钢卷仓储吞吐量趋势预测-源码.html

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<title>钢卷仓储吞吐量趋势预测-源码</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
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  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

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

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

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

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">scipy</span> <span class="k">import</span> <span class="n">stats</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">datetime</span> <span class="k">import</span> <span class="n">date</span><span class="p">,</span> <span class="n">timedelta</span><span class="p">,</span> <span class="n">datetime</span>
<span class="kn">import</span> <span class="nn">xgboost</span> <span class="k">as</span> <span class="nn">xgb</span>

<span class="o">%</span><span class="k">matplotlib</span> inline
</pre></div>

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<div class="prompt input_prompt">In&nbsp;[2]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>
<span class="n">rootpath</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;/home/bingo/桌面/sales_forecasting/steel_storage_throughput_prediction&quot;</span>
<span class="n">os</span><span class="o">.</span><span class="n">chdir</span><span class="p">(</span><span class="n">rootpath</span><span class="p">)</span>
</pre></div>

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<h3 id="&#35757;&#32451;&#38598;&#25972;&#29702;&#20989;&#25968;">&#35757;&#32451;&#38598;&#25972;&#29702;&#20989;&#25968;<a class="anchor-link" href="#&#35757;&#32451;&#38598;&#25972;&#29702;&#20989;&#25968;">&#182;</a></h3><ul>
<li>selectData:加载原始数据，剔除无效数据</li>
<li>loadData:加载数据整理为时间表</li>
</ul>

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<h4 id="&#28165;&#27927;&#25968;&#25454;">&#28165;&#27927;&#25968;&#25454;<a class="anchor-link" href="#&#28165;&#27927;&#25968;&#25454;">&#182;</a></h4><ul>
<li>预测任务<ul>
<li>1.按照两大类货品类型（冷卷、热卷），分别预测未来4个周钢铁的周入库量和周出库量（重量）；</li>
<li>2.按照两大类货品类型（冷卷、热卷），分别预测未来i天的日入库量和日出库量（重量）。</li>
</ul>
</li>
<li>只有产品名称是热卷和圆钢为热卷类型，其余均为冷卷类型</li>
<li>整理目标：<ul>
<li>仅筛选出包含冷卷和热卷两种货品的数据集，添加新列表示冷卷或热卷</li>
<li>丢弃，数量=0而重量&gt;0 重量=0而数量&gt;0的数据</li>
</ul>
</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_item</span><span class="p">(</span><span class="n">dataset</span><span class="p">,</span> <span class="n">target_col</span><span class="p">,</span> <span class="n">item_list</span><span class="p">,</span> <span class="n">new_col</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="n">dataset</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">item_list</span><span class="p">:</span>
        <span class="n">temp</span> <span class="o">=</span> <span class="n">dataset</span><span class="p">[</span><span class="n">dataset</span><span class="p">[</span><span class="n">target_col</span><span class="p">]</span> <span class="o">==</span> <span class="n">item</span><span class="p">]</span>
        <span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">df</span><span class="p">,</span> <span class="n">temp</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">new_col</span><span class="p">:</span>
        <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">new_col</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
            <span class="n">df</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">item</span>
    <span class="k">return</span> <span class="n">df</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">selectData</span><span class="p">(</span><span class="n">inpath</span><span class="p">,</span> <span class="n">extpath</span><span class="p">):</span>
    <span class="c1"># 读取原始数据</span>
    <span class="n">df_train_in</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">inpath</span><span class="p">)</span>
    <span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">extpath</span><span class="p">)</span>
    <span class="c1"># 剔除无效数据</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
    <span class="n">dropind</span> <span class="o">=</span> <span class="n">df_train_in</span><span class="p">[</span><span class="n">df_train_in</span><span class="p">[</span><span class="s2">&quot;r2019&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">index</span>
    <span class="n">df_train_in</span> <span class="o">=</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">dropind</span><span class="p">)</span>
    <span class="n">dropind</span> <span class="o">=</span> <span class="n">df_train_in</span><span class="p">[</span><span class="n">df_train_in</span><span class="p">[</span><span class="s2">&quot;r2018&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">index</span>
    <span class="n">df_train_in</span> <span class="o">=</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">dropind</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
    <span class="n">dropind</span> <span class="o">=</span> <span class="n">df_train_ext</span><span class="p">[</span><span class="n">df_train_ext</span><span class="p">[</span><span class="s2">&quot;c2019&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">index</span>
    <span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">dropind</span><span class="p">)</span>
    <span class="n">dropind</span> <span class="o">=</span> <span class="n">df_train_ext</span><span class="p">[</span><span class="n">df_train_ext</span><span class="p">[</span><span class="s2">&quot;c2018&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">index</span>
    <span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">dropind</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>

    <span class="c1"># 设置种类</span>
    <span class="n">cool_col</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;冷卷&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">:</span> <span class="mi">0</span><span class="p">}</span>
    <span class="n">hot_col</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;热卷&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">}</span>

    <span class="n">hot_in</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;热卷&quot;</span><span class="p">,</span> <span class="s2">&quot;圆钢&quot;</span><span class="p">]</span>
    <span class="n">cool_in</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">df_train_in</span><span class="p">[</span><span class="s2">&quot;r2017&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">hot_in</span><span class="p">)</span>

    <span class="n">train_in_hot</span> <span class="o">=</span> <span class="n">get_item</span><span class="p">(</span><span class="n">df_train_in</span><span class="p">,</span> <span class="s2">&quot;r2017&quot;</span><span class="p">,</span> <span class="n">hot_in</span><span class="p">,</span> <span class="n">hot_col</span><span class="p">)</span>
    <span class="n">train_in_cool</span> <span class="o">=</span> <span class="n">get_item</span><span class="p">(</span><span class="n">df_train_in</span><span class="p">,</span> <span class="s2">&quot;r2017&quot;</span><span class="p">,</span> <span class="n">cool_in</span><span class="p">,</span> <span class="n">cool_col</span><span class="p">)</span>
    <span class="n">train_in_both</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">train_in_hot</span><span class="p">,</span> <span class="n">train_in_cool</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="k">del</span> <span class="n">train_in_hot</span><span class="p">,</span> <span class="n">train_in_cool</span>

    <span class="n">hot_ext</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;热卷&quot;</span><span class="p">,</span> <span class="s2">&quot;圆钢&quot;</span><span class="p">]</span>
    <span class="n">cool_ext</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">df_train_ext</span><span class="p">[</span><span class="s2">&quot;c2017&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">())</span> <span class="o">-</span> <span class="nb">set</span><span class="p">(</span><span class="n">hot_ext</span><span class="p">)</span>

    <span class="n">train_ext_hot</span> <span class="o">=</span> <span class="n">get_item</span><span class="p">(</span><span class="n">df_train_ext</span><span class="p">,</span> <span class="s2">&quot;c2017&quot;</span><span class="p">,</span> <span class="n">hot_ext</span><span class="p">,</span> <span class="n">hot_col</span><span class="p">)</span>
    <span class="n">train_ext_cool</span> <span class="o">=</span> <span class="n">get_item</span><span class="p">(</span><span class="n">df_train_ext</span><span class="p">,</span> <span class="s2">&quot;c2017&quot;</span><span class="p">,</span> <span class="n">cool_ext</span><span class="p">,</span> <span class="n">cool_col</span><span class="p">)</span>
    <span class="n">train_ext_both</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">train_ext_hot</span><span class="p">,</span> <span class="n">train_ext_cool</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="k">del</span> <span class="n">train_ext_cool</span><span class="p">,</span> <span class="n">train_ext_hot</span>

    <span class="c1"># 出入库数据集样本数</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;train_in samples: &quot;</span><span class="p">,</span> <span class="n">train_in_both</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;train_ext samples: &quot;</span><span class="p">,</span> <span class="n">train_ext_both</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>

    <span class="c1"># 保存</span>
    <span class="n">train_in_both</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">&quot;data/train_in.csv&quot;</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
    <span class="n">train_ext_both</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">&quot;data/train_ext.csv&quot;</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;selecting data Done!&quot;</span><span class="p">)</span>
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<h4 id="&#25968;&#25454;&#36716;&#25442;">&#25968;&#25454;&#36716;&#25442;<a class="anchor-link" href="#&#25968;&#25454;&#36716;&#25442;">&#182;</a></h4><ul>
<li>整理目标<ul>
<li>转换为储户id-产品id-日期格式三层索引,重量为训练值，做为训练集格式</li>
<li>无记录时间记出入库重量为0</li>
<li>补齐中断的缺失时间，时间范围为(2014-02-24,2018-01-28)</li>
<li>转换为储户id-产品id-日期格式三层索引,数量为训练值，做为训练集格式</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">loadData</span><span class="p">(</span><span class="n">in_path</span><span class="p">,</span> <span class="n">ext_path</span><span class="p">,</span> <span class="n">endtime</span><span class="o">=</span><span class="s2">&quot;2018-1-28&quot;</span><span class="p">):</span>
    <span class="n">starttime</span> <span class="o">=</span> <span class="n">date</span><span class="p">(</span><span class="mi">2014</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">24</span><span class="p">)</span>
    <span class="n">endtime</span> <span class="o">=</span> <span class="n">datetime</span><span class="o">.</span><span class="n">strptime</span><span class="p">(</span><span class="n">endtime</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="c1"># 进口重量训练集</span>
    <span class="n">dtypes</span> <span class="o">=</span> <span class="p">{</span>
        <span class="s2">&quot;r2014&quot;</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
        <span class="s2">&quot;r2015&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
        <span class="s2">&quot;r2019&quot;</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
        <span class="s2">&quot;type_id&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
    <span class="p">}</span>
    <span class="n">use_cols</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">10</span><span class="p">]</span>
    <span class="n">train_in</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">in_path</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtypes</span><span class="p">,</span> <span class="n">usecols</span><span class="o">=</span><span class="n">use_cols</span><span class="p">)</span>

    <span class="n">train_in</span><span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">]</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">train_in</span><span class="p">[</span><span class="s2">&quot;r2014&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">:</span><span class="mi">10</span><span class="p">]))</span>

    <span class="c1"># 选择数据列，更改列名</span>
    <span class="n">select_col</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;r2015&quot;</span><span class="p">,</span> <span class="s2">&quot;r2019&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="n">new_names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;store_id&quot;</span><span class="p">,</span> <span class="s2">&quot;sales&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="n">train_in</span> <span class="o">=</span> <span class="n">train_in</span><span class="p">[</span><span class="n">select_col</span><span class="p">]</span>

    <span class="n">train_in</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">new_names</span>

    <span class="c1"># 补全2014-2-24 2018-01-28日期内，缺失的时间及记录</span>
    <span class="n">temp</span> <span class="o">=</span> <span class="n">train_in</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">,</span> <span class="s2">&quot;date&quot;</span><span class="p">])[</span>
        <span class="p">[</span><span class="s2">&quot;sales&quot;</span><span class="p">]]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">unstack</span><span class="p">(</span><span class="n">level</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">temp</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>

    <span class="c1"># 2014-02-24为周一，2018-01-28为周日</span>
    <span class="n">train_in_all</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="n">temp</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
                                <span class="n">columns</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">starttime</span><span class="p">,</span> <span class="n">endtime</span><span class="p">))</span>
    <span class="n">train_in_all</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

