bin/src/01_Training_Models.html

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<title>01_Training_Models</title>

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}
.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;
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fieldset[disabled] .notification_widget.info:focus,
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span.save_widget span.filename:hover {
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[dir="rtl"] span.save_widget.pull-left {
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[dir="rtl"] span.save_widget span.filename {
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span.checkpoint_status,
span.autosave_status {
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@media (max-width: 767px) {
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@media (min-width: 768px) and (max-width: 991px) {
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}
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#maintoolbar .navbar-text {
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[dir="rtl"] .btn-group > .btn,
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.pulse,
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li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
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/**
 * 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
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@-webkit-keyframes fadeIn {
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}
.tooltiptext {
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}
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  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
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  font-family: monospace;
  min-height: 50px;
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  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
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  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
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.pretooltiparrow:before {
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  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
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  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
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ul.typeahead-list i {
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[dir="rtl"] ul.typeahead-list i {
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ul.typeahead-list {
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.cmd-palette .modal-body {
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}
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}
.cmd-palette input {
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.no-shortcut {
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  color: transparent;
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  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
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  float: left;
}
.command-shortcut:before {
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  padding-right: 3px;
  color: #777777;
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.edit-shortcut:before {
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[dir="rtl"] .edit-shortcut.pull-right {
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#find-and-replace #replace-preview .insert {
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[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
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#find-and-replace #replace-preview pre {
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.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);
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  color: white;
  background: black;
  padding: 0.4em;
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  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
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}
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</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="Training-Models-1">Training Models 1<a class="anchor-link" href="#Training-Models-1">&#182;</a></h1><h2 id="Contents">Contents<a class="anchor-link" href="#Contents">&#182;</a></h2><ul>
<li><a href="#linreg">Linear Regression</a></li>
<li><a href="#reglinreg">Regularised Linear Regression</a></li>
<li><a href="#logreg">Logistic Regression</a></li>
<li><a href="#dectree">Decision Trees</a></li>
</ul>

</div>
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<p><a name="linreg"></a></p>
<h2 id="Linear-Regression">Linear Regression<a class="anchor-link" href="#Linear-Regression">&#182;</a></h2>
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<p>Equation 4-1. Linear Regression model prediction</p>
<p>$y = θ_{0} + θ_{1}x_{1} + θ_{2}x_{2} + ⋯ + θ_{n}x_{n}$</p>

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<ul>
<li>ŷ is the predicted value.</li>
<li>n is the number of features.</li>
<li>$x_{i}$ is the ith feature value.</li>
<li>$θ_{j}$ is the jth model parameter (including the bias term $θ_{0}$ and the feature weights $θ_{1} , θ_{2} , ⋯, θ_{n})$.</li>
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<p>Equation 4-2. Linear Regression model prediction (vectorized form)</p>
<p>$y = hθ(x) = θ^{T}.x$</p>

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<p>we use MSE cost Function and then minimise it.</p>
<p>$MSE (x , hθ) = \frac{∑(θ^{T}·x(i)− y(i))^2}{m}$</p>
<p>One way to do this is to use Normal Equation which directly gives us values of theta</p>
<p>$θ = ((X^{T}·X)^{-1}).X^{T}.y$</p>

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<div class=" highlight hl-ipython3"><pre><span></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">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="n">X</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">100</span><span class="p">)</span>
<span class="n">delta</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">36</span><span class="p">,</span><span class="mi">36</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="mi">100</span><span class="p">,))</span>
<span class="n">y</span><span class="o">=</span><span class="mi">4</span><span class="o">+</span><span class="mi">3</span><span class="o">*</span><span class="n">X</span><span class="o">+</span><span class="n">delta</span>
<span class="n">sns</span><span class="o">.</span><span class="n">scatterplot</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">y</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x23b442a41d0&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_b</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">c_</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span><span class="mi">1</span><span class="p">)),</span><span class="n">X</span><span class="p">]</span>
<span class="n">theta_best</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">linalg</span><span class="o">.</span><span class="n">inv</span><span class="p">(</span><span class="n">X_b</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">X_b</span><span class="p">))</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">X_b</span><span class="o">.</span><span class="n">T</span><span class="p">)</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">theta_best</span>
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<pre>array([4.51347616, 2.99506489])</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_new</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">100</span><span class="p">)</span>
<span class="n">X_new_b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">c_</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">1</span><span class="p">)),</span> <span class="n">X_new</span><span class="p">]</span> <span class="c1"># add x0 = 1 to each instance</span>
<span class="n">y_predict</span> <span class="o">=</span> <span class="n">X_new_b</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">theta_best</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span> <span class="n">y_predict</span><span class="p">,</span> <span class="s2">&quot;r-&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span> <span class="n">y</span><span class="p">,</span> <span class="s2">&quot;c.&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<li><p>The Normal Equation gets very slow when the number of features grows large (e.g., 100,000).</p>
</li>
<li><p>The Normal Equation computes the inverse of $X^{T} · X$, which is an n × n matrix (where n is the number of features). The computational complexity of inverting such a matrix is typically about O(n 2.4) to O(n 3 ) (depending on the implementation). In other words, if you double the number of features, you multiply the computation time by roughly 22.4 = 5.3 to 23  = 8.</p>
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<li><p>On the positive side, this equation is linear with regards to the number of instances in the training set (it is O(m)), so it handles large training sets efficiently, provided they can fit in memory.</p>
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<h3 id="Gradient-Descent">Gradient Descent<a class="anchor-link" href="#Gradient-Descent">&#182;</a></h3><p>Gradient Descent is a very generic optimization algorithm capable of finding optimal
solutions to a wide range of problems.</p>
<p>The general idea of Gradient Descent is to tweak parameters iteratively in order to minimize a cost function.you start by filling θ with random values (this is called random initializa‐
tion), and then you improve it gradually, taking one baby step at a time, each step
attempting to decrease the cost function (e.g., the MSE), until the algorithm converges
to a minimum.</p>
<p>An important parameter in Gradient Descent is the size of the steps, determined by
the learning rate hyperparameter. If the learning rate is too small, then the algorithm
will have to go through many iterations to converge, which will take a long time.
On the other hand, if the learning rate is too high, you might jump across the valley
and end up on the other side, possibly even higher up than you were before. This
might make the algorithm diverge, with larger and larger values, failing to find a good
solution</p>

