##// END OF EJS Templates
fixed broken import. not sure how this made it through before.
Greg Caporaso -
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@@ -1,1353 +1,1353 b''
1 1 {
2 2 "metadata": {
3 3 "name": "00_notebook_tour"
4 4 },
5 5 "nbformat": 3,
6 6 "nbformat_minor": 0,
7 7 "worksheets": [
8 8 {
9 9 "cells": [
10 10 {
11 11 "cell_type": "markdown",
12 12 "metadata": {},
13 13 "source": [
14 14 "# A brief tour of the IPython notebook\n",
15 15 "\n",
16 16 "This document will give you a brief tour of the capabilities of the IPython notebook. \n",
17 17 "You can view its contents by scrolling around, or execute each cell by typing `Shift-Enter`.\n",
18 18 "After you conclude this brief high-level tour, you should read the accompanying notebook \n",
19 19 "titled `01_notebook_introduction`, which takes a more step-by-step approach to the features of the\n",
20 20 "system. \n",
21 21 "\n",
22 22 "The rest of the notebooks in this directory illustrate various other aspects and \n",
23 23 "capabilities of the IPython notebook; some of them may require additional libraries to be executed.\n",
24 24 "\n",
25 25 "**NOTE:** This notebook *must* be run from its own directory, so you must ``cd``\n",
26 26 "to this directory and then start the notebook, but do *not* use the ``--notebook-dir``\n",
27 27 "option to run it from another location.\n",
28 28 "\n",
29 29 "The first thing you need to know is that you are still controlling the same old IPython you're used to,\n",
30 30 "so things like shell aliases and magic commands still work:"
31 31 ]
32 32 },
33 33 {
34 34 "cell_type": "code",
35 35 "collapsed": false,
36 36 "input": [
37 37 "pwd"
38 38 ],
39 39 "language": "python",
40 40 "metadata": {},
41 41 "outputs": [
42 42 {
43 43 "output_type": "pyout",
44 44 "prompt_number": 1,
45 45 "text": [
46 46 "u'/Users/minrk/dev/ip/mine/docs/examples/notebooks'"
47 47 ]
48 48 }
49 49 ],
50 50 "prompt_number": 1
51 51 },
52 52 {
53 53 "cell_type": "code",
54 54 "collapsed": false,
55 55 "input": [
56 56 "ls"
57 57 ],
58 58 "language": "python",
59 59 "metadata": {},
60 60 "outputs": [
61 61 {
62 62 "output_type": "stream",
63 63 "stream": "stdout",
64 64 "text": [
65 65 "00_notebook_tour.ipynb callbacks.ipynb python-logo.svg\r\n",
66 66 "01_notebook_introduction.ipynb cython_extension.ipynb rmagic_extension.ipynb\r\n",
67 67 "Animations_and_Progress.ipynb display_protocol.ipynb sympy.ipynb\r\n",
68 68 "Capturing Output.ipynb formatting.ipynb sympy_quantum_computing.ipynb\r\n",
69 69 "Script Magics.ipynb octavemagic_extension.ipynb trapezoid_rule.ipynb\r\n",
70 70 "animation.m4v progbar.ipynb\r\n"
71 71 ]
72 72 }
73 73 ],
74 74 "prompt_number": 2
75 75 },
76 76 {
77 77 "cell_type": "code",
78 78 "collapsed": false,
79 79 "input": [
80 80 "message = 'The IPython notebook is great!'\n",
81 81 "# note: the echo command does not run on Windows, it's a unix command.\n",
82 82 "!echo $message"
83 83 ],
84 84 "language": "python",
85 85 "metadata": {},
86 86 "outputs": [
87 87 {
88 88 "output_type": "stream",
89 89 "stream": "stdout",
90 90 "text": [
91 91 "The IPython notebook is great!\r\n"
92 92 ]
93 93 }
94 94 ],
95 95 "prompt_number": 3
96 96 },
97 97 {
98 98 "cell_type": "heading",
99 99 "level": 2,
100 100 "metadata": {},
101 101 "source": [
102 102 "Plots with matplotlib"
103 103 ]
104 104 },
105 105 {
106 106 "cell_type": "markdown",
107 107 "metadata": {},
108 108 "source": [
109 109 "IPython adds an 'inline' matplotlib backend,\n",
110 110 "which embeds any matplotlib figures into the notebook."