    <span class="c1"># 进口数量训练集</span>
    <span class="n">dtypes</span> <span class="o">=</span> <span class="p">{</span>
        <span class="s2">&quot;r2014&quot;</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
        <span class="s2">&quot;r2015&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
        <span class="s2">&quot;r2018&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
        <span class="s2">&quot;type_id&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
    <span class="p">}</span>
    <span class="n">use_cols</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">10</span><span class="p">]</span>
    <span class="n">train_in</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">in_path</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtypes</span><span class="p">,</span> <span class="n">usecols</span><span class="o">=</span><span class="n">use_cols</span><span class="p">)</span>

    <span class="n">train_in</span><span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">]</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">train_in</span><span class="p">[</span><span class="s2">&quot;r2014&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">:</span><span class="mi">10</span><span class="p">]))</span>

    <span class="c1"># 选择数据列，更改列名</span>
    <span class="n">select_col</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;r2015&quot;</span><span class="p">,</span> <span class="s2">&quot;r2018&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="n">new_names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;store_id&quot;</span><span class="p">,</span> <span class="s2">&quot;nums&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="n">train_in</span> <span class="o">=</span> <span class="n">train_in</span><span class="p">[</span><span class="n">select_col</span><span class="p">]</span>

    <span class="n">train_in</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">new_names</span>

    <span class="c1"># 补全2014-2-24 2018-01-28日期内，缺失的时间及记录</span>
    <span class="n">temp</span> <span class="o">=</span> <span class="n">train_in</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">,</span> <span class="s2">&quot;date&quot;</span><span class="p">])[</span>
        <span class="p">[</span><span class="s2">&quot;nums&quot;</span><span class="p">]]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">unstack</span><span class="p">(</span><span class="n">level</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">temp</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>

    <span class="c1"># 2014-02-24为周一，2018-01-28为周日</span>
    <span class="n">train_in_all_nums</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="n">temp</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
                                     <span class="n">columns</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">starttime</span><span class="p">,</span> <span class="n">endtime</span><span class="p">))</span>
    <span class="n">train_in_all_nums</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

    <span class="c1"># 出口重量训练集</span>
    <span class="n">dtypes</span> <span class="o">=</span> <span class="p">{</span>
        <span class="s2">&quot;c2014&quot;</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
        <span class="s2">&quot;c2015&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
        <span class="s2">&quot;c2019&quot;</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
        <span class="s2">&quot;type_id&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
    <span class="p">}</span>
    <span class="n">use_cols</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">10</span><span class="p">]</span>
    <span class="n">train_ext</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">ext_path</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtypes</span><span class="p">,</span> <span class="n">usecols</span><span class="o">=</span><span class="n">use_cols</span><span class="p">)</span>

    <span class="n">train_ext</span><span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">]</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">train_ext</span><span class="p">[</span><span class="s2">&quot;c2014&quot;</span><span class="p">]</span><span class="o">.</span>
                                       <span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="nb">str</span><span class="o">.</span><span class="n">isdigit</span><span class="p">,</span> <span class="n">x</span><span class="p">))[:</span><span class="mi">8</span><span class="p">])))</span>

    <span class="n">select_col</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;c2015&quot;</span><span class="p">,</span> <span class="s2">&quot;c2019&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="n">new_names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;store_id&quot;</span><span class="p">,</span> <span class="s2">&quot;sales&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">]</span>

    <span class="n">train_ext</span> <span class="o">=</span> <span class="n">train_ext</span><span class="p">[</span><span class="n">select_col</span><span class="p">]</span>
    <span class="n">train_ext</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">new_names</span>

    <span class="n">temp</span> <span class="o">=</span> <span class="n">train_ext</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">,</span> <span class="s2">&quot;date&quot;</span><span class="p">])[</span>
        <span class="p">[</span><span class="s2">&quot;sales&quot;</span><span class="p">]]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">unstack</span><span class="p">(</span><span class="n">level</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">temp</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>

    <span class="n">train_ext_all</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="n">temp</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
                                 <span class="n">columns</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">starttime</span><span class="p">,</span> <span class="n">endtime</span><span class="p">))</span>
    <span class="n">train_ext_all</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

    <span class="c1"># 出口数量集</span>
    <span class="n">dtypes</span> <span class="o">=</span> <span class="p">{</span>
        <span class="s2">&quot;c2014&quot;</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
        <span class="s2">&quot;c2015&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
        <span class="s2">&quot;c2018&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
        <span class="s2">&quot;type_id&quot;</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
    <span class="p">}</span>
    <span class="n">use_cols</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">10</span><span class="p">]</span>
    <span class="n">train_ext</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">ext_path</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtypes</span><span class="p">,</span> <span class="n">usecols</span><span class="o">=</span><span class="n">use_cols</span><span class="p">)</span>

    <span class="n">train_ext</span><span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">]</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">train_ext</span><span class="p">[</span><span class="s2">&quot;c2014&quot;</span><span class="p">]</span><span class="o">.</span>
                                       <span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="nb">str</span><span class="o">.</span><span class="n">isdigit</span><span class="p">,</span> <span class="n">x</span><span class="p">))[:</span><span class="mi">8</span><span class="p">])))</span>

    <span class="n">select_col</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;c2015&quot;</span><span class="p">,</span> <span class="s2">&quot;c2018&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="n">new_names</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;date&quot;</span><span class="p">,</span> <span class="s2">&quot;store_id&quot;</span><span class="p">,</span> <span class="s2">&quot;nums&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="n">train_ext</span> <span class="o">=</span> <span class="n">train_ext</span><span class="p">[</span><span class="n">select_col</span><span class="p">]</span>
    <span class="n">train_ext</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">new_names</span>

    <span class="n">temp</span> <span class="o">=</span> <span class="n">train_ext</span><span class="o">.</span><span class="n">groupby</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span> <span class="s2">&quot;type_id&quot;</span><span class="p">,</span> <span class="s2">&quot;date&quot;</span><span class="p">])[</span>
        <span class="p">[</span><span class="s2">&quot;nums&quot;</span><span class="p">]]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">.</span><span class="n">unstack</span><span class="p">(</span><span class="n">level</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">temp</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">temp</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">get_level_values</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>

    <span class="n">train_ext_all_nums</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">temp</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="n">temp</span><span class="o">.</span><span class="n">index</span><span class="p">,</span>
                                      <span class="n">columns</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">starttime</span><span class="p">,</span> <span class="n">endtime</span><span class="p">))</span>
    <span class="n">train_ext_all_nums</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    
    <span class="c1"># 保存数据</span>
    <span class="n">train_in_all</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">&quot;data/train_in_all.csv&quot;</span><span class="p">)</span>
    <span class="n">train_ext_all</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">&quot;data/train_ext_all.csv&quot;</span><span class="p">)</span>
    <span class="n">train_in_all_nums</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">&quot;data/train_in_all_nums.csv&quot;</span><span class="p">)</span>
    <span class="n">train_ext_all_nums</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="s2">&quot;data/train_ext_all_nums.csv&quot;</span><span class="p">)</span>
    
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;loading data Done!&quot;</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">train_in_all</span><span class="p">,</span> <span class="n">train_ext_all</span><span class="p">,</span> <span class="n">train_in_all_nums</span><span class="p">,</span> <span class="n">train_ext_all_nums</span>
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<h4 id="&#20351;&#29992;">&#20351;&#29992;<a class="anchor-link" href="#&#20351;&#29992;">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">old_in</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;data_org/trainData_IN.csv&quot;</span>
<span class="n">old_ext</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;data_org/trainData_EXT.csv&quot;</span>
<span class="n">new_in</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;data_org/testData4_IN.csv&quot;</span>
<span class="n">new_ext</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;data_org/testData4_EXT.csv&quot;</span>
<span class="c1"># 合并的原始数据集位置</span>
<span class="n">inpath</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;data_org/train_IN.csv&quot;</span>
<span class="n">extpath</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;data_org/train_EXT.csv&quot;</span>

<span class="n">in1</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">old_in</span><span class="p">)</span>
<span class="n">ext1</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">old_ext</span><span class="p">)</span>
<span class="n">in2</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">new_in</span><span class="p">)</span>
<span class="n">ext2</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">new_ext</span><span class="p">)</span>

<span class="n">in3</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">in1</span><span class="p">,</span> <span class="n">in2</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">ext3</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">ext1</span><span class="p">,</span> <span class="n">ext2</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">in3</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="n">inpath</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">ext3</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="n">extpath</span><span class="p">,</span> <span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;in1 shape: &quot;</span><span class="p">,</span><span class="n">in1</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;in2 shape: &quot;</span><span class="p">,</span> <span class="n">in2</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;in3 shape: &quot;</span><span class="p">,</span> <span class="n">in3</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>in1 shape:  (332937, 9)
in2 shape:  (14713, 9)
in3 shape:  (347650, 9)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># 合并的原始数据集位置</span>
<span class="n">inpath</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;data_org/train_IN.csv&quot;</span>
<span class="n">extpath</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;data_org/train_EXT.csv&quot;</span>
<span class="c1"># 训练数据集位置</span>
<span class="n">in_path</span> <span class="o">=</span> <span class="s2">&quot;data/train_in.csv&quot;</span>
<span class="n">ext_path</span> <span class="o">=</span> <span class="s2">&quot;data/train_ext.csv&quot;</span>
<span class="n">endtime</span> <span class="o">=</span> <span class="s2">&quot;2018-6-17&quot;</span>

<span class="n">selectData</span><span class="p">(</span><span class="n">inpath</span><span class="p">,</span> <span class="n">extpath</span><span class="p">)</span>
<span class="n">train_in_all</span><span class="p">,</span> <span class="n">train_ext_all</span><span class="p">,</span> <span class="n">train_in_all_nums</span><span class="p">,</span> <span class="n">train_ext_all_nums</span> <span class="o">=</span> <span class="n">loadData</span><span class="p">(</span>
    <span class="n">in_path</span><span class="p">,</span> <span class="n">ext_path</span><span class="p">,</span> <span class="n">endtime</span><span class="o">=</span><span class="n">endtime</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;train_in_all shape: &quot;</span><span class="p">,</span> <span class="n">train_in_all</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>df_train_in shape:  (347650, 9)
df_train_in shape:  (346906, 9)
df_train_ext shape:  (425405, 9)
df_train_ext shape:  (425359, 9)
train_in samples:  (346906, 11)
train_ext samples:  (425359, 11)
selecting data Done!
loading data Done!
train_in_all shape:  (1386, 1575)
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<h3 id="&#29305;&#24449;&#24037;&#31243;">&#29305;&#24449;&#24037;&#31243;<a class="anchor-link" href="#&#29305;&#24449;&#24037;&#31243;">&#182;</a></h3><ul>
<li>滑窗选取时间窗，提取时间窗范围的统计量作为特征</li>
<li>有大量稀疏值，可以选择合并，可有效降低误差</li>
<li>数据存在异方差性，取log1p减少异方差，可降低误差</li>
<li>滑动平均平滑原始数据，可降低误差</li>
<li>周数据：截取时间段-&gt;/1000-&gt;ewm-&gt;merge-&gt;np.log1p-&gt;resample<ul>
<li>周数据预测使用累计方式计算，然后逐次相减</li>
<li>resample代表按1周、2周、3周、4周重采样</li>
</ul>
</li>
<li>天数据：截取时间段-&gt;/1000-&gt;ewm-&gt;merge-&gt;np.log1p</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># 合并含有大量0值的行</span>
<span class="k">def</span> <span class="nf">merge_zeros_cols</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">merge_end</span><span class="o">=</span><span class="mi">500</span><span class="p">,</span> <span class="n">merge_step</span><span class="o">=</span><span class="mi">50</span><span class="p">):</span>
    <span class="n">freq</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">freqstr</span>
    <span class="n">notzeros</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
    <span class="n">merge_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">merge_end</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span><span class="n">merge_step</span><span class="p">)</span>
    <span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span>
    <span class="n">df_</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">notzeros</span><span class="o">&gt;=</span><span class="n">merge_end</span><span class="p">]</span><span class="o">.</span><span class="n">set_index</span><span class="p">(</span><span class="s2">&quot;type_id&quot;</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">merge_list</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]):</span>
        <span class="n">ind</span> <span class="o">=</span> <span class="p">(</span><span class="n">notzeros</span><span class="o">&gt;=</span><span class="n">value</span><span class="p">)</span><span class="o">&amp;</span><span class="p">(</span><span class="n">notzeros</span><span class="o">&lt;</span><span class="n">merge_list</span><span class="p">[</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">])</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">ind</span><span class="p">,:]</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s2">&quot;type_id&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
        <span class="n">tmp</span><span class="p">[</span><span class="s2">&quot;store_id&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">merge_list</span><span class="p">[</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">]</span>
        <span class="n">df_</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">df_</span><span class="p">,</span><span class="n">tmp</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">df_</span> <span class="o">=</span> <span class="n">df_</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span>
    <span class="n">df_</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DatetimeIndex</span><span class="p">(</span><span class="n">df_</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span><span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">df_</span>
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<h4 id="&#21608;&#25968;&#25454;&#22788;&#29702;">&#21608;&#25968;&#25454;&#22788;&#29702;<a class="anchor-link" href="#&#21608;&#25968;&#25454;&#22788;&#29702;">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">span</span><span class="o">=</span><span class="mi">28</span>

