LSTM(2)_DEFINITIVO.html

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

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

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

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

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
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<h2 id="ANNEX-5-(2):-LSTM-(2)">ANNEX 5 (2): LSTM (2)<a class="anchor-link" href="#ANNEX-5-(2):-LSTM-(2)">&#182;</a></h2><p>In this Annex the method LSTM will be implemented for the time period from 2017-10-01 to 2018-03-22. Due to the window selection, however, the values predicted that will be obtained are 167 instead of 174 (number of days between the above dates). For that reason, predictions will start in 2017-10-07. In this case, a hidden layer consisting of 20 neurons is used.</p>

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<div class=" highlight hl-ipython3"><pre><span></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">time</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">datetime</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>

<span class="c1"># get market info for bitcoin from 28th April 2014 to the current day</span>
<span class="n">bitcoin_market_info</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_html</span><span class="p">(</span><span class="s2">&quot;https://coinmarketcap.com/currencies/bitcoin/historical-data/?start=20130428&amp;end=&quot;</span><span class="o">+</span><span class="n">time</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y%m</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">))[</span><span class="mi">0</span><span class="p">]</span>
<span class="c1"># convert the date string to the correct date format</span>
<span class="n">bitcoin_market_info</span> <span class="o">=</span> <span class="n">bitcoin_market_info</span><span class="o">.</span><span class="n">assign</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">bitcoin_market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]))</span>
<span class="c1"># when Volume is equal to &#39;-&#39; convert it to 0</span>
<span class="n">bitcoin_market_info</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">bitcoin_market_info</span><span class="p">[</span><span class="s1">&#39;Volume&#39;</span><span class="p">]</span><span class="o">==</span><span class="s2">&quot;-&quot;</span><span class="p">,</span><span class="s1">&#39;Volume&#39;</span><span class="p">]</span><span class="o">=</span><span class="mi">0</span>
<span class="c1"># convert to int</span>
<span class="n">bitcoin_market_info</span><span class="p">[</span><span class="s1">&#39;Volume&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">bitcoin_market_info</span><span class="p">[</span><span class="s1">&#39;Volume&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;int64&#39;</span><span class="p">)</span>
<span class="c1"># look at the first few rows</span>
<span class="n">bitcoin_market_info</span> <span class="o">=</span> <span class="n">bitcoin_market_info</span><span class="p">[</span><span class="mi">8</span><span class="p">:]</span> <span class="c1">#depending on which day you want for your last prediction.</span>
<span class="c1">#in this case it was 2018-03-22, as data is retrieved on 30th, we want only from row 7 onwards.</span>
<span class="n">bitcoin_market_info</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
</pre></div>

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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
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      <th></th>
      <th>Date</th>
      <th>Open</th>
      <th>High</th>
      <th>Low</th>
      <th>Close</th>
      <th>Volume</th>
      <th>Market Cap</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>8</th>
      <td>2018-03-22</td>
      <td>8939.44</td>
      <td>9100.71</td>
      <td>8564.90</td>
      <td>8728.47</td>
      <td>5530390000</td>
      <td>151366000000</td>
    </tr>
    <tr>
      <th>9</th>
      <td>2018-03-21</td>
      <td>8937.48</td>
      <td>9177.37</td>
      <td>8846.33</td>
      <td>8929.28</td>
      <td>6043130000</td>
      <td>151316000000</td>
    </tr>
    <tr>
      <th>10</th>
      <td>2018-03-20</td>
      <td>8619.67</td>
      <td>9051.02</td>
      <td>8389.89</td>
      <td>8913.47</td>
      <td>6361790000</td>
      <td>145922000000</td>
    </tr>
    <tr>
      <th>11</th>
      <td>2018-03-19</td>
      <td>8344.12</td>
      <td>8675.87</td>
      <td>8182.40</td>
      <td>8630.65</td>
      <td>6729110000</td>
      <td>141240000000</td>
    </tr>
    <tr>
      <th>12</th>
      <td>2018-03-18</td>
      <td>7890.52</td>
      <td>8245.51</td>
      <td>7397.99</td>
      <td>8223.68</td>
      <td>6639190000</td>
      <td>133547000000</td>
    </tr>
  </tbody>
</table>
</div>
</div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># get market info for ethereum from the start of 2016 to the current day</span>
<span class="n">eth_market_info</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_html</span><span class="p">(</span><span class="s2">&quot;https://coinmarketcap.com/currencies/ethereum/historical-data/?start=20130428&amp;end=&quot;</span><span class="o">+</span><span class="n">time</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y%m</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">))[</span><span class="mi">0</span><span class="p">]</span>
<span class="c1"># convert the date string to the correct date format</span>
<span class="n">eth_market_info</span> <span class="o">=</span> <span class="n">eth_market_info</span><span class="o">.</span><span class="n">assign</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">eth_market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]))</span>
<span class="c1"># look at the first few rows</span>
<span class="n">eth_market_info</span> <span class="o">=</span> <span class="n">eth_market_info</span><span class="p">[</span><span class="mi">8</span><span class="p">:]</span>
<span class="n">eth_market_info</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
</pre></div>

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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Date</th>
      <th>Open</th>
      <th>High</th>
      <th>Low</th>
      <th>Close</th>
      <th>Volume</th>
      <th>Market Cap</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>8</th>
      <td>2018-03-22</td>
      <td>562.10</td>
      <td>577.57</td>
      <td>523.09</td>
      <td>539.70</td>
      <td>1523460000</td>
      <td>55273800000</td>
    </tr>
    <tr>
      <th>9</th>
      <td>2018-03-21</td>
      <td>559.10</td>
      <td>589.61</td>
      <td>550.57</td>
      <td>561.73</td>
      <td>1781270000</td>
      <td>54967300000</td>
    </tr>
    <tr>
      <th>10</th>
      <td>2018-03-20</td>
      <td>556.72</td>
      <td>567.09</td>
      <td>521.20</td>
      <td>557.17</td>
      <td>1833680000</td>
      <td>54722100000</td>
    </tr>
    <tr>
      <th>11</th>
      <td>2018-03-19</td>
      <td>546.63</td>
      <td>558.10</td>
      <td>519.12</td>
      <td>556.73</td>
      <td>2046790000</td>
      <td>53718600000</td>
    </tr>
    <tr>
      <th>12</th>
      <td>2018-03-18</td>
      <td>551.64</td>
      <td>551.64</td>
      <td>460.09</td>
      <td>538.64</td>
      <td>2685500000</td>
      <td>54200100000</td>
    </tr>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#do the same for dash</span>
<span class="n">dash_market_info</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_html</span><span class="p">(</span><span class="s2">&quot;https://coinmarketcap.com/currencies/dash/historical-data/?start=20130428&amp;end=&quot;</span><span class="o">+</span><span class="n">time</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y%m</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">))[</span><span class="mi">0</span><span class="p">]</span>
<span class="c1"># convert the date string to the correct date format</span>
<span class="n">dash_market_info</span> <span class="o">=</span> <span class="n">dash_market_info</span><span class="o">.</span><span class="n">assign</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">dash_market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]))</span>
<span class="c1">#dash_market_info.loc[dash_market_info[&#39;Volume&#39;]==&quot;-&quot;,&#39;Volume&#39;]=0</span>
<span class="c1"># convert to int</span>
<span class="n">dash_market_info</span><span class="p">[</span><span class="s1">&#39;Volume&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">dash_market_info</span><span class="p">[</span><span class="s1">&#39;Volume&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;int64&#39;</span><span class="p">)</span>
<span class="c1"># look at the first few rows</span>
<span class="n">dash_market_info</span> <span class="o">=</span> <span class="n">dash_market_info</span><span class="p">[</span><span class="mi">8</span><span class="p">:]</span> 
<span class="n">dash_market_info</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Date</th>
      <th>Open</th>
      <th>High</th>
      <th>Low</th>
      <th>Close</th>
      <th>Volume</th>
      <th>Market Cap</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>8</th>
      <td>2018-03-22</td>
      <td>434.44</td>
      <td>438.40</td>
      <td>398.59</td>
      <td>411.36</td>
      <td>96356400</td>
      <td>3458220000</td>
    </tr>
    <tr>
      <th>9</th>
      <td>2018-03-21</td>
      <td>429.15</td>
      <td>450.64</td>
      <td>424.79</td>
      <td>434.51</td>
      <td>115173000</td>
      <td>3415280000</td>
    </tr>
    <tr>
      <th>10</th>
      <td>2018-03-20</td>
      <td>412.49</td>
      <td>442.05</td>
      <td>399.17</td>
      <td>428.88</td>
      <td>109677000</td>
      <td>3281830000</td>
    </tr>
    <tr>
      <th>11</th>
      <td>2018-03-19</td>
      <td>392.32</td>
      <td>409.32</td>
      <td>368.52</td>
      <td>409.32</td>
      <td>113994000</td>
      <td>3120600000</td>
    </tr>
    <tr>
      <th>12</th>
      <td>2018-03-18</td>
      <td>388.19</td>
      <td>394.15</td>
      <td>342.51</td>
      <td>394.15</td>
      <td>117296000</td>
      <td>3086950000</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">xmr_market_info</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_html</span><span class="p">(</span><span class="s2">&quot;https://coinmarketcap.com/currencies/monero/historical-data/?start=20130428&amp;end=&quot;</span><span class="o">+</span><span class="n">time</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y%m</span><span class="si">%d</span><span class="s2">&quot;</span><span class="p">))[</span><span class="mi">0</span><span class="p">]</span>
<span class="c1"># convert the date string to the correct date format</span>
<span class="n">xmr_market_info</span> <span class="o">=</span> <span class="n">xmr_market_info</span><span class="o">.</span><span class="n">assign</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">dash_market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]))</span>
<span class="c1">#dash_market_info.loc[dash_market_info[&#39;Volume&#39;]==&quot;-&quot;,&#39;Volume&#39;]=0</span>
<span class="c1"># convert to int</span>
<span class="n">xmr_market_info</span><span class="p">[</span><span class="s1">&#39;Volume&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">xmr_market_info</span><span class="p">[</span><span class="s1">&#39;Volume&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;int64&#39;</span><span class="p">)</span>
<span class="c1"># look at the first few rows</span>
<span class="n">xmr_market_info</span> <span class="o">=</span> <span class="n">xmr_market_info</span><span class="p">[</span><span class="mi">8</span><span class="p">:]</span> 
<span class="n">xmr_market_info</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Date</th>
      <th>Open</th>
      <th>High</th>
      <th>Low</th>
      <th>Close</th>
      <th>Volume</th>
      <th>Market Cap</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>8</th>
      <td>2018-03-22</td>
      <td>218.56</td>
      <td>223.68</td>
      <td>204.90</td>
      <td>212.71</td>
      <td>40394500</td>
      <td>3464170000</td>
    </tr>
    <tr>
      <th>9</th>
      <td>2018-03-21</td>
      <td>224.26</td>
      <td>235.90</td>
      <td>215.28</td>
      <td>218.63</td>
      <td>57121400</td>
      <td>3553750000</td>
    </tr>
    <tr>
      <th>10</th>
      <td>2018-03-20</td>
      <td>217.94</td>
      <td>233.27</td>
      <td>206.96</td>
      <td>223.74</td>
      <td>60005900</td>
      <td>3452770000</td>
    </tr>
    <tr>
      <th>11</th>
      <td>2018-03-19</td>
      <td>210.33</td>
      <td>222.00</td>
      <td>202.38</td>
      <td>216.77</td>
      <td>67314400</td>
      <td>3331520000</td>
    </tr>
    <tr>
      <th>12</th>
      <td>2018-03-18</td>
      <td>197.43</td>
      <td>209.63</td>
      <td>175.08</td>
      <td>209.63</td>
      <td>75859900</td>
      <td>3126390000</td>
    </tr>
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<p>Some python packages have been loaded and then the table in <a href="https://coinmarketcap.com/currencies/bitcoin/historical-data/">https://coinmarketcap.com/currencies/bitcoin/historical-data/</a> is imported. After cleaning the data that table is obtained. By replacing 'bitcoin' with 'ethereum' the corresponding table for the 'ether' token is obtained. Below, both prices are plotted.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># getting the Bitcoin and Eth logos</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">from</span> <span class="nn">PIL</span> <span class="k">import</span> <span class="n">Image</span>
<span class="kn">import</span> <span class="nn">io</span>

