OmniOpt2

Setting	Value
Max. nr. evaluations	50398
Max. nr. evaluations (from arguments)	50000
Number random steps	20
Nr. of workers (parameter)	20
Main process memory (GB)	8
Worker memory (GB)	1
Nr. imported jobs	398
Name	Type	Lower bound	Upper bound	Type	Log Scale?
recent_samples_size	int	1	5000	int	No
n_samples	int	1	5000	int	No
const	float	0.001	10	float	No
max_depth	int	1	20	int	No
threshold	float	0.001	0.999	float	No
Failed	Succeeded	Running	Total
136	627	66	829
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	1
parameter	None
continue_previous_job	/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/
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/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/6&laquo; from OmniOpt2-Share</title>
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				border-radius: 0;
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				padding: 2px;
				color: white;
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				position: relative;
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			.copy-container:hover {
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				color: white !important;
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				padding: 0px !important;
				width: revert !important;
				min-width: revert !important;
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			.img_auto_width {
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			#main_dir_or_plot_view {
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			#refresh_button {
				width: 300px;
			}
			
			._share_link {
				color: black !important;
			}
			
			#footer_element {
				height: 30px;
				background-color: #f8f9fa;
				padding: 0px;
				text-align: center;
				border-top: 1px solid #dee2e6;
				width: 100%;
				box-sizing: border-box;
				position: fixed;
				bottom: 0;
				z-index: 2;
				margin-left: -9px;
				z-index: 99;
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				display: inline-block;
				width: 50px;
				height: 26px;
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			.switch input {
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				width: 0;
				height: 0;
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				cursor: pointer;
				top: 0;
				left: 0;
				right: 0;
				bottom: 0;
				background-color: #ccc;
				transition: .4s;
				border-radius: 26px;
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				content: "";
				height: 20px;
				width: 20px;
				left: 3px;
				bottom: 3px;
				background-color: white;
				transition: .4s;
				border-radius: 50%;
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				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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			        1745483891,
			        993.03125,
			        38.5
			    ],
			    [
			        1745483891,
			        993.03125,
			        36.2
			    ],
			    [
			        1745502739,
			        1010.62890625,
			        36.9
			    ],
			    [
			        1745502739,
			        1010.62890625,
			        34.9
			    ],
			    [
			        1745502739,
			        1010.62890625,
			        34.6
			    ],
			    [
			        1745502739,
			        1010.62890625,
			        35.4
			    ],
			    [
			        1745524377,
			        1017.296875,
			        36.9
			    ],
			    [
			        1745524377,
			        1017.296875,
			        38.5
			    ],
			    [
			        1745524377,
			        1017.296875,
			        37.9
			    ],
			    [
			        1745524377,
			        1017.296875,
			        40.4
			    ],
			    [
			        1745550266,
			        1022.953125,
			        37
			    ],
			    [
			        1745550266,
			        1022.953125,
			        41.4
			    ],
			    [
			        1745550266,
			        1022.953125,
			        40.7
			    ],
			    [
			        1745550266,
			        1022.953125,
			        40.5
			    ],
			    [
			        1745575396,
			        1037.20703125,
			        37.6
			    ],
			    [
			        1745575396,
			        1037.20703125,
			        37
			    ],
			    [
			        1745575396,
			        1037.20703125,
			        37.4
			    ],
			    [
			        1745575396,
			        1037.20703125,
			        40.9
			    ],
			    [
			        1745608990,
			        1075.19140625,
			        37.6
			    ],
			    [
			        1745608990,
			        1075.19140625,
			        44
			    ],
			    [
			        1745608990,
			        1075.19140625,
			        41.6
			    ],
			    [
			        1745608990,
			        1075.19140625,
			        42
			    ],
			    [
			        1745637411,
			        1069.83203125,
			        37.4
			    ],
			    [
			        1745637411,
			        1069.83203125,
			        44.5
			    ],
			    [
			        1745637411,
			        1069.83203125,
			        43.8
			    ],
			    [
			        1745637411,
			        1069.83203125,
			        47.2
			    ]
			];
			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) &&
						!col.startsWith("OO_Info") &&
						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) &&
						!col.startsWith("OO_Info") &&
						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) &&
					!col.startsWith("OO_Info") &&
					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;
					}
					if (!col.startsWith("OO_Info")) {
						return;
					}
					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) &&
					!col.startsWith("OO_Info") &&
					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) &&
					!col.startsWith("OO_Info") &&
					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();
			}
			
			function plotTimelineFromGlobals() {
				if (
					typeof tab_results_headers_json === "undefined" ||
					typeof tab_results_csv_json === "undefined" ||
					!Array.isArray(tab_results_headers_json) ||
					!Array.isArray(tab_results_csv_json)
				) {
					console.warn("Global variables 'tab_results_headers_json' or 'tab_results_csv_json' missing or invalid.");
					return null;
				}
			
				const headers = tab_results_headers_json;
				const data = tab_results_csv_json;
			
				const col = name => headers.indexOf(name);
				const ix_trial_index = col("trial_index");
				const ix_start_time = col("start_time");
				const ix_end_time = col("end_time");
				const ix_status = col("trial_status");
			
				if ([ix_trial_index, ix_start_time, ix_end_time, ix_status].some(ix => ix === -1)) {
					console.warn("One or more needed columns missing");
					return null;
				}
			
				const traces = [];
			
				// Add dummy traces for legend
				traces.push({
					type: "scatter",
					mode: "lines",
					x: [null, null],
					y: [null, null],
					line: { color: "green", width: 4 },
					name: "COMPLETED",
					showlegend: true,
					hoverinfo: "none"
				});
				traces.push({
					type: "scatter",
					mode: "lines",
					x: [null, null],
					y: [null, null],
					line: { color: "yellow", width: 4 },
					name: "RUNNING",
					showlegend: true,
					hoverinfo: "none"
				});
				traces.push({
					type: "scatter",
					mode: "lines",
					x: [null, null],
					y: [null, null],
					line: { color: "red", width: 4 },
					name: "FAILED/OTHER",
					showlegend: true,
					hoverinfo: "none"
				});
			
				for (const row of data) {
					const trial_index = row[ix_trial_index];
					const start = row[ix_start_time];
					const end = row[ix_end_time];
					const status = row[ix_status];
			
					if (
						trial_index === "" || start === "" || end === "" ||
						isNaN(start) || isNaN(end)
					) continue;
			
					let color = "red"; // default
					if (status === "COMPLETED") color = "green";
					else if (status === "RUNNING") color = "yellow";
			
					traces.push({
						type: "scatter",
						mode: "lines",
						x: [new Date(start * 1000), new Date(end * 1000)],
						y: [trial_index, trial_index],
						line: { color: color, width: 4 },
						name: `Trial ${trial_index} (${status})`,
						showlegend: false,
						hoverinfo: "x+y+name"
					});
				}
			
				if (traces.length <= 3) { // only dummy traces added
					console.warn("No valid data for plotting found.");
					return null;
				}
			
				const layout = {
					title: "Trial Timeline",
					xaxis: {
						title: "Time",
						type: "date"
					},
					yaxis: {
						title: "Trial Index",
						autorange: "reversed"
					},
					margin: { t: 50 }
				};
			
				Plotly.newPlot('plot_timeline', traces, add_default_layout_data(layout));
				return true;
			}
			
			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();

