s3400652_MATH2319_Phase2 Report.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />

<title>Phase2_trial4 -final submission</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;
    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 4.7.0 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=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#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;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.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;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-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 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-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 {
  -ms-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-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.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,
.fa-gratipay: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-pp: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-resistance: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-y-combinator-square:before,
.fa-yc-square:before,
.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";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  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;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* 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;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: 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 {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  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;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#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#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
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;
}
.modal-header {
  cursor: move;
}
@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;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* 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 {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
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 .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.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: text-bottom;
  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;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.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_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.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;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.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;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.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;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.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;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-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.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.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);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.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-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* 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;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  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,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@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. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.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. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

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;
}
div.output_area .mglyph > img {
  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: 1px 0 1px 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:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.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;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.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;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
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.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.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;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 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;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  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;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button: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);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.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 .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#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;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -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.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.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;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.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;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#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;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#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;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#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.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.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.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.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 {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
  height: 100%;
  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  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;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#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;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.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;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
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;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#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;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#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/2.7.5/latest.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">
<h1 id="Predicting-the-Contraceptive-Method">Predicting the Contraceptive Method <br>(By Udeshika Dissanayake)<a class="anchor-link" href="#Predicting-the-Contraceptive-Method">&#182;</a></h1><p>The objective of this study is to predict the contraceptive method (no use, long-term methods,or short-term methods) of a woman based on her demographic and socio-economic characteristics.</p>
<p>A data-set of 1473 married women with their demographic and socio-economic characteristics is used in this study. The Source for the data-set is the UCI Machine Learning Repository at, 
<a href="http://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice">http://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice</a> <cite data-cite="Contraceptive_Method_Choice_UCI">(Dua, D. and Graff, C., 2013)</cite>.</p>
<p>This study consists with two phases. Objective of the Phase I is to preprocess and explore the data-set in order to make it ready for Phase II. The objective of phase II is to build a model that predicts the contraceptive method of a women based on here demograpic and socio-econimic characteristics.</p>
<p>All the activities have been performed in <code>Python</code> package in this study and compiled from <a href="http://jupyter.org/">Jupyter Notebook</a>.</p>
<p>This report does not cover the Phase I scope of work (Phase I report has been submitted under the previous assignment submission under this course). This report covers both narratives and the <code>Python</code> codesudes for the model building &amp; evaluation which performed under the phase II.</p>
<p>Content of this report is organized as follows.</p>
<ul>
<li><a href="#2">Section 2 (Overview)</a> summary of the data-set and the methodology.</li>
<li><a href="#3">Section 3 (Data Preparation)</a> data preparation process and the model evaluation strategy. </li>
<li><a href="#4">Section 4 (Hyperparameter Tuning)</a> hyperparameter tuning process for each classification algorithm.</li>
<li><a href="#5">Section 5 (Performance Comparison)</a> model performance comparison results.</li>
<li><a href="#6">Section 6 (Limitations)</a> limitations of the approach and possible solutions. </li>
<li><a href="#7">Section 7 (Summary)</a> summary of the project.</li>
</ul>
<h1 id="2.-Overview-">2. Overview <a class="anchor" id="2" /><a class="anchor-link" href="#2.-Overview-">&#182;</a></h1><h3 id="Data-set">Data-set<a class="anchor-link" href="#Data-set">&#182;</a></h3><p>The date-set contains contraceptive methods used &amp; nine other demographic and socio-economic characteristics of 1473 married women in Indonesia, which obtains from National Indonesia Contraceptive Prevalence Survey in 1987. The data-set has 9 descriptive features and one target feature.</p>
<h4 id="Target-Feature">Target Feature<a class="anchor-link" href="#Target-Feature">&#182;</a></h4><p>The response feature is contraceptive method which is given as:</p>
$$\text{contraceptive method} = \begin{cases}  long-term &amp; \text{ if the contraceptive method is long term} \\short-term &amp; \text{ if the contraceptive method is short term } \\ no-use &amp; \text{ if no contraceptive method is used }\end{cases}$$<p>The target feature has three classes. Hence this can be classified as multinominal (multiclass) target feature.</p>
<h4 id="Descriptive-Features">Descriptive Features<a class="anchor-link" href="#Descriptive-Features">&#182;</a></h4><p>Following are the descriptive features in the data-set.</p>
<ul>
<li><strong><code>Wife's age</code></strong>: numerical </li>
<li><strong><code>Wife's education</code></strong>: categorical (low, medium low, medium high, high)</li>
<li><strong><code>Husband's education</code></strong>: categorical (low, medium low, medium high, high) </li>
<li><strong><code>Number of children ever born</code></strong>: numerical</li>
<li><strong><code>Wife's religion</code></strong>: binary (Non-Islam, Islam)</li>
<li><strong><code>Wife's now working?</code></strong>: binary (Yes, No) </li>
<li><strong><code>Husband's occupation</code></strong>: categorical (Cat1, Cat2, Cat3, Cat4) </li>
<li><strong><code>Standard-of-living index</code></strong>: categorical (low, medium low, medium high, high)</li>
<li><strong><code>Media exposure</code></strong>: binary (Good, Bad) </li>
</ul>
<p>All the descriptive features are self-explanatory.</p>
<h3 id="Methodology">Methodology<a class="anchor-link" href="#Methodology">&#182;</a></h3><p>The data-set that had been preprocessed under Phase I, is now being used in this Phase of work. The data-set has been further preprocessed in order to use it in Scikit-Learn functions. Those additional preprocessed steps that are used under this Phase are,</p>

<pre><code>* Checking for missing values
* Discretizing wife's age feature
* Making ordinal categorical Features using Numeric-Integer-Encoding
* Splitting data-set into the set of descriptive features and the target
* Making nominal categorical features using One-Hot-Encoding
* Encoding target
* Scaling descriptive features
* Feature selection &amp; ranking using Random Forest Importance (RFI) 
* Splitting data-set into training and test sets
* Selecting evaluation strategy

</code></pre>
<p>Three different Machine-Learning (ML) classifier algorithms have been explored and built to predict the target feature. Those three ML algorithms are,</p>

<pre><code>* K-Nearest Neighbors (KNN)
* (Gaussian) Naive Bayes (NB)
* Decision Trees (DT)

</code></pre>
<p>All the observation in the data-set (i.e. full data-set) have been used in for modeling keeping 70:30 ratio of observations for training and test perspectives. This comes down to 1031 observations for training set, while 442 observations for test set.</p>
<p>A pipeline technique is used in modeling: firstly, feature selection has been performed using Random Forest Importance method considering 3, 4, 5, ... 9 features. Secondly, the hyper-parameter tuning has been performed for each classifier and subsequently, 'accuracy' method is used to evaluate the performance.</p>
<p>After selecting the best model, 5-fold cross-validation was performed on test data and performed a paired t-test to determine whether there is any statistically significant difference in each model pair. Additionally, the model was assessed using recall scores and confusion matrices on the test data.</p>

</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">
<h1 id="3.-Data-Preparation-">3. Data Preparation <a class="anchor" id="3" /><a class="anchor-link" href="#3.-Data-Preparation-">&#182;</a></h1>
</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="Loading-Data-set">Loading Data-set<a class="anchor-link" href="#Loading-Data-set">&#182;</a></h3><p>The data-set that had been preprocessed under Phase I has been loaded.</p>

</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="kn">import</span> <span class="nn">warnings</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">&quot;ignore&quot;</span><span class="p">)</span>

<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>

<span class="c1">#reading the data-set</span>
<span class="n">df_con</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;Preprocessed_Data.csv&#39;</span><span class="p">)</span>

<span class="c1">#examining the dta-set</span>
<span class="kn">from</span> <span class="nn">IPython.display</span> <span class="k">import</span> <span class="n">Markdown</span><span class="p">,</span> <span class="n">display</span>
<span class="k">def</span> <span class="nf">printmd</span><span class="p">(</span><span class="n">string</span><span class="p">):</span>
    <span class="n">display</span><span class="p">(</span><span class="n">Markdown</span><span class="p">(</span><span class="n">string</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Dimension of the data set is (</span><span class="si">{}</span><span class="s2">,</span><span class="si">{}</span><span class="s2">).</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">df_con</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">df_con</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="p">)</span>
    
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Data Types are: </span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">df_con</span><span class="o">.</span><span class="n">dtypes</span><span class="p">)</span>
<span class="n">printmd</span><span class="p">(</span><span class="s2">&quot;Random rows in the Data-set&quot;</span><span class="p">)</span>
<span class="n">df_con</span><span class="o">.</span><span class="n">sample</span><span class="p">(</span><span class="mi">6</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>Dimension of the data set is (1473,10).

Data Types are: 

wife_age           int64
wife_edu          object
husb_edu          object
children           int64
wife_religion     object
wife-working      object
husb-occup        object
s-living_index    object
media_exp         object
contrac_mthd      object
dtype: object
</pre>
</div>
</div>

<div class="output_area">

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


<div class="output_markdown rendered_html output_subarea ">
<p>Random rows in the Data-set</p>

