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| 1 | { |
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1 | { | |
| 2 | "metadata": { |
|
2 | "metadata": { | |
| 3 | "name": "00_notebook_tour" |
|
3 | "name": "00_notebook_tour" | |
| 4 | }, |
|
4 | }, | |
| 5 | "nbformat": 3, |
|
5 | "nbformat": 3, | |
| 6 | "nbformat_minor": 0, |
|
6 | "nbformat_minor": 0, | |
| 7 | "worksheets": [ |
|
7 | "worksheets": [ | |
| 8 | { |
|
8 | { | |
| 9 | "cells": [ |
|
9 | "cells": [ | |
| 10 | { |
|
10 | { | |
| 11 | "cell_type": "markdown", |
|
11 | "cell_type": "markdown", | |
| 12 | "metadata": {}, |
|
12 | "metadata": {}, | |
| 13 | "source": [ |
|
13 | "source": [ | |
| 14 | "# A brief tour of the IPython notebook\n", |
|
14 | "# A brief tour of the IPython notebook\n", | |
| 15 | "\n", |
|
15 | "\n", | |
| 16 | "This document will give you a brief tour of the capabilities of the IPython notebook. \n", |
|
16 | "This document will give you a brief tour of the capabilities of the IPython notebook. \n", | |
| 17 | "You can view its contents by scrolling around, or execute each cell by typing `Shift-Enter`.\n", |
|
17 | "You can view its contents by scrolling around, or execute each cell by typing `Shift-Enter`.\n", | |
| 18 | "After you conclude this brief high-level tour, you should read the accompanying notebook \n", |
|
18 | "After you conclude this brief high-level tour, you should read the accompanying notebook \n", | |
| 19 | "titled `01_notebook_introduction`, which takes a more step-by-step approach to the features of the\n", |
|
19 | "titled `01_notebook_introduction`, which takes a more step-by-step approach to the features of the\n", | |
| 20 | "system. \n", |
|
20 | "system. \n", | |
| 21 | "\n", |
|
21 | "\n", | |
| 22 | "The rest of the notebooks in this directory illustrate various other aspects and \n", |
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22 | "The rest of the notebooks in this directory illustrate various other aspects and \n", | |
| 23 | "capabilities of the IPython notebook; some of them may require additional libraries to be executed.\n", |
|
23 | "capabilities of the IPython notebook; some of them may require additional libraries to be executed.\n", | |
| 24 | "\n", |
|
24 | "\n", | |
| 25 | "**NOTE:** This notebook *must* be run from its own directory, so you must ``cd``\n", |
|
25 | "**NOTE:** This notebook *must* be run from its own directory, so you must ``cd``\n", | |
| 26 | "to this directory and then start the notebook, but do *not* use the ``--notebook-dir``\n", |
|
26 | "to this directory and then start the notebook, but do *not* use the ``--notebook-dir``\n", | |
| 27 | "option to run it from another location.\n", |
|
27 | "option to run it from another location.\n", | |
| 28 | "\n", |
|
28 | "\n", | |
| 29 | "The first thing you need to know is that you are still controlling the same old IPython you're used to,\n", |
|
29 | "The first thing you need to know is that you are still controlling the same old IPython you're used to,\n", | |
| 30 | "so things like shell aliases and magic commands still work:" |
|
30 | "so things like shell aliases and magic commands still work:" | |
| 31 | ] |
|
31 | ] | |
| 32 | }, |
|
32 | }, | |
| 33 | { |
|
33 | { | |
| 34 | "cell_type": "code", |
|
34 | "cell_type": "code", | |
| 35 | "collapsed": false, |
|
35 | "collapsed": false, | |
| 36 | "input": [ |
|
36 | "input": [ | |
| 37 | "pwd" |
|
37 | "pwd" | |
| 38 | ], |
|
38 | ], | |
| 39 | "language": "python", |
|
39 | "language": "python", | |
| 40 | "metadata": {}, |
|
40 | "metadata": {}, | |
| 41 | "outputs": [ |
|
41 | "outputs": [ | |
| 42 | { |
|
42 | { | |
| 43 | "output_type": "pyout", |
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43 | "output_type": "pyout", | |
| 44 | "prompt_number": 1, |
|
44 | "prompt_number": 1, | |
| 45 | "text": [ |
|
45 | "text": [ | |
| 46 | "u'/Users/minrk/dev/ip/mine/docs/examples/notebooks'" |
|
46 | "u'/Users/minrk/dev/ip/mine/docs/examples/notebooks'" | |
| 47 | ] |
|
47 | ] | |
| 48 | } |
|
48 | } | |
| 49 | ], |
|
49 | ], | |
| 50 | "prompt_number": 1 |
|
50 | "prompt_number": 1 | |
| 51 | }, |
|
51 | }, | |
| 52 | { |
|
52 | { | |
| 53 | "cell_type": "code", |
|
53 | "cell_type": "code", | |
| 54 | "collapsed": false, |
|
54 | "collapsed": false, | |
| 55 | "input": [ |
|
55 | "input": [ | |
| 56 | "ls" |
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56 | "ls" | |
| 57 | ], |
|
57 | ], | |
| 58 | "language": "python", |
|
58 | "language": "python", | |
| 59 | "metadata": {}, |
|
59 | "metadata": {}, | |
| 60 | "outputs": [ |
|
60 | "outputs": [ | |
| 61 | { |
|
61 | { | |
| 62 | "output_type": "stream", |
|
62 | "output_type": "stream", | |
| 63 | "stream": "stdout", |
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63 | "stream": "stdout", | |
| 64 | "text": [ |
|
64 | "text": [ | |
| 65 | "00_notebook_tour.ipynb callbacks.ipynb python-logo.svg\r\n", |
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65 | "00_notebook_tour.ipynb callbacks.ipynb python-logo.svg\r\n", | |
| 66 | "01_notebook_introduction.ipynb cython_extension.ipynb rmagic_extension.ipynb\r\n", |
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66 | "01_notebook_introduction.ipynb cython_extension.ipynb rmagic_extension.ipynb\r\n", | |
| 67 | "Animations_and_Progress.ipynb display_protocol.ipynb sympy.ipynb\r\n", |
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67 | "Animations_and_Progress.ipynb display_protocol.ipynb sympy.ipynb\r\n", | |
| 68 | "Capturing Output.ipynb formatting.ipynb sympy_quantum_computing.ipynb\r\n", |
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68 | "Capturing Output.ipynb formatting.ipynb sympy_quantum_computing.ipynb\r\n", | |
| 69 | "Script Magics.ipynb octavemagic_extension.ipynb trapezoid_rule.ipynb\r\n", |
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69 | "Script Magics.ipynb octavemagic_extension.ipynb trapezoid_rule.ipynb\r\n", | |
| 70 | "animation.m4v progbar.ipynb\r\n" |
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70 | "animation.m4v progbar.ipynb\r\n" | |
| 71 | ] |
|
71 | ] | |
| 72 | } |
|
72 | } | |
| 73 | ], |
|
73 | ], | |
| 74 | "prompt_number": 2 |
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74 | "prompt_number": 2 | |
| 75 | }, |
|
75 | }, | |
| 76 | { |
|
76 | { | |
| 77 | "cell_type": "code", |
|
77 | "cell_type": "code", | |
| 78 | "collapsed": false, |
|
78 | "collapsed": false, | |
| 79 | "input": [ |
|
79 | "input": [ | |
| 80 | "message = 'The IPython notebook is great!'\n", |
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80 | "message = 'The IPython notebook is great!'\n", | |
| 81 | "# note: the echo command does not run on Windows, it's a unix command.\n", |
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81 | "# note: the echo command does not run on Windows, it's a unix command.\n", | |
| 82 | "!echo $message" |
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82 | "!echo $message" | |
| 83 | ], |
|
83 | ], | |
| 84 | "language": "python", |
|
84 | "language": "python", | |
| 85 | "metadata": {}, |
|
85 | "metadata": {}, | |
| 86 | "outputs": [ |
|
86 | "outputs": [ | |
| 87 | { |
|
87 | { | |
| 88 | "output_type": "stream", |
|
88 | "output_type": "stream", | |
| 89 | "stream": "stdout", |
|
89 | "stream": "stdout", | |
| 90 | "text": [ |
|
90 | "text": [ | |
| 91 | "The IPython notebook is great!\r\n" |
|
91 | "The IPython notebook is great!\r\n" | |
| 92 | ] |
|
92 | ] | |
| 93 | } |
|
93 | } | |
| 94 | ], |
|
94 | ], | |
| 95 | "prompt_number": 3 |
|
95 | "prompt_number": 3 | |
| 96 | }, |
|
96 | }, | |
| 97 | { |
|
97 | { | |
| 98 | "cell_type": "heading", |
|
98 | "cell_type": "heading", | |
| 99 | "level": 2, |
|
99 | "level": 2, | |
| 100 | "metadata": {}, |
|
100 | "metadata": {}, | |
| 101 | "source": [ |
|
101 | "source": [ | |
| 102 | "Plots with matplotlib" |
|
102 | "Plots with matplotlib" | |
| 103 | ] |
|
103 | ] | |
| 104 | }, |
|
104 | }, | |
| 105 | { |
|
105 | { | |
| 106 | "cell_type": "markdown", |
|
106 | "cell_type": "markdown", | |
| 107 | "metadata": {}, |
|
107 | "metadata": {}, | |
| 108 | "source": [ |
|
108 | "source": [ | |
| 109 | "IPython adds an 'inline' matplotlib backend,\n", |
|
109 | "IPython adds an 'inline' matplotlib backend,\n", | |
| 110 | "which embeds any matplotlib figures into the notebook." |
|
110 | "which embeds any matplotlib figures into the notebook." | |
| 111 | ] |
|
111 | ] | |
| 112 | }, |
|
112 | }, | |
| 113 | { |
|
113 | { | |
| 114 | "cell_type": "code", |
|
114 | "cell_type": "code", | |
| 115 | "collapsed": false, |
|
115 | "collapsed": false, | |
| 116 | "input": [ |
|
116 | "input": [ | |
| 117 | "%pylab inline" |
|
117 | "%pylab inline" | |
| 118 | ], |
|
118 | ], | |
| 119 | "language": "python", |
|
119 | "language": "python", | |
| 120 | "metadata": {}, |
|
120 | "metadata": {}, | |
| 121 | "outputs": [ |
|
121 | "outputs": [ | |
| 122 | { |
|
122 | { | |
| 123 | "output_type": "stream", |
|
123 | "output_type": "stream", | |
| 124 | "stream": "stdout", |
|
124 | "stream": "stdout", | |
| 125 | "text": [ |
|
125 | "text": [ | |
| 126 | "\n", |
|
126 | "\n", | |
| 127 | "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n", |
|
127 | "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n", | |
| 128 | "For more information, type 'help(pylab)'.\n" |
|
128 | "For more information, type 'help(pylab)'.\n" | |
| 129 | ] |
|
129 | ] | |
| 130 | } |
|
130 | } | |
| 131 | ], |
|
131 | ], | |
| 132 | "prompt_number": 4 |
|
132 | "prompt_number": 4 | |
| 133 | }, |
|
133 | }, | |
| 134 | { |
|
134 | { | |
| 135 | "cell_type": "code", |
|
135 | "cell_type": "code", | |
| 136 | "collapsed": false, |
|
136 | "collapsed": false, | |
| 137 | "input": [ |
|
137 | "input": [ | |
| 138 | "x = linspace(0, 3*pi, 500)\n", |
|
138 | "x = linspace(0, 3*pi, 500)\n", | |
| 139 | "plot(x, sin(x**2))\n", |
|
139 | "plot(x, sin(x**2))\n", | |
| 140 | "title('A simple chirp');" |
|
140 | "title('A simple chirp');" | |
| 141 | ], |
|
141 | ], | |
| 142 | "language": "python", |
|
142 | "language": "python", | |
| 143 | "metadata": {}, |
|
143 | "metadata": {}, | |
| 144 | "outputs": [ |
|
144 | "outputs": [ | |
| 145 | { |
|
145 | { | |
