text_classification/textClassification_Notebook.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>Text-Classification-assignment</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>

<style type="text/css">
    /*!
*
* Twitter Bootstrap
*
*/
/*!
 * Bootstrap v3.3.7 (http://getbootstrap.com)
 * Copyright 2011-2016 Twitter, Inc.
 * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
 */
/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
  font-family: sans-serif;
  -ms-text-size-adjust: 100%;
  -webkit-text-size-adjust: 100%;
}
body {
  margin: 0;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
hgroup,
main,
menu,
nav,
section,
summary {
  display: block;
}
audio,
canvas,
progress,
video {
  display: inline-block;
  vertical-align: baseline;
}
audio:not([controls]) {
  display: none;
  height: 0;
}
[hidden],
template {
  display: none;
}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
  font-style: italic;
}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
  background: #ff0;
  color: #000;
}
small {
  font-size: 80%;
}
sub,
sup {
  font-size: 75%;
  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
  top: -0.5em;
}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
  overflow: hidden;
}
figure {
  margin: 1em 40px;
}
hr {
  box-sizing: content-box;
  height: 0;
}
pre {
  overflow: auto;
}
code,
kbd,
pre,
samp {
  font-family: monospace, monospace;
  font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
  color: inherit;
  font: inherit;
  margin: 0;
}
button {
  overflow: visible;
}
button,
select {
  text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
  -webkit-appearance: button;
  cursor: pointer;
}
button[disabled],
html input[disabled] {
  cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
  border: 0;
  padding: 0;
}
input {
  line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
  box-sizing: border-box;
  padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: textfield;
  box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
  -webkit-appearance: none;
}
fieldset {
  border: 1px solid #c0c0c0;
  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
}
legend {
  border: 0;
  padding: 0;
}
textarea {
  overflow: auto;
}
optgroup {
  font-weight: bold;
}
table {
  border-collapse: collapse;
  border-spacing: 0;
}
td,
th {
  padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
  *,
  *:before,
  *:after {
    background: transparent !important;
    color: #000 !important;
    box-shadow: none !important;
    text-shadow: none !important;
  }
  a,
  a:visited {
    text-decoration: underline;
  }
  a[href]:after {
    content: " (" attr(href) ")";
  }
  abbr[title]:after {
    content: " (" attr(title) ")";
  }
  a[href^="#"]:after,
  a[href^="javascript:"]:after {
    content: "";
  }
  pre,
  blockquote {
    border: 1px solid #999;
    page-break-inside: avoid;
  }
  thead {
    display: table-header-group;
  }
  tr,
  img {
    page-break-inside: avoid;
  }
  img {
    max-width: 100% !important;
  }
  p,
  h2,
  h3 {
    orphans: 3;
    widows: 3;
  }
  h2,
  h3 {
    page-break-after: avoid;
  }
  .navbar {
    display: none;
  }
  .btn > .caret,
  .dropup > .btn > .caret {
    border-top-color: #000 !important;
  }
  .label {
    border: 1px solid #000;
  }
  .table {
    border-collapse: collapse !important;
  }
  .table td,
  .table th {
    background-color: #fff !important;
  }
  .table-bordered th,
  .table-bordered td {
    border: 1px solid #ddd !important;
  }
}
@font-face {
  font-family: 'Glyphicons Halflings';
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
}
.glyphicon {
  position: relative;
  top: 1px;
  display: inline-block;
  font-family: 'Glyphicons Halflings';
  font-style: normal;
  font-weight: normal;
  line-height: 1;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
.glyphicon-asterisk:before {
  content: "\002a";
}
.glyphicon-plus:before {
  content: "\002b";
}
.glyphicon-euro:before,
.glyphicon-eur:before {
  content: "\20ac";
}
.glyphicon-minus:before {
  content: "\2212";
}
.glyphicon-cloud:before {
  content: "\2601";
}
.glyphicon-envelope:before {
  content: "\2709";
}
.glyphicon-pencil:before {
  content: "\270f";
}
.glyphicon-glass:before {
  content: "\e001";
}
.glyphicon-music:before {
  content: "\e002";
}
.glyphicon-search:before {
  content: "\e003";
}
.glyphicon-heart:before {
  content: "\e005";
}
.glyphicon-star:before {
  content: "\e006";
}
.glyphicon-star-empty:before {
  content: "\e007";
}
.glyphicon-user:before {
  content: "\e008";
}
.glyphicon-film:before {
  content: "\e009";
}
.glyphicon-th-large:before {
  content: "\e010";
}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
.glyphicon-remove:before {
  content: "\e014";
}
.glyphicon-zoom-in:before {
  content: "\e015";
}
.glyphicon-zoom-out:before {
  content: "\e016";
}
.glyphicon-off:before {
  content: "\e017";
}
.glyphicon-signal:before {
  content: "\e018";
}
.glyphicon-cog:before {
  content: "\e019";
}
.glyphicon-trash:before {
  content: "\e020";
}
.glyphicon-home:before {
  content: "\e021";
}
.glyphicon-file:before {
  content: "\e022";
}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
  content: "\e025";
}
.glyphicon-download:before {
  content: "\e026";
}
.glyphicon-upload:before {
  content: "\e027";
}
.glyphicon-inbox:before {
  content: "\e028";
}
.glyphicon-play-circle:before {
  content: "\e029";
}
.glyphicon-repeat:before {
  content: "\e030";
}
.glyphicon-refresh:before {
  content: "\e031";
}
.glyphicon-list-alt:before {
  content: "\e032";
}
.glyphicon-lock:before {
  content: "\e033";
}
.glyphicon-flag:before {
  content: "\e034";
}
.glyphicon-headphones:before {
  content: "\e035";
}
.glyphicon-volume-off:before {
  content: "\e036";
}
.glyphicon-volume-down:before {
  content: "\e037";
}
.glyphicon-volume-up:before {
  content: "\e038";
}
.glyphicon-qrcode:before {
  content: "\e039";
}
.glyphicon-barcode:before {
  content: "\e040";
}
.glyphicon-tag:before {
  content: "\e041";
}
.glyphicon-tags:before {
  content: "\e042";
}
.glyphicon-book:before {
  content: "\e043";
}
.glyphicon-bookmark:before {
  content: "\e044";
}
.glyphicon-print:before {
  content: "\e045";
}
.glyphicon-camera:before {
  content: "\e046";
}
.glyphicon-font:before {
  content: "\e047";
}
.glyphicon-bold:before {
  content: "\e048";
}
.glyphicon-italic:before {
  content: "\e049";
}
.glyphicon-text-height:before {
  content: "\e050";
}
.glyphicon-text-width:before {
  content: "\e051";
}
.glyphicon-align-left:before {
  content: "\e052";
}
.glyphicon-align-center:before {
  content: "\e053";
}
.glyphicon-align-right:before {
  content: "\e054";
}
.glyphicon-align-justify:before {
  content: "\e055";
}
.glyphicon-list:before {
  content: "\e056";
}
.glyphicon-indent-left:before {
  content: "\e057";
}
.glyphicon-indent-right:before {
  content: "\e058";
}
.glyphicon-facetime-video:before {
  content: "\e059";
}
.glyphicon-picture:before {
  content: "\e060";
}
.glyphicon-map-marker:before {
  content: "\e062";
}
.glyphicon-adjust:before {
  content: "\e063";
}
.glyphicon-tint:before {
  content: "\e064";
}
.glyphicon-edit:before {
  content: "\e065";
}
.glyphicon-share:before {
  content: "\e066";
}
.glyphicon-check:before {
  content: "\e067";
}
.glyphicon-move:before {
  content: "\e068";
}
.glyphicon-step-backward:before {
  content: "\e069";
}
.glyphicon-fast-backward:before {
  content: "\e070";
}
.glyphicon-backward:before {
  content: "\e071";
}
.glyphicon-play:before {
  content: "\e072";
}
.glyphicon-pause:before {
  content: "\e073";
}
.glyphicon-stop:before {
  content: "\e074";
}
.glyphicon-forward:before {
  content: "\e075";
}
.glyphicon-fast-forward:before {
  content: "\e076";
}
.glyphicon-step-forward:before {
  content: "\e077";
}
.glyphicon-eject:before {
  content: "\e078";
}
.glyphicon-chevron-left:before {
  content: "\e079";
}
.glyphicon-chevron-right:before {
  content: "\e080";
}
.glyphicon-plus-sign:before {
  content: "\e081";
}
.glyphicon-minus-sign:before {
  content: "\e082";
}
.glyphicon-remove-sign:before {
  content: "\e083";
}
.glyphicon-ok-sign:before {
  content: "\e084";
}
.glyphicon-question-sign:before {
  content: "\e085";
}
.glyphicon-info-sign:before {
  content: "\e086";
}
.glyphicon-screenshot:before {
  content: "\e087";
}
.glyphicon-remove-circle:before {
  content: "\e088";
}
.glyphicon-ok-circle:before {
  content: "\e089";
}
.glyphicon-ban-circle:before {
  content: "\e090";
}
.glyphicon-arrow-left:before {
  content: "\e091";
}
.glyphicon-arrow-right:before {
  content: "\e092";
}
.glyphicon-arrow-up:before {
  content: "\e093";
}
.glyphicon-arrow-down:before {
  content: "\e094";
}
.glyphicon-share-alt:before {
  content: "\e095";
}
.glyphicon-resize-full:before {
  content: "\e096";
}
.glyphicon-resize-small:before {
  content: "\e097";
}
.glyphicon-exclamation-sign:before {
  content: "\e101";
}
.glyphicon-gift:before {
  content: "\e102";
}
.glyphicon-leaf:before {
  content: "\e103";
}
.glyphicon-fire:before {
  content: "\e104";
}
.glyphicon-eye-open:before {
  content: "\e105";
}
.glyphicon-eye-close:before {
  content: "\e106";
}
.glyphicon-warning-sign:before {
  content: "\e107";
}
.glyphicon-plane:before {
  content: "\e108";
}
.glyphicon-calendar:before {
  content: "\e109";
}
.glyphicon-random:before {
  content: "\e110";
}
.glyphicon-comment:before {
  content: "\e111";
}
.glyphicon-magnet:before {
  content: "\e112";
}
.glyphicon-chevron-up:before {
  content: "\e113";
}
.glyphicon-chevron-down:before {
  content: "\e114";
}
.glyphicon-retweet:before {
  content: "\e115";
}
.glyphicon-shopping-cart:before {
  content: "\e116";
}
.glyphicon-folder-close:before {
  content: "\e117";
}
.glyphicon-folder-open:before {
  content: "\e118";
}
.glyphicon-resize-vertical:before {
  content: "\e119";
}
.glyphicon-resize-horizontal:before {
  content: "\e120";
}
.glyphicon-hdd:before {
  content: "\e121";
}
.glyphicon-bullhorn:before {
  content: "\e122";
}
.glyphicon-bell:before {
  content: "\e123";
}
.glyphicon-certificate:before {
  content: "\e124";
}
.glyphicon-thumbs-up:before {
  content: "\e125";
}
.glyphicon-thumbs-down:before {
  content: "\e126";
}
.glyphicon-hand-right:before {
  content: "\e127";
}
.glyphicon-hand-left:before {
  content: "\e128";
}
.glyphicon-hand-up:before {
  content: "\e129";
}
.glyphicon-hand-down:before {
  content: "\e130";
}
.glyphicon-circle-arrow-right:before {
  content: "\e131";
}
.glyphicon-circle-arrow-left:before {
  content: "\e132";
}
.glyphicon-circle-arrow-up:before {
  content: "\e133";
}
.glyphicon-circle-arrow-down:before {
  content: "\e134";
}
.glyphicon-globe:before {
  content: "\e135";
}
.glyphicon-wrench:before {
  content: "\e136";
}
.glyphicon-tasks:before {
  content: "\e137";
}
.glyphicon-filter:before {
  content: "\e138";
}
.glyphicon-briefcase:before {
  content: "\e139";
}
.glyphicon-fullscreen:before {
  content: "\e140";
}
.glyphicon-dashboard:before {
  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
  content: "\e143";
}
.glyphicon-link:before {
  content: "\e144";
}
.glyphicon-phone:before {
  content: "\e145";
}
.glyphicon-pushpin:before {
  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
  content: "\e149";
}
.glyphicon-sort:before {
  content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
  content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
  content: "\e154";
}
.glyphicon-sort-by-attributes:before {
  content: "\e155";
}
.glyphicon-sort-by-attributes-alt:before {
  content: "\e156";
}
.glyphicon-unchecked:before {
  content: "\e157";
}
.glyphicon-expand:before {
  content: "\e158";
}
.glyphicon-collapse-down:before {
  content: "\e159";
}
.glyphicon-collapse-up:before {
  content: "\e160";
}
.glyphicon-log-in:before {
  content: "\e161";
}
.glyphicon-flash:before {
  content: "\e162";
}
.glyphicon-log-out:before {
  content: "\e163";
}
.glyphicon-new-window:before {
  content: "\e164";
}
.glyphicon-record:before {
  content: "\e165";
}
.glyphicon-save:before {
  content: "\e166";
}
.glyphicon-open:before {
  content: "\e167";
}
.glyphicon-saved:before {
  content: "\e168";
}
.glyphicon-import:before {
  content: "\e169";
}
.glyphicon-export:before {
  content: "\e170";
}
.glyphicon-send:before {
  content: "\e171";
}
.glyphicon-floppy-disk:before {
  content: "\e172";
}
.glyphicon-floppy-saved:before {
  content: "\e173";
}
.glyphicon-floppy-remove:before {
  content: "\e174";
}
.glyphicon-floppy-save:before {
  content: "\e175";
}
.glyphicon-floppy-open:before {
  content: "\e176";
}
.glyphicon-credit-card:before {
  content: "\e177";
}
.glyphicon-transfer:before {
  content: "\e178";
}
.glyphicon-cutlery:before {
  content: "\e179";
}
.glyphicon-header:before {
  content: "\e180";
}
.glyphicon-compressed:before {
  content: "\e181";
}
.glyphicon-earphone:before {
  content: "\e182";
}
.glyphicon-phone-alt:before {
  content: "\e183";
}
.glyphicon-tower:before {
  content: "\e184";
}
.glyphicon-stats:before {
  content: "\e185";
}
.glyphicon-sd-video:before {
  content: "\e186";
}
.glyphicon-hd-video:before {
  content: "\e187";
}
.glyphicon-subtitles:before {
  content: "\e188";
}
.glyphicon-sound-stereo:before {
  content: "\e189";
}
.glyphicon-sound-dolby:before {
  content: "\e190";
}
.glyphicon-sound-5-1:before {
  content: "\e191";
}
.glyphicon-sound-6-1:before {
  content: "\e192";
}
.glyphicon-sound-7-1:before {
  content: "\e193";
}
.glyphicon-copyright-mark:before {
  content: "\e194";
}
.glyphicon-registration-mark:before {
  content: "\e195";
}
.glyphicon-cloud-download:before {
  content: "\e197";
}
.glyphicon-cloud-upload:before {
  content: "\e198";
}
.glyphicon-tree-conifer:before {
  content: "\e199";
}
.glyphicon-tree-deciduous:before {
  content: "\e200";
}
.glyphicon-cd:before {
  content: "\e201";
}
.glyphicon-save-file:before {
  content: "\e202";
}
.glyphicon-open-file:before {
  content: "\e203";
}
.glyphicon-level-up:before {
  content: "\e204";
}
.glyphicon-copy:before {
  content: "\e205";
}
.glyphicon-paste:before {
  content: "\e206";
}
.glyphicon-alert:before {
  content: "\e209";
}
.glyphicon-equalizer:before {
  content: "\e210";
}
.glyphicon-king:before {
  content: "\e211";
}
.glyphicon-queen:before {
  content: "\e212";
}
.glyphicon-pawn:before {
  content: "\e213";
}
.glyphicon-bishop:before {
  content: "\e214";
}
.glyphicon-knight:before {
  content: "\e215";
}
.glyphicon-baby-formula:before {
  content: "\e216";
}
.glyphicon-tent:before {
  content: "\26fa";
}
.glyphicon-blackboard:before {
  content: "\e218";
}
.glyphicon-bed:before {
  content: "\e219";
}
.glyphicon-apple:before {
  content: "\f8ff";
}
.glyphicon-erase:before {
  content: "\e221";
}
.glyphicon-hourglass:before {
  content: "\231b";
}
.glyphicon-lamp:before {
  content: "\e223";
}
.glyphicon-duplicate:before {
  content: "\e224";
}
.glyphicon-piggy-bank:before {
  content: "\e225";
}
.glyphicon-scissors:before {
  content: "\e226";
}
.glyphicon-bitcoin:before {
  content: "\e227";
}
.glyphicon-btc:before {
  content: "\e227";
}
.glyphicon-xbt:before {
  content: "\e227";
}
.glyphicon-yen:before {
  content: "\00a5";
}
.glyphicon-jpy:before {
  content: "\00a5";
}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
  content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
  content: "\e232";
}
.glyphicon-education:before {
  content: "\e233";
}
.glyphicon-option-horizontal:before {
  content: "\e234";
}
.glyphicon-option-vertical:before {
  content: "\e235";
}
.glyphicon-menu-hamburger:before {
  content: "\e236";
}
.glyphicon-modal-window:before {
  content: "\e237";
}
.glyphicon-oil:before {
  content: "\e238";
}
.glyphicon-grain:before {
  content: "\e239";
}
.glyphicon-sunglasses:before {
  content: "\e240";
}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
  content: "\e243";
}
.glyphicon-object-align-top:before {
  content: "\e244";
}
.glyphicon-object-align-bottom:before {
  content: "\e245";
}
.glyphicon-object-align-horizontal:before {
  content: "\e246";
}
.glyphicon-object-align-left:before {
  content: "\e247";
}
.glyphicon-object-align-vertical:before {
  content: "\e248";
}
.glyphicon-object-align-right:before {
  content: "\e249";
}
.glyphicon-triangle-right:before {
  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
@media (max-width: 991px) {
  #ipython_notebook {
    margin-left: 10px;
  }
}
[dir="rtl"] #ipython_notebook {
  float: right !important;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#login_widget {
  float: right;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  text-align: center;
  vertical-align: middle;
  display: inline;
  opacity: 0;
  z-index: 2;
  width: 12ex;
  margin-right: -12ex;
}
.alternate_upload .btn-upload {
  height: 22px;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
[dir="rtl"] #tabs li {
  float: right;
}
ul#tabs {
  margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
  margin-right: 0px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons {
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
  padding-top: 1px;
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
  float: right !important;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: baseline;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
#tree-selector {
  padding-right: 0px;
}
[dir="rtl"] #tree-selector a {
  float: right;
}
#button-select-all {
  min-width: 50px;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
[dir="rtl"] #new-menu {
  text-align: right;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
[dir="rtl"] #running .col-sm-8 {
  float: right !important;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
  font-weight: bold;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  border-left-width: 1px;
  padding-left: 5px;
  background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
  border-left-color: #90CAF9;
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected {
  border-color: #ababab;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
  div.cell.selected {
    border-color: transparent;
  }
}
div.cell.selected.jupyter-soft-selected {
  border-left-width: 0;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  padding: 0.4em;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
  /* .CodeMirror-lines */
  padding: 0;
  border: 0;
  border-radius: 0;
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  display: none;
}
.command-shortcut:before {
  content: "(command)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
    </style>
<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
.highlight .vm { color: #19177C } /* Name.Variable.Magic */
.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
    </style>
<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

