OmniOpt2

Setting	Value
Max. nr. evaluations	50359
Max. nr. evaluations (from arguments)	50000
Number random steps	20
Nr. of workers (parameter)	20
Main process memory (GB)	8
Worker memory (GB)	32
Nr. imported jobs	359
Name	Type	Lower bound	Upper bound	Values	Type	Log Scale?
recent_samples_size	int	1	5000		int	No
n_samples	int	1	5000		int	No
confidence	choice			0.25, 0.1, 0.05, 0.025, 0.01, 0.005, 0.001
feature_proportion	float	0.001	0.999		float	No
n_clusters	int	1	50		int	No
Failed	Succeeded	Running	Total
4	559	2	565
name	min/max
ACCURACY	max
RUNTIME	min
Key	Value
config_yaml	None
config_toml	None
config_json	None
num_random_steps	20
max_eval	50000
run_program	None
experiment_name	None
mem_gb	32
parameter	None
continue_previous_job	/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_NOAAWeather_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/
experiment_constraints	None
run_dir	runs
seed	None
decimalrounding	4
enforce_sequential_optimization	False
verbose_tqdm	False
model	None
gridsearch	False
occ	False
show_sixel_scatter	False
show_sixel_general	False
show_sixel_trial_index_result	False
follow	False
send_anonymized_usage_stats	False
ui_url	None
root_venv_dir	/home/s4122485
exclude	None
main_process_gb	8
pareto_front_confidence	1
max_nr_of_zero_results	10
abbreviate_job_names	False
orchestrator_file	None
checkout_to_latest_tested_version	False
live_share	False
disable_tqdm	False
workdir	False
occ_type	euclid
result_names	['RESULT=min']
minkowski_p	2
signed_weighted_euclidean_weights
generation_strategy	None
generate_all_jobs_at_once	False
revert_to_random_when_seemingly_exhausted	True
load_data_from_existing_jobs	[]
n_estimators_randomforest	100
external_generator	None
username	None
max_failed_jobs	None
num_parallel_jobs	20
worker_timeout	120
slurm_use_srun	False
time
partition
reservation	None
force_local_execution	False
slurm_signal_delay_s	0
nodes_per_job	1
cpus_per_task	1
account	None
gpus	0
run_mode	local
verbose	False
verbose_break_run_search_table	False
debug	False
no_sleep	False
tests	False
show_worker_percentage_table_at_end	False
auto_exclude_defective_hosts	False
run_tests_that_fail_on_taurus	False
raise_in_eval	False
show_ram_every_n_seconds	False
Skipped tabs:
Job-Infos
<!DOCTYPE html>
<html lang='en'>
	<head>
		<meta charset='UTF-8'>
		<meta name='viewport' content='width=device-width, initial-scale=1.0'>
		<title>Exported &raquo;s4122485/CSDDM_NOAAWeather_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1&laquo; from OmniOpt2-Share</title>
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				width: 20px;
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				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 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			}
			
			: :-webkit-scrollbar-button: vertical: end{
				height: 17px;
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			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 17px;
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			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 17px;
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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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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
			}
			
			menu[role=tablist] button{
				background: linear-gradient(180deg,#fff,#fafaf9 26%,#f0f0ea 95%,#ecebe5);
				margin-left: -1px;
				margin-right: 2px;
				border-radius: 0;
				border-color: #91a7b4;
				border-top-right-radius: 3px;
				border-top-left-radius: 3px;
				padding: 0 12px 3px
			}
			
			menu[role=tablist] button: hover{
				box-shadow: unset;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]{
				border-color: #919b9c;
				margin-right: -1px;
				border-bottom: 1px solid transparent;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]: first-of-type: before{
				content: "";
				display: block;
				position: absolute;
				z-index: -1;
				top: 100%;
				left: -1px;
				height: 2px;
				width: 0;
				border-left: 1px solid #919b9c
			}
			
			[role=tabpanel]{
				box-shadow: inset 1px 1px #fcfcfe,inset -1px -1px #fcfcfe,1px 2px 2px 0 rgba(208,206,191,.75)
			}
			
			ul.tree-view{
				-webkit-font-smoothing: auto;
				border: 1px solid #7f9db9;
				padding: 2px 5px
			}
			
			@keyframes sliding{
				0%{
					transform: translateX(-30px)
				}
			
				to{
					transform: translateX(100%)
				}
			}
			
			progress{
				box-sizing: border-box;
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				height: 14px;
				border: 1px solid #686868;
				border-radius: 4px;
				padding: 1px 2px 1px 0;
				overflow: hidden;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress,progress: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				height: 14px
			}
			
			progress[value]: :-webkit-progress-bar{
				background-color: transparent
			}
			
			progress[value]: :-webkit-progress-value{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress[value]: :-moz-progress-bar{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]): :-webkit-progress-bar{
				width: 100%;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff);
				animation: sliding 2s linear 0s infinite
			}
			
			progress: not([value]): :-webkit-progress-bar: not([value]){
				animation: sliding 2s linear 0s infinite;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]){
				position: relative
			}
			