| 146 | "output_type": "display_data", |
|
146 | "output_type": "display_data", | |
| 147 | "png": 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AvfZOHEif98nAzd7RrfRlITV8VlYWNmzYgCuvvBLJZBJ33XUX5s+fj40bNwIA\n1qxZg1/96ld4+OGHkZWVhUmTJuGpp55SMnFW7NxJduG6pdrpRlkZ8Mor4Y9rR1sbUFLC10YH6YcV\nyO3u9j87YOJE9Z5+lKWVo7Z3ROv2uJExi73jtsioJn2Z64MCuWnv6QPEslmxYsWwn61Zs2bo//fc\ncw/uuece2WGEEVUQF4iPvcOTvQOoPa+WgsXTV0X6upR+GIHcKAquOf8uMpuzdNo7zuwdlnYinjtP\nCqbI9VEr/VG/IzdK0jf2TgphKn0dpO9VNgFQm6cfdsE1r2CsjNIXsXdEPX2WAme6lbudxNNB6Y9q\n0m9tBT74ALjggmjGLywEWlrYbgJdEMneUXlIOQWLpy9b+hiIhvTTOU9fhrhlPH3e8gVubeh4KgOz\nbiSeTHrvW5GNGUSBUU36r70GLFkS3cqamQkUFQFHj0YzPhCP7B3LYivDEOdAbpDSV5mnH6a9I6v0\nRdpaFiFSnoApIB7I5RnHOUYi4a/eee0jo/Q147e/BS67LNo5RG3xxMHe6enxPtjEjokTU1VBReGX\nZQPES+l7efphBnJ12Dus5G3f5hOXlE3eMXg3Zxmlrxmvvho96RcXA8eORTe+COmrtndY6w8lEvIW\nT1SevkhpZV1KPzubLJwsi6cs6fN67DLtosjeoW281PuYq70TZzQ3k+MKo/LzKYqLo7N3+vsJgfDu\nrFVt7/AUnZPdoJUugVw/T59VpSeTpOSzUzkmEuJ17QG+zVkinr6IYqfjhb05C+C3d4zSjwh1dSRr\nJ+o3uKgoOqXf3k7SNVlr6VNEpfQB+VIM6RTIlVX6lHTd/r4ypE/V6uCgf1s35a1LsdN2YW/OCmrD\nuznLKH2NiIO1A0QbyBXJ3AH0KP2gIC6FbDBXVyDXS5kD6vP0ZTZWUciQfiIhrrxZz60VaRdHT98o\n/Rjht78FPv3pqGcRracv4ucD6gO5vPaOTqUvYsUA6pW+33GJvErfDTKkT9uzePOiSt+LWP1KeqtI\n2aTZNawpmEFjGE8/JmhqIp7+eedFPZNo7R1R0o/S3lFB+n7ZOyKnXAH+pE9vdJ6sI91Kn3Vx8yJ9\n3eTt9nSRmRm8m1UkkGtX1rSCptffyo2UeewdP6VPU1XpOQBRYVSS/m9/C1x6aTT1dpyIMpAro/RH\nayBXB+knEmrKJwB8Sl+XvQOwZ+G4kXeQxeFm79AxVVovIm3c7Be/3Hse+4guELwxNtWIAS2qxyuv\nxMPaAYAvVw5GAAAgAElEQVSCAuDkSbncc1GI1N0B0jeQm0y6547bIWPvBC0mPP36HZcok2NPEQbp\nuylv2paXiIHgzB8V2TtBbXTaO3Hw84FRSPqWBbzwAnDllVHPhCA7m6jtkyfDH1tU6U+aRAjD71Gb\nB2HZO1SN+ykpHUof4Avm0tOZ/GrvsBxXGQel76XYg+rhuI2pmsBF2shuzuJJ74wKo470//IXcgNW\nVEQ9kxSi8vVFs3cSCbUWT9C5tXbIkH6QtQPoJX2eAKxzRypFRgYhDtEdsbzzESVuwF/p8yp2QJzA\neQquBY2jU+k7F4ioMOpIn6r8qH0zO6Ly9UWVPqDW4gnL0w8K4gKp3aq8TzFBpM+zmPgpdIDd4nEr\neEahQukHtfcjb14ipmPytlMdB3AjZlUpm0bpa8KOHfGxdiiiUvoypK8ybTMse4dF6ScSalMsKXiU\nvpefT8EazI3a3pHx9EXtHd7sHd5sHDdi9gvk8mzOMkpfAzo7gT/+MT5BXIqoNmjJkr4qeycs0g/a\nmEWhg/R5+vTb6AWwK/2gQC5rieOwPX3V9o7KHbY6N2cZpa8BdXXAhRcG120PG1Ft0BLN3gGis3dk\nsndYlD4gXiBNVSA3yN5RofRlyiPTOejy9EXtHVXZOzwpmEFjuJG+1+Yvo/Q14IUXgM98JupZjIRR\n+vGxdwCxYC4L6avYVMXTl18gV6ZoGm0vqvRZPP24Zu/Ibs7y2/xllL4GxNHPB6JT+qLZO8DoDeQC\n4scb+pE+z6YqlZ6+jL0zOOitPtMpe0f35ixVdpBR+opx6BAhqYULo57JSKSr0h+NgVyAX+lbFps6\nV+nph2HvUNJ2y3ST9fRFNmfFZUeu2/W8dpDb9UbpK8bWrUBtbTxKLzgRhdJPJgl5isY3orR3RJU+\nTyCXh/T9ShhTqLR3ZDNvAPaUS7/2ImUYWNr62Tu87cIgfb/grJt697reKH3F2LoV+Oxno56FOyZP\nJiTc0RHemKdPk3FFF8EoA7ky9g5rIJe3ZIKfMgfU1cwB+A4ml1H6sqSvspwCbada6Yt49LqeDIzS\nV4iTJ4G9e4HLL496Ju5IJMLP1ZfJ3AGis3fCIH1epc9C+qrz9GUDuaKlkSl0K30Re0c0e4fXo+c9\nRIX1ySAOZZWBUUL627cDy5YF35hRorAQOHEivPFk/HyAKP0o7B3ZlE2WQK4u0uexd4KCwrI7clXY\nO0HtdWzOUllSQaSNzsCvKbimEFu3AtdeG/Us/FFQEC7py2TuAOqUvmXFT+nH3d7hIf0o7Z102Zyl\nKzDrdb3XPgCj9BWhs5McjbhyZdQz8UdBAXD8eHjjySp9VaTf10cOjWD9sMuQvq5Armp7R2UgV5e9\nE8XmrLAKrvHumg0K5LIuREbpK8JvfgMsWQLk50c9E3+MVXuHp8ImkCLPoEO53RCl0uexd1R5+rrt\nnbA3Z4lk/fhZSbSEte6Ca27XG6WvEU89BaxaFfUsghG2vRMXpc9j7QAk20ikNg4QbSCX197x6491\nN23U9o6opx+WvZNMpnbIsrbRmeJplL4CtLWRoxHj7ucD0dg7Mtk7qpQ+L+kD4hZP1IFclfaOTN0c\n1j6i8vRV2zs81ktQG1VlG4zS14SnnyYVNWXILSykm70TldIHxEmf1dMfTfaOTO0dL9Km7aMouKYy\nZdNLWavekcu6OcsofQV48knglluingUb0i17Z/x44quzEpkXRElfJG0znewd3YHcKLN3WDZnhZGy\nKfJEwbPD1m9ORulrQH098Oc/A1dfHfVM2JBu2TuJhBqLJ2x7J12yd3Tn6eu2d5JJEijNzORvK0LG\nlkXGlC2GJtJG1eYso/Ql8dOfkgAui4cbB+TlEbvE7/FVJWRJHxi9pB+1vROXPH0ve4a295sDJUev\nYm2qC655jRc16fNszjJKXwLJJPC//wt88YtRz4QdmZkkrfTkyXDGU0X6svWC4kj6Uds7KsswRJWy\nqaOtn72jisABvYeo0Ou9au8YpS+IV14BZswALrgg6pnwIUyLRzZ7B0g/pd/VlT5lGHQXXNO9Ocuv\neJiIN0/b6VbtQW1UFGgztXc04LHH0kvlU4QZzE1ne0e0vHLU9k7Ynn6UgVyZtiL2jkhuv2jKplsg\nlyd7xyh9xfjgA1J24dZbo54JP8JK2xwcJGQ9ZYpcP+mm9NPF3lHp6Udl7wTFA4JSL8Oyd1SlbKrY\nnGWUviAeeICofFlCiwJh2TsdHYQ4ZVVFbm50pK8zZTPqQG4Yefoqsnf85iCT4x9ne0fn5qy4KP0Y\nTIEdp04B//d/wF/+EvVMxBCWvaPC2gHSS+kPDJAvLxKzQ0Tp+5E0EF3BNR318Gn7oAwc1fZOEBnz\nHqYeVfaOn9LPzXXvJ0ykldJ/+GFyOlZJSdQzEUNY9s5YJH1agsHvSEMKEdIPeoJQWXsnzB25Mp6+\naCBX5PAVvziASktIpOBaulXZjMEU2NDWBjz0ELBzZ9QzEUdY9o6KzB0gWtJvaeFrw2rtAPrq6ff2\nkk1EQQtPnLJ3vF6XTk8/3ewdv0CuV/aO2ZGrAD/4ATn4vKoq6pmIYyzaO7yllQFxpc9K+joCuVlZ\nhOy9yMHZXzrYO6JKX4e9I5K9o9vesSy+JwOj9Dlw5AjwyCPAnj1Rz0QOYZG+bN0dClVKn9fH1E36\nEyaQ61lUOcBG+rTfnp5gNafC07cs/34yM0kWVzLpXioB0Ju9I2rviGy0oiUhnH9LL2WtanPWwAB5\nb912CRulL4mvfx34xjeAWbOinokcqL1jWXrHiZPSDytPn4f0s7LIzcpaEoOH9Fm9eFlPn9aK9yL0\nRCLY4onK0/dT4H7+vNtcEwn+Wjcinj4PiZvaO5LYsgV4/33g29+OeibymDSJfHBVlCz2gyrSjzJl\nk5f0WXfjUvBYPCzZOwB7MFeF0vfL0aeQ2WDFQtxhZ+/4LTJeJKvK0+ddVIzSF8SRI8BXvwo88QTb\nTZcOCMPiSXelL5Knz6P0Ab7TuXjtHZb+VJB+0D3Bkmuvy9MXSfcUsXcA/aTvl3c/JpX+jh07UFVV\nhcrKSqxfv971mq997WuorKzEwoULsYfRmG9vB665BvjXfwUuvFB2lvFBYaH+DB6V2TvpUnCNl/Sp\nr88ClfZOkBcPyAdhWfuRCcbqWDBEduTSdlEofd4yD6NC6SeTSaxduxY7duzAvn378OSTT2L//v3D\nrnnuuedw6NAhHDx4EI8++ii+/OUvB/bb2krq5NfUED9/NMEo/WCEQfq89g4L6bPYOzT45+XF035U\nKH0ZT58Sl1f8KeyCa0ExBBWkz1uz30u5ewWKR4XS3717NyoqKjBnzhxkZ2dj1apV2Lp167Brtm3b\nhtWrVwMALr74YrS1teG4j9T905+AT34SWLwYePBBtuyKdEIYpB+X7B1647PskrVD1NPnVfpR2Dss\nZJ2dTchncND7Gr9iaxQy9k5Ghn+Wi47Mn6iVPm82jkj/aa/0GxsbUV5ePvR9WVkZGhsbA69paGhw\n7a+2NmXpPPCAvxpKV4Rl76gkfdFsIxGVD8jtyGUFj9IPyrahYLF3WILCiUQwYasI5PoFY4Pai27O\n8sptD2rnNx4vyfIuEiL2TpyVvtQUEowy3HKwhle7jIx7ceedwKFDQF1dDWpqamSmF0sUFAB//ave\nMVSR/rhxRPGxkp4TYZN+Otg7LEqf9tXb6/2adNs7QIr03f6GovEASnxuFKAje4fXflFB4rqrbNbV\n1aGurk64vRTpl5aWor6+fuj7+vp6lJWV+V7T0NCA0tJS1/6eeeZememkBQoKgNde0zuGKtIHUmmb\nUZA+6+YpQCyQy2LvWBZ7yiarvcO6gIhaMxQy9g5tL6r0RdpFnbIpkncfhdKvqRkuiO+77z6u9lL2\nzuLFi3Hw4EEcOXIEfX192LJlC2pra4ddU1tbi82bNwMAdu3ahWnTpqGwsFBm2LRGQQHQ3Kyvf8si\nnr6K7B1AztcXJf3MTHLjsJYqBvQpfXpjZzDcKarsHSDYmmFN2VSh9L3aigRyRQKyQDikryrvPu71\n9KXWnaysLGzYsAFXXnklkskk7rrrLsyfPx8bN24EAKxZswYrV67Ec889h4qKCuTk5OCnP/2pkomn\nK3QHcjs7yc2q6sMlk7YpSvpASu2zPmF0dQHTp7P3z0r6rNYOoMfe8QJLIFeVveMGP8VOg6FuJSD8\nyFvk5CxALemryLsf9bV3VqxYgRUrVgz72Zo1a4Z9v2HDBtlhRg10k76qzB2KKJQ+kCL9vDy263XZ\nO6zKnLVPVaTPGsjVZe/4kbC9rfNvIprqKar03RZs3mwcWsdocHD4E5/fImF25BoMIS+PEDNr3Rde\nqPTzATnSF6mwScEbzNVl7/AofRZ7R5WnH7W9I5r5w7I3gHc8lcrd7Xpa38dJ5CLZQXFQ+ob0Q0Zm\nJpCfD5w8qaf/OJG+CqXPCl1lGFTbOzx1fOJs7wQpfS/VHmQLAcQWcmsXRiDXi5Td2pjaOwbM0Gnx\njFXSF9mcpUPpx83eiVLpuxEry2LBQ+AibUTHcBL5mK29Y8CPdCJ9mUqbYSt9HZuzdNg7qkhf545c\n2l7W03dC1BaKmvTdiJx3c5ZR+mMYuklfVbomEF32Tk4OX6VNnYFc1dk7LP3JqnQ6nzh6+iJKX3X2\nDk8g16sN7+Yso/THMHSS/mjL3mFFXAK5YXn6UQdydXj6tJ1ueyczM3Xalh1+StyNyHkXFaP0xzDS\nyd6RJX3eoxIp4kL6PCUowrR3ZAuuDQ76By5pe9X2joynryp7x+u0LT8l7jaGOTnLgBljhfQ7OsIj\nfd6Ts6K0d8IK5PrZO5RE/cpcBOXNB50JwEvedEzdSt+rTZCnz2rvjOoqmwZiGCukPxbtnXTJ0w9S\n3CztdXj6YQRyvdqouj7uVTYN6UcAnfV34kT6YSp9naSvckeuyjx9mR25sidvBbX38/SjTtmkbVg3\nW/FeH/faO4b0I0A6Ze/k5kZbe4cFlpVe2TthFVzzs3d0k77IjlwgnOwdgN/T57nebYFwK+MQFWIw\nhbGHsZK9I6v0WVM26c3Io6LSPU+fNZArmnJJ2/sVQBPZnBUnpc9r78hszqIqPw4nARrSjwC5uSRl\njCcPnRVxsndk8/RZlT7vxixATxmGMOvpyxZci6vSFwkAhxXIldmcFRc/HzCkHwkSCT2+vmXp2ZwV\nd0+f19oB9JRhCLP2ThzsHdUBWUAsFhBlIJd1c1bQ6w4ThvQjwsyZ6i2e7m7iGYqccuUFmXNyw/L0\nRUh/NNg7OpW6bHsv8hb19MMK5Pp5+qz2jldOv1H6Yxw6fP22Nr6DRFiQnU0+rCxWiB2WFW/Sj3sg\nV3ftnTDsnTA9fd6nA141zrs5i3WBiAKG9COCDtJvbVXr51OIWDw9PakFQwQ8pM+7MQuItgyDito7\nKvL0ZUhfpnBaHLJ3VAVyWTdnGaVvkDZKHxBL25Tx84FwlH5vL0mj80M62ztxTdlMx81ZPE8GVOnb\nLVGj9A1GvdKPO+knEsHECvDV3jH2Tgo6Cq7pzt5RtTkrI4N82Q+DMUrfIK2Uvgjpy/j5AF+evgjp\nA2wWD8+OXOpj+z09qErZlM3Tj6vSDyuQy1NLh17PW6DN3r9R+gZG6QeAJ0+f99QsClbSZ1X6iUSw\nxaMyZTPu9s5oKrjGszkLGLlIGKVvYJR+AHjtHd5ALqA28EoRZPGMBntHpixzXJS+zs1Zbv0bpW9g\nlH4A6A3iVQbADt32Dg/pBy0kqmrvRJmnT9W6SFlmmawfXtLnzfjhIXE6J9a8fqP0DTBzJtmRG5Q9\nwgOdSp83e0dW6QPsal+U9HUo/SB7J8zSyrrsHZmyzDLHJfIEci1LLYnz2jtG6RuMwPjxhBTb2tT1\nqUvpixyOLqv0Af2kr0PpB9k7YR+XqMPeYW0bpac/MECORfSqasm7gUrE3nEqfUP6Bsrr76gutkYR\nhacPsJO+yOYsIN72ThDps8xL9hAV0VIKfmPr8PTdFhiRnb+qNmcBIxcJU3DNAIB6X7+1NT6BXFVK\nnyVtM93sHVnSHxwkOeBBpK3L3mEtyyzq6TvJOJkk8QMv1c5L4CJtRMo2GKVvMAKqSX+sKv10sXfo\nLk0WxedH+jRdM6g2O1XqbsXyZMo4sCwYfk8JvFU2VRO4Vxu/YCvP5izAKH0DDxil7w/WXP04kb7f\n0wMlWpaDNPz8eNanhYwM76P7dJO+Sk8/LNIXUfqsi4RR+gYA1JJ+MkmIdsoUNf3ZEXelL7o5K8je\n4VHm9j5lyRrwt2ZU9MNK+ryZNPa2qjx9kXLMQaTPG8iVXSSM0jcAoJb029sJ4es4g1MkZTPs7B0d\ngVyeujsUfvaOCFmLWjMUsmpdddt0Vfq89o6zf6P0DQCoJX1dfj4glrI5Gjx9XmsHCLZ3WPvLyCAp\nh25Km2deXjZRXD19tzHD9PR12TtG6RsAUEv6uvx8INrsnSg3Z4mSvpe9w1O8DfAO5oZp74w1pa9q\nc5Zb7R2j9A3SRulH6enrTNnUofRV2Tu0L1nS9yJfWdJn2ZHLWxoBiJ70dW3OMkrfAEB6Kf2ODr5z\ncsNU+roCuTrsnShIPwp7R+Zg9DBIXySQK7M5yyh9AwBAXh4JwLIUFQuCTqWflUU+sCzHC1KoUPo8\nKZs6ArlR2zsyKp1Cxt7xyvNn2ZwlupvX7QlBR/aOKk/fKH0DLmRkAPn5wMmT8n3pVPoAfwZPOnj6\nUdg7PPPUae+wqHWa5+9UuLqVflSB3CBPX2aRMErfYAiqLB6dSh/g8/Uti5B+3LN3wg7kdnfz7+51\n6yus7B3a3knCMpuzwlLtOjx9HnvHrcqmUfoGANSRvq4KmxQ8aZt9fUQlBhFDEFhI37LipfT9FpKe\nnvgo/TBIPyxPPyuLbE7kOYhctlRy0PVu9fSN0jcAoFbp67Z3WElfhbUDsJF+by+5mTIz+ftnIX0e\nDx7wt3dUKf2wPH1AnPRFPX0R0k8k3HfABi0UYW7OMkrfYAiqyivrVvo8pK8iiAuwkb6oygeiydMP\nm/SjtHdElL7I5izAnWRVFlwztXcMlMEofW+w5OnLkH7c7R0V2TtR2jtOkqQlof0Ur0jtHbd2ussw\nWJb/azG1dww8kS6ePk/2Troo/bBr76gM5MraOyxECoiTPvW07ceBUlINOluX195xa6d7cxY9mcvr\ntRilb+AJVaTf0kLSP3UhCqXPkqcvujELSG97J+rsnSACSyRGqn3W/P6wSF/nmbdG6Rt4QgXpW1Y4\nefpx9fRFNmYBwUq/u1ttIDcds3fcArKsTwnOtqxHNKog/aCxeMsqOLNxeJ8kjNI3GIIK0j99mpCJ\nbIqkH3hSNsPM3tEZyO3u5l+8/PocLdk7LIrdrS1LuygDuTx5935BX8B9kTBK3wCAGtI/dYqUdNCJ\nuCp9mbGClL6IdZQO2TuDg+LEDfDFA3jUN6DW3uFJDR0cJF9eqb9uZRXGnNJvaWnB8uXLMW/ePFxx\nxRVoa2tzvW7OnDk477zzcP755+NjH/uY8ERHK3JzSRYASzVJL+j28wF+T18F6VOVmkx6XyND+tnZ\n5EZ3ersUXV381pFKe0dX9g4lbdZjG0WyadzGFvX0w8jeCQoy8+4DGJW1d9atW4fly5fjwIEDuPzy\ny7Fu3TrX6xKJBOrq6rBnzx7s3r1beKKjFYmEfK5+3JT+mTNqjm1MJILVvswCk0gE2zG8pB+GvSOb\nvUMPVmeBjNKP0tPnJeUgJe52fZC9M+qU/rZt27B69WoAwOrVq/HMM894Xmvx1OQdg5C1eE6dCkfp\ns6Zsnj6t7qzeINLv7JSLH/hZPCJKPx2yd/r61Dwp8LZl9fTdSF+10ufNrjFKH8Dx48dRWFgIACgs\nLMTx48ddr0skEli2bBkWL16Mxx57THS4UQ1Z0o+bvaNK6QNspC9jJQWRPq+nnw7ZO6rsIZa2vJ5+\nZmZq4xPPeKrsHVXXx1np+649y5cvx7Fjx0b8/Hvf+96w7xOJBBIeZtjvf/97FBcXo7m5GcuXL0dV\nVRWWLl3qeu2999479P+amhrU1NQETH90QIXS123vTJlCFDwLTp8mi4QKBOXqy5K+nx0jqvTjnr0T\nJunzKn0gRbA0qNrXF/x5CoPEncqdJ1CsUunX1dWhrq5OuL3vNF566SXP3xUWFuLYsWMoKirC0aNH\nUVBQ4HpdcXExAGDmzJm47rrrsHv3bibSH0tQofTPOkvdfNwwdSo58IUFYds7f/+ICUG1vUOJ2rJG\nBgWjyt6JivRFPH3arr8/9V719gY/yYat9Fn2AejakesUxPfddx9Xe2F7p7a2Fps2bQIAbNq0Cdde\ne+2Ia7q6unDm755AZ2cnXnzxRZx77rmiQ45apIPSnzqV1PdhQbrZOyoDuZmZ5MvpSwNi2Ts6UjZV\nkD4Lgckqfft4OuwdnsCsm0cfldKXhTDpf+c738FLL72EefPm4dVXX8V3vvMdAEBTUxOuuuoqAMCx\nY8ewdOlSLFq0CBdffDGuvvpqXHHFFWp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J//BhvgyjoiLyxMr65FhURBZOFtKfOpVsaFMl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\nkL6BgYHBGML/B3suibfww4xPAAAAAElFTkSuQmCC\n" 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147 | "png": 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AvfZOHEif98nAzd7RrfRlITV8VlYWNmzYgCuvvBLJZBJ33XUX5s+fj40bNwIA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\nkL6BgYHBGML/B3suibfww4xPAAAAAElFTkSuQmCC\n" | |
