{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Updating data in plots\n",
    "#### Data used in the following examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = (1..600).map { |i| i/100.0 }\n",
    "y = x.map { |xx| Math.sin(xx ** 2.3) * Math.exp(-xx) }\n",
    "nil"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Updating data stored in file\n",
    "First lets generate a file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1..300"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "File.open('tons_of_data', 'w') { |f| (1..300).each { |i| f.puts \"#{x[i]} #{y[i]}\" } }"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and plot it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "#<File:tons.png>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "require 'pilot-gnuplot'\n",
    "include Gnuplot\n",
    "\n",
    "graph = Plot.new(['tons_of_data', title: 'Tons of data', with: 'lines'])\n",
    "graph.to_png('tons.png')\n",
    "File.open('tons.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can just append file and replot out graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "#<File:tons.png>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "File.open('tons_of_data', 'a') { |f| (301..600).each { |i| f.puts \"#{x[i]} #{y[i]}\" } }\n",
    "\n",
    "graph.to_png('tons.png')\n",
    "File.open('tons.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Updating data given as points array\n",
    "##### 1. Data stored in memory and piped to gnuplot in here-doc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "#<File:updatable.png>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x0 = x[0..200]\n",
    "y0 = y[0..200]\n",
    "updatable_plot = Plot.new([[x0,y0], with: 'lines', title: 'Before update'])\n",
    "updatable_plot.to_png('updatable.png')\n",
    "File.open('updatable.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "#<File:updated.png>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x1 = x[201..600]\n",
    "y1 = y[201..600]\n",
    "updated_plot = updatable_plot.update_dataset(data: [x1,y1], title: 'After update')\n",
    "updated_plot.to_png('updated.png')\n",
    "File.open('updated.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This way is expensive because data is piped to gnuplot each time you want to replot it, but updating data does not affect original Plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "#<File:updatable_new.png>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "updatable_plot.to_png('updatable_new.png')\n",
    "File.open('updatable_new.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 2. Data stored in temporary file and its name is piped to gnuplot\n",
    "Dataset boolean option 'file' corresponds to using temporary file for storage data being plotted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "#<File:updatable_file.png>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x0 = x[0..400]\n",
    "y0 = y[0..400]\n",
    "updatable_file_plot = Plot.new([[x0,y0], with: 'lines', title: 'Before update', file: true])\n",
    "updatable_file_plot.to_png('updatable_file.png')\n",
    "File.open('updatable_file.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "#<File:updated_file.png>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x1 = x[401..600]\n",
    "y1 = y[401..600]\n",
    "updated_file_plot = updatable_file_plot.update_dataset(data: [x1,y1], title: 'After update')\n",
    "updated_file_plot.to_png('updated_file.png')\n",
    "File.open('updated_file.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Be careful**: updating data stored in temp file **affects** original Plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "#<File:updatable_file_after.png>"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "updatable_file_plot.to_png('updatable_file_after.png')\n",
    "File.open('updatable_file_after.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Ruby 2.1.2",
   "language": "ruby",
   "name": "ruby"
  },
  "language_info": {
   "file_extension": "rb",
   "mimetype": "application/x-ruby",
   "name": "ruby",
   "version": "2.1.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}