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background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 -0.5 15 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e6eefc' d='M0 0h1'/%3E%3Cpath stroke='%23d1e0fd' d='M1 0h1M0 1h1m3 0h2M2 3h1M2 4h1'/%3E%3Cpath stroke='%23cad8f9' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23c4d3f7' d='M3 0h1M0 3h1M0 4h1'/%3E%3Cpath stroke='%23bfd0f8' d='M4 0h2M0 5h1'/%3E%3Cpath stroke='%23bdcef7' d='M6 0h1M0 6h1'/%3E%3Cpath stroke='%23baccf4' d='M7 0h1m6 2h1m-1 5h1m-1 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M8 0h1M0 7h1M0 8h1'/%3E%3Cpath stroke='%23b7caf5' d='M9 0h2M0 9h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 0h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 0h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 0h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 0h1'/%3E%3Cpath stroke='%23e1eafe' d='M1 1h1'/%3E%3Cpath stroke='%23dae6fe' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23d4e1fc' d='M3 1h1M1 3h1M1 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M6 1h1M1 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M7 1h1M4 2h2'/%3E%3Cpath stroke='%23cad9fd' d='M8 1h1M6 2h1M3 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M9 1h2'/%3E%3Cpath stroke='%23c5d6fc' d='M11 1h1M2 11h4'/%3E%3Cpath stroke='%23c2d3fc' d='M12 1h1m-2 1h1M1 11h1m0 1h2m-2 1h2'/%3E%3Cpath stroke='%23bccefa' d='M13 1h1m-1 1h1m-1 1h1m-1 1h1M3 15h4'/%3E%3Cpath stroke='%23b9c9f3' d='M14 1h1M3 16h4'/%3E%3Cpath stroke='%23d8e3fc' d='M2 2h1'/%3E%3Cpath stroke='%23d1defd' d='M3 2h1'/%3E%3Cpath stroke='%23c9d8fc' d='M7 2h1M4 3h3M4 4h3M3 6h1m1 0h2M1 7h1M1 8h1'/%3E%3Cpath stroke='%23c5d5fc' d='M8 2h1m-8 8h5'/%3E%3Cpath stroke='%23c5d3fc' d='M9 2h2'/%3E%3Cpath stroke='%23bed0fc' d='M12 2h1M8 3h1M8 4h1m-8 8h1m-1 1h1m0 1h1m1 0h3'/%3E%3Cpath stroke='%23cddbfc' d='M3 3h1M3 4h1M1 6h2'/%3E%3Cpath stroke='%23c8d5fb' d='M7 3h1M7 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M9 3h4M9 4h4M8 5h1M7 6h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 3h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23ceddfd' d='M2 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M4 5h4M1 9h3'/%3E%3Cpath stroke='%23bacdfc' d='M9 5h2m1 0h2M1 14h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1M8 6h2m2 0h2m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%234d6185' d='M4 6h1m5 0h1M3 7h3m3 0h3M4 8h3m1 0h3M5 9h5m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1m-1 1h1'/%3E%3Cpath stroke='%23cad8fd' d='M2 7h1M2 8h2'/%3E%3Cpath stroke='%23c1d3fb' d='M6 7h2M7 8h1M4 9h1'/%3E%3Cpath stroke='%23b6cefb' d='M8 7h1m2 1h1m-2 1h3m-2 1h2'/%3E%3Cpath stroke='%23b6cdfb' d='M13 9h1m-6 6h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 9h1'/%3E%3Cpath stroke='%23b4c8f6' d='M0 10h1'/%3E%3Cpath stroke='%23bdd3fb' d='M9 10h2m-4 4h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 10h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 10h1'/%3E%3Cpath stroke='%23b1c7f6' d='M0 11h1'/%3E%3Cpath stroke='%23c3d5fd' d='M6 11h1'/%3E%3Cpath stroke='%23bad4fc' d='M8 11h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M9 11h4m-2 3h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 11h1m-3 4h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 11h1m-7 5h3'/%3E%3Cpath stroke='%23adc3f6' d='M0 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c2d5fc' d='M4 12h4m-4 1h4'/%3E%3Cpath stroke='%23b7d3fc' d='M9 12h2m-2 1h2m-3 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 12h1m-1 1h1'/%3E%3Cpath stroke='%23afcdfb' d='M12 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afcbfa' d='M13 12h1m-1 1h1'/%3E%3Cpath stroke='%23b2c8f4' d='M14 12h1m-1 1h1m-4 3h1'/%3E%3Cpath stroke='%23c1d2fb' d='M3 14h1'/%3E%3Cpath stroke='%23b6d1fb' d='M9 14h2'/%3E%3Cpath stroke='%23adc9f9' d='M13 14h1m-2 1h1'/%3E%3Cpath stroke='%23b1c6f3' d='M14 14h1m-3 2h1'/%3E%3Cpath stroke='%23abc1f4' d='M0 15h1'/%3E%3Cpath stroke='%23b7cbf9' d='M1 15h1'/%3E%3Cpath stroke='%23b9cefb' d='M2 15h1'/%3E%3Cpath stroke='%23b9cffb' d='M7 15h1'/%3E%3Cpath stroke='%23b2cdfb' d='M9 15h2'/%3E%3Cpath stroke='%23aec8f7' d='M13 15h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 15h1m-2 1h1'/%3E%3Cpath stroke='%23dbe3f8' d='M0 16h1'/%3E%3Cpath stroke='%23b7c6f1' d='M1 16h1'/%3E%3Cpath stroke='%23b8c9f2' d='M2 16h1m4 0h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 16h1'/%3E%3C/svg%3E");
background-size: 15px;
font-size: 11px;
border: none;
background-color: #fff;
box-sizing: border-box;
height: 21px;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
position: relative;
padding: 5px 32px 32px 5px;
background-position: top 50% right 2px;
background-repeat: no-repeat;
border-radius: 0;
border: 1px solid black;
}
body {
font-variant: oldstyle-nums;
font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
background-color: #fafafa;
text-shadow: 0 0.05em 0.1em rgba(0,0,0,0.2);
scroll-behavior: smooth;
text-wrap: balance;
text-rendering: optimizeLegibility;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
font-feature-settings: "ss02", "liga", "onum";
}
.marked_text {
background-color: yellow;
}
.time_picker_container {
font-variant: small-caps;
width: 100%;
}
.time_picker_container > input {
width: 50px;
}
#loader {
display: grid;
justify-content: center;
align-items: center;
height: 100%;
}
.no_linebreak {
line-break: auto;
}
.dark_code_bg {
background-color: #363636;
color: white;
}
.code_bg {
background-color: #C0C0C0;
}
#commands {
line-break: anywhere;
}
.color_red {
color: red;
}
.color_orange {
color: orange;
}
table > tbody > tr:nth-child(odd) {
background-color: #fafafa;
}
table > tbody > tr:nth-child(even) {
background-color: #ddd;
}
table {
border-collapse: collapse;
margin: 0 0;
min-width: 200px;
}
th {
background-color: #4eae46;
color: #ffffff;
text-align: left;
border: 0px;
}
.error_element {
background-color: #e57373;
border-radius: 10px;
padding: 4px;
display: none;
}
button {
background-color: #4eae46;
border: 1px solid #2A8387;
border-radius: 4px;
box-shadow: rgba(0, 0, 0, 0.12) 0 1px 1px;
cursor: pointer;
display: block;
line-height: 100%;
outline: 0;
padding: 11px 15px 12px;
text-align: center;
transition: box-shadow .05s ease-in-out, opacity .05s ease-in-out;
user-select: none;
-webkit-user-select: none;
touch-action: manipulation;
font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
}
button:hover {
box-shadow: rgba(255, 255, 255, 0.3) 0 0 2px inset, rgba(0, 0, 0, 0.4) 0 1px 2px;
text-decoration: none;
transition-duration: .15s, .15s;
}
button:active {
box-shadow: rgba(0, 0, 0, 0.15) 0 2px 4px inset, rgba(0, 0, 0, 0.4) 0 1px 1px;
}
button:disabled {
cursor: not-allowed;
opacity: .6;
}
button:disabled:active {
pointer-events: none;
}
button:disabled:hover {
box-shadow: none;
}
.half_width_td {
vertical-align: baseline;
width: 50%;
}
#scads_bar {
width: 100%;
margin: 0;
padding: 0;
user-select: none;
user-drag: none;
-webkit-user-drag: none;
user-select: none;
-moz-user-select: none;
-webkit-user-select: none;
-ms-user-select: none;
display: -webkit-box;
}
.tab {
display: inline-block;
padding: 0px;
margin: 0px;
font-size: 16px;
font-weight: bold;
text-align: center;
border-radius: 25px;
text-decoration: none !important;
transition: background-color 0.3s, color 0.3s;
color: unset !important;
}
.tooltipster-base {
border: 1px solid black;
position: absolute;
border-radius: 8px;
padding: 2px;
color: white;
background-color: #61686f;
width: 70%;
min-width: 200px;
pointer-events: none;
}
td {
padding-top: 3px;
padding-bottom: 3px;
}
.left_side {
text-align: right;
}
.right_side {
text-align: left;
}
.spinner {
border: 8px solid rgba(0, 0, 0, 0.1);
border-left: 8px solid #3498db;
border-radius: 50%;
width: 50px;
height: 50px;
animation: spin 1s linear infinite;
}
@keyframes spin {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
#spinner-overlay {
-webkit-text-stroke: 1px black;
white !important;
position: fixed;
top: 0;
left: 0;
width: 100%;
height: 100%;
display: flex;
justify-content: center;
align-items: center;
z-index: 9999;
}
#spinner-container {
text-align: center;
color: #fff;
display: contents;
}
#spinner-text {
font-size: 3vw;
margin-left: 10px;
}
a, a:visited, a:active, a:hover, a:link {
color: #007bff;
text-decoration: none;
}
.copy-container {
display: inline-block;
position: relative;
cursor: pointer;
margin-left: 10px;
color: blue;
}
.copy-container:hover {
text-decoration: underline;
}
.clipboard-icon {
position: absolute;
top: 5px;
right: 5px;
font-size: 1.5em;
}
#main_tab {
overflow: scroll;
width: max-content;
}
.ui-tabs .ui-tabs-nav li {
user-select: none;
}
.stacktrace_table {
background-color: black !important;
color: white !important;
}
#breadcrumb {
user-select: none;
}
#statusBar {
user-select: none;
}
.error_line {
background-color: red !important;
color: white !important;
}
.header_table {
border: 0px !important;
padding: 0px !important;
width: revert !important;
min-width: revert !important;
}
.img_auto_width {
max-width: revert !important;
}
#main_dir_or_plot_view {
display: inline-grid;
}
#refresh_button {
width: 300px;
}
._share_link {
color: black !important;
}
#footer_element {
height: 30px;
background-color: #f8f9fa;
padding: 0px;
text-align: center;
border-top: 1px solid #dee2e6;
width: 100%;
box-sizing: border-box;
position: fixed;
bottom: 0;
z-index: 2;
margin-left: -9px;
z-index: 99;
}
.switch {
position: relative;
display: inline-block;
width: 50px;
height: 26px;
}
.switch input {
opacity: 0;
width: 0;
height: 0;
}
.slider {
position: absolute;
cursor: pointer;
top: 0;
left: 0;
right: 0;
bottom: 0;
background-color: #ccc;
transition: .4s;
border-radius: 26px;
}
.slider:before {
position: absolute;
content: "";
height: 20px;
width: 20px;
left: 3px;
bottom: 3px;
background-color: white;
transition: .4s;
border-radius: 50%;
}
input:checked + .slider {
background-color: #444;
}
input:checked + .slider:before {
transform: translateX(24px);
}
.mode-text {
position: absolute;
top: 5px;
left: 65px;
font-size: 14px;
color: black;
transition: .4s;
width: 65px;
display: block;
font-size: 0.7rem;
text-align: center;
}
input:checked + .slider .mode-text {
content: "Dark Mode";
color: white;
}
#mainContent {
height: fit-content;
min-height: 100%;
}
li {
text-align: left;
}
#share_path {
margin-bottom: 20px;
margin-top: 20px;
}
#sortForm {
margin-bottom: 20px;
}
.share_folder_buttons {
margin-top: 10px;
margin-bottom: 10px;
}
.nav_tab_button {
margin: 10px;
}
.header_table {
margin: 10px;
}
.no_border {
border: unset !important;
}
.gui_table {
padding: 5px !important;
}
.gui_parameter_row {
}
.gui_parameter_row_cell {
border: unset !important;
}
.gui_param_table {
width: 95%;
margin: unset !important;
}
table td, table tr,
.parameterRow table {
padding: 2px !important;
}
.parameterRow table {
margin: 0px;
border: unset;
}
.parameterRow > td {
border: 0px !important;
}
.parameter_config_table td, .parameter_config_table tr, #config_table th, #config_table td, #hidden_config_table th, #hidden_config_table td {
border: 0px !important;
}
.green_text {
color: green;
}
.remove_parameter {
white-space: pre;
}
select {
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
background-color: #fff;
color: #222;
padding: 5px 30px 5px 5px;
border: 1px solid #555;
border-radius: 5px;
cursor: pointer;
outline: none;
transition: all 0.3s ease;
background:
url("data:image/svg+xml;charset=UTF-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 10 6'%3E%3Cpath fill='%23888' d='M0 0l5 6 5-6z'/%3E%3C/svg%3E")
no-repeat right 10px center,
linear-gradient(180deg, #fff, #ecebe5 86%, #d8d0c4);
background-size: 12px, auto;
}
select:hover {
border-color: #888;
}
select:focus {
border-color: #4caf50;
box-shadow: 0 0 5px rgba(76, 175, 80, 0.5);
}
select::-ms-expand {
display: none;
}
input, textarea {
border-radius: 5px;
}
#search {
width: 200px;
max-width: 70%;
background-image: url(images/search.svg);
background-repeat: no-repeat;
background-size: auto 40px;
height: 40px;
line-height: 40px;
padding-left: 40px;
box-sizing: border-box;
}
input[type="checkbox"] {
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
width: 25px;
height: 25px;
border: 2px solid #3498db;
border-radius: 5px;
background-color: #fff;
position: relative;
cursor: pointer;
transition: all 0.3s ease;
width: 25px !important;
}
input[type="checkbox"]:checked {
background-color: #3498db;
border-color: #2980b9;
}
input[type="checkbox"]:checked::before {
content: '✔';
position: absolute;
left: 4px;
top: 2px;
color: #fff;
}
input[type="checkbox"]:hover {
border-color: #2980b9;
background-color: #3caffc;
}
.toc {
margin-bottom: 20px;
}
.toc li {
margin-bottom: 5px;
}
.toc a {
text-decoration: none;
color: #007bff;
}
.toc a:hover {
text-decoration: underline;
}
.table-container {
width: 100%;
overflow-x: auto;
}
.section-header {
background-color: #1d6f9a !important;
color: white;
}
.warning {
color: red;
}
.li_list a {
text-decoration: none;
}
.gridjs-td {
white-space: nowrap;
}
th, td {
border: 1px solid gray !important;
}
.no_border {
border: 0px !important;
}
.no_break {
}
img {
user-select: none;
pointer-events: none;
}
#config_table, #hidden_config_table {
user-select: none;
}
.copy_clipboard_button {
margin-bottom: 10px;
}
.badge_table {
background-color: unset !important;
}
.make_markable {
user-select: text;
}
.header-container {
display: flex;
flex-wrap: wrap;
align-items: center;
justify-content: space-between;
gap: 1rem;
padding: 10px;
background: var(--header-bg, #fff);
border-bottom: 1px solid #ccc;
}
.header-logo-group {
display: flex;
gap: 1rem;
align-items: center;
flex: 1 1 auto;
min-width: 200px;
}
.logo-img {
max-height: 45px;
height: auto;
width: auto;
object-fit: contain;
pointer-events: unset;
}
.header-badges {
flex-direction: column;
gap: 5px;
align-items: flex-start;
flex: 0 1 auto;
margin-top: auto;
margin-bottom: auto;
}
.badge-img {
height: auto;
max-width: 130px;
margin-top: 3px;
}
.header-tabs {
margin-top: 10px;
display: flex;
flex-wrap: wrap;
gap: 10px;
flex: 2 1 100%;
justify-content: center;
}
.nav-tab {
display: inline-block;
text-decoration: none;
padding: 8px 16px;
border-radius: 20px;
background: linear-gradient(to right, #4a90e2, #357ABD);
color: white;
font-weight: bold;
white-space: nowrap;
transition: background 0.2s ease-in-out, transform 0.2s;
box-shadow: 0 2px 4px rgba(0,0,0,0.2);
}
.nav-tab:hover {
background: linear-gradient(to right, #5aa0f2, #4a90e2);
transform: translateY(-2px);
}
.current-tag {
padding-left: 10px;
font-size: 0.9rem;
color: #666;
}
.header-theme-toggle {
flex: 1 1 auto;
align-items: center;
margin-top: 20px;
min-width: 120px;
}
.switch {
position: relative;
display: inline-block;
width: 60px;
height: 30px;
}
.switch input {
display: none;
}
.slider {
position: absolute;
top: 0; left: 0; right: 0; bottom: 0;
background-color: #ccc;
border-radius: 34px;
cursor: pointer;
}
.slider::before {
content: "";
position: absolute;
height: 24px;
width: 24px;
left: 3px;
bottom: 3px;
background-color: white;
transition: .4s;
border-radius: 50%;
}
input:checked + .slider {
background-color: #2196F3;
}
input:checked + .slider::before {
transform: translateX(30px);
}
@media (max-width: 768px) {
.header-logo-group,
.header-badges,
.header-theme-toggle {
justify-content: center;
flex: 1 1 100%;
text-align: center;
width: inherit;
}
.logo-img {
max-height: 50px;
pointer-events: unset;
}
.badge-img {
max-width: 100px;
}
.hide_on_mobile {
display: none;
}
.nav-tab {
font-size: 0.9rem;
padding: 6px 12px;
}
.header_button {
white-space: pre;
font-size: 2em;
}
}
.header_button {
white-space: pre;
margin-top: 20px;
margin: 5px;
}
.line_break_anywhere {
line-break: anywhere;
}
.responsive-container {
display: flex;
flex-wrap: wrap;
justify-content: space-between;
gap: 20px;
}
.responsive-container .half {
flex: 1 1 48%;
box-sizing: border-box;
min-width: 500px;
}
.config-section table {
width: 100%;
border-collapse: collapse;
}
@media (max-width: 768px) {
.responsive-container .half {
flex: 1 1 100%;
}
}
@keyframes spin {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
.rotate {
animation: spin 2s linear infinite;
display: inline-block;
}
input::placeholder {
font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
}
.gridjs-th-content {
overflow: visible !important;
}
.error_text {
color: red;
}
h1, h2, h3, h4, h5, h6 {
margin-top: 1em;
font-weight: bold;
color: #333;
border-left: 5px solid #ccc;
padding-left: 0.5em;
}
.no_cursive {
font-style: normal;
}
.caveat {
background-color: #fff8b3;
border: 1px solid #f2d600;
padding: 1em 1em 1em 70px;
position: relative;
font-family: sans-serif;
color: #665500;
margin: 1em 0;
border-radius: 4px;
}
.caveat h1, .caveat h2, .caveat h3, .caveat h4 {
margin-top: 0;
margin-bottom: 0.5em;
font-weight: bold;
}
.caveat::before {
content: "⚠️";
font-size: 50px;
line-height: 1;
position: absolute;
left: 10px;
top: 50%;
transform: translateY(-50%);
pointer-events: none;
user-select: none;
}
.caveat.warning::before { content: "⚠️"; }
.caveat.stop::before { content: "🛑"; }
.caveat.exclamation::before { content: "❗"; }
.caveat.alarm::before { content: "🚨"; }
.caveat.tip::before { content: "💡"; }
.tutorial_icon {
display: inline-block;
font-size: 1.3em;
line-height: 1;
vertical-align: middle;
transform: translateY(-10%);
padding: 0.2em 0;
}
.highlight {
background-color: yellow;
font-weight: bold;
}
#searchResults li {
opacity: 0;
transform: translateY(8px);
animation: fadeInUp 0.3s ease-out forwards;
animation-delay: 0.05s;
list-style: none;
margin-bottom: 5px;
}
@keyframes fadeInUp {
to {
opacity: 1;
transform: translateY(0);
}
}
.search_headline {
font-weight: bold;
margin-top: 1em;
margin-bottom: 0.3em;
color: #444;
}
.search_share_path {
color: black;
display: block ruby;
margin-top: 20px;
}
@media print {
#scads_bar {
display: none !important;
}
}
/*! XP.css v0.2.6 - https: //botoxparty.github.io/XP.css/ */
body{
color: #222
}
.surface{
background: #ece9d8
}
u{
text-decoration: none;
border-bottom: .5px solid #222
}
a{
color: #00f
}
a: focus{
outline: 1px dotted #00f
}
code,code *{
font-family: monospace
}
pre{
display: block;
padding: 12px 8px;
background-color: #000;
color: silver;
font-size: 1rem;
margin: 0;
overflow: scroll;
}
summary: focus{
outline: 1px dotted #000
}
: :-webkit-scrollbar{
width: 16px
}
: :-webkit-scrollbar: horizontal{
height: 17px
}
: :-webkit-scrollbar-track{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='2' height='2' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 0H0v1h1v1h1V1H1V0z' fill='silver'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 0H1v1H0v1h1V1h1V0z' fill='%23fff'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb{
background-color: #dfdfdf;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}
: :-webkit-scrollbar-button: horizontal: end: increment,: :-webkit-scrollbar-button: horizontal: start: decrement,: :-webkit-scrollbar-button: vertical: end: increment,: :-webkit-scrollbar-button: vertical: start: decrement{
display: block
}
: :-webkit-scrollbar-button: vertical: start{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 6H7v1H6v1H5v1H4v1h7V9h-1V8H9V7H8V6z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: end{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 6H4v1h1v1h1v1h1v1h1V9h1V8h1V7h1V6z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: horizontal: start{
width: 16px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 4H8v1H7v1H6v1H5v1h1v1h1v1h1v1h1V4z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: horizontal: end{
width: 16px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7 4H6v7h1v-1h1V9h1V8h1V7H9V6H8V5H7V4z' fill='%23000'/%3E%3C/svg%3E")
}
button{
border: none;
background: #ece9d8;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf;
border-radius: 0;
min-width: 75px;
min-height: 23px;
padding: 0 12px
}
button: not(: disabled).active,button: not(: disabled): active{
box-shadow: inset -1px -1px #fff,inset 1px 1px #0a0a0a,inset -2px -2px #dfdfdf,inset 2px 2px grey
}
button.focused,button: focus{
outline: 1px dotted #000;
outline-offset: -4px
}
label{
display: inline-flex;
align-items: center
}
textarea{
padding: 3px 4px;
border: none;
background-color: #fff;
box-sizing: border-box;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
border-radius: 0
}
textarea: focus{
outline: none
}
select: focus option{
color: #000;
background-color: #fff
}
.vertical-bar{
width: 4px;
height: 20px;
background: silver;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}
&: disabled,&: disabled+label{
color: grey;
text-shadow: 1px 1px 0 #fff
}
input[type=radio]+label{
line-height: 13px;
position: relative;
margin-left: 19px
}
input[type=radio]+label: before{
content: "";
position: absolute;
top: 0;
left: -19px;
display: inline-block;
width: 13px;
height: 13px;
margin-right: 6px;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='%23fff'/%3E%3C/svg%3E")
}
input[type=radio]: active+label: before{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}
input[type=radio]: checked+label: after{
content: "";
display: block;
width: 5px;
height: 5px;
top: 5px;
left: -14px;
position: absolute;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=radio][disabled]+label: before{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}
input[type=radio][disabled]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='gray'/%3E%3C/svg%3E")
}
input[type=email],input[type=password]{
padding: 3px 4px;
border: 1px solid #7f9db9;
background-color: #fff;
box-sizing: border-box;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
border-radius: 0;
height: 21px;
line-height: 2
}
input[type=email]: focus,input[type=password]: focus{
outline: none
}
input[type=range]{
-webkit-appearance: none;
width: 100%;
background: transparent
}
input[type=range]: focus{
outline: none
}
input[type=range]: :-webkit-slider-thumb{
-webkit-appearance: none;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range]: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range]: :-webkit-slider-runnable-track{
background: #000;
border-right: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}
input[type=range]: :-moz-range-track{
background: #000;
border-right: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}
input[type=range].has-box-indicator: :-webkit-slider-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range].has-box-indicator: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}
.is-vertical{
display: inline-block;
width: 4px;
height: 150px;
transform: translateY(50%)
}
.is-vertical>input[type=range]{
width: 150px;
height: 4px;
margin: 0 16px 0 10px;
transform-origin: left;
transform: rotate(270deg) translateX(calc(-50% + 8px))
}
.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
border-left: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}
.is-vertical>input[type=range]: :-moz-range-track{
border-left: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}
.is-vertical>input[type=range]: :-webkit-slider-thumb{
transform: translateY(-8px) scaleX(-1)
}
.is-vertical>input[type=range]: :-moz-range-thumb{
transform: translateY(2px) scaleX(-1)
}
.is-vertical>input[type=range].has-box-indicator: :-webkit-slider-thumb{
transform: translateY(-10px) scaleX(-1)
}
.is-vertical>input[type=range].has-box-indicator: :-moz-range-thumb{
transform: translateY(0) scaleX(-1)
}
.window{
font-size: 11px;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #dfdfdf,inset -2px -2px grey,inset 2px 2px #fff;
background: #ece9d8;
padding: 3px
}
.window fieldset{
margin-bottom: 9px
}
.title-bar{
background: #000;
padding: 3px 2px 3px 3px;
display: flex;
justify-content: space-between;
align-items: center
}
.title-bar-text{
font-weight: 700;
color: #fff;
letter-spacing: 0;
margin-right: 24px
}
.title-bar-controls button{
padding: 0;
display: block;
min-width: 16px;
min-height: 14px
}
.title-bar-controls button: focus{
outline: none
}
.window-body{
margin: 8px
}
.window-body pre{
margin: -8px
}
.status-bar{
margin: 0 1px;
display: flex;
gap: 1px
}
.status-bar-field{
box-shadow: inset -1px -1px #dfdfdf,inset 1px 1px grey;
flex-grow: 1;
padding: 2px 3px;
margin: 0
}
ul.tree-view{
display: block;
background: #fff;
padding: 6px;
margin: 0
}
ul.tree-view li{
list-style-type: none;
margin-top: 3px
}
ul.tree-view a{
text-decoration: none;
color: #000
}
ul.tree-view a: focus{
background-color: #2267cb;
color: #fff
}
ul.tree-view ul{
margin-top: 3px;
margin-left: 16px;
padding-left: 16px;
border-left: 1px dotted grey
}
ul.tree-view ul>li{
position: relative
}
ul.tree-view ul>li: before{
content: "";
display: block;
position: absolute;
left: -16px;
top: 6px;
width: 12px;
border-bottom: 1px dotted grey
}
ul.tree-view ul>li: last-child: after{
content: "";
display: block;
position: absolute;
left: -20px;
top: 7px;
bottom: 0;
width: 8px;
background: #fff
}
ul.tree-view ul details>summary: before{
margin-left: -22px;
position: relative;
z-index: 1
}
ul.tree-view details{
margin-top: 0
}
ul.tree-view details>summary: before{
text-align: center;
display: block;
float: left;
content: "+";
border: 1px solid grey;
width: 8px;
height: 9px;
line-height: 9px;
margin-right: 5px;
padding-left: 1px;
background-color: #fff
}
ul.tree-view details[open] summary{
margin-bottom: 0
}
ul.tree-view details[open]>summary: before{
content: "-"
}
fieldset{
border-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='5' height='5' fill='gray' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h5v5H0V2h2v1h1V2H0' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h4v4H0V1h1v2h2V1H0'/%3E%3C/svg%3E") 2;
padding: 10px;
padding-block-start: 8px;
margin: 0
}
legend{
background: #ece9d8
}
menu[role=tablist]{
position: relative;
margin: 0 0 -2px;
text-indent: 0;
list-style-type: none;
display: flex;
padding-left: 3px
}
menu[role=tablist] button{
z-index: 1;
display: block;
color: #222;
text-decoration: none;
