diff --git a/README.md b/README.md index a4bb604..c9e9b15 100755 --- a/README.md +++ b/README.md @@ -40,6 +40,7 @@ - Entry point: Data - using sci-packages to prepare data for Machine Learning tasks and other data analyses [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/python_data_entry_point.ipynb?create=1)] +- Awesome things that you can do in IPython Notebooks (in progress) [[IPython nb](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/awesome_things_ipynb.ipynb)]
diff --git a/tutorials/awesome_things_ipynb.ipynb b/tutorials/awesome_things_ipynb.ipynb new file mode 100644 index 0000000..c4a0e80 --- /dev/null +++ b/tutorials/awesome_things_ipynb.ipynb @@ -0,0 +1,873 @@ +{ + "metadata": { + "name": "", + "signature": "sha256:68e419b336c43b3a5f99d948a5148ad6a7da83f9796fdc45c9132c236a5a43bc" + }, + "nbformat": 3, + "nbformat_minor": 0, + "worksheets": [ + { + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Sebastian Raschka](http://sebastianraschka.com) \n", + "\n", + "- [Open in IPython nbviewer](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/awesome_things_ipynb?create=1) \n", + "\n", + "- [Link to this IPython notebook on Github](https://github.com/rasbt/python_reference/blob/master/tutorials/awesome_things_ipynb.ipynb) \n", + "\n", + "- [Link to the GitHub Repository python_reference](https://github.com/rasbt/python_reference/)" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import time\n", + "import platform\n", + "print('Last updated: %s' %time.strftime('%d/%m/%Y'))\n", + "print('Created using Python', platform.python_version())" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Last updated: 27/06/2014\n", + "Created using Python 3.4.1\n" + ] + } + ], + "prompt_number": 37 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "I would be happy to hear your comments and suggestions. \n", + "Please feel free to drop me a note via\n", + "[twitter](https://twitter.com/rasbt), [email](mailto:bluewoodtree@gmail.com), or [google+](https://plus.google.com/+SebastianRaschka).\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 1, + "metadata": {}, + "source": [ + "Awesome things that you can do in IPython Notebooks (in progress)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Writing local files" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%%file hello.py\n", + "def func_inside_script(x, y):\n", + " return x + y\n", + "print('Hello World')" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Writing hello.py\n" + ] + } + ], + "prompt_number": 13 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Running Python scripts" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can run Python scripts in IPython via the %run magic command. For example, the Python script that we created in the [Writing local files](#Writing-local-files) section." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%run hello.py" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Hello World\n" + ] + } + ], + "prompt_number": 14 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "func_inside_script(1, 2)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 16, + "text": [ + "3" + ] + } + ], + "prompt_number": 16 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Benchmarking" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%timeit [x**2 for x in range(100)] " + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "10000 loops, best of 3: 38.8 \u00b5s per loop\n" + ] + } + ], + "prompt_number": 4 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%timeit -r 5 -n 100 [x**2 for x in range(100)] " + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "100 loops, best of 5: 39 \u00b5s per loop\n" + ] + } + ], + "prompt_number": 3 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Using system shell commands" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By prepending a \"`!`\" we can conveniently execute most of the system shell commands, below are just a few examples." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "my_dir = 'new_dir'\n", + "!mkdir $my_dir\n", + "!pwd\n", + "!touch $my_dir'/some.txt'\n", + "!ls -l './new_dir'\n", + "!ls -l $my_dir | wc -l" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "/Users/sebastian/Desktop\r\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "total 0\r\n", + "-rw-r--r-- 1 sebastian staff 0 Jun 27 10:11 some.txt\r\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + " 2\r\n" + ] + } + ], + "prompt_number": 12 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Debugging" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%debug \n", + "def some_func():\n", + " var = 'hello world'\n", + " for i in range(5):\n", + " print(i)\n", + " i / 0\n", + " return 'finished'" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "> \u001b[0;32m\u001b[0m(5)\u001b[0;36msome_func\u001b[0;34m()\u001b[0m\n", + "\u001b[0;32m 4 \u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0m\u001b[0;32m----> 5 \u001b[0;31m \u001b[0mi\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0m\u001b[0;32m 6 \u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0;34m'finished'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0m\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "stream": "stdout", + "text": [ + "ipdb> var\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "'hello