8zHal16rjHm9thFqXoi\nIodjnTjeZoz5uNO804DHACdwhDFmwcBHqHpDRBKwEtZpwBfAiWgCZsgQkRRgGTAOuBC4MfACTkRG\nADnGmLUxClGFSUQ+AfYD7gXONsZ47ekurGvKM4CvjDF7xS5KBSAivwEmYd0AXAw8ABxCNwmYaJ0L\nDYouSIPY4fbz3YHJFwBjzFtYF/IA+w5oVCpiIrIHcD5QCpwQmHwBMMb4NPkytIjIDOBS4Dn7oYYY\nY8xRxpiHApMv9vTNwB/sX0+1T1xUbF1kP//df8IBYIzZjnVBD3ChdkUa3Iwx840xp3VOvtjzngYe\nsn/92YAGpvrqKmB3rO/NhhjHoiJ3KTAeuMMYc0Pnu+fGmFpNvgx+IpKIlXwxwBX+5AuAMcaDdZwB\nptnLqhgyxvzXGHOhMeZZY8yGMFeLyrmQJmC6124/h3oT/dOrBiAW1TdnYX3e7zfGNMc6GNU3IhKH\ndaFQD/yR0H+jauhaaj8nAtmxDOTbTkRGAbOw/ic+03m+MeYDrCbz+Vgnn2ro8v/dFcU0ChU2EdkX\nOA94zBjzWqzjUZGxa52diXXRri2Whjav/YDg56X+ac3GmLaBCUlFSzTPhTQB07159vMfRKQ4cIaI\nHI3VQqYUeH2gA1MR+679/KGIZIvIOXYxrFtE5GeaiR5yLgVmAH81xlTGOhjVLybZzx1ATSwDUcy0\nn1cYY9pDLPMF1snlzBDz1dDg/7sri2kUKiz2ucvDWDcC/xLjcFTvzAaygFJjzGYRmSUiV4vIPSJy\nlYgcGOsAVXiMMW7gHaz/hVcGtt61bxxebf/63xiEp/ouaudC2qy7G8aYp0TkSKyirWtE5COgGquZ\n4N7Ax8AZnZvPq8HF7hs9CevuwmTgaax/doH+JSInGWO+GOj4VGTsAmcXA68bYx6NdTyq31xoP79q\nn9So2PGP2rC5m2W22M9j+zcU1V9EZCTwK6z/ldqtc2i4Fuu85nRjjCaqh6Zp9vM2EbkR6Dywx6Ui\n8iJW7UK93hj8/gi8gdWq6fsiEliENxO4BasepRp6onYupC1gemCM+R1W004HcARwGlbypRarBoze\nJRr8RtjPAtwGbAIOBFKx/vG9jDUSy2sikhuLAFV47Ka6D2ON2vH7GIej+omI/Arru7YZK9mmYivV\nfu6u+2aT/ZzWz7GofmDfqX0USAfe1a4sg589LPG5wAvGmC7N4dWQ4b8hOBMr+XIL1khImcAJWC3t\nTwTujEl0KiLGmI1YIzm+AYwCjsc6joXAN8BHgbVh1JAStXOhYdsCRkSux/rQR8IARxpjttnbSAce\nxxpa6mqsk5NyrLsNFwGXAceLyMHGmKbgm1R9FYVjGZhobAa+EzCs7QoROQlr9IDpWMOWz+1bxCqY\naPxNApdjDZX6B2NMaTTjU5GJ0vEMtt0jgXsAH/B7LTyo1IC4G+sm0xa0AO+gJyJJWHXQ6rDuuKuh\ny3+OGgc8Yow5L2DeKyKyDVgI/FxEroqgWKiKATsx+jzW3+bxwCf2rIOAm4DnROQKY8zVITahvgWG\nbQIGKGBnX+ZIBL4nNwHHABcaY64PmP4V8GN7WLjvYo2uM7eXcaqe9fVYNgZMez4g+QKAMcaIyL1Y\nQxkf1qsIVTj6dBxFZDbwd2C+MebeaAameiUa37G7EJGDgJfsZf5sjHm8l7Gp6PLfYEjpZhn/naHG\nbpZRg5CI3IY1NGoZVoJ0e4xDUj37BzAR+LUxpiLEMlqcfmjwf2ca4L7OLS4kDQAAEphJREFUM40x\ni+xuLHsDhwKagBmkRCQTeBFIAvYzxmwKmP2yiKzAuoa8TESeMMasi0GYqveidi40bBMwxpifAz/v\n7foi4rTXN8BjIRZ7HCsBcySagOk3fT2WxphGEanBaua5McRim+znkb3dj+peX48jcBzgBEaKyIJO\n8zLt5/H2PAP8NnCIOBVdUTieu7DvGr2OdeJygTHmP9Hatuoz//fmmG6W8Req39S/oahoEpGbgD8B\n27GSL/qdOTSchNVK8Fci8utO83azn88SkeOAtcaYMwc0OhWJwIRKd+eoe2ONrqIGr2OBHKxunJs6\nzzTGrBeRhViJtMMATcAMLVE7Fxq2CZgoyAPisS7k6kMs45/euaCrGnwWAd/B+mIMxj9du5INXsZ+\n3t1+BPLf6UsGDrGX7S5DrQYREdkPq790CnCpMeamGIekdrXEfp4qIokhhs+c02lZNcjZ3Qj/ijWC\nzlHGmFUxDkmFz2D93zskyDz//8PxWEUj0wcqKNUrgd+ZOVg1XzrTc9ShYbT9HOq6EayuSbCzPqUa\nOqJ2LqRFeEOrxhr+FGD/EMv4p4fKWKvB43n7+fAQ84+yn78cgFhULxhjrjTGOIwxzs4Pdh7X5QHL\nfBXLeFV4RGQf4E2s5MtcY8w/YxyS6sQYUwIsBhKAUzvPF5FDgSKgzBjz6QCHp3pBRP6F1X26Bqsu\n2vIYh6QiYIwZF+x/of3/8GF7sfPtabNiGavqnl0T7XOsxNmRnefb5Q5mYSXd9Bx1cPMnz2YHDkHt\nZw9FPdv+Va8dh5hongtpAiYEY0wH1ug4AtwuIuMD54vId7GqzxvgyYGPUEXoYaAEmC4iVwTOEJFT\ngJ8CHrTK/FClfd2HIBHZG3gLq1r81VqUblDzJ8auE5EJ/okiksfO781/DXhUKmIicg3WMKi1WMmX\nZTEOSUWX/j8ceq61ny+2690BICKJwF1YrZgWGWM+i0VwKmzzgBasLiq32CN3AiAiCcDtWCMj1WDd\neFKDU3ffoVE5FxJjTE/LfGuJSBHwIdZY3u1YVcgrsAqf7YWVfHnCGKMjBgwBIrIv8DZWgaQ1wHKs\nYzsL8AJ/McZoAmYIEpHDsIaFX26MmR7jcFSY7NpMmVhNcl8i+D89g3Unt3ogY1Ndich/gLOANuBd\nwI11xzYNeAE4xehJxaAmIsdjFYkE6276NyEWXWmMuW5golLRJCIPAb/A+t68OcbhqDCJyA3AeVjf\nq59jtcTfB6vgfQlwuNZoGvxE5BfAf7FqFm5jZ1eU2Vh1JtuAHxljXo5NhMpPRGax6433KVjnM2ux\nblCANVbL/p3W6/O5kCZgemAPRX0u8AOs4aeTsC4WlgAPGmOeimF4KkIiMha4FDgayMXqp/kxcJMx\n5uPYRab6wm72Nx9NwAwpIuJjZ22fzskXf40DA4wzxmwZyNhUcCLyY+BsYBpWK9pVwAPGmLtiGpgK\ni4j8EniQnX9fwRjgfWPMEQMWmIoaEXkQKwHzf5qAGVpE5CTgHGAm1vXGFqzW+P/SmxBDh4jMxLp2\nPAgrgQZW96T5wM1ab2twCLh2CJUMEawEjDPIun06F9IEjFJKKaWUUkoppVQ/0xowSimllFJKKaWU\nUv1MEzBKKaWUUkoppZRS/UwTMEoppZRSSimllFL9TBMwSimllFJKKaWUUv1MEzBKKaWUUkoppZRS\n/UwTMEoppZRSSimllFL9TBMwSimllFJKKaWUUv1MEzBKKaWUUkoppZRS/UwTMEoppVQPRGSTiPhE\n5NBYxxKKHV/nR7OIrBaRO0VkfAximmvHcUUv1n3IXveX/RFbNInIfnas/+hhuTMDjs25AxWf6pmI\nLBWRzSKSGOtYlFJKDV+agFFKKaXCY+zHYPcs8JD9eB/IAf4ALBORQwY4FkOQ901EDrOTEPMjXXew\nEREBbgdqget6WPyMgJ9/3W9BDYCApOToWMcSJZcAxcAFsQ5EKaXU8KUJGKWUUio8EusAwmCA840x\nZ9iPY4AJwLtACvCQiDgHMJ47gCn2c+c4A5+Duche98V+iCuafgzsDfzbGFMfaiERmQLsCzQD9cA0\nEdl7YELsN4M6ORYJY8xrwGLgAhHJjXU8SimlhidNwCillFLDmDGmDvid/esYYM4A7rvaGLPGGFPT\naVaPySxjTLm9bkM/hRct5wI+4IEelvO3fnkaeLLTtKFsKCQmw/UAkAycGetAlFJKDU+agFFKKaX6\nQETiROQcEflcRBpEpEVEvhGRf4pIVpDlx9pdNzbav//Rrj/RIiK1IvKiiEyNZozGmI1AHdbF8o4u\nI5HGbq+zj4g8IyKlIuIWkToRWSsij4nI4Z2W7VIDRkQWAO/Zv/q7Ivkf8wOWC1kDRiw/F5EF9nvW\nKiLrReQOERkVIm6fiPjsn08XkU9FpElEGkXkHRE5MNz3M2Cbc7Bav7xvjNnSzXIu4OdYLUYeZGey\n5nQRSQixzo73TkTyReQeESkRkXYR2Wgfo1DrxonI