				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>50398 </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>1     </td></tr><tr><td> Nr. imported jobs</td><td>398   </td></tr></tbody></table><h2>Experiment parameters:                             </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Name</th><th>Type</th><th>Lower bound</th><th>Upper bound</th><th>Type</th><th>Log Scale? </th></tr></thead><tbody><tr><td> recent_samples_size</td><td>int</td><td>1</td><td>5000</td><td>int</td><td>No         </td></tr><tr><td> n_samples</td><td>int</td><td>1</td><td>5000</td><td>int</td><td>No         </td></tr><tr><td> const</td><td>float</td><td>0.001</td><td>10</td><td>float</td><td>No         </td></tr><tr><td> max_depth</td><td>int</td><td>1</td><td>20</td><td>int</td><td>No         </td></tr><tr><td> threshold</td><td>float</td><td>0.001</td><td>0.999</td><td>float</td><td>No         </td></tr></tbody></table><h2>Number of evaluations</h2>
			<table>
			<tbody>
			<tr>
			<th>Failed</th>
			<th>Succeeded</th>
			<th>Running</th>
			<th>Total</th>
			</tr>
			<tr>
			<td>136</td>
			<td>627</td>
			<td>66</td>
			<td>829</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,const,max_depth,threshold
0,0_0,FAILED,Sobol,GenerationStep_0,,,4494,812,2.297981419280171522245836968068,20,0.652324771046638440807896586193
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2150,2791,7.926150933017955146908661845373,4,0.270228381857275989919031644604
2,2_0,FAILED,Sobol,GenerationStep_0,,,1070,1437,3.139797348826192546766833402216,15,0.111387636622413993547908717119
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3726,4666,6.268081024125218725373542838497,9,0.992385063424706448387269119848
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2543,2237,8.933602902077138807612755044829,7,0.850030917622148995960174033826
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,200,4177,0.805816842830739954450791628915,13,0.234249126477167002313706234418
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.820000000000000062172489379009,56.000000000000000000000000000000,1614,362,5.552501691741869471741210873006,1,0.385171646423637881184731668327
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4270,3552,4.923834515389986954403411800740,17,0.502296075535938135736557796918
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3913,1684,6.050676841060631971913608140312,11,0.369539147239178411563642612236
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1257,4715,4.172234771873802650077323050937,7,0.736186329530552074906779580488
10,10_0,FAILED,Sobol,GenerationStep_0,,,489,1059,9.392204860256052612044186389539,17,0.896831862878054386634119055088
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2832,2840,0.014453192384913562951176402294,3,0.031573003368452187689108257018
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1778.000000000000000000000000000000,3369,259,2.681195502394810414870107706520,5,0.127023485580459227772820440805
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,713,3329,7.059444786318578302086734765908,19,0.758498099718242890787678334164
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2439,2134,1.799806260649114753036315050849,10,0.605528091082349395612993703253
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4783,3954,8.677750713783316527383249194827,13,0.472908806506544376890843750516
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4865,1981,3.979676069700159413145001963130,1,0.951387548856437170741173758870
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2209,3794,5.858141959736124171342908084625,18,0.070504393575713045216879493182
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.830000000000000071054273576010,2323.000000000000000000000000000000,816,106,0.598813067856244773956575500051,6,0.283811193250119664366337701722
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3159,3168,9.976550413418561191747357952408,12,0.666021758226677751402178273565
20,20_0,FAILED,Sobol,GenerationStep_0,,,3071,1220,7.329491015892476646342856838601,14,0.550956726973876320663237038389
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,415,2994,2.951256054277531681862001278205,8,0.433961678683757789976027652301
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1516,1845,8.172136493938044310425539151765,20,0.212736653720960011693108526742
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3860,4868,1.294168219954706655627774125605,4,0.828647944658994717315181333106
24,24_0,FAILED,Sobol,GenerationStep_0,,,4206,525,7.732371612540447358696837909520,10,0.041253228152170778875174050881
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1863,3703,2.104225873090326714986986189615,14,0.906626478154212267490663634817
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,156,2400,6.851220355791040717008399951737,4,0.691286942178383490009707657009
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,2812,4327,3.722922358183190283398289466277,18,0.324753793466836193637448104710
28,28_0,FAILED,Sobol,GenerationStep_0,,,3505,1286,1.077083690708503072031021474686,16,0.455290384199470266057829803685
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1162,4503,9.204884072263725514062571164686,2,0.588038930626586076044759465731
30,30_0,RUNNING,Sobol,GenerationStep_0,,,1951,661,4.419440839350223804160577856237,11,0.811053991314023781100672749744
31,31_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4607,2628,5.048084194852971329225965746446,7,0.179708995940163734905681280907
32,32_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,4616,1531,9.557542980846017499629851954523,4,0.525710732651874401710756501416
33,33_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,1959,4555,0.177440759490244098772748770898,20,0.392870727367699124066291460622
34,34_0,FAILED,Sobol,GenerationStep_0,,,1190,907,6.181944070043043026885243307333,9,0.242128567261621352457723332918
35,35_0,COMPLETED,Sobol,GenerationStep_0,0.839999999999999968913755310496,1.000000000000000000000000000000,3534,2680,4.300960731581785267962914076634,15,0.873382282234728357650510588428
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,31.000000000000000000000000000000,4100,39,8.520331141264506413790513761342,1,0.514729608748589417821506231121
37,37_0,FAILED,BoTorch,GenerationStep_1,,,3972,391,8.203234450072384831287308770698,20,0.998999999999999999111821580300
38,38_0,COMPLETED,BoTorch,GenerationStep_1,0.830000000000000071054273576010,4.000000000000000000000000000000,1,1,8.432276726420946388884658517782,20,0.998999999999999999111821580300
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.830000000000000071054273576010,10.000000000000000000000000000000,5000,177,8.546516517754827901853786897846,1,0.998999999999999999111821580300
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,677,8.150181243006606734979868633673,1,0.998999999999999999111821580300
41,41_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,136.000000000000000000000000000000,3912,548,8.139023202898046704945045348722,1,0.001000000000000000020816681712
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,949.000000000000000000000000000000,4214,1,8.744000708840923508091691473965,20,0.998999999999999999111821580300
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,148.000000000000000000000000000000,5000,1,8.328368353310851901483147230465,20,0.001000000000000000020816681712
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,148.000000000000000000000000000000,3645,1,8.755986170581827821024489821866,20,0.001000000000000000020816681712
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,148.000000000000000000000000000000,4537,1,9.713059214952153297417680732906,1,0.001000000000000000020816681712
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,4.000000000000000000000000000000,4343,471,8.022453241116691557976992044132,1,0.998999999999999999111821580300
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,163.000000000000000000000000000000,5000,700,8.008137534156924530748256074730,1,0.001000000000000000020816681712
48,48_0,FAILED,BoTorch,GenerationStep_1,,,1,778,7.993699785736738228081321722129,20,0.001000000000000000020816681712
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,758.000000000000000000000000000000,3714,1,7.951427529897216572862816974521,20,0.998999999999999999111821580300
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,735.000000000000000000000000000000,3731,1,8.143466755177032112555934872944,1,0.998999999999999999111821580300
51,51_0,FAILED,BoTorch,GenerationStep_1,,,3451,747,8.726573839026167789256760443095,20,0.998999999999999999111821580300
52,52_0,FAILED,BoTorch,GenerationStep_1,,,4500,420,9.240351708867384772361219802406,20,0.998999999999999999111821580300
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,162.000000000000000000000000000000,4183,1,7.898668079731460345271898404462,20,0.001000000000000000020816681712
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,151.000000000000000000000000000000,4567,1,8.352484863625695865607667656150,1,0.001000000000000000020816681712
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,4.000000000000000000000000000000,5000,451,9.832627957615969194193894509226,1,0.998999999999999999111821580300
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,97.000000000000000000000000000000,3636,858,8.340549267000222144474719243590,1,0.001000000000000000020816681712
57,57_0,FAILED,BoTorch,GenerationStep_1,,,5000,720,9.764054674177531367718074761797,20,0.998999999999999999111821580300
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,156.000000000000000000000000000000,1,405,8.444812199872776758979853184428,1,0.001000000000000000020816681712
59,59_0,FAILED,BoTorch,GenerationStep_1,,,4016,299,9.991320679438850049791653873399,20,0.001000000000000000020816681712
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,46.000000000000000000000000000000,4840,563,7.382756989634083666373953747097,1,0.716594550231753224522890377557
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,48.000000000000000000000000000000,4303,1078,7.180356408768857612301417248091,1,0.807221390512348091483829648496
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,12.000000000000000000000000000000,4887,1295,7.431185780379863992095579305897,1,0.932067266133331462363287300832
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,550.000000000000000000000000000000,1816,873,6.918878044234597624040361552034,4,0.530776766139578803915810567560
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,11.000000000000000000000000000000,3233,1455,6.675969937019336164496507990407,1,0.729921862710849356226106010581
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,15.000000000000000000000000000000,5000,914,7.452218067454698058327267062850,1,0.842356973379816520441920602025
66,66_0,FAILED,BoTorch,GenerationStep_1,,,39,948,6.728706433282452437083520635497,19,0.686423017819762448787912489934
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,6991.000000000000000000000000000000,1912,1117,6.745966468640340885087880451465,9,0.548773680723615431276130038896
68,68_0,FAILED,BoTorch,GenerationStep_1,,,628,1379,6.632328198902861515762197086588,15,0.655255829128601918753815880336
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1732,7.634607384437464006055051868316,1,0.998999999999999999111821580300
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1256,1566,6.521925921336019449370269285282,1,0.567867295944931571582969809242
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,41.000000000000000000000000000000,1697,1277,6.412373486777015685333935834933,1,0.667059179299657190043149057601
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2600,1754,5.864826626654131125349067588104,1,0.784197864242683784219423159811
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,3999,1344,6.852497453189985598953626322327,1,0.998999999999999999111821580300
74,74_0,FAILED,BoTorch,GenerationStep_1,,,1085,967,5.831889840576867101162861217745,15,0.861060955967748897776914418500
75,75_0,FAILED,BoTorch,GenerationStep_1,,,476,1206,6.035794284653965391385099792387,20,0.850901801564585280601704653236
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,132,1722,6.295876023377624974841637595091,20,0.764492892650543431898313428974
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2964,3424,1.003412800297245111025290498219,1,0.546836086974321511355867642123
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,67.000000000000000000000000000000,510,1102,6.984021942180025810387178353267,1,0.463692823903757100900691057177
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,2.000000000000000000000000000000,5000,1161,7.063359217652683597066243237350,1,0.998999999999999999111821580300
80,80_0,FAILED,BoTorch,GenerationStep_1,,,1039,810,6.878304957858279777838106383570,19,0.564870373142303594526936194598
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4106,3003,1.400205791846677927381392692041,4,0.489948562783024843536594516991
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2220,1561,4.628223796517341170897452684585,1,0.998999999999999999111821580300
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1429.000000000000000000000000000000,155,1501,9.186083477493250271095348580275,20,0.998999999999999999111821580300
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,19.000000000000000000000000000000,1410,1408,6.631819505140359893857748829760,1,0.568765425573969585215650113241
85,85_0,FAILED,BoTorch,GenerationStep_1,,,2226,984,5.264056469663590753782500542002,20,0.998999999999999999111821580300
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1844,3094,0.166099235321229610207183213788,1,0.561672279004889141162948362762
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1736,3184,1.529825843787991690447825021693,20,0.243022348157291429027182516620
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1188,2099,5.512523933760818728444519365439,5,0.575378397344957548398269864265
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4442,2858,1.384933315285585164744475150655,5,0.496767585248303000788894223660
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,1,1978,0.001000000000000000020816681712,20,0.998999999999999999111821580300
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3448,1853,7.978308118497190903894988878164,12,0.001000000000000000020816681712
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,149.000000000000000000000000000000,4938,1052,0.001000000000000000020816681712,2,0.998999999999999999111821580300
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2741,1856,8.092056502856928901223909633700,13,0.493395309849120833334268354520
94,94_0,RUNNING,BoTorch,GenerationStep_1,,,4170,556,0.001000000000000000020816681712,17,0.734071691471233966908016554953
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,835,2172,0.001000000000000000020816681712,19,0.998999999999999999111821580300
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1620,1792,0.001000000000000000020816681712,13,0.998999999999999999111821580300
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4947,1787,8.620113050124668774287783890031,13,0.174050038428399639345300897730
98,98_0,RUNNING,BoTorch,GenerationStep_1,,,4716,540,10.000000000000000000000000000000,15,0.733670359002224770073041781870
99,99_0,RUNNING,BoTorch,GenerationStep_1,,,3711,681,5.112676486212783366624989866978,20,0.765454885917780658566300644452
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4801,1934,10.000000000000000000000000000000,12,0.414419528141673432219960204748
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,239,1819,10.000000000000000000000000000000,13,0.001000000000000000020816681712
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,911,1927,0.001000000000000000020816681712,18,0.998999999999999999111821580300
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,135.000000000000000000000000000000,3192,974,10.000000000000000000000000000000,2,0.993571154353743768439244377078
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,183.000000000000000000000000000000,4370,796,0.001000000000000000020816681712,2,0.843262299838525075657003071683
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,288,2046,0.001000000000000000020816681712,20,0.768268218364940858045031291113
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2119,10.000000000000000000000000000000,18,0.998999999999999999111821580300
107,107_0,FAILED,BoTorch,GenerationStep_1,,,4550,975,0.001000000000000000020816681712,15,0.983525790506839303617425684934
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4380,1974,2.173151179890504547387308775797,17,0.750077695164895197343923882727
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4292,1890,10.000000000000000000000000000000,9,0.512523449520982277149983019626
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,202.000000000000000000000000000000,5000,1081,10.000000000000000000000000000000,3,0.998999999999999999111821580300
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,450,1685,0.001000000000000000020816681712,14,0.012898450071115714551939213095
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,27,1832,0.001000000000000000020816681712,14,0.397917050325906573871037608114
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3995,4162,0.001000000000000000020816681712,8,0.751049740644825547519758401904
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4988,1846,10.000000000000000000000000000000,13,0.630911699273188575354254226113
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,956,1908,0.001000000000000000020816681712,14,0.823889929483441751933980867761
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1931,10.000000000000000000000000000000,11,0.001000000000000000020816681712
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4002,1934,10.000000000000000000000000000000,12,0.221986181220094697108535797270
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1201,2040,10.000000000000000000000000000000,14,0.359522652682607635199474316323
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,773,1839,0.001000000000000000020816681712,17,0.998999999999999999111821580300
120,120_0,RUNNING,BoTorch,GenerationStep_1,,,4881,596,7.213213328039353555709567444865,20,0.663065518656341224001948830846
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,1866,2469,7.944572664763542846344535064418,18,0.559769248292982246617555119883
122,122_0,RUNNING,BoTorch,GenerationStep_1,,,4716,559,7.095214836355371090803600964136,16,0.642496483146418606580141386075
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3223,2346,7.658401093299565864924716152018,14,0.998999999999999999111821580300
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3690,2513,1.433336808599841916134209895972,18,0.398920878435267189932034170852
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3027,2717,7.062410275517675195544597954722,11,0.747471556477516507754899066640
126,126_0,RUNNING,BoTorch,GenerationStep_1,,,4947,714,7.252725585258305684988044959027,17,0.894339903990750362261508144002
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1941,2624,0.608025594699889815331061981851,11,0.814294130020511763845547648089
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4956,2499,2.359674889145964460368531945278,18,0.343942688883508151942436370518
129,129_0,RUNNING,BoTorch,GenerationStep_1,,,4745,433,6.830394112982053123062087252038,18,0.289061727518416022864045089591
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2757,2466,10.000000000000000000000000000000,12,0.199102155486309106979803118520
131,131_0,RUNNING,BoTorch,GenerationStep_1,,,4899,535,7.107074049925778957970123883570,14,0.798315943203140587769439662225
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,309,2590,9.512103584332345818097564915661,19,0.998999999999999999111821580300
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,390,2359,9.610906912150021241814101813361,15,0.998999999999999999111821580300
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2259,2439,0.677607405834054432602897577453,13,0.998999999999999999111821580300
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3728,2495,1.479409375062305187498168379534,13,0.296543458136634963118183350161
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1569,2406,3.302345326935404834500786819262,17,0.378280994994921682117450245642
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1886,2777,4.692790303494419390517577994615,17,0.001000000000000000020816681712
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1265,3057,2.477511866491793668387799698394,16,0.998999999999999999111821580300
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,382,2649,4.010229345345735829653222026536,20,0.998999999999999999111821580300
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2673,6.291893537818795678617789235432,16,0.001000000000000000020816681712
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1621,3110,8.505824234158918528692083782516,15,0.998999999999999999111821580300
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,24,2478,0.001000000000000000020816681712,18,0.001000000000000000020816681712
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3195,4674,3.290411785343012152083019827842,15,0.720885701933119626971802063053
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2918,2512,10.000000000000000000000000000000,16,0.001000000000000000020816681712
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,78,2616,5.794937157801066440754311770434,12,0.001000000000000000020816681712
146,146_0,FAILED,BoTorch,GenerationStep_1,,,4750,524,7.646239411067210056671683560126,20,0.230351587458097167848691810832
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2074,2600,1.952419335565608538018977924366,18,0.998999999999999999111821580300
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1508,4858,7.416284752475498009971488500014,16,0.311871944431634795513730296079
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4326,2661,6.280284913766322141270848078420,11,0.998999999999999999111821580300
150,150_0,FAILED,BoTorch,GenerationStep_1,,,5000,755,10.000000000000000000000000000000,20,0.001000000000000000020816681712
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4069,5000,0.001000000000000000020816681712,11,0.139106979644229272752298243176
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,1062,4004,10.000000000000000000000000000000,3,0.885508193275667876420698121365
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4476,0.001000000000000000020816681712,6,0.998999999999999999111821580300
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4434,10.000000000000000000000000000000,9,0.001000000000000000020816681712
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3536,0.001000000000000000020816681712,8,0.464589077832349650609700120185
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3428,3796,0.001000000000000000020816681712,9,0.998999999999999999111821580300
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3972,4256,0.001000000000000000020816681712,11,0.998999999999999999111821580300