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<h3 id="When-using-Gradient-Descent,-you-should-ensure-that-all-features-have-a-similar-scale-(e.g.,-using-Scikit-Learn&#8217;s-StandardScaler-class),-or-else-it-will-take-much-longer-to-converge.">When using Gradient Descent, you should ensure that all features have a similar scale (e.g., using Scikit-Learn&#8217;s StandardScaler class), or else it will take much longer to converge.<a class="anchor-link" href="#When-using-Gradient-Descent,-you-should-ensure-that-all-features-have-a-similar-scale-(e.g.,-using-Scikit-Learn&#8217;s-StandardScaler-class),-or-else-it-will-take-much-longer-to-converge.">&#182;</a></h3>
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<h1 id="Batch-Gradient-Descent">Batch Gradient Descent<a class="anchor-link" href="#Batch-Gradient-Descent">&#182;</a></h1>
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<p><strong><em>Code not Working</em></strong></p>
<p>probably not working because gradient descent requires scaled data and this is not scaled?</p>

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<div class="prompt input_prompt">In&nbsp;[6]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">100</span><span class="p">)</span>
<span class="n">delta</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">36</span><span class="p">,</span><span class="mi">36</span><span class="p">,</span><span class="mi">100</span><span class="p">)</span>
<span class="n">y</span><span class="o">=</span><span class="mi">4</span><span class="o">+</span><span class="mi">3</span><span class="o">*</span><span class="n">X</span><span class="o">+</span><span class="n">delta</span>
<span class="n">y</span><span class="o">=</span><span class="n">y</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span><span class="mi">1</span><span class="p">))</span>
<span class="n">sns</span><span class="o">.</span><span class="n">scatterplot</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">y</span><span class="p">)</span>
<span class="n">X_b</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">c_</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span><span class="mi">1</span><span class="p">)),</span><span class="n">X</span><span class="p">]</span>
<span class="n">eta</span> <span class="o">=</span> <span class="mf">0.1</span> <span class="c1"># learning rate</span>
<span class="n">n_iterations</span> <span class="o">=</span> <span class="mi">100</span>
<span class="n">m</span> <span class="o">=</span> <span class="mi">100</span>
<span class="n">theta</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span><span class="o">+</span><span class="mi">16</span>
<span class="nb">print</span><span class="p">(</span><span class="n">theta</span><span class="p">)</span><span class="c1"># random initialization</span>
<span class="c1"># print(X_b.shape)</span>
<span class="c1"># print(X_b.T.shape)</span>
<span class="c1"># print(theta.shape)</span>
<span class="c1"># print(y.shape)</span>
<span class="c1"># print((np.subtract(np.dot(X_b,theta),y)).shape)</span>
<span class="k">for</span> <span class="n">iteration</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_iterations</span><span class="p">):</span>
    <span class="n">gradients</span> <span class="o">=</span> <span class="mi">2</span><span class="o">/</span><span class="n">m</span><span class="o">*</span><span class="n">X_b</span><span class="o">.</span><span class="n">T</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">X_b</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">theta</span><span class="p">)</span><span class="o">-</span><span class="n">y</span><span class="p">)</span>
    <span class="c1">#print(gradients.shape)</span>
    <span class="n">theta</span> <span class="o">=</span> <span class="n">theta</span> <span class="o">+</span> <span class="n">eta</span><span class="o">*</span><span class="n">gradients</span>
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<pre>[[15.24191068]
 [15.20969908]]
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<pre>array([[1.21084488e+281],
       [8.03131707e+282]])</pre>
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<h1 id="Stochastic-Gradient-Descent">Stochastic Gradient Descent<a class="anchor-link" href="#Stochastic-Gradient-Descent">&#182;</a></h1><ul>
<li>The main problem with Batch Gradient Descent is the fact that it uses the whole training set to compute the gradients at every step, which makes it very slow when the training set is large. At the opposite extreme, Stochastic Gradient Descent just picks a random instance in the training set at every step and computes the gradients based only on that single instance. Obviously this makes the algorithm much faster since it has very little data to manipulate at every iteration. It also makes it possible to train on huge training sets, since only one instance needs to be in memory at each iteration (SGD can be implemented as an out-of-core algorithm.)</li>
<li>On the other hand, due to its stochastic (i.e., random) nature, this algorithm is much less regular than Batch Gradient Descent: instead of gently decreasing until it reaches the minimum, the cost function will bounce up and down, decreasing only on average. Over time it will end up very close to the minimum, but once it gets there it will continue to bounce around, never settling down </li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_b</span><span class="o">=</span><span class="n">X_b</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">100</span><span class="p">,</span><span class="mi">2</span><span class="p">)</span>
<span class="n">y</span><span class="o">=</span><span class="n">y</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">100</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
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<div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <span class="n">SGDRegressor</span>
<span class="n">sgd_reg</span> <span class="o">=</span> <span class="n">SGDRegressor</span><span class="p">(</span><span class="n">penalty</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">eta0</span><span class="o">=</span><span class="mf">0.1</span><span class="p">)</span>
<span class="n">sgd_reg</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="o">.</span><span class="n">ravel</span><span class="p">())</span>
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<h3 id="Mini-batch-Gradient-Descent">Mini-batch Gradient Descent<a class="anchor-link" href="#Mini-batch-Gradient-Descent">&#182;</a></h3>
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<li>Mini-batch GD computes the gradients on small random sets of instances called minibatches</li>
<li>The main advantage of Mini-batch GD over Stochastic GD is that you can get a performance boost from hardware optimization of matrix operations, especially when using GPUs.</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;&quot;&quot;</span>
<span class="s2">Algorithm           Large m     Out-of-core support      Large n     Hyperparams     Scaling required      Scikit-Learn</span>
<span class="s2">Normal Equation     Fast        No                       Slow        0               No                    n/a</span>
<span class="s2">Batch GD            Slow        No                       Fast        2               Yes                   SGDRegressor</span>
<span class="s2">Stochastic GD       Fast        Yes                      Fast        ≥2              Yes                   SGDRegressor</span>
<span class="s2">Mini-batch GD       Fast        Yes                      Fast        ≥2              Yes                   SGDRegressor</span>
<span class="s2">SVD                 Fast        No                       Slow        0               No                    LinearRegression</span>
<span class="s2">&quot;&quot;&quot;</span><span class="p">)</span>
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Algorithm           Large m     Out-of-core support      Large n     Hyperparams     Scaling required      Scikit-Learn
Normal Equation     Fast        No                       Slow        0               No                    n/a
Batch GD            Slow        No                       Fast        2               Yes                   SGDRegressor
Stochastic GD       Fast        Yes                      Fast        ≥2              Yes                   SGDRegressor
Mini-batch GD       Fast        Yes                      Fast        ≥2              Yes                   SGDRegressor
SVD                 Fast        No                       Slow        0               No                    LinearRegression