<span class="n">df_train_in</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;data/train_in_all.csv&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span><span class="o">/</span><span class="mi">1000</span>
<span class="n">df_train_in</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df_train_in</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df_train_in</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;date&quot;</span>

<span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;data/train_ext_all.csv&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span><span class="o">/</span><span class="mi">1000</span>
<span class="n">df_train_ext</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df_train_ext</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df_train_ext</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;date&quot;</span>

<span class="n">df_train_in_nums</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;data/train_in_all_nums.csv&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span><span class="o">/</span><span class="mi">1000</span>
<span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;date&quot;</span>

<span class="n">df_train_ext_nums</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;data/train_ext_all_nums.csv&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span><span class="o">/</span><span class="mi">1000</span>
<span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;date&quot;</span>

<span class="n">df_train_in</span> <span class="o">=</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">ewm</span><span class="p">(</span><span class="n">span</span><span class="o">=</span><span class="n">span</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">ewm</span><span class="p">(</span><span class="n">span</span><span class="o">=</span><span class="n">span</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="n">df_train_in_nums</span> <span class="o">=</span> <span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">ewm</span><span class="p">(</span><span class="n">span</span><span class="o">=</span><span class="n">span</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="n">df_train_ext_nums</span> <span class="o">=</span> <span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">ewm</span><span class="p">(</span><span class="n">span</span><span class="o">=</span><span class="n">span</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext_shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in_nums shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext_nums shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>df_train_in shape:  (1386, 1575)
df_train_ext_shape:  (1383, 1575)
df_train_in_nums shape:  (1386, 1575)
df_train_ext_nums shape:  (1383, 1575)
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">merge_end</span> <span class="o">=</span> <span class="mi">600</span> 
<span class="n">merge_step</span> <span class="o">=</span> <span class="mi">600</span> 

<span class="n">tmp_in</span> <span class="o">=</span> <span class="n">merge_zeros_cols</span><span class="p">(</span><span class="n">df_train_in</span><span class="p">,</span> <span class="n">merge_end</span><span class="p">,</span> <span class="n">merge_step</span><span class="p">)</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_in_transpose</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log1p</span><span class="p">(</span><span class="n">tmp_in</span><span class="p">)</span>

<span class="n">tmp_ext</span> <span class="o">=</span> <span class="n">merge_zeros_cols</span><span class="p">(</span><span class="n">df_train_ext</span><span class="p">,</span> <span class="n">merge_end</span><span class="p">,</span> <span class="n">merge_step</span><span class="p">)</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_ext_transpose</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log1p</span><span class="p">(</span><span class="n">tmp_ext</span><span class="p">)</span>

<span class="n">tmp_in_nums</span> <span class="o">=</span> <span class="n">merge_zeros_cols</span><span class="p">(</span><span class="n">df_train_in_nums</span><span class="p">,</span> <span class="n">merge_end</span><span class="p">,</span> <span class="n">merge_step</span><span class="p">)</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_in_nums_transpose</span> <span class="o">=</span> <span class="n">tmp_in_nums</span>  

<span class="n">tmp_ext_nums</span> <span class="o">=</span> <span class="n">merge_zeros_cols</span><span class="p">(</span><span class="n">df_train_ext_nums</span><span class="p">,</span> <span class="n">merge_end</span><span class="p">,</span> <span class="n">merge_step</span><span class="p">)</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_ext_nums_transpose</span> <span class="o">=</span> <span class="n">tmp_ext_nums</span>  

<span class="c1"># 按周重采样</span>
<span class="n">df_train_in_W</span> <span class="o">=</span> <span class="n">df_train_in_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_in_2W</span> <span class="o">=</span> <span class="n">df_train_in_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;2W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_in_3W</span> <span class="o">=</span> <span class="n">df_train_in_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;3W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_in_4W</span> <span class="o">=</span> <span class="n">df_train_in_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;4W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>

<span class="n">df_train_ext_W</span> <span class="o">=</span> <span class="n">df_train_ext_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_ext_2W</span> <span class="o">=</span> <span class="n">df_train_ext_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;2W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_ext_3W</span> <span class="o">=</span> <span class="n">df_train_ext_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;3W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_ext_4W</span> <span class="o">=</span> <span class="n">df_train_ext_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;4W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>

<span class="c1"># 数量重采样</span>
<span class="n">df_train_in_nums_W</span> <span class="o">=</span> <span class="n">df_train_in_nums_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_in_nums_2W</span> <span class="o">=</span> <span class="n">df_train_in_nums_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;2W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_in_nums_3W</span> <span class="o">=</span> <span class="n">df_train_in_nums_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;3W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_in_nums_4W</span> <span class="o">=</span> <span class="n">df_train_in_nums_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;4W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>

<span class="n">df_train_ext_nums_W</span> <span class="o">=</span> <span class="n">df_train_ext_nums_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_ext_nums_2W</span> <span class="o">=</span> <span class="n">df_train_ext_nums_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;2W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_ext_nums_3W</span> <span class="o">=</span> <span class="n">df_train_ext_nums_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;3W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
<span class="n">df_train_ext_nums_4W</span> <span class="o">=</span> <span class="n">df_train_ext_nums_transpose</span><span class="o">.</span><span class="n">resample</span><span class="p">(</span>
    <span class="s2">&quot;4W&quot;</span><span class="p">,</span> <span class="n">closed</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;right&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in_W shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in_W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext_W shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext_W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in_nums_W shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in_nums_W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext_nums_W shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext_nums_W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>df_train_in_W shape:  (650, 225)
df_train_ext_W shape:  (641, 225)
df_train_in_nums_W shape:  (650, 225)
df_train_ext_nums_W shape:  (641, 225)
</pre>
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<h4 id="&#22825;&#25968;&#25454;&#22788;&#29702;">&#22825;&#25968;&#25454;&#22788;&#29702;<a class="anchor-link" href="#&#22825;&#25968;&#25454;&#22788;&#29702;">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">span</span><span class="o">=</span><span class="mi">56</span>

<span class="n">df_train_in</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;data/train_in_all.csv&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span><span class="o">/</span><span class="mi">1000</span>
<span class="n">df_train_in</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df_train_in</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df_train_in</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;date&quot;</span>

<span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;data/train_ext_all.csv&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span><span class="o">/</span><span class="mi">1000</span>
<span class="n">df_train_ext</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df_train_ext</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df_train_ext</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;date&quot;</span>

<span class="n">df_train_in_nums</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;data/train_in_all_nums.csv&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span><span class="o">/</span><span class="mi">1000</span>
<span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;date&quot;</span>

<span class="n">df_train_ext_nums</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;data/train_ext_all_nums.csv&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">set_index</span><span class="p">([</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="s2">&quot;type_id&quot;</span><span class="p">])</span><span class="o">/</span><span class="mi">1000</span>
<span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
<span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;date&quot;</span>

<span class="n">df_train_in</span> <span class="o">=</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">ewm</span><span class="p">(</span><span class="n">span</span><span class="o">=</span><span class="n">span</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">ewm</span><span class="p">(</span><span class="n">span</span><span class="o">=</span><span class="n">span</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="n">df_train_in_nums</span> <span class="o">=</span> <span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">ewm</span><span class="p">(</span><span class="n">span</span><span class="o">=</span><span class="n">span</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>
<span class="n">df_train_ext_nums</span> <span class="o">=</span> <span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">ewm</span><span class="p">(</span><span class="n">span</span><span class="o">=</span><span class="n">span</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext_shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in_nums shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in_nums</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext_nums shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext_nums</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>df_train_in shape:  (1386, 1575)
df_train_ext_shape:  (1383, 1575)
df_train_in_nums shape:  (1386, 1575)
df_train_ext_nums shape:  (1383, 1575)
</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">merge_end</span> <span class="o">=</span> <span class="mi">200</span> 
<span class="n">merge_step</span> <span class="o">=</span> <span class="mi">200</span> 

<span class="n">df_train_in</span> <span class="o">=</span> <span class="n">merge_zeros_cols</span><span class="p">(</span><span class="n">df_train_in</span><span class="p">,</span> <span class="n">merge_end</span><span class="p">,</span> <span class="n">merge_step</span><span class="p">)</span>
<span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">merge_zeros_cols</span><span class="p">(</span><span class="n">df_train_ext</span><span class="p">,</span> <span class="n">merge_end</span><span class="p">,</span> <span class="n">merge_step</span><span class="p">)</span>

<span class="c1"># 再直接取对数</span>
<span class="n">df_train_in</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log1p</span><span class="p">(</span><span class="n">df_train_in</span><span class="p">)</span>
<span class="n">df_train_ext</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log1p</span><span class="p">(</span><span class="n">df_train_ext</span><span class="p">)</span>