111 111 ]
112 112 },
113 113 {
114 114 "cell_type": "code",
115 115 "collapsed": false,
116 116 "input": [
117 117 "%pylab inline"
118 118 ],
119 119 "language": "python",
120 120 "metadata": {},
121 121 "outputs": [
122 122 {
123 123 "output_type": "stream",
124 124 "stream": "stdout",
125 125 "text": [
126 126 "\n",
127 127 "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
128 128 "For more information, type 'help(pylab)'.\n"
129 129 ]
130 130 }
131 131 ],
132 132 "prompt_number": 4
133 133 },
134 134 {
135 135 "cell_type": "code",
136 136 "collapsed": false,
137 137 "input": [
138 138 "x = linspace(0, 3*pi, 500)\n",
139 139 "plot(x, sin(x**2))\n",
140 140 "title('A simple chirp');"
141 141 ],
142 142 "language": "python",
143 143 "metadata": {},
144 144 "outputs": [
145 145 {
146 146 "output_type": "display_data",
147 147 "png": 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AvfZOHEif98nAzd7RrfRlITV8VlYWNmzYgCuvvBLJZBJ33XUX5s+fj40bNwIA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\nkL6BgYHBGML/B3suibfww4xPAAAAAElFTkSuQmCC\n"
148 148 }
149 149 ],
150 150 "prompt_number": 5
151 151 },
152 152 {
153 153 "cell_type": "markdown",
154 154 "metadata": {},
155 155 "source": [
156 156 "You can paste blocks of input with prompt markers, such as those from\n",
157 157 "[the official Python tutorial](http://docs.python.org/tutorial/interpreter.html#interactive-mode)"
158 158 ]
159 159 },
160 160 {
161 161 "cell_type": "code",
162 162 "collapsed": false,
163 163 "input": [
164 164 ">>> the_world_is_flat = 1\n",
165 165 ">>> if the_world_is_flat:\n",
166 166 "... print \"Be careful not to fall off!\""
167 167 ],
168 168 "language": "python",
169 169 "metadata": {},
170 170 "outputs": [
171 171 {
172 172 "output_type": "stream",
173 173 "stream": "stdout",
174 174 "text": [
175 175 "Be careful not to fall off!\n"
176 176 ]
177 177 }
178 178 ],
179 179 "prompt_number": 6
180 180 },
181 181 {
182 182 "cell_type": "markdown",
183 183 "metadata": {},
184 184 "source": [
185 185 "Errors are shown in informative ways:"
186 186 ]
187 187 },
188 188 {
189 189 "cell_type": "code",
190 190 "collapsed": false,
191 191 "input": [
192 192 "%run non_existent_file"
193 193 ],
194 194 "language": "python",
195 195 "metadata": {},
196 196 "outputs": [
197 197 {
198 198 "output_type": "stream",
199 199 "stream": "stderr",
200 200 "text": [
201 201 "ERROR: File `u'non_existent_file.py'` not found."
202 202 ]
203 203 }
204 204 ],
205 205 "prompt_number": 7
206 206 },
207 207 {
208 208 "cell_type": "code",
209 209 "collapsed": false,
210 210 "input": [
211 211 "x = 1\n",
212 212 "y = 4\n",
213 213 "z = y/(1-x)"
214 214 ],
215 215 "language": "python",
216 216 "metadata": {},
217 217 "outputs": [
218 218 {
219 219 "ename": "ZeroDivisionError",
220 220 "evalue": "integer division or modulo by zero",
221 221 "output_type": "pyerr",
222 222 "traceback": [
223 223 "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m Traceback (most recent call last)",
224 224 "\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",
225 225 "\u001b[1;31mZeroDivisionError\u001b[0m: integer division or modulo by zero"
226 226 ]
227 227 }
228 228 ],
229 229 "prompt_number": 8
230 230 },
231 231 {
232 232 "cell_type": "markdown",
233 233 "metadata": {},
234 234 "source": [
235 235 "When IPython needs to display additional information (such as providing details on an object via `x?`\n",
236 236 "it will automatically invoke a pager at the bottom of the screen:"
237 237 ]
238 238 },
239 239 {
240 240 "cell_type": "code",
241 241 "collapsed": false,
242 242 "input": [
243 243 "magic"
244 244 ],
245 245 "language": "python",
246 246 "metadata": {},
247 247 "outputs": [],
248 248 "prompt_number": 18
249 249 },
250 250 {
251 251 "cell_type": "markdown",
252 252 "metadata": {},
253 253 "source": [
254 254 "## Non-blocking output of kernel\n",
255 255 "\n",
256 256 "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 {
260 260 "cell_type": "code",
261 261 "collapsed": false,
262 262 "input": [
263 263 "import time, sys\n",
264 264 "for i in range(8):\n",
265 265 " print i,\n",
266 266 " time.sleep(0.5)"
267 267 ],
268 268 "language": "python",
269 269 "metadata": {},
270 270 "outputs": [
271 271 {
272 272 "output_type": "stream",
273 273 "stream": "stdout",
274 274 "text": [
275 275 "0 "
276 276 ]
277 277 },
278 278 {
279 279 "output_type": "stream",
280 280 "stream": "stdout",
281 281 "text": [
282 282 "1 "
283 283 ]
284 284 },
285 285 {
286 286 "output_type": "stream",
287 287 "stream": "stdout",
288 288 "text": [
289 289 "2 "
290 290 ]
291 291 },
292 292 {
293 293 "output_type": "stream",
294 294 "stream": "stdout",
295 295 "text": [
296 296 "3 "
297 297 ]
298 298 },
299 299 {
300 300 "output_type": "stream",
301 301 "stream": "stdout",
302 302 "text": [
303 303 "4 "
304 304 ]
305 305 },
306 306 {
307 307 "output_type": "stream",
308 308 "stream": "stdout",
309 309 "text": [
310 310 "5 "
311 311 ]
312 312 },
313 313 {
314 314 "output_type": "stream",
315 315 "stream": "stdout",
316 316 "text": [
317 317 "6 "
318 318 ]
319 319 },
320 320 {
321 321 "output_type": "stream",
322 322 "stream": "stdout",
323 323 "text": [
324 324 "7\n"
325 325 ]
326 326 }
327 327 ],
328 328 "prompt_number": 19
329 329 },
330 330 {
331 331 "cell_type": "markdown",
332 332 "metadata": {},
333 333 "source": [
334 334 "## Clean crash and restart\n",
335 335 "\n",
336 336 "We call the low-level system libc.time routine with the wrong argument via\n",
337 337 "ctypes to segfault the Python interpreter:"
338 338 ]
339 339 },
340 340 {
341 341 "cell_type": "code",
342 342 "collapsed": false,
343 343 "input": [
344 344 "import sys\n",
345 345 "from ctypes import CDLL\n",
346 346 "# This will crash a Linux or Mac system; equivalent calls can be made on Windows\n",
347 347 "dll = 'dylib' if sys.platform == 'darwin' else '.so.6'\n",
348 348 "libc = CDLL(\"libc.%s\" % dll) \n",
349 349 "libc.time(-1) # BOOM!!"