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4843,0.001000000000000000020816681712,12,0.998999999999999999111821580300
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3967,4397,10.000000000000000000000000000000,6,0.001000000000000000020816681712
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3616,0.001000000000000000020816681712,8,0.998999999999999999111821580300
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1050,4095,10.000000000000000000000000000000,4,0.001000000000000000020816681712
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,2496,4163,0.001000000000000000020816681712,4,0.998999999999999999111821580300
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2324,4167,10.000000000000000000000000000000,20,0.998999999999999999111821580300
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1904,4155,10.000000000000000000000000000000,11,0.998999999999999999111821580300
165,165_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4888,10.000000000000000000000000000000,19,0.998999999999999999111821580300
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3289,10.000000000000000000000000000000,15,0.001000000000000000020816681712
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4803,0.001000000000000000020816681712,1,0.001000000000000000020816681712
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4147,0.001000000000000000020816681712,1,0.056979550082211664896458813701
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1978,5000,10.000000000000000000000000000000,9,0.001000000000000000020816681712
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4381,0.001000000000000000020816681712,5,0.998999999999999999111821580300
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4572,0.001000000000000000020816681712,11,0.001000000000000000020816681712
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,118,5000,0.001000000000000000020816681712,20,0.321416184361661805279908321609
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,1,4297,10.000000000000000000000000000000,11,0.998999999999999999111821580300
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,2900,5000,0.001000000000000000020816681712,20,0.832770657481621157103290897794
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2300,4858,10.000000000000000000000000000000,1,0.001000000000000000020816681712
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3645,10.000000000000000000000000000000,10,0.001000000000000000020816681712
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,10.000000000000000000000000000000,11,0.498202287802444798714418539021
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3334,3873,10.000000000000000000000000000000,5,0.289583970911793553426605285495
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3728,0.001000000000000000020816681712,11,0.001000000000000000020816681712
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2963,10.000000000000000000000000000000,19,0.998999999999999999111821580300
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1892,3454,0.001000000000000000020816681712,4,0.001000000000000000020816681712
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,64.000000000000000000000000000000,5000,1281,10.000000000000000000000000000000,2,0.001000000000000000020816681712
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4031,10.000000000000000000000000000000,17,0.998999999999999999111821580300
184,184_0,FAILED,BoTorch,GenerationStep_1,,,5000,768,10.000000000000000000000000000000,20,0.001000000000000000020816681712
185,185_0,FAILED,BoTorch,GenerationStep_1,,,4272,345,10.000000000000000000000000000000,14,0.001000000000000000020816681712
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1710,10.000000000000000000000000000000,4,0.998999999999999999111821580300
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,344,1734,0.001000000000000000020816681712,4,0.998999999999999999111821580300
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3844,0.001000000000000000020816681712,1,0.001000000000000000020816681712
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3617,3556,10.000000000000000000000000000000,20,0.001000000000000000020816681712
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2316,10.000000000000000000000000000000,1,0.001000000000000000020816681712
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,152.000000000000000000000000000000,3963,1,0.001000000000000000020816681712,16,0.001000000000000000020816681712
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,893,3530,0.001000000000000000020816681712,4,0.001000000000000000020816681712
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1033,3702,10.000000000000000000000000000000,20,0.998999999999999999111821580300
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4095,3488,10.000000000000000000000000000000,4,0.998999999999999999111821580300
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,396,5000,0.001000000000000000020816681712,5,0.001000000000000000020816681712
196,196_0,FAILED,BoTorch,GenerationStep_1,,,5000,642,10.000000000000000000000000000000,20,0.001000000000000000020816681712
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2827,3709,10.000000000000000000000000000000,20,0.998999999999999999111821580300
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3534,10.000000000000000000000000000000,4,0.998999999999999999111821580300
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2773,10.000000000000000000000000000000,1,0.998999999999999999111821580300
200,200_0,FAILED,BoTorch,GenerationStep_1,,,5000,630,0.001000000000000000020816681712,17,0.001000000000000000020816681712
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1087,2537,10.000000000000000000000000000000,1,0.001000000000000000020816681712
202,202_0,FAILED,BoTorch,GenerationStep_1,,,5000,838,1.750334857354599815693063646904,18,0.998999999999999999111821580300
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,803,4261,10.000000000000000000000000000000,20,0.001000000000000000020816681712
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2989,2581,10.000000000000000000000000000000,1,0.998999999999999999111821580300
205,205_0,FAILED,BoTorch,GenerationStep_1,,,4243,348,0.001000000000000000020816681712,20,0.001000000000000000020816681712
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3211,5000,10.000000000000000000000000000000,3,0.001000000000000000020816681712
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,125.000000000000000000000000000000,5000,1060,10.000000000000000000000000000000,2,0.001000000000000000020816681712
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4153,3305,10.000000000000000000000000000000,5,0.001000000000000000020816681712
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3572,2385,0.001000000000000000020816681712,1,0.001000000000000000020816681712
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2434,3232,10.000000000000000000000000000000,8,0.998999999999999999111821580300
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4349,10.000000000000000000000000000000,15,0.998999999999999999111821580300
212,212_0,FAILED,BoTorch,GenerationStep_1,,,5000,770,10.000000000000000000000000000000,20,0.998999999999999999111821580300
213,213_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2706,1665,10.000000000000000000000000000000,3,0.001000000000000000020816681712
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2936,0.001000000000000000020816681712,14,0.001000000000000000020816681712
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3444,0.001000000000000000020816681712,12,0.998999999999999999111821580300
216,216_0,FAILED,BoTorch,GenerationStep_1,,,5000,615,10.000000000000000000000000000000,16,0.001000000000000000020816681712
217,217_0,FAILED,BoTorch,GenerationStep_1,,,5000,858,10.000000000000000000000000000000,17,0.998999999999999999111821580300
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,348,4699,10.000000000000000000000000000000,4,0.001000000000000000020816681712
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,152.000000000000000000000000000000,4118,217,10.000000000000000000000000000000,1,0.001000000000000000020816681712
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4444,5000,10.000000000000000000000000000000,15,0.998999999999999999111821580300
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3721,3969,10.000000000000000000000000000000,20,0.001000000000000000020816681712
222,222_0,FAILED,BoTorch,GenerationStep_1,,,4784,615,10.000000000000000000000000000000,19,0.001000000000000000020816681712
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,2.000000000000000000000000000000,5000,798,10.000000000000000000000000000000,1,0.998999999999999999111821580300
224,224_0,FAILED,BoTorch,GenerationStep_1,,,4571,460,7.125195367231239806926623714389,20,0.001000000000000000020816681712
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1738,3422,10.000000000000000000000000000000,12,0.998999999999999999111821580300
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3197,0.001000000000000000020816681712,8,0.998999999999999999111821580300
227,227_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3012,4437,10.000000000000000000000000000000,14,0.001000000000000000020816681712
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3197,0.001000000000000000020816681712,9,0.998999999999999999111821580300
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1154,3320,10.000000000000000000000000000000,10,0.001000000000000000020816681712
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,10.000000000000000000000000000000,1,0.998999999999999999111821580300
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3461,10.000000000000000000000000000000,13,0.998999999999999999111821580300
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2048,10.000000000000000000000000000000,2,0.001000000000000000020816681712
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4953,2252,0.001000000000000000020816681712,4,0.001000000000000000020816681712
234,234_0,FAILED,BoTorch,GenerationStep_1,,,4058,373,10.000000000000000000000000000000,15,0.001000000000000000020816681712
235,235_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,905,2980,10.000000000000000000000000000000,13,0.001000000000000000020816681712
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3065,4664,10.000000000000000000000000000000,4,0.001000000000000000020816681712
237,237_0,FAILED,BoTorch,GenerationStep_1,,,5000,798,0.001000000000000000020816681712,18,0.001000000000000000020816681712
238,238_0,FAILED,BoTorch,GenerationStep_1,,,5000,559,0.001000000000000000020816681712,17,0.001000000000000000020816681712
239,239_0,FAILED,BoTorch,GenerationStep_1,,,5000,706,0.001000000000000000020816681712,18,0.998999999999999999111821580300
240,240_0,FAILED,BoTorch,GenerationStep_1,,,5000,543,10.000000000000000000000000000000,20,0.001000000000000000020816681712
241,241_0,FAILED,BoTorch,GenerationStep_1,,,5000,711,10.000000000000000000000000000000,20,0.998999999999999999111821580300
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,3.000000000000000000000000000000,5000,626,10.000000000000000000000000000000,1,0.998999999999999999111821580300
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3478,1884,10.000000000000000000000000000000,20,0.998999999999999999111821580300
244,244_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4338,4788,10.000000000000000000000000000000,12,0.001000000000000000020816681712
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,15.000000000000000000000000000000,5000,1485,10.000000000000000000000000000000,3,0.998999999999999999111821580300
246,246_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3777,0.001000000000000000020816681712,1,0.998999999999999999111821580300
247,247_0,FAILED,BoTorch,GenerationStep_1,,,5000,604,10.000000000000000000000000000000,18,0.998999999999999999111821580300
248,248_0,FAILED,BoTorch,GenerationStep_1,,,4810,645,10.000000000000000000000000000000,18,0.197791669360893068718709741916
249,249_0,FAILED,BoTorch,GenerationStep_1,,,4059,351,10.000000000000000000000000000000,19,0.001000000000000000020816681712
250,250_0,FAILED,BoTorch,GenerationStep_1,,,5000,823,10.000000000000000000000000000000,17,0.998999999999999999111821580300
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3969,10.000000000000000000000000000000,8,0.998999999999999999111821580300
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3183,10.000000000000000000000000000000,17,0.001000000000000000020816681712
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1109,5000,0.001000000000000000020816681712,8,0.998999999999999999111821580300
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,737,2234,0.001000000000000000020816681712,2,0.998999999999999999111821580300
255,255_0,FAILED,BoTorch,GenerationStep_1,,,5000,503,10.000000000000000000000000000000,16,0.364338228337803327061550362487
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,353,3232,10.000000000000000000000000000000,3,0.998999999999999999111821580300
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,498,2345,0.001000000000000000020816681712,8,0.001000000000000000020816681712
258,258_0,FAILED,BoTorch,GenerationStep_1,,,4914,613,10.000000000000000000000000000000,16,0.873789787029919828853508079192
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3309,3987,10.000000000000000000000000000000,1,0.998999999999999999111821580300
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,392.000000000000000000000000000000,5000,690,10.000000000000000000000000000000,3,0.998999999999999999111821580300
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1754,4065,10.000000000000000000000000000000,16,0.001000000000000000020816681712
262,262_0,FAILED,BoTorch,GenerationStep_1,,,4677,641,0.001000000000000000020816681712,20,0.168232819295024454975262528933
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3339,3738,0.001000000000000000020816681712,3,0.930259935056636844130650842999
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4162,0.001000000000000000020816681712,1,0.998999999999999999111821580300
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1316,2410,10.000000000000000000000000000000,9,0.998999999999999999111821580300
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1876,2376,10.000000000000000000000000000000,9,0.001000000000000000020816681712
267,267_0,FAILED,BoTorch,GenerationStep_1,,,4265,388,8.719228806727526759345892060082,14,0.001000000000000000020816681712
268,268_0,FAILED,BoTorch,GenerationStep_1,,,5000,465,10.000000000000000000000000000000,15,0.998999999999999999111821580300
269,269_0,FAILED,BoTorch,GenerationStep_1,,,4868,539,10.000000000000000000000000000000,20,0.998999999999999999111821580300
270,270_0,FAILED,BoTorch,GenerationStep_1,,,5000,731,0.001000000000000000020816681712,20,0.998999999999999999111821580300
271,271_0,FAILED,BoTorch,GenerationStep_1,,,4774,562,10.000000000000000000000000000000,20,0.001000000000000000020816681712
272,272_0,FAILED,BoTorch,GenerationStep_1,,,5000,751,10.000000000000000000000000000000,18,0.998999999999999999111821580300
273,273_0,FAILED,BoTorch,GenerationStep_1,,,5000,654,10.000000000000000000000000000000,17,0.001000000000000000020816681712
274,274_0,FAILED,BoTorch,GenerationStep_1,,,4210,406,0.001000000000000000020816681712,20,0.001000000000000000020816681712
275,275_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4857,5000,10.000000000000000000000000000000,18,0.001000000000000000020816681712
276,276_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2891,0.001000000000000000020816681712,20,0.001000000000000000020816681712
277,277_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3117,1837,0.001000000000000000020816681712,10,0.998999999999999999111821580300
278,278_0,FAILED,BoTorch,GenerationStep_1,,,4052,289,0.001000000000000000020816681712,18,0.001000000000000000020816681712
279,279_0,FAILED,BoTorch,GenerationStep_1,,,5000,619,10.000000000000000000000000000000,18,0.998999999999999999111821580300
280,280_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4627,2407,0.001000000000000000020816681712,20,0.998999999999999999111821580300
281,281_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4088,2542,10.000000000000000000000000000000,20,0.001000000000000000020816681712
282,282_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1113,4597,0.001000000000000000020816681712,18,0.998999999999999999111821580300
283,283_0,FAILED,BoTorch,GenerationStep_1,,,4616,388,10.000000000000000000000000000000,14,0.001000000000000000020816681712
284,284_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,10.000000000000000000000000000000,18,0.992501094496366254027464037790
285,285_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1799,0.001000000000000000020816681712,7,0.001000000000000000020816681712
286,286_0,FAILED,BoTorch,GenerationStep_1,,,5000,695,10.000000000000000000000000000000,20,0.001000000000000000020816681712
287,287_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3841,3275,0.001000000000000000020816681712,20,0.998999999999999999111821580300
288,288_0,FAILED,BoTorch,GenerationStep_1,,,5000,454,10.000000000000000000000000000000,16,0.001000000000000000020816681712
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4519,0.001000000000000000020816681712,12,0.998999999999999999111821580300
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3809,4563,10.000000000000000000000000000000,18,0.001000000000000000020816681712
291,291_0,FAILED,BoTorch,GenerationStep_1,,,5000,520,10.000000000000000000000000000000,18,0.001000000000000000020816681712
292,292_0,FAILED,BoTorch,GenerationStep_1,,,5000,834,10.000000000000000000000000000000,17,0.001000000000000000020816681712
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1067,2858,10.000000000000000000000000000000,13,0.998999999999999999111821580300
294,294_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,360,3038,0.001000000000000000020816681712,18,0.001000000000000000020816681712
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2019,4789,0.001000000000000000020816681712,20,0.998999999999999999111821580300
296,296_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,2.000000000000000000000000000000,5000,994,10.000000000000000000000000000000,1,0.998999999999999999111821580300
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2915,2899,10.000000000000000000000000000000,20,0.001000000000000000020816681712
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2761,10.000000000000000000000000000000,8,0.998999999999999999111821580300
299,299_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3019,10.000000000000000000000000000000,11,0.998999999999999999111821580300
300,300_0,RUNNING,BoTorch,GenerationStep_1,,,5000,728,10.000000000000000000000000000000,20,0.998999999999999999111821580300
301,301_0,RUNNING,BoTorch,GenerationStep_1,,,4951,535,10.000000000000000000000000000000,20,0.001000000000000000020816681712
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2232,0.001000000000000000020816681712,14,0.001000000000000000020816681712
303,303_0,RUNNING,BoTorch,GenerationStep_1,,,4127,377,0.001000000000000000020816681712,20,0.001000000000000000020816681712
304,304_0,RUNNING,BoTorch,GenerationStep_1,,,5000,889,10.000000000000000000000000000000,17,0.998999999999999999111821580300
305,305_0,RUNNING,BoTorch,GenerationStep_1,,,5000,620,10.000000000000000000000000000000,18,0.001000000000000000020816681712
306,306_0,RUNNING,BoTorch,GenerationStep_1,,,4525,410,0.001000000000000000020816681712,16,0.001000000000000000020816681712
307,307_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3640,10.000000000000000000000000000000,14,0.001000000000000000020816681712
308,308_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4162,3968,0.001000000000000000020816681712,9,0.001000000000000000020816681712
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,415,4026,10.000000000000000000000000000000,9,0.001000000000000000020816681712
310,310_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4456,4452,0.001000000000000000020816681712,1,0.998999999999999999111821580300
311,311_0,RUNNING,BoTorch,GenerationStep_1,,,5000,726,10.000000000000000000000000000000,20,0.256935355578665924891623717485
312,312_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2369,10.000000000000000000000000000000,10,0.998999999999999999111821580300
313,313_0,FAILED,BoTorch,GenerationStep_1,,,4089,318,10.000000000000000000000000000000,14,0.001000000000000000020816681712
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2841,2195,0.001000000000000000020816681712,15,0.001000000000000000020816681712
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4545,3098,10.000000000000000000000000000000,1,0.001000000000000000020816681712
316,316_0,FAILED,BoTorch,GenerationStep_1,,,3922,215,0.001000000000000000020816681712,19,0.001000000000000000020816681712
317,317_0,FAILED,BoTorch,GenerationStep_1,,,5000,625,10.000000000000000000000000000000,18,0.998999999999999999111821580300
318,318_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3378,2552,10.000000000000000000000000000000,5,0.998999999999999999111821580300
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3588,10.000000000000000000000000000000,15,0.001000000000000000020816681712
320,320_0,FAILED,BoTorch,GenerationStep_1,,,4196,430,10.000000000000000000000000000000,18,0.001000000000000000020816681712
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4305,0.001000000000000000020816681712,2,0.001000000000000000020816681712
322,322_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.001000000000000000020816681712,13,0.001000000000000000020816681712
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2819,0.001000000000000000020816681712,2,0.998999999999999999111821580300
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3682,2835,0.001000000000000000020816681712,9,0.001000000000000000020816681712
325,325_0,FAILED,BoTorch,GenerationStep_1,,,5000,540,10.000000000000000000000000000000,16,0.001000000000000000020816681712
326,326_0,FAILED,BoTorch,GenerationStep_1,,,5000,664,10.000000000000000000000000000000,20,0.998999999999999999111821580300
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4019,0.001000000000000000020816681712,18,0.998999999999999999111821580300
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2372,4633,10.000000000000000000000000000000,1,0.998999999999999999111821580300
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4182,2558,10.000000000000000000000000000000,3,0.001000000000000000020816681712
330,330_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4328,3637,0.001000000000000000020816681712,1,0.001000000000000000020816681712
331,331_0,RUNNING,BoTorch,GenerationStep_1,,,4925,499,0.001000000000000000020816681712,16,0.328602163212721509744085324201
332,332_0,RUNNING,BoTorch,GenerationStep_1,,,5000,612,10.000000000000000000000000000000,18,0.998999999999999999111821580300
333,333_0,FAILED,BoTorch,GenerationStep_1,,,4955,809,10.000000000000000000000000000000,18,0.296406627522246668426930682472