<span class="c1"># 数量处理</span>
<span class="n">df_train_in_nums</span> <span class="o">=</span> <span class="n">merge_zeros_cols</span><span class="p">(</span><span class="n">df_train_in_nums</span><span class="p">,</span> <span class="n">merge_end</span><span class="p">,</span> <span class="n">merge_step</span><span class="p">)</span>
<span class="n">df_train_ext_nums</span> <span class="o">=</span> <span class="n">merge_zeros_cols</span><span class="p">(</span><span class="n">df_train_ext_nums</span><span class="p">,</span> <span class="n">merge_end</span><span class="p">,</span> <span class="n">merge_step</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_in shape: &quot;</span><span class="p">,</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;df_train_ext_shape: &quot;</span><span class="p">,</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>df_train_in shape:  (1120, 1575)
df_train_ext_shape:  (1118, 1575)
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<h4 id="&#29305;&#24449;&#23376;&#38598;&#25277;&#21462;">&#29305;&#24449;&#23376;&#38598;&#25277;&#21462;<a class="anchor-link" href="#&#29305;&#24449;&#23376;&#38598;&#25277;&#21462;">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">prepare_dataset_byDay</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">dnums</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">is_train</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="n">x</span> <span class="o">=</span> <span class="p">{}</span>
    <span class="n">n</span> <span class="o">=</span> <span class="mi">11</span>
    <span class="n">times</span> <span class="o">=</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">14</span><span class="p">,</span><span class="mi">21</span><span class="p">,</span><span class="mi">35</span><span class="p">,</span><span class="mi">56</span><span class="p">]</span> 
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_sum&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_mean&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_sum_decay&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
        <span class="p">(</span><span class="n">tmp</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.999</span><span class="p">,</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_mean_decay&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
        <span class="p">(</span><span class="n">tmp</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.999</span><span class="p">,</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_</span><span class="si">%s</span><span class="s2">_sum_decay&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
        <span class="p">(</span><span class="n">tmp</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_</span><span class="si">%s</span><span class="s2">_mean_decay&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
        <span class="p">(</span><span class="n">tmp</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>

    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_count&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">(</span><span class="n">tmp</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> 
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;no_sales_</span><span class="si">%s</span><span class="s2">_count&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">i</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_count&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span>
        
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;diff_</span><span class="si">%s</span><span class="s2">_mean&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;std_</span><span class="si">%s</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_diff_</span><span class="si">%s</span><span class="s2">_mean&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_std_</span><span class="si">%s</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="o">+</span><span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=-</span><span class="mi">14</span><span class="p">),</span> <span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s1">&#39;diff_</span><span class="si">%s</span><span class="s1">_mean_2&#39;</span> <span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s1">&#39;mean_</span><span class="si">%s</span><span class="s1">_decay_2&#39;</span> <span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
        <span class="p">(</span><span class="n">tmp</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span> <span class="c1">#sum</span>
        
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="o">+</span><span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=-</span><span class="mi">14</span><span class="p">),</span> <span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_diff_</span><span class="si">%s</span><span class="s2">_mean_2&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s1">&#39;nums_mean_</span><span class="si">%s</span><span class="s1">_decay_2&#39;</span> <span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
        <span class="p">(</span><span class="n">tmp</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span> <span class="c1">#sum        </span>
    
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">i</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s1">&#39;has_sales_days_in_last_</span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="p">(</span><span class="n">tmp</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;last_sales_days_in_last_</span><span class="si">%s</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span>\
        <span class="n">i</span> <span class="o">-</span> <span class="p">((</span><span class="n">tmp</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</span><span class="p">))</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;first_sales_days_in_last_</span><span class="si">%s</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span>\
        <span class="p">((</span><span class="n">tmp</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">)</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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="p">))</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">7</span><span class="p">):</span>                  
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_mean_4_dow</span><span class="si">%s</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="mi">28</span><span class="o">-</span><span class="n">i</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;7D&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_mean_8_dow</span><span class="si">%s</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="mi">56</span><span class="o">-</span><span class="n">i</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;7D&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_mean_12_dow</span><span class="si">%s</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="mi">84</span><span class="o">-</span><span class="n">i</span><span class="p">,</span> <span class="mi">12</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;7D&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">31</span><span class="p">):</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;day_</span><span class="si">%s</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
    
    <span class="k">if</span> <span class="n">addType</span><span class="p">:</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;type&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()[</span><span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
    
    <span class="k">if</span> <span class="n">is_train</span><span class="p">:</span>
        <span class="n">y</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">dt</span><span class="o">+</span><span class="n">timedelta</span><span class="p">(</span><span class="mi">1</span><span class="p">),</span><span class="n">periods</span><span class="o">=</span><span class="mi">7</span><span class="p">)]</span><span class="o">.</span><span class="n">values</span>
        <span class="k">return</span> <span class="n">x</span><span class="p">,</span><span class="n">y</span>
    <span class="k">return</span> <span class="n">x</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">minus</span><span class="p">,</span> <span class="n">periods</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;D&quot;</span><span class="p">):</span>
    <span class="k">return</span> <span class="n">df</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">dt</span><span class="o">-</span><span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=</span><span class="nb">int</span><span class="p">(</span><span class="n">minus</span><span class="p">)),</span> <span class="n">periods</span><span class="o">=</span><span class="n">periods</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)]</span>

<span class="n">n</span> <span class="o">=</span> <span class="mi">5</span>
<span class="n">t2018</span> <span class="o">=</span> <span class="n">date</span><span class="p">(</span><span class="mi">2018</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">14</span><span class="p">)</span><span class="o">+</span><span class="n">timedelta</span><span class="p">(</span><span class="mi">28</span><span class="o">*</span><span class="n">n</span><span class="p">)</span>
<span class="n">num_days</span> <span class="o">=</span> <span class="mi">20</span><span class="o">*</span><span class="mi">5</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Preparing dataset...&quot;</span><span class="p">)</span>

<span class="n">x_in</span><span class="p">,</span> <span class="n">y_in</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
<span class="n">x_ext</span><span class="p">,</span> <span class="n">y_ext</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
<span class="n">addType</span> <span class="o">=</span> <span class="kc">True</span>

<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_days</span><span class="p">):</span>
    <span class="n">delta</span> <span class="o">=</span> <span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=</span><span class="n">i</span><span class="p">)</span>

    <span class="n">x_tmp_in</span><span class="p">,</span> <span class="n">y_tmp_in</span> <span class="o">=</span> <span class="n">prepare_dataset_byDay</span><span class="p">(</span>
        <span class="n">df_train_in</span><span class="p">,</span> <span class="n">t2018</span><span class="o">-</span><span class="n">delta</span><span class="p">,</span> <span class="n">df_train_in_nums</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">)</span>
    <span class="n">x_tmp_ext</span><span class="p">,</span> <span class="n">y_tmp_ext</span> <span class="o">=</span> <span class="n">prepare_dataset_byDay</span><span class="p">(</span>
        <span class="n">df_train_ext</span><span class="p">,</span> <span class="n">t2018</span><span class="o">-</span><span class="n">delta</span><span class="p">,</span> <span class="n">df_train_ext_nums</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">)</span>

    <span class="n">x_in</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x_tmp_in</span><span class="p">)</span>
    <span class="n">y_in</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">y_tmp_in</span><span class="p">)</span>
    <span class="n">x_ext</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x_tmp_ext</span><span class="p">)</span>
    <span class="n">y_ext</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">y_tmp_ext</span><span class="p">)</span>

<span class="n">x_train_in</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">x_in</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">y_train_in</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">y_in</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">x_train_ext</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">x_ext</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">y_train_ext</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">y_ext</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_train_in : &quot;</span><span class="p">,</span> <span class="n">x_train_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;y_train_in : &quot;</span><span class="p">,</span> <span class="n">y_train_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_train_ext : &quot;</span><span class="p">,</span> <span class="n">x_train_ext</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;y_train_ext : &quot;</span><span class="p">,</span> <span class="n">y_train_ext</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
</pre></div>

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<pre>Preparing dataset...
x_train_in :  (112000, 167)
y_train_in :  (112000, 7)
x_train_ext :  (111800, 167)
y_train_ext :  (111800, 7)
</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># 验证集 2018-1-21</span>
<span class="n">valdate</span> <span class="o">=</span> <span class="n">date</span><span class="p">(</span><span class="mi">2018</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">21</span><span class="p">)</span> <span class="o">+</span> <span class="n">timedelta</span><span class="p">(</span><span class="mi">28</span><span class="o">*</span><span class="n">n</span><span class="p">)</span>
<span class="n">x_val_in</span><span class="p">,</span> <span class="n">y_val_in</span> <span class="o">=</span> <span class="n">prepare_dataset_byDay</span><span class="p">(</span>
    <span class="n">df_train_in</span><span class="p">,</span>  <span class="n">valdate</span><span class="p">,</span> <span class="n">df_train_in_nums</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">)</span>
<span class="n">x_val_ext</span><span class="p">,</span> <span class="n">y_val_ext</span> <span class="o">=</span> <span class="n">prepare_dataset_byDay</span><span class="p">(</span>
    <span class="n">df_train_ext</span><span class="p">,</span>  <span class="n">valdate</span><span class="p">,</span> <span class="n">df_train_ext_nums</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_val_in shape: &quot;</span><span class="p">,</span> <span class="n">x_val_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>

<span class="c1"># 测试集 2018-1-28</span>
<span class="c1"># testdate = date(2018,1,28)</span>
<span class="n">testdate</span> <span class="o">=</span> <span class="n">date</span><span class="p">(</span><span class="mi">2018</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">28</span><span class="p">)</span> <span class="o">+</span> <span class="n">timedelta</span><span class="p">(</span><span class="mi">28</span><span class="o">*</span><span class="n">n</span><span class="p">)</span>
<span class="n">x_test_in</span> <span class="o">=</span> <span class="n">prepare_dataset_byDay</span><span class="p">(</span>
    <span class="n">df_train_in</span><span class="p">,</span> <span class="n">testdate</span><span class="p">,</span> <span class="n">df_train_in_nums</span><span class="p">,</span>  <span class="n">is_train</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">)</span>
<span class="n">x_test_ext</span> <span class="o">=</span> <span class="n">prepare_dataset_byDay</span><span class="p">(</span>
    <span class="n">df_train_ext</span><span class="p">,</span> <span class="n">testdate</span><span class="p">,</span> <span class="n">df_train_ext_nums</span><span class="p">,</span> <span class="n">is_train</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_test_in shape: &quot;</span><span class="p">,</span> <span class="n">x_test_in</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
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<pre>x_val_in shape:  (1120, 167)
x_test_in shape:  (1120, 167)
</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">prepare_dataset_byWeek</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">dnums</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">is_train</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="n">x</span> <span class="o">=</span> <span class="p">{}</span>
    <span class="n">n</span> <span class="o">=</span> <span class="mi">11</span>
    <span class="n">times</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">10</span><span class="p">]</span>
    <span class="n">freq</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">freqstr</span>
    <span class="k">if</span> <span class="ow">not</span> <span class="n">freq</span><span class="p">:</span>
        <span class="k">if</span> <span class="n">step</span><span class="o">==</span><span class="mi">14</span><span class="p">:</span> <span class="n">freq</span> <span class="o">=</span> <span class="s2">&quot;2W-SUN&quot;</span>
        <span class="k">elif</span> <span class="n">step</span><span class="o">==</span><span class="mi">21</span><span class="p">:</span> <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;3W-SUN&quot;</span>
        <span class="k">else</span><span class="p">:</span> <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;4W-SUN&quot;</span>
            
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>  
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_sum&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_mean&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_sum_decay&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
            <span class="p">(</span><span class="n">tmp</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.999</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_mean_decay&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
            <span class="p">(</span><span class="n">tmp</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.999</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>

        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_</span><span class="si">%s</span><span class="s2">_sum_decay&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
            <span class="p">(</span><span class="n">tmp</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_</span><span class="si">%s</span><span class="s2">_mean_decay&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
            <span class="p">(</span><span class="n">tmp</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>

    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>  
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_count&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">count_nonzero</span><span class="p">(</span><span class="n">tmp</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;no_sales_</span><span class="si">%s</span><span class="s2">_count&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">i</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="s2">&quot;sales_</span><span class="si">%s</span><span class="s2">_count&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span>