30VkpYi0iUiZiDwsIsWh6vKIiFNE/iAin4hI\nvb2fchFZLCI3ikiOvdyv7PdxNNbnaWOnYzg6cDkReVBEskXkdjvudhF5IWC/KSJyiYgsE6tmUZOI\nLBGRi0QkKchr29F9TUQSRORqEVkX8Bm4REQc9rLFIvJf+7PaJiJfichPQx0n4AnAA/xeRIZTYkkp\npdQg4Yp1AEoppdRQJVbBznnAoVhdS+YDLcAhwN+BH4nIEXYCJNj6DwOnYdVqWQ3sAxyPlZiYGWq9\nXsTpxOqCBNDe29hF5DvAa1jnD4uBD4E4rNoZp2B1rQlW1yWwq8o8oBU4Gqiwf/db1cO6/porj2J1\n/ekAFgA1WN17/mjH/T1jzJfBtiUiVwEX27G/AkwHjgAOEpHDjDGfBVkvlBPs53d6WO5YIA9Yb4z5\nyH4d3wB7ACcDj3ezbjGwCOt9+BhIBw7GOkZ7BMSAvV0n8DLW+9sCvA00Yb3GRcCr9qKduw/9F/iF\nvc5HQBVW/aCJwF+xWu5UAWuBh7GOdwpWzaGmgO0E/oy9jS+ANKz3fCFQbceag5WM2xPrGPo/C0cA\n1wKn2Z/B2iDvSzzW+74H1mduNdZn+WqgSERust+vJqy/ryL7fXtERIwxpst7boypFZHFWH+Hs+z3\nSymllIoeY4w+9KEPfehDH/ro5gFswupmckin6dfb01cABQHTE4Fn7HmfdFpnrD3dB6wDxgXMi8e6\nQPYB90YYow/wAqODzDsuYP6YPsT+nj399CD7yAJmdZo2117+8k7TD7Wnv9fN63nIXuYXnab/0Z6+\nDZgSMN0B3GbP2wjEB3l/fEAlMDNgugD32PPeivA9/8he77AelnvJXu6SgGnn2dPeCbHO3ICY7wFc\nAfN2BxrseQd0Ws/fJWqD/1gHfLYeD9jm5QHzxtjTNgG5QWKZ3nm6vWzQz5s9/1cB+5oHpARZ5ml7\n/gIgPWB6ZsB7+3indQ4L2O77QFqnONuxWrGsAG4GJMhnZ203x+pme5nzI/ks6EMf+tCHPvQRzkO7\nICmllFK9YHePOAurJcGfjTFl/nnGmDaskYeagP1E5IAgm/CvtzFgvQ7gSvvXI3obWkCMeSLyc6zW\nDQAvG2M29yH2fHudN7q8GGNqjDGLI42xF86zny8zxqwM2L8POB/YgpVQOCXE+lcYY5YErGeAy+xf\nD5LIihTvhfV+rAy1gIjkA8dgJSseDpj1iD3tMBEZ080+tmAdI09AzKvs9QGO7LT8n+3nS40xmwPW\n6QD+hNXaqbM8+3mxMaay80xjzFfBpoepA/i9MWaX/dqv+RSs9+BME1Drx1h1i87ESoScGqJbmRf4\nnTGmMTBO4HWsZFwicIF9fP3uwRqtaryIFIeI198Ka2b4L1EppZQKjyZglFJKqd6ZjdUFY5sx5t3O\nM40x1VhdXMC6a9+ZhyCJDKyuFACFvYhpl5ocQDnWRX82VleUX/Ux9s/tfTwuIgdEmKzoM/tCfBzW\nxfcjnecbY9zAY/avhwbZhGFnF5zA9bZj1chJwHqvwoklBatgK9hdakL4BeDEau1T0mmfr2Gdi3U3\nJPV7xpj2INP9n5OCgJiKsVpYeYCnOq9gH9e3g2xrJdAI/MCuvRLNoaUXm+D1cQ62nz8zxqztPNNO\nri3Eeu+CDZ++2RizOsj09fbz/MCklb1NL1brKCHgfevEfyzzQ8xXSimlek0TMEoppVTvFNnP3dVp\n8c8Llkwps1tt7CKgJUDQAqtheBar+86DwF1Y9U72M8YcbXYOk9zb2C8ClgDfx+oiUi8i74vI5SIy\nrpfxRsIfd5ndoiOYjZ2W3UWIZABYXXrAajkRjkz7ub3zhX4n/uTKg0HmPWQ//7Kboq+RxBv4/njD\n3Z4xpglrRKZWrNorm0Rkq1jFln8ZqthvmDaHmB7OZ3CD/Rzs76ckyDTYWYOmp/mhjrP/fc0MMV8p\npZTqNS3Cq5RSSvVN52Km4eqSfIkCg1W7IuSIPEGWD3/jxlSIyN5YrWK+AxyIVbD0YOBSEfm9MSZY\noiHaevueR1Od/ZwgIq5gSRgR2R+rXgvA30TknE6L+M/DxmB1JQpWzLc3n5Pu3p+g2zPGPCci72AV\n9T0YOAirQPDJwFwROTiwBU8EWvsQa3d6el96+/eVbj/XdbuUUkop1QvaAkYppZTqHf/FaHctP8bb\nz6X9HEukeh27scw3xlxsjDkUq8vOhVjJhP+ISFrUo93JH3ehiMSHWGZA3nO7pkmL/WtOiMXOCPh5\nNrB/p8ecEMv2lv81F4o19HUwY0OtbIypN8b8zxhzpjFmCtYISPOxEkTXRSG+QP5jOaGbZWLx9+Pv\nglYxgPtUSin1LaEJGKWUUqp3FmF1ZxglIl0K5opINtboQwZrlJfBJGqxG2NajDHXY10kJwCTw9i/\nv/tQRC1xjTGlWN1SnMDPOs8XkTjgp/avCyLZdi8txqonskeQWJKB07Hew4ONMc5gj4B1TxCRPnV7\nMcZsxery4wJODRJTFlbLpXC3twGrSxJYIwwF6tUxDPCh/byfiEzqPFNEpmANLe4FPujlPnrDfzzC\nLSitlFJKhU0TMEoppVR4dukqYY8WdLf9620iMtI/T0QSseqvpGAVGf10wKIMQ29jF5Hzg41IY3dL\nKsDq9rE1jBD8rR8m9qKQ783289UisltADE6sobWLsYZIfjbC7fbGe/bz/kHmnQqkApuMMR+H2oA9\notEiIAn4SRRi+rf9fG1gMV27xdDtWMd1FyKyl4icbh/7zo63nzvXciklRPIpHHY3uWexzkXvERF/\n1x/sRNQ99vafthNvA8V/LOcP4D6VUkp9S2gNGKWUUio8wYqkXgb4a6KsFZH5WDUvDgZGYl20/jTI\nev0lkuGdexP7pcD1IrISa7jedqyEh3+o6uvs0X26ZYzZIiJLsIb6/UpEFtvbWmWMubGHde8UkQOB\nHwPLROR9oAarFs04++dT7RGRIhXp8NgvApcDR7GzpYifv0vRo2Fs5xGsLkpnAHdGGENntwHftR8r\n7ePajHWMEoD/YY3MFFjEeCzwBNBiH4sSIB7r+IzDKkx7eaf9PI810tRjIvI2Vs0UA/zdGFMTZqxn\nYdXIOQzYYB9LgMOxiuAuBc4Oc1t9ZrcQmglsiWBIdaWUUips2gJGKaWU6pkhSLFQe3jg7wJ/Br7B\nupA8Duti9DpgljFm04BFGUFB017G/keskXt89vInYLV8eQk42hhzSZB4QsX0Q+BpYATwI6zRgo4J\nZ11jzE+xkgifYyVeTrRn3QnMMMYsCrHP7nQXa/AVjFkKfAYcIiJj/NNFZAJWEVtDkOGyg3gCa+jo\nmSKyZ5jxhHpvvFjH8WKsEY+OxBrGeQFWws1fLLgqYLVPsUa4eh8YhXVcj8DqpnYjMC1IQuIOrCRe\nKXAsVvLoDKxWPyHj6xRrNVaLE/92vgccjZX8uxg40BjTuRhuT9sN530LNf8nWDcn7+lhH0oppVSv\niDGDYSABpZRSSqmhR0ROx0qgXG2MuSLW8XTHLsy7HKtOz2xjzJIYhzSoiMgirPdmnDGmqqfllVJK\nqUhpCxillFJKqV4yxjwFLAT+1NciutFi13SJ6zQtBasGzGTgK02+7EpEfoDV/eh6Tb4opZTqL9oC\nRimllFKqD0RkH6xuPNcZYy4eBPF8hFUcdxlQDuQCM7CGWK4FjtIEzK7s2jfZwG52kWqllFIq6jQB\no5RSSik1jIjIz7HqmeyJlVQwWKNTvQ3cYI9ApJRSSqkBpgkYpZRSSimllFJKqX6mNWCUUkoppZRS\nSiml+pkmYJRSSimllFJKKaX6mSZglFJKKaWUUkoppfqZJmCUUkoppZRSSiml+pkmYJRS6v/bsWMB\nAAAAgEH+1qPYVxgBAADMBAwAAADALFpN3yzKKaVTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111bcc750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_modehist(coord_merge, norm_factor=0.01):\n",
    "    f1, ax = plt.subplots(1)\n",
    "    f1.set_size_inches(18.5, 5.5)\n",
    "    \n",
    "    # Histogram and plot the position distribution of each mode.\n",
    "    for coordlabel, v in coord_merge.groupby(\"ModeLabel\"):\n",
