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f-akazawa/pythonscraping.ipynb

Created May 4, 2016 08:02
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pythonscraping.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
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},
"outputs": [
{
"name": "stdout",
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"text": [
"showing info https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/index.xml\n"
]
}
],
"source": [
"import nltk\n",
"nltk.download()\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"*** Introductory Examples for the NLTK Book ***\n",
"Loading text1, ..., text9 and sent1, ..., sent9\n",
"Type the name of the text or sentence to view it.\n",
"Type: 'texts()' or 'sents()' to list the materials.\n",
"text1: Moby Dick by Herman Melville 1851\n",
"text2: Sense and Sensibility by Jane Austen 1811\n",
"text3: The Book of Genesis\n",
"text4: Inaugural Address Corpus\n",
"text5: Chat Corpus\n",
"text6: Monty Python and the Holy Grail\n",
"text7: Wall Street Journal\n",
"text8: Personals Corpus\n",
"text9: The Man Who Was Thursday by G . K . Chesterton 1908\n"
]
}
],
"source": [
"from nltk.book import *"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"7.833333333333333"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(text6)/len(set(text6))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[(':', 1197),\n",
" ('.', 816),\n",
" ('!', 801),\n",
" (',', 731),\n",
" (\"'\", 421),\n",
" ('[', 319),\n",
" (']', 312),\n",
" ('the', 299),\n",
" ('I', 255),\n",
" ('ARTHUR', 225)]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from nltk import FreqDist\n",
"fdist = FreqDist(text6)\n",
"fdist.most_common(10)\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"18"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from nltk import bigrams\n",
"trigrams = bigrams(text6)\n",
"trigramDist = FreqDist(trigrams)\n",
"trigramDist[('Sir','Robin')]"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"<table class=\"outer\">\n",
" <!-- Basic Information -->\n",
" <tr>\n",
" <td class=\"head\">ID</td>\n",
" <td class=\"odd\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td width=\"30%\" class=\"head\">Language</td>\n",
" <td class=\"even\">English</td>\n",
" </tr>\n",
" <tr>\n",
" <td width=\"30%\" class=\"head\">Title</td>\n",
" <td class=\"odd\">2D Gabor Wavelet Transform and Inverse Transform (Reconstruction) Demo using Matlab</td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Free Keywords</td>\n",
" <td class=\"even\">Matlab, Gabor function, Wavelet, simple cells</td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Description</td>\n",
" <td class=\"odd\">## New: Compiled version for Mac OS X (that works without Matlab) is now available on this site from:<br /><a href=\"http://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=6951\" target=\"_blank\">http://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=6951</a> (345MB)<br /><br />## There is now a Japanese README file in the package.<br /><br />This Matlab script/application performs a 2D Gabor Wavelet Transform on an arbitrary image,<br />displays the resulting transform, and then performs the inverse transform<br />*slowly* and *sequentially* in animation, so that one can see how the original<br />image is synthesized back by summing many Gabor wavelets.</td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Last Modified Date</td>\n",
" <td class=\"even\">Nov 7, 2012 17:14:15</td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Created Date</td>\n",
" <td class=\"odd\">Oct 19, 2012 19:19:09</td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Contributor</td>\n",
" <td class=\"even\"><a href=\"https://visiome.neuroinf.jp/modules/xoonips/showusers.php?uid=183\" target=\"_self\">Izumi OHZAWA (ohzawa)</a></td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Item Type</td>\n",
" <td class=\"odd\">Model</td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Change Log(History)</td>\n",
" <td class=\"even\"><table>\n",