</div>

</div>

<div class="output_area">

    <div class="prompt output_prompt">Out[1]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>wife_age</th>
      <th>wife_edu</th>
      <th>husb_edu</th>
      <th>children</th>
      <th>wife_religion</th>
      <th>wife-working</th>
      <th>husb-occup</th>
      <th>s-living_index</th>
      <th>media_exp</th>
      <th>contrac_mthd</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>85</th>
      <td>33</td>
      <td>high</td>
      <td>high</td>
      <td>2</td>
      <td>Islam</td>
      <td>No</td>
      <td>Cat1</td>
      <td>high</td>
      <td>good</td>
      <td>No-use</td>
    </tr>
    <tr>
      <th>804</th>
      <td>36</td>
      <td>middle low</td>
      <td>middle low</td>
      <td>5</td>
      <td>Islam</td>
      <td>No</td>
      <td>Cat3</td>
      <td>high</td>
      <td>good</td>
      <td>Short-term</td>
    </tr>
    <tr>
      <th>151</th>
      <td>21</td>
      <td>low</td>
      <td>middle high</td>
      <td>4</td>
      <td>Islam</td>
      <td>No</td>
      <td>Cat3</td>
      <td>middle low</td>
      <td>good</td>
      <td>No-use</td>
    </tr>
    <tr>
      <th>22</th>
      <td>46</td>
      <td>high</td>
      <td>high</td>
      <td>1</td>
      <td>Other</td>
      <td>No</td>
      <td>Cat1</td>
      <td>high</td>
      <td>good</td>
      <td>No-use</td>
    </tr>
    <tr>
      <th>139</th>
      <td>20</td>
      <td>high</td>
      <td>high</td>
      <td>1</td>
      <td>Islam</td>
      <td>No</td>
      <td>Cat1</td>
      <td>high</td>
      <td>good</td>
      <td>No-use</td>
    </tr>
    <tr>
      <th>58</th>
      <td>21</td>
      <td>middle low</td>
      <td>middle high</td>
      <td>0</td>
      <td>Islam</td>
      <td>No</td>
      <td>Cat3</td>
      <td>high</td>
      <td>good</td>
      <td>No-use</td>
    </tr>
  </tbody>
</table>
</div>
</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="Checking-for-missing-values">Checking for missing values<a class="anchor-link" href="#Checking-for-missing-values">&#182;</a></h3><p>The missing values can have a significant impact to the data model. Hence it is always a good practice to check and ensure that there are no missing values before building the model. As can be seen below, there are no missing values in the processed data-set.</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">df_con</span><span class="o">.</span><span class="n">isna</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[2]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>wife_age          0
wife_edu          0
husb_edu          0
children          0
wife_religion     0
wife-working      0
husb-occup        0
s-living_index    0
media_exp         0
contrac_mthd      0
dtype: int64</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="Discretizing-Numeric-Features">Discretizing Numeric Features<a class="anchor-link" href="#Discretizing-Numeric-Features">&#182;</a></h3><p>Since this is a classification task, it is being assumed that transforming the numerical Age feature to ordinal variable will lead to a better performance in the model. As shown below, the Age feature has been transformed to ordinal variable with three levels:</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">contr_df</span> <span class="o">=</span> <span class="n">df_con</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="n">contr_df</span><span class="p">[</span><span class="s1">&#39;wife_age&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">qcut</span><span class="p">(</span><span class="n">contr_df</span><span class="p">[</span><span class="s1">&#39;wife_age&#39;</span><span class="p">],</span> <span class="n">q</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> 
                                     <span class="n">labels</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;young&#39;</span><span class="p">,</span> <span class="s1">&#39;middle-aged&#39;</span><span class="p">,</span> <span class="s1">&#39;old&#39;</span><span class="p">])</span>
<span class="n">contr_df</span><span class="p">[</span><span class="s1">&#39;wife_age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[3]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>young          547
old            469
middle-aged    457
Name: wife_age, dtype: int64</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="Making-Ordinal-Categorical-Features-Numeric-(using-Integer-Encoding)">Making Ordinal Categorical Features Numeric (using Integer-Encoding)<a class="anchor-link" href="#Making-Ordinal-Categorical-Features-Numeric-(using-Integer-Encoding)">&#182;</a></h3><p>All descriptive attributes in the data-set (including target and descriptive features) need to be converted to numeric features, in order to use the data-set in Scikit-Learn functions. Integer-Encoding has been done for the ordinal categorical features as below. It is worth mentioning that "wife_edu", "husd_edu", "husb-occup", "s-livinh_index", and "media_exp" in this data-set do have natural ordering, hence consider as ordinal variables.</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="n">cleanup_nums</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;wife_age&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;young&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;middle-aged&quot;</span><span class="p">:</span> <span class="mi">2</span><span class="p">,</span> <span class="s2">&quot;old&quot;</span><span class="p">:</span> <span class="mi">3</span><span class="p">},</span>
                <span class="s2">&quot;wife_edu&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;low&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;middle low&quot;</span><span class="p">:</span> <span class="mi">2</span><span class="p">,</span> <span class="s2">&quot;middle high&quot;</span><span class="p">:</span> <span class="mi">3</span><span class="p">,</span> <span class="s2">&quot;high&quot;</span><span class="p">:</span> <span class="mi">4</span><span class="p">},</span>
                <span class="s2">&quot;husb_edu&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;low&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;middle low&quot;</span><span class="p">:</span> <span class="mi">2</span><span class="p">,</span> <span class="s2">&quot;middle high&quot;</span><span class="p">:</span> <span class="mi">3</span><span class="p">,</span> <span class="s2">&quot;high&quot;</span><span class="p">:</span> <span class="mi">4</span><span class="p">},</span>
                <span class="s2">&quot;husb-occup&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;Cat1&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;Cat2&quot;</span><span class="p">:</span> <span class="mi">2</span><span class="p">,</span> <span class="s2">&quot;Cat3&quot;</span><span class="p">:</span> <span class="mi">3</span><span class="p">,</span> <span class="s2">&quot;Cat4&quot;</span><span class="p">:</span> <span class="mi">4</span><span class="p">},</span>
                <span class="s2">&quot;s-living_index&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;low&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;middle low&quot;</span><span class="p">:</span> <span class="mi">2</span><span class="p">,</span> <span class="s2">&quot;middle high&quot;</span><span class="p">:</span> <span class="mi">3</span><span class="p">,</span> <span class="s2">&quot;high&quot;</span><span class="p">:</span> <span class="mi">4</span><span class="p">},</span>
                <span class="s2">&quot;media_exp&quot;</span><span class="p">:</span> <span class="p">{</span><span class="s2">&quot;good&quot;</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span> <span class="s2">&quot;bad&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">}}</span>
<span class="n">contr_df</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="n">cleanup_nums</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

<span class="c1">#checking the data-set</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Data Types are: </span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="n">contr_df</span><span class="o">.</span><span class="n">dtypes</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Random rows in the Data-set&quot;</span><span class="p">)</span>
<span class="n">contr_df</span><span class="o">.</span><span class="n">sample</span><span class="p">(</span><span class="mi">6</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>Data Types are: 

wife_age           int64
wife_edu           int64
husb_edu           int64
children           int64
wife_religion     object
wife-working      object
husb-occup         int64
s-living_index     int64
media_exp          int64
contrac_mthd      object
dtype: object
Random rows in the Data-set
</pre>
</div>
</div>

<div class="output_area">

    <div class="prompt output_prompt">Out[4]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>wife_age</th>
      <th>wife_edu</th>
      <th>husb_edu</th>
      <th>children</th>
      <th>wife_religion</th>
      <th>wife-working</th>
      <th>husb-occup</th>
      <th>s-living_index</th>
      <th>media_exp</th>
      <th>contrac_mthd</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>473</th>
      <td>2</td>
      <td>4</td>
      <td>4</td>
      <td>4</td>
      <td>Other</td>
      <td>Yes</td>
      <td>1</td>
      <td>4</td>
      <td>0</td>
      <td>Long-term</td>
    </tr>
    <tr>
      <th>416</th>
      <td>3</td>
      <td>4</td>
      <td>3</td>
      <td>5</td>
      <td>Islam</td>
      <td>No</td>
      <td>1</td>
      <td>4</td>
      <td>0</td>
      <td>Long-term</td>
    </tr>
    <tr>
      <th>1330</th>
      <td>3</td>
      <td>4</td>
      <td>4</td>
      <td>5</td>
      <td>Other</td>
      <td>No</td>
      <td>1</td>
      <td>4</td>
      <td>0</td>
      <td>Short-term</td>
    </tr>
    <tr>
      <th>458</th>
      <td>3</td>
      <td>4</td>
      <td>4</td>
      <td>4</td>
      <td>Islam</td>
      <td>No</td>
      <td>1</td>
      <td>4</td>
      <td>0</td>
      <td>Long-term</td>
    </tr>
    <tr>
      <th>1184</th>
      <td>2</td>
      <td>3</td>
      <td>4</td>
      <td>2</td>
      <td>Islam</td>
      <td>No</td>
      <td>3</td>
      <td>4</td>
      <td>0</td>
      <td>No-use</td>
    </tr>
    <tr>
      <th>301</th>
      <td>2</td>
      <td>4</td>
      <td>2</td>
      <td>0</td>
      <td>Islam</td>
      <td>Yes</td>
      <td>2</td>
      <td>2</td>
      <td>0</td>
      <td>No-use</td>
    </tr>
  </tbody>
</table>
</div>
</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="Splitting-data-set-into-the-set-of-descriptive-features-and-the-target">Splitting data-set into the set of descriptive features and the target<a class="anchor-link" href="#Splitting-data-set-into-the-set-of-descriptive-features-and-the-target">&#182;</a></h3><p>Before encoding the target feature, it is required to split the data-set into descriptive features and the target feature. Then the target feature has been examined to see the distribution of each label. As shown below, the target features of No-use, Short-term and Long-term have 629, 511 and 333 instances, respectively.</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">contr_df_cat</span> <span class="o">=</span> <span class="n">contr_df</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="c1">#Splitting data-set into the set of descriptive features and the target</span>
<span class="n">Data</span> <span class="o">=</span> <span class="n">contr_df_cat</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">columns</span> <span class="o">=</span> <span class="s1">&#39;contrac_mthd&#39;</span><span class="p">)</span>
<span class="n">target</span> <span class="o">=</span> <span class="n">contr_df_cat</span><span class="p">[</span><span class="s1">&#39;contrac_mthd&#39;</span><span class="p">]</span>

<span class="c1"># Checking the count of instances in each label</span>
<span class="n">target</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[5]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>No-use        629
Short-term    511
Long-term     333
Name: contrac_mthd, dtype: int64</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="Making-Nominal-Categorical-Features-Numeric-(using-One-Hot-Encoding)">Making Nominal Categorical Features Numeric (using One-Hot-Encoding)<a class="anchor-link" href="#Making-Nominal-Categorical-Features-Numeric-(using-One-Hot-Encoding)">&#182;</a></h3><p>In the data-set, "wife_religion", and "wife-working" attributes are considered as nominal variables because they possess no natural ordering. The One-Hot-Encoding method has been used in for transforming these nominal variables to numerical.</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">categorical_cols</span> <span class="o">=</span> <span class="n">Data</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">Data</span><span class="o">.</span><span class="n">dtypes</span><span class="o">==</span><span class="nb">object</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">categorical_cols</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[6]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>[&#39;wife_religion&#39;, &#39;wife-working&#39;]</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>For two-level categorical features, drop_first option has been set to 'True' to encode the variable into a single column of 0 or 1. If there are ordinal categorical features with more than two levels, <em>Data = pd.get_dummies(Data)</em> function can be used.</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">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">categorical_cols</span><span class="p">:</span>
    <span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">Data</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">n</span> <span class="o">==</span> <span class="mi">2</span><span class="p">):</span>
        <span class="n">Data</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">Data</span><span class="p">[</span><span class="n">col</span><span class="p">],</span> <span class="n">drop_first</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