min-width: unset
}
menu[role=tablist] button[aria-selected=true]{
padding-bottom: 2px;margin-top: -2px;background-color: #ece9d8;position: relative;z-index: 8;margin-left: -3px;margin-bottom: 1px
}
menu[role=tablist] button: focus{
outline: 1px dotted #222;outline-offset: -4px
}
menu[role=tablist].justified button{
flex-grow: 1;text-align: center
}
[role=tabpanel]{
padding: 14px;clear: both;background: linear-gradient(180deg,#fcfcfe,#f4f3ee);border: 1px solid #919b9c;position: relative;z-index: 2;margin-bottom: 9px
}
: :-webkit-scrollbar{
width: 17px
}
: :-webkit-scrollbar-corner{
background: #dfdfdf
}
: :-webkit-scrollbar-track: vertical{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 1' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1'/%3E%3Cpath stroke='%23f3f1ec' d='M1 0h1'/%3E%3Cpath stroke='%23f4f1ec' d='M2 0h1'/%3E%3Cpath stroke='%23f4f3ee' d='M3 0h1'/%3E%3Cpath stroke='%23f5f4ef' d='M4 0h1'/%3E%3Cpath stroke='%23f6f5f0' d='M5 0h1'/%3E%3Cpath stroke='%23f7f7f3' d='M6 0h1'/%3E%3Cpath stroke='%23f9f8f4' d='M7 0h1'/%3E%3Cpath stroke='%23f9f9f7' d='M8 0h1'/%3E%3Cpath stroke='%23fbfbf8' d='M9 0h1'/%3E%3Cpath stroke='%23fbfbf9' d='M10 0h2'/%3E%3Cpath stroke='%23fdfdfa' d='M12 0h1'/%3E%3Cpath stroke='%23fefefb' d='M13 0h3'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-track: horizontal{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 1 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1M0 16h1'/%3E%3Cpath stroke='%23f3f1ec' d='M0 1h1'/%3E%3Cpath stroke='%23f4f1ec' d='M0 2h1'/%3E%3Cpath stroke='%23f4f3ee' d='M0 3h1'/%3E%3Cpath stroke='%23f5f4ef' d='M0 4h1'/%3E%3Cpath stroke='%23f6f5f0' d='M0 5h1'/%3E%3Cpath stroke='%23f7f7f3' d='M0 6h1'/%3E%3Cpath stroke='%23f9f8f4' d='M0 7h1'/%3E%3Cpath stroke='%23f9f9f7' d='M0 8h1'/%3E%3Cpath stroke='%23fbfbf8' d='M0 9h1'/%3E%3Cpath stroke='%23fbfbf9' d='M0 10h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 12h1'/%3E%3Cpath stroke='%23fefefb' d='M0 13h1m-1 1h1m-1 1h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb{
background-position: 50%;
background-repeat: no-repeat;
background-color: #c8d6fb;
background-size: 7px;
border: 1px solid #fff;
border-radius: 2px;
box-shadow: inset -3px 0 #bad1fc,inset 1px 1px #b7caf5
}
: :-webkit-scrollbar-thumb: vertical{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 7 8' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h6M0 2h6M0 4h6M0 6h6'/%3E%3Cpath stroke='%23bad1fc' d='M6 0h1M6 2h1M6 4h1'/%3E%3Cpath stroke='%23c8d6fb' d='M0 1h1M0 3h1M0 5h1M0 7h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h6M1 3h6M1 5h6M1 7h6'/%3E%3Cpath stroke='%23bad3fc' d='M6 6h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb: horizontal{
background-size: 8px;background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 8 7' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h1m1 0h1m1 0h1m1 0h1M0 1h1m1 0h1m1 0h1m1 0h1M0 2h1m1 0h1m1 0h1m1 0h1M0 3h1m1 0h1m1 0h1m1 0h1M0 4h1m1 0h1m1 0h1m1 0h1M0 5h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23c8d6fb' d='M1 0h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h1m1 0h1m1 0h1m1 0h1M1 2h1m1 0h1m1 0h1m1 0h1M1 3h1m1 0h1m1 0h1m1 0h1M1 4h1m1 0h1m1 0h1m1 0h1M1 5h1m1 0h1m1 0h1m1 0h1M1 6h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23bad1fc' d='M0 6h1m1 0h1'/%3E%3Cpath stroke='%23bad3fc' d='M4 6h1m1 0h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: start{
height: 17px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h1m1 0h1'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M5 6h2M3 7h1'/%3E%3Cpath stroke='%23c5d5fc' d='M9 3h1M3 9h1m3 0h1'/%3E%3Cpath stroke='%23c5d3fc' d='M10 3h1'/%3E%3Cpath stroke='%23bed0fc' d='M12 3h1M9 4h1m-7 7h1m0 1h1'/%3E%3Cpath stroke='%23bccdfa' d='M13 3h1'/%3E%3Cpath stroke='%23baccf4' d='M14 3h1'/%3E%3Cpath stroke='%23bdcbda' d='M16 3h1'/%3E%3Cpath stroke='%23c4d4f7' d='M2 4h1'/%3E%3Cpath stroke='%23cddbfc' d='M5 4h1M3 6h1'/%3E%3Cpath stroke='%23c8d5fb' d='M8 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M10 4h3M9 5h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 4h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c2d5' d='M16 4h1'/%3E%3Cpath stroke='%23bed0f8' d='M2 5h1'/%3E%3Cpath stroke='%23ceddfd' d='M4 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M6 5h2M3 8h2'/%3E%3Cpath stroke='%234d6185' d='M8 5h1M7 6h3M6 7h5M5 8h3m1 0h3M4 9h3m3 0h3m-8 1h1m5 0h1'/%3E%3Cpath stroke='%23bacdfc' d='M10 5h1m1 0h2M3 12h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1m-2 1h1m1 0h2m-1 1h1'/%3E%3Cpath stroke='%23a8bbd4' d='M16 5h1'/%3E%3Cpath stroke='%23cddafc' d='M4 6h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1'/%3E%3Cpath stroke='%23a4b8d3' d='M16 6h1'/%3E%3Cpath stroke='%23cad8fd' d='M4 7h2'/%3E%3Cpath stroke='%23b6cefb' d='M11 7h1m0 1h1'/%3E%3Cpath stroke='%23bacbf4' d='M14 7h1'/%3E%3Cpath stroke='%23a0b5d3' d='M16 7h1m-1 1h1m-1 5h1'/%3E%3Cpath stroke='%23c1d3fb' d='M8 8h1'/%3E%3Cpath stroke='%23b6cdfb' d='M13 8h1m-5 5h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 8h1'/%3E%3Cpath stroke='%23b4c8f6' d='M2 9h1'/%3E%3Cpath stroke='%23c2d5fc' d='M8 9h1m-1 1h1m-3 1h2'/%3E%3Cpath stroke='%23bdd3fb' d='M9 9h1m-2 3h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 9h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 9h1'/%3E%3Cpath stroke='%239fb5d2' d='M16 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c7f6' d='M2 10h1'/%3E%3Cpath stroke='%23c3d5fd' d='M7 10h1'/%3E%3Cpath stroke='%23bad4fc' d='M9 10h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M10 10h1m1 0h1m-2 2h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 10h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 10h1m-6 4h2'/%3E%3Cpath stroke='%23adc3f6' d='M2 11h1'/%3E%3Cpath stroke='%23c3d3fd' d='M5 11h1'/%3E%3Cpath stroke='%23c1d5fb' d='M8 11h1'/%3E%3Cpath stroke='%23b7d3fc' d='M10 11h1m-2 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 11h1'/%3E%3Cpath stroke='%23afcefb' d='M12 11h1'/%3E%3Cpath stroke='%23aecafa' d='M13 11h1'/%3E%3Cpath stroke='%23b1c8f3' d='M14 11h1'/%3E%3Cpath stroke='%23acc2f5' d='M2 12h1'/%3E%3Cpath stroke='%23c1d2fb' d='M5 12h1'/%3E%3Cpath stroke='%23bed1fc' d='M6 12h2'/%3E%3Cpath stroke='%23b6d1fb' d='M10 12h1'/%3E%3Cpath stroke='%23afccfb' d='M12 12h1'/%3E%3Cpath stroke='%23adc9f9' d='M13 12h1m-2 1h1'/%3E%3Cpath stroke='%23b1c5f3' d='M14 12h1'/%3E%3Cpath stroke='%23aac0f3' d='M2 13h1'/%3E%3Cpath stroke='%23b7cbf9' d='M3 13h1'/%3E%3Cpath stroke='%23b9cefb' d='M4 13h1'/%3E%3Cpath stroke='%23bbcef9' d='M7 13h1'/%3E%3Cpath stroke='%23b9cffb' d='M8 13h1'/%3E%3Cpath stroke='%23b2cdfb' d='M10 13h1'/%3E%3Cpath stroke='%23b0cbf9' d='M11 13h1'/%3E%3Cpath stroke='%23aec8f7' d='M13 13h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 13h1'/%3E%3Cpath stroke='%23dbe3f8' d='M2 14h1'/%3E%3Cpath stroke='%23b7c6f1' d='M3 14h1'/%3E%3Cpath stroke='%23b8c9f2' d='M4 14h1m3 0h1'/%3E%3Cpath stroke='%23b2c8f4' d='M11 14h1'/%3E%3Cpath stroke='%23b1c6f3' d='M12 14h1'/%3E%3Cpath stroke='%23b0c4f2' d='M13 14h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 14h1'/%3E%3Cpath stroke='%23aec0d6' d='M16 14h1'/%3E%3Cpath stroke='%23c3d4e7' d='M1 15h1'/%3E%3Cpath stroke='%23aec4e5' d='M15 15h1'/%3E%3Cpath stroke='%23edf1f3' d='M1 16h1'/%3E%3Cpath stroke='%23aac0e1' d='M2 16h1'/%3E%3Cpath stroke='%2394b1d9' d='M3 16h1'/%3E%3Cpath stroke='%2388a7d8' d='M4 16h1'/%3E%3Cpath stroke='%2383a4d3' d='M5 16h1'/%3E%3Cpath stroke='%237da0d4' d='M6 16h1m3 0h3'/%3E%3Cpath stroke='%237e9fd2' d='M7 16h1'/%3E%3Cpath stroke='%237c9fd3' d='M8 16h2'/%3E%3Cpath stroke='%2382a4d6' d='M13 16h1'/%3E%3Cpath stroke='%2394b0dd' d='M14 16h1'/%3E%3Cpath stroke='%23ecf2f7' d='M15 16h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: end{
height: 17px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 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}
.window{
box-shadow: inset -1px -1px #00138c,inset 1px 1px #0831d9,inset -2px -2px #001ea0,inset 2px 2px #166aee,inset -3px -3px #003bda,inset 3px 3px #0855dd;
border-top-left-radius: 8px;
border-top-right-radius: 8px;
padding: 0 0 3px;
-webkit-font-smoothing: antialiased
}
.title-bar{
background: linear-gradient(180deg,#0997ff,#0053ee 8%,#0050ee 40%,#06f 88%,#06f 93%,#005bff 95%,#003dd7 96%,#003dd7);
padding: 3px 5px 3px 3px;
border-top: 1px solid #0831d9;
border-left: 1px solid #0831d9;
border-right: 1px solid #001ea0;
border-top-left-radius: 8px;
border-top-right-radius: 7px;
font-size: 13px;
text-shadow: 1px 1px #0f1089;
height: 21px
}
.title-bar-text{
padding-left: 3px
}
.title-bar-controls{
display: flex
}
.title-bar-controls button{
min-width: 21px;
min-height: 21px;
margin-left: 2px;
background-repeat: no-repeat;
background-position: 50%;
box-shadow: none;
background-color: #0050ee;
transition: background .1s;
border: none
}
.title-bar-controls button: active,.title-bar-controls button: focus,.title-bar-controls button: hover{
box-shadow: none!important
}
.title-bar-controls button[aria-label=Minimize]{
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}
.title-bar-controls button[aria-label=Maximize]: not(: disabled): active{
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}
.title-bar-controls button[aria-label=Restore]{
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}
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}
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stroke='%23b5381a' d='M9 4h1M4 9h1'/%3E%3Cpath stroke='%23b8391a' d='M10 4h1m-7 6h1'/%3E%3Cpath stroke='%23ba3a1b' d='M11 4h1m-8 7h2'/%3E%3Cpath stroke='%23bc3b1c' d='M12 4h1m-9 8h1'/%3E%3Cpath stroke='%23bd3c1c' d='M13 4h1m-1 1h1m-2 1h1m-7 6h1m-3 1h2'/%3E%3Cpath stroke='%23be3d1c' d='M14 4h3m-1 1h1m-1 1h1M4 14h1m-1 1h1m-1 1h2'/%3E%3Cpath stroke='%23bf3d1c' d='M17 4h3m-3 1h3m-2 1h2m-1 1h1M4 17h2m-2 1h4m-4 1h4'/%3E%3Cpath stroke='%235b1d0d' d='M1 5h1'/%3E%3Cpath stroke='%239c3016' d='M3 5h1'/%3E%3Cpath stroke='%23a43217' d='M4 5h1'/%3E%3Cpath stroke='%23b8553e' d='M5 5h1'/%3E%3Cpath stroke='%23d59485' d='M6 5h1M5 6h1'/%3E%3Cpath stroke='%23b33619' d='M7 5h1'/%3E%3Cpath stroke='%23b53719' d='M8 5h1'/%3E%3Cpath stroke='%23b8381a' d='M9 5h1M6 8h1'/%3E%3Cpath stroke='%23b9391b' d='M10 5h1'/%3E%3Cpath stroke='%23ba391b' d='M11 5h1M6 9h1m-2 1h1'/%3E%3Cpath stroke='%23bc3b1b' d='M12 5h1m-2 1h1m-6 5h1m-2 1h1'/%3E%3Cpath stroke='%23dc9887' d='M14 5h1'/%3E%3Cpath stroke='%23c85d42' d='M15 5h1M5 15h1'/%3E%3Cpath stroke='%23611f0e' d='M1 6h1'/%3E%3Cpath stroke='%23a23217' d='M3 6h1'/%3E%3Cpath stroke='%23d79585' d='M6 6h1'/%3E%3Cpath stroke='%23d89585' d='M7 6h1'/%3E%3Cpath stroke='%23b8371a' d='M8 6h1'/%3E%3Cpath stroke='%23ba391a' d='M9 6h1'/%3E%3Cpath stroke='%23bb3a1b' d='M10 6h1m-5 4h1'/%3E%3Cpath stroke='%23dd9887' d='M13 6h3m-4 1h1m-2 1h1M9 9h1m-2 2h1m-2 1h1m-2 1h1m-2 1h2'/%3E%3Cpath stroke='%23c03e1d' d='M17 6h1m-2 1h3m0 1h1m-1 1h1M7 16h1m-2 1h2m0 1h1'/%3E%3Cpath stroke='%2365200e' d='M1 7h1'/%3E%3Cpath stroke='%23902d15' d='M2 7h1'/%3E%3Cpath stroke='%23a73418' d='M3 7h1'/%3E%3Cpath stroke='%23af3518' d='M4 7h1'/%3E%3Cpath stroke='%23b43619' d='M5 7h1'/%3E%3Cpath stroke='%23d99585' d='M6 7h1'/%3E%3Cpath stroke='%23da9686' d='M7 7h1'/%3E%3Cpath stroke='%23db9686' d='M8 7h1M7 8h1'/%3E%3Cpath stroke='%23bc3a1b' d='M9 7h1M7 9h1'/%3E%3Cpath stroke='%23bd3b1b' d='M10 7h1m-4 3h1'/%3E%3Cpath stroke='%23be3c1c' d='M11 7h1m-2 1h1m-3 2h1m-2 1h1'/%3E%3Cpath stroke='%23de9987' d='M13 7h2m-3 1h2m-4 1h2m-3 1h1m-2 2h1m-2 2h1'/%3E%3Cpath stroke='%23c03f1d' d='M15 7h1m-9 8h1'/%3E%3Cpath stroke='%236a220f' d='M1 8h1'/%3E%3Cpath stroke='%23952f15' d='M2 8h1'/%3E%3Cpath stroke='%23ac3518' d='M3 8h1'/%3E%3Cpath stroke='%23b63719' d='M5 8h1'/%3E%3Cpath stroke='%23dc9786' d='M8 8h2M8 9h1'/%3E%3Cpath stroke='%23c2401d' d='M14 8h1m2 0h1m1 3h1M8 14h1m-1 2h1m-1 1h1m0 1h1m1 1h1'/%3E%3Cpath stroke='%23c2401e' d='M15 8h2m1 1h1M8 15h1'/%3E%3Cpath stroke='%23c13f1d' d='M18 8h1m0 2h1M9 19h2'/%3E%3Cpath stroke='%23702410' d='M1 9h1'/%3E%3Cpath stroke='%239b3016' d='M2 9h1'/%3E%3Cpath stroke='%23b03619' d='M3 9h1'/%3E%3Cpath stroke='%23b9381a' d='M5 9h1'/%3E%3Cpath stroke='%23df9a88' d='M12 9h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23c4421e' d='M13 9h1m2 0h2m0 1h1M9 13h1m9 1h1m-1 1h1M9 16h1m9 0h1M9 17h1m0 1h1m3 1h3'/%3E%3Cpath stroke='%23c5431e' d='M14 9h1'/%3E%3Cpath stroke='%23c5431f' d='M15 9h1m-4 1h1m5 1h1m-9 1h1m-2 2h1m-1 1h1m0 2h1m0 1h1m6 0h1'/%3E%3Cpath stroke='%239e3217' d='M2 10h1'/%3E%3Cpath stroke='%23b4381a' d='M3 10h1'/%3E%3Cpath stroke='%23df9a87' d='M10 10h1m-2 1h1m-2 2h1'/%3E%3Cpath stroke='%23c6441f' d='M13 10h1m3 0h1m-8 3h1m-1 3h1'/%3E%3Cpath stroke='%23c74520' d='M14 10h2m-6 4h1m-1 1h1m7 2h1m-7 1h1m4 0h1'/%3E%3Cpath stroke='%23c7451f' d='M16 10h1m1 2h1'/%3E%3Cpath stroke='%237b2711' d='M1 11h1'/%3E%3Cpath stroke='%23a13217' d='M2 11h1'/%3E%3Cpath stroke='%23b7391a' d='M3 11h1'/%3E%3Cpath stroke='%23e09b88' d='M11 11h1'/%3E%3Cpath stroke='%23e29d89' d='M12 11h1'/%3E%3Cpath stroke='%23c94621' d='M13 11h1m-3 2h1'/%3E%3Cpath stroke='%23ca4721' d='M14 11h1m2 1h1m-7 2h1m-1 1h1m0 2h1m2 1h1'/%3E%3Cpath stroke='%23ca4821' d='M15 11h1m1 6h1'/%3E%3Cpath stroke='%23c94620' d='M16 11h1m1 3h1m-8 2h1m6 0h1'/%3E%3Cpath stroke='%23c84620' d='M17 11h1m0 2h1'/%3E%3Cpath stroke='%23a53418' d='M2 12h1'/%3E%3Cpath stroke='%23b83a1b' d='M3 12h1'/%3E%3Cpath stroke='%23e19d89' d='M11 12h1'/%3E%3Cpath stroke='%23e39e89' d='M12 12h1'/%3E%3Cpath stroke='%23e0947c' d='M13 12h1'/%3E%3Cpath stroke='%23cc4a22' d='M14 12h1m-3 2h1m4 0h1m-6 1h1'/%3E%3Cpath stroke='%23cd4a22' d='M15 12h1m0 1h1m0 2h1m-5 1h1m1 1h1'/%3E%3Cpath stroke='%23cb4922' d='M16 12h1m0 1h1m-5 4h1'/%3E%3Cpath stroke='%23c3411e' d='M19 12h1m-1 1h1m-1 4h1m-8 2h2m3 0h1'/%3E%3Cpath stroke='%23a93618' d='M2 13h1'/%3E%3Cpath stroke='%23dd9987' d='M7 13h1m-2 2h1'/%3E%3Cpath stroke='%23e39f8a' d='M12 13h1'/%3E%3Cpath stroke='%23e59f8b' d='M13 13h1'/%3E%3Cpath stroke='%23e5a08b' d='M14 13h1m-2 1h1'/%3E%3Cpath stroke='%23ce4c23' d='M15 13h1m0 3h1'/%3E%3Cpath stroke='%23882b13' d='M1 14h1'/%3E%3Cpath stroke='%23e6a08b' d='M14 14h1'/%3E%3Cpath stroke='%23e6a18b' d='M15 14h1m-2 1h1'/%3E%3Cpath stroke='%23ce4b23' d='M16 14h1m-4 1h1'/%3E%3Cpath stroke='%238b2c14' d='M1 15h1m-1 1h1'/%3E%3Cpath stroke='%23ac3619' d='M2 15h1'/%3E%3Cpath stroke='%23d76b48' d='M15 15h1'/%3E%3Cpath stroke='%23cf4c23' d='M16 15h1m-2 1h1'/%3E%3Cpath stroke='%23c94721' d='M18 15h1m-3 3h1'/%3E%3Cpath stroke='%23bb3c1b' d='M3 16h1'/%3E%3Cpath stroke='%23bf3e1d' d='M6 16h1'/%3E%3Cpath stroke='%23cb4821' d='M12 16h1'/%3E%3Cpath stroke='%23cd4b23' d='M14 16h1'/%3E%3Cpath stroke='%23cc4922' d='M17 16h1m-4 1h1m1 0h1'/%3E%3Cpath stroke='%238d2d14' d='M1 17h1'/%3E%3Cpath stroke='%23bc3c1b' d='M3 17h1m-1 1h1'/%3E%3Cpath stroke='%23c84520' d='M11 17h1m1 1h1'/%3E%3Cpath stroke='%23ae3719' d='M2 18h1'/%3E%3Cpath stroke='%23c94720' d='M14 18h1'/%3E%3Cpath stroke='%23c95839' d='M19 18h1'/%3E%3Cpath stroke='%23a7bdf0' d='M0 19h1m0 1h1'/%3E%3Cpath stroke='%23ead7d3' d='M1 19h1'/%3E%3Cpath stroke='%23b34e35' d='M2 19h1'/%3E%3Cpath stroke='%23c03e1c' d='M8 19h1'/%3E%3Cpath stroke='%23c9583a' d='M18 19h1'/%3E%3Cpath stroke='%23f3dbd4' d='M19 19h1'/%3E%3Cpath stroke='%23a7bcef' d='M20 19h1m-2 1h1'/%3E%3C/svg%3E")
}
.status-bar{
margin: 0 3px;
box-shadow: inset 0 1px 2px grey;
padding: 2px 1px;
gap: 0
}
.status-bar-field{
-webkit-font-smoothing: antialiased;
box-shadow: none;
padding: 1px 2px;
border-right: 1px solid rgba(208,206,191,.75);
border-left: 1px solid hsla(0,0%,100%,.75)
}
.status-bar-field: first-of-type{
border-left: none
}
.status-bar-field: last-of-type{
border-right: none
}
button{
-webkit-font-smoothing: antialiased;
box-sizing: border-box;
border: 1px solid #003c74;
background: linear-gradient(180deg,#fff,#ecebe5 86%,#d8d0c4);
box-shadow: none;
border-radius: 3px
}
button: not(: disabled).active,button: not(: disabled): active{
box-shadow: none;
background: linear-gradient(180deg,#cdcac3,#e3e3db 8%,#e5e5de 94%,#f2f2f1)
}
button: not(: disabled): hover{
box-shadow: inset -1px 1px #fff0cf,inset 1px 2px #fdd889,inset -2px 2px #fbc761,inset 2px -2px #e5a01a
}
button.focused,button: focus{
box-shadow: inset -1px 1px #cee7ff,inset 1px 2px #98b8ea,inset -2px 2px #bcd4f6,inset 1px -1px #89ade4,inset 2px -2px #89ade4
}
button: :-moz-focus-inner{
border: 0
}
input,label,option,select,textarea{
-webkit-font-smoothing: antialiased
}
input[type=radio]{
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
margin: 0;
background: 0;
position: fixed;
opacity: 0;
border: none
}
input[type=radio]+label{
line-height: 16px
}
input[type=radio]+label: before{
background: linear-gradient(135deg,#dcdcd7,#fff);
border-radius: 50%;
border: 1px solid #1d5281
}
input[type=radio]: not([disabled]): not(: active)+label: hover: before{
box-shadow: inset -2px -2px #f8b636,inset 2px 2px #fedf9c
}
input[type=radio]: active+label: before{
background: linear-gradient(135deg,#b0b0a7,#e3e1d2)
}
input[type=radio]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23a9dca6' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%234dbf4a' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23a0d29e' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%2355d551' d='M1 1h1'/%3E%3Cpath stroke='%2343c33f' d='M2 1h1'/%3E%3Cpath stroke='%2329a826' d='M3 1h1'/%3E%3Cpath stroke='%239acc98' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%2342c33f' d='M1 2h1'/%3E%3Cpath stroke='%2338b935' d='M2 2h1'/%3E%3Cpath stroke='%2321a121' d='M3 2h1'/%3E%3Cpath stroke='%23269623' d='M4 2h1'/%3E%3Cpath stroke='%232aa827' d='M1 3h1'/%3E%3Cpath stroke='%2322a220' d='M2 3h1'/%3E%3Cpath stroke='%23139210' d='M3 3h1'/%3E%3Cpath stroke='%2398c897' d='M4 3h1'/%3E%3Cpath stroke='%23249624' d='M2 4h1'/%3E%3Cpath stroke='%2398c997' d='M3 4h1'/%3E%3C/svg%3E")
}
input[type=radio]: focus+label{
outline: 1px dotted #000
}
input[type=radio][disabled]+label: before{
border: 1px solid #cac8bb;
background: #fff
}
input[type=radio][disabled]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e8e6da' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23d2ceb5' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23e5e3d4' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%23d7d3bd' d='M1 1h1'/%3E%3Cpath stroke='%23d0ccb2' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23c7c2a2' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%23e2dfd0' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%23cdc8ac' d='M2 2h1'/%3E%3Cpath stroke='%23c5bf9f' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%23c3bd9c' d='M4 2h1'/%3E%3Cpath stroke='%23bfb995' d='M3 3h1'/%3E%3Cpath stroke='%23e2dfcf' d='M4 3h1M3 4h1'/%3E%3Cpath stroke='%23c4be9d' d='M2 4h1'/%3E%3C/svg%3E")
}
input[type=email],input[type=password],textarea: :selection{
background: #2267cb;
color: #fff
}
input[type=range]: :-webkit-slider-thumb{
height: 21px;
width: 11px;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
transform: translateY(-8px)
}
input[type=range]: :-moz-range-thumb{
height: 21px;
width: 11px;
border: 0;
border-radius: 0;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
transform: translateY(2px)
}
input[type=range]: :-webkit-slider-runnable-track{
width: 100%;
height: 2px;
box-sizing: border-box;
background: #ecebe4;
border-right: 1px solid #f3f2ea;
border-bottom: 1px solid #f3f2ea;
border-radius: 2px;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
}
input[type=range]: :-moz-range-track{
width: 100%;
height: 2px;
box-sizing: border-box;
background: #ecebe4;
border-right: 1px solid #f3f2ea;
border-bottom: 1px solid #f3f2ea;
border-radius: 2px;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
}
input[type=range].has-box-indicator: :-webkit-slider-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(-10px)
}
input[type=range].has-box-indicator: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(0)
}
.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
border-left: 1px solid #f3f2ea;
border-right: 0;
border-bottom: 1px solid #f3f2ea;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
}
.is-vertical>input[type=range]: :-moz-range-track{
border-left: 1px solid #f3f2ea;
border-right: 0;
border-bottom: 1px solid #f3f2ea;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
}
fieldset{
box-shadow: none;
background: #fff;
border: 1px solid #d0d0bf;
border-radius: 4px;
padding-top: 10px
}
legend{
background: transparent;
color: #0046d5
}
.field-row{
display: flex;
align-items: center
}
.field-row>*+*{
margin-left: 6px
}
[class^=field-row]+[class^=field-row]{
margin-top: 6px
}
.field-row-stacked{
display: flex;
flex-direction: column
}
.field-row-stacked *+*{
margin-top: 6px
}
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33.8
],
[
1745520787,
1047.4609375,
32.7
],
[
1745535031,
1077.31640625,
37.7
],
[
1745535031,
1077.31640625,
37.6
],
[
1745535031,
1077.31640625,
36.2
],
[
1745535031,
1077.31640625,
39.1
],
[
1745555600,
1039.5546875,
36.7
],
[
1745555600,
1039.5546875,
34
],
[
1745555600,
1039.5546875,
32.8
],
[
1745555600,
1039.5546875,
33.7
],
[
1745577859,
1064.19140625,
37.8
],
[
1745577859,
1064.19140625,
36.4
],
[
1745577859,
1064.19140625,
36
],
[
1745577859,
1064.19140625,
38.3
],
[
1745606657,
1075.35546875,
37.2
],
[
1745606657,
1075.35546875,
40.3
],
[
1745606657,
1075.35546875,
40.8
],
[
1745606657,
1075.35546875,
41.6
],
[
1745635346,
1166.6328125,
37.5
],
[
1745635346,
1166.6328125,
41.2
],
[
1745635346,
1166.6328125,
41
],
[
1745635346,
1166.6328125,
40.7
]
];
var tab_main_worker_cpu_ram_headers_json = [
"timestamp",
"ram_usage_mb",
"cpu_usage_percent"
];
"use strict";
function add_default_layout_data (layout, no_height = 0) {
layout["width"] = get_graph_width();
if (!no_height) {
layout["height"] = get_graph_height();
}
layout["paper_bgcolor"] = 'rgba(0,0,0,0)';
layout["plot_bgcolor"] = 'rgba(0,0,0,0)';
return layout;
}
function get_marker_size() {
return 12;
}
function get_text_color() {
return theme == "dark" ? "white" : "black";
}
function get_font_size() {
return 14;
}
function get_graph_height() {
return 800;
}
function get_font_data() {
return {
size: get_font_size(),
color: get_text_color()
}
}
function get_axis_title_data(name, axis_type = "") {
if(axis_type) {
return {
text: name,
type: axis_type,
font: get_font_data()
};
}
return {
text: name,
font: get_font_data()
};
}
function get_graph_width() {
var width = document.body.clientWidth || window.innerWidth || document.documentElement.clientWidth;
return Math.max(800, Math.floor(width * 0.9));
}
function createTable(data, headers, table_name) {
if (!$("#" + table_name).length) {
console.error("#" + table_name + " not found");
return;
}
new gridjs.Grid({
columns: headers,
data: data,
search: true,
sort: true,
ellipsis: false
}).render(document.getElementById(table_name));
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
colorize_table_entries();
add_colorize_to_gridjs_table();
}
function download_as_file(id, filename) {
var text = $("#" + id).text();
var blob = new Blob([text], {
type: "text/plain"
});
var link = document.createElement("a");
link.href = URL.createObjectURL(blob);
link.download = filename;
document.body.appendChild(link);
link.click();
document.body.removeChild(link);
}
function copy_to_clipboard_from_id (id) {
var text = $("#" + id).text();
copy_to_clipboard(text);
}
function copy_to_clipboard(text) {
if (!navigator.clipboard) {
let textarea = document.createElement("textarea");
textarea.value = text;
document.body.appendChild(textarea);
textarea.select();
try {
document.execCommand("copy");
} catch (err) {
console.error("Copy failed:", err);
}
document.body.removeChild(textarea);
return;
}
navigator.clipboard.writeText(text).then(() => {
console.log("Text copied to clipboard");
}).catch(err => {
console.error("Failed to copy text:", err);
});
}
function filterNonEmptyRows(data) {
var new_data = [];
for (var row_idx = 0; row_idx < data.length; row_idx++) {
var line = data[row_idx];
var line_has_empty_data = false;
for (var col_idx = 0; col_idx < line.length; col_idx++) {
var col_header_name = tab_results_headers_json[col_idx];
var single_data_point = line[col_idx];
if(single_data_point === "" && !special_col_names.includes(col_header_name)) {
line_has_empty_data = true;
continue;
}
}
if(!line_has_empty_data) {
new_data.push(line);
}
}
return new_data;
}
function make_text_in_parallel_plot_nicer() {
$(".parcoords g > g > text").each(function() {
if (theme == "dark") {
$(this)
.css("text-shadow", "unset")
.css("font-size", "0.9em")
.css("fill", "white")
.css("stroke", "black")
.css("stroke-width", "2px")
.css("paint-order", "stroke fill");
} else {
$(this)
.css("text-shadow", "unset")
.css("font-size", "0.9em")
.css("fill", "black")
.css("stroke", "unset")
.css("stroke-width", "unset")
.css("paint-order", "stroke fill");
}
});
}
function createParallelPlot(dataArray, headers, resultNames, ignoreColumns = []) {
if ($("#parallel-plot").data("loaded") == "true") {
return;
}
dataArray = filterNonEmptyRows(dataArray);
const ignoreSet = new Set(ignoreColumns);
const numericalCols = [];
const categoricalCols = [];
const categoryMappings = {};
headers.forEach((header, colIndex) => {
if (ignoreSet.has(header)) return;
const values = dataArray.map(row => row[colIndex]);
if (values.every(val => !isNaN(parseFloat(val)))) {
numericalCols.push({ name: header, index: colIndex });
} else {
categoricalCols.push({ name: header, index: colIndex });
const uniqueValues = [...new Set(values)];
categoryMappings[header] = Object.fromEntries(uniqueValues.map((val, i) => [val, i]));
}
});
const dimensions = [];
numericalCols.forEach(col => {
dimensions.push({
label: col.name,
values: dataArray.map(row => parseFloat(row[col.index])),
range: [
Math.min(...dataArray.map(row => parseFloat(row[col.index]))),
Math.max(...dataArray.map(row => parseFloat(row[col.index])))
]
});
});
categoricalCols.forEach(col => {
dimensions.push({
label: col.name,
values: dataArray.map(row => categoryMappings[col.name][row[col.index]]),
