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| michaelneuder/she | web_app/she_app/lib/tasks/doc/method_list.html | HTML | apache-2.0 | 1,321 |
<!DOCTYPE html>
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<header>Fitxer de registre KDC</header>
El fitxer de registre KDC.
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| byronka/xenos | utils/ant/apache-ant-1.9.4/manual/api/org/apache/tools/ant/taskdefs/optional/unix/package-frame.html | HTML | mit | 1,368 |
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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
<!-- NewPage -->
<html lang="en">
<head>
<!-- Generated by javadoc (version 1.6.0_32) on Wed Oct 01 12:52:02 MSK 2014 -->
<title>CvType</title>
<meta name="date" content="2014-10-01">
<link rel="stylesheet" type="text/css" href="../../../stylesheet.css" title="Style">
</head>
<body>
<script type="text/javascript"><!--
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parent.document.title="CvType";
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<!-- ========= START OF TOP NAVBAR ======= -->
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</ul>
<div class="aboutLanguage"><em>OpenCV 2.4.10</em></div>
</div>
<div class="subNav">
<ul class="navList">
<li><a href="../../../org/opencv/core/CvException.html" title="class in org.opencv.core"><span class="strong">PREV CLASS</span></a></li>
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<li><a href="#method_summary">METHOD</a></li>
</ul>
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<li>DETAIL: </li>
<li><a href="#field_detail">FIELD</a> | </li>
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<!-- ========= END OF TOP NAVBAR ========= -->
<!-- ======== START OF CLASS DATA ======== -->
<div class="header">
<p class="subTitle">org.opencv.core</p>
<h2 title="Class CvType" class="title">Class CvType</h2>
</div>
<div class="contentContainer">
<ul class="inheritance">
<li>java.lang.Object</li>
<li>
<ul class="inheritance">
<li>org.opencv.core.CvType</li>
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<pre>public final class <strong>CvType</strong>
extends java.lang.Object</pre>
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<tr>
<th class="colFirst" scope="col">Modifier and Type</th>
<th class="colLast" scope="col">Field and Description</th>
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<tr class="altColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_16S">CV_16S</a></strong></code> </td>
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<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_16SC1">CV_16SC1</a></strong></code> </td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_16SC2">CV_16SC2</a></strong></code> </td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_16SC3">CV_16SC3</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_16SC4">CV_16SC4</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_32FC4">CV_32FC4</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_32S">CV_32S</a></strong></code> </td>
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<tr class="altColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_32SC1">CV_32SC1</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_32SC2">CV_32SC2</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_32SC3">CV_32SC3</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_32SC4">CV_32SC4</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_64F">CV_64F</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_64FC1">CV_64FC1</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_64FC2">CV_64FC2</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_64FC3">CV_64FC3</a></strong></code> </td>
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<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_64FC4">CV_64FC4</a></strong></code> </td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8S">CV_8S</a></strong></code> </td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8SC1">CV_8SC1</a></strong></code> </td>
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<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8SC2">CV_8SC2</a></strong></code> </td>
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<tr class="altColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8SC3">CV_8SC3</a></strong></code> </td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8SC4">CV_8SC4</a></strong></code> </td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8U">CV_8U</a></strong></code> </td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8UC1">CV_8UC1</a></strong></code> </td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8UC2">CV_8UC2</a></strong></code> </td>
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<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8UC3">CV_8UC3</a></strong></code> </td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_8UC4">CV_8UC4</a></strong></code> </td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_USRTYPE1">CV_USRTYPE1</a></strong></code> </td>
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<th class="colOne" scope="col">Constructor and Description</th>
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<tr>
<th class="colFirst" scope="col">Modifier and Type</th>
<th class="colLast" scope="col">Method and Description</th>
</tr>
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<td class="colFirst"><code>static int</code></td>
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<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#CV_16SC(int)">CV_16SC</a></strong>(int ch)</code> </td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<td class="colFirst"><code>static int</code></td>
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<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
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int channels)</code> </td>
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<tr class="altColor">
<td class="colFirst"><code>static java.lang.String</code></td>
<td class="colLast"><code><strong><a href="../../../org/opencv/core/CvType.html#typeToString(int)">typeToString</a></strong>(int type)</code> </td>
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<pre>public static final int CV_16S</pre>
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<a name="CvType()">
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</div>
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</div>
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<li><a href="../../../index.html?org/opencv/core/CvType.html" target="_top">FRAMES</a></li>
<li><a href="CvType.html" target="_top">NO FRAMES</a></li>
</ul>
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<li><a href="#method_summary">METHOD</a></li>
</ul>
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<li>DETAIL: </li>
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<li><a href="#constructor_detail">CONSTR</a> | </li>
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| nfscan/cordova-plugin-tesseract-camera | src/android/libs/OpenCV-2.4.10-android-sdk/sdk/java/javadoc/org/opencv/core/CvType.html | HTML | mit | 28,118 |
<html><body>
<!-- 将上传结果序列化为JSON串后填入result中即可 -->
<script>
window.result = '{"url":"http://192.168.146.84:1122/xhr/3.jpg"}';
</script>
<script>
var _result = 'NEJ-UPLOAD-RESULT:{"key":"'+window.name+'","result":"'+encodeURIComponent(result)+'"}';
if (window.postMessage){
parent.postMessage(_result,'*');
}else{
_result = '"'+_result.replace(/"/g,'\\"')+'"';
parent.name = escape('MSG|data='+encodeURIComponent(_result));
}
</script>
</body></html> | JuneAndGreen/jtr | test/demo/webapp/src/javascript/lib/nej/res/src/nej_proxy_upload.html | HTML | mit | 523 |
<!--
JBoss, Home of Professional Open Source
Copyright 2013, Red Hat, Inc. and/or its affiliates, and individual
contributors by the @authors tag. See the copyright.txt in the
distribution for a full listing of individual contributors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
-->
<!DOCTYPE html>
<html lang="en" ng-app="kitchensink">
<head>
<title>kitchensink</title>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<link rel="stylesheet" href="css/screen.css" type="text/css" />
<!-- Load angularjs -->
<script src="js/libs/angular.js"></script>
<!-- Load angularjs-resource, which allows us to interact with REST resources as high level services -->
<script src="js/libs/angular-resource.js"></script>
<!-- Load the controllers for our app -->
<script src="js/controllers.js"></script>
<!-- Load the application wide JS, such as route definitions -->
<script src="js/app.js"></script>
<!-- Load the services we have defined for the application, particularly the REST services -->
<script src="js/services.js"></script>
</head>
<body>
<aside id="container">
<div class="dualbrand">
<img src="gfx/dualbrand_logo.png" />
</div>
<div id="content" ng-view>
<!-- This div will be tempalted by AngularJS -->
[Template content will be inserted here]
</div>
<div id="aside">
<p>Learn more about JBoss WildFly.</p>
<ul>
<li><a
href="https://github.com/wildfly/quickstart/blob/master/guide/Introduction.asciidoc">Getting
Started Developing Applications Guide</a></li>
<li><a href="http://www.wildfly.org/">Community
Project Information</a></li>
</ul>
</div>
<footer id="footer">
<p>
This project was generated from a Maven archetype from
WildFly.<br />
</p>
</footer>
</aside>
</body>
</html>
| jgisler/quickstart | kitchensink-angularjs/src/main/webapp/index.html | HTML | apache-2.0 | 2,594 |
<div class="row">
<a href="{{ pluginName }}/users/{{ entry.who }}">{{ entry.who }}</a>
<span apiman-i18n-key="audit.updated-org">updated organization</span>
<a class="emphasis" href="{{ pluginName }}/orgs/{{ entry.organizationId }}/plans">{{ entry.organizationId }}</a><span apiman-i18n-skip>.</span>
</div>
<div class="row boxed-row">
<div ng-repeat="item in data.changes">
<div>
<span class="capitalized emphasis">{{ item.name }}</span>
</div>
<div class="activity-value">
<span>{{ item.after }}</span>
</div>
</div>
</div>
| cmoulliard/apiman | manager/ui/war/plugins/api-manager/html/directives/audit/Organization/auditUpdate.html | HTML | apache-2.0 | 564 |
<!DOCTYPE html>
<style>
section {
width: 10ch;
}
.justify {
text-align: justify;
}
</style>
<body>
<section class="justify">
<div>1234 5678 9012</div>
<div>1234 5678 9012</div>
<div>1234 5678 9012</div>
</section>
</body>
| chromium/chromium | third_party/blink/web_tests/external/wpt/css/CSS2/normal-flow/block-in-inline-align-justify-001-ref.html | HTML | bsd-3-clause | 242 |
<!DOCTYPE html>
<meta charset=utf-8>
<title>Reference: text-transform with SVG text</title>
<p>Test passes if the greeting below is in <b>ALL-UPPERCASE</b>:</p>
<svg><text y="50">HELLO, WORLD!</text></svg>
| scheib/chromium | third_party/blink/web_tests/external/wpt/svg/text/reftests/text-transform-001-ref.html | HTML | bsd-3-clause | 208 |
<!doctype html>
<title>Container Relative Units: qi, qb, etc</title>
<link rel="help" href="https://drafts.csswg.org/css-contain-3/#container-lengths">
<script src="/resources/testharness.js"></script>
<script src="/resources/testharnessreport.js"></script>
<script src="support/cq-testcommon.js"></script>
<style>
.inline { container-type: inline-size; }
.size { container-type: size; }
.inline.outer { width: 500px; }
.size.outer { height: 400px; }
.inline.inner { width: 300px; }
</style>
<div id=ref></div>
<div class="inline outer">
<div class="size outer">
<div class="inline inner">
<div id=child>Test</div>
</div>
</div>
</div>
<script>
setup(() => assert_implements_container_queries());
function assert_unit_equals(element, actual, expected) {
try {
element.style.padding = actual;
ref.style.padding = expected;
assert_equals(getComputedStyle(element).paddingLeft,
getComputedStyle(ref).paddingLeft);
} finally {
element.style = '';
ref.style = '';
}
}
test(function() {
assert_unit_equals(child, '0qi', '0px');
assert_unit_equals(child, '1qi', '3px');
assert_unit_equals(child, '10qi', '30px');
assert_unit_equals(child, '10qw', '30px');
assert_unit_equals(child, '10qb', '40px');
assert_unit_equals(child, '10qh', '40px');
assert_unit_equals(child, '10qmin', '30px');
assert_unit_equals(child, '10qmax', '40px');
}, 'Container relative units');
test(function() {
assert_unit_equals(child, '10qi', '30px');
assert_unit_equals(child, '10qb', '40px');
assert_unit_equals(child, 'calc(10qi + 10qb)', '70px');
assert_unit_equals(child, 'max(10qi, 10qb)', '40px');
}, 'Container relative units in math functions');
</script>
| chromium/chromium | third_party/blink/web_tests/external/wpt/css/css-contain/container-queries/container-units-basic.html | HTML | bsd-3-clause | 1,786 |
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Example - example-example115-production</title>
<script src="//ajax.googleapis.com/ajax/libs/angularjs/1.5.3/angular.min.js"></script>
<script src="//ajax.googleapis.com/ajax/libs/angularjs/1.5.3/angular-touch.js"></script>
<script src="script.js"></script>
</head>
<body ng-app="ngClickExample">
<button ng-click="count = count + 1" ng-init="count=0">
Increment
</button>
count: {{ count }}
</body>
</html> | zhiqiuyao/travel | public/vendor/angular/docs/examples/example-example115/index-production.html | HTML | mit | 502 |
<!DOCTYPE html>
<script src="../../resources/testharness.js"></script>
<script src="../../resources/testharnessreport.js"></script>
<script src="../../shadow-dom/resources/shadow-dom.js"></script>
<div id="host1">
<template data-mode="open">
<slot name="slot1"></slot>
</template>
<span slot="slot1" id="span1"></span>
<span slot="slot1" id="span2"></span>
</div>
<script>
convertTemplatesToShadowRootsWithin(host1);
document.body.offsetLeft;
test(() => {
assert_equals(document.querySelector('::slotted(span)'), null);
assert_equals(host1.shadowRoot.querySelector('::slotted(span)'), null);
}, "querySelector for ::slotted pseudo element");
test(() => {
assert_equals(document.querySelectorAll('::slotted(span)').length, 0);
assert_equals(host1.shadowRoot.querySelectorAll('::slotted(span)').length, 0);
}, "querySelectorAll for ::slotted pseudo element");
</script>
| chromium/chromium | third_party/blink/web_tests/fast/selectors/querySelector-pseudo-slotted.html | HTML | bsd-3-clause | 890 |
<!DOCTYPE html>
<html class="reftest-wait">
<link rel="help" href="https://drafts.csswg.org/css-backgrounds-3/#background-color">
<link rel="match" href="background-color-animation-ref.html">
<style>
.container {
width: 100px;
height: 100px;
background-color: rgb(0, 200, 0);
transition-property: background-color;
/* Use a long animation that start at 50% progress where the slope of the
selected timing function is zero. By setting up the animation in this way,
we accommodate lengthy delays in running the test without a potential drift
in the animated property value. This is important for avoiding flakes,
especially on debug builds. The screenshots are taken as soon as the
animation is ready, thus the long animation duration has no bearing on
the actual duration of the test. */
transition-duration: 1000000s;
transition-timing-function: cubic-bezier(0,1,1,0);
transition-delay: -500000s;
}
</style>
<script src="/common/reftest-wait.js"></script>
<body>
<div class="container" id="target"></div>
<script>
function update() {
document.getElementById('target').style.backgroundColor = "rgb(200, 0, 0)";
requestAnimationFrame(() => {
takeScreenshot();
});
}
requestAnimationFrame(function() {
requestAnimationFrame(update);
});
</script>
</body>
</html>
| scheib/chromium | third_party/blink/web_tests/external/wpt/css/css-backgrounds/animations/background-color-transition.html | HTML | bsd-3-clause | 1,319 |
<!DOCTYPE html>
<!-- DO NOT EDIT! This test has been generated by /html/canvas/tools/gentest.py. -->
<title>Canvas test: 2d.path.roundrect.nonfinite</title>
<script src="/resources/testharness.js"></script>
<script src="/resources/testharnessreport.js"></script>
<script src="/html/canvas/resources/canvas-tests.js"></script>
<link rel="stylesheet" href="/html/canvas/resources/canvas-tests.css">
<body class="show_output">
<h1>2d.path.roundrect.nonfinite</h1>
<p class="desc">roundRect() with Infinity/NaN is ignored</p>
<p class="output">Actual output:</p>
<canvas id="c" class="output" width="100" height="50"><p class="fallback">FAIL (fallback content)</p></canvas>
<p class="output expectedtext">Expected output:<p><img src="/images/green-100x50.png" class="output expected" id="expected" alt="">
<ul id="d"></ul>
<script>
var t = async_test("roundRect() with Infinity/NaN is ignored");
_addTest(function(canvas, ctx) {
ctx.fillStyle = '#f00';
ctx.fillRect(0, 0, 100, 50)
ctx.moveTo(0, 0);
ctx.lineTo(100, 0);
ctx.roundRect(Infinity, 50, 1, 1, [0]);
ctx.roundRect(-Infinity, 50, 1, 1, [0]);
ctx.roundRect(NaN, 50, 1, 1, [0]);
ctx.roundRect(0, Infinity, 1, 1, [0]);
ctx.roundRect(0, -Infinity, 1, 1, [0]);
ctx.roundRect(0, NaN, 1, 1, [0]);
ctx.roundRect(0, 50, Infinity, 1, [0]);
ctx.roundRect(0, 50, -Infinity, 1, [0]);
ctx.roundRect(0, 50, NaN, 1, [0]);
ctx.roundRect(0, 50, 1, Infinity, [0]);
ctx.roundRect(0, 50, 1, -Infinity, [0]);
ctx.roundRect(0, 50, 1, NaN, [0]);
ctx.roundRect(0, 50, 1, 1, [Infinity]);
ctx.roundRect(0, 50, 1, 1, [-Infinity]);
ctx.roundRect(0, 50, 1, 1, [NaN]);
ctx.roundRect(0, 50, 1, 1, [Infinity,0]);
ctx.roundRect(0, 50, 1, 1, [-Infinity,0]);
ctx.roundRect(0, 50, 1, 1, [NaN,0]);
ctx.roundRect(0, 50, 1, 1, [0,Infinity]);
ctx.roundRect(0, 50, 1, 1, [0,-Infinity]);
ctx.roundRect(0, 50, 1, 1, [0,NaN]);
ctx.roundRect(0, 50, 1, 1, [Infinity,0,0]);
ctx.roundRect(0, 50, 1, 1, [-Infinity,0,0]);
ctx.roundRect(0, 50, 1, 1, [NaN,0,0]);
ctx.roundRect(0, 50, 1, 1, [0,Infinity,0]);
ctx.roundRect(0, 50, 1, 1, [0,-Infinity,0]);
ctx.roundRect(0, 50, 1, 1, [0,NaN,0]);
ctx.roundRect(0, 50, 1, 1, [0,0,Infinity]);
ctx.roundRect(0, 50, 1, 1, [0,0,-Infinity]);
ctx.roundRect(0, 50, 1, 1, [0,0,NaN]);
ctx.roundRect(0, 50, 1, 1, [Infinity,0,0,0]);
ctx.roundRect(0, 50, 1, 1, [-Infinity,0,0,0]);
ctx.roundRect(0, 50, 1, 1, [NaN,0,0,0]);
ctx.roundRect(0, 50, 1, 1, [0,Infinity,0,0]);
ctx.roundRect(0, 50, 1, 1, [0,-Infinity,0,0]);
ctx.roundRect(0, 50, 1, 1, [0,NaN,0,0]);
ctx.roundRect(0, 50, 1, 1, [0,0,Infinity,0]);
ctx.roundRect(0, 50, 1, 1, [0,0,-Infinity,0]);
ctx.roundRect(0, 50, 1, 1, [0,0,NaN,0]);
ctx.roundRect(0, 50, 1, 1, [0,0,0,Infinity]);
ctx.roundRect(0, 50, 1, 1, [0,0,0,-Infinity]);
ctx.roundRect(0, 50, 1, 1, [0,0,0,NaN]);
ctx.roundRect(Infinity, Infinity, 1, 1, [0]);
ctx.roundRect(Infinity, Infinity, Infinity, 1, [0]);
ctx.roundRect(Infinity, Infinity, Infinity, Infinity, [0]);
ctx.roundRect(Infinity, Infinity, Infinity, Infinity, [Infinity]);
ctx.roundRect(Infinity, Infinity, Infinity, 1, [Infinity]);
ctx.roundRect(Infinity, Infinity, 1, Infinity, [0]);
ctx.roundRect(Infinity, Infinity, 1, Infinity, [Infinity]);
ctx.roundRect(Infinity, Infinity, 1, 1, [Infinity]);
ctx.roundRect(Infinity, 50, Infinity, 1, [0]);
ctx.roundRect(Infinity, 50, Infinity, Infinity, [0]);
ctx.roundRect(Infinity, 50, Infinity, Infinity, [Infinity]);
ctx.roundRect(Infinity, 50, Infinity, 1, [Infinity]);
ctx.roundRect(Infinity, 50, 1, Infinity, [0]);
ctx.roundRect(Infinity, 50, 1, Infinity, [Infinity]);
ctx.roundRect(Infinity, 50, 1, 1, [Infinity]);
ctx.roundRect(0, Infinity, Infinity, 1, [0]);
ctx.roundRect(0, Infinity, Infinity, Infinity, [0]);
ctx.roundRect(0, Infinity, Infinity, Infinity, [Infinity]);
ctx.roundRect(0, Infinity, Infinity, 1, [Infinity]);
ctx.roundRect(0, Infinity, 1, Infinity, [0]);
ctx.roundRect(0, Infinity, 1, Infinity, [Infinity]);
ctx.roundRect(0, Infinity, 1, 1, [Infinity]);
ctx.roundRect(0, 50, Infinity, Infinity, [0]);
ctx.roundRect(0, 50, Infinity, Infinity, [Infinity]);
ctx.roundRect(0, 50, Infinity, 1, [Infinity]);
ctx.roundRect(0, 50, 1, Infinity, [Infinity]);
ctx.roundRect(0, 0, 100, 100, [new DOMPoint(10, Infinity)]);
ctx.roundRect(0, 0, 100, 100, [new DOMPoint(10, -Infinity)]);
ctx.roundRect(0, 0, 100, 100, [new DOMPoint(10, NaN)]);
ctx.roundRect(0, 0, 100, 100, [new DOMPoint(Infinity, 10)]);
ctx.roundRect(0, 0, 100, 100, [new DOMPoint(-Infinity, 10)]);
ctx.roundRect(0, 0, 100, 100, [new DOMPoint(NaN, 10)]);
ctx.roundRect(0, 0, 100, 100, [{x: 10, y: Infinity}]);
ctx.roundRect(0, 0, 100, 100, [{x: 10, y: -Infinity}]);
ctx.roundRect(0, 0, 100, 100, [{x: 10, y: NaN}]);
ctx.roundRect(0, 0, 100, 100, [{x: Infinity, y: 10}]);
ctx.roundRect(0, 0, 100, 100, [{x: -Infinity, y: 10}]);
ctx.roundRect(0, 0, 100, 100, [{x: NaN, y: 10}]);
ctx.lineTo(100, 50);
ctx.lineTo(0, 50);
ctx.fillStyle = '#0f0';
ctx.fill();
_assertPixel(canvas, 50,25, 0,255,0,255, "50,25", "0,255,0,255");
_assertPixel(canvas, 90,45, 0,255,0,255, "90,45", "0,255,0,255");
});
</script>
| scheib/chromium | third_party/blink/web_tests/external/wpt/html/canvas/element/path-objects/2d.path.roundrect.nonfinite.html | HTML | bsd-3-clause | 5,033 |
<!DOCTYPE html>
<html>
<head>
<title>Popcorn tagthisperson test</title>
<link rel="stylesheet" href="../../test/qunit/qunit.css" type="text/css" media="screen">
<script src="../../test/qunit/qunit.js"></script>
<!--
do not move - this must be called immediately prior to
popcorn-api-draft.js
-->
<script src="../../popcorn.js"></script>
<script src="popcorn.tagthisperson.js"></script>
<script src="popcorn.tagthisperson.unit.js"></script>
<script src="../../test/inject.js"></script>
<script src="../../test/popcorn.inject.js"></script>
</head>
<body>
<h1 id="qunit-header">Popcorn tagthisperson Plugin</h1>
<h2 id="qunit-banner"></h2>
<div id="qunit-testrunner-toolbar"></div>
<h2 id="qunit-userAgent"></h2>
<ol id="qunit-tests"></ol>
<div id="qunit-fixture"> </div>
<video id="video"
controls
width= "250px"
poster="../../test/poster.png">
<source id="mp4"
src="../../test/trailer.mp4"
type='video/mp4; codecs="avc1, mp4a"'>
<source id="ogv"
src="../../test/trailer.ogv"
type='video/ogg; codecs="theora, vorbis"'>
<source id="webm"
src="../../test/trailer.webm"
type='video/webm; codecs="vp8, vorbis"'>
<p>Your user agent does not support the HTML5 Video element.</p>
</video>
<div id="tagdiv"></div>
<div id="tagdiv2"></div>
</body>
</html>
| azmenak/popcorn-js | unsupported/tagthisperson/popcorn.tagthisperson.unit.html | HTML | mit | 1,366 |
<html>
<body>
Reports deprecated classes, methods and fields which are used in your code nonetheless.
<br>
For example:
<pre>
<b><font color="#000080">class</font></b> MyCode {
@Deprecated
// warning: "Deprecated member is still used"
<b><font color="#000080">void</font></b> <span style="background-color: yellow;">oldMethod</span>() {}
<b><font color="#000080">void</font></b> newMethod() {
oldMethod(); // forgotten usage
}
}
</pre>
(Usages from within deprecated places are ignored).
</body>
</html> | Yihy/resources_cn | src/main/resources/inspectionDescriptions/DeprecatedIsStillUsed.html | HTML | apache-2.0 | 519 |
<!--
Copyright (C) 2014 Samsung Electronics Corporation. All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY SAMSUNG ELECTRONICS CORPORATION AND ITS
CONTRIBUTORS "AS IS", AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING
BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SAMSUNG
ELECTRONICS CORPORATION OR ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES(INCLUDING
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS, OR BUSINESS INTERRUPTION), HOWEVER CAUSED AND ON ANY THEORY
OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT(INCLUDING
NEGLIGENCE OR OTHERWISE ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-->
<html>
<head>
<meta charset="utf-8">
<title>enqueueCopyBufferRect functionality test.</title>
<link rel="stylesheet" href="../../../resources/js-test-style.css"/>
<script src="../../../resources/js-test-pre.js"></script>
<script src="../../../resources/cl_utils.js"></script>
</head>
<body>
<div id="description"></div>
<div id="console"></div>
<script>
try {
debug("enqueueCopyBufferRect functionality test case.");
var wtu = WebCLTestUtils;
var webCLContext = wtu.createContext();
var webCLCommandQueue = wtu.createCommandQueue(webCLContext);
var srcBuffer, dstBuffer;
var result, data;
var numberOfValues = 256;
var BUFFER_SIZE_IN_BYTES = 1024; /* 256 Int32 elements */
data = new Int32Array(numberOfValues);
var maxInt32Value = 2147483647;
wtu.generateRandomNumberInRange (data, 0, maxInt32Value, numberOfValues);
srcBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES, data);
var srcOriginConst = [0, 0, 0];
var dstOriginConst = [0, 0, 0];
var srcRowPitchConst = 0;
var srcSlicePitchConst = 0;
var dstRowPitchConst = 0;
var dstSlicePitchConst = 0;
/*
* Testing for copying whole buffer of 256 values, of 4 bytes each using copyBufferRect.
*/
try {
srcOrigin = [0, 0, 0];
dstOrigin = [0, 0, 0];
region = [16 * 4, 4, 4]; /* Read as 4 rows of 16 int32 elements each with 4 slice.*/
dstBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOrigin, dstOrigin, region, srcRowPitchConst, srcSlicePitchConst, dstRowPitchConst, dstSlicePitchConst);
var result = new Int32Array(numberOfValues);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, BUFFER_SIZE_IN_BYTES, result);
wtu.verifyResult(data, result, numberOfValues, "copying whole buffer using copyBufferRect");
} catch(e) {
testFailed(e.description);
}
/*
* Testing for copying first 10 int32 values from srcBuffer to dstBuffer using copyBufferRect.
*/
try {
srcOrigin = [0, 0, 0];
dstOrigin = [0, 0, 0];
region = [10 * 4, 1, 1];
dstBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOrigin, dstOrigin, region, srcRowPitchConst, srcSlicePitchConst, dstRowPitchConst, dstSlicePitchConst);
var result = new Int32Array(10);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 10 * Int32Array.BYTES_PER_ELEMENT, result);
wtu.verifyResult(data, result, 10, "copying first 10 int32 values from srcBuffer to dstBuffer using copyBufferRect");
} catch(e) {
testFailed(e.description);
}
/*
* Testing for copying last 16 int32 values from srcBuffer using copyBufferRect.
*/
try {
srcOrigin = [0, 3, 3];
dstOrigin = [0, 0, 0];
region = [16 * 4, 1, 1];
dstBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOrigin, dstOrigin, region, 64, 256, dstRowPitchConst, dstSlicePitchConst);
var result = new Int32Array(16);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 16 * 4, result);
var aData = new Int32Array(data.buffer, 1024 - 64, 16);
wtu.verifyResult(aData, result, 16, "copying last 16 values from srcBuffer using copyBufferRect");
} catch(e) {
testFailed(e.description);
}
/*
* Testing for copying into last 16 locations of dstBuffer using copyBufferRect.
*/
try {
srcOrigin = [0, 0, 0];
dstOrigin = [0, 3, 3];
region = [16 * 4, 1, 1];
dstBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOrigin, dstOrigin, region, srcRowPitchConst, srcSlicePitchConst, 64, 256);
var result = new Int32Array(256);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
var aResult = new Int32Array(result.buffer, 1024 - 64, 16);
wtu.verifyResult(data, aResult, 16, "copying into last 16 locations of dstBuffer using copyBufferRect");
} catch(e) {
testFailed(e.description);
}
/*
* Testing for copying a row of 16 int32 values from 3rd row of srcBuffer using copyBufferRect.
*/
try {
srcOrigin = [0, 3, 0];
dstOrigin = [0, 0, 0];
region = [16 * 4, 1, 1];
dstBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOrigin, dstOrigin, region, srcRowPitchConst, srcSlicePitchConst, dstRowPitchConst, dstSlicePitchConst);
var result = new Int32Array(256);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
var aData = new Int32Array(data.buffer, region[0] * srcOrigin[1], 16);
wtu.verifyResult(aData, result, aData.length, "copying from 3rd row of 16 int32 values of srcBuffer using copyBufferRect");
} catch(e) {
testFailed(e.description);
}
/*
* Testing for copying a row of 16 int32 values into 3rd row of dstBuffer using copyBufferRect.
*/
try {
srcOrigin = [0, 0, 0];
dstOrigin = [0, 3, 0];
region = [16 * 4, 1, 1];
dstBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOrigin, dstOrigin, region, srcRowPitchConst, srcSlicePitchConst, dstRowPitchConst, dstSlicePitchConst);
var result = new Int32Array(256);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
var aResult = new Int32Array(result.buffer, region[0] * dstOrigin[1], 16);
wtu.verifyResult(data, aResult, aResult.length, "copying into 3rd row of 16 int32 values of dstBuffer using copyBufferRect");
} catch(e) {
testFailed(e.description);
}
/*
* Testing for copying from 2nd slice of 16 int32 values of srcBuffer using copyBufferRect.
*/
try {
srcOrigin = [0, 0, 2];
dstOrigin = [0, 0, 0];
region = [16 * 4, 1, 1];
dstBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOrigin, dstOrigin, region, srcRowPitchConst, srcSlicePitchConst, dstRowPitchConst, dstSlicePitchConst);
var result = new Int32Array(256);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
// Saving 2nd slice of a row of 16 values of srcBuffer to aData.
var aData = new Int32Array(data.buffer, region[0] * region[1] * srcOrigin[2], 16 * region[1]);
wtu.verifyResult(aData, result, aData.length, "copying from 2nd slice of 16 int32 values of srcBuffer using copyBufferRect");
} catch(e) {
testFailed(e.description);
}
/*
* Testing for copying into 2nd slice of 16 int32 values of dstBuffer using copyBufferRect.
*/
try {
srcOrigin = [0, 0, 0];
dstOrigin = [0, 0, 2];
region = [16 * 4, 1, 1];
dstBuffer = wtu.createBuffer(webCLContext, webcl.MEM_READ_WRITE, BUFFER_SIZE_IN_BYTES);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOrigin, dstOrigin, region, srcRowPitchConst, srcSlicePitchConst, dstRowPitchConst, dstSlicePitchConst);
var result = new Int32Array(256);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
// Saving 2nd slice of a row of 16 values of dstBuffer to aResult.
var aResult = new Int32Array(result.buffer, region[0] * region[1] * dstOrigin[2], 16 * region[1]);
wtu.verifyResult(data, aResult, aResult.length, "copying into 2nd slice of 16 int32 values of dstBuffer using copyBufferRect");
} catch(e) {
testFailed(e.description);
}
var valuesPerRow = 16;
var numberOfRows = 4;
var numberOfSlices = 4;
regionConst = [valuesPerRow * Int32Array.BYTES_PER_ELEMENT, numberOfRows, numberOfSlices];
/*
* Testing for copying from alternate rows of srcBuffer using copyBufferRect.
*/
try {
region = [16 * 4, 2, 1];
srcRowPitch = region[0] * 2;
result = new Int32Array(numberOfValues);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOriginConst, dstOriginConst, region, srcRowPitch, srcSlicePitchConst, dstRowPitchConst, dstSlicePitchConst);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
// Verifying alternate rows of buffer.
for (i = 0, j = 0; i < region[0]; i += 2 * valuesPerRow, j+= valuesPerRow) {
for (z = 0; z < valuesPerRow; z++) {
if (data[i + z] != result[j + z]) {
flag = true;
break;
}
}
}
if (!flag)
testPassed("Test passed for copying from alternate rows of a slice of srcBuffer using copyBufferRect.");
else
testFailed("Test failed for copying from alternate rows of a slice of srcBuffer using copyBufferRect.");
} catch(e) {
testFailed(e.description);
}
srcRowPitch = 0;
/*
* Testing for copying into alternate rows of dstBuffer using copyBufferRect.
*/
try {
region = [16 * 4, 2, 1];
dstRowPitch = region[0] * 2;
result = new Int32Array(numberOfValues);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOriginConst, dstOriginConst, region, srcRowPitchConst, srcSlicePitchConst, dstRowPitch, dstSlicePitchConst);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
for (i = 0, j = 0; i < region[0]; i += 2 * valuesPerRow, j+= valuesPerRow) {
for (z = 0; z < valuesPerRow; z++) {
if (data[i + z] != result[j + z]) {
flag = true;
break;
}
}
}
if (!flag)
testPassed("Test passed for copying into alternate rows of a slice of dstBuffer using copyBufferRect.");
else
testFailed("Test failed for copying into alternate rows of a slice of dstBuffer using copyBufferRect.");
} catch(e) {
testFailed(e.description);
}
dstRowPitch = 0;
/*
* Testing for copying from alternate slices of srcBuffer using copyBufferRect.
*/
try {
region = [16 * 4, 2, 2];
srcSlicePitch = region[0] * region[1] * 2;
result = new Int32Array(numberOfValues);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOriginConst, dstOriginConst, region, srcRowPitchConst, srcSlicePitch, dstRowPitchConst, dstSlicePitchConst);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
var flag = false;
for (i = 0, j = 0; i < regionConst[0]; i += 2 * valuesPerRow * region[1], j += valuesPerRow * region[1]) {
for (z = 0; z < valuesPerRow * region[1] /* 16 * 2 */; z++) {
if (data[i + z] != result[j + z]) {
flag = true;
break;
}
}
}
if (!flag)
testPassed("Test passed for copying from alternate slices of srcBuffer using copyBufferRect.");
else
testFailed("Test failed for copying from alternate slices of srcBuffer using copyBufferRect.");
} catch(e) {
testFailed(e.description);
}
srcSlicePitch = 0;
/*
* Testing for copying into alternate slices of dstBuffer using copyBufferRect.
*/
try {
region = [16 * 4, 2, 2];
dstSlicePitch = region[0] * region[1] * 2;
result = new Int32Array(numberOfValues);
wtu.enqueueCopyBufferRect(webCLCommandQueue, srcBuffer, dstBuffer, srcOriginConst, dstOriginConst, region, srcRowPitchConst, srcSlicePitchConst, dstRowPitchConst, dstSlicePitch);
wtu.enqueueReadBuffer(webCLCommandQueue, dstBuffer, true, 0, 256 * 4, result);
var flag = false;
for (i = 0, j = 0; i < regionConst[0]; i += 2 * valuesPerRow * region[1], j += valuesPerRow * region[1]) {
for (z = 0; z < valuesPerRow * region[1] /* 16 * 2 */; z++) {
if (data[i + z] != result[j + z]) {
flag = true;
break;
}
}
}
if (!flag)
testPassed("Test passed for copying into alternate slices of dstBuffer using copyBufferRect.");
else
testFailed("Test failed for copying into alternate slices of dstBuffer using copyBufferRect.");
} catch(e) {
testFailed(e.description);
}
dstSlicePitch = 0;
} catch(e) {
testFailed(e.description);
}
successfullyParsed = true;
</script>
<script src="../../../resources/js-test-post.js"></script>
</body>
</html>
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<div class="title">type_mat2x2.hpp</div> </div>
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<a href="a00120.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> </div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#pragma once</span></div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include "../fwd.hpp"</span></div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include "<a class="code" href="a00133.html">type_vec2.hpp</a>"</span></div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include "<a class="code" href="a00119.html">type_mat.hpp</a>"</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include <limits></span></div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include <cstddef></span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword">namespace </span><a class="code" href="a00145.html">glm</a></div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P = defaultp></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keyword">struct </span>tmat2x2</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  {</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keyword">typedef</span> tvec2<T, P> col_type;</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keyword">typedef</span> tvec2<T, P> row_type;</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keyword">typedef</span> tmat2x2<T, P> type;</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keyword">typedef</span> tmat2x2<T, P> transpose_type;</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keyword">typedef</span> T value_type;</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U, precision Q></div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">friend</span> tvec2<U, Q> operator/(tmat2x2<U, Q> <span class="keyword">const</span> & m, tvec2<U, Q> <span class="keyword">const</span> & v);</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U, precision Q></div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keyword">friend</span> tvec2<U, Q> operator/(tvec2<U, Q> <span class="keyword">const</span> & v, tmat2x2<U, Q> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">private</span>:</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  col_type value[2];</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  </div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keyword">public</span>:</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// Constructors</span></div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  GLM_FUNC_DECL tmat2x2();</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">template</span> <precision Q></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  GLM_FUNC_DECL tmat2x2(tmat2x2<T, Q> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> </div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(ctor);</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(T <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  GLM_FUNC_DECL tmat2x2(</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  T <span class="keyword">const</span> & x1, T <span class="keyword">const</span> & y1,</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  T <span class="keyword">const</span> & x2, T <span class="keyword">const</span> & y2);</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  GLM_FUNC_DECL tmat2x2(</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  col_type <span class="keyword">const</span> & v1,</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  col_type <span class="keyword">const</span> & v2);</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// Conversions</span></div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U, <span class="keyword">typename</span> V, <span class="keyword">typename</span> M, <span class="keyword">typename</span> N></div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  GLM_FUNC_DECL tmat2x2(</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  U <span class="keyword">const</span> & x1, V <span class="keyword">const</span> & y1,</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  M <span class="keyword">const</span> & x2, N <span class="keyword">const</span> & y2);</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U, <span class="keyword">typename</span> V></div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  GLM_FUNC_DECL tmat2x2(</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  tvec2<U, P> <span class="keyword">const</span> & v1,</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  tvec2<V, P> <span class="keyword">const</span> & v2);</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="comment">// Matrix conversions</span></div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="preprocessor"># ifdef GLM_FORCE_EXPLICIT_CTOR</span></div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U, precision Q></div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat2x2<U, Q> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="preprocessor"># else</span></div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U, precision Q></div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  GLM_FUNC_DECL tmat2x2(tmat2x2<U, Q> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="preprocessor"># endif</span></div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat3x3<T, P> <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat4x4<T, P> <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat2x3<T, P> <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat3x2<T, P> <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat2x4<T, P> <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat4x2<T, P> <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat3x4<T, P> <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  GLM_FUNC_DECL <span class="keyword">explicit</span> tmat2x2(tmat4x3<T, P> <span class="keyword">const</span> & x);</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// Accesses</span></div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="preprocessor"># ifdef GLM_FORCE_SIZE_FUNC</span></div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keyword">typedef</span> <span class="keywordtype">size_t</span> size_type;</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  GLM_FUNC_DECL GLM_CONSTEXPR <span class="keywordtype">size_t</span> size() <span class="keyword">const</span>;</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  GLM_FUNC_DECL col_type & operator[](size_type i);</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  GLM_FUNC_DECL col_type <span class="keyword">const</span> & operator[](size_type i) <span class="keyword">const</span>;</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="preprocessor"># else</span></div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keyword">typedef</span> length_t length_type;</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  GLM_FUNC_DECL GLM_CONSTEXPR length_type <a class="code" href="a00151.html#ga18d45e3d4c7705e67ccfabd99e521604">length</a>() <span class="keyword">const</span>;</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  GLM_FUNC_DECL col_type & operator[](length_type i);</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  GLM_FUNC_DECL col_type <span class="keyword">const</span> & operator[](length_type i) <span class="keyword">const</span>;</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="preprocessor"># endif//GLM_FORCE_SIZE_FUNC</span></div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// Unary arithmetic operators</span></div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator=(tmat2x2<U, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator+=(U s);</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator+=(tmat2x2<U, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator-=(U s);</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator-=(tmat2x2<U, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator*=(U s);</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator*=(tmat2x2<U, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator/=(U s);</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U> </div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator/=(tmat2x2<U, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="comment">// Increment and decrement operators</span></div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator++ ();</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  GLM_FUNC_DECL tmat2x2<T, P> & operator-- ();</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  GLM_FUNC_DECL tmat2x2<T, P> operator++(<span class="keywordtype">int</span>);</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  GLM_FUNC_DECL tmat2x2<T, P> operator--(<span class="keywordtype">int</span>);</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  };</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// Binary operators</span></div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  GLM_FUNC_DECL tmat2x2<T, P> operator+(tmat2x2<T, P> <span class="keyword">const</span> & m, T <span class="keyword">const</span> & s);</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  GLM_FUNC_DECL tmat2x2<T, P> operator+(T <span class="keyword">const</span> & s, tmat2x2<T, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  GLM_FUNC_DECL tmat2x2<T, P> operator+(tmat2x2<T, P> <span class="keyword">const</span> & m1, tmat2x2<T, P> <span class="keyword">const</span> & m2);</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  GLM_FUNC_DECL tmat2x2<T, P> operator-(tmat2x2<T, P> <span class="keyword">const</span> & m, T <span class="keyword">const</span> & s);</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  GLM_FUNC_DECL tmat2x2<T, P> operator-(T <span class="keyword">const</span> & s, tmat2x2<T, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span> </div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  GLM_FUNC_DECL tmat2x2<T, P> operator-(tmat2x2<T, P> <span class="keyword">const</span> & m1, tmat2x2<T, P> <span class="keyword">const</span> & m2);</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  GLM_FUNC_DECL tmat2x2<T, P> operator*(tmat2x2<T, P> <span class="keyword">const</span> & m, T <span class="keyword">const</span> & s);</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  GLM_FUNC_DECL tmat2x2<T, P> operator*(T <span class="keyword">const</span> & s, tmat2x2<T, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  GLM_FUNC_DECL <span class="keyword">typename</span> tmat2x2<T, P>::col_type operator*(tmat2x2<T, P> <span class="keyword">const</span> & m, <span class="keyword">typename</span> tmat2x2<T, P>::row_type <span class="keyword">const</span> & v);</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span> </div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  GLM_FUNC_DECL <span class="keyword">typename</span> tmat2x2<T, P>::row_type operator*(<span class="keyword">typename</span> tmat2x2<T, P>::col_type <span class="keyword">const</span> & v, tmat2x2<T, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  GLM_FUNC_DECL tmat2x2<T, P> operator*(tmat2x2<T, P> <span class="keyword">const</span> & m1, tmat2x2<T, P> <span class="keyword">const</span> & m2);</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  </div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  GLM_FUNC_DECL tmat3x2<T, P> operator*(tmat2x2<T, P> <span class="keyword">const</span> & m1, tmat3x2<T, P> <span class="keyword">const</span> & m2);</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  </div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  GLM_FUNC_DECL tmat4x2<T, P> operator*(tmat2x2<T, P> <span class="keyword">const</span> & m1, tmat4x2<T, P> <span class="keyword">const</span> & m2);</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  GLM_FUNC_DECL tmat2x2<T, P> operator/(tmat2x2<T, P> <span class="keyword">const</span> & m, T <span class="keyword">const</span> & s);</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  GLM_FUNC_DECL tmat2x2<T, P> operator/(T <span class="keyword">const</span> & s, tmat2x2<T, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span> </div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  GLM_FUNC_DECL <span class="keyword">typename</span> tmat2x2<T, P>::col_type operator/(tmat2x2<T, P> <span class="keyword">const</span> & m, <span class="keyword">typename</span> tmat2x2<T, P>::row_type <span class="keyword">const</span> & v);</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  GLM_FUNC_DECL <span class="keyword">typename</span> tmat2x2<T, P>::row_type operator/(<span class="keyword">typename</span> tmat2x2<T, P>::col_type <span class="keyword">const</span> & v, tmat2x2<T, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P></div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  GLM_FUNC_DECL tmat2x2<T, P> operator/(tmat2x2<T, P> <span class="keyword">const</span> & m1, tmat2x2<T, P> <span class="keyword">const</span> & m2);</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="comment">// Unary constant operators</span></div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, precision P> </div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  GLM_FUNC_DECL tmat2x2<T, P> <span class="keyword">const</span> operator-(tmat2x2<T, P> <span class="keyword">const</span> & m);</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span> } <span class="comment">//namespace glm</span></div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span> <span class="preprocessor">#ifndef GLM_EXTERNAL_TEMPLATE</span></div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span> <span class="preprocessor">#include "type_mat2x2.inl"</span></div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span> <span class="preprocessor">#endif</span></div>
<div class="ttc" id="a00151_html_ga18d45e3d4c7705e67ccfabd99e521604"><div class="ttname"><a href="a00151.html#ga18d45e3d4c7705e67ccfabd99e521604">glm::length</a></div><div class="ttdeci">GLM_FUNC_DECL T length(vecType< T, P > const &x)</div><div class="ttdoc">Returns the length of x, i.e., sqrt(x * x). </div></div>
<div class="ttc" id="a00145_html"><div class="ttname"><a href="a00145.html">glm</a></div><div class="ttdef"><b>Definition:</b> <a href="a00003_source.html#l00039">_noise.hpp:39</a></div></div>
<div class="ttc" id="a00133_html"><div class="ttname"><a href="a00133.html">type_vec2.hpp</a></div><div class="ttdoc">OpenGL Mathematics (glm.g-truc.net) </div></div>
<div class="ttc" id="a00119_html"><div class="ttname"><a href="a00119.html">type_mat.hpp</a></div><div class="ttdoc">OpenGL Mathematics (glm.g-truc.net) </div></div>
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| TheMarex/deberg | third_party/glm/doc/api/a00120_source.html | HTML | bsd-2-clause | 34,108 |
<!doctype html>
<title>document.write script into iframe write back into parent</title>
<script src="../../../../../../resources/testharness.js"></script><script src="../../../../../../resources/testharnessreport.js"></script>
<iframe id="test"></iframe>
<script>
var t = async_test();
var iframe = document.getElementById("test");
var order = [];
t.step(function() {
order.push(1);
var s = "<script>parent.order.push(2); parent.document.write('<script>order.push(3);</script'+'>'); parent.order.push(4)</script" + ">";
for (var i=0; i<s.length; i++) {
iframe.contentDocument.write(s[i]);
}
iframe.contentDocument.close();
order.push(5);
assert_array_equals(order, [1,2,3,4,5])
}
);
t.done();
</script>
<div id="log"></div> | js0701/chromium-crosswalk | third_party/WebKit/LayoutTests/imported/web-platform-tests/html/dom/dynamic-markup-insertion/document-write/iframe_004.html | HTML | bsd-3-clause | 741 |
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<pre class="prettyprint lang-js"><span id='Ext-tree-Panel'>/**
</span> * The TreePanel provides tree-structured UI representation of tree-structured data.
* A TreePanel must be bound to a {@link Ext.data.TreeStore}. TreePanel's support
* multiple columns through the {@link #columns} configuration.
*
* Simple TreePanel using inline data:
*
* @example
* var store = Ext.create('Ext.data.TreeStore', {
* root: {
* expanded: true,
* children: [
* { text: "detention", leaf: true },
* { text: "homework", expanded: true, children: [
* { text: "book report", leaf: true },
* { text: "algebra", leaf: true}
* ] },
* { text: "buy lottery tickets", leaf: true }
* ]
* }
* });
*
* Ext.create('Ext.tree.Panel', {
* title: 'Simple Tree',
* width: 200,
* height: 150,
* store: store,
* rootVisible: false,
* renderTo: Ext.getBody()
* });
*
* For the tree node config options (like `text`, `leaf`, `expanded`), see the documentation of
* {@link Ext.data.NodeInterface NodeInterface} config options.
*/
Ext.define('Ext.tree.Panel', {
extend: 'Ext.panel.Table',
alias: 'widget.treepanel',
alternateClassName: ['Ext.tree.TreePanel', 'Ext.TreePanel'],
requires: ['Ext.tree.View', 'Ext.selection.TreeModel', 'Ext.tree.Column', 'Ext.data.TreeStore'],
<span id='Ext-tree-Panel-cfg-viewType'> viewType: 'treeview',
</span><span id='Ext-tree-Panel-cfg-selType'> selType: 'treemodel',
</span>
<span id='Ext-tree-Panel-property-treeCls'> treeCls: Ext.baseCSSPrefix + 'tree-panel',
</span>
<span id='Ext-tree-Panel-cfg-deferRowRender'> deferRowRender: false,
</span>
<span id='Ext-tree-Panel-cfg-rowLines'> /**
</span> * @cfg {Boolean} rowLines
* False so that rows are not separated by lines.
*/
rowLines: false,
<span id='Ext-tree-Panel-cfg-lines'> /**
</span> * @cfg {Boolean} lines
* False to disable tree lines.
*/
lines: true,
<span id='Ext-tree-Panel-cfg-useArrows'> /**
</span> * @cfg {Boolean} useArrows
* True to use Vista-style arrows in the tree.
*/
useArrows: false,
<span id='Ext-tree-Panel-cfg-singleExpand'> /**
</span> * @cfg {Boolean} singleExpand
* True if only 1 node per branch may be expanded.
*/
singleExpand: false,
<span id='Ext-tree-Panel-property-ddConfig'> ddConfig: {
</span> enableDrag: true,
enableDrop: true
},
<span id='Ext-tree-Panel-cfg-animate'> /**
</span> * @cfg {Boolean} animate
* True to enable animated expand/collapse. Defaults to the value of {@link Ext#enableFx}.
*/
<span id='Ext-tree-Panel-cfg-rootVisible'> /**
</span> * @cfg {Boolean} rootVisible
* False to hide the root node.
*/
rootVisible: true,
<span id='Ext-tree-Panel-cfg-displayField'> /**
</span> * @cfg {String} displayField
* The field inside the model that will be used as the node's text.
*/
displayField: 'text',
<span id='Ext-tree-Panel-cfg-root'> /**
</span> * @cfg {Ext.data.Model/Ext.data.NodeInterface/Object} root
* Allows you to not specify a store on this TreePanel. This is useful for creating a simple tree with preloaded
* data without having to specify a TreeStore and Model. A store and model will be created and root will be passed
* to that store. For example:
*
* Ext.create('Ext.tree.Panel', {
* title: 'Simple Tree',
* root: {
* text: "Root node",
* expanded: true,
* children: [
* { text: "Child 1", leaf: true },
* { text: "Child 2", leaf: true }
* ]
* },
* renderTo: Ext.getBody()
* });
*/
root: null,
<span id='Ext-tree-Panel-property-normalCfgCopy'> // Required for the Lockable Mixin. These are the configurations which will be copied to the
</span> // normal and locked sub tablepanels
normalCfgCopy: ['displayField', 'root', 'singleExpand', 'useArrows', 'lines', 'rootVisible', 'scroll'],
<span id='Ext-tree-Panel-property-lockedCfgCopy'> lockedCfgCopy: ['displayField', 'root', 'singleExpand', 'useArrows', 'lines', 'rootVisible'],
</span>
<span id='Ext-tree-Panel-property-isTree'> isTree: true,
</span>
<span id='Ext-tree-Panel-cfg-hideHeaders'> /**
</span> * @cfg {Boolean} hideHeaders
* True to hide the headers.
*/
<span id='Ext-tree-Panel-cfg-folderSort'> /**
</span> * @cfg {Boolean} folderSort
* True to automatically prepend a leaf sorter to the store.
*/
<span id='Ext-tree-Panel-cfg-store'> /**
</span> * @cfg {Ext.data.TreeStore} store (required)
* The {@link Ext.data.TreeStore Store} the tree should use as its data source.
*/
arrowCls: Ext.baseCSSPrefix + 'tree-arrows',
<span id='Ext-tree-Panel-property-linesCls'> linesCls: Ext.baseCSSPrefix + 'tree-lines',
</span><span id='Ext-tree-Panel-property-noLinesCls'> noLinesCls: Ext.baseCSSPrefix + 'tree-no-lines',
</span><span id='Ext-tree-Panel-property-autoWidthCls'> autoWidthCls: Ext.baseCSSPrefix + 'autowidth-table',
</span>
<span id='Ext-tree-Panel-method-constructor'> constructor: function(config) {
</span> config = config || {};
if (config.animate === undefined) {
config.animate = Ext.isBoolean(this.animate) ? this.animate : Ext.enableFx;
}
this.enableAnimations = config.animate;
delete config.animate;
this.callParent([config]);
},
<span id='Ext-tree-Panel-method-initComponent'> initComponent: function() {
</span> var me = this,
cls = [me.treeCls],
store = me.store,
view;
if (me.useArrows) {
cls.push(me.arrowCls);
me.lines = false;
}
if (me.lines) {
cls.push(me.linesCls);
} else if (!me.useArrows) {
cls.push(me.noLinesCls);
}
if (Ext.isString(store)) {
store = me.store = Ext.StoreMgr.lookup(store);
} else if (!store || Ext.isObject(store) && !store.isStore) {
store = me.store = new Ext.data.TreeStore(Ext.apply({
root: me.root,
fields: me.fields,
model: me.model,
folderSort: me.folderSort
}, store));
} else if (me.root) {
store = me.store = Ext.data.StoreManager.lookup(store);
store.setRootNode(me.root);
if (me.folderSort !== undefined) {
store.folderSort = me.folderSort;
store.sort();
}
}
// I'm not sure if we want to this. It might be confusing
// if (me.initialConfig.rootVisible === undefined && !me.getRootNode()) {
// me.rootVisible = false;
// }
me.viewConfig = Ext.apply({
rootVisible: me.rootVisible,
animate: me.enableAnimations,
singleExpand: me.singleExpand,
node: store.getRootNode(),
hideHeaders: me.hideHeaders
}, me.viewConfig);
// If the user specifies the headers collection manually then dont inject our own
if (!me.columns) {
if (me.initialConfig.hideHeaders === undefined) {
me.hideHeaders = true;
}
me.addCls(me.autoWidthCls);
me.columns = [{
xtype : 'treecolumn',
text : 'Name',
width : Ext.isIE6 ? '100%' : 10000, // IE6 needs width:100%
dataIndex: me.displayField
}];
}
if (me.cls) {
cls.push(me.cls);
}
me.cls = cls.join(' ');
me.callParent();
// TreeModel has to know about the TreeStore so that pruneRemoved can work properly upon removal
// of nodes.
me.selModel.treeStore = me.store;
view = me.getView();
// Relay events from the TreeView.
// An injected LockingView relays events from its locked side's View
me.relayEvents(view, [
<span id='Ext-tree-Panel-event-checkchange'> /**
</span> * @event checkchange
* Fires when a node with a checkbox's checked property changes
* @param {Ext.data.NodeInterface} node The node who's checked property was changed
* @param {Boolean} checked The node's new checked state
*/
'checkchange',
<span id='Ext-tree-Panel-event-afteritemexpand'> /**
</span> * @event afteritemexpand
* @inheritdoc Ext.tree.View#afteritemexpand
*/
'afteritemexpand',
<span id='Ext-tree-Panel-event-afteritemcollapse'> /**
</span> * @event afteritemcollapse
* @inheritdoc Ext.tree.View#afteritemcollapse
*/
'afteritemcollapse'
]);
// If there has been a LockingView injected, this processing will be performed by the locked TreePanel
if (!view.isLockingView) {
// If the root is not visible and there is no rootnode defined, then just lets load the store
if (!view.rootVisible && !me.getRootNode()) {
me.setRootNode({
expanded: true
});
}
}
},
<span id='Ext-tree-Panel-method-bindStore'> // @private
</span> // Hook into the TreeStore.