"<tr><td nowrap=\"nowrap\">Nov 7, 2012&nbsp;</td><td>Modified; Description.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Nov 7, 2012&nbsp;</td><td>Modified; Readme, Model file.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 31, 2012&nbsp;</td><td>Modified; Description, Readme, Model file.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 30, 2012&nbsp;</td><td>Modified; Description, Related to.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 30, 2012&nbsp;</td><td>Modified; Description.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 30, 2012&nbsp;</td><td>Modified; Description, Readme, Model file.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 26, 2012&nbsp;</td><td>Modified; インデックス.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 20, 2012&nbsp;</td><td>Modified; Preview, Model file.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 20, 2012&nbsp;</td><td>Modified; Related to.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 20, 2012&nbsp;</td><td>Modified; Description, Preview, Readme, Model file.</td></tr>\n",
"<tr><td nowrap=\"nowrap\">Oct 19, 2012&nbsp;</td><td>Modified; Description, Readme, Model file.</td></tr>\n",
"</table>\n",
"</td>\n",
" </tr>\n",
" \n",
" <!-- Model Item Detail Information -->\n",
" <tr>\n",
" <td class=\"head\">Model type</td>\n",
" <td class=\"odd\">Matlab</td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Creator</td>\n",
" <td class=\"even\">\n",
" <table>\n",
" <tr>\n",
" <td class='odd'>\n",
" Daisuke Kato\n",
" <input type='hidden' name='xnpmodel_creator[0][model_creator_id]' value='113'/>\n",
" <input type='hidden' name='xnpmodel_creator[0][creator]' value='Daisuke Kato'/>\n",
" <input type='hidden' name='xnpmodel_creator[0][creator_order]' value='0'/>\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td class='even'>\n",
" Izumi Ohzawa\n",
" <input type='hidden' name='xnpmodel_creator[1][model_creator_id]' value='114'/>\n",
" <input type='hidden' name='xnpmodel_creator[1][creator]' value='Izumi Ohzawa'/>\n",
" <input type='hidden' name='xnpmodel_creator[1][creator_order]' value='1'/>\n",
" </td>\n",
" </tr>\n",
" </table>\n",
"\n",
"\n",
"\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Preview</td>\n",
" <td class=\"odd\"><table>\n",
"<tr>\n",
"<td style=\"text-align: center; vertical-align: middle;\"><a href=\"https://visiome.neuroinf.jp/modules/xoonips/image.php?file_id=1605\" target=\"_blank\"><img src=\"https://visiome.neuroinf.jp/modules/xoonips/image.php?file_id=1605&amp;thumbnail=1\" alt=\"App window showing Gabor wavelet reconstruction with most significant 2000 wavelets\"/></a></td>\n",
"<td style=\"text-align: center; vertical-align: middle;\"><a href=\"https://visiome.neuroinf.jp/modules/xoonips/image.php?file_id=1608\" target=\"_blank\"><img src=\"https://visiome.neuroinf.jp/modules/xoonips/image.php?file_id=1608&amp;thumbnail=1\" alt=\"Gabor Wavelet Transform (coefficients) for Lena\"/></a></td>\n",
"<td style=\"text-align: center; vertical-align: middle;\"></td>\n",
"</tr>\n",
"<tr>\n",
"<td style=\"text-align: center; vertical-align: middle;\">App window showing Gabor wavelet reconstruction with most significant 2000 wavelets</td>\n",
"<td style=\"text-align: center; vertical-align: middle;\">Gabor Wavelet Transform (coefficients) for Lena</td>\n",
"<td style=\"text-align: center; vertical-align: middle;\"></td>\n",
"</tr>\n",
"</table>\n",
"</td>\n",
" </tr>\n",
"\n",
"\n",
"\n",
" <tr>\n",
" <td class=\"head\">Model file</td>\n",
" <td class=\"even\"><noscript><span style=\"color: red;\">To download this file, enable JavaScript in your browser.</span><br /></noscript>GaborWavelet.zip<br />\n",
" <table>\n",
" <tr>\n",
" <td>Type</td>\n",
" <td>: application/x-zip</td>\n",
" <td rowspan=\"4\" style=\"vertical-align: middle;\">\n",
" <a href=\"download.php?file_id=1713\" onfocus=\"xoonips_download_button_change('focus','1713')\" onblur=\"xoonips_download_button_change('blur','1713')\" onmousedown=\"xoonips_download_button_change('down','1713')\" onmouseup=\"xoonips_download_button_change('over','1713')\" onmouseover=\"xoonips_download_button_change('over','1713')\" onmouseout=\"xoonips_download_button_change('out','1713')\" onkeypress=\"xoonips_download_button_change('down','1713')\" onclick=\"return xoonips_download_button_click('1713');\"><img src=\"images/icon_button.php?label=download&amp;mode=normal\" alt=\"Download\" id=\"xoonips_download_button_1713\"/></a>\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td>Size</td>\n",