tickvals: Object.values(categoryMappings[col.name]),
ticktext: Object.keys(categoryMappings[col.name])
});
});
let colorScale = null;
let colorValues = null;
if (resultNames.length > 1) {
let selectBox = '<select id="result-select" style="margin-bottom: 10px;">';
selectBox += '<option value="none">No color</option>';
var k = 0;
resultNames.forEach(resultName => {
var minMax = result_min_max[k];
if(minMax === undefined) {
minMax = "min [automatically chosen]"
}
selectBox += `<option value="${resultName}">${resultName} (${minMax})</option>`;
k = k + 1;
});
selectBox += '</select>';
$("#parallel-plot").before(selectBox);
$("#result-select").change(function() {
const selectedResult = $(this).val();
if (selectedResult === "none") {
colorValues = null;
colorScale = null;
} else {
const resultCol = numericalCols.find(col => col.name.toLowerCase() === selectedResult.toLowerCase());
colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
let minResult = Math.min(...colorValues);
let maxResult = Math.max(...colorValues);
var _result_min_max_idx = result_names.indexOf(selectedResult);
let invertColor = false;
if (result_min_max.length > _result_min_max_idx) {
invertColor = result_min_max[_result_min_max_idx] === "max";
}
colorScale = invertColor
? [[0, 'red'], [1, 'green']]
: [[0, 'green'], [1, 'red']];
}
updatePlot();
});
} else {
let invertColor = false;
if (Object.keys(result_min_max).length == 1) {
invertColor = result_min_max[0] === "max";
}
colorScale = invertColor
? [[0, 'red'], [1, 'green']]
: [[0, 'green'], [1, 'red']];
const resultCol = numericalCols.find(col => col.name.toLowerCase() === resultNames[0].toLowerCase());
colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
}
function updatePlot() {
const trace = {
type: 'parcoords',
dimensions: dimensions,
line: colorValues ? { color: colorValues, colorscale: colorScale } : {},
unselected: {
line: {
color: get_text_color(),
opacity: 0
}
},
};
dimensions.forEach(dim => {
if (!dim.line) {
dim.line = {};
}
if (!dim.line.color) {
dim.line.color = 'rgba(169,169,169, 0.01)';
}
});
Plotly.newPlot('parallel-plot', [trace], add_default_layout_data({}));
make_text_in_parallel_plot_nicer();
}
updatePlot();
$("#parallel-plot").data("loaded", "true");
make_text_in_parallel_plot_nicer();
}
function plotWorkerUsage() {
if($("#workerUsagePlot").data("loaded") == "true") {
return;
}
var data = tab_worker_usage_csv_json;
if (!Array.isArray(data) || data.length === 0) {
console.error("Invalid or empty data provided.");
return;
}
let timestamps = [];
let desiredWorkers = [];
let realWorkers = [];
for (let i = 0; i < data.length; i++) {
let entry = data[i];
if (!Array.isArray(entry) || entry.length < 3) {
console.warn("Skipping invalid entry:", entry);
continue;
}
let unixTime = parseFloat(entry[0]);
let desired = parseInt(entry[1], 10);
let real = parseInt(entry[2], 10);
if (isNaN(unixTime) || isNaN(desired) || isNaN(real)) {
console.warn("Skipping invalid numerical values:", entry);
continue;
}
timestamps.push(new Date(unixTime * 1000).toISOString());
desiredWorkers.push(desired);
realWorkers.push(real);
}
let trace1 = {
x: timestamps,
y: desiredWorkers,
mode: 'lines+markers',
name: 'Desired Workers',
line: {
color: 'blue'
}
};
let trace2 = {
x: timestamps,
y: realWorkers,
mode: 'lines+markers',
name: 'Real Workers',
line: {
color: 'red'
}
};
let layout = {
title: "Worker Usage Over Time",
xaxis: {
title: get_axis_title_data("Time", "date")
},
yaxis: {
title: get_axis_title_data("Number of Workers")
},
legend: {
x: 0,
y: 1
}
};
Plotly.newPlot('workerUsagePlot', [trace1, trace2], add_default_layout_data(layout));
$("#workerUsagePlot").data("loaded", "true");
}
function plotCPUAndRAMUsage() {
if($("#mainWorkerCPURAM").data("loaded") == "true") {
return;
}
var timestamps = tab_main_worker_cpu_ram_csv_json.map(row => new Date(row[0] * 1000));
var ramUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[1]);
var cpuUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[2]);
var trace1 = {
x: timestamps,
y: cpuUsage,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'CPU Usage (%)',
type: 'scatter',
yaxis: 'y1'
};
var trace2 = {
x: timestamps,
y: ramUsage,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'RAM Usage (MB)',
type: 'scatter',
yaxis: 'y2'
};
var layout = {
title: 'CPU and RAM Usage Over Time',
xaxis: {
title: get_axis_title_data("Timestamp", "date"),
tickmode: 'array',
tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
tickangle: -45
},
yaxis: {
title: get_axis_title_data("CPU Usage (%)"),
rangemode: 'tozero'
},
yaxis2: {
title: get_axis_title_data("RAM Usage (MB)"),
overlaying: 'y',
side: 'right',
rangemode: 'tozero'
},
legend: {
x: 0.1,
y: 0.9
}
};
var data = [trace1, trace2];
Plotly.newPlot('mainWorkerCPURAM', data, add_default_layout_data(layout));
$("#mainWorkerCPURAM").data("loaded", "true");
}
function plotScatter2d() {
if ($("#plotScatter2d").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotScatter2d");
var minInput = document.getElementById("minValue");
var maxInput = document.getElementById("maxValue");
if (!minInput || !maxInput) {
minInput = document.createElement("input");
minInput.id = "minValue";
minInput.type = "number";
minInput.placeholder = "Min Value";
minInput.step = "any";
maxInput = document.createElement("input");
maxInput.id = "maxValue";
maxInput.type = "number";
maxInput.placeholder = "Max Value";
maxInput.step = "any";
var inputContainer = document.createElement("div");
inputContainer.style.marginBottom = "10px";
inputContainer.appendChild(minInput);
inputContainer.appendChild(maxInput);
plotDiv.appendChild(inputContainer);
}
var resultSelect = document.getElementById("resultSelect");
if (result_names.length > 1 && !resultSelect) {
resultSelect = document.createElement("select");
resultSelect.id = "resultSelect";
resultSelect.style.marginBottom = "10px";
var sortedResults = [...result_names].sort();
sortedResults.forEach(result => {
var option = document.createElement("option");
option.value = result;
option.textContent = result;
resultSelect.appendChild(option);
});
var selectContainer = document.createElement("div");
selectContainer.style.marginBottom = "10px";
selectContainer.appendChild(resultSelect);
plotDiv.appendChild(selectContainer);
}
minInput.addEventListener("input", updatePlots);
maxInput.addEventListener("input", updatePlots);
if (resultSelect) {
resultSelect.addEventListener("change", updatePlots);
}
updatePlots();
async function updatePlots() {
var minValue = parseFloat(minInput.value);
var maxValue = parseFloat(maxInput.value);
if (isNaN(minValue)) minValue = -Infinity;
if (isNaN(maxValue)) maxValue = Infinity;
while (plotDiv.children.length > 2) {
plotDiv.removeChild(plotDiv.lastChild);
}
var selectedResult = resultSelect ? resultSelect.value : result_names[0];
var resultIndex = tab_results_headers_json.findIndex(header =>
header.toLowerCase() === selectedResult.toLowerCase()
);
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
if (minValue !== -Infinity) minResult = Math.max(minResult, minValue);
if (maxValue !== Infinity) maxResult = Math.min(maxResult, maxValue);
var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 2) {
console.error("Not enough columns for Scatter-Plots");
return;
}
for (let i = 0; i < numericColumns.length; i++) {
for (let j = i + 1; j < numericColumns.length; j++) {
let xCol = numericColumns[i];
let yCol = numericColumns[j];
let xIndex = tab_results_headers_json.indexOf(xCol);
let yIndex = tab_results_headers_json.indexOf(yCol);
let data = tab_results_csv_json.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
}));
data = data.filter(d => d.result >= minResult && d.result <= maxResult);
let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
let layout = {
title: layoutTitle,
xaxis: {
title: get_axis_title_data(xCol)
},
yaxis: {
title: get_axis_title_data(yCol)
},
showlegend: false
};
let subDiv = document.createElement("div");
let spinnerContainer = document.createElement("div");
spinnerContainer.style.display = "flex";
spinnerContainer.style.alignItems = "center";
spinnerContainer.style.justifyContent = "center";
spinnerContainer.style.width = layout.width + "px";
spinnerContainer.style.height = layout.height + "px";
spinnerContainer.style.position = "relative";
let spinner = document.createElement("div");
spinner.className = "spinner";
spinner.style.width = "40px";
spinner.style.height = "40px";
let loadingText = document.createElement("span");
loadingText.innerText = `Loading ${layoutTitle}`;
loadingText.style.marginLeft = "10px";
spinnerContainer.appendChild(spinner);
spinnerContainer.appendChild(loadingText);
plotDiv.appendChild(spinnerContainer);
await new Promise(resolve => setTimeout(resolve, 50));
let colors = data.map(d => {
if (d.result === null) {
return 'rgb(0, 0, 0)';
} else {
let norm = (d.result - minResult) / (maxResult - minResult);
if (invertColor) {
norm = 1 - norm;
}
return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
}
});
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
mode: 'markers',
marker: {
size: get_marker_size(),
color: data.map(d => d.result !== null ? d.result : null),
colorscale: invertColor ? [
[0, 'red'],
[1, 'green']
] : [
[0, 'green'],
[1, 'red']
],
colorbar: {
title: 'Result',
tickvals: [minResult, maxResult],
ticktext: [`${minResult}`, `${maxResult}`]
},
symbol: data.map(d => d.result === null ? 'x' : 'circle'),
},
text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
type: 'scatter',
showlegend: false
};
try {
plotDiv.replaceChild(subDiv, spinnerContainer);
} catch (err) {
//
}
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
}
$("#plotScatter2d").data("loaded", "true");
}
function plotScatter3d() {
if ($("#plotScatter3d").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotScatter3d");
if (!plotDiv) {
console.error("Div element with id 'plotScatter3d' not found");
return;
}
plotDiv.innerHTML = "";
var minInput3d = document.getElementById("minValue3d");
var maxInput3d = document.getElementById("maxValue3d");
if (!minInput3d || !maxInput3d) {
minInput3d = document.createElement("input");
minInput3d.id = "minValue3d";
minInput3d.type = "number";
minInput3d.placeholder = "Min Value";
minInput3d.step = "any";
maxInput3d = document.createElement("input");
maxInput3d.id = "maxValue3d";
maxInput3d.type = "number";
maxInput3d.placeholder = "Max Value";
maxInput3d.step = "any";
var inputContainer3d = document.createElement("div");
inputContainer3d.style.marginBottom = "10px";
inputContainer3d.appendChild(minInput3d);
inputContainer3d.appendChild(maxInput3d);
plotDiv.appendChild(inputContainer3d);
}
var select3d = document.getElementById("select3dScatter");
if (result_names.length > 1 && !select3d) {
if (!select3d) {
select3d = document.createElement("select");
select3d.id = "select3dScatter";
select3d.style.marginBottom = "10px";
select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");
select3d.addEventListener("change", updatePlots3d);
plotDiv.appendChild(select3d);
}
}
minInput3d.addEventListener("input", updatePlots3d);
maxInput3d.addEventListener("input", updatePlots3d);
updatePlots3d();
async function updatePlots3d() {
var selectedResult = select3d ? select3d.value : result_names[0];
var minValue3d = parseFloat(minInput3d.value);
var maxValue3d = parseFloat(maxInput3d.value);
if (isNaN(minValue3d)) minValue3d = -Infinity;
if (isNaN(maxValue3d)) maxValue3d = Infinity;
while (plotDiv.children.length > 2) {
plotDiv.removeChild(plotDiv.lastChild);
}
var resultIndex = tab_results_headers_json.findIndex(header =>
header.toLowerCase() === selectedResult.toLowerCase()
);
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);
var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 3) {
console.error("Not enough columns for 3D scatter plots");
return;
}
for (let i = 0; i < numericColumns.length; i++) {
for (let j = i + 1; j < numericColumns.length; j++) {
for (let k = j + 1; k < numericColumns.length; k++) {
let xCol = numericColumns[i];
let yCol = numericColumns[j];
let zCol = numericColumns[k];
let xIndex = tab_results_headers_json.indexOf(xCol);
let yIndex = tab_results_headers_json.indexOf(yCol);
let zIndex = tab_results_headers_json.indexOf(zCol);
let data = tab_results_csv_json.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
z: parseFloat(row[zIndex]),
result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
}));
data = data.filter(d => d.result >= minResult && d.result <= maxResult);
let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
let layout = {
title: layoutTitle,
scene: {
xaxis: {
title: get_axis_title_data(xCol)
},
yaxis: {
title: get_axis_title_data(yCol)
},
zaxis: {
title: get_axis_title_data(zCol)
}
},
showlegend: false
};
let spinnerContainer = document.createElement("div");
spinnerContainer.style.display = "flex";
spinnerContainer.style.alignItems = "center";
spinnerContainer.style.justifyContent = "center";
spinnerContainer.style.width = layout.width + "px";
spinnerContainer.style.height = layout.height + "px";
spinnerContainer.style.position = "relative";
let spinner = document.createElement("div");
spinner.className = "spinner";
spinner.style.width = "40px";
spinner.style.height = "40px";
let loadingText = document.createElement("span");
loadingText.innerText = `Loading ${layoutTitle}`;
loadingText.style.marginLeft = "10px";
spinnerContainer.appendChild(spinner);
spinnerContainer.appendChild(loadingText);
plotDiv.appendChild(spinnerContainer);
await new Promise(resolve => setTimeout(resolve, 50));
let colors = data.map(d => {
if (d.result === null) {
return 'rgb(0, 0, 0)';
} else {
let norm = (d.result - minResult) / (maxResult - minResult);
if (invertColor) {
norm = 1 - norm;
}
return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
}
});
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
z: data.map(d => d.z),
mode: 'markers',
marker: {
size: get_marker_size(),
color: data.map(d => d.result !== null ? d.result : null),
colorscale: invertColor ? [
[0, 'red'],
[1, 'green']
] : [
[0, 'green'],
[1, 'red']
],
colorbar: {
title: 'Result',
tickvals: [minResult, maxResult],
ticktext: [`${minResult}`, `${maxResult}`]
},
},
text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
type: 'scatter3d',
showlegend: false
};
let subDiv = document.createElement("div");
try {
plotDiv.replaceChild(subDiv, spinnerContainer);
} catch (err) {
//
}
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
}
}
$("#plotScatter3d").data("loaded", "true");
}
async function plot_worker_cpu_ram() {
if($("#worker_cpu_ram_pre").data("loaded") == "true") {
return;
}
const logData = $("#worker_cpu_ram_pre").text();
const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;
const hostData = {};
logData.split("\n").forEach(line => {
line = line.trim();
const match = line.match(regex);
if (match) {
const timestamp = new Date(parseInt(match[1]) * 1000);
const hostname = match[2];
const cpu = parseFloat(match[3]);
const ram = parseFloat(match[4]);
if (!hostData[hostname]) {
hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
}
hostData[hostname].timestamps.push(timestamp);
hostData[hostname].cpuUsage.push(cpu);
hostData[hostname].ramUsage.push(ram);
}
});
if (!Object.keys(hostData).length) {
console.log("No valid data found");
return;
}
const container = document.getElementById("cpuRamWorkerChartContainer");
container.innerHTML = "";
var i = 1;
Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
const chartId = `workerChart_${index}`;
const chartDiv = document.createElement("div");
chartDiv.id = chartId;
chartDiv.style.marginBottom = "40px";
container.appendChild(chartDiv);
const cpuTrace = {
x: timestamps,
y: cpuUsage,
mode: "lines+markers",
name: "CPU Usage (%)",
yaxis: "y1",
line: {
color: "red"
}
};
const ramTrace = {
x: timestamps,
y: ramUsage,
mode: "lines+markers",
name: "RAM Usage (MB)",
yaxis: "y2",
line: {
color: "blue"
}
};
const layout = {
title: `Worker CPU and RAM Usage - ${hostname}`,
xaxis: {
title: get_axis_title_data("Timestamp", "date")
},
yaxis: {
title: get_axis_title_data("CPU Usage (%)"),
side: "left",
color: "red"
},
yaxis2: {
title: get_axis_title_data("RAM Usage (MB)"),
side: "right",
overlaying: "y",
color: "blue"
},
showlegend: true
};
Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
i++;
});
$("#plot_worker_cpu_ram_button").remove();
$("#worker_cpu_ram_pre").data("loaded", "true");
}
function load_log_file(log_nr, filename) {
var pre_id = `single_run_${log_nr}_pre`;
if (!$("#" + pre_id).data("loaded")) {
const params = new URLSearchParams(window.location.search);
const user_id = params.get('user_id');
const experiment_name = params.get('experiment_name');
const run_nr = params.get('run_nr');
var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;
fetch(url)
.then(response => response.json())
.then(data => {
if (data.data) {
$("#" + pre_id).html(data.data);
$("#" + pre_id).data("loaded", true);
} else {
log(`No 'data' key found in response.`);
}
$("#spinner_log_" + log_nr).remove();
})
.catch(error => {
log(`Error loading log: ${error}`);
$("#spinner_log_" + log_nr).remove();
});
}
}
function load_debug_log () {
var pre_id = `here_debuglogs_go`;
if (!$("#" + pre_id).data("loaded")) {
const params = new URLSearchParams(window.location.search);
const user_id = params.get('user_id');
const experiment_name = params.get('experiment_name');
const run_nr = params.get('run_nr');
var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;
fetch(url)
.then(response => response.json())
.then(data => {
$("#debug_log_spinner").remove();
if (data.data) {
try {
$("#" + pre_id).html(data.data);
} catch (err) {
$("#" + pre_id).text(`Error loading data: ${err}`);
}
$("#" + pre_id).data("loaded", true);
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
} else {
log(`No 'data' key found in response.`);
}
})
.catch(error => {
log(`Error loading log: ${error}`);
$("#debug_log_spinner").remove();
});
}
}
function plotBoxplot() {
if ($("#plotBoxplot").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough numeric columns for Boxplot");
return;
}
var resultIndex = tab_results_headers_json.findIndex(function(header) {
return result_names.includes(header.toLowerCase());
});
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
var plotDiv = document.getElementById("plotBoxplot");
plotDiv.innerHTML = "";
let traces = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
let data = tab_results_csv_json.map(row => parseFloat(row[index]));
return {
y: data,
type: 'box',
name: col,
boxmean: 'sd',
marker: {
color: 'rgb(0, 255, 0)'
},
};
});
let layout = {
title: 'Boxplot of Numerical Columns',
xaxis: {
title: get_axis_title_data("Columns")
},
yaxis: {
title: get_axis_title_data("Value")
},
showlegend: false
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotBoxplot").data("loaded", "true");
}
function plotHeatmap() {
if ($("#plotHeatmap").data("loaded") === "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col => {
if (special_col_names.includes(col) || result_names.includes(col)) {
return false;
}
let index = tab_results_headers_json.indexOf(col);
return tab_results_csv_json.every(row => {
let value = parseFloat(row[index]);
return !isNaN(value) && isFinite(value);
});
});
if (numericColumns.length < 2) {
console.error("Not enough valid numeric columns for Heatmap");
return;
}
var columnData = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
return tab_results_csv_json.map(row => parseFloat(row[index]));
});
var dataMatrix = numericColumns.map((_, i) =>
numericColumns.map((_, j) => {
let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
return values.reduce((a, b) => a + b, 0) / values.length;
})
);
var trace = {
z: dataMatrix,
x: numericColumns,
y: numericColumns,
colorscale: 'Viridis',
type: 'heatmap'
};
var layout = {
xaxis: {
title: get_axis_title_data("Columns")
},
yaxis: {
title: get_axis_title_data("Columns")
},
showlegend: false
};
var plotDiv = document.getElementById("plotHeatmap");
plotDiv.innerHTML = "";
Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
$("#plotHeatmap").data("loaded", "true");
}
function plotHistogram() {
if ($("#plotHistogram").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough columns for Histogram");
return;
}
var plotDiv = document.getElementById("plotHistogram");
plotDiv.innerHTML = "";
const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];
let traces = numericColumns.map((col, index) => {
let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));
return {
x: data,
type: 'histogram',
name: col,
opacity: 0.7,
marker: {
color: colorPalette[index % colorPalette.length]
},
autobinx: true
};
});
let layout = {
title: 'Histogram of Numerical Columns',
xaxis: {
title: get_axis_title_data("Value")
},
yaxis: {
title: get_axis_title_data("Frequency")
},
showlegend: true,
barmode: 'overlay'
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotHistogram").data("loaded", "true");
}
function plotViolin() {
if ($("#plotViolin").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough columns for Violin Plot");
return;
}
var plotDiv = document.getElementById("plotViolin");
plotDiv.innerHTML = "";
let traces = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
let data = tab_results_csv_json.map(row => parseFloat(row[index]));
return {
y: data,
type: 'violin',
name: col,
box: {
visible: true
},
line: {
color: 'rgb(0, 255, 0)'
},
marker: {
color: 'rgb(0, 255, 0)'
},
meanline: {
visible: true
},
};
});
let layout = {
title: 'Violin Plot of Numerical Columns',
yaxis: {
title: get_axis_title_data("Value")
},
xaxis: {
title: get_axis_title_data("Columns")
},
showlegend: false
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotViolin").data("loaded", "true");
}
function plotExitCodesPieChart() {
if ($("#plotExitCodesPieChart").data("loaded") == "true") {
return;
}
var exitCodes = tab_job_infos_csv_json.map(row => row[tab_job_infos_headers_json.indexOf("exit_code")]);
var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
counts[exitCode] = (counts[exitCode] || 0) + 1;
return counts;
}, {});
var labels = Object.keys(exitCodeCounts);
var values = Object.values(exitCodeCounts);
var plotDiv = document.getElementById("plotExitCodesPieChart");
plotDiv.innerHTML = "";
var trace = {
labels: labels,
values: values,
type: 'pie',
hoverinfo: 'label+percent',
textinfo: 'label+value',
marker: {
colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
}
};
var layout = {
title: 'Exit Code Distribution',
showlegend: true
};
Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
$("#plotExitCodesPieChart").data("loaded", "true");
}
function plotResultEvolution() {
if ($("#plotResultEvolution").data("loaded") == "true") {
return;
}
result_names.forEach(resultName => {
var relevantColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
);
var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
var resultIndex = tab_results_headers_json.indexOf(resultName);
let data = tab_results_csv_json.map(row => ({
x: row[xColumnIndex],
y: parseFloat(row[resultIndex])
}));
data.sort((a, b) => a.x - b.x);
let xData = data.map(item => item.x);
let yData = data.map(item => item.y);
let trace = {
x: xData,
y: yData,
mode: 'lines+markers',
name: resultName,
line: {
shape: 'linear'
},
marker: {
size: get_marker_size()
}
};
let layout = {
title: `Evolution of ${resultName} over time`,
xaxis: {
title: get_axis_title_data("Trial-Index")
},
yaxis: {
title: get_axis_title_data(resultName)
},
showlegend: true
};
let subDiv = document.createElement("div");
document.getElementById("plotResultEvolution").appendChild(subDiv);
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
});
$("#plotResultEvolution").data("loaded", "true");
}
function plotResultPairs() {
if ($("#plotResultPairs").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotResultPairs");
plotDiv.innerHTML = "";
for (let i = 0; i < result_names.length; i++) {
for (let j = i + 1; j < result_names.length; j++) {
let xName = result_names[i];
let yName = result_names[j];
let xIndex = tab_results_headers_json.indexOf(xName);
let yIndex = tab_results_headers_json.indexOf(yName);
let data = tab_results_csv_json
.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
status: row[tab_results_headers_json.indexOf("trial_status")]
}));
let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
mode: 'markers',
marker: {
size: get_marker_size(),
color: colors
},
text: data.map(d => `Status: ${d.status}`),
type: 'scatter',
showlegend: false
};
let layout = {
xaxis: {
title: get_axis_title_data(xName)
},
yaxis: {
title: get_axis_title_data(yName)
},
showlegend: false
};
let subDiv = document.createElement("div");
plotDiv.appendChild(subDiv);
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
$("#plotResultPairs").data("loaded", "true");
}
function add_up_down_arrows_for_scrolling () {
const upArrow = document.createElement('div');
const downArrow = document.createElement('div');
const style = document.createElement('style');
style.innerHTML = `
.scroll-arrow {
position: fixed;
right: 10px;
z-index: 100;
cursor: pointer;
font-size: 25px;
display: none;
background-color: green;
color: white;
padding: 5px;
outline: 2px solid white;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
transition: background-color 0.3s, transform 0.3s;
}
.scroll-arrow:hover {
background-color: darkgreen;
transform: scale(1.1);
}
#up-arrow {
top: 10px;
}
#down-arrow {
bottom: 10px;
}
`;
document.head.appendChild(style);
upArrow.id = "up-arrow";
upArrow.classList.add("scroll-arrow");
upArrow.classList.add("invert_in_dark_mode");
upArrow.innerHTML = "↑";
downArrow.id = "down-arrow";
downArrow.classList.add("scroll-arrow");
downArrow.classList.add("invert_in_dark_mode");
downArrow.innerHTML = "↓";
document.body.appendChild(upArrow);
document.body.appendChild(downArrow);
function checkScrollPosition() {
const scrollPosition = window.scrollY;
