Thesis_code.html

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  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

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

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

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

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
  height: 100%;
  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
    </style>
<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
.highlight .vm { color: #19177C } /* Name.Variable.Magic */
.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
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<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

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

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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">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="n">sns</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="n">style</span><span class="o">=</span><span class="s2">&quot;darkgrid&quot;</span><span class="p">)</span>

<span class="kn">import</span> <span class="nn">statsmodels.api</span> <span class="k">as</span> <span class="nn">sm</span>
<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">scs</span>

<span class="kn">import</span> <span class="nn">warnings</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s1">&#39;ignore&#39;</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Scrape OHLC data from Yahoo Finance API for </span>
<span class="c1"># S&amp;P500 Index, CBE VIX Index, SSE Composite Index, CNY/USD rates</span>
<span class="c1"># throughout the time period of 2008-01-01 to 2020-04-30.</span>

<span class="c1"># import yfinance as yf</span>

<span class="c1"># raw = yf.download(</span>
<span class="c1">#         tickers = &quot;^GSPC ^VIX 000001.SS CNYUSD=X&quot;,</span>
<span class="c1">#         start = &quot;2007-01-01&quot;,</span>
<span class="c1">#         end = &quot;2020-05-01&quot;,</span>
<span class="c1">#         interval = &quot;1d&quot;,</span>
<span class="c1">#         group_by = &quot;ticker&quot;</span>
<span class="c1">#         )</span>
<span class="c1"># raw.to_csv(&quot;raw.csv&quot;, header=True)</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;raw.csv&quot;</span><span class="p">)</span>

<span class="c1"># Data Cleanup and Preprocessing</span>
<span class="c1"># Leave only dates and close values.</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">3</span><span class="p">:,</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="mi">6</span><span class="o">*</span><span class="n">i</span> <span class="o">+</span> <span class="mi">4</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">)]]</span>
<span class="n">date</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span><span class="mi">0</span><span class="p">])</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1"># initialize new dataframe</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s2">&quot;date&quot;</span><span class="p">:</span> <span class="n">date</span><span class="p">,</span>
                    <span class="s2">&quot;SPX&quot;</span><span class="p">:</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;^GSPC.3&quot;</span><span class="p">],</span>
                    <span class="s2">&quot;VIX&quot;</span><span class="p">:</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;^VIX.3&quot;</span><span class="p">],</span>
                    <span class="s2">&quot;SSE&quot;</span><span class="p">:</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;000001.SS.3&quot;</span><span class="p">],</span>
                    <span class="s2">&quot;CNY&quot;</span><span class="p">:</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;CNYUSD=X.3&quot;</span><span class="p">]})</span>
<span class="n">df</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">],</span> <span class="n">drop</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">dropna</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">how</span><span class="o">=</span><span class="s2">&quot;any&quot;</span><span class="p">)</span>

<span class="c1"># Manual correction of error entry </span>
<span class="c1"># for this particular date in Yahoo Finance data.</span>
<span class="c1"># Replaced with data from investing.com</span>
<span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">&quot;2011-07-18&quot;</span><span class="p">,</span> <span class="s2">&quot;CNY&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="mf">0.1546</span>

<span class="c1"># preserve date range Series for log-return dataframe.</span>
<span class="n">date</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">]</span>
<span class="k">del</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">]</span>

<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">df</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span>
    <span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_numeric</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">],</span> <span class="n">errors</span><span class="o">=</span><span class="s1">&#39;coerce&#39;</span><span class="p">)</span>

<span class="c1"># generate graphs</span>
<span class="n">sns</span><span class="o">.</span><span class="n">relplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s2">&quot;line&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">df</span><span class="p">[[</span><span class="s2">&quot;SPX&quot;</span><span class="p">,</span><span class="s2">&quot;SSE&quot;</span><span class="p">]])</span>
<span class="n">sns</span><span class="o">.</span><span class="n">relplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s2">&quot;line&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">df</span><span class="p">[</span><span class="s2">&quot;VIX&quot;</span><span class="p">])</span>
<span class="n">sns</span><span class="o">.</span><span class="n">relplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s2">&quot;line&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">df</span><span class="p">[</span><span class="s2">&quot;CNY&quot;</span><span class="p">])</span>
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<pre>&lt;seaborn.axisgrid.FacetGrid at 0x7fb095279990&gt;</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Convert daily close quotes to one-day-ahead log returns in percentages + generate graphs</span>
<span class="k">def</span> <span class="nf">getLogReturns</span><span class="p">(</span><span class="n">quotes</span><span class="p">):</span>
    <span class="k">return</span> <span class="p">[</span><span class="mi">100</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">quotes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">/</span> <span class="n">quotes</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
           <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">quotes</span><span class="p">))]</span>

<span class="n">df_lret</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="n">df</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="n">date</span><span class="p">[</span><span class="mi">1</span><span class="p">:])</span>
<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">df_lret</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span>
    <span class="k">if</span> <span class="n">col</span> <span class="o">==</span> <span class="s2">&quot;VIX&quot;</span><span class="p">:</span>
        <span class="n">df_lret</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">][</span><span class="mi">1</span><span class="p">:]</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">df_lret</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">getLogReturns</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span>
    <span class="n">sns</span><span class="o">.</span><span class="n">relplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s2">&quot;line&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">df_lret</span><span class="p">[</span><span class="n">col</span><span class="p">])</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Separate Dataframes for the Great Recession and Coronavirus Recession</span>
<span class="c1"># defined respectively as Dec 2007 ~ Jun 2009 and Dec 2019 ~</span>

<span class="c1"># Global Date Variables</span>
<span class="n">ALL_START</span> <span class="o">=</span> <span class="s2">&quot;2007-01-01&quot;</span>
<span class="n">ALL_END</span> <span class="o">=</span> <span class="s2">&quot;2020-05-01&quot;</span>
<span class="n">TRAIN_END</span> <span class="o">=</span> <span class="s2">&quot;2018-12-31&quot;</span>
<span class="n">FORECAST_START</span> <span class="o">=</span> <span class="s2">&quot;2019-01-01&quot;</span>
<span class="n">GR_START</span> <span class="o">=</span> <span class="s2">&quot;2007-12-01&quot;</span>
<span class="n">GR_END</span> <span class="o">=</span> <span class="s2">&quot;2009-07-01&quot;</span>
<span class="n">COVID_START</span> <span class="o">=</span> <span class="s2">&quot;2019-12-01&quot;</span>
<span class="n">COVID_END</span> <span class="o">=</span> <span class="s2">&quot;2020-05-01&quot;</span>

<span class="n">COLS_EXCL_VIX</span> <span class="o">=</span> <span class="p">(</span><span class="s2">&quot;SPX&quot;</span><span class="p">,</span> <span class="s2">&quot;SSE&quot;</span><span class="p">,</span> <span class="s2">&quot;CNY&quot;</span><span class="p">)</span>

<span class="n">GRdf</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">GR_START</span><span class="p">:</span><span class="n">GR_END</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="n">GRdf_lret</span> <span class="o">=</span> <span class="n">df_lret</span><span class="p">[</span><span class="n">GR_START</span><span class="p">:</span><span class="n">GR_END</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>

<span class="n">CRdf</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">COVID_START</span><span class="p">:]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="n">CRdf_lret</span> <span class="o">=</span> <span class="n">df_lret</span><span class="p">[</span><span class="n">COVID_START</span><span class="p">:]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>

<span class="n">resultsdb</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;ALL&quot;</span><span class="p">:</span> <span class="p">[</span><span class="s2">&quot;Full Timeframe&quot;</span><span class="p">,</span> <span class="n">df_lret</span><span class="p">],</span>
             <span class="s2">&quot;CR&quot;</span><span class="p">:</span> <span class="p">[</span><span class="s2">&quot;COVID-19 Recession&quot;</span><span class="p">,</span> <span class="n">CRdf_lret</span><span class="p">]}</span>