<span class="k">if</span> <span class="n">sys</span><span class="o">.</span><span class="n">version_info</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">&lt;</span> <span class="mi">3</span><span class="p">:</span>
    <span class="kn">import</span> <span class="nn">urllib2</span> <span class="k">as</span> <span class="nn">urllib</span>
    <span class="n">bt_img</span> <span class="o">=</span> <span class="n">urllib</span><span class="o">.</span><span class="n">urlopen</span><span class="p">(</span><span class="s2">&quot;http://logok.org/wp-content/uploads/2016/10/Bitcoin-Logo-640x480.png&quot;</span><span class="p">)</span>
    <span class="n">eth_img</span> <span class="o">=</span> <span class="n">urllib</span><span class="o">.</span><span class="n">urlopen</span><span class="p">(</span><span class="s2">&quot;https://upload.wikimedia.org/wikipedia/commons/thumb/0/05/Ethereum_logo_2014.svg/256px-Ethereum_logo_2014.svg.png&quot;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
    <span class="kn">import</span> <span class="nn">urllib</span>
    <span class="n">bt_img</span> <span class="o">=</span> <span class="n">urllib</span><span class="o">.</span><span class="n">request</span><span class="o">.</span><span class="n">urlopen</span><span class="p">(</span><span class="s2">&quot;http://logok.org/wp-content/uploads/2016/10/Bitcoin-Logo-640x480.png&quot;</span><span class="p">)</span>
    <span class="n">eth_img</span> <span class="o">=</span> <span class="n">urllib</span><span class="o">.</span><span class="n">request</span><span class="o">.</span><span class="n">urlopen</span><span class="p">(</span><span class="s2">&quot;https://upload.wikimedia.org/wikipedia/commons/thumb/0/05/Ethereum_logo_2014.svg/256px-Ethereum_logo_2014.svg.png&quot;</span><span class="p">)</span>

<span class="n">image_file</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">BytesIO</span><span class="p">(</span><span class="n">bt_img</span><span class="o">.</span><span class="n">read</span><span class="p">())</span>
<span class="n">bitcoin_im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">image_file</span><span class="p">)</span>

<span class="n">image_file</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">BytesIO</span><span class="p">(</span><span class="n">eth_img</span><span class="o">.</span><span class="n">read</span><span class="p">())</span>
<span class="n">eth_im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">image_file</span><span class="p">)</span>
<span class="n">width_eth_im</span> <span class="p">,</span> <span class="n">height_eth_im</span>  <span class="o">=</span> <span class="n">eth_im</span><span class="o">.</span><span class="n">size</span>
<span class="n">eth_im</span> <span class="o">=</span> <span class="n">eth_im</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="nb">int</span><span class="p">(</span><span class="n">eth_im</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="mf">0.1</span><span class="p">),</span> <span class="nb">int</span><span class="p">(</span><span class="n">eth_im</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">*</span><span class="mf">0.1</span><span class="p">)),</span> <span class="n">Image</span><span class="o">.</span><span class="n">ANTIALIAS</span><span class="p">)</span>
<span class="n">bitcoin_im</span> <span class="o">=</span> <span class="n">bitcoin_im</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="nb">int</span><span class="p">(</span><span class="n">bitcoin_im</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="mf">0.1</span><span class="p">),</span> <span class="nb">int</span><span class="p">(</span><span class="n">bitcoin_im</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">*</span><span class="mf">0.1</span><span class="p">)),</span> <span class="n">Image</span><span class="o">.</span><span class="n">ANTIALIAS</span><span class="p">)</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">bitcoin_market_info</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span><span class="p">[</span><span class="n">bitcoin_market_info</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">+</span><span class="p">[</span><span class="s1">&#39;bt_&#39;</span><span class="o">+</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">bitcoin_market_info</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">1</span><span class="p">:]]</span>
<span class="n">eth_market_info</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span><span class="p">[</span><span class="n">eth_market_info</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">+</span><span class="p">[</span><span class="s1">&#39;eth_&#39;</span><span class="o">+</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">eth_market_info</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">1</span><span class="p">:]]</span>
<span class="n">dash_market_info</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span><span class="p">[</span><span class="n">dash_market_info</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">+</span><span class="p">[</span><span class="s1">&#39;dash_&#39;</span><span class="o">+</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">dash_market_info</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">1</span><span class="p">:]]</span>
<span class="n">xmr_market_info</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span><span class="p">[</span><span class="n">xmr_market_info</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">+</span><span class="p">[</span><span class="s1">&#39;xmr_&#39;</span><span class="o">+</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">xmr_market_info</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">1</span><span class="p">:]]</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="n">ax2</span><span class="p">)</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span> <span class="n">gridspec_kw</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;height_ratios&#39;</span><span class="p">:[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">]})</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Closing Price ($)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Volume ($ bn)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_yticks</span><span class="p">([</span><span class="nb">int</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">%d</span><span class="s1">000000000&#39;</span><span class="o">%</span><span class="k">i</span>) for i in range(10)])
<span class="n">ax2</span><span class="o">.</span><span class="n">set_yticklabels</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">10</span><span class="p">))</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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="p">[</span><span class="mi">2014</span><span class="p">,</span> <span class="mi">2016</span><span class="p">,</span> <span class="mi">2018</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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="p">[</span><span class="mi">2014</span><span class="p">,</span> <span class="mi">2016</span><span class="p">,</span> <span class="mi">2018</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">]])</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%b %Y&#39;</span><span class="p">)</span>  <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">2014</span><span class="p">,</span> <span class="mi">2016</span><span class="p">,</span> <span class="mi">2018</span><span class="p">]</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">bitcoin_market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span><span class="n">bitcoin_market_info</span><span class="p">[</span><span class="s1">&#39;bt_Open&#39;</span><span class="p">])</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="n">bitcoin_market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">)</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">bitcoin_market_info</span><span class="p">[</span><span class="s1">&#39;bt_Volume&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
<span class="n">fig</span><span class="o">.</span><span class="n">figimage</span><span class="p">(</span><span class="n">bitcoin_im</span><span class="p">,</span> <span class="mi">100</span><span class="p">,</span> <span class="mi">120</span><span class="p">,</span> <span class="n">zorder</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span><span class="n">alpha</span><span class="o">=.</span><span class="mi">5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

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<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[8]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="n">ax2</span><span class="p">)</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span> <span class="n">gridspec_kw</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;height_ratios&#39;</span><span class="p">:[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">]})</span>
<span class="c1">#ax1.set_yscale(&#39;log&#39;)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Closing Price ($)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Volume ($ bn)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_yticks</span><span class="p">([</span><span class="nb">int</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">%d</span><span class="s1">000000000&#39;</span><span class="o">%</span><span class="k">i</span>) for i in range(10)])
<span class="n">ax2</span><span class="o">.</span><span class="n">set_yticklabels</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">10</span><span class="p">))</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">]])</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%b %Y&#39;</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">eth_market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span><span class="n">eth_market_info</span><span class="p">[</span><span class="s1">&#39;eth_Open&#39;</span><span class="p">])</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">bar</span><span class="p">(</span><span class="n">eth_market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">)</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">eth_market_info</span><span class="p">[</span><span class="s1">&#39;eth_Volume&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
<span class="n">fig</span><span class="o">.</span><span class="n">figimage</span><span class="p">(</span><span class="n">eth_im</span><span class="p">,</span> <span class="mi">300</span><span class="p">,</span> <span class="mi">180</span><span class="p">,</span> <span class="n">zorder</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=.</span><span class="mi">6</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">market_info</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">bitcoin_market_info</span><span class="p">,</span><span class="n">eth_market_info</span><span class="p">,</span> <span class="n">on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">])</span>
<span class="n">market_info</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">market_info</span><span class="p">,</span> <span class="n">dash_market_info</span><span class="p">,</span> <span class="n">on</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">])</span>
<span class="n">market_info</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">market_info</span><span class="p">,</span> <span class="n">xmr_market_info</span><span class="p">,</span> <span class="n">on</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">])</span>

<span class="n">market_info</span> <span class="o">=</span> <span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&gt;=</span><span class="s1">&#39;2016-01-01&#39;</span><span class="p">]</span> 

<span class="k">for</span> <span class="n">coins</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;bt_&#39;</span><span class="p">,</span> <span class="s1">&#39;eth_&#39;</span><span class="p">,</span> <span class="s1">&#39;dash_&#39;</span><span class="p">,</span> <span class="s1">&#39;xmr_&#39;</span><span class="p">]:</span> 
    <span class="n">kwargs</span> <span class="o">=</span> <span class="p">{</span> <span class="n">coins</span><span class="o">+</span><span class="s1">&#39;day_diff&#39;</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;Close&#39;</span><span class="p">]</span><span class="o">-</span><span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;Open&#39;</span><span class="p">])</span><span class="o">/</span><span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;Open&#39;</span><span class="p">]}</span>
    <span class="n">market_info</span> <span class="o">=</span> <span class="n">market_info</span><span class="o">.</span><span class="n">assign</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
    
<span class="n">market_info</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Date</th>
      <th>bt_Open</th>
      <th>bt_High</th>
      <th>bt_Low</th>
      <th>bt_Close</th>
      <th>bt_Volume</th>
      <th>bt_Market Cap</th>
      <th>eth_Open</th>
      <th>eth_High</th>
      <th>eth_Low</th>
      <th>...</th>
      <th>xmr_Open</th>
      <th>xmr_High</th>
      <th>xmr_Low</th>
      <th>xmr_Close</th>
      <th>xmr_Volume</th>
      <th>xmr_Market Cap</th>
      <th>bt_day_diff</th>
      <th>eth_day_diff</th>
      <th>dash_day_diff</th>
      <th>xmr_day_diff</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2018-03-22</td>
      <td>8939.44</td>
      <td>9100.71</td>
      <td>8564.90</td>
      <td>8728.47</td>
      <td>5530390000</td>
      <td>151366000000</td>
      <td>562.10</td>
      <td>577.57</td>
      <td>523.09</td>
      <td>...</td>
      <td>218.56</td>
      <td>223.68</td>
      <td>204.90</td>
      <td>212.71</td>
      <td>40394500</td>
      <td>3464170000</td>
      <td>-0.023600</td>
      <td>-0.039851</td>
      <td>-0.053126</td>
      <td>-0.026766</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2018-03-21</td>
      <td>8937.48</td>
      <td>9177.37</td>
      <td>8846.33</td>
      <td>8929.28</td>
      <td>6043130000</td>
      <td>151316000000</td>
      <td>559.10</td>
      <td>589.61</td>
      <td>550.57</td>
      <td>...</td>
      <td>224.26</td>
      <td>235.90</td>
      <td>215.28</td>
      <td>218.63</td>
      <td>57121400</td>
      <td>3553750000</td>
      <td>-0.000917</td>
      <td>0.004704</td>
      <td>0.012490</td>
      <td>-0.025105</td>
    </tr>
    <tr>
      <th>2</th>
      <td>2018-03-20</td>
      <td>8619.67</td>
      <td>9051.02</td>
      <td>8389.89</td>
      <td>8913.47</td>
      <td>6361790000</td>
      <td>145922000000</td>
      <td>556.72</td>
      <td>567.09</td>
      <td>521.20</td>
      <td>...</td>
      <td>217.94</td>
      <td>233.27</td>
      <td>206.96</td>
      <td>223.74</td>
      <td>60005900</td>
      <td>3452770000</td>
      <td>0.034085</td>
      <td>0.000808</td>
      <td>0.039734</td>
      <td>0.026613</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2018-03-19</td>
      <td>8344.12</td>
      <td>8675.87</td>
      <td>8182.40</td>
      <td>8630.65</td>
      <td>6729110000</td>
      <td>141240000000</td>
      <td>546.63</td>
      <td>558.10</td>
      <td>519.12</td>
      <td>...</td>
      <td>210.33</td>
      <td>222.00</td>
      <td>202.38</td>
      <td>216.77</td>
      <td>67314400</td>
      <td>3331520000</td>
      <td>0.034339</td>
      <td>0.018477</td>
      <td>0.043332</td>
      <td>0.030619</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2018-03-18</td>
      <td>7890.52</td>
      <td>8245.51</td>
      <td>7397.99</td>
      <td>8223.68</td>
      <td>6639190000</td>
      <td>133547000000</td>
      <td>551.64</td>
      <td>551.64</td>
      <td>460.09</td>
      <td>...</td>
      <td>197.43</td>
      <td>209.63</td>
      <td>175.08</td>
      <td>209.63</td>
      <td>75859900</td>
      <td>3126390000</td>
      <td>0.042223</td>
      <td>-0.023566</td>
      <td>0.015353</td>
      <td>0.061794</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 29 columns</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">split_date</span> <span class="o">=</span> <span class="s1">&#39;2017-10-01&#39;</span> <span class="c1">#as with the ARIMA + GARCH (1, 1), we start in 2017-10-01; </span>
<span class="c1">#however, notice that due to the window selection, the first predicted value</span>
<span class="c1">#will correspond to 2017-10-07</span>
<span class="n">fig</span><span class="p">,</span> <span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="n">ax2</span><span class="p">)</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">]])</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%b %Y&#39;</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">7</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">],</span> 
         <span class="n">color</span><span class="o">=</span><span class="s1">&#39;#B08FC7&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Training&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">],</span> 
         <span class="n">color</span><span class="o">=</span><span class="s1">&#39;#8FBAC8&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Test&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">],</span> 
         <span class="n">color</span><span class="o">=</span><span class="s1">&#39;#B08FC7&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span> <span class="o">&gt;=</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;#8FBAC8&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Bitcoin Price ($)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Ethereum Price ($)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mf">0.03</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">borderaxespad</span><span class="o">=</span><span class="mf">0.</span><span class="p">,</span> <span class="n">prop</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;size&#39;</span><span class="p">:</span> <span class="mi">14</span><span class="p">})</span>
<span class="n">fig</span><span class="o">.</span><span class="n">figimage</span><span class="p">(</span><span class="n">bitcoin_im</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="nb">int</span><span class="p">(</span><span class="n">bitcoin_im</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="mf">0.65</span><span class="p">),</span> <span class="nb">int</span><span class="p">(</span><span class="n">bitcoin_im</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">*</span><span class="mf">0.65</span><span class="p">)),</span> <span class="n">Image</span><span class="o">.</span><span class="n">ANTIALIAS</span><span class="p">),</span> 
             <span class="mi">350</span><span class="p">,</span> <span class="mi">170</span><span class="p">,</span> <span class="n">zorder</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span><span class="n">alpha</span><span class="o">=.</span><span class="mi">5</span><span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">figimage</span><span class="p">(</span><span class="n">eth_im</span><span class="o">.</span><span class="n">resize</span><span class="p">((</span><span class="nb">int</span><span class="p">(</span><span class="n">eth_im</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="mf">0.65</span><span class="p">),</span> <span class="nb">int</span><span class="p">(</span><span class="n">eth_im</span><span class="o">.</span><span class="n">size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">*</span><span class="mf">0.65</span><span class="p">)),</span> <span class="n">Image</span><span class="o">.</span><span class="n">ANTIALIAS</span><span class="p">),</span> 
             <span class="mi">360</span><span class="p">,</span> <span class="mi">40</span><span class="p">,</span> <span class="n">zorder</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span><span class="n">alpha</span><span class="o">=.</span><span class="mi">5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<p>First, we may want to make sure the daily change in price follows a normal distribution. We'll plot the histogram of values. This is especially important for recurrent neural networks.</p>

