{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Advanced IPython session\n",
    "\n",
    "* IPython magics for development\n",
    "* Integration in IPython\n",
    "* Parallelization in IPython (in separate notebook)\n",
    "* Advanced Display Capabilities (in separate notebook)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "Image(url='http://imgs.xkcd.com/comics/new_pet.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comic: [XKCD: New Pet](http://xkcd.com/413/)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Where can I find more of this advanced information?\n",
    "\n",
    "We have an [IPython in-depth tutorial](https://github.com/ipython/ipython-in-depth) that you can download.  And you can watch it all online:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import YouTubeVideo\n",
    "YouTubeVideo('xe_ATRmw0KM')  # Part 1/3, the whole 3-part thing is 3 hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "YouTubeVideo('A8VbS-YX2Lo') # Part 2/3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "YouTubeVideo('4tJKZWWRs6s') # Part 3/3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Development goodies\n",
    "\n",
    "### Documentation and source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from matplotlib.pyplot import plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plot?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%pdoc plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%psource plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The IPython kernel/client model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%connect_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%qtconsole"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading from the web\n",
    "\n",
    "Finding useful examples in the [matplotlib gallery](http://matplotlib.org/gallery.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Integration\n",
    "\n",
    "### R (statistical programming package)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Might need to install R and rpy2\n",
    "%load_ext rpy2.ipython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "X = np.arange(100)\n",
    "Y = 200.*X + 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%R -i X,Y -o XYcoeff\n",
    "XYlm = lm(Y~X)\n",
    "print(summary(XYlm))\n",
    "XYcoeff = coef(XYlm)\n",
    "par(mfrow=c(2,2))\n",
    "plot(XYlm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print(XYcoeff)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Octave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Might need to install Octave and oct2py\n",
    "%load_ext octavemagic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%octave -s 600,200 -f png\n",
    "\n",
    "subplot(121);\n",
    "[x,y] = meshgrid(0:0.1:3);\n",
    "r = sin(x-0.5).^2 + cos(y-0.5).^2;\n",
    "surf(x,y,r);\n",
    "\n",
    "subplot(122);\n",
    "sombrero()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cython (C and Python mashup)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%load_ext cython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def f(x):\n",
    "    return x**2-x\n",
    "\n",
    "def integrate_f(a, b, N):\n",
    "    s = 0\n",
    "    dx = (b-a)/N\n",
    "    for i in range(N):\n",
    "        s += f(a+i*dx)\n",
    "    return s * dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%cython\n",
    "\n",
    "cdef double f(double x):\n",
    "    return x**2-x\n",
    "\n",
    "def cyintegrate_f(double a, double b, int N):\n",
    "    cdef int i\n",
    "    cdef double s, dx\n",
    "    s = 0\n",
    "    dx = (b-a)/N\n",
    "    for i in range(N):\n",
    "        s += f(a+i*dx)\n",
    "    return s * dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "a, b, N = 0, 2, 10000\n",
    "%timeit integrate_f(a, b, N)\n",
    "%timeit cyintegrate_f(a, b, N)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ruby"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%ruby\n",
    "s = \"Yo IPython, Ruby's here 4 real!\"\n",
    "s.split(\" \").each do |word| \n",
    "    puts word if word.to_i.to_s == word\n",
    "end"
   ]
  }
 ],
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   "display_name": "Python 3",
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "widgets": {
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