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Updating output notebook.
Brian E. Granger -
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1 {
1 {
2 "metadata": {
2 "metadata": {
3 "name": "",
3 "name": "",
4 "signature": "sha256:b4d7c6b90e8b3e2ab460015611518e5d598dea6903db56a26dc8a81e5d1f5722"
4 "signature": "sha256:cf83dc9e6288480ac94c44a5983b4ee421f0ade792a9fac64bc00719263386c0"
5 },
5 },
6 "nbformat": 3,
6 "nbformat": 3,
7 "nbformat_minor": 0,
7 "nbformat_minor": 0,
8 "worksheets": [
8 "worksheets": [
9 {
9 {
10 "cells": [
10 "cells": [
11 {
11 {
12 "cell_type": "heading",
12 "cell_type": "heading",
13 "level": 1,
13 "level": 1,
14 "metadata": {},
14 "metadata": {},
15 "source": [
15 "source": [
16 "Rich Output"
16 "Rich Output"
17 ]
17 ]
18 },
18 },
19 {
19 {
20 "cell_type": "markdown",
20 "cell_type": "markdown",
21 "metadata": {},
21 "metadata": {},
22 "source": [
22 "source": [
23 "In Python, objects can declare their textual representation using the `__repr__` method. IPython expands on this idea and allows objects to declare other, rich representations including:\n",
23 "In Python, objects can declare their textual representation using the `__repr__` method. IPython expands on this idea and allows objects to declare other, rich representations including:\n",
24 "\n",
24 "\n",
25 "* HTML\n",
25 "* HTML\n",
26 "* JSON\n",
26 "* JSON\n",
27 "* PNG\n",
27 "* PNG\n",
28 "* JPEG\n",
28 "* JPEG\n",
29 "* SVG\n",
29 "* SVG\n",
30 "* LaTeX\n",
30 "* LaTeX\n",
31 "\n",
31 "\n",
32 "A single object can declare some or all of these representations; all are handled by IPython's *display system*. This Notebook shows how you can use this display system to incorporate a broad range of content into your Notebooks."
32 "A single object can declare some or all of these representations; all are handled by IPython's *display system*. This Notebook shows how you can use this display system to incorporate a broad range of content into your Notebooks."
33 ]
33 ]
34 },
34 },
35 {
35 {
36 "cell_type": "heading",
36 "cell_type": "heading",
37 "level": 2,
37 "level": 2,
38 "metadata": {},
38 "metadata": {},
39 "source": [
39 "source": [
40 "Basic display imports"
40 "Basic display imports"
41 ]
41 ]
42 },
42 },
43 {
43 {
44 "cell_type": "markdown",
44 "cell_type": "markdown",
45 "metadata": {},
45 "metadata": {},
46 "source": [
46 "source": [
47 "The `display` function is a general purpose tool for displaying different representations of objects. Think of it as `print` for these rich representations."
47 "The `display` function is a general purpose tool for displaying different representations of objects. Think of it as `print` for these rich representations."
48 ]
48 ]
49 },
49 },
50 {
50 {
51 "cell_type": "code",
51 "cell_type": "code",
52 "collapsed": false,
52 "collapsed": false,
53 "input": [
53 "input": [
54 "from IPython.display import display"
54 "from IPython.display import display"
55 ],
55 ],
56 "language": "python",
56 "language": "python",
57 "metadata": {},
57 "metadata": {},
58 "outputs": [],
58 "outputs": [],
59 "prompt_number": 3
59 "prompt_number": 1
60 },
60 },
61 {
61 {
62 "cell_type": "markdown",
62 "cell_type": "markdown",
63 "metadata": {},
63 "metadata": {},
64 "source": [
64 "source": [
65 "A few points:\n",
65 "A few points:\n",
66 "\n",
66 "\n",
67 "* Calling `display` on an object will send **all** possible representations to the Notebook.\n",
67 "* Calling `display` on an object will send **all** possible representations to the Notebook.\n",
68 "* These representations are stored in the Notebook document.\n",
68 "* These representations are stored in the Notebook document.\n",
69 "* In general the Notebook will use the richest available representation.\n",
69 "* In general the Notebook will use the richest available representation.\n",
70 "\n",
70 "\n",
71 "If you want to display a particular representation, there are specific functions for that:"
71 "If you want to display a particular representation, there are specific functions for that:"
72 ]
72 ]
73 },
73 },
74 {
74 {
75 "cell_type": "code",
75 "cell_type": "code",
76 "collapsed": false,
76 "collapsed": false,
77 "input": [
77 "input": [
78 "from IPython.display import (\n",
78 "from IPython.display import (\n",
79 " display_pretty, display_html, display_jpeg,\n",
79 " display_pretty, display_html, display_jpeg,\n",
80 " display_png, display_json, display_latex, display_svg\n",
80 " display_png, display_json, display_latex, display_svg\n",
81 ")"
81 ")"
82 ],
82 ],
83 "language": "python",
83 "language": "python",
84 "metadata": {},
84 "metadata": {},
85 "outputs": [],
85 "outputs": [],
86 "prompt_number": 4
86 "prompt_number": 2
87 },
87 },
88 {
88 {
89 "cell_type": "heading",
89 "cell_type": "heading",
90 "level": 2,
90 "level": 2,
91 "metadata": {},
91 "metadata": {},
92 "source": [
92 "source": [
93 "Images"
93 "Images"
94 ]
94 ]
95 },
95 },
96 {
96 {
97 "cell_type": "markdown",
97 "cell_type": "markdown",
98 "metadata": {},
98 "metadata": {},
99 "source": [
99 "source": [
100 "To work with images (JPEG, PNG) use the `Image` class."
100 "To work with images (JPEG, PNG) use the `Image` class."
101 ]
101 ]
102 },
102 },
103 {
103 {
104 "cell_type": "code",
104 "cell_type": "code",
105 "collapsed": false,
105 "collapsed": false,
106 "input": [
106 "input": [
107 "from IPython.display import Image"
107 "from IPython.display import Image"
108 ],
108 ],
109 "language": "python",
109 "language": "python",
110 "metadata": {},
110 "metadata": {},
111 "outputs": [],
111 "outputs": [],
112 "prompt_number": 5
112 "prompt_number": 3
113 },
113 },
114 {
114 {
115 "cell_type": "code",
115 "cell_type": "code",
116 "collapsed": false,
116 "collapsed": false,
117 "input": [
117 "input": [
118 "i = Image(filename='../images/ipython_logo.png')"
118 "i = Image(filename='../images/ipython_logo.png')"
119 ],
119 ],
120 "language": "python",
120 "language": "python",
121 "metadata": {},
121 "metadata": {},
122 "outputs": [],
122 "outputs": [],
123 "prompt_number": 6
123 "prompt_number": 4
124 },
124 },
125 {
125 {
126 "cell_type": "markdown",
126 "cell_type": "markdown",
127 "metadata": {},
127 "metadata": {},
128 "source": [
128 "source": [
129 "Returning an `Image` object from an expression will automatically display it:"
129 "Returning an `Image` object from an expression will automatically display it:"
130 ]
130 ]
131 },
131 },
132 {
132 {
133 "cell_type": "code",
133 "cell_type": "code",
134 "collapsed": false,
134 "collapsed": false,
135 "input": [
135 "input": [
136 "i"
136 "i"
137 ],
137 ],
138 "language": "python",
138 "language": "python",
139 "metadata": {},
139 "metadata": {},
140 "outputs": [
140 "outputs": [
141 {
141 {
142 "metadata": {},
142 "metadata": {},
143 "output_type": "pyout",
143 "output_type": "pyout",
144 "png": 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144 "png": 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145 "prompt_number": 7,
145 "prompt_number": 5,
146 "text": [
146 "text": [
147 "<IPython.core.display.Image object>"
147 "<IPython.core.display.Image object>"
148 ]
148 ]
149 }
149 }
150 ],
150 ],
151 "prompt_number": 7
151 "prompt_number": 5
152 },
152 },
153 {
153 {
154 "cell_type": "markdown",
154 "cell_type": "markdown",
155 "metadata": {},
155 "metadata": {},
156 "source": [
156 "source": [
157 "Or you can pass an object with a rich representation to `display`:"
157 "Or you can pass an object with a rich representation to `display`:"
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 "display(i)"
164 "display(i)"
165 ],
165 ],
166 "language": "python",
166 "language": "python",
167 "metadata": {},
167 "metadata": {},
168 "outputs": [
168 "outputs": [
169 {
169 {
170 "metadata": {},
170 "metadata": {},
171 "output_type": "display_data",
171 "output_type": "display_data",
172 "png": 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172 "png": 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173 "text": [
173 "text": [
174 "<IPython.core.display.Image object>"
174 "<IPython.core.display.Image object>"
175 ]
175 ]
176 }
176 }
177 ],
177 ],
178 "prompt_number": 8
178 "prompt_number": 6
179 },
179 },
180 {
180 {
181 "cell_type": "markdown",
181 "cell_type": "markdown",
182 "metadata": {},
182 "metadata": {},
183 "source": [
183 "source": [
184 "An image can also be displayed from raw data or a URL."
184 "An image can also be displayed from raw data or a URL."
185 ]
185 ]
186 },
186 },
187 {
187 {
188 "cell_type": "code",
188 "cell_type": "code",
189 "collapsed": false,
189 "collapsed": false,
190 "input": [
190 "input": [
191 "Image(url='http://python.org/images/python-logo.gif')"
191 "Image(url='http://python.org/images/python-logo.gif')"
192 ],
192 ],
193 "language": "python",
193 "language": "python",
194 "metadata": {},
194 "metadata": {},
195 "outputs": [
195 "outputs": [
196 {
196 {
197 "html": [
197 "html": [
198 "<img src=\"http://python.org/images/python-logo.gif\"/>"
198 "<img src=\"http://python.org/images/python-logo.gif\"/>"
199 ],
199 ],
200 "metadata": {},
200 "metadata": {},
201 "output_type": "pyout",
201 "output_type": "pyout",
202 "prompt_number": 9,
202 "prompt_number": 7,
203 "text": [
203 "text": [
204 "<IPython.core.display.Image object>"
204 "<IPython.core.display.Image object>"
205 ]
205 ]
206 }
206 }
207 ],
207 ],
208 "prompt_number": 9
208 "prompt_number": 7
209 },
209 },
210 {
210 {
211 "cell_type": "markdown",
211 "cell_type": "markdown",
212 "metadata": {},
212 "metadata": {},
213 "source": [
213 "source": [
214 "SVG images are also supported out of the box."
214 "SVG images are also supported out of the box."