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<h2 id="Polynomial-Regression">Polynomial Regression<a class="anchor-link" href="#Polynomial-Regression">&#182;</a></h2><p>What if your data is actually more complex than a simple straight line? Surprisingly,
you can actually use a linear model to fit nonlinear data. A simple way to do this is to
add powers of each feature as new features, then train a linear model on this extended
set of features. This technique is called Polynomial Regression.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">m</span> <span class="o">=</span> <span class="mi">100</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="o">-</span><span class="mi">100</span><span class="p">,</span><span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">200</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="mf">0.5</span> <span class="o">*</span> <span class="n">X</span><span class="o">**</span><span class="mi">2</span> <span class="o">+</span> <span class="n">X</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">+</span> <span class="mi">700</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">200</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">scatterplot</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">y</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x23b475d1550&gt;</pre>
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<div class="prompt input_prompt">In&nbsp;[12]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="kn">import</span> <span class="n">PolynomialFeatures</span>
<span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <span class="n">LinearRegression</span>
<span class="n">poly_features</span> <span class="o">=</span> <span class="n">PolynomialFeatures</span><span class="p">(</span><span class="n">degree</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">include_bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">X_poly</span> <span class="o">=</span> <span class="n">poly_features</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
<span class="n">lin_reg</span> <span class="o">=</span> <span class="n">LinearRegression</span><span class="p">()</span>
<span class="n">lin_reg</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_poly</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
<span class="n">lin_reg</span><span class="o">.</span><span class="n">intercept_</span><span class="p">,</span> <span class="n">lin_reg</span><span class="o">.</span><span class="n">coef_</span>
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<pre>(array([-42.25567918]), array([[1.58865487, 0.51576824]]))</pre>
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<div class=" highlight hl-ipython3"><pre><span></span> <span class="c1"># add x0 = 1 to each instance</span>
<span class="n">y_predict</span> <span class="o">=</span> <span class="n">lin_reg</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_poly</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span> <span class="n">y_predict</span><span class="p">,</span> <span class="s2">&quot;r-&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">y</span><span class="p">,</span><span class="s2">&quot;c.&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<h2 id="Examples-of-Overfitting">Examples of Overfitting<a class="anchor-link" href="#Examples-of-Overfitting">&#182;</a></h2>
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<div class="prompt input_prompt">In&nbsp;[14]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">poly_features</span> <span class="o">=</span> <span class="n">PolynomialFeatures</span><span class="p">(</span><span class="n">degree</span><span class="o">=</span><span class="mi">20</span><span class="p">,</span> <span class="n">include_bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">X_poly</span> <span class="o">=</span> <span class="n">poly_features</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
<span class="n">lin_reg</span> <span class="o">=</span> <span class="n">LinearRegression</span><span class="p">()</span>
<span class="n">lin_reg</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_poly</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
<span class="n">lin_reg</span><span class="o">.</span><span class="n">intercept_</span><span class="p">,</span> <span class="n">lin_reg</span><span class="o">.</span><span class="n">coef_</span>
<span class="n">y_predict</span> <span class="o">=</span> <span class="n">lin_reg</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_poly</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span> <span class="n">y_predict</span><span class="p">,</span> <span class="s2">&quot;r-&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">y</span><span class="p">,</span><span class="s2">&quot;c.&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<h3 id="using-pipelining-for-polynomial-regression">using pipelining for polynomial regression<a class="anchor-link" href="#using-pipelining-for-polynomial-regression">&#182;</a></h3><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.pipeline</span> <span class="kn">import</span> <span class="n">Pipeline</span>
<span class="n">polynomial_regression</span> <span class="o">=</span> <span class="n">Pipeline</span><span class="p">((</span>
 <span class="p">(</span><span class="s2">&quot;poly_features&quot;</span><span class="p">,</span> <span class="n">PolynomialFeatures</span><span class="p">(</span><span class="n">degree</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">include_bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)),</span>
 <span class="p">(</span><span class="s2">&quot;sgd_reg&quot;</span><span class="p">,</span> <span class="n">LinearRegression</span><span class="p">()),</span>
 <span class="p">))</span>
<span class="n">plot_learning_curves</span><span class="p">(</span><span class="n">polynomial_regression</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
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<h1 id="About-Learning-Curves">About Learning Curves<a class="anchor-link" href="#About-Learning-Curves">&#182;</a></h1><h3 id="Learning-curves-code-from-Hands-On-Ml">Learning curves code from Hands-On Ml<a class="anchor-link" href="#Learning-curves-code-from-Hands-On-Ml">&#182;</a></h3>
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<div class="prompt input_prompt">In&nbsp;[16]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="kn">import</span> <span class="n">mean_squared_error</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="kn">import</span> <span class="n">train_test_split</span>
<span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="kn">import</span> <span class="n">PolynomialFeatures</span>
<span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <span class="n">LinearRegression</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>

<span class="k">def</span> <span class="nf">plot_learning_curves</span><span class="p">(</span><span class="n">model</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="n">X_train</span><span class="p">,</span> <span class="n">X_val</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_val</span> <span class="o">=</span> <span class="n">train_test_split</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="n">test_size</span><span class="o">=</span><span class="mf">0.2</span><span class="p">)</span>
    <span class="n">train_errors</span><span class="p">,</span> <span class="n">val_errors</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
    <span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">X_train</span><span class="p">)):</span>
        <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">[:</span><span class="n">m</span><span class="p">],</span> <span class="n">y_train</span><span class="p">[:</span><span class="n">m</span><span class="p">])</span>
        <span class="n">y_train_predict</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_train</span><span class="p">[:</span><span class="n">m</span><span class="p">])</span>
        <span class="n">y_val_predict</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_val</span><span class="p">)</span>
        <span class="n">train_errors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mean_squared_error</span><span class="p">(</span><span class="n">y_train_predict</span><span class="p">,</span> <span class="n">y_train</span><span class="p">[:</span><span class="n">m</span><span class="p">]))</span>
        <span class="n">val_errors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mean_squared_error</span><span class="p">(</span><span class="n">y_val_predict</span><span class="p">,</span> <span class="n">y_val</span><span class="p">))</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">train_errors</span><span class="p">),</span> <span class="s2">&quot;r-+&quot;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;train&quot;</span><span class="p">)</span> 
    <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">val_errors</span><span class="p">),</span> <span class="s2">&quot;b-&quot;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;val&quot;</span><span class="p">)</span>