// Do not callParent in TreePanel's bindStore
// The TreeStore is only relevant to the tree - the View has its own NodeStore
bindStore: function(store, initial) {
var me = this;
me.store = store;
// Connect to store. Return a Destroyable object
me.storeListeners = me.mon(store, {
destroyable: true,
load: me.onStoreLoad,
rootchange: me.onRootChange,
clear: me.onClear,
scope: me
});
// Relay store events. relayEvents always returns a Destroyable object.
me.storeRelayers = me.relayEvents(store, [
<span id='Ext-tree-Panel-event-beforeload'> /**
</span> * @event beforeload
* @inheritdoc Ext.data.TreeStore#beforeload
*/
'beforeload',
<span id='Ext-tree-Panel-event-load'> /**
</span> * @event load
* @inheritdoc Ext.data.TreeStore#load
*/
'load'
]);
// Relay store events with prefix. Return a Destroyable object
me.storeRelayers1 = me.mon(store, {
destroyable: true,
<span id='Ext-tree-Panel-event-itemappend'> /**
</span> * @event itemappend
* @inheritdoc Ext.data.TreeStore#append
*/
append: me.createRelayer('itemappend'),
<span id='Ext-tree-Panel-event-itemremove'> /**
</span> * @event itemremove
* @inheritdoc Ext.data.TreeStore#remove
*/
remove: me.createRelayer('itemremove'),
<span id='Ext-tree-Panel-event-itemmove'> /**
</span> * @event itemmove
* @inheritdoc Ext.data.TreeStore#move
*/
move: me.createRelayer('itemmove', [0, 4]),
<span id='Ext-tree-Panel-event-iteminsert'> /**
</span> * @event iteminsert
* @inheritdoc Ext.data.TreeStore#insert
*/
insert: me.createRelayer('iteminsert'),
<span id='Ext-tree-Panel-event-beforeitemappend'> /**
</span> * @event beforeitemappend
* @inheritdoc Ext.data.TreeStore#beforeappend
*/
beforeappend: me.createRelayer('beforeitemappend'),
<span id='Ext-tree-Panel-event-beforeitemremove'> /**
</span> * @event beforeitemremove
* @inheritdoc Ext.data.TreeStore#beforeremove
*/
beforeremove: me.createRelayer('beforeitemremove'),
<span id='Ext-tree-Panel-event-beforeitemmove'> /**
</span> * @event beforeitemmove
* @inheritdoc Ext.data.TreeStore#beforemove
*/
beforemove: me.createRelayer('beforeitemmove'),
<span id='Ext-tree-Panel-event-beforeiteminsert'> /**
</span> * @event beforeiteminsert
* @inheritdoc Ext.data.TreeStore#beforeinsert
*/
beforeinsert: me.createRelayer('beforeiteminsert'),
<span id='Ext-tree-Panel-event-itemexpand'> /**
</span> * @event itemexpand
* @inheritdoc Ext.data.TreeStore#expand
*/
expand: me.createRelayer('itemexpand', [0, 1]),
<span id='Ext-tree-Panel-event-itemcollapse'> /**
</span> * @event itemcollapse
* @inheritdoc Ext.data.TreeStore#collapse
*/
collapse: me.createRelayer('itemcollapse', [0, 1]),
<span id='Ext-tree-Panel-event-beforeitemexpand'> /**
</span> * @event beforeitemexpand
* @inheritdoc Ext.data.TreeStore#beforeexpand
*/
beforeexpand: me.createRelayer('beforeitemexpand', [0, 1]),
<span id='Ext-tree-Panel-event-beforeitemcollapse'> /**
</span> * @event beforeitemcollapse
* @inheritdoc Ext.data.TreeStore#beforecollapse
*/
beforecollapse: me.createRelayer('beforeitemcollapse', [0, 1])
});
// TreeStore must have an upward link to the TreePanel so that nodes can find their owning tree in NodeInterface.getOwnerTree
store.ownerTree = me;
if (!initial) {
me.view.setRootNode(me.getRootNode());
}
},
<span id='Ext-tree-Panel-method-unbindStore'> // @private
</span> // TODO: Decide whether it is possible to reconfigure a TreePanel.
unbindStore: function() {
var me = this,
store = me.store;
if (store) {
Ext.destroy(me.storeListeners, me.storeRelayers, me.storeRelayers1);
delete store.ownerTree;
}
},
<span id='Ext-tree-Panel-method-onClear'> onClear: function(){
</span> this.view.onClear();
},
<span id='Ext-tree-Panel-method-setRootNode'> /**
</span> * Sets root node of this tree.
* @param {Ext.data.Model/Ext.data.NodeInterface/Object} root
* @return {Ext.data.NodeInterface} The new root
*/
setRootNode: function() {
return this.store.setRootNode.apply(this.store, arguments);
},
<span id='Ext-tree-Panel-method-getRootNode'> /**
</span> * Returns the root node for this tree.
* @return {Ext.data.NodeInterface}
*/
getRootNode: function() {
return this.store.getRootNode();
},
<span id='Ext-tree-Panel-method-onRootChange'> onRootChange: function(root) {
</span> this.view.setRootNode(root);
},
<span id='Ext-tree-Panel-method-getChecked'> /**
</span> * Retrieve an array of checked records.
* @return {Ext.data.NodeInterface[]} An array containing the checked records
*/
getChecked: function() {
return this.getView().getChecked();
},
<span id='Ext-tree-Panel-method-isItemChecked'> isItemChecked: function(rec) {
</span> return rec.get('checked');
},
<span id='Ext-tree-Panel-method-expandNode'> /**
</span> * Expands a record that is loaded in the tree.
* @param {Ext.data.Model} record The record to expand
* @param {Boolean} [deep] True to expand nodes all the way down the tree hierarchy.
* @param {Function} [callback] The function to run after the expand is completed
* @param {Object} [scope] The scope of the callback function.
*/
expandNode: function(record, deep, callback, scope) {
return this.getView().expand(record, deep, callback, scope || this);
},
<span id='Ext-tree-Panel-method-collapseNode'> /**
</span> * Collapses a record that is loaded in the tree.
* @param {Ext.data.Model} record The record to collapse
* @param {Boolean} [deep] True to collapse nodes all the way up the tree hierarchy.
* @param {Function} [callback] The function to run after the collapse is completed
* @param {Object} [scope] The scope of the callback function.
*/
collapseNode: function(record, deep, callback, scope) {
return this.getView().collapse(record, deep, callback, scope || this);
},
<span id='Ext-tree-Panel-method-expandAll'> /**
</span> * Expand all nodes
* @param {Function} [callback] A function to execute when the expand finishes.
* @param {Object} [scope] The scope of the callback function
*/
expandAll : function(callback, scope) {
var me = this,
root = me.getRootNode(),
animate = me.enableAnimations;
if (root) {
if (!animate) {
Ext.suspendLayouts();
}
root.expand(true, callback, scope || me);
if (!animate) {
Ext.resumeLayouts(true);
}
}
},
<span id='Ext-tree-Panel-method-collapseAll'> /**
</span> * Collapse all nodes
* @param {Function} [callback] A function to execute when the collapse finishes.
* @param {Object} [scope] The scope of the callback function
*/
collapseAll : function(callback, scope) {
var me = this,
root = me.getRootNode(),
animate = me.enableAnimations,
view = me.getView();
if (root) {
if (!animate) {
Ext.suspendLayouts();
}
scope = scope || me;
if (view.rootVisible) {
root.collapse(true, callback, scope);
} else {
root.collapseChildren(true, callback, scope);
}
if (!animate) {
Ext.resumeLayouts(true);
}
}
},
<span id='Ext-tree-Panel-method-expandPath'> /**
</span> * Expand the tree to the path of a particular node.
* @param {String} path The path to expand. The path should include a leading separator.
* @param {String} [field] The field to get the data from. Defaults to the model idProperty.
* @param {String} [separator='/'] A separator to use.
* @param {Function} [callback] A function to execute when the expand finishes. The callback will be called with
* (success, lastNode) where success is if the expand was successful and lastNode is the last node that was expanded.
* @param {Object} [scope] The scope of the callback function
*/
expandPath: function(path, field, separator, callback, scope) {
var me = this,
current = me.getRootNode(),
index = 1,
view = me.getView(),
keys,
expander;
field = field || me.getRootNode().idProperty;
separator = separator || '/';
if (Ext.isEmpty(path)) {
Ext.callback(callback, scope || me, [false, null]);
return;
}
keys = path.split(separator);
if (current.get(field) != keys[1]) {
// invalid root
Ext.callback(callback, scope || me, [false, current]);
return;
}
expander = function(){
if (++index === keys.length) {
Ext.callback(callback, scope || me, [true, current]);
return;
}
var node = current.findChild(field, keys[index]);
if (!node) {
Ext.callback(callback, scope || me, [false, current]);
return;
}
current = node;
current.expand(false, expander);
};
current.expand(false, expander);
},
<span id='Ext-tree-Panel-method-selectPath'> /**
</span> * Expand the tree to the path of a particular node, then select it.
* @param {String} path The path to select. The path should include a leading separator.
* @param {String} [field] The field to get the data from. Defaults to the model idProperty.
* @param {String} [separator='/'] A separator to use.
* @param {Function} [callback] A function to execute when the select finishes. The callback will be called with
* (bSuccess, oLastNode) where bSuccess is if the select was successful and oLastNode is the last node that was expanded.
* @param {Object} [scope] The scope of the callback function
*/
selectPath: function(path, field, separator, callback, scope) {
var me = this,
root,
keys,
last;
field = field || me.getRootNode().idProperty;
separator = separator || '/';
keys = path.split(separator);
last = keys.pop();
if (keys.length > 1) {
me.expandPath(keys.join(separator), field, separator, function(success, node){
var lastNode = node;
if (success && node) {
node = node.findChild(field, last);
if (node) {
me.getSelectionModel().select(node);
Ext.callback(callback, scope || me, [true, node]);
return;
}
}
Ext.callback(callback, scope || me, [false, lastNode]);
}, me);
} else {
root = me.getRootNode();
if (root.getId() === last) {
me.getSelectionModel().select(root);
Ext.callback(callback, scope || me, [true, root]);
} else {
Ext.callback(callback, scope || me, [false, null]);
}
}
}
});
</pre>
</body>
</html>
| abarry/sf2-extjs | web/bundles/sfrdemosf2extjs/js/ext-4.2.1.883/docs/source/Panel6.html | HTML | mit | 22,775 |
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<h1>PixiShader Class</h1>
<div class="box meta">
<div class="foundat">
Defined in: <a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l6"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:6</code></a>
</div>
Module: <a href="../modules/PIXI.html">PIXI</a>
</div>
<div class="box intro">
</div>
<div class="constructor">
<h2>Constructor</h2>
<div id="method_PixiShader" class="method item">
<h3 class="name"><code>PixiShader</code></h3>
<span class="paren">()</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l6"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:6</code></a>
</p>
</div>
<div class="description">
</div>
</div>
</div>
<div id="classdocs" class="tabview">
<ul class="api-class-tabs">
<li class="api-class-tab index"><a href="#index">Index</a></li>
<li class="api-class-tab methods"><a href="#methods">Methods</a></li>
<li class="api-class-tab properties"><a href="#properties">Properties</a></li>
</ul>
<div>
<div id="index" class="api-class-tabpanel index">
<h2 class="off-left">Item Index</h2>
<div class="index-section methods">
<h3>Methods</h3>
<ul class="index-list methods">
<li class="index-item method">
<a href="#method_destroy">destroy</a>
</li>
<li class="index-item method">
<a href="#method_init">init</a>
</li>
<li class="index-item method">
<a href="#method_initSampler2D">initSampler2D</a>
</li>
<li class="index-item method">
<a href="#method_initUniforms">initUniforms</a>
</li>
<li class="index-item method">
<a href="#method_syncUniforms">syncUniforms</a>
</li>
</ul>
</div>
<div class="index-section properties">
<h3>Properties</h3>
<ul class="index-list properties">
<li class="index-item property">
<a href="#property_defaultVertexSrc">defaultVertexSrc</a>
</li>
<li class="index-item property">
<a href="#property_fragmentSrc - The fragment shader.">fragmentSrc - The fragment shader.</a>
</li>
<li class="index-item property">
<a href="#property_gl">gl</a>
</li>
<li class="index-item property">
<a href="#property_program - The WebGL program.">program - The WebGL program.</a>
</li>
<li class="index-item property">
<a href="#property_textureCount - A local texture counter for multi-texture shaders.">textureCount - A local texture counter for multi-texture shaders.</a>
</li>
</ul>
</div>
</div>
<div id="methods" class="api-class-tabpanel">
<h2 class="off-left">Methods</h2>
<div id="method_destroy" class="method item">
<h3 class="name"><code>destroy</code></h3>
<span class="paren">()</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l303"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:303</code></a>
</p>
</div>
<div class="description">
<p>Destroys the shader</p>
</div>
</div>
<div id="method_init" class="method item">
<h3 class="name"><code>init</code></h3>
<span class="paren">()</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l46"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:46</code></a>
</p>
</div>
<div class="description">
<p>Initialises the shader</p>
</div>
</div>
<div id="method_initSampler2D" class="method item">
<h3 class="name"><code>initSampler2D</code></h3>
<span class="paren">()</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l171"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:171</code></a>
</p>
</div>
<div class="description">
<p>Initialises a Sampler2D uniform (which may only be available later on after initUniforms once the texture has loaded)</p>
</div>
</div>
<div id="method_initUniforms" class="method item">
<h3 class="name"><code>initUniforms</code></h3>
<span class="paren">()</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l98"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:98</code></a>
</p>
</div>
<div class="description">
<p>Initialises the shader uniform values.
Uniforms are specified in the GLSL_ES Specification: <a href="http://www.khronos.org/registry/webgl/specs/latest/1.0/">http://www.khronos.org/registry/webgl/specs/latest/1.0/</a>
<a href="http://www.khronos.org/registry/gles/specs/2.0/GLSL_ES_Specification_1.0.17.pdf">http://www.khronos.org/registry/gles/specs/2.0/GLSL_ES_Specification_1.0.17.pdf</a></p>
</div>
</div>
<div id="method_syncUniforms" class="method item">
<h3 class="name"><code>syncUniforms</code></h3>
<span class="paren">()</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l246"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:246</code></a>
</p>
</div>
<div class="description">
<p>Updates the shader uniform values.</p>
</div>
</div>
</div>
<div id="properties" class="api-class-tabpanel">
<h2 class="off-left">Properties</h2>
<div id="property_defaultVertexSrc" class="property item">
<h3 class="name"><code>defaultVertexSrc</code></h3>
<span class="type">String</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l316"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:316</code></a>
</p>
</div>
<div class="description">
<p>The Default Vertex shader source</p>
</div>
</div>
<div id="property_fragmentSrc - The fragment shader." class="property item">
<h3 class="name"><code>fragmentSrc - The fragment shader.</code></h3>
<span class="type">Array</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l23"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:23</code></a>
</p>
</div>
<div class="description">
</div>
</div>
<div id="property_gl" class="property item">
<h3 class="name"><code>gl</code></h3>
<span class="type">WebGLContext</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l12"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:12</code></a>
</p>
</div>
<div class="description">
</div>
</div>
<div id="property_program - The WebGL program." class="property item">
<h3 class="name"><code>program - The WebGL program.</code></h3>
<span class="type">Any</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l18"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:18</code></a>
</p>
</div>
<div class="description">
</div>
</div>
<div id="property_textureCount - A local texture counter for multi-texture shaders." class="property item">
<h3 class="name"><code>textureCount - A local texture counter for multi-texture shaders.</code></h3>
<span class="type">Number</span>
<div class="meta">
<p>
Defined in
<a href="../files/src_pixi_renderers_webgl_shaders_PixiShader.js.html#l36"><code>src/pixi/renderers/webgl/shaders/PixiShader.js:36</code></a>
</p>
</div>
<div class="description">
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<script src="../assets/vendor/prettify/prettify-min.js"></script>
<script>prettyPrint();</script>
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</body>
</html>
| noffle/pixi.js | docs/classes/PixiShader.html | HTML | mit | 21,860 |
<!DOCTYPE html>
<title>Flex gaps</title>
<link rel="author" title="David Grogan" href="mailto:dgrogan@chromium.org">
<link rel="help" href="https://drafts.csswg.org/css-flexbox/#algo-line-break">
<link rel="help" href="https://drafts.csswg.org/css-align/#gaps">
<link rel="match" href="../reference/ref-filled-green-100px-square.xht">
<meta name="assert" content="Gaps are respected when gathering items into lines for row flexboxes." />
<style>
.item {
width: 100px;
height: 50px;
flex: 0 0 auto;
background: green;
}
#reference-overlapped-red {
position: absolute;
background-color: red;
width: 100px;
height: 100px;
z-index: -1;
}
</style>
<p>Test passes if there is a filled green square and <strong>no red</strong>.</p>
<div id=reference-overlapped-red></div>
<div style="display: flex; width: 200px; column-gap: 50px; flex-flow: row wrap">
<div class=item></div>
<div class=item></div>
</div>
| chromium/chromium | third_party/blink/web_tests/external/wpt/css/css-flexbox/gap-011.html | HTML | bsd-3-clause | 925 |
<!DOCTYPE HTML>
<!--
Any copyright is dedicated to the Public Domain.
http://creativecommons.org/publicdomain/zero/1.0/
-->
<html><head>
<meta charset="utf-8">
<title>Reference: Masonry layout intrinsic sizing</title>
<link rel="author" title="Mats Palmgren" href="mailto:mats@mozilla.com">
<link rel="stylesheet" type="text/css" href="/fonts/ahem.css">
<style>
html,body {
color:black; background-color:white; font:15px/1 Ahem; padding:0; margin:0;
}
grid {
display: inline-grid;
gap: 1px 2px;
grid-auto-flow: column;
border: 1px solid;
padding: 0 1px 0 2px;
vertical-align: top;
}
item {
background-color: #444;
color: blue;
writing-mode: vertical-lr;
}
</style>
</head>
<body>
<grid style="grid-template-rows: 3ch repeat(3,1ch)">
<item style="height:3ch">1</item>
<item>2</item>
<item>3</item>
<item>4</item>
<item>5 5</item>
<item>6</item>
<item>7</item>
<item>8</item>
<item>9 9</item>
</grid>
<grid style="grid-template-rows: repeat(4,1ch)">
<item>1</item>
<item>2</item>
<item>3</item>
<item>4</item>
<item style="height:3ch">5 5</item>
<item>6</item>
<item>7</item>
<item>8</item>
<item>9 9</item>
</grid>
<grid style="grid-template-rows: 3ch repeat(3,1ch)">
<item>1</item>
<item>2</item>
<item>3</item>
<item>4</item>
<item style="height:3ch; grid-row:1">5 5</item>
<item>6</item>
<item>7</item>
<item>8</item>
<item>9 9</item>
</grid>
<grid style="grid-template-rows: 3ch repeat(3,1ch)">
<item>1</item>
<item>2</item>
<item>3</item>
<item>4</item>
<item style="height:3ch; grid-column:1">5 5</item>
<item>6</item>
<item>7</item>
<item>8</item>
<item>9 9</item>
</grid>
</body>
</html>
| scheib/chromium | third_party/blink/web_tests/external/wpt/css/css-grid/masonry/tentative/masonry-intrinsic-sizing-005-ref.html | HTML | bsd-3-clause | 1,714 |
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<pre class="prettyprint lang-js"><span id='Ext-layout-container-Box'>/**
</span> * Base Class for HBoxLayout and VBoxLayout Classes. Generally it should not need to be used directly.
*/
Ext.define('Ext.layout.container.Box', {
/* Begin Definitions */
alias: ['layout.box'],
extend: 'Ext.layout.container.Container',
alternateClassName: 'Ext.layout.BoxLayout',
requires: [
'Ext.layout.container.boxOverflow.None',
'Ext.layout.container.boxOverflow.Menu',
'Ext.layout.container.boxOverflow.Scroller',
'Ext.util.Format',
'Ext.dd.DragDropManager'
],
/* End Definitions */
<span id='Ext-layout-container-Box-cfg-defaultMargins'> /**
</span> * @cfg {Object} defaultMargins
* If the individual contained items do not have a margins property specified or margin specified via CSS, the
* default margins from this property will be applied to each item.
*
* This property may be specified as an object containing margins to apply in the format:
*
* {
* top: (top margin),
* right: (right margin),
* bottom: (bottom margin),
* left: (left margin)
* }
*
* This property may also be specified as a string containing space-separated, numeric margin values. The order of
* the sides associated with each value matches the way CSS processes margin values:
*
* - If there is only one value, it applies to all sides.
* - If there are two values, the top and bottom borders are set to the first value and the right and left are
* set to the second.
* - If there are three values, the top is set to the first value, the left and right are set to the second,
* and the bottom is set to the third.
* - If there are four values, they apply to the top, right, bottom, and left, respectively.
*/
defaultMargins: {
top: 0,
right: 0,
bottom: 0,
left: 0
},
<span id='Ext-layout-container-Box-cfg-padding'> /**
</span> * @cfg {String} padding
* Sets the padding to be applied to all child items managed by this layout.
*
* This property must be specified as a string containing space-separated, numeric padding values. The order of the
* sides associated with each value matches the way CSS processes padding values:
*
* - If there is only one value, it applies to all sides.
* - If there are two values, the top and bottom borders are set to the first value and the right and left are
* set to the second.
* - If there are three values, the top is set to the first value, the left and right are set to the second,
* and the bottom is set to the third.
* - If there are four values, they apply to the top, right, bottom, and left, respectively.
*/
padding: 0,
<span id='Ext-layout-container-Box-cfg-pack'> /**
</span> * @cfg {String} pack
* Controls how the child items of the container are packed together. Acceptable configuration values for this
* property are:
*
* - **start** - child items are packed together at **left** (HBox) or **top** (VBox) side of container (*default**)
* - **center** - child items are packed together at **mid-width** (HBox) or **mid-height** (VBox) of container
* - **end** - child items are packed together at **right** (HBox) or **bottom** (VBox) side of container
*/
pack: 'start',
<span id='Ext-layout-container-Box-cfg-flex'> /**
</span> * @cfg {Number} flex
* This configuration option is to be applied to **child items** of the container managed by this layout. Each child
* item with a flex property will be flexed (horizontally in `hbox`, vertically in `vbox`) according to each item's
* **relative** flex value compared to the sum of all items with a flex value specified. Any child items that have
* either a `flex = 0` or `flex = undefined` will not be 'flexed' (the initial size will not be changed).
*/
flex: undefined,
<span id='Ext-layout-container-Box-cfg-stretchMaxPartner'> /**
</span> * @cfg {String/Ext.Component} stretchMaxPartner
* Allows stretchMax calculation to take into account the max perpendicular size (height for HBox layout and width
* for VBox layout) of another Box layout when calculating its maximum perpendicular child size.
*
* If specified as a string, this may be either a known Container ID, or a ComponentQuery selector which is rooted
* at this layout's Container (ie, to find a sibling, use `"^>#siblingItemId`).
*/
stretchMaxPartner: undefined,
<span id='Ext-layout-container-Box-property-alignRoundingMethod'> alignRoundingMethod: 'round',
</span>
<span id='Ext-layout-container-Box-property-type'> type: 'box',
</span><span id='Ext-layout-container-Box-property-scrollOffset'> scrollOffset: 0,
</span><span id='Ext-layout-container-Box-cfg-itemCls'> itemCls: Ext.baseCSSPrefix + 'box-item',
</span><span id='Ext-layout-container-Box-property-targetCls'> targetCls: Ext.baseCSSPrefix + 'box-layout-ct',
</span><span id='Ext-layout-container-Box-property-targetElCls'> targetElCls: Ext.baseCSSPrefix + 'box-target',
</span><span id='Ext-layout-container-Box-property-innerCls'> innerCls: Ext.baseCSSPrefix + 'box-inner',
</span>
<span id='Ext-layout-container-Box-property-availableSpaceOffset'> // availableSpaceOffset is used to adjust the availableWidth, typically used
</span> // to reserve space for a scrollbar
availableSpaceOffset: 0,
<span id='Ext-layout-container-Box-property-reserveOffset'> // whether or not to reserve the availableSpaceOffset in layout calculations
</span> reserveOffset: true,
<span id='Ext-layout-container-Box-property-manageMargins'> manageMargins: true,
</span>
<span id='Ext-layout-container-Box-property-createsInnerCt'> createsInnerCt: true,
</span>
<span id='Ext-layout-container-Box-property-childEls'> childEls: [
</span> 'innerCt',
'targetEl'
],
<span id='Ext-layout-container-Box-property-renderTpl'> renderTpl: [
</span> '{%var oc,l=values.$comp.layout,oh=l.overflowHandler;',
'if (oh.getPrefixConfig!==Ext.emptyFn) {',
'if(oc=oh.getPrefixConfig())dh.generateMarkup(oc, out)',
'}%}',
'<div id="{ownerId}-innerCt" class="{[l.innerCls]} {[oh.getOverflowCls()]}" role="presentation">',
'<div id="{ownerId}-targetEl" class="{targetElCls}">',
'{%this.renderBody(out, values)%}',
'</div>',
'</div>',
'{%if (oh.getSuffixConfig!==Ext.emptyFn) {',
'if(oc=oh.getSuffixConfig())dh.generateMarkup(oc, out)',
'}%}',
{
disableFormats: true,
definitions: 'var dh=Ext.DomHelper;'
}
],
<span id='Ext-layout-container-Box-method-constructor'> constructor: function(config) {
</span> var me = this,
type;
me.callParent(arguments);
// The sort function needs access to properties in this, so must be bound.
me.flexSortFn = Ext.Function.bind(me.flexSort, me);
me.initOverflowHandler();
type = typeof me.padding;
if (type == 'string' || type == 'number') {
me.padding = Ext.util.Format.parseBox(me.padding);
me.padding.height = me.padding.top + me.padding.bottom;
me.padding.width = me.padding.left + me.padding.right;
}
},
<span id='Ext-layout-container-Box-property-_percentageRe'> // Matches: `<spaces>digits[.digits]<spaces>%<spaces>`
</span> // Captures: `digits[.digits]`
_percentageRe: /^\s*(\d+(?:\.\d*)?)\s*[%]\s*$/,
<span id='Ext-layout-container-Box-method-getItemSizePolicy'> getItemSizePolicy: function (item, ownerSizeModel) {
</span> var me = this,
policy = me.sizePolicy,
align = me.align,
flex = item.flex,
key = align,
names = me.names,
width = item[names.width],
height = item[names.height],
percentageRe = me._percentageRe,
percentageWidth = percentageRe.test(width),
isStretch = (align == 'stretch'),
isStretchMax = (align == 'stretchmax'),
constrain = me.constrainAlign;
// Getting the size model is expensive, so we only want to do so if we really need it
if (!ownerSizeModel && (isStretch || flex || percentageWidth || (constrain && !isStretchMax))) {
ownerSizeModel = me.owner.getSizeModel();
}
if (isStretch) {
// If we are height.shrinkWrap, we behave as if we were stretchmax (for more
// details, see beginLayoutCycle)...
if (!percentageRe.test(height) && ownerSizeModel[names.height].shrinkWrap) {
key = 'stretchmax';
// We leave %age height as stretch since it will not participate in the
// stretchmax size calculation. This avoid running such a child in its
// shrinkWrap mode prior to supplying the calculated size.
}
} else if (!isStretchMax) {
if (percentageRe.test(height)) {
// Height %ages are calculated based on container size, so they are the
// same as align=stretch for this purpose...
key = 'stretch';
} else if (constrain && !ownerSizeModel[names.height].shrinkWrap) {
// Same functionality as stretchmax, only the max is going to be the size
// of the container, not the largest item
key = 'stretchmax';
} else {
key = '';
}
}
if (flex || percentageWidth) {
// If we are width.shrinkWrap, we won't be flexing since that requires a
// container width...
if (!ownerSizeModel[names.width].shrinkWrap) {
policy = policy.flex; // both flex and %age width are calculated
}
}
return policy[key];
},
<span id='Ext-layout-container-Box-method-flexSort'> flexSort: function (a, b) {
</span> // We need to sort the flexed items to ensure that we have
// the items with max/min width first since when we set the
// values we may have the value constrained, so we need to
// react accordingly. Precedence is given from the largest
// value through to the smallest value
var maxWidthName = this.names.maxWidth,
minWidthName = this.names.minWidth,
infiniteValue = Infinity,
aTarget = a.target,
bTarget = b.target,
result = 0,
aMin, bMin, aMax, bMax,
hasMin, hasMax;
aMax = aTarget[maxWidthName] || infiniteValue;
bMax = bTarget[maxWidthName] || infiniteValue;
aMin = aTarget[minWidthName] || 0;
bMin = bTarget[minWidthName] || 0;
hasMin = isFinite(aMin) || isFinite(bMin);
hasMax = isFinite(aMax) || isFinite(bMax);
if (hasMin || hasMax) {
if (hasMax) {
result = aMax - bMax;
}
// If the result is 0, it means either
// a) hasMax was false
// b) The max values were the same
if (result === 0 && hasMin) {
result = bMin - aMin;
}
}
return result;
},
<span id='Ext-layout-container-Box-method-isItemBoxParent'> isItemBoxParent: function (itemContext) {
</span> return true;
},
<span id='Ext-layout-container-Box-method-isItemShrinkWrap'> isItemShrinkWrap: function (item) {
</span> return true;
},
<span id='Ext-layout-container-Box-method-roundFlex'> roundFlex: function(width) {
</span> return Math.ceil(width);
},
<span id='Ext-layout-container-Box-method-beginCollapse'> /**
</span> * @private
* Called by an owning Panel before the Panel begins its collapse process.
* Most layouts will not need to override the default Ext.emptyFn implementation.
*/
beginCollapse: function(child) {
var me = this;
if (me.direction === 'vertical' && child.collapsedVertical()) {
child.collapseMemento.capture(['flex']);
delete child.flex;
} else if (me.direction === 'horizontal' && child.collapsedHorizontal()) {
child.collapseMemento.capture(['flex']);
delete child.flex;
}
},
<span id='Ext-layout-container-Box-method-beginExpand'> /**
</span> * @private
* Called by an owning Panel before the Panel begins its expand process.
* Most layouts will not need to override the default Ext.emptyFn implementation.
*/
beginExpand: function(child) {
// Restores the flex if we used to be flexed before
child.collapseMemento.restore(['flex']);
},
<span id='Ext-layout-container-Box-method-beginLayout'> beginLayout: function (ownerContext) {
</span> var me = this,
owner = me.owner,
smp = owner.stretchMaxPartner,
style = me.innerCt.dom.style,
names = me.names;
ownerContext.boxNames = names;
// this must happen before callParent to allow the overflow handler to do its work
// that can effect the childItems collection...
me.overflowHandler.beginLayout(ownerContext);
// get the contextItem for our stretchMax buddy:
if (typeof smp === 'string') {
smp = Ext.getCmp(smp) || owner.query(smp)[0];
}
ownerContext.stretchMaxPartner = smp && ownerContext.context.getCmp(smp);
me.callParent(arguments);
ownerContext.innerCtContext = ownerContext.getEl('innerCt', me);
// Capture whether the owning Container is scrolling in the parallel direction
me.scrollParallel = owner.scrollFlags[names.x];
// Capture whether the owning Container is scrolling in the perpendicular direction
me.scrollPerpendicular = owner.scrollFlags[names.y];
// If we *are* scrolling parallel, capture the scroll position of the encapsulating element
if (me.scrollParallel) {
me.scrollPos = owner.getTargetEl().dom[names.scrollLeft];
}
// Don't allow sizes burned on to the innerCt to influence measurements.
style.width = '';
style.height = '';
},
<span id='Ext-layout-container-Box-method-beginLayoutCycle'> beginLayoutCycle: function (ownerContext, firstCycle) {
</span> var me = this,
align = me.align,
names = ownerContext.boxNames,
pack = me.pack,
heightModelName = names.heightModel;
// this must happen before callParent to allow the overflow handler to do its work
// that can effect the childItems collection...
me.overflowHandler.beginLayoutCycle(ownerContext, firstCycle);
me.callParent(arguments);
// Cache several of our string concat/compare results (since width/heightModel can
// change if we are invalidated, we cannot do this in beginLayout)
ownerContext.parallelSizeModel = ownerContext[names.widthModel];
ownerContext.perpendicularSizeModel = ownerContext[heightModelName];
ownerContext.boxOptions = {
align: align = {
stretch: align == 'stretch',
stretchmax: align == 'stretchmax',
center: align == names.center,
bottom: align == names.afterY
},
pack: pack = {
center: pack == 'center',
end: pack == 'end'
}
};
// Consider an hbox w/stretch which means "assign all items the container's height".
// The spirit of this request is make all items the same height, but when shrinkWrap
// height is also requested, the height of the tallest item determines the height.
// This is exactly what the stretchmax option does, so we jiggle the flags here to
// act as if stretchmax were requested.
if (align.stretch && ownerContext.perpendicularSizeModel.shrinkWrap) {
align.stretchmax = true;
align.stretch = false;
}
// This is handy for knowing that we might need to apply height %ages
align.nostretch = !(align.stretch || align.stretchmax);
// In our example hbox, packing items to the right (end) or center can only work if
// there is a container width. So, if we are shrinkWrap, we just turn off the pack
// options for the run.
if (ownerContext.parallelSizeModel.shrinkWrap) {
pack.center = pack.end = false;
}
me.cacheFlexes(ownerContext);
// We set the width of the target el equal to the width of the innerCt
// when the layout cycle is finished, so we need to clear the width here
// to prevent the children from being crushed.
// IE needs it because of its scrollIntoView bug: https://sencha.jira.com/browse/EXTJSIV-6520
// Webkit needs it because of its mouse drag bug: https://sencha.jira.com/browse/EXTJSIV-5962
// FF needs it because of a vertical tab bug: https://sencha.jira.com/browse/EXTJSIV-8614
me.targetEl.setWidth(20000);
},
<span id='Ext-layout-container-Box-method-cacheFlexes'> /**
</span> * This method is called to (re)cache our understanding of flexes. This happens during beginLayout and may need to
* be called again if the flexes are changed during the layout (e.g., like ColumnLayout).
* @param {Object} ownerContext
* @protected
*/
cacheFlexes: function (ownerContext) {
var me = this,
names = ownerContext.boxNames,
widthModelName = names.widthModel,
heightModelName = names.heightModel,
nostretch = ownerContext.boxOptions.align.nostretch,
totalFlex = 0,
childItems = ownerContext.childItems,
i = childItems.length,
flexedItems = [],
minWidth = 0,
minWidthName = names.minWidth,
percentageRe = me._percentageRe,
percentageWidths = 0,
percentageHeights = 0,
child, childContext, flex, match;
while (i--) {
childContext = childItems[i];
child = childContext.target;
// check widthModel to see if we are the sizing layout. If so, copy the flex
// from the item to the contextItem and add it to totalFlex
//
if (childContext[widthModelName].calculated) {
childContext.flex = flex = child.flex;
if (flex) {
totalFlex += flex;
flexedItems.push(childContext);
minWidth += child[minWidthName] || 0;
} else { // a %age width...
match = percentageRe.exec(child[names.width]);
childContext.percentageParallel = parseFloat(match[1]) / 100;
++percentageWidths;
}
}
// the above means that "childContext.flex" is properly truthy/falsy, which is
// often times quite convenient...
if (nostretch && childContext[heightModelName].calculated) {
// the only reason we would be calculated height in this case is due to a
// height %age...
match = percentageRe.exec(child[names.height]);
childContext.percentagePerpendicular = parseFloat(match[1]) / 100;
++percentageHeights;
}
}
ownerContext.flexedItems = flexedItems;
ownerContext.flexedMinSize = minWidth;
ownerContext.totalFlex = totalFlex;
ownerContext.percentageWidths = percentageWidths;
ownerContext.percentageHeights = percentageHeights;
// The flexed boxes need to be sorted in ascending order of maxSize to work properly
// so that unallocated space caused by maxWidth being less than flexed width can be
// reallocated to subsequent flexed boxes.
Ext.Array.sort(flexedItems, me.flexSortFn);
},
<span id='Ext-layout-container-Box-method-calculate'> calculate: function(ownerContext) {
</span> var me = this,
targetSize = me.getContainerSize(ownerContext),
names = ownerContext.boxNames,
state = ownerContext.state,
plan = state.boxPlan || (state.boxPlan = {}),
targetContext = ownerContext.targetContext;
plan.targetSize = targetSize;
// If we are not widthModel.shrinkWrap, we need the width before we can lay out boxes:
if (!ownerContext.parallelSizeModel.shrinkWrap && !targetSize[names.gotWidth]) {
me.done = false;
return;
}
if (!state.parallelDone) {
state.parallelDone = me.calculateParallel(ownerContext, names, plan);
}
if (!state.perpendicularDone) {
state.perpendicularDone = me.calculatePerpendicular(ownerContext, names, plan);
}
if (state.parallelDone && state.perpendicularDone) {
// Fix for left and right docked Components in a dock component layout. This is for docked Headers and docked Toolbars.
// Older Microsoft browsers do not size a position:absolute element's width to match its content.
// So in this case, in the publishInnerCtSize method we may need to adjust the size of the owning Container's element explicitly based upon
// the discovered max width. So here we put a calculatedWidth property in the metadata to facilitate this.
if (me.owner.dock && (Ext.isIE7m || Ext.isIEQuirks) && !me.owner.width && !me.horizontal) {
plan.isIEVerticalDock = true;
plan.calculatedWidth = plan.maxSize + ownerContext.getPaddingInfo().width + ownerContext.getFrameInfo().width;
if (targetContext !== ownerContext) {
// targetContext can have additional padding, e.g. vertically
// oriented toolbar body element has a few px of left or right padding
// to make room for the tab strip.
plan.calculatedWidth += targetContext.getPaddingInfo().width;
}
}
me.publishInnerCtSize(ownerContext, me.reserveOffset ? me.availableSpaceOffset : 0);
// Calculate stretchmax only if there is >1 child item, or there is a stretchMaxPartner wanting the info
if (me.done && (ownerContext.childItems.length > 1 || ownerContext.stretchMaxPartner) && ownerContext.boxOptions.align.stretchmax && !state.stretchMaxDone) {
me.calculateStretchMax(ownerContext, names, plan);
state.stretchMaxDone = true;
}
me.overflowHandler.calculate(ownerContext);
} else {
me.done = false;
}
},
<span id='Ext-layout-container-Box-method-calculateParallel'> calculateParallel: function(ownerContext, names, plan) {
</span> var me = this,
widthName = names.width,
childItems = ownerContext.childItems,
beforeXName = names.beforeX,
afterXName = names.afterX,
setWidthName = names.setWidth,
childItemsLength = childItems.length,
flexedItems = ownerContext.flexedItems,
flexedItemsLength = flexedItems.length,
pack = ownerContext.boxOptions.pack,
padding = me.padding,
containerWidth = plan.targetSize[widthName],
totalMargin = 0,
left = padding[beforeXName],
nonFlexWidth = left + padding[afterXName] + me.scrollOffset +
(me.reserveOffset ? me.availableSpaceOffset : 0),
scrollbarWidth = Ext.getScrollbarSize()[names.width],
i, childMargins, remainingWidth, remainingFlex, childContext, flex, flexedWidth,
contentWidth, mayNeedScrollbarAdjust, childWidth, percentageSpace;
// We may need to add scrollbar size to parallel size if
// Scrollbars take up space
// and we are scrolling in the perpendicular direction
// and shrinkWrapping in the parallel direction,
// and NOT stretching perpendicular dimensions to fit
// and NOT shrinkWrapping in the perpendicular direction
if (scrollbarWidth &&
me.scrollPerpendicular &&
ownerContext.parallelSizeModel.shrinkWrap &&
!ownerContext.boxOptions.align.stretch &&
!ownerContext.perpendicularSizeModel.shrinkWrap) {
// If its possible that we may need to add scrollbar size to the parallel size
// then we need to wait until the perpendicular size has been determined,
// so that we know if there is a scrollbar.
if (!ownerContext.state.perpendicularDone) {
return false;
}
mayNeedScrollbarAdjust = true;
}
// Gather the total size taken up by non-flexed items:
for (i = 0; i < childItemsLength; ++i) {
childContext = childItems[i];
childMargins = childContext.marginInfo || childContext.getMarginInfo();
totalMargin += childMargins[widthName];
if (!childContext[names.widthModel].calculated) {
childWidth = childContext.getProp(widthName);
nonFlexWidth += childWidth; // min/maxWidth safe
if (isNaN(nonFlexWidth)) {
return false;
}
}
}
nonFlexWidth += totalMargin;
if (ownerContext.percentageWidths) {
percentageSpace = containerWidth - totalMargin;
if (isNaN(percentageSpace)) {
return false;
}
for (i = 0; i < childItemsLength; ++i) {
childContext = childItems[i];
if (childContext.percentageParallel) {
childWidth = Math.ceil(percentageSpace * childContext.percentageParallel);
childWidth = childContext.setWidth(childWidth);
nonFlexWidth += childWidth;
}
}
}
// if we get here, we have all the childWidths for non-flexed items...
if (ownerContext.parallelSizeModel.shrinkWrap) {
plan.availableSpace = 0;
plan.tooNarrow = false;
} else {
plan.availableSpace = containerWidth - nonFlexWidth;
// If we're going to need space for a parallel scrollbar, then we need to redo the perpendicular measurements
plan.tooNarrow = plan.availableSpace < ownerContext.flexedMinSize;
if (plan.tooNarrow && Ext.getScrollbarSize()[names.height] && me.scrollParallel && ownerContext.state.perpendicularDone) {
ownerContext.state.perpendicularDone = false;
for (i = 0; i < childItemsLength; ++i) {
childItems[i].invalidate();
}
}
}
contentWidth = nonFlexWidth;
remainingWidth = plan.availableSpace;
remainingFlex = ownerContext.totalFlex;
// Calculate flexed item sizes:
for (i = 0; i < flexedItemsLength; i++) {
childContext = flexedItems[i];
flex = childContext.flex;
flexedWidth = me.roundFlex((flex / remainingFlex) * remainingWidth);
flexedWidth = childContext[setWidthName](flexedWidth); // constrained
// due to minWidth constraints, it may be that flexedWidth > remainingWidth
contentWidth += flexedWidth;
// Remaining space has already had margins subtracted, so just subtract size
remainingWidth = Math.max(0, remainingWidth - flexedWidth); // no negatives!
remainingFlex -= flex;
}
if (pack.center) {
left += remainingWidth / 2;
// If content is too wide to pack to center, do not allow the centering calculation to place it off the left edge.
if (left < 0) {
left = 0;
}
} else if (pack.end) {
left += remainingWidth;
}
// Assign parallel position for the boxes:
for (i = 0; i < childItemsLength; ++i) {
childContext = childItems[i];
childMargins = childContext.marginInfo; // already cached by first loop
left += childMargins[beforeXName];
childContext.setProp(names.x, left);
// We can read directly from "props.width" because we have already properly
// requested it in the calculation of nonFlexedWidths or we calculated it.
// We cannot call getProp because that would be inappropriate for flexed items
// and we don't need any extra function call overhead:
left += childMargins[afterXName] + childContext.props[widthName];
}
contentWidth += ownerContext.targetContext.getPaddingInfo()[widthName];
// Stash the contentWidth on the state so that it can always be accessed later in the calculation
ownerContext.state.contentWidth = contentWidth;
// if there is perpendicular overflow, the published parallel content size includes
// the size of the perpendicular scrollbar.
if (mayNeedScrollbarAdjust &&
(ownerContext.peek(names.contentHeight) > plan.targetSize[names.height])) {
contentWidth += scrollbarWidth;
ownerContext[names.hasOverflowY] = true;
// tell the component layout to set the parallel size in the dom
ownerContext.target.componentLayout[names.setWidthInDom] = true;
// IE8 in what passes for "strict" mode will not create a scrollbar if
// there is just the *exactly correct* spare space created for it. We
// have to force that to happen once all the styles have been flushed
// to the DOM (see completeLayout):
ownerContext[names.invalidateScrollY] = Ext.isStrict && Ext.isIE8;
}
ownerContext[names.setContentWidth](contentWidth);
return true;
},
<span id='Ext-layout-container-Box-method-calculatePerpendicular'> calculatePerpendicular: function(ownerContext, names, plan) {
</span> var me = this,
heightShrinkWrap = ownerContext.perpendicularSizeModel.shrinkWrap,
targetSize = plan.targetSize,
childItems = ownerContext.childItems,
childItemsLength = childItems.length,
mmax = Math.max,
heightName = names.height,
setHeightName = names.setHeight,
beforeYName = names.beforeY,
topPositionName = names.y,
padding = me.padding,
top = padding[beforeYName],
availHeight = targetSize[heightName] - top - padding[names.afterY],
align = ownerContext.boxOptions.align,
isStretch = align.stretch, // never true if heightShrinkWrap (see beginLayoutCycle)
isStretchMax = align.stretchmax,
isCenter = align.center,
isBottom = align.bottom,
constrain = me.constrainAlign,
maxHeight = 0,
hasPercentageSizes = 0,
onBeforeInvalidateChild = me.onBeforeConstrainInvalidateChild,
onAfterInvalidateChild = me.onAfterConstrainInvalidateChild,
scrollbarHeight = Ext.getScrollbarSize().height,
childTop, i, childHeight, childMargins, diff, height, childContext,
stretchMaxPartner, stretchMaxChildren, shrinkWrapParallelOverflow,
percentagePerpendicular;
if (isStretch || ((isCenter || isBottom) && !heightShrinkWrap)) {
if (isNaN(availHeight)) {
return false;
}
}
// If the intention is to horizontally scroll child components, but the container is too narrow,
// then:
// if we are shrinkwrapping height:
// Set a flag because we are going to expand the height taken by the perpendicular dimension to accommodate the scrollbar
// else
// We must allow for the parallel scrollbar to intrude into the height
if (me.scrollParallel && plan.tooNarrow) {
if (heightShrinkWrap) {
shrinkWrapParallelOverflow = true;
} else {
availHeight -= scrollbarHeight;
plan.targetSize[heightName] -= scrollbarHeight;
}
}
if (isStretch) {
height = availHeight; // never heightShrinkWrap...
} else {
for (i = 0; i < childItemsLength; i++) {
childContext = childItems[i];
childMargins = (childContext.marginInfo || childContext.getMarginInfo())[heightName];
if (!(percentagePerpendicular = childContext.percentagePerpendicular)) {
childHeight = childContext.getProp(heightName);
} else {
++hasPercentageSizes;
if (heightShrinkWrap) {
// height %age items cannot contribute to maxHeight... they are going
// to be a %age of that maxHeight!
continue;
} else {
childHeight = percentagePerpendicular * availHeight - childMargins;
childHeight = childContext[names.setHeight](childHeight);
}
}
// Summary:
// 1) Not shrink wrapping height, so the height is not determined by the children
// 2) Constrain is set
// 3) The child item is shrink wrapping
// 4) It execeeds the max
if (!heightShrinkWrap && constrain && childContext[names.heightModel].shrinkWrap && childHeight > availHeight) {
childContext.invalidate({
before: onBeforeInvalidateChild,
after: onAfterInvalidateChild,
layout: me,
childHeight: availHeight,
names: names
});
// By invalidating the height, it could mean the width can change, so we need
// to recalculate in the parallel direction.
ownerContext.state.parallelDone = false;
}
// Max perpendicular measurement (used for stretchmax) must take the min perpendicular size of each child into account in case any fall short.
if (isNaN(maxHeight = mmax(maxHeight, childHeight + childMargins,
childContext.target[names.minHeight] || 0))) {
return false; // heightShrinkWrap || isCenter || isStretchMax ??
}
}
// If there is going to be a parallel scrollbar maxHeight must include it to the outside world.
// ie: a stretchmaxPartner, and the setContentHeight
if (shrinkWrapParallelOverflow) {
maxHeight += scrollbarHeight;
ownerContext[names.hasOverflowX] = true;
// tell the component layout to set the perpendicular size in the dom
ownerContext.target.componentLayout[names.setHeightInDom] = true;
// IE8 in what passes for "strict" mode will not create a scrollbar if
// there is just the *exactly correct* spare space created for it. We
// have to force that to happen once all the styles have been flushed
// to the DOM (see completeLayout):
ownerContext[names.invalidateScrollX] = Ext.isStrict && Ext.isIE8;
}
// If we are associated with another box layout, grab its maxChildHeight
// This must happen before we calculate and publish our contentHeight
stretchMaxPartner = ownerContext.stretchMaxPartner;
if (stretchMaxPartner) {
// Publish maxChildHeight as soon as it has been calculated for our partner:
ownerContext.setProp('maxChildHeight', maxHeight);
stretchMaxChildren = stretchMaxPartner.childItems;
// Only wait for maxChildHeight if our partner has visible items:
if (stretchMaxChildren && stretchMaxChildren.length) {
maxHeight = mmax(maxHeight, stretchMaxPartner.getProp('maxChildHeight'));
if (isNaN(maxHeight)) {
return false;
}
}
}
ownerContext[names.setContentHeight](maxHeight + me.padding[heightName] +
ownerContext.targetContext.getPaddingInfo()[heightName]);
// We have to publish the contentHeight with the additional scrollbarHeight
// to encourage our container to accomodate it, but we must remove the height
// of the scrollbar as we go to sizing or centering the children.
if (shrinkWrapParallelOverflow) {
maxHeight -= scrollbarHeight;
}
plan.maxSize = maxHeight;
if (isStretchMax) {
height = maxHeight;
} else if (isCenter || isBottom || hasPercentageSizes) {
if (constrain) {
height = heightShrinkWrap ? maxHeight : availHeight;
} else {
height = heightShrinkWrap ? maxHeight : mmax(availHeight, maxHeight);
}
// When calculating a centered position within the content box of the innerCt,
// the width of the borders must be subtracted from the size to yield the
// space available to center within. The publishInnerCtSize method explicitly
// adds the border widths to the set size of the innerCt.
height -= ownerContext.innerCtContext.getBorderInfo()[heightName];
}
}
for (i = 0; i < childItemsLength; i++) {
childContext = childItems[i];
childMargins = childContext.marginInfo || childContext.getMarginInfo();
childTop = top + childMargins[beforeYName];
if (isStretch) {
childContext[setHeightName](height - childMargins[heightName]);
} else {
percentagePerpendicular = childContext.percentagePerpendicular;
if (heightShrinkWrap && percentagePerpendicular) {
childMargins = childContext.marginInfo || childContext.getMarginInfo();
childHeight = percentagePerpendicular * height - childMargins[heightName];
childHeight = childContext.setHeight(childHeight);
}
if (isCenter) {
diff = height - childContext.props[heightName];
if (diff > 0) {
childTop = top + Math[me.alignRoundingMethod](diff / 2);
}
} else if (isBottom) {
childTop = mmax(0, height - childTop - childContext.props[heightName]);
}
}
childContext.setProp(topPositionName, childTop);
}
return true;
},
<span id='Ext-layout-container-Box-method-onBeforeConstrainInvalidateChild'> onBeforeConstrainInvalidateChild: function(childContext, options){
</span> // NOTE: No "this" pointer in here...
var heightModelName = options.names.heightModel;
if (!childContext[heightModelName].constrainedMin) {
// if the child hit a min constraint, it needs to be at its configured size, so
// we leave the sizeModel alone
childContext[heightModelName] = Ext.layout.SizeModel.calculated;
}
},
<span id='Ext-layout-container-Box-method-onAfterConstrainInvalidateChild'> onAfterConstrainInvalidateChild: function(childContext, options){
</span> // NOTE: No "this" pointer in here...
var names = options.names;
// We use 0 here because we know the size exceeds the available size.
// This was chosen on purpose, even for align: 'bottom', because it doesn't
// make practical sense to place the item at the bottom and then have it overflow
// over the top of the container, since it's not possible to scroll to it. As such,
// we always put the component at the top to follow normal document flow.
childContext.setProp(names.beforeY, 0);
if (childContext[names.heightModel].calculated) {
childContext[names.setHeight](options.childHeight);
}
},
<span id='Ext-layout-container-Box-method-calculateStretchMax'> calculateStretchMax: function (ownerContext, names, plan) {
</span> var me = this,
heightName = names.height,
widthName = names.width,
childItems = ownerContext.childItems,
length = childItems.length,
height = plan.maxSize,
onBeforeStretchMaxInvalidateChild = me.onBeforeStretchMaxInvalidateChild,
onAfterStretchMaxInvalidateChild = me.onAfterStretchMaxInvalidateChild,
childContext, props, i, childHeight;
for (i = 0; i < length; ++i) {
childContext = childItems[i];
props = childContext.props;
childHeight = height - childContext.getMarginInfo()[heightName];
if (childHeight != props[heightName] || // if (wrong height ...
childContext[names.heightModel].constrained) { // ...or needs invalidation)
// When we invalidate a child, since we won't be around to size or position
// it, we include an after callback that will be run after the invalidate
// that will (re)do that work. The good news here is that we can read the
// results of all that from the childContext props.
//
// We also include a before callback to change the sizeModel to calculated
// prior to the layout being invoked.
childContext.invalidate({
before: onBeforeStretchMaxInvalidateChild,
after: onAfterStretchMaxInvalidateChild,
layout: me,
// passing this data avoids a 'scope' and its Function.bind
childWidth: props[widthName],
// subtract margins from the maximum value
childHeight: childHeight,
childX: props.x,
childY: props.y,
names: names
});
}
}
},
<span id='Ext-layout-container-Box-method-onBeforeStretchMaxInvalidateChild'> onBeforeStretchMaxInvalidateChild: function (childContext, options) {
</span> // NOTE: No "this" pointer in here...
var heightModelName = options.names.heightModel;
// Change the childItem to calculated (i.e., "set by ownerCt"). The component layout
// of the child can course-correct (like dock layout does for a collapsed panel),
// so we must make these changes here before that layout's beginLayoutCycle is
// called.
if (!childContext[heightModelName].constrainedMax) {
// if the child hit a max constraint, it needs to be at its configured size, so
// we leave the sizeModel alone...
childContext[heightModelName] = Ext.layout.SizeModel.calculated;
}
},
<span id='Ext-layout-container-Box-method-onAfterStretchMaxInvalidateChild'> onAfterStretchMaxInvalidateChild: function (childContext, options) {
</span> // NOTE: No "this" pointer in here...
var names = options.names,
childHeight = options.childHeight,
childWidth = options.childWidth;
childContext.setProp('x', options.childX);
childContext.setProp('y', options.childY);
if (childContext[names.heightModel].calculated) {
// We need to respect a child that is still not calculated (such as a collapsed
// panel)...
childContext[names.setHeight](childHeight);
}
if (childContext[names.widthModel].calculated) {
childContext[names.setWidth](childWidth);
}
},
<span id='Ext-layout-container-Box-method-completeLayout'> completeLayout: function(ownerContext) {
</span> var me = this,
names = ownerContext.boxNames,
invalidateScrollX = ownerContext.invalidateScrollX,
invalidateScrollY = ownerContext.invalidateScrollY,
dom, el, overflowX, overflowY, styles;
me.overflowHandler.completeLayout(ownerContext);
if (invalidateScrollX || invalidateScrollY) {
el = me.getTarget();
dom = el.dom;
styles = dom.style;
if (invalidateScrollX) {
// get computed style to see if we are 'auto'
overflowX = el.getStyle('overflowX');
if (overflowX == 'auto') {
// capture the inline style (if any) so we can restore it later:
overflowX = styles.overflowX;
styles.overflowX = 'scroll'; // force the scrollbar to appear
} else {
invalidateScrollX = false; // no work really since not 'auto'
}
}
if (invalidateScrollY) {
// get computed style to see if we are 'auto'
overflowY = el.getStyle('overflowY');
if (overflowY == 'auto') {
// capture the inline style (if any) so we can restore it later:
overflowY = styles.overflowY;
styles.overflowY = 'scroll'; // force the scrollbar to appear
} else {
invalidateScrollY = false; // no work really since not 'auto'
}
}
if (invalidateScrollX || invalidateScrollY) { // if (some form of 'auto' in play)
// force a reflow...
dom.scrollWidth;
if (invalidateScrollX) {
styles.overflowX = overflowX; // restore inline style
}
if (invalidateScrollY) {
styles.overflowY = overflowY; // restore inline style
}
}
}
// If we are scrolling parallel, restore the saved scroll position
if (me.scrollParallel) {
me.owner.getTargetEl().dom[names.scrollLeft] = me.scrollPos;
}
},
<span id='Ext-layout-container-Box-method-finishedLayout'> finishedLayout: function(ownerContext) {
</span> this.overflowHandler.finishedLayout(ownerContext);
this.callParent(arguments);
// Fix for an obscure webkit bug (EXTJSIV-5962) caused by the targetEl's 20000px
// width. We set a very large width on the targetEl at the beginning of the
// layout cycle to prevent any "crushing" effect on the child items, however
// in some cases the very large width makes it possible to scroll the innerCt
// by dragging on certain child elements. To prevent this from happening we ensure
// that the targetEl's width is the same as the innerCt.
// IE needs it because of its scrollIntoView bug: https://sencha.jira.com/browse/EXTJSIV-6520
// Webkit needs it because of its mouse drag bug: https://sencha.jira.com/browse/EXTJSIV-5962
// FF needs it because of a vertical tab bug: https://sencha.jira.com/browse/EXTJSIV-8614
this.targetEl.setWidth(ownerContext.innerCtContext.props.width);
},
<span id='Ext-layout-container-Box-method-publishInnerCtSize'> publishInnerCtSize: function(ownerContext, reservedSpace) {
</span> var me = this,
names = ownerContext.boxNames,
heightName = names.height,
widthName = names.width,
align = ownerContext.boxOptions.align,
dock = me.owner.dock,
padding = me.padding,
plan = ownerContext.state.boxPlan,
targetSize = plan.targetSize,
height = targetSize[heightName],
innerCtContext = ownerContext.innerCtContext,
innerCtWidth = (ownerContext.parallelSizeModel.shrinkWrap || (plan.tooNarrow && me.scrollParallel)
? ownerContext.state.contentWidth - ownerContext.targetContext.getPaddingInfo()[widthName]
: targetSize[widthName]) - (reservedSpace || 0),
innerCtHeight;
if (align.stretch) {
innerCtHeight = height;
} else {
innerCtHeight = plan.maxSize + padding[names.beforeY] + padding[names.afterY] + innerCtContext.getBorderInfo()[heightName];
if (!ownerContext.perpendicularSizeModel.shrinkWrap && (align.center || align.bottom)) {
innerCtHeight = Math.max(height, innerCtHeight);
}
}
innerCtContext[names.setWidth](innerCtWidth);
innerCtContext[names.setHeight](innerCtHeight);
// If unable to publish both dimensions, this layout needs to run again
if (isNaN(innerCtWidth + innerCtHeight)) {
me.done = false;
}
// If a calculated width has been found (this only happens for widthModel.shrinkWrap
// vertical docked Components in old Microsoft browsers) then, if the Component has
// not assumed the size of its content, set it to do so.