" <td>: 18.5 MB</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Last updated</td>\n",
" <td>: Nov 7, 2012</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Downloads</td>\n",
" <td>: 952</td>\n",
" </tr>\n",
" </table>\n",
" <br />\n",
" Total downloads since Oct 19, 2012 : 1141<br />\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Readme</td>\n",
" <td class=\"odd\"><textarea readonly=\"readonly\" rows=\"5\" cols=\"40\" style=\"width:320px;\">00_README.txt [v.1.06]\n",
"\n",
"2D Gabor Wavelet Transform and Inverse Transform (Reconstruction) Demo using Matlab\n",
"Matlab script:\n",
"http://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=6894\n",
"Mac OS X stand alone application:\n",
"http://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=6951\n",
"\n",
"Authors: Daisuke Kato and Izumi Ohzawa\n",
"Graduate School of Frontier Biosciences, Osaka University\n",
"kato@fbs.osaka-u.ac.jp, ohzawa@fbs.osaka-u.ac.jp\n",
"Copyright 2012 some rights reserved: Daisuke Kato and Izumi Ohzawa \n",
"License: http://creativecommons.org/licenses/by/3.0/\n",
"\n",
"Modification Dates: \n",
"v1.00: 2012-10-19 Daisuke Kato\n",
"v1.01: 2012-10-19 Izumi Ohzawa: (cosmetic changes and typo corrections)\n",
"v1.02: 2012-10-20 Izumi Ohzawa: (cosmetic changes and typo corrections)\n",
"v1.03: 2012-10-23 Daisuke Kato: (inverted checkmark logic, pyramid drawing order)\n",
"v1.04: 2012-10-30 Izumi Ohzawa: Matlab Compiler OS X (64bit) native executable\n",
"\t\t\t\tthat can run without Matlab environment.\n",
"\t\t\t\tHacked app wrapper by doing setenv in &quot;prelaunch&quot; to make it run.\n",
"v1.05: 2012-10-31 Izumi Ohzawa: Additional test images from the Kansai area\n",
"v1.06: 2012-11-06 Daisuke Kato: Button can now start and stop (toggle)\n",
"\n",
"------------------------------------------\n",
"\n",
"--------\n",
"Purpose:\n",
"--------\n",
"\n",
"This Matlab script/application performs a 2D Gabor Wavelet Transform on an arbitrary image,\n",
"displays the resulting transform, and then performs the inverse transform\n",
"*slowly* and *sequentially* in animation, so that one can see how the original\n",
"image is reconstructed by summing many Gabor wavelets.\n",
"\n",
"This app has been developed for demonstrating intuitively how a\n",
"population of V1 simple cells represent arbitrary images, essentially\n",
"via a 2-D Gabor wavelet transform.\n",
"Simple cells have often been described casually as &quot;detecting edges and lines&quot;\n",
"in images, but that is not a modern view of what these cells do.\n",
"However, simply talking about Gabor functions and wavelet transforms\n",
"may not work well for many beginning students and general audience.\n",
"We hope that this application solves that problem by visually intuitive demonstrations.\n",
"We appreciate any feedback and suggestions for improvements. \n",
"\n",
"---------------------------------------------------------------------\n",
"How to Install and Use GaborWavelet.app (For Mac OSX without Matlab):\n",
"---------------------------------------------------------------------\n",
"[1m] Install Matlab Compiler Runtime (MCR), unless you have already done it before.\n",
" Run MCRInstaller/InstallForMacOSX.app\n",
" That is, go to folder &quot;MCRInstaller&quot;, and double-click on &quot;InstallForMacOSX.app&quot;\n",
" *Use the suggested install directory etc. Do not specify other custom locations.\n",
"\n",
"[2m] Copy (by drag-and-drop) the &quot;GaborWavelet.app&quot; into the /Applications folder on your Mac.\n",
" *Do so while holding down the &quot;Option&quot; key, if you wish to leave the original in the\n",
" original folder.\n",
" \n",
"[3m] Double click on GaborWavelet.app icon.\n",
"\n",
"[4m] Go to [2] below, wash and repeat.\n",
"\n",