<span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="o">-</span><span class="mi">100</span><span class="p">,</span><span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">200</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="mf">0.5</span> <span class="o">*</span> <span class="n">X</span><span class="o">**</span><span class="mi">2</span> <span class="o">+</span> <span class="n">X</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">+</span> <span class="mi">700</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">200</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>

<span class="n">poly_features</span> <span class="o">=</span> <span class="n">PolynomialFeatures</span><span class="p">(</span><span class="n">degree</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">include_bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">X_poly</span> <span class="o">=</span> <span class="n">poly_features</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
<span class="n">lin_reg</span> <span class="o">=</span> <span class="n">LinearRegression</span><span class="p">()</span>
<span class="n">plot_learning_curves</span><span class="p">(</span><span class="n">lin_reg</span><span class="p">,</span> <span class="n">X_poly</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
</pre></div>

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<pre>&lt;matplotlib.legend.Legend at 0x23b47bbe278&gt;</pre>
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<li>One way to improve an overfitting model is to feed it more training data until the validation error reaches the training error</li>
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<p><strong>The Bias/Variance Tradeoff</strong></p>
<ul>
<li>a model’s generalization error can be expressed as the sum of three very different errors:</li>
</ul>
<p><strong>Bais</strong></p>
<ul>
<li>This part of the generalization error is due to wrong assumptions, such as assum‐ ing that the data is linear when it is actually quadratic. A high-bias model is most likely to underfit the training data.</li>
</ul>
<p><strong>Variance</strong></p>
<ul>
<li>This part is due to the model’s excessive sensitivity to small variations in the training data. A model with many degrees of freedom (such as a high-degree polynomial model) is likely to have high variance, and thus to overfit the training data</li>
</ul>
<p><strong>Irreducible error</strong></p>
<ul>
<li>This part is due to the noisiness of the data itself. The only way to reduce this part of the error is to clean up the data (e.g., fix the data sources, such as broken sensors, or detect and remove outliers)</li>
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<p><a name="reglinreg"></a></p>
<h1 id="Regularuized-Linear-Models">Regularuized Linear Models<a class="anchor-link" href="#Regularuized-Linear-Models">&#182;</a></h1>
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<h2 id="Ridge-Regression">Ridge Regression<a class="anchor-link" href="#Ridge-Regression">&#182;</a></h2><p><em><em>Ridge Regression</em></em> (also called Tikhonov regularization) is a regularized version of Linear Regression: a regularization term equal to $α∑θ(i)^{2}$
 is added to the cost function.
This forces the learning algorithm to not only fit the data but also keep the model
weights as small as possible. Note that the regularization term should only be added
to the cost function during training. Once the model is trained, you want to evaluate
the model’s performance using the unregularized performance measure.</p>

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<p><strong><em>It is important to scale the data (e.g., using a StandardScaler) before performing Ridge Regression, as it is sensitive to the scale of the input features. This is true of most regularized models</em></strong></p>

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<p>$J(θ)=MSE(θ)+α*0.5*∑θ(i)^{2}$</p>

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<h3 id="Ridge-Regression-Closed-Form">Ridge Regression Closed Form<a class="anchor-link" href="#Ridge-Regression-Closed-Form">&#182;</a></h3><p><strong><em>$θ = ((X^{T}·X + αA)^{-1})·X^{T}·Y$</em></strong></p>
<p>A is the n × n identity matrix except with a 0 in the top-left cell, corresponding to the bias term</p>
<p>code example</p>
<div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <span class="n">Ridge</span>
<span class="n">ridge_reg</span> <span class="o">=</span> <span class="n">Ridge</span><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">solver</span><span class="o">=</span><span class="s2">&quot;cholesky&quot;</span><span class="p">)</span>
<span class="n">ridge_reg</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="n">ridge_reg</span><span class="o">.</span><span class="n">predict</span><span class="p">([[</span><span class="mf">1.5</span><span class="p">]])</span>
<span class="n">sgd_reg</span> <span class="o">=</span> <span class="n">SGDRegressor</span><span class="p">(</span><span class="n">penalty</span><span class="o">=</span><span class="s2">&quot;l2&quot;</span><span class="p">)</span>
<span class="n">sgd_reg</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="o">.</span><span class="n">ravel</span><span class="p">())</span>
<span class="n">sgd_reg</span><span class="o">.</span><span class="n">predict</span><span class="p">([[</span><span class="mf">1.5</span><span class="p">]])</span>
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<p><strong><em>In layman terms using ridge regression flattens the prediction line. 
write code to check this for yourself. plot prediction line for different values of alpha</em></strong></p>

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<h2 id="Lasso-Regression">Lasso Regression<a class="anchor-link" href="#Lasso-Regression">&#182;</a></h2><p>Least Absolute Shrinkage and Selection Operator Regression (simply called Lasso
Regression) is another regularized version of Linear Regression: just like Ridge
Regression, it adds a regularization term to the cost function, but it uses the ℓ1 norm
of the weight vector instead of half the square of the ℓ2
 norm</p>

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<p>$J(θ) = MSE(θ) + α∑|θ_{i}|$</p>

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<h3 id="An-important-characteristic-of-Lasso-Regression-is-that-it-tends-to-completely-eliminate-the-weights-of-the-least-important-features-(i.e.,-set-them-to-zero).">An important characteristic of Lasso Regression is that it tends to completely eliminate the weights of the least important features (i.e., set them to zero).<a class="anchor-link" href="#An-important-characteristic-of-Lasso-Regression-is-that-it-tends-to-completely-eliminate-the-weights-of-the-least-important-features-(i.e.,-set-them-to-zero).">&#182;</a></h3>
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<div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <span class="n">Lasso</span>
<span class="n">lasso_reg</span> <span class="o">=</span> <span class="n">Lasso</span><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.1</span><span class="p">)</span>
<span class="n">lasso_reg</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="n">lasso_reg</span><span class="o">.</span><span class="n">predict</span><span class="p">([[</span><span class="mf">1.5</span><span class="p">]])</span>
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<h2 id="Elastic-Net">Elastic Net<a class="anchor-link" href="#Elastic-Net">&#182;</a></h2><p>Elastic Net is a middle ground between Ridge Regression and Lasso Regression. The
regularization term is a simple mix of both Ridge and Lasso’s regularization terms,
and you can control the mix ratio r. When r = 0, Elastic Net is equivalent to Ridge
Regression, and when r = 1, it is equivalent to Lasso Regression</p>