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<div class="prompt input_prompt">In&nbsp;[11]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="n">ax2</span><span class="p">)</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;bt_day_diff&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">market_info</span><span class="p">[</span><span class="n">market_info</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;eth_day_diff&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Bitcoin Daily Price Changes&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Ethereum Daily Price Changes&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<h2 id="Long-Short-Term-Memory-(LSTM)">Long Short Term Memory (LSTM)<a class="anchor-link" href="#Long-Short-Term-Memory-(LSTM)">&#182;</a></h2><p>For an explanation of how ANN, and especially LSTM work, see the references in the sub-section Long Short-Term Memory (LSTM). The Keras (2018) package is used. First, some transformations are carried out, in order to get variables 'close_off_high' and 'volatility' for each cryptocurrency.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">for</span> <span class="n">coins</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;bt_&#39;</span><span class="p">,</span> <span class="s1">&#39;eth_&#39;</span><span class="p">,</span> <span class="s1">&#39;dash_&#39;</span><span class="p">,</span> <span class="s1">&#39;xmr_&#39;</span><span class="p">]:</span> 
    <span class="n">kwargs</span> <span class="o">=</span> <span class="p">{</span> <span class="n">coins</span><span class="o">+</span><span class="s1">&#39;close_off_high&#39;</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="mi">2</span><span class="o">*</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;High&#39;</span><span class="p">]</span><span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;Close&#39;</span><span class="p">])</span><span class="o">/</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;High&#39;</span><span class="p">]</span><span class="o">-</span><span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;Low&#39;</span><span class="p">])</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span>
            <span class="n">coins</span><span class="o">+</span><span class="s1">&#39;volatility&#39;</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;High&#39;</span><span class="p">]</span><span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;Low&#39;</span><span class="p">])</span><span class="o">/</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">coins</span><span class="o">+</span><span class="s1">&#39;Open&#39;</span><span class="p">])}</span>
    <span class="n">market_info</span> <span class="o">=</span> <span class="n">market_info</span><span class="o">.</span><span class="n">assign</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model_data</span> <span class="o">=</span> <span class="n">market_info</span><span class="p">[[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">+</span><span class="p">[</span><span class="n">coin</span><span class="o">+</span><span class="n">metric</span> <span class="k">for</span> <span class="n">coin</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;bt_&#39;</span><span class="p">,</span> <span class="s1">&#39;eth_&#39;</span><span class="p">,</span> <span class="s1">&#39;dash_&#39;</span><span class="p">,</span> <span class="s1">&#39;xmr_&#39;</span><span class="p">]</span> 
                                   <span class="k">for</span> <span class="n">metric</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">,</span><span class="s1">&#39;Volume&#39;</span><span class="p">,</span><span class="s1">&#39;close_off_high&#39;</span><span class="p">,</span><span class="s1">&#39;volatility&#39;</span><span class="p">]]]</span>
<span class="c1"># need to reverse the data frame so that subsequent rows represent later timepoints</span>
<span class="n">model_data</span> <span class="o">=</span> <span class="n">model_data</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">by</span><span class="o">=</span><span class="s1">&#39;Date&#39;</span><span class="p">)</span>
<span class="n">model_data</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Date</th>
      <th>bt_Close</th>
      <th>bt_Volume</th>
      <th>bt_close_off_high</th>
      <th>bt_volatility</th>
      <th>eth_Close</th>
      <th>eth_Volume</th>
      <th>eth_close_off_high</th>
      <th>eth_volatility</th>
      <th>dash_Close</th>
      <th>dash_Volume</th>
      <th>dash_close_off_high</th>
      <th>dash_volatility</th>
      <th>xmr_Close</th>
      <th>xmr_Volume</th>
      <th>xmr_close_off_high</th>
      <th>xmr_volatility</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>811</th>
      <td>2016-01-01</td>
      <td>434.33</td>
      <td>36278900</td>
      <td>-0.560641</td>
      <td>0.020292</td>
      <td>0.948024</td>
      <td>206062</td>
      <td>-0.418477</td>
      <td>0.025040</td>
      <td>3.38</td>
      <td>98317</td>
      <td>6.666667e-02</td>
      <td>0.090090</td>
      <td>0.497867</td>
      <td>88914</td>
      <td>0.286720</td>
      <td>0.194582</td>
    </tr>
    <tr>
      <th>810</th>
      <td>2016-01-02</td>
      <td>433.44</td>
      <td>30096600</td>
      <td>0.250597</td>
      <td>0.009641</td>
      <td>0.937124</td>
      <td>255504</td>
      <td>0.965898</td>
      <td>0.034913</td>
      <td>3.28</td>
      <td>62353</td>
      <td>5.789474e-01</td>
      <td>0.056213</td>
      <td>0.532668</td>
      <td>64901</td>
      <td>-0.040275</td>
      <td>0.132592</td>
    </tr>
    <tr>
      <th>809</th>
      <td>2016-01-03</td>
      <td>430.01</td>
      <td>39633800</td>
      <td>-0.173865</td>
      <td>0.020827</td>
      <td>0.971905</td>
      <td>407632</td>
      <td>-0.317885</td>
      <td>0.060792</td>
      <td>3.24</td>
      <td>87155</td>
      <td>-1.998401e-15</td>
      <td>0.066869</td>
      <td>0.500312</td>
      <td>43237</td>
      <td>0.619697</td>
      <td>0.093337</td>
    </tr>
    <tr>
      <th>808</th>
      <td>2016-01-04</td>
      <td>433.09</td>
      <td>38477500</td>
      <td>-0.474265</td>
      <td>0.012649</td>
      <td>0.954480</td>
      <td>346245</td>
      <td>-0.057657</td>
      <td>0.047943</td>
      <td>3.32</td>
      <td>65748</td>
      <td>-4.545455e-01</td>
      <td>0.033846</td>
      <td>0.517388</td>
      <td>29381</td>
      <td>-0.244774</td>
      <td>0.058405</td>
    </tr>
    <tr>
      <th>807</th>
      <td>2016-01-05</td>
      <td>431.96</td>
      <td>34522600</td>
      <td>-0.013333</td>
      <td>0.010391</td>
      <td>0.950176</td>
      <td>219833</td>
      <td>0.697930</td>
      <td>0.025236</td>
      <td>3.33</td>
      <td>71861</td>
      <td>4.666667e-01</td>
      <td>0.045181</td>
      <td>0.499272</td>
      <td>30449</td>
      <td>0.811877</td>
      <td>0.092133</td>
    </tr>
  </tbody>
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<p>A new data frame ('model_data') was created, removing columns Open, High and Low, and adding 'close_off_high', which represents how close the closing price is from the high price of that day. It is between 1 and -1 (1: close = high, -1: close = low). 'Volatility' is measured as the difference between high and low divided by open. 
This model uses previous data from bitcoin, ether and dash to predict next day's closing price of bitcoin and ether, separately. It has access to the previous 5 days (window = 5). After trying different windows, it was found that providing the model with too many previous data makes it remember long term relationships among the variables in the training phase that do not hold in the test phase. 
As widely varying inputs affect data negatively, the close price is normalized as in Aungiers (2017) to the first value of the window. 'Volume' column for each cryptocurrency is eliminated. After this normalization, most of the values for each window are between -1 and 1, which is desirable for deep learning models.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># we don&#39;t need the date columns anymore</span>
<span class="n">training_set</span><span class="p">,</span> <span class="n">test_set</span> <span class="o">=</span> <span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span><span class="n">split_date</span><span class="p">],</span> <span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&gt;=</span><span class="n">split_date</span><span class="p">]</span>
<span class="n">training_set</span> <span class="o">=</span> <span class="n">training_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;Date&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">test_set</span> <span class="o">=</span> <span class="n">test_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;Date&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">training_set</span> <span class="o">=</span> <span class="n">training_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;bt_Volume&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">training_set</span> <span class="o">=</span> <span class="n">training_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;eth_Volume&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">training_set</span> <span class="o">=</span> <span class="n">training_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;dash_Volume&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">test_set</span> <span class="o">=</span> <span class="n">test_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;bt_Volume&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">test_set</span> <span class="o">=</span> <span class="n">test_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;eth_Volume&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">test_set</span> <span class="o">=</span> <span class="n">test_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;dash_Volume&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">training_set</span> <span class="o">=</span> <span class="n">training_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;dash_close_off_high&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">test_set</span> <span class="o">=</span> <span class="n">test_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;dash_close_off_high&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">training_set</span> <span class="o">=</span> <span class="n">training_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;xmr_Volume&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">test_set</span> <span class="o">=</span> <span class="n">test_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;xmr_Volume&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">training_set</span> <span class="o">=</span> <span class="n">training_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;xmr_close_off_high&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">test_set</span> <span class="o">=</span> <span class="n">test_set</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;xmr_close_off_high&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">window_len</span> <span class="o">=</span> <span class="mi">5</span>
<span class="n">norm_cols</span> <span class="o">=</span> <span class="p">[</span><span class="n">coin</span><span class="o">+</span><span class="n">metric</span> <span class="k">for</span> <span class="n">coin</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;bt_&#39;</span><span class="p">,</span> <span class="s1">&#39;eth_&#39;</span><span class="p">,</span> <span class="s1">&#39;dash_&#39;</span><span class="p">,</span> <span class="s1">&#39;xmr_&#39;</span><span class="p">]</span> <span class="k">for</span> <span class="n">metric</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">&#39;Close&#39;</span><span class="p">]]</span>
<span class="nb">print</span><span class="p">(</span><span class="n">norm_cols</span><span class="p">)</span>
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<pre>[&#39;bt_Close&#39;, &#39;eth_Close&#39;, &#39;dash_Close&#39;, &#39;xmr_Close&#39;]
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">LSTM_training_inputs</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">training_set</span><span class="p">)</span><span class="o">-</span><span class="n">window_len</span><span class="p">):</span>
    <span class="n">temp_set</span> <span class="o">=</span> <span class="n">training_set</span><span class="p">[</span><span class="n">i</span><span class="p">:(</span><span class="n">i</span><span class="o">+</span><span class="n">window_len</span><span class="p">)]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
    <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">norm_cols</span><span class="p">:</span>
        <span class="n">temp_set</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">temp_set</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">/</span><span class="n">temp_set</span><span class="p">[</span><span class="n">col</span><span class="p">]</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="mi">1</span>
    <span class="n">LSTM_training_inputs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">temp_set</span><span class="p">)</span>
<span class="n">LSTM_training_outputs</span> <span class="o">=</span> <span class="p">(</span><span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">values</span><span class="o">/</span><span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">][:</span><span class="o">-</span><span class="n">window_len</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">LSTM_test_inputs</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">test_set</span><span class="p">)</span><span class="o">-</span><span class="n">window_len</span><span class="p">):</span>
    <span class="n">temp_set</span> <span class="o">=</span> <span class="n">test_set</span><span class="p">[</span><span class="n">i</span><span class="p">:(</span><span class="n">i</span><span class="o">+</span><span class="n">window_len</span><span class="p">)]</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
    <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">norm_cols</span><span class="p">:</span>
        <span class="n">temp_set</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span> <span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">temp_set</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">/</span><span class="n">temp_set</span><span class="p">[</span><span class="n">col</span><span class="p">]</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="mi">1</span>
    <span class="n">LSTM_test_inputs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">temp_set</span><span class="p">)</span>
<span class="n">LSTM_test_outputs</span> <span class="o">=</span> <span class="p">(</span><span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">values</span><span class="o">/</span><span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">][:</span><span class="o">-</span><span class="n">window_len</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span>