    "        histogram, edges = np.histogram(v[\"Z\"], bins=300, range=[-20,20], normed=False)                                              \n",
    "        ax.fill_between(edges[1:], 0, histogram*norm_factor,\n",
    "                                              linewidth=0.5,\n",
    "                                              facecolor=mode_color_dict[coordlabel],\n",
    "                                              alpha=0.75)\n",
    "        \n",
    "    # Show the sum of all modes too...\n",
    "    histogram, edges = np.histogram(coord_merge[\"Z\"], bins=300, range=[-20,20], normed=False)\n",
    "    ax.plot(edges[1:], histogram*norm_factor, linewidth=2.0, color=\"black\")\n",
    "    \n",
    "    ax.set_xlim([-8,10])\n",
    "    ax.set_ylim([0,1])\n",
    "    ax.grid(True)\n",
    "    ax.set_xlabel(\"Ion Position (Angstrom)\")\n",
    "    ax.set_ylabel(\"Probability (arb. units)\")\n",
    "    \n",
    "plot_modehist(coord_merge)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 14) Studying protein flexibility in the channel\n",
    "\n",
    "![Ion Channels Are Flexible](assets/NavAbSideViewDunking.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Frame</th>\n",
       "      <th>Time</th>\n",
       "      <th>S1-Chi2</th>\n",
       "      <th>S2-Chi2</th>\n",
       "      <th>S3-Chi2</th>\n",
       "      <th>S4-Chi2</th>\n",
       "      <th>TrajNum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>500</td>\n",
       "      <td>10</td>\n",
       "      <td>73.892</td>\n",
       "      <td>36.320</td>\n",
       "      <td>301.221</td>\n",
       "      <td>301.673</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1000</td>\n",
       "      <td>20</td>\n",
       "      <td>333.938</td>\n",
       "      <td>43.428</td>\n",
       "      <td>306.579</td>\n",
       "      <td>79.402</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1499</th>\n",
       "      <td>1500</td>\n",
       "      <td>30</td>\n",
       "      <td>303.713</td>\n",
       "      <td>286.884</td>\n",
       "      <td>303.528</td>\n",
       "      <td>303.080</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>2000</td>\n",
       "      <td>40</td>\n",
       "      <td>323.949</td>\n",
       "      <td>299.396</td>\n",
       "      <td>312.750</td>\n",
       "      <td>291.897</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2499</th>\n",
       "      <td>2500</td>\n",
       "      <td>50</td>\n",
       "      <td>300.581</td>\n",
       "      <td>293.666</td>\n",
       "      <td>85.650</td>\n",
       "      <td>287.496</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2999</th>\n",
       "      <td>3000</td>\n",
       "      <td>60</td>\n",
       "      <td>301.213</td>\n",
       "      <td>312.540</td>\n",
       "      <td>95.065</td>\n",
       "      <td>292.090</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3499</th>\n",
       "      <td>3500</td>\n",
       "      <td>70</td>\n",
       "      <td>310.511</td>\n",
       "      <td>48.897</td>\n",
       "      <td>294.006</td>\n",
       "      <td>307.242</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3999</th>\n",
       "      <td>4000</td>\n",
       "      <td>80</td>\n",
       "      <td>302.491</td>\n",
       "      <td>79.076</td>\n",
       "      <td>57.945</td>\n",
       "      <td>295.435</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4499</th>\n",
       "      <td>4500</td>\n",
       "      <td>90</td>\n",
       "      <td>289.829</td>\n",
       "      <td>50.219</td>\n",
       "      <td>290.140</td>\n",
       "      <td>306.218</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4999</th>\n",
       "      <td>5000</td>\n",
       "      <td>100</td>\n",
       "      <td>76.211</td>\n",
       "      <td>81.412</td>\n",
       "      <td>301.120</td>\n",
       "      <td>307.405</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5499</th>\n",
       "      <td>5500</td>\n",
       "      <td>110</td>\n",
       "      <td>70.271</td>\n",
       "      <td>54.333</td>\n",
       "      <td>104.022</td>\n",
       "      <td>308.461</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5999</th>\n",
       "      <td>6000</td>\n",
       "      <td>120</td>\n",
       "      <td>163.007</td>\n",