| 148 | } |
|
148 | } | |
| 149 | ], |
|
149 | ], | |
| 150 | "prompt_number": 5 |
|
150 | "prompt_number": 5 | |
| 151 | }, |
|
151 | }, | |
| 152 | { |
|
152 | { | |
| 153 | "cell_type": "markdown", |
|
153 | "cell_type": "markdown", | |
| 154 | "metadata": {}, |
|
154 | "metadata": {}, | |
| 155 | "source": [ |
|
155 | "source": [ | |
| 156 | "You can paste blocks of input with prompt markers, such as those from\n", |
|
156 | "You can paste blocks of input with prompt markers, such as those from\n", | |
| 157 | "[the official Python tutorial](http://docs.python.org/tutorial/interpreter.html#interactive-mode)" |
|
157 | "[the official Python tutorial](http://docs.python.org/tutorial/interpreter.html#interactive-mode)" | |
| 158 | ] |
|
158 | ] | |
| 159 | }, |
|
159 | }, | |
| 160 | { |
|
160 | { | |
| 161 | "cell_type": "code", |
|
161 | "cell_type": "code", | |
| 162 | "collapsed": false, |
|
162 | "collapsed": false, | |
| 163 | "input": [ |
|
163 | "input": [ | |
| 164 | ">>> the_world_is_flat = 1\n", |
|
164 | ">>> the_world_is_flat = 1\n", | |
| 165 | ">>> if the_world_is_flat:\n", |
|
165 | ">>> if the_world_is_flat:\n", | |
| 166 | "... print \"Be careful not to fall off!\"" |
|
166 | "... print \"Be careful not to fall off!\"" | |
| 167 | ], |
|
167 | ], | |
| 168 | "language": "python", |
|
168 | "language": "python", | |
| 169 | "metadata": {}, |
|
169 | "metadata": {}, | |
| 170 | "outputs": [ |
|
170 | "outputs": [ | |
| 171 | { |
|
171 | { | |
| 172 | "output_type": "stream", |
|
172 | "output_type": "stream", | |
| 173 | "stream": "stdout", |
|
173 | "stream": "stdout", | |
| 174 | "text": [ |
|
174 | "text": [ | |
| 175 | "Be careful not to fall off!\n" |
|
175 | "Be careful not to fall off!\n" | |
| 176 | ] |
|
176 | ] | |
| 177 | } |
|
177 | } | |
| 178 | ], |
|
178 | ], | |
| 179 | "prompt_number": 6 |
|
179 | "prompt_number": 6 | |
| 180 | }, |
|
180 | }, | |
| 181 | { |
|
181 | { | |
| 182 | "cell_type": "markdown", |
|
182 | "cell_type": "markdown", | |
| 183 | "metadata": {}, |
|
183 | "metadata": {}, | |
| 184 | "source": [ |
|
184 | "source": [ | |
| 185 | "Errors are shown in informative ways:" |
|
185 | "Errors are shown in informative ways:" | |
| 186 | ] |
|
186 | ] | |
| 187 | }, |
|
187 | }, | |
| 188 | { |
|
188 | { | |
| 189 | "cell_type": "code", |
|
189 | "cell_type": "code", | |
| 190 | "collapsed": false, |
|
190 | "collapsed": false, | |
| 191 | "input": [ |
|
191 | "input": [ | |
| 192 | "%run non_existent_file" |
|
192 | "%run non_existent_file" | |
| 193 | ], |
|
193 | ], | |
| 194 | "language": "python", |
|
194 | "language": "python", | |
| 195 | "metadata": {}, |
|
195 | "metadata": {}, | |
| 196 | "outputs": [ |
|
196 | "outputs": [ | |
| 197 | { |
|
197 | { | |
| 198 | "output_type": "stream", |
|
198 | "output_type": "stream", | |
| 199 | "stream": "stderr", |
|
199 | "stream": "stderr", | |
| 200 | "text": [ |
|
200 | "text": [ | |
| 201 | "ERROR: File `u'non_existent_file.py'` not found." |
|
201 | "ERROR: File `u'non_existent_file.py'` not found." | |
| 202 | ] |
|
202 | ] | |
| 203 | } |
|
203 | } | |
| 204 | ], |
|
204 | ], | |
| 205 | "prompt_number": 7 |
|
205 | "prompt_number": 7 | |
| 206 | }, |
|
206 | }, | |
| 207 | { |
|
207 | { | |
| 208 | "cell_type": "code", |
|
208 | "cell_type": "code", | |
| 209 | "collapsed": false, |
|
209 | "collapsed": false, | |
| 210 | "input": [ |
|
210 | "input": [ | |
| 211 | "x = 1\n", |
|
211 | "x = 1\n", | |
| 212 | "y = 4\n", |
|
212 | "y = 4\n", | |
| 213 | "z = y/(1-x)" |
|
213 | "z = y/(1-x)" | |
| 214 | ], |
|
214 | ], | |
| 215 | "language": "python", |
|
215 | "language": "python", | |
| 216 | "metadata": {}, |
|
216 | "metadata": {}, | |
| 217 | "outputs": [ |
|
217 | "outputs": [ | |
| 218 | { |
|
218 | { | |
| 219 | "ename": "ZeroDivisionError", |
|
219 | "ename": "ZeroDivisionError", | |
| 220 | "evalue": "integer division or modulo by zero", |
|
220 | "evalue": "integer division or modulo by zero", | |
| 221 | "output_type": "pyerr", |
|
221 | "output_type": "pyerr", | |
| 222 | "traceback": [ |
|
222 | "traceback": [ | |
| 223 | "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m Traceback (most recent call last)", |
|
223 | "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m Traceback (most recent call last)", | |
| 224 | "\u001b[1;32m<ipython-input-8-dc39888fd1d2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m4\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", |
|
224 | "\u001b[1;32m<ipython-input-8-dc39888fd1d2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m4\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", | |
| 225 | "\u001b[1;31mZeroDivisionError\u001b[0m: integer division or modulo by zero" |
|
225 | "\u001b[1;31mZeroDivisionError\u001b[0m: integer division or modulo by zero" | |
| 226 | ] |
|
226 | ] | |
| 227 | } |
|
227 | } | |
| 228 | ], |
|
228 | ], | |
| 229 | "prompt_number": 8 |
|
229 | "prompt_number": 8 | |
| 230 | }, |
|
230 | }, | |
| 231 | { |
|
231 | { | |
| 232 | "cell_type": "markdown", |
|
232 | "cell_type": "markdown", | |
| 233 | "metadata": {}, |
|
233 | "metadata": {}, | |
| 234 | "source": [ |
|
234 | "source": [ | |
| 235 | "When IPython needs to display additional information (such as providing details on an object via `x?`\n", |
|
235 | "When IPython needs to display additional information (such as providing details on an object via `x?`\n", | |
| 236 | "it will automatically invoke a pager at the bottom of the screen:" |
|
236 | "it will automatically invoke a pager at the bottom of the screen:" | |
| 237 | ] |
|
237 | ] | |
| 238 | }, |
|
238 | }, | |
| 239 | { |
|
239 | { | |
| 240 | "cell_type": "code", |
|
240 | "cell_type": "code", | |
| 241 | "collapsed": false, |
|
241 | "collapsed": false, | |
| 242 | "input": [ |
|
242 | "input": [ | |
| 243 | "magic" |
|
243 | "magic" | |
| 244 | ], |
|
244 | ], | |
| 245 | "language": "python", |
|
245 | "language": "python", | |
| 246 | "metadata": {}, |
|
246 | "metadata": {}, | |
| 247 | "outputs": [], |
|
247 | "outputs": [], | |
| 248 | "prompt_number": 18 |
|
248 | "prompt_number": 18 | |
| 249 | }, |
|
249 | }, | |
| 250 | { |
|
250 | { | |
| 251 | "cell_type": "markdown", |
|
251 | "cell_type": "markdown", | |
| 252 | "metadata": {}, |
|
252 | "metadata": {}, | |
| 253 | "source": [ |
|
253 | "source": [ | |
| 254 | "## Non-blocking output of kernel\n", |
|
254 | "## Non-blocking output of kernel\n", | |
| 255 | "\n", |
|
255 | "\n", | |
| 256 | "If you execute the next cell, you will see the output arriving as it is generated, not all at the end." |
|
256 | "If you execute the next cell, you will see the output arriving as it is generated, not all at the end." | |
| 257 | ] |
|
257 | ] | |
| 258 | }, |
|
258 | }, | |
| 259 | { |
|
259 | { | |
| 260 | "cell_type": "code", |
|
260 | "cell_type": "code", | |
| 261 | "collapsed": false, |
|
261 | "collapsed": false, | |
| 262 | "input": [ |
|
262 | "input": [ | |
| 263 | "import time, sys\n", |
|
263 | "import time, sys\n", | |
| 264 | "for i in range(8):\n", |
|
264 | "for i in range(8):\n", | |
| 265 | " print i,\n", |
|
265 | " print i,\n", | |
| 266 | " time.sleep(0.5)" |
|
266 | " time.sleep(0.5)" | |
| 267 | ], |
|
267 | ], | |
| 268 | "language": "python", |
|
268 | "language": "python", | |
| 269 | "metadata": {}, |
|
269 | "metadata": {}, | |
| 270 | "outputs": [ |
|
270 | "outputs": [ | |
| 271 | { |
|
271 | { | |
| 272 | "output_type": "stream", |
|
272 | "output_type": "stream", | |
| 273 | "stream": "stdout", |
|
273 | "stream": "stdout", | |
| 274 | "text": [ |
|
274 | "text": [ | |
| 275 | "0 " |
|
275 | "0 " | |
| 276 | ] |
|
276 | ] | |
| 277 | }, |
|
277 | }, | |
| 278 | { |
|
278 | { | |
| 279 | "output_type": "stream", |
|
279 | "output_type": "stream", | |
| 280 | "stream": "stdout", |
|
280 | "stream": "stdout", | |
| 281 | "text": [ |
|
281 | "text": [ | |
| 282 | "1 " |
|
282 | "1 " | |
| 283 | ] |
|
283 | ] | |
| 284 | }, |
|
284 | }, | |
| 285 | { |
|
285 | { | |
| 286 | "output_type": "stream", |
|
286 | "output_type": "stream", | |
| 287 | "stream": "stdout", |
|
287 | "stream": "stdout", | |
| 288 | "text": [ |
|
288 | "text": [ | |
| 289 | "2 " |
|
289 | "2 " | |
| 290 | ] |
|
290 | ] | |
| 291 | }, |
|
291 | }, | |
| 292 | { |
|
292 | { | |
| 293 | "output_type": "stream", |
|
293 | "output_type": "stream", | |
| 294 | "stream": "stdout", |
|
294 | "stream": "stdout", | |
| 295 | "text": [ |
|
295 | "text": [ | |
| 296 | "3 " |
|
296 | "3 " | |
| 297 | ] |
|
297 | ] | |
| 298 | }, |
|
298 | }, | |
| 299 | { |
|
299 | { | |
| 300 | "output_type": "stream", |
|
300 | "output_type": "stream", | |
| 301 | "stream": "stdout", |
|
301 | "stream": "stdout", | |
| 302 | "text": [ |
|
302 | "text": [ | |
| 303 | "4 " |
|
303 | "4 " | |
| 304 | ] |
|
304 | ] | |
| 305 | }, |
|
305 | }, | |
| 306 | { |
|
306 | { | |
| 307 | "output_type": "stream", |
|
307 | "output_type": "stream", | |
| 308 | "stream": "stdout", |
|
308 | "stream": "stdout", | |
| 309 | "text": [ |
|
309 | "text": [ | |
| 310 | "5 " |
|
310 | "5 " | |
| 311 | ] |
|
311 | ] | |
| 312 | }, |
|
312 | }, | |
| 313 | { |
|
313 | { | |
| 314 | "output_type": "stream", |
|
314 | "output_type": "stream", | |
| 315 | "stream": "stdout", |
|
315 | "stream": "stdout", | |
| 316 | "text": [ |
|
316 | "text": [ | |
| 317 | "6 " |
|
317 | "6 " | |
| 318 | ] |
|
318 | ] | |
| 319 | }, |
|
319 | }, | |
| 320 | { |
|
320 | { | |
| 321 | "output_type": "stream", |
|
321 | "output_type": "stream", | |
| 322 | "stream": "stdout", |
|
322 | "stream": "stdout", | |
| 323 | "text": [ |
|
323 | "text": [ | |
| 324 | "7\n" |
|
324 | "7\n" | |
| 325 | ] |
|
325 | ] | |
| 326 | } |
|
326 | } | |
| 327 | ], |
|
327 | ], | |
| 328 | "prompt_number": 19 |
|
328 | "prompt_number": 19 | |
| 329 | }, |
|
329 | }, | |
| 330 | { |
|
330 | { | |