<span class="k">for</span> <span class="n">data</span> <span class="ow">in</span> <span class="n">GRdf</span><span class="p">,</span> <span class="n">CRdf</span><span class="p">:</span>
    <span class="n">sns</span><span class="o">.</span><span class="n">relplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s2">&quot;line&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">[[</span><span class="s2">&quot;SPX&quot;</span><span class="p">,</span><span class="s2">&quot;SSE&quot;</span><span class="p">]])</span>
    <span class="n">sns</span><span class="o">.</span><span class="n">relplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s2">&quot;line&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">&quot;VIX&quot;</span><span class="p">])</span>
    <span class="n">sns</span><span class="o">.</span><span class="n">relplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s2">&quot;line&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="s2">&quot;CNY&quot;</span><span class="p">])</span>
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msTQGvdr5RqB/YA99mX3gfsUUrFKtVYIVa7mRLEzAg4uMJFGCvR1hTE63HJnhBVUsorez5WeeGvlFI3AnHgvwIJoFdrbQBorQ2lVB+wCRgstQGtrZGlLyoSi0WXdX09kj7Wp3L0KRjyAdDR0UhTNAhAczRY1f+vjbEIw5OpeZ9zNb5uxardv1IC2AucB+zVWv+pUuoa4EfA75SjAcPD8bM2jF5ILBZlcHCyHE/rWNLH+lSuPk1MWkfJj41MkUpZN8JcmFX9/4o1hzh5euKs51yNr1ux5favHGFdSg34JJDFLjVorZ8EhrBGwBuVUh4A++8NQPc5t0qINSprmLiw5u76KnwTbiEbWsMMjiXIZI2qPu9atGQAa62HgF8C/wnAnvnQDhwC9gG32JfegjVKLrn8IISYzcjl8Ng33zwVnoa2kM7WMKYJ/SNyPFGllToL4nbgL5RSLwL3A7dqrcfsx+9QSh0C7rDfFkKskGGYheD1FWZBVHsELJvyVEtJr6zW+hjwmnkePwhcU+Y2CbFmGYZZ2AXNU5gFUeUR8LowLqwz40RlyUo4IRzEyOXw2AFcqxqw3+ehtSkoI+AqkAAWwkGyuZkSRL4WXO0aMFgr4mQucOVJAAvhIIZx9gi42jVgsPYGPjMyXfIUUbEyEsBCOIhRNALe3tXE9ZesZ0tH9Rc/bGhrIJPNMTyRrPpzryUSwEI4iGGYhT0gomE/H37LLgJV3Asir3A6htSBK0oCWAgHyRaVIGqpcD7ckFUHTqUNHnjoUOHEDlEeEsBCOIiRMwub8NRSJOSjIehlYMxajPH80SG+9pMDHO0dr3HLVpfav9JCiAIjZzpiBAzQ1hxiaNwK4KFxqxYcT2Rr2aRVRwJYCAcxHFKCAIg1BRkas4I3H8BTclJGWUkAC+EgWYeUIADamkIMTyQxTZMhuxQxlZAALidnvNJCCMDeC8IhI+DWpiCZbI7xqTSDhRKEBHA5SQAL4SDWbmjO+LaMNVsbwg+OJRiWAK4IZ7zSQgjA2g84Pw+41lqbQgAc7Z0oTD+bSspNuHKSABbCQYo346m1tiZrBHzw1CgALpeMgMtNAlgIB7GmoTnj2zLg89AY9nGoewyArvaI3IQrM2e80kIIwFklCLDKEMm0dTTR+Rubics0tLKSABaihh58upt7f36o8LY1D9g535b5G3FNDX5am4JMJTKYpuyQVi7OeaWFWIP2Hh5k35GZYxSt3dCcNAK2AritOUg07CdrmKQzsh9EuUgAC1FDo5MpplMzMwuyhrMCOGbPhGhrChEJ+wG5EVdOEsBC1IhpmozGUyRSBrmcSS5nkjVy+L3V335yIfmZEG1NQRobfIAEcDlVf6t9IQQA06ls4df5RDpLvrQaDjrn27JjnbUvcOe6MFF7BCz7QZSPc15pIdaY0clU4d/TyWzh+J9I0FerJp0l1hziE+/fw7b1jaRNqzQiI+DykQAWokbmBrBhB7CTRsAAO7qaAQgErB8MMhe4fJz1SguxhswK4FQWw17u2xByzgi4WL4EEZflyGUjASxEjcwdAWcMa8FDg8NGwHk+r5uA3yMj4DJy5istxBowOpnCBZjAdCpDJmuNgMMOqgHPFQl6pQZcRjINTYgaGZ1MEWu25tkmktnCyNKpI2CwyiMyAi4fCWAhamR0MkVnaxgXVg14Kpkl4PM45kSM+URCPtkPooyc+0oLscqNTiZpbQwSCniZTmaZTmZpCDl39AvQEPTJwZxl5OxXW4hVKp0xmEpmaY4GCAe9TCWzJNNZwgHn1n/BGgFLCaJ8ZAQsRA2Mxq0ZEOuiAcIBLwm7BOHk+i/YNeBkhpzsiFYWEsBC1MDohBXA+RHwdDLDVDLj2DnAedGQD9O0ps2Jc1fSj1ul1Akgaf8B+DOt9c+UUtcC9wAh4ATwfq31QPmbKcTqUjwCDgW8DI4lmE5mHbcKbq6WaACwbiBGHP7Doh4s59V+p9Z6f/4NpZQL+DrwQa31Y0qp/wp8BvhwmdsoxKqTX4TRHLFHwKksU8mMo/aBmM9MACfZ1B6pcWvq37mUIK4Eklrrx+y37wbede5NEmL1G51MEQp4CAW8hAM+JqYypDO5uhkBjxSt4hMrt5xX+1571PsY8BfAZuBk/p1a6yGllFsptU5rPVLqJ21tXd5P0Vgsuqzr65H0sT4tp0/TaYO25jCxWJTYunDh2PeOWMTR/zfbt7bidkHKMB3dzpWqdp9KDeAbtNbdSqkA8AXgS8D3ytGA4eF4YRu+pcRiUQYHJ8vxtI4lfaxPy+3TmaEpGkNeBgcnMY2ZI37MrOHY/5tYLMrIyBRNkQC9ZyYd286VWu5rWI6wLqkEobXutv9OAf8/8ErgFLAlf41Sqg0wlzP6FWKtGp1M0hK1TpsoLjs4vQQBVhlidDK59IViSUsGsFKqQSnVZP/bBbwH2Ac8C4SUUtfbl94OPFCphgqxWhi5HONTaZrtemo4MBO6DQ6/CQdWAEsNuDxKGQF3AI8opV4A9gM7gT/UWueAW4F/UEodBl4N/HnFWirEKjEeT2Oa1hQ0mD3qdfpCDMiPgCWAy2HJV1trfQzYvcD7ngAuKXejhFjN8nOA8yPgUKC4BFEfI+Bk2iCRys5qu1g+WQknRJXlV8HNHQG7mF2OcKrixRji3EgAC1Flc0fA+Q14QgEvbrerZu0q1Tr75qEE8LmTABaiykYnU3g9LqL2Ut5gwIMLHL8VZd7MYgyZCXGuJICFqLKxyRTNkQAulzXadbtc1oq4Oqj/grV8GmQEXA4SwEJU2chkqlD/zQsHvXUxAwKswzkbwz4J4DKoj1dciFVkbDLF1vWzV1GpTc202efD1YOWaFACuAwkgIWoItM0GZlMsWdnbNbjv/vWC2vUopVpiQY4NTDJo8/3EQp4CdobC4X8Xruc4iXg89S6mY4nASxEFU0ls2SNXGEGRL3atj7KviND/MtPDs77fo/bxSc/cCWbO1bfhj3lJAEsRBWNTFgzB+bWgOvNza/cxk1XdJFIWQsyEuksiZRBMp1leCLJt355lJP9kxLAS5AAFqKKxubMAa5n4aBv3pkbWSPHdx45xuBYogatqi8yC0KIKspvYlPvI+DFeD1uWpsCDI7JPOGlSAALUUVjkylcLmhs8Ne6KRUVaw7JCLgEEsBCVNHIZIrGBj9ez+r+1os1hxgYrWwAn+qf5Ks/PVjygQ5OtLq/CoRwmLF5FmGsRu3NIeKJDIlU5Y6v/8WzPTyyr4+h8fodaUsAC1FFo/Yy5NUuZi8qqVQZwjRN9h+3Dt8ZHK/fWrMEsBBVNDqZKuwmtppVOoB7B6cKK/HqudYsASxElaTSBtOpLM3R1X0DDooDuDKj0xePDQPgcsFQHc+2kHnAQlRJfh/gtTACzm8uNFCh0emLx4bpikVIZw0ZAQshljZqr4JbDYswSlGpqWiJVJbDPeNcct46Yk1BuQknhFjazAh4bQRwe0tlAlifGsPImVx8Xqsd8vVbgpAAFqJK8jeN1tIIeHg8iZHLlfXzHuoew+txsX1jI21VmO5WSRLAQlTJyGSKhjW0TWN7cwgjZ5Z9QcbhnjG2rm/E5/UUbvYN1elUNAlgIapkbDK1Zka/ADs3NwPw8onRsn3OVMbgxJlJdnQ1AdDWZN3QrNcbcRLAQlTJyGSqcKDlWtDeHKK1McjLJ0bK9jmP9U1g5Ex2dlnhXhgBSwALIRYzNpmiZQ2sgstzuVxctK2Fg6fGylYHPtwzhgvYbo+AG4JeQgFP3d6IkwAWogqyRo6JqfSaGgEDXLh1HYlUlhOnJ8vy+Q53j7Ex1kCDvQ+xy+Ui1hRisE6nokkAC1EF4/E0Jqy5AN61pQWgLGUII5fjSN8EOzY1z3q8rTlE/8g0pll/u6JJAAtRBQOj0wC0NdXPycflEA372dwRYd+RYeKJzDl9ru6BOKm0Uaj/5u3a0kL/aIJfPd93Tp+/FiSAhaiCk/1xADZ1RGrckuq7elcHx09P8EdffJS/+eozfP/RYxzpHV92XfhQ9zhAYQZE3o17NnLxtnV848HDnOovT6mjWmQvCCGq4NTAJC3RAI3h1b8Rz1xvumYzOzc1s//YMPuPj/CjJ07ww8dPEA54uXBrC5ec38p1F3UuuUn94e4x2pqCrGucvZeG2+XiI2+9kL/856f49q+O8vF3XV7J7pSVBLAQVXDyzCRb1ugJwS6Xi+0bm9i+sYm333Ae8USGl0+MsP/4CPuPDfOMHiTk93LlBe0Lfg7TNDncM8ZF29bN+/7GBj/bNzZxZmS6Ut2oCClBCFFhqbTBmZFpNq/B8sN8IiEfV+/q4MNv3sV//73rAArB+dSBfj755SeZSs6uF/ePJpiYzpx1A65YNOxjcjpduYZXwLJGwEqpvwI+BVyitd6vlLoWuAcIASeA92utB8rdSCHqWfdgHNOELZ1rcwS8mIDfQ2ODv7Cj2csnRugdnOK7vzrGrW9QhesOd48BnHUDrlg07COeyJAzTdwuV2UbXiYlj4CVUnuAa4FT9tsu4OvAR7XWO4FfA5+pRCOFqGf5G0NrtQSxlFhTsLCQon/ECuJH9vZyrG+icM2hnjEiIR/rW8MLfp5o2I9pwtQ5zraoppICWCkVAO4C/hDIT7a7EkhqrR+z374beFfZWyiEw0xMp/nE//oN++1TGZZy8swkkZBvzc0BLlXxvsFnRqe5QsVoivi5/+HDhWsOd4+zo6sJ1yIj22jYWpwxOV0/AVxqCeKvga9rrY8rVfi1YDNwMv+G1npIKeVWSq3TWpc867q1dXl1sVhs9Y8ipI/O9tOfHKB/ZJpDvRPceM3WwuML9alvZJrtm5ppb2+sUgsrpxKv25YNTTx1cIBQJMh4PM1F57exY/M6HnhI0xANkkwbDIwleOsN5y36/JvWWyHu8XtX3M5qf10uGcBKqeuAq4A/r0QDhofj5HKlrWCJxaIMDtbXPL/lkj46WyKV5UePHgPgwInhQj8W6pORy3Gib4LXX7WpbvucV6nXLexzk8uZPPbsKQAifg/BqJ+cCU+90Me0vdfv+pbgos9vpK3ruvvG6Whc/m8by+1fOcK6lBHwq4ELgPzotwv4GfBFYEv+IqVUG2AuZ/QrRL15ZG8viVQWtamZ46cnMHI5PO6FK3nTySxGzpTywyLyO5rlj5lvbwnR1hTCBRzpHSeeyOD3uZesoUftOdb1NBNiyRqw1vozWusNWuutWuutQA/wBuBzQEgpdb196e3AAxVrqRAO8Mu9veza0sKrLttAOpvj9NDi807zJzWEAjLlfiGFAD5mBXBHS5hw0MvGWIQjPWMc7hnj/A1NSy7UqMca8IrnAWutc8CtwD8opQ5jjZQrUqYQwinGp9Js7Yyydb01Gjt+ZmLR6/O/PoeDEsALaYkG8LhdDE8kaYkGCPitE0N2dDVxpHeC7oH4WcuP5+P1uAkFvHUVwMv+qrBHwfl/PwFcUs4GCeFUOdMkk83h93noWBcm4Pdw8swkN1y68MckknYAywh4QW63i9amIAOjCTpaZjYr2r6xiV/u7QVYdAFGsWjYx2RiFZUghBCWTMbaPMbvc+N2udjSEeXEmcVv2kynDEBKEEvJlyHaW2bm+eY3XXe7XJy/obQZJNZquPoZAUsAC1GiVNYKU7/X+hV5a2eU7oE4WWPhXb2kBlyamH22W+e6mQBuawrSFLG2swz6S/v/awz76+omnHxVCFGidCYfwNa4ZWtnlEw2R9/QFOs7569RSgCXJj8CLi5BuFwuPvSmXQT9pZ8iHQ37Zq2gczoZAQtRonShBGGPgNdbvxafXKQMMRPAa+Mo+pXa3BnF43axqX32wqxLz29lZ4n1X7CmosUTmbo5HUMCWIgSpfMlCJ/1bdPeEiLo9yxaB55OZQn4PIvOFRZw0dZ1fOFj19PWfG4nhkRDPoycWZh94nTyVSFEieaOgN0uF1s7F78Rl0hlZfRbovxBm+diZjFGfdyIkwAWokT5EXDAOxOoW+a5EdczEOeEPT/YCmCp/1bLzGKM+rgRJwEsRInSRdPQ8rZ2NpI1cpwqGgV/46FDfPWnGrACWOYAV4+MgIVYpQqzIHwzI+Ct9ibr+Q3DwTq9YSyeAqx5wDICrh4ZAQuxSqWz9gjYO/NtE2sJEQp4OdpjBXAmazA2mWJiyjqZQUoQ1X+jl3gAABrnSURBVFVv+0HIV4YQJUrNMwK2VsRFOGwH8NB4EhPrEMl4IiMBXGU+r4eg38N4XEbAQqwq+RJEwDf722br+kZO9E2QNXKFo3UAJuJpqQHXwM5NzTx5oL8wB9vJJICFKFE6k8MFZ22LuLUzStbI0Ts4VThcEmBkMkk6m5NpaFX2tuu3EU9keOjZnlo3ZUkSwEKUKJ018PncZ51Llr8Rd+LMROFsM4Az9gGTUoKorm3rG7l8exs/e/IU00ln14IlgIUoUTqTK2zEUyzWHKIh5OPEmUkGx5KF0y/OjFibtUsAV9/brt/GdCrLz5/urnVTFiUBLESJ0hnjrPovWJvGbO9qsgM4wab2CH6vmzPDU4DsBVwLWzqjXLEzxoPPdBN38DH1EsBClChtb8Y+n+1dzfQMxBkYTRBrDtHY4C+MgOU0jNp42w3bSKYMfvbUqVo3ZUESwEKUKJ0x5i1BAGzf1IyRM0llDGLNIZoifsbsqVBSgqiNrliEq3a189AzPUwssDBDnxqlb2iqyi2bIQEsRImsEfD83zLbu2a2TIw1BWlqmDkFWQK4dt52/TbSWYOfPjn/KPjuH77EL2o4W0ICWIgSpTPGgiWIjnVhGuxSQ74EkScBXDvrWxu49sJOHn62h/F4CtM0CxsnTSezjMfTtNqncdSCBLAQJUplcrOWIRdzuVxssaejtTUHaZoVwDIPuJZ+6/qtZA2Trz94iL/+12f4xD2/IWeahRp98TFI1SY/moUoUTprEFhgBAxwxc4YhmES9HsLASybsddeR0uYV1zSyWMvnMbjdmHkTAZHE5wZsWq/61slgIVwvHTGwLfACBjgxj1d3LinC6AQwDL6dYbfec35bG6PsDEW4XP37eVk/ySnh6dxu1yF8+hqQQJYiBKlMwtPQ5urMZIPYPkWc4Jo2M/rrtxEJpvD43Zxqj9O/+g0sZbQWUvLq0m+OoQoUTprLDgLYq4me2NwWYThLD6vmw1tDZzqn2Q0nmJ9Deu/IDfhhChJLmeSNcxZxxEtprFBRsBOtaUjysn+SfpHEjW9AQcSwEKUZOZE5NIC2O/zEAp4JYAdaHNHhMnpDFkjR2cNb8CBlCCEKMl858Et5ZWXdLKlI1qpJokV2lz0mtR6BCwBLEQJCufBlViCAHjv63ZWqjniHGxqj+ACTKj5CFhKEEKUIJVd/ghYOFMo4KW9JURD0Es05KtpW2QELEQJ5jsRWdSvK1Q74/HUWZvrV5sEsBAlmClByAh4NXjna86vdROAEgNYKfV9YBuQA+LAHVrrfUqpncBXgFZgGLhNa324Uo0VolYKR9LLCFiUUak/zj+gtb5Ma70b+Dzwz/bjdwN3aa13AncB91SgjULUnIyARSWU9NWktR4verMJyCml2oE9wH324/cBe5RSsfI2UYjay09DW2wzHiGWq+QasFLqn4DXAy7gjcAmoFdrbQBorQ2lVJ/9+GCpn7e1NbKsBsdiq39epfTRefzBYQDWdzbS2jT/5i311qeVWO19rHb/Sg5grfVHAJRStwKfAz5ZjgYMD8fJ5cySro3FogwOTpbjaR1L+uhMw6PW3rGTEwly6exZ76/HPi3Xau/jcvtXjrBedkFLa/014EagB9iolPIA2H9vAJx9DrQQK5DJLn8hhhBLWTKAlVIRpdSmordvBkaAAWAfcIv9rluAvVrrkssPQtSLVCaHywVeT23njYrVpZQSRAPwLaVUA2Bghe/NWmtTKXU78BWl1F8Co8BtlWuqELWTPw+u1hP3xeqyZABrrfuBaxd430HgmnI3SginSWdzBGQKmigz+YoSogTWcURS/xXlJQEsRAmsEoR8u4jykr0ghFjEkd5xDveMEU9kZBmyKDsJYCEW8ZPfnGTv4SEAdnY11bg1YrWRABZiEX3D02xuj5AxcmxsX96qTSGWIgEsxAKyRo7B0QRvvm4z//lVzti+UKwucldBiAX0jybImSbrWxtq3RSxSkkAC7GA00NTAGyQABYVIgEsxAJOD1sBXOuTc8XqJQEsxAJOD0/T2hgg4JfpZ6IyJICFWMDp4Wmp/4qKkgAWYh450+T0yJQEsKgoCWAh5jEykSSdybG+Veq/onIkgIWYx+lh6wQMCWBRSRLAQswjPwVtfZuUIETlSAALMY/eoSkiIR+NYX+tmyJWMQlgIebRNzRFV0xGv6KyJICFmMM0TXqHptgg5QdRYRLAQswxMpEimTbYKAEsKkwCWIg5eu0bcBtjsv2kqCwJYCHm6MtvwiMjYFFhEsBCzNE7GKepwU8k5Kt1U8QqJwEsxBy9Q1NslBkQogokgIUokjNN+oZlBoSoDglgIYoMjVt7QMgMCFENEsBCFOkblBkQonokgIUo0jsUB+QYIlEdEsBCFOkdmqIlGiAclAPDReVJAAtRpG9QZkCI6pEAFsKWy5n0DU/LDThRNRLAQtgGxhJkjZxMQRNVIwEshK3XngHRJTMgRJUseadBKdUKfA04H0gBR4Df11oPKqWuBe4BQsAJ4P1a64HKNVeIyumzZ0DIMUSiWkoZAZvAZ7XWSmt9KXAU+IxSygV8Hfio1non8GvgM5VrqhCV1Ts0RVtTkKBfZkCI6lgygLXWI1rrR4oe+g2wBbgSSGqtH7Mfvxt4V9lbKESV9A5NyQ04UVXL+lGvlHIDfwD8ENgMnMy/T2s9pJRyK6XWaa1HSv2cra3Lq7fFYtFlXV+PpI/VlzVy9I9Mc+3F61fcNqf1qRJWex+r3b/l/q7190Ac+BLw2+VowPBwnFzOLOnaWCzK4OBkOZ7WsaSPtdE7NEXWMGlp8K2obU7sU7mt9j4ut3/lCOuSZ0EopT4P7ADerbXOAaewShH597cB5nJGv0I4RX4T9o1tMgNCVE9JAayU+jRwBfB2rXXKfvhZIKSUut5++3bggfI3UYjK6x2M43LJDAhRXaVMQ7sI+AvgEPCEUgrguNb6t5VStwL3KKWC2NPQKthWISqmd2iK9uYQfp+n1k0Ra8iSAay1fglwLfC+J4BLyt0oIaqtT46hFzUgK+HEmpfJ5ugfScgmPKLqJIBFTZlmaTNgKunMyDQ505QbcKLqJIBFzTx/ZIg/+uJjHOoeq2k78puwyyIMUW0SwKImXjg6zF3fe5F4IsNzhwZr2pbewSncLhcd62QGhKguWfQuqu65gwN86bsvsqGtARcuDvfUdgTcNzRFx7oQPq+MR0R1yVecqKqXjo/w6X95kvWtYf7kPbu5+Lx1nDwTJ5U2atYm2QNC1IoEsKial0+M8MXvvMCGWIQ/ec/lREI+dnQ1kzNNjp2eqEmbJqfTDI4m2NQuN+BE9UkAi6o4cHKUL377BdpbQvzN7a8gGvYDsH1jIy6oWRli/7ERTODi81pr8vxibZMAFhWnT43yP7/9PG3NIf70PbtpigQK7wsHfWyMNXC4Z7wmbXv+6BCNDX62dK7uXb6EM0kAi4o61D3GF771Aq2NQf70lt00NvjPumZHVzNHescxcrmqti1r5Nh/bIRLz2vF7Zp3sacQFVWXAXzyzCRf+u6LJd24yWRz7D00yHQyW4WWiWKHe8b4u289T0s0wJ237KZpnvAF2LGpiVTa4FB3dUfBR3vHmU5luWy7lB9EbdRlAP/gseM8d2iQpw72L3nt9359jL//7ot8/K7H+MZDh8g5YOXVWnC0d5y/e+B5miMB7nzv7LLDXLt3xGhs8PPjJ05Ur4HA80eH8bhdXLh1XVWfV4i8ugvggbEEzx8ZAuDRF04vem3vYJwHn+nmip0x9uyM8dAzPfxqb281mrmmHe0b5388sI/GBj933rKb5kXCFyDg8/CmazZz4ORoYVWcaZp865dHuOeHL/HUgX4SqfL+BmOaJnsPDbJzUzOhgEyHF7VRd195v3yuB5fLxU17NvLQsz2cHp5ifevZczhN0+TeBw8R9Hu47Y2KSMjH5FSaBx45yqXnt9HaFKxB61e/46cn+B/f3Ec0ZIVvS3Tx8M17ze6N/OQ3J/nur45yxzsv5cGnu/nJk6cIBTw8+XI/Xo+bi7etY8/OGDs3NXG4Z5yxeIo3XbtlRfXbo70T9I8mePN1W5a+WIgKqasATqayPPr8aa5QMd5y3RYefq6XR184zbtu3H7WtU8e6OfgqTFufYMqTHn6wBsv4JNffop7HzzEx955abWbfxbTNDFyJl5P3f0iMq8TZyb42/v30RD0ced7d7OusfQfcgGfh7ffcB5f/Znm4196nEw2x/WXrucDb1Qc6RnnuUNDPHdogH32bz95Ozc1s6OruaTnyOVMkuks4aCPR1/oI+DzcNUF7cvqoxDlVFcBnEhlCQe9vOnazTRFAly2vZVf7etlUyzCtRd14LJHQolUlm8+fIQtnVFefdmGwse3NYd487Wb+d6jx2u++imZzvI/v/UCU8ksn/rQVbjd9X0X/uSZSf72/n2Eg95lh2/ea3Zv5LwNjTz8XA85E257g8LjdqM2t6A2t/Cem7Zzsn+So70TdMUa+Pz9+9h7aKikAD5+eoJ//clB+ken+cO3X8xTBwe48oKYHEEvaqquhl4tjUH+v9uvY2tnIwDvvmkHG1ob+Mcfv8yX/+1A4bofPn6ciXiaW1+vzgq2V+/eiNfj5uFne6ra9mLpjMEXv/0CunuMnsE4LxwbrllbyuFU/ySfv38vQb+HO2/ZTVtTaMWfa3NHlA++aRcffvOus34zcLlcbO1s5KYrulCbW9i1pYXnDg8uuqVlKm3wzYcP8zdffYaJ6TQt0SBf+NYLpNIGN1y6YcGPE6Ia6iqAgcIoF6C9OcQnbr2C11+1iSf2n+H46Ql6BuM8+HQPN1y2gfM2NJ718Y1hP9dc2M4T+8/UZGpaJpvjS999EX1qjA+/eRct0QAPPdNd9XaUS/dAnM/fv4+A38OfvncPbc0rD9/l2r0zxsBogr7hafpHpzk9PDXr/S8dH+GTX36Snz3Vzasv28CnP3INf/6+PWxoa2BjrIEdXU1Va6sQ86n737/cLhdvu34bj794mh88dpxU2iAU8PCOV5+34Me87opNPP7iGR57oY/XX725am3NGjn+4fv72X98hA++6QKuv3Q941MpvvOrY2eVRIbGEtzzo5cIB3y0NQdpawrS1hSirSlIrDlEQ9A764dRLfQMxvncfXvxed3cectu2qsYvgCXb2/jaz/TfOeRoxw4OQrAH7/ncjrXhfnmLw7z+P4zdKwL82fv3Y3a3FL4uE996Coy2VzN//+EqPsABggFvLz+6s1879fHAKt2mL/xNp8tnVHO39DIYy+erloAG7kc/+uHL7HvyBDvf/1OXmXXpl912QZ++PgJfvrkSX73LRcWrn/yQD9HeyfY3BHhWN84U3NG66GAh1dcvJ533Xg+Pm/1D5LstcPX63Fx53t3095S/b10W6IBtq1vZN+RIbpiDaSzOf7ugefxelxMJ7O89RVbufkVW876//F63Kvmxqeob6sigAFed0UXP3/qFLHmUCHcFnPtRZ3c++ChqtyMy5kmX/63AzyjB3nPa7fz2j1dhfdFw35u2tPFT586xTUXdnBjzNqT4IWjw2zpiPJXH7oKgOlkluGJJENjCQbHk5w8M8Evnu3hSM84H3vnpSVP9yqHvqEpPnffXtxuF3e+dw8dNQjfvLdet4Vn9ADv+087SaQMPnvfc0TDfj74xgvokh3OhMOtmgAOBbx86kNXEw56S5pRcKWK8Y2HDvH0gX423rBwuaIcnnjxDL95qZ/fvmHbvCPut9+wjeePDvEv/36Qqy7ewFQyw5Hecd5y3dbCNeGgl3AwMmvbxCsvaOeeH77EA788wu//1kUV7UPe6WErfHG5uPOW3XTW+BSJ3Ttj7N4ZA6yNff77712Hy4WUF0RdWFW/h7U2BUte1dQUCXDB5haePDBQ0YMhE6ks3/nVUc7f0MhbXrF13mv8Pg8feeuFjMfT3PP9F3np+AimCZeev/geBbt3xLhpTxdPvdx/1g2ocslkc5wZmeaFo0P8/KlTfPa+vZimyZ237J53AUytud0uCV9RN1bNCHglrt7Vzld+qjnVHz/n7Qhzpkl8OsPAWIJkKovH7cLjcfPkgX7Gp9Lc8Y5LF12xtW19Ize/cis/eOw4Lx8bpiHo5bz1Z8/imOsNV2/mF8/18OMnTvJ/3HzhkteX6sSZCR5+tpcnD/STyc7sUhZrDvKxd1zKBjlBQohztqYD+ArVztd/fogvfOt5rr2og+su6mRzx+wgHhhL8I0HD9EzGCcS8hEN+WgI+UhncsQTmcKfqWSGhQbSr7i4c94pcXO95botvHRihCM941x7YUdJpZTGBj837t7Iz5/upm9oChOT9a0NdMUa6IpZJYt8fXgsnmZiKk0qY9DZGqZxzo3KTDbH0wf7efi5Xo71TeD3ubnuok52bmoi1hyic1140ZubQojlWdMBHAn5+ON3X86Dz3Tz0DM9/OypbrpiDVx3cSfbOq2764/s7cXtdnH5jjYSySzxRIah8SR+n4dIyEdXe4RIyEck5KUx7LeniPkwcjmyhpXIanNpS2W9Hjcff+8V3Pn3j3L1hR0l9+NN126hfyRBzjQxTTjSM86TL8/sFBcOeDFM86ztO9e3hrnpii4u2rqOx148za+f72NyOkPHujC33LSDV17SSTjoK7kdQojlcVWy/rmErcDx4eE4uVxpbYjFogwOTlakMfFEhqcO9PMf+89wtM86n8zrcbFnZ4x3v3ZH1WYZxGJRBgYmzrmOOZ3M0DM4Re9gnO7BKbxuF52tYZoaAvh9bnoG4jx3eJCjvVZfXS5rXu1r93Sxa2tLRTcor+TrWCursU9zrfY+Lrd/sVj0nL9J1vQIuFgk5OO1e7p47Z4u+kem6RmcYteW5pqMAMtxEykc9LFzUzM7N80/+r7kvFbeeM1mDp4c5WR/nKsuaJcd4oSoMgngeXSsC9NR4+lV1eByudi1dR27ZENyIWpiVU1DE0KIeiIBLIQQNSIBLIQQNbJkDVgp9XngHVizFi7RWu+3H98JfAVoBYaB27TWhyvXVCGEWF1KGQF/H3gVcHLO43cDd2mtdwJ3AfeUuW1CCLGqLRnAWuvHtNazdgxXSrUDe4D77IfuA/YopWLlb6IQQqxOK52Gtgno1VobAFprQynVZz8+uJxP1Nq6vC0DY7Fz27OhHkgf69Nq7NNcq72P1e5fzecBO2UlnFNIH+vTauzTXKu9jytYCXfOz7nSWRDdwEallAfA/nuD/bgQQogSrCiAtdYDwD7gFvuhW4C9WutllR+EEGItWzKAlVJfVEr1AF3AQ0qpl+x33Q7coZQ6BNxhvy2EEKJES9aAtdYfAz42z+MHgWvO4bk9QEl73hZb7vX1SPpYn1Zjn+Za7X1cZv+2Aj1AdonrFlTL7SivBx6t1ZMLIUQZbANOrPSDaxnAAeAq4DRgLHGtEEI4Ud2OgIUQYk2TzXiEEKJGJICFEKJGJICFEKJGJICFEKJGJICFEKJGJICFEKJGJICFEKJGJICFEKJGKrIfsFKqFfgacD6QAo4Av6+1HlRKXYt1fFEIawnf++3d1VBK3QvcCKwHolrreNHn/BDwX7D2kDgGfEBrPbLA88/7eexz7O6xH88CTwN/qLVOVKOPSz2/Uupm4HNYr8uzwIe01tMLPP+81yqlAsAPgCsBtNZty+1bHfTxFcDngWb70n8D/kxrnavjPq0Hfgj4sL7GDwK/p7UeXapP9dLHove7gIeAy1by9enU/imlttpt2V90+U1a6+GF+lKpEbAJfFZrrbTWlwJHgc/Y//FfBz5qnyX3a+AzRR/3ZeDyuZ9MKbUL+BuszlwEPAn8t0Wef97PA6SBj2utLwAuBcLAnyy3c7aV9HHB51dKRYB/BG7WWm8HJhdq2xLXGljh9LoV9qse+jiB9QP4QmA3cB3wvjrv0xDwaq315VrrS7CWuH6yxD7VSx/z/k/OYf8Eh/dvzH4N838WDF+oUABrrUe01o8UPfQbYAvWqCyptX7Mfvxu4F1FH/dwfjQ8x8XAvqL9hv+dRb7hFvo8WusTWuu99r9zwFN2u5ZtJX1c4vnfBDxTdLL03cC7F3j6Ba/VWme11g8BYyvpVzEH93F//nGtdQrYS4mvo4P7lMmPuOwDDiLAkiP6euqj3bcdwHuYPfBaNf1brorXgJVSbuAPsH692kzR6cpa6yHArZRat8SneR64Uim1zf4p914gUsLHLdauEPBhu13nZCV9nOf5Z30ccArrjL35LOfasnBqH+0DYt+BVYZYFif2SSm1D+tcxR3AXy+vR2dzUh/ttvwj8FEgs7Iezeak/tkalVLPKKWeVUr9qZ1XC6rGTbi/B+LAl1b6CbTWh4A/Ar6J9dMuP6xf0S5ESikvcD/wsNb6nAOYZfaxAs9fDY7ro1IqivVN9Lf50c0yOa5PWuvLgQ7gAOU55MBJffwT4Nda631l/JxO6t9poEtrfSXWSPkdwO8u9gEVPZRTKfV5rJ/kN2utc0qpUxT9qqiUagNMvcDNtGJa6/ux/uNQSl2NdSrzhFLq/wZ+x77sv2itf7lEmzzAvcAo82w0v1zL7eMiz38K68Zh3mbsM/aUUncBr7Qff/di11aCE/uolAoDPwZ+rrX+29XQpzytdUYp9RWs0eJnl9s3B/fxVcClSqnbsLKnRSl1ArhUaz1R7/2zy2ED9r8H7MkArwT+aaE+VGwErJT6NHAF8Ha7YWDdMQwppa63374deKDEz9dp/x0E/h+sG01orT9dVPBeKnzdwL9i3aj6Xa31Oe3Fudw+LvH8PwWusmtksz5Oa/3Roj7qxa4tNyf20f4a+BHwG631X66SPm2yb/Dkn+8dwIvL7ZuT+6i1fqvWerPWeivWgQyjWuutKwxfx/VPK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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="c1"># Diagnostic Tests</span>