    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>  
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;diff_</span><span class="si">%s</span><span class="s2">_mean&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;std_</span><span class="si">%s</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>

        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_diff_</span><span class="si">%s</span><span class="s2">_mean&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_std_</span><span class="si">%s</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>

    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>  
        <span class="n">n</span> <span class="o">=</span> <span class="n">step</span> <span class="k">if</span> <span class="n">step</span> <span class="o">%</span> <span class="mi">14</span> <span class="ow">or</span> <span class="mi">14</span> <span class="o">%</span> <span class="n">step</span> <span class="k">else</span> <span class="mi">14</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="o">+</span><span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=-</span><span class="n">n</span><span class="p">),</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s1">&#39;diff_</span><span class="si">%s</span><span class="s1">_mean_2&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s1">&#39;mean_</span><span class="si">%s</span><span class="s1">_decay_2&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
            <span class="p">(</span><span class="n">tmp</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</span><span class="p">)</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">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>  <span class="c1"># sum</span>

        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">dnums</span><span class="p">,</span> <span class="n">dt</span><span class="o">+</span><span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=-</span><span class="n">n</span><span class="p">),</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;nums_diff_</span><span class="si">%s</span><span class="s2">_mean_2&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s1">&#39;nums_mean_</span><span class="si">%s</span><span class="s1">_decay_2&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> \
            <span class="p">(</span><span class="n">tmp</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="mf">0.9</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</span><span class="p">)</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">mean</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>  

    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">times</span><span class="p">:</span>  
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s1">&#39;has_sales_days_in_last_</span><span class="si">%s</span><span class="s1">&#39;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="p">(</span><span class="n">tmp</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;last_sales_days_in_last_</span><span class="si">%s</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span>\
            <span class="n">i</span> <span class="o">-</span> <span class="p">((</span><span class="n">tmp</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">)</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</span><span class="p">))</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;first_sales_days_in_last_</span><span class="si">%s</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span>\
            <span class="p">((</span><span class="n">tmp</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">)</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">i</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="p">))</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>

    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">8</span><span class="p">):</span>  
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;day_</span><span class="si">%s</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">i</span><span class="p">)]</span> <span class="o">=</span> <span class="n">get_span</span><span class="p">(</span>
            <span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)</span><span class="o">.</span><span class="n">values</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>

    <span class="k">if</span> <span class="n">addType</span><span class="p">:</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="n">x</span><span class="p">[</span><span class="s2">&quot;type&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()[</span><span class="s2">&quot;type_id&quot;</span><span class="p">]</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>

    <span class="k">if</span> <span class="n">is_train</span><span class="p">:</span>
        <span class="n">y</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">dt</span><span class="p">,</span> <span class="n">periods</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)]</span><span class="o">.</span><span class="n">values</span>
        <span class="k">return</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span>
    <span class="k">return</span> <span class="n">x</span>
</pre></div>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">getDatas</span><span class="p">(</span><span class="n">df_in</span><span class="p">,</span> <span class="n">df_ext</span><span class="p">,</span> <span class="n">df_in_nums</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">df_ext_nums</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dt</span><span class="o">=</span><span class="s2">&quot;2018-01-21&quot;</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">7</span><span class="p">,</span> <span class="n">num_days</span><span class="o">=</span><span class="nb">int</span><span class="p">(</span><span class="mi">15</span><span class="p">),</span> <span class="n">is_train</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Preparing dataset...step&quot;</span><span class="p">,</span> <span class="n">step</span><span class="p">)</span>
    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">dt</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
        <span class="n">dt</span> <span class="o">=</span> <span class="n">datetime</span><span class="o">.</span><span class="n">strptime</span><span class="p">(</span><span class="n">dt</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="n">num_days</span> <span class="o">=</span> <span class="n">num_days</span>
    <span class="n">x_in</span><span class="p">,</span> <span class="n">y_in</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
    <span class="n">x_ext</span><span class="p">,</span> <span class="n">y_ext</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
    <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_days</span><span class="p">):</span>
        <span class="n">delta</span> <span class="o">=</span> <span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=</span><span class="n">i</span><span class="o">*</span><span class="n">step</span><span class="p">)</span>
        <span class="k">if</span> <span class="n">is_train</span><span class="p">:</span>
            <span class="n">x_tmp_in</span><span class="p">,</span> <span class="n">y_tmp_in</span> <span class="o">=</span> <span class="n">prepare_dataset_byWeek</span><span class="p">(</span>
                <span class="n">df_in</span><span class="p">,</span> <span class="n">dt</span><span class="o">-</span><span class="n">delta</span><span class="p">,</span> <span class="n">df_in_nums</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="n">step</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">,</span> <span class="n">is_train</span><span class="o">=</span><span class="n">is_train</span><span class="p">)</span>
            <span class="n">x_tmp_ext</span><span class="p">,</span> <span class="n">y_tmp_ext</span> <span class="o">=</span> <span class="n">prepare_dataset_byWeek</span><span class="p">(</span>
                <span class="n">df_ext</span><span class="p">,</span> <span class="n">dt</span><span class="o">-</span><span class="n">delta</span><span class="p">,</span> <span class="n">df_ext_nums</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="n">step</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">,</span> <span class="n">is_train</span><span class="o">=</span><span class="n">is_train</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">x_tmp_in</span> <span class="o">=</span> <span class="n">prepare_dataset_byWeek</span><span class="p">(</span>
                <span class="n">df_in</span><span class="p">,</span> <span class="n">dt</span><span class="o">-</span><span class="n">delta</span><span class="p">,</span> <span class="n">df_in_nums</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="n">step</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">,</span> <span class="n">is_train</span><span class="o">=</span><span class="n">is_train</span><span class="p">)</span>
            <span class="n">x_tmp_ext</span> <span class="o">=</span> <span class="n">prepare_dataset_byWeek</span><span class="p">(</span>
                <span class="n">df_ext</span><span class="p">,</span> <span class="n">dt</span><span class="o">-</span><span class="n">delta</span><span class="p">,</span> <span class="n">df_ext_nums</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="n">step</span><span class="p">,</span> <span class="n">addType</span><span class="o">=</span><span class="n">addType</span><span class="p">,</span> <span class="n">is_train</span><span class="o">=</span><span class="n">is_train</span><span class="p">)</span>
            <span class="n">y_tmp_in</span> <span class="o">=</span> <span class="p">[]</span>
            <span class="n">y_tmp_ext</span> <span class="o">=</span> <span class="p">[]</span>

        <span class="n">x_in</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x_tmp_in</span><span class="p">)</span>
        <span class="n">y_in</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">y_tmp_in</span><span class="p">)</span>
        <span class="n">x_ext</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x_tmp_ext</span><span class="p">)</span>
        <span class="n">y_ext</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">y_tmp_ext</span><span class="p">)</span>

    <span class="n">x_train_in</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">x_in</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">y_train_in</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">y_in</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">x_train_ext</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">x_ext</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">y_train_ext</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">y_ext</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">x_train_in</span><span class="p">,</span> <span class="n">y_train_in</span><span class="p">,</span> <span class="n">x_train_ext</span><span class="p">,</span> <span class="n">y_train_ext</span>
</pre></div>

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<div class="prompt input_prompt">In&nbsp;[18]:</div>
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    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_span</span><span class="p">(</span><span class="n">df</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">minus</span><span class="p">,</span> <span class="n">periods</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="s2">&quot;D&quot;</span><span class="p">):</span>
    <span class="k">return</span> <span class="n">df</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">date_range</span><span class="p">(</span><span class="n">dt</span><span class="o">-</span><span class="n">timedelta</span><span class="p">(</span><span class="n">days</span><span class="o">=</span><span class="nb">int</span><span class="p">(</span><span class="n">minus</span><span class="p">)),</span> <span class="n">periods</span><span class="o">=</span><span class="n">periods</span><span class="p">,</span> <span class="n">freq</span><span class="o">=</span><span class="n">freq</span><span class="p">)]</span>

<span class="n">i</span> <span class="o">=</span> <span class="o">-</span><span class="mi">2</span>
<span class="n">train_date</span> <span class="o">=</span> <span class="p">[</span>
    <span class="n">df_train_in_W</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">],</span>
    <span class="n">df_train_in_2W</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">],</span>
    <span class="n">df_train_in_3W</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">],</span>
    <span class="n">df_train_in_4W</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="p">]</span>

<span class="c1"># 训练集</span>
<span class="n">x_train_in_W</span><span class="p">,</span> <span class="n">y_train_in_W</span><span class="p">,</span> <span class="n">x_train_ext_W</span><span class="p">,</span> <span class="n">y_train_ext_W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_W</span><span class="p">,</span> <span class="n">df_train_ext_W</span><span class="p">,</span> <span class="n">df_train_in_nums_W</span><span class="p">,</span> <span class="n">df_train_ext_nums_W</span><span class="p">,</span> <span class="n">train_date</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">7</span><span class="p">)</span>

<span class="n">x_train_in_2W</span><span class="p">,</span> <span class="n">y_train_in_2W</span><span class="p">,</span> <span class="n">x_train_ext_2W</span><span class="p">,</span> <span class="n">y_train_ext_2W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_2W</span><span class="p">,</span> <span class="n">df_train_ext_2W</span><span class="p">,</span> <span class="n">df_train_in_nums_2W</span><span class="p">,</span> <span class="n">df_train_ext_nums_2W</span><span class="p">,</span> <span class="n">train_date</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">14</span><span class="p">)</span>

<span class="n">x_train_in_3W</span><span class="p">,</span> <span class="n">y_train_in_3W</span><span class="p">,</span> <span class="n">x_train_ext_3W</span><span class="p">,</span> <span class="n">y_train_ext_3W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_3W</span><span class="p">,</span> <span class="n">df_train_ext_3W</span><span class="p">,</span> <span class="n">df_train_in_nums_3W</span><span class="p">,</span> <span class="n">df_train_ext_nums_3W</span><span class="p">,</span> <span class="n">train_date</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="mi">21</span><span class="p">)</span>

<span class="n">x_train_in_4W</span><span class="p">,</span> <span class="n">y_train_in_4W</span><span class="p">,</span> <span class="n">x_train_ext_4W</span><span class="p">,</span> <span class="n">y_train_ext_4W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_4W</span><span class="p">,</span> <span class="n">df_train_ext_4W</span><span class="p">,</span> <span class="n">df_train_in_nums_4W</span><span class="p">,</span> <span class="n">df_train_ext_nums_4W</span><span class="p">,</span> <span class="n">train_date</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="mi">28</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_train_in_W shape: &quot;</span><span class="p">,</span> <span class="n">x_train_in_W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_train_in_2W shape: &quot;</span><span class="p">,</span> <span class="n">x_train_in_2W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>

<span class="c1"># 验证集</span>
<span class="n">i</span><span class="o">=-</span><span class="mi">1</span>
<span class="n">val_date</span> <span class="o">=</span> <span class="p">[</span>
    <span class="n">df_train_in_W</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">],</span>
    <span class="n">df_train_in_2W</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">],</span>
    <span class="n">df_train_in_3W</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">],</span>
    <span class="n">df_train_in_4W</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="p">]</span>  
<span class="n">x_val_in_W</span><span class="p">,</span> <span class="n">y_val_in_W</span><span class="p">,</span> <span class="n">x_val_ext_W</span><span class="p">,</span> <span class="n">y_val_ext_W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_W</span><span class="p">,</span> <span class="n">df_train_ext_W</span><span class="p">,</span> <span class="n">df_train_in_nums_W</span><span class="p">,</span> <span class="n">df_train_ext_nums_W</span><span class="p">,</span> <span class="n">val_date</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>