<span class="nb">print</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">))</span>
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<pre>&lt;class &#39;list&#39;&gt;
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">LSTM_training_inputs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

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

    .dataframe thead th {
        text-align: right;
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</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>bt_Close</th>
      <th>bt_close_off_high</th>
      <th>bt_volatility</th>
      <th>eth_Close</th>
      <th>eth_close_off_high</th>
      <th>eth_volatility</th>
      <th>dash_Close</th>
      <th>dash_volatility</th>
      <th>xmr_Close</th>
      <th>xmr_volatility</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>811</th>
      <td>0.000000</td>
      <td>-0.560641</td>
      <td>0.020292</td>
      <td>0.000000</td>
      <td>-0.418477</td>
      <td>0.025040</td>
      <td>0.000000</td>
      <td>0.090090</td>
      <td>0.000000</td>
      <td>0.194582</td>
    </tr>
    <tr>
      <th>810</th>
      <td>-0.002049</td>
      <td>0.250597</td>
      <td>0.009641</td>
      <td>-0.011498</td>
      <td>0.965898</td>
      <td>0.034913</td>
      <td>-0.029586</td>
      <td>0.056213</td>
      <td>0.069900</td>
      <td>0.132592</td>
    </tr>
    <tr>
      <th>809</th>
      <td>-0.009946</td>
      <td>-0.173865</td>
      <td>0.020827</td>
      <td>0.025190</td>
      <td>-0.317885</td>
      <td>0.060792</td>
      <td>-0.041420</td>
      <td>0.066869</td>
      <td>0.004911</td>
      <td>0.093337</td>
    </tr>
    <tr>
      <th>808</th>
      <td>-0.002855</td>
      <td>-0.474265</td>
      <td>0.012649</td>
      <td>0.006810</td>
      <td>-0.057657</td>
      <td>0.047943</td>
      <td>-0.017751</td>
      <td>0.033846</td>
      <td>0.039209</td>
      <td>0.058405</td>
    </tr>
    <tr>
      <th>807</th>
      <td>-0.005457</td>
      <td>-0.013333</td>
      <td>0.010391</td>
      <td>0.002270</td>
      <td>0.697930</td>
      <td>0.025236</td>
      <td>-0.014793</td>
      <td>0.045181</td>
      <td>0.002822</td>
      <td>0.092133</td>
    </tr>
  </tbody>
</table>
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<p>There are hundreds of similar tables like the above (remember that the model takes 5 previous days and tries to predict the 6th closing price of bitcoin and ether, separately). The next step is to build the LSTM. As the close columns are normalized so that the first value in the window is 0, changes with respect to this point will be predicted.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># easier to work with numpy arrays rather than pandas dataframes</span>
<span class="c1"># especially as we now only have numerical data</span>
<span class="n">LSTM_training_inputs</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">LSTM_training_input</span><span class="p">)</span> <span class="k">for</span> <span class="n">LSTM_training_input</span> <span class="ow">in</span> <span class="n">LSTM_training_inputs</span><span class="p">]</span>
<span class="n">LSTM_training_inputs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">)</span>

<span class="n">LSTM_test_inputs</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)</span> <span class="k">for</span> <span class="n">LSTM_test_inputs</span> <span class="ow">in</span> <span class="n">LSTM_test_inputs</span><span class="p">]</span>
<span class="n">LSTM_test_inputs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">keras.models</span> <span class="k">import</span> <span class="n">Sequential</span>
<span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">Activation</span><span class="p">,</span> <span class="n">Dense</span>
<span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">LSTM</span><span class="p">,</span> <span class="n">LeakyReLU</span> 
<span class="kn">from</span> <span class="nn">keras.layers</span> <span class="k">import</span> <span class="n">Dropout</span>
<span class="kn">from</span> <span class="nn">keras.utils</span> <span class="k">import</span> <span class="n">plot_model</span>

<span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">202</span><span class="p">)</span> 

<span class="k">def</span> <span class="nf">build_model</span><span class="p">(</span><span class="n">inputs</span><span class="p">,</span> <span class="n">output_size</span><span class="p">,</span> <span class="n">neurons</span><span class="p">,</span> <span class="n">activ_func</span><span class="o">=</span><span class="s2">&quot;linear&quot;</span><span class="p">,</span>
                <span class="n">dropout</span><span class="o">=</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">loss</span><span class="o">=</span><span class="s2">&quot;mae&quot;</span><span class="p">,</span> <span class="n">optimizer</span><span class="o">=</span><span class="s2">&quot;adam&quot;</span><span class="p">):</span>
    
    <span class="n">model</span> <span class="o">=</span> <span class="n">Sequential</span><span class="p">()</span>

    <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">LSTM</span><span class="p">(</span><span class="n">neurons</span><span class="p">,</span> <span class="n">input_shape</span><span class="o">=</span><span class="p">(</span><span class="n">inputs</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">inputs</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">2</span><span class="p">])))</span>
    <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Dropout</span><span class="p">(</span><span class="mf">0.25</span><span class="p">))</span>
    <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Dense</span><span class="p">(</span><span class="n">units</span><span class="o">=</span><span class="n">output_size</span><span class="p">))</span>
    <span class="n">model</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">Activation</span><span class="p">(</span><span class="n">activ_func</span><span class="p">))</span>
    <span class="n">model</span><span class="o">.</span><span class="n">compile</span><span class="p">(</span><span class="n">loss</span><span class="o">=</span><span class="n">loss</span><span class="p">,</span> <span class="n">optimizer</span><span class="o">=</span><span class="n">optimizer</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">model</span>
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<pre>Using TensorFlow backend.
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<p>This build_model function is then used for fitting the model into the data. The LSTM layer has been shaped to fit our inputs. For the rest of the specifications in the model, see the references provided in the sub-section 'Long Short-Term Memory (LSTM)'.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># random seed for reproducibility</span>
<span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">202</span><span class="p">)</span>
<span class="c1"># initialise model architecture</span>
<span class="n">eth_model</span> <span class="o">=</span> <span class="n">build_model</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">neurons</span> <span class="o">=</span> <span class="mi">20</span><span class="p">,</span> <span class="n">dropout</span> <span class="o">=</span> <span class="mf">0.35</span><span class="p">)</span> 
<span class="c1"># model output is next price normalised to 5th previous closing price</span>

<span class="c1"># train model on data</span>
<span class="c1"># note: eth_history contains information on the training error per epoch</span>
<span class="n">eth_history</span> <span class="o">=</span> <span class="n">eth_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">,</span> <span class="n">LSTM_training_outputs</span><span class="p">,</span> 
                            <span class="n">epochs</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">batch_size</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="mi">2</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<pre>Epoch 1/50
 - 5s - loss: 0.0965
Epoch 2/50
 - 4s - loss: 0.0721
Epoch 3/50
 - 4s - loss: 0.0697
Epoch 4/50
 - 4s - loss: 0.0664
Epoch 5/50
 - 4s - loss: 0.0628
Epoch 6/50
 - 4s - loss: 0.0620
Epoch 7/50
 - 4s - loss: 0.0614
Epoch 8/50
 - 4s - loss: 0.0607
Epoch 9/50
 - 4s - loss: 0.0575
Epoch 10/50
 - 4s - loss: 0.0578
Epoch 11/50
 - 4s - loss: 0.0578
Epoch 12/50
 - 4s - loss: 0.0591
Epoch 13/50
 - 4s - loss: 0.0575
Epoch 14/50
 - 4s - loss: 0.0572
Epoch 15/50
 - 4s - loss: 0.0576
Epoch 16/50
 - 4s - loss: 0.0558
Epoch 17/50
 - 4s - loss: 0.0544
Epoch 18/50
 - 4s - loss: 0.0541
Epoch 19/50
 - 4s - loss: 0.0555
Epoch 20/50
 - 4s - loss: 0.0561
Epoch 21/50
 - 4s - loss: 0.0568
Epoch 22/50
 - 4s - loss: 0.0557
Epoch 23/50
 - 4s - loss: 0.0538
Epoch 24/50
 - 4s - loss: 0.0557
Epoch 25/50
 - 4s - loss: 0.0558
Epoch 26/50
 - 4s - loss: 0.0541
Epoch 27/50
 - 4s - loss: 0.0549
Epoch 28/50
 - 4s - loss: 0.0545
Epoch 29/50
 - 4s - loss: 0.0547
Epoch 30/50
 - 4s - loss: 0.0541
Epoch 31/50
 - 4s - loss: 0.0533
Epoch 32/50
 - 4s - loss: 0.0545
Epoch 33/50
 - 4s - loss: 0.0542
Epoch 34/50
 - 4s - loss: 0.0553
Epoch 35/50
 - 4s - loss: 0.0534
Epoch 36/50
 - 4s - loss: 0.0548
Epoch 37/50
 - 4s - loss: 0.0537
Epoch 38/50
 - 4s - loss: 0.0542
Epoch 39/50
 - 4s - loss: 0.0522
Epoch 40/50
 - 4s - loss: 0.0556
Epoch 41/50
 - 4s - loss: 0.0547
Epoch 42/50
 - 4s - loss: 0.0540
Epoch 43/50
 - 4s - loss: 0.0537
Epoch 44/50
 - 4s - loss: 0.0546
Epoch 45/50
 - 4s - loss: 0.0552
Epoch 46/50
 - 4s - loss: 0.0534
Epoch 47/50
 - 4s - loss: 0.0537
Epoch 48/50
 - 4s - loss: 0.0537
Epoch 49/50
 - 4s - loss: 0.0549
Epoch 50/50
 - 4s - loss: 0.0526
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pydot_ng</span> <span class="k">as</span> <span class="nn">pydot</span>
<span class="nb">print</span><span class="p">(</span><span class="n">pydot</span><span class="o">.</span><span class="n">find_graphviz</span><span class="p">())</span>
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<pre>{&#39;twopi&#39;: &#39;/anaconda3/bin/twopi&#39;, &#39;sfdp&#39;: &#39;/anaconda3/bin/sfdp&#39;, &#39;fdp&#39;: &#39;/anaconda3/bin/fdp&#39;, &#39;neato&#39;: &#39;/anaconda3/bin/neato&#39;, &#39;dot&#39;: &#39;/anaconda3/bin/dot&#39;, &#39;circo&#39;: &#39;/anaconda3/bin/circo&#39;}
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plot_model</span><span class="p">(</span><span class="n">eth_model</span><span class="p">,</span> <span class="n">to_file</span><span class="o">=</span><span class="s1">&#39;LSTM_ethmodel_plot.png&#39;</span><span class="p">,</span> <span class="n">show_shapes</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">show_layer_names</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="c1">#with this, the model structure is plotted into a new file. </span>
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<p>As it is noticeable, the error decreases throughout time, as expected.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>