<span class="c1"># Augmented Dickey-Fuller: Stationarity (Unit Root)</span>
<span class="k">def</span> <span class="nf">adf</span><span class="p">(</span><span class="n">timeseries</span><span class="p">,</span> <span class="n">title</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="mf">0.01</span><span class="p">):</span>
    <span class="n">result</span> <span class="o">=</span> <span class="kc">False</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Results of Dickey-Fuller Test for: &#39;</span> <span class="o">+</span> <span class="n">title</span><span class="p">)</span>
    <span class="n">dftest</span> <span class="o">=</span> <span class="n">sm</span><span class="o">.</span><span class="n">tsa</span><span class="o">.</span><span class="n">stattools</span><span class="o">.</span><span class="n">adfuller</span><span class="p">(</span><span class="n">timeseries</span><span class="p">,</span> <span class="n">autolag</span><span class="o">=</span><span class="s1">&#39;AIC&#39;</span><span class="p">)</span>
    
    <span class="n">pvalue</span> <span class="o">=</span> <span class="n">dftest</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
    <span class="k">if</span> <span class="n">pvalue</span> <span class="o">&lt;</span> <span class="n">cutoff</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;p-value = </span><span class="si">%.6f</span><span class="s1">. The series is likely stationary.&#39;</span> <span class="o">%</span> <span class="n">pvalue</span><span class="p">)</span>
        <span class="n">result</span> <span class="o">=</span> <span class="kc">True</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;p-value = </span><span class="si">%.6f</span><span class="s1">. The series is likely non-stationary.&#39;</span> <span class="o">%</span> <span class="n">pvalue</span><span class="p">)</span>

    <span class="n">dfoutput</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="n">dftest</span><span class="p">[</span><span class="mi">0</span><span class="p">:</span><span class="mi">4</span><span class="p">],</span> <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Test Statistic&#39;</span><span class="p">,</span><span class="s1">&#39;p-value&#39;</span><span class="p">,</span><span class="s1">&#39;#Lags Used&#39;</span><span class="p">,</span><span class="s1">&#39;Number of Observations Used&#39;</span><span class="p">])</span>
    <span class="k">for</span> <span class="n">key</span><span class="p">,</span><span class="n">value</span> <span class="ow">in</span> <span class="n">dftest</span><span class="p">[</span><span class="mi">4</span><span class="p">]</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
        <span class="n">dfoutput</span><span class="p">[</span><span class="s1">&#39;Critical Value (</span><span class="si">%s</span><span class="s1">)&#39;</span><span class="o">%</span><span class="k">key</span>] = value
    <span class="nb">print</span><span class="p">(</span><span class="n">dfoutput</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">()</span>
    
    <span class="k">return</span> <span class="n">result</span>

<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">resultsdb</span><span class="o">.</span><span class="n">values</span><span class="p">():</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">v</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot;: </span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">data</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span>
        <span class="n">title</span> <span class="o">=</span> <span class="s2">&quot; - &quot;</span><span class="o">.</span><span class="n">join</span><span class="p">((</span><span class="n">v</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">col</span><span class="p">))</span>
        <span class="n">adf</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">col</span><span class="p">],</span> <span class="n">title</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">()</span>
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<pre>Full Timeframe: 

Results of Dickey-Fuller Test for: Full Timeframe - SPX
p-value = 0.000000. The series is likely stationary.
Test Statistic                -1.003840e+01
p-value                        1.519034e-17
#Lags Used                     2.900000e+01
Number of Observations Used    3.097000e+03
Critical Value (1%)           -3.432463e+00
Critical Value (5%)           -2.862474e+00
Critical Value (10%)          -2.567267e+00
dtype: float64


Results of Dickey-Fuller Test for: Full Timeframe - VIX
p-value = 0.000136. The series is likely stationary.
Test Statistic                   -4.588621
p-value                           0.000136
#Lags Used                       12.000000
Number of Observations Used    3114.000000
Critical Value (1%)              -3.432452
Critical Value (5%)              -2.862469
Critical Value (10%)             -2.567264
dtype: float64


Results of Dickey-Fuller Test for: Full Timeframe - SSE
p-value = 0.000000. The series is likely stationary.
Test Statistic                  -20.690108
p-value                           0.000000
#Lags Used                        6.000000
Number of Observations Used    3120.000000
Critical Value (1%)              -3.432448
Critical Value (5%)              -2.862467
Critical Value (10%)             -2.567263
dtype: float64


Results of Dickey-Fuller Test for: Full Timeframe - CNY
p-value = 0.000000. The series is likely stationary.
Test Statistic                -8.693642e+00
p-value                        3.978517e-14
#Lags Used                     2.400000e+01
Number of Observations Used    3.102000e+03
Critical Value (1%)           -3.432460e+00
Critical Value (5%)           -2.862472e+00
Critical Value (10%)          -2.567266e+00
dtype: float64


COVID-19 Recession: 

Results of Dickey-Fuller Test for: COVID-19 Recession - SPX
p-value = 0.090549. The series is likely non-stationary.
Test Statistic                 -2.611965
p-value                         0.090549
#Lags Used                      6.000000
Number of Observations Used    89.000000
Critical Value (1%)            -3.506057
Critical Value (5%)            -2.894607
Critical Value (10%)           -2.584410
dtype: float64


Results of Dickey-Fuller Test for: COVID-19 Recession - VIX
p-value = 0.536593. The series is likely non-stationary.
Test Statistic                 -1.493765
p-value                         0.536593
#Lags Used                      3.000000
Number of Observations Used    92.000000
Critical Value (1%)            -3.503515
Critical Value (5%)            -2.893508
Critical Value (10%)           -2.583824
dtype: float64


Results of Dickey-Fuller Test for: COVID-19 Recession - SSE
p-value = 0.000000. The series is likely stationary.
Test Statistic                -9.882943e+00
p-value                        3.728173e-17
#Lags Used                     0.000000e+00
Number of Observations Used    9.500000e+01
Critical Value (1%)           -3.501137e+00
Critical Value (5%)           -2.892480e+00
Critical Value (10%)          -2.583275e+00
dtype: float64


Results of Dickey-Fuller Test for: COVID-19 Recession - CNY
p-value = 0.000000. The series is likely stationary.
Test Statistic                -1.079802e+01
p-value                        2.051714e-19
#Lags Used                     0.000000e+00
Number of Observations Used    9.500000e+01
Critical Value (1%)           -3.501137e+00
Critical Value (5%)           -2.892480e+00
Critical Value (10%)          -2.583275e+00
dtype: float64


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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Apply second-order differencing to non-stationary dataset</span>
<span class="k">def</span> <span class="nf">getSecondOrderLogReturns</span><span class="p">(</span><span class="n">quotes</span><span class="p">):</span>
    <span class="k">return</span> <span class="p">[</span><span class="mi">100</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">((</span><span class="n">quotes</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">/</span> <span class="n">quotes</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span> <span class="o">/</span> <span class="p">(</span><span class="n">quotes</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">/</span> <span class="n">quotes</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">2</span><span class="p">]))</span>
           <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">quotes</span><span class="p">))]</span>

<span class="c1">#df.loc[&quot;2019-11-25&quot;:&quot;2019-12-01&quot;].head()</span>
<span class="n">COVID_df</span> <span class="o">=</span> <span class="n">resultsdb</span><span class="p">[</span><span class="s2">&quot;CR&quot;</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span>
<span class="n">COVID_df</span><span class="p">[</span><span class="s2">&quot;SPX&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">getSecondOrderLogReturns</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="s2">&quot;2019-11-27&quot;</span><span class="p">:,</span><span class="s2">&quot;SPX&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span>
<span class="n">adf</span><span class="p">(</span><span class="n">COVID_df</span><span class="p">[</span><span class="s2">&quot;SPX&quot;</span><span class="p">],</span> <span class="s2">&quot;COVID-SPX&quot;</span><span class="p">)</span>
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<pre>Results of Dickey-Fuller Test for: COVID-SPX
p-value = 0.000000. The series is likely stationary.
Test Statistic                -6.011769e+00
p-value                        1.567317e-07
#Lags Used                     7.000000e+00
Number of Observations Used    8.800000e+01
Critical Value (1%)           -3.506944e+00
Critical Value (5%)           -2.894990e+00
Critical Value (10%)          -2.584615e+00
dtype: float64

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<pre>True</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Find ARIMA(p,1,q) models for log-return series that minimize AIC</span>
<span class="c1"># where p,q &lt;= 5 and excluding ARIMA(0,1,0)</span>
<span class="kn">import</span> <span class="nn">statsmodels.tsa.arima_model</span> <span class="k">as</span> <span class="nn">arima</span>

<span class="k">def</span> <span class="nf">fit_ARIMA</span><span class="p">(</span><span class="n">timeseries</span><span class="p">,</span> <span class="n">d</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
    <span class="n">min_aic</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">**</span> <span class="mi">32</span>
    <span class="n">pdq</span> <span class="o">=</span> <span class="p">(</span><span class="mi">6</span><span class="p">,</span><span class="n">d</span><span class="p">,</span><span class="mi">6</span><span class="p">)</span>
    <span class="n">results</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Approximating model fitting to save time...&quot;</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">6</span><span class="p">):</span>
        <span class="k">for</span> <span class="n">q</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">6</span><span class="p">):</span>
            <span class="k">if</span> <span class="n">p</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">q</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
                <span class="k">try</span><span class="p">:</span>
                    <span class="n">model</span> <span class="o">=</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMA</span><span class="p">(</span><span class="n">timeseries</span><span class="p">,</span> <span class="p">(</span><span class="n">p</span><span class="p">,</span><span class="n">d</span><span class="p">,</span><span class="n">q</span><span class="p">))</span>
                    <span class="n">fitted</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">transparams</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
                                       <span class="n">method</span><span class="o">=</span><span class="s2">&quot;css&quot;</span><span class="p">,</span>
                                       <span class="n">trend</span><span class="o">=</span><span class="s2">&quot;nc&quot;</span><span class="p">,</span>
                                       <span class="n">maxiter</span><span class="o">=</span><span class="mi">50</span><span class="p">)</span>
                    <span class="n">aic</span> <span class="o">=</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMAResults</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">fitted</span><span class="o">.</span><span class="n">params</span><span class="p">)</span><span class="o">.</span><span class="n">aic</span>
                    <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
                        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;ARIMA(&quot;</span> <span class="o">+</span> <span class="s2">&quot;,&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">((</span><span class="nb">str</span><span class="p">(</span><span class="n">p</span><span class="p">),</span><span class="nb">str</span><span class="p">(</span><span class="n">d</span><span class="p">),</span><span class="nb">str</span><span class="p">(</span><span class="n">q</span><span class="p">)))</span> <span class="o">+</span> <span class="s2">&quot;) - AIC: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">aic</span><span class="p">))</span>                    
                    <span class="n">results</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">aic</span><span class="p">,</span> <span class="p">(</span><span class="n">p</span><span class="p">,</span><span class="n">d</span><span class="p">,</span><span class="n">q</span><span class="p">)])</span>
                <span class="k">except</span> <span class="ne">ValueError</span><span class="p">:</span>
                    <span class="k">continue</span>

    <span class="n">results</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
    <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Refitting best model without approximation...&quot;</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">result</span> <span class="ow">in</span> <span class="n">results</span><span class="p">:</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="n">p</span><span class="p">,</span><span class="n">d</span><span class="p">,</span><span class="n">q</span> <span class="o">=</span> <span class="n">result</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
            <span class="n">model</span> <span class="o">=</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMA</span><span class="p">(</span><span class="n">timeseries</span><span class="p">,</span> <span class="p">(</span><span class="n">p</span><span class="p">,</span><span class="n">d</span><span class="p">,</span><span class="n">q</span><span class="p">))</span>
            <span class="n">fitted</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">transparams</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
            <span class="n">residuals</span> <span class="o">=</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMAResults</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">fitted</span><span class="o">.</span><span class="n">params</span><span class="p">)</span><span class="o">.</span><span class="n">resid</span>
            <span class="n">aic</span> <span class="o">=</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMAResults</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">fitted</span><span class="o">.</span><span class="n">params</span><span class="p">)</span><span class="o">.</span><span class="n">aic</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;ARIMA(&quot;</span> <span class="o">+</span> <span class="s2">&quot;,&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">((</span><span class="nb">str</span><span class="p">(</span><span class="n">p</span><span class="p">),</span><span class="nb">str</span><span class="p">(</span><span class="n">d</span><span class="p">),</span><span class="nb">str</span><span class="p">(</span><span class="n">q</span><span class="p">)))</span> <span class="o">+</span> <span class="s2">&quot;) - AIC: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">aic</span><span class="p">))</span>
            <span class="k">return</span> <span class="p">((</span><span class="n">p</span><span class="p">,</span><span class="n">d</span><span class="p">,</span><span class="n">q</span><span class="p">),</span> <span class="n">model</span><span class="p">,</span> <span class="n">fitted</span><span class="p">,</span> <span class="n">residuals</span><span class="p">)</span>
        <span class="k">except</span> <span class="ne">ValueError</span><span class="p">:</span>
            <span class="k">continue</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">resultsdb</span><span class="o">.</span><span class="n">values</span><span class="p">():</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
    <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
        <span class="n">v</span><span class="o">.</span><span class="n">append</span><span class="p">({})</span>
    <span class="n">ARIMA</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
    <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">COLS_EXCL_VIX</span><span class="p">:</span>
        <span class="n">title</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; - &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">col</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="n">title</span><span class="p">)</span>
        <span class="k">if</span> <span class="n">v</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">==</span> <span class="s2">&quot;COVID-19 Recession&quot;</span> <span class="ow">and</span> <span class="n">col</span> <span class="o">==</span> <span class="s2">&quot;SPX&quot;</span><span class="p">:</span>
            <span class="n">ARIMA</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">fit_ARIMA</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">col</span><span class="p">],</span> <span class="n">d</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span> 
            <span class="n">ARIMA</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">fit_ARIMA</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">col</span><span class="p">],</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
        <span class="n">p</span><span class="p">,</span><span class="n">d</span><span class="p">,</span><span class="n">q</span> <span class="o">=</span> <span class="n">ARIMA</span><span class="p">[</span><span class="n">col</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
        <span class="nb">print</span><span class="p">(</span><span class="n">title</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Best Model: ARIMA(&quot;</span> <span class="o">+</span> <span class="s2">&quot;,&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">((</span><span class="nb">str</span><span class="p">(</span><span class="n">p</span><span class="p">),</span><span class="nb">str</span><span class="p">(</span><span class="n">d</span><span class="p">),</span><span class="nb">str</span><span class="p">(</span><span class="n">q</span><span class="p">)))</span> <span class="o">+</span> <span class="s2">&quot;)</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
    
    <span class="n">summary</span> <span class="o">=</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMAResults</span><span class="p">(</span><span class="n">ARIMA</span><span class="p">[</span><span class="n">col</span><span class="p">][</span><span class="mi">1</span><span class="p">],</span> <span class="n">ARIMA</span><span class="p">[</span><span class="n">col</span><span class="p">][</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">params</span><span class="p">)</span><span class="o">.</span><span class="n">summary</span><span class="p">()</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">summary</span><span class="p">)</span>
</pre></div>

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<pre>Full Timeframe - SPX
Approximating model fitting to save time...
ARIMA(0,1,1) - AIC: 11749.930355829167
ARIMA(0,1,2) - AIC: 11567.663751077278
ARIMA(0,1,3) - AIC: 11514.839055718472
ARIMA(0,1,4) - AIC: 11363.052595944382
ARIMA(0,1,5) - AIC: 11273.546717075522
ARIMA(1,1,0) - AIC: 12173.969068524175
ARIMA(1,1,1) - AIC: 10845.549752623167
ARIMA(1,1,2) - AIC: 10778.651008568477
ARIMA(1,1,3) - AIC: 10840.722701216633
ARIMA(1,1,4) - AIC: 10770.844434678547
ARIMA(2,1,0) - AIC: 11674.187177830709
ARIMA(2,1,1) - AIC: 10947.939247631915
ARIMA(2,1,2) - AIC: 10863.000051320236
ARIMA(2,1,3) - AIC: 10790.875458941477
ARIMA(2,1,4) - AIC: 10803.937166813052
ARIMA(2,1,5) - AIC: 10777.28216313549
ARIMA(3,1,0) - AIC: 11483.930890167936
ARIMA(3,1,1) - AIC: 10938.176087141996
ARIMA(3,1,2) - AIC: 10853.182544304942
ARIMA(3,1,3) - AIC: 10812.94749739814
ARIMA(3,1,4) - AIC: 10786.970502321403
ARIMA(3,1,5) - AIC: 10799.970704368643
ARIMA(4,1,0) - AIC: 11377.680353976686
ARIMA(4,1,1) - AIC: 10951.0800046722
ARIMA(4,1,2) - AIC: 10839.864373949174
ARIMA(4,1,3) - AIC: 10797.28020079763
ARIMA(4,1,4) - AIC: 10800.80808880263
ARIMA(4,1,5) - AIC: 10790.18290991058
ARIMA(5,1,0) - AIC: 11295.17030490211
ARIMA(5,1,1) - AIC: 10959.954669199215
ARIMA(5,1,2) - AIC: 10852.319289718107
ARIMA(5,1,3) - AIC: 10785.7652638736
ARIMA(5,1,4) - AIC: 10783.00935155667
ARIMA(5,1,5) - AIC: 10783.660728149518
Refitting best model without approximation...
ARIMA(1,1,4) - AIC: 10758.198192546315
Full Timeframe - SPX
Best Model: ARIMA(1,1,4)