215 ]
215 ]
216 },
216 },
217 {
217 {
218 "cell_type": "code",
218 "cell_type": "code",
219 "collapsed": false,
219 "collapsed": false,
220 "input": [
220 "input": [
221 "from IPython.display import SVG\n",
221 "from IPython.display import SVG\n",
222 "SVG(filename='../images/python_logo.svg')"
222 "SVG(filename='../images/python_logo.svg')"
223 ],
223 ],
224 "language": "python",
224 "language": "python",
225 "metadata": {},
225 "metadata": {},
226 "outputs": [
226 "outputs": [
227 {
227 {
228 "metadata": {},
228 "metadata": {},
229 "output_type": "pyout",
229 "output_type": "pyout",
230 "prompt_number": 10,
230 "prompt_number": 8,
231 "svg": [
231 "svg": [
232 "<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",
232 "<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",
233 " <metadata id=\"metadata2193\">\n",
233 " <metadata id=\"metadata2193\">\n",
234 " <rdf:RDF>\n",
234 " <rdf:RDF>\n",
235 " <cc:Work rdf:about=\"\">\n",
235 " <cc:Work rdf:about=\"\">\n",
236 " <dc:format>image/svg+xml</dc:format>\n",
236 " <dc:format>image/svg+xml</dc:format>\n",
237 " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
237 " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
238 " </cc:Work>\n",
238 " </cc:Work>\n",
239 " </rdf:RDF>\n",
239 " </rdf:RDF>\n",
240 " </metadata>\n",
240 " </metadata>\n",
241 " <sodipodi:namedview bordercolor=\"#666666\" borderopacity=\"1.0\" id=\"base\" inkscape:current-layer=\"svg2\" inkscape:cx=\"243.02499\" inkscape:cy=\"71.887497\" inkscape:pageopacity=\"0.0\" inkscape:pageshadow=\"2\" inkscape:window-height=\"543\" inkscape:window-width=\"791\" inkscape:window-x=\"0\" inkscape:window-y=\"0\" inkscape:zoom=\"1.4340089\" pagecolor=\"#ffffff\"/>\n",
241 " <sodipodi:namedview bordercolor=\"#666666\" borderopacity=\"1.0\" id=\"base\" inkscape:current-layer=\"svg2\" inkscape:cx=\"243.02499\" inkscape:cy=\"71.887497\" inkscape:pageopacity=\"0.0\" inkscape:pageshadow=\"2\" inkscape:window-height=\"543\" inkscape:window-width=\"791\" inkscape:window-x=\"0\" inkscape:window-y=\"0\" inkscape:zoom=\"1.4340089\" pagecolor=\"#ffffff\"/>\n",
242 " <defs id=\"defs4\">\n",
242 " <defs id=\"defs4\">\n",
243 " <linearGradient id=\"linearGradient2795\">\n",
243 " <linearGradient id=\"linearGradient2795\">\n",
244 " <stop id=\"stop2797\" offset=\"0\" style=\"stop-color:#b8b8b8;stop-opacity:0.49803922\"/>\n",
244 " <stop id=\"stop2797\" offset=\"0\" style=\"stop-color:#b8b8b8;stop-opacity:0.49803922\"/>\n",
245 " <stop id=\"stop2799\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
245 " <stop id=\"stop2799\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
246 " </linearGradient>\n",
246 " </linearGradient>\n",
247 " <linearGradient id=\"linearGradient2787\">\n",
247 " <linearGradient id=\"linearGradient2787\">\n",
248 " <stop id=\"stop2789\" offset=\"0\" style=\"stop-color:#7f7f7f;stop-opacity:0.5\"/>\n",
248 " <stop id=\"stop2789\" offset=\"0\" style=\"stop-color:#7f7f7f;stop-opacity:0.5\"/>\n",
249 " <stop id=\"stop2791\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
249 " <stop id=\"stop2791\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
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291 " </g>\n",
291 " </g>\n",
292 "</svg>"
292 "</svg>"
293 ],
293 ],
294 "text": [
294 "text": [
295 "<IPython.core.display.SVG object>"
295 "<IPython.core.display.SVG object>"
296 ]
296 ]
297 }
297 }
298 ],
298 ],
299 "prompt_number": 10
299 "prompt_number": 8
300 },
300 },
301 {
301 {
302 "cell_type": "heading",
302 "cell_type": "heading",
303 "level": 3,
303 "level": 3,
304 "metadata": {},
304 "metadata": {},
305 "source": [
305 "source": [
306 "Embedded vs non-embedded Images"
306 "Embedded vs non-embedded Images"
307 ]
307 ]
308 },
308 },
309 {
309 {
310 "cell_type": "markdown",
310 "cell_type": "markdown",
311 "metadata": {},
311 "metadata": {},
312 "source": [
312 "source": [
313 "By default, image data is embedded in the notebook document so that the images can be viewed offline. However it is also possible to tell the `Image` class to only store a *link* to the image. Let's see how this works using a webcam at Berkeley."
313 "By default, image data is embedded in the notebook document so that the images can be viewed offline. However it is also possible to tell the `Image` class to only store a *link* to the image. Let's see how this works using a webcam at Berkeley."
314 ]
314 ]
315 },
315 },
316 {
316 {
317 "cell_type": "code",
317 "cell_type": "code",
318 "collapsed": false,
318 "collapsed": false,
319 "input": [
319 "input": [
320 "from IPython.display import Image\n",
320 "from IPython.display import Image\n",
321 "img_url = 'http://www.lawrencehallofscience.org/static/scienceview/scienceview.berkeley.edu/html/view/view_assets/images/newview.jpg'\n",
321 "img_url = 'http://www.lawrencehallofscience.org/static/scienceview/scienceview.berkeley.edu/html/view/view_assets/images/newview.jpg'\n",
322 "\n",
322 "\n",
323 "# by default Image data are embedded\n",
323 "# by default Image data are embedded\n",
324 "Embed = Image(img_url)\n",
324 "Embed = Image(img_url)\n",
325 "\n",
325 "\n",
326 "# if kwarg `url` is given, the embedding is assumed to be false\n",
326 "# if kwarg `url` is given, the embedding is assumed to be false\n",
327 "SoftLinked = Image(url=img_url)\n",
327 "SoftLinked = Image(url=img_url)\n",
328 "\n",
328 "\n",
329 "# In each case, embed can be specified explicitly with the `embed` kwarg\n",
329 "# In each case, embed can be specified explicitly with the `embed` kwarg\n",
330 "# ForceEmbed = Image(url=img_url, embed=True)"
330 "# ForceEmbed = Image(url=img_url, embed=True)"
331 ],
331 ],
332 "language": "python",
332 "language": "python",
333 "metadata": {},
333 "metadata": {},
334 "outputs": [],
334 "outputs": [],
335 "prompt_number": 12
335 "prompt_number": 9
336 },
336 },
337 {
337 {
338 "cell_type": "markdown",
338 "cell_type": "markdown",
339 "metadata": {},
339 "metadata": {},
340 "source": [
340 "source": [
341 "Here is the embedded version. Note that this image was pulled from the webcam when this code cell was originally run and stored in the Notebook. Unless we rerun this cell, this is not todays image."
341 "Here is the embedded version. Note that this image was pulled from the webcam when this code cell was originally run and stored in the Notebook. Unless we rerun this cell, this is not todays image."
342 ]
342 ]
343 },
343 },
344 {
344 {
345 "cell_type": "code",
345 "cell_type": "code",
346 "collapsed": false,
346 "collapsed": false,
347 "input": [
347 "input": [
348 "Embed"
348 "Embed"
349 ],
349 ],
350 "language": "python",
350 "language": "python",
351 "metadata": {},
351 "metadata": {},
352 "outputs": [
352 "outputs": [
353 {
353 {
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ahzq+lu8VqInS3fVsHvFEGG7xU4bvFVE4bvFHpd4oqfS7xU4bv+ND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\nmaSILglwdL78MSzfexXT2b9MUW2dm7Ztp+gUQsby5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oCITmOR80BIMmZwnIJoKQST/pE1KAgZnAMUepRB9u9ReQBYEAfpHt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\nTLiN8bFraIISojbIUkmcGsTa0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ndIjsDJmBn6f19y1tb/AE5lNwBqDHkuhp9aEFseqFhJ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\n",
355 "metadata": {},
355 "metadata": {},
356 "output_type": "pyout",
356 "output_type": "pyout",
357 "prompt_number": 13,
357 "prompt_number": 10,
358 "text": [
358 "text": [
359 "<IPython.core.display.Image at 0x1068d0a10>"
359 "<IPython.core.display.Image object>"
360 ]
360 ]
361 }
361 }
362 ],
362 ],
363 "prompt_number": 13
363 "prompt_number": 10
364 },
364 },
365 {
365 {
366 "cell_type": "markdown",
366 "cell_type": "markdown",
367 "metadata": {},
367 "metadata": {},
368 "source": [
368 "source": [
369 "Here is today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connection, that should be different from the previous one. Notebooks saved with this kind of image will be smaller and always reflect the current version of the source, but the image won't display offline."
369 "Here is today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connection, that should be different from the previous one. Notebooks saved with this kind of image will be smaller and always reflect the current version of the source, but the image won't display offline."
370 ]
370 ]
371 },
371 },
372 {
372 {
373 "cell_type": "code",
373 "cell_type": "code",
374 "collapsed": false,
374 "collapsed": false,
375 "input": [
375 "input": [
376 "SoftLinked"
376 "SoftLinked"
377 ],
377 ],
378 "language": "python",
378 "language": "python",
379 "metadata": {},
379 "metadata": {},
380 "outputs": [
380 "outputs": [
381 {
381 {
382 "html": [
382 "html": [
383 "<img src=\"http://www.lawrencehallofscience.org/static/scienceview/scienceview.berkeley.edu/html/view/view_assets/images/newview.jpg\"/>"
383 "<img src=\"http://www.lawrencehallofscience.org/static/scienceview/scienceview.berkeley.edu/html/view/view_assets/images/newview.jpg\"/>"
384 ],
384 ],
385 "metadata": {},
385 "metadata": {},
386 "output_type": "pyout",
386 "output_type": "pyout",
387 "prompt_number": 14,
387 "prompt_number": 11,
388 "text": [
388 "text": [
389 "<IPython.core.display.Image at 0x106ab19d0>"
389 "<IPython.core.display.Image object>"
390 ]
390 ]
391 }
391 }
392 ],
392 ],
393 "prompt_number": 14
393 "prompt_number": 11
394 },
394 },
395 {
395 {
396 "cell_type": "markdown",
396 "cell_type": "markdown",
397 "metadata": {},
397 "metadata": {},
398 "source": [
398 "source": [
399 "Of course, if you re-run this Notebook, the two images will be the same again."
399 "Of course, if you re-run this Notebook, the two images will be the same again."
400 ]
400 ]
401 },
401 },
402 {
402 {
403 "cell_type": "heading",
403 "cell_type": "heading",
404 "level": 2,
404 "level": 2,
405 "metadata": {},
405 "metadata": {},
406 "source": [
406 "source": [
407 "HTML"
407 "HTML"
408 ]
408 ]
409 },
409 },
410 {
410 {
411 "cell_type": "markdown",
411 "cell_type": "markdown",
412 "metadata": {},
412 "metadata": {},
413 "source": [
413 "source": [
414 "Python objects can declare HTML representations that will be displayed in the Notebook. If you have some HTML you want to display, simply use the `HTML` class."