<span class="c1"># use one-hot-encoding for categorical features with &gt;2 levels</span>
<span class="c1">#Data = pd.get_dummies(Data)</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">Data</span><span class="o">.</span><span class="n">sample</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[8]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>wife_age</th>
      <th>wife_edu</th>
      <th>husb_edu</th>
      <th>children</th>
      <th>wife_religion</th>
      <th>wife-working</th>
      <th>husb-occup</th>
      <th>s-living_index</th>
      <th>media_exp</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>608</th>
      <td>3</td>
      <td>4</td>
      <td>4</td>
      <td>5</td>
      <td>1</td>
      <td>0</td>
      <td>2</td>
      <td>4</td>
      <td>0</td>
    </tr>
    <tr>
      <th>863</th>
      <td>1</td>
      <td>4</td>
      <td>3</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>3</td>
      <td>4</td>
      <td>0</td>
    </tr>
    <tr>
      <th>1111</th>
      <td>1</td>
      <td>4</td>
      <td>4</td>
      <td>1</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>3</td>
      <td>0</td>
    </tr>
    <tr>
      <th>1373</th>
      <td>2</td>
      <td>4</td>
      <td>4</td>
      <td>2</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>4</td>
      <td>0</td>
    </tr>
    <tr>
      <th>691</th>
      <td>2</td>
      <td>2</td>
      <td>4</td>
      <td>3</td>
      <td>0</td>
      <td>0</td>
      <td>3</td>
      <td>3</td>
      <td>0</td>
    </tr>
  </tbody>
</table>
</div>
</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="Encoding-Target">Encoding Target<a class="anchor-link" href="#Encoding-Target">&#182;</a></h3><p>The target feature has been encoded to numeric values as shown below:</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="c1">#Encoding Target</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">preprocessing</span>
<span class="n">target</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="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">target</span><span class="p">)</span>

<span class="c1">#Checking the encoding</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">target</span><span class="p">))</span>
<span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">target</span><span class="p">,</span> <span class="n">return_counts</span> <span class="o">=</span> <span class="kc">True</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>&lt;class &#39;numpy.ndarray&#39;&gt;
</pre>
</div>
</div>

<div class="output_area">

    <div class="prompt output_prompt">Out[9]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>(array([0, 1, 2]), array([333, 629, 511], dtype=int64))</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 'Long-term' is labeled as 0, 'No-use' is labeled as 1 and 'Short-term' is labeled as 2 due to the fact that the LabelEncoder() function labels them in alphabetical order.</p>

</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="Scaling-Descriptive-Features">Scaling Descriptive Features<a class="anchor-link" href="#Scaling-Descriptive-Features">&#182;</a></h3><p>Feature scaling  (Standardization) is performed to get the highly varying numeric data to a common scale. Even though the scaling is essential only for some of the models (such as KNN, Deep learning and SVMs), scaling is highly recommended for any model. Therefore, Min-Max Scaling has been used in this task, which can convert numerical data to common scale between 0 and 1.</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="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">preprocessing</span>

<span class="c1">#Data_df = Data.copy()</span>

<span class="n">Data_scaler</span> <span class="o">=</span> <span class="n">preprocessing</span><span class="o">.</span><span class="n">MinMaxScaler</span><span class="p">()</span>
<span class="n">Data_scaler</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">Data</span><span class="p">)</span>
<span class="n">Data</span> <span class="o">=</span> <span class="n">Data_scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">Data</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="Feature-Selection-&amp;-Ranking">Feature Selection &amp; Ranking<a class="anchor-link" href="#Feature-Selection-&amp;-Ranking">&#182;</a></h3><p>In this section, best 6 features of the data-set has been examined using Random Forest Importance (RFI) to get an quick understanding on the importance of each feature. However, during the hyperparameter tuning phase inside the pipeline, the feature selection is performed in more systematic and detailed way using RFI, which eventually determines the optimal number of features for each classifier.</p>

</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">
<h4 id="Selecting-the-best-6-features-in-the-dataset-using-RFI-(Random-Forest-Importance)">Selecting the best 6 features in the dataset using RFI (Random Forest Importance)<a class="anchor-link" href="#Selecting-the-best-6-features-in-the-dataset-using-RFI-(Random-Forest-Importance)">&#182;</a></h4>
</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="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestClassifier</span>
<span class="n">num_features</span> <span class="o">=</span> <span class="mi">6</span>
<span class="n">model_rfi</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
<span class="n">model_rfi</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">Data</span><span class="p">,</span> <span class="n">target</span><span class="p">)</span>
<span class="n">fs_indices_rfi</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argsort</span><span class="p">(</span><span class="n">model_rfi</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)[::</span><span class="o">-</span><span class="mi">1</span><span class="p">][</span><span class="mi">0</span><span class="p">:</span><span class="n">num_features</span><span class="p">]</span>

<span class="n">best_features_rfi</span> <span class="o">=</span> <span class="n">contr_df_cat</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">fs_indices_rfi</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
<span class="n">best_features_rfi</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[11]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>array([&#39;children&#39;, &#39;s-living_index&#39;, &#39;wife_edu&#39;, &#39;husb-occup&#39;, &#39;wife_age&#39;,
       &#39;husb_edu&#39;], dtype=object)</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;[12]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">feature_importances_rfi</span> <span class="o">=</span> <span class="n">model_rfi</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">[</span><span class="n">fs_indices_rfi</span><span class="p">]</span>
<span class="n">feature_importances_rfi</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[12]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>array([0.33239353, 0.12593069, 0.11249967, 0.11167203, 0.1006196 ,
       0.09379219])</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;[13]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">altair</span> <span class="k">as</span> <span class="nn">alt</span>
<span class="n">alt</span><span class="o">.</span><span class="n">renderers</span><span class="o">.</span><span class="n">enable</span><span class="p">(</span><span class="s1">&#39;notebook&#39;</span><span class="p">)</span>

<span class="k">def</span> <span class="nf">plot_imp</span><span class="p">(</span><span class="n">best_features</span><span class="p">,</span> <span class="n">scores</span><span class="p">,</span> <span class="n">method_name</span><span class="p">,</span> <span class="n">color</span><span class="p">):</span>
    
    <span class="n">df</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;features&#39;</span><span class="p">:</span> <span class="n">best_features</span><span class="p">,</span> 
                       <span class="s1">&#39;importances&#39;</span><span class="p">:</span> <span class="n">scores</span><span class="p">})</span>
    
    <span class="n">chart</span> <span class="o">=</span> <span class="n">alt</span><span class="o">.</span><span class="n">Chart</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> 
                      <span class="n">width</span><span class="o">=</span><span class="mi">500</span><span class="p">,</span> 
                      <span class="n">title</span><span class="o">=</span><span class="n">method_name</span> <span class="o">+</span> <span class="s1">&#39; Feature Importances&#39;</span>
                     <span class="p">)</span><span class="o">.</span><span class="n">mark_bar</span><span class="p">(</span><span class="n">opacity</span><span class="o">=</span><span class="mf">0.85</span><span class="p">,</span> 
                                <span class="n">color</span><span class="o">=</span><span class="n">color</span><span class="p">)</span><span class="o">.</span><span class="n">encode</span><span class="p">(</span>
        <span class="n">alt</span><span class="o">.</span><span class="n">X</span><span class="p">(</span><span class="s1">&#39;features&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Feature&#39;</span><span class="p">,</span> <span class="n">sort</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">alt</span><span class="o">.</span><span class="n">AxisConfig</span><span class="p">(</span><span class="n">labelAngle</span><span class="o">=</span><span class="mi">45</span><span class="p">)),</span>
        <span class="n">alt</span><span class="o">.</span><span class="n">Y</span><span class="p">(</span><span class="s1">&#39;importances&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Importance&#39;</span><span class="p">)</span>
    <span class="p">)</span>
    
    <span class="k">return</span> <span class="n">chart</span>

<span class="c1">#plotting</span>
<span class="n">plot_imp</span><span class="p">(</span><span class="n">best_features_rfi</span><span class="p">,</span> <span class="n">feature_importances_rfi</span><span class="p">,</span> <span class="s1">&#39;Random Forest&#39;</span><span class="p">,</span> <span class="s1">&#39;blue&#39;</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 id="3749653c-13b1-44a0-bfb8-1b57f0e44fbf"></div>
<div class="output_subarea output_javascript ">
<script type="text/javascript">
var element = $('#3749653c-13b1-44a0-bfb8-1b57f0e44fbf');
var spec = {"config": {"view": {"width": 400, "height": 300}, "mark": {"tooltip": null}}, "data": {"name": "data-46e1cc1357946dd13da390f943a452c6"}, "mark": {"type": "bar", "color": "blue", "opacity": 0.85}, "encoding": {"x": {"type": "nominal", "axis": {"labelAngle": 45}, "field": "features", "sort": null, "title": "Feature"}, "y": {"type": "quantitative", "field": "importances", "title": "Importance"}}, "title": "Random Forest Feature Importances", "width": 500, "$schema": "https://vega.github.io/schema/vega-lite/v3.2.1.json", "datasets": {"data-46e1cc1357946dd13da390f943a452c6": [{"features": "children", "importances": 0.3323935346629785}, {"features": "s-living_index", "importances": 0.1259306870228802}, {"features": "wife_edu", "importances": 0.1124996744074474}, {"features": "husb-occup", "importances": 0.11167203245753538}, {"features": "wife_age", "importances": 0.10061959616840038}, {"features": "husb_edu", "importances": 0.09379219444082806}]}};
var opt = {};
var type = "vega-lite";
var id = "d6b023b0-5d31-4f66-ae11-881205ec9fa0";

var output_area = this;

require(["nbextensions/jupyter-vega/index"], function(vega) {
  var target = document.createElement("div");
  target.id = id;
  target.className = "vega-embed";

  var style = document.createElement("style");
  style.textContent = [
    ".vega-embed .error p {",
    "  color: firebrick;",
    "  font-size: 14px;",
    "}",
  ].join("\\n");

  // element is a jQuery wrapped DOM element inside the output area
  // see http://ipython.readthedocs.io/en/stable/api/generated/\
  // IPython.display.html#IPython.display.Javascript.__init__
  element[0].appendChild(target);
  element[0].appendChild(style);

  vega.render("#" + id, spec, type, opt, output_area);
}, function (err) {
  if (err.requireType !== "scripterror") {
    throw(err);
  }
});

</script>
</div>

</div>

<div class="output_area">

    <div class="prompt output_prompt">Out[13]:</div>


<div class="output_text output_subarea output_execute_result">
<pre></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 text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>As per the results above, best 6 features of the data-set are 'children', 's-living_index', 'wife_edu', 'husb-occup',  'wife_age', and 'husb_edu'.</p>

</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="Splitting-Data-into-Training-and-Test-Sets">Splitting Data into Training and Test Sets<a class="anchor-link" href="#Splitting-Data-into-Training-and-Test-Sets">&#182;</a></h3><p>Data sampling is not required as the original data-set is not a significantly larger one: data-set only has 1473 observations.
As shown below, the model has been trained and tuned on 1031 rows of training data and tested on 442 rows of test data. This is constituted from 70:30 ratio of training Vs test observations in the data-set.</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="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">train_test_split</span>