			progress: not([value]): before{
				box-sizing: border-box;
				content: "";
				position: absolute;
				top: 0;
				left: 0;
				width: 100%;
				height: 100%;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before,progress: not([value]): before: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): after{
				box-sizing: border-box;
				content: "";
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 NOAAWeather 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 2726 n_samples 473 confidence 0.005 feature_proportion 0.9330367422104456 n_clusters 29",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 NOAAWeather 2000 HoeffdingTreeClassifier CSDDM recent_samples_size 4159 n_samples 3926 confidence 0.01 feature_proportion 0.957896660052395 n_clusters 48",
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			    ],
			    [
			        1746741727.5009074,
			        20,
			        1,
			        5
			    ],
			    [
			        1746741727.5805042,
			        20,
			        1,
			        5
			    ],
			    [
			        1746745768.4887106,
			        20,
			        1,
			        5
			    ],
			    [
			        1746745769.0985456,
			        20,
			        1,
			        5
			    ],
			    [
			        1746745770.7302911,
			        20,
			        2,
			        10
			    ],
			    [
			        1746745771.3163865,
			        20,
			        2,
			        10
			    ],
			    [
			        1746745781.3498893,
			        20,
			        1,
			        5
			    ],
			    [
			        1746745781.7930667,
			        20,
			        1,
			        5
			    ],
			    [
			        1746750117.510269,
			        20,
			        1,
			        5
			    ],
			    [
			        1746750118.3794386,
			        20,
			        1,
			        5
			    ],
			    [
			        1746750120.418814,
			        20,
			        2,
			        10
			    ],
			    [
			        1746750121.9174018,
			        20,
			        2,
			        10
			    ],
			    [
			        1746750136.0475862,
			        20,
			        1,
			        5
			    ],
			    [
			        1746750136.151664,
			        20,
			        1,
			        5
			    ],
			    [
			        1746755184.7458024,
			        20,
			        1,
			        5
			    ],
			    [
			        1746755185.372629,
			        20,
			        1,
			        5
			    ],
			    [
			        1746755187.3441534,
			        20,
			        2,
			        10
			    ],
			    [
			        1746755188.659961,
			        20,
			        2,
			        10
			    ],
			    [
			        1746755199.5512016,
			        20,
			        1,
			        5
			    ],
			    [
			        1746755199.6527991,
			        20,
			        1,
			        5
			    ],
			    [
			        1746759320.6472747,
			        20,
			        1,
			        5
			    ],
			    [
			        1746759321.2312272,
			        20,
			        1,
			        5
			    ],
			    [
			        1746759323.1469018,
			        20,
			        2,
			        10
			    ],
			    [
			        1746759324.2276564,
			        20,
			        2,
			        10
			    ],
			    [
			        1746759335.2265592,
			        20,
			        1,
			        5
			    ],
			    [
			        1746759335.303439,
			        20,
			        1,
			        5
			    ],
			    [
			        1746763250.802533,
			        20,
			        1,
			        5
			    ],
			    [
			        1746763251.1555555,
			        20,
			        1,
			        5
			    ],
			    [
			        1746763252.976147,
			        20,
			        2,
			        10
			    ],
			    [
			        1746763253.6596265,
			        20,
			        2,
			        10
			    ],
			    [
			        1746763264.8697836,
			        20,
			        1,
			        5
			    ],
			    [
			        1746763264.9391522,
			        20,
			        1,
			        5
			    ],
			    [
			        1746767489.8216183,
			        20,
			        1,
			        5
			    ],
			    [
			        1746767490.1990395,
			        20,
			        1,
			        5
			    ],
			    [
			        1746767491.917522,
			        20,
			        2,
			        10
			    ],
			    [
			        1746767492.5349884,
			        20,
			        2,
			        10
			    ],
			    [
			        1746767502.3678534,
			        20,
			        1,
			        5
			    ],
			    [
			        1746767502.8095589,
			        20,
			        1,
			        5
			    ],
			    [
			        1746771094.6373131,
			        20,
			        1,
			        5
			    ],
			    [
			        1746771095.023444,
			        20,
			        1,
			        5
			    ],
			    [
			        1746771096.4958909,
			        20,
			        2,
			        10
			    ],
			    [
			        1746771097.1339095,
			        20,
			        2,
			        10
			    ],
			    [
			        1746771106.6730556,
			        20,
			        1,
			        5
			    ],
			    [
			        1746771106.8580103,
			        20,
			        1,
			        5
			    ],
			    [
			        1746775236.6193624,
			        20,
			        1,
			        5
			    ],
			    [
			        1746775237.0194988,
			        20,
			        1,
			        5
			    ],
			    [
			        1746775238.560284,
			        20,
			        2,
			        10
			    ],
			    [
			        1746775239.067593,
			        20,
			        2,
			        10
			    ],
			    [
			        1746775249.4447358,
			        20,
			        1,
			        5
			    ],
			    [
			        1746775249.6177304,
			        20,
			        1,
			        5
			    ]
			];
			var tab_main_worker_cpu_ram_csv_json = [
			    [
			        1746192507,
			        633.76953125,
			        32.9
			    ],
			    [
			        1746192507,
			        633.76953125,
			        36.2
			    ],
			    [
			        1746192507,
			        633.76953125,
			        33.7
			    ],
			    [
			        1746192507,
			        633.76953125,
			        34.7
			    ],
			    [
			        1746192507,
			        633.76953125,
			        35.6
			    ],
			    [
			        1746192507,
			        633.76953125,
			        36.1
			    ],
			    [
			        1746192507,
			        633.76953125,
			        37
			    ],
			    [
			        1746211444,
			        814.4921875,
			        38.1
			    ],
			    [
			        1746211444,
			        814.4921875,
			        31
			    ],
			    [
			        1746211444,
			        814.4921875,
			        31.2
			    ],
			    [
			        1746211444,
			        814.4921875,
			        31.3
			    ],
			    [
			        1746229737,
			        850.1796875,
			        19
			    ],
			    [
			        1746229737,
			        850.1796875,
			        14.8
			    ],
			    [
			        1746229737,
			        850.1796875,
			        15
			    ],
			    [
			        1746229737,
			        850.1796875,
			        16.2
			    ],
			    [
			        1746281912,
			        926.44921875,
			        15.5
			    ],
			    [
			        1746281912,
			        926.44921875,
			        15.1
			    ],
			    [
			        1746281912,
			        926.44921875,
			        15.2
			    ],
			    [
			        1746281912,
			        926.44921875,
			        12.1
			    ],
			    [
			        1746339988,
			        935.5703125,
			        15.9
			    ],
			    [
			        1746339988,
			        935.5703125,
			        14.3
			    ],
			    [
			        1746339988,
			        935.5703125,
			        14.6
			    ],
			    [
			        1746339988,
			        935.5703125,
			        10.3
			    ],
			    [
			        1746389647,
			        974.265625,
			        17.1
			    ],
			    [
			        1746389647,
			        974.265625,
			        17.5
			    ],
			    [
			        1746389647,
			        974.265625,
			        17.2
			    ],
			    [
			        1746389647,
			        974.265625,
			        16.9
			    ],
			    [
			        1746443694,
			        1025.27734375,
			        17.8
			    ],
			    [
			        1746443694,
			        1025.27734375,
			        25.7
			    ],
			    [
			        1746443694,
			        1025.27734375,
			        24.9
			    ],
			    [
			        1746443694,
			        1025.27734375,
			        21.4
			    ],
			    [
			        1746515798,
			        1027.40625,
			        23.7
			    ],
			    [
			        1746515798,
			        1027.40625,
			        14.8
			    ],
			    [
			        1746515798,
			        1027.40625,
			        14.4
			    ],
			    [
			        1746515798,
			        1027.40625,
			        16.7
			    ],
			    [
			        1746596462,
			        1075.80859375,
			        16.2
			    ],
			    [
			        1746596462,
			        1075.80859375,
			        15.7
			    ],
			    [
			        1746596462,
			        1075.80859375,
			        15.6
			    ],
			    [
			        1746596462,
			        1075.80859375,
			        16.1
			    ],
			    [
			        1746685244,
			        1127.19140625,
			        17.4
			    ],
			    [
			        1746685244,
			        1127.19140625,
			        17.7
			    ],
			    [
			        1746685244,
			        1127.19140625,
			        17.6
			    ],
			    [
			        1746685244,
			        1127.19140625,
			        22
			    ],
			    [
			        1746775256,
			        1141.20703125,
			        16.6
			    ],
			    [
			        1746775256,
			        1141.20703125,
			        16.5
			    ],
			    [
			        1746775256,
			        1141.20703125,
			        16.9
			    ],
			    [
			        1746775256,
			        1141.20703125,
			        20.5
			    ]
			];
			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 = "&#8593;";
			
				downArrow.id = "down-arrow";
				downArrow.classList.add("scroll-arrow");
				downArrow.classList.add("invert_in_dark_mode");
				downArrow.innerHTML = "&#8595;";
			
				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();;
				plotExitCodesPieChart();