414 "Python objects can declare HTML representations that will be displayed in the Notebook. If you have some HTML you want to display, simply use the `HTML` class."
415 ]
415 ]
416 },
416 },
417 {
417 {
418 "cell_type": "code",
418 "cell_type": "code",
419 "collapsed": false,
419 "collapsed": false,
420 "input": [
420 "input": [
421 "from IPython.display import HTML"
421 "from IPython.display import HTML"
422 ],
422 ],
423 "language": "python",
423 "language": "python",
424 "metadata": {},
424 "metadata": {},
425 "outputs": [],
425 "outputs": [],
426 "prompt_number": 11
426 "prompt_number": 12
427 },
427 },
428 {
428 {
429 "cell_type": "code",
429 "cell_type": "code",
430 "collapsed": false,
430 "collapsed": false,
431 "input": [
431 "input": [
432 "s = \"\"\"<table>\n",
432 "s = \"\"\"<table>\n",
433 "<tr>\n",
433 "<tr>\n",
434 "<th>Header 1</th>\n",
434 "<th>Header 1</th>\n",
435 "<th>Header 2</th>\n",
435 "<th>Header 2</th>\n",
436 "</tr>\n",
436 "</tr>\n",
437 "<tr>\n",
437 "<tr>\n",
438 "<td>row 1, cell 1</td>\n",
438 "<td>row 1, cell 1</td>\n",
439 "<td>row 1, cell 2</td>\n",
439 "<td>row 1, cell 2</td>\n",
440 "</tr>\n",
440 "</tr>\n",
441 "<tr>\n",
441 "<tr>\n",
442 "<td>row 2, cell 1</td>\n",
442 "<td>row 2, cell 1</td>\n",
443 "<td>row 2, cell 2</td>\n",
443 "<td>row 2, cell 2</td>\n",
444 "</tr>\n",
444 "</tr>\n",
445 "</table>\"\"\""
445 "</table>\"\"\""
446 ],
446 ],
447 "language": "python",
447 "language": "python",
448 "metadata": {},
448 "metadata": {},
449 "outputs": [],
449 "outputs": [],
450 "prompt_number": 12
450 "prompt_number": 13
451 },
451 },
452 {
452 {
453 "cell_type": "code",
453 "cell_type": "code",
454 "collapsed": false,
454 "collapsed": false,
455 "input": [
455 "input": [
456 "h = HTML(s)"
456 "h = HTML(s)"
457 ],
457 ],
458 "language": "python",
458 "language": "python",
459 "metadata": {},
459 "metadata": {},
460 "outputs": [],
460 "outputs": [],
461 "prompt_number": 13
461 "prompt_number": 14
462 },
462 },
463 {
463 {
464 "cell_type": "code",
464 "cell_type": "code",
465 "collapsed": false,
465 "collapsed": false,
466 "input": [
466 "input": [
467 "display(h)"
467 "display(h)"
468 ],
468 ],
469 "language": "python",
469 "language": "python",
470 "metadata": {},
470 "metadata": {},
471 "outputs": [
471 "outputs": [
472 {
472 {
473 "html": [
473 "html": [
474 "<table>\n",
474 "<table>\n",
475 "<tr>\n",
475 "<tr>\n",
476 "<th>Header 1</th>\n",
476 "<th>Header 1</th>\n",
477 "<th>Header 2</th>\n",
477 "<th>Header 2</th>\n",
478 "</tr>\n",
478 "</tr>\n",
479 "<tr>\n",
479 "<tr>\n",
480 "<td>row 1, cell 1</td>\n",
480 "<td>row 1, cell 1</td>\n",
481 "<td>row 1, cell 2</td>\n",
481 "<td>row 1, cell 2</td>\n",
482 "</tr>\n",
482 "</tr>\n",
483 "<tr>\n",
483 "<tr>\n",
484 "<td>row 2, cell 1</td>\n",
484 "<td>row 2, cell 1</td>\n",
485 "<td>row 2, cell 2</td>\n",
485 "<td>row 2, cell 2</td>\n",
486 "</tr>\n",
486 "</tr>\n",
487 "</table>"
487 "</table>"
488 ],
488 ],
489 "metadata": {},
489 "metadata": {},
490 "output_type": "display_data",
490 "output_type": "display_data",
491 "text": [
491 "text": [
492 "<IPython.core.display.HTML object>"
492 "<IPython.core.display.HTML object>"
493 ]
493 ]
494 }
494 }
495 ],
495 ],
496 "prompt_number": 14
496 "prompt_number": 15
497 },
497 },
498 {
498 {
499 "cell_type": "markdown",
499 "cell_type": "markdown",
500 "metadata": {},
500 "metadata": {},
501 "source": [
501 "source": [
502 "You can also use the `%%html` cell magic to accomplish the same thing."
502 "You can also use the `%%html` cell magic to accomplish the same thing."
503 ]
503 ]
504 },
504 },
505 {
505 {
506 "cell_type": "code",
506 "cell_type": "code",
507 "collapsed": false,
507 "collapsed": false,
508 "input": [
508 "input": [
509 "%%html\n",
509 "%%html\n",
510 "<table>\n",
510 "<table>\n",
511 "<tr>\n",
511 "<tr>\n",
512 "<th>Header 1</th>\n",
512 "<th>Header 1</th>\n",
513 "<th>Header 2</th>\n",
513 "<th>Header 2</th>\n",
514 "</tr>\n",
514 "</tr>\n",
515 "<tr>\n",
515 "<tr>\n",
516 "<td>row 1, cell 1</td>\n",
516 "<td>row 1, cell 1</td>\n",
517 "<td>row 1, cell 2</td>\n",
517 "<td>row 1, cell 2</td>\n",
518 "</tr>\n",
518 "</tr>\n",
519 "<tr>\n",
519 "<tr>\n",
520 "<td>row 2, cell 1</td>\n",
520 "<td>row 2, cell 1</td>\n",
521 "<td>row 2, cell 2</td>\n",
521 "<td>row 2, cell 2</td>\n",
522 "</tr>\n",
522 "</tr>\n",
523 "</table>"
523 "</table>"
524 ],
524 ],
525 "language": "python",
525 "language": "python",
526 "metadata": {},
526 "metadata": {},
527 "outputs": [
527 "outputs": [
528 {
528 {
529 "html": [
529 "html": [
530 "<table>\n",
530 "<table>\n",
531 "<tr>\n",
531 "<tr>\n",
532 "<th>Header 1</th>\n",
532 "<th>Header 1</th>\n",
533 "<th>Header 2</th>\n",
533 "<th>Header 2</th>\n",
534 "</tr>\n",
534 "</tr>\n",
535 "<tr>\n",
535 "<tr>\n",
536 "<td>row 1, cell 1</td>\n",
536 "<td>row 1, cell 1</td>\n",
537 "<td>row 1, cell 2</td>\n",
537 "<td>row 1, cell 2</td>\n",
538 "</tr>\n",
538 "</tr>\n",
539 "<tr>\n",
539 "<tr>\n",
540 "<td>row 2, cell 1</td>\n",
540 "<td>row 2, cell 1</td>\n",
541 "<td>row 2, cell 2</td>\n",
541 "<td>row 2, cell 2</td>\n",
542 "</tr>\n",
542 "</tr>\n",
543 "</table>"
543 "</table>"
544 ],
544 ],
545 "metadata": {},
545 "metadata": {},
546 "output_type": "display_data",
546 "output_type": "display_data",
547 "text": [
547 "text": [
548 "<IPython.core.display.HTML object>"
548 "<IPython.core.display.HTML object>"
549 ]
549 ]
550 }
550 }
551 ],
551 ],
552 "prompt_number": 15
552 "prompt_number": 16
553 },
553 },
554 {
554 {
555 "cell_type": "heading",
555 "cell_type": "heading",
556 "level": 2,
556 "level": 2,
557 "metadata": {},
557 "metadata": {},
558 "source": [
558 "source": [
559 "JavaScript"
559 "JavaScript"
560 ]
560 ]
561 },
561 },
562 {
562 {
563 "cell_type": "markdown",
563 "cell_type": "markdown",
564 "metadata": {},
564 "metadata": {},
565 "source": [
565 "source": [
566 "The Notebook also enables objects to declare a JavaScript representation. At first, this may seem odd as output is inherently visual and JavaScript is a programming language. However, this opens the door for rich output that leverages the full power of JavaScript and associated libraries such as [d3.js](http://d3js.org) for output."
566 "The Notebook also enables objects to declare a JavaScript representation. At first, this may seem odd as output is inherently visual and JavaScript is a programming language. However, this opens the door for rich output that leverages the full power of JavaScript and associated libraries such as [d3.js](http://d3js.org) for output."
567 ]
567 ]
568 },
568 },
569 {
569 {
570 "cell_type": "code",
570 "cell_type": "code",
571 "collapsed": false,
571 "collapsed": false,
572 "input": [
572 "input": [
573 "from IPython.display import Javascript"
573 "from IPython.display import Javascript"
574 ],
574 ],
575 "language": "python",
575 "language": "python",
576 "metadata": {},
576 "metadata": {},
577 "outputs": [],
577 "outputs": [],
578 "prompt_number": 16
578 "prompt_number": 17
579 },
579 },
580 {
580 {
581 "cell_type": "markdown",
581 "cell_type": "markdown",
582 "metadata": {},
582 "metadata": {},
583 "source": [
583 "source": [
584 "Pass a string of JavaScript source code to the `JavaScript` object and then display it."
584 "Pass a string of JavaScript source code to the `JavaScript` object and then display it."