const pageHeight = document.documentElement.scrollHeight;
const windowHeight = window.innerHeight;
if (scrollPosition > 0) {
upArrow.style.display = "block";
} else {
upArrow.style.display = "none";
}
if (scrollPosition + windowHeight < pageHeight) {
downArrow.style.display = "block";
} else {
downArrow.style.display = "none";
}
}
window.addEventListener("scroll", checkScrollPosition);
upArrow.addEventListener("click", function () {
window.scrollTo({ top: 0, behavior: 'smooth' });
});
downArrow.addEventListener("click", function () {
window.scrollTo({ top: document.documentElement.scrollHeight, behavior: 'smooth' });
});
checkScrollPosition();
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
}
function plotGPUUsage() {
if ($("#tab_gpu_usage").data("loaded") === "true") {
return;
}
Object.keys(gpu_usage).forEach(node => {
const nodeData = gpu_usage[node];
var timestamps = [];
var gpuUtilizations = [];
var temperatures = [];
nodeData.forEach(entry => {
try {
var timestamp = new Date(entry[0]* 1000);
var utilization = parseFloat(entry[1]);
var temperature = parseFloat(entry[2]);
if (!isNaN(timestamp) && !isNaN(utilization) && !isNaN(temperature)) {
timestamps.push(timestamp);
gpuUtilizations.push(utilization);
temperatures.push(temperature);
} else {
console.warn("Invalid data point:", entry);
}
} catch (error) {
console.error("Error processing GPU data entry:", error, entry);
}
});
var trace1 = {
x: timestamps,
y: gpuUtilizations,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'GPU Utilization (%)',
type: 'scatter',
yaxis: 'y1'
};
var trace2 = {
x: timestamps,
y: temperatures,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'GPU Temperature (°C)',
type: 'scatter',
yaxis: 'y2'
};
var layout = {
title: 'GPU Usage Over Time - ' + node,
xaxis: {
title: get_axis_title_data("Timestamp", "date"),
tickmode: 'array',
tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
tickangle: -45
},
yaxis: {
title: get_axis_title_data("GPU Utilization (%)"),
overlaying: 'y',
rangemode: 'tozero'
},
yaxis2: {
title: get_axis_title_data("GPU Temperature (°C)"),
overlaying: 'y',
side: 'right',
position: 0.85,
rangemode: 'tozero'
},
legend: {
x: 0.1,
y: 0.9
}
};
var divId = 'gpu_usage_plot_' + node;
if (!document.getElementById(divId)) {
var div = document.createElement('div');
div.id = divId;
div.className = 'gpu-usage-plot';
document.getElementById('tab_gpu_usage').appendChild(div);
}
var plotData = [trace1, trace2];
Plotly.newPlot(divId, plotData, add_default_layout_data(layout));
});
$("#tab_gpu_usage").data("loaded", "true");
}
function plotResultsDistributionByGenerationMethod() {
if ("true" === $("#plotResultsDistributionByGenerationMethod").data("loaded")) {
return;
}
var res_col = result_names[0];
var gen_method_col = "generation_node";
var data = {};
tab_results_csv_json.forEach(row => {
var gen_method = row[tab_results_headers_json.indexOf(gen_method_col)];
var result = row[tab_results_headers_json.indexOf(res_col)];
if (!data[gen_method]) {
data[gen_method] = [];
}
data[gen_method].push(result);
});
var traces = Object.keys(data).map(method => {
return {
y: data[method],
type: 'box',
name: method,
boxpoints: 'outliers',
jitter: 0.5,
pointpos: 0
};
});
var layout = {
title: 'Distribution of Results by Generation Method',
yaxis: {
title: get_axis_title_data(res_col)
},
xaxis: {
title: get_axis_title_data("Generation Method")
},
boxmode: 'group'
};
Plotly.newPlot("plotResultsDistributionByGenerationMethod", traces, add_default_layout_data(layout));
$("#plotResultsDistributionByGenerationMethod").data("loaded", "true");
}
function plotJobStatusDistribution() {
if ($("#plotJobStatusDistribution").data("loaded") === "true") {
return;
}
var status_col = "trial_status";
var status_counts = {};
tab_results_csv_json.forEach(row => {
var status = row[tab_results_headers_json.indexOf(status_col)];
if (status) {
status_counts[status] = (status_counts[status] || 0) + 1;
}
});
var statuses = Object.keys(status_counts);
var counts = Object.values(status_counts);
var colors = statuses.map((status, i) =>
status === "FAILED" ? "#FF0000" : `hsl(${30 + ((i * 137) % 330)}, 70%, 50%)`
);
var trace = {
x: statuses,
y: counts,
type: 'bar',
marker: { color: colors }
};
var layout = {
title: 'Distribution of Job Status',
xaxis: { title: 'Trial Status' },
yaxis: { title: 'Nr. of jobs' }
};
Plotly.newPlot("plotJobStatusDistribution", [trace], add_default_layout_data(layout));
$("#plotJobStatusDistribution").data("loaded", "true");
}
function _colorize_table_entries_by_generation_method () {
document.querySelectorAll('[data-column-id="generation_node"]').forEach(el => {
let text = el.textContent.toLowerCase();
let color = text.includes("manual") ? "green" :
text.includes("sobol") ? "orange" :
text.includes("saasbo") ? "pink" :
text.includes("uniform") ? "lightblue" :
text.includes("legacy_gpei") ? "sienna" :
text.includes("bo_mixed") ? "aqua" :
text.includes("randomforest") ? "darkseagreen" :
text.includes("external_generator") ? "purple" :
text.includes("botorch") ? "yellow" : "";
if (color !== "") {
el.style.backgroundColor = color;
}
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_trial_status () {
document.querySelectorAll('[data-column-id="trial_status"]').forEach(el => {
let color = el.textContent.includes("COMPLETED") ? "lightgreen" :
el.textContent.includes("RUNNING") ? "orange" :
el.textContent.includes("FAILED") ? "red" :
el.textContent.includes("ABANDONED") ? "yellow" : "";
if (color) el.style.backgroundColor = color;
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_run_time() {
let cells = [...document.querySelectorAll('[data-column-id="run_time"]')];
if (cells.length === 0) return;
let values = cells.map(el => parseFloat(el.textContent)).filter(v => !isNaN(v));
if (values.length === 0) return;
let min = Math.min(...values);
let max = Math.max(...values);
let range = max - min || 1;
cells.forEach(el => {
let value = parseFloat(el.textContent);
if (isNaN(value)) return;
let ratio = (value - min) / range;
let red = Math.round(255 * ratio);
let green = Math.round(255 * (1 - ratio));
el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_results() {
result_names.forEach((name, index) => {
let minMax = result_min_max[index];
let selector_query = `[data-column-id="${name}"]`;
let cells = [...document.querySelectorAll(selector_query)];
if (cells.length === 0) return;
let values = cells.map(el => parseFloat(el.textContent)).filter(v => v > 0 && !isNaN(v));
if (values.length === 0) return;
let logValues = values.map(v => Math.log(v));
let logMin = Math.min(...logValues);
let logMax = Math.max(...logValues);
let logRange = logMax - logMin || 1;
cells.forEach(el => {
let value = parseFloat(el.textContent);
if (isNaN(value) || value <= 0) return;
let logValue = Math.log(value);
let ratio = (logValue - logMin) / logRange;
if (minMax === "max") ratio = 1 - ratio;
let red = Math.round(255 * ratio);
let green = Math.round(255 * (1 - ratio));
el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
el.classList.add("invert_in_dark_mode");
});
});
}
function _colorize_table_entries_by_generation_node_or_hostname() {
["hostname", "generation_node"].forEach(element => {
let selector_query = '[data-column-id="' + element + '"]:not(.gridjs-th)';
let cells = [...document.querySelectorAll(selector_query)];
if (cells.length === 0) return;
let uniqueValues = [...new Set(cells.map(el => el.textContent.trim()))];
let colorMap = {};
uniqueValues.forEach((value, index) => {
let hue = Math.round((360 / uniqueValues.length) * index);
colorMap[value] = `hsl(${hue}, 70%, 60%)`;
});
cells.forEach(el => {
let value = el.textContent.trim();
if (colorMap[value]) {
el.style.backgroundColor = colorMap[value];
el.classList.add("invert_in_dark_mode");
}
});
});
}
function colorize_table_entries () {
setTimeout(() => {
if (typeof result_names !== "undefined" && Array.isArray(result_names) && result_names.length > 0) {
_colorize_table_entries_by_trial_status();
_colorize_table_entries_by_results();
_colorize_table_entries_by_run_time();
_colorize_table_entries_by_generation_method();
_colorize_table_entries_by_generation_node_or_hostname();
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
}
}, 300);
}
function add_colorize_to_gridjs_table () {
let searchInput = document.querySelector(".gridjs-search-input");
if (searchInput) {
searchInput.addEventListener("input", colorize_table_entries);
}
}
function updatePreWidths() {
var width = window.innerWidth * 0.95;
var pres = document.getElementsByTagName('pre');
for (var i = 0; i < pres.length; i++) {
pres[i].style.width = width + 'px';
}
}
function demo_mode(nr_sec = 3) {
let i = 0;
let tabs = $('menu[role="tablist"] > button');
setInterval(() => {
tabs.attr('aria-selected', 'false').removeClass('active');
let tab = tabs.eq(i % tabs.length);
tab.attr('aria-selected', 'true').addClass('active');
tab.trigger('click');
i++;
}, nr_sec * 1000);
}
function resizePlotlyCharts() {
const plotlyElements = document.querySelectorAll('.js-plotly-plot');
if (plotlyElements.length) {
const windowWidth = window.innerWidth;
const windowHeight = window.innerHeight;
const newWidth = windowWidth * 0.9;
const newHeight = windowHeight * 0.9;
plotlyElements.forEach(function(element, index) {
const layout = {
width: newWidth,
height: newHeight,
plot_bgcolor: 'rgba(0, 0, 0, 0)',
paper_bgcolor: 'rgba(0, 0, 0, 0)',
};
Plotly.relayout(element, layout)
});
}
make_text_in_parallel_plot_nicer();
apply_theme_based_on_system_preferences();
}
window.addEventListener('load', updatePreWidths);
window.addEventListener('resize', updatePreWidths);
$(document).ready(function() {
colorize_table_entries();
add_up_down_arrows_for_scrolling();
add_colorize_to_gridjs_table();
});
window.addEventListener('resize', function() {
resizePlotlyCharts();
});
"use strict";
function get_row_by_index(idx) {
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
var trial_index_col_idx = tab_results_headers_json.indexOf("trial_index");
if(trial_index_col_idx == -1) {
error(`"trial_index" could not be found in tab_results_headers_json. Cannot continue`);
return null;
}
for (var i = 0; i < tab_results_csv_json.length; i++) {
var row = tab_results_csv_json[i];
var trial_index = row[trial_index_col_idx];
if (trial_index == idx) {
return row;
}
}
return null;
}
function load_pareto_graph_from_idxs () {
if (!Object.keys(window).includes("pareto_idxs")) {
error("pareto_idxs is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
if(pareto_idxs === null) {
var err_msg = "pareto_idxs is null. Cannot plot or create tables from empty data. This can be caused by a defective <tt>pareto_idxs.json</tt> file. Please try reloading, or re-calculating the pareto-front and re-submitting if this problem persists.";
$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
return;
}
var table = get_pareto_table_data_from_idx();
var html_tables = createParetoTablesFromData(table);
$("#pareto_from_idxs_table").html(html_tables);
renderParetoFrontPlots(table);
apply_theme_based_on_system_preferences();
}
function renderParetoFrontPlots(data) {
try {
let container = document.getElementById("pareto_front_idxs_plot_container");
if (!container) {
console.error("DIV with id 'pareto_front_idxs_plot_container' not found.");
return;
}
container.innerHTML = "";
if(data === undefined || data === null) {
var err_msg = "There was an error getting the data for Pareto-Fronts. See the developer's console to see further details.";
$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
return;
}
Object.keys(data).forEach((key, idx) => {
if (!key.startsWith("Pareto front for ")) return;
let label = key.replace("Pareto front for ", "");
let [xKey, yKey] = label.split("/");
if (!xKey || !yKey) {
console.warn("Could not extract two objectives from key:", key);
return;
}
let entries = data[key];
let x = [];
let y = [];
let hoverTexts = [];
entries.forEach((entry) => {
let results = entry.results || {};
let values = entry.values || {};
let xVal = (results[xKey] || [])[0];
let yVal = (results[yKey] || [])[0];
if (xVal === undefined || yVal === undefined) {
console.warn("Missing values for", xKey, yKey, "in", entry);
return;
}
x.push(xVal);
y.push(yVal);
let hoverInfo = [];
if ("trial_index" in values) {
hoverInfo.push(`<b>Trial Index:</b> ${values.trial_index[0]}`);
}
Object.keys(values)
.filter(k => k !== "trial_index")
.sort()
.forEach(k => {
hoverInfo.push(`<b>${k}:</b> ${values[k][0]}`);
});
Object.keys(results)
.sort()
.forEach(k => {
hoverInfo.push(`<b>${k}:</b> ${results[k][0]}`);
});
hoverTexts.push(hoverInfo.join("<br>"));
});
let wrapper = document.createElement("div");
wrapper.style.marginBottom = "30px";
let titleEl = document.createElement("h3");
titleEl.textContent = `Pareto Front: ${xKey} (${getMinMaxByResultName(xKey)}) vs ${yKey} (${getMinMaxByResultName(yKey)})`;
wrapper.appendChild(titleEl);
let divId = `pareto_plot_${idx}`;
let plotDiv = document.createElement("div");
plotDiv.id = divId;
plotDiv.style.width = "100%";
plotDiv.style.height = "400px";
wrapper.appendChild(plotDiv);
container.appendChild(wrapper);
let trace = {
x: x,
y: y,
text: hoverTexts,
hoverinfo: "text",
mode: "markers",
type: "scatter",
marker: {
size: 8,
color: 'rgb(31, 119, 180)',
line: {
width: 1,
color: 'black'
}
},
name: label
};
let layout = {
xaxis: { title: { text: xKey } },
yaxis: { title: { text: yKey } },
margin: { t: 10, l: 60, r: 20, b: 50 },
hovermode: "closest",
showlegend: false
};
Plotly.newPlot(divId, [trace], add_default_layout_data(layout, 1));
});
} catch (e) {
console.error("Error while rendering Pareto front plots:", e);
}
}
function createParetoTablesFromData(data) {
try {
var container = document.createElement("div");
var parsedData;
try {
parsedData = typeof data === "string" ? JSON.parse(data) : data;
} catch (e) {
console.error("JSON parsing failed:", e);
return container;
}
for (var sectionTitle in parsedData) {
if (!parsedData.hasOwnProperty(sectionTitle)) {
continue;
}
var sectionData = parsedData[sectionTitle];
var heading = document.createElement("h2");
heading.textContent = sectionTitle;
container.appendChild(heading);
var table = document.createElement("table");
table.style.borderCollapse = "collapse";
table.style.marginBottom = "2em";
table.style.width = "100%";
var thead = document.createElement("thead");
var headerRow = document.createElement("tr");
var allValueKeys = new Set();
var allResultKeys = new Set();
sectionData.forEach(entry => {
var values = entry.values || {};
var results = entry.results || {};
Object.keys(values).forEach(key => {
allValueKeys.add(key);
});
Object.keys(results).forEach(key => {
allResultKeys.add(key);
});
});
var sortedValueKeys = Array.from(allValueKeys).sort();
var sortedResultKeys = Array.from(allResultKeys).sort();
if (sortedValueKeys.includes("trial_index")) {
sortedValueKeys = sortedValueKeys.filter(k => k !== "trial_index");
sortedValueKeys.unshift("trial_index");
}
var allColumns = [...sortedValueKeys, ...sortedResultKeys];
allColumns.forEach(col => {
var th = document.createElement("th");
th.textContent = col;
th.style.border = "1px solid black";
th.style.padding = "4px";
headerRow.appendChild(th);
});
thead.appendChild(headerRow);
table.appendChild(thead);
var tbody = document.createElement("tbody");
sectionData.forEach(entry => {
var tr = document.createElement("tr");
allColumns.forEach(col => {
var td = document.createElement("td");
td.style.border = "1px solid black";
td.style.padding = "4px";
var value = null;
if (col in entry.values) {
value = entry.values[col];
} else if (col in entry.results) {
value = entry.results[col];
}
if (Array.isArray(value)) {
td.textContent = value.join(", ");
} else {
td.textContent = value !== null && value !== undefined ? value : "";
}
tr.appendChild(td);
});
tbody.appendChild(tr);
});
table.appendChild(tbody);
container.appendChild(table);
}
return container;
} catch (err) {
console.error("Unexpected error:", err);
var errorDiv = document.createElement("div");
errorDiv.textContent = "Error generating tables.";
return errorDiv;
}
}
function get_pareto_table_data_from_idx () {
if (!Object.keys(window).includes("pareto_idxs")) {
error("pareto_idxs is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
var x_keys = Object.keys(pareto_idxs);
var tables = {};
for (var i = 0; i < x_keys.length; i++) {
var x_key = x_keys[i];
var y_keys = Object.keys(pareto_idxs[x_key]);
for (var j = 0; j < y_keys.length; j++) {
var y_key = y_keys[j];
var indices = pareto_idxs[x_key][y_key];
for (var k = 0; k < indices.length; k++) {
var idx = indices[k];
var row = get_row_by_index(idx);
if(row === null) {
error(`Error getting the row for index ${idx}`);
return;
}
var row_dict = {
"results": {},
"values": {},
};
for (var l = 0; l < tab_results_headers_json.length; l++) {
var header = tab_results_headers_json[l];
if (!special_col_names.includes(header) || header == "trial_index") {
var val = row[l];
if (result_names.includes(header)) {
if (!Object.keys(row_dict["results"]).includes(header)) {
row_dict["results"][header] = [];
}
row_dict["results"][header].push(val);
} else {
if (!Object.keys(row_dict["values"]).includes(header)) {
row_dict["values"][header] = [];
}
row_dict["values"][header].push(val);
}
}
}
var table_key = `Pareto front for ${x_key}/${y_key}`;
if(!Object.keys(tables).includes(table_key)) {
tables[table_key] = [];
}
tables[table_key].push(row_dict);
}
}
}
return tables;
}
function getMinMaxByResultName(resultName) {
try {
if (typeof resultName !== "string") {
error("Parameter resultName must be a string");
return;
}
if (!Array.isArray(result_names)) {
error("Global variable result_names is not an array or undefined");
return;
}
if (!Array.isArray(result_min_max)) {
error("Global variable result_min_max is not an array or undefined");
return;
}
if (result_names.length !== result_min_max.length) {
error("Global arrays result_names and result_min_max must have the same length");
return;
}
var index = result_names.indexOf(resultName);
if (index === -1) {
error("Result name '" + resultName + "' not found in result_names");
return;
}
var minMaxValue = result_min_max[index];
if (minMaxValue !== "min" && minMaxValue !== "max") {
error("Value for result name '" + resultName + "' is invalid: expected 'min' or 'max'");
return;
}
return minMaxValue;
} catch (e) {
error("Unexpected error: " + e.message);
}
}
$(document).ready(function() {
colorize_table_entries();;
plotWorkerUsage();;
plotCPUAndRAMUsage();;
createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names);;
plotScatter2d();;
plotScatter3d();
plotJobStatusDistribution();;
plotBoxplot();;
plotViolin();;
plotHistogram();;
plotHeatmap();;
plotResultPairs();;
plotResultEvolution();
colorize_table_entries();
});
</script>
<h1> Overview</h1>
<h2>Experiment overview: </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Setting</th><th>Value </th></tr></thead><tbody><tr><td> Max. nr. evaluations</td><td>50000 </td></tr><tr><td> Number random steps</td><td>20 </td></tr><tr><td> Nr. of workers (parameter)</td><td>20 </td></tr><tr><td> Main process memory (GB)</td><td>8 </td></tr><tr><td> Worker memory (GB)</td><td>1 </td></tr></tbody></table><h2>Experiment parameters: </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Name</th><th>Type</th><th>Lower bound</th><th>Upper bound</th><th>Type</th><th>Log Scale? </th></tr></thead><tbody><tr><td> recent_samples_size</td><td>int</td><td>1</td><td>5000</td><td>int</td><td>No </td></tr><tr><td> batch_size</td><td>int</td><td>1</td><td>5000</td><td>int</td><td>No </td></tr><tr><td> theta</td><td>float</td><td>0.0001</td><td>0.999</td><td>float</td><td>No </td></tr><tr><td> lambida</td><td>float</td><td>0.001</td><td>0.999</td><td>float</td><td>No </td></tr></tbody></table><h2>Number of evaluations</h2>
<table>
<tbody>
<tr>
<th>Failed</th>
<th>Succeeded</th>
<th>Running</th>
<th>Total</th>
</tr>
<tr>
<td>6</td>
<td>698</td>
<td>1</td>
<td>705</td>
</tr>
</tbody>
</table>
<h2>Result names and types</h2>
<table>
<tr><th>name</th><th>min/max</th></tr>
<tr>
<td>ACCURACY</td>
<td>max</td>
</tr>
<tr>
<td>RUNTIME</td>
<td>min</td>
</tr>
</table>
<br>
<h2>Git-Version</h2>
<tt>Commit: 2223ae6553abdd3e288f4b391080b763a7a48477
</tt>
<h1> Results</h1>
<div id='tab_results_csv_table'></div>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download »results.csv« as file</button>
<pre id='tab_results_csv_table_pre'>trial_index,arm_name,trial_status,generation_method,generation_node,ACCURACY,RUNTIME,recent_samples_size,batch_size,theta,lambida
0,0_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,872,2094,0.970058648765087072618484853592,0.876536382198333741122553419700
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4094,4351,0.056712592495232826139694992662,0.400326041644439079014716753591
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2930,756,0.712037229666300119923505462793,0.516474552702158695716150305088
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2050,2874,0.251348218974936754577242936648,0.011741272073239088918894523772
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1847,281,0.133351427943818268140319105441,0.248241430031135690281729466733
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3194,3672,0.828067333260271709605149226263,0.724451474087312807803584746580
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4530,1328,0.424554693400394145275100754588,0.358747966885566704764443102249
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,525,4813,0.604182285462692370003878750140,0.863481098800897628464667832304
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,186,1129,0.466066859850753079097529507635,0.660958646090701207320705634629
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4776,2742,0.505344933042116473131954990095,0.186925263347104186895109023681
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3456,2273,0.224628753627091642952606775907,0.803686777755618142471405462857
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1523,3785,0.810210735303070417323567653511,0.293851312354207028221253494848
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2414,1808,0.678436805902793982347986911918,0.463759904703125336311586579541
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2629,4554,0.358338901340495785685646978891,0.937793495645746544298049229837
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3809,334,0.886723567453119865255928289116,0.071594528313726188417653872875
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1250,3214,0.082752974636666476460078456512,0.581430320885032436706296721241
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1090,519,0.535456795604620117146055235935,0.318588887447491309057312491859
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3961,3421,0.496208970126323423155412228880,0.841352768683806040428407868603
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2787,1701,0.779790880802646246827691811632,0.210918134696781639503271321701
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2260,4425,0.194300118578504765753933725136,0.699312223590910386761265726818
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1364,2496,0.325921860509365779456913969625,0.556690762324258736626347854326
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3611,3952,0.646232920558657442100525258866,0.033926732374355200727578107944
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4937,984,0.114739119984675203012258748458,0.913802563149482049986715992418
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,35,2653,0.918861896549351464535959621571,0.425408206570893510090058953210
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,369,1414,0.026648310960363595645272738466,0.097131145237013702398165548857
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4685,4961,0.939903135684505119940013173618,0.618173517970368235907585585664
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3354,118,0.281712767252139728579862776314,0.484518177423626184019411766712
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1694,3446,0.742371530230436449393494058313,0.979505394045263488855823652557
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1891,883,0.860459536992199680582871224033,0.778085435101762423748539276858
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3082,2984,0.165591447927523394145765678331,0.257043389538303024277610120407
30,30_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.998999999999999999111821580300,0.998999999999999999111821580300
31,31_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.000100000000000000004792173602,0.001000000000000000020816681712
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.998999999999999999111821580300,0.001000000000000000020816681712
33,33_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.000100000000000000004792173602,0.998999999999999999111821580300
34,34_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.998999999999999999111821580300,0.001000000000000000020816681712
35,35_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,196,0.000100000000000000004792173602,0.001000000000000000020816681712
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.998999999999999999111821580300,0.001000000000000000020816681712
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.000100000000000000004792173602,0.998999999999999999111821580300
38,38_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.000100000000000000004792173602,0.998999999999999999111821580300
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.998999999999999999111821580300,0.998999999999999999111821580300
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.000100000000000000004792173602,0.998999999999999999111821580300
41,41_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.000100000000000000004792173602,0.001000000000000000020816681712