334,334_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,939,4799,10.000000000000000000000000000000,19,0.001000000000000000020816681712
335,335_0,FAILED,BoTorch,GenerationStep_1,,,4126,294,0.001000000000000000020816681712,14,0.001000000000000000020816681712
336,336_0,FAILED,BoTorch,GenerationStep_1,,,4015,243,0.001000000000000000020816681712,18,0.001000000000000000020816681712
337,337_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4237,10.000000000000000000000000000000,3,0.998999999999999999111821580300
338,338_0,FAILED,BoTorch,GenerationStep_1,,,5000,712,10.000000000000000000000000000000,16,0.001000000000000000020816681712
339,339_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4664,3834,0.001000000000000000020816681712,2,0.001000000000000000020816681712
340,340_0,FAILED,BoTorch,GenerationStep_1,,,4875,477,10.000000000000000000000000000000,16,0.001000000000000000020816681712
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,0.001000000000000000020816681712,7,0.001000000000000000020816681712
342,342_0,FAILED,BoTorch,GenerationStep_1,,,5000,653,10.000000000000000000000000000000,20,0.998999999999999999111821580300
343,343_0,FAILED,BoTorch,GenerationStep_1,,,4767,443,0.001000000000000000020816681712,14,0.001000000000000000020816681712
344,344_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,880,1800,10.000000000000000000000000000000,10,0.001000000000000000020816681712
345,345_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4383,10.000000000000000000000000000000,20,0.998999999999999999111821580300
346,346_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,921,4754,0.001000000000000000020816681712,9,0.001000000000000000020816681712
347,347_0,FAILED,BoTorch,GenerationStep_1,,,5000,774,0.294207151781216424968334877121,18,0.998999999999999999111821580300
348,348_0,FAILED,BoTorch,GenerationStep_1,,,1,636,0.001000000000000000020816681712,20,0.001000000000000000020816681712
349,349_0,FAILED,BoTorch,GenerationStep_1,,,5000,532,10.000000000000000000000000000000,18,0.998999999999999999111821580300
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3323,0.001000000000000000020816681712,2,0.001000000000000000020816681712
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2933,4840,0.001000000000000000020816681712,20,0.001000000000000000020816681712
352,352_0,FAILED,BoTorch,GenerationStep_1,,,5000,619,0.001000000000000000020816681712,20,0.001000000000000000020816681712
353,353_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3179,10.000000000000000000000000000000,3,0.998999999999999999111821580300
354,354_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4198,0.001000000000000000020816681712,14,0.998999999999999999111821580300
355,355_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1846,0.001000000000000000020816681712,18,0.001000000000000000020816681712
356,356_0,FAILED,BoTorch,GenerationStep_1,,,5000,696,4.080087531430275582522426702781,18,0.998999999999999999111821580300
357,357_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,160.000000000000000000000000000000,3697,1,10.000000000000000000000000000000,18,0.001000000000000000020816681712
358,358_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2085,1990,10.000000000000000000000000000000,18,0.001000000000000000020816681712
359,359_0,FAILED,BoTorch,GenerationStep_1,,,5000,626,10.000000000000000000000000000000,17,0.998999999999999999111821580300
360,360_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3262,3423,0.001000000000000000020816681712,18,0.001000000000000000020816681712
361,361_0,FAILED,BoTorch,GenerationStep_1,,,5000,755,0.001000000000000000020816681712,18,0.476942225419542398245908998433
362,362_0,FAILED,BoTorch,GenerationStep_1,,,4780,441,0.001000000000000000020816681712,15,0.001000000000000000020816681712
363,363_0,FAILED,BoTorch,GenerationStep_1,,,4200,307,10.000000000000000000000000000000,13,0.001000000000000000020816681712
364,364_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3717,1818,10.000000000000000000000000000000,5,0.001000000000000000020816681712
365,365_0,FAILED,BoTorch,GenerationStep_1,,,5000,626,0.001000000000000000020816681712,20,0.001000000000000000020816681712
366,366_0,FAILED,BoTorch,GenerationStep_1,,,4130,394,3.355165986419716528388335063937,14,0.998999999999999999111821580300
367,367_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,105.000000000000000000000000000000,5000,743,0.001000000000000000020816681712,1,0.998999999999999999111821580300
368,368_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,788,3810,0.001000000000000000020816681712,7,0.001000000000000000020816681712
369,369_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3352,0.001000000000000000020816681712,13,0.001000000000000000020816681712
370,370_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3938,4317,0.001000000000000000020816681712,12,0.001000000000000000020816681712
371,371_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1805,0.001000000000000000020816681712,10,0.001000000000000000020816681712
372,372_0,FAILED,BoTorch,GenerationStep_1,,,5000,592,0.001000000000000000020816681712,17,0.855835481097209416212479027308
373,373_0,FAILED,BoTorch,GenerationStep_1,,,5000,449,10.000000000000000000000000000000,13,0.975663087434908149475631944370
374,374_0,FAILED,BoTorch,GenerationStep_1,,,1,673,0.001000000000000000020816681712,20,0.001000000000000000020816681712
375,375_0,FAILED,BoTorch,GenerationStep_1,,,5000,703,0.001000000000000000020816681712,16,0.001000000000000000020816681712
376,376_0,FAILED,BoTorch,GenerationStep_1,,,5000,823,0.001000000000000000020816681712,20,0.998999999999999999111821580300
377,377_0,FAILED,BoTorch,GenerationStep_1,,,4962,514,0.001000000000000000020816681712,17,0.998999999999999999111821580300
378,378_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,3.000000000000000000000000000000,5000,544,10.000000000000000000000000000000,1,0.998999999999999999111821580300
379,379_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4828,10.000000000000000000000000000000,2,0.998999999999999999111821580300
380,380_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3896,5000,0.001000000000000000020816681712,1,0.001000000000000000020816681712
381,381_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1866,10.000000000000000000000000000000,20,0.998999999999999999111821580300
382,382_0,FAILED,BoTorch,GenerationStep_1,,,5000,755,10.000000000000000000000000000000,18,0.998999999999999999111821580300
383,383_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2122,3505,10.000000000000000000000000000000,7,0.001000000000000000020816681712
384,384_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,71.000000000000000000000000000000,5000,1252,10.000000000000000000000000000000,2,0.998999999999999999111821580300
385,385_0,FAILED,BoTorch,GenerationStep_1,,,5000,684,10.000000000000000000000000000000,16,0.998999999999999999111821580300
386,386_0,FAILED,BoTorch,GenerationStep_1,,,4667,484,10.000000000000000000000000000000,20,0.998999999999999999111821580300
387,387_0,FAILED,BoTorch,GenerationStep_1,,,4015,271,10.000000000000000000000000000000,18,0.001000000000000000020816681712
388,388_0,FAILED,BoTorch,GenerationStep_1,,,5000,661,10.000000000000000000000000000000,20,0.998999999999999999111821580300
389,389_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3489,2294,10.000000000000000000000000000000,20,0.001000000000000000020816681712
390,390_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2898,0.001000000000000000020816681712,8,0.998999999999999999111821580300
391,391_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,10.000000000000000000000000000000,5,0.998999999999999999111821580300
392,392_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2242,0.001000000000000000020816681712,12,0.998999999999999999111821580300
393,393_0,RUNNING,BoTorch,GenerationStep_1,,,4268,431,10.000000000000000000000000000000,14,0.490387682232395150094816926867
394,394_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4711,0.001000000000000000020816681712,7,0.001000000000000000020816681712
395,395_0,RUNNING,BoTorch,GenerationStep_1,,,4819,719,10.000000000000000000000000000000,18,0.998999999999999999111821580300
396,396_0,RUNNING,BoTorch,GenerationStep_1,,,4121,427,10.000000000000000000000000000000,20,0.001000000000000000020816681712
397,397_0,RUNNING,BoTorch,GenerationStep_1,,,4084,324,10.000000000000000000000000000000,17,0.001000000000000000020816681712
398,398_0,RUNNING,BoTorch,GenerationStep_1,,,5000,717,10.000000000000000000000000000000,18,0.001000000000000000020816681712
399,399_0,RUNNING,BoTorch,GenerationStep_1,,,4512,516,10.000000000000000000000000000000,18,0.998999999999999999111821580300
400,400_0,RUNNING,BoTorch,GenerationStep_1,,,5000,797,10.000000000000000000000000000000,19,0.998999999999999999111821580300
401,401_0,RUNNING,BoTorch,GenerationStep_1,,,4307,316,0.001000000000000000020816681712,13,0.001000000000000000020816681712
402,402_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2325,3375,0.001000000000000000020816681712,15,0.998999999999999999111821580300
403,403_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2208,0.001000000000000000020816681712,13,0.998999999999999999111821580300
404,404_0,RUNNING,BoTorch,GenerationStep_1,,,5000,627,10.000000000000000000000000000000,20,0.001000000000000000020816681712
405,405_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4720,4091,0.001000000000000000020816681712,18,0.001000000000000000020816681712
406,406_0,RUNNING,BoTorch,GenerationStep_1,,,5000,653,10.000000000000000000000000000000,15,0.998999999999999999111821580300
407,407_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,586,4432,0.001000000000000000020816681712,9,0.998999999999999999111821580300
408,408_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4791,0.001000000000000000020816681712,4,0.998999999999999999111821580300
409,409_0,RUNNING,BoTorch,GenerationStep_1,,,4552,502,10.000000000000000000000000000000,17,0.001000000000000000020816681712
410,410_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,5000,902,10.000000000000000000000000000000,1,0.998999999999999999111821580300
411,411_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,603,3675,10.000000000000000000000000000000,18,0.998999999999999999111821580300
412,412_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3181,10.000000000000000000000000000000,2,0.001000000000000000020816681712
413,413_0,RUNNING,BoTorch,GenerationStep_1,,,5000,595,10.000000000000000000000000000000,16,0.998999999999999999111821580300
414,414_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3274,0.001000000000000000020816681712,17,0.998999999999999999111821580300
415,415_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3759,3038,10.000000000000000000000000000000,6,0.998999999999999999111821580300
416,416_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4246,2112,0.001000000000000000020816681712,7,0.001000000000000000020816681712
417,417_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,776,2789,10.000000000000000000000000000000,1,0.001000000000000000020816681712
418,418_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1912,3803,0.001000000000000000020816681712,16,0.998999999999999999111821580300
419,419_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4155,2302,0.001000000000000000020816681712,6,0.998999999999999999111821580300
420,420_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2220,0.001000000000000000020816681712,17,0.998999999999999999111821580300
421,421_0,RUNNING,BoTorch,GenerationStep_1,,,4460,362,10.000000000000000000000000000000,15,0.001000000000000000020816681712
422,422_0,RUNNING,BoTorch,GenerationStep_1,,,1,796,8.116770183507338032313782605343,20,0.058994491136176413492719916576
423,423_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,0.000000000000000000000000000000,2648,3132,0.001000000000000000020816681712,9,0.001000000000000000020816681712
424,424_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,883,10.000000000000000000000000000000,1,0.998999999999999999111821580300
425,425_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,197,5000,0.001000000000000000020816681712,14,0.998999999999999999111821580300
426,426_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1534,10.000000000000000000000000000000,3,0.001000000000000000020816681712
427,427_0,RUNNING,BoTorch,GenerationStep_1,,,4461,577,7.512410767002706712958115531364,19,0.001000000000000000020816681712
428,428_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1276,4286,10.000000000000000000000000000000,6,0.001000000000000000020816681712
429,429_0,RUNNING,BoTorch,GenerationStep_1,,,3980,272,10.000000000000000000000000000000,20,0.001000000000000000020816681712
430,430_0,RUNNING,BoTorch,GenerationStep_1,,,4730,471,10.000000000000000000000000000000,20,0.001000000000000000020816681712
431,431_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3640,0.001000000000000000020816681712,1,0.998999999999999999111821580300
432,432_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3816,10.000000000000000000000000000000,4,0.001000000000000000020816681712
433,433_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2475,4429,10.000000000000000000000000000000,1,0.001000000000000000020816681712
434,434_0,RUNNING,BoTorch,GenerationStep_1,,,5000,578,10.000000000000000000000000000000,17,0.001000000000000000020816681712
435,435_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1133,1530,0.001000000000000000020816681712,2,0.998999999999999999111821580300
436,436_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,226,2067,10.000000000000000000000000000000,1,0.998999999999999999111821580300
437,437_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1501,2866,0.001000000000000000020816681712,18,0.998999999999999999111821580300
438,438_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1515,0.001000000000000000020816681712,2,0.001000000000000000020816681712
439,439_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,73.000000000000000000000000000000,5000,1059,10.000000000000000000000000000000,1,0.001000000000000000020816681712
440,440_0,RUNNING,BoTorch,GenerationStep_1,,,4380,444,10.000000000000000000000000000000,19,0.001000000000000000020816681712
441,441_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1376,3931,0.001000000000000000020816681712,20,0.998999999999999999111821580300
442,442_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1180,3096,0.001000000000000000020816681712,5,0.001000000000000000020816681712
443,443_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2585,0.001000000000000000020816681712,3,0.998999999999999999111821580300
444,444_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4485,1800,0.001000000000000000020816681712,7,0.998999999999999999111821580300
445,445_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,737,1957,0.001000000000000000020816681712,1,0.001000000000000000020816681712
446,446_0,RUNNING,BoTorch,GenerationStep_1,,,4593,450,0.001000000000000000020816681712,17,0.001000000000000000020816681712
447,447_0,FAILED,BoTorch,GenerationStep_1,,,5000,694,10.000000000000000000000000000000,20,0.001000000000000000020816681712
448,448_0,FAILED,BoTorch,GenerationStep_1,,,5000,553,10.000000000000000000000000000000,18,0.001000000000000000020816681712
449,449_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2397,0.001000000000000000020816681712,20,0.998999999999999999111821580300
450,450_0,COMPLETED,BoTorch,GenerationStep_1,0.830000000000000071054273576010,4.000000000000000000000000000000,1,1,0.001000000000000000020816681712,20,0.038893396472768425320420959679
451,451_0,RUNNING,BoTorch,GenerationStep_1,,,95,313,10.000000000000000000000000000000,20,0.680447003407676165309680982318
452,452_0,RUNNING,BoTorch,GenerationStep_1,,,2336,371,9.820542323194986877865630958695,15,0.680915814694941778917325336806
453,453_0,FAILED,BoTorch,GenerationStep_1,,,154,417,0.001000000000000000020816681712,17,0.693758458525476351397287544387
454,454_0,FAILED,BoTorch,GenerationStep_1,,,4730,327,10.000000000000000000000000000000,13,0.712960221789661341418309348228
455,455_0,FAILED,BoTorch,GenerationStep_1,,,1168,260,0.001000000000000000020816681712,16,0.721950786504495845008477772353
456,456_0,FAILED,BoTorch,GenerationStep_1,,,1,158,0.001000000000000000020816681712,20,0.001000000000000000020816681712
457,457_0,COMPLETED,BoTorch,GenerationStep_1,0.830000000000000071054273576010,1926.000000000000000000000000000000,265,58,1.023212794410726544924727932084,20,0.641505043776396943755457868974
458,458_0,FAILED,BoTorch,GenerationStep_1,,,42,238,0.001000000000000000020816681712,16,0.661454101718912279572748502687
459,459_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,54.000000000000000000000000000000,3562,351,10.000000000000000000000000000000,1,0.710993139277586894131388817186
460,460_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,4550.000000000000000000000000000000,522,37,10.000000000000000000000000000000,20,0.069453448698040709530232561519
461,461_0,FAILED,BoTorch,GenerationStep_1,,,1237,545,10.000000000000000000000000000000,20,0.719553777461609977983414410119
462,462_0,FAILED,BoTorch,GenerationStep_1,,,1929,436,10.000000000000000000000000000000,19,0.701330757880445965213311865227
463,463_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,76.000000000000000000000000000000,1356,9,4.183484902976159602872030518483,14,0.697229959871345283950461180211
464,464_0,FAILED,BoTorch,GenerationStep_1,,,3464,276,10.000000000000000000000000000000,14,0.694977382788224629095452655747
465,465_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,130.000000000000000000000000000000,1955,45,10.000000000000000000000000000000,13,0.673339098050273587858782775584
466,466_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,32.000000000000000000000000000000,35,31,7.272606509439924593607429414988,17,0.651452871451790982426643950021
467,467_0,FAILED,BoTorch,GenerationStep_1,,,932,573,10.000000000000000000000000000000,18,0.733391186387846616412389266770
468,468_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,148.000000000000000000000000000000,1,1,10.000000000000000000000000000000,20,0.001000000000000000020816681712
469,469_0,FAILED,BoTorch,GenerationStep_1,,,1,292,9.998807027099799071834240749013,19,0.645734615848184256847730466689
470,470_0,FAILED,BoTorch,GenerationStep_1,,,2799,436,10.000000000000000000000000000000,17,0.750103887913138089871267766284
471,471_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,48.000000000000000000000000000000,4875,366,10.000000000000000000000000000000,1,0.704931763194253657722754269344
472,472_0,FAILED,BoTorch,GenerationStep_1,,,1162,355,10.000000000000000000000000000000,14,0.714080075935720315349897191481
473,473_0,FAILED,BoTorch,GenerationStep_1,,,1204,447,0.001000000000000000020816681712,20,0.671048023682697336589342285151
474,474_0,COMPLETED,BoTorch,GenerationStep_1,0.830000000000000071054273576010,3776.000000000000000000000000000000,787,98,10.000000000000000000000000000000,14,0.662902771423162673336548778025
475,475_0,FAILED,BoTorch,GenerationStep_1,,,4328,434,10.000000000000000000000000000000,15,0.723977810611394323458966937324
476,476_0,FAILED,BoTorch,GenerationStep_1,,,963,224,10.000000000000000000000000000000,13,0.709852304366057174078719071986
477,477_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,933.000000000000000000000000000000,4549,1,10.000000000000000000000000000000,12,0.670434478186252569287262303988
478,478_0,FAILED,BoTorch,GenerationStep_1,,,4790,690,5.833903092749272545347594132181,18,0.725295265515275677792317310377
479,479_0,FAILED,BoTorch,GenerationStep_1,,,135,370,10.000000000000000000000000000000,16,0.664646816712529897586136939935
480,480_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2610,1936,0.001000000000000000020816681712,5,0.001000000000000000020816681712
481,481_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3624,5000,10.000000000000000000000000000000,7,0.001000000000000000020816681712
482,482_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4079,0.001000000000000000020816681712,6,0.998999999999999999111821580300
483,483_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2031,0.001000000000000000020816681712,11,0.001000000000000000020816681712
484,484_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3848,0.001000000000000000020816681712,7,0.998999999999999999111821580300
485,485_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2760,2032,10.000000000000000000000000000000,10,0.001000000000000000020816681712
486,486_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2091,1966,10.000000000000000000000000000000,5,0.998999999999999999111821580300
487,487_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2301,5000,0.001000000000000000020816681712,17,0.001000000000000000020816681712
488,488_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4733,0.001000000000000000020816681712,16,0.998999999999999999111821580300
489,489_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2076,0.001000000000000000020816681712,10,0.998999999999999999111821580300
490,490_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,74,4719,10.000000000000000000000000000000,15,0.001000000000000000020816681712
491,491_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2036,10.000000000000000000000000000000,6,0.998999999999999999111821580300
492,492_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1795,0.001000000000000000020816681712,16,0.001000000000000000020816681712
493,493_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3057,0.001000000000000000020816681712,10,0.001000000000000000020816681712
494,494_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1372,2004,0.001000000000000000020816681712,8,0.001000000000000000020816681712
495,495_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4910,0.001000000000000000020816681712,9,0.998999999999999999111821580300
496,496_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4573,10.000000000000000000000000000000,17,0.998999999999999999111821580300
497,497_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1147,10.000000000000000000000000000000,1,0.998999999999999999111821580300
498,498_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3133,1812,0.001000000000000000020816681712,16,0.998999999999999999111821580300
499,499_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3347,3880,10.000000000000000000000000000000,15,0.998999999999999999111821580300
500,500_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2162,4358,0.001000000000000000020816681712,8,0.001000000000000000020816681712
501,501_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2045,10.000000000000000000000000000000,9,0.998999999999999999111821580300
502,502_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3429,10.000000000000000000000000000000,20,0.001000000000000000020816681712
503,503_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3345,1899,0.001000000000000000020816681712,4,0.998999999999999999111821580300