585 ]
585 ]
586 },
586 },
587 {
587 {
588 "cell_type": "code",
588 "cell_type": "code",
589 "collapsed": false,
589 "collapsed": false,
590 "input": [
590 "input": [
591 "js = Javascript('alert(\"hi\")');"
591 "js = Javascript('alert(\"hi\")');"
592 ],
592 ],
593 "language": "python",
593 "language": "python",
594 "metadata": {},
594 "metadata": {},
595 "outputs": [],
595 "outputs": [],
596 "prompt_number": 17
596 "prompt_number": 18
597 },
597 },
598 {
598 {
599 "cell_type": "code",
599 "cell_type": "code",
600 "collapsed": false,
600 "collapsed": false,
601 "input": [
601 "input": [
602 "display(js)"
602 "display(js)"
603 ],
603 ],
604 "language": "python",
604 "language": "python",
605 "metadata": {},
605 "metadata": {},
606 "outputs": [
606 "outputs": [
607 {
607 {
608 "javascript": [
608 "javascript": [
609 "alert(\"hi\")"
609 "alert(\"hi\")"
610 ],
610 ],
611 "metadata": {},
611 "metadata": {},
612 "output_type": "display_data",
612 "output_type": "display_data",
613 "text": [
613 "text": [
614 "<IPython.core.display.Javascript object>"
614 "<IPython.core.display.Javascript object>"
615 ]
615 ]
616 }
616 }
617 ],
617 ],
618 "prompt_number": 18
618 "prompt_number": 19
619 },
619 },
620 {
620 {
621 "cell_type": "markdown",
621 "cell_type": "markdown",
622 "metadata": {},
622 "metadata": {},
623 "source": [
623 "source": [
624 "The same thing can be accomplished using the `%%javascript` cell magic:"
624 "The same thing can be accomplished using the `%%javascript` cell magic:"
625 ]
625 ]
626 },
626 },
627 {
627 {
628 "cell_type": "code",
628 "cell_type": "code",
629 "collapsed": false,
629 "collapsed": false,
630 "input": [
630 "input": [
631 "%%javascript\n",
631 "%%javascript\n",
632 "\n",
632 "\n",
633 "alert(\"hi\");"
633 "alert(\"hi\");"
634 ],
634 ],
635 "language": "python",
635 "language": "python",
636 "metadata": {},
636 "metadata": {},
637 "outputs": [
637 "outputs": [
638 {
638 {
639 "javascript": [
639 "javascript": [
640 "\n",
640 "\n",
641 "alert(\"hi\");"
641 "alert(\"hi\");"
642 ],
642 ],
643 "metadata": {},
643 "metadata": {},
644 "output_type": "display_data",
644 "output_type": "display_data",
645 "text": [
645 "text": [
646 "<IPython.core.display.Javascript object>"
646 "<IPython.core.display.Javascript object>"
647 ]
647 ]
648 }
648 }
649 ],
649 ],
650 "prompt_number": 20
650 "prompt_number": 20
651 },
651 },
652 {
652 {
653 "cell_type": "markdown",
653 "cell_type": "markdown",
654 "metadata": {},
654 "metadata": {},
655 "source": [
655 "source": [
656 "Here is a more complicated example that loads `d3.js` from a CDN, uses the `%%html` magic to load CSS styles onto the page and then runs ones of the `d3.js` examples."
656 "Here is a more complicated example that loads `d3.js` from a CDN, uses the `%%html` magic to load CSS styles onto the page and then runs ones of the `d3.js` examples."
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 "Javascript(\n",
663 "Javascript(\n",
664 " \"\"\"$.getScript('//cdnjs.cloudflare.com/ajax/libs/d3/3.2.2/d3.v3.min.js')\"\"\"\n",
664 " \"\"\"$.getScript('//cdnjs.cloudflare.com/ajax/libs/d3/3.2.2/d3.v3.min.js')\"\"\"\n",
665 ")"
665 ")"
666 ],
666 ],
667 "language": "python",
667 "language": "python",
668 "metadata": {},
668 "metadata": {},
669 "outputs": [
669 "outputs": [
670 {
670 {
671 "javascript": [
671 "javascript": [
672 "$.getScript('//cdnjs.cloudflare.com/ajax/libs/d3/3.2.2/d3.v3.min.js')"
672 "$.getScript('//cdnjs.cloudflare.com/ajax/libs/d3/3.2.2/d3.v3.min.js')"
673 ],
673 ],
674 "metadata": {},
674 "metadata": {},
675 "output_type": "pyout",
675 "output_type": "pyout",
676 "prompt_number": 21,
676 "prompt_number": 21,
677 "text": [
677 "text": [
678 "<IPython.core.display.Javascript object>"
678 "<IPython.core.display.Javascript object>"
679 ]
679 ]
680 }
680 }
681 ],
681 ],
682 "prompt_number": 21
682 "prompt_number": 21
683 },
683 },
684 {
684 {
685 "cell_type": "code",
685 "cell_type": "code",
686 "collapsed": false,
686 "collapsed": false,
687 "input": [
687 "input": [
688 "%%html\n",
688 "%%html\n",
689 "<style type=\"text/css\">\n",
689 "<style type=\"text/css\">\n",
690 "\n",
690 "\n",
691 "circle {\n",
691 "circle {\n",
692 " fill: rgb(31, 119, 180);\n",
692 " fill: rgb(31, 119, 180);\n",
693 " fill-opacity: .25;\n",
693 " fill-opacity: .25;\n",
694 " stroke: rgb(31, 119, 180);\n",
694 " stroke: rgb(31, 119, 180);\n",
695 " stroke-width: 1px;\n",
695 " stroke-width: 1px;\n",
696 "}\n",
696 "}\n",
697 "\n",
697 "\n",
698 ".leaf circle {\n",
698 ".leaf circle {\n",
699 " fill: #ff7f0e;\n",
699 " fill: #ff7f0e;\n",
700 " fill-opacity: 1;\n",
700 " fill-opacity: 1;\n",
701 "}\n",
701 "}\n",
702 "\n",
702 "\n",
703 "text {\n",
703 "text {\n",
704 " font: 10px sans-serif;\n",
704 " font: 10px sans-serif;\n",
705 "}\n",
705 "}\n",
706 "\n",
706 "\n",
707 "</style>"
707 "</style>"
708 ],
708 ],
709 "language": "python",
709 "language": "python",
710 "metadata": {},
710 "metadata": {},
711 "outputs": [
711 "outputs": [
712 {
712 {
713 "html": [
713 "html": [
714 "<style type=\"text/css\">\n",
714 "<style type=\"text/css\">\n",
715 "\n",
715 "\n",
716 "circle {\n",
716 "circle {\n",
717 " fill: rgb(31, 119, 180);\n",
717 " fill: rgb(31, 119, 180);\n",
718 " fill-opacity: .25;\n",
718 " fill-opacity: .25;\n",
719 " stroke: rgb(31, 119, 180);\n",
719 " stroke: rgb(31, 119, 180);\n",
720 " stroke-width: 1px;\n",
720 " stroke-width: 1px;\n",
721 "}\n",
721 "}\n",
722 "\n",
722 "\n",
723 ".leaf circle {\n",
723 ".leaf circle {\n",
724 " fill: #ff7f0e;\n",
724 " fill: #ff7f0e;\n",
725 " fill-opacity: 1;\n",
725 " fill-opacity: 1;\n",
726 "}\n",
726 "}\n",
727 "\n",
727 "\n",
728 "text {\n",
728 "text {\n",
729 " font: 10px sans-serif;\n",
729 " font: 10px sans-serif;\n",
730 "}\n",
730 "}\n",
731 "\n",
731 "\n",
732 "</style>"
732 "</style>"
733 ],
733 ],
734 "metadata": {},
734 "metadata": {},
735 "output_type": "display_data",
735 "output_type": "display_data",
736 "text": [
736 "text": [
737 "<IPython.core.display.HTML object>"
737 "<IPython.core.display.HTML object>"
738 ]
738 ]
739 }
739 }
740 ],
740 ],
741 "prompt_number": 22
741 "prompt_number": 22
742 },
742 },
743 {
743 {
744 "cell_type": "code",
744 "cell_type": "code",
745 "collapsed": false,
745 "collapsed": false,
746 "input": [
746 "input": [
747 "%%javascript\n",
747 "%%javascript\n",
748 "\n",
748 "\n",
749 "// element is the jQuery element we will append to\n",
749 "// element is the jQuery element we will append to\n",
750 "var e = element.get(0);\n",
750 "var e = element.get(0);\n",
751 " \n",
751 " \n",
752 "var diameter = 600,\n",
752 "var diameter = 600,\n",
753 " format = d3.format(\",d\");\n",
753 " format = d3.format(\",d\");\n",
754 "\n",
754 "\n",
755 "var pack = d3.layout.pack()\n",
755 "var pack = d3.layout.pack()\n",
756 " .size([diameter - 4, diameter - 4])\n",
756 " .size([diameter - 4, diameter - 4])\n",
757 " .value(function(d) { return d.size; });\n",
757 " .value(function(d) { return d.size; });\n",
758 "\n",
758 "\n",
759 "var svg = d3.select(e).append(\"svg\")\n",
759 "var svg = d3.select(e).append(\"svg\")\n",
760 " .attr(\"width\", diameter)\n",
760 " .attr(\"width\", diameter)\n",
761 " .attr(\"height\", diameter)\n",
761 " .attr(\"height\", diameter)\n",
762 " .append(\"g\")\n",
762 " .append(\"g\")\n",
763 " .attr(\"transform\", \"translate(2,2)\");\n",
763 " .attr(\"transform\", \"translate(2,2)\");\n",
764 "\n",
764 "\n",
765 "d3.json(\"data/flare.json\", function(error, root) {\n",
765 "d3.json(\"data/flare.json\", function(error, root) {\n",
766 " var node = svg.datum(root).selectAll(\".node\")\n",
766 " var node = svg.datum(root).selectAll(\".node\")\n",
767 " .data(pack.nodes)\n",
767 " .data(pack.nodes)\n",
768 " .enter().append(\"g\")\n",
768 " .enter().append(\"g\")\n",
769 " .attr(\"class\", function(d) { return d.children ? \"node\" : \"leaf node\"; })\n",
769 " .attr(\"class\", function(d) { return d.children ? \"node\" : \"leaf node\"; })\n",
770 " .attr(\"transform\", function(d) { return \"translate(\" + d.x + \",\" + d.y + \")\"; });\n",
770 " .attr(\"transform\", function(d) { return \"translate(\" + d.x + \",\" + d.y + \")\"; });\n",
771 "\n",
771 "\n",
772 " node.append(\"title\")\n",
772 " node.append(\"title\")\n",
773 " .text(function(d) { return d.name + (d.children ? \"\" : \": \" + format(d.size)); });\n",
773 " .text(function(d) { return d.name + (d.children ? \"\" : \": \" + format(d.size)); });\n",
774 "\n",
774 "\n",
775 " node.append(\"circle\")\n",
775 " node.append(\"circle\")\n",
776 " .attr(\"r\", function(d) { return d.r; });\n",
776 " .attr(\"r\", function(d) { return d.r; });\n",
777 "\n",
777 "\n",
778 " node.filter(function(d) { return !d.children; }).append(\"text\")\n",
778 " node.filter(function(d) { return !d.children; }).append(\"text\")\n",
779 " .attr(\"dy\", \".3em\")\n",
779 " .attr(\"dy\", \".3em\")\n",
780 " .style(\"text-anchor\", \"middle\")\n",
780 " .style(\"text-anchor\", \"middle\")\n",
781 " .text(function(d) { return d.name.substring(0, d.r / 3); });\n",
781 " .text(function(d) { return d.name.substring(0, d.r / 3); });\n",
782 "});\n",
782 "});\n",
783 "\n",
783 "\n",
784 "d3.select(self.frameElement).style(\"height\", diameter + \"px\");"
784 "d3.select(self.frameElement).style(\"height\", diameter + \"px\");"
785 ],
785 ],
786 "language": "python",
786 "language": "python",
787 "metadata": {},
787 "metadata": {},
788 "outputs": [
788 "outputs": [
789 {
789 {
790 "javascript": [
790 "javascript": [
791 "\n",
791 "\n",
792 "// element is the jQuery element we will append to\n",
792 "// element is the jQuery element we will append to\n",
793 "var e = element.get(0);\n",
793 "var e = element.get(0);\n",
794 " \n",
794 " \n",
795 "var diameter = 600,\n",
795 "var diameter = 600,\n",
796 " format = d3.format(\",d\");\n",
796 " format = d3.format(\",d\");\n",
797 "\n",
797 "\n",
798 "var pack = d3.layout.pack()\n",
798 "var pack = d3.layout.pack()\n",
799 " .size([diameter - 4, diameter - 4])\n",
799 " .size([diameter - 4, diameter - 4])\n",
800 " .value(function(d) { return d.size; });\n",
800 " .value(function(d) { return d.size; });\n",
801 "\n",
801 "\n",
802 "var svg = d3.select(e).append(\"svg\")\n",