//
// We MUST pass the dirty flag to get that into the DOM, and because we are a Container
// layout, and not really supposed to perform sizing, we must also use the force flag.
if (plan.calculatedWidth && (dock == 'left' || dock == 'right')) {
// TODO: setting the owner size should be the job of the component layout.
ownerContext.setWidth(plan.calculatedWidth, true, true);
}
},
<span id='Ext-layout-container-Box-method-onRemove'> onRemove: function(comp){
</span> var me = this;
me.callParent(arguments);
if (me.overflowHandler) {
me.overflowHandler.onRemove(comp);
}
if (comp.layoutMarginCap == me.id) {
delete comp.layoutMarginCap;
}
},
<span id='Ext-layout-container-Box-method-initOverflowHandler'> /**
</span> * @private
*/
initOverflowHandler: function() {
var me = this,
handler = me.overflowHandler,
handlerType,
constructor;
if (typeof handler == 'string') {
handler = {
type: handler
};
}
handlerType = 'None';
if (handler && handler.type !== undefined) {
handlerType = handler.type;
}
constructor = Ext.layout.container.boxOverflow[handlerType];
if (constructor[me.type]) {
constructor = constructor[me.type];
}
me.overflowHandler = Ext.create('Ext.layout.container.boxOverflow.' + handlerType, me, handler);
},
<span id='Ext-layout-container-Box-method-getRenderTarget'> // Overridden method from Ext.layout.container.Container.
</span> // Used in the beforeLayout method to render all items into.
getRenderTarget: function() {
return this.targetEl;
},
<span id='Ext-layout-container-Box-method-getElementTarget'> // Overridden method from Ext.layout.container.Container.
</span> // Used by Container classes to insert special DOM elements which must exist in addition to the child components
getElementTarget: function() {
return this.innerCt;
},
<span id='Ext-layout-container-Box-property-calculateChildBox'> //<debug>
</span> calculateChildBox: Ext.deprecated(),
<span id='Ext-layout-container-Box-property-calculateChildBoxes'> calculateChildBoxes: Ext.deprecated(),
</span><span id='Ext-layout-container-Box-property-updateChildBoxes'> updateChildBoxes: Ext.deprecated(),
</span> //</debug>
<span id='Ext-layout-container-Box-method-destroy'> /**
</span> * @private
*/
destroy: function() {
Ext.destroy(this.innerCt, this.overflowHandler);
this.callParent(arguments);
},
<span id='Ext-layout-container-Box-method-getRenderData'> getRenderData: function() {
</span> var data = this.callParent();
data.targetElCls = this.targetElCls;
return data;
}
});
</pre>
</body>
</html>
| abarry/sf2-extjs | web/bundles/sfrdemosf2extjs/js/ext-4.2.1.883/docs/source/Box.html | HTML | mit | 54,498 |
{% load i18n wagtailadmin_tags %}
{% test_page_is_public page as is_public %}
{% if not page_perms %}
{% page_permissions page as page_perms %}
{% endif %}
<div class="privacy-indicator {% if is_public %}public{% else %}private{% endif %}">
{% trans "Privacy" %}
{% if page_perms.can_set_view_restrictions %}
<a href="{% url 'wagtailadmin_pages:set_privacy' page.id %}" class="status-tag primary action-set-privacy">
{# labels are shown/hidden in CSS according to the 'private' / 'public' class on view-permission-indicator #}
<span class="label-public icon icon-view">{% trans 'Public' %}</span>
<span class="label-private icon icon-no-view">{% trans 'Private' %}</span>
</a>
{% else %}
{% if is_public %}
<span class="label-public status-tag primary icon icon-view ">{% trans 'Public' %}</span>
{% else %}
<span class="label-private status-tag primary icon icon-no-view">{% trans 'Private' %}</span>
{% endif %}
{% endif %}
</div>
| mephizzle/wagtail | wagtail/wagtailadmin/templates/wagtailadmin/pages/_privacy_switch.html | HTML | bsd-3-clause | 1,056 |
<!doctype html>
<meta charset=utf-8>
<title>CSS Text test: forced breaks create preserverd leading spaces with white-space:pre-wrap</title>
<link rel="author" title="Javier Fernandez" href="mailto:jfernandez@igalia.com" />
<link rel="help" href="https://drafts.csswg.org/css-text-3/#white-space-phase-2">
<link rel="help" href="https://drafts.csswg.org/css-text-3/#white-space-property">
<link rel="help" href="https://drafts.csswg.org/css-text-3/#valdef-white-space-pre-wrap">
<link rel="match" href="reference/white-space-break-spaces-005-ref.html">
<meta name="assert" content="Preserved white space after forced breaks become leading white-spaces and should not be collapsed, honoring white-space: pre-wrap.">
<link rel="stylesheet" type="text/css" href="/fonts/ahem.css" />
<style>
div {
font: 20px/1 Ahem;
}
.ref {
position: absolute;
color: red;
z-index: -1;
}
span { color: green; }
.test {
color: green;
width: 5ch;
white-space: pre-wrap;
}
</style>
</style>
<p>Test passes if there is a <strong>filled green square</strong> and <strong>no red</strong>.</p>
<div class="ref">XXX<span>XX<br>XXX</span>XX<br><span>XXXXX<br>XXXXX<br>XXXXX</span></div>
<div class="test">XXX <!--end of line spaces intentional-->
XX</div>
| scheib/chromium | third_party/blink/web_tests/external/wpt/css/css-text/white-space/pre-wrap-leading-spaces-007.html | HTML | bsd-3-clause | 1,247 |
<div class="doc-content">
<header class="api-profile-header" >
<h2 class="md-display-1" >{{currentDoc.name}} API Documentation</h2>
</header>
<div layout="row" class="api-options-bar with-icon"></div>
<div class="api-profile-description">
<p>Provides ripple effects for md-button. See $mdInkRipple service for all possible configuration options.</p>
</div>
<div>
<section class="api-section">
<div class="api-param-section">
<h2>
Arguments
</h2>
<div class="api-param-table">
<table class="md-api-table">
<thead>
<tr>
<th>Parameter</th>
<th>Type</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr class="api-params-item">
<td style="white-space: nowrap;">
scope
<span hide show-sm>
<code class="api-type label type-hint type-hint-object">object</code></span>
</td>
<td style="white-space: nowrap;">
<code class="api-type label type-hint type-hint-object">object</code></td>
<td class="description">
<p>Scope within the current context</p>
</td>
</tr>
<tr class="api-params-item">
<td style="white-space: nowrap;">
element
<span hide show-sm>
<code class="api-type label type-hint type-hint-object">object</code></span>
</td>
<td style="white-space: nowrap;">
<code class="api-type label type-hint type-hint-object">object</code></td>
<td class="description">
<p>The element the ripple effect should be applied to</p>
</td>
</tr>
<tr class="api-params-item">
<td style="white-space: nowrap;">
options
<span hide show-sm>
<code class="api-type label type-hint type-hint-object">object</code></span>
</td>
<td style="white-space: nowrap;">
<code class="api-type label type-hint type-hint-object">object</code></td>
<td class="description">
<p>(Optional) Configuration options to override the default ripple configuration</p>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<section class="api-section">
</section>
</section>
</div>
</div>
| StephenFluin/code.material.angularjs.org | latest/partials/api/material.core/service/$mdButtonInkRipple.html | HTML | mit | 2,389 |
<!DOCTYPE html
PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html><head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<!--
This HTML was auto-generated from MATLAB code.
To make changes, update the MATLAB code and republish this document.
--><title>linearKernelDemo</title><meta name="generator" content="MATLAB 7.12"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2012-03-27"><meta name="DC.source" content="linearKernelDemo.m"><style type="text/css">
body {
background-color: white;
margin:10px;
}
h1 {
color: #990000;
font-size: x-large;
}
h2 {
color: #990000;
font-size: medium;
}
/* Make the text shrink to fit narrow windows, but not stretch too far in
wide windows. */
p,h1,h2,div.content div {
max-width: 600px;
/* Hack for IE6 */
width: auto !important; width: 600px;
}
pre.codeinput {
background: #EEEEEE;
padding: 10px;
}
@media print {
pre.codeinput {word-wrap:break-word; width:100%;}
}
span.keyword {color: #0000FF}
span.comment {color: #228B22}
span.string {color: #A020F0}
span.untermstring {color: #B20000}
span.syscmd {color: #B28C00}
pre.codeoutput {
color: #666666;
padding: 10px;
}
pre.error {
color: red;
}
p.footer {
text-align: right;
font-size: xx-small;
font-weight: lighter;
font-style: italic;
color: gray;
}
</style></head><body><div class="content"><h2>Contents</h2><div><ul><li><a href="#1">Compare different linear kernel classifiers on several datasets</a></li><li><a href="#2">Data</a></li><li><a href="#3">Models</a></li><li><a href="#4">Main</a></li></ul></div><h2>Compare different linear kernel classifiers on several datasets<a name="1"></a></h2><p>We need to use CV/ARD to pick lambda/C but at least the kernel has no hyper-params to tune...</p><pre class="codeinput"><span class="comment">%PMTKslow</span>
<span class="comment">% This file is from pmtk3.googlecode.com</span>
<span class="comment">% See also classificationShootout and classificationShootoutCvLambdaOnly</span>
clear <span class="string">all</span>
setSeed(0);
</pre><pre class="codeoutput">Warning: Using 'state' to set RANDN's
internal state causes RAND, RANDI, and RANDN
to use legacy random number generators.
</pre><h2>Data<a name="2"></a></h2><pre class="codeinput">split = 0.7;
d = 1;
<span class="keyword">if</span> 1
loadData(<span class="string">'soy'</span>) <span class="comment">% 3 classes, X is 307*35</span>
dataSets(d).X = X;
dataSets(d).y = Y;
dataSets(d).name = <span class="string">'soy'</span>;
d=d+1;
<span class="keyword">end</span>
<span class="keyword">if</span> 1
loadData(<span class="string">'fglass'</span>); <span class="comment">% 6 classes, X is 214*9</span>
X = [Xtrain; Xtest];
y = canonizeLabels([ytrain; ytest]); <span class="comment">% class 4 is missing, so relabel 1:6</span>
dataSets(d).X = X;
dataSets(d).y = y;
dataSets(d).name = <span class="string">'fglass'</span>;
d=d+1;
<span class="keyword">end</span>
<span class="keyword">if</span> 1
loadData(<span class="string">'colon'</span>) <span class="comment">% 2 class, X is 62*2000</span>
dataSets(d).X = X;
dataSets(d).y = y;
dataSets(d).name = <span class="string">'colon'</span>;
d=d+1;
<span class="keyword">end</span>
<span class="keyword">if</span> 1
loadData(<span class="string">'amlAll'</span>); <span class="comment">% 2 class, X is 72*7129</span>
X = [Xtrain; Xtest];
y = [ytrain; ytest];
dataSets(d).X = X;
dataSets(d).y = y;
dataSets(d).name = <span class="string">'amlAll'</span>;
d=d+1;
<span class="keyword">end</span>
dataNames = {dataSets.name};
nDataSets = numel(dataSets);
<span class="keyword">for</span> d=1:nDataSets
nClasses(d) = nunique(dataSets(d).y);
X = dataSets(d).X;
[nCases(d), nFeatures(d)] = size(X);
<span class="keyword">end</span>
attrNames = {<span class="string">'nClasses'</span>, <span class="string">'nFeatures'</span>, <span class="string">'nCases'</span>};
<span class="comment">%folder = fullfile(pmtk3Root(), 'data');</span>
folder = pmtk3Root();
htmlTableSimple(<span class="string">'data'</span>, [nClasses(:) nFeatures(:) nCases(:)], <span class="keyword">...</span>
<span class="string">'colNames'</span>, attrNames, <span class="string">'rowNames'</span>, dataNames, <span class="keyword">...</span>
<span class="string">'format'</span>, <span class="string">'int'</span>, <span class="string">'fname'</span>, fullfile(folder, <span class="string">'infoOnDataSets.html'</span>) );
</pre><h2>Models<a name="3"></a></h2><p>(For some reason, the path versions of SMLR and RMLR give worse results than the versions that search over a discrete grid of lambdas.)</p><pre class="codeinput"><span class="comment">%methods = {'SVM', ' RVM', 'SMLR', 'RMLR', 'SMLRpath', 'RMLRpath', 'logregL2', 'logregL1'};</span>
methods = {<span class="string">'SVM'</span>, <span class="string">'RVM'</span>, <span class="string">'SKLR'</span>, <span class="string">'RKLR'</span>, <span class="string">'L1'</span> };
nMethods = numel(methods);
</pre><h2>Main<a name="4"></a></h2><pre class="codeinput">seeds = [0,1,2];
<span class="keyword">for</span> d=1:nDataSets
X = dataSets(d).X;
y = dataSets(d).y;
<span class="keyword">for</span> s=1:numel(seeds);
setSeed(seeds(s));
[X, y] = shuffleRows(X, y);
X = rescaleData(standardizeCols(X));
N = size(X, 1);
nTrain = floor(split*N);
nTest = N - nTrain;
Xtrain = X(1:nTrain, :);
Xtest = X(nTrain+1:end, :);
ytrain = y(1:nTrain);
ytest = y(nTrain+1:end);
<span class="keyword">for</span> m=1:nMethods
method = methods{m};
tic;
<span class="keyword">switch</span> lower(method)
<span class="keyword">case</span> <span class="string">'svm'</span>
Crange = logspace(-6, 1, 20); <span class="comment">% if too small, libsvm crashes!</span>
model = svmFit(Xtrain, ytrain, <span class="string">'C'</span>, Crange, <span class="string">'kernel'</span>, <span class="string">'linear'</span>);
predFn = @(m,X) svmPredict(m,X);
chosenC(d,m,s) = model.C;
<span class="keyword">case</span> <span class="string">'rvm'</span>
model = rvmFit(Xtrain, ytrain, <span class="string">'kernelFn'</span>, @kernelLinear);
<span class="comment">%model = rvmFit(X,y, 'kernelFn', @(X1, X2)kernelRbfGamma(X1, X2, 1));</span>
predFn = @(m,X) rvmPredict(m,X);
<span class="keyword">case</span> <span class="string">'smlrpath'</span>
model = smlrFit(Xtrain, ytrain, <span class="string">'kernelFn'</span>, @kernelLinear, <span class="keyword">...</span>
<span class="string">'regType'</span>, <span class="string">'L1'</span>, <span class="string">'usePath'</span>, true);
predFn = @(m,X) smlrPredict(m,X);
<span class="keyword">case</span> {<span class="string">'smlrnopath'</span>, <span class="string">'smlr'</span>, <span class="string">'sklr'</span>}
model = smlrFit(Xtrain, ytrain, <span class="string">'kernelFn'</span>, @kernelLinear, <span class="keyword">...</span>
<span class="string">'regType'</span>, <span class="string">'L1'</span>, <span class="string">'usePath'</span>, false);
predFn = @(m,X) smlrPredict(m,X);
<span class="keyword">case</span> <span class="string">'rmlrpath'</span>
model = smlrFit(Xtrain, ytrain, <span class="string">'kernelFn'</span>, @kernelLinear, <span class="keyword">...</span>
<span class="string">'regtype'</span>, <span class="string">'L2'</span>, <span class="string">'usePath'</span>, true);
predFn = @(m,X) smlrPredict(m,X);
<span class="keyword">case</span> {<span class="string">'rmlrnopath'</span>, <span class="string">'rmlr'</span>, <span class="string">'rklr'</span>}
model = smlrFit(Xtrain, ytrain, <span class="string">'kernelFn'</span>, @kernelLinear, <span class="keyword">...</span>
<span class="string">'regtype'</span>, <span class="string">'L2'</span>, <span class="string">'usePath'</span>, false);
predFn = @(m,X) smlrPredict(m,X);
<span class="keyword">case</span> {<span class="string">'l2'</span>, <span class="string">'logregl2'</span>}
model = logregFitPathCv(Xtrain, ytrain, <span class="string">'regtype'</span>, <span class="string">'L2'</span>);
predFn = @(m,X) logregPredict(m,X);
<span class="keyword">case</span> {<span class="string">'l1'</span>, <span class="string">'logregl1'</span>}
model = logregFitPathCv(Xtrain, ytrain, <span class="string">'regtype'</span>, <span class="string">'L1'</span>);
predFn = @(m,X) logregPredict(m,X);
<span class="keyword">end</span>
trainingTime(d,m,s) = toc;
saveModel{d,m,s} = model;
tic
yHat = predFn(model, Xtest);
testingTime(d,m,s) = toc;
nerrs = sum(yHat ~= ytest);
testErrRate(d,m,s) = nerrs/nTest;
numErrors(d,m,s) = nerrs;
maxNumErrors(d) = nTest;
<span class="keyword">end</span>
<span class="keyword">end</span>
<span class="keyword">end</span>
fprintf(<span class="string">'test err\n'</span>);
numErrors
folder = fullfile(pmtk3Root(), <span class="string">'data'</span>);
htmlTableSimple(<span class="string">'data'</span>, median(testErrRate,3), <span class="string">'colNames'</span>, methods, <span class="string">'rowNames'</span>, dataNames, <span class="keyword">...</span>
<span class="string">'format'</span>, <span class="string">'float'</span>, <span class="string">'fname'</span>, fullfile(folder, <span class="string">'err.html'</span>), <span class="keyword">...</span>
<span class="string">'title'</span>, sprintf(<span class="string">'test error rate (median over %d trials)'</span>, numel(seeds)));
fprintf(<span class="string">'training time\n'</span>);
trainingTime
htmlTableSimple(<span class="string">'data'</span>, median(trainingTime,3), <span class="string">'rowNames'</span>, dataNames, <span class="string">'colNames'</span>, methods, <span class="keyword">...</span>
<span class="string">'format'</span>, <span class="string">'float'</span>, <span class="string">'fname'</span>, fullfile(folder, <span class="string">'time.html'</span>), <span class="keyword">...</span>
<span class="string">'title'</span>, sprintf(<span class="string">'training time in seconds (median over %d trials)'</span>, numel(seeds)));
<span class="keyword">for</span> d=1:nDataSets
<span class="keyword">for</span> m=1:nMethods
fprintf(<span class="string">'(%5.3f, %5.3f, %5.3f), '</span>, testErrRate(d,m,:));
<span class="keyword">end</span>
fprintf(<span class="string">'\n'</span>);
<span class="keyword">end</span>
folder = <span class="string">'C:\kmurphy\GoogleCode\pmtk3\docs\tutorial\extraFigures'</span>;
<span class="comment">%figure;</span>
<span class="keyword">for</span> d=1:nDataSets
figure;
<span class="comment">%subplot(2,2,d);</span>
M = squeeze(testErrRate(d,:,:));
boxplot(M', <span class="string">'labels'</span>, methods)
title(sprintf(<span class="string">'%s'</span>, dataNames{d}))
printPmtkFigure(sprintf(<span class="string">'linearKernelBoxplot-%s'</span>, dataNames{d}));
<span class="comment">%print(gcf, '-dpng', fullfile(folder, sprintf('linearKernelBoxplot-%s.png', dataNames{d})))</span>
ylabel(<span class="string">'test misclassification rate'</span>)
<span class="keyword">end</span>
<span class="comment">%print(gcf, '-dpng', fullfile(folder, 'linearKernelBoxplotErr.png'))</span>
<span class="comment">%figure</span>
<span class="keyword">for</span> d=1:nDataSets
figure;
<span class="comment">%subplot(2,2,d);</span>
M = squeeze(trainingTime(d,:,:));
boxplot(M', <span class="string">'labels'</span>, methods)
title(sprintf(<span class="string">'%s'</span>, dataNames{d}))
printPmtkFigure(sprintf(<span class="string">'linearKernelBoxplotTime-%s'</span>, dataNames{d}));
<span class="comment">%print(gcf, '-dpng', fullfile(folder, sprintf('linearKernelBoxplotTime-%s.png', dataNames{d})))</span>
ylabel(<span class="string">'total training time (seconds)'</span>)
<span class="keyword">end</span>
<span class="comment">%print(gcf, '-dpng', fullfile(folder, 'linearKernelBoxplotTime.png'))</span>
</pre><pre class="codeoutput">Undefined function or method 'libLinearTrain' for input arguments of type 'double'.
Error in ==> svmlibLinearFit at 20
model = libLinearTrain(y, sparse(X), options); % requires sparse matrix
Error in ==> svmFit>@(X,y,p)fitFn(X,y,p(1),p(2),kernel,fitOptions{:}) at 140
fitcore = @(X, y, p)fitFn(X, y, p(1), p(2), kernel, fitOptions{:});
Error in ==> fitCv>@(X,y)fitFn(X,y,param) at 68
[mu(m), se(m)] = cvEstimate(@(X, y) fitFn(X, y, param), predictFn, lossFn, X, y, Nfolds, 'testFolds', testFolds);
Error in ==> cvEstimate at 34
model = fitFn(Xtrain, ytrain);
Error in ==> fitCv at 68
[mu(m), se(m)] = cvEstimate(@(X, y) fitFn(X, y, param), predictFn, lossFn, X, y, Nfolds, 'testFolds', testFolds);
Error in ==> svmFit at 141
[model, varargout{1}, varargout{2}, varargout{3}] = ...
Error in ==> linearKernelDemo at 106
model = svmFit(Xtrain, ytrain, 'C', Crange, 'kernel', 'linear');
</pre><p class="footer"><br>
Published with MATLAB® 7.12<br></p></div><!--
##### SOURCE BEGIN #####
%% Compare different linear kernel classifiers on several datasets
% We need to use CV/ARD to pick lambda/C
% but at least the kernel has no hyper-params to tune...
%PMTKslow
% This file is from pmtk3.googlecode.com
% See also classificationShootout and classificationShootoutCvLambdaOnly
clear all
setSeed(0);
%% Data
split = 0.7;
d = 1;
if 1
loadData('soy') % 3 classes, X is 307*35
dataSets(d).X = X;
dataSets(d).y = Y;
dataSets(d).name = 'soy';
d=d+1;
end
if 1
loadData('fglass'); % 6 classes, X is 214*9
X = [Xtrain; Xtest];
y = canonizeLabels([ytrain; ytest]); % class 4 is missing, so relabel 1:6
dataSets(d).X = X;
dataSets(d).y = y;
dataSets(d).name = 'fglass';
d=d+1;
end
if 1
loadData('colon') % 2 class, X is 62*2000
dataSets(d).X = X;
dataSets(d).y = y;
dataSets(d).name = 'colon';
d=d+1;
end
if 1
loadData('amlAll'); % 2 class, X is 72*7129
X = [Xtrain; Xtest];
y = [ytrain; ytest];
dataSets(d).X = X;
dataSets(d).y = y;
dataSets(d).name = 'amlAll';
d=d+1;
end
dataNames = {dataSets.name};
nDataSets = numel(dataSets);
for d=1:nDataSets
nClasses(d) = nunique(dataSets(d).y);
X = dataSets(d).X;
[nCases(d), nFeatures(d)] = size(X);
end
attrNames = {'nClasses', 'nFeatures', 'nCases'};
%folder = fullfile(pmtk3Root(), 'data');
folder = pmtk3Root();
htmlTableSimple('data', [nClasses(:) nFeatures(:) nCases(:)], ...
'colNames', attrNames, 'rowNames', dataNames, ...
'format', 'int', 'fname', fullfile(folder, 'infoOnDataSets.html') );
%% Models
% (For some reason, the path versions of SMLR and RMLR
% give worse results than the versions that search over
% a discrete grid of lambdas.)
%methods = {'SVM', ' RVM', 'SMLR', 'RMLR', 'SMLRpath', 'RMLRpath', 'logregL2', 'logregL1'};
methods = {'SVM', 'RVM', 'SKLR', 'RKLR', 'L1' };
nMethods = numel(methods);
%% Main
seeds = [0,1,2];
for d=1:nDataSets
X = dataSets(d).X;
y = dataSets(d).y;
for s=1:numel(seeds);
setSeed(seeds(s));
[X, y] = shuffleRows(X, y);
X = rescaleData(standardizeCols(X));
N = size(X, 1);
nTrain = floor(split*N);
nTest = N - nTrain;
Xtrain = X(1:nTrain, :);
Xtest = X(nTrain+1:end, :);
ytrain = y(1:nTrain);
ytest = y(nTrain+1:end);
for m=1:nMethods
method = methods{m};
tic;
switch lower(method)
case 'svm'
Crange = logspace(-6, 1, 20); % if too small, libsvm crashes!
model = svmFit(Xtrain, ytrain, 'C', Crange, 'kernel', 'linear');
predFn = @(m,X) svmPredict(m,X);
chosenC(d,m,s) = model.C;
case 'rvm'
model = rvmFit(Xtrain, ytrain, 'kernelFn', @kernelLinear);
%model = rvmFit(X,y, 'kernelFn', @(X1, X2)kernelRbfGamma(X1, X2, 1));
predFn = @(m,X) rvmPredict(m,X);
case 'smlrpath'
model = smlrFit(Xtrain, ytrain, 'kernelFn', @kernelLinear, ...
'regType', 'L1', 'usePath', true);
predFn = @(m,X) smlrPredict(m,X);
case {'smlrnopath', 'smlr', 'sklr'}
model = smlrFit(Xtrain, ytrain, 'kernelFn', @kernelLinear, ...
'regType', 'L1', 'usePath', false);
predFn = @(m,X) smlrPredict(m,X);
case 'rmlrpath'
model = smlrFit(Xtrain, ytrain, 'kernelFn', @kernelLinear, ...
'regtype', 'L2', 'usePath', true);
predFn = @(m,X) smlrPredict(m,X);
case {'rmlrnopath', 'rmlr', 'rklr'}
model = smlrFit(Xtrain, ytrain, 'kernelFn', @kernelLinear, ...
'regtype', 'L2', 'usePath', false);
predFn = @(m,X) smlrPredict(m,X);
case {'l2', 'logregl2'}
model = logregFitPathCv(Xtrain, ytrain, 'regtype', 'L2');
predFn = @(m,X) logregPredict(m,X);
case {'l1', 'logregl1'}
model = logregFitPathCv(Xtrain, ytrain, 'regtype', 'L1');
predFn = @(m,X) logregPredict(m,X);
end
trainingTime(d,m,s) = toc;
saveModel{d,m,s} = model;
tic
yHat = predFn(model, Xtest);
testingTime(d,m,s) = toc;
nerrs = sum(yHat ~= ytest);
testErrRate(d,m,s) = nerrs/nTest;
numErrors(d,m,s) = nerrs;
maxNumErrors(d) = nTest;
end
end
end
fprintf('test err\n');
numErrors
folder = fullfile(pmtk3Root(), 'data');
htmlTableSimple('data', median(testErrRate,3), 'colNames', methods, 'rowNames', dataNames, ...
'format', 'float', 'fname', fullfile(folder, 'err.html'), ...
'title', sprintf('test error rate (median over %d trials)', numel(seeds)));
fprintf('training time\n');
trainingTime
htmlTableSimple('data', median(trainingTime,3), 'rowNames', dataNames, 'colNames', methods, ...
'format', 'float', 'fname', fullfile(folder, 'time.html'), ...
'title', sprintf('training time in seconds (median over %d trials)', numel(seeds)));
for d=1:nDataSets
for m=1:nMethods
fprintf('(%5.3f, %5.3f, %5.3f), ', testErrRate(d,m,:));
end
fprintf('\n');
end
folder = 'C:\kmurphy\GoogleCode\pmtk3\docs\tutorial\extraFigures';
%figure;
for d=1:nDataSets
figure;
%subplot(2,2,d);
M = squeeze(testErrRate(d,:,:));
boxplot(M', 'labels', methods)
title(sprintf('%s', dataNames{d}))
printPmtkFigure(sprintf('linearKernelBoxplot-%s', dataNames{d}));
%print(gcf, '-dpng', fullfile(folder, sprintf('linearKernelBoxplot-%s.png', dataNames{d})))
ylabel('test misclassification rate')
end
%print(gcf, '-dpng', fullfile(folder, 'linearKernelBoxplotErr.png'))
%figure
for d=1:nDataSets
figure;
%subplot(2,2,d);
M = squeeze(trainingTime(d,:,:));
boxplot(M', 'labels', methods)
title(sprintf('%s', dataNames{d}))
printPmtkFigure(sprintf('linearKernelBoxplotTime-%s', dataNames{d}));
%print(gcf, '-dpng', fullfile(folder, sprintf('linearKernelBoxplotTime-%s.png', dataNames{d})))
ylabel('total training time (seconds)')
end
%print(gcf, '-dpng', fullfile(folder, 'linearKernelBoxplotTime.png'))
##### SOURCE END #####
--></body></html> | phoenixstar7/pmtk3 | docs/demoOutput/otherDemos/linearKernelDemo.html | HTML | mit | 19,132 |
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series : [
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<h1>operations_research::FindOneNeighbor Member List</h1>This is the complete list of members for <a class="el" href="classoperations__research_1_1FindOneNeighbor.html">operations_research::FindOneNeighbor</a>, including all inherited members.<p><table>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1DecisionBuilder.html#e7ca51f2177acc62d1a863694278ba20">Accept</a>(ModelVisitor *const visitor) const </td><td><a class="el" href="classoperations__research_1_1DecisionBuilder.html">operations_research::DecisionBuilder</a></td><td><code> [virtual]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1DecisionBuilder.html#61ba3c6d0da12541495cfea7e892ec99">AppendMonitors</a>(Solver *const solver, std::vector< SearchMonitor * > *const extras)</td><td><a class="el" href="classoperations__research_1_1DecisionBuilder.html">operations_research::DecisionBuilder</a></td><td><code> [virtual]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1BaseObject.html#bcf5669a8a0612adb1665e276efb416f">BaseObject</a>()</td><td><a class="el" href="classoperations__research_1_1BaseObject.html">operations_research::BaseObject</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1FindOneNeighbor.html#109c3947aefa0550826a1194a0cb47e8">DebugString</a>() const </td><td><a class="el" href="classoperations__research_1_1FindOneNeighbor.html">operations_research::FindOneNeighbor</a></td><td><code> [inline, virtual]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1DecisionBuilder.html#dcbdca02b7495a6f2ffcff7f77e32b1c">DecisionBuilder</a>()</td><td><a class="el" href="classoperations__research_1_1DecisionBuilder.html">operations_research::DecisionBuilder</a></td><td><code> [inline]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1FindOneNeighbor.html#af1bb246ec878f56f07b233b34ebd35b">FindOneNeighbor</a>(Assignment *const assignment, SolutionPool *const pool, LocalSearchOperator *const ls_operator, DecisionBuilder *const sub_decision_builder, const SearchLimit *const limit, const std::vector< LocalSearchFilter * > &filters)</td><td><a class="el" href="classoperations__research_1_1FindOneNeighbor.html">operations_research::FindOneNeighbor</a></td><td></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1FindOneNeighbor.html#ce2242a7334e412623a749056b5ad04c">Next</a>(Solver *const solver)</td><td><a class="el" href="classoperations__research_1_1FindOneNeighbor.html">operations_research::FindOneNeighbor</a></td><td><code> [virtual]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1BaseObject.html#9bd95fcee9e5856c6097b5dfae0b7076">~BaseObject</a>()</td><td><a class="el" href="classoperations__research_1_1BaseObject.html">operations_research::BaseObject</a></td><td><code> [inline, virtual]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1DecisionBuilder.html#fbc698929600b865c7c63ad3147758c0">~DecisionBuilder</a>()</td><td><a class="el" href="classoperations__research_1_1DecisionBuilder.html">operations_research::DecisionBuilder</a></td><td><code> [inline, virtual]</code></td></tr>
<tr class="memlist"><td><a class="el" href="classoperations__research_1_1FindOneNeighbor.html#b85ced557851815ad35973136163f9a3">~FindOneNeighbor</a>()</td><td><a class="el" href="classoperations__research_1_1FindOneNeighbor.html">operations_research::FindOneNeighbor</a></td><td><code> [inline, virtual]</code></td></tr>
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| capturePointer/or-tools | documentation/reference_manual/or-tools/src/constraint_solver/classoperations__research_1_1FindOneNeighbor-members.html | HTML | apache-2.0 | 8,309 |
<html><head>
<script>
if (window.testRunner)
testRunner.dumpAsText();
var types = [
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];
function gc()
{
if (window.GCController)
return GCController.collect();
for (var i = 0; i < 10000; i++) { // > force garbage collection (FF requires about 9K allocations before a collect)
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| wuhengzhi/chromium-crosswalk | third_party/WebKit/LayoutTests/http/tests/security/contentSecurityPolicy/1.1/frame-ancestors/frame-ancestors-nested-cross-in-same-none-block.html | HTML | bsd-3-clause | 414 |
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description("Series of tests to ensure correct results on applying different blend modes when drawing a pattern on top of an image.");
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function actualColor(x, y) {
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}
function checkBlendModeResult(i, context, sigma) {
var expectedColor = blendColors([129 / 255, 1, 129 / 255, 1], [1, 129 / 255, 129 / 255, 1], i);
var ac = "actualColor(0, 0)";
shouldBeCloseTo(ac + "[0]", expectedColor[0], sigma);
shouldBeCloseTo(ac + "[1]", expectedColor[1], sigma);
shouldBeCloseTo(ac + "[2]", expectedColor[2], sigma);
shouldBeCloseTo(ac + "[3]", expectedColor[3], sigma);
}
function drawElement(context, i) {
if (i >= blendModes.length) {
finishJSTest();
return;
}
debug("Testing blend mode " + blendModes[i]);
context.clearRect(0, 0, 10, 10);
context.save();
drawBackdropColorImageInContext(context, function() {
context.globalCompositeOperation = blendModes[i];
drawSourceColorPatternInContext(context, function() {
checkBlendModeResult(i, context, 5);
context.restore();
debug('');
drawElement(context, ++i);
});
});
}
function runTest() {
var canvas = document.createElement("canvas");
var sigma = 5;
canvas.width = 10;
canvas.height = 10;
context = canvas.getContext("2d");
drawElement(context, 0);
}
runTest();
</script>
</body>
</html>
| js0701/chromium-crosswalk | third_party/WebKit/LayoutTests/fast/canvas/canvas-blending-pattern-over-image.html | HTML | bsd-3-clause | 2,160 |
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<div class="info">
<p>This example shows FixedHeader operating with the jQuery UI ThemeRoller styling framework.</p>
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<table id="example" class="display" cellspacing="0" width="100%">
<thead>
<tr>
<th>Name</th>
<th>Position</th>
<th>Office</th>
<th>Age</th>
<th>Start date</th>
<th>Salary</th>
</tr>
</thead>
<tfoot>
<tr>
<th>Name</th>
<th>Position</th>
<th>Office</th>
<th>Age</th>
<th>Start date</th>
<th>Salary</th>
</tr>
</tfoot>
<tbody>
<tr>
<td>Tiger Nixon</td>
<td>System Architect</td>
<td>Edinburgh</td>
<td>61</td>
<td>2011/04/25</td>
<td>$320,800</td>
</tr>
<tr>
<td>Garrett Winters</td>
<td>Accountant</td>
<td>Tokyo</td>
<td>63</td>
<td>2011/07/25</td>
<td>$170,750</td>
</tr>
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<td>Ashton Cox</td>
<td>Junior Technical Author</td>
<td>San Francisco</td>
<td>66</td>
<td>2009/01/12</td>
<td>$86,000</td>
</tr>
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<td>Cedric Kelly</td>
<td>Senior Javascript Developer</td>
<td>Edinburgh</td>
<td>22</td>
<td>2012/03/29</td>
<td>$433,060</td>
</tr>
<tr>
<td>Airi Satou</td>
<td>Accountant</td>
<td>Tokyo</td>
<td>33</td>
<td>2008/11/28</td>
<td>$162,700</td>
</tr>
<tr>
<td>Brielle Williamson</td>
<td>Integration Specialist</td>
<td>New York</td>
<td>61</td>
<td>2012/12/02</td>
<td>$372,000</td>
</tr>
<tr>
<td>Herrod Chandler</td>
<td>Sales Assistant</td>
<td>San Francisco</td>
<td>59</td>
<td>2012/08/06</td>
<td>$137,500</td>
</tr>
<tr>
<td>Rhona Davidson</td>
<td>Integration Specialist</td>
<td>Tokyo</td>
<td>55</td>
<td>2010/10/14</td>
<td>$327,900</td>
</tr>
<tr>
<td>Colleen Hurst</td>
<td>Javascript Developer</td>
<td>San Francisco</td>
<td>39</td>
<td>2009/09/15</td>
<td>$205,500</td>
</tr>
<tr>
<td>Sonya Frost</td>
<td>Software Engineer</td>
<td>Edinburgh</td>
<td>23</td>
<td>2008/12/13</td>
<td>$103,600</td>
</tr>
<tr>
<td>Jena Gaines</td>
<td>Office Manager</td>
<td>London</td>
<td>30</td>
<td>2008/12/19</td>
<td>$90,560</td>
</tr>
<tr>
<td>Quinn Flynn</td>
<td>Support Lead</td>
<td>Edinburgh</td>
<td>22</td>
<td>2013/03/03</td>
<td>$342,000</td>
</tr>
<tr>
<td>Charde Marshall</td>
<td>Regional Director</td>
<td>San Francisco</td>
<td>36</td>
<td>2008/10/16</td>
<td>$470,600</td>
</tr>
<tr>
<td>Haley Kennedy</td>
<td>Senior Marketing Designer</td>
<td>London</td>
<td>43</td>
<td>2012/12/18</td>
<td>$313,500</td>
</tr>
<tr>
<td>Tatyana Fitzpatrick</td>
<td>Regional Director</td>
<td>London</td>
<td>19</td>
<td>2010/03/17</td>
<td>$385,750</td>
</tr>
<tr>
<td>Michael Silva</td>
<td>Marketing Designer</td>
<td>London</td>
<td>66</td>
<td>2012/11/27</td>
<td>$198,500</td>
</tr>
<tr>
<td>Paul Byrd</td>
<td>Chief Financial Officer (CFO)</td>
<td>New York</td>
<td>64</td>
<td>2010/06/09</td>
<td>$725,000</td>
</tr>
<tr>
<td>Gloria Little</td>
<td>Systems Administrator</td>
<td>New York</td>
<td>59</td>
<td>2009/04/10</td>
<td>$237,500</td>
</tr>
<tr>
<td>Bradley Greer</td>
<td>Software Engineer</td>
<td>London</td>
<td>41</td>
<td>2012/10/13</td>
<td>$132,000</td>
</tr>
<tr>
<td>Dai Rios</td>
<td>Personnel Lead</td>
<td>Edinburgh</td>
<td>35</td>
<td>2012/09/26</td>
<td>$217,500</td>
</tr>
<tr>
<td>Jenette Caldwell</td>
<td>Development Lead</td>
<td>New York</td>
<td>30</td>
<td>2011/09/03</td>
<td>$345,000</td>
</tr>
<tr>
<td>Yuri Berry</td>
<td>Chief Marketing Officer (CMO)</td>
<td>New York</td>
<td>40</td>
<td>2009/06/25</td>
<td>$675,000</td>
</tr>
<tr>
<td>Caesar Vance</td>
<td>Pre-Sales Support</td>
<td>New York</td>
<td>21</td>
<td>2011/12/12</td>
<td>$106,450</td>
</tr>
<tr>
<td>Doris Wilder</td>
<td>Sales Assistant</td>
<td>Sidney</td>
<td>23</td>
<td>2010/09/20</td>
<td>$85,600</td>
</tr>
<tr>
<td>Angelica Ramos</td>
<td>Chief Executive Officer (CEO)</td>
<td>London</td>
<td>47</td>
<td>2009/10/09</td>
<td>$1,200,000</td>
</tr>
<tr>
<td>Gavin Joyce</td>
<td>Developer</td>
<td>Edinburgh</td>
<td>42</td>
<td>2010/12/22</td>
<td>$92,575</td>
</tr>
<tr>
<td>Jennifer Chang</td>
<td>Regional Director</td>
<td>Singapore</td>
<td>28</td>
<td>2010/11/14</td>
<td>$357,650</td>
</tr>
<tr>
<td>Brenden Wagner</td>
<td>Software Engineer</td>
<td>San Francisco</td>
<td>28</td>
<td>2011/06/07</td>
<td>$206,850</td>
</tr>
<tr>
<td>Fiona Green</td>
<td>Chief Operating Officer (COO)</td>
<td>San Francisco</td>
<td>48</td>
<td>2010/03/11</td>
<td>$850,000</td>
</tr>
<tr>
<td>Shou Itou</td>
<td>Regional Marketing</td>
<td>Tokyo</td>
<td>20</td>
<td>2011/08/14</td>
<td>$163,000</td>
</tr>
<tr>
<td>Michelle House</td>
<td>Integration Specialist</td>
<td>Sidney</td>
<td>37</td>
<td>2011/06/02</td>
<td>$95,400</td>
</tr>
<tr>
<td>Suki Burks</td>
<td>Developer</td>
<td>London</td>
<td>53</td>
<td>2009/10/22</td>
<td>$114,500</td>
</tr>
<tr>
<td>Prescott Bartlett</td>
<td>Technical Author</td>
<td>London</td>
<td>27</td>
<td>2011/05/07</td>
<td>$145,000</td>
</tr>
<tr>
<td>Gavin Cortez</td>
<td>Team Leader</td>
<td>San Francisco</td>
<td>22</td>
<td>2008/10/26</td>
<td>$235,500</td>
</tr>
<tr>
<td>Martena Mccray</td>
<td>Post-Sales support</td>
<td>Edinburgh</td>
<td>46</td>
<td>2011/03/09</td>
<td>$324,050</td>
</tr>
<tr>
<td>Unity Butler</td>
<td>Marketing Designer</td>
<td>San Francisco</td>
<td>47</td>
<td>2009/12/09</td>
<td>$85,675</td>
</tr>
<tr>
<td>Howard Hatfield</td>
<td>Office Manager</td>
<td>San Francisco</td>
<td>51</td>
<td>2008/12/16</td>
<td>$164,500</td>
</tr>
<tr>
<td>Hope Fuentes</td>
<td>Secretary</td>
<td>San Francisco</td>
<td>41</td>
<td>2010/02/12</td>
<td>$109,850</td>
</tr>
<tr>
<td>Vivian Harrell</td>
<td>Financial Controller</td>
<td>San Francisco</td>
<td>62</td>
<td>2009/02/14</td>
<td>$452,500</td>
</tr>
<tr>
<td>Timothy Mooney</td>
<td>Office Manager</td>
<td>London</td>
<td>37</td>
<td>2008/12/11</td>
<td>$136,200</td>
</tr>
<tr>
<td>Jackson Bradshaw</td>
<td>Director</td>
<td>New York</td>
<td>65</td>
<td>2008/09/26</td>
<td>$645,750</td>
</tr>
<tr>
<td>Olivia Liang</td>
<td>Support Engineer</td>
<td>Singapore</td>
<td>64</td>
<td>2011/02/03</td>
<td>$234,500</td>
</tr>
<tr>
<td>Bruno Nash</td>
<td>Software Engineer</td>
<td>London</td>
<td>38</td>
<td>2011/05/03</td>
<td>$163,500</td>
</tr>
<tr>
<td>Sakura Yamamoto</td>
<td>Support Engineer</td>
<td>Tokyo</td>
<td>37</td>
<td>2009/08/19</td>
<td>$139,575</td>
</tr>
<tr>
<td>Thor Walton</td>
<td>Developer</td>
<td>New York</td>
<td>61</td>
<td>2013/08/11</td>
<td>$98,540</td>
</tr>
<tr>
<td>Finn Camacho</td>
<td>Support Engineer</td>
<td>San Francisco</td>
<td>47</td>
<td>2009/07/07</td>
<td>$87,500</td>
</tr>
<tr>
<td>Serge Baldwin</td>
<td>Data Coordinator</td>
<td>Singapore</td>
<td>64</td>
<td>2012/04/09</td>
<td>$138,575</td>
</tr>
<tr>
<td>Zenaida Frank</td>
<td>Software Engineer</td>
<td>New York</td>
<td>63</td>
<td>2010/01/04</td>
<td>$125,250</td>
</tr>
<tr>
<td>Zorita Serrano</td>
<td>Software Engineer</td>
<td>San Francisco</td>
<td>56</td>
<td>2012/06/01</td>
<td>$115,000</td>
</tr>
<tr>
<td>Jennifer Acosta</td>
<td>Junior Javascript Developer</td>
<td>Edinburgh</td>
<td>43</td>
<td>2013/02/01</td>
<td>$75,650</td>
</tr>
<tr>
<td>Cara Stevens</td>
<td>Sales Assistant</td>
<td>New York</td>
<td>46</td>
<td>2011/12/06</td>
<td>$145,600</td>
</tr>
<tr>
<td>Hermione Butler</td>
<td>Regional Director</td>
<td>London</td>
<td>47</td>
<td>2011/03/21</td>
<td>$356,250</td>
</tr>
<tr>
<td>Lael Greer</td>
<td>Systems Administrator</td>
<td>London</td>
<td>21</td>
<td>2009/02/27</td>
<td>$103,500</td>
</tr>
<tr>
<td>Jonas Alexander</td>
<td>Developer</td>
<td>San Francisco</td>
<td>30</td>
<td>2010/07/14</td>
<td>$86,500</td>
</tr>
<tr>
<td>Shad Decker</td>
<td>Regional Director</td>
<td>Edinburgh</td>
<td>51</td>
<td>2008/11/13</td>
<td>$183,000</td>
</tr>
<tr>
<td>Michael Bruce</td>
<td>Javascript Developer</td>
<td>Singapore</td>
<td>29</td>
<td>2011/06/27</td>
<td>$183,000</td>
</tr>
<tr>
<td>Donna Snider</td>
<td>Customer Support</td>
<td>New York</td>
<td>27</td>
<td>2011/01/25</td>
<td>$112,000</td>
</tr>
</tbody>
</table>
<ul class="tabs">
<li class="active">Javascript</li>
<li>HTML</li>
<li>CSS</li>
<li>Ajax</li>
<li>Server-side script</li>
</ul>
<div class="tabs">
<div class="js">
<p>The Javascript shown below is used to initialise the table shown in this example:</p><code class="multiline language-js">$(document).ready(function() {
$('#example').DataTable( {
fixedHeader: true
} );
} );</code>
<p>In addition to the above code, the following Javascript library files are loaded for use in this example:</p>
<ul>
<li><a href="//code.jquery.com/jquery-1.11.3.min.js">//code.jquery.com/jquery-1.11.3.min.js</a></li>
<li><a href="../../../../media/js/jquery.dataTables.js">../../../../media/js/jquery.dataTables.js</a></li>
<li><a href="../../../../media/js/dataTables.jqueryui.js">../../../../media/js/dataTables.jqueryui.js</a></li>
<li><a href="../../js/dataTables.fixedHeader.js">../../js/dataTables.fixedHeader.js</a></li>
</ul>
</div>
<div class="table">
<p>The HTML shown below is the raw HTML table element, before it has been enhanced by DataTables:</p>
</div>
<div class="css">
<div>
<p>This example uses a little bit of additional CSS beyond what is loaded from the library files (below), in order to correctly display the table. The
additional CSS used is shown below:</p><code class="multiline language-css"></code>
</div>
<p>The following CSS library files are loaded for use in this example to provide the styling of the table:</p>
<ul>
<li><a href="//code.jquery.com/ui/1.11.3/themes/smoothness/jquery-ui.css">//code.jquery.com/ui/1.11.3/themes/smoothness/jquery-ui.css</a></li>
<li><a href="../../../../media/css/dataTables.jqueryui.css">../../../../media/css/dataTables.jqueryui.css</a></li>
<li><a href="../../css/fixedHeader.jqueryui.css">../../css/fixedHeader.jqueryui.css</a></li>
</ul>
</div>
<div class="ajax">
<p>This table loads data by Ajax. The latest data that has been loaded is shown below. This data will update automatically as any additional data is
loaded.</p>
</div>
<div class="php">
<p>The script used to perform the server-side processing for this table is shown below. Please note that this is just an example script using PHP. Server-side
processing scripts can be written in any language, using <a href="//datatables.net/manual/server-side">the protocol described in the DataTables
documentation</a>.</p>
</div>
</div>
</section>
</div>
<section>
<div class="footer">
<div class="gradient"></div>
<div class="liner">
<h2>Other examples</h2>
<div class="toc">
<div class="toc-group">
<h3><a href="../options/index.html">Initialisation and options</a></h3>
<ul class="toc">
<li><a href="../options/simple.html">Basic initialisation</a></li>
<li><a href="../options/header_footer.html">Header and footer fixed</a></li>
<li><a href="../options/two_tables.html">Multiple tables</a></li>
<li><a href="../options/offset.html">Offset</a></li>
<li><a href="../options/enable-disable.html">Enable / disable FixedHeader</a></li>
<li><a href="../options/new.html">Alternative initialisation</a></li>
</ul>
</div>
<div class="toc-group">
<h3><a href="./index.html">Styling</a></h3>
<ul class="toc active">
<li><a href="./bootstrap.html">Bootstrap</a></li>
<li><a href="./foundation.html">Foundation</a></li>
<li class="active"><a href="./jqueryui.html">jQuery UI styling</a></li>
</ul>
</div>
<div class="toc-group">
<h3><a href="../integration/index.html">Integration with other DataTables extensions</a></h3>
<ul class="toc">
<li><a href="../integration/responsive.html">Responsive integration</a></li>
<li><a href="../integration/colreorder.html">ColReorder integration</a></li>
</ul>
</div>
</div>
<div class="epilogue">
<p>Please refer to the <a href="http://www.datatables.net">DataTables documentation</a> for full information about its API properties and methods.<br>
Additionally, there are a wide range of <a href="http://www.datatables.net/extensions">extensions</a> and <a href=
"http://www.datatables.net/plug-ins">plug-ins</a> which extend the capabilities of DataTables.</p>
<p class="copyright">DataTables designed and created by <a href="http://www.sprymedia.co.uk">SpryMedia Ltd</a> © 2007-2015<br>
DataTables is licensed under the <a href="http://www.datatables.net/mit">MIT license</a>.</p>
</div>
</div>
</div>
</section>
</body>
</html> | DirectDev/wds-V2 | www/admin/plugins/DataTables/extensions/FixedHeader/examples/styling/jqueryui.html | HTML | mit | 17,123 |
<!DOCTYPE html>
<html>
<!--
Copyright 2010 The Closure Library Authors. All Rights Reserved.
Use of this source code is governed by the Apache License, Version 2.0.
See the COPYING file for details.
Author: nicksantos@google.com (Nick Santos) (Ported to Closure)
-->
<head>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta charset="UTF-8" />
<title>
JsUnit tests for goog.events.ImeHandler
</title>
<script src="../base.js">
</script>
<script>
goog.require('goog.events.ImeHandlerTest');
</script>
</head>
<body>
<div id="sandbox">
</div>
<div>
<b>
Last 10 events:
</b>
<div id="logger" style="padding: 0.5em;">
</div>
</div>
</body>
</html>
| LeoLombardi/tos-laimas-compass | tos-laimas-compass-win32-x64/resources/app/node_modules/closure-util/.deps/library/b06c979ecae7d78dd1ac4f7b09adec643baac308/closure/goog/events/imehandler_test.html | HTML | mit | 709 |
<!DOCTYPE html>
<html>
<title>WebVTT rendering, only css properties with default value inherit should inherit from media element</title>
<style>
video {
color: #f0f;
white-space: pre-wrap;
font: italic small-caps bold 36px/72px sans-serif;
text-decoration: overline underline line-through;
text-shadow: 0px 0px 5px #0f0;
background: #0f0 url('../../media/background.gif') repeat-x top left;
outline: solid #00f 2px;
}
</style>
<script src="../../support/refTestWait.js"></script>
<video width="1280" height="720" autoplay onplaying="this.onplaying = null; this.pause(); takeScreenshot();">
<source src="../../media/white.webm" type="video/webm">
<source src="../../media/white.mp4" type="video/mp4">
<track src="../../support/white-spaces_long.vtt">
</video>
<script>
document.getElementsByTagName('track')[0].track.mode = 'showing';
</script>
</html>
| js0701/chromium-crosswalk | third_party/WebKit/LayoutTests/media/track/opera/track/webvtt/rendering/reftest/selectors/default_styles/inherit_as_default_value_inherits_values_from_media_element.html | HTML | bsd-3-clause | 892 |
<!DOCTYPE HTML>
<html>
<body>
<p>foreignObject should not isolate. The test passes if you see a lime square.</p>
<svg xmlns="http://www.w3.org/2000/svg" version="1.1" width="200px" height="200px">
<rect x="0" y="0" width="200" height="200" style="fill: lime"/>
</svg>
</body>
</html>
| wuhengzhi/chromium-crosswalk | third_party/WebKit/LayoutTests/css3/blending/svg-isolation-foreign-no-isolation-expected.html | HTML | bsd-3-clause | 328 |
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
</head>
<body>
<p>The following is a test for having a <rt> immediately following another.</p>
<br>
<br>
<p><ruby> uses <ruby><rt><rt>ruby</rt><rt>text</rt></ruby> to contain the annotation.