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<p>$J(θ) = MSE(θ) + rα∑|θ_{i}| + (\frac{(1 − r)}{2})*α∑(θ_{i})^{2}$</p>
<div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <span class="n">ElasticNet</span>
<span class="n">elastic_net</span> <span class="o">=</span> <span class="n">ElasticNet</span><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">l1_ratio</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">elastic_net</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="n">elastic_net</span><span class="o">.</span><span class="n">predict</span><span class="p">([[</span><span class="mf">1.5</span><span class="p">]])</span>
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<h2 id="Important(when-to-use-what-kind-Of-regression)">Important(when to use what kind Of regression)<a class="anchor-link" href="#Important(when-to-use-what-kind-Of-regression)">&#182;</a></h2><p><strong><em>It is almost always preferable to have at least a little bit of regularization, so generally you should avoid plain Linear Regression. Ridge is a good default, but if you suspect that only a few features are actually useful, you should prefer Lasso or Elastic Net since they tend to reduce the useless features’ weights down to zero as we have discussed. In general, Elastic Net is preferred over Lasso since Lasso may behave erratically when the num‐ ber of features is greater than the number of training instances or when several fea‐ tures are strongly correlated.</em></strong></p>

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<h2 id="Early-Stopping">Early Stopping<a class="anchor-link" href="#Early-Stopping">&#182;</a></h2><p>A very different way to regularize iterative learning algorithms such as Gradient
Descent is to stop training as soon as the validation error reaches a minimum. This is called early stopping.</p>
<p>Figure 4-20 shows a complex model (in this case a high-degree
Polynomial Regression model) being trained using Batch Gradient Descent. As the
epochs go by, the algorithm learns and its prediction error (RMSE) on the training set naturally goes down, and so does its prediction error on the validation set. However, after a while the validation error stops decreasing and actually starts to go back up.
This indicates that the model has started to overfit the training data. With early stop‐
ping you just stop training as soon as the validation error reaches the minimum. It is
such a simple and efficient regularization technique that Geoffrey Hinton called it a
“beautiful free lunch.”</p>
<p><img src="img/earlystop.PNG" alt=""></p>
<p>Basic Implementation</p>
<div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.base</span> <span class="kn">import</span> <span class="n">clone</span>
<span class="c1"># prepare the data</span>
<span class="n">poly_scaler</span> <span class="o">=</span> <span class="n">Pipeline</span><span class="p">([</span>
 <span class="p">(</span><span class="s2">&quot;poly_features&quot;</span><span class="p">,</span> <span class="n">PolynomialFeatures</span><span class="p">(</span><span class="n">degree</span><span class="o">=</span><span class="mi">90</span><span class="p">,</span> <span class="n">include_bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)),</span>
 <span class="p">(</span><span class="s2">&quot;std_scaler&quot;</span><span class="p">,</span> <span class="n">StandardScaler</span><span class="p">())</span>
 <span class="p">])</span>
<span class="n">X_train_poly_scaled</span> <span class="o">=</span> <span class="n">poly_scaler</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_val_poly_scaled</span> <span class="o">=</span> <span class="n">poly_scaler</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_val</span><span class="p">)</span>
<span class="n">sgd_reg</span> <span class="o">=</span> <span class="n">SGDRegressor</span><span class="p">(</span><span class="n">max_iter</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">tol</span><span class="o">=-</span><span class="n">np</span><span class="o">.</span><span class="n">infty</span><span class="p">,</span> <span class="n">warm_start</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
 <span class="n">penalty</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">learning_rate</span><span class="o">=</span><span class="s2">&quot;constant&quot;</span><span class="p">,</span> <span class="n">eta0</span><span class="o">=</span><span class="mf">0.0005</span><span class="p">)</span>
<span class="n">minimum_val_error</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="s2">&quot;inf&quot;</span><span class="p">)</span>
<span class="n">best_epoch</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">best_model</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1000</span><span class="p">):</span>
    <span class="n">sgd_reg</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train_poly_scaled</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span> <span class="c1"># continues where it left off</span>
    <span class="n">y_val_predict</span> <span class="o">=</span> <span class="n">sgd_reg</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_val_poly_scaled</span><span class="p">)</span>
    <span class="n">val_error</span> <span class="o">=</span> <span class="n">mean_squared_error</span><span class="p">(</span><span class="n">y_val</span><span class="p">,</span> <span class="n">y_val_predict</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">val_error</span> <span class="o">&lt;</span> <span class="n">minimum_val_error</span><span class="p">:</span>
        <span class="n">minimum_val_error</span> <span class="o">=</span> <span class="n">val_error</span>
        <span class="n">best_epoch</span> <span class="o">=</span> <span class="n">epoch</span>
        <span class="n">best_model</span> <span class="o">=</span> <span class="n">clone</span><span class="p">(</span><span class="n">sgd_reg</span><span class="p">)</span>
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<p><a name="logreg"></a></p>
<h2 id="Logistic-Regression">Logistic Regression<a class="anchor-link" href="#Logistic-Regression">&#182;</a></h2><p><strong>Logistic Regression</strong> (also called Logit Regression) is commonly used to estimate the probability that an instance belongs to a particular class
(e.g., what is the probability that this email is spam?). If the estimated probability is
greater than 50%, then the model predicts that the instance belongs to that class
(called the positive class, labeled “1”), or else it predicts that it does not (i.e., it
belongs to the negative class, labeled “0”). This makes it a binary classifier.</p>
<blockquote><p>Just like a Linear Regression model, a Logistic Regression
model computes a weighted sum of the input features (plus a bias term), but instead
of outputting the result directly like the Linear Regression model does, it outputs the
logistic of this result</p>
<p>Logistic Regression model estimated probability (vectorized form)</p>
</blockquote>
<p>$p = hθ(x) = σ(θ^{T}.x)$</p>
<p>The logistic—also called the logit, noted σ(·)—is a sigmoid function (i.e., S-shaped)
that outputs a number between 0 and 1.</p>