"\n",
"------------------------------------------------------\n",
"How to Use the Matlab Script (For those with Matlab):\n",
"------------------------------------------------------\n",
"[1] Run &quot;GaborWaveletRepresentation.m&quot;\n",
"\n",
"[2] Select one of the images in the directory &quot;test image&quot;\n",
"Analysis is performed using 7 scales and 8 orientations.\n",
"\n",
"[3] Press &quot;show pyramid&quot; button to see the wavelet pyramid for the image.\n",
"A separate window will open.\n",
"The resulting Gabor wavelet coefficients for 6 scales are displayed \n",
"(the smallest scale is not shown for performance reasons), one square area for each scale.\n",
"The saturation (degree of red coloring) of each pair of triangular elements indicates\n",
"the amplitude of each wavelet (phase is not shown).\n",
"The orientation of a pair of wedge-shaped elements depicts the orientation of the wavelet.\n",
"\n",
"With the &quot;normalize each scale&quot; check box ON, the amplitude of the pyramid display\n",
"is normalized for each scale.\n",
"With &quot;normalize each scale&quot; OFF, the amplitudes are normalized to a single max across all scales. This check box state affects only the wavelet pyramid display. It has no effect on the reconstruction.\n",
"\n",
"[4] Press &quot;add N wavelets&quot; button (after optionally changing the N value).\n",
"The wavelets are added to the &quot;Sum of Gabors&quot; area, one by one, to\n",
"sequentially reconstruct the original image in the order of coefficient value\n",
"(more significant ones first).\n",
"## Please note that, as of v1.06, the buttun can now stop the animated addition.\n",
"\n",
"Using the &quot;fast-slow&quot; slider below the &quot;Original Image&quot;, you may slow down the\n",
"reconstruction process to examine individual wavelets and changes in the sum image\n",
"contributed by each wavelet, especially during the initial part of the process.\n",
"\n",
"The middle view, &quot;Wavelet Added&quot;, shows the most recent wavelet added (at full contrast).\n",
"The actual wavelet added is much fainter in contrast (to the extent that they\n",
"are invisible after the initial part of the process).\n",
"\n",
"While the automatic addition of wavelets is in progress, the polar plot\n",
"&quot;Scale &amp; Orientation&quot; indicates the spatial frequency and orientation of the\n",
"most recent wavelet added. The position is obvious in the &quot;Wavelet Added&quot; panel.\n",
"\n",
"After some wavelets have been added, clicking within the &quot;Scale &amp; Orientation&quot;\n",
"plot allows you to see the locations where that particular spatial frequency\n",
"component has been added.\n",
"\n",
"[5] Use the &quot;reset&quot; button to reset the reconstruction for the current image, or\n",
"Use &quot;load&quot; button to load a different image (by going back to step [2]).\n",
"\n",
"[6] You may load an arbitrary image (of reasonable size) in formats that Matlab supports.\n",
"\n",
"---------------------------------------------------------------------\n",
"Additional (optional) demo of oriented spatial frequency filtering\n",
"\n",
"[0a] Follow [1] and [2] as above.\n",
"\n",
"[1a] Click a point within the polar &quot;Scale &amp; Orientation&quot; to select a\n",
"wavelet of a particular orientation and spatial frequency.\n",
"\n",
"[2a] Click the &quot;select all&quot; button below the &quot;Position Select&quot; panel.\n",
"\n",
"[3a] The image shown in &quot;Sum of Gabors&quot; represents the result of \n",
"oriented spatial frequency filtering.\n",
"(Essentially what you might see if your V1 is made up of just one type of\n",
"simple cells with the orientation and spatial frquency tuning you specified in [1a].)\n",
"(E.g., see image: appimages/OrientedSF-Filtering.png)\n",
"\n",
"[4a] Press the &quot;reset&quot; button to try a different wavelet. Go to [1a].\n",
"\n",
"Enjoy!\n",
"\n",
"-----------------------------------------------------------------------\n",
"Some technical details (may be modified in code, if you know what you are doing):\n",