</body>
</html>
| scheib/chromium | third_party/blink/web_tests/fast/ruby/ruby-empty-rt.html | HTML | bsd-3-clause | 307 |
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Underscore Test Suite</title>
<link rel="stylesheet" href="../node_modules/qunitjs/qunit/qunit.css">
</head>
<body>
<div id="qunit"></div>
<script>
// Avoid reporting tests to Sauce Labs when script errors occur.
if (location.port == '9001') {
window.onerror = function(message) {
if (window.QUnit) {
QUnit.config.done.length = 0;
}
global_test_results = { 'message': message };
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}
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<script src="../node_modules/qunitjs/qunit/qunit.js"></script>
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<script src="../node_modules/platform/platform.js"></script>
<script src="./asset/test-ui.js"></script>
<script src="../lodash.js"></script>
<script>
QUnit.config.asyncRetries = 10;
QUnit.config.hidepassed = true;
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'chunk': [
'defaults to empty array (chunk size 0)'
],
'difference': [
'can perform an OO-style difference'
],
'drop': [
'is an alias for rest'
],
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'returns an empty array when n <= 0 (0 case)',
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'returns the whole array if n > length'
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'Died on test #15',
'context works'
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'filter': [
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'[{"a":1,"b":2},{"a":1,"b":3},{"a":1,"b":4}]',
'[{"a":1,"b":2},{"a":2,"b":2}]',
'Empty object accepts all items',
'OO-filter'
],
'find': [
'{"a":1,"b":4}',
'undefined when not found',
'undefined when searching empty list',
'works on objects',
'undefined',
'called with context'
],
'findWhere': [
'checks properties given function'
],
'groupBy': [
'true'
],
'includes': [
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],
'invoke': [
'handles null & undefined'
],
'map': [
'tripled numbers with context',
'OO-style doubled numbers'
],
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'can perform a computation-based max',
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'Finds correct max in array starting with NaN',
'Respects iterator return value of -Infinity',
'String keys use property iterator',
'Iterator context',
'Lookup falsy iterator'
],
'min': [
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'can perform a computation-based min',
'Minimum value of an empty object',
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'Finds correct min in array starting with NaN',
'Respects iterator return value of Infinity',
'String keys use property iterator',
'Iterator context',
'Lookup falsy iterator'
],
'partition': [
'can reference the array index',
'Died on test #8',
'partition takes a context argument',
'function(a){[code]}'
],
'pluck': [
'[1]'
],
'reduce': [
'can reduce with a context object'
],
'reject': [
'Returns empty list given empty array'
],
'sample': [
'behaves correctly on negative n',
'Died on test #3'
],
'some': [
'Can be called with object',
'Died on test #17',
'context works'
],
'where': [
'checks properties given function'
],
'Can use various collection methods on NodeLists': [
'<span id="id2"></span>',
'<span id="id1"></span>'
]
},
'Functions': {
'debounce asap': true,
'debounce asap cancel': true,
'debounce after system time is set backwards': true,
'debounce asap recursively': true,
'throttle repeatedly with results': true,
'more throttle does not trigger leading call when leading is set to false': true,
'throttle does not trigger trailing call when trailing is set to false': true,
'before': [
'stores a memo to the last value',
'provides context'
],
'bind': [
'Died on test #2'
],
'bindAll': [
'throws an error for bindAll with no functions named'
],
'memoize': [
'{"bar":"BAR","foo":"FOO"}',
'Died on test #8'
],
'partial':[
'can partially apply with placeholders',
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'unfilled placeholders are undefined',
'keeps prototype',
'allows the placeholder to be swapped out'
]
},
'Objects': {
'#1929 Typed Array constructors are functions': true,
'allKeys': [
'is not fooled by sparse arrays; see issue #95',
'is not fooled by sparse arrays with additional properties',
'[]'
],
'defaults': [
'defaults skips nulls',
'defaults skips undefined'
],
'extend': [
'extending null results in null',
'extending undefined results in undefined'
],
'extendOwn': [
'extending non-objects results in returning the non-object value',
'extending undefined results in undefined'
],
'functions': [
'also looks up functions on the prototype'
],
'isEqual': [
'`0` is not equal to `-0`',
'Commutative equality is implemented for `0` and `-0`',
'`new Number(0)` and `-0` are not equal',
'Commutative equality is implemented for `new Number(0)` and `-0`',
'false'
],
'isFinite': [
'Numeric strings are numbers',
'Number instances can be finite'
],
'isMatch': [
'doesnt falsey match constructor on undefined/null'
],
'isSet': [
'Died on test #9'
],
'findKey': [
'called with context'
],
'keys': [
'is not fooled by sparse arrays; see issue #95',
'[]'
],
'mapObject': [
'keep context',
'called with context',
'mapValue identity'
],
'matcher': [
'null matches null',
'treats primitives as empty'
],
'omit': [
'can accept a predicate',
'function is given context'
],
'pick': [
'can accept a predicate and context',
'function is given context'
]
},
'Utility': {
'noConflict (node vm)': true,
'now': [
'Produces the correct time in milliseconds'
],
'times': [
'works as a wrapper'
]
}
};
var mixinPrereqs = (function() {
var aliasToReal = {
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'allKeys': 'keysIn',
'any': 'some',
'collect': 'map',
'compose': 'flowRight',
'contains': 'includes',
'detect': 'find',
'extendOwn': 'assign',
'findWhere': 'find',
'foldl': 'reduce',
'foldr': 'reduceRight',
'include': 'includes',
'indexBy': 'keyBy',
'inject': 'reduce',
'invoke': 'invokeMap',
'mapObject': 'mapValues',
'matcher': 'matches',
'methods': 'functions',
'object': 'zipObject',
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'select': 'filter',
'unique': 'uniq',
'where': 'filter'
};
var keyMap = {
'rest': 'tail',
'restArgs': 'rest'
};
var lodash = _.noConflict();
return function(_) {
lodash.defaultsDeep(_, { 'templateSettings': lodash.templateSettings });
lodash.mixin(_, lodash.pick(lodash, lodash.difference(lodash.functions(lodash), lodash.functions(_))));
lodash.forOwn(keyMap, function(realName, otherName) {
_[otherName] = lodash[realName];
_.prototype[otherName] = lodash.prototype[realName];
});
lodash.forOwn(aliasToReal, function(realName, alias) {
_[alias] = _[realName];
_.prototype[alias] = _.prototype[realName];
});
};
}());
// Only excuse in Sauce Labs.
if (!ui.isSauceLabs) {
delete QUnit.config.excused.Functions['throttle does not trigger trailing call when trailing is set to false'];
delete QUnit.config.excused.Utility.now;
}
// Load prerequisite scripts.
document.write(ui.urlParams.loader == 'none'
? '<script src="' + ui.buildPath + '"><\/script>'
: '<script data-dojo-config="async:1" src="' + ui.loaderPath + '"><\/script>'
);
</script>
<script>
if (ui.urlParams.loader == 'none') {
mixinPrereqs(_);
document.write([
'<script src="../vendor/underscore/test/collections.js"><\/script>',
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'<script src="../vendor/underscore/test/utility.js"><\/script>',
'<script src="../vendor/underscore/test/chaining.js"><\/script>'
].join('\n'));
}
</script>
<script>
(function() {
if (window.curl) {
curl.config({ 'apiName': 'require' });
}
if (!window.require) {
return;
}
// Wrap to work around tests assuming Node `require` use.
require = (function(func) {
return function() {
return arguments[0] === '..' ? window._ : func.apply(null, arguments);
};
}(require));
var reBasename = /[\w.-]+$/,
basePath = ('//' + location.host + location.pathname.replace(reBasename, '')).replace(/\btest\/$/, ''),
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locationPath = modulePath.replace(reBasename, '').replace(/^\/|\/$/g, ''),
moduleId = /\bunderscore\b/i.test(ui.buildPath) ? 'underscore' : 'lodash',
moduleMain = modulePath.match(reBasename)[0],
uid = +new Date;
function getConfig() {
var result = {
'baseUrl': './',
'urlArgs': 't=' + uid++,
'waitSeconds': 0,
'paths': {},
'packages': [{
'name': 'test',
'location': '../vendor/underscore/test',
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'exports': 'QUnit',
'loader': 'curl/loader/legacy'
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}]
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if (ui.isModularize) {
result.packages.push({
'name': moduleId,
'location': locationPath,
'main': moduleMain
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result.paths[moduleId] = modulePath;
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return result;
}
QUnit.config.autostart = false;
require(getConfig(), [moduleId], function(lodash) {
mixinPrereqs(lodash);
require(getConfig(), [
'test/collections',
'test/arrays',
'test/functions',
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'test/cross-document',
'test/utility',
'test/chaining'
], function() {
QUnit.start();
});
});
}());
</script>
</body>
</html>
| kurideja/pizza-diagram | www/libs/lodash/test/underscore.html | HTML | mit | 16,201 |
<h2>{{ repoDetails.full_name }}</h2>
<pre>this.repoDetails = {{ repoDetails | json }}</pre>
| dsilva2401/server-seed | src/setup/webapps/src/register/src/_app/github/repo-detail/repo-detail.html | HTML | mit | 93 |
{% macro may_break(item) -%}
[{{ item / 0 }}]
{%- endmacro %}
| ychen820/microblog | y/google-cloud-sdk/platform/google_appengine/lib/jinja2-2.6/examples/basic/templates/subbroken.html | HTML | bsd-3-clause | 64 |
<!--
Any copyright is dedicated to the Public Domain.
http://creativecommons.org/publicdomain/zero/1.0/
-->
<!DOCTYPE html>
<html>
<head>
<!--
The original and initial filename of this test was
wide- -auto- -nonpercent-width-omitted-height.html
-->
<title>CSS Backgrounds and Borders Test: background-size: auto; for nonpercent-width-omitted-height.svg</title>
<link rel="author" title="Jeff Walden" href="http://whereswalden.com/">
<link rel="help" href="http://www.w3.org/TR/css3-background/#the-background-size">
<link rel="help" href="http://www.w3.org/TR/SVG/coords.html#IntrinsicSizing">
<link rel="help" href="http://www.w3.org/TR/SVG/coords.html#PreserveAspectRatioAttribute">
<link rel="match" href="reference/ref-wide-lime8x128-aqua8x128.html">
<meta name="flags" content="svg">
<style type="text/css">
div
{
background-image: url("support/nonpercent-width-omitted-height.svg");
background-repeat: no-repeat;
background-size: auto;
border: black solid 1px;
height: 256px;
width: 768px;
}
</style>
</head>
<body>
<div></div>
</body>
</html>
| scheib/chromium | third_party/blink/web_tests/external/wpt/css/css-backgrounds/background-size/vector/wide--auto--nonpercent-width-omitted-height.html | HTML | bsd-3-clause | 1,122 |
<!DOCTYPE html>
<html>
<head>
<title>CSS Test (Transforms): Inversion Stress Test</title>
<link rel="author" title="Clint Talbert" href="mailto:ctalbert@mozilla.com">
<link rel="author" title="Aryeh Gregor" href="mailto:ayg@aryeh.name">
<link rel="help" href="http://www.w3.org/TR/css-transforms-1/#two-d-transform-functions">
<meta name="assert" content="This simply applies and then inverts a large
number of 2D transform functions, and expects the result to be no transform
at all. One extra translateX(100px) is added at the end to ensure that the
lack of transform isn't just because the UA parsed it incorrectly, or
doesn't support transforms at all.">
<link rel="match" href="transform-stresstest-ref.html">
<style>
div {
height: 200px;
width: 200px;
background: gold;
transform: skewx(45deg)
translate(50px, 50px)
rotate(45deg)
translatex(50px)
scale(2.0, 4.0)
scale(0.5, 0.25)
translatex(-50px)
rotate(-45deg)
translate(-50px, -50px)
skewx(135deg)
translateX(100px);
}
</style>
</head>
<body>
<div></div>
</body>
</html>
| haoxli/web-testing-service | wts/tests/2dtransforms/csswg/transform-stresstest-001-manual.html | HTML | bsd-3-clause | 1,365 |
<!DOCTYPE html>
<!-- DO NOT EDIT! Generated by referrer-policy/generic/tools/generate.py using referrer-policy/generic/template/test.release.html.template. -->
<html>
<head>
<title>Referrer-Policy: Referrer Policy is set to 'no-referrer-when-downgrade'</title>
<meta name="description" content="Check that non a priori insecure subresource gets the full Referrer URL. A priori insecure subresource gets no referrer information.">
<meta http-equiv="Content-Security-Policy" content="referrer no-referrer-when-downgrade">
<link rel="author" title="Kristijan Burnik" href="burnik@chromium.org">
<link rel="help" href="https://w3c.github.io/webappsec/specs/referrer-policy/#referrer-policy-state-no-referrer-when-downgrade">
<meta name="assert" content="The referrer URL is stripped-referrer when a
document served over http requires an http
sub-resource via script-tag using the meta-csp
delivery method with keep-origin-redirect and when
the target request is same-origin.">
<script src="/resources/testharness.js"></script>
<script src="/resources/testharnessreport.js"></script>
<!-- TODO(kristijanburnik): Minify and merge both: -->
<script src="/referrer-policy/generic/common.js"></script>
<script src="/referrer-policy/generic/referrer-policy-test-case.js?pipe=sub"></script>
</head>
<body>
<script>
ReferrerPolicyTestCase(
{
"referrer_policy": "no-referrer-when-downgrade",
"delivery_method": "meta-csp",
"redirection": "keep-origin-redirect",
"origin": "same-origin",
"source_protocol": "http",
"target_protocol": "http",
"subresource": "script-tag",
"subresource_path": "/referrer-policy/generic/subresource/script.py",
"referrer_url": "stripped-referrer"
},
document.querySelector("meta[name=assert]").content,
new SanityChecker()
).start();
</script>
<div id="log"></div>
</body>
</html>
| youtube/cobalt | third_party/web_platform_tests/referrer-policy/no-referrer-when-downgrade/meta-csp/same-origin/http-http/script-tag/insecure-protocol.keep-origin-redirect.http.html | HTML | bsd-3-clause | 2,129 |
<!DOCTYPE html>
<!--
Distributed under both the W3C Test Suite License [1] and the W3C
3-clause BSD License [2]. To contribute to a W3C Test Suite, see the
policies and contribution forms [3].
[1] http://www.w3.org/Consortium/Legal/2008/04-testsuite-license
[2] http://www.w3.org/Consortium/Legal/2008/03-bsd-license
[3] http://www.w3.org/2004/10/27-testcases
-->
<html>
<head>
<title>Shadow DOM Test: A_10_02_02_01</title>
<link rel="author" title="Sergey G. Grekhov" href="mailto:sgrekhov@unipro.ru">
<link rel="help" href="http://www.w3.org/TR/2013/WD-shadow-dom-20130514/#shadow-aware-methods">
<meta name="assert" content="Extensions to Element Interface: attachShadow method creates new instance of Shadow root object">
<script src="/resources/testharness.js"></script>
<script src="/resources/testharnessreport.js"></script>
<script src="../../../../../html/resources/common.js"></script>
</head>
<body>
<div id="log"></div>
<script>
test(function () {
var d = newHTMLDocument();
var host = d.createElement('div');
d.body.appendChild(host);
var s = host.attachShadow({mode: 'open'});
assert_true(s instanceof ShadowRoot, 'attachShadow() method should create new instance ' +
'of ShadowRoot object');
}, 'A_10_02_02_01_T01');
</script>
</body>
</html>
| danakj/chromium | third_party/WebKit/LayoutTests/imported/wpt/shadow-dom/untriaged/elements-and-dom-objects/extensions-to-element-interface/methods/test-001.html | HTML | bsd-3-clause | 1,296 |
<!DOCTYPE html>
<html>
<head>
<meta name='author' title='Google' href='http://www.google.com'>
<meta name='assert' content='Shadow DOM should not leak via window.frames.'>
<link rel='help' href='https://w3c.github.io/webcomponents/spec/shadow/'>
<script src='/resources/testharness.js'></script>
<script src='/resources/testharnessreport.js'></script>
</head>
<body>
<div id='log'></div>
<iframe src='about:blank' name='mainFrame1'></iframe>
<div id='host-open'></div>
<div id='host-closed'></div>
</body>
<script>
'use strict';
var host_open = document.getElementById('host-open');
var root_open = host_open.attachShadow({mode: 'open'});
root_open.innerHTML = '<iframe src="about:blank" name="shadowFrame1"></iframe>';
var host_closed = document.getElementById('host-closed');
var root_closed = host_closed.attachShadow({mode: 'closed'});
root_closed.innerHTML = '<iframe src="about:blank" name="shadowFrame2"></iframe>';
test(() => {
assert_equals(window.frames.length, 1, 'window.frames should return only frames in document.');
assert_equals(window.frames[0].name, 'mainFrame1', 'window.frames[0] should be mainFrame1.');
assert_equals(window.frames['mainFrame1'], window.frames[0], 'window.frames[\'mainFrame1\'] should be equal to mainFrame1.');
assert_equals(window.frames['shadowFrame1'], undefined, 'shadowFrame1 should not leak.');
assert_equals(window.frames['shadowFrame2'], undefined, 'shadowFrame2 should not leak.');
}, 'window.frames should not leak frames in Shadow DOM.');
</script>
</html>
| scheib/chromium | third_party/blink/web_tests/external/wpt/shadow-dom/leaktests/window-frames.html | HTML | bsd-3-clause | 1,523 |
<!DOCTYPE html>
<html>
<head>
<!-- Programmatically converted from a WebKit Reftest, please forgive resulting idiosyncracies.-->
<title>report-blocked-data-uri</title>
<script src="/resources/testharness.js"></script>
<script src="/resources/testharnessreport.js"></script>
<script src="../support/logTest.sub.js?logs=[]"></script>
<script src="../support/alertAssert.sub.js?alerts=[]"></script>
<!-- enforcing policy:
img-src 'none'; report-uri resources/save-report.php?test=report-blocked-data-uri.html; script-src 'self' 'unsafe-inline'; connect-src 'self';
-->
</head>
<body>
<img src="data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==">
<div id="log"></div>
<script async defer src="../support/checkReport.sub.js?reportExists=true&reportField=violated-directive&reportValue=img-src%20'none'"></script>
</body>
</html>
| youtube/cobalt | third_party/web_platform_tests/content-security-policy/blink-contrib/report-blocked-data-uri.sub.html | HTML | bsd-3-clause | 910 |
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>Example "webworker"</title>
</head>
<body>
<script src="web.bundle.js"></script>
</body>
</html>
| bdwain/webpack-dev-server | examples/webworker/index.html | HTML | mit | 160 |
<!doctype html>
<html class="no-js" lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Contact form here</title>
<link rel="stylesheet" type="text/css" href="http://localhost:4000/assets/css/styles_feeling_responsive.css">
<script src="http://localhost:4000/assets/js/modernizr.min.js"></script>
<script src="https://ajax.googleapis.com/ajax/libs/webfont/1.5.18/webfont.js"></script>
<script>
WebFont.load({
google: {
families: [ 'Lato:400,700,400italic:latin', 'Volkhov::latin' ]
}
});
</script>
<noscript>
<link href='http://fonts.googleapis.com/css?family=Lato:400,700,400italic%7CVolkhov' rel='stylesheet' type='text/css'>
</noscript>
<!-- Netlify CMS -->
<script src="https://identity.netlify.com/v1/netlify-identity-widget.js"></script>
<!-- Search Engine Optimization -->
<meta name="description" content="Women In Black is a barbershop chorus in Berlin.">
<!-- Facebook Open Graph -->
<meta property="og:title" content="Contact form here">
<meta property="og:description" content="Women In Black is a barbershop chorus in Berlin.">
<meta property="og:url" content="http://localhost:4000/contact/">
<meta property="og:locale" content="en_EN">
<meta property="og:type" content="website">
<meta property="og:site_name" content="Women In Black">
<link type="text/plain" rel="author" href="http://localhost:4000/humans.txt">
<link rel="icon" sizes="32x32" href="http://localhost:4000/assets/img/favicon-32x32.png">
<link rel="icon" sizes="192x192" href="http://localhost:4000/assets/img/icon-144x144.png">
<link rel="apple-touch-icon-precomposed" sizes="180x180" href="http://localhost:4000/assets/img/apple-touch-icon-180x180-precomposed.png">
<link rel="apple-touch-icon-precomposed" sizes="152x152" href="http://localhost:4000/assets/img/apple-touch-icon-152x152-precomposed.png">
<link rel="apple-touch-icon-precomposed" sizes="144x144" href="http://localhost:4000/assets/img/apple-touch-icon-144x144-precomposed.png">
<link rel="apple-touch-icon-precomposed" sizes="120x120" href="http://localhost:4000/assets/img/apple-touch-icon-120x120-precomposed.png">
<link rel="apple-touch-icon-precomposed" sizes="114x114" href="http://localhost:4000/assets/img/apple-touch-icon-114x114-precomposed.png">
<link rel="apple-touch-icon-precomposed" sizes="76x76" href="http://localhost:4000/assets/img/apple-touch-icon-76x76-precomposed.png">
<link rel="apple-touch-icon-precomposed" sizes="72x72" href="http://localhost:4000/assets/img/apple-touch-icon-72x72-precomposed.png">
<link rel="apple-touch-icon-precomposed" href="http://localhost:4000/assets/img/apple-touch-icon-precomposed.png">
<meta name="msapplication-TileImage" content="http://localhost:4000/assets/img/icon-144x144.png">
<meta name="msapplication-TileColor" content="#fabb00">
</head>
<body id="top-of-page" class="">
<div id="navigation" class="sticky">
<nav class="top-bar" role="navigation" data-topbar>
<ul class="title-area">
<li class="name">
<h1 class="show-for-small-only"><a href="http://localhost:4000" class="icon-tree"> Women In Black</a></h1>
</li>
<!-- Remove the class "menu-icon" to get rid of menu icon. Take out "Menu" to just have icon alone -->
<li class="toggle-topbar menu-icon"><a href="#"><span>Navigation</span></a></li>
</ul>
<section class="top-bar-section">
<ul class="right">
</ul>
<ul class="left">
<li><a href="http://localhost:4000/">Home</a></li>
<li class="divider"></li>
<li><a href="http://localhost:4000/about/">About</a></li>
<li class="divider"></li>
<li><a href="http://localhost:4000/media/">Media</a></li>
<li class="divider"></li>
<li><a href="http://localhost:4000/blog/">Blog</a></li>
<li class="divider"></li>
<li class="active"><a href="http://localhost:4000/contact/">Contact</a></li>
<li class="divider"></li>
</ul>
</section>
</nav>
</div><!-- /#navigation -->
<div id="masthead-no-image-header">
<div class="row">
<div class="small-12 columns">
<a id="logo" href="http://localhost:4000" title="Women In Black – Women In Black, Berlin's Barbershop Chorus">
<img src="http://localhost:4000/assets/img/logo.png" alt="Women In Black – Women In Black, Berlin's Barbershop Chorus">
</a>
</div><!-- /.small-12.columns -->
</div><!-- /.row -->
</div><!-- /#masthead -->
<div class="row t30">
<div class="medium-8 columns medium-offset-2 end">
<article itemscope itemtype="http://schema.org/Article">
<header>
<div itemprop="name">
<h1>Kontakt</h1>
</div>
</header>
<div itemprop="articleSection">
<p>Wir freuen uns sehr, dass Sie Kontakt mit uns aufnehmen wollen!</p>
<p><a href="/about/">Hier</a> können Sie mehr über uns erfahren.</p>
<form action="//formspree.io/wibberlin@gmail.com" method="POST">
<input type="text" name="name" placeholder="Your name" />
<input type="email" name="_replyto" placeholder="Your email" />
<textarea name="body"></textarea>
<input type="submit" value="Send" />
</form>
</div>
</article>
</div><!-- /.medium-8.columns -->
</div><!-- /.row -->
<div id="up-to-top" class="row">
<div class="small-12 columns" style="text-align: right;">
<a class="iconfont" href="#top-of-page"></a>
</div><!-- /.small-12.columns -->
</div><!-- /.row -->
<footer id="footer-content" class="bg-grau">
<div id="footer">
<div class="row">
<div class="medium-6 large-5 columns">
<h5 class="shadow-black">Über diese Website</h5>
<p class="shadow-black">
Women In Black is a barbershop chorus in Berlin.
<a href="http://localhost:4000/info/">Mehr ›</a>
</p>
</div><!-- /.large-6.columns -->
<div class="small-6 medium-3 large-3 large-offset-1 columns">
<ul class="no-bullet shadow-black">
</ul>
</div><!-- /.large-4.columns -->
<div class="small-6 medium-3 large-3 columns">
<h5 class="shadow-black">Quick Links</h5>
<ul class="no-bullet shadow-black">
<li >
<a href="http://localhost:4000" title=""></a>
</li>
<li >
<a href="http://localhost:4000/contact/" title="Contact">Contact</a>
</li>
<li >
<a href="http://localhost:4000/sitemap.xml" title="Sitemap for Google Webmaster Tools">sitemap.xml</a>
</li>
</ul>
</div><!-- /.large-3.columns -->
</div><!-- /.row -->
</div><!-- /#footer -->
<div id="subfooter">
<nav class="row">
<section id="subfooter-left" class="small-12 medium-6 columns credits">
</section>
<section id="subfooter-right" class="small-12 medium-6 columns">
<ul class="inline-list social-icons">
<li><a href="http://www.youtube.com/wibberlin" target="_blank" class="icon-youtube" title="watch our performances!"></a></li>
<li><a href="http://twitter.com/wibchorus" target="_blank" class="icon-twitter" title="follow us!"></a></li>
<li><a href="http://www.facebook.com/wibberlin" target="_blank" class="icon-facebook" title="like us!"></a></li>
</ul>
</section>
</nav>
</div><!-- /#subfooter -->
</footer>
<script src="http://localhost:4000/assets/js/javascript.min.js"></script>
<!-- Netlify CMS -->
<script>
if (window.netlifyIdentity) {
window.netlifyIdentity.on("init", user => {
if (!user) {
window.netlifyIdentity.on("login", () => {
document.location.href = "/admin/";
});
}
});
}
</script>
</body>
</html>
| flapperleenie/womeninblack | _site/contact/index.html | HTML | mit | 9,253 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>mathcomp-field: 12 m 42 s 🏆</title>
<link rel="shortcut icon" type="image/png" href="../../../../../favicon.png" />
<link href="../../../../../bootstrap.min.css" rel="stylesheet">
<link href="../../../../../bootstrap-custom.css" rel="stylesheet">
<link href="//maxcdn.bootstrapcdn.com/font-awesome/4.2.0/css/font-awesome.min.css" rel="stylesheet">
<script src="../../../../../moment.min.js"></script>
<!-- HTML5 Shim and Respond.js IE8 support of HTML5 elements and media queries -->
<!-- WARNING: Respond.js doesn't work if you view the page via file:// -->
<!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.2/html5shiv.min.js"></script>
<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
<![endif]-->
</head>
<body>
<div class="container">
<div class="navbar navbar-default" role="navigation">
<div class="container-fluid">
<div class="navbar-header">
<a class="navbar-brand" href="../../../../.."><i class="fa fa-lg fa-flag-checkered"></i> Coq bench</a>
</div>
<div id="navbar" class="collapse navbar-collapse">
<ul class="nav navbar-nav">
<li><a href="../..">clean / released</a></li>
<li class="active"><a href="">8.7.1+1 / mathcomp-field - 1.10.0</a></li>
</ul>
</div>
</div>
</div>
<div class="article">
<div class="row">
<div class="col-md-12">
<a href="../..">« Up</a>
<h1>
mathcomp-field
<small>
1.10.0
<span class="label label-success">12 m 42 s 🏆</span>
</small>
</h1>
<p>📅 <em><script>document.write(moment("2022-02-24 04:07:54 +0000", "YYYY-MM-DD HH:mm:ss Z").fromNow());</script> (2022-02-24 04:07:54 UTC)</em><p>
<h2>Context</h2>
<pre># Packages matching: installed
# Name # Installed # Synopsis
base-bigarray base
base-num base Num library distributed with the OCaml compiler
base-ocamlbuild base OCamlbuild binary and libraries distributed with the OCaml compiler
base-threads base
base-unix base
camlp5 7.14 Preprocessor-pretty-printer of OCaml
conf-findutils 1 Virtual package relying on findutils
conf-perl 2 Virtual package relying on perl
coq 8.7.1+1 Formal proof management system
num 0 The Num library for arbitrary-precision integer and rational arithmetic
ocaml 4.02.3 The OCaml compiler (virtual package)
ocaml-base-compiler 4.02.3 Official 4.02.3 release
ocaml-config 1 OCaml Switch Configuration
ocamlfind 1.9.3 A library manager for OCaml
# opam file:
opam-version: "2.0"
maintainer: "Mathematical Components <mathcomp-dev@sympa.inria.fr>"
homepage: "https://math-comp.github.io/"
bug-reports: "https://github.com/math-comp/math-comp/issues"
dev-repo: "git+https://github.com/math-comp/math-comp.git"
license: "CeCILL-B"
build: [ make "-C" "mathcomp/field" "-j" "%{jobs}%" ]
install: [ make "-C" "mathcomp/field" "install" ]
depends: [ "coq-mathcomp-solvable" { = version } ]
tags: [ "keyword:algebra" "keyword:field" "keyword:small scale reflection" "keyword:mathematical components" "keyword:odd order theorem" "logpath:mathcomp.field" ]
authors: [ "Jeremy Avigad <>" "Andrea Asperti <>" "Stephane Le Roux <>" "Yves Bertot <>" "Laurence Rideau <>" "Enrico Tassi <>" "Ioana Pasca <>" "Georges Gonthier <>" "Sidi Ould Biha <>" "Cyril Cohen <>" "Francois Garillot <>" "Alexey Solovyev <>" "Russell O'Connor <>" "Laurent Théry <>" "Assia Mahboubi <>" ]
synopsis: "Mathematical Components Library on Fields"
description:"""
This library contains definitions and theorems about field extensions,
galois theory, algebraic numbers, cyclotomic polynomials...
"""
url {
src: "http://github.com/math-comp/math-comp/archive/mathcomp-1.10.0.tar.gz"
checksum: "sha256=3f8a88417f3456da05e2755ea0510c1bd3fd13b13c41e62fbaa3de06be040166"
}
</pre>
<h2>Lint</h2>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>true</code></dd>
<dt>Return code</dt>
<dd>0</dd>
</dl>
<h2>Dry install 🏜️</h2>
<p>Dry install with the current Coq version:</p>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>opam install -y --show-action coq-mathcomp-field.1.10.0 coq.8.7.1+1</code></dd>
<dt>Return code</dt>
<dd>0</dd>
</dl>
<p>Dry install without Coq/switch base, to test if the problem was incompatibility with the current Coq/OCaml version:</p>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>true</code></dd>
<dt>Return code</dt>
<dd>0</dd>
</dl>
<h2>Install dependencies</h2>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>opam list; echo; ulimit -Sv 4000000; timeout 4h opam install -y --deps-only coq-mathcomp-field.1.10.0 coq.8.7.1+1</code></dd>
<dt>Return code</dt>
<dd>0</dd>
<dt>Duration</dt>
<dd>14 m 26 s</dd>
</dl>
<h2>Install 🚀</h2>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>opam list; echo; ulimit -Sv 16000000; timeout 8h opam install -y -v coq-mathcomp-field.1.10.0 coq.8.7.1+1</code></dd>
<dt>Return code</dt>
<dd>0</dd>
<dt>Duration</dt>
<dd>12 m 42 s</dd>
</dl>
<h2>Installation size</h2>
<p>Total: 13 M</p>
<ul>
<li>4 M <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/fieldext.vo</code></li>
<li>1 M <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/galois.vo</code></li>
<li>717 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algebraics_fundamentals.vo</code></li>
<li>571 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algnum.vo</code></li>
<li>568 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/galois.glob</code></li>
<li>533 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algC.vo</code></li>
<li>528 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/separable.vo</code></li>
<li>510 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/closed_field.glob</code></li>
<li>480 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/closed_field.vo</code></li>
<li>471 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algebraics_fundamentals.glob</code></li>
<li>464 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/fieldext.glob</code></li>
<li>457 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/falgebra.vo</code></li>
<li>433 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/separable.glob</code></li>
<li>398 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/finfield.vo</code></li>
<li>354 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algC.glob</code></li>
<li>322 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algnum.glob</code></li>
<li>316 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/falgebra.glob</code></li>
<li>256 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/finfield.glob</code></li>
<li>186 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/cyclotomic.vo</code></li>
<li>122 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/cyclotomic.glob</code></li>
<li>69 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/galois.v</code></li>
<li>67 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/fieldext.v</code></li>
<li>61 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/all_field.vo</code></li>
<li>52 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algebraics_fundamentals.v</code></li>
<li>49 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algC.v</code></li>
<li>47 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/falgebra.v</code></li>
<li>44 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/separable.v</code></li>
<li>39 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/closed_field.v</code></li>
<li>39 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/algnum.v</code></li>
<li>32 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/finfield.v</code></li>
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<li>1 K <code>../ocaml-base-compiler.4.02.3/lib/coq/user-contrib/mathcomp/field/all_field.v</code></li>
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<h2>Uninstall 🧹</h2>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>opam remove -y coq-mathcomp-field.1.10.0</code></dd>
<dt>Return code</dt>
<dd>0</dd>
<dt>Missing removes</dt>
<dd>
none
</dd>
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<dd>
none
</dd>
</dl>
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<h1>
pi-calc
<small>
8.5.0
<span class="label label-info">Not compatible 👼</span>
</small>
</h1>
<p>📅 <em><script>document.write(moment("2022-01-18 12:47:20 +0000", "YYYY-MM-DD HH:mm:ss Z").fromNow());</script> (2022-01-18 12:47:20 UTC)</em><p>
<h2>Context</h2>
<pre># Packages matching: installed
# Name # Installed # Synopsis
base-bigarray base
base-num base Num library distributed with the OCaml compiler
base-threads base
base-unix base
camlp5 7.14 Preprocessor-pretty-printer of OCaml
conf-findutils 1 Virtual package relying on findutils
conf-perl 1 Virtual package relying on perl
coq 8.6 Formal proof management system
num 0 The Num library for arbitrary-precision integer and rational arithmetic
ocaml 4.04.2 The OCaml compiler (virtual package)
ocaml-base-compiler 4.04.2 Official 4.04.2 release
ocaml-config 1 OCaml Switch Configuration
ocamlfind 1.9.1 A library manager for OCaml
# opam file:
opam-version: "2.0"
maintainer: "matej.kosik@inria.fr"
homepage: "https://github.com/coq-contribs/pi-calc"
license: "Proprietary"
build: [make "-j%{jobs}%"]
install: [make "install"]
remove: ["rm" "-R" "%{lib}%/coq/user-contrib/PiCalc"]
depends: [
"ocaml"
"coq" {>= "8.5" & < "8.6~"}
]
tags: [
"keyword:process algebra"
"keyword:pi-calculus"
"keyword:concurrency"
"keyword:higher-order syntax"
"category:Computer Science/Concurrent Systems and Protocols/Theory of concurrent systems"
"date:1998-07"
]
authors: [ "Ivan Scagnetto <scagnett@dimi.uniud.it>" ]
bug-reports: "https://github.com/coq-contribs/pi-calc/issues"
dev-repo: "git+https://github.com/coq-contribs/pi-calc.git"
synopsis: "Pi-calculus in Coq"
description: """
This is a HOAS-based encoding of the pi-calculus (as originally
conceived by Milner, Parrow and Walker in "A Calculus of Mobile
Processes" Parts I-II, Information and Computation n. 100)
together with the formal verification of a large part of the
metatheory of Strong Late Bisimilarity."""
flags: light-uninstall
url {
src: "https://github.com/coq-contribs/pi-calc/archive/v8.5.0.tar.gz"
checksum: "md5=a252c95cf701763d911c861983ab3cd3"
}
</pre>
<h2>Lint</h2>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>true</code></dd>
<dt>Return code</dt>
<dd>0</dd>
</dl>
<h2>Dry install 🏜️</h2>
<p>Dry install with the current Coq version:</p>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>opam install -y --show-action coq-pi-calc.8.5.0 coq.8.6</code></dd>
<dt>Return code</dt>
<dd>5120</dd>
<dt>Output</dt>
<dd><pre>[NOTE] Package coq is already installed (current version is 8.6).
The following dependencies couldn't be met:
- coq-pi-calc -> coq < 8.6~ -> ocaml < 4.03.0
base of this switch (use `--unlock-base' to force)
Your request can't be satisfied:
- No available version of coq satisfies the constraints
No solution found, exiting
</pre></dd>
</dl>
<p>Dry install without Coq/switch base, to test if the problem was incompatibility with the current Coq/OCaml version:</p>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>opam remove -y coq; opam install -y --show-action --unlock-base coq-pi-calc.8.5.0</code></dd>
<dt>Return code</dt>
<dd>0</dd>
</dl>
<h2>Install dependencies</h2>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>true</code></dd>
<dt>Return code</dt>
<dd>0</dd>
<dt>Duration</dt>
<dd>0 s</dd>
</dl>
<h2>Install 🚀</h2>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>true</code></dd>
<dt>Return code</dt>
<dd>0</dd>
<dt>Duration</dt>
<dd>0 s</dd>
</dl>
<h2>Installation size</h2>
<p>No files were installed.</p>
<h2>Uninstall 🧹</h2>
<dl class="dl-horizontal">
<dt>Command</dt>
<dd><code>true</code></dd>
<dt>Return code</dt>
<dd>0</dd>
<dt>Missing removes</dt>
<dd>
none
</dd>
<dt>Wrong removes</dt>
<dd>
none
</dd>
</dl>
</div>
</div>
</div>
<hr/>
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data-color-major-ticks="#f5f5f5"
data-color-minor-ticks="#ddd"
data-color-numbers="#ccc"
data-color-needle="rgba(240, 128, 128, 1)"
data-color-needle-end="rgba(255, 160, 122, .9)"
data-value-box="false"
data-value-text-shadow="false"
data-color-circle-inner="#fff"
data-color-needle-circle-outer="#ccc"
data-needle-circle-size="15"
data-needle-circle-outer="false"
data-needle-type="line"
data-needle-start="75"
data-needle-end="99"
data-needle-width="3"
data-borders="true"
data-border-inner-width="0"
data-border-middle-width="0"
data-border-outer-width="10"
data-color-border-outer="#ccc"
data-color-border-outer-end="#ccc"
data-color-needle-shadow-down="#222"
data-animation-target="plate"
data-animation-duration="1500"
data-animation-rule="linear"
data-width="500"
data-height="500"
data-units="ᵍ"
data-value="0"
></canvas>
<canvas data-type="radial-gauge"
data-width="500"
data-height="500"
data-min-value="0"
data-max-value="360"
data-major-ticks="N,NE,E,SE,S,SW,W,NW,N"
data-minor-ticks="22"
data-ticks-angle="360"
data-start-angle="180"
data-stroke-ticks="false"
data-highlights="false"
data-color-plate="#33a"
data-color-major-ticks="#f5f5f5"
data-color-minor-ticks="#ddd"
data-color-numbers="#ccc"
data-color-needle="rgba(240, 128, 128, 1)"
data-color-needle-end="rgba(255, 160, 122, .9)"
data-value-box="false"
data-value-text-shadow="false"
data-color-circle-inner="#fff"
data-color-needle-circle-outer="#ccc"
data-needle-circle-size="15"
data-needle-circle-outer="false"
data-animation-rule="linear"
data-needle-type="line"
data-needle-start="75"
data-needle-end="99"
data-needle-width="3"
data-borders="true"
data-border-inner-width="0"
data-border-middle-width="0"
data-border-outer-width="10"
data-color-border-outer="#ccc"
data-color-border-outer-end="#ccc"
data-color-needle-shadow-down="#222"
data-border-shadow-width="0"
data-animation-target="plate"
data-units="ᵍ"
data-title="DIRECTION"
data-font-title-size="19"
data-color-title="#f5f5f5"
data-animation-duration="1500"
data-value="45"
data-animate-on-init="true"
></canvas>
<script>
if (!Array.prototype.forEach) {
Array.prototype.forEach = function(cb) {
var i = 0, s = this.length;
for (; i < s; i++) {
cb && cb(this[i], i, this);
}
}
}
document.fonts && document.fonts.forEach(function(font) {
font.loaded.then(function() {
if (font.family.match(/Led/)) {
document.gauges.forEach(function(gauge) {
gauge.update();
});
}
});
});
var timers = [];
function animateGauges() {
document.gauges.forEach(function(gauge) {
timers.push(setInterval(function() {
gauge.value = Math.random() *
(gauge.options.maxValue - gauge.options.minValue) / 4 +
gauge.options.minValue / 4;
}, gauge.animation.duration + 50));
});
}
function stopGaugesAnimation() {
timers.forEach(function(timer) {
clearInterval(timer);
});
}
</script>
</html>
| akramawardhana/libs | examples/radial.html | HTML | mit | 4,353 |
<div class="row">
<div class="panel panel-default">
<div class="panel-heading">
<h2>{{contact.name}}</h2>
</div>
<div class="panel-body">
<p class="email" ng-show="contact.email">{{contact.email}}</p>
<p class="phone" ng-show="contact.phone">{{contact.phone}}</p>
</div>
</div>
<div class="panel panel-default">
<div class="panel-heading">Available Day
<span class="availableToday yes" ng-show="availableToday(contact)">
( Today : YES )
</span>
<span class="availableToday" ng-hide="availableToday(contact)">
( Today : NO )
</span>
</div>
<div class="panel-body">
<span ng-show="{{contact.canwork.mon}}" class="label label-primary">Monday</span>
<span ng-show="{{contact.canwork.tue}}" class="label label-primary">Tuesday</span>
<span ng-show="{{contact.canwork.wed}}" class="label label-primary">Wednesday</span>
<span ng-show="{{contact.canwork.thu}}" class="label label-primary">Thursday</span>
<span ng-show="{{contact.canwork.fri}}" class="label label-primary">Friday</span>
<span ng-show="{{contact.canwork.sat}}" class="label label-danger">Saturday</span>
<span ng-show="{{contact.canwork.sun}}" class="label label-danger">Sunday</span>
</div>
</div>
<hr/>
<hr/>
<a class="btn btn-left back" href="#/">Go Back</a>
<a class="btn" href="#/edit/{{contact.id}}">Edit</a>
</div>
| withfpp/angular-findPeople | app/partials/view.html | HTML | mit | 1,486 |
https://pubchem.ncbi.nlm.nih.gov/summary/summary.cgi?cid=177355
| andrewdefries/ToxCast | Figure4/FDA_Pesticides/PCID_177355.html | HTML | mit | 64 |
---
layout: post
authors: ["Greg Wilson"]
title: "An Update on Upcoming Bootcamps"
date: 2014-09-06
time: "12:00:00"
tags: ["Bootcamps"]
---
<p>
So it turns out we have more events coming up than
<a href="{{site.baseurl}}/blog/2014/08/fall-2014-bootcamps.html">I realized</a>:
</p>
<!--more-->
<table class="table table-striped">
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>University of Delaware</td>
<td>bootcamp</td>
<td>Sep 11-12, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/au.png" /></td>
<td>University of Melbourne</td>
<td>bootcamp</td>
<td>Sep 15-25, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/uk.png" /></td>
<td>Imperial College London</td>
<td>bootcamp</td>
<td>Sep 16-17, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Lawrence Berkeley National Laboratory</td>
<td>bootcamp</td>
<td>Sep 22-23, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>University of Virginia</td>
<td>instructor training</td>
<td>Sep 22-23, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Federal Reserve Board</td>
<td>bootcamp</td>
<td>Sep 24-25, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Arizona State University</td>
<td>bootcamp</td>
<td>Sep 27-28, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Indiana University</td>
<td>bootcamp</td>
<td>Oct 6-7, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/ca.png" /></td>
<td>University of Toronto</td>
<td>bootcamp</td>
<td>Oct 6-7, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/de.png" /></td>
<td>GFZ Potsdam</td>
<td>bootcamp</td>
<td>Oct 13-14, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Rice University</td>
<td>bootcamp</td>
<td>Oct 13-14, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/uk.png" /></td>
<td>The Genome Analysis Centre, Norwich</td>
<td>instructor training</td>
<td>Oct 22-23, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/ca.png" /></td>
<td>University of Toronto</td>
<td>bootcamp</td>
<td>Oct 30-31, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/au.png" /></td>
<td>University of Sydney</td>
<td>bootcamp</td>
<td>Oct 30-31, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Northwestern University</td>
<td>bootcamp</td>
<td>Oct 31-Nov 1, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/ch.png" /></td>
<td>University of Zurich</td>
<td>bootcamp</td>
<td>Nov 6-7, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>University of Washington</td>
<td>instructor training</td>
<td>Nov 12-14, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Entomological Society of America</td>
<td>bootcamp</td>
<td>Nov 13-14, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>New York Academy of Sciences</td>
<td>bootcamp</td>
<td>Dec 2-3, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Lawrence Berkeley National Laboratory</td>
<td>bootcamp</td>
<td>Dec 16-17, 2014</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>University of Michigan</td>
<td>bootcamp</td>
<td>Jan 5-6, 2015</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>UC Davis</td>
<td>instructor training</td>
<td>Jan 6-8, 2015</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>University of Nebraska</td>
<td>bootcamp</td>
<td>Jan 8-9, 2015</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Earlham College</td>
<td>bootcamp</td>
<td>Jan 11-12, 2015</td>
</tr>
<tr>
<td><img src="{{site.url}}/assets/img/flags/16/us.png" /></td>
<td>Weill Cornell Medical College</td>
<td>bootcamp</td>
<td>Jan 12-13, 2015</td>
</tr>
</table>
| swcarpentry/website | _posts/2014/09/2014-09-06-update-on-fall-2014-bootcamps.html | HTML | mit | 4,624 |
<!DOCTYPE html>
<html>
<head lang="en">
<meta charset="UTF-8">
<title>A lazy tree</title>
<link rel="stylesheet" href="vendor/bootstrap/dist/css/bootstrap.css"/>
<link rel="stylesheet" href="vendor/angular-ui-tree/dist/angular-ui-tree.min.css"/>
</head>
<body ng-app="lazyTree">
<div class="container" ng-controller="TreeCtrl">
<div class="jumbotron">
<h2>A simple example of a lazy loading tree using ui-tree</h3>
<p class="text-right">v. 0.0.1</p>
</div>
<div ui-tree data-drag-enabled="false">
<ol ui-tree-nodes data-collapsed ng-model="companies">
<li ui-tree-node ng-repeat="company in companies">
<div ui-tree-node ng-class="{'no-children': !companies.length}" >
<button class="btn btn-lg btn-link disclosure-btn" ng-click="toggle(this); loadNames(collapsed)">
<span class="caret" ng-class="{open: !collapsed}"></span>
</button> {{ company.company }}
<ol ui-tree-nodes ng-model="names" ng-class="{hidden: collapsed}">
<li ui-tree-node ng-repeat="name in names">
<button class="btn btn-lg btn-link disclosure-btn" ng-click="toggle(this); loadEmails(collapsed)">
<span class="caret" ng-class="{open: !collapsed}"></span>
</button> {{ name.fullname }}
<ol ui-tree-nodes ng-model="emails" ng-class="{hidden: collapsed}">
<li ui-tree-node ng-repeat="email in emails">
{{ email.email }}
</li>
</ol>
</li>
</ol>
</div>
</li>
</ol>
</div>
</div>
<script src="vendor/jquery/dist/jquery.js"></script>
<script src="vendor/angular/angular.js"></script>
<script src="vendor/bootstrap/dist/js/bootstrap.js"></script>
<script src="vendor/angular-ui-tree/dist/angular-ui-tree.js"></script>
<script src="src/app.js"></script>
</body>
</html> | m0t0r/ng-fun | lazy_tree/index.html | HTML | mit | 2,264 |
<!doctype html>
<!--[if lt IE 7]><html class="no-js lt-ie9 lt-ie8 lt-ie7" lang="en"> <![endif]-->
<!--[if (IE 7)&!(IEMobile)]><html class="no-js lt-ie9 lt-ie8" lang="en"><![endif]-->
<!--[if (IE 8)&!(IEMobile)]><html class="no-js lt-ie9" lang="en"><![endif]-->
<!--[if gt IE 8]><!--> <html class="no-js" lang="en"><!--<![endif]-->
<head>
{% include head.html %}
<script src="{{ site.url }}/assets/js/scrolltop.js"></script>
<link rel="stylesheet" href="{{ site.url }}/assets/css/scrolltop.css">
</head>
<body id="post">
<!-- Return to Top -->
<div onClick="scrollback()" id="return-to-top"><i class="fa fa-chevron-up"></i></div>
{% include navigation.html %}
<div id="main" role="main">
<article class="hentry">
{% if page.header-img %}<div class="header-img-overflow"><img src="{{ site.url }}/{{ page.header-img }}" class="entry-feature-image" alt="{{ page.title }}" {% if site.logo == null %}style="margin-top:0;"{% endif %}></div>{% if page.image.credit %}<p class="image-credit">Image credit: <a href="{{ page.image.creditlink }}">{{ page.image.credit }}</a></p>{% endif %}{% endif %}
<div class="entry-wrapper">
<header class="entry-header center">
{% if page.link %}
<h1 class="entry-title"><a href="{{ page.link }}">{% if page.headline %}{{ page.headline }}{% else %}{{ page.title }}{% endif %} <span class="link-arrow">→</span></a></h1>
{% else %}
<h1 class="entry-title pulse">{% if page.headline %}{{ page.headline }}{% else %}{{ page.title }}{% endif %}</h1>
{% endif %}
</header>
<footer class="entry-meta">
{% if page.contributors %}
{% assign author = page.contributors %}
{% endif %}
<!--
{% if author.avatar contains 'http' %}
<img src="{{ author.avatar }}" class="bio-photo" alt="{{ author.name }} bio photo"></a>
{% elsif author.avatar %}
<img src="{{ site.url }}/images/{{ author.avatar }}" class="bio-photo" alt="{{ author.name }} bio photo"></a>
{% endif %}
-->
<span class="author vcard">By <span class="fn">{{ author }}</span></span>
{% if page.last_updated %}
<span class="entry-date date published"><time datetime="{{ page.last_updated | date_to_xmlschema }}"><i class="fa fa-calendar-o"></i> <strong>Last Updated:</strong> {{ page.last_updated | last_updated: "%B %d, %Y" }}</time></span>
{% endif %}
<!--
{% if page.modified %}<span class="entry-date date modified"><time datetime="{{ page.modified }}"><i class="fa fa-pencil"></i> {{ page.modified | date: "%B %d, %Y" }}</time></span>{% endif %}
-->
{% if site.owner.disqus-shortname and page.comments or site.comments %}<span class="entry-comments"><i class="fa fa-comment-o"></i> <a href="#disqus_thread">Comment</a></span>{% endif %}
{% if page.share %}{% include social-share.html %}{% endif %}
<!--
<ul class="entry-tags">
Tags: {% for tag in page.tags %}<li><a href="{{ site.url }}/tags/#{{ tag }}" title="Pages tagged {{ tag }}">{{ tag }}</a></li>{% endfor %}
</ul>
-->
</footer>
<div class="entry-content">
{{ content }}
{% if site.owner.disqus-shortname and page.comments or site.comments %}
<div id="disqus_thread"></div><!-- /#disqus_thread -->
{% include disqus-comments.html %}
{% endif %}
</div><!-- /.entry-content -->
</div><!-- /.entry-wrapper -->
<nav class="pagination" role="navigation">
{% if page.previous %}
<a href="{{ site.url }}{{ page.previous.url }}" class="btn" title="{{ page.previous.title }}">Previous</a>
{% endif %}
{% if page.next %}
<a href="{{ site.url }}{{ page.next.url }}" class="btn" title="{{ page.next.title }}">Next</a>
{% endif %}
</nav><!-- /.pagination -->
</article>
</div><!-- /#main -->
<div class="footer-wrapper">
<footer role="contentinfo" class="entry-wrapper">
{% include footer.html %}
</footer>
</div><!-- /.footer-wrapper -->
{% include scripts.html %}
</body>
</html>
| grubdragon/erc-website-jekyll | _layouts/tutorial.html | HTML | mit | 4,131 |
<!DOCTYPE HTML>
<!-- NewPage -->
<html lang="en">
<head>
<!-- Generated by javadoc (11.0.13) on Thu Feb 03 14:46:53 MST 2022 -->
<title>Uses of Class mil.nga.geopackage.extension.coverage.GriddedTileDao (GeoPackage Core 6.2.0 API)</title>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta name="dc.created" content="2022-02-03">
<link rel="stylesheet" type="text/css" href="../../../../../../stylesheet.css" title="Style">
<link rel="stylesheet" type="text/css" href="../../../../../../jquery/jquery-ui.css" title="Style">
<script type="text/javascript" src="../../../../../../script.js"></script>
<script type="text/javascript" src="../../../../../../jquery/jszip/dist/jszip.min.js"></script>
<script type="text/javascript" src="../../../../../../jquery/jszip-utils/dist/jszip-utils.min.js"></script>
<!--[if IE]>
<script type="text/javascript" src="../../../../../../jquery/jszip-utils/dist/jszip-utils-ie.min.js"></script>
<![endif]-->
<script type="text/javascript" src="../../../../../../jquery/jquery-3.5.1.js"></script>
<script type="text/javascript" src="../../../../../../jquery/jquery-ui.js"></script>
</head>
<body>
<script type="text/javascript"><!--
try {
if (location.href.indexOf('is-external=true') == -1) {
parent.document.title="Uses of Class mil.nga.geopackage.extension.coverage.GriddedTileDao (GeoPackage Core 6.2.0 API)";
}
}
catch(err) {
}
//-->
var pathtoroot = "../../../../../../";
var useModuleDirectories = true;
loadScripts(document, 'script');</script>
<noscript>
<div>JavaScript is disabled on your browser.</div>
</noscript>
<header role="banner">
<nav role="navigation">
<div class="fixedNav">
<!-- ========= START OF TOP NAVBAR ======= -->
<div class="topNav"><a id="navbar.top">
<!-- -->
</a>
<div class="skipNav"><a href="#skip.navbar.top" title="Skip navigation links">Skip navigation links</a></div>
<a id="navbar.top.firstrow">
<!-- -->
</a>
<ul class="navList" title="Navigation">
<li><a href="../../../../../../index.html">Overview</a></li>
<li><a href="../package-summary.html">Package</a></li>
<li><a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">Class</a></li>
<li class="navBarCell1Rev">Use</li>
<li><a href="../package-tree.html">Tree</a></li>
<li><a href="../../../../../../deprecated-list.html">Deprecated</a></li>
<li><a href="../../../../../../index-all.html">Index</a></li>
<li><a href="../../../../../../help-doc.html">Help</a></li>
</ul>
</div>
<div class="subNav">
<ul class="navList" id="allclasses_navbar_top">
<li><a href="../../../../../../allclasses.html">All Classes</a></li>
</ul>
<ul class="navListSearch">
<li><label for="search">SEARCH:</label>
<input type="text" id="search" value="search" disabled="disabled">
<input type="reset" id="reset" value="reset" disabled="disabled">
</li>
</ul>
<div>
<script type="text/javascript"><!--
allClassesLink = document.getElementById("allclasses_navbar_top");
if(window==top) {
allClassesLink.style.display = "block";
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<div>JavaScript is disabled on your browser.</div>
</noscript>
</div>
<a id="skip.navbar.top">
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</a></div>
<!-- ========= END OF TOP NAVBAR ========= -->
</div>
<div class="navPadding"> </div>
<script type="text/javascript"><!--
$('.navPadding').css('padding-top', $('.fixedNav').css("height"));
//-->
</script>
</nav>
</header>
<main role="main">
<div class="header">
<h2 title="Uses of Class mil.nga.geopackage.extension.coverage.GriddedTileDao" class="title">Uses of Class<br>mil.nga.geopackage.extension.coverage.GriddedTileDao</h2>
</div>
<div class="classUseContainer">
<ul class="blockList">
<li class="blockList">
<table class="useSummary">
<caption><span>Packages that use <a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">GriddedTileDao</a></span><span class="tabEnd"> </span></caption>
<tr>
<th class="colFirst" scope="col">Package</th>
<th class="colLast" scope="col">Description</th>
</tr>
<tbody>
<tr class="altColor">
<th class="colFirst" scope="row"><a href="#mil.nga.geopackage.extension.coverage">mil.nga.geopackage.extension.coverage</a></th>
<td class="colLast"> </td>
</tr>
</tbody>
</table>
</li>
<li class="blockList">
<ul class="blockList">
<li class="blockList">
<section role="region"><a id="mil.nga.geopackage.extension.coverage">
<!-- -->
</a>
<h3>Uses of <a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">GriddedTileDao</a> in <a href="../package-summary.html">mil.nga.geopackage.extension.coverage</a></h3>
<table class="useSummary">
<caption><span>Methods in <a href="../package-summary.html">mil.nga.geopackage.extension.coverage</a> that return <a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">GriddedTileDao</a></span><span class="tabEnd"> </span></caption>
<tr>
<th class="colFirst" scope="col">Modifier and Type</th>
<th class="colSecond" scope="col">Method</th>
<th class="colLast" scope="col">Description</th>
</tr>
<tbody>
<tr class="altColor">
<td class="colFirst"><code>static <a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">GriddedTileDao</a></code></td>
<th class="colSecond" scope="row"><span class="typeNameLabel">GriddedTileDao.</span><code><span class="memberNameLink"><a href="../GriddedTileDao.html#create(mil.nga.geopackage.db.GeoPackageCoreConnection)">create</a></span>​(<a href="../../../db/GeoPackageCoreConnection.html" title="class in mil.nga.geopackage.db">GeoPackageCoreConnection</a> db)</code></th>
<td class="colLast">
<div class="block">Create the DAO</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static <a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">GriddedTileDao</a></code></td>
<th class="colSecond" scope="row"><span class="typeNameLabel">GriddedTileDao.</span><code><span class="memberNameLink"><a href="../GriddedTileDao.html#create(mil.nga.geopackage.GeoPackageCore)">create</a></span>​(<a href="../../../GeoPackageCore.html" title="interface in mil.nga.geopackage">GeoPackageCore</a> geoPackage)</code></th>
<td class="colLast">
<div class="block">Create the DAO</div>
</td>
</tr>
<tr class="altColor">
<td class="colFirst"><code><a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">GriddedTileDao</a></code></td>
<th class="colSecond" scope="row"><span class="typeNameLabel">CoverageDataCore.</span><code><span class="memberNameLink"><a href="../CoverageDataCore.html#getGriddedTileDao()">getGriddedTileDao</a></span>()</code></th>
<td class="colLast">
<div class="block">Get a 2D Gridded Tile DAO</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static <a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">GriddedTileDao</a></code></td>
<th class="colSecond" scope="row"><span class="typeNameLabel">CoverageDataCore.</span><code><span class="memberNameLink"><a href="../CoverageDataCore.html#getGriddedTileDao(mil.nga.geopackage.db.GeoPackageCoreConnection)">getGriddedTileDao</a></span>​(<a href="../../../db/GeoPackageCoreConnection.html" title="class in mil.nga.geopackage.db">GeoPackageCoreConnection</a> db)</code></th>
<td class="colLast">
<div class="block">Get a 2D Gridded Tile DAO</div>
</td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>static <a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">GriddedTileDao</a></code></td>
<th class="colSecond" scope="row"><span class="typeNameLabel">CoverageDataCore.</span><code><span class="memberNameLink"><a href="../CoverageDataCore.html#getGriddedTileDao(mil.nga.geopackage.GeoPackageCore)">getGriddedTileDao</a></span>​(<a href="../../../GeoPackageCore.html" title="interface in mil.nga.geopackage">GeoPackageCore</a> geoPackage)</code></th>
<td class="colLast">
<div class="block">Get a 2D Gridded Tile DAO</div>
</td>
</tr>
</tbody>
</table>
</section>
</li>
</ul>
</li>
</ul>
</div>
</main>
<footer role="contentinfo">
<nav role="navigation">
<!-- ======= START OF BOTTOM NAVBAR ====== -->
<div class="bottomNav"><a id="navbar.bottom">
<!-- -->
</a>
<div class="skipNav"><a href="#skip.navbar.bottom" title="Skip navigation links">Skip navigation links</a></div>
<a id="navbar.bottom.firstrow">
<!-- -->
</a>
<ul class="navList" title="Navigation">
<li><a href="../../../../../../index.html">Overview</a></li>
<li><a href="../package-summary.html">Package</a></li>
<li><a href="../GriddedTileDao.html" title="class in mil.nga.geopackage.extension.coverage">Class</a></li>
<li class="navBarCell1Rev">Use</li>
<li><a href="../package-tree.html">Tree</a></li>
<li><a href="../../../../../../deprecated-list.html">Deprecated</a></li>
<li><a href="../../../../../../index-all.html">Index</a></li>
<li><a href="../../../../../../help-doc.html">Help</a></li>
</ul>
</div>
<div class="subNav">
<ul class="navList" id="allclasses_navbar_bottom">
<li><a href="../../../../../../allclasses.html">All Classes</a></li>
</ul>
<div>
<script type="text/javascript"><!--
allClassesLink = document.getElementById("allclasses_navbar_bottom");
if(window==top) {
allClassesLink.style.display = "block";
}
else {
allClassesLink.style.display = "none";
}
//-->
</script>
<noscript>
<div>JavaScript is disabled on your browser.</div>
</noscript>
</div>
<a id="skip.navbar.bottom">
<!-- -->
</a></div>
<!-- ======== END OF BOTTOM NAVBAR ======= -->
</nav>
<p class="legalCopy"><small>Copyright © 2022 <a href="https://www.nga.mil/">National Geospatial-Intelligence Agency</a>. All rights reserved.</small></p>
</footer>
</body>
</html>
| ngageoint/geopackage-core-java | docs/docs/api/mil/nga/geopackage/extension/coverage/class-use/GriddedTileDao.html | HTML | mit | 9,842 |
<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
<html lang="en">
<head>
<meta name="generator" content="AWStats 7.1.1 (build 1.989) from config file awstats.desenvolupament.vitaworke3.com-https.conf (http://www.awstats.org)">
<meta name="robots" content="noindex,nofollow">
<meta http-equiv="content-type" content="text/html; charset=utf-8">
<meta http-equiv="description" content="Awstats - Advanced Web Statistics for desenvolupament.vitaworke3.com (2015-01) - unknownip">
<title>Statistics for desenvolupament.vitaworke3.com (2015-01) - unknownip</title>
<style type="text/css">
body { font: 11px verdana, arial, helvetica, sans-serif; background-color: #FFFFFF; margin-top: 0; margin-bottom: 0; }
.aws_bodyl { }
.aws_border { border-collapse: collapse; background-color: #CCCCDD; padding: 1px 1px 1px 1px; margin-top: 0px; margin-bottom: 0px; }
.aws_title { font: 13px verdana, arial, helvetica, sans-serif; font-weight: bold; background-color: #CCCCDD; text-align: center; margin-top: 0; margin-bottom: 0; padding: 1px 1px 1px 1px; color: #000000; }
.aws_blank { font: 13px verdana, arial, helvetica, sans-serif; background-color: #FFFFFF; text-align: center; margin-bottom: 0; padding: 1px 1px 1px 1px; }
.aws_data {
background-color: #FFFFFF;
border-top-width: 1px;
border-left-width: 0px;
border-right-width: 0px;
border-bottom-width: 0px;
}
.aws_formfield { font: 13px verdana, arial, helvetica; }
.aws_button {
font-family: arial,verdana,helvetica, sans-serif;
font-size: 12px;
border: 1px solid #ccd7e0;
background-image : url(/awstats-icon/other/button.gif);
}
th { border-color: #ECECEC; border-left-width: 0px; border-right-width: 1px; border-top-width: 0px; border-bottom-width: 1px; padding: 1px 2px 1px 1px; font: 11px verdana, arial, helvetica, sans-serif; text-align:center; color: #000000; }
th.aws { border-color: #ECECEC; border-left-width: 0px; border-right-width: 1px; border-top-width: 0px; border-bottom-width: 1px; padding: 1px 2px 1px 1px; font-size: 13px; font-weight: bold; }
td { border-color: #ECECEC; border-left-width: 0px; border-right-width: 1px; border-top-width: 0px; border-bottom-width: 1px; font: 11px verdana, arial, helvetica, sans-serif; text-align:center; color: #000000; }
td.aws { border-color: #ECECEC; border-left-width: 0px; border-right-width: 1px; border-top-width: 0px; border-bottom-width: 1px; font: 11px verdana, arial, helvetica, sans-serif; text-align:left; color: #000000; padding: 0px;}
td.awsm { border-left-width: 0px; border-right-width: 0px; border-top-width: 0px; border-bottom-width: 0px; font: 11px verdana, arial, helvetica, sans-serif; text-align:left; color: #000000; padding: 0px; }
b { font-weight: bold; }
a { font: 11px verdana, arial, helvetica, sans-serif; }
a:link { color: #0011BB; text-decoration: none; }
a:visited { color: #0011BB; text-decoration: none; }
a:hover { color: #605040; text-decoration: underline; }
.currentday { font-weight: bold; }
</style>
</head>
<body style="margin-top: 0px">
<a name="top"></a>
<a name="menu"> </a>
<form name="FormDateFilter" action="/cgi-bin/awstats.pl?config=desenvolupament.vitaworke3.com-https&staticlinks&configdir=/usr/local/psa/etc/awstats&output=unknownip" style="padding: 0px 0px 0px 0px; margin-top: 0">
<table class="aws_border" border="0" cellpadding="2" cellspacing="0" width="100%">
<tr><td>
<table class="aws_data sortable" border="0" cellpadding="1" cellspacing="0" width="100%">
<tr><td class="aws" valign="middle"><b>Statistics for:</b> </td><td class="aws" valign="middle"><span style="font-size: 14px;">desenvolupament.vitaworke3.com</span></td><td align="right" rowspan="3"><a href="http://www.awstats.org" target="awstatshome"><img src="/awstats-icon/other/awstats_logo6.png" border="0" alt='Awstats Web Site' title='Awstats Web Site' /></a></td></tr>
<tr valign="middle"><td class="aws" valign="middle" width="150"><b>Last Update:</b> </td><td class="aws" valign="middle"><span style="font-size: 12px;"><span style="color: #880000">Never updated (See 'Build/Update' on awstats_setup.html page)</span></span></td></tr>
<tr><td class="aws" valign="middle"><b>Reported period:</b></td><td class="aws" valign="middle"><span style="font-size: 14px;">Month Jan 2015</span></td></tr>
</table>
</td></tr></table>
</form><br />
<table>
<tr><td class="aws"><a href="javascript:parent.window.close();">Close window</a></td></tr>
</table>
<a name="unknownip"> </a><br />
<table class="aws_border sortable" border="0" cellpadding="2" cellspacing="0" width="100%">
<tr><td class="aws_title" width="70%">Unresolved IP Address </td><td class="aws_blank"> </td></tr>
<tr><td colspan="2">
<table class="aws_data" border="1" cellpadding="2" cellspacing="0" width="100%">
<tr bgcolor="#ECECEC"><th>0 Unknown (unresolved ip)</th><th bgcolor="#4477DD" width="80">Pages</th><th bgcolor="#66DDEE" width="80">Hits</th><th class="datasize" bgcolor="#2EA495" width="80">Bandwidth</th><th width="120">Last visit</th></tr>
</table></td></tr></table><br />
<br /><br />
<span dir="ltr" style="font: 11px verdana, arial, helvetica; color: #000000;"><b>Advanced Web Statistics 7.1.1 (build 1.989)</b> - <a href="http://www.awstats.org" target="awstatshome">Created by awstats</a></span><br />
<br />
</body>
</html>
| VITAWORKE3/Projecte | statistics/webstat-ssl/2015-01/awstats.desenvolupament.vitaworke3.com-https.unknownip.html | HTML | mit | 5,351 |
