Pandas Particle Grouping

notebook.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:e7aad82d7e6a200e7cb5f47fb8a0596598609da8577c1d4e1ee3a6299fd236a8"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline\n",
      "import pprint\n",
      "import numpy as np\n",
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.read_csv(\"./trackingbac_track.csv\")\n",
      "# Rename.\n",
      "df.columns = [\"timestamp\", \"particle no\", \"x\", \"y\", \"field strength\", \"field direction\", \"zoom id\"]\n",
      "df[:10]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>timestamp</th>\n",
        "      <th>particle no</th>\n",
        "      <th>x</th>\n",
        "      <th>y</th>\n",
        "      <th>field strength</th>\n",
        "      <th>field direction</th>\n",
        "      <th>zoom id</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 446</td>\n",
        "      <td> 0</td>\n",
        "      <td>  89</td>\n",
        "      <td> 236</td>\n",
        "      <td> 1.8</td>\n",
        "      <td> 147.9090</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 446</td>\n",
        "      <td> 1</td>\n",
        "      <td>  46</td>\n",
        "      <td> 203</td>\n",
        "      <td> 1.8</td>\n",
        "      <td> 338.5450</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 446</td>\n",
        "      <td> 2</td>\n",
        "      <td> 450</td>\n",
        "      <td> 452</td>\n",
        "      <td> 1.8</td>\n",
        "      <td>  38.8182</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 446</td>\n",
        "      <td> 3</td>\n",
        "      <td> 553</td>\n",
        "      <td> 429</td>\n",
        "      <td> 1.8</td>\n",
        "      <td>  82.4545</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 446</td>\n",
        "      <td> 4</td>\n",
        "      <td> 632</td>\n",
        "      <td> 169</td>\n",
        "      <td> 1.8</td>\n",
        "      <td> 102.2730</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> 446</td>\n",
        "      <td> 5</td>\n",
        "      <td> 464</td>\n",
        "      <td> 288</td>\n",
        "      <td> 1.8</td>\n",
        "      <td> 102.2730</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td> 446</td>\n",
        "      <td> 6</td>\n",
        "      <td> 374</td>\n",
        "      <td> 248</td>\n",
        "      <td> 1.8</td>\n",
        "      <td>  63.3636</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td> 446</td>\n",
        "      <td> 7</td>\n",
        "      <td> 298</td>\n",
        "      <td> 261</td>\n",
        "      <td> 1.8</td>\n",
        "      <td> 167.7270</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td> 446</td>\n",
        "      <td> 8</td>\n",
        "      <td> 138</td>\n",
        "      <td> 349</td>\n",
        "      <td> 1.8</td>\n",
        "      <td> 317.7270</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td> 446</td>\n",
        "      <td> 9</td>\n",
        "      <td> 509</td>\n",
        "      <td> 252</td>\n",
        "      <td> 1.8</td>\n",
        "      <td>  13.2727</td>\n",
        "      <td> 20</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>10 rows \u00d7 7 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "   timestamp  particle no    x    y  field strength  field direction  zoom id\n",
        "0        446            0   89  236             1.8         147.9090       20\n",
        "1        446            1   46  203             1.8         338.5450       20\n",
        "2        446            2  450  452             1.8          38.8182       20\n",
        "3        446            3  553  429             1.8          82.4545       20\n",
        "4        446            4  632  169             1.8         102.2730       20\n",
        "5        446            5  464  288             1.8         102.2730       20\n",
        "6        446            6  374  248             1.8          63.3636       20\n",
        "7        446            7  298  261             1.8         167.7270       20\n",
        "8        446            8  138  349             1.8         317.7270       20\n",
        "9        446            9  509  252             1.8          13.2727       20\n",
        "\n",
        "[10 rows x 7 columns]"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "grouped = df.groupby([\"particle no\", \"field strength\"])\n",
      "print \"Available groups:\"\n",
      "pprint.pprint(sorted(grouped.groups.keys()))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Available groups:\n",
        "[(0, 1.8),\n",
        " (1, 1.8),\n",
        " (2, 1.8),\n",
        " (3, 1.8),\n",
        " (4, 1.8),\n",
        " (5, 1.8),\n",
        " (6, 1.8),\n",
        " (7, 1.8),\n",
        " (8, 1.8),\n",
        " (9, 1.8),\n",
        " (10, 1.8),\n",
        " (11, 1.8),\n",
        " (12, 1.8)]\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for group_name, group in grouped:\n",
      "    x = group[\"x\"]\n",
      "    y = group[\"y\"]\n",
      "    time = group[\"timestamp\"]\n",
      "    \n",
      "    if np.abs(np.diff(x)).sum() + np.abs(np.diff(y)).sum() < 1000:\n",
      "        continue\n",
      "        \n",
      "    group.plot(x=\"x\", y=\"y\", title=group_name)\n",
      "    plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x1137da8d0>"
       ]
      }
     ],
     "prompt_number": 43
    }
   ],
   "metadata": {}
  }
 ]
}