504,504_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4103,0.001000000000000000020816681712,20,0.001000000000000000020816681712
505,505_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,947,1914,10.000000000000000000000000000000,4,0.001000000000000000020816681712
506,506_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3007,4796,0.001000000000000000020816681712,12,0.001000000000000000020816681712
507,507_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,100.000000000000000000000000000000,5000,877,10.000000000000000000000000000000,1,0.001000000000000000020816681712
508,508_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4459,2028,10.000000000000000000000000000000,8,0.001000000000000000020816681712
509,509_0,FAILED,BoTorch,GenerationStep_1,,,5000,915,7.119527104447218590621559997089,20,0.998999999999999999111821580300
510,510_0,RUNNING,BoTorch,GenerationStep_1,,,5000,620,2.241243627110144576164429963683,15,0.903718128814632537526563282881
511,511_0,RUNNING,BoTorch,GenerationStep_1,,,5000,852,10.000000000000000000000000000000,20,0.998999999999999999111821580300
512,512_0,RUNNING,BoTorch,GenerationStep_1,,,5000,641,10.000000000000000000000000000000,8,0.998999999999999999111821580300
513,513_0,RUNNING,BoTorch,GenerationStep_1,,,5000,650,10.000000000000000000000000000000,11,0.998999999999999999111821580300
514,514_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,3.000000000000000000000000000000,5000,711,10.000000000000000000000000000000,1,0.998999999999999999111821580300
515,515_0,RUNNING,BoTorch,GenerationStep_1,,,5000,977,10.000000000000000000000000000000,20,0.998999999999999999111821580300
516,516_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,2.000000000000000000000000000000,5000,964,5.187647434025284276515321835177,1,0.998999999999999999111821580300
517,342_0,RUNNING,BoTorch,GenerationStep_1,,,5000,653,10.000000000000000000000000000000,20,0.998999999999999999111821580300
518,518_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,2.000000000000000000000000000000,5000,854,10.000000000000000000000000000000,1,0.998999999999999999111821580300
519,519_0,RUNNING,BoTorch,GenerationStep_1,,,5000,686,1.664501017129026427809890265053,11,0.998999999999999999111821580300
520,520_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,770.000000000000000000000000000000,5000,621,10.000000000000000000000000000000,4,0.998999999999999999111821580300
521,521_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,3.000000000000000000000000000000,5000,1038,10.000000000000000000000000000000,1,0.998999999999999999111821580300
522,522_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,714.000000000000000000000000000000,4870,678,10.000000000000000000000000000000,4,0.998999999999999999111821580300
523,523_0,RUNNING,BoTorch,GenerationStep_1,,,5000,781,10.000000000000000000000000000000,20,0.998999999999999999111821580300
524,524_0,RUNNING,BoTorch,GenerationStep_1,,,4442,773,10.000000000000000000000000000000,20,0.998999999999999999111821580300
525,525_0,RUNNING,BoTorch,GenerationStep_1,,,5000,683,10.000000000000000000000000000000,18,0.756743582617356747022085983190
526,526_0,RUNNING,BoTorch,GenerationStep_1,,,5000,602,10.000000000000000000000000000000,10,0.965636044512797275807258756686
527,527_0,RUNNING,BoTorch,GenerationStep_1,,,5000,926,10.000000000000000000000000000000,20,0.998999999999999999111821580300
528,528_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,3.000000000000000000000000000000,5000,672,10.000000000000000000000000000000,1,0.998999999999999999111821580300
529,529_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,443.000000000000000000000000000000,5000,599,6.977964117983680658596767898416,3,0.001000000000000000020816681712
530,530_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,2.000000000000000000000000000000,5000,944,10.000000000000000000000000000000,1,0.998999999999999999111821580300
531,531_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1304.000000000000000000000000000000,5000,626,10.000000000000000000000000000000,5,0.001000000000000000020816681712
532,532_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2270.000000000000000000000000000000,4659,680,10.000000000000000000000000000000,6,0.998999999999999999111821580300
533,533_0,RUNNING,BoTorch,GenerationStep_1,,,5000,693,10.000000000000000000000000000000,20,0.998999999999999999111821580300
534,534_0,RUNNING,BoTorch,GenerationStep_1,,,5000,630,6.545404579390678989625484973658,18,0.998999999999999999111821580300
535,535_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,840.000000000000000000000000000000,5000,545,10.000000000000000000000000000000,4,0.998999999999999999111821580300
536,536_0,RUNNING,BoTorch,GenerationStep_1,,,5000,834,3.277145125074808706955309389741,20,0.001000000000000000020816681712
537,537_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1432.000000000000000000000000000000,5000,579,10.000000000000000000000000000000,5,0.998999999999999999111821580300
538,538_0,RUNNING,BoTorch,GenerationStep_1,,,4551,678,10.000000000000000000000000000000,20,0.998999999999999999111821580300
539,539_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,368.000000000000000000000000000000,5000,641,10.000000000000000000000000000000,3,0.998999999999999999111821580300
540,540_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1207,2506,0.001000000000000000020816681712,5,0.128818679230374683042370520525
541,541_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1811,3608,10.000000000000000000000000000000,1,0.998999999999999999111821580300
542,542_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1156,4305,5.946021733483554783106228569523,17,0.998999999999999999111821580300
543,543_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3932,10.000000000000000000000000000000,13,0.001000000000000000020816681712
544,544_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2265,3832,10.000000000000000000000000000000,13,0.001000000000000000020816681712
545,545_0,COMPLETED,BoTorch,GenerationStep_1,0.849999999999999977795539507497,12.000000000000000000000000000000,5000,934,0.001000000000000000020816681712,1,0.998999999999999999111821580300
546,546_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4908,2989,10.000000000000000000000000000000,4,0.001000000000000000020816681712
547,547_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2123,10.000000000000000000000000000000,20,0.001000000000000000020816681712
548,548_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4507,0.001000000000000000020816681712,19,0.001000000000000000020816681712
549,549_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2539,5000,10.000000000000000000000000000000,8,0.998999999999999999111821580300
550,550_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1285,5000,10.000000000000000000000000000000,8,0.998999999999999999111821580300
551,551_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2091,3946,0.001000000000000000020816681712,13,0.998999999999999999111821580300
552,552_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,853,3282,0.001000000000000000020816681712,5,0.998999999999999999111821580300
553,553_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1822,4953,7.055956774105591300383366615279,1,0.998999999999999999111821580300
554,554_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3579,2148,0.001000000000000000020816681712,20,0.972849266900153941683981884125
555,555_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3163,2757,0.001000000000000000020816681712,1,0.998999999999999999111821580300
556,556_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,840,3937,0.001000000000000000020816681712,15,0.001000000000000000020816681712
557,557_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4954,3257,10.000000000000000000000000000000,20,0.998999999999999999111821580300
558,558_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3351,3535,0.001000000000000000020816681712,9,0.001000000000000000020816681712
559,559_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2101,0.001000000000000000020816681712,20,0.001000000000000000020816681712
560,560_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2424,0.001000000000000000020816681712,10,0.001000000000000000020816681712
561,561_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4164,4411,0.001000000000000000020816681712,17,0.001000000000000000020816681712
562,562_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,3003,3988,10.000000000000000000000000000000,11,0.001000000000000000020816681712
563,563_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4461,10.000000000000000000000000000000,1,0.749825252876562764470236288616
564,564_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,1955,5000,10.000000000000000000000000000000,17,0.998999999999999999111821580300
565,565_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,4678,3671,10.000000000000000000000000000000,18,0.001000000000000000020816681712
566,566_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,2886,5000,10.000000000000000000000000000000,12,0.998999999999999999111821580300
567,567_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,2.000000000000000000000000000000,5000,1218,10.000000000000000000000000000000,1,0.998999999999999999111821580300
568,568_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3408,10.000000000000000000000000000000,17,0.998999999999999999111821580300
569,569_0,COMPLETED,BoTorch,GenerationStep_1,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2868,10.000000000000000000000000000000,4,0.998999999999999999111821580300
570,570_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,640,2297,1.027354380898177543812721523864,5,0.156345545560121534922615182950
571,571_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,4269,4287,8.863766551333480236962714116089,20,0.992279063167050501270693985134
572,572_0,RUNNING,Sobol,SOBOL,,,2537,302,2.614612913884222678007063223049,10,0.669002472087740884809647923248
573,573_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2414,3157,7.276331606241875249452277785167,15,0.448444122707471248823196674493
574,574_0,RUNNING,Sobol,SOBOL,,,1273,975,7.587874658302404817789010849083,12,0.315209655558690404753008351690
575,575_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3661,3110,2.288440806021913687118285452016,8,0.535189211651682872350477282453
576,576_0,FAILED,Sobol,SOBOL,,,4380,1470,6.038435066432692899240919359727,18,0.859046380581334201309573472827
577,577_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,517,4489,3.838018666839227321929683967028,2,0.022534309487789869891338767616
578,578_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,3379.000000000000000000000000000000,98,557,5.109440202244558193456214212347,6,0.899441528899595166279823388322
579,579_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,4975,3488,4.781432687712833917714760900708,12,0.250161472104489801537852144975
580,580_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3241,2005,8.531441847794688726480671903118,2,0.417989295521751069717453219710
581,581_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1869,3916,1.359597918478772093919815233676,16,0.700420528341084702717012078210
582,582_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1975,1723,3.543531938746571796627904404886,19,0.567098498631268710390429532708
583,583_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3113,4822,6.332840554068797089826148294378,3,0.284271211782470334394901101405
584,584_0,FAILED,Sobol,SOBOL,,,3829,681,0.083711352080106743445142569726,13,0.116841226957738394953700833412
585,585_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1217,2740,9.792532407577150266320131777320,9,0.765725467665120951288315609418
586,586_0,FAILED,Sobol,SOBOL,,,988,900,4.399692964300514042008671822259,17,0.473413676127791394065980057348
587,587_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3922,2518,5.320292580883019262216748757055,3,0.627455041622743014961827157094
588,588_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2883,1659,1.571065355539321917177630894003,13,0.958781437914818512879833178886
589,589_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2068,4884,8.149096601749770130140859691892,7,0.173284330965951083314280367631
590,590_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1630,2076,6.598014786758461092119887325680,10,0.057257691623643039435798129944
591,591_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,3304,3842,3.136776300830766750493694416946,14,0.842846287172287711442209001689
592,592_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1423.000000000000000000000000000000,4736,326,9.386382292293943052641225222033,4,0.511430424785241477536601450993
593,593_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,161,3717,0.348270526347681907974873638523,20,0.357480309948325136737423690647
594,594_0,FAILED,Sobol,SOBOL,,,444,1405,9.065464609310962984523030172568,14,0.720281221607700028464194019762
595,595_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,4629,4552,0.654769052645191584893780145649,9,0.379616734731942406799731770661
596,596_0,FAILED,Sobol,SOBOL,,,3588,1192,6.904361336410977934008315060055,18,0.203742913169786321603282885917
597,597_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,1522,2889,2.815705449229106260844446296687,4,0.927336799107492004701214227680
598,598_0,FAILED,Sobol,SOBOL,,,2331,72,1.892060069821774881404508050764,1,0.810918031774461312011226254981
599,599_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,2757,3385,7.842673914778046651008480694145,17,0.088207504553720353368539974781
600,600_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,1.000000000000000000000000000000,4186,2369,4.093423445947468763961296644993,7,0.263199989903718234440788137363
601,601_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,167.000000000000000000000000000000,5000,882,10.000000000000000000000000000000,2,0.998999999999999999111821580300
602,602_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3718,2.888534436629692780940104057663,6,0.998999999999999999111821580300
603,603_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3857,2317,10.000000000000000000000000000000,1,0.998999999999999999111821580300
604,604_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3152,0.001000000000000000020816681712,12,0.001000000000000000020816681712
605,605_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4014,1984,0.001000000000000000020816681712,19,0.001000000000000000020816681712
606,606_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2552,0.001000000000000000020816681712,3,0.001000000000000000020816681712
607,607_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4399,3043,10.000000000000000000000000000000,11,0.001000000000000000020816681712
608,608_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1837,1697,10.000000000000000000000000000000,16,0.001000000000000000020816681712
609,609_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2714,0.001000000000000000020816681712,17,0.001000000000000000020816681712
610,610_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2138,2740,0.001000000000000000020816681712,14,0.001000000000000000020816681712
611,611_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3574,4445,10.000000000000000000000000000000,4,0.998999999999999999111821580300
612,612_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3812,3469,10.000000000000000000000000000000,1,0.998999999999999999111821580300
613,613_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,73.000000000000000000000000000000,5000,1097,0.001000000000000000020816681712,1,0.998999999999999999111821580300
614,614_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1473,4217,0.001000000000000000020816681712,14,0.001000000000000000020816681712
615,615_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1896,5000,10.000000000000000000000000000000,15,0.001000000000000000020816681712
616,616_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2744,0.001000000000000000020816681712,5,0.001000000000000000020816681712
617,617_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2031,10.000000000000000000000000000000,15,0.001000000000000000020816681712
618,618_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,398,4021,0.001000000000000000020816681712,4,0.998999999999999999111821580300
619,619_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3262,4307,10.000000000000000000000000000000,17,0.998999999999999999111821580300
620,620_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3059,5000,0.001000000000000000020816681712,7,0.998999999999999999111821580300
621,621_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4846,0.001000000000000000020816681712,9,0.998999999999999999111821580300
622,622_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3822,3224,0.001000000000000000020816681712,1,0.998999999999999999111821580300
623,623_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4539,10.000000000000000000000000000000,20,0.001000000000000000020816681712
624,624_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2620,0.001000000000000000020816681712,14,0.001000000000000000020816681712
625,625_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4486,0.001000000000000000020816681712,13,0.998999999999999999111821580300
626,626_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1550,1587,10.000000000000000000000000000000,2,0.001000000000000000020816681712
627,627_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3477,0.001000000000000000020816681712,2,0.998999999999999999111821580300
628,628_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4442,3707,0.001000000000000000020816681712,11,0.998999999999999999111821580300
629,629_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4685,0.001000000000000000020816681712,18,0.001000000000000000020816681712
630,630_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,124.000000000000000000000000000000,1,881,0.001000000000000000020816681712,1,0.001000000000000000020816681712
631,631_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4598,0.001000000000000000020816681712,5,0.001000000000000000020816681712
632,632_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4254,1818,0.001000000000000000020816681712,3,0.571340390048676649570325025707
633,633_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2608,10.000000000000000000000000000000,10,0.998999999999999999111821580300
634,634_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,914,4324,0.001000000000000000020816681712,3,0.998999999999999999111821580300
635,635_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2510,4732,10.000000000000000000000000000000,20,0.001000000000000000020816681712
636,636_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,846,4768,0.001000000000000000020816681712,1,0.998999999999999999111821580300
637,637_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3216,10.000000000000000000000000000000,12,0.998999999999999999111821580300
638,638_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,767,2567,0.001000000000000000020816681712,16,0.001000000000000000020816681712
639,639_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1590,10.000000000000000000000000000000,2,0.998999999999999999111821580300
640,640_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2559,3734,10.000000000000000000000000000000,8,0.001000000000000000020816681712
641,641_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4032,4641,0.001000000000000000020816681712,20,0.998999999999999999111821580300
642,642_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1770,10.000000000000000000000000000000,3,0.001000000000000000020816681712
643,643_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1017,3562,0.001000000000000000020816681712,17,0.001000000000000000020816681712
644,644_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3239,3000,0.001000000000000000020816681712,14,0.001000000000000000020816681712
645,645_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2333,3505,10.000000000000000000000000000000,14,0.001000000000000000020816681712
646,646_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3465,4754,10.000000000000000000000000000000,18,0.001000000000000000020816681712
647,647_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3004,0.001000000000000000020816681712,20,0.001000000000000000020816681712
648,648_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3284,0.001000000000000000020816681712,6,0.998999999999999999111821580300
649,649_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1352,4640,10.000000000000000000000000000000,15,0.998999999999999999111821580300
650,650_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3879,10.000000000000000000000000000000,19,0.001000000000000000020816681712
651,651_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,178.000000000000000000000000000000,5000,816,10.000000000000000000000000000000,2,0.998999999999999999111821580300
652,652_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3372,0.001000000000000000020816681712,1,0.001000000000000000020816681712
653,653_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,10.000000000000000000000000000000,1,0.998999999999999999111821580300
654,654_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3046,10.000000000000000000000000000000,20,0.001000000000000000020816681712
655,655_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2791,10.000000000000000000000000000000,6,0.001000000000000000020816681712
656,656_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4980,4167,10.000000000000000000000000000000,11,0.436139540072146614235748529609
657,657_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,1830,0.001000000000000000020816681712,15,0.998999999999999999111821580300
658,658_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2772,10.000000000000000000000000000000,18,0.001000000000000000020816681712
659,659_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3850,1858,0.001000000000000000020816681712,12,0.998999999999999999111821580300
660,660_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,43.000000000000000000000000000000,1,1290,0.001000000000000000020816681712,1,0.001000000000000000020816681712
661,661_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3621,2103,0.001000000000000000020816681712,3,0.560706885273231314670283609303
662,662_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,1104,0.001000000000000000020816681712,17,0.998999999999999999111821580300
663,663_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,1381,10.000000000000000000000000000000,1,0.998999999999999999111821580300
664,664_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2666,4185,0.001000000000000000020816681712,1,0.286913107594039984427070066886
665,665_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,125.000000000000000000000000000000,5000,647,0.001000000000000000020816681712,1,0.998999999999999999111821580300
666,666_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2754,0.001000000000000000020816681712,12,0.998999999999999999111821580300