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.998999999999999999111821580300,0.001000000000000000020816681712
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4881,0.998999999999999999111821580300,0.998999999999999999111821580300
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.998999999999999999111821580300,0.998999999999999999111821580300
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.000100000000000000004792173602,0.001000000000000000020816681712
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3078,0.000100000000000000004792173602,0.998999999999999999111821580300
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2309,1,0.998999999999999999111821580300,0.998999999999999999111821580300
48,48_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4438,2501,0.998999999999999999111821580300,0.001000000000000000020816681712
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2432,1,0.000100000000000000004792173602,0.998999999999999999111821580300
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2321,0.000100000000000000004792173602,0.998999999999999999111821580300
51,51_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.000100000000000000004792173602,0.449383757928467575393227662062
52,52_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2353,5000,0.000100000000000000004792173602,0.001000000000000000020816681712
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2012,1,0.998999999999999999111821580300,0.001000000000000000020816681712
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1981,5000,0.000100000000000000004792173602,0.998999999999999999111821580300
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2790,5000,0.998999999999999999111821580300,0.001000000000000000020816681712
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2903,0.998999999999999999111821580300,0.001000000000000000020816681712
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2859,5000,0.998999999999999999111821580300,0.998999999999999999111821580300
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2104,0.000100000000000000004792173602,0.001000000000000000020816681712
59,59_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,51,490,0.514457862563297507740855962766,0.998999999999999999111821580300
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,160,2432,0.000100000000000000004792173602,0.553568219733470590071533479204
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,150,703,0.998999999999999999111821580300,0.692930647004994182402981550695
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4902,256,0.000100000000000000004792173602,0.468808064981844185847847938930
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,848,0.998999999999999999111821580300,0.540662230487113038002178200259
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1979,0.000100000000000000004792173602,0.001000000000000000020816681712
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,687,3610,0.000100000000000000004792173602,0.001000000000000000020816681712
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3615,1,0.000100000000000000004792173602,0.001000000000000000020816681712
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.606219592974093002268887175887,0.001000000000000000020816681712
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2147,0.998999999999999999111821580300,0.998999999999999999111821580300
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2003,1,0.000100000000000000004792173602,0.001000000000000000020816681712
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4628,5000,0.533061960123254352517108145548,0.001000000000000000020816681712
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.000100000000000000004792173602,0.694553629949563378076504704950
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2979,0.998999999999999999111821580300,0.998999999999999999111821580300
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.510049693606626108888235648919,0.998999999999999999111821580300
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1561,5000,0.998999999999999999111821580300,0.001000000000000000020816681712
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.650689391432167862916458034306,0.001000000000000000020816681712
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.000100000000000000004792173602,0.564207996056031224618720898434
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.000100000000000000004792173602,0.001000000000000000020816681712
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3539,0.000100000000000000004792173602,0.001000000000000000020816681712
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3742,5000,0.000100000000000000004792173602,0.001000000000000000020816681712
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.562954605562519416750433265406,0.001000000000000000020816681712
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.802360030770999710370006141602,0.998999999999999999111821580300
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.654933701990644268065011601720,0.354657946684237557199992352253
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.268345435515238817103522706020,0.001000000000000000020816681712
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4372,0.369780474783088841661538026528,0.998999999999999999111821580300
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.998999999999999999111821580300,0.607005069516049600153451137885
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1965,0.998999999999999999111821580300,0.001000000000000000020816681712
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.593783416432409949514692470984,0.998999999999999999111821580300
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.000100000000000000004792173602,0.677537785321185359599382991291
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,859,5000,0.000100000000000000004792173602,0.998999999999999999111821580300
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,88,57,0.998999999999999999111821580300,0.461538369365699585600282262021
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1,0.998999999999999999111821580300,0.324394257759465398649467715586
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,317,1842,0.000100000000000000004792173602,0.998999999999999999111821580300
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1321,5000,0.998999999999999999111821580300,0.998999999999999999111821580300
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3997,0.998999999999999999111821580300,0.001000000000000000020816681712
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,144,0.000100000000000000004792173602,0.998999999999999999111821580300
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1064,0.998999999999999999111821580300,0.998999999999999999111821580300
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1233,1,0.000100000000000000004792173602,0.998999999999999999111821580300
98,98_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.998999999999999999111821580300,0.344011259847838313241652485885
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1582,1,0.998999999999999999111821580300,0.998999999999999999111821580300
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,675,0.998999999999999999111821580300,0.001000000000000000020816681712
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,30,1900,0.998999999999999999111821580300,0.001000000000000000020816681712
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3846,0.998999999999999999111821580300,0.001000000000000000020816681712
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,447,0.000100000000000000004792173602,0.411094345705804331547739138841
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3391,1,0.998999999999999999111821580300,0.001000000000000000020816681712
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3590,5000,0.000100000000000000004792173602,0.998999999999999999111821580300
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3463,0.998999999999999999111821580300,0.998999999999999999111821580300
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4307,138,0.998999999999999999111821580300,0.707999185264932440198037966184
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3467,1,0.000100000000000000004792173602,0.998999999999999999111821580300
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4808,1060,0.998999999999999999111821580300,0.001000000000000000020816681712
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3948,5000,0.998999999999999999111821580300,0.001000000000000000020816681712
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3443,537,0.998999999999999999111821580300,0.998999999999999999111821580300
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1087,0.000100000000000000004792173602,0.001000000000000000020816681712
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1162,0.998999999999999999111821580300,0.998999999999999999111821580300
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.327563925771609920634119816896,0.998999999999999999111821580300
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,854,511,0.438401642203792851759658333322,0.001000000000000000020816681712
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3608,207,0.454968560151625345255865795480,0.998999999999999999111821580300
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.998999999999999999111821580300,0.998999999999999999111821580300
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4894,5000,0.433975913296336723856683192935,0.998999999999999999111821580300
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.258204855597635285491264767188,0.998999999999999999111821580300
120,120_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,641,2073,0.000100000000000000004792173602,0.523463945925419560367686244717
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,18,2094,0.998999999999999999111821580300,0.582535377760536099422949973814
122,122_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2019,0.998999999999999999111821580300,0.423442619455632607294859326430
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,4798,2104,0.000100000000000000004792173602,0.601935885590805908051947881177
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,214,1938,0.000100000000000000004792173602,0.320348735617373314710221166024
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4709,0.998999999999999999111821580300,0.001000000000000000020816681712
126,126_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4886,2010,0.000100000000000000004792173602,0.402208094879137778576705386513
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2564,4048,0.000100000000000000004792173602,0.998999999999999999111821580300
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3913,4791,0.000100000000000000004792173602,0.001000000000000000020816681712
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4753,2136,0.998999999999999999111821580300,0.739161394180770425776927368133
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,66,1909,0.998999999999999999111821580300,0.297493617279598498992498889493
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1395,3842,0.998999999999999999111821580300,0.998999999999999999111821580300
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,157,2076,0.998999999999999999111821580300,0.418560964696418236208330654335
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4480,2631,0.000100000000000000004792173602,0.998999999999999999111821580300
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4430,1388,0.998999999999999999111821580300,0.998999999999999999111821580300
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1577,4541,0.000100000000000000004792173602,0.001000000000000000020816681712
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4072,0.998999999999999999111821580300,0.998999999999999999111821580300
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,166,3229,0.000100000000000000004792173602,0.001000000000000000020816681712
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3856,0.000100000000000000004792173602,0.998999999999999999111821580300
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3984,0.000100000000000000004792173602,0.998999999999999999111821580300
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,177,783,0.000100000000000000004792173602,0.998999999999999999111821580300
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4997,4017,0.998999999999999999111821580300,0.998999999999999999111821580300
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,677,4748,0.998999999999999999111821580300,0.001000000000000000020816681712
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,582,2671,0.998999999999999999111821580300,0.998999999999999999111821580300
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4862,4148,0.000100000000000000004792173602,0.257016973348111354980005671678
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,93,4492,0.998999999999999999111821580300,0.001000000000000000020816681712
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1414,4284,0.000100000000000000004792173602,0.001000000000000000020816681712
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4776,4723,0.000100000000000000004792173602,0.272058193094110112308925408797
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,231,4657,0.998999999999999999111821580300,0.262522621161264346767438837560
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1012,2323,0.000100000000000000004792173602,0.001000000000000000020816681712
150,150_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3853,2321,0.998999999999999999111821580300,0.976917976590574110851150635426
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,316,1731,0.000100000000000000004792173602,0.393341591013706248780579244340
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,76,1670,0.998999999999999999111821580300,0.425584957821112053188983281871
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4827,2246,0.000100000000000000004792173602,0.353122082472763665350612427574
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4775,4390,0.000100000000000000004792173602,0.134192188414906210525145979773
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,292,489,0.998999999999999999111821580300,0.853384831570560553615223398083
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5,4827,0.998999999999999999111821580300,0.479119999990853584481698135278
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,179,849,0.000100000000000000004792173602,0.112926543760047015663161573684
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,802,4893,0.998999999999999999111821580300,0.138907980753726845168927184204
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4010,4986,0.000100000000000000004792173602,0.152405394876059391284783828269
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,196,4306,0.998999999999999999111821580300,0.312702443979431810028302152205
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,212,4890,0.000100000000000000004792173602,0.136040274793947840725749642843
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4764,1603,0.998999999999999999111821580300,0.432376095510340618943700974341
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,766,3873,0.000100000000000000004792173602,0.858497425867187247128242688632
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,267,2250,0.000100000000000000004792173602,0.359701458817428543213168268267
165,165_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4558,2562,0.000100000000000000004792173602,0.495840154586554171523005152267
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4951,97,0.000100000000000000004792173602,0.127999077471875055689309874651
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1425,377,0.000100000000000000004792173602,0.683740450968852830904154416203
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4985,4394,0.998999999999999999111821580300,0.331961230702889908972252897001
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4913,967,0.998999999999999999111821580300,0.171760364707827462016354047591
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4906,1263,0.998999999999999999111821580300,0.860027708183648043060998134024
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3801,105,0.000100000000000000004792173602,0.868586085062283630442436788144
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,970,3366,0.998999999999999999111821580300,0.001000000000000000020816681712
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4294,415,0.998999999999999999111821580300,0.591749242469705838409765874530
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.820000000000000062172489379009,1.000000000000000000000000000000,3392,529,0.000100000000000000004792173602,0.853793801226887638655682621902
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4134,4696,0.000100000000000000004792173602,0.998999999999999999111821580300
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2782,1,0.998999999999999999111821580300,0.861930093481117487463905035838
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,268,4999,0.000100000000000000004792173602,0.749850240645937526906550374406
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,100,886,0.998999999999999999111821580300,0.200186411851675627460167561367
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,344,4326,0.998999999999999999111821580300,0.831176911241878646485758963536
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1183,2289,0.998999999999999999111821580300,0.626197940175651557304092875711
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4681,1683,0.998999999999999999111821580300,0.556954371628301636576452438021
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,135,2909,0.998999999999999999111821580300,0.353770006269589598613123371251
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2541,0.000100000000000000004792173602,0.604961307336757125874271423527
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4884,3428,0.998999999999999999111821580300,0.168719049970636109092581023106
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,406,1250,0.998999999999999999111821580300,0.501161906164969694899014029943
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,450,4370,0.998999999999999999111821580300,0.552038844910251347286589407304
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4960,3994,0.998999999999999999111821580300,0.423541589148896779892794484113
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,82,3699,0.998999999999999999111821580300,0.147812774093128485031201080346
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4952,4188,0.998999999999999999111821580300,0.585059399757035247802150479401
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,32,3066,0.998999999999999999111821580300,0.130245446798297775936603670743
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,176,3475,0.998999999999999999111821580300,0.542450377410742978767643762694
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2649,0.998999999999999999111821580300,0.306595902651067508948301565397
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,486,1711,0.998999999999999999111821580300,0.593225879447782156184132418275
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4363,0.000100000000000000004792173602,0.551944222428904618382716762426
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4720,1323,0.278943565849829822056449302181,0.515620132465161695733968372224
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,628,3418,0.000100000000000000004792173602,0.176005122354744802937176473279
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4821,4102,0.998999999999999999111821580300,0.700722556468542534524601705925
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4882,955,0.000100000000000000004792173602,0.306565784071221480999724917638
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4986,4209,0.998999999999999999111821580300,0.144942760222615929510681098691
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,253,1465,0.998999999999999999111821580300,0.001000000000000000020816681712
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,249,3966,0.998999999999999999111821580300,0.518067324859563527184036502149
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1587,0.000100000000000000004792173602,0.001000000000000000020816681712
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3555,1754,0.998999999999999999111821580300,0.721575380784496678288064686058
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1176,3048,0.998999999999999999111821580300,0.400434434166656250120297499961
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,160,1545,0.998999999999999999111821580300,0.562642198648818925299508464377
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4733,3332,0.998999999999999999111821580300,0.397084086443766970386803905058
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3015,0.998999999999999999111821580300,0.823401058888779568967208888353
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,364,2569,0.998999999999999999111821580300,0.302730586937382639689531060867
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,474,4055,0.080784260611054287126719941625,0.697057868539173397515185115481
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,667,2373,0.998999999999999999111821580300,0.639487529200160720321832741320
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2388,0.998999999999999999111821580300,0.638562307354622160637802608107
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,1,1800,0.000100000000000000004792173602,0.769010060156666286346194283396
213,213_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,928,2090,0.998999999999999999111821580300,0.567622095379369473455710704002
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2116,0.998999999999999999111821580300,0.567572568532330401502861150220
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,756,2353,0.000100000000000000004792173602,0.644547269036794268082246617269
216,216_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,1489,2201,0.000100000000000000004792173602,0.567465922244068221580448607710
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,2756,2205,0.000100000000000000004792173602,0.660483682444033881608902447624
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1800,2344,0.998999999999999999111821580300,0.646745302017880385747616855951
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,621,0.000100000000000000004792173602,0.453303521946999576908154949706
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4288,2105,0.998999999999999999111821580300,0.567380144121561347247961748508
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1018,337,0.000100000000000000004792173602,0.289154368185540133762145842411
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,17,2066,0.000100000000000000004792173602,0.567990545019029680062772058591
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,367,2332,0.998999999999999999111821580300,0.650677131627590443763153871259
224,224_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2256,0.000100000000000000004792173602,0.567780758624108150556253349350
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1936,2050,0.998999999999999999111821580300,0.568004532600690059673809173546
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1384,2017,0.998999999999999999111821580300,0.568303418081888112034505411430
227,227_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,491,2033,0.000100000000000000004792173602,0.568440081198959168418127774203
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,3.000000000000000000000000000000,4498,1610,0.000100000000000000004792173602,0.771630472857655513863051055523
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,1092,2402,0.000100000000000000004792173602,0.637967425506446805805182975746
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,5000,2073,0.000100000000000000004792173602,0.567662917910581654723500832915
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1117,4776,0.998999999999999999111821580300,0.911799202322381097118864090589
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,460,2541,0.998999999999999999111821580300,0.653886556087467041287197844213
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,628,924,0.998999999999999999111821580300,0.863774583641155446755988123186
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1060,2415,0.998999999999999999111821580300,0.632367845701450215223360373784
235,235_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4904,2117,0.998999999999999999111821580300,0.567754587725621373550666248775
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4613,0.000100000000000000004792173602,0.045886918779906485377217961741
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4898,0.998999999999999999111821580300,0.302700232246825351456465114097
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,746,0.998999999999999999111821580300,0.951400614314588777276071596134
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,626,4851,0.000100000000000000004792173602,0.193573065282327566594133827493
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3470,2563,0.331521555742055440418880607467,0.998999999999999999111821580300
241,241_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3586,2691,0.216781351128239707648504008830,0.998999999999999999111821580300
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,388,2268,0.427226797622934084674994892339,0.939341084361712597150528836210
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2436,2490,0.315510335921363016531415723875,0.998999999999999999111821580300