    </style>


<style type="text/css">
/* Overrides of notebook CSS for static HTML export */
body {
  overflow: visible;
  padding: 8px;
}

div#notebook {
  overflow: visible;
  border-top: none;
}@media print {
  div.cell {
    display: block;
    page-break-inside: avoid;
  } 
  div.output_wrapper { 
    display: block;
    page-break-inside: avoid; 
  }
  div.output { 
    display: block;
    page-break-inside: avoid; 
  }
}
</style>

<!-- Custom stylesheet, it must be in the same directory as the html file -->
<link rel="stylesheet" href="custom.css">

<!-- Loading mathjax macro -->
<!-- Load mathjax -->
    <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_HTML"></script>
    <!-- MathJax configuration -->
    <script type="text/x-mathjax-config">
    MathJax.Hub.Config({
        tex2jax: {
            inlineMath: [ ['$','$'], ["\\(","\\)"] ],
            displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
            processEscapes: true,
            processEnvironments: true
        },
        // Center justify equations in code and markdown cells. Elsewhere
        // we use CSS to left justify single line equations in code cells.
        displayAlign: 'center',
        "HTML-CSS": {
            styles: {'.MathJax_Display': {"margin": 0}},
            linebreaks: { automatic: true }
        }
    });
    </script>
    <!-- End of mathjax configuration --></head>
<body>
  <div tabindex="-1" id="notebook" class="border-box-sizing">
    <div class="container" id="notebook-container">

<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="2nd-assignment-(text-classification)">2nd assignment (text classification)<a class="anchor-link" href="#2nd-assignment-(text-classification)">&#182;</a></h2><ul>
<li>Dimitris Georgiou - DS3517004</li>
<li>Stratos Gounidellis - DS3517005</li>
<li>Natasa Farmaki - DS3517018</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[1]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># import necessary libraries</span>

<span class="kn">import</span> <span class="nn">csv</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">precision_recall_curve</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">average_precision_score</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">sklearn.decomposition</span> <span class="k">import</span> <span class="n">TruncatedSVD</span>
<span class="kn">from</span> <span class="nn">sklearn.feature_extraction.text</span> <span class="k">import</span> <span class="n">TfidfVectorizer</span>
<span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestClassifier</span><span class="p">,</span> <span class="n">ExtraTreesClassifier</span>
<span class="kn">from</span> <span class="nn">sklearn.feature_selection</span> <span class="k">import</span> <span class="n">SelectKBest</span><span class="p">,</span> <span class="n">f_classif</span><span class="p">,</span> <span class="n">SelectFromModel</span>
<span class="kn">from</span> <span class="nn">sklearn.linear_model.logistic</span> <span class="k">import</span> <span class="n">LogisticRegression</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">train_test_split</span><span class="p">,</span> <span class="n">cross_val_score</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">preprocessing</span>
<span class="kn">from</span> <span class="nn">matplotlib.font_manager</span> <span class="k">import</span> <span class="n">FontProperties</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">roc_curve</span><span class="p">,</span> <span class="n">auc</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">os</span> <span class="k">import</span> <span class="n">listdir</span>
<span class="kn">from</span> <span class="nn">os.path</span> <span class="k">import</span> <span class="n">isfile</span><span class="p">,</span> <span class="n">join</span>
<span class="kn">from</span> <span class="nn">scipy.sparse</span> <span class="k">import</span> <span class="n">vstack</span><span class="p">,</span> <span class="n">hstack</span>
<span class="kn">from</span> <span class="nn">scipy</span> <span class="k">import</span> <span class="n">sparse</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">GridSearchCV</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">confusion_matrix</span>
<span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="k">import</span> <span class="n">LabelEncoder</span><span class="p">,</span> <span class="n">MinMaxScaler</span><span class="p">,</span> <span class="n">StandardScaler</span>
<span class="kn">from</span> <span class="nn">sklearn.naive_bayes</span> <span class="k">import</span> <span class="n">GaussianNB</span>
<span class="o">%</span><span class="k">matplotlib</span> inline
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>The Enron Corpus is a large database of over 600,000 emails generated by 158 employees of the Enron Corporation and acquired by the Federal Energy Regulatory Commission during its investigation after the company's collapse.</p>
<p>The Enron data was originally collected at Enron Corporation headquarters in Houston during two weeks in May 2002 by Joe Bartling, a litigation support and data analysis contractor working for Aspen Systems, now Lockheed Martin, whom the Federal Energy Regulatory Commission (FERC) had hired to preserve and collect the vast amounts of data in the wake of the Enron Bankruptcy in December 2001. In addition to the Enron employee emails, all of Enron's enterprise database systems, hosted in Oracle databases on Sun Microsystems servers, were also captured and preserved including its online energy trading platform, EnronOnline.</p>
<p>In the current subset we used a subset of the above dataset with 5172 pre-processed emails (3672 legitimate emails and 1500 spam emails). That subset can be found <a href="http://nlp.cs.aueb.gr/software_and_datasets/Enron-Spam/preprocessed/enron1.tar.gz">here</a>.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[2]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">ham_path</span> <span class="o">=</span> <span class="s2">&quot;enron1</span><span class="se">\\</span><span class="s2">ham&quot;</span>
<span class="n">spam_path</span><span class="o">=</span><span class="s2">&quot;enron1</span><span class="se">\\</span><span class="s2">spam&quot;</span>
<span class="n">onlyfiles</span> <span class="o">=</span> <span class="p">[</span><span class="n">f</span> <span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="n">listdir</span><span class="p">(</span><span class="n">ham_path</span><span class="p">)</span> <span class="k">if</span> <span class="n">isfile</span><span class="p">(</span><span class="n">join</span><span class="p">(</span><span class="n">ham_path</span><span class="p">,</span> <span class="n">f</span><span class="p">))]</span>
<span class="n">messages</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;label&quot;</span><span class="p">,</span> <span class="s2">&quot;message&quot;</span><span class="p">])</span>
<span class="k">for</span> <span class="n">mail</span> <span class="ow">in</span> <span class="n">onlyfiles</span><span class="p">:</span>
    <span class="n">file</span> <span class="o">=</span> <span class="nb">open</span><span class="p">(</span><span class="n">ham_path</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\\</span><span class="s2">&quot;</span> <span class="o">+</span> <span class="n">mail</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">)</span> 
    <span class="n">messages</span> <span class="o">=</span> <span class="n">messages</span><span class="o">.</span><span class="n">append</span><span class="p">({</span><span class="s2">&quot;label&quot;</span><span class="p">:</span> <span class="s1">&#39;ham&#39;</span> <span class="p">,</span> <span class="s2">&quot;message&quot;</span><span class="p">:</span> <span class="n">file</span><span class="o">.</span><span class="n">read</span><span class="p">()},</span>
                               <span class="n">ignore_index</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Legitimate emails:&quot;</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">onlyfiles</span><span class="p">))</span>
        