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<h2 id="Sigmoid-Function">Sigmoid Function<a class="anchor-link" href="#Sigmoid-Function">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">x</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="o">-</span><span class="mi">10</span><span class="p">,</span><span class="mi">10</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sigma</span> <span class="o">=</span> <span class="mi">1</span><span class="o">/</span><span class="p">(</span><span class="mi">1</span><span class="o">+</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="o">*</span><span class="n">x</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s2">&quot;whitegrid&quot;</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">lineplot</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">sigma</span><span class="p">)</span>
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<blockquote><p>Logistic Regression cost function (log loss)</p>
</blockquote>
<p>$J(θ)= \frac{−1}{m}∑(y(i)log(p(i))+ (1 − y(i))log( 1 − p(i))$</p>
<blockquote><p>Logistic cost function partial derivatives</p>
</blockquote>
<p>$(\frac{∂}{∂θj})(J(θ)) = (1/m) ∑ (σ(θ^{T}·x(i))− y(i))x_{j}(i)$</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn</span> <span class="kn">import</span> <span class="n">datasets</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="n">iris</span><span class="o">=</span><span class="n">datasets</span><span class="o">.</span><span class="n">load_iris</span><span class="p">()</span>
<span class="nb">list</span><span class="p">(</span><span class="n">iris</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
<span class="n">x</span><span class="o">=</span><span class="n">iris</span><span class="p">[</span><span class="s2">&quot;data&quot;</span><span class="p">][:,</span><span class="mi">3</span><span class="p">:]</span>
<span class="n">y</span><span class="o">=</span><span class="p">(</span><span class="n">iris</span><span class="p">[</span><span class="s2">&quot;target&quot;</span><span class="p">]</span><span class="o">==</span><span class="mi">2</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">int</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="kn">import</span> <span class="n">LogisticRegression</span>
<span class="n">log_reg</span><span class="o">=</span><span class="n">LogisticRegression</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">log_reg</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>
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<pre>D:\ProgramData\Anaconda3\envs\ds\lib\site-packages\sklearn\linear_model\logistic.py:432: FutureWarning: Default solver will be changed to &#39;lbfgs&#39; in 0.22. Specify a solver to silence this warning.
  FutureWarning)
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<pre>LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,
                   intercept_scaling=1, l1_ratio=None, max_iter=100,
                   multi_class=&#39;warn&#39;, n_jobs=None, penalty=&#39;l2&#39;,
                   random_state=None, solver=&#39;warn&#39;, tol=0.0001, verbose=0,
                   warm_start=False)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_new</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">1000</span><span class="p">)</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">y_proba</span><span class="o">=</span><span class="n">log_reg</span><span class="o">.</span><span class="n">predict_proba</span><span class="p">(</span><span class="n">X_new</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">X_new</span><span class="p">,</span><span class="n">y_proba</span><span class="p">[:,</span><span class="mi">1</span><span class="p">],</span><span class="s2">&quot;g-&quot;</span><span class="p">,</span><span class="n">label</span><span class="o">=</span><span class="s2">&quot;Iris-Virginica&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">X_new</span><span class="p">,</span><span class="n">y_proba</span><span class="p">[:,</span><span class="mi">0</span><span class="p">],</span><span class="s2">&quot;b--&quot;</span><span class="p">,</span><span class="n">label</span><span class="o">=</span><span class="s2">&quot;Not Iris-Virginica&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<h2 id="Softmax-Regression">Softmax Regression<a class="anchor-link" href="#Softmax-Regression">&#182;</a></h2><p>The Logistic Regression model can be generalized to support multiple classes directly,
without having to train and combine multiple binary classifiers 
This is called Softmax Regression, or Multinomial Logistic Regression.</p>
<blockquote><p>Softmax score for class k</p>
</blockquote>
<p>$sk(x) = θ_{k}^{T}·x$</p>

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<h3 id="Cross-Entropy">Cross Entropy<a class="anchor-link" href="#Cross-Entropy">&#182;</a></h3><p>Cross entropy originated from information theory. Suppose you want to efficiently
transmit information about the weather every day. If there are eight options (sunny,
rainy, etc.), you could encode each option using 3 bits since 23
 = 8. However, if you
think it will be sunny almost every day, it would be much more efficient to code
“sunny” on just one bit (0) and the other seven options on 4 bits (starting with a 1).
Cross entropy measures the average number of bits you actually send per option. If
your assumption about the weather is perfect, cross entropy will just be equal to the
entropy of the weather itself (i.e., its intrinsic unpredictability). But if your assump‐
tions are wrong (e.g., if it rains often), cross entropy will be greater by an amount
called the Kullback–Leibler divergence.
The cross entropy between two probability distributions p and q is defined as
H p, q = − ∑x
p x log q x (at least when the distributions are discrete).</p>

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<p><a name="dectree"></a></p>
<h1 id="Decision-Trees">Decision Trees<a class="anchor-link" href="#Decision-Trees">&#182;</a></h1>
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<p>Decision Trees are versatile Machine Learning algorithms that can per‐
form both classification and regression tasks, and even multioutput tasks</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># sklearn example for iris dataset w Decision Tree</span>

<span class="kn">from</span> <span class="nn">sklearn.datasets</span> <span class="kn">import</span> <span class="n">load_iris</span>
<span class="kn">from</span> <span class="nn">sklearn.tree</span> <span class="kn">import</span> <span class="n">DecisionTreeClassifier</span>
<span class="n">iris</span> <span class="o">=</span> <span class="n">load_iris</span><span class="p">()</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">iris</span><span class="o">.</span><span class="n">data</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">:]</span> <span class="c1"># petal length and width</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">iris</span><span class="o">.</span><span class="n">target</span>
<span class="n">tree_clf</span> <span class="o">=</span> <span class="n">DecisionTreeClassifier</span><span class="p">(</span><span class="n">max_depth</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">tree_clf</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="n">tree_clf</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="n">X</span><span class="p">,</span><span class="n">y</span><span class="p">)</span>
</pre></div>