802 "var svg = d3.select(e).append(\"svg\")\n",
803 " .attr(\"width\", diameter)\n",
803 " .attr(\"width\", diameter)\n",
804 " .attr(\"height\", diameter)\n",
804 " .attr(\"height\", diameter)\n",
805 " .append(\"g\")\n",
805 " .append(\"g\")\n",
806 " .attr(\"transform\", \"translate(2,2)\");\n",
806 " .attr(\"transform\", \"translate(2,2)\");\n",
807 "\n",
807 "\n",
808 "d3.json(\"data/flare.json\", function(error, root) {\n",
808 "d3.json(\"data/flare.json\", function(error, root) {\n",
809 " var node = svg.datum(root).selectAll(\".node\")\n",
809 " var node = svg.datum(root).selectAll(\".node\")\n",
810 " .data(pack.nodes)\n",
810 " .data(pack.nodes)\n",
811 " .enter().append(\"g\")\n",
811 " .enter().append(\"g\")\n",
812 " .attr(\"class\", function(d) { return d.children ? \"node\" : \"leaf node\"; })\n",
812 " .attr(\"class\", function(d) { return d.children ? \"node\" : \"leaf node\"; })\n",
813 " .attr(\"transform\", function(d) { return \"translate(\" + d.x + \",\" + d.y + \")\"; });\n",
813 " .attr(\"transform\", function(d) { return \"translate(\" + d.x + \",\" + d.y + \")\"; });\n",
814 "\n",
814 "\n",
815 " node.append(\"title\")\n",
815 " node.append(\"title\")\n",
816 " .text(function(d) { return d.name + (d.children ? \"\" : \": \" + format(d.size)); });\n",
816 " .text(function(d) { return d.name + (d.children ? \"\" : \": \" + format(d.size)); });\n",
817 "\n",
817 "\n",
818 " node.append(\"circle\")\n",
818 " node.append(\"circle\")\n",
819 " .attr(\"r\", function(d) { return d.r; });\n",
819 " .attr(\"r\", function(d) { return d.r; });\n",
820 "\n",
820 "\n",
821 " node.filter(function(d) { return !d.children; }).append(\"text\")\n",
821 " node.filter(function(d) { return !d.children; }).append(\"text\")\n",
822 " .attr(\"dy\", \".3em\")\n",
822 " .attr(\"dy\", \".3em\")\n",
823 " .style(\"text-anchor\", \"middle\")\n",
823 " .style(\"text-anchor\", \"middle\")\n",
824 " .text(function(d) { return d.name.substring(0, d.r / 3); });\n",
824 " .text(function(d) { return d.name.substring(0, d.r / 3); });\n",
825 "});\n",
825 "});\n",
826 "\n",
826 "\n",
827 "d3.select(self.frameElement).style(\"height\", diameter + \"px\");"
827 "d3.select(self.frameElement).style(\"height\", diameter + \"px\");"
828 ],
828 ],
829 "metadata": {},
829 "metadata": {},
830 "output_type": "display_data",
830 "output_type": "display_data",
831 "text": [
831 "text": [
832 "<IPython.core.display.Javascript object>"
832 "<IPython.core.display.Javascript object>"
833 ]
833 ]
834 }
834 }
835 ],
835 ],
836 "prompt_number": 23
836 "prompt_number": 23
837 },
837 },
838 {
838 {
839 "cell_type": "heading",
839 "cell_type": "heading",
840 "level": 2,
840 "level": 2,
841 "metadata": {},
841 "metadata": {},
842 "source": [
842 "source": [
843 "LaTeX"
843 "LaTeX"
844 ]
844 ]
845 },
845 },
846 {
846 {
847 "cell_type": "markdown",
847 "cell_type": "markdown",
848 "metadata": {},
848 "metadata": {},
849 "source": [
849 "source": [
850 "The IPython display system also has builtin support for the display of mathematical expressions typeset in LaTeX, which is rendered in the browser using [MathJax](http://mathjax.org)."
850 "The IPython display system also has builtin support for the display of mathematical expressions typeset in LaTeX, which is rendered in the browser using [MathJax](http://mathjax.org)."
851 ]
851 ]
852 },
852 },
853 {
853 {
854 "cell_type": "markdown",
854 "cell_type": "markdown",
855 "metadata": {},
855 "metadata": {},
856 "source": [
856 "source": [
857 "You can pass raw LaTeX test as a string to the `Math` object:"
857 "You can pass raw LaTeX test as a string to the `Math` object:"
858 ]
858 ]
859 },
859 },
860 {
860 {
861 "cell_type": "code",
861 "cell_type": "code",
862 "collapsed": false,
862 "collapsed": false,
863 "input": [
863 "input": [
864 "from IPython.display import Math\n",
864 "from IPython.display import Math\n",
865 "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')"
865 "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')"
866 ],
866 ],
867 "language": "python",
867 "language": "python",
868 "metadata": {},
868 "metadata": {},
869 "outputs": [
869 "outputs": [
870 {
870 {
871 "latex": [
871 "latex": [
872 "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$"
872 "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$"
873 ],
873 ],
874 "metadata": {},
874 "metadata": {},
875 "output_type": "pyout",
875 "output_type": "pyout",
876 "prompt_number": 24,
876 "prompt_number": 24,
877 "text": [
877 "text": [
878 "<IPython.core.display.Math object>"
878 "<IPython.core.display.Math object>"
879 ]
879 ]
880 }
880 }
881 ],
881 ],
882 "prompt_number": 24
882 "prompt_number": 24
883 },
883 },
884 {
884 {
885 "cell_type": "markdown",
885 "cell_type": "markdown",
886 "metadata": {},
886 "metadata": {},
887 "source": [
887 "source": [
888 "With the `Latex` class, you have to include the delimiters yourself. This allows you to use other LaTeX modes such as `eqnarray`:"
888 "With the `Latex` class, you have to include the delimiters yourself. This allows you to use other LaTeX modes such as `eqnarray`:"
889 ]
889 ]
890 },
890 },
891 {
891 {
892 "cell_type": "code",
892 "cell_type": "code",
893 "collapsed": false,
893 "collapsed": false,
894 "input": [
894 "input": [
895 "from IPython.display import Latex\n",
895 "from IPython.display import Latex\n",
896 "Latex(r\"\"\"\\begin{eqnarray}\n",
896 "Latex(r\"\"\"\\begin{eqnarray}\n",
897 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
897 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
898 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
898 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
899 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
899 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
900 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
900 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
901 "\\end{eqnarray}\"\"\")"
901 "\\end{eqnarray}\"\"\")"
902 ],
902 ],
903 "language": "python",
903 "language": "python",
904 "metadata": {},
904 "metadata": {},
905 "outputs": [
905 "outputs": [
906 {
906 {
907 "latex": [
907 "latex": [
908 "\\begin{eqnarray}\n",
908 "\\begin{eqnarray}\n",
909 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
909 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
910 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
910 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
911 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
911 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
912 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
912 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
913 "\\end{eqnarray}"
913 "\\end{eqnarray}"
914 ],
914 ],
915 "metadata": {},
915 "metadata": {},
916 "output_type": "pyout",
916 "output_type": "pyout",
917 "prompt_number": 25,
917 "prompt_number": 25,
918 "text": [
918 "text": [
919 "<IPython.core.display.Latex object>"
919 "<IPython.core.display.Latex object>"
920 ]
920 ]
921 }
921 }
922 ],
922 ],
923 "prompt_number": 25
923 "prompt_number": 25
924 },
924 },
925 {
925 {
926 "cell_type": "markdown",
926 "cell_type": "markdown",
927 "metadata": {},
927 "metadata": {},
928 "source": [
928 "source": [
929 "Or you can enter LaTeX directly with the `%%latex` cell magic:"
929 "Or you can enter LaTeX directly with the `%%latex` cell magic:"
930 ]
930 ]
931 },
931 },
932 {
932 {
933 "cell_type": "code",
933 "cell_type": "code",
934 "collapsed": false,
934 "collapsed": false,
935 "input": [
935 "input": [
936 "%%latex\n",
936 "%%latex\n",
937 "\\begin{align}\n",
937 "\\begin{align}\n",
938 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
938 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
939 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
939 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
940 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
940 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
941 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
941 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
942 "\\end{align}"
942 "\\end{align}"
943 ],
943 ],
944 "language": "python",
944 "language": "python",
945 "metadata": {},
945 "metadata": {},
946 "outputs": [
946 "outputs": [
947 {
947 {
948 "latex": [
948 "latex": [
949 "\\begin{align}\n",
949 "\\begin{align}\n",
950 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
950 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
951 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
951 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
952 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
952 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
953 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
953 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
954 "\\end{align}"
954 "\\end{align}"
955 ],
955 ],
956 "metadata": {},
956 "metadata": {},
957 "output_type": "display_data",
957 "output_type": "display_data",
958 "text": [
958 "text": [
959 "<IPython.core.display.Latex object>"
959 "<IPython.core.display.Latex object>"
960 ]
960 ]
961 }
961 }
962 ],
962 ],
963 "prompt_number": 26
963 "prompt_number": 26
964 },
964 },
965 {
965 {
966 "cell_type": "heading",
966 "cell_type": "heading",
967 "level": 2,
967 "level": 2,
968 "metadata": {},
968 "metadata": {},
969 "source": [
969 "source": [
970 "Audio"
970 "Audio"
971 ]
971 ]
972 },
972 },
973 {
973 {
974 "cell_type": "markdown",
974 "cell_type": "markdown",
975 "metadata": {},
975 "metadata": {},
976 "source": [
976 "source": [
977 "IPython makes it easy to work with sounds interactively. The `Audio` display class allows you to create an audio control that is embedded in the Notebook. The interface is analogous to the interface of the `Image` display class. All audio formats supported by the browser can be used. Note that no single format is presently supported in all browsers."
977 "IPython makes it easy to work with sounds interactively. The `Audio` display class allows you to create an audio control that is embedded in the Notebook. The interface is analogous to the interface of the `Image` display class. All audio formats supported by the browser can be used. Note that no single format is presently supported in all browsers."