<span class="n">onlyfiles</span> <span class="o">=</span> <span class="p">[</span><span class="n">f</span> <span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="n">listdir</span><span class="p">(</span><span class="n">spam_path</span><span class="p">)</span> <span class="k">if</span> <span class="n">isfile</span><span class="p">(</span><span class="n">join</span><span class="p">(</span><span class="n">spam_path</span><span class="p">,</span> <span class="n">f</span><span class="p">))]</span>
<span class="k">for</span> <span class="n">mail</span> <span class="ow">in</span> <span class="n">onlyfiles</span><span class="p">:</span>
    <span class="n">file</span> <span class="o">=</span> <span class="nb">open</span><span class="p">(</span><span class="n">spam_path</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\\</span><span class="s2">&quot;</span> <span class="o">+</span> <span class="n">mail</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">,</span> <span class="n">errors</span><span class="o">=</span><span class="s1">&#39;ignore&#39;</span><span class="p">)</span> 
    <span class="n">messages</span> <span class="o">=</span> <span class="n">messages</span><span class="o">.</span><span class="n">append</span><span class="p">({</span><span class="s2">&quot;label&quot;</span><span class="p">:</span> <span class="s1">&#39;spam&#39;</span> <span class="p">,</span> <span class="s2">&quot;message&quot;</span><span class="p">:</span> <span class="n">file</span><span class="o">.</span><span class="n">read</span><span class="p">()},</span>
                               <span class="n">ignore_index</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Spam emails:&quot;</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">onlyfiles</span><span class="p">))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Legitimate emails: 3672
Spam emails: 1500
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Split the dataset into training and test set with test size equal to the thirty percent (30%) of the initial dataset (3620 training data and 1552 test data). Additionally, the label is encoded with values 0 and 1, with 0 standing for "ham" and 1 standing for "spam".</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[3]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">msg_train</span><span class="p">,</span> <span class="n">msg_test</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">label_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">messages</span><span class="p">[</span><span class="s1">&#39;message&#39;</span><span class="p">],</span>
                                                                <span class="n">messages</span><span class="p">[</span><span class="s1">&#39;label&#39;</span><span class="p">],</span>
                                                                <span class="n">test_size</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span>
                                                                <span class="n">random_state</span><span class="o">=</span><span class="mi">2018</span><span class="p">)</span>

<span class="n">le</span> <span class="o">=</span> <span class="n">preprocessing</span><span class="o">.</span><span class="n">LabelEncoder</span><span class="p">()</span>
<span class="n">le</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">label_train</span><span class="p">)</span>
<span class="n">label_train</span> <span class="o">=</span> <span class="n">le</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">label_train</span><span class="p">)</span>
<span class="n">label_test</span> <span class="o">=</span> <span class="n">le</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">label_test</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Convert the collection of the to a sparse matrix of TF-IDF features. We use unigrams, bigrams and trigrams. When building the vocabulary ignore terms that have a document frequency strictly lower than the given threshold, i.e. 10 in our case. This value is also called cut-off in the literature. Apart from the TF-IDF features we utilize also the length of each email as a feature.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[4]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># smooth_idf=False -&gt; SOS not working properly</span>
<span class="n">vectorizer</span> <span class="o">=</span> <span class="n">TfidfVectorizer</span><span class="p">(</span><span class="n">ngram_range</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">),</span> <span class="n">stop_words</span><span class="o">=</span><span class="s1">&#39;english&#39;</span><span class="p">,</span>
                             <span class="n">min_df</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>

<span class="n">X_train</span> <span class="o">=</span> <span class="n">vectorizer</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">msg_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">vectorizer</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">msg_test</span><span class="p">)</span>

<span class="n">msg_train_len</span> <span class="o">=</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">message</span><span class="p">)</span> <span class="k">for</span> <span class="n">message</span> <span class="ow">in</span> <span class="n">msg_train</span><span class="p">]</span>
<span class="n">msg_test_len</span> <span class="o">=</span> <span class="p">[</span><span class="nb">len</span><span class="p">(</span><span class="n">message</span><span class="p">)</span> <span class="k">for</span> <span class="n">message</span> <span class="ow">in</span> <span class="n">msg_test</span><span class="p">]</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">hstack</span><span class="p">((</span><span class="n">X_train</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">msg_train_len</span><span class="p">)[:,</span> <span class="kc">None</span><span class="p">]))</span><span class="o">.</span><span class="n">A</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">hstack</span><span class="p">((</span><span class="n">X_test</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">msg_test_len</span><span class="p">)[:,</span> <span class="kc">None</span><span class="p">]))</span><span class="o">.</span><span class="n">A</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Normalize the features to be between -1 and 1. This is a significant pre-processing step especially for the SVD method following later.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[5]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">normalizer</span> <span class="o">=</span> <span class="n">MinMaxScaler</span><span class="p">(</span><span class="n">feature_range</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">))</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">normalizer</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">normalizer</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Determine the most significant features after performing Random Forest Classifier on the data. Keep the 20 most important features, according to their significance derived from the algorithm. In addition, select features according to the k highest scores. As score is used the f_classif. This is a scoring function to be used in a feature seletion procedure, not a free standing feature selection procedure.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[6]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">clfRandomForest</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">2018</span><span class="p">)</span>
<span class="n">clfRandomForest</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">)</span>
<span class="n">importantFeat</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">clfRandomForest</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">,</span>
                             <span class="n">index</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">X_train</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]),</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;Importance&quot;</span><span class="p">])</span>
<span class="n">top10Random</span> <span class="o">=</span> <span class="n">importantFeat</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s2">&quot;Importance&quot;</span><span class="p">,</span>
                                        <span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span><span class="o">.</span><span class="n">index</span>

<span class="n">X_score</span> <span class="o">=</span> <span class="n">SelectKBest</span><span class="p">(</span><span class="n">score_func</span><span class="o">=</span><span class="n">f_classif</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="s1">&#39;all&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">)</span>
<span class="n">feature_scores</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span>
        <span class="s1">&#39;feature&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">X_train</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]),</span>
        <span class="s1">&#39;score&#39;</span><span class="p">:</span> <span class="n">X_score</span><span class="o">.</span><span class="n">scores_</span>
<span class="p">})</span>
<span class="n">top10KBest</span> <span class="o">=</span> <span class="n">feature_scores</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s1">&#39;score&#39;</span><span class="p">,</span>
                                        <span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">20</span><span class="p">)[</span><span class="s1">&#39;feature&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>

<span class="n">topFeatures_ind</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">hstack</span><span class="p">([</span><span class="n">top10Random</span><span class="p">,</span> <span class="n">top10KBest</span><span class="p">]))</span>
<span class="n">topFeatures_train</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">[:,</span> <span class="nb">list</span><span class="p">(</span><span class="n">topFeatures_ind</span><span class="p">)]</span>
<span class="n">topFeatures_test</span> <span class="o">=</span> <span class="n">X_test</span><span class="p">[:,</span> <span class="nb">list</span><span class="p">(</span><span class="n">topFeatures_ind</span><span class="p">)]</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Moreover, we apply SVD on the TF-IDF matrix. More specifically, in linear algebra, the singular-value decomposition (SVD) is a factorization of a real or complex matrix. It is the generalization of the eigendecomposition of a positive semidefinite normal matrix (for example, a symmetric matrix with positive eigenvalues) to any m X n matrix via an extension of the polar decomposition. It has many useful applications in signal processing and statistics. We select the number of components to keep based on the variance explained. Indeed, we keep enough components to explain at least 80% of the variance.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[7]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">select_features_svd</span><span class="p">(</span><span class="n">train_X</span><span class="p">,</span> <span class="n">test_X</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
    <span class="n">selector</span> <span class="o">=</span> <span class="n">TruncatedSVD</span><span class="p">(</span><span class="n">n_components</span><span class="o">=</span><span class="n">k</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">1989</span><span class="p">)</span>
    <span class="n">selector</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train_X</span><span class="p">)</span>
    <span class="n">train_X</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">train_X</span><span class="p">)</span>
    <span class="n">test_X</span> <span class="o">=</span> <span class="n">selector</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">test_X</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">train_X</span><span class="p">,</span> <span class="n">test_X</span>


<span class="k">def</span> <span class="nf">select_n_components</span><span class="p">(</span><span class="n">var_ratio</span><span class="p">,</span> <span class="n">goal_var</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
    <span class="c1"># Set initial variance explained so far</span>
    <span class="n">total_variance</span> <span class="o">=</span> <span class="mf">0.0</span>

    <span class="c1"># Set initial number of features</span>
    <span class="n">n_components</span> <span class="o">=</span> <span class="mi">0</span>

    <span class="c1"># For the explained variance of each feature:</span>
    <span class="k">for</span> <span class="n">explained_variance</span> <span class="ow">in</span> <span class="n">var_ratio</span><span class="p">:</span>

        <span class="c1"># Add the explained variance to the total</span>
        <span class="n">total_variance</span> <span class="o">+=</span> <span class="n">explained_variance</span>

        <span class="c1"># Add one to the number of components</span>
        <span class="n">n_components</span> <span class="o">+=</span> <span class="mi">1</span>

        <span class="c1"># If we reach our goal level of explained variance</span>
        <span class="k">if</span> <span class="n">total_variance</span> <span class="o">&gt;=</span> <span class="n">goal_var</span><span class="p">:</span>
            <span class="c1"># End the loop</span>
            <span class="k">break</span>

    <span class="c1"># Return the number of components</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Total variance:&quot;</span><span class="p">,</span> <span class="n">total_variance</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Number of components:&quot;</span><span class="p">,</span> <span class="n">n_components</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">n_components</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[8]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tsvd</span> <span class="o">=</span> <span class="n">TruncatedSVD</span><span class="p">(</span><span class="n">n_components</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">2018</span><span class="p">)</span>
<span class="n">X_tsvd</span> <span class="o">=</span> <span class="n">tsvd</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">tsvd_var_ratios</span> <span class="o">=</span> <span class="n">tsvd</span><span class="o">.</span><span class="n">explained_variance_ratio_</span>

<span class="n">k</span> <span class="o">=</span> <span class="n">select_n_components</span><span class="p">(</span><span class="n">tsvd_var_ratios</span><span class="p">,</span> <span class="mf">0.80</span><span class="p">)</span>

<span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span> <span class="o">=</span> <span class="n">select_features_svd</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Total variance: 0.800075595578
Number of components: 684
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Combine the SVD components with the features selected with the two methods mentioned above. The final number of features used to predict the label of the email is 715.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[9]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_train</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">hstack</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">X_train</span><span class="p">),</span> <span class="n">topFeatures_train</span><span class="p">))</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">hstack</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">X_test</span><span class="p">),</span> <span class="n">topFeatures_test</span><span class="p">))</span>

<span class="n">X_train</span> <span class="o">=</span> <span class="n">sparse</span><span class="o">.</span><span class="n">csr_matrix</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span> <span class="o">=</span> <span class="n">sparse</span><span class="o">.</span><span class="n">csr_matrix</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">X_train</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">X_test</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>(3620, 715)
(1552, 715)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Helper-functions">Helper functions<a class="anchor-link" href="#Helper-functions">&#182;</a></h3>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Compute Receiver operating characteristic. In statistics, a receiver operating characteristic curve, i.e. ROC curve, is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied.
The ROC curve is created by plotting the true positive rate (TPR) against the false positive rate (FPR) at various threshold settings.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[10]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">roc_curve_plot</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">):</span>
    <span class="n">false_positive_rate</span><span class="p">,</span> <span class="n">recall</span><span class="p">,</span> <span class="n">thresholds</span> <span class="o">=</span> <span class="n">roc_curve</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span>
                                                        <span class="n">predictions</span><span class="p">)</span>
    <span class="n">roc_auc</span> <span class="o">=</span> <span class="n">auc</span><span class="p">(</span><span class="n">false_positive_rate</span><span class="p">,</span> <span class="n">recall</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Receiver Operating Characteristic&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">false_positive_rate</span><span class="p">,</span> <span class="n">recall</span><span class="p">,</span> <span class="s1">&#39;b&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;AUC = </span><span class="si">%0.2f</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="n">roc_auc</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">&#39;lower right&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="s1">&#39;r--&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Recall&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Fall-out&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Compute confusion matrix to evaluate the accuracy of a classification. In the field of machine learning and specifically the problem of statistical classification, a confusion matrix, also known as an error matrix,is a specific table layout that allows visualization of the performance of an algorithm, typically a supervised learning one (in unsupervised learning it is usually called a matching matrix). Each row of the matrix represents the instances in a predicted class while each column represents the instances in an actual class (or vice versa).</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[11]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">conf_matrix</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">):</span>
    <span class="n">confusion</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">confusion</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">matshow</span><span class="p">(</span><span class="n">confusion</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Confusion matrix&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">()</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;True label&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Predicted label&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Compute metrics (f1-score &amp; accuracy) for the classifier as it is trained in an increasing number of training data. The metrics will be later used to draw the learning curves.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[12]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">benchmark</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">train_X</span><span class="p">,</span> <span class="n">train_y</span><span class="p">,</span> <span class="n">test_X</span><span class="p">,</span> <span class="n">test_y</span><span class="p">):</span>
    <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train_X</span><span class="p">,</span> <span class="n">train_y</span><span class="p">)</span>
    <span class="n">pred</span> <span class="o">=</span> <span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_X</span><span class="p">)</span>
    <span class="n">f1</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">f1_score</span><span class="p">(</span><span class="n">test_y</span><span class="p">,</span> <span class="n">pred</span><span class="p">,</span> <span class="n">average</span><span class="o">=</span><span class="s1">&#39;weighted&#39;</span><span class="p">)</span>
    <span class="n">accuracy</span> <span class="o">=</span> <span class="n">metrics</span><span class="o">.</span><span class="n">accuracy_score</span><span class="p">(</span><span class="n">test_y</span><span class="p">,</span> <span class="n">pred</span><span class="p">)</span>
    <span class="n">result</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;f1&#39;</span> <span class="p">:</span> <span class="n">f1</span><span class="p">,</span> <span class="s1">&#39;accuracy&#39;</span> <span class="p">:</span> <span class="n">accuracy</span><span class="p">,</span> <span class="s1">&#39;train size&#39;</span> <span class="p">:</span> <span class="nb">len</span><span class="p">(</span><span class="n">train_y</span><span class="p">),</span>
              <span class="s1">&#39;test size&#39;</span> <span class="p">:</span> <span class="nb">len</span><span class="p">(</span><span class="n">test_y</span><span class="p">),</span> <span class="s1">&#39;predictions&#39;</span><span class="p">:</span> <span class="n">pred</span> <span class="p">}</span>
    <span class="k">return</span> <span class="n">result</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Compute the metrics for all the training phases of the classifier. Both accuracy and f1-score are used as metrics because the dataset is characterised by the class imbalance problem, and f1-score takes into account also precision and recall, which can be more valid metrics for our case.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[13]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">calc_metrics</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">label_test</span><span class="p">):</span>
    <span class="n">train_x_s_s</span><span class="p">,</span> <span class="n">train_y_s_s</span> <span class="o">=</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span>
    <span class="n">test_x_s_s</span><span class="p">,</span> <span class="n">test_y_s_s</span> <span class="o">=</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">label_test</span>
    