Full Timeframe - SSE
Approximating model fitting to save time...
ARIMA(0,1,1) - AIC: 13048.354529023858
ARIMA(0,1,2) - AIC: 12854.293516758573
ARIMA(0,1,3) - AIC: 12729.897795401514
ARIMA(0,1,4) - AIC: 12792.105897801455
ARIMA(0,1,5) - AIC: 12598.185720794956
ARIMA(1,1,0) - AIC: 13425.710583403781
ARIMA(1,1,1) - AIC: 12240.184921713499
ARIMA(1,1,2) - AIC: 12217.496565325078
ARIMA(1,1,3) - AIC: 12243.725013263349
ARIMA(1,1,4) - AIC: 12276.001589235706
ARIMA(1,1,5) - AIC: 12167.982435061538
ARIMA(2,1,0) - AIC: 13005.189035617846
ARIMA(2,1,1) - AIC: 12291.68646729945
ARIMA(2,1,2) - AIC: 12269.438135623755
ARIMA(2,1,3) - AIC: 12235.70168514302
ARIMA(2,1,4) - AIC: 12259.868352700958
ARIMA(2,1,5) - AIC: 12191.973357498264
ARIMA(3,1,0) - AIC: 12741.968491802483
ARIMA(3,1,1) - AIC: 12322.616785316886
ARIMA(3,1,2) - AIC: 12289.886629863337
ARIMA(3,1,3) - AIC: 12258.794592679495
ARIMA(3,1,4) - AIC: 12226.56775958633
ARIMA(3,1,5) - AIC: 12192.37688068479
ARIMA(4,1,0) - AIC: 12679.850141504729
ARIMA(4,1,1) - AIC: 12196.580403307791
ARIMA(4,1,2) - AIC: 12196.995690643858
ARIMA(4,1,3) - AIC: 12175.114551467388
ARIMA(4,1,4) - AIC: 12186.594367798509
ARIMA(4,1,5) - AIC: 12185.60211431534
ARIMA(5,1,0) - AIC: 12611.258919001144
ARIMA(5,1,1) - AIC: 12249.232927276098
ARIMA(5,1,2) - AIC: 12218.510698655042
ARIMA(5,1,3) - AIC: 12174.974489862365
ARIMA(5,1,4) - AIC: 12174.988293055208
ARIMA(5,1,5) - AIC: 12172.229252496123
Refitting best model without approximation...
ARIMA(1,1,5) - AIC: 12169.557534309832
Full Timeframe - SSE
Best Model: ARIMA(1,1,5)

Full Timeframe - CNY
Approximating model fitting to save time...
ARIMA(0,1,1) - AIC: -29.13573675333828
ARIMA(0,1,2) - AIC: -206.52548076525773
ARIMA(0,1,3) - AIC: -371.4381182408606
ARIMA(0,1,4) - AIC: -499.5858414269346
ARIMA(0,1,5) - AIC: -484.5723642095395
ARIMA(1,1,0) - AIC: 410.7425329222119
ARIMA(1,1,1) - AIC: -993.2026469596458
ARIMA(1,1,3) - AIC: -984.1199967204666
ARIMA(1,1,4) - AIC: -978.2931294556129
ARIMA(1,1,5) - AIC: -964.0756003582028
ARIMA(2,1,0) - AIC: -53.85230670134297
ARIMA(2,1,1) - AIC: -963.478153585922
ARIMA(2,1,2) - AIC: -990.851344364708
ARIMA(2,1,3) - AIC: -990.2270026319829
ARIMA(2,1,4) - AIC: -976.6396762590339
ARIMA(2,1,5) - AIC: -961.8864251986461
ARIMA(3,1,0) - AIC: -301.0374075420541
ARIMA(3,1,1) - AIC: -940.1179932359623
ARIMA(3,1,2) - AIC: -971.9734353448985
ARIMA(3,1,3) - AIC: -974.7453831649482
ARIMA(3,1,4) - AIC: -977.2645130643805
ARIMA(3,1,5) - AIC: -970.1053513393567
ARIMA(4,1,0) - AIC: -489.5427088080846
ARIMA(4,1,1) - AIC: -886.445363256255
ARIMA(4,1,2) - AIC: -947.5900990771224
ARIMA(4,1,3) - AIC: -955.2473210088333
ARIMA(4,1,4) - AIC: -976.4885335347017
ARIMA(4,1,5) - AIC: -979.5448719116303
ARIMA(5,1,0) - AIC: -552.3145348592652
ARIMA(5,1,1) - AIC: -945.9725836487696
ARIMA(5,1,2) - AIC: -972.2018515217806
ARIMA(5,1,3) - AIC: -968.6237081054169
ARIMA(5,1,4) - AIC: -977.610171230469
ARIMA(5,1,5) - AIC: -976.2338505088715
Refitting best model without approximation...
ARIMA(1,1,1) - AIC: -1003.5401487642739
Full Timeframe - CNY
Best Model: ARIMA(1,1,1)

                             ARIMA Model Results                              
==============================================================================
Dep. Variable:                  D.CNY   No. Observations:                 3126
Model:                    ARIMA(1, 1)   Log Likelihood                 505.770
Method:                       css-mle   S.D. of innovations              0.206
Date:                Sat, 23 May 2020   AIC                          -1003.540
Time:                        05:33:02   BIC                           -979.350
Sample:                             0   HQIC                          -994.857
                                                                              
===============================================================================
                  coef    std err          z      P&gt;|z|      [0.025      0.975]
-------------------------------------------------------------------------------
const       -1.374e-05   3.63e-06     -3.783      0.000   -2.09e-05   -6.62e-06
ar.L1.D.CNY    -0.1216      0.018     -6.851      0.000      -0.156      -0.087
ma.L1.D.CNY    -1.0000      0.001   -975.481      0.000      -1.002      -0.998
                                    Roots                                    
=============================================================================
                  Real          Imaginary           Modulus         Frequency
-----------------------------------------------------------------------------
AR.1           -8.2227           +0.0000j            8.2227            0.5000
MA.1            1.0000           +0.0000j            1.0000            0.0000
-----------------------------------------------------------------------------
COVID-19 Recession - SPX
Approximating model fitting to save time...
ARIMA(0,2,1) - AIC: 702.2275385887779
ARIMA(1,2,0) - AIC: 698.3855337436279
ARIMA(2,2,0) - AIC: 608.8200158343711
ARIMA(2,2,3) - AIC: 495.86513896282014
ARIMA(3,2,0) - AIC: 582.2799030010531
ARIMA(4,2,1) - AIC: 505.387192273352
Refitting best model without approximation...
ARIMA(2,2,3) - AIC: 509.51875670318844
COVID-19 Recession - SPX
Best Model: ARIMA(2,2,3)

COVID-19 Recession - SSE
Approximating model fitting to save time...
ARIMA(0,1,1) - AIC: 351.20128860037755
ARIMA(0,1,2) - AIC: 353.17923858313753
ARIMA(0,1,3) - AIC: 354.75355390468417
ARIMA(0,1,4) - AIC: 356.5167803806821
ARIMA(0,1,5) - AIC: 350.1952566686148
ARIMA(1,1,0) - AIC: 383.55488038383845
ARIMA(1,1,1) - AIC: 352.0694241935647
ARIMA(1,1,2) - AIC: 346.12846447683467
ARIMA(1,1,3) - AIC: 348.24209735649737
ARIMA(2,1,0) - AIC: 370.063646528214
ARIMA(2,1,1) - AIC: 350.4994830615223
ARIMA(3,1,0) - AIC: 367.75832433888826
ARIMA(3,1,1) - AIC: 352.6320239249319
ARIMA(3,1,2) - AIC: 350.8264568135313
ARIMA(4,1,0) - AIC: 361.7281812927287
ARIMA(4,1,1) - AIC: 348.48309641874084
ARIMA(4,1,2) - AIC: 334.6230784034026
ARIMA(5,1,0) - AIC: 355.79532895220757
ARIMA(5,1,1) - AIC: 333.88749654055965
ARIMA(5,1,2) - AIC: 334.72764073255837
ARIMA(5,1,3) - AIC: 335.8066613798002
Refitting best model without approximation...
ARIMA(5,1,1) - AIC: 364.6105897315973
COVID-19 Recession - SSE
Best Model: ARIMA(5,1,1)

COVID-19 Recession - CNY
Approximating model fitting to save time...
ARIMA(0,1,1) - AIC: 61.8423647479326
ARIMA(0,1,2) - AIC: 62.805232421211414
ARIMA(0,1,3) - AIC: 64.79015051315758
ARIMA(0,1,4) - AIC: 66.78886798354763
ARIMA(0,1,5) - AIC: 66.52381230483124
ARIMA(1,1,0) - AIC: 100.95309994629721
ARIMA(1,1,1) - AIC: 65.04968116043507
ARIMA(1,1,2) - AIC: 64.93717661439098
ARIMA(1,1,3) - AIC: 56.82570193397082
ARIMA(1,1,4) - AIC: 68.79203696762332
ARIMA(2,1,0) - AIC: 91.01400085161377
ARIMA(2,1,1) - AIC: 75.17600539275571
ARIMA(2,1,2) - AIC: 72.7061498780293
ARIMA(2,1,3) - AIC: 40.23815710355153
ARIMA(2,1,4) - AIC: 44.67707628881007
ARIMA(2,1,5) - AIC: 53.39382277818554
ARIMA(3,1,0) - AIC: 80.27619872803231
ARIMA(3,1,1) - AIC: 68.00263286776112
ARIMA(3,1,2) - AIC: 55.017790629922324
ARIMA(3,1,3) - AIC: 45.02582134715941
ARIMA(3,1,4) - AIC: 58.67187880834588
ARIMA(4,1,0) - AIC: 79.20229102336008
ARIMA(4,1,1) - AIC: 54.11074220677971
ARIMA(4,1,2) - AIC: 56.83777111930435
ARIMA(4,1,3) - AIC: 59.46247332556818
ARIMA(4,1,4) - AIC: 60.734089714793164
ARIMA(5,1,0) - AIC: 80.55854986870862
ARIMA(5,1,1) - AIC: 72.3839406920231
ARIMA(5,1,2) - AIC: 67.69047302121399
ARIMA(5,1,4) - AIC: 60.76539446743671
Refitting best model without approximation...
ARIMA(2,1,3) - AIC: 72.41321131046692
COVID-19 Recession - CNY
Best Model: ARIMA(2,1,3)

                             ARIMA Model Results                              
==============================================================================
Dep. Variable:                  D.CNY   No. Observations:                   95
Model:                    ARIMA(2, 3)   Log Likelihood                 -29.207
Method:                       css-mle   S.D. of innovations              0.318
Date:                Sat, 23 May 2020   AIC                             72.413
Time:                        05:33:24   BIC                             90.290
Sample:                             0   HQIC                            79.637
                                                                              
===============================================================================
                  coef    std err          z      P&gt;|z|      [0.025      0.975]
-------------------------------------------------------------------------------
const          -0.0008      0.001     -0.686      0.493      -0.003       0.002
ar.L1.D.CNY    -0.6477      0.147     -4.400      0.000      -0.936      -0.359
ar.L2.D.CNY    -0.9421      0.054    -17.306      0.000      -1.049      -0.835
ma.L1.D.CNY    -0.3082      0.122     -2.520      0.012      -0.548      -0.068
ma.L2.D.CNY     0.3082      0.126      2.443      0.015       0.061       0.555
ma.L3.D.CNY    -1.0000      0.073    -13.661      0.000      -1.143      -0.857
                                    Roots                                    
=============================================================================
                  Real          Imaginary           Modulus         Frequency
-----------------------------------------------------------------------------
AR.1           -0.3437           -0.9712j            1.0303           -0.3041
AR.2           -0.3437           +0.9712j            1.0303            0.3041
MA.1            1.0000           -0.0000j            1.0000           -0.0000
MA.2           -0.3459           -0.9383j            1.0000           -0.3062
MA.3           -0.3459           +0.9383j            1.0000            0.3062
-----------------------------------------------------------------------------
</pre>
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<div class="prompt input_prompt">In&nbsp;[10]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Quickly populate resultsdb with known values from above cell</span>

<span class="c1"># def fit_arima(timeseries, pdq_tuple):</span>
<span class="c1">#     model = arima.ARIMA(timeseries, pdq_tuple)</span>
<span class="c1">#     fitted = model.fit(transparams=False)</span>
<span class="c1">#     residuals = arima.ARIMAResults(model, fitted.params).resid</span>
<span class="c1">#     return (pdq_tuple, model, fitted, residuals)</span>

<span class="c1"># pdq = [[(1,1,4),(1,1,5),(1,1,1),</span>
<span class="c1">#         (4,2,1),(5,1,1),(2,1,3)]]</span>

<span class="c1"># for i, v in enumerate(resultsdb.values()):</span>
<span class="c1">#     data = v[1]</span>
<span class="c1">#     if (len(v) == 2):</span>
<span class="c1">#         v.append({})</span>
<span class="c1">#     ARIMA = v[2]</span>
<span class="c1">#     for j, col in enumerate(COLS_EXCL_VIX):</span>
<span class="c1">#         if v[2] == {}:</span>
<span class="c1">#             ARIMA[col] = fit_arima(data[col], pdq[i][j])</span>
<span class="c1">#         summary = arima.ARIMAResults(ARIMA[col][1], ARIMA[col][2].params).summary()</span>
<span class="c1">#         print(&quot;\n&quot; + v[0] + &quot; - &quot; + col + &quot;:&quot;)</span>
<span class="c1">#         print(summary)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Jarque-Bera Test of Normality in the ARIMA-fitted residuals + QQ plots</span>
<span class="kn">from</span> <span class="nn">statsmodels.graphics.gofplots</span> <span class="k">import</span> <span class="n">qqplot</span>

<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">resultsdb</span><span class="o">.</span><span class="n">values</span><span class="p">():</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
    <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">COLS_EXCL_VIX</span><span class="p">:</span>
        <span class="n">title</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; - &quot;</span> <span class="o">+</span> <span class="n">col</span>
        <span class="n">res</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">2</span><span class="p">][</span><span class="n">col</span><span class="p">][</span><span class="mi">3</span><span class="p">]</span>
        <span class="n">result</span> <span class="o">=</span> <span class="n">sm</span><span class="o">.</span><span class="n">stats</span><span class="o">.</span><span class="n">stattools</span><span class="o">.</span><span class="n">jarque_bera</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="n">title</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;JB statistic: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span> <span class="s2">&quot;, p-value: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
             <span class="o">+</span> <span class="s2">&quot;, Skewness: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span> <span class="o">+</span> <span class="s2">&quot;, Kurtosis: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="mi">3</span><span class="p">]))</span>
        <span class="k">if</span> <span class="n">result</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mf">0.01</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">col</span> <span class="o">+</span> <span class="s2">&quot; is within the threshold for normal distribution.&quot;</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">col</span> <span class="o">+</span> <span class="s2">&quot; is non-normal.&quot;</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="n">qqplot</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">col</span><span class="p">]))</span>
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<pre>Full Timeframe - SPX
JB statistic: 26321.99838872674, p-value: 0.0, Skewness: -0.7784613884980597, Kurtosis: 17.13026082004475
SPX is within the threshold for normal distribution.
Figure(432x288)
Full Timeframe - SSE
JB statistic: 3900.9178348127566, p-value: 0.0, Skewness: -0.670277179851941, Kurtosis: 8.305881562115317
SSE is within the threshold for normal distribution.
Figure(432x288)
Full Timeframe - CNY
JB statistic: 14418.441043841709, p-value: 0.0, Skewness: -0.2366809297674625, Kurtosis: 13.510667549752903
CNY is within the threshold for normal distribution.
Figure(432x288)
COVID-19 Recession - SPX
JB statistic: 33.02975607260703, p-value: 6.72480351290286e-08, Skewness: 0.6089636467507317, Kurtosis: 5.636243979181655
SPX is within the threshold for normal distribution.
Figure(432x288)
COVID-19 Recession - SSE
JB statistic: 280.14620535656053, p-value: 1.4690089567623833e-61, Skewness: -1.766356498578403, Kurtosis: 10.635032224886872
SSE is within the threshold for normal distribution.
Figure(432x288)
COVID-19 Recession - CNY
JB statistic: 19.10228166462337, p-value: 7.112008068191216e-05, Skewness: -0.6099076344549264, Kurtosis: 4.826989405597512
CNY is within the threshold for normal distribution.
Figure(432x288)
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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="c1"># Box-Ljung Test of Autocorrelation in the ARIMA residuals + ACF, PACF plots.</span>
<span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">resultsdb</span><span class="o">.</span><span class="n">values</span><span class="p">():</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
    <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">COLS_EXCL_VIX</span><span class="p">:</span>
        <span class="n">title</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; - &quot;</span> <span class="o">+</span> <span class="n">col</span>
        <span class="n">p</span><span class="p">,</span><span class="n">d</span><span class="p">,</span><span class="n">q</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">2</span><span class="p">][</span><span class="n">col</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
        <span class="n">model</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">2</span><span class="p">][</span><span class="n">col</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span>
        <span class="n">fitted</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">2</span><span class="p">][</span><span class="n">col</span><span class="p">][</span><span class="mi">2</span><span class="p">]</span>
        <span class="n">res</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">2</span><span class="p">][</span><span class="n">col</span><span class="p">][</span><span class="mi">3</span><span class="p">]</span>
        <span class="n">result</span> <span class="o">=</span> <span class="n">sm</span><span class="o">.</span><span class="n">stats</span><span class="o">.</span><span class="n">diagnostic</span><span class="o">.</span><span class="n">acorr_ljungbox</span><span class="p">(</span><span class="n">res</span><span class="p">,</span> 
                                                    <span class="n">lags</span><span class="o">=</span><span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">),</span>
                                                    <span class="n">boxpierce</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> 
                                                    <span class="n">model_df</span><span class="o">=</span><span class="n">p</span><span class="o">+</span><span class="n">q</span><span class="p">,</span> 
                                                    <span class="n">return_df</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
        <span class="k">if</span> <span class="n">result</span><span class="p">[(</span><span class="n">result</span><span class="p">[</span><span class="s2">&quot;lb_pvalue&quot;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mf">0.01</span><span class="p">)</span> <span class="o">&amp;</span>
                 <span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s2">&quot;bp_pvalue&quot;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mf">0.01</span><span class="p">)]</span><span class="o">.</span><span class="n">size</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">title</span> <span class="o">+</span> <span class="s2">&quot;: ARIMA-fitted residuals exhibit autocorrelation.&quot;</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">title</span> <span class="o">+</span> <span class="s2">&quot;: No autocorrelation.&quot;</span><span class="p">)</span>

        <span class="n">sm</span><span class="o">.</span><span class="n">graphics</span><span class="o">.</span><span class="n">tsa</span><span class="o">.</span><span class="n">plot_acf</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">col</span><span class="p">],</span> <span class="n">lags</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="n">title</span> <span class="o">+</span> <span class="s2">&quot;: Autocorrelation&quot;</span><span class="p">)</span>
        <span class="n">sm</span><span class="o">.</span><span class="n">graphics</span><span class="o">.</span><span class="n">tsa</span><span class="o">.</span><span class="n">plot_pacf</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">col</span><span class="p">],</span> <span class="n">lags</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span> <span class="n">title</span><span class="o">=</span><span class="n">title</span> <span class="o">+</span> <span class="s2">&quot;: Partial Autocorrelation&quot;</span><span class="p">)</span>
</pre></div>