978 ]
978 ]
979 },
979 },
980 {
980 {
981 "cell_type": "code",
981 "cell_type": "code",
982 "collapsed": false,
982 "collapsed": false,
983 "input": [
983 "input": [
984 "from IPython.display import Audio\n",
984 "from IPython.display import Audio\n",
985 "Audio(url=\"http://www.nch.com.au/acm/8k16bitpcm.wav\")"
985 "Audio(url=\"http://www.nch.com.au/acm/8k16bitpcm.wav\")"
986 ],
986 ],
987 "language": "python",
987 "language": "python",
988 "metadata": {},
988 "metadata": {},
989 "outputs": [
989 "outputs": [
990 {
990 {
991 "html": [
991 "html": [
992 "\n",
992 "\n",
993 " <audio controls=\"controls\" >\n",
993 " <audio controls=\"controls\" >\n",
994 " <source src=\"http://www.nch.com.au/acm/8k16bitpcm.wav\" type=\"audio/x-wav\" />\n",
994 " <source src=\"http://www.nch.com.au/acm/8k16bitpcm.wav\" type=\"audio/x-wav\" />\n",
995 " Your browser does not support the audio element.\n",
995 " Your browser does not support the audio element.\n",
996 " </audio>\n",
996 " </audio>\n",
997 " "
997 " "
998 ],
998 ],
999 "metadata": {},
999 "metadata": {},
1000 "output_type": "pyout",
1000 "output_type": "pyout",
1001 "prompt_number": 28,
1001 "prompt_number": 27,
1002 "text": [
1002 "text": [
1003 "<IPython.lib.display.Audio object>"
1003 "<IPython.lib.display.Audio object>"
1004 ]
1004 ]
1005 }
1005 }
1006 ],
1006 ],
1007 "prompt_number": 28
1007 "prompt_number": 27
1008 },
1008 },
1009 {
1009 {
1010 "cell_type": "markdown",
1010 "cell_type": "markdown",
1011 "metadata": {},
1011 "metadata": {},
1012 "source": [
1012 "source": [
1013 "A NumPy array can be auralized automatically. The `Audio` class normalizes and encodes the data and embeds the resulting audio in the Notebook.\n",
1013 "A NumPy array can be auralized automatically. The `Audio` class normalizes and encodes the data and embeds the resulting audio in the Notebook.\n",
1014 "\n",
1014 "\n",
1015 "For instance, when two sine waves with almost the same frequency are superimposed a phenomena known as [beats](https://en.wikipedia.org/wiki/Beat_%28acoustics%29) occur. This can be auralised as follows:"
1015 "For instance, when two sine waves with almost the same frequency are superimposed a phenomena known as [beats](https://en.wikipedia.org/wiki/Beat_%28acoustics%29) occur. This can be auralised as follows:"
1016 ]
1016 ]
1017 },
1017 },
1018 {
1018 {
1019 "cell_type": "code",
1019 "cell_type": "code",
1020 "collapsed": false,
1020 "collapsed": false,
1021 "input": [
1021 "input": [
1022 "import numpy as np\n",
1022 "import numpy as np\n",
1023 "max_time = 3\n",
1023 "max_time = 3\n",
1024 "f1 = 220.0\n",
1024 "f1 = 220.0\n",
1025 "f2 = 224.0\n",
1025 "f2 = 224.0\n",
1026 "rate = 8000.0\n",
1026 "rate = 8000.0\n",
1027 "L = 3\n",
1027 "L = 3\n",
1028 "times = np.linspace(0,L,rate*L)\n",
1028 "times = np.linspace(0,L,rate*L)\n",
1029 "signal = np.sin(2*np.pi*f1*times) + np.sin(2*np.pi*f2*times)\n",
1029 "signal = np.sin(2*np.pi*f1*times) + np.sin(2*np.pi*f2*times)\n",
1030 "\n",
1030 "\n",
1031 "Audio(data=signal, rate=rate)"
1031 "Audio(data=signal, rate=rate)"
1032 ],
1032 ],
1033 "language": "python",
1033 "language": "python",
1034 "metadata": {},
1034 "metadata": {},
1035 "outputs": [
1035 "outputs": [
1036 {
1036 {
1037 "html": [
1037 "html": [
1038 "\n",
1038 "\n",
1039 " <audio controls=\"controls\" >\n",
1039 " <audio controls=\"controls\" >\n",
1040 " <source 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\" 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\" type=\"audio/wav\" />\n",
1041 " Your browser does not support the audio element.\n",
1041 " Your browser does not support the audio element.\n",
1042 " </audio>\n",
1042 " </audio>\n",
1043 " "
1043 " "
1044 ],
1044 ],
1045 "metadata": {},
1045 "metadata": {},
1046 "output_type": "pyout",
1046 "output_type": "pyout",
1047 "prompt_number": 29,
1047 "prompt_number": 28,
1048 "text": [
1048 "text": [
1049 "<IPython.lib.display.Audio object>"
1049 "<IPython.lib.display.Audio object>"
1050 ]
1050 ]
1051 }
1051 }
1052 ],
1052 ],
1053 "prompt_number": 29
1053 "prompt_number": 28
1054 },
1054 },
1055 {
1055 {
1056 "cell_type": "heading",
1056 "cell_type": "heading",
1057 "level": 2,
1057 "level": 2,
1058 "metadata": {},
1058 "metadata": {},
1059 "source": [
1059 "source": [
1060 "Video"
1060 "Video"
1061 ]
1061 ]
1062 },
1062 },
1063 {
1063 {
1064 "cell_type": "markdown",
1064 "cell_type": "markdown",
1065 "metadata": {},
1065 "metadata": {},
1066 "source": [
1066 "source": [
1067 "More exotic objects can also be displayed, as long as their representation supports the IPython display protocol. For example, videos hosted externally on YouTube are easy to load:"
1067 "More exotic objects can also be displayed, as long as their representation supports the IPython display protocol. For example, videos hosted externally on YouTube are easy to load:"
1068 ]
1068 ]
1069 },
1069 },
1070 {
1070 {
1071 "cell_type": "code",
1071 "cell_type": "code",
1072 "collapsed": false,
1072 "collapsed": false,
1073 "input": [
1073 "input": [
1074 "from IPython.display import YouTubeVideo\n",
1074 "from IPython.display import YouTubeVideo\n",
1075 "YouTubeVideo('sjfsUzECqK0')"
1075 "YouTubeVideo('sjfsUzECqK0')"
1076 ],
1076 ],
1077 "language": "python",
1077 "language": "python",
1078 "metadata": {},
1078 "metadata": {},
1079 "outputs": [
1079 "outputs": [
1080 {
1080 {
1081 "html": [
1081 "html": [
1082 "\n",
1082 "\n",
1083 " <iframe\n",
1083 " <iframe\n",
1084 " width=\"400\"\n",
1084 " width=\"400\"\n",
1085 " height=300\"\n",
1085 " height=300\"\n",
1086 " src=\"https://www.youtube.com/embed/sjfsUzECqK0\"\n",
1086 " src=\"https://www.youtube.com/embed/sjfsUzECqK0\"\n",
1087 " frameborder=\"0\"\n",
1087 " frameborder=\"0\"\n",
1088 " allowfullscreen\n",
1088 " allowfullscreen\n",
1089 " ></iframe>\n",
1089 " ></iframe>\n",
1090 " "
1090 " "
1091 ],
1091 ],
1092 "metadata": {},
1092 "metadata": {},
1093 "output_type": "pyout",
1093 "output_type": "pyout",
1094 "prompt_number": 20,
1094 "prompt_number": 29,
1095 "text": [
1095 "text": [
1096 "<IPython.lib.display.YouTubeVideo at 0x10a0d8190>"
1096 "<IPython.lib.display.YouTubeVideo at 0x107c1eb50>"
1097 ]
1097 ]
1098 }
1098 }
1099 ],
1099 ],
1100 "prompt_number": 20
1100 "prompt_number": 29
1101 },
1101 },
1102 {
1102 {
1103 "cell_type": "markdown",
1103 "cell_type": "markdown",
1104 "metadata": {},
1104 "metadata": {},
1105 "source": [
1105 "source": [
1106 "Using the nascent video capabilities of modern browsers, you may also be able to display local\n",
1106 "Using the nascent video capabilities of modern browsers, you may also be able to display local\n",
1107 "videos. At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n",
1107 "videos. At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n",
1108 "we will continue testing this and looking for ways to make it more robust. \n",
1108 "we will continue testing this and looking for ways to make it more robust. \n",
1109 "\n",
1109 "\n",
1110 "The following cell loads a local file called `animation.m4v`, encodes the raw video as base64 for http\n",
1110 "The following cell loads a local file called `animation.m4v`, encodes the raw video as base64 for http\n",
1111 "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control bar at the bottom with a play/pause button and a location slider."
1111 "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control bar at the bottom with a play/pause button and a location slider."