<span class="n">D_train</span><span class="p">,</span> <span class="n">D_test</span><span class="p">,</span> <span class="n">t_train</span><span class="p">,</span> <span class="n">t_test</span> <span class="o">=</span> \
    <span class="n">train_test_split</span><span class="p">(</span><span class="n">Data</span><span class="p">,</span> <span class="n">target</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">stratify</span><span class="o">=</span><span class="n">target</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">999</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">D_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">D_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>(1031, 9)
(442, 9)
</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="Model-Evaluation-Strategy">Model Evaluation Strategy<a class="anchor-link" href="#Model-Evaluation-Strategy">&#182;</a></h3><p>Stratified 5-fold cross-validation with 3 repetitions has been used as the model evaluation strategy.</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="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">RepeatedStratifiedKFold</span><span class="p">,</span> <span class="n">GridSearchCV</span>

<span class="n">cv_method</span> <span class="o">=</span> <span class="n">RepeatedStratifiedKFold</span><span class="p">(</span><span class="n">n_splits</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span>
                                    <span class="n">n_repeats</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span>
                                    <span class="n">random_state</span><span class="o">=</span><span class="mi">999</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">
<h1 id="4.-Hyperparameter-Tuning-">4. Hyperparameter Tuning <a class="anchor" id="4" /><a class="anchor-link" href="#4.-Hyperparameter-Tuning-">&#182;</a></h1>
</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>Since a pipeline can be used to automate the work-flows of the machine learning, it has been used in for feature selection and hyperparameter tuning. The grid search for hyperparameter tuning of each classifiers has been performed via cross-validation approach. In addition to the hyperparameter tuning, feature selection using RFI has also been stacked to the pipeline along with the checks for best number of feature to be selected.</p>
<p>KNN, NB &amp; DT classifiers have been chosen for this classification task. As shown below, each classifier has been optimized using the training data for optimal parameters.</p>

</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="K-Nearest-Neighbors-(KNN)">K-Nearest Neighbors (KNN)<a class="anchor-link" href="#K-Nearest-Neighbors-(KNN)">&#182;</a></h3><p>A dictionary for the hyperparameters of the KNN classifier is defined as below:</p>
<ul>
<li>value range for "number of neighbors (n_neighbors)": 1, 10, 20, 40, 60, 100</li>
<li>values for $p$: 1 (Manhattan), 2 (Euclidean)</li>
</ul>

</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="kn">from</span> <span class="nn">sklearn.base</span> <span class="k">import</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">TransformerMixin</span>

<span class="c1"># custom function for RFI feature selection inside a pipeline</span>
<span class="k">class</span> <span class="nc">RFIFeatureSelector</span><span class="p">(</span><span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">TransformerMixin</span><span class="p">):</span>
    
    <span class="c1"># class constructor </span>
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">n_features_</span><span class="o">=</span><span class="mi">6</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">n_features_</span> <span class="o">=</span> <span class="n">n_features_</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">fs_indices_</span> <span class="o">=</span> <span class="kc">None</span>

    <span class="c1"># override the fit function</span>
    <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
        <span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestClassifier</span>
        <span class="kn">from</span> <span class="nn">numpy</span> <span class="k">import</span> <span class="n">argsort</span>
        <span class="n">model_rfi</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
        <span class="n">model_rfi</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">fs_indices_</span> <span class="o">=</span> <span class="n">argsort</span><span class="p">(</span><span class="n">model_rfi</span><span class="o">.</span><span class="n">feature_importances_</span><span class="p">)[::</span><span class="o">-</span><span class="mi">1</span><span class="p">][</span><span class="mi">0</span><span class="p">:</span><span class="bp">self</span><span class="o">.</span><span class="n">n_features_</span><span class="p">]</span> 
        <span class="k">return</span> <span class="bp">self</span> 
    
    <span class="c1"># override the transform function</span>
    <span class="k">def</span> <span class="nf">transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">X</span><span class="p">[:,</span> <span class="bp">self</span><span class="o">.</span><span class="n">fs_indices_</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;[17]:</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.pipeline</span> <span class="k">import</span> <span class="n">Pipeline</span>
<span class="kn">from</span> <span class="nn">sklearn.neighbors</span> <span class="k">import</span> <span class="n">KNeighborsClassifier</span>
<span class="c1">#from sklearn.metrics import roc_auc_score</span>

<span class="n">pipe_KNN</span> <span class="o">=</span> <span class="n">Pipeline</span><span class="p">(</span><span class="n">steps</span><span class="o">=</span><span class="p">[(</span><span class="s1">&#39;rfi_fs&#39;</span><span class="p">,</span> <span class="n">RFIFeatureSelector</span><span class="p">()),</span> 
                           <span class="p">(</span><span class="s1">&#39;knn&#39;</span><span class="p">,</span> <span class="n">KNeighborsClassifier</span><span class="p">())])</span>

<span class="n">params_pipe_KNN</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;rfi_fs__n_features_&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">6</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">8</span><span class="p">,</span><span class="mi">9</span><span class="p">,</span> <span class="n">Data</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;knn__n_neighbors&#39;</span><span class="p">:</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">20</span><span class="p">,</span> <span class="mi">40</span><span class="p">,</span> <span class="mi">60</span><span class="p">,</span> <span class="mi">100</span><span class="p">],</span>
                   <span class="s1">&#39;knn__p&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">]}</span>

<span class="n">gs_pipe_KNN</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">pipe_KNN</span><span class="p">,</span> 
                           <span class="n">param_grid</span><span class="o">=</span><span class="n">params_pipe_KNN</span><span class="p">,</span> 
                           <span class="n">cv</span><span class="o">=</span><span class="n">cv_method</span><span class="p">,</span>
                           <span class="n">refit</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
                           <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">2</span><span class="p">,</span>
                           <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">,</span>
                           <span class="n">verbose</span><span class="o">=</span><span class="mi">1</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;[18]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">gs_pipe_KNN</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">D_train</span><span class="p">,</span> <span class="n">t_train</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>Fitting 15 folds for each of 96 candidates, totalling 1440 fits
</pre>
</div>
</div>

<div class="output_area">

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


<div class="output_subarea output_stream output_stderr output_text">
<pre>[Parallel(n_jobs=-2)]: Using backend LokyBackend with 3 concurrent workers.
[Parallel(n_jobs=-2)]: Done  44 tasks      | elapsed:    7.7s
[Parallel(n_jobs=-2)]: Done 194 tasks      | elapsed:   18.6s
[Parallel(n_jobs=-2)]: Done 444 tasks      | elapsed:   36.8s
[Parallel(n_jobs=-2)]: Done 794 tasks      | elapsed:  1.0min
[Parallel(n_jobs=-2)]: Done 1244 tasks      | elapsed:  1.6min
[Parallel(n_jobs=-2)]: Done 1440 out of 1440 | elapsed:  1.9min finished
C:\Users\udesh\Software\Anaconda2\lib\site-packages\sklearn\model_selection\_search.py:841: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
</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;[19]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">gs_pipe_KNN</span><span class="o">.</span><span class="n">best_params_</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[19]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>{&#39;knn__n_neighbors&#39;: 20, &#39;knn__p&#39;: 2, &#39;rfi_fs__n_features_&#39;: 5}</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">gs_pipe_KNN</span><span class="o">.</span><span class="n">best_score_</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[20]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>0.5354025218234724</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>As shown above, the KNN model has a mean accuracy score of 0.535. The best parameters for the KNN model are 5 features with 20 nearest neighbors and $p=2$.</p>

</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">
<h4 id="Visualising-the-KNN-model-accuracy-based-on-other-parameter-combinations">Visualising the KNN model accuracy based on other parameter combinations<a class="anchor-link" href="#Visualising-the-KNN-model-accuracy-based-on-other-parameter-combinations">&#182;</a></h4>
</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="c1"># custom function to format the search results as a Pandas data frame</span>

<span class="k">def</span> <span class="nf">get_search_results</span><span class="p">(</span><span class="n">gs</span><span class="p">):</span>
    
    <span class="k">def</span> <span class="nf">model_result</span><span class="p">(</span><span class="n">scores</span><span class="p">,</span> <span class="n">params</span><span class="p">):</span>
        <span class="n">scores</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;mean_score&#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="s1">&#39;std_score&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">scores</span><span class="p">),</span>
             <span class="s1">&#39;min_score&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="n">scores</span><span class="p">),</span>
             <span class="s1">&#39;max_score&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">scores</span><span class="p">)}</span>
        <span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">({</span><span class="o">**</span><span class="n">params</span><span class="p">,</span><span class="o">**</span><span class="n">scores</span><span class="p">})</span>
    
    <span class="n">models</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">scores</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="n">gs</span><span class="o">.</span><span class="n">n_splits_</span><span class="p">):</span>
        <span class="n">key</span> <span class="o">=</span> <span class="n">f</span><span class="s2">&quot;split</span><span class="si">{i}</span><span class="s2">_test_score&quot;</span>
        <span class="n">r</span> <span class="o">=</span> <span class="n">gs</span><span class="o">.</span><span class="n">cv_results_</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
        <span class="n">scores</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">r</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">))</span>
        
    <span class="n">all_scores</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">scores</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">p</span><span class="p">,</span> <span class="n">s</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">gs</span><span class="o">.</span><span class="n">cv_results_</span><span class="p">[</span><span class="s1">&#39;params&#39;</span><span class="p">],</span> <span class="n">all_scores</span><span class="p">):</span>
        <span class="n">models</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">model_result</span><span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="n">p</span><span class="p">)))</span>

    <span class="n">pipe_results</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">models</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">sort_values</span><span class="p">([</span><span class="s1">&#39;mean_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="n">columns_first</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;mean_score&#39;</span><span class="p">,</span> <span class="s1">&#39;std_score&#39;</span><span class="p">,</span> <span class="s1">&#39;max_score&#39;</span><span class="p">,</span> <span class="s1">&#39;min_score&#39;</span><span class="p">]</span>
    <span class="n">columns</span> <span class="o">=</span> <span class="n">columns_first</span> <span class="o">+</span> <span class="p">[</span><span class="n">c</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">pipe_results</span><span class="o">.</span><span class="n">columns</span> <span class="k">if</span> <span class="n">c</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">columns_first</span><span class="p">]</span>