				colorize_table_entries();
			});
		</script>

					<h1>&nbsp;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>50359 </td></tr><tr><td> Max. nr. evaluations (from arguments)</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>32    </td></tr><tr><td> Nr. imported jobs</td><td>359   </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>Values</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></td><td>int</td><td>No         </td></tr><tr><td> n_samples</td><td>int</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> confidence</td><td>choice</td><td></td><td></td><td>0.25, 0.1, 0.05, 0.025, 0.01, 0.005, 0.001</td><td></td><td></td></tr><tr><td> feature_proportion</td><td>float</td><td>0.001</td><td>0.999</td><td></td><td>float</td><td>No         </td></tr><tr><td> n_clusters</td><td>int</td><td>1</td><td>50</td><td></td><td>int</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>4</td>
			<td>559</td>
			<td>2</td>
			<td>565</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>&nbsp;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 &raquo;results.csv&laquo; 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,n_samples,feature_proportion,n_clusters,confidence
0,0_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,8.000000000000000000000000000000,1805,1049,0.339940486490726445634180663546,38,0.025
1,1_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,4.000000000000000000000000000000,4327,4143,0.666193685077130837157710629981,25,0.25
2,2_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,6.000000000000000000000000000000,2644,1491,0.778249274721369177498786484648,2,0.005
3,3_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,3.000000000000000000000000000000,132,3399,0.231248476630076776894284762420,37,0.25
4,4_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,4.000000000000000000000000000000,893,2461,0.529093715840950662432362605614,9,0.01
5,5_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,4.000000000000000000000000000000,3366,3053,0.481096903273835752035125779003,29,0.05
6,6_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,88.000000000000000000000000000000,4816,81,0.090057989563792947840248359626,46,0.01
7,7_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,3.000000000000000000000000000000,2333,4486,0.915307191472500614182195022295,17,0.1
8,8_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,7.000000000000000000000000000000,1939,1672,0.173996782450005410547433370994,14,0.01
9,9_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,6.000000000000000000000000000000,4428,3519,0.812607054723426647235839936911,50,0.05
10,10_0,COMPLETED,Sobol,SOBOL,0.750000000000000000000000000000,8.000000000000000000000000000000,3603,869,0.740950158357620236593277240900,26,0.25
11,11_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,3.000000000000000000000000000000,1126,4020,0.256814059242606140820441851247,13,0.025
12,12_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,5.000000000000000000000000000000,363,583,0.990836506966501495696775236866,34,0.05
13,13_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,3.000000000000000000000000000000,2881,4932,0.007696779239922762159975544449,5,0.25
14,14_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,10.000000000000000000000000000000,3939,1957,0.423148508237674858545318556935,22,0.001
15,15_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,23.000000000000000000000000000000,1413,2610,0.562762409122660733906684527028,41,0.1
16,16_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,5.000000000000000000000000000000,1344,2142,0.440724125197157257094460192093,43,0.005
17,17_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,6.000000000000000000000000000000,3852,2738,0.549151879375800455740375127789,21,0.05
18,18_0,COMPLETED,Sobol,SOBOL,0.750000000000000000000000000000,10.000000000000000000000000000000,3125,401,0.879689359374344337361151247023,7,0.025
19,19_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,3.000000000000000000000000000000,588,4801,0.114863603912293915643161312801,33,0.1
20,20_0,COMPLETED,Sobol,SOBOL,0.750000000000000000000000000000,8.000000000000000000000000000000,1037,738,0.629810717847198220376014887734,11,0.1
21,21_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,5.000000000000000000000000000000,3536,3838,0.363988472025841447443639253834,27,0.01
22,22_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,5.000000000000000000000000000000,4652,1801,0.191579928034916524559605477407,48,0.05
23,23_0,COMPLETED,Sobol,SOBOL,0.719999999999999973354647408996,3.000000000000000000000000000000,2184,3704,0.799004172572866044887973657751,16,0.001
24,24_0,COMPLETED,Sobol,SOBOL,0.750000000000000000000000000000,7.000000000000000000000000000000,2421,267,0.041369166195392610696490720557,19,0.25
25,25_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,4.000000000000000000000000000000,4884,4612,0.960179395839571903081832715543,45,0.1
26,26_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,5.000000000000000000000000000000,3142,2272,0.608979062406346249858302144276,31,0.005
27,27_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,3.000000000000000000000000000000,649,2930,0.405043396545574085898522298521,8,0.001
28,28_0,COMPLETED,Sobol,SOBOL,0.719999999999999973354647408996,4.000000000000000000000000000000,201,1368,0.858127040611579960938115618774,35,0.005
29,29_0,COMPLETED,Sobol,SOBOL,0.729999999999999982236431605997,10.000000000000000000000000000000,2732,3210,0.155187270255759346415658228580,3,0.025
30,30_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,73.000000000000000000000000000000,13,5000,0.219270795778068600112575836647,19,0.005
31,31_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,35.000000000000000000000000000000,1491,3631,0.124038053309826215575562002869,18,0.005
32,32_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,48.000000000000000000000000000000,1910,116,0.472059687905347358238827837340,1,0.25
33,33_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,49.000000000000000000000000000000,1973,111,0.470779725889027111929152624725,1,0.1
34,34_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,908,5000,0.618645119673674304117128031066,20,0.005
35,35_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,2775,408,0.544323860324325781157028814050,1,0.1
36,36_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,2506,4673,0.529282231145449255649282349623,19,0.005
37,37_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,296.000000000000000000000000000000,38,4426,0.007951913665264018910017185249,17,0.005
38,38_0,FAILED,BoTorch,BOTORCH_MODULAR,,,924,1,0.384949498169853299156528692038,4,0.25
39,39_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,134.000000000000000000000000000000,499,3760,0.087951256713477754534125097052,17,0.005
40,40_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,11.000000000000000000000000000000,3001,302,0.562042644774090272008493229805,1,0.05
41,41_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,134.000000000000000000000000000000,2086,2938,0.074224520385833978042278147313,18,0.005
42,42_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,1,5000,0.703240273648240932224950938689,20,0.05
43,43_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,1342,4558,0.371921780226302067795529637806,19,0.005
44,44_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,38.000000000000000000000000000000,1088,72,0.413205590776034525912763228916,1,0.1
45,45_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,3265,4945,0.484098993324376614122428463816,19,0.005
46,46_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,203.000000000000000000000000000000,3333,4583,0.140860692033182133275914793558,19,0.005
47,47_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,1016,490,0.464792331234444300314123665885,1,0.25
48,48_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2980,1,0.617510072017478983674720893760,50,0.25
49,49_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,2759,663,0.540787171616597506229595637706,1,0.25
50,50_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,86.000000000000000000000000000000,732,5000,0.001000000000000000020816681712,22,0.005
51,51_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,3357,829,0.666740460462049266965323113254,1,0.1
52,52_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,5000,2117,0.897851100800671542145892090048,9,0.05
53,53_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,26.000000000000000000000000000000,201,4901,0.001000000000000000020816681712,19,0.05
54,54_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,264.000000000000000000000000000000,1714,4194,0.001000000000000000020816681712,18,0.005
55,55_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,35.000000000000000000000000000000,2600,57,0.495745890203924288730519265300,2,0.25
56,56_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,943,5000,0.998999999999999999111821580300,20,0.005
57,57_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,17.000000000000000000000000000000,1413,4963,0.001000000000000000020816681712,21,0.005
58,58_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,10.000000000000000000000000000000,905,319,0.508346724781483016997185586661,1,0.1
59,59_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,3610,1281,0.760305930482997105457343423041,6,0.05
60,60_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,12.000000000000000000000000000000,3228,525,0.862842978409946392837071016402,16,0.1
61,61_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,12.000000000000000000000000000000,3572,602,0.819374502881191624226175918011,15,0.025
62,62_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,11.000000000000000000000000000000,3269,757,0.750853176295872559720123717852,5,0.25
63,63_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,540,4575,0.713656717328100209662977704284,50,0.005
64,64_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,1393,1039,0.605071800332133480360141675192,18,0.05
65,65_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,377,588,0.707489994518357812047781862930,3,0.005
66,66_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,12.000000000000000000000000000000,1818,578,0.720248166707835646427326992125,2,0.005
67,67_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,898,1247,0.686005766078001677499287325190,5,0.05
68,68_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3725,4582,0.650308614818416841352188839664,1,0.25
69,69_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,4464,4417,0.681850953281741278821925789089,1,0.01
70,70_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,1971,802,0.688578059439778789041497475409,13,0.005
71,71_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,2358,617,0.768909417284201257558606812381,3,0.1
72,72_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,4555,1272,0.745130193713281596679109952674,2,0.05
73,73_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,90,4736,0.663577136094084418793670465675,50,0.01
74,74_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,52.000000000000000000000000000000,2611,1285,0.001000000000000000020816681712,6,0.001
75,75_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,228,3522,0.658006307716178073796697844955,48,0.05
76,76_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,6.000000000000000000000000000000,217,784,0.675765088398944446801408503234,12,0.025
77,77_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2882,5000,0.666850789096958940227466428041,50,0.001
78,78_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,2716,898,0.721885666943998027811346673843,35,0.25
79,79_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,23.000000000000000000000000000000,4825,393,0.725255270987470113119854886463,4,0.01
80,80_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,16.000000000000000000000000000000,3988,414,0.663736323286671092702704299882,4,0.005
81,81_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,3742,4618,0.698759549757274278647400933551,43,0.025
82,82_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,3201,797,0.648958693731959912476270346815,39,0.005
83,83_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1050,4648,0.711416699011969022592438705033,14,0.025
84,84_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,1384,769,0.646103906997748445029117192462,50,0.1
85,85_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,151,2017,0.669799651260231443394843608985,50,0.001
86,86_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,92.000000000000000000000000000000,3370,734,0.620118744816251288298758481687,42,0.001
87,87_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,14.000000000000000000000000000000,3016,270,0.793622323737459334225263773988,27,0.025
88,88_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,23.000000000000000000000000000000,3978,320,0.894744632791682370509533939185,1,0.025
89,89_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,5000,4621,0.712159711538742024039549960435,50,0.025
90,90_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,2884,5000,0.693450921314891610691688583756,1,0.025
91,91_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,2878,922,0.590683401855301770666528682341,50,0.1
92,92_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,4335,1354,0.736561648523710976732559174707,47,0.05
93,93_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,2541,769,0.668588846071901166112638748018,46,0.005
94,94_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,4224,4613,0.750902226203021716521845974057,50,0.1
95,95_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,4550,1035,0.712181271544793270678042063082,1,0.05
96,96_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2123,4784,0.661611524851310472961074538034,50,0.025
97,97_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,9.000000000000000000000000000000,4419,973,0.699568662735777557770688872552,1,0.1
98,98_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,4788,4502,0.663564923883523061221012540045,50,0.1
99,99_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,643,4435,0.643496405812430505299914784700,50,0.05
100,100_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,4957,1198,0.998999999999999999111821580300,1,0.05
101,101_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,25,4389,0.666569362562927980597748955915,50,0.025
102,102_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,54,3517,0.677503871142174807218339083192,1,0.025
103,103_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1023,4090,0.659742483343910057769221566559,1,0.05
104,104_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4738,931,0.773275501056007175115780682972,1,0.05
105,105_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,885,796,0.792397969056979567525900165492,1,0.1
106,106_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,4471,1811,0.707015312122792005666838122124,1,0.01
107,107_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,5000,4699,0.688721727564337249383186190244,50,0.1
108,108_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,147,796,0.680509839060423060708160392096,1,0.01
109,109_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2973,4571,0.314057052394787206139881163836,50,0.05
110,110_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,3253,846,0.688927920843858787591784675897,21,0.05
111,111_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,2272,794,0.001000000000000000020816681712,1,0.25
112,112_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,3553,805,0.736735184069128967720985201595,1,0.05
113,113_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,5000,4793,0.998999999999999999111821580300,50,0.25
114,114_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,4679,4724,0.918348286149616166440523556957,50,0.01
115,115_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4228,749,0.689832284684471663815941155917,39,0.05
116,116_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,5000,3467,0.657519150551500897172729764861,50,0.05
117,117_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,694,5000,0.630281618267671039923527587234,50,0.1
118,118_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,4432,832,0.780042658480544437438197746815,40,0.05
119,119_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2197,4477,0.001000000000000000020816681712,50,0.1
120,120_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,826,2297,0.681829892587176300544626883493,1,0.05
121,121_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,5000,4860,0.626343812548354139657647010608,50,0.1
122,122_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,3289,619,0.997676310220434237052700154891,47,0.05
123,123_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,4438,914,0.917564194281883960258028309909,1,0.05
124,124_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,4053,2160,0.797724139730061176933872957306,50,0.01
125,125_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,6.000000000000000000000000000000,3064,2336,0.713925111129737555160090778372,50,0.005
126,126_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,4328,4287,0.657247159691648263901697646361,50,0.025
127,127_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,164,3572,0.217149422965646154981556037455,1,0.1
128,128_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,4909,851,0.738426351598907793061243864940,41,0.05
129,129_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2052,722,0.661513666539807920763394122332,49,0.05