    <span class="n">results</span> <span class="o">=</span> <span class="p">{}</span>
    <span class="n">results</span><span class="p">[</span><span class="s1">&#39;train_size&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_test_acc&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_train_acc&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>

    <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_test_f1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_train_f1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>

    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">11</span><span class="p">):</span>
        <span class="k">if</span><span class="p">(</span><span class="n">i</span><span class="o">==</span><span class="mi">10</span><span class="p">):</span>
            <span class="n">train_x_part</span> <span class="o">=</span> <span class="n">train_x_s_s</span>
            <span class="n">train_y_part</span> <span class="o">=</span> <span class="n">train_y_s_s</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">to</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">i</span><span class="o">*</span><span class="p">(</span><span class="n">train_x_s_s</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">/</span><span class="mi">10</span><span class="p">))</span>
            <span class="n">train_x_part</span> <span class="o">=</span> <span class="n">train_x_s_s</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span> <span class="n">to</span><span class="p">,</span> <span class="p">:]</span>
            <span class="n">train_y_part</span> <span class="o">=</span> <span class="n">train_y_s_s</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span> <span class="n">to</span><span class="p">]</span>

        <span class="nb">print</span><span class="p">(</span><span class="n">train_x_part</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
        <span class="n">results</span><span class="p">[</span><span class="s1">&#39;train_size&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">train_x_part</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>

        <span class="n">result</span> <span class="o">=</span> <span class="n">benchmark</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">train_x_part</span><span class="p">,</span> <span class="n">train_y_part</span><span class="p">,</span> 
                           <span class="n">test_x_s_s</span><span class="p">,</span> <span class="n">test_y_s_s</span><span class="p">)</span>

        <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_test_acc&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>
        <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_test_f1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s1">&#39;f1&#39;</span><span class="p">])</span>
        <span class="n">result</span> <span class="o">=</span> <span class="n">benchmark</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">train_x_part</span><span class="p">,</span> <span class="n">train_y_part</span><span class="p">,</span> 
                           <span class="n">train_x_part</span><span class="p">,</span> <span class="n">train_y_part</span><span class="p">)</span>

        <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_train_acc&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>
        <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_train_f1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s1">&#39;f1&#39;</span><span class="p">])</span>
    <span class="k">return</span> <span class="n">results</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Plot the learning curves. A learning curve conventionally depicts improvement in performance on the vertical axis when there are changes in another parameter (on the horizontal axis), such as training set size (in machine learning). In our case, on the vertical axis the learning curves depict f1-score/accuracy and on the horizontal axis the number of the training data.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[14]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">learning_curves</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="n">metric</span><span class="p">,</span> <span class="n">method</span><span class="p">):</span>
    <span class="n">fontP</span> <span class="o">=</span> <span class="n">FontProperties</span><span class="p">()</span>
    <span class="n">fontP</span><span class="o">.</span><span class="n">set_size</span><span class="p">(</span><span class="s1">&#39;small&#39;</span><span class="p">)</span>
    <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
    <span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s1">&#39;Learning Curves - &#39;</span> <span class="o">+</span> <span class="n">method</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">17</span><span class="p">)</span>
    <span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
    <span class="n">ax</span><span class="o">.</span><span class="n">axis</span><span class="p">([</span><span class="mi">300</span><span class="p">,</span> <span class="mi">3800</span><span class="p">,</span> <span class="mf">0.8</span><span class="p">,</span> <span class="mf">1.1</span><span class="p">])</span>
    <span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s2">&quot;K-Nearest-Neighbors&quot;</span><span class="p">:</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">axis</span><span class="p">([</span><span class="mi">300</span><span class="p">,</span> <span class="mi">3800</span><span class="p">,</span> <span class="mf">0.4</span><span class="p">,</span> <span class="mf">1.1</span><span class="p">])</span>
    <span class="k">if</span> <span class="n">metric</span> <span class="o">==</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">:</span>
        <span class="n">line_up</span><span class="p">,</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">results</span><span class="p">[</span><span class="s1">&#39;train_size&#39;</span><span class="p">],</span> <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_train_acc&#39;</span><span class="p">],</span>
                           <span class="s1">&#39;o-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Accuracy on Train&#39;</span><span class="p">)</span>
        <span class="n">line_down</span><span class="p">,</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">results</span><span class="p">[</span><span class="s1">&#39;train_size&#39;</span><span class="p">],</span> <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_test_acc&#39;</span><span class="p">],</span>
                             <span class="s1">&#39;o-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Accuracy on Test&#39;</span><span class="p">)</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Accuracy&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">13</span><span class="p">)</span>

        <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">([</span><span class="n">line_up</span><span class="p">,</span> <span class="n">line_down</span><span class="p">],</span> <span class="p">[</span><span class="s1">&#39;Accuracy on Train&#39;</span><span class="p">,</span> <span class="s1">&#39;Accuracy on Test&#39;</span><span class="p">],</span>
                   <span class="n">prop</span><span class="o">=</span><span class="n">fontP</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">line_up</span><span class="p">,</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">results</span><span class="p">[</span><span class="s1">&#39;train_size&#39;</span><span class="p">],</span> <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_train_f1&#39;</span><span class="p">],</span>
                           <span class="s1">&#39;o-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;F1-score on Train&#39;</span><span class="p">)</span>
        <span class="n">line_down</span><span class="p">,</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">results</span><span class="p">[</span><span class="s1">&#39;train_size&#39;</span><span class="p">],</span> <span class="n">results</span><span class="p">[</span><span class="s1">&#39;on_test_f1&#39;</span><span class="p">],</span>
                             <span class="s1">&#39;o-&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;F1-score on Test&#39;</span><span class="p">)</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;F1-score&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">13</span><span class="p">)</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">([</span><span class="n">line_up</span><span class="p">,</span> <span class="n">line_down</span><span class="p">],</span> <span class="p">[</span><span class="s1">&#39;F1-score on Train&#39;</span><span class="p">,</span> <span class="s1">&#39;F1-score on Test&#39;</span><span class="p">],</span>
                   <span class="n">prop</span><span class="o">=</span><span class="n">fontP</span><span class="p">)</span>

    <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Number of training instances&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">13</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Plot precision-recall curve. The trade-off between precision and recall can be observed using the precision-recall curve, and an appropriate balance between the two obtained. Depending on the requirement (high precision at the cost of recall, or high recall with lower precision), an appropriate algorithm can be chosen.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[15]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">prec_rec_curve</span><span class="p">(</span><span class="n">X_test</span><span class="p">,</span> <span class="n">label_test</span><span class="p">,</span> <span class="n">type_classifier</span><span class="p">,</span> <span class="n">classifier</span><span class="p">):</span>

    <span class="k">if</span> <span class="n">type_classifier</span> <span class="o">==</span> <span class="s2">&quot;decision&quot;</span><span class="p">:</span>
        <span class="n">y_score</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">decision_function</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">y_score</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">predict_proba</span><span class="p">(</span><span class="n">X_test</span><span class="p">)[:,</span> <span class="mi">1</span><span class="p">]</span>

    <span class="n">average_precision</span> <span class="o">=</span> <span class="n">average_precision_score</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">y_score</span><span class="p">)</span>

    <span class="n">precision</span><span class="p">,</span> <span class="n">recall</span><span class="p">,</span> <span class="n">thresholds</span> <span class="o">=</span> <span class="n">precision_recall_curve</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">y_score</span><span class="p">)</span>

    <span class="n">plt</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">recall</span><span class="p">,</span> <span class="n">precision</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;b&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span>
             <span class="n">where</span><span class="o">=</span><span class="s1">&#39;post&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">fill_between</span><span class="p">(</span><span class="n">recall</span><span class="p">,</span> <span class="n">precision</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="s1">&#39;post&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span>
                     <span class="n">color</span><span class="o">=</span><span class="s1">&#39;b&#39;</span><span class="p">)</span>

    <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Recall&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Precision&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.05</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;2-class Precision-Recall curve: AP=</span><span class="si">{0:0.2f}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
              <span class="n">average_precision</span><span class="p">))</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Classifiers">Classifiers<a class="anchor-link" href="#Classifiers">&#182;</a></h3>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="1.--Baseline-Classifier">1.  Baseline Classifier<a class="anchor-link" href="#1.--Baseline-Classifier">&#182;</a></h3>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>To get a clear picture of a classifier’s performance, it is common to compare its accuracy or error rate to those of a simplistic “baseline” approach. In our case, we used the most simple classifier. As stated above the dataset is imbalanced, which means that the legitimate messages are far more than the spam messages. So the most simple classifier would just classify all emails as legitimate. In other words, legitimate messages are (correctly) never blocked, and spam messages (mistakenly) always pass.</p>
<p>Additionally, since the dataset is imbalanced we should employ an accurate and reliable metric to compare each of the implemented classifiers with the baseline classifier. Thus, we calculated the weighted versions of accuracy and error for the baseline classifier giving more weight to the number of the legitimate emails. In our case, we set the weight to two (2).</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[16]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">nspam</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">label_test</span><span class="p">[</span><span class="n">label_test</span> <span class="o">==</span> <span class="mi">1</span><span class="p">])</span>
<span class="n">nham</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">label_test</span><span class="p">[</span><span class="n">label_test</span> <span class="o">==</span> <span class="mi">0</span><span class="p">])</span>

<span class="n">l</span> <span class="o">=</span> <span class="mi">2</span>
<span class="n">wb_accuracy</span> <span class="o">=</span> <span class="p">(</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">/</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">+</span> <span class="n">nspam</span><span class="p">)</span>
<span class="n">wb_error</span> <span class="o">=</span> <span class="n">nspam</span> <span class="o">/</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">+</span> <span class="n">nspam</span><span class="p">)</span>

<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Accuracy (baseline classifier):&quot;</span><span class="p">,</span> <span class="n">wb_accuracy</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Error (baseline classifier):&quot;</span><span class="p">,</span> <span class="n">wb_error</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Accuracy (baseline classifier): 0.8352720450281426
Error (baseline classifier): 0.1647279549718574
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="2.-Logistic-Regression">2. Logistic Regression<a class="anchor-link" href="#2.-Logistic-Regression">&#182;</a></h3><p>Build a logistic regression model. Use grid search and cross validation in order to calculate the best hyperparameters for the classifier.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[17]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Create logistic regression</span>
<span class="n">logistic</span> <span class="o">=</span> <span class="n">LogisticRegression</span><span class="p">()</span>

<span class="c1"># Create regularization hyperparameter space</span>
<span class="n">C</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.01</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">100</span><span class="p">,</span> <span class="mi">1000</span><span class="p">]</span>

<span class="c1"># Create hyperparameter options</span>
<span class="n">hyperparameters</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">C</span><span class="o">=</span><span class="n">C</span><span class="p">)</span>

<span class="c1"># Create grid search using 5-fold cross validation</span>
<span class="n">clf</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">logistic</span><span class="p">,</span> <span class="n">hyperparameters</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>

<span class="n">classifier</span> <span class="o">=</span> <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Evaluate accuracy, precision, recall and f1-score of the logistic score by cross-validation.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[18]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">scores</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;Accuracy&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">scores</span><span class="p">),</span> <span class="n">scores</span><span class="p">)</span>
<span class="n">precisions</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span>
                             <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;precision&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;Precision&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">precisions</span><span class="p">),</span> <span class="n">precisions</span><span class="p">)</span>
<span class="n">recalls</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span>
                          <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;recall&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;Recall&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">recalls</span><span class="p">),</span> <span class="n">recalls</span><span class="p">)</span>
<span class="n">f1s</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;f1&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;F1&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">f1s</span><span class="p">),</span> <span class="n">f1s</span><span class="p">)</span>