    <span class="k">return</span> <span class="n">pipe_results</span><span class="p">[</span><span class="n">columns</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;[22]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results_KNN</span> <span class="o">=</span> <span class="n">get_search_results</span><span class="p">(</span><span class="n">gs_pipe_KNN</span><span class="p">)</span>
<span class="n">results_KNN</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[22]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>mean_score</th>
      <th>std_score</th>
      <th>max_score</th>
      <th>min_score</th>
      <th>knn__n_neighbors</th>
      <th>knn__p</th>
      <th>rfi_fs__n_features_</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>42</th>
      <td>0.535442</td>
      <td>0.030889</td>
      <td>0.595122</td>
      <td>0.487923</td>
      <td>20.0</td>
      <td>2.0</td>
      <td>5.0</td>
    </tr>
    <tr>
      <th>35</th>
      <td>0.534826</td>
      <td>0.030386</td>
      <td>0.619512</td>
      <td>0.492754</td>
      <td>20.0</td>
      <td>1.0</td>
      <td>6.0</td>
    </tr>
    <tr>
      <th>67</th>
      <td>0.531927</td>
      <td>0.030572</td>
      <td>0.590244</td>
      <td>0.473430</td>
      <td>60.0</td>
      <td>1.0</td>
      <td>6.0</td>
    </tr>
    <tr>
      <th>51</th>
      <td>0.531637</td>
      <td>0.037078</td>
      <td>0.590244</td>
      <td>0.439614</td>
      <td>40.0</td>
      <td>1.0</td>
      <td>6.0</td>
    </tr>
    <tr>
      <th>34</th>
      <td>0.530589</td>
      <td>0.026493</td>
      <td>0.570048</td>
      <td>0.487923</td>
      <td>20.0</td>
      <td>1.0</td>
      <td>5.0</td>
    </tr>
  </tbody>
</table>
</div>
</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">results_KNN_5_features</span> <span class="o">=</span> <span class="n">results_KNN</span><span class="p">[</span><span class="n">results_KNN</span><span class="p">[</span><span class="s1">&#39;rfi_fs__n_features_&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mf">5.0</span><span class="p">]</span>

<span class="n">alt</span><span class="o">.</span><span class="n">Chart</span><span class="p">(</span><span class="n">results_KNN_5_features</span><span class="p">,</span> 
          <span class="n">title</span><span class="o">=</span><span class="s1">&#39;KNN Performance Comparison with 5 Features&#39;</span>
         <span class="p">)</span><span class="o">.</span><span class="n">mark_line</span><span class="p">(</span><span class="n">point</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">encode</span><span class="p">(</span>
    <span class="n">alt</span><span class="o">.</span><span class="n">X</span><span class="p">(</span><span class="s1">&#39;knn__n_neighbors&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Number of Neighbors&#39;</span><span class="p">),</span>
    <span class="n">alt</span><span class="o">.</span><span class="n">Y</span><span class="p">(</span><span class="s1">&#39;mean_score&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="n">alt</span><span class="o">.</span><span class="n">Scale</span><span class="p">(</span><span class="n">zero</span><span class="o">=</span><span class="kc">False</span><span class="p">)),</span>
    <span class="n">alt</span><span class="o">.</span><span class="n">Color</span><span class="p">(</span><span class="s1">&#39;knn__p:N&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;p&#39;</span><span class="p">)</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 id="cfde1209-9e9a-4c6b-a68f-a60b19ae0c6b"></div>
<div class="output_subarea output_javascript ">
<script type="text/javascript">
var element = $('#cfde1209-9e9a-4c6b-a68f-a60b19ae0c6b');
var spec = {"config": {"view": {"width": 400, "height": 300}, "mark": {"tooltip": null}}, "data": {"name": "data-f255d38514b9c57665341e071fdc18c8"}, "mark": {"type": "line", "point": true}, "encoding": {"color": {"type": "nominal", "field": "knn__p", "title": "p"}, "x": {"type": "quantitative", "field": "knn__n_neighbors", "title": "Number of Neighbors"}, "y": {"type": "quantitative", "field": "mean_score", "scale": {"zero": false}, "title": "accuracy"}}, "title": "KNN Performance Comparison with 5 Features", "$schema": "https://vega.github.io/schema/vega-lite/v3.2.1.json", "datasets": {"data-f255d38514b9c57665341e071fdc18c8": [{"mean_score": 0.535441655865834, "std_score": 0.030889079362594555, "max_score": 0.5951219512195122, "min_score": 0.48792270531400966, "knn__n_neighbors": 20.0, "knn__p": 2.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5305887435685951, "std_score": 0.02649339267000084, "max_score": 0.5700483091787439, "min_score": 0.48792270531400966, "knn__n_neighbors": 20.0, "knn__p": 1.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5254891795294765, "std_score": 0.038552484711851576, "max_score": 0.6048780487804878, "min_score": 0.4444444444444444, "knn__n_neighbors": 40.0, "knn__p": 1.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5219370802403678, "std_score": 0.03908379637741051, "max_score": 0.6, "min_score": 0.4396135265700483, "knn__n_neighbors": 60.0, "knn__p": 1.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5209206236989907, "std_score": 0.032609045333427844, "max_score": 0.5707317073170731, "min_score": 0.46859903381642515, "knn__n_neighbors": 40.0, "knn__p": 2.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5199293036408625, "std_score": 0.029940932338207493, "max_score": 0.5707317073170731, "min_score": 0.46859903381642515, "knn__n_neighbors": 10.0, "knn__p": 1.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5176968697223204, "std_score": 0.027327176293741928, "max_score": 0.5804878048780487, "min_score": 0.4830917874396135, "knn__n_neighbors": 60.0, "knn__p": 2.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5170181846746004, "std_score": 0.03532203179544736, "max_score": 0.5804878048780487, "min_score": 0.4492753623188406, "knn__n_neighbors": 10.0, "knn__p": 2.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5067467892070225, "std_score": 0.034374588741512155, "max_score": 0.5609756097560976, "min_score": 0.43478260869565216, "knn__n_neighbors": 100.0, "knn__p": 1.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.5012277601036881, "std_score": 0.031718065424012204, "max_score": 0.5609756097560976, "min_score": 0.43478260869565216, "knn__n_neighbors": 100.0, "knn__p": 2.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.4633612191194377, "std_score": 0.034678057315250504, "max_score": 0.5365853658536586, "min_score": 0.4106280193236715, "knn__n_neighbors": 1.0, "knn__p": 1.0, "rfi_fs__n_features_": 5.0}, {"mean_score": 0.45751698676407065, "std_score": 0.033263915357139046, "max_score": 0.5317073170731708, "min_score": 0.4106280193236715, "knn__n_neighbors": 1.0, "knn__p": 2.0, "rfi_fs__n_features_": 5.0}]}};
var opt = {};
var type = "vega-lite";
var id = "7a9bd8ce-37a7-42e0-becd-6de833e62d73";

var output_area = this;

require(["nbextensions/jupyter-vega/index"], function(vega) {
  var target = document.createElement("div");
  target.id = id;
  target.className = "vega-embed";

  var style = document.createElement("style");
  style.textContent = [
    ".vega-embed .error p {",
    "  color: firebrick;",
    "  font-size: 14px;",
    "}",
  ].join("\\n");

  // element is a jQuery wrapped DOM element inside the output area
  // see http://ipython.readthedocs.io/en/stable/api/generated/\
  // IPython.display.html#IPython.display.Javascript.__init__
  element[0].appendChild(target);
  element[0].appendChild(style);

  vega.render("#" + id, spec, type, opt, output_area);
}, function (err) {
  if (err.requireType !== "scripterror") {
    throw(err);
  }
});

</script>
</div>

</div>

<div class="output_area">

    <div class="prompt output_prompt">Out[23]:</div>


<div class="output_text output_subarea output_execute_result">
<pre></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 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="(Gaussian)-Naive-Bayes-(NB)">(Gaussian) Naive Bayes (NB)<a class="anchor-link" href="#(Gaussian)-Naive-Bayes-(NB)">&#182;</a></h3><p>A dictionary for the hyperparameters of the NB classifier is defined as below:</p>
<ul>
<li>var_smoothing: start with 10 and end with $10^{-2}$ with 10 different values for random search over only 20 different values</li>
</ul>

</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="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="k">import</span> <span class="n">PowerTransformer</span>
<span class="n">D_train_transformed</span> <span class="o">=</span> <span class="n">PowerTransformer</span><span class="p">()</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">D_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;[40]:</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.naive_bayes</span> <span class="k">import</span> <span class="n">GaussianNB</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">RandomizedSearchCV</span>

<span class="n">pipe_NB</span> <span class="o">=</span> <span class="n">Pipeline</span><span class="p">([(</span><span class="s1">&#39;rfi_fs&#39;</span><span class="p">,</span> <span class="n">RFIFeatureSelector</span><span class="p">()),</span> 
                     <span class="p">(</span><span class="s1">&#39;nb&#39;</span><span class="p">,</span> <span class="n">GaussianNB</span><span class="p">())])</span>

<span class="n">params_pipe_NB</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;rfi_fs__n_features_&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">6</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">8</span><span class="p">,</span><span class="mi">9</span><span class="p">,</span> <span class="n">Data</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;nb__var_smoothing&#39;</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">logspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="o">-</span><span class="mi">2</span><span class="p">,</span> <span class="n">num</span><span class="o">=</span><span class="mi">10</span><span class="p">)}</span>

<span class="n">n_iter_search</span> <span class="o">=</span> <span class="mi">20</span>
<span class="n">gs_pipe_NB</span> <span class="o">=</span> <span class="n">RandomizedSearchCV</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">pipe_NB</span><span class="p">,</span> 
                          <span class="n">param_distributions</span><span class="o">=</span><span class="n">params_pipe_NB</span><span class="p">,</span> 
                          <span class="n">cv</span><span class="o">=</span><span class="n">cv_method</span><span class="p">,</span>
                          <span class="n">refit</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
                          <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">2</span><span class="p">,</span>
                          <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">,</span>
                          <span class="n">n_iter</span><span class="o">=</span><span class="n">n_iter_search</span><span class="p">,</span>
                          <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> 

<span class="n">gs_pipe_NB</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">D_train_transformed</span><span class="p">,</span> <span class="n">t_train</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>Fitting 15 folds for each of 20 candidates, totalling 300 fits
</pre>
</div>
</div>

<div class="output_area">

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


<div class="output_subarea output_stream output_stderr output_text">
<pre>[Parallel(n_jobs=-2)]: Using backend LokyBackend with 3 concurrent workers.
[Parallel(n_jobs=-2)]: Done  44 tasks      | elapsed:    2.8s
[Parallel(n_jobs=-2)]: Done 194 tasks      | elapsed:   11.5s
[Parallel(n_jobs=-2)]: Done 300 out of 300 | elapsed:   17.9s finished
</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">gs_pipe_NB</span><span class="o">.</span><span class="n">best_params_</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[41]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>{&#39;rfi_fs__n_features_&#39;: 5, &#39;nb__var_smoothing&#39;: 0.0774263682681127}</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;[42]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">gs_pipe_NB</span><span class="o">.</span><span class="n">best_score_</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[42]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>0.5337859683155513</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>As shown above, NB model has a mean accuracy score of 0.534. The best parameters for the NB model are 5 features with 0.077 var_smoothing.</p>