130,130_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,4481,1873,0.700700034441276708996326760825,1,0.05
131,131_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3358,4501,0.715671524177428186597182957485,1,0.1
132,132_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,456,4672,0.630376423132175789376674401865,50,0.25
133,133_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,13.000000000000000000000000000000,4935,866,0.656016314704904957011422084179,1,0.05
134,134_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,3288,3036,0.750109837097756360080325066519,1,0.25
135,135_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,1397,841,0.760314418883950904337609699724,1,0.1
136,136_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,4985,888,0.674094960435558387956689330167,46,0.05
137,137_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,10.000000000000000000000000000000,4877,1001,0.675311804176946584021834496525,50,0.05
138,138_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,5000,1582,0.284413723643648919114923501184,1,0.001
139,139_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4990,926,0.892431559924260042748755950015,48,0.05
140,140_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,725,4392,0.644299280083008407693512253900,1,0.01
141,141_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4.000000000000000000000000000000,2059,817,0.788030997655975062876620995667,1,0.1
142,142_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,1842,734,0.760089391038542450118598026165,50,0.1
143,143_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,5000,5000,0.669397411504050854347269705613,50,0.05
144,144_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,5000,1046,0.700583825972989404640145494341,50,0.1
145,145_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,3968,5000,0.623241431998919459545049903682,50,0.025
146,146_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,4831,882,0.842864695517178463823881884309,50,0.1
147,147_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,5.000000000000000000000000000000,2121,963,0.743404556438009067598216006445,50,0.05
148,148_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,5000,1288,0.664114440047672727196470532363,50,0.05
149,149_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,5000,1393,0.631409903254823157148223344848,50,0.05
150,150_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,913,0.776790679265886296889220830053,21,0.05
151,151_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,5000,496,0.692361530283377102357178500824,50,0.05
152,152_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3897,5000,0.270565021196211008547294341042,50,0.25
153,153_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,5000,1382,0.748313226673614217965280204226,8,0.05
154,154_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,1211,0.998999999999999999111821580300,50,0.1
155,155_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4.000000000000000000000000000000,509,5000,0.656848147269627702371508348733,50,0.05
156,156_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,14.000000000000000000000000000000,5000,607,0.998999999999999999111821580300,41,0.05
157,157_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,1005,0.256339887484753614632637663817,50,0.05
158,158_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,5000,1341,0.822066307181056665775997771561,50,0.1
159,159_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,832,0.931349408966395286846307044470,50,0.1
160,160_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,824,0.892619411307316146242385457299,50,0.05
161,161_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4969,822,0.707939050056386687259646350867,45,0.1
162,162_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,665,0.716074442090067986299573021824,50,0.1
163,163_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,985,0.638786476276400616569617341156,50,0.05
164,164_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,3.000000000000000000000000000000,2402,5000,0.998999999999999999111821580300,1,0.025
165,165_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,836,0.771547582190615588437765381968,50,0.05
166,166_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,5000,578,0.803236811665681393890281469794,35,0.1
167,167_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,2590,2291,0.621373572104775284685729275225,1,0.01
168,168_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,5000,1972,0.595929580789694712805726339866,50,0.01
169,169_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4186,983,0.660281796365938755677404969902,50,0.1
170,170_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,9.000000000000000000000000000000,5000,1040,0.797978289149529507184865906311,50,0.1
171,171_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,656,0.764843294511132976154499374388,50,0.1
172,172_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,3.000000000000000000000000000000,337,4739,0.631092825876900187509477291314,1,0.25
173,173_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,19.000000000000000000000000000000,5000,352,0.733787915838006510327318210329,50,0.05
174,174_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,14.000000000000000000000000000000,5000,520,0.849626579751364685577641466807,50,0.1
175,175_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,779,0.874070052593864499357323438744,1,0.05
176,176_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2817,4402,0.624481532219521073834300750605,50,0.025
177,177_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,14.000000000000000000000000000000,1764,523,0.998999999999999999111821580300,50,0.1
178,178_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,5000,2406,0.777539863210893855693939258344,1,0.05
179,179_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,1713,945,0.858045172303146475023538641835,50,0.1
180,180_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,5000,4414,0.647195215592056172226875787601,50,0.05
181,181_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,5000,1089,0.818019236798636639740323062142,6,0.05
182,182_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,2154,792,0.001000000000000000020816681712,50,0.05
183,183_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,511,3596,0.836515425636122467167865579540,50,0.01
184,184_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,5000,3572,0.646862158943413589895499171689,50,0.1
185,185_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,10.000000000000000000000000000000,5000,1213,0.800198158607863363478429619136,50,0.05
186,186_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,5000,1504,0.622679761809201481881359541148,50,0.1
187,187_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,5000,1561,0.769457778827045579816967801889,36,0.1
188,188_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1,4512,0.590427821077970649277233405883,50,0.1
189,189_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,5000,1158,0.911010357423044037084025603690,50,0.05
190,190_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,923,0.826304007913409743757426895172,50,0.25
191,191_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,775,0.642013435649086638967730777949,50,0.1
192,192_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,5000,1076,0.944477599189634475784771439066,5,0.1
193,193_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,4401,1291,0.821767543801023125915605760383,50,0.1
194,194_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,5000,3991,0.612354253901608136523293524078,50,0.05
195,195_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,4750,1757,0.646440134894017193190052239515,50,0.1
196,196_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,733,0.676129726435472422352290777781,50,0.05
197,197_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,904,0.998999999999999999111821580300,50,0.25
198,198_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,5000,2183,0.806336436352385721448854383198,50,0.1
199,199_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,5000,3556,0.159119853991399023973585258318,50,0.1
200,200_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,3006,708,0.986277823980979184703699047532,50,0.25
201,201_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,5000,2112,0.972194691032594593416149564291,50,0.25
202,202_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,827,0.842035573335651821302860753349,50,0.25
203,203_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,3412,616,0.857407401595982276987228942744,50,0.05
204,204_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,882,0.998999999999999999111821580300,50,0.05
205,205_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,17.000000000000000000000000000000,4942,397,0.001000000000000000020816681712,50,0.25
206,206_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,3978,1697,0.921504049566188698783264499070,50,0.25
207,207_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,5000,2762,0.663331453999214226691094609123,50,0.05
208,208_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,5000,1536,0.835854396739428628926305009372,50,0.25
209,209_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,5000,1525,0.830652032824637731600603274273,50,0.05
210,210_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,970,0.899957407564291878010465097759,50,0.25
211,211_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,4666,1031,0.920858894663071914088448011171,50,0.25
212,212_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,568.000000000000000000000000000000,5000,4857,0.001000000000000000020816681712,50,0.005
213,213_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,3188,654,0.500367040968610843343356009427,50,0.005
214,214_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,16.000000000000000000000000000000,4499,463,0.561293445513244337874425582413,50,0.25
215,215_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,2511,875,0.812985040532476332941769214813,50,0.25
216,216_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,10.000000000000000000000000000000,4361,1049,0.537183023792320635259045502607,50,0.1
217,217_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,4702,1161,0.458377362694985912572320785330,50,0.1
218,218_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,2315,906,0.838658046371677845520764549292,50,0.25
219,219_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,1215,936,0.087665481922601304343167782918,50,0.1
220,220_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,5.000000000000000000000000000000,2090,720,0.899662328533544664033172466588,50,0.05
221,221_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,1823,655,0.835417828047011479242200948647,50,0.05
222,222_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,1333,987,0.405954847641972593752512921128,50,0.005
223,223_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2946,3770,0.701458395658111522052990949305,3,0.01
224,224_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,9.000000000000000000000000000000,4364,1069,0.875528338857528343197600406711,50,0.25
225,225_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,3.000000000000000000000000000000,410,5000,0.445042486964761674350654629961,50,0.05
226,226_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,2672,1242,0.814769500237110366747117495834,50,0.1
227,227_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,4370,1253,0.261584943433505467957900236797,50,0.05
228,228_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,13.000000000000000000000000000000,1325,640,0.860235888265295622900907801522,50,0.25
229,229_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,4115,3745,0.462731729668264424315538008159,50,0.1
230,230_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2426,4434,0.822231936788205164390319623635,50,0.05
231,231_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,2923,1566,0.808083542776833141374481783714,50,0.05
232,232_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,171.000000000000000000000000000000,1204,853,0.057033397644436607809570460859,50,0.005
233,233_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,3154,766,0.604720862209332188363930526975,50,0.005
234,234_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,4920,847,0.001000000000000000020816681712,50,0.25
235,235_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,3622,837,0.998999999999999999111821580300,50,0.005
236,236_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1034,1547,0.515491678235619699144365313259,50,0.1
237,237_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,116.000000000000000000000000000000,2917,188,0.436976784413402541407123180761,50,0.005
238,238_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,5000,2877,0.223031673536557284442949367076,50,0.1
239,239_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,3936,1281,0.784884697448535617603226910433,50,0.25
240,240_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,5000,3892,0.399726376806832983668016368028,50,0.05
241,241_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,3946,912,0.799004266632274640080879635207,50,0.005
242,242_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,1435,4584,0.396730239520824035093227166726,50,0.1
243,243_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,38.000000000000000000000000000000,2878,1061,0.088091128285536945963229982226,50,0.025
244,244_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,4775,851,0.769029056891159967790372320451,50,0.005
245,245_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1648,5000,0.382347671699859281702060798125,50,0.005
246,246_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,27.000000000000000000000000000000,1674,1023,0.007279073960341602735069077568,50,0.05
247,247_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,601,4152,0.940941904114748650655997153081,50,0.25
248,248_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2208,692,0.993504507721459595437352163572,50,0.1
249,249_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,2830,950,0.916754204934457916920109710190,50,0.005
250,250_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,1604,790,0.866002937705283026836866611120,50,0.005
251,251_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,1379,3735,0.183094995963103607250488380487,50,0.1
252,252_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,888,0.615019083116143394640573660581,50,0.25
253,253_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,1844,3492,0.854610259284317108630091297528,50,0.025
254,254_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,544.000000000000000000000000000000,5000,1458,0.142656131155792287312777943953,50,0.001
255,255_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,2183,723,0.857488384267570458163731927925,50,0.01
256,256_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,3217,648,0.439370777468963524814427046294,1,0.001
257,257_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,704,0.581180291923760417027722269268,1,0.005
258,258_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,796,0.951871927095502168292284750351,50,0.005
259,259_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,13.000000000000000000000000000000,5000,692,0.907934527353332909704874964518,50,0.005
260,260_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,738,0.987861307248344755471691769344,50,0.005
261,261_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,40.000000000000000000000000000000,5000,725,0.998999999999999999111821580300,50,0.005
262,262_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,746,0.895211344271998776811471998371,50,0.005
263,263_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,737,0.998999999999999999111821580300,50,0.25
264,264_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,720,0.880138351603788726684740595374,50,0.005
265,265_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,755,0.998999999999999999111821580300,36,0.25
266,266_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,632,0.943986265964539050798975949874,50,0.005
267,267_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,9.000000000000000000000000000000,5000,819,0.909220590605802403416646484402,50,0.005
268,268_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,748,0.801976890897353911213940591551,27,0.005
269,269_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,4404,667,0.865411403676152768404961079796,50,0.005
270,270_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,841,0.988403246262388290865885664971,50,0.005
271,271_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,780,0.916604133210698446276865070104,12,0.25
272,272_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,844,0.931679388847070133472527686536,50,0.25
273,273_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,717,0.998999999999999999111821580300,50,0.25
274,274_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,770,0.910516806937320732906471221213,32,0.005
275,275_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,3452,713,0.823810431564999001707860770694,50,0.005
276,276_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,13.000000000000000000000000000000,5000,549,0.869997908069080061466138431570,50,0.005
277,277_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,760,0.998999999999999999111821580300,50,0.005