       "      <td>93.134</td>\n",
       "      <td>294.282</td>\n",
       "      <td>285.026</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6499</th>\n",
       "      <td>6500</td>\n",
       "      <td>130</td>\n",
       "      <td>313.007</td>\n",
       "      <td>76.567</td>\n",
       "      <td>42.591</td>\n",
       "      <td>264.991</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6999</th>\n",
       "      <td>7000</td>\n",
       "      <td>140</td>\n",
       "      <td>288.247</td>\n",
       "      <td>83.455</td>\n",
       "      <td>89.607</td>\n",
       "      <td>72.417</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7499</th>\n",
       "      <td>7500</td>\n",
       "      <td>150</td>\n",
       "      <td>317.561</td>\n",
       "      <td>64.148</td>\n",
       "      <td>72.982</td>\n",
       "      <td>71.456</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7999</th>\n",
       "      <td>8000</td>\n",
       "      <td>160</td>\n",
       "      <td>297.075</td>\n",
       "      <td>86.952</td>\n",
       "      <td>79.759</td>\n",
       "      <td>67.109</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8499</th>\n",
       "      <td>8500</td>\n",
       "      <td>170</td>\n",
       "      <td>308.306</td>\n",
       "      <td>85.635</td>\n",
       "      <td>59.951</td>\n",
       "      <td>74.533</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8999</th>\n",
       "      <td>9000</td>\n",
       "      <td>180</td>\n",
       "      <td>307.104</td>\n",
       "      <td>90.101</td>\n",
       "      <td>46.185</td>\n",
       "      <td>57.678</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9499</th>\n",
       "      <td>9500</td>\n",
       "      <td>190</td>\n",
       "      <td>320.471</td>\n",
       "      <td>74.893</td>\n",
       "      <td>64.181</td>\n",
       "      <td>65.484</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>10000</td>\n",
       "      <td>200</td>\n",
       "      <td>299.951</td>\n",
       "      <td>71.249</td>\n",
       "      <td>91.372</td>\n",
       "      <td>56.680</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10499</th>\n",
       "      <td>10500</td>\n",
       "      <td>210</td>\n",
       "      <td>305.593</td>\n",
       "      <td>66.274</td>\n",
       "      <td>35.463</td>\n",
       "      <td>91.457</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10999</th>\n",
       "      <td>11000</td>\n",
       "      <td>220</td>\n",
       "      <td>328.312</td>\n",
       "      <td>43.097</td>\n",
       "      <td>86.635</td>\n",
       "      <td>86.317</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11499</th>\n",
       "      <td>11500</td>\n",
       "      <td>230</td>\n",
       "      <td>304.565</td>\n",
       "      <td>58.447</td>\n",
       "      <td>68.678</td>\n",
       "      <td>93.954</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11999</th>\n",
       "      <td>12000</td>\n",
       "      <td>240</td>\n",
       "      <td>322.191</td>\n",
       "      <td>80.706</td>\n",
       "      <td>94.386</td>\n",
       "      <td>67.690</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12499</th>\n",
       "      <td>12500</td>\n",
       "      <td>250</td>\n",
       "      <td>301.365</td>\n",
       "      <td>70.399</td>\n",
       "      <td>29.812</td>\n",
       "      <td>72.486</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12999</th>\n",
       "      <td>13000</td>\n",
       "      <td>260</td>\n",
       "      <td>303.482</td>\n",
       "      <td>66.694</td>\n",
       "      <td>41.102</td>\n",
       "      <td>74.765</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13499</th>\n",
       "      <td>13500</td>\n",
       "      <td>270</td>\n",
       "      <td>297.614</td>\n",
       "      <td>82.191</td>\n",
       "      <td>39.280</td>\n",
       "      <td>87.243</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13999</th>\n",
       "      <td>14000</td>\n",
       "      <td>280</td>\n",
       "      <td>306.515</td>\n",
       "      <td>66.140</td>\n",
       "      <td>52.955</td>\n",
       "      <td>95.696</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14499</th>\n",
       "      <td>14500</td>\n",