</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">
<h4 id="Visualising-the-NB-model-accuracy-based-on-other-parameter-combinations">Visualising the NB model accuracy based on other parameter combinations<a class="anchor-link" href="#Visualising-the-NB-model-accuracy-based-on-other-parameter-combinations">&#182;</a></h4>
</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_NB</span> <span class="o">=</span> <span class="n">get_search_results</span><span class="p">(</span><span class="n">gs_pipe_NB</span><span class="p">)</span>
<span class="n">results_NB</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[43]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>mean_score</th>
      <th>std_score</th>
      <th>max_score</th>
      <th>min_score</th>
      <th>rfi_fs__n_features_</th>
      <th>nb__var_smoothing</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>5</th>
      <td>0.533882</td>
      <td>0.031144</td>
      <td>0.595122</td>
      <td>0.473430</td>
      <td>5.0</td>
      <td>0.077426</td>
    </tr>
    <tr>
      <th>8</th>
      <td>0.532590</td>
      <td>0.029704</td>
      <td>0.585366</td>
      <td>0.473430</td>
      <td>5.0</td>
      <td>0.016681</td>
    </tr>
    <tr>
      <th>18</th>
      <td>0.529038</td>
      <td>0.029615</td>
      <td>0.590244</td>
      <td>0.483092</td>
      <td>5.0</td>
      <td>0.215443</td>
    </tr>
    <tr>
      <th>17</th>
      <td>0.527428</td>
      <td>0.036078</td>
      <td>0.604878</td>
      <td>0.473430</td>
      <td>9.0</td>
      <td>0.129155</td>
    </tr>
    <tr>
      <th>19</th>
      <td>0.526136</td>
      <td>0.036811</td>
      <td>0.604878</td>
      <td>0.473430</td>
      <td>9.0</td>
      <td>0.027826</td>
    </tr>
  </tbody>
</table>
</div>
</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">results_NB_5_features</span> <span class="o">=</span> <span class="n">results_NB</span><span class="p">[</span><span class="n">results_NB</span><span class="p">[</span><span class="s1">&#39;rfi_fs__n_features_&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mf">5.0</span><span class="p">]</span>

<span class="n">alt</span><span class="o">.</span><span class="n">Chart</span><span class="p">(</span><span class="n">results_NB_5_features</span><span class="p">,</span> 
          <span class="n">title</span><span class="o">=</span><span class="s1">&#39;NB Performance Comparison with 5 Features&#39;</span>
         <span class="p">)</span><span class="o">.</span><span class="n">mark_line</span><span class="p">(</span><span class="n">point</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">encode</span><span class="p">(</span>
    <span class="n">alt</span><span class="o">.</span><span class="n">X</span><span class="p">(</span><span class="s1">&#39;nb__var_smoothing&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Var. Smoothing&#39;</span><span class="p">),</span>
    <span class="n">alt</span><span class="o">.</span><span class="n">Y</span><span class="p">(</span><span class="s1">&#39;mean_score&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="n">alt</span><span class="o">.</span><span class="n">Scale</span><span class="p">(</span><span class="n">zero</span><span class="o">=</span><span class="kc">False</span><span class="p">))</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 id="bed5b2b2-729a-429f-b2bd-a152434eaa9c"></div>
<div class="output_subarea output_javascript ">
<script type="text/javascript">
var element = $('#bed5b2b2-729a-429f-b2bd-a152434eaa9c');
var spec = {"config": {"view": {"width": 400, "height": 300}, "mark": {"tooltip": null}}, "data": {"name": "data-667442add1a4950c077143adbfa103b0"}, "mark": {"type": "line", "point": true}, "encoding": {"x": {"type": "quantitative", "field": "nb__var_smoothing", "title": "Var. Smoothing"}, "y": {"type": "quantitative", "field": "mean_score", "scale": {"zero": false}, "title": "accuracy"}}, "title": "NB Performance Comparison with 5 Features", "$schema": "https://vega.github.io/schema/vega-lite/v3.2.1.json", "datasets": {"data-667442add1a4950c077143adbfa103b0": [{"mean_score": 0.5338816228741996, "std_score": 0.03114430633513517, "max_score": 0.5951219512195122, "min_score": 0.47342995169082125, "rfi_fs__n_features_": 5.0, "nb__var_smoothing": 0.0774263682681127}, {"mean_score": 0.532590236047288, "std_score": 0.029704319610618517, "max_score": 0.5853658536585366, "min_score": 0.47342995169082125, "rfi_fs__n_features_": 5.0, "nb__var_smoothing": 0.016681005372000592}, {"mean_score": 0.5290381367581791, "std_score": 0.029614710832875098, "max_score": 0.5902439024390244, "min_score": 0.4830917874396135, "rfi_fs__n_features_": 5.0, "nb__var_smoothing": 0.2154434690031884}, {"mean_score": 0.5248419150858176, "std_score": 0.033120406800353004, "max_score": 0.6048780487804878, "min_score": 0.4782608695652174, "rfi_fs__n_features_": 5.0, "nb__var_smoothing": 0.35938136638046275}, {"mean_score": 0.5193166018616708, "std_score": 0.029298350965748617, "max_score": 0.5756097560975609, "min_score": 0.47342995169082125, "rfi_fs__n_features_": 5.0, "nb__var_smoothing": 1.0}]}};
var opt = {};
var type = "vega-lite";
var id = "4042aef1-dde1-4304-89a0-9dd7fc1eb3ca";

var output_area = this;

require(["nbextensions/jupyter-vega/index"], function(vega) {
  var target = document.createElement("div");
  target.id = id;
  target.className = "vega-embed";

  var style = document.createElement("style");
  style.textContent = [
    ".vega-embed .error p {",
    "  color: firebrick;",
    "  font-size: 14px;",
    "}",
  ].join("\\n");

  // element is a jQuery wrapped DOM element inside the output area
  // see http://ipython.readthedocs.io/en/stable/api/generated/\
  // IPython.display.html#IPython.display.Javascript.__init__
  element[0].appendChild(target);
  element[0].appendChild(style);

  vega.render("#" + id, spec, type, opt, output_area);
}, function (err) {
  if (err.requireType !== "scripterror") {
    throw(err);
  }
});

</script>
</div>

</div>

<div class="output_area">

    <div class="prompt output_prompt">Out[44]:</div>


<div class="output_text output_subarea output_execute_result">
<pre></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 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="Decision-Trees-(DT)">Decision Trees (DT)<a class="anchor-link" href="#Decision-Trees-(DT)">&#182;</a></h3><p>A dictionary for the hyperparameters of the DT classifier is defined as below:</p>
<ul>
<li>Value range for maximum depth (max_depth): 3, 4, 5, 6, 7</li>
<li>Value for minimum sample split (min_samples_split): 2, 3, 4, 5, 6 , 7</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[49]:</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.tree</span> <span class="k">import</span> <span class="n">DecisionTreeClassifier</span>

<span class="n">pipe_DT</span> <span class="o">=</span> <span class="n">Pipeline</span><span class="p">([(</span><span class="s1">&#39;rfi_fs&#39;</span><span class="p">,</span> <span class="n">RFIFeatureSelector</span><span class="p">()),</span>
                    <span class="p">(</span><span class="s1">&#39;dt&#39;</span><span class="p">,</span> <span class="n">DecisionTreeClassifier</span><span class="p">(</span><span class="n">criterion</span><span class="o">=</span><span class="s1">&#39;gini&#39;</span><span class="p">))])</span>

<span class="n">params_pipe_DT</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;rfi_fs__n_features_&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">6</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">8</span><span class="p">,</span><span class="mi">9</span><span class="p">,</span> <span class="n">Data</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;dt__max_depth&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">,</span> <span class="mi">7</span><span class="p">],</span>
                  <span class="s1">&#39;dt__min_samples_split&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">,</span> <span class="mi">7</span><span class="p">]}</span>

<span class="n">gs_pipe_DT</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">pipe_DT</span><span class="p">,</span> 
                          <span class="n">param_grid</span><span class="o">=</span><span class="n">params_pipe_DT</span><span class="p">,</span> 
                          <span class="n">cv</span><span class="o">=</span><span class="n">cv_method</span><span class="p">,</span>
                          <span class="n">refit</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
                          <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">2</span><span class="p">,</span>
                          <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">,</span>
                          <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> 

<span class="n">gs_pipe_DT</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">D_train</span><span class="p">,</span> <span class="n">t_train</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>Fitting 15 folds for each of 240 candidates, totalling 3600 fits
</pre>
</div>
</div>

<div class="output_area">

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


<div class="output_subarea output_stream output_stderr output_text">
<pre>[Parallel(n_jobs=-2)]: Using backend LokyBackend with 3 concurrent workers.
[Parallel(n_jobs=-2)]: Done  44 tasks      | elapsed:    2.6s
[Parallel(n_jobs=-2)]: Done 194 tasks      | elapsed:   10.9s
[Parallel(n_jobs=-2)]: Done 444 tasks      | elapsed:   24.8s
[Parallel(n_jobs=-2)]: Done 794 tasks      | elapsed:   46.9s
[Parallel(n_jobs=-2)]: Done 1244 tasks      | elapsed:  1.2min
[Parallel(n_jobs=-2)]: Done 1794 tasks      | elapsed:  1.8min
[Parallel(n_jobs=-2)]: Done 2444 tasks      | elapsed:  2.4min
[Parallel(n_jobs=-2)]: Done 3194 tasks      | elapsed:  3.1min
[Parallel(n_jobs=-2)]: Done 3600 out of 3600 | elapsed:  3.4min finished
C:\Users\udesh\Software\Anaconda2\lib\site-packages\sklearn\model_selection\_search.py:841: DeprecationWarning: The default of the `iid` parameter will change from True to False in version 0.22 and will be removed in 0.24. This will change numeric results when test-set sizes are unequal.
  DeprecationWarning)
</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;[50]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">gs_pipe_DT</span><span class="o">.</span><span class="n">best_params_</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[50]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>{&#39;dt__max_depth&#39;: 5, &#39;dt__min_samples_split&#39;: 3, &#39;rfi_fs__n_features_&#39;: 6}</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;[51]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">gs_pipe_DT</span><span class="o">.</span><span class="n">best_score_</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[51]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>0.5638538635628839</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>As shown above , DT model has a mean accuracy score of 0.564. The best parameters for the DT model are  6 features with maximum depth of 5 and minimum split value of 3.</p>

</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">
<h4 id="Visualising-the-DT-model-accuracy-based-on-other-parameter-combinations">Visualising the DT model accuracy based on other parameter combinations<a class="anchor-link" href="#Visualising-the-DT-model-accuracy-based-on-other-parameter-combinations">&#182;</a></h4>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[52]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">results_DT</span> <span class="o">=</span> <span class="n">get_search_results</span><span class="p">(</span><span class="n">gs_pipe_DT</span><span class="p">)</span>

<span class="n">results_DT_6_features</span> <span class="o">=</span> <span class="n">results_DT</span><span class="p">[</span><span class="n">results_DT</span><span class="p">[</span><span class="s1">&#39;rfi_fs__n_features_&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mf">6.0</span><span class="p">]</span>