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<pre>0.96</pre>
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<p>We can export Decision Tree graphs by using export_graphviz</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn</span> <span class="kn">import</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">graphviz</span> <span class="kn">import</span> <span class="n">Source</span>
<span class="n">graph</span> <span class="o">=</span> <span class="n">Source</span><span class="p">(</span><span class="n">tree</span><span class="o">.</span><span class="n">export_graphviz</span><span class="p">(</span><span class="n">tree_clf</span><span class="p">,</span> <span class="n">out_file</span><span class="o">=</span><span class="s2">&quot;iris_tree.dot&quot;</span>
   <span class="p">,</span> <span class="n">feature_names</span><span class="o">=</span><span class="n">iris</span><span class="o">.</span><span class="n">feature_names</span><span class="p">[</span><span class="mi">2</span><span class="p">:],</span> <span class="n">class_names</span><span class="o">=</span><span class="n">iris</span><span class="o">.</span><span class="n">target_names</span><span class="p">,</span> 
   <span class="n">rounded</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">filled</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># display(SVG(graph.pipe(format=&#39;svg&#39;)))</span>
<span class="kn">from</span> <span class="nn">sklearn.tree</span> <span class="kn">import</span> <span class="n">export_graphviz</span>
<span class="n">export_graphviz</span><span class="p">(</span>
 <span class="n">tree_clf</span><span class="p">,</span>
 <span class="n">out_file</span><span class="o">=</span><span class="n">image_path</span><span class="p">(</span><span class="s2">&quot;iris_tree.dot&quot;</span><span class="p">),</span>
 <span class="n">feature_names</span><span class="o">=</span><span class="n">iris</span><span class="o">.</span><span class="n">feature_names</span><span class="p">[</span><span class="mi">2</span><span class="p">:],</span>
 <span class="n">class_names</span><span class="o">=</span><span class="n">iris</span><span class="o">.</span><span class="n">target_names</span><span class="p">,</span>
 <span class="n">rounded</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
 <span class="n">filled</span><span class="o">=</span><span class="kc">True</span>
 <span class="p">)</span>
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<h2 id="Use-graphviz-to-convert-following-to-png-image-using-the-following-command-in-command-line">Use graphviz to convert following to png image using the following command in command line<a class="anchor-link" href="#Use-graphviz-to-convert-following-to-png-image-using-the-following-command-in-command-line">&#182;</a></h2><p>dot -Tpng iris_tree.dot -o iris_tree.png</p>
<p><img src="img/iris_tree.png" alt=""></p>

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<blockquote><p>One of the many qualities of Decision Trees is that they require
very little data preparation. In particular, they don’t require feature
scaling or centering at all.</p>
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<p>A node’s gini attribute measures its impur‐
ity: a node is “pure” (gini=0) if all training instances it applies to belong to the same
class. For example, since the depth-1 left node applies only to Iris-Setosa training
instances, it is pure and its gini score is 0.</p>
<p>$Gi = 1 − ∑(pi, k^{2})$</p>
<ul>
<li>pi,k is the ratio of class k instances among the training instances in the $i^{th}$ node</li>
</ul>
<blockquote><p>Scikit-Learn uses the CART algorithm, which produces only binary
trees: nonleaf nodes always have two children (i.e., questions only
have yes/no answers). However, other algorithms such as ID3 can
produce Decision Trees with nodes that have more than two chil‐
dren.</p>
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<h1 id="Estimating-Probabilities">Estimating Probabilities<a class="anchor-link" href="#Estimating-Probabilities">&#182;</a></h1>
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<p>A Decision Tree can also estimate the probability that an instance belongs to a partic‐
ular class k: first it traverses the tree to find the leaf node for this instance, and then it
returns the ratio of training instances of class k in this node. For example, suppose
you have found a flower whose petals are 5 cm long and 1.5 cm wide. The corre‐
sponding leaf node is the depth-2 left node, so the Decision Tree should output the
following probabilities: 0% for Iris-Setosa (0/54), 90.7% for Iris-Versicolor (49/54),
and 9.3% for Iris-Virginica (5/54). And of course if you ask it to predict the class, it
should output Iris-Versicolor (class 1) since it has the highest probability.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tree_clf</span><span class="o">.</span><span class="n">predict_proba</span><span class="p">([[</span><span class="mi">5</span><span class="p">,</span><span class="mf">1.5</span><span class="p">]])</span>
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<pre>array([[0.        , 0.90740741, 0.09259259]])</pre>
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<h2 id="Model-Interpretation:-White-Box-Versus-Black-Box">Model Interpretation: White Box Versus Black Box<a class="anchor-link" href="#Model-Interpretation:-White-Box-Versus-Black-Box">&#182;</a></h2><p>As you can see Decision Trees are fairly intuitive and their decisions are easy to interpret. Such models are often called white box models. In contrast, as we will see, Random Forests or neural networks are generally considered black box models. They
make great predictions, and you can easily check the calculations that they performed
to make these predictions; nevertheless, it is usually hard to explain in simple terms
why the predictions were made. For example, if a neural network says that a particular person appears on a picture, it is hard to know what actually contributed to this
prediction: did the model recognize that person’s eyes? Her mouth? Her nose? Her
shoes? Or even the couch that she was sitting on? Conversely, Decision Trees provide
nice and simple classification rules that can even be applied manually if need be (e.g.,
for flower classification).</p>

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<h1 id="Under-the-Hood-for-Decision-Tree">Under the Hood for Decision Tree<a class="anchor-link" href="#Under-the-Hood-for-Decision-Tree">&#182;</a></h1>
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<ul>
<li>Uses the Classification and Regression tree algorithm to train Decision trees;CART Training Algorithm.</li>
<li>The idea is really quite simple: the algorithm first splits the training set in two subsets using a single feature k and a threshold tk.(e.g., “petal length ≤ 2.45 cm”). How does it choose k and tk ? It searches for the pair (k, tk) that produces the purest subsets (weighted by their size). The cost function is </li>
</ul>
<p><img src="img/DecisionTreeEQ.PNG" alt=""></p>