Parsed configuration options
============================
title: My book title
author: "Change this: Author Name"
edition: First edition
language: en
publication_date: null
generator: [array]
name: easybook
version: 4.8-DEV
contents: [array]
0: [array]
element: cover
editions: [array]
edition3: [array]
format: html
highlight_code: false
include_styles: true
isbn: null
labels: [array]
0: appendix
1: chapter
2: figure
margin: [array]
top: 25mm
bottom: 25mm
inner: 30mm
outter: 20mm
page_size: A4
theme: clean
toc: [array]
deep: 2
elements: [array]
0: appendix
1: chapter
two_sided: true
| juanda/doDoc | src/Easybook/Tests/Configurator/fixtures/book2/expected/edition3/book.html | HTML | mit | 973 |
<div class = "row">
<div class = "col-sm-12 countdown-timer">
Time Remaining: {{timer}}
</div>
</div>
<div class = "row">
<div class = "col-sm-6">
<span class = "player-health-header"></span>
<div class="progress-bar" role="progressbar" aria-valuenow="100"
aria-valuemin="0" aria-valuemax="100" style="width:0%">
<span class = "perc">{{health}}</span>
</div>
</div>
<div class = "col-sm-6">
<span class = "enemy-health-header"></span>
<div class="enemy-progress-bar" role="progressbar" aria-valuenow="100" aria-valuemin="0" aria-valuemax="100" style="width:0%">
<span class = "perc">{{enemyHealth}}</span>
</div>
</div> | Petey101/summoners-universe | app/assets/templates/timer.html | HTML | mit | 635 |
<div ng-controller="projectsCtrl" class="container sub-page" style="width:100%;">
<div class="row" style="margin:0">
<uib-tabset vertical="true" class="tabs-left" >
<uib-tab ng-repeat="project in projects" heading="{{project.name}}" active="tab.active" disable="tab.disabled">
<ul class="{{project.id}} content-list" >
<li class="name"><h3>{{project.name}}</h3></li>
<li class="description">Description: {{project.description}}</li>
<li class="status">Status: {{project.status}}</li>
<li class="languages">Languages: {{project.languages}}</li>
<li class="code_url">Source: {{project.code_url}}</li>
<li class="last-updated">Last Updated: {{project.last_updated}}</li>
</ul>
</uib-tab>
</uib-tabset>
</div>
</div>
| codeforsanjose/codeforsanjose-frontend | templates/projects.html | HTML | mit | 780 |
<!DOCTYPE html>
<html xmlns:wb="http://open.weibo.com/wb">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<!-- 上述3个meta标签*必须*放在最前面，任何其他内容都*必须*跟随其后！ -->
{% block meta %}<!-- block meta -->{% endblock %}
<title>{% block title %} ? {% endblock %} - Mblog Python Webapp</title>
<link rel="shortcut icon" href="/static/img/favicon.ico"/>
<link rel="bookmark" href="/static/img/favicon.ico"/>
<!-- uikit 核心 CSS 文件 -->
<link rel="stylesheet" href="//cdn.bootcss.com/uikit/2.26.3/css/uikit.min.css">
<link rel="stylesheet" href="/static/css/uikit.gradient.min.css">
<link rel="stylesheet" href="/static/css/components/sticky.min.css" />
<link rel="stylesheet" href="/static/css/pygments.css" />
<link rel="stylesheet" href="/static/css/mblog.css">
<script src="http://tjs.sjs.sinajs.cn/open/api/js/wb.js?appkey=366603916" type="text/javascript" charset="utf-8"></script>
{% block beforehead %}<!-- before head -->{% endblock %}
</head>
<body style="background-color: #fff;">
<nav class="tm-navbar uk-navbar uk-navbar-attached" data-uk-sticky>
<div class="uk-container uk-container-center">
<a class="uk-navbar-brand uk-hidden-small" href="/bootstrap/" style="background: #563d7c;">
<img src="/static/img/bootstrap.png" alt="Brand-other-index" style="height: 42px;" />
</a>
<ul class="uk-navbar-nav uk-hidden-small" id="navbar-left">
<li><a href="/uk/"><i class="uk-icon-home"></i> Home</a></li>
<li><a href="/uk/manage"><i class="uk-icon-book"></i> Manage</a></li>
<li><a href="//github.com/moling3650/mblog" target="_blank"><i class="uk-icon-code"></i> code</a></li>
</ul>
<ul class="uk-navbar-nav uk-navbar-flip">
{% if __user__ %}
<li class="uk-parent" data-uk-dropdown="" aria-haspopup="true" aria-expanded="true">
<a href="#"><i class="uk-icon-user"></i> <span class="uk-hidden-small">{{ __user__.name }}</span> <i class="uk-icon-caret-down"></i></a>
<div class="uk-dropdown uk-dropdown-navbar uk-dropdown-bottom">
<ul class="uk-nav uk-nav-navbar">
{% if __user__.admin %}
<li><a href="/uk/manage/blogs/create"><i class="uk-icon-pencil"></i> New Blog</a></li>
{% endif %}
<li><a href="/signout"><i class="uk-icon-sign-out"></i> Sign Out</a></li>
</ul>
</div>
</li>
{% else %}
<li><a href="https://api.weibo.com/oauth2/authorize?client_id=366603916&redirect_uri=http://www.qiangtaoli.com/oauth2"><i class="uk-icon-weibo"></i></a></li>
<li><a href="/uk/signin"><i class="uk-icon-sign-in"></i><span class="uk-hidden-small"> Sign In</span></a></li>
<li><a href="/uk/register"><i class="uk-icon-registered"></i><span class="uk-hidden-small"> Register</span></a></li>
{% endif %}
</ul>
<a href="#tm-offcanvas" class="uk-navbar-toggle uk-visible-small" data-uk-offcanvas></a>
<a class="uk-navbar-brand uk-navbar-center uk-visible-small" href="/">
<img src="/static/img/bootstrap.png" alt="Brand-other-index" style="height: 42px;" />
</a>
</div>
</nav>
<div class="uk-container uk-container-center">
<div class="uk-grid">
<!-- content -->
{% block content %}
{% endblock %}
<!-- // content -->
</div>
</div>
<a id="go-top" href="javascript:void(0);" title="go-top" hidden="hidden"><i class="uk-icon-arrow-up uk-icon-large"></i></a>
<footer class="uk-margin-large-top" style="background-color:#ddd; border-top:1px solid #aaa;">
<div class="uk-container uk-container-center uk-text-center">
<div class="uk-panel uk-margin-top uk-margin-bottom">
<p>
<a target="_blank" href="http://weibo.com/moling3650" class="uk-icon-button uk-icon-weibo"></a>
<a target="_blank" href="https://github.com/moling3650" class="uk-icon-button uk-icon-github"></a>
</p>
<p>Powered by <a href="http://getuikit.net">uikit</a></p>
<p><a href="http://www.miitbeian.gov.cn">粤ICP备16049607号-1</a> © 2016 mblog</p>
<p><a href="www.qiangtaoli.com" target="_blank">www.qiangtaoli.com</a>. All rights reserved.</p>
</div>
</div>
</footer>
<nav id="tm-offcanvas" class="uk-offcanvas">
<div class="uk-offcanvas-bar">
<ul class="uk-nav uk-nav-offcanvas">
<li><a href="/uk/"> Home</a></li>
<li><a href="/uk/manage"> Manage</a></li>
<li><a href="//github.com/moling3650/mblog" target="_blank"> code</a></li>
</ul>
</div>
</nav>
<script src="//cdn.bootcss.com/jquery/1.11.3/jquery.min.js"></script>
<!-- uikit 核心 JavaScript 文件 -->
<script src="//cdn.bootcss.com/uikit/2.26.3/js/uikit.min.js"></script>
<script src="/static/js/components/sticky.min.js"></script>
<script src="/static/js/awesome.js"></script>
<script>
$('.uk-navbar-brand').attr('href', location.href.replace('/uk/', '/bootstrap/'));
</script>
{% block script %}
{% endblock %}
</body>
</html> | moling3650/mblog | www/app/templates/uk-base.html | HTML | mit | 5,712 |
<div class="container-fluid" ng-controller="View1Ctrl" style="background-image: url(http://bgfons.com/upload/aluminum_texture1644.jpg); background-repeat: no-repeat; height: 640px; color: white;">
<div class="row text-center" >
<div class="col-md-11" style="padding: 10px; border-left: 1px solid white; padding-right: 30px;">
<h2 style="margin: 45px;">Vinay demo blog!</h2>
<h4 style="margin: 65px;"> Login: abc@gmail.com  password: 123</h4>
<div><br/><br/><br/></div>
<div class="input-group" style="margin: 45px;" >
<span class="input-group-addon"><i class="fa fa-fw fa-envelope-o"></i></span>
<input class="form-control" type="text" placeholder="Email Address" ng-model="formModel.email">
</div>
<div class="input-group" style="margin: 45px;">
<span class="input-group-addon"><i class="fa fa-fw fa-lock"></i></span>
<input class="form-control" type="password" placeholder="Password" ng-model="formModel.password">
</div>
<button class="btn btn-primary" style="margin: 15px;" ng-click="submit()">Login</button>
<div ng-if="flag" class="text-danger" style="background-color: white; margin-left:150px; margin-right: 150px;">* Invalid Username or Password</div>
</div>
</div>
</div>
| nori-vinay/Angular-Blog-3 | app/view1/view1.html | HTML | mit | 1,235 |
<table width="90%" border="0"><tr><td><script>function openfile(url) {fullwin = window.open(url, "fulltext", "toolbar=no,location=no,directories=no,status=no,menubar=no,scrollbars=yes,resizable=yes");}</script><div class="flayoutclass"><div class="flayoutclass_first"><table class="tableoutfmt2"><tr><th class="std1"><b>條目 </b></th><td class="std2">貴遠鄙近</td></tr>
<tr><th class="std1"><b>注音 </b></th><td class="std2">ㄍㄨㄟ<sup class="subfont">ˋ</sup> ㄩㄢ<sup class="subfont">ˇ</sup> ㄅ｜<sup class="subfont">ˇ</sup> ㄐ｜ㄣ<sup class="subfont">ˋ</sup></td></tr>
<tr><th class="std1"><b>漢語拼音 </b></th><td class="std2"><font class="english_word">guì yuǎn bǐ jìn</font></td></tr>
<tr><th class="std1"><b>釋義 </b></th><td class="std2">推崇古代的事物，而鄙視當代的。宋˙胡仔˙苕溪漁隱叢話前集˙卷二十一˙香山居士：<img src=/cydic/dicword/fa40.gif border=0 alt=* class=fontimg valign=center>楚人發語之辭曰羌、曰蹇，平語之詞曰些，一經屈、宋采用，後世遂為佳句。但世俗常情，不能無貴遠鄙近耳。<img src=/cydic/dicword/fa41.gif border=0 alt=* class=fontimg valign=center>亦作<img src=/cydic/dicword/fa40.gif border=0 alt=* class=fontimg valign=center>貴遠賤近<img src=/cydic/dicword/fa41.gif border=0 alt=* class=fontimg valign=center>。</td></tr>
<tr><th class="std1"><b><font class="fltypefont">附錄</font> </b></th><td class="std2">修訂本參考資料</td></tr>
</td></tr></table></div> <!-- flayoutclass_first --><div class="flayoutclass_second"></div> <!-- flayoutclass_second --></div> <!-- flayoutclass --></td></tr></table>
| BuzzAcademy/idioms-moe-unformatted-data | all-data/23000-23999/23486-22.html | HTML | mit | 1,692 |
<!DOCTYPE html>
<!--[if lt IE 9]><html class="no-js lt-ie9" lang="en" dir="ltr"><![endif]-->
<!--[if gt IE 8]><!-->
<html class="no-js" lang="en" dir="ltr">
<!--<![endif]-->
<!-- Usage: /eic/site/ccc-rec.nsf/tpl-eng/template-1col.html?Open&id=3 (optional: ?Open&page=filename.html&id=x) -->
<!-- Created: ; Product Code: 536; Server: stratnotes2.ic.gc.ca -->
<head>
<!-- Title begins / Début du titre -->
<title>
D.M.K. Marine Services Ltd. -
Complete profile - Canadian Company Capabilities - Industries and Business - Industry Canada
</title>
<!-- Title ends / Fin du titre -->
<!-- Meta-data begins / Début des métadonnées -->
<meta charset="utf-8" />
<meta name="dcterms.language" title="ISO639-2" content="eng" />
<meta name="dcterms.title" content="" />
<meta name="description" content="" />
<meta name="dcterms.description" content="" />
<meta name="dcterms.type" content="report, data set" />
<meta name="dcterms.subject" content="businesses, industry" />
<meta name="dcterms.subject" content="businesses, industry" />
<meta name="dcterms.issued" title="W3CDTF" content="" />
<meta name="dcterms.modified" title="W3CDTF" content="" />
<meta name="keywords" content="" />
<meta name="dcterms.creator" content="" />
<meta name="author" content="" />
<meta name="dcterms.created" title="W3CDTF" content="" />
<meta name="dcterms.publisher" content="" />
<meta name="dcterms.audience" title="icaudience" content="" />
<meta name="dcterms.spatial" title="ISO3166-1" content="" />
<meta name="dcterms.spatial" title="gcgeonames" content="" />
<meta name="dcterms.format" content="HTML" />
<meta name="dcterms.identifier" title="ICsiteProduct" content="536" />
<!-- EPI-11240 -->
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<!-- MCG-202 -->
<meta content="width=device-width,initial-scale=1" name="viewport">
<!-- EPI-11567 -->
<meta name = "format-detection" content = "telephone=no">
<!-- EPI-12603 -->
<meta name="robots" content="noarchive">
<!-- EPI-11190 - Webtrends -->
<script>
var startTime = new Date();
startTime = startTime.getTime();
</script>
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<link href="/utils/scripts/_WET_4-0/apps/themes-dist/gcweb/assets/favicon.ico" rel="icon" type="image/x-icon">
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<summary>Third-Party Information Liability Disclaimer</summary>
<p>Some of the information on this Web page has been provided by external sources. The Government of Canada is not responsible for the accuracy, reliability or currency of the information supplied by external sources. Users wishing to rely upon this information should consult directly with the source of the information. Content provided by external sources is not subject to official languages, privacy and accessibility requirements.</p>
</details>
<h2>
D.M.K. Marine Services Ltd.
</h2>
<div class="row">
<div class="col-md-5">
<h2 class="h5 mrgn-bttm-0">Legal/Operating Name:</h2>
<p>D.M.K. Marine Services Ltd.</p>
<p><a href="mailto:dmkmarine@nb.aibn.com" title="dmkmarine@nb.aibn.com">dmkmarine@nb.aibn.com</a></p>
</div>
<div class="col-md-4 mrgn-sm-sm">
<h2 class="h5 mrgn-bttm-0">Mailing Address:</h2>
<address class="mrgn-bttm-md">
P.O Box 27125<br/>
RPO Lancaster <br/>
SAINT JOHN,
New Brunswick<br/>
E2M 5S8
<br/>
</address>
<h2 class="h5 mrgn-bttm-0">Location Address:</h2>
<address class="mrgn-bttm-md">
130 Lingly Lane <br/>
SAINT JOHN,
New Brunswick<br/>
E2M 4K5
<br/>
</address>
<p class="mrgn-bttm-0"><abbr title="Telephone">Tel.</abbr>:
(506) 635-4150
</p>
<p class="mrgn-bttm-lg"><abbr title="Facsimile">Fax</abbr>:
(506) 635-8714</p>
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Full profile
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Contact information
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<div class="col-md-3">
<strong>
Keith S.
Rogers
</strong></div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Title:
</strong>
</div>
<div class="col-md-7">
<!--if client gender is not null or empty we use gender based job title-->
Chairman
</div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Area of Responsibility:
</strong>
</div>
<div class="col-md-7">
Management Executive.
</div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Telephone:
</strong>
</div>
<div class="col-md-7">
(506) 635-4150
</div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Facsimile:
</strong>
</div>
<div class="col-md-7">
(506) 635-8714
</div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Email:
</strong>
</div>
<div class="col-md-7">
dmkmarine@nb.aibn.com
</div>
</div>
</section>
<p class="mrgn-tp-lg text-right small hidden-print">
<a href="#wb-cont">top of page</a>
</p>
<!-- Company Description -->
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Company description
</h3>
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<div class="row">
<div class="col-md-5">
<strong>
Country of Ownership:
</strong>
</div>
<div class="col-md-7">
Canada
</div>
</div>
<div class="row">
<div class="col-md-5">
<strong>
Exporting:
</strong>
</div>
<div class="col-md-7">
No
</div>
</div>
<div class="row">
<div class="col-md-5">
<strong>
Primary Industry (NAICS):
</strong>
</div>
<div class="col-md-7">
238990 - All Other Specialty Trade Contractors
</div>
</div>
<div class="row">
<div class="col-md-5">
<strong>
Primary Business Activity:
</strong>
</div>
<div class="col-md-7">
Services
</div>
</div>
</section>
<!-- Products / Services / Licensing -->
<h3 class="page-header">
Product / Service / Licensing
</h3>
<section class="container-fluid">
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Product Name:
</strong>
</div>
<div class="col-md-9">
Docks & Moorings<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Diving services <br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Linesboat Service<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Barging<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Fabrication, welding & repairs<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Towing & Salvage<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Ship's Anchor & Chain Installation<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Crane Services<br>
</div>
</div>
</section>
<p class="mrgn-tp-lg text-right small hidden-print">
<a href="#wb-cont">top of page</a>
</p>
<!-- Technology Profile -->
<!-- Market Profile -->
<!-- Sector Information -->
<details class="mrgn-tp-md mrgn-bttm-md">
<summary>
Third-Party Information Liability Disclaimer
</summary>
<p>
Some of the information on this Web page has been provided by external sources. The Government of Canada is not responsible for the accuracy, reliability or currency of the information supplied by external sources. Users wishing to rely upon this information should consult directly with the source of the information. Content provided by external sources is not subject to official languages, privacy and accessibility requirements.
</p>
</details>
</details>
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Contact information
</h2>
<!-- Contact Information -->
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<div class="row mrgn-tp-lg">
<div class="col-md-3">
<strong>
Keith S.
Rogers
</strong></div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Title:
</strong>
</div>
<div class="col-md-7">
<!--if client gender is not null or empty we use gender based job title-->
Chairman
</div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Area of Responsibility:
</strong>
</div>
<div class="col-md-7">
Management Executive.
</div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Telephone:
</strong>
</div>
<div class="col-md-7">
(506) 635-4150
</div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Facsimile:
</strong>
</div>
<div class="col-md-7">
(506) 635-8714
</div>
</div>
<div class="row mrgn-lft-md">
<div class="col-md-5">
<strong>
Email:
</strong>
</div>
<div class="col-md-7">
dmkmarine@nb.aibn.com
</div>
</div>
</section>
</details>
<details id="details-panel3">
<summary>
Description
</summary>
<h2 class="wb-invisible">
Company description
</h2>
<section class="container-fluid">
<div class="row">
<div class="col-md-5">
<strong>
Country of Ownership:
</strong>
</div>
<div class="col-md-7">
Canada
</div>
</div>
<div class="row">
<div class="col-md-5">
<strong>
Exporting:
</strong>
</div>
<div class="col-md-7">
No
</div>
</div>
<div class="row">
<div class="col-md-5">
<strong>
Primary Industry (NAICS):
</strong>
</div>
<div class="col-md-7">
238990 - All Other Specialty Trade Contractors
</div>
</div>
<div class="row">
<div class="col-md-5">
<strong>
Primary Business Activity:
</strong>
</div>
<div class="col-md-7">
Services
</div>
</div>
</section>
</details>
<details id="details-panel4">
<summary>
Products, services and licensing
</summary>
<h2 class="wb-invisible">
Product / Service / Licensing
</h2>
<section class="container-fluid">
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Product Name:
</strong>
</div>
<div class="col-md-9">
Docks & Moorings<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Diving services <br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Linesboat Service<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Barging<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Fabrication, welding & repairs<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Towing & Salvage<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Ship's Anchor & Chain Installation<br>
</div>
</div>
<div class="row mrgn-bttm-md">
<div class="col-md-3">
<strong>
Service Name:
</strong>
</div>
<div class="col-md-9">
Crane Services<br>
</div>
</div>
</section>
</details>
</div>
</div>
<div class="row">
<div class="col-md-12 text-right">
Last Update Date 2016-12-19
</div>
</div>
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<span><time>2017-03-02</time></span>
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<HTML><HEAD>
<TITLE>Review for Planet of the Apes (1968)</TITLE>
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<H1 ALIGN="CENTER" CLASS="title"><A HREF="/Title?0063442">Planet of the Apes (1968)</A></H1><H3 ALIGN=CENTER>reviewed by<BR><A HREF="/ReviewsBy?Andrew+Hicks">Andrew Hicks</A></H3><HR WIDTH="40%" SIZE="4">
<PRE> PLANET OF THE APES
A film review by Andrew Hicks
Copyright 1996 Andrew Hicks / Fatboy Productions</PRE>
<PRE>(1968) * (out of four)</PRE>
<P> "You damn dirty apes!" That's just one of the inadvertenty
hilarious lines from PLANET OF THE APES that's taken on a comedic
context over time. No one back then seemed to realize how over-the-
top Charlton Heston's acting style was, but it shows now, particularly
in this "Mystery Science Theater 3000" wannabe that was taken for a
film masterpiece in its time, actually winning one Oscar (for makeup,
no less) and being nominated for a couple others. It also spawned
multiple sequels like Beneath the Planet of the Apes,
Escape From the Planet of the Apes, Return of the
Planet of the Apes, Beneath the Escape from the
Return of the Planet of the Apes, Planet of the
Apes: The Next Generation, Police Academy of the
Apes... the list goes on.</P>
<P> Heston is an American astronaut who spends a few thousand
light years in space with his three companions and ends up on a planet
not too dissimilar from Earth. The thing is, on this planet humans
can't talk or think and the guys in the gorilla masks are the dominant
species. Heston's companions are killed or turned into vegetables by
the apon is imprisoned. He surprises them all with his
gift of speech, making two primate scientists (Roddy McDowall and
Kim Hunter) believe Heston is the missing link between ape and man.
Believe me, we movie critics have been thinking the same thing for
years.</P>
<P> When the two apes present the idea before a judicial
counsel (the head ape being Shakespearean actor Maurice Evans),
it is received as heresy, for all good monkeys know God "created ape
in His image." But Heston has already seen a cave that contains
evidence that humans were originally the dominant species, before
apes ever gained the ability to speak and run for president. And he
takes them there, holding up a baby doll and yelling, "If humans
couldn't speak, then how do you account for this TALKING DOLL?!"
And how do you account for your acting ability, Mr. Heston?</P>
<P> The absolute most laughable scene comes with the movie's
surprise conclusion. I won't reveal the details except to say it involves
Heston falling to his knees on a beach and yelling "God damn you all
to hell!" several times in succession. The movie is atrocious and
should only be viewed by those members of society who like to
watch bad movies and laugh at them.</P>
<P> What makes PLANET OF THE APES even more amusing
is that it was supposed to function as some sort of social irony, a
condemnation of fundamentals who reject the theories of evolution.
But let me tell you, if Darwin could see the ape masks and hear the
rotten dialogue exchanges (HESTON [to female ape]: May I kiss you
before I go? APE: But... you're so... ugly.), he'd convert to creationism
on the spot. Luckily for us, science-fiction movies have evolved over
time to the point at which some of them are actually good.</P>
<PRE>--</PRE>
<P>Visit the Movie Critic at LARGE homepage at
<A HREF="http://www.missouri.edu/~c667778/movies.html">http://www.missouri.edu/~c667778/movies.html</A></P>
<HR><P CLASS=flush><SMALL>The review above was posted to the
<A HREF="news:rec.arts.movies.reviews">rec.arts.movies.reviews</A> newsgroup (<A HREF="news:de.rec.film.kritiken">de.rec.film.kritiken</A> for German reviews).<BR>
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belongs to the author.<BR>
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<li class="header">Type</li>
<li><a href="/OpenTl.Schema/api/OpenTl.Schema.Bots/RequestSendCustomRequest">Request<wbr>Send<wbr>Custom<wbr>Request</a></li>
<li role="separator" class="divider"></li>
<li class="header">Property Members</li>
<li class="selected"><a href="/OpenTl.Schema/api/OpenTl.Schema.Bots/RequestSendCustomRequest/32725498.html">CustomMethod</a></li>
<li><a href="/OpenTl.Schema/api/OpenTl.Schema.Bots/RequestSendCustomRequest/0E296DE7.html">CustomMethodAsBinary</a></li>
<li><a href="/OpenTl.Schema/api/OpenTl.Schema.Bots/RequestSendCustomRequest/79A707E3.html">Params</a></li>
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<h3><a href="/OpenTl.Schema/api/OpenTl.Schema.Bots/RequestSendCustomRequest">Request<wbr>Send<wbr>Custom<wbr>Request</a>.</h3>
<h1>CustomMethod <small>Property</small></h1>
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<dt>Namespace</dt>
<dd><a href="/OpenTl.Schema/api/OpenTl.Schema.Bots">OpenTl<wbr>.Schema<wbr>.Bots</a></dd>
<dt>Containing Type</dt>
<dd><a href="/OpenTl.Schema/api/OpenTl.Schema.Bots/RequestSendCustomRequest">Request<wbr>Send<wbr>Custom<wbr>Request</a></dd>
</dl>
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<h1 id="Syntax">Syntax</h1>
<pre><code>public string CustomMethod { get; set; }</code></pre>
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<h1 class="dtH1">LineEliminator.fillGaps Method </h1>
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<div id="nstext">
<p>
</p>
<div class="syntax">public <a href="http://msdn.microsoft.com/library/default.asp?url=/library/en-us/cpref/html/frlrfSystemDrawingBitmapClassTopic.asp">Bitmap</a> fillGaps(<br /> <a href="http://msdn.microsoft.com/library/default.asp?url=/library/en-us/cpref/html/frlrfSystemDrawingBitmapClassTopic.asp">Bitmap</a> <i>bmp</i><br />);</div>
<h4 class="dtH4">See Also</h4>
<p>
<a href="OCRPreProcessing.LineEliminator.html">LineEliminator Class</a> | <a href="OCRPreProcessing.html">OCRPreProcessing Namespace</a></p>
<object type="application/x-oleobject" classid="clsid:1e2a7bd0-dab9-11d0-b93a-00c04fc99f9e" viewastext="true" style="display: none;">
<param name="Keyword" value="fillGaps method">
</param>
<param name="Keyword" value="fillGaps method, LineEliminator class">
</param>
<param name="Keyword" value="LineEliminator.fillGaps method">
</param>
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<a>(c) 2004 Rene Schulte and Torsten Baer</a>
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<dt><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding"><span class="typeNameLink">AbstractNavigation</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#AbstractNavigation-doneNavigating-pathSearchRange-moveToPositionU-moveToPositionB-moveToEntityU-moveToentityB-speedU-clearPathEntityU-setCanPassDoors-setCanOpenDoors-setCanFloat-canPassDoors-canOpenDoors-canFloat-">AbstractNavigation(doneNavigating, pathSearchRange, moveToPositionU, moveToPositionB, moveToEntityU, moveToentityB, speedU, clearPathEntityU, setCanPassDoors, setCanOpenDoors, setCanFloat, canPassDoors, canOpenDoors, canFloat)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding"><span class="typeNameLink">AbstractPathfinderPlayer</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#AbstractPathfinderPlayer-player-relativeMotionX-relativeMotionY-relativeMotionZ-relativeMotionYaw-relativeMotionPitch-relativeMotionForward-relativeMotionSideward-jump-">AbstractPathfinderPlayer(player, relativeMotionX, relativeMotionY, relativeMotionZ, relativeMotionYaw, relativeMotionPitch, relativeMotionForward, relativeMotionSideward, jump)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#addPathfinderGoal-priority-pathfinderGoal-">addPathfinderGoal(priority, pathfinderGoal)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#addTargetPathfinderGoal-priority-pathfinderGoal-">addTargetPathfinderGoal(priority, pathfinderGoal)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
</dl>
<a name="I:C">
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</a>
<h2 class="title">C</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#canContinueToUse--">canContinueToUse()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderGoal</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#canFloat--">canFloat()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#canFloat--">canFloat()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#canOpenDoors--">canOpenDoors()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#canOpenDoors--">canOpenDoors()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#canPassDoors--">canPassDoors()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#canPassDoors--">canPassDoors()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#clearPathEntity--">clearPathEntity()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd>
<div class="block">sets active PathEntity to null</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#clearPathEntity--">clearPathEntity()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd>
<div class="block">sets active PathEntity to null</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#clearPathfinderGoals--">clearPathfinderGoals()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#clearTargetPathfinderGoals--">clearTargetPathfinderGoals()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding</a> - package com.github.ysl3000.bukkit.pathfinding</dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/entity/package-summary.html">com.github.ysl3000.bukkit.pathfinding.entity</a> - package com.github.ysl3000.bukkit.pathfinding.entity</dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals</a> - package com.github.ysl3000.bukkit.pathfinding.goals</dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals.notworking</a> - package com.github.ysl3000.bukkit.pathfinding.goals.notworking</dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding.pathfinding</a> - package com.github.ysl3000.bukkit.pathfinding.pathfinding</dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html#Companion">Companion</a></span> - Static variable in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalGimmiCookie</a></dt>
<dd> </dd>
</dl>
<a name="I:D">
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</a>
<h2 class="title">D</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.DefaultImpls.html#DefaultImpls--">DefaultImpls()</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.DefaultImpls.html" title="class in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderGoal.DefaultImpls</a></dt>
<dd> </dd>
</dl>
<a name="I:E">
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</a>
<h2 class="title">E</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html#execute--">execute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalFollowEntity</a></dt>
<dd>
<div class="block">Is called when <a href="#">.shouldExecute</a> returns true</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html#execute--">execute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalReturnToLocation</a></dt>
<dd>
<div class="block">Is called when <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#shouldExecute--"><code>PathfinderGoal.shouldExecute</code></a> returns true</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html#execute--">execute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalSteerEntity</a></dt>
<dd>
<div class="block">Is called when <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#shouldExecute--"><code>PathfinderGoal.shouldExecute</code></a> returns true</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html#execute--">execute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalWalkToSteakAndEat</a></dt>
<dd>
<div class="block">Is called when <a href="#">.shouldExecute</a> returns true</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html#execute--">execute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalGimmiCookie</a></dt>
<dd>
<div class="block">Is called when <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#shouldExecute--"><code>PathfinderGoal.shouldExecute</code></a> returns true</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html#execute--">execute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalMoveToLocation</a></dt>
<dd>
<div class="block">Is called when <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#shouldExecute--"><code>PathfinderGoal.shouldExecute</code></a> returns true</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html#execute--">execute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">TalkToStrangers</a></dt>
<dd>
<div class="block">Is called when <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#shouldExecute--"><code>PathfinderGoal.shouldExecute</code></a> returns true</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#execute--">execute()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderGoal</a></dt>
<dd>
<div class="block">Is called when <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#shouldExecute--"><code>PathfinderGoal.shouldExecute</code></a> returns true</div>
</dd>
</dl>
<a name="I:G">
<!-- -->
</a>
<h2 class="title">G</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/PathfinderGoalAPI.html#getAPI--">getAPI()</a></span> - Static method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/PathfinderGoalAPI.html" title="class in com.github.ysl3000.bukkit.pathfinding">PathfinderGoalAPI</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#getBukkitEntity--">getBukkitEntity()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">Will return the LivingEntity of Bukkit</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#getHeadHeight--">getHeadHeight()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">Get the entities headHeight</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#getLookingAt--">getLookingAt()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#getMotionForward--">getMotionForward()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#getMotionForward--">getMotionForward()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#getMotionSideward--">getMotionSideward()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#getMotionSideward--">getMotionSideward()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#getNavigation--">getNavigation()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">Get the Navigation for moving Entity</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html#getPathfinderGoalEntity-creature-">getPathfinderGoalEntity(creature)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManager</a></dt>
<dd>
<div class="block">Returns a pathfinderGoalEntity from creature</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html#getPathfinderGoalEntity-flying-">getPathfinderGoalEntity(flying)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManager</a></dt>
<dd>
<div class="block">Returns a pathfinderGoalEntity from flying</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html#getPathfinderGoalEntity-ambient-">getPathfinderGoalEntity(ambient)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManager</a></dt>
<dd>
<div class="block">Returns a pathfinderGoalEntity from ambient</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html#getPathfinderGoalEntity-slime-">getPathfinderGoalEntity(slime)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManager</a></dt>
<dd>
<div class="block">Returns a pathfinderGoalEntity from slime</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html#getPathfinderGoalEntity-enderDragon-">getPathfinderGoalEntity(enderDragon)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManager</a></dt>
<dd>
<div class="block">Returns a pathfinderGoalEntity from slime</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManagerMob.html#getPathfinderGoalEntity-mob-">getPathfinderGoalEntity(mob)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManagerMob.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManagerMob</a></dt>
<dd>
<div class="block">Returns a pathfinderGoalEntity from Mob 1.13+ only (Mob got added to Bukkit API in 1.13)</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html#getPathfinderPlayer-player-">getPathfinderPlayer(player)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManager</a></dt>
<dd>
<div class="block">Returns a instance of the pathfinderPlayer</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#getPathSearchRange--">getPathSearchRange()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd>
<div class="block">The maximal distance the pathfinder search</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#getPathSearchRange--">getPathSearchRange()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd>
<div class="block">The maximal distance the pathfinder search</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#getPlayer--">getPlayer()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd>
<div class="block">Returns the Bukkit Player</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#getPlayer--">getPlayer()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd>
<div class="block">Returns the Bukkit Player</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#getRelativeMotionPitch--">getRelativeMotionPitch()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#getRelativeMotionPitch--">getRelativeMotionPitch()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#getRelativeMotionX--">getRelativeMotionX()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#getRelativeMotionX--">getRelativeMotionX()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#getRelativeMotionY--">getRelativeMotionY()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#getRelativeMotionY--">getRelativeMotionY()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#getRelativeMotionYaw--">getRelativeMotionYaw()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#getRelativeMotionYaw--">getRelativeMotionYaw()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#getRelativeMotionZ--">getRelativeMotionZ()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#getRelativeMotionZ--">getRelativeMotionZ()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
</dl>
<a name="I:H">
<!-- -->
</a>
<h2 class="title">H</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#hasPathfinderGoal-pathfinderGoal-">hasPathfinderGoal(pathfinderGoal)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#hasPositionChanged--">hasPositionChanged()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">Will return if entity changed position</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#hasTargetPathfinderGoal-pathfinderGoal-">hasTargetPathfinderGoal(pathfinderGoal)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
</dl>
<a name="I:I">
<!-- -->
</a>
<h2 class="title">I</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html#init--">init()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalFollowEntity</a></dt>
<dd>
<div class="block">Runs initially and should be used to setUp goalEnvironment Condition needs to be defined thus
your code in it isn't called</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html#init--">init()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalReturnToLocation</a></dt>
<dd>
<div class="block">Runs initially and should be used to setUp goalEnvironment Condition needs to be defined thus
your code in it isn't called</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html#init--">init()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalSteerEntity</a></dt>
<dd>
<div class="block">Runs initially and should be used to setUp goalEnvironment Condition needs to be defined thus
your code in it isn't called</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html#init--">init()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalWalkToSteakAndEat</a></dt>
<dd>
<div class="block">Runs initially and should be used to setUp goalEnvironment Condition needs to be defined thus
your code in it isn't called</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html#init--">init()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalGimmiCookie</a></dt>
<dd>
<div class="block">Runs initially and should be used to setUp goalEnvironment Condition needs to be defined thus
your code in it isn't called</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html#init--">init()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalMoveToLocation</a></dt>
<dd>
<div class="block">Runs initially and should be used to setUp goalEnvironment Condition needs to be defined thus
your code in it isn't called</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html#init--">init()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">TalkToStrangers</a></dt>
<dd>
<div class="block">Runs initially and should be used to setUp goalEnvironment Condition needs to be defined thus
your code in it isn't called</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#init--">init()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderGoal</a></dt>
<dd>
<div class="block">Runs initially and should be used to setUp goalEnvironment Condition needs to be defined thus
your code in it isn't called</div>
</dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity"><span class="typeNameLink">Insentient</span></a> - Interface in <a href="com/github/ysl3000/bukkit/pathfinding/entity/package-summary.html">com.github.ysl3000.bukkit.pathfinding.entity</a></dt>
<dd>
<div class="block">Created by Yannick on 30.11.2016.</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#Insentient--">Insentient()</a></span> - Constructor for interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/PathfinderGoalAPI.html#INSTANCE">INSTANCE</a></span> - Static variable in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/PathfinderGoalAPI.html" title="class in com.github.ysl3000.bukkit.pathfinding">PathfinderGoalAPI</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#isDoneNavigating--">isDoneNavigating()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#isDoneNavigating--">isDoneNavigating()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html#isJumping--">isJumping()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractPathfinderPlayer.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractPathfinderPlayer</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#isJumping--">isJumping()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
</dl>
<a name="I:J">
<!-- -->
</a>
<h2 class="title">J</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#jump--">jump()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
</dl>
<a name="I:L">
<!-- -->
</a>
<h2 class="title">L</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#lookAt-location-">lookAt(location)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">The entity will look to the given location</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#lookAt-entity-">lookAt(entity)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">The entity will look to the given entity</div>
</dd>
</dl>
<a name="I:M">
<!-- -->
</a>
<h2 class="title">M</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#moveTo-location-">moveTo(location)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd>
<div class="block">Will let the entity walk/move to the given location with default speed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#moveTo-entity-">moveTo(entity)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd>
<div class="block">Will let the entity walk/move to the given entity's location with default speed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#moveTo-location-speed-">moveTo(location, speed)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd>
<div class="block">Will let the entity walk/move to the given location with given speed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#moveTo-entity-speed-">moveTo(entity, speed)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd>
<div class="block">Will let the entity walk/move to the given entity's location with given speed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#moveTo-location-">moveTo(location)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd>
<div class="block">Will let the entity walk/move to the given location with default speed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#moveTo-entity-">moveTo(entity)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd>
<div class="block">Will let the entity walk/move to the given entity's location with default speed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#moveTo-location-speed-">moveTo(location, speed)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd>
<div class="block">Will let the entity walk/move to the given location with given speed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#moveTo-entity-speed-">moveTo(entity, speed)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd>
<div class="block">Will let the entity walk/move to the given entity's location with given speed</div>
</dd>
</dl>
<a name="I:N">
<!-- -->
</a>
<h2 class="title">N</h2>
<dl>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding"><span class="typeNameLink">Navigation</span></a> - Interface in <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding.pathfinding</a></dt>
<dd>
<div class="block">Created by Yannick on 30.11.2016.</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#Navigation--">Navigation()</a></span> - Constructor for interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd> </dd>
</dl>
<a name="I:O">
<!-- -->
</a>
<h2 class="title">O</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#onEntityKill-livingEntity-">onEntityKill(livingEntity)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">method gets called when the entity kills another entity</div>
</dd>
</dl>
<a name="I:P">
<!-- -->
</a>
<h2 class="title">P</h2>
<dl>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding"><span class="typeNameLink">PathfinderGoal</span></a> - Interface in <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding.pathfinding</a></dt>
<dd>
<div class="block">Created by Yannick on 30.11.2016.</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#PathfinderGoal--">PathfinderGoal()</a></span> - Constructor for interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderGoal</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.DefaultImpls.html" title="class in com.github.ysl3000.bukkit.pathfinding.pathfinding"><span class="typeNameLink">PathfinderGoal.DefaultImpls</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding.pathfinding</a></dt>
<dd>
<div class="block">Created by Yannick on 30.11.2016.</div>
</dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/PathfinderGoalAPI.html" title="class in com.github.ysl3000.bukkit.pathfinding"><span class="typeNameLink">PathfinderGoalAPI</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking"><span class="typeNameLink">PathfinderGoalFollowEntity</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals.notworking</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html#PathfinderGoalFollowEntity-pathfinderGoalEntity-entity-moveRadius-walkspeed-">PathfinderGoalFollowEntity(pathfinderGoalEntity, entity, moveRadius, walkspeed)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalFollowEntity</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals"><span class="typeNameLink">PathfinderGoalGimmiCookie</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/goals/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals</a></dt>
<dd>
<div class="block">Created by 2008Choco</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html#PathfinderGoalGimmiCookie-pathfinderGoalEntity-creature-">PathfinderGoalGimmiCookie(pathfinderGoalEntity, creature)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalGimmiCookie</a></dt>
<dd>
<div class="block">Created by 2008Choco</div>
</dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.Companion.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals"><span class="typeNameLink">PathfinderGoalGimmiCookie.Companion</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/goals/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals"><span class="typeNameLink">PathfinderGoalMoveToLocation</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/goals/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html#PathfinderGoalMoveToLocation-pathfinderGoalEntity-targetLocation-walkSpeed-distance-">PathfinderGoalMoveToLocation(pathfinderGoalEntity, targetLocation, walkSpeed, distance)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalMoveToLocation</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking"><span class="typeNameLink">PathfinderGoalReturnToLocation</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals.notworking</a></dt>
<dd>
<div class="block">Created by Yannick on 30.11.2016.</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html#PathfinderGoalReturnToLocation-pathfinderGoalEntity-entity-moveRadius-">PathfinderGoalReturnToLocation(pathfinderGoalEntity, entity, moveRadius)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalReturnToLocation</a></dt>
<dd>
<div class="block">Created by Yannick on 30.11.2016.</div>
</dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking"><span class="typeNameLink">PathfinderGoalSteerEntity</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals.notworking</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html#PathfinderGoalSteerEntity-pathfinderManager-pathfinderGoalEntity-">PathfinderGoalSteerEntity(pathfinderManager, pathfinderGoalEntity)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalSteerEntity</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking"><span class="typeNameLink">PathfinderGoalWalkToSteakAndEat</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals.notworking</a></dt>
<dd>
<div class="block">Created by ysl3000 on 09.12.16. todo check if working else update</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html#PathfinderGoalWalkToSteakAndEat-pathfinderGoalEntity-distance-">PathfinderGoalWalkToSteakAndEat(pathfinderGoalEntity, distance)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalWalkToSteakAndEat</a></dt>
<dd>
<div class="block">Created by ysl3000 on 09.12.16. todo check if working else update</div>
</dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding"><span class="typeNameLink">PathfinderManager</span></a> - Interface in <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding.pathfinding</a></dt>
<dd>
<div class="block">Created by ysl3000 on 08.12.16.</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html#PathfinderManager--">PathfinderManager()</a></span> - Constructor for interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManager.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManager</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManagerMob.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding"><span class="typeNameLink">PathfinderManagerMob</span></a> - Interface in <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding.pathfinding</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManagerMob.html#PathfinderManagerMob--">PathfinderManagerMob()</a></span> - Constructor for interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderManagerMob.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderManagerMob</a></dt>
<dd> </dd>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding"><span class="typeNameLink">PathfinderPlayer</span></a> - Interface in <a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/package-summary.html">com.github.ysl3000.bukkit.pathfinding.pathfinding</a></dt>
<dd>
<div class="block">The PathfinderPlayer grants access to functionality needed for PathfinderEntities e.g. get the
relative Motion of the player</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html#PathfinderPlayer--">PathfinderPlayer()</a></span> - Constructor for interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderPlayer.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderPlayer</a></dt>
<dd> </dd>
</dl>
<a name="I:R">
<!-- -->
</a>
<h2 class="title">R</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#removePathfinderGoal-pathfinderGoal-">removePathfinderGoal(pathfinderGoal)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#removeTargetPathfinderGoal-pathfinderGoal-">removeTargetPathfinderGoal(pathfinderGoal)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html#reset--">reset()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalFollowEntity</a></dt>
<dd>
<div class="block">Reset the pathfinder AI pack to its initial state</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html#reset--">reset()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalReturnToLocation</a></dt>
<dd>
<div class="block">Reset the pathfinder AI pack to its initial state</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html#reset--">reset()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalSteerEntity</a></dt>
<dd>
<div class="block">Reset the pathfinder AI pack to its initial state</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html#reset--">reset()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalWalkToSteakAndEat</a></dt>
<dd>
<div class="block">Reset the pathfinder AI pack to its initial state</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html#reset--">reset()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalGimmiCookie</a></dt>
<dd>
<div class="block">Reset the pathfinder AI pack to its initial state</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html#reset--">reset()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalMoveToLocation</a></dt>
<dd>
<div class="block">Reset the pathfinder AI pack to its initial state</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html#reset--">reset()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">TalkToStrangers</a></dt>
<dd>
<div class="block">Reset the pathfinder AI pack to its initial state</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#reset--">reset()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderGoal</a></dt>
<dd>
<div class="block">Reset the pathfinder AI pack to its initial state</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#resetGoalsToDefault--">resetGoalsToDefault()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">Will reset goals to default one</div>
</dd>
</dl>
<a name="I:S">
<!-- -->
</a>
<h2 class="title">S</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/PathfinderGoalAPI.html#setApi-pathfinderManager-">setApi(pathfinderManager)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/PathfinderGoalAPI.html" title="class in com.github.ysl3000.bukkit.pathfinding">PathfinderGoalAPI</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#setCanFloat-canFloat-">setCanFloat(canFloat)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#setCanFloat-canFloat-">setCanFloat(canFloat)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#setCanOpenDoors-canOpenDoors-">setCanOpenDoors(canOpenDoors)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#setCanOpenDoors-canOpenDoors-">setCanOpenDoors(canOpenDoors)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#setCanPassDoors-canPassDoors-">setCanPassDoors(canPassDoors)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#setCanPassDoors-canPassDoors-">setCanPassDoors(canPassDoors)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#setMovementDirection-direction-speed-">setMovementDirection(direction, speed)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#setRotation-yaw-pitch-">setRotation(yaw, pitch)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">Rotates the entity</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html#setSpeed-speed-">setSpeed(speed)</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/AbstractNavigation.html" title="class in com.github.ysl3000.bukkit.pathfinding">AbstractNavigation</a></dt>
<dd>
<div class="block">Will set the entity's walkspeed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html#setSpeed-speed-">setSpeed(speed)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/Navigation.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">Navigation</a></dt>
<dd>
<div class="block">Will set the entity's walkspeed</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#setStrafeDirection-forward-sideward-">setStrafeDirection(forward, sideward)</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd> </dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html#shouldExecute--">shouldExecute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalFollowEntity</a></dt>
<dd>
<div class="block">Whether the pathfinder goal should commence execution or not</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html#shouldExecute--">shouldExecute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalReturnToLocation</a></dt>
<dd>
<div class="block">Whether the pathfinder goal should commence execution or not</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html#shouldExecute--">shouldExecute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalSteerEntity</a></dt>
<dd>
<div class="block">Whether the pathfinder goal should commence execution or not</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html#shouldExecute--">shouldExecute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalWalkToSteakAndEat</a></dt>
<dd>
<div class="block">Whether the pathfinder goal should commence execution or not</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html#shouldExecute--">shouldExecute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalGimmiCookie</a></dt>
<dd>
<div class="block">Whether the pathfinder goal should commence execution or not</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html#shouldExecute--">shouldExecute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalMoveToLocation</a></dt>
<dd>
<div class="block">Whether the pathfinder goal should commence execution or not</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html#shouldExecute--">shouldExecute()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">TalkToStrangers</a></dt>
<dd>
<div class="block">Whether the pathfinder goal should commence execution or not</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#shouldExecute--">shouldExecute()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderGoal</a></dt>
<dd>
<div class="block">Whether the pathfinder goal should commence execution or not</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html#shouldTerminate--">shouldTerminate()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalFollowEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalFollowEntity</a></dt>
<dd>
<div class="block">Whether the goal should Terminate</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html#shouldTerminate--">shouldTerminate()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalReturnToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalReturnToLocation</a></dt>
<dd>
<div class="block">Whether the goal should Terminate</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html#shouldTerminate--">shouldTerminate()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalSteerEntity.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalSteerEntity</a></dt>
<dd>
<div class="block">Whether the goal should Terminate</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html#shouldTerminate--">shouldTerminate()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.notworking.<a href="com/github/ysl3000/bukkit/pathfinding/goals/notworking/PathfinderGoalWalkToSteakAndEat.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals.notworking">PathfinderGoalWalkToSteakAndEat</a></dt>
<dd>
<div class="block">Whether the goal should Terminate</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html#shouldTerminate--">shouldTerminate()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalGimmiCookie.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalGimmiCookie</a></dt>
<dd>
<div class="block">Whether the goal should Terminate</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html#shouldTerminate--">shouldTerminate()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/PathfinderGoalMoveToLocation.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">PathfinderGoalMoveToLocation</a></dt>
<dd>
<div class="block">Whether the goal should Terminate</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html#shouldTerminate--">shouldTerminate()</a></span> - Method in class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">TalkToStrangers</a></dt>
<dd>
<div class="block">Whether the goal should Terminate</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html#shouldTerminate--">shouldTerminate()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.pathfinding.<a href="com/github/ysl3000/bukkit/pathfinding/pathfinding/PathfinderGoal.html" title="interface in com.github.ysl3000.bukkit.pathfinding.pathfinding">PathfinderGoal</a></dt>
<dd>
<div class="block"><span class="deprecatedLabel">Deprecated.</span> </div>
</dd>
</dl>
<a name="I:T">
<!-- -->
</a>
<h2 class="title">T</h2>
<dl>
<dt><a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals"><span class="typeNameLink">TalkToStrangers</span></a> - Class in <a href="com/github/ysl3000/bukkit/pathfinding/goals/package-summary.html">com.github.ysl3000.bukkit.pathfinding.goals</a></dt>
<dd>
<div class="block">Created by ysl3000</div>
</dd>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html#TalkToStrangers-insentient-messages-delay-">TalkToStrangers(insentient, messages, delay)</a></span> - Constructor for class com.github.ysl3000.bukkit.pathfinding.goals.<a href="com/github/ysl3000/bukkit/pathfinding/goals/TalkToStrangers.html" title="class in com.github.ysl3000.bukkit.pathfinding.goals">TalkToStrangers</a></dt>
<dd>
<div class="block">Created by ysl3000</div>
</dd>
</dl>
<a name="I:U">
<!-- -->
</a>
<h2 class="title">U</h2>
<dl>
<dt><span class="memberNameLink"><a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html#updateRenderAngles--">updateRenderAngles()</a></span> - Method in interface com.github.ysl3000.bukkit.pathfinding.entity.<a href="com/github/ysl3000/bukkit/pathfinding/entity/Insentient.html" title="interface in com.github.ysl3000.bukkit.pathfinding.entity">Insentient</a></dt>
<dd>
<div class="block">Updates the the angles for rendering</div>
</dd>
</dl>
<a href="#I:A">A</a> <a href="#I:C">C</a> <a href="#I:D">D</a> <a href="#I:E">E</a> <a href="#I:G">G</a> <a href="#I:H">H</a> <a href="#I:I">I</a> <a href="#I:J">J</a> <a href="#I:L">L</a> <a href="#I:M">M</a> <a href="#I:N">N</a> <a href="#I:O">O</a> <a href="#I:P">P</a> <a href="#I:R">R</a> <a href="#I:S">S</a> <a href="#I:T">T</a> <a href="#I:U">U</a> </div>
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| ysl3000/PathfindergoalAPI | docs/index-all.html | HTML | mit | 79,163 |
---
layout: default
---
<noscript>
<style>
article .footnotes {
display: block;
}
</style>
</noscript>
<article id="post_body">
<div class="center">
<h1>{{ page.title }}</h1>
<!--<time>{{ page.date | date: '%B %-d, %Y' }}</time>-->
</div>
<div class="divider"></div>
{{ content }}
</article>
<div class="back">
<a href="{{site.baseurl}}/">Back</a>
</div>
| ajsingh273/site | _layouts/post.html | HTML | mit | 382 |
<div class="panel panel-default">
<div class="panel-heading">
<a href="{% url 'compendia:pk_detail' compendium.pk %}">
{{ compendium.title }}
</a>
</div>
<div class="panel-body">
<p>{{ compendium.journal }}</p>
<p>{{ compendium.authors_text|truncatewords_html:100 }}</p>
<p><a class="btn btn-primary" href="{% url 'compendia:pk_detail' compendium.pk %}"><i class="fa fa-book"></i> Details</a></p>
</div>
</div>
| researchcompendia/researchcompendia | companionpages/templates/compendia/card_browse.html | HTML | mit | 447 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<!--
Blog Theme for Hexo: St. Andrews
Designed by Sharvari Desai
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-->
<!-- Favicon -->
<!-- Title -->
<title>FUTUROLOGIE</title>
<!--Description-->
<!--Author-->
<meta name="author" content="Alexandre Impinna">
<!--Open Graph Title-->
<!--Open Graph Site Name-->
<meta property="og:site_name" content="FUTUROLOGIE"/>
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<![endif]-->
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(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,'script','//www.google-analytics.com/analytics.js','ga');
ga('create', 'UA-72475923-1', 'auto');
ga('send', 'pageview');
</script>
</head>
<body>
<div class="container my-4">
<nav class="navbar navbar-toggleable-sm navbar-light px-1 py-3 my-3 mb-sm-3">
<a class="navbar-brand ml-1" href="/">
<span class="title">FUTUROLOGIE
</a>
<span class="subtitle">LE BLOG AU FUTUR CONDITIONNEL</span>
</span>
<button class="navbar-toggler navbar-toggler-right py-2" type="button" data-toggle="collapse" data-target="#navbarCollapse" aria-controls="navbarCollapse" aria-expanded="false" aria-label="Toggle navigation">
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</button>
<div class="collapse navbar-collapse text-center mt-3 mt-md-0" id="navbarCollapse">
<ul class="navbar-nav ml-auto my-auto">
<li class="nav-item">
<a class="nav-link" href="/">Accueil</a>
</li>
<li class="nav-item">
<a class="nav-link" href="/categories">Categories</a>
</li>
<li class="nav-item">
<a class="nav-link" href="mailto:contact@futurologie.xyz">Contact</a>
</li>
</ul>
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</div>
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<div class="container">
<div class="row">
<div class="col-lg-4 col-md-6 col-12 mb-5">
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<a href="/2017/06/24/bienvenue-chez-vous/">
<img class="img-fluid" src="/images/2017/header/bienvenue-chez-vous.jpg" alt="Bienvenue chez vous">
</a>
</div>
</div>
<div class="post-details text-center mt-3">
<a href="/2017/06/24/bienvenue-chez-vous/">Bienvenue chez vous</a>
<hr>
<span class="date">24-06-2017</span>
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</body>
</html>
| Aleximpinna/Aleximpinna.github.io | archives/2017/06/index.html | HTML | mit | 4,732 |