667,667_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,966,0.001000000000000000020816681712,19,0.998999999999999999111821580300
668,668_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2582,0.001000000000000000020816681712,20,0.998999999999999999111821580300
669,669_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4695,10.000000000000000000000000000000,8,0.001000000000000000020816681712
670,670_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,927,0.001000000000000000020816681712,18,0.998999999999999999111821580300
671,671_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3781,2664,0.001000000000000000020816681712,1,0.001000000000000000020816681712
672,672_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3899,2706,10.000000000000000000000000000000,20,0.001000000000000000020816681712
673,673_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,793,3773,0.001000000000000000020816681712,3,0.998999999999999999111821580300
674,674_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3288,2853,10.000000000000000000000000000000,1,0.001000000000000000020816681712
675,675_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,834,3619,10.000000000000000000000000000000,6,0.001000000000000000020816681712
676,676_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1209,3656,0.001000000000000000020816681712,10,0.998999999999999999111821580300
677,677_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3866,4335,10.000000000000000000000000000000,20,0.001000000000000000020816681712
678,678_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,21.000000000000000000000000000000,1,1439,0.001000000000000000020816681712,1,0.998999999999999999111821580300
679,679_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2407,0.001000000000000000020816681712,8,0.998999999999999999111821580300
680,680_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3274,2999,0.001000000000000000020816681712,18,0.001000000000000000020816681712
681,681_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1203,2643,0.001000000000000000020816681712,8,0.001000000000000000020816681712
682,682_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4634,0.001000000000000000020816681712,13,0.001000000000000000020816681712
683,683_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,824,4001,10.000000000000000000000000000000,1,0.998999999999999999111821580300
684,684_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2218,1544,0.001000000000000000020816681712,17,0.998999999999999999111821580300
685,685_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1678,2462,0.001000000000000000020816681712,11,0.001000000000000000020816681712
686,686_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2057,4806,0.001000000000000000020816681712,5,0.998999999999999999111821580300
687,687_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2475,4127,0.001000000000000000020816681712,6,0.001000000000000000020816681712
688,688_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1003,1716,10.000000000000000000000000000000,15,0.998999999999999999111821580300
689,689_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,467,4776,10.000000000000000000000000000000,7,0.998999999999999999111821580300
690,690_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,5000,0.001000000000000000020816681712,10,0.001000000000000000020816681712
691,691_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,5000,10.000000000000000000000000000000,20,0.001000000000000000020816681712
692,692_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2928,2883,10.000000000000000000000000000000,15,0.001000000000000000020816681712
693,693_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,664,2852,10.000000000000000000000000000000,15,0.001000000000000000020816681712
694,694_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3774,4135,10.000000000000000000000000000000,14,0.001000000000000000020816681712
695,695_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1356,5000,0.001000000000000000020816681712,3,0.998999999999999999111821580300
696,696_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,188.000000000000000000000000000000,5000,1105,10.000000000000000000000000000000,2,0.998999999999999999111821580300
697,697_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,989,0.001000000000000000020816681712,18,0.982675964733800588746248649841
698,698_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2415,4587,10.000000000000000000000000000000,13,0.998999999999999999111821580300
699,699_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2875,10.000000000000000000000000000000,12,0.001000000000000000020816681712
700,700_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3935,0.001000000000000000020816681712,18,0.998999999999999999111821580300
701,701_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1253,4475,0.001000000000000000020816681712,14,0.001000000000000000020816681712
702,702_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1800,10.000000000000000000000000000000,16,0.998999999999999999111821580300
703,703_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,1234,10.000000000000000000000000000000,17,0.998999999999999999111821580300
704,704_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3843,3552,10.000000000000000000000000000000,16,0.998999999999999999111821580300
705,705_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4132,10.000000000000000000000000000000,20,0.998999999999999999111821580300
706,706_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2570,10.000000000000000000000000000000,20,0.001000000000000000020816681712
707,707_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3552,4888,0.001000000000000000020816681712,15,0.998999999999999999111821580300
708,708_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2502,4285,0.001000000000000000020816681712,14,0.998999999999999999111821580300
709,709_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2304,4651,0.001000000000000000020816681712,1,0.001000000000000000020816681712
710,710_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1588,3349,0.001000000000000000020816681712,20,0.998999999999999999111821580300
711,711_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1817,4515,10.000000000000000000000000000000,7,0.001000000000000000020816681712
712,712_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4782,3888,10.000000000000000000000000000000,6,0.001000000000000000020816681712
713,713_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3082,1986,10.000000000000000000000000000000,10,0.998999999999999999111821580300
714,714_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1531,4656,10.000000000000000000000000000000,9,0.998999999999999999111821580300
715,715_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3640,10.000000000000000000000000000000,1,0.001000000000000000020816681712
716,716_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2340,1977,0.001000000000000000020816681712,8,0.998999999999999999111821580300
717,717_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,835,2349,10.000000000000000000000000000000,7,0.001000000000000000020816681712
718,718_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,976,5000,0.001000000000000000020816681712,16,0.001000000000000000020816681712
719,719_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4099,3868,0.001000000000000000020816681712,13,0.998999999999999999111821580300
720,720_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4726,4738,10.000000000000000000000000000000,10,0.001000000000000000020816681712
721,721_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,878,0.001000000000000000020816681712,2,0.998999999999999999111821580300
722,722_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4181,3328,0.001000000000000000020816681712,9,0.998999999999999999111821580300
723,723_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,4815,957,0.001000000000000000020816681712,17,0.998999999999999999111821580300
724,724_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2732,5000,0.001000000000000000020816681712,14,0.001000000000000000020816681712
725,725_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4769,10.000000000000000000000000000000,2,0.998999999999999999111821580300
726,726_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,898,4.795263996302606024357828573557,18,0.998999999999999999111821580300
727,727_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4125,4887,0.001000000000000000020816681712,8,0.001000000000000000020816681712
728,728_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1045,4517,0.001000000000000000020816681712,4,0.001000000000000000020816681712
729,729_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,322,3414,10.000000000000000000000000000000,7,0.001000000000000000020816681712
730,730_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3409,2021,10.000000000000000000000000000000,1,0.001000000000000000020816681712
731,731_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,888,0.001000000000000000020816681712,2,0.998999999999999999111821580300
732,732_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1885,2461,0.001000000000000000020816681712,2,0.998999999999999999111821580300
733,733_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3673,2857,10.000000000000000000000000000000,11,0.998999999999999999111821580300
734,734_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2676,2134,10.000000000000000000000000000000,20,0.998999999999999999111821580300
735,735_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4044,10.000000000000000000000000000000,11,0.998999999999999999111821580300
736,736_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1147,0.001000000000000000020816681712,17,0.001000000000000000020816681712
737,737_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2499,3579,10.000000000000000000000000000000,3,0.001000000000000000020816681712
738,738_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1028,10.000000000000000000000000000000,19,0.998999999999999999111821580300
739,739_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3635,3070,0.001000000000000000020816681712,11,0.998999999999999999111821580300
740,740_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1970,3824,10.000000000000000000000000000000,4,0.998999999999999999111821580300
741,741_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3751,3907,10.000000000000000000000000000000,1,0.001000000000000000020816681712
742,742_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4358,2916,10.000000000000000000000000000000,16,0.998999999999999999111821580300
743,743_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4689,10.000000000000000000000000000000,3,0.998999999999999999111821580300
744,744_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3429,3526,10.000000000000000000000000000000,7,0.001000000000000000020816681712
745,745_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3098,4793,0.001000000000000000020816681712,13,0.998999999999999999111821580300
746,746_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2434,10.000000000000000000000000000000,3,0.998999999999999999111821580300
747,747_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1868,2976,10.000000000000000000000000000000,1,0.001000000000000000020816681712
748,748_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,34.000000000000000000000000000000,2908,1401,10.000000000000000000000000000000,2,0.001000000000000000020816681712
749,749_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1826,2844,10.000000000000000000000000000000,3,0.998999999999999999111821580300
750,750_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1370,3935,0.001000000000000000020816681712,20,0.001000000000000000020816681712
751,751_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3427,2146,10.000000000000000000000000000000,1,0.998999999999999999111821580300
752,752_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,4168,10.000000000000000000000000000000,7,0.001000000000000000020816681712
753,753_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,198.000000000000000000000000000000,5000,925,0.001000000000000000020816681712,2,0.998999999999999999111821580300
754,754_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1403,3861,10.000000000000000000000000000000,1,0.001000000000000000020816681712
755,755_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2265,10.000000000000000000000000000000,18,0.001000000000000000020816681712
756,756_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,5239.000000000000000000000000000000,5000,1474,0.001000000000000000020816681712,16,0.998999999999999999111821580300
757,757_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2727,2746,10.000000000000000000000000000000,8,0.998999999999999999111821580300
758,758_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,605,4666,10.000000000000000000000000000000,1,0.001000000000000000020816681712
759,759_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4934,4229,10.000000000000000000000000000000,4,0.001000000000000000020816681712
760,760_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,95,2901,0.001000000000000000020816681712,8,0.998999999999999999111821580300
761,761_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2404,3324,0.001000000000000000020816681712,4,0.998999999999999999111821580300
762,762_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3115,3521,0.001000000000000000020816681712,20,0.998999999999999999111821580300
763,763_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2331,10.000000000000000000000000000000,20,0.998999999999999999111821580300
764,764_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,27.000000000000000000000000000000,5000,1371,0.001000000000000000020816681712,1,0.998999999999999999111821580300
765,765_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4278,0.001000000000000000020816681712,15,0.998999999999999999111821580300
766,766_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,973,1718,0.001000000000000000020816681712,6,0.998999999999999999111821580300
767,767_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2466,0.001000000000000000020816681712,1,0.998999999999999999111821580300
768,768_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,131.000000000000000000000000000000,5000,827,0.001000000000000000020816681712,1,0.001000000000000000020816681712
769,769_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1103,10.000000000000000000000000000000,1,0.998999999999999999111821580300
770,770_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3631,4602,0.001000000000000000020816681712,4,0.001000000000000000020816681712
771,771_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1272,10.000000000000000000000000000000,1,0.998999999999999999111821580300
772,772_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3919,0.001000000000000000020816681712,3,0.998999999999999999111821580300
773,773_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2255,0.001000000000000000020816681712,20,0.507808806878279117569263689802
774,774_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2217,10.000000000000000000000000000000,5,0.998999999999999999111821580300
775,775_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3030,0.001000000000000000020816681712,17,0.998999999999999999111821580300
776,776_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1102,10.000000000000000000000000000000,1,0.998999999999999999111821580300
777,777_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1553,2973,10.000000000000000000000000000000,20,0.001000000000000000020816681712
778,778_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1274,10.000000000000000000000000000000,1,0.998999999999999999111821580300
779,779_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,719,3228,0.001000000000000000020816681712,1,0.001000000000000000020816681712
780,780_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2106,1694,0.001000000000000000020816681712,8,0.001000000000000000020816681712
781,781_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,173,2891,10.000000000000000000000000000000,1,0.001000000000000000020816681712
782,782_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,159,3777,0.001000000000000000020816681712,17,0.001000000000000000020816681712
783,783_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3422,2646,10.000000000000000000000000000000,15,0.001000000000000000020816681712
784,784_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2793,10.000000000000000000000000000000,20,0.998999999999999999111821580300
785,785_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3880,10.000000000000000000000000000000,10,0.001000000000000000020816681712
786,786_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1787,10.000000000000000000000000000000,20,0.001000000000000000020816681712
787,787_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,331,3205,10.000000000000000000000000000000,1,0.998999999999999999111821580300
788,788_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,441,4159,10.000000000000000000000000000000,20,0.998999999999999999111821580300
789,789_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3965,10.000000000000000000000000000000,5,0.001000000000000000020816681712
790,790_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,691,3616,10.000000000000000000000000000000,19,0.001000000000000000020816681712
791,791_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1270,10.000000000000000000000000000000,1,0.998999999999999999111821580300
792,792_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2706,4508,0.001000000000000000020816681712,10,0.998999999999999999111821580300
793,793_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,1782,10.000000000000000000000000000000,10,0.257642392357844196570937356228
794,794_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4144,1839,0.001000000000000000020816681712,20,0.001000000000000000020816681712
795,795_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3459,10.000000000000000000000000000000,1,0.001000000000000000020816681712
796,796_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2727,3123,10.000000000000000000000000000000,20,0.998999999999999999111821580300
797,797_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3579,1693,10.000000000000000000000000000000,5,0.998999999999999999111821580300
798,798_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1129,2198,10.000000000000000000000000000000,14,0.244772802023521501846303749517
799,799_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2567,0.001000000000000000020816681712,6,0.998999999999999999111821580300
800,800_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2119,10.000000000000000000000000000000,1,0.998999999999999999111821580300
801,801_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3386,3997,0.001000000000000000020816681712,20,0.998999999999999999111821580300
802,802_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2302,3945,10.000000000000000000000000000000,20,0.998999999999999999111821580300
803,803_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,668,2651,0.001000000000000000020816681712,2,0.998999999999999999111821580300
804,804_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4107,2168,0.001000000000000000020816681712,1,0.001000000000000000020816681712
805,805_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2449,10.000000000000000000000000000000,20,0.001000000000000000020816681712
806,806_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,115.000000000000000000000000000000,5000,1032,0.001000000000000000020816681712,1,0.998999999999999999111821580300
807,807_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4529,3696,0.001000000000000000020816681712,4,0.998999999999999999111821580300
808,808_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,3694,10.000000000000000000000000000000,4,0.998999999999999999111821580300
809,809_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4191,4408,0.001000000000000000020816681712,20,0.001000000000000000020816681712
810,810_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,2815,4271,0.001000000000000000020816681712,1,0.998999999999999999111821580300
811,811_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,3028,1794,10.000000000000000000000000000000,19,0.001000000000000000020816681712
812,812_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2277,0.001000000000000000020816681712,11,0.001000000000000000020816681712
813,813_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4433,829,10.000000000000000000000000000000,1,0.998999999999999999111821580300
814,814_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1107,10.000000000000000000000000000000,1,0.998999999999999999111821580300
815,815_0,FAILED,BoTorch,BOTORCH_MODULAR,,,5000,1279,10.000000000000000000000000000000,1,0.998999999999999999111821580300
816,816_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,4557,0.001000000000000000020816681712,15,0.998999999999999999111821580300
817,817_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4170,3255,10.000000000000000000000000000000,13,0.998999999999999999111821580300
818,818_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,2946,0.001000000000000000020816681712,4,0.998999999999999999111821580300
819,819_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4323,4658,10.000000000000000000000000000000,17,0.998999999999999999111821580300
820,820_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,2190,0.001000000000000000020816681712,5,0.998999999999999999111821580300
821,821_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,5000,3759,0.001000000000000000020816681712,17,0.001000000000000000020816681712
822,822_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4205,2297,0.001000000000000000020816681712,15,0.001000000000000000020816681712
823,823_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1,993,10.000000000000000000000000000000,1,0.998999999999999999111821580300
824,824_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,5000,1113,10.000000000000000000000000000000,1,0.998999999999999999111821580300
825,825_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,4998,3430,0.001774770381076328428990307451,18,0.001000000000000000020816681712
826,826_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1256,1821,0.001000000000000000020816681712,12,0.001000000000000000020816681712
827,827_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,1.000000000000000000000000000000,1814,1718,0.001000000000000000020816681712,1,0.001000000000000000020816681712
828,828_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,3512,1873,0.001000000000000000020816681712,1,0.001000000000000000020816681712
</pre>
			<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download &raquo;results.csv&laquo; as file</button>
			<script>
				createTable(tab_results_csv_json, tab_results_headers_json, 'tab_results_csv_table');</script>
			