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<p>It stops recursing once it rea‐
ches the maximum depth (defined by the max_depth hyperparameter), or if it cannot
find a split that will reduce impurity</p>
<blockquote><p>the CART algorithm is a greedy algorithm: it greed‐
ily searches for an optimum split at the top level, then repeats the
process at each level. It does not check whether or not the split will
lead to the lowest possible impurity several levels down. A greedy
algorithm often produces a reasonably good solution, but it is not
guaranteed to be the optimal solution.</p>
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<h2 id="Regression">Regression<a class="anchor-link" href="#Regression">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">m</span> <span class="o">=</span> <span class="mi">100</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="o">-</span><span class="mi">100</span><span class="p">,</span><span class="mi">100</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">200</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="mf">0.5</span> <span class="o">*</span> <span class="n">X</span><span class="o">**</span><span class="mi">2</span> <span class="o">+</span> <span class="n">X</span> <span class="o">+</span> <span class="mi">2</span> <span class="o">+</span> <span class="mi">700</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">200</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sns</span><span class="o">.</span><span class="n">scatterplot</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">y</span><span class="p">)</span>
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<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x23b48476ef0&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.tree</span> <span class="kn">import</span> <span class="n">DecisionTreeRegressor</span>
<span class="n">tree_reg</span> <span class="o">=</span> <span class="n">DecisionTreeRegressor</span><span class="p">(</span><span class="n">max_depth</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">tree_reg</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>
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<pre>DecisionTreeRegressor(criterion=&#39;mse&#39;, max_depth=2, max_features=None,
                      max_leaf_nodes=None, min_impurity_decrease=0.0,
                      min_impurity_split=None, min_samples_leaf=1,
                      min_samples_split=2, min_weight_fraction_leaf=0.0,
                      presort=False, random_state=None, splitter=&#39;best&#39;)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">y_new</span><span class="o">=</span><span class="n">tree_reg</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
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<h2 id="Plot-for-Depth=2">Plot for Depth=2<a class="anchor-link" href="#Plot-for-Depth=2">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">y</span><span class="p">,</span><span class="s2">&quot;c.&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">y_new</span><span class="p">,</span><span class="s2">&quot;r-&quot;</span><span class="p">)</span>
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<pre>[&lt;matplotlib.lines.Line2D at 0x23b484e5358&gt;]</pre>
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<h2 id="Plot-for-depth=10">Plot for depth=10<a class="anchor-link" href="#Plot-for-depth=10">&#182;</a></h2>
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<h3 id="Is-this-overfit?-try-increasing-max_depth-for-clear-idea">Is this overfit? try increasing max_depth for clear idea<a class="anchor-link" href="#Is-this-overfit?-try-increasing-max_depth-for-clear-idea">&#182;</a></h3>
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<div class="prompt input_prompt">In&nbsp;[44]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tree_reg2</span><span class="o">=</span><span class="n">DecisionTreeRegressor</span><span class="p">(</span><span class="n">max_depth</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
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<div class="prompt input_prompt">In&nbsp;[45]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tree_reg2</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="n">y_new2</span><span class="o">=</span><span class="n">tree_reg2</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
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<div class="prompt input_prompt">In&nbsp;[46]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">y</span><span class="p">,</span><span class="s2">&quot;c.&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">y_new2</span><span class="p">,</span><span class="s2">&quot;r-&quot;</span><span class="p">)</span>
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<pre>[&lt;matplotlib.lines.Line2D at 0x23b4846e048&gt;]</pre>
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<p>The CART algorithm works mostly the same way as earlier, except that instead of try‐
ing to split the training set in a way that minimizes impurity, it now tries to split the
training set in a way that minimizes the MSE.</p>
<p><img src="img/DecisionTreeREGEQ.PNG" alt=""></p>

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<p>using a reularization Hyperparameter we can fit data better</p>

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<div class="prompt input_prompt">In&nbsp;[47]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tree_reg2</span><span class="o">=</span><span class="n">DecisionTreeRegressor</span><span class="p">(</span><span class="n">min_samples_leaf</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
<span class="n">tree_reg2</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="n">y_new2</span><span class="o">=</span><span class="n">tree_reg2</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">y</span><span class="p">,</span><span class="s2">&quot;c.&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">y_new2</span><span class="p">,</span><span class="s2">&quot;r-&quot;</span><span class="p">)</span>
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<pre>[&lt;matplotlib.lines.Line2D at 0x23b4854c780&gt;]</pre>
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<h2 id="Regularization-Hyperparameters">Regularization Hyperparameters<a class="anchor-link" href="#Regularization-Hyperparameters">&#182;</a></h2>
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<p>Decision Trees make very few assumptions about the training data (as opposed to lin‐
ear models, which obviously assume that the data is linear, for example). If left
unconstrained, the tree structure will adapt itself to the training data, fitting it very
closely, and most likely overfitting it. Such a model is often called a nonparametric
model, not because it does not have any parameters (it often has a lot) but because the
number of parameters is not determined prior to training, so the model structure is
free to stick closely to the data. In contrast, a parametric model such as a linear model
has a predetermined number of parameters, so its degree of freedom is limited,
reducing the risk of overfitting (but increasing the risk of underfitting).
To avoid overfitting the training data, you need to restrict the Decision Tree’s freedom
during training. As you know by now, this is called regularization. The regularization
hyperparameters depend on the algorithm used, but generally you can at least restrict
the maximum depth of the Decision Tree. In Scikit-Learn, this is controlled by the
max_depth hyperparameter (the default value is None, which means unlimited).
Reducing max_depth will regularize the model and thus reduce the risk of overfitting.
The DecisionTreeClassifier class has a few other parameters that similarly restrict
the shape of the Decision Tree: min_samples_split (the minimum number of samples a node must have before it can be split), min_samples_leaf (the minimum num‐
ber of samples a leaf node must have), min_weight_fraction_leaf (same as
min_samples_leaf but expressed as a fraction of the total number of weighted
instances), max_leaf_nodes (maximum number of leaf nodes), and max<em>features
(maximum number of features that are evaluated for splitting at each node). Increas‐
ing min</em><em> hyperparameters or reducing max_</em> hyperparameters will regularize the
model.</p>
<blockquote><p>Other algorithms work by first training the Decision Tree without
restrictions, then pruning (deleting) unnecessary nodes. A node
whose children are all leaf nodes is considered unnecessary if the
purity improvement it provides is not statistically significant. Stan‐
dard statistical tests, such as the χ
2
test, are used to estimate the
probability that the improvement is purely the result of chance
(which is called the null hypothesis). If this probability, called the pvalue, is higher than a given threshold (typically 5%, controlled by
a hyperparameter), then the node is considered unnecessary and its
children are deleted. The pruning continues until all unnecessary
nodes have been pruned.</p>
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<h1 id="Instability">Instability<a class="anchor-link" href="#Instability">&#182;</a></h1><ul>
<li>Decision Trees love orthogonal decision boundaries (all splits are perpendicular to an axis), which makes them sensitive to training set rotation.<blockquote><p>One way to limit this problem is to use PCA(Dimensionality reduction algorithm).</p>
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</li>
<li>Decision Trees is that they are very sensitive to small variations in the training data. </li>
<li>the training algorithm used by Scikit-Learn is stochastic6 you may get very different models even on the same training data (unless you set the random_state hyperparameter).</li>
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