       "      <td>290</td>\n",
       "      <td>298.790</td>\n",
       "      <td>62.217</td>\n",
       "      <td>64.935</td>\n",
       "      <td>74.210</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14999</th>\n",
       "      <td>15000</td>\n",
       "      <td>300</td>\n",
       "      <td>283.104</td>\n",
       "      <td>74.810</td>\n",
       "      <td>54.048</td>\n",
       "      <td>77.710</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985518</th>\n",
       "      <td>35500</td>\n",
       "      <td>710</td>\n",
       "      <td>102.368</td>\n",
       "      <td>92.612</td>\n",
       "      <td>69.926</td>\n",
       "      <td>319.643</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986018</th>\n",
       "      <td>36000</td>\n",
       "      <td>720</td>\n",
       "      <td>91.484</td>\n",
       "      <td>87.907</td>\n",
       "      <td>75.811</td>\n",
       "      <td>306.657</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986518</th>\n",
       "      <td>36500</td>\n",
       "      <td>730</td>\n",
       "      <td>83.440</td>\n",
       "      <td>54.905</td>\n",
       "      <td>44.640</td>\n",
       "      <td>308.457</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987018</th>\n",
       "      <td>37000</td>\n",
       "      <td>740</td>\n",
       "      <td>78.425</td>\n",
       "      <td>87.425</td>\n",
       "      <td>81.528</td>\n",
       "      <td>285.311</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987518</th>\n",
       "      <td>37500</td>\n",
       "      <td>750</td>\n",
       "      <td>84.823</td>\n",
       "      <td>43.080</td>\n",
       "      <td>68.876</td>\n",
       "      <td>296.982</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988018</th>\n",
       "      <td>38000</td>\n",
       "      <td>760</td>\n",
       "      <td>75.991</td>\n",
       "      <td>85.365</td>\n",
       "      <td>76.800</td>\n",
       "      <td>292.664</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988518</th>\n",
       "      <td>38500</td>\n",
       "      <td>770</td>\n",
       "      <td>74.315</td>\n",
       "      <td>46.252</td>\n",
       "      <td>59.794</td>\n",
       "      <td>308.933</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989018</th>\n",
       "      <td>39000</td>\n",
       "      <td>780</td>\n",
       "      <td>76.080</td>\n",
       "      <td>86.105</td>\n",
       "      <td>74.900</td>\n",
       "      <td>302.890</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989518</th>\n",
       "      <td>39500</td>\n",
       "      <td>790</td>\n",
       "      <td>88.302</td>\n",
       "      <td>85.258</td>\n",
       "      <td>75.507</td>\n",
       "      <td>279.307</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990018</th>\n",
       "      <td>40000</td>\n",
       "      <td>800</td>\n",
       "      <td>89.257</td>\n",
       "      <td>82.913</td>\n",
       "      <td>68.970</td>\n",
       "      <td>300.222</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990518</th>\n",
       "      <td>40500</td>\n",
       "      <td>810</td>\n",
       "      <td>86.214</td>\n",
       "      <td>85.340</td>\n",
       "      <td>75.663</td>\n",
       "      <td>305.257</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991018</th>\n",
       "      <td>41000</td>\n",
       "      <td>820</td>\n",
       "      <td>89.604</td>\n",
       "      <td>52.468</td>\n",
       "      <td>301.446</td>\n",
       "      <td>310.369</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991518</th>\n",
       "      <td>41500</td>\n",
       "      <td>830</td>\n",
       "      <td>53.822</td>\n",
       "      <td>82.509</td>\n",
       "      <td>63.840</td>\n",
       "      <td>311.845</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992018</th>\n",
       "      <td>42000</td>\n",
       "      <td>840</td>\n",
       "      <td>70.234</td>\n",
       "      <td>86.424</td>\n",
       "      <td>57.878</td>\n",
       "      <td>311.815</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992518</th>\n",
       "      <td>42500</td>\n",
       "      <td>850</td>\n",
       "      <td>76.504</td>\n",
       "      <td>284.048</td>\n",
       "      <td>24.774</td>\n",