244,244_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4000,2567,0.252799631813118763634662400364,0.998999999999999999111821580300
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3071,2676,0.348905113077664863485694013434,0.998999999999999999111821580300
246,246_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4299,2619,0.000100000000000000004792173602,0.296359697165530955320633665906
247,247_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1521,735,0.257089813622689344896343754954,0.998999999999999999111821580300
248,248_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3403,2637,0.396918263843459684370174045398,0.869902148630166127674101517187
249,249_0,COMPLETED,BoTorch,GenerationStep_1,0.830000000000000071054273576010,1.000000000000000000000000000000,4496,633,0.211299047576111675983412396818,0.998999999999999999111821580300
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,3516,826,0.304118021147909978196821612073,0.998999999999999999111821580300
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3310,2274,0.439201376859489289739002515489,0.961954151636751353393606223108
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2793,2641,0.271130957496966862318998892079,0.998999999999999999111821580300
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3250,2467,0.370866087322823889671496999654,0.998999999999999999111821580300
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4187,2389,0.418689173776914280722394323675,0.998999999999999999111821580300
255,255_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1746,2728,0.000100000000000000004792173602,0.297146614023831745488024580482
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,1.000000000000000000000000000000,470,676,0.277444913413504135046849796709,0.998999999999999999111821580300
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1542,1819,0.236954654588448859753313513465,0.181321401668810056051484025375
258,258_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,788,532,0.201031051103783775513278442304,0.998999999999999999111821580300
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,1117,788,0.298931093566698335983744527766,0.998999999999999999111821580300
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,993,2577,0.251642566742344087060700985603,0.998999999999999999111821580300
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,918,1867,0.229828591965425349519236419837,0.261417565659822992429894839006
262,262_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3665,4966,0.257892742348687309394961175713,0.151756226273005362381596228261
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3835,2542,0.301042510452670053489043766604,0.998999999999999999111821580300
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3369,1503,0.500491140502045128712893529155,0.998999999999999999111821580300
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,679,2537,0.343203905372443884846944683886,0.970122534799666702554077346576
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2944,2002,0.287494697285076705739470526169,0.258721372093494939026214751721
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3075,1976,0.478071054450592891615912094494,0.832827382432649865329210570053
268,268_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4068,518,0.271735197100929248836820306678,0.804339648735621914887872208055
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1959,2274,0.693207662306717375955145143962,0.906499647341726833005282060185
270,270_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,42,125,0.094506072689592837687833082327,0.938563213944435092983553658996
271,271_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2685,3757,0.610521593613177482318121747085,0.206952386638149632425154322846
272,272_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,4299,2308,0.401481658053584378187395032000,0.621242007238790416856488718622
273,273_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1705,3440,0.884326896225009151386586836452,0.358479662476107463486840742917
274,274_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2371,1476,0.739064662764314594944892178319,0.446938741521909821408087282180
275,275_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,4728,2769,0.223051810866035510327876068004,0.713569186212494988019727770734
276,276_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3270,1168,0.763148736804723726301347141998,0.114138412320986384895782350668
277,277_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,865,4961,0.280298566192667908403279852791,0.849616388717666315422150091763
278,278_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1177,2165,0.832935293998382952906922582770,0.641047022137790967200032810069
279,279_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3583,3299,0.316915057393629073789753647361,0.377278317648917449478318530964
280,280_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,4415,598,0.669725619899388391331740422174,0.793491273399442476055298811843
281,281_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2059,4232,0.186868060859665258144346466906,0.062946052383631462268098744062
282,282_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1392,689,0.437653950508311406775163732163,0.149916452638804903463309869949
283,283_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3986,4474,0.953677337102498912102532813151,0.884390924610197526334331996622
284,284_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2998,1631,0.057885788663197310088825986440,0.286866473034024238586425781250
285,285_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,355,2916,0.540738887853734140342965019954,0.554563476711511627037509697402
286,286_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,508,1846,0.373679474542010559012794601585,0.081384385684505108904396308844
287,287_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2865,2983,0.858479561176709871084256064933,0.812693518662825242770963996009
288,288_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3903,914,0.130113869548216465332757252327,0.484288493933156150017538266184
289,289_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1497,4551,0.644174907615687741824217482645,0.746870939867571026482551133086
290,290_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1286,3245,0.000455926524820534848081443613,0.532410340337469256688507357467
291,291_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4758,4529,0.938464550134755826071852879977,0.001000000000000000020816681712
292,292_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4415,4525,0.783118017795100374023320455308,0.001000000000000000020816681712
293,293_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1555,4838,0.849675865001861541081495943217,0.001000000000000000020816681712
294,294_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,969,4837,0.502964258253411289345535806206,0.998999999999999999111821580300
295,295_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4898,0.896017264707844596216546051437,0.001000000000000000020816681712
296,296_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,2.000000000000000000000000000000,684,563,0.718624470630214173816341372003,0.998999999999999999111821580300
297,297_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,82,290,0.805081017265529941262514057598,0.998999999999999999111821580300
298,298_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1313,4203,0.766823346051501264497574084089,0.998999999999999999111821580300
299,299_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,20,107,0.829086362633761342344485001377,0.998999999999999999111821580300
300,300_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,429,1316,0.793701373857354841589994975948,0.998999999999999999111821580300
301,301_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,152,509,0.631646455499741188432949456910,0.998999999999999999111821580300
302,302_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4904,4723,0.467974513053476537383090771982,0.001000000000000000020816681712
303,303_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1014,4880,0.904176095743423946515804345836,0.998999999999999999111821580300
304,304_0,FAILED,BoTorch,BOTORCH_MODULAR,,,161,1272,0.162349121006712171499941632646,0.998999999999999999111821580300
305,305_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4924,4336,0.726650212923517502261461231683,0.001000000000000000020816681712
306,306_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4955,4880,0.687635157695106746800206565240,0.001000000000000000020816681712
307,307_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,885,338,0.041866573158108752461536994360,0.998999999999999999111821580300
308,308_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,343,973,0.898757298711972407723180822359,0.998999999999999999111821580300
309,309_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,669,343,0.235956855337564275210127107130,0.676134003102112135508150458918
310,310_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,822,527,0.649928543938728009443650535104,0.521066106869788825406430987641
311,311_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,768,140,0.731662311408964427528189844452,0.236441028704310246544295637250
312,312_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,668,1583,0.644151718266341433150046213996,0.741837225106568465271550394391
313,313_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1187,4781,0.134454465465344147334647573189,0.358693619770218130593519845206
314,314_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,765,3321,0.916996500100207390104856131074,0.998999999999999999111821580300
315,315_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,348,838,0.931579272572152561338043597061,0.659193855685965224289191155549
316,316_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,744,1935,0.883056673635857269921700662962,0.998999999999999999111821580300
317,317_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1002,4851,0.696215160599128246587952162372,0.998999999999999999111821580300
318,318_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4533,0.523060070694305823124636845023,0.399742932020139773996447729587
319,319_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,17,2423,0.153544226945320466670708015045,0.998999999999999999111821580300
320,320_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4816,4971,0.412419239108618940203854208448,0.001000000000000000020816681712
321,321_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,359,3780,0.306054063115277497075794599368,0.998999999999999999111821580300
322,322_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,209,4035,0.099001881557850099357942497136,0.001000000000000000020816681712
323,323_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,6,1529,0.569378219459363288379449841159,0.998999999999999999111821580300
324,324_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1233,663,0.824115307597708457443275165133,0.389447376039160575444952883117
325,325_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2228,4883,0.740517231497191619205011647864,0.453500251121078279403775468381
326,326_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,274,2869,0.596413485790659669838476020232,0.998999999999999999111821580300
327,327_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3609,4449,0.866716222763597166078852751525,0.417448734621249206711013357562
328,328_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,917,430,0.583738696715261018432840955938,0.998999999999999999111821580300
329,329_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,112,1080,0.233610323789324975107817294884,0.808783769365554627839287604729
330,330_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1054,3821,0.415163501158675951607790466369,0.490064564432005522753854620532
331,331_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.551881487402486547999558297306,0.771822963392016503370030022779
332,332_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,445,833,0.358140777992862313627853154685,0.524970502690361162656529359083
333,333_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,712,2536,0.243029976789339685616653241595,0.326400330495941859432207365899
334,334_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,873,2048,0.000100000000000000004792173602,0.180791031385925476948628443097
335,335_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4048,3249,0.653124312484073654694327615289,0.001000000000000000020816681712
336,336_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,777,1103,0.622275922796273639470143734798,0.001000000000000000020816681712
337,337_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1304,2243,0.748853315918974971054922207259,0.001000000000000000020816681712
338,338_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.420902219396755594704728764555,0.591023258540763096746672999870
339,339_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.453409410895735276447737760463,0.359361006362027946003934175678
340,340_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.829999999999999960031971113494,1.000000000000000000000000000000,1,487,0.000100000000000000004792173602,0.840776571694647478771855730884
341,341_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2526,0.700644072241228932362844261661,0.001000000000000000020816681712
342,342_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,940,4344,0.481596481412687460466059974351,0.183826059017434179088112955469
343,343_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,349,4206,0.607985773286599195941448670055,0.383208462855816056613633691086
344,344_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,683,4615,0.533612366404269566899642995850,0.189936626342402714584522982477
345,345_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1113,3678,0.418194245538289044450408482589,0.001000000000000000020816681712
346,346_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,200,4107,0.534061634970149134993278039474,0.652246188532978110607984945091
347,347_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,56,3467,0.482692332296147330605862180164,0.001000000000000000020816681712
348,348_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2034,2484,0.627485145876599648140370391047,0.537389301721477918860614408914
349,349_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,928,4039,0.589458069821904295793046912877,0.808477299378730918100188773678
350,350_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,627,3481,0.264790149140479602607456399710,0.001000000000000000020816681712
351,351_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,502,1650,0.779419844506813563889124907291,0.866129558142046618307574590290
352,352_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,539,5000,0.622258855168450031314364423451,0.199439542400699693081023156083
353,353_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,84,3153,0.654991355989892665157015017030,0.182242128753401289031899068505
354,354_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,342,2089,0.727302088709437244418154477898,0.236090262575654297183547214445
355,355_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,70,4095,0.522172294017835825208351252513,0.998999999999999999111821580300
356,356_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,305,645,0.711541197458337326686717005941,0.001000000000000000020816681712
357,357_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,26,2454,0.618801447532627002523497594666,0.741019254283746708900082467153
358,358_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1715,1133,0.463856698203866824048446915185,0.261457799953423497552051912862
359,359_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,317,3211,0.489337033190456127673684250112,0.689354573668450543166841271159
360,360_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,660,2438,0.552079293788448666191470692866,0.330195290165959109973670138061
361,361_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,664,2966,0.337529333771904305194766493514,0.537394805545396092583132485743
362,362_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,799,1240,0.647842208251782514238925614336,0.579092626190649051309833339474
363,363_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,589,3627,0.998999999999999999111821580300,0.802632759590390376658319837588
364,364_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3663,2031,0.699760934317859906172998307738,0.998999999999999999111821580300
365,365_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,718,4016,0.322420711118045044685231914627,0.346389499335959416548291756044
366,366_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,11,5000,0.388948474831272927865200017550,0.478197798645523863836359623747
367,367_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,436,5000,0.789461616180756942107166196365,0.789239651848217538265828352451
368,368_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2563,0.435630923061250063810234678385,0.001000000000000000020816681712
369,369_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3738,1840,0.711724422091659647549022338353,0.001000000000000000020816681712
370,370_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,124,4535,0.287572738997633525759312078662,0.575077469308084898713673283055
371,371_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,612,2892,0.175955712512477768783014653309,0.442459703522999459046616266278
372,372_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,684,967,0.333023520639827541600652693887,0.001000000000000000020816681712
373,373_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,558,3777,0.082307699687963836732151889919,0.306705180390984044613844616833
374,374_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1062,309,0.998999999999999999111821580300,0.195596664662437108583858957900
375,375_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,231,1457,0.788260894347216800603916908585,0.001000000000000000020816681712
376,376_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,21,3392,0.774751463082480773536531160062,0.601222893839359340262262776378
377,377_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,83,5000,0.694578297735013006075632802094,0.574017712193638063311595942650
378,378_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,199,3792,0.725504632548552463866542439064,0.998999999999999999111821580300
379,379_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4282,0.489603772161023742537366842953,0.001000000000000000020816681712
380,380_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,75,4607,0.314828615588733262686815805864,0.001000000000000000020816681712
381,381_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,527,1522,0.998999999999999999111821580300,0.998999999999999999111821580300
382,382_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1950,0.554544449409997253219728463591,0.505013289494098294163393347844
383,383_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,130,2945,0.613769962558919579542759947799,0.001000000000000000020816681712
384,384_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1924,1,0.734363876400499937524557481083,0.553134367748999378200380760973
385,385_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,852,3262,0.064580829022128499738997220447,0.846775199097412056836731153453
386,386_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4572,2369,0.916999960460982199705881612317,0.194794954501977646277310896039
387,387_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,72,5000,0.249906205048595980722225817772,0.330017671110717336624418294377
388,388_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,23,3707,0.669639001691640589619680667965,0.489657563831520092900717600060
389,389_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1744,3658,0.998999999999999999111821580300,0.346637431009248542235212653395
390,390_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1369,0.254494614383345030272920439529,0.249105794262855839704684512981
391,391_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4312,3539,0.348753249823101130200342367971,0.164947656594856245648728076958
392,392_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3590,3531,0.373775622530138573740288165936,0.609794984464978928606626595865
393,393_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,184,905,0.654535378596715511356762817741,0.709905304301664985544562114228
394,394_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,975,4567,0.000100000000000000004792173602,0.785739228355151086979901720042
395,395_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,935,4363,0.000100000000000000004792173602,0.977258254052047803384084545542
396,396_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,59,42,0.998999999999999999111821580300,0.782740026183157078243368687254
397,397_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4699,1724,0.998999999999999999111821580300,0.162978501394506786192906133692
398,398_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3375,4449,0.525839610263064471951111045200,0.670787255793293568650881297799
399,399_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,746,520,0.798099684861556024628725936054,0.217166895990171332497808975859
400,400_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,768,2053,0.686867537991669219188395345554,0.701191652676796839394057769823
401,401_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,411,3657,0.703044396588211939480572709726,0.001000000000000000020816681712
402,402_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,9,3086,0.584452728060847692681534226722,0.335989862869002398060302994054
403,403_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4515,2827,0.810602047933852154493195030227,0.202578867675099805190086499351
404,404_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,448,3282,0.000100000000000000004792173602,0.408024344389857962500656185512
405,405_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,679,3952,0.736829540577606412199429541943,0.096834703494083268493497484997
406,406_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,117,3884,0.045534691020521413096222573813,0.525817112882515425020812926959
407,407_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2268,3189,0.998999999999999999111821580300,0.586121772567997578740062181168
408,408_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,612,1413,0.905135347871273143738335420494,0.716013674424099577642266467592
409,409_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,995,4737,0.430018516178029774899016501877,0.322909818519514613122112223209
410,410_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4580,0.998999999999999999111821580300,0.708931153290766502550468430854
411,411_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,657,5000,0.449611054187456782305076785633,0.734960458316850528959207622393
412,412_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4322,1468,0.623758920744406974989715308766,0.001000000000000000020816681712
413,413_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4172,3908,0.277090201534784030812375021924,0.704793999275874383236839548772
414,414_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,947,507,0.998999999999999999111821580300,0.477115559450171589084277457005
415,415_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1461,1434,0.998999999999999999111821580300,0.214138439831595278617371036489
416,416_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,335,2615,0.000100000000000000004792173602,0.084072177937903252997742242769
417,417_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,169,43,0.790716954298484764329657537019,0.773697728313549548673222489015
418,418_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,264,4763,0.000100000000000000004792173602,0.887209987003988564957523976773
419,419_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,63,4327,0.665188199286616654859471964301,0.185328888576785782982270234243
420,420_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2422,4630,0.000100000000000000004792173602,0.593483245595608055467096164648
421,421_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,16,1221,0.783364743621683845553604896850,0.326825664433532891983702484140
422,422_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,492,4354,0.691332953386851634114407261222,0.545463019176852581537673358980
423,423_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3776,0.236137852290811967037598151364,0.123542411249618275248529641885
424,424_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1820,452,0.036064217448069688098932772391,0.001000000000000000020816681712
425,425_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1434,5000,0.000100000000000000004792173602,0.288163388610503223841163844554
426,426_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,498,4518,0.196647763427896943300154930512,0.153135334929734440168047626685
427,427_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,679,2396,0.169652288740813034229049094392,0.199751034008015165843730187589
428,428_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4761,4547,0.221837160262084637230017847287,0.186099306769470229649954262641
429,429_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2818,1732,0.793436734348035632713447284914,0.998999999999999999111821580300
430,430_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,682,3422,0.710598567008005055356534285238,0.230544992513764118724495233437
431,431_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1007,3763,0.779893214752986896343145417632,0.828721958700162297795088761632
432,432_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1367,3029,0.352679813289986654467611515429,0.730308935429299754815701817279