350 350 ],
351 351 "language": "python",
352 352 "metadata": {},
353 353 "outputs": [],
354 354 "prompt_number": "*"
355 355 },
356 356 {
357 357 "cell_type": "markdown",
358 358 "metadata": {},
359 359 "source": [
360 360 "## Markdown cells can contain formatted text and code\n",
361 361 "\n",
362 362 "You can *italicize*, **boldface**\n",
363 363 "\n",
364 364 "* build\n",
365 365 "* lists\n",
366 366 "\n",
367 367 "and embed code meant for illustration instead of execution in Python:\n",
368 368 "\n",
369 369 " def f(x):\n",
370 370 " \"\"\"a docstring\"\"\"\n",
371 371 " return x**2\n",
372 372 "\n",
373 373 "or other languages:\n",
374 374 "\n",
375 375 " if (i=0; i<n; i++) {\n",
376 376 " printf(\"hello %d\\n\", i);\n",
377 377 " x += 4;\n",
378 378 " }"
379 379 ]
380 380 },
381 381 {
382 382 "cell_type": "markdown",
383 383 "metadata": {},
384 384 "source": [
385 385 "Courtesy of MathJax, you can include mathematical expressions both inline: \n",
386 386 "$e^{i\\pi} + 1 = 0$ and displayed:\n",
387 387 "\n",
388 388 "$$e^x=\\sum_{i=0}^\\infty \\frac{1}{i!}x^i$$"
389 389 ]
390 390 },
391 391 {
392 392 "cell_type": "markdown",
393 393 "metadata": {},
394 394 "source": [
395 395 "## Rich displays: include anyting a browser can show\n",
396 396 "\n",
397 397 "Note that we have an actual protocol for this, see the `display_protocol` notebook for further details.\n",
398 398 "\n",
399 399 "### Images"
400 400 ]
401 401 },
402 402 {
403 403 "cell_type": "code",
404 404 "collapsed": false,
405 405 "input": [
406 406 "from IPython.display import Image\n",
407 407 "Image(filename='../../source/_static/logo.png')"
408 408 ],
409 409 "language": "python",
410 410 "metadata": {},
411 411 "outputs": [
412 412 {
413 413 "output_type": "pyout",
414 414 "png": 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415 415 "prompt_number": 1,
416 416 "text": [
417 417 "<IPython.core.display.Image at 0x10faeafd0>"
418 418 ]
419 419 }
420 420 ],
421 421 "prompt_number": 1
422 422 },
423 423 {
424 424 "cell_type": "markdown",
425 425 "metadata": {},
426 426 "source": [
427 427 "An image can also be displayed from raw data or a url"
428 428 ]
429 429 },
430 430 {
431 431 "cell_type": "code",
432 432 "collapsed": false,
433 433 "input": [
434 434 "Image(url='http://python.org/images/python-logo.gif')"
435 435 ],
436 436 "language": "python",
437 437 "metadata": {},
438 438 "outputs": [
439 439 {
440 440 "html": [
441 441 "<img src=\"http://python.org/images/python-logo.gif\" />"
442 442 ],
443 443 "output_type": "pyout",
444 444 "prompt_number": 2,
445 445 "text": [
446 446 "<IPython.core.display.Image at 0x1060e7410>"
447 447 ]
448 448 }
449 449 ],
450 450 "prompt_number": 2
451 451 },
452 452 {
453 453 "cell_type": "markdown",
454 454 "metadata": {},
455 455 "source": [
456 456 "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 {
460 460 "cell_type": "code",
461 461 "collapsed": false,
462 462 "input": [
463 463 "from IPython.display import SVG\n",
464 464 "SVG(filename='python-logo.svg')"
465 465 ],
466 466 "language": "python",
467 467 "metadata": {},
468 468 "outputs": [
469 469 {
470 470 "output_type": "pyout",
471 471 "prompt_number": 3,
472 472 "svg": [
473 473 "<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",
474 474 " <metadata id=\"metadata2193\">\n",
475 475 " <rdf:RDF>\n",
476 476 " <cc:Work rdf:about=\"\">\n",
477 477 " <dc:format>image/svg+xml</dc:format>\n",
478 478 " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
479 479 " </cc:Work>\n",
480 480 " </rdf:RDF>\n",
481 481 " </metadata>\n",
482 482 " <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",
483 483 " <defs id=\"defs4\">\n",
484 484 " <linearGradient id=\"linearGradient2795\">\n",
485 485 " <stop id=\"stop2797\" offset=\"0\" style=\"stop-color:#b8b8b8;stop-opacity:0.49803922\"/>\n",
486 486 " <stop id=\"stop2799\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
487 487 " </linearGradient>\n",
488 488 " <linearGradient id=\"linearGradient2787\">\n",
489 489 " <stop id=\"stop2789\" offset=\"0\" style=\"stop-color:#7f7f7f;stop-opacity:0.5\"/>\n",
490 490 " <stop id=\"stop2791\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
491 491 " </linearGradient>\n",
492 492 " <linearGradient id=\"linearGradient3676\">\n",
493 493 " <stop id=\"stop3678\" offset=\"0\" style=\"stop-color:#b2b2b2;stop-opacity:0.5\"/>\n",
494 494 " <stop id=\"stop3680\" offset=\"1\" style=\"stop-color:#b3b3b3;stop-opacity:0\"/>\n",
495 495 " </linearGradient>\n",
496 496 " <linearGradient id=\"linearGradient3236\">\n",