world'\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Inline Plotting with matplotlib" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%matplotlib inline" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 33 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "import math\n", + "\n", + "def pdf(x, mu=0, sigma=1):\n", + " \"\"\"Calculates the normal distribution's probability density \n", + " function (PDF). \n", + " \n", + " \"\"\"\n", + " term1 = 1.0 / ( math.sqrt(2*np.pi) * sigma )\n", + " term2 = np.exp( -0.5 * ( (x-mu)/sigma )**2 )\n", + " return term1 * term2\n", + "\n", + "\n", + "x = np.arange(0, 100, 0.05)\n", + "\n", + "pdf1 = pdf(x, mu=5, sigma=2.5**0.5)\n", + "pdf2 = pdf(x, mu=10, sigma=6**0.5)\n", + "\n", + "plt.plot(x, pdf1)\n", + "plt.plot(x, pdf2)\n", + "plt.title('Probability Density Functions')\n", + "plt.ylabel('p(x)')\n", + "plt.xlabel('random variable x')\n", + "plt.legend(['pdf1 ~ N($\\mu=5$, $\\sigma=2.5$)', 'pdf2 ~ N($\\mu=10$, $\\sigma=6$)'], loc='upper right')\n", + "plt.ylim([0,0.5])\n", + "plt.xlim([0,20])\n", + "\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": 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rnj/+/OrVq7zxxhv6aWdnZyZPnsy2bdt4/Pix0TKkpqYyZ84cPvroowyfX7JkCe3bt6dg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\nnumcvH2Sz/0/p4dXj9cerlpta9fqBh1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+ "text": [ + "" + ] + } + ], + "prompt_number": 36 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "C-extensions via the Cython magic" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Cython (see [Cython's C-extensions for Python](http://cython.org)) is basically a hybrid between C and Python and can be pictured as compiled Python code with type declarations.\n", + "Since we are working in an IPython notebook here, we can make use of the very convenient IPython magic: It will take care of the conversion to C code, the compilation, and eventually the loading of the function.\n", + "Also, we are adding C type declarations; those type declarations are not necessary for using Cython, however, it will improve the performance of our code significantly." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%load_ext cythonmagic" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 29 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%%cython\n", + "import numpy as np\n", + "cimport numpy as np\n", + "cimport cython\n", + "@cython.boundscheck(False) \n", + "@cython.wraparound(False)\n", + "@cython.cdivision(True)\n", + "cpdef cython_lstsqr(x_ary, y_ary):\n", + " \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n", + " cdef double x_avg, y_avg, var_x, cov_xy,\\\n", + " slope, y_interc, temp\n", + " cdef double[:] x = x_ary # memoryview\n", + " cdef double[:] y = y_ary\n", + " cdef unsigned long N, i\n", + " \n", + " N = x.shape[0]\n", + " x_avg = 0\n", + " y_avg = 0\n", + " for i in range(N):\n", + " x_avg += x[i]\n", + " y_avg += y[i]\n", + " x_avg = x_avg/N\n", + " y_avg = y_avg/N\n", + " var_x = 0\n", + " cov_xy = 0\n", + " for i in range(N):\n", + " temp = (x[i] - x_avg)\n", + " var_x += temp**2\n", + " cov_xy += temp*(y[i] - y_avg)\n", + " slope = cov_xy / var_x\n", + " y_interc = y_avg - slope*x_avg\n", + " return (slope, y_interc)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "building '_cython_magic_cf6c91cb1e11de8d2dbe7d9178e469df' extension\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "C compiler: /usr/bin/clang -fno-strict-aliasing -Werror=declaration-after-statement -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/sebastian/miniconda3/envs/py34/include -arch x86_64\n", + "\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "compile options: '-I/Users/sebastian/miniconda3/envs/py34/lib/python3.4/site-packages/numpy/core/include -I/Users/sebastian/miniconda3/envs/py34/include/python3.4m -c'\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "clang: /Users/sebastian/.ipython/cython/_cython_magic_cf6c91cb1e11de8d2dbe7d9178e469df.c\n" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "/usr/bin/clang -bundle -undefined dynamic_lookup -L/Users/sebastian/miniconda3/envs/py34/lib -arch x86_64 /Users/sebastian/.ipython/cython/Users/sebastian/.ipython/cython/_cython_magic_cf6c91cb1e11de8d2dbe7d9178e469df.o -L/Users/sebastian/miniconda3/envs/py34/lib -o /Users/sebastian/.ipython/cython/_cython_magic_cf6c91cb1e11de8d2dbe7d9178e469df.so\n" + ] + } + ], + "prompt_number": 30 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import numpy as np\n", + "\n", + "x_ary = np.array([x_i*np.random.randint(8,12)/10 for x_i in range(100)])\n", + "y_ary = np.array([y_i*np.random.randint(10,14)/10 for y_i in range(100)])" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 31 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "cython_lstsqr(x_ary, y_ary)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 32, + "text": [ + "(1.1399825800539194, 2.0824398156005444)" + ] + } + ], + "prompt_number": 32 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Running Fortran Code" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "There is also a convenient IPython magic command for compiling Fortran code. The Fortran magic uses NumPy's [F2PY](http://www.f2py.com) module for compiling and running the Fortran code. For more information, please see the ['Fortran magic's documentation'](http://nbviewer.ipython.org/github/mgaitan/fortran_magic/blob/master/documentation.ipynb)." