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 "metadata": {
  "name": "",
  "signature": "sha256:f22bd85e82a2a92bfc795829d7b53aefc09c1f824389a0a4e041ab89dcd00399"
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 "worksheets": [
  {
   "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",
     "collapsed": false,
     "input": [
      "from IPython.display import Image\n",
      "Image(url='http://imgs.xkcd.com/comics/new_pet.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "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",
     "collapsed": false,
     "input": [
      "from IPython.display import YouTubeVideo\n",
      "YouTubeVideo('xe_ATRmw0KM')  # Part 1/3, the whole 3-part thing is 3 hours"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "YouTubeVideo('A8VbS-YX2Lo') # Part 2/3"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "YouTubeVideo('4tJKZWWRs6s') # Part 3/3"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## 1. Development goodies\n",
      "\n",
      "### Documentation and source"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pdoc plot"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%psource plot"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### The IPython kernel/client model"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%connect_info"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%qtconsole"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "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": "code",
     "collapsed": false,
     "input": [
      "%load http://matplotlib.org/mpl_examples/showcase/xkcd.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## 2. Integration\n",
      "\n",
      "### R (statistical programming package)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Might need to install R and rpy2\n",
      "%load_ext rpy2.ipython"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "X = np.arange(100)\n",
      "Y = 200.*X + 100."
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%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)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print XYcoeff"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Octave"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Might need to install Octave and oct2py\n",
      "%load_ext octavemagic"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%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()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Cython (C and Python mashup)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load_ext cythonmagic"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "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"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%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"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a, b, N = 0, 2, 10000\n",
      "%timeit integrate_f(a, b, N)\n",
      "%timeit cyintegrate_f(a, b, N)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Ruby (wuhuu)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%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"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## 3. Interactive Widgets"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**NOTE** Only in IPython 2.0 and later!"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The IPython website has [documentation and examples](http://nbviewer.ipython.org/github/ipython/ipython/blob/2.x/examples/Interactive%20Widgets/Index.ipynb)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.html.widgets import interactive\n",
      "from IPython.display import Audio, display"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def beat_freq(f1=220.0, f2=224.0):\n",
      "    max_time = 3\n",
      "    rate = 8000\n",
      "    times = np.linspace(0,max_time,rate*max_time)\n",
      "    signal = np.sin(2*np.pi*f1*times) + np.sin(2*np.pi*f2*times)\n",
      "    print(f1, f2, abs(f1-f2))\n",
      "    display(Audio(data=signal, rate=rate))\n",
      "    return signal"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "v = interactive(beat_freq, f1=(200.0,300.0), f2=(200.0,300.0))\n",
      "display(v)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "v.kwargs"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "f1, f2 = v.children\n",
      "f1.value = 255\n",
      "f2.value = 260\n",
      "plt.plot(v.result[0:6000])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}