497 497 " <stop id=\"stop3244\" offset=\"0\" style=\"stop-color:#f4f4f4;stop-opacity:1\"/>\n",
498 498 " <stop id=\"stop3240\" offset=\"1\" style=\"stop-color:#ffffff;stop-opacity:1\"/>\n",
499 499 " </linearGradient>\n",
500 500 " <linearGradient id=\"linearGradient4671\">\n",
501 501 " <stop id=\"stop4673\" offset=\"0\" style=\"stop-color:#ffd43b;stop-opacity:1\"/>\n",
502 502 " <stop id=\"stop4675\" offset=\"1\" style=\"stop-color:#ffe873;stop-opacity:1\"/>\n",
503 503 " </linearGradient>\n",
504 504 " <linearGradient id=\"linearGradient4689\">\n",
505 505 " <stop id=\"stop4691\" offset=\"0\" style=\"stop-color:#5a9fd4;stop-opacity:1\"/>\n",
506 506 " <stop id=\"stop4693\" offset=\"1\" style=\"stop-color:#306998;stop-opacity:1\"/>\n",
507 507 " </linearGradient>\n",
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509 509 " <linearGradient gradientTransform=\"translate(100.2702,99.61116)\" gradientUnits=\"userSpaceOnUse\" id=\"linearGradient2990\" x1=\"172.94208\" x2=\"26.670298\" xlink:href=\"#linearGradient4689\" y1=\"77.475983\" y2=\"76.313133\"/>\n",
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513 513 " <linearGradient gradientTransform=\"translate(100.2702,99.61116)\" gradientUnits=\"userSpaceOnUse\" id=\"linearGradient2250\" x1=\"224.23996\" x2=\"-65.308502\" xlink:href=\"#linearGradient4671\" y1=\"144.75717\" y2=\"144.75717\"/>\n",
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534 534 ],
535 535 "text": [
536 536 "<IPython.core.display.SVG at 0x10fb998d0>"
537 537 ]
538 538 }
539 539 ],
540 540 "prompt_number": 3
541 541 },
542 542 {
543 543 "cell_type": "markdown",
544 544 "metadata": {},
545 545 "source": [
546 546 "#### Embedded vs Non-embedded Images"
547 547 ]
548 548 },
549 549 {
550 550 "cell_type": "markdown",
551 551 "metadata": {},
552 552 "source": [
553 553 "As of IPython 0.13, images are embedded by default for compatibility with QtConsole, and the ability to still be displayed offline.\n",
554 554 "\n",
555 555 "Let's look at the differences:"
556 556 ]
557 557 },
558 558 {
559 559 "cell_type": "code",
560 560 "collapsed": false,
561 561 "input": [
562 562 "# by default Image data are embedded\n",
563 563 "Embed = Image( 'http://scienceview.berkeley.edu/view/images/newview.jpg')\n",
564 564 "\n",
565 565 "# if kwarg `url` is given, the embedding is assumed to be false\n",
566 566 "SoftLinked = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg')\n",
567 567 "\n",
568 568 "# In each case, embed can be specified explicitly with the `embed` kwarg\n",
569 569 "# ForceEmbed = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg', embed=True)"
570 570 ],
571 571 "language": "python",
572 572 "metadata": {},
573 573 "outputs": [],
574 574 "prompt_number": 4
575 575 },
576 576 {
577 577 "cell_type": "markdown",
578 578 "metadata": {},
579 579 "source": [
580 580 "Today's image from a webcam at Berkeley, (at the time I created this notebook). This should also work in the Qtconsole.\n",
581 581 "Drawback is that the saved notebook will be larger, but the image will still be present offline."
582 582 ]
583 583 },
584 584 {
585 585 "cell_type": "code",
586 586 "collapsed": false,
587 587 "input": [
588 588 "Embed"
589 589 ],
590 590 "language": "python",
591 591 "metadata": {},
592 592 "outputs": [
593 593 {
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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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595 595 "output_type": "pyout",
596 596 "prompt_number": 5,
597 597 "text": [
598 598 "<IPython.core.display.Image at 0x10fb99b50>"
599 599 ]
600 600 }
601 601 ],
602 602 "prompt_number": 5
603 603 },
604 604 {
605 605 "cell_type": "markdown",
606 606 "metadata": {},
607 607 "source": [
608 608 "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",
609 609 "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 {
613 613 "cell_type": "code",
614 614 "collapsed": false,
615 615 "input": [
616 616 "SoftLinked"
617 617 ],
618 618 "language": "python",
619 619 "metadata": {},
620 620 "outputs": [
621 621 {
622 622 "html": [
623 623 "<img src=\"http://scienceview.berkeley.edu/view/images/newview.jpg\" />"
624 624 ],
625 625 "output_type": "pyout",
626 626 "prompt_number": 6,
627 627 "text": [
628 628 "<IPython.core.display.Image at 0x10fb99b10>"
629 629 ]
630 630 }
631 631 ],
632 632 "prompt_number": 6
633 633 },
634 634 {
635 635 "cell_type": "markdown",
636 636 "metadata": {},
637 637 "source": [
638 638 "Of course, if you re-run the all notebook, the two images will be the same again."