278,278_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,4686,765,0.869462293969304966800848433195,50,0.005
279,279_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,828,0.888175162882933189045786548377,50,0.005
280,280_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,5000,714,0.998999999999999999111821580300,50,0.005
281,281_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,837,0.998999999999999999111821580300,50,0.005
282,282_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,747,0.932075858778956267691739867587,50,0.005
283,283_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,737,0.968974787912714297100080784730,50,0.25
284,284_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,898,0.980765352781194921227836402977,50,0.005
285,285_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,22.000000000000000000000000000000,5000,362,0.939541657729270007770594475005,50,0.005
286,286_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,9.000000000000000000000000000000,4248,870,0.930612330460161674139385468152,25,0.25
287,287_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,3529,631,0.998999999999999999111821580300,50,0.005
288,288_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,3875,604,0.957409071627942309667957943020,50,0.25
289,289_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,5000,656,0.998999999999999999111821580300,50,0.005
290,290_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,15.000000000000000000000000000000,5000,675,0.970054755969665283288350110524,50,0.005
291,291_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4157,756,0.884913443187803072653707658901,50,0.005
292,292_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,2504,615,0.932195351793931314965391266014,50,0.005
293,293_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,5000,646,0.998999999999999999111821580300,49,0.005
294,294_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,10.000000000000000000000000000000,5000,865,0.919467866073905404356025883317,50,0.005
295,295_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,724,0.907425653420207423138776903215,50,0.25
296,296_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,13.000000000000000000000000000000,5000,645,0.859199226240712210511674129521,50,0.005
297,297_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,19.000000000000000000000000000000,5000,703,0.861960452199340809720240486058,50,0.005
298,298_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,701,0.781873657817306666473200493783,26,0.005
299,299_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,13.000000000000000000000000000000,5000,541,0.998999999999999999111821580300,50,0.005
300,300_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,11.000000000000000000000000000000,5000,606,0.959829931656139390128146260395,50,0.005
301,301_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,4062,576,0.998999999999999999111821580300,50,0.25
302,302_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,16.000000000000000000000000000000,5000,659,0.998999999999999999111821580300,50,0.05
303,303_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,13.000000000000000000000000000000,4473,704,0.930791750735157963347887744021,50,0.005
304,304_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,12.000000000000000000000000000000,5000,675,0.998999999999999999111821580300,50,0.25
305,305_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,2416,459,0.783338814304556652068356470409,50,0.005
306,306_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,5000,1476,0.937508647373535453084514301736,25,0.005
307,307_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,4801,559,0.892790183073988496964545902301,50,0.005
308,308_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,703,0.072914891408173851394813880233,50,0.25
309,309_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,709,0.907169671058133952890045748063,50,0.25
310,310_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,770,0.852964851477177932181916730769,50,0.005
311,311_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,4704,707,0.998999999999999999111821580300,50,0.005
312,312_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,714,0.745136161393588181134362002922,50,0.25
313,313_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,719,0.947298559957085672955656718841,50,0.25
314,314_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,726,0.969052035749555895627338486520,50,0.005
315,315_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4648,781,0.883495540827234471237261459464,50,0.005
316,316_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,719,0.943722616589075968818178807851,50,0.005
317,317_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,17.000000000000000000000000000000,5000,757,0.902848980120487420997221761354,44,0.005
318,318_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,767,0.001000000000000000020816681712,50,0.25
319,319_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,13.000000000000000000000000000000,5000,631,0.929018237472571839496993106877,50,0.25
320,320_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,708,0.200056991286463259349659438158,50,0.25
321,321_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,14.000000000000000000000000000000,4889,641,0.890314051486438384763744124939,50,0.005
322,322_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,5000,685,0.001000000000000000020816681712,50,0.05
323,323_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,5000,743,0.808969820473308676156420915504,26,0.25
324,324_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,771,0.960791353067550479849501243734,50,0.005
325,325_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,754,0.985908224949913147838742588647,50,0.25
326,326_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,734,0.689620902793175560852034777781,50,0.25
327,327_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,805,0.174531907063454172490679638940,50,0.25
328,328_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,713,0.859809319593180854113256827986,50,0.25
329,329_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,4644,649,0.908318378104963963792783943063,50,0.005
330,330_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,4681,668,0.003608756039881771786326236651,27,0.25
331,331_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,11.000000000000000000000000000000,5000,670,0.998999999999999999111821580300,50,0.25
332,332_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,711,0.930503788929153308195907357003,50,0.25
333,333_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,797,0.417151724384731747985455285743,50,0.25
334,334_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,2775,551,0.119302854482368617117238329683,50,0.25
335,335_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,28.000000000000000000000000000000,5000,796,0.834273494191502318351183475897,50,0.005
336,336_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,742,0.260439533231550834901923963116,50,0.25
337,337_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,843,0.252087363563203492589082088671,50,0.25
338,338_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,16.000000000000000000000000000000,4133,623,0.188274234648659222202127239143,50,0.25
339,339_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,5000,747,0.756910806980752193240391534346,50,0.005
340,340_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,18.000000000000000000000000000000,5000,513,0.216254604216242901637556883543,50,0.25
341,341_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,15.000000000000000000000000000000,5000,670,0.853155300976478736529884372430,50,0.005
342,342_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,723,0.374560974750140773803508409401,50,0.05
343,343_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,757,0.842168634629018031390046417073,50,0.005
344,344_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,5000,749,0.001000000000000000020816681712,50,0.05
345,345_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,869,0.146705391133078705268033559150,50,0.25
346,346_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,4599,769,0.001000000000000000020816681712,50,0.25
347,347_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,737,0.417955697099704759356342265164,50,0.05
348,348_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,42.000000000000000000000000000000,1609,312,0.598298353638116564567894783977,50,0.005
349,349_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,15.000000000000000000000000000000,5000,675,0.001000000000000000020816681712,50,0.25
350,350_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,13.000000000000000000000000000000,5000,814,0.313178382279871436733031941912,50,0.05
351,351_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,2842,802,0.998999999999999999111821580300,50,0.005
352,352_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,13.000000000000000000000000000000,5000,819,0.998999999999999999111821580300,50,0.25
353,353_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,16.000000000000000000000000000000,4358,695,0.303965675168486881840834712420,50,0.25
354,354_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,726,0.001000000000000000020816681712,50,0.1
355,355_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,12.000000000000000000000000000000,5000,935,0.779720754821281780699848695804,50,0.005
356,356_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,5000,707,0.335713031697496944172343091850,50,0.1
357,357_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,4019,745,0.022488389315619861097417242490,50,0.25
358,358_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,14.000000000000000000000000000000,5000,729,0.539459132334821456211670920311,50,0.25
359,359_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,5000,735,0.801301212531214557266423526016,50,0.005
360,360_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,861,0.277784621025934763682840866750,50,0.05
361,361_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,706,0.715097582393546482570911848597,19,0.005
362,362_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,695,0.064599628371728237685722717742,30,0.25
363,363_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,800,0.135138516023326465953502406592,50,0.25
364,364_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,2951,785,0.006812174622822167804891968501,50,0.25
365,365_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,710,0.140241304925628168520645999706,50,0.25
366,366_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,601,0.057605731580224826815506133926,50,0.25
367,367_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,796,0.081379979302275751162909500636,50,0.25
368,368_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,9.000000000000000000000000000000,3147,608,0.001000000000000000020816681712,4,0.25
369,369_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,5000,953,0.120898662207141072144622739870,30,0.05
370,370_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,3751,864,0.204932297019751130662257310178,50,0.05
371,371_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,4356,965,0.123910581456199916927651827336,50,0.05
372,372_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,5000,721,0.258537985273254056206582163213,50,0.05
373,373_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,823,0.001000000000000000020816681712,50,0.25
374,374_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4804,877,0.001000000000000000020816681712,50,0.05
375,375_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,18.000000000000000000000000000000,5000,447,0.530074836699928275685067546874,1,0.005
376,376_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,817,0.053661266206456607885666443281,50,0.25
377,377_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,4253,669,0.066967007570730485710441826086,50,0.25
378,378_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,744,0.088282576773994009267099158933,50,0.25
379,379_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,731,0.041277755690881011430004576823,50,0.25
380,380_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,38.000000000000000000000000000000,1979,749,0.237613938940244157072001485176,17,0.005
381,381_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,5000,4071,0.998999999999999999111821580300,50,0.025
382,382_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,757,0.001000000000000000020816681712,44,0.05
383,383_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,5000,690,0.001000000000000000020816681712,50,0.1
384,384_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,3187,615,0.743650807661401347381513460277,50,0.005
385,385_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,13.000000000000000000000000000000,5000,818,0.001000000000000000020816681712,50,0.05
386,386_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,5000,684,0.085998559415221081936309133198,50,0.25
387,387_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,889,0.045499796865145845925493262030,50,0.1
388,388_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,4761,723,0.001000000000000000020816681712,50,0.25
389,389_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,12.000000000000000000000000000000,4206,679,0.001000000000000000020816681712,29,0.25
390,390_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,9.000000000000000000000000000000,4793,819,0.010310073992859688021828112880,50,0.25
391,391_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,5000,716,0.001000000000000000020816681712,50,0.25
392,392_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,11.000000000000000000000000000000,5000,702,0.411911582466322978568484813877,50,0.05
393,393_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,13.000000000000000000000000000000,4677,611,0.437040267382312164201607629366,50,0.05
394,394_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,745,0.819812912817189820557928214839,50,0.005
395,395_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,13.000000000000000000000000000000,5000,750,0.093431093638057127748197672190,50,0.05
396,396_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,12.000000000000000000000000000000,5000,667,0.111757666716636061554623893244,50,0.1
397,397_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,756,0.001000000000000000020816681712,34,0.25
398,398_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,5000,790,0.060702934149730984614290463242,50,0.1
399,399_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,899,0.065631849025169483602404341127,50,0.25
400,400_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,5000,786,0.707019820963124878687722230097,50,0.005
401,401_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4975,787,0.125993729321409009269672196751,50,0.25
402,402_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2164,972,0.377018672168950796930175783928,17,0.005
403,403_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,16.000000000000000000000000000000,1,367,0.443950553936765135443209828736,22,0.005
404,404_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,37.000000000000000000000000000000,4549,1091,0.266605180408814645964810097212,42,0.005
405,405_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3259,3570,0.388762796914336794529276630783,11,0.025
406,406_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,16.000000000000000000000000000000,3456,1833,0.490563952216490517521663150546,1,0.001
407,407_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,3680,1460,0.998999999999999999111821580300,50,0.005
408,408_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,5000,1904,0.416624710521824925812950368709,1,0.25
409,409_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,4407,975,0.392436323176736767681660467133,32,0.005
410,410_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,1121,671,0.193855410205254985456235772290,50,0.25
411,411_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,1519,1581,0.559603380026482244424812506622,38,0.005
412,412_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,9.000000000000000000000000000000,3854,736,0.434256406249019288878798761289,23,0.25
413,413_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,1272,649,0.001000000000000000020816681712,23,0.25
414,414_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,4.000000000000000000000000000000,2021,1334,0.526907171135147400775622372748,15,0.25
415,415_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,3825,2242,0.445621835412223665784381410049,18,0.05
416,416_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,93.000000000000000000000000000000,4259,680,0.176080426867661649081853170173,50,0.005
417,417_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,2683,1113,0.998999999999999999111821580300,42,0.25
418,418_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1941,3529,0.428109240930045764628175675170,33,0.01
419,419_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,11.000000000000000000000000000000,1649,633,0.001000000000000000020816681712,50,0.25
420,420_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,1604,1894,0.604697239004147735208505309856,21,0.01
421,421_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1,2556,0.533712194304054921012436807359,34,0.001
422,422_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,4124,2248,0.453668925593781469096654745954,16,0.001