			<h1>&nbsp;Errors</h1>
			<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download &raquo;oo_errors.txt&laquo; as file</button>
<pre id='simple_pre_tab_tab_errors'><span style="background-color: black; color: white">
⚠ Job 4620892 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4620892/4620892_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4620892/4620892_0_log.out
----------------------------------------
submitit INFO (2025-04-23 12:50:35,584) - Starting with JobEnvironment(job_id=4620892, hostname=i7185, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-23 12:50:35,587) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4620892/4620892_submitted.pkl
slurmstepd: error: *** JOB 4620892 ON i7185 CANCELLED AT 2025-04-23T14:50:51 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4620892.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4620892/4620892_0_log.err not found


⚠ Job 4621224 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4621224/4621224_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4621224/4621224_0_log.out
----------------------------------------
submitit INFO (2025-04-23 12:56:40,541) - Starting with JobEnvironment(job_id=4621224, hostname=i7183, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-23 12:56:40,543) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4621224/4621224_submitted.pkl
slurmstepd: error: *** JOB 4621224 ON i7183 CANCELLED AT 2025-04-23T14:56:51 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4621224/4621224_0_log.err not found


⚠ Job 4621325 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4621325/4621325_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4621325/4621325_0_log.out
----------------------------------------
submitit INFO (2025-04-23 12:57:01,221) - Starting with JobEnvironment(job_id=4621325, hostname=i7183, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-23 12:57:01,223) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4621325/4621325_submitted.pkl
slurmstepd: error: *** JOB 4621325 ON i7183 CANCELLED AT 2025-04-23T14:56:51 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4621325.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4621325/4621325_0_log.err not found