| 331 | "cell_type": "markdown", |
|
331 | "cell_type": "markdown", | |
| 332 | "metadata": {}, |
|
332 | "metadata": {}, | |
| 333 | "source": [ |
|
333 | "source": [ | |
| 334 | "## Clean crash and restart\n", |
|
334 | "## Clean crash and restart\n", | |
| 335 | "\n", |
|
335 | "\n", | |
| 336 | "We call the low-level system libc.time routine with the wrong argument via\n", |
|
336 | "We call the low-level system libc.time routine with the wrong argument via\n", | |
| 337 | "ctypes to segfault the Python interpreter:" |
|
337 | "ctypes to segfault the Python interpreter:" | |
| 338 | ] |
|
338 | ] | |
| 339 | }, |
|
339 | }, | |
| 340 | { |
|
340 | { | |
| 341 | "cell_type": "code", |
|
341 | "cell_type": "code", | |
| 342 | "collapsed": false, |
|
342 | "collapsed": false, | |
| 343 | "input": [ |
|
343 | "input": [ | |
| 344 | "import sys\n", |
|
344 | "import sys\n", | |
| 345 | "from ctypes import CDLL\n", |
|
345 | "from ctypes import CDLL\n", | |
| 346 | "# This will crash a Linux or Mac system; equivalent calls can be made on Windows\n", |
|
346 | "# This will crash a Linux or Mac system; equivalent calls can be made on Windows\n", | |
| 347 | "dll = 'dylib' if sys.platform == 'darwin' else '.so.6'\n", |
|
347 | "dll = 'dylib' if sys.platform == 'darwin' else '.so.6'\n", | |
| 348 | "libc = CDLL(\"libc.%s\" % dll) \n", |
|
348 | "libc = CDLL(\"libc.%s\" % dll) \n", | |
| 349 | "libc.time(-1) # BOOM!!" |
|
349 | "libc.time(-1) # BOOM!!" | |
| 350 | ], |
|
350 | ], | |
| 351 | "language": "python", |
|
351 | "language": "python", | |
| 352 | "metadata": {}, |
|
352 | "metadata": {}, | |
| 353 | "outputs": [], |
|
353 | "outputs": [], | |
| 354 | "prompt_number": "*" |
|
354 | "prompt_number": "*" | |
| 355 | }, |
|
355 | }, | |
| 356 | { |
|
356 | { | |
| 357 | "cell_type": "markdown", |
|
357 | "cell_type": "markdown", | |
| 358 | "metadata": {}, |
|
358 | "metadata": {}, | |
| 359 | "source": [ |
|
359 | "source": [ | |
| 360 | "## Markdown cells can contain formatted text and code\n", |
|
360 | "## Markdown cells can contain formatted text and code\n", | |
| 361 | "\n", |
|
361 | "\n", | |
| 362 | "You can *italicize*, **boldface**\n", |
|
362 | "You can *italicize*, **boldface**\n", | |
| 363 | "\n", |
|
363 | "\n", | |
| 364 | "* build\n", |
|
364 | "* build\n", | |
| 365 | "* lists\n", |
|
365 | "* lists\n", | |
| 366 | "\n", |
|
366 | "\n", | |
| 367 | "and embed code meant for illustration instead of execution in Python:\n", |
|
367 | "and embed code meant for illustration instead of execution in Python:\n", | |
| 368 | "\n", |
|
368 | "\n", | |
| 369 | " def f(x):\n", |
|
369 | " def f(x):\n", | |
| 370 | " \"\"\"a docstring\"\"\"\n", |
|
370 | " \"\"\"a docstring\"\"\"\n", | |
| 371 | " return x**2\n", |
|
371 | " return x**2\n", | |
| 372 | "\n", |
|
372 | "\n", | |
| 373 | "or other languages:\n", |
|
373 | "or other languages:\n", | |
| 374 | "\n", |
|
374 | "\n", | |
| 375 | " if (i=0; i<n; i++) {\n", |
|
375 | " if (i=0; i<n; i++) {\n", | |
| 376 | " printf(\"hello %d\\n\", i);\n", |
|
376 | " printf(\"hello %d\\n\", i);\n", | |
| 377 | " x += 4;\n", |
|
377 | " x += 4;\n", | |
| 378 | " }" |
|
378 | " }" | |
| 379 | ] |
|
379 | ] | |
| 380 | }, |
|
380 | }, | |
| 381 | { |
|
381 | { | |
| 382 | "cell_type": "markdown", |
|
382 | "cell_type": "markdown", | |
| 383 | "metadata": {}, |
|
383 | "metadata": {}, | |
| 384 | "source": [ |
|
384 | "source": [ | |
| 385 | "Courtesy of MathJax, you can include mathematical expressions both inline: \n", |
|
385 | "Courtesy of MathJax, you can include mathematical expressions both inline: \n", | |
| 386 | "$e^{i\\pi} + 1 = 0$ and displayed:\n", |
|
386 | "$e^{i\\pi} + 1 = 0$ and displayed:\n", | |
| 387 | "\n", |
|
387 | "\n", | |
| 388 | "$$e^x=\\sum_{i=0}^\\infty \\frac{1}{i!}x^i$$" |
|
388 | "$$e^x=\\sum_{i=0}^\\infty \\frac{1}{i!}x^i$$" | |
| 389 | ] |
|
389 | ] | |
| 390 | }, |
|
390 | }, | |
| 391 | { |
|
391 | { | |
| 392 | "cell_type": "markdown", |
|
392 | "cell_type": "markdown", | |
| 393 | "metadata": {}, |
|
393 | "metadata": {}, | |
| 394 | "source": [ |
|
394 | "source": [ | |
| 395 | "## Rich displays: include anyting a browser can show\n", |
|
395 | "## Rich displays: include anyting a browser can show\n", | |
| 396 | "\n", |
|
396 | "\n", | |
| 397 | "Note that we have an actual protocol for this, see the `display_protocol` notebook for further details.\n", |
|
397 | "Note that we have an actual protocol for this, see the `display_protocol` notebook for further details.\n", | |
| 398 | "\n", |
|
398 | "\n", | |
| 399 | "### Images" |
|
399 | "### Images" | |
| 400 | ] |
|
400 | ] | |
| 401 | }, |
|
401 | }, | |
| 402 | { |
|
402 | { | |
| 403 | "cell_type": "code", |
|
403 | "cell_type": "code", | |
| 404 | "collapsed": false, |
|
404 | "collapsed": false, | |
| 405 | "input": [ |
|
405 | "input": [ | |
| 406 | "from IPython.display import Image\n", |
|
406 | "from IPython.display import Image\n", | |
| 407 | "Image(filename='../../source/_static/logo.png')" |
|
407 | "Image(filename='../../source/_static/logo.png')" | |
| 408 | ], |
|
408 | ], | |
| 409 | "language": "python", |
|
409 | "language": "python", | |
| 410 | "metadata": {}, |
|
410 | "metadata": {}, | |
| 411 | "outputs": [ |
|
411 | "outputs": [ | |
| 412 | { |
|
412 | { | |
| 413 | "output_type": "pyout", |
|
413 | "output_type": "pyout", | |
| 414 | "png": 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414 | "png": 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| |
| 415 | "prompt_number": 1, |
|
415 | "prompt_number": 1, | |
| 416 | "text": [ |
|
416 | "text": [ | |
| 417 | "<IPython.core.display.Image at 0x10faeafd0>" |
|
417 | "<IPython.core.display.Image at 0x10faeafd0>" | |
| 418 | ] |
|
418 | ] | |
| 419 | } |
|
419 | } | |
| 420 | ], |
|
420 | ], | |
| 421 | "prompt_number": 1 |
|
421 | "prompt_number": 1 | |
| 422 | }, |
|
422 | }, | |
| 423 | { |
|
423 | { | |
| 424 | "cell_type": "markdown", |
|
424 | "cell_type": "markdown", | |
| 425 | "metadata": {}, |
|
425 | "metadata": {}, | |
| 426 | "source": [ |
|
426 | "source": [ | |
| 427 | "An image can also be displayed from raw data or a url" |
|
427 | "An image can also be displayed from raw data or a url" | |
| 428 | ] |
|
428 | ] | |
| 429 | }, |
|
429 | }, | |
| 430 | { |
|
430 | { | |
| 431 | "cell_type": "code", |
|
431 | "cell_type": "code", | |
| 432 | "collapsed": false, |
|
432 | "collapsed": false, | |
| 433 | "input": [ |
|
433 | "input": [ | |
| 434 | "Image(url='http://python.org/images/python-logo.gif')" |
|
434 | "Image(url='http://python.org/images/python-logo.gif')" | |
| 435 | ], |
|
435 | ], | |
| 436 | "language": "python", |
|
436 | "language": "python", | |
| 437 | "metadata": {}, |
|
437 | "metadata": {}, | |
| 438 | "outputs": [ |
|
438 | "outputs": [ | |
| 439 | { |
|
439 | { | |
| 440 | "html": [ |
|
440 | "html": [ | |
| 441 | "<img src=\"http://python.org/images/python-logo.gif\" />" |
|
441 | "<img src=\"http://python.org/images/python-logo.gif\" />" | |
| 442 | ], |
|
442 | ], | |
| 443 | "output_type": "pyout", |
|
443 | "output_type": "pyout", | |
| 444 | "prompt_number": 2, |
|
444 | "prompt_number": 2, | |
| 445 | "text": [ |
|
445 | "text": [ | |
| 446 | "<IPython.core.display.Image at 0x1060e7410>" |
|
446 | "<IPython.core.display.Image at 0x1060e7410>" | |
| 447 | ] |
|
447 | ] | |
| 448 | } |
|
448 | } | |
| 449 | ], |
|
449 | ], | |
| 450 | "prompt_number": 2 |
|
450 | "prompt_number": 2 | |
| 451 | }, |
|
451 | }, | |
| 452 | { |
|
452 | { | |
| 453 | "cell_type": "markdown", |
|
453 | "cell_type": "markdown", | |
| 454 | "metadata": {}, |
|
454 | "metadata": {}, | |
| 455 | "source": [ |
|
455 | "source": [ | |
| 456 | "SVG images are also supported out of the box (since modern browsers do a good job of rendering them):" |
|
456 | "SVG images are also supported out of the box (since modern browsers do a good job of rendering them):" | |
| 457 | ] |
|
457 | ] | |
| 458 | }, |
|
458 | }, | |
| 459 | { |
|
459 | { | |
| 460 | "cell_type": "code", |
|
460 | "cell_type": "code", | |
| 461 | "collapsed": false, |
|
461 | "collapsed": false, | |
| 462 | "input": [ |
|
462 | "input": [ | |
| 463 | "from IPython.display import SVG\n", |
|
463 | "from IPython.display import SVG\n", | |
| 464 | "SVG(filename='python-logo.svg')" |
|
464 | "SVG(filename='python-logo.svg')" | |
| 465 | ], |
|
465 | ], | |
| 466 | "language": "python", |
|
466 | "language": "python", | |
| 467 | "metadata": {}, |
|
467 | "metadata": {}, | |
| 468 | "outputs": [ |
|
468 | "outputs": [ | |
| 469 | { |
|
469 | { | |
| 470 | "output_type": "pyout", |
|
470 | "output_type": "pyout", | |
| 471 | "prompt_number": 3, |
|
471 | "prompt_number": 3, | |
| 472 | "svg": [ |
|
472 | "svg": [ | |
| 473 | "<svg height=\"115.02pt\" id=\"svg2\" inkscape:version=\"0.43\" sodipodi:docbase=\"/home/sdeibel\" sodipodi:docname=\"logo-python-generic.svg\" sodipodi:version=\"0.32\" version=\"1.0\" width=\"388.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:cc=\"http://web.resource.org/cc/\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:inkscape=\"http://www.inkscape.org/namespaces/inkscape\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\" xmlns:sodipodi=\"http://inkscape.sourceforge.net/DTD/sodipodi-0.dtd\" xmlns:svg=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", |
|
473 | "<svg height=\"115.02pt\" id=\"svg2\" inkscape:version=\"0.43\" sodipodi:docbase=\"/home/sdeibel\" sodipodi:docname=\"logo-python-generic.svg\" sodipodi:version=\"0.32\" version=\"1.0\" width=\"388.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:cc=\"http://web.resource.org/cc/\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:inkscape=\"http://www.inkscape.org/namespaces/inkscape\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\" xmlns:sodipodi=\"http://inkscape.sourceforge.net/DTD/sodipodi-0.dtd\" xmlns:svg=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", | |
| 474 | " <metadata id=\"metadata2193\">\n", |
|
474 | " <metadata id=\"metadata2193\">\n", | |
| 475 | " <rdf:RDF>\n", |
|
475 | " <rdf:RDF>\n", | |
| 476 | " <cc:Work rdf:about=\"\">\n", |
|
476 | " <cc:Work rdf:about=\"\">\n", | |
| 477 | " <dc:format>image/svg+xml</dc:format>\n", |
|