423,423_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,14.000000000000000000000000000000,5000,1394,0.477625107671685811272510591152,23,0.005
424,424_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1604,1834,0.392083879201792273594406879056,1,0.05
425,425_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,14.000000000000000000000000000000,4922,1857,0.412608852917262680648491368629,1,0.001
426,426_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,5000,1512,0.001000000000000000020816681712,29,0.25
427,427_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1852,2082,0.506919170275711761242121156101,35,0.001
428,428_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,4918,1621,0.356003870917465103929089309531,26,0.05
429,429_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,2666,565,0.018428485618589250660814826688,27,0.05
430,430_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,903,607,0.998999999999999999111821580300,12,0.025
431,431_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,213,508,0.525410021387004322335201322858,4,0.1
432,432_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1,464,0.531365272759059426022076877416,1,0.025
433,433_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,998,909,0.544296568939507174889058660483,39,0.005
434,434_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,15.000000000000000000000000000000,3697,757,0.477459507819400774675244747414,19,0.005
435,435_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,3825,1451,0.386401471287374287388871607618,1,0.05
436,436_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,4474,3407,0.794937912960462567113495424564,22,0.1
437,437_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,6.000000000000000000000000000000,4289,3083,0.404716077364522863746287839604,50,0.05
438,438_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,2677,1183,0.998999999999999999111821580300,31,0.005
439,439_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,16.000000000000000000000000000000,1707,321,0.001000000000000000020816681712,5,0.25
440,440_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4466,810,0.964148328783408281594802247128,4,0.005
441,441_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,4668,1864,0.732192229455304377516711156204,31,0.05
442,442_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,5000,3229,0.314176100647539646715244998632,24,0.05
443,443_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,2957,1855,0.705992859325076937970777635201,14,0.05
444,444_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,4637,3520,0.492926059613003342274595297567,32,0.1
445,445_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1675,2116,0.751948222366103702363204774883,29,0.005
446,446_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3980,4537,0.750141835777250132188953557488,38,0.001
447,447_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,1126,682,0.441920718132653267407050634574,1,0.005
448,448_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,1852,3528,0.426818809435887069891890632789,21,0.005
449,449_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,2726,473,0.933036742210445635414828302601,29,0.005
450,450_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,4159,3926,0.957896660052395043649653416651,48,0.01
451,451_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,1667,3286,0.596525254643563651590909557854,24,0.025
452,452_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,3881,1711,0.284648593683260175968285921044,1,0.25
453,453_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,3474,2176,0.621091782895955124566000904451,35,0.001
454,454_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,73.000000000000000000000000000000,1890,2094,0.165851593999197077788920751118,12,0.001
455,455_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3988,4696,0.225230781022691950443714858920,17,0.1
456,456_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,135,3235,0.615624436653656181839266992029,19,0.001
457,457_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,909,4500,0.739751425343020185820819278888,35,0.001
458,458_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,3779,1900,0.722315838152073563804833611357,16,0.005
459,459_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,295,3057,0.454488982973220378980272471381,1,0.025
460,460_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,5000,2491,0.892151721187094515208571010589,30,0.05
461,461_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,1130,970,0.214048626504335010034552055913,1,0.25
462,462_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,5000,4501,0.955702682845724682536570071534,8,0.05
463,463_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,858,801,0.998999999999999999111821580300,34,0.25
464,464_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,4410,5000,0.894940669526202325911867774266,16,0.05
465,465_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,3835,2279,0.013321466062740212887849367007,19,0.25
466,466_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1707,5000,0.281682526308101588430332640201,10,0.1
467,467_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,5000,2455,0.176329281544734622899639475690,1,0.05
468,468_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1,0.985616855642394096292946414906,20,0.001
469,469_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,4059,1558,0.491517322466783090906261577402,50,0.005
470,470_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1,0.972156599630160878078299901972,22,0.001
471,471_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,1949,3477,0.293145461709787891191325570617,14,0.01
472,472_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,3594,1331,0.525545605576692942406680231215,30,0.05
473,473_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,4537,3580,0.239005745928803026156828082094,33,0.1
474,474_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,3726,2394,0.217333794128108603871396553586,12,0.05
475,475_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,1903,3503,0.298224772674392180071833990951,15,0.005
476,476_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,1489,4763,0.956895337138477075633602453308,49,0.001
477,477_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,1099,953,0.486079435455599895288258949222,8,0.25
478,478_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,285.000000000000000000000000000000,5000,1226,0.337523844485550339467039293595,50,0.001
479,479_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1669,5000,0.283785604556700821188286454344,8,0.005
480,480_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,326,1164,0.389718666337045327452415222069,42,0.25
481,481_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,4503,1025,0.414506412437835203288472030181,1,0.05
482,482_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,52.000000000000000000000000000000,3025,3940,0.001000000000000000020816681712,1,0.01
483,483_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3382,4335,0.939200007019728166923755452444,35,0.001
484,484_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,3507,1362,0.885429064462801673762726295536,20,0.005
485,485_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,6.000000000000000000000000000000,2576,1919,0.548133703380192960352701447846,42,0.05
486,486_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,8.000000000000000000000000000000,3684,1555,0.554366818838050945394968493929,32,0.005
487,487_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,820,4531,0.520613283537056825700517492805,30,0.1
488,488_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1255,1947,0.600642285926474839286015594553,50,0.025
489,489_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,19.000000000000000000000000000000,3619,2223,0.483294359148543961612887187584,30,0.001
490,490_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,5000,2318,0.243665708426591465229904542866,23,0.25
491,491_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,1016,1359,0.915879732816389124927525244857,10,0.25
492,492_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1750,3841,0.736248499394575040000177068578,46,0.05
493,493_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,1813,3497,0.512147687495143388858309663192,7,0.01
494,494_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,3034,3888,0.694701270667978598716274518665,50,0.001
495,495_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,10.000000000000000000000000000000,2820,613,0.204892334887466359694130346725,1,0.001
496,496_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,3.000000000000000000000000000000,2002,4603,0.776548526719723630762359789514,47,0.001
497,497_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,3787,3071,0.533145226884063960781645619136,1,0.001
498,498_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,1614,812,0.485825780208454904851578248781,35,0.25
499,499_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1129,2030,0.001000000000000000020816681712,1,0.25
500,500_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1289,1567,0.450650269685266946506629892610,26,0.25
501,501_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,1474,1765,0.823468982344020217212232637394,9,0.05
502,502_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,908,655,0.635110253172258887310874797549,1,0.025
503,503_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1596,4834,0.860052668092869954108437013929,17,0.001
504,504_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,3453,1753,0.626199565018022985540824265627,30,0.001
505,505_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,3569,968,0.987116622139282418046946077084,50,0.05
506,506_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,22.000000000000000000000000000000,1594,1913,0.652835140135089475599272645923,45,0.001
507,507_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,1864,3548,0.297428805478562596764646741576,44,0.005
508,508_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3857,3435,0.732698525036588610426235845807,32,0.01
509,509_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,1019,3408,0.491461079843373505049441973824,1,0.001
510,510_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,4820,3511,0.839405679484290123681944351119,34,0.01
511,511_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1002,3341,0.545441437833131703705191739573,24,0.001
512,512_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,6.000000000000000000000000000000,2935,1626,0.818123348781825354691932261630,14,0.05
513,513_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,7.000000000000000000000000000000,2082,827,0.482785993263006418807492536871,35,0.005
514,514_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,1884,3501,0.849848155998508714148442777514,19,0.01
515,515_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2808,2823,0.794897990920041874751689192635,3,0.001
516,516_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,872,848,0.895818505932466813135306438198,18,0.25
517,517_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,534,3511,0.400916804581421704067878408750,25,0.1
518,518_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,897,2087,0.192696101797181884585086208972,24,0.1
519,519_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1063,3470,0.919587576921961691311935283011,46,0.001
520,520_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,2680,532,0.001000000000000000020816681712,50,0.25
521,521_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,3946,3466,0.267346565172076500171982615939,41,0.1
522,522_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,1890,3257,0.663641781455691859292755907518,5,0.25
523,523_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2513,2690,0.828872663610195736794139520498,13,0.01
524,524_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,1480,1464,0.377270533359544024687437513421,7,0.005
525,525_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,4737,3677,0.875177980277005773679377398366,10,0.01
526,526_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,907,831,0.404764510576581637568693849971,2,0.005
527,527_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,1638,1993,0.560445980034962043525581520953,34,0.005
528,528_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,3257,878,0.379116818048832571186324003065,1,0.05
529,529_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,4.000000000000000000000000000000,3836,3429,0.911602838580895524778213712125,16,0.01
530,530_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,3020,1564,0.537465239667204941476086332841,50,0.25
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3940,4205,0.925708819867112064905256829661,24,0.05
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,970,3057,0.648732499621442415538297154853,2,0.001
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,127.000000000000000000000000000000,4381,65,0.540734928256417890501950296311,2,0.25
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,886,593,0.790713968932922228738391368097,4,0.25
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,707,1896,0.486362022039473651524588149186,50,0.25
536,536_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,2635,456,0.749286376991949998327413595689,3,0.01
537,537_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,17.000000000000000000000000000000,1965,685,0.115404995023142220578193928304,27,0.1
538,538_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,1577,751,0.176380466410206548921735247859,28,0.05
539,539_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,2771,609,0.620562632829450233629131616908,50,0.01
540,540_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,3869,2289,0.773526082604999332126283206890,17,0.05
541,541_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,2776,3390,0.711166598446386855059131448797,22,0.01
542,542_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,7.000000000000000000000000000000,2887,753,0.938563450648668418097031462821,38,0.25
543,543_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,3305,4797,0.883073224903898057469575633149,41,0.001
544,544_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,1358,1854,0.465360421294270354408695311577,50,0.005
545,545_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,6.000000000000000000000000000000,1483,1817,0.466616326340494602664676904169,50,0.01
546,546_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,3387,1983,0.553581699543684857545144950564,24,0.001
547,547_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1006,3914,0.944358813587900636221661443415,35,0.1
548,548_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,396,2208,0.001000000000000000020816681712,1,0.25
549,549_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,3754,2406,0.998142100795950448777205110673,37,0.05
550,550_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,9.000000000000000000000000000000,3912,1239,0.972862857112115841928812187689,27,0.05
551,551_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,68.000000000000000000000000000000,627,3074,0.051217718722649914486755307053,9,0.01
552,552_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,23.000000000000000000000000000000,4403,836,0.518409014360055153680661987892,44,0.005
553,553_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1,3032,0.716585185876548957928378058568,11,0.025
554,554_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,10.000000000000000000000000000000,1590,762,0.001000000000000000020816681712,1,0.25
555,555_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,298,2235,0.459025255893326267209175739481,50,0.001
556,556_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,5.000000000000000000000000000000,3328,1934,0.579388030947756704769346924877,50,0.005
557,557_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,7.000000000000000000000000000000,1778,1952,0.792004972370447424268036229478,2,0.01
558,558_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,5.000000000000000000000000000000,4180,4773,0.455494307325340130887525447179,26,0.025
559,559_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,6.000000000000000000000000000000,1032,946,0.520349909020738188303312199423,50,0.025
560,560_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,1931,3287,0.468515413684634507429649374899,1,0.25
561,561_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.750000000000000000000000000000,8.000000000000000000000000000000,1630,780,0.998999999999999999111821580300,38,0.025
562,562_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,4.000000000000000000000000000000,302,1842,0.140332346920781780852394149406,5,0.25
563,563_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,160.000000000000000000000000000000,4755,3343,0.302446737387545683262146667403,40,0.001
564,564_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,3898,2390,0.998999999999999999111821580300,41,0.001
</pre>
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			<h1>&nbsp;Errors</h1>
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<pre id='simple_pre_tab_tab_errors'><span style="background-color: black; color: white">
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_NOAAWeather_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4950223/4950223_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_NOAAWeather_HoeffdingTreeClassifier_ACCURACY-RUNTIME/2/single_runs/4950596/4950596_0_log.err not found