<span class="n">predictions</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Accuracy 0.978172580063 [ 0.98344828  0.9820442   0.97790055  0.97928177  0.96818811]
Precision 0.951441872455 [ 0.97183099  0.95022624  0.95794393  0.94570136  0.93150685]
Recall 0.975498272655 [ 0.97183099  0.99056604  0.96698113  0.98584906  0.96226415]
F1 0.963248580861 [ 0.97183099  0.96997691  0.96244131  0.96535797  0.94663573]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Calculate the weighted versions of accuracy and error for the logistic regression classifier giving more weight to the number of the legitimate emails, the false postive (legitimate -&gt; spam) and the true negative (legitimate -&gt; legitimate). In our case, we set the weight to two (2), as state also above.</p>
<p>Calculate the the ratio of the weighted error of the baseline classifier to the weighted error of the logistic regression classifier. This is the total cost ratio (TCR). The higher TCR, the better our classifier is in comparison to the baseline classifier. Logistic regression classifier seems to perform quite well as far as TCR is concerned.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[19]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tn</span><span class="p">,</span> <span class="n">fp</span><span class="p">,</span> <span class="n">fn</span><span class="p">,</span> <span class="n">tp</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
<span class="n">wlog_accuracy</span> <span class="o">=</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">tn</span><span class="p">)</span> <span class="o">+</span> <span class="n">tp</span><span class="p">)</span> <span class="o">/</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">+</span> <span class="n">nspam</span><span class="p">)</span>

<span class="n">wlog_error</span> <span class="o">=</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">fp</span><span class="p">)</span> <span class="o">+</span> <span class="n">fn</span><span class="p">)</span> <span class="o">/</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">+</span> <span class="n">nspam</span><span class="p">)</span>
<span class="n">tcr</span> <span class="o">=</span> <span class="n">wb_error</span> <span class="o">/</span> <span class="n">wlog_error</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Total cost ratio - Logistic Regression vs. baseline classifier:&quot;</span><span class="p">,</span> <span class="n">tcr</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Total cost ratio - Logistic Regression vs. baseline classifier: 10.2093023256
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[20]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">roc_curve_plot</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[21]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">conf_matrix</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>[[1096   17]
 [   9  430]]
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[22]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span> <span class="o">=</span> <span class="n">calc_metrics</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">label_test</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>(362, 715)
(724, 715)
(1086, 715)
(1448, 715)
(1810, 715)
(2172, 715)
(2534, 715)
(2896, 715)
(3258, 715)
(3620, 715)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[23]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">learning_curves</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">,</span> <span class="s2">&quot;Logistic Regression&quot;</span><span class="p">)</span>
<span class="n">learning_curves</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="s2">&quot;f1-score&quot;</span><span class="p">,</span> <span class="s2">&quot;Logistic Regression&quot;</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[24]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">prec_rec_curve</span><span class="p">(</span><span class="n">X_test</span><span class="p">,</span> <span class="n">label_test</span><span class="p">,</span> <span class="s2">&quot;decision&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="3.-Naive-Bayes">3. Naive Bayes<a class="anchor-link" href="#3.-Naive-Bayes">&#182;</a></h3>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[25]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">clf</span> <span class="o">=</span> <span class="n">GaussianNB</span><span class="p">()</span>
<span class="n">classifier</span> <span class="o">=</span> <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_train</span><span class="p">)</span>

<span class="n">scores</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Accuracy&quot;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">scores</span><span class="p">),</span> <span class="n">scores</span><span class="p">)</span>
<span class="n">precisions</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span>
                             <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;precision&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;Precision&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">precisions</span><span class="p">),</span> <span class="n">precisions</span><span class="p">)</span>
<span class="n">recalls</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span>
                          <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;recall&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;Recall&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">recalls</span><span class="p">),</span> <span class="n">recalls</span><span class="p">)</span>
<span class="n">f1s</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;f1&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;F1&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">f1s</span><span class="p">),</span> <span class="n">f1s</span><span class="p">)</span>

<span class="n">predictions</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="o">.</span><span class="n">toarray</span><span class="p">())</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Accuracy 0.897235580669 [ 0.89793103  0.89226519  0.89364641  0.91160221  0.89073306]
Precision 0.748190167133 [ 0.75090253  0.73591549  0.74907749  0.77007299  0.73498233]
Recall 0.97926742847 [ 0.97652582  0.98584906  0.95754717  0.99528302  0.98113208]
F1 0.848203607014 [ 0.84897959  0.84274194  0.84057971  0.86831276  0.84040404]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Calculate the weighted versions of accuracy and error for the Naive Bayes classifier giving more weight to the number of the legitimate emails, the false postive (legitimate -&gt; spam) and the true negative (legitimate -&gt; legitimate). In our case, we set the weight to two (2), as state also above.</p>
<p>Calculate the the ratio of the weighted error of the baseline classifier to the weighted error of the Naive Bayes classifier. This is the total cost ratio (TCR). The higher TCR, the better our classifier is in comparison to the baseline classifier. Naive Bayes classifier does not seem to perform well as far as TCR is concerned.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[26]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tn</span><span class="p">,</span> <span class="n">fp</span><span class="p">,</span> <span class="n">fn</span><span class="p">,</span> <span class="n">tp</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
<span class="n">wgnb_accuracy</span> <span class="o">=</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">tn</span><span class="p">)</span> <span class="o">+</span> <span class="n">tp</span><span class="p">)</span><span class="o">/</span><span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">+</span> <span class="n">nspam</span><span class="p">)</span>