---
# DO NOT EDIT!
# This file is automatically generated by get-members. If you change it, bad
# things will happen.
layout: default
title: "Sir Tony Cunningham"
house: commons
---
<div class="row">
<div class="col-md-8">
{% include members/sir-tony-cunningham.html %}
<h3>What is Sir Tony Cunningham interested in?</h3>
<li><a href="http://jenit.github.io/childs-guide-to-parliament/interests/third-world.html">Third World</a></li>
<li><a href="http://jenit.github.io/childs-guide-to-parliament/interests/education.html">Education</a></li>
<li><a href="http://jenit.github.io/childs-guide-to-parliament/interests/tourism.html">Tourism</a></li>
<li><a href="http://jenit.github.io/childs-guide-to-parliament/interests/sport.html">Sport</a></li>
<li><a href="http://jenit.github.io/childs-guide-to-parliament/interests/small-businesses.html">Small Businesses</a></li>
</div>
<div class="col-md-4">
<div class="panel panel-default">
<div class="panel-heading">
<h3 class="panel-title">Place</h3>
</div>
<div class="panel-body">
<p>Sir Tony Cunningham is the MP for <b>Workington</b>.</p>
<div id="constituency-map" style="width:100%;height:250px"></div>
<script>
L.mapbox.accessToken = 'pk.eyJ1IjoiamFja3NvbmowNCIsImEiOiJxNmRPTDhvIn0.zxOHkhRVui-0MBwEdKnfUg';
var map = L.mapbox.map('constituency-map', 'jacksonj04.k663m066',{
zoomControl: false
});
var featureLayer = L.mapbox.featureLayer()
.loadURL('{{ site.baseurl }}/data/boundaries/workington.geojson')
.addTo(map);
featureLayer.on('ready', function() {
map.fitBounds(featureLayer.getBounds());
});
</script>
<p class="small"><a href="{{ site.baseurl }}/glossary.html#constituency">What is a constituency?</a><p>
</div>
</div>
<div class="panel panel-default">
<div class="panel-heading">
<h3 class="panel-title">Party</h3>
</div>
<div class="panel-body">
<p>Sir Tony Cunningham is an MP in the <b>Labour</b> party.</p>
<p class="small"><a href="{{ site.baseurl }}/glossary.html#party">What is a party?</a><p>
</div>
</div>
</div>
</div>
| JeniT/childs-guide-to-parliament | members/sir-tony-cunningham.html | HTML | mit | 2,540 |
<header id="header">
<h1>{{title}}</h1>
<form id="todo-form" ng-submit="addTodo()">
<input id="new-todo" placeholder="What needs to be done?" ng-model="newTodo" autofocus>
</form>
</header>
<section id="main" ng-show="todos.length" ng-cloak>
<input id="toggle-all" type="checkbox" ng-model="allChecked" ng-click="markAll(allChecked)">
<label for="toggle-all">Mark all as complete</label>
<ul id="todo-list">
<li ng-repeat="todo in todos | filter:statusFilter" ng-class="{completed: todo.completed, editing: todo == editedTodo}">
<div class="view">
<input class="toggle" type="checkbox" ng-model="todo.completed">
<label ng-dblclick="editTodo(todo)">{{todo.title}}</label>
<button class="destroy" ng-click="removeTodo(todo)"></button>
</div>
<form ng-submit="doneEditing(todo)">
<input class="edit" ng-model="todo.title" todo-escape="revertEditing(todo)" todo-blur="doneEditing(todo)" todo-focus="todo == editedTodo">
</form>
</li>
</ul>
</section>
<footer id="footer" ng-show="todos.length" ng-cloak>
<span id="todo-count"><strong>{{remainingCount}}</strong>
<ng-pluralize count="remainingCount" when="{ one: 'item left', other: 'items left' }"></ng-pluralize>
</span>
<ul id="filters">
<li>
<a ng-class="{selected: location.path() == '/'} " href="#/">All</a>
</li>
<li>
<a ng-class="{selected: location.path() == '/active'}" href="#/active">Active</a>
</li>
<li>
<a ng-class="{selected: location.path() == '/completed'}" href="#/completed">Completed</a>
</li>
</ul>
<button id="clear-completed" ng-click="clearCompletedTodos()" ng-show="completedCount">Clear completed ({{completedCount}})</button>
</footer> | ppxu/Dota-Legend | todo/views/todo.html | HTML | mit | 1,885 |
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</li>
<li>
<a href="#tree" role="tab" id="tree-tab" data-toggle="tab" data-link="dom-tree">DOM Tree</a>
</li>
</ul>
<div class="tab-content">
<div class="tab-pane fade active in" id="info"><p class="comment">
<h3>File</h3>
</p>
<p class="comment">
<code>src/app/ngx-blog/components/post/post.component.ts</code>
</p>
<p class="comment">
<h3>Description</h3>
</p>
<p class="comment">
<p>post.component
component for ngxb-post</p>
</p>
<p class="comment">
<h3>Implements</h3>
</p>
<p class="comment">
<code><a href="https://angular.io/docs/ts/latest/api/core/index/OnInit-interface.html" target="_blank" >OnInit</a></code>
<code><a href="https://angular.io/docs/ts/latest/api/core/index/OnChanges-interface.html" target="_blank" >OnChanges</a></code>
<code><a href="https://angular.io/docs/ts/latest/api/core/index/AfterViewInit-interface.html" target="_blank" >AfterViewInit</a></code>
</p>
<section>
<h3>Metadata</h3>
<table class="table table-sm table-hover">
<tbody>
<tr>
<td class="col-md-3">encapsulation</td>
<td class="col-md-9"><code>ViewEncapsulation.None</code></td>
</tr>
<tr>
<td class="col-md-3">selector</td>
<td class="col-md-9"><code>ngxb-post, [ngxb-post]</code></td>
</tr>
<tr>
<td class="col-md-3">styleUrls</td>
<td class="col-md-9"><code>theme.scss</code></td>
</tr>
<tr>
<td class="col-md-3">template</td>
<td class="col-md-9"><pre class="line-numbers"><code class="language-html"><ng-content></ng-content></code></pre></td>
</tr>
</tbody>
</table>
</section>
<section>
<h3 id="index">Index</h3>
<table class="table table-sm table-bordered index-table">
<tbody>
<tr>
<td class="col-md-4">
<h6><b>Properties</b></h6>
</td>
</tr>
<tr>
<td class="col-md-4">
<ul class="index-list">
<li>
<span class="modifier">Public</span> <a href="#element">element</a>
</li>
<li>
<a href="#post">post</a>
</li>
<li>
<span class="modifier">Public</span> <a href="#postsService">postsService</a>
</li>
</ul>
</td>
</tr>
<tr>
<td class="col-md-4">
<h6><b>Methods</b></h6>
</td>
</tr>
<tr>
<td class="col-md-4">
<ul class="index-list">
<li>
<a href="#handleData">handleData</a>
</li>
<li>
<a href="#handleRaw">handleRaw</a>
</li>
<li>
<a href="#handleSrc">handleSrc</a>
</li>
<li>
<a href="#ngAfterViewInit">ngAfterViewInit</a>
</li>
<li>
<a href="#ngOnChanges">ngOnChanges</a>
</li>
<li>
<a href="#ngOnInit">ngOnInit</a>
</li>
<li>
<a href="#prepare">prepare</a>
</li>
</ul>
</td>
</tr>
<tr>
<td class="col-md-4">
<h6><b>Inputs</b></h6>
</td>
</tr>
<tr>
<td class="col-md-4">
<ul class="index-list">
<li>
<a href="#data">data</a>
</li>
<li>
<a href="#src">src</a>
</li>
</ul>
</td>
</tr>
</tbody>
</table>
</section>
<section>
<h3 id="constructor">Constructor</h3>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<code>constructor(postsService: <a href="../injectables/PostsService.html">PostsService</a>, element: <a href="https://angular.io/docs/ts/latest/api/core/index/ElementRef-class.html" target="_blank">ElementRef</a>)</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="37" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:37</a></div>
</td>
</tr>
<tr>
<td class="col-md-4">
<div>
<b>Parameters :</b>
<table class="params">
<thead>
<tr>
<td>Name</td>
<td>Type</td>
<td>Optional</td>
<td>Description</td>
</tr>
</thead>
<tbody>
<tr>
<td>postsService</td>
<td>
<code><a href="../injectables/PostsService.html" target="_self" >PostsService</a></code>
</td>
<td>
</td>
<td></td>
</tr>
<tr>
<td>element</td>
<td>
<code><a href="https://angular.io/docs/ts/latest/api/core/index/ElementRef-class.html" target="_blank" >ElementRef</a></code>
</td>
<td>
</td>
<td></td>
</tr>
</tbody>
</table>
</div>
</td>
</tr>
</tbody>
</table>
</section>
<section>
<h3 id="inputs">Inputs</h3>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-2">
<a name="data"></a>
<code>data</code>
</td>
<td class="col-md-10">
<p>
<em>Type:</em> <code><a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/string" target="_blank" >string</a></code>
</p>
</td>
</tr>
<tr>
<td class="col-md-2" colspan="2">
<div class="io-line">Defined in <a href="" data-line="34" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:34</a></div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-2">
<a name="src"></a>
<code>src</code>
</td>
<td class="col-md-10">
<p>
<em>Type:</em> <code><a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/string" target="_blank" >string</a></code>
</p>
</td>
</tr>
<tr>
<td class="col-md-2" colspan="2">
<div class="io-line">Defined in <a href="" data-line="35" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:35</a></div>
</td>
</tr>
</tbody>
</table>
</section>
<section>
<h3 id="methods">
Methods
</h3>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="handleData"></a>
<span class="name"><b> handleData</b><a href="#handleData"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<code>handleData()</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="68" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:68</a></div>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-description">
<b>Returns : </b> <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >void</a></code>
</div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="handleRaw"></a>
<span class="name"><b> handleRaw</b><a href="#handleRaw"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<code>handleRaw(raw: <a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/string" target="_blank">string</a>)</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="85" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:85</a></div>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-description">
<b>Parameters :</b>
<table class="params">
<thead>
<tr>
<td>Name</td>
<td>Type</td>
<td>Optional</td>
<td>Description</td>
</tr>
</thead>
<tbody>
<tr>
<td>raw</td>
<td>
<code><a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/string" target="_blank" >string</a></code>
</td>
<td>
</td>
<td></td>
</tr>
</tbody>
</table>
</div>
<div>
</div>
<div class="io-description">
<b>Returns : </b> <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >void</a></code>
</div>
<div class="io-description">
</div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="handleSrc"></a>
<span class="name"><b> handleSrc</b><a href="#handleSrc"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<code>handleSrc()</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="72" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:72</a></div>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-description">
<b>Returns : </b> <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >void</a></code>
</div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="ngAfterViewInit"></a>
<span class="name"><b> ngAfterViewInit</b><a href="#ngAfterViewInit"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<code>ngAfterViewInit()</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="44" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:44</a></div>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-description">
<b>Returns : </b> <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >void</a></code>
</div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="ngOnChanges"></a>
<span class="name"><b> ngOnChanges</b><a href="#ngOnChanges"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<code>ngOnChanges(changes: <a href="https://angular.io/docs/ts/latest/api/core/index/SimpleChanges-interface.html" target="_blank">SimpleChanges</a>)</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="57" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:57</a></div>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-description">
<b>Parameters :</b>
<table class="params">
<thead>
<tr>
<td>Name</td>
<td>Type</td>
<td>Optional</td>
<td>Description</td>
</tr>
</thead>
<tbody>
<tr>
<td>changes</td>
<td>
<code><a href="https://angular.io/docs/ts/latest/api/core/index/SimpleChanges-interface.html" target="_blank" >SimpleChanges</a></code>
</td>
<td>
</td>
<td></td>
</tr>
</tbody>
</table>
</div>
<div>
</div>
<div class="io-description">
<b>Returns : </b> <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >void</a></code>
</div>
<div class="io-description">
</div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="ngOnInit"></a>
<span class="name"><b> ngOnInit</b><a href="#ngOnInit"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<code>ngOnInit()</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="42" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:42</a></div>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-description">
<b>Returns : </b> <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >void</a></code>
</div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="prepare"></a>
<span class="name"><b> prepare</b><a href="#prepare"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<code>prepare(raw: <a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/string" target="_blank">string</a>)</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="91" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:91</a></div>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-description">
<b>Parameters :</b>
<table class="params">
<thead>
<tr>
<td>Name</td>
<td>Type</td>
<td>Optional</td>
<td>Description</td>
</tr>
</thead>
<tbody>
<tr>
<td>raw</td>
<td>
<code><a href="https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/string" target="_blank" >string</a></code>
</td>
<td>
</td>
<td></td>
</tr>
</tbody>
</table>
</div>
<div>
</div>
<div class="io-description">
<b>Returns : </b> <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >any</a></code>
</div>
<div class="io-description">
</div>
</td>
</tr>
</tbody>
</table>
</section>
<section>
<h3 id="inputs">
Properties
</h3>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="element"></a>
<span class="name"><b><span class="modifier">Public</span> element</b><a href="#element"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<span class="modifier-icon fa fa-reset"></span><code>element: <code><a href="https://angular.io/docs/ts/latest/api/core/index/ElementRef-class.html" target="_blank" >ElementRef</a></code>
</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<i>Type : </i> <code><a href="https://angular.io/docs/ts/latest/api/core/index/ElementRef-class.html" target="_blank" >ElementRef</a></code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="40" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:40</a></div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="post"></a>
<span class="name"><b> post</b><a href="#post"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<code>post: <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >any</a></code>
</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<i>Type : </i> <code><a href="https://www.typescriptlang.org/docs/handbook/basic-types.html" target="_blank" >any</a></code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="37" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:37</a></div>
</td>
</tr>
</tbody>
</table>
<table class="table table-sm table-bordered">
<tbody>
<tr>
<td class="col-md-4">
<a name="postsService"></a>
<span class="name"><b><span class="modifier">Public</span> postsService</b><a href="#postsService"><span class="fa fa-link"></span></a></span>
</td>
</tr>
<tr>
<td class="col-md-4">
<span class="modifier-icon fa fa-reset"></span><code>postsService: <code><a href="../injectables/PostsService.html" target="_self" >PostsService</a></code>
</code>
</td>
</tr>
<tr>
<td class="col-md-4">
<i>Type : </i> <code><a href="../injectables/PostsService.html" target="_self" >PostsService</a></code>
</td>
</tr>
<tr>
<td class="col-md-4">
<div class="io-line">Defined in <a href="" data-line="39" class="link-to-prism">src/app/ngx-blog/components/post/post.component.ts:39</a></div>
</td>
</tr>
</tbody>
</table>
</section>
</div>
<div class="tab-pane fade tab-source-code" id="source">
<pre class="line-numbers"><code class="language-typescript">import { AfterViewInit, Component, ElementRef, Input, OnChanges, OnInit, SimpleChanges, ViewEncapsulation } from '@angular/core';
import { PostsService } from '../../services/posts.service';
import 'rxjs/add/operator/switchMap';
import * as marked from 'marked';
import * as Prism from 'prismjs';
import 'prismjs/prism';
import 'prismjs/components/prism-bash';
import 'prismjs/components/prism-c';
import 'prismjs/components/prism-cpp';
import 'prismjs/components/prism-csharp';
import 'prismjs/components/prism-css';
import 'prismjs/components/prism-diff';
import 'prismjs/components/prism-java';
import 'prismjs/components/prism-javascript';
import 'prismjs/components/prism-python';
import 'prismjs/components/prism-sass';
import 'prismjs/components/prism-scss';
import 'prismjs/components/prism-typescript';
/**
* post.component
* component for ngxb-post
*/
@Component({
selector: 'ngxb-post, [ngxb-post]',
template: `
<ng-content></ng-content>`,
encapsulation: ViewEncapsulation.None,
styleUrls: [ 'theme.scss' ]
})
export class PostComponent implements OnInit, OnChanges, AfterViewInit {
@Input() data: string;
@Input() src: string;
post: any;
constructor(public postsService: PostsService,
public element: ElementRef) { }
ngOnInit() {}
ngAfterViewInit() {
if (this.data) {
this.handleData();
return;
}
if (this.src) {
this.handleSrc();
return;
}
this.handleRaw(this.element.nativeElement.innerHTML);
}
// SimpleChanges parameter is required for AoT compilation (do not remove)
ngOnChanges(changes: SimpleChanges) {
if (changes.data) {
this.handleData();
return;
}
if (changes.src) {
this.handleSrc();
return;
}
}
handleData() {
this.handleRaw(this.data);
}
handleSrc() {
const extension = this.src
? this.src.split('.').splice(-1).join()
: null;
this.postsService.getSource(this.src)
.subscribe(data => {
const raw = extension !== 'md'
? '```' + extension + '\n' + data + '\n```'
: data;
this.handleRaw(raw);
});
}
handleRaw(raw: string) {
const markdown = raw;
this.element.nativeElement.innerHTML = marked(markdown);
Prism.highlightAll(false);
}
prepare(raw: string) {
if (!raw) {
return '';
}
let indentStart: number;
return raw
.replace(/\&gt;/g, '>')
.split('\n')
.map((line: string) => {
// find position of 1st non-whitespace character
// to determine the markdown indentation start
if (line.length > 0 && isNaN(indentStart)) {
indentStart = line.search(/\S|$/);
}
// remove whitespaces before indentation start
return indentStart
? line.substring(indentStart)
: line;
}).join('\n');
}
}
</code></pre>
</div>
<div class="tab-pane fade" id="tree">
<div id="tree-container"></div>
<div class="tree-legend">
<div class="title">
<b>Legend</b>
</div>
<div>
<div class="color htmlelement"></div><span>Html element</span>
</div>
<div>
<div class="color component"></div><span>Component</span>
</div>
<div>
<div class="color directive"></div><span>Html element with directive</span>
</div>
</div>
</div>
</div>
<script src="../js/libs/vis.min.js"></script>
<script src="../js/libs/htmlparser.js"></script>
<script src="../js/libs/deep-iterator.js"></script>
<script>
var COMPONENT_TEMPLATE = '<div><ng-content></ng-content></div>'
var COMPONENTS = [{'name': 'AppComponent', 'selector': 'ngxb-app'},{'name': 'BlogComponent', 'selector': 'ngxb-blog'},{'name': 'HomeComponent', 'selector': 'ngxb-home'},{'name': 'PostComponent', 'selector': 'ngxb-post, [ngxb-post]'},{'name': 'PostsComponent', 'selector': 'ngxb-posts'}];
var DIRECTIVES = [];
var ACTUAL_COMPONENT = {'name': 'PostComponent'};
</script>
<script src="../js/tree.js"></script>
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<div class="has-results">
<h1 class="search-results-title"><span class='search-results-count'></span> results matching "<span class='search-query'></span>"</h1>
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<script src="../js/libs/bootstrap-native.js"></script>
<script src="../js/libs/es6-shim.min.js"></script>
<script src="../js/libs/EventDispatcher.js"></script>
<script src="../js/libs/promise.min.js"></script>
<script src="../js/libs/zepto.min.js"></script>
<script src="../js/compodoc.js"></script>
<script>var COMPODOC_CURRENT_PAGE_DEPTH = 1;</script>
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| jasonhodges/ngx-blog | documentation/components/PostComponent.html | HTML | mit | 55,172 |
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>CodePen - A Pen by Ren Valeroso</title>
</head>
<body>
<head>
<title> Ren's Notes</title>
</head>
<h1>Basics of the Web</h1>
<b>World Wide Web(WWW)</b>- collection of HTML documents<br>
<b>HTML</b>-hypertext markup language-main type of document on the web. <br><br>
<b> Major pieces of the web</b><br>
-you<br>-your computer<br>-the internet<br>-HTTP<br>-servers<br><br>
<b>HTML is made of</b><br>-text content<br>-markup<br>-references to other docs<br>-links to other pages<br><br>
<b>HTML tags</b><br>
Computers can only understand the instructions given by human programmers(must be exact).<br>
HTML elements refers to everything within a set of opening & closing tags. <a href="https://www.udacity.com/course/viewer/#!/c-nd000/l-3851658626/m-3847388548">This video</a> is an overview of tags<br><br>
Tags are contained eithing angles brackets<br>
Void tags do not require end tags<br><br>
Images can be added to HTML documents and is demonstrated in <a href="https://www.udacity.com/course/viewer/#!/c-nd000/l-3851658626/m-3847388548">this video</a><br>
To help remember HTML codes, Google search <a href="https://www.google.com/?gws_rd=ssl#q=adding+links+to+HTML"> adding links to HTML</a><br><br>
<b>Inline vs block</b><br>
HTML elements are either inline or block.<br>
Containers elements do nothing bu contain stuff inside them.<br>
</body>
</html> | tyrodan/getting-started-with-html | index.html | HTML | mit | 1,440 |
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<div class="document" id="learning-to-classify-text">
<h1 class="title">6. Learning to Classify Text</h1>
<!-- -*- mode: rst -*- -->
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<!-- Replacements that rely on previous definitions :-) -->
<!-- standard global imports
>>> from __future__ import division
>>> import nltk, re, pprint -->
<!-- Organization:
- Supervised Classification - - this introduces basic concepts, and
runs through lots of interesting examples
- Evaluation - - talks about evaluation :)
- Classification Methods (x3)
- Generative vs Conditional
- Joint Classification
- Data modeling - - this talks about abstractly what we can learn
about language as linguists
- ML in Python -->
<!-- XXX clustering and nltk.cluster not mentioned at all -->
<span class="target" id="chap-data-intensive"></span><!-- XXX "sample set" or "evaluation set"- - and what about "gold standard"? -->
<!-- XXX globally, "<word>"(ie word enclosed by double quotes) needs to be replaced by -->
<!-- `<word>`:lx: -->
<!-- nomenclature note: training corpus/sample corpus or training set/sample set?? -->
<!-- discuss qc corpus -->
<!-- explain that segmentation (e.g. tokenization, sentence segmentation) can
be viewed as a classification task -->
<!-- Determinize, for the sake of doctest:
>>> import random; random.seed(12345) -->
<p>Detecting patterns is a central part of Natural Language Processing. Words ending in
<span class="example">-ed</span> tend to be past tense verbs (<a class="reference external" href="http://www.nltk.org/book/ch05.html#chap-tag">5.</a>). Frequent use of
<span class="example">will</span> is indicative of news text (<a class="reference external" href="http://www.nltk.org/book/ch03.html#chap-words">3</a>). These observable
patterns — word structure and word frequency — happen to
correlate with particular aspects of meaning, such as tense and topic.
But how did we know where to start looking, which aspects of form to
associate with which aspects of meaning?</p>
<p>The goal of this chapter is to answer the following questions:</p>
<ol class="arabic simple">
<li>How can we identify particular features of language data that
are salient for classifying it?</li>
<li>How can we construct models of language that can
be used to perform language processing tasks automatically?</li>
<li>What can we learn about language from these models?</li>
</ol>
<p>Along the way we will study some important machine learning
techniques, including decision trees, naive Bayes' classifiers,
and maximum entropy classifiers. We will gloss over the mathematical and
statistical underpinnings of these techniques, focusing instead on how
and when to use them (see the Further Readings section for more
technical background). Before looking at these methods, we first need
to appreciate the broad scope of this topic.</p>
<div class="section" id="supervised-classification">
<span id="sec-supervised-classification"></span><h1>1 Supervised Classification</h1>
<p><a name="classification_index_term"><span class="termdef">Classification</span> is the task of choosing the correct </a><a name="class_label_index_term"><span class="termdef">class
label</span> for a given input. In basic classification tasks, each
input is considered in isolation from all other inputs, and the set of
labels is defined in advance. Some examples of classification tasks
are:</a></p><a name="class_label_index_term">
<ul class="simple">
<li>Deciding whether an email is spam or not.</li>
<li>Deciding what the topic of a news article is, from a fixed list of
topic areas such as "sports," "technology," and "politics."</li>
<li>Deciding whether a given occurrence of the word <span class="example">bank</span> is used to
refer to a river bank, a financial institution, the act of tilting
to the side, or the act of depositing something in a financial
institution.</li>
</ul>
<p>The basic classification task has a number of interesting variants.
For example, in multi-class classification, each instance may be
assigned multiple labels; in open-class classification, the set of
labels is not defined in advance; and in sequence classification, a
list of inputs are jointly classified.</p>
</a><p><a name="class_label_index_term">A classifier is called </a><a name="supervised_index_term"><span class="termdef">supervised</span> if it is built based on
training corpora containing the correct label for each input. The
framework used by supervised classification is shown in
</a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-supervised-classification">1.1</a>.</p>
<span class="target" id="fig-supervised-classification"></span><div class="figure" id="fig-supervised-classification">
<img alt="../images/supervised-classification.png" src="./6. Learning to Classify Text_files/supervised-classification.png" style="width: 456.5px; height: 235.5px;">
<p class="caption"><span class="caption-label">Figure 1.1</span>: Supervised Classification. (a) During training, a feature
extractor is used to convert each input value to a feature set.
These feature sets, which capture the basic information about
each input that should be used to classify it, are discussed in
the next section.
Pairs of feature sets and labels are fed into the machine learning
algorithm to generate a model. (b) During prediction, the same
feature extractor is used to convert unseen inputs to feature sets.
These feature sets are then fed into the model, which generates
predicted labels.</p>
</div>
<p>In the rest of this section, we will look at how classifiers can be
employed to solve a wide variety of tasks. Our discussion is not intended
to be comprehensive, but to give a representative sample of tasks that
can be performed with the help of text classifiers.</p>
<div class="section" id="gender-identification">
<h2>1.1 Gender Identification</h2>
<p>In <a class="reference external" href="http://www.nltk.org/book/ch02.html#sec-lexical-resources">4</a> we saw that male and female names
have some distinctive characteristics. Names ending in <span class="example">a</span>,
<span class="example">e</span> and <span class="example">i</span> are likely to be female, while names ending in
<span class="example">k</span>, <span class="example">o</span>, <span class="example">r</span>, <span class="example">s</span> and <span class="example">t</span> are likely to be male.
Let's build a classifier to model these differences more precisely.</p>
<p>The first step in creating a classifier is deciding what
<a name="features_index_term"><span class="termdef">features</span> of the input are relevant, and how to </a><a name="encode_index_term"><span class="termdef">encode</span>
those features. For this example, we'll start by just looking at the
final letter of a given name. The following </a><a name="feature_extractor_index_term"><span class="termdef">feature extractor</span>
function builds a dictionary containing relevant information about a
given name:</a></p><a name="feature_extractor_index_term">
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">def</span> <span class="pysrc-defname">gender_features</span>(word):
<span class="pysrc-more">... </span> return {<span class="pysrc-string">'last_letter'</span>: word[-1]}
<span class="pysrc-prompt">>>> </span>gender_features(<span class="pysrc-string">'Shrek'</span>)
<span class="pysrc-output">{'last_letter': 'k'}</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
</a><p><a name="feature_extractor_index_term">The returned dictionary, known as a </a><a name="feature_set_index_term"><span class="termdef">feature set</span>, maps from
features' names to their values. Feature names are case-sensitive
strings that typically provide a short human-readable description of
the feature. Feature values are values with simple types, such as
booleans, numbers, and strings.</a></p><a name="feature_set_index_term">
<div class="note">
<p class="first admonition-title">Note</p>
<p class="last">Most classification methods require that features be encoded using
simple value types, such as booleans, numbers, and strings. But
note that just because a feature has a simple type, does not
necessarily mean that the feature's value is simple to express or
compute; indeed, it is even possible to use very complex and
informative values, such as the output of a second supervised
classifier, as features.</p>
</div>
<p>Now that we've defined a feature extractor, we need to prepare
a list of examples and corresponding
class labels.</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">from</span> nltk.corpus <span class="pysrc-keyword">import</span> names
<span class="pysrc-prompt">>>> </span>labeled_names = ([(name, <span class="pysrc-string">'male'</span>) <span class="pysrc-keyword">for</span> name <span class="pysrc-keyword">in</span> names.words(<span class="pysrc-string">'male.txt'</span>)] +
<span class="pysrc-more">... </span>[(name, <span class="pysrc-string">'female'</span>) <span class="pysrc-keyword">for</span> name <span class="pysrc-keyword">in</span> names.words(<span class="pysrc-string">'female.txt'</span>)])
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">import</span> random
<span class="pysrc-prompt">>>> </span>random.shuffle(labeled_names)</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<!-- XXX say something about what featuresets are -->
</a><p><a name="feature_set_index_term">Next, we use the feature extractor to process the <tt class="doctest"><span class="pre">names</span></tt> data, and
divide the resulting list of feature sets into a </a><a name="training_set_index_term"><span class="termdef">training set</span>
and a </a><a name="test_set_index_term"><span class="termdef">test set</span>. The training set is used to train a new
"naive Bayes" classifier.</a></p><a name="test_set_index_term">
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>featuresets = [(gender_features(n), gender) <span class="pysrc-keyword">for</span> (n, gender) <span class="pysrc-keyword">in</span> labeled_names]
<span class="pysrc-prompt">>>> </span>train_set, test_set = featuresets[500:], featuresets[:500]
<span class="pysrc-prompt">>>> </span>classifier = nltk.NaiveBayesClassifier.train(train_set)</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>We will learn more about the naive Bayes classifier later in the
chapter. For now, let's just test it out on some names that did not
appear in its training data:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>classifier.classify(gender_features(<span class="pysrc-string">'Neo'</span>))
<span class="pysrc-output">'male'</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span>classifier.classify(gender_features(<span class="pysrc-string">'Trinity'</span>))
<span class="pysrc-output">'female'</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Observe that these character names from <em>The Matrix</em> are correctly
classified. Although this science fiction movie is set in 2199, it
still conforms with our expectations about names and genders. We can
systematically evaluate the classifier on a much larger quantity of
unseen data:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(nltk.classify.accuracy(classifier, test_set))
<span class="pysrc-output">0.758</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Finally, we can examine the classifier to determine which features it
found most effective for distinguishing the names' genders:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>classifier.show_most_informative_features(5)
<span class="pysrc-output">Most Informative Features</span>
<span class="pysrc-output"> last_letter = 'a' female : male = 38.3 : 1.0</span>
<span class="pysrc-output"> last_letter = 'k' male : female = 31.4 : 1.0</span>
<span class="pysrc-output"> last_letter = 'f' male : female = 15.3 : 1.0</span>
<span class="pysrc-output"> last_letter = 'p' male : female = 10.6 : 1.0</span>
<span class="pysrc-output"> last_letter = 'w' male : female = 10.6 : 1.0</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
</a><p><a name="test_set_index_term">This listing shows that the names in the training set that end in "a"
are female 38 times more often than they are male, but names that end
in "k" are male 31 times more often than they are female. These
ratios are known as </a><a name="likelihood_ratios_index_term"><span class="termdef">likelihood ratios</span>, and can be useful for
comparing different feature-outcome relationships.</a></p><a name="likelihood_ratios_index_term">
<div class="note">
<p class="first admonition-title">Note</p>
<p class="last"><strong>Your Turn:</strong>
Modify the <tt class="doctest"><span class="pre">gender_features()</span></tt> function to provide the
classifier with features encoding the length of the name, its first
letter, and any other features that seem like they might be
informative. Retrain the classifier with these new features, and
test its accuracy.</p>
</div>
<p>When working with large corpora, constructing a single list
that contains the features of every instance can use up a large
amount of memory. In these cases, use the function
<tt class="doctest"><span class="pre">nltk.classify.apply_features</span></tt>, which returns an object that acts
like a list but does not store all the feature sets in memory:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">from</span> nltk.classify <span class="pysrc-keyword">import</span> apply_features
<span class="pysrc-prompt">>>> </span>train_set = apply_features(gender_features, names[500:])
<span class="pysrc-prompt">>>> </span>test_set = apply_features(gender_features, names[:500])</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
</a></div><a name="likelihood_ratios_index_term">
</a><div class="section" id="choosing-the-right-features"><a name="likelihood_ratios_index_term">
<h2>1.2 Choosing The Right Features</h2>
<p>Selecting relevant features and deciding how to encode them for a
learning method can have an enormous impact on the learning method's
ability to extract a good model. Much of the interesting work in
building a classifier is deciding what features might be relevant, and
how we can represent them. Although it's often possible to get decent
performance by using a fairly simple and obvious set of features,
there are usually significant gains to be had by using carefully
constructed features based on a thorough understanding of the task at
hand.</p>
</a><p><a name="likelihood_ratios_index_term">Typically, feature extractors are built through a process of
trial-and-error, guided by intuitions about what information is
relevant to the problem. It's common to start with a
"kitchen sink" approach, including all the features that you can think
of, and then checking to see which features actually are
helpful. We take this approach for name gender features in
</a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-gender-features-overfitting">1.2</a>.</p>
<!-- XXX is it worth telling readers not to confuse feature names like "count(j)"
with functions? -->
<!-- XXX how about mentioning the term "presence feature" as the name
for boolean-valued features? -->
<!-- XXX briefly explain what's being done in
features["count(%s)" % letter] = name.lower().count(letter) -->
<span class="target" id="code-gender-features-overfitting"></span><div class="pylisting">
<p></p><table border="0" cellpadding="0" cellspacing="0" class="pylisting" width="95%">
<tbody><tr><td class="codeblock">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_codeblock_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-keyword">def</span> <span class="pysrc-defname">gender_features2</span>(name):
features = {}
features[<span class="pysrc-string">"first_letter"</span>] = name[0].lower()
features[<span class="pysrc-string">"last_letter"</span>] = name[-1].lower()
<span class="pysrc-keyword">for</span> letter <span class="pysrc-keyword">in</span> <span class="pysrc-string">'abcdefghijklmnopqrstuvwxyz'</span>:
features[<span class="pysrc-string">"count(%s)"</span> % letter] = name.lower().count(letter)
features[<span class="pysrc-string">"has(%s)"</span> % letter] = (letter <span class="pysrc-keyword">in</span> name.lower())
return features</pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>gender_features2(<span class="pysrc-string">'John'</span>)
<span class="pysrc-output">{'count(j)': 1, 'has(d)': False, 'count(b)': 0, ...}</span></pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="caption"><p class="caption"><a class="reference external" href="http://www.nltk.org/book/pylisting/code_gender_features_overfitting.py" type="text/x-python"><span class="caption-label">Example 1.2 (code_gender_features_overfitting.py)</span></a>: <span class="caption-label">Figure 1.2</span>: A Feature Extractor that Overfits Gender Features.
The featuresets returned by this feature extractor contain a
large number of specific features, leading to overfitting for
the relatively small Names Corpus.</p></td></tr>
</tbody></table></div>
<p>However, there are usually limits to the number of features
that you should use with a given learning algorithm — if you provide
too many features, then the algorithm will have a higher chance of
relying on idiosyncrasies of your training data that don't generalize
well to new examples. This problem is known as <a name="overfitting_index_term"><span class="termdef">overfitting</span>, and
can be especially problematic when working with small training sets. For
example, if we train a naive Bayes classifier using the feature
extractor shown in </a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-gender-features-overfitting">1.2</a>, it will overfit
relatively small training set, resulting in a system whose accuracy
is about 1% lower than the accuracy of a classifier that only
pays attention to the final letter of each name:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>featuresets = [(gender_features2(n), gender) <span class="pysrc-keyword">for</span> (n, gender) <span class="pysrc-keyword">in</span> names]
<span class="pysrc-prompt">>>> </span>train_set, test_set = featuresets[500:], featuresets[:500]
<span class="pysrc-prompt">>>> </span>classifier = nltk.NaiveBayesClassifier.train(train_set)
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(nltk.classify.accuracy(classifier, test_set))
<span class="pysrc-output">0.748</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<!-- XXX How common is it to call the training + dev-sample data a 'development set'? -->
<!-- I've not come across it. In -->
<!-- any case, the extra label seems unnecessary. J&M seem to be more standard; they -->
<!-- call partition into "training", "dev-sample" and "sample" (p187) -->
<p>Once an initial set of features has been chosen, a very productive
method for refining the feature set is <a name="error_analysis_index_term"><span class="termdef">error analysis</span>. First,
we select a </a><a name="development_set_index_term"><span class="termdef">development set</span>, containing the corpus data for
creating the model. This development set is then subdivided
into the </a><a name="training_set_index_term_2"><span class="termdef">training set</span> and the </a><a name="dev_test_index_term"><span class="termdef">dev-test</span> set.</a></p><a name="dev_test_index_term">
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>train_names = names[1500:]
<span class="pysrc-prompt">>>> </span>devtest_names = names[500:1500]
<span class="pysrc-prompt">>>> </span>test_names = names[:500]</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
</a><p><a name="dev_test_index_term">The training set is used to train the model, and the dev-test set is
used to perform error analysis. The test set serves in our final
evaluation of the system. For reasons discussed below, it is
important that we employ a separate dev-test set for error analysis,
rather than just using the test set. The division of the corpus data
into different subsets is shown in </a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-corpus-org">1.3</a>.</p>
<span class="target" id="fig-corpus-org"></span><div class="figure" id="fig-corpus-org">
<img alt="../images/corpus-org.png" src="./6. Learning to Classify Text_files/corpus-org.png" style="width: 319.0px; height: 166.0px;">
<p class="caption"><span class="caption-label">Figure 1.3</span>: Organization of corpus data for training supervised classifiers.
The corpus data is divided into two sets: the development set,
and the test set. The development set is often further subdivided
into a training set and a dev-test set.</p>
</div>
<p>Having divided the corpus into appropriate datasets, we train a model
using the training set <a class="reference internal" href="http://www.nltk.org/book/ch06.html#err-analysis-train"><span id="ref-err-analysis-train"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></span></a>, and then run it on the
devtest set <a class="reference internal" href="http://www.nltk.org/book/ch06.html#err-analysis-run"><span id="ref-err-analysis-run"><img src="./6. Learning to Classify Text_files/callout2.gif" alt="[2]" class="callout"></span></a>.</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>train_set = [(gender_features(n), gender) <span class="pysrc-keyword">for</span> (n, gender) <span class="pysrc-keyword">in</span> train_names]
<span class="pysrc-prompt">>>> </span>devtest_set = [(gender_features(n), gender) <span class="pysrc-keyword">for</span> (n, gender) <span class="pysrc-keyword">in</span> devtest_names]
<span class="pysrc-prompt">>>> </span>test_set = [(gender_features(n), gender) <span class="pysrc-keyword">for</span> (n, gender) <span class="pysrc-keyword">in</span> test_names]
<span class="pysrc-prompt">>>> </span>classifier = nltk.NaiveBayesClassifier.train(train_set) <a name="err-analysis-train"></a><a href="http://www.nltk.org/book/ch06.html#ref-err-analysis-train"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></a>
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(nltk.classify.accuracy(classifier, devtest_set)) <a name="err-analysis-run"></a><a href="http://www.nltk.org/book/ch06.html#ref-err-analysis-run"><img src="./6. Learning to Classify Text_files/callout2.gif" alt="[2]" class="callout"></a>
<span class="pysrc-output">0.765</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Using the dev-test set, we can generate a list of the errors that the
classifier makes when predicting name genders:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>errors = []
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">for</span> (name, tag) <span class="pysrc-keyword">in</span> devtest_names:
<span class="pysrc-more">... </span> guess = classifier.classify(gender_features(name))
<span class="pysrc-more">... </span> <span class="pysrc-keyword">if</span> guess != tag:
<span class="pysrc-more">... </span> errors.append( (tag, guess, name) )</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>We can then examine individual error cases where the model predicted
the wrong label, and try to determine what additional pieces of
information would allow it to make the right decision (or which
existing pieces of information are tricking it into making the wrong
decision). The feature set can then be adjusted accordingly. The
names classifier that we have built generates about 100 errors on the
dev-test corpus:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">for</span> (tag, guess, name) <span class="pysrc-keyword">in</span> sorted(errors):
<span class="pysrc-more">... </span> <span class="pysrc-keyword">print</span>(<span class="pysrc-string">'correct=%-8s guess=%-8s name=%-30s'</span> % (tag, guess, name))
<span class="pysrc-more"> ...</span>
<span class="pysrc-output">correct=female guess=male name=Cindelyn</span>
<span class="pysrc-output"> ...</span>
<span class="pysrc-output">correct=female guess=male name=Katheryn</span>
<span class="pysrc-output">correct=female guess=male name=Kathryn</span>
<span class="pysrc-output"> ...</span>
<span class="pysrc-output">correct=male guess=female name=Aldrich</span>
<span class="pysrc-output"> ...</span>
<span class="pysrc-output">correct=male guess=female name=Mitch</span>
<span class="pysrc-output"> ...</span>
<span class="pysrc-output">correct=male guess=female name=Rich</span>
<span class="pysrc-output"> ...</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Looking through this list of errors makes it clear that some suffixes
that are more than one letter can be indicative of name genders. For
example, names ending in <span class="example">yn</span> appear to be predominantly female,
despite the fact that names ending in <span class="example">n</span> tend to be male; and names
ending in <span class="example">ch</span> are usually male, even though names that end in <span class="example">h</span>
tend to be female. We therefore
adjust our feature extractor to include features for two-letter
suffixes:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">def</span> <span class="pysrc-defname">gender_features</span>(word):
<span class="pysrc-more">... </span> return {<span class="pysrc-string">'suffix1'</span>: word[-1:],
<span class="pysrc-more">... </span> <span class="pysrc-string">'suffix2'</span>: word[-2:]}</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Rebuilding the classifier with the new feature extractor, we see that
the performance on the dev-test dataset improves by almost 2
percentage points (from 76.5% to 78.2%):</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>train_set = [(gender_features(n), gender) <span class="pysrc-keyword">for</span> (n, gender) <span class="pysrc-keyword">in</span> train_names]
<span class="pysrc-prompt">>>> </span>devtest_set = [(gender_features(n), gender) <span class="pysrc-keyword">for</span> (n, gender) <span class="pysrc-keyword">in</span> devtest_names]
<span class="pysrc-prompt">>>> </span>classifier = nltk.NaiveBayesClassifier.train(train_set)
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(nltk.classify.accuracy(classifier, devtest_set))
<span class="pysrc-output">0.782</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>This error analysis procedure can then be repeated, checking for
patterns in the errors that are made by the newly improved classifier.
Each time the error analysis procedure is repeated, we should select a
different dev-test/training split, to ensure that the classifier
does not start to reflect idiosyncrasies in the dev-test set.</p>
<p>But once we've used the dev-test set to help us develop the
model, we can no longer trust that it will give us an accurate idea of
how well the model would perform on new data. It is therefore
important to keep the test set separate, and unused, until our model
development is complete. At that point, we can use the test set to
evaluate well our model will perform on new input values.</p>
</div>
<div class="section" id="document-classification">
<h2>1.3 Document Classification</h2>
<!-- Determinize, for the sake of doctest:
>>> import random; random.seed(12345) -->
<p>In <a class="reference external" href="http://www.nltk.org/book/ch02.html#sec-extracting-text-from-corpora">1</a>, we saw several examples of
corpora where documents have been labeled with categories. Using
these corpora, we can build classifiers that will automatically tag
new documents with appropriate category labels. First, we
construct a list of documents, labeled with the appropriate
categories. For this example, we've chosen the Movie Reviews Corpus,
which categorizes each review as positive or negative.</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">from</span> nltk.corpus <span class="pysrc-keyword">import</span> movie_reviews
<span class="pysrc-prompt">>>> </span>documents = [(list(movie_reviews.words(fileid)), category)
<span class="pysrc-more">... </span> <span class="pysrc-keyword">for</span> category <span class="pysrc-keyword">in</span> movie_reviews.categories()
<span class="pysrc-more">... </span> <span class="pysrc-keyword">for</span> fileid <span class="pysrc-keyword">in</span> movie_reviews.fileids(category)]
<span class="pysrc-prompt">>>> </span>random.shuffle(documents)</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Next, we define a feature extractor for documents, so the classifier
will know which aspects of the data it should pay attention to
(<a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-document-classify-fd">1.4</a>). For document topic identification, we can
define a feature for each word, indicating whether the document
contains that word. To limit the number of features that the
classifier needs to process, we begin by constructing a list of the
2000 most frequent words in the overall corpus
<a class="reference internal" href="http://www.nltk.org/book/ch06.html#document-classify-all-words"><span id="ref-document-classify-all-words"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></span></a>. We can then define a feature extractor
<a class="reference internal" href="http://www.nltk.org/book/ch06.html#document-classify-extractor"><span id="ref-document-classify-extractor"><img src="./6. Learning to Classify Text_files/callout2.gif" alt="[2]" class="callout"></span></a> that simply checks whether each of these
words is present in a given document.</p>
<span class="target" id="code-document-classify-fd"></span><div class="pylisting">
<p></p><table border="0" cellpadding="0" cellspacing="0" class="pylisting" width="95%">
<tbody><tr><td class="codeblock">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_codeblock_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest">all_words = nltk.FreqDist(w.lower() <span class="pysrc-keyword">for</span> w <span class="pysrc-keyword">in</span> movie_reviews.words())
word_features = all_words.keys()[:2000] <a name="document-classify-all-words"></a><a href="http://www.nltk.org/book/ch06.html#ref-document-classify-all-words"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></a>
<span class="pysrc-keyword">def</span> <span class="pysrc-defname">document_features</span>(document): <a name="document-classify-extractor"></a><a href="http://www.nltk.org/book/ch06.html#ref-document-classify-extractor"><img src="./6. Learning to Classify Text_files/callout2.gif" alt="[2]" class="callout"></a>
document_words = set(document) <a name="document-classify-set"></a><a href="http://www.nltk.org/book/ch06.html#ref-document-classify-set"><img src="./6. Learning to Classify Text_files/callout3.gif" alt="[3]" class="callout"></a>
features = {}
<span class="pysrc-keyword">for</span> word <span class="pysrc-keyword">in</span> word_features:
features[<span class="pysrc-string">'contains(%s)'</span> % word] = (word <span class="pysrc-keyword">in</span> document_words)
return features</pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(document_features(movie_reviews.words(<span class="pysrc-string">'pos/cv957_8737.txt'</span>)))
<span class="pysrc-output">{'contains(waste)': False, 'contains(lot)': False, ...}</span></pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="caption"><p class="caption"><a class="reference external" href="http://www.nltk.org/book/pylisting/code_document_classify_fd.py" type="text/x-python"><span class="caption-label">Example 1.4 (code_document_classify_fd.py)</span></a>: <span class="caption-label">Figure 1.4</span>: A feature extractor for document classification, whose
features indicate whether or not individual words are present
in a given document.</p></td></tr>
</tbody></table></div>
<div class="note">
<p class="first admonition-title">Note</p>
<p class="last">The reason that we compute the set of all words in a document in
<a class="reference internal" href="http://www.nltk.org/book/ch06.html#document-classify-set"><span id="ref-document-classify-set"><img src="./6. Learning to Classify Text_files/callout3.gif" alt="[3]" class="callout"></span></a>, rather than just checking if
<tt class="doctest"><span class="pre">word <span class="pysrc-keyword">in</span> document</span></tt>, is
that checking whether a word occurs in a set is much faster than
checking whether it occurs in a list (<a class="reference external" href="http://www.nltk.org/book/ch04.html#sec-algorithm-design">4.7</a>).</p>
</div>
<p>Now that we've defined our feature extractor, we can use it to train a
classifier to label new movie reviews (<a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-document-classify-use">1.5</a>). To
check how reliable the resulting classifier is, we compute its
accuracy on the test set <a class="reference internal" href="http://www.nltk.org/book/ch06.html#document-classify-test"><span id="ref-document-classify-test"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></span></a>. And once again,
we can use <tt class="doctest"><span class="pre">show_most_informative_features()</span></tt> to find out which
features the classifier found to be most informative
<a class="reference internal" href="http://www.nltk.org/book/ch06.html#document-classify-smif"><span id="ref-document-classify-smif"><img src="./6. Learning to Classify Text_files/callout2.gif" alt="[2]" class="callout"></span></a>.</p>
<span class="target" id="code-document-classify-use"></span><div class="pylisting">
<p></p><table border="0" cellpadding="0" cellspacing="0" class="pylisting" width="95%">
<tbody><tr><td class="codeblock">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_codeblock_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest">featuresets = [(document_features(d), c) <span class="pysrc-keyword">for</span> (d,c) <span class="pysrc-keyword">in</span> documents]
train_set, test_set = featuresets[100:], featuresets[:100]
classifier = nltk.NaiveBayesClassifier.train(train_set)</pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(nltk.classify.accuracy(classifier, test_set)) <a name="document-classify-test"></a><a href="http://www.nltk.org/book/ch06.html#ref-document-classify-test"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></a>
<span class="pysrc-output">0.81</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span>classifier.show_most_informative_features(5) <a name="document-classify-smif"></a><a href="http://www.nltk.org/book/ch06.html#ref-document-classify-smif"><img src="./6. Learning to Classify Text_files/callout2.gif" alt="[2]" class="callout"></a>
<span class="pysrc-output">Most Informative Features</span>
<span class="pysrc-output"> contains(outstanding) = True pos : neg = 11.1 : 1.0</span>
<span class="pysrc-output"> contains(seagal) = True neg : pos = 7.7 : 1.0</span>
<span class="pysrc-output"> contains(wonderfully) = True pos : neg = 6.8 : 1.0</span>
<span class="pysrc-output"> contains(damon) = True pos : neg = 5.9 : 1.0</span>
<span class="pysrc-output"> contains(wasted) = True neg : pos = 5.8 : 1.0</span></pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="caption"><p class="caption"><a class="reference external" href="http://www.nltk.org/book/pylisting/code_document_classify_use.py" type="text/x-python"><span class="caption-label">Example 1.5 (code_document_classify_use.py)</span></a>: <span class="caption-label">Figure 1.5</span>: Training and testing a classifier for document classification.</p></td></tr>
</tbody></table></div>
<p>Apparently in this corpus, a review that mentions "Seagal" is almost 8
times more likely to be negative than positive, while a review that
mentions "Damon" is about 6 times more likely to be positive.</p>
<!-- I tried adding simple frequencies w/ binning, but it didn't improve
performance. Using something more advanced like tf-idf probably
would, but I don't want to take up the space here to explain all that. -->
</div>
<div class="section" id="part-of-speech-tagging">
<h2>1.4 Part-of-Speech Tagging</h2>
<!-- The decision tree classifier is currently RIDICULOUSLY SLOW. :-/ -->
<p>In <a class="reference external" href="http://www.nltk.org/book/ch05.html#chap-tag">5.</a> we built a regular expression tagger that chooses a
part-of-speech tag for a word by looking at the internal make-up of
the word. However, this regular expression tagger had to be
hand-crafted. Instead, we can train a classifier to work out which
suffixes are most informative. Let's begin by finding out what the
most common suffixes are:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">from</span> nltk.corpus <span class="pysrc-keyword">import</span> brown
<span class="pysrc-prompt">>>> </span>suffix_fdist = nltk.FreqDist()
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">for</span> word <span class="pysrc-keyword">in</span> brown.words():
<span class="pysrc-more">... </span> word = word.lower()
<span class="pysrc-more">... </span> suffix_fdist[word[-1:]] += 1
<span class="pysrc-more">... </span> suffix_fdist[word[-2:]] += 1
<span class="pysrc-more">... </span> suffix_fdist[word[-3:]] += 1</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>common_suffixes = [suffix <span class="pysrc-keyword">for</span> (suffix, count) <span class="pysrc-keyword">in</span> suffix_fdist.most_common(100)]
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(common_suffixes)
<span class="pysrc-output">['e', ',', '.', 's', 'd', 't', 'he', 'n', 'a', 'of', 'the',</span>
<span class="pysrc-output"> 'y', 'r', 'to', 'in', 'f', 'o', 'ed', 'nd', 'is', 'on', 'l',</span>
<span class="pysrc-output"> 'g', 'and', 'ng', 'er', 'as', 'ing', 'h', 'at', 'es', 'or',</span>
<span class="pysrc-output"> 're', 'it', '``', 'an', "''", 'm', ';', 'i', 'ly', 'ion', ...]</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<!-- To make the emacs mode less confused: `` -->
<p>Next, we'll define a feature extractor function which checks a given
word for these suffixes:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">def</span> <span class="pysrc-defname">pos_features</span>(word):
<span class="pysrc-more">... </span> features = {}
<span class="pysrc-more">... </span> <span class="pysrc-keyword">for</span> suffix <span class="pysrc-keyword">in</span> common_suffixes:
<span class="pysrc-more">... </span> features[<span class="pysrc-string">'endswith(%s)'</span> % suffix] = word.lower().endswith(suffix)
<span class="pysrc-more">... </span> return features</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Feature extraction functions behave like tinted glasses, highlighting
some of the properties (colors) in our data and making it impossible
to see other properties. The classifier will rely exclusively on
these highlighted properties when determining how to label inputs. In
this case, the classifier will make its decisions based only on
information about which of the common suffixes (if any) a given word
has.</p>
<!-- XXX I like the use of spaces in the doctest block, but I think this the only time -->
<!-- they are used. -->
<p>Now that we've defined our feature extractor, we can use it to
train a new "decision tree" classifier (to be discussed in
<a class="reference internal" href="http://www.nltk.org/book/ch06.html#sec-decision-trees">4</a>):</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>tagged_words = brown.tagged_words(categories=<span class="pysrc-string">'news'</span>)
<span class="pysrc-prompt">>>> </span>featuresets = [(pos_features(n), g) <span class="pysrc-keyword">for</span> (n,g) <span class="pysrc-keyword">in</span> tagged_words]</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>size = int(len(featuresets) * 0.1)
<span class="pysrc-prompt">>>> </span>train_set, test_set = featuresets[size:], featuresets[:size]</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>classifier = nltk.DecisionTreeClassifier.train(train_set)
<span class="pysrc-prompt">>>> </span>nltk.classify.accuracy(classifier, test_set)
<span class="pysrc-output">0.62705121829935351</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>classifier.classify(pos_features(<span class="pysrc-string">'cats'</span>))
<span class="pysrc-output">'NNS'</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<!-- XXX raise the issue of interpretability of models earlier?