<span class="n">x_val_in_2W</span><span class="p">,</span> <span class="n">y_val_in_2W</span><span class="p">,</span> <span class="n">x_val_ext_2W</span><span class="p">,</span> <span class="n">y_val_ext_2W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_2W</span><span class="p">,</span> <span class="n">df_train_ext_2W</span><span class="p">,</span>  <span class="n">df_train_in_nums_2W</span><span class="p">,</span> <span class="n">df_train_ext_nums_2W</span><span class="p">,</span> <span class="n">val_date</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">14</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>

<span class="n">x_val_in_3W</span><span class="p">,</span> <span class="n">y_val_in_3W</span><span class="p">,</span> <span class="n">x_val_ext_3W</span><span class="p">,</span> <span class="n">y_val_ext_3W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_3W</span><span class="p">,</span> <span class="n">df_train_ext_3W</span><span class="p">,</span> <span class="n">df_train_in_nums_3W</span><span class="p">,</span> <span class="n">df_train_ext_nums_3W</span><span class="p">,</span> <span class="n">val_date</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>

<span class="n">x_val_in_4W</span><span class="p">,</span> <span class="n">y_val_in_4W</span><span class="p">,</span> <span class="n">x_val_ext_4W</span><span class="p">,</span> <span class="n">y_val_ext_4W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_4W</span><span class="p">,</span> <span class="n">df_train_ext_4W</span><span class="p">,</span> <span class="n">df_train_in_nums_4W</span><span class="p">,</span> <span class="n">df_train_ext_nums_4W</span><span class="p">,</span> <span class="n">val_date</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_val_in_W shape: &quot;</span><span class="p">,</span> <span class="n">x_val_in_W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_val_in_2W shape: &quot;</span><span class="p">,</span> <span class="n">x_val_in_2W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_val_ext_2W shape: &quot;</span><span class="p">,</span> <span class="n">y_val_ext_2W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>

<span class="c1"># 测试集</span>
<span class="n">test_date</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">steps</span> <span class="o">=</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span><span class="mi">14</span><span class="p">,</span><span class="mi">21</span><span class="p">,</span><span class="mi">28</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">4</span><span class="p">):</span>
    <span class="n">test_date</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">val_date</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">+</span> <span class="n">timedelta</span><span class="p">(</span><span class="n">steps</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span>

<span class="n">x_test_in_W</span><span class="p">,</span> <span class="n">y_test_in_W</span><span class="p">,</span> <span class="n">x_test_ext_W</span><span class="p">,</span> <span class="n">y_test_ext_W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_W</span><span class="p">,</span> <span class="n">df_train_ext_W</span><span class="p">,</span> <span class="n">df_train_in_nums_W</span><span class="p">,</span> <span class="n">df_train_ext_nums_W</span><span class="p">,</span> <span class="n">test_date</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">7</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>

<span class="n">x_test_in_2W</span><span class="p">,</span> <span class="n">y_test_in_2W</span><span class="p">,</span> <span class="n">x_test_ext_2W</span><span class="p">,</span> <span class="n">y_test_ext_2W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_2W</span><span class="p">,</span> <span class="n">df_train_ext_2W</span><span class="p">,</span> <span class="n">df_train_in_nums_2W</span><span class="p">,</span> <span class="n">df_train_ext_nums_2W</span><span class="p">,</span> <span class="n">test_date</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="mi">14</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>

<span class="n">x_test_in_3W</span><span class="p">,</span> <span class="n">y_test_in_3W</span><span class="p">,</span> <span class="n">x_test_ext_3W</span><span class="p">,</span> <span class="n">y_test_ext_3W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_3W</span><span class="p">,</span> <span class="n">df_train_ext_3W</span><span class="p">,</span> <span class="n">df_train_in_nums_3W</span><span class="p">,</span> <span class="n">df_train_ext_nums_3W</span><span class="p">,</span> <span class="n">test_date</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>

<span class="n">x_test_in_4W</span><span class="p">,</span> <span class="n">y_test_in_4W</span><span class="p">,</span> <span class="n">x_test_ext_4W</span><span class="p">,</span> <span class="n">y_test_ext_4W</span> <span class="o">=</span> <span class="n">getDatas</span><span class="p">(</span>
    <span class="n">df_train_in_4W</span><span class="p">,</span> <span class="n">df_train_ext_4W</span><span class="p">,</span> <span class="n">df_train_in_nums_4W</span><span class="p">,</span> <span class="n">df_train_ext_nums_4W</span><span class="p">,</span> <span class="n">test_date</span><span class="p">[</span><span class="mi">3</span><span class="p">],</span> <span class="mi">28</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_test_in_W shape: &quot;</span><span class="p">,</span> <span class="n">x_test_in_W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;x_test_in_2W shape: &quot;</span><span class="p">,</span> <span class="n">x_test_ext_2W</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
</pre></div>

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<pre>Preparing dataset...step 7
Preparing dataset...step 14
Preparing dataset...step 21
Preparing dataset...step 28
x_train_in_W shape:  (9750, 103)
x_train_in_2W shape:  (9750, 103)
Preparing dataset...step 7
Preparing dataset...step 14
Preparing dataset...step 21
Preparing dataset...step 28
x_val_in_W shape:  (650, 103)
x_val_in_2W shape:  (650, 103)
x_val_ext_2W shape:  (641, 1)
Preparing dataset...step 7
Preparing dataset...step 14
Preparing dataset...step 21
Preparing dataset...step 28
x_test_in_W shape:  (650, 103)
x_test_in_2W shape:  (641, 103)
</pre>
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</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[19]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">x_train_in_Wall</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_train_in_W</span><span class="p">,</span> <span class="n">x_train_in_2W</span><span class="p">,</span> <span class="n">x_train_in_3W</span><span class="p">,</span> <span class="n">x_train_in_4W</span><span class="p">]</span>
<span class="n">y_train_in_Wall</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span>
    <span class="p">[</span><span class="n">y_train_in_W</span><span class="p">,</span> <span class="n">y_train_in_2W</span><span class="p">,</span> <span class="n">y_train_in_3W</span><span class="p">,</span> <span class="n">y_train_in_4W</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">x_train_ext_Wall</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_train_ext_W</span><span class="p">,</span> <span class="n">x_train_ext_2W</span><span class="p">,</span>
                    <span class="n">x_train_ext_3W</span><span class="p">,</span> <span class="n">x_train_ext_4W</span><span class="p">]</span>
<span class="n">y_train_ext_Wall</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span>
    <span class="p">[</span><span class="n">y_train_ext_W</span><span class="p">,</span> <span class="n">y_train_ext_2W</span><span class="p">,</span> <span class="n">y_train_ext_3W</span><span class="p">,</span> <span class="n">y_train_ext_4W</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

<span class="n">x_val_in_Wall</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_val_in_W</span><span class="p">,</span> <span class="n">x_val_in_2W</span><span class="p">,</span> <span class="n">x_val_in_3W</span><span class="p">,</span> <span class="n">x_val_in_4W</span><span class="p">]</span>
<span class="n">y_val_in_Wall</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span>
    <span class="p">[</span><span class="n">y_val_in_W</span><span class="p">,</span> <span class="n">y_val_in_2W</span><span class="p">,</span> <span class="n">y_val_in_3W</span><span class="p">,</span> <span class="n">y_val_in_4W</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">x_val_ext_Wall</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_val_ext_W</span><span class="p">,</span> <span class="n">x_val_ext_2W</span><span class="p">,</span> <span class="n">x_val_ext_3W</span><span class="p">,</span> <span class="n">x_val_ext_4W</span><span class="p">]</span>
<span class="n">y_val_ext_Wall</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span>
    <span class="p">[</span><span class="n">y_val_ext_W</span><span class="p">,</span> <span class="n">y_val_ext_2W</span><span class="p">,</span> <span class="n">y_val_ext_3W</span><span class="p">,</span> <span class="n">y_val_ext_4W</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

<span class="n">x_test_in_Wall</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_test_in_W</span><span class="p">,</span> <span class="n">x_test_in_2W</span><span class="p">,</span> <span class="n">x_test_in_3W</span><span class="p">,</span> <span class="n">x_test_in_4W</span><span class="p">]</span>
<span class="n">x_test_ext_Wall</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_test_ext_W</span><span class="p">,</span> <span class="n">x_test_ext_2W</span><span class="p">,</span> <span class="n">x_test_ext_3W</span><span class="p">,</span> <span class="n">x_test_ext_4W</span><span class="p">]</span>
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<h3 id="&#31639;&#27861;&#24314;&#27169;">&#31639;&#27861;&#24314;&#27169;<a class="anchor-link" href="#&#31639;&#27861;&#24314;&#27169;">&#182;</a></h3><ul>
<li>天粒度预测</li>
<li>周粒度预测</li>
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<h4 id="&#32454;&#31890;&#24230;-1&#22825;1&#20010;&#27169;&#22411;">&#32454;&#31890;&#24230;-1&#22825;1&#20010;&#27169;&#22411;<a class="anchor-link" href="#&#32454;&#31890;&#24230;-1&#22825;1&#20010;&#27169;&#22411;">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">params1</span> <span class="o">=</span> <span class="p">{</span>
    <span class="s2">&quot;booster&quot;</span><span class="p">:</span> <span class="s2">&quot;gblinear&quot;</span><span class="p">,</span>
    <span class="s2">&quot;eta&quot;</span><span class="p">:</span> <span class="mf">0.005</span><span class="p">,</span>
    <span class="s2">&quot;alpha&quot;</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span>
    <span class="s2">&quot;lambda&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
    <span class="s2">&quot;nthread&quot;</span><span class="p">:</span> <span class="mi">4</span><span class="p">,</span>
    <span class="s2">&quot;objective&quot;</span><span class="p">:</span> <span class="s2">&quot;reg:linear&quot;</span><span class="p">,</span>
    <span class="s2">&quot;eval_metric&quot;</span><span class="p">:</span> <span class="s2">&quot;rmse&quot;</span><span class="p">,</span>
    <span class="s2">&quot;silent&quot;</span><span class="p">:</span> <span class="mi">1</span><span class="p">,</span>
<span class="p">}</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># 一天一个模型</span>
<span class="n">boosting_round</span> <span class="o">=</span> <span class="p">[</span><span class="mi">100</span><span class="p">,</span><span class="mi">200</span><span class="p">,</span><span class="mi">400</span><span class="p">]</span>
<span class="n">MAX_ROUNDS</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">boosting_round</span><span class="p">)</span>
<span class="n">etas</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.01</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.0001</span><span class="p">]</span>
<span class="n">eta_</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">MAX_ROUNDS</span><span class="p">)</span>
<span class="n">eta_list</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">tile</span><span class="p">(</span><span class="n">eta</span><span class="p">,</span> <span class="n">rounds</span><span class="p">)</span> <span class="k">for</span> <span class="n">rounds</span><span class="p">,</span> <span class="n">eta</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">boosting_round</span><span class="p">,</span> <span class="n">etas</span><span class="p">)]</span>
<span class="n">eta_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">eta_list</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>