433,433_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4893,4353,0.308526711331164882334832100241,0.392854122734686173057383484775
434,434_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1370,0.856160272677186862111398113484,0.821514890827730992484134731058
435,435_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4795,3058,0.998999999999999999111821580300,0.751893931114273272875436759932
436,436_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1950,0.662193418124251365064480978617,0.937197698319641947506397627876
437,437_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,356,4012,0.367108349190219007684987673201,0.101358199381265376426419777545
438,438_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,503,3873,0.385726452255332197260884186107,0.827138304233866361592220073362
439,439_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,939,4553,0.998999999999999999111821580300,0.998999999999999999111821580300
440,440_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2018,1619,0.512200118896467770923663920257,0.283713694023919049680415582770
441,441_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,320,4190,0.780406069753213360584709334944,0.826202102384804071277812909102
442,442_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,88,2138,0.555273213764197803854472113017,0.001000000000000000020816681712
443,443_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2119,1576,0.000100000000000000004792173602,0.189557568327573672251062930627
444,444_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3137,2689,0.402980087465675151925381669571,0.447541840144377367494143982185
445,445_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,247,4192,0.223284880093490706309822257936,0.876330239568191338150882074842
446,446_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,194,4773,0.616882218110277991129919428204,0.565774157483740158802731912147
447,447_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,847,2872,0.679308689681574318086632047198,0.660514100743334053866817612288
448,448_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4176,1,0.804072399865984777100891278678,0.001000000000000000020816681712
449,449_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1026,1377,0.433714663623037011142002938868,0.001000000000000000020816681712
450,450_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1085,4532,0.589564483754971613294060261978,0.998999999999999999111821580300
451,451_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4158,0.414837284193050159775140173224,0.001000000000000000020816681712
452,452_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,147,260,0.501108977078124961934690873022,0.123585109928129002754282339538
453,453_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3290,3321,0.925643236571565330983446528990,0.001000000000000000020816681712
454,454_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3608,620,0.998999999999999999111821580300,0.001000000000000000020816681712
455,455_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1972,3968,0.000100000000000000004792173602,0.001000000000000000020816681712
456,456_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1105,5000,0.233989318317023020643574682254,0.001000000000000000020816681712
457,457_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2990,1,0.707859012271293774887226391002,0.198565058846465247732737680053
458,458_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,349,969,0.292760109490869113724187400294,0.336262094015234824784243983231
459,459_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1103,1,0.288881791028943513133242504409,0.252509312200535573911253095503
460,460_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3679,4478,0.685347770217329399500272302248,0.848235578045968829918876963347
461,461_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,244,117,0.361048602587179079392853964237,0.495459558397424004727582769192
462,462_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3351,2938,0.998999999999999999111821580300,0.001000000000000000020816681712
463,463_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1044,337,0.881770941202674296555130695197,0.611847605810458938790930005780
464,464_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4697,3361,0.694072054155452922152846895187,0.681557795033208568824534268060
465,465_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,842,3432,0.936138435278167313491337608866,0.113509415922580528257590515295
466,466_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,160,1039,0.998999999999999999111821580300,0.388431697845670331759038163000
467,467_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2693,4610,0.757908664649709296057267238211,0.625383010440068387580936359882
468,468_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1586,2207,0.998999999999999999111821580300,0.130671301298370762244971388100
469,469_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4689,2852,0.997220856923943910210539343097,0.501846373578984650265510936151
470,470_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4388,4246,0.404958329064973254762804799611,0.772572347244153245782172234613
471,471_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1641,2923,0.000100000000000000004792173602,0.001000000000000000020816681712
472,472_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2722,0.900651864752949671277804100100,0.052734390904326085280917624232
473,473_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4826,2935,0.860163609880698509790875050385,0.998999999999999999111821580300
474,474_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3179,2193,0.696047629773896003868571824569,0.343670718153571030928361551560
475,475_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4919,4349,0.174721691813416735161723636338,0.001000000000000000020816681712
476,476_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4866,3981,0.705945051126716793810089711769,0.499870295923641239088652810096
477,477_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1026,5000,0.972027153059712323290852964419,0.841263902494494120176682372403
478,478_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3387,4677,0.200605772613106664303828097218,0.998999999999999999111821580300
479,479_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3899,3946,0.324071349467040470404555208006,0.200323412353959784404366928356
480,480_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,678,3117,0.236326308454968714301003274159,0.073630191111491424815760353795
481,481_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,459,3493,0.515615251119806550228474861797,0.998999999999999999111821580300
482,482_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4801,2330,0.000100000000000000004792173602,0.223868989460116990519722435238
483,483_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,85,3938,0.863809750607938520161610540526,0.602556857117201527529459781363
484,484_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,744,1,0.669095218824561799308980880596,0.392704624647063349485165417718
485,485_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,90,5000,0.143712456647120734309908129944,0.557080152285202023776378155162
486,486_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2090,0.569659044935896363703875522333,0.998999999999999999111821580300
487,487_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1001,1290,0.998999999999999999111821580300,0.001000000000000000020816681712
488,488_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1116,1109,0.551143328343571492489161300909,0.450402736033213402233599254032
489,489_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,860,2574,0.738246258767857432836478892568,0.143391901461424137176337012534
490,490_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1951,950,0.772118818718198873796154657612,0.001000000000000000020816681712
491,491_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1143,432,0.714290589418609678240557059326,0.658121713703219479718597995088
492,492_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2140,584,0.998999999999999999111821580300,0.385205381607911290231527345895
493,493_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4235,3619,0.202530620472965272593768304432,0.486294042095401279901523139415
494,494_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,12,1783,0.689547012611047893670956909773,0.840887115242858751429366748198
495,495_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,729,1,0.605559837739067852169227990089,0.904044811857519947650985159271
496,496_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,41,342,0.998999999999999999111821580300,0.307591651182807901410143358589
497,497_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,309,3505,0.583899989322852919215733891178,0.622782357866180413807910554169
498,498_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,473,5000,0.338138538968290491837365152605,0.138768687010472180354270221869
499,499_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4588,2379,0.637286558228544408599702819629,0.631619211874472008538816680812
500,500_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2852,4021,0.799225018452835000992706682155,0.001000000000000000020816681712
501,501_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,412,278,0.998999999999999999111821580300,0.066353557317551922767329131148
502,502_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,990,3534,0.313922594288247702731808885801,0.311771354482135332197856314451
503,503_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,641,2202,0.521057803306688605005092540523,0.261942553794735633054813206400
504,504_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1,0.350389446067603527179556976989,0.001000000000000000020816681712
505,505_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2222,2234,0.382866865398955480426224085022,0.001000000000000000020816681712
506,506_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,55,349,0.998999999999999999111821580300,0.776232391073632621569799994177
507,507_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1387,329,0.801579756804408294357244813000,0.001000000000000000020816681712
508,508_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4848,4587,0.753706552949076402647676786728,0.209827667179442178824189113584
509,509_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,725,5000,0.181458185239897318297153105959,0.770575253497966405902275255357
510,510_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2515,1043,0.998999999999999999111821580300,0.668649445860866831203850324528
511,511_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,545,3151,0.305250808061191980513626731408,0.001000000000000000020816681712
512,512_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3714,1459,0.348334944597735618465605966776,0.157422446252376307951337253144
513,513_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4441,4883,0.917701561525326781065814429894,0.758743745372944533578163373022
514,514_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,2.000000000000000000000000000000,53,2977,0.000100000000000000004792173602,0.473326176742312865197703786180
515,515_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,17,2460,0.541836685055346989337010654708,0.133665342356672489643187873298
516,516_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,646,2460,0.767334641444856968561794019479,0.418101822460549554794084770037
517,517_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,670,4386,0.536066079126869765580920557113,0.885172588278534067107727878465
518,518_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1176,3514,0.259879275381685315160495974851,0.749765104504877100133342082700
519,519_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,218,3198,0.771699300717010872041612401517,0.437439531115905999580917296043
520,520_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1741,3575,0.010478405848853183587876536365,0.744910390634067942627893899044
521,521_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4726,719,0.605656977805735574627021833294,0.288226329339157205655652660425
522,522_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2054,0.000100000000000000004792173602,0.144608055904410504055590536154
523,523_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3968,769,0.966087393161474294878132695885,0.257146134904909895446678547160
524,524_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,577,4412,0.000100000000000000004792173602,0.310264701011056409640787023818
525,525_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4506,5000,0.569322107868543425546192793263,0.827608151965664395888211402053
526,526_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3844,3817,0.000100000000000000004792173602,0.214749524051295881399425979907
527,527_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3986,3823,0.000100000000000000004792173602,0.501250395271181203860066943889
528,528_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4754,4667,0.200356666144219652814228993520,0.506847419418237965516027543345
529,529_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,805,4029,0.998999999999999999111821580300,0.303286951831414075542170394328
530,530_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,74,3411,0.469967341746516720224491336921,0.206509086148947140770815167343
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4398,477,0.204372267368122029207455625510,0.102178652141934916963705859416
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1275,582,0.391054034500790737016728826347,0.608658305287707035446942427370
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,290,2666,0.463101278795217674577600064367,0.337997162574435239257297780568
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4953,2724,0.525051721898227463647401691560,0.563324302885492511627774092631
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4328,2827,0.414822718025138037489796261070,0.815183603068547202319393818470
536,536_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,970,2709,0.438039909847197261871798446009,0.661655863582175318704514666024
537,537_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3932,4829,0.545534880230563290481882177119,0.601247745197931560134918527183
538,538_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2841,3250,0.644468595544525513219014101196,0.342953743154564338890821773020
539,539_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3876,3273,0.293017865896718687768185418463,0.001000000000000000020816681712
540,540_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,220,1322,0.651421511225314664450536383811,0.755897800008631826074179116404
541,541_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4611,861,0.000100000000000000004792173602,0.001000000000000000020816681712
542,542_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,289,4599,0.317666513320719046120643724862,0.765172003631231167908310908388
543,543_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,516,4943,0.755411719936448733392353460658,0.155246243638995390368151561233
544,544_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,915,3473,0.141580810371297188821060331065,0.998999999999999999111821580300
545,545_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,794,2313,0.998999999999999999111821580300,0.001000000000000000020816681712
546,546_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,524,2428,0.808961310986025639024887823325,0.845734190012499165156611979910
547,547_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3202,1712,0.998999999999999999111821580300,0.950864496144281257095087767084
548,548_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4441,4632,0.723609020523417467707361083740,0.352254437461503311368460344966
549,549_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,113,4320,0.119836587142782211024005789568,0.466086101077785419644072817391
550,550_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4772,805,0.444358358829507360532318216428,0.001000000000000000020816681712
551,551_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1029,323,0.998999999999999999111821580300,0.001000000000000000020816681712
552,552_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,850,0.513526604128106134439235574973,0.001000000000000000020816681712
553,553_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4837,3872,0.647893737822975435136640953715,0.989720845995602283018399702996
554,554_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2452,3843,0.313276471927004973583308355956,0.467547044271213019239752384237
555,555_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,733,3546,0.650504574149751157996490746882,0.378415535137093084205872628445
556,556_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3289,1,0.998999999999999999111821580300,0.170778855761018838466114289076
557,557_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,392,2204,0.331727032041855274258068675408,0.267537527303205568962596316851
558,558_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4740,1933,0.605509388954404315086321730632,0.001000000000000000020816681712
559,559_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,325,3960,0.190187809417545178325426036281,0.422360582351667068756739809032
560,560_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,413,4127,0.000100000000000000004792173602,0.223900939472283511122441268526
561,561_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4739,2882,0.693808843231951355434716788295,0.323697947066236502156044707590
562,562_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,29,3706,0.000100000000000000004792173602,0.625108510431108155280810478871
563,563_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,813,932,0.998999999999999999111821580300,0.762018274033810838474778392992
564,564_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1543,4938,0.427562004719088784021607807517,0.898645404246680490345511316264
565,565_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,312,3252,0.323340213183275715369546787770,0.210829933119527523910363697723
566,566_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1291,2738,0.998999999999999999111821580300,0.808061165666194791690202237078
567,567_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,445,1575,0.411761812672286009462396805247,0.372307568682685663397080588766
568,568_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3848,2354,0.329771956827392909161744682933,0.334611415833677205977636504031
569,569_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3775,4130,0.998999999999999999111821580300,0.896044898819139734591487922444
570,570_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,105,4601,0.844336516017008098522467207658,0.812097705722545137874135434686
571,571_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,488,1512,0.221348915468285806218418088065,0.001000000000000000020816681712
572,572_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,220,3289,0.998999999999999999111821580300,0.717868122363776950400904297567
573,573_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4127,2654,0.000100000000000000004792173602,0.001000000000000000020816681712
574,574_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1228,959,0.998999999999999999111821580300,0.001000000000000000020816681712
575,575_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2526,3818,0.998999999999999999111821580300,0.901976964561665983666216561687
576,576_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3066,1300,0.133699476497557062648624537360,0.001000000000000000020816681712
577,577_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4881,3324,0.889707232416537596719763314468,0.646836432501758262780811037373
578,578_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1233,3913,0.273687569192505864013043037630,0.917952054372591863540264967014
579,579_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,431,3790,0.239724775596179440206867639063,0.001000000000000000020816681712
580,580_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1792,3252,0.412442533832516167180415322946,0.998999999999999999111821580300
581,581_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2579,2402,0.821363258532806783662749694486,0.322777772305503030114692819552
582,582_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,97,3534,0.998999999999999999111821580300,0.998999999999999999111821580300
583,583_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,575,445,0.363764671802316974513757941168,0.201455933107077156396513828440
584,584_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1094,3807,0.000100000000000000004792173602,0.098110420689053470799656508916
585,585_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,964,907,0.664953421083290252546760257246,0.130135861873127589571907947175
586,586_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,926,893,0.707821630926021794216751459317,0.265059972957144507343940631472
587,587_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4914,3476,0.543817224987656167023430953122,0.094385829296461803972206894287
588,588_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3354,3298,0.528125326523856575278159652953,0.483645523623085771269813903928
589,589_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,128,1227,0.998999999999999999111821580300,0.829259731842278524638345515996
590,590_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,617,1680,0.737717918230972546922430410632,0.001000000000000000020816681712
591,591_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2135,0.000100000000000000004792173602,0.163191570776390348918027939362
592,592_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4787,1724,0.776611003285676559926287154667,0.807185432638732547339088796434
593,593_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,21,2268,0.609958545206197411125970120338,0.475243024195641017293212371442
594,594_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4488,4330,0.779198049270687032041848851804,0.712189797192655849045195282088
595,595_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,561,3140,0.998999999999999999111821580300,0.998999999999999999111821580300
596,596_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4453,3628,0.813644608456450035838258827425,0.263979138608162688939273721189
597,597_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1028,2627,0.808130294268031956761433320935,0.998999999999999999111821580300
598,598_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,427,4190,0.000100000000000000004792173602,0.840917543336006212406630311307
599,599_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1001,1074,0.800872954480841392488343899458,0.499503649305370889255328847867
600,600_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,428,262,0.431606077867469073439110616164,0.680949920817124909611095517903
601,601_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,745,306,0.680003064453544081580105284957,0.469467954526163133710525698916
602,602_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,103,4474,0.956380659190050552709294606757,0.427897281928492578817468938723
603,603_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4381,4767,0.105221788851634953654290427494,0.802007276022905002399454588158
604,604_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,337,4137,0.797364206288086685425753330492,0.249009122520779307974336802545
605,605_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4821,4466,0.893110133621435875461713749246,0.182695964885715184111703024428
606,606_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4147,2282,0.164265760443712993676967926149,0.241143096070020934718058924773
607,607_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2059,1004,0.459990852701298191806955628635,0.548334518463797659926228789118
608,608_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,204,3827,0.000100000000000000004792173602,0.346630486630615131105059845140
609,609_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,434,3007,0.274280001339519630132457450600,0.893308857501412090229564455512
610,610_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,149,1,0.486266923005655826717230638678,0.998999999999999999111821580300
611,611_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,248,1721,0.724716305091123391690643984475,0.139485503642629932175012186235
612,612_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4539,3067,0.884882690131161275814974942477,0.183199064179273535257763683148
613,613_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,31,3049,0.452103604199543152031282033931,0.121355175122437985990586639673
614,614_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4062,1770,0.000100000000000000004792173602,0.168674288442731801218599230197
615,615_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2449,3539,0.210999336444024992998080847428,0.207237523265203449351901099362
616,616_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4713,3437,0.455306828002590258108739362797,0.404860379000185677256240524002
617,617_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1574,4446,0.471736445621535604999507995672,0.489532708966530727412447276947
618,618_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1696,1378,0.000100000000000000004792173602,0.246389405912240733176332696530
619,619_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3635,3918,0.397498483539977798262299302223,0.001000000000000000020816681712
620,620_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,690,5000,0.998999999999999999111821580300,0.367204112894192802318826807095
621,621_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,133,1537,0.777424417320727534352897691861,0.581845250247847611824170144246