639 639 ]
640 640 },
641 641 {
642 642 "cell_type": "markdown",
643 643 "metadata": {},
644 644 "source": [
645 645 "### Video"
646 646 ]
647 647 },
648 648 {
649 649 "cell_type": "markdown",
650 650 "metadata": {},
651 651 "source": [
652 652 "And more exotic objects can also be displayed, as long as their representation supports \n",
653 653 "the IPython display protocol.\n",
654 654 "\n",
655 655 "For example, videos hosted externally on YouTube are easy to load (and writing a similar wrapper for other\n",
656 656 "hosted content is trivial):"
657 657 ]
658 658 },
659 659 {
660 660 "cell_type": "code",
661 661 "collapsed": false,
662 662 "input": [
663 663 "from IPython.display import YouTubeVideo\n",
664 664 "# a talk about IPython at Sage Days at U. Washington, Seattle.\n",
665 665 "# Video credit: William Stein.\n",
666 666 "YouTubeVideo('1j_HxD4iLn8')"
667 667 ],
668 668 "language": "python",
669 669 "metadata": {},
670 670 "outputs": [
671 671 {
672 672 "html": [
673 673 "\n",
674 674 " <iframe\n",
675 675 " width=\"400\"\n",
676 676 " height=\"300\"\n",
677 677 " src=\"http://www.youtube.com/embed/1j_HxD4iLn8\"\n",
678 678 " frameborder=\"0\"\n",
679 679 " allowfullscreen\n",
680 680 " ></iframe>\n",
681 681 " "
682 682 ],
683 683 "output_type": "pyout",
684 684 "prompt_number": 7,
685 685 "text": [
686 686 "<IPython.lib.display.YouTubeVideo at 0x10fba2190>"
687 687 ]
688 688 }
689 689 ],
690 690 "prompt_number": 7
691 691 },
692 692 {
693 693 "cell_type": "markdown",
694 694 "metadata": {},
695 695 "source": [
696 696 "Using the nascent video capabilities of modern browsers, you may also be able to display local\n",
697 697 "videos. At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n",
698 698 "we will continue testing this and looking for ways to make it more robust. \n",
699 699 "\n",
700 700 "The following cell loads a local file called `animation.m4v`, encodes the raw video as base64 for http\n",
701 701 "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control\n",
702 702 "bar at the bottom with a play/pause button and a location slider."
703 703 ]
704 704 },
705 705 {
706 706 "cell_type": "code",
707 707 "collapsed": false,
708 708 "input": [
709 709 "from IPython.display import HTML\n",
710 710 "video = open(\"animation.m4v\", \"rb\").read()\n",
711 711 "video_encoded = video.encode(\"base64\")\n",
712 712 "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n",
713 713 "HTML(data=video_tag)"
714 714 ],
715 715 "language": "python",
716 716 "metadata": {},
717 717 "outputs": [
718 718 {
719 719 "html": [
720 720 "<video controls alt=\"test\" src=\"data:video/x-m4v;base64,AAAAHGZ0eXBNNFYgAAACAGlzb21pc28yYXZjMQAAAAhmcmVlAAAqiW1kYXQAAAKMBgX//4jcRem9\n",
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929 929 "\">"
930 930 ],
931 931 "output_type": "pyout",
932 932 "prompt_number": 8,
933 933 "text": [
934 934 "<IPython.core.display.HTML at 0x10fba28d0>"
935 935 ]
936 936 }
937 937 ],
938 938 "prompt_number": 8
939 939 },
940 940 {
941 941 "cell_type": "markdown",
942 942 "metadata": {},
943 943 "source": [
944 944 "## Local Files\n",
945 945 "\n",
946 946 "The above examples embed images and video from the notebook filesystem in the output\n",
947 947 "areas of code cells. It is also possible to request these files directly in markdown cells\n",
948 948 "if they reside in the notebook directory via relative urls prefixed with `files/`:\n",
949 949 "\n",
950 950 " files/[subdirectory/]<filename>\n",
951 951 "\n",
952 952 "\n",
953 953 "For example, in the example notebook folder, we have the Python logo, addressed as:\n",
954 954 "\n",
955 955 " <img src=\"files/python-logo.svg\" />\n",
956 956 "\n",
957 957 "<img src=\"/files/python-logo.svg\" />\n",
958 958 "\n",
959 959 "and a video with the HTML5 video tag:\n",
960 960 "\n",
961 961 " <video controls src=\"files/animation.m4v\" />\n",
962 962 "\n",
963 963 "<video controls src=\"/files/animation.m4v\" />\n",
964 964 "\n",
965 965 "These do not embed the data into the notebook file,\n",
966 966 "and require that the files exist when you are viewing the notebook.\n",
967 967 "\n",
968 968 "### Security of local files\n",
969 969 "\n",
970 970 "Note that this means that the IPython notebook server also acts as a generic file server\n",
971 971 "for files inside the same tree as your notebooks. Access is not granted outside the\n",
972 972 "notebook folder so you have strict control over what files are visible, but for this\n",
973 973 "reason it is highly recommended that you do not run the notebook server with a notebook\n",
974 974 "directory at a high level in your filesystem (e.g. your home directory).\n",
975 975 "\n",
976 976 "When you run the notebook in a password-protected manner, local file access is restricted\n",
977 977 "to authenticated users unless read-only views are active."