⚠ Job 4629299 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629299/4629299_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629299/4629299_0_log.out
----------------------------------------
submitit INFO (2025-04-23 15:10:17,634) - Starting with JobEnvironment(job_id=4629299, hostname=i7186, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-23 15:10:17,636) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629299/4629299_submitted.pkl
slurmstepd: error: *** JOB 4629299 ON i7186 CANCELLED AT 2025-04-23T17:10:29 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629299/4629299_0_log.err not found


⚠ Job 4629399 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629399/4629399_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629399/4629399_0_log.out
----------------------------------------
submitit INFO (2025-04-23 15:12:09,058) - Starting with JobEnvironment(job_id=4629399, hostname=i7183, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-23 15:12:09,060) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629399/4629399_submitted.pkl
slurmstepd: error: *** JOB 4629399 ON i7183 CANCELLED AT 2025-04-23T17:11:59 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629399/4629399_0_log.err not found


⚠ Job 4629482 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629482/4629482_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629482/4629482_0_log.out
----------------------------------------
submitit INFO (2025-04-23 15:12:09,319) - Starting with JobEnvironment(job_id=4629482, hostname=i7182, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-23 15:12:09,321) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629482/4629482_submitted.pkl
slurmstepd: error: *** JOB 4629482 ON i7182 CANCELLED AT 2025-04-23T17:11:59 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4629482.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4629482/4629482_0_log.err not found


⚠ Job 4674262 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4674262/4674262_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4674262/4674262_0_log.out
----------------------------------------
submitit INFO (2025-04-24 06:19:53,182) - Starting with JobEnvironment(job_id=4674262, hostname=i7185, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-24 06:19:53,184) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4674262/4674262_submitted.pkl
slurmstepd: error: *** JOB 4674262 ON i7185 CANCELLED AT 2025-04-24T08:20:15 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4674262/4674262_0_log.err not found


⚠ Job 4686425 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4686425/4686425_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4686425/4686425_0_log.out
----------------------------------------
submitit INFO (2025-04-24 13:08:14,685) - Starting with JobEnvironment(job_id=4686425, hostname=i7186, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-24 13:08:14,696) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4686425/4686425_submitted.pkl
slurmstepd: error: *** JOB 4686425 ON i7186 CANCELLED AT 2025-04-24T15:08:11 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4686425/4686425_0_log.err not found


⚠ Job 4697862 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4697862/4697862_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4697862/4697862_0_log.out
----------------------------------------
submitit INFO (2025-04-24 19:46:45,277) - Starting with JobEnvironment(job_id=4697862, hostname=i7186, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-24 19:46:45,282) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4697862/4697862_submitted.pkl
slurmstepd: error: *** JOB 4697862 ON i7186 CANCELLED AT 2025-04-24T21:46:54 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4697862.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4697862/4697862_0_log.err not found


⚠ Job 4704731 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4704731/4704731_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4704731/4704731_0_log.out
----------------------------------------
submitit INFO (2025-04-24 23:37:49,192) - Starting with JobEnvironment(job_id=4704731, hostname=i7181, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-24 23:37:49,208) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4704731/4704731_submitted.pkl
slurmstepd: error: *** JOB 4704731 ON i7181 CANCELLED AT 2025-04-25T01:38:01 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4704731.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4704731/4704731_0_log.err not found


⚠ Job 4707299 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4707299/4707299_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4707299/4707299_0_log.out
----------------------------------------
submitit INFO (2025-04-25 01:05:50,153) - Starting with JobEnvironment(job_id=4707299, hostname=i7186, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 01:05:50,156) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4707299/4707299_submitted.pkl
slurmstepd: error: *** JOB 4707299 ON i7186 CANCELLED AT 2025-04-25T03:06:03 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4707299/4707299_0_log.err not found


⚠ Job 4708325 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4708325/4708325_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4708325/4708325_0_log.out
----------------------------------------
submitit INFO (2025-04-25 01:39:30,298) - Starting with JobEnvironment(job_id=4708325, hostname=i7180, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 01:39:30,301) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4708325/4708325_submitted.pkl
slurmstepd: error: *** JOB 4708325 ON i7180 CANCELLED AT 2025-04-25T03:39:33 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4708325/4708325_0_log.err not found


⚠ Job 4725631 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4725631/4725631_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4725631/4725631_0_log.out
----------------------------------------
submitit INFO (2025-04-25 12:02:58,369) - Starting with JobEnvironment(job_id=4725631, hostname=i7182, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 12:02:58,372) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4725631/4725631_submitted.pkl
slurmstepd: error: *** JOB 4725631 ON i7182 CANCELLED AT 2025-04-25T14:03:21 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4725631.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4725631/4725631_0_log.err not found


⚠ Job 4730001 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4730001/4730001_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4730001/4730001_0_log.out
----------------------------------------
submitit INFO (2025-04-25 14:48:00,687) - Starting with JobEnvironment(job_id=4730001, hostname=i7185, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 14:48:00,690) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4730001/4730001_submitted.pkl
slurmstepd: error: *** JOB 4730001 ON i7185 CANCELLED AT 2025-04-25T16:48:25 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4730001.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4730001/4730001_0_log.err not found


⚠ Job 4732811 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4732811/4732811_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4732811/4732811_0_log.out
----------------------------------------
submitit INFO (2025-04-25 16:38:41,922) - Starting with JobEnvironment(job_id=4732811, hostname=i7182, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 16:38:41,925) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4732811/4732811_submitted.pkl
slurmstepd: error: *** JOB 4732811 ON i7182 CANCELLED AT 2025-04-25T18:39:01 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4732811.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4732811/4732811_0_log.err not found


⚠ Job 4734010 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4734010/4734010_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4734010/4734010_0_log.out
----------------------------------------
submitit INFO (2025-04-25 17:26:42,697) - Starting with JobEnvironment(job_id=4734010, hostname=i7182, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 17:26:42,700) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4734010/4734010_submitted.pkl
slurmstepd: error: *** JOB 4734010 ON i7182 CANCELLED AT 2025-04-25T19:27:03 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4734010.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4734010/4734010_0_log.err not found


⚠ Job 4741991 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4741991/4741991_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4741991/4741991_0_log.out
----------------------------------------
submitit INFO (2025-04-25 22:09:48,068) - Starting with JobEnvironment(job_id=4741991, hostname=i7003, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-25 22:09:48,070) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4741991/4741991_submitted.pkl
slurmstepd: error: *** JOB 4741991 ON i7003 CANCELLED AT 2025-04-26T00:10:13 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4741991.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4741991/4741991_0_log.err not found


⚠ Job 4754920 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4754920/4754920_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4754920/4754920_0_log.out
----------------------------------------
submitit INFO (2025-04-26 06:58:53,577) - Starting with JobEnvironment(job_id=4754920, hostname=i7183, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-26 06:58:53,579) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4754920/4754920_submitted.pkl
slurmstepd: error: *** JOB 4754920 ON i7183 CANCELLED AT 2025-04-26T08:59:02 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4754920.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4754920/4754920_0_log.err not found


⚠ Job 4755542 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4755542/4755542_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4755542/4755542_0_log.out
----------------------------------------
submitit INFO (2025-04-26 07:26:14,012) - Starting with JobEnvironment(job_id=4755542, hostname=i7186, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-26 07:26:14,014) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4755542/4755542_submitted.pkl
slurmstepd: error: *** JOB 4755542 ON i7186 CANCELLED AT 2025-04-26T09:26:34 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4755542.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4755542/4755542_0_log.err not found


⚠ Job 4756093 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4756093/4756093_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4756093/4756093_0_log.out
----------------------------------------
submitit INFO (2025-04-26 07:49:54,258) - Starting with JobEnvironment(job_id=4756093, hostname=i7185, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-04-26 07:49:54,260) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4756093/4756093_submitted.pkl
slurmstepd: error: *** JOB 4756093 ON i7185 CANCELLED AT 2025-04-26T09:50:04 DUE TO TIME LIMIT ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4756093.batch. Some of the step tasks have been OOM Killed.



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4756093/4756093_0_log.err not found

</span></pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'> Download &raquo;oo_errors.txt&laquo; as file</button>
			
			<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>1                                                                                                                                 </td></tr><tr><td> parameter</td><td>None                                                                                                                              </td></tr><tr><td> continue_previous_job</td><td>/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/BNDM_TMDBalanced5s_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0/ </td></tr><tr><td> experiment_constraints</td><td>None                                                                                                                              </td></tr><tr><td> run_dir</td><td>runs                                                                                                                              </td></tr><tr><td> seed</td><td>None                                                                                                                              </td></tr><tr><td> decimalrounding</td><td>4                                                                                                                                 </td></tr><tr><td> enforce_sequential_optimization</td><td>False                                                                                                                             </td></tr><tr><td> verbose_tqdm</td><td>False                                                                                                                             </td></tr><tr><td> model</td><td>None                                                                                                                              </td></tr><tr><td> gridsearch</td><td>False                                                                                                                             </td></tr><tr><td> occ</td><td>False                                                                                                                             </td></tr><tr><td> show_sixel_scatter</td><td>False                                                                                                                             </td></tr><tr><td> show_sixel_general</td><td>False                                                                                                                             </td></tr><tr><td> show_sixel_trial_index_result</td><td>False                                                                                                                             </td></tr><tr><td> follow</td><td>False                                                                                                                             </td></tr><tr><td> send_anonymized_usage_stats</td><td>False                                                                                                                             </td></tr><tr><td> ui_url</td><td>None                                                                                                                              </td></tr><tr><td> root_venv_dir</td><td>/home/s4122485                                                                                                                    </td></tr><tr><td> exclude</td><td>None                                                                                                                              </td></tr><tr><td> main_process_gb</td><td>8                                                                                                                                 </td></tr><tr><td> pareto_front_confidence</td><td>1                                                                                                                                 </td></tr><tr><td> max_nr_of_zero_results</td><td>10                                                                                                                                </td></tr><tr><td> abbreviate_job_names</td><td>False                                                                                                                             </td></tr><tr><td> orchestrator_file</td><td>None                                                                                                                              </td></tr><tr><td> checkout_to_latest_tested_version</td><td>False                                                                                                                             </td></tr><tr><td> live_share</td><td>False                                                                                                                             </td></tr><tr><td> disable_tqdm</td><td>False                                                                                                                             </td></tr><tr><td> workdir</td><td>False                                                                                                                             </td></tr><tr><td> occ_type</td><td>euclid                                                                                                                            </td></tr><tr><td> result_names</td><td>[&#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>
			<div class='invert_in_dark_mode' id='workerUsagePlot'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download &raquo;worker_usage.csv&laquo; as file</button>
<pre id="pre_tab_worker_usage">1745405312.4162683,20,0,0
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1745582903.30178,20,1,5
1745582916.440993,20,0,0
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1745584047.7334986,20,0,0
1745584048.23626,20,0,0
1745584051.2817295,20,1,5
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1745588974.7784638,20,3,15
1745588984.6519606,20,3,15
1745589003.3336213,20,2,10
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1745590316.3897653,20,3,15
1745590325.2809951,20,3,15
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1745591919.0595222,20,2,10
1745591919.4847121,20,2,10
1745591921.1888146,20,3,15
1745591928.6523416,20,3,15
1745591947.2069988,20,2,10
1745591947.415991,20,2,10
1745593211.0623324,20,2,10
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1745593213.2579906,20,3,15
1745593230.0528781,20,3,15
1745593253.422594,20,2,10
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1745594786.5808084,20,2,10
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1745594788.4916291,20,3,15
1745594794.503781,20,3,15
1745594812.2523687,20,2,10
1745594812.39286,20,2,10
1745596567.1961794,20,2,10
1745596567.6910882,20,2,10
1745596569.2842858,20,3,15
1745596591.906302,20,3,15
1745597958.4737933,20,3,15
1745597959.0843349,20,3,15
1745597961.1182494,20,4,20
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1745597990.2145364,20,3,15
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1745599250.0969496,20,4,20
1745599262.6740305,20,3,15
1745599270.3023963,20,2,10
1745599282.1107717,20,1,5
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1745600347.7708938,20,1,5
1745600348.2597067,20,1,5
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1745600366.8577504,20,2,10
1745601302.453628,20,2,10
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1745611547.1997,20,1,5
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1745612873.571403,20,1,5
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1745612894.8610911,20,2,10
1745614247.4670403,20,2,10
1745614248.2109408,20,2,10
1745614250.0972626,20,3,15
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1745614275.9769185,20,2,10
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1745615809.377052,20,2,10
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1745615835.6756394,20,2,10
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1745617081.0410473,20,2,10
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</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
1745405312,640.34765625,2.8
1745405312,640.34765625,3.8
1745405312,640.34765625,3.1
1745405312,640.34765625,2.0
1745405312,640.34765625,5.4
1745405312,640.34765625,1.9
1745405312,640.34765625,4.2
1745405984,686.765625,35.5
1745405984,686.765625,51.1
1745405984,686.765625,42.3
1745405984,686.765625,47.6
1745418918,924.62109375,42.4
1745418918,924.62109375,45.9
1745418918,924.62109375,46.4
1745418918,924.62109375,48.9
1745433048,973.9609375,37.7
1745433048,973.9609375,41.6
1745433048,973.9609375,41.9
1745433048,973.9609375,46.9
1745446204,982.23046875,42.1
1745446204,982.23046875,41.9
1745446204,982.23046875,40.6
1745446204,982.23046875,47.7
1745461706,969.28125,40.5
1745461706,969.28125,45.0
1745461706,969.28125,44.6
1745461706,969.28125,39.3
1745483891,993.03125,42.6
1745483891,993.03125,39.0
1745483891,993.03125,38.5
1745483891,993.03125,36.2
1745502739,1010.62890625,36.9
1745502739,1010.62890625,34.9
1745502739,1010.62890625,34.6
1745502739,1010.62890625,35.4
1745524377,1017.296875,36.9
1745524377,1017.296875,38.5
1745524377,1017.296875,37.9
1745524377,1017.296875,40.4
1745550266,1022.953125,37.0
1745550266,1022.953125,41.4
1745550266,1022.953125,40.7
1745550266,1022.953125,40.5
1745575396,1037.20703125,37.6
1745575396,1037.20703125,37.0
1745575396,1037.20703125,37.4
1745575396,1037.20703125,40.9
1745608990,1075.19140625,37.6
1745608990,1075.19140625,44.0
1745608990,1075.19140625,41.6
1745608990,1075.19140625,42.0
1745637411,1069.83203125,37.4
1745637411,1069.83203125,44.5
1745637411,1069.83203125,43.8
1745637411,1069.83203125,47.2
</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>
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