477 | " <dc:format>image/svg+xml</dc:format>\n", | |
| 478 | " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", |
|
478 | " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", | |
| 479 | " </cc:Work>\n", |
|
479 | " </cc:Work>\n", | |
| 480 | " </rdf:RDF>\n", |
|
480 | " </rdf:RDF>\n", | |
| 481 | " </metadata>\n", |
|
481 | " </metadata>\n", | |
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| 530 | " <path d=\"M 463.5544,26.909383 L 465.11635,26.909383 L 465.11635,17.113143 L 468.81648,17.113143 L 468.81648,15.945483 L 459.85427,15.945483 L 459.85427,17.113143 L 463.5544,17.113143 L 463.5544,26.909383 M 470.20142,26.909383 L 471.53589,26.909383 L 471.53589,17.962353 L 474.4323,26.908259 L 475.91799,26.908259 L 478.93615,17.992683 L 478.93615,26.909383 L 480.39194,26.909383 L 480.39194,15.945483 L 478.46605,15.945483 L 475.16774,25.33834 L 472.35477,15.945483 L 470.20142,15.945483 L 470.20142,26.909383\" id=\"text3004\" style=\"font-size:15.16445827px;font-style:normal;font-weight:normal;line-height:125%;fill:#646464;fill-opacity:1;stroke:none;stroke-width:1px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;font-family:Bitstream Vera Sans\"/>\n", |
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| 531 | " <path d=\"M 110.46717 132.28575 A 48.948284 8.6066771 0 1 1 12.570599,132.28575 A 48.948284 8.6066771 0 1 1 110.46717 132.28575 z\" id=\"path1894\" style=\"opacity:0.44382019;fill:url(#radialGradient1480);fill-opacity:1;fill-rule:nonzero;stroke:none;stroke-width:20;stroke-miterlimit:4;stroke-dasharray:none;stroke-opacity:1\" transform=\"matrix(0.73406,0,0,0.809524,16.24958,27.00935)\"/>\n", |
|
531 | " <path d=\"M 110.46717 132.28575 A 48.948284 8.6066771 0 1 1 12.570599,132.28575 A 48.948284 8.6066771 0 1 1 110.46717 132.28575 z\" id=\"path1894\" style=\"opacity:0.44382019;fill:url(#radialGradient1480);fill-opacity:1;fill-rule:nonzero;stroke:none;stroke-width:20;stroke-miterlimit:4;stroke-dasharray:none;stroke-opacity:1\" transform=\"matrix(0.73406,0,0,0.809524,16.24958,27.00935)\"/>\n", | |
| 532 | " </g>\n", |
|
532 | " </g>\n", | |
| 533 | "</svg>" |
|
533 | "</svg>" | |
| 534 | ], |
|
534 | ], | |
| 535 | "text": [ |
|
535 | "text": [ | |
| 536 | "<IPython.core.display.SVG at 0x10fb998d0>" |
|
536 | "<IPython.core.display.SVG at 0x10fb998d0>" | |
| 537 | ] |
|
537 | ] | |
| 538 | } |
|
538 | } | |
| 539 | ], |
|
539 | ], | |
| 540 | "prompt_number": 3 |
|
540 | "prompt_number": 3 | |
| 541 | }, |
|
541 | }, | |
| 542 | { |
|
542 | { | |
| 543 | "cell_type": "markdown", |
|
543 | "cell_type": "markdown", | |
| 544 | "metadata": {}, |
|
544 | "metadata": {}, | |
| 545 | "source": [ |
|
545 | "source": [ | |
| 546 | "#### Embedded vs Non-embedded Images" |
|
546 | "#### Embedded vs Non-embedded Images" | |
| 547 | ] |
|
547 | ] | |
| 548 | }, |
|
548 | }, | |
| 549 | { |
|
549 | { | |
| 550 | "cell_type": "markdown", |
|
550 | "cell_type": "markdown", | |
| 551 | "metadata": {}, |
|
551 | "metadata": {}, | |
| 552 | "source": [ |
|
552 | "source": [ | |
| 553 | "As of IPython 0.13, images are embedded by default for compatibility with QtConsole, and the ability to still be displayed offline.\n", |
|
553 | "As of IPython 0.13, images are embedded by default for compatibility with QtConsole, and the ability to still be displayed offline.\n", | |
| 554 | "\n", |
|
554 | "\n", | |
| 555 | "Let's look at the differences:" |
|
555 | "Let's look at the differences:" | |
| 556 | ] |
|
556 | ] | |
| 557 | }, |
|
557 | }, | |
| 558 | { |
|
558 | { | |
| 559 | "cell_type": "code", |
|
559 | "cell_type": "code", | |
| 560 | "collapsed": false, |
|
560 | "collapsed": false, | |
| 561 | "input": [ |
|
561 | "input": [ | |
| 562 | "# by default Image data are embedded\n", |
|
562 | "# by default Image data are embedded\n", | |
| 563 | "Embed = Image( 'http://scienceview.berkeley.edu/view/images/newview.jpg')\n", |
|
563 | "Embed = Image( 'http://scienceview.berkeley.edu/view/images/newview.jpg')\n", | |
| 564 | "\n", |
|
564 | "\n", | |
| 565 | "# if kwarg `url` is given, the embedding is assumed to be false\n", |
|
565 | "# if kwarg `url` is given, the embedding is assumed to be false\n", | |
| 566 | "SoftLinked = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg')\n", |
|
566 | "SoftLinked = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg')\n", | |
| 567 | "\n", |
|
567 | "\n", | |
| 568 | "# In each case, embed can be specified explicitly with the `embed` kwarg\n", |
|
568 | "# In each case, embed can be specified explicitly with the `embed` kwarg\n", | |
| 569 | "# ForceEmbed = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg', embed=True)" |
|
569 | "# ForceEmbed = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg', embed=True)" | |
| 570 | ], |
|
570 | ], | |
| 571 | "language": "python", |
|
571 | "language": "python", | |
| 572 | "metadata": {}, |
|
572 | "metadata": {}, | |
| 573 | "outputs": [], |
|
573 | "outputs": [], | |
| 574 | "prompt_number": 4 |
|
574 | "prompt_number": 4 | |
| 575 | }, |
|
575 | }, | |
| 576 | { |
|
576 | { | |
| 577 | "cell_type": "markdown", |
|
577 | "cell_type": "markdown", | |
| 578 | "metadata": {}, |
|
578 | "metadata": {}, | |
| 579 | "source": [ |
|
579 | "source": [ | |
| 580 | "Today's image from a webcam at Berkeley, (at the time I created this notebook). This should also work in the Qtconsole.\n", |
|
580 | "Today's image from a webcam at Berkeley, (at the time I created this notebook). This should also work in the Qtconsole.\n", | |
| 581 | "Drawback is that the saved notebook will be larger, but the image will still be present offline." |
|
581 | "Drawback is that the saved notebook will be larger, but the image will still be present offline." | |
| 582 | ] |
|
582 | ] | |
| 583 | }, |
|
583 | }, | |
| 584 | { |
|
584 | { | |
| 585 | "cell_type": "code", |
|
585 | "cell_type": "code", | |
| 586 | "collapsed": false, |
|
586 | "collapsed": false, | |
| 587 | "input": [ |
|
587 | "input": [ | |
| 588 | "Embed" |
|
588 | "Embed" | |
| 589 | ], |
|
589 | ], | |
| 590 | "language": "python", |
|
590 | "language": "python", | |
| 591 | "metadata": {}, |
|
591 | "metadata": {}, | |
| 592 | "outputs": [ |
|
592 | "outputs": [ | |
| 593 | { |
|
593 | { | |
| 594 | "jpeg": 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+lASoKhSUc4oCA1M0AM+tDNAHPGaG6oAbsVCc1RQpNAmhAZoE0KLm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JsEjY4wSD5ZrN0s+s9D9PaXqHQ/Ul3rd9ds/i313vAgg+nw8Rs7qAQSuMHO0epxzknJKK/3Nc1D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\nfwpJIyi7nVphszkjeCo54rKUor2g7esdX/Grqbpq66YurnqC60m+s7Sxu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+lASoKhSUc4oCA1M0AM+tDNAHPGaG6oAbsVCc1RQpNAmhAZoE0KLm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JsEjY4wSD5ZrN0s+s9D9PaXqHQ/Ul3rd9ds/i313vAgg+nw8Rs7qAQSuMHO0epxzknJKK/3Nc1D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\nfwpJIyi7nVphszkjeCo54rKUor2g7esdX/Grqbpq66YurnqC60m+s7Sxu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| |
| 595 | "output_type": "pyout", |
|
595 | "output_type": "pyout", | |
| 596 | "prompt_number": 5, |
|
596 | "prompt_number": 5, | |
| 597 | "text": [ |
|
597 | "text": [ | |
| 598 | "<IPython.core.display.Image at 0x10fb99b50>" |
|
598 | "<IPython.core.display.Image at 0x10fb99b50>" | |
| 599 | ] |
|
599 | ] | |
| 600 | } |
|
600 | } | |
| 601 | ], |
|
601 | ], | |
| 602 | "prompt_number": 5 |
|
602 | "prompt_number": 5 | |
| 603 | }, |
|
603 | }, | |
| 604 | { |
|
604 | { | |
| 605 | "cell_type": "markdown", |
|
605 | "cell_type": "markdown", | |
| 606 | "metadata": {}, |
|
606 | "metadata": {}, | |
| 607 | "source": [ |
|
607 | "source": [ | |
| 608 | "Today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connexion, that should be different from the previous one. This will not work on Qtconsole.\n", |
|
608 | "Today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connexion, that should be different from the previous one. This will not work on Qtconsole.\n", | |
| 609 | "Notebook saved with this kind of image will be lighter and always reflect the current version of the source, but the image won't display offline." |
|
609 | "Notebook saved with this kind of image will be lighter and always reflect the current version of the source, but the image won't display offline." | |
| 610 | ] |
|
610 | ] | |
| 611 | }, |
|
611 | }, | |
| 612 | { |
|
612 | { | |
| 613 | "cell_type": "code", |
|
613 | "cell_type": "code", | |
| 614 | "collapsed": false, |
|
614 | "collapsed": false, | |
| 615 | "input": [ |
|
615 | "input": [ | |
| 616 | "SoftLinked" |
|
616 | "SoftLinked" | |
| 617 | ], |
|
617 | ], | |
| 618 | "language": "python", |
|
618 | "language": "python", | |
| 619 | "metadata": {}, |
|
619 | "metadata": {}, | |
| 620 | "outputs": [ |
|
620 | "outputs": [ | |
| 621 | { |
|
621 | { | |
| 622 | "html": [ |
|
622 | "html": [ | |
| 623 | "<img src=\"http://scienceview.berkeley.edu/view/images/newview.jpg\" />" |
|
623 | "<img src=\"http://scienceview.berkeley.edu/view/images/newview.jpg\" />" | |
| 624 | ], |
|
624 | ], | |
| 625 | "output_type": "pyout", |
|
625 | "output_type": "pyout", | |
| 626 | "prompt_number": 6, |
|
626 | "prompt_number": 6, | |
| 627 | "text": [ |
|
627 | "text": [ | |
| 628 | "<IPython.core.display.Image at 0x10fb99b10>" |
|
628 | "<IPython.core.display.Image at 0x10fb99b10>" | |
| 629 | ] |
|
629 | ] | |
| 630 | } |
|
630 | } | |
| 631 | ], |
|
631 | ], | |
| 632 | "prompt_number": 6 |
|
632 | "prompt_number": 6 | |
| 633 | }, |
|
633 | }, | |
| 634 | { |
|
634 | { | |
| 635 | "cell_type": "markdown", |
|
635 | "cell_type": "markdown", | |
| 636 | "metadata": {}, |
|
636 | "metadata": {}, | |
| 637 | "source": [ |
|
637 | "source": [ | |
| 638 | "Of course, if you re-run the all notebook, the two images will be the same again." |
|
638 | "Of course, if you re-run the all notebook, the two images will be the same again." | |
| 639 | ] |
|
639 | ] | |
| 640 | }, |
|
640 | }, | |
| 641 | { |
|
641 | { | |
| 642 | "cell_type": "markdown", |
|
642 | "cell_type": "markdown", | |
| 643 | "metadata": {}, |
|
643 | "metadata": {}, | |
| 644 | "source": [ |
|
644 | "source": [ | |
| 645 | "### Video" |
|
645 | "### Video" | |
| 646 | ] |
|
646 | ] | |
| 647 | }, |
|