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<pre>Full Timeframe - SPX: No autocorrelation.
Full Timeframe - SSE: No autocorrelation.
Full Timeframe - CNY: No autocorrelation.
COVID-19 Recession - SPX: No autocorrelation.
COVID-19 Recession - SSE: No autocorrelation.
COVID-19 Recession - CNY: No autocorrelation.
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oFIpBFtAidZeOH2b6IXVIjUxIKePnp6N7B1YJA0sHVgkJ7eDSzo6Wt0aCJNo973CVxNePHGgJm9DbjTzF4dvTikJJ2dOV8fW7Kuro6K5q+FZowJmjOukcTU191L/8DQrtH9A4Os3dRf9e822rdVPSmu0tUjpromgegNRJm/fxu9TPogwtumStLXt6nsGyi6ujpYvXpj8QnrqBljguaMa6QxdY5rp72tha1ZiaC9rYWJ49qr+t12hW1VL4qrdNWKKZlMFLx4rmt1UPRezszf8wg9ibyeMUh8zJ3dyeyp4yE1AOk0Y6I2gbmzOxsdmkjTqFoSMLPvmNlyYB/gXjN7Khp+j5kdHk12mZk9aWZ/IbzX9NTs0oFINSWTCc47cR6svB/6HufM9xyoRmGRYarZO+gc4Jwcw9+Z9ffp1VqfSCmSyQSJl5bDS8uZN2evRocj0nR0x7CISIwpCYiIxJiSgIhIjCkJiIjEmJKAiEiMKQmIiMSYkoCISIwpCYiIxJiSgIhIjCkJiIjEmJKAiEiMKQmIiMSYkoCISIwpCYiIxJiSgIhIjFXtfQJm9i3gOMLbwg529ydzTNMCfAf4OyANXO7u11UrBhERGZlqlgTuAN4ILCkwzYeAOcB+wJHARWY2q4ox5JRKpeleuIaf/NbpXrim7HcUi4jsaqr5ZrEHAcys0GQnAte6ewpYbWZ3AMcD36xWHMOlUmmuuKWbnt4N9A8M0h69Z1avGRQRqX+bwAyGlhSWAtNrucIFPX309G5g68AgaWDrwCA9vRtY0NNXy9WKiIwKVSsJ1Etn57gRTd/X3Uv/wOCQYf0Dg6zd1E9XV0c1Qytbs8QxXDPGVU5M7e2tZc9bql1lW9WD4ipdPWKqdxJYCswEHo0+Dy8ZFNXXt2lEdfqd49ppb2tha1YiaG9rYeK4dlav3jiSVddEV1dHU8QxXDPGVW5M/f3bAGr2fXalbVVriqt01YopmUwUvHiud3XQbcDHzSxpZl3Ae4Hba7nCubM7mT11PKQGIJ1mTNQmMHd2Zy1XKyIyKlQtCZjZd8xsObAPcK+ZPRUNv8fMDo8muxHoAZ4DHgEucfeeasWQSzKZ4LwT58HK+2lZ/xfOfM+BahQWEYlUs3fQOcA5OYa/M+vvQeCT1VpnqZLJBImXltM6sJJ5c/aq9+pFRJqW7hgWEYkxJQERkRhTEhARiTElARGRGFMSEBGJMSUBEZEYUxIQEYkxJQERkRhTEhARiTElARGRGBt1j5IWqaZUKs2Cnj6WrtrIjMkdzJ3dqedKSawoCUhs6a1zIqoOkhjTW+dElAQkxpau2pjzrXPLVjXXy0VEaklJQGJrxuQO2ttahgxrb2th+uTme82gSK0oCUhs6a1zIlVsGDaz/YHrgU6gDzjN3Z8bNs1FwKeA3mjQH9z909WKQWQkMm+dO+PcC6C9kzPP+vCIegdlehb1dffSOa5dPYtkVKpm76Crgavc/SYzOwW4BnhLjulucPfzq7hekbJl3jrHS8tH9NY59SySXUVVqoPMbBIwH7g5GnQzMD96mbzILqdYz6JUKk33wjXc9YdFdC9cQyqVbmzAInlUqyQwHXg+eocw7j5oZr3R8NXDpj3JzN4OrAQudPeHR7Kizs5xZQXY3h6+aldX8zX6NWNM0JxxlRNTsd++nH2jr7s3Z8+itZv6mdg5jgv/4yF8yTq29g8ypr0Fm7knF3/iKFrqWEpoxt8PFNdI1COmet8sdjVwqbsPmNnbgDvN7NXuXnLH7L6+TWVdVfX3b6O9vZXVq5ur+19XV0fTxQTNGVe5MfX3bwPIO2+x8bl0jmunva2FrVmJoL2thYnj2rnvj4t5ZvG67eO29A/yzOJ13PfHxSOqcqpEM/5+oLgySrlTvVoxJZOJghfP1eodtAyYZmYtANH/U6Ph27n7SncfiP7+bTT+oCrFIFI3hXoW6f4DKSTTnnTNnU9x5wOLuObOp7jilu6GVRlWJQm4+wtAN3ByNOhk4HF3H1IVZGbTsv6eB8wCvBoxiNRTpmcRK++nZf1fOPM9B25vFNb9B1JIs92pXs37BM4CzjazZ4Gzo8+Y2T1mdng0zWVm9qSZ/QW4FjjV3VdWMQaRusn0LGpd/wTz5uy1vTiv+w+kkGYrKVatTcDdnwFek2P4O7P+Pr1a6xNpVpXefyC7tkxJcXh7UqNKinqKqEgNlHv/gez6MiXFvy56ARKtjGlvHVJSrPdNiEoCIiJ1VKik2IibEPXsIBGROsuUFBPr/jKkPakRjcZKAiIiTaIRjcZKAiIiTaIR3YuVBEREmkQjuhcrCYiINIlCNyHWinoHiYwypTx3Rkav7TchDqysS/diJQGRUUTvMZBqi20SGEylh9yx1yhrN2zh5a3bGh3GTpoxrnJjSqXDg7nyzZtvfCqV5qnFa1n+wib2mTSOA2dN3OlEm0qnGdiWyrnsYustxxM9ffT0rmfrQArIdCFcz6P+Agdn1Rs34+8Hiitbof0j1341pq2lJo8ij20S2DowyNKVjX+q4x5bBnnxxZcbHcZOmjGucmPa0h+Sfb7fO9f4VCrNrfcvZEXfywxsS9HWmmRK5+6ccPScIYlgS/8gra25l11ovalUmp4VG3hh3WYm7bkbs6eML+lK/qmetdsTQMbWgRRP9axlwu7t24c14+8Hiitbof0j1341Y+8Odh9T/VN2bJOASCE9KzZsTwAAA9tSrOh7mZ4VG5gzbUJFyy41weQyac/daGtNbo8LoK01yaQ9d9u+7J4VG9iwsI/xu7WWnFwkvpQERHJ4Yd3mISdaCInghXWbK04ClSSY2VPGM6Vzd5b0roNkK+1tLUzp3J3ZU8aXlFzKLYHIrktdREVyyFxxZ8u+4q5EoQRTTDKZ4ISj59C//D62vfBnjj1q1vaTfKHkAjtKIHc/tJgHn1jB3Q8t5tb7F+r9xzGnJCCSQ+aKOz04QDqd3n5VPXvK+IqXXWmCSSYTpDYuZdvqx5kzbcL2K/liyaVYkpDqSaXSLHx+PQ89uZKFz69v6kRbteogM9sfuB7oBPqA09z9uWHTtADfAf4OSAOXu/t11YpBpFoyV9yXfuPrJMd2ctzxJ1St6qRQlU4lirUX1LKKS3aopM2nEapZErgauMrd9weuAq7JMc2HgDnAfsCRwEVmNquKMcTCaLrKGM3yXXFXY7n5qnQqUaz0UssqLtlhtJW4qpIEzGwSMB+4ORp0MzDfzLqGTXoicK27p6L3D98BHF+NGEabzIn8vj8tG9GJXPW6u4ZaJJjs5JJa89hOyaWWVVyj9cKk3OOwkErafBohkU5X/qXN7DDgBnc/MGvY08Ap7v5Y1rAngI+6+6PR5y8A+7j7OSWsZhaw6NIfPMK6DVtHHKP7X0kkE+y/36sAGEyn2drfmJvF0uk0q1/cQn/0zPAE4UmBXXuMJZEofDLYvHUbfeu3kP2rJYDOCWPZrYp9iFtbk2wbtiM3WrkxLV70LACz9t1/xONLmTeRSDBz1n5VW286nWZL/yD921K0tyYZ296y035RLOZ8MaXTaZYsW0oi2cakrklDll3KenMpZX/OLHtbKk1rMlHysmupkuOwkFKP0ZH+hmPaW2gpI649x4/hSx99LcC+wOLh40ddF9HWthba2luKTzjMQQcfNORzYluKwdbwM/3fQgfglXMs57z5xqfTaXoWLYFkG1P2nsRuY1p32nlyzfvylgH6tw1u30nSQP+2QQYGU+w+tq3gvNs2pxmettMQDq6son6h71Tu9x2t886JEn8+hcbXe950Os3Kvs1s3joAJEgmE4xpa2Hvzt2H7FsVrXf2vmWvt5z9uZJllzKu3HlLOQ7LWe+4ljY2bR4IL4ZJQyIR7vYdt3tbRb9ha0tyyDFeqta2wufLaiWBZcA0M2tx98GoAXhqNDzbUmAm8Gj0eQawZCQrOuOdry67yNbV1cHq1eEOvJe3btt+N97Fv7kCgOM/9s6c8+Uan6mWSbR1QLKVtRu2MqWzhROOfuWQon2ueR96ciWr1g4tGqbTsN+0PTjqoL0Lzrvw+fXc/dDinRr/3nLotCGNe4W+Uynft7W1pex5K1lvoXnzxVTKsmtpjz12r9rdpgufX8/dqxeTSISDPZ0OjziZv1/XiBpvRxpTqestZ38uZdmpVJpLH76N5NhODp3zup0a4Wux35VyHBZabqGYq3E/xvDfsNw7houttyptAu7+AtANnBwNOhl4PKr3z3Yb8HEzS0btBe8Fbq9GDPWWafxJtITsPpLGn0oa6DL1upn5q1mvK43XqPrkUtabSqVJdsygtevQIfXnxfbnYsvOXFC17/MWWicdVrd2rkqOw2IxJ5MJ5kybwFEH7V3VTgW1UM3eQWcBZ5vZs8DZ0WfM7B4zOzya5kagB3gOeAS4xN17qhhD3VRysFZyIs80/h171Cxef/CUqvUskebQqB48xdZb6KRXbH8utuxiF1T5kk+lKjkOK7kIbDZVaxNw92eA1+QY/s6svweBT1ZrnY1UrE92IZkTec+KDWzYso3xY0f2jJfMVYb6du96Miem4X3Ma13SK7be7JMe7Pyoi8z+nKv6o9iyC11QzZ4yfnvyIdnK3Q8tzvkojGTHDJJjO1n4/PqSj6VKjsNd6Z6LUdcw3CwqPVgzJ/Jq1ifXWrGDrdyDUXbIPjHV8/k+xdZb7KRX6MKk2Mm20AVVseSTXULJlySKfe9yjsNKLgKbjZJAmRp1sNba9hP57nsNOZEXO9gqPRhlh0aV9Aqtt9KTXqGTbaELqkeeXlUw+RRLErXSqBJbLSgJVGA0VssUulovdCIvdrA16mCU+qjlSa/QBVWlj8KoVel0V7oIVBKooWarHil2tV7oRF7sYNuV6khlZ7U+6eW7oCqWfAoliVqXTkfjRWAuSgI10ozVI8Wu1gudyItdke1KdaSSWyNOesWST6EkodJpaWKbBMa0tTBj7w4AxkZ3IGc+D1dsfC5P9PSxau3QHXDV2pfZuGVgyLtgO8bvxvixue/oK2e9heZ9avHanCf5/m2DzNi7g/Uv9/PoM6uGvL5wTFuSA2dP5MBZE3ly0VqWrNzA1oEUY9qSzNx7PEcfOo1kMsE+k8YVHJ9KpRm75ywYM5H1L/fnfF9voe87tr2FlpaWqv5G1VLoN2yUZowJyo9r1tT81U7nn3QoTy1ey/OrNzGta8e7oP+6dF3B/b2UuJppvxpT5M7fcsU2CbQkE9vvvktGt3Lnuxuv2PhcVq19mf5h74LtH0jxwtqX2f3Vk7cPmzh+LINbB6q23kLzvnLaBMa0tbB1YMczk8a0tTB76gR2H9PKETaJ33f30tO7gf6BQdrbWpg9dTxH2CSSyQRfOPlQFvT0sWzVRqZP7mDu7M4hJ/J841OpNFfc0k1iytGQaOVH9zzD7KnjOe/EeUPmL/R9k4kEba3Jqv5G1VLoN2yUZowJahfXa149GbKOKyi+vxeLK5VKkxg3HcZ08uyyF3fa32utXr9hbJNArc2Y3EH7sB2wva2F6ZPrf0WRMXd2J7Onjt/pJD83KpkkkwnOO3EeC3r6WLupn4nj2ofs+Mlkgnlz9mLenL1yLj/f+AU9ffT0boBkKBVtHRikp3cDC3r68i5LpFLF9vdCMhcu7H00JFq55s6ncl647AqUBGqkkh2wVrJP8vmu5jMn8uznLFVq6aqN9A8MfWJr/8Agy1ZtVBKQmillf88nThcuSgI1UskOWKlUKk36FfvAmE66F64Z0dV8LTRjqUjiodz9PU4XLkoCNdSIE24zFmObsVQkUkicLlyUBHYxzViMbWSpSKQccbpwURLYxTRrMbYRpSKRcsXpwkVJYBcTp2KsSC3F5cKlmu8TkCaQKcaOaWshQaZf9K5ZjBWRylVcEjCz3YEfAocB24Dz3f3nOaY7GrgHeDYatNXdd3r/gFQmTsVYEalcNaqDzgc2uvscM9sPeMDM5rj7phzTPu3uh+cY3rQKdbds1vXGpRgrIpWrRnXQicDVAO7+HPAn4B1VWG7DDeluOfFQrrnzKa64pbvm7z5t1HpFJH6qkQRmAEuyPi8FpueZdn8ze8zM/mhmp1dh3TU1pLtlIjGku+WuuF4RiZ+i1UFm9hjhRJ/L5DzDc3kMmO7u681sX+BeM3ve3e8dwTLo7Bw3ksl30tW1cy+Z9t+rSMkAAA1KSURBVPbWnOP6untzdrdcu6k/53KqFVO91jvSuGot3+9QbFwp42utUestpBljAsU1EvWIqWgScPf5hcab2VJgJrA6GjQD+O8cy9mQ9fciM7sDeB0woiTQ17ep7GqRfM/D6e/fBrDTuM5x7Tm7W04c11615+rkiqke6y0nrlrL9ztkxrW3t+aNqdC8tdaIbVVMM8YEimskqhVTMpkoePFcjeqg24AzAaKG4SOAXw2fyMymmFki+nsi8Haguwrrr5lGdbeMYzfPTEN4euIhdC9co/YPkTqpRu+gbwI/MrOFwCDwCXffCGBmlwC97n41cBzwSTMbiNZ7g7vfWYX110yjulvGrZtnMz7vSCQuKk4C7v4ScHyecV/J+vu7wHcrXV+9Naq7ZZy6eTbj845E4kJ3DEvDFXreEeyoKto24WBVFYlUmZKANFzmeUfZMs87yq4qGpxwiO6ZEKkyJQFpuEIN4bpnQqS29BRRabhCDeHN+mhskV2FkoA0hXwN4Xo0tkhtxb46SP3Tm1sc75kQqadYlwTUP735ZVcVrd3Uz8Rx7bv0PRMi9RbrJKD+6aNDpqqoGW/tFxntYl0dVKx/uojIri7WSaBQ/3QRkTiIdRJQo6OIxF2s2wTi9qA2EZHhYp0EIF4PahMRGS7W1UEiInGnJCAiEmNKAiIiMVZxm4CZnQJ8ATgAODd6eUy+aT8OfBFIAL8EznH3VKUxiIhIeapREugGTgL+s9BEZrYvcCFwJLBf9O+UKqxfRETKVHEScPcn3f1poNgV/QeAO9x9dXT1fy1wYqXrFxGR8tWzi+gMYEnW56XA9JEupLNzXEVBdHU1393AzRgTNGdc+WJqb28tOL7WRtO2ajTFVbp6xFQ0CZjZY4QTeC6T3X0wz7ia6OvbVPbjnpvxAWTNGBM0Z1yFYurv3wbQkJhH27ZqJMVVumrFlEwmCl48F00C7j6/4iiCpcDMrM8zgGVVWraIiJShntVBtwO/N7OLgT7g4xRpTBYRkdqquGHYzE42s+XA8cBXzWy5mR0QjbvEzM4CcPce4KvAI8BzQA9wU6XrFxGR8lVcEnD3m4Gb84z7yrDP1wDXVLpOERGpDt0xLCISY0oCIiIxpiQgIhJjSgIiIjGmJCAiEmNKAiIiMaYkICISY0oCIiIxpiQgIhJjSgIiIjGmJCAiEmNKAiIiMaYkICISY0oCIiIxpiQgIhJjFb9PwMxOAb4AHACc6+7fzTPd0cA9wLPRoK3u/ppK1y8iIuWrxuslu4GTgH8oYdqn3f3wKqxTRESqoBpvFnsSwMxSlYcjIiL1VM8XzQPsb2aPAQPA99z9+jqvX0REshRNAtFJe0ae0ZPdfbDEdT0GTHf39Wa2L3CvmT3v7veWOD8AnZ3jRjL5Trq6OiqavxaaMSZozrjyxdTe3lpwfK2Npm3VaIqrdPWIqWgScPf51ViRu2/I+nuRmd0BvA4YURLo69tEKpUuK4aurg5Wr95Y1ry10owxQXPGVSim/v5tAA2JebRtq0ZSXKWrVkzJZKLgxXPduoia2RQzS0R/TwTeTmhUFhGRBqk4CZjZyWa2HDge+KqZLTezA6Jxl5jZWdGkxwFPmlk38HvgRne/s9L1i4hI+arRO+hm4OY8476S9fd3gZz3EIiISGPojmERkRhTEhARiTElARGRGFMSEBGJMSUBEZEYUxIQEYkxJQERkRhTEhARiTElARGRGFMSEBGJMSUBEZEYUxIQEYkxJQERkRhTEhARiTElARGRGFMSEBGJsYpfKmNmVwFvBbYCm4DPuvuf8kz7T8CHo48/cvevVrp+EREpXzVKAr8EDnb3Q4CvAbfkmsjM3kh4BeVB0b/jo2EiItIgFScBd/+5uw9EHx8G9jGzXMs9EbjB3Te7+2bghmiYiIg0SMXVQcN8BviFu6dyjJsB3J/1eSkw4pJAZ+e48iKLdHV1VDR/LTRjTNCcceWLqb29teD4WhtN26rRFFfp6hFT0SRgZo8RTuC5THb3wWi6k4APUsaJfST6+jaRSqXLmrerq4PVqzdWOaLKNGNM0JxxFYqpv38bQENiHm3bqpEUV+mqFVMymSh48Vw0Cbj7/GLTmNn7gEuBt7r7qjyTLQVmZn2eASwrtmwREamditsEzOxdwJXAMe6+uMCktwGnmdluZrYbcBpwa6XrFxGR8lWjd9APgXbgp2bWHf3rBDCz68zs3QDufj/wM+BJ4CngZ+7+P1VYv4iIlKnihmF37yow7oxhny8CLqp0nSIiUh26Y1hEJMaUBEREYkxJQEQkxpQERERiTElARCTGlARERGJMSUBEJMaUBEREYkxJQEQkxpQERERiTElARCTGlARERGJMSUBEJMaUBEREYkxJQEQkxqryonkzuwp4K7AV2AR81t3/lGO6DwP/CiyOBi1y9/dVIwYRERm5qiQB4JfAue4+EL1u8hbglXmmvdfdP1Cl9YqISAWqkgTc/edZHx8G9jGzpLunqrF8ERGpjVq0CXwG+EWBBPCm6D3Evzezv6/B+iVmUqk06VfsQ3riIXQvXEMqlW50SCKjRiKdLn7AmNljwIw8oye7+2A03UnAxcAb3X1VjuXsBbzk7pvN7FDgV8DR7v7XEmKdBSwqYTqJkcFUmgv/4yH+4isg0crYMa3YzD25+BNH0ZJMNDo8kWayLzvaY7crqTrI3ecXm8bM3gdcCrw1VwKIlrMm6+/HzexB4G+AUpIAAH19m8q+0uvq6mD16o1lzVsrzRgTNGdcuWLqXriGZxavg2QbAFv6B3lm8Tru++Ni5s3Zq2FxNVozxgSKaySqFVMymaCzc1z+8RWvAYgag68EjnH3xQWmm5b190zgtcCCasQg8bR01Ub6BwaHDOsfGGTZquY6oEWaVbV6B/0Q6Ad+amaZYW919z4zuw64y93vAj5tZu8BtkXTXODuj1cpBomhGZM7aG9rYWtWImhva2H65I4GRiUyelSrd1BXgXFnZP19AXBBNdYpAjB3diezp46np3cD/QODtLe1MHvqeObO7mx0aCKjQrVKAiINkUwmOO/EeSzo6WPZqo1Mn9zB3NmdJNUoLFISJQEZ9ZLJBPPm7FW3hmCRXYmeHSQiEmNKAiIiMaYkICISY0oCIiIxNpoahluAint9NGOvkWaMCZozrmaMCZozrmaMCRTXSFQjpqxltOQaX9Kzg5rE64EHGh2EiMgo9QbgweEDR1MSGAMcAawABotMKyIiQQswBXiU8OKvIUZTEhARkSpTw7CISIwpCYiIxJiSgIhIjCkJiIjEmJKAiEiMKQmIiMSYkoCISIyNpsdGlM3M9geuBzqBPuA0d3+uwTEtBrZE/wC+6O6/bkAc3wKOA2YBB7v7k9Hwhm6zAnEtpkHbzcw6gRuBVxJuulkInOnuq83stcA1wG7AYuAUd3+hwTGlgSeAVDT5qe7+RK1jyortDmDfaP2bgLPdvbuR+1aBmBbTHMfjhcBFRPt8PfaruJQErgaucvf9gasIG7UZfMDd50X/6r7DRe4A3ggsGTa80dssX1zQuO2WBr7h7ubuc4H/Ay43swRwE/DpaHv9Hri8kTFljT8qa1vVLQFETnf3Q9z9UOBbwA+i4Y3ct/LFBA0+Hs1sPvBaYGn0uS771S6fBMxsEjAfuDkadDMw38zyvhc5Ttz9QXdflj2sGbZZrrgazd3Xuvv9WYMeAWYChwNb3D3zXJargRMaHFPDufv6rI8TgFSj961cMdVjvcWY2RhCQvwUIbFDnfarXT4JANOB5919ECD6vzca3mg/NrMFZvY9M9uj0cFkaeZtBk2w3cwsCXwSuAuYQVaJxd3XAEkzm9jAmDLuN7NuM/tadKKpKzO7zsyWA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<div class="prompt input_prompt">In&nbsp;[13]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Fit a GARCH(1,1) model for each asset using the ARIMA-fitted residuals.</span>
<span class="c1"># Forecast the assets&#39; 95%, 99% Value at Risk for various timeranges.</span>
<span class="kn">from</span> <span class="nn">arch</span> <span class="k">import</span> <span class="n">arch_model</span>