       "      <td>303.515</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993018</th>\n",
       "      <td>43000</td>\n",
       "      <td>860</td>\n",
       "      <td>81.789</td>\n",
       "      <td>73.887</td>\n",
       "      <td>69.380</td>\n",
       "      <td>288.855</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993518</th>\n",
       "      <td>43500</td>\n",
       "      <td>870</td>\n",
       "      <td>93.973</td>\n",
       "      <td>92.899</td>\n",
       "      <td>64.031</td>\n",
       "      <td>323.260</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994018</th>\n",
       "      <td>44000</td>\n",
       "      <td>880</td>\n",
       "      <td>84.656</td>\n",
       "      <td>79.774</td>\n",
       "      <td>301.890</td>\n",
       "      <td>299.074</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994518</th>\n",
       "      <td>44500</td>\n",
       "      <td>890</td>\n",
       "      <td>82.968</td>\n",
       "      <td>74.821</td>\n",
       "      <td>45.359</td>\n",
       "      <td>61.996</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995018</th>\n",
       "      <td>45000</td>\n",
       "      <td>900</td>\n",
       "      <td>85.350</td>\n",
       "      <td>78.114</td>\n",
       "      <td>25.645</td>\n",
       "      <td>63.815</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995518</th>\n",
       "      <td>45500</td>\n",
       "      <td>910</td>\n",
       "      <td>89.989</td>\n",
       "      <td>97.296</td>\n",
       "      <td>25.015</td>\n",
       "      <td>68.574</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996018</th>\n",
       "      <td>46000</td>\n",
       "      <td>920</td>\n",
       "      <td>84.791</td>\n",
       "      <td>94.393</td>\n",
       "      <td>67.805</td>\n",
       "      <td>79.544</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996518</th>\n",
       "      <td>46500</td>\n",
       "      <td>930</td>\n",
       "      <td>85.117</td>\n",
       "      <td>79.320</td>\n",
       "      <td>68.383</td>\n",
       "      <td>66.900</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997018</th>\n",
       "      <td>47000</td>\n",
       "      <td>940</td>\n",
       "      <td>89.345</td>\n",
       "      <td>81.332</td>\n",
       "      <td>66.651</td>\n",
       "      <td>70.874</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997518</th>\n",
       "      <td>47500</td>\n",
       "      <td>950</td>\n",
       "      <td>79.116</td>\n",
       "      <td>70.404</td>\n",
       "      <td>75.621</td>\n",
       "      <td>302.797</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998018</th>\n",
       "      <td>48000</td>\n",
       "      <td>960</td>\n",
       "      <td>101.900</td>\n",
       "      <td>106.086</td>\n",
       "      <td>46.407</td>\n",
       "      <td>71.168</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998518</th>\n",
       "      <td>48500</td>\n",
       "      <td>970</td>\n",
       "      <td>73.319</td>\n",
       "      <td>77.642</td>\n",
       "      <td>11.266</td>\n",
       "      <td>73.970</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999018</th>\n",
       "      <td>49000</td>\n",
       "      <td>980</td>\n",
       "      <td>73.101</td>\n",
       "      <td>82.179</td>\n",
       "      <td>44.331</td>\n",
       "      <td>54.179</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999518</th>\n",
       "      <td>49500</td>\n",
       "      <td>990</td>\n",
       "      <td>76.094</td>\n",
       "      <td>95.740</td>\n",
       "      <td>313.247</td>\n",
       "      <td>64.743</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000018</th>\n",
       "      <td>50000</td>\n",
       "      <td>1000</td>\n",
       "      <td>63.893</td>\n",
       "      <td>83.593</td>\n",
       "      <td>46.107</td>\n",
       "      <td>62.901</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2000 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Frame  Time  S1-Chi2  S2-Chi2  S3-Chi2  S4-Chi2  TrajNum\n",
       "499        500    10   73.892   36.320  301.221  301.673        1\n",
       "999       1000    20  333.938   43.428  306.579   79.402        1\n",
       "1499      1500    30  303.713  286.884  303.528  303.080        1\n",