<span class="n">alt</span><span class="o">.</span><span class="n">Chart</span><span class="p">(</span><span class="n">results_DT_6_features</span><span class="p">,</span> 
          <span class="n">title</span><span class="o">=</span><span class="s1">&#39;DT Performance Comparison with 6 Features&#39;</span>
         <span class="p">)</span><span class="o">.</span><span class="n">mark_line</span><span class="p">(</span><span class="n">point</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">encode</span><span class="p">(</span>
    <span class="n">alt</span><span class="o">.</span><span class="n">X</span><span class="p">(</span><span class="s1">&#39;dt__min_samples_split&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Min Samples for Split&#39;</span><span class="p">),</span>
    <span class="n">alt</span><span class="o">.</span><span class="n">Y</span><span class="p">(</span><span class="s1">&#39;mean_score&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="n">alt</span><span class="o">.</span><span class="n">Scale</span><span class="p">(</span><span class="n">zero</span><span class="o">=</span><span class="kc">False</span><span class="p">)),</span>
    <span class="n">alt</span><span class="o">.</span><span class="n">Color</span><span class="p">(</span><span class="s1">&#39;dt__max_depth:N&#39;</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Max Depth&#39;</span><span class="p">)</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 id="77c064be-66a1-4adc-85fa-d966b620599c"></div>
<div class="output_subarea output_javascript ">
<script type="text/javascript">
var element = $('#77c064be-66a1-4adc-85fa-d966b620599c');
var spec = {"config": {"view": {"width": 400, "height": 300}, "mark": {"tooltip": null}}, "data": {"name": "data-944a134c5f49315a6f55bed444ba44ca"}, "mark": {"type": "line", "point": true}, "encoding": {"color": {"type": "nominal", "field": "dt__max_depth", "title": "Max Depth"}, "x": {"type": "quantitative", "field": "dt__min_samples_split", "title": "Min Samples for Split"}, "y": {"type": "quantitative", "field": "mean_score", "scale": {"zero": false}, "title": "accuracy"}}, "title": "DT Performance Comparison with 6 Features", "$schema": "https://vega.github.io/schema/vega-lite/v3.2.1.json", "datasets": {"data-944a134c5f49315a6f55bed444ba44ca": [{"mean_score": 0.5639181493264207, "std_score": 0.0317698700506156, "max_score": 0.6146341463414634, "min_score": 0.5072463768115942, "dt__max_depth": 5.0, "dt__min_samples_split": 3.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5635929460743881, "std_score": 0.0313713987286841, "max_score": 0.6146341463414634, "min_score": 0.5072463768115942, "dt__max_depth": 5.0, "dt__min_samples_split": 7.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5635929460743881, "std_score": 0.0313713987286841, "max_score": 0.6146341463414634, "min_score": 0.5072463768115942, "dt__max_depth": 5.0, "dt__min_samples_split": 6.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5635929460743881, "std_score": 0.0313713987286841, "max_score": 0.6146341463414634, "min_score": 0.5072463768115942, "dt__max_depth": 5.0, "dt__min_samples_split": 4.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5635929460743881, "std_score": 0.0313713987286841, "max_score": 0.6146341463414634, "min_score": 0.5072463768115942, "dt__max_depth": 5.0, "dt__min_samples_split": 5.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5622952751266641, "std_score": 0.030534090127458727, "max_score": 0.6097560975609756, "min_score": 0.5072463768115942, "dt__max_depth": 5.0, "dt__min_samples_split": 2.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5574894937355169, "std_score": 0.03560416685404393, "max_score": 0.624390243902439, "min_score": 0.48792270531400966, "dt__max_depth": 4.0, "dt__min_samples_split": 4.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5574894937355169, "std_score": 0.03560416685404393, "max_score": 0.624390243902439, "min_score": 0.48792270531400966, "dt__max_depth": 4.0, "dt__min_samples_split": 5.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5574894937355169, "std_score": 0.03560416685404393, "max_score": 0.624390243902439, "min_score": 0.48792270531400966, "dt__max_depth": 4.0, "dt__min_samples_split": 6.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5574894937355169, "std_score": 0.03560416685404393, "max_score": 0.624390243902439, "min_score": 0.48792270531400966, "dt__max_depth": 4.0, "dt__min_samples_split": 7.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5574894937355169, "std_score": 0.03560416685404393, "max_score": 0.624390243902439, "min_score": 0.48792270531400966, "dt__max_depth": 4.0, "dt__min_samples_split": 3.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5561918227877932, "std_score": 0.03495461460505111, "max_score": 0.6195121951219512, "min_score": 0.48792270531400966, "dt__max_depth": 4.0, "dt__min_samples_split": 2.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5487687050783552, "std_score": 0.03676812451312695, "max_score": 0.6146341463414634, "min_score": 0.47342995169082125, "dt__max_depth": 6.0, "dt__min_samples_split": 6.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5484466438867287, "std_score": 0.03719145427843444, "max_score": 0.6146341463414634, "min_score": 0.47342995169082125, "dt__max_depth": 6.0, "dt__min_samples_split": 7.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5471615411806291, "std_score": 0.036583380710800334, "max_score": 0.6146341463414634, "min_score": 0.47342995169082125, "dt__max_depth": 6.0, "dt__min_samples_split": 3.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5468426220494089, "std_score": 0.03779931329645522, "max_score": 0.6146341463414634, "min_score": 0.47342995169082125, "dt__max_depth": 6.0, "dt__min_samples_split": 4.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5468426220494089, "std_score": 0.03779931329645522, "max_score": 0.6146341463414634, "min_score": 0.47342995169082125, "dt__max_depth": 6.0, "dt__min_samples_split": 5.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5461827893641255, "std_score": 0.036383854212311426, "max_score": 0.6097560975609756, "min_score": 0.47342995169082125, "dt__max_depth": 6.0, "dt__min_samples_split": 2.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5416299438356701, "std_score": 0.03550937099453017, "max_score": 0.6097560975609756, "min_score": 0.46859903381642515, "dt__max_depth": 7.0, "dt__min_samples_split": 7.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5413047405836375, "std_score": 0.035576355278875885, "max_score": 0.6097560975609756, "min_score": 0.46859903381642515, "dt__max_depth": 7.0, "dt__min_samples_split": 6.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.540670044381603, "std_score": 0.036353129023186444, "max_score": 0.6048780487804878, "min_score": 0.463768115942029, "dt__max_depth": 7.0, "dt__min_samples_split": 4.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5406637602607909, "std_score": 0.035587603817128444, "max_score": 0.6097560975609756, "min_score": 0.47342995169082125, "dt__max_depth": 7.0, "dt__min_samples_split": 5.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.539366089313067, "std_score": 0.036129632645829184, "max_score": 0.6097560975609756, "min_score": 0.463768115942029, "dt__max_depth": 7.0, "dt__min_samples_split": 2.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5393660893130668, "std_score": 0.03595951310491578, "max_score": 0.6048780487804878, "min_score": 0.463768115942029, "dt__max_depth": 7.0, "dt__min_samples_split": 3.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5209520443030516, "std_score": 0.0374889250779176, "max_score": 0.5756097560975609, "min_score": 0.43478260869565216, "dt__max_depth": 3.0, "dt__min_samples_split": 5.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5209520443030516, "std_score": 0.0374889250779176, "max_score": 0.5756097560975609, "min_score": 0.43478260869565216, "dt__max_depth": 3.0, "dt__min_samples_split": 4.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5209520443030516, "std_score": 0.0374889250779176, "max_score": 0.5756097560975609, "min_score": 0.43478260869565216, "dt__max_depth": 3.0, "dt__min_samples_split": 3.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5209520443030516, "std_score": 0.0374889250779176, "max_score": 0.5756097560975609, "min_score": 0.43478260869565216, "dt__max_depth": 3.0, "dt__min_samples_split": 6.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5209520443030516, "std_score": 0.0374889250779176, "max_score": 0.5756097560975609, "min_score": 0.43478260869565216, "dt__max_depth": 3.0, "dt__min_samples_split": 7.0, "rfi_fs__n_features_": 6.0}, {"mean_score": 0.5196543733553277, "std_score": 0.03713295595497576, "max_score": 0.5707317073170731, "min_score": 0.43478260869565216, "dt__max_depth": 3.0, "dt__min_samples_split": 2.0, "rfi_fs__n_features_": 6.0}]}};
var opt = {};
var type = "vega-lite";
var id = "c52f7b3b-770d-462a-aa74-08f50ef670bc";

var output_area = this;

require(["nbextensions/jupyter-vega/index"], function(vega) {
  var target = document.createElement("div");
  target.id = id;
  target.className = "vega-embed";

  var style = document.createElement("style");
  style.textContent = [
    ".vega-embed .error p {",
    "  color: firebrick;",
    "  font-size: 14px;",
    "}",
  ].join("\\n");

  // element is a jQuery wrapped DOM element inside the output area
  // see http://ipython.readthedocs.io/en/stable/api/generated/\
  // IPython.display.html#IPython.display.Javascript.__init__
  element[0].appendChild(target);
  element[0].appendChild(style);

  vega.render("#" + id, spec, type, opt, output_area);
}, function (err) {
  if (err.requireType !== "scripterror") {
    throw(err);
  }
});

</script>
</div>

</div>

<div class="output_area">

    <div class="prompt output_prompt">Out[52]:</div>


<div class="output_text output_subarea output_execute_result">
<pre></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 text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h4 id="Mean-accuracy-scores-for-each-classifiers">Mean accuracy scores for each classifiers<a class="anchor-link" href="#Mean-accuracy-scores-for-each-classifiers">&#182;</a></h4>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[53]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Mean accuracy score for KNN model: &quot;</span> <span class="p">,</span><span class="n">gs_pipe_KNN</span><span class="o">.</span><span class="n">best_score_</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Mean accuracy score for NB model: &quot;</span> <span class="p">,</span><span class="n">gs_pipe_NB</span><span class="o">.</span><span class="n">best_score_</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Mean accuracy score for DT model: &quot;</span> <span class="p">,</span><span class="n">gs_pipe_DT</span><span class="o">.</span><span class="n">best_score_</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>Mean accuracy score for KNN model:  0.5354025218234724
Mean accuracy score for NB model:  0.5337859683155513
Mean accuracy score for DT model:  0.5638538635628839
</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>Based on above accuracy scores, it can be stated that the best model out of the three explored is DT model.</p>

</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">
<h1 id="5.-Performance-Comparison-">5. Performance Comparison <a class="anchor" id="5" /><a class="anchor-link" href="#5.-Performance-Comparison-">&#182;</a></h1><p>After optimizing each of three classifiers using the training data, test data has been fitted in cross-validation manner in order to compare the performance of each model. Pairwise t-test has been conducted to determine whether the performance difference of each pair of models is statistically significant. This is done because cross-validation is a random process.</p>
<p>Paired t-test has been performed for the below model pairs with accuracy score.</p>
<ul>
<li>DT vs. KNN</li>
<li>DT vs. NB</li>
<li>KNN vs. NB</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[54]:</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.model_selection</span> <span class="k">import</span> <span class="n">cross_val_score</span>