622,622_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,359,1,0.998999999999999999111821580300,0.254187565597288389618313431129
623,623_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4110,4549,0.769516201053079273997070686164,0.998999999999999999111821580300
624,624_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4518,3215,0.756335379175576139054726354516,0.972051494582972352986871555913
625,625_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3800,3634,0.998999999999999999111821580300,0.001000000000000000020816681712
626,626_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2341,4564,0.998999999999999999111821580300,0.001000000000000000020816681712
627,627_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2572,5000,0.687494569346929984554606107849,0.998999999999999999111821580300
628,628_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2413,4849,0.526232712118207435203487420949,0.119654050687698479404907914159
629,629_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3777,2911,0.998999999999999999111821580300,0.173989962907134115832619158937
630,630_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1063,841,0.000100000000000000004792173602,0.715474872564904273986030602828
631,631_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1116,275,0.293608674508269107406022158102,0.998999999999999999111821580300
632,632_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1516,252,0.337433912536377389468356113866,0.886628312914039651282394061127
633,633_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,153,1,0.998999999999999999111821580300,0.590553018267570228871932158654
634,634_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4391,4120,0.998999999999999999111821580300,0.001000000000000000020816681712
635,635_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,495,0.089398486756264702868257643331,0.001000000000000000020816681712
636,636_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,366,1683,0.738244763718784779982229338202,0.998999999999999999111821580300
637,637_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,20,2906,0.388375824176284634159372899376,0.001000000000000000020816681712
638,638_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,122,2826,0.288057184748179317956839895487,0.155298154511244707043360335774
639,639_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4923,612,0.747246991150086858901602226979,0.087663680782335592911458377330
640,640_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2608,1508,0.710362178796634213817640102206,0.901755678875770461111471831828
641,641_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2965,1538,0.957576970442674424432993873779,0.264377953763069051262846187456
642,642_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,197,3842,0.962468411236876986158961244655,0.717613648503297452130311739893
643,643_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,21,2433,0.000100000000000000004792173602,0.224524421277765839910500744736
644,644_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2883,3041,0.790142297076892541340953357576,0.001000000000000000020816681712
645,645_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,950,217,0.564757069637221831293061313772,0.239737725452217359523032769175
646,646_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4986,2559,0.255966482322560195949989747533,0.001000000000000000020816681712
647,647_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,261,4559,0.061001068222988619194069315199,0.998999999999999999111821580300
648,648_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2686,3645,0.998999999999999999111821580300,0.475505092163185594245078391396
649,649_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,569,1899,0.661094291935833133777578041190,0.396996792069326365215431451361
650,650_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3858,5000,0.880713575119838054661158821546,0.256350844291041379818807399715
651,651_0,FAILED,BoTorch,BOTORCH_MODULAR,,,725,680,0.000100000000000000004792173602,0.765146994524924295433265797328
652,652_0,FAILED,BoTorch,BOTORCH_MODULAR,,,933,717,0.000100000000000000004792173602,0.684898759129685230639950077602
653,653_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3425,3870,0.998999999999999999111821580300,0.001000000000000000020816681712
654,654_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,847,131,0.495658034763492072460877579942,0.801520763585934603590033020737
655,655_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1680,2553,0.598365371207086438332112265925,0.709169735386283695000031457312
656,656_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,328,0.807421212086622874792851689563,0.371928640395549237052108537682
657,657_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2902,4409,0.998999999999999999111821580300,0.998999999999999999111821580300
658,658_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,777,845,0.043701690560884187686241375559,0.727554693009763275846069063846
659,659_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1151,3528,0.000100000000000000004792173602,0.466960278206977663639776210402
660,660_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1004,687,0.000100000000000000004792173602,0.694228663513266841533777551376
661,661_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,275,3319,0.998999999999999999111821580300,0.904666944643258807978725144494
662,662_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,284,3563,0.433391800586835351793979498325,0.733492314484231244797740600916
663,663_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4119,1466,0.998999999999999999111821580300,0.001000000000000000020816681712
664,664_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1979,4664,0.998999999999999999111821580300,0.768608399762362615170729895908
665,665_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3250,2835,0.684584045647718353322375151038,0.819032171488706439710369977547
666,666_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4012,1061,0.728960752501958131333026358334,0.610650147418818733946466181806
667,667_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4111,3992,0.620186950278576620831927357358,0.692458184846679314361495016783
668,668_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2205,3487,0.000100000000000000004792173602,0.998999999999999999111821580300
669,669_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,852,2741,0.119747429818031145276613358419,0.125233016953568782048122898232
670,670_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,948,1,0.000100000000000000004792173602,0.349562031554527807841736830596
671,671_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1701,5000,0.194358481260986537542123642197,0.501920381392259806752065287583
672,672_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3676,1059,0.463318726068036867982158355517,0.080654359173816067563045351108
673,673_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2438,2960,0.998999999999999999111821580300,0.399401684248040511615585046457
674,674_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2336,2576,0.998999999999999999111821580300,0.886359182492812425202544091007
675,675_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4273,0.000100000000000000004792173602,0.001000000000000000020816681712
676,676_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1889,2815,0.998999999999999999111821580300,0.001000000000000000020816681712
677,677_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,985,2655,0.000100000000000000004792173602,0.998999999999999999111821580300
678,678_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3660,4729,0.998999999999999999111821580300,0.998999999999999999111821580300
679,679_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1267,4242,0.383923517417523896266828842272,0.529777752373680077546680422529
680,680_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1327,1775,0.434810629927328162747102169305,0.001000000000000000020816681712
681,681_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,275,4248,0.247790747452635351510963346300,0.998999999999999999111821580300
682,682_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,208,3570,0.268921700772428384773604648217,0.557698274353873424402650016418
683,683_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,890,1348,0.685430914067244212439788952906,0.168717534425916276807910776370
684,684_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4507,1212,0.998999999999999999111821580300,0.157922477912226549845442491460
685,685_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3032,2152,0.623855851314759513037699889537,0.846946087424878757410340313072
686,686_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4665,2306,0.998999999999999999111821580300,0.347630886352832180197225397933
687,687_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3053,3186,0.000100000000000000004792173602,0.098859508706536758371186124350
688,688_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,153,704,0.233984396457383808654029166973,0.001000000000000000020816681712
689,689_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4979,4948,0.216948862710244522178371084919,0.001000000000000000020816681712
690,690_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4775,2974,0.998999999999999999111821580300,0.677902622733387971720731002279
691,691_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,753,335,0.621119978795637961432873908052,0.778305466149493918592838781478
692,692_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,773,1339,0.008876002727986992760222939580,0.353771302873497117680301471410
693,693_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2675,3430,0.000100000000000000004792173602,0.662881514920846348637439859885
694,694_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,540,237,0.299905284433084673434422029459,0.001000000000000000020816681712
695,695_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,674,85,0.332532678546208049219501390326,0.998999999999999999111821580300
696,696_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,158,2553,0.444044904101026483012049084209,0.534686265222337753222348055715
697,697_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1388,2187,0.636260000604328856965707927884,0.806383327391660409411144883052
698,698_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1274,3167,0.671844281022281664128570355388,0.998999999999999999111821580300
699,699_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1369,219,0.998999999999999999111821580300,0.998999999999999999111821580300
700,700_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3123,4273,0.403899031085939774765591891992,0.163696461201487009073929357328
701,701_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3313,4562,0.522985726819155116729120891250,0.001000000000000000020816681712
702,702_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1606,1,0.998999999999999999111821580300,0.609356567132291582211678360181
703,703_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,328,3828,0.312256358945586676156835892471,0.569172258378874529327617892704
704,704_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,4136,296,0.998999999999999999111821580300,0.001000000000000000020816681712
</pre>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download »results.csv« as file</button>
<script>
createTable(tab_results_csv_json, tab_results_headers_json, 'tab_results_csv_table');</script>
<h1> Errors</h1>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download »oo_errors.txt« as file</button>
<pre id='simple_pre_tab_tab_errors'><span style="background-color: black; color: white">Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
⚠ Job 4623615 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4623615/4623615_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4623615/4623615_0_log.out
----------------------------------------
submitit INFO (2025-04-23 13:25:01,723) - Starting with JobEnvironment(job_id=4623615, hostname=i7169, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-23 13:25:01,725) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4623615/4623615_submitted.pkl
slurmstepd: error: *** JOB 4623615 ON i7169 CANCELLED AT 2025-04-23T15:24:55 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4623615.batch. Some of the step tasks have been OOM Killed.
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4623615/4623615_0_log.err not found
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
⚠ Job 4688809 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4688809/4688809_0_result.pkl
has not produced any output (state: NODE_FAIL)
No output/error stream produced ! Check: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4688809/4688809_0_log.out
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4688809/4688809_0_log.out not found
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4688809/4688809_0_log.err not found
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
⚠ Job 4717749 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4717749/4717749_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4717749/4717749_0_log.out
----------------------------------------
submitit INFO (2025-04-25 07:12:15,256) - Starting with JobEnvironment(job_id=4717749, hostname=i7182, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 07:12:15,259) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4717749/4717749_submitted.pkl
slurmstepd: error: *** JOB 4717749 ON i7182 CANCELLED AT 2025-04-25T09:12:42 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4717749.batch. Some of the step tasks have been OOM Killed.
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4717749/4717749_0_log.err not found
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
⚠ Job 4728470 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4728470/4728470_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4728470/4728470_0_log.out
----------------------------------------
submitit INFO (2025-04-25 13:50:10,461) - Starting with JobEnvironment(job_id=4728470, hostname=i7185, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 13:50:10,477) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4728470/4728470_submitted.pkl
slurmstepd: error: *** JOB 4728470 ON i7185 CANCELLED AT 2025-04-25T15:50:24 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4728470.batch. Some of the step tasks have been OOM Killed.
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4728470/4728470_0_log.err not found
⚠ Job 4728903 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4728903/4728903_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4728903/4728903_0_log.out
----------------------------------------
submitit INFO (2025-04-25 14:06:44,390) - Starting with JobEnvironment(job_id=4728903, hostname=i7185, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 14:06:44,392) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4728903/4728903_submitted.pkl
slurmstepd: error: *** JOB 4728903 ON i7185 CANCELLED AT 2025-04-25T16:06:55 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4728903.batch. Some of the step tasks have been OOM Killed.
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4728903/4728903_0_log.err not found
⚠ Job 4735815 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4735815/4735815_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4735815/4735815_0_log.out
----------------------------------------
submitit INFO (2025-04-25 18:37:25,509) - Starting with JobEnvironment(job_id=4735815, hostname=i7176, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 18:37:25,511) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4735815/4735815_submitted.pkl
slurmstepd: error: *** JOB 4735815 ON i7176 CANCELLED AT 2025-04-25T20:37:37 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4735815.batch. Some of the step tasks have been OOM Killed.
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4735815/4735815_0_log.err not found
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
Error while simulating loading data: Expecting value: line 1 column 1 (char 0)
</span></pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download »oo_errors.txt« as file</button>
<h1> Args Overview</h1>
<h2>Arguments Overview: </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Key</th><th>Value </th></tr></thead><tbody><tr><td> config_yaml</td><td>None </td></tr><tr><td> config_toml</td><td>None </td></tr><tr><td> config_json</td><td>None </td></tr><tr><td> num_random_steps</td><td>20 </td></tr><tr><td> max_eval</td><td>50000 </td></tr><tr><td> run_program</td><td>None </td></tr><tr><td> experiment_name</td><td>None </td></tr><tr><td> mem_gb</td><td>1 </td></tr><tr><td> parameter</td><td>None </td></tr><tr><td> continue_previous_job</td><td>/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/DDAL_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/ </td></tr><tr><td> experiment_constraints</td><td>None </td></tr><tr><td> run_dir</td><td>runs </td></tr><tr><td> seed</td><td>None </td></tr><tr><td> decimalrounding</td><td>4 </td></tr><tr><td> enforce_sequential_optimization</td><td>False </td></tr><tr><td> verbose_tqdm</td><td>False </td></tr><tr><td> model</td><td>None </td></tr><tr><td> gridsearch</td><td>False </td></tr><tr><td> occ</td><td>False </td></tr><tr><td> show_sixel_scatter</td><td>False </td></tr><tr><td> show_sixel_general</td><td>False </td></tr><tr><td> show_sixel_trial_index_result</td><td>False </td></tr><tr><td> follow</td><td>False </td></tr><tr><td> send_anonymized_usage_stats</td><td>False </td></tr><tr><td> ui_url</td><td>None </td></tr><tr><td> root_venv_dir</td><td>/home/s4122485 </td></tr><tr><td> exclude</td><td>None </td></tr><tr><td> main_process_gb</td><td>8 </td></tr><tr><td> pareto_front_confidence</td><td>1 </td></tr><tr><td> max_nr_of_zero_results</td><td>10 </td></tr><tr><td> abbreviate_job_names</td><td>False </td></tr><tr><td> orchestrator_file</td><td>None </td></tr><tr><td> checkout_to_latest_tested_version</td><td>False </td></tr><tr><td> live_share</td><td>False </td></tr><tr><td> disable_tqdm</td><td>False </td></tr><tr><td> workdir</td><td>False </td></tr><tr><td> occ_type</td><td>euclid </td></tr><tr><td> result_names</td><td>['RESULT=min'] </td></tr><tr><td> minkowski_p</td><td>2 </td></tr><tr><td> signed_weighted_euclidean_weights</td><td></td></tr><tr><td> generation_strategy</td><td>None </td></tr><tr><td> generate_all_jobs_at_once</td><td>False </td></tr><tr><td> revert_to_random_when_seemingly_exhausted</td><td>True </td></tr><tr><td> load_data_from_existing_jobs</td><td>[] </td></tr><tr><td> n_estimators_randomforest</td><td>100 </td></tr><tr><td> external_generator</td><td>None </td></tr><tr><td> username</td><td>None </td></tr><tr><td> max_failed_jobs</td><td>None </td></tr><tr><td> num_parallel_jobs</td><td>20 </td></tr><tr><td> worker_timeout</td><td>120 </td></tr><tr><td> slurm_use_srun</td><td>False </td></tr><tr><td> time</td><td></td></tr><tr><td> partition</td><td></td></tr><tr><td> reservation</td><td>None </td></tr><tr><td> force_local_execution</td><td>False </td></tr><tr><td> slurm_signal_delay_s</td><td>0 </td></tr><tr><td> nodes_per_job</td><td>1 </td></tr><tr><td> cpus_per_task</td><td>1 </td></tr><tr><td> account</td><td>None </td></tr><tr><td> gpus</td><td>0 </td></tr><tr><td> run_mode</td><td>local </td></tr><tr><td> verbose</td><td>False </td></tr><tr><td> verbose_break_run_search_table</td><td>False </td></tr><tr><td> debug</td><td>False </td></tr><tr><td> no_sleep</td><td>False </td></tr><tr><td> tests</td><td>False </td></tr><tr><td> show_worker_percentage_table_at_end</td><td>False </td></tr><tr><td> auto_exclude_defective_hosts</td><td>False </td></tr><tr><td> run_tests_that_fail_on_taurus</td><td>False </td></tr><tr><td> raise_in_eval</td><td>False </td></tr><tr><td> show_ram_every_n_seconds</td><td>False </td></tr></tbody></table>
<h1> Worker-Usage</h1>
<div class='invert_in_dark_mode' id='workerUsagePlot'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download »worker_usage.csv« as file</button>
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1745631029.7384565,20,1,5
1745631030.251835,20,1,5
1745631032.3321748,20,2,10
1745631033.7696824,20,2,10
1745631053.732653,20,1,5
1745631053.9606729,20,1,5
1745632819.3200305,20,1,5
1745632820.226595,20,1,5
1745632822.2781327,20,2,10
1745632823.684946,20,2,10
1745632843.4380887,20,1,5
1745632843.90954,20,1,5
1745633799.8312237,20,1,5
1745633800.5803423,20,1,5
1745633802.4710648,20,2,10
1745633804.149383,20,2,10
1745633825.2975914,20,1,5
1745633825.7233055,20,1,5
1745635308.5252807,20,1,5
1745635309.2046955,20,1,5
1745635310.966183,20,2,10
1745635312.001302,20,2,10
1745635330.5516355,20,1,5
1745635331.0326228,20,1,5
1745635332.0677757,20,1,5
1745635345.291404,20,0,0
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download »worker_usage.csv« as file</button>
<h1> CPU/RAM-Usage (main)</h1>
<div class='invert_in_dark_mode' id='mainWorkerCPURAM'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download »cpu_ram_usage.csv« as file</button>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1745405322,616.63671875,3.7
1745405322,610.3984375,4.4
1745405322,610.3984375,4.8
1745405322,610.3984375,5.7
1745405322,610.3984375,2.8
1745405322,610.3984375,6.5
1745405322,610.3984375,4.2
1745405610,653.46875,24.3
1745405610,653.46875,43.1
1745405610,653.46875,45.6
1745405610,653.46875,33.3
1745408006,818.2421875,43.3
1745408006,818.2421875,38.6
1745408006,818.2421875,42.1
1745408006,818.2421875,42.9
1745417325,840.90625,42.3
1745417325,840.90625,42.7
1745417325,840.90625,42.7
1745417325,840.90625,40.4
1745421455,825.00390625,38.0
1745421455,825.00390625,26.3
1745421455,825.00390625,26.7
1745421455,825.00390625,29.6
1745426041,831.5078125,35.8
1745426041,831.5078125,34.5
1745426041,831.5078125,34.9
1745426041,831.5078125,27.3
1745429796,887.16796875,37.8
1745429796,887.16796875,42.9
1745429796,887.16796875,44.1
1745429796,887.16796875,43.1
1745434288,858.71484375,42.2
1745434288,858.71484375,41.5
1745434289,858.71484375,41.8
1745434289,858.71484375,44.4
1745440130,918.01953125,42.8
1745440130,918.01953125,41.3
1745440130,918.01953125,39.5
1745440130,918.01953125,41.3
1745445950,881.796875,41.5
1745445950,881.796875,41.2
1745445950,881.796875,40.4
1745445950,881.796875,45.2
1745454703,904.125,39.6
1745454703,904.125,46.1
1745454703,904.125,46.4
1745454703,904.125,53.4
1745462976,941.1640625,42.2
1745462976,941.1640625,45.8
1745462976,941.1640625,44.4
1745462976,941.1640625,50.0
1745472540,941.63671875,42.8
1745472540,941.63671875,43.7
1745472540,941.63671875,42.9
1745472540,941.63671875,45.8
1745482602,944.7265625,42.6
1745482602,944.7265625,39.7
1745482602,944.7265625,38.7
1745482602,944.7265625,39.1
1745495116,980.67578125,38.3
1745495116,980.67578125,35.2
1745495116,980.67578125,35.1
1745495116,980.67578125,28.9
1745508038,997.12890625,35.4
1745508038,997.12890625,36.6
1745508038,997.12890625,36.8
1745508038,997.12890625,38.4
1745520787,1047.4609375,37.0
1745520787,1047.4609375,33.6
1745520787,1047.4609375,33.8
1745520787,1047.4609375,32.7
1745535031,1077.31640625,37.7
1745535031,1077.31640625,37.6
1745535031,1077.31640625,36.2
1745535031,1077.31640625,39.1
1745555600,1039.5546875,36.7
1745555600,1039.5546875,34.0
1745555600,1039.5546875,32.8
1745555600,1039.5546875,33.7
1745577859,1064.19140625,37.8
1745577859,1064.19140625,36.4
1745577859,1064.19140625,36.0
1745577859,1064.19140625,38.3
1745606657,1075.35546875,37.2
1745606657,1075.35546875,40.3
1745606657,1075.35546875,40.8
1745606657,1075.35546875,41.6
1745635346,1166.6328125,37.5
1745635346,1166.6328125,41.2
1745635346,1166.6328125,41.0
1745635346,1166.6328125,40.7
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download »cpu_ram_usage.csv« as file</button>
<h1> Parallel Plot</h1>
<div class="invert_in_dark_mode" id="parallel-plot"></div>
<h1> Scatter-2D</h1>
<div class='invert_in_dark_mode' id='plotScatter2d'></div>
<h1> Scatter-3D</h1>
<div class='invert_in_dark_mode' id='plotScatter3d'></div>
<h1> Job Status Distribution</h1>
<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
<h1> Boxplots</h1>
<div class="invert_in_dark_mode" id="plotBoxplot"></div>
<h1> Violin</h1>
<div class="invert_in_dark_mode" id="plotViolin"></div>
<h1> Histogram</h1>
<div class="invert_in_dark_mode" id="plotHistogram"></div>
<h1> Heatmap</h1>
<div class="invert_in_dark_mode" id="plotHeatmap"></div><br>
<h1>Correlation Heatmap Explanation</h1>
<p>
This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
</p>
<h2>How It Works</h2>
<p>
The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
</p>
<ul>
<li><strong>Positive correlation</strong>: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).</li>
<li><strong>Negative correlation</strong>: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).</li>
<li><strong>Zero correlation</strong>: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).</li>
</ul>
<h2>Color Scale: Yellow to Purple (Viridis)</h2>
<p>
The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
</p>
<ul>
<li><strong>Yellow (brightest)</strong>: A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.</li>
<li><strong>Green</strong>: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.</li>
<li><strong>Blue</strong>: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.</li>
<li><strong>Purple (darkest)</strong>: A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.</li>
</ul>
<h2>What the Heatmap Shows</h2>
<p>
In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
</p>
<h1> Result-Pairs</h1>
<div class="invert_in_dark_mode" id="plotResultPairs"></div>
<h1> Evolution</h1>
<div class="invert_in_dark_mode" id="plotResultEvolution"></div>
</body>
</html>
Job-Infos