       "1999      2000    40  323.949  299.396  312.750  291.897        1\n",
       "2499      2500    50  300.581  293.666   85.650  287.496        1\n",
       "2999      3000    60  301.213  312.540   95.065  292.090        1\n",
       "3499      3500    70  310.511   48.897  294.006  307.242        1\n",
       "3999      4000    80  302.491   79.076   57.945  295.435        1\n",
       "4499      4500    90  289.829   50.219  290.140  306.218        1\n",
       "4999      5000   100   76.211   81.412  301.120  307.405        1\n",
       "5499      5500   110   70.271   54.333  104.022  308.461        1\n",
       "5999      6000   120  163.007   93.134  294.282  285.026        1\n",
       "6499      6500   130  313.007   76.567   42.591  264.991        1\n",
       "6999      7000   140  288.247   83.455   89.607   72.417        1\n",
       "7499      7500   150  317.561   64.148   72.982   71.456        1\n",
       "7999      8000   160  297.075   86.952   79.759   67.109        1\n",
       "8499      8500   170  308.306   85.635   59.951   74.533        1\n",
       "8999      9000   180  307.104   90.101   46.185   57.678        1\n",
       "9499      9500   190  320.471   74.893   64.181   65.484        1\n",
       "9999     10000   200  299.951   71.249   91.372   56.680        1\n",
       "10499    10500   210  305.593   66.274   35.463   91.457        1\n",
       "10999    11000   220  328.312   43.097   86.635   86.317        1\n",
       "11499    11500   230  304.565   58.447   68.678   93.954        1\n",
       "11999    12000   240  322.191   80.706   94.386   67.690        1\n",
       "12499    12500   250  301.365   70.399   29.812   72.486        1\n",
       "12999    13000   260  303.482   66.694   41.102   74.765        1\n",
       "13499    13500   270  297.614   82.191   39.280   87.243        1\n",
       "13999    14000   280  306.515   66.140   52.955   95.696        1\n",
       "14499    14500   290  298.790   62.217   64.935   74.210        1\n",
       "14999    15000   300  283.104   74.810   54.048   77.710        1\n",
       "...        ...   ...      ...      ...      ...      ...      ...\n",
       "985518   35500   710  102.368   92.612   69.926  319.643       20\n",
       "986018   36000   720   91.484   87.907   75.811  306.657       20\n",
       "986518   36500   730   83.440   54.905   44.640  308.457       20\n",
       "987018   37000   740   78.425   87.425   81.528  285.311       20\n",
       "987518   37500   750   84.823   43.080   68.876  296.982       20\n",
       "988018   38000   760   75.991   85.365   76.800  292.664       20\n",
       "988518   38500   770   74.315   46.252   59.794  308.933       20\n",
       "989018   39000   780   76.080   86.105   74.900  302.890       20\n",
       "989518   39500   790   88.302   85.258   75.507  279.307       20\n",
       "990018   40000   800   89.257   82.913   68.970  300.222       20\n",
       "990518   40500   810   86.214   85.340   75.663  305.257       20\n",
       "991018   41000   820   89.604   52.468  301.446  310.369       20\n",
       "991518   41500   830   53.822   82.509   63.840  311.845       20\n",
       "992018   42000   840   70.234   86.424   57.878  311.815       20\n",
       "992518   42500   850   76.504  284.048   24.774  303.515       20\n",
       "993018   43000   860   81.789   73.887   69.380  288.855       20\n",
       "993518   43500   870   93.973   92.899   64.031  323.260       20\n",
       "994018   44000   880   84.656   79.774  301.890  299.074       20\n",
       "994518   44500   890   82.968   74.821   45.359   61.996       20\n",
       "995018   45000   900   85.350   78.114   25.645   63.815       20\n",
       "995518   45500   910   89.989   97.296   25.015   68.574       20\n",
       "996018   46000   920   84.791   94.393   67.805   79.544       20\n",
       "996518   46500   930   85.117   79.320   68.383   66.900       20\n",
       "997018   47000   940   89.345   81.332   66.651   70.874       20\n",
       "997518   47500   950   79.116   70.404   75.621  302.797       20\n",
       "998018   48000   960  101.900  106.086   46.407   71.168       20\n",
       "998518   48500   970   73.319   77.642   11.266   73.970       20\n",
       "999018   49000   980   73.101   82.179   44.331   54.179       20\n",