"Scales are in 1-octave steps, 7 scales. (It is actually not exactly the case. Will fix..)\n",
"Spatial frequency tuning bandwidth (full width@half height): 1.5 octaves\n",
"8 orientations.\n",
"Wavelet coefficients are normalized by L2-Norm, by the energy of wavelets.\n",
"Gabor functions are tiled with 1.5 sigma separations between centers of neighboring Gabors.\n",
"\n",
"---------------------------------------------\n",
"Sample Image Copyrights and Acknowledgements:\n",
"---------------------------------------------\n",
"\n",
"original image/statue1.png:\n",
"test image/Statue.tiff:\n",
"\n",
"Reprinted by permission from Macmillan Publishers Ltd: Nature\n",
"Isamu Motoyoshi , Shin&#039;ya Nishida , Lavanya Sharan and Edward H.\n",
"Adelson, Image statistics and the perception of surface qualities,\n",
"Nature, 447(7141): 206-209, copyright 2007\n",
"--\n",
"\n",
"Bark, Boat, Bridge, Brodatrz, elaine, lena_std, mandrill, Peppers\n",
"are from The USC-SIPI Image Database:\n",
"http://sipi.usc.edu/database/database.php\n",
"\n",
"Bark.tiff\n",
"http://sipi.usc.edu/database/download.php?vol=textures&amp;img=1.1.02\n",
"Bridge.tiff\n",
"http://sipi.usc.edu/database/download.php?vol=misc&amp;img=5.2.10\n",
"lena_std.tiff\n",
"http://www.cs.cmu.edu/~chuck/lennapg/lena_std.tif\n",
"mandrill.tiff\n",
"http://sipi.usc.edu/database/download.php?vol=misc&amp;img=4.2.03\n",
"Boat.tiff\n",
"http://sipi.usc.edu/database/download.php?vol=misc&amp;img=boat.512\n",
"Brodatz.tiff -&gt; cloth.tiff\n",
"http://sipi.usc.edu/database/download.php?vol=textures&amp;img=1.3.05\n",
"Peppers.tiff\n",
"http://sipi.usc.edu/database/download.php?vol=misc&amp;img=4.2.07\n",
"elaine.tiff\n",
"http://sipi.usc.edu/database/download.php?vol=misc&amp;img=elaine.512\n",
"\n",
"All other images listed below were taken or generated by Ohzawa Lab members:\n",
"sin.tiff\n",
"ChezP.png\n",
"Kinkakuji.png\n",
"KiyomizuDera.png\n",
"TaiyounoTou.png\n",
"Thai.png\n",
"\n",
"------------------------------------------\n",
"\n",
"-----------\n",
"References:\n",
"-----------\n",
"\n",
"[1] Tai Sing Lee, Image representation using 2D Gabor wavelets.\n",
"IEEE Trans. on Pattern Analysis and Machine Intelligence, 18(10): 959-971, 1996.\n",
"\n",
"[2] Kendrick N. Kay, Thomas Naselaris, Ryan J. Prenger, Jack L. Gallant,\n",
"Identifying natural images from human brain activity. Nature, 452(7185): 352-355, 2008.\n",
"(esp. supplementary material)\n",
"\n",
"[3] Visiome Platform: Visiome Platform is a web-based database system with a variety of digital research resources in Vision Science. http://visiome.neuroinf.jp\n",
"\n",
"---\n",
"end</textarea></td>\n",
" </tr>\n",
" <tr>\n",
" <td class=\"head\">Rights</td>\n",
" <td class=\"even\"><!-- Creative Commons License -->\n",
"<table>\n",
" <tr>\n",
" <td><a rel=\"license\" href=\"http://creativecommons.org/licenses/by/2.5/\" target=\"_blank\"><img alt=\"Creative Commons License\" border=\"0\" src=\"http://creativecommons.org/images/public/somerights20.png\" /></a><br /></td>\n",
" <td>This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by/2.5/\" target=\"_blank\">Creative Commons Attribution 2.5 License</a></td>\n",
" </tr>\n",
"</table>\n",
"<!-- /Creative Commons License -->\n",
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" <requires rdf:resource=\"http://creativecommons.org/ns#Notice\" />\n",
"</License>\n",
"</rdf:RDF>\n",
"--></td>\n",
" </tr>\n",
" <!-- index -->\n",
" <tr>\n",
" <td class=\"head\">Index</td>\n",
" <td class=\"odd\"><table>\n",
"<tr class=\"odd\"><td style=\"vertical-align: middle;\"><a href=\"listitem.php?index_id=326\">/ Public / Visiome 2004 / Visual System / Visual Pathway / V1/Area 17/Striate Cortex / Cell Type / Simple Cell</a><br /><a href=\"listitem.php?index_id=5902\">/ Public / Model</a><br /><a href=\"listitem.php?index_id=5973\">/ Public / Demonstration</a><br /></td><td style=\"vertical-align: middle; text-align: left;\"></td></tr>\n",
"</table>\n",
"</td>\n",
" </tr>\n",
" <!-- related_to -->\n",
" <tr>\n",
" <td class=\"head\">Related to</td>\n",
" <td class=\"even\"><!-- begin of xoonips_detail_related_to.html -->\n",