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			<h1>&nbsp;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>32                                                                                                                               </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/CSDDM_NOAAWeather_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/ </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>[&#039;RESULT=min&#039;]                                                                                                                   </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>&nbsp;Worker-Usage</h1>
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<pre id="pre_tab_worker_usage">1746192507.224396,20,0,0
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1746755187.3441534,20,2,10
1746755188.659961,20,2,10
1746755199.5512016,20,1,5
1746755199.6527991,20,1,5
1746759320.6472747,20,1,5
1746759321.2312272,20,1,5
1746759323.1469018,20,2,10
1746759324.2276564,20,2,10
1746759335.2265592,20,1,5
1746759335.303439,20,1,5
1746763250.802533,20,1,5
1746763251.1555555,20,1,5
1746763252.976147,20,2,10
1746763253.6596265,20,2,10
1746763264.8697836,20,1,5
1746763264.9391522,20,1,5
1746767489.8216183,20,1,5
1746767490.1990395,20,1,5
1746767491.917522,20,2,10
1746767492.5349884,20,2,10
1746767502.3678534,20,1,5
1746767502.8095589,20,1,5
1746771094.6373131,20,1,5
1746771095.023444,20,1,5
1746771096.4958909,20,2,10
1746771097.1339095,20,2,10
1746771106.6730556,20,1,5
1746771106.8580103,20,1,5
1746775236.6193624,20,1,5
1746775237.0194988,20,1,5
1746775238.560284,20,2,10
1746775239.067593,20,2,10
1746775249.4447358,20,1,5
1746775249.6177304,20,1,5
</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 &raquo;worker_usage.csv&laquo; as file</button>
			