647 | }, | |
| 648 | { |
|
648 | { | |
| 649 | "cell_type": "markdown", |
|
649 | "cell_type": "markdown", | |
| 650 | "metadata": {}, |
|
650 | "metadata": {}, | |
| 651 | "source": [ |
|
651 | "source": [ | |
| 652 | "And more exotic objects can also be displayed, as long as their representation supports \n", |
|
652 | "And more exotic objects can also be displayed, as long as their representation supports \n", | |
| 653 | "the IPython display protocol.\n", |
|
653 | "the IPython display protocol.\n", | |
| 654 | "\n", |
|
654 | "\n", | |
| 655 | "For example, videos hosted externally on YouTube are easy to load (and writing a similar wrapper for other\n", |
|
655 | "For example, videos hosted externally on YouTube are easy to load (and writing a similar wrapper for other\n", | |
| 656 | "hosted content is trivial):" |
|
656 | "hosted content is trivial):" | |
| 657 | ] |
|
657 | ] | |
| 658 | }, |
|
658 | }, | |
| 659 | { |
|
659 | { | |
| 660 | "cell_type": "code", |
|
660 | "cell_type": "code", | |
| 661 | "collapsed": false, |
|
661 | "collapsed": false, | |
| 662 | "input": [ |
|
662 | "input": [ | |
| 663 | "from IPython.display import YouTubeVideo\n", |
|
663 | "from IPython.display import YouTubeVideo\n", | |
| 664 | "# a talk about IPython at Sage Days at U. Washington, Seattle.\n", |
|
664 | "# a talk about IPython at Sage Days at U. Washington, Seattle.\n", | |
| 665 | "# Video credit: William Stein.\n", |
|
665 | "# Video credit: William Stein.\n", | |
| 666 | "YouTubeVideo('1j_HxD4iLn8')" |
|
666 | "YouTubeVideo('1j_HxD4iLn8')" | |
| 667 | ], |
|
667 | ], | |
| 668 | "language": "python", |
|
668 | "language": "python", | |
| 669 | "metadata": {}, |
|
669 | "metadata": {}, | |
| 670 | "outputs": [ |
|
670 | "outputs": [ | |
| 671 | { |
|
671 | { | |
| 672 | "html": [ |
|
672 | "html": [ | |
| 673 | "\n", |
|
673 | "\n", | |
| 674 | " <iframe\n", |
|
674 | " <iframe\n", | |
| 675 | " width=\"400\"\n", |
|
675 | " width=\"400\"\n", | |
| 676 | " height=\"300\"\n", |
|
676 | " height=\"300\"\n", | |
| 677 | " src=\"http://www.youtube.com/embed/1j_HxD4iLn8\"\n", |
|
677 | " src=\"http://www.youtube.com/embed/1j_HxD4iLn8\"\n", | |
| 678 | " frameborder=\"0\"\n", |
|
678 | " frameborder=\"0\"\n", | |
| 679 | " allowfullscreen\n", |
|
679 | " allowfullscreen\n", | |
| 680 | " ></iframe>\n", |
|
680 | " ></iframe>\n", | |
| 681 | " " |
|
681 | " " | |
| 682 | ], |
|
682 | ], | |
| 683 | "output_type": "pyout", |
|
683 | "output_type": "pyout", | |
| 684 | "prompt_number": 7, |
|
684 | "prompt_number": 7, | |
| 685 | "text": [ |
|
685 | "text": [ | |
| 686 | "<IPython.lib.display.YouTubeVideo at 0x10fba2190>" |
|
686 | "<IPython.lib.display.YouTubeVideo at 0x10fba2190>" | |
| 687 | ] |
|
687 | ] | |
| 688 | } |
|
688 | } | |
| 689 | ], |
|
689 | ], | |
| 690 | "prompt_number": 7 |
|
690 | "prompt_number": 7 | |
| 691 | }, |
|
691 | }, | |
| 692 | { |
|
692 | { | |
| 693 | "cell_type": "markdown", |
|
693 | "cell_type": "markdown", | |
| 694 | "metadata": {}, |
|
694 | "metadata": {}, | |
| 695 | "source": [ |
|
695 | "source": [ | |
| 696 | "Using the nascent video capabilities of modern browsers, you may also be able to display local\n", |
|
696 | "Using the nascent video capabilities of modern browsers, you may also be able to display local\n", | |
| 697 | "videos. At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n", |
|
697 | "videos. At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n", | |
| 698 | "we will continue testing this and looking for ways to make it more robust. \n", |
|
698 | "we will continue testing this and looking for ways to make it more robust. \n", | |
| 699 | "\n", |
|
699 | "\n", | |
| 700 | "The following cell loads a local file called `animation.m4v`, encodes the raw video as base64 for http\n", |
|
700 | "The following cell loads a local file called `animation.m4v`, encodes the raw video as base64 for http\n", | |
| 701 | "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control\n", |
|
701 | "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control\n", | |
| 702 | "bar at the bottom with a play/pause button and a location slider." |
|
702 | "bar at the bottom with a play/pause button and a location slider." | |
| 703 | ] |
|
703 | ] | |
| 704 | }, |
|
704 | }, | |
| 705 | { |
|
705 | { | |
| 706 | "cell_type": "code", |
|
706 | "cell_type": "code", | |
| 707 | "collapsed": false, |
|
707 | "collapsed": false, | |
| 708 | "input": [ |
|
708 | "input": [ | |
| 709 | "from IPython.display import HTML\n", |
|
709 | "from IPython.display import HTML\n", | |
| 710 | "video = open(\"animation.m4v\", \"rb\").read()\n", |
|
710 | "video = open(\"animation.m4v\", \"rb\").read()\n", | |
| 711 | "video_encoded = video.encode(\"base64\")\n", |
|
711 | "video_encoded = video.encode(\"base64\")\n", | |
| 712 | "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n", |
|
712 | "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n", | |
| 713 | "HTML(data=video_tag)" |
|
713 | "HTML(data=video_tag)" | |
| 714 | ], |
|
714 | ], | |
| 715 | "language": "python", |
|
715 | "language": "python", | |
| 716 | "metadata": {}, |
|
716 | "metadata": {}, | |
| 717 | "outputs": [ |
|
717 | "outputs": [ | |
| 718 | { |
|
718 | { | |
| 719 | "html": [ |
|
719 | "html": [ | |
| 720 | "<video controls alt=\"test\" src=\"data:video/x-m4v;base64,AAAAHGZ0eXBNNFYgAAACAGlzb21pc28yYXZjMQAAAAhmcmVlAAAqiW1kYXQAAAKMBgX//4jcRem9\n", |
|
720 | "<video controls alt=\"test\" src=\"data:video/x-m4v;base64,AAAAHGZ0eXBNNFYgAAACAGlzb21pc28yYXZjMQAAAAhmcmVlAAAqiW1kYXQAAAKMBgX//4jcRem9\n", | |
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|
721 | "5tlIt5Ys2CDZI+7veDI2NCAtIGNvcmUgMTE4IC0gSC4yNjQvTVBFRy00IEFWQyBjb2RlYyAtIENv\n", | |
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794 | "mvsiPvCBWUHFChacdY5whj5mP5rqQ0dqLJCsWjrs4TWnIbL2V/Iwfj3hwI35jfo1JkTOeR+8GhOd\n", | |
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812 | "DcCagAAAAodBmoRJ4Q8mUwIr/wArPWF/KOw78THwadfPqhJO0CnmR/M74/XYZLqVYKlNcEaYauf+\n", | |
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817 | "Ur0NCYNp7M4cVd/n73Rjetnixz4SAKpcz/P47UsijZG7T3SxzK2D79WS42aEalc12hQwCZ01LfmF\n", | |
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818 | "/H2mmGEvOzPBie1D0YT7Jh19vxa4Dd3SQ1FrDfmSUpvv4DjbYcZ2PrPpFpWtMjWqHBeoyMiZf6RP\n", | |
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820 | "RQuDMGGS7B2zuf/0GbJyRhUO48UbMrqnILMrbQg1LF00Q3pH9nbGEK/RRQpRN3T/J/4IZQjwW2Ft\n", | |
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821 | "2ipWGztg1Jn9I4DmffKS60QC+JQcyakdVON6zDcKttIKlqeTcmAi4xzmo4QXa2dRKleS+fs3EtTd\n", | |
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822 | "BBtony2wK9T2Imj+NCziOSEL7Q7VuIU8kclUHrJJsSneFcxGRgIgGGUEQM8/pklwTOqab7mMmJeR\n", | |
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840 | "DIdg/XVmgsC9CzVzUyq4VsS/sk97lJggcddpWLNw/29egz8iLyzWHOAXCvl2fTIPkviYAOQXfVhZ\n", | |
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878 | "R3I7mTrQDdlTAqYgqO7Gn5NMXQVHu2i1zhFSdo9GjMbeGnbkJwsFbQ2XkoKRIDpuW7AewC9AEBt0\n", | |
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879 | "Ox/Ah6dGXfXO1jl8pEApj2RFmgAAAPlBm61J4Q8mUwIr/wAlR+eW/VZ7bSrmwwMA62G05DZ7p/5F\n", | |
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880 | "UugsSsQdonUq6abtbU5hjFr+I1lPgoiV5c3CkTQZS+K5zivdo+Ti2P4K90xXANp8dSMAu85uJIOC\n", | |
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881 | "Qn2TXbEnNDifLB+3V84ht5tj4lvTaZx317BcliV8D5v2zZQW8RO1mUbuJEBItst8E7hfE+ZXj7tf\n", | |
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882 | "DxNZPTvtpFyUv0fH1cTg1pr2VLy0d0zQLiA58dg+GkRvR1/hs2LyifBgHcj6eTWz0vsypVn9iPXR\n", | |
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|
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| 929 | "\">" |
|
929 | "\">" | |
| 930 | ], |
|
930 | ], | |
| 931 | "output_type": "pyout", |
|
931 | "output_type": "pyout", | |
| 932 | "prompt_number": 8, |
|
932 | "prompt_number": 8, | |
| 933 | "text": [ |
|
933 | "text": [ | |
| 934 | "<IPython.core.display.HTML at 0x10fba28d0>" |
|
934 | "<IPython.core.display.HTML at 0x10fba28d0>" | |
| 935 | ] |
|
935 | ] | |
| 936 | } |
|
936 | } | |
| 937 | ], |
|
937 | ], | |
| 938 | "prompt_number": 8 |
|
938 | "prompt_number": 8 | |
| 939 | }, |
|
939 | }, | |
| 940 | { |
|
940 | { | |
| 941 | "cell_type": "markdown", |
|
941 | "cell_type": "markdown", | |
| 942 | "metadata": {}, |
|
942 | "metadata": {}, | |
| 943 | "source": [ |
|
943 | "source": [ | |
| 944 | "## Local Files\n", |
|
944 | "## Local Files\n", | |
| 945 | "\n", |
|
945 | "\n", | |
| 946 | "The above examples embed images and video from the notebook filesystem in the output\n", |
|
946 | "The above examples embed images and video from the notebook filesystem in the output\n", | |
| 947 | "areas of code cells. It is also possible to request these files directly in markdown cells\n", |
|
947 | "areas of code cells. It is also possible to request these files directly in markdown cells\n", | |
| 948 | "if they reside in the notebook directory via relative urls prefixed with `files/`:\n", |
|
948 | "if they reside in the notebook directory via relative urls prefixed with `files/`:\n", | |
| 949 | "\n", |
|
949 | "\n", | |
| 950 | " files/[subdirectory/]<filename>\n", |
|
950 | " files/[subdirectory/]<filename>\n", | |
| 951 | "\n", |
|
951 | "\n", | |
| 952 | "\n", |
|
952 | "\n", | |
| 953 | "For example, in the example notebook folder, we have the Python logo, addressed as:\n", |
|
953 | "For example, in the example notebook folder, we have the Python logo, addressed as:\n", | |
| 954 | "\n", |
|
954 | "\n", | |
| 955 | " <img src=\"files/python-logo.svg\" />\n", |
|
955 | " <img src=\"files/python-logo.svg\" />\n", | |
| 956 | "\n", |
|
956 | "\n", | |
| 957 | "<img src=\"/files/python-logo.svg\" />\n", |
|
957 | "<img src=\"/files/python-logo.svg\" />\n", | |
| 958 | "\n", |
|
958 | "\n", | |
| 959 | "and a video with the HTML5 video tag:\n", |
|
959 | "and a video with the HTML5 video tag:\n", | |
| 960 | "\n", |
|
960 | "\n", | |
| 961 | " <video controls src=\"files/animation.m4v\" />\n", |
|
961 | " <video controls src=\"files/animation.m4v\" />\n", | |
| 962 | "\n", |
|
962 | "\n", | |
| 963 | "<video controls src=\"/files/animation.m4v\" />\n", |