<span class="n">wgnb_error</span> <span class="o">=</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">fp</span><span class="p">)</span> <span class="o">+</span> <span class="n">fn</span><span class="p">)</span> <span class="o">/</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">+</span> <span class="n">nspam</span><span class="p">)</span>
<span class="n">tcr</span> <span class="o">=</span> <span class="n">wb_error</span> <span class="o">/</span> <span class="n">wgnb_error</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Total cost ratio - Naive Bayes vs. baseline classifier:&quot;</span><span class="p">,</span> <span class="n">tcr</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Total cost ratio - Naive Bayes vs. baseline classifier:: 1.44884488449
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[27]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">roc_curve_plot</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAYoAAAEWCAYAAAB42tAoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAIABJREFUeJzt3Xd8VGX2+PHPoQvSBNZCV1DpxXwprgIWFLGAggo2QJG1rYroqrtf1/7zq2tbFUUFVldXsC0CLpZVQESFTCgiRZCiELAAAtIChJzfH88NGUIymSRz504579drXplyZ+7JzWTOPM9zn/OIqmKMMcYUp0LQARhjjElsliiMMcZEZInCGGNMRJYojDHGRGSJwhhjTESWKIwxxkRkicJETUQuF5GPg44jkYjIDhE5NoD9NhMRFZFK8d63H0RkiYj0KsPz7D0ZB5YokpSIfC8iu70Pqp9E5BUROdzPfarqv1T1LD/3EU5EThaR6SKyXUS2ichUEWkdr/0XEc9MERkefp+qHq6qq33a3/Ei8raIbPJ+/0UicpuIVPRjf2XlJawW5XkNVW2jqjNL2M8hyTHe78l0ZYkiuZ2vqocDHYFOwN0Bx1MmRX0rFpHuwMfAZOAYoDnwNfCFH9/gE+2buYgcB8wF1gHtVLU2cDGQAdSM8b4C+90T7bibYqiqXZLwAnwPnBl2+zHgP2G3qwKPA2uBn4ExwGFhj/cDFgK/AauAPt79tYFxwI/AeuAhoKL32FBgtnd9DPB4oZgmA7d5148B3gU2AmuAm8O2uw94B3jd2//wIn6/z4Hni7j/A+Cf3vVeQDbwZ2CTd0wuj+YYhD33TuAn4DWgLvC+F/MW73ojb/uHgf1ADrADeM67X4EW3vVXgNHAf4DtuA/648LiOQtYDmwDngc+K+p397Z9PfzvWcTjzbx9D/F+v03AX8Ie7wJ8BWz1/pbPAVXCHlfgRuA7YI13399xiek3YB5watj2Fb3jvMr73eYBjYFZ3mvt9I7Lpd725+HeX1uBL4H2hd67dwKLgD1AJcLez17sWV4cPwNPevev9fa1w7t0J+w96W3TBvgv8Kv33D8H/b+aCpfAA7BLGf9wB/9jNQK+Af4e9vjTwBTgCNw30KnAI95jXbwPq964VmVD4ETvsfeAF4EawO+ATOAP3mMH/imBHt6Hini36wK7cQmigvdB8legCnAssBo429v2PmAf0N/b9rBCv1t13IfyaUX83sOAH73rvYBc4ElcUujpfWCdEMUxyH/uo95zDwPqAQO8/dcE3gbeC9v3TAp9sHNoovjVO76VgH8BE73H6nsffBd5j93iHYPiEsVPwLAIf/9m3r5f9mLvgPvQbeU9fhLQzdtXM2AZcGuhuP/rHZv85HmFdwwqAaO8GKp5j92Be4+dAIi3v3qFj4F3uzPwC9AVl2CG4N6vVcPeuwtxieawsPvy389fAVd61w8HuhX6nSuF7WsoBe/JmrikOAqo5t3uGvT/aipcAg/ALmX8w7l/rB24b3cKfArU8R4T3Adm+LfZ7hR8c3wReKqI1zzS+7AJb3kMBmZ418P/KQX3Da+Hd/taYLp3vSuwttBr3w38w7t+HzArwu/WyPudTizisT7APu96L9yHfY2wx98C7oniGPQC9uZ/EBYTR0dgS9jtmZScKMaGPdYX+Na7fhXwVdhjgku0xSWKfXitvGIez//QbBR2XyYwqJjtbwUmFYr79BLeY1uADt715UC/YrYrnCheAB4stM1yoGfYe/fqIt7P+YliFnA/UL+Y37m4RDEYWODn/126Xqx/MLn1V9VPRKQn8AbuW+tWoAHuW/E8EcnfVnDf7sB9k5tWxOs1BSoDP4Y9rwLuA+0gqqoiMhH3zzkLuAzXXZL/OseIyNawp1TEdSflO+Q1w2wB8oCjgW8LPXY0rpvlwLaqujPs9g+4Vk1JxwBgo6rmHHhQpDrwFC4Z1fXurikiFVV1f4R4w/0Udn0X7hsxXkwHfmfv+GVHeJ3NuN+1TPsTkeNxLa0M3HGohGvlhTvobyAio4DhXqwK1MK9p8C9Z1ZFEQ+4v/8QEflj2H1VvNctct+FXAM8AHwrImuA+1X1/Sj2W5oYTSnYYHYKUNXPcN9mH/fu2oTrBmqjqnW8S211A9/g/kmPK+Kl1uFaFPXDnldLVdsUs+sJwEARaYprRbwb9jprwl6jjqrWVNW+4WFH+H124rofLi7i4Utwrad8dUWkRtjtJsCGKI5BUTGMwnWtdFXVWrjuNXAJJmLMUfgR11JyL+iyV6PiN+cTXDdYWb2AS7Itvd/lzxT8HvkO/D4icipu3OASoK6q1sF1T+Y/p7j3TFHWAQ8X+vtXV9UJRe27MFX9TlUH47o+HwXe8f7GJR3/0sRoSsESRep4GugtIh1VNQ/Xd/2UiPwOQEQaisjZ3rbjgGEicoaIVPAeO1FVf8SdafSEiNTyHjvOa7EcQlUX4AZ+xwIfqWp+CyIT+E1E7hSRw0Skooi0FZH/KcXvcxfuW+nNIlJTROqKyEO47qP7C217v4hU8T7szgPejuIYFKUmLrlsFZEjgHsLPf4zbrylLP4DtBOR/t6ZPjcCR0XY/l7gZBH5m4gc5cXfQkReF5E6UeyvJm5MZIeInAhcH8X2ubi/ZyUR+SuuRZFvLPCgiLQUp72I1PMeK3xcXgauE5Gu3rY1RORcEYnqbC0RuUJEGnh/w/z31H4vtjyK/xu8DxwlIreKSFXvfdM1mn2ayCxRpAhV3Qj8E9c/D+7b4Upgjoj8hvuGeoK3bSZuUPgp3LfGz3DdBeD60qsAS3FdQO8QuQtkAnAmrusrP5b9wPm4Pv41uG/3Y3FnVEX7+8wGzsYN/v6I61LqBJyiqt+FbfqTF+cG3ODxdaqa311V7DEoxtO4geFNwBzgw0KP/x3XgtoiIs9E+7t4v88mXAvpMVy3UmvcmT17itl+FS4pNgOWiMg2XIstCzcuVZLbcd2B23Ef3G+WsP1HuDPKVuCOdQ4Hdw89iRv/+RiXgMbhjhW4MadXRWSriFyiqlm4MavncH+blbixhGj1wf3OO3DHfJCq5qjqLtzZZ194++oW/iRV3Y47QeN83PviO+C0UuzXFCP/jBVjko43k/d1VY3UhZOQRKQC7vTcy1V1RtDxGBOJtSiMiRMROVtE6ohIVQrGDOYEHJYxJfItUYjIeBH5RUQWF/O4iMgzIrLSK03Q2a9YjEkQ3XFn5WzCdY/0V9XdwYZkTMl863oSkR648/z/qapti3i8L/BH3LnmXXGTxWzgyRhjEoxvLQpVnYWbpVqcfrgkoqo6B6gjItGcN26MMSaOgpxw15CDz6rI9u77sfCGIjICGAFQo0aNk0488cS4BGhMOsvvbAj/Gc318twXy+fHa5/RvE6QmvADddjKInI3qWqDsrxGkImi8OQfKGZCjaq+BLwEkJGRoVlZWX7GZZKQKuTlwf79xV9ycyM/Hs0lXV4jET7golWhAlSsWHCpVKno66W5lPV5frxOmV6jgrqflYQ6E16g0pZfqPvUfT+U9RgHmSiycVPu8zXCnQufNiJ9sCXDh0kivUZeXtB/zegV/mCLxQdI1arp+YFYoQJIUV8509n69XD99XDppXD55XCPN9fyqfvK/JJBJoopwE1evaCuwDZvZnDK2LwZunWDjRuL/nBLFiKx/+evXBmqVUuPD7PCF/tgM75QhbFj4fbbYd8+OPfcmL20b4lCRCbgKnTW94qf3YsrOIeqjsEVpeuLm7W5CzdTOKXMmgUrV8IVV0CDBsn7gWgfbMYkuFWr4NprYcYMOO00ePllOO64mL28b4nCK+oV6XHF1btJWaGQ+8B96SU47LCStzfGmDL55huYN8992AwfHvNvd1Zm3EehELRrZ0nCGOODxYth/ny46iro3x9Wr4Z69Up+XhlYCQ+f5OW5RPE/pamXaowxJdm7F+67Dzp3hr/8BXK8JVV8ShJgicI3K1fCtm2WKIwxMTR3rksQ99/vzmpasMCdFeIz63rySSjkfnbpEmwcxpgUsX49nHoqHHkkvP9+TM9qKom1KHwSCrmxidatg47EGJPUVqxwPxs2hDffhCVL4pokwBKFbzIzXQuxkrXZjDFlsXUrjBgBJ57ozrUHuPBCqFUr8vN8YInCB/v2ua5DG58wxpTJlCnQpg2MGwd33BH4h4l93/XBkiXuRAQbnzDGlNrw4S5BtGsHkydDRkbQEVmi8EP+QLa1KIwxUcmvwijiEkPTpnDnnVClSrBxeSxR+CAzE+rWjekMemNMqlq3Dq67DgYNgiuvdNcTjI1R+CB/op3VSDLGFCsvD154wY1FzJwJe/YEHVGxLFHE2K5dbma9dTsZY4r13XeueN8NN0DXru5DY/jwoKMqlnU9xdjCha6EuCUKY0yxli6FRYtg/HgYOjThux8sUcRYZqb7aYnCGHOQr7923ySHDIF+/VwRv7p1g44qKtb1FGOhkJtAecwxQUdijEkIe/bAPfe4s5nuuaegiF+SJAmwRBFzVjHWGHPAV19Bp07w0ENw2WVxK+IXa5YoYmjLFjdGZYnCGMP69dCzJ+zYAdOmwauv+loK3E+WKGIoK8v9tERhTBpbtsz9bNgQ3nrLlWo455xgYyonSxQxlD8jOwFm3Btj4m3LFrj6alcy+vPP3X39+0PNmsHGFQN21lMMhULQsmVSjVEZY2Jh0iQ3J2LjRrj77pTrVrBEEUOZmdCrV9BRGGPi6uqr4R//gI4d4T//cesLpBhLFDGyYYO7pNgXCWNMUcKL+HXr5roSbr8dKlcONi6fWKKIEVv61Jg08cMP8Ic/uNNdr7rKLS6U4mwwO0ZCIahY0bU+jTEpKC8PRo+Gtm1h9my3QlmasBZFjGRmuvdP9epBR2KMibnly13Rvtmz4ayz4MUXoVmzoKOKG2tRxICqm0Nh4xPGpKjly918iFdegQ8/TKskAdaiiIlVq9wp1DY+YUwKWbDAFfEbNgwuuMAV8atTJ+ioAmEtihiwpU+NSSE5OfDnP7t/6PvuKyjil6ZJAixRxERmpqvz1aZN0JEYY8rliy/cGSmPPOLOaFq4MCmL+MWadT3FQCjk5tik6CnUxqSH9evdqnMNG8JHH7lBawNYi6LccnNh/nzrdjImaS1d6n42bAjvvgvffGNJohBLFOW0dCns3m2Jwpik8+uvbhnSNm1g1ix33/nnw+GHBxpWIrKup3KypU+NSULvvgs33gibN8Nf/mKnLJbAEkU5hULuZIgWLYKOxBgTlaFD3SJCnTu7ORFWTqFElijKKRRy609UsE48YxJXeBG/k0+GVq1g1CioZB+B0fD1401E+ojIchFZKSJ3FfF4ExGZISILRGSRiPT1M55Y273bjXtZt5MxCWzNGjc4/c9/utsjRsCdd1qSKAXfEoWIVARGA+cArYHBItK60Gb/C7ylqp2AQcDzfsXjh4UL3VlPliiMSUD798Mzz7gibHPmFLQqTKn52aLoAqxU1dWquheYCPQrtI0CtbzrtYENPsYTc1Za3JgEtWwZnHoq3HIL9Ozp6jQNHRp0VEnLz7ZXQ2Bd2O1soGuhbe4DPhaRPwI1gDOLeiERGQGMAGjSpEnMAy2rUAiOPtqdfm2MSSArV7pCfq+9Bpdf7sYmTJn52aIo6i9TuO03GHhFVRsBfYHXROSQmFT1JVXNUNWMBg0a+BBq2WRmWreTMQlj3jwYP95dP/98NzZxxRWWJGLAz0SRDTQOu92IQ7uWrgHeAlDVr4BqQH0fY4qZrVthxQpLFMYEbvduuOsu6NoVHnywoIhfrVqRn2ei5meiCAEtRaS5iFTBDVZPKbTNWuAMABFphUsUG32MKWbmzXM/bXzCmADNmgUdOsCjj7oxiAULrIifD3wbo1DVXBG5CfgIqAiMV9UlIvIAkKWqU4BRwMsiMhLXLTVUNTlOTcgfyM7ICDYOY9LW+vVwxhnQuDF88om7bnzh64nEqjoNmFbovr+GXV8K/N7PGPySmQnHHQdHHBF0JMakmW++gXbt3Fkkkya5iq81agQdVUqz+cRlFApZt5MxcbVpE1x5JbRvX1DE77zzLEnEgU1NLIOffoLsbBvINiYuVOHtt+Gmm9yaw/fe6wauTdxYoigDW/rUmDgaMsTNh8jIgE8/dd1OJq4sUZRBZqYrAtipU9CRGJOiwov49ezpuptuvdXqMwXExijKIBRy5WOsa9QYH6xeDWeeCa+84m5fcw3cfrsliQBZoiglVZcorNvJmBjbvx+eftp1LYVCVrs/gViKLqU1a9wKipYojImhpUvh6qth7lw491wYMwYaNQo6KuOxRFFKtvSpMT5YswZWrYI33oBBg6w+U4KxRFFKoRBUrWonXhhTbqGQW9Tl2mtdK2L1aqhZM+ioTBGsE7CUQiF3tlPlykFHYkyS2rXLDU536waPPFJQxM+SRMKyRFEKubmuGKB1OxlTRjNnulNdn3jCtSSsiF9SsK6nUli2zH0ZskRhTBlkZ0Pv3tC0KUyf7mo0maRgLYpSsKVPjSmDr792Pxs1gsmTYdEiSxJJxhJFKYRCbi2Uli2DjsSYJLBxI1x2GXTsCJ995u7r2xeqVw82LlNq1vVUCpmZrtyMzQMyJgJVmDgRbr4Ztm2D+++H7t2DjsqUg33kRSknx7WYbXzCmBJceaVrSRx3nBus/utfoUqVoKMy5WAtiih9/bU768nGJ4wpQl6emyQn4sYfTjrJtSgqVgw6MhMD1qKIkpUWN6YYK1e6ZUj/8Q93+5prYORISxIpxBJFlDIz4cgjrfyMMQfk5sLjj7syBQsWWPdSCrOupyjlL31qJWiMARYvhmHDICsL+vWD55+HY44JOirjE2tRROG332D5cut2MuaAtWvhhx/c2U2TJlmSSHHWoojCvHnujD9LFCatzZ3rzuoYMcLNh1i9Gg4/POioTBxYiyIK+aXFMzKCjcOYQOzcCbfd5uZCPPYY7Nnj7rckkTYsUUQhFIJjj4X69YOOxJg4mz7dFfF76im47jqYP9/V2TdpxbqeohAK2cRSk4ays+Hss6F5c1eCo0ePoCMyAbEWRQl+/tmN29n4hEkbCxa4n40awdSpblzCkkRas0RRAptoZ9LGzz/DpZdC584FRfz69IHDDgs2LhM4SxQlCIVcEcDOnYOOxBifqMLrr0Pr1vDee/DQQ3DyyUFHZRKIjVGUIBRy/z92godJWZdd5uZDdO8O48ZBq1ZBR2QSjCWKCFRdojj//KAjMSbGwov4nXWWSxI33mj1mUyRrOspgu+/h02bbHzCpJgVK1yF1/Hj3e1hw6zSq4nIEkUEtvSpSSm5uW7CXIcObnEVG6Q2UbKupwhCIVcQs127oCMxppwWLYKrr3b1aC68EEaPhqOPDjoqkyQsUUSQmemW+7XqySbpZWfDunXw9tswYICVQTal4mvXk4j0EZHlIrJSRO4qZptLRGSpiCwRkTf8jKc09u93X75sfMIkrS+/hDFj3PX8In4DB1qSMKXmW6IQkYrAaOAcoDUwWERaF9qmJXA38HtVbQPc6lc8pfXtt64Wmo1PmKSzYwfccguccgo88URBEb8aNYKNyyQtP1sUXYCVqrpaVfcCE4F+hba5FhitqlsAVPUXH+MpFZuRbZLSxx9D27bw7LPudFcr4mdiwM9E0RBYF3Y727sv3PHA8SLyhYjMEZE+Rb2QiIwQkSwRydq4caNP4R4sMxNq1oQTTojL7owpv3Xr4NxzoVo1mDXLJYuaNYOOyqQAPxNFUR2hWuh2JaAl0AsYDIwVkTqHPEn1JVXNUNWMBg0axDzQooRCbv2JCnYCsUl08+a5n40bw7RpsHCh63YyJkb8/BjMBhqH3W4EbChim8mquk9V1wDLcYkjUHv2uIKZ1u1kEtpPP8HFF7tvNPlF/Hr3di0KY2LIz0QRAlqKSHMRqQIMAqYU2uY94DQAEamP64pa7WNMUVm0CPbts0RhEpQqvPqqK0I2dSr8v/9nRfyMr3ybR6GquSJyE/ARUBEYr6pLROQBIEtVp3iPnSUiS4H9wB2qutmvmKKVv/SpJQqTkAYNgrfegt//HsaOhRNPDDoik+J8nXCnqtOAaYXu+2vYdQVu8y4JIxSC3/0OmjQJOhJjPOFF/Pr2hVNPhRtusEE0Exf2LitCKORaEzYvySSEb791K8yNG+duDxkCN91kScLEjb3TCtm+HZYts24nkwD27XPjDx06wNKltiiKCYzVeipk3jw3VmiJwgRq4UJX/nvhQld249ln4aijgo7KpClLFIXYjGyTEH76yV3efRcuuijoaEyai5goRCTiILOqPhnbcIIXCkGzZhCneX3GFJg9252bfcMN0KcPrFoF1asHHZUxJY5R1CzhknLyB7KNiZvt293g9KmnwtNPFxTxsyRhEkTEFoWq3h+vQBLBxo1u+dMbbgg6EpM2PvoIRoxwdZpuuQUeesiK+JmEU1LX0zORHlfVm2MbTrBs6VMTV+vWwXnnQYsWrtvJZlebBFXSYPa8uESRIEIhN3eic+egIzEpS9W90bp0cUX8PvjAFfCz+kwmgZXU9fRqvAJJBJmZ0KqVVWY2PvnxR7dGxKRJMHMm9OwJZ54ZdFTGlCiq02NFpAFwJ26lugNffVT1dJ/iirv8L3p9+wYdiUk5qvDKK3DbbZCTA48+6uo0GZMkop2Z/S9gGdAcuB/4HlcdNmWsXesGs218wsTcJZfA1VdDu3aufv2f/gSVbAqTSR7RJop6qjoO2Keqn6nq1UA3H+OKO5toZ2Jq/35XyA/g/PPh+eddd9PxxwcaljFlEW2i2Of9/FFEzhWRTriFiFJGZiZUrgzt2wcdiUl6y5a5ORH5Rfyuugquv96K+JmkFW379yERqQ2MAp4FagEjfYsqAKEQdOxop7Cbcti3z40/PPigK+BXu3bQERkTE1ElClV937u6DW9FulSSl+eKAV55ZdCRmKS1YAEMHepKcFx6KTzzjFvUxJgUEFVbWEReFZE6Ybfrish4/8KKr+XLXRUFG58wZfbzz7BpE7z3HkycaEnCpJRou57aq+rW/BuqusUbp0gJtvSpKZNZs+Cbb9zciD59YOVKOOywoKMyJuaiHV2rICJ182+IyBGkUInyUMh1KdvSwyYqv/3mCoL17Om6mPKL+FmSMCkq2g/7J4AvReQdQIFLgId9iyrOQiE46SSoWDHoSEzCmzYN/vAH2LDBTaB74AE7A8KkvKhaFKr6T2AA8DOwEbhIVV/zM7B42bvXLSJm3U6mROvWQb9+7mymL7+EJ56AGjWCjsoY35XmxO4jgJ2q+iywUUSa+xRTXC1a5JKFJQpTJFWYM8ddb9wYPv4Y5s+Hrl2DjcuYOIr2rKd7cbWe7vbuqgy87ldQ8WSlxU2xNmyA/v2he3f47DN332mnQZUqwcZlTJxF26K4ELgA2AmgqhtIkRXuQiGoXx+aNg06EpMwVGHsWGjd2rUgHn/civiZtBbtYPZeVVURUQARSZmO2fylT0WCjsQkjIED4d//dmc1jR3rFhYyJo1F26J4S0ReBOqIyLXAJ8BY/8KKjx07YOlSG58wHFzEr39/GDMGpk+3JGEM0ZfweFxEegO/AScAf1XV//oaWRzMn+8+G2x8Is0tXgzDh8M118C111otF2MKiXrSnJcY/gsgIhVF5HJV/ZdvkcWBlRZPc3v3wiOPwMMPu1Ne69Yt+TnGpKGIXU8iUktE7haR50TkLHFuAlbjJt0ltVAImjSxsjxpad48N8vyvvvg4otdH+TAgUFHZUxCKqlF8RqwBfgKGA7cAVQB+qnqQp9j811mprUm0tbmzbB1K0ydCuedF3Q0xiS0khLFsaraDkBExgKbgCaqut33yHy2aROsWQPXXRd0JCZuZsxwRfxuvhnOOgu++w6qVSv5ecakuZLOespf2Q5V3Q+sSYUkAZCV5X5aiyINbNvm6jOdfjq88EJBET9LEsZEpaRE0UFEfvMu24H2+ddF5Ld4BOiXzEw3d+Kkk4KOxPhq6lQ3cW7sWLj9djc2YUX8jCmViF1Pqpqy9VRDIVdWvFatoCMxvlm3DgYMcH/o996z5qMxZZSWq72rFszINilG1VV2hYIifllZ9sc2phx8TRQi0kdElovIShG5K8J2A0VERSTDz3jyZWe7lSvtsyPFZGfDBRe4ukz5Rfx69bIifsaUk2+JQkQqAqOBc4DWwGARaV3EdjWBm4G5fsVSmC19mmLy8uDFF91YxKefwpNPwimnBB2VMSnDzxZFF2Clqq5W1b3ARKBfEds9CDwG5PgYy0FCIahcGTp0iNceja8GDHDnOf/P/7hyHCNH2nKFxsSQn4miIbAu7Ha2d98BItIJaKyq70d6IREZISJZIpK1cePGcgcWCkH79nZ2ZFLLzS0o4jdgALz8MnzyCRx7bLBxGZOC/EwURRXu1gMPilQAngJGlfRCqvqSqmaoakaDBg3KFVReno1tJr1Fi9xiQi+/7G5fcYUr6me14o3xhZ+JIhtoHHa7EbAh7HZNoC0wU0S+B7oBU/we0F6xAn77zRJFUtqzB+69101++eEHKOeXBmNMdKKuHlsGIaClt7b2emAQcFn+g6q6Daiff1tEZgK3q2qWjzHZ0qfJKhSCoUNd8b4rr4SnnoJ69YKOypi04FuiUNVcr9LsR0BFYLyqLhGRB4AsVZ3i174jCYWgRg1o1SqIvZsy27LFrTQ1bRqcc07Q0RiTVkRVS94qgWRkZGhWVtkbHd27uzOeZs2KYVDGH9OnuyJ+t9zibu/ZY+U3jCkjEZmnqmXq2k+rmdl798KCBTY+kfC2bnUrzZ1xhpsfkV/Ez5KEMYFIq0SxeLH7zLHxiQQ2ebKbODd+PPzpT1bEz5gE4OdgdsKxpU8T3Nq1brW5Vq1gyhTIiEtFF2NMCdKqRREKuRNlmjcPOhJzgCp8/rm73qSJmzQXClmSMCaBpFWiyMx0nz82LytBrF0L554LPXoUFPHr0cOK+BmTYNImUezcCUuW2PhEQsjLg+efhzZt3OlnzzxjRfyMSWBpM0axYIH7fLLxiQRw0UVu0Lp3b3jpJWjWLOiIjDERpE2isNLiAcvNhQoV3OXSS6FfPzfT2voBjUl4adP1FAq5Bc+OOiroSNLQ119D166NTn++AAATmElEQVSu9QAweDAMG2ZJwpgkkVaJwloTcZaTA//7v+4Mguxsy9LGJKm0SBS//gqrVlmiiKvMTOjUCR5+GC6/HJYtg/79g47KGFMGaTFGYRPtAvDbb7B7N3z4IZx9dtDRGGPKIa0Shc3h8tnHH7tzkEeOhDPPhOXLrfyGMSkgLbqeQiE44QSoXTvoSFLUli1ucPrss2HcOCviZ0yKSflEoeq6y63bySf//rcr4vfaa3D33W6dWUsQxqSUlO96Wr8efvrJEoUv1q6FQYOgbVu3oFCnTkFHZIzxQcq3KGzp0xhTLajL1KSJW1xo7lxLEsaksLRIFJUqQceOQUeSAn74wS1D2qtXQbI45RS3ZKAxJmWlRaJo1w6qVQs6kiSWlwfPPeeK+M2eDc8+C6eeGnRUxpg4Sekxirw8lyguvTToSJJc//4wdao7q+nFF6Fp06AjMsbEUUonipUrYds2G58ok337oGJFV8Rv8GAYOBCuvNLqMxmThlK668lmZJfR/Pkuu44Z424PHgxXXWVJwpg0lfKJ4rDD3Gn+Jgq7d7u5EF26uHOKGzcOOiJjTAJI6a6nzEzo3Nmd9WRKMGcODBkCK1bA1VfD449D3bpBR2WMSQAp26LYt8+tamfjE1HaudMdtP/+15XhsCRhjPGk7HftJUvccgg2PhHBhx+6AzVqFJxxBnz7LVSpEnRUxpgEk7ItClv6NILNm1030znnwKuvwt697n5LEsaYIqRsogiFXO/JcccFHUkCUYV33nGj+2+84VafC4UsQRhjIkrZrqf8pU/tjM4wa9fCZZdB+/Zu7YgOHYKOyBiTBFKyRbFrFyxebN1OgGtFTJ/urjdtCjNnujOcLEkYY6KUkoliwQLYv98SBWvWwFlnuYHq/CJ+J59s5wsbY0olJRNF2pcW378f/v53t07E3LnwwgtWxM8YU2Yp+dUyFIKGDeHoo4OOJCD9+sF//gN9+7oyHDbD2hhTDimbKNKu2ym8iN+VV7r6TJddZqP5xphy87XrSUT6iMhyEVkpIncV8fhtIrJURBaJyKciUu761Vu2wHffpVmiyMqCjAzXxQSurvrll1uSMMbEhG+JQkQqAqOBc4DWwGARKVyebwGQoartgXeAx8q736ws9zMtxid274Y774SuXWHjRlsnwhjjCz9bFF2Alaq6WlX3AhOBfuEbqOoMVd3l3ZwDNCrvTvMHsjMyyvtKCe6rr9wpro895or4LV0K550XdFTGmBTk5xhFQ2Bd2O1soGuE7a8BPijqAREZAYwAaNKkScSdhkLQsiXUqVOqWJPP7t1uCb9PPnGnvxpjjE/8bFEU1UGuRW4ocgWQAfytqMdV9SVVzVDVjAYNGkTcaWZmCo9PTJsGf/MO0emnw7JlliSMMb7zM1FkA+HnZTYCNhTeSETOBP4CXKCqe8qzww0b3CXlxic2bYIrroBzz4V//augiF/lysHGZYxJC34mihDQUkSai0gVYBAwJXwDEekEvIhLEr+Ue4eptvSpKkycCK1awVtvwb33uiaTFfEzxsSRb2MUqporIjcBHwEVgfGqukREHgCyVHUKrqvpcOBtcadyrlXVC8q6z1DITSXo2DEGv0AiWLvWlQPv0MEtJtSuXdARGWPSkK8T7lR1GjCt0H1/Dbt+Ziz3l5npqlZUrx7LV40zVfj0UzjzTHe662efuSZSxYpBR2aMSVMpU+tJ1c2hSOrxiVWr3OB0794FRfy6dbMkYYwJVMokilWr3KzspByf2L8fnnzSdS3NmwcvvmhF/IwxCSNlaj0l9dKn558PH3zgJsy98AI0Kve8Q2OMiZmUSRShEBx2GLRpE3QkUdq7160LUaECDB3qCvkNGmT1mYwxCSdlup5CIejUKUmmFmRmwkknwfPPu9uXXOKqvVqSMMYkoJRIFLm5MH9+EnQ77doFo0ZB9+5uQOW444KOyBhjSpQSXU9LlrjSRwmdKGbPdnMiVq+GP/wBHn0UatcOOipjjClRSiSKpFj6NH9hoRkzoFevoKMxxpiopUyiqFMHWrQIOpJCpk51hfv+9Cc47TRXCrxSShxyY0waSYkxilDIrT+RMGPBGze6ZUgvuAAmTCgo4mdJwhiThJI+UezeDYsWJcj4hCq88YYr4vfOO/DAAzB3rhXxM8YktaT/irtwoZvYnBDjE2vXwrBh7jzdceOSaFKHMcYUL+lbFIGXFs/Lg48+ctebNoXPP4cvvrAkYYxJGSmRKI4+Gho2DGDn333nVprr0wdmzXL3deliRfyMMSkl6RNFIEuf5ua6JUnbt3d9X+PGWRE/Y0zKSuoxiq1bYcUKuOqqOO/4vPNcd1O/fq4MxzHHxDkAY5LDvn37yM7OJicnJ+hQ0ka1atVo1KgRlWNYzyipE8W8ee5nXFoUe/a4QlIVKsDw4XD11XDxxQl0Tq4xiSc7O5uaNWvSrFkzxP5XfKeqbN68mezsbJo3bx6z103qrqf8geyMDJ93NGcOdO4Mo0e72wMHukJ+9sY3JqKcnBzq1atnSSJORIR69erFvAWX1IkiM9PV1TviCJ92sHMnjBwJJ58M27dDy5Y+7ciY1GVJIr78ON5J3fUUCvk4hvz5566I35o1cMMN8MgjUKuWTzszxpjElbQtip9+guxsH8cncnPdmMRnn7kuJ0sSxiStSZMmISJ8++23B+6bOXMm55133kHbDR06lHfeeQdwA/F33XUXLVu2pG3btnTp0oUPPvig3LE88sgjtGjRghNOOIGP8udgFTJ9+nQ6d+5M27ZtGTJkCLm5uQBMnjyZ9u3b07FjRzIyMpg9e3a544lG0iYKXybavfeeazmAK+K3ZAn06BHDHRhjgjBhwgROOeUUJk6cGPVz7rnnHn788UcWL17M4sWLmTp1Ktu3by9XHEuXLmXixIksWbKEDz/8kBtuuIH9+/cftE1eXh5Dhgxh4sSJLF68mKZNm/Lqq68CcMYZZ/D111+zcOFCxo8fz/Dhw8sVT7SStuspM9PNa+vUKQYv9vPP8Mc/wttvu0HrUaNcfSYr4mdMzNx6q5t2FEsdO8LTT0feZseOHXzxxRfMmDGDCy64gPvuu6/E1921axcvv/wya9asoWrVqgAceeSRXHLJJeWKd/LkyQwaNIiqVavSvHlzWrRoQWZmJt27dz+wzebNm6latSrHH388AL179+aRRx7hmmuu4fDDDz+w3c6dO+M2/pPULYo2baBGjXK8iCq89hq0bg2TJ8PDD7sznKyInzEp47333qNPnz4cf/zxHHHEEcyfP7/E56xcuZImTZpQK4ou55EjR9KxY8dDLv/3f/93yLbr16+ncePGB243atSI9evXH7RN/fr12bdvH1lZWQC88847rFu37sDjkyZN4sQTT+Tcc89l/PjxJcYXC0n5lVnVJYoLLyznC61d6+ZEZGS42dUnnhiT+Iwxhyrpm79fJkyYwK233grAoEGDmDBhAp07dy7223hpv6U/9dRTUW+rqiXuT0SYOHEiI0eOZM+ePZx11llUCuvduPDCC7nwwguZNWsW99xzD5988kmp4i2LpEwUq1fDr7+WcXwiv4jfOee4In5ffOH6r6w+kzEpZ/PmzUyfPp3FixcjIuzfvx8R4bHHHqNevXps2bLloO1//fVX6tevT4sWLVi7di3bt2+nZs2aEfcxcuRIZsyYccj9gwYN4q677jrovkaNGh3UOsjOzuaYIio7dO/enc8//xyAjz/+mBUrVhyyTY8ePVi1ahWbNm2ifv36EWMsN1VNqstJJ52kEyaogur8+Vo6y5ernnqqe/LMmaV8sjGmtJYuXRro/seMGaMjRow46L4ePXrorFmzNCcnR5s1a3Ygxu+//16bNGmiW7duVVXVO+64Q4cOHap79uxRVdUNGzboa6+9Vq54Fi9erO3bt9ecnBxdvXq1Nm/eXHNzcw/Z7ueff1ZV1ZycHD399NP1008/VVXV7777TvPy8lRVdd68eXrMMcccuB2uqOMOZGkZP3eTcowiFIJq1aBt2yifkJsLjz7qivh98w384x92NpMxaWDChAlcWKiPesCAAbzxxhtUrVqV119/nWHDhtGxY0cGDhzI2LFjqV27NgAPPfQQDRo0oHXr1rRt25b+/fvToEGDcsXTpk0bLrnkElq3bk2fPn0YPXo0Fb3ejL59+7JhwwYA/va3v9GqVSvat2/P+eefz+mnnw7Au+++S9u2benYsSM33ngjb775ZlwGtEWL6DNLZBkZGVq9ehb79sFXX0X5pLPPho8/hosucnMijjrK1xiNMc6yZcto1apV0GGknaKOu4jMU9UyFTxKuhaFqisGWOL4RE6OW/oOYMQItzTpu+9akjDGmFJKukSRkwO7dpWw9OkXX7gTrPOL+A0Y4C7GGGNKLekSxc6d7meRLYodO+Dmm10BqJwcsCavMYFLtu7tZOfH8U66RLFrlyu7dEgh188+c6Pbzz0HN90EixdD796BxGiMcapVq8bmzZstWcSJeutRVKtWLaavm3TzKHbuhG7d3PpBh6he3VV9/f3v4x6XMeZQjRo1Ijs7m40bNwYdStrIX+EulpIuUezeHTY+8e9/w7ffwp//DD17ulNfbeKcMQmjcuXKMV1pzQTD164nEekjIstFZKWI3FXE41VF5E3v8bki0qyk11SFU1r85FaZGzAAJk2CvXvdg5YkjDEm5nxLFCJSERgNnAO0BgaLSOtCm10DbFHVFsBTwKMlvW49NnPOba3g/fddSfAvv7QifsYY4yM/WxRdgJWqulpV9wITgX6FtukHvOpdfwc4Q0qYZtiUH5D2beHrr+Guu9ziQsYYY3zj5xhFQ2Bd2O1soGtx26hqrohsA+oBm8I3EpERwAjv5p4Ks2cvtkqvANSn0LFKY3YsCtixKGDHosAJZX2in4miqJZB4XPkotkGVX0JeAlARLLKOg091dixKGDHooAdiwJ2LAqISFZZn+tn11M20DjsdiNgQ3HbiEgloDbwq48xGWOMKSU/E0UIaCkizUWkCjAImFJomynAEO/6QGC62swcY4xJKL51PXljDjcBHwEVgfGqukREHsDVRZ8CjANeE5GVuJbEoChe+iW/Yk5CdiwK2LEoYMeigB2LAmU+FklXZtwYY0x8JV2tJ2OMMfFlicIYY0xECZso/Cj/kayiOBa3ichSEVkkIp+KSNMg4oyHko5F2HYDRURFJGVPjYzmWIjIJd57Y4mIvBHvGOMliv+RJiIyQ0QWeP8nfYOI028iMl5EfhGRxcU8LiLyjHecFolI56heuKyLbft5wQ1+rwKOBaoAXwOtC21zAzDGuz4IeDPouAM8FqcB1b3r16fzsfC2qwnMAuYAGUHHHeD7oiWwAKjr3f5d0HEHeCxeAq73rrcGvg86bp+ORQ+gM7C4mMf7Ah/g5rB1A+ZG87qJ2qLwpfxHkirxWKjqDFXd5d2cg5uzkoqieV8APAg8BuTEM7g4i+ZYXAuMVtUtAKr6S5xjjJdojoUCtbzrtTl0TldKUNVZRJ6L1g/4pzpzgDoicnRJr5uoiaKo8h8Ni9tGVXOB/PIfqSaaYxHuGtw3hlRU4rEQkU5AY1V9P56BBSCa98XxwPEi8oWIzBGRPnGLLr6iORb3AVeISDYwDfhjfEJLOKX9PAESdz2KmJX/SAFR/54icgWQAfT0NaLgRDwWIlIBV4V4aLwCClA074tKuO6nXrhW5uci0lZVt/ocW7xFcywGA6+o6hMi0h03f6utqub5H15CKdPnZqK2KKz8R4FojgUicibwF+ACVd0Tp9jiraRjURNoC8wUke9xfbBTUnRAO9r/kcmquk9V1wDLcYkj1URzLK4B3gJQ1a+AariCgekmqs+TwhI1UVj5jwIlHguvu+VFXJJI1X5oKOFYqOo2Va2vqs1UtRluvOYCVS1zMbQEFs3/yHu4Ex0Qkfq4rqjVcY0yPqI5FmuBMwBEpBUuUaTj+qxTgKu8s5+6AdtU9ceSnpSQXU/qX/mPpBPlsfgbcDjwtjeev1ZVLwgsaJ9EeSzSQpTH4iPgLBFZCuwH7lDVzcFF7Y8oj8Uo4GURGYnrahmail8sRWQCrquxvjcecy9QGUBVx+DGZ/oCK4FdwLCoXjcFj5UxxpgYStSuJ2OMMQnCEoUxxpiILFEYY4yJyBKFMcaYiCxRGGOMicgShTGAiOwXkYVhl2YRtm2WX51TRHqJSEzKhXivdXIsXsuYWErIeRTGBGC3qnYMOIZewA7gy4DjMOYg1qIwphhey+FzEZnvXUr1bV9EzvDWP/jGWyegqnf/995MaUQkQ0Rmei2Y64CRXovm1Fj/PsaUlSUKY5zDwrqdJnn3/QL0VtXOwKXAM9G+mIhUA14BLlXVdrjW+/XFba+q3wNjgKdUtaOqfl62X8OY2LOuJ2OcorqeKgPPiUhHXAmM40vxeicAa1R1hXf7VeBG4OlyR2pMnFmiMKZ4I4GfgQ641nfEhZBE5CPgSCALeC7CprkUtOarlT9MY/xlicKY4tUGslU1T0SG4ArOFUtVz86/7nU9NRORFqq6ErgS+Mx7+HvgJNwCUwPCXmI7BauwGZMwbIzCmOI9DwwRkTm4bqed0T5RVXNwlTnfFpFvgDzcGATA/cDfReRzXJdWvqnAhTaYbRKNVY81xhgTkbUojDHGRGSJwhhjTESWKIwxxkRkicIYY0xEliiMMcZEZInCGGNMRJYojDHGRPT/AcwXHVBxFNI3AAAAAElFTkSuQmCC
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[28]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">conf_matrix</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>[[965 148]
 [  7 432]]
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[29]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span> <span class="o">=</span> <span class="n">calc_metrics</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">X_train</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">X_test</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_test</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>(362, 715)
(724, 715)
(1086, 715)
(1448, 715)
(1810, 715)
(2172, 715)
(2534, 715)
(2896, 715)
(3258, 715)
(3620, 715)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[30]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">learning_curves</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">,</span> <span class="s2">&quot;Naive Bayes&quot;</span><span class="p">)</span>
<span class="n">learning_curves</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="s2">&quot;f1-score&quot;</span><span class="p">,</span> <span class="s2">&quot;Naive Bayes&quot;</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[31]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">prec_rec_curve</span><span class="p">(</span><span class="n">X_test</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_test</span><span class="p">,</span> <span class="s2">&quot;proba&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="4.-k-Nearest-Neighbors">4. k-Nearest Neighbors<a class="anchor-link" href="#4.-k-Nearest-Neighbors">&#182;</a></h3>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[35]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.neighbors</span> <span class="k">import</span> <span class="n">KNeighborsClassifier</span>
<span class="n">neigh</span> <span class="o">=</span> <span class="n">KNeighborsClassifier</span><span class="p">()</span>