<span class="k">def</span> <span class="nf">buildGARCH</span><span class="p">(</span><span class="n">arima_pkg</span><span class="p">,</span> <span class="n">asset</span><span class="p">,</span> <span class="n">dataframe</span><span class="p">,</span> <span class="n">date_cutoff</span><span class="o">=</span><span class="n">ALL_END</span><span class="p">,</span> <span class="n">dist</span><span class="o">=</span><span class="s1">&#39;normal&#39;</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="n">arima_res</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="n">asset</span><span class="p">:</span> <span class="n">arima_pkg</span><span class="p">[</span><span class="mi">3</span><span class="p">]},</span>
                              <span class="n">index</span><span class="o">=</span><span class="n">dataframe</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
    <span class="n">am</span> <span class="o">=</span> <span class="n">arch_model</span><span class="p">(</span><span class="n">arima_res</span><span class="p">,</span> <span class="n">mean</span><span class="o">=</span><span class="s1">&#39;Zero&#39;</span><span class="p">,</span> <span class="n">vol</span><span class="o">=</span><span class="s1">&#39;Garch&#39;</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">o</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">dist</span><span class="o">=</span><span class="n">dist</span><span class="p">)</span>
    <span class="n">res</span> <span class="o">=</span> <span class="n">am</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">disp</span><span class="o">=</span><span class="s1">&#39;off&#39;</span><span class="p">,</span> <span class="n">last_obs</span><span class="o">=</span><span class="n">date_cutoff</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="n">res</span><span class="o">.</span><span class="n">summary</span><span class="p">())</span>
        <span class="n">fig</span> <span class="o">=</span> <span class="n">res</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">annualize</span><span class="o">=</span><span class="s1">&#39;D&#39;</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">am</span><span class="p">,</span> <span class="n">res</span>

<span class="k">def</span> <span class="nf">VaR_parametric</span><span class="p">(</span><span class="n">asset</span><span class="p">,</span> <span class="n">scope</span><span class="o">=</span><span class="s2">&quot;ALL&quot;</span><span class="p">,</span> 
                   <span class="n">train_end_date</span><span class="o">=</span><span class="n">ALL_END</span><span class="p">,</span> <span class="n">forecast_start_date</span><span class="o">=</span><span class="n">ALL_START</span><span class="p">,</span> 
                   <span class="n">start_date</span><span class="o">=</span><span class="n">ALL_START</span><span class="p">,</span> <span class="n">end_date</span><span class="o">=</span><span class="n">ALL_END</span><span class="p">,</span>
                   <span class="n">dist</span><span class="o">=</span><span class="s1">&#39;skewt&#39;</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="n">arima_pkg</span> <span class="o">=</span> <span class="n">resultsdb</span><span class="p">[</span><span class="n">scope</span><span class="p">][</span><span class="mi">2</span><span class="p">][</span><span class="n">asset</span><span class="p">]</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">resultsdb</span><span class="p">[</span><span class="n">scope</span><span class="p">][</span><span class="mi">1</span><span class="p">][</span><span class="n">asset</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
    <span class="n">len_diff</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">size</span> <span class="o">-</span> <span class="n">arima_pkg</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span><span class="o">.</span><span class="n">size</span>
    <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">len_diff</span><span class="p">:]</span>
    <span class="n">am</span><span class="p">,</span> <span class="n">res</span> <span class="o">=</span> <span class="n">buildGARCH</span><span class="p">(</span><span class="n">arima_pkg</span><span class="p">,</span> <span class="n">asset</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">date_cutoff</span><span class="o">=</span><span class="n">train_end_date</span><span class="p">,</span> <span class="n">dist</span><span class="o">=</span><span class="n">dist</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="n">verbose</span><span class="p">)</span>
    
    <span class="n">forecasts</span> <span class="o">=</span> <span class="n">res</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">start</span><span class="o">=</span><span class="n">forecast_start_date</span><span class="p">)</span>
    <span class="n">cond_mean</span> <span class="o">=</span> <span class="n">forecasts</span><span class="o">.</span><span class="n">mean</span><span class="p">[</span><span class="n">forecast_start_date</span><span class="p">:]</span>
    <span class="n">cond_var</span> <span class="o">=</span> <span class="n">forecasts</span><span class="o">.</span><span class="n">variance</span><span class="p">[</span><span class="n">forecast_start_date</span><span class="p">:]</span>
    <span class="n">q</span> <span class="o">=</span> <span class="n">am</span><span class="o">.</span><span class="n">distribution</span><span class="o">.</span><span class="n">ppf</span><span class="p">([</span><span class="mf">0.01</span><span class="p">,</span><span class="mf">0.05</span><span class="p">],</span> <span class="n">res</span><span class="o">.</span><span class="n">params</span><span class="p">[</span><span class="o">-</span><span class="mi">2</span><span class="p">:])</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">q</span><span class="p">)</span>

    <span class="n">VaR</span> <span class="o">=</span> <span class="o">-</span><span class="n">cond_mean</span><span class="o">.</span><span class="n">values</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">cond_var</span><span class="p">)</span><span class="o">.</span><span class="n">values</span> <span class="o">*</span> <span class="n">q</span><span class="p">[</span><span class="kc">None</span><span class="p">,</span> <span class="p">:]</span>
    <span class="n">VaR</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">VaR</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;1%&quot;</span><span class="p">,</span><span class="s2">&quot;5%&quot;</span><span class="p">],</span> <span class="n">index</span><span class="o">=</span><span class="n">cond_var</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
    <span class="n">VaR</span> <span class="o">=</span> <span class="n">VaR</span><span class="p">[</span><span class="n">start_date</span><span class="p">:</span><span class="n">end_date</span><span class="p">]</span>
    
    <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">resultsdb</span><span class="p">[</span><span class="n">scope</span><span class="p">])</span> <span class="o">==</span> <span class="mi">3</span><span class="p">:</span>
        <span class="n">resultsdb</span><span class="p">[</span><span class="n">scope</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">({})</span>

    <span class="n">ax</span> <span class="o">=</span> <span class="n">VaR</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">legend</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">&quot;#BBBBBB&quot;</span><span class="p">)</span>
    <span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">col</span> <span class="o">+</span> <span class="s1">&#39;: Parametric VaR&#39;</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">ax</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">VaR</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Parametrically-fitted VaR Series for the three assets in the Full Timeframe</span>
<span class="c1"># Great Recession time-period slice of Full-range VaR Series</span>
<span class="c1"># COVID-19 time-period slice of VaR forecast data based on training data from 2007-2018</span>
<span class="c1"># Graphs showing how closely fitted the VaR series are with historical asset returns.</span>

<span class="n">GR_VaR</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">CR_forecast_VaR</span> <span class="o">=</span> <span class="p">{}</span>

<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">COLS_EXCL_VIX</span><span class="p">:</span>
    <span class="n">resultsdb</span><span class="p">[</span><span class="s2">&quot;ALL&quot;</span><span class="p">][</span><span class="mi">3</span><span class="p">][</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">VaR_parametric</span><span class="p">(</span><span class="n">col</span><span class="p">,</span> <span class="n">scope</span><span class="o">=</span><span class="s2">&quot;ALL&quot;</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="n">CR_forecast_VaR</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">VaR_parametric</span><span class="p">(</span><span class="n">col</span><span class="p">,</span> <span class="n">scope</span><span class="o">=</span><span class="s2">&quot;ALL&quot;</span><span class="p">,</span> 
                                          <span class="n">train_end_date</span><span class="o">=</span><span class="n">TRAIN_END</span><span class="p">,</span> 
                                          <span class="n">forecast_start_date</span><span class="o">=</span><span class="n">FORECAST_START</span><span class="p">,</span> 
                                          <span class="n">start_date</span><span class="o">=</span><span class="n">COVID_START</span><span class="p">,</span> <span class="n">end_date</span><span class="o">=</span><span class="n">COVID_END</span><span class="p">,</span> 
                                          <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
    <span class="n">GR_VaR</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">VaR_parametric</span><span class="p">(</span><span class="n">col</span><span class="p">,</span> <span class="n">scope</span><span class="o">=</span><span class="s2">&quot;ALL&quot;</span><span class="p">,</span> 
                                 <span class="n">start_date</span><span class="o">=</span><span class="n">GR_START</span><span class="p">,</span> <span class="n">end_date</span><span class="o">=</span><span class="n">GR_END</span><span class="p">,</span> 
                                 <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
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<pre>                             Zero Mean - GARCH Model Results                             
=========================================================================================
Dep. Variable:                               SPX   R-squared:                       0.000
Mean Model:                            Zero Mean   Adj. R-squared:                  0.000
Vol Model:                                 GARCH   Log-Likelihood:               -4215.94
Distribution:      Standardized Skew Student&#39;s t   AIC:                           8441.89
Method:                       Maximum Likelihood   BIC:                           8472.13
                                                   No. Observations:                 3126
Date:                           Sat, May 23 2020   Df Residuals:                     3121
Time:                                   05:33:53   Df Model:                            5
                              Volatility Model                              
============================================================================
                 coef    std err          t      P&gt;|t|      95.0% Conf. Int.
----------------------------------------------------------------------------
omega          0.0170  4.689e-03      3.620  2.944e-04 [7.784e-03,2.616e-02]
alpha[1]       0.1381  1.653e-02      8.350  6.840e-17     [  0.106,  0.170]
beta[1]        0.8619  1.517e-02     56.833      0.000     [  0.832,  0.892]
                              Distribution                              
========================================================================
                 coef    std err          t      P&gt;|t|  95.0% Conf. Int.
------------------------------------------------------------------------
nu             5.1420      0.456     11.269  1.871e-29 [  4.248,  6.036]
lambda        -0.1593  1.982e-02     -8.037  9.209e-16 [ -0.198, -0.120]
========================================================================

Covariance estimator: robust
[-2.87047116 -1.66651082]
AxesSubplot(0.125,0.2;0.775x0.68)
[-2.84053341 -1.66428855]
AxesSubplot(0.125,0.2;0.775x0.68)
[-2.87047116 -1.66651082]
AxesSubplot(0.125,0.2;0.775x0.68)
                             Zero Mean - GARCH Model Results                             
=========================================================================================
Dep. Variable:                               SSE   R-squared:                       0.000
Mean Model:                            Zero Mean   Adj. R-squared:                  0.000
Vol Model:                                 GARCH   Log-Likelihood:               -5375.57
Distribution:      Standardized Skew Student&#39;s t   AIC:                           10761.1
Method:                       Maximum Likelihood   BIC:                           10791.4
                                                   No. Observations:                 3126
Date:                           Sat, May 23 2020   Df Residuals:                     3121
Time:                                   05:33:54   Df Model:                            5
                              Volatility Model                              
============================================================================
                 coef    std err          t      P&gt;|t|      95.0% Conf. Int.
----------------------------------------------------------------------------
omega      7.2603e-03  3.312e-03      2.192  2.835e-02 [7.696e-04,1.375e-02]
alpha[1]       0.0504  7.989e-03      6.306  2.866e-10 [3.472e-02,6.603e-02]
beta[1]        0.9496  7.563e-03    125.570      0.000     [  0.935,  0.964]
                                Distribution                               
===========================================================================
                 coef    std err          t      P&gt;|t|     95.0% Conf. Int.
---------------------------------------------------------------------------
nu             4.4693      0.360     12.405  2.465e-35    [  3.763,  5.175]
lambda        -0.0792  1.801e-02     -4.397  1.098e-05 [ -0.115,-4.389e-02]
===========================================================================

Covariance estimator: robust
[-2.77902962 -1.59179588]
AxesSubplot(0.125,0.2;0.775x0.68)
[-2.77469168 -1.6019205 ]
AxesSubplot(0.125,0.2;0.775x0.68)
[-2.77902962 -1.59179588]
AxesSubplot(0.125,0.2;0.775x0.68)
                             Zero Mean - GARCH Model Results                             
=========================================================================================
Dep. Variable:                               CNY   R-squared:                       0.000
Mean Model:                            Zero Mean   Adj. R-squared:                  0.000
Vol Model:                                 GARCH   Log-Likelihood:                1444.80
Distribution:      Standardized Skew Student&#39;s t   AIC:                          -2879.60
Method:                       Maximum Likelihood   BIC:                          -2849.36
                                                   No. Observations:                 3126
Date:                           Sat, May 23 2020   Df Residuals:                     3121
Time:                                   05:33:55   Df Model:                            5
                              Volatility Model                              
============================================================================
                 coef    std err          t      P&gt;|t|      95.0% Conf. Int.
----------------------------------------------------------------------------
omega      8.4580e-04  8.424e-05     10.040  1.015e-23 [6.807e-04,1.011e-03]
alpha[1]       0.0500  6.697e-03      7.466  8.265e-14 [3.687e-02,6.313e-02]
beta[1]        0.9300  5.664e-03    164.201      0.000     [  0.919,  0.941]
                                 Distribution                                
=============================================================================
                 coef    std err          t      P&gt;|t|       95.0% Conf. Int.
-----------------------------------------------------------------------------
nu             4.1952      0.165     25.494 2.306e-143      [  3.873,  4.518]
lambda         0.0000  1.462e-02      0.000      1.000 [-2.866e-02,2.866e-02]
=============================================================================

Covariance estimator: robust

WARNING: The optimizer did not indicate successful convergence. The message was
Positive directional derivative for linesearch. See convergence_flag.
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<pre>/home/majorlift/bin/miniconda3/envs/thicconda/lib/python3.7/site-packages/arch/univariate/base.py:605: ConvergenceWarning: The optimizer returned code 8. The message is:
Positive directional derivative for linesearch
See scipy.optimize.fmin_slsqp for code meaning.

  ConvergenceWarning)
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<pre>[-2.64206002 -1.52172451]
AxesSubplot(0.125,0.2;0.775x0.68)
[-2.64362595 -1.51908519]
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<pre>/home/majorlift/bin/miniconda3/envs/thicconda/lib/python3.7/site-packages/arch/univariate/base.py:605: ConvergenceWarning: The optimizer returned code 8. The message is:
Positive directional derivative for linesearch
See scipy.optimize.fmin_slsqp for code meaning.

  ConvergenceWarning)
/home/majorlift/bin/miniconda3/envs/thicconda/lib/python3.7/site-packages/arch/univariate/base.py:605: ConvergenceWarning: The optimizer returned code 8. The message is:
Positive directional derivative for linesearch
See scipy.optimize.fmin_slsqp for code meaning.