			<h1>&nbsp;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 &raquo;cpu_ram_usage.csv&laquo; as file</button>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1746192507,633.76953125,32.9
1746192507,633.76953125,36.2
1746192507,633.76953125,33.7
1746192507,633.76953125,34.7
1746192507,633.76953125,35.6
1746192507,633.76953125,36.1
1746192507,633.76953125,37.0
1746211444,814.4921875,38.1
1746211444,814.4921875,31.0
1746211444,814.4921875,31.2
1746211444,814.4921875,31.3
1746229737,850.1796875,19.0
1746229737,850.1796875,14.8
1746229737,850.1796875,15.0
1746229737,850.1796875,16.2
1746281912,926.44921875,15.5
1746281912,926.44921875,15.1
1746281912,926.44921875,15.2
1746281912,926.44921875,12.1
1746339988,935.5703125,15.9
1746339988,935.5703125,14.3
1746339988,935.5703125,14.6
1746339988,935.5703125,10.3
1746389647,974.265625,17.1
1746389647,974.265625,17.5
1746389647,974.265625,17.2
1746389647,974.265625,16.9
1746443694,1025.27734375,17.8
1746443694,1025.27734375,25.7
1746443694,1025.27734375,24.9
1746443694,1025.27734375,21.4
1746515798,1027.40625,23.7
1746515798,1027.40625,14.8
1746515798,1027.40625,14.4
1746515798,1027.40625,16.7
1746596462,1075.80859375,16.2
1746596462,1075.80859375,15.7
1746596462,1075.80859375,15.6
1746596462,1075.80859375,16.1
1746685244,1127.19140625,17.4
1746685244,1127.19140625,17.7
1746685244,1127.19140625,17.6
1746685244,1127.19140625,22.0
1746775256,1141.20703125,16.6
1746775256,1141.20703125,16.5
1746775256,1141.20703125,16.9
1746775256,1141.20703125,20.5
</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 &raquo;cpu_ram_usage.csv&laquo; as file</button>
			
			<h1>&nbsp;Parallel Plot</h1>
			<div class="invert_in_dark_mode" id="parallel-plot"></div>
			<h1>&nbsp;Scatter-2D</h1>
			<div class='invert_in_dark_mode' id='plotScatter2d'></div>
			<h1>&nbsp;Scatter-3D</h1>
			<div class='invert_in_dark_mode' id='plotScatter3d'></div>
			<h1>&nbsp;Job Status Distribution</h1>
			<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
			<h1>&nbsp;Boxplots</h1>
			<div class="invert_in_dark_mode" id="plotBoxplot"></div>
			<h1>&nbsp;Violin</h1>
			<div class="invert_in_dark_mode" id="plotViolin"></div>
			<h1>&nbsp;Histogram</h1>
			<div class="invert_in_dark_mode" id="plotHistogram"></div>
			<h1>&nbsp;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>&nbsp;Result-Pairs</h1>
			<div class="invert_in_dark_mode" id="plotResultPairs"></div>
			<h1>&nbsp;Evolution</h1>
			<div class="invert_in_dark_mode" id="plotResultEvolution"></div>
			<h1>&nbsp;Exit-Codes</h1>
			<div class="invert_in_dark_mode" id="plotExitCodesPieChart"></div>
	</body>
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