978 978 ]
979 979 },
980 980 {
981 981 "cell_type": "markdown",
982 982 "metadata": {},
983 983 "source": [
984 984 "## Linking to files and directories for viewing in the browser\n",
985 985 "\n",
986 986 "It is also possible to link directly to files or directories so they can be opened in the browser. This is especially convenient if you're interacting with a tool within IPython that generates HTML pages, and you'd like to easily be able to open those in a new browser window. Alternatively, if your IPython notebook server is on a remote system, creating links provides an easy way to download any files that get generated.\n",
987 987 "\n",
988 988 "As we saw above, there are a bunch of `.ipynb` files in our current directory."
989 989 ]
990 990 },
991 991 {
992 992 "cell_type": "code",
993 993 "collapsed": false,
994 994 "input": [
995 995 "ls"
996 996 ],
997 997 "language": "python",
998 998 "metadata": {},
999 999 "outputs": [
1000 1000 {
1001 1001 "output_type": "stream",
1002 1002 "stream": "stdout",
1003 1003 "text": [
1004 1004 "00_notebook_tour.ipynb formatting.ipynb\r\n",
1005 1005 "01_notebook_introduction.ipynb octavemagic_extension.ipynb\r\n",
1006 1006 "Animations_and_Progress.ipynb publish_data.ipynb\r\n",
1007 1007 "Capturing Output.ipynb python-logo.svg\r\n",
1008 1008 "Script Magics.ipynb rmagic_extension.ipynb\r\n",
1009 1009 "animation.m4v sympy.ipynb\r\n",
1010 1010 "cython_extension.ipynb sympy_quantum_computing.ipynb\r\n",
1011 1011 "display_protocol.ipynb trapezoid_rule.ipynb\r\n"
1012 1012 ]
1013 1013 }
1014 1014 ],
1015 1015 "prompt_number": 1
1016 1016 },
1017 1017 {
1018 1018 "cell_type": "markdown",
1019 1019 "metadata": {},
1020 1020 "source": [
1021 1021 "If we want to create a link to one of them, we can call use the `FileLink` object."
1022 1022 ]
1023 1023 },
1024 1024 {
1025 1025 "cell_type": "code",
1026 1026 "collapsed": false,
1027 1027 "input": [
1028 1028 "from IPython.display import FileLink\n",
1029 1029 "FileLink('00_notebook_tour.ipynb')"
1030 1030 ],
1031 1031 "language": "python",
1032 1032 "metadata": {},
1033 1033 "outputs": [
1034 1034 {
1035 1035 "html": [
1036 1036 "<a href='files/00_notebook_tour.ipynb' target='_blank'>00_notebook_tour.ipynb</a><br>"
1037 1037 ],
1038 1038 "output_type": "pyout",
1039 1039 "prompt_number": 2,
1040 1040 "text": [
1041 1041 "<IPython.lib.display.FileLink at 0x10f7ea3d0>"
1042 1042 ]
1043 1043 }
1044 1044 ],
1045 1045 "prompt_number": 2
1046 1046 },
1047 1047 {
1048 1048 "cell_type": "markdown",
1049 1049 "metadata": {},
1050 1050 "source": [
1051 1051 "Alternatively, if we want to link to all of them, we can 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."
1052 1052 ]
1053 1053 },
1054 1054 {
1055 1055 "cell_type": "code",
1056 1056 "collapsed": false,
1057 1057 "input": [
1058 "from IPython.display import FileLink\n",
1058 "from IPython.display import FileLinks\n",
1059 1059 "FileLinks('.')"
1060 1060 ],
1061 1061 "language": "python",
1062 1062 "metadata": {},
1063 1063 "outputs": [
1064 1064 {
1065 1065 "html": [
1066 1066 "<a href='files/./00_notebook_tour.ipynb' target='_blank'>00_notebook_tour.ipynb</a><br>\n",
1067 1067 "<a href='files/./01_notebook_introduction.ipynb' target='_blank'>01_notebook_introduction.ipynb</a><br>\n",
1068 1068 "<a href='files/./animation.m4v' target='_blank'>animation.m4v</a><br>\n",
1069 1069 "<a href='files/./Animations_and_Progress.ipynb' target='_blank'>Animations_and_Progress.ipynb</a><br>\n",
1070 1070 "<a href='files/./Capturing Output.ipynb' target='_blank'>Capturing Output.ipynb</a><br>\n",
1071 1071 "<a href='files/./cython_extension.ipynb' target='_blank'>cython_extension.ipynb</a><br>\n",
1072 1072 "<a href='files/./display_protocol.ipynb' target='_blank'>display_protocol.ipynb</a><br>\n",
1073 1073 "<a href='files/./formatting.ipynb' target='_blank'>formatting.ipynb</a><br>\n",
1074 1074 "<a href='files/./octavemagic_extension.ipynb' target='_blank'>octavemagic_extension.ipynb</a><br>\n",
1075 1075 "<a href='files/./publish_data.ipynb' target='_blank'>publish_data.ipynb</a><br>\n",
1076 1076 "<a href='files/./python-logo.svg' target='_blank'>python-logo.svg</a><br>\n",
1077 1077 "<a href='files/./rmagic_extension.ipynb' target='_blank'>rmagic_extension.ipynb</a><br>\n",
1078 1078 "<a href='files/./Script Magics.ipynb' target='_blank'>Script Magics.ipynb</a><br>\n",
1079 1079 "<a href='files/./sympy.ipynb' target='_blank'>sympy.ipynb</a><br>\n",
1080 1080 "<a href='files/./sympy_quantum_computing.ipynb' target='_blank'>sympy_quantum_computing.ipynb</a><br>\n",
1081 1081 "<a href='files/./trapezoid_rule.ipynb' target='_blank'>trapezoid_rule.ipynb</a><br>"
1082 1082 ],
1083 1083 "output_type": "pyout",
1084 1084 "prompt_number": 7,
1085 1085 "text": [
1086 1086 "<IPython.lib.display.FileLinks at 0x10f7eaad0>"
1087 1087 ]
1088 1088 }
1089 1089 ],
1090 1090 "prompt_number": 7
1091 1091 },
1092 1092 {
1093 1093 "cell_type": "markdown",
1094 1094 "metadata": {},
1095 1095 "source": [
1096 1096 "### External sites\n",
1097 1097 "\n",
1098 1098 "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n",