(E.g. deliberately use the word "interpret" in the opening of the chapter?) -->
<p>One nice feature of decision tree models is that they are often fairly
easy to interpret — we can even instruct NLTK to print them
out as pseudocode:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(classifier.pseudocode(depth=4))
<span class="pysrc-output">if endswith(,) == True: return ','</span>
<span class="pysrc-output">if endswith(,) == False:</span>
<span class="pysrc-output"> if endswith(the) == True: return 'AT'</span>
<span class="pysrc-output"> if endswith(the) == False:</span>
<span class="pysrc-output"> if endswith(s) == True:</span>
<span class="pysrc-output"> if endswith(is) == True: return 'BEZ'</span>
<span class="pysrc-output"> if endswith(is) == False: return 'VBZ'</span>
<span class="pysrc-output"> if endswith(s) == False:</span>
<span class="pysrc-output"> if endswith(.) == True: return '.'</span>
<span class="pysrc-output"> if endswith(.) == False: return 'NN'</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<!-- XXX NOTE: Last time I ran the doctests, I got a slightly different
decision tree. Is this nondeterministic? It appeared that the
decision tree was making *mostly* the same decisions. We can
update this, but it will require updating the following text too.
Here's the decision tree I got on the most recent run:
if endswith(the) == False:
if endswith(,) == False:
if endswith(s) == False:
if endswith(.) == False: return '.'
if endswith(.) == True: return '.'
if endswith(s) == True:
if endswith(is) == False: return 'PP$'
if endswith(is) == True: return 'BEZ'
if endswith(,) == True: return ','
if endswith(the) == True: return 'AT' -->
<p>Here, we can see that the classifier begins by checking whether a word
ends with a comma — if so, then it will receive the special tag
<tt class="doctest"><span class="pre"><span class="pysrc-string">","</span></span></tt>. Next, the classifier checks if the word ends in <tt class="doctest"><span class="pre"><span class="pysrc-string">"the"</span></span></tt>,
in which case it's almost certainly a determiner. This "suffix" gets
used early by the decision tree because the word "the" is so common.
Continuing on, the classifier checks if the word ends in "s". If so,
then it's most likely to receive the verb tag <tt class="doctest"><span class="pre">VBZ</span></tt> (unless it's
the word "is", which has a special tag <tt class="doctest"><span class="pre">BEZ</span></tt>), and if not,
then it's most likely a noun (unless it's the punctuation mark ".").
The actual classifier contains further nested if-then statements below
the ones shown here, but the <tt class="doctest"><span class="pre">depth=4</span></tt> argument just displays the
top portion of the decision tree.</p>
<!-- XXX How about some features that match word patterns more generally,
linking back to the knowledge represented in a regular expression
tagger, such as: (r'^-?[0-9]+(.[0-9]+)?$', 'CD')
-> response: this is a very large search space, though we could
manually throw some of them in. -->
</div>
<div class="section" id="exploiting-context">
<h2>1.5 Exploiting Context</h2>
<!-- Change this to use DecisionTree, to match prev section? -->
<p>By augmenting the feature extraction function, we could modify this
part-of-speech tagger to leverage a variety of other word-internal
features, such as the length of the word, the number of syllables it
contains, or its prefix. However, as long as the feature extractor
just looks at the target word, we have no way to add features that
depend on the <em>context</em> that the word appears in. But contextual
features often provide powerful clues about the correct tag — for
example, when tagging the word "fly," knowing that the previous word
is "a" will allow us to determine that it is functioning as a noun, not
a verb.</p>
<p>In order to accommodate features that depend on a word's context, we
must revise the pattern that we used to define our feature extractor.
Instead of just passing in the word to be tagged, we will pass in a
complete (untagged) sentence, along with the index of the target word.
This approach is demonstrated in <a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-suffix-pos-tag">1.6</a>, which employs a
context-dependent feature extractor to define a part of speech tag
classifier.</p>
<span class="target" id="code-suffix-pos-tag"></span><div class="pylisting">
<p></p><table border="0" cellpadding="0" cellspacing="0" class="pylisting" width="95%">
<tbody><tr><td class="codeblock">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_codeblock_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-keyword">def</span> <span class="pysrc-defname">pos_features</span>(sentence, i): <a name="suffix-pos-tag-fd"></a><a href="http://www.nltk.org/book/ch06.html#ref-suffix-pos-tag-fd"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></a>
features = {<span class="pysrc-string">"suffix(1)"</span>: sentence[i][-1:],
<span class="pysrc-string">"suffix(2)"</span>: sentence[i][-2:],
<span class="pysrc-string">"suffix(3)"</span>: sentence[i][-3:]}
<span class="pysrc-keyword">if</span> i == 0:
features[<span class="pysrc-string">"prev-word"</span>] = <span class="pysrc-string">"<START>"</span>
<span class="pysrc-keyword">else</span>:
features[<span class="pysrc-string">"prev-word"</span>] = sentence[i-1]
return features</pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>pos_features(brown.sents()[0], 8)
<span class="pysrc-output">{'suffix(3)': 'ion', 'prev-word': 'an', 'suffix(2)': 'on', 'suffix(1)': 'n'}</span>
<span class="pysrc-output"></span>
<span class="pysrc-prompt">>>> </span>tagged_sents = brown.tagged_sents(categories=<span class="pysrc-string">'news'</span>)
<span class="pysrc-prompt">>>> </span>featuresets = []
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">for</span> tagged_sent <span class="pysrc-keyword">in</span> tagged_sents:
<span class="pysrc-more">... </span> untagged_sent = nltk.tag.untag(tagged_sent)
<span class="pysrc-more">... </span> <span class="pysrc-keyword">for</span> i, (word, tag) <span class="pysrc-keyword">in</span> enumerate(tagged_sent):
<span class="pysrc-more">... </span> featuresets.append( (pos_features(untagged_sent, i), tag) )
<span class="pysrc-prompt">>>> </span>size = int(len(featuresets) * 0.1)
<span class="pysrc-prompt">>>> </span>train_set, test_set = featuresets[size:], featuresets[:size]
<span class="pysrc-prompt">>>> </span>classifier = nltk.NaiveBayesClassifier.train(train_set)
<span class="pysrc-prompt">>>> </span>nltk.classify.accuracy(classifier, test_set)
<span class="pysrc-output">0.78915962207856782</span></pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="caption"><p class="caption"><a class="reference external" href="http://www.nltk.org/book/pylisting/code_suffix_pos_tag.py" type="text/x-python"><span class="caption-label">Example 1.6 (code_suffix_pos_tag.py)</span></a>: <span class="caption-label">Figure 1.6</span>: A part-of-speech classifier whose feature detector
examines the context in which a word appears in order to
determine which part of speech tag should be assigned. In
particular, the identity of the previous word is included as a
feature.</p></td></tr>
</tbody></table></div>
<!-- This needs a comparison point from prev classifier!! -->
<!-- It would be nice to actually show this (using
show_most_informative_features or something): -->
<p>It is clear that exploiting contextual features improves the performance
of our part-of-speech tagger. For example, the classifier learns
that a word is likely to be a noun if it comes immediately after the
word "large" or the word "gubernatorial". However, it is unable to
learn the generalization that a word is probably a noun if it follows
an adjective, because it doesn't have access to the previous word's
part-of-speech tag. In general, simple classifiers always treat each
input as independent from all other inputs. In many contexts, this
makes perfect sense. For example, decisions about whether names tend
to be male or female can be made on a case-by-case basis. However,
there are often cases, such as part-of-speech tagging, where we are
interested in solving classification problems that are closely related
to one another.</p>
</div>
<div class="section" id="sequence-classification">
<h2>1.6 Sequence Classification</h2>
<p>In order to capture the dependencies between related classification
tasks, we can use <a name="joint_classifier_index_term"><span class="termdef">joint classifier</span> models, which choose an
appropriate labeling for a collection of related inputs. In the case
of part-of-speech tagging, a variety of different </a><a name="sequence_classifier_index_term"><span class="termdef">sequence
classifier</span> models can be used to jointly choose part-of-speech
tags for all the words in a given sentence.</a></p><a name="sequence_classifier_index_term">
<!-- note that consecutive classification isn't a widely-used term,
but it seems reasonably good to me. -->
</a><p><a name="sequence_classifier_index_term">One sequence classification strategy, known as </a><a name="consecutive_classification_index_term"><span class="termdef">consecutive
classification</span> or </a><a name="greedy_sequence_classification_index_term"><span class="termdef">greedy sequence classification</span>, is to
find the most likely class label for the first input,
then to use that answer to help find the best label for the next
input. The process can then be repeated until all of the inputs have
been labeled. This is the approach that was taken by the bigram
tagger from </a><a class="reference external" href="http://www.nltk.org/book/ch05.html#sec-n-gram-tagging">5</a>, which began by choosing a
part-of-speech tag for the first word in the sentence, and then chose
the tag for each subsequent word based on the word itself and the
predicted tag for the previous word.</p>
<p>This strategy is demonstrated in <a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-consecutive-pos-tagger">1.7</a>.
First, we must
augment our feature extractor function to take a <tt class="doctest"><span class="pre">history</span></tt>
argument, which provides a list of the tags that we've predicted for
the sentence so far <a class="reference internal" href="http://www.nltk.org/book/ch06.html#consec-pos-tag-features"><span id="ref-consec-pos-tag-features"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></span></a>.
Each tag in <tt class="doctest"><span class="pre">history</span></tt> corresponds with a word in <tt class="doctest"><span class="pre">sentence</span></tt>. But
note that <tt class="doctest"><span class="pre">history</span></tt> will only contain tags for words we've already
classified, that is, words to the left of the target word. Thus, while it is
possible to look at some features of words to the right
of the target word, it is not possible to look at the tags for those
words (since we haven't generated them yet).</p>
<p>Having defined a feature extractor, we can proceed to build our
sequence classifier <a class="reference internal" href="http://www.nltk.org/book/ch06.html#consec-pos-tagger"><span id="ref-consec-pos-tagger"><img src="./6. Learning to Classify Text_files/callout2.gif" alt="[2]" class="callout"></span></a>. During training, we use
the annotated tags to
provide the appropriate history to the feature extractor, but when
tagging new sentences, we generate the history list based on the
output of the tagger itself.</p>
<span class="target" id="code-consecutive-pos-tagger"></span><div class="pylisting">
<p></p><table border="0" cellpadding="0" cellspacing="0" class="pylisting" width="95%">
<tbody><tr><td class="codeblock">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_codeblock_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"> <span class="pysrc-keyword">def</span> <span class="pysrc-defname">pos_features</span>(sentence, i, history): <a name="consec-pos-tag-features"></a><a href="http://www.nltk.org/book/ch06.html#ref-consec-pos-tag-features"><img src="./6. Learning to Classify Text_files/callout1.gif" alt="[1]" class="callout"></a>
features = {<span class="pysrc-string">"suffix(1)"</span>: sentence[i][-1:],
<span class="pysrc-string">"suffix(2)"</span>: sentence[i][-2:],
<span class="pysrc-string">"suffix(3)"</span>: sentence[i][-3:]}
<span class="pysrc-keyword">if</span> i == 0:
features[<span class="pysrc-string">"prev-word"</span>] = <span class="pysrc-string">"<START>"</span>
features[<span class="pysrc-string">"prev-tag"</span>] = <span class="pysrc-string">"<START>"</span>
<span class="pysrc-keyword">else</span>:
features[<span class="pysrc-string">"prev-word"</span>] = sentence[i-1]
features[<span class="pysrc-string">"prev-tag"</span>] = history[i-1]
return features
<span class="pysrc-keyword">class</span> <span class="pysrc-defname">ConsecutivePosTagger</span>(nltk.TaggerI): <a name="consec-pos-tagger"></a><a href="http://www.nltk.org/book/ch06.html#ref-consec-pos-tagger"><img src="./6. Learning to Classify Text_files/callout2.gif" alt="[2]" class="callout"></a>
<span class="pysrc-keyword">def</span> <span class="pysrc-defname">__init__</span>(self, train_sents):
train_set = []
<span class="pysrc-keyword">for</span> tagged_sent <span class="pysrc-keyword">in</span> train_sents:
untagged_sent = nltk.tag.untag(tagged_sent)
history = []
<span class="pysrc-keyword">for</span> i, (word, tag) <span class="pysrc-keyword">in</span> enumerate(tagged_sent):
featureset = pos_features(untagged_sent, i, history)
train_set.append( (featureset, tag) )
history.append(tag)
self.classifier = nltk.NaiveBayesClassifier.train(train_set)
<span class="pysrc-keyword">def</span> <span class="pysrc-defname">tag</span>(self, sentence):
history = []
<span class="pysrc-keyword">for</span> i, word <span class="pysrc-keyword">in</span> enumerate(sentence):
featureset = pos_features(sentence, i, history)
tag = self.classifier.classify(featureset)
history.append(tag)
return zip(sentence, history)</pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>tagged_sents = brown.tagged_sents(categories=<span class="pysrc-string">'news'</span>)
<span class="pysrc-prompt">>>> </span>size = int(len(tagged_sents) * 0.1)
<span class="pysrc-prompt">>>> </span>train_sents, test_sents = tagged_sents[size:], tagged_sents[:size]
<span class="pysrc-prompt">>>> </span>tagger = ConsecutivePosTagger(train_sents)
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(tagger.evaluate(test_sents))
<span class="pysrc-output">0.79796012981</span></pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="caption"><p class="caption"><a class="reference external" href="http://www.nltk.org/book/pylisting/code_consecutive_pos_tagger.py" type="text/x-python"><span class="caption-label">Example 1.7 (code_consecutive_pos_tagger.py)</span></a>: <span class="caption-label">Figure 1.7</span>: Part of Speech Tagging with a Consecutive Classifier</p></td></tr>
</tbody></table></div>
</div>
<div class="section" id="other-methods-for-sequence-classification">
<h2>1.7 Other Methods for Sequence Classification</h2>
<p>One shortcoming of this approach is that we commit to every decision
that we make. For example, if we decide to label a word as a noun,
but later find evidence that it should have been a verb, there's no
way to go back and fix our mistake. One solution to this problem is
to adopt a transformational strategy instead. Transformational joint
classifiers work by creating an initial assignment of labels for the
inputs, and then iteratively refining that assignment in an attempt to
repair inconsistencies between related inputs. The Brill tagger,
described in <a class="reference external" href="http://www.nltk.org/book/ch05.html#sec-transformation-based-tagging">(1)</a>, is a good example of this strategy.</p>
<p>Another solution is to assign scores to all of the possible
sequences of part-of-speech tags, and to choose the sequence
whose overall score is highest. This is the approach taken by
<a name="hidden_markov_models_index_term"><span class="termdef">Hidden Markov Models</span>.
Hidden Markov Models are similar to consecutive classifiers in
that they look at both the inputs and the history of predicted
tags. However, rather than simply finding the single best tag
for a given word, they generate a probability distribution over
tags. These probabilities are then combined to calculate
probability scores for tag sequences, and the tag sequence with
the highest probability is chosen. Unfortunately, the number of
possible tag sequences is quite large. Given a tag set with 30
tags, there are about 600 trillion (30<sup>10</sup>) ways to label
a 10-word sentence. In order to avoid considering all these possible
sequences separately, Hidden Markov Models require that the
feature extractor only look at the most recent tag (or the most
recent <span class="math">n</span> tags, where <span class="math">n</span> is fairly small). Given that
restriction, it is possible to use dynamic programming (</a><a class="reference external" href="http://www.nltk.org/book/ch04.html#sec-algorithm-design">4.7</a>)
to efficiently find the most likely tag sequence. In particular,
for each consecutive word index <span class="math">i</span>,
a score is computed for each possible current and previous tag.
This same basic approach is taken by
two more advanced models, called <a name="maximum_entropy_markov_models_index_term"><span class="termdef">Maximum Entropy Markov Models</span> and
</a><a name="linear_chain_conditional_random_field_models_index_term"><span class="termdef">Linear-Chain Conditional Random Field Models</span>;
but different algorithms are used to find scores for tag sequences.</a></p><a name="linear_chain_conditional_random_field_models_index_term">
</a></div><a name="linear_chain_conditional_random_field_models_index_term">
</a></div><a name="linear_chain_conditional_random_field_models_index_term">
</a><div class="section" id="further-examples-of-supervised-classification"><a name="linear_chain_conditional_random_field_models_index_term">
<span id="sec-further-examples-of-supervised-classification"></span><h1>2 Further Examples of Supervised Classification</h1>
</a><div class="section" id="sentence-segmentation"><a name="linear_chain_conditional_random_field_models_index_term">
<h2>2.1 Sentence Segmentation</h2>
<p>Sentence segmentation can be viewed as a classification task for
punctuation: whenever we encounter a symbol that could possibly end a
sentence, such as a period or a question mark, we have to decide
whether it terminates the preceding sentence.</p>
<p>The first step is to obtain some data that has already been segmented
into sentences and convert it into a form that is suitable for
extracting features:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>sents = nltk.corpus.treebank_raw.sents()
<span class="pysrc-prompt">>>> </span>tokens = []
<span class="pysrc-prompt">>>> </span>boundaries = set()
<span class="pysrc-prompt">>>> </span>offset = 0
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">for</span> sent <span class="pysrc-keyword">in</span> sents:
<span class="pysrc-more">... </span> tokens.extend(sent)
<span class="pysrc-more">... </span> offset += len(sent)
<span class="pysrc-more">... </span> boundaries.add(offset-1)</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Here, <tt class="doctest"><span class="pre">tokens</span></tt> is a merged list of tokens from the individual
sentences, and <tt class="doctest"><span class="pre">boundaries</span></tt> is a set containing the indexes of all
sentence-boundary tokens. Next, we need to specify the features of
the data that will be used in order to decide whether punctuation
indicates a sentence-boundary:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">def</span> <span class="pysrc-defname">punct_features</span>(tokens, i):
<span class="pysrc-more">... </span> return {<span class="pysrc-string">'next-word-capitalized'</span>: tokens[i+1][0].isupper(),
<span class="pysrc-more">... </span> <span class="pysrc-string">'prev-word'</span>: tokens[i-1].lower(),
<span class="pysrc-more">... </span> <span class="pysrc-string">'punct'</span>: tokens[i],
<span class="pysrc-more">... </span> <span class="pysrc-string">'prev-word-is-one-char'</span>: len(tokens[i-1]) == 1}</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Based on this feature extractor, we can create a list of labeled
featuresets by selecting all the punctuation tokens, and tagging
whether they are boundary tokens or not:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>featuresets = [(punct_features(tokens, i), (i <span class="pysrc-keyword">in</span> boundaries))
<span class="pysrc-more">... </span> <span class="pysrc-keyword">for</span> i <span class="pysrc-keyword">in</span> range(1, len(tokens)-1)
<span class="pysrc-more">... </span> <span class="pysrc-keyword">if</span> tokens[i] <span class="pysrc-keyword">in</span> <span class="pysrc-string">'.?!'</span>]</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Using these featuresets, we can train and evaluate a
punctuation classifier:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>size = int(len(featuresets) * 0.1)
<span class="pysrc-prompt">>>> </span>train_set, test_set = featuresets[size:], featuresets[:size]
<span class="pysrc-prompt">>>> </span>classifier = nltk.NaiveBayesClassifier.train(train_set)
<span class="pysrc-prompt">>>> </span>nltk.classify.accuracy(classifier, test_set)
<span class="pysrc-output">0.936026936026936</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
</a><p><a name="linear_chain_conditional_random_field_models_index_term">To use this classifier to perform sentence segmentation, we simply
check each punctuation mark to see whether it's labeled as a boundary;
and divide the list of words at the boundary marks. The listing
in </a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-classification-based-segmenter">2.1</a> shows how this can be done.</p>
<span class="target" id="code-classification-based-segmenter"></span><div class="pylisting">
<p></p><table border="0" cellpadding="0" cellspacing="0" class="pylisting" width="95%">
<tbody><tr><td class="codeblock">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_codeblock_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-keyword">def</span> <span class="pysrc-defname">segment_sentences</span>(words):
start = 0
sents = []
<span class="pysrc-keyword">for</span> i, word <span class="pysrc-keyword">in</span> enumerate(words):
<span class="pysrc-keyword">if</span> word <span class="pysrc-keyword">in</span> <span class="pysrc-string">'.?!'</span> <span class="pysrc-keyword">and</span> classifier.classify(punct_features(words, i)) == True:
sents.append(words[start:i+1])
start = i+1
<span class="pysrc-keyword">if</span> start < len(words):
sents.append(words[start:])
return sents</pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="caption"><p class="caption"><a class="reference external" href="http://www.nltk.org/book/pylisting/code_classification_based_segmenter.py" type="text/x-python"><span class="caption-label">Example 2.1 (code_classification_based_segmenter.py)</span></a>: <span class="caption-label">Figure 2.1</span>: Classification Based Sentence Segmenter</p></td></tr>
</tbody></table></div>
</div>
<div class="section" id="identifying-dialogue-act-types">
<h2>2.2 Identifying Dialogue Act Types</h2>
<p>When processing dialogue, it can be useful to think of
utterances as a type of <em>action</em> performed by the speaker. This
interpretation is most straightforward for performative statements
such as "I forgive you" or "I bet you can't climb that hill." But
greetings, questions, answers, assertions, and clarifications can all
be thought of as types of speech-based actions. Recognizing the
<a name="dialogue_acts_index_term"><span class="termdef">dialogue acts</span> underlying the utterances in a dialogue can be an
important first step in understanding the conversation.</a></p><a name="dialogue_acts_index_term">
</a><p><a name="dialogue_acts_index_term">The NPS Chat Corpus, which was demonstrated in
</a><a class="reference external" href="http://www.nltk.org/book/ch02.html#sec-extracting-text-from-corpora">1</a>, consists of over 10,000 posts from
instant messaging sessions. These posts have all been labeled with
one of 15 dialogue act types, such as "Statement," "Emotion,"
"ynQuestion", and "Continuer." We can therefore use this data to
build a classifier that can identify the dialogue act types for new
instant messaging posts. The first step is to extract the basic
messaging data. We will call <tt class="doctest"><span class="pre">xml_posts()</span></tt> to get a data structure
representing the XML annotation for each post:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>posts = nltk.corpus.nps_chat.xml_posts()[:10000]</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Next, we'll define a simple feature extractor that checks what words
the post contains:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">def</span> <span class="pysrc-defname">dialogue_act_features</span>(post):
<span class="pysrc-more">... </span> features = {}
<span class="pysrc-more">... </span> <span class="pysrc-keyword">for</span> word <span class="pysrc-keyword">in</span> nltk.word_tokenize(post):
<span class="pysrc-more">... </span> features[<span class="pysrc-string">'contains(%s)'</span> % word.lower()] = True
<span class="pysrc-more">... </span> return features</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Finally, we construct the training and testing data by applying the
feature extractor to each post (using <tt class="doctest"><span class="pre">post.get(<span class="pysrc-string">'class'</span>)</span></tt> to get
a post's dialogue act type), and create a new classifier:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>featuresets = [(dialogue_act_features(post.text), post.get(<span class="pysrc-string">'class'</span>))
<span class="pysrc-more">... </span> <span class="pysrc-keyword">for</span> post <span class="pysrc-keyword">in</span> posts]
<span class="pysrc-prompt">>>> </span>size = int(len(featuresets) * 0.1)
<span class="pysrc-prompt">>>> </span>train_set, test_set = featuresets[size:], featuresets[:size]
<span class="pysrc-prompt">>>> </span>classifier = nltk.NaiveBayesClassifier.train(train_set)
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(nltk.classify.accuracy(classifier, test_set))
<span class="pysrc-output">0.67</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<!-- XXX delete note -->
<!-- *We had planned to extend this example by showing how a sequence
classifier can be used to take advantage of the fact that
some sequences (eg ynquestion->yanswer) are more likely than
others.* -->
</div>
<div class="section" id="recognizing-textual-entailment">
<h2>2.3 Recognizing Textual Entailment</h2>
<p>Recognizing textual entailment (RTE) is the task of determining
whether a given piece of text <em>T</em> entails another text called the
"hypothesis" (as already discussed in <a class="reference external" href="http://www.nltk.org/book/ch01.html#sec-automatic-natural-language-understanding">5</a>).
To date, there have been four RTE Challenges, where
shared development and test data is made available to competing teams.
Here are a couple of examples of text/hypothesis pairs from the
Challenge 3 development dataset. The label <em>True</em> indicates that the
entailment holds, and <em>False</em>, that it fails to hold.</p>
<blockquote>
<p>Challenge 3, Pair 34 (True)</p>
<blockquote>
<p><strong>T</strong>: Parviz Davudi was representing Iran at a meeting of the Shanghai
Co-operation Organisation (SCO), the fledgling association that
binds Russia, China and four former Soviet republics of central
Asia together to fight terrorism.</p>
<p><strong>H</strong>: China is a member of SCO.</p>
</blockquote>
<p>Challenge 3, Pair 81 (False)</p>
<blockquote>
<p><strong>T</strong>: According to NC Articles of Organization, the members of LLC
company are H. Nelson Beavers, III, H. Chester Beavers and Jennie
Beavers Stewart.</p>
<p><strong>H</strong>: Jennie Beavers Stewart is a share-holder of Carolina Analytical
Laboratory.</p>
</blockquote>
</blockquote>
<p>It should be emphasized that the relationship between text and
hypothesis is not intended to be logical entailment, but rather
whether a human would conclude that the text provides reasonable
evidence for taking the hypothesis to be true.</p>
<p>We can treat RTE as a classification task, in which we try to
predict the <em>True</em>/<em>False</em> label for each pair. Although it seems
likely that successful approaches to this task will involve a
combination of parsing, semantics and real world
knowledge, many early attempts at RTE achieved reasonably good results
with shallow analysis, based on similarity between the text and
hypothesis at the word level. In the ideal case, we would expect that if
there is an entailment, then all the information expressed by the hypothesis
should also be present in the text. Conversely, if there is information
found in the hypothesis that is absent from the text, then there
will be no entailment.</p>
<p>In our RTE feature detector (<a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-rte-features">2.2</a>), we let words
(i.e., word types) serve as proxies for information, and
our features count the degree of word overlap, and the degree to which
there are words in the hypothesis but not in the text (captured by the
method <tt class="doctest"><span class="pre">hyp_extra()</span></tt>). Not all words are equally important —
Named Entity mentions such as the names of people, organizations and
places are likely to be more significant, which motivates us to
extract distinct information for <tt class="doctest"><span class="pre">word</span></tt>s and <tt class="doctest"><span class="pre">ne</span></tt>s (Named
Entities). In addition, some high frequency function words are
filtered out as "stopwords".</p>
<!-- XXX following pylisting is not referenced from the text -->
<table class="docutils citation" frame="void" id="xx" rules="none">
<colgroup><col class="label"><col></colgroup>
<tbody valign="top">
<tr><td class="label">[xx]</td><td>give some intro to RTEFeatureExtractor??</td></tr>
</tbody>
</table>
<span class="target" id="code-rte-features"></span><div class="pylisting">
<p></p><table border="0" cellpadding="0" cellspacing="0" class="pylisting" width="95%">
<tbody><tr><td class="codeblock">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_codeblock_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-keyword">def</span> <span class="pysrc-defname">rte_features</span>(rtepair):
extractor = nltk.RTEFeatureExtractor(rtepair)
features = {}
features[<span class="pysrc-string">'word_overlap'</span>] = len(extractor.overlap(<span class="pysrc-string">'word'</span>))
features[<span class="pysrc-string">'word_hyp_extra'</span>] = len(extractor.hyp_extra(<span class="pysrc-string">'word'</span>))
features[<span class="pysrc-string">'ne_overlap'</span>] = len(extractor.overlap(<span class="pysrc-string">'ne'</span>))
features[<span class="pysrc-string">'ne_hyp_extra'</span>] = len(extractor.hyp_extra(<span class="pysrc-string">'ne'</span>))
return features</pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="caption"><p class="caption"><a class="reference external" href="http://www.nltk.org/book/pylisting/code_rte_features.py" type="text/x-python"><span class="caption-label">Example 2.2 (code_rte_features.py)</span></a>: <span class="caption-label">Figure 2.2</span>: "Recognizing Text Entailment" Feature Extractor. The
<tt class="doctest"><span class="pre">RTEFeatureExtractor</span></tt> class builds a bag
of words for both the text and the hypothesis after throwing
away some stopwords, then calculates overlap and difference.</p></td></tr>
</tbody></table></div>
<p>To illustrate the content of these features, we examine some
attributes of the text/hypothesis Pair 34 shown earlier:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>rtepair = nltk.corpus.rte.pairs([<span class="pysrc-string">'rte3_dev.xml'</span>])[33]
<span class="pysrc-prompt">>>> </span>extractor = nltk.RTEFeatureExtractor(rtepair)
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(extractor.text_words)
<span class="pysrc-output">{'Russia', 'Organisation', 'Shanghai', 'Asia', 'four', 'at',</span>
<span class="pysrc-output">'operation', 'SCO', ...}</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(extractor.hyp_words)
<span class="pysrc-output">{'member', 'SCO', 'China'}</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(extractor.overlap(<span class="pysrc-string">'word'</span>))
<span class="pysrc-output">set()</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(extractor.overlap(<span class="pysrc-string">'ne'</span>))
<span class="pysrc-output">{'SCO', 'China'}</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(extractor.hyp_extra(<span class="pysrc-string">'word'</span>))
<span class="pysrc-output">{'member'}</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>These features indicate that all important words in the hypothesis are
contained in the text, and thus there is some evidence for labeling this
as <em>True</em>.</p>
<p>The module <tt class="doctest"><span class="pre">nltk.classify.rte_classify</span></tt> reaches just over 58%
accuracy on the combined RTE test data using methods like these. Although
this figure is not very impressive, it requires significant effort, and more
linguistic processing, to achieve much better results.</p>
</div>
<div class="section" id="scaling-up-to-large-datasets">
<h2>2.4 Scaling Up to Large Datasets</h2>
<p>Python provides an excellent environment for performing basic text
processing and feature extraction. However, it is not able to perform
the numerically intensive calculations required by machine learning
methods nearly as quickly as lower-level languages such as C. Thus,
if you attempt to use the pure-Python machine learning implementations
(such as <tt class="doctest"><span class="pre">nltk.NaiveBayesClassifier</span></tt>) on large datasets, you may
find that the learning algorithm takes an unreasonable amount of time
and memory to complete.</p>
<p>If you plan to train classifiers with large amounts of training data
or a large number of features, we recommend that you explore
NLTK's facilities for interfacing with external machine learning
packages. Once these packages have been installed, NLTK can
transparently invoke them (via system calls) to train classifier
models significantly faster than the pure-Python classifier
implementations. See the NLTK webpage for a list of recommended
machine learning packages that are supported by NLTK.</p>
<!-- SB: I think numpy and other numerical libraries do their work in C, and
are probably quite efficient. Not clear about support for sparse arrays. -->
<!-- EL: Yes, but even with numpy etc, python is *slow* for this stuff.
I speak from experience. :) -->
<!-- XXX Note that the additive nature of a lot of training tasks mean
that parallelization will work fine. If those can be done using
MapReduce we'll be able to use NLTK for some non-toy problems here. -->
</div>
</div>
<div class="section" id="evaluation">
<span id="sec-evaluation"></span><h1>3 Evaluation</h1>
<p>In order to decide whether a classification model is accurately
capturing a pattern, we must evaluate that model. The result of this
evaluation is important for deciding how trustworthy the model is, and
for what purposes we can use it. Evaluation can also be an effective tool
for guiding us in making future improvements to the model.</p>
<div class="section" id="the-test-set">
<h2>3.1 The Test Set</h2>
<p>Most evaluation techniques calculate a score for a model by comparing
the labels that it generates for the inputs in a <a name="test_set_index_term_2"><span class="termdef">test set</span>
(or </a><a name="evaluation_set_index_term"><span class="termdef">evaluation set</span>)
with the correct labels for those inputs. This test set
typically has the same format as the training set. However, it is
very important that the test set be distinct from the training
corpus: if we simply re-used the training set as the test
set, then a model that simply memorized its input, without learning
how to generalize to new examples, would receive misleadingly high
scores.</a></p><a name="evaluation_set_index_term">
<p>When building the test set, there is often a trade-off between
the amount of data available for testing and the amount available
for training. For classification tasks that have a small
number of well-balanced labels and a diverse test set, a
meaningful evaluation can be performed with as few as 100 evaluation
instances. But if a classification task has a large number of labels,
or includes very infrequent labels, then the size of the test
set should be chosen to ensure that the least frequent label occurs at
least 50 times. Additionally, if the test set contains many
closely related instances — such as instances drawn from a single
document — then the size of the test set should be increased to
ensure that this lack of diversity does not skew the evaluation
results. When large amounts of annotated data are available, it is
common to err on the side of safety by using 10% of the overall data
for evaluation.</p>
<p>Another consideration when choosing the test set is the degree
of similarity between instances in the test set and those in the
development set. The more similar these two datasets are, the less
confident we can be that evaluation results will generalize to other
datasets. For example, consider the part-of-speech tagging task. At
one extreme, we could create the training set and test set by
randomly assigning sentences from a data source that reflects a single
genre (news):</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">import</span> random
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">from</span> nltk.corpus <span class="pysrc-keyword">import</span> brown
<span class="pysrc-prompt">>>> </span>tagged_sents = list(brown.tagged_sents(categories=<span class="pysrc-string">'news'</span>))
<span class="pysrc-prompt">>>> </span>random.shuffle(tagged_sents)
<span class="pysrc-prompt">>>> </span>size = int(len(tagged_sents) * 0.1)
<span class="pysrc-prompt">>>> </span>train_set, test_set = tagged_sents[size:], tagged_sents[:size]</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>In this case, our test set will be <em>very</em> similar to our training
set. The training set and test set are taken from the same
genre, and so we cannot be confident that evaluation results would
generalize to other genres. What's worse, because of the call to
<tt class="doctest"><span class="pre">random.shuffle()</span></tt>, the test set contains sentences that are
taken from the same documents that were used for training. If there
is any consistent pattern within a document — say, if a given word
appears with a particular part-of-speech tag especially frequently — then
that difference will be reflected in both the development set and the
test set. A somewhat better approach is to ensure that
the training set and test set are taken from different documents:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>file_ids = brown.fileids(categories=<span class="pysrc-string">'news'</span>)
<span class="pysrc-prompt">>>> </span>size = int(len(file_ids) * 0.1)
<span class="pysrc-prompt">>>> </span>train_set = brown.tagged_sents(file_ids[size:])
<span class="pysrc-prompt">>>> </span>test_set = brown.tagged_sents(file_ids[:size])</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>If we want to perform a more stringent evaluation, we can draw the
test set from documents that are less closely related to those
in the training set:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>train_set = brown.tagged_sents(categories=<span class="pysrc-string">'news'</span>)
<span class="pysrc-prompt">>>> </span>test_set = brown.tagged_sents(categories=<span class="pysrc-string">'fiction'</span>)</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>If we build a classifier that performs well on this test set,
then we can be confident that it has the power to generalize well
beyond the data that it was trained on.</p>
</a></div><a name="evaluation_set_index_term">
</a><div class="section" id="accuracy"><a name="evaluation_set_index_term">
<h2>3.2 Accuracy</h2>
</a><p><a name="evaluation_set_index_term">The simplest metric that can be used to evaluate a classifier,
</a><a name="accuracy_index_term"><span class="termdef">accuracy</span>, measures the percentage of inputs in the test
set that the classifier correctly labeled. For example, a name gender
classifier that predicts the correct name 60 times in a test
set containing 80 names would have an accuracy of 60/80 = 75%. The
function <tt class="doctest"><span class="pre">nltk.classify.accuracy()</span></tt> will calculate the
accuracy of a classifier model on a given test set:</a></p><a name="accuracy_index_term">
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>classifier = nltk.NaiveBayesClassifier.train(train_set)
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(<span class="pysrc-string">'Accuracy: %4.2f'</span> % nltk.classify.accuracy(classifier, test_set))
<span class="pysrc-output">0.75</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
</a><p><a name="accuracy_index_term">When interpreting the accuracy score of a classifier, it is important
to take into consideration the frequencies of the individual class
labels in the test set. For example, consider a classifier that
determines the correct word sense for each occurrence of the word
<span class="example">bank</span>. If we evaluate this classifier on financial newswire text,
then we may find that the <tt class="doctest"><span class="pre">financial-institution</span></tt> sense appears 19
times out of 20. In that case, an accuracy of 95% would hardly be
impressive, since we could achieve that accuracy with a model that
always returns the <tt class="doctest"><span class="pre">financial-institution</span></tt> sense. However, if we
instead evaluate the classifier on a more balanced corpus, where the
most frequent word sense has a frequency of 40%, then a 95% accuracy
score would be a much more positive result. (A similar issue arises
when measuring inter-annotator agreement in
</a><a class="reference external" href="http://www.nltk.org/book/ch11.html#sec-life-cycle-of-a-corpus">2</a>.)</p>
</div>
<div class="section" id="precision-and-recall">
<h2>3.3 Precision and Recall</h2>
<p>Another instance where accuracy scores can be misleading is in
"search" tasks, such as information retrieval, where we are attempting
to find documents that are relevant to a particular task. Since the
number of irrelevant documents far outweighs the number of relevant
documents, the accuracy score for a model that labels every document
as irrelevant would be very close to 100%.</p>
<span class="target" id="fig-precision-recall"></span><div class="figure" id="fig-precision-recall">
<img alt="../images/precision-recall.png" src="./6. Learning to Classify Text_files/precision-recall.png" style="width: 523.0px; height: 283.5px;">
<p class="caption"><span class="caption-label">Figure 3.1</span>: True and False Positives and Negatives</p>
</div>
<p>It is therefore conventional to employ a different set of measures for
search tasks, based on the number of items in each of the four
categories shown in <a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-precision-recall">3.1</a>:</p>
<ul class="simple">
<li><a name="true_positives_index_term"><span class="termdef">True positives</span> are relevant items that we correctly identified
as relevant.</a></li><a name="true_positives_index_term">
</a><li><a name="true_positives_index_term"></a><a name="true_negatives_index_term"><span class="termdef">True negatives</span> are irrelevant items that we correctly identified
as irrelevant.</a></li><a name="true_negatives_index_term">
</a><li><a name="true_negatives_index_term"></a><a name="false_positives_index_term"><span class="termdef">False positives</span> (or </a><a name="type_i_errors_index_term"><span class="termdef">Type I errors</span>) are irrelevant items
that we incorrectly identified as relevant.</a></li><a name="type_i_errors_index_term">
</a><li><a name="type_i_errors_index_term"></a><a name="false_negatives_index_term"><span class="termdef">False negatives</span> (or </a><a name="type_ii_errors_index_term"><span class="termdef">Type II errors</span>) are relevant items
that we incorrectly identified as irrelevant.</a></li><a name="type_ii_errors_index_term">
</a></ul><a name="type_ii_errors_index_term">
<p>Given these four numbers, we can define the following metrics:</p>
</a><ul class="simple"><a name="type_ii_errors_index_term">
</a><li><a name="type_ii_errors_index_term"></a><a name="precision_index_term"><span class="termdef">Precision</span>, which indicates how many of the items that we
identified were relevant, is <span class="math">TP/(TP+FP)</span>.</a></li><a name="precision_index_term">
</a><li><a name="precision_index_term"></a><a name="recall_index_term"><span class="termdef">Recall</span>, which indicates how many of the relevant items that we
identified, is <span class="math">TP/(TP+FN)</span>.</a></li><a name="recall_index_term">
</a><li><a name="recall_index_term">The </a><a name="f_measure_index_term"><span class="termdef">F-Measure</span> (or </a><a name="f_score_index_term"><span class="termdef">F-Score</span>), which combines the precision
and recall to give a single score, is defined to be the harmonic
mean of the precision and recall:
(2 × <em>Precision</em> × <em>Recall</em>) / (<em>Precision</em> + <em>Recall</em>).</a></li><a name="f_score_index_term">
</a></ul><a name="f_score_index_term">
<!-- alternative def for f-score: 2/(1/Precision+1/Recall) -->
</a></div><a name="f_score_index_term">
</a><div class="section" id="confusion-matrices"><a name="f_score_index_term">
<h2>3.4 Confusion Matrices</h2>
<!-- Repeat some code from chapter 5, which recreates the tagger t2.
This tagger is used to illustrate the confusion matrix:
>>> from nltk.corpus import brown
>>> brown_tagged_sents = brown.tagged_sents(categories='news')
>>> size = int(len(brown_tagged_sents) * 0.9)
>>> train_sents = brown_tagged_sents[:size]
>>> test_sents = brown_tagged_sents[size:]
>>> t0 = nltk.DefaultTagger('NN')
>>> t1 = nltk.UnigramTagger(train_sents, backoff=t0)
>>> t2 = nltk.BigramTagger(train_sents, backoff=t1) -->
</a><p><a name="f_score_index_term">When performing classification tasks with three or more labels, it can
be informative to subdivide the errors made by the model based on
which types of mistake it made. A </a><a name="confusion_matrix_index_term"><span class="termdef">confusion matrix</span> is a table
where each cell [<span class="math">i</span>,<span class="math">j</span>] indicates how often label <span class="math">j</span> was
predicted when the correct label was <span class="math">i</span>. Thus, the diagonal
entries (i.e., cells </a><a href="http://www.nltk.org/book/ch06.html#id17"><span class="problematic" id="id18">|ii|</span></a>) indicate labels that were
correctly predicted, and the off-diagonal entries indicate errors. In
the following example, we generate a confusion matrix for the bigram
tagger developed in <a class="reference external" href="http://www.nltk.org/book/ch05.html#sec-automatic-tagging">4</a>:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">def</span> <span class="pysrc-defname">tag_list</span>(tagged_sents):
<span class="pysrc-more">... </span> return [tag <span class="pysrc-keyword">for</span> sent <span class="pysrc-keyword">in</span> tagged_sents <span class="pysrc-keyword">for</span> (word, tag) <span class="pysrc-keyword">in</span> sent]
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">def</span> <span class="pysrc-defname">apply_tagger</span>(tagger, corpus):
<span class="pysrc-more">... </span> return [tagger.tag(nltk.tag.untag(sent)) <span class="pysrc-keyword">for</span> sent <span class="pysrc-keyword">in</span> corpus]
<span class="pysrc-prompt">>>> </span>gold = tag_list(brown.tagged_sents(categories=<span class="pysrc-string">'editorial'</span>))
<span class="pysrc-prompt">>>> </span>test = tag_list(apply_tagger(t2, brown.tagged_sents(categories=<span class="pysrc-string">'editorial'</span>)))
<span class="pysrc-prompt">>>> </span>cm = nltk.ConfusionMatrix(gold, test)
<span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(cm.pp(sort_by_count=True, show_percents=True, truncate=9))
<span class="pysrc-output"> | N |</span>
<span class="pysrc-output"> | N I A J N V N |</span>
<span class="pysrc-output"> | N N T J . S , B P |</span>
<span class="pysrc-output">----+----------------------------------------------------------------+</span>
<span class="pysrc-output"> NN | <11.8%> 0.0% . 0.2% . 0.0% . 0.3% 0.0% |</span>
<span class="pysrc-output"> IN | 0.0% <9.0%> . . . 0.0% . . . |</span>
<span class="pysrc-output"> AT | . . <8.6%> . . . . . . |</span>
<span class="pysrc-output"> JJ | 1.7% . . <3.9%> . . . 0.0% 0.0% |</span>
<span class="pysrc-output"> . | . . . . <4.8%> . . . . |</span>
<span class="pysrc-output">NNS | 1.5% . . . . <3.2%> . . 0.0% |</span>
<span class="pysrc-output"> , | . . . . . . <4.4%> . . |</span>
<span class="pysrc-output"> VB | 0.9% . . 0.0% . . . <2.4%> . |</span>
<span class="pysrc-output"> NP | 1.0% . . 0.0% . . . . <1.8%>|</span>
<span class="pysrc-output">----+----------------------------------------------------------------+</span>
<span class="pysrc-output">(row = reference; col = test)</span>
<span class="pysrc-output"></span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>The confusion matrix indicates that common errors include a
substitution of <tt class="doctest"><span class="pre">NN</span></tt> for <tt class="doctest"><span class="pre">JJ</span></tt> (for 1.6% of words), and of <tt class="doctest"><span class="pre">NN</span></tt> for <tt class="doctest"><span class="pre">NNS</span></tt> (for
1.5% of words). Note that periods (<tt class="doctest"><span class="pre">.</span></tt>) indicate cells
whose value is 0, and that the diagonal entries — which correspond to
correct classifications — are marked with angle brackets.
.. XXX explain use of "reference" in the legend above.</p>
</div>
<div class="section" id="cross-validation">
<h2>3.5 Cross-Validation</h2>
<p>In order to evaluate our models, we must reserve a portion of the
annotated data for the test set. As we already mentioned,
if the test set is too small, then
our evaluation may not be accurate. However, making the test set
larger usually means making the training set smaller, which can have a
significant impact on performance if a limited amount of annotated
data is available.</p>
<p>One solution to this problem is to perform multiple evaluations on
different test sets, then to combine the scores from those
evaluations, a technique known as <a name="cross_validation_index_term"><span class="termdef">cross-validation</span>. In
particular, we subdivide the original corpus into <span class="math">N</span>
subsets called </a><a name="folds_index_term"><span class="termdef">folds</span>. For each of these folds, we train a model using all
of the data <em>except</em> the data in that fold, and then test that
model on the fold. Even though the individual folds might
be too small to give accurate evaluation scores on their own, the
combined evaluation score is based on a large amount of data, and is
therefore quite reliable.</a></p><a name="folds_index_term">
<p>A second, and equally important, advantage of using cross-validation
is that it allows us to examine how widely the performance varies
across different training sets. If we get very similar scores for all
<span class="math">N</span> training sets, then we can be fairly confident that the
score is accurate. On the other hand, if scores vary widely across
the <span class="math">N</span> training sets, then we should probably be skeptical
about the accuracy of the evaluation score.</p>
<!-- XXX give a code snippet for dividing corpus up for cross-validation -->
<!-- mention statistical significance tests explicitly here? -->
</a></div><a name="folds_index_term">
</a></div><a name="folds_index_term">
</a><div class="section" id="decision-trees"><a name="folds_index_term">
<span id="sec-decision-trees"></span><h1>4 Decision Trees</h1>
<p>In the next three sections, we'll take a closer look at three machine
learning methods that can be used to automatically build
classification models: decision trees, naive Bayes classifiers, and
Maximum Entropy classifiers. As we've seen, it's possible to treat these
learning methods as black boxes, simply training models and using them
for prediction without understanding how they work. But there's a lot
to be learned from taking a closer look at how these learning methods
select models based on the data in a training set. An
understanding of these methods can help guide our selection of
appropriate features, and especially our decisions about how those
features should be encoded. And an understanding of the generated
models can allow us to extract information about which features
are most informative, and how those features relate to one another.</p>
<!-- Note that they haven't necessarily seen syntax trees before this, so
it may seem odd to them (or at least not obvious) that these "trees"
are upside down. -->
<!-- XXX some people will know the concept of a "dichotomous key".
("tree-structured flowchart" assumes domain knowledge so doesn't
communicate as widely) -->
</a><p><a name="folds_index_term">A </a><a name="decision_tree_index_term"><span class="termdef">decision tree</span> is a simple flowchart that selects
labels for input values. This flowchart consists of </a><a name="decision_nodes_index_term"><span class="termdef">decision
nodes</span>, which check feature values, and </a><a name="leaf_nodes_index_term"><span class="termdef">leaf nodes</span>, which
assign labels. To choose the label for an input value, we begin at
the flowchart's initial decision node, known as its </a><a name="root_node_index_term"><span class="termdef">root node</span>.
This node contains a condition that checks one of the input value's
features, and selects a branch based on that feature's value.
Following the branch that describes our input value, we arrive at a
new decision node, with a new condition on the input value's features.
We continue following the branch selected by each node's condition,
until we arrive at a leaf node which provides a label for the input
value. </a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-decision-tree">4.1</a> shows an example decision tree model for
the name gender task.</p>
<span class="target" id="fig-decision-tree"></span><div class="figure" id="fig-decision-tree">
<img alt="../images/decision-tree.png" src="./6. Learning to Classify Text_files/decision-tree.png" style="width: 197.5px; height: 93.0px;">
<p class="caption"><span class="caption-label">Figure 4.1</span>: Decision Tree model for the name gender task. Note that tree
diagrams are conventionally drawn "upside down," with the root at the
top, and the leaves at the bottom.</p>
</div>
<!-- XXX show: train decision tree, then print it as pseudocode & as more
compact tree. -->
<!-- XXX seems odd to talk about a decision tree "modeling a training set" below. -->
<p>Once we have a decision tree, it is straightforward to
use it to assign labels to new input values. What's less straightforward
is how we can build a decision tree that models a given
training set. But before we look at the learning algorithm for
building decision trees, we'll consider a simpler task: picking the
best "decision stump" for a corpus. A <a name="decision_stump_index_term"><span class="termdef">decision stump</span> is a
decision tree with a single node that decides how to classify inputs
based on a single feature. It contains one leaf for each possible
feature value, specifying the class label that should be assigned to
inputs whose features have that value. In order to build a decision
stump, we must first decide which feature should be used. The
simplest method is to just build a decision stump for each possible
feature, and see which one achieves the highest accuracy on the
training data, although there are other alternatives that we will discuss below.
Once we've picked a feature, we can build the decision stump by assigning a
label to each leaf based on the most frequent label for the selected
examples in the training set (i.e., the examples where the selected
feature has that value).</a></p><a name="decision_stump_index_term">
<!-- XX show building a decision stump -->
<!-- XX show refining a decision stump's leaf -->
</a><p><a name="decision_stump_index_term">Given the algorithm for choosing decision stumps, the algorithm for
growing larger decision trees is straightforward. We
begin by selecting the overall best decision stump for the
classification task. We
then check the accuracy of each of the leaves on the training set.
Leaves that do not achieve sufficient accuracy are then
replaced by new decision stumps, trained on the subset of the training
corpus that is selected by the path to the leaf. For example, we
could grow the decision tree in </a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-decision-tree">4.1</a> by replacing the
leftmost leaf with a new decision stump, trained on the subset of the
training set names that do not start with a "k" or end with a vowel
or an "l."</p>
<div class="section" id="entropy-and-information-gain">
<h2>4.1 Entropy and Information Gain</h2>
<p>As was mentioned before, there are several methods for identifying
the most informative feature for a decision stump. One
popular alternative, called <a name="information_gain_index_term"><span class="termdef">information gain</span>, measures how
much more organized the input values become when we divide them up
using a given feature. To measure how disorganized the original set
of input values are, we calculate entropy of their labels, which will
be high if the input values have highly varied labels, and low if many
input values all have the same label. In particular, entropy is
defined as the sum of the probability of each label times the log
probability of that same label:</a></p><a name="information_gain_index_term">
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(1)</td><td width="15"></td><td><span class="math">H</span> = −Σ<sub>l |in| labels</sub><span class="math">P(l)</span> × <span class="math">log</span><sub>2</sub><span class="math">P(l)</span>.</td></tr></tbody></table></p>
<span class="target" id="fig-entropy"></span><div class="figure" id="fig-entropy">
<img alt="../images/Binary_entropy_plot.png" src="./6. Learning to Classify Text_files/Binary_entropy_plot.png" style="width: 85.0px; height: 85.5px;">
<p class="caption"><span class="caption-label">Figure 4.2</span>: The entropy of labels in the name gender prediction task, as a
function of the percentage of names in a given set that are male.</p>
</div>
</a><p><a name="information_gain_index_term">For example, </a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-entropy">4.2</a> shows how the entropy of labels in
the name gender prediction task depends on the ratio of male to female
names. Note that if most input values have the same label (e.g., if
P(male) is near 0 or near 1), then entropy is low. In particular,
labels that have low frequency do not contribute much to the entropy
(since <span class="math">P(l)</span> is small), and labels with high frequency also do
not contribute much to the entropy (since <span class="math">log</span><sub>2</sub><span class="math">P(l)</span> is small). On the other hand, if the input values have
a wide variety of labels, then there are many labels with a "medium"
frequency, where neither <span class="math">P(l)</span> nor <span class="math">log</span><sub>2</sub><span class="math">P(l)</span> is small, so the entropy is high.
<a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-entropy">4.3</a> demonstrates how to calculate the entropy
of a list of labels.</p>
<!-- (skip doctest on the 0-entropy example below because it prints
-0.0, and it's not worth it to explain *why* it does that.) -->
<span class="target" id="code-entropy"></span><div class="pylisting">
<p></p><table border="0" cellpadding="0" cellspacing="0" class="pylisting" width="95%">
<tbody><tr><td class="codeblock">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_codeblock_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-keyword">import</span> math
<span class="pysrc-keyword">def</span> <span class="pysrc-defname">entropy</span>(labels):
freqdist = nltk.FreqDist(labels)
probs = [freqdist.freq(l) <span class="pysrc-keyword">for</span> l <span class="pysrc-keyword">in</span> freqdist]
return -sum(p * math.log(p,2) <span class="pysrc-keyword">for</span> p <span class="pysrc-keyword">in</span> probs)</pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(entropy([<span class="pysrc-string">'male'</span>, <span class="pysrc-string">'male'</span>, <span class="pysrc-string">'male'</span>, <span class="pysrc-string">'male'</span>]))
<span class="pysrc-output">0.0</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(entropy([<span class="pysrc-string">'male'</span>, <span class="pysrc-string">'female'</span>, <span class="pysrc-string">'male'</span>, <span class="pysrc-string">'male'</span>]))
<span class="pysrc-output">0.811...</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(entropy([<span class="pysrc-string">'female'</span>, <span class="pysrc-string">'male'</span>, <span class="pysrc-string">'female'</span>, <span class="pysrc-string">'male'</span>]))
<span class="pysrc-output">1.0</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(entropy([<span class="pysrc-string">'female'</span>, <span class="pysrc-string">'female'</span>, <span class="pysrc-string">'male'</span>, <span class="pysrc-string">'female'</span>]))
<span class="pysrc-output">0.811...</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">print</span>(entropy([<span class="pysrc-string">'female'</span>, <span class="pysrc-string">'female'</span>, <span class="pysrc-string">'female'</span>, <span class="pysrc-string">'female'</span>]))
<span class="pysrc-output">0.0</span></pre>
</td>
</tr></tbody></table></td></tr>
<tr><td class="caption"><p class="caption"><a class="reference external" href="http://www.nltk.org/book/pylisting/code_entropy.py" type="text/x-python"><span class="caption-label">Example 4.3 (code_entropy.py)</span></a>: <span class="caption-label">Figure 4.3</span>: Calculating the Entropy of a List of Labels</p></td></tr>
</tbody></table></div>
<!-- The doctest: +SKIP in the last example is because doctest prints
-0.0 on some systems rather than 0.0, which can be confusing;
but isn't worth explaining here. -->
<p>Once we have calculated the entropy of the original set of input
values' labels, we can determine how much more organized the labels
become once we apply the decision stump. To do so, we calculate the
entropy for each of the decision stump's leaves, and take the average
of those leaf entropy values (weighted by the number of samples in
each leaf). The information gain is then equal to the original
entropy minus this new, reduced entropy. The higher the information
gain, the better job the decision stump does of dividing the input
values into coherent groups, so we can build decision trees by
selecting the decision stumps with the highest information gain.</p>
<p>Another consideration for decision trees is efficiency. The simple
algorithm for selecting decision stumps described above must construct
a candidate decision stump for every possible feature, and this
process must be repeated for every node in the constructed decision
tree. A number of algorithms have been developed to cut down on the
training time by storing and reusing information about previously
evaluated examples.</p>
<!-- <<references>>. -->
<!-- XXX the point about decision trees being easy to interpret
has already been made, so this sounds repetitive.
It would be fine to delete the earlier mention of this point,
since it was not in a section on decision trees. -->
<p>Decision trees have a number of useful qualities. To begin with,
they're simple to understand, and easy to interpret. This is
especially true near the top of the decision tree, where it is usually
possible for the learning algorithm to find very useful features.
Decision trees are especially well suited to cases where many
hierarchical categorical distinctions can be made. For example,
decision trees can be very effective at capturing phylogeny trees.</p>
<p>However, decision trees also have a few disadvantages. One problem is
that, since each branch in the decision tree splits the training data,
the amount of training data available to train nodes lower in the tree
can become quite small. As a result, these lower decision nodes may</p>
<!-- XXX overfitting was already introduced as a :dt: earlier -->
<p><a name="overfit_index_term"><span class="termdef">overfit</span> the training set, learning patterns that reflect
idiosyncrasies of the training set rather than linguistically significant
patterns in
the underlying problem. One solution to this problem is to stop
dividing nodes once the amount of training data becomes too small.
