scratch_AV.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "import il_tutorial.cost_graphs as cg\n",
    "from IPython.display import HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script>\n",
       "code_show=true; \n",
       "function code_toggle() {\n",
       " if (code_show){\n",
       " $('div.input').hide();\n",
       " } else {\n",
       " $('div.input').show();\n",
       " }\n",
       " code_show = !code_show\n",
       "} \n",
       "$( document ).ready(code_toggle);\n",
       "</script>\n",
       "The raw code for this IPython notebook is by default hidden for easier reading.\n",
       "To toggle on/off the raw code, click <a href=\"javascript:code_toggle()\">here</a>."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTML('''<script>\n",
    "code_show=true; \n",
    "function code_toggle() {\n",
    " if (code_show){\n",
    " $('div.input').hide();\n",
    " } else {\n",
    " $('div.input').show();\n",
    " }\n",
    " code_show = !code_show\n",
    "} \n",
    "$( document ).ready(code_toggle);\n",
    "</script>\n",
    "The raw code for this IPython notebook is by default hidden for easier reading.\n",
    "To toggle on/off the raw code, click <a href=\"javascript:code_toggle()\">here</a>.''')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## transitions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<svg baseProfile=\"full\" height=\"240\" version=\"1.1\" width=\"320\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:ev=\"http://www.w3.org/2001/xml-events\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><defs><marker id=\"id42\" markerHeight=\"10\" markerWidth=\"10\" orient=\"auto\" refX=\"5\" refY=\"5\"><path d=\"M 0 0 L 10 5 L 0 10 z\" fill=\"blue\" /></marker></defs><text x=\"0\" y=\"40\">Noun</text><text x=\"0\" y=\"80\">Verb</text><text x=\"0\" y=\"120\">Modal</text><text x=\"0\" y=\"160\">Pronoun</text><text x=\"80\" y=\"200\">I</text><text x=\"160\" y=\"200\">can</text><text x=\"240\" y=\"200\">fly</text><line marker-end=\"url(#id42)\" stroke=\"rgb(10%,10%,16%)\" x1=\"80\" x2=\"160\" y1=\"160\" y2=\"120\" /><line marker-end=\"url(#id42)\" stroke=\"rgb(10%,10%,16%)\" x1=\"160\" x2=\"240\" y1=\"120\" y2=\"120\" /><text x=\"250\" y=\"120\">cost = 1</text><text x=\"80\" y=\"115\">rollin</text><text x=\"240\" y=\"75\">rollout</text><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"85\" x2=\"155\" y1=\"40\" y2=\"40\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"85\" x2=\"155\" y1=\"80\" y2=\"80\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"85\" x2=\"155\" y1=\"120\" y2=\"120\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"85\" x2=\"155\" y1=\"160\" y2=\"160\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"165\" x2=\"235\" y1=\"40\" y2=\"40\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"165\" x2=\"235\" y1=\"80\" y2=\"80\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"165\" x2=\"235\" y1=\"120\" y2=\"120\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"165\" x2=\"235\" y1=\"160\" y2=\"160\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"80\" x2=\"80\" y1=\"45\" y2=\"75\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"80\" x2=\"80\" y1=\"85\" y2=\"115\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"80\" x2=\"80\" y1=\"125\" y2=\"155\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"160\" x2=\"160\" y1=\"45\" y2=\"75\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"160\" x2=\"160\" y1=\"85\" y2=\"115\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"160\" x2=\"160\" y1=\"125\" y2=\"155\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"240\" x2=\"240\" y1=\"45\" y2=\"75\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"240\" x2=\"240\" y1=\"85\" y2=\"115\" /><line stroke=\"rgb(10%,10%,16%)\" stroke-dasharray=\"5 5\" x1=\"240\" x2=\"240\" y1=\"125\" y2=\"155\" /></svg>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows = ['Noun', 'Verb', 'Modal', 'Pronoun']\n",
    "columns = ['I', 'can', 'fly']\n",
    "path = [(0,3),(1,2),(2,1)]\n",
    "cost = 0\n",
    "cost_cell = (2,1)\n",
    "cg.draw_cost_breakdown(rows, columns, path, cost, cost_cell, roll_in_cell=(0,2), roll_out_cell=(2,2))\n",
    "time.sleep(1.0)\n",
    "path = [(0,3),(1,2),(2,2)]\n",
    "cost = 1\n",
    "cost_cell = (2,2)\n",
    "cg.draw_cost_breakdown(rows, columns, path, cost, cost_cell, roll_in_cell=(0,2), roll_out_cell=(2,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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XMPbkWaKWpHHHyx1JnwayuzbHQRJjp/MtRWPv2FhsVLDWquLIclIDU9tyBoJh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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33e75a1ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import time\n",
    "import pylab as pl\n",
    "from IPython import display\n",
    "for i in range(10):\n",
    "    pl.clf()\n",
    "    pl.plot(pl.randn(100))\n",
    "    display.display(pl.gcf())\n",
    "    display.clear_output(wait=True)\n",
    "    time.sleep(1.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### sdfs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}