|
963 | "<video controls src=\"/files/animation.m4v\" />\n", | |
| 964 | "\n", |
|
964 | "\n", | |
| 965 | "These do not embed the data into the notebook file,\n", |
|
965 | "These do not embed the data into the notebook file,\n", | |
| 966 | "and require that the files exist when you are viewing the notebook.\n", |
|
966 | "and require that the files exist when you are viewing the notebook.\n", | |
| 967 | "\n", |
|
967 | "\n", | |
| 968 | "### Security of local files\n", |
|
968 | "### Security of local files\n", | |
| 969 | "\n", |
|
969 | "\n", | |
| 970 | "Note that this means that the IPython notebook server also acts as a generic file server\n", |
|
970 | "Note that this means that the IPython notebook server also acts as a generic file server\n", | |
| 971 | "for files inside the same tree as your notebooks. Access is not granted outside the\n", |
|
971 | "for files inside the same tree as your notebooks. Access is not granted outside the\n", | |
| 972 | "notebook folder so you have strict control over what files are visible, but for this\n", |
|
972 | "notebook folder so you have strict control over what files are visible, but for this\n", | |
| 973 | "reason it is highly recommended that you do not run the notebook server with a notebook\n", |
|
973 | "reason it is highly recommended that you do not run the notebook server with a notebook\n", | |
| 974 | "directory at a high level in your filesystem (e.g. your home directory).\n", |
|
974 | "directory at a high level in your filesystem (e.g. your home directory).\n", | |
| 975 | "\n", |
|
975 | "\n", | |
| 976 | "When you run the notebook in a password-protected manner, local file access is restricted\n", |
|
976 | "When you run the notebook in a password-protected manner, local file access is restricted\n", | |
| 977 | "to authenticated users unless read-only views are active." |
|
977 | "to authenticated users unless read-only views are active." | |
| 978 | ] |
|
978 | ] | |
| 979 | }, |
|
979 | }, | |
| 980 | { |
|
980 | { | |
| 981 | "cell_type": "markdown", |
|
981 | "cell_type": "markdown", | |
| 982 | "metadata": {}, |
|
982 | "metadata": {}, | |
| 983 | "source": [ |
|
983 | "source": [ | |
| 984 | "### External sites\n", |
|
984 | "### External sites\n", | |
| 985 | "\n", |
|
985 | "\n", | |
| 986 | "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n", |
|
986 | "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n", | |
| 987 | "page for mobile users:" |
|
987 | "page for mobile users:" | |
| 988 | ] |
|
988 | ] | |
| 989 | }, |
|
989 | }, | |
| 990 | { |
|
990 | { | |
| 991 | "cell_type": "code", |
|
991 | "cell_type": "code", | |
| 992 | "collapsed": false, |
|
992 | "collapsed": false, | |
| 993 | "input": [ |
|
993 | "input": [ | |
| 994 | "HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350>')" |
|
994 | "HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>')" | |
| 995 | ], |
|
995 | ], | |
| 996 | "language": "python", |
|
996 | "language": "python", | |
| 997 | "metadata": {}, |
|
997 | "metadata": {}, | |
| 998 | "outputs": [ |
|
998 | "outputs": [ | |
| 999 | { |
|
999 | { | |
| 1000 | "html": [ |
|
1000 | "html": [ | |
| 1001 | "<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350>" |
|
1001 | "<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>" | |
| 1002 | ], |
|
1002 | ], | |
| 1003 | "output_type": "pyout", |
|
1003 | "output_type": "pyout", | |
| 1004 | "prompt_number": 9, |
|
1004 | "prompt_number": 9, | |
| 1005 | "text": [ |
|
1005 | "text": [ | |
| 1006 |
"<IPython.core.display.HTML at 0x10 |
|
1006 | "<IPython.core.display.HTML at 0x1094900d0>" | |
| 1007 | ] |
|
1007 | ] | |
| 1008 | } |
|
1008 | } | |
| 1009 | ], |
|
1009 | ], | |
| 1010 | "prompt_number": 9 |
|
1010 | "prompt_number": 9 | |
| 1011 | }, |
|
1011 | }, | |
| 1012 | { |
|
1012 | { | |
| 1013 | "cell_type": "markdown", |
|
1013 | "cell_type": "markdown", | |
| 1014 | "metadata": {}, |
|
1014 | "metadata": {}, | |
| 1015 | "source": [ |
|
1015 | "source": [ | |
| 1016 | "### Mathematics\n", |
|
1016 | "### Mathematics\n", | |
| 1017 | "\n", |
|
1017 | "\n", | |
| 1018 | "And we also support the display of mathematical expressions typeset in LaTeX, which is rendered\n", |
|
1018 | "And we also support the display of mathematical expressions typeset in LaTeX, which is rendered\n", | |
| 1019 | "in the browser thanks to the [MathJax library](http://mathjax.org). \n", |
|
1019 | "in the browser thanks to the [MathJax library](http://mathjax.org). \n", | |
| 1020 | "\n", |
|
1020 | "\n", | |
| 1021 | "Note that this is *different* from the above examples. Above we were typing mathematical expressions\n", |
|
1021 | "Note that this is *different* from the above examples. Above we were typing mathematical expressions\n", | |
| 1022 | "in Markdown cells (along with normal text) and letting the browser render them; now we are displaying\n", |
|
1022 | "in Markdown cells (along with normal text) and letting the browser render them; now we are displaying\n", | |
| 1023 | "the output of a Python computation as a LaTeX expression wrapped by the `Math()` object so the browser\n", |
|
1023 | "the output of a Python computation as a LaTeX expression wrapped by the `Math()` object so the browser\n", | |
| 1024 | "renders it. The `Math` object will add the needed LaTeX delimiters (`$$`) if they are not provided:" |
|
1024 | "renders it. The `Math` object will add the needed LaTeX delimiters (`$$`) if they are not provided:" | |
| 1025 | ] |
|
1025 | ] | |
| 1026 | }, |
|
1026 | }, | |
| 1027 | { |
|
1027 | { | |
| 1028 | "cell_type": "code", |
|
1028 | "cell_type": "code", | |
| 1029 | "collapsed": false, |
|
1029 | "collapsed": false, | |
| 1030 | "input": [ |
|
1030 | "input": [ | |
| 1031 | "from IPython.display import Math\n", |
|
1031 | "from IPython.display import Math\n", | |
| 1032 | "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')" |
|
1032 | "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')" | |
| 1033 | ], |
|
1033 | ], | |
| 1034 | "language": "python", |
|
1034 | "language": "python", | |
| 1035 | "metadata": {}, |
|
1035 | "metadata": {}, | |
| 1036 | "outputs": [ |
|
1036 | "outputs": [ | |
| 1037 | { |
|
1037 | { | |
| 1038 | "latex": [ |
|
1038 | "latex": [ | |
| 1039 | "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$" |
|
1039 | "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$" | |
| 1040 | ], |
|
1040 | ], | |
| 1041 | "output_type": "pyout", |
|
1041 | "output_type": "pyout", | |
| 1042 | "prompt_number": 10, |
|
1042 | "prompt_number": 10, | |
| 1043 | "text": [ |
|
1043 | "text": [ | |
| 1044 | "<IPython.core.display.Math at 0x10fba26d0>" |
|
1044 | "<IPython.core.display.Math at 0x10fba26d0>" | |
| 1045 | ] |
|
1045 | ] | |
| 1046 | } |
|
1046 | } | |
| 1047 | ], |
|
1047 | ], | |
| 1048 | "prompt_number": 10 |
|
1048 | "prompt_number": 10 | |
| 1049 | }, |
|
1049 | }, | |
| 1050 | { |
|
1050 | { | |
| 1051 | "cell_type": "markdown", |
|
1051 | "cell_type": "markdown", | |
| 1052 | "metadata": {}, |
|
1052 | "metadata": {}, | |
| 1053 | "source": [ |
|
1053 | "source": [ | |
| 1054 | "With the `Latex` class, you have to include the delimiters yourself. This allows you to use other LaTeX modes such as `eqnarray`:" |
|
1054 | "With the `Latex` class, you have to include the delimiters yourself. This allows you to use other LaTeX modes such as `eqnarray`:" | |
| 1055 | ] |
|
1055 | ] | |
| 1056 | }, |
|
1056 | }, | |
| 1057 | { |
|
1057 | { | |
| 1058 | "cell_type": "code", |
|
1058 | "cell_type": "code", | |
| 1059 | "collapsed": false, |
|
1059 | "collapsed": false, | |
| 1060 | "input": [ |
|
1060 | "input": [ | |
| 1061 | "from IPython.display import Latex\n", |
|
1061 | "from IPython.display import Latex\n", | |
| 1062 | "Latex(r\"\"\"\\begin{eqnarray}\n", |
|
1062 | "Latex(r\"\"\"\\begin{eqnarray}\n", | |
| 1063 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", |
|
1063 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", | |
| 1064 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", |
|
1064 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", | |
| 1065 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", |
|
1065 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", | |
| 1066 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n", |
|
1066 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n", | |
| 1067 | "\\end{eqnarray}\"\"\")" |
|
1067 | "\\end{eqnarray}\"\"\")" | |
| 1068 | ], |
|
1068 | ], | |
| 1069 | "language": "python", |
|
1069 | "language": "python", | |
| 1070 | "metadata": {}, |
|
1070 | "metadata": {}, | |
| 1071 | "outputs": [ |
|
1071 | "outputs": [ | |
| 1072 | { |
|
1072 | { | |
| 1073 | "latex": [ |
|
1073 | "latex": [ | |
| 1074 | "\\begin{eqnarray}\n", |
|
1074 | "\\begin{eqnarray}\n", | |
| 1075 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", |
|
1075 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", | |
| 1076 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", |
|
1076 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", | |
| 1077 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", |
|
1077 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", | |
| 1078 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n", |
|
1078 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n", | |
| 1079 | "\\end{eqnarray}" |
|
1079 | "\\end{eqnarray}" | |
| 1080 | ], |
|
1080 | ], | |
| 1081 | "output_type": "pyout", |
|
1081 | "output_type": "pyout", | |
| 1082 | "prompt_number": 11, |
|
1082 | "prompt_number": 11, | |
| 1083 | "text": [ |
|
1083 | "text": [ | |
| 1084 | "<IPython.core.display.Latex at 0x10fba2c10>" |
|
1084 | "<IPython.core.display.Latex at 0x10fba2c10>" | |
| 1085 | ] |
|
1085 | ] | |
| 1086 | } |
|
1086 | } | |
| 1087 | ], |
|
1087 | ], | |
| 1088 | "prompt_number": 11 |
|
1088 | "prompt_number": 11 | |
| 1089 | }, |
|
1089 | }, | |
| 1090 | { |
|
1090 | { | |
| 1091 | "cell_type": "markdown", |
|
1091 | "cell_type": "markdown", | |
| 1092 | "metadata": {}, |
|
1092 | "metadata": {}, | |
| 1093 | "source": [ |
|
1093 | "source": [ | |
| 1094 | "Or you can enter latex directly with the `%%latex` cell magic:" |
|
1094 | "Or you can enter latex directly with the `%%latex` cell magic:" | |