  ConvergenceWarning)
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<pre>AxesSubplot(0.125,0.2;0.775x0.68)
[-2.64206002 -1.52172451]
AxesSubplot(0.125,0.2;0.775x0.68)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Granger Causality Implementation: Testing for Risk Spillover</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.stattools</span> <span class="k">import</span> <span class="n">grangercausalitytests</span> <span class="k">as</span> <span class="n">granger_</span>

<span class="k">def</span> <span class="nf">granger_bilateral</span><span class="p">(</span><span class="n">cause_data</span><span class="p">,</span> <span class="n">effect_data</span><span class="p">,</span> <span class="n">cause_title</span><span class="p">,</span> <span class="n">effect_title</span><span class="p">,</span> 
                      <span class="n">title</span><span class="p">,</span> <span class="n">dateindex</span><span class="p">,</span> <span class="n">confs</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;5%&quot;</span><span class="p">,</span><span class="s2">&quot;1%&quot;</span><span class="p">],</span> <span class="n">lag</span><span class="o">=</span><span class="mi">20</span><span class="p">):</span>
    <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">confs</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
        <span class="n">results</span> <span class="o">=</span> <span class="p">{}</span>
        <span class="n">data</span> <span class="o">=</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="n">cause_title</span><span class="p">:</span> <span class="n">cause_data</span><span class="p">[</span><span class="n">conf</span><span class="p">],</span>
                              <span class="n">effect_title</span><span class="p">:</span> <span class="n">effect_data</span><span class="p">[</span><span class="n">conf</span><span class="p">]},</span>
                             <span class="n">index</span><span class="o">=</span><span class="n">dateindex</span><span class="p">)</span>
               <span class="k">for</span> <span class="n">conf</span> <span class="ow">in</span> <span class="n">confs</span><span class="p">)</span>
        <span class="k">for</span> <span class="n">dataframe</span><span class="p">,</span> <span class="n">conf</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">confs</span><span class="p">):</span>
            <span class="n">forward</span> <span class="o">=</span> <span class="p">(</span><span class="n">granger_</span><span class="p">(</span><span class="n">dataframe</span><span class="p">[[</span><span class="n">effect_title</span><span class="p">,</span> <span class="n">cause_title</span><span class="p">]],</span> <span class="n">lag</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> 
                       <span class="p">(</span><span class="n">cause_title</span><span class="p">,</span> <span class="n">effect_title</span><span class="p">),</span> <span class="n">title</span><span class="p">,</span> <span class="n">lag</span><span class="p">)</span>
            <span class="n">backward</span> <span class="o">=</span> <span class="p">(</span><span class="n">granger_</span><span class="p">(</span><span class="n">dataframe</span><span class="p">[[</span><span class="n">cause_title</span><span class="p">,</span> <span class="n">effect_title</span><span class="p">]],</span> <span class="n">lag</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> 
                        <span class="p">(</span><span class="n">effect_title</span><span class="p">,</span> <span class="n">cause_title</span><span class="p">),</span> <span class="n">title</span><span class="p">,</span> <span class="n">lag</span><span class="p">)</span>
            <span class="n">results</span><span class="p">[</span><span class="n">conf</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">forward</span><span class="p">,</span> <span class="n">backward</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">results</span>
    
    <span class="k">else</span><span class="p">:</span>
        <span class="n">dataframe</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="n">cause_title</span><span class="p">:</span> <span class="n">cause_data</span><span class="p">,</span>
                                  <span class="n">effect_title</span><span class="p">:</span> <span class="n">effect_data</span><span class="p">},</span>
                                 <span class="n">index</span><span class="o">=</span><span class="n">dateindex</span><span class="p">)</span>
        <span class="n">forward</span> <span class="o">=</span> <span class="p">(</span><span class="n">granger_</span><span class="p">(</span><span class="n">dataframe</span><span class="p">[[</span><span class="n">effect_title</span><span class="p">,</span> <span class="n">cause_title</span><span class="p">]],</span> <span class="n">lag</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> 
                   <span class="p">(</span><span class="n">cause_title</span><span class="p">,</span> <span class="n">effect_title</span><span class="p">),</span> <span class="n">title</span><span class="p">,</span> <span class="n">lag</span><span class="p">)</span>
        <span class="n">backward</span> <span class="o">=</span> <span class="p">(</span><span class="n">granger_</span><span class="p">(</span><span class="n">dataframe</span><span class="p">[[</span><span class="n">cause_title</span><span class="p">,</span> <span class="n">effect_title</span><span class="p">]],</span> <span class="n">lag</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> 
                    <span class="p">(</span><span class="n">effect_title</span><span class="p">,</span> <span class="n">cause_title</span><span class="p">),</span> <span class="n">title</span><span class="p">,</span> <span class="n">lag</span><span class="p">)</span>
        <span class="k">return</span> <span class="p">(</span><span class="n">forward</span><span class="p">,</span> <span class="n">backward</span><span class="p">)</span>
        
<span class="c1"># Weak GC if p-value &lt; alpha in &gt;50% of lag entry F-tests</span>
<span class="c1"># Strong GC if &gt;90%</span>
<span class="c1"># No GC if &lt;50%</span>
<span class="c1"># Delayed effect if more than 3 out of the first 5 lags are non-significant or lag=1 is.</span>
<span class="k">def</span> <span class="nf">print_granger</span><span class="p">(</span><span class="n">result</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">title</span><span class="p">,</span> <span class="n">lag</span><span class="p">,</span> <span class="n">conf</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="n">first_term</span> <span class="o">=</span> <span class="kc">True</span>
    <span class="n">yes_count</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">short_term</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="n">short_term_reject</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
    
    <span class="n">header</span> <span class="o">=</span> <span class="n">title</span> <span class="o">+</span> <span class="s2">&quot;: </span><span class="se">\n</span><span class="s2">&quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
    <span class="n">causal_order</span> <span class="o">=</span> <span class="n">order</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
    <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="n">header</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Lag, Confidence Level, F-statistic, p-value, Granger-Causality&quot;</span><span class="p">)</span>
    <span class="c1"># Data</span>
    <span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">v</span> <span class="ow">in</span> <span class="n">result</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
        <span class="n">ftest</span> <span class="o">=</span> <span class="n">v</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="s2">&quot;params_ftest&quot;</span><span class="p">]</span>
        <span class="k">if</span> <span class="n">ftest</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">&lt;</span> <span class="nb">int</span><span class="p">(</span><span class="n">conf</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span><span class="o">*</span><span class="mf">0.01</span><span class="p">:</span>
            <span class="n">causality</span> <span class="o">=</span> <span class="s2">&quot;Yes&quot;</span>
            <span class="n">yes_count</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">causality</span> <span class="o">=</span> <span class="s2">&quot;No&quot;</span>
            <span class="k">if</span> <span class="n">k</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
                <span class="n">first_term</span> <span class="o">=</span> <span class="kc">False</span>
            <span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">6</span><span class="p">):</span>
                <span class="n">short_term</span> <span class="o">+=</span> <span class="mi">1</span>
        <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;, &quot;</span><span class="o">.</span><span class="n">join</span><span class="p">((</span><span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">),</span> <span class="n">conf</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="n">ftest</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="nb">str</span><span class="p">(</span><span class="n">ftest</span><span class="p">[</span><span class="mi">1</span><span class="p">]),</span> <span class="n">causality</span><span class="p">)))</span>
    <span class="c1"># Conclusion</span>
    <span class="k">if</span> <span class="n">yes_count</span> <span class="o">&gt;=</span> <span class="n">lag</span> <span class="o">/</span> <span class="mi">2</span><span class="p">:</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="n">first_term</span> <span class="ow">or</span> <span class="n">short_term</span> <span class="o">&gt;</span> <span class="mi">3</span><span class="p">:</span>
            <span class="n">short_term_reject</span> <span class="o">=</span> <span class="s2">&quot;delayed&quot;</span>
        <span class="k">if</span> <span class="n">yes_count</span> <span class="o">&gt;=</span> <span class="n">lag</span> <span class="o">*</span> <span class="mf">0.9</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
                <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Strong Granger-Causality exists from &quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; to &quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; at conf=&quot;</span> <span class="o">+</span> <span class="n">conf</span> <span class="o">+</span> <span class="s2">&quot;.&quot;</span><span class="p">)</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;, &quot;</span><span class="o">.</span><span class="n">join</span><span class="p">((</span><span class="n">causal_order</span><span class="p">,</span> <span class="n">conf</span><span class="p">,</span> <span class="s2">&quot;Strong&quot;</span><span class="p">,</span> <span class="n">short_term_reject</span><span class="p">)))</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
                <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Weak Granger-Causality exists from &quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; to &quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot;.&quot;</span><span class="p">)</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;, &quot;</span><span class="o">.</span><span class="n">join</span><span class="p">((</span><span class="n">causal_order</span><span class="p">,</span> <span class="n">conf</span><span class="p">,</span> <span class="s2">&quot;Weak&quot;</span><span class="p">,</span> <span class="n">short_term_reject</span><span class="p">)))</span>
        <span class="k">if</span> <span class="n">verbose</span> <span class="ow">and</span> <span class="n">short_term_reject</span> <span class="o">!=</span> <span class="s2">&quot;&quot;</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;But it is rejected in the short term.&quot;</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;No Granger-Causality from &quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot; to &quot;</span> <span class="o">+</span> <span class="n">order</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="s2">&quot;.&quot;</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;, &quot;</span><span class="o">.</span><span class="n">join</span><span class="p">((</span><span class="n">causal_order</span><span class="p">,</span> <span class="n">conf</span><span class="p">,</span> <span class="s2">&quot;None&quot;</span><span class="p">)))</span>
    <span class="k">if</span> <span class="n">verbose</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Bidirectional Granger Causality in </span>
<span class="c1"># Implied Volatility (VIX) vs. Realized Volatility from Historical Data.</span>

<span class="k">def</span> <span class="nf">RealVolAnnualized</span><span class="p">(</span><span class="n">timeseries</span><span class="p">):</span>
    <span class="n">real_var</span> <span class="o">=</span> <span class="n">timeseries</span><span class="o">.</span><span class="n">rolling</span><span class="p">(</span><span class="mi">21</span><span class="p">)</span><span class="o">.</span><span class="n">var</span><span class="p">()</span> <span class="o">*</span> <span class="p">(</span><span class="mi">252</span> <span class="o">/</span> <span class="mi">21</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">real_var</span><span class="o">.</span><span class="n">dropna</span><span class="p">())</span>

<span class="n">spx_real_vol</span> <span class="o">=</span> <span class="n">RealVolAnnualized</span><span class="p">(</span><span class="n">df_lret</span><span class="p">[</span><span class="s2">&quot;SPX&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">())</span>
<span class="n">sns</span><span class="o">.</span><span class="n">relplot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s2">&quot;line&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s2">&quot;SPX Realized Volatility&quot;</span><span class="p">:</span> <span class="n">spx_real_vol</span><span class="p">,</span> 
                                            <span class="s2">&quot;VIX Returns&quot;</span><span class="p">:</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;VIX&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">()},</span>
                                            <span class="n">index</span><span class="o">=</span><span class="n">spx_real_vol</span><span class="o">.</span><span class="n">index</span><span class="p">)</span><span class="o">.</span><span class="n">dropna</span><span class="p">())</span>

<span class="n">realvol_forward</span><span class="p">,</span> <span class="n">realvol_backward</span> <span class="o">=</span> <span class="n">granger_bilateral</span><span class="p">(</span><span class="n">spx_real_vol</span><span class="p">,</span> <span class="n">df</span><span class="p">[</span><span class="s2">&quot;VIX&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">copy</span><span class="p">(),</span> 
                                        <span class="s2">&quot;SPX Realized Volatility (Rolling Window)&quot;</span><span class="p">,</span> 
                                        <span class="s2">&quot;VIX Daily Quotes&quot;</span><span class="p">,</span> 
                                         <span class="n">title</span><span class="o">=</span><span class="s2">&quot;Implied vs. Realized Volatility&quot;</span><span class="p">,</span>
                                         <span class="n">dateindex</span><span class="o">=</span><span class="n">spx_real_vol</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> 
                                         <span class="n">confs</span><span class="o">=</span><span class="p">[],</span> <span class="n">lag</span><span class="o">=</span><span class="mi">40</span><span class="p">)</span>

<span class="n">print_granger</span><span class="p">(</span><span class="o">*</span><span class="n">realvol_forward</span><span class="p">,</span> <span class="n">conf</span><span class="o">=</span><span class="s2">&quot;5%&quot;</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">print_granger</span><span class="p">(</span><span class="o">*</span><span class="n">realvol_backward</span><span class="p">,</span> <span class="n">conf</span><span class="o">=</span><span class="s2">&quot;5%&quot;</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<pre>Implied vs. Realized Volatility: 
SPX Realized Volatility (Rolling Window) -&gt; VIX Daily Quotes
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 24.36829587360606, 8.376780865595236e-07, Yes
2, 5%, 2.7009439694860715, 0.0673001076912734, No
3, 5%, 1.3059024624766187, 0.27069385233580995, No
4, 5%, 1.4699643861241463, 0.2085883668982806, No
5, 5%, 0.6448726593099628, 0.66545799440954, No
6, 5%, 2.5179736001600603, 0.019637802234624267, Yes
7, 5%, 2.2226058614141286, 0.029756588743226644, Yes
8, 5%, 5.089394153457854, 2.5983024904153613e-06, Yes
9, 5%, 4.993771489332804, 1.0619260294716553e-06, Yes
10, 5%, 4.456360331424659, 2.9057411247828648e-06, Yes
11, 5%, 3.8245538542074256, 1.722318629862273e-05, Yes
12, 5%, 4.8983050226310185, 4.5632554687837134e-08, Yes
13, 5%, 4.7187361852546, 3.705047132457073e-08, Yes
14, 5%, 4.572146437319556, 2.8589436947672914e-08, Yes
15, 5%, 4.327698263415143, 4.3997478222031966e-08, Yes
16, 5%, 4.096907365324939, 7.349314586404613e-08, Yes
17, 5%, 3.824089779101045, 1.87690109264035e-07, Yes
18, 5%, 3.6417490881778627, 3.0760007415248597e-07, Yes
19, 5%, 4.266495351704287, 1.6993932515534908e-09, Yes
20, 5%, 4.311916275925711, 4.877429339596558e-10, Yes
21, 5%, 4.126896821246119, 8.744652118289925e-10, Yes
22, 5%, 4.057503017360418, 6.744042988131623e-10, Yes
23, 5%, 4.5778357811267645, 3.01002799828903e-12, Yes
24, 5%, 4.788814698426474, 1.54061153080564e-13, Yes
25, 5%, 4.828057433352962, 3.5918232403878567e-14, Yes
26, 5%, 4.657181720280855, 6.833688961957725e-14, Yes
27, 5%, 4.507984497205284, 1.1643018446140934e-13, Yes
28, 5%, 4.653363567125487, 9.30337374496157e-15, Yes
29, 5%, 4.568514235400197, 8.695946921263545e-15, Yes
30, 5%, 4.47196721956871, 9.862205771458145e-15, Yes
31, 5%, 4.3094020178056995, 2.5869983043303542e-14, Yes
32, 5%, 4.170254783883411, 5.674365245262003e-14, Yes
33, 5%, 4.126809028824605, 4.209377295089572e-14, Yes
34, 5%, 4.1211215176272065, 2.0019186182203188e-14, Yes
35, 5%, 4.347663501243697, 4.651211693708007e-16, Yes
36, 5%, 4.158661908141536, 2.404247217070431e-15, Yes
37, 5%, 4.080540362712035, 3.071305205946014e-15, Yes
38, 5%, 4.234097272331656, 1.6212002175725327e-16, Yes
39, 5%, 4.170060793218515, 1.7541875850771032e-16, Yes
40, 5%, 4.0706735911909435, 3.3208658321806326e-16, Yes
Strong Granger-Causality exists from SPX Realized Volatility (Rolling Window) to VIX Daily Quotes at conf=5%.
But it is rejected in the short term.

Implied vs. Realized Volatility: 
VIX Daily Quotes -&gt; SPX Realized Volatility (Rolling Window)
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 298.4629231039453, 6.35311492636268e-64, Yes
2, 5%, 129.93887626175888, 6.4452164212190616e-55, Yes
3, 5%, 80.12940369969735, 6.385608850422787e-50, Yes
4, 5%, 60.1645035436855, 5.324357325228141e-49, Yes
5, 5%, 48.64093031157887, 1.3298149817918351e-48, Yes
6, 5%, 43.41249397846487, 3.660110374298361e-51, Yes
7, 5%, 40.025736285863964, 3.348221007252819e-54, Yes
8, 5%, 39.68209419044631, 1.2445666227367714e-60, Yes
9, 5%, 37.4575310781325, 1.3008951028688191e-63, Yes
10, 5%, 34.68443652086218, 1.0940312915544793e-64, Yes
11, 5%, 32.74436432902965, 1.8587782093287581e-66, Yes
12, 5%, 31.987389748349283, 3.615014319784382e-70, Yes
13, 5%, 29.68483892546842, 8.22328844881284e-70, Yes
14, 5%, 27.69720893559809, 1.962872240805621e-69, Yes
15, 5%, 25.96870827701195, 4.705240603586844e-69, Yes
16, 5%, 24.061177214769117, 1.633622342590591e-67, Yes
17, 5%, 25.129206490367878, 1.2494193015714983e-74, Yes
18, 5%, 25.04302294328365, 2.938685380996399e-78, Yes
19, 5%, 25.41442558991361, 2.11605975769774e-83, Yes
20, 5%, 24.531806752537165, 4.0785289858751324e-84, Yes
21, 5%, 28.483298026450363, 1.4890466734197974e-102, Yes
22, 5%, 22.345683338536464, 6.0111171716300184e-83, Yes
23, 5%, 20.936341375253924, 1.731293270316029e-80, Yes
24, 5%, 19.203637490889076, 3.8101401450162526e-76, Yes
25, 5%, 18.602539325587205, 2.863479920327378e-76, Yes
26, 5%, 17.641829108694516, 1.631571355488724e-74, Yes
27, 5%, 16.89923200666613, 1.7672955474535472e-73, Yes
28, 5%, 16.068427680730643, 9.464804987809589e-72, Yes
29, 5%, 15.419828323409977, 1.117560372224388e-70, Yes
30, 5%, 14.902604962613184, 4.380267547109611e-70, Yes
31, 5%, 14.449067893106088, 1.1506710552651045e-69, Yes
32, 5%, 13.9992862818606, 4.0999857102411073e-69, Yes
33, 5%, 13.505014704472426, 3.753482951642289e-68, Yes
34, 5%, 13.11260953822314, 1.2381333723271116e-67, Yes
35, 5%, 12.783645568064168, 2.2557064270577036e-67, Yes
36, 5%, 12.388176084765004, 1.3868118241574132e-66, Yes
37, 5%, 12.048777079920768, 5.007599285393793e-66, Yes
38, 5%, 11.838795977890896, 3.269120698542394e-66, Yes
39, 5%, 11.622684145109986, 2.763364545331146e-66, Yes
40, 5%, 12.071154705817369, 7.1472149066374675e-71, Yes
Strong Granger-Causality exists from VIX Daily Quotes to SPX Realized Volatility (Rolling Window) at conf=5%.

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Bidirectional Granger Causality of VaRs between SPX and SSE/CNY</span>
<span class="c1"># Full Timeframe, Great Recession, COVID-19 Recession compared.</span>

<span class="n">VaRs</span> <span class="o">=</span> <span class="n">resultsdb</span><span class="p">[</span><span class="s2">&quot;ALL&quot;</span><span class="p">][</span><span class="mi">0</span><span class="p">],</span> <span class="n">resultsdb</span><span class="p">[</span><span class="s2">&quot;ALL&quot;</span><span class="p">][</span><span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="s2">&quot;5%&quot;</span><span class="p">,</span><span class="s2">&quot;1%&quot;</span><span class="p">]</span>
<span class="n">GR_VaRs</span> <span class="o">=</span> <span class="s2">&quot;Great Recession&quot;</span><span class="p">,</span> <span class="n">GR_VaR</span><span class="p">,</span> <span class="p">[</span><span class="s2">&quot;5%&quot;</span><span class="p">,</span><span class="s2">&quot;1%&quot;</span><span class="p">]</span>
<span class="n">CR_VaRs</span> <span class="o">=</span> <span class="s2">&quot;COVID-19 Recession&quot;</span><span class="p">,</span> <span class="n">CR_forecast_VaR</span><span class="p">,</span> <span class="p">[</span><span class="s2">&quot;5%&quot;</span><span class="p">,</span><span class="s2">&quot;1%&quot;</span><span class="p">]</span>

<span class="k">def</span> <span class="nf">print_grangers</span><span class="p">(</span><span class="n">VaR_datasets</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
    <span class="k">for</span> <span class="n">timeframe</span><span class="p">,</span> <span class="n">VaR_df</span><span class="p">,</span> <span class="n">confs</span> <span class="ow">in</span> <span class="n">VaR_datasets</span><span class="p">:</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="n">verbose</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span> <span class="o">+</span> <span class="n">timeframe</span> <span class="o">+</span> <span class="s2">&quot;: </span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
        <span class="k">for</span> <span class="n">CHN</span> <span class="ow">in</span> <span class="p">(</span><span class="s2">&quot;SSE&quot;</span><span class="p">,</span><span class="s2">&quot;CNY&quot;</span><span class="p">):</span>
            <span class="n">results</span> <span class="o">=</span> <span class="n">granger_bilateral</span><span class="p">(</span><span class="n">VaR_df</span><span class="p">[</span><span class="s2">&quot;SPX&quot;</span><span class="p">],</span> <span class="n">VaR_df</span><span class="p">[</span><span class="n">CHN</span><span class="p">],</span> 
                                       <span class="s2">&quot;SPX&quot;</span><span class="p">,</span> <span class="n">CHN</span><span class="p">,</span>
                                        <span class="n">title</span><span class="o">=</span><span class="n">timeframe</span><span class="p">,</span> 
                                        <span class="n">dateindex</span><span class="o">=</span><span class="n">VaR_df</span><span class="p">[</span><span class="s2">&quot;SPX&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
                                        <span class="n">lag</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span>
                                        <span class="n">confs</span><span class="o">=</span><span class="n">confs</span><span class="p">)</span>
            <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">results</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
                <span class="n">print_granger</span><span class="p">(</span><span class="o">*</span><span class="n">v</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">conf</span><span class="o">=</span><span class="n">k</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="n">verbose</span><span class="p">)</span>
                <span class="n">print_granger</span><span class="p">(</span><span class="o">*</span><span class="n">v</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">conf</span><span class="o">=</span><span class="n">k</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="n">verbose</span><span class="p">)</span>
            
<span class="n">print_grangers</span><span class="p">((</span><span class="n">VaRs</span><span class="p">,</span> <span class="n">GR_VaRs</span><span class="p">,</span> <span class="n">CR_VaRs</span><span class="p">),</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="nb">print</span><span class="p">()</span>
<span class="n">print_grangers</span><span class="p">((</span><span class="n">VaRs</span><span class="p">,</span> <span class="n">GR_VaRs</span><span class="p">,</span> <span class="n">CR_VaRs</span><span class="p">),</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>

    </div>
</div>
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<pre>
Full Timeframe: 

SPX -&gt; SSE, 5%, Strong, delayed
SSE -&gt; SPX, 5%, Strong, 
SPX -&gt; SSE, 1%, Weak, delayed
SSE -&gt; SPX, 1%, Weak, 
SPX -&gt; CNY, 5%, Strong, delayed
CNY -&gt; SPX, 5%, None
SPX -&gt; CNY, 1%, Weak, delayed
CNY -&gt; SPX, 1%, None

Great Recession: 

SPX -&gt; SSE, 5%, None
SSE -&gt; SPX, 5%, None
SPX -&gt; SSE, 1%, None
SSE -&gt; SPX, 1%, None
SPX -&gt; CNY, 5%, None
CNY -&gt; SPX, 5%, None
SPX -&gt; CNY, 1%, None
CNY -&gt; SPX, 1%, None

COVID-19 Recession: 

SPX -&gt; SSE, 5%, None
SSE -&gt; SPX, 5%, None
SPX -&gt; SSE, 1%, None
SSE -&gt; SPX, 1%, None
SPX -&gt; CNY, 5%, Strong, delayed
CNY -&gt; SPX, 5%, None
SPX -&gt; CNY, 1%, None
CNY -&gt; SPX, 1%, None

Full Timeframe: 
SPX -&gt; SSE
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 0.021847421778346723, 0.882503261407205, No
2, 5%, 3.554865813474542, 0.028701085970757764, Yes
3, 5%, 5.822405144542828, 0.0005788632829249195, Yes
4, 5%, 4.308501095459372, 0.0017737662340705242, Yes
5, 5%, 3.694984202259988, 0.002453980573913133, Yes
6, 5%, 3.429628347373445, 0.0022337756662623555, Yes
7, 5%, 2.9659727190416083, 0.004225031693973738, Yes
8, 5%, 2.5790761386945684, 0.00833809856918168, Yes
9, 5%, 2.6015063893988586, 0.005452644835583764, Yes
10, 5%, 2.417515971692195, 0.007307764424763815, Yes
Strong Granger-Causality exists from SPX to SSE at conf=5%.
But it is rejected in the short term.