<span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;./model/model1&quot;</span><span class="p">):</span>
    <span class="n">os</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;./model/model1&quot;</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">7</span><span class="p">):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=&quot;</span><span class="o">*</span><span class="mi">50</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;step </span><span class="si">%d</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">))</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">())</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=&quot;</span><span class="o">*</span><span class="mi">50</span><span class="p">)</span>
    <span class="n">dtrain</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">DMatrix</span><span class="p">(</span>
        <span class="n">data</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">x_train_in</span><span class="o">.</span><span class="n">values</span><span class="p">,</span><span class="n">x_train_ext</span><span class="o">.</span><span class="n">values</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
        <span class="n">label</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">y_train_in</span><span class="p">[:,</span><span class="n">i</span><span class="p">],</span> <span class="n">y_train_ext</span><span class="p">[:,</span><span class="n">i</span><span class="p">]],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="p">)</span>
    
    <span class="n">dval</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">DMatrix</span><span class="p">(</span>
        <span class="n">data</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">x_val_in</span><span class="o">.</span><span class="n">values</span><span class="p">,</span><span class="n">x_val_ext</span><span class="o">.</span><span class="n">values</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
        <span class="n">label</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">y_val_in</span><span class="p">[:,</span><span class="n">i</span><span class="p">],</span> <span class="n">y_val_ext</span><span class="p">[:,</span><span class="n">i</span><span class="p">]],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="p">)</span>
    
    <span class="n">bst</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">train</span><span class="p">(</span>
        <span class="n">params1</span><span class="p">,</span>
        <span class="n">dtrain</span><span class="p">,</span>
        <span class="n">num_boost_round</span><span class="o">=</span><span class="n">MAX_ROUNDS</span><span class="p">,</span>
        <span class="n">evals</span><span class="o">=</span><span class="p">[(</span><span class="n">dtrain</span><span class="p">,</span><span class="s2">&quot;dtrain&quot;</span><span class="p">),(</span><span class="n">dval</span><span class="p">,</span><span class="s2">&quot;dval&quot;</span><span class="p">)],</span>
        <span class="n">early_stopping_rounds</span><span class="o">=</span><span class="mi">300</span><span class="p">,</span>
        <span class="n">verbose_eval</span><span class="o">=</span><span class="mi">500</span><span class="p">,</span>
        <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">xgb</span><span class="o">.</span><span class="n">callback</span><span class="o">.</span><span class="n">reset_learning_rate</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">eta_list</span><span class="p">))]</span>
    <span class="p">)</span>

    <span class="n">bst</span><span class="o">.</span><span class="n">save_model</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;./model/model1/bst_byday&quot;</span><span class="o">+</span><span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">+</span><span class="s2">&quot;.model&quot;</span><span class="p">)</span>
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<pre>==================================================
step 1
2018-12-29 22:28:55.591979
==================================================
[0]	dtrain-rmse:0.396163	dval-rmse:0.395486
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[500]	dtrain-rmse:0.010502	dval-rmse:0.008498
[699]	dtrain-rmse:0.010498	dval-rmse:0.008486
==================================================
step 2
2018-12-29 22:29:37.379147
==================================================
[0]	dtrain-rmse:0.39615	dval-rmse:0.395368
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[500]	dtrain-rmse:0.01092	dval-rmse:0.009125
[699]	dtrain-rmse:0.010916	dval-rmse:0.009114
==================================================
step 3
2018-12-29 22:30:18.852348
==================================================
[0]	dtrain-rmse:0.396139	dval-rmse:0.395372
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[500]	dtrain-rmse:0.011335	dval-rmse:0.009063
[699]	dtrain-rmse:0.011331	dval-rmse:0.009052
==================================================
step 4
2018-12-29 22:31:00.272398
==================================================
[0]	dtrain-rmse:0.396129	dval-rmse:0.395306
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[500]	dtrain-rmse:0.01174	dval-rmse:0.009339
[699]	dtrain-rmse:0.011736	dval-rmse:0.009328
==================================================
step 5
2018-12-29 22:31:41.817697
==================================================
[0]	dtrain-rmse:0.39612	dval-rmse:0.395243
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[500]	dtrain-rmse:0.012134	dval-rmse:0.010086
[699]	dtrain-rmse:0.01213	dval-rmse:0.010075
==================================================
step 6
2018-12-29 22:32:23.234350
==================================================
[0]	dtrain-rmse:0.396111	dval-rmse:0.395346
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[500]	dtrain-rmse:0.012512	dval-rmse:0.009816
[699]	dtrain-rmse:0.012508	dval-rmse:0.009806
==================================================
step 7
2018-12-29 22:33:04.803953
==================================================
[0]	dtrain-rmse:0.396106	dval-rmse:0.395516
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[500]	dtrain-rmse:0.012871	dval-rmse:0.009717
[699]	dtrain-rmse:0.012867	dval-rmse:0.009708
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<h4 id="&#31895;&#31890;&#24230;-4&#20010;&#32047;&#31215;&#27169;&#22411;">&#31895;&#31890;&#24230;-4&#20010;&#32047;&#31215;&#27169;&#22411;<a class="anchor-link" href="#&#31895;&#31890;&#24230;-4&#20010;&#32047;&#31215;&#27169;&#22411;">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Training and Predicting models...&quot;</span><span class="p">)</span>
<span class="n">params_w4</span> <span class="o">=</span> <span class="p">{</span>
    <span class="s2">&quot;booster&quot;</span><span class="p">:</span><span class="s2">&quot;gblinear&quot;</span><span class="p">,</span>
    <span class="s2">&quot;eta&quot;</span><span class="p">:</span><span class="mf">0.005</span><span class="p">,</span>
    <span class="s2">&quot;alpha&quot;</span><span class="p">:</span><span class="mi">0</span><span class="p">,</span>
    <span class="s2">&quot;lambda&quot;</span><span class="p">:</span><span class="mi">1</span><span class="p">,</span>
    <span class="s2">&quot;nthread&quot;</span><span class="p">:</span><span class="mi">4</span><span class="p">,</span>
    <span class="s2">&quot;objective&quot;</span><span class="p">:</span><span class="s2">&quot;reg:linear&quot;</span><span class="p">,</span>
    <span class="s2">&quot;eval_metric&quot;</span><span class="p">:</span><span class="s2">&quot;rmse&quot;</span><span class="p">,</span>
    <span class="s2">&quot;silent&quot;</span><span class="p">:</span><span class="mi">1</span>
<span class="p">}</span>
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<pre>Training and Predicting models...
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">boosting_round</span> <span class="o">=</span> <span class="p">[</span><span class="mi">100</span><span class="p">,</span><span class="mi">200</span><span class="p">,</span> <span class="mi">400</span><span class="p">]</span>
<span class="n">MAX_ROUNDS</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">boosting_round</span><span class="p">)</span>
<span class="n">etas</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.01</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.0001</span><span class="p">]</span> 
<span class="n">eta_</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">MAX_ROUNDS</span><span class="p">)</span>
<span class="n">eta_list</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">tile</span><span class="p">(</span><span class="n">eta</span><span class="p">,</span> <span class="n">rounds</span><span class="p">)</span> <span class="k">for</span> <span class="n">rounds</span><span class="p">,</span> <span class="n">eta</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">boosting_round</span><span class="p">,</span> <span class="n">etas</span><span class="p">)]</span>
<span class="n">eta_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">eta_list</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>

<span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;./model/model1&quot;</span><span class="p">):</span>
        <span class="n">os</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;./model/model1&quot;</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">4</span><span class="p">):</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=&quot;</span><span class="o">*</span><span class="mi">50</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;step </span><span class="si">%d</span><span class="s2">&quot;</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">))</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">())</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;=&quot;</span><span class="o">*</span><span class="mi">50</span><span class="p">)</span>
    <span class="n">dtrain_w4</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">DMatrix</span><span class="p">(</span>
        <span class="n">data</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">x_train_in_Wall</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">x_train_ext_Wall</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
        <span class="n">label</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">y_train_in_Wall</span><span class="p">[:,</span><span class="n">i</span><span class="p">],</span> <span class="n">y_train_ext_Wall</span><span class="p">[:,</span><span class="n">i</span><span class="p">]],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="p">)</span>
    
    <span class="n">dval_w4</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">DMatrix</span><span class="p">(</span>
        <span class="n">data</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">x_val_in_Wall</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span><span class="n">x_val_ext_Wall</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">),</span>
        <span class="n">label</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">y_val_in_Wall</span><span class="p">[:,</span><span class="n">i</span><span class="p">],</span> <span class="n">y_val_ext_Wall</span><span class="p">[:,</span><span class="n">i</span><span class="p">]],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="p">)</span>
        
    <span class="n">bst_w4</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">train</span><span class="p">(</span>
        <span class="n">params_w4</span><span class="p">,</span>
        <span class="n">dtrain_w4</span><span class="p">,</span>
        <span class="n">num_boost_round</span><span class="o">=</span><span class="n">MAX_ROUNDS</span><span class="p">,</span>
        <span class="n">evals</span><span class="o">=</span><span class="p">[(</span><span class="n">dtrain_w4</span><span class="p">,</span><span class="s2">&quot;dtrain&quot;</span><span class="p">),(</span><span class="n">dval_w4</span><span class="p">,</span><span class="s2">&quot;dval&quot;</span><span class="p">)],</span>
        <span class="n">early_stopping_rounds</span><span class="o">=</span><span class="mi">300</span><span class="p">,</span>
        <span class="n">verbose_eval</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span>
        <span class="n">callbacks</span><span class="o">=</span><span class="p">[</span><span class="n">xgb</span><span class="o">.</span><span class="n">callback</span><span class="o">.</span><span class="n">reset_learning_rate</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">eta_list</span><span class="p">))]</span>
    <span class="p">)</span>
    
    <span class="n">bst_w4</span><span class="o">.</span><span class="n">save_model</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;./model/model1/bst_byweek&quot;</span><span class="o">+</span><span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span><span class="o">+</span><span class="s2">&quot;.model&quot;</span><span class="p">)</span>
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<pre>==================================================
step 1
2018-12-29 22:33:46.522929
==================================================
[0]	dtrain-rmse:0.416029	dval-rmse:0.41575
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[699]	dtrain-rmse:0.0353	dval-rmse:0.0325
==================================================
step 2
2018-12-29 22:33:53.468409
==================================================
[0]	dtrain-rmse:0.416229	dval-rmse:0.415548
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[699]	dtrain-rmse:0.039435	dval-rmse:0.044357
==================================================
step 3
2018-12-29 22:33:59.051657
==================================================
[0]	dtrain-rmse:0.415886	dval-rmse:0.415353
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[699]	dtrain-rmse:0.040131	dval-rmse:0.051377
==================================================
step 4
2018-12-29 22:34:03.551629
==================================================
[0]	dtrain-rmse:0.415601	dval-rmse:0.41538
Multiple eval metrics have been passed: &#39;dval-rmse&#39; will be used for early stopping.