       "999518   49500   990   76.094   95.740  313.247   64.743       20\n",
       "1000018  50000  1000   63.893   83.593   46.107   62.901       20\n",
       "\n",
       "[2000 rows x 7 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dihe_ts = pd.read_pickle(\"assets/NAVAB_XTAL_PD-NORES-0kcal-CHARMM_NONB_WT_SOD150_DEMO_DIHE.pkl\")\n",
    "dihe_ts[[\"Frame\",\"Time\",\"S1-Chi2\",\"S2-Chi2\",\"S3-Chi2\",\"S4-Chi2\",\"TrajNum\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ptagrBuZ9Zx7wqknP5zi/qKxRl+6DPWk7g3ZPH7TXU1U7r7vqvlU/MxrIr9X4mgUtty+c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\niIg0peChiIiIiIiIiIiINPX/AcyLR8PBbPyCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111fc8e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_glu_timeseries(dihe_ts, traj=7):\n",
    "    fig = plt.figure(figsize=(18.5, 5.5))\n",
    "    gs = mpl.gridspec.GridSpec(1, 2, width_ratios=[10, 1]) \n",
    "    ax0 = plt.subplot(gs[0])\n",
    "    ax1 = plt.subplot(gs[1])\n",
    "    \n",
    "    ax1.tick_params(labelbottom='off',labelleft='off')\n",
    "    ax1.set_ylim([0,360])\n",
    "    ax1.grid(True)\n",
    "    \n",
    "    plotcols = [\"S1-Chi2\",\"S2-Chi2\",\"S3-Chi2\",\"S4-Chi2\"]\n",
    "    plotrgb = [\"red\",\"blue\",\"green\",\"orange\"]\n",
    "    \n",
    "    dihe_subset = dihe_ts[dihe_ts[\"TrajNum\"]==traj]\n",
    "    \n",
    "    dihe_plotargs = dict(ylim=[0,360], kind=\"scatter\", ax=ax0, marker=\"o\", lw=0, s=10, xlim=[0,1000], grid=True)\n",
    "    for column, color in zip(plotcols, plotrgb):\n",
    "        dihe_subset.plot(\"Time\", column, color=color, **dihe_plotargs)\n",
    "        ax1.hist(dihe_subset[column].values, bins=100, orientation='horizontal', alpha=0.5, color=color, lw=0)\n",
    "    \n",
    "    ax0.set_ylabel(\"Glutamic Acid \\n Dihedral Angle (degrees)\")\n",
    "    ax0.set_xlabel(\"Time (ns)\")\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    \n",
    "plot_glu_timeseries(dihe_ts, 7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 15) Restricting protein conformations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Unpickle some dataframes of restricted GLU simulations\n",
    "coord_merge2 = pd.read_pickle(\"assets/NAVAB_XTAL_PD-DIHEREST-CHARMM_NONB_WT_SOD150_DEMO_MERGE.pkl\")\n",
    "\n",
    "# Unpickle some dihedral angle data for those simulations\n",
    "dihe_ts2 = pd.read_pickle(\"assets/NAVAB_XTAL_PD-DIHEREST-CHARMM_NONB_WT_SOD150_DEMO_DIHE.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wL/BnYC3gucDmwA7A9sDqFKc8Hw98OjMf6Pa5g8y9/5IkSZIkqRVzHqpunX5j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\nIiIiIiIiItLQ/wd171xaxPLqDQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112d7d650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_glu_timeseries(dihe_ts2, 7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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31RIkEZHgDB8borO5Ng3dK7G6vZPB/v64wxARaXjm7nHHkDhm5vp3EQnXlz73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\nKs7MGkpSbFyb92W11bIksoarbrnBjxE2bf++/bzz3IuMjEplTFY2Fou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Ep/86VUsbBmVr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\n/T9HNwGgQX8lkAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11399f110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_modehist(coord_merge2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "By restricting protein flexibility we totally disrupted ion binding, what's going on? Keep an eye out for our coming papers..."
   ]
  },
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    "### 16) Acknowledgements\n",
    "\n",
    "Thanks to all members of the Régis Pomès laboratory, especially Nilmadhab Chakrabarti. Thanks to collaborators in the Catterall and Zheng laboratories. Thanks to the Pande Laboratory (and collaborators) for driving structural biology further using Python (see http://www.omnia.md). Thanks to the Fundamentals of Neuroscience MOOC for neuron images (https://www.mcb80x.org/).\n",
    "\n",
    "|  ![title](assets/ThanksCC.png) | ![title](assets/ThanksCIHR.jpg) | ![title](assets/ThanksUofT.png) |\n",
    "|:-:|:-:|:-:|\n",
    "|  ![title](assets/ThanksSickKids.png) | ![title](assets/ThanksPyCon.png) | ![title](assets/ThanksOpenMM.png)  |"
   ]
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