1099 1099 "page for mobile users:"
1100 1100 ]
1101 1101 },
1102 1102 {
1103 1103 "cell_type": "code",
1104 1104 "collapsed": false,
1105 1105 "input": [
1106 1106 "HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>')"
1107 1107 ],
1108 1108 "language": "python",
1109 1109 "metadata": {},
1110 1110 "outputs": [
1111 1111 {
1112 1112 "html": [
1113 1113 "<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>"
1114 1114 ],
1115 1115 "output_type": "pyout",
1116 1116 "prompt_number": 9,
1117 1117 "text": [
1118 1118 "<IPython.core.display.HTML at 0x1094900d0>"
1119 1119 ]
1120 1120 }
1121 1121 ],
1122 1122 "prompt_number": 9
1123 1123 },
1124 1124 {
1125 1125 "cell_type": "markdown",
1126 1126 "metadata": {},
1127 1127 "source": [
1128 1128 "### Mathematics\n",
1129 1129 "\n",
1130 1130 "And we also support the display of mathematical expressions typeset in LaTeX, which is rendered\n",
1131 1131 "in the browser thanks to the [MathJax library](http://mathjax.org). \n",
1132 1132 "\n",
1133 1133 "Note that this is *different* from the above examples. Above we were typing mathematical expressions\n",
1134 1134 "in Markdown cells (along with normal text) and letting the browser render them; now we are displaying\n",
1135 1135 "the output of a Python computation as a LaTeX expression wrapped by the `Math()` object so the browser\n",
1136 1136 "renders it. The `Math` object will add the needed LaTeX delimiters (`$$`) if they are not provided:"
1137 1137 ]
1138 1138 },
1139 1139 {
1140 1140 "cell_type": "code",
1141 1141 "collapsed": false,
1142 1142 "input": [
1143 1143 "from IPython.display import Math\n",
1144 1144 "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')"
1145 1145 ],
1146 1146 "language": "python",
1147 1147 "metadata": {},
1148 1148 "outputs": [
1149 1149 {
1150 1150 "latex": [
1151 1151 "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$"
1152 1152 ],
1153 1153 "output_type": "pyout",
1154 1154 "prompt_number": 10,
1155 1155 "text": [
1156 1156 "<IPython.core.display.Math at 0x10fba26d0>"
1157 1157 ]
1158 1158 }
1159 1159 ],
1160 1160 "prompt_number": 10
1161 1161 },
1162 1162 {
1163 1163 "cell_type": "markdown",
1164 1164 "metadata": {},
1165 1165 "source": [
1166 1166 "With the `Latex` class, you have to include the delimiters yourself. This allows you to use other LaTeX modes such as `eqnarray`:"
1167 1167 ]
1168 1168 },
1169 1169 {
1170 1170 "cell_type": "code",
1171 1171 "collapsed": false,
1172 1172 "input": [
1173 1173 "from IPython.display import Latex\n",
1174 1174 "Latex(r\"\"\"\\begin{eqnarray}\n",
1175 1175 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
1176 1176 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
1177 1177 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
1178 1178 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
1179 1179 "\\end{eqnarray}\"\"\")"
1180 1180 ],
1181 1181 "language": "python",
1182 1182 "metadata": {},
1183 1183 "outputs": [
1184 1184 {
1185 1185 "latex": [
1186 1186 "\\begin{eqnarray}\n",
1187 1187 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
1188 1188 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
1189 1189 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
1190 1190 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
1191 1191 "\\end{eqnarray}"
1192 1192 ],
1193 1193 "output_type": "pyout",
1194 1194 "prompt_number": 11,
1195 1195 "text": [
1196 1196 "<IPython.core.display.Latex at 0x10fba2c10>"
1197 1197 ]
1198 1198 }
1199 1199 ],
1200 1200 "prompt_number": 11
1201 1201 },
1202 1202 {
1203 1203 "cell_type": "markdown",
1204 1204 "metadata": {},
1205 1205 "source": [
1206 1206 "Or you can enter latex directly with the `%%latex` cell magic:"
1207 1207 ]
1208 1208 },
1209 1209 {
1210 1210 "cell_type": "code",
1211 1211 "collapsed": false,
1212 1212 "input": [
1213 1213 "%%latex\n",
1214 1214 "\\begin{aligned}\n",
1215 1215 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
1216 1216 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
1217 1217 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
1218 1218 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
1219 1219 "\\end{aligned}"
1220 1220 ],
1221 1221 "language": "python",
1222 1222 "metadata": {},
1223 1223 "outputs": [
1224 1224 {
1225 1225 "latex": [
1226 1226 "\\begin{aligned}\n",
1227 1227 "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
1228 1228 "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
1229 1229 "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
1230 1230 "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
1231 1231 "\\end{aligned}"
1232 1232 ],
1233 1233 "output_type": "display_data",
1234 1234 "text": [
1235 1235 "<IPython.core.display.Latex at 0x10a617c90>"
1236 1236 ]
1237 1237 }
1238 1238 ],
1239 1239 "prompt_number": 12
1240 1240 },
1241 1241 {
1242 1242 "cell_type": "markdown",
1243 1243 "metadata": {},
1244 1244 "source": [
1245 1245 "There is also a `%%javascript` cell magic for running javascript directly,\n",
1246 1246 "and `%%svg` for manually entering SVG content."