| 1095 | ] |
|
1095 | ] | |
| 1096 | }, |
|
1096 | }, | |
| 1097 | { |
|
1097 | { | |
| 1098 | "cell_type": "code", |
|
1098 | "cell_type": "code", | |
| 1099 | "collapsed": false, |
|
1099 | "collapsed": false, | |
| 1100 | "input": [ |
|
1100 | "input": [ | |
| 1101 | "%%latex\n", |
|
1101 | "%%latex\n", | |
| 1102 | "\\begin{aligned}\n", |
|
1102 | "\\begin{aligned}\n", | |
| 1103 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", |
|
1103 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", | |
| 1104 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", |
|
1104 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", | |
| 1105 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", |
|
1105 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", | |
| 1106 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n", |
|
1106 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n", | |
| 1107 | "\\end{aligned}" |
|
1107 | "\\end{aligned}" | |
| 1108 | ], |
|
1108 | ], | |
| 1109 | "language": "python", |
|
1109 | "language": "python", | |
| 1110 | "metadata": {}, |
|
1110 | "metadata": {}, | |
| 1111 | "outputs": [ |
|
1111 | "outputs": [ | |
| 1112 | { |
|
1112 | { | |
| 1113 | "latex": [ |
|
1113 | "latex": [ | |
| 1114 | "\\begin{aligned}\n", |
|
1114 | "\\begin{aligned}\n", | |
| 1115 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", |
|
1115 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", | |
| 1116 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", |
|
1116 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", | |
| 1117 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", |
|
1117 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", | |
| 1118 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n", |
|
1118 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n", | |
| 1119 | "\\end{aligned}" |
|
1119 | "\\end{aligned}" | |
| 1120 | ], |
|
1120 | ], | |
| 1121 | "output_type": "display_data", |
|
1121 | "output_type": "display_data", | |
| 1122 | "text": [ |
|
1122 | "text": [ | |
| 1123 | "<IPython.core.display.Latex at 0x10a617c90>" |
|
1123 | "<IPython.core.display.Latex at 0x10a617c90>" | |
| 1124 | ] |
|
1124 | ] | |
| 1125 | } |
|
1125 | } | |
| 1126 | ], |
|
1126 | ], | |
| 1127 | "prompt_number": 12 |
|
1127 | "prompt_number": 12 | |
| 1128 | }, |
|
1128 | }, | |
| 1129 | { |
|
1129 | { | |
| 1130 | "cell_type": "markdown", |
|
1130 | "cell_type": "markdown", | |
| 1131 | "metadata": {}, |
|
1131 | "metadata": {}, | |
| 1132 | "source": [ |
|
1132 | "source": [ | |
| 1133 | "There is also a `%%javascript` cell magic for running javascript directly,\n", |
|
1133 | "There is also a `%%javascript` cell magic for running javascript directly,\n", | |
| 1134 | "and `%%svg` for manually entering SVG content." |
|
1134 | "and `%%svg` for manually entering SVG content." | |
| 1135 | ] |
|
1135 | ] | |
| 1136 | }, |
|
1136 | }, | |
| 1137 | { |
|
1137 | { | |
| 1138 | "cell_type": "markdown", |
|
1138 | "cell_type": "markdown", | |
| 1139 | "metadata": {}, |
|
1139 | "metadata": {}, | |
| 1140 | "source": [ |
|
1140 | "source": [ | |
| 1141 | "# Loading external codes\n", |
|
1141 | "# Loading external codes\n", | |
| 1142 | "* Drag and drop a ``.py`` in the dashboard\n", |
|
1142 | "* Drag and drop a ``.py`` in the dashboard\n", | |
| 1143 | "* Use ``%load`` with any local or remote url: [the Matplotlib Gallery!](http://matplotlib.sourceforge.net/gallery.html)\n", |
|
1143 | "* Use ``%load`` with any local or remote url: [the Matplotlib Gallery!](http://matplotlib.sourceforge.net/gallery.html)\n", | |
| 1144 | "\n", |
|
1144 | "\n", | |
| 1145 | "In this notebook we've kept the output saved so you can see the result, but you should run the next\n", |
|
1145 | "In this notebook we've kept the output saved so you can see the result, but you should run the next\n", | |
| 1146 | "cell yourself (with an active internet connection)." |
|
1146 | "cell yourself (with an active internet connection)." | |
| 1147 | ] |
|
1147 | ] | |
| 1148 | }, |
|
1148 | }, | |
| 1149 | { |
|
1149 | { | |
| 1150 | "cell_type": "markdown", |
|
1150 | "cell_type": "markdown", | |
| 1151 | "metadata": {}, |
|
1151 | "metadata": {}, | |
| 1152 | "source": [ |
|
1152 | "source": [ | |
| 1153 | "Let's make sure we have pylab again, in case we have restarted the kernel due to the crash demo above" |
|
1153 | "Let's make sure we have pylab again, in case we have restarted the kernel due to the crash demo above" | |
| 1154 | ] |
|
1154 | ] | |
| 1155 | }, |
|
1155 | }, | |
| 1156 | { |
|
1156 | { | |
| 1157 | "cell_type": "code", |
|
1157 | "cell_type": "code", | |
| 1158 | "collapsed": false, |
|
1158 | "collapsed": false, | |
| 1159 | "input": [ |
|
1159 | "input": [ | |
| 1160 | "%pylab inline" |
|
1160 | "%pylab inline" | |
| 1161 | ], |
|
1161 | ], | |
| 1162 | "language": "python", |
|
1162 | "language": "python", | |
| 1163 | "metadata": {}, |
|
1163 | "metadata": {}, | |
| 1164 | "outputs": [ |
|
1164 | "outputs": [ | |
| 1165 | { |
|
1165 | { | |
| 1166 | "output_type": "stream", |
|
1166 | "output_type": "stream", | |
| 1167 | "stream": "stdout", |
|
1167 | "stream": "stdout", | |
| 1168 | "text": [ |
|
1168 | "text": [ | |
| 1169 | "\n", |
|
1169 | "\n", | |
| 1170 | "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n", |
|
1170 | "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n", | |
| 1171 | "For more information, type 'help(pylab)'.\n" |
|
1171 | "For more information, type 'help(pylab)'.\n" | |
| 1172 | ] |
|
1172 | ] | |
| 1173 | } |
|
1173 | } | |
| 1174 | ], |
|
1174 | ], | |
| 1175 | "prompt_number": 12 |
|
1175 | "prompt_number": 12 | |
| 1176 | }, |
|
1176 | }, | |
| 1177 | { |
|
1177 | { | |
| 1178 | "cell_type": "code", |
|
1178 | "cell_type": "code", | |
| 1179 | "collapsed": false, |
|
1179 | "collapsed": false, | |
| 1180 | "input": [ |
|
1180 | "input": [ | |
| 1181 | "%load http://matplotlib.sourceforge.net/mpl_examples/pylab_examples/integral_demo.py" |
|
1181 | "%load http://matplotlib.sourceforge.net/mpl_examples/pylab_examples/integral_demo.py" | |
| 1182 | ], |
|
1182 | ], | |
| 1183 | "language": "python", |
|
1183 | "language": "python", | |
| 1184 | "metadata": {}, |
|
1184 | "metadata": {}, | |
| 1185 | "outputs": [], |
|
1185 | "outputs": [], | |
| 1186 | "prompt_number": 15 |
|
1186 | "prompt_number": 15 | |
| 1187 | }, |
|
1187 | }, | |
| 1188 | { |
|
1188 | { | |
| 1189 | "cell_type": "code", |
|
1189 | "cell_type": "code", | |
| 1190 | "collapsed": false, |
|
1190 | "collapsed": false, | |
| 1191 | "input": [ |
|
1191 | "input": [ | |
| 1192 | "#!/usr/bin/env python\n", |
|
1192 | "#!/usr/bin/env python\n", | |
| 1193 | "\n", |
|
1193 | "\n", | |
| 1194 | "# implement the example graphs/integral from pyx\n", |
|
1194 | "# implement the example graphs/integral from pyx\n", | |
| 1195 | "from pylab import *\n", |
|
1195 | "from pylab import *\n", | |
| 1196 | "from matplotlib.patches import Polygon\n", |
|
1196 | "from matplotlib.patches import Polygon\n", | |
| 1197 | "\n", |
|
1197 | "\n", | |
| 1198 | "def func(x):\n", |
|
1198 | "def func(x):\n", | |
| 1199 | " return (x-3)*(x-5)*(x-7)+85\n", |
|
1199 | " return (x-3)*(x-5)*(x-7)+85\n", | |
| 1200 | "\n", |
|
1200 | "\n", | |
| 1201 | "ax = subplot(111)\n", |
|
1201 | "ax = subplot(111)\n", | |
| 1202 | "\n", |
|
1202 | "\n", | |
| 1203 | "a, b = 2, 9 # integral area\n", |
|
1203 | "a, b = 2, 9 # integral area\n", | |
| 1204 | "x = arange(0, 10, 0.01)\n", |
|
1204 | "x = arange(0, 10, 0.01)\n", | |
| 1205 | "y = func(x)\n", |
|
1205 | "y = func(x)\n", | |
| 1206 | "plot(x, y, linewidth=1)\n", |
|
1206 | "plot(x, y, linewidth=1)\n", | |
| 1207 | "\n", |
|
1207 | "\n", | |
| 1208 | "# make the shaded region\n", |
|
1208 | "# make the shaded region\n", | |
| 1209 | "ix = arange(a, b, 0.01)\n", |
|
1209 | "ix = arange(a, b, 0.01)\n", | |
| 1210 | "iy = func(ix)\n", |
|
1210 | "iy = func(ix)\n", | |
| 1211 | "verts = [(a,0)] + zip(ix,iy) + [(b,0)]\n", |
|
1211 | "verts = [(a,0)] + zip(ix,iy) + [(b,0)]\n", | |
| 1212 | "poly = Polygon(verts, facecolor='0.8', edgecolor='k')\n", |
|
1212 | "poly = Polygon(verts, facecolor='0.8', edgecolor='k')\n", | |
| 1213 | "ax.add_patch(poly)\n", |
|
1213 | "ax.add_patch(poly)\n", | |
| 1214 | "\n", |
|
1214 | "\n", | |
| 1215 | "text(0.5 * (a + b), 30,\n", |
|
1215 | "text(0.5 * (a + b), 30,\n", | |
| 1216 | " r\"$\\int_a^b f(x)\\mathrm{d}x$\", horizontalalignment='center',\n", |
|
1216 | " r\"$\\int_a^b f(x)\\mathrm{d}x$\", horizontalalignment='center',\n", | |
| 1217 | " fontsize=20)\n", |
|
1217 | " fontsize=20)\n", | |
| 1218 | "\n", |
|
1218 | "\n", | |
| 1219 | "axis([0,10, 0, 180])\n", |
|
1219 | "axis([0,10, 0, 180])\n", | |
| 1220 | "figtext(0.9, 0.05, 'x')\n", |
|
1220 | "figtext(0.9, 0.05, 'x')\n", | |
| 1221 | "figtext(0.1, 0.9, 'y')\n", |
|
1221 | "figtext(0.1, 0.9, 'y')\n", | |
| 1222 | "ax.set_xticks((a,b))\n", |
|
1222 | "ax.set_xticks((a,b))\n", | |
| 1223 | "ax.set_xticklabels(('a','b'))\n", |
|
1223 | "ax.set_xticklabels(('a','b'))\n", | |
| 1224 | "ax.set_yticks([])\n", |
|
1224 | "ax.set_yticks([])\n", | |
| 1225 | "show()\n" |
|
1225 | "show()\n" | |
| 1226 | ], |
|
1226 | ], | |
| 1227 | "language": "python", |
|
1227 | "language": "python", | |
| 1228 | "metadata": {}, |
|
1228 | "metadata": {}, | |
| 1229 | "outputs": [ |
|
1229 | "outputs": [ | |
| 1230 | { |
|
1230 | { | |
| 1231 | "output_type": "display_data", |
|
1231 | "output_type": "display_data", | |
| 1232 | "png": 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k5OQQHBx81glcnqBfv37069ev0e9/5JFHnFiNNJWOdqyHlSth3TrHVjHxTvv2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\n" 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1232 | "png": 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| |
| 1233 | } |
|
1233 | } | |
| 1234 | ], |
|
1234 | ], | |
| 1235 | "prompt_number": 16 |
|
1235 | "prompt_number": 16 | |
| 1236 | } |
|
1236 | } | |
| 1237 | ], |
|
1237 | ], | |
| 1238 | "metadata": {} |
|
1238 | "metadata": {} | |
| 1239 | } |
|
1239 | } | |
| 1240 | ] |
|
1240 | ] | |
| 1241 | } No newline at end of file |
|
1241 | } | |
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