<span class="c1">#Stratified 5-fold cross-validation with 3 repetitions </span>
<span class="n">cv_results_KNN</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">gs_pipe_KNN</span><span class="o">.</span><span class="n">best_estimator_</span><span class="p">,</span>
                                 <span class="n">X</span><span class="o">=</span><span class="n">D_test</span><span class="p">,</span>
                                 <span class="n">y</span><span class="o">=</span><span class="n">t_test</span><span class="p">,</span> 
                                 <span class="n">cv</span><span class="o">=</span><span class="n">cv_method</span><span class="p">,</span> 
                                 <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">2</span><span class="p">,</span>
                                 <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
<span class="n">cv_results_KNN</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[54]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>0.46319344158360043</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;[55]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">D_test_transformed</span> <span class="o">=</span> <span class="n">PowerTransformer</span><span class="p">()</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">D_test</span><span class="p">)</span>

<span class="n">cv_results_NB</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">gs_pipe_NB</span><span class="o">.</span><span class="n">best_estimator_</span><span class="p">,</span>
                                <span class="n">X</span><span class="o">=</span><span class="n">D_test_transformed</span><span class="p">,</span>
                                <span class="n">y</span><span class="o">=</span><span class="n">t_test</span><span class="p">,</span> 
                                <span class="n">cv</span><span class="o">=</span><span class="n">cv_method</span><span class="p">,</span> 
                                <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">2</span><span class="p">,</span>
                                <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
<span class="n">cv_results_NB</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[55]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>0.47942325228260907</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;[56]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">cv_results_DT</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">estimator</span><span class="o">=</span><span class="n">gs_pipe_DT</span><span class="o">.</span><span class="n">best_estimator_</span><span class="p">,</span>
                                <span class="n">X</span><span class="o">=</span><span class="n">D_test</span><span class="p">,</span>
                                <span class="n">y</span><span class="o">=</span><span class="n">t_test</span><span class="p">,</span> 
                                <span class="n">cv</span><span class="o">=</span><span class="n">cv_method</span><span class="p">,</span> 
                                <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">2</span><span class="p">,</span>
                                <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
<span class="n">cv_results_DT</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
</pre></div>

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

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


<div class="output_area">

    <div class="prompt output_prompt">Out[56]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>0.526338060966112</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 <code>stats.ttest_rel</code> function from the <code>SciPy</code> module has been used to run the t-tests on <strong>test data</strong>.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[57]:</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">scipy</span> <span class="k">import</span> <span class="n">stats</span>

<span class="nb">print</span><span class="p">(</span><span class="n">stats</span><span class="o">.</span><span class="n">ttest_rel</span><span class="p">(</span><span class="n">cv_results_DT</span><span class="p">,</span> <span class="n">cv_results_KNN</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="n">stats</span><span class="o">.</span><span class="n">ttest_rel</span><span class="p">(</span><span class="n">cv_results_DT</span><span class="p">,</span> <span class="n">cv_results_NB</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="n">stats</span><span class="o">.</span><span class="n">ttest_rel</span><span class="p">(</span><span class="n">cv_results_KNN</span><span class="p">,</span> <span class="n">cv_results_NB</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>Ttest_relResult(statistic=3.5398348605584475, pvalue=0.0032662059175455754)
Ttest_relResult(statistic=2.878710634761897, pvalue=0.012142085409240956)
Ttest_relResult(statistic=-0.9833375363617465, pvalue=0.3421309032814237)
</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>As per the results above, DT is statistically the best classifier model at 95% significance level. This conclusion has been taken due the fact that $p$-value is smaller than 0.05, which in other words says there is a statistically significant difference between model pairs.</p>

</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">
<h4 id="Model-evaluation-using-other-methods">Model evaluation using other methods<a class="anchor-link" href="#Model-evaluation-using-other-methods">&#182;</a></h4>
</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>Precision, Recall, F1 Score &amp; Confusion Matrix can also used to evaluate the model as below:</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[58]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pred_KNN</span> <span class="o">=</span> <span class="n">gs_pipe_KNN</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">D_test</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;[59]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pred_NB</span> <span class="o">=</span> <span class="n">gs_pipe_NB</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">D_test_transformed</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;[60]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pred_DT</span> <span class="o">=</span> <span class="n">gs_pipe_DT</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">D_test</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;[61]:</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</span> <span class="k">import</span> <span class="n">metrics</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Classification report for K-Nearest Neighbor&quot;</span><span class="p">)</span> 
<span class="nb">print</span><span class="p">(</span><span class="n">metrics</span><span class="o">.</span><span class="n">classification_report</span><span class="p">(</span><span class="n">t_test</span><span class="p">,</span> <span class="n">pred_KNN</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Classification report for Naive Bayes&quot;</span><span class="p">)</span> 
<span class="nb">print</span><span class="p">(</span><span class="n">metrics</span><span class="o">.</span><span class="n">classification_report</span><span class="p">(</span><span class="n">t_test</span><span class="p">,</span> <span class="n">pred_NB</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Classification report for Decision Tree&quot;</span><span class="p">)</span> 
<span class="nb">print</span><span class="p">(</span><span class="n">metrics</span><span class="o">.</span><span class="n">classification_report</span><span class="p">(</span><span class="n">t_test</span><span class="p">,</span> <span class="n">pred_DT</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>
Classification report for K-Nearest Neighbor
              precision    recall  f1-score   support

           0       0.35      0.36      0.36       100
           1       0.56      0.50      0.53       189
           2       0.40      0.45      0.42       153

   micro avg       0.45      0.45      0.45       442
   macro avg       0.44      0.44      0.44       442
weighted avg       0.46      0.45      0.45       442


Classification report for Naive Bayes
              precision    recall  f1-score   support

           0       0.39      0.50      0.44       100
           1       0.60      0.59      0.59       189
           2       0.46      0.37      0.41       153

   micro avg       0.50      0.50      0.50       442
   macro avg       0.48      0.49      0.48       442
weighted avg       0.50      0.50      0.49       442


Classification report for Decision Tree
              precision    recall  f1-score   support

           0       0.42      0.47      0.44       100
           1       0.71      0.58      0.64       189
           2       0.45      0.51      0.48       153

   micro avg       0.53      0.53      0.53       442
   macro avg       0.52      0.52      0.52       442
weighted avg       0.55      0.53      0.54       442

</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;[62]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Confusion matrix for K-Nearest Neighbor&quot;</span><span class="p">)</span> 
<span class="nb">print</span><span class="p">(</span><span class="n">metrics</span><span class="o">.</span><span class="n">confusion_matrix</span><span class="p">(</span><span class="n">t_test</span><span class="p">,</span> <span class="n">pred_KNN</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Confusion matrix for Naive Bayes&quot;</span><span class="p">)</span> 
<span class="nb">print</span><span class="p">(</span><span class="n">metrics</span><span class="o">.</span><span class="n">confusion_matrix</span><span class="p">(</span><span class="n">t_test</span><span class="p">,</span> <span class="n">pred_NB</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Confusion matrix for Decision Tree&quot;</span><span class="p">)</span> 
<span class="nb">print</span><span class="p">(</span><span class="n">metrics</span><span class="o">.</span><span class="n">confusion_matrix</span><span class="p">(</span><span class="n">t_test</span><span class="p">,</span> <span class="n">pred_DT</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>
Confusion matrix for K-Nearest Neighbor
[[36 25 39]
 [31 94 64]
 [35 49 69]]

Confusion matrix for Naive Bayes
[[ 50  20  30]
 [ 39 112  38]
 [ 40  56  57]]

Confusion matrix for Decision Tree
[[ 47  14  39]
 [ 22 110  57]
 [ 43  32  78]]
</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>Depending on which organization uses the model, the "precision" or the "recall" may become key performance indicator. For an example, if government organization that runs a program to find number of womens who do not use any contraceptive method, "recall" would be the best performance indicator. According to above classification report, its is evident that DT is the best method with higher recall value.</p>

</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">
<h1 id="6.-Limitations-">6. Limitations <a class="anchor" id="6" /><a class="anchor-link" href="#6.-Limitations-">&#182;</a></h1><p>Since the size of the data set is significantly small (only 1473), the accuracy rate of the models developed could be considerably low to represent entire county (Indonesia). Also, this data-set could be a biased one, considering the small size of it. As a well know limitation of the supervised machine learning is that it requires large number of data to achieve a reasonably accurate model. Therefore, if a larger data set is available for this exercise, then more accurate model could have been developed. In oppose to the supervised machine learning, deep learning would have been a better approach for this kind of problems with limited data-sets.</p>
<p>There is a room to improve the model in future by considering more parameters and more ensemble methods during the hyperparameter tuning process.</p>
<p>There are few assumptions for the paired sample t-test and it can impact to the evaluation. Main assumptions in paired sample t-test are;</p>
<ul>
<li>The data-set is normally distributed and has no outliers</li>
<li>Variable in the data-set is independent and continuous</li>
</ul>

</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">
<h1 id="7.-Summary--">7. Summary  <a class="anchor" id="7" /><a class="anchor-link" href="#7.-Summary--">&#182;</a></h1><p>Contraceptive method data-set is a multi-class classification problem and K-Nearest Neighbors (KNN), Naive Bayes (NB) &amp; Decision trees (DT) classifiers have been examined for this classification problem.</p>
<p>When evaluating the training set, the DT model with 6 of the best features selected by Random Forest Importance (RFI) produces the highest cross-validated accuracy score. Similarly, when evaluating the test set, the DT model performed the best on accuracy score of approximately 55%. Therefore, it can be concluded that the DT method is the most suitable model for this classification problem based on the given data-set.</p>

</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">
<h1 id="References">References<a class="anchor-link" href="#References">&#182;</a></h1><ul>
<li>Dua, D. and Graff, C (2019). UCI Machine Learning Repository: Contraceptive Method Choice Data Set [online]. Available at
<a href="https://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice">https://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice</a> [Accessed 2019-06-02]</li>
<li>Aksakalli V, Yenice Z (2019). Feature Ranking [online].  Available at <a href="https://www.featureranking.com/">https://www.featureranking.com/</a></li>
<li>Aksakalli V (2019). Machine Learning (1910) Lecture Notes, RMIT University, Melbourne, delivered Semester-1 2019.</li>
<li>Jones E, Oliphant E, Peterson P, et al. SciPy: Open Source Scientific Tools for Python, 2001-, <a href="http://www.scipy.org/">http://www.scipy.org/</a> [Accessed 2019-05-26].</li>
<li>Pedregosa et al. (2011). Scikit-learn: Machine Learning in Python, Pedregosa et al., JMLR 12, pp. 2825-
2830.</li>
<li>Travis E, Oliphant (2006). A guide to NumPy, USA: Trelgol Publishing.</li>
</ul>

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

 
</html>