Full Timeframe: 
SSE -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 7.7944693556756155, 0.005272528156896206, Yes
2, 5%, 6.1893518875035625, 0.0020764364042751087, Yes
3, 5%, 4.109152450947259, 0.006407822071564728, Yes
4, 5%, 3.146321289139116, 0.013615162238432371, Yes
5, 5%, 2.8959415978387044, 0.012973698379000434, Yes
6, 5%, 2.837124271780732, 0.009330389381655906, Yes
7, 5%, 3.7527255594465765, 0.0004677721212625486, Yes
8, 5%, 3.2259122431561718, 0.0011701746243528931, Yes
9, 5%, 2.874075151000713, 0.002212337469327378, Yes
10, 5%, 2.617606479158128, 0.003608454131154772, Yes
Strong Granger-Causality exists from SSE to SPX at conf=5%.

Full Timeframe: 
SPX -&gt; SSE
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 0.02184742177847936, 0.8825032614062798, No
2, 1%, 3.5548658134745814, 0.028701085970757764, No
3, 1%, 5.822405144543004, 0.0005788632829247231, Yes
4, 1%, 4.308501095459352, 0.0017737662340705242, Yes
5, 1%, 3.6949842022602333, 0.002453980573911662, Yes
6, 1%, 3.42962834737353, 0.0022337756662613416, Yes
7, 1%, 2.965972719041576, 0.004225031693973738, Yes
8, 1%, 2.5790761386942074, 0.008338098569190886, Yes
9, 1%, 2.601506389398397, 0.0054526448355915955, Yes
10, 1%, 2.4175159716921706, 0.007307764424763815, Yes
Weak Granger-Causality exists from SPX to SSE.
But it is rejected in the short term.

Full Timeframe: 
SSE -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 7.794469355676027, 0.00527252815689476, Yes
2, 1%, 6.189351887503403, 0.0020764364042755216, Yes
3, 1%, 4.109152450947128, 0.00640782207156569, Yes
4, 1%, 3.1463212891394394, 0.013615162238426579, No
5, 1%, 2.895941597838695, 0.012973698379000434, No
6, 1%, 2.8371242717808536, 0.009330389381651878, Yes
7, 1%, 3.752725559446702, 0.0004677721212623733, Yes
8, 1%, 3.225912243155891, 0.0011701746243538782, Yes
9, 1%, 2.8740751510011204, 0.0022123374693244703, Yes
10, 1%, 2.6176064791580487, 0.0036084541311560666, Yes
Weak Granger-Causality exists from SSE to SPX.

Full Timeframe: 
SPX -&gt; CNY
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 0.007404109663086197, 0.931434464559694, No
2, 5%, 5.371118608690991, 0.004692028004149575, Yes
3, 5%, 3.702962323432571, 0.01124431019591186, Yes
4, 5%, 2.752537393967436, 0.02662866925236379, Yes
5, 5%, 5.450011674400412, 5.346410893652924e-05, Yes
6, 5%, 4.566043625331459, 0.00012756221209663887, Yes
7, 5%, 4.022190030579855, 0.00021526604223064306, Yes
8, 5%, 3.5922935592278846, 0.0003676161526142547, Yes
9, 5%, 3.2152772758832144, 0.0006907095933913869, Yes
10, 5%, 3.040776314692299, 0.0007654472651397235, Yes
Strong Granger-Causality exists from SPX to CNY at conf=5%.
But it is rejected in the short term.

Full Timeframe: 
CNY -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 0.042798963261585214, 0.8361177681254791, No
2, 5%, 0.317148932922031, 0.728245772134188, No
3, 5%, 0.18003271697728254, 0.9099888096534777, No
4, 5%, 0.844743231776071, 0.4966343264718799, No
5, 5%, 0.7214660931333887, 0.6072658287240691, No
6, 5%, 0.7235807940084947, 0.6306010441063025, No
7, 5%, 1.3569112804107173, 0.21926579007270502, No
8, 5%, 1.5164126242346025, 0.14595813547275863, No
9, 5%, 1.7123756982175165, 0.08075231729881488, No
10, 5%, 1.6756071114754936, 0.08049765810782802, No
No Granger-Causality from CNY to SPX.

Full Timeframe: 
SPX -&gt; CNY
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 0.00740410966310745, 0.931434464559694, No
2, 1%, 5.371118608690775, 0.004692028004150179, Yes
3, 1%, 3.7029623234334443, 0.011244310195896562, No
4, 1%, 2.752537393967462, 0.02662866925236379, No
5, 1%, 5.450011674401219, 5.346410893643028e-05, Yes
6, 1%, 4.5660436253316945, 0.00012756221209656317, Yes
7, 1%, 4.022190030576247, 0.0002152660422329003, Yes
8, 1%, 3.5922935592254874, 0.0003676161526170849, Yes
9, 1%, 3.2152772758818586, 0.0006907095933946353, Yes
10, 1%, 3.0407763146907336, 0.0007654472651442364, Yes
Weak Granger-Causality exists from SPX to CNY.
But it is rejected in the short term.

Full Timeframe: 
CNY -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 0.04279896326159704, 0.8361177681254791, No
2, 1%, 0.3171489329220421, 0.728245772134188, No
3, 1%, 0.18003271697729104, 0.9099888096534777, No
4, 1%, 0.8447432317760515, 0.4966343264718799, No
5, 1%, 0.7214660931333869, 0.6072658287240691, No
6, 1%, 0.7235807940084983, 0.6306010441063025, No
7, 1%, 1.3569112804107273, 0.21926579007270502, No
8, 1%, 1.5164126242345888, 0.14595813547275863, No
9, 1%, 1.7123756982175395, 0.08075231729881488, No
10, 1%, 1.6756071114754811, 0.08049765810782802, No
No Granger-Causality from CNY to SPX.

Great Recession: 
SPX -&gt; SSE
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 0.006477523312467091, 0.9358968176365315, No
2, 5%, 0.03744291918647316, 0.9632530985720049, No
3, 5%, 1.1155421771278526, 0.34268489204585295, No
4, 5%, 0.8922813120977329, 0.4686083137983672, No
5, 5%, 0.7447615656712427, 0.590385072872142, No
6, 5%, 0.6475591412305827, 0.6921058048434428, No
7, 5%, 0.6606306338952861, 0.7053946495680483, No
8, 5%, 0.644031894196238, 0.7405158374302763, No
9, 5%, 0.8581783909292331, 0.5630474898868127, No
10, 5%, 0.7702001278062905, 0.6576051137351346, No
No Granger-Causality from SPX to SSE.

Great Recession: 
SSE -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 1.4198274742398163, 0.2341997028807809, No
2, 5%, 1.1883921072353398, 0.3058869854387469, No
3, 5%, 0.9042082605988929, 0.43916825812738813, No
4, 5%, 0.9764746032889376, 0.42031923487321454, No
5, 5%, 0.8935871642019263, 0.48541612203942874, No
6, 5%, 0.902581878061597, 0.49304597244010484, No
7, 5%, 1.788747767409672, 0.08844427101057911, No
8, 5%, 1.5932202402793183, 0.1254242270708926, No
9, 5%, 1.3911433985654393, 0.19053780111259952, No
10, 5%, 1.184654513608004, 0.29996476873883493, No
No Granger-Causality from SSE to SPX.

Great Recession: 
SPX -&gt; SSE
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 0.006477523312463932, 0.9358968176365315, No
2, 1%, 0.03744291918647179, 0.9632530985720049, No
3, 1%, 1.1155421771278493, 0.34268489204585295, No
4, 1%, 0.8922813120977195, 0.46860831379837276, No
5, 1%, 0.7447615656712548, 0.5903850728721365, No
6, 1%, 0.6475591412305924, 0.6921058048434321, No
7, 1%, 0.6606306338952985, 0.7053946495680345, No
8, 1%, 0.6440318941962258, 0.7405158374302884, No
9, 1%, 0.8581783909292546, 0.5630474898867961, No
10, 1%, 0.770200127806287, 0.6576051137351346, No
No Granger-Causality from SPX to SSE.

Great Recession: 
SSE -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 1.4198274742398225, 0.2341997028807809, No
2, 1%, 1.1883921072353811, 0.3058869854387299, No
3, 1%, 0.904208260598912, 0.4391682581273809, No
4, 1%, 0.9764746032889355, 0.42031923487321454, No
5, 1%, 0.8935871642020595, 0.4854161220393365, No
6, 1%, 0.9025818780615817, 0.4930459724401196, No
7, 1%, 1.7887477674096914, 0.08844427101057596, No
8, 1%, 1.5932202402793283, 0.1254242270708878, No
9, 1%, 1.3911433985654342, 0.19053780111260252, No
10, 1%, 1.184654513608003, 0.2999647687388476, No
No Granger-Causality from SSE to SPX.

Great Recession: 
SPX -&gt; CNY
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 0.17110619920061299, 0.679371513896948, No
2, 5%, 0.08836705362035364, 0.9154443833629399, No
3, 5%, 0.1417445736469102, 0.934911035216364, No
4, 5%, 0.25678454418770236, 0.9054404182463326, No
5, 5%, 0.7747185677520589, 0.5684469741477916, No
6, 5%, 0.6562649865282498, 0.6850781249456299, No
7, 5%, 0.9207717979089054, 0.4902807241684015, No
8, 5%, 1.0342364363546492, 0.4097054090534165, No
9, 5%, 1.014746521966741, 0.4276517707890033, No
10, 5%, 0.8768304951291166, 0.5551647149382488, No
No Granger-Causality from SPX to CNY.

Great Recession: 
CNY -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 0.07677399297402038, 0.7818733284728023, No
2, 5%, 1.5537238198133903, 0.212854325881246, No
3, 5%, 1.2206345401409249, 0.30200319561744404, No
4, 5%, 1.0353053553274694, 0.38883417074924387, No
5, 5%, 1.2910073215240174, 0.2671119339535277, No
6, 5%, 1.0865655630897926, 0.3699355736016913, No
7, 5%, 0.9871006890501633, 0.4403087170733406, No
8, 5%, 0.994979155294484, 0.4395833577270414, No
9, 5%, 0.849793896788944, 0.5706913625249761, No
10, 5%, 0.9411414321355277, 0.495328380691207, No
No Granger-Causality from CNY to SPX.

Great Recession: 
SPX -&gt; CNY
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 0.17110619920060988, 0.679371513896948, No
2, 1%, 0.08836705361787736, 0.9154443833652038, No
3, 1%, 0.14174457364633383, 0.9349110352167369, No
4, 1%, 0.256784544187503, 0.9054404182464558, No
5, 1%, 0.7747185677519169, 0.5684469741478979, No
6, 1%, 0.6562649865296585, 0.6850781249444986, No
7, 1%, 0.9207717979095155, 0.49028072416792834, No
8, 1%, 1.034236436355116, 0.40970540905306657, No
9, 1%, 1.014746521966578, 0.42765177078913585, No
10, 1%, 0.8768304951297136, 0.555164714937683, No
No Granger-Causality from SPX to CNY.

Great Recession: 
CNY -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 0.076773992974015, 0.7818733284728023, No
2, 1%, 1.5537238198134309, 0.21285432588123765, No
3, 1%, 1.2206345401409138, 0.30200319561745376, No
4, 1%, 1.0353053553274554, 0.3888341707492454, No
5, 1%, 1.2910073215240172, 0.2671119339535277, No
6, 1%, 1.0865655630898152, 0.36993557360167556, No
7, 1%, 0.9871006890501773, 0.4403087170733313, No
8, 1%, 0.994979155294474, 0.4395833577270488, No
9, 1%, 0.8497938967889584, 0.5706913625249652, No
10, 1%, 0.9411414321355227, 0.4953283806912102, No
No Granger-Causality from CNY to SPX.

COVID-19 Recession: 
SPX -&gt; SSE
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 0.015884015294484768, 0.8999817692180105, No
2, 5%, 0.025191973648224113, 0.9751296469417063, No
3, 5%, 0.12249788297445709, 0.9466031326602677, No
4, 5%, 0.09603695435488173, 0.9834595261577471, No
5, 5%, 0.13395727911155236, 0.9840797685366691, No
6, 5%, 0.4358143548213314, 0.8527720712132807, No
7, 5%, 0.3800916713009316, 0.9112080147893075, No
8, 5%, 0.36830882767411327, 0.9339068153408828, No
9, 5%, 0.3196409782418892, 0.9658503656131835, No
10, 5%, 0.2897413478261196, 0.9812831833436895, No
No Granger-Causality from SPX to SSE.

COVID-19 Recession: 
SSE -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 2.624314948101976, 0.1086608314256975, No
2, 5%, 1.085247872603393, 0.34224587306377713, No
3, 5%, 0.7781209462554409, 0.5093597663533784, No
4, 5%, 0.7365955161062478, 0.5696300233559546, No
5, 5%, 0.65452223241748, 0.658904803914193, No
6, 5%, 0.49017860779699834, 0.8138009393320852, No
7, 5%, 0.3897582372090665, 0.9055545343627065, No
8, 5%, 0.5305371273855034, 0.8297049713194572, No
9, 5%, 0.6161428504687403, 0.7792037632719282, No
10, 5%, 0.5315052994259418, 0.8616638547315986, No
No Granger-Causality from SSE to SPX.

COVID-19 Recession: 
SPX -&gt; SSE
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 0.015884015294489868, 0.8999817692180105, No
2, 1%, 0.025191973648214926, 0.9751296469417208, No
3, 1%, 0.12249788297446738, 0.946603132660262, No
4, 1%, 0.09603695435489347, 0.9834595261577433, No
5, 1%, 0.13395727911154984, 0.9840797685366697, No
6, 1%, 0.4358143548213682, 0.8527720712132564, No
7, 1%, 0.3800916713009757, 0.911208014789282, No
8, 1%, 0.36830882767411194, 0.9339068153408838, No
9, 1%, 0.31964097824188514, 0.9658503656131852, No
10, 1%, 0.2897413478261045, 0.9812831833436932, No
No Granger-Causality from SPX to SSE.

COVID-19 Recession: 
SSE -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 2.624314948101965, 0.10866083142569936, No
2, 1%, 1.085247872603388, 0.34224587306377713, No
3, 1%, 0.7781209462554388, 0.5093597663533818, No
4, 1%, 0.7365955161062536, 0.5696300233559513, No
5, 1%, 0.6545222324174781, 0.658904803914196, No
6, 1%, 0.4901786077969817, 0.8138009393320977, No
7, 1%, 0.3897582372090657, 0.9055545343627079, No
8, 1%, 0.5305371273855088, 0.829704971319453, No
9, 1%, 0.6161428504687312, 0.7792037632719366, No
10, 1%, 0.5315052994259466, 0.8616638547315955, No
No Granger-Causality from SSE to SPX.

COVID-19 Recession: 
SPX -&gt; CNY
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 2.542765276599913, 0.11423039147633007, No
2, 5%, 4.316247455269852, 0.016251934145145974, Yes
3, 5%, 3.1762559183243937, 0.028134281624888163, Yes
4, 5%, 2.6328742803227048, 0.03988307331100667, Yes
5, 5%, 4.314146891607072, 0.0015864815281476613, Yes
6, 5%, 3.421826132627828, 0.004779064108148069, Yes
7, 5%, 2.8011160370509565, 0.01213364591127682, Yes
8, 5%, 2.421939282792654, 0.022513810212731564, Yes
9, 5%, 2.1995490472275976, 0.032507432394819145, Yes
10, 5%, 2.2886750821476287, 0.02277921360022807, Yes
Strong Granger-Causality exists from SPX to CNY at conf=5%.
But it is rejected in the short term.

COVID-19 Recession: 
CNY -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 5%, 0.1444853872115202, 0.7047381605668265, No
2, 5%, 1.1566997663344647, 0.3192048868176528, No
3, 5%, 0.3081198262101782, 0.8194532336357901, No
4, 5%, 0.5641461720402317, 0.6893279237005151, No
5, 5%, 0.6835421175425122, 0.6372294288294209, No
6, 5%, 0.7269397279591865, 0.6292442565685816, No
7, 5%, 0.7476868748997197, 0.6325012736147644, No
8, 5%, 0.6283021881223743, 0.7513387202188752, No
9, 5%, 0.657686029356753, 0.7437218021036418, No
10, 5%, 0.645916827065824, 0.769080929882328, No
No Granger-Causality from CNY to SPX.

COVID-19 Recession: 
SPX -&gt; CNY
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 2.54276527659995, 0.11423039147632737, No
2, 1%, 4.316247455269999, 0.01625193414514377, No
3, 1%, 3.176255918327835, 0.028134281624768723, No
4, 1%, 2.6328742803234846, 0.039883073310959805, No
5, 1%, 4.314146891607203, 0.0015864815281473085, Yes
6, 1%, 3.42182613262804, 0.004779064108146079, Yes
7, 1%, 2.8011160370509396, 0.012133645911277212, No
8, 1%, 2.421939282792516, 0.022513810212738662, No
9, 1%, 2.1995490472271815, 0.03250743239485214, No
10, 1%, 2.2886750821474076, 0.022779213600241054, No
No Granger-Causality from SPX to CNY.

COVID-19 Recession: 
CNY -&gt; SPX
Lag, Confidence Level, F-statistic, p-value, Granger-Causality
1, 1%, 0.14448538721152152, 0.7047381605668265, No
2, 1%, 1.1566997663344625, 0.3192048868176528, No
3, 1%, 0.3081198262101819, 0.8194532336357878, No
4, 1%, 0.5641461720402354, 0.6893279237005134, No
5, 1%, 0.6835421175425134, 0.6372294288294209, No
6, 1%, 0.7269397279591877, 0.6292442565685816, No
7, 1%, 0.7476868748997213, 0.6325012736147619, No
8, 1%, 0.6283021881223787, 0.7513387202188706, No
9, 1%, 0.6576860293567516, 0.7437218021036437, No
10, 1%, 0.6459168270658205, 0.7690809298823301, No
No Granger-Causality from CNY to SPX.

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