1247 1247 ]
1248 1248 },
1249 1249 {
1250 1250 "cell_type": "markdown",
1251 1251 "metadata": {},
1252 1252 "source": [
1253 1253 "# Loading external codes\n",
1254 1254 "* Drag and drop a ``.py`` in the dashboard\n",
1255 1255 "* Use ``%load`` with any local or remote url: [the Matplotlib Gallery!](http://matplotlib.sourceforge.net/gallery.html)\n",
1256 1256 "\n",
1257 1257 "In this notebook we've kept the output saved so you can see the result, but you should run the next\n",
1258 1258 "cell yourself (with an active internet connection)."
1259 1259 ]
1260 1260 },
1261 1261 {
1262 1262 "cell_type": "markdown",
1263 1263 "metadata": {},
1264 1264 "source": [
1265 1265 "Let's make sure we have pylab again, in case we have restarted the kernel due to the crash demo above"
1266 1266 ]
1267 1267 },
1268 1268 {
1269 1269 "cell_type": "code",
1270 1270 "collapsed": false,
1271 1271 "input": [
1272 1272 "%pylab inline"
1273 1273 ],
1274 1274 "language": "python",
1275 1275 "metadata": {},
1276 1276 "outputs": [
1277 1277 {
1278 1278 "output_type": "stream",
1279 1279 "stream": "stdout",
1280 1280 "text": [
1281 1281 "\n",
1282 1282 "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
1283 1283 "For more information, type 'help(pylab)'.\n"
1284 1284 ]
1285 1285 }
1286 1286 ],
1287 1287 "prompt_number": 12
1288 1288 },
1289 1289 {
1290 1290 "cell_type": "code",
1291 1291 "collapsed": false,
1292 1292 "input": [
1293 1293 "%load http://matplotlib.sourceforge.net/mpl_examples/pylab_examples/integral_demo.py"
1294 1294 ],
1295 1295 "language": "python",
1296 1296 "metadata": {},
1297 1297 "outputs": [],
1298 1298 "prompt_number": 15
1299 1299 },
1300 1300 {
1301 1301 "cell_type": "code",
1302 1302 "collapsed": false,
1303 1303 "input": [
1304 1304 "#!/usr/bin/env python\n",
1305 1305 "\n",
1306 1306 "# implement the example graphs/integral from pyx\n",
1307 1307 "from pylab import *\n",
1308 1308 "from matplotlib.patches import Polygon\n",
1309 1309 "\n",
1310 1310 "def func(x):\n",
1311 1311 " return (x-3)*(x-5)*(x-7)+85\n",
1312 1312 "\n",
1313 1313 "ax = subplot(111)\n",
1314 1314 "\n",
1315 1315 "a, b = 2, 9 # integral area\n",
1316 1316 "x = arange(0, 10, 0.01)\n",
1317 1317 "y = func(x)\n",
1318 1318 "plot(x, y, linewidth=1)\n",
1319 1319 "\n",
1320 1320 "# make the shaded region\n",
1321 1321 "ix = arange(a, b, 0.01)\n",
1322 1322 "iy = func(ix)\n",
1323 1323 "verts = [(a,0)] + zip(ix,iy) + [(b,0)]\n",
1324 1324 "poly = Polygon(verts, facecolor='0.8', edgecolor='k')\n",
1325 1325 "ax.add_patch(poly)\n",
1326 1326 "\n",
1327 1327 "text(0.5 * (a + b), 30,\n",
1328 1328 " r\"$\\int_a^b f(x)\\mathrm{d}x$\", horizontalalignment='center',\n",
1329 1329 " fontsize=20)\n",
1330 1330 "\n",
1331 1331 "axis([0,10, 0, 180])\n",
1332 1332 "figtext(0.9, 0.05, 'x')\n",
1333 1333 "figtext(0.1, 0.9, 'y')\n",
1334 1334 "ax.set_xticks((a,b))\n",
1335 1335 "ax.set_xticklabels(('a','b'))\n",
1336 1336 "ax.set_yticks([])\n",
1337 1337 "show()\n"
1338 1338 ],
1339 1339 "language": "python",
1340 1340 "metadata": {},
1341 1341 "outputs": [
1342 1342 {
1343 1343 "output_type": "display_data",
1344 1344 "png": 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1345 1345 }
1346 1346 ],
1347 1347 "prompt_number": 16
1348 1348 }
1349 1349 ],
1350 1350 "metadata": {}
1351 1351 }
1352 1352 ]
1353 1353 } No newline at end of file
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