"<table width=\"100%\" border=\"0\" cellspacing=\"5\">\n",
" <tr style='vertical-align:middle; text-align:center;'>\n",
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" <td width=\"65\" style=\"vertical-align:middle; text-align:center;\">\n",
" <img src=\"https://visiome.neuroinf.jp/modules/xnpmodel/images/icon_model.gif\" alt=\"icon_model\"/>\n",
" </td>\n",
" <td style=\"vertical-align:middle;\">\n",
" <a href=\"https://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=6106\">Two-dimensional spatial frequency filtering by FFT using Matlab&nbsp;</a><br />\n",
" Kota S. Sasaki\n",
" . Izumi Ohzawa\n",
" </td>\n",
"\n",
" <td width=\"65\" style=\"vertical-align:middle; text-align:center;\">\n",
"<a target=\"_blank\" href=\"https://sim.neuroinf.jp/modules/xoonips/detail.php?item_id=56\"><img src=\"https://sim.neuroinf.jp/images/button.png\" title=\"Online Simulation\" alt=\"[BUTTON]\" height=\"35\" /></a> </td>\n",
"\n",
" </tr>\n",
"</table>\n",
" </td>\n",
" </tr>\n",
" <tr valign=\"top\">\n",
" <td class=\"even\">\n",
" <table>\n",
" <tr>\n",
" <td width=\"65\" style=\"vertical-align:middle; text-align:center;\">\n",
" <img src=\"https://visiome.neuroinf.jp/modules/xnptool/images/icon_tool.gif\" alt=\"icon_tool\"/>\n",
" </td>\n",
" <td>\n",
" <a href=\"https://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=6448\">Two-Dimensional Fourier Image Reconstruction (Inverse FT) Demo using Matlab&nbsp;</a><br />\n",
" Matlab<br />\n",
" </td>\n",
" <td width=\"65\">\n",
" </td>\n",
" </tr>\n",
"</table>\n",
" </td>\n",
" </tr>\n",
" <tr valign=\"top\">\n",
" <td class=\"odd\">\n",
" <table>\n",
" <tr>\n",
" <td width=\"65\" style=\"vertical-align:middle; text-align:center;\">\n",
" <img src=\"https://visiome.neuroinf.jp/modules/xnpmodel/images/icon_model.gif\" alt=\"icon_model\"/>\n",
" </td>\n",
" <td style=\"vertical-align:middle;\">\n",
" <a href=\"https://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=6951\">Mac OSX: 2D Gabor Wavelet Transform and Inverse Transform (Reconstruction) Demo&nbsp;</a><br />\n",
" Daisuke Kato\n",
" . Izumi Ohzawa\n",
" </td>\n",
"\n",
" <td width=\"65\" style=\"vertical-align:middle; text-align:center;\">\n",
" </td>\n",
"\n",
" </tr>\n",
"</table>\n",
" </td>\n",
" </tr>\n",
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" <div class='xoonips_download_box'>\n",
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" <td>This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by/2.5/\" target=\"_blank\">Creative Commons Attribution 2.5 License</a></td>\n",
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" <div class='xoonips_download_box'>\n",
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"\t\t\t\t\t\t</td>\n",
"\t\t\t\t\t</tr>\n",
"\t\t\t\t\t<tr>\n",
"\t\t\t\t\t <td align=\"left\" class=\"footer\">\n",
"\t\t\t\t\t \tCopyright (cc) 2005-2011 RIKEN BSI Neuroinformatics Japan Center. Some rights reserved.\n",
"\t\t\t\t\t</td>\n",
"\t\t\t\t\t<td align=\"right\">\n",
"\t\t\t\t\t</td>\n",
"\t\t\t\t</tr>\n",
"\t\t\t </table>\n",
"\t\t\t</div>\n",
"\t\t</td>\n",
"\t\t\t</tr>\n",
"</table>\n",
"<!-- Content area end -->\n",
"\n",
"</body>\n",
"</html>\n"
]
}
],
"source": [
"import requests\n",
"'''\n",
"visiomeログインクローラ初版\n",
"'''\n",
"params = {'uname':'akazawa','pass':'akazawa','op':'login','xoops_redirect':'/'}\n",
"r = requests.post(\n",
" 'https://visiome.neuroinf.jp/modules/xoonips/user.php',\n",
" timeout=3.0,\n",
" data=params)\n",
"# print(r.text) リダイレクトフォーム\n",
"print(\"Cookie is set to:\")\n",
"print(r.cookies.get_dict())\n",
"print(\"---------\")\n",
"print(\"Going to main page\")\n",
"r = requests.get('https://visiome.neuroinf.jp/', cookies=r.cookies)\n",
"#print(r.text)\n",
"r = requests.get('https://visiome.neuroinf.jp/modules/xoonips/detail.php?item_id=6894',cookies=r.cookies)\n",
"print(r.text)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[]"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"r.url\n",
"r.history"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.1"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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