1112 ]
1112 ]
1113 },
1113 },
1114 {
1114 {
1115 "cell_type": "code",
1115 "cell_type": "code",
1116 "collapsed": false,
1116 "collapsed": false,
1117 "input": [
1117 "input": [
1118 "from IPython.display import HTML\n",
1118 "from IPython.display import HTML\n",
1119 "from base64 import b64encode\n",
1119 "from base64 import b64encode\n",
1120 "video = open(\"../images/animation.m4v\", \"rb\").read()\n",
1120 "video = open(\"../images/animation.m4v\", \"rb\").read()\n",
1121 "video_encoded = b64encode(video).decode('ascii')\n",
1121 "video_encoded = b64encode(video).decode('ascii')\n",
1122 "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n",
1122 "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n",
1123 "HTML(data=video_tag)"
1123 "HTML(data=video_tag)"
1124 ],
1124 ],
1125 "language": "python",
1125 "language": "python",
1126 "metadata": {},
1126 "metadata": {},
1127 "outputs": [
1127 "outputs": [
1128 {
1128 {
1129 "html": [
1129 "html": [
1130 "<video controls alt=\"test\" 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1130 "<video controls alt=\"test\" 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1131 ],
1131 ],
1132 "metadata": {},
1132 "metadata": {},
1133 "output_type": "pyout",
1133 "output_type": "pyout",
1134 "prompt_number": 30,
1134 "prompt_number": 30,
1135 "text": [
1135 "text": [
1136 "<IPython.core.display.HTML object>"
1136 "<IPython.core.display.HTML object>"
1137 ]
1137 ]
1138 }
1138 }
1139 ],
1139 ],
1140 "prompt_number": 30
1140 "prompt_number": 30
1141 },
1141 },
1142 {
1142 {
1143 "cell_type": "heading",
1143 "cell_type": "heading",
1144 "level": 2,
1144 "level": 2,
1145 "metadata": {},
1145 "metadata": {},
1146 "source": [
1146 "source": [
1147 "External sites"
1147 "External sites"
1148 ]
1148 ]
1149 },
1149 },
1150 {
1150 {
1151 "cell_type": "markdown",
1151 "cell_type": "markdown",
1152 "metadata": {},
1152 "metadata": {},
1153 "source": [
1153 "source": [
1154 "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n",
1154 "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n",
1155 "page for mobile users:"
1155 "page for mobile users:"
1156 ]
1156 ]
1157 },
1157 },
1158 {
1158 {
1159 "cell_type": "code",
1159 "cell_type": "code",
1160 "collapsed": false,
1160 "collapsed": false,
1161 "input": [
1161 "input": [
1162 "from IPython.display import IFrame\n",
1162 "from IPython.display import IFrame\n",
1163 "IFrame('http://python.org', width='100%', height=350)"
1163 "IFrame('http://ipython.org', width='100%', height=350)"
1164 ],
1164 ],
1165 "language": "python",
1165 "language": "python",
1166 "metadata": {},
1166 "metadata": {},
1167 "outputs": [
1167 "outputs": [
1168 {
1168 {
1169 "html": [
1169 "html": [
1170 "\n",
1170 "\n",
1171 " <iframe\n",
1171 " <iframe\n",
1172 " width=\"100%\"\n",
1172 " width=\"100%\"\n",
1173 " height=350\"\n",
1173 " height=350\"\n",
1174 " src=\"http://python.org\"\n",
1174 " src=\"http://ipython.org\"\n",
1175 " frameborder=\"0\"\n",
1175 " frameborder=\"0\"\n",
1176 " allowfullscreen\n",
1176 " allowfullscreen\n",
1177 " ></iframe>\n",
1177 " ></iframe>\n",
1178 " "
1178 " "
1179 ],
1179 ],
1180 "metadata": {},
1180 "metadata": {},
1181 "output_type": "pyout",
1181 "output_type": "pyout",
1182 "prompt_number": 31,
1182 "prompt_number": 31,
1183 "text": [
1183 "text": [
1184 "<IPython.lib.display.IFrame at 0x10569f950>"
1184 "<IPython.lib.display.IFrame at 0x107c1ecd0>"
1185 ]
1185 ]
1186 }
1186 }
1187 ],
1187 ],
1188 "prompt_number": 31
1188 "prompt_number": 31
1189 },
1189 },
1190 {
1190 {
1191 "cell_type": "heading",
1191 "cell_type": "heading",
1192 "level": 2,
1192 "level": 2,
1193 "metadata": {},
1193 "metadata": {},
1194 "source": [
1194 "source": [
1195 "Links to local files"
1195 "Links to local files"
1196 ]
1196 ]
1197 },
1197 },
1198 {
1198 {
1199 "cell_type": "markdown",
1199 "cell_type": "markdown",
1200 "metadata": {},
1200 "metadata": {},
1201 "source": [
1201 "source": [
1202 "IPython provides builtin display classes for generating links to local files. Create a link to a single file using the `FileLink` object:"
1202 "IPython provides builtin display classes for generating links to local files. Create a link to a single file using the `FileLink` object:"
1203 ]
1203 ]
1204 },
1204 },
1205 {
1205 {
1206 "cell_type": "code",
1206 "cell_type": "code",
1207 "collapsed": false,
1207 "collapsed": false,
1208 "input": [
1208 "input": [
1209 "from IPython.display import FileLink, FileLinks\n",
1209 "from IPython.display import FileLink, FileLinks\n",
1210 "FileLink('Cell Magics.ipynb')"
1210 "FileLink('Cell Magics.ipynb')"
1211 ],
1211 ],
1212 "language": "python",
1212 "language": "python",
1213 "metadata": {},
1213 "metadata": {},
1214 "outputs": [
1214 "outputs": [
1215 {
1215 {
1216 "html": [
1216 "html": [
1217 "<a href='Cell Magics.ipynb' target='_blank'>Cell Magics.ipynb</a><br>"
1217 "<a href='Cell Magics.ipynb' target='_blank'>Cell Magics.ipynb</a><br>"
1218 ],
1218 ],
1219 "metadata": {},
1219 "metadata": {},
1220 "output_type": "pyout",
1220 "output_type": "pyout",
1221 "prompt_number": 33,
1221 "prompt_number": 33,
1222 "text": [
1222 "text": [
1223 "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/IPython Kernel/Cell Magics.ipynb"
1223 "/Users/bgranger/Documents/Computing/IPython/code/ipython/examples/IPython Kernel/Cell Magics.ipynb"
1224 ]
1224 ]
1225 }
1225 }
1226 ],
1226 ],
1227 "prompt_number": 33
1227 "prompt_number": 33
1228 },
1228 },
1229 {
1229 {
1230 "cell_type": "markdown",
1230 "cell_type": "markdown",
1231 "metadata": {},
1231 "metadata": {},
1232 "source": [
1232 "source": [
1233 "Alternatively, to generate links to all of the files in a directory, use the `FileLinks` object, passing `'.'` to indicate that we want links generated for the current working directory. Note that if there were other directories under the current directory, `FileLinks` would work in a recursive manner creating links to files in all sub-directories as well."
1233 "Alternatively, to generate links to all of the files in a directory, use the `FileLinks` object, passing `'.'` to indicate that we want links generated for the current working directory. Note that if there were other directories under the current directory, `FileLinks` would work in a recursive manner creating links to files in all sub-directories as well."
1234 ]
1234 ]
1235 },
1235 },
1236 {
1236 {
1237 "cell_type": "code",
1237 "cell_type": "code",
1238 "collapsed": false,
1238 "collapsed": false,
1239 "input": [
1239 "input": [
1240 "FileLinks('.')"
1240 "FileLinks('.')"
1241 ],
1241 ],
1242 "language": "python",
1242 "language": "python",
1243 "metadata": {},
1243 "metadata": {},
1244 "outputs": [
1244 "outputs": [
1245 {
1245 {
1246 "html": [
1246 "html": [
1247 "./<br>\n",
1247 "./<br>\n",
1248 "&nbsp;&nbsp;<a href='./Animations Using clear_output.ipynb' target='_blank'>Animations Using clear_output.ipynb</a><br>\n",
1248 "&nbsp;&nbsp;<a href='./Animations Using clear_output.ipynb' target='_blank'>Animations Using clear_output.ipynb</a><br>\n",
1249 "&nbsp;&nbsp;<a href='./Background Jobs.ipynb' target='_blank'>Background Jobs.ipynb</a><br>\n",
1249 "&nbsp;&nbsp;<a href='./Background Jobs.ipynb' target='_blank'>Background Jobs.ipynb</a><br>\n",
1250 "&nbsp;&nbsp;<a href='./Beyond Plain Python.ipynb' target='_blank'>Beyond Plain Python.ipynb</a><br>\n",
1250 "&nbsp;&nbsp;<a href='./Beyond Plain Python.ipynb' target='_blank'>Beyond Plain Python.ipynb</a><br>\n",
1251 "&nbsp;&nbsp;<a href='./Capturing Output.ipynb' target='_blank'>Capturing Output.ipynb</a><br>\n",
1251 "&nbsp;&nbsp;<a href='./Capturing Output.ipynb' target='_blank'>Capturing Output.ipynb</a><br>\n",
1252 "&nbsp;&nbsp;<a href='./Cell Magics.ipynb' target='_blank'>Cell Magics.ipynb</a><br>\n",
1252 "&nbsp;&nbsp;<a href='./Cell Magics.ipynb' target='_blank'>Cell Magics.ipynb</a><br>\n",
1253 "&nbsp;&nbsp;<a href='./Custom Display Logic.ipynb' target='_blank'>Custom Display Logic.ipynb</a><br>\n",
1253 "&nbsp;&nbsp;<a href='./Custom Display Logic.ipynb' target='_blank'>Custom Display Logic.ipynb</a><br>\n",
1254 "&nbsp;&nbsp;<a href='./example-demo.py' target='_blank'>example-demo.py</a><br>\n",
1254 "&nbsp;&nbsp;<a href='./example-demo.py' target='_blank'>example-demo.py</a><br>\n",
1255 "&nbsp;&nbsp;<a href='./Index.ipynb' target='_blank'>Index.ipynb</a><br>\n",
1255 "&nbsp;&nbsp;<a href='./Index.ipynb' target='_blank'>Index.ipynb</a><br>\n",
1256 "&nbsp;&nbsp;<a href='./ipython-completion.bash' target='_blank'>ipython-completion.bash</a><br>\n",
1256 "&nbsp;&nbsp;<a href='./ipython-completion.bash' target='_blank'>ipython-completion.bash</a><br>\n",
1257 "&nbsp;&nbsp;<a href='./ipython-get-history.py' target='_blank'>ipython-get-history.py</a><br>\n",
1257 "&nbsp;&nbsp;<a href='./ipython-get-history.py' target='_blank'>ipython-get-history.py</a><br>\n",
1258 "&nbsp;&nbsp;<a href='./ipython-qtconsole.desktop' target='_blank'>ipython-qtconsole.desktop</a><br>\n",
1258 "&nbsp;&nbsp;<a href='./ipython-qtconsole.desktop' target='_blank'>ipython-qtconsole.desktop</a><br>\n",
1259 "&nbsp;&nbsp;<a href='./ipython.desktop' target='_blank'>ipython.desktop</a><br>\n",
1259 "&nbsp;&nbsp;<a href='./ipython.desktop' target='_blank'>ipython.desktop</a><br>\n",
1260 "&nbsp;&nbsp;<a href='./Plotting in the Notebook.ipynb' target='_blank'>Plotting in the Notebook.ipynb</a><br>\n",
1260 "&nbsp;&nbsp;<a href='./Plotting in the Notebook.ipynb' target='_blank'>Plotting in the Notebook.ipynb</a><br>\n",
1261 "&nbsp;&nbsp;<a href='./Raw Input in the Notebook.ipynb' target='_blank'>Raw Input in the Notebook.ipynb</a><br>\n",
1261 "&nbsp;&nbsp;<a href='./Raw Input in the Notebook.ipynb' target='_blank'>Raw Input in the Notebook.ipynb</a><br>\n",