<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">eth_history</span><span class="o">.</span><span class="n">epoch</span><span class="p">,</span> <span class="n">eth_history</span><span class="o">.</span><span class="n">history</span><span class="p">[</span><span class="s1">&#39;loss&#39;</span><span class="p">])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Training Error&#39;</span><span class="p">)</span>

<span class="k">if</span> <span class="n">eth_model</span><span class="o">.</span><span class="n">loss</span> <span class="o">==</span> <span class="s1">&#39;mae&#39;</span><span class="p">:</span>
    <span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Mean Absolute Error (MAE)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="c1"># just in case you decided to change the model loss calculation</span>
<span class="k">else</span><span class="p">:</span>
    <span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Model Loss&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;# Epochs&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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Yk1cbT4RBFJFXJFRPZW3+B4upldyZ6WRqaZXRXD8c1edaHDQs3lEBEB6v/gnwlcHvZ8FnBZxOstWnuVVhcR2UudicPdT2qkOJqsnKxgFUAlDhERIPYxjlYnO1NjHCIi4ZQ46qFVAEVE9qbEUY92GWmYaXBcRKSaEkc9UlKM7AyVHRERqRb17bRmdiihdTJ6uPv3zewQIKMxS5wnS06WVgEUEakWVYvDzM4H3ie0Lnj17bjZwD0JiqtJydYqgCIiu0XbVXUncLq7X0do/W+ABcARCYmqicnJSqewVF1VIiIQfeLoTihRwJ6yI04rKUGirioRkT2iTRxz2XvGOITWDZ8V33CapuxMdVWJiFSLdnD8BuB/ZnY10M7M3gCGAKcnLLImJCcrnR1KHCIiQPQrAH4e3EV1JvAysAZ4OVgPvMVrn5VGkcY4RESAKBOHmf3V3W8Ano3Y/md3vykhkTUh2ZlplJRXUV5ZRXqqpr6ISOsW7afgFbVsjxz3aJGqy45ogFxEpJ4WR9jaG2kR63AADADyExJVE5OdtWcVwE7tMpIcjYhIctXXVVXdoshg79aFA5uAiYkIqqmpbnHsUNkREZF61+M4GcDMfuPuP2+ckJqe3V1VKnQoIhL17bi3m1mN4yHuXhXHeJqknMw9XVUiIq1dtImjgtpniafGKZYma0+LQ11VIiLRJo7+Ec8PBG4DXopvOE2TFnMSEdkj2gmAqyI2rTKzicBsYFLco2pisoPEsX2nWhwiIvszm6090C1egTRlmWmpDOvZnimz11BSXln/ASIiLVi063H8y8yeCPt5nlDhw8mJDa/p+Pk3hrJu+y4embY82aGIiCRVtGMcuRHPi4GH3P2tOMfTZB07sAvjhvXggXeXcd7IPvTokJXskEREkiLaMY47Eh1Ic/Czrx/KO0s38/vXP+eeCSOSHY6ISFLUmjhqKDFSI3d/NH7hNG19u7TlmrH9+dt7y7j02IM4qm+nZIckItLo6mpxRFPA0IFWkzgAvnfyIJ6fu5Y7X1rCC989jpQUS3ZIIiKNqtbEUV1uJF7MbBzwF0ITBh9x999FvJ4JPAGMBLYAE9x9pZldAvw4bNfDgaPcfX4844tWdmYat447hB89t4D/zl/HuUf1TkYYIiJJE/XtuGbWycwuN7OfBr+j7qcxs1TgAeAMYChwkZkNjdjtamCbuw8C7gXuBnD3J919hLuPINQKWpmspFHt3CN7cUTvDtz9+ucUq36ViLQy0d6OeyywDLiO0Df+7wDLgu3RGAPkuvtydy8DngHGR+wzHng8ePw8cKqZRfYDXQQ8HeU5EyYlxbj9rGFs2lHKg+8tS3Y4IiKNKtoWx5+B77n7ce5+kbsfD3wX+GuUx/citNxstbXBthr3cfcKoADoErHPBGpJHGZ2rZnNMbM5eXl5UYbVcCMP6sT4ET15eNpy1mzdmfDziYg0FdEmjiFELBtLqFUwKMrjaxpBjiyaWOc+ZnY0sNPdF9V0And/2N1Hufuobt0aZ0L7bWccQqoZf/zf0kY5n4hIUxBt4vgSuDBi2/mEuq+isRboE/a8N7C+tn3MLA3oAGwNe/1CmkA3VbgDO7ThkqP78vLCDWwsKEl2OCIijSLaxHETcL+ZfWxmU8xsJvA34IYoj58NDDaz/maWQSgJTI3YZyp7VhQ8D3jH3R0gWAvkfEJjI03K5cf2o8qdJ2dG1oEUEWmZokoc7j4DGAjcT6hG1X3AoGB7NMdXANcDbwCfAc+6+2Izu9PMzg52mwR0MbNc4BZCZdurnQCsdfcmVyiqb5e2nHpId56etZrSChVAFJGWz4Iv9bEdZDYAqKyh3HqTMGrUKJ8zZ06jnW/al3lcNmkW91xwhOZ1iEizZWZz3X1UfftFezvu02Z2XPD4SmAxsMTMrt6/MFuGsYO6MrBbOx6fsTLZoYiIJFy0YxynAtVf4W8BvkpobsZttR7RipgZE4/rx4K1BcxbvS3Z4YiIJFS0iSPD3cvMrBfQ2d0/dPfFwAEJjK1ZOfeo3mRnpqnVISItXrSJY76Z/RT4BfAKQJBEdiQqsOYmOzON80b25pVPN7C5ULfmikjLFW3iuBo4DGhDKHkAHAs8mYigmqvLjz2I8krn6Zlr6t9ZRKSZivZ23GXufrG7T3T3TcG25939J4kNr3kZ0C2bE4d048mZqyirqEp2OCIiCRFLddyrzOxNM1sc/L66hiKErd4Vx/Vjc2Epry/emOxQREQSItrbcX8P/AR4gdDaGP8GfkRQ+lz2OHFIN/p1aatBchFpsaJtcVwBnOruD7r7q+7+EHA6cGXCImumUlKMy4/tx9xV21i0riDZ4YiIxF20iaMw+IncpruqanDeqN60zUjlMbU6RKQFqjVxmNmA6h9C63G8YGanmdmhZnY68ByhlfokQvusdM49qhdTF6ynYGd5ssMREYmrWtccB3IJrYcRPgAeuQ75KYQKH0qEC0f3ZfLHq5m6YB2XHdsv2eGIiMRNrS0Od09x99Tgd20/qY0ZbHMyvFcHhh7YnmfnrE12KCIicRX17biRzGxYcLeV1GLC6D58uq6AJes1FCQiLUdMicPMuprZDWY2B1gIDE1MWC3D+BE9yUhN4dk5mkkuIi1HvYnDzNLN7Fwz+y+wjtCqf0OB0e5+ZqIDbM46ts3g9GEH8N/567TIk4i0GHUmDjO7H9gAPACsBk5090FAAaE1wqUeE0b3YfvOct5csinZoYiIxEV9LY7vErqz6lfAL9z944RH1MIcN7ArvTq2YcpsdVeJSMtQX+IYSGh98R8DG83s32b2rSiOk0BqivGtkb2ZnpvPuu27kh2OiMh+qzMBuPtKd78z6J46HdgKTAK6AXeZmQbHo3D+yN64w/O6NVdEWoCoWw7uPs3dvw30AC4B+gDzExVYS9Knc1uOH9SF5+auoarKkx2OiMh+ibnLyd1L3P1pdx8H9It/SC3TBaP6sHbbLj5aviXZoYiI7Jf9Gqtw9/XxCqSl+9qwHrTPStOcDhFp9jTI3Uiy0lMZP6IXry3aqMKHItKsKXE0ogtG9aGsooqpC9YlOxQRkQZT4mhEw3u151AVPhSRZi7apWM7m9lvzexVM/sg/CfRAbYkZsaFQeHDqx+bzYr84mSHJCISs7rW4wj3FJAJPAvsTFw4Ld+lxxzErvJK7nv7S06/932uOr4/158yiJys9GSHJiISFXOvf16Bme0Aurl7aeJD2n+jRo3yOXPmJDuMOm0uLOEPry/lublr6Zqdya3jDua8o3qTkmL1HywikgBmNtfdR9W3X7RjHAuB3vsXkoTrnpPFH84/ghe/fzx9Orfh1ucXMv6BD3lj8UYqNUlQRJqwaFscdwIXAf8ENoa/5u6PJia0hmsOLY5wVVXOiwvW8YfXl7K+oIReHdtw6TEHceHoPnRql5Hs8ESklYi2xRFt4ni3lpfc3U+JNbhEa26Jo1pFZRVvfbaJx2es4qPlW8hMS+HsI3oy8bh+DO/VIdnhiUgLF9fE0dw018QRbunGQp74aCUvfLKOXeWVjB3UlVvHHczhvTsmOzQRaaESljjMzIDdI7juXhV7eInVEhJHtYJd5UyZvZqH3l/O1uIyvn5YD2457WAGdc9Odmgi0sLEu6uqF3A/cAKw11ded09taJCJ0pISR7XCknIembaCR6YtZ1d5JeeP7MONXx1Mz45tkh2aiLQQ8b6r6iGgDDgVKAKOAqYC1zU4QolJTlY6N582hPdvPZmJx/XjP/PWcdIf3+OfH65Idmgi0spEmziOA65y9/mEBsQXAFcDP4z2RGY2zsyWmlmumd1Ww+uZZjYleH2mmfULe+1wM/vIzBab2admlhXteVuartmZ/PKsYbz9wxMZ3a8Tv3vtc7YWlyU7LBFpRaJNHJVARfB4u5l1A4qBXtEcbGapwAPAGcBQ4KIaVg+8GtgWrDZ4L3B3cGwaMBm4zt2HAScBrb68bJ/ObfnlWcMorajiyY9XJTscEWlFok0cM4GvB4/fAKYALwDRDiSMAXLdfbm7lwHPAOMj9hkPPB48fh44NRiIPx1YGLRycPct7l4Z5XlbtCEH5HDCkG488fEqSiv0n0REGke0ieMy4P3g8U3AO8Ai4OIoj+8FhK9gtJZ9Wyu793H3CqAA6AIMAdzM3jCzT8zs1ppOYGbXmtkcM5uTl5cXZVjN39Vj+5NXWMpLCzYkOxQRaSWiShzuvt3dtwaPd7n7b9z9J+4e7adVTQWYIm/nqm2fNGAsoXXOxwLfNLNTa4jxYXcf5e6junXrFmVYzd8Jg7syuHs2k6avoCXOyRGRpifasuqZZnaXmS03s4Jg2+lmdn2U51kL9Al73huIXHZ29z7BuEYHYGuw/X13z3f3ncCrhO7qEkKl2q8a25/PNuzQeuYi0iii7aq6FxhO6Ft/9dfaxcB3ozx+NjDYzPqbWQZwIaHbecNNBSYGj88D3vHQV+g3gMPNrG2QUE4ElkR53lbhm0f2onO7DB6dHt9bcysqq7j3zS94fdHG+ncWkVYj2vU4vgkMcvdiM6sCcPd1wcTAerl7RdA6eQNIBR5198VB8cQ57j4VmAT8y8xyCbU0LgyO3WZm9xBKPg686u6vxHCNLV5WeiqXHt2X+97NZUV+Mf27ttvv9ywpr+QHT8/jzSWbSEsx/nnlaL4yuPV0AYpI7aJtcZQRkWSCW3Kj7htx91fdfYi7D3T3u4JttwdJA3cvcffz3X2Qu49x9+Vhx05292HuPtzdaxwcb+0uPfYg0lNS4jIhcEdJORMfncVbn23ip2ccwqDu2Xx38icsWb8jDpGKSHMXbeJ4DnjczPoDmNmBhEqQPJOowCQ23XOyOOuInjw3Zy0FOxs+zSWvsJQL//4xc1dt488TRvCdEwfy2JVjyMlK46rHZrOhYFccoxaR5ijaxPEzYCXwKaFaVV8SGty+IzFhSUNcPbY/u8oreXr26gYdv2brTs5/aAYr8ot5ZOIoxo8I9UT26JDFP68cTXFpBVf+czY7Slr9/EuRVi3a23HL3P0md88GDgBy3P3mYDKfNBFDe7bnuIFdeHzGSsorYyta/PnGHXzrwRls21nO5GuO5qSDu+/1+iE92vPQZSPJ3VzEdyfPpayiyRVFFpFGUufguJn1reWlPqFJ3eDuDft6Kwlx9dj+XP34HF5btJGzj+hJSXkly/KKyN1cxLLNRazcspPCknKKSisoKq2kqLSc4tJKCnaV0zU7g+euO5YhB+TU+N7HD+rK3d86nB8+t4DbXljIn84/guq/AxFpPeq7q2ole26/rW2CXpMrq96anXxwdwZ0bcedLy3hT/9byuqtO6meF5hi0LtTWzq0SSc7M41eHTPIycqhXWYqHdqkc/HRB9GrnjLt3xrZm3Xbd3HPm1+QasY3j+rFUX07kZVe859BeWUVs1du5Z3PNrNofQG/Hj+cwbUkJhFpHupcj8PM5gNZhGpITWbfSXs0xbpRLXE9jli8+ukGHng3l35d2zGoWzaDD8hmUPds+nVpV+sHfCzcnTtfXsITH62issrJTEthdL/OHD+oK8cP6kLPjm2Y9mUeb322mQ++yKOwpIKM1BTSU43u7bP47/ePp0Ob9DhcqYjEU9wWcjKz4YQm5l0AfA48Abzg7k329prWnjgaS2FJObNWbGV6bj4zcrewdFPhXq93zc7klEO6ceqhBzB2UFeWbNjBRQ9/zIlDuvGPy0eRkqJuLpGmJO5Lx5pZCnAacAWh8uinuPsn+xNkoihxJEdeYSkzluWzbvsujh/YlcN6ddgnOTzx0Upuf3ExN546mJtPG5KcQMMUlpTTLiNNSUyE6BNHtDPHAQYTKvdxLDAP2NbA2KSF6paTufsW3tpcdsxBLFxbwF/e/pLhvTpw2tADGim6vc1bvY2HP1jO64s3cnjvjjxw8ZH07tQ2KbGINDd13o5rZp3N7PtmNgv4L6FlY09w95PdXWuWSszMjN+cM5zDe3fglinzWZZX1Gjnrqpy3lyyifMfmsE3/zaD6bn5XDSmL8s2F3HmfdN5b+nmRotFpDmrb3C8BFgB/Av4uKZ93P2dxITWcOqqavrWbd/FWfdNp3O7DP77/ePJzoyl8RubkvJK/jNvHf+YtpzlecX06tiGq8b2Z8LoPmRnprEiv5jvTp7L0k2F/OCUwdw5ohxSAAAVBklEQVR46mBS1XUlrVBcxjjMbCX7rpsRzt19QOzhJZYSR/MwY1k+l02axVcP7c6Dl4yM+zhDcWkFT81czT+mLWdzYSnDerbn2hMG8I3DDiQtde/G9q6ySn7x4iKen7uWrwzuyp8njKBLdmZc4xFp6uI+ON6cKHE0H5Omr+DXLy/h+ycP5MdfOyQu77mtuIzHZqzksRkrKdhVznEDu/C9kwZx/KAu9U5YnDJ7Nb94cTGd22bw4KVHcWTfTlGds7LK+eDLPNZs3cnGgpLQz47QT1FJBbefNZQzD+8Zj8sTSZhEDI6LxN1Vx/cjd3MRD7y7jJysdK47cWCD36tgVzn3v/MlT85czc6ySk4begDfO2lg1B/+ABNG92VYzw5898m5XPXYbF6/6QQOaJ9V73G/ffUzJgXroaSlGAe0z+KA9pkc0iOHFfk7+eGzC+jXpR3De3Vo8PVJdMorqzjngQ/p27ktvz5nOF3Vcow7tTgk6SqrnJumzOelBev5zTnDufSYg2J+j/yiUi6bNIsvNhVy9hE9ue7EgRzco+Ez1HM3F3HmfdMYdVBnnrhqTJ3daO9+vpkrH5vNRWP6cvNpg+naLnOv/fOLSjn7vukATP3B2Bb1QbY8r4hJ01dw/SmDOLBD3VUHGssrCzfw/ac+IcWgU9sM7vrmYYwb3qPRzl9eWUWqWbO8xTvaFke01XFFEiY1xbjngiP46qHd+cWLi/jPvLUxHb+xoIQJf/+IFflF/POK0dw7YcR+JQ2AQd2z+eVZw5iem7+7JVGTzTtK+NFzCzikRw6/PGso3XOy9vnA6Jqdyd8vG8WW4jK+9+QnMRegbKo++CKPcx74kCdnrub6p+Y1meua/PEqenVswys3fIUDO2Zx3eS53DxlPgW7ElvV+YtNhfz8v58y4o7/ccMz82iJX8qrKXFIk5CemsL9Fx/FsQO68KPnFvLG4uiWq12zdSfn/30Gm3aU8sRVR3PCkPitUnjh6D58bdgB/P6Nz1m0rmCf16uqnFueXUBxWQX3XXRkneVcDuvdgbu/dTizVmzl1y/XvvLxsrwivv3EHM6+fzr3vf0lX24qbHIfQO7OI9OWc8U/Z9GzYxt+9vVDmLtqG/e++UVUx+8oKWdXWWIqFeVuLuKj5Vu4+Oi+HHpge/7zveO58dTBTF2wnq/d+wEffJEX1/OVV1bxysINTPj7R5x+7wc8O2ctw3p14OWFG/j7B8vrf4MGWLN1J9f9ay4fL496Hb24U1eVNCnFpRVcOmkmi9ftYNIVo+pcrjZ3cxGXPjKTkopKHr9yDEf06Rj3eLYVl3HGX6bRNjOVl38wlrYZe4YF//7+Mv7fa5/z228exsVH11ZIem93vbKEf0xbwd3fOowJo/ccU1hSzn3v5PLo9BW0yUhlYLds5q/ZDsCAbu0YN6wH44b3YFjPDqzfvovcvCKW5xWzLC9U9Ti/qJRTDz2AC0b1YVD37AZfr7tTVllFZlrNSbCkvJL/+88i/v3JWs4Y3oM/nn8E7TLT+MnzC3l27hqeuGpMnf/PPt+4g0sfmUVmWgoPXnoUh/eO7/+zO19awr8+XslHPz11ry7BhWu3c8uzC8jdXMR5I3tzwymD6dul4RM+d5ZVMGnaCibPXMWmHaX06tiGS485iAmj+9CpbTrXPzWP1xZt4Imrjmbs4K7xuDQAZq3YynWT57K1uIw+ndvw5s0nxqX+XDXdVaXE0WwV7CxnwsMfsWrLTm4/ayjDerZnQLfsveZ6LF5fwOWTZmFmTL5mDIf0aJ+weGYsy+eSR2Zy4eg+/L9zDwdgwZrtfOvBGZw29AD+dslRUZeXr6is4srHZvPx8i08c+2xHNmnIy/MW8fvXvucLcWlXDCyDz8edzBdszPZtKOE/y3ZxBuLNvLR8i1UVjmpKUZl1Z5/sx3bpjOwWzbtMtOYkZtPRZUz6qBOTBjdh28cfuBeia4++UWlXPvEHBasLWB4z/aM7teZMf07M7pfZzq1y2DzjhK+M3ku81Zv56avDuaGUwbv7pbbVVbJ2fdPZ9vOMl698St0z9n3hoL5a7Yz8dFZtElPJTXFyCss5c7xw7hwTHRJtz67yio5+rdvceLB3bnvoiP3eb2kvJJ73/qCf364ksoq59wje/H9kwfRr2u7qM/h7ryxeBO/fnkJ67bv4oQh3bj8mIM4+ZDue839KS6t4JwHPiS/qJSXfjA2LlUJnpm1ml+8uIg+ndpyzVcG8LP/fBr30j1KHEoczVpeYSkX/eNjcjfvmVnePSeTAd3a0b9rO15ZuIHszDQmX3M0A7o1/Bt2tO5+/XMefG8ZD15yFGMHd+XM+6ZTXlHFazeeQIe2sVX63b6zjLPv/5Bd5ZX07tSGeau3M6JPR+44e1itrabtO8t467PN5G4uol+Xtgzsns3Abtl0bpexe5+8wlJe+GQtU2avYXl+MdmZaZw9oiffPXEgfTrX/cG1Ir+YiY/OYnNhCReO7suSDTuYv2b77gW7hhyQzfadoXVc7rngCMYNP3Cf9/hiUyFn3z+dkQd14omrjt7rg/Tj5Vu4+rHZdMnO5MlrjqZdZho3PjOPaV/mM2FUH+4YP6zGb86lFZW8+/lmvtxUxHdOHEhGWu2968/OWcOtzy9kyrXHcPSALrXut2lHCQ+9v4ynZq6mosoZP6In1588qN6/o9VbdvLLqYt4d2keh/TI4dfnDGd0v8617r88r4jx93/IQV3b8vx1xzW4ZVBRWcVvXvmMx2as5IQh3bjvoiPp0CadHzw9jzcWb+Stm0/cr9ZTOCUOJY5mr7yyihX5xSzPK2JZXjHL84pZnh/qojmwQxaPTBzVaPWlyiqqOO+hGazaspPR/TrzzuebmPKdY+v84KjL0o2FnPu3D2mTkcZtZxzCuUf2ittdOO7O7JXbeGb2al5ZuAGAG04dzLe/MqDGD965q7ZxzeOzMTMmTRy1+/bl0opKFq4tYNaKrcxasZXi0gp+fc5wDj2w9tbdlNmr+cm/P+VHpw/h+lMGA/De0s18519z6dO5LZOvPpoeHUKtkcoq5943v+D+d3M5rFcHHrz0KHp3aou7M3fVNl6Yt45XFm7YPaj9vZMGcuu42uf6jL9/OjvLKvnfzSdE1QLcvKOEhz9YzuSZqyirqOKUQw5gWM/2DOyezaBu2QzoFlqGoKS8kr+/v5wH3sslPcW4+bQhTDyuH+mp9Q8Rv7VkE9c8MYfzRvbmD+cdHvPCZ9t3lnH9U/OYnpvPNWP7c9sZh+yevLqxoIRT//QexwzowqQrRsf0vrVR4lDiaLGq/2Ybe/XBFfnFfOOv09hZVsnNXx3CjV8dvF/vt2lHCdmZabRLYLmVDQW7uGPqEl5fvJFB3bO565zhe30bf2PxRm54eh49OmTx+JVjYuq2qYm7c+Mz83l54XqmfOdY8gtLueGZeQw5IIcnrhpT42z8N5ds4pYp80lNNc4f2Zv/LdnEqi07yUpP4WvDevDNI3vx2qcbeXbuGp7+9jEcU0Nr4tO1BZx1/3R+ddZQrji+f0wx5xWW8o9py3l90UbWbNuz8JkZ9O7UhspKZ31BCWcefiA//8bQ3YkvWve8+QV/fftLfn3OcC4Lu9Xc3dm0o5RF6wpYuaWYnWWV7CqvZFdZ8FNeySert7F5Rym/+eZwLhjVZ5/3fviDZfz21c955PJRfDUOBUOVOJQ4JAHeWrKJ6bn5/OLMoc2qntXbn23i9hcXs277Ls4f2Zuffv1QXlqwnl+9tJgjendk0sRRcSuxUlhSzln3TadgVzkFu8o5sm8nHr1idJ2Ld63IL+a6f83li82FHDugC+ce1Ztxw3vsHtcqLq3gzPumU1peyWs3nbDPe93274W8OH89M//vVNpnNXyRsJLySlbkF+9ZbjmvmO07y7j2hAF1DvrXparKufrx2UzPzef2M4eGksX6Ahat20F+Uele+2akppCVnkKbjFTaZqTRqW06//eNQxl5UM0t2/LKKr7+l2mUVFTGZaBciUOJQ2QvO8sq+OvbuTwybTkZaSm7Z9f/9cIjaZMR3xWgF60r4NwHZzC6Xyf+cfmoqAbpKyqrKC6trHXMqPqGhHHDe3DfRUfubnHuKCnn6LveZvyInvzuW4fH9TripWBnOWc/MJ1VW3aSmmIM7p7NsJ4dOKxXe4b36sDg7jm0zUyNqvsr0oxl+Vz8j5lxGShX4lDiEKnR0o2F3PXqZxx8QDa3nXFowlpO+UWldGqbEdf3f+DdXP7wxlLuueAIzj2qNwCPfbiCX720hJeuH8thvZtuSZe8wlLWbd/FIT1y4noLLbB7oPzNm0/goC4N725U4lDiEGlxKqucix7+mCUbdvDajV+hd6c2nHbvB7TLSOXF68cmO7ykiddAuUqOiEiLk5pi3DPhCMzgpinz+WjZFnI3F3FJA+qbtSQ9OmRx41cH8/bnm3lryaaEn0+JQ0Sald6d2vKbc4Yzd9U2vvfUJ7TPSuMslaznyuP7M7h7Ns/OWZPwc6msuog0O+NH9OK9pXn8Z946rjq+f9wH95uj9NQUHr9qTFTLAOwvJQ4RaZbuGD+Mnh2zmHhcv2SH0mT07Ng4pe2VOESkWWqflR63VSMlNhrjEBGRmChxiIhITJQ4REQkJkocIiISEyUOERGJSaMlDjMbZ2ZLzSzXzG6r4fVMM5sSvD7TzPoF2/uZ2S4zmx/8PNRYMYuIyL4a5XZcM0sFHgBOA9YCs81sqrsvCdvtamCbuw8yswuBu4EJwWvL3H1EY8QqIiJ1a6wWxxgg192Xu3sZ8AwwPmKf8cDjwePngVOtsVfqERGRejXWBMBeQHgBlbXA0bXt4+4VZlYAVC/11d/M5gE7gJ+7+7TIE5jZtcC1wdMiM1u6H/F2BfL34/jmStfduui6W5dorjuqapGNlThqajlE1nOvbZ8NQF9332JmI4H/mtkwd9+x147uDwMPxyVYsznRlBZuaXTdrYuuu3WJ53U3VlfVWiB8wdzewPra9jGzNKADsNXdS919C4C7zwWWAfu3zJWIiDRYYyWO2cBgM+tvZhnAhcDUiH2mAhODx+cB77i7m1m3YHAdMxsADAaWN1LcIiISoVG6qoIxi+uBN4BU4FF3X2xmdwJz3H0qMAn4l5nlAlsJJReAE4A7zawCqASuc/etCQ45Ll1ezZCuu3XRdbcucbvuFrl0rIiIJI5mjouISEyUOEREJCZKHGHqK4vSUpjZo2a22cwWhW3rbGZvmtmXwe9OyYwxEcysj5m9a2afmdliM7sx2N6ir93MssxslpktCK77jmB7/6C8z5dBuZ+MZMeaCGaWambzzOzl4Hlrue6VZvZpUKppTrAtLn/rShyBsLIoZwBDgYvMbGhyo0qYx4BxEdtuA95298HA28HzlqYC+KG7HwocA3w/+H/c0q+9FDjF3Y8ARgDjzOwYQmV97g2uexuhsj8t0Y3AZ2HPW8t1A5zs7iPC5m/E5W9diWOPaMqitAju/gGhO9fChZd8eRw4p1GDagTuvsHdPwkeFxL6MOlFC792DykKnqYHPw6cQqi8D7TA6wYws97AN4BHgudGK7juOsTlb12JY4+ayqL0SlIsyXCAu2+A0Acs0D3J8SRUUH35SGAmreDag+6a+cBm4E1CE2m3u3tFsEtL/Xv/M3ArUBU870LruG4IfTn4n5nNDUoyQZz+1hur5EhzEE1ZFGkBzCwb+Ddwk7vvaA21NN29EhhhZh2B/wCH1rRb40aVWGZ2JrDZ3eea2UnVm2vYtUVdd5jj3X29mXUH3jSzz+P1xmpx7BFNWZSWbJOZHQgQ/N6c5HgSwszSCSWNJ939hWBzq7h2AHffDrxHaIynY1DeB1rm3/vxwNlmtpJQ1/MphFogLf26AXD39cHvzYS+LIwhTn/rShx7RFMWpSULL/kyEXgxibEkRNC/PQn4zN3vCXupRV97ULanY/C4DfBVQuM77xIq7wMt8Lrd/afu3tvd+xH69/yOu19CC79uADNrZ2Y51Y+B04FFxOlvXTPHw5jZ1wl9I6kui3JXkkNKCDN7GjiJUJnlTcAvgf8CzwJ9gdXA+Y1Q2qVRmdlYYBrwKXv6vH9GaJyjxV67mR1OaCA0ldCXxWfd/c6g9tszQGdgHnCpu5cmL9LECbqqfuTuZ7aG6w6u8T/B0zTgKXe/y8y6EIe/dSUOERGJibqqREQkJkocIiISEyUOERGJiRKHiIjERIlDRERiosQh0kyYWT8z87DJayJJocQhEiYoPz7YzAaY2Sf17OtmVmxmRWE/tzZWrCLJom8uIoGgHMlBQC6hmcV1Jo7AEe6em9DARJoYtThE9hgOLPHQrNhRRJc4amRmvzKz54OFggrN7BMzOyLs9UPN7D0z2x4srnR22GttzOxPZrbKzArMbHpQKqTaJWa22szyzez/wo4bY2ZzzGyHmW0ys/CyKiJxo8QhrZ6ZXWlm24EPgWODxz8E7g4+2Ps38K3HA88RKm3xFPBfM0sPWjYvAf8jVNb6B8CTZnZwcNwfgZHAccGx4WXBAcYCBwOnArebWXWl278Af3H39sBAQqUlROJOJUdEAmY2jdCH+FZCxeCO9Dr+gZiZA4Xs/aE+wd3fMLNfAePc/Zhg3xRgHXBBsN9zQE93rwpefxpYCtwJFAPHuPuCiPP1A1YAfdx9bbBtFnCPuz9jZh8QKuB3n7vnN/S/g0h91OKQVi1Yg3m7mRUQ+ob/HqEP8IOBbWZ2Uz1vcZS7dwz7eSPstd0LgwUJYi3QM/hZU500AqsILSjUFcgitNBSbTaGPd4JZAePrwaGAJ+b2exgPQqRuFPikFbN3be6e0fgO8AjwePXgbOCRPDn/Xj73eu7BC2O6rUf1gN9gm3V+hJqkeQDJYS6mmLi7l+6+0WEur/uBp4PSmqLxJUSh0jISPYMhh8JzI3He5rZucG8i5uAUuBjQmXci4FbgzGPk4CzgGeCVsijwD1m1jNY8vVYM8us72RmdqmZdQveY3uwuTIO1yGyFyUOkZCRwCfBegWV7r4tyuMWRMzjCG+hvAhMALYBlwHnunu5u5cBZwNnEGph/A243N2rl/b8EaE1Q2YTGm+5m+j+rY4DFptZEaGB8gvdvSTK6xCJmgbHRRIgGBwf5O6XJjsWkXhTi0NERGKixCEiIjFRV5WIiMRELQ4REYmJEoeIiMREiUNERGKixCEiIjFR4hARkZj8f0YpeweR2uqSAAAAAElFTkSuQmCC
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<p>"We've just built an LSTM model to predict tomorrow's Ethereum closing price. Let's see how well it performs. We start by examining its performance on the training set (data before October 2017). That number below the code represents the model's mean absolute error (mae) on the training set after the 50th training iteration (or epoch). Instead of relative changes, we can view the model output as daily closing prices." (Sheehan, 2017)</p>