Another solution is to grow a full decision tree, but then to
</a><a name="prune_index_term"><span class="termdef">prune</span> decision nodes that do not improve performance on a
dev-test.</a></p><a name="prune_index_term">
<p>A second problem with decision trees is that they force features to be
checked in a specific order, even when features may act relatively
independently of one another. For example, when classifying documents
into topics (such as sports, automotive, or murder mystery), features
such as <tt class="doctest"><span class="pre">hasword(football)</span></tt> are highly indicative of a specific
label, regardless of what other the feature values are. Since there
is limited space near the top of the decision tree, most of these
features will need to be repeated on many different branches in the
tree. And since the number of branches increases exponentially as we
go down the tree, the amount of repetition can be very large.</p>
<p>A related problem is that decision trees are not good at making use of
features that are weak predictors of the correct label. Since these
features make relatively small incremental improvements, they tend to
occur very low in the decision tree. But by the time the decision
tree learner has descended far enough to use these features, there is
not enough training data left to reliably determine what effect they
should have. If we could instead look at the effect of these features
across the entire training set, then we might be able to make some
conclusions about how they should affect the choice of label.</p>
<p>The fact that decision trees require that features be checked in a
specific order limits their ability to exploit features that are
relatively independent of one another. The naive Bayes classification
method, which we'll discuss next, overcomes this limitation by
allowing all features to act "in parallel."</p>
</a></div><a name="prune_index_term">
</a></div><a name="prune_index_term">
</a><div class="section" id="naive-bayes-classifiers"><a name="prune_index_term">
<h1>5 Naive Bayes Classifiers</h1>
</a><p><a name="prune_index_term">In </a><a name="naive_bayes_index_term"><span class="termdef">naive Bayes</span> classifiers, every feature gets a say in
determining which label should be assigned to a given input value. To
choose a label for an input value, the naive Bayes classifier begins
by calculating the </a><a name="prior_probability_index_term"><span class="termdef">prior probability</span> of each label, which is
determined by checking frequency of each label in the training set.
The contribution from each feature is then combined with this prior
probability, to arrive at a likelihood estimate for each label. The
label whose likelihood estimate is the highest is then assigned to the
input value. </a><a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-naive-bayes-triangle">5.1</a> illustrates this process.</p>
<!-- I go back and forth on whether we should include a figure like this
one. I think it gives a good high-level feeling of what's going
on, but the details don't really line up with the algorithm's
specifics, and it takes a good amount of work to explain the figure. -->
<span class="target" id="fig-naive-bayes-triangle"></span><div class="figure" id="fig-naive-bayes-triangle">
<img alt="../images/naive-bayes-triangle.png" src="./6. Learning to Classify Text_files/naive-bayes-triangle.png" style="width: 370.2px; height: 237.6px;">
<p class="caption"><span class="caption-label">Figure 5.1</span>: An abstract illustration of the procedure used by the naive Bayes
classifier to choose the topic for a document. In the training
corpus, most documents are automotive, so the classifier starts out
at a point closer to the "automotive" label. But it then
considers the effect of each feature. In this example, the input
document contains the word "dark," which is a weak indicator for
murder mysteries, but it also contains the word "football," which
is a strong indicator for sports documents. After every feature
has made its contribution, the classifier checks which label it is
closest to, and assigns that label to the input.</p>
</div>
<p>Individual features make their contribution to the overall decision by
"voting against" labels that don't occur with that feature very often.
In particular, the likelihood score for each label is reduced by
multiplying it by the probability that an input value with that label
would have the feature. For example, if the word <span class="example">run</span> occurs in 12%
of the sports documents, 10% of the murder mystery documents, and 2%
of the automotive documents, then the likelihood score for the sports
label will be multiplied by 0.12; the likelihood score for the murder
mystery label will be multiplied by 0.1, and the likelihood score for
the automotive label will be multiplied by 0.02. The overall effect
will be to reduce the score of the murder mystery label slightly more
than the score of the sports label, and to significantly reduce the
automotive label with respect to the other two labels. This
process is illustrated in <a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-naive-bayes-bargraph">5.2</a> and
<a class="reference internal" href="http://www.nltk.org/book/ch06.html#fig-naive-bayes-graph">5.3</a>.</p>
<span class="target" id="fig-naive-bayes-bargraph"></span><div class="figure" id="fig-naive-bayes-bargraph">
<img alt="../images/naive_bayes_bargraph.png" src="./6. Learning to Classify Text_files/naive_bayes_bargraph.png" style="width: 660.0px; height: 367.5px;">
<p class="caption"><span class="caption-label">Figure 5.2</span>: Calculating label likelihoods with naive Bayes. Naive Bayes begins
by calculating the prior probability of each label, based on how
frequently each label occurs in the training data. Every feature
then contributes to the likelihood estimate for each label, by
multiplying it by the probability that input values with that label
will have that feature. The resulting likelihood score can be
thought of as an estimate of the probability that a randomly
selected value from the training set would have both the given
label and the set of features, assuming that the feature
probabilities are all independent.</p>
</div>
<div class="section" id="underlying-probabilistic-model">
<h2>5.1 Underlying Probabilistic Model</h2>
<p>Another way of understanding the naive Bayes classifier is that it
chooses the most likely label for an input, under the assumption that
every input value is generated by first choosing a class label for
that input value, and then generating each feature, entirely
independent of every other feature. Of course, this assumption is
unrealistic; features are often highly dependent on one another. We'll
return to some of the consequences of this assumption at the end of
this section. This simplifying assumption, known as the
<a name="naive_bayes_assumption_index_term"><span class="termdef">naive Bayes assumption</span> (or </a><a name="independence_assumption_index_term"><span class="termdef">independence assumption</span>)
makes it much
easier to combine the contributions of the different features, since
we don't need to worry about how they should interact with one
another.</a></p><a name="independence_assumption_index_term">
<span class="target" id="fig-naive-bayes-graph"></span></a><div class="figure" id="fig-naive-bayes-graph"><a name="independence_assumption_index_term">
<img alt="../images/naive_bayes_graph.png" src="./6. Learning to Classify Text_files/naive_bayes_graph.png" style="width: 266.4px; height: 163.79999999999998px;">
</a><p class="caption"><a name="independence_assumption_index_term"><span class="caption-label">Figure 5.3</span>: A </a><a name="bayesian_network_graph_index_term"><span class="termdef">Bayesian Network Graph</span> illustrating the generative process
that is assumed by the naive Bayes classifier. To generate a
labeled input, the model first chooses a label for the input,
then it generates each of the input's features based on that label.
Every feature is assumed to be entirely independent of every other
feature, given the label.</a></p><a name="bayesian_network_graph_index_term">
</a></div><a name="bayesian_network_graph_index_term">
<p>Based on this assumption, we can calculate an expression for
<span class="math">P(label|features)</span>, the probability that an input will have a
particular label given that it has a particular set of features. To
choose a label for a new input, we can then simply pick the label
<span class="math">l</span> that maximizes <span class="math">P(l|features)</span>.</p>
<p>To begin, we note that <span class="math">P(label|features)</span> is equal to the
probability that an input has a particular label <em>and</em> the specified
set of features, divided by the probability that it has the specified
set of features:</p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(2)</td><td width="15"></td><td><span class="math">P(label|features) = P(features, label)/P(features)</span></td></tr></tbody></table></p>
<p>Next, we note that <span class="math">P(features)</span> will be the same for every
choice of label, so if we are simply interested in finding the most
likely label, it suffices to calculate <span class="math">P(features, label)</span>,
which we'll call the label likelihood.</p>
<div class="note">
<p class="first admonition-title">Note</p>
<p>If we want to generate a probability estimate for each
label, rather than just choosing the most likely label, then the
easiest way to compute P(features) is to simply calculate the sum
over labels of P(features, label):</p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(3)</td><td width="15"></td><td><span class="math">P(features)</span> =
Σ<sub>l in| labels</sub> <span class="math">P(features, label)</span></td></tr></tbody></table></p>
</div>
<p>The label likelihood can be expanded out as the probability of the
label times the probability of the features given the label:</p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(4)</td><td width="15"></td><td><span class="math">P(features, label) = P(label)</span> × <span class="math">P(features|label)</span></td></tr></tbody></table></p>
<p>Furthermore, since the features are all independent of one another
(given the label), we can separate out the probability of each
individual feature:</p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(5)</td><td width="15"></td><td><span class="math">P(features, label)</span> = <span class="math">P(label)</span> × Prod<sub>f in| features</sub><span class="math">P(f|label)`</span></td></tr></tbody></table></p>
<p>This is exactly the equation we discussed above for calculating the
label likelihood: <span class="math">P(label)</span> is the prior probability for a
given label, and each <span class="math">P(f|label)</span> is the contribution of a single
feature to the label likelihood.</p>
</a></div><a name="bayesian_network_graph_index_term">
</a><div class="section" id="zero-counts-and-smoothing"><a name="bayesian_network_graph_index_term">
<h2>5.2 Zero Counts and Smoothing</h2>
<p>The simplest way to calculate <span class="math">P(f|label)</span>, the contribution of a
feature <cite>f</cite> toward the label likelihood for a label <cite>label</cite>, is to
take the percentage of training instances with the given label that
also have the given feature:</p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(6)</td><td width="15"></td><td><span class="math">P(f|label) = count(f, label) / count(label)</span></td></tr></tbody></table></p>
<p>However, this simple approach can become problematic when a feature
<em>never</em> occurs with a given label in the training set. In this
case, our calculated value for <span class="math">P(f|label)</span> will be zero, which will
cause the label likelihood for the given label to be zero. Thus, the
input will never be assigned this label, regardless of how well the
other features fit the label.</p>
<p>The basic problem here is with our calculation of <span class="math">P(f|label)</span>, the
probability that an input will have a feature, given a label. In
particular, just because we haven't seen a feature/label combination
occur in the training set, doesn't mean it's impossible for that
combination to occur. For example, we may not have seen any murder
mystery documents that contained the word "football," but we wouldn't
want to conclude that it's completely impossible for such documents to
exist.</p>
</a><p><a name="bayesian_network_graph_index_term">Thus, although <span class="math">count(f,label)/count(label)</span> is a good estimate for
<span class="math">P(f|label)</span> when <span class="math">count(f, label)</span> is relatively high, this
estimate becomes less reliable when <span class="math">count(f)</span> becomes smaller.
Therefore, when building naive Bayes models, we usually employ
more sophisticated techniques, known as </a><a name="smoothing_index_term"><span class="termdef">smoothing</span> techniques,
for calculating <span class="math">P(f|label)</span>, the probability of a feature given a
label. For example, the </a><a name="expected_likelihood_estimation_index_term"><span class="termdef">Expected Likelihood Estimation</span> for the
probability of a feature given a label basically adds 0.5 to each
<span class="math">count(f,label)</span> value, and the </a><a name="heldout_estimation_index_term"><span class="termdef">Heldout Estimation</span> uses a heldout
corpus to calculate the relationship between feature frequencies and
feature probabilities. The <tt class="doctest"><span class="pre">nltk.probability</span></tt> module provides support
for a wide variety of smoothing techniques.</a></p><a name="heldout_estimation_index_term">
<!-- XXX Refer to J&M 4.5 probably just in the further reading section -->
<!-- XXX Mention that NLTK supports many smoothing methods, and name some of them -->
</a></div><a name="heldout_estimation_index_term">
</a><div class="section" id="non-binary-features"><a name="heldout_estimation_index_term">
<h2>5.3 Non-Binary Features</h2>
</a><p><a name="heldout_estimation_index_term">We have assumed here that each feature is binary, i.e.
that each input either has a feature or does not. Label-valued
features (e.g., a color feature which could be red, green, blue,
white, or orange) can be converted to binary features by replacing
them with binary features such as "color-is-red". Numeric features can be
converted to binary features by </a><a name="binning_index_term"><span class="termdef">binning</span>, which replaces them with
features such as "4<x<6".</a></p><a name="binning_index_term">
<p>Another alternative is to use regression methods to model the
probabilities of numeric features. For example, if we assume that the
height feature has a bell curve distribution, then we could estimate
P(height|label) by finding the mean and variance of the heights of the
inputs with each label. In this case, <span class="math">P(f=v|label)</span> would not
be a fixed value, but would vary depending on the value of <cite>v</cite>.</p>
</a></div><a name="binning_index_term">
<div class="section" id="the-naivete-of-independence">
<h2>5.4 The Naivete of Independence</h2>
<p>The reason that naive Bayes classifiers are called "naive" is that
it's unreasonable to assume that all features are independent of one
another (given the label). In particular, almost all real-world
problems contain features with varying degrees of dependence on one
another. If we had to avoid any features that were dependent on one
another, it would be very difficult to construct good feature sets
that provide the required information to the machine learning
algorithm.</p>
<p>So what happens when we ignore the independence assumption, and use
the naive Bayes classifier with features that are not independent?
One problem that arises is that the classifier can end up
"double-counting" the effect of highly correlated features, pushing
the classifier closer to a given label than is justified.</p>
<p>To see how this can occur, consider a name gender classifier that
contains two identical features, <span class="math">f</span><sub>1</sub> and <span class="math">f</span><sub>2</sub>. In other words, <span class="math">f</span><sub>2</sub> is an exact copy of
<span class="math">f</span><sub>1</sub>, and contains no new information.
When the classifier is considering an input, it will include the
contribution of both <span class="math">f</span><sub>1</sub> and <span class="math">f</span><sub>2</sub> when
deciding which label to choose. Thus, the information content of
these two features will be given more weight than it deserves.</p>
<p>Of course, we don't usually build naive Bayes classifiers that contain
two identical features. However, we do build classifiers that contain
features which are dependent on one another. For example, the
features <tt class="doctest"><span class="pre">ends-with(a)</span></tt> and <tt class="doctest"><span class="pre">ends-with(vowel)</span></tt> are dependent on
one another, because if an input value has the first feature, then it
must also have the second feature. For features like these, the
duplicated information may be given more weight than is justified by
the training set.</p>
</div>
</a><div class="section" id="the-cause-of-double-counting"><a name="binning_index_term">
<h2>5.5 The Cause of Double-Counting</h2>
<p>The reason for the double-counting problem is that
during training, feature contributions are computed separately;
but when using the classifier to choose labels for new inputs, those
feature contributions are combined. One solution, therefore, is to
consider the possible interactions between feature contributions
during training. We could then use those interactions to adjust the
contributions that individual features make.</p>
<p>To make this more precise, we can rewrite the equation used to
calculate the likelihood of a label, separating out the
contribution made by each feature (or label):</p>
<!-- .. _parameterized-naive-bayes: -->
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(7)</td><td width="15"></td><td><span class="math">P(features, label) = w[label]</span> × Prod<sub>f |in| features</sub> <span class="math">w[f, label]</span></td></tr></tbody></table></p>
</a><p><a name="binning_index_term">Here, <span class="math">w[label]</span> is the "starting score" for a given label, and
<span class="math">w[f, label]</span> is the contribution made by a given feature
towards a label's likelihood. We call these values <span class="math">w[label]</span>
and <span class="math">w[f, label]</span> the </a><a name="parameters_index_term"><span class="termdef">parameters</span> or </a><a name="weights_index_term"><span class="termdef">weights</span> for the
model. Using the naive Bayes algorithm, we set each of these
parameters independently:</a></p><a name="weights_index_term">
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(8)</td><td width="15"></td><td><span class="math">w[label] = P(label)</span></td></tr></tbody></table></p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(9)</td><td width="15"></td><td><span class="math">w[f, label] = P(f|label)</span></td></tr></tbody></table></p>
<p>However, in the next section, we'll look at a classifier that
considers the possible interactions between these parameters when
choosing their values.</p>
</a></div><a name="weights_index_term">
</a></div><a name="weights_index_term">
</a><div class="section" id="maximum-entropy-classifiers"><a name="weights_index_term">
<h1>6 Maximum Entropy Classifiers</h1>
</a><p><a name="weights_index_term">The </a><a name="maximum_entropy_index_term"><span class="termdef">Maximum Entropy</span> classifier uses a model that is very
similar to the model employed by the naive Bayes classifier. But rather
than using probabilities to set the model's parameters, it uses search
techniques to find a set of parameters that will maximize the
performance of the classifier. In particular, it looks for the set of
parameters that maximizes the </a><a name="total_likelihood_index_term"><span class="termdef">total likelihood</span> of the training
corpus, which is defined as:</a></p><a name="total_likelihood_index_term">
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(10)</td><td width="15"></td><td><span class="math">P(features)</span> =
Σ<sub>x |in| corpus</sub> <span class="math">P(label(x)|features(x))</span></td></tr></tbody></table></p>
<p>Where <tt class="doctest"><span class="pre">P(label|features)</span></tt>, the probability that an input whose
features are <tt class="doctest"><span class="pre">features</span></tt> will have class label <tt class="doctest"><span class="pre">label</span></tt>, is defined as:</p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(11)</td><td width="15"></td><td><span class="math">P(label|features) = P(label, features) /</span>
Σ<sub>label</sub> <span class="math">P(label, features)</span></td></tr></tbody></table></p>
</a><p><a name="total_likelihood_index_term">Because of the potentially complex interactions between the effects of
related features, there is no way to directly calculate the model
parameters that maximize the likelihood of the training set.
Therefore, Maximum Entropy classifiers choose the model parameters
using </a><a name="iterative_optimization_index_term"><span class="termdef">iterative optimization</span> techniques, which initialize the
model's parameters to random values, and then repeatedly refine those
parameters to bring them closer to the optimal solution. These
iterative optimization techniques guarantee that each refinement of
the parameters will bring them closer to the optimal values, but do
not necessarily provide a means of determining when those optimal
values have been reached. Because the parameters for Maximum Entropy
classifiers are selected using iterative optimization techniques, they
can take a long time to learn. This is especially true when the size
of the training set, the number of features, and the number of
labels are all large.</a></p><a name="iterative_optimization_index_term">
<div class="note">
<p class="first admonition-title">Note</p>
<p class="last">Some iterative optimization techniques are much faster than
others. When training Maximum Entropy models, avoid the use of
Generalized Iterative Scaling (GIS) or Improved Iterative Scaling
(IIS), which are both considerably slower than the Conjugate
Gradient (CG) and the BFGS optimization methods.</p>
</div>
<!-- The above note could go in the further reading section with a couple
of literature references -->
<!-- For related work section:?
The use of iterative optimization techniques to find the parameters
that maximize the performance of a model is quite common in machine
learning. -->
</a><div class="section" id="the-maximum-entropy-model"><a name="iterative_optimization_index_term">
<h2>6.1 The Maximum Entropy Model</h2>
<p>The Maximum Entropy classifier model is a generalization of the model
used by the naive Bayes classifier. Like the naive Bayes model, the
Maximum Entropy classifier calculates the likelihood of each label for
a given input value by multiplying together the parameters that are
applicable for the input value and label. The naive Bayes classifier
model defines a parameter for each label, specifying its prior
probability, and a parameter for each (feature, label) pair,
specifying the contribution of individual features towards a label's
likelihood.</p>
<p>In contrast, the Maximum Entropy classifier model leaves it up to the
user to decide what combinations of labels and features should receive
their own parameters. In particular, it is possible to use a single
parameter to associate a feature with more than one label; or to
associate more than one feature with a given label. This will
sometimes allow the model to "generalize" over some of the
differences between related labels or features.</p>
</a><p><a name="iterative_optimization_index_term">Each combination of labels and features that receives its own
parameter is called a </a><a name="joint_feature_index_term"><span class="termdef">joint-feature</span>. Note that joint-features
are properties of <em>labeled</em> values, whereas (simple) features are
properties of <em>unlabeled</em> values.</a></p><a name="joint_feature_index_term">
<div class="note">
<p class="first admonition-title">Note</p>
<p class="last">In literature that describes and discusses Maximum Entropy
models, the term "features" often refers to
joint-features; the term "contexts" refers to what
we have been calling (simple) features.</p>
</div>
<p>Typically, the joint-features that are used to construct Maximum
Entropy models exactly mirror those that are used by the naive Bayes
model. In particular, a joint-feature is defined for each label,
corresponding to <span class="math">w</span>[<span class="math">label</span>], and for each combination of
(simple) feature and label, corresponding to <span class="math">w</span>[<span class="math">f</span>,<span class="math">label</span>].
Given the joint-features for a Maximum Entropy model, the score
assigned to a label for a given input is simply the product of the
parameters associated with the joint-features that apply to that input
and label:</p>
<!-- .. _parameterized-maxent: -->
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(12)</td><td width="15"></td><td><span class="math">P(input, label) =</span> Prod<sub>joint-features(input,label)</sub> <span class="math">w[joint-feature]</span></td></tr></tbody></table></p>
</a></div><a name="joint_feature_index_term">
</a><div class="section" id="maximizing-entropy"><a name="joint_feature_index_term">
<h2>6.2 Maximizing Entropy</h2>
<p>The intuition that motivates Maximum Entropy classification is that we
should build a model that captures the frequencies of individual
joint-features, without making any unwarranted assumptions.
An example will help to illustrate this principle.</p>
<p>Suppose we are assigned the task of picking the correct word sense for
a given word, from a list of ten possible senses (labeled A-J). At
first, we are not told anything more about the word or the senses.
There are many probability distributions that we could choose for the
ten senses, such as:</p>
<p class="caption"><span class="caption-label">Table 6.1</span></p><table border="1" class="docutils">
<colgroup>
<col width="7%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
</colgroup>
<thead valign="bottom">
<tr><th class="head"></th>
<th class="head">A</th>
<th class="head">B</th>
<th class="head">C</th>
<th class="head">D</th>
<th class="head">E</th>
<th class="head">F</th>
<th class="head">G</th>
<th class="head">H</th>
<th class="head">I</th>
<th class="head">J</th>
</tr>
</thead>
<tbody valign="top">
<tr><td><cite>(i)</cite></td>
<td>10%</td>
<td>10%</td>
<td>10%</td>
<td>10%</td>
<td>10%</td>
<td>10%</td>
<td>10%</td>
<td>10%</td>
<td>10%</td>
<td>10%</td>
</tr>
<tr><td><cite>(ii)</cite></td>
<td>5%</td>
<td>15%</td>
<td>0%</td>
<td>30%</td>
<td>0%</td>
<td>8%</td>
<td>12%</td>
<td>0%</td>
<td>6%</td>
<td>24%</td>
</tr>
<tr><td><cite>(iii)</cite></td>
<td>0%</td>
<td>100%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
</tbody>
</table>
<p>Although any of these distributions <em>might</em> be correct, we are likely
to choose distribution <cite>(i)</cite>, because without any more information,
there is no reason to believe that any word sense is more likely than
any other. On the other hand, distributions <cite>(ii)</cite> and <cite>(iii)</cite> reflect
assumptions that are not supported by what we know.</p>
</a><p><a name="joint_feature_index_term">One way to capture this intuition that distribution <cite>(i)</cite> is more "fair"
than the other two is to invoke the concept of entropy. In the
discussion of decision trees, we described entropy as a measure of how
"disorganized" a set of labels was. In particular, if a single label
dominates then entropy is low, but if the labels are more evenly
distributed then entropy is high. In our example, we chose
distribution <cite>(i)</cite> because its label probabilities are evenly
distributed — in other words, because its entropy is high. In
general, the </a><a name="maximum_entropy_principle_index_term"><span class="termdef">Maximum Entropy principle</span> states that, among the
distributions that are consistent with what we know, we should choose
the distribution whose entropy is highest.</a></p><a name="maximum_entropy_principle_index_term">
<p>Next, suppose that we are told that sense A appears 55% of the time.
Once again, there are many distributions that are consistent with this
new piece of information, such as:</p>
<p class="caption"><span class="caption-label">Table 6.2</span></p><table border="1" class="docutils">
<colgroup>
<col width="7%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
</colgroup>
<thead valign="bottom">
<tr><th class="head"></th>
<th class="head">A</th>
<th class="head">B</th>
<th class="head">C</th>
<th class="head">D</th>
<th class="head">E</th>
<th class="head">F</th>
<th class="head">G</th>
<th class="head">H</th>
<th class="head">I</th>
<th class="head">J</th>
</tr>
</thead>
<tbody valign="top">
<tr><td><cite>(iv)</cite></td>
<td>55%</td>
<td>45%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr><td><cite>(v)</cite></td>
<td>55%</td>
<td>5%</td>
<td>5%</td>
<td>5%</td>
<td>5%</td>
<td>5%</td>
<td>5%</td>
<td>5%</td>
<td>5%</td>
<td>5%</td>
</tr>
<tr><td><cite>(vi)</cite></td>
<td>55%</td>
<td>3%</td>
<td>1%</td>
<td>2%</td>
<td>9%</td>
<td>5%</td>
<td>0%</td>
<td>25%</td>
<td>0%</td>
<td>0%</td>
</tr>
</tbody>
</table>
<p>But again, we will likely choose the distribution that makes the
fewest unwarranted assumptions — in this case, distribution <cite>(v)</cite>.</p>
<p>Finally, suppose that we are told that the word "up" appears in the
nearby context 10% of the time, and that when it does appear in the
context there's an 80% chance that sense A or C will be used. In
this case, we will have a harder time coming up with an appropriate
distribution by hand; however, we can verify that the following
distribution looks appropriate:</p>
<p class="caption"><span class="caption-label">Table 6.3</span></p><table border="1" class="docutils">
<colgroup>
<col width="7%">
<col width="7%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
<col width="9%">
</colgroup>
<thead valign="bottom">
<tr><th class="head"></th>
<th class="head"> </th>
<th class="head">A</th>
<th class="head">B</th>
<th class="head">C</th>
<th class="head">D</th>
<th class="head">E</th>
<th class="head">F</th>
<th class="head">G</th>
<th class="head">H</th>
<th class="head">I</th>
<th class="head">J</th>
</tr>
</thead>
<tbody valign="top">
<tr><td><cite>(vii)</cite></td>
<td>+up</td>
<td>5.1%</td>
<td>0.25%</td>
<td>2.9%</td>
<td>0.25%</td>
<td>0.25%</td>
<td>0.25%</td>
<td>0.25%</td>
<td>0.25%</td>
<td>0.25%</td>
<td>0.25%</td>
</tr>
<tr><td>` `</td>
<td>-up</td>
<td>49.9%</td>
<td>4.46%</td>
<td>4.46%</td>
<td>4.46%</td>
<td>4.46%</td>
<td>4.46%</td>
<td>4.46%</td>
<td>4.46%</td>
<td>4.46%</td>
<td>4.46%</td>
</tr>
</tbody>
</table>
<p>In particular, the distribution is consistent with what we know: if we
add up the probabilities in column A, we get 55%; if we add up the
probabilities of row 1, we get 10%; and if we add up the boxes for
senses A and C in the +up row, we get 8% (or 80% of the +up cases).
Furthermore, the remaining probabilities appear to be "evenly
distributed."</p>
<p>Throughout this example, we have restricted ourselves to distributions
that are consistent with what we know; among these, we chose the
distribution with the highest entropy. This is exactly what the
Maximum Entropy classifier does as well. In particular, for each
joint-feature, the Maximum Entropy model calculates the "empirical
frequency" of that feature — i.e., the frequency with which it occurs
in the training set. It then searches for the distribution which
maximizes entropy, while still predicting the correct frequency for
each joint-feature.</p>
</a></div><a name="maximum_entropy_principle_index_term">
</a><div class="section" id="generative-vs-conditional-classifiers"><a name="maximum_entropy_principle_index_term">
<h2>6.3 Generative vs Conditional Classifiers</h2>
<!-- XXX cannot parse next sentence -->
</a><p><a name="maximum_entropy_principle_index_term">An important difference between the naive Bayes classifier and the
Maximum Entropy classifier concerns the type of questions they can be
used to answer. The naive Bayes classifier is an example of a
</a><a name="generative_index_term"><span class="termdef">generative</span> classifier, which builds a model that predicts
<span class="math">P(input, label)</span>, the joint probability of a <span class="math">(input,
label)</span> pair. As a result, generative models can be used to
answer the following questions:</a></p><a name="generative_index_term">
<ol class="arabic simple">
<li>What is the most likely label for a given input?</li>
<li>How likely is a given label for a given input?</li>
<li>What is the most likely input value?</li>
<li>How likely is a given input value?</li>
<li>How likely is a given input value with a given label?</li>
<li>What is the most likely label for an input that might have one
of two values (but we don't know which)?</li>
</ol>
<!-- XXX possibly add expressions like argmax_label P(label|input) to each
of the above questions, to make more explicit connections with the
earlier discussion -->
</a><p><a name="generative_index_term">The Maximum Entropy classifier, on the other hand, is an example of a
</a><a name="conditional_index_term"><span class="termdef">conditional</span> classifier. Conditional classifiers build models
that predict <span class="math">P(label|input)</span> — the probability of a label
<em>given</em> the input value. Thus, conditional models can still be used
to answer questions 1 and 2. However, conditional models can <em>not</em> be
used to answer the remaining questions 3-6.</a></p><a name="conditional_index_term">
<p>In general, generative models are strictly more powerful than
conditional models, since we can calculate the conditional probability
<span class="math">P(label|input)</span> from the joint probability <span class="math">P(input,
label)</span>, but not vice versa.
However, this additional power comes at a price. Because the model is
more powerful, it has more "free parameters" which need to be learned.
However, the size of the training set is fixed. Thus, when using a
more powerful model, we end up with less data that can be used to
train each parameter's value, making it harder to find the best
parameter values. As a result, a generative model may not do as good
a job at answering questions 1 and 2 as a conditional model, since the
conditional model can focus its efforts on those two questions.
However, if we do need answers to questions like 3-6, then we have no
choice but to use a generative model.</p>
<p>The difference between a generative model and a conditional model is
analogous to the difference between a topographical map and a picture of
a skyline. Although the topographical map can be used to answer a wider
variety of questions, it is significantly more difficult to generate
an accurate topographical map than it is to generate an accurate skyline.</p>
<!-- I want a figure here. But the images I used for this in the past
(on powerpoint) are probably copyrighted, so I'll need to draw/find
some new images. They should be a side-by-side picture of a
topographical map and a skyline. The left/right axis of each should
be labeled as (output value), the up/down axis of each should be
labeled as (probability), and the forward/back axis of the topo map
should be (input value). -->
</a></div><a name="conditional_index_term">
</a></div><a name="conditional_index_term">
</a><div class="section" id="modeling-linguistic-patterns"><a name="conditional_index_term">
<h1>7 Modeling Linguistic Patterns</h1>
</a><p><a name="conditional_index_term">Classifiers can help us to understand the linguistic patterns that
occur in natural language, by allowing us to create explicit
</a><a name="models_index_term"><span class="termdef">models</span> that capture those patterns. Typically, these models are
using supervised classification techniques, but it is also possible to
build analytically motivated models. Either way, these explicit
models serve two important purposes: they help us to understand
linguistic patterns, and they can be used to make predictions about
new language data.</a></p><a name="models_index_term">
<p>The extent to which explicit models can give us insights into
linguistic patterns depends largely on what kind of model is used.
Some models, such as decision trees, are relatively transparent, and
give us direct information about which factors are important in making
decisions and about which factors are related to one another. Other
models, such as multi-level neural networks, are much more opaque.
Although it can be possible to gain insight by studying them, it
typically takes a lot more work.</p>
</a><p><a name="models_index_term">But all explicit models can make predictions about new "</a><a name="unseen_index_term"><span class="termdef">unseen</span>"
language data that was not included in the corpus used to build the
model. These predictions can be evaluated to assess the accuracy of
the model. Once a model is deemed sufficiently accurate, it can then
be used to automatically predict information about new language
data. These predictive models can be combined into systems that
perform many useful language processing tasks, such as document
classification, automatic translation, and question answering.</a></p><a name="unseen_index_term">
</a><div class="section" id="what-do-models-tell-us"><a name="unseen_index_term">
<h2>7.1 What do models tell us?</h2>
</a><p><a name="unseen_index_term">It's important to understand what we can learn about language from an
automatically constructed model. One important consideration when
dealing with models of language is the distinction between descriptive
models and explanatory models. Descriptive models capture patterns in
the data but they don't provide any information about <em>why</em> the data
contains those patterns. For example, as we saw in </a><a class="reference external" href="http://www.nltk.org/book/ch03.html#tab-absolutely">3.1</a>,
the synonyms <span class="example">absolutely</span> and <span class="example">definitely</span> are not
interchangeable: we say <span class="example">absolutely adore</span> not <span class="example">definitely
adore</span>, and <span class="example">definitely prefer</span> not <span class="example">absolutely prefer</span>.
In contrast, explanatory models attempt to capture properties and
relationships that cause the linguistic patterns. For example, we
might introduce the abstract concept of "polar verb", as one that
has an extreme meaning, and categorize some verb like
<span class="example">adore</span> and <span class="example">detest</span> as polar. Our explanatory model would
contain the constraint that <span class="example">absolutely</span> can only combine with
polar verbs, and <span class="example">definitely</span> can only combine with non-polar
verbs. In summary, descriptive models provide information about
correlations in the data, while explanatory models go further to
postulate causal relationships.</p>
<p>Most models that are automatically constructed from a corpus are
descriptive models; in other words, they can tell us what features are
relevant to a given pattern or construction, but they can't
necessarily tell us how those features and patterns relate to one
another. If our goal is to understand the linguistic patterns, then
we can use this information about which features are related as a
starting point for further experiments designed to tease apart the
relationships between features and patterns. On the other hand, if
we're just interested in using the model to make predictions (e.g., as
part of a language processing system), then we can use the model to
make predictions about new data without worrying about the details
of underlying causal relationships.</p>
</div>
</div>
<div class="section" id="summary">
<h1>8 Summary</h1>
<ul class="simple">
<li>Modeling the linguistic data found in corpora can help us to
understand linguistic patterns, and can be used to make predictions
about new language data.</li>
<li>Supervised classifiers use labeled training corpora to build models
that predict the label of an input based on specific features of
that input.</li>
<li>Supervised classifiers can perform a wide variety of
NLP tasks, including document classification, part-of-speech
tagging, sentence segmentation, dialogue act type identification,
and determining entailment relations, and many other tasks.</li>
<li>When training a supervised classifier, you should split your corpus
into three datasets: a training set for building the
classifier model; a dev-test set for helping select
and tune the model's features; and a test set for
evaluating the final model's performance.</li>
<li>When evaluating a supervised classifier, it is important that you
use fresh data, that was not included in the training or dev-test
set. Otherwise, your evaluation results may be unrealistically
optimistic.</li>
<li>Decision trees are automatically constructed tree-structured
flowcharts that are used to assign labels to input values based on
their features. Although they're easy to interpret, they are not
very good at handling cases where feature values interact in
determining the proper label.</li>
<li>In naive Bayes classifiers, each feature independently contributes
to the decision of which label should be used. This allows feature
values to interact, but can be problematic when two or more features
are highly correlated with one another.</li>
<li>Maximum Entropy classifiers use a basic model that is similar to the
model used by naive Bayes; however, they employ iterative optimization
to find the set of feature weights that maximizes the probability of
the training set.</li>
<li>Most of the models that are automatically constructed from a corpus
are descriptive — they let us know which features are relevant
to a given patterns or construction, but they don't give any
information about causal relationships between those features and
patterns.</li>
</ul>
</div>
<div class="section" id="further-reading">
<h1>9 Further Reading</h1>
<p>Please consult <tt class="doctest"><span class="pre">http://nltk.org/</span></tt> for further materials on this chapter and on how to
install external machine learning packages, such as Weka, Mallet,
TADM, and MEGAM.
For more examples of classification and machine learning with NLTK,
please see the classification HOWTOs at <tt class="doctest"><span class="pre">http://nltk.org/howto</span></tt>.</p>
<p>For a general introduction to machine learning, we recommend
<a class="reference external" href="http://www.nltk.org/book/bibliography.html#alpaydin2004" id="id1">(Alpaydin, 2004)</a>. For a more mathematically intense introduction to
the theory of machine learning, see <a class="reference external" href="http://www.nltk.org/book/bibliography.html#hastie2009" id="id2">(Hastie, Tibshirani, & Friedman, 2009)</a>. Excellent books on
using machine learning techniques for NLP include <a class="reference external" href="http://www.nltk.org/book/bibliography.html#abney2008" id="id3">(Abney, 2008)</a>,
<a class="reference external" href="http://www.nltk.org/book/bibliography.html#daelemans2005" id="id4">(Daelemans & Bosch, 2005)</a>, <a class="reference external" href="http://www.nltk.org/book/bibliography.html#feldman2007" id="id5">(Feldman & Sanger, 2007)</a>, <a class="reference external" href="http://www.nltk.org/book/bibliography.html#segaran2007" id="id6">(Segaran, 2007)</a>, <a class="reference external" href="http://www.nltk.org/book/bibliography.html#weiss2004" id="id7">(Weiss et al, 2004)</a>. For
more on smoothing techniques for language problems, see
<a class="reference external" href="http://www.nltk.org/book/bibliography.html#manning1999fsn" id="id8">(Manning & Schutze, 1999)</a>. For more on sequence modeling, and especially
hidden Markov models, see <a class="reference external" href="http://www.nltk.org/book/bibliography.html#manning1999fsn" id="id9">(Manning & Schutze, 1999)</a> or <a class="reference external" href="http://www.nltk.org/book/bibliography.html#jurafskymartin2008" id="id10">(Jurafsky & Martin, 2008)</a>.
Chapter 13 of <a class="reference external" href="http://www.nltk.org/book/bibliography.html#manning2008ir" id="id11">(Manning, Raghavan, & Schutze, 2008)</a> discusses the use of naive Bayes for
classifying texts.</p>
<p>Many of the machine learning algorithms discussed in this chapter are
numerically intensive, and as a result, they will run slowly when
coded naively in Python. For information on increasing the efficiency
of numerically intensive algorithms in Python, see <a class="reference external" href="http://www.nltk.org/book/bibliography.html#kiusalaas2005" id="id12">(Kiusalaas, 2005)</a>.</p>
<p>The classification techniques described in this chapter can be applied
to a very wide variety of problems. For example, <a class="reference external" href="http://www.nltk.org/book/bibliography.html#agirre2007" id="id13">(Agirre & Edmonds, 2007)</a> uses
classifiers to perform word-sense disambiguation; and <a class="reference external" href="http://www.nltk.org/book/bibliography.html#melamed2001" id="id14">(Melamed, 2001)</a>
uses classifiers to create parallel texts. Recent textbooks that
cover text classification include <a class="reference external" href="http://www.nltk.org/book/bibliography.html#manning2008ir" id="id15">(Manning, Raghavan, & Schutze, 2008)</a> and <a class="reference external" href="http://www.nltk.org/book/bibliography.html#croft2009" id="id16">(Croft, Metzler, & Strohman, 2009)</a>.</p>
<p>Much of the current research in the application of machine learning
techniques to NLP problems is driven by government-sponsored
"challenges," where a set of research organizations are all provided
with the same development corpus, and asked to build a system; and the
resulting systems are compared based on a reserved test set. Examples
of these challenge competitions include CoNLL Shared Tasks, the ACE
competitions, the Recognizing Textual Entailment competitions,
and the AQUAINT competitions. Consult <tt class="doctest"><span class="pre">http://nltk.org/</span></tt> for a
list of pointers to the webpages for these challenges.</p>
<!-- - supported ML packages
- http://www.cs.waikato.ac.nz/~ml/weka/book.html
- choosing prepositions http://itre.cis.upenn.edu/~myl/languagelog/archives/002003.html
- Jurafsky and Martin
- publications describing some of the corpora that were created for the
purpose of training and testing classifiers
Xin Li, Dan Roth, Learning Question Classifiers: The Role of Semantic Information
http://l2r.cs.uiuc.edu/~danr/Papers/LiRo05a.pdf
Current challenge: The problem of applying models trained on one genre
to another (portability across domains; domain adaptation);
Use of unsupervised or weakly supervised approaches to exploit a small
amount of in-domain training data, or of unlabeled in-domain training data
[REFS] -->
</div>
<div class="section" id="exercises">
<h1>10 Exercises</h1>
<ol class="arabic">
<li><p class="first">☼ Read up on one of the language technologies mentioned in this section, such as
word sense disambiguation, semantic role labeling, question answering, machine translation,
named entity detection.
Find out what type and quantity of annotated data is required for developing such systems.
Why do you think a large amount of data is required?</p>
</li>
<li><p class="first">☼ Using any of the three classifiers described in this
chapter, and any features you can think of, build the best name
gender classifier you can. Begin by splitting the Names Corpus
into three subsets: 500 words for the test set, 500 words for the
dev-test set, and the remaining 6900 words for the training set.
Then, starting with the example name gender classifier, make
incremental improvements. Use the dev-test set to check your
progress. Once you are satisfied with your classifier, check its
final performance on the test set. How does the performance on
the test set compare to the performance on the dev-test set?
Is this what you'd expect?</p>
</li>
<li><p class="first">☼ The Senseval 2 Corpus contains data intended to train
word-sense disambiguation classifiers. It contains data for
four words: hard, interest, line, and serve. Choose one of these
four words, and load the corresponding data:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">from</span> nltk.corpus <span class="pysrc-keyword">import</span> senseval
<span class="pysrc-prompt">>>> </span>instances = senseval.instances(<span class="pysrc-string">'hard.pos'</span>)
<span class="pysrc-prompt">>>> </span>size = int(len(instances) * 0.1)
<span class="pysrc-prompt">>>> </span>train_set, test_set = instances[size:], instances[:size]</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Using this dataset, build a classifier that predicts the correct
sense tag for a given instance. See the corpus HOWTO at
<tt class="doctest"><span class="pre">http://nltk.org/howto</span></tt> for information on using the instance objects
returned by the Senseval 2 Corpus.</p>
</li>
<li><p class="first">☼
Using the movie review document classifier discussed in this
chapter, generate a list of the 30 features that the classifier
finds to be most informative. Can you explain why these particular
features are informative? Do you find any of them surprising?</p>
</li>
<li><p class="first">☼
Select one of the classification tasks described in this chapter,
such as name gender detection, document classification,
part-of-speech tagging, or dialog act classification. Using the
same training and test data, and the same feature extractor,
build three classifiers for the task: a decision tree, a naive
Bayes classifier, and a Maximum Entropy classifier. Compare
the performance of the three classifiers on your selected task.
How do you think that your results might be different if you used
a different feature extractor?</p>
</li>
<li><p class="first">☼
The synonyms <span class="example">strong</span> and <span class="example">powerful</span> pattern
differently (try combining them with <span class="example">chip</span> and <span class="example">sales</span>).
What features are relevant in this distinction?
Build a classifier that predicts when each word should be used.</p>
</li>
<li><p class="first">◑
The dialog act classifier assigns labels to individual posts,
without considering the context in which the post is found.
However, dialog acts are highly dependent on context, and some
sequences of dialog act are much more likely than others. For
example, a ynQuestion dialog act is much more likely to be
answered by a <tt class="doctest"><span class="pre">yanswer</span></tt> than by a <tt class="doctest"><span class="pre">greeting</span></tt>. Make use of this
fact to build a consecutive classifier for labeling dialog acts.
Be sure to consider what features might be useful. See the code
for the consecutive classifier for part-of-speech tags in
<a class="reference internal" href="http://www.nltk.org/book/ch06.html#code-consecutive-pos-tagger">1.7</a> to get some ideas.</p>
</li>
<li><p class="first">◑
Word features can be very useful for performing document
classification, since the words that appear in a document give a
strong indication about what its semantic content is. However,
many words occur very infrequently, and some of the most
informative words in a document may never have occurred in our
training data. One solution is to make use of a <a name="lexicon_index_term"><span class="termdef">lexicon</span>,
which describes how different words relate to one another. Using
WordNet lexicon, augment the movie review document classifier
presented in this chapter to use features that generalize the words
that appear in a document, making it more likely that they will
match words found in the training data.</a></p><a name="lexicon_index_term">
</a></li><a name="lexicon_index_term">
<li><p class="first">★
The PP Attachment Corpus is a corpus describing
prepositional phrase attachment decisions. Each instance in the
corpus is encoded as a <tt class="doctest"><span class="pre">PPAttachment</span></tt> object:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span><span class="pysrc-keyword">from</span> nltk.corpus <span class="pysrc-keyword">import</span> ppattach
<span class="pysrc-prompt">>>> </span>ppattach.attachments(<span class="pysrc-string">'training'</span>)
<span class="pysrc-output">[PPAttachment(sent='0', verb='join', noun1='board',</span>
<span class="pysrc-output"> prep='as', noun2='director', attachment='V'),</span>
<span class="pysrc-output"> PPAttachment(sent='1', verb='is', noun1='chairman',</span>
<span class="pysrc-output"> prep='of', noun2='N.V.', attachment='N'),</span>
<span class="pysrc-output"> ...]</span>
<span class="pysrc-output"></span><span class="pysrc-prompt">>>> </span>inst = ppattach.attachments(<span class="pysrc-string">'training'</span>)[1]
<span class="pysrc-prompt">>>> </span>(inst.noun1, inst.prep, inst.noun2)
<span class="pysrc-output">('chairman', 'of', 'N.V.')</span></pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Select only the instances where <tt class="doctest"><span class="pre">inst.attachment</span></tt> is <tt class="doctest"><span class="pre">N</span></tt>:</p>
<div class="doctest">
<table border="0" cellpadding="0" cellspacing="0" class="doctest" width="95%">
<tbody><tr><td class="doctest">
<table border="0" cellpadding="0" cellspacing="0" width="100%">
<tbody><tr><td width="1" class="copybar" onclick="javascript:copy_doctest_to_clipboard(this.nextSibling);"> </td>
<td class="pysrc"><pre class="doctest"><span class="pysrc-prompt">>>> </span>nattach = [inst <span class="pysrc-keyword">for</span> inst <span class="pysrc-keyword">in</span> ppattach.attachments(<span class="pysrc-string">'training'</span>)
<span class="pysrc-more">... </span> <span class="pysrc-keyword">if</span> inst.attachment == <span class="pysrc-string">'N'</span>]</pre>
</td>
</tr></tbody></table></td></tr>
</tbody></table></div>
<p>Using this sub-corpus, build a classifier that attempts to predict
which preposition is used to connect a given pair of nouns. For
example, given the pair of nouns "team" and "researchers," the
classifier should predict the preposition "of". See the corpus
HOWTO at <tt class="doctest"><span class="pre">http://nltk.org/howto</span></tt> for more information on using the PP
attachment corpus.</p>
</li>
<li><p class="first">★ Suppose you wanted to automatically generate a prose description of a scene,
and already had a word to uniquely describe each entity, such as <span class="example">the jar</span>,
and simply wanted to decide whether to use <span class="example">in</span> or <span class="example">on</span> in relating
various items, e.g. <span class="example">the book is in the cupboard</span> vs <span class="example">the book is on the shelf</span>.
Explore this issue by looking at corpus data; writing programs as needed.</p>
</li>
</a></ol><a name="lexicon_index_term">
<span class="target" id="ex-prepositions"></span><p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">(13)</td><td width="15"></td><td><p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">a.</td><td width="15"></td><td>in the car <em>versus</em> on the train</td></tr></tbody></table></p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">b.</td><td width="15"></td><td>in town <em>versus</em> on campus</td></tr></tbody></table></p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">c.</td><td width="15"></td><td>in the picture <em>versus</em> on the screen</td></tr></tbody></table></p>
<p><table border="0" cellpadding="0" cellspacing="0" class="example">
<tbody><tr valign="top"><td width="30" align="right">d.</td><td width="15"></td><td>in Macbeth <em>versus</em> on Letterman</td></tr></tbody></table></p>
</td></tr></tbody></table></p>
<!-- Footer to be used in all chapters -->
</a><div class="admonition-about-this-document admonition"><a name="lexicon_index_term">
<p class="first admonition-title">About this document...</p>
</a><p><a name="lexicon_index_term">UPDATED FOR NLTK 3.0.
This is a chapter from <em>Natural Language Processing with Python</em>,
by </a><a class="reference external" href="http://estive.net/">Steven Bird</a>, <a class="reference external" href="http://homepages.inf.ed.ac.uk/ewan/">Ewan Klein</a> and <a class="reference external" href="http://ed.loper.org/">Edward Loper</a>,
Copyright © 2014 the authors.
It is distributed with the <em>Natural Language Toolkit</em> [<tt class="doctest"><span class="pre">http://nltk.org/</span></tt>],
Version 3.0, under the terms of the
<em>Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License</em>
[<a class="reference external" href="http://creativecommons.org/licenses/by-nc-nd/3.0/us/">http://creativecommons.org/licenses/by-nc-nd/3.0/us/</a>].</p>
<p class="last">This document was built on
Mon 3 Nov 2014 11:04:10 PST</p>
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<h3><a class="anchor" id="index_q"></a>- q -</h3><ul>
<li>QCheckBoxSetting()
: <a class="el" href="classSideCar_1_1GUI_1_1QCheckBoxSetting.html#a6eecdc3bf5cf49079d37b5f05c7e6aeb">SideCar::GUI::QCheckBoxSetting</a>
</li>
<li>QColorSetting()
: <a class="el" href="classSideCar_1_1GUI_1_1QColorSetting.html#aaf4eeaf2f876c1b2807dbf0517884a5d">SideCar::GUI::QColorSetting</a>
</li>
<li>QComboBoxSetting()
: <a class="el" href="classSideCar_1_1GUI_1_1QComboBoxSetting.html#acb7c0c1c2874ac0ec1de787b9ba9e30c">SideCar::GUI::QComboBoxSetting</a>
</li>
<li>QDoubleSpinBoxSetting()
: <a class="el" href="classSideCar_1_1GUI_1_1QDoubleSpinBoxSetting.html#a43689c95dc6bd84912e18905bd513bb7">SideCar::GUI::QDoubleSpinBoxSetting</a>
</li>
<li>QSpinBoxSetting()
: <a class="el" href="classSideCar_1_1GUI_1_1QSpinBoxSetting.html#a1dc8720fbc3ac2d46ab83b4261747409">SideCar::GUI::QSpinBoxSetting</a>
</li>
<li>QTimeEditSetting()
: <a class="el" href="classSideCar_1_1GUI_1_1QTimeEditSetting.html#a0a3e24f862d4174fb9085cd6dab79200">SideCar::GUI::QTimeEditSetting</a>
</li>
<li>QtMonitor()
: <a class="el" href="classSideCar_1_1GUI_1_1QtMonitor.html#acabab2868702dfe82ed6c32a55f54120">SideCar::GUI::QtMonitor</a>
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| bradhowes/sidecar | docs/functions_func_q.html | HTML | mit | 6,152 |
<!DOCTYPE html>
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| otterthecat/poptart | test/index.html | HTML | mit | 1,105 |
<html>
<head>
<link href="https://v4-alpha.getbootstrap.com/dist/css/bootstrap.min.css" rel="stylesheet">
<style>
body {
padding-top: 2rem;
padding-bottom: 2rem;
}
h3, h4, h5 {
padding: 2rem 0 0.5rem 0;
}
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padding-left: 0;
margin-bottom: 0;
list-style-type: none;
}
</style>
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<body>
<div class="container">
{% block content %}
{% endblock %}
</div>
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| california-civic-data-coalition/django-calaccess-processed-data | example/toolbox/templates/base.html | HTML | mit | 479 |
---
layout: default
---
<div class="post">
<h1>{{ page.title }}</h1>
<span class="post-date">
<img class="img-icon" src="/public/images/iconmonstr-calendar-5-icon.svg"></img>{{ page.date | date_to_string }}
<img class="img-icon" src="/public/images/iconmonstr-user-icon.svg"></img>{{ page.author }}
<!--
<img class="img-icon" src="/public/images/iconmonstr-tags-3-icon.svg"></img>{% for categories in page.categories %} {{ categories }} {% if forloop.last != true %} {% endif %} {% endfor %}
-->
<img class="img-icon" src="/public/images/iconmonstr-speech-bubble-14-icon.svg"></img><a href="{{site.url}}{{ page.url }}#disqus_thread" data-disqus-identifier="{{ page.url }}"></a>
</span>
{{ content }}
</div>
<div id="disqus_thread"></div>
<script type="text/javascript">
/* * * CONFIGURATION VARIABLES: EDIT BEFORE PASTING INTO YOUR WEBPAGE * * */
var disqus_shortname = 'sotothe'; // required: replace example with your forum shortname
/* * * DON'T EDIT BELOW THIS LINE * * */
(function() {
var dsq = document.createElement('script'); dsq.type = 'text/javascript'; dsq.async = true;
dsq.src = '//' + disqus_shortname + '.disqus.com/embed.js';
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{% for post in site.related_posts limit:3 %}
<li>
<h3>
<a href="{{ post.url }}">
{{ post.title }}
<small>{{ post.date | date_to_string }}</small>
</a>
</h3>
</li>
{% endfor %}
</ul>
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-->
| sotothe/sotothe.github.io | _layouts/post.html | HTML | mit | 2,011 |
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
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| tliang1/Java-Practice | Practice/Intro-To-Java-8th-Ed-Daniel-Y.-Liang/Chapter-6/Chapter06P22/doc/main/package-use.html | HTML | mit | 3,660 |
<HTML><HEAD><TITLE>NSF Award Abstracts Links for awards_2000/awd_2000_89</TITLE><HEAD><BODY>
<A HREF=a0089117.txt>a0089117.txt</A><BR>
</BODY></HTML>
| camilldesmoulins/SearchEngine | Corpus/Part 3/awards_2000/awd_2000_89/links.html | HTML | mit | 150 |
<table width="90%" border="0"><tr><td><script>function openfile(url) {fullwin = window.open(url, "fulltext", "toolbar=no,location=no,directories=no,status=no,menubar=no,scrollbars=yes,resizable=yes");}</script><div class="layoutclass_pic"><div class="layoutclass_first_pic"><table class="ztable"><tr><th class="ztd1"><b>成語 </b></th><td class="ztd2">高節清風</td></tr>
<tr><th class="ztd1"><b>典故說明 </b></th><td class="ztd2"> 此處所列為「高風亮節」之典故說明，提供參考。</font> 「高風亮節」係由「高風」及「亮節」二語組合而成。「高風」見於《後漢書．卷二八下．馮衍傳》。馮衍，字敬通，東漢辭賦家，京兆杜陵人，生卒年不詳。少有奇才，博通群書。王莽時，諸公薦舉，馮衍辭不肯仕。新朝末年入更始政權，後與鮑永歸降光武帝；但光武帝怨衍遲不歸降，未予重用。後衍因與外戚交往，被免官歸里，撰〈顯志賦〉以自傷。賦中借史實以諷諭時政，借追慕古人而抒發其鬱抑不平。賦云：「沮先聖之成論兮，<img src=/cydic/dicword/c03981-001.jpg border=0 alt=* class=fontimg valign=center>名賢之高風。」是寫馮衍雖然傷己不能遇到堯舜這樣的明君，但自己依然保持著高尚的志節，不苟同這種世俗之見。「亮節」則見於晉．陸雲〈晉故豫章內史夏府君誄〉。陸雲（西元<font class="english_word">２</font><font class="english_word">６</font><font class="english_word">２</font><font class="english_word">∼</font><font class="english_word">３</font><font class="english_word">０</font><font class="english_word">３</font>），字士龍，晉吳郡人。與兄陸機齊名，時稱「二陸」。其文詞藻麗密，旨意深雅。他在好友豫章內史夏府君過世後，寫了一篇哀祭文。其中：「越殷自周，紹膺遺祉，亮節三恪，侯服千祀，悠悠訖茲，徽烈不巳。」是敘述好友生前美好的德行、偉大的功業。並以「亮節」一詞，形容故友的堅貞節操。後來這兩個詞語被合成「高風亮節」，用來形容人的品格高尚，氣節堅貞。<br></font></td></tr>
</td></tr></table></div> <!-- layoutclass_first_pic --><div class="layoutclass_second_pic"></div> <!-- layoutclass_second_pic --></div> <!-- layoutclass_pic --></td></tr></table>
| BuzzAcademy/idioms-moe-unformatted-data | all-data/4000-4999/4387-32.html | HTML | mit | 2,386 |
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css">
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<body ng-app="metadataapp" ng-cloak layout="column">
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| subhasisghosal/NDL_ErrorLogAnalysisPortal | Backup/reports.html | HTML | mit | 2,630 |
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<div class="modal-dialog">
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<label for="name">Your name</label>
<input required type="text" id="name" name="name" maxlength="255" autofocus >
</div>
<div class="col-lg-6">
<label for="email">Your email</label>
<input type="email" id="email" name="email" required pattern="[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,3}$" title="Use the following format '-@-.--' ">
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<label for="subject">Subject</label>
<div class="js_custom_select custom_select">
<select required class="custom_select__field" name="subject" id="subject" tabindex="-1">
<option value="General feedback">General feedback</option>
<option value="Current workflow of the portal">Current workflow of the portal</option>
<option value="Technical issues">Technical issues</option>
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<input class="custom_select__placeholder" type="text" value="General feedback" readonly>
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<li class="custom_select__item" data-value="General feedback">General feedback</li>
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| ticketmaster-api/ticketmaster-api.github.io | _includes/feedback.html | HTML | mit | 4,292 |
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