1262 "&nbsp;&nbsp;<a href='./Rich Output.ipynb' target='_blank'>Rich Output.ipynb</a><br>\n",
1262 "&nbsp;&nbsp;<a href='./Rich Output.ipynb' target='_blank'>Rich Output.ipynb</a><br>\n",
1263 "&nbsp;&nbsp;<a href='./Script Magics.ipynb' target='_blank'>Script Magics.ipynb</a><br>\n",
1263 "&nbsp;&nbsp;<a href='./Script Magics.ipynb' target='_blank'>Script Magics.ipynb</a><br>\n",
1264 "&nbsp;&nbsp;<a href='./SymPy.ipynb' target='_blank'>SymPy.ipynb</a><br>\n",
1264 "&nbsp;&nbsp;<a href='./SymPy.ipynb' target='_blank'>SymPy.ipynb</a><br>\n",
1265 "&nbsp;&nbsp;<a href='./Terminal Usage.ipynb' target='_blank'>Terminal Usage.ipynb</a><br>\n",
1265 "&nbsp;&nbsp;<a href='./Terminal Usage.ipynb' target='_blank'>Terminal Usage.ipynb</a><br>\n",
1266 "&nbsp;&nbsp;<a href='./Third Party Rich Output.ipynb' target='_blank'>Third Party Rich Output.ipynb</a><br>\n",
1266 "&nbsp;&nbsp;<a href='./Third Party Rich Output.ipynb' target='_blank'>Third Party Rich Output.ipynb</a><br>\n",
1267 "&nbsp;&nbsp;<a href='./Trapezoid Rule.ipynb' target='_blank'>Trapezoid Rule.ipynb</a><br>\n",
1267 "&nbsp;&nbsp;<a href='./Trapezoid Rule.ipynb' target='_blank'>Trapezoid Rule.ipynb</a><br>\n",
1268 "&nbsp;&nbsp;<a href='./Working With External Code.ipynb' target='_blank'>Working With External Code.ipynb</a><br>\n",
1268 "&nbsp;&nbsp;<a href='./Working With External Code.ipynb' target='_blank'>Working With External Code.ipynb</a><br>\n",
1269 "./data/<br>\n",
1269 "./data/<br>\n",
1270 "&nbsp;&nbsp;<a href='./data/flare.json' target='_blank'>flare.json</a><br>\n",
1270 "&nbsp;&nbsp;<a href='./data/flare.json' target='_blank'>flare.json</a><br>\n",
1271 "./gui/<br>\n",
1271 "./gui/<br>\n",
1272 "&nbsp;&nbsp;<a href='./gui/gui-glut.py' target='_blank'>gui-glut.py</a><br>\n",
1272 "&nbsp;&nbsp;<a href='./gui/gui-glut.py' target='_blank'>gui-glut.py</a><br>\n",
1273 "&nbsp;&nbsp;<a href='./gui/gui-gtk.py' target='_blank'>gui-gtk.py</a><br>\n",
1273 "&nbsp;&nbsp;<a href='./gui/gui-gtk.py' target='_blank'>gui-gtk.py</a><br>\n",
1274 "&nbsp;&nbsp;<a href='./gui/gui-gtk3.py' target='_blank'>gui-gtk3.py</a><br>\n",
1274 "&nbsp;&nbsp;<a href='./gui/gui-gtk3.py' target='_blank'>gui-gtk3.py</a><br>\n",
1275 "&nbsp;&nbsp;<a href='./gui/gui-pyglet.py' target='_blank'>gui-pyglet.py</a><br>\n",
1275 "&nbsp;&nbsp;<a href='./gui/gui-pyglet.py' target='_blank'>gui-pyglet.py</a><br>\n",
1276 "&nbsp;&nbsp;<a href='./gui/gui-qt.py' target='_blank'>gui-qt.py</a><br>\n",
1276 "&nbsp;&nbsp;<a href='./gui/gui-qt.py' target='_blank'>gui-qt.py</a><br>\n",
1277 "&nbsp;&nbsp;<a href='./gui/gui-tk.py' target='_blank'>gui-tk.py</a><br>\n",
1277 "&nbsp;&nbsp;<a href='./gui/gui-tk.py' target='_blank'>gui-tk.py</a><br>\n",
1278 "&nbsp;&nbsp;<a href='./gui/gui-wx.py' target='_blank'>gui-wx.py</a><br>"
1278 "&nbsp;&nbsp;<a href='./gui/gui-wx.py' target='_blank'>gui-wx.py</a><br>"
1279 ],
1279 ],
1280 "metadata": {},
1280 "metadata": {},
1281 "output_type": "pyout",
1281 "output_type": "pyout",
1282 "prompt_number": 34,
1282 "prompt_number": 34,
1283 "text": [
1283 "text": [
1284 "./\n",
1284 "./\n",
1285 " Animations Using clear_output.ipynb\n",
1285 " Animations Using clear_output.ipynb\n",
1286 " Background Jobs.ipynb\n",
1286 " Background Jobs.ipynb\n",
1287 " Beyond Plain Python.ipynb\n",
1287 " Beyond Plain Python.ipynb\n",
1288 " Capturing Output.ipynb\n",
1288 " Capturing Output.ipynb\n",
1289 " Cell Magics.ipynb\n",
1289 " Cell Magics.ipynb\n",
1290 " Custom Display Logic.ipynb\n",
1290 " Custom Display Logic.ipynb\n",
1291 " example-demo.py\n",
1291 " example-demo.py\n",
1292 " Index.ipynb\n",
1292 " Index.ipynb\n",
1293 " ipython-completion.bash\n",
1293 " ipython-completion.bash\n",
1294 " ipython-get-history.py\n",
1294 " ipython-get-history.py\n",
1295 " ipython-qtconsole.desktop\n",
1295 " ipython-qtconsole.desktop\n",
1296 " ipython.desktop\n",
1296 " ipython.desktop\n",
1297 " Plotting in the Notebook.ipynb\n",
1297 " Plotting in the Notebook.ipynb\n",
1298 " Raw Input in the Notebook.ipynb\n",
1298 " Raw Input in the Notebook.ipynb\n",
1299 " Rich Output.ipynb\n",
1299 " Rich Output.ipynb\n",
1300 " Script Magics.ipynb\n",
1300 " Script Magics.ipynb\n",
1301 " SymPy.ipynb\n",
1301 " SymPy.ipynb\n",
1302 " Terminal Usage.ipynb\n",
1302 " Terminal Usage.ipynb\n",
1303 " Third Party Rich Output.ipynb\n",
1303 " Third Party Rich Output.ipynb\n",
1304 " Trapezoid Rule.ipynb\n",
1304 " Trapezoid Rule.ipynb\n",
1305 " Working With External Code.ipynb\n",
1305 " Working With External Code.ipynb\n",
1306 "./data/\n",
1306 "./data/\n",
1307 " flare.json\n",
1307 " flare.json\n",
1308 "./gui/\n",
1308 "./gui/\n",
1309 " gui-glut.py\n",
1309 " gui-glut.py\n",
1310 " gui-gtk.py\n",
1310 " gui-gtk.py\n",
1311 " gui-gtk3.py\n",
1311 " gui-gtk3.py\n",
1312 " gui-pyglet.py\n",
1312 " gui-pyglet.py\n",
1313 " gui-qt.py\n",
1313 " gui-qt.py\n",
1314 " gui-tk.py\n",
1314 " gui-tk.py\n",
1315 " gui-wx.py"
1315 " gui-wx.py"
1316 ]
1316 ]
1317 }
1317 }
1318 ],
1318 ],
1319 "prompt_number": 34
1319 "prompt_number": 34
1320 },
1320 },
1321 {
1321 {
1322 "cell_type": "heading",
1322 "cell_type": "heading",
1323 "level": 2,
1323 "level": 2,
1324 "metadata": {},
1324 "metadata": {},
1325 "source": [
1325 "source": [
1326 "Rich output and security"
1326 "Rich output and security"
1327 ]
1327 ]
1328 },
1328 },
1329 {
1329 {
1330 "cell_type": "markdown",
1330 "cell_type": "markdown",
1331 "metadata": {},
1331 "metadata": {},
1332 "source": [
1332 "source": [
1333 "The IPython Notebook allows arbitrary code execution in both the IPython kernel and in the browser, though HTML and JavaScript output. More importantly, because IPython has a JavaScript API for running code in the browser, HTML and JavaScript output can actually trigger code to be run in the kernel. This poses a significant security risk as it would allow IPython Notebooks to execute arbitrary code on your computers.\n",
1333 "The IPython Notebook allows arbitrary code execution in both the IPython kernel and in the browser, though HTML and JavaScript output. More importantly, because IPython has a JavaScript API for running code in the browser, HTML and JavaScript output can actually trigger code to be run in the kernel. This poses a significant security risk as it would allow IPython Notebooks to execute arbitrary code on your computers.\n",
1334 "\n",
1334 "\n",
1335 "To protect against these risks, the IPython Notebook has a security model that specifies how dangerous output is handled. Here is a short summary:\n",
1335 "To protect against these risks, the IPython Notebook has a security model that specifies how dangerous output is handled. Here is a short summary:\n",
1336 "\n",
1336 "\n",
1337 "* When you run code in the Notebook, all rich output is displayed.\n",
1337 "* When you run code in the Notebook, all rich output is displayed.\n",
1338 "* When you open a notebook, rich output is only displayed if it doesn't contain security vulberabilities,...\n",
1338 "* When you open a notebook, rich output is only displayed if it doesn't contain security vulberabilities,...\n",
1339 "* ..or if you have trusted a notebook, all rich output will run upon opening it.\n",
1339 "* ..or if you have trusted a notebook, all rich output will run upon opening it.\n",
1340 "\n",
1340 "\n",
1341 "A full description of the IPython security model can be found on [this page](http://ipython.org/ipython-doc/dev/notebook/security.html)."
1341 "A full description of the IPython security model can be found on [this page](http://ipython.org/ipython-doc/dev/notebook/security.html)."
1342 ]
1342 ]
1343 },
1343 },
1344 {
1344 {
1345 "cell_type": "heading",
1345 "cell_type": "heading",
1346 "level": 2,
1346 "level": 2,
1347 "metadata": {},
1347 "metadata": {},
1348 "source": [
1348 "source": [
1349 "Rich output and nbviewer"
1349 "Rich output and nbviewer"
1350 ]
1350 ]
1351 },
1351 },
1352 {
1352 {
1353 "cell_type": "markdown",
1353 "cell_type": "markdown",
1354 "metadata": {},
1354 "metadata": {},
1355 "source": [
1355 "source": [
1356 "Much of the power of the Notebook is that it enables users to share notebooks with each other using http://nbviewer.ipython.org, without installing IPython locally. As of IPython 2.0, notebooks rendere on nbviewer will display all output, including HTML and JavaScript. Furthermore, to provide a consistent JavaScript environment on the live Notebook and nbviewer, the following JavaScript libraries are loaded onto the nbviewer page, *before* the notebook and its output is displayed:\n",
1356 "Much of the power of the Notebook is that it enables users to share notebooks with each other using http://nbviewer.ipython.org, without installing IPython locally. As of IPython 2.0, notebooks rendere on nbviewer will display all output, including HTML and JavaScript. Furthermore, to provide a consistent JavaScript environment on the live Notebook and nbviewer, the following JavaScript libraries are loaded onto the nbviewer page, *before* the notebook and its output is displayed:\n",
1357 "\n",
1357 "\n",
1358 "* [jQuery](http://jquery.com/)\n",
1358 "* [jQuery](http://jquery.com/)\n",
1359 "* [RequireJS](http://requirejs.org/)\n",
1359 "* [RequireJS](http://requirejs.org/)\n",
1360 "\n",
1360 "\n",
1361 "Libraries such as [mpld3](http://mpld3.github.io/) use these capabilities to generate interactive visualizations that work on nbviewer."
1361 "Libraries such as [mpld3](http://mpld3.github.io/) use these capabilities to generate interactive visualizations that work on nbviewer."
1362 ]
1362 ]
1363 }
1363 }
1364 ],
1364 ],
1365 "metadata": {}
1365 "metadata": {}
1366 }
1366 }
1367 ]
1367 ]
1368 } No newline at end of file
1368 }
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