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<div class="prompt input_prompt">In&nbsp;[25]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">mpl_toolkits.axes_grid1.inset_locator</span> <span class="k">import</span> <span class="n">zoomed_inset_axes</span>
<span class="kn">from</span> <span class="nn">mpl_toolkits.axes_grid1.inset_locator</span> <span class="k">import</span> <span class="n">mark_inset</span>

<span class="n">fig</span><span class="p">,</span> <span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%b %Y&#39;</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Actual&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">eth_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">))</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> 
         <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Predicted&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Training Set: Single Timepoint Prediction&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Ethereum Price ($)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mf">0.15</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">borderaxespad</span><span class="o">=</span><span class="mf">0.</span><span class="p">,</span> <span class="n">prop</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;size&#39;</span><span class="p">:</span> <span class="mi">14</span><span class="p">})</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">annotate</span><span class="p">(</span><span class="s1">&#39;MAE: </span><span class="si">%.4f</span><span class="s1">&#39;</span><span class="o">%</span><span class="k">np</span>.mean(np.abs((np.transpose(eth_model.predict(LSTM_training_inputs))+1)-\
            <span class="p">(</span><span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[</span><span class="n">window_len</span><span class="p">:])</span><span class="o">/</span><span class="p">(</span><span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">]))),</span> 
             <span class="n">xy</span><span class="o">=</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">),</span>  <span class="n">xycoords</span><span class="o">=</span><span class="s1">&#39;axes fraction&#39;</span><span class="p">,</span>
            <span class="n">xytext</span><span class="o">=</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">),</span> <span class="n">textcoords</span><span class="o">=</span><span class="s1">&#39;axes fraction&#39;</span><span class="p">)</span>
<span class="c1"># figure inset code taken from http://akuederle.com/matplotlib-zoomed-up-inset</span>
<span class="n">axins</span> <span class="o">=</span> <span class="n">zoomed_inset_axes</span><span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="mf">3.35</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span> <span class="c1"># zoom-factor: 3.35, location: centre</span>
<span class="n">axins</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">axins</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Actual&#39;</span><span class="p">)</span>
<span class="n">axins</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">eth_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">))</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> 
         <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Predicted&#39;</span><span class="p">)</span>
<span class="n">axins</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2017</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2017</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">1</span><span class="p">)])</span>
<span class="n">axins</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="mi">10</span><span class="p">,</span><span class="mi">60</span><span class="p">])</span>
<span class="n">axins</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
<span class="n">mark_inset</span><span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="n">axins</span><span class="p">,</span> <span class="n">loc1</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">loc2</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">fc</span><span class="o">=</span><span class="s2">&quot;none&quot;</span><span class="p">,</span> <span class="n">ec</span><span class="o">=</span><span class="s2">&quot;0.5&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

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<p>As can be observed, the model is very accurate in the training phase, as expected. This, however, is not very surprising, as the model has access to its error every iteration. The prediction of interest is the one in the test phase, as it will show if the prediction error is so small due to good fit or due to overfitting. For avoiding this problem, a dropout of 0.25 was set in the model.</p>

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<div class="prompt input_prompt">In&nbsp;[26]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="c1">#ax1.set_xticks([datetime.date(2017,i+1,1) for i in range(12)])</span>
<span class="c1">#ax1.set_xticklabels([datetime.date(2017,i+1,1).strftime(&#39;%b %d %Y&#39;)  for i in range(12)])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2017</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%b %Y&#39;</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">2017</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&gt;=</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Actual&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&gt;=</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">eth_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">))</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> 
         <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Predicted&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">annotate</span><span class="p">(</span><span class="s1">&#39;MAE: </span><span class="si">%.4f</span><span class="s1">&#39;</span><span class="o">%</span><span class="k">np</span>.mean(np.abs((np.transpose(eth_model.predict(LSTM_test_inputs))+1)-\
            <span class="p">(</span><span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[</span><span class="n">window_len</span><span class="p">:])</span><span class="o">/</span><span class="p">(</span><span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">]))),</span> 
             <span class="n">xy</span><span class="o">=</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">),</span>  <span class="n">xycoords</span><span class="o">=</span><span class="s1">&#39;axes fraction&#39;</span><span class="p">,</span>
            <span class="n">xytext</span><span class="o">=</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">),</span> <span class="n">textcoords</span><span class="o">=</span><span class="s1">&#39;axes fraction&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Test Set: Single Timepoint Prediction&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">13</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Ethereum Price ($)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">borderaxespad</span><span class="o">=</span><span class="mf">0.</span><span class="p">,</span> <span class="n">prop</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;size&#39;</span><span class="p">:</span> <span class="mi">14</span><span class="p">})</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>

<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">eth_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)))</span>


<span class="n">mape_eth</span> <span class="o">=</span> <span class="p">(</span><span class="mi">100</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">eth_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(((</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">eth_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)))</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">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[</span><span class="n">window_len</span><span class="p">:])</span><span class="o">/</span><span class="p">(</span><span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">])))</span>

<span class="nb">print</span><span class="p">(</span><span class="n">mape_eth</span><span class="p">)</span> 

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;the accuracy in percentage measured as 100 - MAPE for ether using LSTM is </span><span class="si">%.5f</span><span class="s1">&#39;</span><span class="o">%</span><span class="p">(</span><span class="mi">100</span><span class="o">-</span><span class="n">mape_eth</span><span class="p">))</span>

<span class="c1">#the accuracy in percentage measured as 100 - MAPE for ether using LSTM is 95.29775</span>
</pre></div>