Will train until dval-rmse hasn&#39;t improved in 300 rounds.
[699]	dtrain-rmse:0.042391	dval-rmse:0.057413
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<h3 id="&#39044;&#27979;&#25552;&#20132;">&#39044;&#27979;&#25552;&#20132;<a class="anchor-link" href="#&#39044;&#27979;&#25552;&#20132;">&#182;</a></h3>
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<h4 id="&#20989;&#25968;">&#20989;&#25968;<a class="anchor-link" href="#&#20989;&#25968;">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">prediction</span><span class="p">(</span><span class="n">test</span><span class="p">,</span> <span class="n">path</span><span class="o">=</span><span class="s2">&quot;./model/model1&quot;</span><span class="p">,</span><span class="n">mode</span><span class="o">=</span><span class="s2">&quot;wd&quot;</span><span class="p">):</span>
    <span class="k">if</span> <span class="n">mode</span><span class="o">==</span><span class="s2">&quot;wd&quot;</span><span class="p">:</span>
        <span class="n">week_ext</span><span class="p">,</span> <span class="n">week_in</span><span class="p">,</span> <span class="n">day_ext</span><span class="p">,</span> <span class="n">day_in</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[],</span> <span class="p">[],</span> <span class="p">[]</span>
        <span class="n">results</span> <span class="o">=</span> <span class="p">[</span><span class="n">week_ext</span><span class="p">,</span> <span class="n">week_in</span><span class="p">,</span> <span class="n">day_ext</span><span class="p">,</span> <span class="n">day_in</span><span class="p">]</span>
        <span class="n">bases</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;bst_byweek</span><span class="si">%s</span><span class="s2">.model&quot;</span><span class="p">,</span><span class="s2">&quot;bst_byweek</span><span class="si">%s</span><span class="s2">.model&quot;</span><span class="p">,</span><span class="s2">&quot;bst_byday</span><span class="si">%s</span><span class="s2">.model&quot;</span><span class="p">,</span><span class="s2">&quot;bst_byday</span><span class="si">%s</span><span class="s2">.model&quot;</span><span class="p">]</span>
        <span class="n">steps</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">7</span><span class="p">]</span>
        <span class="k">for</span> <span class="n">step</span><span class="p">,</span> <span class="n">res</span><span class="p">,</span> <span class="n">base</span><span class="p">,</span> <span class="n">data</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">steps</span><span class="p">,</span> <span class="n">results</span><span class="p">,</span> <span class="n">bases</span><span class="p">,</span> <span class="n">test</span><span class="p">):</span>
            <span class="n">dtest</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">DMatrix</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
            <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">step</span><span class="p">):</span>
                <span class="n">model</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">base</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">))</span>
                <span class="nb">print</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
                <span class="n">bst</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">Booster</span><span class="p">()</span>
                <span class="n">bst</span><span class="o">.</span><span class="n">load_model</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
                <span class="n">res</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">bst</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">dtest</span><span class="p">))</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">W</span><span class="p">,</span> <span class="n">W2</span><span class="p">,</span> <span class="n">W3</span><span class="p">,</span> <span class="n">W4</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[],</span> <span class="p">[],</span> <span class="p">[]</span>
        <span class="n">results</span> <span class="o">=</span> <span class="p">[</span><span class="n">W</span><span class="p">,</span> <span class="n">W2</span><span class="p">,</span> <span class="n">W3</span><span class="p">,</span> <span class="n">W4</span><span class="p">]</span>
        <span class="n">bases</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;bst_byweek</span><span class="si">%s</span><span class="s2">.model&quot;</span><span class="p">]</span><span class="o">*</span><span class="mi">4</span>
        <span class="n">steps</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span>
        <span class="k">for</span> <span class="n">step</span><span class="p">,</span> <span class="n">res</span><span class="p">,</span> <span class="n">base</span><span class="p">,</span> <span class="n">data</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">steps</span><span class="p">,</span> <span class="n">results</span><span class="p">,</span> <span class="n">bases</span><span class="p">,</span> <span class="n">test</span><span class="p">):</span>
            <span class="n">dtest</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">DMatrix</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
            <span class="n">model</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">base</span><span class="o">%</span><span class="p">(</span><span class="n">step</span><span class="o">+</span><span class="mi">1</span><span class="p">))</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
            <span class="n">bst</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">Booster</span><span class="p">()</span>
            <span class="n">bst</span><span class="o">.</span><span class="n">load_model</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
            <span class="n">res</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">bst</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">dtest</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">results</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">getLastW</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
    <span class="n">d1</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">data</span><span class="p">)</span><span class="o">.</span><span class="n">squeeze</span><span class="p">()</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
    <span class="n">d2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">expm1</span><span class="p">(</span><span class="n">d1</span><span class="p">)</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="mi">7</span><span class="p">,</span><span class="mi">14</span><span class="p">,</span><span class="mi">21</span><span class="p">,</span><span class="mi">28</span><span class="p">])</span> 
    <span class="n">d3</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">d2</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
    <span class="n">d2</span><span class="p">[:,</span><span class="mi">1</span><span class="p">:]</span><span class="o">=</span> <span class="n">d3</span>
    <span class="n">d2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">clip</span><span class="p">(</span><span class="n">d2</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="kc">None</span><span class="p">)</span>
    <span class="n">res</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log1p</span><span class="p">(</span><span class="n">d2</span><span class="p">)</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
    <span class="k">return</span> <span class="n">res</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">makeSubmission</span><span class="p">(</span><span class="n">preds</span><span class="p">,</span> <span class="n">inds</span><span class="p">,</span> <span class="n">steps</span><span class="o">=</span><span class="p">[</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">7</span><span class="p">],</span> <span class="n">filename</span><span class="o">=</span><span class="s2">&quot;./submission/result.csv&quot;</span><span class="p">):</span>
    <span class="n">stack</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="k">for</span> <span class="n">ind</span><span class="p">,</span><span class="n">pred</span><span class="p">,</span><span class="n">step</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">inds</span><span class="p">,</span> <span class="n">preds</span><span class="p">,</span> <span class="n">steps</span><span class="p">):</span>
        <span class="n">pred</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">pred</span><span class="p">)</span><span class="o">.</span><span class="n">transpose</span><span class="p">()</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">expm1</span><span class="p">(</span><span class="n">pred</span><span class="p">),</span><span class="n">index</span><span class="o">=</span><span class="n">ind</span><span class="p">)</span> 
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">reset_index</span><span class="p">()</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s2">&quot;store_id&quot;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s2">&quot;type_id&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">sum</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">tmp</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">step</span><span class="p">)</span>
        <span class="n">stack</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
    <span class="n">stack_pred</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">stack</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">stack_pred</span><span class="p">[:</span><span class="mi">16</span><span class="p">]</span> <span class="o">=</span> <span class="n">stack_pred</span><span class="p">[:</span><span class="mi">16</span><span class="p">]</span><span class="o">*</span><span class="mi">1000</span>
    <span class="n">stack_pred</span><span class="p">[</span><span class="mi">16</span><span class="p">:]</span> <span class="o">=</span> <span class="n">stack_pred</span><span class="p">[</span><span class="mi">16</span><span class="p">:]</span><span class="o">*</span><span class="mi">1000</span>
    <span class="n">result</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;./submission/result_org.csv&quot;</span><span class="p">)</span>
    <span class="n">result</span><span class="p">[</span><span class="s2">&quot;VALUE&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">stack_pred</span>
    <span class="n">result</span><span class="o">.</span><span class="n">to_csv</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span><span class="n">float_format</span><span class="o">=</span><span class="s2">&quot;</span><span class="si">%.4f</span><span class="s2">&quot;</span><span class="p">,</span><span class="n">index</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;done!&quot;</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">stack_pred</span>
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<h4 id="&#20351;&#29992;">&#20351;&#29992;<a class="anchor-link" href="#&#20351;&#29992;">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">x_test_in_Wall</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_test_in_W</span><span class="p">,</span> <span class="n">x_test_in_2W</span><span class="p">,</span> <span class="n">x_test_in_3W</span><span class="p">,</span> <span class="n">x_test_in_4W</span><span class="p">]</span>
<span class="n">x_test_ext_Wall</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_test_ext_W</span><span class="p">,</span> <span class="n">x_test_ext_2W</span><span class="p">,</span> <span class="n">x_test_ext_3W</span><span class="p">,</span> <span class="n">x_test_ext_4W</span><span class="p">]</span>
<span class="n">test</span> <span class="o">=</span> <span class="p">[</span><span class="n">x_test_ext_W</span><span class="p">,</span> <span class="n">x_test_in_W</span><span class="p">,</span> <span class="n">x_test_ext</span><span class="p">,</span> <span class="n">x_test_in</span><span class="p">]</span>

<span class="n">mpath</span> <span class="o">=</span> <span class="s1">&#39;./model/model1&#39;</span>
<span class="n">res_ext_W</span> <span class="o">=</span> <span class="n">prediction</span><span class="p">(</span><span class="n">x_test_ext_Wall</span><span class="p">,</span><span class="n">path</span><span class="o">=</span><span class="n">mpath</span><span class="p">,</span><span class="n">mode</span><span class="o">=</span><span class="s2">&quot;w&quot;</span><span class="p">)</span>
<span class="n">res_in_W</span> <span class="o">=</span> <span class="n">prediction</span><span class="p">(</span><span class="n">x_test_in_Wall</span><span class="p">,</span><span class="n">path</span><span class="o">=</span><span class="n">mpath</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;w&quot;</span><span class="p">)</span>
<span class="n">res</span> <span class="o">=</span> <span class="n">prediction</span><span class="p">(</span><span class="n">test</span><span class="p">,</span><span class="n">path</span><span class="o">=</span><span class="n">mpath</span><span class="p">)</span>

<span class="c1"># 求各周</span>
<span class="n">res1</span> <span class="o">=</span> <span class="n">getLastW</span><span class="p">(</span><span class="n">res_ext_W</span><span class="p">)</span>
<span class="n">res2</span> <span class="o">=</span> <span class="n">getLastW</span><span class="p">(</span><span class="n">res_in_W</span><span class="p">)</span>
<span class="n">results</span> <span class="o">=</span> <span class="p">[</span><span class="n">res1</span><span class="p">,</span><span class="n">res2</span><span class="p">,</span><span class="n">res</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span><span class="n">res</span><span class="p">[</span><span class="mi">3</span><span class="p">]]</span>

<span class="n">inds</span> <span class="o">=</span> <span class="p">[</span><span class="n">df_train_ext_W</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">df_train_in_W</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">df_train_ext</span><span class="o">.</span><span class="n">index</span><span class="p">,</span> <span class="n">df_train_in</span><span class="o">.</span><span class="n">index</span><span class="p">]</span>

<span class="c1"># 取exp</span>
<span class="n">pred1</span> <span class="o">=</span> <span class="n">makeSubmission</span><span class="p">(</span><span class="n">results</span><span class="p">,</span> <span class="n">inds</span><span class="p">)</span>
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<pre>./model/model1/bst_byweek1.model
./model/model1/bst_byweek2.model
./model/model1/bst_byweek3.model
./model/model1/bst_byweek4.model
./model/model1/bst_byweek1.model
./model/model1/bst_byweek2.model
./model/model1/bst_byweek3.model
./model/model1/bst_byweek4.model
./model/model1/bst_byday1.model
./model/model1/bst_byday2.model
./model/model1/bst_byday3.model
./model/model1/bst_byday4.model
./model/model1/bst_byday5.model
./model/model1/bst_byday6.model
./model/model1/bst_byday7.model
./model/model1/bst_byday1.model
./model/model1/bst_byday2.model
./model/model1/bst_byday3.model
./model/model1/bst_byday4.model
./model/model1/bst_byday5.model
./model/model1/bst_byday6.model
./model/model1/bst_byday7.model
done!
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