<span class="c1"># Create regularization hyperparameter space</span>
<span class="n">n_neighbors</span> <span class="o">=</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">7</span><span class="p">]</span>

<span class="c1"># Create hyperparameter options</span>
<span class="n">hyperparameters</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">n_neighbors</span><span class="o">=</span><span class="n">n_neighbors</span><span class="p">)</span>

<span class="c1"># Create grid search using 5-fold cross validation</span>
<span class="n">clf</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">neigh</span><span class="p">,</span> <span class="n">hyperparameters</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>

<span class="n">classifier</span> <span class="o">=</span> <span class="n">clf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[36]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">scores</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Accuracy&quot;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">scores</span><span class="p">),</span> <span class="n">scores</span><span class="p">)</span>
<span class="n">precisions</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span>
                             <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;precision&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;Precision&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">precisions</span><span class="p">),</span> <span class="n">precisions</span><span class="p">)</span>
<span class="n">recalls</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span>
                          <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;recall&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;Recall&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">recalls</span><span class="p">),</span> <span class="n">recalls</span><span class="p">)</span>
<span class="n">f1s</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">classifier</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;f1&#39;</span><span class="p">)</span>
<span class="nb">print</span> <span class="p">(</span><span class="s1">&#39;F1&#39;</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">f1s</span><span class="p">),</span> <span class="n">f1s</span><span class="p">)</span>

<span class="n">predictions</span> <span class="o">=</span> <span class="n">classifier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Accuracy 0.816572924514 [ 0.8262069   0.79005525  0.82458564  0.8218232   0.82019364]
Precision 0.617076932675 [ 0.62908012  0.58426966  0.62686567  0.6231454   0.62202381]
Recall 0.988683674373 [ 0.99530516  0.98113208  0.99056604  0.99056604  0.98584906]
F1 0.759785799879 [ 0.77090909  0.73239437  0.7678245   0.76502732  0.76277372]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Calculate the weighted versions of accuracy and error for the knn classifier giving more weight to the number of the legitimate emails, the false postive (legitimate -&gt; spam) and the true negative (legitimate -&gt; legitimate). In our case, we set the weight to two (2), as state also above.</p>
<p>Calculate the the ratio of the weighted error of the baseline classifier to the weighted error of the knn classifier. This is the total cost ratio (TCR). The higher TCR, the better our classifier is in comparison to the baseline classifier. knn classifier does not seem to perform well as far as TCR is concerned.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[38]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tn</span><span class="p">,</span> <span class="n">fp</span><span class="p">,</span> <span class="n">fn</span><span class="p">,</span> <span class="n">tp</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
<span class="n">wneigh_accuracy</span> <span class="o">=</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">tn</span><span class="p">)</span> <span class="o">+</span> <span class="n">tp</span><span class="p">)</span><span class="o">/</span><span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">+</span> <span class="n">nspam</span><span class="p">)</span>

<span class="n">wneigh_error</span> <span class="o">=</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">fp</span><span class="p">)</span> <span class="o">+</span> <span class="n">fn</span><span class="p">)</span> <span class="o">/</span> <span class="p">((</span><span class="n">l</span> <span class="o">*</span> <span class="n">nham</span><span class="p">)</span> <span class="o">+</span> <span class="n">nspam</span><span class="p">)</span>
<span class="n">tcr</span> <span class="o">=</span> <span class="n">wb_error</span> <span class="o">/</span> <span class="n">wneigh_error</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Total cost ratio - knn vs. baseline classifier:&quot;</span><span class="p">,</span> <span class="n">tcr</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Total cost ratio - knn vs. baseline classifier: 0.67125382263
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[41]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">roc_curve_plot</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[42]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">conf_matrix</span><span class="p">(</span><span class="n">label_test</span><span class="p">,</span> <span class="n">predictions</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>[[788 325]
 [  4 435]]
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[43]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results</span> <span class="o">=</span> <span class="n">calc_metrics</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">label_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">label_test</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>(362, 715)
(724, 715)
(1086, 715)
(1448, 715)
(1810, 715)
(2172, 715)
(2534, 715)
(2896, 715)
(3258, 715)
(3620, 715)
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[44]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">learning_curves</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="s2">&quot;accuracy&quot;</span><span class="p">,</span> <span class="s2">&quot;K-Nearest-Neighbors&quot;</span><span class="p">)</span>
<span class="n">learning_curves</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="s2">&quot;f1-score&quot;</span><span class="p">,</span> <span class="s2">&quot;K-Nearest-Neighbors&quot;</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[45]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">prec_rec_curve</span><span class="p">(</span><span class="n">X_test</span><span class="o">.</span><span class="n">toarray</span><span class="p">(),</span> <span class="n">label_test</span><span class="p">,</span> <span class="s2">&quot;proba&quot;</span><span class="p">,</span> <span class="n">clf</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,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
"
>
</div>

</div>

</div>
</div>

</div>
    </div>
  </div>
</body>

 
</html>