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<pre>168
4.73004092482
the accuracy in percentage measured as 100 - MAPE for ether using LSTM is 95.26996
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<p>As it is seen, the LSTM model performs well in the test period, with some weaknesses. First, the model tends to overestimate the future ether price, which can be due to the fact that during the training period ether's price rose incredibly, therefore it expects the trend to continue. Also, in spikes, where big changes take place, the model is not able to capture these behaviors. Now, the same methodology is applied to bitcoin's prices.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># random seed for reproducibility</span>
<span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">202</span><span class="p">)</span>
<span class="c1"># initialise model architecture</span>
<span class="n">bt_model</span> <span class="o">=</span> <span class="n">build_model</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">neurons</span> <span class="o">=</span> <span class="mi">20</span><span class="p">,</span> <span class="n">dropout</span> <span class="o">=</span> <span class="mf">0.25</span><span class="p">)</span>
<span class="c1"># train model on data</span>
<span class="c1"># note: btc_history contains information on the training error per epoch</span>
<span class="n">bt_history</span> <span class="o">=</span> <span class="n">bt_model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">,</span> 
                            <span class="p">(</span><span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">values</span><span class="o">/</span><span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">][:</span><span class="o">-</span><span class="n">window_len</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> 
                            <span class="n">epochs</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span> <span class="n">batch_size</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="mi">2</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<pre>Epoch 1/50
 - 5s - loss: 0.0513
Epoch 2/50
 - 4s - loss: 0.0373
Epoch 3/50
 - 4s - loss: 0.0337
Epoch 4/50
 - 4s - loss: 0.0317
Epoch 5/50
 - 4s - loss: 0.0294
Epoch 6/50
 - 4s - loss: 0.0295
Epoch 7/50
 - 4s - loss: 0.0283
Epoch 8/50
 - 4s - loss: 0.0285
Epoch 9/50
 - 4s - loss: 0.0269
Epoch 10/50
 - 4s - loss: 0.0263
Epoch 11/50
 - 4s - loss: 0.0266
Epoch 12/50
 - 4s - loss: 0.0266
Epoch 13/50
 - 4s - loss: 0.0257
Epoch 14/50
 - 4s - loss: 0.0262
Epoch 15/50
 - 4s - loss: 0.0258
Epoch 16/50
 - 4s - loss: 0.0258
Epoch 17/50
 - 4s - loss: 0.0247
Epoch 18/50
 - 4s - loss: 0.0255
Epoch 19/50
 - 4s - loss: 0.0253
Epoch 20/50
 - 4s - loss: 0.0250
Epoch 21/50
 - 4s - loss: 0.0245
Epoch 22/50
 - 4s - loss: 0.0250
Epoch 23/50
 - 4s - loss: 0.0246
Epoch 24/50
 - 4s - loss: 0.0253
Epoch 25/50
 - 4s - loss: 0.0242
Epoch 26/50
 - 4s - loss: 0.0241
Epoch 27/50
 - 4s - loss: 0.0251
Epoch 28/50
 - 4s - loss: 0.0243
Epoch 29/50
 - 4s - loss: 0.0246
Epoch 30/50
 - 4s - loss: 0.0243
Epoch 31/50
 - 4s - loss: 0.0244
Epoch 32/50
 - 4s - loss: 0.0243
Epoch 33/50
 - 4s - loss: 0.0243
Epoch 34/50
 - 4s - loss: 0.0240
Epoch 35/50
 - 4s - loss: 0.0241
Epoch 36/50
 - 4s - loss: 0.0242
Epoch 37/50
 - 4s - loss: 0.0247
Epoch 38/50
 - 4s - loss: 0.0241
Epoch 39/50
 - 4s - loss: 0.0240
Epoch 40/50
 - 4s - loss: 0.0244
Epoch 41/50
 - 4s - loss: 0.0240
Epoch 42/50
 - 4s - loss: 0.0244
Epoch 43/50
 - 4s - loss: 0.0239
Epoch 44/50
 - 4s - loss: 0.0242
Epoch 45/50
 - 4s - loss: 0.0242
Epoch 46/50
 - 4s - loss: 0.0241
Epoch 47/50
 - 4s - loss: 0.0241
Epoch 48/50
 - 4s - loss: 0.0244
Epoch 49/50
 - 4s - loss: 0.0242
Epoch 50/50
 - 4s - loss: 0.0239
</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">mpl_toolkits.axes_grid1.inset_locator</span> <span class="k">import</span> <span class="n">zoomed_inset_axes</span>
<span class="kn">from</span> <span class="nn">mpl_toolkits.axes_grid1.inset_locator</span> <span class="k">import</span> <span class="n">mark_inset</span>

<span class="n">fig</span><span class="p">,</span> <span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%b %Y&#39;</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Actual&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">bt_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">))</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> 
         <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Predicted&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Training Set: Single Timepoint Prediction&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Bitcoin Price ($)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">annotate</span><span class="p">(</span><span class="s1">&#39;MAE: </span><span class="si">%.4f</span><span class="s1">&#39;</span><span class="o">%</span><span class="k">np</span>.mean(np.abs((np.transpose(bt_model.predict(LSTM_training_inputs))+1)-\
            <span class="p">(</span><span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[</span><span class="n">window_len</span><span class="p">:])</span><span class="o">/</span><span class="p">(</span><span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">]))),</span> 
             <span class="n">xy</span><span class="o">=</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">),</span>  <span class="n">xycoords</span><span class="o">=</span><span class="s1">&#39;axes fraction&#39;</span><span class="p">,</span>
            <span class="n">xytext</span><span class="o">=</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">),</span> <span class="n">textcoords</span><span class="o">=</span><span class="s1">&#39;axes fraction&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">borderaxespad</span><span class="o">=</span><span class="mf">0.</span><span class="p">,</span> <span class="n">prop</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;size&#39;</span><span class="p">:</span> <span class="mi">14</span><span class="p">})</span>
<span class="c1"># figure inset code taken from http://akuederle.com/matplotlib-zoomed-up-inset</span>
<span class="n">axins</span> <span class="o">=</span> <span class="n">zoomed_inset_axes</span><span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="mf">2.52</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mi">400</span><span class="p">,</span> <span class="mi">307</span><span class="p">))</span> <span class="c1"># zoom-factor: 2.52, location: centre</span>
<span class="n">axins</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2013</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">axins</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Actual&#39;</span><span class="p">)</span>
<span class="n">axins</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&lt;</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">bt_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_training_inputs</span><span class="p">))</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">training_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> 
         <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Predicted&#39;</span><span class="p">)</span>
<span class="n">axins</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2017</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">15</span><span class="p">),</span> <span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="mi">2017</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">1</span><span class="p">)])</span>
<span class="n">axins</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="mi">920</span><span class="p">,</span> <span class="mi">1400</span><span class="p">])</span>
<span class="n">axins</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="s1">&#39;&#39;</span><span class="p">)</span>
<span class="n">mark_inset</span><span class="p">(</span><span class="n">ax1</span><span class="p">,</span> <span class="n">axins</span><span class="p">,</span> <span class="n">loc1</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">loc2</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">fc</span><span class="o">=</span><span class="s2">&quot;none&quot;</span><span class="p">,</span> <span class="n">ec</span><span class="o">=</span><span class="s2">&quot;0.5&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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<div class="prompt input_prompt">In&nbsp;[29]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>

<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</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">2017</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">([</span><span class="n">datetime</span><span class="o">.</span><span class="n">date</span><span class="p">(</span><span class="n">i</span><span class="p">,</span><span class="n">j</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%b %Y&#39;</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">2017</span><span class="p">,</span><span class="mi">2019</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">9</span><span class="p">]])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&gt;=</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Actual&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">model_data</span><span class="p">[</span><span class="n">model_data</span><span class="p">[</span><span class="s1">&#39;Date&#39;</span><span class="p">]</span><span class="o">&gt;=</span> <span class="n">split_date</span><span class="p">][</span><span class="s1">&#39;Date&#39;</span><span class="p">][</span><span class="n">window_len</span><span class="p">:]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="p">),</span>
         <span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">bt_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">))</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">])[</span><span class="mi">0</span><span class="p">],</span> 
         <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Predicted&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">annotate</span><span class="p">(</span><span class="s1">&#39;MAE: </span><span class="si">%.4f</span><span class="s1">&#39;</span><span class="o">%</span><span class="k">np</span>.mean(np.abs((np.transpose(bt_model.predict(LSTM_test_inputs))+1)-\
            <span class="p">(</span><span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[</span><span class="n">window_len</span><span class="p">:])</span><span class="o">/</span><span class="p">(</span><span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">]))),</span> 
             <span class="n">xy</span><span class="o">=</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">),</span>  <span class="n">xycoords</span><span class="o">=</span><span class="s1">&#39;axes fraction&#39;</span><span class="p">,</span>
            <span class="n">xytext</span><span class="o">=</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">),</span> <span class="n">textcoords</span><span class="o">=</span><span class="s1">&#39;axes fraction&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Test Set: Single Timepoint Prediction&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">13</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;Bitcoin Price ($)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">borderaxespad</span><span class="o">=</span><span class="mf">0.</span><span class="p">,</span> <span class="n">prop</span><span class="o">=</span><span class="p">{</span><span class="s1">&#39;size&#39;</span><span class="p">:</span> <span class="mi">11</span><span class="p">})</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>

<span class="nb">print</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">bt_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)))</span>

<span class="n">mape_bt</span> <span class="o">=</span> <span class="p">(</span><span class="mi">100</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">bt_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(((</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">bt_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)))</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">test_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[</span><span class="n">window_len</span><span class="p">:])</span><span class="o">/</span><span class="p">(</span><span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="n">window_len</span><span class="p">])))</span>

<span class="nb">print</span><span class="p">(</span><span class="n">mape_bt</span><span class="p">)</span> 

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;the accuracy in percentage measured as 100 - MAPE for bitcoin using LSTM is </span><span class="si">%.5f</span><span class="s1">&#39;</span><span class="o">%</span><span class="p">(</span><span class="mi">100</span><span class="o">-</span><span class="n">mape_bt</span><span class="p">))</span>

<span class="c1">#</span>
</pre></div>

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<pre>168
4.84961391248
the accuracy in percentage measured as 100 - MAPE for bitcoin using LSTM is 95.15039
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<p>After getting the accuracy of LSTM for this time period, the next step is to check the trading strategy based in this algorithm, to calculate the sharp ratio. For that reason, the predicted prices are stored in the files below, in order to be able to work with them in R.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">eth_pred_prices</span> <span class="o">=</span> <span class="p">((</span><span class="n">eth_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)[:</span><span class="o">-</span><span class="mi">1</span><span class="p">][::</span><span class="mi">1</span><span class="p">]</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">*</span>\
                   <span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;eth_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="p">(</span><span class="n">window_len</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)][::</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ceil</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span><span class="o">/</span><span class="nb">float</span><span class="p">(</span><span class="mi">1</span><span class="p">))),</span><span class="mi">1</span><span class="p">))</span>

<span class="n">np</span><span class="o">.</span><span class="n">savetxt</span><span class="p">(</span><span class="s2">&quot;eth_pred_prices_lstm_2_def.csv&quot;</span><span class="p">,</span> <span class="n">eth_pred_prices</span><span class="p">,</span> <span class="n">delimiter</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">)</span> <span class="c1">#we save the predicted values in order to implement the rest of the backtesting for the trading strategy in R, as the language is more flexible. </span>

<span class="nb">print</span><span class="p">(</span><span class="n">eth_pred_prices</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">bt_pred_prices</span> <span class="o">=</span> <span class="p">((</span><span class="n">bt_model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)[:</span><span class="o">-</span><span class="mi">1</span><span class="p">][::</span><span class="mi">1</span><span class="p">]</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">*</span>\
                   <span class="n">test_set</span><span class="p">[</span><span class="s1">&#39;bt_Close&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">[:</span><span class="o">-</span><span class="p">(</span><span class="n">window_len</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)][::</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ceil</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">LSTM_test_inputs</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span><span class="o">/</span><span class="nb">float</span><span class="p">(</span><span class="mi">1</span><span class="p">))),</span><span class="mi">1</span><span class="p">))</span>

<span class="n">np</span><span class="o">.</span><span class="n">savetxt</span><span class="p">(</span><span class="s2">&quot;btc_pred_prices_lstm_2_def.csv&quot;</span><span class="p">,</span> <span class="n">bt_pred_prices</span><span class="p">,</span> <span class="n">delimiter</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="n">bt_pred_prices</span><span class="p">)</span>
<span class="nb">len</span><span class="p">(</span><span class="n">bt_pred_prices</span><span class="p">)</span>
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<pre>167</pre>
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