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%install_ext https://raw.github.com/mgaitan/fortran_magic/master/fortranmagic.py" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Installed fortranmagic.py. To use it, type:\n", + " %load_ext fortranmagic\n" + ] + } + ], + "prompt_number": 17 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%load_ext fortranmagic" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "javascript": [ + "$.getScript(\"https://raw.github.com/marijnh/CodeMirror/master/mode/fortran/fortran.js\", function () {\n", + "IPython.config.cell_magic_highlight['magic_fortran'] = {'reg':[/^%%fortran/]};});\n" + ], + "metadata": {}, + "output_type": "display_data" + } + ], + "prompt_number": 18 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%%fortran\n", + "SUBROUTINE fortran_lstsqr(ary_x, ary_y, slope, y_interc)\n", + " ! Computes the least-squares solution to a linear matrix equation. \"\"\"\n", + " IMPLICIT NONE\n", + " REAL(8), INTENT(in), DIMENSION(:) :: ary_x, ary_y\n", + " REAL(8), INTENT(out) :: slope, y_interc\n", + " REAL(8) :: x_avg, y_avg, var_x, cov_xy, temp\n", + " INTEGER(8) :: N, i\n", + " \n", + " N = SIZE(ary_x)\n", + "\n", + " x_avg = SUM(ary_x) / N\n", + " y_avg = SUM(ary_y) / N\n", + " var_x = 0\n", + " cov_xy = 0\n", + " \n", + " DO i = 1, N\n", + " temp = ary_x(i) - x_avg\n", + " var_x = var_x + temp**2\n", + " cov_xy = cov_xy + (temp*(ary_y(i) - y_avg))\n", + " END DO\n", + " \n", + " slope = cov_xy / var_x\n", + " y_interc = y_avg - slope*x_avg\n", + "\n", + "END SUBROUTINE fortran_lstsqr" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\tBuilding module \"_fortran_magic_a044885f2b0c0feac78a230b6b714e2b\"...\n", + "\t\tConstructing wrapper function \"fortran_lstsqr\"...\n", + "\t\t slope,y_interc = fortran_lstsqr(ary_x,ary_y)\n", + "\tWrote C/API module \"_fortran_magic_a044885f2b0c0feac78a230b6b714e2b\" to file \"/var/folders/bq/_946cdn92t7bqzz5frpfpw7r0000gp/T/tmp3y_jxtl_/src.macosx-10.5-x86_64-3.4/_fortran_magic_a044885f2b0c0feac78a230b6b714e2bmodule.c\"\n", + "\tFortran 77 wrappers are saved to \"/var/folders/bq/_946cdn92t7bqzz5frpfpw7r0000gp/T/tmp3y_jxtl_/src.macosx-10.5-x86_64-3.4/_fortran_magic_a044885f2b0c0feac78a230b6b714e2b-f2pywrappers.f\"\n" + ] + } + ], + "prompt_number": 22 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import numpy as np\n", + "\n", + "x_ary = np.array([x_i*np.random.randint(8,12)/10 for x_i in range(100)])\n", + "y_ary = np.array([y_i*np.random.randint(10,14)/10 for y_i in range(100)])" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 23 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "fortran_lstsqr(x_ary, y_ary)" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 25, + "text": [ + "(1.1313508052697814, 3.681685640167956)" + ] + } + ], + "prompt_number": 25 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "
" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Running code from other interpreters: Ruby, Perl, and Bash" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To use any interpreter that is installed on your system:" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%%script perl\n", + "print 'Hello, World!';" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Hello, World!" + ] + } + ], + "prompt_number": 44 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Or use the magic command for the respective interpreter directly:" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%%perl\n", + "print 'Hello, World!';" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Hello, World!" + ] + } + ], + "prompt_number": 45 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%%ruby\n", + "puts \"Hello, World!\"" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Hello, World!\n" + ] + } + ], + "prompt_number": 46 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%%bash\n", + "echo \"Hello World!\"" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Hello World!\n" + ] + } + ], + "prompt_number": 47 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%%script R --no-save\n", + "cat(\"Goodbye, World!\\n\")" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "R version 3.0.2 (2013-09-25) -- \"Frisbee Sailing\"\n", + "Copyright (C) 2013 The R Foundation for Statistical Computing\n", + "Platform: x86_64-apple-darwin10.8.0 (64-bit)\n", + "\n", + "R is free software and comes with ABSOLUTELY NO WARRANTY.\n", + "You are welcome to redistribute it under certain conditions.\n", + "Type 'license()' or 'licence()' for distribution details.\n", + "\n", + " Natural language support but running in an English locale\n", + "\n", + "R is a collaborative project with many contributors.\n", + "Type 'contributors()' for more information and\n", + "'citation()' on how to cite R or R packages in publications.\n", + "\n", + "Type 'demo()' for some demos, 'help()' for on-line help, or\n", + "'help.start()' for an HTML browser interface to help.\n", + "Type 'q()' to quit R.\n", + "\n", + "> cat(\"Goodbye, World!\\n\")\n", + "Goodbye, World!\n", + "> \n" + ] + } + ], + "prompt_number": 55 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [], + "language": "python", + "metadata": {}, + "outputs": [] + } + ], + "metadata": {} + } + ] +} \ No newline at end of file